RA-22-0002, Appendix 10-B - Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station
| ML22019A125 | |
| Person / Time | |
|---|---|
| Site: | Oconee  |
| Issue date: | 01/07/2022 |
| From: | Duke Energy Carolinas |
| To: | Office of Nuclear Reactor Regulation |
| Shared Package | |
| ML22019A137 | List: |
| References | |
| RA-22-0002 | |
| Download: ML22019A125 (395) | |
Text
Appendix 10-8 Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0
- Issue Date: 5fl.712fY1.0 Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrorrt at Oconee Nuclear Station Originator. Spencer Nush, EIT 9/12/2019 Reviewer: Scott Loughery, PE 10/1/2019 Approver: Scott Loughary, PE 4/10/2020 Revision No. Revised by: Approved by: OescripUon 0
Calculation Summary:
- ---:-:-i _-:- -__- -
Number of Cooling Tower Booster Pumps 14 14 14 Cooling Tower Booster Pump Flow Rate gpm 50,571 50,571 50,571 Coating Tower Booster Pump Total Dynamic Head ft 92.7 92.7 92 .7 Number of Make-uo Water Pumps - -
Make-up Waler Pump Flow Rate gpm - -
Make-up Wate r Pump Total Dynamic Head ft - - -
1 of4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 5/27/2020 Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrofft at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a thre&-untt nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Estimate the additional headloss through the cooling water pipe associated with the hypothetical cooling tower retrofit and size new booster pumps and make-up pumps for the new system.
Calculation Objectives:
- 1. List the calculation methodology and data required for the calculations.
- 2. Provide the inputs required for the calculations.
- 3. Estimate the additional dynamic head required for the booster pump system.
- 4. Estimate the additional clyMmic head required for the make-up water system.
- 5. Estimate the additional head required for the closed-cycle cooling system.
Calculation Methodology:
Formula 1 HL1* [ 10.44. L. 0'*" 1/(C1. . . ( c,. d t 11 1
Units: II
'M"lere:
Hu= Headless duo to pipe waft friction far each new pump I pipe system (It)
L = Total pipe length per pump (It)
Q = Flow rate through pipe per pump (gpm)
C = Hazen-Wtlliams roughness coefficient d = Pipe diameter (inch)
C1 = Conversion /actor from feet to inches (inch I ft)
Formula 2 HLm*Ik*v't( 2* g)
Units:11
..+iere:
HLffl = Minor headloss due to irregutarities in each pipe/pump system (ft)
Ik = Sum of minor heacloss coefficients 'M"lich are specified for each headloss feature V = Flow velocity [V* Q / ( n
- cf 14) ](It/ s) 2 g = Gravitational acceleration (ft/ s )
Formula 3 Hy-= HLF + HLm+ Hs Units:11
'M"lere:
Hr= Total dynamic head required (It)
Hs = Static head (ft) 2 of 4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revt1lon:
Issue Date: 5/27/2020 Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station Calculation Inputs:
.~~_ ~T l. --
Circulating Water Flow Rate a
-gpm
-*708,000
-- 708,000
-- 708,000 (1), Note 3 Number of Cooling Tower Booster PLKTlps N....,., 14 14 14 Assumption 2 Make-up Pump Discharge Capacity QM gpm - - - Assumption 3 Nt.mber of Addrtional Make-up Pumps N....,., 0 0 0 Assumption 3 Pipe Length for Each Booster Pt.mp Le ft 3,500 3,500 3,500 Note2 Pipe Length for Each Make-up PLKTlp LM ft - - - Auu"1)'1:lon 3 Pipe Diameter for Each Booster pump de ft 4.5 4 .5 4 .5 Note 1 Pipe Diameter for Each Make-up Pump dM ft - - Assumption 3 Pipe Roughness C 100 100 100 [21 Gravrtational Acceleration g ft / s2 32.2 32.2 32.2 Static Head for Each Booster Pump Hse ft 59.1 59.1 59.1 Assumption 1 Static Head for Each Make-up Pump HsM ft - - - ANu""1ion 3 lntenmediate Calculations:
Booster Pump Discharge Capacity a.
v.
gpm 11 /s 50,571 7.1 50,571 7.1 50,571 7.1 R-Assumption 2, Note 5 Note 1 VM Il l s Assumption 3 Sum of Minor Headless Coefficients I:ke ft 6.1 6.1 6.1 Sum of Minor Headless Coefficients I:kM ft 2.1 2.1 2.1 Minor ......,touri Unlt1 Unlt2 Unlt3 Description k Number Headloss (ftl Number Headloss (ftl Number thadloss lftl 90 Elbow 0.3 10 2.34 10 2.34 10 2 Wye 0.2 8 1.25 8 1.25 8 1.25 Entrance Loss 0.5 1 0.39 1 0.39 1 0,39 Exit Loss 1.0 1 0.78 1 0.78 1 0.78 Total 6.1 4.75 6.1 4.75 6.1 4.75 Minor Headlosffs Unltf Unlt2 UnIU DeecrlDtlon k Number Headloss lftl Number HeadloM 1ft) Nlllllber Headlon lftl 90 Elbow 0.3 2 - 2 - 2.0 -
Wve 0.2 0 - .o - 0.0 -
Entrance Loss 0.5 1 - 1 - 1.0 -
Exit Loss 1.0 1 - 1 - 1.0 -
Total 2.1 - 2.1 - 2.1 -
3 014
Duke Energy Carolinas, LLC I Oconee Nuclear Stltion Revision:
J55ue Date: 5'1.7'2020 Pump and Pipe Selection Calculations for a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station Conversion Factors:
C1= 12 inch / ft Assumptions:
- 1. Total pump head is a summation of expected headloss due to pipe friction, minor losses, and the static head requirement, where the static head is the sum of wet well depth (10 ft pipe belowv.1!t v.1!llwater surface+ 3 ft of draw down), and the height to the water distribution system of the cooling t0v.1lr (46.09 ft). The calculation does not include topography (3).
- 2. 14 booster pumps In addition to the four existing condenser cooling water pumps, per unit.
- 3. It Is assumed that a hypothetical passive water intake system utilizing the existing curtain wall would withdraw make-up water from Lake Ke0v.1!e into the intake canal. Make-up water pumps would not be required.
Notes:
- 1. Pipe diameters v.1lre selected to maintain a relatively consistent flow velocity within the pipe network.
- 2. Pipe lengths v.1lre estimated based on approximate cooling tov.1lr booster pump locations.
- 3. Existing cooling system requires four circulating water pumps per un~. mh a total four-pump operating capacity of 708,000 gpm.
- 4. Required make-up discharge based on evaporation calculations.
- 5. Circulating water flow rate is divided between each of the cooling t0v.1lr booster pumps to exchange hot and cold water.
References:
[1) Duke Energy. 2019. Oconee Nuclear Station Actual Intake Flow Rates: 7/1/2014 - 6/30/2019. Received: 3 Jul 2019.
[21 Lindeburg, Michael, R., 2003. Environmental Engineering Reference Manual for PE Exam, Second Edition. Professional Publications, Inc.
[3) SPX Cooling Technologies, Inc. (SPX). 2019. Quote for Cooling TOv.1lr Feasibility. 26 Sep 2019.
Calculations:
- 1. Estimate the Additional Dynamic Head Required for the Booster Pumps Formulas Used: 1, 2, 3 Booster Pump Friction Headloss
.--,*T-l - - .
HLI
- ft
-- 13.4 13.4
-- 13.4 Booster Pump Minor Headloss HL.m ft 4.75 4.75 4.75 Booster Pump Total Head Required (with a safely factor of 1.2) Hr ft 92 .7 92.7 92.7
- 2. Estimate the Additional Head Required for the Make-up Pump System Formulas Used: 1, 2, 3 Make-up Pump Friction Headloss Make-up Pump Minor Headloss ft Make-up Pump Total Head Required (with a safely factor of 1.2) Hr ft 4of4
Appendix 10-C Capital Cost Estimate for a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station
This page intentionally left blank.
Oconee Nuclear Station MDCT Retrofit - Capital Cost Estimate DATE:
8/27/2020 REVISION:
7 1515 Market St Su ite 2020
- Philadelphia, PA 19147 * (215) 845- 6700 r I Block l nou :
Paae 1te CLIENT I PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station ACTIVITY: MDCT Retrofit - Capital Cost Estimate TAKE OFF BY: SL COSTING BY: SL/SN CHECKED BY: SLISNITZ
8/31/2020 Oconee Nuclear Station Basis of Estimate
System Description
This document provides an AACE Class 4 capital cost estimate for the installation of three mechanical draft cooling towers to reduce impingement mortality and entrainment at Oconee Nuclear Station. This would involve the installation of new hot/cold water piping, blowdown piping, cooling tower booster pumps, and make-up water system. Condenser modifications are also included.
Assumptions 1 Union Labor drawn from the greater Greenville, SC metropolitan area. The national average cost differential would be approximately 25% higher for union verses open shop labor.
2 Work week will be Five (5) Eight (8) hour days.
3 Craft labor rates obtained from R.S. Means "Labor Rates for the Construction Industry, 2019 edition".
4 Quantities provided by HOR Engineering.
5 All costs are in 2019 dollars.
6 Material and unit installation rates obtained from R.S. Means Cost Data, 2019, Richardson Cost Data Online, and HOR Project historical data.
7 Native soils are adequate for structural backfill.
8 Design Engineering is calculated as 10 percent of the Construction Direct Costs.
9 Project Management (Engineering) is calculated as 10 percent of the Design Engineering Costs.
Exclusions 1 Escalation.
2 Sales tax.
3 Salvage value for any demolished materials.
8/31/2020 1,
Oconee Nuclear Station M OCT Retrofit Man-Hours Mat'I/Equ1p Labor Total Cost Construction Direct Costs Demolition 5,000 $ 10,250,000 $ 198,000 $ 10,448,000 Civil/Sitework 629,772 $ 331,889,000 $ 24,970,000 $ 356,859,000 Mechanical 123,600 $ 130,840,000 $ 4,691,000 $ 135,531,000 Structural 30,160 $ 9,500,000 $ 1,196,000 $ 10,696,000 Electrical and I&C 6,340 $ 18,946,000 $ 226,000 $ 19,172,000 Subtotal Construction Direct Costs .. 794,872 $ "so1,42s,oocr$ -31,2si;ooo -53i) 06,000 Construction Indirect Costs Contractor Site Supervision 0 $ - $ 31,200,000 $ 31,200,000 General Conditions 74,418 $ 97,975,000 $ 2,951,000 $ 100,926,000 General Admin & Profit 15% $ 99, 725,000 Subtotal Construction Indirect Costs 7<418 $- 97~000$ '34~ ls"i,bbo"T 231 ,85 1, 000 Total Construction Cost 869,290 $ 599,400,000 $ 65,432,000 $ 764,557,000 Design Engineering {10% Const LJ1rJ $ 53,271,000 Engineering PM (10% Eng Cost) $ 5,327,000 Esca1at1on (Mat I U%, Labor U0/oJ $ - $ - $ -
Owners Cost Labor $ 15,434,000 Labor Loadings $ 12,116,000 Overhead $ 52,825,000 Contingency $ 205,789,000
,u--rAL C.Al'J. £AL c.*u:;; I - ~ 1 1 1U!l,31!1 1 uuu
8/31/2020 Oconee Nuclear Station CUENT / PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: HDCT Retrof",t - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: General Conditions CHECKED BY: SLISNITZ I MATERIAL/ EQUIPMENT LABOR EQUIPMENT UNIT COST NO OE<arRIPT!ON nTY UNITS <:/UNIT TOTAL-< HRS/UNIT WAGE TnTAL HRS TOTAL-* TOTAL-$ *IUNIT TOTAL 1 Trainino / Safetv 1 Is $ - $ - 1 000 $ 39.65 1 000 $ 39 650 $ - $ 39 650 $ 39 650 2 Mobilization / Demobilization 1 Is $ - $ - 3 000 $ 39 .65 3 000 $ 118 950 $ - $ 118 950 $ 118 950 3 Field Office Exoenses 195 wk $ 80 000 $ 15 600 000 12 $ 39.65 2 340 $ 92 781 $ - $ 80 476 $ 15 692 781 4 Temoorarv Facilities 195 wk $ 7 500 $ 1 462 500 25 $ 39 .65 4 778 $ 189 428 $ - $ 8 471 $ 1 651 928 5 Temoorarv Utilities 195 wk $ 7 500 $ 1 462 500 100 $ 39 .65 19 500 $ 773 175 $ - $ 11465 $ 2 235 675 6 Suooort Craft & Site Services 195 wk $ - $ - 200 $ 39 .65 39 000 $ 1 546 350 $ - $ 7 930 $ 1 546 350 7 Construction Testing 12 wk $ 500 000 $ 6 000 000 150 $ 39 .65 1 800 $ 71 370 $ - $ 505 948 $ 6 071 370 8 Perfonnance Testina 12 wk $ 500 000 $ 6 000 000 100 $ 39 .65 1 200 $ 47 580 $ - $ 503 965 $ 6 047 580 9 Permits 1 Is $ 1 500 000 $ 1 500 000 0 $ 39 .65 0 $ - $ - $ 1 500 000 $ 1 500 000 10 11 Construction Eouioment Rentals Hvdrostatic / Static Head Testino 195 12 wk wk 200 500 000 000 39 6
000 000 000 000 0
150 39 .65 39.65 0
1 800 71 370 200 000 505 948
$ 39 6
000 071 000 370 12 Freioht 1 Is $ 250 000 $ 250 000 0 $ 39 .65 0 $ - $ - $ 250 000 $ 250 000 13 Small Tools 195 wk $ 50 000 $ 9 750 000 0 $ 39.65 0 $ - $ - $ 50 000 $ 9 750 000 14 Consumables 195 wk $ so 000 $ 9 750 000 0 $ 39 .65 0 $ - $ - $ so 000 $ 9 750 000 15 316/bl Studies 1 Is $ 1 200 000 $ 1 200 000 0 $ 39.65 0 $ - $ - $ 1 200 000 $ 1 200 000 16 17 18 19 20 21 22 23 24 25 TOTAL $ 97 975 000 74 418 $ 2 950 654 $ - $ 100 925 654 I
I Sales Tax TOTAL 0%
- 97 975 000 I 74 418 I $
NA 2 950 654 $
N/A 100 925 654
8/31/2020 Oconee Nuclear Station CUENT I PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: HDCT Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Civil/Site
- Demolition CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST EQUIPMENT NO DESCRIPTION OTY UNITS $ I UNIT TOTAL*$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ $/UNIT TOTAL l General Structural Demolition 1 Is $ 5 000 000 $ 5 000 000 2 000 $ 39.65 2 000 $ 79 300 $ . $ 5 079 300 $ 5 079 300 2 Demolition of Miscellaneous Mechanical Items l Is $ 5 000 000 $ 5 000 000 2 000 $ 39.65 2 000 $ 79 300 $ . $ 5 079 300 $ 5 079 300 3 5Poils Removal l Is $ 250 000 $ 250 000 l 000 $ 39.65 l 000 $ 39 650 $ - $ 289 650 $ 289 650 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ 10 250 000 5 000 $ 198 250 $ - $ 10 448 250 ISales Tax 0% $ - NA N/A $ -
(TOTAL $ 10 250 000 5 000 $ 198 250 $ - < 10 448 250
8/31/2020 Oconee Nuclear Station CUENT / PRO.JECT: Duke Energy Carolinas, LLC
- Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: HDCT Retrofit - capita/ Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Clv/1/Slte CHECKED BY: SLISNITZ I MATERIAL/ EQUIPMENT LABOR CONST, UNIT COST EQUIPMENT NO OESCRIPTION nn UNITS < I UNIT TOTAL-< HRS UNIT WAGE TOTAL HRS TOTAL-< TOTAL-$ <!UNIT TOTAL 1 Coolinn Tower Basin Excavation 19 274 CV s - - 0.20 s 39.65 3 855 s 152 843 - s 8 152 843 2 Coolina Tower Basin Backfill 8 673 CV 30.00 260 199 0.24 $ 39.65 2 082 82 535 - $ 40 342 734 3 Coolina Tower Basin Sooils Removal and Disoosal 10 601 CV - - 0.34 s 39.65 3 604 142 908 - s 13 142 908 4 Booster Pumo Station Excavation 9 019 CV - - 0.20 $ 39.65 1 804 71 524 - s 8 71 524 5 Booster Pumo Station Backfill 4 059 CV 30.00 121 763 0.24 $ 39.65 974 38 623 - $ 40 160 386 6 Booster Puma Station Sooils Removal and Dlsoosal 4 961 CV - $ - 0.34 $ 39.65 1 687 66 875 * - $ 13 $ 66 875 7 Booster Puma Station Shorina 8 Duct Bank Excavation 20 000 4 600 sv CY 100.00
- $ 2 000 000 6.00 0.20 39.65 39.65 120 000 920 4 758 36 000 478 s
338 8
6 758 000 36 478 9 Duct Bank Backfill 2 070 CV s 30.00 $ 62 100 0.24 $ 39.65 497 $ 19 698 $ $ 40 s 81 798 10 Duct Bank Snails Removal and Dlsaosal 2 530 CV s - $ - 0.34 $ 39 .65 860 $ 34 107 $ - $ 13 s 34 107 11 Coollna Tower Basin Concrete 16 760 CV s 300.00 $ 5 028 000 5.00 $ 39.65 83 800 s 3 322 670 $ - $ 498 $ 8 350 670 12 13 Coolina Tower Basin Pilina {9 522 @ SO' ea)
Coolina Tower Basin Shoring 476 100 20,000 SY If s 100.00 100.00 s
47 2
610 000 000 000 0.00 6.00 39.65 39.65 0
120,000 s
4 758,000 s
100 338 47 610 000 6 758 000 14 Booster Pumo Station Concrete 15 Booster Pumo Station Pilina fl 377 @ 50' eal 7 843 68 850 CV If 300.00 100.00 $
$ 2 6
352 885 900 000 5.00 o.oo 39.65 39.65 39 215 0
s s
1 554 875
- *s -
s 498 100 s
s 3 907 775 6 885 000 16 Duct Bank Concrete 17 Hot Water Pioe Trench Excavation 4 000 7 035 CV CV s
300.00 1 200 000 5.00 0.20
- $ 39.65 39.65 20 000 1407 793 000 55 788 s
498 8
1 993 000 55 788 18 Hot Water Pioe Backfill 19 Hot Water Ptoe Sooils Removal and Disoosal 3 166 3 869 CV CV s
30.00
- *s 94 973 0.24 0.34
- 39.65 39.65 760 1 316 30 125 52 161 s
40 13 125 098 52 161 20 Cold Water Pioe Trench Excavation 21 Cold Water Ploe Backfill 2 680 1 206 CV CV 30.00 $
s -
36 180 0 .20 0.24 39.65 39.65 536 289 21 252 11 476 $
s 8
40 21 252 47 656 22 Cold Water Pioe Sooils Removal and Disoosal 1,474 CV $ - $ - 0.34 $ 39.65 501 $ 19,871 $ $ 13 $ 19,871 23 24 Bk>wdown Pioe Trench Excavation Slowdown Pioe Backfill 335 151 CV CV s
30.00 4 523 0.20 0 .24 $
$ 39.65 39.65 67 36 s
2 657 1435 s
8 40 s 2 657 5 957 25 Slowdown PiD@ Sooils Removal and Disposa l 184 CV $ - s - 0 .34 $ 39.65 63 $ 2 484 - 13 2 484 26 Install Hot Water Pioe and Fittings 10 500 If $ 2 ODO.OD $ 21 000 000 3.00 $ 39.65 31 500 $ 1 248 975 - l 2 119 22 248 975 27 Install Cold Water Discharae Channel 4 000 If $ 10 000.00 s 40 000 000 10.0 $ 39.65 40 000 $ 1 586 000 - l 10 397 41 586 000 28 Install Slowdown Pin@ and Fittings 500 If $ 1 000 .00 $ 500 000 3.00 $ 39.65 1 500 $ 59 475 - l 1 119 559 475 29 Install Miscellaneous Concrete 15 000 CV $ 300.00 $ 4 500 000 5.00 $ 39.65 75 000 $ 2 973 750 - s 498 7 473 750 30 Hot Water Pipe Pilina fl 750 @ 50' eal 87 500 If $ 100.00 $ 8 750 000 0.00 s 39.65 0 $ - - s 100 8 750 000 31 Cold Water Pipe Pilina (667 @ 50' eal 32 Install Booster Pumo Station Buildino 33 333 1
If Is
$ 10 100.00 000 000.00 s
3 333 333 10 000 000 0.00 2 500.00 s
39.65 39.65 0
2 500 s 99 125 s
< 10 099 100 125 3,333,333 10 099 125 33 Install Make-uo Water Svstem Racks and Screens 1 ea s 1 000 000.00 $ 1 000 000 500.00 $ 39.65 500 s 19 825 $ - s 1 019 825 $ 1 019 825 34 Install Concrete for Make- uo Water Svstem 1 334 CV s 300.00 s 400 200 SO.DO $ 39.65 66 700 s 2 644 655 $ $ 2 283 $ 3 044 855 35 Oewaterina 36 Additional General Excavation and Rearadino - Allowance 195 1
wk Is
- 50 50 000.00 000 000.00 9 750 000 50 000 000 40.00 0.00 s
39.65 39.65 7 800 0
s 309 270
$ 50 000 51 586 000 10 059 270 50 000 000 37 38 Nuclear 5afetv Service Water Svstem Retrofit
- Allowance Settlina / Treatment Basin for Coolina Tower Slowdown - Allowance 1
1 Is Is
- s 50 15 000 000.00 000 000.00 50 000 000 15 000 000 0.00 0.00 39.65 39.65 0
0 so 000 15 000 000 000 s
50 000 000 15 000 000 39 40 Transm ission line Relocation - Allowance 1 Is $ so 000 000.00 50 000 000 0.00 $ 39.65 0 $ - s - $ so 000 000
- 50 000 000 TOTAL $ 331889170 629 772 $ 24 970 460 $ - $ 356 859 630 5ales Tax TOTAL 0% $
s 331 889 170 629 772 NA
$ 24 970 460 NIA 356 859 630
8/31/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: HDCT Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Structural CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST EOUIPMENT NO DESCRIPTION OTY UNITS $ I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ UUNIT TOTAL 1 Install Pilina Cross Members Suooort Steel 600 ton $ 10 000 $ 6 000 000 50 $ 39 .65 30 000 $ 1 189 500 $ - $ 11 983 $ 7 189 500 2 Install Pre-Fabricated Sheetino 1 Is $ 2,500,000 $ 2,500,000 80 $ 39.65 80 $ 3,172 $ - $ 2,503,172 $ 2,503 172 3 Miscellaneous Steel Allowance 1 Is $ 1 000 000 $ 1 000 000 80 $ 39 .65 80 $ 3 172 $ - $ 1 003 172 $ 1 003 172 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ 9 500 000 30 160 $ 1 195 844 $ - $ 10 695 844
!Sales Tax 0% $ - NA NIA $ -
!TOTAL s 9 500 000 30 160 s 1 195 844 s - S 10 695 844
8131/2020 Oconee Nuclear Station CUENT / PROJECT: Duke Energy Carollnas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVETY: HDCT Retront - capita/ Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Hechanlcal CHECKED BY: SL/SN Ill I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST EOUIPMENT NO DESCRIPTION OTY UNITS S / UNIT TOTAL*S HRS/UNIT WAGE T TAL HRS TOTAL*< TOTAL*S <!UNIT T TAL 1 Install Coolina Tower Booster Pumos (42@ 51 000 aom) 42 ea $ 1 020 000.00 $ 42 840 000 800 $ 37.95 33 600 $ 1 275 120 $ - $ 1 050 360 $ 44 115 120 2 Condenser Uoorades ~ Allowance 1 Is $ 25 000 000.00 $ 25 000 000 0 $ 37.95 o s - $ - $ 25 000 000 $ 25 000 000 3 Install 30-cell Mechanical Orafl Coolina Tower 3 ea 21 000 000.00 $ 63 000 000 30 000 $ 37.95 90 000 s 3 415 500 $ - S 22 138 500 $ 66 415 500 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 TOTAL $ 130 840 000 123600 $ 4 690 620 $ - $ 135 530 620
,sales Tax 0% $ - NA N/A $ -
ITOTAL $ 130 840 000 123 600 $ 4 690 620 $ $ 135 530 620
8/31/2020 Oconee Nuclear Station CUENT / PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: MDCT Retrofit - capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Electrical and IAC CHECKED BY: SL/SNITZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST EQUIPMENT NO DESCRIPTION OTY UNITS $/UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ $/UNIT TOTAL 1 Install Wirino and Connections 25 000 If $ 10.00 $ 250 000 0.08 $ 35.65 l 925 $ 68 626 $ - $ 13 $ 318 626 2 Install Conduit 10 000 If $ 45.00 $ 450 000 0.05 $ 35.65 500 $ 17 825 $ - $ 47 $ 467 825 3 Install Terminations 300 ea $ 2.00 $ 600 0.60 $ 35.65 180 $ 6 417 $ - $ 23 $ 7 017 4 Install MCC 6 ea $ 400 000 $ 2 400 000 40.00 $ 35.65 240 $ 8 556 $ - $ 401 426 $ 2 408 556 5 Install DC5 60 ea $ 5 000 $ 300 000 10.00 $ 35.65 600 $ 21 390 $ - $ 5 357 $ 321 390 6 Install Breakers 6 ea $ 5 000 $ 30 000 1.00 $ 35.65 6 $ 214 $ - $ 5 036 $ 30 214 7 Alarm Dialer 3 ea $ 5 000 $ 15 000 3.00 $ 35.65 9 $ 321 $ - $ 5 107 $ 15 321 8 Install Power Distribution Center 3 ea $ 700 000 $ 2 100 000 240 $ 35.65 720 $ 25 668 $ - $ 708 556 $ 2 125 668 9 Install Transformers 12 ea $ 200 000 $ 2 400 000 80 $ 35.65 960 $ 34 224 $ - $ 202 852 $ 2 434 224 1 o Power Suoolv 3 ea $ 3 000 000 $ 9 000 000 400 $ 35.65 1 200 $ 42 780 $ - $ 3 014 260 $ 9 042 780 11 Additional Electrica l Eouioment - Allowance 1 Is $ 1 000 000 $ 1 000 000 0.00 $ 35.65 0 $ - $ - $ 1 000 000 $ 1 000 000 12 Additional Electrical Enoineerino - Allowance 1 Is $ 1 000 000 $ 1 000 000 0.00 $ 35.65 0 $ - $ - $ 1 000 000 $ 1 000 000 13 14 15 TOTAL $ 18 945 600 6 340 $ 226 021 0 $6 342 663 $ 19 171 62 1 ISales Tax 0% $ - NA NIA $ -
!TOTAL $ 18 945 600 6 340 $ 226 021 $ - $ 19171621
8/31/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: MDCT Retrofit - Capital Cost Estimate COSTING BY: SLISN I DISCIPLINE: Engineering CHECKED BY: SLISNITZ I MATERIAL/ EOUIPMENT LABOR UNIT COST NO DESCRIPTION OTY UNITS ,i; I UNIT TOTAL-"' HRS/UNIT WAGE TOTAL HRS TOTAL-$ <!UNIT TOTAL 1 Enaineerina 1 Is $ - -$
- 0 $ - 0 $ 53 270 597 $ 53 270 597 $ 53 270 597 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL
"' - 0 $ 53 270 597 $ 53 270 597 Sales Tax 0% N/A NA Sub Total ~ - $ 53 270 597 $ 53 270 597 Continaencv 0% ~ - $ - $ -
TOTAL $ - 0 $ 53 270 597 $ 53 270 597
8/31/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: HDCT Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DlSClPLlNE: Construction Management CHECKED BY: SLISNITZ MATERIAL/ EQUIPMENT LABOR UNIT COST NO DESCRIPTION OTY UNITS s I UNIT TOTAL-t HRS/UNIT WAGE TOTAL HRS TOTAL-$ t/UNIT TOTAL 1 Construction Manaoement 195 wk $ - $ - 0 $ 160 000 0 $ 31 200 000 $ 160 000 $ 31 200 ODO 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ 31 200 000 $ 31 200 000 Sales Tax 0% NIA NA ITOTAL $ - 0 $ 31 200 000 $ 31 200 000
8/31/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL ACllVITY: MDCT Retrofit - Capital Cost Estimate COSTING BY: SL/SN DISCIPLINE: Project Management CHECKED BY: SL/SN/TZ I MATERIAL/ EQUIPMENT LABOR UNIT COST NO DESCRIPTION QTY UNITS $ I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL- $ $/UNIT TOTAL 1 Project ManaQem ent 1 Is $ - $ - 0 $ - 0 $ 5,327 060 $ 5,327 060 $ 5 327 060 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ 5 32 7 060 $ 5 327 060 Sales Tax 0% N/ A NA Sub Total $ - $ 5 327 060 $ 5 327 060 Continaencv 0% $ - $ - $ -
TOTAL $ - o $ 5 327 060 $ 5 327 060
Appendix 10-D Engineering Estimates of Through-screen Velocity for Existing Coarse-mesh Screens at Oconee Nuclear Station
This page intentionally left blank.
Duka Energy Carolinas, U.C I Oconee Nuclear Station
- ReYiafon:
laaue Date:
Engineering Estimates of Through-Screen Velocity for Existing Fixed Panel Mesh Screens at Oconee Nuclear Station Originator: Spencer Nush, EIT 11/30/2018 Reviewer: Shane Galloway, EIT 6/6/2019 Approver: Scott Loughery, PE 6/13/2019 Revision No. Revised by: Approved by: Descriplion 0
Calculation Summary:
- ---.--~ ~-~- ' .
One-pump Operation
-fps
-* 2.90
-- 2.90
- -- 2.90 Two-pump Operation fps 2.74 2.74 2.74 Three-pump Operation fps 2.39 2.39 2.39 Four-pump Operation fps 2.08 2.08 2.08 1 of 5
Duka Energy Carolina*, U.C I Oconee Nuclear Station Rwiaion:
lasue Date:
Engineering Estimates of Through-Screen Velocity for Existing Fixed Panel Mesh Screens at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-U'ltt nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Calculate the design through-screen velocity, through-bar velocity, and approach veloctty at the Oconee Nuclear Station cooling water intake structure.
Calculation Objectives:
- 1. Identify the screen physical parameters and design intake flow rate.
- 2. Calculate the open area of the foced panel mesh screens and the open width at each bar rack open for water flow.
- 3. Calculate the through-screen and through-bar velocities for the desig:1 intake flow.
Calculation Methodology:
Formula 1 v..
- Q/ (WD
- SW - FAj
- EOA
- C1)
Units: fps where:
Q = Flow rate (gpm) v.., = Effective through-screen veloctty (fps)
WD = Screen area available to flow (ft)
EOA = Proportion of effective open area FA= Screen frame area (tr)
SW = Screen width (ft)
C1 = Conversion factor from gpm to els (1 els = 449 gpm)
Formula 2 OA* (W' L)/((W+ D)* (L+d))
Units: unitiess Vr'here:
0A = Proportion of screen open area to total screen area d= Horizontal v.ire diameter (1'!.ch)
D* Vertical wire diameter (inch)
W= Width of mesh opening (inch)
L= Vertical length of mesh opening (inch)
Fonnula3 EOA*PC*OA Units: percent
'Nhere:
PC= Screen percent clean (%)
Formula 4 v_-o,cc1
- cs*woi Units: fps where:
v,.. = Approach velocily (fps)
CS = Width of channel immediately before screen (ft)
Formula 5 v..,-01(c1 *wo* ow,.)
Units: fps Yt'here:
v,_
- Through-bar velocity (fps)
OW.,* Open width at each bar reek (ft)
Formula 6 OW., * (n
- BS) /C2 Units:ff where:
n = Number of spaces per bar rack BS= Bar rack bar spacing (inch)
C2 = Conversion factor from inch to ft (1 foot= 12 inches) 2 of 5
Duke Energy Carolinas, LLC I Oconee Nuclear Station R8'1iaion:
laueDate:
Engineering Estimates of Through-Screen Velocity for Existing Fixed Panel Mesh Screens at Oconee Nuclear Station Design Inputs:
Waterbody Information Station Datum Bottom of Overha Bar Rack Information Bar Rack Bar S acin Number of S aces er Bar Rack Fixed Screen Information Elevation at Bottom of CWIS 761 .0 761 .0 761.0 Number of Screens 8 8 8 [1)
Screen Width 10.75 10.75 10.75 n (2)
Frame Area Bottom of Overhan El. 46.78 46.78 46.78 ft' [5], Note 1, Assumption 1 Width of Channel lmmediatel before Screen 11 .3 11.3 11 .3 n 0.375 0 .375 0.375 mch [2) 0.375 0.375 0.375 (2)
U.S. Standard U.S. Standard U.S . Standard Assumption 6 11 11 11 Aslumption6 0.125 0.125 0 .125 [4) 11 11 11 Aasumption6 0.125 0.125 0.125 [4) 0% 0% 0% Assumption Number of Condense 4 4 4 121 ondenser Coolin Water Pu 246,000 246,000 246 000 (3], Assumption 5 708 000 708,000 708 000 [3], Assumption 5 Flow Based 246,000 246,000 246,000 IJL Aa11umption 7 Screens Utilized w
- 2 2 2 [3L Aasumption 7 Flow Based on 465,000 465,000 465,000 [3), AIIUl'Tlption 7 4 4 4 {3], Assumpt>on 7 609,000 609,000 609,000 (3], Assumption 7 6 6 6 [3), AHumption 7 708,000 708,000 708,000 gpm (3], Auumption 7 8 8 8 [3], AalWTlption 7 Assumptions:
- 1. Screen area available to flow is impacted by the presence of the overhang at the CWIS. Cooling water is wrthdrawn from the bottom of the overhang elevation (781.0ft msl) to the bottom of the CWIS elevation (761 .0ft msl).
- 2. The cooling water intake structure has not been modified since dates of references used.
3 . All screens function similarly.
- 4. For the purposes of these calculations, the screens are assumed to be free of debris and 100% clean. The through-screen velocity would increase with the presence of debris.
- 5. While the individual condenser cooling water pump design capacity is 246,000 gpm, when multiple pumps are operating for a given lllrt, a piping restriction limits the cooling system capacity to 708,000 gpm per unit. Due to the piping restriction, the total water withdrawal through the cooling water intake structure (all ttvee units comt,;ned) is limrted to 2,124,000 gpm (3,059 MGD) [3].
6.
The gauge type is Number 11 U .S. Standard Gauge for Sheet and Plate Iron and Steel, given ver1ical and horizontal wire diameter of 0.125-inch.
- 7. Due to a piping restriction. the condenser cooling water pump flow per unrt changes based on number of pumps operating and number of screens utilized. It is assumed that flow is distributed equally among utilized screens.
Notes:
- 1. The closed fixed screen frame area was calculated using dimensions from provided engineering drawing 0-346, and was subtracted from the total screen area to achieve an accurate effective open area value [5].
References:
[1] Duke Power Company. 2000. Oconee Nuclear Station- Intake Structure General Arrangement Plans and Sections. Drawing No. 0-339- Rev 7.
16 Nov 2000.
[21 Electric Power Research Institute (EPRI). 2008. Information Submitted for Best Professional Judgment §316(b) Decision-making for Duke Energy's Oconee Nuclear Station - Final Report. October 2008.
[3] Duke Energy. 2019. Oconee Nuclear Station Actual Intake Flow Rates: 7/112014 -6/30/2019. Received: 3 Jul 2019.
[4] Alden and EPRI. 2004. Evaluation of the Oconee Nuclear Station with respect to the Environmental Protection Agency's §316(b) Rule for Existing Facilities. October 2004.
[5] Duke Power Company. 2004. Oconee Nuclear Station Unrts 1, 2 & 3 - Intake Structure Bulkhead Gates & Screens. Drawing No. 0-346 - Rev. 3.
13 Aug2004.
[6] Duke Power Company. 1994. Oconee Nuclear Station- Unrts 1, 2, & 3 Intake Structure Trash Rack Details. Drawing No. 0-347 -Rev. 3. 2 May 1994.
[7] Duke Energy. 2020. Oconee Nuclear Station CWIS Photos - Overhang and Fixed Screen Slot. Received 3 Apr 2020.
[8] Unrted States Army Corps of Engineers (USACE). 2014. Final Environmental Assessment - New Operating Agreement between U.S. Army Corps of Engineers. Southeastern Power Administration, and Duke Energy Carolinas, LLC. October 2014.
3 of S
Duke Energy Carolinas, Ll.C I Oconee Nuclear Station RtHision:
l11ueDate:
Engineering Estimates ol Tilrough-Screen Velocity for Exl1tlng Fixed Panel Mesh Screens at Oconee Nuclear Station Calculations:
- 1. Screen Physical Parameters and Design Intake Flow Rate Given : - c ..... =
-- 708,000
--708,000
~-
708,000
--gpm Q..,.= 123,000 123,000 123,000 gpm per screen C1wo= 116,250 116,250 116,250 gpm per screen Ottir*= 101 ,500 101,500 101,500 gpm per screen c ..,= 88,500 88,500 88,500 gpm per screen D= 0.125 0.125 0.125 inch d= 0.125 0.125 0.1 25 inch L= 0.375 0.375 0.375 inch W= 0.375 0.375 0.375 inch WD~= 20.0 20.0 20.0 ft WO..--,= 29.0 29.0 29.0 ft C1= 448.8 448.8 448.8 1 els = 448.8 apm C2= 12 12 12 1 ft= 12 inch SW= 10.75 10.75 10.75 ft FA_,-.,= 46.78 46.78 46.78 tr BS= 2.5 2.5 2.5 inch PC= 100% 100% 100%
CS= 11.3 11.3 11.3 ft n= 46 46 46
- 2. Proportion of Effective Open Screen Area to Total Screen Area Formulae Used:
Formulae 2 and 3 Given:
Screen parameters as above Calculate:
Screen OA= (Y'./ *L)/((W+ D) * (L + d))=
EOA = PC *OA =
- 3. Design Tilrough-screen Velocity Formula Used:
Formula 1 Given:
Screen parameters as above and calculated screen open area proportion Calculate:
v.,.= Q /(Y'./D *SW-FA)* EOA *C1) One-pt.mp Operation Two.pump Operation Three-oumo Ooeration
' -* 2.90 2.74 2.39
- -- 2.90 2.74 2.39 I
---2.90' 2.74 2.39
-fps fps fos i
Four-puma Ooeration 2.08 2.08 2.08 fos 4 of 5
Duka Energy Carolinas, Ll.C I Oconee Nuclear Station RIM91on:
luueDate:
Engineering Estimates of Through-Screen Velocity for Existing Fixed Panel Mesh Screens at Oconee Nuclear Station
- 4. Design Approach Velocity Formula Used:
Formula 4 Given:
Channel dimensions and stated assumption Calculate:
v..., = Q / (C1 *CS* WD) = One-pump Operation
- -- 0.83
-- 0.83
---0.83
-fps Two-cump Operation 0.79 0.79 0.79 fps Three-pumo Ooeration 0.69 0.69 0.69 IDS Four-pumo Ooeration 0.60 0.60 0.60 fps Calculations: cont.
- 5. Design Through-bar Velocity at Bar Rack Formulae Used:
Formulae 5 and 6 Given:
Bar rack parameters as shown in design inputs Calculate:
ow,,= (n
- BS)/C2 = 9.581 9.s8I 9.SBI n v... =a /(C1 *wD *ow.,J =
One-pump Operation Two-pump Operation Three-pump Operation
-* 1.43 1.35 118 1.43 1.35 1.18 1.43 1.35 118 fps fps fos Four-pump Operation 1 03 103 1.03 fps S of S
This page intentionally left blank.
Appendix 10-E Evaluation of Biological Efficacy of Fine-mesh Screen Sizes at Oconee
- Nuclear Station
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 10-E rL "'\~
.I~
- 1 2
Table of Contents Introduction .........................................................................................................................................1 Background .........................................................................................................................................1 3 Fine Mesh Screen Size Availability .....................................................................................................2 4 FMS Selection Methodology ...............................................................................................................2 5 Results ................................................................................................................................................3 5.1 Fine-mesh Screen Feasibility ....................................................................................................3 5.2 FMS Exclusion ..........................................................................................................................5 5.3 FMS Size Performance .............................................................................................................6 5.3.1 Reductions in Annual Entrainment Loss Estimates ..................................................... 7 5.3.2 Reductions in Production Foregone and Equivalent Adults ......................................... 9 6 Conclusions .......................................................................................................................................10 7 References ........................................................................................................................................12 Figures Figure 5-1. Estimated Headless and Through-Screen Velocity Calculated by Screen Mesh Size at Maximum Water Withdrawal and Maximum Clogging (50 Percent) ................................................5 Figure 5-2. Total Organism Measurement Frequencies from Morphometric Data Collected During the 2016-2017 Entrainment Characterization Study at Oconee Nuclear Station ............................. 6 Figure 5-3. 2016-2017 Estimated Annual Entrainment Losses under Existing Condition (3/8-inch mesh) and Alternative Fine-mesh Screen Sizes ..............................................................................8 Tables Table 5-1. Estimated Performance Conditions of FMS at Oconee Nuclear Station ..................................... 4 Table 5-2. Annualized Entrainment Mortality by Screen Mesh Size Estimated for 2016 and 2017 under Maximum Water Withdrawals at Oconee Nuclear Station .....................................................?
Table 5-3. Estimated Percent Reductions in Annual Entrainment Losses by FMS Size .............................. 8 Table 5-4. Estimated Production Foregone and Equivalent Adult Losses by Screen Mesh Size for 2016 and 2017 ...............................................................................................................................10
- Duke Energy 110-E-i
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 10-E rL "\""
.I~
- 1 Introduction The cooling water intake structure (CWIS) at Oconee Nuclear Station (Oconee) is currently equipped with fixed, 3/8-inch coarse-mesh screens and has a design intake flow (DIF) of greater than 2 million gallons per day (MGD). Therefore, Section §316(b) of the final Clean Water Act (CWA) rule (Rule) requires the evaluation of technical feasibility and costs associated with entrainment reduction technologies including fine-mesh screens (FMS) with a mesh size of 2.0 millimeters (mm) or smaller (§122.21(r)(10)). While any FMS technology with 2.0-mm or smaller openings may be considered in the evaluation, commercially available technologies are generally limited to modified Ristroph traveling screens, wedgewire screens (both cylindrical and flat panel), and perforated plate (typically flat panel)1.
The FMS size selection methodology was developed to provide a framework for selecting the FMS size on a site-specific basis for use in the evaluations required at 122.21(r)(10)-(12) and is driven by the biological efficacy, or the efficiency of a given mesh size at excluding ichthyoplankton from entrainment at the CWIS. This document describes the methodology used to evaluate available mesh sizes and presents the mesh size recommended for further evaluation as a candidate entrainment compliance technology at Oconee. The recommended FMS size will be evaluated for feasibility and design considerations including estimated costs for permitting, installing, operating, and maintaining FMS as an entrainment reduction technology (detailed in Section 10 of the Oconee §316(b) compliance document) .
- 2 Background A decrease in screen mesh size can have a number of effects on the physical conditions at the CWIS as well as the biological community in the vicinity of the CWIS. With a smaller mesh size, the open area available for water flow becomes restricted, which increases through-screen velocity (TSV) and headloss values; this can subsequently affect the structural integrity of the screens and/or cause increased wear and tear on the equipment over time. Furthermore, for organisms that become impinged, on-screen trauma and mortality rates may increase in response to increased TSV. For juvenile fish, scale loss and injury can increase at higher TSV values and mortality rates may be greatest at velocities higher than 2.0 feet per second (fps)
(EPRI 2006). For early life stage organisms that are converted 2 to impingement on FMS, survival on FMS is largely determined by the larval life stage (EPRI 2010). Younger and smaller larvae, such as yolk-sac larvae, have a much higher on-screen mortality rate than older life stages (post yolk-sac larvae, young-of-year, or juveniles) due to underdeveloped scaling and 1 Filter barriers, for example the GunderboomTM Marine Exclusion Barrier, are generally not considered as "fine-mesh screen" and thus not considered herein. However, the results for entrainment reductions under alternative fine-mesh screen sizes provided in this section would be generally applicable to filter barriers.
2 Converts, as defined by the Rule (p. 48331), are ichthyoplankton that would have been entrained through a 3/8-inch mesh screen but instead are impinged on an FMS.
Duke Energy J 10-E-1
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 10-E rL "\'""
.I~
- musculature (EPRI 2010). Approach velocity can also be a predictor of convert survival: 0.5 fps has been shown to result in significantly greater survival than 1.0 fps for smaller larvae, while an approach velocity of up to 1.5 fps has shown to have little effect on larger larvae (EPRI 2010).
However, research has indicated that there is a marked decrease in survival at 2.0 fps, particularly at longer impingement durations (EPRI 2010).
With these considerations and site-specific information regarding existing facility configuration and the biological community in the vicinity of the Oconee CWIS, an FMS analysis was completed to determine a recommended FMS size(s) that should be considered in
§122.21 (r)(10)-(12) evaluations.
3 Fine Mesh Screen Size Availability Based on communications with screen vendors and a review of existing projects/facilities, the smallest mesh-size traveling screen that has been installed at a once-through CWIS is 0.5 mm (e.g., TECO Energy, Big Bend Station 3). While wedgewire screens can be ordered in virtually any slot size (pers. comm. Bilfinger), there are few existing CWIS screens with slot sizes of 1.0 mm or smaller. The smallest slot-size wedgewire screen in use at a once-through electric generating station is at Upstate Power Producers' Cayuga Generating Station, which has 0.75-mm slot wedgewire screens on a 247-million gallon per day (MGD) offshore intake4
- Perforated plates are uncommon at once-through CWISs due to the relatively small percent open area associated with this technology, and as a result is not evaluated further. Where flat panel screens may be considered, wedgewire would generally be preferred over perforated plate due to its strength and greater percent open area and associated lower TSV. FMS are available in a limited number of mesh sizes, typically including 2.0 mm, 1.0 mm, 0. 75 mm, and 0.5 mm (Evoqua 2019 and Ovivo 2014). Therefore, these mesh sizes were c.hosen for evaluation in this analysis .
.4 FMS Selection Methodology The following approach was designed to incorporate annual entrainment estimates from the 2016-2017 Oconee Entrainment Characterization Study (Appendix 9-A) to determine which FMS size(s) should be evaluated as a part of the analyses required in 122.21(r)(10)-(12):
- 1. Engage screen vendors to confirm commercially available fine-mesh screen mesh/slot sizes and associated percent open areas to facilitate through-screen velocity (TSV) calculations.
3 Florida, marine facility; seasonally deployed 0.5-mm FMS at two of four units; screens are in series with the 3/8-inch traveling screens; design intake flow of 704.5 MGD 4 New York, freshwater oligotrophic lake; permanent offshore deployment (525 feet offshore, 40 feet water depth); 0.75-mm slot size; 0.35 fps through screen velocity; design intake flow of 247 MGD Duke Energy I 10-E-2
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 10-E rL J"'\""i~
- 2. Evaluate the technical feasibility of each mesh relative to headless, operational 3.
constraints, and other site-specific engineering factors.
Evaluate site-specific entrainment relative to contributions from these categories, as applicable:
- a. Recreationally and commercially important species;
- b. Ecologically important species (e.g., habitat formers, forage);
- c. Federal and/or state-listed protected species; and
- d. Invasive and/or nuisance species.
- 4. Calculate percent reductions in estimated annual entrainment at commercially available and technically feasible mesh sizes based on:
- a. Total numbers lost;
- b. Total equivalent adults5;
- c. Total production foregone (biomass) 6 ; and
- d. Additional site-specific factors, as may be applicable from #3 above.
- 5. Consider on-screen survival vs. through-plant survival for excluded 7 organisms based on site-specific factors, as applicable.
- 6. Finally, after consideration of the above, use Best Professional Judgment to select a mesh size (or sizes) for advancement in evaluations conducted to fulfill requirements at
§122.21(r)(10)-(12).
5 Results 5.1 Fine-mesh Screen Feasibility Headless (obtained from commercial vendors) and TSV values were calculated for each FMS size in orde*r to assess the performance and feasibility of the mesh size under consideration.
Calculations were completed under clear-screen (i.e., zero percent), 15 percent, and 50 percent clogging scenarios for maximum water withdrawals (intake flows at design pump capacity) at maximum reservoir drawn-down conditions. A trash boom is present upstream of the Oconee CWIS, therefore debris loads on the screens are generally not considered problematic; however, influx of vegetation during certain times of year or following a storm event could cause short-term blinding of the screens.
5 The number of fish that would have survived to some defined future age (age of equivalence) if they had not been entrained.
6 The prey and non-game species biomass that has been removed from the system due to entrainment.
7 Organisms that are excluded from the cooling water system by the FMS .
Duke Energy 11 0-E-3
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal A ppendix 10-E 1-~""'
.I~
- Headloss values and TSV increase with decreasing mesh size and/or increased clogging (Table 5-1 , Figure 5-1); therefore , head loss values increase with the installation of (or conversion to)
FMS. The largest incremental changes (i.e., increases) result from 2.0-mm and 1.0-mm FMS (increases from 0.7 to 6.0 or 12.3 inches, respectively) , and smaller incremental changes occur with remaining mesh sizes. By converting to a FMS from an existing coarse-mesh screen (3/8 inch) , TSV increases by over seven percent at 2.0 mm , and up to over 35 percent at 0.5 mm, assuming maximum water withdrawals and 50 percent clogging . The TSV for all fine-mesh options evaluated exceed 0.5 feet per second (fps) , which is the Rule-defined TSV threshold for establishing Best Technology Available (BTA) for impingement mortality compliance.
Table 5-1. Estimated Performance Conditions of FMS at Oconee Nuclear Station
.,,q.Y.,..
Summary
-- hf 0
Maximum Drawdown Elevation and Design Intake Flow (Most Conservative Estimates)
Effective Open Area(%)
56 Headloss (inches) 0.4 TSV (fps) 1.4 3/8 inch None 15 48 0.4 1.7 50 28 0.7 2.8 0 51 4.6 1.5 2.0mm 1.0 inch 15 44 4.7 1.8 50 26 6.0 3.0
- 1.0 mm 1.0 inch 0
15 50 0
45 38 22 43 9.8 10.1 12.3 9.8 1.7 2.0 3.4 1.8 0.75 mm 1.0 inch 15 37 10.2 2.1 50 22 12.6 3.6 0 40 10.0 1.9 0.5mm 1.0 inch 15 34 10.4 2.2 50 20 13.1 3.8
- Duke Energy I 10-E-4
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §3 16(b) Compliance Submittal Appendix 10-E L.:)~
~ *~
- 14 12
-(/) 10 a,
H e adless TSV
},
4 3.5 3
~
(/)
0..
!t:,
u 0
..c: 2.5 u 8 ~
-C:
( /)
(/)
0 6 -
Ii 2 C:
a, a,
u
=aro 1.5 (/)
a, 4 ,,,. ..c:'
Cl I 1 ::J 0
2 ..c:
0.5 I-0 LIi - 0 3/8 inch 2.0 mm 1.0 mm 0.75 mm 0.5 mm Screen Mesh Size Figure 5-1 . Estimated Headloss and Through-Screen Velocity Calculated by Screen Mesh Size at Maximum Water Withdrawal and Maximum Clogging (50 Percent) 5.2 FMS Exclusion Species-specific morphometric data collected during the 2016-2017 Entrainment
- Characterization Study (Study) (HOR 2019) performed at Oconee, including average head capsule depth (larvae) and minimum width/diameter (eggs), were used to determine species and life stage-specific exclusion efficacy for each FMS size . Head capsule depth is known to dictate larval exclusion because it is the only hard structure in larval fish (EPRI 2014). Prior to transformation to the juvenile stage, larval skeletal and muscular systems are undeveloped ,
flexible , and fragile . While it could be argued that the maximum egg diameter should be used to calculate exclusion on a square mesh , the force of intake flow can be sufficient to deform eggs and pull them into the cooling system when impinged on a screen (particularly at high TSVs) ;
therefore, the use of minimum egg diameter is a conservative approach to help offset these effects .
Morphometric data from six larvae which included a single Shad Group 8 larvae , three Clupeid Group 9 post yolk-sac larvae, one Clupeid Group yolk-sac larvae, and one unidentified sunfish (Lepomis spp .) post yolk-sac larvae, in addition to six Shad Group eggs and 52 Blueback Herring (Alosa aestivalis) eggs were used to calculate the fraction of each taxa and life stage excluded by each FMS mesh size opening . The percentage of collected organisms excluded for all species and life stage for each FMS size evaluated is presented in Figure 5-2 .
8 Organisms could not be identified to species, but were possibly Gizzard Shad (Dorosoma cepedianum) or Threadfin Shad (D. petenense) .
9 Organisms could not be identified to species, but were possibly Blueback Herring (Alosa aestivalis) ,
Alewife (A. pseudoharengus) , Gizzard Shad , or Threadfin Shad .
- Duke Energy 11 0-E-5
Duke Energy Carolinas, LLC I Ocon ee Nuclear Stati on CWA §316(b) Complia nce Submittal Appendix 10-E
- -0 Q)
(/)
ro Q) 60 50 40 Measurement Cumulative Frequency 100%
90%
80%
70%
~
0
(.J C
Q)
~ 60% ::s CT
._ Q)
Q) 30 50% LL
.n E
- s 40%
Q) z 20 :;::.
ro 30% :i 20%
E 10 0 10%
0 0%
q ...- C"! Cf:! -.:t: '-".! ~ I'--; <X:! ~ q -r: C"! Cf:! -.:t: '-".! ~ I'--; <X:! ~ q 0 0 0 0 0 0 0 0 0 0 ...- ...- ...- ...- ...- ...- ...- ...- ...- ...- N Measurement mm Figure 5-2. Total Organism Measurement Frequencies from Morphometric Data Collected During the 2016-2017 Entrainment Characterization Study at Oconee Nuclear Station 5.3 FMS Size Performance To evaluate FMS performance or efficacy (percent organism exclusion) , species and life stage-specific FMS exclusion rates were applied to the annualized entrainment estimates based on data collected at Oconee during the 2016-2017 Study (HOR 2019) . The organisms that were excluded by application of the FMS-specific exclusion rates (i.e., converts [79 Federal Register 158, 48331]) represent the potential entrainment reduction benefit of each FMS size evaluated .
While not part of the existing configuration , this evaluation assumes that installation of FMS would also include installation of a fish-friendly organism return system .
Early life stage organisms are naturally delicate due to limited protective scaling or musculature development (particularly yolk-sac larvae) (EPRI 2010), therefore additional organism losses may occur due to trauma from impingement on FMS. During the development of the Rule, the review carried out by the U.S. Environmental Protection Agency (USEPA) of entrainment-reducing technologies found that "the survival of converts on FMS was very poor, and in some cases comparable to the extremely low survival of entrained organisms that are allowed to pass entirely through the facility" (USEPA 2014). Therefore , the survival of excluded organisms cannot be considered 100 percent and it is imperative that on-screen mortality be taken into consideration (USEPA 2014). Consequently, on-screen survival data obtained from existing literature (EPRI 2003, 2004, 2006 , 2013) were applied to the convert estimates to account for the organisms that would suffer mortality despite being excluded from the cooling water system .
The total number of convert mortalities was added to the annual entrainment losses estimated for the Oconee CWIS under each FMS size scenario (79 Federal Register 158, 48431) .
- Duke Energy 110-E-6
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §31 6(b) Compliance Submittal Appendix 10-E I..:)""
~ ~
- 5.3.1 Reductions in Annual Entrainment Loss Estimates Under existing CWIS design and operations (coarse mesh, no fish return , and maximum water withdrawal) , the estimated entrainment losses for 2016 were estimated at 36.8 million ichthyoplankton (Table 5-2) primarily from the Clupeidae family (36 .3 million) , which included Blueback Herring (33 .8 million) , Clupeid Group 10 (1 .5 million), and Shad Group 11 (998,471) .
Unidentified sunfish species, the only remaining taxa , contributed approximately 495 ,596 additional organisms (1 .3 percent) to the estimated annual entrainment.
Table 5-2. Annualized Entrainment Mortality by Screen Mesh Size Estimated for 2016 and 2017 under Maximum Water Withdrawals at Oconee Nuclear Station
--fl:MMWJ*l11l,IMMl*i,,i,,Mi*iti11i11il*ii11i,,i Screen Mesh Size Common Name 2016 Estimated Annual Entrainment Blueback Herring Egg FF 33 ,781 ,252 33,781 ,252 5,846 ,755 (Alosa aestivalis)
Clupeid Group (Alosa aestivalisl A. pseudoharengusl Larvae FF 1,486,787 1,486,787 1,486,787 1,486,787 1,486,787 Dorosoma cepedianuml D. petenense)
Shad Group (Dorosoma cepedianuml Larvae FF 988 ,471 988,471 988,471 988,471 988 ,471 D. petenense)
- Sunfish Species (Lepomis spp.)
Total Blueback Herring (Alosa aestivalis)
Larvae Egg RR FF 495 ,596 36,752,104 29,246,695 495,596 36,752,104 2017 Estimated Annual Entrainment 29,246,695 310,491 8,632,503 5,061 ,928 310,491 2,785,748 310,491 2,785,748 Clupeid Group (Alosa aestivalisl A. pseudoharengusl Larvae FF 5,252 ,501 5,252 ,501 5,028,119 5,028 ,119 5,028,119 Dorosoma cepedianuml D. petenense)
Shad Group (Dorosoma cepedianuml Egg FF 3,228,230 3,228,230 2,152,153 D. petenense)
Unidentified Fish 2 Larvae FF 353 ,226 353 ,226 303,245 303,245 303,245 Egg FF 353 ,917 353,917 Total 38,434,569 38,434,569 12,545,445 5,331,364 5,331,364
-- No organisms estimated 1Type represents the species' vulnerability to impingement (first letter: fragile (F) or robust (R)) and economic role (second letter: forage (F) or recreational (R)). Therefore , FF: fragile-forage ; RR: robust-recreational.
2 Unidentified Fish were processed as fragile-forage species based on best professional judgment.
10 Organisms could not be identified to species, but were possibly Blueback Herring (Alosa aestivalis) ,
Alewife (A pseudoharengus) , Gizzard Shad (Dorosoma cepedianum) or Threadfin Shad (D.
petenense) .
11 Organisms could not be identified to species, but were possibly Gizzard Shad or Threadfin Shad .
Duke Energy 110-E-7
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 10-E 1-)~ *~
- Annual entrainment losses for 2017 (38.4 million) were slightly higher than 2016 estimates, due in part to a greater number of clupeids collected . Only clupeids (98 .2 percent) and unidentified organisms (1 .8 percent) were collected in 2017 . No recreational species (such as sunfish or bass) were collected .
Physical exclusion based on organism morphometrics from the 2016-2017 Study (HOR 2019) estimated zero reductions in annual entrainment losses (total numbers lost) with the conversion to 2.0-mm FMS (Table 5-3, Figure 5-3) . The greatest incremental reduction in total numbers lost would be achieved with the conversion from 3-8-inch screen to 1.0-mm FMS , which would result in the exclusion of 67.4 to 76 .5 percent of organisms, based on 2016 and 201 7 entrainment data, respectively. Installing 0.75-mm FMS would provide an incremental percent reduction of 15.9 to 18.8 percent, for a total exclusion of 86.1 to 92.4 percent compared to existing conditions, based on 2016 and 2017 data. No additional percent reduction in entrainment losses (i. e., exclusion) would be attained with the smallest mesh size of 0.5 mm (Table 5-3) .
Table 5-3. Estimated Percent Reductions in Annual Entrainment Losses by FMS Size Screen Mesh Size Percent Reductions EtH@NWl*l11l11Mlh*l1il11i 1*ifi11i,,iiifui11i1,I Percent Reduction from Existing Condition 0.0 -76.5 -92.4 -92.4 2016 Incremental Percent Reduction 0.0 -76.5 -15.9 0.0 Percent Reduction from Existing Condition 0.0 -67.4 -86.1 -86.1 2017 Incremental Percent Reduction 0.0 -67.4 - 18.8 0.0
- *Existing condition 40,000,000
.....C 2016 2017
~
C 35,000 ,000
"§ 30,000 ,000
.....C w
0 25,000,000
(/)
0
_J 20,000,000
....(l)
(/)
15,000,000
.0 E
- J 10,000,000 z
.....n,0 5,000,000 I-0 3/8 in
- 2.0 mm 1.0 mm 0.75 mm 0 .5mm "Existing Condition Screen Mesh Size Figure 5-3. 2016-20.17 Estimated Annual Entrainment Losses under Existing Condition (3/8-inch mesh) and Alternative Fine-mesh Screen Sizes Duke Energy I10-E-8
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 10-E rL "'""'
.I~
- The efficacy of the FMS would be limited by the morphometrics of organisms collected during the Study, which indicated entrainment at Oconee is dominated by smaller organisms . None of the organisms collected during the Study had a larval head depth or egg width greater than 2.0 mm , therefore no organisms are estimated to be excluded at this mesh size. All of the organisms excluded at 1.0-mm FMS size were eggs (1 .1-mm width) , with the exception of a single unidentified sunfish post yolk-sac larvae with a head depth of 1.5 mm. The remaining organisms excluded at 0.75-mm were eggs with egg widths of 1.0 mm. None of the other larvae collected (shads and clupeids) would be excluded at any FMS size (all had a head depth of 0.3 mm or smaller) .
The ichthyoplankton community composition near the CWIS also limits the efficacy of FMS at th is facility due to post-impingement survival rates. Almost 99 percent of estimated organism losses in 2016 and 100 percent of those estimated fo r 2017 are fragile species 12 (Table 5-2) .
Therefore, these organisms experience high on-screen mortality, limiting the benefit of FMS.
5.3.2 Reductions in Production Foregone and Equivalent Adults In addition to determining the potential reduction in entrainment losses from each FMS size, this evaluation also included an assessment of FMS exclusion impacts to the fishery through the Production Foregone (PF) and Equivalent Adults (EA) models. The PF model estimates the prey/non-game (i.e., "forage") biomass that is removed from the ecosystem due to entrainment losses. The EA model estimates the harvestable species (i.e ., "recreational") that wou ld have survived to the age of equivalence (species and age-specific fishing vulnerability) but are now unavailable to the fishery due to entrainment. These models together demonstrate the impact of entrainment losses to the fishery . A comparative analysis of the model results was performed to determine the FMS size that would provide optimal benefits to the fishery through the reduction of entrainment losses at the Oconee CWIS .
The PF losses estimated for 2016 and 2017 varied slightly between years (Table 5-4) , primarily due to a greater number of forage species estimated to be entrained in 2017 versus 2016 (Table 5-2). The maximum reduction in PF that could be achieved with installation of FMS (based on data collected during the two-year Study) would be up to 70 percent, or up to 1,759 pounds (lbs) . The greatest incremental reduction in PF would be attained with 1.0-mm FMS (a reduction of 41 .8-59.1 percent) .
Recreational species were collected in only 2016 , therefore no EA losses are estimated for 2017. Recreational species consist of just over one percent of the total estimated losses for 2016 and consist of unidentified sunfish (Table 5-2, Table 5-4) . An equivalent of 40 adults would be lost to entrainment with the current configuration (3/8-inch mesh) or 2.0-mm FMS , but would be reduced to 25 adults (5 lbs of biomass) at any screen mesh size of 1.0-mm or smaller.
12 Threadfin Shad , however not specifically stated in the Rule's "non-exclusive" list (§125.92(m}) , are considered a fragile species for the purposes of this analysis .
Duke Energy I 10-E-9
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 10-E l.:)'"'
~ ~
- Table 5-4. Estimated Production Foregone and Equivalent Adult Losses by Screen Mesh Extrapolation Model Production Foregone 1!111111:MM lbs Size for 2016 and 2017 Estimated Losses for 2016 2,504 2,504 Mi*i,,i,,Ml*i&ittinlli&i,,i,,Y 1,049 745 745 No. 40 40 25 25 25 Equivalent Adults lbs 8 8 5 5 5 Estimated Losses for 2017 Production Foregone lbs 3,358 3,358 1,954 1,605 1,605 No.
Equivalent Adults lbs
- Existing condition W ith consideration of the U.S . Fish and Wildlife's Information , Planning , and Consultation database (IPAC) , the South Carolina Department of Natural Resources (SCDNR), and the existing aquatic habitat near the CWIS , no threatened or endangered species are expected in the vicinity of Oconee. No commercially important shellfish occur in Lake Keowee and none were collected at Oconee during the Study.
The organisms identified in the Shad or Clupeid groups may consist of Blueback Herring and/or Threadfin Shad , as both were collected during the 2016-2017 Study (HOR 2019). Both of these species are nonindigenous to Lake Keowee as Threadfin Shad were stocked into the lake, while Blueback Herring resulted from an inadvertent release. Regardless of how they were introduced to the system , both species provide an important forage base for sportfish predators in Lake Keowee , such as catfish and black basses .
6 Conclusions This FMS evaluation demonstrates that, based on organisms collected during the Study, no early life stage fish would be excluded with 2.0-mm FMS , and that the greatest incremental reduction in entra inment losses would occur with 1.0-mm FMS. The maximum number of organisms excluded would be achieved with either 0.75-mm or 0.5-mm FMS . Similarly, results of the PF and EA models demonstrate the greatest incremental reduction in lost forage biomass or EA would also occur with the conversion to 1.0-mm FMS . However, a much higher proportion of forage species were collected compared to recreational species in both years (over 99 percent in 2016 and 100 percent in 2017).
The forage species collected at Oconee during both years of the Study consisted solely of clupeids , which are fragile species (as defined by the Rule) that exhibit less than 30 percent on-screen survival. While the Rule assumes "100 percent of entrained organisms suffer mortality" (79 Federal Register 158, 48318) , recent through-plant entrainment survival analyses demonstrate some survival may occur depending on site-specific design , operations , and the Duke Energy I 10-E-10
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 10-E rL "\~
.I~
- species and life stages entrained at the facility (EPRI 2018). Therefore, it may be possible to achieve greater survival at Oconee without the installation of FMS.
Each of the available FMS sizes would result in TSV values greater than 0.5 feet per second (fps), which is the Rule-defined TSV threshold for establishing BTA for impingement compliance (79 Federal Register 158, 48321 ). Furthermore, the TSV for both 1.0-mm and 0. 75-mm FMS (i.e., mesh sizes with substantive reductions in entrainment) is close to or above 2.0 fps assuming 15 percent clogging. The TSV of the recommended FMS size should also be considered as it could directly impact the FMS exclusion efficacy due to on-screen impingement survival rates for organisms converted from entrainment to impingement.
Several options are available to reduce TSV values with the installation of FMS, however not all options may provide a net-positive benefit. For example, to ensure TSV values remain at or below 1.5 fps, the CWIS would need to be expanded to provide greater surface area coverage for intake flows; withdrawals may be reduced; and/or alternative technologies, such as dual-flow screens, may be required. Each alternative comes with a cost, rendering some options impractical due to high cost-benefit ratios.
This analysis considers the potential reduction in entrainment losses that would be achievable by installation of FMS at the CWIS; however, entrainment rates at Oconee are already low due to the effectiveness of the curtain wall located at the inlet of the intake canal. A separate study was completed at Oconee in 2017 to evaluate the effect of the existing curtain wall on ichthyoplankton densities on the lake side vs. the intake side of the curtain wall (HOR 2018) .
Results from that study demonstrated a reduction of up to 89.7 percent in ichthyoplankton density from the lake side of the curtain wall to the intake side of the curtain wall. Additionally, ichthyoplankton densities on the intake side of the curtain wall were comparable to those observed in the 2016-2017 Study, suggesting that the reductions in ichthyoplankton density provided by the curtain wall extend to the CWIS (HOR 2019). Therefore, the curtain wall acts as an effective entrainment-reducing technology by limiting the passage of organisms under the curtain wall into the intake canal where they may become susceptible to entrainment.
With the consideration of estimated annual entrainment rates and reduced on-screen survival of converts, HOR recommends the 1.0-mm FMS for developing the FMS compliance technology scenario for inclusion in the biological model, which will be used to support the cost-benefit evaluation of potential Rule compliance options at Oconee. Although an evaluation of FMS is required under §122.21(r)(10) Comprehensive Technical Feasibility and Cost Evaluation Study, the conversion to FMS as an entrainment-reducing technology at Oconee would provide limited entrainment-reducing benefit (i.e., exclusion of organisms) because ichthyoplankton densities are already low at the Oconee CWIS. When considering the increase in TSV resulting from FMS, the limited entrainment-reducing benefit may be further reduced due to on-screen mortality of sensitive and fragile early life stage organisms .
- Duke Energy I 10-E-11
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal 1
Appendix 10-E rL "'\~
.I~
- 7 References Bilfinger. Undated. Personal communication.
Electric Power Research Institute (EPRI). 2003. Evaluating the Effects of Power Plant Operations on Aquatic Communities. Final Report 1007821. Palo Alto, CA.
_ _ . 2004. Chapter 1. Traveling Water Screens. 1011546. Palo Alto, CA.
_ _ . 2006. Laboratory Evaluation of Modified Ristroph Traveling Screens for Protecting Fish at Cooling Water Intakes. Final Report 1013238. Palo Alto, CA.
_ _ . 2010. Laboratory Evaluation of Fine-Mesh traveling Water Screens. Final Report 1019027. Palo Alto, CA.
_ _ . 2013. Engineering and Biological Assessment of Fine Mesh Fish Protection-Modified Traveling Water Screens. Technical Update 3002001104. Palo Alto, CA.
_ _ . 2014. Fish Protection Technical Brief: Estimating the Physical Exclusion of Fine-Mesh Screens. Technical Update 3002003432.
_ _ . 2018. Entrainment Survival Transferability: Application of Prior Studies under the 2014 316(b) Rule. Final Report 3002013685. Palo Alto, CA.,
Evoqua. 2016. Intake Traveling Water Screens. Accessed December 2016. [URL]:
http://www.evoqua.com/en/brands/intake-screens/Pages/Traveling-Water-Screens.aspx.
HOR Engineering, Inc. (HOR). 2018. 2017 Curtain Wall Entrainment Reduction Performance Study Report, Oconee Nuclear Station NPDES Permit No. SC0000515. Charlotte, NC.
_ _ . 2019. Entrainment Characterization Study Report, Oconee Nuclear Station NPDES
. Permit No. SC0000515. Charlotte, NC.
Ovivo. 2014. Specification for a Fish Handling Thru Flow Band Screen, Bl14-089R0.
U.S. Environmental Protection Agency. 2014. Technical Development Document for the Final Section of 316(b) Existing Facilities Rule. EPA-821-R-14-002. Washington, DC .
- Duke Energy I 10-E-12
Appendix 10-F Engineering Estimates of Through-screen Velocity for Hypothetical Fine-mesh Screens at Oconee Nuclear
- Station
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 512.7'2.020 Engineering Estimates of Through-screen Velocity for Hypothetical Fine-mesh Screens at Oconee Nuclear Station Originator: Spencer Nush, EIT 7/10/2019 Reviewer: Scott Loughery, PE 7/11/2019 Approver: Scott Loughery, PE 4/10/2020 Revision No. Revised bv: Aooroved bv: Descriolion 0
Calculation Summary:
One-oump Ooeration fos 3.64 3.64 3.64 Two-pump Operation fps 3.44 3.44 3.44 Three-oump Ooeration fps 3.00 3.00 3.00 Four-pump Operation fps 2.62 2.62 2.62
- lof4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 5/27/2020 Engineering Estimates of Through-screen Velocity for Hypothetical Fine-mesh Screens at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Calculate the design through-screen velocity at the Oconee Nuclear Station cooling water intake structure after a hypothetical 1-mm fine-mesh screen retrofit.
Calculation Objectives:
- 1. Identify the screen physical parameters and design intake flow rate.
- 2. Estimate the proportion of fine-mesh screen open area.
- 3. Calculate the through-screen velocities for the design intake flow.
Calculation Methodology:
Formula 1 v** = QI (WD*EOA *rw* K)
Units: fps where:
Veff= effective through-screen velocity (fps)
Q = flow rate (gpm)
WO = screen area available to flow (ft)
EOA = proportion of effective open area TW = nominal screen basket width (ft)
K = 396 for through-flow screen Formula 2 OA= (W* L)/((W+ DJ *(L+ d))
Units: unitless where:
OA = proportion of screen open area to total screen area d = horizontal wire diameter (inch)
D = vertical wire diameter Onch)
W = width of mesh opening (inch)
L = vertical length of mesh opening (inch)
Formula 3 EOA=PC*OA Units: percent where:
PC= screen percent clean(%)
- 2 of4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 5!27/2020 Engineering Estimates of Through-screen Velocity for Hypothetical Fine-mesh Screens at Oconee Nuclear Station Design Inputs:
,',~.i+L,,;,Ct:\;:[,;lt~~:Panfmet,frs "arid Varia~leS ,i~:: ',:t<<' ,,,:,,* ,1,:*<,::,_ cUrilf1,'f!f,;!<c *it Wilif2~e<': i:1!:'!~,:11Uftit3:,~t-:,::; !')L;~, :unitsf ; ~ !fclB:!f~f~hij/Not~'} ,
Waterbody Information Plant Datum! MSL MSLI MSLI I [1]
Bottom of Overhang Elevation 78LO 78LOI 1am fl I [4J, [6], Assumption 1 Traveling Water Screen Information Elevation at Bottom of CWIS 76m 761.0 76LO ft [4]
Number of Screens 8 8 8 [4]
Screen Basket Width 9.5 9,5 9.5 ft [2]
Mesh Size (L) 0.039 0.039 0.039 inch [2]
Mesh Size (W) 0.039 0.039 0.039 inch [2]
Vertical Wire Diameter 0.015 0.015 0.015 inch [3]
Horizontal Wire Diameter 0.015 0.015 0.015 inch [3]
Opening of Support Backing (L'"""') 1.0 1.0 1.0 inch [2]
Opening of Support Backing (W'"""') 1.0 1.0 1.0 inch [2]
Vertical Wire Diameter for Support Backing (Doac*a,) 0.08 0.08 0.08 inch [2]
Horizontal Wire Diameter for Support Backing (d'"""') 0.08 0,08 0,08 inch [2]
Screen Percent Cloaged 0% 0% 0% Assumption 5 Cooling Water Intake Structure Pump Information Number of Condenser Cooling Water Pumps 4 4 4 [1]
Condenser Cooling Water Pumps Name Plate Rating 246,000 246,000 246,000 gpm [5], Assumption 6 Design Intake Flow per Unit 708,000 708,000 708,000 gpm [5], Assumption 6 Flow Based on One-pump Operation 246,000 246,000 246,000 gpm [5], Assumption 7 Screens Utilized with One-pump Operation 2 2 2 {5], Assumption 7 Flow Based on Two-pump Operation 465,000 465,000 465,000 gpm [5], Assumption 7 Screens Utilized based on Two-pump Operation 4 4 4 [5], Assumption 7 Flow Based on Three-pump Operation 609,000 609,000 609,000 gpm [5], Assumption 7 Screens Utilized based on Three-pump Operation 6 6 6 (5], Assumption 7 Flow Based on Four-pump Operation 708,000 708,000 708,000 gpm [5], Assumption 7 Screens Utilized based on Four-pump Operation 8 8 8 (5], Assumption 7 Assumptions:
- 1. Screen area available to flow is impacted by the presence of the overhang at the CWIS. Cooling water is withdrawn from the bottom of the overhang elevation (781.0 ft msl) to the bottom of the CWIS elevation (761.0 ft msl).
- 2. The cooling water intake structure has not been modified since dates of references used .
- 3. All screens function similarly.
- 4. The constant in Formula 1 includes units conversion (gpm to cfs) and other screen factors.
- 5. For the purposes of these calculations, the screens are assumed to be free of debris and 100% clean. The through-screen velocity would increase with the presence of debris.
- 6. While the individual condenser cooling water pump design capacity is 246,000 gpm, when multiple pumps are operating for a given unit, a piping restriction limits the cooling system capacity to 708,000 gpm per unit. Due to the piping restriction, the total water withdrawal through the cooling water intake structure (all three units combined) is limited to 2,124,000 gpm (3,059 MGD) [5].
- 7. Due to a piping restriction, the condenser cooling water pump flow per unit changes based on number of pumps operating and number of screens utilized. It is assumed that flow is distributed equally among utilized screens.
References:
[1] Electric Power Research Institute (EPRI). 2008. Information Submitted for Best Professional Judgment §316(b) Decision-making for Duke Energy's Oconee Nuclear Station - Final Report. October 2008.
[2] Evoqua Water Technologies. 2019. Evoqua Water Technologies Budget Proposal File No. 45062.
[3] Lide, D.R., CRC Handbook of Chemistry and Physics (Ed. 72), Chemical Rubber Publishing Co., USA, 1991-1992.
[4] Duke Power Company. 2000. Oconee Nuclear Station - Intake Structure General Arrangement Plans and Sections. Drawing No. 0-339 - Rev 7. 16 Nov 2000.
[5] Duke Energy. 2019. Oconee Nuclear Station Actual Intake Flow Rates: 7/1/2014 - 11/13/2018. Received: 3 Jul 2019.
(6] Duke Energy. 2020. Oconee Nuclear Station CWIS Photos - Overhang and Fixed Screen Slot. Received 3 Apr 2020 .
- 3 of4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date-. 5127/2020 Engineering Estimates of Through-screen Velocity for Hypothetical Fine-mesh Screens at Oconee Nuclear Station Calculations:
- 1. Screen Physical Parameters and Design Intake Flow Rate Given: 'ill!i!~l1Nar1ii61esw,a;ii! ~Oiilt12~*s ~Unil'3i,a; -~Uiiits'li&iiiim1 Otota1= 708,000 708,000 708,000 gpm Oona= 123,000 123,000 123,000 gpm per screen a..,= 116,250 116,250 116,250 gpm per screen Othree= 101,500 101,500 101,500 gpm per screen a,,,,= 88,500 88,500 88,500 gpm per screen D= 0.Q15 0,015 0.015 inch d= 0.015 0.015 0.015 inch L= 0.039 0.039 0.039 inch W= 0.039 0.039 0.039 inch WDoverhancJ= 20.0 20,0 20.0 ft K= 396 396 396 TW= 9.5 9.5 9.5 ft PC= 100% 100% 100%
Lbackina= 1.0 1.0 1.0 inch Wbackinn= 1.0 1.0 1.0 inch Dbackln<1= 0.08 0,08 0,08 inch dbackln"= 0.08 0.08 0.08 inch
- 2. Proportion of Effective Open Screen Area to Total Screen Area Formulae Used:
Formulae 2 and 3 Given:
Screen parameters as above Calculate: .,i.'Unlt'1:ftiii/A! ifJs-Unlt!2ftt 4 " " *mnlt3-*!
Qm Qm Qm OA1 = (W* L)/((W+ D) *(L+ d)) =
OA2 = (Wbacklng
- Lbacking) / ((Wbacklng + Dbacking) * (Lbacklng + dbacking)) = 45% 45% 45%
EOA= PC *OA1
- OA2 =
- 3. Design Through-screen Velocity Formula Used:
Formula 1 Given:
Screen parameters as above and calculated screen open area proportion Calculate: ilt:ifJEstimateairtirotigh"\s.i:f!\eii',Viiloclty~'!fii;!f!Urilt,1~ f,f,+s,,"Uiiif2~ J*Unlf3i!iim1 ;J!j/Si!Onlfs,a;,
Vo1,= QI (WD
- EOA *TW* K) = One-pump Operation 3.64 3.64 3.64 fps Two-pump Operation 3.44 3.44 3.44 fps Three-pump Operation 3.00 3.00 3.00 fps Four-pump Operation 2.62 2.62 2.62 fps
- 4of4
Appendix 10-G Engineering Estimates of Through-screen Velocity for a Hypothetical Installation of Fine-mesh Screens within a New CWIS at Oconee Nuclear Station
This page intentionally left blank.
Duke Energy Carolinas, LLC f Oconee Nuclear Station Revision:
Issue Date: 5/27/2020 Engineering Estimates of Through-screen Velocity for a Hypothetical Installation of Fine-mesh Screens in a New CWIS at Oconee Nuclear Station Originator: Spencer Nush, EIT 11/21/2019 Reviewer: Shane Galloway, EIT 11/27/2019 Approver. Scott Loughery, PE 4/10/2020 Revision No. Revised bv: Accroved bv: Descriction 0 - -
Calculation Summary:
0.95 0.95 0.71 0.71 1.24 1.24 1.24 0.92 0.92 0.92 1.44 1.44 1.44 1.07 1.07 1.07
- lof4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 5127/2020 Engineering Estimates of Through-screen Velocity for a Hypothetical Installation of Fine-mesh Screens in a New CWIS at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Calculate the design through-screen velocity at Oconee Nuclear Station after a hypothetical installation of 1-mm fine-mesh screens in a new CWIS.
Calculation Objectives:
- 1. Identify the screen physical parameters and design intake flow rate.
- 2. Estimate the proportion of fine-mesh screen open area.
- 3. Calculate the through-screen velocities for the design intake flow at maximum drawdown and full pond elevar,ons.
Calculation Methodology:
Formula 1 V,tt= Q /(WD" EOA" TW" K)
Units: fps where:
Ve'lf= Effective through-screen velocity (fps)
Q = Flow rate (gpm)
WD = Screen area *available to flow (ft)
EOA = Proportion of effective open area TW = Nominal screen basket width (ft)
K = 396 for through-flow screen Formula 2 OA= (W" L) / ((W+ D) * (L + d))
Units: unitless where:
OA = Proportion of screen open area to total screen area d= Horizontal 'Mire diameter (inch)
D= Vertical \/I/ire diameter (inch)
W= Width of mesh opening 0nch)
L= Vertical length of mesh opening (inch)
Formula 3 EOA= PC" OA Units: percent where:
PC= Screen percent clean(%}
- 2of4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Data: 5/27/2020 Engineering Estimates of Through-screen Velocity for a Hypothetical Installation of Fine-mesh Screens in a New CWIS at Oconee Nuclear Station Design Inputs:
~llar.iiileters:and:Vaiialiles")f~~ -:Unit~1fi!liii g,i!Uiiit'2~!~Uiilt*3~ 111!!1Uiiltsli111ml *R*Je7e~ce/!<~,
Waterbody lnfonnation Plant Datum I MSL MSLI MSLI [1]
Maximum Drawdown Elevation\ 790.0 790.0\ 790.0\ ft 16]
Full Pond Elevation! 800.0 800.0I 800.01 ft 14]
Traveling Water Screen lnfonnatlon Elevation at Bottom of CWIS 761.0 761.0 761.0 ft [41 Number of Screens 10 10 10 [4]
Screen Basket Width 9.5 9.5 9.5 ft [21 Mesh Size (L 0.039 0.039 0.039 inch [2]
Mesh Size (Wl 0.039 0.039 0.039 inch [2)
Vertical Wire Diameter O.D15 0.D15 0.D15 inch [31 Horizontal Wire Diameter O.D15 0.015 O.Q15 inch [31 Opening of Support Backing (L'"""') 1.0 1.0 1.0 inch [2]
Opening of Support Backing (W"'""') 1.0 1.0 1.0 [2]
Vertical Wire Diameter for Support Backing (D'"""') 0.08 0.08 0.08 inch [21 Horizontal Wire Diameter for Support Backing (d"'""') O.Q8 0.08 0.08 [21 Screen Percent Clogged 0% 0% 0% Assumption 5 Cooling Water Intake. Structure Pumc lnfonnation .. ,:
Number of Condenser Cooling Water Pumps 4 4 4 [1]
Condenser Cooling Water Pumps Name Plate Rating 246.000 246,000 246,000 gpm IS], Assumption 6 Design Intake Flow per Unit 708,000 708,000 708,000 gpm [SJ, Assumption 6 Flow Based on One-pumc Operation 246,000 246,000 246,000 gpm [51. Assumption 7 Screens Utilized with One-pump Operation 10 10 10 [5], Assumption 7 Flow Based on Two-pump Operation 465,000 465,000 465,000 gpm [SJ, Assumption 7 Screens Utilized based on Two-pump Operation 10 10 10 [5], Assumption 7 Flow Based on Three-pump Operation 609,000 609,000 609,000 gpm [SJ, Assumption 7 Screens Utilized based on Three-pump Operation 10 10 10 (5], Assumption 7 Flow Based on Four-pump Operation 708,000 708,000 708,000 gpm [5], Assumption 7 Screens Utilized based on Four-pump Operation 10 10 10 [5], Assumption 7 Assumptions:
- 1. Water elevation inside screenhouse Is same as in the source waterbody immediate[y outside the bar racks.
- 2. The cooling water intake structure has not been modified since dates of references used .
- 3. All screens function simila~y.
- 4. The constant in Formula 1 includes units conversion (gpm to cfs) and other screen factors.
- 5. For the purposes of these calculations, the screens are assumed to be free of debris and 100% clean. The through-screen velocity would increase with the presence of debris,
- 6. While the individual condenser cooling water pump design capacity is 246,000 gpm, when multiple pumps are operating for a given unit, a piping restriction limits the cooling system capacity to 708,000 gpm per unit. Due to the piping restriction, the total water withdrawal through the cooling water intake structure (all three units combined) is limited to 2,124,000 gpm (3,059 MGD) [5].
- 7. Due to a piping restriction, the condenser cooling water pump *now per unit changes based on number of pumps operating. It is assumed that fiow is distributed equally among screens.
- 8. It is assumed that water flow is equal through all screens, since the new intake structure has hydraulically connected intake bays.
References:
[1] Electric Power Research Institute (EPRI). 2008. Information Submitted for Best Professional Judgment §316(b) Decision-making for Duke Energy's Oconee Nuclear Station - Final Report. October 2008.
[2] Evoqua Water Technologies, 2019. Evoqua Water Technologies Budget Proposal File No, 45062.
[3] Lide, D.R., CRC Handbook of Chemistry and Physics (Ed. 72), Chemical Rubber Publishing Co., USA, 1991-1992.
[4] Duke Power Company, 2000. Oconee Nuclear Station - Intake Structure General Arrangement Plans and Sections. Drawing No. 0-339 - Rev 7. 16 Nov 2000.
[5] Duke Energy. 2019. Oconee Nuclear Station Actual Intake Flow Rates: 7/1/2014 - 11/13/2018. Received: 3 Jul 2019.
[6] United States Army Corps of Engineers (USAGE). 2014. Final Environmental Assessment- New Operating Agreement between U.S. Army Corps of Engineers, Southeastern Power Administration, and Duke Energy Carolinas, LLC. October 2014 .
- 3of4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 5/2712020 Engineering Estimates of Through-screen Velocity for a Hypothetical Installation of Fine-mesh Screens in a New CWIS at Oconee Nuclear Station Calculations:
- 1. Screen Physical Parameters and Design Intake Flow Rate Given:
Otota1= 708,ooo 708,000 708,000 gpm O,oo= 24,600 24,600 24,600 gpm per screen Q""'= 46,500 46,500 46,500 gpm per screen Ou,.,= 60,900 60,900 60,900 gpm per screen o,.,,= 70,800 70,800 70,800 gpm per screen D= 0.015 0.015 0. 15 inch d= 0.015 0. 15 0.015 inch L= 0.039 0.039 0,039 inch W= 0.039 0.039 0.039 inch WDmaxdrmwown= 29.0 29.0 29.0 fl WDtunoond= 39.0 39,0 39,0 ft K= 396 396 396 TW= 9.5 9.5 9.5 fl PC= 100% 100% 100%
Lbackina= 1.0 1.0 1.0 inch WbackiM= 1.0 1.0 1.0 inch 0.08 0,08 0.08 inch 0.08 0.08 0,08 inch
- 2. Proportion of Effective Open Screen Area to Total Screen Area Formulae Used:
Formulae 2 and 3 Given:
Screen parameters as above Calculate: l<,';i , llnit-V1;<*: 1,:;1;10unlt 2 ~11)1 ,i'.;4 Unit131JB:GA Qm Qm Qm OA1 = (W* L)/((W+ D) *(L+ d)) = Qffi Qffi Qffi OA2 = (Wbacking
- Lbacking) / ((Wbacklng + Dbat:king) * (Lbacklng + dbacklng)) .= 45% 45% 45%
EOA=Pc*oA1*0A2=
- 3. Design Through-screen Velocity Formula Used:
Formula 1 Given:
Screen parameters as above and calculated screen open area proportion Calculate:
v.ff= QI (WD. EOA *Tw* K) =
- 4ol4
Appendix 10-H Capital Cost Estimate for a Hypothetical Fine-mesh Screen Retrofit at Oconee Nuclear Station
This page intentionally left blank.
Oconee Nuclear Station 1.0-mm FMS Retrofit - Capital Cost Estimate DATE:
6/11/2020 REVISION:
5 1515 Market St Suite 2020
- Philadelphia, PA 19147 * (215) 845-6700 Paae Title Block lnout:
CLIENT I PROJECT: Duke Enerav Carolinas, LLC - Oconee Nuclear Station ACTIVITY: 1.0-mm FMS Retrofit - Caoital Cost Estimate TAKE OFF BY: SL COSTING BY: SUSN CHECKED BY: SUSNITZ
- 6/11/2020 Oconee Nuclear Station Basis of Estimate
System Description
This document provides an AACE Class 4 capital cost estimate for the installation of 1.0-mm fine-mesh modified-Ristroph traveling water screens in the existing cooling water intake structure to reduce impingement mortality and entrainment at Oconee Nuclear Station. The installation of new screenwash pumps and an aquatic organism return system to Lake Keowee are also included.
Assumptions 1 Union Labor drawn from the greater Greenville, SC metropolitan area. The national average cost differential would be approximately 25% higher for union verses open shop labor.
2 Work week will be Five (5) Eight (8) hour days.
3 Craft labor rates obtained from R.S. Means "Labor Rates for the Construction Industry, 2019 edition".
4 Quantities provided by HDR Engineering.
5 Costs are presented in 2019 dollars.
6 Material and unit installation rates obtained from R.S. Means Cost Data, 2019, Richardson Cost Data Online, and HDR Project historical data.
7 Native soils are adequate for structural backfill.
8 Design Engineering is calculated as 10 percent of the Construction Direct Costs.
9 Project Management (Engineering) is calculated as 10 percent of the Design Engineering Costs.
Exclusions 1 Escalation 2 Sales Tax 3 Salvage value for any demolished materials.
- *6/11/2020 2019 Dollars Oconee Nuclear Station 1.0-mm FMS Retrofit Man-Hours Mat'I/Equip Labor Total Cost Construction Direct Costs Demolition 4,800 $ 1,200,000 $ 190,000 $ 1,390,000 Civil/Sitework 14,000 $ 6,900,000 $ 555,000 $ 7,455,000 Mechanical 15,600 $ 20,280,000 $ 592,000 $ 20,872,000 Structural 1,920 $ 1,450,000 $ 76,000 $ 1,526,000 Electrical
"'"'-"'="tt~"' - , ..
and I&C l'.+.;';>:'"8-..~ . = 7 ' . '
- J * * , N *=v n,,,_.,,,,,_~W~" .'.=-.:.:.:,0-,1,~ * ~ <<-t<*C. = n , *... ?*NJ,~§? .l = rn~, * .!I:, 1'2§/JOO ~$**A--tt~ X. ,~,,,~?r 00.Q Ml,,,., ....~1 7 5 , o_o,2_
Subtotal Construction Direct Costs 38,205 $ 33,938,000 $ 1,480,000 $ 35,418,000 Construction Indirect Costs Contractor Site Supervision 0 $ - $ 507,000 $ 507,000 General Conditions 21,779 $ 2,167,000 $ 864,000 $ 3,031,000 General
=w~r,<;.,.,'W~'°""" -*
Admin & Profit
,_s,,,,,,,,,sli4 'CZ .,-,,s..w,.s,:;,
15%
?.:.:1/4~SS<oS<,, ,t,,,*,,.s,,,.i,,,.,_;,o,m-<<1' I,: , -* *""*"*=-~* **-*-- =-= ,_..., .* .,~ .,,,==*"* *r**,,,. $_,..,,..~**** ~~!cS':!},,9.00 Subtotal Construction Indirects 21,779 $ 2,167,000 $ 1,371,000 $ 9,381,000 Total Construction Cost 59,984 $ 36,105,000 $ 2,851,000 $ 44,799,000 Design Engineering (10% Const Dir) $ 3,542,000 Engineering PM (10% Eng Cost) $ 354,000 Escalation (Mat'I 0%, Labor 0%) $ - $ - $ -
Owners Cost Labor $ 913,000 Labor Loadings $ 717,000 Overhead $ 3,125,000 Contingency $ 12,174,000 1J'JTAL:.CAl?ITAL\C!JS}J :,., .:LC, ';,.::*;'.'; I' ':;. ,ft';;,/{ .'.',:,\::/'J's;}!,'."'; **;.:c/,c*;;,\J'.;c ', **.1.:i /i,:.* ',, :"::,:: ~:* ': :: ,:;r ' $i .).X"i::6~f6241000.,i'
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PRO.JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: General Conditions CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST onlJIPMENT .
NO DESCRIPTION DTY UNITS $/UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-~ TOTAL-$ $/UNIT TOTAL 1 Trainina/Safetv 1 Is $ - - 80 $ 39.65 80 3 172 - 3 172 3 172 2 Mobilization ron and Dffl 1 Is $ - ' - 150 39.65 150 5 948 - 5 948 5 948 3 Field Office Exoenses 169 wk $ 100 16 900 3 39.65 507 20 103 - 219 37 003 4 Temoorarv Facilities 169 wk ! 100 16 900 3 39.65 507 20 103 - 219 37 003 5 Temoorarv Utilities 169 wk 100 16 900 5 39.65 845 33 504 - 298 so 404 6 Suooort Craft & Site Services 169 wk - ! - 10 39.65 1 690 67 009 - 397 67 009 7 Construction Testina 4 wk 7 500 30 000 20 $ 39.65 80 $ 3 172 $ - 8 293 $ 33 172 8 Performance Testing 4 wk 7 500 30 000 20 $ 39.65 80 $ 3 172 $ - 8 293 $ 33 172 9 Permits 1 Is 200 000 200 000 0 $ 39.65 0 $ - $ - 200 000 $ 200 000 10 Construction Scaffoldina and Eauioment Rental 1 Is 330 000 330 000 0 $ 39.65 0 $ - $ - 330 000 330 000 11 Hydrostatic/ Static Head Testinn 4 wk 7 500 30 000 20 $ 39.65 80 $ 3 172 $ - 8 293 33 172 12 Freiaht 1 Is t 10 000 10 000 0 $ 39.65 0 $ - $ - 10 000 10 000 13 Small Tools 1 Is $ 10 000 10 000 0 39.65 0 - - 10 000 10 000 14 Consumables 1 Is $ 10 000 10 000 0 39.65 0 - - 10 000 10 000 15 Screen Ootimization 104 wk $ 1 500 ! 156 000 120 39.65 12 480 494 832 - 6 258 650 832 16 Bioloaical Samolina 110 ea $ 1 000 $ 110 000 48 39.65 5 280 209 352 - $ 2 903 $ 319 352 17 316(bl Studies 1 Is $ 1 200 000 $ 1 200 000 0 39.65 0 - - $ 1 200 000 $ 1 200 000 18 19 20 21 22 23 TOTAL $ 2 166 700 21 779 $ 863 537 $ - $ 3 030 237 I Sales Tax 0% $ - NA N/A $ -
I TOTAL $ 2 166 700 I 21 779 I $ 863 537 $ - $ - $ 3 030 237
- *
- 6/_11/2020 Oconee Nuclear Station CLIENT I PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BV: SL I ACTIVITY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BV: SLISN I DISCIPUNE: Civil/Site - Demolition CHECKED BV: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST FOllTPMFNT NO DESCRIPTION "TY UNITS "- I UNIT TOTAL-"- HRSIUNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ $/UNIT TOTAL 1 General Screenhouse Demolition 1 Is $ - $ 1200 . 39.65 1 200 $ 47 580 $ - $ 47 580 $ 47 580 2 Demolition of Miscellaneous Mechanical Items 3 Existino Screen Demolition and Removal 1
24 Is ea
$ 50 000
$ 1 200 000 1200 100 .
$ 39.65 39.65 1 200 2 400 47 580 95 160 47 580 53 965 47 580 1295160 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL . 1 200 000 4 800 $ 190 320 $ - $ 1 390 320 Sales Tax 0% $ - NA NIA $ -
TOTAL . 1 200 000 4 800 $ 190 320 $ - $ 1 390 320
- *
- 6/11/2020 Oconee Nuclear Station CUENT I PRO:JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I AC77VITY: l.O-mm FMS Retrofit - capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Civil/Site CHECKED BY: SL/SN/TZ MATERIAL/ EQUIPMENT I
LABOR --..-..
EQUIPMENT UNIT COST NO DESCRIPTION TY UNITS $ UNIT TOTAL-$ HRS/UNIT WAGE. TOTAL HRS OTAL-$ TOTAL-$ $lUNIT TOTAL 1 General Site Clearina 1 Is $ 500 ODO.DO $ 500 000 0.00 $ 39.65 0 $ - $ - $ 500 000 $ 500 000 2 Aouatic Oroanism Return Svstem Suooorts 4 ODO If $ 100.00 $ 400 000 3.00 $ 39.65 12 000 $ 475 800 $ - $ 219 $ 875 800 3 Install Aauatic Oraanism Return Svstem 4 ODO If $ 1 SOD.DO $ 6 000 000 a.so $ 39.65 2 000 $ 79 300 $ - $ 1 520 $ 6 079 300 4
5 6
7 8
9 10 11 12 13 14 15 16 17 TOTAL $ b,900,QQQ 14,000 $ ss,,100 $ - $ 7,4,5,100 Sales Tax 0% $ - NA NIA $ -
TOTAL $ 6,900,000 14,000 $ 555,100 $ - $ 7,45,,100
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I D:CSC:CPUNE: Structural CHECKED BY: SLISNITZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST eOUIPMeNT NO DESCR! PTION TY UNITS
- I UNIT TOTAL~ HRS1 UNIT WAGE TOTAL HRS TOTAL-,!; TOTAL-< <!UNIT TOTAL 1 Install Pre-Fabricated Metal Sheetino 24 ea $ 50 000.00 $ 1 200 000 80 $ 39.65 1 920 ;; 76 128 $ - ;; 53 172 <t 1 276 128 2 Miscellaneous Steel Allowance 1 Is ;; 250 000 ;; 250 000 0 ;; 39.65 0 $ - $ - $ 250 000 $ 250 ODO 3
4 5
6 7
8 9
10 11 12 13 14 15 16 17 18 19 20 TOTAL
- 1450 000 1 920 ;; 76 128 ;; - ;; 1 526 128 Sales Tax TOTAL 0% ;;
1 450 000 1 920 $
NA 76 128 $
NIA 1 526 128
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTill.lTY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Mechanical CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST Enl/lPMFNT NO DESCRIPTION TY UNITS 4: t UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ $/UNIT TOTAL 1 Install 1.0-mm Fine-mesh Modified-Ristronh Screens 24 ea $ 452 132.92 $ 10 851 190 400 $ 37.95 9 600 $ 364 320 $ - $ 467 313 $ 11 215 510 2 Install Screenwash Pumos (476 o m each) 24 ea $ 9 520.00 $ 228 480 120 $ 37.95 2 880 $ 109 296 $ - $ 14 074 $ 337 776 3 Install Screenwash Headers Branches Valves 24 ea $ 50 000.00 $ 1 200 000 80 $ 37.95 1 920 $ 72 864 $ $ 53 036 $ 1 272 864 4 Heavv Dutv Gantrv Crane and Rail Svstem 1 ea $ 8 000 000.00 $ 8 000 000 1 200 $ 37.95 1 200 $ 45 540 $ - $ 8 045 540 $ 8 045 540 5
6 7
8 9
10 11 12 13 TOTAL $ 20 279 670 15600 $ 592 020 $ - $ 20 871 690 Sales Tax 0% $ - NA N/A $ -
TOTAL < 20 279 670 15 600 $ 592 020 $ $ 20 871 690
- *
- 611112020 Oconee Nuclear Station CLIENT/ PRO:IECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.O-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Electrical and I&C CHECKED BY: SLISNITZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST
~nlJIPMENT NO DESCRIPTION TY UNITS $ I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-~ TOTAL-$ <tUNIT TOTAL 1 Install Wirino and Connections 5 000 If $ 10.00 so 000 0.08 $ 35.65 385 $ 13 725 $ - 13 63 725 2 Install Conduit 2 500 If $ 45.00 ' 112 500 0.05 $ 35.65 125 $ 4 456 $ - 47 116 956 3 Install Terminations 400 ea 6 2.00 800 0.60 $ 35.65 240 $ 8 556 - 23 9 356 4 Install MCC 3 ea 200 000.00 600 000 40.00 $ 35.65 120 $ 4 278 - 201 426 604 278 5 Install DCS 60 ea 5 000.00 300 000 10.00 $ 35.65 600 $ 21 390 - 5 357 321 390 6 Install Breakers 6 ea 5 000.00 30 000 1.00 $ 35.65 6 $ 214 - 5 036 30 214 7 Alarm Dialer 3 ea 5 000.00 15 000 3.00 $ 35.65 9 $ 321 - 5 107 15 321 8 Power Suoolv 1 Is '
$ 2 000 000.00 2 000 000 400.00 $ 35.65 400 $ 14 260 l - $ 2 014 260 2 014 260 9 Additional Electrical Eauinment - Allowance 1 Is $ 250 000.00 250 000 o.oo $ 35.65 0 $ - - $ 250 000 250 000 10 Additional Electrical Enoineerino - Allowance 1 Is $ 750 000.00 750 000 o.oo $ 35.65 0 $ - - $ 750 000 750 000 11 '
12 13 14 15 16 17 18 TOTAL $ 4 108 300 1 885 $ 67 200 0 $3 231 255 $ 4 175 500 Sales Tax 0% << - NA NIA ~ -
TOTAL $ 4 108 300 1 885 $ 67 200 $ - $ 4 175 500
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Engineering CHECKED BY: SLISNITZ I MATERIAL/ EQUIPMENT LABOR UNIT COST NO DESCRIPTION OTY UNITS <1; I UNIT TOTAL-<!; HRS/UNIT WAGE TOTAL HRS TOTAL-<!; <!;/UNIT TOTAL 1 Desian Enoineerina 1 Is $ - $ - o $ - a $ 3 541 874 $ 3 541 874 $ 3 541 874 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL <I; - a <I; 3 541 874 $ 3 541 874 I Sales Tax 0% N/A NA ISub Total $ - $ 3 541 874 $ 3 541 874 IContinoencv 0% $ - $ - $ -
I TOTAL $ - a $ 3 541 874 $ 3 541 874
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL ACTIVITY: 1.0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN DISCIPLINE: Construction Management CHECKED BY: SLISNITZ I MATERIAL/ EQUIPMENT LABOR UNIT COST NO DESCRIPTION OTY UNITS $ I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ $/UNIT TOTAL 1 Construction Manaaement 169 Weeks $ - $ - 0 $ 3 000 0 $ 507 000 $ 3 000 $ 507 000 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ 507 000 $ 507 000
!Sales Tax 0% N/A NA ITOTAL $ - 0 $ 507 000 $ 507 000
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: l. 0-mm FMS Retrofit - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Project Management CHECKED BY: SLISNITZ I LABOR UNIT COST NO DESCRIPTION nTY UNITS <;; I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-<t <;;/UNIT TOTAL 1 Project Manaqement 1 Is <!; - $ - 0 $ - 0 $ 354 187 $ 354 187 $ 354 187 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL g; - 0 g; 354 187 g; 354 187 Sales Tax 0% NIA NA Sub Total $ - $ 354 187 $ 354 187 Continaencv 0% $ - $ - $ -
TOTAL <!; - 0 <I; 354 187 $ 354 187
Appendix 10-1 Capital Cost Estimate for a Hypothetical Installation of Fine-mesh Screens in a New CWIS at Oconee
- Nuclear Station
This page intentionally left blank.
Oconee Nuclear Station 1.0-mm FMS in New Intake - Capital Cost Estimate DATE:
6/11/2020 REVISION:
3 1515 Market St Suite 2020
- Philadelphia , PA 19147 * (215) 845 - 6700 Paae Title Block Input:
CLJENT I PROJECT: Duke Enerav Carolinas, LLC - Oconee Nuclear Station ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate TAKE OFF BY: SL COSTING BY: SUSN CHECKED BY: SUSNITZ
- 6/11/2020 Oconee Nuclear Station Basis of Estimate
System Description
This document provides an AACE Class 4 capital cost estimate for the installation of 1.0-mm fine-mesh modified-Ristroph traveling water screens in a new expanded cooling water intake structure to reduce impingement mortality and entrainment at Oconee Nuclear Station. The installation of new screenwash pumps and an aquatic organism.
return system to Lake Keowee are also included.
Assumptions 1 Union Labor drawn from the greater Greenville, SC metropolitan area. The national average cost differential would be approximately 25% higher for union verses open shop labor.
2 Work week will be Five (5) Eight (8) hour days.
3 Cralt labor rates obtained from R.S. Means "Labor Rates for the Construction Industry, 2019 edition".
4 Quantities provided by HDR Engineering.
5 Costs are presented in 2019 dollars.
6 Material and unit installation rates obtained from R.S. Means Cost Data, 2019, Richardson Cost Data Online, and HDR Project historical data.
7 Native soils are adequate for structural backfill.
8 Design Engineering is calculated as 10 percent of the Construction Direct Costs.
9 Project Management (Engineering) is calculated as 10 percent of the Design Engineering Costs.
Exclusions 1 Escalation 2 Sales Tax 3 Salvage value for any demolished materials.
- 6/11/2020 2019 Dollars Oconee Nuclear Station 1.0-mm FMS in New Intake Man-Hours Mat'I/Equip Labor Total Cost Construction Direct Costs Demolition O $ - $ - $ -
Civil/Sitework 73,128 $ 23,917,000 $ 2,900,000 $ 26,817,000 Mechanical 19,200 $ 27,350,000 $ 729,000 $ 28,079,000 Structural 2,400 $ 2,500,000 $ 95,000 $ 2,595,000 Electrical and I&C 2,313 $ 5,281,000 $ 82,000 $ 5,363,000 subtotaf c;nstrucfioil-ri,rect"c~ts*- -- - gj;E40 -$ = - - s9,o4s;oo5~$ ~-- -3,so6~oob - f --- 62,ss4,foo -
Construction Indirect Costs Contractor Site Supervision O $ - $ 1,170,000 $ 1,170,000 General Conditions 28,276 $ 7,690,000 $ 1,121,000 $ 8,811,000 General Admin & Profit _ _ 15% __ $ 10,925,000 SubtoiaTc~i-tstructfori In~directs~--k- -v.~28~76~-$---= -7J3~fo;ooo*** $= ". *-2;§1,0'oo $ -- = 20~06,000 Total Construction Cost 125,316 $ 66,738,000 $ 6,097,000 $ 83,760,000 Design Engineering (10% Const Dir) $ 6,285,000 Engineering PM (10% Eng Cost) $ 629,000 Escalation (Mat'I 0%, Labor 0%) $ - $ - $ -
Owners Cost Labor $ 1,700,000 Labor Loadings $ 1,335,000 Overhead $ 5,819,000 Contingency $ 22,669,000 TOTAL CAPITAi COST -$ 122,.1~7,0.00
- *
- 6111/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: General Conditions CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST ECll lTPMENT NO DESCRIPTION nTY UNITS < I UNIT TOTAL-< HRS/UNIT WAGE TOTAL HRS TOTAL-< TOTAL-< <!UNIT TOTAL 1 Trainino/Safetv 156 wk $ - $ - 32 $ 39.65 4 992 $ 197 933 $ - 1 269 $ 197 933 2 Mobilization (On and Off) 4 wk 6 - 6 400 $ 39.65 1 600 $ 63 440 $ - 15 860 $ 63 440 3 Field Office Ex enses 156 wk 1 000 156 000 1 $ 39.65 156 $ 6 185 $ - 1 040 $ 162 185 4 Temoorarv Facilities 156 wk 1 500 234 000 1 $ 39.65 156 $ 6 185 $ - 1 540 $ 240 185 5 Temoorarv Utilities 156 wk 1 500 234 000 1 $ 39.65 156 $ 6 185 - 1 540 $ 240 185 6 Sunoort Craft & Site Services 156 wk - 20 $ 39.65 3 120 $ 123 708 - 793 $ 123 708 7 Construction Testinq 4 wk 100 000 400 000 28 $ . 39.65 112 $ 4 441 - 101 110 $ 404 441 8 Performance Testina 4 wk 100 000 400 000 28 $ 39.65 112 $ 4 441 - 101 110 $ 404 441 9 Permits 1 Is 500 000 500 000 0 $ 39.65 0 $ - - 500 000 $ 500 000 10 Construction Scaffoldinq and Eouioment Rental 156 wk $ 15 000 2 340 000 0 $ 39.65 0 $ - - 15 000 $ 2 340 000 11 Hvdrostatic / Static Head Testlna 4 wk $ 100 000 400 000 28 $ 39.65 112 $ 4 441 - 101 110 $ 404 441 12 Freiaht 156 wk $ 5 000 780 000 0 $ 39.65 0 $ - - 5 000 $ 780 000 13 Small Tools 156 wk $ 2 500 390 000 0 $ 39.65 0 $ - - 2 500 $ 390 000 14 Consumables 156 wk $ 2 500 $ 390 000 0 $ 39.65 0 $ - $ - $ 2 500 $ 390 000 15 Screen Ootimization 104 wk $ 1 500 $ 156 000 120 $ 39.65 12 480 $ 494 832 $ - $ 6 258 $ 650 832 16 Biolooical Samolino 110 ea $ 1 000 $ 110 000 48 $ 39.65 5 280 $ 209 352 $ - $ 2 903 $ 319 352 17 316(bl Studies 1 Is $ 1 200 000 $ 1 200 000 0 $ 39.65 0 $ - $ - $ 1 200 000 $ 1 200 000 18 19 20 21 22 23 TOTAL $ 7 690 000 28 276 $ 1 121 143 $ $ 8 811 143 Sales Tax 0% $ - NA NIA $ -
TOTAL $ 7 690 000 I 28 276 I $ 1 121 143 $ - $ - $ 8 811143
- 6/11/2020 Oconee Nuclear Station CUENT / PRO.JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Civil/Site - Demolition CHECKED BY: SLISNITZ I*
CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST J'nlllPMJ'NT NO OESCRIPTION OTY UNITS ;; I UNIT TOTAL-;; HRS/UNIT WAGE TOTAL HRS TOTAL-;; TOTAL-t t/UNIT TOTAL 1
2 3
4 5
6 7
8 9
10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ - $ - $ -
!Sales Tax 0% $ - NA NIA $ - -
ITOTAL ;; - 0 $ - $ - $ -
- *
- 6/11/2020 Oconee Nuclear Station CUENT I PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Civil/Site CHECKED BY: SL/SN/TZ I
~~"~"
MATERIAL/ EQUIPMENT LABOR EQUIPMENT UNIT COST NO DESCRIPTION l.>TY UNITS $/UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-$ TOTAL-$ $/UNIT TOTAL 1 General Site Clearina 1 Is $ 1 000 000.00 1 000 000 0.00 39.65 0 - 1 1 000 000 1 000 000 2 Aouatic Oraanism Return Svstem Suooorts 4 500 If $ 100.00 450 000 3.00 39.65 13 500 535 275 219 985 275 3 Install Aauatic Oraanism Return Svstem 4 500 If $ 1 500.00 6 750 000 0.50 39.65 2 250 89 213 - 1 520 6 839 213 4 Exoanded Intake Structure Foundation 9 333 CV 300.00 2 800 000 2.00 39.65 18 667 740 133 - 379 3 540 133 5 Exoanded Intake Structure Foundation Pilina 60 000 If 100.00 6 000 000 0.00 39.65 0 - ' 100 6 000 000 6 Install Excanded Intake Structure Concrete 11 556 CV 300.00 3 466 667 2.00 39.65 23 111 916 356 379 4 383 022 7 Install Excanded Intake Structure - Additional Miscellaneous 1 Is
' 1 500 000.00 1 500 000 0.00
' 39.65 0 - 1 500 000 1 500 000 a oewaterina 156 wk 12 500.00 1 950 000 100.00 39.65 15 600 618 540 - 16 465 2 568 540 9
10 11 12 13 14 15 16 17 18 19 20 21 TOTAL $ 23,916,667 73,128 $ 2,899,516 ~ $ 26,816,183 Sales Tax 0% $ NA N/A $
TOTAL $ 23,916,667 73,128 $ 2,899,516 $ - $ 26,816,183
- *
- 6/11/2020 Oconee Nuclear Station CUENT / PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1,O-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Structural CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR r:/"\11TnMENT UNIT COST NO DESCRIPTION nTY UNITS < I UNIT TOTAL-< HRS/UNIT WAGE TOTAi HRS TOTAL-t TOTAL-< </UNIT TOTAL 1 Install Pre-Fabricated Metal Sheeting 30 ea $ so 000.00 $ 1 500 000 80 $ 39.65 2 400 $ 95160 $ - $ 53 172 $ 1 595 160 2 Miscellaneous Steel Allowance 1 Is $ 1 000 000 $ 1 000 000 0 $ 39.65 0 $ - $ - $ 1 000 000 $ 1 000 000 3
4 5
6 7
8 9
10 11 12 13 14 15 16 17 18 19 20 TOTAL $ 2 500 000 2 400 $ 95 160 $ - $ 2 595 160 Sales Tax 0% t - NA NIA $ -
TOTAL $ 2 500 000 2 400 $ 95 160 $ - $ 2 595 160
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVZTY: 1.0-mm FMS In New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Mechanical CHECKED BY: SL/SN/TZ I CONST.
MATERIAL/ EQUIPMENT LABOR UNIT COST E"'"DMENT NO DESCRIPTION OTY UNITS $ I UNIT TOTAL-< HRS UNIT WAGE TOTAL HRS TOTAL-< TOTAL-< <tUNIT TOTAL 1 Install 1.0-mm Fine-mesh Modified-Ristrooh Screens 30 ea $ 452 132.92 $ 13 563 988 400 $ 37.95 12 000 $ 455 400 $ - $ 467 313 $ 14 019 388 2 Install Screenwash Pumos (476 oom each\ 30 ea $ 9 520.00 $ 285 600 120 $ 37.95 3 600 $ 136 620 * - $ 14 074 $ 422 220 3 Install Screenwash Headers Branches Valves 4 Heavv Dutv Gantrv Crane and Rail Svstem 30 1
ea ea
$ so 000.00
$ 12 000 ODO.OD 1 500 000 12 000 000 BO 1 200 37.95 37.95 2 400 1 200 91 45 080 540
- $ 53
$ 12 045 036 540
$ 1 591 '0BO
$ 12 045 540 5
6 7
B 9
10 11 12 13 TOTAL $ 27 349 588 19200 $ 728 640 $ - $ 28 078 228 Sales Tax 0% $ - NA N/A $
TOTAL $ 27 349 588 19 200 $ 728 640 < - s 28 078 228
- *
- 6/11/2020 Oconee Nuclear Station CUENT / PRO:JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Electrical and I&C CHECKED BY: SL/SN/TZ CONST.
MATERIAL/ EQUIPMENT LABOR cn1 ITPM~NT UNIT COST NO DESCRIPTION TY UNITS ¢ i UNIT TOTAL:,- HRSiUNIT WAGE TOTAL HRS TOTAL-$ TOTAL-ot ot/UNIT TOTAL l Install Wlrlna and Connections 7 500 3 000 If If
¢ 10.00 45.00 75 135 ODO 000 0.08 0.05 35.65 35.65 578 150 l 20 5
588 348 13 47 95 140 588 348 2 Install Conduit 3 Install Terminations 500 ea $ 2.00 l 000 0.60 35.65 300 ' 10 695 $ - $ 23 $ 11 695 4 Install MCC 3 ea $ 200 000.00 600 000 40.00 35.65 120 4 278 $ - $ 201 426 $ 604 278 5 Install DCS 75 ea $ 5 000.00 375 000 10.00 35.65 750 26 738 - $ 5 357 401 738 6 Install Breakers 6 ea ¢ 5 000.00 30 000 1.00 ¢ 35.65 6 $ 214 - $ 5 036 30 214 7 Alarm Dialer 3 ea $ 5 000.00 15 000 3.00 ¢ 35.65 9 $ 321 - $ 5 107 15 321 8 Power Suoolv l Is $ 2 500 000.00 2 500 000 400.00 $
35.65 400 $ 14 260 - $ 2 514 260 2 514 260 9 Liahtlna l Is $ 50 000.00 50 000 0.00 35.65 0 $ - - $ 50 000 50 000 10 Additional Electrical Eauioment - Allowance 1 Is ¢ 500 000.00 500 000 0.00 ¢ 35.65 0 $ - - $ 500 000 500 000 11 Additional Electrical Enaineerina - Allowance 1 Is ¢ 1 000 000.00 1 000 000 o.oo ¢ 35.65 a $ - - $ l 000 000 l 000 000 12 13 14 15 16 17 18 19 2 313 82 441 $4 281 255
.. 5 363 441
¢ 5 281 000 0 TOTAL Sales Tax 0% d: - NA NIA -
TOTAL ¢ 5 281 000 2 313 $ 82 441 $ - 5 363 441
- 6/11/2020 Oconee Nuclear Station CLIENT/ PROJECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I AC17VITY: l.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPLINE: Engineering CHECKED BY: SLISNITZ I MATERIAL / EQUIPMENT LABOR UNIT COST NO DESCRIPTION nTY UNITS <t; I UNIT TOTAL-<t HRS/UNIT WAGE TOTAL HRS TOTAL-'t 't/UNIT TOTAL 1 Desi n En ineerin 1 Is $ - $ - 0 $ - 0 $ 6 285 301 $ 6 285 301 $ 6 285 301 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL Sales Tax 0%
N/A
- 0 . 6 285 301 NA
. 6 285 301 Sub Total $ - $ 6 285 301 $ 6 285 301 Continaencv 0% $ - $ - $ -
TOTAL $ - 0 <!; 6 285 301 $ 6 285 301
- *
- 6/11/2020 Oconee Nuclear Station CUENT I PRO:JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSTING BY: SL/SN I DISCIPUNE: Construction Management CHECKED BY: SL/SN/TZ I MATERIAL/ EuUIPMENT LABOR UNIT COST NO DESCRIPTION OTY UNITS , s; I UNIT TOTAL-$ HRS/UNIT WAGE TOTAL HRS TOTAL-g; g;/UNIT TOTAL 1 Construction Manaaement 156 Weeks $ - $ - 0 $ 7 500 0 $ 1 170 000 $ 7 500 $ 1 170 000 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ 1170 000 $ 1170 000
- Sales Tax 0% N/A NA ITOTAL ,;; - 0 $ 1170 000 $ 1170 000
- *
- 6/11/2020 Oconee Nuclear Station CLIENT/ PRO:JECT: Duke Energy Carolinas, LLC - Oconee Nuclear Station TAKE OFF BY: SL I ACTIVITY: 1.0-mm FMS in New Intake - Capital Cost Estimate COSllNG BY: SL/SN I DISCIPLINE: Project Management CHECKED BY: SL/SN/TZ MATERIAL/ EQUIPMENT LABOR UNIT COST NO DESCRIPTION nTY UNITS <t I UNIT TOTAl-<t HRS/UNIT WAGE TOTAL HRS TOTAL-<t <ttUNIT TOTAL 1 Proiect Manaaement 1 Is $ - $ - 0 $ - 0 $ 628 530 $ 628 530 $ 628 530 2
3 4
5 6
7 8
9 10 11 12 13 14 15 16 17 18 19 20 TOTAL $ - 0 $ 628 530 $ 628 530 Sales Tax 0% N/A NA Sub Total $ - $ 628 530 $ 628 530 Continaenc 0% $ - $ - $ -
TOTAL $ - 0 $ 628 530 $ 628 530
Appendix 10-J Social Costs of Purchasing and Installing Entrainment Reduction Technologies:
Oconee Nuclear Station
This page intentionally left blank.
- Social Costs of Purchasing and Installing Entrainment Reduction Technologies:
Oconee Nuclear Station Final Report Prepared for:
Duke Energy Carolinas, LLC
- Prepared by:
Veritas Economic Consulting September 2020 VERITAS 1851 Evans Road Cary, NC 27513 Office: 919.677.8787 Economic Consulting Fax: 919.677.8331 VeritasEconomics.com
Social Cost Study: Oconee September 2020
- Section 1.
Table of Contents Overview .................................................................................................................. 1 1.1 Summary of Social Costs ..............................................................................................2 Page
- 2. The Social Costs of Compliance and Governmental Regulation Costs ............ 6 2.1 Social Costs of Compliance Costs ................................................................................6 2.2 Social Costs of Governmental Regulation Costs ........................................................ 12
- 3. Social Costs of Power System Effects ................................................................13 3.1 Outages .......................................................................................................................13 3.2 Backpressure and Equipment Load .................................................................._. ......... 14 3.3 Energy Penalty Study Approach .................................................................................17 3.3.1 Step 1-Source Water and Wet Bulb Data .....................................................20 3.3.2 Step 2-Calculate Cooling Tower Approach Temperatures ........................... 21 3.3.3 Step 3-Calculate Cooling Tower Circulating Temperatures .......................... 22 3.3.4 Step 4-Estimate the Water Temperature to Generation Relationship ........... 23 3.3.5 Step 5-Determine Efficiency/Capacity lmpacts ............................................. 24 3.4 Power System .............................................................................................................25 3.4.1 Specify Regional Total Hourly Load ................................................................26
- 4.
3.4.2 3.4.3 3.4.4 3.4.5 Develop Baseline Model. .................................................................................27 Create With Technology Output Schedules ....................................................31 Conduct PROSYM Model Simulations for With Technology Conditions ......... 37 Calculate Differences in Fuel Costs and Emissions ........................................ 37 Social Costs of Externalities .................................................................................40 4.1 Property Value Effects ..............'...................................................................................40 4.1.1 Nature of the Issue and Identifying Possible Property Value Effects .............. 42 4.1.2 Study Approach and Available Information .....................................................43 4.1.3 Viewshed Effects .............................................................................................44 4.1.4 Viewshed Effect Quantification ....................................................................... .45 4.2 Water Consumption Effects ...................................................................................... ..47 4.2.1 Net Water Loss ................................................................................................49 4.2.2 Water Level and Flow Effects ..........................................................................50 4.2.3 Scenario 1-AII Effects Are Water Level Effects ............................................. 52 4.2.4 Scenario 2-AII Effects Are Flow Effects ........................................................53 4.2.5 Conclusion .......................................................................................................53 4.3 Winter Fishery Effects .................................................................................................54 4.3.1 Thermal Discharge Reduction Impacts ...........................................................55 4.3.2 Recreational Fishery lmpacts ..........................................................................55 4.3.3 Summary of Winter Fishery Impacts ...............................................................60
- 5. References .............................................................................................................63 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Appendix A Social Costs of Water Level Impacts from a Closed-Cycle Cooling Conversion: Oconee Nuclear Station .................................... 67 Appendix B HOR Study of Hydroelectric Generation Flow Impacts Due to Cooling Towers at Oconee .....................................................................81
- ii VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Figure Figure 1:
Figure 2:
List of Figures Social Costs Associated with Technology Expenditures ............................................ 6 Duke Energy Carolinas Electric Service Territory and Generation Assets ................. 8 Page Figure 3: Duke Energy Carolinas Owned Nameplate Generation Portfolio by Fuel Type ......... 9 Figure 4: Effects of Construction Outage Time ........................................................................ 14 Figure 5: Effects of Operating Cooling Towers-Backpressure, Pumps Operation, and Fans Operation ..................................................................................................................15 Figure 6: Potential for Efficiency Effects from Closed-Cycle Cooling ...................................... 18 Figure 7: Technical Parameters and Ambient Conditions Underlie Efficiency Effects ............. 19 Figure 8: Hourly Once-Through Source Water Temperature Data for Oconee Nuclear Station, 2018 ..........................................................................................................................20 Figure 9: Hourly Wet Bulb Temperature Data for Oconee Nuclear Station, 2018 ................... 21 Figure 10: Hourly Approach Temperatures for Oconee Nuclear Station, 2018 ......................... 22 Figure 11: Cooling Water Temperatures for Once-Through and Closed-Cycle Cooling for Oconee Nuclear Station, 2018 ..................................................................................22 Figure 12: Relationship Between Water Temperature and Output, Oconee Nuclear Station .... 24 Figure 13: Hourly Maximum Generation for a Unit at Oconee Nuclear Station ......................... 24
- Figure 14: Duke Energy Carolinas' Hourly Load for 2020 .........................................................27 Figure 15: Oconee Nuclear Station Unit 1 Conversion Year Baseline Output ........................... 28 Figure 16: Oconee Nuclear Station Unit 1 Ongoing Year Baseline Output ............................... 28 Figure 17: Oconee Nuclear Station Unit 2 Conversion Year Baseline Output ...........................29 Figure 18: Oconee Nuclear Station Unit 2 Ongoing Year Baseline Output ............................... 29 Figure 19: Oconee Nuclear Station Unit 3 Conversion Year Baseline Output ........................... 30 Figure 20: Oconee Nuclear Station Unit 3 Ongoing Year Baseline Output ............................... 30 Figure 21: 2020 Hourly Prices for Duke Energy Carolinas ........................................................31 Figure 22: Oconee Nuclear Station Unit 1 Conversion Year Output.. ........................................ 33 Figure 23: Oconee Nuclear Station Unit 1 Ongoing Year Output .............................................. 34 Figure 24: Oconee Nuclear Station Unit 2 Conversion Year Output.. ........................................ 35 Figure 25: Oconee Nuclear Station Unit 2 Ongoing Year Output .............................................. 35 Figure 26: Oconee Nuclear Station Unit 3 Conversion Year Output.. ........................................ 36 Figure 27: Oconee Nuclear Station Unit 3 Ongoing Year Output ..............................................36 Figure 28: Location of Oconee Nuclear Station and Surrounding Communities ...................... .41 Figure 29: Potential Effects of Cooling-Tower Operations on Property Values ........................ .42 Figure 30: Value of Properties within Six Miles of Oconee Nuclear Station ............................. .46 VERITAS iii Economic Consulting
Social Cost Study: Oconee September 2020 Figure 31: System Effects and Social Costs of Tower Evaporation .......................................... .48 Figure 32: Effects of Increased Evaporation from Lake Keowee ............................................... 51 Figure 33: Social Costs/Benefits from Reduction in Thermal Discharge ................................... 55 Figure 34: Location of Lake Keowee Fishing Sites ....................................................................57 Figure 35: Location of Sites with Affected Catch Rates, Location of Substitute Sites, and the Concentration of Anglers ............................................................, ............................. 59 Figure 36: Estimated Trip Change With Reduction of Oconee's Thermal Discharge ................ 61 Figure 37: Change in Welfare with Reduction of Oconee's Thermal Discharge ........................ 62 Figure A.1: Incremental Water Level Reduction by Reservoir Elevation Due to Cooling Towers for Lake Keowee .......................................................................................................69 Figure A.2: Incremental Surface Area per Reservoir Elevation for Lake Keowee ....................... 70 Figure A.3: Incremental Wetted Area Reduction by Reservoir Elevation Due to a One-Foot Reduction in Lake Level Caused by Cooling Towers for Lake Keowee ................... 71 Figure A.4: Incremental Percent Surface Area Reduction by Reservoir Elevation Due to a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation for Lake Keowee72 Figure A.5: Incremental Reduction in Fishing Trips to Lake Keowee Due to a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation ................................ 73 Figure A.6: Incremental Social Costs of Fishing Impacts Due to a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation ..............................................................74 Figure A.7: Incremental Lost Hydroelectric Generation from Reduction in Lake Level Due to Evaporation Caused by Cooling Tower Operation ...................................................75 Figure A.8: Incremental Costs of Lost Hydroelectric Generation from Reduction in Lake Level Due to Evaporation Caused by Cooling Tower Operation ........................................ 76 Figure A.9: Property Value Sample Sections along Lake Keowee ............................................. 78
- iv VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Table List of Tables Table 1 Total Engineering and Social Costs of Feasible Technology Options at Oconee ............ 3 Table 2 Timing Specified for Feasible Technologies at Oconee8 ************************************************* .4 Table 3 2018 Residential Cost and Use of Electricity and Its Percentage of Household Income in Areas Served by Duke Energy Carolinas ................................................................. 1O Table 4 Statistical Output Relating Water Temperature to Gross Generation ............................. 23 Table 5 Increased Power System Costs for Duke Energy's Service Territory with Entrainment Reduction Technologies at Oconee .......................................................................... 38 Table 6 Increased Duke Energy System-Wide Emissions (Tons) ...............................................39 Table 7 Lake Keowee Mandated Water Levels .............................................. :........................... .49 Table 8 Net Difference in Water Consumption for the Period 2014 to 2019 ............................... 50 Table 9 Increased Emissions from Lost MWh at the Keowee Development ............................... 54 Table 10 Social Costs of Water Consumption from Closed-Cycle Cooling ................................. 54 Table 11 Affected Population, Trips, and Sites in the Recreational Angling Demand Model ...... 58 Table 12 Catch Rates at Sites Affected by Oconee's Thermal Discharge .................................. 60 Table 8.1 Estimated Net Difference in Water Consumption between Existing Design Evaporation Rates and Hypothetical Design Evaporation Rates Due to Installation of Cooling Towers at Oconee Nuclear Station from July 1, 2014 through June 30, 2019 1.........................................................................................................................82 Table 8.2 Parameters used in Lost Energy Calculations ............................................................83
- V VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1. Overview This document evaluates the social costs of entrainment reduction technologies at the Oconee Nuclear Station (Oconee). By social costs, the U.S. Environmental Protection Agency (USEPA) means costs estimated from the viewpoint of society, rather than individual stakeholders.
Social cost represents the total burden imposed on the economy; it is the sum of all opportunity costs incurred associated with taking actions. These opportunity costs consist of the value lost to society of all the goods and services that will not be produced and consumed as a facility complies with permit requirements, and society reallocates resources away from other production activities and towards minimizing adverse environmental impacts. (79 Fed. Reg. 158, 48432)
Reducing entrainment can generally be accomplished by altering operations, closing.the facility, or by purchasing, installing, and operating entrainment reduction technologies. Installing and operating entrainment reduction technologies would lead to a number of physical changes and financial effects that give rise to opportunity costs. When monetized, these are social costs.
Social costs from entrainment reductions can arise from several sources (Electric Power Research Institute [EPRI] 2015; Bingham and Kinnell 2014):
- Compliance Costs-the owner's cost for purchasing, permitting, installing, operating, and maintaining entrainment reduction technologies .
- Government Regulatory Costs-permitting, monitoring, administering, and enforcing regulatory compliance.
- Power System Costs-increased fuel costs from running more expensive units when the facility is subject to outage, capacity reductions, or closure due to the implementation of entrainment reducing technologies.
- Environmental Externalities-changes in environmental quality such as those to water flow, noise, emissions, and viewsheds.
- Economic Impacts-unit closures and electricity price increases.
The analysis conducted for Oconee includes quantitative estimates for the first four categories listed above. Duke Energy Carolinas, LLC (Duke Energy) (Duke Energy Carolinas 2020) considered several alternative screen, water reuse, and closed-cycle cooling technologies and have evaluated the following options as potentially feasible at Oconee:
- Closed-cycle cooling system retrofit,
- 1.0-mm fine-mesh Ristroph screens in the existing intake structure with a fish return system, and
- 1.0-mm FMS in a new intake structure with a fish return system .
VERITAS 1 Economic Consulting
Social Cost Study: Oconee *september 2020
- 1.1 Summary of Social Costs The first step in estimating social costs is to determine whether the entrainment reducing technology costs will result in the plant becoming uneconomic to operate. A premature shutdown of the plant would have social costs related to loss of jobs, loss of income and expenditures, loss of tax base, increased electricity costs because of generation being dispatched at a higher price from less efficient plants, and increased infrastructure costs to maintain grid reliability. The fact that Oconee supplies approximately 11 percent of Duke Energy's total nameplate generation portfolio (Duke Energy 2019a) suggests that only an extraordinarily expensive conversion requirement would lead to premature closure. Therefore, this analysis assumes Duke Energy will incur the entrainment reducing compliance costs and continue to operate Oconee.
The social costs of installing entrainment reduction technologies are estimated by determining the design, construction and installation costs of the evaluated technologies along with the operation and maintenance (O&M), power system, externality, and permitting costs. The analysis assumes that all compliance costs would be passed on to Duke Energy's electric customers. Table 1 summarizes the results of this evaluation and its implication for social costs.
Following the requirements of the Rule, Table 1 evaluates social costs under two discount rates: 3 percent and 7 percent (79 Fed. Reg. 158, p. 48428). As the first column of Table 1 shows, the top half of the table presents the present value of social costs discounted at 3 percent, and the bottom half presents the social costs discounted at 7 percent. The next column of the table presents each of the feasible technologies evaluated at Oconee. The third and fourth columns present the compliance costs estimated for each feasible technology. The third column presents the estimated design, construction, and installation costs, and the fourth column presents the annual O&M costs for each feasible technology.
The remaining columns in the table present the individual categories of social costs developed for this analysis: electricity price increases from compliance and power system costs, externality costs, and government regulatory costs. The analysis discounts the future stream of each of these social costs at the relevant discount rate and sums them over the years they are specified to occur to develop the Total Social Cost estimate presented in the penultimate column.
The table concludes by presenting the Annual Social Cost estimate for each technology. The annual estimate divides the Total Social Cost by the number of years included in the analysis .
- 2 VERITAS Economic Consulting
Social Cost Study: Oconee *
- September 2020 Table 1 Total Engineering and Social Costs of Feasible Technology Options at Oconee Compliance Costsa Social Costs (Present Value)h Total Design, Electricity Price Increases Construction, Resulting From and Annual Power Government Total Annual Discount Installation O&M Compliance System Externality Regulatory Social Social Rate Technology Type Costs Costsc Costs Costs Costs Costs Costs Costs 3% Closed-Cycle Cooling Tower Retrofit $1,109.32M $15.0M $901.54M $326.73M $11.85M $0.186M $1,240.30M $137.81M 1.0-mm Fine-mesh Screen Retrofit $65.62M $1.9M $64.66M $36.45M N/A $0.012M $101.13M $9.19M 1.0-mm Fine-mesh Screens Installed in a New CWIS $122.20M $2.3M $103.53M $2.06M N/A $0.020M $105.61M $11.73M 7% Closed-Cycle Cooling Tower Retrofit $1,109.32M $15.0M $600.23M $227.44M $8.68M $0.148M $836.49M $92.94M 1.0-mm Fine-mesh Screen Retrofit $65.62M $1.9M $45.00M $28.98M N/A $0.010M $73.99M $6.73M 1.0-mm Fine-mes,h Screens Installed in a New CWIS $122.20M $2.3M $68.93M $1.52M N/A $0.016M $70.47M $7.83M a Compliance costs presented in Table 1 are undiscounted and in 2019 dollars. Costs are represented in millions (M) of dollars.
b Social costs associated with each technology are in 2019 dollars and discounted at 3 and 7 percent using the specifications outlined in Table 2. Numbers may not sum due to rounding.
c Operation and Maintenance costs vary by year. Annual O&M Costs represent the average for each technology.
VERITAS 3 Economic Consulting
Social Cost Study: Oconee September 2020 Implementation timelines were developed for each of the entrainment reduction technologies evaluated for Oconee. These timelines are used to determine when to start accruing operation and maintenance costs and entrainment reduction benefits for each evaluated technology. All modeled technology scenarios assumed 2034 as the end of useful plant life which is based on Duke Energy's anticipated retirement date for Oconee. Because of the complexity of retrofitting an existing nuclear station and nuances of minimizing and balancing station downtime requirements with regional power grid stability, the implementation of alternative technologies would occur incrementally over an extended period of time.
Compliance costs are specified as occurring over a 9-year time period for both a cooling tower retrofit and fine-mesh screens in a new intake structure. Compliance costs are specified as occurring over an 11-year time period for fine mesh screens in the existing intake. Power system costs are specified to occur during construction, based on outage impacts, and during operation, based on efficiency and auxiliary load impacts. Regulatory documents will be submitted in 2020; permitting, design, construction, and installation is specified to occur from 2021-2025 for a cooling tower retrofit and fine-mesh screens in a new intake structure and 2021-2023 for fine-mesh screens in the existing intake structure; operations are specified to begin for Unit 1 in 2026 for both a cooling tower retrofit and fine-mesh screens in a new intake structure, and 2024 for fine-
- mesh screens in the existing intake structure. Operations for Unit 2 are specified to begin in 2027 for a cooling tower retrofit and fine-mesh screens in a new intake structure, and 2025 for fine-mesh screens in the existing intake structure. Operations for Unit 3 are specified to begin in 2028 for a cooling tower retrofit and fine-mesh screens in a new intake structure, and 2026 for fine-mesh screens in the existing intake structure. For fine-mesh screens, all units are specified to begin operations in 2024. Table 2 reflects the timing specifications for each evaluated alternative.
Table 2 Timing Specified for Feasible Technologies at Oconeea Regulatory Permitting, Design, Years of Entrainment Reducing Documents Construction, and O&M Costs Operation Before Technology Submitted Installation Begin Retirementh Closed-cycle cooling retrofit 2020 2021-2025 2026 9 Fine-mesh screens 2020 2021-2023 2024 11 Fine-mesh screens in a new CWIS 2020 2021-2025 2026 9 8
Timelines are from Duke Energy's PROSYM model.
hAnticipated station retirement date. Oconee's U.S. Nuclear Regulatory Commission (NRC) operating licenses expire at midnight on the following dates for each unit: Unit 1 - 2/6/2033, Unit 2 - 10/6/2033, and Unit 3 - 7/19/2034
- 4 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 As Table 1 shows, the social costs of each technology include the expected electricity price increases associated with each technology's compliance costs, the additional power system costs that would be incurred with each technology, the externality costs of each technology, and the governmental regulatory costs. As previously noted, the analysis specifies that all compliance costs are passed on to Duke Energy's rate payers, resulting in increased electricity prices. To develop the electricity price increases, the design, construction, and installation costs are allocated over the specified construction and installation time-periods presented in Table 2.
Operation and maintenance costs are then added for each year the technology is operational, and the future streams of those costs are discounted by 3 and 7 percent to develop the present value estimate for each discount rate.
Power system costs represent the additional power needed to operate the new technologies and the additional fuel needed from running less efficient units during installation construction outages. The power system costs are developed from evaluating backpressure and auxiliary load effects, capacity losses from each of the technologies with estimated outage times, and electricity consumption associated with each technology.
Externality costs represent the environmental impacts associated with the installation of entrainment reducing technologies. For example, operation of a closed-cycle cooling system would create cooling tower plumes that have the potential to affect nearby property values. There would also be costs associated with increased evaporation due to cooling tower operation and the impact of the reduction of the thermal discharge into the source waterbody once closed-cycle recirculation is implemented.
Governmental regulatory costs include the total costs associated with permitting, monitoring, administering, and enforcing the technology selection and installation. Costs are incurred by the government as the permitting and review process is undertaken. These vary with the type of technology, as certain technologies require substantially more permitting. Those with more significant environmental effects would have higher permitting costs. These costs are initially borne by the government, but ultimately paid by taxpayers. The following sections present the analysis for estimating each category of social cost.
- 5 VERITAS Economic Consulting
Sodal Cost Study: Oconee September 2020
- 2. The Social Costs of Compliance and Governmental Regulation Costs This section describes the methods used to estimate the social costs associated the compliance costs of designing, constructing, installing, permitting, operating, and maintaining entrainment reduction technologies. The section also describes the method for estimating the social costs associated with governmental costs of permitting, monitoring, administering, and enforcing regulatory compliance.
2.1 Social Costs of Compliance Costs As Figure 1 shows, expenditures on entrainment reduction technologies would have implications for Duke Energy's balance sheet and construction activities. Balance sheet implications would accompany the purchase, installation and operation of any of these entrainment reduction technologies. As the figure depicts, construction generates nearby economic activity, which can lead to good social outcomes such as more jobs. These economic impacts can be studied via economic input-output analysis techniques. As related local outcomes are typically considered good, they are not measured under social costs and not considered further here.
Social Cost Categories Physical Change System Effects (r)(10)
(r)(10)(111)
I Shareholders Balance Sheet Electricity Markets ......1-* I Ratepayers (r)(1 O)(ili)
Compliance Cost Implications Technology Economic Impacts Expenditures (Jobs)
Construction Activities ~ - - - - - - - -.....--+ I NearbyJobs v.rm-o111 System Effects and Social Costs of Technology Expenditures VERITAS Figure 1: Social Costs Associated with Technology Expenditures Balance sheet implications are transmitted through financial, electricity, and regulatory markets to register as social costs (i.e., consumer and producer surplus) to groups that potentially VERITAS 6 Economic Consulllng
Soda! Cost Study: Oconee Saptember 2020 include shareholders, ratepayers, and the general population. How these are realized as social costs depends upon the regulatory and market environments.
Oconee is a nuclear power plant located in Oconee County, near Seneca, South Carolina.
Oconee withdraws water from Lake Keowee through a once-through cooling water intake structure (CWIS). Oconee is owned by Duke Energy Carolinas (Duke Energy), a regulated, investor-owned public utility that is a subsidiary of Duke Energy Corporation. Duke Energy generates, transmits, distributes, and sells electricity in central and western North Carolina and western South Carolina . Over 2.6 million residential, commercial, and industrial customers are served across a 24,000-square mile service territory (Duke Energy Corporation 2018, Duke Energy Carolinas 2019a). Duke Energy's assets include approximately 22,164 megawatts (MW)
(winter capacity) of nuclear, natural gas, oil, and coal generating capacity (Duke Energy Carolinas 2019a). Figure 2 presents Duke Energy's electric service territory and location of generating assets. Figure 3 illustrates Duke Energy's generation portfolio fuel type (Duke Energy Carolinas 2019a).
Duke Energy is potentially eligible to recover all or part of the costs of installing entrainment reduction technologies by filing rate requests. Since installing entrainment reducing technologies is a regulatory environmental compliance requirement (as opposed to typical operations and maintenance), these costs are expected to be passed on to customers in the form of higher rates. The Public Service Commission of South Carolina (PSCSC) is the governing body that regulates the operations of Duke Energy and the setting of rates (PSCSC 2020). The PSCSC holds hearings to review requests and can approve authorization for cost recovery.
Similarly, the North Carolina Utilities Commission (NCUC) regulates the operations of Duke Energy in North Carolina . Procedures involved in rate request hearings include allowing intervener comments and Duke Energy rebuttals.
Duke Energy's recent rate case history is instructive with respect to the implications of an additional rate increase. On November 8, 2018, Duke Energy filed for a rate increase beginning in the 2019 calendar year. On May 1, 2019, the PSCSC approved a rate increase averaging 3.7 percent for all residential customers and approximately 1.6 percent for commercial and industrial customers effective June 1, 2019 (Duke Energy Carolinas 2019b).
VERITAS 7 Economic Con ultlng
Social Cost Study: Oconee September 2020
- Dan River Legend Duke Energy Carolinas Service Territory Duke Energy Carolinas Duke Energy Carolinas/Progress Overlap Service Territory and Generation Assets Fuel Source
- Combined Cycle Station
- Combustion Turbine Station
- Fossil Station 0 Nuclear Station
- Natural Gas Station with Combined Cycle Unit Note : Various solar power collection areas and hydro stations are located throughout VERITAS Economic Consulting the service territory.
Source: 2019 Duke Energy Carolinas Integrated Resource Plan Figure 2: Duke Energy Carolinas Electric Service Territory and Generation Assets
- 8 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Bad Creek Jocassee (3.4%) ""
(5.9%) '-..__
Other Hydro (4.8%)
\
Dan River (3.1%)
I Rockingham
<3-9%) Buck I
(3.1%)
Lincoln (6.8%)
Mill Creek (3.3%)
Oconee (11 .3%) - - WS Lee (3.4%)
Lee
- (1 .2%)
Catawba /
(10.3%)
- McGuire (10.3%)
I Allen Cliffside (4.9%)
(6.0%)
Legend Duke Energy Carolinas Natural gas Generation Portfolio Coal Fuel Type Nuclear Hydro VER IT AS Note: Percentages based on winter generation. Economic Consulting Solar generation accounts for <0.01 % of winter generation Source: 2019 Duke Energy Carolinas Integrated Resource Plan Figure 3: Duke Energy Carolinas Owned 1 Nameplate Generation Portfolio by Fuel Type 1 Catawba is jointly owned with North Carolina Municipal Power Agency Number 1, North Carolina Electric Membership Corporation ,
and Piedmont Municipal Power Agency . Duke Energy Carolinas owns 19.25 percent of the facility .
VERITAS 9 Economic Consulting
Social Cost Study: Oconee September 2020 The costs associated with new entrainment reduction technologies could potentially lead to a rate increase filing, which would subsequently result in higher prices for residential, commercial, and industrial customers. Table 3 lists the average cost of electricity, average electricity use, and monthly electric bills for residential customers in North Carolina and South Carolina for 2018 (U.S. Energy Information Administration [EIA] 2018). The table also lists the percentage of household income spent for electricity at selected household income levels (U.S.
Census Bureau 2018a; U.S. Census Bureau 2018b).
Residential electricity rates in North Carolina and South Carolina were the 13th and 28th lowest among U.S. states in 2018, respectively (U.S. EIA 2018). Although the burden of electricity expenditures is relatively low for many Duke Energy customers, many households spend a significant portion of their income on electricity. All households would share the burden; however, lower-income households would experience a proportionately larger impact.
Table 3 2018 Residential Cost and Use of Electricity and Its Percentage of Household Income in Areas Served by Duke Energy Carolinas Category North Carolina South Carolina Average cost of electricity per kilowatt hour (kWh) $0.1109 $0.1244
- Average use of electricity in kWh per month Average monthly bill Median annual income Percentage of annual household income needed for electricity (monthly bill x 12):
1,129
$125.17
$52,413 1,159
$144.20
$51,015
$5,000 annual income 30.0% 34.6%
$12,500 annual income 12.0% 13.8%
$20,000 annual income 7.5% 8.7%
$30,000 annual income 5.0% 5.8%
$50,500 annual income 3.0% 3.4%
$62,500 annual income 2.4% 2.8%
$87,500 annual income 1.7% 2.0%
$125,000 annual income 1.2% 1.4%
$175,000 annual income 0.9% 1.0%
$200,000 annual income 0.8% 0.9%
Source: U.S. EIA (2018); U.S. Census Bureau (2018a, 2018b)
For households, the implications of higher electricity prices depend on the price elasticity of demand for electricity. Price elasticity refers to the amount that quantity demanded changes VERITAS 10 Economic Consulting
Social Cost Study:* Oconee September 2020 with changes in price. The EIA estimates that when the price of electricity increases by ten percent, aggregate electricity use decreases by 1.2 to 2.4 percent in the short run (elasticity of -
0.12 to -0.24) and 4.0 percent in the long run (elasticity of -0.40). 2 In the billing context, if a customer with an elasticity of -0.2 who spends $100 ($0.10/kWh x 1000 kWh) per month on electricity in baseline conditions experiences a 10-percent increase in electricity rates, the customer would reduce use by 2 percent to 980 kWh. This would result in a monthly bill of $107.80 and an annual increase in electricity expenditures of $93.60 ($7.80 x 12).
Two effects occur that relate to changes in the customer's wellbeing. First, the customer has decreased electricity use by 240 kWh (20 kWh x 12) over the course of a year. For context, this is equivalent to not operating a typical 5 kW air conditioning unit for 48 hours5.555556e-4 days <br />0.0133 hours <br />7.936508e-5 weeks <br />1.8264e-5 months <br /> in a year. By not operating the air conditioning unit, the household loses the utility of a cooler environment. The monetized willingness to pay of this lost utility is one component of social costs from the electricity rate increase. The second component is the cost of having to pay more for using less electricity.
The second effect is that the household incurs $93.60 in increased electricity costs. Under the conventional (neoclassical) economic theory applied here, households spend money to maximize their utility. For example, when anglers choose among fishing sites or diners among
- restaurants, they pick ones that give them the greatest happiness relative to costs. This measure of happiness, referred to as willingness to pay, is greater than their expenditures. For example, a consumer taking a $100 trip or paying $100 for dinner at a restaurant would have a higher willingness to pay .than the $100 expenditure. For illustrative purposes, the consumer's total willingness to pay could be $140. This means that the consumer gained $40 in consumer surplus, the value over and above the $100 that the consumer had to pay for the trip or dinner.
An activity-specific investigation of consumer surplus to expenditure ratios has not been conducted for this analysis. However, an important result of optimizing time and expenditures over some fixed period is that the relative marginal values of expenditures are equated. 3 An implication is that if the example person chose to spend $100 on a restaurant trip or consumer good, those expenditures would return something like $140 in value. Because the example household has forgone $24 in electricity use (240 kWh x $0.10/kWh), the equating of relative value indicates this is $33.60 in forgone value from electricity use.
2 These price elasticity of demand estimates for electricity are presented in EIA (2014), "Price Elasticities for Energy Use in Buildings of the United States." While the text above presents point estimates, the results in EIA (2014) are estimated with uncertainty.
3 Neoclassical theory posits that utility of an activity/good over a time period diminishes as the amount of the activity/good increases. An implication is that amounts of activities/goods are purchased so that a dollar spent on one activity/good returns the same value as a dollar spent on another activity/good.
VERITAS 11 Economic Consulting
Social Cost Study: Oconee September 2020 For this illustrative household, a ten-percent price increase results in a social cost of
$33.60 in electricity use and $131.04 ($93.6 x 1.4) in forgone enjoyment from goods and activities due to increased electricity expenditures. In total the social cost is $164.64 ($131.04 + $33.60).
The magnitude of these additional increases could also lead to economic impacts that can accompany electricity price increases (Deschenes 2010). Changes in electricity prices can lead to economy-wide employment impacts through their effect on residential and business electricity consumers. For business electricity impacts, the commercial and industrial sectors are all major users of electricity as an input to production. Electricity price increases would raise the costs of providing final goods and services in these sectors. The analysis does not quantify this effect on other sectors of the economy.
2.2 Social Costs of Governmental Regulation Costs Government regulatory costs include the total costs associated with permitting, monitoring, administering, and enforcing the technology selection and installation. Costs are incurred by the government as the permitting and review process is undertaken. These vary with the type of technology as certain technologies require substantially more permitting. Those with more significant environmental effects would have higher permitting costs. These costs are initially borne by the government but ultimately paid by taxpayers .
Government regulatory costs are developed from USEPA's estimates in the Economic Analysis document developed for the 2014 Rule (USEPA 2014a). Following Table 7-7 in USEPA's Economic Analysis document (USEPA 2014b), government administrative costs (regulatory costs) are specified to be 0.02 percent of compliance costs .
- 12 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 3. Social Costs of Power System Effects The USEPA's 2014 Section(§) 316(b) Rule (79 Fed. Reg. 158, 48300-48439) (hereafter Rule) requires that applicants submit studies of technologies or operational measures that can reduce entrainment. Section 122.21 (r)(12) Non-Water Quality Environmental and Other Impacts Study requires a study and "detailed facility-specific discussion of the changes in non-water quality environmental and other impacts" attributed to technologies or operational measures considered under §122.21 (r) (10). The non-water quality environmental and other impacts as defined in the Rule are:
(i) Estimates of changes to energy consumption (ii) Estimates of air pollutant emissions and of the human health and environmental impacts associated with such emissions (iii) Estimates of changes in noise (iv) A discussion of impacts to safety (v) A discussion of facility reliability (vi) Significant changes in consumption of water (vii) A discussion of all reasonable attempts to mitigate each of these factors.
- This section focuses on estimating the social costs associated with changes in energy consumption,§ 122.21 (r)(12)(i), and offsite emissions,§ 122.21 (r)(12)(ii). Energy consumption and emissions impacts arise from plant outages for technology installation, additional electricity consumption required to operate the technology, and unit-efficiency changes related to warmer
- cooling water temperatures.
3.1 Outages Extended outage times during technology installation are, effectively, temporary capacity reductions .. As depicted in Figure 4, these construction outages lead to system level efficiency and capacity changes. 4 4 Significant capacity reductions can affect system reliability which can have social costs. Reliability effects are to be evaluated under (r)(12)(v)-Facility Reliability and are a factor that Directors may consider under§ 125.98(f)(3)(iv)
(May Factor 4-Grid Reliability Impacts). These are unlikely with planned outages, but offset costs may be identified if extended outages for multiple units are anticipated. The social costs of reliability effects are not evaluated in this study.
VERITAS 13 Economic Consulting
Social Cost Study: Oconee September 2020
- Physical Change System Effects Social Cost/Benefit Categories (r)(10)
Must 2-Aollutant Impacts (12)(11)-Emlsslons Health and Environment Stack Emission Environmental Impacts (Acid Rain)
May 4-Reliability Impacts Changes-Pollutant Emissions (12)(I)-Energy Consumption Health Impacts (COPD)
System Efficiency Construction
& Capacity Outage Time Changes Shareholders Electricity Price &
Output Changes i---- I Ratepayers Economic Impacts (Jobs)
Verit s-0157 Effects of Installing Technology and Construction Outage Time V E RITAS Economic Con.ultJnt Figure 4: Effects of Construction Outage Time
- Shutdowns and outages lead to less efficient plants being dispatched to replace the power previously generated by the plant undergoing the entrainment technology installation . This leads to changes in energy consumption that are to be assessed under § 122.21 (r)(12)(i)- Energy Consumption . Changes in energy consumption impact electricity costs and outputs, leading to social costs that must be quantified in§ 122.21 (r)(10)(iii)-Outages Other. Also , the re-dispatch associated with the system-level efficiency changes lead to stack emission changes, which are studied under§ 122.21 (r)(12)(ii)-Emissions Health and Environment. Moreover, this is a factor that Directors are required to consider§ 125.98(f)(2)(ii) (Must 2-Pollutant Impacts) , and that can also have an important impact on social costs.
The effect of an outage for equipment installation is evaluated by modeling the outage within the context of the relevant power and economic systems. This is accomplished by developing a "With Construction Outage" specification in which the capacity of Oconee is reduced to zero to accommodate the outage required to retrofit the station with an entrainment reduction technology .
3.2 Backpressure and Equipment Load Certain other effects become important once entrainment reduction is underway. These
- can occur with most types of entrainment technologies but are typically more pronounced with 14 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 cooling towers. As depicted in Figure 5, when operated , cooling towers have increased backpressure and require additional auxiliary equipment load to operate . This leads to loss of net electrical generation capacity and efficiency effects which also must be identified under § 122.21 (r)(12)(i)-Energy Consumption . As with outages , these energy consumption changes have social costs and lead to stack emission changes as additional electricity must be generated to make up lost generation due to the energy penalty.5 ,6 ,7 Social Cost Categories Physical Change System Effects (r)(10)
Must 2-Pollutant Impacts 125.98(f)(2)(ii)
(12)(1i)-Emlssions Health May4 I
- and Environment Environmental (12)(i)-Energy Consumption Impacts (Acid Rain)
Stack Emission Changes-Pollutant Backpressure ~ Emissions Health Impacts (COPD)
Syste m & Unit Pumps Operation Effici ency &
Capacity Changes Shareholders (10)(iii)-Outages and Other Fans Operation
~ Electricity Price & I Output Changes ,..........,......_ Ratepayers Economic Impacts (Jobs)
Vefitas-0142 V ER ITAS ystem Effects and Social Costs from Backpressure Effects and Pump and Fan Operation *-Cono.!ti<>o Figure 5: Effects of Operating Cooling Towers-Backpressure, Pumps Operation, and Fans Operation The energy penalty evaluation is an important input to a number of studies necessary for the§ 122.21(r)(12) report as well as social costs that must be studied under§ 122.21(r)(10).
Energy penalties arise from "slightly lower generating efficiency attributed to higher turbine backpressure when the condenser is not replaced with one optimized for closed cycle operation 5 " .. . the social cost of the energy penalty is the cost of generating the electricity that would otherwise be available for consumption except for the energy penalty. Aga in, an assessment of these costs would be determ ined under the
§ 122.21(r)(10) demonstration" (79 Fed. Reg. 158, 48370) .
6 "While both of these factors contribute to increased air emissions, the larger contributor to projected increased air emissions is by far the energy penalty" (79 Fed. Reg. 158, p. 48341 ).
7 "EPA is not able to quantify the frequency with wh ich facilities could experience these local impacts, and therefore has concluded that the proper forum to address such local impacts fully is in a site-specific setting" (79 Fed. Reg .
158, 48342).
VERITAS 15 Economic Consulting
Social Cost Study: Oconee September 2020 when retrofitting existing units" (79 Fed. Reg. 158, 48341). Studying energy penalty effects is important because:
(1) They relate directly to energy consumption, which must be studied under§ 122.21 (r)(12)(i).
"The study must include the following: Estimates of changes to energy consumption, including but not limited to auxiliary power consumption and turbine backpressure energy penalty"(§ 122.21 (r)(12), 79 Fed. Reg. 158, page 48428).
(2) They produce indirect and direct social costs, which must be studied under§ 122.21 (r)(10).
"EPA is using energy penalty to mean only the opportunity costs associated with reduced power production due to derating (turbine backpressure)" (79 Fed. Reg. 158, 48370).
"... the social cost of the energy penalty is the cost of generating the electricity that would otherwise be available for consumption except for the energy penalty. Again, an assessment of these costs would be determined under the
§ 122.21 (r)(10) demonstration" (79 Fed. Reg. 158, 48370).
(3) They affect air emissions, which must be studied under§ 122.21 (r)(12)(iii) .
- " ... increased air emissions ... due to the energy penalty" (79 Fed. Reg. 158, 48341)
"The study must include the following: ... Estimates of air pollutant emissions and of the human health and environmental impacts associated with such emissions. (79 Fed. Reg. 158, 48428)
(4) These air emissions lead to environmental, health, and social cost (welfare effects),
which must be studied under§ 122.21(r)(12)(iii) and (r)(10):
" ... due to the energy penalty when retrofitting to cooling towers" related to "human health, welfare, and global climate" (79 Fed. Reg. 158, 48341).
"Estimates of air
- pollutant emissions and of the human health and environmental impacts associated with such emissions" (79 Fed. Reg. 158, 48428).
The required studies under§ 122.21 (r)(12) are described as "a detailed, facility-specific discussion." Both§ 122.21 (r)(10) and (r)(12) reports are subject to peer review (79 Fed. Reg.
158, 48368). Energy efficiency impacts result in important social costs and can also be an important determinant in their own right. For example, decision-makers looking ahead to greenhouse gas requirements may find these effects and their costs more important than comparable capital costs .
VERITAS 16 Economic Consulting
Social Cost Study: Oconee September 2020 Unlike losses from operating pumps and fans, the energy penalty effect is difficult to generalize. Energy penalties on the hottest days of summer can be higher (EPRI 2011a; U.S.
Department of Energy Office of Electricity Delivery and Energy Reliability 2008). An important consideration is that energy penalty effects vary hourly and tend to be at their highest when atmospheric conditions are already leading to high air-conditioning loads, generation costs, and wholesale electricity prices.
3.3 Energy Penalty Study Approach The temperature of cooling water affects turbine performance. Generally speaking, colder cooling water improves efficiency (EPRI 2011 a). Energy penalty effects are attributable to the difference in cooling water temperatures of the cooling towers as compared with that of once-through waterbody temperatures. With once-through cooling, the cooling water is the temperature of the source waterbody. With closed-cycle cooling, the cooling water temperature is related to cooling tower design characteristics and atmospheric conditions, in particular wet bulb temperatures.
As wet-bulb temperatures increase, units cooled by closed-cycle recirculating systems become less efficient. Some fossil facilities have the capability to "over-fire" to compensate for
- efficiency impacts. Depending upon operational considerations, these facilities may experience increased fuel costs and less dramatic capacity reductions. 8 Generally speaking, capacity reductions are experienced when fuel input is at the boiler rated maximum and/or unit backpressure is at the highest tolerated point. At this point, fossil units cannot increase British Thermal Unit (BTU) input, and therefore experience capacity reductions. Nuclear units cannot vary fuel input. As noted by EPA, "the cost may be incurred by the facility ... or by another generating unit" (79 Fed. Reg. 158, 48370). In both cases costs (and environmental effects) of providing lost electricity are incurred by other units. 9 Figure 6 depicts the generalized _approach for identifying efficiency effects from a closed-cycle conversion. The approach uses the baseline and counterfactual structure recommended in USEPA (2016) Guidelines for Preparing Economic Analysis. The baseline (red) input-output curve has output limited by line 1 and input (in one million BTUs, MMBTUs) limited at line 2 (number of BTUs per kilowatt hour.) With an energy penalty from operating the cooling tower, the new input-output curve is represented by the blue line. If the unit cannot over-fire, the output is limited to where line 2 intersects the blue curve as indicated by line 3. Additionally, auxiliary 8 An important consideration is that both electricity prices and cooling tower performance are correlated with wet-bulb temperatures .
9 When cooling towers result in lower cooling water temperatures, the opposite occurs.
VERITAS 17 Economic Consulting
Social Cost Study: Oconee September 2020 load increases as cooling tower fans are operated . This is represented by the shift in capacity to line 4. The original fuel input is maintained to serve the parasitic load. The resulting input-output curve (5) represents reduced efficiency and lost net capacity.
BTU/hr Input With Cooling Tower With Cool ing Tower BTU (does not over-fire) (does over-fire) 2 5 \
- - - - _ ,(_ - - - - ~
/ ~r:::: ~ :fl - <:
/ / / Baseline
/ / I I 1
/ / I I I
__..... - : , / I 1 11111 i 3
/ / I I
/ 1 11111 4 I I I I 0---,...------------------.. . -~. . .
0 MW Output Capacity Loss:
does over-fire
~ Capacity Loss:
does not over-fire Veritas--0170 Figure 6: Potential for Efficiency Effects from Closed-Cycle Cooling Because atmospheric conditions vary hourly, the curves depicted in Figure 6 may increase or decrease. Figure 7 depicts the energy penalty effect for time periods when the source water is cooler than the cooling tower water. As depicted in the figure , the magnitude of the energy penalty depends upon fixed (time invariant) technical factors including the slope of the turbine back pressure curve and cooling tower design parameters. The energy penalty also depends upon factors that vary somewhat predictably over the course of a year including source waterbody temperatures and wet bulb temperatures. To evaluate this effect, these are combined in baseline (i. e., existing) and counterfactual simulations .
- 18 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Wet Bulb Temperature I
Cooling Tower Design Parameters I
Once-Through Closed-Cycle Cooling Water Cooling Water Temperature Temperature Condenser Design Parameters I
f l Once-Through Closed-Cycle Condensing Condensing Temperature Temperature
% Increase '~ BTU/
in Heat Rate kWh 10.0 5,000 9.0 Exhaust Pressure 8.0 7.0 I I 6.0
_Lkj 5.0 4.0 3.0 2.0 ... -- ----:,------ , -----
1.0 0.0
- 1.0 0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5 0 MW Output Exhaust Pressure: In . Hg. Abs .
Turbine Backpressure Curve Heat Rate Veritas-0171 Figure 7: Technical Parameters and Ambient Condit ions Underlie Efficiency Effects Because the backpressure effects exhibit nonlinear variability, they are characterized on an hourly basis.10 Details for doing so (including equations) are presented in EPRI (2011 a). The analysis follows these general steps:
- Step 1-Collect and compile hourly ambient conditions data .
- Step 2-Calculate approach temperatures.
10 Turbine backpressure curves are steepest and electricity prices are often highest when wet bulb temperatures are high.
VERITAS 19 Economic Consulting
Social Cost Study: Oconee September 2020
- Step 3-Calculate cooling tower circulating temperatures .
- Step 4-Estimate the water temperature to heat rate curve
- Step 5-Oetermine efficiency impacts.
This sequence results in an estimated hourly energy penalty effect that is specific to the atmospheric, water temperature and operating characteristics of the unit and tower and is relative to baseline conditions .
3.3.1 Step 1-Source Water and Wet Bulb Data Information requirements for hourly ambient conditions include open-cycle source water temperatures and wet-bulb temperatures. Duke Energy provided 2018 hourly source water temperature data for Oconee. Water temperature data used in this analysis are shown in Figure 8.
90 80 70 60
~
1!., 50 E
~
40 30 3:
20 10 0
0 1000 2000 3000 4000 5000 6000 7000 6000 9000 Hour Figure 8: Hourly Once-Through Source Water Temperature Data for Oconee Nuclear Station, 2018 Wet bulb data are available from the National Oceanic and Atmospheric Administration (NOAA) Quality Control Climatological Data. The nearest publicly available readings are from Oconee County Regional Airport, which is approximately 8.5 miles south of Oconee. Hourly wet-bulb temperatures for 2018 are presented in Figure 9 .
- 20 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 80 70 60
~
f
- , 50 l!
D.
E 40
~
.c
'5 30 Ill s';
20 10 0
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Hour Figure 9: Hourly Wet Bulb Temperature Data for Oconee Nuclear Station, 2018 3.3.2 Step 2-Calculate Cooling Tower Approach Temperatures For the cooling tower, the approach temperature is calculated using Equation 1 (EPRI 2011 a). Based on the wet bulb data retrieved from NOAA and the Oconee site-specific discharge data provided by Duke Energy, design wet bulb is specified at 76 degrees and the design
- approach is 10 degrees. The relationship between wet bulb and approach is 0.5 degrees.
Approachh = 0.5*(CT_Design_Wet_Bulb)+(CT_Design_Approach)-0 .5*(Hourly_Wet_Bulb) where CT_Design_Wet_Bulb = 76 and _Design_Approach = 1O (1)
Due to the use of source water temperatures , design wet bulb and approach temperatures, and the same wet bulb data, calculated approach temperatures are very similar across the three units.
Cooling tower hourly approaches for Unit 1 are depicted in Figure 10 .
- 21 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 45 40 35 f
30 i!
~ 25 E
~
.,: 20 u
[ 15 Q.
10 5
1000 2000 Hour Figure 10: Hourly Approach Temperatures for Oconee Nuclear Station, 2018 3.3.3 Step 3-Calculate Cooling Tower Circulating Temperatures Utilizing information on cooling tower hourly approach and hourly wet bulb temperatures ,
circulating water temperatures for cooling towers were calculated following EPRI (2011 a):
Th cooling = Th wet bulb + A pproachh (2)
Figure 11 depicts cooling water temperatures for once-through cooling (baseline/red curve) and closed-cycle cooling (with cooling tower/blue curve) for Unit 1.
90 80
!£ 70 f
60 f.,
Q.
E 50
~
7a 40
- l:
30
.s"'
0 0 20 0
10 0
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Hour Scenario
- Baseline - Wrth Cooling Tower Figure 11: Cooling Water Temperatures for Once-Through and Closed-Cycle Cooling for Oconee Nuclear Station, 2018
- 22 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 3.3.4 Step 4-Estimate the Water Temperature to Generation Relationship For nuclear plants such as Oconee, plant fuel input is fixed . Unit output and heat rate vary with each unit's operational state (e.g. , startup versus running) and with cooling water temperatures. The relationship between cooling water temperatures and gross generation is identified by eliminating observations where the unit is not operational (output of O megawatts) and using linear regression to plot contemporaneous output against water temperatures. This process results in statistical output that relates water temperature to station generation (i.e.,
output), as shown in Table 4. Due to the operational parameters of Oconee and the relative similarity between Unit 1, Unit 2, and Unit 3, it can be assumed that all three units will have similar efficiency impacts under cooling tower operation. Because of this, the data for Unit 1, Unit 2, and Unit 3 was used to derive a relationship between water temperature and output that could be applied to all of the units at Oconee. The relationship between water temperature and output is depicted in Figure 12.
Table 4 Statistical Output Relating Water Temperature to Gross Generation Oconee Nuclear Station Number of obs = 24755 R-square 0.0209
- Variables Water Temp Constant Coefficient
-0.506898 931 .1546 Standard Error 0.0220262 1.471059 t
-23 .01 632.98 Prob> F P>ltl 0.000 0.000
-0.5500706 928.2713
=
95% Conf. Interval 0.0000
-0.4637254 934.038
- 23 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 904 902 900 898 896 i;§. 894 5
- a. 892 5
0 890 888 886 884 65 70 75 80 85 90 95 Water Temperature Figure 12: Relationship Between Water Temperature and Output, Oconee Nuclear Station 3.3.5 Step 5-Determine Efficiency/Capacity Impacts Hourly cooling water temperatures and the equations that relate cooling-water temperature to output, were then used to identify maximum generation under baseline and with
- cooling towers conditions . Figure 13 depicts generation in MW for once-through and closed-cycle cooling .
906 904 902 900
~ 898
'.5 896 a.
'.5 894 0
892 890 888 886 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 Hour Scenario
- Baseline - With Cooling Tower Figure 13: Hourly Maximum Generation for a Unit at Oconee Nuclear Station As shown in Figure 12 and 13, when using a closed-cycle system , the hourly generation
- would decrease due to the warmer water resulting in a loss in efficiency.
24 Once-through VERITAS Economic Con sulting
Social Cost Study: Oconee September 2020 efficiencies relate to source water temperatures, whereas closed-cycle efficiencies are related to atmospheric heat and humidity (that is, wet bulb temperatures) , which leads to more variability in the hourly effect (i.e ., blue curve) . These calculations were conducted with 2018 water temperature and wet bulb temperature data . Based 2018 data, the average annual change in gross output for all hours is 0.58 percent. Efficiency impacts vary hourly with maximum efficiency impacts around 1.66 percent.
3.4 Power System The outage and operational implications described previously are initial physical effects.
These costs would be reflected in the power system as social costs . Understanding how these physical effects would ultimately be reflected as social costs requires considering the relevant power system relation to unit owners and customers within the associated electric service territory.
Retail electric markets in South Carolina and North Carolina are served by regulated ,
investor-owned utilities, municipally-owned utilities, and electric membership cooperatives. The utilities generate, transmit, distribute, and sell electricity to local customers that live in their defined geographic service territory. State public service commissions regulate investor-owned utilities
- through a rate-making process that ensures electricity is produced and delivered cost-effectively while allowing the utilities to recover costs along with a fair rate of return (South Carolina Office of Regulatory Staff 2020) .
Duke Energy does not participate in any of the multi-state Regional Transmission Organizations (RTO) . Rates are set for each regulated utility to cover the costs to produce and deliver reliable power to customers. To ensure reliability, rates include reserve capacity that is available as needed for peak periods, extreme weather events, planned plant outages for maintenance, inspections and refueling , and for any unplanned outage that may occur. Duke Energy's integrated resource planning protocol sets a minimum reserve capacity at 17 percent of total capacity (Duke Energy Carolinas 2019a) . Customers pay for the year-round availability of this reserve margin within their rates regardless of whether they use this electricity or not. Recent projections indicate Duke Energy will be operating with reserve margins between 17 and 24 percent through 2034 (Duke Energy Carolinas 2019a).
Effects are identified by specifying relevant Baseline and With Entrainment Reduction Technology (With-Technology) conditions and then simulating outcomes using Duke Energy's capital cost model-an hourly, chronological production cost simulation model referred to as the Power System Simulation Model (PROSYM) (Duke Energy Carolinas 2019a). This is the same VERITAS 25 Economic Consulting
Social Cost Study: Oconee September 2020 model used by Duke Energy for Integrated Resource Planning (IRP). Given inputs of electric demand, fuel price, generating unit characteristics , and transmission constraints, the model simulates the operation of the electric power system. For the current evaluation, PROSYM was used to determine the annual system production cost difference and emission differences between various alternatives through 2033 for Unit 1 and Unit 2 and 2034 for Unit 3, following timing developed in the § 122.21 (r)(10) for Oconee.
Calculation of least cost dispatch estimates may be affected by several characteristics of the electric system such as generation must run requirements associated with transmission constraints, voltage control and ancillary requirements , as well as other factors. In addition , plant retirements , unit efficiencies and replacement generation alter the dispatch order over time. The Duke Energy Carolinas PROSYM model accounts for these characteristics in the electric system and known changes to future generation. Initially, annual system production costs are determined based on existing operations (i.e., Baseline conditions) . Annual system production costs are determined based on the entrainment reduction alternatives evaluated for this study which include closed-cycle cooling and screen technologies. Specific steps in the power system modeling process include each of the following :
- 1. Determine regional total hourly load based on a 25-year retail and wholesale hourly load forecast.
- 2. Conduct PROSYM model to meet load under Baseline conditions.
- 3. Create With-Technology conditions that characterize conversion downtime and operating conditions .
- 4. Conduct PROSYM model simulations to identify changes under With-Technology conditions.
- 5. Calculate differences in annual costs and emissions.
These steps are implemented as follows.
3.4.1 Specify Regional Total Hourly Load Since electricity production costs and cooling tower effects vary hourly, it is useful to model power system effects at an hourly level. To do this, Duke Energy's 25-year retail and wholesale hourly load forecasts based on internal projections are specified as Baseline load conditions.
Figure 14 depicts Duke Energy's 2020 projected hourly load .
- 26 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- i~
"C Ill 0
...J
- s 20,000 18,000 16,000 14,000 0
J:
12,000 Ill Ill C:
10,000
~
0 Ill u 8,000 C')
~ 6,000 Q)
C:
w 4 ,000 Q)
~
- s 2,000 C
0 N 0 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 N
Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Oec 2020 Hourly Load of Duke Ene rgy Carolinas in Megawatts (MW) V E RITAS Economic Consulti ng Figure 14: Duke Energy Carolinas' Hourly Load for 2020
- 3.4.2 Develop Baseline Model To create baseline outputs, the PROSYM least cost dispatch model was used to meet the load patterns depicted in Figure 14 (and further years) with appropriate sensitivity to factors relevant for § 316(b) determinations. This includes sensitivity of unit efficiency to inlet water temperatures at an hourly level. Predicted historical hourly generation is used to specify baseline conditions . Figures 15 through 20 present Baseline output for Oconee Units 1, 2, and 3. Because the plant has planned outages every 24 months , the figures depict the Baseline output for both the year that an entrainment reduction technology installation would occur (the Conversion Year) and the year after the installation w ould occur (the Ongoing Year) .
- 27 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 i
- ii!: 600 Q.
500 400 0
300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 1 Conversion Year Output VERITAS Economic Consulting Figure 15: Oconee Nuclear Station Unit 1 Conversion Year Baseline Output
- 1,000 900 800 700 i
- ii!: 600 0
Q.
500 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 1 Ongoing Year Output VERITAS Economic Consulting
- Figure 16: Oconee Nuclear Station Unit 1 Ongoing Year Baseline Output 28 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 i'
~ 600 C.
500 400 0
300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 2 Conve rsion Year Output V E RITAS Economic Cont ultlng Figure 17: Oconee Nuclear Station Unit 2 Conversion Year Baseline Output
- 1,000 900 800 700 i'
~
600 0
C.
500 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 2 Ong oing Year Output VERI T AS Economic Con1ultlng
- Figure 18: Oconee Nuclear Station Unit 2 Ongoing Year Baseline Output 29 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 L
§'
600
~
- I C.
- I 500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 3 Conversion Year Output VERITAS Economic Consulting Figure 19: Oconee Nuclear Station Unit 3 Conversion Year Baseline Output
- 1,000 900 800 700
§'
~
... 600
- I C.
- I 500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Baseline Oconee Unit 3 Ongoing Year Output VERITAS Economic Consulting
- Figure 20: Oconee Nuclear Station Unit 3 Ongoing Year Baseline Output 30 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 To create the baseline model , PROSYM and the output specified for Oconee Units 1, 2, and 3 were calibrated to be consistent with the 2020 average hourly prices depicted in Figure 21.
-3::
.c:
$1 ,600
~
~
Cl) $1,400 u
a..
$1 ,200 ni C:
...Clcu $1 ,000
~
...E Cl)
II)
$800
$600 en Cl)
II) cu $400 u
Cl)
II) cu $200 DJ 0
N $0 I* r ff r
- I ., ,-
0 "
N 1,000 2,000 3,000 4,000 6,000 7,000 8,000 5,000 Hours
- 2020 Base Case Hourly Prices for Duke Energy Carolinas in US Dollars Figure 21: 2020 Hourly Prices for Duke Energy Carolinas VERITAS Economic Consulting 3.4.3 Create With Technology Output Schedules With-Technology output schedules are used to identify the difference between output under Baseline cond itions and With-Technology conditions . With-Technology output schedules are created by specifying output from the plant being evaluated and then operating PROSYM .
With-Technology output schedu les are identified for an appropriate number of years to include outage years and ongoing operations. Due to the complexity of retrofitting an existing nuclear station and nuances of minimizing and balancing station downtime requirements with regional power grid stability, the implementation of alternative technologies would occur incrementally over an extended period of time. In PROSYM , Oconee is specified to have a six-month outage for the hypothetical closed-cycle cooling tower retrofit of Unit 1 in 2026 from June 1 through November 29, a six-month outage for Unit 2 in 2027 from June 1 through November 29 , and a six- month outage for Unit 3 in 2028 from March 1 through August 31. Oconee's NRC operating licenses expire at midnight on February 6, 2033 for Unit 1, October 6, 2033 for Unit 2, and July 19, 2034
- for Unit 3. These dates are considered the retirement dates for each of the With-Technology 31 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 scenarios considered in this analysis. Similarly, Oconee is specified to have staggered outages over three years for the hypothetical 1.0mm fine-nesh screen retrofit. Unit 1 would have a two-month outage in 2024 from October 1 to November 30 , Unit 2 would have a two-month outage in 2025 from October 1 to November 30 , and Unit 3 would have a two-month outage in 2026 from April 1 to May 31. The following figures depict Oconee's output schedules under the hypothetical closed-cycle cooling tower retrofit scenario .
Figures 22 and 23 depict Oconee's Unit 1 output for two of the years evaluated in PROSYM : the year the outage occurs for the closed-cycle cooling retrofit (Conversion Year) and the year following the outage (Ongoing Year) . In the conversion year, Oconee Unit 1 is offline for construction , illustrated in Figure 22 by the With-Cooling-Tower Scenario output (blue line) at zero for six-months. When Oconee comes back online after the six-month outage under the With-Cooling-Tower Scenario, auxiliary load and backpressure effects occur over the remainder of the year. The difference between the red and blue lines in Figure 22 illustrates the auxiliary load and backpressure effects. After the construction outage occurs, Oconee's output is lower under the With-Cooling-Tower Scenario (blue line) than under the Baseline Scenario (red line). For the ongoing year, when Unit 1 comes back online under the With-Cooling-Tower Scenario (presented in Figure 23), auxiliary load and backpressure effects occur over the entire year. The difference
- between the red and blue lines in Figure 23 illustrates the auxiliary load and backpressure effects.
For every hour of the year, Unit 1's output is lower under the With-Cooling-Tower Scenario (blue line) than under the Baseline Scenario (red line) .
- 32 VERITAS Economic Consulting
Social Cost Stu=dy-'-':'---"'0-"'co=n=e=e,___ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _---'S=e~p=te=m=be=r'-'2=0=2=0
- 1,000 900 800 700 i
600 500
....::::,a, 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 1 Conversion Year Output VERITAS Economic Consulting Figure 22: Oconee Nuclear Station Unit 1 Conversion Year Output
- 33 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 i::!!:
-- 600 Q,
500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 1 Ongoing Year Output V E RITAS Economic Conaultlng Figure 23: Oconee Nuclear Station Unit 1 Ongoing Year Output
- Output schedules fo r conversion and ongoing years are shown fo r Unit 2 in Figu res 24 and 25 and Unit 3 in Figures 26 and 27 .
- 34 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 i
- a:: 600
- I 0.
- I 500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 2 Conversion Year Output VERITAS Economic Con1uttlng Figure 24: Oconee Nuclear Station Unit 2 Conversion Year Output
- 1,000 900 800 700 i
- a::
600
- I 0.
- I 500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 2 Ongoing Year Output VERITAS Economic Consulting
- Figure 25: Oconee Nuclear Station Unit 2 Ongoing Year Output 35 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 1,000 900 800 700 L..
i'
- !!: 600
- J 500 C.
- J 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 3 Conversion Year Output V E RITAS Economic Consulting Figure 26: Oconee Nuclear Station Unit 3 Conversion Year Output
- 1,000 900 800 700 i'
~
- J C.
- J 600 500 0 400 300 200 100 0
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Hours Scenario
- Baseline - With Cooling Tower Oconee Unit 3 Ongoing Year Output V E RITAS Economic Consulting
- Figure 27: Oconee Nuclear Station Unit 3 Ongoing Year Output 36 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 3.4.4 Conduct PROSYM Model Simulations for With Technology Conditions With capacities from Oconee specified, PROSYM is simulated to identify the With-Technology outcomes. With-Technology output schedules are created by setting appropriate capacity limitations and running PROSYM. Under these conditions, more expensive units are dispatched to make up for lost generation from Oconee.
3.4.5 Calculate Differences in Fuel Costs and Emissions Following identification of hourly cost differentials across Baseline and With-Technology conditions, annual costs are calculated by summing over hours. Table 5 summarizes the results of this process for the three technologies evaluated at Oconee: a closed-cycle cooling tower retrofit, a 1.0-mm fine-mesh screen retrofit in the existing CWIS, and installation of 1.0 mm fine-mesh screens in a new intake. Table 6 presents the resulting emissions associated with the increased fuel consumption presented in Table 5. The increased system-wide emissions in Table 5 are calculated based on changes in unit operations at Oconee as well as other units in the Duke Energy system that would provide compensatory power under With-Technology scenarios .
- 37 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Table 5 Increased Power System Costs for Duke Energy's Service Territory with Entrainment Reduction Technologies at Oconee Cost Component (thousands of Technology 2019$) 2024 2025 2026 2027 2028 2029 2034 Total Closed-Cycle Cooling Fuel Cost NIA NIA $59,179.36 $82,200.20 $93,812.86 $29,313.70 $10,024.89 $395,590.69 Tower Retrofit Variable O&M Cost NIA NIA $5,334.02 $9,445.89 $6,247.56 $4,814.87 $1,132.08 $39,140.79 Environmental Cost NIA NIA $8.62 $10.53 $8.73 $2.23 $0.75 $39.87 1.0-mm Fine-mesh Screen Fuel Cost $14,179.64 $12,287.06 $11,322.32 $348.84 $170.48 -$476.11 $26.10 $38,363.23 Retrofit Variable O&M Cost $685.30 $1,784.35 $1,939.45 $343.43 $259.93 $195.17 $37.46 $5,233.21 Environmental Cost $1.91 $1.42 $1.51 $0.16 $0.02 $0.01 $0.01 $5.10 1.0-mm Fine-mesh Screen Fuel Cost NIA NIA $336.59 $295.48 $300.80 -$473.11 $19.23 $480.87 Installation in a new CWIS Variable O&M Cost NIA NIA $968.62 $350.42 $280.96 $192.57 $85.12 $2,128.03 Environmental Cost NIA NIA $0.05 $0.17 $0.05 $0.03 $0.01 $0.30 Note: Cooling towers and fine mesh screens in a new intake would not become operational until 2026.
The results from Duke's PROSYM model predict negative Fuel Costs for some years. The expectation is that these costs would be positive for every year that the technology operates. When summed over all years and all Power System Costs categories (i.e., Fuel, Variable O&M, and Environmental costs), the total increase in Power System Costs are positive and are most likely underestimated.
These numbers are undiscounted and in 2019 dollars.
VERITAS 38 Economic Consulting
Social Cost Study: Oconee September 2020 Table 6 Increased Duke Energy System-Wide Emissions (Tons)
Technology Emissions 2024 2025 2026 2027 2028 2029 2034 Closed-Cycle Cooling Tower Retrofit CO 2 Output N/A N/A 1,772,880.0 2,235,400.0 2,394,890.0 648,560.0 <10,000.0 SO2 Output N/A N/A 1,030.0 1,200.0 740.0 200.0 10.0 NOx Output NIA N/A 1,350.0 1,710.0 1,570.0 400.0 30.0 1.0-mm Fine-mesh Screen Retrofit CO 2 Output 447,180" 394,230 358,450.0 13,710.0 4,280.0 4,490.0 0.0 SO2 Output 200 200 110.0 20.0 0.0 <10.0 0.0 NOx Output 330 250 270.0 50.0 30.0 <10.0 0.0 1.0-mm Fine-mesh Screen CO 2 Output N/A N/A 17,790.0 12,720.0 7,540.0 4,960.0 0.0 Installation in a New CWIS N/A N/A SO2 Output 0.0 20.0 0.0 <10.0 0.0 NOx Output N/A N/A <10.0 40.0 30.0 <10.0 0.0 Note: Cooling towers and fine mesh screens in a new intake would not become operational until 2026.
VERITAS 39 Economic Consulting
Social Cost Study: Oconee September 2020
- 4. Social Costs of Externalities A number of potential externalities could result from installing cooling towers at Oconee.
This section describes the potential effects of physical changes from a closed-cycle cooling conversion that can produce externalities.
4.1 Property Value Effects Figure 28 depicts Oconee's location and the surrounding communities. Oconee is located in a suburban area in Oconee County, South Carolina and withdraws cooling water from Lake Keowee (Duke Energy Corporation 2019). Population centers closest to the plant include the towns of Walhalla (population approximately 4,300), Seneca (population approximately 8,200),
Clemson (population approximately 15,375) and Central (population approximately 5,200). The plant is located 30 miles west of the city of Greenville, South Carolina's sixth most populous city (population approximately 68,000) and 130 miles northwest of the city of Columbia, South Carolina's capital city (population approximately 133,000) (U.S. Census Bureau 2018). A closed-cycle cooling retrofit at Oconee could potentially affect the quality of life for residents on nearby properties and thereby impact the value of those properties .
- 40 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- I061f. Ct I ooc.i n Lym " /
LakeKeowee P1(11.c 1 WolM I ~
c.,.. ,.,, '
b a ty
- E loy r
Oconee Nuclear Station Wo utt
,. Cl ,on a o
\. endl on A N 10 miles ..
I Location of
,,. .:;-. ,-- -~-~- Oconee Nuclear Station
~
Area 1-=---~-----+--.. "' Enlarged r "
Above
... ~ ...... VERITAS Economic Consulting Figure 28: Location of Oconee Nuclear Station and Surrounding Communities
- 41 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 4.1.1 Nature of the Issue and Identifying Possible Property Value Effects Entrainment reductions can be achieved at some facilities through implementation of operational measures and/or technology installations including wedge wire screens, fine-mesh traveling screens , mechanical draft cooling towers, and natural draft cooling towers . Of these, mechanical and natural draft cooling towers are expected to have the greatest potential to affect property values. Property value impacts are expected to be most pronounced when physical effects from cooling towers affect the quality of life of residential property owners. The primary pathways considered include changes in viewshed and noise levels. Figure 29 depicts the relationship between the potential physical changes resulting from a closed-cycle cooling retrofit, the effects of each change, and the social cost category associated with each effect under the Rule .
Physical Change Effects Social Cost (r)(10)
(r)(1 0)(i)
Tower Installation Structure Viewshed (r)(12)(1v)
Property Tower Evaporation Plume Viewshed Value Determination Pumps Operation (r)(12)(111)
Noise Fans Operation Ventas-0135 Potential Effects of Cooling-Tower Operations on Property Values VERI T AS Figure 29: Potential Effects of Cooling-Tower Operations on Property Values The view from a nearby property (i.e ., viewshed) could be impacted by the profile of a cooling tower structure and/or by the presence of a visible plume. Additionally, noise levels on a nearby property could be impacted from the operation of cooling tower pumps and fans. As depicted in Figure 29, cooling tower noise and plumes are studied under§ 122.21(r)(12) (iii) and
- (iv) and the dimensions and design of a proposed cooling tower results from the cost and 42 VERITAS Economic Con sulting
Social Cost Study: Oconee September 2020 feasibility studies that are conducted under § 122.21 (r)(1 0)(i). Based on currently available information, noise is not expected to impact property value, and it is not considered further.
4.1.2 Study Approach and Available Information Studies to understand the determinants of property values typically apply the hedonic modeling approach. In such studies, statistical modeling is used to relate the price of a property to its characteristics (such as size, features, and condition) and characteristics of the surrounding neighborhood (such as accessibility to schools and shopping and the value of other homes).
These studies have also been used to identify the impact that environmental disamenities, such as industrial sites and noise (e.g., from roadways and airports), have on property values.
The hedonic concept that a property's value arises from its individual components has intuitive appeal. The approach also has strong economic foundations and support in numerous applications (Freeman, Herriges, and Kling 2014). The results derived from market exchanges and hedonic studies are consistently able to rigorously and statistically separate effects; however, hedonic studies can be data and resource intensive. Moreover, independent of effort requirements, it is not technically feasible to develop an original hedonic study for the Rule-permitting context. The primary reason for this is that hedonic property value studies are, by nature, empirical, whereas the Rule-permitting process is forward looking. Because the towers have not been installed, site-specific empirical studies are not possible.
Given this situation, a transfer approach is required; that is, results from one or more other studies of realized effects must be applied to evaluate likely effects. Under the study transfer paradigm, high-quality transfer studies are important, as is coherence between the nature of effects from the transfer site and the study site. This creates additional challenges as closed-cycle cooling conversions are a specific type of incremental change to an existing industrial site.
Examples of power plants that have been retrofitted from open-cycle to closed-cycle cooling include Palisades Nuclear Power Station in Michigan and Brayton Point Power Stc!tion in Massachusetts. Hedonic studies of nearby property values that include transactions before and after a conversion could potentially be used to estimate the incremental effect of installing and operating cooling towers; however, the Palisades Nuclear Power Station conversion occurred in the early 1970's, and it is unlikely that property value information suitable for conducting such an analysis is available. The Brayton Point Power Station conversion of a nearly 500-foot natural draft hyperbolic cooling tower was more recent; however, no such studies have been conducted for this conversion. As a result, the best feasible methods currently available for studying cooling
- 43 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 tower impacts on property value must rely on inferring a reduction in property value rather than empirically identifying one.
4.1.3 Viewshed Effects Various factors can alter a viewshed, including topography, distance to objects, haze, humidity, background landscape, atmospheric conditions, and weather (Development Partners Funding I, LLC 2013). A study of the influence of viewsheds on residential home sales found that residential property owners value larger total views and larger continuous view segments (Hindsley, Hamilton, and Morgan 2013). The proximity of residential properties to the towers and a visible plume is an important aspect in determining negative impacts. Because mechanical draft cooling towers are the proposed closed-cycle cooling technology for Oconee, viewshed effects from the structure itself are not expected because these types of towers are typically less than 60 feet tall (EPRI 2011 b).
Property value effects could arise from viewshed impacts caused by cooling tower plumes.
A visible plume from a cooling tower is composed of water vapor and a small amount of water droplets. One study of mechanical draft cooling tower plumes found a plume could rise as high as 571 feet (Enercon 2003). Plume abatement can be incorporated into the cooling tower design, but it is costly and may require substantial increases in tower size. Plume-abatement technology
- works by recovering and condensing part or all of the vapor stream leaving a tower (Lindahl and Mortensen 2010; Infinite Cooling 2020).
Viewshed effects of a visible plume would apply over a much larger distance than would tower profile, and plume height is an important factor in determining this distance. Several studies have modeled viewshed effects using these factors:
- Saratoga Associates (2009) used a 10-mile distance for modeling viewshed effects of plumes rising 1,200 feet above a cooling tower.
- Niagara Mohawk Power Corporation et al. (1984) considered a 10-mile viewshed to be appropriate for estimating visibility of plumes rising from a 536-foot natural draft cooling tower.
- Development Partners Funding I, LLC (2013) estimated that plumes from a proposed facility with mechanical draft cooling towers would potentially be visible in a community 7 .2 miles from the site.
- Tronaas (2002) estimated that a residential population had a moderate view of 470-foot-high plumes from mechanical draft cooling towers four miles away.
Although these studies identify the areas from which cooling tower plumes are visible, none evaluate their effect on property values .
- 44 .
VERITAS Economic Consultlng
Social Cost Study: Oconee September 2020 The Electric Power Research Institute (EPRI) used the Seasonal Annual Cooling Tower Impact (SACTI) model to estimate the potential for fogging, icing, and shadowing impacts from cooling towers and provided illustrations and summaries of plume fogging impacts for several representative facilities (EPRI 2011 b). Summaries for some of these facilities focused on a 1.2-mile distance used in calculating viewshed effects from cooling towers, while others cited a 6-mile distance for those effects.
4.1.4 Viewshed Effect Quantification The viewshed near Oconee could be affected by a visible plume. Residential properties located nearest to the plant would be the most likely to receive negative effects from cooling tower plumes. The quantification of property value losses from cooling tower related viewshed effects is accomplished via a three-step approach:
- 1. Identify changes in viewshed under Baseline and With Cooling Towers conditions by characterizing changes at Oconee.
- 2. Identify the value of the properties that could experience viewshed effects.
- 3. Where meaningful changes in viewshed are expected to occur to residential properties, characterize them and assign related changes in value.
This analysis considers effects of cooling tower plumes on property values within a 6-mile radius of the site following EPRl's (2011 b) approach. Figure 30 depicts the census tracts located within six miles of Oconee that could potentially be affected by a visible plume from cooling towers at the site (U.S. Census Bureau 2017). The figure lists the total value of the residential properties in each census tract, and the legend sums the total value of properties within six miles of the plant. There are approximately 3,366 residential properties located within six miles of Oconee (U.S. Census Bureau 2017). The residential properties located in the census tracts within six miles of Oconee are collectively valued at approximately $776.2 million. The value of these properties could potentially be negatively impacted by changes in viewshed from a visible plume .
- 45 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
~"~
~~
302 r I' /
$3.5M * %
{?..
1-< J.
Ar0 I
- Legend
(
01....,
{~~*
,-t /
(
I f!t. 1'1.ib kl l\
D Census Tracts within 6 Mile Radius of Oconee Nuclear Station Q Approximate 6 Mile Radius Property Value =
Census Tract within 6 mile Radius
- .,,.... *-:.i ~
Tract 102 $62 .1M ~:t: - ' - - ..... - * ::.: *. * :~ ~ ~
Tract 103 $116.2M . '.'-" .-..:.:==~~ '..: ; ~ :~. ,_; ~ ', Yii-:. Area
~--' *,\.. -* Enlarged Tract 111.01 $6 .6M .- ... "'-
- - ..,_- ',.., ..,,:_*-- '* Above Tract 112.04 $61 .3M .: ':;; ,,/ -:-_._ - ":;': .
Tract 302 $531K
' _..,. I *
- .\
~~
-.... - '\
,i!":
j::...
Tract 303 $327.3M -* '
Tract 306.01 $18 .8M Tract 306.02 $183.4M Value of Properties Within a 6 Mile Radius VERITAS of Oconee Nuclear Station Economic Consulting Figure 30: Value of Properties within Six Miles of Oconee Nuclear Station
- 46 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 As previously stated , no studies in the economic literature directly evaluate the effect of cooling towers or cooling tower plumes on property values. However, in its national evaluation of the net environmental effects of closed-cycle cooling retrofits, EPRI (2011 b) applied results from a study that evaluated the effect that an industrial site with a vapor plume had on nearby property values (Anstine 2003). EPRI (2011 b) used the results from Anstine (2003) to infer that plumes from a closed-cycle cooling retrofit are likely to result in a 1.8 percent reduction in affected property values due to viewshed impacts; therefore , this analysis applies the 1.8 percent impact from EPRI (2011 b) to the $776.2 million in properties with in six miles of Oconee. Results indicate a potentially negative property value impact of approximately $13.97 million within six miles of Oconee. Discounted at 3 percent and 7 percent, this gives a present value of $11 .03 million and
$8 .13 million , respectively. While properties closer to the facility are expected to experience higher losses than those farther away, the results from Anstine (2003) are an average estimate. We therefore apply the average across the entire six-mile area .
4.2 Water Consumption Effects Closed-cycle cooling systems that use "wet cooling " rely on evaporation to cool water, and evaporative losses are typically made up through source waterbody withdrawals. In some systems this can reduce water levels and availability. Reductions in water levels and availability
- in impounded systems (i.e., reservoirs) may result in social costs by negatively impacting hydroelectric generation , drinking water supplies, industrial use/output, recreation , and property values. As depicted below, evaporative losses are to be identified under§ 122.21(r)(12)(vi) and any resulting social costs are to be quantified under§ 122.21(r)(10) .
This section assesses the social costs of changes in water consumption that could result from implementing closed-cycle cooling at Oconee. Oconee is part of the Keowee-Toxaway Hydroelectric Project and is located on Lake Keowee in Oconee County, South Carolina . Lake Keowee is an impoundment created by the construction of the Keowee and Little River dams in 1971. The upper and lower sections of the lake are joined by a man-made (i.e ., excavated) canal that extends across the middle part of the lake. Lake Keowee serves as the source waterbody for the Keowee hydroelectric generating facility and is used by Oconee for cooling purposes. Lake Keowee also supplies municipal drinking water to the City of Greenville and Seneca, South Carolina and is a popular boating , fishing , wildlife and scenic viewing , swimming , recreational vehicle, and tent camping recreation destination (HOR 201 O; FERC 2016a) .
- 47 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Physical Change (12)(vi)-Evaporative Losses System Effects Social Cost Categories (r)(10)
Downstream Recreation Flow Hydro Generation Tower Evaporation ~-+ Net Water Loss Drinking Water Industrial Use Level Reservoir Recreation Reservoir Property Values Verltn-0158
- Figure 31: System Effects and Social Costs of Tower Evaporation Lake Keowee is part of the upper Savannah River Basin . Duke Energy operates three hydropower stations in this watershed , the upstream Bad Creek Pumped Storage Project and the Keowee-Toxaway Hydroelectric Project which is comprised of the Jocassee and Keowee Developments. The U.S. Army Corps of Engineers (USAGE) operates three developments downstream of the Keowee-Toxaway Hydroelectric Project. Through operation of the Keowee-Toxaway Hydroelectric Project, Duke Energy manages the water levels of two lakes (reservoirs) in the watershed ; Lake Jocassee and Lake Keowee. The Federal Energy Regulatory Commission (FERG) license governs Keowee-Toxaway Hydroelectric Project operations (FERG 2016b) .
The FERG license includes the Keowee-Toxaway Project Relicensing Agreement (RA) .
The RA reflects the input of Duke Energy and sixteen other stakeholders who helped develop a collective vision for the region 's water-related needs (primarily water supply, environmental ,
recreation , and energy demand) . As part of this agreement, minimum, maximum, and target water levels were set for each lake to balance competing interests in the basin by protecting water supply needs and promoting environmental and recreation resource enhancements ,
while preserving renewable power resources for the region (Duke Energy Corporation 2020a) .
VERITAS 48 Economic Consulting
Social Cost Study: Oconee September 2020 The minimum reservoir elevations stipulated in the operating license were based in part on thermal power generation needs (at Oconee) and municipal water withdrawals. For Lake Keowee, the target water level is 796 feet above mean sea level (ft msl) with a normal maximum level of 800 ft msl. Minimum target level is 790 ft msl. Table 7 presents the mandated water levels for Lake Keowee (FERC 2016b).
Table 7 Lake Keowee Mandated Water Levels Minimum (ft) Target (ft) Maximum (ft) 8 790 796 800 a Full pond elevation is 800 ft msl. (FERG 2016b)
The FERC operating license also contains a drought management Low Inflow Protocol that establishes water-use restrictions during drought conditions. This is a joint management plan that establishes protocols for periods of low inflow to delay the point at which the available water storage inventory is depleted and applies to entities with water intakes and large water users of the Keowee-Toxaway basin (Duke 2020b).
4.2.1 Net Water Loss Characterizing changes in Lake Keowee's volume requires estimates of changes in evaporation due to cooling towers. Net water loss due to evaporation was estimated as part of the § 122.21(r)(12) water consumption study (HOR 2020). The net difference in evaporation between design baseline conditions and design evaporation (42.0 MGD) with cooling towers was calculated in millions of gallons per day (MGD) and by month (MGM). Baseline refers to conditions that exist on Lake Keowee if Oconee continues to operate without cooling towers.
Results are presented in Table 8 for July 1, 2014 through June 30, 2019 .
- 49 VERITAS Economic Consultlng
Social Cost Study: Oconee September 2020 Table 8 Net Difference in Water Consumption for the Period 2014 to 2019 Average Forced Difference in Water Difference in Water Cumulative Difference in Evaporation at Consumption from Consumption from Water Consumption from Month Design Conditions Cooling Tower Cooling Tower Cooling Tower (MGD) Evaporation (MGD) Evaporation (MGM) Evaporation (MG)
January 17.3 24.7 765.7 765.7 February 17.9 24.1 680.8 1,446.5 March 18.6 23.4 725.4 2,171.9 April 21.3 20.7 621.0 2,792.9 May 24.4 17.6 545.6 3,338.5 June 27.1 14.9 447.0 3,785.5 July 28.9 13.1 406.1 4,191.6 August 29.6 12.4 384.4 4,576.0 September 29.2 12.8 384.0 4,960.0 October 25.5 16.5 511.5 5,471.5 November 21.7 20.3 609.0 6,080.5 December 19.7 22.3 691.3 6,771.8 a Source: HDR (2020)
- Evaluating the social costs of the daily losses (average forced evaporation at design conditions) represented in the first column of Table 8 requires considering the total changes in volume as a result of the net difference. To do this, the total evaporative effect of cooling towers was specified to accumulate over the course of a year. Meteorological conditions were specified to be identical under both Baseline and With Cooling Tower scenarios, meaning that increased evaporation would not change rainfall frequency or amount. 11 To identify the cumulative evaporative effect, the difference in evaporation was identified at the monthly level by multiplying daily evaporation difference (in the second column) in each month by the number of days in each month, which produces output for the third column in Table 8 (monthly difference in water consumption from cooling tower evaporation). The cumulative monthly difference is shown in the fourth column of Table 8, which Hsts the total millions of gallons evaporated by the end of each month for the 2014-2019 period.
4.2.2 Water Level and Flow Effects As depicted in Figure 31, evaporative losses from hydropower reservoirs can lead to social costs due to changes in reservoir level/area resulting from changes in flow through turbines and
- 11 It is specified that no water lost due to the new cooling system is returned to the watershed via precipitation.
50 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 downstream of the dam. For any given volume of water, these effects are mutually exclusive; there is either a water level effect or a flow effect.
At one extreme, only water level is affected as there is less water in the impoundment.
This can impact the efficiency of the hydroelectric generating units (i.e., reduced water levels lower the operating head, or pressure, on the turbines), property values around the reservoir, and recreation on the reservoir. However, in this scenario, the amount of flow through the hydroelectric plant is not affected, and there are no impacts to downstream aquatic habitat or activities such as paddling and fishing.
At the other extreme, only flow is affected as hydroelectric operations are reduced to exactly offset losses due to the increased cooling tower evaporation. Since there is no change in water level, there would be no social costs that would arise from water level effects. However, reduced hydroelectric operations would create social costs from lost generation and reduced downstream flow.
Figure 32 depicts the framework used to evaluate the effects of increased evaporation from Lake Keowee. As this figure indicates, evaporation at Lake Keowee directly impacts the volume of water in the lake. Changes in volume lead to changes in lake levels. Because Lake
- Keowee's levels are governed by the FERC operating license, there is a feedback (double arrows) between the license conditions and lake levels. Changes in downstream releases are a primary mechanism for controlling lake level; therefore, there is a connection between the FERC license and downstream flow.
FERC Flow Operating License l~--V-ol_u_m_e_~1--------** ~---L--,evr-e_1_ _ ::---- L __H_y_d_ro_p_ow-er_ _,
I Area ~---_,.;*
Recreation and Property Values Veritas-0159 /
- Figure 32: Effects of Increased Evaporation from Lake Keowee 51 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Like most lakes, Lake Keowee has a sloping shoreline. As a result, when the water level of the lake goes down, the surface area and volume decrease proportionately. This relationship is indicated by the arrow between level and area. Recreation and property could be affected through reductions in waterbody surface acreage and levels. The number of visits to a lake are typically related to its size. Changes in reservoir levels can affect shoreline attractiveness and the size of navigable areas. Lower reservoir levels can lead directly to property damage (dock rotting, for example) and indirectly to damage resulting from reduced aesthetics of the shoreline.
There are several water intakes on Lake Keowee that are unrelated to Oconee operations, including two municipal water intakes and two irrigation intakes. There are also intakes on three USAGE reservoirs downstream of Lake Keowee, including additional hydropower generation facilities (FERG 2016a). Although there could be impacts to water availability for these uses, social costs associated with these uses were not evaluated as part of this study.
As described earlier, flow and water level effects for any given volume of water are mutually exclusive. In this study, the degree to which effects manifest as water level effects or flow effects has been evaluated. The supporting analyses are contained in the appendices and summarized in the following subsections.
- 4.2.3 Scenario 1-AII Effects Are Water Level Effects Under Scenario 1, impacts to hydroelectric generation, property value, and recreation are evaluated from a water level effect perspective. Detailed descriptions of each of the analyses conducted can be found in Appendix A. Generation impacts due to a reduction in operating head are determined by the equation below:
Generation = Head (ft) x Flow (gallons per minute (GPM)) I Efficiency factor (1)
The cost of this lost generation was determined by multiplying the estimated MWh loss by the assumed $50 value of a MWh. Lost generation costs range from approximately $25,257 per year to $29,389 per year at lake elevations of 800 ft msl and 790 ft msl, respectively. The present value of social costs of water consumption from conversion to closed-cycle cooling with respect to hydroelectric generation are $117,160 using a 7 percent discount rate and $175,975 using a 3 percent discount rate at the target level of 796 ft msl.
Recreation impacts from water level changes were identified using recreation economics methods. The loss of wetted surface area can have a negative impact on the number of fishing trips an angler makes to a particular location. The annual social costs of recreation at 796 ft msl are $24,763 using a 7 percent discount rate and $37, 194 using a 3 percent discount rate. The
- 52 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 present value of social costs with respect to recreation impacts are $222,867 and $334,747 for 7 percent and 3 percent discount rates, respectively.
This scenario also includes property value impacts. A lake's water level is an important attribute associated with lakefront properties. Any changes to water levels have the potential to affect the value of those lakefront properties. At the target level of 796 ft msl, the social cost of a 0.0363-percent property value impact is $1.22 million. The present value of property value social costs is $712,649 and $966,603 for 7 percent and 3 percent discount rates, respectively.
The total social costs for this scenario are $1,477,324 at a 3 percent discount rate.
4.2.4 Scenario 2-AII Effects Are Flow Effects Under Scenario 2, impacts are evaluated for hydroelectric generation as a flow effect The net difference in water consumption between the existing once-through cooling operations versus evaporation from hypothetical closed-cycle cooling towers was determined. The total energy lost at the Keowee Development was estimated by taking the average daily water consumption and calculating the lost energy for this flow rate as shown in the equations below.
Turbine Power (PJ in kW= e1HQw I (737.6 Ft-lb /kW-sec) (2)
Net Output Power (PneJ in kW to Grid= P1eges1 (3)
Annual Lost MWH = Pned365.25 dayslyear)(24 hour2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />s/day)/(1000 kWIMI.N,) (4)
The estimated annual lost generation at the Keowee Development due to increased cooling tower evaporation is estimated at $124,390. The present value of this lost generation ranges from $540,024 to $811,115 for 7 percent and 3 percent discount rates, respectively, which equals approximately 2.535 percent of the annual generation at the Keowee Development.
Assuming downstream recreation impacts are proportional to the percentage of generation impacts due to decreased flow releases, recreation is not expected to be severely impacted and, therefore, is not evaluated in this process.
4.2.5 Conclusion Whether social costs arise primarily as water level effects or as flow effects depends upon the relationship between the operation of the Keowee Development and lake levels. The Keowee-Toxaway Project RA recognizes that potential water level effects over the allowable reservoir operating range would be offset by restricted flow through the Keowee powerhouse. Reservoir level effects would only occur when the powerhouse is prohibited from operating due to low lake levels that may arise under drought conditions. As previously discussed, low inflow protocols are in place to delay the point at which the available water storage inventory is depleted in the VERITAS 53 Economic Consulting
Social Cost Study: Oconee September 2020 Keowee-Toxaway basin (Duke 2020b). During severe drought conditions, hydrogeneration operations at the Keowee-Toxaway Project have been suspended to preserve lake elevations for as long as possible. It is possible that increased evaporation due to cooling tower operations could exacerbate this issue. However, droughts of this severity occur infrequently, and this analysis concludes that water level effects and resulting social costs are unlikely.
Based on this determination, social costs are expected to arise from lost generation due to flow reductions rather than from water level effects. This lost generation, which is estimated to be 2487.8 MWh per year, would be offset by dispatching less efficient generating units in the Duke Energy system. Offsetting the hydroelectric generation with fossil generation would lead to system-level changes in air emissions. Based on average emission rates from the Duke Energy Power Systems Model, generating the additional 2487.8 MWh leads to increased emissions presented in Table 9. At an assumed incremental additional cost of $50 per MWh,. the present value of estimated annual lost hydroelectric generation at the Keowee Development ranges from
$540,024 to $811,115 for 7 percent and 3 percent discount rates, respectively. These costs are shown in Table 10.
Table 9 Increased Emissions from Lost MWh at the Keowee Development
- Emission CO 2 NOx Average Emissions per Lost MWH (tons) 0.5518 0.0002 0.0003 Annual Increased Emissions (tons) 1,372.7 Ok 0.8 Table 10 Social Costs of Water Consumption from Closed-Cycle Cooling Discount Category Affected . Estimated Impact Total Social Cost Rate 3% Hydro Generation . $124,390 $811,115 7% Hydro Generation $124,390 $540,024 4.3 Winter Fishery Effects Under the cooling tower installation scenario, one of the potential changes in operations is the loss of thermal discharge to the source waterbody. The resulting impacts and associated social costs/benefits must be evaluated on a site-specific basis. This section estimates the winter
- 54 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 fishery impacts associated with the loss of thermal discharge into Lake Keowee at Oconee as a result of cooling tower operation .
4.3.1 Thermal Discharge Reduction Impacts Reductions in thermal discharge to a receiving waterbody can affect fisheries and wildlife refuges, potentially resulting in social costs/benefits . Reducing the number of fish deaths from cold shock when a unit is taken off-line in the winter and curtailing the growth of warm water nuisance species are potential improvements that may result from the elimination of thermal discharge. Figure 33 shows the system effects and social costs and benefits from eliminating thermal discharge as well as their relationship to Rule requirements .
Social Cost/Benefit Physical Change System Effects Categories May 2-Thermal Impacts
~
Recreation Trip Quality Thermal Impacts
- Figure 33: Social Costs/Benefits from Reduction in Thermal Discharge Veritas--0116 This section evaluates the social costs associated with recreational fishing losses that would occur with the reduction or elimination of thermal discharges resulting from cooling tower installation . These social costs are illustrated by the top row of Figure 33 , where thermal discharge reductions result in fish habitat changes that cause catch rate changes , in turn resulting in decreases in recreation trip quality. This study does not evaluate the potential social benefit associated with thermal discharge reductions . This evaluation is performed in (r)(11)(vi).
4.3.2 Recreational Fishery Impacts Heated water discharged into Lake Keowee from Oconee creates favorable habitat conditions during colder winter months by forming a warm water refuge in the vicinity of Oconee, which supports a substantial winter fishery for recreational anglers. Under a closed-cycle cooling operation, there may be a social cost related to loss of this fishery. Estimating the impacts of the loss of Oconee's winter fishery requires assessing the relationship between the thermal
- discharge, fishery changes , and the impact that fishery changes have on people . For recreational 55 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 values , this includes understanding how Oconee's thermal discharge affects recreational fishing catch rates and how changes in catch rates affect angler well-being .
The Recreational Angling Demand Model developed to estimate the benefits of entrainment reductions was also used to evaluate the potential changes in Oconee's thermal discharge and the effect on recreational anglers. The model modified site catch estimates to generate recreational catch values that would likely occur if thermal discharges were removed .
The Recreational Angling Demand Model links fishery-specific catch and effort rates. This forms a bio-economic equilibrium for the Lake Keowee fishery expected to be affected by the loss of Oconee's thermal discharge. The integrated partial equilibrium model simulates conditions under With Thermal Discharge (baseline) and Without Thermal Discharge conditions, and the monetized welfare differences between these two conditions determine the impacts of the loss of Oconee's thermal discharge. As described in USEPA's Guidelines for Preparing Economic Analysis (USEPA 2016), equilibrium modeling using the With- and Without-Impact approach is central to all sound benefit estimation processes and regulatory impact analyses .
Changes in catch rates resulting from the loss of the thermal discharge could occur at recreational sites affected by Oconee's thermal discharge. Figure 34 illustrates the recreational
- fishing sites included in the Recreational Angling Demand Model. The red circle in Figure 34 represents the site in the model that is specified to be affected by the loss of Oconee's thermal discharge. In addition to the affected site on Lake Keowee , the figure also illustrates the location of alternative (i.e., substitute) sites (blue circles) included in the model. These are sites where anglers can fish that are not affected by Oconee's thermal discharge .
- 56 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Lake Keowee
,,J..i-
,,.;,-;.'O
~
- c.,_ ,~
.......... c,... y ' , ., ,,.
W,~ Mll"(;.l "t ~
....""'* Pff'o.JJ! Ut'I
- e Legend Oconee Nuclear Station
- ,** a** ** .,_,.,
Area Affected Winter Fishery Sites Enlarged Above
- Substitute Winter Fishery Sites Affected Sites on Lake Keowee VER IT AS Economic Consulting Figure 34: Location of Lake Keowee Fishing Sites
- 57 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Figure 35 shows the angling population that is specified to be most likely affected by changes in Oconee's thermal discharge. Affected anglers are those located in counties within 50 miles of Oconee. The shading illustrates the number of anglers residing in each ZIP Code within the surrounding area .
Table 11 summarizes the data on anglers , trips , and sites (illustrated in Figure 34) used to develop the Recreational Angling Demand Model.
Table 11 Affected Population, Trips, and Sites in the Recreational Angling Demand Model Data Component Estimate Total Number of ZIP Codes in Affected Population a 192 Total Population Residing in Affected ZIP Codes b 1,973,224 Total Anglers Residing in Affected ZIP Codes c 187,679 Total Annual Fishing Days by Anglers in Affected ZIP Codes c 3,417,029 Number of Modeled Fishing Sites 56 Total Annual Fishing Days by Affected Population to Modeled Sites d 1,582 ,554 Total Winter Fishing Trips by Affected Population to Modeled Sites 189,414 Number of Sites Affected by Oconee's Thermal Discharge 1 Total Annual Fishing Days to Affected Site e 3,549 Total Winter Fishing Trips to Site Affected by Oconee's Thermal Discharge 1 424 Sources and Notes:
a The analysis specifies the affected population as those anglers residing in counties within 50 miles of affected sites.
b ZIP Code populati on is from the 2018 American Community Survey (ACS) (U .S. Census Bureau 2019) .
c The estimate of the total anglers in the affected population is developed from the U.S. Fish and Wildlife Service's 2011 National Survey of Fishing , Hunting , and Wildlife-Associated Recreation for Georgia, North Carolina and South Carolina ; the 2010 U.S. Census ; and the 2018 ACS (USFWS 2013a , 2013b, 2013c; U.S. Census Bureau 2019). The analysis uses the 2010 Census population for Georgia, North Carolina , and South Carolina and the 2011 estimate of the total number of resident non-Great Lakes freshwater anglers from the 201 1 USFWS to estimate the percentage of the population that are anglers (7.91 % [GA] , 10.58% [NC], 9.56% (SC]) . The analysis applies this percentage to the 2018 ACS population in the affected ZIP Codes. To develop the estimate of total angling days, the analysis applies the average number of days that these anglers spend fishing non-Great Lakes freshwater sites from the 2011 USFWS (11 days [GA], 16 days [NC] , 20 days [SC]) to the number of anglers residing in the affected ZIP Codes .
d While the model accounts for all of the anglers in the affected population , it does not account for all of the sites where they can take their fishing trips. Therefore, not all of their trips are included in the model. The analysis uses annual trip information that is available for each site in the model to determine the total number of modeled trips (46 .3 percent of affected population 's total trips).
eThe estimated number of total angling days to the affected site is developed from the following publicly available sources: Schmitt and Hornsby (1985).
1 Based on information from the National Marine Fisheries Service (2015) and Nash, Christie , and Stroud (1990), on average, winter trips to a site with a winter fishery account for 11 .97 percent of an nual fishing trips .
- 58 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Kno v ille far Leno ir nton St es rookf d Cha La Oconee Nucl L kA Ss n y J.. er Ros Nel Columbia 1163fl L 1*1rencev1lle
,f>71ft SOUTH 0 12.5 25 CAROLINA llant a
>-c 89011 *
' l~
~,. Au ust ee ".tl Legend e Affected Winter Fishery Sites f:.
._ Substitute Winter Fishery Sites
- , I :: -,* ** * ... * \,,_.
- Area Number of Anglers Residing in Each ZIP Code ~~----fEnlarged Above
- 1-500 501 -1,000 1,001-2 ,000 2,001 -3,000 Angling Population and Sites at VERITAS Oconee Nuclear Station Economic Consulting 3,001+
Figure 35: Location of Sites with Affected Catch Rates, Location of Substitute Sites, and the Concentration of Anglers
- 59 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Table 12 lists catch rates at the sites affected by Oconee's thermal discharge. Catch rates are specified to be catch per hour and are provided for four species groups for both winter and non-winter seasons. The second column represents non-winter catch rates at each fishing site affected by Oconee's thermal discharge. Non-winter catch rates are estimated based on Savannah River creel survey data conducted from December 1979 through December 1982 presented in Schmitt and Hornsby (1985). The third and fourth columns present winter catch rates for the fishing site affected by Oconee's thermal discharge. The Thermal Discharge column represents winter catch rates under baseline conditions, and the No Thermal Discharge column represents winter catch rates under the cooling tower installation scenario where the thermal discharge no longer occurs . Winter catch rates for the With Thermal Discharge scenario were estimated based on recreational fishing winter catch rate data from Lake Raleigh , North Carolina presented in lvasauskas et al. (2017) and data from J . Strom Thurmond Lake in Georgia and South Carolina presented in Bales (2003) . The Without Thermal Discharge scenario catch rates were estimated based on the Savannah River creel survey conducted from December 1979 through December 1982 presented in Schmitt and Hornsby (1985) .
Table 12 Catch Rates at Sites Affected by Oconee's Thermal Discharge
- Species Trout/Shad Panfish Non-Winter Catch Rates 0.0000 0.1170 Winter Catch Rates With Thermal Discharge 0.0000 0.0000 Without Thermal Discharge 0.0000 0.0000 Freshwater Game 0.0360 0.2300 0.0360 Freshwater Other 0.9140 0.0860 0.0860 Sources: Bales (2003); lvasauskas et al. (2017) ; Schmitt and Hornsby (1985) 4.3.3 Summary of Winter Fishery Impacts Based on expected catch changes , equations from welfare economics are used to identify annual changes in trips and economic benefits based on changes in expected catch for all affected species . The change in consumer surplus that arises from changes in site demand is the metric for estimating economic benefits. This methodology is consistent with economic theory and adheres to Rule discussion with respect to considering the "the availability of alternative competing water resources for recreational usage [alternative substitute sites] , and the resulting estimated change in demand for use and value of the affected water resources" (79 Fed. Reg.
158, p. 48 ,371) .
VERITAS 60 Economic Consulting
Social Cost Study: Oconee September 2020 Figure 36 depicts the change in trips to sites affected by the complete reduction of Oconee's thermal discharge. The start-up of the hypothetical closed-cycle cooling towers is specified in the model as occurring in 2026, when the cooling towers would become operational ,
and remain operational through 2034 when the plant is scheduled to retire.
450 440 411 CII
.:: 430 (I) - - - - l I
- 420 "0
CII u
410 \ \
~
< \ \
-0 411 Q.
400 390
\ I
~
... 380 C
~
CII 370 360 350 2020 2025 2030 2035 2040 2045 2050 2055 Years Scenario
... Basellne ... Without Thermal Discharge Affected Sites Change in Trips V E RITAS Economic Consulting Figure 36: Estimated Trip Change With Reduction of Oconee's Thermal Discharge The thermal discharge is specified in the model to be eliminated in 2026 , corresponding with the proposed start-up timeline of the hypothetical cooling towers . The elimination of the thermal discharge is modeled through 2034 , with the baseline conditions being changed from With Thermal to Without Thermal Discharge. The model accounts for the closing of the plant in 2034, resulting in a lack of thermal discharge and subsequent loss of a winter fishery under baseline conditions. In the absence of the thermal discharge, there is a loss of approximately 32 trips at the affected site .
Figure 37 depicts the annual change in dollar-valued welfare associated with the estimated trip changes resulting from the elimination of Oconee's thermal discharge. These are the annual , und iscounted social costs resulting from the lost winter fishery . To develop the present value estimate of this social cost, the annual losses are discounted at 3 percent and 7
- percent following the Rule requirements in § 122.21(r)(10) and summed over the specified 9-year 61 VERITAS Economic Consulting
Social Cost Studv: Oconee September 2020 time period . This produces a present value estimate of the social cost ranging from a loss of
$5 ,727 (7 percent discount rate) to $8 ,602 (3 percent discount rate) .
0 ..--------......----....-- - - - - , - - - -- - - - -...........- -......- - - -......- - - - .
-200 -t-- - - - i - - - - - --tt-- - - - + - - - -- ----+-----+-----+------!
~
-400 +-- - - + - - - --++-- - - + - - - - - - - ,H--- - - - + - - - - - + - - - - - + - - - - - - - - l u
C CII -600 +-- - - + - - - -++-- - - - + - - -- f- + - - - - - + - - - - - + - - - - - + - - - - - - - - l
£ c -800 -+-- - - - + - - - - - + -~- - - - + - - ---<--+------+-----+-----+-------<
~
i -1000 +-- - - - + - - - - + - - - + - - --+-- + - - - - - + - - - - - + - - - - - + - - - - - - - - l
-1200 + -- - - - - - - + -+-- - - - + - -----f - t - - - - - + - - - - - - + - - - - - - + - - - - - - i
-1400 - t - - - - + - - - - - + - - - - - - + - - - - - - + - -- - --+------+-- - - - + - - - - - - !
2015 2020 2025 2030 2035 2040 2045 2050 2055 Years
- Welfare Difference in US Dollars Figure 37: Change in Welfare with Reduction of Oconee's Thermal Discharge VERITAS Economic Consulting
- 62 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 5. References Anstine, J. 2003. "Property Values in a Low Populated Area When Dual Noxious Facilities Are Present." Growth and Change 34:345-358.
Bales, C. Wade. 2003. "Catch, Release, and Harvest Characteristics of Tournament and Non-Tournament Bass Anglers, J. Strom Thurmond Lake, Georgia and South Carolina."
Presented at 2003 Southern Division American Fisheries Society Annual Spring Meeting, Wilmington, North Carolina, February 12-16.
Bingham, Matthew, and Jason Kinnell. 2014. "EPA's New 316(b) Rule and the Opportunity of Social Costs." Power158(9)48,51-54.
Deschenes, Olivier. 2010. "Climate Policy and Labor Markets." Working Paper 16111.
Cambridge, MA: National Bureau of Economic Research. Available at http://www.nber.org/papers/w16111.
- Retrieved on September 17, 2015.
Development Partners Funding I, LLC. 2013. "Exhibit R Scenic Resources." Available at https://www.oregon.gov/energy/Siting/docs/TEC/ASC/R.pdf. Retrieved on May 26, 2016.
Duke Energy Corporation. 2018. Company Website. Available at https://www.duke-energy.com/home.
Duke Energy Corporation. 2019. Company Website. Available at https://www.duke-energy.com/home. Retrieved January 2019 .
- Duke Energy Corporation. 2020a. "Relicensing the Keowee Toxaway Project." Available at https://www.duke-energy.com/community/lakes/hydroelectric-relicensing/keowee-toxaway/relicensing. Retrieved March 2020.
Duke Energy Corporation. 2020b. "Keowee-Toxaway Drought Management Advisory Group."
Available at https://www.duke-energy.com/community/lakes/drought-management-advisory/keowee-toxaway-dmag. Retrieved March 2020.
Duke Energy Carolinas. 2019a. "2019 Integrated Resource Plan." September 4, 2019.
Available at http://energy.sc.gov/fi1es/2019%20DEC%20IRP%20Document%20-
%20PUBLIC2.pdf. Retrieved on April 14, 2020.
Duke Energy Carolinas. 2019b. "Rate Case Update." Available at https://www.duke-enei-gy.com/home/billing/de-carolinas-rates. Retrieved April 20, 2020.
Duke Energy Carolinas. 2020. "PROSYM Results." Personal communication with Veritas Economic Consulting.
Electric Power Research Institute. 2011 a. Full-Time/Seasonal Closed-Cycle Cooling. Product ID 1023100. Palo Alto, CA: EPRI.
Electric Power Research Institute. 2011 b. Net Environmental and Social Effects of Retrofitting Power Plants with Once-Through Cooling to Closed-Cycle Cooling: Final Report. Product ID 1022760. Palo Alto, CA: EPRI.
- 63 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Electric Power Research Institute. 2015. An Introduction to Social Costs and Resources for
- 316(b) Entrainment Evaluations. Product Id: 3002006306. Palo Alto, CA: EPRI Enercon. 2003. "General Site Considerations." In Conversion of Indian Point Units 2 & 3 to a Closed-Loop Cooling Water Configuration. Available at https://www.nrc.gov/docs/ML 1430/ML14307A050.pdf. Retrieved on January 30, 2019.
Federal Energy Regulatory Commission. 2016a. "Final Environmental Assessment For Hydropower License: Keowee-Toxaway Hydroelectric Project- FERG Project No. 2503-154." Available at https://www.ferc.gov/industries/hydropower/enviro/eis/2016/P-2503-154-EA. pdf.
Federal Energy Regulatory Commission. 2016b. "August 16, 2016 Order Issuing New License for the Keowee-Toxaway Hydroelectric Project, 156 FERG 62,122." Available at https://d ms. psc.sc. gov/Attachments/Matter/db 1b7381-8809-403c-bcb3-ccebdda 19598.
Freeman, A. Myrick, Ill., Joseph A. Herriges, and Catherine L. Kling. 2014. The Measurement of Environmental and Resource Values: Theory and Methods. Washington, DC:
Resources for the Future, Inc.
HOR. 2010. "Lake Keowee Bathymetry Study Report." September 2010.
HOR. 2020. Draft Clean Water Act §316(b) Compliance Submittal, Section 12.3.7 Consumptive Use of Water.
Hindsley, Paul, Stuart E. Hamilton, and 0. Ashton Morgan. 2013. "Gulf Views: Toward a Better
- Infinite Understanding of Viewshed Scope in Hedonic Property Models." Journal of Real Estate Finance & Economics 47(3):489-505.
Cooling. 2020. "Plume Abatement Technology". Available cooling.com/plume-abatement-technology/ Visited on May 15, 2020.
at https://infinite-lvasauskas, Tomas J., Wilson N. Xiong, Augustin C. Engman, Jesse R. Fischer, Thomas J. Kwak, and Kirk R. Rundle. 2017. "Relationships Among Catch, Angler Satisfaction, and Fish Assemblage Characteristics of an Urban Small lmpoundment Fishery." Journal of the Southeastern Association of Fish and Wildlife Agencies 4:31-38.
Lindahl, Paul, and Ken Mortensen. 2010. "Plume Abatement-The Next Generation." CTI Journal 31 (2):8-24.
Nash, Val S., Richard W. Christie, and Robert M. Stroud. 1990. "Fisheries Investigations in Lakes and Streams District IV." Available at https:llwww.nrc.gov/docs/ML0303IML030300694.pdf. Retrieved on February 1, 2018.
National Marine Fisheries Service. 2015. "U.S. Marine Recreational Fisheries." Available at https://www.st.nmfs.noaa.gov/Assets/commercial/fus/fus15/documents/04_Recreational 2015.pdf. Retrieved on March 10, 2020.
Niagara Mohawk Power Corporation, Rochester Gas and Electric Corporation, Central Hudson Gas and Electric Corporation, New York State Electric and Gas Corporation, and Long Island Lighting Company. 1984. Draft Environmental Statement Related to the Operation of Nine Mile Point Nuclear Station, Unit No. 2. Docket No. 50-410 .
VERITAS 64 Economic Consulting
Social Cost Study: Oconee September 2020 Saratoga Associates. 2009. "Indian Point Energy Center: Closed Cycle Cooling Conversion Feasibility Study Visual Assessment." Saratoga Springs, NY: Saratoga Associates.
Schmitt, Dennis N., and Jon H. Hornsby. 1985. "A Fisheries Survey of the Savannah River."
Available at https://www.nrc.gov/docs/ML0713/ML071310323.pdf. Retrieved on January 17, 2018.
South Carolina Office of Regulatory Staff. 2017. "Public Service Commission (PSC) of South Carolina." Available at http://www.regulatorystaff.sc.gov/Pages/PSC.aspx. Retrieved on August 4, 2017.
The Public Service Commission of South Carolina. 2020. "Learn About the Public Service Commission of South Carolina." Available at https://www.scutilityconsumer.com/abouV.
Retrieved April 14, 2020 Tronaas, Nancy. 2002. "Pastoral Energy Facility (99-AFC-7C) Staff Analysis of Petition to Modify VIS-7-Plume Abatement." Available at http://www.energy.ca.gov/sitingcases/pastoria/co mpliance/2002 04_STAFF_ANALYSIS.PDF. Retrieved on May 26, 2016.
U.S. Census Bureau. 2017. "American Fact Finder: Value of Owner-Occupied Housing Units; 2006-2010 American Community Survey 5-Year Estimates." Available at https://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t.
Retrieved April 2019.
U.S. Census Bureau. 2018a. "North Carolina Quick Facts: Median Household Income, 2014-
- 2018." Available at https://www.census.gov/quickfacts/NC. Retrieved May 2020.
U.S. Census Bureau. 2018b. "South Carolina Quick Facts: Median Household Income, 2014-2018." Available at https://www.census.gov/quickfacts/SC. Retrieved May 2020.
U.S. Census Bureau. 2019. "Advanced Search. " Available at https://www2.census.gov/data/
Retrieved December 2019.
U.S. Department of Energy Office of Electricity Delivery and Energy Reliability. 2008.
Electricity Reliability Impacts of a Mandatory Cooling Tower Rule for Existing Steam Generation Units. Available at http://www.netl.doe.gov/energy-analyses/pubs/Cooling_Tower_Report.pdf. Retrieved on September 15, 2015.
U.S. Energy Information Administration. 2014. "Price Elasticities for Energy Use in Buildings of the United States." Available at https://www.eia.gov/analysis/studies/buildings/energyuse/pdf/price elasticities.pdf.
Retrieved June 2020.
U.S. Energy Information Administration. 2018. "2017 Average Monthly Bill - Residential."
Available at https://www.eia.gov/electricity/sales_revenue_price/pdf/table5_a.pdf.
Retrieved August 2019.
U.S. Environmental Protection Agency. 2014a. "National Pollutant Discharge Elimination System-Final Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities and Amend Requirements at Phase I Facilities; Final Rule." 79 Federal Register 158 (Friday, August 15) 48,300-48,439.
VERITAS 65 Economic Consulting
Social Cost Study: Oconee September 2020 U.S. Environmental Protection Agency. 2014b. Economic Analysis for the Final Section 316(b)
Existing Facilities Rule. EPA-821-R-14-001. Washington, DC: U.S. EPA.
U.S. Environmental Protection Agency. 2016. Guidelines for Preparing Economic Analyses.
Report Number EPA 240-R-10-001. December. Washington, DC: U.S. EPA. Available at https://www.epa.gov/sites/production/ti les/2017-08/documents/ee-0568-50. pdf.
Retrieved on October 22, 2018.
U.S. Fish and Wildlife Service. 2013a. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Georgia. Available at http://www.census.gov/prod/2013pubs/fhw11-ga.pdf. Retrieved on August 29, 2013.
U.S. Fish and Wildlife Service. 2013b. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: North Carolina. Available at http://www.census.gov/prod/2013pubs/fhw11-nc.pdf. Retrieved on August 30, 2013.
U.S. Fish and Wildlife Service. 2014c. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: South Carolina. Available at http://www2.census.gov/programs-surveys/fhwar/publications/2011/fhw11-sc.pdf. Retrieved on March 27, 2018 .
- 66 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Appendix A Social Costs of Water Level Impacts from a Closed-Cycle Cooling Conversion: Oconee Nuclear Station
- 67 VERITAS Economic Consulting J
Social Cost Study: Oconee September 2020
- The Social Costs of Water Consumption that Lead to Water Level Effects Physical Effects on Lake Area and Water Level Closed-cycle cooling systems relying on wet cooling have direct physical impacts on lake area and water level through evaporative effects. As water used for cooling is extracted from the lake, the water level drops. Because lakes have sloping shorelines, the area of the lake decreases as the water level drops. This water level effect can cause negative economic impacts on recreation and shoreline property values.
The stage-area-volume curve for Lake Keowee (HOR 2010) was used to determine the incremental volume (in acre-feet) associated with each foot of elevation change in Lake Keowee for the upper 1O feet of the reservoir. The upper 1O feet of the reservoir are within the FERG-required reservoir operating range. The evaporation rate is specified to be cumulative over a year. This means that the midpoint of evaporation would occur approximately in the middle of the year. Based on this, a reasonable expected value for the average annual effect would occur at the end of June. The cumulative amount of water evaporated at the end of June was subtracted from the stage-volume curve to determine the effect on stage (converted to inches). Sloped shorelines and the loss in lake level depend on the baseline water elevation and this can vary depending on baseline conditions. Figure A.1 illustrates these estimates for the upper 1O feet of water in Lake Keowee (i.e., between 790-800 ft msl) .
- 68 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 C:
9.6 C: 9.4 0
g 9.2 "C
Cl) 0:: 9 a;
Cl) 8.8
.J
~
Cl) 8.6
-ra 8.4 C:
Cl)
E 8.2 Cl)
(.)
C:
791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.1: Incremental Water Level Reduction by Reservoir Elevation Due to Cooling Towers for Lake Keowee
- As Figure A.1 illustrates, if the baseline elevation is full pond elevation (800 ft msl) , the implied reduction from cooling tower operation in reservoir level is 8.030 inches. At a 10-foot drawdown , (i.e ., a baseline elevation of 790 ft msl), the implied reduction in water level is 9.343 inches.
There would also be an associated decrease in reservoir surface area due to cooling tower evaporation . The incremental loss of surface area (in acres) for Lake Keowee reservo ir at varying baseline elevations is presented in Figure A.2 .
- 69 V E RITAS Economic Consulting
Social Cost Study: Oconee September 2020 Ill Q)
(J
~ 350 ns 450 400 e
<C 300 C:
Q) 250 Cl C:
n,
.c: 200 u
]i 150 C:
Q)
E 100 Q)
(J 50
-=
0 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.2: Incremental Surface Area per Reservoir Elevation for Lake Keowee As Figure A.2 indicates, impacts to surface acreage depend upon the starting (baseline) reservoir elevation . In the upper 10 feet of Lake Keowee , incremental changes in surface area
- range between 208 and 425 acres, on a per-foot basis , as dictated by bathymetry .
The loss of wetted surface area due to increased evaporative losses was determined by converting the loss of lake level (in inches) from Figure A.1 to a percentage of a foot (by dividing by 12). The resulting percentage was then multiplied by the incremental change in surface area (per each reservoir elevation) provided in Figure A.2. The resulting loss of wetted surface area is depicted in Figure A.3. The relatively large changes above 798 ft msl are consistent with the stage-volume curve and are believed to accurately reflect bathymetric features . For example, the large loss in acreage between 799 and 800 ft msl would result from a relatively more gradual shoreline slope over this range .
- 70 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
~
1/)
a, 0
a, 300 280 260 Cl C:
CV
.r:. 240 0
a, Cl 220 CV a,
0 200
<(
-CV C:
a, E
180 a, 160 0
C:
140 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.3: Incremental Wetted Area Reduction by Reservoir Elevation Due to a One-Foot Reduction in Lake Level Caused by Cooling Towers for Lake Keowee
- These reductions represent a small portion of Lake Keowee's total surface area at full pond (Figure A.4) .
- 71 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Q)
Cl IU Q)
(.)
<(
C:
1.8%
1.6%
1.4%
Q)
Cl 1.2%
C:
IU
.t: 1%
u C:
Q)
(.)
0.8%
Q) 0.6%
a.
-IU C:
Q) 0.4%
E 0.2%
Q)
(.)
C: 0%
790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.4: Incremental Percent Surface Area Reduction by Reservoir Elevation Due to a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation for Lake Keowee
- Recreation Impacts Impacts to recreational fishing can be determined using recreation economics methods.
The loss of wetted surface area can have a negative impact on the number of fishing trips an angler makes to a particular location. Utilizing the results from Schmitt and Hornsby (1985) for the Savannah River Basin , anglers spend an estimated 31.87 hours0.00101 days <br />0.0242 hours <br />1.438492e-4 weeks <br />3.31035e-5 months <br /> per acre on Lake Keowee .
Each trip is assumed to consist of 4.4 hours4.62963e-5 days <br />0.00111 hours <br />6.613757e-6 weeks <br />1.522e-6 months <br />. This implies approximately 7.24 fishing trips per acre on Lake Keowee. Multiplying this by the estimated reduction in acreage for each reservoir elevation results in an estimate of the reduced number of fishing trips per year resulting from operation of cooling towers on Lake Keowee 12 . Figure A.5 presents the decrease in fish ing trips per year due to a one-foot reduction in lake level from each of the baseline elevations displayed on the horizontal axis .
12 Cordell and Bergstrom (1993) ; Cameron et al. (1996) ; Eiswerth (2000) ; Jakus, Dowell , and Murray (2000); and Jakus et al (2011) present stated and revealed preference approaches for estimating the impact that water level-related changes have on anglers. Because it was determined that all effects would be flow effects and water level impacts were not included in total social costs , the methodology presented in these studies was not undertaken in this analysis.
VE RI TAS 72 Economic Consulting
Social Cost Study: Oconee September 2020 ca
~...
Cl) a.
1/1 0.
2200 2000 1800 1600 I-C'l 1400 C:
J: 1200
.!!?
....0 1000 1/1 800 1/1 0
...J 600 sC: 400 Cl)
E Cl)
CJ 200 C: 0 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft ms l)
Figure A.5: Incremental Reduction in Fishing Trips to Lake Keowee Due t o a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation
- Impacts to fishing trips are larger at higher reservoir elevations (i.e ., from 800 ft msl to 796 ft msl) because the decrease in surface area due to a one-foot decrease in water level is larger at these higher elevations compared to reservoir elevations below 796 ft msl (as shown in Figures A.3 and A.4) . There are approximately 2,059 trips lost when the water level drops from 800 ft msl to 799 ft msl. Meanwhile, the lowest loss of trips occurs when the water level drops from 790 ft msl to 789 ft msl (1 ,172 trips lost). The value of these lost trips by reservoir elevation is presented in Figure A.6 . Per-trip values are specified to be $41 .67 (Bingham et al. 2011 ). The social cost of these lost fishing trips ranges from approximately $48 ,858 per year to $85 ,794 per year at baseline reservoir elevations of 790 ft msl and 800 ft msl , respectively .
- 73 VE R ITAS Econ omic Consulting
Social Cost Study: Oconee September 2020
- ~ra C.
E Cl C:
$90,000
$80.000
$70,000 ni C:
Cl)
$20,000 E
...CJ Cl) $10,000 C:
$0 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.6: Incremental Social Costs of Fishing Impacts Due to a One-Foot Reduction in Lake Level Caused by Cooling Tower Operation
- Hydroelectric Generation Impacts Impacts to hydroelectric generation can be estimated using the hydropower equation which characterizes generation as a function of head , flow, and turbine efficiency:
Generation = Head (ft) x Flow (GPM) / Turbine Efficiency factor (1)
Head is directly related to reservoir elevation , which in turn is affected by increased evaporative losses. To calculate the effect, the distance between the turbines and the lake level for conditions of Baseline and With Cooling Towers is estimated . The Keowee powerhouse turbines are located at the base of Keowee Dam at an elevation of 670 ft msl. Subtracting this elevation from the midpoint of the operating range of 800 to 790 ft msl returns Baseline Head.
Baseline generation is estimated using total generation of the Keowee Development for 2018, which was 98,140 megawatt hours (MWh) (USEPA 2020) . With Cooling Towers Head is the amount of water rema ining after evaporative losses. Baseline Generation and With Cooling Towers Generation are then calculated and compared to estimate lost hydroelectric generation from the operation of cooling towers on Lake Keowee . Figure A.7 presents these estimates .
- 74 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
.£::
~ 600
- E I'll
~...
590 580 Cl)
- a. 570 C:
0 560 I'll Cl) 550 C:
Cl)
(!) 540 Ill 530 0
..J
- I'll C:
Cl)
E 520 510
...u Cl) 500 C: 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.7: Incremental Lost Hydroelectric Generation from Reduction in Lake Level Due to Evaporation Caused by Cooling Tower Operation
- The horizontal axis represents the baseline water elevation prior to evaporative losses.
For example, if the baseline elevation is full pool elevation (i.e., 800 ft msl) there is expected to be a water level reduction of 8.030 inches. This reduction in lake level from the baseline elevation would reduce hydrogeneration by approximately 505 MWh. As expected , generation losses become larger as the reservoir elevation decreases. The cost of this lost generation was determined by multiplying the estimated MWh loss by the expected value of a MWh . For purposes of this evaluation , a value of $50 per MWh was used . This was specified to be higher than average generation costs because the Keowee turbines typically operate during times of peak demand and therefore offset relatively expensive generation costs . The incremental cost of lost hydroelectric generation , per reservoir elevation , due to increased evaporative losses associated with cooling towers is presented in Figure A.8 . Lost generation costs range from approximately
$25 ,257 per year to $29,389 per year at lake elevations of 800 ft msl and 790 ft msl , respectively .
- 75 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- 3:
- i!E Cl) a.
$30,000
$29,500
$29,000 0 $28,500 ll) 4:R-
$28,000 CV 1/) $27,500 0
u
$27,000 CV C: $26,500 Cl)
E Cl)
CJ
$26,000 C: $25,500
$25,000 790 791 792 793 794 795 796 797 798 799 800 Baseline Elevation (ft msl)
Figure A.8: Incremental Costs of Lost Hydroelectric Generation from Reduction in Lake Level Due to Evaporation Caused by Cooling Tower Operation
- Property Impacts A lake's water level is an important attribute associated with lakefront properties . Any changes in water levels have the potential to affect the value of lakefront properties . Carey et al.
(2011) is a Lake Keowee-specifi c study wh ich analyzed the economic and property value impacts from changing water levels at Lake Keowee in South Carolina . The authors developed a hedonic price model to determine the relationsh ip between shoreline property values and lake levels. Lake Keowee elevati ons are divided into quartiles for modeling pu rposes. These quartiles are described as maximum , quartile, med ian , quartile, and minimum fo r the 100-percent, 75-percent, SO-percent, 25-percent, and 0-percent quartiles, respectively . Elevations at the 25-percent (94.99 ft, msl normalized to 100 ft), SO-percent (96 .15 ft) , and 75-percent (98 .33 ft) quartile were used for model estimations. Results indicate that when lake levels are at the 25-percent quartile, a one-foot decline in lake water levels resulted in a 1.6 percent decline in property values . At the median , 50 percent quartile, a one-foot decline in water levels resulted in property value declines of approximately 0.05 percent.
Estimating the potential property value impact from a reduction in water levels requires an estimate of Baseline property values for properties along the Lake Keowee shoreline . There is
- no available data file that specifically identifies the value of these properties. The website Zillow 76 VERITAS Economi c Con sulting
Social Cost Study: Oconee September 2020 (https://www.zillow.com0 provides market value estimates that are publicly available; however, collecting values for each house is time intensive. Lake Keowee has approximately 300 miles of shoreline and numerous shoreline properties. Given the extent of Lake Keowee's shoreline and number of shoreline properties , this analysis sampled shoreline properties along Lake Keowee and extrapolated property values to estimate the value of all properties along Lake Keowee's 300 miles of shoreline.
The sampling and extrapolation approach used the Graphical Image Manipulation Program (GIMP) , an image manipulating software, to trace the outline of Lake Keowee. The traced outline of Lake Keowee's shoreline resulted in 2,577 pixels . Five geographically distinct sections of approximately 50 pixels each were selected as a sample. This sample represents approximately 9.82 percent of Lake Keowee's shoreline. Figure A.9 shows Lake Keowee's shoreline with the five sampled sections denoted in red and labeled Section 1, 2, 3, 4, and 5. A database of shoreline property values for each of the properties in the 5-section sample was then developed using property information from the Zillow website. The sum of the values of properties located along the shoreline within the 5-section sample was $331 million . The total property value of the sample sections was then extrapolated to estimate the total property value of the entire Lake Keowee shoreline at $3.4 billion .
- 77 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Jll"section 1 Section2 _,(
Salem vj @)
Tamassee
@ ~~
Section 3 Six Mile
@)
Section4
~
@ Cateechee Walhalla @)
No,ris White Harbor Newry @) Central Avonda le Keowee Go .,gle Location of Waterfront Property t"':l'::
Value Sample Sections Along Lake Keowee VERITAS Economic Consulting Area Enlarged Above Figure A.9: Property Value Sample Sections along Lake Keowee
- 78 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 The estimated range of lake level reduction at normal full pond elevation and a 10-foot drawdown is between 8.030 and 9.343 inches (Figure A.1) . The analysis utilized the results from Carey et al. (2011) to estimate the decrease in property values resulting from a reduction in Lake Keowee water level from the target elevation of 796 ft msl. The incremental water level reduction from a baseline elevation of 796 ft msl is 8.579 inches. Based on the results from Carey et al.
(2011) , an 8.579-inch reduction in water level at the target level of 796 ft msl results in a 0.0363 to 1.147 percent reduction in lakefront property values . Applying the 0.0363 percent reduction to the estimated value of Lake Keowee properties corresponds to a $1 .22 million decrease in shoreline property values the year after cooling towers begin operation . The present value of these property value impacts is $712 ,649 and $966,603 at 7 and 3 percent discount rates ,
respectively .
- 79 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- References Bingham , Matthew F., Zhimin Li , Kristy E. Mathews, Colleen M. Spagnardi , Jennifer S. Whaley, Sara G. Vea le, and Jason C. Kinnell. 2011 . "An Application of Behavioral Modeling to Characterize Urban Angling Decisions and Values." North American Journal of Fisheries Management 31 :257-268 .
Cameron , T.A. , et al. 1996. "Using Actual and Contingent Behavior Data with Differing Levels of Time Aggregation to Model Recreation Demand ." J. Agricultural and Resource Economics , 21(1) :130-149.
Carey, Robert T. , Lori Dickes , Ellen W. Saltzman , and Jeffery Allen . 2011 . "Regional Economic Analysis of Changing Lake Levels in Lake Keowee ." Strom Thurmond Institute, South Carolina Water Resources Center. Appendix R of the Final Environmental Assessment:
New Operating Agreement Between U.S . Army Corps of Engineers , Southeastern Power Administration , and Duke Energy Carolinas, LLC . Available at http://www.sas.usace.army.mil/Portals/61/docs/Planning/Plansandreports/Duke/AppR.pd
- f. Retrieved on February 22 , 2018 .
Cordell, H.K., and J.C. Bergstrom. 1993. "Comparison of Recreation Use Values Among Alternative Reservoir Water Management Level Scenarios." Water Resources Research .
29(2) :247-58 .
Eiswerth , M.E. 2000 . "The Value of Water Levels in Water-Based Recreation : A Pooled Revealed Preference/Contingent Behavior Mode." Water Resources Research , 36(4) :1079-1086
- HOR. 2010 . "Lake Keowee Bathymetry Study Report. " September 2010.
Jakus, P.M., P. Dowell , and M. Murray. 2000. "The Effect of Fluctuating Water Levels on Reservoir Fishing ." J. Agricultural and Resource Economics , 25(2) :520-532.
Jakus, P.M., J.C. Bergstrom , M. Philips , and K. Maloney. "Modeling behavioral response to changes in reservoir operations in the Tennessee Valley region " Chapter 17 in, Whitehead , J., T. Haab, and J-C. Huang (eds .) Preference Data for Environmental Valuation . New York: Routledge Schmitt, Dennis N., and Jon H. Hornsby. 1985. "A Fisheries Survey of the Savannah River. " Avai lable at https://www.nrc.gov/docs/ML0713/ML071310323.pdf. Retrieved on January 17, 2018.
U.S. Environmental Protection Agency (USEPA) . 2020 . "Emission & Generation Resource Integrated Database (eGRID) , eGRID 2018 Plant File Sequence Number 9204 Keowee. "
Available at https://www.epa .gov/energy/emissions-generation-resource-integrated-database-egrid . Retrieved on January 30 , 2020 .
- 80 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020 Appendix B HDR Study of Hydroelectric Generation Flow Impacts Due to Cooling Towers at Oconee
- 81 VERITAS Economic Consulting
Social Cost Study: Oconee September 2020
- Estimated Annual Losses in Hydroelectric Generation if Cooling Towers Are Installed at Oconee Nuclear Station Increased evaporation at Lake Keowee due to the operation of hypothetical cooling towers for Oconee Nuclear Station (Oconee) will reduce the available water for hydroelectric generation at Keowee Hydroelectric Station .
The net difference in water consumption in million gallons per day (MGD) between the existing once-through cooling operations versus evaporation from hypothetical closed-cycle cooling towers is provided in Table 8.1 .
Table B.1 Estimated Net Difference in Water Consumption between Existing Design Evaporation Rates and Hypothetical Design Evaporation Rates Due to Installation of Cooling Towers at Oconee Nuclear Station from July 1, 2014 through June 30, 2019 1 Average Forced Net Increase in Month Evaporation at Design ** * ** *
- Evaporation Conditions (MGD)
. * * (MGD)
January 17.3 42.0 24.7 February 17.9 42.0 24.1 March 18.6 42.0 23.4 April 21 .3 42.0 20 .7 May 24.4 42.0 17.6 June 27.1 42.0 14.9 July 28.9 42.0 13.1 August 29 .6 42.0 12.4 September 29.2 42.0 12.8 October 25 .5 42.0 16.5 November 21 .7 42.0 20.3 December 19.7 42.0 22.3 23.4 42.0 18.6 1 Source: HOR. 2020. Draft Clean Water Act §316(b) Compliance Submittal, Section 12.3. 7 Consumptive Use of Water.
2 Design cooling tower evaporation is calculated using the design cooling tower range and design intake flow for the station.
Lost Generation Analysis The difference in average daily water consumption (i.e., net increase in evaporation) presented in Table 8 .1 is 18.6 MGD or 28.8 cubic feet per second (cfs). The energy lost from VERITAS 82 Economic Consulting
Social Cost Study: Oconee September 2020 reduced operations at the Keowee Development was estimated by using the average daily water consumption of 28.8 cfs and calculating the lost energy for this flow rate.
The lost energy in megawatt hours (MWH) was calculated based on the following equations using the values presented in Table B.2:
Turbine Power (Pt) in kilowatts (kW) = e1HQw I (737 .6 foot-pounds/kW-second) (1)
Net Output Power (Pnet) in kW to Grid= P1e9 es1 (2)
Annual Lost MWH = Pnet (365 .25 days/year)(24 hour2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />s/day)/(1000 kW/MW) (3)
Table B.2 Parameters used in Lost Energy Calculations 28.8 cfs 130 ft 62.31 lb/ ft3 @ 70F 92.0%
The estimated lost (annual) hydroelectric generation (in 2019 dollars($]) that would result
- from the addition of cooling towers at Oconee was calculated using Equations 1 - 3 and assuming the value of a MWH = $50 .
Turbine Power= (0.92 x 130 ft x 28 .8 cfs x 62 .31 lb/ft3) / (737 .6 ft-lb/kW-sec)= 291 .0 kW Net Output Power to Grid = 291 .0 x 0.985 x 0.99 = 283.8 kW Annual Lost MWH = (283.8 kW x 365 .25 days/year x 24 hour2.777778e-4 days <br />0.00667 hours <br />3.968254e-5 weeks <br />9.132e-6 months <br />s/day)/ (1000 kw/MW) = 2487.8 MWH Annual Lost Revenue (in 2019 $) = 2487.8 MWH x $50/MWH = $124,390 Note the U.S. Army Corps of Engineers (USACE) owns and operates three hydroelectric projects downstream from the Keowee Development (i.e ., Hartwell Project, Richard B. Russell Project, and J . Strom Thurmond Project) . While increases in consumptive use would also impact hydroelectric generation at these three projects , no attempt has been made to quantify this from a lost revenue perspective .
- 83 VERITAS Economic Consulting
This page intentionally left blank.
Appendix 11-A Estimated Losses and Changes in Stock and Harvest under Baseline Conditions
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L "\"") .
Append ix 11-A r ..I~
- Table 11 -A1. Estimated Annual Impingement Losses Based on 2016 Actual Water Common Name Threadfin Shad Withdrawals at Oconee Nuclear Station 1 Scientific Name Dorosoma petenense 11 1 11,1111,a-11 mm 32,122 1,673 33,795 Blueback herring Alosa aestivalis 911 9,694 10,605 Bluegill Lepomis macrochirus 298 1,046 1,344 Spotted Bass Micropterus punctatus 253 253 Redbreast Sunfish Lepomis auritus 55 147 202 Redeye bass Micropterus coosae 43 27 70 Warmouth Lepomis gulosus 50 50 Blackbanded Darter Percina nigrofasciata 41 41 White Catfish Ameiurus catus 31 31 Flathead Catfish Pylodictis olivaris 30 30 Golden Shiner Notemigonus crysoleucas 16 16 Total 33,834 12,603 46,437 1 Numbers were rounded to the nearest whole number.
-- No organisms estimated Table 11 -A2. Estimated Annual Impingement Losses Based on 2017 Actual Water Withdrawal Volumes at Oconee Nuclear Station 1 Common Name Scientific Name 11 1 Nl1iiillM#*il-Threadfin Shad Dorosoma petenense 31 ,122 1,621 32,743 Blueback herring Alosa aestivalis 908 9,664 10,572 Bluegill Lepomis macrochirus 308 1,079 1,387 Spotted Bass Micropterus punctatus 252 252 Redbreast Sunfish Lepomis auritus 58 146 204 Redeye bass Micropterus coosae 43 30 73 Warmouth Lepomis gulosus 50 50 Blackbanded Darter Percina nigrofasciata 41 41 White Catfish Ameiurus catus 31 31 Flathead Catfish Pylodictis olivaris 28 28 Golden Shiner Notemigonus crysoleucas 18 18 Total 32,841 12,558 45,399 1 Numbers were rounded to the nearest whole number.
-- No organisms estimated Duke Energy J 11-A-1
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11 -A rL .J,
'"\""'
- Table 11-A3. Annual Loss Estimates by Candidate Entrainment Reduction Technology for 2016, Oconee Nuclear Station
- --****+&§ Classification 2 Blueback Eggs 33,323,418 5,767,515 5,767,515 866,409 Forage Herring Clupeid Larvae 1,371,354 1,371,354 1,371,354 35,655 Forage Group 3 Shad Larvae 911,727 911,727 911 ,727 23 ,705 Forage Group 4 Sunfish Larvae 495,596 310,491 310,491 12,885 Recreational Species Total 1 36,102,095 8,050,596 310,491 8,361,087 938,654 1Total is the sum of life stages rounded to the nearest whole number.
2 Classifications include Forage , Recreational , or Commercial. No specimens collected in entrainment or impingement studies were classified as commercially harvestable.
3 Clupeid Group - Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad 4Shad Group - Gizzard Shad/Threadfin Shad
-- No organisms estimated Note: MDCT - mechanical draft cooling tower; FMS - fine-mesh screens; mm - millimeters Table 11-A4. Annual Loss Estimates by Candidate Entrainment Reduction Technology for 2017, Oconee Nuclear Station
- **-l~liil1i-liM&Mi*
Blueback Herring Clupeid Eggs Larvae 29 ,121 ,391 4,757,413 5,040,241 3,284,759 1,264,274 5,040 ,241 4,549,032 757 ,156 123,693 Classification 2 Forage Forage Group 3 Shad Eggs 3,046 ,046 2,030,697 2,030,697 79 ,197 Forage Group 4 Unidentified Eggs 304,995 7,930 Forage Fish 5 Unidentified Larvae 304,400 261,327 261,327 7,914 Forage Fish 5 Total 1 37,534,245 10,355,697 1,525,601 11,881,297 975,890 1Total is the sum of life stages rounded to the nearest whole number.
2 Classifications include Forage , Recreational , or Commercial. No specimens collected in entrainment or impingement studies were classified as commercially harvestable.
3 Clupeid Group - Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad 4
Shad Group - Gizzard Shad/Threadfin Shad 5 Based on months of occurrence, Unidentified Fish eggs were mapped to Blueback Herring and Unidentified Fish Larvae were mapped to Threadfin Shad.
-- No organisms estimated Note: MDCT - mechanical draft cooling tower; FMS - fine-mesh screens ; mm - millimeters
- Duke Energy I 11 -A-2
Duke Energy Carolinas, LLC I Oconee Nuclear Stati on CWA §316(b) Compliance Submittal Appendix 11 -A rL "'\""
.I~
- Table 11-AS. Annual Loss Estimates by Candidate Impingement Reduction Technology Taxa for 2016, Oconee Nuclear Station Scientific Name Compliance Scenario Threadfin Shad Dorosoma petenense Juvenile 32,122 29,986 835 Blueback Herring Alosa aestivalis Age 1 9,694 9,598 252 Threadfin Shad Dorosoma petenense Age 1 1,673 1,656 44 Bluegill Lepomis macrochirus Age 1 1,046 251 27 Blueback Herring Alosa aestivalis Juvenile 911 850 24 Bluegill Lepomis macrochirus Juvenile 298 122 8 Spotted Bass Micropterus punctulatus Juvenile 253 104 7 Redbreast Sunfish Lepomis auritus Age 1 147 35 4 Redbreast Sunfish Lepomis auritus Juvenile 55 22 Warmouth Lepomis gulosus Juvenile 50 20 Redeye Bass Micropterus coosae Juvenile 43 18 Blackbanded Darter Percina nigrofasciata Juvenile 41 17 White catfish Ameiurus catus Juvenile 31 13 Flathead Catfish Pylodictis olivaris Juvenile 30 12 Redeye Bass Micropterus coosae Age 1 27 6 Golden Shiner Notemigonus crysoleucas Age 1 16 4 Total 1 46,437 42,714 1,208 1Total is the sum of life stages rou nded to the nearest whole number.
-- No organisms estimated Note: MDCT - mechanical draft cooling tower; Post-lM BTA - post impingement best technology available
- Duke Energy I 11-A-3
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11-A I..:)""
~ ~
- Table 11-AS. Annual Loss Estimates by Candidate Impingement Reduction Technology Taxa for 2017, Oconee Nuclear Station Scientific Name Compliance Scenario 1111111 Threadfin Shad Dorosoma petenense Juvenile 31 ,122 29,053 809 Blueback Herring Alosa aestivalis Age 1 9,664 9 ,568 251 Blueback Herring Alosa aestivalis Age 1 9,664 9 ,568 251 Threadfin Shad Dorosoma petenense Age 1 1,621 1,605 42 Bluegill Lepomis macrochirus Age 1 1,079 259 28 Blueback Herring Alosa aestivalis Juvenile 908 847 24 Bluegill Lepomis macrochirus Juvenile 308 126 8 Spotted Bass Micropterus punctulatus Juvenile 252 103 7 Redbreast Sunfish Lepomis auritus Age 1 146 35 4 Redbreast Sunfish Lepomis auritus Juvenile 58 24 2 Warmouth Lepomis gulosus Juvenile 50 20 1 Redeye Bass Micropterus coosae Juvenile 43 18 1 Blackbanded Darter Percina nigrofasciata Juvenile 41 17 1 White catfish Ameiurus catus Juvenile 31 12 Redeye Bass Micropterus coosae Age 1 30 7 Flathead Catfish Pylodictis olivaris Juvenile 28 11 Golden Shiner Notemigonus crysoleucas Age 1 18 4 Total1 45,399 41,709 1,181 1Total is the sum of life stages rounded to the nearest whole number.
-- No organisms estimated Note: MDCT - mechanical draft cooli ng tower; Post-l M BTA - post im pingement best technology available
- Duke Energy I 11-A-4
Appendix 11-8 Best Professional Judgment Decisions Made in Life History Table Development for Candidate Technology
- Modeling
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L ~""II Appendix 11-B r .I~
- Table 11-B1. Age of Equivalence Stage Order Selections for Oconee Nuclear Station Species 1 Blueback Herring Classification 2 Forage Biological Modeling Equivalent Adult Stage Order Selection Reproductive maturity - Age 4 References EPRI 2012 Logperch Forage Reproductive maturity Age2 EPRI 2012 Bluegill Recreational 100% vulnerability to gear Age4 USEPA 2006 Channel Catfish Recreational 100% vulnerability to gear Age2 USEPA 2006 Emerald Shiner Forage Reproductive maturity Age 1 EPRI 2012 Smallmouth Bass Recreational 100% vulnerability to gear Age4 EPRI 2012 EPRI 2012, Threadfin Shad Forage Reproductive maturity Age 1 Rohde et al. 2009 1 Life history table species .
2 Classifications include forage species (prey and non-game species) and Recreational species (harvested species taken via recreational fishing).
References :
USEPA 2006 U.S. Environmental Protection Agency (USEPA). 2006. Regional Benefits Analysis for the Final Section 316(b) Phase Ill Existing Facilities Rule. EPA-821 -R-04-007 .
EPRI 2012 Electric Power Research Institute (EPRI). 2012. Fish Life History Parameter Values for Equivalent Adult and Production Foregone Models: Comprehensive Update. Final Report 1023103. Palo Alto , CA.
Rohde et al. 2009 Rohde , F.C., R.G. Arndt, J.W. Foltz, and J.M. Quattro. 2009. Freshwater Fishes of South Carolina. University of South Carolina Press , Columbia , SC .
- Duke Energy I 11 -B-1
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11 -8 L ~""II r .I~
Table 11-82. Summary of Best Professional Judgment Decisions in Life History Table Mapping of Species Collected at Oconee Nuclear Station during the 2016-2017 Entrainment Characterization Study Species/Life Stage Mapped To Life Collected History Table Justification Sources 2 111111*11**111111111111*1 EPRI 2012 (5-9);
Blueback Blueback Eggs Eggs Exact match Herring Herring USEPA 2004 (H1-6)
Threadfin Family match; Threadfin Shad were the dominant species collected in purse EPRI 2012 (5-90);
Unidentified Larvae Shad seine sampling nearest to the facility. USEPA 2006 (G1 -15)
Clupeidae Threadfin Fam ily match; Threadfin Shad were the dominant species collected in purse EPRI 2012 (5-90);
spp. PYSL Larvae Shad seine sampl ing nearest to the facility. USEPA 2006 (G1-15)
Threadfin Family match ; Threadfin Shad were the dominant species collected in purse EPRI 2012 (5-90);
YSL Larvae Shad seine sampling nearest to the facility. USEPA 2006 (G1-15)
Threadfin Genus match (Oorosoma); Threadfin Shad were the dominant species EPRI 2012 (5-90);
Eggs Eggs Dorosoma Shad collected in purse seine sampling nearest to the facility. USEPA 2006 (G1-15) spp. Threadfin Genus match (Oorosoma); Threadfin Shad were the dominant species EPRI 2012 (5-90);
Unidentified Larvae Shad collected in purse seine samP.ling nearest to the facility. USEPA 2006 (G1-15)
Lepomis Genus match (Lepomis) ; common and abundant sunfish species in the EPRI 2012 (5-123);
PYSL Bluegill Larvae spp. Piedmont and collected in electrofi shing surveys. USEPA 2006 (H1-7)
Blueback Mapped to Blueback Herring based on seasonal occurrence and other egg EPRI 2012 (5-9) ;
Eggs Eggs Herring identification in entrainment samples. USEPA 2006 (H1-6)
Unidentified Mapped to Threadfin Shad based on seasonal occurrence and presence in Threadfi n historic studies. based on species selecti on fo r Clupeidae spp . and Dorosoma EPRI 2012 (5-90);
Unidentified Larvae Shad spp. and abundance of frag ile forage species in entrainment collections (as USEPA 2006 (G1 -15) compared to robust recreational species) 1 Life Stages incl ude YSL: yol k-sac larvae; PYSL: post yolk-sac larvae; Organ isms identified to YSL or PYS L were mapped to "larvae" life stage if higher resolution was unavailable 2
References:
USEPA 2006 U.S. Environmental Protection Agency (USEPA). 2006. Regional Benefits Analysis fo r the Fina l Section 316(b) Phase Ill Exi stin g Facilities Rule.
EPA-82 1-R-04-007.
EPRI 2012 Electri c Power Research Institute (EPRI ). 2012. Fish Life History Parameter Values for Equivalent Adult and Production Foregone Models:
Comprehensive Update. Final Report 1023103 . Pa lo Alto, CA.
Duke Energy I 11-8-2
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11-B rL """
.I~
Table 11-83. Summary of Best Professional Judgment Decisions in Life History Table Mapping of Taxa Collected at Oconee Nuclear Station during the 2006-2007 Impingement Study Species/Life Stage Mapped to Life Collected History Table Life History Table Data Justification I Resources 2 Life Stage 1 Species Life Stage Genus match (Percina); limited information available for darters, and EPRI 2012 (5-96);
Logperch JUV Logperch are larger wh ich results in conservative estimates. USEPA 2006 (H1-12)
Blueback EPRI 2012 (5-9);
YOY JUV Exact match herring USEPA 2006 (H1-6)
Blueback Yearling And Blueback EPRI 2012 (5-9);
Herring Age 1 Exact match Older herring USEPA 2006 (H1-6)
Blueback EPRI 2012 (5-9) ;
Undetermined JUV Exact match herring USEPA 2006 (H 1-6)
EPRI 2012 (5-123);
YOY Bluegill JUV Exact match USEPA 2006 (H1 -7)
Bluegill Yearli ng And EPRI 2012 (5-123) ;
Bluegill Age 1 Exact match Older USEPA 2006 (H1 -7)
Exact match. Mapped to the juvenile life stage since smaller fish are EPRI 2012 (5-123);
Undetermined Bluegill JUV more likely to be susceptible to impingement. USEPA 2006 (H1-7)
Flathead Channel Family match (lctaluridae); mapped to the juvenile life stage since EP RI 2012 (5-78);
Undetermined JUV Catfish Catfish smaller fish are more likely to be susceptible to impingement. USEPA 2006 (H1-13)
Subfam ily match (Leuciscinae); mapped to the juvenile life stage since Golden Emerald smaller fish are more likely to be susceptible to impingement. Golden EP RI 2012 (5-92) ;
Undetermined JUV Shiner Sh iner Shiner are la rger than Emerald Sh iner and therefore may result in USEPA 2006 (H1 -24) underestimates for this species .
Genus match (Lepomis spp.) and of similar size. Mapped to the juvenile Redbreast EPRI 2012 (5-1 23);
Undetermined Bluegill JUV life stage since smaller fish are more likely to be susceptible to Sunfish USEPA 2006 (H1 -7) impingement.
Genus match (Micropterus spp. ) and of similar size. Mapped to the Redeye Smallmouth EPRI 2012 (5-1 19);
Undetermi ned JUV juven ile life stage since smaller fish are more likely to be susceptible to Bass Bass USEPA 2006 (H1-3) impingement.
Spotted Smallmouth EPRI 2012 (5-119);
YOY JUV Genus match (Micropterus spp.) and of similar size Bass Bass USEPA 2006 (H1 -3)
Duke Energy I11-B-3
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11-B rL .I~
~--
Species/Life Stage Mapped to Life Collected History Table Life History Table Data Justification Resources 2 Life Stage 1 Species Life Stage Threadfin YOY JUV Exact match EPRI 2012 (5-90)
Shad Threadfin Yearling And Threadfin Age 1 Exact match EPRI 2012 (5-90)
Shad Older Shad Threadfin Undetermined JUV Exact match EPRI 2012 (5-90)
Shad EPRI 2012 (5-123); EPA Warmouth Undetermined Bluegill JUV Genus match (Lepomis spp.) and of similar size 2006 (H1-7)
White EPRI 2012 (5-78);
Undetermined Channel catfish JUV Family match lctaluridae Catfish USEPA 2006 (H1-13) 1 Life stage mapping includes JUV Uuvenile), YOY (young-of-year), and Age 1. Yearling and older life stage was mapped to Ag e 1 since it was likely that fish susceptible to impingement are smaller/of younger age.
2 References :
USEPA U.S. Environmental Protection Agency (USEPA). 2006. Regiona l Benefits Analysis for the Final Section 316(b) Phase Ill Existing Facilities Rule. EPA-2006 821-R-04-007 .
EPRI 2012 Electric Power Research Institute (EPRI). 2012 . Fish Life History Parameter Values for Equivalent Adult and Production Foregone Models:
Comprehensive Update. Final Report 1023103 . Palo Alto, CA.
Duke Energy I 11 -B-4
Duke Energy Carolinas I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11 -B
- Table 11-84. Classification Assignments for Species Collected at Oconee Nuclear Station Family during Entrainment and Impingement Studies Identified Species Bluegill Scientific Name Lepomis macrochirus Classification 1 Recreational Vulnerability 2 Robust Lepomis spp. Lepomis spp. Recreational Robust Redbreast Sunfish Lepomis auritus Recreational Robust Centrarchidae Redeye Bass Micropterus coosae Recreational Robust Spotted Bass Micropterus punctulatus Recreational Robust Unidentified Sunfish Lepomis spp . Recreational Robust Warmouth Lepomis gulosus Recreational Robust Blueback Herring . Alosa aestivalis Forage Frag ile Clupeid group Clupeidae Forage Fragile Dorosoma spp. Oorosoma spp . Forage Fragile Clupeidae Threadfin Shad Dorosoma petenense Forage Fragile Unidentified egg Alosa aestiva/is Forage 3 Fragile Unidentified larvae Dorosoma petenense Forage 3 Fragile
- Cyprinidae lctaluridae Percidae 1 Classifications Golden Shiner White Catfish Flathead Catfish Blackbanded Darter Notemigonus cryso/eucas Ameiurus catus Pylodictis olivaris Percina nigrofasciata Forage Recreational Recreational Forage Robust Robust Robust Robust include forage (prey or non-game species) or recreational (harvested species taken by recreational fishing).
2 Species within the fam ily Clupeidae were considered fragile; al l other taxa were classified as robust.
3 Unidentified fish eggs were mapped to Blueback Herring , and unidentified fish larvae were mapped to Threadfin Shad (see Table 11-B2) .
- 11 -B-5
Duke Energy Carolinas I Oconee Nuclear Station CWA §316(b) Compliance Submittal L ~"'II Appendix 11 -8 r .I~
- Table 11-BS. Summary of Best Professional Judgment Decisions Made in Life History Table Compilation for Oconee Nuclear Station Biological Modeling Life History Table/Species All Species Comment When starting weights were provided in both EPRI 2004 and 2012 , values from 2012 were selected .
Equivalent age stage orders were selected based on the age of 100%
vulnerability to the fishery for recreational species, or reproductive maturity for 2 All Species forage/non-game species. Where ages of reproductive maturity differed between males and females , the age of maturity for females was selected.
r Where no median weights were available, median weight was calculated by averaging stage i and i+1 start weights . "In practice , it may be sufficient to simply 3 All Species approximate the average weight-at-death ... from the midpoint between the initial weights of successive life stages. " (EPRI 2004 pg 5-3)
Due to growth rates reaching an asymptote toward the end of life, a growth rate 4 All Species of zero was assumed for the last row in life history tables for all species Production foregone modeling was replicated to results produced in EPRI 2004 for confirmation of modeling approach . However, these calculations utilized 5 All Species Median Weight at Death and we determined that Start Weight is the appropriate metric for production foregone calculations. Therefore , all subsequent modeling efforts applied Start Weight for the production foregone modeling effort.
Where USEPA (2006) data were used, data from the Inland Region was 6 All Species selected/preferred.
Combined the life stage durations of yolk sack larvae and post yolk sac larvae 7 Blueback Herring for a single larvae life stage .
Age 2 weight was assumed to be the same as Age 1 weight since few Threadfin 8 Threadfin Shad Shad reach Age 2 and it is unlikely there is substantive change in size due to growth rates reaching an asymptote (FAO 1969).
References USEPA 2006 U.S. Environmental Protection Agency (USEPA). 2006 . Regional Benefits Analysis for the Final Section 316(b) Phase Ill Existing Facilities Rule. EPA-821-R-04-007 .
EPRI 2004 Electric Power Research Institute (EPRI) . 2004. Extrapolating Impingement and Entrainment Losses to Equivalent Adults and Production Foregone . Final Report 1008471 . Palo Alto , CA.
EPRI 201 2 Electric Power Research Institute (EPRI). 2012. Fish Life History Parameter Values for Equivalent Adult and Production Foregone Models: Comprehensive Update. Final Report 1023103. Palo Alto , CA.
FAQ 1969 Food and Agriculture Organization of the United Nations (FAO). 1969. Manual Methods for Fish Stock Assessment - Section 3. Growth. Accessed 4 March 2020. [URL]:
http://www.fao .org/3/x5685e/x5685e03.htm#section%203 .%20g rowth .
- 11 6
Duke Energy Carolinas I Oconee Nuclear Station CWA §316(b) Compliance Submittal L ~'"'II Appendix 11 -B r J~
- Table 11-86. Summary of On-screen Survival Data used to Adjust Estimated Losses for the Ristroph Screens and Fish Return System Scenario for Oconee Nuclear Station I
Biological Modeling Percent Extended Survival for all Mesh Sizes Post-Impingement No. Organisms (hours)
Larvae 0.00 0.14 0.97 0.5-4 .5 24-96 4,303 Fragile Juvenile 0.00 0.07 0.99 0.5-13 .5 24-102 8,160 Fragile Adult 0.00 0.01 0.93 0.5-13 .5 24-102 384 Robust Larvae 0.23 0.37 0.51 0.5-3 .2 24+ 65 Robust Juvenile 0.00 0.59 1.00 0.5-13.5 24-102 1,776 Robust Adult 0.68 0.76 2 <13.5 24 1 Based on the limited availability of species and life stage-specific on-screen survival data, available data were pooled and grouped by fragile or robust species for three age groups: larvae (yolk-sac larvae and post yolk-sac larvae), juvenile (JUV), adult (yearling and older) . Very little egg survival information is available, and therefore a survival rate of 100 percent was applied , which results in reduced mortalities and therefore greater estimation (i .e.,
overestimation) of benefits. 2 Median extended survival for Robust Adults was designated as 0.76 , the USEPA expected efficacy for Ristroph mod ified screens for non-fragile species based on the impingement mortality standard (79 Fed . Reg. 158, 48321) .
References used in the development of on-screen survival rates:
Electric Power Research Institute (EPRI). 2003 . Evaluating the Effects of Power Plant Operations on Aquatic Communities. Final Report 1007821 . Palo Alto , CA.
_ _ . 2004. Chapter 1. Traveling Water Screens. 1011546. Palo Alto, CA.
_ _ . 2006. Laboratory Evaluation of Modified Ristroph Traveling Screens for Protecting Fish at Cooling Water Intakes. Final Report 1013238. Palo Alto, CA.
_ _ . 2010 . Laboratory Evaluation of Fine-Mesh traveling Water Screens. Final Report 1019027. Palo Alto ,
CA.
_ _ . 2013 . Engineering and Biological Assessment of Fine Mesh Fish Protection-Modified Traveling Water Screens. Technical Update 3002001104. Palo Alto, CA .
- 11-B-7
This page intentionally left blank.
Appendix 11-C Estimated Losses and Changes in Stock and Harvest under Evaluated Entrainment Reduction
- Technologies
This page intentionally left blank.
Duke Energy Ca rolinas, LLC I Oconee Nuclear Station CWA §3 16(b} Compliance Submittal Appendix 11-C Table 11-C1 . Candidate Technology Modeling Outputs by Taxa and Life Stage for 2016 Entrainment Loss Estimates at Oconee Nuclear Station 1*2 1111111111111---1---1 Equivalent Adults (No.) Equivalent Adults (lbsJ Produclton Foregone (lbsl Harvest Foregone (lbsl Blueback Herring Eggs 1,735 300 300 45 Clupeid Group Larvae 413 413 413 11 Shad group Larvae 274 274 274 7 Lepomis spp. Eggs 40 25 25 8 5 5 <1 3 2 2 <1 Total 40 25 25 8 5 5 <1 2,423 987 987 63 3 2 2 <1
, Numbers rounded to the nearest whole number.
2Existing condition represents the current configuration of 3/8-inch coarse-mesh traveling water screens and no orga nism return system. This technology represent the losses that woul d be eliminated under the MWithout- Entra inmenr scenario. Other com pliance alternative scenarios include fine mesh screens (FMS) and mechanical draft cooling towers {MOCT).
3 Converts are defined as ichthyoplankton that would have been entrained through a 3/8-inch mesh screen but instead are impinged on a fine-mesh screen. Converts are adjusted for on-screen survival and added to the total number of mortalities (FMS Total ).
- No organisms estimated Note: mm - millimeters; lbs - pounds Table 11 -C2. Candidate Technology Modeling Outputs by Taxa and Life Stage for 2017 Entrainment Loss Estimates at Oconee Generating Station 1*2 l-l--1---1---1 Equivalent Adults (No.) Equivalent Adults (lbsl Production Foregone (lbs) Harvest Foregone (lbs)
Blueback Herring Eggs 1,517 262 262 39 Clupeid Group Larvae 1,432 989 380 1369 37 Shad Group Larvae 122 81 81 3 Unidentified Fish Eggs 92 2 Uniden@ed Fish Larvae 16 79 <1 Total 3,178 1,332 459 1,791 83 1
Numbers rounded to the nearest whole number.
2 Existing condition represents the current configuration of 3/8-inch coarse-mesh traveling water screens and no organism return system. This technology represent the losses that 'w\Ould be eliminated under the 'W'ithout-Entrainmenr scenario. Other compliance alternative scenarios include fine mesh screens (FMS) and mechanical draft cooling tov.ers (MDCTI.
3 Converts are defined as ichthyoplankton that would have been entrained through a 3/8-inch mesh screen but instead are impinged on a fine.mesh screen. Converts are adjusted for on-screen survival and added to the total number of mortalities (FMS Total).
- No organisms estimated Note: mm - millimeters; lbs - pounds Duke Energy I 11 -C1
Duke Energy Carolinas, LLC I Ocone e Nu clear Station CWA §316(b) Compliance Submittal Appe ndix 11 -C Table 11-C3. Compliance Alternative Modeling Outputs by Species and Life Stage for 2016 Impingement Loss Estimates at Oconee Nuclear Station 1*2 m1imnrnr111m111ma.1111111N1"tjrnw:tr111111N11m11111+M*H+
Equivalent Adults (No.) Equivalent Adults (lbs) Production Foregone (lbs) Harvest Foregone (lbs)
Common Name Scientific Name Blackbanded Darter Percina nigrofasciata Juvenile Blueback hening Alosa aestivalis Age 1 2,554 2,528 66 Blueback Herring Alosa aestivalis Juvenile 9 8 Bluegill Lepomis macrochirus Age 1 549 132 14 106 25 3 43 10 Bluegill Lepomis macrochirus Juvenile Flathead Catfish Pylodictis o/ivaris Juvenile 3 Golden Shiner Notemigonus crysoleucas Age 1 Redbreast Sunfish Lepomis auritus Age 1 Redbreast Sunfish Lepomis auritus Juvenile Redeye Bass Micropterus coosae Age 1 9 2 5 4 Redeye Bass Micropterus coosae Juvenile Spotted Bass M1cropterus punctu/atus Juvenile 6 2 4 2 2 Threadfin Shad Dorasoma petenense Age 1 90 89 2 Threadfin Shad Dorosoma petenense Juvenile 897 838 23 Warmouth Lepomis gulosus Juvenile White catfish Ameiurus catus Juvenile 3 Total 571 139 15 116 29 3 3,550 3,463 91 52 13 1
Numbers rounded to the nearest v.tiol e number.
2 Compliance alternative scenarios include fish-friendly Ristroph screen install ation with an organism return system (Post-lM BTA) and mechanical draft cooling towers (MDCn. Existing cond ition represents the current configuration of 3/8-inch coarse-mesh traveling water screens and no organism return system. This technology represent the losses that would be eliminated under the 'Without-Entrainment" scenario .
-- No organisms estimated Note: mm - millimeters; lbs - pounds; Post-lM BTA - post imping ement best technology avail able Duke Energy 11 1-c2
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11 -C Table 11-C4. Candidate Technology Modeling Outputs by Species and Life Stage for 2017 Impingement Loss Estimates at Oconee Nuclear Station 1*2
- -1Ai:nw:t:-ftl1Ai:.wl-Nfll'A\MlilillllllN!it\:IIIIMf:i*\51 Equivalent Adults (No.) Equivalent Adults (lbs) Production Foregone (lbs) Harvest Foregone (lbs)
Common Name Scientific Name Blackbanded Darter Percina nigrofasciata Juvenile Blueback herring Alosa aestivalis Age 1 2.546 2.520 66 Blueback Herring Alosa aestivalis Juvenile 9 8 Bluegill Lepomis macrochirus Age 1 566 136 15 Bluegill Lepomis macrochirus Juvenile Flathead Catfish Pylodictis olivaris Juvenile 3 Golden Shiner Notemiganus cryso/eucas Age 1 Redbreast Sunfish Lepomis auritus Age 1 Redbreast Sunfish Lepomis auritus Juvenile Redeye Bass Micropterus coosae Age 1 10 4 Redeye Bass Micropterus coosae Juvenile Spotted Bass Micropterus punctulatus Juvenile 6 Threadfin Shad Dorosoma petenense Age 1 88 87 Threadfin Shad Dorosoma petenense Juvenile 869 812 23 Warmouth Lepomis gulosus Juvenile White catfish Ameiuros catus Juvenile 3 Total 589 143 15 120 29 3,512 3,427 91 54 14 1 Numbers rounded to the nearest whole number.
2 Compliance alternative scenarios include fish-friendly Ristroph screen installation with an organism return system (Post-lM BTA} and mechanical draft cooling tOYvers (MDCT). Existing condition represents the current configuration of 3/8-inch coarse-mesh traveling water screens and no organism return system. This technology represent the losses that would be eliminated under the 'Without-Entrainment" scenario.
-- No organisms estimated Note: mm - millimeters; lbs- pounds; Post-lM BTA- post impingement best technology available Duke Energy I 11-C3
This page intentionally left blank.
Appendix 11-D Summary of Entrainment Mortality Reduction Benefits
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11-D 1-~~
-1 ~
Table 11-D1. Annual Entrainment Mortality Reduction Benefits Estimated for 2016 Entrainment Reduction Technologies Evaluated for Oconee Nuclear Station 1 Fine-mesh Screens Mechanical Draft Cooling Towers Common Name Blueback Herring Clupeid Group2 1.---
Egg Larvae t "
t 27 ,555,903 I ,.
- I .,
- 1,435
. . t ,.
32,457,009 1,335,698
.t I ..
- I *
- 1,690 402 Shad Group 3 Larvae 888,022 267 Sunfish Species Larvae 185,105 15 3 482 ,710 39 8 3
' Numbers were not rounded .
2Clupeid Group - Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad 3Shad Group - Gizzard Shad/Threadfin Shad
- No organisms estimated ; lbs - pounds Table 11 -D2. Annual Entrainment Mortality Reduction Benefits Estimated for 2017 Entrainment Reduction Technologies Evaluated for Oconee Nuclear Station 1 Fine-mesh Screens Mechanical Draft Cooling Towers Common Name Blueback Herring Clupeid Group 2 1.---
Egg Larvae 24,081,150 208,381 1,254 63 28,364,234 4,633,720 1,477 1,395 Shad Egg 1,015,349 41 2,966,849 Group3 Unidentified Larvae 43,073 13 296,485 89 Osteichthyes 4 Unidentified Egg 304,995 16 297,065 15 Osteichthyes4
' Numbers were not rounded .
2Clupeid Group - Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad 3
Shad Group - Gizzard Shad/Threadfin Shad 4 Unidentified larvae were assumed to be Threadfin Shad and unidentified eggs were assumed to be Blueback Herring (see Append ix 11 -B)
-- No organisms estimated ; lbs - pounds Duke Energy I 11 -D-1
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal 1-)"\
Appendix 11 -D ~
Table 11-D3. Annual Change in Recreational Yield Under the Without Entrainment Scenario Based 2025 on 2016 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Without Entrainment Scenario Bluegill3 0.0 Smallmouth Bass 4 0.0 2026 0.0 0.0 2027 0.0 0.0 2028 0.0 3.6 2029 2.9 5.0 2030 3.7 5.7 2031 3.8 5.9 2032 3.9 5.9 2033 3.9 5.9 2034 3.9 5.9 2035 3.9 5.9 2036 3.9 2.3 2037 1.0 0.9
- 2038 2039 2040 2041 0.1 0.0 0.0 0.0 0.2 0.1 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass .
2Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3 Represents Lepomis species collected in entrainment samples at Oconee in 2016.
4Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass .
Duke Energy I 11 -D-2
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L "\""}
Appendix 11-0 r .I~
Table 11-D4. Annual Change in Recreational Yield Under the Mechanical Draft Cooling Tower 2025 Scenario Based on 2016 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Mechanical Draft Cooling Tower Scenario BluegilP 0.0 Smallmouth Bass 4 0.0 2026 0.0 0.0 2027 0.0 0.0 2028 0.0 3.5 2029 2.8 4.9 2030 3.6 5.6 2031 3.7 5.7 2032 3.8 5.8 2033 3.8 5.8 2034 3.8 5.8 2035 3.8 5.8 2036 3.8 2.3 2037 0.9 0.9
- 2038 2039 2040 2041 0.1 0.0 0.0 0.0 0.2 0.1 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass.
2 Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3 Represents Lepomis species collected in entrainment samples at Oconee in 2016.
4 Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass.
Duke Energy 111 3
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L "'\~
Appendix 11 -D r .I~
Table 11-05. Annual Change in Recreational Yield Under the Fine-mesh Screen Scenario Based on 2023 2016 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Fine-mesh Screen Scenario BluegilP 0.0 Smallmouth Bass 4 0.0 2024 0.0 0.0 2025 0.0 0.0 2026 0.0 2.1 2027 1.4 3.0 2028 1.8 3.4 2029 1.9 3.5 2030 1.9 3.5 2031 1.9 3.5 2032 1.9 3.5 2033 1.9 3.5 2034 1.9 3.5 2035 1.9 3.5
- 2036 2037 2038 2039 1.9 0.5 0.1 0.0 1.4 0.5 0.1 0.0 2040 0.0 0.0 2041 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 1Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass.
2Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3 Represents Lepomis species collected in entrainment samples at Oconee in 2016.
4Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass .
Duke Energy I 11 4
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11 -D
- Table 11-D6. Annual Change in Recreational Yield Under the Fine-mesh Screen with Cooling Water Intake Structure Expansion Scenario Based on 2016 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Fine-mesh Screen with Cooling Water Intake
- 2025 2026 2027 Bluegill 3 0.0 0.0 0.0 Structure Expansion Scenario Smallmouth Bass 4 0.0 0.0 0.0 2028 0.0 2.1 2029 1.4 3.0 2030 1.8 3.4 2031 1.9 3.5 2032 1.9 3.5 2033 1.9 3.5 2034 1.9 3.5 2035 1.9 3.5 2036 1.9 1.4 2037 0.5 0.5 2038 0.1 0.1 2039 0.0 0.0
- 2040 2041 2042 2043 2044 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1
Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass.
2Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3 Represents Lepomis species collected in entrainment samples at Oconee in 2016.
4 Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass .
- Duke Energy I 11-D-5
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L Ill\~
Appendix 11 -D r .I~
Table 11 -D7. Annual Change in Recreational Yield Under the Without Entrainment Scenario Based 2025
~----
on 2017 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Without Entrainment Scenario Bluegill3 0.0 Smallmouth Bass 4 0.0 2026 0.0 0.0 2027 0.0 0.0 2028 0.0 5.0 2029 0.0 7.0 2030 0.0 7.9 2031 0.0 8.1 2032 0.0 8.2 2033 0.0 8.2 2034 0.0 8.2 2035 0.0 8.2 2036 0.0 3.2 2037 0.0 1.2 2038 0.0 0.3 2039 0.0 0.1 2040 0.0 0.0 2041 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass .
2 Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3No Lepomis species were collected in 2017 entrainment samples at Oconee .
4 Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass .
- Duke Energy I 11 -D-6
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal Appendix 11-D
- Table 11-D8. Annual Change in Recreational Yield Under the Mechanical Draft Cooling Tower Scenario Based on 2017 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Mechanical Draft Cooling Tower Scenario Bluegill3 Smallmouth Bass 4 2025 0.0 0.0 2026 0.0 0.0 2027 0.0 0.0 2028 0.0 4.8 2029 0.0 6.8 2030 0.0 7.7 2031 0.0 7.9 2032 0.0 7.9 2033 0.0 8.0 2034 0.0 8.0 2035 0.0 8.0 2036 0.0 3.1 2037 0.0 1.2
- 2038 2039 2040 2041 0.0 0.0 0.0 0.0 0.3 0.1 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1Total Number of Equivalent Ad ults includes direct changes in recreational fish stock and indirect cha nges through troph ic transfer of forage stock biomass .
2 Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station, presented in Section 11 of the Oconee comp liance submittal document.
3No Lepomis species were collected in 2017 entrainment samples at Oconee .
4Surrogate recreational predator species to demonstrate indirect yield change benefits acquired th rough trophic transfer of fo rage stock biomass.
Duke Energy I 11-D-7
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal L "'\""
Appendix 11 -D r .I~
Table 11-09. Annual Change in Recreational Yield Under the Fine-mesh Screen Scenario Based on 2023 2017 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Fine-mesh Screen Scenario
.-------- 0.0 Bluegill3 Smallmouth Bass 4 0.0 2024 0.0 0.0 2025 0.0 0.0 2026 0.0 2.2 2027 0.0 3.0 2028 0.0 3.4 2029 0.0 3.5 2030 0.0 3.6 2031 0.0 3.6 2032 0.0 3.6 0.0 3.6 0.0 3.6 2035 0.0 3.6
- 2036 2037 2038 2039 0.0 0.0 0.0 0.0 1.4 0.5 0.1 0.0 2040 0.0 0.0 2041 0.0 0.0 2042 0.0 0.0 2043 0.0 0.0 2044 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 1 Tota l Number of Equivalent Adults includes direct changes in recreational fis h stock and indirect changes through trophic transfer of forage stock biomass.
2Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated useful life of the station , presented in Section 11 of the Oconee compliance submittal document.
3No Lepomis species were collected in 2017 entrainment samples at Oconee.
4 Surrogate recreationa l predator species to demonstrate indirect yie ld change benefits acquired thro ugh trophic transfer of forage stock biomass .
Duke Energy I 11-D-8
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal I-."\'"\
Appendix 11 -D -
- Table 11-D10. Annual Change in Recreational Yield Under the Fine-mesh Screen with Cooling Water Intake Structure Expansion Scenario Based on 2017 Entrainment Losses at Oconee Nuclear Station 1 Equivalent Adult 1 Total by Year for the Fine-mesh Screen with Cooling Water Intake Structure Ex ansion Scenario Bluegill3 Smallmouth Bass 4 2025 0.0 0.0 2026 0.0 0.0 2027 0.0 0.0 2028 0.0 2.2 2029 0.0 3.0 2030 0.0 3.4 2031 0.0 3.5 2032 0.0 3.6 2033 0.0 3.6 2034 0.0 3.6 2035 0.0 3.6 2036 0.0 1.4 2037 0.0 0.5 2038 0.0 0.1 2039 0.0 0.0
- 2040 2041 2042 2043 2044 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2045 0.0 0.0 2046 0.0 0.0 2047 0.0 0.0 2048 0.0 0.0 2049 0.0 0.0 2050 0.0 0.0 1 Total Number of Equivalent Adults includes direct changes in recreational fish stock and indirect changes through trophic transfer of forage stock biomass.
2Anticipated time frame for benefits to accrue under the Without-Entrainment Scenario based on technology implementation date and anticipated usefu l life of the station , presented in Section 11 of the Oconee compliance submittal document.
3 No Lepomis species were collected in 2017 entrainment samples at Oconee.
4Surrogate recreational predator species to demonstrate indirect yield change benefits acquired through trophic transfer of forage stock biomass .
- Duke Energy I 11 -D-9
This page intentionally left blank.
Appendix 11-E Entrainment Reduction Benefits Study: Oconee Nuclear Station
This page intentionally left blank.
- Entrainment Reduction Benefits Study:
Oconee Nuclear Station Final Report Prepared for:
Duke Energy Carolinas, LLC
- Prepared by:
Veritas Economic Consulting August 2020 1851 Evans Road Cary, NC 27513 VERITAS
- Office: 919.677.8787 Fax: 919.677.8331 Economic Consulting VeritasEconomics.com
Entrainment Reduction Benefits Study: Oconee August2020
- Section 1.
Table of Contents Overview and Results .............................................................................................1 1.1 § 122.21 (r)(11)(i): Incremental Changes in Fish .......................................................... 1 1.2 § 122.21 (r)(11)(ii): Description of Changes in Stock or Harvest Levels ...................... .4 1.3 § 122.21 (r)(11)(iii): Description of Monetized Values of Recreational and Forage Species ...........................................................................................................13 1.3.1 Recreational Benefits ...................................................................................... 13 1.3.2 Non use Benefits .............................................................................................. 18 1.4 Summary of Benefits ...................................................................................................19 1.5 Report Organization ....................................................................................................21
- 2. Methodological Overview .....................................................................................22 2.1 Methods ...................................................................................................*................... 22 2.2 Recreational Benefits Overview ..................................................................................26 2.3 Non use Benefits ..........................................................................................................29 2.3.1 Non-Economic Methods ..................................................................................30 2.3.2 Rule-of-Thumb Method ...................................................................................32 2.3.3 Hypothetical Scenario Survey Methods ..........................................................32 2.3.4 Evaluating the Applicability of Quantitative Methods for Estimating Non use Benefits for Entrainment Reduction at Oconee .................................. 37 2.3.5 Qualitative Evaluation of Nonuse Benefits for Entrainment Reduction at Oconee ........................................................................................................38
- 3. Baseline Recreational Fishing Conditions .................... :....................................40 3.1 Angler Preferences .....................................................................................................40 3.2 Angler Participation: Population Size and Annual Fishing Trips ............................... .41 3.3 Angling Sites ........................ :......................................................................................42 3.4 Calibrated Baseline Trips and Expected Catch .......................................................... .43 3.5 Future Baseline Fishing Participation, Trips, and Site Quality ................................... .43
- 4. Modeling and Valuing Changes in Recreational Yield .......................................44 4.1 Valuing Changes in Recreational Yield ...................................................................... .44
- 5. References .............................................................................................................48 Appendix A Fishing Sites and Characteristics of Sites ............................................54
- VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020
- Figure Figure 1.1:
Figure 1.2:
List of Figures Change in Recreational Yield with Technology Installation ...................................... 5 Direct Changes in Recreational Fish Stocks as Equivalent Adults with Elimination of Entrainment at Oconee ......................................................................7 Figure 1.3: Direct Changes in Forage Stocks as Biomass (pounds) with Elimination of Entrainment at Oconee ............................................................................................8 Figure 1.4: Trophic Transfer Based* Changes in Pounds of Biomass with Elimination of Entrainment at Oconee .......................................................................................... 1O Figure 1.5: Total (Direct and Indirect) Changes in Recreational Yield with Elimination of Entrainment at Oconee ..........................................................................................12 Figure 1.6: Location of Sites with Affected Catch Rates, Location of Substitute Sites, and the Concentration of Anglers ........................................................................... 14 Figure 1. 7: Change in Expected Catch per Trip by Species in Lake Keowee .......................... 16 Figure 1.8: Estimated Trip Change with Elimination of Entrainment at Oconee ....................... 17 Figure 1.9: Change in Welfare with Elimination of Entrainment at Oconee .............................. 18 Figure 2.1: Aerial View of Oconee ............................................................................................23 Figure 2.2: Overview of Methodology for Estimating the Benefits of Entrainment Reductions 25 Figure 2.3: Example of the Choice Question Format in the Stated-Preference Survey ........... 35
- Figure 4.1: Example Site Demand Curve and Consumer Surplus .......................................... .45 Figure 4.2: Increase in Consumer Surplus from Increase in Catch Rates .............................. .46 List of Tables Table Table 1.1 Oconee: Annual Impingement ......................................................................................2 Table 1.2 Oconee: Total Entrainment, 2016 .................................................................................3 Table 1.3 Oconee: Total Entrainment, 2017 .................................................................................3 Table 1.4 Affected Population, Trips, and Sites included in the Recreation Angling Demand Model .......................................................................................................15 Table 1.5 Timing Specified for Benefits Modeling of Feasible Technologies at Oconee ............. 20 Table 1.6 Summary of Recreational Social Benefits of Entrainment Reduction Alternatives at Oconee ...............................................................................................................20 Table 3.1 Coefficients from the Bingham et al. (2011) Model .................................................... .41 Table 3.2 Conditions of Lake Keowee Affected Sites ................................................................. .42 Table A.1 Site Characteristics of Lake Keowee and Substitute Fishing Sites ............................. 55
- ii VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020
- 1. Overview and Results The U.S. Environmental Protection Agency's (EPA's) 2014 Section (§) 316(b) Rule (79 Fed. Reg. 158, 48300-48439) (Rule) requires that applicants submit studies of technologies or operational measures that can reduce entrainment (USEPA 2014a). The studies must discuss cost, feasibility, impact, and social costs and benefits of technologies including cooling towers, 2-millimeter (mm) or smaller screens, and water reuse or alternative water sources
(§ 122.21 (r)(10)(i-iii) and § 122.21 (r)(11 )(i-vi)). The Benefits Valuation Study presents the benefits of each technology and must include the following elements as defined in 79 Fed. Reg.
158, 48428 (r)(11):
(i) Incremental changes in the numbers of individual fish and shellfish lost due to impingement mortality and entrainment as defined in 40 CFR 125.92, for all life stages of each exposed species; (ii) Description of basis for any estimates of changes in the stock sizes or harvest levels of commercial and recreational fish or shellfish species, or forage fish species; (iii) Description of basis for any monetized values assigned to changes in the stock size or harvest levels of commercial and recreational fish or shellfish species, forage fish, and to any other ecosystem or nonuse benefits; (iv) A discussion of mitigation efforts completed prior to October 14, 2014 including how long they have been implemented and level of effectiveness; (v) Discussion, with quantification and monetization where possible, of any other benefits expected to accrue to the environment and local communities, including but not limited to improvements for mammals, birds, and other organisms and aquatic habitats; and (vi) Discussion, with quantification and monetization where possible, of benefits expected to result from any reductions in thermal discharges from entrainment technologies.
This report contains the results, data, and methods for estimating the fishing benefits associated with entrainment reductions at Oconee Nuclear Station (Oconee). The remainder of this Overview and Results section summarizes the data, methods, and results for the
§ 122.21 (r)(11 )(i)-(iii) requirements listed above.
1.1 § 122.21(r)(11)(i): Incremental Changes in Fish Table 1.1 demonstrates the level of impingement occurring at Oconee based on impingement data collected from September 2006 to August 2007 (ASA 2008) and scaled to actual intake flow (AIF) from January 1, 2016 to December 31, 2017 (HOR 2020). The table also provides the reduction in impingement mortality for all species and life stages of fish and shellfish that would occur with 100 percent reduction of Oconee's impingement. The incremental change
- 1 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 data for impingement also identifies species based on their economic and ecological classification (i.e., forage, recreational, and commercial) in the fishery.
Table 1.1 Oconee: Annual Impingement 2016 AIF 2017 AIF Classification Threatened or Common Name Juvenile Age 1 Total Juvenile Age 1 Total Forage Commercial Recreational Endangered Threadfin Shad 32,122 1,673 33,795 31,122 1,621 32,743
- No Blueback Herring 911 9,694 10,605 908 9,664 10,572
- No Bluegill 298 1,046 1,344 308 1,079 1,387
- No Spotted Bass 253 253 252 252
- No Redbreast Sunfish 55 147 202 58 146 204
- No Redeye Bass 43 27 70 43 30 73
- No Warmouth 50 50 50 50
- No Blackbanded 41 41 41 41
- No Darter White Catfish 31 31 31 31
- No Flathead Catfish 30 30 28 28
- No Golden Shiner 16 16 18 18
- No Total 33,834 12,603 46,437 32,841 12,558 45,399 Sources: HOR (2020); South Carolina Wildlife Federation (2019); U.S. Fish and Wildlife Service (2019)
Annual ichthyoplankton entrainment was estimated for 2016 and 2017 based on entrainment sampling data collected at Oconee from March 1 through October 31, 2016 and from March 1 through October 31, 2017 (HOR 2018) and AIF data based on Oconee operations in 2016 and 2017. Tables 1.2 and 1.3 present the estimates of annual entrainment and the classification of species as forage, recreationally harvested, or threatened or endangered. 1 No threatened or endangered species were entrained at Oconee during the study period. Species of all classifications were incorporated into modeling efforts to evaluate the influence entrainment reduction technologies may have on fish groups representing different ecological and economic roles.
1 The State of South Carolina allows commercial fishing for shad and herring in Lake Keowee, but there are no reports of anyone harvesting fish commercially from the lake (South Carolina Department of Natural Resources Marine Resources Division 2019). Therefore, no commercial benefits are estimated .
- 2 VERITAS Economic Consulting
- Entrainment Reduction Benefits Study: Oconee
- Table 1.2 August 2020 Oconee: Total Entrainment, 2016 Classification Threatened or Taxa Eggs Larvae Taxa Total Forage Commercial Recreational Endangered Blueback Herring 33,323,418 33,323,418
- No Clupeid Group 8 1,371,354 1,371,354
- No Shad Groupb 911,727 911,727
- No Sunfish Species 495,596 495,596
- No Total 33,323,418 2,778,677 36,102,095
- Clupeid Group: Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad b Shad Group: Gizzard Shad/Threadfin Shad Sources: HOR (2020); South Carolina Wildlife Federation (2019); U.S. Fish and Wildlife Service (2019)
Notes: Entrainment numbers based on March 1 through October 31, 2016 entrainment sampling and 2016 AIF (HOR 2018).
Table 1.3 Oconee: Total Entrainment, 2017 Classification Threatened or Taxa Eggs Larvae Taxa Total Forage Commercial Recreational Endangered Blueback Herring 29,121,391 29,121,391
- No Clupeid Group 8 4,757,413 4,757,413
- No Shad Groupb 3,046,046 3,046,046
- No Unidentified Fish 304,995 304,400 609,395
- No Total 32,472,432 5,061,813 37,534,245
- Clupeid Group: Blueback Herring/Alewife/Gizzard Shad/Threadfin Shad b Shad Group: Gizzard Shad/Threadfin Shad Sources: HOR (2020); South Carolina Wildlife Federation (2019); U.S. Fish and Wildlife Service (2019)
Notes: Entrainment numbers based on March 1 through October 31, 2017 entrainment sampling and 2017 AIF (HOR 2018). All species entrained in 2017 are considered forage species.
VERITAS 3 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2O20
- 1.2 § 122.21(r)(11)(ii): Description of Changes in Stock or Harvest Levels Differences between With-Entrainment (baseline) and Reduced-Entrainment (i.e., with a technology installed) conditions are used to quantify the benefits of entrainment reduction technologies by modeling fishery stocks. This is accomplished by creating age-structured transition (i.e., Leslie) matrices (Leslie 1945, 1948; Caswell 2001) that characterize the survival rates by age of modeled stocks. The Leslie matrix model is frequently used in fisheries management and has traditionally been an important component of best professional judgment (BPJ) §316(b) assessments under 1977 draft guidance (Akgakaya et al. 2002; Public Service Electric and Gas Company 1999; USEPA 2002). These dynamic matrix models are populated with survival rates and weights-at-age, simulated through the remaining useful plant life to identify changes in fish stocks (based on ecological or economic use classifications: forage, commercial, or recreational) with each evaluated technology.
Figure 1.1 provides an illustrative depiction of the results of the benefits valuation process with notes on interpreting the subsequent figures presented throughout this section. The figure shows the estimated difference between With-Entrainment (baseline) and Reduced-Entrainment conditions. This difference shows how much greater recreational yield would be under Reduced-Entrainment conditions than under baseline conditions. 2 The change in recreational yield is
- shown for a technology that becomes operational in 2024 (illustrated by the first arrow) and remains operational until the plant is scheduled to shut down under baseline conditions (2043 as indicated by the second arrow). Over this time period, the figure shows the general pattern of increasing recreational yield change that would occur from baseline conditions to under Reduced-Entrainment conditions and then cease to occur once the plant is retired or ceases operation.
The figure depicts the recreational yield changes for two species. Species A is recruited to the fishery quickly and has a relatively short lifespan-approximately six years. Species B is recruited to the fishery more slowly and has a longer lifespan-approximately 25 years. For both species, although entrainment is reduced in 20.24, the juveniles that are spared are not yet eligible to be caught in 2024; therefore, there is no increase in yield.
- In 2025, the juveniles of Species A that were not entrained in 2024 become vulnerable to fishing gear and there is an increase in yield of 32 fish for Species A.
2 For expositional purposes, Figure 1.1 presents the metric of recreational yield. The concepts described in the text accompanying Figure 1.1 can also be applied to the additional metrics presented throughout this section including number of recreational adults, forage species biomass, change in expected catch, change in number of trips, and welfare difference .
VERITAS 4 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- In 2026 , additional juveniles of Species A become vulnerable to fishing gear.
However, the change in yield for Species A does not double from 2025 to 2026 because the fish caught in 2025 and those that died naturally are removed from the fishery. Thus , the yield of Species A increases to 43 , consisting of:
- 32 one-year-olds that were not entrained in 2025; and
- 11 two-year-olds that were not entrained in 2024.
- In 2027, the yield of Species A increases by a total of 47 , consisting of:
- 32 one-year-olds that were not entrained in 2026;
- 11 two-year-olds that were not entrained in 2025; and
- 4 three-year-olds that were not entrained in 2024.
80
!?
3 I ____ I 1 ____
'"O 70 I
_) v-i:
-; 60 \
I \
3 0" 60
.Cl C 40 r l \ \
.c I I I \ \
0
'"O 30
> "'"""'" T I Baseline Plant \
Closure 2043
\
'"'" ~;
-; 20 C
-....., I \ "\
r~
0 10
.c.>
I \ \ r---.......
a: 0 2015 2020 2025 2030 2035 2040 2045 2050 2055 Time(years)
Recreational Species
... Species A ,._ Species B V,rita:J-(1161 V ERITAS Change in Recreational Yield Figure 1.1: Change in Recreational Yield with Technology Installation As the fishery evolves, the yield of Species A reaches a steady state around 2030 when the fish not entrained in 2024 have either been caught or have died naturally and are no longer part of the fishery. This steady state continues one year past the scheduled baseline plant closure in 2043. After 2043, there is no difference between With- and Reduced-Entrainment Conditions because the plant is scheduled to cease operations. The 32 recru its to the fishery that would not have been entrained in 2044 with the technology in operation are no longer included in the analysis because the plant is no longer operating ; therefore , the increase in recreational yield change starts to decline (15 caught fish in 2045) .
VERITAS 5 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 In 2046, only fish spared before 2043 are caught (i.e. , age three and older) , reducing the change in recreational yield further (five fish in 2046) . This decline in the recreational yield change continues until there are no more fish in the fishery that have a maximum lifespan of six years and would have otherwise been entrained in 2043. Yield changes for Species B are similar; however, the curve has a slightly different position because Species B takes two years longer to be recruited to the fishery and lives longer. As a result, Species B yield changes begin in 2026, do not begin to drop off until 2047, and take longer to dissipate than Species A.
The results in Figure 1.1 are presented for one year of entrainment data . The following figures presented throughout this section depict results using two years of entrainment data (2016 and 2017). The simulated model results using each year are presented individually so the effects that interannual variation have on each component of the benefit estimation process are transparent.
Presenting the results for the multiple entrainment reduction technologies being considered at Oconee adds additional complexity to the benefit reduction figures and makes them difficult to interpret. To simplify interpretation of the benefits figures , a Without-Entrainment scenario (i .e., a 100 percent elimination of entrainment) is used to demonstrate the maximum potential entrainment reduction benefit achievable at Oconee. A summary of the estimated
- benefits of each entrainment reduction technology evaluated for Oconee are presented in Table 1.6 at the end of this section.
Figure 1.2 depicts the estimated changes in fish stocks expected for recreational species (i. e., Sunfish Species) in Lake Keowee that would occur with the elimination of entrainment at Oconee.
Monetizing impacts to forage species is accomplished by converting them to an equivalent number and biomass of recreational and commercial species via the "trophic-transfer" method, detailed in the Electric Power Research Institute (EPRI) document "Extrapolating Impingement and Entrainment Losses to Equivalent Adults and Production Foregone" (EPRI 2004) . As typically applied , this approach multiplies adult equivalent forage biomass (i.e ., production forgone) by a conversion factor to identify changes in higher trophic level species that are recreationally and commercially valuable. Figure 1.3 depicts the adult equivalent forage biomass for the forage species entrained at Oconee. The top panel of Figure 1.3 presents the results using 2016 entrainment data, and the bottom panel presents the results using the 2017 entrainment data .
- 6 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- ~
"O
<(
"iij 20 18 16 14
{
I v-C:
.Q 12 iii Cl) 0 10 Cl) 0::
0 Cl)
.0 8
6 E l
- , 4 z
2 \
I
\_
0 2020 2025 2030 2035 2040 2045 2050 Time (years)
Entrainment Year
- 20 16 ... 2017 Recreational Species (Sunfish Species) V E R IT AS Economic Conaultlng Figure 1.2: Direct Changes in Recreational Fish Stocks as Equivalent Adults with
- Elimination of Entrainment at Oconee
- 7 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
-0 C
0 Panel A: 2016 1800 1600 1400 I ll--"""
\
0.
,,,,,, 1200 I \
cu E 1000 I \
/--
0 iii
,,, 800 \ -- - *--
QI i3 QI 600 \
0.
(/)
QI 400 I \
0) cu 0 200 I ~ (\ \
u.
1// ~~
0 2020 2025 2030 2035 2040 2045 2050 Time (years)
Forage Species
-- Clupeld Group -+- Unidentified Fish (larvae) - Unidentified Fish (egg)
... Shad Group Blueback Herring Panel B: 2017 1600
'ii,
1
-0 C
1400 0
E; 1200 - - - - - ---*--- - -- - - t-- - - --- --
cu E
0 iii
~
0 QI 0.
(/)
1000 800 - - - - - - -
600 400
---f-I
+---
\
I \
QI 0) cu 0 200 - --* I- - - --- -
u.
0 2020 2025 I~
2030 2035
~ -"-- 2040 2045 2050 Time (years)
Forage Species
-- Clupeld Group -+- Unidentified Fish (larvae) - Unidentified Fish (egg)
... Shad Group Blueback Herring Forage Species VERI T AS Economic Consu lting Figure 1.3: Direct Changes in Forage Stocks as Biomass (pounds) with Elimination of Entrainment at Oconee
- 8 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 The approach of directly converting forage fish biomass to recreational and commercial fish biomass has had some important advantages in the historical §316(b) regulatory context by providing a method of "accounting for" all entrained species. However, the trophic-transfer method is straightforward to implement and simplifies the complexity of predator-prey relationships of actual food webs. Under the 2014 Rule's peer-review requirement, it is important to recognize the deficiencies of this approach. Primarily, the trophic-transfer approach interprets observed average biomasses at different trophic levels (i.e., 10-to-1 forage to predator) as causal without meaningful foundations for doing so and in the face of extensive information that indicates otherwise (Pauly and Christensen 1995; Zhao et al. 2013; Madenjian et al. 1996). Perhaps the most glaring issue with this approach is its inconsistency with the estimates developed for recreational and commercial species. In particular, this approach assumes that populations of harvestable species are limited by fishing pressure (humans) , as opposed to resource limitations (forage availability). Moreover, if forage constraints do limit populations of higher trophic levels, consistency would require considering that some or all of the increased stocks implied by the reduced entrainment such as those depicted in Figure 1.2 would consume the increase in forage biomass. Unlike complex, food-web based considerations this concern about the trophic-transfer approach is a simple one of consistency and the avoidance of double counting within a benefits
- analysis. With these concerns recognized , the trophic-transfer approach is applied . Figure 1.4 depicts trophic transfer-based changes to predator stock as a result of the changes in forage biomass (in pounds) .
- 9 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 'iii' "C
C Panel A: 2016 45 40
/-
0
.e: 35 1-- - - -
VI
~-
0 30 I \
QI C.
1/)
25 I \
QI C) 20 0
II.
E 15 I \
-e.,,
VI VI 10 I
I
\
\
E 5
.Q
!O 0
1/ ~ \._
2020 2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
... Sunfish Species ... Alabama Bass Panel B: 2017
'iii' 70 ------ ---7-----1 ---- ..------- -
"C C
g 60 ...--
a.
.5! 50
/ \
0 QI a.
II) 40 I \
QI 0
C) 30 f \
I
-\l II.
E e
VI VI 20 -
10 I
~
E in 0
0 j
2020 2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
... Sunfish Species ... Alabama Bass Biomass from Forage Species VERITAS Economic Consulting Figure 1.4: Trophic Transfer Based Changes in Pounds of Biomass with Elimination of Entrainment at Oconee
- 10 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 To identify the yield changes associated with changes in stocks, harvest rates are applied to stock changes. When possible, these harvest rates are based on fishery stock assessments of the source waterbody. When stock-specific recreational harvest rates are not available, they are developed based on species-specific harvest rates provided in the literature (USEPA 2006; EPRI 2004, 2012a) with adjustments based on BPJ . Figure 1.5 depicts the estimated recreational yield changes in number of fish for the recreational species impacted by entrainment at Oconee .
- 11 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- l
- i
-0 c.
Panel A: 2016 6 ,-- - - - - - - , - - - - - ~~==-==-===i- - - - - - ~ - - - - - - , - - - - - - ,
5 +--- - - - - _ _ ,
~
- i 4 -- - - --+-----1--
C"
~
Cl
~ 3 -t--- - - - - - - - - + - - ----+-- +-- + - - - - - - - - - - < f - -,-+-- - - - - + - - - - - - - + - - - - - - ~
.c u
2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
,._ Sunfish Species .. Alabama Bass Panel 8: 2017 9
i
- i 8 "0
- c. / I -
---/-
7 iii
- i 6 ~- - - - - * - - - --- - - * - - - --- ---
C"
~-
~
. 5 Cl
.c 0
C 4 1 \
"0
-.; 3 I \
iii C 2 I \
I 0
i
.e u
\
0::
0 j "'----
2020 2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
,._ Sunfish Species ... Alabama Bass Recreational Yield VERI T AS Economic Consulting Figure 1.5: Total (Direct and Indirect) Changes in Recreational Yield with Elimination of Entrainment at Oconee
- 12 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 1.3 § 122.21{r){11){iii): Description of Monetized Values of Recreational and Forage Species Estimating the benefits of entrainment reductions requires assessing the relationship between entrainment, fish stock changes , and the impact that fish stock changes may have on people . For instance, this includes understanding how Oconee's entrainment affects recreational fishing catch rates and how that affects angler well-being.
To evaluate these relationships, a site-choice simulation is used to evaluate the effects that entrainment losses have on recreational fisheries. The analysis modifies site catch estimates to generate recreational catch that could occur with entrainment reductions and then estimates the economic value of catch rates by linking them to models of recreational angling demand presented in Bingham et al. (2011) .
HOR developed the models used to generate age-structured changes in stock using survival parameters and provided them to Veritas (HOR 2020). These are linked to the site-choice simulation model through fishery-specific catch and effort rates . This forms a bio-economic equilibrium (i.e. , yield , trips, and expected catch are integrated) for the With-Entrainment representation of the Lake Keowee fishery expected to be affected by entrainment at Oconee.
The integrated partial equilibrium models are used to simulate conditions under With-Entrainment
- (baseline) and Reduced-Entrainment conditions, and the monetized welfare differences between these two conditions determine the benefits of entrainment reductions. As described in USEPA's Guidelines for Preparing Economic Analysis, equilibrium modeling using the With- and Without-Impact (or reduced-impact) approach is central to all sound benefit estimation processes and regulatory impact analysis (USEPA 2016).
1.3.1 Recreational Benefits Changes in yield could occur at recreational sites throughout Lake Keowee . These sites are aggregated into the affected sites illustrated by the red circles in Figure 1 .6. Figure 1.6 also shows the estimated angling population to be most likely affected by changes in Oconee's entrainment. The affected population is specified to be those anglers residing in the counties located within 50 miles of affected sites. Figure 1.6 also illustrates sites where anglers can fish that are not affected by Oconee's entrainment ("substitute sites"). The substitute sites are generally within 100 miles of the affected sites. Table 1.4 summarizes the data on anglers , trips, and sites illustrated in Figure 1.6 and used to develop the site-choice simulation of recreational angling demand .
- 13 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- D n I N.lllo nel:
f p***f Lo nn ,
Ccwbin e
Oconee Nuclear Station C r.11 1110 OI C OJtY III~ ** Senec Clemson
~
L*-
1-.orm t.b es11111e "1178 9,£6~
.,., ~ l:rj
... M rl tt rid l _ _ _ _
- oowe llfl311 olun JJIJ
~
, _37811 L .,. ,er e\'1 1~
1' U I
~
., 0 12.5 25 50 Miles CARO NA Atlant a 8!l() ff
~
~'f<, I I Legend e Affected Sites ,......
A Substitute Sites Area Number of Anglers Residing in Each ZIP Code Enlarged 1-500 Above 501-1 ,000 1,001 -2,000 2,001 -3,000 Angling Population and Sites VER IT AS 3,001+ at Oconee Nuclear Station Econom ic Consutting Figure 1.6: Location of Sites with Affected Catch Rates, Location of Substitute Sites, and the Concentration of Anglers
- 14 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 Table 1.4 Affected Population, Trips, and Sites included in the Recreation Angling Demand Model Data Components Estimate Total Number of ZIP Codes in Affected Population a 221 Total Population Residing in Affected ZIP Codes b 2,333 ,882 Total Anglers Residing in Affected ZIP Codes c 224,071 Total Annual Fishing Days by Anglers in Affected ZIP Codes c 3,982,970 Number of Modeled Fishing Sites 53 Total Annual Fishing Days by Affected Population to Modeled Sites ct 1,568,362 Number of Affected Sites 16 Total Annual Fishing Days to Affected Sites e 94,891 Sources and Notes:
The analysis specifies the affected population as those anglers residing in counties within 50 miles of affected sites.
ZIP Code population is from the 2018 American Community Survey (ACS) (U.S . Census Bureau 2019) .
The estimate of the total anglers in the affected population is developed from the U.S. Fish and Wildlife Service's 20 11 National Survey of Fishing , Hunting , and Wildlife-Associated Recreation for Georgia , North Carolina and South Carolina ; the 2010 U.S.
Census; and the 2018 ACS (USFWS 2013a, 2013b , 2013c; U.S. Census Bureau 2019) . The analysis uses the 2010 Census population for Georgia, North Carolina, and South Carolina and the 2011 estimate of the total number of resident non-Great Lakes freshwater anglers from the 2011 USFWS to estimate the percentage of the population that are anglers (7.91 % [GA), 10.58% [NC),
9.56 [SC]) . The analysis applies this percentag e to the 2018 ACS population in the affected ZIP Codes. To develop the estimate of total angling days , the analysis applies the average number of days that these anglers spend fishing non-Great Lakes freshwater sites from the 2011 USFWS (11 days [GA], 16 days [NC), 20 days [SC]) to the number of anglers residing in the affected ZIP Codes.
While the model accounts for all of the anglers in the affected population , it does not account for all of the sites where they can take their fishing trips. Therefore, not all of their trips are included in the model. The analysis uses annual trip information that is available for each site in the model to determine the total number of modeled trips (39.38% of affected population's total trips).
The estimated number of total angling days to Lake Keowee is developed from the following publicly available sources: Schmitt and Hornsby (1985)
Figure 1.7 presents the change in the expected catch per unit effort (i.e., catch per trip) of each recreationally harvested species at Lake Keowee .
- 15 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- C:
j!:
Panel A: 2016 0.00007 0.00006 GI C.
.s::.
u: 0.00005 I I
.s::.
16 u
0.00004 I \
(.)
'0 u
GI 0.00003 !/ \\
w GI C.
)(
0.00002 II ,\
GI CIJ C 0.00001 II 1
.s::.
(.)
0 II ~
2020 2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
... Sunfish Species ... Alabama Bass PanelB:2017 0.00009 C:
j!:
GI C.
0.00008 0.00007
(
-- \
.s::.
u: 0.00006 I \
.s::.
16 u
0.00005 I \
(.)
'0 u
GI 0.00004 I \
GI C.
)( 0.00003 I \
w
.!: 0.00002 I \
GI Cl C
"' 0.00001 I \
.s::.
(.)
0 j '\____
2020 2025 2030 2035 2040 2045 2050 Time (years)
Impacted Recreational Species
... Sunfish Species ... Alabama Bass Expected Catch VERITAS Economic Consulting Figure 1.7: Change in Expected Catch per Trip by Species in Lake Keowee
- 16 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 Based on these expected catch changes, equations from welfare economics are used to identify annual changes in trips and economic benefits (based on changes in expected catch for all affected species). As detailed in Section 4, changes in consumer surplus that arise from changes in site demand is the metric for economic benefits. This methodology is consistent with economic theory and adheres to rule discussion with respect to considering the "the availability of alternative competing water resources for recreational usage [alternative substitute sites] , and the resulting estimated change in demand for use and value of the affected water resources" (US EPA 2014a , p. 48 ,371) . Figure 1.8 depicts the total change in trips at Lake Keowee where catch changes are specified to occu r based on the complete elimination of entrainment at Oconee.
1.6 Ill c..
i=-
1.4 - ---*---
v--- \
\
/17 \I 1.2
£ GI
1/
C, 1 C
I'll
.s::
\
0 0.8 1-* - - - --- ~- - -- ---- - --- ~ - --
Ill in
,, 0.6 0 0.4 \
__\
<(
0.2 - - - - -~ - - - -*-~ ------*- -* * - -
0 2020 2025 I 2030 2035
"'-2040 2045 2050 Time (years)
Entrainment Year
- 2016 ... 2017 Affected Sites Change in Trips VER IT AS Econom ic Consu lting Figure 1.8: Estimated Trip Change with Elimination of Entrainment at Oconee Figure 1.9 depicts the annual change in dollar-valued welfare associated with the estimated trip changes from a complete reduction in Oconee's entrainment.
- 17 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- e 70 60 I
r \
i\
/ ----
50 QI 0
C:
~ 40
/, \
QI 0
~
30
'/
I
~
c,:i QI 3: 20 -- - ----
10 \
0 2020 2025 J
2030 2035 Time (years)
'-- 2040 2045 2050 Entrainment Year
- 2016 - 2017 We lfare Difference in US Doll ars VERITAS Economic Consulting Figure 1.9: Change in Welfare with Elimination of Entrainment at Oconee
- 1.3.2 Nonuse Benefits The fina l category of benefits that could be monetized is nonuse benefits. Krutilla (1967) presented the original philosophical underpinning for nonuse values, arguing that individuals do not have to be active consumers of unique, irreplaceable resources in order to derive value from the continuing existence of such resources . He wrote :
"when the existence of a grand scenic wonder or a unique and fragile ecosystem is involved , its preservation and continued availabi lity are a significant part of the real income of many individuals" (Kruti lla 1967, p. 779) .
Important components of Krutilla 's original concept are that nonuse values are related to the continuing existence of unique resources . Under this framework, common resources suffering from limited injury do not generate significant nonuse values . The economic literature emphasizes the relationship between nonuse values and both the uniqueness of the resource in question and the irreversibility of the loss or injury (Freeman , Herriges, and Kling 2014; Freeman 2003). Freeman (2003) summarizes this relati onship as follows :
" ... economists have suggested that there are important non use values in
.. . preventing the global or local extinction of species and the destruction of unique
- ecological communities. In contrast, resources such as ordinary streams and 18 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 lakes or a subpopulation of a widely dispersed wildlife species are not likely to generate significant non use values because of the availability of close substitutes" (Freeman 2003, p. 156).
As Freeman's text indicates, common resources (i.e., resources that are not unique) that do not experience irreversible losses are not likely to generate significant nonuse value.
Entrainment sampling indicates that no threatened or endangered species are being entrained at Oconee, and all of the estimated increased recreational yield are Sunfish Species and Alabama Bass, species that are not unique and not expected to experience irreversible losses. Therefore, reductions in Oconee's entrainment are not likely to generate significant nonuse values .
While experts tend to agree on the existence of nonuse values , there is a high degree of debate on the ability to develop reliable estimates of nonuse benefits (Barnthouse, Bingham, and Kinnell 2016). There is also uncertainty regarding what population can hold nonuse values for an individual facility and whether individuals with no prior knowledge of a resource can hold nonuse values (Johnson et al. 2001 ). Non use values have therefore not been quantified as part of this effort. Section 2 of this document summarizes the approaches that have been applied to quantify non use values both in the context of entrainment reductions and more generally. It also describes why those approaches have not been used to develop a quantitative estimate of nonuse values
- at Oconee .
Rather than quantify nonuse values, we consider them qualitatively. Specifically, we expect that the nonuse benefits should have little impact on a cost-to-benefit-based Best Technology Available (BTA) determination at Oconee. Given estimated entrainment reduction costs and benefits, reliably measured nonuse benefits are not expected to impact a BTA determination that considers benefits and costs.
1.4 Summary of Benefits The results presented in this section demonstrate the effects of each step to develop the benefits of a complete reduction in Oconee's entrainment. In addition to a 100-percent entrainment reduction scenario , the analysis also considers the benefits that would result from the entrainment reduction alternatives evaluated at Oconee. Implementation timelines were developed for each of the entrainment reduction technologies evaluated for Oconee, as presented in Section 10. These timelines are used to determine when to start accruing operation and maintenance costs and entrainment reduction benefits for each evaluated technology. All modeled technology scenarios assumed 2034 as the end of useful plant life which is based on Duke Energy's anticipated retirement date for Oconee. Due to the complexity of retrofitting an
- existing nuclear station and nuances of minimizing and balancing station downtown requirements 19 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 with regional power grid stability, the implementation of alternative technologies would occur incrementally over an extended period of time . As such , when modeling costs , a BPJ decision was made to begin accruing costs once technologies were installed and operation at all of Oconee's units. In order to maximize the potential entrainment reduction benefits of each technology, a BPJ decision was made to begin accruing benefits after the installation of the technologies on the first of the units was completed ; thus providing a longer timeframe for the accrual of benefits before statement retirement in 2034. Table 1.5 presents the timelines used to model entrainment reduction benefits for the feasible technologies.
Table 1.5 Timing Specified for Benefits Modeling of Feasible Technologies at Oconee Modeled Technology Modeled Technology Years of Entrainment Reducing Technology Benefit State Date End Datea Operationh Mechanical Draft Cooling Towers (MDCT) 2026 2034 9 2.0-mm Fine Mesh Ristroph Screens (FMS) with a Fish Return System 2024 2034 11 2.0-mm Fine Mesh Ristroph Screens (FMS) with a Fish Return System with 2026 2034 9 Expanded Intake a Anticipated station retirem ent date. Oconee's NRC operati ng licenses expire at midnight on the following dates for each unit: Unit 1 - 2/6/2 033, Unit 2 - 10/6/2033 , and Unit 3 - 7/1 9/2034 b Timelines are from Duke Energy 's PROSYM model Table 1.6 presents the recreational benefits for each evaluated technology for both the present and annual value of benefits. To develop the present value estimates , the benefits estimated for each feasible alternative are discounted at 3 and 7 percent annually and summed over the specified time period used in the analysis.
Table 1.6 Summary of Recreational Social Benefits of Entrainment Reduction Alternatives at Oconee 2016 Entrainment Data 2017 Entrainment Data Discount Rate Technology Present Value Annual Value Present Value Annual Value 3% 100% Reduction $279 $3 1 $362 $40 MDCT $272 $30 $353 $39 FMS $211 $19 $204 $19 FMS with Expansion $164 $1 8 $158 $18 7% 100% Reduction $165 $18 $214 $24 MDCT $160 $18 $209 $23 FMS $130 $1 2 $126 $11
- FMS with Expansion $97 20
$1 1 $93 $10 VERITAS Economic Con sulting
Entrainment Reduction Benefits Study: Oconee August 2020 1.5 Report Organization The following sections present more detailed discussions of the data and methods.
Section 2 presents a detailed discussion on the methods used to assess the recreational and nonuse values associated with entrainment reduction alternatives. Section 3 provides a characterization of the baseline fishery (i.e., the state of the fishery with Oconee's current rate of entrainment) and Section 4 presents the methods for evaluating the recreational benefits resulting from the changes in yield .
- 21 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 2. Methodological Overview This section presents an overview of the methods for estimating the fishing benefits associated with entrainment reductions at Oconee as required by§ 122.21(r)(11)(i-iii)). Oconee is located near Seneca , South Carolina , in Oconee County (Figure 2.1). In the course of its normal operation, Oconee withdraws water from Lake Keowee through a cooling water intake structure (CWIS) . As this water is withdrawn and used for cooling purposes, entrainment of fish occurs.
Entrainment is defined as "any life stages of fish and shellfish in the intake water flow entering and passing through a CWIS and into a cooling water system"(§ 125.92(h)).
2.1 Methods Under the Rule , social benefits and social costs of entrainment control technologies as identified in peer-reviewed studies play a role in establishing case-by-case BTA entrainment reduction standards (§ 125.98(f)(2)(iv)). Social benefits must be assessed by the facility owner and included in the plant's permit application submissions . An important part of this evaluation is the identification of fishery impacts from entrainment. These impacts are uncertain and could result in no effect. 3 Estimating the benefits of entrainment reductions requires assessing the relationship
- between entrainment, its corresponding changes to the relevant fishery, and the impact that fishery changes have on people . For example, properly assessing recreational values requires understanding how Oconee's entrainment affects recreational fishing catch rates and how those changed catch rates affect the well-being of anglers located in the plant's relevant vicinity .
This study uses a resource-economic simulation to evaluate the effects that entrainment has on recreational fisheries . To evaluate the effect of entrainment, site-catch estimates were modified to generate the recreational catch that could occur without the facility's entrainment. The economic value of the estimated changes in recreational catch are determined by linking the changes in catch to a model of recreational angling demand.
3 Barnthouse (2013) notes that the available peer-reviewed literature does not support a conclusion that entrainment reductions will produce measurable improvements in recreational or commercial fish populations .
VERITAS 22 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- Londrun !> IUTH CAR.OU><A l rcrteil!B l
,2067ff Gre Dt lO C,1'1 Ly7
~
/akeKeowee P1tkc Berea re-anvil
,,.,.,~
f.1 ~tlcn Eool !Y)I
- 7' ""1'1..
~
~ .-Jin W.;1 la ~ bm y ' )
C ent r.:11
.. Oconee Nuclear Station m om -1ll c, Wo odruff Clern !Son ..
0 ~
W0$1. ftU I let ,p
- Hart .. ctl
- 7..,.
Location of Oconee Nuclear Station lb
(' \
"' Economic Consulting Source of aerial photo: Google Earth Figure 2.1: Aerial View of Oconee
- 23 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 The methodology presented here extends the most relevant fishery and resource-economic studies published in the peer reviewed literature. Important modeling features include linking yield equivalence , expected catch , and choice-based behavioral fishing models. These integrated partial equilibrium models are used to simulate conditions under With-Entrainment (baseline) and Reduced-Entrainment conditions, and the differences between these two states determine the benefits of entrainment reductions. As described in USEPA's Guidelines for Preparing Economic Analysis, equilibrium modeling using the With- and Without-Impact (or reduced impact) approach is central to all sound benefit estimation processes and regulatory impact analysis (USEPA 2016) .
Figure 2.2 provides an overview of the methodology for evaluating the economic benefits of reducing entrainment at Oconee. The shading in the bottom portion of the figure denotes that the evaluation is separated into two parts: a Baseline (With-Entrainment) evaluation (top white portion) and a Reduced-Entrainment evaluation (bottom shaded portion). The calculated difference in recreational and commercial yield , catch rates, trips , angler welfare , and commercial profits represent the benefits of entrainment reductions . As the top portion of the figure shows, the approach begins by specifying the baseline yield for each evaluated species and dividing that into recreational (R) and commercial (C) yield. The model then relates that yield to expected
- catch rates for the affected waterbody under the baseline , With-Entrainment, conditions (for brevity , the figure illustrates this process for estimating recreational fishing benefits) . Those catch rates are apportioned over the number of trips that are estimated for affected sites .
- 24 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- Stock Cl)
C Cl) Stock CYield en cu m I I
I
~----------------------
I I i I
I I
RYield t
I Expected Catch Trips I
I I I Consumer Stock Yield Expected Catch Trip Surplus Differential Differential Differential Differential Differential tI I I
I I
I I
I I
+
R Yield
+
Expected
+
Trips I Catch I
,,w I
I t I
Cl)
CJ
,,:::s I
Stock CYield -----------------------
Cl)
~
Stock+ E Veritas-0098 Figure 2.2: Overview of Methodology for Estimating the Benefits of Entrainment Reductions Under the Reduced-Entrainment conditions, the reduction in entrainment and the change in recreational and commercial yield that wou ld accompany the entrainment reduction are identified . The new recreational yield is incorporated into changes in expected catch rates and the corresponding changes in trips that would accompany increase catch rates are estimated. To calculate recreationa l fishing benefits the model evaluates the differences in yield , expected catch, and number of fishing trips between the two modeled scenarios. In Figure 2.2, the dashed
- line illustrates that the expected catch and trip differentials result in recreational fishing benefits 25 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee Auqust2020 measured as the consumer surplus differential. Consumer surplus is the difference between what an angler has to pay for a fishing trip and what the angler would be willing to pay.
Simulating the linked models produces equilibrium-based changes in stock, yield, trips and expected catch under the Reduced-Entrainment conditions. Equations from welfare and market-based economics are used to identify changes in consumer and producer surplus, which are then discounted to calculate present values. The following subsections provide additional detail on the recreational and non use value components of the model.
2.2 Recreational Benefits Overview Correctly calculating recreational benefits requires a significant amount of information and
- calculations. As stated in the Rule,
"... assessing recreational use benefits involves estimating the improvements in recreational fishing opportunities resulting from reduced impingement mortality and entrainment, and assigning a value to these improvements. The value assignment is based on the estimated population profile-in particular, number and proximity to affected water resources-of recreational users, the availability of alternative competing water resources for recreational usage [alternative substitute sites], and the resulting estimated change in demand for use and value of the affected water resources based on reduced impingement mortality and entrainment and increased recreational fishing performance (USEPA 2014a, p.
- 48,371)."
The methodology for estimating recreational angler benefits is based on simulating angler behavior and changes in social welfare resulting from reductions in entrainment and the associated increases in expected catch. Angler behavior was simulated by a mathematical representation of angler demand (Recreational Angling Demand Model) for the population expected to be affected by reductions in Oconee's entrainment. The Recreational Angling Demand Model identifies angler behavior using site characteristics that occur in both the Baseline and Reduced-Entrainment conditions. Important modeling features include fusing an existing, behavioral (choice-based) preference function to spatially represent population data. This fusing process produces integrated partial equilibrium models that are used to simulate conditions under Baseline and Reduced-Entrainment conditions. The differences between these two conditions determine the social welfare changes associated with the entrainment reductions resulting from an individual entrainment control technology.
Important factors accounted for in the Recreation Angling Demand Model include angler preferences; attributes associated with the fishing sites they have to choose from; the number, quality, and availability of substitute fishing sites; the geographic range of impacted species; the
- number of trips with improved catch rates; and the number of anglers associated with those trips .
26 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 Preference functions are used to identify how anglers trade off the characteristics of alternative fishing sites when they choose how and where to participate in recreational fishing.
When anglers take a trip, they have a choice of which site to visit. The sites from which they can choose have numerous characteristics such as the distance from their home, catch rates, facility amenities (e.g., presence of a boat launch), and water-body characteristics and surroundings (e.g., fresh versus saltwater, level of crowding, aesthetics, and remoteness of the surroundings).
Preference functions include the (nonmarket) price of fishing as the costs that anglers incur in traveling from their homes to recreation sites. These "prices" vary according to angler locations. When existing fishing sites have their features changed, such as a change in catch rates that could occur with entrainment reductions at a power plant, the preference function allows interpreting the value of the quality change in terms of travel costs. Anglers respond to catch rate changes by reallocating their trips so as to maximize the value of their fishing experience. For example, if entrainment rates are reduced and catch rates increase, an angler who typically visits a site farther away with a higher catch rate under Baseline conditions, would not have to travel as far to achieve a similar fishing experience under Without-Entrainment conditions. This angler would incur lower travel and time costs arid experience welfare improvement because the same fishing experience costs the angler less in avoided travel and time costs .
- Random utility analysis is the best method for evaluating angler preferences and valuing entrainment reductions on recreational fishing. 4 However, conducting an original random utility maximization (RUM) study can require extensive primary data collection. Developing a recreation demand model using a site-calibrated transfer of a preference function from an existing RUM study can capture important behavioral responses (i.e., changes in trip-taking behavior as a result of changes to a fishery) without requiring survey-data collection. The accuracy of this methodology is limited only by the analyst's ability to calibrate an already estimated preference function to a different population using appropriate economic methodologies (Smith et al. 2002).
Economists have long used the preference functions from random utility models (RUMs) to estimate demand curves (Bingham et. al 2011; Kinnell et al. 2006; Bockstael et al. 1986, 1987, 1991; Morey et al. 1991; Caulkins et al. 1986; Feenberg and Mills 1980). The USEPA's Benefits Analysis for the Final Section 316(b) Existing Facilities Rule uses the results of a meta-analysis 4 Random Utility Maximization (RUM) models are recognized in the Department of the Interior (DOI) regulations (43 CFR §11.83) as an appropriate method for quantifying recreation service losses in natural resource damage claims.
Currently, the RUM is the most widely used model for quantifying and valuing natural resource services. RU Ms are also widely accepted in other areas of the economics profession. RUMs have been used in transportation (Beggs, Cardell, and Hausman 1981; Hensher 1991 ), housing (McFadden 1997), and electricity demand estimation (Cameron 1985), as well as in environmental and resource economics .
VERITAS 27 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 of existing RUMs in the economics literature to estimate the benefits of the 2014 Rule (USEPA 2014b). In addition, USEPA's Guidelines for Preparing Economic Analysis describe the use of RUMs to estimate the benefits of changes in environmental quality (USEPA 2016).
The RUM is based on welfare theory and posits that individuals make choices that maximize their utility, subject to constraints. RUMs divide fishing areas into discrete sites, with each site being a plausible destination for fishing. In this framework, anglers choose which sites to visit based on costs and fishing opportunities at the sites. Because anglers trade off factors, such as the cost of getting to the site against the quality of the fishing opportunity, this approach can evaluate the relative influence of these variables as revealed by anglers' decisions.
Incorporating the relevant alternative, substitute sites allows evaluating the importance of site characteristics at each of these sites to identify the site-demand curves. These form the foundation for appropriately estimated economic benefits of changes in site attributes such as catch rate improvements.
The focus on site characteristics, such as catch rates, allows for the isolation of benefits to recreational fishing due to entrainment reductions. All other site characteristics are held constant. The better the characteristics of a site are, the higher the probability that an angler will choose that site, which is reflected in a higher value for the site. RU Ms can be used to estimate both the distribution of trips among various sites and the total satisfaction received from a given set of fishing opportunities.
The analysis uses four main steps to develop the Recreational Angling Demand Model and estimate the benefits associated with reductions in Oconee's entrainment. The first step
- involves selecting the angling preference function from the best available RUM study. The next step identifies the appropriate geographic scope for substitute sites and selects a representative sample of substitute sites. Available information on recreation in the area and typical travel distances are used to develop an appropriate area of alternative, substitute sites to include in the model (generally within 100-200 miles of the affected site). Most RU Ms based on original data use studies providing high-quality data. Several substitute sites are used that are representative and reasonable and provide a similar fishing experience for anglers who potentially fish near Oconee. By capturing substitution among sites, the simulation adds a critical level of realism relative to approaches that ignore substitution possibilities.
The third step in the analysis entails fusing the preference function to the affected population and calibrating the model's prediction of the population's trips. For this analysis, affected anglers can include any of the anglers located in counties within a 50-mile radius of affected sites. Because distance-based travel cost is an important variable in the Recreational VERITAS 28 Economic Consulting
- Entrainment Reduction Benefits Study: Oconee August2020 Angling Demand Model, anglers closer to the site have a higher predicted likelihood of visiting the site than those farther away, but the model does not make any specification of which anglers are included in the model or not. For the sites affected by Oconee's entrainment, the number of trips is set to correspond to the best available information on current visitation. Within these constraints, the remaining trips are distributed among the substitute sites in an appropriate manner, also based on available visitation information.
The distance traveled to a site is one of the most important site characteristics in a RUM.
It directly influences the travel cost to each site for each angler. A critical factor for the site-calibrated benefits transfer is distance from each angler's residence (ZIP code) to each site included in the Recreational Angling Demand Model. These distances are calculated using the most recent version of a popular transportation routing software called PC*Miler (ALK Technologies 2016). Travel costs reflect both direct costs and travel time costs. Direct costs are calculated by multiplying the round-trip miles by $0.2054 per mile, which is the American Automobile Association's (AAA) 2019 per-mile cost of operating a motor vehicle (AAA 2019). The cost per mile includes gas, maintenance, and tires and is averaged across nine types of vehicles:
small, medium, and large sedans; small and medium SUVs; minivans; crew cab pickups; hybrid vehicles; and electric vehicles. The average hourly wage of each ZIP code within the model is
- calculated by dividing household income from the U.S. Census by 2,000 work hours per year (U.S. Census Bureau 2019). 5 Travel time in minutes is also calculated by PC*Miler. The round-trip time estimate is multiplied by one-third of the average hourly wage rate to reflect the opportunity cost of time based on the original research of Cesario (1976) and the more recent evaluation by Phaneuf and Smith (2004).
In the fourth step, changes in trip patterns that anglers make in response to changes in catch rates are simulated. For purposes of this assessment, we increase catch only for sites on Lake Keowee. The increased catch rate is incorporated into the calibrated RUM while all other site characteristics for the relevant sites are held constant.
2.3 Nonuse Benefits Recreational benefits from entrainment reductions arise from changes in catch rates and therefore accrue to people who use the affected resource. Another benefit category, nonuse 5 While the U.S. Census' household income data can include income from more categories than just the amount of earnings for a household's hourly wages times the number of hours worked in a year, the U.S. Census' household income by ZIP Code is the best data source available to estimate the modeled population's opportunity cost of time.
The potential effect on benefit estimates from using the U.S. Census income data would be to have an upward bias on benefit estimates .
VERITAS 29
- Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 benefits, results from changes in values that people may hold for a resource, independent of their use of the resource. These can arise for a number of reasons: they may be happy that other people can use the resource, they may want it to be available for people to use in the future, or they may believe the resource has some inherent right to exist. However, as Freeman (2003) notes, common resources (i.e., resources that are not unique) that do not experience irreversible losses are not likely to generate significant nonuse values.
While experts tend to concur on the existence of nonuse values, they are inherently difficult to observe. As a result, these values are looked upon quite differently from recreational and commercial values. By comparison with use values, there is less agreement among experts about how nonuse values should be measured, and the reliability of measurement techniques (Barnthouse, Bingham, and Kinilell 2016). Given this lack of agreement and concerns about the reliability of quantitative measurement techniques, this assessment does not quantify nonuse values. The following subsections presents a summary of the approaches that have been applied to quantify nonuse values both in the context of entrainment reductions and more generally and describes why those approaches have not been used to develop a quantitative estimate of non use values at Oconee.
There are a handful of approaches that have been applied to quantify non use values both in the context of entrainment reductions and more generally. These include the non-economic methods Habitat Replacement Cost (HRC) and Societal Revealed Preference (SRP), a "rule-of-thumb" approach called the Fisher-Raucher approximation, and two approaches that require administering surveys that pose hypothetical questions called Contingent Valuation (CV) and Discrete Choice Experiments (DCE). 6 The following text summarizes these methods as they've been applied for entrainment, evaluates their applicability, and describes why they were not used to develop quantitative estimates of nonuse values for Oconee.
2.3.1 Non-Economic Methods We refer to HRC and SRP as non-economic methods because they do not attempt to measure economic value. Considering HRC, the costs estimated are the total costs of restoring habitats so that they produce ecological services equivalent to those expected from technological alternatives. These are not benefits, and over the course of USEPA's §316(b) rulemaking, numerous reviewers commented as such. Rather, they are alternative costs for achieving similar 6 Both CV and DCE can also appropriately be called "Stated Preference" (SP) techniques as they both rely on stated rather than revealed (i.e., by taking fishing trips) preferences. Although DCE is often called SP, here we use the more precise term. Also, DCE is often referred to as "conjoint analysis" which is a related, but not identical technique .
VERITAS 30 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 objectives. Mitigation approaches, such as stocking and habitat restoration, may achieve similar waterbody-level outcomes as entrainment reductions. However, the cost of such alternatives bears no implicit relationship to the benefits of reducing entrainment.
The underlying reason for this is that measures of economic benefits must be based on the willingness-to-pay (WTP) principle, and HRC is not based on this principle. In many cases, the cost of developing a resource can substantially exceed the resource's value. Although USEPA extensively evaluated HRC during its development of the Phase II Rule, USEPA ultimately decided that the HRC method should not be used as a means of estimating nonuse benefits due to limitations and uncertainties regarding the application of this methodology (69 Fed. Reg. 131, p. 41,625).
The second cost-based methodology considered in USEPA rulemaking is called Societal Revealed Preference (SRP). Rather than using the cost of a hypothetical alternative (as under HRC), SRP uses historical costs under prior government mandates to measure benefits. Like the HRC method, this is a cost-based approach that has no foundation in economics. Accordingly, it is not accepted by economists as a legitimate method of empirical valuation. In fact, the SRP method is a corrupted application of the legitimate revealed preference (RP) method. An essential characteristic of RP analysis, that is not part of SRP, is that willingness to pay is revealed by those who are doing the paying. In contrast, the SRP methodology inappropriately takes the fact that a program exists as evidence that its benefits exceed its costs.
The drawbacks of these methods, with respect to valuation, would seem to indicate that they should not be used for estimating the non use values of entrainment reductions. This position is, strictly speaking, correct. However, as the following discussions will describe, the methods that appear at least theoretically capable of quantifying nonuse values are subject to disagreement regarding their reliability, and important questions remain about bias in nonuse C
survey estimates and extrapolation of non use survey results. In part because of these difficulties, Natural Resource Damage Assessments (NRDAs) have effectively abandoned nonuse valuation and embraced the Habitat and Resource Equivalency Analysis (HEA and REA) methods.
The effective abandonment of non use valuation in Natural Resource Damage Assessment and Restoration evaluations and use of Habitat and Resource Equivalency Analysis points out the current quandary with site-specific valuation of changes in ecological services. The best techniques available given the current state of the science are not used because of concerns about their reliability. The technique that is used is a cost-based technique that does not reflect society's values for changes in ecological services but rather the costs required to restore VERITAS 31 Economic Consulting
Entrainment Reduction Benefits.Study: Oconee
- August 2020 ecological services to the conditions they would have been in but for the presence of a specific environmental impact.
2.3.2 Rule-of-Thumb Method USEPA has also considered the Fisher-Raucher or "50 percent" rule. This approach approximates nonuse values at 50 percent of recreational use values. The approximation is derived from a comparison of use and non use values for water-quality improvements, where the nonuse values were estimated using the CV method (Fisher and Raucher 1984). Applying this "SO-percent rule" for entrainment reductions has the great advantage of being simple. However, it is based on CV studies which are subject to questions about their reliability. This rule-of-thumb was based on water quality improvements. There is a lack of good evidence that the ratio of nonuse to use benefits from water-quality improvements is similar to that same ratio for environmental improvement from reductions in entrainment. In particular, use values from fish often arise from their consumption whereas use values from water quality are typically non-consumptive.
2.3.3 Hypothetical Scenario Survey Methods Currently, the only conceptually correct methods (i.e., those applying the WTP concept) available for estimating nonuse values are survey-based techniques that ask respondents to value, or to choose natural resource services in a hypothetical context. These are the Contingent Valuation and Discrete Choice survey methods.
Contingent Valuation The CV method involves surveying individuals to elicit their WTP for different levels of services.7 For example, the survey may ask respondents a question such as, "What is the maximum amount you would pay to restore wild salmon runs in the Columbia River Basin?" 8 The responses are analyzed to determine the average WTP for preserving wild salmon runs. This method requires that individuals be able to express their value for changes in the fishery and, furthermore, that their responses to hypothetical questions indicate their actual valuations of the changes described in the questions.
7 See Champ, Boyle, and Brown (2017); Carson (2012); Hausman (1993, 2012); and Arrow et al. (1993) for a more detailed critique of CV.
8 Natural resource economists have used a variety of question formats. This question is an open-ended format.
Alternatives include bidding games, payment cards, and referendum or dichotomous choice. In the dichotomous choice format, respondents are offered a particular payment amount and allowed to accept or reject that amount.
See Mitchell and Carson (1989) for a detailed discussion .
VERITAS 32 Economic Consulting
Entrainment Reduction Benefits Study: Oconee
- August 2020 The CV method attempts to establish, through the course of a survey, a hypothetical market where environmental changes can be traded like commodities. Ultimately, the goal of the CV survey is to establish circumstances that represent an exchange of money for the environmental service. Oral or written descriptions, supplemented by visual aids, are used to make the survey informative and realistic.
The validity and reliability of CV has been questioned because respondents' hypothetical payment for a nonuse service has no behavioral experience to support or test the expressed value. This lack of a linkage between actual behavior and the hypothetical payment makes CV estimates particularly sensitive to variations in survey design, implementation, and analysis.
In addition to this sensitivity, the hypothetical nature of CV makes responses subject to.
bias. The inclination is for respondents to state that they would pay a higher amount for a good or service than they would actually pay. This problem was recognized by the National Oceanic and Atmospheric Administration (NOAA) when it suggested that CV estimates be treated to the "divide by 2" procedure. That is, to accou11t for hypothetical bias, researchers should divide estimates of WTP from CV by 2.
NOAA's "divide by two" rule has no strong empirical basis, but it did set economists on the
- task of calibrating hypothetical valuations by comparing them with values derived from real exchanges, where respondents gave up real money for real goods. Bias from valuation for public goods (such as fisheries) is especially difficult to investigate, however, because hypothetical versus real experiments for public goods are difficult to design.
The value estimate from CV data is typically the average WTP from the survey question.
Researchers may model these responses to determine what characteristics of respondents influence their WTP. An important implication is that, in addition to designing the survey, researchers must determine the relevant population for the survey. That is, they must determine "to whom do these results apply?" Identifying this group is .important because survey WTP estimates must be aggregated over the affected population to determine total WTP. A critical and unresolved consideration is that, by its nature, participating in a survey raises awareness. This is a fundamental difference between the surveyed "aware" population and the not-surveyed population that is less aware of the impact, but sometimes makes up the vast majority of the WTP population.
Discrete Choice Experiments A more sophisticated stated preference technique is DCE. DCE's explicitly recognize that commodities have value because of their attributes. For example, a car has value because of VERITAS 33 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 such specific characteristics as size, color, comfort, body style, handling, gas mileage, price, etc .
A DCE survey asks respondents to choose among a series of different alternatives with different levels of attributes and different costs. By analyzing the choices made by respondents, researchers can uncover the underlying preferences for these attributes and respondents' WTP for different attributes or attribute bundles such as environmental programs.
DCE methods have been applied in the fields of environmental and health economics as an alternative to the CV method. For example, the DCE technique has been used to value hunting and fishing trips (Gan and Luzar 1993; Mackenzie 1993; Roe et al. 1996), to explain recreation site-choice selection (Adamowicz et al. 1994), and to determine public preferences for siting an industrial facility (Opaluch et al. 1993). DCE has also been applied to measure values for changes in fishery services such as catch (Banzhaf et al. 2001).
The USEPA conducted a DCE to evaluate total (use and nonuse) values for entrainment reductions (USEPA 2012). USEPA selected a total target sample of 2,000 completed surveys across four regions and a national sample. The USEPA allocated these surveys across regions based on an experimental design which presents a set of three hypothetical choices to each respondent. Figure 2.3 presents an example of the choice questions.
- As Figure 2.3 shows, the choices presented to respondents are profiles that include a monetary payment and improvement in environmental variables, including reductions in entrainment, improvements in fish populations, commercial fish populations, and overall aquatic health. Responses to the choice experiment are modeled for a Northeast, Southeast, Inland (containing the Great Lakes), Pacific, and National region using the mixed logit econometric technique. Although many environmental variables are insignificant, in all cases the variable representing reductions in entrainment is statistically significant. The USEPA approximated the WTP of survey respondents for a 1-percent change in yield increase due to entrainment reductions by conducting simulations for alternative uncertainty distributions of resulting preference coefficients. Ultimately, USEPA estimated that WTP for a 1-percent reduction in the number of fish impinged and entrained varies between $0. 75 and $2.52 per household per year for the four regions surveyed, and averages at $1.13 per household per year for the National region (USEPA 2012, Exhibit 11-10). 9 9
"National" refers to the survey administered to a national sample and is referred to as a region for convenience .
VERITAS 34 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- Question 4. Assume that Options A and B wou ld require a different mix of filters and closed cycle cooling in different areas . Assume all types of fish are affected. How would you vote?
Policy Effect Current Option A Option B NE Waters Situation NE Waters NE Waters (No policy) 43°/o 44% 45%
Commercial Fish (100% is populations (100% is populations (100% is populations Populations that allow for ma><imum that allow for maximum that allow for maximum (In 3-5 Years) harvest) harvest) harvest) 31% 32% 35%
Fish Populations 100% is populations (100% is populations (100% is populations (all fish) without human without human without human (in 3-5 Years) influence) influence) influence) 0% 25% 50%
Fish Saved per Year (Out of 1.1 billion fish No change in status quo 0.3 billion fish saved 0 .6 billion fish saved lost In water Intakes)
Condition of Aquatic 48% 49% 50%
Ecosystems (100% is pristine (100% is pristine (100% is pristine (In 3-5 Years) condition) condition) condition)
$ $0 $24 $36 Increase in Cost of No cost increase per year per year Living for Your ($2 per month) ($3 per month)
Household HOW WOULD YOU VOTE?
(CHOOSE ONE I would vote for I wou ld vote for I would vote for ONLY) NO POLICY OPTION A OPTION B Figure 2.3: Example of the Choice Question Format in the Stated-Preference Survey
- 35 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 DCE, such as that conducted by USEPA, has advantages over CV. DCE encourages respondents to explore their preferences for various attribute combinations through a series of choices. The process of explicitly trading off attributes encourages greater respondent introspection than is likely to occur in a traditional CV format. The absence of such introspection has been a major criticism of the validity and reliability of CV estimates (Schkade and Payne 1994). The approach also allows analysts to devise internal consistency checks because respondents provide answers to multiple questions. Having more information from respondents on their relative preferences for the scenarios allows analysts to systematically evaluate whether a respondent's pattern of answers is plausible and consistent with economic theory used to construct social values (Johnson and Bingham 2001). These internal consistency checks are a significant improvement over the rudimentary technique of using general follow-up questions to assess respondents' motives for answers to single CV questions.
Because it provides values for individual components of commodities, as well as for commodities as a whole in a single survey, DCE has general applicability. DCE is frequently used to evaluate the market potential for new goods or services that are being developed and have not yet been brought to market or have only recently been introduced to the market. The large number of such studies that have been done have given the technique substantial credibility in
- the area of new product development and forecasting demand for unfamiliar products (Louviere et al. 2010). Certain of these are for environmental products that have a "non use flavor" such as green electricity (Johnson et al. 1995).
Despite these advantages, DCE has significant drawbacks for calculating nonuse values.
Like CV, it elicits expressed preferences under hypothetical conditions. As a result, the responses are likewise hypothetical, which implies that respondents do not have to make a real dollar commitment as they would in a real-market situation. Experimental evidence demonstrating hypothetical bias in choice experiments has been found by Johansson-Stenman and Svedsater
- (2008). Also, like CV, the question of the affected population is critical. DCE offers higher potential for connecting WTP to personal characteristics (EPRI 2012b). However, there is currently no solution to the fact that, by nature of them having taken the survey, the surveyed population is fundamentally different from the not surveyed population (EPRI 2012b). Although there is no study of nonuse values in which these obstacles have been surmounted, recent efforts have proposed novel extensions of typical DCE surveys that propose methods for minimizing bias and extrapolating to the not surveyed population (Barnthouse, Bingham, and Kinnell 2016) .
- 36 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee Ai.lgust2020
- 2.3.4 Evaluating the Applicability of Quantitative Methods for Estimating Nonuse Benefits for Entrainment Reduction at Oconee As this overview of methods indicates, certain approaches that have been proposed for evaluating the nonuse value of entrainment impacts are not consistent with WTP, the economic concept of monetary value. Considering the use of replacement cost and societal revealed preference approaches, some analysts attempt to use per-fish stocking costs as indicators of value. Setting aside questions as to the validity of this approach, the recreational values of entrainment reductions are already considered in the analysis.
Forage species are also accounted for in the monetization of benefits through the trophic transfer to econpmically important species. Lack of stocking of forage species would tend to indicate these species would not be assigned value in the SRP approach. While HEA and REA (techniques that are similar to HRC and could be used to value forage) are implemented under Natural Resource Damage Assessment (NOAA 2000), they are cost-based approaches and are not consistent with WTP.
The "rule of thumb" approach is straightforward to implement. However, the approach is based on water quality instead of fishery impacts. Although the approach is based on methods that are conceptually capable of identifying nonuse values, the reliability of these methods is
- questionable. Moreover, the approach is dated. If the approach were applied, non use benefits would simply be half of the estimated recreational benefits.
The USEPA DCE study elicits values from users and nonusers and therefore elicits both use and nonuse values. It is potentially feasible to extract a use/nonuse ratio from this study and apply those results to an individual facility. However, this has not been attempted and may not be straightforward-users can experience nonuse values and it is not clear how to disentangle them from use values. In addition, as described in EPRI (2012b) and Barnthouse, Bingham, and Kinnell (2016), an important consideration with nonuse values is the appropriate population to extrapolate over. Identifying an appropriate population of individuals who* may hold non use values for entrainment reductions at an individual facility such as Oconee is problematic because there is no utility theoretic foundation that allows unaware nonusers to experience welfare increases (Johnson et al. 2001).
The reason this is problematic for a plant-specific evaluation is because USEPA's DCE provides information to respondents explaining what entrainment is before they are asked the willingness to pay questions. By comparison, members of the general population have not received such information and do not have the same awareness level of the survey respondents
- 37 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 (Veritas Economic Consulting 2012). Any extrapolation of study results would therefore have to take the population's awareness level into consideration.
The results from the Veritas Economic Consulting (2012) Environmental Impacts Awareness survey provide insight into this concept. The survey was administered to Harris lnteractive's representative sample of more than 2,000 U.S. residents and asked questions about their current awareness of environmental impacts, including impacts from power plants (Veritas Economic Consulting 2012). The results of the survey indicate that slightly over 13 percent of the U.S. population is aware of aquatic impacts from steam electric plants. These include impacts such as water pollution, thermal discharge, wastewater impacts, and impacts to fish. No respondents specifically mentioned impingement and entrainment, only one respondent was aware that fish could be impacted through cooling water intakes, and fewer than five percent of
. respondents are aware that fish can be affected by power plant operations (this includes respondents who are aware of fish impacts resulting from either steam electric or hydroelectric plants).
The most site-specific approach would be to develop and administer a stated preference survey that elicits nonuse values for impacts at Oconee. Although a significant amount of work has been done in this area, conducting a site-specific study for an individual facility like Oconee would be a significant undertaking and has not been contemplated for this effort because the likely magnitude of reliably estimated non use benefits for entrainment reductions at Oconee is expected to be modest relative to the cost of achieving those benefits. In addition, the inclusion of reliably estimated nonuse values is not expected to change a best technology available determination for the facility.
2.3.5 Qualitative Evaluation of Nonuse Benefits for Entrainment Reduction at Oconee The magnitude of nonuse values for entrainment reductions at Oconee has not been quantitatively evaluated as part of this effort; rather, nonuse values have been addressed qualitatively. Given the importance of benefits in site-specific decision-making, it is important to provide context for this qualitative assessment. Of particular interest is the question of whether there is any reason to believe that nonuse values could have a magnitude that would have implications for decision-making. Nonuse values are a component of all benefits, which must be considered by Directors making BTA determinations. These social benefits are to be compared against social costs.
With regard to the CWA, the idea of weighing costs relative to benefits appears in
- §304(b)(1)(B), referring to effluent limitation guidelines.
38 The actual phraseology of "wholly VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 disproportionate" as rendered in the judicial history states that "[t]he balancing test between total cost and effluent reduction benefits is intended to limit the application of technology only where the additional degree of effluent reduction is wholly out of proportion to the costs of achieving such marginal level of reduction for any class or category of sources" (Kennecott v. United States EPA).
The "wholly disproportionate cost test" was first applied to §316(b) during In the Matter of Public Service Company of New Hampshire 10 ERG 1257 (May and Van Rossum 1995). In the decision for that case, the sole basis for applying the "wholly disproportionate" cost test came from the aforementioned legislative history of the CWA. The ruling stated that §316(b) did not require implementation of technology whose cost was "wholly disproportionate" to its environmental benefits. Following the Seabrook II Decision, the "wholly disproportionate" cost test has been applied differently in various cases, depending on the specific facts of the case. In the previously issued Phase Ill Rule, USEPA promulgated national standards only for new offshore oil and gas extraction facilities, but also prepared a cost-benefit analysis of regulating additional Phase Ill facilities (i.e., existing manufacturing facilities that use cooling water). In this analysis, USEPA found a ratio of costs to benefits that ranged from 17-to-1 to 22-to-1 and found this to be "wholly disproportionate." Ratios as low as two or three to one have also been
- determined as wholly disproportionate.
An implication of the qualitatively "low" estimate for non use values at Oconee and these determinations is that nonuse values should have little impact on a cost-to-benefit based BTA determination at Oconee. Specifically, with entrainment reduction costs that are hundreds to thousands of times the level of benefits, correctly measured nonuse benefits will not influence a BTA determination that considers benefits and costs based on any historically applied criteria .
- 39 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020
- 3. Baseline Recreational Fishing Conditions Baseline fishing conditions are defined as the current conditions at Oconee, which include entrainment. The characterization of baseline fishing conditions considers recreational fishing, both current and into the future. To characterize baseline fishing conditions, we assess current recreational yield with Oconee's entrainment, the number of recreational anglers potentially affected by the impact of Oconee's entrainment on recreational yield, the number of fishing trips the anglers take, the sites that those anglers visit, and catch rates.
When anglers take a fishing trip, they have many sites to choose from with varying attributes. These attributes include how far the site is from the angler's home, the type and number of fish the angler can expect to catch at each site, and the level of development at each site. Angler preferences across varying site attributes are characterized using Recreational Angling Demand Models.
3.1 Angler Preferences The most sophisticated angling demand models are econometrically estimated using RUMs. RUMs are the best method for evaluating angler preferences across these different site attributes (USEPA 2016). 10 The RUM is based on choice theory and posits that individuals make
- choices that maximize their utility, subject to constraints. In this framework, anglers choose which sites to visit, based on costs and fishing opportunities at the sites. Because anglers trade off factors, such as the cost of getting to the site against the quality of the fishing opportunity, this approach cari evaluate the relative influence of these variables as revealed by anglers' decisions.
To evaluate the factors influencing anglers' decisions, the analysis uses the angler preference function presented in Bingham et al. (2011 ). Bingham et al. (2011) covers fishing sites across New Jersey and explicitly considers various fishing experiences, including ocean, estuarine, and freshwater sites (e.g., inland lakes, rivers, and stream). The survey process was consistent with accepted survey protocols. The study's response rate is consistent with survey research standards, and its models are rigorous, perform well, and reveal results that are consistent with expectations (Bingham et al. 2011).
The statistical model estimated in Bingham et al. (2011) is a nested logit. To delineate potential differences in angler preferences with respect to fishery type, Bingham et al. (2011) uses 10 RU Ms are also widely accepted in other areas of the economics profession. RU Ms have been used in transportation (Beggs, Cardell, and Hausman 1981; Hensher 1991 }, housing (McFadden 1997), and electricity demand estimation (Cameron 1985).
VERITAS 40 Economic Consulting
_J
Entrainment Reduction Benefits Study: Oconee August2020 a three-level fishing structure. On the first level, anglers choose whether or not they will fish. On the second level, anglers choose which waterbody type to fish from (freshwater, saltwater, or tidal sites). Lastly, after selecting a water body type, anglers decide which site to choose.
The model output is a coefficient for each site characteristic. Each coefficient reflects the importance of that site characteristic to angler welfare. These coefficients play a key role in the approach used in this assessment. Table 3.1 contains the relevant coefficients and t-statistics from the Bingham et al. (2011) model.
Table 3.1 Coefficients from the Bingham et al. (2011) Model Characteristic Coefficient t-Statistic Travel cost -0.024 -9.93 Advisorya -0.42 -2.30 Boat ramp 1.49 19.69 Trout and shad 0.31 7.42 Panfish 0.16 4.72 Freshwater game 0.16 8.67 Other freshwater 0.08 2.71 Other saltwater 0.36 8.86 Saltwater small game 0.16 3.01 Flatfish 0.95 10.70 a Advisory is a 1 if the waterbody has a fish consumption advisory warning anglers to limit their consumption of fish from the affected waterbody.
When considering yield changes, value at the species level is a critical component of overall value. The Bingham et al. (2011) model includes coefficients for catch rates for both freshwater and saltwater species. The "freshwater game" species group includes species such as Alabama bass. The "other freshwater" species group includes species such as bluegill, sunfish, and catfish. "Panfish" includes crappie species. Relative species values can be evaluated by comparing these coefficients. Freshwater game species are valued higher than freshwater other species.
3.2 Angler Participation: Population Size and Annual Fishing Trips The U.S. Fish and Wildlife Service (USFWS) conducts the National Survey of Fishing, Hunting, and Wildlife-Associated Recreation every five years. Among other information, the survey collects data on anglers and the types of fish that they catch. This assessment uses data from the 2011 survey for Georgia, North Carolina, and South Carolina because those are the VERITAS 41 Economic Consulting
Entrainment Reduction Benefits Study: Oconee
- August 2020 most recent, complete data on angling activity. According to the national survey, 7.91 percent of Georgia residents, 10.58 percent of North Carolina residents, and 9.56 percent of South Carolina residents 16 years of age and older fished non-Great Lakes freshwater waterbodies during 2011 (USFWS 2013a; 2013b, 2013c, U.S. Census Bureau 2019). To develop the estimate of total angling days, the analysis applies the average number of days that these anglers spend fishing non-Great Lakes freshwater waterbodies from the 2011 USFWS ( 11 days for GA, 16 days for NC, and 20 days for SC) to the number of anglers residing in the affected ZIP Codes.
3.3 Angling Sites In addition to using information on angler preferences and participation, the Recreational Angling Demand Model has to contain information on the sites an angler can potentially visit. We.
collect information from publicly available sources on the most popular inland river and lake sites.
Model sites include fishing sites on Lake Keowee and South Carolina inland lakes and rivers, as well as lakes and rivers in neighboring states. Fishing sites include shore and boat fishing.
Appendix A presents the characteristics of the sites included in the model.
Table 3.2 lists conditions at Lake Keowee. Catch rates are specified to be the catch per hour and are listed for three categories. All 16 affected sites on Lake Keowee are specified to
- have the same catch rates. Appendix A presents the distribution of trips across the affected sites included in the model.
Table 3.2 Conditions of Lake Keowee Affected Sites Category Lake Keowee Angler trips 94,891 Catch rate:
Panfish 0.1170 Freshwater game 0.0360 Other freshwater fish 0.9140 Sources: Schmitt and Hornsby (1985)
The distance traveled to a site is one of the most important site characteristics in a Recreational Angling Demand Model. It directly influences the travel cost to each site for each angler. Thus, a critical factor in the simulation model is distance from each angler's residence (ZIP Code) to each site. These distances are calculated using the most recent version of a popular transportation routing software called PC*Miler (ALK Technologies 2016). Travel costs reflect both direct costs and travel time costs. Direct costs are calculated by multiplying the round-VER IT AS 42 Economic Consulting
Entrainment Reduction Benefits Study: Oconee
- August 2020 trip miles by the standard per mile reimbursement. The average hourly wage of each ZIP Code in counties within 50-miles of the affected sites is calculated by dividing household income from the U.S. Census by 2,000 work hours per year (U.S. Census Bureau 2019). Travel time in minutes is also calculated by PC*Miler. The round-trip time estimate is multiplied by one-third of the average hourly wage rate to reflect the opportunity cost of time. The travel cost included in the model is the sum of the direct travel cost and the opportunity cost of time.
3.4 Calibrated Baseline Trips and Expected Catch Travel costs and the other site characteristics are combined with the coefficients from the Bingham et al. (2011) model to allocate the estimated annual trips by the affected angling population to the affected and substitute sites. Total trips to Lake Keowee are calibrated to.
correspond to the best available visitation information for the affected sites. This process results in the distribution of trips to the affected sites listed in Table 3.2 and Appendix A. The remaining trips are distributed among the substitute sites using the best available visitation information.
In the calibrated baseline dynamic recreational fishing model, baseline trips (from above) and yield were combined by dividing recreational catch by trips, to identify a calibrated baseline expected catch for each affected species.
- 3.5 Future Baseline Fishing Participation, Trips, and Site Quality Because the modeling predicts decades into the future, differences from the current state of fishing could impact results. This means anticipated changes in site quality and availability or changes in economic conditions and fishing preferences should be expressed in the baseline case going forward.
The recreational fishing demand model is based on fishing participation rates from 2012, which is the most recently available information for the affected population. Participation in recreational fishing declined nationally to a low point around the turn of the century and has been on the increase more recently. For example, according to the National Survey of Fishing, Hunting, and Wildlife-Associated Recreation, the number of anglers rose 11 percent nationwide from 2006 to 2011. A potential implication is that 2012 fishing rates underestimate the number of affected fishing trips. When site quality is constant, fishing trips are directly tied to benefits. For evaluations of increases in yield, the yield changes are divided by trips. This has a mitigating effect against underestimates of trips. For example, if yield changes by 100 fish and there are 50 affected trips, expected catch per trip increases by 2 fish per trip. If there are 100 affected trips instead of 50 trips, yield would change by 1 fish per trip. Based on this mitigating effect and the lack of more
- 43 VERITAS Economic Consulting
7 Entrainment Reduction Benefits Study: Oconee August2020 recent information, the baseline of fishing participation and trips was specified to be consistent with the pre-2012 calibrated baseline estimates described above .
- 44 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 4.1
- 4. Modeling and Valuing Changes in Recreational Yield Modeling Changes in Recreational Yield Once the baseline stock and fishing conditions have been established, the next step in the analysis was to model the recreational yield impacts associated with Oconee's entrainment.
The model incorporates two types of yield changes associated with simulating a reduction in Oconee's entrainment: direct and indirect yield changes. The direct yield changes are the increases in recreational species that would occur as a result of removing entrainment. The indirect yield changes are the increases in recreational yields that would occur as a result of removing Oconee's entrainment of forage species. HOR undertook the evaluation of direct yield changes to recreational and forage species (HOR 2020) ..
After modeling the yield impacts associated with Oconee's entrainment, economic values are developed for the yield changes. Developing these values requires assessing the relationship between the recreational yield changes and the impact that these yield changes have on people.
For example, properly assessing recreational values requires understanding how Oconee's entrainment affects recreational fishing catch rates and how those changed catch rates affect the well-being of anglers located in the plant's relevant vicinity.
- 4.2 Valuing Changes in Recreational Yield For a recreational fishery, the appropriate measure for valuing changes in recreational yield is the increase in consumer surplus resulting from changes in catch rates attributable to entrainment reductions. Consumer surplus is measured using demand functions. Demand functions describe the maximum number of trips a person would be willing to take at each price over a given time period. For a nonmarket service like recreational fishing, "price" is the cost of taking a trip to that site. This cost may include transportation costs, the opportunity cost of time, entrance fees, and other trip-related costs. Differences across demand functions under Baseline and Without-Entrainment catch rates are used to identify economic benefits.
Figure 4.1 depicts an econometrically estimated demand curve from Bingham et al. (2011) for exposition purposes. Here, the example angler's round-trip travel cost is $25. 11 Consistent with the concept of diminishing marginal utility, each additional trip is valued somewhat less than the previous trip. The fifth (and higher) trip is valued at less than travel cost. Therefore, the angler maximizes his utility by taking four trips. In the figure, the gray area above the per-trip cost and 11 Travel cost consists of direct expenditures and the value of time going to and from the site .
VERITAS 45 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 below the demand curve is the difference between what an angler pays for fishing trips to a site and the value that the angler has for those trips. This area is called consumer surplus, and it is the dollar measure of the satisfaction received from trips to the site. It is the difference between what the angler actually has to pay to visit a site and how much they would be willing to pay to visit the site .
250 225 200
~
1/)
175 150 Consumer surplus 0
(.) 125 Trip cost Cl)
.......cu> 100 75 Number of trips taken at $25 per trip 50 25 0
0 1 2 3 4 5 6 7 8 9 10 Trips EPRl-0289 Figure 4.1: Example Site Demand Curve and Consumer Surplus Consumer surplus changes when a site's catch rates change. Figure 4.2 depicts the process. In the figure , the red demand curve reflects catch rates with entrainment. The blue curve depicts demand curve when the site has higher rates (Without-Entrainment) . This new demand curve is to the right of the With-Entrainment curve . For each level of visitation , the trip is more valuable because of the higher catch rates. Consequently, the angler takes more trips to the site (five trips rather than four) and these trips have a higher value .
- 46 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 250 225 200 Demand with l&E Demand without l&E
--,,, 175
~
-0
(.)
150 125 Change in Q) consumer surplus
...I-ns> 100 75 Number of trips taken at $25 per trip 50 25 +----+-- - - - - ---=-~
/
0 0 1 2 3 4 5 6 7 8 9 10 Trips EPRI-02SIO Figure 4.2: Increase in Consumer Surplus from Increase in Catch Rates Developing these estimates of demand and changes in consumer surplus requires estimating changes in angler utility associated with changes in catch rates resulting from entrainment reductions . In mathematical terms , an individual angler' s utility, U;pwJ (the well-being they receive from a fishing trip) , is treated as a random variable composed of a determin istic component and a random component. The utility associated with a recreational fishing trip to site j of waterbody type w after making participation decision p by angler i can be expressed as :
(1) where VipwJ is the determin istic part of the utility function and B;pwJ represents the random terms, which are assumed to be jointly distributed according to the generalized extreme value (GEV) distribution . V is a function of site characteristics , such as how far the site is from the angler's house, what type of fish he can catch there, how many fish he might expect to catch there, and how developed the site is.
For this assessment, the analysis uses the structure from Bingham et al. (2011) to
- estimate changes in angler utility resulting from reductions in Oconee's entrainment. An important 47 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- aspect of the angling demand model is that it can be used to estimate changes in consumer surplus attributable to site quality changes, such as improved catch rates resulting from reduced entrainment, as well as the addition or elimination of a site. For this analysis, to estimate the changes in demand that would- occur if Oconee's entrainment was not occurring, the analysis uses the results from Bingham et al. (2011) to determine how changes in catch would change anglers' trip-taking behavior and utility. The coefficients c;m expected catch in Bingham et al.
(2011) are used to link the recreational yield changes to the preferences of affected anglers presented earlier.
After esUmating the changes in catch resulting from the reduced entrainment, the analysis simulates the changes in trip patterns that anglers make in response to changes in catch rates in Lake Keowee. The economic assessment proceeds by developing the estimated changes in
. social welfare, in dollars, associated with the changes in trips that result from the changes in catch and trips. The analysis estimates the monetized benefits by calculating the difference in angler welfare without and with the increased catch rates and trips associated with reduced entrainment at Oconee .
- 48 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020
- 5. References AAA. 2_019. "Your Driving Costs." Available at https://exchange.aaa.com/wp-content/uploads/2019/09/AAA-Your-Driving-Costs-2019.pdf. Retrieved on October 18, 2019.
ASA Analysis & Communication, Inc. (ASA). 2008. Oconee Nuclear Station Impingement Mortality Characterization Report 2006-2007. Washingtonville, NY.
Adamowicz, Wiktor, Jordan Louviere, and Michael Williams. 1994. "Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities." Journal of Environmental Economics and Management 26:271-292.
Ak9akaya, H. Resit, Mark A. Burgman, and Lev Ginzburg. 2002. Applied Population Ecology Principles and Computer Exercises Using RAMAS: Second Edition. Available at http://www.ramas.com/contents.htm. Retrieved on August 7, 2012.
ALK Technologies, Inc. 2016. PC*Miler software. Princeton, NJ: ALK Technologies, Inc.
Arrow, Kenneth J., Robert M. Solow, Paul R. Portnoy, E.E. Leamer, R. Radner, and H. Schuman.
1993. "Report of the NOAA Panel on Contingent Valuation." 58 Fed. Reg. 4601 et. seq.
January 15.
Banzhaf, Melissa R., F .Reed Johnson, and Kristy E. Mathews. 2001. "Opt-Out Alternatives and Anglers' Stated Preferences." In The Choice Modelling Approach to Environmental Evaluation, Jeff Bennett and Russell Blarney, eds. Northampton, MA: Edward Elgar Publishing.
Barnthouse, Lawrence W. 2013. "Impacts of Entrainment and Impingement on Fish Populations:
A Review of the Scientific Evidence." Environmental Science & Policy 31(August):149-156.
Barnthouse, Lawrence W., Matthew Bingham, and Jason Kinnell. 2016. "Quantifying Nonuse and Indirect Economic Benefits of Impingement & Entrainment Reductions at U.S. Power Plants." Environmental Science and Policy 60:53-62.
Beggs, S., S. Cardell, and J. Hausman. 1981. "Assessing the Potential Demand for Electric Cars." Journal of Econometrics 17(1):1-19.
Bingham, M.F., Z. Li, K.E. Mathews, C. Spagnardi, J. Whaley, S. Veale, and J. Kinnell. 2011.
"An Application of Behavioral Modeling to Characterize. Urban Angling Decisions and Values." North American Journal of Fisheries Management 31 :257-268.
Bockstael, N.E., W.M. Hanemann, and Catherine L. Kling. 1987. "Estimating the Value of Water Quality Improvements in a Recreational Demand Framework." Water Resources Research 23(5):951-960.
Bockstael, N.E., W.M. Hanemann, and I.E. Strand, Jr. 1986. Measuring the Benefits of Water Quality Improvements Using Recreation Demand Models. Report to the U.S.
Environmental Protection Agency. College Park, MD: University of Maryland .
- 49 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 Bockstael, N.E., K.E. McConnell, and I.E. Strand. 1991. "Recreation." In Measuring the Demand for Environmental Quality, J.B. Braden and C.D. Kolstad, eds. North Holland: Elsevier Science Publishers B.V.
Cameron, Trudy Ann. 1985. "A Nested Logit Model of Energy Conservation Activity by Owners of Existing Single Family Dwellings." The Review of Economics and Statistics 67(2):205-211.
Carson, Richard T. 2012. "Contingent Valuation: A Practical Alternative When Prices Aren't Available." Journal of Economic Perspectives 26(4):27-42. Available at http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.26.4.27. Retrieved on December 5, 2012.
Caswell, H. 2001. Matrix Population Models. Construction, Analysis, and Interpretation, 2nd Edition. Sunderland, MA: Sinauer.
Caulkins, Peter P., Richard C. Bishop, and Nicolaas W. Bouwes, Sr. 1986. "The Travel Cost Model for Lake Recreation: A Comparison of Two Methods for Incorporating Site Quality and Substitution Effects." American Journal of Agricultural Economics 68(2):291-297.
Cesario, Frank J. 1976. "Value of Time and Recreation Benefit Studies." Land Economics 52(1):32-41.
Champ, Patricia A., Kevin J. Boyle, and Thomas C. Brown, eds. 2017. A Primer on Nonmarket Valuation, Second Edition. Dordrecht, The Netherlands: Springer.
- Electric Power Research Institute. 2004. Extrapolating Impingement and Entrainment Losses to Equivalent Adults and Production Foregone. Product ID 1008471. Palo Alto, CA:
EPRI.
Electric Power Research Institute. 2012a. Fish Life History Parameter Values for Equivalent
- Adult and Production Foregone Models: Comprehensive Update. Product No. 1023103.
Palo Alto, CA: EPRI.
Electric Power Research Institute. 2012b. Technical Comments on EPA's National Pollutant Discharge Elimination System Proposed Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities: Notice of Data Availability Related to EPA's Stated Preference Survey (Federal RegisterV77, N113; June 12, 2012).
1025381 (8). Palo Alto, CA: EPRI.
Feenberg, Daniel, and Edwin S. Mills. 1980. Measuring the Benefits of Water Pollution Abatement. New York: Academic Press.
Fisher, A., and R. Raucher. 1984. "Intrinsic Benefits of Improved Water Quality: Conceptual and Empirical Perspectives." In Advances in Applied Micro-Economics, V.K. Smith, ed.
Greenwich, CT: JAi Press Inc.
Freeman, A. Myrick, Ill. 2003. The Measurement of Environmental and Resource Values:
Theory and Methods, Second Edition. Washington, DC: Resources for the Future, Inc.
Freeman, A. Myrick, Ill, Joseph A. Herriges, and Catherine L. Kling. 2014. The Measurement of Environmental and Resource Values: Theory and Methods, Third Edition. Washington, DC: Resources for the Future, Inc.
VERITAS 50 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 Gan, Christopher, and E. Jane Luzar. 1993. "A Conjoint Analysis of Waterfowl Hunting in Louisiana." Journal of Agricultural and Applied Economics 25:36-45.
Hausman, Jerry A., ed. 1993. Contingent Valuation: A Critical Assessment. Amsterdam:
Elsevier Science Publishers.
Hausman, Jerry A. 2012. "Contingent Valuation: From Dubious to Hopeless." Journal of Economic Perspectives 26(4):43-56. Available at http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.26.4.43. Retrieved on December 5, 2012.
HOR. 2018. Oconee Nuclear Station 2-Year Entrainment Characterization Study Report.
Prepared for Duke Energy, December 2018.
HOR. 2020. "Oconee Revised Benefits." Personal communication with Erin Settevendemio on January 9, 2020.
Hensher, David A. 1991. 'The Use of Discrete Choice Models in the Determination of Community Choices in Public Issue Areas Impacting on Business Decision Making." Journal of Business Research 23(4):299-309.
Johansson-Stenman, Olaf, and Henrik Svedsater. 2008. "Measuring Hypothetical Bias in Choice Experiments: The Importance of Cognitive Consistency." The B.E. Journal of Economic Analysis & Policy 8(1) (Topics), Article 41.
Johnson, F. Reed, and Matthew F. Bingham. 2001. "Evaluating the Validity of Stated-Preference
- Estimates of Health Values." Swiss Journal of Economics and Statistics 137(1):49-64 .
Johnson, F.R., W.H. Desvousges, E.E. Fries, and LL. Wood. 1995. "Conjoint Analysis of Individual and Aggregate Environmental Preferences." TER Technical Working Paper T-9502 .. Durham, NC: Triangle Economic Research.
Johnson, F. Reed, Richard W. Dunford, William H. Desvousges, and Melissa Ruby Banzhaf.
2001. "Role of Knowledge in Assessing Nonuse Values for Natural Resource Damages."
Growth and Change 32(Winter):43-68.
Kinnell, Jason C., Matthew F. Bingham, Ateesha F. Mohamed, William H. Desvousges, Thomas B. Kiler, Elizabeth K. Hastings, and Karen T. Kuhns. 2006. "Estimating Site Choice Decisions for Urban Recreators." Land Economics 82(2):257-272.
Krutilla, John V. 1967. "Conservation Reconsidered." American Economic Review 57(4):777-786.
Leslie, P.H. 1945. "On the Use of Matrices in Certain Population Mathematics." Biometrika 33: 183-212.
Leslie, P.H. 1948. "Some Further Notes on the Use of Matrices in Population Mathematics."
Biometrika 35:213-245.
Louviere, Jordan J., Terry N. Flynn, and Richard T. Carson. 2010. "Discrete Choice Experiments Are Not Conjoint Analysis." Journal of Choice Modelling 3(3):57-72 .
- S1 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee Auqust2020 Lupi, Frank, John P. Hoehn, Heng Zhang Chen, and Theodore D. Tomasi. 1998. "The Michigan Recreational Angling Demand Model." Staff Paper 97-58, Department of Agricultural Economics. March. East Lansing, Ml: Michigan State University.
Mackenzie, John. 1993. "A Comparison of Contingent Preference Models." American Journal of Agricultural Economics 75(3):593-603.
Madenjian, Charles P., Jeffrey J. Tyson, Roger L. Knight, Mark W. Kershner, and Michael J.
Hansen. 1996. "First-Year Growth, Recruitment, and Maturity of Walleyes in Western Lake Erie." Transactions of the American Fisheries Society 125:821-830.
May, J.R., and M.K. Van Rossum. 1995. "The Quick and the Dead: Fish Entrainment, Entrapment, and Application of Section 316(b) of the Clean Water Act." Vermont Law Review 20(2)Winter:402. (See http://www.swrcb.ca.gov/rwqcb3/MorroBayDNA/Reports/TetraTechMBPP.pdf, the source of this reference.)
McFadden, Daniel. 1997. "Modelling the Choice of Residential Location." In The Economics of Housing, Volume 1, J.M. Quigley, ed. Northampton, MA: Elgar.
Mitchell, RC., and R.T. Carson. 1989. Using Surveys to Value Public Goods: The Contingent Valuation Method. Baltimore: John Hopkins University Press.
Morey, Edward R., W. Douglas Shaw, and Robert D. Rowe. 1991. "A Discrete-Choice Model of Recreational Participation, Site Choice, and Activity Valuation When Complete Trip Data Are Not Available." Journal of Environmental Economics and Management 20(2):181-201.
National Oceanic and Atmospheric Administration. 2000. "Habitat Equivalency Analysis: An Overview." Silver ~pring, MD: Damage Assessment and Restoration Program.
Available. at https://casedocuments.darrp.noaa.gov/northwest/cbay/pdf/cbhy-a.pdf.
Retrieved on June 8, 2017.
Opaluch, James J., Stephen K. Swallow, Thomas Weaver, Christopher W. Wessells, and Dennis Wichelns. 1993. "Evaluating Impacts from Noxious Facilities: Including Public Preferences in Current Siting Mechanisms." Journal of Environmental Economics and Management 24:41-59.
Page, Kevin S., Richard D. Zweifel, George Carter, Nick Radabaugh, Michael Wilkerson, Matthew Wolfe, Michael Greenlee, and Kipp Brown. 2012. "Do Anglers Know What They Catch?
Identification Accuracy and Its Effect on Angler Survey-Derived Catch Estimates." North American Journal of Fisheries Management 32(6): 1080-1089.
Pauly, D., and V. Christensen. 1995. "Primary Production Required to Sustain Global Fisheries."
Nature 374:255-257.
Phaneuf, Daniel J., and V. Kerry Smith. 2004. "Recreation Demand Models." Prepared for Handbook of Environmental Economics, Volume 2, K.-G. Maler and J.R. Vincent, eds.
Amsterdam: Elsevier Science Publishers B.V.
Public Service Electric and Gas Company (PSEG). 1999. Permit Renewal Application, NJDPES
- Permit No. NJ0005622, Salem Generating Station. March 4 .
52 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 Roe, Brian, Kevin J. Boyle, and Mario F. Teisl. 1996. "Using Conjoint Analysis to Derive Estimates of Compensating Variation." Journal of Environmental Economics and Management 31:145-59.
Schkade, David A., and John W. Payne. 1994. "How People Respond to Contingent Valuation Questions: A Verbal Protocol Analysis of Willingness to Pay for an Environmental Regulation." Journal of Environmental Economics and Management 26(1):88-109.
Schmitt, Dennis N., and Jon H. Hornsby. 1985. "A Fisheries Survey of the Savannah River."
Available at https://www.nrc.gov/docs/ML0713/ML071310323.pdf. Retrieved on January 17,2018.
Smith, V. Kerry, George L. van Houtven, and Subhrendu Pattanayak. 2002. "Benefit Transfer via Preference Calibration: 'Prudential Algebra' for Policy." Land Economics 78(1):132-152.
South Carolina Department of Natural Resources Marine Resources Division. 2019. "Summary of Laws for Commercial Herring Fishing with Legal References 2019-2020." Charleston, SC: South Carolina Department of Natural Resources.
South Carolina Wildlife Federation. 2019. Threatened and Endangered Species in South Carolina." Available at http://www.scwf.org/endangered-species. Retrieved on September 23, 2019.
U.S. Census Bureau. 2019. "Advanced Search." Available at https://www2.census.gov/data/ Retrieved December 2019 .
U.S. Environmental Protection Agency. 2002. Economic and Benefits Analysis for the Proposed Section 316(b) Phase II Existing Facilities Rule. Report Number 821-R-02-001. February.
Washington, DC: U.S. Environmental Protection Agency.
U.S. Environmental Protection Agency. 2006. Regional Benefits Analysis for the Final Section 316(b) Phase /II Existing Facilities Rule. EPA-821-R-04-007. Washington, DC: U.S.
Environmental Protection Agency.
U.S. Environmental Protection Agency. 2012. "Survey Support Document in Support of Section 316(b) Stated Preference Survey Notice of Data Availability." June. Washington, DC:
U.S. Environmental Protection Agency.
U.S. Environmental Protection Agency. 2014a. National Pollutant Discharge Elimination System-Final Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities and Amend Requirements at Phase I Facilities; Final Rule. Federal RegisterVol. 79, No. 158 (August 15):48300-48439.
U.S. Environmental Protection Agency. 2014b. Benefits Analysis for the Final Section 316(b)
Existing Facilities Rule. EPA 821-R-14-005.
U.S. Environmental Protection Agency. 2016. Guidelines for Preparing Economic Analyses.
Report Number EPA 240-R-10-001. December. Washington, DC: U.S. EPA. Available at https://www.epa.gov/sites/production/files/2017-08/documents/ee-0568-50. pdf.
Retrieved on October 22, 2018 .
- 53 VERITAS Economic Consulting
Entrainment Reduction ee*nefits Study: Oconee Auqust2020 U.S. Fish and Wildlife Service. 2004. "National Fishing License Report." Available at http://wsfrprograms.fws.gov/Subpages/Licensel nfo/FishinglicCertHistory. pdf. Retrieved on May 10, 2013.
- U.S. Fish and Wildlife Service. 2013a. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: Georgia. Available at http://www.census.gov/prod/2013pubs/fhw11-ga.pdf. Retrieved on August 30, 2013.
U.S. Fish and Wildlife Service. 2013b. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: North Carolina. Available at http://www.census.gov/prod/2013pubs/fhw11-nc.pdf. Retrieved on August 30, 2013.
U.S. Fish and Wildlife Service. 2013c. 2011 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: South Carolina. Available at http://www.census.gov/prod/2013pubs/fhw11-sc.pdf. Retrieved on August 30, 2013.
U.S. Fish and Wildlife Service. 2015. "National Fishing License Report." Available at http://wsfrprograms.fws.gov/Subpages/Licensel nfo/Fish inglicCertHistory20042015. pdf.
Retrieved on July 26, 2018.
U.S. Fish and Wildlife Service. 2017. 2016 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation: National Overview. Available at https:/wsfrprograms. fws .gov/subpages/nationalsuruvey/nat_survey2016. pdf. Retrieved on April 18, 2018.
U.S. Fish and Wildlife Service. 2019. "Listed Animals." https://ecos.fws.gov/ecp0/reports/ad-hoc-species-report?kingdom=V&kingdom=l&status=E&status=T&status=EmE&status=EmT&status=
EXPE&status=EXPN&status=SAE&status=SAT&mapstatus=3&fcrithab=on&fstatus=on&
fspecrule=on&finvpop=on&fgroup=on&header=Listed+Animals. Retrieved on September 23, 2019.
Veritas Economic Consulting. 2012. Results of the National Environmental Impacts Awareness Survey. Available at http://www.veritaseconomics.com/Working%20Papers/2012-01.Bingham.Kinnell.Hickman.National.Environmental.lmpacts.Awareness.pdf. Retrieved on April 11, 2016.
Zhao, Yingming, Patrick M. Kocovsky, and Charles P. Madenjian. 2013. "Development of a Stock-Recruitment Model and Assessment of Biological Reference Points for the Lake Erie Walleye Fishery." North American Journal of Fisheries Management 33:956-964 .
- 54 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August 2020 Appendix A Fishing Sites and Characteristics of Sites
- 55 VERITAS Economic Consulting
Entra inment Reduction Benef'rts Stud y: Oconee August 20 20 Table A .1 lists the site characteristics of Lake Keowee and substitute fishing sites in South Carolina, Georgia , and North Carolina, including estimated catch rates and fishing pressure.
Table A.1 Site Characteristics of Lake Keowee and Substitute Fishing Sites Acreage or Affected Boat No. Boat Trout. Fres hwater Other Othe r Sa ltwater Fishing Angler Sportfish Caught from Site Name Location River Latitude Long itude Ad visory Panfish Flatfish Trips Site Launch Ramps Shad Game Freshwate r Saltwate r Small Game Press ure Hrs/Ac re* Walerbody Segment Lake Keowee War Path Landing, off 18,372 acres 34.811575 -82.882390 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 3,549 15,614 31 .87 Black bass (largemouth, War Path Rd , Six Mile, redeye, smallmouth, spotted),
Pickens County, SC bluegill, catfish, crappie ,
striped bass, yellow perch Lake Keowee High Falls County Park, 18,372 acres 34.794709 -82.930703 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 3,549 15,614 31 .87 Black bass (largemouth, off High Falls Rd , redeye , smallmouth, spotted),
Seneca , Oconee bluegill, catfish, crappie ,
County, SC striped bass, yellow perch Lake Keowee High Falls County Park 18,372 acres 34.793758 -82. 931126 0 0 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 444 1,952 31 .87 Black bass (largemouth, fishing pier, off High redeye, smallmouth, spotted),
Falls Rd , Seneca, bluegill , catfish, crappie, Oconee County, SC striped bass, yellow perch Lake Keowee Stamp Creek Landing , 18,372 acres 34.826883 -82.941440 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (largemouth, Kershaw Lane , Seneca, redeye, smallmouth, spotted),
Oconee County, SC bluegill, catfish , crappie, striped bass, yellow perch Lake Keowee Keowee Sailing Club, 18,372 acres 34.727136 -82.918387 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 5,529 24,326 31 .87 Black bass (largemouth, Keowee Sailing Club redeye , smallmouth, spotted ),
Rd , Seneca , Oconee bluegill, catfish, crappie ,
County, SC striped bass, yellow perch Lake Keowee Gap Hill Landing/Sunset 18,372 acres 34.846064 -82 .880920 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 3,549 15,614 31 .87 Black bass (largemouth, Marina, Gap Hill Rd , Six redeye, smallmouth, spotted),
Mile, Pickens County, bluegill, catfish , crappie ,
SC striped bass, yellow perch Lake Keowee Keowee Town Landing, 18,372 acres 34.856527 -82.908602 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (la rgemouth ,
Keowee Town Landing redeye , smallmouth, spotted),
Rd , Salem, Oconee bluegill, catfish , crappie ,
County, SC striped bass, yellow perch Lake Keowee Arvee Lane , West 18,372 acres 34.765935 -82.968691 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 3,549 15,614 31 .87 Black bass (largemouth, Union, Oconee County, redeye , smallmouth, spotted),
SC bluegill, catfish, crappie, striped bass, yellow perch Lake Keowee Lake Keowee Marina, 18,372 acres 34.711696 -82.948469 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,299 32,114 31 .87 Black bass (largemouth, Keowee Marina Dr, redeye, smallmouth, spotted),
Seneca , Oconee bluegill, catfish, crappie, County, SC striped bass, yellow perch Lake Keowee Mile Creek County Park, 18,372 acres 34.851978 -82.883034 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 10,646 46,841 31 .87 Black bass (largemouth, State Rd S-39-327, Six redeye, smallmouth, spotted),
Mile, Pickens County, bluegill , catfish, cra ppie, SC striped bass, yellow perch Lake Keowee Fall Creek Landing, off 18,372 acres 34.903935 -82.910605 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 10,646 46,841 31 .87 Black bass (largemouth, State Rd SC-37-44, redeye, smallmouth, spotted),
Salem, Oconee County, bluegill, catfish , crappie ,
SC striped bass, yellow perch Lake Keowee Off Landing Rd , Salem , 18,372 acres 34.901421 -82.910236 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (largemouth, Oconee County, SC redeye , smallmouth, spotted),
bluegill, catfish, crappie, striped bass, yellow perch VERITAS 56 Economic Consulting
Entra inment Reduction Benef'tts study: Oco nee August 2020 Table A.1, continued Acreage or Affected Boat No. Boat Tro ut1 Freshwater Other Othe r Saltwater Fishing Angler Sportfish Caught from Site Name Location River Latitude Long itude Advisory Panflsh Flatfish Tri ps Site Launch Ramps Shad G ame Freshwate r Saltwater Small Ga me Pressure Hrs/Acre* Wate rbody Segment Lake Keowee Crowe Creek Landing, 18,372 acres 34.899665 -82.849300 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (largemouth, Crowe Creek Access red eye, smallmouth, spotted),
Rd , Sunset, Pickens bluegill, catfish , crappie ,
County, SC striped bass, yellow perch Lake Keowee Cane Creek Landing, 18,372 acres 34.735794 -82.985492 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (largemouth, Cane Creek Land ing Rd, redeye , smallmouth, spotted),
Seneca , Oconee bluegill, catfish, crappie, County, SC striped bass, yellow perch Lake Keowee South Cove County 18,372 acres 34.711376 -82.966784 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 7,097 31 ,228 31 .87 Black bass (largemouth, Park, S Cove Rd , redeye , smallmouth, spotted),
Seneca , Oconee bluegill, catfish, crappie, County, SC striped bass, yellow perch Lake Keowee Cliffs at Keowee 18,372 acres 34.955769 -82.903673 16 0.0000 0.1170 0.0360 0.9140 0.0000 0.0000 0.0000 3,549 15,614 31 .87 Black bass (largemouth ,
Vineyard, Mariner Circle, redeye, smallmouth, spotted),
Sunset, Pickens County, bluegill, catfish , crappie, SC striped bass, yellow perch Catawba River, SC Highway 9 boat ramp , Estimated 0 34.709071 -80.865988 12 0.0000 0.4047 0.2596 0.1957 0.0000 0.0000 0.0000 144,29 585,827 20.24 Bluegill, bullhead, catfish, off SC-9, west of 28,944 acres 2 crappie, largemouth bass, Lancaster Mill, (60 miles striped bass, sunfish Lancaster County, SC approx.) (redbreast, redear, other) ,
white bass Clark Hill Lake/J. Strom State Rd S-33-89, 71 ,000 acres 0 33.779455 -82.221883 4 0.0000 0.0850 0.0490 0.6250 0.0000 0.0000 0.0000 202,00 808,000 11 .38 Black crappie, bluegill , catfish, Thurmond Reservoir, Parksville, McConmick 0 chain pickerel, hybrid striped SC and Georgia County, SC bass , largemouth bass, striped bass, sunfish Fishing Creek Reservoir, Spring Parks Rd , 1,937 acres 0 34.608675 -80.881464 2 0.0000 0.3687 0.2858 0.1324 0.0000 0.0000 0.0000 6,438 25,751 13.29 Bla ck crappie , bluegill, catfish, SC Lancaster, Lancaster largemouth bass County, SC John D. Long Lake, SC Black Bottom Rd , Union BO acres 0 34.774133 -81 .515101 0 0.0000 0.0000 0.2596 0.1957 0.0000 0.0000 0.0000 256 1,041 13.01 Bluegill, catfish , largemouth County, SC bass, redear sunfish (shellaacker)
Lake Blalock, SC Off Highway 221 north 1,105 aaes 0 35.086253 -81 .886811 0 0.0000 0.4047 0.2596 0.1957 0.0000 0.0000 0.0000 3,541 14,376 13.01 Black bass (largemouth, of Spartanburg , smallmouth, spotted), catfish, Spartanburg Co unty, SC crappie Lake Cherokee, SC Lake Cherokee Road , 250 acres 0 35.042102 -81 .577003 0 0.0000 0.0850 0.0340 0.9480 0.0000 0.0000 0.0000 1,811 7,968 31 .87 Black crappie, bluegill, bowfin, Cherokee County, SC carp , catfish , largemouth bass, suckers, sunfish Lake Greenwood , SC Lake Greenwood State 11 ,400 acres 0 34.174237 -81 .920190 6 0 0.0000 0.0850 0.0360 0.9460 0.0000 0.0000 0.0000 82,572 363,318 31 .87 Channel catfish, crappie ,
Park, Ninety Six, largemouth bass, striped bass, Greenwood County, SC sunfish, white bass, white perch Lake Hartwell, SC Marina Road , Anderson, 56,000 acres 0 34.535564 -82.785328 27 0.0000 0.0000 0.0000 0.5708 0.0000 0.0000 0.0000 175,00 700,000 12.50 Chain pickerel, crappie, hybrid Anderson County, SC (SC and 0 striped bass, largemouth bass, 2 lanes Georgia) spotted bass, sunfish, striped bass, walleye, yellow perch Lake Jocassee, SC Devils For!< State Park, 7,565 acres 0 34.953392 -82.946572 3 0.0180 0.0000 0.0440 0.6150 0.0000 0.0000 0.0000 21 ,136 93,000 12.29 Bluegill; catfish ; brook, brown, Lake Jocassee Rd , and ra inbow trout; redeye Salem , Oconee County, bass; smallmouth bass; SC spotted bass; sunfish VER ITAS 57 Economic Con1ultlng
Entrainment Reduction Benerats Study: Oconee August 2020 Table A.1, continued Acreage or Affected Boat No. Boat Trout, Freshwater Other Other Saltwater Fishing Angler Sportflsh Caught from Site Name Location River Latitude Longitude Advisory Panfish Flatfish Trips Site Launch Ramps Shad Game Freshwate r Saltwater Small Game Pressure Hrs/Acre* Waterbody Segment Lake Monticello, SC Off State Rd S-20-99 6,839 aaes 0 34.376268 -81 .317904 2 0 0.0000 0.0929 0.0695 0.4923 0.0000 0.0000 0.0000 11 ,455 45,818 6.70 Bluegill, catfish, crappie ,
near Monticello, Fairfield largemouth bass, white bass County, SC Lake Murray, SC Dreher Island State 48,000 aaes 0 34.089633 -81.413212 11 0 0.0000 0.0850 0.0360 0.9460 0.0000 0.0000 0.0000 347,67 1,529,760 31 .87 Bullhead, catfish , crappie ,
Park, Prosperity, 3 largemouth bass, striped bass, Newberry County, SC sunfish, white bass, white perch Lake Rabon, SC Lake Rabon Park, 546 aaes 0 34.479438 -82.146997 0 0.0000 0.0850 0.0340 0.9480 0.0000 0.0000 0.0000 3,955 17,401 31 .87 Black bass, catfish , aappie, Laurens County, SC sunfish Lake Russell , SC Calhoun Falls State 26,650 acres 0 34.101717 -82.617186 6 0.0000 0.0850 0.0360 0.6590 0.0000 0.0000 0.0000 25,364 111 ,600 31 .87 Black bass (spotted and Park, off Calhoun Falls largemouth), catfish, crappie, State Park Rd , Calhoun striped bass, sunfish, trout Falls, Abbeville County, SC Lake Wateree, SC 4479 River Rd , 13,025 acres 0 34.437677 -80.875767 9 0.0000 0.3687 0.2858 0.1324 0.0000 0.0000 0.0000 43,276 173,102 13.29 Black crappie, catfish, Wi nnsboro, Fairfield largemouth bass, striped bass, County, SC white bass Lake Wylie, SC Blucher Cirde, Clover, 13,443 aaes 0 35.106913 -81 .038716 7 0.0000 0.3687 0.2858 0.1324 0.0000 0.0000 0.0000 44,664 178,657 13.29 Catfish, crappie, largemouth York County, SC (32 miles long, bass, striped bass, sunfish, 3.7 miles white bass, white perch wide)
Lyman Lake, SC Off Lyman Lodge Road, 350 acres 0 34.994493 -82.197032 2 0.0180 0.0850 0.0340 0.9300 0.0000 0.0000 0.0000 2,535 11 ,155 31 .87 Crappie, largemouth bass, Spartanburg County, SC northern pike, rainbow trout, smallmouth bass, wal leye, yellow bass Parr Reservo ir, SC Off Broad River Rd, 4,400 acres 0 34.286860 -81 .362670 2 0 0.0000 0.0000 0.0695 0.4923 0.0000 0.0000 0.0000 7,370 29,460 6.70 Bluegill, catfish (blue, channel ,
Pomaria, Newberry white) , largemouth and County, SC smallmouth bass, sunfish (redbreast, redear, pumpkinseed), yellow perch Saluda River, SC Off Old Anderson Rd , 11 miles 0 34.803682 -82.470728 0 0 0.0180 0.0320 0.0460 0.6370 0.0000 0.0000 0.0000 15,145 66,639 6058.09 Bluegill, carp , channel catfish ,
Greenville, Anderson chain pickerel, largemouth County, SC bass, redbreast and redea r sunfish, spotted sucker, striped bass, trout, yellow perch Blue Ridge Lake, GA Lake Dr, Morganton, 3,290 acres 0 34.869087 -84.254337 4 0.0000 0.0018 0.3860 0.1034 0.0000 0.0000 0.0000 6,636 31 ,123 9.46 Bluegill, catfish , largemouth Fannin County, Georgia and small mouth* bass, rainbow trout, walleye, white bass, yellow perch Buford Dam, GA Near Buford Dam, 31 miles 0 34.157928 -84.077246 4 0.8066 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 87,970 286,266 9,234.00 Brown and rainbow trout Cumming, Forsyth and Gwinnett Counties, Georgia Lake Burton, GA Moccasin Creek State 2,775 acres 0 34.843466 -83.587625 2 0.0000 0.0850 0.0440 0.3480 0.0000 0.0000 0.0000 10,457 46,012 16.58 Bluegill, brown trout, chain Park, off GA-197, pickerel, crappie , largemouth Clarksville, Rabun and spotted bass, redear County, Georgia sunfish, white bass Lake Lanier, GA River Forks Park, Keith 38,542 acres 0 34.287702 -83.905820 42 0.0000 0.0000 0.0000 0.5708 0.0000 0.0000 0.0000 125,35 501 ,431 13.01 Bluegill, carp, catfish , crappie ,
Bridge Rd, Gainesville, 8 largemouth bass, spotted Hall County, Georgia bass, striped bass, walleye VERITAS 58 Ec:onomic: ConsuNlng
Entrainment Reduction Benef"lts Study: Oconee August 2020 Table A.1, continued Acreage or Affected Boat No. Boat Trout, Freshwater Other Other Saltwater Fishing Angler Sportfish Caught from Site Name Location River Latitude Longitude Advisory Panfish Flatfish Trips Site Launch Ramps Shad Game Freshwater Saltwater Small Game Pressure Hrs/Acre* Waterbody Segment Nottely Lake, GA Deavers Rd , Blairsville, 4,200 acres 0 34.926452 -84.065533 5 0.0000 0.0201 0.4089 0.0353 0.0000 0.0000 0.0000 8,472 39,732 9.46 Black crappie; blue and Union County, Georgia flathead catfish ; brown trout; hybrid striped bass; largemouth, smallmouth, and spotted bass; st[iped bass; walleye ; white bass; yellow perch Bear Creek Lake , NC East of Tuckasegee, 476 acres 0 35.244147 -83.064029 0.0089 0.0000 0.1229 0.031 7 0.0000 0.0000 0.0000 472 2,504 5.26 Brown and rainbow trout, Jaci<son County, North largemouth bass, walleye Carolina Chatuge Reservoir, NC Jaci< Rabbit Rd , 6,976 acres 0 35.011214 -83.769265 3 0.0000 0.0000 0.6340 0.6090 0.0000 0.0000 0.0000 11 ,007 55,035 7.89 Bluegill; Bodie bass; channel and GA Hayesville , Clay County, catfish; crappie; largemouth, North Carolina smallmouth, and spotted bass; walleye Cheoah Reservoir, NC Off Far1ey Branch Rd , 644 acres 0 35.448057 -83.868668 0.4967 0.0277 0.0000 0.0833 0.0000 0.0000 0.0000 2,205 11 ,687 18.10 Bluegill, channel and flathead east ofTapoca , Graham catfish , crappie, muskellunge, County, North Carolina rock bass, smallmouth bass, trout Fontana Lake, NC Off Tsali Rd , Almond , 10,600 acres 0 35.394384 -83.577032 4 0.0089 0.0000 0.1229 0.0317 0.0000 0.0000 0.0000 10,520 55,756 5.26 Bluegill, brown and rainbow Swain County, North (30 miles) trout, carp, channel and Carolina flathead catfish , crappie ,
Kentucky spotted bass, largemouth and smallmouth bass, muskellunge, steelhead, walleye, yellow perch Frend, Broad River, NC 170 Apac Dr., Pisgah 70 miles 0 35.269470 -82.636245 2 0.2900 0.0000 0.1229 0.0317 0.0000 0.0000 0.0000 400 3,710 53.00 Brown and rainbow trout, Forest, Transylvania catfish , largemouth bass County, North Carolina Hiwassee Lake, NC State Rte 1447, Murphy, 6,090 acres 0 35.097190 -84.092860 3 0.0000 0.0000 0.6340 0.6090 0.0000 0.0000 0.0000 9,610 48,050 7.89 Blaci< crappie, bluegill, channel Cherokee County, North catfish, hybrid striped bass, Carolina largemouth and smallmouth bass, spotted bass, striped bass, walleye, white bass Kings Mountain Oak Grove Rd , Kings 1,500 acres 0 35.277594 -81.457959 0.0000 0.3687 0.2857 0.1155 0.0000 0.0000 0.0000 7,478 30,360 20.24 Channel catfish, crappie Lake/John H. Moss Mountain, Cleveland (blaci<, white) , largemouth Lake, NC County, North Carolina bass, hybrid striped bass, spotted bass, striped bass, sunfish, white bass Lake Glenville, NC Off Pine Creek Rd , east 1,400 acres 0 35.194108 -83.173849 3 0.0000 0.0000 0.6340 0.6090 0.0000 0.0000 0.0000 2,209 11 ,046 7.89 Bream, catfish, crappie , lake of Erastus, Jackson trout, largemouth and County, North Carolina smallmouth bass, walleye Lake James, NC Black Bear boating 6,510 acres 0 35.730190 -81 .991266 3 0.0000 0.3687 0.2858 0.1324 0.0000 0.0000 0.0000 21 ,629 86,518 13.29 Bluegill, catfish , crappie, access, off Hankins Rd , largemouth and smallmouth Marion, McDowell bass, muskellunge, walleye ,
County, North Carolina white perch Lake Lure, NC Off Memorial Highway, 720 acres 0 35.434342 -82.230317 0.2300 0.0400 0.2600 2.6600 0.0000 0.0000 0.0000 2,941 16,790 23.32 Bluegill, carp, catfish, crappie, Lake Lure, Rutherford largemouth and smallmouth County, North Carolina bass, perch, trout, white bass Mccrary Access Area , River Hwy, Mooresville, 32,510 acres 0 35.603472 -80.928987 16 0.0000 0.3703 0.2858 0.1308 0.0000 0.0000 0.0000 4,154 16,618 13.29 Bullhead , carp, crappie, catfish Lake Norman, NC Iredell County, North (blue, channel , flathead) ,
Carolina largemouth bass, striped bass, sunfish, white bass, yellow perch VERITAS 59 Economic Contutting
Entrainment Reduction Benef'rt:s study: Oconee August 2020 Table A.1, continued Acreage or Affected Boal No. Boat Trout, Freshwater Other Other Saltwater Fishing Angler Sportfish Caught from Site Name Location River Latitude Longitude Advisory Panfish Flatfish Trips Sile Launch Ramps Shad Game Freshwater Saltwater Small Game Pressure Hrs/Acre* Waterbody Segment Mountain Island Lake, Mt. Island Harbor Dr, 2,788 aaes 0 35.342197 -80.978157 2 0.0000 1.1205 0.7188 0.5418 0.0000 0.0000 0.0000 11 ,351 46,086 16.53 Bluegill, catfish, aappie, NC Chartotte, Meci<lenburg largemouth bass, striped bass, County, North Carolina sunfish, white bass, white perch Nantahala Lake, NC Off Wayah Rd , Aquone , 1,605 aaes 0 35.181826 -83.657076 3 0.0089 0.0000 0.1229 0.0317 0.0000 0.0000 0.0000 1,593 8,442 5.26 Kokanee salmon, largemouth Macon County, North and small mouth bass, stripers, Carolina steel head trout, walleye, yellow perch Santeetlah Lake, NC Off Massey Branch Rd, 1,300 aaes 0 35.335235 -83.828213 3 0.0089 0.0000 0.1229 0.0317 0.0000 0.0000 0.0000 10,526 55,788 42.90 Black bass, bluegill, catfish, Robbinsville , Graham crappie, rock bass, sunfish, County, North Carolina trout, walleye
- If rtver, angler hours per mile unless acres are given Sources: Abt Associates, Inc. (2005) ; Black (2009, 2014) ; BlueRidgeMountains.com {2019); Blue Ridge NaUonal Heritage Area (2018); City of Kings Mountain (2009); DavisHunter.com (undated); DeLonne (2006); Explore Georgia (2019) ; Georgia Department of Natural Resources et al. (2006) ; Georgia Slate Parks & Historic Siles (2019); Google Earth (2019) ; Grist (2002) ; Habera et al. (2019); Jones et al. (2000) ; Kiein (2003); Kleinschmidt (2005, 2016); Lake Lanier Partners (2019) ; LakeStromThunnond .com (2019); Madewell (2018); McRae and Waters (2008) ; Meckienburg County Government (2019); Nash , Christie , and Stroud (1990); National Park Service (2019) ; North Carolina State Parks (2019a-b) ; RA Media LLC (2019); Recreation .gov (2019a~); Rundle, Colla rt, and McRae (2009); RussellLakesOnline .com (2019) ; Schmitt and Hornsby (1985); Siter, Foris, and Mcinern y (1986) ; Smoky Mountain Host (2019); South Carolina Department of Parks , Recreation and Tourism (2008 , 201 9a-g) ; South Carolina Office of Tourism (2019a-b); South Carolina State Parks (2019a-b); South Carolina Trails (2019) ; Spartanburg County Parks Department (2019); Sport Fishing Institute (1984) ; U.S. Army Corps of Engineers (2019a-b); U.S.
Environmental Protedion Agency (1994); U.S. Forest Service (2019a-e) ; Yow, Loftis, and Ganus (2002)
VERITAS 60 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020
- References Abt Associates, Inc. 2005. Linking Ecological Risk Assessment and Economic Benefits.
Prepared for National Center for Environmental Economics Office of Policy, Economics and Innovation, US Environmental Protection Agency. Contract #68-W-99-042, Work Assignment 4-44.
Black, William P. 2009. Tennessee Reservoir Creel Survey 2008 Results. Available at http://pbadupws.nrc.gov/docs/ML 1413/ML14132A090.pdf. Retrieved on June 22, 2017.
Black, William P. 2014. Tennessee Statewide Creel Survey 2013 Results: Final Report.
Nashville, TN: Tennessee Wildlife Resources Agency. Available at http://twra4streams.homestead.com/Report_-_2013_Final.pdf. Retrieved on August 25, 2017.
BlueRidgeMountains.com. 2019. "Lake Blue Ridge Water Fun." Available at https://www.blueridgemountains.com/things-to-do/outdoors/water-sports/lake-blue-ridge/. Retrieved on September 23, 2019.
Blue Ridge National Heritage Area. 2018. "Fontana Dam and Visitor Center." Available at https://www.blueridgeheritage.com/destinations/fontana-dam/. Retrieved on September 23, 2019.
City of Kings Mountain. 2009. "John H. Moss Reservoir." Kings Mountain, NC: John H. Moss Reservoir.
DavisHunter.com. Undated. "Devils Fork State Park." Available at http://www.davishunter.com/home/place/Devils%20Fork%20State%20Park. Retrieved on September 19, 2019.
Delorme. 2006. North Carolina Atlas and Gazetteer. Yarmouth, ME: Delorme.
Explore Georgia. 2019. "Lake Nottely." Available at https://www.exploregeorgia.org/blairsville/outdoors-nature/fishing/lake-nottely. Retrieved on September 23, 2019.
Georgia Department of Natural Resources, South Carolina Department of Natural Resources, South Carolina Department of Health and Environmental Control, U.S. Army Corps of Engineers, U.S. Fish and Wildlife Service. 2006. Lake Hartwell Restoration and Compensation Determination Plan: Final. Available at https://dc.statelibrary.sc.gov/handle/10827/11272. Retrieved on September 16, 2019.
Georgia State Parks & Historic Sites. 2019. "Moccasin Creek State Park." Ayailable at https://gastateparks.org/MoccasinCreek. Retrieved on September 23, 2019. '.
1 Google Earth. 2019. Google Earth Pro, version 7.3. Available at Google.com.
Grist, Joseph Daniel. 2002. "Analysis of a Blue Catfish Population in a Southeastern Reservoir:
Lake Norman, North Carolina." Blacksburg, VA: Virginia Polytechnic Institute and State University. Available at https://vtechworks.lib.vt.edu/handle/10919/35040. Retrieved on September 29, 2017 .
- 61 VERITAS Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 Habera, James W., Sally J. Petre, Bart D. Carter, and Carl E. Williams. 2019. Region 4 Trout Fisheries Report 2018. Fisheries Report 19-08. Jackson, TN: Tennessee Wildlife Resources Agency.
Jones, T. Wayne, William J. Collart, Doug Hinshaw, and Scott Van Horn. 2000. "Harris Lake Creel Survey, 1997-1998." Piedmont Fisheries Investigations. Raleigh, NC: North Carolina Wildlife Resources Commission Division of Inland Fisheries. Available at https://www.nrc.gov/docs/ML 1129/ML11292A106.pdf. Retrieved on January 17, 2018.
Klein, Lisa. 2003. "Investigation of the Trout Fishery in the Chattahoochee River Below Buford Dam." Social Circle, GA: Georgia Department of Natural Resources Wildlife Resources Division.
Kleinschmidt. 2005. Saluda Hydro FERG Project No.516 Saluda Hydro Initial Consultation Document. Prepared for South Carolina Electric & Gas Company. Columbia, SC: South Carolina Electric & Gas Company.
Kleinschmidt. 2016. Recreation Use and Needs Study Report Parr Hydroelectric Project. FERG No. 1894. Prepared for South Carolina Electric & Gas Company. Lexington, SC:
Kleinschmidt.
Lake Lanier Partners. 2019. "Lake Lanier Boat Ramps." Available at http://www.lakelanierboatramps.com/. Retrieved on September 18, 2019.
LakeStromThurmond.com. 2019. "About Lake Strom Thurmond." Available at http://lakestromthurmond.com/. Retrieved on September 23, 2019 .
Madewell, Terry. 2018. "5 Fall Hotspots for South Carolina Bass." Available at https://www.gameandfishmag.com/editorial/5-fall-hotspots-for-south-carolina-bass/190046. Retrieved on September 18, 2019.
McRae, Brian J., and Christian T. Waters. *2008. "Lake Norman Recreational Angling Survey."
In "2008 Annual Meeting Program," North Carolina Chapter American Fisheries Society, February 18-20. Available at nc.fisheries.org/wp-content/uploads/2014/09/2008ProgramAndAbstracts.pdf. Retrieved on February 1, 2018.
Mecklenburg County Government. 2019. "McDowell Nature Center and Preserve." Available at https://www.mecknc.gov/ParkandRec/StewardshipServices/NatureCenters/Pages/McDo well.aspx: Retrieved on September 23, 2019.
Nash, Val S., Richard W. Christie, and Robert M. Stroud. 1990. "Fisheries Investigations in Lakes and Streams District IV." Available at https://www.nrc.gov/docs/ML0303/ML030300694.pdf. Retrieved on February 1, 2018.
National Park Service. 2019. "An Ancient River in a Modern City." Available at https://www.nps.gov/chat/index.htm. Retrieved on September 23, 2019.
North Carolina State Parks. 2019a. "Chimney Rock State Park." Available at https://www.ncparks.gov/chimney-rock-state-park. Retrieved on September 23, 2019.
North Carolina State Parks. 2019b. "Lake Norman State Park." Available at https://www.ncparks.gov/lake-norman-state-park. Retrieved on September 11, 2019.
VERITAS 62 Economic Consultlng
Entrainment Reduction Benefits Study: Oconee August 2020 RA Media LLC. 2019. "Lake Glenville, NC." Available at https://www.romanticasheville.com/lake_glenville.htm. Retrieved on September 23, 2019.
Recreation.gov. 2019a. "Hiwassee Lake." Available at https://www.recreation.gov/camping/gateways/1912. Retrieved on September 23, 2019.
Recreation.gov. 2019b. "J. Strom Thurmond Lake." Available at https://www.recreation.gov/camping/gateways/453. Retrieved on September 23, 2019.
Recreation.gov. 2019c. "Lake Nottely." Available at https://www.recreation.gov/camping/gateways/1913. Retrieved on September 23, 2019.
Rundle, Kirk, Bill Collart, and Brian McRae. 2009. "Lake Gaston Creel Survey, 2007-2008 Roanoke Rapids and Gaston, FERC Project No. 2009 Article 422 Recreation Monitoring."
Raleigh, NC: North Carolina Wildlife Resources Commission Division of Inland Fisheries.
RussellLakesOnline.com. 2019. "Fishing at Richard 8. Russell Lake, Georgia." Available at http://russell.lakesonline.com/Fishing/. Retrieved on September 18, 2019.
Schmitt, Dennis N., and Jon H. Hornsby. 1985. "A Fisheries Survey of the Savannah River."
Available at https://www.nrc.gov/docs/ML0713/ML071310323.pdf. Retrieved on January 17, 2018.
Siler, J. Robert, William J. Faris, and Michael C. Mcinerny. 1986. "Spatial Heterogeneity in Fish
- Parameters within a Reservoir." In Reservoir Fisheries Management Strategies for the BO's, G.E. Hall and M.J. Van Den Avyle, eds., pp. 122-136.
Smoky Mountain Host. 2019. "Fontana Lake Camping Trips." Available at https://www.visitsmokies.org/smoky-mountain-blueways/fontana-lake/fontana-lake-camping-trips/. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation and Tourism. 2008. South Carolina State Comprehensive Outdoor Recreation Plan (SCORP). Columbia, SC: South Carolina Department of Parks, Recreation and Tourism Recreation, Planning and Engineering Office.
South Carolina Department of Parks, Recreation & Tourism. 2019a. "Dreher Island State Park."
Available at https://southcarolinaparks.com/dreher-island. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation & Tourism. 2019b. "Keowee Toxaway State Park." Available at https://southcarolinaparks.com/keowee-toxaway. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation & Tourism. 2019c. "Lake Greenwood State Park." Available at https://southcarolinaparks.com/lake-greenwood. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation & Tourism. 2019d. "Lake Hartwell State Park."
Available at https://southcarolinaparks.com/lake-hartwell. Retrieved on September 12, 2019 .
VERITAS 63 Economic Consulting
- Entrainment Reduction Benefits Study: Oconee August 2020 South Carolina Department of Parks, Recreation & Tourism. 2019e. "Lake Wateree State Park."
Available at https://southcarolinaparks.com/lake-wateree. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation & Tourism. 2019f. "Landsford Canal State Park." Available at https://southcarolinaparks.com/landsford-canal. Retrieved on September 12, 2019.
South Carolina Department of Parks, Recreation & Tourism. 2019g. "Sadlers Creek State Park."
Available at https://southcarolinaparks.com/sadlers-creek. Retrieved on September 12, 2019.
South Carolina Office of Tourism. 2019a. "Fishing Creek Reservoir." Available at https://discoversouthcarolina.com/products/25578 .. Retrieved on September 12, 2019.
South Carolina Office of Tourism. 2019b. "Lake Monticello Reservoir." Available at https://discoversouthcarolina.com/products/25575. Retrieved on September 12, 2019.
South Carolina State Parks. 2019a. "Calhoun Falls State Park." Available at https://southcarolinaparks.com/calhoun-falls/things-to-do. Retrieved on September 17, 2019.
South Carolina State Parks. 2019b. "Devils Fork State Park." Available at https://southcarolinaparks.com/devils-fork/faqs. Retrieved on September 17, 2019.
South Carolina Trails. 2019. "Lake Rabon Park." Available at https://www.sctrails.net/trails/trail/lake-rabon-park. Retrieved on September 23, 2019 .
Spartanburg County Parks Department. . 2019. "Lake Blalock Park." Available at https://spartanburgparks.org/facilities/facility/details/Lake-Blalock-Park-71. Retrieved on September 12, 2019.
Sport Fishing Institute. 1984. "Adequacy and Predictive Value of Fish and Wildlife Planning Recommendations at Corps of Engineers-Reservoir Projects." Washington, DC: U.S.
Army Corps of Engineers.
U.S. Army Corps of Engineers. 2019a. "Lake Sidney Lanier." Available at Available at https://www.sam.usace.army.mil/Missions/Civil-Works/Recreation/Lake-Sidney-Lanier/.
Retrieved on September 23, 2019.
U.S. Army Corps of Engineers. 2019b. "Richard B. Russell Dam and Lake." Available at https://www.sas.usace.army.mil/About/Divisions-and-Offices/Operations-Division/Richard-B-Russell-Dam-and-Lake/Plan-a-Visit/Trails/. Retrieved on September 23, 2019.
U.S. Environmental Protection Agency. 1994. Final Record of Decision forthe Sangamo Weston, lnc./Twelvemile Creek/Lake Hartwell PCB Contamination Superfund Site-Operable Unit Two Pickens, Pickens County, South Carolina. Atlanta, GA: U.S. EPA U.S. Forest Service. 2019a. "Cheoah Point Recreation Area." Available at https://www.fs.usda.gov/wps/portal/fsinternet/cs/recarea?ss= 110811 &navtype=BROWS EBYSUBJECT&cid=FSE_003738&navid=110240000000000&pnavid=11000000000000 VERITAS 64 Economic Consulting
Entrainment Reduction Benefits Study: Oconee August2020 0&position=generalinfo&recid=48928&ttype=recarea&pname=Cheoah%20Point%20Rec reation%20Area. Retrieved on September 23, 2019.
U.S. Forest Service. 2019b. "Hanging Dog Recreation Area." Available at https://www.fs.usda.gov/recarea/nfsnc/recarea/?recid=48914. Retrieved on September 23, 2019.
U.S. Forest Service. 2019c. "Jackrabbit Mountain Recreation Area, Nantahala National Forest, North Carolina." Available at
- https://www.fs.usda.gov/detail/nfsnc/recreation?cid=stelprdb5389305. Retrieved on September 23, 2019.
U.S. Forest Service. 2019d. "Lake Russell Recreation Area." Available at https://www. fs. usda .gov/wps/portal/fsinternet/cs/recarea?ss= 11 0803&navtype=BROWS EBYSUBJECT&cid=FSE_003738&navid=110240000000000&pnavid=11000000000000 0&position= BROWS EBYS UBJ ECT&recid= 10490&actid=29&ttype=recarea&pname= Lak e%20Russell%20Recreation%20Area. Retrieved on September 17, 2019.
U.S. Forest Service. 2019e. "Nantahala National Forest." Available at https://www.fs.usda.gov/recarea/nfsnc/recarea/?recid=48634. Retrieved on September 23, 2019.
Yow, David L., C. Scott Loftis, and Eric Ganus. 2002. Creel Surveys of Santeetlah, Cheoah, Calderwood, and Chilhowee Reservoirs, 1998-99 Final Report. Federal Aid in Fish Restoration Project F-24. Raleigh, NC: North Carolina Wildlife Resources Commission .
- 65 VERITAS Economic Consultlng
This page intentionally left blank.
Appendix 11-F Sources of Uncertainty in Entrainment and Impingement Analyses
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 11-F rL "\-,_
.I~
- 1 Sources of Uncertainty in Entrainment and Impingement Analyses The Benefits Valuation Study, presented in the Clean Water Act (CWA) §316(b) compliance submittal document as Section 11, presents the estimated incremental changes in annual entrainment losses and the associated benefit, both ecological and economic, of entrainment reductions achievable under each of the candidate entrainment reduction compliance scenarios evaluated for Oconee Nuclear Station (Oconee) in Section 10. The assumptions and Best Professional Judgment (BPJ) decisions made during model development are summarized in Appendix 11-B. Data from the 2016-2017 Entrainment Characterization Study (Study) (discussed in Section 9 of the compliance document) and a historical impingement study (discussed in Section 4 of the compliance document) at Oconee were incorporated into the equivalent adult, production foregone, and equivalent yield (which calculates harvest foregone) models to provide annual loss and benefit estimates for each of the selected candidate entrainment reduction compliance scenarios.
1.1 Types of Uncertainty Uncertainty exists in almost all model-based estimation techniques, especially for environmental and economic estimations or predictions, due to the dynamic nature inherent to both fields. Uncertainty in benefit valuation studies typically arises from three general sources: (1) natural variation, (2)
- uncertainty in the structure of the model, and (3) uncertainty in values for model input parameters (EPRI 2006).
Natural Variation - Uncertainty may result from natural variation within a population or within a population over time. The model-derived entrainment loss and benefit estimates were based on data from the 2-year Study performed at Oconee. The estimated changes in stock and harvest presented in Section 11 of the compliance document are provided separately for 2016 and 2017 based on data from the Study to quantify model uncertainty resulting from interannual variation in entrainment at Oconee.
Model Structure - Uncertainty related to model structure is oftentimes related to the uncertainty in choosing the most appropriate model to estimate a given process or achieve a specific end result (e.g.,.mortality estimates). The equivalent adult, production foregone, and equivalent yield models used for the Oconee Benefits Valuation Study were selected because of their acceptance by biological professionals, the Electric Power Research Institute (EPRI), and the U.S. Environmental Protection Agency (USEPA). An additional assumption related to model structure within the Oconee models is that the mechanical draft cooling tower (MDCT) scenario would result in reductions to entrainment due to decreases in cooling water withdrawals based on an assumption of a linear relationship.
Model Parameters - Estimated environmental and economic benefit values are especially sensitive to uncertainty in model input parameters due to inherent variability, limited understanding of underlying processes, and challenges in making accurate measurements of the underlying model parameters (EPRI 2006). The equivalent adult and production foregone model parameters used to Duke Energy I 11-F-1
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316{b) Compliance Submittal L -.,-,.
Appendix 11-F r .I~
- estimate the changes in fish stock and harvest under candidate entrainment reduction technologies are no exception regarding concerns with parameter uncertainty. The underlying model input parameters are based on species and stage-specific life history information, including life stage durations, body weights (start of life stage and median weight at death), fishing mortality, and natural mortality. Natural mortality, specifically, exhibits a high degree of sensitivity in equivalent adult and production foregone models (EPRI 2006). However, as stated by EPRI (2016), "given the variability in fish life history characteristics between sites, regions, ecosystems and years, no single set of values could accurately reflect growth and mortality rates expected at every site of interest."
Additionally, species and stage-specific life history information has not been developed for many species encountered throughout the United States, thus making it difficult to develop site- or region-specific life history tables.
A summary of potential sources of uncertainty (such as surrogate species information, life history table development, age of equivalence designations, use classifications, through-plant and on-screen survival incorporation, and trophic transfer), the approach used to address these uncertainties, and implications on the estimated losses and benefits is included in Table 11-F1 .
- Duke Energy I 11-F-2
Duke Energy Carolinas, LLC 1Oconee Nuclear Station CWA §316(b) Compliance Submittal 1-~"'\
Append ix1 1-F J~
Table 11-F1. Sources of Uncertainty in Entrainment and Impingement Analyses Category of Input Approach Rationale Alternatives Implications for Model Outputs (Losses) and/or Benefits Valuation
- Threadfin Shad were the dominant species collected in purse seine sampling nearest to the fa cility (Southern Upper Lake Keowee) (Duke Energy 2013).
- Unidentified Clupeidae spp. mapped to
- Selection of Gizzard Shad or Blueback Herring would result in a more Only 1 Gizzard Shad had been sampled in purse Threadfin Shad
- Map to a larger species conseivative (i.e., greater) estimate of production foregone biomass, as both se ines, and none in electrofish ing, and therefore
- Threadfin Shad are a fragile forage species species are larger and have longer life spans than Threadfin Shad.
indicates limited population in Oconee. Blueback Herring were dominant in Northern Upper Lake Keowee .
Surrogate Species Used to substitute l~e
- Threadfin Shad were the dominant species collected history information due to in purse seine sampling nearest to the facility limited available (Southern Upper Lake Keowee) (Duke Energy 2013).
information or low
- Dorosoma spp. mapped to Threadfin Shad Only 1 Gizzard Shad had been sampled in purse Map to Gizzard Shad, a larger species
- Selection of Gizzard Shad would result in a more c:onseivative (i.e., greater) resolution of organism
- Threadfin Shad are a frag ile forage species se ines, and none in electrofishing, and therefore of Dorosoma estimate of production foregone biomass, as it is a larger species.
identification indicates limited population in Oconee. Blueback Herring were dominant in Northern Upper Lake Keowee.
- Surrogate species information or mapping was
- Selection of Emerald Shiner may result in an underestimate of production Golden Shiner mapped to Emerald Shiner preferential to within the same family/subfamily foregone biomass for this species
- No better alternative identffied Emerald Shiner is a smaller shiner species (Leuciscinae), however no larger shiner/Golden
- Unavailable infonnation for true life history characteristics result in unknown Shiner life history information was identffied variability and uncertainty in the applied data.
Life History Table
- Populations are generally stable in the long-term Balancing
- Negative net growth of a population may underestimate the benefits for each
- Natural mortalrty adjusted to achieve a
- Limits the magnitude of the biases in model
- Assume population is growing technology.
Assumption that a *balanced* lrfe history table for a net-zero per projections that can occur when parameters are population is neither generation growth rate (EPRI 2004a, 2012)
- Assume population is declining
- Positive net growth of a population may overestim ate the benefit of each developed by combining data from different studies increasing nor decreasing. technology.
(EPRI 2004a)
Age of Equivalence
- A comparison of age of equivalence for both, recreational or forage species (age of entry to the fishery or age of reproductive maturity, respectively) showed The age to which the model
- Age of equivalence was defined as the age of
- Setting the age of equivalence to a several ages were 1 to 3 years above age 1.
is extrapolated. Commonly entry to the fishery for recreational species, and
- Setting the age of equivalence according to fishing designated age (age 1 is common)
- A lower age of equivalence (i.e., age 1) would have an effect on the equivalent selected ages of the age of reproductive maturity for forage pressure (for recreational species) accounts for
- Setting the age of equivalence to the adult model by increasing the number of equivalent adult losses due to a shorter equivalence are: age 1, the species potential harvest patterns age of reproductive maturity (for period of time for the fish to experience cumulative natural mortality, however it age of entry to a fishery, or the age of sexual maturity recreational species) may reduce the equivalent adult biomass since the fish would be of smaller size .
(EPRI 2012). Similarly, production foregone biomass may or may not be lower or higher due to a greater number of fish contributing to the biomass, but of a smaller size.
Use Cla111ftc1tlon Species were designated
- Selection of a larger fragile species (e.g., Gizzard Shad) would result in a higher
- Mapped eggs to Blueback Herring based on seasonal as either forage/non-game production foregone estimate.
- Unidentified eggs and larvae mapped to occurrence and other egg identification in entrainment (forage) or
- Map to larger species
- Selection of a robust species wou ld result in lower mortality rates and therefore Blueback Herring and Threadfin Shad samples commercially/recreationally
- Map to robust species greater survival and benefits in the fine-mesh screen (FMS) candidate
- Blueback Hernng and Threadfin Shad are
- Mapped larvae to Threadfin Shad based on species harvestable (CIR). Some
- Map to recreational species technology scenario.
species' classifications can fragile forage species selection for Clupeidae spp. and Oorosoma spp./abundance of fragile forage species in collections
- Selection of a recreational species would contribute to equivalent adult be site-specific, dependent estimates {versus production foregone) .
on the local fishery.
Duke Energ y j 11-F-3
Duke Energy Carolinas, LLC I Ocon ee Nuclear Station CWA §316(b) Complian ce Submittal Appendix 11-F Category of Input Approach Rationale Alternatives Implications for Model Outputs (Losses) and/or Benefits Valuation Through-Plant Survival The Environmental Protection Agency (USEPA) assumes 100
- No through-plant survival studies have been
- Through-plant survival may occur under
- If su rvival was detected, it would reduce the benefrts of each technology (FMS percent mortality of
- Assume 100% mortality of entrained organisms perfonned at Oconee the right conditions (EPRI 2018) and MDCT) in proportion to the percent survival assumed entrained organisms (79 Fed. Reg. 158, 48318)
(USEPA 2014).
- Due to limited on-screen survival data, species-
- Overestimating survival may overestimate the benefit of screening candidate specific or mesh size-specific survival rates were
- Several species within the Clupeidae family are technologies.
unavailable included on the fragile species list (§ 125.92(m))
- Assume 100% survival
- A lack of species-specific on-screen mortality may result in an over- or
- Taxa were ciassrfied as either "fragile* (dupeids)
- Fragile speoes naturally have low tolerance ranges for
- Apply the same on-screen survival underestimate of losses due to FMS or coarse-mesh screen impingement (post-or *robusr (all other taxa) environmental conditions or trauma values to all taxa based on available impingemenl Best Technology Available (PoS1-IM BTAJ scenario).
- On-saeen survival values were calculated for
- Fragile species should not have the same mortality information, as one group
- Assumptions of fragile species designations can overestimate losses, however if each group based on data found in literature rates as robust species, or v,se-versa they were considered robust they could potentially overestimate benefits of FMS On-Screen Survival (E PRI 2003, 2004b, 2006, 2010, 2013) due to higher survival rates .
Applied to account for mortality due to
- Initial suMYal can be high for many species, inciuding fragile species.
impingement on a coarse-
- Latent survival was used in the application of on-
- The Rule specifies the impingement mortality standard Overestimating on-screen survival would result in an underestimation of mesh screen or FMS . to apply to fish held and evaluated for a penod of 18 to 1 1
- Apply initial survival instead of latent impingement mortality (for coarse-mesh screens) and entrainment (convert (converts). ~:~~: u ~ ! ::su:nsidered survival after 18 96 hours0.00111 days <br />0.0267 hours <br />1.587302e-4 weeks <br />3.6528e-5 months <br /> (79 Fed. Reg . 158, 48323) survival mortality on FMS), thereby overestimating benefits of screening candidate hours of impingement
- Initial suMYal can be up to 100 percent, even for fragile technologies.
species (EPRI 2003)
- A higher robust-adult mortality rate (i.e., lower survival rate) would result in
- Assumed a robust-adult on-screen survival of
- The impingement mortality standard was developed
- Use the calculated on-screen survival for substantially higher loss estimates.
76%, the impingement mortality standard (79 and established after thorough testing of organism on- robust adults from available data, which
- Overestim ating losses would reduce the potential benefits of FMS or Post-lM Fed. Reg . 158, 48323)(USEPA 2014) screen survival was 68%
BTA.
- A comparative analysis of trophic levels derived from FishBase.org and
- Use alternative website/database (i. e., SeaAroundUs.org showed trophic levels to be, generall y, slightly higher from SeaAroundUs.org by Pauly and Zeller FtshBase.org. Higher trophic level differences between harvested and forage
- Trophic levels obtained from FishBase.org
- FishBase.org is a comprehensive database of fish 2015 ) species results in a lower transfer efficiency due to energy losses, such as
( Froese and Pauly 2018) information regularty cited by th e scientific and
- Calculate based on diet information metabolic heat This would result in a lower impact to economically important
. . . regulatory community
- Generally the trophic level dunng its adults stage
- An organism spends a longer period of time in the adult derived from literature species and yield developed in the benefits model.
Trophic Levels and
- If trophic level efficiencies are generally higher across use classifications (i.e.,
life stage compared with early life stages
- Use variable trophic levels based on life Efficiency stage/diet transitions higher for both, forage and recrea tiona l species), then the effect may be less Appl ied for the Best Professional Judgment impactlul to the biological model, though the difference is large ly contingent on a incorporation of PF species-paring basis.
calculated for forage species for indusion to the
- More accurately represents the predator-prey benefits analysis relationships in the vicinity of the CWIS and the
- Calculated gross trophic transfer efficiency may be lower (8.2-10.0%) than the
- Trophic transfer efficiency was calculated using potential benefits of entrainment reduction via prey assumed value used by the USE PA.
site-specific data biomass transfer to econom ically valuable predator
- Assume 10% gross transfer (Lindeman
- A lower trophic transfer efficiency results in a lower portion of biomass
- Used a
- surrogate* recreationa l predator species species 1942; USEPA 2006) transferred to recreational species.
to assume forage biomass transfer
- The trophic transfer method is an oversimplification of
- Underestimating biomass transferred would underestimate yield, and therefore, the complex ecosystem and food web relationsh ips benefits of a given technology.
w ithin a given watert>ody (Bums 1989, US EPA 2006)
Duke Energy I 11-F-4
Duke Energy Carolinas, LLC I Oconee Nuclear Station CWA §316(b) Compliance Submittal
. Appendix 11-F rL ~"II
.I~
e References Burns, T.P. 1989. Lindeman's Contradiction and the Trophic Structure of Ecosystems. Ecology 70(5): 1355-1362.
Duke Energy. 2013. Oconee Nuclear Station 316(a) Demonstration Report. NPDES No.
SC0000515. Duke Energy Environmental Services McGuire Environmental Center, Huntersville, NC. March 2013. 136 pp.
Electric Power Research Institute (EPRI). 2003. Evaluating the Effects of Power Plant Operations on Aquatic Communities. Final Report 1007821. Palo Alto, CA.
_ _ . 2004a. Extrapolating Impingement and Entrainment Losses to Equivalent Adults and Production Foregone. Final Report 1008471. Palo Alto, CA.
_ _ . 2004b. Chapter 1. Traveling Water Screens. Technical Report 1011546. Palo Alto, CA.
_ _ . 2006. Laboratory Evaluation of Modified Ristroph Traveling Screens for Protecting Fish at Cooling Water Intakes. Final Report 1013238. Palo Alto, CA.
_ _ . 2010. Laboratory Evaluation of Fine-Mesh traveling Water Screens. Final Report 1019027.
Palo Alto, CA.
_ _ . 2012. Fish Life History Parameter Values for Equivalent Adult and Production Foregone Models: Comprehensive Update. Final Report 1023103. Palo Alto, CA.
- _ _. 2013. Engineering and Biological Assessment of Fine Mesh Fish Protection-Modified Traveling Water Screens. Technical Update 3002001104. Palo Alto, CA.
_ _ . 2018. Entrainment Survival Transferability: Application of Prior Studies' under the 2014
§316(b) Rule. Technical Report 3002013685. Palo Alto, CA.
Froese, R. and D. Pauly, Editors. 2018. FishBase. World Wide Web electronic publication, version 10/2018. [URL]: www.FishBase.org.
Lindeman, R.L. 1942. The Trophic-Dynamic Aspect of Ecology. Ecology 23(4): 399-417.
Pauly D. and Zeller D. (Editors). 2015. Sea Around Us Concepts, Design and Data. [URL]:
www.seaaroundus.org .
U.S. Environmental Protection Agency (USEPA). 2006. Regional Benefits Analysis for the Final Section 316(b) Phase Ill Existing Facilities Rule. EPA-821-R-04-007.
_ _ . 2014. National Pollutant Discharge Elimination System - Final Regulations to Establish Requirements for Cooling Water Intake Structures at Existing Facilities and Amend Requirements at Phase I Facilities, 79 FR 158, 48299 (August 15, 2014) .
- Duke Energy I11-F-5
This page intentionally left blank.
Appendix 12-A Estimated Increase in Energy Consumption due to a Hypothetical Cooling Tower Retrofit at Oconee Nuclear
- Station
This page intentionally left blank.
Duke Energy Carolinas, LLC I Ocon ee Nuclear Station Revilion. .
Issue Date 8/31/2020 Estimated Increase in Energy Consumption due to a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station Originator: Spencer Nush, EIT 9/6/2019 Reviewer: Scott Loughery, PE 10/1/2019 Approver. Scott Loughery, PE 4/10/2020 Revi sion No. Revised bv: Aooroved bv : Description 1 SRL TKZ Number of cooling tower cells has been revised .
Calculation Summary:
Energy ~ul19ment Unlta Unlt1 Unlt2 Unlt3 Pumps MW 16.2 16.2 16.2 Fans MW 6 .7 6 .7 6 .7 Backpressu re Energy Penalty MW 5.2 5.3 5.3 Total Annual Maximum MWhr / year 246 ,338 246,592 247,050 Operational Total with Capacity Utilization Rate MWhr / year 226 ,123 236,549 236,190 Construction Outage Energy Loss MWhr 3,420,384 3,374,040 3,495,456
- 1 of S
Duke Energy Carolinas, LLC I Oconee Nuclear Station Issue Date* 8/31/2020 Estimated Increase in Energy Consumption due to a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County , SC . Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Estimate the consumptive energy use associated with a retrofit of the current once-through cooling system to a closed-cycle cooling system, and by the construction outage required to tie in the hypothetical mechanical draft cooling tower to the closed-cycle cooling system.
Calculation Objective s:
- 1. List the calculation methodology and data required for the calculations.
2 . Provide the inputs required for the calculations .
- 3. Estimate the parasitic energy losses.
4 . Estimate the backpres sure energy penalty.
- 5. Estimate the construction outag e energy loss .
- 2 of s
Duke Energy Carolinas, LLC I Oconee Nuclear Station R1viaion: 0 luue01te: 8/31/2021)
Estimated Increase in Energy Consumption due to a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station Ca lculation Methodology:
Formula 1 P,,..,.,. = ( ( (H,
- a,
- SG ) / 3956 J/ ~ J
- N,.,,.,.
- C1 111 Unils: MW where:
PBJ:unp
- Power required to operate closed-cycle cooling system booster pumps (MW) 0 8 = Booster pump discharge capacity (gpm)
H8 .. Hydraulic head required for booster pumps to circulate water through cooling system Note 1 (H,,) , (ft)
SG = Specific gravity of cooling water Auumption1 ri
- Efficiency (%)
NBplnlp a Number of booster system pumps required C1 = Conversion factor from hp to MW (MW/ hp)
Formula 2 PMpvmp = ( ((H M* Q M* SG) / 3956 J/ r, )
- N Mpump
- C1 Units: MW
'M'lere:
PMp,.rnp = Power required to operate closed-cycle cooling system make-up pumps (MW)
QM* Make-up pump discharge capacity (gpm)
HM* Hydraulic head required for make-up water pumps to circulate water through cooling system (H.,J , (ft)
NM~* Number of make-up pumps required Fonnula 3 P1a11 = P111111
- N,an
- C1 Units: MW where:
P,.,
- Power required to operate closed-cycle cooling system fans (MW)
P;, ,.,, = Power required to operate an individual fan (hp)
N1.,
- Number of cooling system fans required Auumpion2 Fonnula 4 PaPEP = C 11 ,ou
- l!ap£P Units: MW where:
PBF'EP = Power lost to the backpressure energy penalty (MW) Note2 C AfOH
- Gross generating capacity of facility (MW) l! Bf>Ep = Backpressure energy penalty(%) Note3 Fonnula 5 P Total = ( P apunlf) + PMpump + P,.., + P al'EP )
- OP Auunl)lion 3 Units: MIM'lr where:
PTo111I
- Total energy loss if the plant were utilized 100 percent of the time with a closed-cycle coo ling system in place (MWhr)
OP= Annual operating hours (hr) or 8,760 hours0.0088 days <br />0.211 hours <br />0.00126 weeks <br />2.8918e-4 months <br /> Fonnula 6 Pop= PTo1a1
- CUR Assumption3 Units: MIM'lr where:
POfl = Total energy loss assuming current capacity utilization extends into future operations as well (MWhr)
CUR
- Average capacity utflization rate (%)
Fonnula 7 ERM= OT
- CUR
- C9 ,.,. 1
- C2 Units: MIM'lr where :
ERM
- Construction outage energy loss (MWhr)
OT= Construction outage downtime (days)
C2 = Conversion factor from days to hours
- 3 of 5
Duke Energy Carolinas , LLC I Oconee Nuclear Station Revision:
Issue Date: 8/3 1/2020 Estimated Increase in Energ y Consumption due to a Hypothetical Cooling Tower Retrofit at Oconee Nuclear Station Calculation Inputs:
Parametera anij Varlal Booster Pump Discharge Capacity Make-up Pump Discharge Capacity Required Booster Pump Head
... a.
QM H,
Unlt1 50,571 92.7 Unlt2 50,571 92.7 Unlt3 50,571 92.7 Units gpm gpm ft Anurr¢on 4, Note 3 Ass~S Note1 Required Make-up Pump Head HM ft Auumption5 Specific Gravity of Water SG 1.0 1.0 1.0 Auu~1 Pump Efficiency
~--- 85% 65% 85% % Note4 Pump Motor Efficiency rJmo1or 90% 90% 90% % Note4 Number of Additional Booster Pumps No.-. 14 14 14 Asau~ 4, Nole 3 Number of Additional Make-up Pumps N MDumn 0 0 0 Assumption 5 Power Required for Fan Operation P ttan 300 300 300 hp 121 Number of Cooling System Fans N,M 30 30 30 AssumFtlon2, [2)
Gross Facility Generating Capacity c_ 902 907 916 MW 141 Backpressure Energy Penalty EBP£p 0.58% 0 .58% 0.58% % 131 Annual Operating Hours OP 8 760 8 760 8 760 hr AIIU!TlfXion3 Average Capacity Utilization Rate CUR 92% 96% 96% % 151 Construction Outage Downtime DT 158 155 159 days Conversion Factors:
C1 = 7.46E-04 MW / HP C2 = 24 hours per day Assumptions :
- 1. Specific gravity of cooling water is assumed constant.
- 2. Number of fans equal to number of cooling toVv"er cells (1 fan per cell).
- 3. Cooling towers are operated continuously for a given year, unless the unit is in a planned outage .
- 4. 14 booster pumps are required for the hypothetical retrofit of the existing cooling system, per unit.
- 5. It is assumed that a hypothetical passive water intake system utilizing the existing curtain wall would withdraw make-up water from Lake Keowee into the intake canal. Make-up water pump s would not be required .
Notes:
- 1. Total pump head is a summation of expected headloss due to pipe friction , minor losses , and the static head require ment. Where the static head is the sum of \WI
\'Yell depth (10-ft pipe below wet well water surface+ 3 ft of draw down) , and the height to the water distribution system of the cooling to\Wr (46.09 ft) . The calculation does not include topography [2].
2 . Backpressure energy penalty results from a loss of turbine efficiency due to a redu ction in temperature change across the plant condensers . This originates from an increase in cooling water temperature in a closed-cycle cooling system.
- 3. Th e retrofit of the existing cooling system requires 14 pumps (per unit) 'Mth 50 ,571 gpm capacity.
4 . A pump efficiency of 85% and a pump motor efficiency of 90% was considered in the calculations of power required to operate closed-cycle cooling system booster and make-up pumps .
References :
[1] lindeburg, Michael, R. , 2003. Environmental Engineering Reference Manual for PE Exam, Second Edition . Professional Publications , Inc.
[2] SPX Cooling Technologies , Inc. (SPX). 2019 . Quote for Cooling Tower Feas ibility. 26 Sep 2019 .
[3] Veritas Economic Consulting , LTD (Veritas) . 2020. Oconee Nuclear Station : Energy Penalty Study. Prepared for Duke Energy Carolinas , LLC . February 2020 .
[4) Duke Energy. 2019a . Individual Unit Gross Capacity Confirmation- Email communication 'Mth Duke Energy. Email received: 15 Oct 2019 .
[SJ Duke Energy . 2019b. Oconee Nuclear Station Hourly Gross Generating Data Units 1-3 for July 1, 2014 through June 30, 2019 .
- 4 of s
Duke Energy Carolinas, LLC I Oconee Nuclear Statio n Revillon ls.sue Dale 0/31/2020 Estimated Increase in Energy Con sumption due to a Hypothetica l Cooling Tower Retrofit at Oconee Nuclear Station Calculations:
- 1. Estimate Parasitic Power Losses Associate with Auxiliary Loads Formulas Used: 1, 2, 3, Note 4, Assumption 5 Parameters an Varlablei Units Unit 1 Unlt2 Unlt3 Booster Pump Power Requirement p MW 16.2 16.2 16.2 Make*up Pump Power Requirement p MW Fan Power Requirement MW 6.7 6 .7 6 .7
- 2. Estimate Backpressure Energy Pen alty Power Loss Formu la Used:
Parameters and Va ables Un Unlt1 Unlt2 Unlt3 Backpressure Energy Penalty Power Requirement PaPEP MW 5.23 5.26 5.31
- 3. Estimate Total Power Loss Formulas Used: 5, 6 Parameta nd Variables Units Unlt1 Unlt2 Un 3 Total Power Requirement P,..., MWhr / year 246 ,338 246,592 247 ,050 Operational Power Requirement Poe MWhr / year 226,123.29 236 ,549 236 ,190
- 4. Estimate the Construction Outag e Energy Loss Formula Used: 7 Parameters and V rlablea Units Unlt1 Unlt2 Unlt3 Construction Outage Energy Loss ERM MWhr 3,420,384 3,374,040 3,495 ,456
- S of S
This page intentionally left blank.
Appendix 12-8 Estimated Cooling Tower Particulate Matter Emissions at Oconee Nuclear Station
This page intentionally left blank.
Duke Energy C arolinas , LLC I Oconee Nuclear Station Revision. 0 laaue Date: 4/10/2020 Estimated Cooling Tower Particulate Matter Emission s at Oconee Nuclear Stati on Originator. Spencer Nush, EIT 12/30/2019 Reviewer: Shane Galloway, EIT 1/10/2020 Approver: Scott Loughery, PE 4/10/2020 Revis ion No. Revised by: Approved by: Description 0
Calculation Summ ary :
Particulate Matter Emission Rate Units Unlt1 Unlt2 Unlt3 PM lb / hr 0.14 0.14 0.14 PM tons I year 0.58 0.60 0 .60 PM 10 lb / hr 0.14 0.14 0.14 PM 10 tons I year 0.56 0.59 0.58 PM2s lb / hr 0.09 0.09 0.09 PM 2.5 tons I year 0.37 0.39 0.39 Particulate Matter Emission Rate per Cell Units Unlt1 Unlt2 Unlt3 PM lb /hr 0.004 0.004 0.004 PM tons / year 0.014 0,015 0.015 PM 10 lb / hr 0.003 0.003 0.003 PM 10 tons I year 0.014 0.015 0.015 PM2s lb / hr 0.002 0.002 0.002 PM2s tons / year 0.009 0.010 0.010
- 1 of 4
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision:
Issue Date: 4110/2020 Estimated Cooling Tower Particulate Matter Emissions at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unij nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation Purpose :
Estimate the cooling tower particulate matter emission rate from hypothetical cooling tower installation.
Calculation Objectives :
- 1. List the calculation methodology and data required for the calculations.
- 2. Provide the inputs required for the calculations.
- 3. Estimate the cooling tower particulate emission rates .
Calc ulation Methodology:
Formula 1 (TSlcr a (TDS + TSS)
- C 111 Units: PPM where:
(TS)cr = Expected total solids {dissolved and suspended) of the circulating water (PPM)
TDS = Total dissolved solids of the source water (PPM)
TSS = Total suspended solids of the source water (PPM)
C = Cycles of concentration Formula 2 E, = Ocr" DE * (TS)cr* PM
- C1 (1 ]
Units: lb I hr where:
E, = Hourly emission rate of specified particulate matter size PM (lb
/ hr), PM, .,, or PM 10 Ocr = Cooling tower water flow rate gallons per minute (gpm )
DE= Drift eliminator efficiency(%)
(TS)c, = Expected total solids (dissolved and suspended) of the circulating water (PPM)
PM= Weight percent of specified particulate matter size(%) , PM (all particulate matter), PM 2 .5 (particulate matter with a nominal size of less than 2.5 microns), or PM 10 (particulate matter with a nominal size of less than 10 microns)
C1 = Conversion factor from gpm
- PPM to lb/hr Formula 3 E, =e,*u*op*c2 Units: tons I year 1M'lere:
E2 = Annual emission rate of specified particulate matter size PM (tons/year) , PM 2 .5 , or PM 10 E1 = Hourly emission rate of specified particulate matter size PM (lb
/ hr.), PM2 ., , or PM 10 U = Capacity utilization rate (%)
OP = Annual operating hours (hr)
C2 = Conversion factor from lb I year to tons I year
- 2 of 4
Duke Energy Carolinas , LLC I Oconee Nuclear Station Revision Issue Date: 4110/2020 Estimated Cooling Tower Particulate Matter Emissions at Oconee Nuclear Stati on Calculation Inputs :
Parameters and Vanabl* Unlt1 ~Unlt2 Uiilt3 Units Ret*enc::tiNote Cooling Tower Water Flow Rate Ocr 708,000 708,000 708,000 gpm (21 Number of CoolinQ Tower Cells n 40 40 40 (31 Dr~t Eliminator Efficiency DE 0.000005 0.000005 0.000005 % 131 Source Waler Total Dissolved Solids TDS 15 15 15 PPM 141 Source Water Total Susoended Solids TSS 2 2 2 PPM (41 Cvcles of Concentration C 5.0 5.0 5.0 Assumption 4 W eight Percent PM 10 PM 10 97% 97% 97% % Assumption 1, Note 1, (11 W eight Percent PM25 PM2., 64% 64% 64% % Assumption 1, Note 1, (1)
Capac~y Utilization Rate u 92% 96% 96% % (51 Annual Operating Hours OP 8 760 8,760 8760 hr Assumption 2 Conversion Factors :
hour 60 minutes PPM 1,000,000 parts gallon 8.3453 pounds ton 2,000 pounds C1 = GPM*PPMx 5.01 E-04 = pounds per hour C2 = pounds x 5.00E-04 = tons Assumptions:
- 2. Cooling towers are operated non-stop for a given year.
- 3. Emission rates are equally distributed amongst all cooling tower cells.
- 4. Five cycles of concentration assumed due to freshwater source.
Notes :
- 1. ~ PMxx represents less than 12.00% of total PM mass, PMxx fraction is linearly interpolated between 12% and 0%.
References:
[1) Riesman, Joel, and Gordon Frisbie . 2002. Calculating real istic PM 10 emissions from cooling towers, published by the American lnst~ute of Chemical Engineers.
[2) Duke Energy. 2019. Oconee Nuclear Station Actual Intake Flow Rates: 7/1/2014 -6/30/2019. Rece ived: 3 Jul 2019.
[3) SPX Cooling Technologies, Inc. (S PX). 2019. Quote for Cooling Tower Feasibility. 26 Sep 2019.
[4) United States Army Corps Engineers (USAGE). 2014. Duke Energy New Operating Agreement - Savannah River Basin; Appendix C - Water Quality Standards and Designated Use Class~ication. October 2014.
[5) Duke Energy. 2019. Oconee Nuclear Station Hourly Gross Generating Data Units 1-3 for July 1, 2014 through June 30, 2019 .
- 3 of 4
Duke Energy Carolinas , LLC I Oconee Nuclear Station Revision Issue Date. 4/10/2020 Estimated Cooling Tower Particulate Matter Emissions at Oconee Nuclear Station Calculations:
- 1. Estimate Total Solids in Circulating Water Formulas Used:
Parameters and Variables Unlta Unlt1 Unit nlt3 Total Solids in Circulating Water (TS)cr PPM 81 81 81
- 2. Estimate Emission Rates for PM Sizes Formulas Used: 2, 3 Parameters and Vartables Unlta Unlt1 Ulilt2 Urilt3 PM lb / hr 0.14 0.14 0.14 Total PM PM tons / year 0.58 0.60 0.60 PM 10 lb / hr 0 .14 0.14 0.14 PM,o PM 10 tons I year 0.56 0.59 0.58 PM25 lb / hr 0.09 0.09 0.09 PM 25 PM25 tons I year 0.37 0.39 0.39
- 3. Estimate Emission Rates per Cell Formulas Used: Assumption 3 Parameters and Variables Unlta Unlt1 Unlt2 Unlt3 PM lb / hr 0.004 0.004 0 .004 Total PM PM tons I year 0.014 0.015 0 .015 PM 10 lb / hr 0.003 0.003 0.003 PM ,o PM 10 tons I year 0.014 0.015 0.015 PM25 lb / hr 0.002 0.002 0.002 PM 25 PM2.* tons / year 0.009 0.010 0.010
- 4 of 4
Appendix 12-C Estimated Forced Evaporation from the Existing Cooling Water System at Oconee Nuclear Station
This page intentionally left blank.
Duke Energy Carolinas, LLC I Oconee Nuclear Station
- Revision: 0 Issue Date: 8/31/2020 Estimated Forced Evaporation from the Existing Cooling Water System at Oconee Nuclear Station Originator: Spencer Nush, EIT 12/25/2019 Reviewer: Shane Galloway, EIT 1/7/2020 Approver : Scott Loughery, PE 2/19/20202 Revision No . Revised by: Approved by: Description 1 SRL TKZ Revised design circulating water temperature rise for each unit.
Calculation Summary:
Forced Evaporation from July 1, 2014 throu1 h June 30, 2019 Design Conditions Actual Conditions Month Maximum Averaae Maximum Averaae (MGD) (MGD) (MGD) (MGD)
January 19.0 17.3 16.4 14.4 February 19.4 17.9 16.5 14.8 March 19.3 18.6 17.6 14.4 April 22 .7 21 .3 20 .7 17.3 May 25 .1 24.4 22 .6 19.7 June 27.6 27 .1 25 .9 22 .1 July 29 .6 28 .9 26.5 22 .6 Auaust 30.3 29 .6 28.6 23.5 September 29.9 29 .2 27 .6 23.6 October 27.0 25 .5 23.8 18.2 November 22.8 21 .7 14.5 12 .9 December 21 .9 19.7 20.3 16.0
- 1 of 3
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Estimated Forced Evaporation from the Existing Cooling Water System at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooli ng water source for the station .
Calculation
Purpose:
Estimate the forced evaporation due to the facility's thermal discharge by using the Edinger-Geyer Method.
Estimate design forced evaporation using the design condenser cooling water flow and design temperature differential across the condensers , and the actual forced evaporation using the actual condenser cooling water flow and actual temperatu re differential across the condensers , for the period of record from July 1, 2014 through June 30, 2019 .
Calculation Objectives:
- 1. List the calculation methodology and data required for the calculations .
2 . Provide the inputs required for the calculations.
- 3. Estimate the waterbody evaporative water loss using the Edinger-Geyer Method for both design and actual condenser conditions .
- 2 of 3
Duk e Energy Caroli n as , LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8131/2020 Estimated Forced Evap o ration from th e Exi st ing Cooling W ater Sy stem at O c o n ee Nucle ar Statio n Calcu lation Methodology:
Formu la 1 EE = H,
- C
- C 1 Units: MGD where:
EE = evaporative loss due to thermal discharge (MG D)
H, = Power plant's heat rejection rate (BTU / hr)
C = Evaporative loss coefficient (cfs / [10'9 BTU / hr])
C1 = Conversion from cfs to MGD 9
Fo rmu la 2 C = (4450 IL)* (B * (K - 15.7)) / ((0.26 + B)
- K) / 10 Units: cfs I (10'9 BTU I hr) where:
C = evaporative loss coefficient ( cfs / [10'9 BTU / hr])
B = slope of saturated water vapor pressure (mmHg / °F )
K = surface heat exchange coefficient (BTU / sq. ft/ °F)
L = latent heat of vaporization (BTU / lb)
Formula 3 L = 1093 - 0.56
- T.
Units: BTU I lb where:
Ts = background temperature of the receiving waterbody (°F) 2 Fo rmu la 4 B = 0.255 - 0.0088
- T + 0.000204
- T Units: mmHg I 'F where:
T= 1/2*(T, +Td)
T d = dew point temperature, °F Formula 5 K = 15.7 + (B + 0.26)
- f(u)
Units: BTU I sq. ft / 'F where:
f(u) = 70 + 0.7
- u2 u = wind speed , miles per hour (mph)
Formula 6 H, = C2
- p
- Q
- c
- AT Units: BTU I hr w here :
H, = power plant's heat rejection rate (BTU / hr) 3 p = density of water, assumed to be 62.37 lb.,/ ft for all calculations c = specific heat of water, assumed to be 1 BTU / lb.,/ °F for all calculations LIT= change in temperature across the condensers (°F)
Q = circulating water flow rate (MGD) 3 C2 = conversion from MGD to ft / hr
- 3 of 3
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date : 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculation Inputs for Unit 1:
Yearly Ambient Meteoroloalcal Data and Condenser Information for Unit 1 2014 Avg. Condenser Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Cooling Water (CCW)
Month Water (T.) (Td) Speed (u) Across Unit (AT)
Flow(Q)
"F "F MPH MGD "F January - - - - -
February - - - - -
March - - - - -
April - - - - -
May - - - - -
June - - - - -
July 75 .2 64.2 4.6 924 .8 16.9 August 80 .1 65.3 3.8 976 .3 16.2 September 81 .5 63.6 4.3 976 .3 16.5 October 76 .1 51.4 4.6 955.1 17.1 November 59 .9 32.2 5.2 229.1 1.3 December 58 .8 37.4 4.0 764.4 13.6 2015 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Speed (u) Across Unit (AT)
"F "F MPH MGD "F January 54.3 26.7 5.6 697.9 22.3 February 51.4 22.4 5.3 641.2 23 .7 March 50.2 40.3 5.4 651 .6 23.3 April 55.3 49.4 5.1 737.2 20 .7 May 62 .5 56.7 3.6 833.8 18.3 June 69.6 66.0 4.3 905.0 16.8 July 77.1 68.8 4.6 976 .3 15.5 August 83.0 66.6 3.2 976.3 15.6 September 82 .6 62.6 4.5 968 .0 15.8 October 75 .0 51 .8 5.1 929 .3 16.7 November 68 .0 46.2 4.4 924 .0 16.6 December 62.2 48.5 3.6 836 .6 18.3 2016 Avg. Temp of Receiving Avg. Dew Point Temp Avg . Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water (Ts) (Td) Soeed lul Across Unit (AT)
"F "F MPH MGD "F January 57 .6 27.5 5.5 766 .9 19.5 February 52.5 31 .3 7.1 638 .9 23 .5 March 53 .1 43.4 4.8 746.8 6.0 April 58 .3 44.2 5.6 833.8 18.9 May 63 .1 55.2 5.0 833 .8 18.7 June 69 .9 63.5 5.0 867.0 17.9 July 77.6 68.3 4.9 976.3 11. 9 August 83.6 70.5 3.5 976 .3 12.5 September 84.8 62.9 3.7 976.3 12.7 October 79.3 51 .0 4.2 962 .0 13.5 November 69.4 39.1 3.6 381.2 15.3 December 61 .8 33.5 4.6 833.8 15.9 1 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision : 0 Issue Date: 8/31/2 020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculation Inputs (cont'd):
2017 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg . CCW Flow (Q)
Month Water(Ts) (Td) Soeed lul Across Unit (6T)
- F *F MPH MGD *F January 56.8 37.2 5.3 773.6 16.8 February 56 .1 36.9 5.5 749.3 18.3 March 57.5 36.5 5.6 807.4 15.8 April 60.2 52.8 4.7 837.4 15.0 May 65 .7 57.6 5.3 839.2 15.0 June 72 .1 67.3 3.5 976.3 12.5 July 78 .5 70.8 4.1 976.3 11 .7 August 82 .9 69.1 4.1 976.3 12.0 September 80.0 62 .5 4.7 976 .3 11 .9 October 77.6 55.4 4.6 976 .3 12.7 November 68.7 45.4 2.9 833 .8 14.5 December 60 .9 35.2 4.5 833 .8 15.6 2018 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water (Ts) (Td) Soeed lul Across Unit (6T)
- F *F MPH MGD *F January 53.3 25.7 4.2 733.4 16.9 February 52 .1 45.9 4.3 626.4 18.8 March 54 .9 33.9 6 .7 626.4 19.2 April 57 .9 42.8 5.7 807.9 14.5 May 62 .2 62 .8 3.4 829 .0 13.8 June 67 .6 67.3 4.2 842 .7 15.3 July 74 .1 69.2 3.7 976 .3 12.2 August 79.6 68.8 3.2 976 .3 11 .3 September 82 .0 69.4 3.6 976.3 12.3 October 77.6 54.8 4.4 625.5 14.3 November 67.1 40.9 4.8 627.9 12.8 December 57 .8 37.9 4.9 785 .7 14.7 2019 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water (Ts) (Td) Soeed lul Across Unit (6T)
- F *F MPH MGD *F January 54.6 32.9 5.1 820.4 14.7 February 51.9 39.1 5.1 626.4 18.8 March 53.6 36.4 4.5 630 .3 18.5 April 57.0 50.1 4.5 716.3 17.1 May 61 .8 61 .1 4.2 833.8 14.6 June 68.6 64.4 4.2 894.1 13.8 July - - - - -
August - - - - -
September - - - - -
October - - - - -
November - - - - -
December - - - - -
- 2 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision : 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculation Inputs (cont'd):
Design Flow: 976 MGD Density (p) : 62.37 LBM/ FT 3 Design Circulating Water Rise: 17.15£1°F Specific Heat of Water (c): 1.0 BTU/ LBM/ °F Conversions:
cubic foot = 7.481 gallons MG (million gallons) = 1000000 gallons day = 24 hours hour = 3600 seconds C1 = CFS x 0.646 =MGD C2 = MGD x 5570 = cubic feet per hour Assumptions:
- 1. The selection of the nearest meteorological station is reflective of conditions at site.
- 2. The design service water flow was subracted from the actual intake flow for the period of record from July 1, 2014 through June 30 , 2019 to obtain the actual condenser cooling water flow for the same time period
[1) [3) .
Notes:
- 1. Edinger-Geyer Method is an empirical formula developed under Pennsylvania conditions. Authors have evaluated other locations within the United States with success.
References:
[1) Duke Power Company . 1970. Oconee Nuclear Plant Unit No. 1, Surface Condenser Circulating Water Pumps and Air Removal Equipment. Baldwin-Lima-Hamilton Corp. Order Number 320-50295. 27 Mar 1970.
[2) Duke Power Company. 2001 . Oconee Nuclear Station Units 1, 2, and 3 Condenser Cooling Water Intake and Discharge Pipe . Specification No. OSS-0101 .00-0000 - Rev 1. 24 Apr 2001 .
[3) Duke Energy Carolinas, LLC (Duke Energy) . 2019. Oconee Nuclear Station Actual Intake Flow Rates:
7/1/2014- 6/30/2019 . Received : 3 Jul 2019 .
- 3 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/3 1/2 020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculations:
- 1. Monthly Forced Evaporation due to Thermal Discharge at Unit 1 1a. Calculate monthly evaporative loss coefficient (C)
Formulas Used: 2, 3, 4, 5 Given:
Calculate:
2014 Month L T B f(u) K C January - - - - - -
February - - - - - -
March - - - - - -
April - - - - - -
May - - - - - -
June - - - - - -
July 1050.9 69.7 0.6 84 .9 91.4 2.48E-09 August 1048.1 72 .7 0.7 80.2 92.2 2.56E-09 September 1047.4 72.5 0.7 83 .2 94.8 2.57E-09 October 1050.4 63.7 0.5 85.1 82.3 2.29E-09 November 1059.5 46.1 0.3 88 .8 63.9 1.65E-09 December 1060.1 48.1 0.3 81.4 61 .6 1.69E-09 2015 Month L T B f(u) K C January 1062.6 40.5 0.2 91 .6 60.9 1.47E-09 February 1064.2 36.9 0.2 89.5 57.6 1.35E-09 March 1064.9 45.2 0.3 90 .3 64.0 1.62E-09 April 1062.0 52.4 0.4 88 .3 69.9 1.87E-09 May 1058.0 59.6 0.5 79.3 72.4 2.10E-09 June 1054.0 67.8 0.6 83 .0 86.8 2.41 E-09 July 1049.8 73.0 0.7 85 .0 97.2 2.59E-09 August 1046.5 74.8 0.7 77.4 92.9 2.61E-09 September 1046.7 72.6 0.7 84.1 95.7 2.58E-09 October 1051.0 63.4 0.5 88 .6 84.5 2.29E-09 November 1054.9 57.1 0.4 83.3 72.2 2.03E-09 December 1058.2 55.3 0.4 78.9 67.2 1.94E-09 2016 Month L T B f(u) K C January 1060.8 42 .5 0.2 91.4 62.3 1.5E-09 February 1063.6 41 .9 0.2 105.1 68.7 1.6E-09 March 1063.3 48.2 0.3 86.2 64.4 1.7E-09 April 1060.4 51.2 0.3 91 .7 70.7 1.8E-09 May 1057.7 59.2 0.4 87 .8 77. 9 2 .1 E-09 June 1053.9 66.7 0.6 87.8 89.1 2.4E-09 July 1049.5 73 .0 0.7 87 .0 99.1 2.6E-09 August 1046.2 77.0 0 .8 78.7 98.2 2.7E-09 September 1045.5 73.9 0.7 79.4 93.3 2.6E-09 October 1048.6 65.1 0.5 82.5 82.2 2.3E-09 November 1054.1 54.3 0.4 78.8 66.0 1.9E-09 December 1058.4 47.7 0.3 84.6 63.0 1.7E-09
- 4 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculations (cont'd):
2017 Month L T B f(u) K C January 106 1.2 47.0 0.3 89.3 65.0 1.7E-09 February 1061.6 46.5 0.3 91.4 65.7 1.7E-09 March 1060.8 47.0 0.3 92 .2 66.6 1.7E-09 April 1059.3 56.5 0.4 85.3 72.8 2.0E-09 May 1056.2 61 .6 0.5 89.9 82 .9 2.2E-09 June 1052.6 69.7 0.6 78 .5 85.8 2.4E-09 July 1049.0 74.7 0.7 81 .6 96.9 2.6E-09 August 1046.6 76.0 0.8 81 .9 99.7 2.7E-09 September 1048.2 71 .3 0.7 85 .8 94.9 2.5E-09 October 1049.6 66.5 0.6 84.5 86.0 2.4E-09 November 1054.5 57.0 0.4 75 .8 67.0 2.0E-09 December 1058.9 48.1 0.3 83 .9 63.0 1.7E-09 2018 Month L T B f(u) K C January 1063.2 39.5 0.2 82 .5 55.7 1.4E-09 February 1063.8 49.0 0 .3 83.2 63.5 1.7E-09 March 1062.3 44.4 0.3 101 .8 69.3 1.6E-09 April 1060.6 50.3 0.3 92.6 70.2 1.8E-09 May 1058.2 62.5 0.5 78.0 75.1 2.2E-09 June 1055.1 67.5 0.6 82 .3 85.7 2.4E-09 July 1051 .5 71 .7 0.7 79.4 89.7 2.5E-09 August 1048.4 74.2 0.7 77 .2 91 .8 2.6E-09 September 1047.1 75.7 0.8 79 .0 96.1 2.6E-09 October 1049.6 66.2 0.6 83 .8 85.0 2.4E-09 November 1055.4 54.0 0.4 86 .0 70.3 1.9E-09 December 1060.7 47.8 0.3 86.7 64.3 1.7E-09 2019 Month L T B f(u) K C January 1062.4 43.8 0.3 88 .2 61 .6 1.6E-09 February 1063.9 45.5 0.3 88 .1 63.0 1.6E-09 March 1063.0 45.0 0.3 84.0 60.4 1.6E-09 April 1061 .1 53.6 0.4 84.1 68.6 1.9E-09 May 1058.4 61 .5 0.5 82.4 77.1 2.2E-09 June 1054.6 66.5 0.6 82 .1 84.0 2.4E-09 Ju ly - - - - - -
August - - - - - -
September - - - - - -
October - - - - - -
November - - - - - -
December - - - - - -
- 5 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision : 0 Issue Date: 8131/2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculations (cont'd):
- 1. Monthly Forced Evaporation due to Thermal Discharge at Unit 1 1b. Calculate monthly heat rejection rate (H,) and forced evaporation (EE)
Formulas Used: 1, 6 Calculate:
2014 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January - - - -
February - - - -
March - - - -
April - - - -
May - - - -
June - - - -
July 5.82E+09 9.3 5.43E+09 8.7 August 5.82E+09 9.6 5.50E+09 9.1 September 5.82E+09 9.7 5.60E+09 9.3 October 5.82E+09 8.6 5.67E+09 8.4 November 5.82E+09 6 .2 1.03E+08 0.1 December 5.82E+09 6 .3 3.60E+09 3.9 2015 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.5 5.41E+09 5.1 February 5.82E+09 5.1 5.28E+09 4 .6 March 5.82E+09 6.1 5.28E+09 5.5 April 5.82E+09 7.0 5.30E+09 6.4 May 5.82E+09 7.9 5.29E+09 7 .2 June 5.82E+09 9.1 5.28E+09 8.2 July 5.82E+09 9.7 5.27E+09 8.8 August 5.82E+09 9.8 5.29E+09 8.9 September 5.82E+09 9.7 5.31E+09 8.9 October 5.82E+09 8.6 5.40E+09 8.0 November 5.82E+09 7.6 5.32E+09 7.0 December 5.82E+09 7.3 5.33E+09 6 .7 2016 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.8 5.20E+09 5.2 February 5.82E+09 5.9 5.22E+09 5.3 March 5.82E+09 6 .4 1.55E+09 1.7 April 5.82E+09 7.0 5.47E+09 6.5 May 5.82E+09 8.0 5.42E+09 7.4 June 5.82E+09 9.0 5.39E+09 8.3 July 5.82E+09 9.8 4.02E+09 6.8 August 5.82E+09 10.1 4.23E+09 7.3 September 5.82E+09 9.8 4.32E+09 7.3 October 5.82E+09 8.7 4.52E+09 6.8 November 5.82E+09 7.2 2.02E+09 2.5 December 5.82E+09 6.3 4 .61E+09 5.0 6 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date : 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Calculations (cont'd):
2017 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 6.3 4.53E+09 4 .9 February 5.82E+09 6.3 4.76E+09 5.1 March 5.82E+09 6.4 4.43E+09 4 .9 April 5.82E+09 7.6 4.35E+09 5.7 May 5.82E+09 8.4 4.37E+09 6.3 June 5.82E+09 9.2 4.24E+09 6.7 July 5.82E+09 9.9 3.96E+09 6 .7 August 5.82E+09 10.1 4.06E+09 7.0 September 5.82E+09 9.6 4.04E+09 6 .7 October 5.82E+09 9.0 4.32E+09 6.7 November 5.82E+09 7.5 4.20E+09 5.4 December 5.82E+09 6.4 4 .51E+09 4 .9 2018 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.3 4.30E+09 3.9 February 5.82E+09 6.5 4.08E+09 4 .5 March 5.82E+09 6.2 4.19E+09 4.4 April 5.82E+09 6.8 4.06E+09 4 .8 May 5.82E+09 8.2 3.97E+09 5.6 June 5.82E+09 9.0 4.48E+09 6.9 July 5.82E+09 9.5 4.15E+09 6 .8 August 5.82E+09 9.7 3.84E+09 6.4 September 5.82E+09 10.0 4.19E+09 7.2 October 5.82E+09 8.9 3.12E+09 4.8 November 5.82E+09 7.3 2.80E+09 3.5 December 5.82E+09 6.4 4.00E+09 4.4 2019 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.9 4.18E+09 4 .2 February 5.82E+09 6 .1 4.09E+09 4 .3 March 5.82E+09 6.0 4.05E+09 4 .2 April 5.82E+09 7.1 4.26E+09 5.2 May 5.82E+09 8.2 4 .24E+09 6 .0 June 5.82E+09 8.9 4.29E+09 6.5 July - - - -
August - - - -
September - - - -
October - - - -
November - - - -
December - - - -
- 7 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision : 0 Issue Date: 8/31 /2020 Forced Evaporation Due to Thermal Discharge - Unit 1 Unit 1 Calculation Summary:
Forced Evaporation from July 1, 2014 through June 30, 2019 Design Conditions Actual Conditions Month Maximum Average Maximum Average (MGD) (MGD) (MGD) (MGD)
January 6.3 5.7 5.2 4.7 February 6.5 6.0 5.3 4.8 March 6.4 6.2 5.5 4.1 April 7.6 7.1 6.5 5.7 May 8.4 8.1 7.4 6.5 June 9.2 9.0 8.3 7.3 July 9.9 9.6 8.8 7.6 August 10.1 9.9 9.1 7.8 September 10.0 9.7 9.3 7.9 October 9.0 8.8 8.4 6.9 November 7.6 7.2 7.0 3.7 December 7.3 6.6 6 .7 5.0
- 8 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revi sion: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculation Inputs for Unit 2:
Yearly Ambient Meteorological Data and Condenser Information for Unit 2 2014 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(T, ) (Td) Speed (u) Across Unit (4T)
- F *F MPH MGD *F January - - - -
February - - - - -
March - - - - -
April - - - - -
May - - - - -
June - - - - -
July 75.2 64.2 4.6 975.4 16.0 August 80.2 65.3 3.8 976.3 15.9 September 81 .5 63.6 4.3 976.3 16.1 October 76.1 51.4 4.6 976.3 15.4 November 66.7 32.2 5.2 945.9 17.5 December 58.8 37.4 4.0 833.8 20.0 2015 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Speed (u) Across Unit (4n
- F *F MPH MGD *F January 54.4 26.7 5.6 700.0 24.2 February 51 .6 22.4 5.3 634.7 26.4 March 50.4 40.3 5.4 639.7 25.9 April 55.6 49.4 5.1 743.9 22.7 May 62.7 56.7 3.6 833.8 19.6 June 69.8 66.0 4.3 901 .9 18.1 July 77.3 68.8 4.6 976.3 15.6 August 83.0 66.6 3.2 976.3 17.1 September 82.7 62.6 4.5 971 .6 16.6 October 45.5 51 .8 5.1 558.4 8.1 November 66.7 46.2 4.4 722.2 11 .6 December 62.4 48.5 3.6 833.8 18.7 2016 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Speed (u) Across Unit (An
- F *F MPH MGD *F January 57.8 27.5 5.5 761 .3 20.6 February 52.8 31 .3 7.1 640.7 23.5 March 53.3 43.4 4.8 665.3 22.5 April 58.4 44.2 5.6 806.1 19.2 May 63.1 55.2 5.0 833.8 18.8 June 69.9 63.5 5.0 905.0 17.4 July 77.7 68.3 4.9 976.3 11 .7 August 83.6 70.5 3.5 976.3 12.2 September 84.8 62.9 3.7 976.3 12.5 October 79.2 51 .0 4.2 970.0 13.1 November 71.4 39.1 3.6 900.8 13.4 December 61 .8 33.5 4.6 833.8 15.7
- 1 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculation Inputs (cont'd):
2017 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Soeed lul Across Unit (tff)
OF OF MPH MGD OF January 56.7 37.2 5.3 833 .8 16.8 February 56.0 36.9 5.5 833 .8 18.1 March 57.5 36.5 5.6 833 .8 16.1 April 60.2 52.8 4.7 833 .8 14.7 May 65.6 57 .6 5.3 833 .8 15.0 June 720 67.3 3.5 966.8 12.2 July 78.5 70.8 4.1 976.3 11 .6 August 82 .9 69.1 4.1 976 .3 12.2 September 80 .0 62.5 4.7 976.3 11 .7 October 77.5 55.4 4.6 876.4 12.7 November 68.9 45.4 2.9 385.2 14.1 December 60.9 35 .2 4.5 833.8 15.3 2018 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) ITd) S""""d lul Across Unit (4n OF OF MPH MGD OF January 53 .3 25.7 4.2 733.4 16.8 February 52 .1 45.9 4.3 640.4 18.7 March 54 .9 33.9 6.7 626.4 19.3 April 58.0 42.8 5.7 807.3 13.9 May 62.2 62.8 3.4 847.6 13.6 June 67.7 67.3 4.2 843 .0 14.9 July 74.2 69.2 3.7 976.3 12.2 August 79.7 68.8 3.2 976 .3 11 .1 September 82 .1 69.4 3.6 976.3 12.4 October 79.6 54 .8 4.4 953 .3 11 .9 November 67.6 40.9 4.8 881 .3 12.5 December 57 .8 37.9 4.9 833 .8 14.5 2019 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Soeed (ul Across Unit (4n OF OF MPH MGD OF January 54 .6 32.9 5.1 820.4 14.8 February 52 .0 39.1 5. 1 626.4 18.6 March 53 .6 36.4 4.5 627 .3 18.8 April 57 .1 50.1 4.5 716 .7 17.0 May 61.9 61 .1 4.2 833 .8 14.2 June 68.6 64.4 4.2 892 .3 13.7 July - - - - -
August - - - - -
September - - - - -
October - - - - -
November - - - - -
December - - - - -
- 2 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: o*
Issue Date: 8131/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculation Inputs (cont'd):
Design Flow: 976 MGD 3
Density (p) : 62 .37 LBM/ FT Design Circulating Water Rise: 17.15 ~°F Specific Heat of Water (c): 1.0 BTU / LBM/ °F Conversions:
cubic foot = 7.481 gallons MG (million gallons) = 1000000 gallons day = 24 hours 1 hour 3600 seconds C1= CFS X 0.646 =MGD C2 = MGDx 5570 = cubic feet per hour Assumptions :
- 1. The selection of the nearest meteorological station is reflective of cond itions at site.
- 2. The design service water flow was subracted from the actual intake flow for the period of record from July 1, 2014 through June 30, 2019 to obtain the actual condenser cooling water flow for the same time period
[1) [3] .
Notes:
- 1. Edinger-Geyer Method is an empirical formula developed under Pennsylvania conditions . Authors have evaluated other locations within the United States with success.
References:
[1)
Duke Power Company. 1970. Oconee Nuclear Plant Unit No . 1, Surface Condenser Circulating Water Pumps and Air Removal Equipment. Baldwin-Lima-Ham ilton Corp. Order Number 320-50295. 27 Mar 1970.
[2) Duke Power Company. 2001 . Oconee Nuclear Station Units 1, 2, and 3 Condenser Cooling Water Intake and Disch arge Pipe . Specification No . OSS-0101.00-0000 - Rev 1. 24 Apr 2001 .
[3) Duke Energy Carolinas , LLC (Duke Energy) . 2019. Oconee Nuclear Station Actual Intake Flow Rates:
7/1/2014 - 6/30/2019. Received : 3 Jul 2019 .
- 3 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculations:
- 1. Monthly Forced Evaporation due to Thermal Discharge at Unit 2 1a. Calculate monthly evaporative loss coefficient (C)
Formulas Used: 2, 3, 4, 5 Given :
Calcu late
- 2014 Month L T B f(u) K C January - - - - - -
February - - - - - -
March - - - - - -
April - - - - - -
May - - - - - -
June - - - - - -
July 1050.9 69.7 0.6 84.9 91.4 2.49E-09 August 1048.1 72.8 0.7 80.2 92.3 2.56E-09 September 1047.4 72.6 0.7 83.2 94.8 2.58E-09 October 1050.4 63.8 0.5 85.1 82.4 2.29E-09 November 1055.6 49.5 0.3 88.8 67.1 1.78E-09 December 1060.1 48.1 0.3 81.4 61 .6 1.69E-09 2015 Month L T B f(u) K C January 1062.5 40.5 0.2 91.6 60.9 1.5E-09 February 1064.1 37.0 0.2 89.5 57.7 1.4E-09 March 1064.8 45.3 0.3 90.3 64.0 1.6E-09 April 1061 .9 52.5 0.4 88.3 70.0 1.9E-09 May 1057.9 59.7 0.5 79.3 72.6 2.1E-09 June 1053.9 67.9 0.6 83.0 87. 0 2.4E-09 July 1049.7 73.1 0.7 85.0 97.4 2.6E-09 August 1046.5 74.8 0.7 77.4 92. 9 2.6E-09 September 1046.7 72.6 0.7 84.1 95.8 2.6E-09 October 1067.5 48.7 0.3 88.6 66.2 1.7E-09 November 1055.6 56.4 0.4 83.3 71.4 2.0E-09 December 1058.0 55.4 0.4 78.9 67.3 1.9E-09 2016 Month L T B f(u) K C January 1060.6 42.6 0.3 91.4 62.4 1.5E-09 February 1063.5 42.0 0.2 105.1 68.8 1.6E-09 March 1063.1 48.4 0.3 86.2 64.5 1.7E-09 April 1060.3 51 .3 0.3 91 .7 70.8 1.9E-09 May 1057.6 59.2 0.4 87.8 78.0 2.1E-09 June 1053.8 66.7 0.6 87.8 89.1 2.4E-09 July 1049.5 73.0 0.7 87.0 99.1 2.6E-09 August 1046.2 77.0 0.8 78.7 98.2 2.7E-09 September 1045.5 73.9 0.7 79.4 93.4 2.6E-09 October 1048.6 65.1 0.5 82.5 82.2 2.3E-09 November 1053.0 55.2 0.4 78.8 67.0 1.9E-09 December 1058.4 47.6 0.3 84.6 63.0 1.7E-09
- 4 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal D ischarge - Un it 2 Calculations (cont'd) :
2017 Month L T B f(u) K C January 1061 .3 46.9 0.3 89 .3 65.0 1.7E-09 February 1061 .6 46.5 0.3 91.4 65.7 1.7E-09 March 1060.8 47.0 0.3 92.2 66.6 1.7E-09 April 1059.3 56.5 0.4 85 .3 72.8 2.0E-09 May 1056.3 61 .6 0.5 89 .9 82.9 2.2E-09 June 1052.7 69.7 0.6 78.5 85 .8 2.4E-09 July 1049.1 74.6 0.7 81 .6 96.8 2.6 E-09 August 1046.6 76.0 0.8 81 .9 99 .6 2.7E-09 September 1048.2 71 .2 0.7 85.8 94.9 2.5E-09 October 1049.6 66.5 0.6 84.5 86.0 2.4E-09 November 1054.4 57.1 0.4 75.8 67.1 2.0E-09 December 1058.9 48.1 0.3 83.9 62.9 1.7E-09 2018 Month L T B f(u) K C January 1063.2 39.5 0.2 82.5 55 .7 1.4E-09 February 1063.8 49.0 0.3 83.2 63.5 1.7E-09 March 1062.2 44.4 0.3 101 .8 69.3 1.6E-09 April 1060.5 50.4 0.3 92.6 70.2 1.8E-09 May 1058.1 62.5 0.5 78.0 75.2 2.2E-09 June 1055.1 67.5 0.6 82 .3 85 .7 2.4E-09 July 1051.5 71.7 0.7 79.4 89.7 2.5E-09 August 1048.4 74.3 0.7 77.2 91 .8 2.6E-09 September 1047.1 75.7 0.8 79.0 96 .2 2.6E-09 October 1048.4 67.2 0.6 83.8 86.5 2.4E-09 November 1055.2 54 .2 0.4 86.0 70.5 1.9E-09 December 1060.6 47.8 0.3 86.7 64.3 1.7E-09 2019 Month L T B f(u) K C January 1062.4 43.8 0.3 88.2 61 .7 1.6 E-09 February 1063.9 45.5 0.3 88.1 63.1 1.6E-09 March 1063.0 45.0 0.3 84.0 60.4 1.6E-09 April 1061 .0 53 .6 0.4 84.1 68.6 1.9E-09 May 1058.3 61 .5 0.5 82.4 77.1 2.2E-09 June 1054.6 66.5 0.6 82.1 84.0 2.4E-09 July - - - - - -
August - - - - - -
September - - - - - -
October - - - - - -
November - - - - - -
December - - - - - -
- 5 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revisi on: 0 Issue Date: 813112020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculations (cont'd):
- 1. Monthly Forced Evaporation due to Thermal Discharge at Unit 2 1b. Calculate monthly heat rejection rate (H,) and forced evaporation (EE)
Formulas Used: 1, 6 Calculate:
2014 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January - - - -
February - - - -
March - - - -
April - - - -
May - - - -
June - - - -
July 5.82E+09 9.3 5.41E+09 8.7 August 5.82E+09 9.6 5.40E+09 8.9 September 5.82E+09 9.7 5.46E+09 9.1 October 5.82E+09 8.6 5.21E+09 7.7 November 5.82E+09 6.7 5.76E+09 6.6 December 5.82E+09 6.3 5.79E+09 6.3 2015 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.5 5.89E+09 5.6 February 5.82E+09 5.1 5.83E+09 5.1 March 5.82E+09 6.1 5.76E+09 6.0 April 5.82E+09 7.1 5.87E+09 7.1 May 5.82E+09 7.9 5.69E+09 7.7 June 5.82E+09 9.1 5.66E+09 8.8 July 5.82E+09 9.8 5.28E+09 8.8 August 5.82E+09 9.8 5.81E+09 9.8 September 5.82E+09 9.7 5.61E+09 9.4 October 5.82E+09 6.5 1.58E+09 1.8 November 5.82E+09 7.6 2.90E+09 3.8 December 5.82E+09 7.3 5.41E+09 6.8 2016 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.8 5.44E+09 5.4 February 5.82E+09 5.9 5.24E+09 5.3 March 5.82E+09 6.4 5.19E+09 5.8 April 5.82E+09 7.0 5.37E+09 6.4 May 5.82E+09 8.0 5.43E+09 7.5 June 5.82E+09 9.0 5.46E+09 8.5 July 5.82E+09 9.8 3.97E+09 6.7 August 5.82E+09 10.1 4.15E+09 7.2 September 5.82E+09 9.8 4.22E+09 7.1 October 5.82E+09 8.7 4.43E+09 6.7 November 5.82E+09 7.3 4.20E+09 5.3 December 5.82E+09 6.3 4.56E+09 5.0 6 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Calculations (cont'd):
2017 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 6.3 4.88E+09 5.3 February 5.82 E+09 6.3 5.24E+09 5.7 March 5.82E+09 6.4 4.66E+09 5.1 April 5.82E+09 7.6 4.27E+09 5.6 May 5.82E+09 8.4 4.35E+09 6.3 June 5.82 E+09 9.2 4.08E+09 6.5 July 5.82 E+09 9.9 3.93E+09 6.7 August 5.82E+09 10.0 4. 13E+09 7.1 September 5.82E+09 9.6 3.98E+09 6.5 October 5.82E+09 9.0 3.86E+09 5.9 November 5.82E+09 7.5 1.89E+09 2.4 December 5.82E+09 6.4 4.43E+09 4.9 2018 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.3 4.28E+09 3.9 February 5.82E+09 6.5 4.17E+09 4.6 March 5.82E+09 6.2 4.21E+09 4.5 April 5.82E+09 6.8 3.91E+09 4.6 May 5.82 E+09 8.2 4.01E+09 5.7 June 5.82E+09 9.0 4.37E+09 6.8 July 5.82E+09 9.5 4.13E+09 6.7 August 5.82E+09 9.7 3.76E+09 6.3 September 5.82E+09 10.0 4.20E+09 7.2 October 5.82E+09 9.0 3.95E+09 6.1 November 5.82E+09 7.3 3.82E+09 4.8 December 5.82E+09 6.4 4.20E+09 4.6 2019 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.9 4.22E+09 4.3 February 5.82 E+09 6.1 4.05E+09 4.2 March 5.82E+09 6.0 4.09E+09 4.2 April 5.82E+09 7. 1 4.24E+09 5.2 May 5.82E+09 8.2 4.12E+09 5.8 June 5.82E+09 8.9 4.23E+09 6.5 July . . . .
August . . . .
September . . . .
October . . . .
November . . . .
December . . . .
- 7 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revi siOn: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 2 Unit 2 Calculation Summary :
Forced Evaporation from July 1, 2014 through June 30, 2019 Design Conditions Actual Conditions Month Maximum Average Maximum Average
{MGD) (MGD) (MGD) {MGD)
January 6.3 5.8 5.6 4.9 February 6.5 6.0 5.7 5.0 March 6.4 6.2 6.0 5.1 April 7.6 7.1 7. 1 5.8 May 8.4 8.1 7.7 6.6 June 9.2 9.0 8.8 7.4 July 9.9 9.6 8.8 7.5 August 10.1 9.9 9.8 7.9 September 10.0 9.7 9.4 7.9 October 9.0 8.4 7.7 5.6 November 7.6 7.3 6.6 4 .6 December 7.3 6.6 6.8 5.5
- 8 of 8
Duke Energy Carol inas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 3 Calculation Inputs for Unit 3:
Yearlv Ambient Meteorological Data and Condenser Information for Unit 3 2014 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Fl ow (Q)
Month Water(T. ) (Td) Speed (u) Across Unit (An
- F *F MPH MGD *F January - - - - -
February - - - - -
March - - - - -
April - - - - -
May - - - - -
June - - - - -
July 75.2 64.2 4.6 975.4 16.0 August 80.2 65.3 3.8 976.3 15.9 September 81.5 63.6 4.3 976.3 16.1 October 76.1 51.4 4.6 976.3 15.4 November 66.7 32.2 5.2 945.9 17.5 December 58.8 37.4 4.0 833.8 20.0 2015 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) SIM!9d (u) Across Unit (An
- F *F MPH MGD *F January 54.4 26.7 5.6 700.0 24.2 February 51 .6 22.4 5.3 634 .7 26.4 March 50.4 40.3 5.4 639.7 25.9 April 55.6 49.4 5.1 743.9 22.7 May 62.7 56.7 3.6 833.8 19.6 June 69.8 66.0 4.3 901 .9 18.1 July 77.3 68.8 4.6 976.3 15.6 August 83.0 66.6 3.2 976.3 17.1 September 82.7 62.6 4.5 971.6 16.6 October 45.5 51 .8 5.1 558.4 8.1 November 66.7 46.2 4.4 722.2 11 .6 December 62.4 48.5 3.6 833.8 18.7 2016 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg . CCW Flow (Q)
Month Water( Ts) (Td) Soeed (u) Across Unit (An
- F *F MPH MGD *F January 57.8 27.5 5.5 761 .3 20.6 February 52.8 31 .3 7.1 640.7 23.5 March 53.3 43.4 4.8 665.3 22.5 April 58.4 44.2 5.6 806.1 19.2 May 63.1 55.2 5.0 833. 8 18.8 June 69.9 63.5 5.0 905.0 17.4 July 77.7 68.3 4.9 976.3 11 .7 August 83.6 70.5 3.5 976.3 12.2 September 84.8 62.9 3.7 976.3 12.5 October 79.2 51 .0 4.2 970.0 13.1 November 71.4 39.1 3.6 900.8 13.4 December 61 .8 33.5 4.6 833.8 15.7
- 1 of 8
Du ke Energy Carol inas, LLC I Oconee Nuclear Stat ion Revision: 0 Issue Date: 8/3112020 Forced Evaporatio n Due to Thermal Dis charge
- Unit 3 Calculation Inputs (cont'd):
2017 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg . Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Speed (ul Across Unit (6T)
"F "F MPH MGD "F January 56 .7 37.2 5.3 833 .8 16.8 February 56.0 36.9 5.5 833.8 18.1 March 57 .5 36.5 5.6 833 .8 16.1 April 60.2 52.8 4.7 833.8 14.7 May 65.6 57.6 5.3 833.8 15.0 June 72. 0 67.3 3.5 966 .8 12.2 July 78.5 70.8 4.1 976 .3 11 .6 August 82 .9 69.1 4.1 976 .3 12.2 September 80 .0 62.5 4.7 976 .3 11 .7 October 77.5 55.4 4.6 876.4 12.7 November 68.9 45.4 2.9 385 .2 14.1 December 60.9 35.2 4.5 833.8 15.3 2018 Avg. Temp of Receiving Avg. Dew Point Temp Avg. Wind Avg. Change in Temp.
Avg. CCW Flow (Q)
Month Water(Ts) (Td) Speed (ul Across Unit (6T)
"F "F MPH MGD "F January 53.3 25.7 4.2 733.4 16.8 February 52 .1 45.9 4.3 640.4 18.7 March 54 .9 33.9 6.7 626.4 19.3 April 58 .0 42.8 5.7 807 .3 13.9 May 62.2 62.8 3.4 847 .6 13.6 June 67.7 67.3 4.2 843 .0 14.9 July 74.2 69.2 3.7 976 .3 12.2 August 79.7 68.8 3.2 976 .3 11 .1 September 82 .1 69.4 3.6 976 .3 12.4 October 79.6 54.8 4.4 953 .3 11 .9 November 67.6 40.9 4.8 881 .3 12.5 December 57 .8 37.9 4.9 833.8 14.5 2019 Avg. Temp of Receiving Avg. Dew Point Temp Avg . Wind Avg. Change in Temp.
Avg . CCW Flow (Q)
Month Water(Ts) (Td) Speed (u) Across Unit (6T)
"F "F MPH MGD "F January 54 .6 32 .9 5.1 820.4 14.8 February 52.0 39.1 5.1 626.4 18.6 March 53.6 36.4 4.5 627 .3 18.8 April 57 . 1 50.1 4.5 716 .7 17.0 May 61 .9 61 .1 4.2 833 .8 14.2 June 68.6 64.4 4.2 892.3 13.7 July . . . . .
August . . . . .
September . . . . .
October . . . . .
November . . . . .
December . . . . .
- 2 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 3 Calculation Inputs (cont'd):
Design Flow: 976 MGD Density (p) : 62.37 LBM/ FT' Design Circulating Water Rise: 17.15 ti°F Specific Heat of Water (c): 1 .0 BTU / LBM/ °F Conversions:
cubic foot 7.481 gallons MG (million gallons) 1000000 gallons day 24 hours 1 hour 3600 seconds C1 = CFS x 0.646 =MGD C2 = MGD x 5570 = cubic feet per hour Assumptions:
- 1. The selection of the nearest meteorological station is reflective of cond itions at site .
- 2. The design service water flow was subracted from the actual intake flow for the period of record from July 1, 2014 through June 30 , 2019 to obtain the actual condenser cooling water flow for the same time period
[1] [3].
Notes:
- 1. Edinger-Geyer Method is an empirical formula developed under Pennsylvania conditions. Authors have evaluated other locations within the United States with success .
References:
[1]
Duke Power Company. 1970. Oconee Nuclear Plant Unit No. 1, Surface Condenser Circulating Water Pumps and Air Removal Equipment. Baldwin-Lima-Hamilton Corp. Order Number 320-50295. 27 Mar 1970.
[2] Duke Power Company. 2001 . Oconee Nuclear Station Units 1, 2, and 3 Condenser Cooling Water Intake and Discharge Pipe. Specification No . OSS-0101 .00-0000 - Rev 1. 24 Apr 2001 .
[3] Duke Energy Carolinas , LLC (Duke Energy) . 2019. Oconee Nuclear Station Actual Intake Flow Rates:
7/1/2014 - 6/30/2019. Received: 3 Jul 2019 .
- 3 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 3 Calculations :
- 1. Monthly Forced Evaporation due to Thermal Discharge at Unit 3 1a. Calculate monthly evaporative loss coefficient (C)
Formulas Used : 2 , 3, 4, 5 Given :
Calculate :
2014 Month L T B f(u) K C January - - - - - -
February - - - - - -
March - - - - - -
April - - - - - -
May - - - - - -
June - - - - - -
July 1050.9 69.7 0.6 84.9 91.4 2.5E-09 August 1048.1 72.8 0.7 80.2 92.3 2.6E-09 September 1047.4 72.6 0.7 83.2 94.8 2.6E-09 October 1050.4 63.8 0.5 85.1 82.4 2.3E-09 November 1055.6 49.5 0.3 88.8 67.1 1.8E-09 December 1060.1 48.1 0.3 81.4 61 .6 1.7E-09 2015 Month L T B f(u) K C January 1062.5 40.5 0.2 91 .6 60.9 1.5E-09 February 1064.1 37.0 0.2 89.5 57.7 1.4E-09 March 1064.8 45.3 0.3 90.3 64.0 1.6E-09 April 1061 .9 52.5 0.4 88.3 70.0 1.9E-09 May 1057.9 59.7 0.5 79.3 72.6 2.1E-09 June 1053.9 67.9 0.6 83.0 87.0 2.4E-09 July 1049.7 73.1 0.7 85.0 97.4 2.6E-09 August 1046.5 74.8 0.7 77.4 92.9 2.6E-09 September 1046.7 72.6 0.7 84.1 95.8 2.6E-09 October 1067.5 48.7 0.3 88.6 66.2 1.7E-09 November 1055.6 56.4 0.4 83.3 71 .4 2.0E-09 December 1058.0 55.4 0.4 78.9 67.3 1.9E-09 2016 Month L T B f(u) K C January 1060.6 42.6 0.3 91.4 62.4 1.5E-09 February 1063.5 42.0 0.2 105.1 68.8 1.6E-09 March 1063.1 48.4 0.3 86.2 64.5 1.7E-09 April 1060.3 51 .3 0.3 91 .7 70.8 1.9E-09 May 1057.6 59.2 0.4 87.8 78.0 2.1E-09 June 1053.8 66.7 0.6 87.8 89.1 2.4E-09 July 1049.5 73.0 0.7 87.0 99.1 2.6E-09 August 1046.2 77.0 0.8 78.7 98.2 2.7E-09 September 1045.5 73.9 0.7 79.4 93.4 2.6E-09 October 1048.6 65.1 0.5 82.5 82.2 2.3E-09 November 1053.0 55.2 0.4 78.8 67.0 1.9E-09 Decem ber 1058.4 47.6 0.3 84.6 63.0 1.7E-09
- 4 of 8
Du ke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge
- Unit 3 Calculations (cont'd):
2017 Month L T B f(u) K C January 1061.3 46.9 0.3 89.3 65.0 1.7E-09 February 1061.6 46.5 0.3 91.4 65.7 1.7E-09 March 1060.8 47.0 0.3 92.2 66.6 1.7E-09 April 1059.3 56 .5 0.4 85.3 72.8 2 0E-09 May 1056.3 61 .6 0.5 89.9 82 .9 2.2E-09 June 1052.7 69.7 0.6 78.5 85 .8 2.4E-09 July 1049.1 74.6 0.7 81.6 96 .8 2.6E-09 August 1046.6 76.0 0.8 81 .9 99 .6 2.7E-09 Septem ber 1048.2 71 .2 0.7 85 .8 94 .9 2.5E-09 October 1049.6 66.5 0.6 84.5 86 .0 2.4E-09 November 1054.4 57 .1 0.4 75.8 67.1 2.0E-09 December 1058.9 48.1 0.3 83.9 62.9 1.7E-09 2018 Month L T B f(u) K C January 1063.2 39 .5 0.2 82 .5 55.7 1.4E-09 February 1063.8 49.0 0.3 83 .2 63.5 1.7E-09 March 1062.2 44.4 0.3 101 .8 69.3 1.6E-09 April 1060.5 50 .4 0.3 92.6 70.2 1.8E-09 May 1058.1 62.5 0.5 78.0 75.2 2.2E-09 June 1055.1 67.5 0.6 82.3 85 .7 2.4E-09 July 1051 .5 71 .7 0.7 79.4 89 .7 2.5E-09 August 1048.4 74.3 0.7 77.2 91 .8 2.6E-09 September 1047.1 75.7 0.8 79.0 96 .2 2.6E-09 October 1048.4 67.2 0.6 83.8 86 .5 2.4E-09 November 1055.2 54 .2 0.4 86.0 70.5 1.9E-09 December 1060.6 47.8 0.3 86.7 64.3 1.7E-09 2019 Month L T B f(u) K C January 1062.4 43.8 0.3 88.2 61 .7 1.6E-09 February 1063.9 45.5 0.3 88 .1 63.1 1.6E-09 March 1063.0 45.0 0.3 84.0 60.4 1.6E-09 April 1061 .0 53 .6 0.4 84. 1 68.6 1.9E-09 May 1058.3 61 .5 0.5 82.4 77.1 2.2E-09 June 1054.6 66.5 0.6 82.1 84 .0 2.4E-09 July . . . . . .
August . . . . . .
September . . . . . .
October . . . . . .
November . . . . . .
December . . . . . .
- 5 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 3 Calculations (cont'd) :
1 . Monthly Forced Evaporation due to Thermal Discharge at Unit 3 1b. Calculate monthly heat rejection rate (H ,) and forced evaporation (EE)
Formulas Used : 1, 6 Calculate :
2014 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January - - - -
February - - -
March - - - -
April - - - -
May - - - -
June - - - -
July 5.82E+09 9.3 5.41E+09 8.7 August 5.82E+09 9.6 5.40E+09 8.9 September 5.82 E+ 09 9.7 5.46E+09 9.1 October 5.82 E+09 8.6 5.21E+09 7.7 November 5.82 E+09 6.7 5.76E+09 6.6 December 5.82E+09 6.3 5.79E+09 6.3 2015 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.5 5.89E+09 5.6 February 5.82E+09 5.1 5.83E+09 5.1 March 5.82E+09 6.1 5.76E+09 6.0 April 5.82E+09 7.1 5.87E+09 7.1 May 5.82E+09 7.9 5.69E+09 7.7 June 5.82E+09 9.1 5.66E+09 8.8 July 5.82E+09 9.8 5.28E+09 8.8 August 5.82E+09 9.8 5.81E+09 9. 8 September 5.82E+09 9.7 5.61E+09 9.4 October 5.82E+09 6.5 1.58E+09 1.8 November 5.82E+09 7.6 2.90E+09 3.8 December 5.82E+09 7.3 5.41E+09 6.8 2016 Desian Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.8 5.44E+09 5.4 February 5.82E+09 5.9 5.24E+09 5.3 March 5.82E+09 6.4 5.19E+09 5.8 April 5.82E+09 7.0 5.37E+09 6.4 May 5.82 E+09 8.0 5.43E+09 7.5 June 5.82E+09 9.0 5.46E+09 8.5 July 5.82E+09 9.8 3.97E+09 6.7 August 5.82E+09 10.1 4.15E+09 7.2 September 5.82E+09 9.8 4.22E+09 7.1 October 5.82E+09 8.7 4.43E+09 6.7 November 5.82E+09 7.3 4.20E+09 5.3 December 5.82E+09 6.3 4.56E+09 5.0
- 6 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revision: 0 Issue Date: 8/31/2020 Forced Evaporation Due to Thermal Discharge - Unit 3 Calculations (cont'd) :
2017 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 6.3 4.88E+09 5.3 February 5.82E+09 6.3 5.24E+09 5.7 March 5.82E+09 6.4 4.66E+09 5.1 April 5.82E+09 7.6 4.27E+09 5.6 May 5.82 E+09 8.4 4.35E+09 6.3 June 5.82 E+09 9.2 4.08E+09 6.5 July 5.82 E+09 9.9 3.93E+09 6.7 August 5.82E+09 10.0 4.13E+09 7.1 September 5.82E+09 9.6 3.98E+09 6.5 October 5.82 E+09 9.0 3.86E+09 5.9 November 5.82E+09 7.5 1.89E+09 2.4 December 5.82E+09 6.4 4.43E+09 4.9 2018 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82 E+09 5.3 4.28E+09 3.9 February 5.82E+09 6.5 4.17E+09 4.6 March 5.82 E+09 6.2 4.2 1E+09 4.5 April 5.82E+09 6.8 3.91E+09 4.6 May 5.82E+09 8.2 4.01E+09 5.7 June 5.82 E+09 9.0 4.37E+09 6.8 July 5.82E+09 9.5 4.13E+09 6.7 August 5.82E+09 9.7 3.76E+09 6.3 September 5.82 E+09 10.0 4.20E+09 7.2 October 5.82E+09 9.0 3.95E+09 6.1 November 5.82E+09 7. 3 3.82E+09 4.8 December 5.82E+09 6.4 4.20E+09 4.6 2019 Design Conditions Actual Conditions Month H, EE H, EE (BTU/HR) (MGD) (BTU/HR) (MGD)
January 5.82E+09 5.9 4.22E+09 4.3 February 5.82E+09 6.1 4.05E+09 4.2 March 5.82E+09 6.0 4.09E+09 4.2 April 5.82E+09 7.1 4.24E+09 5.2 May 5.82E+09 8.2 4.12E+09 5.8 June 5.82E+09 8.9 4.23E+09 6.5 July - - - -
August - - - -
September - - - -
October - - - -
November - - - -
December - - - -
- 7 of 8
Duke Energy Carolinas, LLC I Oconee Nuclear Station Revi sion: 0 Issue Date: 8/31 12020 Forced Evaporation Due to Thermal Discharge - Unit 3 Unit 3 Calculation Summary:
Forceit Evaporation from July 1, 2014 through June 30, 2019 Design Conditions Actual Conditions Month Maximum Average Maximum Average (MGD) (MGD) (MGD) (MGD)
January 6.3 5.8 5.6 4.9 February 6.5 6.0 5.7 5.0 March 6.4 6.2 6.0 5.1 April 7.6 7.1 7.1 5.8 May 8.4 8.1 7.7 6.6 June 9.2 9.0 8.8 7.4 July 9.9 9.6 8.8 7.5 August 10.1 9.9 9.8 7.9 September 10.0 9.7 9.4 7.9 October 9.0 8.4 7.7 5.6 November 7.6 7.3 6.6 4.6 December 7.3 6.6 6.8 5.5
- 8 of 8
This page intentionally left blank.
.Appendix 12-D Estimated Increase in Energy Consumption due to a Hypothetical Fine-mesh Screen Retrofit at Oconee
- Nuclear Station
This page intentionally left blank.
Duke Energy Ca rolin as, LLC I Oconee Nuclear Station Revision:
IS$ue O.t, : 6130 020 Estimated Energy Consumption due to a Hypothetical Fine-mesh Screen Retrofit at Oconee Nuclear Station Originator: Spencer Nush, EIT 10/4/2019 Reviewer: S cott Loughery, PE 10/4/2019 Approver: Scott Loughery, PE 4/10/2020 Revision No . Revised by: Approved by; Description Calculation Summary :
Energy Conaumplion due to Hypothetical FinHnHh 8clffn Retrofit Untts Unft1 Untt2 Untt3 otal Operational En ergy Consumption MWhrlyear 2,094 2,133 2,129 6,356 Construction Outage Energy Loss MWhr 714 ,384 783,648 725 ,472 2,223,504
- l ofS
Duke Energy Carolinas, LLC I Oconee Nuclear Station R~ion:
lnu*Oat*: 11/312020 Estimated Energy Cons um pt ion due t o a Hypothetical Fine-mes h Screen Retrofit at Ocooee Nuclear Statton System Description :
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County, SC . Lake Keowee acts as a cooling water source for the station.
Ca lcu lation Purpose :
Estimate the energy consumption requirement for operation of fish-protective fine-mesh traveling water screens and screen wash pumps , and by the construction outage required to tie in the hypothetical system .
Calculation Objectives:
- 1. List th e calculation methodo log y and data required for the calculations .
- 2. Id entify inputs req uired for the calculations.
- 3. Estimate the ene rgy consumption.
- 5. Estimate the construction outage energy loss .
- 2 ofS
Duke Energy CarollnH , LLC I Oconee Nuclear Station RIMSlon.
lssue o.t. .,,12020 Estimated Energy Consumption due to a Hypothetical Fine-mesh Screen Retrofit at Oconee Nuclear Station Calc ulation Methodology:
Formula 1 P, ,.... , * (PR* aH,..,. _ ... ,H,, )11114 *,,
Units HP w here.
Ppu,.._"' Power ratin g for pump (HP)
PR= Pressure (psi/ pump) a_ _.,_= Screen wash pump discharge capacity (gpm)
'1 = Efficiency(")
Formula 2 P ..1 .,.,. . . * (Psc*- * -
- P..,,.... _.,, )" N.,., ..,.
- C1
- HR Unifi MWhrlyear or AM'71r/Mek where P.,. _ = Power required to operate ex:isllng course-mesh screens (MW)
P_ - = Power required to operate ex:istlng coarse-mesh screen motor (HP)
P - - -~ = Power reqU1red to operate existing screen wash pump (HP)
N_._ = Number of screens C1 = Conversion factor from HP to MW (MW/ HP)
HR = Total hour$ per week (hr/ week) or total hours per year (tv / ytiar)
Formula 3 P11n,*" "" * ((( P ,111urH11 + Pu*tc1H11w.. 11 + PH~K1H11-~11* PAM1Lll*u 1N11-11)
- Nu, .. ,.) P.,_ ,11,.*t.-,)
- C1
- HR" le,.
Units MWhr I year or MWhr I weBk w here*
P11n:o - - : Power re quired to operate
- hypothetical fine~mesh screen system due to new screen nd pump motors (MWhr I week I screen)
PFw- = Power required to operate* fine.mesh screen motor {HP/ screen)
Pu . . - -
- Power required to operate a low prHsure saeen wash pump (HP I screen)
P~,...,, = Power required to operate* high pressLM"e screen wash pump (HP/ screen)
P,.,.LI'ktwft_"" Power required to operate an auxiiary low pressure screenw sh pump (HP/ screen)
P"""""' ,...-up= Power required to operate e trough make-up w ater pum p (HP)
!cf-= Intake flow capacity factor(%)
Formula 4 P
- Q"H " g"p l>l Units Watrs where P = Power(W) 0 = *~n intake flow rate (m3 / s)
H = Screen headless (m )
g = Accelerallon of gravity (9 81 m Is')
p = Density of w ater( 1000 kg I m 3 )
Formula 5 P.,.......,. (.6P) * (Q
- g " p * .6H
- OP
- lc,.)111 / C J where P,_._ (.6P) = lncrHse in power reqund ta operate a hypolhebcal f10e--mesh screen system due to headloH impacts on lOl!w,g condenser cooing water pumps (MWht I year)
.6H = Increase in head required to operate a hypothetica l fine~ash screen system (m)
CJ = Conversion fa ctor from Watts to megawatts Formula 8 P......yp
- P11n, UONII P., _ _
Units M\IWir I year where P..,.i,y,"" Total increase.., power required to oper11te a hypothebcal file-mesh screen system due to new screen and pump motors and headless vnpacts on exrst,ng condenser coolrlg water pumps (MWhr / year)
Formula 7 EllM - OT
- c,,o..
- C2 Units MWhr where ERM= Construction outage energy loss (MWht)
OT= Construction outage downtime (days)
C2 = Conversion factor from days to hours
- 3 ofS
Duke Energy Carolinas, LLC I Oconee Nuclear Station
""2020 Estimated Energy Cons umption due to a Hypothetical Fine-mesh Scree n Retrofit at Oconee Nuclear Station Calculation Inputs:
Param ... rs and VanablH I untt1 I Urill2 I UnU Unb I Exloting Byatfln Motor Rating of the Existing Screens 0 0 0 HP /screen Not,4 N --
P &Cf..-.tn01Ql'-hlgh Number of Screens 8 8 8 1*1 Screen Wash Pump Pressure 0 0 0 PSI N01e4 p tefff!'lwalh Screen Wash Pump Flow 0 0 0 GPM Note Hours of Operation per Year Total OP_,.101a1 0 0 0 hour/year Not14 Design Intake Flow Rate a 45 45 45 3 m /s 111 Hypothetical 8 ~
Screen Motor Input Power P FMacrNn 2 2 2 HP/screen Pl Flow Rate for Low Pressure Screen Wash 176 176 176 gpm / screen 121
.~
P LP1a-,wu11 Pressure for Low Pressure Screen Wash 15 15 15 psi 121 Flow Rate for High Pressure Screen Wash 221 221 221 gpm / screen 121 P ~eenwNtl Pressure for High Pressure Screen Wash 80 80 80 121 Flow Rate for Auxiliary Low Pressure Screen Wash 70 70 70 gpm I screen 121 PAUILPsc1eenwMh Pressure for Auxiliary Low Pressure Screen Wash 7 7 7 psi 121 Flow Rate for Trough Make-up Water Pressure for Trough Make-up Water Hours per Week Pvougm,ai.~
HRwNk 166 192 5
168 168 gpm hour/week 12), NoCeS 121, NoleS Hours per Year HR_ 8760 8760 8760 houri year Pump Efficiency Pump Motor Efficiency H eadloss Existing Coarse-mesh Screens Headloss Hypothetical Fine-mesh Screens
~-
~
l.lH 85%
90%
0.017 0.323 85%
90%
0.017 0.323 85%
90%
0.017 0.323 m
m N11te 2 Nllte2 Construction Outage Downtime OT 33 36 33 days Nllte3 Gross Generating Capacity Cg_ 902 907 916 MW ,,,
Intake flow Capacity Factor le, 85% 86% 86% % MN11te&
Conversion Factors :
C1 = 7 .46E-04 MW / HP C2 = 24 hours per day C3= 1.00E+06 Watt / megawatt Notes:
- 1. Recurring operational energy consumption takes Into account the intake flow capacity factor (see Note 6) .
- 2. A pump efficiency of 85% and a pump motor efficiency o f 90% was considered in the calculation of horsepower req uired for the hypothetical low pressure screen wash , high pressure screen wash , auxiliary low pressure screen wash , and fish trough make-up water systems. These efficiencies were also considered in the calculation of increase of annual energy requirement due lo headless impacts on existing condenser cooling water pumps .
- 3. It is assumed the FM S construction outage would be 2 months in total for each unit, and would include a regularly scheduled unit outage (approximately 1 month) lo minimize replacement energy costs .
- 4. The existing scree ns at Oconee Nuclear Station are coarse-mesh fixed -panel screens without motors or an automated screen wash system .
- 5. Units 1, 2, and 3 utilize a common aquatic organism return trough , and therefore trough make-up water is common to all un its .
- 6. The intake flow capacity fa ctor is the proportion of actual intake fl ow over the five year period of record (July 1, 20 14 th rough June 30 , 2019) to th e design in take flow .
Referen ces :
(1] Duke Energy. 2019a . Oconee Nuclear Station Actual Intake Ftow Rates : 7/1/2014- 6/30/2019. R eceived : 3 Jul 2019 .
{2] Evoqua Water Technologies. 2019. Evoqua Water Technologies Budget Proposal File No . 45062.
(3] Lindeburg , Michael, R., 2003 . Envlronmental Eng ineering Reference Manual for PE Exam , Second Edition . Professional Publications, Inc.
(4J US Filter Corporation (US Filler) . 2016. Communication between US Fitter Staff and HOR Staff - TSV and Headloss Curves.
[5] Duke Energy. 2019b. Individual Unit Gross Capacity ConfinTiation- Ema il communication with Duke Energy. Email received : 15 Oct 2019.
[61 Duke Power Company. 2000 . Oconee Nuclear Station - Intake Structure General Arrangement Plans and Sections. Drawing No. 0-339 - Rev 7. 16 Nov 2000 .
- 4 ofS
Duke Energy Carolinas , LLC I Oconee Nuclear Station Revision:
IHu*Da!I: 8/312020 Estimated Energy Consumption due to a Hypothetical Fine-mesh Screen Retrofit at Oconee Nuclear Station Calculations:
- 1. Power Rating for Screen Wash and Trough Make-u p Water Pumps Formula Used : 1, Note 2 Hvoomelical System Parameters unna Untt1 I Untt2 I Untt3 Total Screen Wash Pump Motor Input Power (H igh Pressure) HP /screen 13.5 I 13.5 I 13.5 Screen Wash Pump Motor Input Power (Low Pressure) HP/ screen 2.0 I 2.0 I 2.0 Screen Wash Pump Motor Input Power (Auxiliary Low Pressure) HP/screen o.4 I 0.4 I 0.4 Aquatic Organism Trough Water Pump Motor Input Pow er HP 0.7
- 2. Current Energy Use Formula Used: 2, Note 4 Existing System Prametera Unb Untt1 UnH2 UnH3 Total Current Energy Usage Weekly per Screen MWhr /week/ screen 0 0 0 0 Current Energy Usag e Weekly MWhr/ week 0 0 0 0 Current Energy Usage Annually per Screen MWhr / year / screen 0 0 0 0 Current Energy Usage Annually MWhr lyear 0 0 0 0
- 3. Energy Required to Operate a Hypothetical Fine-mesh Screen System due to New Screen and Pump Motors Formulas Used: 3, Note 1 Hypothetical System Pllrameten Unb UnH1 Unlt2 Unl3 Total Energy Use due to a FMS Retrofit (Weekly) MWhr /week/ screen 1.9 1.9 1.9 Energy Use due to a FMS Retrofit (Weekly) MWhr /week 15 15 15 46 Energy Use due to a FMS Retrofit (Annually) MWhr I year I screen 99 101 100 Energy Use due to a FMS Retrofit (Annually) MWhr / year 791 806 805 2,402 Increase in En ergy Use (Annually) MWhr / year/ screen 99 101 100 Increase in Energy Use due to New Screen and Pump Motors MWhr/year 791 806 805 2,402 4 Energy Required to Operate a Fine-m esh Screen System due to Headloss Impacts on Ex isting Condenser Cooling Water Pumps Formulas Used: 5, Note 1, Note 2 Hypothetical System Parameten Unb Unl1 Untt2 Unl3 Total Energy Consumption Due to Headless Impacts on Existing Condense, MWhr /week 25 .05 26 25 76 Cooling Water Pumps Energy Consumption Due to Headless Impacts on Existing Condense, MWhrlyear 1,303 1,327 1,325 3,954 Cooling Water Pumps
- 5. Total Energy Required to Operate a Hypothetical Fi ne-mesh Scree n System Formulas Used:
Hypothetical System Parameten Untts Unl3 Total Operational Energy Consumption MWhr/ ear 2,129 6,356
- 6. Estimate the Con stru ction Outage Energy Loss Formula Used:
Hypothetical S
_,. Unh Un11 Untt2 UnR3 Total Construction Outage Energy Loss MWhr 714,384 783 ,648 725 ,472 2,223 ,504
- 5 ofS
This page intentionally left blank.
Appendix 12-E Estimated Increase in Energy Consumption due to Installation of Fine-mesh Screens in a New CWIS at
- Oconee Nuclear Station
This page intentionally left blank.
Duke Energy Carolinas, lLC I Oconee Nuclear Station Re'lislon.
luueOate 6/J/2020 Estimated Energy Consumption due to a Hypothetlca l Installation of Fine-mesh Screens In a New CWIS at Oconee Nuclear Station Originator. Spencer Nush, EIT 11 12112019 Reviewer: Shane Galloway, EIT 11712019 Approver: Scott Loughery, PE 4/1012020 Revision No. Revised by: Approved bv: Description Calculation Summary:
Ulllla un111 Unl2 Unll3 Total MWhr/year 1,945 1,981 1,978 5,904 Construction Outage Energy Loss MWhr
- 1 of5
Duke Energy Carolinas, LLC I Oconee Nuclear Station ls1ueOat.;
0 6/3/2020 Estimated Energy Consumption due to a Hypothetical Installation of Fine-mesh Screens In a New CWIS at Oconee Nuclear Station System
Description:
Oconee Nuclear Station is a three-unit nuclear-fueled power station located on Lake Keowee in Oconee County, SC. Lake Keowee acts as a cooling water source for the station.
Calculation
Purpose:
Estimate the energy consumption requirement for operation of fish-protective fine-mesh traveling water screens and screen wash pumps , and by the construction outage required to tie in the screens within a new CWIS.
Calculation Objectives:
- 1. List the calculation methodology and data required for the calculations .
- 2. Identify inputs required for the calculations.
- 3. Estimate the energy consumption .
- 5. Estimate the construction outage energy loss .
- 2 ofS
Duke Energ y Carolinas , LLC I Oconee Nuclear Station IIIJ/2020 Estimated Energy Consumption due to a Hypothetical Installation of Fine-mesh Screens In a New CWIS at Oconee Nuclear Station Calculation Methodology:
Formula 1 P,..111, * (PR. QICINIIWMll ,11111,}I 1114
- 11 Units: HP where:
Ppump= PolNl!r rating for pump (HP)
PR = Pressure (psi I pump) 0 _ _ 11 pu 1111
= Screen wash pump discharge capacity (gpm) ri = Efficiency(%) Note2 Formula 2 Put"'""= (PKfHIIMOti:11 + P KrN 11 wanl
- N*cr**
- C1
- HR Units
- MWhrlyear or MYVhr l week where:
P** KtN11 = Pov.<er required to operate existing course-mesh screens (MW)
P,-.11mo1u, = Po-.ver required to operate existing coarse-mesh screen motor (HP)
P_ _.. = Power required to operate existing screen wash pump (HP)
N_ = Number of screens C1 = Conversion factor from HP to fwfiN(MW/HP)
HR = Total hours per 'Week {hr/ week) or total hours per year (hr I year)
Formula 3 P11v, UfMII = (((P,MIIC<Mfl + PU'screH wHII PHhcrMII wnh + P ....,. LhcrMII wa1h)
- N.,... ) + P 1r0,.1 11 111 a1,-,)
- C1
- le, Units: MWhr I year or MWhr I week where:
P""'_,, = Po'Ner requited to operate a hypothetical fine-mesh screen system due to new screen and pump motors {MWhr / week I screen)
PFM"'"" = Po'Ner requited to operate a fine-mesh screen motor {HP/ screen )
Pl.Fwwft- = Po'Ner requited lo operate a low pressure screen wash pump(HP /screen)
P~ - " = Po-Ner requited to operate a high pressure screen wash pump (HP /screen)
PA... lPK_n_*" = Power required to operate an audiary low pressure screen wash pum p (HP/ screen)
P"""9'1,.."-, = Power requited to operate a trough make-up waler pump (HP) la= Intake now capacity factor (%)
Formula P
- Q " H
- g *p (3(
Units Watts P= Power(W) a= Oes~n intake now rate (m 3 / s)
H = Screen headloss (m) g = Acceleration of gravity (9.81 m / s1)
P = Density ofwatef(1000 kg/ m3 )
Formula 5 P11oar11o$* (dP) * (Q
- g" p" dH" OP" lc,)/fl /C3 Units MWhr I year where:
P,.. __ (Af)) = Increase in po'N'er requited to operate a hypothetical fine-mesh screen system due to headless impacts on existing circulating water pumps (MWhr / year)
.O.H = Increase in head requited to operate a hypothetical fine-mesh screen system (m)
CJ = Conversion factor from Watts to megawatts Formula 6 P IOUll llv, = p ll)'P ICfMII P... _, ....
Units M\Mlr I year where P 1G1a111r, = Total increase in power required to operate a hypothetical fine-mesh screen system due to new screen and pump motors and headloss Impacts on existing circulating water pumps (MWhr I year)
Formula 7 E"M* OT" C 8 10 . . ° C2 Unifs MYVhr where*
~ = Construction outage energy loss (MWhr)
OT = Construction outage dOYmtime (days)
C2 = Conversion factor from days to hours
- 3 ofS
Duke Energy Carolinas, LLC I Oconee Nuclear Station 6/J/2020 Estimated Energy Consumptio n due to a Hypothetica l In stallation of Fine-mesh Sc reens tn a New CWIS at Oconee Nuclear Station Calculation Inputs:
Existing System Para- and V1r1lbln Motor Rating of the Existing Screens Number of Screens p _ _ _ -hioh p_ N~_ -
I un*1 0
10 I un*2 0
10 I un*a 0
10 Unltl HP /screen
- - Not15 I~
Screen Wash Pump Pressure 0 0 0 PSI Note5 Screen Wash Pump Flow 0 0 0 gpm Notes Hours of Operation per Year Total OPV- *lolal 0 0 0 hour I year Note s Design Intake Flow Rate a 45 45 45 m3 /S 111 HYl)Oll!ellc1I Systam Screen Motor Input Power p, _ 2 2 2 HP /screen ~I Flow Rate for Low Pressure Screen Wash plhg_ _,. 176 176 176 gpm / screen 121 Pressure for Low Pressure Screen Wash 15 15 15 psi 121 Flow Rate for High Pressure Screen Wash 221 221 221 gpm / screen 121 P HPlaeen ~
Pressure for High Pressure Screen Wash 80 80 80 psi I~
Flow Rate for Auxiliary Low Pressure Screen Wash 70 70 70 gpm I screen I~
P,,__L~-_,,
Pressure for Auxiliary Low Pressure Screen Wash 7 7 7 psi I~
Flow Rate for Trough Make-up Water 192 gpm (2J, No1e6 P .,ou!lhfflllke.vp Pressure for Trough Make-up Water 5 psi [2], Nole6 Hours per Week HR_. 168 168 168 hour /week Hours per Year HR,_ 8760 8760 8760 hour I year Pump Efficiency Pump Motor Efficiency Headless Existing Coarse-mesh Screens Headloss Hypothetical Fine- mesh Screens
~-
~
IIH 85%
90%
0.017 0.242 85%
90%
0.017 0.242 85%
90%
0.017 0.242 m
m Nole2 Nole2 1*1 l*I Construction Outage Downtime DT 0 0 0 days Nole 4 Gross Generat ing Capacity c_ 902 907 916 ,..,,, I~
Intake Flow Capacity Factor le, 85% 86% 86% % (1 L Note7 Conversion Factors :
C1 = 7.46E-04 MW / HP C2 = 24 hours per day NoteJ CJ = 1.00E+06 Watt I megawatt Notes:
- 1. Recurri ng operational energy co nsumption takes into account the Intake flow capacity factor (see Note 7) .
- 2. A pump efficiency of 85% and a pump motor efficiency of 90% was considered in the calculation of horsepower required for the hypothetical low pressure screen wash , high pressure screen wash , auxiliary low pressure screen wash , and fish trough make-up water systems . These efficiencies were also considered ln the calculation of increase of annual energy requirement due to headless impacts on existing circulating water pumps .
- 3. Hours in a month are equal to the average hours in a month.
- 4. It is assumed that the new CW1S would be constructed while th e station is operating .
- 5. The existing screens at Oconee Nuclear Station are coarse-mesh fixed-panel screens without motors or an automated screen wash system .
- 6. Units 1, 2, and 3 utilize a common aquatic organism return trough , and therefore trough make-up water is common to all units.
- 7. The intake flow capacity factor Is the proportion of actual intake flow over the five year period of record (July 1, 2014 through June 30, 2019) to the design intake flow .
References :
[1] Duke Energy. 2019a . Oconee Nuclear Station Actual Intake Flow Rates: 71112014 - 6/3012019 . Received: 3 Jul 2019 .
[2) Evoqua Water Technologies . 2019. Evoqua Water Technologies Budget Proposal File No. 45062 .
(3] Llndeburg , Michael, R., 2003 . Environmental Engineering Reference Manual for PE Exam, Second Edition. Professional Publications , Inc.
(4] US Filter Corporation (US Filter) . 2016 . Communication between us Filter Staff and HOR Staff- TSV and Headloss Curves .
[SJ Duke Energy. 2019b. Individual Unit Gross Capacity Confirmation- Email communication with Duke Energy. Email received: 15 Oct 2019 .
(6) Duke Power Company. 2000. Oconee Nuclear Station . Intake Structure General Arrangement Plans and Sections . Drawing No. 0-339 - Rev 7. 16 Nov 2000 .
- 4 ofS
Duke Energy Carollnas , LLC I Oconee Nuclear Station 0 Estimated Energy Consu mption due to a Hypothetical Installation of Fine-mesh Sc reens In a New CWIS at Oconee Nuclear Station Calculations :
- 1. Power Rating for Screen Wash and Trough Make-up Water Pum ps Formula Used : 1, Note 2 nypcn:hetlcal SVSlem Para_,. units Unlt1 I UnU I Unft3 Total Screen Wash Pump Motor Input Power (High Pressure) HP /screen 13.5 I 13.5 I 13.5 Screen Wash Pump Motor Input Power (Low Pressure) HP /screen 2.0 I 2.0 I 2 .0 Screen W ash Pump Motor Inp ut Power (Auxiliary Low Pressure) HP /screen 0.4 I 0.4 I 0.4 Aquatic Organism Trough Water Pump Motor Input Power HP 0.7
- 2. Current Energy Use Formula Used: 2, Note 5 ExlsUnas-m
-- Parameters un1ts Unlt1 UnM2 Unlt3 Total Current Energy Usage Weekly per Screen MWhr I week/ screen 0 0 0 0 Current Energy Usage Weekly MWhr/week 0 0 0 0 Current Energy Usage Annually per Screen MWhr I year/ screen 0 0 0 0 Current Energy Usage Annually MWhr lyear 0 0 0 0
- 3. Energy Required to Operate a Hypothetical Fine-mesh Screen System due to New Screen and Pump Motors Formulas Used : 3, Note 1 NVDOthetlcal System Paramotera un1ts Unlt1 Unlt2 Unft3 Total Energy Use due to Installation of FMSs in New CWIS (Weekty) MWhr I week / screen 1.9 1.9 1.9 Energy Use due to Installation of FMSs in New CWlS (Weekly) MWhr/week 19 19 19 58 Energy Use due to Installation of FMSs in New CW1S (Annualty) MVVhr /year/ screen 99 101 100 Energy Use due to Installation of FMSs in New CWIS (Annualty) MWhr/year 989 1,007 1,005 3,001 Increase in Energy Use (Annually) MWhr / year / screen 99 101 100 Increase in Energy Use due to New Screen and Pump Motors MWhr/year 989 1,007 1,005 3,001 4 Energy Required to Operate a Fine-mesh Screen System due to Headloss Impacts on Existing Circulating Water Pumps Formulas Used: 5, Note 1, Note 2
-hetlcllSiistem Parameters un1ts Unlt1 un*z UnM3 Total Energy Consumption Due to Headless Impacts on Existing Circulating MWhr/week 18.4 18.7 18.7 56 Water Pumps Energy Consumption Due to Headless Impact s on Existing Circulating MWhr/year 956 974 972 2 ,903 Water Pumps
- 5. Total Energy Required to Operate a Hypothetical Fine-mesh Screen System Formulas Used:
hettcalSyatem Parameters Units Unlt1 Unft2 Unlt3 Total Operat ional Energy Consumption MWhr /year 1,945 1,981 1,978 5,904 6, Estimate the Construction Outage Energy Loss Formula Used:
hetlcll System Parameters Units unit 1 Unll 2 Unft3 Total Construction Outage Energy Loss MWh,
- 5 of S
This page intentionally left blank.
Appendix 13-A Peer Reviewer Resumes
This page intentionally left blank.
Charles C. Coutant, Ph.D.
(Retired Distinguished Research Ecologist, Oak Ridge National Laboratory; Coutant Aquatics)
- BRIEF RESUME Charles C. Coutant, Ph. D.
Retired Distinguished Research Ecologist, Environmental Sciences Division Oak Ridge National Laboratory, Oak Ridge, Tennessee 120 Miramar Circle, Oak Ridge, TN 37830 (865) 483-5976; ccoutant3@comcast.net Education: BA 1960 (Lehigh University, Bethlehem, Pennsylvania); MS 1962 (Lehigh); PhD 1965 (Lehigh).
Positions: (1) Battelle-Pacific Northwest Laboratories, Richland, Washington (1965-70):
Research Scientist, Columbia River Thermal Effects Studies; (2) Environmental Sciences Division, Oak Ridge National Laboratory (1970-2005): Manager Cooling Systems Program (1970-79),
Leader Multimedia Modeling Project (1979-82); Manager DOE Global Carbon Cycle Program (1985-86); Manager ORNL Exploratory Studies Program (1989-1991); Senior Research Staff (1982-85, 1986-88, 1992-2004); Distinguished Research Staff (2004-2005); (3) Private consultant (2005-present).
- Professional Affiliations: American Association for the Advancement of Science (Fellow);
American Institute of Fishery Research Biologists (Fellow); American Fisheries Society (AFS; Presidents of Water Quality Section, Tennessee Chapter, Southern Division, and full Society; Co-Editor of journal Transactions of the American Fisheries Society}; American Society of Limnology and Oceanography, lapsed; American Society for Testing and Materials (Chair Environmental Fate Models Task Group; lapsed); Ecological Society of America (Vice Chair Applied Ecology Section); Sigma Xi (Southeast Regional Lecturer, President Oak Ridge Chapter);
Water Pollution Control Federation (Literature Review Committee-Thermal Effects; lapsed).
Honors: Darbaker Prize in Microbiology, Pennsylvania Academy of Science; Director's Award, Battelle-Northwest; Excellence in Fisheries,. TN Chapter AFS; Outstanding Publication, Martin Marietta Energy Systems (then operator of ORNL); Distinguished Publication, American Society for Information Science; Distinguished Service Award, AFS; Outstanding Achievement Award, Southern Division, AFS; 2002 ORNL Distinguished Scientist of the Year; 2013 Career Achievement Award by Bioengineering Section AFS.
Publications: >337 exclusive of consulting reports Synopsis of Significant Technical Contributions: Field study of thermal discharge effects on invertebrates of Delaware River; Laboratory and field studies of thermal effects of Hanford reactors on Columbia River salmonids and other aquatic life; annual reviews of thermal effects publications 1968-1980; evaluation of aquatic thermal effects information to provide national water temperature criteria recommendations by the National Academy of Sciences; participation in development of EPA guidelines for Clean Water Act §316(a) thermal studies of power stations; development of biological data and criteria for environmental impact assessments of steam electric power plants; participant in the establishment of the Electric Power Research Institute and member of its national Advisory Council; development of electronic temperature telemetry of fishes as a research tool for thermal behavior studies; lead role in developing guidance for thermal power plant impact assessment for UNESCO and International Atomic Energy Agency; advisor on project evaluation to Bonneville Power Administration (BPA) Fish and Wildlife Program and member of Scientific Review Group; member ofNorthwest Power Planning Council's (NPPC) Independent
- Scientific Group; member National Marine Fisheries Service and NPPC' s Independent Scientific Advisory Board for Pacific salmon restoration; member NPPC's Independent Scientific Review Panel for review of projects for BPA's Fish and Wildlife Program; elucidation of the thermal ecology of striped bass through laboratory and field research and its application to management of the species in fresh water and estuaries; evaluation of impacts ofhydropower on aquatic systems; review and evaluation of Clean Water Act §316(a and b) study plans, studies, and documents for power companies; new concepts for behavioral guidance of salmon smolts; book editor, Behavioral Technologies for Fish Guidance (2001 ); book co-editor, Biology and Management of Inland Striped Bass and Hybrid Striped Bass (2103).
Synopsis of Management Experience: Leader of several research teams up to about 15 people; manager of Department of Energy intra- and extramural carbon dioxide research program ($4 million/yr); manager of ORNL internal funding program ($6-10 million/yr).
Synopsis of Power Plant-related Advisory Roles: Co-author ofEPA's 316(a) guidelines (1977);
Co-chair of Technical Advisory Committee for Virginia Power Company's North Anna Power Station 316(a) studies (1980s ); Co-chair of Technical Advisory Committee for Commonwealth Edison Co. 316(a, b) studies on Upper Illinois waterway (1991-1996); Technical Advisor to Electricity Corp of New Zealand for thermal discharge permitting patterned after 316(a) (1991-1994); Third-party advisor for Georgia Power Co. and the State of Georgia for Plant Branch 316(a) demonstration (1993-1999); Advisor for 316(a) demonstration studies for Carolina Power and Light Co.' s H. B. Robinson Steam Plant ( 1994-1996); Advisor for 316(a) demonstration by Public Service Electric and Gas Co. for Hudson Station (1995-1998), Mercer Station (1998-2001) and Salem Nuclear Station (1998-2000; 2006); Advisor for siting a power plant in Portugal (1997); Review of Brayton Point Plant 316(a) studies for USEPA (1997-1998 and 2003); Review and testimony on Diablo Canyon thermal effects monitoring for Pacific Gas and Electric (1999-2000); Review and white paper preparation on fish population status and trends for Hudson River Utilities (2001-2002); Advised Dynegy Northeast on Danskammer and Roseton power plant relicensing issues (2002-2005); Served on Fishery Panel for City of Newport News water intake (2004); Consultant to Dominion North Anna regarding biological aspects ofNRC Early Site Permit for additional units at North Anna Nuclear Station (2005-2007); Advisor to Natural Solutions for implementation of a Flow Velocity Enhancement System for fish guidance and debris management at intakes (2005-present); Member of University of Tennessee team for 316(a) biological assessment of thermal discharge from Blue Ridge Paper Products paper mill (2005-2006), related litigation (2009-2011) and permit renewal studies (2012-2013); Technical advisor to a stakeholder group evaluating revision of Colorado temperature standards (2006-2007);
Participant in EPRI study of effectiveness of strobe lights for reducing impingement at power plant intakes (2006-2007); Advisor for Millstone Nuclear Power Plant (Connecticut) NPDES re-permitting (2006-2009); Expert witness for Vermont Yankee Atomic Power Plant NPDES re-licensing (2007); Advisor and expert witness for resolving aquatic environmental impacts for NRC Early Site Permit for expansion of the Vogtle nuclear power plant, Georgia (2006-2009); Advisor of the Utility Water Act Group (UWAG) for developing consistent national approaches for 316(a) implementation (2007-2010); Consultant and expert witness for Environment Canada (2008-2009); Consultant to Utility Water Act Group (2006-2009); Consultant to Dominion Manchester for planning biological studies for a 316(a) Demonstration for the Manchester Street Station, Providence, RI (2009-2010); Consultant to Arcadis, Inc. for thermal-effects analyses of two Florida power stations (2010); Consultant to Idaho Power Co. for application for a site-specific temperature standard for the Snake River (2010-2014); Consultant to Tennessee Valley Authority for entrainment and impingement studies leading to NRC permit for Watts Bar Nuclear 2 (2010-2011 ); Consultant to Duke Energy for post-event analysis of a water-intake incident at McGuire
- Nuclear Station, North Carolina (2011); Consultant to ASA Analysis and Communication for review of316(a) documents (2012); Participant in EPRl-funded study by Natural Solutions of debris and fish-impingement management at the water intake of Dairyland Cooperative's Genoa Station on the Mississippi River (2012); Consultant to Dominion Virginia Power for approaches to meeting West Virginia water temperature standards (2012-present); Consultant to Energy Northwest for analysis of existing cooling-water intake structure for NPDES re-permitting and development of a 316(b) study plan for the Columbia (nuclear) Generating Station (2013-present);
Consultant to Alden Research Laboratories for design of studies of American eel guidance (2014-present); Reviewer for EPRI of 3 l 6(b) entrainment study plans for seven power plants on the Ohio River (Cardinal, Clifty Creek, F. B. Culley, Kyger Creek, Mill Creek, Sammis, and Stuart)(2014);
Reviewer for entrainment study plans for BC Hydro's "Site C" new hydropower plant on behalf of the Natural Sciences and Engineering Research Council of Canada (2015).
March2015
Dr.PaulJakus (Professor, Utah State University- Department of Applied Economics)
- PAUL MARK JAKUS Dept. of Applied Economics September 2018 4835 Old Main Hill Utah State University Logan, UT 84322-4835 (435) 797-2309 Paul.Jakus@usu.edu Current Position Professor, Department of Applied Economics, Utah State University (May 2008-present)
Professional Experience Faculty Associate, Ecology Center, Utah State University (August 2014 -present)
Visiting Scholar, Center for Business and Economic Research, University of Tennessee (August 2012-December 2012.
Professor and Head, Dept. of Applied Economics, Utah State University (May 2008-May 2012)
Associate Professor/Professor, Department of Economics, Utah State University (July 2001-May 2008)
Assistant/Associate Professor, Dept. of Agricultural Economics and Rural Sociology, University of Tennessee (February 1992- June 2001)
Graduate Research Assistant, Dept. of Economics and Business, North Carolina State University (May 1987 - February 1992)
Peace Corps Volunteer, The Gambia, West Africa (August 1984 - July 1986)
Graduate Research Assistant, Colorado State University (August 1982 - August 1984)
Research Assistant, University ofNevada, Reno (September 1980 -August 1982)
Education Ph.D., North Carolina State University, Economics, 1992 MS., Colorado State University, Agricultural and Natural Resource Economics, 1984 B.S., University of Nevada, Reno, Agricultural and Natural Resource Economics, 1982 Publications in Refereed Journals (Graduate student in italics)
Jakus, Paul M., and Sherzod B. Akhundjanov. 2018. "Neither Boon nor Bane: The Economic Effects of a Landscape-Scale National Monument." Land Economics, 94(3):323-339.
Jakus, Paul M. 2018. "A Review of Economic Studies Related to the Bureau of Land Management's Wild Horse and Burro Program." Human-Wildlife Interactions, 12(1):58-74 .
- Jakus, Paul M., Nanette Nelson, and Jeffrey Ostenniller. 2017. "Using Survey Data to Determine a Numeric Criterion for Nutrient Pollution." Water Resources Research, 53(12):10,188-10,200. doi:10.1002/2017WR021527 Jakus, Paul M., Jan E. Stambro, Michael T. Hogue, John C. Downen, Levi Pace, and Therese C.
Grijalva. 2017. "Western Public Lands and the Fiscal Implications of a Transfer to States." Land Economics 93(3):371-389.
Nelson, Nanette, John Loomis, Paul M. Jakus, Mary Jo Kealy, Nicholas von Stackelberg, and Jeffrey Ostermiller. 2015. "Linking Ecological Data and Economics to Estimate the Total Economic Value of Improving Water Quality by Reducing Nutrients." Ecological Economics, 118:1-9. doi: I 0.1016/j.ecolecon.2015.06.013 Liu, Lu and Paul M. Jakus. 2015. "Bedonie Valuation in an Urban High-Rise Housing Market."
Canadian J ofAgricultural Economics, 63(2):259-273. doi: 10.1111/cjag. l 2052 Coulibaly, Lassina, Paul M. Jakus and John E. Keith. 2014. "Modeling Water Demand When Households Have Multiple Sources of Water." Water Resources Research, 50, doi: 10.1002/2013WR015090.
Shaw, W. Douglass, Paul M. Jakus, and Mary Riddel. 2012. "Perceived Arsenic-Related Mortality Risks for Smokers and Non-smokers." Contemporary Economic Policy, 30(3):417-429. doi :10.1111/j .1465-7287.2011.00283.x Nguyen, To N., Paul M. Jakus., W. Douglass Shaw and Mary Riddel. 2010. "An Empirical Model of Perceived Mortality Risks for Selected United States Arsenic Hot Spots." Risk Analysis 30(10):1550-1562. doi:10.l l l l/j.1539-6924.2010.01450.x J akus, Paul M., John E. Keith, Lu Liu, and Dale Blahna. 2010. "The Welfare Effects of Restricting Off-Highway Vehicle Access to Public Lands." Agricultural and Resource Economics Review 39(1):89-100.
Jakus, Paul M., W. Douglass Shaw, To N. Nguyen, and Mark Walker. 2009. "Risk Perceptions of Arsenic in Tap Water and Consumption of Bottled Water." Water Resources Research, 45, W05405, doi:10.1029/2008WR007427.
Swain, Edward B., Paul M. Jakus, Glenn Rice, Frank Lupi, Peter Maxson, Joseph Pacyna, Alan Penn, Samuel Spiegel, and Marcello Viega. 2007. "Socioeconomic Consequences of Mercury Use and Pollution." Ambio, 36(1):45-61.
Jaenicke, Edward C., R. Wesley Harrison, Kimberly L. Jensen, and Paul M. Jakus. 2006. "Follow the Leader: Adoption Behavior in Food Retailers' Decision to Offer Fresh Irradiated Ground Beef." Agribusiness: An International J 22(4):547-568.
- Tiller, Kelly H and Paul M. Jakus. 2005. "Applying the Miceli Model to Explain Cooperation in Municipal Solid Waste Management." Agricultural and Resource Economics Review, 34(2):217-225.
Jensen, Kimberly L., Paul M. Jakus, Burton C. English and Jamey Menard. 2004. "Consumers' Willingness to Pay for Eco-Certified Wood Products." J. Agricultural and Applied Economics, 36(3):617-626.
Jakus, Paul M., Kimberly L. Jensen, and George C. Davis. 2003. "Revenue Impacts ofMPP Branded Funds: A Firm Level Analysis." Agricultural and Resource Economics Review, 32(2):184-197.
Jensen, Kimberly L., Paul M. Jakus, Burton C. English, and Jamey Menard. 2003. "Market Participation and Willingness to Pay for Environmentally Certified Hardwood Products."
Forest Science, 49(4):632-641.
Jakus, Paul M. and W. Douglass Shaw. 2003. "Perceived Hazard and Product Choice: An Application to Recreational Site Choice." J. Risk and Uncertainty, 26(1):77-92.
Caplan, Arthur, Therese C. Grijalva, and Paul M. Jakus. 2002. "Waste Not or Want Not: A Contingent Ranking Analysis of Curbside Waste Disposal Options." Ecological Economics, 43(2-3):185-197.
Grijalva, Therese A., Robert P. Berrens, Alok Bohara, Paul M. Jakus, and W. Douglass Shaw.
2002. "Valuing the Loss of Rock Climbing Access in Wilderness Areas: A National-Level Random Utility Model." Land Economics, 78(1):103-120.
Jakus, Paul M., Paula Dowell, and Matthew N. Murray. 2000. "The Effect of Fluctuating Water Levels on Reservoir Fishing." J. Agricultural and Resource Economics, 25(2):520-532.
Parsons, George R., Paul M. Jakus, and Theodore D. Tomasi. 1999. "A Comparison of Welfare Estimates from Four Models for Linking Seasonal Recreational Trips to Multinomial Lo git Models of Site Choice." J. Environmental Economics and Management, 3 8(2): 143-157.
Jakus, Paul M., Dimitrios Dadakas, and J. Mark Fly. 1998. "Fish Consumption Advisories:
Incorporating Angler-Specific Knowledge, Habits, and Catch Rates in a Site Choice Model." AmericanJ. Agricultural Economics, 80(5):1019-1024. (Proceedings article)
Jakus, Paul M., J. Mark Fly, Becky Stephens, and Alan Barefield. 1998. "Leasing by Tennessee Hunters." Proceedings of the Southeastern Association of Fish and Wildlife Agencies, 52:349-358. (Refereed)
- Adams, Barry H., George C. Davis, Kimberly L. Jensen, and Paul M. Jakus. 1997. "Priorities and Preferences in the Allocation of MPP Funds to Agribusiness Firms." American J.
Agricultural Economics, 79(4): 1319-1331.
Kelly H Tiller, Paul M. Jakus, and William M. Park. 1997. "Household Willingness to Pay for DropoffRecycling: A Contingent Valuation Study." J. Agricultural and Resource Economics, 22(December):310-320.
Jakus, Paul M., Mark Downing, Mark S. Bevelhimer and J. Mark Fly. 1997. "Do Fish Consumption Advisories Affect Reservoir Anglers' Site Choice?" Agricultural and Resource Economics Review, 26(2):198-204.
Jakus, P.M., J. Mark Fly and Becky Stephens. 1997. "Estimating Tennessee Residents' Willingness to Pay for Teaming with Wildlife." Human Dimensions of Wildlife 2(3):15-25.
Jakus, Paul M. and W. Douglass Shaw. 1997. "Congestion at Recreation Areas: Empirical Evidence on Perceptions, Mitigating Behavior, and Management Preferences." J.
Environmental Management, 50(4):389-402 .
- Jakus, Paul M. and Paul B. Siegel. 1997. "The Effect of Individual and Community Attributes on Residents' Attitudes Toward Tourism-Based Development." Review of Regional Studies, 27(1):49-64.
Jakus, Paul M., Kelly H Tiller and William M. Park. 1997. "Explaining Rural Household Participation in Recycling." J. Agricultural and Applied Economics, 29(1 ): 141-148.
Shaw, W. Douglass and Paul M. Jakus. 1996. "Travel Cost Demand Models for Rock Climbing." Agricultural and Resource Economics Review, 25(4):133-142.
Jakus, Paul M. and W. Douglass Shaw. 1996. "An Empirical Analysis of Rock Climbers' Response to Hazard Warnings." Risk Analysis, 16(4):581-586.
Jakus, Paul M., Kelly H Tiller, and William M. Park. 1996. "Generation of Recyclables by Rural Households." J. Agricultural and Resource Economics, 21(1):96-108.
Jakus, Paul M., J. Mark Fly, and J. Larry Wilson. 1996. "Explaining Public Support for Fisheries Management Alternatives." North American J. of Fisheries Management, 16:41-48 .
- Siegel, Paul B. and Paul M. Jakus. 1995. "Tourism as a Sustainable Rural Development Strategy: Finding Consensus in Resident Attitudes." Southern Rural Sociology, 11(1):17-41.
Jakus, Paul M. 1994. "Averting Behavior in the Presence of Public Spillovers: Household Control of Nuisance Pests." Land Economics, 70(3):273-285.
Jakus, Paul M., J. Mark Fly and J. Larry Wilson. 1993. "Activities, Regulatory Preferences and Regulatory Perceptions of Tennessee Anglers." Proceedings of the Southeastern Association of Fish and Wildlife Agencies, 47:767-774. (Refereed)
Smith, V. Kerry, Raymond B. Palmquist and Paul M. Jakus. 1991. "Combining Farrell Frontier and Bedonie Travel Cost Models for Valuing Estuarine Quality." Review of Economics and Statistics, 73(4):694-699.
Miller, Watkins W., Chauncey T.K. Ching, John F. Yanagida and Paul M. Jakus. 1985.
"Agricultural Water Pollution Control: An Interdisciplinary Approach." Environmental Management, 9(1):1-6.
Manuscripts in Progress Kim, Man-Keun, and Paul M. Jakus. "Wildfire, National Park Visitation, and Changes in Regional Economic Activity." Revise and Re-submit, J Outdoor Recreation and Tourism, June 2018.
Jakus, Paul M. and Sherzod Akhundjanov. "Landscape-scale National Monuments and Regional Per Capita Income." Under review, August 2018.
Landis, Malieka, Don E. Albrecht, Paul M. Jakus, Marion T. Bentley, Thomas R. Harris, Linda J. Cox, Phil Watson, George Borden, and Paul Lewin. "Area Sector Analysis Process:
Identifying Where Community Goals and Industry Needs Intersect." April 2018.
Book Chapters and Non-Refereed Proceedings Kealy, Mary Jo, Nick von Stackelberg, Jeffrey Ostermiller, Nanette Nelson, John Loomis, and Paul M. Jakus. 2014. "The Value oflmproving Water Quality: Case Study of Nutrient Reductions in Utah's Waters." Proceedings of the Annual Meeting of the Water Environment Federation, 2014(7):6237-6252 .
- Jakus, Paul M. 2014. "Outdoor Recreation." Entry (pp. 242-244) in Environmental and Natural Resource Economics: An Encyclopedia. J.C. Whitehead and T.C. Haab, eds. Santa Barbara, CA: Greenwood ABC Clio.
Jakus, Paul M. 2013. "Economic Analysis of Fish Consumption Advisories." Chapter 33 in Biology and Management oflnland Striped Bass and Hybrid Striped Bass, James S.
Bulak, Charles C. Coutant, and J.A. Rice, eds. American Fisheries Society.
Jakus, Paul M., John C. Bergstrom, Marty Phillips, and Kelly O'Brien. 2011. "Modeling Behavioral Changes in Reservoir Operations in the Tennessee Valley Region." Chapter 17 in Preference Data for Environmental Valuation, John Whitehead, Ju-Chin Huang, and Tim Haab, eds. Routledge.
Jakus, Paul M., Becky Stephens, and J. Mark Fly. 2006. "Temporal Reliability in Contingent Valuation (With a Restrictive Research Budget)." Chapter 11 in Handbook on Contingent Valuation, Anna Alberini and James Kahn, eds. Northampton, MA: Edward Elgar.
Shaw, W. Douglass, Mary Riddel, and Paul M. Jakus. 2005. "Valuing Environmental Changes in the Presence of Risk: A Review and Discussion of Some Empirical Issues." Chapter 7 in Folmer, H. and T. Teitenberg (eds.), International Yearbook of Environmental and Resource Economics: A Survey of Current Issues 2005/2006 .
Kelly H. Tiller, Paul M. Jakus, and William M. Park. 2003. "Household Willingness to Pay for DropoffRecycling: A Contingent Valuation Study." Book chapter in, T.C. Kinnaman (ed.), The Economics of Residential Solid Waste Management, Ashgate. (Re-print of 1997 JARE article)
Jakus, Paul M., Mary Riddel, and W. Douglass Shaw. 2003. "Are Climbers Fools? Modelling Risky Recreation." Chapter 5 in N.D. Hanley, W.D. Shaw, and R. Wright (eds.), The New Economics of Outdoor Recreation, Edward Elgar.
Other Publications Jakus, Paul M., Steven W. Burr, Tyler A. Baird, and Carlos Silva. 2013. "The Economic Impact of Bear River Heritage Area Tourism." Center for Society, Economy, and the Environment Research Report #5. July.
Kim, Man-Keun and Paul M. Jakus. 2013. "The Economic Contribution and Benefits of Utah's Blue Ribbon Fisheries." Center for Society, Economy, and the Environment Research Report #4. February.
Ward, R.A., Paul M. Jakus and Lassina Coulibaly. 2013. "The Economic Contribution of Agriculture to the Economy of Utah in 2011." Center for Society, Economy, and the Environment Research Report #3. February.
- Jakus, Paul M., Meghan McGuinness, and Alan Krupnick. 2002. "The Benefits and Costs of Fish Consumption Advisories for Mercury in the Chesapeake Bay." Resources for the Future Discussion Paper 02-55, October.
http://www.rff.org/disc papers/PDF files/025 5 .pdf Jakus, Paul M. 2001. Book Review: National Parks and Rural Development, edited by Gary Machlis and Donald Field. Growth and Change, 32(3):435-437.
Jakus, Paul M. and D. Alan Barefield. 2000. "Hunting Adds Value to Land and Farms."
Tennessee Agri-Science, Issue 189, pp.37-38.
Jakus, Paul M., Dimitrios Dadakas, Becky Stephens, and J. Mark Fly. 1999. "Fishing and Boating by Tennessee Residents in 1998 and 1999." University of Tennessee Agricultural Experiment Station Research Report 99-17(October).
Harper, Craig A., Charles E. Dixon, Paul M. Jakus, and D. Alan Barefield. 1999. "Earning Additional Income through Hunt Leases on Private Land." PB1627, Agricultural Extension Service, University of Tennessee.
Fly, J. Mark, Becky Stephens, and Paul M. Jakus. 1997. "Monitoring Hunting Activities in Tennessee." Tennessee Wildlife, 20(5):2-5.
Fly, J. Mark, Becky Stephens, and Paul M. Jakus. 1997. "Hunting by Tennessee Residents: A Report on Activities and Attitudes for the 1992, 1993, and 1994 Hun{ing Seasons."
University of Tennessee Agricultural Experiment Station Research Report 97-13. May.
Fly, J. Mark, J. Larry Wilson, Paul M. Jakus, and Becky Stephens. 1996. "Social and Biological Dimensions of Fisheries Management Research on Norris Reservoir." Tennessee Agri-Science, 180(Fall):32-33.
Fly, J. Mark, Paul M. Jakus and Becky Stephens. 1996. "Access to Private Land for Recreation:
Issues and Opportunities." Tennessee Agri-Science, 180(Fall):34-37.
Jakus, Paul M., J. Mark Fly, and Becky Stephens. 1996. "Public Opinion on the Tennessee Wildlife Resources Agency." University of Tennessee Agricultural Experiment Station Research Report 96-06. April.
Jakus, Paul M., Paul B. Siegel and Richard L. White. 1995. "Tourism as a Rural Development Strategy: Finding Consensus in Resident Attitudes." Tennessee Agri-Science, 176(Fall):22-29 .
- Jakus, Paul M., Laurienne Whinstanley, and J. Mark Fly. 1994. "Fishing, and Hunting by Tennessee Residents: A Report on Activities and Attitudes: March-August 1993."
University of Tennessee Agricultural Experiment Station Research Report 94-18.
September.
Jakus, Paul M. and V. Kerry Smith. 1992. "Measuring Use and Nonuse Values for Landscape Amenities: A Contingent Behavior Analysis of Gypsy Moth Control." Resources for the Future Discussion Paper QE-92-07, Washington, D.C.
Grants and Contracts (lead or co-lead PI unless otherwise indicated)
Jakus, P.M., E. Hammill, M-K Kim, N. Mesner, and R. Martin. "The Physical and Economic Consequences of Reducing the Probability of Wildfire in Utah." 8/16 through 12/16. Utah Department of Agriculture and Food. $160,094.
Jakus, P.M. "Analysis ofFederal Public Lands Transfer to the State of Utah." 4/13 through 11/14.
Utah Governor's Public Lands Policy Coordination Office. $118,187.
Jakus, P .M. and R.A. Ward. "The Economic Impact of Agriculture and CS As in Utah." Utah Dept.
of Agriculture and Food. 7/12 through 6/13. $30,275 .
Jakus, P.M. and R.A. Ward. "Economic Impact of USU Sponsored Programs." 7/12 through 5/13.
$30,000.
Ward, R.A. and P.M. Jakus. "Economic Impact of USU Sponsored Programs." 7/11 through 5/12.
$30,000.
Kim, M-K. and P .M. Jakus. "Economic Benefit of Blue Ribbon Fisheries in Utah." Utah Division of WildlifeResources. 2011-2012. $27,617 Ward, R.A. and P .M. Jakus. "Economic Impact of USU Sponsored Programs." 6/10 through 5/11.
$30,000.
Jakus, P .M., R.A. Ward, M.K. Kim and D. Feuz. "Research on the Agricultural and Rural Economy of Utah." 10/09 through 3/12. Utah Department of Agriculture and Food. $48,877.
Keith, J., R. Krannich, C. Fawson, P.M. Jakus, and S. Burr. Utah Public Lands Socioeconomic Baseline Study. 6/06 through 7/11. Utah Governor's Public Lands Policy Coordination Office. $750,000 .
- Keith, J. and P .M. Jakus. 3/1/05-10/1/06. Recreation Valuation of Ken's Lake, UT. Utah Division of Water Resources. ($39,510).
Jakus, P.M. (7/1/02-6/30/05). "Irradiated ground beef: the adoption decision by supermarkets and grocery stores." Sub-contract from Pennsylvania State University as part of NRI grant of same name. $10,648.
"Effectiveness of Fish License Marketing in Utah." Funded by the Utah Division of Wildlife Resources. January-December 2003, $10,000.
"Recreational Trip-Response to Changes in TVA Reservoir Management." Funded by Kleinschmidt and Associates, as part of TVA Reservoir Operations Review. 2002-2003,
$37,000.
"Estimating the Economic Value of Off-Highway Vehicle Recreation in Utah." Funded by New Faculty Research Grant, Utah State University. 2002-2003, $12,800.
"Valuing TVA's Intangible Assets for Integrated Capital Asset Decision-Making," funded by the Tennessee Valley Authority. 2000-2002, $83,700. With Steven Stewart and James Kahn .
- "Monitoring the Behavior of Tennessee Sportsmen," funded by Tennessee Wildlife Resources Agency. 2000-2001, $90,000. With J. Mark Fly.
"Irradiated Ground Beef: the Adoption . Decision by Supermarkets and Grocery Stores," funded .
by USDA National Research Initiative. 2000-2002, $110,000. With E.C. Jaenicke, R.W.
Harrison, and K.L. Jensen.
"Consumers' Willingness to Pay for Eco-Labeled Hardwood Forest Products from Environmental Management Certified Programs," funded by US Forest Service. 2000-2001, $40,550. With K.L. Jensen and B.C. English.
"Economic Consequences of Tier III Water Quality Designation for Tennessee Streams," funded by East Tennessee Development District and Tennessee Department of Environment and Conservation. 1999-2000, $25,200 "Economic Consequences of TVA's Lake Draw-down," funded by UT Center for Business and Economic Research. 1998, $3,500 "Monitoring the Behavior of Tennessee Sportsmen," funded by Tennessee Wildlife Resources Agency. 1996-1999. $225,000, with J. Mark Fly
- "Analysis of Onsite Recreation Visitation at Mohonk Preserve," funded by Mohonk Preserve, Inc. 1995, $1,700 "Monitoring the Behavior of Tennessee Sportsmen," funded by Tennessee Wildlife Resources Agency. 1993-1996, $280,000. With J. Mark Fly "Conservation Efforts and Their Impacts on Rural Regions," funded by USDA Soil Conservation Service. 1993-1995, $120,000. With B.C. English (lead PI), D.E. Ray, P.B. Siegel "Sustainable Development Strategies for Communities with Tourism Based Economies in the Southern Appalachians," funded by Tennessee Valley Authority. 1993,
$8,000. With P.B. Siegel.
"Survey of Tennessee Anglers," funded by Tennessee Wildlife Resources Agency. 1992-1993,
$25,000. With J.L. Wilson (lead PI) and J.M. Fly Staff Papers and Miscellaneous Reports to Granting Agencies (Not appearing elsewhere as Publications in Refereed Journals, Research Reports or Papers in Progress)
Jakus, Paul M., Man-Keun Kim, Randy C. Martin, Ian Hammond, Edd Hammill, Nancy Mesner, and Jacob Stout. 2017. "Wildfire in Utah: The Physical and Economic Consequences of Wildfire." February.
Stambro, J.E., J.C. Downen, M.T. Hogue, L. Pace, P.M. Jakus, and T.C. Grijalva. 2014. "An Analysis of a Transfer of Federal Lands to the State of Utah." November.
Jakus, Paul M., Mary Jo Kealy, John Loomis, Nanette Nelson, Jeff Ostermiller, Cody Stanger, and Nicholas von Stackelberg. 2013. "Economic Benefits of Nutrient Reductions in Utah's Waters. Project Report prepared for Utah Division of Water Quality by CH2M Hill, April.
Kim, Man-Keun and Paul M. Jakus. 2013. "The Economic Contribution and Benefits of Utah's Blue Ribbon Fisheries." Center for Society, Economy, and the Environment Research Report #4. Prepared for Utah Division of Wildlife Resources.
Ward, R.A., Paul M. Jakus, and Lassina Coulibaly. 2013. "The Economic Contribution of Agriculture to the Economy of Utah in 2011." Center for Society, Economy, and the Environment Research Report #3. February. Prepared for the Utah Department of Agriculture and Food.
Ward, Ruby A., Paul M. Jakus, Anne I. Whyte, and L. Walker. 2011. "The Economic Impact of Utah State University Sponsored Research Programs on the Utah Economy." Economic
- Research Institute Report 2011-1. March. Prepared for the Utah Department of Agriculture and Food.
Ward, Ruby A., Paul M. Jakus, and Dillon Feuz. 2010. "The Economic Impact of Agriculture on the State of Utah." Economics Research Institute Report 2010-02. Prepared for the Utah Department of Agriculture and Food.
Jakus, Paul M., John E, Keith, and Lu Liu. 2008. "Economic Impacts of Land Use Restrictions on OHV Recreation in Utah." December. Prepared for Utah Public Lands Policy Coordination Office.
Keith, John E. Paul M. Jakus, and Jacoba Larsen. 2008. "Impacts of Wild and Scenic River Designation." December. Prepared for Utah Public Lands Policy Coordination Office.
Keith, John E., Steven W. Burr, Jody Gale, Paul M. Jakus, Richard S. Krannich, Douglas Reiter, and David G. Tarboton. 2008. "Utah's Public Lands Socioeconomic Baseline Study:
Summary Report." December. Prepared for Utah Public Lands Policy Coordination Office.
Jakus, Paul M. 2003. "Estimating the Economic Value of All-Terrain Vehicle Recreation in Utah." Final report in fulfillment of USU New Faculty Grant. September.
- Jakus, P.M., J.R. Kahn, and S.R. Stewart. 2002. "Incorporating Economic Values into TVA River Scheduling Operations." Final Contract Report in fulfillment of Tennessee Valley Authority Activity Authorization Contract No. 99R2A-252850 entitled, "Valuing TVA's Intangible Assets for Integrated Capital Asset Decision-Making." March.
Jensen, Kimberly, Paul M. Jakus, Burton C. English, and Jamey Menard. 2001.
"Environmentally Certified Wood Products: A Study of Consumer's Perceptions and Willingness to Pay." Final Report for US Forest Service, September.
Stewart, Steven, James R. Kahn, and Paul M. Jakus. 2001. "Economic Values and TVA River Operations." Interim report for Tennessee Valley Authority, August.
Stephens, Becky, Paul M. Jakus, and J. Mark Fly. 2001. "Fall 2000 REAL Database Fishing Survey Results." University of Tennessee Human Dimensions Research Lab, March.
Jakus, Paul M., Dimitrios Dadakas, Alexandria Huerta, Matthew N. Murray, and Paula Dowell.
2000. "Economic Analysis of Designating Outstanding National Resource Waters in Tennessee: Theory and An Application in Monroe County." March.
Dadakas, Dimitrios and Paul M. Jakus. 1999. "El Nifio/Southern Oscillation Effects on Farmland Values in the United States." University of Tennessee Dept. of Agricultural
- Economics and Rural Sociology Staff Paper #99-05(May).
Murray, Matthew N., Paul M. Jakus, Paula Dowell, Vickie Cunningham, and Sanela Porca.
1998. "Economic and Fiscal Consequences of TVA's Drawdown of Cherokee and Douglas Lakes." University of Tennessee Center for Business and Economic Research, October.
Jakus, Paul M., Fly, J. Mark, Becky Stephens, and Dimitrios Dadakas. 1998. "Fishing and Boating by Tennessee Residents in 1994, 1995, and 1996." Dept. of Agricultural Economics and Rural Sociology Staff Paper #98-10, July.
- Becky Stephen*s, Paul M. Jakus and J. Mark Fly. 1997. "Fishing for Wild, Stream-Bred Trout in Tennessee." Dept. of Agricultural Economics and Rural Sociology Staff Paper #97-03, May.
Fly, J. Mark, Becky Stephens, and Paul M. Jakus. 1997. "Monitoring of the 1995 Special September Goose Season." University of Tennessee Human Dimensions Research Lab, January.
Fly, J. Mark, Becky Stephens, and Paul M. Jakus. 1996. "Hunting by Tennessee Residents:
Cherokee Wildlife Management Area." University of Tennessee Human Dimensions Research Lab, December.
- Jakus, Paul M., J. Mark Fly, and Becky Stephens. 1996. "Gauging Support Among Tennessee
_Residents for Nongame Species Management Funding Alt,ernatives." University of Tennessee Human Dimensions Research Lab, March.
Jakus, Paul M. 1996. "Hunter Support for Two Methods of Access to Public Hunting Areas:
Preliminary Analysis." University of Tennessee Human Dimensions Research Lab, February.
Jakus, Paul M.; J. Mark Fly, Becky Stephens, and Ramsi Chewning. 1996. "Fishing, Hunting and Nonconsumptive Activities by Tennessee Residents: March-August 1995."
University of Tennessee Human Dimensions Research Lab, April.
Jakus, Paul M., Laurienne Whinstanley, and J. Mark Fly. 1995. "Fishing, Hunting and Nonconsumptive Activities by Tennessee Residents: March-August 1994." University of Tennessee Human Dimensions Research Lab, July.
Teaching Experience Utah State University APEC 3012: Introduction to Natural Resource and Regional Economics (3 er), Fall 2009
- APEC/ECN 2010: Introductory Microeconomics (3 er), 13 sections, Spring 2002 through Spring 2014.
Econ 4310/5310: Mathematical Economics (3 er) Fall 2001-2006.
APEC 5950: Applied Economic Policy (3 er) Fall 2015-16, Spring 2018.
Econ 7510: Environmental Economics (4 er) Spring 2002-2006.
APEC/ECN 7950: Graduate Seminar (1 er) each semester, Fall 2003 through Spring 2006.
ENVS 3000: Natural Resource Policy and Economics (4 er) Fall 2007.
University of Tennessee AE 320: Agricultural Microeconomics (3 er) Fall 1999 through Fall 2000.
AE 570: Advanced Natural Resource Economics (3 er) Fall 1992 through 1998.
AE 505: Microeconomic Theory (3 er) Fall 1995 through Fall 1997.
AE 670: Topics in Natural Resource Economics (2 er) Summer 1996.
I also helped team teach AE 670 (Summer 1992), AE 620, Advanced Quantitative Methods (Spring, 1993 - 1995), and EC 678, Economics of Environmental Policy (Spring 2001 ).
Ph.D. Dissertations Chaired Coulibaly, Lassina, December 2014. "Household demand for a reliable public water supply."
Liu, Lu, August 2010. "Three Essays on Environmental and Spatial-Based Valuation of Urban Land and Housing.
Zhu, Yuexia, December 2007. "Three Essays on Environmental Economics."
M.S. Theses Chaired Crabb, Ben. 2016. 'The Influence of Institutional Oil and Gas Ownerships on County Wages in the Intermountain West."
Carlos Silva. 2014. "Calculating Willingness to Pay as a Function of Biophysical Water quality and Water Quality Perceptions."
Kevin L. Brady. 2008. "Safety-Focused Altruism: Valuing the Lives of Others."
Andrea Bohmholdt, 2007. "Benefit Cost Analysis for a Wind Turbine at Utah State University."
(Plan B professional paper)
Benjamin Blau, 2005. "An Economic Approach to Charitable Giving." (Plan B Professional Paper)
University of Tennessee Alexandria 1 Huerta, 2001. "Consumer Willingness to Pay for Certified Wood Products."
- Dimitrios Dadakas, 1999. "El Nino/Southern Oscillation Effects on United States Farmland Values: A Ricardian Approach."
Laurienne Whinstanley, 1995. "Empirically Estimating the Role of Water Quality on Participation and Visitation in Reservoir Fishing: An Application to the Conservation Reserve Program."
Michael Bates, 1994. "Analyzing the Effect of Site Quality on Tennessee Reservoir Fishing Site Selection Using a Random Utility Model."
W Larry Waters, 1994. "Reservoir Fishing Benefits Across Tennessee Regions."
Honors and Awards Agricultural and Resource Economics Review, Fellow J Agricultural and Resource Economics, Associate Editor, 2003-2006 Society and Natural Resources, Associate Editor, 2003-2005 J Environmental Economics and Management, Editorial Council, 2001-2003 Water Resources Research, Associate Editor, 1999-2002 Outstanding Referee Citation, Water Resources Research, 1998 Western Regional Research Project W-133, President, 1997-98.
Dutch and Marilee Cavender Award for Best Research Publication, University of Tennessee Institute of Agriculture, 1997 J Agricultural and Applied Economics, Editorial Council, 1996-99 Outstanding Graduate Student Paper, 1991. Southern Association of Agricultural Economics Reviewer Refereed Journals American J. Agricultural Econ. J. Agricultural and Applied Econ.
J. Environmental Econ. & Management Land Economics J. Agricultural and Resource Econ. Water Resources Research Agricultural and Resource Econ. Rev. Growth and Change Marine Resource Econ. Canadian J. Forestry Econ.
J. Environmental Management Review of Regional Studies Human Dimensions of Wildlife Australian J. Agricultural and Resource Econ.
Conservation Biology J. Policy Analysis and Management Canadian J. Agricultural Econ. Economic Inquiry Choices J. Toxicology and Environmental Health Environment and Resource Econ. STOTEN J. Environmental Policy & Mgmt.
- Competitive Grant and Scholarship Programs Genome Canada LSARP (2014, 2016)
United States-Israel Bi-national Agricultural Research and Development Fund United States Environmental Protection Agency 1998, 1999 NSF/EPA Decision Making and Environmental Policy 1997, 1999-2001 STAR Fellowship Program 1997 Exploratory Research Program University of Georgia Sea Grant Program Service (Utah State Universit)')
Chair, APEC Natural Resource Economics Search Committee, 2015-16 (Sherzod Akhunjanov)
Chair, APEC Natural Resource Economics*search Committee, 2013-14 (Eric Edwards)
Chair, ENVS Department Head Search Committee, 2013-14 (Chris Lant)
Member, Vice-President for Agriculture Search Committee, 2013 (Ken White)
Chair, College of Agriculture and Applied Sciences Post-Tenure Review Committee (2013/14)
Member, College of Natural Resources Strategic Planning Committee, 2011-12 Member, USU Department Heads Executive Council, 2009-12 (Chair, 2010-11)
Member, Economics Search Committee, 2008 Member, Dept. of Environment and Society, 2008 (Chris Monz)
Member, USU Central Promotion Committee, 2006-2007 Chair, Department of Economics International Trade Search Committee, 2004 (Reza Oladi)
Chair, Graduate Programs, Dept. of Economics, 2002-2006 Member, Utah State University Water Resources Task Force, 2002-2005 Chair and Member, Numerous promotion and tenure committees (Colleges of Agriculture, Arts, Business, Humanities & Social Sciences, and Natural Resources)
John S. Maulbetsch, PhD (Maulbetsch Consulting, Menlo Park, California)
- JOHNS. MAULBETSCH Maulbetsch Consulting 770 Menlo Avenue, Suite 211 Menlo Park, California 94025 Tel.: 650.327.7040 FAX: 650.327.7045 E-Mail: maulbets@sbcglobal.net Professional history Maulbetsch Consulting, Menlo Park, California: Consultant to government and industry (1999-present)
Electric Power Research Institute Palo Alto, California, Executive Scientist (1975 - 1999),
Dynatech RID Company, Cambridge, Massachusetts, Director, Energy Technology (1969-1975)
Massachusetts Institute of Technology, Cambridge, Massachusetts, Assistant Professor of Mechanical Engineering and Ford Post-Doctoral Fellow (1965 -1969),
Recent projects (Maulbetsch Consulting)
Evaluation of water-conserving cooling system options for Arizona Public Service .... nuclear plant Arizona Public Service----gas-fired, combined-cycle plant Public Service New Mexico----coal plant Cost/performance estimating tool for wet/dry/hybrid cooling (EPRl)
Analysis of performance limitations ofan ACC at a coal-fired power plant (PacifiCorp)
Life cycle analysis of the cost and value of water at gas-fired combined-cycle plants (CEC)
Field testing of wind effects on ACCs (CEC)
Spray enhancement of ACC performance (CEC)
Analysis of the comparative costs of wet vs. dry cooling (CBC; EPRl)
National cost of closed-cycle cooling retrofits (EPRl)
Plant specific cost/performance estimates of cooling system retrofits (several) (EPRl)
Recent research reports Performance, Cost and Environmental Effects of Saltwater Cooling Towers; CEC-500-2008-043 Cost and Value of Water Use at Combined-cycle Power Plants; CEC-500-2006-034 Spray Cooling Enhancement of Air-Cooled Condensers; P500-03-109 Comparison of Alternate Cooling Technologies for California Power Plants; P500-02-079F Inlet Air Spray Cooling for Air-Cooled Condensers; CEC-500-2013-058 Effect of Wind on the Performance of Air-Cooled Condensers; CEC-500-2013-065 Economic Evaluation of Alternative Cooling Technologies; EPRI #1024805 Publications/Invited presentations:
"Effect of Wind on Air-Cooled Condenser Performance", ASME Paper No. IMECE201 l-63137 (2011);
with M. Difilippo and J. O'Hagan "Cost/Performance Comparisons of Water-Conserving Power Plant Cooling Systems", ASME Paper No.
IMECE2011-63135, (2011)
"Cost and Performance Consequences of Closed-cycle Retrofit", Proceedings of EPRl Third Thermal Ecology Workshop, Maple Grove, MN (2011); with M. Difilippo "Wind Effects on Air-Cooled Condensers for Power Plant Cooling", Proceedings of the International Heat Transfer Conference (IHTC14), (2010); with M. Difilippo, M. Owen and D. Kroger
- "Cost of Closed-Cycle Cooling Retrofits", EPRI Environment Council, San Diego, CA, 2009 "Advanced Cooling Technologies", International Congress on Advances in Nuclear Power Plants (ICAPP),
Anaheim, CA, (2008)
"The Effects of Wind on the Performance of Air-cooled Condensers", CTI Journal, Vol. 28, No. 2, Summer, 2007 "Thermal Ecology Issues/Technology Responses", Proceedings ofEPRI Second Thermal Ecology Workshop, Westminster, CO, October, 2007 "Effects of Wind on ACC Performance", EPRI Cooling Tower Conference, Des Moines, IA, August, 2006 "EPRl's Dry Cooling Guidelines", EPRI Cooling Tower Conference, Des Moines, IA, August, 2006 "Application of Spray Enhancement to Crockett Air-cooled Condenser", California Energy Commission Workshop; June,2005 "Cost/Performance Comparisons of Alternative Cooling Systems", California Energy Commission Workshop; June, 2005 "Spray Cooling-An Approach to Performance Enhancement of Air-Cooled Condensers", California Energy Commission Workshop; June, 2005 "Water Conservation Options for Wet-Cooled Power Plants", California Energy Commission Workshop; June, 2005 Book Chapters "Cooling Towers and Cooling Ponds", Chapter 10, Volume 2, in Handbook of Heat Transfer: Applications, Edited by W. M. Rohsenow, J.P. Hartnett, and E.N. Ganie, McGraw-Hill, 1985. (w. J.A. Bartz)
"Environmental Control in Coal-Fired Power Plants," Chapter 22, pp. 940-997 of Handbook of Energy Technology and Economics, Edited by Robert A Meyers, Wiley-Interscience Series, John Wiley & Sons, 1983. (with S. Dalton, et al.)
Selected Invited Presentations (since 2000)
American Nuclear Society, International Congress on Advances in Nuclear Power Plants (2008)
Cambridge Energy Research Associates, CERAWeek '08, Water and Energy Panel (2008)
California SWRCB Workshop, "Environmental Effects of Once-Through Cooling (2008)
EUCI Workshop, "A Water-Constrained Future for Power Producers" (2007)
US DOE Workshop, Energy-Water Nexus, "Power Plant Cooling System Options", Salt Lake City, UT (2006)
California State Water Resources Control Board, Once-Through Cooling Workshop, Oakland, CA (2005)
PowerGen Short Course on Dry Cooling,, Section on "Spray Enhancement of ACC's", Orlando, FL, (2002)
IAHR 12 th International Conference, Sydney, Australia, Advanced Dry Cooling (2001)
- Professional Activities ASME International, Member since 1965, Life Fellow---2004 American Association for the Advancement of Science, Council Delegate, Engineering Section, 1997-2000 Advisory Boards Corporate Advisory Board, Combustion Research Facility, Sandia National Laboratory, Livermore, California Council for Energy Engineering Research, Advisory Committee to U.S. Department of Energy, Basic Energy Sciences, Energy Engineering Research Program Education S.B. (1960) Massachusetts Institute of Technology S.M. (1962) Cambridge, Massachusetts Ph.D. (1965)
Joseph S. Raulli, PE (SME/Technical Manager, O'Brien and Gere)
JOSEPH S. RAULLI, PE
- Joseph S. Raulli, PE SME/Technical Manager Mr. Raulli has more than 38 years of professional experience in the power and central utility industries.
He has extensive experience associated with fossil and hydropower generating facilities and central utility plants, including providing study and engineering Prefect engineeri~g ~nd manageme~t
~.~n*. ' - * *' ..
- design services for modifications and additions to for improved efficiency, reliability, enhanced safety, and environmental compliance.
',;,"fossii,fll~I 'ahd 6vclmpbwerg~ne~~ti6ri<'
,*',, ' -* -*,,;_, ,; <: ' ,c' ' '
Central' Utility Plant/' ., As a Technical Manager with O'Brien & Gere, he provides for the technical delivery of solutions for
- 1Cpoling Water l,ntake,s clients. He is responsible for managing projects
<; E:n~irdni)1en\al .compHan~e wherein he is accountable for scope and budget, staff administration and development, and client management. He is also responsible for financial Wjth O'Brien & Gere: 6 , management, resource allocation, and risk management. Mr. Raulli maintains a close relationship With ci~ediims: ~2 with clients during the study, design, and construction phases of a project, and following project completion.
EQtJCATl,bN
'MBA/1987 . '*"
/Chapm,fn
. '. ~
Colleg~
REPRESENTATIVE PROJECTS
's~/1980/Mec,~~nical Engine~ring; Rochesief Beaver Falls LLC, Beaver Falls, NY - Provided Institute;, of Technology
- engineering review and evaluation for the preparation of a Desktop Entrainment Reduction PROFESSI.ONAL.
REGISTRATION.,, '. Study to address ongoing New York State Department of Environmental Conservation (NYSDEC) concerns Prgfesslonal Engirieer:'.Nv regarding the potential for entrainment of resident fish eggs and larvae at the Beaver Falls Co generation Plant cooling water intake structure (CWIS).
ARCADIS, 316(b) Peer Review, Chemical Process Facility, Tennessee - Completed peer reviews for both the 122.21(r)(10), Comprehensive Technical Feasibility and Cost Evaluation Study and the 122.21(r)(12), Non-Water Quality Environmental and Other Impacts Study, that was prepared for a chemical processing facility with multiple cooling water intakes for once through cooling. The facility was located in Tennessee.
Veritas Economic Consulting, 316(b) Peer Review, Power Generating Stations, Michigan - Completed peer reviews for both the 122.21(r)(10),
Comprehensive Technical Feasibility and Cost Evaluation Study and the 122.21(r)(12), Non-Water Quality Environmental and Other Impacts Study, that
- was prepared for one coal fired electric power generating station with once through cooling located in Michigan.
ARCADIS, 316(b) Peer Review, Power Generating Stations, Michigan - Completed peer reviews for recommended compliance strategy for the client's facility.
LimnoTech, Ann Arbor, Ml - Completed a peer review of the 40 CFR 122.2l(r)(12), Non-Water Quality Environmental and Other Impacts Studies that both the 122.Zl(r)(lO), Comprehensive Technical were prepared for American Electric Power's (AEP)
Feasibility and Cost Evaluation Study and the DC Cook Nuclear Generating Station.
122.21(r)(12), Non-Water Quality Environmental and Other Impacts Study, that were prepared for two Honeywell, 316(b) Strategy Evaluation, Hopewell, electric power generating stations with once through Virginia - Provided the technical evaluation of cooling located in Michigan. potential intake technologies for compliance with current 316(b) regulations. Technology options were Beaver Falls LLC, Beaver Falls, NY - Prepare evaluated and compared based on feasibility, cost, responses to the New York State Department of operational experience, and effectiveness in reducing Environmental Conservation (NYSDEC) Request for impingement mortality and entrainment. Provided a Information (RFI) as required in preparation for final report detailing the evaluation and Beaver Falls' State Pollutant Discharge Elimination recommendations.
System (SPDES) permit renewal. Provided the technical expertise to collect, develop, and report RED-Rochester LLC, Evaluation of Intake information and data that was responsive to the Compliance Options, Rochester, New York -
information request and would assist the NYSDEC to provided a feasibility review and cost estimate for the determine Best Technology Available (BTA) for the installation of cylindrical wedgewire screens at an Beaver Falls Facility cooling water intake structure existing off-shore intake, in addition to the evaluation (CWIS). A response to the information request of other potential compliance options. Project included plant and intake operating data, a deliverable included a letter report summarizing the description of implemented technologies and results of the feasibility review and a discussion of operational measures for 316(b) compliance, and a other potential compliance options.
feasibility analysis with estimated efficacies and costs for alternate intake technologies and operational measures. PRIOR TO O'BRIEN & GERE NRG Energy, Installation and Testing of Fine Mesh PeroxyChem, Tonawanda, NY - Prepare a Screens, Staten Island, NY, Principal Engineer -
conceptual design and cost estimate for a new cooling Served as Principal Engineer and Project Manager for water intake and pump house to provide once the installation and testing of new dual flow fine mesh through cooling to a chemical manufacturing facility intake screens. Project included the use of CFD with a cooling water demand of 15 MGD. The new Modeling to determine the maximum velocities and intake design consisted of three submerged the flow patterns around the screens and lab testing cylindrical wedge-wire screens with an air-burst to determine the impact of mesh size and velocity on system, a shoreline wet-well, and pump house with entrainment reduction effectiveness. In addition, three vertical pumps. A slot opening of 0.86 mm was design services were provided for the modifications proposed in the design for 316(b) compliance.
to the screen well, spray wash system and electrical power supply for the installation of the new screens.
Newport News Shipbuilding, Newport News, VA-Provided client with technical assistance to determine FPL Seabrook, USEPA 316(b) Information the specific applicability requirements and to develop Request, Seabrook, New Hampshire, Principal a long-term strategy for compliance with Section Engineer - Directed the effort to prepare a Cooling 316(b) of the Clean Water Act (CWA). This included Water Intake Structure (CWIS) Information Document an assessment of the current intake equipment in response to a supplemental information request relative to the requirements of Section 316(b) and a from the USEPA for the Seabrook Nuclear Power conceptual overview of potential options to bring the Station. This information was requested as a part of facility into compliance with the impingement and the station's NPDES permit reissuance and necessary entrainment requirements of Section 316(b). A final for determination of the station's compliance with the report was developed which provided a requirements of CWA §316(b) for cooling water
- intakes. Information requirements included source water body characterization, description of the design and operation of the cooling water system, engineering evaluation of potential technologies and operational measures for reducing impingement mortality and entrainment, and fisheries data Flow Information, Impingement Mortality and/or Entrainment Characterization Study, and the Design and Construction Technology Plan (DCTP). The DCTP included plant operational data, calculated through-screen velocities, the description and evaluation of potential technologies and/or operational measures collected during entrainment and impingement for the reduction of impingement mortality, and sampling. calculations of the projected reduction in impingement mortality.
Exelon, 316(b) Technology Evaluations, Pennsylvania/ Texas, Principal Engineer - Consumers Energy, Campbell 316(b)
Completed Cooling Water Intake Technology Comprehensive Demonstration Study, Grand Evaluations for four fossil generating stations in Haven, Michigan - Work included the preparation of Pennsylvania and two fossil plants in Texas. The the CDS for the fossil generating station which has evaluation of each technology included a discussion cooling water intakes on Lake Michigan and Pigeon on the conceptual design, construction feasibility, Lake. The CDS included the Source Water Physical operation and maintenance requirements, permitting Data, Cooling Water Intake Structure Data, Cooling requirements, and impingement mortality and Water System Data and the Impingement mortality entrainment reduction effectiveness. The technology and Entrainment Characterization Study. In addition evaluation was followed by the development of the to the reports included as a part of each CDS, the Design and Construction Technology Plan (DCTP) for scope of work for each plant included the completion each of the Pennsylvania stations. Each DCTP of an evaluation of alternative intake technologies and included plant operational data, description of operational measures for the reduction of existing intake technology, the description and impingement mortality and entrainment. Each intake evaluation of potential technologies and/or technology evaluation included the development of operational measures for the reduction of cost opinions for capital and O&M costs for each impingement mortality, and calculations of the technology, estimates of effectiveness in reducing projected reduction in impingement mortality. impingement mortality and entrainment, and preliminary estimates of economic benefits.
Consumers Energy, Karn-Weadock 316(b)
Comprehensive Demonstration Study, Jackson, FPL Seabrook, 316(b) Proposal for Information Michigan - Served as Project Manager for the Collection, Seabrook, New Hampshire - Provided preparation of the CDSs for the two fossil generating engineering and technical support for the completion stations which have intakes on Saginaw Bay and of the Proposal for Information Collection (PIC).
Saginaw River. Each CDS included the Source Water Responsibilities included the evaluation of baseline Physical Data, Cooling Water Intake Structure Data, credits associated with the off-shore intake, screening Cooling Water System Data and the Impingement evaluation for other potential compliance mortality and Entrainment Characterization Study. In technologies and operational measures, preparation addition to the reports included as a part of each CDS, of the CWIS data and cooling water system data, and the scope of work for each plant included the preparation of the technical sections of the PIC.
completion of an evaluation of alternative intake technologies and operational measures for the Orion Power, Installation of Dual-Flow Traveling reduction of impingement mortality and entrainment. Water Intake Screens, Astoria, New York- Project Each intake technology evaluation included the engineer for the installation of the intake screens development of cost opinions for capital and O&M employing marine life recovery process technology costs for each technology, estimates of effectiveness and a fish return system as required for the restart of in reducing impingement mortality and entrainment, Unit 2 at the Astoria Generating Station.
and preliminary estimates of economic benefits.
Niagara Mohawk Power Corp., Procurement and PPL, Brunner Island 316(b) BTA Evaluation, Installation of Dual-Flow Fish Handling Intake Allentown, Pennsylvania - Project Manager and lead Screens, Dunkirk, New York - Mechanical Engineer engineer for the completion of an evaluation of Best for the team responsible for the procurement and Technology Available (BTA) for the Brunner Island installation of new dual-flow fish handling intake intake structures. The BTA Evaluation document was screens at Dunkirk Steam Station, including the required by the PADEP to include Source Waterbody design of the spray wash water system and the fish
- transport system, including a fish return pump, for the return of the fish to an acceptable location approximately 1,200 feet offshore.
Niagara Mohawk Power Corp., Procurement and Installation of Dual-Flow Fish Handling Intake Screens, Tonawanda, New York- Mechanical Engineer for the team responsible for the procurement and installation of new dual-flow fish handling intake screens, including the design of the spray wash water system and the shoreline fish return system at Huntley Steam Station .
Dr. James A. Rice (Professor Emeritus, North Carolina State University- Department of Applied Ecology)
CURRICULUM VITAE
- James A. Rice Professor Emeritus Department of Applied Ecology North Carolina State Telephone: 919-515-4592 FAX:919-515-5327 E-mail: jrice@ncsu.edu University Raleigh, NC 27695-7617 Education:
B.A. 1978, Biology (Summa Cum Laude), St. Louis University, St. Louis, MO.
M.S. 1981, Zoology, University of Wisconsin, Madison, WI.
Ph.D. 1985, Zoology, University of Wisconsin, Madison, WI.
Employment:
1978 - 1985 Research and Teaching Assistant, Center for Limnology and Department of Zoology, University of Wisconsin-Madison.
1985 Research Associate, Center for Limnology, University of Wisconsin- Madison.
1985 - 1991 Assistant Professor of Zoology and Extension Fisheries Specialist, North Carolina State University.
1986 - 2019 Fisheries, Wildlife and Conservation Biology Faculty, North Carolina State University.
1989 - 1990, 2001 Acting Zoology Department Extension Leader.
1991 - 1998 Associate Professor of Zoology and Extension Fisheries Specialist, North Carolina State University.
1998 - 2019 Professor of Applied Ecology (formerly Zoology, Biology) and Extension Fisheries Specialist, North Carolina State University.
2001 - 2005 Zoology Director of Graduate Programs.
Professional Memberships:
American Fisheries Society AFS Early Life History Section AFS Education Section NC Chapter, American Fisheries Society Ecological Society of America ESA Aquatic Ecology Section Professional Service:
Nomination Committee, AFS, 2016-present Nomination Committee, Southern Division of AFS, 2016-present.
Northern Regional Advisory Committee to the NC Marine Fisheries Comm., 2012-present.
Striped Bass Committee, Southern Division of AFS, 2005-present.
Small Impoundments Committee, Southern Division of AFS, 2002-2016.
Faculty advisor for NCSU student subunit of AFS, 1996-present.
Lake Norman Advisory Committee for the NC Wildlife Resources Comm., 2005-2013.
Education and Outreach Committee, NC Chapter of AFS, 2005-2010.
Awards Committee Chair, NC Chapter of AFS, 2001-2005 .
- Inland Regional Advisory Committee to the NC Marine Fisheries Comm., 2000-2012.
Fisheries Resources Grant review panel (UNC Sea Grant), 2000-2004.
National Trout Unlimited Embrace-A-Stream review panel, 2000-2003.
Finance Committee, NC Chapter of AFS, 2000-2002.
Nominating Committee, NC Chapter of AFS, 1995-1996, 2000-2001, 2013, 2015.
Education Committee, NC Chapter of AFS, 1996-1999.
Environmental Concerns Committee, NC Chapter of AFS, 1991-1995.
Publications Overvie~ Committee, American Fisheries Society, 1991-1992.
President, North Carolina Chapter, American Fisheries Society, 1990-1991.
President, North Carolina Fisheries Workers Association, 1990-1991.
American Fisheries Society Campus Network Representative, 1989-1996.
Board of Directors, North Carolina Wildlife Federation, 1988-1993.
Associate Editor, North American Journal of Fisheries Management, 1989-1991.
- Ballot Committee, Southern Division of the American Fisheries Society, 1988.
Program Committee, 1986 Annual Meeting of the American Fisheries Society.
Awards
- 2015 Best Student Paper Award (coauthor), NC Chapter, American Fisheries Society.
- 2008 Service Award, NC State Student Fisheries Society
- 2006 Richard L. Noble Best Student Paper Award (coauthor), NC Chapter, American Fisheries Society.
- 2006 Distinguished Service Award, NC Chapter, American Fisheries Society
- 2005 Best Paper Award (coauthor), 8th Annual NC State University Zoology and Botany Graduate Student Symposium.
- 2003 Honorable Mention, Best Student Paper Award (coauthor), American Fisheries Society Southern Division Meeting.
- 2001 Inducted into Triangle Fly Fishers Trout Unlimited Chapter Hall of Fame.
- 2001 W. Don Baker Memorial Award for Best Paper Overall (coauthor), NC Chapter, American Fisheries Society.
- 2001 Best Student Paper Award (coauthor), NC Chapter, American Fisheries Society.
- Finalist in Most Significant Paper competition (coauthor) in the Transactions of the American Fisheries Society, Vol. 126 (1997).
- 1998 Best Student Paper Award (coauthor), Tidewater Chapter, American Fisheries Society.
- 1995 George and Rhoda Kris Study Leave Award, NC State University.
- Co-author, Science Citation Classic (Miller et al. 1988, CJFAS 45:1657-1670). J
- Honorable Mention, Best Student Paper Award Competition (coauthor), 1991 American, Fisheries Society Meeting.
- 1990 Best Paper Award (coauthor), American Fisheries Society Southern Division.
- Most Significant Paper in the Transactions of the American Fisheries Society, Vol. 116 (1987).
- Honorable Mention, Best Student Paper competition, 1984 American Fisheries Society Meeting.
- Best Student Paper Award, 1982 American Fisheries Society Meeting .
- Research Interests:
Biological and anthropogenic impacts on survival, growth and distribution of fishes, including: Predator-prey interactions and food web dynamics in aquatic systems; direct and indirect fish responses to hypoxia; bioenergetics modeling of predation and habitat effects; impacts and management of introduced species; factors driving variation in fish tissue mercury concentration, and intersex condition in fishes.
Current and Pending Grants and Contracts:
Aquatic Species Restoration and Research at the Eastern Aquatic Conservation Facility at Yates Mill (NC). W.G. Cope, J.F. Levine, C.B. Eads, T.J. Kwak, J.A. Rice, J.M. Burkholder and R.J. Richardson, Pis. National Fish and Wildlife Foundation - North Carolina and Virginia River and Waters Program. 2016-2020. $1,120,000.
Refereed Research Publications (* indicates student author):
Campbell*, L.A, J.A. Rice, and R.J. Borski. 2018. Magnitude and timing of changes in bioindicators ofrecent growth in relation to changes in growth rate for juvenile spot Leiostomus xanthurus. Journal of Fish Biology. In Revision.
- 86. Bradley*, C.E. J.A. Rice, and D.D. Aday. 2018. Modeling the Effects of Vital Rate Manipulation and Management Scenarios to Predict Population Impact of Restoration Programs on an Unrecovered Coastal Population of Striped Bass. North American Journal of Fisheries Management 38:639-649. DOI: 10.1002/nafm. l 0062 .
- 85. Grieshaber*, C.A., T.N. Penland, T.J. Kwak, W. G. Cope, R.J. Heise, J.M. Law, D. Shea, D.D. Aday, J.A. Rice, S.W. Kullman. 2018. Relation offish intersex to contaminants in riverine sport fishes. Science of the Total Environment 643:73-89. DOI:
10.1016/j.scitotenv.2018.06.071.
- 84. Bradley*, C.E., J.A. Rice, D.D. Aday, J.E. Hightower, J. Rock, and K.J. Lincoln. 2018.
Juvenile and adult Striped Bass mortality and distribution in an unrecovered coastal population. North American Journal of Fisheries Management 38:104-119. DOI:
10.1002/nafin.10036.
- 83. Henson*, M.N., D.D. Aday, J.A. Rice, and C.A. Layman. 2018. Assessing the influence of Tilapia on sport species in North Carolina reservoirs. Transactions of the American Fisheries Society 147:350-362. DOI: 10.1002/tafs.10031.
- 82. Henson*, M.N., J.A. Rice, and D.D. Aday. 2018. Thermal tolerance and survival ofNile Tilapia Oreochromis niloticus and Blue Tilapia Oreochromis aureus under rapid and natural temperature declination rates. Transactions of the American Fisheries Society 147:278-286. DOI: 10.1002/tafs.10023.
- 81. Campbell, L.A. and J.A. Rice. 2017. Development and field application of a model predicting effects of episodic hypoxia on short-term growth of Spot Leiostomus xanthurus .
- Marine and Coastal Fisheries Dynamics, Management, and Ecosystem Science 9:504-520. DOI: 10.1080/19425120.2017.1362492.
- 80. Deslauriers, D., S.R. Chipps, J.E. Breck, J.A. Rice, and C.P. Madenjian. 2017. Fish Bioenergetics 4.0: An R-based modeling application. Fisheries 42:11, 586-596. DOI:
10.1080/03632415.2017.1377558.
- 79. Lee Pow*, C.S.D., K. Tilahun, K. Creech, J.M. Law, W.G. Cope, T.J. Kwak, J.A. Rice, D.D. Aday, and S. Kullman. 2017. Windows of Susceptibility and Consequences of Early Life Exposures to 17j)----estradiol on medaka ( Oryzias latipes) Reproductive Success.
Environmental Science & Technology. 51:5296-5305. DOI: 10.1021/acs.est.7b01568.
- 78. Owensby*, D.P., J.A. Rice, and D.D. Aday. 2017. Mortality, Dispersal, and Habitat Use of Stocked Juvenile Muskellunge Esox masquinongy in Two Western North Carolina Rivers.
North American Journal of Fisheries Management. North American Journal of Fisheries Management 37(1):108-121. DOI: 10.1080/02755947.2016.1245222.
- 77. Lee Pow*, C., M. Law, T. Kwak, W.G. Cope, J.A. Rice, S. Kullman, and D.D. Aday. 2017.
Endocrine Active Contaminants in Aquatic Systems and Intersex in Common Sport Fishes. Environmental Toxicology and Chemistry 36(4):959-968. DOI:
I 0.1002/etc.3607.
- 76. Lincoln*, K.J., D.D. Aday, and J.A. Rice. 2016. Potential Mechanisms Underlying a Perceived White Bass Marone chrysops Decline in a Southeastern Reservoir. Transactions of the American Fisheries Society 145:1035-1046. DOI:
I0.1080/00028487.2016.l 195444.
- 75. Brown*, D.T., D.D. Aday, and J.A. Rice. 2015. Responses of coastal Largemouth Bass Micropterus salmoides to episodic hypoxia. Transactions of the American Fisheries Society 144:65 5-666. DOI: 10.1080/00028487.2015 .1024801.
- 74. Brown*, D.T., J.A. Rice, C.D. Suski, and D.D. Aday. 2015. Dispersal patterns of coastal Largemouth Bass in response to tournament displacement. North American Journal of Fisheries Management 35:431-439. DOI: 10.1080/02755947.2015.1009660.
- 73. Sackett, D.K., C. Lee Pow*, M.J. Rubino, D.D. Aday, W.G. Cope, S. Kullman, J.A. Rice, T.J. Kwak, and M. Law. 2015. Sources of Endocrine Disrupting Compounds in North Carolina Waterways: A Geographic Information Systems Approach. Environmental Toxicology and Chemistry 34(2):437-445. DOI 10.1002/etc.2797.
- 72. Campbell*, L.A. and J.A. Rice. 2014. Effects of hypoxia-induced habitat compression on growth of juvenile fish in the Neuse River Estuary, North Carolina. Marine Ecology Progress Series 497: 199-213. DOI: 10.3354/meps10607 .
- 71. Bethke*, B.J., J.A. Rice, and D.D. Aday. 2014. White Perch in Small North Carolina Reservoirs: What Explains Variation in Population Structure? Transactions of the American Fisheries Society 143:77-84. DOI: 10.1080/00028487.2013.830989.
- 70. Cerino*, D., A.S. Overton, J.A. Rice, and J.A. Morris Jr. 2013. Bioenergetics and Trophic Impacts of the Invasive Indo-Pacific Lionfish. Transactions of the American Fisheries Society 142:1522-1534. DOI: 10.1080/00028487.2013.811098.
- 69. Sackett*, D.K, D.D. Aday, and J.A. Rice and W.G. Cope. 2013. Maternally transferred mercury in wild largemouth bass, Micropterus salmoides. Environmental Pollution 178:493-497. DOI: 10.1016/j.envpol.2013.03.046.
- 68. Feiner*, Z.S., J.A. Rice, A.J. Bunch, and D.D. Aday. 2013. Trophic niche and diet overlap between invasive white perch and resident white bass in a southeastern reservoir.
Transactions of the American Fisheries Society 142:912-919. DOI:
10.1080/00028487.2013.788563.
- 67. Rice, J. A., J. S. Thompson, J. A. Sykes, and C. T. Waters. 2013. The role of metalimnetic hypoxia in striped bass summer kills: consequences and management implications. Pages 121-145 in J. S. Bulak, C. C. Coutant, and J. A. Rice, editors. Biology and management of inland striped bass and hybrid striped bass. American Fisheries Society, Symposium 80, Bethesda, Maryland .
- 66. Feiner*, Z.S., J.A. Rice, and D.D. Aday. 2013. Trophic niche of invasive white perch and potential interactions with established reservoir species. Transactions of the American Fisheries Society 142:628-641. DOI: 10.1080/00028487.2013.763854.
- 65. Thompson, J.S. andJ.A. Rice. 2013. The relative influence of temperature and forage availability on growth of age 1-5 striped bass in two southeastern reservoirs. Pages93-120 in J. S. Bulak, C. C. Coutant, and J. A. Rice, editors. Biology and management of inland striped bass and hybrid striped bass. American Fisheries Society, Symposium 80, Bethesda, Maryland.
- 64. Sackett*, D.K, W.G. Cope, J.A. Rice, and D.D. Aday. 2013. The influence offish length on tissue mercury dynamics: implications for natural resource management and human health risk. International Journal of Environmental Research and Public Health 10: 638-659.
DOI: 10.3390/ijerph10020638.
- 63. Sackett*, D.K, D.D. Aday, J.A. Rice, and W.G. Cope. 2013. Validation of a predictive model for fish tissue mercury concentrations. Transactions of the American Fisheries Society 142:380-387. DOI: 10.1080/00028487.2012. 747990.
- 62. Feiner*, Z.S., D.D. Aday, and J.A. Rice. 2012. Phenotypic shifts in white perch life history strategy across stages of invasion. Biological Invasions 14(11): 2315-2329. DOI 10.1007/s10530-012-023 l-z .
- 61. Morris*, J.A. Jr., K.W. Shertzer, and J.A. Rice. 2011. A stage-based matrix population model of invasive lionfish with implications for control. Aquatic Invasions. 13:7-12.
(Published online June 2010).
- 60. Sackett*, D.K, D.D. Aday, J.A. Rice, W.G. Cope, and D. Buckwalter. 2010. Does proximity to coal-fired power plants influence fish tissue mercury? Ecotoxicology. 19:1601-1611.
- 59. Thompson*, J.S., J.A. Rice, and D.S. Waters. 2010. Striped bass habitat selection rules in reservoirs without suitable summer habitat offer insight into consequences for growth.
Transactions of the American Fisheries Society. 139:1450-1464.
- 58. Godbout*, J.D., D.D. Aday, J.A. Rice, M.R. Bangs, and J.M. Quattro. 2009. Morphological models for identifying largemouth, spotted and hybrid largemouth-spotted bass. North American Journal of Fisheries Management. 29:1425-1437.
- 57. Sackett*, D.K, D.D. Aday, J.A. Rice, and W.G. Cope. 2009. A statewide assessment of mercury dynamics in North Carolina waterbodies and fish. Transactions of the American Fisheries Society. 138:1328-1341.
- 56. Breitburg, D. L., J.K. Craig, R.S. Fulford, KA. Rose, W.R. Boynton, D. Brady, B.J. Ciotti, R.J. Diaz, K.D. Friedland, J.D. Hagy III, D.R. Hart, A.H. Hines, E.D. Houde, S.E.
Kolesar, S.W. Nixon, J.A. Rice, D.H. Secor, and T.E. Targett. 2009. Nutrient Enrichment and Fisheries Exploitation: Interactive Effects on Estuarine Living Resources
- and Their Management. Hydrobiologia. 629:31-47.
- 55. Cope, W.G., R.B. Bringolf, S. Mosher, J.A. Rice, R.L. Noble, and H.C. Edwards. 2008.
Controlling nitrogen release from farm ponds with a subsurface outflow device:
implications for improved water quality in receiving streams. Agricultural Water Management. 95:737-742.
- 54. Craig, J.K., J.A. Rice, L.B. Crowder, and D.A. Nadeau. 2007. Density-dependent growth and survival in an estuary-dependent fish: an experimental approach with juvenile spot Leiostomus xanthurus. Marine Ecology Progress Series. 343 :251-262.
- 53. Thompson*, J.S., D.S. Waters, J.A. Rice, and J.E. Hightower. 2007. Seasonal fishing and natural mortality of striped bass in a southeastern reservoir. North American Journal of Fisheries Management. 27:681-694.
- 52. Pine*, W.E., T.J. Kwak, and J.A. Rice. 2007. Modeling management scenarios and the effects of an introduced apex predator on a coastal riverine fish community. Transactions of the American Fisheries Society. 136:105-120.
- 51. Bestgen, K.R., D.W. Beyers, J.A. Rice, and G.B. Haines. 2006. Factors affecting recruitment of young Colorado pikeminnow: synthesis of predation experiments, field studies and individual-based modeling. Transactions of the American Fisheries Society. 135:1722-1742 .
- 50. Fulford*, R.S., J.A. Rice, and F.P. Binkowski. 2006. Examination of sampling bias for larval yellow perch in southern Lake Michigan. Journal of Great Lakes Research. 32:434-441.
- 49. Craig, J.K., B.J. Burke, L.B. Crowder, and J.A. Rice. 2006. Prey growth and size-dependent predation in juvenile estuarine fishes: experimental and modeling analyses. Ecology.
87(9): 2366-2377.
- 48. Fulford*, R.S., J.A. Rice, T.J. Miller, and F.P. Binkowski. 2006. Elucidating patterns of size-dependent predation on larval yellow perch (Percaflavescens) in Lake Michigan: an experimental and modeling approach. Canadian Journal of Fisheries and Aquatic Sciences. 63(1): 11-27.
- 47. Fulford*, R.S., J.A. Rice, T.J. Miller, F.P. Binkowski, J.M. Dettmers, and B. Belonger. 2006.
Foraging selectivity by larval yellow perch (Percaflavescens): implications for understanding recruitment in small and large lakes. Canadian Journal of Fisheries and Aquatic Sciences. 63(1): 28-42.
- 46. Shimps*, E.L., J.A. Rice, and J.A. Osborne. 2005. Hypoxia tolerance in two juvenile estuary-dependent fishes. Journal of Experimental Marine Biology and Ecology.
325(2): 146-162.
- 45. Pine*, W.E. III, T.J. Kwak, D.S. Waters, and J.A. Rice. 2005. Diet Selectivity oflntroduced Flathead Catfish in Coastal Rivers. Transactions of the American Fisheries Society.
134(4):901-909.
- 44. McNatt*, R.A., and J.A. Rice. 2004. Hypoxia induced growth rate reduction in two juvenile estuary dependent fishes. Journal of Experimental Marine Biology and Ecology.
311(1):147-156.
- 43. Pine*, W.E., K.H. Pollock, J.E. Hightower, T.J. Kwak, and J.A. Rice. 2003. A review of tagging methods for estimating fish population size and components of mortality.
Fisheries 28:10-23.
- 42. Rice, J.A. 2002. Cascading effects of human impacts on fish populations in the Laurentian Great Lakes. pp. 257-272, In L.A. Fuiman and R.G. Werner, eds., Fishery Science: The Unique Contributions of Early Life Stages. Blackwell Science Ltd., Oxford, UK.
- 41. Beyers, D.W., and J.A. Rice. 2002. Evaluating stress in fish using bioenergetics-based stressor-response models. Pages 289-320 In S.M. Adams (ed.). Biological Indicators of Aquatic Ecosystem Stress. American Fisheries Society, Bethesda, MD.
- 40. Burke*, B.J., and J.A. Rice. 2002. A linked foraging and bioenergetics model for southern flounder. Transactions of the American Fisheries Society 131:120-131.
- 39. Heyer*, C.J., T.J. Miller, F.P. Binkowski, E.M. Caldarone, and J.A. Rice. 2001. Maternal effects as a recruitment mechanism in Lake Michigan yellow perch (Percaflavescens).
Canadian Journal of Fisheries and Aquatic Sciences 58:1477-1487.
- 38. Wannamaker*, C.M., and J.A. Rice. 2000. Effects of hypoxia on movements and behavior of selected estuarine organisms from the southeastern United States. Journal of Experimental Marine Biology and Ecology 249 (2):145-163.
- 37. Ahrenholz, D.W., D.D. Squires J.A. Rice, S.W. Nixon, and G.R. Fitzhugh. 2000. Periodicity of increment formation in otoliths of over-wintering post-larval and pre-juvenile Atlantic menhaden (Brevoortia tyrannus). Fishery Bulletin 98:421-426.
- 36. Rice, J.A., J.A. Quinlan*, S.W. Nixon, W.F. Hettler, S.M. Warlen, and P.M. Stegmann.
1999. Spawning and transport dynamics of Atlantic menhaden: inferences from characteristics of immigrating larvae and predictions of a hydrodynamic model. Fisheries Oceanography 8 (Suppl. 2): 93-110.
- 35. Beyers, D.W., J.A. Rice, W.H. Clements, and C.J. Henry. 1999. Estimating physiological cost of chemical exposure: integrating energetics and stress to quantify toxic effects in fish. Canadian Journal of Fisheries and Aquatic Sciences 56(5):814-822.
- 34. Beyers, D.W., J.A. Rice, and W.H. Clements. 1999. Evaluating biological significance of chemical exposure to fish using a bioenergetics-based stressor-response model. Canadian Journal of Fisheries and Aquatic Sciences 56(5):823-829 .
- 33. Neal*, J.W., J.A. Rice, and R.L. Noble. 1999. Evaluation of two sizes of hybrid striped bass for introduction into small ponds. North American Journal of Aquaculture 61 :74-78.
- 32. Neal*, J.W., R.L. Noble, and J.A. Rice. 1999. Fish community response to hybrid striped bass introduction in small warmwater impoundments. North American Journal of Fisheries Management 19: 1044-1053.
- 31. Rice, J.A., L.B. Crowder, and E.A. Marschall. 1997. Predation on juvenile fishes: dynamic interactions between size-structured predators and prey. p. 333-356 Jn R.C. Chambers and E.A. Trippel (eds), Early Life History and Recruitment in Fish Populations. Chapman and Hall, London.
- 30. Crowder, L.B., D.D. Squires, and J.A. Rice. 1997. Non-additive effects of terrestrial and aquatic predators on juvenile estuarine fish. Ecology 78: 1796-1804.
- 29. Fitzhugh, G.R., S.W. Nixon, D.W. Ahrenholz, and J.A. Rice. 1997. Temperature effects on otolith microstructure and birthmonth estimation from otolith increment patterns in Atlantic menhaden. Trans. Am. Fish. Soc. 126:579-593.
- 28. Letcher*, B.H., and J.A. Rice. 1997. Prey patchiness and larval fish growth and survival:
inferences from an individual-based model. Ecological Modeling 95:29-43 .
- 27. Letcher*, B.H., J.A. Rice, L.B. Crowder, and F.P. Binkowski. 1997. Size- and species-dependent variability in consumption and growth rates of larvae and juveniles of three freshwater fishes. Can. J. Fish. Aquat. Sci. 54:405-414.
- 26. Letcher*, B.H., J.A. Rice, and L.B. Crowder. 1996. Size-dependent effects of continuous and intermittent feeding on starvation time and mass loss in starving yellow perch larvae and juveniles. Transactions of the American Fisheries Society. 125:14-26.
- 25. Letcher*, B.H., J.A. Rice, L.B. Crowder, and KA. Rose. 1996. Variability in survival of larval fish: disentangling components with a generalized individual-based model. Can. J.
Fish. Aquat. Sci. 53:787-801.
- 24. Ahrenholz, D.W., G.R. Fitzhugh, J.A. Rice, S.W. Nixon, and W:C. Pritchard. 1995.
Confidence of otolith ageing through the juvenile stage for Atlantic menhaden (Brevoortia tyrannus). Fishery Bulletin 93:209-216.
- 23. Fitzhugh*, G.R. and J.A. Rice. 1995. Error in back-calculation of lengths of juvenile southern flounder, Paralichthys lethostigma, and implications for analysis of size-selection. p. 227-246 in: D.H. Secor, J.M. Dean, and S.E. Campana (eds.). Recent Developments in Fish Otolith Research. University of South Carolina Press, Columbia, South Carolina.
- 22. Schael*, D.M., J.A. Rice, and D.J. Degan. 1995. Spatial and temporal distribution of thread fin shad in a Southeastern reservoir. Transactions of the American Fisheries Society.
124:804-812.
2L Crowder, L.B., R.A. Wright*, KA. Rose, T.H. Martin*, and J.A. Rice. 1994. Direct and indirect effects of southern flounder predation on a spot population: experimental and model analyses. p. 61-77 In D.J. Stouder, KL. Fresh, and R.J. Feller (eds.) Theory and Application in Fish Feeding Ecology. University of South Carolina Press, Columbia South Carolina.
- 20. Rice, J.A., L.B. Crowder, and KA. Rose. 1993. Interactions between size-structured predator and prey populations: experimental test and model comparison. Trans. Am. Fish.
Soc. 122:481-491. *
- 19. Rice, J.A., T.J. Miller*, KA. Rose, L.B. Crowder, E.A. Marschall*, A. Trebitz, and D.L.
DeAngelis. 1993. Growth rate variation and larval survival: inferences from an individual-based size-dependent predation model. Can. J. Fish. Aquat. Sci. 50:133-142.
- 18. Miller*, T.J., L.B. Crowder, and J.A. Rice. 1993. Ontogenetic changes in behavioral and histological measures of visual acuity in three species offish. Env. Biol. Fish. 37:1-8.
- 17. Crowder, L.B., J.A. Rice, T.J. Miller*, and E.A. Marschall. 1992*. Empirical and theoretical approaches to size-based interactions and recruitment variability in fishes. p. 237-255 In
- D.L. DeAngelis and L.J. Gross (eds.) Individual-Based Approaches in Ecology.
Routledge, Chapman and Hall, New York. 544 pp.
- 16. Miller*, T.J., L.B. Crowder, J.A. Rice, and F.P. Binkowski. 1992. Body size and the ontogeny of the functional response in fishes. Can. J. Fish. Aquat. Sci. 49:809-812.
- 15. Rice, J.A. 1990. Bioenergetics modeling approaches to evaluate consequences of stress in fishes. American Fisheries Society Symposium 8:80-92.
- 14. Jackson*, J.R., J.M. Phillips*, R.L. Noble, and J.A. Rice. 1990. Relationship ofplanktivory by shad and diet shifts by young-of-year largemouth bass in a southern reservoir. Proc.
Annu. Conf. Southeast. Assoc. Fish and Wildl. Agencies. 44:114-125. (1990 AFS Southern Division Best Paper Award)
- 13. Luecke, C., J.A. Rice, L.B. Crowder, and S.E. Yeo. 1990. Recruitment mechanisms of bloater in Lake Michigan: an analysis of the predatory gauntlet. Can. J. Fish. Aquat. Sci.
47:524-532.
- 12. Miller*, T.J., L.B. Crowder, J.A. Rice, and E.A. Marschall*. 1988. Larval size and recruitment mechanisms in fishes: toward a conceptual framework. Can. J. Fish. and Aquat. Sci. 45:1657-1670. (Science Citation Classic)
- 11. Rice, J.A. 1987. Reliability of age and growth rate estimates derived from otolith analysis .
Pages 167-176 In Robert C. Summerfelt (ed.), Age and Growth of Fish. Iowa State University Press, Ames Iowa.
- 10. Rice, J.A., L.B. Crowder, and F .P. Binkowski. 1987. Evaluating potential sources of mortality for larval bloater: starvation vs. predation. Can. J. Fish. Aquat. Sci. 44:467-472.
- 9. Rice, J.A., L.B. Crowder, and M.E. Holey. 1987. Exploration of mechanisms regulating larval survival in Lake Michigan bloater: a recruitment analysis based on characteristics of individual larvae. Trans. Am. Fish. Soc. 116:703-718. (Most Significant Paper Award, 1987)
- 8. Crowder, L.B., M.E. McDonald, and J.A. Rice. 1987. Understanding recruitment of Lake Michigan fishes: the importance of size-based interactions between fish and zooplankton.
Can. J. Fish. Aquat. Sci. 44 (Suppl. 2):141-147.
- 7. Kitchell, J.A., C.H. Boggs, J.A. Rice, J.F. Kitchell, A. Hoffman and J. Martinell. 1986.
Anomalies in naticid predatory behavior: a critique and experimental observations.
Malacologia 27:291-298.
- 6. Rice, J.A., L.B. Crowder and F.P. Binkowski. 1985. Evaluating otolith analysis for bloater Coregonus hoyi: do otoliths ring true? Trans. Am. Fish. Soc. 114:532-539.
- 5. Rice, J.A., and P.A. Cochran. 1984. Independent evaluation of a bioenergetics model for
- largemouth bass. Ecology 65:732-739.
- 4. Boggs, C.H., J.A. Rice, J.A. Kitchell, and J.F. Kitchell. 1984. Predation at a snail's pace:
what's time to a gastropod? Oecologia 62:13-17.
- 3. Rice, J.A., J.E. Breck, S.M. Bartell, and J.F. Kitchell. 1983. Evaluating the constraints of temperature, activity and consumption on growth of largemouth bass. Env. Biol. Fish.
9:263-275.
- 2. Cochran, P.A., and J.A. Rice. 1982. A comparison ofbioenergetics and direct field estimates of cumulative seasonal food consumption by largemouth bass (Micropterus salmoides).
Pages 88-96 In G. Cailliet and C. Simenstad (eds.), Gutshop '81: fish food habits studies.
Washington Sea Grant, Seattle, Washington, USA.
- 1. Kitchell, J.A., C.H. Boggs, J.F. Kitchell, and J.A. Rice. 1981. Prey selection by naticid gastropods: experimental tests and application to the fossil record. Paleobiology 7:533-552.
Books:
Bulak, J.S., C.C. Coutant, and J.A. Rice, editors. 2013. Biology and management of inland striped bass and hybrid striped bass. American Fisheries Society, Symposium 80, Bethesda, Maryland .
- Book Chapters, Reviews and Editorials:
Rice, J.A., J.S. Thompson, J.A. Sykes, and C.T. Waters. 2013. The role ofmetalimnetic hypoxia in striped bass summer kills: consequences and management implications. Pages 121-145 in J. S. Bulak, C. C. Coutant, and J. A. Rice, editors. Biology and management of inland striped bass and hybrid striped bass. American Fisheries Society, Symposium 80, Bethesda, Maryland.
Thompson, J.S. and J.A. Rice. 2013. The relative influence of temperature and forage availability on growth of age 1-5 striped bass in two southeastern reservoirs. Pages93-120 in J. S. Bulak, C. C. Coutant, and J. A. Rice, editors. Biology and management of inland striped bass and hybrid striped bass. American Fisheries Society, Symposium 80, Bethesda, Maryland.
Rice, J.A. 2002. Cascading effects of human impacts on fish populations in the Laurentian Great Lakes. pp. 257-272 In L.A. Fuiman and R.G. Werner, eds. Fishery Science: The Unique Contributions of Early Life Stages. Blackwell Science, Oxford, England.
Rice, J.A. 1999. Coping with Uncertainty. Fisheries 24(7): 44.
Rice, J.A. 1998. Evolution of the Process-Oriented Approach to Recruitment Dynamics in Fishes. Stages 19(2):10-12.
Rice, J.A. 1992. Physiological Ecology and Community Structure (symposium review). Bulletin
- of the Ecological Society of America 73(4):269-270.
Technical Reports:
Lee Pow, C., C. A. Grieshaber, D. D. Aday, S. W. Kullman, W. G. Cope, T. J. Kwak, J. M. Law, and J. A. Rice. A comprehensive examination of endocrine disrupting compounds and intersex fish in North Carolina water bodies. Federal Aid in Sport Fish Restoration Project F-99-R Final Report, Submitted to Division oflnland Fisheries, North Carolina Wildlife Resources Commission, Raleigh.
Lincoln, K.J., D.D. Aday, and J.A. Rice. 2014. Potential Mechanisms Underlying a Perceived White Bass Morone chrysops Decline in a Southeastern Reservoir. Final Report. Federal Aid in Fish Restoration Project F-101. North Carolina State University, Raleigh, NC, USA. 61 pp.
Brown, D.T., J.A. Rice, and D.D. Aday. 2014. Responses of Largemouth Bass to Seasonal Hypoxia and Tournament Displacement in a Coastal System. Final Report. Federal Aid in Fish Restoration Project F-100-R. North Carolina State University, Raleigh, NC, USA. 98 pp.
Bethke, B.J., J.A. Rice, and D.D. Aday. 2012. Unpredictable outcomes of an invader in small reservoirs. Final Report. Federal Aid in Fish Restoration Project F-68-12. North Carolina State University, Raleigh, NC, USA. 50 pp .
- Brey, M.K., Z.S. Feiner, J.D. Godbout, D.D. Aday, and J.A. Rice. 2012. Trophic Interactions and Reservoir Food Web Dynamics. Final Report. Federal Aid in Sport Fish Restoration Project F-68-08 North Carolina State University, Raleigh, NC, USA. 303 pp.
Sackett, D.K, J.A. Rice, and D.D. Aday. 2011. The influence of fish length on tissue mercury dynamics: implications for natural resource management and human health risk. Final Report. Federal Aid in Fish Restoration Project F-68-13. North Carolina State University, Raleigh, NC, USA. 47 pp.
Craig, J.K. and J.A. Rice. 2008. Estuarine residency, movements, and exploitation of southern flounder (Paralichthys lethostigma) in North Carolina. Final Report. North Carolina Sea Grant, Fishery Research Grant 05-FEG-15. North Carolina State University, Raleigh, NC, USA. 39 pp.
Thompson, J.S., J.A. Rice, D.S. Waters, J.C. Taylor, J.E. Hightower, L.A. Davias, and P.S.
Rand. 2005. Energetics ofreservoir striped bass populations: Phase 1 Final Report.
Federal Aid in Fish Restoration Project F-68-04. North Carolina State University, Raleigh, NC, USA. 329 pp.
Kwak, T.J., W.E. Pine, D.S. Waters, J.A. Rice, J.E. Hightower, and R.L. Noble. Population Dynamics and Ecology oflntroduced Flathead Catfish: Phase 1 Final Report. Federal Aid in Sport Fish Restoration Project F-68-01. North Carolina State University, Raleigh, NC, USA. 217 pp .
- Bestgen, K.R., D.W. Beyers, G.B. Haines, and J.A. Rice. 1997. Recruitment models for Colorado squawfish: tools for evaluating relative importance of natural and managed processes. Colorado Squawfish Recovery Program Project Final Report. Colorado State University Larval Fish Laboratory, Fort Collins, CO, USA. 54 pp.
Jackson, J.R., J.A. Rice, R.L. Noble, and S.C. Mozley. 1991. Mechanisms ofreservoir fish community dynamics. Federal Aid in Fish Restoration Project F-30-1 Final Report. North Carolina Agricultural Research Service, North Carolina State University, Raleigh, NC, USA. 104 pp.
Extension Publications:
Rice, J.A., J.W. Neal, and R.L. Noble. 2000. Hybrid striped bass performance and management
- impacts in small warmwater impoundments. pp. 203-212 in R.M. Timm and S.L. Dann (eds.) Leading the Way Toward Sustainability: Extension in the New Millennium.
Proceedings of the 9th National Extension Wildlife, Fisheries, and Aquaculture Conference in Portland, ME, 1999. National Resources and Environment Unit, CSREES/USDA, Washington, D.C. 312 p.
Rice, J.A. 2000. Quantitative Evaluation of the Effectiveness of a Pond Management Video Tape. pp. 273-278 in R.M. Timm and S.L. Dann (eds.) Leading the Way Toward Sustainability: Extension in the New Millennium. Proceedings of the 9th National
- Extension Wildlife, Fisheries, and Aquaculture Conference in Portland, ME, 1999 .
National Resources and Environment Unit, CSREES/USDA, Washington, D.C. 312 p.
Rice, J.A., R.L. Noble, and R.L. Curry, eds. Pond management guide, 2nd Edition. 1999. NC Cooperative Extension Service and NC Wildlife Resources Commission. 29 pp.
Rice, J.A. 1996. Zebra mussels and aquaculture: what you should know. North Carolina Sea Grant Program. 4 p.
Kay, S.H, and J.A. Rice. 1992. Using grass carp for aquatic weed management. N.C.
Cooperative Extension Service. 4 p.
Rice, J.A., R.L. Noble, and F.T. McBride, eds. Pond management guide. 1990. NC Wildlife Resources Commission and NC Agricultural Extension Service. 27 pp.
North Carolina Natural Resources: An Inventory and Conservation Issues. 1990. Written and edited by the NCAES Natural Resources Work Group (J.A. Rice, member).
Rice, J.A., and J.M. Hinshaw. 1989. North Carolina Aquaculture Directory. NC Agricultural Extension Service.
Other Extension Communication Products:
Rice, J.A. 2002. Pond Management: Good Fishing in the Balance. 4-H Wildlife Project web-
- based publication (www.nc4h.org/enrichment/wildlife/13-15-pondman.pdf) .
Rice, J.A., B.J. Burke, and W.S. Payne. 1999. Extension Wildlife, Fisheries and Aquaculture Web Site, NC Cooperative Extension Service. http://www.ces.ncsu.edu/nreos/wild/.
Rice, J.A. 1994. Managing your pond for better fishing (23-min. video tape). N.C. Cooperative Extension Service.
Cope, W.G., J.A. Rice, S.L. Bryant and P.A. Harris. 2003. Aquatic Nuisance Species Poster.
N.C. Cooperative Extension Service.
Popular Articles:
Rice, J.A. 1994. A Recommended Dose ofLWD. Friend of Wildlife, North Carolina Wildlife Federation. Fall 1994: 16.
Rice, J.A. 1994. The Holiday Dinner Dilemma. Friend of Wildlife, North Carolina Wildlife Federation. January/February 1994:13.
Rice, J.A. 1993. Are You a Member of a (Gasp!) Special Interest Group? Friend of Wildlife, North Carolina Wildlife Federation. September/October 1993:14.
Rice, J.A. 1993. The Web of Life: How Strong is our Safety Net? Friend of Wildlife, North Carolina Wildlife Federation. January 1993:15 .
- Rice, J.A. 1992. Fish Stocking and Species Introductions: Blessing or Curse? Friend of Wildlife, North Carolina Wildlife Federation. 40(3):14-15.
Rice, J.A. 1991. From Russia With Lenok. Friend of Wildlife, North Carolina Wildlife Federation. 39(3):8-10.
Rice, J.A. 1991. Up Close and Personal With the Private Landowner. Friend of Wildlife, North Carolina Wildlife Federation. 38(6):20.
Rice, J.A. 1991. Are You Nervous? Friend of Wildlife, North Carolina Wildlife Federation.
38(2):13.
Rice, J.A. 1990. Living Within Our Means. Friend of Wildlife, North Carolina Wildlife Federation. 37(4): 14-15.
Rice, J.A. 1990. The Rhyme and Reason of Regulations. Friend of Wildlife, North Carolina Wildlife Federation. 37(1):14-15.
Rice, J.A. 1989. Life in the Catacombs. The Flyline, North Carolina Council of Trout Unlimited.
2:14.
Rice, J.A. 1988. Situational Jitterbugging and the case for credibility. Friend of Wildlife, North
Carolina Wildlife Federation. 35(6): 11.
Rice, J.A. 1988. Planning for tomorrow's fisheries today. Friend of Wildlife, North Carolina Wildlife Federation. 35(2):6.
Rice, J.A. 1988. A Rare Opportunity. The Fly line, North Carolina Council of Trout Unlimited.
1:16.
Rice, J.A. 1988. Special places. The Flyline, North Carolina Council of Trout Unlimited. 1:8.
Rice, J.A. 1987. What's in a fish? Friend of Wildlife, North Carolina Wildlife Federation.
34(5):6.
- Rice, J.A. 1987. Water, extraordinary, ordinary water. Friend of Wildlife, North Carolina Wildlife Federation. 33(6):11.
Rice, J.A. 1986. Plant a seed for the future - take a kid fishing! Friend of Wildlife, North Carolina Wildlife Federation. 33(4):4 .