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| number = ML110030898
| number = ML110030898
| issue date = 01/03/2011
| issue date = 01/03/2011
| title = 2011/01/03-Pilgrim Watch SAMA Remand Pre-Filed Testimony
| title = Pilgrim Watch SAMA Remand Pre-Filed Testimony
| author name = Lampert M
| author name = Lampert M
| author affiliation = Pilgrim Watch
| author affiliation = Pilgrim Watch
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| page count = 163
| page count = 163
}}
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=Text=
{{#Wiki_filter:UNITED STATES OF AMERICA NUCLEAR REGULATORY COMMISSION BEFORE THE ATOMIC SAFETY AND LICENSING BOARD In the Matter of                                      Docket # 50-293-LR Entergy Corporation Pilgrim Nuclear Power Station License Renewal Application                          January 3, 2011 PILGRIM WATCH SAMA REMAND PRE-FILED TESTIMONY Mary Lampert Pilgrim Watch, pro se 148 Washington Street Duxbury, MA 02332
TABLE OF CONTENTS Introduction                                                                          1 Meteorological Patterns/Issues                                                        2 Straight-Line Gaussian Plume Model Used by Entergy is Deficient                    4 PW Evidence Showed Deficiencies of Entergys Use of a Straight-Line Gaussian Plume  5 Model to Characterize Consequences in Pilgrims SAMA analysis Sea Breeze                                                                          6 Behavior of Plumes Over Water                                                      8 Storms                                                                              9 Geographical Variations, Terrain Effects, and Distance                              9 PW Evidence Showed That Entergys Inputs to the MACCS2 Code Were Deficient and      10 Did Not Account for Site-Specific Conditions Meteorological Inputs                                                              10 Affected Area                                                                      14 NEPAs Rule of Reason- Meteorological Plume Model & MACCS2 Code                    16 Board Majoritys Specific Questions (Board Order, Appendix A)                          19 ASLBs Questions Avoid Significant Meteorological Issues Brought Forward            20 Appendix A Questions and Responses                                                  23 Beyond Meteorology                                                                    50 The Boards Prior Orders                                                              52 What Pilgrim Watch Would Have Proved But for the Prior Orders                          55 Probabilistic Modeling                                                              55 Amount of Radioactive Release - Size of Accident,Core and Spent Fuel Pool Releases  58 Use of the MACCS2 Code                                                              65 Cleanup/Decontamination, Health and Other Costs                                    67 Appendices                                                                            83 Appendix 1: Review Of Prior Board And Commission Decisions (2006-2010)
Appendix 2: Meteorological Modeling: Government and Independent Studies Appendix 3: Use of Risk Measures in Design and Licensing Future Reactors, Kamiar Jamali Appendix 4: A Critique Of The Radiological Consequence Assessment Conducted In Support Of The Indian Point Severe Accident Mitigation Alternatives Analysis, Dr.
Edwin S. Lyman Appendix 5: Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 Appendix 6: Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ
PILGRIM WATCH SAMA REMAND PRE-FILED TESTIMONY I.          INTRODUCTION On September 23, 2010, the Board Ordered (Order Confirming Matters Addressed at September 15, 2010, (Telephone Conference), hereinafter September Order) that the hearing now scheduled for March 2010 will be bifurcated to consider two issues.
According to the September Order (pp. 1, 2),
[T]he primary and threshold issue [is] whether the meteorological modeling in the Pilgrim SAMA analysis is adequate and reasonable to satisfy NEPA, and whether accounting for the meteorological patterns/issues of concern to Pilgrim Watch could, on its own, credibly alter the Pilgrim SAMA analysis conclusions on which SAMAs are cost-beneficial to implement (hereinafter referred to as the meteorological modeling issues).
Then, and only if the Board decides in favor of of Interventors on the primary and threshold issue..., the hearing will proceed to consideration of whether, and the extent to which, additional issues as set forth below will be heard.
The Board also said that the Board will, if it finds that they were timely raised, consider whether Pilgrim Watchs concerns about the NRCs practice of using mean consequence values in SAMA analyses, resulting in an averaging of potential consequences (hereinafter referred to as averaging practice concerns) could bring into question the reasonableness of this NRC practice and affect the Boards findings and conclusions of the the meteorological issues. (September Order)
On November 23, a majority of the Board found that the mean consequences values issue was not timely raised and therefore the issue will not be entertained by the Board during the evidentiary hearing on Contention 3. (November 23 Order, pp. 1-2).
In view of these Orders, on December 2, 2010, Pilgrim Watch (PW) submitted to the Board Pilgrim Watch Memorandum Regarding SAMA Remand Hearing. As there said, Pilgrim Watch will not present any new evidence at the upcoming SAMA Remand Hearing and will rely solely on what has previously been presented.
The evidence already of record shows, as discussed below, that use of a site-appropriate variable plume model, rather than a straight line Gaussian plume model, could result in significant changes in the areas that would be affected by a serious accident at PNPS.
It is also clear, however, that simply a change in area, on its own would not alter the Pilgrim SAMA Analysis. The majority Orders of September 23, 2010 and November 23, 2010 have so limited the scope of the remand hearing (in PWs view improperly) that it would be a fools-errand for PW to expend its limited resources to prepare and submit to the Board additional meteorological evidence for the limited initial phase of the remand hearing, or additional cost evidence for the limited second phase, should a second phase occur.1 II.        Meteorological Patterns/Issues The September and November Orders preordain that a majority of this Board will find that accounting for the meteorological patterns/issues of concern to Pilgrim Watch could [not],
on its own, credibly alter the Pilgrim SAMA analysis conclusions on which SAMAs are cost-beneficial (September Order).
It is not possible for either Pilgrim Watch, or anyone else, to show that meteorology, in and of itself, would result in a significantly different SAMA analysis. But that is all Pilgrim 1
As said in PWs memorandum, we of course do not waive, and reserve, all of our appeal rights.
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Watch has been left to argue. Further, at least a majority of the Board has effectively again rewritten Contention 3 to require Pilgrim Watch not only to show that further analysis is required (as Contention 3 states), but to require that Pilgrim Watch itself conduct the further analysis listed in the Appendix to the Order - something that neither it nor any other intervenor could possible do without spending hundreds of thousands of dollars, or should be required to do.
As for whether meteorology could, on its own, credibly alter the Pilgrim SAMA analysis, the evidence already before the Board shows (as discussed below) that the Gaussian Plume model used by Entergy in its SAMA analysis is non-conservative and deficient, and that if a proper, e.g. a variable plume, model were to be used, the geographical area affected by a serious accident, and the deposition within that area, would be different.
But on its own using a variable plume model would not alter Entergys SAMA analysis.
That analysis would continue to use the MACCS2 in the same flawed way in which Entergy has used it; in particular Entergys choice of source, ill-chosen average (mean) and probability would reduce any consequences that resulted from different meteorological inputs to such a low level that they could have no effect on the SAMA cost-benefit analysis.
Moreover, the effect a variable plume would have on even a proper SAMA analysis cannot be determined without running a site-appropriate variable plume model to determine exactly where and how large the affected area might be, and, more importantly, how a major radiological accident could affect that area and what, using an updated computer modeling code with proper inputs, the true resulting costs and damage might be.
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Simply stated, Pilgrim Watch has shown (as discussed below) that the meteorological model used by Entergy is deficient. But neither Pilgrim Watch nor anyone else, regardless of how much time and money they might spend, can prove that meteorological patterns/issues ... could, on its own, credibly alter the Pilgrim SAMA analysis/issues of concern. Contention 3 as admitted should not require Pilgrim Watch to do so.
A      Straight-Line Gaussian Plume Model Used by Entergy is Deficient
: 1.      Introduction PW has submitted significant evidence to the Board and Commission that the straight-line Gaussian plume model does not subsume all reasonably possible meteorologic patterns, and is not appropriate for the PNPS coastal location. [Egan Dec. at 132] and did not predict site-specific atmospheric dispersion. The MACCS2 code used by Entergy could not model many site-specific conditions and did not determine economic costs for Pilgrims affected area that includes within its 50-mile radius densely populated areas of Boston, Providence, smaller cities and Cape Cod and Islands in summer, located across the bay.
The Gaussian plume model assumes that a released radioactive plume travels in a steady-state straight-line [Egan, 9], i.e., the plume functions much like a beam from a flashlight. The MACCS2 code used by Entergy was based upon this straight-line, steady-state model; it also assumed meterological conditions that are steady in time and uniform spatially across the study region [Egan, 9]. However, PW presented evidence that, the assumption of a steady-state, straight-line plume are inappropriate when complex inhomogeneous wind flow patterns happen 2
Dr. Bruce Egans Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pg., 132. Adams ML071840568, Exhibit 1 4
to be prevailing in the affected region. [Rothstein3, 2] The meteorological inputs that Entergys Gaussian plume model ignored include the variability of winds, sea breeze effects, the behavior of plumes over water, and re-suspension of contaminants.
PW evidence shows another significant defect in Entergys model - its meterological inputs (e.g., wind speed, wind direction, atmospheric stability and mixing heights) into the MACCS2 are based on data collected by Applicant at a single, on-site anemometer, plus precipitation data from Plymouth airport, some 5 or so miles inland [Application ER, E.1.5.2.6],
and that the data is from only one year.
The record before the Board shows that the use of a variable trajectory model could materially affect whether additional SAMAs may be cost-beneficial. Using its straight-line Gaussian plume model, Entergy projected costs could well be as low as $567,000 or even $0.00.
PWs evidence shows that, using a variable trajectory model, the projected costs could run from
$31 to >$100 Billion dollars. 4
: 2. PW Evidence Showed Deficiencies of Entergys Use of a Straight-Line Gaussian Plume Model to Characterize Consequences in Pilgrims SAMA analysis Entergys straight-line, steady-state Gaussian plume model does not allow consideration for the fact that the winds for a given time period may be spatially varying, and it ignores the presence of sea breeze circulations which dramatically alter air flow patterns. Because of these 3
Richard Rothsteins Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pg., 168. Adams ML071840568, Exhibit 5 4
Dr. Jan Beyeas Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pgs., 97, 112; Summary Comparison- Population Multiplied by Sensitivity Case, pg., 88-9. Adams ML071840568, Exhibit 2 5
failings the straight-line Gaussian plume model is not appropriate for the PNPS coastal location. [Egan 9, 13]
The nearby presence of the ocean greatly affects atmospheric dispersion processes and is of great importance to estimating the consequences in terms of human lives and health effects of any radioactive releases from the facility [Egan, 9], and that the transport, diffusion, and deposition of airborne species emitted along a shoreline can be influenced by mesoscale atmospheric motions. These cannot be adequately simulated using a Gaussian plume model.
[Feasibility of Exposure Assessment for The Pilgrim Nuclear Power Plant, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988, 9]
: a. Sea breeze effect The sea breeze effect, ignored by Entergys model, is a critical feature to consider at Pilgrims coastal location. Egan explained, at 10, The sea breeze circulation is well documented (Slade, 1968, Houghton, 1985, Watts, 1994, Simpson, 1994). [T]he presence of a sea breeze circulation changes the wind directions, wind speeds and turbulence intensities both spatially and temporally through out its entire area of influence. The classic reference Meteorology and Atomic Energy, (Section 2-3.5 ) (Slade, 1968) succinctly comments on the importance of sea breeze circulations as The sea breeze is important to diffusion studies at seaside locations because of the associated changes in atmospheric stability, turbulence and transport patterns. Moreover its almost daily occurrence at many seaside locations during the warmer seasons results in significant differences in diffusion climatology over rather short distances.
Spengler and Keeler5, 1988 showed that the sea breeze at Pilgrims coastal location increases doses on communities inland to an approximate 15 Km (9.3 miles). [Spengler; see also Egan, 12], and that the topography of a coastal environment plays an important role in the sea breeze circulation, and can alter the typical flow pattern expected from a typical sea breeze along a flat 5
Final Project Report, Feasibility of Exposure Assessment For the Pilgrim Nuclear Power Plant, Prepared for the Massachusetts Department of Public Health, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988. Exhibit 11 6
coastline. [Spengler, 40]        But as PW showed, [t]The atmospheric model included in the
[MACCS2] code does not model the impact of terrain effects on atmospheric dispersion. 1997 User Guide for MACCS2.
PWs expert specifically contradicted Entergys expert Kevin OKula statements about the sea breeze effect at Pilgrim Station. [Egan, 13, replying to OKulas declaration, item 10]
: 1) [Mr. OKulas] statement that the meteorological data collected at the PNPS site would reflect the occurrence of the sea breeze in terms of wind speeds and direction is not necessarily true.
: 2) A measurement at a single station tower, 220 feet, will not provide sufficient information to allow one to project how an accidental release of a hazardous material would travel.6 Measurement data from one station will definitely not suffice to define the sea breeze.
: 3) [Mr. OKulas] contention that the seabreeze is generally beneficial in dispersing the plume and in decreasing doses is incorrect. In fact, the development of seabreeze flow that would transfer a release inland is the greatest danger. Contrary to the implications of this declaration, the development of a sea breeze flow is the common meteorological condition that must be most closely monitored at the PNPS.
: 4) [Mr. OKulas] statement reflects a misconception that the sea breeze is generally a highly beneficial phenomena that disperses and dilutes the plume concentration and thereby lowers the projected doses downwind from the release point. If the same meteorological conditions (strong solar insolation, low synoptic-scale winds) that are conducive to the formation of sea breezes at a coastal site occurred at a non coastal location, the resulting vertical thermals developing over a pollution source would carry 6
License Application 2.10 Meteorology and Air Quality at 2-31; and at Attachment E, E.1.5.2.6 at E.1-63]
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contaminants aloft. In contrast, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses.
: b. Behavior of Plumes Over Water Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence. The marine atmospheric boundary layer provides for efficient transport. Because of the relatively cold water, offshore transport occurs in stable layers. Wayne Angevines (NOAA) research of the transport of poluttants on New Englands coast concluded that major pollution episodes along the coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories. Therefore a plume will remain concentrated until winds blow it onto land. [Zager et al.; Angevine et al.
20067]. This can lead to hot spots of radioactivity in places along the coast, certainly to Boston.
[Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative model that Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used for sensitivity studies. [Beyea, 11-12].
7 Angevine, Wayne; Tjernstrm, Michael; Žagar, Mark, Modeling of the Coastal Boundary Layer and Pollutant Transport in New England, Journal of Applied Meteorology and Climatology 2006; 45: 137-154, Exhibit 6 8
: c. Storms The storm cycle consists generally of northeasters in the winter and spring (and)
[h]Hurricanes sometimes occur in the late summer and fall. [Applicants LA Apprendix E, 2-31]. The accompanying strong and variable winds would carry a plume to a considerable distance.
: d. Geographical Variations, Terrain Effects, and Distance PW showed that topography of a coastal environment plays an important role in the sea breeze circulation, and can alter the typical flow pattern expected from a typical sea breeze along a flat coastline. [Spengler, 40] But [t]The atmospheric model included in the [MACCS2] code does not model the impact of terrain effects on atmospheric dispersion. [1997 User Guide for MACCS2.]
The Gaussian plume model also does not take terrain effects, which PW showed can have a highly complex impact on wind field patterns and plume dispersion, into account. Wind blowing inland will experience the frictional effects of the surface which decrease speed and direction.
[PW Motion to Intervene, May 25, 2006 citing Lyman, Chernobyl on the Hudson, 27; Rothstein, Appendix A].
EPA has recognized that geographical variations can generate local winds and circulations, and modify the prevailing ambient winds and circulations and that assumptions of steady-state straight-line transport both in time and space are inappropriate. [EPA Guidelines on Air Quality Models (Federal Register Nov. 9, 2005, Section 7.2.8, Inhomogeneous Local Winds, italics added EPA's November 9, 2005 modeling Guideline (Appendix A to Appendix W) lists EPA's "preferred model; the Gaussian plume model used by Entergy (ATMOS) is not on the 9
list. EPA recommends that CALPUFF, a non-straight-line model, be used for dispersion beyond 50 Km.8 The essential difference between the models that EPA recommends for dispersion studies and the two-generation-old Gaussian plume model (ATMOS) used by Entergy and the NRC is more than determining where a plume will likely to go. Major improvements in the simulation of vertical dispersion rates have been made in the EPA models by recognizing the importance of surface conditions on turbulence rates as a function of height above the ground (or ocean) surfaces. We know that turbulence rates and wind speeds vary greatly as a function of height above a surface depending upon whether the surface is rough or smooth (trees vs over water transport) (Roughness), how effectively the surface reflects or absorbs incoming solar radiation (Albedo) and the degree that the surface converts latent energy in moisture into thermal energy (Bowen ratio). These parameters are included in the AERMOD and CALPUFF models and determine the structure of the temperature, wind speed and turbulent mixing rate profiles as a function of height above the ground.              Entergys ATMOS model does not include these parameters. This is an especially important deficiency when modeling facilities located along coastlines, such as Pilgrim.
: 3. PW Evidence Showed That Entergys Inputs to the MACCS2 Code Were Deficient and Did Not Account for Site-Specific Conditions
: a.      Meteorological Inputs One fundamental defect in Entergys use of the MACCS2 code is that its meterological inputs to that code are all based on the straight-line Gaussian plume model. PW showed that this model does not allow consideration of the fact that the winds for a given time period may be 8
Appendix A to Appendix W to 40 CFR Part 51, EPA Revision to the Guideline on Air Quality Models:
Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule, November 9, 2005. http://www.epa.gov/ scram001/guidance/guide/appw_05.pdf.
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spatially varying. [Egan, 9]        The 1997 User Guide for MACCS2, SAND 97-05949 makes a related point: The atmospheric model included in the code does not model the impact of terrain effects on atmospheric dispersion.
Indeed, the MACCS2 Guidance Report, June 2004,10 is even clearer that Entergys inputs to the code do not account for variations resulting from site-specific conditions such as those present at PNPS. (1)The code does not model dispersion close to the source (less than 100 meters from the source). Thereby ignoring resuspension of contamination blowing offsite. (2)
The code should be applied with caution at distances greater than ten to fifteen miles, especially if meteorological conditions are likely to be different from those at the source of release. There are large potentially affected population concentrations more than 10-15 miles from Pilgrim - for example: Boston, Providence, Brockton, New Bedford, Fall River, Quincy, Cape Cod. (3)
Gaussian models are inherently flat-earth models, and perform best over regions where there is minimal variation in terrain. Entergy description of the PNPS site says that the, [t]opography consists of rolling forested hills interspersed with urban areas. [Lic.A, Appendix E, 2-1]
A second defect in the Applicants inputs into the MACCS2 code lies in the data itself.
Entergy input meteorological data for only a single year [OKula Dec. at 21; WMSM at 22], and except for precipitation all of the data was collected from a single, on-site weather station.
[Application ER, E.1.5.2.6]
PW showed that one year of data would have been insufficient even if more than one station had been used; Seasonal wind distributions can vary greatly from one year to the next.
[Spengler and Keeler          Report, Page 22]. The NRC staff considers 5 years of hourly 9
Chanin, D.I., and M.L. Young, Code Manual for MACCS2:Volume 1, Users Guide, SAND97-0594 Sandia National Laboratories, Albuquerque, NM, (1997) 10 MACCS2 Guidance Report June 2004 Final Report page 3-8:3.2 Phenomenological Regimes of Applicability, Exhibit 21 11
observations to be representative of long-term trends at most sites, although with sufficient justification [not presented by Entergy here] of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations.
(NRC Regulatory Guide 1.194, 2003)
The simple fact is that measurements from a single 220 high anemometer will not provide sufficient information to project how an accidental release of a hazardous material would travel.
[Egan, 13] For cases when the sea breeze was just developing and for cases when the onshore component winds do not reach entirely from the ground to the anemometer height. The occurrence of a sea breeze would not be identified. The anemometer would likley indicate an offshore wind indication. Furthur PW demonstrated that basing wind direction on the single on-site meteorological tower data ignores shifting wind patterns away from the the Pilgrim Plant including temporary stagnations, re-circulations, and wind flow reversals that produce a different plume trajectory. [Rothstein, Town of Plymouth Nuclear Matters Committee Recommendation to Selectmen, Appendix A Meteorology, 13, Exhibit 5, Exhibits 3,4]
Since the 1970s, the USNRC has historically documented all the advanced modeling technique concepts and potential need for multiple meteorological towers especially in coastal regions. [Rothstein, June 24, 2006 letter, 2] NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.[Ibid., cited in Appendix 1]; and an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000, Sec 3.4 points to the need for multiple inland meteorological monitoring sites.
See also      Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for 12
Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936.
Entergy should have taken data from more locations over a longer period; and modified the MACCS2 code to account for the inability of the code that Entergy used to account for site-specific conditions. The user has total control over the results that will be produced. [1997 User Guide, Section 6.10].
Finally, PW presented evidence that statements made in the OKula declarations that were relied on by Entergy to support its contention that the inputs into the MACCS2 code were sufficient are incorrect or misleading. As Egan, at 13, established,
: 1) MACCS2 is not a state-of-the-art computer model. It does not rely upon or utilize current understandings of boundary layer meteorological parameterizations such as          those adopted by the EPA in the models AERMOD OR CALPUFF (EPA, 2001).
: 2) The Gaussian plume model employed in the PNPS MACCS2 model may be the standard for NRC but it is not the basis for advanced modeling used by other US regulatory agencies.
: 3) Computational time should not be a major factor in the choice of a dispersion model used for non-real time applications. Contrary to Entergy, these applications are not simply impracticable
: 4) The idea that randomly chosen meteorological conditions would give the same results as inputting meteorological conditions as a function of time is erroneous. To accommodate the real role of persistence in dispersion modeling EPA requires sequential modeling for all averaging times from 3 hour averages to annual averages.
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: 5)    The fact that a model may seem to be conservative in particular applications or in limited data comparisons does not mean that the model is better or should be recommended.          Models can be conservative but have incorrect simulations of the underlying physics. Sensitivity studies do not add useful information if the primary model is flawed.
: b.        The Affected Area The evidence presented by PW also established important disputes of material fact with respect to Entergys site specific meteorology-related economic inputs into its MACCS2 code analyses. Pilgrim Watch evidence showed that Entergy choices of inputs consistently and significantly underestimated the economic consequences of a radioactive release from PNPS.11 Entergys choice of a straight-line Gaussian plume rather than a variable trajectory model drastically reduced, to a wedge, the size of the area that might potentially be impacted by a release. Entergys analyses also assumed a small accident that had no real impact beyond 10 miles. Entergy did not consider the potential of the by far largest, and perhaps also the most likely, potential radiological release - from the spent fuel pool. In addition, Entergy chose to use the MACCS2 Code that, absent site specific modifications that Entergy chose not to make, cannot provide credible cost estimates.
The use of a variable trajectory model, rather than the straight-line Gaussian plume, would have significantly increased the area potentially affected by a released readioactive plume, and thus would also greatly increase the size of the affected population and property, and the economic effect, beyond 10 miles.
11 Beyond its statements that PWs challenges were immaterial, the Board majority opinion gives no indication of what PW evidence the majority actually considered. In dissent, Judge Young said that my colleagues apply a standard that overlooks or ignores genuine issues of material fact that Intervenors present through reputable experts, as well as considerations of practical reality and fundamental fairness. [LBP-06-848, 02-LR, at 40]
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Entergy admits that its MACCS2 analysis does not assume an evacuation zone of greater than 10 miles because to do so would not be realistic [Sowden, 4-5]. Entergys KLD Time Estimates assume that the only area to be evacuated will be an area 2-miles around the reactor and the area within the key-hole from 2-5 miles, or perhaps extended within the key-hole, 5-10 miles. [Sowden, 3; KLD 1998 Report, 9-1.; and KLD 2004 Report, 2-2]. A variable plume analysis would increase the potentially affected area to far more than 2 miles around the plant and a few miles within the key-hole, resulting in potentially far greater risk and damage and also increasing evacuation time estimates. Despite orders to the contrary, more people inside and outside the EPZ will self evacuate. [Martecchini, 3; Zeigler,1-2]
PW showed that the consequences from a severe accident would not be restricted to a key-hole shaped wedge within a 10 mile radius, or to the entire populated area within 10 miles, but rather could encompass a much wider area including the densely populated metropolitan areas of Boston (38 miles NNW), Providence (44 miles SW), smaller cities of Quincy, Brockton, New Bedford and Fall River, and the summer population of Cape Cod and the Islands. The majority of the Capes population is within 10-20 miles; the summer population approximates 600,000, the year round about 210,000. [Rep. Patrick, 2]
A second major defect in the MACCS2 inputs is that Entergy apparently assumed that the only source of radiation in the event of an accident would be from the reactor within the containment. The potentially far greater source of leaked radiation, the spent fuel pool, contains far more radioactive material and is located outside the containment. It was ignored. [Beyea Decl.]
Absent modifications to permit inputs that address the MACCS2 code limitations discussed above, the MACCS2 code used by Entergy is incapable of providing an accurate 15
estimate of economic consequence, here. David Chanin author of the code said, If you want to discuss economic costs  the cost model of MACCS2 is not worth anyones time. My sincere advice is to not waste anyones time (and money) in trying to make any sense of it. (and) I have spent many many hours pondering how MACCS2 could be used to calculate economic costs and concluded it was impossible. [Chanin Decl.]
: c. NEPAs Rule of Reason (1) Meteorological plume model: CLI-10-22, pg., 9 emphasized, as they had done earlier, that NEPA requirements are tempered by a practical rule of reason and an environmental impact statement is not intended to be a research document. If relevant or necessary meteorological data or modeling methodology prove to be unavailable, unreliable, inapplicable, or simply not adaptable for evaluating the SAMA analysis cost-benfit conclusions, there may be no way to assess, through mathmatical or precise model-to model comparisons, how alternative meteorological models would change the SAMA analysis results.
The plume modeling that PW presented as appropriate for Pilgrims SAMA analysis, instead of Entergys decision to use the straight line Gaussian model, are not techniques that require research. They are, in fact, established methods that are publically available, routinely used, and appropriate for quantifying atmospheric dispersion of contaminants. (Appendix 2 lists examples from government and independent sources) Although an effort may be required to adapt these methods for SAMA analyses, this would be very straightforward and research would not be required.
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Appropriate meteorological data or modeling methodology is available. There is no shortage of appropriate meteorological data for a licensing model application. Alternative modeling methods that would use more extensive meteorological data are also available.
The applicant chose to use only one year of onsite data collected at the Pilgrims site.
Meteorological data is also available from nearby airports and, importantly, processed data on a gridded basis can be obtained from NOAA to augment the onsite meteorological data relied upon for    the SAMA analyses that have been provided by Entergy. PW demonstrated this by disclosing, for example, the Jennifer Thorpe12 site-specific meteorological study and Spengler and Keeler study (both Dr. Egan and Hanna attended the studies sea breeze workshop, Chapter 8 of Spenglers study) and Dr. Egans Development of a Dispersion Modeling Capability for Sea Breeze Circulations and other Air Flow Patterns over Southeastern Massachusetts, Upper Cape Cod Modeling Study, that used available meteorological data. Also there are several publically available meteorological modeling methods that can simulate variable trajectory transport and dispersion phenomena. MM5 is one which is routinely used nationally and internationally.
There are other options as well. The present state of art of an appropriate meteorological model would use multi station meteorological measurement data as input to the meteorological model.
The numerical computations, based upon numerical weather prediction techniques, would compute wind fields appropriate for modeling dispersion over a much larger geographic area than the a single measurement site would be appropriate for.
A second reasonableness criterion is that the modeling method must be reliable. The outputs from such meteorological models that are used to produce inputs for the dispersion 12 Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Scince in Applied Meteorology, May 2009.
Exhibit 10 17
models are well accepted and form the basis for the weather predictions provided by the national weather service as well as analyses of air pollution impacts of concern to regulatory agencies .
These techniques have been proven to be reliable and acceptable for air quality permitting and policy applications in complex terrain and over large distances for the US EPA , the US Park Service as well as internationally. PW argued with sufficient particularity that for complex meteorological situations such as for the Pilgrim, these techniques would be more reliable than using the straight line Gaussian model.
The third reasonableness criterion is that the modeling methods be applicable to SAMA analyses. The methods PW recommended are applicable because with straightforward modifications to incorporate nuclear radiation decay rates, they can produce the fields of concentration values and deposition rates needed for dosage calculations.
The fourth reasonableness criterion is that the modeling methodology be adaptable for evaluating SAMA analysis cost benefit conclusions. There is nothing inherent in variable trajectory models that would prohibit the output concentration and deposition fields from being applied to SAMA analyses.
None of the criteria cited would make the use of alternative models unreasonable to apply to the Pilgrims SAMA analyses.
Further there is no basis to the argument that there may be no way to assess through mathematical or precise model to model comparisons, how alternative meteorological models would change the SAMA analysis results. Some assessments may necessarily be qualitative, based simply upon expert opinion. But this argument seems to undercut the very value of mathematical simulation models in general as a method to assess the impacts of nuclear reactor emissions.
18
Last, the rationale offered that the use of advanced models would be computationally too expensive and/or burdensome to use are not justified by the actual run time shown in our review of MACCS2 output files. With modern computers, the use in inappropriate models on the basis of differences of computational costs is indefensible.
Invoking the practical rule of reason to the present disagreement about the most appropriate modeling methodology for application to the Pilgrim SAMA analyses is blatantly dismissive of the concept that the present methods are inappropriate and outdated and that there are indeed alternative modeling available.
(2) MACCS2 risk consequence code: The Applicants SAMA analysis uses MELCOR Accident Consequence Code System (MACCS2) computer program. PW stated the plain fact that there is no NRC regulation requiring the use of that code, or any other particular code. It was Entergys choice. There are other consequence computer codes in use for nuclear accidents around the world. Research is not necessary. Alternatively modifying the code with updated assumptions and inputs is clearly reasonable for a site-specific, Category 2 analysis.
B. The Board Majoritys Specific Questions (Board Order, Appendix A, Sept., 23, 2010)
Appendix A to the September 23, 2010 Board order asked parties to address specific issues concerning meteorological patterns raised by Pilgrim Watch, limited to only the sea-breeze effect and the hot spot effect.
Pilgrim Watch has attempted to do so below. It appears, however, that the questions avoid significant meteorological issues brought forward by PW in these proceedings that are pertinent 19
to understanding how Entergy underestimated the likely area impacted in a severe accident and deposition in that area; pertinent to answering the specific questions; and that should not be ignored. At the risk of being repetitive, these include:
ASLBs Questions Avoid Significant Meteorological Issues Brought Forward
: 1.      Data Source:
PW demonstrated (PW Response to CLI pages 8-9) that basing wind direction on the single on-site meteorological tower data ignores shifting wind patterns away from the Pilgrim Plant including temporary stagnations, re-circulations, and wind flow reversals that produce a different plume trajectory. [Motion to Intervene, Pg., 36; Rothstein, Town of Plymouth Nuclear Matters Committee Recommendation to Selectmen, Appendix A Meteorology, 13]
Since the 1970s, the USNRC has historically documented all the advanced modeling technique concepts and potential need for multiple meteorological towers especially in coastal regions. [Rothstein, June 24, 2006 letter, 2] NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.[Ibid., cited in Appendix 1]; and an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000, Sec 3.4 points to the need for multiple inland meteorological monitoring sites.
See also Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936.
Entergy should have taken data from more locations over a longer period; and modified the MACCS2 code to account for the inability of the code that Entergy used to account for site-specific conditions. The user has total control over the results that will be produced. [1997 20
User Guide, Section 6.10]. There are many other data sources available for coastal Massachusetts and SE Massachusetts, in general.
: 2.        Single-Year data: (CLI , Pg.,8)
PW showed that one year of data would have been insufficient even if more than one station had been used; Seasonal wind distributions can vary greatly from one year to the next.
[Spengler and Keeler          Report13, Page 22].          The NRC staff considers 5 years of hourly observations to be representative of long-term trends at most sites, although with sufficient justification [not presented by Entergy here] of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations.
(NRC Regulatory Guide 1.194, 2003)
: 3.        Precipitation, Moisture, Fog14.
Entergy failed to properly account for another site specific characteristic in Pilgrims coastal location - precipitation, moisture, fog - that affects dispersion (concentration) and hence the cost-benefit analysis. Dispersion (concentration) is affected by precipitation that, like wind flow, is highly complex. Fog varies along the coast and also in the interior, affected by bogs and ponds. Fog with low inversion layer and constant easterly winds could result in less dispersion of the plume. Because fog patches and precipitation can be highly localized, precipitation data from one location at Plymouth Airport 5 or so miles inland is inadequate. [PW Motion to Intervene, 3.3.3.1.c]
worst case scenario of exposure from a release at the Pilgrim Plant may (be) drizzly, foggy day with a low inversion layer and constant easterly winds (because they) could potentially have less dispersion. (Spengler, Decl., pg., 35) 13 Feasibility of Exposure Assessment For The Pilgrim Nuclear Power Plant- prepared for the Massachusetts Department of Public Health, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988; Egan Decl., at 12 I support (Spenglers and Keelers) analysis of the sea breeze effects and their general recommendations.
14 http://www.mass.gov/czm//oceanmanagement/waves_of_change/pdf/troceancc.pdf 21
: 4.          Storms:
The storm cycle consists generally of northeasters in the winter and spring (and)
[h]Hurricanes sometimes occur in the late summer and fall. [Applicants LA Appendix E, 2-31].
The accompanying strong and variable winds would carry a plume to a considerable distance.
(CLI-09) Coastal storms are an intricate combination of events that impact a coastal area. A coastal storm can occur any time of the year and at varying levels of severity; common to coastal storms are high winds, erosion, heavy surf and unsafe tidal conditions, and fog.15 Massachusetts is susceptible to high wind from several types of weather events, including, hurricanes and tropical storms, tornados, and noreasters.
PW brought forward these issues forward throughout these proceedings beginning in PWs Request for Hearing May 25, 2006 at 37-38. There PW said that, However with onshore winds the tower measurements do not reflect the effects of the overland conditions. The wind is likely to be slightly stable as it approaches land and Pilgrim's meteorological tower. As air flows over a heated surface thermally generated turbulence is induced. Under sea breeze conditions the turbulence structure of the atmosphere will not be accurately determined by the meteorological sensors at the coastal site. Dispersion is also affected by precipitation. Like wind flow, precipitation is highly complex - for example, fog patches vary along coastal locations and also in the interior affected by ponds and bogs. On a drizzly, foggy day with a low inversion layer and constant easterly winds there would potentially be less dispersion than a clear day with strong winds and a sea breeze. Fog patches and precipitation can be highly localized therefore precipitation data from one location at Plymouth Airport located 5 or so miles inland are inadequate. To obtain an accurate analysis it is necessary to install continuous recording meteorological instruments along the coast and at additional inland sites in the communities likely to be impacted by Pilgrim, for example the 7 towns identified by Spengler and Keeler (see Exhibit C). The parameters measured should include wind speed and direction, temperature, dew point, and solar insulation. This would allow an analysis which could more adequately analyze the penetration of the sea breeze front and better 15 Commonwealth of Massachusetts -State Hazard Mitigation Plan,2007http://www.mass.gov/Eeops/docs/mema/disaster_recovery/state_plan_2007_rvn4.pdf at 1.2 Natural hazards 22
characterize the spatial variation of the wind flow. The NRC has acknowledged that more meteorological data may be required. In Regulatory Guide 1. 194, this subject is discussed as follows: "The NRC staff considers 5years of hourly observations to be representative of long-term trends at most sites. With sufficient justification of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations" (NRC, 2003). Despite the fact that several site specific reports (see Exhibit C) have been prepared for Pilgrim that show one year of observations gathered from one site will not satisfy this "representativeness" requirement, the Applicant has used only one year's worth of observations, gathered from only one location. The inputs into the MACCS2 Code are inadequate. In Exhibit E Petitioners describe an improved scheme for meteorological monitoring. This improved monitoring will not just provide better inputs for this kind of Severe Accident Modeling, but it is also a necessary tool for Emergency Planning.
APPENDIX A, SEPTEMBER 23, 2010 - QUESTIONS Q.1. Regarding the meteorological phenomena at issue in this remand hearing, describe in depth each of the following, with supporting data also provided, to the extent available:
Q.1.a. The annual frequency of occurrence of the sea breeze effect and the hot spot effect, and the respective duration of each such occurrence
: 1.      The annual frequency of the sea breeze effect and the hot spot effect cannot be known without reviewing data from multiple weather stations and over at least a 5-year period. This is the further analysis that is properly the responsibility of the Applicant, not the Petitioner. Data is available. For example, NOAA lists multiple weather stations in SE Massachusetts. Included, for example, are Logan Airport, Cape Cod Canal, Scituate Harbor, Plymouth Airport, Taunton, Chatham, and Hyannis.
PWs expert, Dr. Egan, was clear that data from Pilgrims single 220 high anemometer will not provide sufficient information to determine the frequency of sea breeze and the hot spot effects. [See Egan, 13, replying to OKula declaration, item 10] A measurement at a single 23
station tower, 220 feet, will not provide sufficient information to allow one to project how an accidental release of a hazardous material would travel.16 For cases when the sea breeze was just developing and for cases when the onshore component winds do not reach entirely from the ground to the anemometer height, the occurrence of a sea breeze would not be identified. The anemometer would likely indicate an offshore wind indication. (CLI, Pg., 8) This was also explained in PW Motion to Intervene, May 25, 2006 at 36-38.
: 2.      A sea-breeze (or onshore breeze) is a wind from the sea that develops over land near coasts. It is formed by increasing temperature differences between the land and water which create a pressure minimum over the land due to its relative warmth and forces higher pressure, cooler air from the sea to move inland. Therefore in Plymouths climate, while the sea breeze can occur throughout the year, it occurs most frequently during the spring and summer months when the land warms up relative to the ocean. On average, Pilgrim experiences about 45 sea breeze days during these two seasons. Typically the onshore component commences round 10 AM and can persist to about 4 PM. (Spengler and Keeler, page 1) Late afternoon, the land cools off quicker than the ocean due to differences in their specific heat values, which forces the dying of the daytime sea breeze. If the land cools below that of the adjacent sea surface temperature, the pressure over the water will be lower than that of the land, setting up a land breeze as long as the environmental surface wind pattern is not strong enough to oppose it. The breeze, and plume, will swing back out to sea. Seasonal wind distributions can vary greatly from one year to the next (Ibid, p., 22)
: 3.      The hot spot effect can occur in combination with the sea breeze or when winds headed intially offshore are blown back towards shore due to wind shifts. The prevailing wind direction 16 License Application 2.10 Meteorology and Air Quality at 2-31; and at Attachment E, E.1.5.2.6 at E.1-63]
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at Plymouth is from the south west,17 heading generally towards the Outer-Cape Cod or Provincetown. Although, seasonal wind distributions can vary greatly from one year to the next (Spengler, p., 22)
: 4.      The annual frequency of occurrence and duration of the sea breeze effect and the hot spot effect was made irrelevant by the Boards October 16, 2006 and November 23, 2010 Orders, that respectively took Entergys use of probabilities and averaging off the table.
Although both the sea breeze and hot spot effects increase the area likely to be impacted (areas 17 Town of Plymouth Wind Energy Feasibility Study, DNV Global Energy Concepts, Inc., August 2008 Pg., 3-5:
online at:
http://www.masstech.org/Project%20Deliverables/Comm_Wind/Plymouth/PlymouthWWTPFinalFeasibilityStudy.p df 25
of greater population density) and the deposition in that area, both are trivialized by Entergys choice to use an extremely low likelihood of an accident and the mean as an average instead of the 95th percentile. Entergy used hourly meteorological data from 2001 (WSMS, p., 6) yielding 8760 observations. There are, on average, 45 sea breeze days a year; i.e., 12 percent of the 365 days in a year. This impact would not be reflected by Entergys use of a mean average; its impact would be reflected if Entergy had used the 95% percentile.
Q.1.b. The spatial and time-dependent pattern of wind and other meteorological phenomenological parameters associated with each such occurrence, or, if such data are not available, expert professional opinion for such parameters, and scientific literature references supporting those opinions
: 1.      The Gaussian plume model assumes that a released radioactive plume travels in a steady-state straight-line [Egan, 9], i.e., the plume functions much like a beam from a flashlight. The MACCS2 code used by Applicant is based upon this straight-line, steady-state model; it also assumes meteorological conditions that are steady in time and uniform spatially across the study region [Egan, 9]. Entergys expert, Kevin OKula acknowledges that the MACCS2 does not model spatial variation in weather conditions. (WSMS Report, pg., 13)
: 2.      PW presented evidence to the Board and Commission that, the assumption of a steady-state, straight-line plume are inappropriate when complex inhomogeneous wind flow patterns happen to be prevailing in the affected region. (Rothstein, p., 2)
Sea Breeze
: 3.      PWs expert, Dr. Bruce Egans declaration responded to the Boards question.
The MAACS2 code is based upon a straight line, steady state Gaussian plume equation that assumes that meteorological conditions are steady in time and uniform 26
spatially across the study region for each time period of simulation. It does not allow consideration for the fact that the winds for a given time period may be spatially varying. For example, the wind speeds and directions over the ocean and over the land near the Pilgrim Nuclear Power Station (PNPS) are assumed to be the same.
Thus the presences of sea breeze circulations which dramatically alter air flow patterns are ignored by the model. As discussed later, the nearby presence of the ocean greatly affect atmospheric dispersion processes and is of great importance to estimating the consequences in terms of human lives and health effects of any radioactive releases from the facility (Egan Decl., item 8)
And The sea breeze circulation is well documented (Slade, 1968, Houghton, 1985, Watts, 1994, Simpson, 1994).The pressure differences that result in the development of a sea breeze essentially start over the land area well after sunrise. Along a coast, the sun heats the land surfaces faster than water surfaces. The warmer air above the land is more buoyant and initially rises vertically. The resulting lower pressure over the land draws air horizontally in from surrounding areas. Near a coast, the air over the water is cooler and denser and is drawn in to replace the rising air. This horizontal flow represents the advent of the sea breeze. The air starting to flow over the land is cooler than the air aloft and like any dense gas tends to resist upward vertical motions and prefers to pass around a terrain obstacle rather than up and over it. The density difference also suppresses turbulence that would mix the air vertically. As this air flows over the rougher and warmer land, an internal boundary layer is created which grows in height within the land bound sea breeze flow. Further inland the flow slows and warms and creates a return flow aloft which flows much more gently back out over the ocean to complete the overall circulations. Thus, the presence of a sea breeze circulation changes the wind directions, wind speeds and turbulence intensities both spatially and temporally through out its entire area of influence. The classic reference Meteorology and Atomic Energy, (Section 2-3.5 ) (Slade, 1968) succinctly comments on the importance of sea breeze circulations as The sea breeze is important to diffusion studies at seaside locations because of the associated changes in atmospheric stability, turbulence and transport patterns. Moreover its almost daily occurrence at many seaside locations during the warmer seasons results in significant differences in diffusion climatology over rather short distances.
Regarding the models ability to take into account meteorological conditions as a function of time, Dr, Egan explained that, 27
[Entergys expert, OKulas] declaration seems to state that randomly chosen meteorological conditions would give the same results as inputting meteorological conditions as a function of time. This is an erroneous concept with real meteorology which does not generally behave in a random manner. In order to take into account meteorological conditions as a function of time a model must process the meteorological data sequentially with time. A common phenomena in weather data analysis is the role of persistence of combinations of meteorological events over periods of hours to many days. The probability that the next hours meteorology will be similar to the previous hours or that tomorrows weather will be like todays is fairly high and certainly not random or independent of what happened in the previous time period . It also matters from an air quality point of view if winds are very low and dispersion very small for several hours in a row. To accommodate the real role of persistence in dispersion modeling EPA requires sequential modeling for all averaging times from 3 hour averages to annual averages. (Egan Decl., item 12 Comments on OKulas declarations, item 16)
PW further explained in its Motion to Intervene:
3.3.3.1. a Wind speed: Accurately characterizing wind speed is critical to estimating concentration sea breeze will decrease wind speed as they move over land.
3.3.3.1. b Wind Direction Wind direction will change with height above the ground and will be influenced by terrain features. The coriolis effect will cause a clockwise turning of the wind direction as the sea breeze develops over the course of the day.
This effect is reflected in the coastal wind sensor, but the effect of surface friction and surface features are not. As a result wind blowing inland will experience the frictional effects of the surface which decreases speed and changes direction.
: 3.      Entergys experts declaration (OKula WSMS Report, pg., 21) agreed that sea breezes are sometimes recognized to be able to penetrate long distances inland. Simpson (1994) shows evidence of sea breeze penetrations up to 300 km inland over a period of 15 hrs in Australia.
Although not all coastal locations will experience such a large inland penetration, Simpson (1994) noted that penetrations on the south coast of England up to 100 km inland. Buckley and Kurzeja (1997) found evidence of sea breeze penetration over 100 km on the South Carolina coast. Penetration on Massachusetts southern coast have not been fully documented; yet data 28
gathered to date do not indicate deep penetration. However the important point is that as OKula acknowledges meteorological data collected on towers at the Pilgrim site do not reflect the occurrence of sea breeze conditions in both the wind speed and direction. (OKula report, pg.,
21)
: 4.      Wind direction will change with height above the ground and will be influenced by terrain features. The coriolis effect will cause a clockwise turning of wind direction as the sea breeze develops during course of the day and eventually heads back to sea.        [Spengler and Keeler, Pg., 39]
: 5.      The topography of the coastal environment also plays an important role in the sea breeze circulation. When cool, dense, stable marine air encounters a hill or mountain, the heavy air tends to flow around them rather than over them. This can alter the flow pattern expected from a typical sea breeze along a flat coastline. [Spengler and Keeler, Pg., 6] Hence, a larger area becomes impacted.
: 6.      Note that there can be larger (synoptic) scale weather patterns that are interacting with seabreeze conditions and vice-versa that can affect the wind flow and degree of seabreeze penetration inland.
29
Hot Spot Effect18:
PWs response to the Commission (CLI-09-11 at 5) explained, Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. This is important because about 60% of the land mass around Pilgrim NPS is water. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds blow it onto land [Zager et al.; Angevine et al. 2006]. At 153, Angevine concluded that, major pollution episodes along the northern New England coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories.
Although Angevine did not specifically study the transport of radionuclides, there is no reason to believe that the basic principles do not hold.
This effect can lead to hot spots of radioactivity in places along the coast, certainly to Boston. [Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative 18 Listing of references: Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.; Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M., Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology & Climatology, 45:137-154, 2006;Beyea, Jan, PhD.,Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, May 25, 2006, The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006; Miller, Samule T.K.; Keim, Barry; Synoptic-Scale Controls on the Sea Breeze of the Central New England Coast, AMS Journal Online, Volume 18, Issue 2 (April 2003); Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Applied Meteorology, May 2009.
30
model that Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used for sensitivity studies. [Beyea, 11-12].
Q.1.c. The radioactive deposition distribution you would expect to occur from each such occurrence, assuming a normalized source term. If such depositions are not readily discernable or determinable, a computer model, such as those contained in ATMOS (excluding the straight line Gaussian plume portion) or another model selected by the relevant expert may be utilized to provide such information Both the sea breeze and behavior of plumes over water (the so-called hot spot effect) will change the area of impact and concentration within that area. DOE explained that, straight-line Gaussian models could not only underestimate the consequences of a release, but also can incorrectly identify locations where higher concentrations can occur.19 [Emhasis added]
Sea Breeze
: 1.      Entergys cost-benefit analysis is based on its contention that the sea breeze is generally beneficial in dispersing the plume and in decreasing doses. This fundamental underlying assumption is incorrect. Dr. Egan explained that, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses.
[Egan, 13].
[Mr. OKulas] contention that the seabreeze is generally beneficial in dispersing the plume and in decreasing doses is incorrect. In fact, the development of seabreeze flow that would transfer a release inland is the greatest danger. Contrary to the implications of this declaration, the development of a sea breeze flow is the common meteorological condition that must be most closely monitored at the PNPS.
[Mr. OKulas] statement reflects a misconception that the sea breeze is generally a highly beneficial phenomena that disperses and dilutes the plume concentration and 19 DOE/EH-0173T CHAPTER 4 (REVISED 2004), February 11, 2005, Pg., 4-6, Exhibit 13 31
thereby lowers the projected doses downwind from the release point. If the same meteorological conditions (strong solar insolation, low synoptic-scale winds) that are conducive to the formation of sea breezes at a coastal site occurred at a non coastal location, the resulting vertical thermals developing over a pollution source would carry contaminants aloft. In contrast, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses. (Egan Decl., Item 13 Comment on OKulas declarations, Item 20)
Spengler confirmed that [t]hese flow reversals and stagnations documented here at our coast result in an increased area impacted, increased concentration of the plume and ultimate cost.
(Spengler, 3).
: 2.      Closely related, Entergy model failed to take into account that wind direction changes and terrain features could not only change plume direction (resulting in a larger affected area),
but could also reduce diffusion of the plume (increasing the amount of radiation received within the area). PW explained that a variable plume model could take account not only of the sea breeze, but also of wind direction changes that occur with height above the ground and terrain changes. [PW Motion to Intervene, citing Lyman at 27; Rothstein, Appendix A; MACCS2 Guidance Report, June 2004, Entergy LA, Appendix E, 2-1]
: 3.      Dose can be defined as a product of concentration and episode duration. The duration is a function of the relative sea breeze strength. Thus it is necessary to gather information on the affected receptor location(s), vector speed and strength, wind speeds, mixing heights, and spread statistics. (Spengler at 35) Entergys reliance simply on meteorological data from the onsite met tower necessarily means that they do not have sufficient data. This further analysis is the responsibility of the Applicant, not the Petitioner.
4        The coriolis effect will cause a clockwise turning of wind direction and decrease in speed as the sea breeze develops during course of the day. [Spengler and Keeler, Pg., 39] This will result in a larger area of impact than modeled by a straight line model and the the decrease in 32
speed will result in increased exposure. Sea breeze and gradient winds would advect ( convey horizontally) emissions over populated areas [Spengler at 2]
: 5.      The direction of the sea breeze is not constant but rotates in a clockwise direction during the day. The winds start off normal to the shore and eventually blow parallel to the shorethis may preferentially expose populations to the west and north. [Spengler and Keeler, Pg., 2]
: 6.      Air pollution effects of sea breezes have been studied for a long time. One of the generally occurring effects of the onshore flow of marine air is fumigation of pollutants, in this case radiation, downwind of the shoreline. Effluent in a severe accident at Pilgrims shore location blown inland by onshore winds may be confined to a plume in the stably stratified marine air. However, as this plume intersects the convective boundary layer inland, pollutants can be mixed down to the surface resulting in fumigation (Lyons and Cole, 1973). Another commonly occurring effect in coastal areas is plume trapping. Stably stratified marine air moving onshore can have a mean mixing depth that is 10% of that existing away from the influence of the water (Lyons and Cole, 1973). Thus, effluent that is ejected into this layer is effectively trapped and high concentrations of pollutants can subsequently reach the surface. Fumigation and plume trapping commonly occur in association with sea or lake breezes. However, lake and land breezes can introduce unique problems. The first is the ability of sea/lake and land breezes to transport pollutants in three dimensions. Lake and land breezes are quasi-closed circulations and pollutants emitted into them can be recirculated several times over the near-shore area (Lyons, 1972). That is, pollutants emitted into the inflow layer get lofted in the frontal regions and disperse into the return flow aloft. A fraction of these pollutants are forced into the inflow layer again by the descending branch of the circulation. Remaining pollutants reside in an elevated layer aloft. Lyons and Olsson (1973) observed a helical trajectory within a sea/lake 33
breeze circulation and suggested that the motion of pollutants might include an along-coast component in addition to the cross-coast components. Lyons et al. (1995) have successfully simulated this three-dimensional behaviour using a numerical model. Also, during periods of stagnant synoptic conditions, lake and land breezes can occur nearly continuously, effectively confining pollutants to coastal regions and causing the accumulation of pollutants over periods of several days (Simpson, 1994; Lu and Turco, 1995). Despite apparently adequate ventilation with onshore winds, rapidly deteriorating air quality can result.
Hot Spots or the Behavior of Plumes Over Water 20
: 7.          Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds blow it onto land [Zager et al.; Angevine et al. 2006]. This can lead to hot spots of radioactivity in places along the coast, certainly to Metropolitan Boston and its densely populated suburbs.
[Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative model that 20 Listing of references: Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.; Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M., Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology & Climatology, 45:137-154, 2006; Beyea, Jan, PhD.,Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, May 25, 2006, The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006; Miller, Samule T.K.; Keim, Barry; Synoptic-Scale Controls on the Sea Breeze of the Central New England Coast, AMS Journal Online, Volume 18, Issue 2 (April 2003); Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Applied Meteorology, May 2009.
34
Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used. [Beyea, 11-12].
: 8.      Wayne Angevine (NOAA) has performed extensive research on pollutant transport along New Englands coast, the behaviour of plumes over these waters.21 Experiments showed that polluted air becomes stably stratified, and vertical mixing is limited. Although, he studied ozone, and not radionuclide transport, there is no reason to believe that the results would be different.
He showed (Exhibit 6) that:
Pollutant transport is most efficient over the ocean. The coastline makes transport processes complex because it makes the structure of the atmospheric boundary layer complex. During pollution episodes, the air over land in daytime is warmer than the sea surface, so air transported from land over water becomes statically stable and the formerly well-mixed boundary layer separates into possibly several layers, each transported in a different direction. His 2006 study examined several of the atmospheric boundary layer processes involved in pollutant transport. The basic conclusion is: major pollution episodes along the northern New England coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories.
To summarize, the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast. The sea breeze modifies the large-scale flow to select the particular sites that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km).
21 Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.;
Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M.,
Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology &
Climatology, 45:137-154, 2006 35
In another study, Coastal Boundary Layer Influence on Pollutant Transport in New England Angevine et al22 they found that:
the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast.
The sea breeze modifies the large-scale flow to select the particular sites that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km). Air pollution episodes in northern New England often are caused by transport of pollutants over water. Two such episodes in the summer of 2002 ware examined (22-23 July and 11-14 August). In both cases, the pollutants that affected the study areas, coastal New Hampshire and coastal southwest Maine, were transported over coastal waters in stable layers at the surface. These layers were at least intermittently turbulent but retained their chemical constituents. The lack of deposition or deep vertical mixing on the overwater trajectories allowed pollutant concentrations to remain strong.
Why is overwater transport important; and different than transport over land?
In northern New England, air transported from land encounters a cooler, smoother surface; convective mixing, therefore, decreases. A persistent pool of cold water exists offshore in the northern and eastern Gulf of Maine and the Bay of Fundy, with warmer water inshore Strong layering of the atmosphere caused by the cold water offshore overwater transport more efficient than transport over land. Because the overwater trajectory segments are always stable in these episodes, the pollutants in the surface layer are not diluted by deep vertical mixing. The surface layer is, however, turbulent, as evidenced by its cooling, and, therefore, pollutants could be lost to surface deposition. However, ozone and most of its precursors are deposited much more slowly to water surfaces than to vegetation, and so the polluted layers over water retain most of their ozone and precursors.
To summarize, the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast. The sea breeze modifies the large-scale flow to select the particular sites 22 Coastal Boundary Layer Influence on Pollutant Transport in New England,Wayne M. Angevine, Christoph J. Senff, Allen B. White, Eric J. Williams, James Koermer, Samuel T. K. Miller, Robert Talbot, Paul E. Johnston, Stuart A. McKeen, and Tom Downs, Journal of Applied Meteorology 2004; 43: 1425-1437, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1 36
that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km).
Although the study focsued on waters north of Boston, the water temperature also is cold in Cape Cod and Massachusetts Bays. The Gulf stream, warmer waters, are kicked offshore by Cape Cod.
Q.1.d. How that deposition would differ from that expected using a straight-line Gaussian plume model The straight-line Gaussian plume model decreases the potential area of impact and concentration within that area. Entergys model reflects only the initial direction of the wind, as indicated by their onsite meteorological tower. It further underestimates potential radiological damage and costs because it cannot reflect that offsite surface friction and surface features can decrease plume speed thereby increasing dose and change plume direction affecting larger areas.
[PW Motion to Intervene, citing Lyman at 27; Rothstein, Appendix A; MACCS2 Guidance Report, June 2004, Entergy LA, Appendix E, 2-1]
Q.1.e. The cost differential caused by the differences indicated in subsection d above (to be provided quantitatively if practicable, or if not, supported qualitative estimates may be provided).
: 1.      This question makes little sense, for a number of reasons.
: a. It is premature. On September 23, 2010, the Board ordered (Order Confirming Matters Addressed at September 15, 2010, Telephone Conference) that the hearing on Contention 3 will be bifurcated. In phase one, the parties were instructed to first look at meteorological patterns/issues of concern to Pilgrim Watch. The second phase of the hearing will not proceed unless the Board finds that meteorological patterns/issues of concern to 37
Pilgrim Watch could, on its own, credibly alter the Pilgrim SAMA analysis conclusion, and even if the Board did so find, it would, consider at most, very limited economic costs issues and would not address real costs..
: b.      Second the question incorrectly assumes that the cost differential caused by the differences in the model could be determined while holding all variables in Entergys SAMA analysis, except the plume model, constant. The only way to compare consequence would be to run both Entergys flawed model and a proper model, and to account for all consequences in a severe, not fantasy, accident (including: health costs, based on up-to-date dose response research; economic costs, including cleanup costs and excluding a discount factor; using the 95%
percentile, instead of the mean; and not multiplying probability by the consequences.) The methodology to determine costs would then be modeled on the Estimation of Attributable Costs from Plutonium-Dispersal Accidents, SAND96-0957, David Chanin, Walt Murfin, UC-502, (May 1996) and studies            commissioned by the US Department of Homeland Security,23 discussed in this briefs section What Pilgrim Watch would have proved but for prior Board and Commission orders.
: c.      Third, it is not reasonable to expect Pilgrim Watch to answer this question. As Administrative Judge Ann Marshall Young explained, at 38, in her Dissenting Opinion in the Memorandum and Order (Ruling on Motion to Dismiss Petitioners contention 3 Regarding Severe Accident Mitigation Alternatives), October 30, 2007, In this proceeding, Intervenors provide the reasoned statements of several well-qualified experts. They do not, it is true, provide any results of calculations proving 23 Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 (Attachment 6, Exhibit 8); Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ (Attachment 7, Exhibit 9) 38
the negative of Entergys sensitivity analysis. But such a requirement  or anything approaching its essential equivalent  is unreasonable, given the extremely complex, expensive, and time-consuming nature of the computer calculations that would be necessary to do this, which even the Applicant, with its relatively greater resources, has called impractical. See Entergys Motion for Summary Disposition of Pilgrim Watch Contention 3 at 13 (May 17, 2007).
Also the accepted contention called for further analysis -i.e., further analysis by the Applicant not the Petitioner.
: 2.      Nonetheless, PW in Pilgrim Watchs Answer Opposing Entergys Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007,            provided rough ball park estimates using Entergys population and trivialized economic data; the Massachusetts Attorney Generals analysis by Jan Beyea, reference to Sandias CRAC 11 study, and Chernobyl.
Economic Consequences using a spatial distribution: The total population was estimated by Entergy for the year 2032 for each spatial element by combining total population projections with transient population data obtained from Massachusetts and Rhode Island.
E. 1.5.2.1 Projected Total Population by Spatial Element, 2032 (PNPS Applicants Environmental Report Operating License Renewal Stage, Attachment E, E.1-61) 39
The table below illustrates potential costs if a variable trajectory plume dispersion model is used so that variable wind conditions are modeled and releases are not minimized to simply a minor release.
For illustration purposes, if all or most of the 10-20 mile area is impacted; some of the 20-30; and a portion of the 30-50 then you have a very different situation than simply assuming impact in the two miles around and a pie-shaped wedge from 2 to 5 miles. PW explained in our Response to Entergys Motion for Summary Disposition and Brief in Response to CLI-09-11 that Entergys cost figures are unrealistically low and it is necessary to consider both the initial deposition and subsequent resuspension in Pilgrims coastal area characterized by variable winds.
Table: Population Per Mile Multiplied By Sensitivity Case I&2 Costs Sector Miles  Total Population  Pop x $135,187.77/per person    Pop x $189,041/person st 1 sensitivity                    2nd sensitivity 0-10          165,236            $22,337,886,364                  $31,236,378,676 10-20          619,601            $83,762,477,480                  $117,129,992,641 20-30          1,659,661          $224,365,869,546                $313,743,975,101 30-40          3,197,941          $432,322,512,382                $604,541,964,581 40-50          1,847,128          $249,709,115,225                $ 349,182,924,248 50 total      7,489,767          $1,012,524,898,550              $ 1,415,873,043,447 In contrast, the table below illustrates potential costs if a straight-line plume distribution is used.
For illustration when looking at the table assume only a minimal, not moderately severe accident, so that only a portion of any 0-10 sector is assumed impacted. It is not hard to understand how using an inappropriate plume model and minimizing a severe accident to a hiccup can reduce projected costs.
40
Table: Population Per Geographic Sector Multiplied By Sensitivity Case I&2 Costs Sector Total Population 0-        Pop x $135,187.77/per person -    Pop x $189,041/person -2nd 10 miles                1st sensitivity                  sensitivity N        0                        0                                0 NNE      3                        $405,563.31                      $567,123.00 NE        3                        $405,563.31                      $567,123.00 ENE      3                        $405,563                          $567,123 E        5                        $675,939                          $945,2050 ESE      23                      $3,109,319                        $4,347,943 SE        950                      $128,428,381                      $179,588,950 SSE      13,289                  $17,883,854,906                  $2,512,165,849 S        23,695                  $3,203,274,210                    $4,479,326,495 SSW      23,695                  $3,203,274,210                    $4,479,326,495 SW        23,695                  $3,203,274,210                    $4,479,326,495 WSW 23,695                        $3,203,274,210                    $4,479,326,495 W        22,818                  $3,084,714,536                    $4,313,537,538 WNW 19,494                        $2,635,350,388                    $3,685,165,254 NW        11,269                  $1,523,430,980                    $2,130,303,029 NNW 5,599                          $756,916,324                      $1,058,440,559 In the above table, imagine if Entergy assumes a severe accident is really one with small off-site release. For example if their straight line plume model, once averaged, predicts winds blowing to the NNE, perhaps one person will be affected costing at most $189,041 in damages Summary: In contrast if a variable trajectory plume distribution model is used, winds shifting carrying the plume over many geographic areas; and a severe accident is assumed to be more than a small offsite release, then more SAMAs are likely to come into play - as the table below illustrates.
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Summary Comparison- Population Multiplied by Sensitivity Case Population within area                                1st sensitivity                        2nd sensitivity-
                                                  $135,187.77/person                      $189,041/person Straight-line Gaussian Plume Model Population SE Sector, 950 (0-10  $128,428,382 > 128 Million                          $179,588,950 miles)
Population SSW Sector, 23695    $3,203,274,210    > 3 Billion                      $4,479,326,495 (0-10 miles)                                                                          >4 billion Variable Plume Model Population within 10 miles,      $22,337,886,364 > 22 Billion                        $31,236,378,676 165236                                                                                >31 Billion Population within 20 miles      $83,762,477,480 > 83 Billion                        $117,129,992,641 619601                                                                                >117 Billion Population within 50 miles      $1,012,524,898,550 (1 Trillion +)                    $ 1,415,873,043,447
                                                                                      > 1 Trillion Previous Projections Core Melt, Pilgrim (1982)        $81.8 Billion CRAC-2, Sandia National Laboratory,198224 Release C-137 from Core -Beyea  $105-488 Billion [MA AGO, Dr. Beyea]
[Based upon Massachusetts Attorney Generals Office Analysis, Dr. Jan Beyea25]
In reviewing the above table, it is sobering to consider the impact of the 1996 Chernobyl accident, 1986, to help understand the potential impact from an accident as Pilgrim. Sheep remain contaminated in Scotland and reindeer are still contaminated in Lapland, from an accident 20 years ago. Chernobyl was bad, no doubt, but certainly not worst case. The 1986 Chernobyl accident released 2,403,000 curies of C-137; whereas Pilgrims core during license 24 Calculation of Reactor Accident Consequences U.S. Nuclear Power Plants (CRAC-2), Sandia National Laboratory, 1982 25 The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006 includes a Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, PhD., May 25, 2006. Exhibit 2 42
extension will have 5,130,000 curies of C-137 [Beyea Decl, Chernobyl; and LR, Pilgrim CS-137 figures].
Q.2 . Regarding the radioactive contamination to be computed from the dispersion and deposition caused by the meteorological patterns at issue, describe in sufficient detail for scientific understanding the following:
Q.2.a. How the source term to be used for each computation of radioactivity dispersion and deposition is determined Entergy knows how the source terms it used were determined. PW understands that Entergy used the MAAP code, a proprietary industry code, to estimate the consequences of severe accidents (radionuclide release fractions generated by the Modular Accident Analysis Progression, MAAP26). The code has not been validated by NRC. The release fractions are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations. This has been observed by NRC in studies such as NUREG-1150. A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable 26 See, for example, ER. E. 1,2,1; and the limitations of the code are examined in Appendix 4, A Critique Of The Radiological Consequence Assessment Conducted In Support Of The Indian Point Severe Accident Mitigation Alternatives Analysis, Dr. Edwin S. Lyman. Dr Lyman would have performed a similar reprot for Piglrim Watch had the issue not been removed from consideration in these proceedings. Exhibit 12 43
scenarios  the NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR. Apparently the differences in the release fractions  are primarily attributable to the use of the different codes in the two analyses. 27 Thus, Entergys use of source terms generated by MAAP appears to lead to anomalously low consequences when compared to source terms generated by NRC staff. In fact, NRC has been aware of this discrepancy for at least two decades.                  In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without performing controlled comparisons for identical boundary conditions and input data.28 We are unaware of NRC having performed such comparisons.
The NUREG-1465 source term was also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.29 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.30 27 J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.
28 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.
29 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.
30 J. Schaperow (2002), op cit.
44
Q.2.b. The degree of conservatism imbedded in that methodology, its sources, and the rationale for each source of conservatism
: 1.      There are two conventional meanings of conservative. One definition is old-fashioned or old-school. In this sense of the term, the methodology used by Entergy was indeed old-school, and that is a major problem with their analysis. The straight-line Gaussian plume model is a simplistic out-of-date model as illustrated in Appendix 2, Meteorological Modeling:
Government and Independent Studies. Dr Egan explained:
The field of dispersion modeling has developed rapidly since models were first routinely used in regulatory applications in the 1960 s and early 1970s. The Clean Air Act Amendments of 1977 created further reliance on atmospheric dispersion models for the establishment of emission limits for new industrial sources seeking licenses and permits under the Clean Air Act. The US EPA and other groups initiated research program to improve the science of dispersion models and the US EPA began to establish performance measures for models and to provide guidance and recommendations for the testing and adoption of improved models in permit applications. The result was further advancement in modeling methods that have persisted to the current decade. Specifically, very significant improvements have been made in the parameterization of the atmospheric boundary layer wind profiles, temperature profiles and variations of turbulent mixing rates with height above the ground surface. As a result of the Clean Air Amendments of 1977, The US EPA has been instrumental in encouraging and supporting the development of improved models including those defined as guideline models AERMOD and CALPUFF (EPA, 2005). AERMOD includes highly sophisticated algorithms for including spatial variations of the ground surface parameters of roughness lengths, surface albedo and the Bowen ratio into the parameterizations of wind and turbulence levels as a function of height. CALPUFF has the added features of allowing spatially variable wind fields. These models are now routinely used for regulatory applications and for risk assessments. (Egan Decl., at 7)
Additionally, the assumptions regarding dose-response are outdated and likewise the entire MACCS2 computer code.
45
: 2.      The second definition of conservatism is cautious. PWs response to the Commission (CLI-09-11 at 15) explained that the Gaussian Plume Model/ MACCS2 Applied in Entergys and the Boards Cost-Benefit Analysis was not conservative.
: a.        Lewellen and Mollenkamp: Entergys experts cite two reports (Lewellen and Mollenkamp31) claiming that they showed the straight-line Gaussian model was conservative.
[Entergy, Motion for Summary Disposition, 12] The fundamental flaw in Entergys contention is that a comparison made in the high desert land in Idaho, Kansas or Oklahoma tells little or nothing about what a comparison made in Plymouth, Massachusetts would show. PNPS site is characterized by its coastal location, varying terrain, forested hills interspersed with urban areas (Appendix E, 2.1). In contrast, the Lewellen and Mollenkamp studies were performed in areas that are not in the least comparable to the PNPS site. As a predictor of what might happen at PNPS, Entergys reports are not conservative; they are simply meaningless. Whether the Gaussian plume model is conservative relative to the Pilgrim site cannot be determined without running both ATMOS (the Gaussian plume) and an alternative model (e.g. MM5 and CALPUFF) with PNPS site specific data.
NRC itself has said that the Mollenkamp study site in central Oklahoma and Kansas did not have topography that would interact with the large-scale flow producing local modification of wind speed and direction and that it did not have changes in surface properties that could affect local flow, such as a coastal site with a land-sea breeze [NUREG/CR 6853, 3]. The Mollenkamp sites are  relatively smooth and (have) has minimal effect on the wind field and the 31 WSMS refers to the results from a test that released a tracer conducted in 1981 at the Idaho National lab (INL is located in high desert land, eastern Idaho), Lewellen, 1985, NUREG/CR-4159; Mollenkamp et al (2004) compared several codes for recorded data in the Midwest, NUREG/CR-6853] Exhibit 16 46
surface is fairly uniform and therefore produces relatively little thermal forcing. The NUREG says that it would have preferred a site with greater topological and diurnal homogeneity (NUREG/CR-6853, Oct. 2004, at xi and 2); and readily admitted that it would be best if MACCS2 and RASCAL/RATCHET results could be compared with measurements over the long distances and types of terrain of interest to the NRC. The only reason that the less desirable comparison with a state-of-the art code was chosen to provide input into the decision on the adequacy of MACCS2 ATD was that such measurements do not exist. (Ibid at 2)
: b. Entergys Sensitivity Studies: Entergys two supplemental sensitivity studies, by Enercon and WSMS, similarly were not conservative. PWs initial brief also pointed to evidence (at 16) that no matter how many scenarios WSMS may have studied using a downwind in a straight line assumption, they cannot provide a valid comparison to variable trajectory scenarios that WSMS never studied. The same holds true for Enercon. PW evidence showed that both the code used by Entergy and the meterological and economic information it used were inadequate. Dr. Egan summed it up: sensitivity studies do not add useful information if the primary model is flawed. Egan Decl. ¶ 13.
: c.      Whether the Gaussian plume model is conservative relative to the Pilgrim site cannot be determined without running both ATMOS (the Gaussian plume) and an alternative model (e.g. MM5 and CA NRC Staffs own expert, Dr. Bixler, (Exhibit 7) generally agreed with Dr. Egan and admitted that the Gaussian plume model results are conservative is correct only if the word conservative is defined narrowly:
: 8. (NEB) Material fact number 12 states that the MACCS2 Gaussian plume model results are in good agreement with, and generally more conservative than those obtained by more sophisticated models. If the word conservative implies that calculated plumes with the MACCS2 code are generally more focused and more concentrated than would be the case if the calculations had been performed with more sophisticated models, then the statement is accurate. However, a more focused, 47
more concentrated plume does not always correspond to a smaller number of person-rem, depending on the trajectory of the plume compared with population centers.
(Emphasis added)
Therefore NRC Staffs expert is in full accordance with PWs argument that whether a Gaussian model is conservative depends entirely on the trajectory of the plume compared with population centers; and PW submitted significant evidence that the straight-line Gaussian plume could not, and did not, predict site-specific atmospheric dispersion for Pilgrims coastal region, or accurately predict what population centers the likely variable plume would affect. [PW CLI 11 Br., 4-10, 14,17]
For example, while Entergy assumed that a plume blowing out to sea would have no impact on any population centers, PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds change the plumes trajectory and blow it ashore. This can lead to hot spots of concentrated radioactivity in places along the coast, certainly including densely populated Metropolitan Boston; or to Cape Cod directly across the Bay with a summer population of 600,000. [PW Br., 5, 17, Rep. Patrick Decl., 2]
Further, Dr. Bixler (Exhibit 7) said very plainly that Entergys claim, that its study was conservative because it used conditions at the beginning of a plume release, was erroneous.
: 9. (NEB) Material Fact number 16 states that Sensitivity Case 2 estimated the effects of changing wind direction trajectory and was conservative because it used conditions at the beginning of a plume release, when the release has larger dose quantity and less decay has occurred. The MACCS2 value modified in Sensitivity Case 2 appears to have been REFTIM (Representative Time Point for Dispersion and Radioactive Decay). REFTIM affects the way in which dispersion, deposition, and radioactive decay are calculated. It does not affect the manner in which "wind direction trajectory" is calculated. This statement appears to be erroneous 48
Again, the Staffs expert is in full accordance with PWs expert, leaving Entergy and NRC Staff at odds.
Although the sea breeze effect is a critical feature at Pilgrims coastal site, here again Dr.
Bixler agrees with PW and Dr Egan, [Egan Decl.,13, Item 20] and says that the effect of sea breeze is not taken into account in Entergys studies.
: 10. (NEB) Material Fact number 19 states that the effect of sea breeze is taken into account in the Pilgrim site meteorological data. Although the wind speed and direction of a sea breeze may be included in the actual PNPS meteorological data, the effect of sea breeze is not taken into account. The effect that is not taken into account is that the complex flow pattern under sea breeze conditions differs substantially from the straight-line pattern used in the MACCS2 analyses. The sea breeze occurrences are typically diurnal events, occurring during daylight hours and during warmer seasons. (Emphasis added, Exhibit 7)
Entergy claims that the Gaussian model concentrates and maximizes the plume in a narrow wedge close to the reactor maximizing health effects; whereas a variable model will produce a more diffuse plume and thereby have less impact on population dose. However, Entergy has presented no data to justify its claim; so far as PW knows, Entergy has never run a variable plume model, much less one that properly used the MACCS2 code.
And most important, one cannot be conservative both close to the reactor and far afield.
Arguably, the severe health effects close in may be greater with a Gaussian model; but the latent health effects, economic damage and cleanup costs will be greater due with a variable model due to its larger area of impact.
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Q.2.c. The extent to which those conservatisms cause the resultant deposition to be conservative; be as quantitative as is practicable, but qualitative discussions are acceptable where quantitative analysis is not practicable PWs response to Q.2.b answers this question. The short answer is that the straight-line Gaussian plume is not conservative or cautious, the resultant deposition is underestimated and consequences minimized.
Once again, it is not reasonable to expect Pilgrim Watch to answer this question because, as explained in The Dissenting Opinion of Administrative Judge Ann Marshall Young, at 38, in the Memorandum and Order (Ruling on Motion to Dismiss Petitioners contention 3 Regarding Severe Accident Mitigation Alternatives), October 30, 2007:
In this proceeding, Intervenors provide the reasoned statements of several well-qualified experts. They do not, it is true, provide any results of calculations proving the negative of Entergys sensitivity analysis. But such a requirement  or anything approaching its essential equivalent  is unreasonable, given the extremely complex, expensive, and time-consuming nature of the computer calculations that would be necessary to do this, which even the Applicant, with its relatively greater resources, has called impractical. See Entergys Motion for Summary Disposition of Pilgrim Watch Contention 3 at 13 (May 17, 2007).
The accepted contention called for further analysis - i.e., further analysis by the Applicant not the Petitioner.
III.      Beyond Meteorology Even if a majority of the Board should find that meteorological concerns/issues ... could, on its own, credibly alter the Pilgrim SAMA analysis conclusions, the economic issues that might be open for adjudication have, once again, been so drastically limited that the result is preordained.
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Evidence showed that the most significant economic costs - clean/up, decontamination, and health - have been forced off the table. All that Pilgrim Watch even might be permitted to show about costs has been limited to business and tourism in Plymouth County.
No matter what weather, or what loss of business and tourism in Plymouth County, might be input into the MACCS2 code, a downstream portion of the code (the MACCS2s so-called output file) would reduce consequences to such a low level that there would be no change in the SAMA conclusion. The MACCS2 output file uses Entergys chosen ill-chosen mean average rather than the 95th or higher percentile permitted by the code, averages the consequences produced by EARLY and CHRONC (using a discount figure when prices increase over time) and then applies a ridiculously small probability, again selected by Entergy. The result, as intended by Entergy, is that no significant SAMAs will be required.32 The prior orders of this Board have precluded Pilgrim Watch from proving real costs. At the beginning of these proceedings the Board rewrote Contention 3 in ways that, at least in the view of the majority, eliminated any discussion of probability, and any discussion of the code other than a few particular inputs; the majoritys Summary Disposition Order and its Order of November 23, 2010 took Entergys misuse of the code off the table. These decisions were wrong, and subject to appeal, but they unfortunately (for both Pilgrim Watch and the public) have made this remand hearing meaningless.
32 Consequences necessarily depend on the size of an accident, the source input into the code. This critical input, chosen by Energy, has also been taken off the table.
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IV.          The Boards Prior Orders In attached Appendix I, Pilgrim Watch has outlined prior decisions of this Board to show how they have removed from consideration any real chance that this proceeding will meet the NRCs stated goal of ensur[ing[ adequate protection of the public health and safety and the environment. (See NRC Strategic Plan, Fiscal Years 2008-2010, At-A-Glance). The NRC says that its MISSION is to [l]icense and regulate the Nations civilian use of byproduct, source, and special nuclear materials to ensure adequate protection of public health and safety ... and protect the environment, and that its desired Strategic Outcomes include (Id.):
x  Prevent the occurrence of any nuclear reactor accidents.
x  Prevent the occurrence of any inadvertent criticality events.
x  Prevent the occurrence of any acute radiation exposures resulting in facilities.
x  Prevent the occurrence of any releases of radioactive materials that result in significant radiation exposure.
x  Prevent the occurrence of any releases of radioactive materials that cause significant environmental impacts.
This Boards own brochure says that Congress made it possible for the public to get a full and fair hearing on nuclear matters.
Pilgrim Watch respectfully submits that, in the aggregate, the prior decisions of this Board have created a situation that is inconsistent with the NRCs fundamental goals, and that that has failed to provide for ... a full and fair hearing.
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Pilgrim Watchs Contention 3 squarely raised important issues that are consistent with ensur[ing] adequate protection of public health and safety ... and protect[ion of] the environment. Originally filed Contention 3 (Request For Hearing and Petition To Intervene By Pilgrim Watch, May 25, 2006 (Hearing Request), p 26) was:
Contention 3: The Environmental Report is inadequate because it ignores the true off-site radiological and economic consequences of a severe accident at Pilgrim in its Severe Accident Mitigation Alternatives (SAMA) analysis 3.0 Contention The Environmental Report inadequately accounts for off-site and economic costs in the SAMA analysis of severe accidents. By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. (Italics added)
Pilgrim Watchs Hearing Request explained numerous ways in which Entergy misused the MACCS2 code,and in which its Environmental Report inadequately accounts for off-site health exposure and economic costs in its SAMA analysis of severe accidents.
As shown in Appendix I, prior decisions of this Board have (improperly in PWs view) taken essentially everything important to protecting the public and the environment off the table. The result has been effectively to ensure that this proceeding will not fulfill the NRCs stated Mission or accomplish the NRCs stated Strategic Objectives. The Board should review its prior orders, and particularly its October 16, 2006 Order that threw out the heart of Pilgrim Watchs original contention, portions of the Majoritys Summary Disposition Order that further limited rewritten Contention 3, and its Order of Novembr 23, 2010.
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In her dissent from the majoritys order granting summary disposition, Judge Young recognized the importance of insuring the public understand that fairness and justice had been done:
Even if in the end Entergy were, in such a hypothetical situation, to prevail on all points, the hearing process, appropriately and flexibly handled so as to assure reasonable and meaningful efficiencies, would (as it should always) ultimately allow for differences between the testimony of the parties various experts on relevant issues to be addressed with all interested parties in one room, without the need for the filing of perhaps so much paper, and with the ability to address much more directly and concisely relevant questions to clarify matters in dispute. Consequently, even if Intervenors lost on these matters, they might well walk away with greater understanding of the issues and a greater sense that fairness and justice had been done. While the resulting increase in public confidence and trust in the NRC adjudication process may not be measurable, I would expect that this would benefit as well from allowing a hearing on the matters of public concern at issue in Contention 3 (at 43, italics added)33 One unfortunate, and perhaps unforseen, result of the Boards prior orders is that licensee applicants have been citing the orders to create the impression that the Board decided issues against PilgrimWatch on their merits, rather than only as a matter of pleading Pilgrim Watch moves that this Board revisit its prior orders and ensure that their effect is consistent with the NRCs stated goals, Mission, and Strategic Outcomes, and provides the full and fair hearing promised by the Boards own brochure.
33 See also fn 47, p 39: [I]n my view my colleagues apply a standard that overlooks or ignores gejuine issues of material fact the Intervenors present throug reputable experts, as well as considerations of practical reality and fundamental fairness.
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V.          What Pilgrim Watch Would Have Proved But for the Prior Orders If Pilgrim Watch had been allowed to argue issues that were properly brought forward in its initial Motion to Intervene, May 25, 2006, and it would have offered evidence to prove that:
(i)      Entergys use of probabilistic modeling, (ii)    Entergys assumption of a small sized accident, instead of what is commonly understood as a severe accident, (iii)    Entergys use of the MACCS2 code, (iv)    Entergys use of the mean consequence values, and (v)      The Boards and Commissions elimination of the significant economic costs, especially cleanup and health costs, both individually and collectively improperly watered- down consequences and permitted Entergy to avoid having to take mitigation steps that would have been required by a proper SAMA analysis.
A. Probabilistic Modeling If PW had been allowed to dispute Entergys use of probabilistic modeling in its SAMA analysis, we would have introduced evidence to show the following:
: 1. The probability/likelihood of a severe accident used by Entergy in its SAMA analysis was far too low and was intentionally chosen to insure that Entergy would not have to make any significant mitigation steps.
: 2. By using probabilistic modeling and incorrect parameters in its SAMA analysis Entergy arrives at a result that downplays the likely consequences of a severe accident at PNPS, and thus incorrectly discounts possible mitigation alternatives.
This could have enormous implications for public health and safety because a 55
potentially cost effective mitigation alternative might not be considered that could prevent or reduce the impacts of that accident. Petitioners allege the Environmental Report's SAMA analysis is deficient and the deficiency could significantly impact health and safety.
: 3. Entergys SAMA analysis multiplied mean consequences by a weighted too-low probability to improperly insure that, no matter how large real economic consequences might be, the consequences supposedly balanced against costs in the SAMA analysis would be trivialized.
: 4. Permitting an Applicant to simply multiply all consequences of an accident by extremely low probability and thus reject all possible mitigation as too costly, is inconsistent with the NRCs supposedly required Severe Accident Mitigation Analysis.
: 5. It is widely recognized that probabilistic modeling can underestimate the deaths, injuries, and economic impact likely from a severe accident. By multiplying high consequence values with low probability numbers, the consequence figures appear far less startling.
For example a release that would cause 100,000 cancer fatalities would only appear to cause 1 cancer fatality per year if the associated probability of the release were 1/100,000 per year.
: 6. NRC in the GEIS recognized what happens when probability weighted consequences are used by the Applicant. It said that, The probability weighted consequences of atmospheric releases, fallout onto open bodies of water, releases to ground water, and societal and economic impacts from severe accidents are small for all plants. However, alternatives to mitigate severe accidents must be considered for all plants that have not considered such alternatives. See § 51.53(c)(3)(ii)(L). (10 C.F.R. Part 51, Subpart A, Appendix B, Table B-1, Issue 76.) (Emphasis added) 56
: 7. This statement was misinterpreted by Entergy, NRC Staff, the Board, and Commission.        Properly understood, the GEIS does not say that accident consequences        small; rather it simply says that probability weighted consequences insures that they will appear to be small.
: 8. The GEIS supports PWs contention that Entergys choice to multiply the mean by the weighted probability in the MACCS2 Output File resulted in minimizing the true consequences in Pilgrims SAMA analysis.
: 9. Probability may be taken into consideration, but it must be taken with caution, particularly as it relates to Pilgrims SAMA analysis. Kamiar Jamalis (DOE Project Manager for Code Manual for MACCS2) Use of Risk Measures in Design and Licensing Future Reactors,34 explains that PRA uncertainties are so large and so unknowable that it is a huge mistake to use a single number coming from them for any decision regarding adequate protection. Examples of these uncertainties include probabilistic quantification of single and common-cause hardware or software failures, occurrence of certain physical phenomena, human errors of omission and commission, magnitudes of source terms, radionuclide release and transport, atmospheric dispersion, biological effects of radiation, dose calculations, and many others. (Jamali, Pg., 935) (Emphasis added)
: 10. Probability analysis has other pitfalls. Human error is not considered in PRAs. PRAs project into the future and come up with some very small number that an accident scenario only is likely to occur in so many hundreds-to-thousands of years. But no reactor has operated 45 or more years so actual experience is absent to base predictions.
Uncertainty must be respected by making certain that appropriate and up-to-date methods and assumptions are used in the analysis. Entergy failed to do so.
34 Appendix 3, Exhibit 14 57
B. Amount of Radioactive Release - Size of Accident If PW had been permitted to do so, it would have presented evidence that
: 1. Entergy limited its SAMA analysis to avoid having to take proper mitigation steps by assuming, and inputting into the MACCS2 code.35
: 2. A proper source input would have shown that more SAMAs would be justified.
: 3. Entergy severely and improperly minimized the likely amount of radiation that could be released in a severe accident by (i) assuming, for example, a relatively small release of CsI from the core; (ii) ignoring any release from the spent fuel pool; (iii) and using a source code that underestimated consequence.
: 4. The source terms used by Entergy to estimate the consequences of severe accidents (radionuclide release fractions generated by the Modular Accident Analysis Progression, MAAP36) code, have not been validated by NRC. They are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.
: 5. MAAP generates lower release fractions than those derived and used by NRC in studies such as NUREG-1150.              A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results 35 Expert
==Reference:==
Dr. Edwin Lyman would conduct for PW a similar analysis as provided to Riverkeeper in Riverkeeper, Incs Request for Hearing and Petition to Intervene in the License Renewal Proceedings of Indian Point Nuclear Plant, November 30, 2007, pgs., 68-9. Dr. Lymans expert testimony is attached, Appendix 4, Exhibit
: 12. Because Entergy also used MAAP at Pilgrim, comments made by Dr. Lyman in that declaration are applicable.
36 See, for example, ER. E.1.2.1 58
reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable scenarios.
: 6. The NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR.
: 7. The differences in the release fractions are primarily attributable to the use of the different codes in the two analyses. 37
: 8. The use of source terms generated by MAAP, a proprietary industry code that has not been independently validated by NRC, leads to anomalously low consequences when compared to source terms generated by NRC staff.
: 9. The NRC has been aware of this discrepancy for at least two decades. In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without 37 See J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.
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performing controlled comparisons for identical boundary conditions and input data.38 We are unaware of NRC having performed such comparisons.
: 10. The NUREG-1465 source term was also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.39 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.40
: 11. Entergy should not have used a MAAP-generated source terms in its SAMA analysis.
Core Release If permitted to do so, PW would have presented evidence that Entergy ignored the consequences of a severe accident,41 for example, that
: 1. Pilgrim has the potential to release more than twice the amount of Cs-137 than was released at Chernobyl. The amount of Cs-137 released during Chernobyl in 1986 was 2,403,000 curies; the amount of Cs-137 in Pilgrims Core during license extension will be 190,000 TBq or 190,000 X 27 Ci = 5,130,000 curies.
: 2. Entergys MACCS2 model apparently estimated costs based on a release (i) of noble gases in the core inventory and (ii) a small fraction of the core inventory of CsI.
[PNPS Radionuclide Release Category Summary, Figure E.1.1].
38 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.
39 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.
40 J. Schaperow (2002), op cit.
41 See for example, Pilgrim Watchs Brief In Response To CLI-09-11 (Requesting Additional Briefing), June 25, 2009, Pg.,20-21; and Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007,Pgs 89-90; Declaration Jan Beyea and Report To The Massachusetts Attorney General On The Potential Consequences Of A Spent-Fuel-Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, Ph.D., May 25, 2006, Pg, 94 -
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Magnitude of Release: Source term results from previous risk studies suggest that categorization of release magnitude based on cesium iodide (CsI) release fractions are appropriate [Reference E.1-5]. The CsI release fraction indicates the fraction of in-vessel radionuclides escaping to the environment. (Noble gas release levels are non-informative since release of the total core inventory is essentially complete given containment failure.) The source terms were grouped into four distinct radionuclide release categories or bins according to release magnitude as follows:
(1) High (HI) - A radionuclide release of sufficient magnitude to have the potential to cause early fatalities. This implies a total integrated release of 10% of the initial core inventory of CsI
[Reference E.1-5]. (1) High (HI) - A radionuclide release of sufficient magnitude to have the potential to cause early fatalities. This implies a total integrated release of >10% of the initial core inventory of CsI [Reference E.1-5].(2) Medium (MED) - A radionuclide release of sufficient magnitude to cause near term health effects. This implies a total integrated release of between 1 and 10% of the initial core inventory of CsI [Reference E.1-5]. (3) Low (LO) - A radionuclide release with the potential for latent health effects. This implies a total integrated release of between 0.001% and 1% of the initial core inventory of CsI. (4) Negligible (NCF) - A radionuclide release that is less than or equal to the containment design base leakage. This implies total integrated release of <0.001% of the initial core inventory of CsI.
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Spent Fuel Pool Release If permitted to do so, PW would have presented evidence that:
: 1. A spent fuel pool fire could release more than 44,010,000 curies of Cs-137, an amount that is 8 times more than a core release. Further a spent fuel pool fire would result in releases going higher into the air and thereby significantly impacting locations at greater distance with denser populations.
: 2. Accidents are severe by reason of their consequence, not because of where originate
[NUREG-1437, GEIS, Section 5]. If the costs of an accident resulting from a pool fire were considered, the value of SAMAs would rise significantly.              Dr. Beyea estimated the cost of a 10% release from a spent pool fire to be $105-175 billion dollars; and that a 100% release of C-137 would cost between $342-$488 billion.
(Beyea, 10). In contrast, Entergy modeled only the release of a relatively small amount of C-137 from the reactor core.
: 3. A severe accident from the spent fuel pool at Pilgrim resulting from either human error, mechanical failure or an act of malice is reasonably foreseeable. The offsite cost risk of a pool fire is substantially higher than the offsite cost of a release from a core-damage accident.
: 4. SAMAs designed to avoid or mitigate conventional accidents may be different than SAMAs designed to avoid or mitigate spent fuel accidents. Moreover, the radiological consequences of a spent-fuel-pool fire are significantly different from the consequences of a core-damage accident.
: 5. There are significant potential interactions between the pool and the reactor in the context of severe accidents at Pilgrim. The spent-fuel pool is located in the attic of the 62
main reactor building, outside containment. It shares essential support systems with the reactor. There could be at least three types of interactions between the pool and reactor.42 First, a pool fire and a core-damage accident could occur together, with a common cause. For example, a severe earthquake could cause leakage of water from the pool, while also damaging the reactor and its supporting systems to such an extent that a core-damage accident occurs. Second, the high radiation field produced by a pool fire could initiate or exacerbate an accident at the reactor by precluding the presence and functioning of operating personnel. Third, the high radiation field produced by a core-damage accident could initiate or exacerbate a pool fire, again by precluding the presence and functioning of operating personnel. Many core-damage sequences would involve the interruption of cooling to the pool, which would call for the presence of personnel to provide makeup water or spray cooling of exposed fuel.
The third type of interaction was considered in a license-amendment proceeding in regard to expansion of spent-fuel-pool capacity at the Harris nuclear power plant.
Such accidents are conceivable and would result in a very high magnitude of release.
: 6. 10 C.F.R. &sect; 51.53(c)(3)(ii)(L), does not provide a definition of severe accidents.
: 7. GEIS43 which provides the factual background for the SAMA requirement in the regulations, does define a severe accident.
The term "accident" refers to any unintentional event outside the normal plant operational envelope that results in a release or the potential for release of radioactive materials into the environment. Generally, the U.S.
42 Dr. Gordon Thompson, Risks of Pool Storage of Spent Fuel at Pilgrim Nuclear Power Station and Vermont Yankee, A Report for the Massachusetts Attorney General by IRSS, May 2006, Pgs., 12, 16. NRC Electronic Library, Adams Accession Number ML061630088 43 See NUREG-1437, Generic Environmental Impact Statement for License Renewal of Nuclear Plants (May 1960)
[hereinafter GEIS]; Final Rule, Environmental Review for Renewal of Nuclear Power Plant Operating Licenses, 61 Fed. Reg. 28, 467 (June 5, 1960, amended by 61 Fed. Reg. 66, 537 (Dec. 18, 1996); 10 C.F.R. Pt. 51, Subpart A, Appendix B n.1) 63
Nuclear Regulatory Commission (NRC) categorizes accidents as "design basis" (i.e., the plant is designed specifically to accommodate these) or "severe" (i.e., those involving multiple failures of equipment or function and, therefore, whose likelihood is generally lower than design-basis accidents but where consequences may be higher), for which plants are analyzed to determine their response. The predominant focus in environmental assessments is on events that can lead to releases substantially in excess of permissible limits for normal operation. Normal release limits are specified in the NRC's regulations (10 C.F.R. Part 20 and 10 C.F.R. Part 50, Appendix A). GEIS, 5.2.1. Italics added
: 8. According to Section 5.2.1 of NUREG 1437 General Characteristics of Accidents, the term accident refers to any unintentional event outside the normal plant operational envelope that results in a release or the potential for release of radioactive materials into the environment and severe  [includes] those involving multiple failures of equipment or function and, therefore, whose likelihood is generally lower than design basis accidents but where consequences may be higher . . . (emphasis added). This section recognizes the potential for a severe accident in which there are releases substantially in excess of permissible limits for normal operation.
: 9. Section 5 focuses on potential consequences to determine whether or not a potential accident is severe - and thus within the scope of a Severe Accident Mitigation Analysis.
: 10. Section 6 of the GEIS with Section 5. Section 6 deals with normal operations (see, for example, section 6.1: Accidental releases  could conceivable result in releases that would cause moderate or large radiological impacts. Such conditions are beyond the scope of regulations controlling normal operations. (Emphasis added).
: 11. Section 5, not Section 6, deals with severe accidents. The question is not whether the source of the Severe Accident is the first or second largest inventory of radioactive 64
materials. Nothing in Section 5 excludes severe accidents involving what at Pilgrim Station is the largest inventory of radioactive materials - the spent fuel pool.
Use of the MACCS2 Code If permitted to do so, PW would have presented evidence that Entergy improperly used the MACCS2 code to reduce the supposed consequences of an improperly assumed accident and, thus, mitigation steps that Entergy properly should be required to take. More particularly, PW would have presented evidence showing:
: 1. No NRC regulation requires the use of the MACCS2 code, or any other particular code, and there other codes available.
: 2. The code is not Quality Assured.44 The MACCS & MACCS2 codes were developed for research purposes not licensing purposes -for that reason they were not held to the QA requirements of NQA-a (American Society of Mechanical Engineering, QA Program Requirements for Nuclear Facilities, 1994). Rather they were developed using following the less rigorous QA guidelines of ANSI/ANS 10.4. [American Nuclear Standards Institute and American Nuclear Society, Guidelines for the Verification and Validation of Scientific and Engineering Codes for the Nuclear Industry, ANSI/ANS 10.4, La Grange Park, IL (1987).
: 3. In addition to the meteorological inputs discussed above, important code input parameters include source, average (cumulative distribution function), probability, and a discount rate applied in CHRONC.
44 Chanin, D.I. (2005), "The Development of MACCS2: Lessons Learned," [written for:] EFCOG Safety Analysis Annual Workshop Proceedings, Santa Fe, NM, April 29-May 5, 2005. Full text: the development of maccs2.pdf (154 KB), revised 12/17/2009. http://chaninconsulting.com/index.php?resume. (Attachment 5, Exhibit 4) 65
: 4. Source is chosen by Entergy and input to ATMOS. ATMOS outputs, based on Entergys chosen source, are input into both EARLY and CHRONC which determine consequences of an accident from Entergys chosen source. Entergy chose an unrealistically low source input for the purpose of avoiding having to take mitigation steps that would have to be taken if a realistic source input was used.
: 5. A discount rate is chosen by Entergy and input to CHRONC, which in determining consequences applies the discount rate to property that must be condemned. A discount makes little sense. Properties appreciate over 20 years, not depreciate.
: 6. The type of average and probability of an accident are also chosen by Entergy. The Output file averages consequences from EARLY and CHRONC and permits the user to average using any one of several percentiles, including mean, 90th percentile, and 95th percentile. Entergy chose mean for the purpose of avoiding having to take mitigation steps that would have to be taken if a higher, i.e., 90th or 95th percentile had been chosen.
: 7. Entergy failed to consider the uncertainties in its consequence calculation resulting from meteorological variations by only using mean values (LRA, Appendix E.1.5.3) for population dose and offsite economic cost estimates. If PW had been allowed to show the impact from using different statistical analyses, more SAMAs would have come into play.
: 8. In the License Renewal GEIS refers repeatedly to the 95th percentile of the risk uncertainty distribution as an appropriate upper confidence bound in order not to underestimate potential future environmental impacts.45 45 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol. 1, May 1996, Section 5.3.3.2.1.
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: 9. The consequence calculation, as carried out by the MACCS2 code, generates a series of results based on random sampling of a years worth of weather data. The code provides a statistical distribution of the results. Based on calculations done at other reactors such as Indian Point, the ratio of the 95th percentile to the mean of this distribution is typically a factor of 3 to 4 for outcomes such as early fatalities, latent cancer fatalities and off-site economic consequences. 46
: 10. The Output file also multiplies the consequences resulting from Entergys chosen consequence percentile by an assumed probability of an accident, which is also chosen by Entergy.          Entergy improperly assumed, and chose, an extremely low probability for the purpose of avoiding having to take mitigation steps that would have to be taken if a probability that was realistic and would provide protection to the public had been chosen.
Cleanup/Decontamination, Health and Other Costs If permitted to do so, Pilgrim Watch would have presented evidence that Entergy, severely minimized decontamination and clean-up costs47, health costs48 (that includes inaccurately 46 Dr. Edwin S. Lyman, Senior Staff Scientist, Union of Concerned Scientists report commissioned by Riverkeeper, Inc., November 2007, A Critique of the Radiological Consequence Assessment Conducted in Support of the Indian Point Severe Accident Mitigation Alternatives Analysis; available at NRC Electronic Library, Adams Accession Number ML073410093, Exhibit 12 47 Decontamination/Cleanup, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg., 90-; And Accompanying Declaration Of David L.
Chanin In Support Of Pilgrim Watch's Response Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, (Maccs2 Support Forum, August 23, 2006 & January 23, 2007) June 5, 2007; and Pilgrim Watchs Brief in Response to CLI-09-11 (Requesting Additional Briefing) June 25, 2009, Pgs., 12-13 48 Health Costs, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007,Pg.,7,8,18,23,32-37,46-48,66, 81-86; and Declaration Dr. Jan Beyea (Report To The Massachusetts Attorney General On The Potential Consequences Of A Spent-Fuel-Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, Ph.D., May 25, 2006), Pgs., 6,7,13,15; and Pilgrim Watchs Brief in Response to CLI-09-11 (Requesting Additional Briefing) June 25, 2009, Pgs.,12, 19. Evacuation time estimates incorrect resulting in increased health costs as fewer people evacuate in a timely manner: see : Pilgrim 67
modeling evacuation time estimates), and minimized and ignored a myriad of other economic costs,49 both within and outside of Plymouth County, that belong in a SAMA analysis.
For example, with respect to the area potentially affected by a severe accident at PNPS, Pilgrim Watch would have presented evidence that:
: 1. The costs of a radiological accident at PNPS would not be limited to Plymouth County, but would affect the Commonwealth of Massachusetts, Southeastern Massachusetts, and three other counties.
: 2. Both Providence and Boston are within 45 miles PNPS and could be sustain significant radiological damage if a severe accident should occur at PNPS.
With respect to cleanup, Pilgrim Watch would have presented evidence showing that:
: 1. Cleanup costs are the Elephant in the Room that NRC and Entergy want to avoid.
Proper clean-up would result in major offsite costs requiring the addition of a large number of mitigations.
: 2. The MACCS2 Decontamination Plan is described in part in the Code Manual for MACCS2: Volume I, Users Guide (NUREG/CR-6613, Vol. 1) Prepared by D.
Chanin and M.I. Young, May 1998. Section 7.5 Decontamination Plan describes some of the assumptions. It says at 7-10 that, Many decontamination processes (e.g., plowing, fire hosing) reduce groundshine and resuspension doses by washing surface contamination down into the ground. Since these processes may not move contamination out of the root zone, the WASH-1400 based economic cost model of Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007,Pg.,58-71 and Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg., 11,19-20.
49 Other Economic Costs, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg.,72-91; Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg.,10-12, 22.
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MACCS2 assumes that farmland decontamination reduces direct exposure doses to farmers without reducing uptake of radioactivity by root systems.
Thus decontamination of farmland does not reduce the ingestion doses produced by the consumption of crops that are contaminated by root uptake.
: 3. The MACCS2 cleanup assumptions used by Entergy are directly based on WASH-1400; WASH-1400, in turn, was based on clean up after a nuclear explosion.
: 4. Cleanup after a nuclear bomb explosion is not comparable to clean up after a nuclear reactor accident; Entergys apparent assumption that the two are comparabile severely underestimated cleanup costs. Nuclear explosions result in larger-sized radionuclide particles; reactor accidents release small sized particles. Decontamination is far less effective, or even possible, for small particle sizes. Nuclear reactor releases range in size from a fraction of a micron to a couple of microns; whereas nuclear bomb explosions fallout is much larger- particles that are ten to hundreds of microns. These small nuclear reactor releases can get wedged into small cracks and crevices of buildings.
: 5. WASH-1400s nuclear weapon clean up experiments involved cleaning up fallout involving large mass loading where the there was a small amount of radioactive material in a large mass of dirt and demolished material. Only the bottom layer will be in contact with the soil and the massive amount of debris can be swept up with brooms or vacuums resulting in a relatively effective, quick and cheap cleanup that would not be the case with a nuclear reactors fine particulate. (CLI-10-11, Pg., 29-30)
: 6. A weapon explosion results in non-penetrating radiation so that workers only require basic respiration and skin protection. This allows for cleaning up soon after the event.
In contrast a reactor release involves gamma radiation and there is no gear to protect 69
workers from gamma radiation. Therefore cleanup cannot be expedited and decontamination is less effective with the passage of time.
: 7. Entergys cost model ignored radioactive waste disposal. In a weapons event, the waste could be shipped to Utah or to the Nevada Test Site. The Greater- than- Class C waste expected in a reactor accident would not have a repository likely available to receive such a large quantity of material in the foreseeable future. Also, the costs incurred for safeguarding the wastes and preventing their being re-suspended are not accounted for in the model. Even optimistically assuming a repository becoming available, (Utah site is approximately one-square mile) it seems unlikely that there would be a sufficient quantity of transport containers and communities not objecting to the hazardous materials going over their roads and through their communities.
: 8. The Users Guide describes decontamination processes as plowing and fire hosing. CERLA, EPA and local authorities would not allow use of those methods.
Fire hosing and plowing do not decontaminate, it simply moves the contamination from one place to another - only to reappear again later in groundwater, resuspended into the air, or in food. Therefore cleanup will take far longer and be more expensive than assumed by Entergy; and its success (defined as returning to pre-accident status) unlikely.
: 9. Also apparently missing from consideration is that forests, wetlands and shorelines cannot realistically be cleanup and decontaminated. The area within 50-miles of Pilgrim Station consists of miles of beaches, rivers, lakes, ponds, bogs, wetlands, forests and park land Additionally, urban areas will be considerably more expensive and time consuming to decontaminate and clean than rural areas.
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: 10. The US Department of Homeland Security has commissioned studies for the economic consequences of a Rad/Nuc attack. Much more deposition would occur in reactor accident, magnifying consequences and costs, but there are important lessons to be learned from these studies. Barbara Reichmuths study, Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost, 2005,50 Table 1 Summary Unit Costs for D &D (Decontamination and Decommissioning) Building Replacement and Evacuation Costs provides estimates for different types of areas from farm or range land to high density urban areas.
Reichmuths study also points out that the economic consequences of a Rad/Nuc event are highly dependent on cleanup standards: Cleanup costs generally increase dramatically for standards more stringent than 500 mrem/yr.
: 11. Currently the NRC and EPA have not agreed on a cleanup standard.51 The potential standard appears to range from 15 mrem/yr to 5 rem/yr. The General Accounting Office (GAO) reports that the current EPA and NRC cleanup standards differ and these differences have implications for both the pace and ultimate cost of cleanup.52 Entergy should have used the EPA (15 mrem/yr) standard in determining clean-up costs; it did not.
50 Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 (Attachment 6, Exhibit 8) 51 See Pilgrim Watchs Request For Hearing On New Contention; the information upon which this contention is available from a trade publication INSIDE EPA; please see report and supporting documents at http://environmentalnewsstand.com/Environmental-NewsStand-General/Public-Content/agencies-struggle-to-craft-offsite-cleanup-plan-for-nuclear-power-accidents/menu-id-608.html 52 GAO, Radiation Standards Scientific Basis Inconclusive, and EPA and NRC Disagreement Continues, June 2004 71
: 12. A similar study was done by Robert Luna, Survey of Costs Arising from Potential Radionuclide Scattering Events,.53 concluded that, the expenditures needed to recover from a successful attack using an RDD type device are likely to be significant from the standpoint of resources available to local or state governments Even a device that contaminates an area of a few hundred acres (a square kilometer) to a level that requires modest remediation is likely to produce costs ranging from
                  $10M to $300M or more depending on the intensity of commercialization, population density, and details of land use in the area. (Luna, Pg., 6)
: 13. A severe accident at Pilgrim will result in huge costs, not accounted for by Entergy, largely because the type and magnitude of radionuclides released in a reactor accident are very different than those released by a RDD type device as explained directly above, 3-5.
: 14. In place of the outdated decontamination costs figure in the MACCS2 code, the SAMA analysis for Entergy should have incorporated the analytical framework contained in the 1996 Sandia National laboratories report concerning site restoration costs54 as well as Lunas and Reichmuths methodology and studies examining Chernobyl.
: 15. The Sandia Site restoration study analyzed the expected financial costs for cleaning up and decontaminating a mixed-use urban land and Midwest farm and range land. The study was commissioned by DOE to estimate activities 53 Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ (Attachment 7, Exhibit 9) 54 Site Restoration: Estimation of Attributable Costs from Plutonium-Dispersal Accidents, SAND96-0957, David Chanin, Walt Murfin, UC-502, (May 1996) 72
likely to be involved in the decontamination of an accident involving the dispersal of plutonium. Although there would be many differences in a nuclear reactor accident, the methodology and conclusions to estimate costs are directly useful.
: 16. The Sandia Site study recognized that earlier estimates (those incorporated in WASH-1400 and incorporated in MACCS2) of decontamination costs are incorrect because they examined fallout from nuclear explosion of nuclear weapons that produce large particle sizes and high mass loadings.
: 17. For an extended decontamination and remediation operation in a mixed-use urban area with an average population density, Site restoration (1996) predicted a cleanup cost of $311,000,000 per square km using offsite disposal and
    $309,000,000 per square km using on-site disposal. (Site restoration, Pg., 6-5)
: 18. The costs would be much higher today with inflation and for example for the metropolitan areas of Boston and Providence considering that they are tourist, educational, transportation, and financial centers. The economic losses stemming from the stigma effects of a severe accident would be staggering.
The Sandia Site restoration study further says, In comparing the numbers of cancer health effects that could result from a plutonium-dispersal accident to those that could result from a severe accident at a commercial nuclear power plant, it is readily apparent that the health consequences and costs of a severe reactor accident could greatly exceed the consequences of even a worst- case plutonium-dispersal accident because the quantities of radioactive material in nuclear weapons are a small fraction of the quantities present in an operating nuclear power plant. (Site restoration, Pg., 2-3, 2-4) 73
: 19. Under decontamination costs, Entergy lists the costs of farm and non-farm decontamination and the value of farm and nonfarm wealth. However nowhere is there a discussion of the loss of, and costs to remediate the economic infrastructure that make business, tourism and other economic activity possible.
: 20. Economic infrastructure is the basic physical and organizational structures needed for the operation of a society or enterprise, or the services and facilities necessary for an economy to function. The term typically, and as used by PW, refers to the technical structures that support a society, such as roads, water supply, sewers, power grids telecommunications, and so forth. Viewed functionally, infrastructure facilitates the production of goods and services; for example, roads enable the transport of raw materials to a factory, and also for the distribution of finished products to markets. Also, the term may also include basic social services such as schools and hospitals.
: 21. Entergy appears to ignore the indirect economic effects or the multiplier effects. For example, depending on the business done inside the building contaminated, the regional and national economy could be negatively impacted.
A resulting decrease in the areas real estate prices, tourism, and commercial transactions could have long-term negative effects on the regions economy.
: 22. Entergy should have been required to take all of these real cleanup costs into account; but the Board and Commissions decisions resulted in their not being required to do so and as a result the public will not get the safety enhancements that we deserve.
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: 23. The following illustrates the significant effect of Entergys failure properly to consider the costs of cleanup:
1987 Radiological Accident in Goiania, Brazil55 In September 1987, a hospital in Goiania, Brazil, moved to a new location and left its radiation cancer therapy unit behind. Found by scrap metal hunters, it was dismantled and the cesium chloride source containing 1,400 Ci of cesium-137 was removed. Pieces were distributed to family and friends, and several who were intrigued by the glow spread it across their skin. Eleven days later, alert hospital staff recognized symptoms of acute radiation syndrome in a number of victims.
The ensuing panic caused more than 112,000 people - 10% of the population - to request radiation surveys to determine whether they had been exposed. At a makeshift facility in the citys Olympic Stadium, 250 people were found to be contaminated. 28 had sustained radiation-induced skin injuries (burns), while 50 had ingested cesium, so for them the internal deposition translated to an increased risk of cancer over their lifetime. Tragically, 2 men, 1 woman, and 1 child died from acute radiation exposure to the very high levels of gamma radiation from the breached source.
In addition to the human toll, contamination had been tracked over roughly 40 city blocks. Of the 85 homes found to be significantly contaminated, 41 were evacuated and 7 were demolished. It was also discovered that through routine travels, within that short time people had cross-contaminated houses nearly 100 miles away.
Cleanup generated 3,500 m3 radioactive waste at a cost of $20 million.
The impacts of this incident continued beyond the health and physical damage to profound psychological effects including fear and depression for a large fraction of the citys inhabitants.
Further, frightened by the specter of radioactive contamination, neighboring provinces isolated Goiania and boycotted its products. The price of their manufactured goods dropped 40% and stayed low for more than a month. Tourism, a 55 Revisiting Goiania: Toward a final repository for radioactive waste, IAEA Bulletin 1993,Rad waste 3,500 cubic meters,1270 to 1340 curies in waste,http://www.ead.anl.gov/pub/doc/rdd.pdf Exhibit 15 75
primary industry, collapsed and recent population gains were reversed by business regression. Total economic losses were estimated at hundreds of millions of dollars.
Health Costs With respect to health costs, Pilgrim Watch would have presented evidence showing that Entergys life lost value is much too low.
: 1. EPA values a life lost at $6.1 million (U.S.E.P.A., 1997, The Benefits and Costs of the Clean Air Act, 1970 to 1990, Report to US Congress (October), pages 44-45). Pilgrims ER assigns a value of $2000 per person rem.
: 2. The population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure is based on a deeply flawed analysis and seriously underestimates the cost of the health consequences of severe accidents.
: 3. Entergy underestimates the population-dose related costs of a severe accident by relying inappropriately on a $2000/person-rem conversion factor.            Entergys use of the conversion factor is inappropriate because it (a) does not take into account the significant loss of life associated with early fatalities from acute radiation exposure that could result from some severe accident scenarios; and (b) underestimates the generation of stochastic health effects by failing to take into account the fact that some members of the public exposed to radiation after a severe accident will receive doses above the threshold level for application of a dose- and dose-rate reduction effectiveness factor (DDREF).
: 4. Entergys $2000/person-rem conversion factor is apparently intended to represent the cost associated with the harm caused by radiation exposure with respect to the causation 76
of stochastic health effects, that is, fatal cancers, nonfatal cancers, and hereditary effects.56 The value was derived by NRC staff by dividing the Staffs estimate for the value of a statistical life, $3 million (presumably in 1995 dollars, the year the analysis was published) by a risk coefficient for stochastic health effects from low-level radiation of 7x10-4/person-rem, as recommended in Publication No. 60 of the International Commission on Radiological Protection (ICRP). (This risk coefficient includes nonfatal stochastic health effects in addition to fatal cancers.) But the use of this conversion factor in Pilgrims SAMA analysis is inappropriate in two key respects. As a result Entergy underestimated the health-related costs associated with severe accidents.
: 5. First, the $2000/person-rem conversion factor is specifically intended to represent only stochastic health effects (e.g. cancer), and not deterministic health effects including early fatalities which could result from very high doses to particular individuals.57 However, for some of the severe accident scenarios evaluated, large numbers of early fatalities could occur representing a significant fraction of the total number of projected fatalities, both early and latent. This is consistent with the findings of the Generic Environmental Impact Statement for License Renewal of Nuclear Plants (NUREG-1437).58 Therefore, it is inappropriate to use a conversion factor that does not include deterministic effects. According to NRCs guidance, the NRC believes that regulatory issues involving deterministic effects and/or early fatalities would be very rare, and can be addressed on a case-specific basis, as the need arises.59 Based on our estimate of the 56 U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy, NUREG-1530, 1995, p. 12.
57 U.S. NRC (1995), op cit., p. 1.
58 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol.
1, May 1996, Table 5.5.
59 U.S. NRC, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy (1995), op cit., p. 13.
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potential number of early fatalities resulting from a severe accident at Pilgrim, this is certainly a case where this need exists.
: 6. Second, the $2000/person-rem factor, as derived by NRC, also underestimates the total cost of the latent cancer fatalities that would result from a given population dose because it assumes that all exposed persons receive dose commitments below the threshold at which the dose and dose-rate reduction factor (DDREF) (typically a factor of 2) should be applied. However, for certain severe accident scenarios at Pilgrim evaluated by Entergy, we estimate that considerable numbers of people would receive doses high enough so that the DDREF should not be applied.60 This means, essentially, that for those individuals, a one-rem dose would be worth more because it would be more effective at cancer induction than for individuals receiving doses below the threshold. To illustrate, if a group of 1000 people receive doses of 30 rem each over a short period of time (population dose 30,000 person-rem), 30 latent cancer fatalities would be expected, associated with a cost of $90 million, using NRCs estimate of $3 million per statistical life and a cancer risk coefficient of 1x10-3/person-rem. If a group of 100,000 people received doses of 0.3 rem each (also a population dose of 30,000 person- rem), a DDREF of 2 would be applied, and only 15 latent cancer fatalities would be expected, at a cost of
        $45 million. Thus a single cost conversion factor, based on a DDREF of 2, is not appropriate when some members of an exposed population receive doses for which a DDREF would not be applied.
: 7. A better way to evaluate the cost equivalent of the health consequences resulting from a severe accident is simply to sum the total number of early fatalities and latent cancer 60 The default value of the DDREF threshold is 20 rem in the MACCS2 code input 78
fatalities, as computed by the MACCS2 code, and multiply by the $3 million figure. It is not reasonable to distinguish between the loss of a statistical life and the loss of a deterministic life when calculating the cost of health effects.
: 8. That Entergys estimates of how many lives might be lost are too low is also shown by the 1982 Sandia National Laboratory report.              Using 1970 census data, that report estimated the number of cancer deaths at Pilgrim as a consequence of a severe reactor accident61 in a severe accident to be 3,000 early fatalities within the first year and 30,000 peak early injuries within the first year.7,000 and early injuries 27,000. Peak fatalities were estimated by CRAC to occur within 20 miles of Pilgrim; and peak injuries to occur with 65 miles of Pilgrim from a core melt. (CRAC 2, Sandia, 198262)
: 9. The population of the affected area, no matter what model is used, has greatly increased during the intervening almost 40 years; SAMAs project forward to 2050 based on projected demographics. Entergy estimated the population within 50-miles (2032) to total 7489767. (LRA, Appendix E.1.5.2.1, Table E.1-13) Further CRAC was based on old, and now outdated, dose response models.
: 10. In Entergys SAMA analysis, cancer incidence was not considered; neither were the many other potential health effects from exposure in a severe radiological event (National Academy of Sciences, BEIR VII Report, 2005).
: 11. Entergys cost-benefit analysis ignored a marked increase in the value of cancer mortality risk per unit of radiation at low doses (2-3 rem average), as shown by recent studies 61 Sandia National Laboratory study for U.S. Nuclear Regulatory Commission, Calculation of Reactor Accident Consequences for U.S. Nuclear Power Plants (CRAC 2), 1981.
62 Calculation of Reactor Accident Consequences, U.S. Nuclear Power Plants (CRAC-2), Sandia National Laboratory, 1982.
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published on radiation workers (Cardis et al. 200563) and by the Techa River cohort (Krestina et al (200564). Both studies give similar values for low dose, protracted exposure, namely (1) cancer death per Sievert (100 rem). According to the results of the study by Cardis et al. and use of the risk numbers derived from the Techa River cohort the SAMA analyses prepared for Pilgrim needs to be redone. If done so properly a number of additional SAMAs that were previously rejected by the applicants methodology would become cost effective.
: 12. Cancer incidence and the other many health effects from exposure to radiation in a severe radiological event (National Academy of Sciences, BEIR VII Report, 2005) should have been considered; they were not. Neither did Entergy consider indirect costs. Medical expenditures are only one component of the total economic burden of cancer. The indirect costs include losses in time and economic productivity and liability resulting from radiation health related illness and death.
: 13. Applicants data into the code were unrealistically low. If correct evacuation times and assumptions regarding evacuation had been used, the analysis would show far fewer will evacuate in a timely manner, increasing health-related costs.
Evacuation Time Estimates  Health Costs If Pilgrim Watch had been permitted to do so, it also would have presented evidence showing:
63 Elizabeth Cardis, Risk of cancer risk after low doses of ionising radiation: retrospective cohort study in 15 countries. British Medical Journal (2005) 331:77. Referenced Beyea, Exhibit 2 64 Krestinina LY, Preston DL, Ostroumova EV, Degteva MO, Ron E, Vyushkova OV, et al. 2005.Protracted radiation exposure and cancer mortality in the Techa River cohort. Radiation Research 164(5):602-611.Exh 2 80
: 14. The KLD time estimates relied upon did not take into consideration in the analysis variables that would slow evacuation: shadow evacuation; evacuation time estimates during inclement weather coinciding with high traffic periods such as commuter traffic, traffic during peak commute times, holidays, summer beach/holiday traffic; notification delay delays because notification is largely based on sirens that cannot be heard in doors above normal ambient noise with windows closed or air conditioning systems operating.
: 15. The Applicant performed a sensitivity analysis that assumed no evacuation of the population in a severe accident and found only a small increase to the overall total accident dose risk and no change in economic risk. However, Entergys sensitivity studies did not provide useful information since the model on which they were based was flawed.
Myriad of Other Economic Costs
: 16. Entergy did not appear to include in their economic cost estimates the business value of property and the incurred costs such as costs required from job retraining, unemployment payments, and inevitable litigation. Entergy used an assumed value of non-farm wealth that appeared not justified by review of Banker and Tradesmen sales figures. Entergy underestimated Farm Value, for example, by not considering the value of the farm property for development purposes as opposed to agricultural; and farm land assessments are intentionally very low to encourage farming and open space.
If the Board Majority and Commission had not removed from consideration all the important factors initially brought forward by Pilgrim Watch, PW could have proved that Entergy 81
significantly minimized the consequences from a severe accident at Pilgrim to such a degree as to require substantial mitigation.
The magnitude of Entergys minimization of costs makes obvious that many SAMAs would be cost effective if the described defects in the analysis were addressed. In Duke Energy Corp.,
at 13, the board said that [w]hile NEPA does not require agencies to select particular options, it is intended to foster both informed decision-making and informed public participation, and thus to ensure the agency does not act upon incomplete information, only to regret its decision after it is too late to correct (citing Louisiana Energy Services (Claiborne Enrichment Center), CLI 3, 47 NRC 77, 88 (1998)). It then said if further analysis is called for, that in itself is a valid and meaningful remedy under NEPA.
In its Contention 3, PilgrimWatch pointed to a material deficiency in the Application -
Entergy has drastically under counted the costs of a severe accident that could have led to erroneously rejecting mitigation alternatives and the admitted contentions statement that further analysis is required is correct, and could produce a very different outcome of this proceeding.
Respectfully Submitted,
[Signed electronically]
Mary Lampert Pilgrim Watch, pro se 148 Washington Street Duxbury, MA 02332 781-934-0389 Mary.lampert@comcast.net January 3, 2011 82
Appendices 83
APPENDIX 1 A Review of Prior Board and Commission Decisions (2006-2010)
A. Request for Hearing.
Pilgrim Watch filed its Request For Hearing and Petition To Intervene By Pilgrim Watch on May 25, 2006        (Hearing Request). That Hearing Request set forth four Contentions.
Contentions 1, 2 and 4 have been rejected by the Board and Commission, and remain only for appeal.
Pilgrim Watchs Contention 3 squarely raised important issues that are consistent with ensur[ing] adequate protection of public health and safety ... and protect[ion of] the environment. Originally filed Contention was (Hearing Request p 26):
Contention 3: The Environmental Report is inadequate because it ignores the true off-site radiological and economic consequences of a severe accident at Pilgrim in its Severe Accident Mitigation Alternatives (SAMA) analysis 3.0 Contention The Environmental Report inadequately accounts for off-site and economic costs in the SAMA analysis of severe accidents. By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. (Italics added)
The complete inputs to the MACCS2 actually used by Entergy were not publicly available, and were not included in Entergys Environmental Report. Without knowing what parameters (e.g., probabilities, source term, consequences percentile) and other specific inputs chosen by Entergy, it [was] not possible [for PW] to fully evaluate the correctness of the
conclusions about Severe Accident Mitigation Alternatives. However, from what is included in the ER, Petitioners have been able to piece together some possible reasons that Entergys described consequences of a severe accident at Pilgrim look so small. (Hearing Request 34).
Based on the information available to it, Pilgrim Watchs Hearing Request pointed out a number of ways in which Entergy improperly used the MACCS2 code, and in which its Environmental Report inadequately accounted for off-site health exposure and economic costs in its SAMA analysis of severe accidents.
For example, the Hearing Request said at the outset that:
By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. [Emphasis added] (Hearing Request, 28)
Pilgrim Watch then said, not that probabiltic modeling was per se improper, but that Entergy had misused it to improperly minimize SAMAs:
x  [T]he likely impacts of a servere accident have been dramatically minimized by using probabilistic modeling which makes the costs of all severe accidents appear negligible. ...    [A]ny time an applicant multiplies an accident consequence by an extremely low probability number, the consequences will appear minute. (Hearing Request 29)
Appendix 1 - Page 2
x  It would make no sense for the NRC to require Severe Accident Mitigation Analysis if an applicant could simply multiply all consequences of an accident by extremely low probability and thus reject all possible mitigation as too costly. (Hearing Request 30).
As for the manner in which consequences were calculated, before being reduced to nothingness by Entergys choice of probability used in the codes Output File, the Hearing Request said, as quoted above, that Entergy has downplayed the consequences of a severe accident by incorrrectly inputting certain parameters into the modeling software. (Hearing Request 28). The Request went on to say:
In addition, Entergy has used incorrect input parameters, including meteorological, emerency response, and economic data, into a software model of limited scope.
(Hearing Request 29).
Because of the limited public information available showing what Entergy had actually done, Pilgrim Watchs use of including was not, could not be, and was not intended to be, inclusive. Entergys choice of a low probability number was clearly encompassed by the Hearing Request (see Hearing Request 28, 29).
What Pilgrim Watch now knows, is that there many important inputs and parameters, chosen by Entergy, that drastically effect consequences. These include not only meteorological, emergency response, and economic data and the probability number, but also the chosen source (Entergy chose a small source) and averaging method Appendix 1 - Page 3
(Entergy chose mean rather than one of larger percentiles, e.g., 95th, that the code presents as options).
On the basis of what it then knew from public knowledge, Pilgrim Watchs Hearing Request was able to, and did, say that: Neither the MACCS2 model used to analyze consequence nor the input data provided by the applicant provide an accurate assessment of the off-site dose and economic consequences of a severe accident....          [T]here are limitations inherent in the software ... which by design omit the majority of economic costs. (Hearing Request 34)
In short, Pilgrim Watchs original contention made at least three points, specific to Pilgrims SAMA:
: 1) The way in which Entergy used probabilistic modeling was inadequate.
: 2) As used by Entergy to analyze consequences, the MACCS2 model did not provide an accurate assessment of the off-site dose and economic consequences of a severe accident
: 3) Entergys choice of parameters it put into the modeling software had the intended result of downplaying the consequences of a severe accident.
There can be no question that each of these points, as applied to Pilgrims SAMA analysis, could be proved. There also can be no question that the Hearing Request pointed to Appendix 1 - Page 4
each as specific deficiencies in Pilgrims SAMA analysis, and that Pilgrim Watchs original Contentiion was not generic.65 B.      The Orders Narrowing Contention 3 Nonetheless, at the outset of this proceeding, in its October 16, 2006 Memorandum And Order (Ruling on Standing and Contentions of Petitioners Massachusetts Attorney General and Pilgrim Watch), the Board, in Pilgrim Watchs view improperly, rewrote Contention 3 to say only that:
Applicants SAMA analysis for the Pilgrim plant is deficient in that the input data concerning (1) evacuation times, (2) economic consequences, and (3) meteorological patterns are incorrect, resulting in incorrect conclusions about the costs versus benefits of possible mitigation alternatives, such that further analysis is called for.
In doing so, the Board entirely deleted by using probabilistic modeling from PWs original contention, saying that probabilistic techniques that evaluate risk could not be challenged on a generic basis,66 and that the use of probabilistic risk assessment and modeling is obviously accepted and standard practice in SAMA analyses. (Id at 100).
65 Under NRC Regulations, SAMAs are a Category 2 (site specific), and not a Category 1 (generic), issue.
Table 9.1 of NUREG 1437 lists both Category 1 and Category 2 issues, and identifies SAMAs as Category 2. Entergy seems to agree that SAMAs are Category 2.
66 The Board majority seemed not to appreciate that PWs original Contention 3 did not generically challenge probabilistic modeling, the MACCS2 code, or averaging. Pilgrim Watchs challenges were specific both to the site and to the ways in which Entergy chose to misuse probabilities, the MACCS2 code, and averaging: Applicants SAMA analysis for the Pilgrim plant is deficient...
Appendix 1 - Page 5
The Board then went on to limit what remained of the original contention -
incorrectly inputting certain parameters into the modeling software - to the specific in addition inputs that Pilgrim Watch had been able to identify from public information at the time its Hearing Request was filed.      To complete its exclusion of probabilistic modeling from the rewritten contention and scope of this proceeding, the low probability number (Hearing Request 29) and extremely low probability (Hearing Request 30) inputs were never mentioned.
At that time in history, Pilgrim Watch, a small public interest group, did not fully appreciate what the Boards re-writing of Contention 3 had done. And PW certainly did not appreciate, and then could not have appreciated, that the majoritys later Summary Disposition decision would go even farther, and hold that its rewriting of Contention 3 eliminated all challenges, not simply to probabilistic modeling, but also to the adequacy of the MACCS2 code (Order Granting Summary Disposition, pg.,2, italics added):
Not at issue here, as discussed below in more depth, because these matters were raised and eliminated at the contention admissibility stage, are issues related to: (1) the adequacy of the computer code (MACCS2) used to perform the SAMA computations; (2) the use for SAMA analyses of probabilistic (as opposed to deterministic) methodologies; and (3) the health effects of low doses of radiation.
Judge Young certainly did not understand the October 2006 order to be that draconian (Dissenting Opinion of Administrative Judge Ann Marshall Young, 35, italics Judge Youngs):
Appendix 1 - Page 6
By stating that we found inadmissible any part of the contention that could be construed as challenging on a generic basis the use of probabilistic techniques that evaluate risk, we did not exclude specific challenges that might bring into question specific aspects of the SAMA analysis regarding the three types of input we admitted.
Judge Young also recognized that what the Board majority really did was to exclude any meaningful challenge to what is put into the code, and to render Contention 3 meaningless (Id. at 35-36, italics added):
The upshot of this is that, although we admitted the issue of whether the input data regarding meteorological patterns were correct, by now excluding consideration of anything relating to the adequacy of the MACCS2 code as specifically applied with regard to the Pilgrim plants SAMA analysis, the majority in effect excludes any meaningful challenge to what is put into the code relating to meteorological patterns, because such input is effectively predetermined by the current state of the MACCS2 code. Our admission of Contention 3 is thus rendered meaningless with regard to meteorological issues.
The majoritys efforts to render Contention 3 meaningless continued in its order of November 23, 2010. Without mentioning any of the portions of Pilgrim Watchs Hearing Request quoted above, the majority held that Pilgrim Watchs Hearing Request failed not only to raise any issues about the NRCs practice of using mean consequence values in SAMA analyses, resulting in an averaging of potential consequences, but also to raise anything that could bring into question the reasonableness of this NRC practice and affect the Boards findings and conclusions on the meteorological modeling issues. (November Order).
Appendix 1 - Page 7
Once again, and in PWs view correctly, Judge Young disagreed (Order of September 23, 2010:
First, in consulting the Users Guide for the MACCS2 code, I find various references to mean consequence values, mean consequence results, and averaging, some of which appear in discussions of plumes and deposition processes in the ATMOS part of the code. This would seem to support straightaway a conclusion that these usages of the terms are implicitly encompassed within Pilgrim Watchs challenge in Contention 3 to the Gaussian plume model and the modeling processes associated with that - which would lead to a conclusion that the subject at issue was timely raised, at least as to these usages (Sept. Order, at 3)
Entergys arguments and assertions were challenged by Pilgrim Watch in response to Entergys summary disposition motion. Intervenor also challenged Entergys arguments and assertions relating to the use of mean consequence values and averaging. And again, these mean consequence values/averaging issues would also seem to fall under, and be material to, the broad, bottom-line issue the Commission has remanded - namely, whether the Pilgrim SAMA analysis resulted in erroneous conclusions on the SAMAs found cost-beneficial to implement. It seems at a minimum arguable that, much as it raises the conservatisms and sensitivity studies, Entergy has raised these averaging/mean consequence values issues in the manner of raising defenses to Pilgrim Watchs charges in Contention 3, with respect to the effect such averaging has on whether any additional SAMAs might be cost-beneficial to implement.(Sept. Order, at 10)
Appendix 1 - Page 8
C.        The Bases of the Majority Decisions and What They Overlooked A. Probabilities and the MACCS2 Code In its October 16, 2006 Order rewriting Contention 3, the Board majority said (emphasis added):
With respect to Entergys characterization of PWs contention as being that risk is to be ignored [in a SAMA analysis], to the extent that anypart of the contentions or basis may be construed as challenging on a generic basis the use of probabilistic techniques that evaluate risk, we find any such portion(s) to be inadmissible. The use of probabilistic risk assessment and modling is obviously accepted and standard practice in SAMA analyses.
The majoritys Order granting Summary Disposition, went even further. Over Judge Youngs dissent, the majority construed the October Order as having eliminated ... issues related to: (1) the adequacy of the computer code (MACCS2) used to perform the SAMA computations; [and]
(2) the use for SAMA analyses of probabilistic (as opposed to deterministic) methodologies.
The majoritys justification for removing all aspects of the MACCS2 code from consideration was again NRC practice: it is necessary for the Staff to take a uniform approach to its review of such analyses by license applicants and for performance of its own analyses, and it would be imprudent for the Staff to do otherwise without sound technical justification.
In relying on practice, the majority overlooked at least two important things.
Appendix 1 - Page 9
First, it failed to appreciate that NRC practice is not NRC regulation- neither probabilistic modeling nor the use of the MACCS2 code are required. Regardless of what the Staffs practice may be, no NRC regulation requires probabilistic modeling or use of the MACCS2 code. In CLI-10-11, the Commission agreed that the Staff used a customarily used code, widely used and accepted as an appropriate tool for conducting SAMA analyses, and that the Gaussian plume model is a fundamental part of the MACCS2 Code. But the Commission was equally clear that those reasons are not a sufficient ground to exclude the codes integral dispersion model from all challenge if adequate support is presented for a contention. (CLI010-11, 17). Indeed, for the Commission to have concluded that they were not sufficient would have been to endorse the view that a desire foruniformity could somehow have made it proper for Entergy (and apparently the NRC Staff) to have designed and used an approach that insured that no significant SAMAs will ever be required.
Second, the majority overlooked that Pilgrim Watchs contention did not challenge anything on a generic basis. Pilgrim Watchs challenge was directed to probability and the MACCS2 Code as they were specifically used by Entergy in its SAMA analyses.
B.      Health and Cleanup Costs The majoritys Summary Disposition decision also said that health consequences caused by low doses of radiation had been rejected at the contention admissibility stage because the only economic impact computations it [apparently Pilgrim Watchs Hearing Request] intended to challenge were those relating specifically to loss of economic activity, loss of economic Appendix 1 - Page 10
infrastructure and loss of tourism income (and not the economic costs relating to the effects of low levels of radiation upon human health). However, the majority overlooked PWs Hearing Request explicitly included health costs: The Environmental Report inadequately accounts for off-site health exposure and economic costs in its SAMA analysis of severe accidents. (Hearing Request, 2)
As for costs of clean-up and decontamination, Pilgrim Watchs Hearing Request did say that the MACCS2 model analysis of economic costs include the cost of decontamination, [and ]
the cost of condemnation of property that cannot be decontaminated to a specified level (Hearing Request, 43)      But the October Order overlooked that Pilgrim Watch never said that Entergys use of the MACCS2 code properly determined any of these. The October Order simply paraphrased what Pilgrim Watch said (October Order 83), and never mentioned the subject cleanup or decontamination again.
In its October 26 Order, the Board found that Pigrim Watch has provided sufficient alleged facts ... to demonstrate a genuine dispute with the Applicant on the material factual issues of whether in its SAMA analysis the Applicant had adequately taken into account relevant and realistic data with respect to evacuation times....[and] economic consequences of a severe accident in the area (October Order, 103). It went on to say that it thus admitted that part of Contention 23 having to do with the input data for evacuation [and] economic ... information (id.).
Appendix 1 - Page 11
The majoritys decision granting Summary Disposition seemed to echo that the admitted arguments of Pilgrim Watch were that the estimates of economic cost impact failed to preperly account for loss of economic activity, or for loss of economic infrastructure and tourism (SD 13); but it soon became clear that the majoritys view of what economic conseqences, economic activiety and loss of economic infrastructure were included was very limited.
Judge Young recognized the contrary (SD 34):
The term economic consequences is a broad one, which may fairly be said to encompass some of the various tyupes of costs that Intervenors now wish to litigate.
Before deciding these issues, I would at least allow oral arugment on, among other things, issues relating to the scope of the contentions and the types of economic costs that are normally included in SAMA analyses.67 Yet the majority of the Board has since made plain that the only a few economic costs will be considered, e.g., the cost differential caused by the differences between the radiological deposition caused by the sea breeze or hot spot effects from that expected using a straight-line Gausssian plume model, (September 23 Order, Appendix A) and even then apparently only to the extent they might effect the loss of tourism and other business in Plymouth County.68 67 All members of the Board seem to agree that clean-up and decontamination costs are normally included in SAMA analyses.
68 Pilgrim Watchs Hearing Request said that the MACCS2 model used by Entergy did not account for the loss of economic activity in Plymouth County (Hearing Request 44) But Pilgrim Watch never said that the costs of a radiological accident at PNPS woule be limited to Plymouth County. Indeed, the very next paragraph of the Hearing Request specifically referred to the Commonwealth of Massachusetts, Southeastern Massachusetts, and three other counties. The Hearing Request also said that both Providence and Boston are within 45 miles of a severe PNPS accident should one occur (Hearing Request 50)
Appendix 1 - Page 12
Despite the Boards finding that there were material factual issues of whether ... the Applicant had adequately taken into account relevant and realistic data with respect to ...
economic consequences of a severe accident in the area (October Order, 103), the majority has consistently overlooked the largest economic consequence[] of a severe accident,  the cost of cleaning up contaminated infrastructure to its pre-accident condition. Yet there can be, and apparently is, no disagreement that one of the types of economic costs that are normally included in SAMA analyses is cleanup/ decontamination costs.
As for input data concerning (1) evacuation times, majority dismissed this part of rewritten contention 3 ever more curtly:        Applicants MACCS2 Sensitivity Case 6 ....
convincely demonstrates that the evacuation time assumptions ... cannot make any difference....
(SD 11-12) Overlooked was the fact that Sensitivity Case 6 in fact proves nothing, because is based on the same faulty practices and inputs as Entergy used in the rest of its SAMA analyses.
C.      Inputs In addition to excluding the two perhaps most important inputs - source and likelihood of an accident - at the outset, the majoritys Summary Disposition Decision said that the adequacy of the computer code was eliminated at the contention admissibility stage; and on November 23, 2010 the majority held that contention 3 did not include any consideration whatever of what the MACCS2 Code as used by Entergy actually did. Apparently adopting some unknown definition of inputs, the majority, in what is effectively a one paragraph order, said that the Appendix 1 - Page 13
the mean consequene values issue was not timely raised and ... will not be entertained by the Board....
The majority reached this decision only after having ordered the experts for both parties to explain to it, in detail sufficient for understanding of the computer codes process order and mechanics... at what point in the process of SAMA computations perfomred using the MACCS2 code the mean consequences ... are done. In particular, the majority of the Board asked what was done by each of three specific modules - ATOMOS, EARLY and CHRONC. For some reason the majority never mentioned the codes OUTPUT FILE in which it now appears that the averaging and probability that so drastically reduce consequences are actually accomplished.
If, even at this late date, a majority of the Board, including the Judges with technical backgrounds, in found it necessary to ask about ATOMOS, EARLY and CHRONC, but not to ask about the OUTPUT FILE, it hardly was fair for the same majority to use Pilgrim Watchs failure, in May of 2006, to understand exactly what was an input and exactly what was done within the code, as a basis for rejecting Pilgrim Watchs challenge to how Entergy used the code.
Further, both the Commission and Judge Young have recognized that the outcome of this proceeding should not depend on a hypertechnical definition of what is or is not an input. What is important is not what technically is an input, but what the Code does with the information put into it to reach the final estimated consequences on which SAMA determinations are based. In plain language, what the code finally put out.
Appendix 1 - Page 14
Judge Young recognized that the plume model, while not input per se in the technical sense, is implicitly part of what is put in to the MACCS2 code to produce results about meteorologial patterns. (SD Dissent 34). And in CLI 10-11, the Commission was equally clear that the Board decision admitting the contention ... did not make a distinction between specific input date that is entered into the MACCS2 code and the specific models embedded in the code....      Therefore, there easily may be an overlap between arguments challenging the sufficiency of input data used and challenging the model used.... (CLI 10-11, 14-15)
Pilgrim Watch suggests that the Board majority has consistently overlooked the overlap, and drawn distinctions that the Board decision admitting the rewritten Contention 3 did not make, and that the Board majority should not have made thereafter.
As said before, these decisions have denied Pilgrim Watch the opportunity to deal with substance. Equally important, and again as said before, the Boards brochure says that Congress made it possible for the public to get a full and fair hearing on nuclear matters.
Given the cumulative effect of the Boards prior decisions, the Board should consider whether this was possible for Pilgrim Watch.
Appendix 1 - Page 15
APPENDIX 2 Meteorological Modeling: Government and Independent Studies Government and Independent Studies support Petitioners claim that a straight line Gaussian plume model cannot account for the effects of complex terrain on the dispersion of pollutants from a source. Therefore its use is inappropriate for use for Pilgrims SAMA analysis to determine the potential area of impact and deposition in a severe accident. For example:
NRC Since    the    1970s,    the  USNRC      has  historically  documented      advanced      modeling technique concepts and potential need for multiple meteorological towers appropriately located in offsite communities, especially in coastal site regions. But ignored implementing its own advice.
In 2009, the NRC made a presentation to the National Radiological Emergency Planning Conference;69 and although it was focused on emergency planning, the content is equally relevant to meteorological modeling for consequence analysis. The presentation concluded that the straight-line Gaussian plume models cannot accurately predict dispersion in a complex terrain and are therefore scientifically defective for that purpose [full presentation is available at ML091050226, ML091050257, and ML091050269 (page references used here refer to the portion attached, Part 2, ML091050257). Exhibit 19 Most reactors, if not all, are located in complex terrains, including Pilgrim. In the presentation, NRC said that the most limiting aspect of the basic Gaussian Model, is its inability to evaluate spatial and temporal differences in model inputs [Slide 28]. Spatial refers to the ability to represent impacts on the plume after releases from the site e.g., plume bending to follow a 69 Whats in the Black Box Known as Emergency Dose Assessment (ML091050226), 2. Dispersion (ML091050257), 3. Dose Calculation (ML091050269), 2009 National Radiological Emergency Planning Conference, Stephen F. LaVie
river valley or sea breeze circulation. Temporal refers to the ability of the model to reflect data changes over time, e.g., change in release rate and meteorology [Slide 4].
Because the basic Gaussian model is non-spatial, it cannot account for the effect of terrain on the trajectory of the plume - that is, the plume is assumed to travel in a straight line regardless of the surrounding terrain. Therefore, it cannot, for example, curve a plume around mountains or follow a river valley. NRC 2009 Presentation, Slide 33. Entergy acknowledges that within 50-miles from Pilgrim there are hills and river valleys. Further it cannot account for transport and diffusion in coastal sites subject to the sea breeze. Sea breeze also applies to any other large bodies of water. The sea breeze causes the plume to change direction caused by differences in temperature of the air above the water versus that above the land after sunrise. If the regional wind flow is light, a circulation will be established between the two air masses. At night, the land cools faster, and a reverse circulation (weak) may occur [Slide 43]. Turbulence causes the plume to be drawn to ground level [Slide 44].
The presentation goes on to say that, Additional meteorological towers may be necessary to adequately model sea breeze sites [Slide 40].
Significantly, the NRC 2009 Presentation then discussed the methods of more advanced models that can address terrain impact on plume transport, including models in which emissions from a source are released as a series of puffs, each of which can be carried separately by the wind, (NRC 2009 Presentation Slides 35, 36). This modeling method is similar to CALPUFF.
Licensees are not required, however, to use these models in order to more accurately predict where the plume will travel to base either consequence analyses or protective action recommendations.
The NRC recognized as early as 1977 that complex terrain presented special problems that a model must address if the air dispersion analysis is to be accurate.70 For example: NRC, Regulatory Guide 1.111, Methods for Estimating Atmospheric Transport and Dispersion of Gaseous Effluents in Routine Releases from Light-Water-Cooled Reactors (July 1977) (Draft for 70 Ibid Appendix 2 - Page 2
Comment) says that, Geographic features such as hills, valleys, and large bodies of water greatly influence dispersion and airflow patterns. Surface roughness, including vegetative cover, affects the degree of turbulent mixing. (Emphasis added).
This is not new information; knowledge of the inappropriateness of straight-line Gaussian plume in at complex sites goes back a long way within NRC. For example:
1972: NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.
1977: NRC began to question the feasibility of using straight line Gaussian plume models for complex terrain. See U.S.NRC, 1977, Draft for Comment Reg. Guide 1.111 at 1c (pages 1.111-9 to 1.111-10) 1983: In January 1983, NRC Guidance [ NUREG-0737, Supplement 1 Clarification of TMI Action Plan Requirements," January 1983 Regulatory Guide 1.97- Application to Emergency Response Facilities; 6.1 Requirements], suggested that changes in on-site meteorological monitoring systems would be warranted if they have not provided a reliable indication of monitoring conditions that are representative within the 10-mile plume exposure EPZ.
1996: The NRC acknowledged the inadequacy of simple straight-line Gaussian plume models to predict air transport and dispersion of a pollutant released from a source in a complex terrain when it issued RTM-96, Response Technical Manual, which contains simple methods for estimating possible consequences of various radiological accidents. In the glossary of that document, the NRCs definition of Gaussian plume dispersion model states that such models have important limitations, including the inability to deal well with complex terrain.
NUREG/BR-0150, Vol.1 Rev.4, Section Q; ADAMS Accession Number ML062560259, Appendix 2 - Page 3
2004: A NRC research paper, Comparison of Average Transport and Dispersion Among a Gaussian, A Two- Dimensional and a Three-Dimensional Model, Lawrence Livermore National Laboratory, October, 2004 at 2. (Livermore Report) had an important caveat added to the Reports summary about the scientific reliability of the use of a straight-line Gaussian model in complex terrains:
        . . . [T]his study was performed in an area with smooth or favorable terrain and persistent winds although with structure in the form of low-level nocturnal jets and severe storms. In regions with complex terrain, particularly if the surface wind direction changes with height, caution should be used.
Livermore Report at 72 (Emphasis added) Exhibit 16 2005: In December, 2005, as part of a cooperative program between the governments of the United States and Russia to improve the safety of nuclear power plants designed and built by the former Soviet Union, the NRC issued a Procedures Guide for a Probabilistic Risk, related to a Russian Nuclear Power Station. The Guide, prepared by the Brookhaven National Laboratory and NRC staff, explained that atmospheric transport of released material is carried out assuming Gaussian plume dispersion, which is generally valid for flat terrain. However, the Guide the caveat that in specific cases of plant location, such as, for example, a mountainous area or a valley, more detailed dispersion models may have to be considered. Kalinin VVER-1000 Nuclear power Station Unit 1 PRA, Procedures Guide for a Probabilistic Risk Assessment, NUREG/CR- 6572, Rev. 1 at 3-114; excerpt attached as Exhibit 8, full report available at http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6572. Exhibit 20 2007: NRC revised their Regulatory Guide 1.23, Meteorological Monitoring Programs for Nuclear Power Plants. On page 11, the section entitled Special Considerations for Complex Terrain Sites says that, At some sites, because of complex flow patterns in nonuniform terrain, Appendix 2 - Page 4
additional wind and temperature instrumentation and more comprehensive programs may be necessary. For example, the representation of circulation for a hill-valley complex or a site near a large body of water may need additional measuring points to determine airflow patterns and spatial variations of atmospheric stability. Occasionally, the unique diffusion characteristics of a particular site may also warrant the use of special meteorological instrumentation and/or studies.
The plants operational meteorological monitoring program should provide an adequate basis for atmospheric transport and diffusion estimates within the plume exposure emergency planning zone [i.e., within approximately 16 kilometers (10 miles)].71 These excerpts from Regulatory Guide 1.23 demonstrate that the NRC recognizes there are certain sites, such as those located in coastal areas, like Pilgrim, that multiple meteorological data input sources are needed for appropriate air dispersion modeling. Not simply one or two meteorological towers onsite. Since the straight-line Gaussian plume model is incapable of handling complex flow patterns and meteorological data input from multiple locations, Regulatory Guide 1.23 demonstrates NRCs recognition that it should not be used at any site with complex terrain.
EPA Likewise, EPA recognized the need for complex models. For example: EPAs 2005 Guideline on Air Quality Models says in Section 7.2.8 Inhomogenous Local Winds that, In very rugged hilly or mountainous terrain, along coastlines, or near large land use variations, the characterization of the winds is a balance of various forces, such that the assumptions of steady-state straight line transport both in time and space are inappropriate.
(Fed. Reg., 11/09/05).
71 For example, if the comparison of the primary and supplemental meteorological systems indicates convergence in a lake breeze setting, then a keyhole protective action recommendation (e.g., evacuating a 2-mile radius)
Appendix 2 - Page 5
EPA goes on to say that, In special cases described, refined trajectory air quality models can be applied in a case-by-case basis for air quality estimates for such complex non-steady-state meteorological conditions. This EPA Guideline also references an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000. Section 3.4 of this Guidance for coastal Locations, discusses the need for multiple inland meteorological monitoring sites, with the monitored parameters dictated by the data input needs of particular air quality models.
72 EPA concludes that a report prepared for NRC                provides a detailed discussion of considerations for conducting meteorological measurement programs at coastal sites, reactors on large bodies of water. Most important, EPA's November 2005 Modeling Guideline (Appendix A to Appendix W) lists EPA's "preferred models and the use of straight line Gaussian plume model, called ATMOS, is not listed. Sections 6.1 and 6.2.3 discuss that the Gaussian model is not capable of modeling beyond 50 km (32 miles) and the basis for EPA to recommend CALPUFF, a non - straight line model.73 DOE DOE, too, recognizes the limitations of the straight-line Gaussian plume model. They say for example that Gaussian models are inherently flat-earth models, and perform best over regions of transport where there is minimal variation in terrain. Because of this, there is inherent 72 Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936, U.S. Nuclear Regulatory Commission, Washington, DC 73 http://www.epa.gov/scram001/guidance/guide/appw_05.pdf Appendix 2 - Page 6
conservatism (and simplicity) if the environs have a significant nearby buildings, tall vegetation, or grade variations not taken into account in the dispersion parameterization.74 National Research Council Tracking and Predicting The Atmospheric Dispersion of Hazardous Material Releases Implications for Homeland Security, Committee on the Atmospheric Dispersion of Hazardous Material Releases Board on Atmospheric Sciences and Climate Division on Earth and Life Studies, National Research Council of the National Academies, 2003. The report discusses how the analytical Gaussian models were used in the 1960s and tested against limited field experiments in flat terrain areas performed in earlier decades.
In the 1970s the US passed the Clean Air Act which required the use of dispersion models to estimate the air quality impacts of emissions sources for comparison to regulatory limits. This resulted in the development and testing of advanced models for applications in complex terrain settings such as in mountainous or coastal areas. In the 1980s, further advances were made with Lagrangian puff models and with Eulerian grid models. Gaussian models moved beyond the simple use of sets of dispersion coefficients to incorporate Monin-Obukhov and other boundary layer similarity measures which are the basis of contemporary EPA models used for both short range and long range transport applications. Helped enormously by advances in computer technologies, in the 1990s, significant advances were made in numerical weather prediction models and also further improve dispersion models through the incorporation of field experiment results and improved boundary layer parameterization. The decade starting with the year 2000 has seen improved resolution of meteorological models such as MM5 and the routine linkage of meteorological models with transport and dispersion models as exemplified by the 74 the MACCS2 Guidance Report June 2004 Final Report, page 3-8:3.2 Phenomenological Regimes of Applicability Appendix 2 - Page 7
real time forecasts of detailed fine grid weather conditions available to the public at Olympic events. Computational Fluid Dynamics (CFD) models which involve very fine grid numerical simulations of turbulence and fluid flow began to see applications in atmospheric dispersion studies. The next decade will see routine application of CFD techniques to complex flows associated with emergency response needs.
The nuclear industry does not show evidence of keeping up with these technological advances. For use in modeling air quality concentrations, the NRC uses straight-line Gaussian dispersion algorithms that date back to the 1960s. Complex flow situations such as those associated with flow around high terrain features or that would incorporate sea breeze circulations are not simulated. For emergency response applications, the NRC does not seem to require any advanced modeling to be installed at nuclear power plants.
Atmospheric Scientists & Meteorologists For over three decades atmospheric scientists and meteorologists have been identifying problems in the use of models similar to ATMOS for such settings. Example: Steven R. Hanna, Gary A. Briggs, Rayford P. Hosker, Jr., National Oceanic and Atmospheric Administration, Atmospheric Turbulence and Diffusion Laboratory, Handbook on Atmospheric Diffusion (1982)).
The inability of a simple Gaussian plume model to accurately predict air transport and dispersion in complex terrains is such a basic flaw that it is discussed in a textbook for a college-level introductory course in environmental science and engineering (Steven R. Hanna, Gary A.
Briggs, Rayford P. Hosker, Jr., National Oceanic and Atmospheric Administration, Atmospheric Turbulence and Diffusion Laboratory, Handbook on Atmospheric Diffusion (1982)). (Chapter 13 Appendix 2 - Page 8
authored by William J. Moroz). In listing the assumptions that are made to develop a simple straight line Gaussian plume model, the textbook warns that:
The equation is to be used over relatively flat, homogeneous terrain. It should not be used routinely in coastal or mountainous areas, in any area where building profiles are highly irregular, or where the plume travels over warm bare soil and then over colder snow or ice covered surfaces Appendix 2 - Page 9
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_-inlo""", 1 . . -.. _ ... . ~ .t~ ....... _                                  .... ....                                                      , nbmo<~    .. _            ........
,...- -. a _ ..."" '."--"_ "'....... (1Wb) _ _ nod                                          ..... '0 """'". .... , _ '-i""" ' _ ....... _;., ....a        ~
, ........ . , ......... ~" of .......,...;"" . ... OMbLD..., a                                              ~
    -~            -~"""'~ -~            ....... '""".............
............... of ,,,,,"," ""' ........ ~*'
                                                                        ~ "'" ~
0-...-.....
                                                                                                          ...        """~
oIood"'~"'"
__    '" ._ ~ "" ,""",,"" "",*
_    -inlo""", fo-.........rt.          ~""""""'
  ...... ,,,. ........... <k< .......... K _ _ .... I<n>> . ... ~d                            "on<              .. ,""'.
                                                                                                                    ... _..,q"'"........
                                                                                                                                    ..."" a.... """__.... _  "" ,.t~.........-.
'''' ow**U _ . , ...              (_~ ~        ........ - . . - ., .. ....                  """' .... ' .... _ ...,/a ,_" ,........_ .....11'. ""'....
* "", ""' " )1"' . ............ ""'- ThoC.... _                      ...  ~ .o, "' ...    .... ~ ..... <>< ...... - " " ' - - - ... - ....
lao- '''''''..... 0 .. a .... R<h _ ' """ ..... _ ......, ... .. .                          .............- . .. ~.. a q"""""''''' .... """" (..."" ........
mo""" , ... , .... _              . NlC"> _
............ ,.,;..'"' ... "'m... d._~                  __ .. ,.... ". <k<"";nl"
* o........ ., .
My ,n..--!'o .. -... . _ _ ...- ;,,' m ....... ) *
                                                                                            "'" _"", .. "'" """,.. a ...... 'n ... ~ . ~ ....... .........0
                                                                                            ........ ' ..... a _ ",,", __ "'........ a ...... y"' ....._
                                                                                                                                                                  ~ _~ "
                                                                                              "',.... ..-Li" " q"""""-"
: a. ............ '" _              ..""
a Io il ~,",- _
                                                                                                                                                      ...... . ... "'....,0-
                                                                                                                                                        . """'.        a an","
_"' .. ~ , ....... "'..... """" a 0 . . ._                    . . . . , ....- .
_ ' 4""~ . _          .... __......            a ~ ",,
",,"",.,.;n."_
Appendix 3 - Page 2
...." i ."""o(_ ~
                                                                                                ".,. c.... _            *. , ... , .... ... '" "",,,,,,,,, "" "" 0( PlA d ' _~          .... bpcoJ _ . 0( , ........ .....
                          ~ """"-lInU.. d ....... i ~. ~~ .......... ...
                                                                                          . . . . _ io .......... " " ' _..... ;-,;_(l ~ _ .... _
                                                                                          ' ... -.......d .... "' .......... "I ..... I.. .. ' '' ...... i ... .........
io
,....,., _ .. "*_ow,..                      ( q.. n'... .-~. _ _ _.. _
                                                                                            * ...... '" " " _ ";!h , ... ,"",.,....., ....... ' ..... i .... ....
""' ) .... ~ .............. _ _ ..... i ... _                            .. in ......
Go..m: " " ... ('( " ..... '" .... :
......  ~      u~~      ......... ---...,.., ",", ....-""-.. _
'... 0_'" .................            ~ _"""'~              0......................          ".,.~.. o(PlA " 'h"' ..... '..,"" ... i_
                                                                                                ..."...,.., ........... , _ ....... _o--d~ ........ io PlA
                                                                                                                                                          ..... "' .. ........ ~
~
Lim ....... ~q ... oot ...
                                      ..""'i" iw ....    ""'"..... _ .... "'... ...._,
    ",IUJ .........,.,.. _ _ ... im"""""", io .....,. . ..
_~
                                                                        ~      __
                                                                            "'..... 0(
_ , ........ . "" io . . . . 0 ..........
NlC"> .... _ _ _ .......- ...... ..-.' , ...
NlC">
_ ooupt~'riOorio ( ' . . .. """ ... _ , .... _                          'Pi .... . ...        , ........., - - - . " " ... . pt; ... ~ ...
d , _ ...... _ _ ... . ; _ ,'"                                      i ""~ . .. .. ....
                                                                                                ".,. C.... m i......*....... - " I..- "",It... ""_                      ..........
"",LM><). . .. "'''' '" ..11K .. , '0 """'.,. ,'" . . . . . - . . .....
jood_. ............. ...-....""_"".-                              ...
                                                                                                . . .'._  .-- "    ,'_  _ .. ...,_      ....      .,. '0 ... "'... ";110
""''''' ~ ~    m i...... i... 0 ' i"",moo' ____ H..,
                                                        'm."'... "'"' . _ ~  .........                                                  0(
                                                                                                                                                ~"'...,. i -.        ~
~""" O:._
"-",~.~_
.. ....s ............ __ ......... : a .
d'" _      ......... ~;w ........ _
                                                  .. . _",, ...o o o a _).
                                                                                        ~
                                                                                                "",,,,~                          ~
I;o;~ ............... ~i""""" on """'... ...-. . ....
AI> m.-...... ...... "'"' ~ au ..... d ,,,. ."' ''' d .... ........
_i. . . . . . . . ..
. . . ~ .... " ..,. 0( d ....... "' ........ d . ........ ~ * ..., ....                        " .,. C....... _ . _ ........... ""'. . . ..... an ... _
                                    . . . . . .,."". . o. .. . ""'. . . ..,._.,. . . . __. .._o_..."..... . ._
-.-........, .... _ o ( ..... "' .... _                        .... k _ ... ~ ....      '010 ........... _                  ........ _        ...... n """" ,_ ('I.
1"... 10. *.,. " ......      ~  .............." ...... _                .... .... '...,  """"" ......-              dm~'''''        0(  _~_                  ........_ _
_~n_"""'_                                                              ~                  ""' .................... , .... , ... C.... _oo"""' ...,. .........
d _.. 01", ..... _
                                                                                                                    ~
_ 'I"""...(.....
(U"""~
__ ,........... ...... "..;,)-.
_ _ ot....... ..., ....                  i ...... - . ......
                                                                                          " - " an ,'" "" ....... """ .. 0( . _                              ....
_"'~ G.... , . ' " (6( ... ~, _ ,'" " . - ....
_ .. l>I> . ... ~ , . . . . . . . , . . . . . . . , _ _ ,.,.    ,~~.-        ... _        _-inlo ....... ""'-... ' o .. ~Q<"" '..... i.,. _ . , . ",",nt _
"'s''' ......... i,;''''' .......... ,,, _                      .... _        ... ....  ,,,,,,1;0; " ........    '0'" _ ...            bO<H. ........... " ...... ' " ,...,
, ............ (q. . *        ~oot.    ,au~        _            ., _          "', .....    """""' .. PlA _ ,.. _ ' " _10"" .... , ... "..;,1..-_ ...
"' .... 0" '" ................ - . _                " . d i.... '" '''' ......... i. i...  .......... , ...... d .. ......... _ ... tWo ... . '''' ..... (a . _                    ...
"""'-) .... 1.., ..... _ _ _ ",""",,,, i"' ....... ......                                  ,...... "",,,, .... (_                        _        " ' _ ........ i ~ .. "I.
_ _.... '..., i_ _ o d ' _ .................. . ....
i~ ..;,;,..,,..      _no              -.......-d........
                                                                                          . ...... ","",,0. _
                                                                                                                                    """'i............ ...."""' _
i"'''.... io _      ....
                                                                                                                                                                  ~
                                                                                                                                                            !. ....  ~
om"","", ";' ~ o ,'" "'''' .... o ( d _ "'_~ ...... .....p .. .
, ........... ....... """' ................ _ U.... ,..._~ ....
"" .............. 100: .... (.....". d _ _ _ ..... i ... _                              '_
0....,..
                                                                                          ... ......... ) "'"' ..... ., ....... 1..-.
                                                                                                        ,onOO"Ot " " ' - . . . _
                                                                                            "'.. ""._.A ............
                                                                                                  ~
n..t~n_ ......... "-
                                                                                                                                        ............ " - " 0. okt ..... i _
d ..... .., ...... "" .. (5<<_
. . ~ ...." . PlA """' .. ) ao..... . ...... " ..              t.,., ......"n,...,        U ), ..... *
............... , ...... &..... ~"' ..... - . . ,,,, ,..,, ... - . &.....                            ",. Nor: .... -..n ...... ",,0.:_ odKY"'"''''''''"''
' ''''''''' 0 ~,*", ..... ' (foo-_ . .......... i""'...... ""''__-p ...
............... d * ..,..... ins.o:_1 ) "" .... . - "'""" .IA
                                                                                                """," o'*>" .mo" i"'''.... '" _                    ..... ""' ..............      "~
                                                                                                ".......,~_......,. ....... ... i ..... ' .... ,,'                  __
.............. " ..... an " .. i.. . in . .... '0 .....,. , .... " .                            '" d ..... . "" ,"""'_ "'""""'.,. ....... _                          ",., odKY ~
_ _ i _ _ ... ~"" ... .,,;1;0; ........... ""',..
_              "".,. . "I "".....- . ...... "'''''''' I... tIoo ....
n - f.....
In,..,........
",",Km.. , " ' ....... _ . 0 ( ........ "' ... . ..........
FO"                                        io                        ioot" ' ' ' ' _
C>OO . . . . . ... . . . . -
                                                                                                , ......... - . .... " ................... _.,; ............ tIoo
""" .. ,."...,." ,..., , ... 10. ............ ",,,,, d ......... i. i...
                                                                                                .....rity d, ... ""It... ""_
                                                                                                                                            ......... ".,...100: ..... " ' _
                                                                                ~    ~
                                                                                                ,..., _ It... ...-. .."' ..... """'" _ ' " .... ~ ............. .. .
, ..........., .... n... . .... ~ ~" "" 'on~ 0(                                                .""'-
........i"''''
d
_~n_
".n ..... . w ...... qni&: .... im...., an .... ..!...
                                                ~      ~.""""'.,_
                                                                              "fIo."".
of ....
                                                                                                "'_~,.                        .,.~  ...............  ---".,.
                                                                                                                                                            ~d"""._
~  .... 'iw "'''''''',_d..__                                                                  ".,. , ..... ..... , ", .. i","" *
                                                                                            ....... .,;110    .....,.~.... d" ......
ow, ......
no .. _~
d ....... ....... ....
: 1. - - . - " ... . ...... _                        . .. _ .~                .......
                                                                                          .... '0 ,.... ,'" "''''.... _
                                                                                          ' '',*",,,,, ~o"""""'"
                                                                                                                                              ...  ~-n""''''
I " ....."'_ ........
NO(    ""tI ...... , ... s.Itty Goo!>        ......". "",,,,,,,,, 0 ........ . .          c.w .... an        "'"' _      ... ~  G....      '-17< .... .. _ _ _ io
' 98& (> ~ """ .. , ... "". 0(,,,, PI><&#xa3;y "' ................ ~.. ....                    ..... k _ o ~ , .... . .... i _
                                                                                                                                                .... " ...... i ...."",,";!h.
........ . "' _~ .. _
- . ,...N, 'o_ .... ~..
                                  " .", .. .. .... , ... "" d .... d_ ~ ..
d .... ~ ..... ~" 110                                                              ,...".
                                                                                          ..... ~ i ....... ""',.. d ....... _ _1;o; 1'IAL
                                                                                            "" ...............i . ."" k ... i ... "";' ''~ '" ."" ~ _
"",. ..... (QHOo) "I ........ l.wi_ ("h ) ........... ''''' ...
lot .. . .. (lIT.) .......... ~ _-oo:~ ,.om... I n ' -                                          Fi ... ' .... "",. 1 0(Ov. ..... ' 9"ft ... ......... . . . - ..... (YJ')
...... ~ ," ' . . - .... d ....      """i"'.....        d * .............. .... .....    (1( ........... , ... QHO-->o~" 0( <bn " - ''"'''''''''"
.... _ _ AI> i ......... .......... d , ... ~ ... ~ . d ..... _
-=Il10: ....... la, ......... _ . , ; . . ......... QHOo . ,...,
..... _ ... M<OtU"            "'''''S'.... _          . ... ,..., _ _ &.....              ""    , - ~-~.
( CU') .... tNp ...._
                                                                                                ".,. . . . ' _ _ _ 0
                                                                                                                                  '''''''''''' (Ul) _ ............
m..    .... _            ~    , ........ NO(
, ... "'~_ ..... d .. , " " _ " ' _ * ..., _ , ............ io                            C.... _ " ' " ..... _                  ........... . ...... _ _
* _ _ ."
, ...... "_IIIo:PlA_                                                                        " " ' ..... 0 " " . . .. d.",      Y"' ..... - . io _ , .... ....... 0(
Appendix 3 - Page 3
......    ".,...~"'"""''''        ... "''..,.. ...' -""""'        .,.0..,...."" ..........    .."' _
                                                                                                      " ..... . .... , ... C........ _
_ _ , .. . Ct>f .........
_      ....... .. of 1[ - '1>"' d
_on<'"      ~
_              SKY_
I... H... , ...        ..,..y....'..i.... ......
......... ... ~ ~ ~...,. i, , ... m-at ...
                                                    ~
1."" ' - 1
                                                                ~..-. d I............. b il""" .... "'"'" ..... ~ . .... ~ .."" ...... "" ....
PIA~""
_ i"...        90..,,6 (ll( ...... S6l. Tli. _ . . . , ..... '" bo ....... i _
_ _ ,..;tk ....... d "'.... ,...... "',.,. ""'.........,
                                                                                                                                                                                        ~
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i_
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                                                                                                    !..      =- ............ ,,... ............","'an.
C....- . . ...... "
                                                                                                                                          , .~ -w_,                      "'~-..
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, ....... , , _. ......... ..... "" ....... it . ' . ' - " " """'~ i ""                              .... '"' d ............ _                  "" """..- .., .... - .... ....
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                                                                                                    , ........ _ _ ...... ........... ""om>; _
                                                                                                    ........... ..1& _ .... ~ ..... _
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                                                                                                              ;.,;"'~ ............. ....-."'-                                                .,.
,_~
.......,. "' ............... I .. y"," (Ca ) .. ~' oi " "... """_                                    ,..................                                                    ...
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  ...._...... .(....        "' ...... 'o_'i_'..............-. q.. (ll()
                                                                                                            ~            _          *. YI" * * ,.. .... ""' ..........
                                                                                                                                                ~
0: i""' .....
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_        bod '''''''''    '0 ...... ,..;...... .. ~ IK........ of, .../;d"", ..                m"oi ..        0..,.
                                                                                                .... d ""..... _ ... _
q"'Li ..~ .. ,." _
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T ............ 0_ ...... ....., "'.. "'" ,0 ... M-
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ThoC............ ~... - . . . ............... d 1E _.,.,.. ,..;"', , ...
PIA M'''''''''
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                                                                                                                                                    ... . .....,... ,_.,. do ""
.....,. """, - . _ ........... ""'''''''' d """ .........0 , ...                                m .. d ... . """ ..... d .... """ WI"", of 10 .. '" '" _ ,
......... .....". .... fo. ...... ..." ..... .... m. A _ _ .... .....                          ...m ........ _. ~ """" "' ........ ~ .... ........ ...,.,........ , ...
H,., .............
_ _ ..... .... - . . . in                                          (l ~ "    (91 "" .....    ....... _              , , _ .... . "'"'" "" "" i",, ... """"~ <ri<_,
,..-.... _                oi _      .. . ""    ~ .. , ~  " ' .... _oW ..... . .....          ......- i ... ..,~ ... of ........ _ ................. d""rimi .....
_ _ lou' .......... ""'" SKY . . - . (_
                                                                                                .... dso .. .,. .... """" ......                _.nc'" "'..."'" ."''''' ...              fn> m i_ ..... ","'an. ""~ "
w                '0 ___              , *' _  .;
y,",  __ ' . ............
An    ~      d"' ......
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"' .... ,,'" '0 , ...            <mo ......... ... , ......C ....., """
..... . . - _                    ..... ('J:M.) _              - . <mo .. _                ""
                                                                                                ...,. ..... i" , - . . . in .... "'.. "'_                            .... wmn< "",""
..", .. ~ (..as) ........ 0 <t-t <mo ....... (q.. (10() _                                      ..",""" ... .oro..... """ ...... ,"', _                                  ....... m .....' _
d ..... ", .. , ~.      _          Tho<mo ........."'Rd ......... .. ..... ..                  '''''"'''''' foriL............................., "'_ .... V,.........
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. . . , " ' . . - _ _ ''' .... '''' _ _ _ d .... ....                                          _            ....... .,.. As. _~..... i, " ,,, .. , 1. , ... . . . - ....
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                                    """lOti.....                                                                                    or<""
d_ . .
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_""_ .... ___                                    ..... ) _....0' ..... ..-......                ...... _ . ""'. " .... "" ,om .....~ .. ,..; ... QHO> .. "'" . .
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wnw '''''' _'ar'''''
                                                                                                <)lll! ...........
i, . ... ",, _ o i , ... _ I.. ., .....
                                                                                                                            <ri< .... (.... _            ",,,,,,.,.J),..,,,,, ..... ,...
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  . ........... . .....'IK_.of .... ...--..                                                    ....... NK C................ ..... ".".., . ......... ..., ;, ,,...
  . ........... .        _        .... " '''''''' ..... , ......... GooJ "'Ie)'
ot;.o<"-> _ bri"" _
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                                                                                                ............. '....,. pobLnt"" d' ... . -....... ... ..,...., .. ,
i"' '''...... "......................._
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                                                                                                                                                                        ~      d _ ........
In ,... _ .......... "'................                                                  ... _              - tk"""' ...... ""' .... "'" , .....................
_                ..... d * ..,.. _ ... do!\~~ .... ....." ..... """""
oi' , _ _ ,,...
                                                                                                ..... ~ "
p_ . . . . . . .
                                                                                                                  ... ""'~"". , ........ '" * . . . _ d NK " ...
                                                                                                ............ (q.. (".15(). .. _ , . . . . . ~ .................... .
                                                                                                ""bk_.. (q.. (IG-ll() .........                                                          d _ _
                              ""'" ..........10,_,.., .........................
. _        ... q"'Li _ _ ....... _ . o .... ~of                                      l ' _ ~1><
;, _ .....""oK" .... ..." ....                                                                  ""'..."". mom.. (, .......... _                              .... _ i"' ......... ...    ~
In_~"" '"                                            d .... ......... i ... ..... _ ....      "'; ... i, , ......... _            ) _~          i ........... . - I""" d * ~
.. ""0&#xa3;(;_11 \0 (1 ( ................. Rd " ' _ .... ......." ... '"                          """".'..,.........,. (fC)'....... Fe _ _ ........ .. ,..;......
, , . . . . . . . . . -. . . . . ""    P . ", ..._      i.. d "_ ~I>"' ........ <DI"          ~ ... - - . ..... , .............. _                          . . -oi.,. ..............,
........... _~ .. of 1[ - ' 1>< "" ... m .. ''''' ... , ....                                    ""'" ""' ..... ,.. ........... ............... ....., , .. QHO>. .... ...
......... QHO> (11( ( ~" "'" ........ , ......... ~~ .... ....                                  _        ..... ...,-i",..,... _ " ' .                    .....,.~  .... _            .. _    ..
_              dm ......... _ _ ."" , ... _""' ...... ).                                      "'~ nnd " " _ ~ ' '''' ..,..,...... '" ....                              loom . - . **
Appendix 3 - Page 4
-                                                                                . _ . . __...... (-..,                              .  . ,
                                                                                                                                                .i_
                                                              ~ _      I -
' _ "'.'''''' i.....- n ........ '..
C.......""'"' _            , , _ ~ ""' ...... d K'" _ y....._on<'        "  pM<
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Ii<"".,. _ .....
_Ii<.                M ... " ........ PIA ~ _""
d ,,,. ""''''''' ...... , _ .,. ....
11l ~ """ "'''''' imp """""'" an ...... . ... _                                                                    _              ...... A                        i"' ..... i, .... _          . ""
~_          ............."""..... .. ..... ,._""1
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                                                                                                                  , .../ip< ,..... , _                d 'Ifi< .... .... _
d , .... .
d ..... ..
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_ . ' '''' ~""" _
1 . ... ....,. .. . "'~. _ _ ""." ... QHO>."""'.. ....
                                                                                                                                                                    ... - " " """ '~ d
                                                                                                            <Df ....... ....        ,wo. _      ~      I.. .,. * * ~i<_ '0 01' .... ""'""
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                                                                                                              " ....... (""h ......                , ""'.om......... ...          '00"" ,..._
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m ""' . .... an orin '" "' ". _ i.... .........- _                                  "P"l "'
_ _.tOo ,_
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                          ,,, ' k . . .... d .......... d ... '_ i.........
                                                    ~                                    d ... .
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                                                                                                  ........ of. - " ' _ ..... ind ... ~._ (_.....-'"
d""'........ '_ . ~ .                ~  _"" , ... "" .. oft ... _ .
AA "" _ _ pM< 0( , . . - . . . . . . . . ,,,. ....... ' ''''''. 0(
om.      (' .... ll() Tlw ""OS . . ~"' . ""m ..... d <D"''''''
* _ _ _ of . ... "'"," (1 6(.
                                                                                                                                                                                            ,.iI"
""0&#xa3;(;_      "'" '" tIooso d o","""                  ~ SHY-OI-01 01 ..... ", ,,~                        "'lEG-,.'" .... _ .. "'"' " ' - ' '" ' ''- '                        on ""' __
_ ,,,,,,,,,,, ***        "'''~ "'' "  .. l :><~ '" _            to . ... C....... _          _ ......._                    (lID&#xa3;<."""'''          i" , _ .... "'.,. .... , ......,,'"
d i",,'''' .... NO<: , ..II' .. ... , ",. ' ........ ... "., h ..... <rt ""                        _ . ) _ ...... .. , ... _                        bo~",,",," .... ..... ......no """-
on """" fu .. " ,,"" ... _                                                                        A...... "" d"' .. _                '"'"'''' .. _ /ip< ....... _ . ",. ""m .....
      ".,. ..... U...,. ~ .... , ... _",,01 '" of , ...                                            of .. ..... - . . . ... q . (U.'"..l"I ( _ ......._ * . . - _
. ... ~.t<nMd .... _"'~ ""' .... ~_'" " f
,yo... . .... "'""""""                    .... _ . " - ' _. .......... . .....
                                                                                              ..  '"'"'~_. ""-..,.., "'_                                ~            d ' [ - , /1<. . ..... d
                                    ~
(Ita'OP) (1' 1_ ".,. ' .... illa<_ ... .......... <on 10""""" ....
l' ""' .... -.. ...... ""'...... (" " '). , in< . * * "".......... '0 d ............ .,.
ftGN. ,.. ..... . ....... '"' ~ .... .,-...w", ..... . ,. ~ tK                              ...  . . ..
                                                                                                            ' " " . . . . . . . . . . . . . . . . !)O.A , " - . .
                                                                                                              "'" h,~........                        i,''''''"" ..... ""'''''''.... .,.
""""" .., 01' I... "          """on ...          ~""~            _..,od _"""              H,.t  """'.... ...i"            , ... ",",,'" Wkro . . -L....                  of ..!... .,.,.....
...,..., ..,...,. " . ... . 0 . . . . . . . . . . . . , . . . ~ ... """,," " " , - , . , . .
,,,. "-I' ..... " .... ...., .... ("" "') -...w.., .... ao " ' _ on
                                                                                                  " " _ .,. , ... , " , , " _ d . ..... I~ ' "," ait ...... ....
                                                                                                  ......... '" , ... ..., "' _ _. ' d - . G_7 of ",O&#xa3;(; _,.",. ~
_ _ .... '_OJ _ "' ''''';';'''' q_'" an _ _                                                        ."' ,.....
,'"""">' * ..,...... ,,"'an ... '''''_ ,~........... ...., ......"
'mq_n'" -., ..... ~.,. ""' '0 "" ...i" . _iw                                                                  .... i .. _            ~  , ...    ~        of  '_1' "", ....... _ *
,...".        '" ",._.                                                                                ""'''''''' of 1[ _' ......... Tho .... ""~ ....... _~ i
      ",. . .... ,.., "'" _ _                  ...... i ....        _            "'" "'. of
                                                                                                        ,...........0<. "". _ ".-.., *_.
                                                                  ~
                                                                                                        ,oe ... "'." (>'I( .....              ' Ocrl ' 00 (101        ~  l ' '""'.  (""'~    ",.
""""""" ""',.. d PIA.                            _        _ _ ... ) .. ... , .... _                                                                                            of 15 '"'"    . ""
                                                                                                        ""' ~ -~.... '" "'..." ~(
( ~.
                                                                  . ..                                                                                                      _.I. .
opi"" ...-~ U                                                      ( ~.
" . ..... ) . . ._            in  "'0&#xa3;(;_1I"' .... ' ... _ iL............ _
**................Nl C.
'"0M,,,,,,,                  ___      -~-.
      .....,'............. of ....,.. _
                                          ... ,_              _"" -i""'-.
                                                                        ..... _ rot'" "",.,                ...... '" , ... ,."..d 15 _' OO'""' ......
d" _' .... ~....
                                                                                                                                                                                            ~
.......... _ " . , .............. ... i_                            " . ..... """"'-
_ .. i, , ...        '.".. ' OO_lI.'''''' .... _ _ *                  ""'~ d
                                                                                                        "_G ...... . . 100-100...., * ""''''''''" d Il _ 7 ..... ~....
      """'.. .... '" _ _                    1. ~' .      11.1. "--'-1. .... G.J of
"'0&#xa3;(;_"'" ,,_,                                                                                        ........ '" "".~<O ..... _"" .............. ,..., ""'""' ..
                                                                                                        "_7 ..... ....    ~
      ",. Fe Q" W      ~ ~_        '" ","IoL"""'"" ....,...
        '- .", ... " - mof ........ "" ..... , _ ( 11") ( _ __
                                                                                                                                                    ~"""      'iI. '  in ....... ~ ... .....
in " 'lEG-,.,.-.O,on .... .. .
_    .... _      ... , .,...,...od n (''() """ """ "",<2<>!.                          ""...,.,. d ",i _                      ' ....... """ .. .... ,..., """" "" ,..,."',
m..,<2<>! . .... ,.,....-.                                                              ( ') , ...... d .... ....... d " ""''''''''~' ' .... .,,""" .... - .. .....
          " " " . ....... "' ..,,,"" ","", ... "", d " " , _ ", _                                (l) < >> m _ d .... .....,.._ ait ..... opi"" ....... _ ... d i ""~d "",,        .. , ...... "'_              (. . ",,,,,,"'0 i....,." _ _ ...            d
              ........... n . ...... " " ' _ . '" , ... PIA _ " " .... in",",
                                                                                                          . """ .. <Df ... ta.). _ _ ry.
m ....... " _ , , , _ on .... ,....,. ..... ".,.. d PIA ,""                          _
              ......... .. ..... , ~ "'" """" ........ ,,,," "'" ",mn<
                                                            "'''n""
              . . . ~ (\non, .....                                        I. ............ "'~        * ",.e....... _                ........ _ _ ... ~ , . ~ ""..". "''''' of _ _
do ...
              ",00... . ,.,..,..,. ,..,
0 ...
of ... . . . . - _ ' ....... """.
i .... in ,,_        .. ..... .....
at..,n...      d_            ..,.....,.. .. .,..,.., ....."',"".." ,.,
                                                                                                        ~"'.,....<i.......
                                                                                                                                                              -    ... , ... QHO> .. .,,,...
                                                                                                                                      . ... o-d~ ...... (bo'" d _ . , . ....... _
              ' _ _4.,. i.... _' ~ ........ ~ ...... ... _                                              ...... .... 1."'''1_"'''"'' ......... ,.;'"                    Li ... ... ... _ .. ...
_ _ ........"i"" '''''....._'' _
                                                                                                          . . . ..o,.._._. ._
              ~                    . ( ~~                                                              ............ ) _ " ' . . ,.;'" _                      PIA ~ d. ,,"", ... , ...
1>OO'f) T... ,,"0&#xa3;(;_          "'" PIA ......... _ ...." . ""'_
f..- , ~. d .. - . . .. ....,...,."" .... .......... - . .
01.,. "" .... 01' i"' ........ "'. "'_                        """"""" Inn
                                                                                                                      ~,                                                        d' ... _        *
              ........ i ~' ioti""...-            .. _ i"''''''''_                ",_                ~"'.,....<i.. "''''' ... . . -...... d .....""" .......... ~-.
              ,..,.,. " " "i ..... ",""...NL.,. _ .. " .. ... ..".                  ~i
              ...... ,,_ ......no.    ~                .......".,..,......  ""' ...... ......          ~"'  ........ ..,). .... . _.,._..
                                                                                                        ............... i ... _                  .......... ( .. _""" _
d _ . "" ~ "'      ...
oIo-
              .......                                "."            01 ...    , on " " _              , .., _          iot ...... , ( " " 01 ) , ............. ........... .. , ...
Appendix 3 - Page 5
-                                                                                . _ . . __...... (-..,                              .  . ,
                                                                                                                                                .i_
                                                              ~ _      I -
' _ "'.'''''' i.....- n ........ '..
C.......""'"' _            , , _ ~ ""' ...... d K'" _ y....._on<'        "  pM<
                                                                                  " m..
                                                                                              ...                  on ....
Ii<"".,. _ .....
_Ii<.                M ... " ........ PIA ~ _""
d ,,,. ""''''''' ...... , _ .,. ....
11l ~ """ "'''''' imp """""'" an ...... . ... _                                                                    _              ...... A                        i"' ..... i, .... _          . ""
~_          ............."""..... .. ..... ,._""1
                                                "' ~
0(
                                                                                                                  , .... _ .. of , ....... an .....0 ..... _
                                                                                                                  , .../ip< ,..... , _                d 'Ifi< .... .... _
d , .... .
d ..... ..
._    ~
MlIlG-' ' ' '
                  .. .. _D<Y-<D"' _ _                          c.w "_                                            ,...............  .
_ . ' '''' ~""" _
1 . ... ....,. .. . "'~. _ _ ""." ... QHO>."""'.. ....
                                                                                                                                                                    ... - " " """ '~ d
                                                                                                            <Df ....... ....        ,wo. _      ~      I.. .,. * * ~i<_ '0 01' .... ""'""
      "..., _ m ....."" .
" ,. . " " '. . .... on    Fe    aHW bOof _
d . , ... rlI< ... _
pot ...........      " ' _ f ..
(.....
                                                                                                            ...-_I{R;., ....
                                                                                                              " ....... (""h ......                , ""'.om......... ...          '00"" ,..._
""""OJ """ , .....              ) 0/.", ~ ........ ...-.". ....                                        1.,.. . ..... .. ............ a .
* m- , ... !........,.. of
....    , ..._... ... _ ........ .....,.t .. ,-..-.. ., on_..
          ~        ~
_ ' " "'00 .... '0 ..""'_~.. 10m ..... . _ .. (
_ _ _ ... oomrl)' NlJlIC-' 8601" L.... -""., *..-                                                          ' ..... io~ Ib..... tIoo >Ie ~ In>", , box "'_~
m ""' . .... an orin '" "' ". _ i.... .........- _                                  "P"l "'
_ _.tOo ,_
                              """" "'''** NlJO&#xa3;(;_,."' .......
                          ,,, ' k . . .... d .......... d ... '_ i.........
                                                    ~                                    d ... .
                                                                                                      '''- "--' d          "'0&#xa3;(;_'..-.0. =""'''''' ....... '''- '. ..                    ~
                                                                                                  ........ of. - " ' _ ..... ind ... ~._ (_.....-'"
d""'........ '_ . ~ .                ~  _"" , ... "" .. oft ... _ .
AA "" _ _ pM< 0( , . . - . . . . . . . . ,,,. ....... ' ''''''. 0(
om.      (' .... ll() Tlw ""OS . . ~"' . ""m ..... d <D"''''''
* _ _ _ of . ... "'"," (1 6(.
                                                                                                                                                                                            ,.iI"
""0&#xa3;(;_      "'" '" tIooso d o","""                  ~ SHY-OI-01 01 ..... ", ,,~                        "'lEG-,.'" .... _ .. "'"' " ' - ' '" ' ''- '                        on ""' __
_ ,,,,,,,,,,, ***        "'''~ "'' "  .. l :><~ '" _            to . ... C....... _          _ ......._                    (lID&#xa3;<."""'''          i" , _ .... "'.,. .... , ......,,'"
d i",,'''' .... NO<: , ..II' .. ... , ",. ' ........ ... "., h ..... <rt ""                        _ . ) _ ...... .. , ... _                        bo~",,",," .... ..... ......no """-
on """" fu .. " ,,"" ... _                                                                        A...... "" d"' .. _                '"'"'''' .. _ /ip< ....... _ . ",. ""m .....
      ".,. ..... U...,. ~ .... , ... _",,01 '" of , ...                                            of .. ..... - . . . ... q . (U.'"..l"I ( _ ......._ * . . - _
. ... ~.t<nMd .... _"'~ ""' .... ~_'" " f
,yo... . .... "'""""""                    .... _ . " - ' _. .......... . .....
                                                                                              ..  '"'"'~_. ""-..,.., "'_                                ~            d ' [ - , /1<. . ..... d
                                    ~
(Ita'OP) (1' 1_ ".,. ' .... illa<_ ... .......... <on 10""""" ....
l' ""' .... -.. ...... ""'...... (" " '). , in< . * * "".......... '0 d ............ .,.
ftGN. ,.. ..... . ....... '"' ~ .... .,-...w", ..... . ,. ~ tK                              ...  . . ..
                                                                                                            ' " " . . . . . . . . . . . . . . . . !)O.A , " - . .
                                                                                                              "'" h,~........                        i,''''''"" ..... ""'''''''.... .,.
""""" .., 01' I... "          """on ...          ~""~            _..,od _"""              H,.t  """'.... ...i"            , ... ",",,'" Wkro . . -L....                  of ..!... .,.,.....
...,..., ..,...,. " . ... . 0 . . . . . . . . . . . . , . . . ~ ... """,," " " , - , . , . .
,,,. "-I' ..... " .... ...., .... ("" "') -...w.., .... ao " ' _ on
                                                                                                  " " _ .,. , ... , " , , " _ d . ..... I~ ' "," ait ...... ....
                                                                                                  ......... '" , ... ..., "' _ _. ' d - . G_7 of ",O&#xa3;(; _,.",. ~
_ _ .... '_OJ _ "' ''''';';'''' q_'" an _ _                                                        ."' ,.....
,'"""">' * ..,...... ,,"'an ... '''''_ ,~........... ...., ......"
'mq_n'" -., ..... ~.,. ""' '0 "" ...i" . _iw                                                                  .... i .. _            ~  , ...    ~        of  '_1' "", ....... _ *
,...".        '" ",._.                                                                                ""'''''''' of 1[ _' ......... Tho .... ""~ ....... _~ i
      ",. . .... ,.., "'" _ _                  ...... i ....        _            "'" "'. of
                                                                                                        ,...........0<. "". _ ".-.., *_.
                                                                  ~
                                                                                                        ,oe ... "'." (>'I( .....              ' Ocrl ' 00 (101        ~  l ' '""'.  (""'~    ",.
""""""" ""',.. d PIA.                            _        _ _ ... ) .. ... , .... _                                                                                            of 15 '"'"    . ""
                                                                                                        ""' ~ -~.... '" "'..." ~(
( ~.
                                                                  . ..                                                                                                      _.I. .
opi"" ...-~ U                                                      ( ~.
" . ..... ) . . ._            in  "'0&#xa3;(;_1I"' .... ' ... _ iL............ _
**................Nl C.
'"0M,,,,,,,                  ___      -~-.
      .....,'............. of ....,.. _
                                          ... ,_              _"" -i""'-.
                                                                        ..... _ rot'" "",.,                ...... '" , ... ,."..d 15 _' OO'""' ......
d" _' .... ~....
                                                                                                                                                                                            ~
.......... _ " . , .............. ... i_                            " . ..... """"'-
_ .. i, , ...        '.".. ' OO_lI.'''''' .... _ _ *                  ""'~ d
                                                                                                        "_G ...... . . 100-100...., * ""''''''''" d Il _ 7 ..... ~....
      """'.. .... '" _ _                    1. ~' .      11.1. "--'-1. .... G.J of
"'0&#xa3;(;_"'" ,,_,                                                                                        ........ '" "".~<O ..... _"" .............. ,..., ""'""' ..
                                                                                                        "_7 ..... ....    ~
      ",. Fe Q" W      ~ ~_        '" ","IoL"""'"" ....,...
        '- .", ... " - mof ........ "" ..... , _ ( 11") ( _ __
                                                                                                                                                    ~"""      'iI. '  in ....... ~ ... .....
in " 'lEG-,.,.-.O,on .... .. .
_    .... _      ... , .,...,...od n (''() """ """ "",<2<>!.                          ""...,.,. d ",i _                      ' ....... """ .. .... ,..., """" "" ,..,."',
m..,<2<>! . .... ,.,....-.                                                              ( ') , ...... d .... ....... d " ""''''''''~' ' .... .,,""" .... - .. .....
          " " " . ....... "' ..,,,"" ","", ... "", d " " , _ ", _                                (l) < >> m _ d .... .....,.._ ait ..... opi"" ....... _ ... d i ""~d "",,        .. , ...... "'_              (. . ",,,,,,"'0 i....,." _ _ ...            d
              ........... n . ...... " " ' _ . '" , ... PIA _ " " .... in",",
                                                                                                          . """ .. <Df ... ta.). _ _ ry.
m ....... " _ , , , _ on .... ,....,. ..... ".,.. d PIA ,""                          _
              ......... .. ..... , ~ "'" """" ........ ,,,," "'" ",mn<
                                                            "'''n""
              . . . ~ (\non, .....                                        I. ............ "'~        * ",.e....... _                ........ _ _ ... ~ , . ~ ""..". "''''' of _ _
do ...
              ",00... . ,.,..,..,. ,..,
0 ...
of ... . . . . - _ ' ....... """.
i .... in ,,_        .. ..... .....
at..,n...      d_            ..,.....,.. .. .,..,.., ....."',"".." ,.,
                                                                                                        ~"'.,....<i.......
                                                                                                                                                              -    ... , ... QHO> .. .,,,...
                                                                                                                                      . ... o-d~ ...... (bo'" d _ . , . ....... _
              ' _ _4.,. i.... _' ~ ........ ~ ...... ... _                                              ...... .... 1."'''1_"'''"'' ......... ,.;'"                    Li ... ... ... _ .. ...
_ _ ........"i"" '''''....._'' _
                                                                                                          . . . ..o,.._._. ._
              ~                    . ( ~~                                                              ............ ) _ " ' . . ,.;'" _                      PIA ~ d. ,,"", ... , ...
1>OO'f) T... ,,"0&#xa3;(;_          "'" PIA ......... _ ...." . ""'_
f..- , ~. d .. - . . .. ....,...,."" .... .......... - . .
01.,. "" .... 01' i"' ........ "'. "'_                        """"""" Inn
                                                                                                                      ~,                                                        d' ... _        *
              ........ i ~' ioti""...-            .. _ i"''''''''_                ",_                ~"'.,....<i.. "''''' ... . . -...... d .....""" .......... ~-.
              ,..,.,. " " "i ..... ",""...NL.,. _ .. " .. ... ..".                  ~i
              ...... ,,_ ......no.    ~                .......".,..,......  ""' ...... ......          ~"'  ........ ..,). .... . _.,._..
                                                                                                        ............... i ... _                  .......... ( .. _""" _
d _ . "" ~ "'      ...
oIo-
              .......                                "."            01 ...    , on " " _              , .., _          iot ...... , ( " " 01 ) , ............. ........... .. , ...
Appendix 3 - Page 6
                                                  <_1_. ._"' __"'' *)'' ' '                                                                                                .,
                                        'Eo' t
J
                                                                = !.";::Z---
00 _    ... - . . _ " , , - -
0-.,""
                                                  'w.. -.-. _ _._'....<.l'4..-:.,.""
  ~"'" ............ ...."._Io<.... ( ~~
  ....p.. ) ' _ ' _ ........
d ............ '"    ""so"..... _
  .. """' ...... ',.... . od _
_d,"...
                  .................. , .. !.......,. ....... =- ,...
d ~_pM_ (""'"
                                                                  <i,..... _ d
                                          .. d , ... ""'..." ... d . ......,.."
p--
_          ' 0 ""," ... .. , ... , .....
                                                                                              " *""" .... ""'_ ,.......,.",.-v.
an , ...
                                                                                                    """ .. ,... ..,.. _ 0( -"",""_- """", d'_
a1w"''''''''''''''' '"
iod"....,. ""'"' .... " ' _ ... _ _ '" , ....."'.,._
                                                                                                                                                            '0.",.00 , . . .
d .... '",." ,........_                  ... .,.    ~~          ... _          ..                """' _ _ .................... _                          lor ~w ""' ''
  "' ..... ... jo.d-- * ~ ,~... ,..., , ..... "',., """"" - -
  ...... ...,.. .. " ... ~ d N*",I ...*.,...., , . . . . " ' _ " ' _
  .... b _ _ """, _~ ... """,,, d .... , . , . d ....
i...._........
                                                                                                          .,. ......u.d_...........        """'"
                                                                                                  "", .,.... d Fe aH. . " . ..,,"'._ ",. ,,,,om _ " ' ...
                                                                                                                                    "'. d'_ ..
: 0. """'_ ,"'.,._
d .. io~ ""'" .. , ... _ , ~ d _                          .. "",,,", __ ~                1. ...... . """' ..- . ~,.... """" , ............. "".
          "''"'~                      ,,,- -.... ""'....-                                    ,,_          . _...... __                ... _ T ........... tbo _      .. d ti~
  "io " _ ....._"". ''"''''''''''' ~""'"""
  ~'*    """"'--                                          . od , ...
                                                                                              ~",m.i-,.,.            _ _ ........... ""..,......          "* ""'_""
* ",. QHOo ...... .        _  .. ,......".,' . ""' " ....
_ _ d' ......."'.,. _ _ .. ..,..., .... ., ... ......
                                                                  "* ..... ....              .,. ... . . . . . _            ......... ,,,,,,,,,,,,,,, *
* od .,..,...,
* q....at;.,. ."''' ..          fnq"",,;"          . od <u _          ... d
  " .... - ',... ... ...It " _"-'_ ".,.,. ... _                      .... _      d
  , .....-, "" _    ..... u ... , .. ~ , & .. . ~ ..11 , .... ... , ... ,, ~ . . . .    '- c... " ........." ... ~ " ........ ...., ... ..... , .... ....... ~ ,"'-
H,., , ......... """ d .... ",ok . .., ...... .".,... .....K .. ""'"-                      ,..., .,. ....... ... _ ... "" " " ' - """"'""- opi .. ,
IK.t , _ "' ... '" , ... _              d .... """' .,. .. " ........... ...              . .... _          .... <riO .... . -        _Mo"" "' ..." ... ... _        ~
  '0> A
          """"m ........ ""'"
(-      """"' ... "'''''......      ,.,;'''  .... ".....
lor 1..", ,, ,,"' .... . . - ..                    ",.
_ ..*0","_m  ...... 1.-"'_ (" *""" ""......
                                                                                                                                              ~
0 .00'% '"
                                                                                                                                                                ''''')d,'''
q",LO. _ - ' o( .... C.... _ , . . . . . . , ... ,.,;"',. " ....,                          .-.
                                                                                                      ..,i-.""      "* (..." "';"'i, ....._,......... "" ...
                                                                                                            ...... ) .. _ , .... _ o p i " " .... , -
  .... _ .. d'... ~ ... od.,nw' ... ..,.. ........ "'" '""" ....
  ,. . ._.on.
_ , ..... ' .............-.m.                  "~,, .  "'"" _ .. "'" d                      " n.........    ".d""        iod"....,. "' _ _
                                                                                                    ""....n.ty ... """..".... .. if
* W  ,. '"  "'I""""' .."
                                                                                                                                                            .... "'''''''01>-
*  """~,,,, ; !K    ....... lC1< .,. _ ........... " ' _                                          ......-_0(.., Fe , ... ~                """"w, ...      Q!HClo ( .. ,.,...
  'Pi"" , ... QHOo. "'''' d ,........ _ , ...... ""'" .. _                                        _~ )      miJt<  "iL'............ ,.,;"'  ...... _~
  ~.... ''"'''S* _ , "'Q'tO>. " .. " .. <Df .... l.Uf", lWl                                    o  A IDOWOn. , _                    ~  ,..., ....    " . d _            ....
                  .,. ''''''''..                            d_ ""'" ....
  "~K_                              q' _ _ ..... .,.                                              . . . - """~ ... -..... , .,. ... _                          .. """'01>-
  , _ _ d .u ""'_ "'"""'_ ..... .,. "'_
          ""'"""'"'"      "*""""- ,_"" "* ....."'" i- . -
                  "'no im",,,",,, ' " _ , _ ,
i,
                                                                                                  ......- " ........... _              .. _ ... . .,.,-". _ h
_ .......... ,""' .. ............. ...-q""'....
                                                                                                                                  ~
  '- !l<f;""""' ''' , .....'''orili_ d          ............ " " ' _ ,....... _                  ~-... jood- ".. * - , - ~,;, ..
        ...  ~  _ _ ... "'t!o ....                _ h PlA ..... ~ ( ~~                            ......... . . Ii"" "';"'i, , ... ""'''''_ "" ... , ...... _
        .... 10. . uot'"'""    ....~ no""",,, - . l 1MJ, ,~"""                                    .... - . . ............ m.... , ......'" ons<_
        ..... no ) ........ _ ' " .~'" - . . . (~,,,,,,,,,,.,;t!o                                  "'i"b ... "" ......... -..~_
__ "' ... .......,...... -..., .... ,,.,,."",.,;t!o __                          * ~  *  ~  .. ",""" ,...,
* 1..,,,. - . . d '" >fiG. 0 ' "" ....
        ............. ''*'''') "'os,.....              ,... _ _ ... .,. ""                ..... , .... Fe '" .. ~ "'"" , ... NlC "';LI ... an "",", lor Appendix 3 - Page 7
i/yi"" ..... ' ... _
                                          ..". _ ~ _      , -      . _
                                                          .............,.iI".....
d "*-"-<I . . . . d .... _                        ~
                                                                                      ... __ .              (- ) . . ,  ....,
                                                                                                "'~ <riO ..... ,..;LI ..... . . - .... . "' " ........
PIA _            ......"," , , _ T .. . _
                                                                                                                                                                            ,,,,,iA<
I ... ' ... ... ....... """
""" _        d sol.... own .... ....,... " " ' _ ..........                                    i._'.....
....
* tt ........ ~"""ol""            ~ ~  .... ",. .._ ...._ 011                ~
....... _          ..... ~ ,,,. - " ,i ", _~""'" ~ '""" ....                                  *  ~  , .. p<no.nt ,..., , ... NlC ,,.,, ...        "'I~uM          d .... _
' ody.. " ............ or . . . . ~ .. ~~;dy...sa-! . . '". "lC.                          "',., " , .... """",..;" ' ... C.... _ . d l"" .. " '" ... ~"" ....
....... on A""" or ""' ............ i "( ll ~ >to .. """' ....                            " ... "", . -... '" ...... <:.-"''''' i, "" ... "" _ " "
_rot", ""' .... . d" ..., .. Ok .... '" ... ,, "'_
io .... . ,,""' .......... _ , . " ' " ,,,. - " ,i"" i_ .. "
                                                                          "' .........    .....,.." """ ........ fua."
                                                                                          , _ _ "';LI "" _ _ '""" , ..............
p""" _ ..." .....""C_      '" ...... ", ...
... ....... . ... f ... _            ... _~,
" " - ",,,",,, , - . .. II U...,. _ _ _ ... ~ Fe , . ,"'-
_                " ......,~"" ' ...... " . _ d .... . ~ ...~
A_        .......... ""01 ........... d .... , . ... . "" ... _
..... "'0&#xa3;(; "1"'" ..... .. Nor: ""'" ..... __ '0                        ",,<nOd
                                                                                          - - -                  .. "'~ pI ......... _
f" o .. ........ a<> d l"",...... 0 . . d .....
                                                                                          ..... 0( * . . . - , _ _ . . -.... - ' " _ _"""" , ...
_d_... .
                                                                                                                                              ......... ~ . ..... . . '"'~
i","" .. ",. i,""""'_
"' '''"....... ''"''""'''''' .... - . d ...,. d ",,,",,,                                  ,..;LI .. _    .... , ..............-,,01 ....                                d l_
...... ~ ""' ..... , ,,. NlC _          ... ' ",. ..........  ""'''"~      ,,,,,,,.    '""'" _                ............ d "' _ _ 1/;0; , ....."'_ r i : .p-
_ (... q."'(l~lll)                  """' '''''''''. ''''' ''''' ''_ .....
_K'......... ..-.
prno<" ,. - . . . . . . " _: , _.... d ... * <>-<:01 ... _ " , , _
""",                                                                                      ....... ....." .... ..-..,d_."",
                                                                                                              . . .._"'m l.,.. pot......, ...... ... I......_ ....
i *
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                                                                                          ~"'I""""",".
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* ",,"'~        ,n.N ,...., ",.
: m. ... _ ...... _ _
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                                            " ("~    m'_....... ., ....
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of~  ..... _ _ ...... ""' ... ~<""""
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I._m_  ... "' ..... .. .
                                                                                          ............... 01 ...... "" " ....... . ...IIK_ "''' 01 ...........
ao _        .0 .......
_~          .....m__ 'y,,,. .."'_ _
d ... "....., "' ....... " ........            .... m ' ip;..
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_ ( ~.,..,.
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T". , _ _ .... _ _ " . ""'..... _ _ _
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,.."'an ...,. .................. ........... ." ..""- .... "" ...                        ,..;LI * .,;.t. . ........ .,. ......... 1" 0" " ..... _                .... ..... d ....
po ....... 0< '" ""_ ";,k " ... .,. ....                ~"M<H<'"          _
  " "" ........ ~ d ",. _ ..                (_ "''C .          _ L.,t. ...    "",
ct>f .... LW"",,",,,,,,,,,,, "''''~'''''''' __ "" ......... 01
                                                                                          ... " ......... Fe "n...... , ... ... .tlod _ , . ... .... _
                                                                                                      " . ...... ~ ;,;.,." ~ -~..... "''''.''''                  ..                  .
b y " ,.."'''' .... ipj ;, . ,,""or ......... . .. ,. ..
    ~ ... _      ....._ " ..<<oo .... ,.."'''' (HTat). ,., .. ""tho-
    ""~~.~ ....... -                                          ... <. . ~-. ....          *. .,.. .. ,,* ...._ .... - ...
    ~              .... , ... ' ....... """ .. d ....      ",....no "' . ....
                                                      ~ """",,- -"                              _    ' .. _    d ......... , .. ""'''''' ........... """. ....... i *
                                                                                          ...... o ....... ' ... FeaH. . d"" .<:.-Ia50 .. .
    " ', . . . . . . _ " ' " ",. . .... .,. 0(, ... , _....... , _
(. ) ... '" ** ",. ___ d ~"'....,...,. '" ",. ~ ... b,,"
    ~ """'.. d ....
* ml....... _                                    d ..-.. 0(
                                                                                          ~~
                                                                                                          ,..                              ~- .,
                                                                                                        '''''~....... ,""" ......... , _ .. m .. _
                                                                                                                                                              .. ml.... m _
i" _ .... i . ... . .,..,;.. """' .... _                ..... , .... _          ...,..,. .
_" '"          ..... 'k ... _
                    ""          ~ ...        , ..... " .... "''' (to)
    ....... " ................ , , _ !'ilwo hq""",
                                                                          <ri'" ..
                                                      ,.......,. """ pot""'"  -'-        A .... _
m",_....,. _ ... ..
                                                                                                            "'" ....,. ". .............. i. "'" ~ ~ .... .
                                                                                          . . - - i ....,........ 01 _                _ ...-
                                                          .I_, ........-                  i"" .. ;.. .... ' ..      _._~ .... , _ _ ...... PIA
    """"" .. ' WI .. _
                        ~ --        "
: .... (')"*
                                                                    ~"'""                            ~                                                                d _.~
    """"" . ....... (q * ...,. ....... .."",~"o(
            ... mot ... f,.. ... _              . ... ", .. __ , ... '" ..                ....,.      ............ "'_...... .................... ... ,.
                                                                                          .."~ ............. ,,,. ...... ,..., ... _                          .. , .. i_ .. ..
    - - . " -~ ~-                                                                        ..... ..... _                  , .. oni _              ..... 1. . (q . ..... "" **
    .... ) T ..... , ... ".""" a<> ... . "' . " " " .... ~ " ,...,              ",.      ..;.0:_ 01,.,. d .. ..... ) , .. 'M " ... ~ * ~ ........... , ...
    ......noW~ '" ... """""."._" ,..;on ........
- - . . . d "'_                ",....no.                ""'"~
                                                                                          ............G...,..-
_ -.00:,"""".
                                                                                                                      """.........        m_ . . . . . . . . ..
                                                                                          , .. ~.. o(q,...,," ";" PIA ....... ,. ... moot ... d d .. is<< "
                                                                                                                                    ,n..v. ... . - ... .u. ,........
                                                                                                                                                                            ~
......... .. ",. , _            _        d "'_            , ......... doll .... ..,      , .. ... ~........ ,..;U          oo: .... pl. " , ... ... .,., ...... .,.,.. (_
(.. ~ -'Y''''''      _    ) ....    ,.i< ~ "    ",. ,....        PIA """'01.          ,..,. ..................... ) ... _" .. oop.. m .... _                            .. ' ...
_      .." ....... '" .... ....-.. 0( .. , ......              ",....no. ""'"
                                                                          ....... ,.{n, ...
                                                                                          ......"' ''' ... ,..;tIo ""H<:_llro. . ." " ., 01.., Fe w""-
I.... d 10 , .. ........ " i" ~ _            _    " "' ...... A,.
... ~"- "",,,,. ~~, .... ,0 .... """.. ,..;"' "' ..... .. ,,_ ... ,...
                                                                        ,                , . .... . . . . . . - .. .... 25 . ... _            _ _ ..
                                                                                                            ~-'"
.... ",. " " ............ ' ........ _                      * " ...... " " " . 0(
"'..",    .. "_'1..-.
_ o o : . " . _ .......
U ... .,. , ... Fe a H. . m .. ~ ..... ;,
_~          _ _ ........ ......
                                                                ~
_    ,. ..... , _ 0 .... i" 10 en 100 .... 10 C... " '.H                          ~
...... ","To" _ _ .."                                                                    . _ ........ . .. Ioao"'" .. ,.".. ",.                  m.n..o .... """" .. ",.
  "  ,-",.~        .. d , .. _oo:_",. <rl",", . ,,,,. _                            o(    NO<: . ..... 11*
* 0 _ ... " ' _ . , _ .......... ",.<aJ
_<aJ          00: ... . . ....,.;", ( . . _ _ ...... 'S'..              ..... -    c.... _          ...................... ....- .... _~ ",NlC
    ,w) _            ... _          .. ..,..Ioi.. , ......... _
_ "-..d..,;...... ""' .... _ ",.,,_o( __                                                            *. __ _ .0"",","                  .... ",,,,,,,,,.
                                                                                          ............... d""'..... '"            , ~,            ,,_ . ................          ~
01 ""'iI' ......
    "" "'om; .......... "' .. ....,. .... _ ....... ' - ''''''(111.                      , _ ( _ ___ ,.....                An<~;p.t'"      """_              Oa:~""", ,,      . ""
_    ....... ... ... ..,... _          """ 0( _        . . . . . . _ _ '"              ",.,..., ...... Aa_ . ) , ..... "" ... ....                  ~  , ... " , . - - . .
ttU''''''''ol . ... _ _ d ' ..... , .................. _ _                                o""'........"""..              ,..;U ... ...... (.. ~ " ... _        d,. ..", TID&#xa3;).
Appendix 3 - Page 8
                                                  ~_ ' -"_"'                        __            "(-"''''''
__....... ... .....-._-i.o_
                                                                                      ..._ " " ' _ .. ow                  oIq"""""'''' PlA ...
_ "" ... _ i""" ,....,..."" '0 ,.. ...,"",.,'" .oJ.... "...
                                                                                                                                                        ".~ T ..... _
                                                                                      ..... .. ,~_ ... "' ...... ...- ..... . <10100"" "IU""",, " .." . of Add~lo na l      control,
_ _.... i, _ " " ,.,;...... to" ... of
                                                                                                    .... ,,, ........ in ' . ' ..i ' ........... _      ... ~~_ d
                                                                                                                                                      ~.,....,.-
                                                                                    ' ...... ...... " ,.u ... '<n>~"" ( i"..,... ) _ _ "" d                              ....
                                                                                    , _...... _            (~      ... .... lCf.... , .......... _            ",~"
                                                                                    ..,' " ...... ct>f ...... CRf) >pi'" QHOo ( .. ...... . ..,.,._
                                                                                    '~. q..          ,,-'I>< ....
                                                                                          ,,_,... ~~..... ",,""""oJ
                                                                                                                        <Df)....,. .. . _ . _ .'
                                                                                                                                    .... """b _"""'" , .....
                                                                                    ,.., _ _ i"..,.4 _                    ........ " ........ _ . _ _ .....
                                                                                    . . .... _ ' " " i ...." '>' (.. ~ _                '0 .... ,......""') '"" .....
                                                                                      """,.""" ~"" __ "'"''q''''''''' ......... d                          ...... ......
                                                                                      """' d ..........        i, ........ i_ ' ....._ .... .0......., *
                                                                                    ......... _,oIoty"" ........ i p i'_d,.......... "'...
_; .... "',"" "............. 0""''''' b_ .....,...... _
                                                                                    ,..., , _ of .... '"""" .,., " ... "' . . o""," i ", ..",""" ...,.
                                                                                    ............. ..,. _              .. 0""" ond "" ... ,,,, .,,,** d . . . ...
                                                                                    ""_            ,.,;.. ""' ~ "". ~mK""'" .....""""l""""
T ..... ....... an ..... ., ......., ",i _
                                                                                                                                                      ' .... , _ ~ "'-i,
      .............. . ..... _"", """"' ... ", .. -... I ......                      LK ...... dl" o .. _            ..... ",. <H. . . . . ................. _ " "
_rlI< ..........
(. ) _ , .... ~""_ ...... _ o f _ . . , o _                                        ''''_'-'                      d .. ~~"" ,....,.~
d ...... ;..s. ...... .... ,.,;'"    d""'.... __ (....... '"                      _ ......      4."0_"" oJ '''- '''~w'''' , !"""",,,-...,
                                                                                    ' _ " " "" " " ' ' ' . _                    .. _ _ _ * "                    m,,"",",
              ............. U " ) "" ~ .... ,..,...,"""..
      ........ ,..., "'"" _ _ Tho 0                      """'w ...,. ...,...        ,<><>, ... ~w ........",0>< ................ '"              0...,.""'.
      ....._        of . ........ hq""", .. "' ..... """. ( .... _
o ',....a U,. ~.... I<" .u) .. ",0* .<bi<<' '0 ""'""""'.....
      """i"" ................... '......            d . _U". ........
      ........... d '" _ _ _ ",, ..,.....4", .. _                  ""''''~~''
(,;) _ """"l""'"            ",.0, ...,. ... _      ... ., .....,.,..,.,. ",bk            _    .... " m-d ." ....... ..... ' " " d ""' ............
                                                                                    ,,"",,,, ... .. , ....... _        01 .... 1>_... d, ... A""_" .......
      ...oJ ....._"" ........ '''''_ ... , ... i"''''_ d ....                        """". ... .. .... """" d _                ........ (.., .. _          ) "' .... ....
      .. d ...... , .......
(,;;) ~"'. , ... a"..
                              ~ ...... """" .... . . .
                            ~~....................              , ... _On<.        q"'"'" of 1em .. , ... US NlC. .. ~ .. , ... ...""" .... '"' ""'" m..
      ........... ,WI' _ ' " ..... '" _              .... _ .. , ... . ",,"' _
4>iL'". .. .... Lodt , _ ... <riM ... "';"...,. pm d arum.... iodud"" , ... _~ , pa''''~ T... "IU1oO>,
it, rnJ.
                                                                                    ,"'US_ d' ~.
                                                                                                            ",. .". of _ , om"", _            .
                                                                                                                                            ~ "    """"'"-...,.
      .... .... , .. 4it. d .... . .............. ~, okI-.. .......                . . .......... "" ................... ...,. q.J              '_ Lit. "' _
* _        .... , ... orq>OO'"      O""''' ~ '''  """ ,.., .........        "'Lity ....... ""' ...... "' _ _ ... ...,. ""n! ... ~". ~w d
                                                                                    , .. """,.. d ,,'" ~w of ...,. """""'"' ~~ . . . - , .. """'"
      ............... okI ...... " " .        '"+-" ""''''''''''''' ....
      ", ... _OJ PlA ~ '" '""'''''''''' ""' .... pm--
d""_.... ,.,.....,."
0_"""'              ...........    ...._."
                                                                                                                                                        ! I<,  ........
                ..."'~--
    ""'. ,.., , ... _ _ of ...                      .",~      , ......... _      ..
                                                                                    '0,.,.
                                                                                                """" ~
                                                                                                              ... _ . ......... ..-. *.........,., """"w*
_ .....        "'" _~
                                                                                                                  ............... u...m."'.......,..." .<m......""~. it,
..,'" "'........... _ _ ...,. ..* ,.., '" ,m.in """om_'" _ .....,. _                                                                                                  s..."
~""""""wof~.,_.. - ' '''''"""",
......... ~ ~ ~ ...,. ~ ... '" _
In"" , ... ""...w,. ~"" ..orr." ....
I .... """;., _ ' " '~ .
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Appendix 3 - Page 9
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Appendix 3 - Page 10
APPENDIX 4 A CRITIQUE OF THE RADIOLOGICAL CONSEQUENCE ASSESSMENT CONDUCTED IN SUPPORT OF THE INDIAN POINT SEVERE ACCIDENT MITIGATION ALTERNATIVES ANALYSIS Dr. Edwin S. Lyman Senior Staff Scientist Union of Concerned Scientists Commissioned by Riverkeeper, Inc.
November 2007 In Memoriam: John Gofman Introduction In order to conduct the Severe Accident Mitigation Alternatives (SAMA) analysis for the Environmental Report submitted as part of its application for renewal of the licenses for the Indian Point 2 and 3 reactors, Entergy Nuclear was required to conduct a quantitative assessment of the radiological consequences of severe accidents at the Indian Point nuclear plant. This analysis is needed to calculate the value of the radiological consequences that would be averted if the SAMAs considered by Entergy were implemented. When combined with calculated core damage frequencies from the Indian Point Probabilistic Risk Assessment (PRA), the annual radiological risk to the public from severe accidents can be computed, and the value of the averted risk associated with each SAMA can be compared to the SAMAs cost to evaluate which options, if any, are cost-beneficial.
The calculation of radiological risk to the public is a highly uncertain exercise. The uncertainties are associated both with the values of the severe accident frequencies and the quantitative results of consequence calculations. This report will focus on the consequence assessment.
We find that in three significant respects, Entergys consequence calculations are seriously flawed and do not lead to an assessment of risk to the public that is sufficiently conservative to serve as a reasonable basis for its SAMA analysis:
First, the source term used by Entergy to estimate the consequences of the most severe accidents with early containment failure is based on radionuclide release fractions generated by the MAAP code (a proprietary industry code that has not been validated by NRC),
which are smaller for key radionuclides than the release fractions specified in NRC guidance such as NUREG-1465 and its recent reevaluation for high-burnup fuel.75 The source term used by Entergy results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.
75 L. Soffer, et al. U.S. Nuclear Regulatory Commission, Accident Source Terms for Light-Water Nuclear Power Plants: Final Report, NUREG-1465, February 1995; Energy Research, Inc., Accident Source Terms for Light-Water Nuclear Power Plants: High-Burnup and MOX Fuels: Final Report, ERI/NRC 02-202, November 2002.
Second, Entergy fails to consider the uncertainties in its consequence calculation resulting from meteorological variations by using only mean values for population dose and offsite economic cost estimates.
Third, the population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure underestimates the cost of the health consequences of severe accidents by failing to address the value of lives lost as a result of acute radiation syndrome, in addition to cancer.
As a result of these deficiencies in Entergys analysis, Entergy rejected most SAMAs on the basis that they were not cost-beneficial. In contrast, an analysis based on the more severe consequences that we have calculated would likely conclude that many of these SAMAs in fact would be cost-effective.
We have used the MACCS2 code to conduct an independent evaluation of severe accident consequences for Indian Point Unit 2 for the highest-impact severe accident scenario. Our results indicate that Entergys baseline consequence analysis significantly underestimates (by more than a factor of three) mean population doses and other off-site costs resulting from such an accident. This is partly due to the particular source term used by Entergy, which was derived from calculations using the industry-developed MAAP code, as opposed to our study, which used a source term derived from NRC studies and regulatory guidance. In addition, we find that taking into account reasonable uncertainties associated with meteorological variations (in particular, by considering the 95th percentile consequences over the course of a year rather than the mean consequences) can increase the consequences by at least another factor of three relative to the mean consequences.
In summary, we calculate for the highest-impact severe accident scenario that the 95th percentile equivalent cost of off-site health impacts is more than ten times greater than Entergys estimate of the equivalent cost of off-site health impacts. We also find that the 95th percentile off-site economic impacts for this scenario is over 70 times greater than Entergys estimate of off-site economic impacts for the same scenario, and is over 12 times greater than Entergys estimate of the total cost (off- and on-site) for all severe accident scenarios, the value it used to determine the cost-effectiveness of candidate SAMAs.
We have not carried out a similar analysis of Entergys consequence assessment for IP3, but we would expect to find similar results in that case as well.
Major Flaws in the Entergy SAMA Analysis
: 1. The source terms used by Entergy to estimate the consequences of severe accidents Radionuclide release fractions generated by the MAAP code, which has not been validated by NRC, are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used by Entergy results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.
Appendix 4 - Page 2
For example, the IP2 cesium release fraction for the early containment failure, high release (early high) category used by Entergy is 0.229, compared to a total of 0.75 for NUREG-1465.
It has been previously observed that MAAP generates lower release fractions than those derived and used by NRC in studies such as NUREG-1150. A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable scenarios  the NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR. Apparently the differences in the release fractions  are primarily attributable to the use of the different codes in the two analyses. 76 Thus the use of source terms generated by MAAP, a proprietary industry code that has not been independently validated by NRC, appears to lead to anomalously low consequences when compared to source terms generated by NRC staff. In fact, NRC has been aware of this discrepancy for at least two decades. In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR quite similar to the Indian Point reactors), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without performing controlled comparisons for identical boundary conditions and input data.77 We are unaware of NRC having performed such comparisons.
In light of this, it is clear that Entergy should not rely on MAAP-generated source terms in its SAMA analysis unless it can provide a technically credible justification for the differences between them and those developed by NRC.
In contrast, we have based our analysis on the more conservative NUREG-1465 source term, which has undergone extensive review by the public, and which is being voluntarily implemented by licensees in other regulatory applications.78 The NUREG-1465 source term was 76 J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.
77 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.
78 In adapting NUREG-1465 for this purpose, we have assumed that all radionuclides released to containment are released to the environment in early containment failure scenarios, as explained in this authors attached report, Chernobyl-on-the-Hudson?
Appendix 4 - Page 3
also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.79 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.80
: 2. Entergy fails to consider the uncertainties in its consequence calculation resulting from meteorological variations by only using mean values for population dose and offsite economic cost estimates.
Entergy applies an inconsistent approach to its consideration of the uncertainties in its risk calculations. Entergy conducted an uncertainty analysis for its estimate of the internal events core damage frequency (CDF). As a measure of the uncertainty inherent in the internal events CDF as determined by the PRA, Entergy provides the ratio of the CDF at the 95 th percentile confidence level to the mean CDF, which it calculates to be 2.1 for IP2 and 1.4 for IP3 (ER at 4-51). It then bases its SAMA cost-benefit evaluation on the 95th percentile CDF (ER at E.1-31),
rather than the mean CDF. However, Entergy omits consideration of the uncertainties associated with other aspects of its risk calculation. In particular, it does not consider the impact of the uncertainties associated with meteorological variations, which we find to be even greater than the CDF uncertainties reported by Entergy.
The consequence calculation, as carried out by the MACCS2 code, generates a series of results based on random sampling of a years worth of weather data. The code provides a statistical distribution of the results. We find, based on our own MACCS2 calculations, that the ratio of the 95th percentile to the mean of this distribution is typically a factor of 3 to 4 for outcomes such as early fatalities, latent cancer fatalities and off-site economic consequences. Because these ratios are greater than the ones considered in Entergys CDF uncertainty analysis, it is illogical to ignore these uncertainties, as Entergy has done. For consistency, the baseline benefit with uncertainty that Entergy uses in the SAMA cost-benefit evaluation should be based on the 95th percentile of the meteorological distribution in addition to the 95th percentile of the CDF distribution. This would also be consistent with the approach taken in the License Renewal GEIS, which refers repeatedly to the 95th percentile of the risk uncertainty distribution as an appropriate upper confidence bound in order not to underestimate potential future environmental impacts.81
: 3. The population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure is based on a deeply flawed analysis and seriously underestimates the cost of the health consequences of severe accidents.
Entergy underestimates the population-dose related costs of a severe accident by relying inappropriately on a $2000/person-rem conversion factor. Entergys use of the conversion factor 79 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.
80 J. Schaperow (2002), op cit.
81 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol. 1, May 1996, Section 5.3.3.2.1.
Appendix 4 - Page 4
is inappropriate because it (a) does not take into account the significant loss of life associated with early fatalities from acute radiation exposure that could result from some of the severe accident scenarios included in Entergys risk analysis; and (b) underestimates the generation of stochastic health effects by failing to take into account the fact that some members of the public exposed to radiation after a severe accident will receive doses above the threshold level for application of a dose- and dose-rate reduction effectiveness factor (DDREF).
The $2000/person-rem conversion factor is intended to represent the cost associated with the harm caused by radiation exposure with respect to the causation of stochastic health effects, that is, fatal cancers, nonfatal cancers, and hereditary effects.82 The value was derived by NRC staff by dividing the Staffs estimate for the value of a statistical life, $3 million (presumably in 1995 dollars, the year the analysis was published) by a risk coefficient for stochastic health effects from low-level radiation of 7x10-4/person-rem, as recommended in Publication No. 60 of the International Commission on Radiological Protection (ICRP). (This risk coefficient includes nonfatal stochastic health effects in addition to fatal cancers.) But the use of this conversion factor in Entergys SAMA analysis is inappropriate in two key respects. As a result Entergy underestimates the health-related costs associated with severe accidents.
First, the $2000/person-rem conversion factor is specifically intended to represent only stochastic health effects (e.g. cancer), and not deterministic health effects including early fatalities which could result from very high doses to particular individuals.83 However, for some of the severe accident scenarios evaluated by Entergy at IP, we find that large numbers of early fatalities (hundreds to thousands) could occur, representing a significant fraction of the total number of projected fatalities, both early and latent. This is consistent with the findings of the Generic Environmental Impact Statement for License Renewal of Nuclear Plants (NUREG-1437).84 Therefore, it is inappropriate to use a conversion factor that does not include deterministic effects. According to NRCs guidance, the NRC believes that regulatory issues involving deterministic effects and/or early fatalities would be very rare, and can be addressed on a case-specific basis, as the need arises.85 Based on our estimate of the potential number of early fatalities resulting from a severe accident at Indian Point, this is certainly a case where this need exists.
Second, the $2000/person-rem factor, as derived by NRC, also underestimates the total cost of the latent cancer fatalities that would result from a given population dose because it assumes that all exposed persons receive dose commitments below the threshold at which the dose and dose-rate reduction factor (DDREF) (typically a factor of 2) should be applied. However, for certain severe accident scenarios at IP evaluated by Entergy, we calculate that considerable numbers of people would receive doses high enough so that the DDREF should not be applied.86 This means, essentially, that for those individuals, a one-rem dose would be worth more because it would be more effective at cancer induction than for individuals receiving doses below the threshold. To illustrate, if a group of 1000 people receive doses of 30 rem each over a short 82 U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy, NUREG-1530, 1995, p. 12.
83 U.S. NRC (1995), op cit., p. 1.
84 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol.
1, May 1996, Table 5.5.
85 U.S. NRC, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy (1995), op cit., p. 13.
86 The default value of the DDREF threshold is 20 rem in the MACCS2 code input.
Appendix 4 - Page 5
period of time (population dose 30,000 person-rem), 30 latent cancer fatalities would be expected, associated with a cost of $90 million, using NRCs estimate of $3 million per statistical life and a cancer risk coefficient of 1x10-3/person-rem. If a group of 100,000 people received doses of 0.3 rem each (also a population dose of 30,000 person-rem), a DDREF of 2 would be applied, and only 15 latent cancer fatalities would be expected, at a cost of $45 million.
Thus a single cost conversion factor, based on a DDREF of 2, is not appropriate when some members of an exposed population receive doses for which a DDREF would not be applied.
A better way to evaluate the cost equivalent of the health consequences resulting from a severe accident is simply to sum the total number of early fatalities and latent cancer fatalities, as computed by the MACCS2 code, and multiply by the $3 million figure. Again, we do not believe it is reasonable to distinguish between the loss of a statistical life and the loss of a deterministic life when calculating the cost of health effects.
Results of IP2 Consequence Assessment We have performed our own calculation of the consequences of a severe accident at IP2, using the MACCS2 code. The model is largely based on the one used in this authors 2004 study Chernobyl-on-the-Hudson? (copy attached), to which the reader is referred for all details. The model was revised, based on Entergys ER, to incorporate (1) the core inventory specified in Table E.1-13, and (2) the expected population in 2034. To calculate the latter, we scaled the output of the SECPOP2000 code by a factor of 1.145. This normalized the total population within 50 miles to 19.2 million, to correspond to Entergys projection of the total population within 50 miles of the IP site in 2034.87 We use a finer site data input grid than Entergy does, with 21 intervals between 0 and 50 miles, compared to the five intervals used by Entergy. This allows for more accurate modeling of the dose and economic consequences.
The model we use is different compared to the one used by Entergy in a number of notable respects. First, we use a source term derived from NUREG-1465, as discussed previously, with regard to both the magnitude and timing of radionuclide releases. We use a two-plume model based on the approach of NUREG/CR-629588 that more realistically models the releases that would occur in an early containment failure scenario.89 We also assume that the entire population of the 10-mile EPZ evacuates as determined by the evacuation time estimates provided by KLD Associates in 2004 (ER reference E.1-21), whereas Entergy assumes no 87 We have adjusted the SECPOP2000 input and output files to correct the errors disclosed in the August 2007 memo to SECPOP2000 users from Sandia National Laboratories and verified that the county data file is being read correctly. However, according to a personal communication from Nathan Bixler of Sandia National Laboratories, there is another potential problem with SECPOP2000 that was not mentioned in the August 2007 memo. When this problem is rectified, we will amend our calculations accordingly.
88 R. Davis, A. Hanson, V. Mubayi and H. Nourbakhsh, Reassessment of Selected Factors Affecting Siting of Nuclear Power Plants, NUREG/CR-6295, US Nuclear Regulatory Commission, 1997, p. 3-30.
89 Entergys model assumes a single plume with a duration of over 22 hours, which is longer than for any other early containment failure source term we have encountered. We note that when we ran the MACCS2 code using Entergys source term for the early, high scenario, the MACCS2 output file contained the following warning:
The total release duration exceeds 20 hours. This may cause erroneous results to be produced. Thus it is unclear to us that Entergys results for this case are even valid.
Appendix 4 - Page 6
evacuation at all. (It is not clear whether Entergy assumes sheltering or normal activity for the inhabitants of the EPZ.) We use the evacuation scenario because we have found that for the source term that we utilize, the all-sheltering scenario actually results in a smaller number of latent cancer fatalities than in an evacuation scenario, in part because more individuals succumb to acute radiation syndrome in the former scenario (and thus do not get cancer).90 In our model, we utilize the option in MACCS2 to calculate consequences for an entire years worth of weather conditions, starting on each hour of the year. Each of these 8760 results is a weighted sum of results evaluated for each of the 16 compass directions, with the weighting determined by the Indian Point site wind rose. The accident is assumed to occur randomly at any time during the year. (Entergy does not make clear in the ER whether it calculated as large a number of outcomes or used the random sampling function of MACCS2, which selects only a few hundred hours during the year for evaluation.) We use the meteorological data file originally compiled for the Indian Point site for the CRAC2 study, which is publicly available.
Our results for off-site health consequences within a 50-mile radius of IP for the early high release category with full evacuation, compared to Entergys, are presented in Table I. The values for latent cancer fatalities as a result of early exposures (e.g. during the 1-week emergency phase) are reported separately from those resulting from chronic exposures (those resulting from the intermediate and long-term phases, as defined by MACCS2). The results for chronic exposures depend in on the parameters for long-term protective actions and have greater uncertainties than the results for early exposures. We assume, for purposes of comparison, that Entergys result for total population dose is the sum of both early and chronic exposures.
TABLE I Health Impacts of Early, High Release This study                          Environmental Report (Table E.1-14)
Mean early fatalities                    860                                  Not reported Mean latent cancer fatalities            37,600                              Not reported from early exposure Mean latent cancer fatalities            950                                  Not reported from chronic exposure Mean latent cancer fatalities            38,500                              Not reported (total)
Mean          population          dose    4.97 x105                            1.58 x105 (person-Sv) 95th percentile early fatalities          4,440                                Not reported 95th percentile latent cancer            129,000                              Not reported 90 We find for our source term that the evacuation scenario actually results in a slightly greater number of combined early and latent fatalities. This appears to be an artifact of the particular population data file used rather than a reflection of a general principle.
Appendix 4 - Page 7
fatalities from early exposure 95th percentile latent cancer 3,450                                  Not reported fatalities      from        chronic exposure 95th percentile latent cancer 130,000                                Not reported fatalities (total) 95th percentile population 1.64x106                                  Not reported dose from early and chronic exposures (person-Sv)
Our mean population dose result is over three times greater than that calculated by Entergy. To try to understand the reason for this difference, we reran the calculation with Entergys MAAP-derived source term. For the no-evacuation (all-sheltering) scenario, we found a 45% reduction in population dose to 276,000 person-rem, which is still nearly twice Entergys result of 158,000 person-rem. Without access to all the MACCS2 input files used by Entergy in its calculation, we cannot identify the other factors that may account for the remainder of the difference. But it is clear that the choice of source terms alone can have a significant (at least two-fold) impact on the population dose results.
We can also see from Table I that the 95th percentile population dose is over three times the mean population dose, and the 95th percentile number of early fatalities is over five times the mean value. This demonstrates that Entergys focus on the mean consequences significantly underestimates the potential consequences of accidents occurring during less frequent but not uncommon meteorological conditions.
As discussed above, we maintain that the mean population dose is not an accurate representation of the total cost detriment associated with lives lost, because it does not include the costs of early fatalities, which as one can see from Table I, are substantial. In addition, as shown above, use of population dose as a surrogate for latent cancer fatalities is not appropriate because the total population dose does not account for the non-linear relationship between population dose and total number of latent cancer fatalities when the range of individual doses include both doses above and below the DDREF threshold. To remedy these problems, the total number of early fatalities and latent fatalities should be summed and the total multiplied by the monetary equivalent of lives lost, which is $3 million in NRC guidance.
From this data, we obtain an equivalent cost, at $3 million per life lost, of $118 billion for the mean case. For the 95th percentile case, the equivalent cost of the latent cancer fatalities alone would be $390 billion.91 This should be compared to the result if only the equivalent cost of the population dose, using the $2000/person-rem conversion factor, were considered: $99.8 billion and $328 billion for the mean and 95th percentile, respectively.
However, in either case these results are far greater than Entergys calculated equivalent cost of
$31.6 billion. From the results presented in Table II, we see that our result for the cost detriment associated with loss of life from the early, high release is approximately 3.7 times greater than Entergys result for the mean case, and over 12 times greater for the 95th percentile case.
91 The MACCS2 code does not have an option for calculating the sum of early and latent cancer fatalities, and therefore does not report the 95th percentile value of this sum.
Appendix 4 - Page 8
According to Entergys calculations, this scenario is the largest single contributor (47%) to the overall population dose risk.
TABLE II Equivalent Cost of Off-Site Health Impacts of Early, High Release This study                          Environmental Report Mean        off-site    health $118 billion                            $31.6 billion impacts equivalent cost (early and latent cancer fatalities) 95th      percentile      health $390 billion                            Not reported impacts equivalent cost (latent fatalities only)
We have also obtained results for the off-site economic costs from the early, high release. We generally follow the methodology of Beyea, Lyman and von Hippel for our calculation of economic impacts.92 The model utilizes the results of a 1996 Sandia National Laboratories report that estimates radiological decontamination costs for mixed-use urban areas.93 We refer interested readers to these two references for information on the limitations and assumptions of the model.
Our results, as calculated by SECPOP2000 and the MACCS2 code, are also considerably higher than Entergys results. In Table II, the MACCS2 results, which were obtained from 1996 and 1997 data, were converted to 2005 dollars by multiplying by an inflation factor of 1.2.
TABLE III Off-Site Economic Impacts of Early, High Release This study                          Environmental Report Mean off-site economic $816 billion                                      $34.2 billion impacts 95th    percentile      off-site $2.48 trillion                        Not reported economic impacts By using the standard discount factor applied by Entergy (e.g. see page 4-53 of the ER),
Entergys frequency result, and neglecting the risk contributions of all other scenarios, we find a mean monetary equivalent present dollar value for the early, high release of $825,514, and a 95th percentile present dollar value (for latent cancers alone) of $2.73 million.
92 J. Beyea, E. Lyman and F. von Hippel, Damages from a Major Release of 137Cs into the Atmosphere of he United States, Science and Global Security 12 (2004) 1-12.
93 D. Chanin and W. Murfin, Site Restoration: Estimates of Attributable Costs From Plutonium Dispersal Accidents, SND96-0057, Sandia National Laboratories, 1996.
Appendix 4 - Page 9
Again using the same discount factor, we find a mean present dollar value of the off-site economic consequences of the early, high release of $5.71 million, and a 95th percentile present dollar value of $17.3 million.
Adding the equivalent cost of off-site health impacts to the off-site economic cost, we find for the early, high release alone the mean total cost equivalent present dollar value is $6.54 million. (We have not made our own estimates of on-site dose and on-site economic costs.)
This is nearly seven times greater than Entergys estimate of the sum of these two costs for all release categories.
For the 95th percentile, the present dollar value off-site economic cost for the early, high release alone is over 72 times Entergys mean estimate for the same release and over 12 times Entergys mean estimate for all costs (off- and on-site) and all release categories of $1.34 million.
These results are summarized in Table IV.
TABLE IV Present Dollar Value Equivalent of Early, High Release Consequences This study                      Environmental Report Mean present dollar value $6.54 million                          $460,334 of total off-site costs 95th    percentile    present $2.73 million                    Not reported dollar value equivalent of off-site fatalities (latent cancers only) 95th    percentile    present $17.3 million                    Not reported dollar value of off-site economic impacts We have not carried out a review of Entergys calculations for the other release categories that contribute to the Indian Point 2 severe accident risk. However, we would expect similar findings to those we have obtained in our review of the early, high release. In our judgment, many SAMA candidates would become cost-effective based on the difference in mean consequences alone, and many more rejected SAMA candidates would become cost-effective when the 95th percentile case is considered. If we were to extrapolate our result for the 95th percentile off-site costs of the early,high release to all release categories, leading to a nearly twenty-fold increase in total economic cost compared to Entergys estimate, even the most costly SAMAs, such as the Phase II SAMA #015, Strengthen Containment, could well become cost-effective.
We note that this conclusion would be further strengthened if we incorporated the increased frequency of the early, high release category estimated by Dr. Gordon Thompson in his Appendix 4 - Page 10
November 2007 report Risk-Related Impacts from Continued Operation of the Indian Point Nuclear Power Plant.
Based on these findings, we believe that Entergy has grossly underestimated the off-site costs of severe accidents at Indian Point, and should revise its estimates using more credible and conservative source terms. It should also consider the 95th percentile consequence values of the distribution with respect to weather variations and use these values as the upper confidence bound in carrying out the SAMA cost-benefit evaluation for Indian Point. Entergy should use a methodology for calculating the cost equivalent of off-site health impacts that properly accounts for individuals who receive acute radiation doses above the threshold for early fatalities, and for those who receive chronic doses above the threshold for application of a DDREF.
Analysis Our estimate of the mean off-site economic consequences of the early, high release is approximately 20 times Entergys estimate. We have identified some of the reasons for the difference, but not all of them. The difference in source terms does not appear to be as great a factor as for the calculation of health impacts. The differences in the choices of economic and other parameters between Entergys model and ours also plays a role. For instance, we use decontamination cost estimates obtained from a 1996 Sandia study that are significantly higher than those used by Entergy, which uses values based on the default parameters in the MACCS2 code. However, even after running the code with Entergys source term and economic parameters, we still find economic consequences at least an order of magnitude greater than Entergys. The results are also dependent on factors such as the dose criteria for triggering interdiction and condemnation actions. We use a more restrictive model than the default MACCS2 model in order to more closely approximate the EPA Protective Action Guides.94 In 94 U.S. Environmental Protection Agency, Manual of Protective Action Guides and Protective Actions for Nuclear Incidents, Washington, DC, 1991.
Appendix 4 - Page 11
any event, it is clear that reasonable differences in parameter choices can lead to order-of-magnitude differences in consequences in the MACCS2 long-term economic consequences model, and that Entergy has not done due diligence in exploring the sensitivity of their results to parameter variations.
Appendix 4 - Page 12
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                                                                    """ .-SJ.-<",.
llllnA.'*' ...... _,"''' _ _ _ .. _ ** _ -.. ... _
_ . _ _ .. r"",,                                                      -..
no _ _ _ _ _ .. LlDnA.,* , ,, _ _,-... .. _ _ ,_                                  *
....... _          , '_  _ _ .. . . Y"C.,., _ _ ",.""", _
                                    ~
_    ..... >>.00>_..'      r ..... - . .... ' _ _ _ llllnA.'*'
T . _ . . . . . . . _ N.. Y. . <>or.* ....,. _  _ _ _ _ ... _ ..
--,......"'_ ...-... -... _.....--.._....,..>r
_ .. mmy _        , ('1_ _ _ * ' _ .. 11.1........ "'... . . , _ ...
,....... ""~c-          __ ...ot_"""'.            no, _
_ _ ...... llllnA.""_
_ \><WI-.. .' ..
_      ..... 1I-rc_-"' _ _ _ _ _ _ ... .
_ h............
                                -rc....
C_  .....
_ ...      ot .. _. . <>or.". ...,.
_ _otN_Y
. . DB~"Y ......... . _      .. _
                                    ~
_ _ _ .. T. ... '
Appendix 5 - Page 18
_ ,_            ** o P _ .. _ _ I .... ""' I _ _
                                                                                    ""''',S}.''''''
' - _ l>uu.. .. _            . .........
n.,_ . .......... .-.........,. ......... _                            .... ,..." ... ... ...
                                                                                              ~
""J, _ _ _ ..nIoood _ _ _ _ _ . . UIlTUN ,, _ ..-                                          _
_    . . . . 'U"y OlI I _ ....... _ _ . . . . . . - _ _ _ _
_          . ...... .-.......,..                      _ n... _,.. .. _ ..........
-n. _, ,"",,,,,,,,,,,._," ' _                                    ........    -... .. __ _ ...
..... _ ... _ _ .. LlDlU..,.,,, _ _                                    .--.....
_ _. . . _                  ' .... _      .. _    . . UllnAN' _ _ . . .. .
...h...... n. _ ,.... __ ....... _ _ .. nm.
O - " .... * .... _              .. . . , ...
* _ k P _
                                                                                .. ..,I_
            .. " I' _    _        ._        ot ll' .. ..... . _          .. _        .._          ..
                                                    .100'
: n. rnI ~
. . liTe _ _ " " " .....""                                    _ ( . a d ..... _ . . ....-
_        .. _"',). "",".-. _                _      ot",, _ _ e... .. UDTUN'
-          --.....,..._    ",,,,.,y
..... . . lITe_ . . . ' .
..... .......~--
_ ... >U>..."' Y_._                            -
                                                ,,""!"!I""""
                                        * .. " . . y . .
                        .. """' ...... ....."kP _ _ * ....... y    "
c.r. _" .... __ _
. . . . . .... . . _"'-'""'' ' " ". .. .,. 0;,>----
......... k P _ ..... ....            ~        ... _ _ _ ,                      ,
                                                                                        " >U>.'Y
_        .. r""' l I ' - " - Co>!
n., .. . _          ... _      .. _              __ _ ,                          '''' ''''''' ot
...... .....            ........ _ _ _ _ _ . . UIlTUN ' ''_
        ~      _~,
",,,,,      _"_,,,,,.,,, _.........                  _ .._    _c        ,,-, .........
                                                                    ... LlDlU..,."
_ . ... _ _ _ _ ....                                                    -. l ... ,.. _ ...
..... -... --_ ... .. _-(... _                                                      -)
                                            "'"~
....-............ r"'",
OOSlJ:"... nm" I1lOI.! U ' UC"            no.~  or THIS UITBODO'-"""
: n. ...... ot _ _ .... _                      _      .....            '-....,. ..... .."
....... .. - . .. ..,., _ _ -1ft.. _ " " " " ... _                            ........ n. _
_ _ . . - _ .. . _                .J. I ..,., .. - . _ _ ....... """ ot ......
_          ;, _ _ _ .......                  _ot_  _    [7]. ""' .... _ _ _
                                                              *u                  ... _ _
* f>p.,............. _ ... ____ "' _
_    h......
_ _ _ _) ... _ _ _ _ _ _ .. . U-lI
_ _ _ .. , - . . . . . . . .. ... _ " ' - ........... . "'. . . " .. ,<0 Appendix 5 - Page 19
      -'-"'~P_ * -_I""= I -
                                        ... _-                            ""'L"'""""
_"_aK><'
r _ . L """'_"--"'...... ~aC1o_"....
              -. ~-....,.      __ _      .
                                            "~,,                  ,..-- ..
1>. . . ",,, " . .
          ,      (mt,..._J- , ..
                    ~--                      ~
lDO ,,... __._ _*....,. ..,, ..,,,,_ .. __
a;,,.._ .. _ ..
_l*''''_ .... l.O*n ___ . .... ,....
                                                            ~
                                                                    .... lD~ "_ . "
_,~ a;, , _
ao,-.h'Y . ...
,,",Y- . CA
                                                    . . ... ,.,.. . . . . .p--
              ..... .. H , - . . _C - .. 1OO->I ... ' ' ' ' ' - ....."
                      ....  ..,.- . ---." ~. """,-.....,
                    ...... - . . . _ .. .... y ... ""'. _ ..... . . . - " ' - -
            .. _, .. _          . . """" .... _c.....do ... uufno. , ...., ..........
Appendix 5 - Page 20
_ , _ ** o P _ .. _ _ I .... ""' I _ _
no.-. .....
y ..
c-._ ... _
_~_                .. ...  ~u
                            ,, _ _ ........ _ _ _ of .. _
                                                                                      """ .-SJ.-<",.
_ _ _ N_
,.....- ....... . .... """_. _ , . . ... _ ,                              1    .... _Y. . C.,.
"'""' _        ...,. _        ..... _ ....... IIO ..... __                  _ _ _ .. ...
_ ..... _                _          (r.IlPJof... U... _                    ~
                                                                .. """ _ _ _ .._ no
. . - n;" " ... _ _
_ ->O ........ , . . . .'_ _ ........ """" _
_ _ "'. "'_"_')(00
                                                                              -~
                                                . . . . ;, ... _ , . . (.. !l:tD <..t) ...
of ... .....
H .. _ _
                                                                                              ~ ...
. .... ' _ . . . WD ... .".. .. '
                ,~  "_ "''''_of,
_ ....... """"-..of.....---'_. no ...... ,., ..... , __ _
c-_ .......',_ :_ ......
                                  .. ' ...... _ * ..*'lDD
                                      )~ _                    _,....,of_
. . , _
* _ ...... _ 4 ... ..... _                                .. , _ _ _ _ ..
_ .... _,.. __ * *_ ...... .._ ... . -.._                                                  of..
                                              ~
_,                      K .. . :. .aC~"'        lDD    .. ~_ y. . C.,.~_              .. ,_  .
Appendix 5 - Page 21
Appendix 5 - Page 22
_ ,__ ** 0,,**.. _ .. _ _ 1_=1_ _
                                                        """-4t-"""
..- ",......ar _'""ot""
_ (_ ..... _tl.,."""-
                  '...... -,..,.""'C_I,_
.-... . . __ ._.opI--"". . _,""""-
_,",C~IJl ,,_ ..... _ , " ' ...... , ... ..
Appendix 5 - Page 23
_ ,_              *
* o P _ .. _ _ I .... """ I _ _
                                                                            """.-SJ.-<",.
~
Jlcw> '
'" ..'..:...""::'C---...
                                  '~ CJ- , "n-..
CO,",Ll'SJOS '
                                                          .. _Y. . "",
n.n _ _ _ _ _ ......... .....
                                    .. .. . bOh... . . - . . _ _ . . . .......
        ~-.          _ _.......      ......-.  ._..........
_ (,,_-..l.....-...
n.n ....
            ...... __eutu.
m
                                                              <.l.,, .. _ .. __
                                                                  =
                                                        ;"'_ " .-~-
l"'''-
..... I>A _ ...
                                            . ~- . -
.....,. .. _ _ __ bClit!' " ' _ _ .... __ ....... _
A{ DID" L11. Gl.IISU
                                                              ~c-          _ _..
_ _ N_,--,(Ph"''l.).
_ , ,
* _ ..... ~u..-..-.N_.--.(lllo1.),
                                                  "'--..we                  .... ...-
Appendix 5 - Page 24
_ , _ ** o P _ .. _ _ I .... """ I _ _
                                                              """-'SA"""
-"'-1'-_. -
1.00'-'-''''-' '-""(lJJ>1..), ~N_ ~",~1..), " """'L
_ _ ... . _,.,"'-...                      r..-...,.~_
1 UTIltL'<CIS
[lJu-.."*'..- ... ~O& ~ ~_ .. _                            .....
              . . "'A . .
[l J _ ot .-O.C...
          ... r.w        1y U'O'_... "'..
                          ~"'~"--
          ' ... K C_ _ ....... --.K u.' .n..
S. . - - A' _
...r....-._ .. ""'_ ', _... ~-.uc _ .,..B"""Br_CODE _ ,..
_cm;<.n"l1'<I4 rr _COIlE_**' " ,...w:H
['I_D.'              _000JI'-' "1lvtr_, ""..- __ "
v...._h_lI.J-._
['l J_ _ J_o.. ...      C&ol_ "_ .. ..,.,_
" ....... _ _ y . . C>IJ."FU>.-y_-,._.__
                                                          ~
                                                            ""'~
... _        ....mmm .....' __''';O'~
[6]n-."...., . . 11"_ * . _        .........m. I _      .. A _
c.... _          _ _ ""'_          - U},"D90--0051. _ _ J'          ...
,~
[J]OI.,,_ _ _ . . ~ 1. Doloo. " ' . - . " ~_ _ 1I'_ " C__
"*'...-.. v.... .... - . . . _ ..."""_ '                          *    ,on Appendix 5 - Page 25
APPENDIX 6 Roo.n E. u- 1'bD, 1'&#xa3;, Coc.:ulIm
                                      ~, ,,""          871l!
H. Richard Yosbimn mdMuk S. SooHoo SmdiINatiomILa~ '
                                      ~ , ,,"" 8711~
.-\BSIR\CT The pom:rW <ff<n. frool """""'! rwhoocIi\.., .,.I!rial. in ptu ~ ~ booI!h. klcial,
.mol<C<lOalDC~ . n.....,. _ I I ~rNtn~ 10potmial~
octi\'iI>e> that ~...., of~~ IWII!rial ~                  d." ",., (RDD>> . Su<h 1Il ..._ ,,""
Iadi~ r<Ieuod md dtpost~OO Arla= """'" md i=dt p<<lfI<', ~ md
~ ofW<rl, """"'""", m:I """,mao "ill ~ dta",- <lit _ 1 0 """... ~om tm
......t 0... aopt<f o f _ do=iom ,,:ill b< tm <<>OIlO d * ." ~ tm =<boI ndiOO<ll'~
<<<'amm"''''' 10 mol. tm -.. ftD<IlOOaI . g:om ,...,.,. _ _ _ .m:\'<< ~ md o...... ~ ofd.><q>proc= bo.,..,""" tm . . .' of~ from tm be~ of tm ~ ,~, rut formalizN rost ~.,. m.an,'<I}-Br<.mol """";' awbo'" 10 l<q 1<rn1m.lS<S lit ~ Sl1<s. ~. . . <~ rost -....tioo of coot                  f<<<1eazq> of
~~            mal!rial. .. ~ 10 u...,.toll< ....." _ , . . , , i""" that """...., op<ndi<
octi\'iIj' "'Of u.. bot 10 10 30)...... nu. ~ will m.lIj.......... .......! oftm".,.. _ _
.11'_    10 <SIimo... tm <<lOb ofl~ or IUltl! m:I ~ of 0000<II,'<1}-
<<<,amm,,<<I .,.n Tht <<>01-"""" for sur:h """'.".. will be,",*,&#xa5;",<<1 in,.",.. of.'{)OO doIlan for tm Ah of~ . ~ of rost ..,.",.... OCI p<&#xa5;llanOCl dmsily.mol nt<<I<d ~ of d<< .... pm"'""" will be m-", 10 b< <p1< ottoD!! m u.. ",.".g JR><d2Il'" of u..do....
UIT.R.\ nlU: On.R\ U W T~ 1B<<I f<< <u<s of ",J._ rwhoocIi\.., mo.1<riaI. in tm ...... of III ><cidrd <blJI!
1r>DSpOO bo.\~ '-" . JlIizripal >Om:< ofrost <SIimo.UO!~ .            n.....,. <-.inN lit tm RAD1RA."< 1r>DSpOO rut .......,.,.,. codoo thaI " .... lim ~<<I lit 1974 f<< .... in ~
t-"UREG--OI70{!,>"RC, 1'fl7). ThaI '"<Hl<>D. RADIRA."< I, hod ........t "",..... lit ~
, ...... ofu.. ooa.lO tm ~ ,.....,., <-.inN in RAD11t'.N VI. Two IO>-RADIRA."<
.......    . ___ .--,._., .....                ~        * .-      --.~
'lop " .. ,0<......". - - . . ...... _ _ _ _ "...,... ",,--.eo, .,'," rm
                                                                              ...... c.--,...
Illll!JI II!II Ili!lir"1111 ~ Sftrl~J,
                                                        ~"mn :1 I
I!w:~ ,[i .~~ I ~ ! ~~it5 l~"['l '.~'[ "                    ,,<.,.< ~ [illrl~ fH ~
rn 1~lrll'                    I"il ill'lt1j'              hl ~          1 j!J1
                          ! ~ rlp[ lh~.1              ,q .....  ~~                        ii[tH~ ~
                            ~l~l~f~ il~f! iii                  Iltfil!1                  'p &sect;H~
LI8~PI
                                                                                                      ~
Appendix 6 - Page 2 1111111 rl~ll iii li1fl!JI                                        nth .!
                                                                                          ~~J~U "
r ltWlrl rt mtHi!" --    HhL.          _ 1-
                                                                                          ~h~Hi      ;
i<    I                                                  iJ~(ifs
                            .lHIH t~m                          'IP<i~~
j
                            ~<"III
                            ~ :t~i'i Ii ~~'i'[
Vii'
[r I~          "!"'I        -
Ii' l8 } ij:ijI r~fllj''Il ,
                                                                                          ,~
                            ~tHh~ f~i                                  l~!t[
:as g,t!a,g, :
                                                                                          ~~Hil
* IJ}[
I,    * <Hodfh$
a B~~i      ~  Ii'
                                                      ~
j.,H
                                                                        ~~    ~i
                                                                                                        ,I I
I I
f ar 11>< dItI ~ bol<m-1I>< oripm! ~<""                    _ ...      ~ II! 11>< s<u<<
~ " ... ~.mol com"<fl<<l '" 1001 coou ~ stmdord root dd lo,,,,,
(\\,lb" ....,.., 1006). hi gm<r>l. <OSb " . . , _ uli<d .,.'11>< .. na1 ....... of<OOl"""'""," "
~""OF, lu.... ~<OOI"""''''''"~''' . OF, <1:m<<Iium. l-< OF,
<11l-,.mol b<a\)" OF, >10. Coso. in 11>< RADTIlA.'I I<p<>rb ..... IIn><r _ _ .,..
* spt<if""'lCII r<!mn;o; '" _ >1"'00 d=>!;' (nnl A1Iubm. ml url>oD,) OOD~ to """"
_>loti"" ~ of.oo.. 10, 7lQ, md,goo!""OO' J"f 11m' =ptctil"<iy. 10 11>< ChmIII r<p<>n. 1I><.non J"'!'lIaboo d!mil)' \-.n.. " .., IIk<o '" bo """" l,lQ I"""""lm'
<<ar~ to * .,...., J>O!'lIatloo <!<mil)' in ..... .a.mr..d .. urbamz<d .,.'11>< """"
luftul. R<iilimth >b1<<I thotpopulation <!<mi';'" (PO II! _              '1 m')""", .. foll<m~
Rlnl                                                      0 < I'D < lQ U""",,                                                  lQ < I'D < JOOO
          ~D<miI}-Urou.                                        J.OOO < PD < lo'oOO HJl"" o..""y lhban                                        10,000 < I'D A. i. 00;""" from 11>< ""''', ""'" " "" >Iriot trmsIa!ion of " "m, ~ p<&#xa5;>lm"" di=n;'
~- II! <p>mi1l1i\.. _              ~ t!m-. IS <mUgh 'l""'5ci1J' "'<_'~ coot.
, stmW.. H . fim1>oct ofpopuldioo. d<nst!y.
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Latest revision as of 09:14, 11 March 2020

Pilgrim Watch SAMA Remand Pre-Filed Testimony
ML110030898
Person / Time
Site: Pilgrim
Issue date: 01/03/2011
From: Lampert M
Pilgrim Watch
To:
Atomic Safety and Licensing Board Panel
SECY RAS
Shared Package
ML110030897 List:
References
50-293-LR, ASLBP 06-848-02-LR, RAS 19369
Download: ML110030898 (163)


Text

UNITED STATES OF AMERICA NUCLEAR REGULATORY COMMISSION BEFORE THE ATOMIC SAFETY AND LICENSING BOARD In the Matter of Docket # 50-293-LR Entergy Corporation Pilgrim Nuclear Power Station License Renewal Application January 3, 2011 PILGRIM WATCH SAMA REMAND PRE-FILED TESTIMONY Mary Lampert Pilgrim Watch, pro se 148 Washington Street Duxbury, MA 02332

TABLE OF CONTENTS Introduction 1 Meteorological Patterns/Issues 2 Straight-Line Gaussian Plume Model Used by Entergy is Deficient 4 PW Evidence Showed Deficiencies of Entergys Use of a Straight-Line Gaussian Plume 5 Model to Characterize Consequences in Pilgrims SAMA analysis Sea Breeze 6 Behavior of Plumes Over Water 8 Storms 9 Geographical Variations, Terrain Effects, and Distance 9 PW Evidence Showed That Entergys Inputs to the MACCS2 Code Were Deficient and 10 Did Not Account for Site-Specific Conditions Meteorological Inputs 10 Affected Area 14 NEPAs Rule of Reason- Meteorological Plume Model & MACCS2 Code 16 Board Majoritys Specific Questions (Board Order, Appendix A) 19 ASLBs Questions Avoid Significant Meteorological Issues Brought Forward 20 Appendix A Questions and Responses 23 Beyond Meteorology 50 The Boards Prior Orders 52 What Pilgrim Watch Would Have Proved But for the Prior Orders 55 Probabilistic Modeling 55 Amount of Radioactive Release - Size of Accident,Core and Spent Fuel Pool Releases 58 Use of the MACCS2 Code 65 Cleanup/Decontamination, Health and Other Costs 67 Appendices 83 Appendix 1: Review Of Prior Board And Commission Decisions (2006-2010)

Appendix 2: Meteorological Modeling: Government and Independent Studies Appendix 3: Use of Risk Measures in Design and Licensing Future Reactors, Kamiar Jamali Appendix 4: A Critique Of The Radiological Consequence Assessment Conducted In Support Of The Indian Point Severe Accident Mitigation Alternatives Analysis, Dr.

Edwin S. Lyman Appendix 5: Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 Appendix 6: Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ

PILGRIM WATCH SAMA REMAND PRE-FILED TESTIMONY I. INTRODUCTION On September 23, 2010, the Board Ordered (Order Confirming Matters Addressed at September 15, 2010, (Telephone Conference), hereinafter September Order) that the hearing now scheduled for March 2010 will be bifurcated to consider two issues.

According to the September Order (pp. 1, 2),

[T]he primary and threshold issue [is] whether the meteorological modeling in the Pilgrim SAMA analysis is adequate and reasonable to satisfy NEPA, and whether accounting for the meteorological patterns/issues of concern to Pilgrim Watch could, on its own, credibly alter the Pilgrim SAMA analysis conclusions on which SAMAs are cost-beneficial to implement (hereinafter referred to as the meteorological modeling issues).

Then, and only if the Board decides in favor of of Interventors on the primary and threshold issue..., the hearing will proceed to consideration of whether, and the extent to which, additional issues as set forth below will be heard.

The Board also said that the Board will, if it finds that they were timely raised, consider whether Pilgrim Watchs concerns about the NRCs practice of using mean consequence values in SAMA analyses, resulting in an averaging of potential consequences (hereinafter referred to as averaging practice concerns) could bring into question the reasonableness of this NRC practice and affect the Boards findings and conclusions of the the meteorological issues. (September Order)

On November 23, a majority of the Board found that the mean consequences values issue was not timely raised and therefore the issue will not be entertained by the Board during the evidentiary hearing on Contention 3. (November 23 Order, pp. 1-2).

In view of these Orders, on December 2, 2010, Pilgrim Watch (PW) submitted to the Board Pilgrim Watch Memorandum Regarding SAMA Remand Hearing. As there said, Pilgrim Watch will not present any new evidence at the upcoming SAMA Remand Hearing and will rely solely on what has previously been presented.

The evidence already of record shows, as discussed below, that use of a site-appropriate variable plume model, rather than a straight line Gaussian plume model, could result in significant changes in the areas that would be affected by a serious accident at PNPS.

It is also clear, however, that simply a change in area, on its own would not alter the Pilgrim SAMA Analysis. The majority Orders of September 23, 2010 and November 23, 2010 have so limited the scope of the remand hearing (in PWs view improperly) that it would be a fools-errand for PW to expend its limited resources to prepare and submit to the Board additional meteorological evidence for the limited initial phase of the remand hearing, or additional cost evidence for the limited second phase, should a second phase occur.1 II. Meteorological Patterns/Issues The September and November Orders preordain that a majority of this Board will find that accounting for the meteorological patterns/issues of concern to Pilgrim Watch could [not],

on its own, credibly alter the Pilgrim SAMA analysis conclusions on which SAMAs are cost-beneficial (September Order).

It is not possible for either Pilgrim Watch, or anyone else, to show that meteorology, in and of itself, would result in a significantly different SAMA analysis. But that is all Pilgrim 1

As said in PWs memorandum, we of course do not waive, and reserve, all of our appeal rights.

2

Watch has been left to argue. Further, at least a majority of the Board has effectively again rewritten Contention 3 to require Pilgrim Watch not only to show that further analysis is required (as Contention 3 states), but to require that Pilgrim Watch itself conduct the further analysis listed in the Appendix to the Order - something that neither it nor any other intervenor could possible do without spending hundreds of thousands of dollars, or should be required to do.

As for whether meteorology could, on its own, credibly alter the Pilgrim SAMA analysis, the evidence already before the Board shows (as discussed below) that the Gaussian Plume model used by Entergy in its SAMA analysis is non-conservative and deficient, and that if a proper, e.g. a variable plume, model were to be used, the geographical area affected by a serious accident, and the deposition within that area, would be different.

But on its own using a variable plume model would not alter Entergys SAMA analysis.

That analysis would continue to use the MACCS2 in the same flawed way in which Entergy has used it; in particular Entergys choice of source, ill-chosen average (mean) and probability would reduce any consequences that resulted from different meteorological inputs to such a low level that they could have no effect on the SAMA cost-benefit analysis.

Moreover, the effect a variable plume would have on even a proper SAMA analysis cannot be determined without running a site-appropriate variable plume model to determine exactly where and how large the affected area might be, and, more importantly, how a major radiological accident could affect that area and what, using an updated computer modeling code with proper inputs, the true resulting costs and damage might be.

3

Simply stated, Pilgrim Watch has shown (as discussed below) that the meteorological model used by Entergy is deficient. But neither Pilgrim Watch nor anyone else, regardless of how much time and money they might spend, can prove that meteorological patterns/issues ... could, on its own, credibly alter the Pilgrim SAMA analysis/issues of concern. Contention 3 as admitted should not require Pilgrim Watch to do so.

A Straight-Line Gaussian Plume Model Used by Entergy is Deficient

1. Introduction PW has submitted significant evidence to the Board and Commission that the straight-line Gaussian plume model does not subsume all reasonably possible meteorologic patterns, and is not appropriate for the PNPS coastal location. [Egan Dec. at 132] and did not predict site-specific atmospheric dispersion. The MACCS2 code used by Entergy could not model many site-specific conditions and did not determine economic costs for Pilgrims affected area that includes within its 50-mile radius densely populated areas of Boston, Providence, smaller cities and Cape Cod and Islands in summer, located across the bay.

The Gaussian plume model assumes that a released radioactive plume travels in a steady-state straight-line [Egan, 9], i.e., the plume functions much like a beam from a flashlight. The MACCS2 code used by Entergy was based upon this straight-line, steady-state model; it also assumed meterological conditions that are steady in time and uniform spatially across the study region [Egan, 9]. However, PW presented evidence that, the assumption of a steady-state, straight-line plume are inappropriate when complex inhomogeneous wind flow patterns happen 2

Dr. Bruce Egans Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pg., 132. Adams ML071840568, Exhibit 1 4

to be prevailing in the affected region. [Rothstein3, 2] The meteorological inputs that Entergys Gaussian plume model ignored include the variability of winds, sea breeze effects, the behavior of plumes over water, and re-suspension of contaminants.

PW evidence shows another significant defect in Entergys model - its meterological inputs (e.g., wind speed, wind direction, atmospheric stability and mixing heights) into the MACCS2 are based on data collected by Applicant at a single, on-site anemometer, plus precipitation data from Plymouth airport, some 5 or so miles inland [Application ER, E.1.5.2.6],

and that the data is from only one year.

The record before the Board shows that the use of a variable trajectory model could materially affect whether additional SAMAs may be cost-beneficial. Using its straight-line Gaussian plume model, Entergy projected costs could well be as low as $567,000 or even $0.00.

PWs evidence shows that, using a variable trajectory model, the projected costs could run from

$31 to >$100 Billion dollars. 4

2. PW Evidence Showed Deficiencies of Entergys Use of a Straight-Line Gaussian Plume Model to Characterize Consequences in Pilgrims SAMA analysis Entergys straight-line, steady-state Gaussian plume model does not allow consideration for the fact that the winds for a given time period may be spatially varying, and it ignores the presence of sea breeze circulations which dramatically alter air flow patterns. Because of these 3

Richard Rothsteins Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pg., 168. Adams ML071840568, Exhibit 5 4

Dr. Jan Beyeas Declaration: Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007, pgs., 97, 112; Summary Comparison- Population Multiplied by Sensitivity Case, pg., 88-9. Adams ML071840568, Exhibit 2 5

failings the straight-line Gaussian plume model is not appropriate for the PNPS coastal location. [Egan 9, 13]

The nearby presence of the ocean greatly affects atmospheric dispersion processes and is of great importance to estimating the consequences in terms of human lives and health effects of any radioactive releases from the facility [Egan, 9], and that the transport, diffusion, and deposition of airborne species emitted along a shoreline can be influenced by mesoscale atmospheric motions. These cannot be adequately simulated using a Gaussian plume model.

[Feasibility of Exposure Assessment for The Pilgrim Nuclear Power Plant, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988, 9]

a. Sea breeze effect The sea breeze effect, ignored by Entergys model, is a critical feature to consider at Pilgrims coastal location. Egan explained, at 10, The sea breeze circulation is well documented (Slade, 1968, Houghton, 1985, Watts, 1994, Simpson, 1994). [T]he presence of a sea breeze circulation changes the wind directions, wind speeds and turbulence intensities both spatially and temporally through out its entire area of influence. The classic reference Meteorology and Atomic Energy, (Section 2-3.5 ) (Slade, 1968) succinctly comments on the importance of sea breeze circulations as The sea breeze is important to diffusion studies at seaside locations because of the associated changes in atmospheric stability, turbulence and transport patterns. Moreover its almost daily occurrence at many seaside locations during the warmer seasons results in significant differences in diffusion climatology over rather short distances.

Spengler and Keeler5, 1988 showed that the sea breeze at Pilgrims coastal location increases doses on communities inland to an approximate 15 Km (9.3 miles). [Spengler; see also Egan, 12], and that the topography of a coastal environment plays an important role in the sea breeze circulation, and can alter the typical flow pattern expected from a typical sea breeze along a flat 5

Final Project Report, Feasibility of Exposure Assessment For the Pilgrim Nuclear Power Plant, Prepared for the Massachusetts Department of Public Health, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988. Exhibit 11 6

coastline. [Spengler, 40] But as PW showed, [t]The atmospheric model included in the

[MACCS2] code does not model the impact of terrain effects on atmospheric dispersion. 1997 User Guide for MACCS2.

PWs expert specifically contradicted Entergys expert Kevin OKula statements about the sea breeze effect at Pilgrim Station. [Egan, 13, replying to OKulas declaration, item 10]

1) [Mr. OKulas] statement that the meteorological data collected at the PNPS site would reflect the occurrence of the sea breeze in terms of wind speeds and direction is not necessarily true.
2) A measurement at a single station tower, 220 feet, will not provide sufficient information to allow one to project how an accidental release of a hazardous material would travel.6 Measurement data from one station will definitely not suffice to define the sea breeze.
3) [Mr. OKulas] contention that the seabreeze is generally beneficial in dispersing the plume and in decreasing doses is incorrect. In fact, the development of seabreeze flow that would transfer a release inland is the greatest danger. Contrary to the implications of this declaration, the development of a sea breeze flow is the common meteorological condition that must be most closely monitored at the PNPS.
4) [Mr. OKulas] statement reflects a misconception that the sea breeze is generally a highly beneficial phenomena that disperses and dilutes the plume concentration and thereby lowers the projected doses downwind from the release point. If the same meteorological conditions (strong solar insolation, low synoptic-scale winds) that are conducive to the formation of sea breezes at a coastal site occurred at a non coastal location, the resulting vertical thermals developing over a pollution source would carry 6

License Application 2.10 Meteorology and Air Quality at 2-31; and at Attachment E, E.1.5.2.6 at E.1-63]

7

contaminants aloft. In contrast, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses.

b. Behavior of Plumes Over Water Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence. The marine atmospheric boundary layer provides for efficient transport. Because of the relatively cold water, offshore transport occurs in stable layers. Wayne Angevines (NOAA) research of the transport of poluttants on New Englands coast concluded that major pollution episodes along the coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories. Therefore a plume will remain concentrated until winds blow it onto land. [Zager et al.; Angevine et al.

20067]. This can lead to hot spots of radioactivity in places along the coast, certainly to Boston.

[Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative model that Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used for sensitivity studies. [Beyea, 11-12].

7 Angevine, Wayne; Tjernstrm, Michael; Žagar, Mark, Modeling of the Coastal Boundary Layer and Pollutant Transport in New England, Journal of Applied Meteorology and Climatology 2006; 45: 137-154, Exhibit 6 8

c. Storms The storm cycle consists generally of northeasters in the winter and spring (and)

[h]Hurricanes sometimes occur in the late summer and fall. [Applicants LA Apprendix E, 2-31]. The accompanying strong and variable winds would carry a plume to a considerable distance.

d. Geographical Variations, Terrain Effects, and Distance PW showed that topography of a coastal environment plays an important role in the sea breeze circulation, and can alter the typical flow pattern expected from a typical sea breeze along a flat coastline. [Spengler, 40] But [t]The atmospheric model included in the [MACCS2] code does not model the impact of terrain effects on atmospheric dispersion. [1997 User Guide for MACCS2.]

The Gaussian plume model also does not take terrain effects, which PW showed can have a highly complex impact on wind field patterns and plume dispersion, into account. Wind blowing inland will experience the frictional effects of the surface which decrease speed and direction.

[PW Motion to Intervene, May 25, 2006 citing Lyman, Chernobyl on the Hudson, 27; Rothstein, Appendix A].

EPA has recognized that geographical variations can generate local winds and circulations, and modify the prevailing ambient winds and circulations and that assumptions of steady-state straight-line transport both in time and space are inappropriate. [EPA Guidelines on Air Quality Models (Federal Register Nov. 9, 2005, Section 7.2.8, Inhomogeneous Local Winds, italics added EPA's November 9, 2005 modeling Guideline (Appendix A to Appendix W) lists EPA's "preferred model; the Gaussian plume model used by Entergy (ATMOS) is not on the 9

list. EPA recommends that CALPUFF, a non-straight-line model, be used for dispersion beyond 50 Km.8 The essential difference between the models that EPA recommends for dispersion studies and the two-generation-old Gaussian plume model (ATMOS) used by Entergy and the NRC is more than determining where a plume will likely to go. Major improvements in the simulation of vertical dispersion rates have been made in the EPA models by recognizing the importance of surface conditions on turbulence rates as a function of height above the ground (or ocean) surfaces. We know that turbulence rates and wind speeds vary greatly as a function of height above a surface depending upon whether the surface is rough or smooth (trees vs over water transport) (Roughness), how effectively the surface reflects or absorbs incoming solar radiation (Albedo) and the degree that the surface converts latent energy in moisture into thermal energy (Bowen ratio). These parameters are included in the AERMOD and CALPUFF models and determine the structure of the temperature, wind speed and turbulent mixing rate profiles as a function of height above the ground. Entergys ATMOS model does not include these parameters. This is an especially important deficiency when modeling facilities located along coastlines, such as Pilgrim.

3. PW Evidence Showed That Entergys Inputs to the MACCS2 Code Were Deficient and Did Not Account for Site-Specific Conditions
a. Meteorological Inputs One fundamental defect in Entergys use of the MACCS2 code is that its meterological inputs to that code are all based on the straight-line Gaussian plume model. PW showed that this model does not allow consideration of the fact that the winds for a given time period may be 8

Appendix A to Appendix W to 40 CFR Part 51, EPA Revision to the Guideline on Air Quality Models:

Adoption of a Preferred General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule, November 9, 2005. http://www.epa.gov/ scram001/guidance/guide/appw_05.pdf.

10

spatially varying. [Egan, 9] The 1997 User Guide for MACCS2, SAND 97-05949 makes a related point: The atmospheric model included in the code does not model the impact of terrain effects on atmospheric dispersion.

Indeed, the MACCS2 Guidance Report, June 2004,10 is even clearer that Entergys inputs to the code do not account for variations resulting from site-specific conditions such as those present at PNPS. (1)The code does not model dispersion close to the source (less than 100 meters from the source). Thereby ignoring resuspension of contamination blowing offsite. (2)

The code should be applied with caution at distances greater than ten to fifteen miles, especially if meteorological conditions are likely to be different from those at the source of release. There are large potentially affected population concentrations more than 10-15 miles from Pilgrim - for example: Boston, Providence, Brockton, New Bedford, Fall River, Quincy, Cape Cod. (3)

Gaussian models are inherently flat-earth models, and perform best over regions where there is minimal variation in terrain. Entergy description of the PNPS site says that the, [t]opography consists of rolling forested hills interspersed with urban areas. [Lic.A, Appendix E, 2-1]

A second defect in the Applicants inputs into the MACCS2 code lies in the data itself.

Entergy input meteorological data for only a single year [OKula Dec. at 21; WMSM at 22], and except for precipitation all of the data was collected from a single, on-site weather station.

[Application ER, E.1.5.2.6]

PW showed that one year of data would have been insufficient even if more than one station had been used; Seasonal wind distributions can vary greatly from one year to the next.

[Spengler and Keeler Report, Page 22]. The NRC staff considers 5 years of hourly 9

Chanin, D.I., and M.L. Young, Code Manual for MACCS2:Volume 1, Users Guide, SAND97-0594 Sandia National Laboratories, Albuquerque, NM, (1997) 10 MACCS2 Guidance Report June 2004 Final Report page 3-8:3.2 Phenomenological Regimes of Applicability, Exhibit 21 11

observations to be representative of long-term trends at most sites, although with sufficient justification [not presented by Entergy here] of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations.

(NRC Regulatory Guide 1.194, 2003)

The simple fact is that measurements from a single 220 high anemometer will not provide sufficient information to project how an accidental release of a hazardous material would travel.

[Egan, 13] For cases when the sea breeze was just developing and for cases when the onshore component winds do not reach entirely from the ground to the anemometer height. The occurrence of a sea breeze would not be identified. The anemometer would likley indicate an offshore wind indication. Furthur PW demonstrated that basing wind direction on the single on-site meteorological tower data ignores shifting wind patterns away from the the Pilgrim Plant including temporary stagnations, re-circulations, and wind flow reversals that produce a different plume trajectory. [Rothstein, Town of Plymouth Nuclear Matters Committee Recommendation to Selectmen, Appendix A Meteorology, 13, Exhibit 5, Exhibits 3,4]

Since the 1970s, the USNRC has historically documented all the advanced modeling technique concepts and potential need for multiple meteorological towers especially in coastal regions. [Rothstein, June 24, 2006 letter, 2] NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.[Ibid., cited in Appendix 1]; and an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000, Sec 3.4 points to the need for multiple inland meteorological monitoring sites.

See also Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for 12

Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936.

Entergy should have taken data from more locations over a longer period; and modified the MACCS2 code to account for the inability of the code that Entergy used to account for site-specific conditions. The user has total control over the results that will be produced. [1997 User Guide, Section 6.10].

Finally, PW presented evidence that statements made in the OKula declarations that were relied on by Entergy to support its contention that the inputs into the MACCS2 code were sufficient are incorrect or misleading. As Egan, at 13, established,

1) MACCS2 is not a state-of-the-art computer model. It does not rely upon or utilize current understandings of boundary layer meteorological parameterizations such as those adopted by the EPA in the models AERMOD OR CALPUFF (EPA, 2001).
2) The Gaussian plume model employed in the PNPS MACCS2 model may be the standard for NRC but it is not the basis for advanced modeling used by other US regulatory agencies.
3) Computational time should not be a major factor in the choice of a dispersion model used for non-real time applications. Contrary to Entergy, these applications are not simply impracticable
4) The idea that randomly chosen meteorological conditions would give the same results as inputting meteorological conditions as a function of time is erroneous. To accommodate the real role of persistence in dispersion modeling EPA requires sequential modeling for all averaging times from 3 hour3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> averages to annual averages.

13

5) The fact that a model may seem to be conservative in particular applications or in limited data comparisons does not mean that the model is better or should be recommended. Models can be conservative but have incorrect simulations of the underlying physics. Sensitivity studies do not add useful information if the primary model is flawed.
b. The Affected Area The evidence presented by PW also established important disputes of material fact with respect to Entergys site specific meteorology-related economic inputs into its MACCS2 code analyses. Pilgrim Watch evidence showed that Entergy choices of inputs consistently and significantly underestimated the economic consequences of a radioactive release from PNPS.11 Entergys choice of a straight-line Gaussian plume rather than a variable trajectory model drastically reduced, to a wedge, the size of the area that might potentially be impacted by a release. Entergys analyses also assumed a small accident that had no real impact beyond 10 miles. Entergy did not consider the potential of the by far largest, and perhaps also the most likely, potential radiological release - from the spent fuel pool. In addition, Entergy chose to use the MACCS2 Code that, absent site specific modifications that Entergy chose not to make, cannot provide credible cost estimates.

The use of a variable trajectory model, rather than the straight-line Gaussian plume, would have significantly increased the area potentially affected by a released readioactive plume, and thus would also greatly increase the size of the affected population and property, and the economic effect, beyond 10 miles.

11 Beyond its statements that PWs challenges were immaterial, the Board majority opinion gives no indication of what PW evidence the majority actually considered. In dissent, Judge Young said that my colleagues apply a standard that overlooks or ignores genuine issues of material fact that Intervenors present through reputable experts, as well as considerations of practical reality and fundamental fairness. [LBP-06-848, 02-LR, at 40]

14

Entergy admits that its MACCS2 analysis does not assume an evacuation zone of greater than 10 miles because to do so would not be realistic [Sowden, 4-5]. Entergys KLD Time Estimates assume that the only area to be evacuated will be an area 2-miles around the reactor and the area within the key-hole from 2-5 miles, or perhaps extended within the key-hole, 5-10 miles. [Sowden, 3; KLD 1998 Report, 9-1.; and KLD 2004 Report, 2-2]. A variable plume analysis would increase the potentially affected area to far more than 2 miles around the plant and a few miles within the key-hole, resulting in potentially far greater risk and damage and also increasing evacuation time estimates. Despite orders to the contrary, more people inside and outside the EPZ will self evacuate. [Martecchini, 3; Zeigler,1-2]

PW showed that the consequences from a severe accident would not be restricted to a key-hole shaped wedge within a 10 mile radius, or to the entire populated area within 10 miles, but rather could encompass a much wider area including the densely populated metropolitan areas of Boston (38 miles NNW), Providence (44 miles SW), smaller cities of Quincy, Brockton, New Bedford and Fall River, and the summer population of Cape Cod and the Islands. The majority of the Capes population is within 10-20 miles; the summer population approximates 600,000, the year round about 210,000. [Rep. Patrick, 2]

A second major defect in the MACCS2 inputs is that Entergy apparently assumed that the only source of radiation in the event of an accident would be from the reactor within the containment. The potentially far greater source of leaked radiation, the spent fuel pool, contains far more radioactive material and is located outside the containment. It was ignored. [Beyea Decl.]

Absent modifications to permit inputs that address the MACCS2 code limitations discussed above, the MACCS2 code used by Entergy is incapable of providing an accurate 15

estimate of economic consequence, here. David Chanin author of the code said, If you want to discuss economic costs the cost model of MACCS2 is not worth anyones time. My sincere advice is to not waste anyones time (and money) in trying to make any sense of it. (and) I have spent many many hours pondering how MACCS2 could be used to calculate economic costs and concluded it was impossible. [Chanin Decl.]

c. NEPAs Rule of Reason (1) Meteorological plume model: CLI-10-22, pg., 9 emphasized, as they had done earlier, that NEPA requirements are tempered by a practical rule of reason and an environmental impact statement is not intended to be a research document. If relevant or necessary meteorological data or modeling methodology prove to be unavailable, unreliable, inapplicable, or simply not adaptable for evaluating the SAMA analysis cost-benfit conclusions, there may be no way to assess, through mathmatical or precise model-to model comparisons, how alternative meteorological models would change the SAMA analysis results.

The plume modeling that PW presented as appropriate for Pilgrims SAMA analysis, instead of Entergys decision to use the straight line Gaussian model, are not techniques that require research. They are, in fact, established methods that are publically available, routinely used, and appropriate for quantifying atmospheric dispersion of contaminants. (Appendix 2 lists examples from government and independent sources) Although an effort may be required to adapt these methods for SAMA analyses, this would be very straightforward and research would not be required.

16

Appropriate meteorological data or modeling methodology is available. There is no shortage of appropriate meteorological data for a licensing model application. Alternative modeling methods that would use more extensive meteorological data are also available.

The applicant chose to use only one year of onsite data collected at the Pilgrims site.

Meteorological data is also available from nearby airports and, importantly, processed data on a gridded basis can be obtained from NOAA to augment the onsite meteorological data relied upon for the SAMA analyses that have been provided by Entergy. PW demonstrated this by disclosing, for example, the Jennifer Thorpe12 site-specific meteorological study and Spengler and Keeler study (both Dr. Egan and Hanna attended the studies sea breeze workshop, Chapter 8 of Spenglers study) and Dr. Egans Development of a Dispersion Modeling Capability for Sea Breeze Circulations and other Air Flow Patterns over Southeastern Massachusetts, Upper Cape Cod Modeling Study, that used available meteorological data. Also there are several publically available meteorological modeling methods that can simulate variable trajectory transport and dispersion phenomena. MM5 is one which is routinely used nationally and internationally.

There are other options as well. The present state of art of an appropriate meteorological model would use multi station meteorological measurement data as input to the meteorological model.

The numerical computations, based upon numerical weather prediction techniques, would compute wind fields appropriate for modeling dispersion over a much larger geographic area than the a single measurement site would be appropriate for.

A second reasonableness criterion is that the modeling method must be reliable. The outputs from such meteorological models that are used to produce inputs for the dispersion 12 Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Scince in Applied Meteorology, May 2009.

Exhibit 10 17

models are well accepted and form the basis for the weather predictions provided by the national weather service as well as analyses of air pollution impacts of concern to regulatory agencies .

These techniques have been proven to be reliable and acceptable for air quality permitting and policy applications in complex terrain and over large distances for the US EPA , the US Park Service as well as internationally. PW argued with sufficient particularity that for complex meteorological situations such as for the Pilgrim, these techniques would be more reliable than using the straight line Gaussian model.

The third reasonableness criterion is that the modeling methods be applicable to SAMA analyses. The methods PW recommended are applicable because with straightforward modifications to incorporate nuclear radiation decay rates, they can produce the fields of concentration values and deposition rates needed for dosage calculations.

The fourth reasonableness criterion is that the modeling methodology be adaptable for evaluating SAMA analysis cost benefit conclusions. There is nothing inherent in variable trajectory models that would prohibit the output concentration and deposition fields from being applied to SAMA analyses.

None of the criteria cited would make the use of alternative models unreasonable to apply to the Pilgrims SAMA analyses.

Further there is no basis to the argument that there may be no way to assess through mathematical or precise model to model comparisons, how alternative meteorological models would change the SAMA analysis results. Some assessments may necessarily be qualitative, based simply upon expert opinion. But this argument seems to undercut the very value of mathematical simulation models in general as a method to assess the impacts of nuclear reactor emissions.

18

Last, the rationale offered that the use of advanced models would be computationally too expensive and/or burdensome to use are not justified by the actual run time shown in our review of MACCS2 output files. With modern computers, the use in inappropriate models on the basis of differences of computational costs is indefensible.

Invoking the practical rule of reason to the present disagreement about the most appropriate modeling methodology for application to the Pilgrim SAMA analyses is blatantly dismissive of the concept that the present methods are inappropriate and outdated and that there are indeed alternative modeling available.

(2) MACCS2 risk consequence code: The Applicants SAMA analysis uses MELCOR Accident Consequence Code System (MACCS2) computer program. PW stated the plain fact that there is no NRC regulation requiring the use of that code, or any other particular code. It was Entergys choice. There are other consequence computer codes in use for nuclear accidents around the world. Research is not necessary. Alternatively modifying the code with updated assumptions and inputs is clearly reasonable for a site-specific, Category 2 analysis.

B. The Board Majoritys Specific Questions (Board Order, Appendix A, Sept., 23, 2010)

Appendix A to the September 23, 2010 Board order asked parties to address specific issues concerning meteorological patterns raised by Pilgrim Watch, limited to only the sea-breeze effect and the hot spot effect.

Pilgrim Watch has attempted to do so below. It appears, however, that the questions avoid significant meteorological issues brought forward by PW in these proceedings that are pertinent 19

to understanding how Entergy underestimated the likely area impacted in a severe accident and deposition in that area; pertinent to answering the specific questions; and that should not be ignored. At the risk of being repetitive, these include:

ASLBs Questions Avoid Significant Meteorological Issues Brought Forward

1. Data Source:

PW demonstrated (PW Response to CLI pages 8-9) that basing wind direction on the single on-site meteorological tower data ignores shifting wind patterns away from the Pilgrim Plant including temporary stagnations, re-circulations, and wind flow reversals that produce a different plume trajectory. [Motion to Intervene, Pg., 36; Rothstein, Town of Plymouth Nuclear Matters Committee Recommendation to Selectmen, Appendix A Meteorology, 13]

Since the 1970s, the USNRC has historically documented all the advanced modeling technique concepts and potential need for multiple meteorological towers especially in coastal regions. [Rothstein, June 24, 2006 letter, 2] NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.[Ibid., cited in Appendix 1]; and an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000, Sec 3.4 points to the need for multiple inland meteorological monitoring sites.

See also Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936.

Entergy should have taken data from more locations over a longer period; and modified the MACCS2 code to account for the inability of the code that Entergy used to account for site-specific conditions. The user has total control over the results that will be produced. [1997 20

User Guide, Section 6.10]. There are many other data sources available for coastal Massachusetts and SE Massachusetts, in general.

2. Single-Year data: (CLI , Pg.,8)

PW showed that one year of data would have been insufficient even if more than one station had been used; Seasonal wind distributions can vary greatly from one year to the next.

[Spengler and Keeler Report13, Page 22]. The NRC staff considers 5 years of hourly observations to be representative of long-term trends at most sites, although with sufficient justification [not presented by Entergy here] of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations.

(NRC Regulatory Guide 1.194, 2003)

3. Precipitation, Moisture, Fog14.

Entergy failed to properly account for another site specific characteristic in Pilgrims coastal location - precipitation, moisture, fog - that affects dispersion (concentration) and hence the cost-benefit analysis. Dispersion (concentration) is affected by precipitation that, like wind flow, is highly complex. Fog varies along the coast and also in the interior, affected by bogs and ponds. Fog with low inversion layer and constant easterly winds could result in less dispersion of the plume. Because fog patches and precipitation can be highly localized, precipitation data from one location at Plymouth Airport 5 or so miles inland is inadequate. [PW Motion to Intervene, 3.3.3.1.c]

worst case scenario of exposure from a release at the Pilgrim Plant may (be) drizzly, foggy day with a low inversion layer and constant easterly winds (because they) could potentially have less dispersion. (Spengler, Decl., pg., 35) 13 Feasibility of Exposure Assessment For The Pilgrim Nuclear Power Plant- prepared for the Massachusetts Department of Public Health, Dr. J.D. Spengler and Dr. G.J. Keeler, May 12, 1988; Egan Decl., at 12 I support (Spenglers and Keelers) analysis of the sea breeze effects and their general recommendations.

14 http://www.mass.gov/czm//oceanmanagement/waves_of_change/pdf/troceancc.pdf 21

4. Storms:

The storm cycle consists generally of northeasters in the winter and spring (and)

[h]Hurricanes sometimes occur in the late summer and fall. [Applicants LA Appendix E, 2-31].

The accompanying strong and variable winds would carry a plume to a considerable distance.

(CLI-09) Coastal storms are an intricate combination of events that impact a coastal area. A coastal storm can occur any time of the year and at varying levels of severity; common to coastal storms are high winds, erosion, heavy surf and unsafe tidal conditions, and fog.15 Massachusetts is susceptible to high wind from several types of weather events, including, hurricanes and tropical storms, tornados, and noreasters.

PW brought forward these issues forward throughout these proceedings beginning in PWs Request for Hearing May 25, 2006 at 37-38. There PW said that, However with onshore winds the tower measurements do not reflect the effects of the overland conditions. The wind is likely to be slightly stable as it approaches land and Pilgrim's meteorological tower. As air flows over a heated surface thermally generated turbulence is induced. Under sea breeze conditions the turbulence structure of the atmosphere will not be accurately determined by the meteorological sensors at the coastal site. Dispersion is also affected by precipitation. Like wind flow, precipitation is highly complex - for example, fog patches vary along coastal locations and also in the interior affected by ponds and bogs. On a drizzly, foggy day with a low inversion layer and constant easterly winds there would potentially be less dispersion than a clear day with strong winds and a sea breeze. Fog patches and precipitation can be highly localized therefore precipitation data from one location at Plymouth Airport located 5 or so miles inland are inadequate. To obtain an accurate analysis it is necessary to install continuous recording meteorological instruments along the coast and at additional inland sites in the communities likely to be impacted by Pilgrim, for example the 7 towns identified by Spengler and Keeler (see Exhibit C). The parameters measured should include wind speed and direction, temperature, dew point, and solar insulation. This would allow an analysis which could more adequately analyze the penetration of the sea breeze front and better 15 Commonwealth of Massachusetts -State Hazard Mitigation Plan,2007http://www.mass.gov/Eeops/docs/mema/disaster_recovery/state_plan_2007_rvn4.pdf at 1.2 Natural hazards 22

characterize the spatial variation of the wind flow. The NRC has acknowledged that more meteorological data may be required. In Regulatory Guide 1. 194, this subject is discussed as follows: "The NRC staff considers 5years of hourly observations to be representative of long-term trends at most sites. With sufficient justification of its representativeness, the minimum meteorological data set is one complete year (including all four seasons) of hourly observations" (NRC, 2003). Despite the fact that several site specific reports (see Exhibit C) have been prepared for Pilgrim that show one year of observations gathered from one site will not satisfy this "representativeness" requirement, the Applicant has used only one year's worth of observations, gathered from only one location. The inputs into the MACCS2 Code are inadequate. In Exhibit E Petitioners describe an improved scheme for meteorological monitoring. This improved monitoring will not just provide better inputs for this kind of Severe Accident Modeling, but it is also a necessary tool for Emergency Planning.

APPENDIX A, SEPTEMBER 23, 2010 - QUESTIONS Q.1. Regarding the meteorological phenomena at issue in this remand hearing, describe in depth each of the following, with supporting data also provided, to the extent available:

Q.1.a. The annual frequency of occurrence of the sea breeze effect and the hot spot effect, and the respective duration of each such occurrence

1. The annual frequency of the sea breeze effect and the hot spot effect cannot be known without reviewing data from multiple weather stations and over at least a 5-year period. This is the further analysis that is properly the responsibility of the Applicant, not the Petitioner. Data is available. For example, NOAA lists multiple weather stations in SE Massachusetts. Included, for example, are Logan Airport, Cape Cod Canal, Scituate Harbor, Plymouth Airport, Taunton, Chatham, and Hyannis.

PWs expert, Dr. Egan, was clear that data from Pilgrims single 220 high anemometer will not provide sufficient information to determine the frequency of sea breeze and the hot spot effects. [See Egan, 13, replying to OKula declaration, item 10] A measurement at a single 23

station tower, 220 feet, will not provide sufficient information to allow one to project how an accidental release of a hazardous material would travel.16 For cases when the sea breeze was just developing and for cases when the onshore component winds do not reach entirely from the ground to the anemometer height, the occurrence of a sea breeze would not be identified. The anemometer would likely indicate an offshore wind indication. (CLI, Pg., 8) This was also explained in PW Motion to Intervene, May 25, 2006 at 36-38.

2. A sea-breeze (or onshore breeze) is a wind from the sea that develops over land near coasts. It is formed by increasing temperature differences between the land and water which create a pressure minimum over the land due to its relative warmth and forces higher pressure, cooler air from the sea to move inland. Therefore in Plymouths climate, while the sea breeze can occur throughout the year, it occurs most frequently during the spring and summer months when the land warms up relative to the ocean. On average, Pilgrim experiences about 45 sea breeze days during these two seasons. Typically the onshore component commences round 10 AM and can persist to about 4 PM. (Spengler and Keeler, page 1) Late afternoon, the land cools off quicker than the ocean due to differences in their specific heat values, which forces the dying of the daytime sea breeze. If the land cools below that of the adjacent sea surface temperature, the pressure over the water will be lower than that of the land, setting up a land breeze as long as the environmental surface wind pattern is not strong enough to oppose it. The breeze, and plume, will swing back out to sea. Seasonal wind distributions can vary greatly from one year to the next (Ibid, p., 22)
3. The hot spot effect can occur in combination with the sea breeze or when winds headed intially offshore are blown back towards shore due to wind shifts. The prevailing wind direction 16 License Application 2.10 Meteorology and Air Quality at 2-31; and at Attachment E, E.1.5.2.6 at E.1-63]

24

at Plymouth is from the south west,17 heading generally towards the Outer-Cape Cod or Provincetown. Although, seasonal wind distributions can vary greatly from one year to the next (Spengler, p., 22)

4. The annual frequency of occurrence and duration of the sea breeze effect and the hot spot effect was made irrelevant by the Boards October 16, 2006 and November 23, 2010 Orders, that respectively took Entergys use of probabilities and averaging off the table.

Although both the sea breeze and hot spot effects increase the area likely to be impacted (areas 17 Town of Plymouth Wind Energy Feasibility Study, DNV Global Energy Concepts, Inc., August 2008 Pg., 3-5:

online at:

http://www.masstech.org/Project%20Deliverables/Comm_Wind/Plymouth/PlymouthWWTPFinalFeasibilityStudy.p df 25

of greater population density) and the deposition in that area, both are trivialized by Entergys choice to use an extremely low likelihood of an accident and the mean as an average instead of the 95th percentile. Entergy used hourly meteorological data from 2001 (WSMS, p., 6) yielding 8760 observations. There are, on average, 45 sea breeze days a year; i.e., 12 percent of the 365 days in a year. This impact would not be reflected by Entergys use of a mean average; its impact would be reflected if Entergy had used the 95% percentile.

Q.1.b. The spatial and time-dependent pattern of wind and other meteorological phenomenological parameters associated with each such occurrence, or, if such data are not available, expert professional opinion for such parameters, and scientific literature references supporting those opinions

1. The Gaussian plume model assumes that a released radioactive plume travels in a steady-state straight-line [Egan, 9], i.e., the plume functions much like a beam from a flashlight. The MACCS2 code used by Applicant is based upon this straight-line, steady-state model; it also assumes meteorological conditions that are steady in time and uniform spatially across the study region [Egan, 9]. Entergys expert, Kevin OKula acknowledges that the MACCS2 does not model spatial variation in weather conditions. (WSMS Report, pg., 13)
2. PW presented evidence to the Board and Commission that, the assumption of a steady-state, straight-line plume are inappropriate when complex inhomogeneous wind flow patterns happen to be prevailing in the affected region. (Rothstein, p., 2)

Sea Breeze

3. PWs expert, Dr. Bruce Egans declaration responded to the Boards question.

The MAACS2 code is based upon a straight line, steady state Gaussian plume equation that assumes that meteorological conditions are steady in time and uniform 26

spatially across the study region for each time period of simulation. It does not allow consideration for the fact that the winds for a given time period may be spatially varying. For example, the wind speeds and directions over the ocean and over the land near the Pilgrim Nuclear Power Station (PNPS) are assumed to be the same.

Thus the presences of sea breeze circulations which dramatically alter air flow patterns are ignored by the model. As discussed later, the nearby presence of the ocean greatly affect atmospheric dispersion processes and is of great importance to estimating the consequences in terms of human lives and health effects of any radioactive releases from the facility (Egan Decl., item 8)

And The sea breeze circulation is well documented (Slade, 1968, Houghton, 1985, Watts, 1994, Simpson, 1994).The pressure differences that result in the development of a sea breeze essentially start over the land area well after sunrise. Along a coast, the sun heats the land surfaces faster than water surfaces. The warmer air above the land is more buoyant and initially rises vertically. The resulting lower pressure over the land draws air horizontally in from surrounding areas. Near a coast, the air over the water is cooler and denser and is drawn in to replace the rising air. This horizontal flow represents the advent of the sea breeze. The air starting to flow over the land is cooler than the air aloft and like any dense gas tends to resist upward vertical motions and prefers to pass around a terrain obstacle rather than up and over it. The density difference also suppresses turbulence that would mix the air vertically. As this air flows over the rougher and warmer land, an internal boundary layer is created which grows in height within the land bound sea breeze flow. Further inland the flow slows and warms and creates a return flow aloft which flows much more gently back out over the ocean to complete the overall circulations. Thus, the presence of a sea breeze circulation changes the wind directions, wind speeds and turbulence intensities both spatially and temporally through out its entire area of influence. The classic reference Meteorology and Atomic Energy, (Section 2-3.5 ) (Slade, 1968) succinctly comments on the importance of sea breeze circulations as The sea breeze is important to diffusion studies at seaside locations because of the associated changes in atmospheric stability, turbulence and transport patterns. Moreover its almost daily occurrence at many seaside locations during the warmer seasons results in significant differences in diffusion climatology over rather short distances.

Regarding the models ability to take into account meteorological conditions as a function of time, Dr, Egan explained that, 27

[Entergys expert, OKulas] declaration seems to state that randomly chosen meteorological conditions would give the same results as inputting meteorological conditions as a function of time. This is an erroneous concept with real meteorology which does not generally behave in a random manner. In order to take into account meteorological conditions as a function of time a model must process the meteorological data sequentially with time. A common phenomena in weather data analysis is the role of persistence of combinations of meteorological events over periods of hours to many days. The probability that the next hours meteorology will be similar to the previous hours or that tomorrows weather will be like todays is fairly high and certainly not random or independent of what happened in the previous time period . It also matters from an air quality point of view if winds are very low and dispersion very small for several hours in a row. To accommodate the real role of persistence in dispersion modeling EPA requires sequential modeling for all averaging times from 3 hour3.472222e-5 days <br />8.333333e-4 hours <br />4.960317e-6 weeks <br />1.1415e-6 months <br /> averages to annual averages. (Egan Decl., item 12 Comments on OKulas declarations, item 16)

PW further explained in its Motion to Intervene:

3.3.3.1. a Wind speed: Accurately characterizing wind speed is critical to estimating concentration sea breeze will decrease wind speed as they move over land.

3.3.3.1. b Wind Direction Wind direction will change with height above the ground and will be influenced by terrain features. The coriolis effect will cause a clockwise turning of the wind direction as the sea breeze develops over the course of the day.

This effect is reflected in the coastal wind sensor, but the effect of surface friction and surface features are not. As a result wind blowing inland will experience the frictional effects of the surface which decreases speed and changes direction.

3. Entergys experts declaration (OKula WSMS Report, pg., 21) agreed that sea breezes are sometimes recognized to be able to penetrate long distances inland. Simpson (1994) shows evidence of sea breeze penetrations up to 300 km inland over a period of 15 hrs in Australia.

Although not all coastal locations will experience such a large inland penetration, Simpson (1994) noted that penetrations on the south coast of England up to 100 km inland. Buckley and Kurzeja (1997) found evidence of sea breeze penetration over 100 km on the South Carolina coast. Penetration on Massachusetts southern coast have not been fully documented; yet data 28

gathered to date do not indicate deep penetration. However the important point is that as OKula acknowledges meteorological data collected on towers at the Pilgrim site do not reflect the occurrence of sea breeze conditions in both the wind speed and direction. (OKula report, pg.,

21)

4. Wind direction will change with height above the ground and will be influenced by terrain features. The coriolis effect will cause a clockwise turning of wind direction as the sea breeze develops during course of the day and eventually heads back to sea. [Spengler and Keeler, Pg., 39]
5. The topography of the coastal environment also plays an important role in the sea breeze circulation. When cool, dense, stable marine air encounters a hill or mountain, the heavy air tends to flow around them rather than over them. This can alter the flow pattern expected from a typical sea breeze along a flat coastline. [Spengler and Keeler, Pg., 6] Hence, a larger area becomes impacted.
6. Note that there can be larger (synoptic) scale weather patterns that are interacting with seabreeze conditions and vice-versa that can affect the wind flow and degree of seabreeze penetration inland.

29

Hot Spot Effect18:

PWs response to the Commission (CLI-09-11 at 5) explained, Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. This is important because about 60% of the land mass around Pilgrim NPS is water. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds blow it onto land [Zager et al.; Angevine et al. 2006]. At 153, Angevine concluded that, major pollution episodes along the northern New England coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories.

Although Angevine did not specifically study the transport of radionuclides, there is no reason to believe that the basic principles do not hold.

This effect can lead to hot spots of radioactivity in places along the coast, certainly to Boston. [Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative 18 Listing of references: Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.; Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M., Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology & Climatology, 45:137-154, 2006;Beyea, Jan, PhD.,Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, May 25, 2006, The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006; Miller, Samule T.K.; Keim, Barry; Synoptic-Scale Controls on the Sea Breeze of the Central New England Coast, AMS Journal Online, Volume 18, Issue 2 (April 2003); Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Applied Meteorology, May 2009.

30

model that Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used for sensitivity studies. [Beyea, 11-12].

Q.1.c. The radioactive deposition distribution you would expect to occur from each such occurrence, assuming a normalized source term. If such depositions are not readily discernable or determinable, a computer model, such as those contained in ATMOS (excluding the straight line Gaussian plume portion) or another model selected by the relevant expert may be utilized to provide such information Both the sea breeze and behavior of plumes over water (the so-called hot spot effect) will change the area of impact and concentration within that area. DOE explained that, straight-line Gaussian models could not only underestimate the consequences of a release, but also can incorrectly identify locations where higher concentrations can occur.19 [Emhasis added]

Sea Breeze

1. Entergys cost-benefit analysis is based on its contention that the sea breeze is generally beneficial in dispersing the plume and in decreasing doses. This fundamental underlying assumption is incorrect. Dr. Egan explained that, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses.

[Egan, 13].

[Mr. OKulas] contention that the seabreeze is generally beneficial in dispersing the plume and in decreasing doses is incorrect. In fact, the development of seabreeze flow that would transfer a release inland is the greatest danger. Contrary to the implications of this declaration, the development of a sea breeze flow is the common meteorological condition that must be most closely monitored at the PNPS.

[Mr. OKulas] statement reflects a misconception that the sea breeze is generally a highly beneficial phenomena that disperses and dilutes the plume concentration and 19 DOE/EH-0173T CHAPTER 4 (REVISED 2004), February 11, 2005, Pg., 4-6, Exhibit 13 31

thereby lowers the projected doses downwind from the release point. If the same meteorological conditions (strong solar insolation, low synoptic-scale winds) that are conducive to the formation of sea breezes at a coastal site occurred at a non coastal location, the resulting vertical thermals developing over a pollution source would carry contaminants aloft. In contrast, at a coastal site, the sea breeze would draw contaminants across the land and inland subjecting the population to potentially larger doses. (Egan Decl., Item 13 Comment on OKulas declarations, Item 20)

Spengler confirmed that [t]hese flow reversals and stagnations documented here at our coast result in an increased area impacted, increased concentration of the plume and ultimate cost.

(Spengler, 3).

2. Closely related, Entergy model failed to take into account that wind direction changes and terrain features could not only change plume direction (resulting in a larger affected area),

but could also reduce diffusion of the plume (increasing the amount of radiation received within the area). PW explained that a variable plume model could take account not only of the sea breeze, but also of wind direction changes that occur with height above the ground and terrain changes. [PW Motion to Intervene, citing Lyman at 27; Rothstein, Appendix A; MACCS2 Guidance Report, June 2004, Entergy LA, Appendix E, 2-1]

3. Dose can be defined as a product of concentration and episode duration. The duration is a function of the relative sea breeze strength. Thus it is necessary to gather information on the affected receptor location(s), vector speed and strength, wind speeds, mixing heights, and spread statistics. (Spengler at 35) Entergys reliance simply on meteorological data from the onsite met tower necessarily means that they do not have sufficient data. This further analysis is the responsibility of the Applicant, not the Petitioner.

4 The coriolis effect will cause a clockwise turning of wind direction and decrease in speed as the sea breeze develops during course of the day. [Spengler and Keeler, Pg., 39] This will result in a larger area of impact than modeled by a straight line model and the the decrease in 32

speed will result in increased exposure. Sea breeze and gradient winds would advect ( convey horizontally) emissions over populated areas [Spengler at 2]

5. The direction of the sea breeze is not constant but rotates in a clockwise direction during the day. The winds start off normal to the shore and eventually blow parallel to the shorethis may preferentially expose populations to the west and north. [Spengler and Keeler, Pg., 2]
6. Air pollution effects of sea breezes have been studied for a long time. One of the generally occurring effects of the onshore flow of marine air is fumigation of pollutants, in this case radiation, downwind of the shoreline. Effluent in a severe accident at Pilgrims shore location blown inland by onshore winds may be confined to a plume in the stably stratified marine air. However, as this plume intersects the convective boundary layer inland, pollutants can be mixed down to the surface resulting in fumigation (Lyons and Cole, 1973). Another commonly occurring effect in coastal areas is plume trapping. Stably stratified marine air moving onshore can have a mean mixing depth that is 10% of that existing away from the influence of the water (Lyons and Cole, 1973). Thus, effluent that is ejected into this layer is effectively trapped and high concentrations of pollutants can subsequently reach the surface. Fumigation and plume trapping commonly occur in association with sea or lake breezes. However, lake and land breezes can introduce unique problems. The first is the ability of sea/lake and land breezes to transport pollutants in three dimensions. Lake and land breezes are quasi-closed circulations and pollutants emitted into them can be recirculated several times over the near-shore area (Lyons, 1972). That is, pollutants emitted into the inflow layer get lofted in the frontal regions and disperse into the return flow aloft. A fraction of these pollutants are forced into the inflow layer again by the descending branch of the circulation. Remaining pollutants reside in an elevated layer aloft. Lyons and Olsson (1973) observed a helical trajectory within a sea/lake 33

breeze circulation and suggested that the motion of pollutants might include an along-coast component in addition to the cross-coast components. Lyons et al. (1995) have successfully simulated this three-dimensional behaviour using a numerical model. Also, during periods of stagnant synoptic conditions, lake and land breezes can occur nearly continuously, effectively confining pollutants to coastal regions and causing the accumulation of pollutants over periods of several days (Simpson, 1994; Lu and Turco, 1995). Despite apparently adequate ventilation with onshore winds, rapidly deteriorating air quality can result.

Hot Spots or the Behavior of Plumes Over Water 20

7. Entergys Gaussian plume model assumed that plumes blowing out to sea would have no impact. PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds blow it onto land [Zager et al.; Angevine et al. 2006]. This can lead to hot spots of radioactivity in places along the coast, certainly to Metropolitan Boston and its densely populated suburbs.

[Beyea, 11] The compacted plume also could be blown ashore to Cape Cod, directly across the Bay from Pilgrim and heavily populated in summer. [Rep. Patrick, 2] An alternative model that 20 Listing of references: Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.; Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M., Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology & Climatology, 45:137-154, 2006; Beyea, Jan, PhD.,Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, May 25, 2006, The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006; Miller, Samule T.K.; Keim, Barry; Synoptic-Scale Controls on the Sea Breeze of the Central New England Coast, AMS Journal Online, Volume 18, Issue 2 (April 2003); Thorp, Jennifer E., Eastern Massachusetts Sea Breeze Study, Thesis Submitted to Plymouth State University in Partial Fulfillment of the Requirements for the Degree of Master of Science in Applied Meteorology, May 2009.

34

Entergy did not use, CALPUFF, could provide the ability to account for reduced turbulence over water and could be used. [Beyea, 11-12].

8. Wayne Angevine (NOAA) has performed extensive research on pollutant transport along New Englands coast, the behaviour of plumes over these waters.21 Experiments showed that polluted air becomes stably stratified, and vertical mixing is limited. Although, he studied ozone, and not radionuclide transport, there is no reason to believe that the results would be different.

He showed (Exhibit 6) that:

Pollutant transport is most efficient over the ocean. The coastline makes transport processes complex because it makes the structure of the atmospheric boundary layer complex. During pollution episodes, the air over land in daytime is warmer than the sea surface, so air transported from land over water becomes statically stable and the formerly well-mixed boundary layer separates into possibly several layers, each transported in a different direction. His 2006 study examined several of the atmospheric boundary layer processes involved in pollutant transport. The basic conclusion is: major pollution episodes along the northern New England coast are caused by efficient transport of pollutants from distant sources. The transport is efficient because the stable marine boundary layer allows the polluted air masses or plumes to travel long distances with little dilution or chemical modification. The sea-breeze or diurnal modulation of the wind, and thermally driven convergence along the coast, modify the transport trajectories.

To summarize, the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast. The sea breeze modifies the large-scale flow to select the particular sites that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km).

21 Angevine, Wayne; Senff, Cristoph; White,Allen; Williams, Eric; Koermer,James; Miller,Samuel T.K.;

Talbot,Robert, Johnston,Paul; McKeen,Stuart, Coastal Boundary Layer Influence on Pollutant Transport in New England, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1;Angevine WM, Tjernstrom M, Zagar M.,

Modeling of Coastal Boundary Layer and Pollutant Transport in New England, J. of Applied Meterorology &

Climatology, 45:137-154, 2006 35

In another study, Coastal Boundary Layer Influence on Pollutant Transport in New England Angevine et al22 they found that:

the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast.

The sea breeze modifies the large-scale flow to select the particular sites that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km). Air pollution episodes in northern New England often are caused by transport of pollutants over water. Two such episodes in the summer of 2002 ware examined (22-23 July and 11-14 August). In both cases, the pollutants that affected the study areas, coastal New Hampshire and coastal southwest Maine, were transported over coastal waters in stable layers at the surface. These layers were at least intermittently turbulent but retained their chemical constituents. The lack of deposition or deep vertical mixing on the overwater trajectories allowed pollutant concentrations to remain strong.

Why is overwater transport important; and different than transport over land?

In northern New England, air transported from land encounters a cooler, smoother surface; convective mixing, therefore, decreases. A persistent pool of cold water exists offshore in the northern and eastern Gulf of Maine and the Bay of Fundy, with warmer water inshore Strong layering of the atmosphere caused by the cold water offshore overwater transport more efficient than transport over land. Because the overwater trajectory segments are always stable in these episodes, the pollutants in the surface layer are not diluted by deep vertical mixing. The surface layer is, however, turbulent, as evidenced by its cooling, and, therefore, pollutants could be lost to surface deposition. However, ozone and most of its precursors are deposited much more slowly to water surfaces than to vegetation, and so the polluted layers over water retain most of their ozone and precursors.

To summarize, the coastal boundary layer influences pollutant transport in northern New England by allowing for stable layers over water that carry pollutants, relatively undiluted and with minimal deposition, to distant (20-200 km) areas on other parts of the coast. The sea breeze modifies the large-scale flow to select the particular sites 22 Coastal Boundary Layer Influence on Pollutant Transport in New England,Wayne M. Angevine, Christoph J. Senff, Allen B. White, Eric J. Williams, James Koermer, Samuel T. K. Miller, Robert Talbot, Paul E. Johnston, Stuart A. McKeen, and Tom Downs, Journal of Applied Meteorology 2004; 43: 1425-1437, http://journals.ametsoc.org/doi/full/10.1175/JAM2148.1 36

that receive polluted air. Elevated layers transport polluted air very long distances (200-2000 km).

Although the study focsued on waters north of Boston, the water temperature also is cold in Cape Cod and Massachusetts Bays. The Gulf stream, warmer waters, are kicked offshore by Cape Cod.

Q.1.d. How that deposition would differ from that expected using a straight-line Gaussian plume model The straight-line Gaussian plume model decreases the potential area of impact and concentration within that area. Entergys model reflects only the initial direction of the wind, as indicated by their onsite meteorological tower. It further underestimates potential radiological damage and costs because it cannot reflect that offsite surface friction and surface features can decrease plume speed thereby increasing dose and change plume direction affecting larger areas.

[PW Motion to Intervene, citing Lyman at 27; Rothstein, Appendix A; MACCS2 Guidance Report, June 2004, Entergy LA, Appendix E, 2-1]

Q.1.e. The cost differential caused by the differences indicated in subsection d above (to be provided quantitatively if practicable, or if not, supported qualitative estimates may be provided).

1. This question makes little sense, for a number of reasons.
a. It is premature. On September 23, 2010, the Board ordered (Order Confirming Matters Addressed at September 15, 2010, Telephone Conference) that the hearing on Contention 3 will be bifurcated. In phase one, the parties were instructed to first look at meteorological patterns/issues of concern to Pilgrim Watch. The second phase of the hearing will not proceed unless the Board finds that meteorological patterns/issues of concern to 37

Pilgrim Watch could, on its own, credibly alter the Pilgrim SAMA analysis conclusion, and even if the Board did so find, it would, consider at most, very limited economic costs issues and would not address real costs..

b. Second the question incorrectly assumes that the cost differential caused by the differences in the model could be determined while holding all variables in Entergys SAMA analysis, except the plume model, constant. The only way to compare consequence would be to run both Entergys flawed model and a proper model, and to account for all consequences in a severe, not fantasy, accident (including: health costs, based on up-to-date dose response research; economic costs, including cleanup costs and excluding a discount factor; using the 95%

percentile, instead of the mean; and not multiplying probability by the consequences.) The methodology to determine costs would then be modeled on the Estimation of Attributable Costs from Plutonium-Dispersal Accidents, SAND96-0957, David Chanin, Walt Murfin, UC-502, (May 1996) and studies commissioned by the US Department of Homeland Security,23 discussed in this briefs section What Pilgrim Watch would have proved but for prior Board and Commission orders.

c. Third, it is not reasonable to expect Pilgrim Watch to answer this question. As Administrative Judge Ann Marshall Young explained, at 38, in her Dissenting Opinion in the Memorandum and Order (Ruling on Motion to Dismiss Petitioners contention 3 Regarding Severe Accident Mitigation Alternatives), October 30, 2007, In this proceeding, Intervenors provide the reasoned statements of several well-qualified experts. They do not, it is true, provide any results of calculations proving 23 Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 (Attachment 6, Exhibit 8); Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ (Attachment 7, Exhibit 9) 38

the negative of Entergys sensitivity analysis. But such a requirement or anything approaching its essential equivalent is unreasonable, given the extremely complex, expensive, and time-consuming nature of the computer calculations that would be necessary to do this, which even the Applicant, with its relatively greater resources, has called impractical. See Entergys Motion for Summary Disposition of Pilgrim Watch Contention 3 at 13 (May 17, 2007).

Also the accepted contention called for further analysis -i.e., further analysis by the Applicant not the Petitioner.

2. Nonetheless, PW in Pilgrim Watchs Answer Opposing Entergys Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, provided rough ball park estimates using Entergys population and trivialized economic data; the Massachusetts Attorney Generals analysis by Jan Beyea, reference to Sandias CRAC 11 study, and Chernobyl.

Economic Consequences using a spatial distribution: The total population was estimated by Entergy for the year 2032 for each spatial element by combining total population projections with transient population data obtained from Massachusetts and Rhode Island.

E. 1.5.2.1 Projected Total Population by Spatial Element, 2032 (PNPS Applicants Environmental Report Operating License Renewal Stage, Attachment E, E.1-61) 39

The table below illustrates potential costs if a variable trajectory plume dispersion model is used so that variable wind conditions are modeled and releases are not minimized to simply a minor release.

For illustration purposes, if all or most of the 10-20 mile area is impacted; some of the 20-30; and a portion of the 30-50 then you have a very different situation than simply assuming impact in the two miles around and a pie-shaped wedge from 2 to 5 miles. PW explained in our Response to Entergys Motion for Summary Disposition and Brief in Response to CLI-09-11 that Entergys cost figures are unrealistically low and it is necessary to consider both the initial deposition and subsequent resuspension in Pilgrims coastal area characterized by variable winds.

Table: Population Per Mile Multiplied By Sensitivity Case I&2 Costs Sector Miles Total Population Pop x $135,187.77/per person Pop x $189,041/person st 1 sensitivity 2nd sensitivity 0-10 165,236 $22,337,886,364 $31,236,378,676 10-20 619,601 $83,762,477,480 $117,129,992,641 20-30 1,659,661 $224,365,869,546 $313,743,975,101 30-40 3,197,941 $432,322,512,382 $604,541,964,581 40-50 1,847,128 $249,709,115,225 $ 349,182,924,248 50 total 7,489,767 $1,012,524,898,550 $ 1,415,873,043,447 In contrast, the table below illustrates potential costs if a straight-line plume distribution is used.

For illustration when looking at the table assume only a minimal, not moderately severe accident, so that only a portion of any 0-10 sector is assumed impacted. It is not hard to understand how using an inappropriate plume model and minimizing a severe accident to a hiccup can reduce projected costs.

40

Table: Population Per Geographic Sector Multiplied By Sensitivity Case I&2 Costs Sector Total Population 0- Pop x $135,187.77/per person - Pop x $189,041/person -2nd 10 miles 1st sensitivity sensitivity N 0 0 0 NNE 3 $405,563.31 $567,123.00 NE 3 $405,563.31 $567,123.00 ENE 3 $405,563 $567,123 E 5 $675,939 $945,2050 ESE 23 $3,109,319 $4,347,943 SE 950 $128,428,381 $179,588,950 SSE 13,289 $17,883,854,906 $2,512,165,849 S 23,695 $3,203,274,210 $4,479,326,495 SSW 23,695 $3,203,274,210 $4,479,326,495 SW 23,695 $3,203,274,210 $4,479,326,495 WSW 23,695 $3,203,274,210 $4,479,326,495 W 22,818 $3,084,714,536 $4,313,537,538 WNW 19,494 $2,635,350,388 $3,685,165,254 NW 11,269 $1,523,430,980 $2,130,303,029 NNW 5,599 $756,916,324 $1,058,440,559 In the above table, imagine if Entergy assumes a severe accident is really one with small off-site release. For example if their straight line plume model, once averaged, predicts winds blowing to the NNE, perhaps one person will be affected costing at most $189,041 in damages Summary: In contrast if a variable trajectory plume distribution model is used, winds shifting carrying the plume over many geographic areas; and a severe accident is assumed to be more than a small offsite release, then more SAMAs are likely to come into play - as the table below illustrates.

41

Summary Comparison- Population Multiplied by Sensitivity Case Population within area 1st sensitivity 2nd sensitivity-

$135,187.77/person $189,041/person Straight-line Gaussian Plume Model Population SE Sector, 950 (0-10 $128,428,382 > 128 Million $179,588,950 miles)

Population SSW Sector, 23695 $3,203,274,210 > 3 Billion $4,479,326,495 (0-10 miles) >4 billion Variable Plume Model Population within 10 miles, $22,337,886,364 > 22 Billion $31,236,378,676 165236 >31 Billion Population within 20 miles $83,762,477,480 > 83 Billion $117,129,992,641 619601 >117 Billion Population within 50 miles $1,012,524,898,550 (1 Trillion +) $ 1,415,873,043,447

> 1 Trillion Previous Projections Core Melt, Pilgrim (1982) $81.8 Billion CRAC-2, Sandia National Laboratory,198224 Release C-137 from Core -Beyea $105-488 Billion [MA AGO, Dr. Beyea]

[Based upon Massachusetts Attorney Generals Office Analysis, Dr. Jan Beyea25]

In reviewing the above table, it is sobering to consider the impact of the 1996 Chernobyl accident, 1986, to help understand the potential impact from an accident as Pilgrim. Sheep remain contaminated in Scotland and reindeer are still contaminated in Lapland, from an accident 20 years ago. Chernobyl was bad, no doubt, but certainly not worst case. The 1986 Chernobyl accident released 2,403,000 curies of C-137; whereas Pilgrims core during license 24 Calculation of Reactor Accident Consequences U.S. Nuclear Power Plants (CRAC-2), Sandia National Laboratory, 1982 25 The Massachusetts Attorney Generals Request for a Hearing and Petition for Leave to Intervene With respect to Entergy Nuclear Operations Inc.s Application for Renewal of the Pilgrim Nuclear Power Plants Operating License and Petition for Backfit Order Requiring New Design features to Protect Against Spent Fuel Pool Accidents, Docket No. 50-293, May 26, 2006 includes a Report to The Massachusetts Attorney General On The Potential Consequences Of A Spent Fuel Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, PhD., May 25, 2006. Exhibit 2 42

extension will have 5,130,000 curies of C-137 [Beyea Decl, Chernobyl; and LR, Pilgrim CS-137 figures].

Q.2 . Regarding the radioactive contamination to be computed from the dispersion and deposition caused by the meteorological patterns at issue, describe in sufficient detail for scientific understanding the following:

Q.2.a. How the source term to be used for each computation of radioactivity dispersion and deposition is determined Entergy knows how the source terms it used were determined. PW understands that Entergy used the MAAP code, a proprietary industry code, to estimate the consequences of severe accidents (radionuclide release fractions generated by the Modular Accident Analysis Progression, MAAP26). The code has not been validated by NRC. The release fractions are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations. This has been observed by NRC in studies such as NUREG-1150. A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable 26 See, for example, ER. E. 1,2,1; and the limitations of the code are examined in Appendix 4, A Critique Of The Radiological Consequence Assessment Conducted In Support Of The Indian Point Severe Accident Mitigation Alternatives Analysis, Dr. Edwin S. Lyman. Dr Lyman would have performed a similar reprot for Piglrim Watch had the issue not been removed from consideration in these proceedings. Exhibit 12 43

scenarios the NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR. Apparently the differences in the release fractions are primarily attributable to the use of the different codes in the two analyses. 27 Thus, Entergys use of source terms generated by MAAP appears to lead to anomalously low consequences when compared to source terms generated by NRC staff. In fact, NRC has been aware of this discrepancy for at least two decades. In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without performing controlled comparisons for identical boundary conditions and input data.28 We are unaware of NRC having performed such comparisons.

The NUREG-1465 source term was also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.29 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.30 27 J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.

28 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.

29 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.

30 J. Schaperow (2002), op cit.

44

Q.2.b. The degree of conservatism imbedded in that methodology, its sources, and the rationale for each source of conservatism

1. There are two conventional meanings of conservative. One definition is old-fashioned or old-school. In this sense of the term, the methodology used by Entergy was indeed old-school, and that is a major problem with their analysis. The straight-line Gaussian plume model is a simplistic out-of-date model as illustrated in Appendix 2, Meteorological Modeling:

Government and Independent Studies. Dr Egan explained:

The field of dispersion modeling has developed rapidly since models were first routinely used in regulatory applications in the 1960 s and early 1970s. The Clean Air Act Amendments of 1977 created further reliance on atmospheric dispersion models for the establishment of emission limits for new industrial sources seeking licenses and permits under the Clean Air Act. The US EPA and other groups initiated research program to improve the science of dispersion models and the US EPA began to establish performance measures for models and to provide guidance and recommendations for the testing and adoption of improved models in permit applications. The result was further advancement in modeling methods that have persisted to the current decade. Specifically, very significant improvements have been made in the parameterization of the atmospheric boundary layer wind profiles, temperature profiles and variations of turbulent mixing rates with height above the ground surface. As a result of the Clean Air Amendments of 1977, The US EPA has been instrumental in encouraging and supporting the development of improved models including those defined as guideline models AERMOD and CALPUFF (EPA, 2005). AERMOD includes highly sophisticated algorithms for including spatial variations of the ground surface parameters of roughness lengths, surface albedo and the Bowen ratio into the parameterizations of wind and turbulence levels as a function of height. CALPUFF has the added features of allowing spatially variable wind fields. These models are now routinely used for regulatory applications and for risk assessments. (Egan Decl., at 7)

Additionally, the assumptions regarding dose-response are outdated and likewise the entire MACCS2 computer code.

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2. The second definition of conservatism is cautious. PWs response to the Commission (CLI-09-11 at 15) explained that the Gaussian Plume Model/ MACCS2 Applied in Entergys and the Boards Cost-Benefit Analysis was not conservative.
a. Lewellen and Mollenkamp: Entergys experts cite two reports (Lewellen and Mollenkamp31) claiming that they showed the straight-line Gaussian model was conservative.

[Entergy, Motion for Summary Disposition, 12] The fundamental flaw in Entergys contention is that a comparison made in the high desert land in Idaho, Kansas or Oklahoma tells little or nothing about what a comparison made in Plymouth, Massachusetts would show. PNPS site is characterized by its coastal location, varying terrain, forested hills interspersed with urban areas (Appendix E, 2.1). In contrast, the Lewellen and Mollenkamp studies were performed in areas that are not in the least comparable to the PNPS site. As a predictor of what might happen at PNPS, Entergys reports are not conservative; they are simply meaningless. Whether the Gaussian plume model is conservative relative to the Pilgrim site cannot be determined without running both ATMOS (the Gaussian plume) and an alternative model (e.g. MM5 and CALPUFF) with PNPS site specific data.

NRC itself has said that the Mollenkamp study site in central Oklahoma and Kansas did not have topography that would interact with the large-scale flow producing local modification of wind speed and direction and that it did not have changes in surface properties that could affect local flow, such as a coastal site with a land-sea breeze [NUREG/CR 6853, 3]. The Mollenkamp sites are relatively smooth and (have) has minimal effect on the wind field and the 31 WSMS refers to the results from a test that released a tracer conducted in 1981 at the Idaho National lab (INL is located in high desert land, eastern Idaho), Lewellen, 1985, NUREG/CR-4159; Mollenkamp et al (2004) compared several codes for recorded data in the Midwest, NUREG/CR-6853] Exhibit 16 46

surface is fairly uniform and therefore produces relatively little thermal forcing. The NUREG says that it would have preferred a site with greater topological and diurnal homogeneity (NUREG/CR-6853, Oct. 2004, at xi and 2); and readily admitted that it would be best if MACCS2 and RASCAL/RATCHET results could be compared with measurements over the long distances and types of terrain of interest to the NRC. The only reason that the less desirable comparison with a state-of-the art code was chosen to provide input into the decision on the adequacy of MACCS2 ATD was that such measurements do not exist. (Ibid at 2)

b. Entergys Sensitivity Studies: Entergys two supplemental sensitivity studies, by Enercon and WSMS, similarly were not conservative. PWs initial brief also pointed to evidence (at 16) that no matter how many scenarios WSMS may have studied using a downwind in a straight line assumption, they cannot provide a valid comparison to variable trajectory scenarios that WSMS never studied. The same holds true for Enercon. PW evidence showed that both the code used by Entergy and the meterological and economic information it used were inadequate. Dr. Egan summed it up: sensitivity studies do not add useful information if the primary model is flawed. Egan Decl. ¶ 13.
c. Whether the Gaussian plume model is conservative relative to the Pilgrim site cannot be determined without running both ATMOS (the Gaussian plume) and an alternative model (e.g. MM5 and CA NRC Staffs own expert, Dr. Bixler, (Exhibit 7) generally agreed with Dr. Egan and admitted that the Gaussian plume model results are conservative is correct only if the word conservative is defined narrowly:
8. (NEB) Material fact number 12 states that the MACCS2 Gaussian plume model results are in good agreement with, and generally more conservative than those obtained by more sophisticated models. If the word conservative implies that calculated plumes with the MACCS2 code are generally more focused and more concentrated than would be the case if the calculations had been performed with more sophisticated models, then the statement is accurate. However, a more focused, 47

more concentrated plume does not always correspond to a smaller number of person-rem, depending on the trajectory of the plume compared with population centers.

(Emphasis added)

Therefore NRC Staffs expert is in full accordance with PWs argument that whether a Gaussian model is conservative depends entirely on the trajectory of the plume compared with population centers; and PW submitted significant evidence that the straight-line Gaussian plume could not, and did not, predict site-specific atmospheric dispersion for Pilgrims coastal region, or accurately predict what population centers the likely variable plume would affect. [PW CLI 11 Br., 4-10, 14,17]

For example, while Entergy assumed that a plume blowing out to sea would have no impact on any population centers, PW showed that a plume over water, rather than being rapidly dispersed, will remain tightly concentrated due to the lack of turbulence, and will remain concentrated until winds change the plumes trajectory and blow it ashore. This can lead to hot spots of concentrated radioactivity in places along the coast, certainly including densely populated Metropolitan Boston; or to Cape Cod directly across the Bay with a summer population of 600,000. [PW Br., 5, 17, Rep. Patrick Decl., 2]

Further, Dr. Bixler (Exhibit 7) said very plainly that Entergys claim, that its study was conservative because it used conditions at the beginning of a plume release, was erroneous.

9. (NEB) Material Fact number 16 states that Sensitivity Case 2 estimated the effects of changing wind direction trajectory and was conservative because it used conditions at the beginning of a plume release, when the release has larger dose quantity and less decay has occurred. The MACCS2 value modified in Sensitivity Case 2 appears to have been REFTIM (Representative Time Point for Dispersion and Radioactive Decay). REFTIM affects the way in which dispersion, deposition, and radioactive decay are calculated. It does not affect the manner in which "wind direction trajectory" is calculated. This statement appears to be erroneous 48

Again, the Staffs expert is in full accordance with PWs expert, leaving Entergy and NRC Staff at odds.

Although the sea breeze effect is a critical feature at Pilgrims coastal site, here again Dr.

Bixler agrees with PW and Dr Egan, [Egan Decl.,13, Item 20] and says that the effect of sea breeze is not taken into account in Entergys studies.

10. (NEB) Material Fact number 19 states that the effect of sea breeze is taken into account in the Pilgrim site meteorological data. Although the wind speed and direction of a sea breeze may be included in the actual PNPS meteorological data, the effect of sea breeze is not taken into account. The effect that is not taken into account is that the complex flow pattern under sea breeze conditions differs substantially from the straight-line pattern used in the MACCS2 analyses. The sea breeze occurrences are typically diurnal events, occurring during daylight hours and during warmer seasons. (Emphasis added, Exhibit 7)

Entergy claims that the Gaussian model concentrates and maximizes the plume in a narrow wedge close to the reactor maximizing health effects; whereas a variable model will produce a more diffuse plume and thereby have less impact on population dose. However, Entergy has presented no data to justify its claim; so far as PW knows, Entergy has never run a variable plume model, much less one that properly used the MACCS2 code.

And most important, one cannot be conservative both close to the reactor and far afield.

Arguably, the severe health effects close in may be greater with a Gaussian model; but the latent health effects, economic damage and cleanup costs will be greater due with a variable model due to its larger area of impact.

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Q.2.c. The extent to which those conservatisms cause the resultant deposition to be conservative; be as quantitative as is practicable, but qualitative discussions are acceptable where quantitative analysis is not practicable PWs response to Q.2.b answers this question. The short answer is that the straight-line Gaussian plume is not conservative or cautious, the resultant deposition is underestimated and consequences minimized.

Once again, it is not reasonable to expect Pilgrim Watch to answer this question because, as explained in The Dissenting Opinion of Administrative Judge Ann Marshall Young, at 38, in the Memorandum and Order (Ruling on Motion to Dismiss Petitioners contention 3 Regarding Severe Accident Mitigation Alternatives), October 30, 2007:

In this proceeding, Intervenors provide the reasoned statements of several well-qualified experts. They do not, it is true, provide any results of calculations proving the negative of Entergys sensitivity analysis. But such a requirement or anything approaching its essential equivalent is unreasonable, given the extremely complex, expensive, and time-consuming nature of the computer calculations that would be necessary to do this, which even the Applicant, with its relatively greater resources, has called impractical. See Entergys Motion for Summary Disposition of Pilgrim Watch Contention 3 at 13 (May 17, 2007).

The accepted contention called for further analysis - i.e., further analysis by the Applicant not the Petitioner.

III. Beyond Meteorology Even if a majority of the Board should find that meteorological concerns/issues ... could, on its own, credibly alter the Pilgrim SAMA analysis conclusions, the economic issues that might be open for adjudication have, once again, been so drastically limited that the result is preordained.

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Evidence showed that the most significant economic costs - clean/up, decontamination, and health - have been forced off the table. All that Pilgrim Watch even might be permitted to show about costs has been limited to business and tourism in Plymouth County.

No matter what weather, or what loss of business and tourism in Plymouth County, might be input into the MACCS2 code, a downstream portion of the code (the MACCS2s so-called output file) would reduce consequences to such a low level that there would be no change in the SAMA conclusion. The MACCS2 output file uses Entergys chosen ill-chosen mean average rather than the 95th or higher percentile permitted by the code, averages the consequences produced by EARLY and CHRONC (using a discount figure when prices increase over time) and then applies a ridiculously small probability, again selected by Entergy. The result, as intended by Entergy, is that no significant SAMAs will be required.32 The prior orders of this Board have precluded Pilgrim Watch from proving real costs. At the beginning of these proceedings the Board rewrote Contention 3 in ways that, at least in the view of the majority, eliminated any discussion of probability, and any discussion of the code other than a few particular inputs; the majoritys Summary Disposition Order and its Order of November 23, 2010 took Entergys misuse of the code off the table. These decisions were wrong, and subject to appeal, but they unfortunately (for both Pilgrim Watch and the public) have made this remand hearing meaningless.

32 Consequences necessarily depend on the size of an accident, the source input into the code. This critical input, chosen by Energy, has also been taken off the table.

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IV. The Boards Prior Orders In attached Appendix I, Pilgrim Watch has outlined prior decisions of this Board to show how they have removed from consideration any real chance that this proceeding will meet the NRCs stated goal of ensur[ing[ adequate protection of the public health and safety and the environment. (See NRC Strategic Plan, Fiscal Years 2008-2010, At-A-Glance). The NRC says that its MISSION is to [l]icense and regulate the Nations civilian use of byproduct, source, and special nuclear materials to ensure adequate protection of public health and safety ... and protect the environment, and that its desired Strategic Outcomes include (Id.):

x Prevent the occurrence of any nuclear reactor accidents.

x Prevent the occurrence of any inadvertent criticality events.

x Prevent the occurrence of any acute radiation exposures resulting in facilities.

x Prevent the occurrence of any releases of radioactive materials that result in significant radiation exposure.

x Prevent the occurrence of any releases of radioactive materials that cause significant environmental impacts.

This Boards own brochure says that Congress made it possible for the public to get a full and fair hearing on nuclear matters.

Pilgrim Watch respectfully submits that, in the aggregate, the prior decisions of this Board have created a situation that is inconsistent with the NRCs fundamental goals, and that that has failed to provide for ... a full and fair hearing.

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Pilgrim Watchs Contention 3 squarely raised important issues that are consistent with ensur[ing] adequate protection of public health and safety ... and protect[ion of] the environment. Originally filed Contention 3 (Request For Hearing and Petition To Intervene By Pilgrim Watch, May 25, 2006 (Hearing Request), p 26) was:

Contention 3: The Environmental Report is inadequate because it ignores the true off-site radiological and economic consequences of a severe accident at Pilgrim in its Severe Accident Mitigation Alternatives (SAMA) analysis 3.0 Contention The Environmental Report inadequately accounts for off-site and economic costs in the SAMA analysis of severe accidents. By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. (Italics added)

Pilgrim Watchs Hearing Request explained numerous ways in which Entergy misused the MACCS2 code,and in which its Environmental Report inadequately accounts for off-site health exposure and economic costs in its SAMA analysis of severe accidents.

As shown in Appendix I, prior decisions of this Board have (improperly in PWs view) taken essentially everything important to protecting the public and the environment off the table. The result has been effectively to ensure that this proceeding will not fulfill the NRCs stated Mission or accomplish the NRCs stated Strategic Objectives. The Board should review its prior orders, and particularly its October 16, 2006 Order that threw out the heart of Pilgrim Watchs original contention, portions of the Majoritys Summary Disposition Order that further limited rewritten Contention 3, and its Order of Novembr 23, 2010.

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In her dissent from the majoritys order granting summary disposition, Judge Young recognized the importance of insuring the public understand that fairness and justice had been done:

Even if in the end Entergy were, in such a hypothetical situation, to prevail on all points, the hearing process, appropriately and flexibly handled so as to assure reasonable and meaningful efficiencies, would (as it should always) ultimately allow for differences between the testimony of the parties various experts on relevant issues to be addressed with all interested parties in one room, without the need for the filing of perhaps so much paper, and with the ability to address much more directly and concisely relevant questions to clarify matters in dispute. Consequently, even if Intervenors lost on these matters, they might well walk away with greater understanding of the issues and a greater sense that fairness and justice had been done. While the resulting increase in public confidence and trust in the NRC adjudication process may not be measurable, I would expect that this would benefit as well from allowing a hearing on the matters of public concern at issue in Contention 3 (at 43, italics added)33 One unfortunate, and perhaps unforseen, result of the Boards prior orders is that licensee applicants have been citing the orders to create the impression that the Board decided issues against PilgrimWatch on their merits, rather than only as a matter of pleading Pilgrim Watch moves that this Board revisit its prior orders and ensure that their effect is consistent with the NRCs stated goals, Mission, and Strategic Outcomes, and provides the full and fair hearing promised by the Boards own brochure.

33 See also fn 47, p 39: [I]n my view my colleagues apply a standard that overlooks or ignores gejuine issues of material fact the Intervenors present throug reputable experts, as well as considerations of practical reality and fundamental fairness.

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V. What Pilgrim Watch Would Have Proved But for the Prior Orders If Pilgrim Watch had been allowed to argue issues that were properly brought forward in its initial Motion to Intervene, May 25, 2006, and it would have offered evidence to prove that:

(i) Entergys use of probabilistic modeling, (ii) Entergys assumption of a small sized accident, instead of what is commonly understood as a severe accident, (iii) Entergys use of the MACCS2 code, (iv) Entergys use of the mean consequence values, and (v) The Boards and Commissions elimination of the significant economic costs, especially cleanup and health costs, both individually and collectively improperly watered- down consequences and permitted Entergy to avoid having to take mitigation steps that would have been required by a proper SAMA analysis.

A. Probabilistic Modeling If PW had been allowed to dispute Entergys use of probabilistic modeling in its SAMA analysis, we would have introduced evidence to show the following:

1. The probability/likelihood of a severe accident used by Entergy in its SAMA analysis was far too low and was intentionally chosen to insure that Entergy would not have to make any significant mitigation steps.
2. By using probabilistic modeling and incorrect parameters in its SAMA analysis Entergy arrives at a result that downplays the likely consequences of a severe accident at PNPS, and thus incorrectly discounts possible mitigation alternatives.

This could have enormous implications for public health and safety because a 55

potentially cost effective mitigation alternative might not be considered that could prevent or reduce the impacts of that accident. Petitioners allege the Environmental Report's SAMA analysis is deficient and the deficiency could significantly impact health and safety.

3. Entergys SAMA analysis multiplied mean consequences by a weighted too-low probability to improperly insure that, no matter how large real economic consequences might be, the consequences supposedly balanced against costs in the SAMA analysis would be trivialized.
4. Permitting an Applicant to simply multiply all consequences of an accident by extremely low probability and thus reject all possible mitigation as too costly, is inconsistent with the NRCs supposedly required Severe Accident Mitigation Analysis.
5. It is widely recognized that probabilistic modeling can underestimate the deaths, injuries, and economic impact likely from a severe accident. By multiplying high consequence values with low probability numbers, the consequence figures appear far less startling.

For example a release that would cause 100,000 cancer fatalities would only appear to cause 1 cancer fatality per year if the associated probability of the release were 1/100,000 per year.

6. NRC in the GEIS recognized what happens when probability weighted consequences are used by the Applicant. It said that, The probability weighted consequences of atmospheric releases, fallout onto open bodies of water, releases to ground water, and societal and economic impacts from severe accidents are small for all plants. However, alternatives to mitigate severe accidents must be considered for all plants that have not considered such alternatives. See § 51.53(c)(3)(ii)(L). (10 C.F.R. Part 51, Subpart A, Appendix B, Table B-1, Issue 76.) (Emphasis added) 56
7. This statement was misinterpreted by Entergy, NRC Staff, the Board, and Commission. Properly understood, the GEIS does not say that accident consequences small; rather it simply says that probability weighted consequences insures that they will appear to be small.
8. The GEIS supports PWs contention that Entergys choice to multiply the mean by the weighted probability in the MACCS2 Output File resulted in minimizing the true consequences in Pilgrims SAMA analysis.
9. Probability may be taken into consideration, but it must be taken with caution, particularly as it relates to Pilgrims SAMA analysis. Kamiar Jamalis (DOE Project Manager for Code Manual for MACCS2) Use of Risk Measures in Design and Licensing Future Reactors,34 explains that PRA uncertainties are so large and so unknowable that it is a huge mistake to use a single number coming from them for any decision regarding adequate protection. Examples of these uncertainties include probabilistic quantification of single and common-cause hardware or software failures, occurrence of certain physical phenomena, human errors of omission and commission, magnitudes of source terms, radionuclide release and transport, atmospheric dispersion, biological effects of radiation, dose calculations, and many others. (Jamali, Pg., 935) (Emphasis added)
10. Probability analysis has other pitfalls. Human error is not considered in PRAs. PRAs project into the future and come up with some very small number that an accident scenario only is likely to occur in so many hundreds-to-thousands of years. But no reactor has operated 45 or more years so actual experience is absent to base predictions.

Uncertainty must be respected by making certain that appropriate and up-to-date methods and assumptions are used in the analysis. Entergy failed to do so.

34 Appendix 3, Exhibit 14 57

B. Amount of Radioactive Release - Size of Accident If PW had been permitted to do so, it would have presented evidence that

1. Entergy limited its SAMA analysis to avoid having to take proper mitigation steps by assuming, and inputting into the MACCS2 code.35
2. A proper source input would have shown that more SAMAs would be justified.
3. Entergy severely and improperly minimized the likely amount of radiation that could be released in a severe accident by (i) assuming, for example, a relatively small release of CsI from the core; (ii) ignoring any release from the spent fuel pool; (iii) and using a source code that underestimated consequence.
4. The source terms used by Entergy to estimate the consequences of severe accidents (radionuclide release fractions generated by the Modular Accident Analysis Progression, MAAP36) code, have not been validated by NRC. They are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.
5. MAAP generates lower release fractions than those derived and used by NRC in studies such as NUREG-1150. A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results 35 Expert

Reference:

Dr. Edwin Lyman would conduct for PW a similar analysis as provided to Riverkeeper in Riverkeeper, Incs Request for Hearing and Petition to Intervene in the License Renewal Proceedings of Indian Point Nuclear Plant, November 30, 2007, pgs., 68-9. Dr. Lymans expert testimony is attached, Appendix 4, Exhibit

12. Because Entergy also used MAAP at Pilgrim, comments made by Dr. Lyman in that declaration are applicable.

36 See, for example, ER. E.1.2.1 58

reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable scenarios.

6. The NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR.
7. The differences in the release fractions are primarily attributable to the use of the different codes in the two analyses. 37
8. The use of source terms generated by MAAP, a proprietary industry code that has not been independently validated by NRC, leads to anomalously low consequences when compared to source terms generated by NRC staff.
9. The NRC has been aware of this discrepancy for at least two decades. In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without 37 See J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.

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performing controlled comparisons for identical boundary conditions and input data.38 We are unaware of NRC having performed such comparisons.

10. The NUREG-1465 source term was also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.39 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.40
11. Entergy should not have used a MAAP-generated source terms in its SAMA analysis.

Core Release If permitted to do so, PW would have presented evidence that Entergy ignored the consequences of a severe accident,41 for example, that

1. Pilgrim has the potential to release more than twice the amount of Cs-137 than was released at Chernobyl. The amount of Cs-137 released during Chernobyl in 1986 was 2,403,000 curies; the amount of Cs-137 in Pilgrims Core during license extension will be 190,000 TBq or 190,000 X 27 Ci = 5,130,000 curies.
2. Entergys MACCS2 model apparently estimated costs based on a release (i) of noble gases in the core inventory and (ii) a small fraction of the core inventory of CsI.

[PNPS Radionuclide Release Category Summary, Figure E.1.1].

38 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.

39 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.

40 J. Schaperow (2002), op cit.

41 See for example, Pilgrim Watchs Brief In Response To CLI-09-11 (Requesting Additional Briefing), June 25, 2009, Pg.,20-21; and Pilgrim Watch's Answer Opposing Entergy's Motion for Summary Disposition of Pilgrim Watch Contention 3, June 29, 2007,Pgs 89-90; Declaration Jan Beyea and Report To The Massachusetts Attorney General On The Potential Consequences Of A Spent-Fuel-Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, Ph.D., May 25, 2006, Pg, 94 -

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Magnitude of Release: Source term results from previous risk studies suggest that categorization of release magnitude based on cesium iodide (CsI) release fractions are appropriate [Reference E.1-5]. The CsI release fraction indicates the fraction of in-vessel radionuclides escaping to the environment. (Noble gas release levels are non-informative since release of the total core inventory is essentially complete given containment failure.) The source terms were grouped into four distinct radionuclide release categories or bins according to release magnitude as follows:

(1) High (HI) - A radionuclide release of sufficient magnitude to have the potential to cause early fatalities. This implies a total integrated release of 10% of the initial core inventory of CsI

[Reference E.1-5]. (1) High (HI) - A radionuclide release of sufficient magnitude to have the potential to cause early fatalities. This implies a total integrated release of >10% of the initial core inventory of CsI [Reference E.1-5].(2) Medium (MED) - A radionuclide release of sufficient magnitude to cause near term health effects. This implies a total integrated release of between 1 and 10% of the initial core inventory of CsI [Reference E.1-5]. (3) Low (LO) - A radionuclide release with the potential for latent health effects. This implies a total integrated release of between 0.001% and 1% of the initial core inventory of CsI. (4) Negligible (NCF) - A radionuclide release that is less than or equal to the containment design base leakage. This implies total integrated release of <0.001% of the initial core inventory of CsI.

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Spent Fuel Pool Release If permitted to do so, PW would have presented evidence that:

1. A spent fuel pool fire could release more than 44,010,000 curies of Cs-137, an amount that is 8 times more than a core release. Further a spent fuel pool fire would result in releases going higher into the air and thereby significantly impacting locations at greater distance with denser populations.
2. Accidents are severe by reason of their consequence, not because of where originate

[NUREG-1437, GEIS, Section 5]. If the costs of an accident resulting from a pool fire were considered, the value of SAMAs would rise significantly. Dr. Beyea estimated the cost of a 10% release from a spent pool fire to be $105-175 billion dollars; and that a 100% release of C-137 would cost between $342-$488 billion.

(Beyea, 10). In contrast, Entergy modeled only the release of a relatively small amount of C-137 from the reactor core.

3. A severe accident from the spent fuel pool at Pilgrim resulting from either human error, mechanical failure or an act of malice is reasonably foreseeable. The offsite cost risk of a pool fire is substantially higher than the offsite cost of a release from a core-damage accident.
4. SAMAs designed to avoid or mitigate conventional accidents may be different than SAMAs designed to avoid or mitigate spent fuel accidents. Moreover, the radiological consequences of a spent-fuel-pool fire are significantly different from the consequences of a core-damage accident.
5. There are significant potential interactions between the pool and the reactor in the context of severe accidents at Pilgrim. The spent-fuel pool is located in the attic of the 62

main reactor building, outside containment. It shares essential support systems with the reactor. There could be at least three types of interactions between the pool and reactor.42 First, a pool fire and a core-damage accident could occur together, with a common cause. For example, a severe earthquake could cause leakage of water from the pool, while also damaging the reactor and its supporting systems to such an extent that a core-damage accident occurs. Second, the high radiation field produced by a pool fire could initiate or exacerbate an accident at the reactor by precluding the presence and functioning of operating personnel. Third, the high radiation field produced by a core-damage accident could initiate or exacerbate a pool fire, again by precluding the presence and functioning of operating personnel. Many core-damage sequences would involve the interruption of cooling to the pool, which would call for the presence of personnel to provide makeup water or spray cooling of exposed fuel.

The third type of interaction was considered in a license-amendment proceeding in regard to expansion of spent-fuel-pool capacity at the Harris nuclear power plant.

Such accidents are conceivable and would result in a very high magnitude of release.

6. 10 C.F.R. § 51.53(c)(3)(ii)(L), does not provide a definition of severe accidents.
7. GEIS43 which provides the factual background for the SAMA requirement in the regulations, does define a severe accident.

The term "accident" refers to any unintentional event outside the normal plant operational envelope that results in a release or the potential for release of radioactive materials into the environment. Generally, the U.S.

42 Dr. Gordon Thompson, Risks of Pool Storage of Spent Fuel at Pilgrim Nuclear Power Station and Vermont Yankee, A Report for the Massachusetts Attorney General by IRSS, May 2006, Pgs., 12, 16. NRC Electronic Library, Adams Accession Number ML061630088 43 See NUREG-1437, Generic Environmental Impact Statement for License Renewal of Nuclear Plants (May 1960)

[hereinafter GEIS]; Final Rule, Environmental Review for Renewal of Nuclear Power Plant Operating Licenses, 61 Fed. Reg. 28, 467 (June 5, 1960, amended by 61 Fed. Reg. 66, 537 (Dec. 18, 1996); 10 C.F.R. Pt. 51, Subpart A, Appendix B n.1) 63

Nuclear Regulatory Commission (NRC) categorizes accidents as "design basis" (i.e., the plant is designed specifically to accommodate these) or "severe" (i.e., those involving multiple failures of equipment or function and, therefore, whose likelihood is generally lower than design-basis accidents but where consequences may be higher), for which plants are analyzed to determine their response. The predominant focus in environmental assessments is on events that can lead to releases substantially in excess of permissible limits for normal operation. Normal release limits are specified in the NRC's regulations (10 C.F.R. Part 20 and 10 C.F.R. Part 50, Appendix A). GEIS, 5.2.1. Italics added

8. According to Section 5.2.1 of NUREG 1437 General Characteristics of Accidents, the term accident refers to any unintentional event outside the normal plant operational envelope that results in a release or the potential for release of radioactive materials into the environment and severe [includes] those involving multiple failures of equipment or function and, therefore, whose likelihood is generally lower than design basis accidents but where consequences may be higher . . . (emphasis added). This section recognizes the potential for a severe accident in which there are releases substantially in excess of permissible limits for normal operation.
9. Section 5 focuses on potential consequences to determine whether or not a potential accident is severe - and thus within the scope of a Severe Accident Mitigation Analysis.
10. Section 6 of the GEIS with Section 5. Section 6 deals with normal operations (see, for example, section 6.1: Accidental releases could conceivable result in releases that would cause moderate or large radiological impacts. Such conditions are beyond the scope of regulations controlling normal operations. (Emphasis added).
11. Section 5, not Section 6, deals with severe accidents. The question is not whether the source of the Severe Accident is the first or second largest inventory of radioactive 64

materials. Nothing in Section 5 excludes severe accidents involving what at Pilgrim Station is the largest inventory of radioactive materials - the spent fuel pool.

Use of the MACCS2 Code If permitted to do so, PW would have presented evidence that Entergy improperly used the MACCS2 code to reduce the supposed consequences of an improperly assumed accident and, thus, mitigation steps that Entergy properly should be required to take. More particularly, PW would have presented evidence showing:

1. No NRC regulation requires the use of the MACCS2 code, or any other particular code, and there other codes available.
2. The code is not Quality Assured.44 The MACCS & MACCS2 codes were developed for research purposes not licensing purposes -for that reason they were not held to the QA requirements of NQA-a (American Society of Mechanical Engineering, QA Program Requirements for Nuclear Facilities, 1994). Rather they were developed using following the less rigorous QA guidelines of ANSI/ANS 10.4. [American Nuclear Standards Institute and American Nuclear Society, Guidelines for the Verification and Validation of Scientific and Engineering Codes for the Nuclear Industry, ANSI/ANS 10.4, La Grange Park, IL (1987).
3. In addition to the meteorological inputs discussed above, important code input parameters include source, average (cumulative distribution function), probability, and a discount rate applied in CHRONC.

44 Chanin, D.I. (2005), "The Development of MACCS2: Lessons Learned," [written for:] EFCOG Safety Analysis Annual Workshop Proceedings, Santa Fe, NM, April 29-May 5, 2005. Full text: the development of maccs2.pdf (154 KB), revised 12/17/2009. http://chaninconsulting.com/index.php?resume. (Attachment 5, Exhibit 4) 65

4. Source is chosen by Entergy and input to ATMOS. ATMOS outputs, based on Entergys chosen source, are input into both EARLY and CHRONC which determine consequences of an accident from Entergys chosen source. Entergy chose an unrealistically low source input for the purpose of avoiding having to take mitigation steps that would have to be taken if a realistic source input was used.
5. A discount rate is chosen by Entergy and input to CHRONC, which in determining consequences applies the discount rate to property that must be condemned. A discount makes little sense. Properties appreciate over 20 years, not depreciate.
6. The type of average and probability of an accident are also chosen by Entergy. The Output file averages consequences from EARLY and CHRONC and permits the user to average using any one of several percentiles, including mean, 90th percentile, and 95th percentile. Entergy chose mean for the purpose of avoiding having to take mitigation steps that would have to be taken if a higher, i.e., 90th or 95th percentile had been chosen.
7. Entergy failed to consider the uncertainties in its consequence calculation resulting from meteorological variations by only using mean values (LRA, Appendix E.1.5.3) for population dose and offsite economic cost estimates. If PW had been allowed to show the impact from using different statistical analyses, more SAMAs would have come into play.
8. In the License Renewal GEIS refers repeatedly to the 95th percentile of the risk uncertainty distribution as an appropriate upper confidence bound in order not to underestimate potential future environmental impacts.45 45 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol. 1, May 1996, Section 5.3.3.2.1.

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9. The consequence calculation, as carried out by the MACCS2 code, generates a series of results based on random sampling of a years worth of weather data. The code provides a statistical distribution of the results. Based on calculations done at other reactors such as Indian Point, the ratio of the 95th percentile to the mean of this distribution is typically a factor of 3 to 4 for outcomes such as early fatalities, latent cancer fatalities and off-site economic consequences. 46
10. The Output file also multiplies the consequences resulting from Entergys chosen consequence percentile by an assumed probability of an accident, which is also chosen by Entergy. Entergy improperly assumed, and chose, an extremely low probability for the purpose of avoiding having to take mitigation steps that would have to be taken if a probability that was realistic and would provide protection to the public had been chosen.

Cleanup/Decontamination, Health and Other Costs If permitted to do so, Pilgrim Watch would have presented evidence that Entergy, severely minimized decontamination and clean-up costs47, health costs48 (that includes inaccurately 46 Dr. Edwin S. Lyman, Senior Staff Scientist, Union of Concerned Scientists report commissioned by Riverkeeper, Inc., November 2007, A Critique of the Radiological Consequence Assessment Conducted in Support of the Indian Point Severe Accident Mitigation Alternatives Analysis; available at NRC Electronic Library, Adams Accession Number ML073410093, Exhibit 12 47 Decontamination/Cleanup, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg., 90-; And Accompanying Declaration Of David L.

Chanin In Support Of Pilgrim Watch's Response Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, (Maccs2 Support Forum, August 23, 2006 & January 23, 2007) June 5, 2007; and Pilgrim Watchs Brief in Response to CLI-09-11 (Requesting Additional Briefing) June 25, 2009, Pgs., 12-13 48 Health Costs, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007,Pg.,7,8,18,23,32-37,46-48,66, 81-86; and Declaration Dr. Jan Beyea (Report To The Massachusetts Attorney General On The Potential Consequences Of A Spent-Fuel-Pool Fire At The Pilgrim Or Vermont Yankee Nuclear Plant, Jan Beyea, Ph.D., May 25, 2006), Pgs., 6,7,13,15; and Pilgrim Watchs Brief in Response to CLI-09-11 (Requesting Additional Briefing) June 25, 2009, Pgs.,12, 19. Evacuation time estimates incorrect resulting in increased health costs as fewer people evacuate in a timely manner: see : Pilgrim 67

modeling evacuation time estimates), and minimized and ignored a myriad of other economic costs,49 both within and outside of Plymouth County, that belong in a SAMA analysis.

For example, with respect to the area potentially affected by a severe accident at PNPS, Pilgrim Watch would have presented evidence that:

1. The costs of a radiological accident at PNPS would not be limited to Plymouth County, but would affect the Commonwealth of Massachusetts, Southeastern Massachusetts, and three other counties.
2. Both Providence and Boston are within 45 miles PNPS and could be sustain significant radiological damage if a severe accident should occur at PNPS.

With respect to cleanup, Pilgrim Watch would have presented evidence showing that:

1. Cleanup costs are the Elephant in the Room that NRC and Entergy want to avoid.

Proper clean-up would result in major offsite costs requiring the addition of a large number of mitigations.

2. The MACCS2 Decontamination Plan is described in part in the Code Manual for MACCS2: Volume I, Users Guide (NUREG/CR-6613, Vol. 1) Prepared by D.

Chanin and M.I. Young, May 1998. Section 7.5 Decontamination Plan describes some of the assumptions. It says at 7-10 that, Many decontamination processes (e.g., plowing, fire hosing) reduce groundshine and resuspension doses by washing surface contamination down into the ground. Since these processes may not move contamination out of the root zone, the WASH-1400 based economic cost model of Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007,Pg.,58-71 and Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg., 11,19-20.

49 Other Economic Costs, see for example: Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg.,72-91; Pilgrim Watch's Answer Opposing Entergy's Motion For Summary Disposition Of Pilgrim Watch Contention 3, June 29, 2007, Pg.,10-12, 22.

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MACCS2 assumes that farmland decontamination reduces direct exposure doses to farmers without reducing uptake of radioactivity by root systems.

Thus decontamination of farmland does not reduce the ingestion doses produced by the consumption of crops that are contaminated by root uptake.

3. The MACCS2 cleanup assumptions used by Entergy are directly based on WASH-1400; WASH-1400, in turn, was based on clean up after a nuclear explosion.
4. Cleanup after a nuclear bomb explosion is not comparable to clean up after a nuclear reactor accident; Entergys apparent assumption that the two are comparabile severely underestimated cleanup costs. Nuclear explosions result in larger-sized radionuclide particles; reactor accidents release small sized particles. Decontamination is far less effective, or even possible, for small particle sizes. Nuclear reactor releases range in size from a fraction of a micron to a couple of microns; whereas nuclear bomb explosions fallout is much larger- particles that are ten to hundreds of microns. These small nuclear reactor releases can get wedged into small cracks and crevices of buildings.
5. WASH-1400s nuclear weapon clean up experiments involved cleaning up fallout involving large mass loading where the there was a small amount of radioactive material in a large mass of dirt and demolished material. Only the bottom layer will be in contact with the soil and the massive amount of debris can be swept up with brooms or vacuums resulting in a relatively effective, quick and cheap cleanup that would not be the case with a nuclear reactors fine particulate. (CLI-10-11, Pg., 29-30)
6. A weapon explosion results in non-penetrating radiation so that workers only require basic respiration and skin protection. This allows for cleaning up soon after the event.

In contrast a reactor release involves gamma radiation and there is no gear to protect 69

workers from gamma radiation. Therefore cleanup cannot be expedited and decontamination is less effective with the passage of time.

7. Entergys cost model ignored radioactive waste disposal. In a weapons event, the waste could be shipped to Utah or to the Nevada Test Site. The Greater- than- Class C waste expected in a reactor accident would not have a repository likely available to receive such a large quantity of material in the foreseeable future. Also, the costs incurred for safeguarding the wastes and preventing their being re-suspended are not accounted for in the model. Even optimistically assuming a repository becoming available, (Utah site is approximately one-square mile) it seems unlikely that there would be a sufficient quantity of transport containers and communities not objecting to the hazardous materials going over their roads and through their communities.
8. The Users Guide describes decontamination processes as plowing and fire hosing. CERLA, EPA and local authorities would not allow use of those methods.

Fire hosing and plowing do not decontaminate, it simply moves the contamination from one place to another - only to reappear again later in groundwater, resuspended into the air, or in food. Therefore cleanup will take far longer and be more expensive than assumed by Entergy; and its success (defined as returning to pre-accident status) unlikely.

9. Also apparently missing from consideration is that forests, wetlands and shorelines cannot realistically be cleanup and decontaminated. The area within 50-miles of Pilgrim Station consists of miles of beaches, rivers, lakes, ponds, bogs, wetlands, forests and park land Additionally, urban areas will be considerably more expensive and time consuming to decontaminate and clean than rural areas.

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10. The US Department of Homeland Security has commissioned studies for the economic consequences of a Rad/Nuc attack. Much more deposition would occur in reactor accident, magnifying consequences and costs, but there are important lessons to be learned from these studies. Barbara Reichmuths study, Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost, 2005,50 Table 1 Summary Unit Costs for D &D (Decontamination and Decommissioning) Building Replacement and Evacuation Costs provides estimates for different types of areas from farm or range land to high density urban areas.

Reichmuths study also points out that the economic consequences of a Rad/Nuc event are highly dependent on cleanup standards: Cleanup costs generally increase dramatically for standards more stringent than 500 mrem/yr.

11. Currently the NRC and EPA have not agreed on a cleanup standard.51 The potential standard appears to range from 15 mrem/yr to 5 rem/yr. The General Accounting Office (GAO) reports that the current EPA and NRC cleanup standards differ and these differences have implications for both the pace and ultimate cost of cleanup.52 Entergy should have used the EPA (15 mrem/yr) standard in determining clean-up costs; it did not.

50 Economic Consequences of a Rad/Nuc attack: Cleanup Standards Significantly Affect Cost Barbara Reichmuth, Steve Short, Tom Wood, Fred Rutz, Debbie Swartz, Pacific Northwest National laboratory, 2005 (Attachment 6, Exhibit 8) 51 See Pilgrim Watchs Request For Hearing On New Contention; the information upon which this contention is available from a trade publication INSIDE EPA; please see report and supporting documents at http://environmentalnewsstand.com/Environmental-NewsStand-General/Public-Content/agencies-struggle-to-craft-offsite-cleanup-plan-for-nuclear-power-accidents/menu-id-608.html 52 GAO, Radiation Standards Scientific Basis Inconclusive, and EPA and NRC Disagreement Continues, June 2004 71

12. A similar study was done by Robert Luna, Survey of Costs Arising from Potential Radionuclide Scattering Events,.53 concluded that, the expenditures needed to recover from a successful attack using an RDD type device are likely to be significant from the standpoint of resources available to local or state governments Even a device that contaminates an area of a few hundred acres (a square kilometer) to a level that requires modest remediation is likely to produce costs ranging from

$10M to $300M or more depending on the intensity of commercialization, population density, and details of land use in the area. (Luna, Pg., 6)

13. A severe accident at Pilgrim will result in huge costs, not accounted for by Entergy, largely because the type and magnitude of radionuclides released in a reactor accident are very different than those released by a RDD type device as explained directly above, 3-5.
14. In place of the outdated decontamination costs figure in the MACCS2 code, the SAMA analysis for Entergy should have incorporated the analytical framework contained in the 1996 Sandia National laboratories report concerning site restoration costs54 as well as Lunas and Reichmuths methodology and studies examining Chernobyl.
15. The Sandia Site restoration study analyzed the expected financial costs for cleaning up and decontaminating a mixed-use urban land and Midwest farm and range land. The study was commissioned by DOE to estimate activities 53 Survey of Costs Arising From Potential Radionuclide Scattering Events, Robert Luna, Sandia National laboratories, WM2008 Conference, February 24-28, 2008, Phoenix AZ (Attachment 7, Exhibit 9) 54 Site Restoration: Estimation of Attributable Costs from Plutonium-Dispersal Accidents, SAND96-0957, David Chanin, Walt Murfin, UC-502, (May 1996) 72

likely to be involved in the decontamination of an accident involving the dispersal of plutonium. Although there would be many differences in a nuclear reactor accident, the methodology and conclusions to estimate costs are directly useful.

16. The Sandia Site study recognized that earlier estimates (those incorporated in WASH-1400 and incorporated in MACCS2) of decontamination costs are incorrect because they examined fallout from nuclear explosion of nuclear weapons that produce large particle sizes and high mass loadings.
17. For an extended decontamination and remediation operation in a mixed-use urban area with an average population density, Site restoration (1996) predicted a cleanup cost of $311,000,000 per square km using offsite disposal and

$309,000,000 per square km using on-site disposal. (Site restoration, Pg., 6-5)

18. The costs would be much higher today with inflation and for example for the metropolitan areas of Boston and Providence considering that they are tourist, educational, transportation, and financial centers. The economic losses stemming from the stigma effects of a severe accident would be staggering.

The Sandia Site restoration study further says, In comparing the numbers of cancer health effects that could result from a plutonium-dispersal accident to those that could result from a severe accident at a commercial nuclear power plant, it is readily apparent that the health consequences and costs of a severe reactor accident could greatly exceed the consequences of even a worst- case plutonium-dispersal accident because the quantities of radioactive material in nuclear weapons are a small fraction of the quantities present in an operating nuclear power plant. (Site restoration, Pg., 2-3, 2-4) 73

19. Under decontamination costs, Entergy lists the costs of farm and non-farm decontamination and the value of farm and nonfarm wealth. However nowhere is there a discussion of the loss of, and costs to remediate the economic infrastructure that make business, tourism and other economic activity possible.
20. Economic infrastructure is the basic physical and organizational structures needed for the operation of a society or enterprise, or the services and facilities necessary for an economy to function. The term typically, and as used by PW, refers to the technical structures that support a society, such as roads, water supply, sewers, power grids telecommunications, and so forth. Viewed functionally, infrastructure facilitates the production of goods and services; for example, roads enable the transport of raw materials to a factory, and also for the distribution of finished products to markets. Also, the term may also include basic social services such as schools and hospitals.
21. Entergy appears to ignore the indirect economic effects or the multiplier effects. For example, depending on the business done inside the building contaminated, the regional and national economy could be negatively impacted.

A resulting decrease in the areas real estate prices, tourism, and commercial transactions could have long-term negative effects on the regions economy.

22. Entergy should have been required to take all of these real cleanup costs into account; but the Board and Commissions decisions resulted in their not being required to do so and as a result the public will not get the safety enhancements that we deserve.

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23. The following illustrates the significant effect of Entergys failure properly to consider the costs of cleanup:

1987 Radiological Accident in Goiania, Brazil55 In September 1987, a hospital in Goiania, Brazil, moved to a new location and left its radiation cancer therapy unit behind. Found by scrap metal hunters, it was dismantled and the cesium chloride source containing 1,400 Ci of cesium-137 was removed. Pieces were distributed to family and friends, and several who were intrigued by the glow spread it across their skin. Eleven days later, alert hospital staff recognized symptoms of acute radiation syndrome in a number of victims.

The ensuing panic caused more than 112,000 people - 10% of the population - to request radiation surveys to determine whether they had been exposed. At a makeshift facility in the citys Olympic Stadium, 250 people were found to be contaminated. 28 had sustained radiation-induced skin injuries (burns), while 50 had ingested cesium, so for them the internal deposition translated to an increased risk of cancer over their lifetime. Tragically, 2 men, 1 woman, and 1 child died from acute radiation exposure to the very high levels of gamma radiation from the breached source.

In addition to the human toll, contamination had been tracked over roughly 40 city blocks. Of the 85 homes found to be significantly contaminated, 41 were evacuated and 7 were demolished. It was also discovered that through routine travels, within that short time people had cross-contaminated houses nearly 100 miles away.

Cleanup generated 3,500 m3 radioactive waste at a cost of $20 million.

The impacts of this incident continued beyond the health and physical damage to profound psychological effects including fear and depression for a large fraction of the citys inhabitants.

Further, frightened by the specter of radioactive contamination, neighboring provinces isolated Goiania and boycotted its products. The price of their manufactured goods dropped 40% and stayed low for more than a month. Tourism, a 55 Revisiting Goiania: Toward a final repository for radioactive waste, IAEA Bulletin 1993,Rad waste 3,500 cubic meters,1270 to 1340 curies in waste,http://www.ead.anl.gov/pub/doc/rdd.pdf Exhibit 15 75

primary industry, collapsed and recent population gains were reversed by business regression. Total economic losses were estimated at hundreds of millions of dollars.

Health Costs With respect to health costs, Pilgrim Watch would have presented evidence showing that Entergys life lost value is much too low.

1. EPA values a life lost at $6.1 million (U.S.E.P.A., 1997, The Benefits and Costs of the Clean Air Act, 1970 to 1990, Report to US Congress (October), pages 44-45). Pilgrims ER assigns a value of $2000 per person rem.
2. The population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure is based on a deeply flawed analysis and seriously underestimates the cost of the health consequences of severe accidents.
3. Entergy underestimates the population-dose related costs of a severe accident by relying inappropriately on a $2000/person-rem conversion factor. Entergys use of the conversion factor is inappropriate because it (a) does not take into account the significant loss of life associated with early fatalities from acute radiation exposure that could result from some severe accident scenarios; and (b) underestimates the generation of stochastic health effects by failing to take into account the fact that some members of the public exposed to radiation after a severe accident will receive doses above the threshold level for application of a dose- and dose-rate reduction effectiveness factor (DDREF).
4. Entergys $2000/person-rem conversion factor is apparently intended to represent the cost associated with the harm caused by radiation exposure with respect to the causation 76

of stochastic health effects, that is, fatal cancers, nonfatal cancers, and hereditary effects.56 The value was derived by NRC staff by dividing the Staffs estimate for the value of a statistical life, $3 million (presumably in 1995 dollars, the year the analysis was published) by a risk coefficient for stochastic health effects from low-level radiation of 7x10-4/person-rem, as recommended in Publication No. 60 of the International Commission on Radiological Protection (ICRP). (This risk coefficient includes nonfatal stochastic health effects in addition to fatal cancers.) But the use of this conversion factor in Pilgrims SAMA analysis is inappropriate in two key respects. As a result Entergy underestimated the health-related costs associated with severe accidents.

5. First, the $2000/person-rem conversion factor is specifically intended to represent only stochastic health effects (e.g. cancer), and not deterministic health effects including early fatalities which could result from very high doses to particular individuals.57 However, for some of the severe accident scenarios evaluated, large numbers of early fatalities could occur representing a significant fraction of the total number of projected fatalities, both early and latent. This is consistent with the findings of the Generic Environmental Impact Statement for License Renewal of Nuclear Plants (NUREG-1437).58 Therefore, it is inappropriate to use a conversion factor that does not include deterministic effects. According to NRCs guidance, the NRC believes that regulatory issues involving deterministic effects and/or early fatalities would be very rare, and can be addressed on a case-specific basis, as the need arises.59 Based on our estimate of the 56 U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy, NUREG-1530, 1995, p. 12.

57 U.S. NRC (1995), op cit., p. 1.

58 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol.

1, May 1996, Table 5.5.

59 U.S. NRC, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy (1995), op cit., p. 13.

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potential number of early fatalities resulting from a severe accident at Pilgrim, this is certainly a case where this need exists.

6. Second, the $2000/person-rem factor, as derived by NRC, also underestimates the total cost of the latent cancer fatalities that would result from a given population dose because it assumes that all exposed persons receive dose commitments below the threshold at which the dose and dose-rate reduction factor (DDREF) (typically a factor of 2) should be applied. However, for certain severe accident scenarios at Pilgrim evaluated by Entergy, we estimate that considerable numbers of people would receive doses high enough so that the DDREF should not be applied.60 This means, essentially, that for those individuals, a one-rem dose would be worth more because it would be more effective at cancer induction than for individuals receiving doses below the threshold. To illustrate, if a group of 1000 people receive doses of 30 rem each over a short period of time (population dose 30,000 person-rem), 30 latent cancer fatalities would be expected, associated with a cost of $90 million, using NRCs estimate of $3 million per statistical life and a cancer risk coefficient of 1x10-3/person-rem. If a group of 100,000 people received doses of 0.3 rem each (also a population dose of 30,000 person- rem), a DDREF of 2 would be applied, and only 15 latent cancer fatalities would be expected, at a cost of

$45 million. Thus a single cost conversion factor, based on a DDREF of 2, is not appropriate when some members of an exposed population receive doses for which a DDREF would not be applied.

7. A better way to evaluate the cost equivalent of the health consequences resulting from a severe accident is simply to sum the total number of early fatalities and latent cancer 60 The default value of the DDREF threshold is 20 rem in the MACCS2 code input 78

fatalities, as computed by the MACCS2 code, and multiply by the $3 million figure. It is not reasonable to distinguish between the loss of a statistical life and the loss of a deterministic life when calculating the cost of health effects.

8. That Entergys estimates of how many lives might be lost are too low is also shown by the 1982 Sandia National Laboratory report. Using 1970 census data, that report estimated the number of cancer deaths at Pilgrim as a consequence of a severe reactor accident61 in a severe accident to be 3,000 early fatalities within the first year and 30,000 peak early injuries within the first year.7,000 and early injuries 27,000. Peak fatalities were estimated by CRAC to occur within 20 miles of Pilgrim; and peak injuries to occur with 65 miles of Pilgrim from a core melt. (CRAC 2, Sandia, 198262)
9. The population of the affected area, no matter what model is used, has greatly increased during the intervening almost 40 years; SAMAs project forward to 2050 based on projected demographics. Entergy estimated the population within 50-miles (2032) to total 7489767. (LRA, Appendix E.1.5.2.1, Table E.1-13) Further CRAC was based on old, and now outdated, dose response models.
10. In Entergys SAMA analysis, cancer incidence was not considered; neither were the many other potential health effects from exposure in a severe radiological event (National Academy of Sciences, BEIR VII Report, 2005).
11. Entergys cost-benefit analysis ignored a marked increase in the value of cancer mortality risk per unit of radiation at low doses (2-3 rem average), as shown by recent studies 61 Sandia National Laboratory study for U.S. Nuclear Regulatory Commission, Calculation of Reactor Accident Consequences for U.S. Nuclear Power Plants (CRAC 2), 1981.

62 Calculation of Reactor Accident Consequences, U.S. Nuclear Power Plants (CRAC-2), Sandia National Laboratory, 1982.

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published on radiation workers (Cardis et al. 200563) and by the Techa River cohort (Krestina et al (200564). Both studies give similar values for low dose, protracted exposure, namely (1) cancer death per Sievert (100 rem). According to the results of the study by Cardis et al. and use of the risk numbers derived from the Techa River cohort the SAMA analyses prepared for Pilgrim needs to be redone. If done so properly a number of additional SAMAs that were previously rejected by the applicants methodology would become cost effective.

12. Cancer incidence and the other many health effects from exposure to radiation in a severe radiological event (National Academy of Sciences, BEIR VII Report, 2005) should have been considered; they were not. Neither did Entergy consider indirect costs. Medical expenditures are only one component of the total economic burden of cancer. The indirect costs include losses in time and economic productivity and liability resulting from radiation health related illness and death.
13. Applicants data into the code were unrealistically low. If correct evacuation times and assumptions regarding evacuation had been used, the analysis would show far fewer will evacuate in a timely manner, increasing health-related costs.

Evacuation Time Estimates Health Costs If Pilgrim Watch had been permitted to do so, it also would have presented evidence showing:

63 Elizabeth Cardis, Risk of cancer risk after low doses of ionising radiation: retrospective cohort study in 15 countries. British Medical Journal (2005) 331:77. Referenced Beyea, Exhibit 2 64 Krestinina LY, Preston DL, Ostroumova EV, Degteva MO, Ron E, Vyushkova OV, et al. 2005.Protracted radiation exposure and cancer mortality in the Techa River cohort. Radiation Research 164(5):602-611.Exh 2 80

14. The KLD time estimates relied upon did not take into consideration in the analysis variables that would slow evacuation: shadow evacuation; evacuation time estimates during inclement weather coinciding with high traffic periods such as commuter traffic, traffic during peak commute times, holidays, summer beach/holiday traffic; notification delay delays because notification is largely based on sirens that cannot be heard in doors above normal ambient noise with windows closed or air conditioning systems operating.
15. The Applicant performed a sensitivity analysis that assumed no evacuation of the population in a severe accident and found only a small increase to the overall total accident dose risk and no change in economic risk. However, Entergys sensitivity studies did not provide useful information since the model on which they were based was flawed.

Myriad of Other Economic Costs

16. Entergy did not appear to include in their economic cost estimates the business value of property and the incurred costs such as costs required from job retraining, unemployment payments, and inevitable litigation. Entergy used an assumed value of non-farm wealth that appeared not justified by review of Banker and Tradesmen sales figures. Entergy underestimated Farm Value, for example, by not considering the value of the farm property for development purposes as opposed to agricultural; and farm land assessments are intentionally very low to encourage farming and open space.

If the Board Majority and Commission had not removed from consideration all the important factors initially brought forward by Pilgrim Watch, PW could have proved that Entergy 81

significantly minimized the consequences from a severe accident at Pilgrim to such a degree as to require substantial mitigation.

The magnitude of Entergys minimization of costs makes obvious that many SAMAs would be cost effective if the described defects in the analysis were addressed. In Duke Energy Corp.,

at 13, the board said that [w]hile NEPA does not require agencies to select particular options, it is intended to foster both informed decision-making and informed public participation, and thus to ensure the agency does not act upon incomplete information, only to regret its decision after it is too late to correct (citing Louisiana Energy Services (Claiborne Enrichment Center), CLI 3, 47 NRC 77, 88 (1998)). It then said if further analysis is called for, that in itself is a valid and meaningful remedy under NEPA.

In its Contention 3, PilgrimWatch pointed to a material deficiency in the Application -

Entergy has drastically under counted the costs of a severe accident that could have led to erroneously rejecting mitigation alternatives and the admitted contentions statement that further analysis is required is correct, and could produce a very different outcome of this proceeding.

Respectfully Submitted,

[Signed electronically]

Mary Lampert Pilgrim Watch, pro se 148 Washington Street Duxbury, MA 02332 781-934-0389 Mary.lampert@comcast.net January 3, 2011 82

Appendices 83

APPENDIX 1 A Review of Prior Board and Commission Decisions (2006-2010)

A. Request for Hearing.

Pilgrim Watch filed its Request For Hearing and Petition To Intervene By Pilgrim Watch on May 25, 2006 (Hearing Request). That Hearing Request set forth four Contentions.

Contentions 1, 2 and 4 have been rejected by the Board and Commission, and remain only for appeal.

Pilgrim Watchs Contention 3 squarely raised important issues that are consistent with ensur[ing] adequate protection of public health and safety ... and protect[ion of] the environment. Originally filed Contention was (Hearing Request p 26):

Contention 3: The Environmental Report is inadequate because it ignores the true off-site radiological and economic consequences of a severe accident at Pilgrim in its Severe Accident Mitigation Alternatives (SAMA) analysis 3.0 Contention The Environmental Report inadequately accounts for off-site and economic costs in the SAMA analysis of severe accidents. By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. (Italics added)

The complete inputs to the MACCS2 actually used by Entergy were not publicly available, and were not included in Entergys Environmental Report. Without knowing what parameters (e.g., probabilities, source term, consequences percentile) and other specific inputs chosen by Entergy, it [was] not possible [for PW] to fully evaluate the correctness of the

conclusions about Severe Accident Mitigation Alternatives. However, from what is included in the ER, Petitioners have been able to piece together some possible reasons that Entergys described consequences of a severe accident at Pilgrim look so small. (Hearing Request 34).

Based on the information available to it, Pilgrim Watchs Hearing Request pointed out a number of ways in which Entergy improperly used the MACCS2 code, and in which its Environmental Report inadequately accounted for off-site health exposure and economic costs in its SAMA analysis of severe accidents.

For example, the Hearing Request said at the outset that:

By using probabilistic modeling and incorrectly inputting certain parameters into the modeling software, Entergy has downplayed the consequences of a severe accident at Pilgrim and this has caused it to draw incorrect conclusions about the costs versus benefits of possible mitigation alternatives. [Emphasis added] (Hearing Request, 28)

Pilgrim Watch then said, not that probabiltic modeling was per se improper, but that Entergy had misused it to improperly minimize SAMAs:

x [T]he likely impacts of a servere accident have been dramatically minimized by using probabilistic modeling which makes the costs of all severe accidents appear negligible. ... [A]ny time an applicant multiplies an accident consequence by an extremely low probability number, the consequences will appear minute. (Hearing Request 29)

Appendix 1 - Page 2

x It would make no sense for the NRC to require Severe Accident Mitigation Analysis if an applicant could simply multiply all consequences of an accident by extremely low probability and thus reject all possible mitigation as too costly. (Hearing Request 30).

As for the manner in which consequences were calculated, before being reduced to nothingness by Entergys choice of probability used in the codes Output File, the Hearing Request said, as quoted above, that Entergy has downplayed the consequences of a severe accident by incorrrectly inputting certain parameters into the modeling software. (Hearing Request 28). The Request went on to say:

In addition, Entergy has used incorrect input parameters, including meteorological, emerency response, and economic data, into a software model of limited scope.

(Hearing Request 29).

Because of the limited public information available showing what Entergy had actually done, Pilgrim Watchs use of including was not, could not be, and was not intended to be, inclusive. Entergys choice of a low probability number was clearly encompassed by the Hearing Request (see Hearing Request 28, 29).

What Pilgrim Watch now knows, is that there many important inputs and parameters, chosen by Entergy, that drastically effect consequences. These include not only meteorological, emergency response, and economic data and the probability number, but also the chosen source (Entergy chose a small source) and averaging method Appendix 1 - Page 3

(Entergy chose mean rather than one of larger percentiles, e.g., 95th, that the code presents as options).

On the basis of what it then knew from public knowledge, Pilgrim Watchs Hearing Request was able to, and did, say that: Neither the MACCS2 model used to analyze consequence nor the input data provided by the applicant provide an accurate assessment of the off-site dose and economic consequences of a severe accident.... [T]here are limitations inherent in the software ... which by design omit the majority of economic costs. (Hearing Request 34)

In short, Pilgrim Watchs original contention made at least three points, specific to Pilgrims SAMA:

1) The way in which Entergy used probabilistic modeling was inadequate.
2) As used by Entergy to analyze consequences, the MACCS2 model did not provide an accurate assessment of the off-site dose and economic consequences of a severe accident
3) Entergys choice of parameters it put into the modeling software had the intended result of downplaying the consequences of a severe accident.

There can be no question that each of these points, as applied to Pilgrims SAMA analysis, could be proved. There also can be no question that the Hearing Request pointed to Appendix 1 - Page 4

each as specific deficiencies in Pilgrims SAMA analysis, and that Pilgrim Watchs original Contentiion was not generic.65 B. The Orders Narrowing Contention 3 Nonetheless, at the outset of this proceeding, in its October 16, 2006 Memorandum And Order (Ruling on Standing and Contentions of Petitioners Massachusetts Attorney General and Pilgrim Watch), the Board, in Pilgrim Watchs view improperly, rewrote Contention 3 to say only that:

Applicants SAMA analysis for the Pilgrim plant is deficient in that the input data concerning (1) evacuation times, (2) economic consequences, and (3) meteorological patterns are incorrect, resulting in incorrect conclusions about the costs versus benefits of possible mitigation alternatives, such that further analysis is called for.

In doing so, the Board entirely deleted by using probabilistic modeling from PWs original contention, saying that probabilistic techniques that evaluate risk could not be challenged on a generic basis,66 and that the use of probabilistic risk assessment and modeling is obviously accepted and standard practice in SAMA analyses. (Id at 100).

65 Under NRC Regulations, SAMAs are a Category 2 (site specific), and not a Category 1 (generic), issue.

Table 9.1 of NUREG 1437 lists both Category 1 and Category 2 issues, and identifies SAMAs as Category 2. Entergy seems to agree that SAMAs are Category 2.

66 The Board majority seemed not to appreciate that PWs original Contention 3 did not generically challenge probabilistic modeling, the MACCS2 code, or averaging. Pilgrim Watchs challenges were specific both to the site and to the ways in which Entergy chose to misuse probabilities, the MACCS2 code, and averaging: Applicants SAMA analysis for the Pilgrim plant is deficient...

Appendix 1 - Page 5

The Board then went on to limit what remained of the original contention -

incorrectly inputting certain parameters into the modeling software - to the specific in addition inputs that Pilgrim Watch had been able to identify from public information at the time its Hearing Request was filed. To complete its exclusion of probabilistic modeling from the rewritten contention and scope of this proceeding, the low probability number (Hearing Request 29) and extremely low probability (Hearing Request 30) inputs were never mentioned.

At that time in history, Pilgrim Watch, a small public interest group, did not fully appreciate what the Boards re-writing of Contention 3 had done. And PW certainly did not appreciate, and then could not have appreciated, that the majoritys later Summary Disposition decision would go even farther, and hold that its rewriting of Contention 3 eliminated all challenges, not simply to probabilistic modeling, but also to the adequacy of the MACCS2 code (Order Granting Summary Disposition, pg.,2, italics added):

Not at issue here, as discussed below in more depth, because these matters were raised and eliminated at the contention admissibility stage, are issues related to: (1) the adequacy of the computer code (MACCS2) used to perform the SAMA computations; (2) the use for SAMA analyses of probabilistic (as opposed to deterministic) methodologies; and (3) the health effects of low doses of radiation.

Judge Young certainly did not understand the October 2006 order to be that draconian (Dissenting Opinion of Administrative Judge Ann Marshall Young, 35, italics Judge Youngs):

Appendix 1 - Page 6

By stating that we found inadmissible any part of the contention that could be construed as challenging on a generic basis the use of probabilistic techniques that evaluate risk, we did not exclude specific challenges that might bring into question specific aspects of the SAMA analysis regarding the three types of input we admitted.

Judge Young also recognized that what the Board majority really did was to exclude any meaningful challenge to what is put into the code, and to render Contention 3 meaningless (Id. at 35-36, italics added):

The upshot of this is that, although we admitted the issue of whether the input data regarding meteorological patterns were correct, by now excluding consideration of anything relating to the adequacy of the MACCS2 code as specifically applied with regard to the Pilgrim plants SAMA analysis, the majority in effect excludes any meaningful challenge to what is put into the code relating to meteorological patterns, because such input is effectively predetermined by the current state of the MACCS2 code. Our admission of Contention 3 is thus rendered meaningless with regard to meteorological issues.

The majoritys efforts to render Contention 3 meaningless continued in its order of November 23, 2010. Without mentioning any of the portions of Pilgrim Watchs Hearing Request quoted above, the majority held that Pilgrim Watchs Hearing Request failed not only to raise any issues about the NRCs practice of using mean consequence values in SAMA analyses, resulting in an averaging of potential consequences, but also to raise anything that could bring into question the reasonableness of this NRC practice and affect the Boards findings and conclusions on the meteorological modeling issues. (November Order).

Appendix 1 - Page 7

Once again, and in PWs view correctly, Judge Young disagreed (Order of September 23, 2010:

First, in consulting the Users Guide for the MACCS2 code, I find various references to mean consequence values, mean consequence results, and averaging, some of which appear in discussions of plumes and deposition processes in the ATMOS part of the code. This would seem to support straightaway a conclusion that these usages of the terms are implicitly encompassed within Pilgrim Watchs challenge in Contention 3 to the Gaussian plume model and the modeling processes associated with that - which would lead to a conclusion that the subject at issue was timely raised, at least as to these usages (Sept. Order, at 3)

Entergys arguments and assertions were challenged by Pilgrim Watch in response to Entergys summary disposition motion. Intervenor also challenged Entergys arguments and assertions relating to the use of mean consequence values and averaging. And again, these mean consequence values/averaging issues would also seem to fall under, and be material to, the broad, bottom-line issue the Commission has remanded - namely, whether the Pilgrim SAMA analysis resulted in erroneous conclusions on the SAMAs found cost-beneficial to implement. It seems at a minimum arguable that, much as it raises the conservatisms and sensitivity studies, Entergy has raised these averaging/mean consequence values issues in the manner of raising defenses to Pilgrim Watchs charges in Contention 3, with respect to the effect such averaging has on whether any additional SAMAs might be cost-beneficial to implement.(Sept. Order, at 10)

Appendix 1 - Page 8

C. The Bases of the Majority Decisions and What They Overlooked A. Probabilities and the MACCS2 Code In its October 16, 2006 Order rewriting Contention 3, the Board majority said (emphasis added):

With respect to Entergys characterization of PWs contention as being that risk is to be ignored [in a SAMA analysis], to the extent that anypart of the contentions or basis may be construed as challenging on a generic basis the use of probabilistic techniques that evaluate risk, we find any such portion(s) to be inadmissible. The use of probabilistic risk assessment and modling is obviously accepted and standard practice in SAMA analyses.

The majoritys Order granting Summary Disposition, went even further. Over Judge Youngs dissent, the majority construed the October Order as having eliminated ... issues related to: (1) the adequacy of the computer code (MACCS2) used to perform the SAMA computations; [and]

(2) the use for SAMA analyses of probabilistic (as opposed to deterministic) methodologies.

The majoritys justification for removing all aspects of the MACCS2 code from consideration was again NRC practice: it is necessary for the Staff to take a uniform approach to its review of such analyses by license applicants and for performance of its own analyses, and it would be imprudent for the Staff to do otherwise without sound technical justification.

In relying on practice, the majority overlooked at least two important things.

Appendix 1 - Page 9

First, it failed to appreciate that NRC practice is not NRC regulation- neither probabilistic modeling nor the use of the MACCS2 code are required. Regardless of what the Staffs practice may be, no NRC regulation requires probabilistic modeling or use of the MACCS2 code. In CLI-10-11, the Commission agreed that the Staff used a customarily used code, widely used and accepted as an appropriate tool for conducting SAMA analyses, and that the Gaussian plume model is a fundamental part of the MACCS2 Code. But the Commission was equally clear that those reasons are not a sufficient ground to exclude the codes integral dispersion model from all challenge if adequate support is presented for a contention. (CLI010-11, 17). Indeed, for the Commission to have concluded that they were not sufficient would have been to endorse the view that a desire foruniformity could somehow have made it proper for Entergy (and apparently the NRC Staff) to have designed and used an approach that insured that no significant SAMAs will ever be required.

Second, the majority overlooked that Pilgrim Watchs contention did not challenge anything on a generic basis. Pilgrim Watchs challenge was directed to probability and the MACCS2 Code as they were specifically used by Entergy in its SAMA analyses.

B. Health and Cleanup Costs The majoritys Summary Disposition decision also said that health consequences caused by low doses of radiation had been rejected at the contention admissibility stage because the only economic impact computations it [apparently Pilgrim Watchs Hearing Request] intended to challenge were those relating specifically to loss of economic activity, loss of economic Appendix 1 - Page 10

infrastructure and loss of tourism income (and not the economic costs relating to the effects of low levels of radiation upon human health). However, the majority overlooked PWs Hearing Request explicitly included health costs: The Environmental Report inadequately accounts for off-site health exposure and economic costs in its SAMA analysis of severe accidents. (Hearing Request, 2)

As for costs of clean-up and decontamination, Pilgrim Watchs Hearing Request did say that the MACCS2 model analysis of economic costs include the cost of decontamination, [and ]

the cost of condemnation of property that cannot be decontaminated to a specified level (Hearing Request, 43) But the October Order overlooked that Pilgrim Watch never said that Entergys use of the MACCS2 code properly determined any of these. The October Order simply paraphrased what Pilgrim Watch said (October Order 83), and never mentioned the subject cleanup or decontamination again.

In its October 26 Order, the Board found that Pigrim Watch has provided sufficient alleged facts ... to demonstrate a genuine dispute with the Applicant on the material factual issues of whether in its SAMA analysis the Applicant had adequately taken into account relevant and realistic data with respect to evacuation times....[and] economic consequences of a severe accident in the area (October Order, 103). It went on to say that it thus admitted that part of Contention 23 having to do with the input data for evacuation [and] economic ... information (id.).

Appendix 1 - Page 11

The majoritys decision granting Summary Disposition seemed to echo that the admitted arguments of Pilgrim Watch were that the estimates of economic cost impact failed to preperly account for loss of economic activity, or for loss of economic infrastructure and tourism (SD 13); but it soon became clear that the majoritys view of what economic conseqences, economic activiety and loss of economic infrastructure were included was very limited.

Judge Young recognized the contrary (SD 34):

The term economic consequences is a broad one, which may fairly be said to encompass some of the various tyupes of costs that Intervenors now wish to litigate.

Before deciding these issues, I would at least allow oral arugment on, among other things, issues relating to the scope of the contentions and the types of economic costs that are normally included in SAMA analyses.67 Yet the majority of the Board has since made plain that the only a few economic costs will be considered, e.g., the cost differential caused by the differences between the radiological deposition caused by the sea breeze or hot spot effects from that expected using a straight-line Gausssian plume model, (September 23 Order, Appendix A) and even then apparently only to the extent they might effect the loss of tourism and other business in Plymouth County.68 67 All members of the Board seem to agree that clean-up and decontamination costs are normally included in SAMA analyses.

68 Pilgrim Watchs Hearing Request said that the MACCS2 model used by Entergy did not account for the loss of economic activity in Plymouth County (Hearing Request 44) But Pilgrim Watch never said that the costs of a radiological accident at PNPS woule be limited to Plymouth County. Indeed, the very next paragraph of the Hearing Request specifically referred to the Commonwealth of Massachusetts, Southeastern Massachusetts, and three other counties. The Hearing Request also said that both Providence and Boston are within 45 miles of a severe PNPS accident should one occur (Hearing Request 50)

Appendix 1 - Page 12

Despite the Boards finding that there were material factual issues of whether ... the Applicant had adequately taken into account relevant and realistic data with respect to ...

economic consequences of a severe accident in the area (October Order, 103), the majority has consistently overlooked the largest economic consequence[] of a severe accident, the cost of cleaning up contaminated infrastructure to its pre-accident condition. Yet there can be, and apparently is, no disagreement that one of the types of economic costs that are normally included in SAMA analyses is cleanup/ decontamination costs.

As for input data concerning (1) evacuation times, majority dismissed this part of rewritten contention 3 ever more curtly: Applicants MACCS2 Sensitivity Case 6 ....

convincely demonstrates that the evacuation time assumptions ... cannot make any difference....

(SD 11-12) Overlooked was the fact that Sensitivity Case 6 in fact proves nothing, because is based on the same faulty practices and inputs as Entergy used in the rest of its SAMA analyses.

C. Inputs In addition to excluding the two perhaps most important inputs - source and likelihood of an accident - at the outset, the majoritys Summary Disposition Decision said that the adequacy of the computer code was eliminated at the contention admissibility stage; and on November 23, 2010 the majority held that contention 3 did not include any consideration whatever of what the MACCS2 Code as used by Entergy actually did. Apparently adopting some unknown definition of inputs, the majority, in what is effectively a one paragraph order, said that the Appendix 1 - Page 13

the mean consequene values issue was not timely raised and ... will not be entertained by the Board....

The majority reached this decision only after having ordered the experts for both parties to explain to it, in detail sufficient for understanding of the computer codes process order and mechanics... at what point in the process of SAMA computations perfomred using the MACCS2 code the mean consequences ... are done. In particular, the majority of the Board asked what was done by each of three specific modules - ATOMOS, EARLY and CHRONC. For some reason the majority never mentioned the codes OUTPUT FILE in which it now appears that the averaging and probability that so drastically reduce consequences are actually accomplished.

If, even at this late date, a majority of the Board, including the Judges with technical backgrounds, in found it necessary to ask about ATOMOS, EARLY and CHRONC, but not to ask about the OUTPUT FILE, it hardly was fair for the same majority to use Pilgrim Watchs failure, in May of 2006, to understand exactly what was an input and exactly what was done within the code, as a basis for rejecting Pilgrim Watchs challenge to how Entergy used the code.

Further, both the Commission and Judge Young have recognized that the outcome of this proceeding should not depend on a hypertechnical definition of what is or is not an input. What is important is not what technically is an input, but what the Code does with the information put into it to reach the final estimated consequences on which SAMA determinations are based. In plain language, what the code finally put out.

Appendix 1 - Page 14

Judge Young recognized that the plume model, while not input per se in the technical sense, is implicitly part of what is put in to the MACCS2 code to produce results about meteorologial patterns. (SD Dissent 34). And in CLI 10-11, the Commission was equally clear that the Board decision admitting the contention ... did not make a distinction between specific input date that is entered into the MACCS2 code and the specific models embedded in the code.... Therefore, there easily may be an overlap between arguments challenging the sufficiency of input data used and challenging the model used.... (CLI 10-11, 14-15)

Pilgrim Watch suggests that the Board majority has consistently overlooked the overlap, and drawn distinctions that the Board decision admitting the rewritten Contention 3 did not make, and that the Board majority should not have made thereafter.

As said before, these decisions have denied Pilgrim Watch the opportunity to deal with substance. Equally important, and again as said before, the Boards brochure says that Congress made it possible for the public to get a full and fair hearing on nuclear matters.

Given the cumulative effect of the Boards prior decisions, the Board should consider whether this was possible for Pilgrim Watch.

Appendix 1 - Page 15

APPENDIX 2 Meteorological Modeling: Government and Independent Studies Government and Independent Studies support Petitioners claim that a straight line Gaussian plume model cannot account for the effects of complex terrain on the dispersion of pollutants from a source. Therefore its use is inappropriate for use for Pilgrims SAMA analysis to determine the potential area of impact and deposition in a severe accident. For example:

NRC Since the 1970s, the USNRC has historically documented advanced modeling technique concepts and potential need for multiple meteorological towers appropriately located in offsite communities, especially in coastal site regions. But ignored implementing its own advice.

In 2009, the NRC made a presentation to the National Radiological Emergency Planning Conference;69 and although it was focused on emergency planning, the content is equally relevant to meteorological modeling for consequence analysis. The presentation concluded that the straight-line Gaussian plume models cannot accurately predict dispersion in a complex terrain and are therefore scientifically defective for that purpose [full presentation is available at ML091050226, ML091050257, and ML091050269 (page references used here refer to the portion attached, Part 2, ML091050257). Exhibit 19 Most reactors, if not all, are located in complex terrains, including Pilgrim. In the presentation, NRC said that the most limiting aspect of the basic Gaussian Model, is its inability to evaluate spatial and temporal differences in model inputs [Slide 28]. Spatial refers to the ability to represent impacts on the plume after releases from the site e.g., plume bending to follow a 69 Whats in the Black Box Known as Emergency Dose Assessment (ML091050226), 2. Dispersion (ML091050257), 3. Dose Calculation (ML091050269), 2009 National Radiological Emergency Planning Conference, Stephen F. LaVie

river valley or sea breeze circulation. Temporal refers to the ability of the model to reflect data changes over time, e.g., change in release rate and meteorology [Slide 4].

Because the basic Gaussian model is non-spatial, it cannot account for the effect of terrain on the trajectory of the plume - that is, the plume is assumed to travel in a straight line regardless of the surrounding terrain. Therefore, it cannot, for example, curve a plume around mountains or follow a river valley. NRC 2009 Presentation, Slide 33. Entergy acknowledges that within 50-miles from Pilgrim there are hills and river valleys. Further it cannot account for transport and diffusion in coastal sites subject to the sea breeze. Sea breeze also applies to any other large bodies of water. The sea breeze causes the plume to change direction caused by differences in temperature of the air above the water versus that above the land after sunrise. If the regional wind flow is light, a circulation will be established between the two air masses. At night, the land cools faster, and a reverse circulation (weak) may occur [Slide 43]. Turbulence causes the plume to be drawn to ground level [Slide 44].

The presentation goes on to say that, Additional meteorological towers may be necessary to adequately model sea breeze sites [Slide 40].

Significantly, the NRC 2009 Presentation then discussed the methods of more advanced models that can address terrain impact on plume transport, including models in which emissions from a source are released as a series of puffs, each of which can be carried separately by the wind, (NRC 2009 Presentation Slides 35, 36). This modeling method is similar to CALPUFF.

Licensees are not required, however, to use these models in order to more accurately predict where the plume will travel to base either consequence analyses or protective action recommendations.

The NRC recognized as early as 1977 that complex terrain presented special problems that a model must address if the air dispersion analysis is to be accurate.70 For example: NRC, Regulatory Guide 1.111, Methods for Estimating Atmospheric Transport and Dispersion of Gaseous Effluents in Routine Releases from Light-Water-Cooled Reactors (July 1977) (Draft for 70 Ibid Appendix 2 - Page 2

Comment) says that, Geographic features such as hills, valleys, and large bodies of water greatly influence dispersion and airflow patterns. Surface roughness, including vegetative cover, affects the degree of turbulent mixing. (Emphasis added).

This is not new information; knowledge of the inappropriateness of straight-line Gaussian plume in at complex sites goes back a long way within NRC. For example:

1972: NRC Regulatory Guide 123 (Safety Guide 23) On Site Meteorological Programs 1972, states that, "at some sites, due to complex flow patterns in non-uniform terrain, additional wind and temperature instrumentation and more comprehensive programs may be necessary.

1977: NRC began to question the feasibility of using straight line Gaussian plume models for complex terrain. See U.S.NRC, 1977, Draft for Comment Reg. Guide 1.111 at 1c (pages 1.111-9 to 1.111-10) 1983: In January 1983, NRC Guidance [ NUREG-0737, Supplement 1 Clarification of TMI Action Plan Requirements," January 1983 Regulatory Guide 1.97- Application to Emergency Response Facilities; 6.1 Requirements], suggested that changes in on-site meteorological monitoring systems would be warranted if they have not provided a reliable indication of monitoring conditions that are representative within the 10-mile plume exposure EPZ.

1996: The NRC acknowledged the inadequacy of simple straight-line Gaussian plume models to predict air transport and dispersion of a pollutant released from a source in a complex terrain when it issued RTM-96, Response Technical Manual, which contains simple methods for estimating possible consequences of various radiological accidents. In the glossary of that document, the NRCs definition of Gaussian plume dispersion model states that such models have important limitations, including the inability to deal well with complex terrain.

NUREG/BR-0150, Vol.1 Rev.4, Section Q; ADAMS Accession Number ML062560259, Appendix 2 - Page 3

2004: A NRC research paper, Comparison of Average Transport and Dispersion Among a Gaussian, A Two- Dimensional and a Three-Dimensional Model, Lawrence Livermore National Laboratory, October, 2004 at 2. (Livermore Report) had an important caveat added to the Reports summary about the scientific reliability of the use of a straight-line Gaussian model in complex terrains:

. . . [T]his study was performed in an area with smooth or favorable terrain and persistent winds although with structure in the form of low-level nocturnal jets and severe storms. In regions with complex terrain, particularly if the surface wind direction changes with height, caution should be used.

Livermore Report at 72 (Emphasis added) Exhibit 16 2005: In December, 2005, as part of a cooperative program between the governments of the United States and Russia to improve the safety of nuclear power plants designed and built by the former Soviet Union, the NRC issued a Procedures Guide for a Probabilistic Risk, related to a Russian Nuclear Power Station. The Guide, prepared by the Brookhaven National Laboratory and NRC staff, explained that atmospheric transport of released material is carried out assuming Gaussian plume dispersion, which is generally valid for flat terrain. However, the Guide the caveat that in specific cases of plant location, such as, for example, a mountainous area or a valley, more detailed dispersion models may have to be considered. Kalinin VVER-1000 Nuclear power Station Unit 1 PRA, Procedures Guide for a Probabilistic Risk Assessment, NUREG/CR- 6572, Rev. 1 at 3-114; excerpt attached as Exhibit 8, full report available at http://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr6572. Exhibit 20 2007: NRC revised their Regulatory Guide 1.23, Meteorological Monitoring Programs for Nuclear Power Plants. On page 11, the section entitled Special Considerations for Complex Terrain Sites says that, At some sites, because of complex flow patterns in nonuniform terrain, Appendix 2 - Page 4

additional wind and temperature instrumentation and more comprehensive programs may be necessary. For example, the representation of circulation for a hill-valley complex or a site near a large body of water may need additional measuring points to determine airflow patterns and spatial variations of atmospheric stability. Occasionally, the unique diffusion characteristics of a particular site may also warrant the use of special meteorological instrumentation and/or studies.

The plants operational meteorological monitoring program should provide an adequate basis for atmospheric transport and diffusion estimates within the plume exposure emergency planning zone [i.e., within approximately 16 kilometers (10 miles)].71 These excerpts from Regulatory Guide 1.23 demonstrate that the NRC recognizes there are certain sites, such as those located in coastal areas, like Pilgrim, that multiple meteorological data input sources are needed for appropriate air dispersion modeling. Not simply one or two meteorological towers onsite. Since the straight-line Gaussian plume model is incapable of handling complex flow patterns and meteorological data input from multiple locations, Regulatory Guide 1.23 demonstrates NRCs recognition that it should not be used at any site with complex terrain.

EPA Likewise, EPA recognized the need for complex models. For example: EPAs 2005 Guideline on Air Quality Models says in Section 7.2.8 Inhomogenous Local Winds that, In very rugged hilly or mountainous terrain, along coastlines, or near large land use variations, the characterization of the winds is a balance of various forces, such that the assumptions of steady-state straight line transport both in time and space are inappropriate.

(Fed. Reg., 11/09/05).

71 For example, if the comparison of the primary and supplemental meteorological systems indicates convergence in a lake breeze setting, then a keyhole protective action recommendation (e.g., evacuating a 2-mile radius)

Appendix 2 - Page 5

EPA goes on to say that, In special cases described, refined trajectory air quality models can be applied in a case-by-case basis for air quality estimates for such complex non-steady-state meteorological conditions. This EPA Guideline also references an EPA 2000 report, Meteorological Monitoring Guidance for Regulatory Model Applications, EPA-454/R-99-005, February 2000. Section 3.4 of this Guidance for coastal Locations, discusses the need for multiple inland meteorological monitoring sites, with the monitored parameters dictated by the data input needs of particular air quality models.

72 EPA concludes that a report prepared for NRC provides a detailed discussion of considerations for conducting meteorological measurement programs at coastal sites, reactors on large bodies of water. Most important, EPA's November 2005 Modeling Guideline (Appendix A to Appendix W) lists EPA's "preferred models and the use of straight line Gaussian plume model, called ATMOS, is not listed. Sections 6.1 and 6.2.3 discuss that the Gaussian model is not capable of modeling beyond 50 km (32 miles) and the basis for EPA to recommend CALPUFF, a non - straight line model.73 DOE DOE, too, recognizes the limitations of the straight-line Gaussian plume model. They say for example that Gaussian models are inherently flat-earth models, and perform best over regions of transport where there is minimal variation in terrain. Because of this, there is inherent 72 Raynor, G.S.P. Michael, and S. SethuRaman, 1979, Recommendations for Meteorological Measurement Programs and Atmospheric Diffusion Prediction Methods for Use at Coastal Nuclear Reactor Sites. NUREG/CR-0936, U.S. Nuclear Regulatory Commission, Washington, DC 73 http://www.epa.gov/scram001/guidance/guide/appw_05.pdf Appendix 2 - Page 6

conservatism (and simplicity) if the environs have a significant nearby buildings, tall vegetation, or grade variations not taken into account in the dispersion parameterization.74 National Research Council Tracking and Predicting The Atmospheric Dispersion of Hazardous Material Releases Implications for Homeland Security, Committee on the Atmospheric Dispersion of Hazardous Material Releases Board on Atmospheric Sciences and Climate Division on Earth and Life Studies, National Research Council of the National Academies, 2003. The report discusses how the analytical Gaussian models were used in the 1960s and tested against limited field experiments in flat terrain areas performed in earlier decades.

In the 1970s the US passed the Clean Air Act which required the use of dispersion models to estimate the air quality impacts of emissions sources for comparison to regulatory limits. This resulted in the development and testing of advanced models for applications in complex terrain settings such as in mountainous or coastal areas. In the 1980s, further advances were made with Lagrangian puff models and with Eulerian grid models. Gaussian models moved beyond the simple use of sets of dispersion coefficients to incorporate Monin-Obukhov and other boundary layer similarity measures which are the basis of contemporary EPA models used for both short range and long range transport applications. Helped enormously by advances in computer technologies, in the 1990s, significant advances were made in numerical weather prediction models and also further improve dispersion models through the incorporation of field experiment results and improved boundary layer parameterization. The decade starting with the year 2000 has seen improved resolution of meteorological models such as MM5 and the routine linkage of meteorological models with transport and dispersion models as exemplified by the 74 the MACCS2 Guidance Report June 2004 Final Report, page 3-8:3.2 Phenomenological Regimes of Applicability Appendix 2 - Page 7

real time forecasts of detailed fine grid weather conditions available to the public at Olympic events. Computational Fluid Dynamics (CFD) models which involve very fine grid numerical simulations of turbulence and fluid flow began to see applications in atmospheric dispersion studies. The next decade will see routine application of CFD techniques to complex flows associated with emergency response needs.

The nuclear industry does not show evidence of keeping up with these technological advances. For use in modeling air quality concentrations, the NRC uses straight-line Gaussian dispersion algorithms that date back to the 1960s. Complex flow situations such as those associated with flow around high terrain features or that would incorporate sea breeze circulations are not simulated. For emergency response applications, the NRC does not seem to require any advanced modeling to be installed at nuclear power plants.

Atmospheric Scientists & Meteorologists For over three decades atmospheric scientists and meteorologists have been identifying problems in the use of models similar to ATMOS for such settings. Example: Steven R. Hanna, Gary A. Briggs, Rayford P. Hosker, Jr., National Oceanic and Atmospheric Administration, Atmospheric Turbulence and Diffusion Laboratory, Handbook on Atmospheric Diffusion (1982)).

The inability of a simple Gaussian plume model to accurately predict air transport and dispersion in complex terrains is such a basic flaw that it is discussed in a textbook for a college-level introductory course in environmental science and engineering (Steven R. Hanna, Gary A.

Briggs, Rayford P. Hosker, Jr., National Oceanic and Atmospheric Administration, Atmospheric Turbulence and Diffusion Laboratory, Handbook on Atmospheric Diffusion (1982)). (Chapter 13 Appendix 2 - Page 8

authored by William J. Moroz). In listing the assumptions that are made to develop a simple straight line Gaussian plume model, the textbook warns that:

The equation is to be used over relatively flat, homogeneous terrain. It should not be used routinely in coastal or mountainous areas, in any area where building profiles are highly irregular, or where the plume travels over warm bare soil and then over colder snow or ice covered surfaces Appendix 2 - Page 9

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Appendix 3 - Page 2

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Appendix 3 - Page 3

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Appendix 3 - Page 4

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Appendix 3 - Page 5

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Appendix 3 - Page 6

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APPENDIX 4 A CRITIQUE OF THE RADIOLOGICAL CONSEQUENCE ASSESSMENT CONDUCTED IN SUPPORT OF THE INDIAN POINT SEVERE ACCIDENT MITIGATION ALTERNATIVES ANALYSIS Dr. Edwin S. Lyman Senior Staff Scientist Union of Concerned Scientists Commissioned by Riverkeeper, Inc.

November 2007 In Memoriam: John Gofman Introduction In order to conduct the Severe Accident Mitigation Alternatives (SAMA) analysis for the Environmental Report submitted as part of its application for renewal of the licenses for the Indian Point 2 and 3 reactors, Entergy Nuclear was required to conduct a quantitative assessment of the radiological consequences of severe accidents at the Indian Point nuclear plant. This analysis is needed to calculate the value of the radiological consequences that would be averted if the SAMAs considered by Entergy were implemented. When combined with calculated core damage frequencies from the Indian Point Probabilistic Risk Assessment (PRA), the annual radiological risk to the public from severe accidents can be computed, and the value of the averted risk associated with each SAMA can be compared to the SAMAs cost to evaluate which options, if any, are cost-beneficial.

The calculation of radiological risk to the public is a highly uncertain exercise. The uncertainties are associated both with the values of the severe accident frequencies and the quantitative results of consequence calculations. This report will focus on the consequence assessment.

We find that in three significant respects, Entergys consequence calculations are seriously flawed and do not lead to an assessment of risk to the public that is sufficiently conservative to serve as a reasonable basis for its SAMA analysis:

First, the source term used by Entergy to estimate the consequences of the most severe accidents with early containment failure is based on radionuclide release fractions generated by the MAAP code (a proprietary industry code that has not been validated by NRC),

which are smaller for key radionuclides than the release fractions specified in NRC guidance such as NUREG-1465 and its recent reevaluation for high-burnup fuel.75 The source term used by Entergy results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.

75 L. Soffer, et al. U.S. Nuclear Regulatory Commission, Accident Source Terms for Light-Water Nuclear Power Plants: Final Report, NUREG-1465, February 1995; Energy Research, Inc., Accident Source Terms for Light-Water Nuclear Power Plants: High-Burnup and MOX Fuels: Final Report, ERI/NRC 02-202, November 2002.

Second, Entergy fails to consider the uncertainties in its consequence calculation resulting from meteorological variations by using only mean values for population dose and offsite economic cost estimates.

Third, the population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure underestimates the cost of the health consequences of severe accidents by failing to address the value of lives lost as a result of acute radiation syndrome, in addition to cancer.

As a result of these deficiencies in Entergys analysis, Entergy rejected most SAMAs on the basis that they were not cost-beneficial. In contrast, an analysis based on the more severe consequences that we have calculated would likely conclude that many of these SAMAs in fact would be cost-effective.

We have used the MACCS2 code to conduct an independent evaluation of severe accident consequences for Indian Point Unit 2 for the highest-impact severe accident scenario. Our results indicate that Entergys baseline consequence analysis significantly underestimates (by more than a factor of three) mean population doses and other off-site costs resulting from such an accident. This is partly due to the particular source term used by Entergy, which was derived from calculations using the industry-developed MAAP code, as opposed to our study, which used a source term derived from NRC studies and regulatory guidance. In addition, we find that taking into account reasonable uncertainties associated with meteorological variations (in particular, by considering the 95th percentile consequences over the course of a year rather than the mean consequences) can increase the consequences by at least another factor of three relative to the mean consequences.

In summary, we calculate for the highest-impact severe accident scenario that the 95th percentile equivalent cost of off-site health impacts is more than ten times greater than Entergys estimate of the equivalent cost of off-site health impacts. We also find that the 95th percentile off-site economic impacts for this scenario is over 70 times greater than Entergys estimate of off-site economic impacts for the same scenario, and is over 12 times greater than Entergys estimate of the total cost (off- and on-site) for all severe accident scenarios, the value it used to determine the cost-effectiveness of candidate SAMAs.

We have not carried out a similar analysis of Entergys consequence assessment for IP3, but we would expect to find similar results in that case as well.

Major Flaws in the Entergy SAMA Analysis

1. The source terms used by Entergy to estimate the consequences of severe accidents Radionuclide release fractions generated by the MAAP code, which has not been validated by NRC, are consistently smaller for key radionuclides than the release fractions specified in NUREG-1465 and its recent revision for high-burnup fuel. The source term used by Entergy results in lower consequences than would be obtained from NUREG-1465 release fractions and release durations.

Appendix 4 - Page 2

For example, the IP2 cesium release fraction for the early containment failure, high release (early high) category used by Entergy is 0.229, compared to a total of 0.75 for NUREG-1465.

It has been previously observed that MAAP generates lower release fractions than those derived and used by NRC in studies such as NUREG-1150. A Brookhaven National Laboratory study that independently analyzed the costs and benefits of one SAMA in the license renewal application for the Catawba and McGuire plants noted that the collective dose results reported by the applicant for early failures seemed less by a factor between 3 and 4 than those found for NUREG-1150 early failures for comparable scenarios. The difference in health risk was then traced to differences between [the applicants definitions of the early failure release classes] and the release classes from NUREG-1150 for comparable scenarios the NUREG-1150 release fractions for the important radionuclides are about a factor of 4 higher than the ones used in the Duke PRA. The Duke results were obtained using the Modular Accident Analysis Package (MAAP) code, while the NUREG-1150 results were obtained with the Source Term Code Package [NRCs state-of-the-art methodology for source term analysis at the time of NUREG-1150] and MELCOR. Apparently the differences in the release fractions are primarily attributable to the use of the different codes in the two analyses. 76 Thus the use of source terms generated by MAAP, a proprietary industry code that has not been independently validated by NRC, appears to lead to anomalously low consequences when compared to source terms generated by NRC staff. In fact, NRC has been aware of this discrepancy for at least two decades. In the draft Reactor Risk Reference Document (NUREG-1150, Vol. 1), NRC noted that for the Zion plant (a four-loop PWR quite similar to the Indian Point reactors), that comparisons made between the Source Term Code Package results and MAAP results indicated that the MAAP estimates for environmental release fractions were significantly smaller. It is very difficult to determine the precise source of the differences observed, however, without performing controlled comparisons for identical boundary conditions and input data.77 We are unaware of NRC having performed such comparisons.

In light of this, it is clear that Entergy should not rely on MAAP-generated source terms in its SAMA analysis unless it can provide a technically credible justification for the differences between them and those developed by NRC.

In contrast, we have based our analysis on the more conservative NUREG-1465 source term, which has undergone extensive review by the public, and which is being voluntarily implemented by licensees in other regulatory applications.78 The NUREG-1465 source term was 76 J. Lehner et al., Benefit Cost Analysis of Enhancing Combustible Gas Control Availability at Ice Condenser and Mark III Containment Plants, Final Letter Report, Brookhaven National Laboratory, Upton, NY, December 23, 2002, p. 17. ADAMS Accession Number ML031700011.

77 U.S. NRC, Reactor Risk Reference Document: Main Report, Draft for Comment, NUREG-1150, Volume 1, February 1987, p. 5-14.

78 In adapting NUREG-1465 for this purpose, we have assumed that all radionuclides released to containment are released to the environment in early containment failure scenarios, as explained in this authors attached report, Chernobyl-on-the-Hudson?

Appendix 4 - Page 3

also reviewed by an expert panel in 2002, which concluded that it was generally applicable for high-burnup fuel.79 This and other insights by the panel on the NUREG-1465 source term are being used by the NRC in radiological consequence assessments for the ongoing analysis of nuclear power plant vulnerabilities.80

2. Entergy fails to consider the uncertainties in its consequence calculation resulting from meteorological variations by only using mean values for population dose and offsite economic cost estimates.

Entergy applies an inconsistent approach to its consideration of the uncertainties in its risk calculations. Entergy conducted an uncertainty analysis for its estimate of the internal events core damage frequency (CDF). As a measure of the uncertainty inherent in the internal events CDF as determined by the PRA, Entergy provides the ratio of the CDF at the 95 th percentile confidence level to the mean CDF, which it calculates to be 2.1 for IP2 and 1.4 for IP3 (ER at 4-51). It then bases its SAMA cost-benefit evaluation on the 95th percentile CDF (ER at E.1-31),

rather than the mean CDF. However, Entergy omits consideration of the uncertainties associated with other aspects of its risk calculation. In particular, it does not consider the impact of the uncertainties associated with meteorological variations, which we find to be even greater than the CDF uncertainties reported by Entergy.

The consequence calculation, as carried out by the MACCS2 code, generates a series of results based on random sampling of a years worth of weather data. The code provides a statistical distribution of the results. We find, based on our own MACCS2 calculations, that the ratio of the 95th percentile to the mean of this distribution is typically a factor of 3 to 4 for outcomes such as early fatalities, latent cancer fatalities and off-site economic consequences. Because these ratios are greater than the ones considered in Entergys CDF uncertainty analysis, it is illogical to ignore these uncertainties, as Entergy has done. For consistency, the baseline benefit with uncertainty that Entergy uses in the SAMA cost-benefit evaluation should be based on the 95th percentile of the meteorological distribution in addition to the 95th percentile of the CDF distribution. This would also be consistent with the approach taken in the License Renewal GEIS, which refers repeatedly to the 95th percentile of the risk uncertainty distribution as an appropriate upper confidence bound in order not to underestimate potential future environmental impacts.81

3. The population dose conversion factor of $2000/person-rem used by Entergy to estimate the cost of the health effects generated by radiation exposure is based on a deeply flawed analysis and seriously underestimates the cost of the health consequences of severe accidents.

Entergy underestimates the population-dose related costs of a severe accident by relying inappropriately on a $2000/person-rem conversion factor. Entergys use of the conversion factor 79 J. Schaperow, U.S. NRC, memorandum to F. Eltawila, Radiological Source Terms for High-Burnup and MOX Fuels, December 13, 2002.

80 J. Schaperow (2002), op cit.

81 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol. 1, May 1996, Section 5.3.3.2.1.

Appendix 4 - Page 4

is inappropriate because it (a) does not take into account the significant loss of life associated with early fatalities from acute radiation exposure that could result from some of the severe accident scenarios included in Entergys risk analysis; and (b) underestimates the generation of stochastic health effects by failing to take into account the fact that some members of the public exposed to radiation after a severe accident will receive doses above the threshold level for application of a dose- and dose-rate reduction effectiveness factor (DDREF).

The $2000/person-rem conversion factor is intended to represent the cost associated with the harm caused by radiation exposure with respect to the causation of stochastic health effects, that is, fatal cancers, nonfatal cancers, and hereditary effects.82 The value was derived by NRC staff by dividing the Staffs estimate for the value of a statistical life, $3 million (presumably in 1995 dollars, the year the analysis was published) by a risk coefficient for stochastic health effects from low-level radiation of 7x10-4/person-rem, as recommended in Publication No. 60 of the International Commission on Radiological Protection (ICRP). (This risk coefficient includes nonfatal stochastic health effects in addition to fatal cancers.) But the use of this conversion factor in Entergys SAMA analysis is inappropriate in two key respects. As a result Entergy underestimates the health-related costs associated with severe accidents.

First, the $2000/person-rem conversion factor is specifically intended to represent only stochastic health effects (e.g. cancer), and not deterministic health effects including early fatalities which could result from very high doses to particular individuals.83 However, for some of the severe accident scenarios evaluated by Entergy at IP, we find that large numbers of early fatalities (hundreds to thousands) could occur, representing a significant fraction of the total number of projected fatalities, both early and latent. This is consistent with the findings of the Generic Environmental Impact Statement for License Renewal of Nuclear Plants (NUREG-1437).84 Therefore, it is inappropriate to use a conversion factor that does not include deterministic effects. According to NRCs guidance, the NRC believes that regulatory issues involving deterministic effects and/or early fatalities would be very rare, and can be addressed on a case-specific basis, as the need arises.85 Based on our estimate of the potential number of early fatalities resulting from a severe accident at Indian Point, this is certainly a case where this need exists.

Second, the $2000/person-rem factor, as derived by NRC, also underestimates the total cost of the latent cancer fatalities that would result from a given population dose because it assumes that all exposed persons receive dose commitments below the threshold at which the dose and dose-rate reduction factor (DDREF) (typically a factor of 2) should be applied. However, for certain severe accident scenarios at IP evaluated by Entergy, we calculate that considerable numbers of people would receive doses high enough so that the DDREF should not be applied.86 This means, essentially, that for those individuals, a one-rem dose would be worth more because it would be more effective at cancer induction than for individuals receiving doses below the threshold. To illustrate, if a group of 1000 people receive doses of 30 rem each over a short 82 U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy, NUREG-1530, 1995, p. 12.

83 U.S. NRC (1995), op cit., p. 1.

84 U.S. NRC, Generic Environmental Impact Statement for License Renewal of Nuclear Plants, NUREG-1437, Vol.

1, May 1996, Table 5.5.

85 U.S. NRC, Reassessment of NRCs Dollar Per Person-Rem Conversion Factor Policy (1995), op cit., p. 13.

86 The default value of the DDREF threshold is 20 rem in the MACCS2 code input.

Appendix 4 - Page 5

period of time (population dose 30,000 person-rem), 30 latent cancer fatalities would be expected, associated with a cost of $90 million, using NRCs estimate of $3 million per statistical life and a cancer risk coefficient of 1x10-3/person-rem. If a group of 100,000 people received doses of 0.3 rem each (also a population dose of 30,000 person-rem), a DDREF of 2 would be applied, and only 15 latent cancer fatalities would be expected, at a cost of $45 million.

Thus a single cost conversion factor, based on a DDREF of 2, is not appropriate when some members of an exposed population receive doses for which a DDREF would not be applied.

A better way to evaluate the cost equivalent of the health consequences resulting from a severe accident is simply to sum the total number of early fatalities and latent cancer fatalities, as computed by the MACCS2 code, and multiply by the $3 million figure. Again, we do not believe it is reasonable to distinguish between the loss of a statistical life and the loss of a deterministic life when calculating the cost of health effects.

Results of IP2 Consequence Assessment We have performed our own calculation of the consequences of a severe accident at IP2, using the MACCS2 code. The model is largely based on the one used in this authors 2004 study Chernobyl-on-the-Hudson? (copy attached), to which the reader is referred for all details. The model was revised, based on Entergys ER, to incorporate (1) the core inventory specified in Table E.1-13, and (2) the expected population in 2034. To calculate the latter, we scaled the output of the SECPOP2000 code by a factor of 1.145. This normalized the total population within 50 miles to 19.2 million, to correspond to Entergys projection of the total population within 50 miles of the IP site in 2034.87 We use a finer site data input grid than Entergy does, with 21 intervals between 0 and 50 miles, compared to the five intervals used by Entergy. This allows for more accurate modeling of the dose and economic consequences.

The model we use is different compared to the one used by Entergy in a number of notable respects. First, we use a source term derived from NUREG-1465, as discussed previously, with regard to both the magnitude and timing of radionuclide releases. We use a two-plume model based on the approach of NUREG/CR-629588 that more realistically models the releases that would occur in an early containment failure scenario.89 We also assume that the entire population of the 10-mile EPZ evacuates as determined by the evacuation time estimates provided by KLD Associates in 2004 (ER reference E.1-21), whereas Entergy assumes no 87 We have adjusted the SECPOP2000 input and output files to correct the errors disclosed in the August 2007 memo to SECPOP2000 users from Sandia National Laboratories and verified that the county data file is being read correctly. However, according to a personal communication from Nathan Bixler of Sandia National Laboratories, there is another potential problem with SECPOP2000 that was not mentioned in the August 2007 memo. When this problem is rectified, we will amend our calculations accordingly.

88 R. Davis, A. Hanson, V. Mubayi and H. Nourbakhsh, Reassessment of Selected Factors Affecting Siting of Nuclear Power Plants, NUREG/CR-6295, US Nuclear Regulatory Commission, 1997, p. 3-30.

89 Entergys model assumes a single plume with a duration of over 22 hours2.546296e-4 days <br />0.00611 hours <br />3.637566e-5 weeks <br />8.371e-6 months <br />, which is longer than for any other early containment failure source term we have encountered. We note that when we ran the MACCS2 code using Entergys source term for the early, high scenario, the MACCS2 output file contained the following warning:

The total release duration exceeds 20 hours2.314815e-4 days <br />0.00556 hours <br />3.306878e-5 weeks <br />7.61e-6 months <br />. This may cause erroneous results to be produced. Thus it is unclear to us that Entergys results for this case are even valid.

Appendix 4 - Page 6

evacuation at all. (It is not clear whether Entergy assumes sheltering or normal activity for the inhabitants of the EPZ.) We use the evacuation scenario because we have found that for the source term that we utilize, the all-sheltering scenario actually results in a smaller number of latent cancer fatalities than in an evacuation scenario, in part because more individuals succumb to acute radiation syndrome in the former scenario (and thus do not get cancer).90 In our model, we utilize the option in MACCS2 to calculate consequences for an entire years worth of weather conditions, starting on each hour of the year. Each of these 8760 results is a weighted sum of results evaluated for each of the 16 compass directions, with the weighting determined by the Indian Point site wind rose. The accident is assumed to occur randomly at any time during the year. (Entergy does not make clear in the ER whether it calculated as large a number of outcomes or used the random sampling function of MACCS2, which selects only a few hundred hours during the year for evaluation.) We use the meteorological data file originally compiled for the Indian Point site for the CRAC2 study, which is publicly available.

Our results for off-site health consequences within a 50-mile radius of IP for the early high release category with full evacuation, compared to Entergys, are presented in Table I. The values for latent cancer fatalities as a result of early exposures (e.g. during the 1-week emergency phase) are reported separately from those resulting from chronic exposures (those resulting from the intermediate and long-term phases, as defined by MACCS2). The results for chronic exposures depend in on the parameters for long-term protective actions and have greater uncertainties than the results for early exposures. We assume, for purposes of comparison, that Entergys result for total population dose is the sum of both early and chronic exposures.

TABLE I Health Impacts of Early, High Release This study Environmental Report (Table E.1-14)

Mean early fatalities 860 Not reported Mean latent cancer fatalities 37,600 Not reported from early exposure Mean latent cancer fatalities 950 Not reported from chronic exposure Mean latent cancer fatalities 38,500 Not reported (total)

Mean population dose 4.97 x105 1.58 x105 (person-Sv) 95th percentile early fatalities 4,440 Not reported 95th percentile latent cancer 129,000 Not reported 90 We find for our source term that the evacuation scenario actually results in a slightly greater number of combined early and latent fatalities. This appears to be an artifact of the particular population data file used rather than a reflection of a general principle.

Appendix 4 - Page 7

fatalities from early exposure 95th percentile latent cancer 3,450 Not reported fatalities from chronic exposure 95th percentile latent cancer 130,000 Not reported fatalities (total) 95th percentile population 1.64x106 Not reported dose from early and chronic exposures (person-Sv)

Our mean population dose result is over three times greater than that calculated by Entergy. To try to understand the reason for this difference, we reran the calculation with Entergys MAAP-derived source term. For the no-evacuation (all-sheltering) scenario, we found a 45% reduction in population dose to 276,000 person-rem, which is still nearly twice Entergys result of 158,000 person-rem. Without access to all the MACCS2 input files used by Entergy in its calculation, we cannot identify the other factors that may account for the remainder of the difference. But it is clear that the choice of source terms alone can have a significant (at least two-fold) impact on the population dose results.

We can also see from Table I that the 95th percentile population dose is over three times the mean population dose, and the 95th percentile number of early fatalities is over five times the mean value. This demonstrates that Entergys focus on the mean consequences significantly underestimates the potential consequences of accidents occurring during less frequent but not uncommon meteorological conditions.

As discussed above, we maintain that the mean population dose is not an accurate representation of the total cost detriment associated with lives lost, because it does not include the costs of early fatalities, which as one can see from Table I, are substantial. In addition, as shown above, use of population dose as a surrogate for latent cancer fatalities is not appropriate because the total population dose does not account for the non-linear relationship between population dose and total number of latent cancer fatalities when the range of individual doses include both doses above and below the DDREF threshold. To remedy these problems, the total number of early fatalities and latent fatalities should be summed and the total multiplied by the monetary equivalent of lives lost, which is $3 million in NRC guidance.

From this data, we obtain an equivalent cost, at $3 million per life lost, of $118 billion for the mean case. For the 95th percentile case, the equivalent cost of the latent cancer fatalities alone would be $390 billion.91 This should be compared to the result if only the equivalent cost of the population dose, using the $2000/person-rem conversion factor, were considered: $99.8 billion and $328 billion for the mean and 95th percentile, respectively.

However, in either case these results are far greater than Entergys calculated equivalent cost of

$31.6 billion. From the results presented in Table II, we see that our result for the cost detriment associated with loss of life from the early, high release is approximately 3.7 times greater than Entergys result for the mean case, and over 12 times greater for the 95th percentile case.

91 The MACCS2 code does not have an option for calculating the sum of early and latent cancer fatalities, and therefore does not report the 95th percentile value of this sum.

Appendix 4 - Page 8

According to Entergys calculations, this scenario is the largest single contributor (47%) to the overall population dose risk.

TABLE II Equivalent Cost of Off-Site Health Impacts of Early, High Release This study Environmental Report Mean off-site health $118 billion $31.6 billion impacts equivalent cost (early and latent cancer fatalities) 95th percentile health $390 billion Not reported impacts equivalent cost (latent fatalities only)

We have also obtained results for the off-site economic costs from the early, high release. We generally follow the methodology of Beyea, Lyman and von Hippel for our calculation of economic impacts.92 The model utilizes the results of a 1996 Sandia National Laboratories report that estimates radiological decontamination costs for mixed-use urban areas.93 We refer interested readers to these two references for information on the limitations and assumptions of the model.

Our results, as calculated by SECPOP2000 and the MACCS2 code, are also considerably higher than Entergys results. In Table II, the MACCS2 results, which were obtained from 1996 and 1997 data, were converted to 2005 dollars by multiplying by an inflation factor of 1.2.

TABLE III Off-Site Economic Impacts of Early, High Release This study Environmental Report Mean off-site economic $816 billion $34.2 billion impacts 95th percentile off-site $2.48 trillion Not reported economic impacts By using the standard discount factor applied by Entergy (e.g. see page 4-53 of the ER),

Entergys frequency result, and neglecting the risk contributions of all other scenarios, we find a mean monetary equivalent present dollar value for the early, high release of $825,514, and a 95th percentile present dollar value (for latent cancers alone) of $2.73 million.

92 J. Beyea, E. Lyman and F. von Hippel, Damages from a Major Release of 137Cs into the Atmosphere of he United States, Science and Global Security 12 (2004) 1-12.

93 D. Chanin and W. Murfin, Site Restoration: Estimates of Attributable Costs From Plutonium Dispersal Accidents, SND96-0057, Sandia National Laboratories, 1996.

Appendix 4 - Page 9

Again using the same discount factor, we find a mean present dollar value of the off-site economic consequences of the early, high release of $5.71 million, and a 95th percentile present dollar value of $17.3 million.

Adding the equivalent cost of off-site health impacts to the off-site economic cost, we find for the early, high release alone the mean total cost equivalent present dollar value is $6.54 million. (We have not made our own estimates of on-site dose and on-site economic costs.)

This is nearly seven times greater than Entergys estimate of the sum of these two costs for all release categories.

For the 95th percentile, the present dollar value off-site economic cost for the early, high release alone is over 72 times Entergys mean estimate for the same release and over 12 times Entergys mean estimate for all costs (off- and on-site) and all release categories of $1.34 million.

These results are summarized in Table IV.

TABLE IV Present Dollar Value Equivalent of Early, High Release Consequences This study Environmental Report Mean present dollar value $6.54 million $460,334 of total off-site costs 95th percentile present $2.73 million Not reported dollar value equivalent of off-site fatalities (latent cancers only) 95th percentile present $17.3 million Not reported dollar value of off-site economic impacts We have not carried out a review of Entergys calculations for the other release categories that contribute to the Indian Point 2 severe accident risk. However, we would expect similar findings to those we have obtained in our review of the early, high release. In our judgment, many SAMA candidates would become cost-effective based on the difference in mean consequences alone, and many more rejected SAMA candidates would become cost-effective when the 95th percentile case is considered. If we were to extrapolate our result for the 95th percentile off-site costs of the early,high release to all release categories, leading to a nearly twenty-fold increase in total economic cost compared to Entergys estimate, even the most costly SAMAs, such as the Phase II SAMA #015, Strengthen Containment, could well become cost-effective.

We note that this conclusion would be further strengthened if we incorporated the increased frequency of the early, high release category estimated by Dr. Gordon Thompson in his Appendix 4 - Page 10

November 2007 report Risk-Related Impacts from Continued Operation of the Indian Point Nuclear Power Plant.

Based on these findings, we believe that Entergy has grossly underestimated the off-site costs of severe accidents at Indian Point, and should revise its estimates using more credible and conservative source terms. It should also consider the 95th percentile consequence values of the distribution with respect to weather variations and use these values as the upper confidence bound in carrying out the SAMA cost-benefit evaluation for Indian Point. Entergy should use a methodology for calculating the cost equivalent of off-site health impacts that properly accounts for individuals who receive acute radiation doses above the threshold for early fatalities, and for those who receive chronic doses above the threshold for application of a DDREF.

Analysis Our estimate of the mean off-site economic consequences of the early, high release is approximately 20 times Entergys estimate. We have identified some of the reasons for the difference, but not all of them. The difference in source terms does not appear to be as great a factor as for the calculation of health impacts. The differences in the choices of economic and other parameters between Entergys model and ours also plays a role. For instance, we use decontamination cost estimates obtained from a 1996 Sandia study that are significantly higher than those used by Entergy, which uses values based on the default parameters in the MACCS2 code. However, even after running the code with Entergys source term and economic parameters, we still find economic consequences at least an order of magnitude greater than Entergys. The results are also dependent on factors such as the dose criteria for triggering interdiction and condemnation actions. We use a more restrictive model than the default MACCS2 model in order to more closely approximate the EPA Protective Action Guides.94 In 94 U.S. Environmental Protection Agency, Manual of Protective Action Guides and Protective Actions for Nuclear Incidents, Washington, DC, 1991.

Appendix 4 - Page 11

any event, it is clear that reasonable differences in parameter choices can lead to order-of-magnitude differences in consequences in the MACCS2 long-term economic consequences model, and that Entergy has not done due diligence in exploring the sensitivity of their results to parameter variations.

Appendix 4 - Page 12

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APPENDIX 6 Roo.n E. u- 1'bD, 1'£, Coc.:ulIm

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mi1l1i\.. _ ~ t!m-. IS <mUgh 'l""'5ci1J' "'<_'~ coot. , stmW.. H . fim1>oct ofpopuldioo. d<nst!y. 111< 5-:-'1. >IUd)- (Cbmm. 1996) lID',dtd . &i:Ij' drbikd~' inwbXh to .._ """'. far "".nm .... 11>< Ol.wl =lin thot<..,., out of1l>< <lfm ... """'" m T. b!< 1 T. b!< I. liban Area (lJ.I.I J"f'OO"1:m") R<m<dimoo eo." far Y... 2001 in t\t:km' ~"'" ~G((WJin. 1996). eo... .......tundod far ~ _ of1l>< "'..wJ .... m thot lmd _ tI. ... Sbat Appendix 6 - Page 3 h< mod. by ~!hoI lop<< p<¥lbo"" d=n}'~!hoI 1h<r< ... """" ""~Ilq ..... P'" km' .... 1ha! obt <<lOb"""'" m T. bi< I .., bos<d "" mdi,'iola] ~ A> . =ult. IWInpl;lIIl obt ""-aI coo.. b)'

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_,latio", in obt Am< ..... In _""- """'*l&Ut1'W opo<<" lilol;' to <>pUId " nh _dati"" dtnstty, obt '"""*"""'w ,-.ru.. ,,'WId also h< .qu.1<<I m. <IIIlibr 1IlOm<f. Th<s< ... _ ........... _ _ .... 1>l<fuI OIlly for mI<f ofmaptud..-sIimat<s Th< =uIr ofmch odjI-." .b.",," in l . bi< n. T. N< n . E.mmattd ~ Com fa-l'<w York C"jfy ~ Lmd u .. DIsInbllloo .... ~"" D<miIy 111<~. US<<! ., pro<bc< T. N< n <011 h< usN to d<rn~ rmI<<Iimom cost ...,..,.... for ocbo< _dati"" d=n}........ ..""." by obt ~ P"""" m Fi~ I. FipJr< I .bo <<<Dlm r<mt<Iian"" cost dm. from obt OO<I({< _ di""",oN . ""'~ 111< ~ m FipJr< I is ~t< ~ \u IS ~ ko)'<<I fa- """" I<kIitiao <Wuy R<d m.. and .yon... .,. for ta, >10), <nng< fa- (I < Of, < IO~ and _ fa- (I < Of, < I). ~ .yon... .,. for 0SIim0.... rhar "1mSp<<i60 . bout obt Of, obt)'"I¥;" " , bur obt y.ru..could h< .. ~ .. 'j(I. F~ I .."".~ . fur ml<U1f of,~* II! obt <<lOb ostimat<<l by obt ,~ _ _ .ml ..u= "",.I<<I m rlIn ",..".-n. Th< _ "r.,gU lin<> p<nriI<<I II! 00 obt plot D. III!<nd<d to SI>gE<SI bm\' ' <<lOb IlllgU '"Uy ,.."h p<¥lbuoo dmsifJ' and <I<p<< of (OOImnn. o",,- 111< 1m<> or< . rfttOOIbl< ~ ofDl<h ofobt mformo.ti",,- \u ><mt ""'" poizn cIrI",,, ..hu",,.II;' and I<ilI h< di""",o<<I_. Th< ..." , "" di", panI. rhar or< ,,~U . ""'~ obt~... ... from obt ~ b)" Rrithm:fh and ... bos<d ""......,.... ofc"" dm,'Od ",<10m", and =0-< C- ~ "" 16 acl< 'WTC .... m "",. YOlk CifJ _ WI I. Th< cost to !qUe< obt fxiIiI><> is _0<<1 ., h< "" mI<f of .... gm:tud. Ialgoc C- .."".'" "" "" plo<) Appendix 6 - Page 4 I ~M J!'.""_ ! " ...*r:~ ~~;\.~.~~......................... ...... ' _ _ _w ~ .~-- - .-~ -.~ a i Sl~

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Appendix 6 - Page 5 SiI>:. tho osbmat<d ""'" ",as \.....:I "" tho .... of tho 1!.'l'C silO. rut tho actuoIoxpondi .... <<l'I~ """"'" mao>. 0\. . tho surrom<linfo; .,... .mol il>:hDd ><Il<m< ..,.,....-bal t..,"OOd " hat ,,'WId bo 0lIj><<.10d In ~ 10 III RDD~.... tho actuoI =t'1m' rould bo "'~ by W% 1 06O"/~ Tho ~ _ .. bo.,., tbo tu'.~ ' "1'<=11 tho 0S!imat.. thaI " ... _ miDI! RADTItA..'1 I in tho ""d 1910', ,,,th an ~~ . !>b=.., t b o . . - ... tbo oIdon m:I ""'" """'" 10 ~- ISSOa2I<d " l1h . .~ tho """ dol!ator llatisli< for t¢tml <00I:I. Tho RADTItA.."< 6 . . - (pIp!< d i _ ) Ibo ... boIa\O' tbo 1r<Dd 1m.. \u ""' .. proooom<od anoff<<f .. ",th RADTItA.."< 6 (WunlOO7). N<JOt that tho RADTItA.'16 \..ru.. (>qIIIl<I with C<rnf crossos) 1\1_ IIl<n dosol)' with tho oobor <>1I.mI ... m:I tho _ lin<I n..1r<Dd 1m.. &\""tbo ""'" \..ru.. ~b)' tho Sudio 101;' (Cbomn 19I16), btc...., of tbo a.tUl im"k..d in tho IIDtW.-..... m:I tho oblitj'lO""ojoct tho""" ., orbo< p<¥>laUorJ do=Jtin m:l1ml ""' .... ~ CO'iCLUSIO'i Tho lil<!ibood of . '1lut)- Bomb" III1><k in tbo US or oI....b!R .. ~n ~bt I<U<e> IIJU<'I (0. ~ , Kor.m. 20(1) that tho~.ol <~ ofouch ... . ttrl ... m lihly '" bo lifo t1R. ~ m:I that tho ~_ mortol ~ J> 10 """"" oxposod 10 bb" fr<m tbo ""' (ISnrrin~ thaI IS~' _ of ,¥"Ooo,j. Ilo-wo\..", tho oxponditt=< D<<<Iod 10 1<<"- from 1 ~ -1l<III!! "" ROO 1)l'" cr.>oo, .. drptYd in Fipn I, ... lihI;' 10 bo ~C;UJI from tho l1IJXp.inl of~ ,,-.iloblo 10 loc.ol or ..... ~,,_. E\= 1 ""' that <<Umnn_ "" .... of. IN-hIDbod 0=0 (. _ _ kilornt!e-) 10 . 1.-.01 that ~_ J<m<didioo." lik<ly 10 Jl"O'b:. """"rmgJIIl from ilOM ., iJOOM or_o a.p.min;o; "" ,""",,1)' of~"",,- p<¥llIo"" domJl),. mol drbih of lml US< in tho ..... A> . ,.,w,."" in¥>- " ~ ~'" 00 tho d f "",,",,,' ~ ,*"" 1>>' tbo D<partm!m of~' , NIrlo .. RrguIaIOr;' CQmO'u u"" m:I tho o.p.nm.u of !bn<lm:I Sorunt)-IO""",-.a.~* fa-1Iooioootn~ IIlI1<nab utod m tho ~ m:I " " " ' _ - . .milO d<IOct, .. fi>l!J' .. "","bIo, tnffio in po-.l dinj' _ mI1<nIl. " tthm mol 011 tho bord<noftboUSA Appendix 6 - Page 6 (CIwIi.D, ~ : a..mn. Dmdl lDd!>lImn l!.'II1<' B., ~1< R<sI<nIioo:1: F<IpNIj"" of Anribwbl< eo... han Pl\roomm-o;,p.n.a! A=:d!nt.". s-JiI N1t>OnaI La-..., Rq>OO SA.>,U SI6-09~7, !>b.)' 1996 (CIu .... !,;, 100j): Cbanock. T. " al "co)..l)(): SoftIO~ for &~tbt ~ of o.coo""'N""" Opbom", "mooal ~1I1"rrucu"" Board. Rq>OO t-"RPB-\\'43. May 2003) (DHS, ! 007): o.p.nm.nt of~W:d s.c..iIy. Pr..,.,-<<b= Dir<<1<no.; "Pr0W!J\~ Ar.1ioo. GwIrs fa- ~ DIsp<naI ~= (ROO) m ~,..dNucl<or ~><< (ISD)". F<<I<nI~. Vol 11, No. I, lamJOr}' 3. :>006, pl14-lS16 (lWoip4'. 199! ~ . K.mpt, F m~. K. S.. "RADTIlA..'1 4: VoIImIo 4 Progt ......... . M.....II". s.m.. N.11cm.l LaOOraoont., Rq>OO SA.>,US9-1J1O, 1u!j* 1992. (Un .... 1005): Ku:am. AnoUw, "~ T<nOC\= " Hanan ml ENIogtcal Risk Ao.....,...., \'01.. 11, 2001, W . 501 _513 C'tU ...,.,. 199 1 ) : ~ , K S. .md iUDipo. F., "RAD"ITAN 4: VoIImIo 3 U... Gwdt", sam. NlIlcm.l Lata-..., Rq>oo SA.>'"D89_1J1O, 1>W1r}' 19')2. C'tU ...,.,. 1993): ~ , K S. .md K>Dipo. F.. "IlAIJ"ITAN 4: VoIImIo ! T<<1DcaI M.....II". sam. N.11cm.l Lata-..., Rq>oo SA.>,US9_1J1O, ~ 1993 (<hbono. : 007): Pri,~ ( _ _ ....... "" ,,,Ih~. o.boo1. SKI. ",b",~ to...,..,.~ clNmlp <OSI ........ ~ bJ*llAD"ffiAN\l. Octobto 2007 (P....... : (07): ~ 1. P., m I!.'.u.." R , "An Ero!xcm< MOOtI of> Rodioo<ti,,, M...ri1h r~""" Mia... for tbt IlAD"ffiANRisk Ao......-eoa.", Pr~ of W_ M.....~ 2001, F<<>ruar;' !7-Morch 3, 1001, T"""",- AZ (SAt-"D200l--3!102q C>"RC, 1~ 7) : "fiml Emir",""",,,,1 St....,..", "" tbt T~", ofR1oiOO<",,, !.-11Uriah by An m 0Ib<r !dod<s", )"'UREG-OI lIl, lJS Nud... ~ Caozm"""", I!.'~ OC, o.o..m..- 1971 (Rft, . ... do, 100,."): Rr><ba:fh. B., " II. '"E<<lmo:Ic ~ of. RAD!:-O-UC Anad:: ~ s..m.rn. SigniOOld;' Afl'<<1 Cosr", ~ ofl!.'~ T<>g<Ilm- R&D ~ m ~Imd S<nrit;., _<111. Mt\. Apil2003 (!'acID< _ , . , . NIIimaI Labontory. I'SNL.SA-I ~ l S6) (\\111i""""". 1006): \\,Ib..,..,.., s.m..Ili , "Fi,,, I!.'I:)~ to ~ tho~" VU>. of. US 001l1f Amou:t. 1790 _!OO~ : !>W"""'lI!.'octhC<m. :>006 I'lIgrIIwww ~w!l!!!!'!!1!""'", "" . Appendix 6 - Page 7