ML071930137

Biomass Feedstock Availability in the United States: 1999 State Level Analysis

ML071930137
Person / Time
Site:	Oyster Creek
Issue date:	07/02/2007
From:	Becker D, Graham R, Perlack R, Ray D, Slinsky S, Turhollow A, Ugarte D, Mary Walsh Oak Ridge, Science Applications International Corp (SAIC), Univ of Tennessee, US Dept of Energy (DOE)
To:	Office of Nuclear Reactor Regulation
Wrona D J, NRR/DLR - 415-2292
Shared Package
ML071920528	List: ML071920527 ML071920531 ML071920533 ML071920535 ML071920536 ML071920537 ML071930092 ML071930099 ML071930104 ML071930110 ML071930111 ML071930113 ML071930125 ML071930129 ML071930135 ML071930137
References
Download: ML071930137 (16)

Text

{{#Wiki_filter:. Bioniass Feedstock Availability in the United States: 1999 State Level Analysis Page I of 16 Biomass Feedstock Availability in the United States: 1999 State Level Analysis Marie E. Walsha, Robert L. Perlacka, Anthony Turhollowa, Daniel de la Torre Ugarteb, Denny A. Beckerc, Robin L. Grahama, Stephen E. Slinskyb, and Daryll E. Rayb aOak Ridge National Laboratory, Oak Ridge, TN 3783 1-6205 bUniversity of Tennessee, Knoxville, TN 37901-1071 CScience Applications International Corporation, Oak Ridge, TN 37830 April 30, 1999, Updated January, 2000

1. Introduction Interest in using biomass feedstocks to produce power, liquid fuels, and chemicals in the U.S. is increasing. Central to determining the potential for these industries to develop is an understanding of the location, quantities, and prices of biomass resources. This paper describes the methodology used to estimate biomass quantities and prices for each state in the continental U.S. An ExcelTM spreadsheet contains estimates of biomass quantities potentially available in five categories: mill wastes, urban wastes, forest residues, agricultural residues and energy crops. Availabilities are sorted by anticipated delivered price. A presentation that explains how this information was used to support the goal of increasing biobased products and bioenergy 3 times by 2010 expressed in Executive Order 13 134 of August 12, 1999 is also available.

II. Biomass Feedstock Availability For the purpose of this analysis, biomass feedstocks are classified into five general categories: forest residues, mill residues, agricultural residues, urban wood wastes, and dedicated energy crops. Forestry is a major industry in the United States encompassing nearly 559 million acres in publicly and privately held forest lands in the continental U.S. (USDA, 1997). Nearly 16 million cubic feet of roundwood are harvested and processed annually to produce sawlogs, paper, veneers, composites and other fiber products (USDA, 1998a). The extensive forest acreage and roundwood harvest generate logging residues and provide the potential to harvest pon-merchantable wood for energy. Processing of the wood into fiber products creates substantial quantities of mill residues that could potentially be used for energy. Agriculture is another major industry in the United States. Approximately 337 million acres of cropland are currently in agricultural production (USDA, 1997). Following the harvest of many of the traditional agricultural crops, residues (crop stalks) are left in the field. A portion of these residues could potentially be collected and used for energy. Alternatively, crop acres could be used to grow dedicated energy crops. A final category of biomass feedstocks includes urban wood wastes. These wastes include yard trimmings and other wood materials that are generally disposed of in municipal solid waste (MSW) and construction/demolition (C/D) landfills. Following is a description of the potential availability of these biomass feedstocks in the United States. A. Forest Residues Forest wood residues can be grouped into the following categories--logging residues; rough, rotten, and salvable dead wood; excess saplings; and small pole trees-U}. The forest wood residue supplies that could potentially be available for energy use in the U.S. are estimated using an updated version of a model originally developed by McQuillan et al. (1984). The McQuillan model estimates the total quantities of forest wood residues that can be recovered by first classifying the total forest inventory by the above wood categories (for both softwood and hardwood), and by volume, haul distances, and equipment operability constraints. This total inventory is then revised downward to reflect the quantities that can be recovered in each class due to constraints on equipment retrieval efficiencies, road access to a site, and impact of site http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

Biomoass Feedstock Availability in the United States: 1999 State Level Analysis Page 2 of 16 slope on harvest equipment choice-U!. The costs of obtaining the recoverable forest wood residues are estimated for each category. Prices include collection, harvesting, chipping, loading, hauling, and unloading costs, a stumpage fee, and a return for profit and risk. Prices are in 1995 dollars. For the purposes of this analysis, we have included only logging residues and rough, rotten, and salvable dead wood quantities. The potential annual forest waste residues available by state for three price scenarios are presented in Table 1. Quantities are cumulative quantities at each price (i.e., quantities at $50/dt include all quantities available at $40/dt plus quantities available between $40 and $50/dt). Polewood, which represent the growing stock of merchantable trees, has not been included in the analysis due to the fact that it could potentially be left to grow and used for higher value fiber products. It is doubtful that these trees will be harvested for energy use. However, if harvested, they could add another 17 million dry tons at less than $30/dt delivered; 37.7 million dry tons at less than $40 delivered; and 65 million dry tons at less than $50/dt delivered. For a more detailed explanation of the methodology used to estimate the forest wood residue quantities and prices, see Walsh et al, 1998. Table 1: Estimated Annual Cumulative Forest Residues Quantities (dry tons), by Delivered Price and State

                       <$30/dry ton delivered     < $40/dry ton delivered j[< $50/dry ton delivered
]Alabama             111009000                    1475000                   1899000 1Arizona             11134000                   1200000                     261400 Arkansas              928000                     1352000                   1737800

[California 11231000. 1819000 2364400 Colorado 11373000 1554000 720300 Connecticut 11109000 1159000 204100 Delaware 1126000 137000 48400 IFlorida 1515000 I755000 11[9757ooo IGeorgia 111041000 I1525000 [1967800 [Idaho ..- - 11605000 . . 1902000 F[179500 Ilinois 11228000 1330000 423300 Indiana 1253000 1367000 -- 1470100 IIowa 1172000 I105000 F135000 Kansas 47000 68000 88100 Kentucky 475000 690000 883500 Louisiana o[1275000 872000 1[1641800 Maine - I806000 1[182000 1[529100 Maryland 11189000 I[273000 135i200 Massachuset 196000 [284000 366200 IMichigan I710000 111034000 111327900 Minnesota 468000 682000 874900 Mississippi [1946000 11380000 111774600 i oI 1ii II http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 3 of 16 Missouri 505000 733000 938700 1Montana 11676000 11007000 1-1316700 Nebraska 19000 27000 34400 1Nevada 81F00 000 001014400 INew Hampshire J29900 1438000 564400 INew Jersey 70000 102000 I1130700 INew Mexico 125000 I 185000 11241900 New York 933000 1360000 l746400 North Carolina 1[1068000 1557000 2004900 North Dakota 1000 117000 1121700 200 2ohi3 1335000 430100 Oklahoma 156000 228000 292200 1299000 11928000 2515900 IPennsylvania 9400 1173000 1377000 Rhode Island 200 27000 35900 SouthCarolna 13000 1[898000 11158400 South Dakota 133000 1149000 164300 Tennessee 930000 F351000 1 1[732600 iTexas 557000814000 ][lo5o700 Utah 90000 133000 1173000 IVermont 26000 1386000 1[497200 Virginia 99000 11397000 1F793600 IWashington 11200 11825000 i2379600 West Virginia 11 000 111056000 1352500 Wisconsin 609000 886000 1138400 WyomIng 1]32000 1196000 256100 IU.S. Total j2374=7000 34771000 44871800 B. Primary Mill Residues The quantities of mill residues generated at primary wood mills (i.e., mills producing lumber, pulp, veneers, other composite wood fiber materials) in the U.S. are obtained from the data compiled by the USDA Forest Service for the 1997 Resource Policy Act (RPA) Assessment (USDA, 1998a). Mill residues are classified by type and include bark; coarse residues (chunks and slabs); and fine residues (shavings and sawdust). Data is available for quantities of residues generated by residue type and on uses of residues by residue type and use category (i.e., not used, fuel, pulp, composite wood materials, etc.). Data is available at the county, state, subregion, and regional level. In cases where a county has fewer than three mills, data from multiple counties are combined to maintain the confidentiality of the data provided by http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

Bion)ass Feedstock Availability in the United States: 1999 State Level Analysis Page 4 of 16 individual mills. Data represent short run average quantities. Because primary mill residues are clean, concentrated at one source, and relatively homogeneous, nearly 98 percent of all residues generated in the United States are currently used as fuel or to produce other fiber products. Of the 24.2 million dry tons of bark produced in the U.S., 2.2 percent is not used while 79.4 percent is used for fuel and 18 percent is used for

• such things as mulch, bedding, and charcoal. Only about 1.4 percent of the 38.7 million dry tons of coarse residues are not used. The remainder are used to produce pulp or composite wood products such as particle board, wafer board, and oriented strand board (78 percent) and about 13 percent are used for fuel. Of the 27.5 million dry tons of fine wood residues, approximately 55.6 percent are used for fuel, 23 percent are used to produce pulp or composite wood products, 18.7 percent are used for bedding, mulch and other such uses, and about 2.6 percent are unused.

The residues, while currently used, could potentially be available for energy use if utilities could pay a higher price for the residues than their value in their current uses. Data regarding the value of these residues in their current uses are difficult to obtain. Much of the residues used for fuel are used on site by the residue generator in low efficiency boiler systems to produce heat and steam. Conversations with those in the industry and other anecdotal evidence suggests that these residues could be purchased for $15-25/dry ton for use in higher efficiency fuel systems. Similar anecdotal evidence suggests that residues used to produce fiber products (pulp, composite wood materials) sell for about $30-40/dry ton. For the purposes of this analysis, we assume that the residues not currently used could potentially be available for energy uses at delivered prices of less than $20/dry ton (assuming transportation distances of less than 50 miles). For similar transportation distances, we assume that residues currently used for fuel could be available at less than $30/dry ton delivered and residues currently used for pulp, composite wood materials, mulch, bedding, and other such uses could potentially be available at delivered prices of less than $50/dry ton. Table 2 presents the cumulative annual quantities of mill residues by delivered price for each state. Table 2: Estimated Annual Cumulative Mill Residue Quantities (dry.tons), by Delivered Price and State

                        <$20/dry ton delivered [< $30/dry ton delivered I< $50/dry ton delivered Alabama             ]17000                      4581000                   7802000

[Arizona 10 175000 1251000 [Arkansas [2000 2497000 4705000 California 8000 2294000 4823000 186000 1121000 11180000 10 140000 919000 I0 14000 116000 14000 [11412000 12678000 172000 3913000 17969000 1[69000 11629000 4400000 119000 1117000 ]282000 131000 213000 ]699000 1[2000 46000 1[158000 1Iooo 9000 20000 1[109000 421000 1940000 64000 1943000 13245000 1143000 209000 1o504000 http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

BioMass Feedstock Availability in the United States: 1999 State Level Analysis Page 5 of 16 Ik~rInl NAlnbn U.....J*'..... II'-"____ 111 -In ____..... [166000 Massachusetts 0 F44000 Jr135000 IMichigan [10000 932000 [1564000 Minnesota 71000 F916000 1[121000 Mississippi 128000 3178000 F6029000 Missouri 162000 315000 ]1196000 Montana 17000 659000 2173000 Nebraska 12000 21000 69000 Nevada 110 110 0o New Hampshire 23000 439000 1109000 New Jersey 0 18000 L21000 New Mexico 25000 - 7125000 61000 New York 128000 495000 1274000 North Carolina 33000 2060000 5028000 North Dakota 0 3000 4000 Ohio 0 0 o0 698000 Oklahoma 0 318000 Oregon 10000 1738000 16834000 Pennsylvania 172000 591000 1628000 Rhode Island I70 [11000 25000 South Carolina 14000 1706000 [3382000 South Dakota 18000 46000 124000 Tennessee 1202000 1325000 2018000 Texas 71118000 1649000 4043000 Utah 20000 67000 102000 IVermont 110 159000 1124000 Virginia 180000 1234000 2860000 Washington 15000 2262000 15689000 West Virginia 11136000 459000 967000 IWionsin 142000 l1202000 1192000 IWyoming 147000 = [124000 I[255000 U.S. Total 11780000 41459000 [90418000 C. Agricultural Residues http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 6 of 16 Agriculture is a major activity in the United States. Among the most important crops in terms of average total acres planted from 1995 to 1997 are corn (77 million acres), wheat (72 million acres), soybeans (65 million acres), hay (60.5 million acres), cotton (15 million acres), grain sorghum (10 million acres), barley (7 million acres), oats (5 million acres), rice (3 million acres), and rye (1.5 million acres) (USDA, 1998b). After harvest, a portion of the stalks could potentially be collected for energy use. The analysis in this paper is limited to corn stover and wheat straw. Large acreage is dedicated to soybean production, but in general, residue production is relatively small and tends to deteriorate rapidly in the field, limiting the usefulness of soybean as an energy feedstock. However, additional residue quantities could be available from this source that have not been included in this analysis. Similarly, additional residue quantities could be available if barley, oats, rice, and rye production were included. Production of some of these crops (rice in particular) tends to be concentrated in a relatively small geographic area, and thus these crops could be an important local source of resources. Another potential source in the southern U.S. is cotton. A recent study (NEOS. 1998) suggests that approximately 500,000 dry tons of cotton gin trash is currently produced in the United States and this material is generally given away to farmers for use as a soil amendment. Another 171,000 dry tons of textile mill residues are produced, but much of this material is used to make other textiles and sells for prices in excess of $100/dry ton. These quantities are not included in this analysis. The quantities of corn stover and wheat straw residues that can be available in each state are estimated by first calculating the total quantities of residues produced and then calculating the total quantities that can be collected after taking into consideration quantities that must be left to maintain soil quality (i.e., maintain organic matter and prevent erosion). Residue quantities generated are estimated using grain yields, total grain production, and a ratio of residue quantity to grain yield,-l The net quantities of residue per acre that are available for collection are estimated by subtracting from the total residue quantity generated, the quantities of residues that must remain to maintain quality (Lightle, 1997). Quantities that must remain differ by crop type, soil type, typical weather conditions, and the tillage system used. A state average was used for this analysis. In general, about 30 to 40 percent of the residues can be collected. The estimated prices of corn stover and wheat straw include the cost of collecting the residues, the premium paid to farmers to encourage participation, and transportation costs. The cost of collecting the agricultural residues are estimated using an engineering approach. For each harvest Operation, an equipment complement is defined. Using typical engineering specifications, the time per acre required to complete each operation and the cost per hour of using each piece of equipment is calculated (ASAE, 1995; NADA, 1995; USDA, 1996; Doanes, 1995). For corn stover, the analysis assumes lx mow, Ix rake, Ix bale with a large round baler, and pickup, transport, and unloading of the bales at the side of the field where they are stored until transport to the user facility.'The same operations are assumed for wheat straw minus the mowing. The operations assumed are conservative-- mowing is often eliminated and the raking operation is also eliminated in some circumstances. The method used to estimate collection costs is consistent with that used by USDA to estimate the costs of producing agricultural crops (USDA, 1996). An additional cost of $20/dry ton is added to account for the premium paid to farmers and the transportation cost from the site of production to the user facility. Currently, several companies purchase corn stover and/or wheat straw to produce bedding, insulating materials, particle board, paper, and chemicals (Gogerty, 1996). These firms typically pay $10 to $15/dry ton to farmers to compensate for any lost nutrient or environmental benefits that result from harvesting residues. The premium paid to farmers depends, in part, on transportation distance with farmers whose fields are at greater distances from the user facility receiving lower premiums. Studies have estimated that the cost of transporting giant round bales of switchgrass are $5 to $10 per dry ton for haul distances of less than 50 miles (Bhat et al, 1992; Graham et al, 1996; Noon et al, 1996). Agricultural residue bales are of similar size, weight, and density as switchgrass bales, and a similar transportation cost is assumed. This cost is similar to the reported transportation costs offacilities that utilize agricultural residues (Schechinger, 1997). Prices are in 1995$. For a more detailed explanation of the methodology used to estimate agricultural residue quantities and prices, see Walsh et al, 1998. The estimated annual cumulated agricultural residues quantities, by delivered price and state are contained in Table 3. Table 3 also contains by state, the percent of the total available residues that are corn stover. Table 3: Estimated Annual Cumulative Agricultural Residue Quantities (dry tons), by http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 7 of 16 Delivered Price and State

                      <e$vre.

3/dry ton < $40/dry ton delivered < $50/dry ton delivered Quntity  % Corn IQuantity  % Corn Quantity Corn Alabama ]100 0 119267 0 Arizona 221864 24 1221864 24 Arkansas jj 0 1[0 859361 1984495 13 California l[0 jj 0 1478283 40 11478283 40 Colorado t2 125 -3820 2523820 90 Connecticut 010 0 10 0 Delaware 1[0i]0 188077 0 1 300736 F1J Florida II0 1Io 14824 344423)7798710 0 114824 56 Georgia 0 Idaho 1 1248120,o 11248120 10 Illinois ][ 24270757 10 ]94 24270757 94 Indiana 1t0ll 11883845 111883845 94 Iowa lol l0 23911214 923911214 99 s0 ] 8570003 8570003 4 Kentucky 1 It0ll 471819 12280603 4 Louisiana ~ 1[o1o m 180930 0 380557 79 Maine 0 ][o 10 o 1 ]o Maryland 1j1lo 272468 0 ]802298, 66 I Massachusetts 1111 0 0o ]o 06 I Michigan 10i0 680783 ] 14265671 84 I sota 111935896 111935896 I Mississippi 0 0 37877 ] Missouri [10 1204353 14081358 70 1 Montana 0 i 11406592 9 406592 I Nebraska 10 016326915 98 16326915 98 Nevada 0 1 1o 15350 o1155 0 New Hampshire ]0 ]00 0 New Jersey ] 0 132723 ]32723 1 0 New Mexico [10 I 10 476529 155 476529 55 New York 129515 1129515 [North Carolina 0 1 473229 ][E= 11130744 58 http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 8 of 16 North Dakota 10 I0 114015 0 13715404 ]0 Ohio ]0i 0III 17634476 7634476 182 82 Oklahoma 3214403 0 3440745 7 3440745 7 Oregon 1155855 [4 155855 40 Pennsylvania 11 0 197689 0 ,1031195 0 Rhode Island 0o o] South Carolina 10239680 1239680 0 South Dakota 13686246 [71 2852740 71 Tennessee i0.iI 0 1300849 [ 11004781 [7 jTexas f]0 10 4497784 14497784 66 IUtah 01 [216546 19216546 2 IVermont 01 000 IVirginia 0297986 1585717 21 Washington 0 01j364254 30 1364254 30 West virginia 0 12008 ] 151295i[77 W isc 15179618 15179618 97 t~yoming oo [ý 11171585  :]=5 1171585 5 U.S. Total 3214403 135331029 81 150651402 80 D. Dedicated Energy Crops Dedicated energy crops include short rotation woody crops (SRWC) such as hybrid poplar and hybrid willow, and herbaceous crops such as switchgrass (SG). Currently, dedicated energy crops are not produced in the United States, but could be if they could be sold at a price that ensures the producer a profit at least as high as could be earned using the land for alternative usessuch as producing traditional agricultural crops. The POLYSYS model is used to estimate the quantities of energy crops that could potentially be produced at various energy crop prices. POLYSYS is an agricultural sector model that includes all major agricultural crops (wheat, corn, soybeans, cotton, rice, grain sorghum, barley, oats, alfalfa, other hay crops); a livestock sector; and food, feed, industrial, and export demand functions. POLYSYS was developed and is maintained bythe Agricultural Policy Analysis Center at the University of Tennessee and is used by the USDA Economic Research Service to conduct economic and policy analysis. Under a joint project between USDA and DOE, POLYSYS is being modified to include dedicated energy crops. A workshop consisting of USDA and DOE experts was held in November, 1997 to review the energy crop data being incorporated into the POLYSYS model. The analysis includes cropland acres that are presently planted to traditional crops, idled, in pasture, or are in the Conservation Reserve Program. Energy crop production is limited to areas climatically suited for their production--states in the Rocky Mountain region and the Western Plains region are excluded. Because the CRP is an environmental program, two management scenarios have been evaluated--one to optimize for biomass yield and one to provide for high wildlife divesity. Energy crop yields vary within and between states, and are based on-field trial data and expert opinion. Energy crop production costs are estimated using the same approach that is used by USDA to estimate the cost of producing conventional crops (USDA, 1996). Recommended management practices (planting density, fertilizer and chemical applications, rotation lengths) are assumed. Additionally, switchgrass stands are assumed to remain in production for 10 years before replanting, are harvested annually, and are delivered as large round bales. Hybrid poplars are planted at a 8 x 10 foot spacing (545 trees/acre) and are harvested in the 10th year of production in the northern U.S., http://bi6energv.oml.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 9 of 16 after 8 years of production in the southern U.S., and after 6 years of production in the Pacific Northwest. Poplar harvest is by custom operation and the product is delivered as whole tree wood chips. Hybrid willow varieties are suitable for production in the northern U.S. The analysis assumes 6200 trees/acre, with first harvest in year 4 and subsequentharvests every three years for a total of 7 harvests before replanting is necessary. Willow is delivered as whole tree chips. The estimated quantities of energy crops are those that could potentially be produced at a profit at least as great as could be earned producing traditional crops on tile same acres, given the assumed energy crop yield and production costs, and the 1999 USDA baseline production costs, yields, and traditional crop prices (USDA, 1999b). In the U.S., switchgrass production dominates hybrid poplar and willow production at the equivalent (on an MBTU basis) market prices. The POLYSYS model estimates the farmgate price; an average transportation cost of $8/dt is added to determine the delivered price. Prices are in $1997. Table 4 presents the estimated annual cumulative quantities of energy crops by state by delivered price. For a more detailed explanation of the methodology used to estimate dedicated energy crop prices and quantities, see Walsh et al, 1998 and de la Torre Ugarte et al, 1999. Table 4: Estimated Annual Cumulative Energy Crop Quantities (dry tons), by Delivered Price and State 11 1 1< $30/dry ton delivered <$40/dry ton delivered ]1< $50/dry ton delivered Alabama 10 3283747 6588812 Arizona 110 0 10 Arkansas 10 1709915 5509780 California 11000 10 [Colorado 110 10 o0 Connecticut IF0 11199646 IDelaware 110 10 :131454 IFlorida 00 i11268290 I3eorgia 1131438 210 I3958181 I1daho 0 10 I0 I'Illinois ndiana 0 04148042 11427349 063 17689694 I Iowa0O F4184 150262346 E~Iowa IIl 2334292 - -]8295486 Kansas 110 2859261 I11438271 Kentucky 0 3598827 5128780 ILouisiana II 0 13923954 5813200 IMaine 0 0 0 IMaryland 10 10 1298653 Massachusetts 10 110 1235908 IMichigan 10 F,154228 14179308 Minnesota 10 1427467 5783002 Mississippi 10 5330671 Mississipri 0_5251442F 19304782 IMissouri 10 115251442 1112780923 I ii ii http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007

Biomass Feedstock Availability in the United States: 1999 State Level Analysis Page 10 of 16 Montana 0110 112778386 Nebraska 10 I2I)22058 15172860 Nevada 11 50 New Hampshire [0 0f 1158757 New Jersey [o][ o 142902 New Mexico FO 0 0 New York FO 0 3388035 North Carolina O 639228 1632077 North Dakota o 1928463 16757889 0~o 3808089 9657080 Ohio Oklahoma 0 3644173 8083722 Oregon m0 ]0 0 Pennsylvania FO0 2338243 Rhode Island 1 110 4943 South Carolina 10o 1338745 12438152 0o 15613863 112757734 South Dakota Tennessee 0 6616717 119350856 Texas o 4549899 F9139885 Utah Fo 0 .o __0 Vermont [0 333465 Virginia 10 11260668 112609867 Washington 0 10 110 West Virginia 0 269250 11"90299 Wisconsin 10 113595636 116114270 Wyoming = 10 1[0 11487361 U.S. Total =0 1166127422 IF88067187 I E. Urban Wood Wastes Urban wood wastes include yard trimmings, site clearing wastes, pallets, wood packaging, and other miscellaneous commercial and household wood wastes that are generally disposed of at municipal solid waste (MSW) landfills and demolition and construction wastes that are generally disposed of in construction/demolition (C/D) landfills. Data regarding quantities of these wood wastes is difficult to find and price information is even rarer. Additionally, definitions differ by states. Some states collect data on total wastes deposited at each MSW and C/D landfill in their states, and in some states, the quantities are further categorized by type (i.e., wood, paper and cardboard, plastics, etc.). However, not all states collect this data. Therefore, the quantities presented are crude estimates based on survey data (Glenn, 1998; Bush et al, 1997; Araman et al, 1997). http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

Bionmass Feedstock Availability in the United States: 1999 State Level Analysis Page I I of 16 For municipal solid wastes (MSW) a survey by Glenn, 1998 is used to estimate total MSW generated by state. These quantities are adjusted slightly to correspond to regional MSW quantities that are land-filled as estimated by a survey conducted by Araman et al, 1997. Using tile Araman survey, tile total amount of wood contained in land-filled MSW is estimated. According to this survey, about 6 percent of municipal solid waste in the Midwest is wood, with 8 percent of the MSW being wood in the South, 6.6 percent being wood in the Northeast and 7.3 percent being wood in the West. Estimated quantities were in wet tons; they were corrected to dry tons by assuming a 15 percent moisture content by weight. To estimate construction and demolition wastes (C/D), tile Glenn study and the Bush et al, 1997 survey were used. The Glenn study provided the number of C/D landfills by state, and the Bush et al survey provided the average quantity of waste received per C/D landfill by region as well as the regional percent of the waste that was wood. According to tile Bush et al survey, C/D landfills in the Midwest receive an average 25,700 tons of waste per year with 46 percent of that quantity being wood. In tile South, C/D landfills receive an average 36,500 tons of waste/yr with 39 percent being wood. Northeastern C/D landfills receive an average 13,700 tons of waste/yr with 21 percent being wood and Western C/D landfills receive an average 28,800 tons of waste/yr with 18 percent being wood. Estimated quantities were in wet tons; they were corrected to dry tons by assuming a 15 percent moisture content by weight. Yard trimmings taken directly to a compost facility rather than land-filled, were estimated from the Glenn study. This estimate was made by multiplying the number of compost facilities in each state by the national average tons of material received by site (2750 tons). The total compost material was then corrected for the percent that is yard trimmings (assumed to be 80 percent) and for the quantity that is wood (assumed to be 90 percent). Quantities were corrected to dry tons by assuming a 40 percent moisture by weight. In an effort to reduce the quantities of waste materials that are land-filled, most states actively encourage the recycling of wastes. Quantities and prices of recycled wood wastes are not readily available. However, the Araman and Bush surveys report limited data on the recycling of wood wastes at MSW and C/D sites. They report that in the South, approximately 36 percent of C/D landfills and 50 percent of MSW landfills operate a wood/yard waste recycling facility and that about 34 percent of the wood at C/D landfills and 39 percent of the wood at MSW landfills is recycled. In the Midwest, about 31 percent of the MSW and 25 percent of the C/D landfills operate wood recycling facilities with 16 percent of the MSW wood and 1 percent of the C/D wood is recycled. In the West, 27 percent of the MSW and C/D landfills operate wood recycling facilities and recycle 25 percent each of their wood. In the Northeast, 39 percent of the MSW and 28 percent of the C/D landfills operate wood recycling facilities and recycle 39 percent of the MSW wood and 28 percent of the C/D wastes. The surveys do not report the use of total recycled wood, but do report the uses of recycled pallets which represent about 7 percent of the total wood and 4 percent of the recycled wood at C/D landfills and about 24 percent of the total wood and about 13 percent of the recycled wood at MSW landfills. At C/D landfills, about 14 percent of the recycled pallets are re-used as pallets, about 39 percent are used as fuel, and the remainder is used for other purposes such as mulch and composting. About 69 percent of the recyclers reported that they gave away the pallet material. Of those selling the material, the mean sale price was $11.01/ton and the median sale price was $10.50/ton. At MSW landfills, about 3 percent of the recycled pallets are re-used as pallets, about 41 percent are used as fuel, and the remainder is used for other purposes such as mulch and composting. About 58 percent of the C/D recyclers reported that they gave away tile pallet material. Of those selling the material, the mean sale price was $13.17/ton and the median sale price was $10.67/ton. Transportation costs must still be added to the sale price. Given the lack of information regarding prices, we assumed that of the total quantity available, 60 percent could be available at less than $20/dry ton and that the remaining quantities could be available at less than $30/dry ton. Table 5 presents the estimated annual cumulative quantities of urban wood wastes by state and price. Table 5: Estimated Annual Cumulative Delivered Urban Wood Price and Waste Quantities (dry tons)., by State F< $20/dry ton 11< $30/dry ton < $40/dry ton <$50/dry ton Alabama 1823566 11372610 11372610 11372610 Arizona [[219736 1366227 366227 366227 Arkansas ][4:000364 667273 16672736 http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

Bioniass Feedstock Availability in the United States: 1999 State Level Analysis Page 12 of 16 California 111579813 112633022 112633022 12633022 Colorado 194661 ]1157769 F157769 11157769 Connecticut 246938 1411563 1f411563 11411563 Delaware 38959 1164931 64931 1164931 Florida 2757950 114596584 114596584 14596584 Georgia 862094 111436823 111436823 111436823 Idaho 135265 11338162 338162 338162 Illinois 1416047 1693411 1693411 Indiana 1316610 1527684 11527684 527684 Ilowa 11171802 286337 [286337 286337 Kansas 736289 11227148 1227148 1122714 Kentucky 345699 576165576165 Loisiana 452322 753870 753870 753870 ] Maine 1108358 180597 ]180597 1180597 ] ]Maryland 204643 341071 ][341071 11341071 ] [Massachusetts 1419272 698787 ][698787 1698787 ] Michigan 495734 826224 826224 11826224 ] Minnesota j]1919517 11532529 ][1532529 f1532529 1 Mississippi []1470831 1784719 784719 11784719 [Missouri 1 315547 525911 1E525911 525911 I ]Montana 152060. 1186766 86766 Nebraska 102073 1170121 11170121 170121 INevada ]1184112 306853 306853 306853 INew Hampshire  !]110579 1184298 4298 1184298 INew Jersey ]1389089 f648481 [64848 11648481I [New Mexico 71142896 238160 1238160 238160 INew York _]11140080 11900133 ]1900133 1190013 North Carolina 1]636035 111060056 11060056 ]11060056 I INorth Dakota 11326510 11544184 ]5,44184 1544184 Ohio [744518 111240864 ][1240864 14864 jOklahoma [111173 185289 185289 185289 Oregon 11182532 3220 =F304220 D_304220 Pennsylvania 399963 666605 666605 11666605 Rhode Island ]129803 49671 49671 49671 South Carolina ]11289900 2149833 2149833 1214983 South Dakota 1123982 206637 206637 11206637

                     ]Tennessee 676029           1126715             1126715         1112671 Texas                   11209449        112015749            2015749           201574 Utah                  11138765          1231275             231275           11231275

[Vermont F40802 1F68004 68004 68004 [W a -]519454 2865757 4867765757iiI11~~i1Ii1 1hino865757 lWashington 2924ý32 14873874837837 http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

.Biormass Feedstock Availability in the United States: 1999 State Level Analysis Page 13 of 16 West Virginia 105236 1175393 1175393 175393 Wisconsin 383466 1639110 10 1639110 Wyoming 177383 11295638 58 295638 [U.S. Total 22040338 36846616 36846616 36846616 III. Summary Table 6 summarizes the estimated total annual cumulative quantities of biomass resources available by state and delivered price. It is estimated that substantial quantities of biomass (5 10 million dry tons) could be available annually at prices of less that $50/dt delivered. However, several caveats should be noted. There is a great deal of uncertainty surrounding some of the estimates. For example, while there is substantial confidence in the estimated quantities of mill residues available by state, there is a great deal of uncertainty about the estimated prices of these residues. The value of these feedstocks in their current uses, is speculative and based solely on anecdotal discussions. Given that the feedstock is already being used--much of it under contract or in-house by tile generator of the waste--energy facilities may need to pay a higher price than assumed to obtain the feedstock. Additionally, both the quantity and price of urban wastes are highly speculative. The analysis is based solely on one national study and regional averages taken from two additional surveys. There is no indication of the quality of the material present (i.e., whether the wood is contaminated with chemicals, etc.). Because of tile ways in which the surveys were conducted, there may be double counting of some quantities (i.e., MSW may contain yard trimmings and C/D wastes as well). Additionally, the analysis assumes that the majority of this urban wood is available for a minimal fee, with much of the cost resulting from transportation. Other industries have discovered that once a market is established, these "waste materials" become more valuable and are no longer available at minimal price. This situation could also happen with urban wastes used for energy if a steady customer becomes available. It should also be noted however, that some studies indicate that greater quantities of urban wastes are available, and are available at lower prices, than are assumed in this analysis (Wiltsee, 1998). Given the high level of uncertainty surrounding the quantity and price estimates of urban wastes and mill residues, and the fact that these wastes are estimated to be the least cost feedstocks available, they should be viewed with caution until a more detailed analysis is completed. The analysis has assumed that substantial quantities of dead forest wood could be harvested. The harvest of deadwood is a particularly dangerous activity and not one relished by most foresters. Additionally, large polewood trees represent the growing stock of trees, that if left for sufficient time, could be harvested for higher value uses. These opportunity costs have not been considered. And, the sustainability of removing these forest resources has not been thoroughly analyzed. We estimate the price of agricultural residues to be high largely because of the small quantities that can be sustainably removed on a per acre basis. Improvements in the collection/transport technologies and the ability to sustainably collect larger quantities (due to a shift in no-till site preparation practices for example) could increase quantities and decrease prices over time. Also, the inclusion of some of the minor grain crops (i.e., barley, oats, rye, rice) and soybeans could increase the total quantities of agricultural residues available by state. However, further elucidation of quantities that can sustainably be removed might lower available quantities. Dedicated energy crops (i.e., switchgrass and short rotation wood crops) are not currently produced--the analysis is based on our best estimates of yield, production costs, and profitability of alternative crops that could be produced on the same land. Improving yields and decreasing production costs through improved harvest and transport technologies could increase available quantities at lower costs. We have assumed a transportation cost of $8/dry ton for most feedstocks. This cost is based on a typical cost of transporting materials (i.e., switchgrass bales and wood chips) for less than 50 miles (Graham et al, 1996; Bhat et al, 1992; Noon et al, 1996). Finally, the analysis is conducted at a state level and the distribution of biomass resources within the state is not specifically considered. We have simply assumed that the feedstock is available within 50 miles of a user facility. This may not be the case which would result either in the cost of the feedstock being higher to a user facility due to increased transportation costs, or the quantities of availabl& feedstock being lower to a user facility if the material is simply too far away from the end-user site to be practical to obtain. Biomass resource assessments are needed at a lower aggregation level than the state. Any facility considering using the analysis need to conduct its own local analysis to http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

,Bion)ass Feedstock Availability in the United States: 1999 State Level Analysis Page 14 of 16 verify feedstock quantity and prices. Table 6: Estimated Cumulative Biomass Quantities (dry ton/yr), by Delivered Price and State I< $20/dry ton -1< $30/dry ton <$40/dry ton ]F $50/dry ton Alabama ]1840566 6962610 10712357 1[17681689 Arizona 1219736 1575227 863091 11100491 Arkansas 402364 4092273 7085549 113604348 California 111587813 16158022 8224305 111298705 Colorado 180661 3356589 365769 113581889 Connecticut ][246938 5605633 Delaware. 38959 94931 ]i46 1 Florida 2761950 116753122 6778408 195398 Georgia ]34094 6390823 8540684 16111675 Idaho f1204265 21572162 4117282 7165782 lllinois f435047 1038411 26838517 F)33359162 IIndiana 1[347610 11993684 13409571 18606863

 ,lowa                    173802          1404337             24582843        1[32786037 Kansas              1737289           111283148             12733412          21343522 Kentucky             F454699           11472165            5757811          1[o0809048 Louisiana             516322           13568870            7976754            11834427 Maine               1151358           1195597             11571597            13697 1Maryland             1204643           11543071Fl9539                        11959222       1 IMassachusetts        11419272          11938787            11026787            1435895 IMichigan             I1505734          ][2468224           L4627235            12163103 Mesota        11990517             [916529           [15493892           21247327 Missippi             FJ59883-1         14908719           10673390            17930978 ouri              477547         111345911            8029706            19522892

[Montana l 69060 1421766 2159358 6761444

 ]Nebraska             I114073           10121              1118467094     __21773296 Nevada              11184112          11314853                       11111    336603 NewHampshire          1,33579          1922298           101o298             12016455    1 NewJersey         1389089            11726481                              12975806 New Mexico           [j167896         11424160           11960689             1081589    ]

[New York 1116808 113328133 113884648 18438083 SII IF IF I I http://bioenergy.oml.gov/resourcedata/index.html 7/2/2007

.Bionjass Feedstock Availability in the United States: 1999 State Level Analysis Page 15 of 16 North Carolina 11669035 4188056 5789513 10855777 North Dakota 3_6510 558184 2 6 21043177 Ohio ]744518 1472864 13018429 18962520 Oklahoma 33873692 17816207 12699956 Oregon 192532 3341220 4126075 9809975 Pennsylvania 571963 2205605 2832294 7427043 Rhode Island 1129803 87671 180671 15514 South Carolina 1293900 4468833 6332258 9368065 South Dakota 131982 285637 9601746 16005411 I Tennessee ]1878029 113381715 10720281 15232952 Texas ]11227449 14221749 13526432 20747118 Utah 158765 388275 722821 [1 Vermont ]4082 1392004 513004 10226'69

 ~Virginia                                 3058757 1599454          115055411            8714941 Washington              297432            3979387           593864l            9920241 West virginia         1241236            1361393           1971651             3736487 12450110           1[502364        ][14963398 Wisconsin              [425466 Wyoming               1224383             551638            787223            11465684 23820338           105496557        314535067        1510855005 U.S. Total REFERENCES

1. American Society of Agricultural Engineers, Standards 1995-Standards,EngineeringPractices,and Data, 1995.

2. P.A. Araman, R.J. Bush, and V.S. Reddy, Municipal Solid Waste Landfills and Wood Pallets--What's Happening in the U.S., PalletEnterprise, March 1997, pp. 50-56.

3. M.B. Bhat, B.C. English, and M. Ojo, Regional Costs of Transporting Biomass Feedstocks, Liquid Fuels From Renewable Resources, John S. Cundiff (ed.), American Society of Agricultural Engineers, St. Joseph, MI, December 1992.

4. R.J. Bush, V.S. Reddy, and P.A. Araman, Construction and Demolition Landfills and Wood Pallets--What's Happening in the U.S., Pallet Enterprise, March 1997, pp. 27-3 1.

5. D.G. de la Torre Ugarte, S.P. Slinsky, and D.E. Ray, The Economic Impacts of Biomass Crop Production on the U.S. Agriculture Sector, University of Tennessee Agricultural Policy Analysis Center, Knoxville, TN, July 1999, Draft Document.

6. Doane's Agricultural Report, Estimated Machinery OperatingCosts, 1995, Vol. 58, No. 15-5, April 14, 1995.

7. J. Glenn, The State of Garbage, BioCycle, April 1998, pp.. 3 2 - 4 3 .

8. R. Gogerty, Crop Leftovers: More Uses, More Value, Resource: Engineeringand Technology for a Sustainable World, Vol. 3, No. 7, July 1996.

9. R.L. Graham, W. Liu, H.I. Jager, B.C. English, C.E. Noon, and M.J. Daly, A Regional-Scale GIS-Based Modeling System for Evaluating the Potential Costs and Supplies of Biomass From Biomass Crops, in Proceedingsof Bioenergy '96 - The Seventh National Bioenergy Conference, Nashville, TN, September 15-20, 1996, Southeastern Regional Biomass Energy Program, pp. 444-450, 1996.

10. W.G. Heid, Jr., Turning GreatPlains Crop Residues and Other Products into Energy, U.S. Department of http://bioenergy.oml.gov/resourcedata/index.htmi 7/2/2007

, . Bigrass Feedstock Availability in the United States: 1999 State Level Analysis Page 16 of 16 Agriculture, Economic Research Service, Agricultural Economic Report No. 523, Washington, DC, November 1984. 1I. D.T. Lightle, A Soil ConditioningIndexjbr CroplandManagement Systems (Draft), U.S. Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center, April 1997.

12. A. McQuillan, K. Skog, T. Nagle, and R. Loveless, MarginalCost Supply CurvesJbr Utilizing Forest Waste Wood in the United States, Unpublished Manuscript, University of Montana, Missoula, February 1984.

13. NEOS Corporation, Non-synthetic Cellulosic Textile Feedstock Resource Assessment, Southeastern Regional Biomass Energy Program, Muscle Shoals, AL, July 1998.

14. C.E. Noon, M.J. Daly, R.L. Graham, and F.B. Zahn, Transportation and Site Location Analysis for Regional Integrated Biomass Assessment (RIBA), in Proceedingsof Bioenergy '96 - The Seventh NationalBioenergy Conference, Nashville, TN, September 15-20, 1996, Southeastern Regional Biomass Energy Program, pp. 487-493, 1996.

15. North American Dealers Association, Official Guide--Tractors and Farm Equipment, 1995.

16. T. Schechinger, Great Lakes Chemical Corporation, personal communication, 1997.

17. U.S. Department of Agricultural, National Agricultural Statistics Service, World Agricultural Outlook Board, USDA Agricultural Baseline Projections to 2009, WAOB-99-l, Washington, DC, February 1999.

18. U.S. Department of Agriculture, Forest Service, Forest Inventory andAnalysis Timber ProductOutput Database Retrieval System, (http://srsfia.usfs.msstate.edu/rpa/tpo), 1998a.

19. U.S. Department of Agriculture, National Agricultural Statistical Service, Crop ProductionSummary, Washington, DC, January 1998b.

20. U.S. Department of Agriculture, Economic Research Service, Agricultural Resources and Environmental Indicators, 1996-1997, Agricultural Handbook No. 712, Washington, DC, July 1997.

21. U.S. Department of Agriculture, Economic Research Service, Economic Indicators of the Farm Sector.: Costs of Production--MajorField Crops, 1995, Washington, DC, 1996.

22. M.E. Walsh, R.L. Perlack, D.AN Becker, A. Turhollow, and R.L. Graham, Evolution of the Fuel Ethanol Industry:

Feedstock Availability andPrice, Oak Ridge National Laboratory, Oak Ridge, TN, April 21, 1998, Draft Document.

23. G. Wiltsee, Urban Wood Waste Resources in 30 US MetropolitanAreas, Appel Consultants, Inc., Valencia, CA, 1998.

1. Logging residues are the unused portion of the growing of stock trees (i.e., commercial species with a diameter breast height (dbh) greater than 5 inches, excluding cull trees) that are cut or killed by logging and left behind. Rough trees are those that do not contain a sawlog (i.e., 50 percent or more of live cull volume) or are not a currently merchantable species. Rotten trees are trees that do not contain a sawlog because of rot (i.e., 50 percent or more of the live cull volume). Salvable dead wood includes downed or standing trees that are considered currently or potentially merchantable.

Excess saplings are live trees having a dbh of between 1.0 and 4.9 inches. Small pole trees are trees with a dbh greater than 5 inches, but smaller than saw timber trees. (back to report)

2. Retrieval efficiency accounts for the quantity of the inventory that can actually be recovered due to technology or equipment (assumed to be 40 percent). It is assumed that 50 percent of the resource is accessible without having to construct roads, except for logging residues for which 100 percent of the inventory is assumed accessible. Finally, inventory that lies on slopes greater than 20 percent or where conventional equipment cannot be used are eliminated for cost and environmental reasons. (back to report)

3. The assumed residue factors are--I ton of corn stover for every I ton of corn grain produced; 1.7 tons of wheat straw for every 1 ton of winter wheat grain; and 1.3 ton of wheat straw for every I ton of spring and duram wheat grain (Heid, 1984). We assume a grain weight of 56 and 60 lb/bu for corn and wheat grain respectively. Grain moisture factors are assumed to be I for corn and .87 for wheat. (back* ,r* )

http://bioenergy.ornl.gov/resourcedata/index.html 7/2/2007}}