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electronic supplementary material

water use in lca

Measuring ecological impact of water consumption by bioethanol using life cycle impact assessment

Yi-Wen Chiu • Sangwon Suh • Stephan Pfister • Stefanie Hellweg • Annette Koehler

Received: 28 April 2011 / Accepted: 7 August 2011

© Springer-Verlag 2011

Y. W. Chiu

Water Resources Science, University of Minnesota. 9700 South Cass Avenue, Building 362, Lemont, IL 60439, USA

Supporting Information

Corn production and supply to nearby ethanol plants of each watershed

To incorporate corn production data into watershed scale, we applied the following sources:

  • Corn production (by county): NASS, 2007 (U.S. Department of Agriculture 2009b)

Corn yield of each county was calculated and converted to watershed average by applying the zonal statistic function of geographic information system. Corn production is then estimated based on corn harvest area (Aest, see description below) and GIS-interpolated yield data:

  • Land use: Crop land cover map, NASS, 2008 (U.S. Department of Agriculture 2009a)

The GIS map layer was further calibrated based on NASS 2007 data to overcome the potential error caused by spatial interpolation. The following equation was employed:

where Aest is the estimated corn area (m2) of each watershed, AGIS is the projected corn area (m2) from map raster image. The final corn area (Aest), yield rate, and total production within each watershed are listed in Table S4.

  • Determine corn sourcing area:

To draw the corn acquiring radius (r), each ethanol plant was used as center point to estimate the radius of corn cultivation areas which suffice the plant demand under full capacity. We first determined corn demand for each facility based on its ethanol production capacity. The radius was then calculated using information of corn yield rates of nearby watersheds (see Figure S1). Thus, if an ethanol plant X needs M kg of corn, the plant would source corn from watershed A, B, and Cwhich appear to have yield rate of YA, YB, and YC, respectively, to satisfy its annual production. Given this information, corn area size contributed by watershed A, B, and C can be estimated as a, b, and c, with which the radius r can be obtained.

Fig. S1 Diagram illustrating corn acquiring assumption used in this study

Table S1 Watershed corn production data used in the study

Watershed
ID / Watershed / Watershed Area
(m2) / Corn Area
(Aest, m2) / Corn Yield (kg/m2) / Corn Production
(kg)
1 / Lake Superior - North / 4124520000 / 94 / 0.00 / 0
2 / Lake Superior - South / 1637480000 / 94 / 0.00 / 0
3 / St. Louis River / 7388580000 / 516711 / 0.01 / 6498
4 / CLoquet River / 2055280000 / 115286 / 0.00 / 0
5 / Nemadji River / 719417000 / 460861 / 0.11 / 51526
7 / Mississippi River - Headwaters / 5079200000 / 3989914 / 0.07 / 282092
8 / Leech Lake River / 3458690000 / 3647830 / 0.00 / 0
9 / Mississippi River - Grand Rapids / 5373130000 / 4321526 / 0.19 / 834746
10 / Mississippi River - Brainerd / 4370420000 / 99794460 / 0.43 / 43206411
11 / Pine River / 2032330000 / 7986715 / 0.19 / 1498531
12 / Crow Wing River / 5039330000 / 104395145 / 0.30 / 31718168
13 / Redeye River / 2328370000 / 163237134 / 0.72 / 117052288
14 / Long Prairie River / 2313470000 / 144782035 / 0.57 / 82853692
15 / Mississippi River - Sartell / 2641300000 / 373322269 / 0.46 / 170865496
16 / Sauk River / 2700110000 / 593355774 / 0.60 / 357689101
17 / Mississippi River - St.Cloud / 2904750000 / 386345907 / 0.63 / 242055756
18 / North Fork Crow River / 3840900000 / 811713764 / 0.71 / 576147124
19 / South Fork Crow River / 3312050000 / 1178333879 / 0.85 / 1005690291
20 / Mississippi River / 2629990000 / 69931898 / 0.55 / 38671011
21 / Rum River / 4035020000 / 202552393 / 0.49 / 99055615
22 / Minnesota River - Headwaters / 1969750000 / 524108139 / 0.83 / 435508706
23 / Pomme de Terre River / 2266100000 / 627483918 / 0.83 / 518267205
24 / Lac qui Parle River / 1971240000 / 701810458 / 0.89 / 622470083
25 / Minnesota River - Granite Falls / 5372570000 / 2228009063 / 0.92 / 2051659917
26 / Chippewa River / 5370680000 / 1687079546 / 0.81 / 1369576237
27 / Redwood River / 1826160000 / 766265422 / 0.95 / 730724499
28 / Minnesota River - Mankato / 3490060000 / 1481947652 / 0.95 / 1403801589
29 / Cottonwood River / 3400130000 / 1512630519 / 0.98 / 1485046189
30 / Blue Earth River / 3137610000 / 1518616994 / 1.06 / 1607850929
31 / Watonwan River / 2272840000 / 1099891856 / 1.02 / 1124595427
32 / Le Sueur River / 2880750000 / 1345305921 / 1.02 / 1373194113
33 / Minnesota River - Shakopee / 4714120000 / 1455977171 / 0.87 / 1261627515
34 / St.Croix River - Upper / 1416860000 / 5658448 / 0.62 / 3480466
35 / Kettle River / 2720440000 / 7616706 / 0.39 / 2959539
36 / Snake River / 2612570000 / 57648279 / 0.49 / 28254401
37 / St.Croix River - Stillwater / 2389000000 / 164532167 / 0.62 / 101496768
38 / Mississippi River & Lake Pepin / 1565960000 / 307582743 / 0.95 / 291447568
39 / Cannon River / 3808680000 / 1198150333 / 0.99 / 1190597194
40 / Mississippi River - Winona / 1712610000 / 282652478 / 1.06 / 300162799
41 / Zumbro River / 3684010000 / 1188338099 / 1.07 / 1266471329
42 / Mississippi River - La Crescent / 221967000 / 5923737 / 1.04 / 6168980
43 / Root River / 4296050000 / 1026183163 / 1.06 / 1083947013
44 / Mississippi River - Reno / 474850000 / 29702086 / 1.00 / 29827726
46 / Upper Iowa River / 563004000 / 209467383 / 1.06 / 221740077
47 / Wapsipinican River / 32378400 / 18835674 / 1.08 / 20334052
48 / Cedar River / 1840470000 / 796351386 / 1.08 / 863451954
49 / Shell Rock River / 636674000 / 236869033 / 1.09 / 257199502
50 / Winnebago River / 184476000 / 93371653 / 1.09 / 101402549
51 / West Fork Des Moines - Head / 3229070000 / 1371129794 / 0.99 / 1355274049
52 / West Fork Des Moines - Lower / 225392000 / 100848638 / 1.03 / 103389015
53 / East Fork Des Moines / 522282000 / 259121965 / 1.03 / 267623757
54 / Bois de Sioux River / 1460520000 / 369716421 / 0.77 / 286390843
55 / Mustinka River / 2277910000 / 818258744 / 0.83 / 677016647
56 / Otter Tail River / 5136380000 / 382436372 / 0.73 / 278113466
57 / Red River of the North / 1139130000 / 166270514 / 0.74 / 123722388
58 / Buffalo River / 2870810000 / 364379208 / 0.77 / 280369760
59 / Marsh River / 1013660000 / 134851119 / 0.78 / 105155554
60 / Wild Rice River / 4219720000 / 457202734 / 0.75 / 343404059
61 / Sandhill River / 1460870000 / 121122369 / 0.73 / 88341205
62 / Upper/Lower Red Lake / 5113910000 / 6084308 / 0.01 / 76249
63 / Red Lake River / 3417080000 / 67066069 / 0.60 / 40136896
65 / Thief River / 2788540000 / 13697428 / 0.43 / 5907112
66 / Clearwater River / 3588080000 / 66703041 / 0.67 / 45020150
67 / Grand Marais Creek / 1552170000 / 20888180 / 0.72 / 14936615
68 / Snake River / 2033160000 / 12601362 / 0.69 / 8710087
69 / Tamarac / Joe Rivers / 2325930000 / 9812328 / 0.67 / 6623184
70 / Two River / 2787570000 / 26902580 / 0.64 / 17151041
71 / Roseau River / 2758150000 / 4140012 / 0.56 / 2327776
72 / Rainy River - Headwaters / 6496030000 / 94 / 0.00 / 0
73 / Vermilion River / 2680820000 / 10566 / 0.00 / 0
74 / Rainy River - Rainy Lake / 2353460000 / 94 / 0.00 / 0
75 / Rainy River - Manitou / 1355840000 / 38491 / 0.00 / 0
76 / Little Fork River / 4773570000 / 69907 / 0.00 / 0
77 / Big Fork River / 5370070000 / 492277 / 0.00 / 0
78 / Rapid River / 2319090000 / 272365 / 0.00 / 0
79 / Rainy River - Baudette / 789827000 / 754076 / 0.00 / 0
80 / Lake of the Woods / 2977980000 / 1165973 / 0.12 / 142574
81 / Big Sioux - Medary Creek / 106898000 / 39821498 / 0.96 / 38240465
82 / Big Sioux - Pipestone / 1321010000 / 542671448 / 0.93 / 506979404
83 / Rock River / 2374620000 / 1048380244 / 0.97 / 1016921498
84 / Little Sioux River / 810364000 / 351955963 / 1.01 / 355472003

Table S2 Watershed information in CFEQ, and corn supply to ethanol production

Watershed ID / NPPwt-lim / Precipitation / CFEQ / Irrigation consumption / Corn field acquired / Corn field acquired
(m) / (m) / (m3) / (2007 existing plants, m2) / (after expansion, m2)
10 / 0.16 / 0.70 / 0.23 / 2863451 / 99794460 / 99794460
15 / 0.18 / 0.71 / 0.25 / 13154229 / 333820425 / 333820425
18 / 0.19 / 0.75 / 0.25 / 15331159 / 296927532 / 296927532
19 / 0.19 / 0.77 / 0.25 / 47164 / 259650467 / 259650467
23 / 0.20 / 0.62 / 0.33 / 7231289 / 231889912 / 364879150
25 / 0.21 / 0.68 / 0.32 / 185791 / 515451350 / 515565412
26 / 0.20 / 0.65 / 0.31 / 21855255 / 494107690 / 494107690
27 / 0.23 / 0.66 / 0.35 / 99480 / 227774472 / 227774472
28 / 0.21 / 0.70 / 0.30 / 243089 / 430273169 / 430486164
29 / 0.23 / 0.67 / 0.35 / 362953 / 141681569 / 595521569
30 / 0.22 / 0.75 / 0.30 / 425792 / 322474466 / 1518616994
31 / 0.23 / 0.70 / 0.33 / 1045218 / 308602530 / 768298704
32 / 0.21 / 0.76 / 0.27 / 49724 / 97975327 / 519687473
33 / 0.19 / 0.78 / 0.24 / 352858 / 960229108 / 960229108
39 / 0.19 / 0.79 / 0.24 / 5744647 / 75842487 / 93047595
41 / 0.18 / 0.79 / 0.23 / 29061 / 221803370 / 344943288
43 / 0.18 / 0.83 / 0.22 / 0 / 354192663 / 354192663
48 / 0.20 / 0.81 / 0.24 / 370239 / 91027729 / 132274685
49 / 0.20 / 0.81 / 0.25 / 50097 / 236869033 / 236869033
50 / 0.21 / 0.80 / 0.26 / 190930 / 346411 / 24782915
51 / 0.24 / 0.69 / 0.35 / 439122 / 109882565 / 560466819
53 / 0.23 / 0.73 / 0.32 / 0 / 0 / 259121965
54 / 0.21 / 0.60 / 0.36 / 0 / 0 / 44028993
55 / 0.21 / 0.59 / 0.36 / 90787 / 0 / 108934738
56 / 0.19 / 0.61 / 0.31 / 13475083 / 0 / 382436372
82 / 0.24 / 0.67 / 0.36 / 1047741 / 34113409 / 34115000
83 / 0.24 / 0.70 / 0.35 / 278198 / 159962109 / 159975000

(a) (b)

Fig.S2 Geographic distribution of NPPwat-lim (a) and CFEQ(b) in Minnesota

Consumptive corn irrigation embedded in ethanol and process water in ethanol plants

  • Irrigated water

We combined the Hargreaves potential evapotranspiration model (Hargreaves and Samani 1982) with the crop water estimation proposed by the Food and Agriculture Organization (FAO) of the United Nations (Allen et al. 1998) for estimating monthly evapotranspiration (ET). Historical climate data of Minnesota were then employed as the input data to simulate temporally and spatially explicit crop ET for every watershed. The result showed that an average share of 73% of the irrigation water withdrawals is subject to evapotranspiration with minimal geographical variation in Minnesota (SD=0.03). This estimates is in line with previous studies indicating that average water loss through evapotranspiration accounts for 70% to 75% of irrigation withdrawals for crop cultivation in the U.S. (FAO 2002; Torcellini et al. 2003). In order to further distinguish this ratio for corn, Minnesota’s primary crops and planting area size were analyzed. Corn, potato, and cereal (wheat) are three primary crops accounting for 33%, 33% and 29% of agricultural land in Minnesota respectively (U.S. Department of Agriculture 2009b). However, only potato and corn are grown in summer and both share similar growing schedule and crop coefficient which affects evapotranspiration (FAO 2002). Therefore, it is reasonable assume that also 73% of corn irrigation withdrawal is subject to be consumptive.

  • Process water

To account for process-related water use, we applied facility-specific data from Minnesota’s Water Appropriations Permit Program to quantify water withdrawals supporting the ethanol production process (MN DNR 2008) ranging from 2.7 to 7.6 L water/L ethanol, and a production-averaged 3.8 L water/L ethanol for new plants or if plant information was not available. For new and planned facilities, we estimated an average ratio of total water input to ethanol output amounting to 3.8 liters ofwater used per liter of ethanol produced, using survey information from ethanol facilitiesand WAPP data. Modern ethanol plants use extensive internal water recycling and therefore only withdraw freshwater to compensate for the losses due to evaporation, drifting or windage, and cooling tower blow down. These water outflows from conversion facilities are either evaporated or disposed to wastewater treatment plants, making them only to alimited degree available for the watershed/local environment. Therefore, the whole amount of water withdrawn by new and planned ethanol conversion facilities was considered as consumptive water use (3.8 L/L). Distinguishing the sources of water withdrawal within Minnesota’s 81 major watersheds, facility-specific water consumption encompassing both irrigation-water consumption of the corn supplied and plant-water consumption was determined for 21 bioethanol conversion facilities including 15 existing and six under-constructionplants. We assumed water consumption to take place in the watershed of withdrawals.

Sensitivity Analysis

To compute ΔEQEtOH, we used the following equation to construct the relationship between “forecast” (or ΔEQEtOH) and “assumptions” which are all the variables listed in the second line of the equation.

where

Wirg-EtOH = consumptive irrigated water in ethanol (m3)

Wpw = ethanol process water (m3)

WUirg-corn = irrigated water withdrawn for corn (m3)

cwirg = Fraction of irrigation consumption in withdrawal

Acorn-EtOH = Corn field acquired in supporting ethanol (m2)

Acorn = Total corn-planting area size (m2)

Ew = Process water efficiency (L water/L EtOH)

PEtOH = ethanol production supported by a watershed (m3)

p = watershed-based precipitation depth (m)

The distribution of each assumption was derived based on the watershed basis data collected in this study (Table S3). To understand how the ecological damage ΔEQEtOH responds to the changes in key parameters, we employedMonte Carlo Simulation to test the sensitivity of the independent input variables defining water consumption, climate, and the impact factor in this study. The contribution to variance of the selected parameters to ΔEQEtOHcan be expressed as (Robert and Casella 1999):

where CTVi is the contribution to variance of parameter i to ΔEQEtOH, riis the rank-order correlation coefficient between parameter i, and ni is the number of parameters contributing to the variance in the result of ΔEQEtOH. A state-averaged ecological damage ΔEQEtOH was estimated based on a set of input variables following the same procedure of computing equation 1. The contribution of each variable to the variance of the state-averaged ΔEQEtOH was then recorded. The distribution of each input variable was created based on the watershed-level data derived for this study (Table S3).

Table S3 Assumptions used in this study. All variables are on a watershed basis

Statistics / Distribution / Mean / Standard Deviation / Minimum / Maximum
Corn field acquired in supporting ethanol (m2) / Lognormal / 3.83E+08 / 3.59E+08 / 4.26E+07 / 2.85E+09
Ethanol production supported by a watershed (m3) / Lognormal / 2.03E+05 / 1.35E+05 / 6.51E+04 / 1.14E+06
Fraction of irrigation consumption in withdrawal / Normal / 7.29E-01 / 1.97E-02 / 6.69E-01 / 7.80E-01
Irrigation withdrawal volume for corn (m3) / Lognormal / 5.44E+08 / 1.17E+12 / 4.91E+00 / 7.57E+10
Water-limited NPP / Lognormal / 2.08E-01 / 2.00E-02 / 1.68E-01 / 3.17E-01
Precipitation depth (m) / Beta / 7.17E-01 / 6.87E-02 / 5.76E-01 / 8.33E-01
Process water efficiency (L water/L EtOH) / Logistic / 3.92E+00 / 9.38E-01 / 9.10E-01 / 7.00E+00
Total corn-planting area size (m2) / Maximum Extreme / 2.94E+09 / 1.73E+09 / 1.09E+08 / 9.54E+09

The result indicates that EQEtOH is most sensitive to the ethanol production volume, irrigated water withdrawal volume which can further define irrigation water consumption, and the plant’s water-use efficiency (Table S4). The integrity of industrial water consumption data appears to play a critical role in the application of ecological impact assessment.

Table S4 Sensitivity analysis result. Listed are the top key factors responsible for the variation in EQEtOH. Only those having contribution to the variation of ΔEQEtOH1% are shown

Input Variables / Contribution to the Variation of EQEtOH / Rank Correlation / Origin and Availability
Ethanol production / 41% / 0.56 / Governmental investigation, public available
Water withdrawal for corn irrigation / 40% / 0.55 / Governmental investigation, public available
Plant water use efficiency / 8% / 0.24 / Self-report, official monitoring program, or assumed, partially available
Precipitation / 5% / -0.20 / Governmental monitoring, public available
Water-limited net primary production, NPPwat-lim / 2% / 0.11 / Scientific estimation, public available
Corn field acquired in supporting ethanol / 1% / 0.07 / Assumption, described in this manuscript

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Results of corn-ethanol water consumption impact in ecological damage

The results are derived to demonstrate the ecological damage from resource (watershed) and product (plant) aspects.

Table S5 Ethanol water use impact ΔEQEtOH (in 1000 m2yr) on a watershed and plant basis given the CFEQ (m2yr/m3) of each watershed. ΔEQEtOHcaused by ethanol water consumption (WUEtOH, in million liters) may show different attribute on a watershed basis from a plant basis. Ethanol production is in million liters. Numbers may not sum to total due to rounding

Watershed ID / CF / Watershed-Based / Plant-Based
Supported EtOH production / Ethanol Water Consumption WUEtOH / ΔEQEtOH from irg. / ΔEQEtOH from process water / ΔEQEtOH / On-site EtOH production / Ethanol Water Consumption WUEtOH / ΔEQEtOH from irg. / ΔEQEtOH from process water / ΔEQEtOH
Irrigation water in EtOH / EtOH process water / Total / Irrigation water in EtOH / EtOH process water / Total
10 / 0.23 / 18 / 2,863 / 416 / 3,280 / 644 / 94 / 738 / 83 / 14,626 / 416 / 15,042 / 3,549 / 94 / 3,643
15 / 0.25 / 65 / 11,762 / - / 11,762 / 2,905 / - / 2,905 / - / - / - / - / - / - / -
18 / 0.25 / 90 / 5,608 / 515 / 6,123 / 1,390 / 128 / 1,518 / 151 / 5,616 / 515 / 6,130 / 1,392 / 128 / 1,520
19 / 0.25 / 94 / 10 / 286 / 297 / 3 / 72 / 74 / 68 / 24 / 286 / 311 / 6 / 72 / 78
23 / 0.33 / 81 / 2,672 / 521 / 3,193 / 882 / 172 / 1,054 / 81 / 2,672 / 521 / 3,193 / 882 / 172 / 1,054
25 / 0.32 / 202 / 43 / 551 / 594 / 14 / 174 / 188 / 197 / 42 / 551 / 593 / 13 / 174 / 187
26 / 0.31 / 170 / 6,401 / 630 / 7,031 / 1,985 / 195 / 2,180 / 170 / 6,401 / 630 / 7,031 / 1,985 / 195 / 2,180
27 / 0.35 / 92 / 30 / 1,151 / 1,180 / 10 / 402 / 413 / 151 / 64 / 1,151 / 1,214 / 22 / 402 / 424
28 / 0.30 / 173 / 71 / 571 / 641 / 21 / 174 / 195 / 197 / 196 / 571 / 767 / 63 / 174 / 237
29 / 0.35 / 59 / 34 / - / 34 / 12 / - / 12 / - / - / - / - / - / - / -
30 / 0.30 / 145 / 90 / 683 / 773 / 27 / 202 / 229 / 167 / 81 / 683 / 764 / 24 / 202 / 226
31 / 0.33 / 134 / 293 / 521 / 814 / 96 / 170 / 266 / 121 / 193 / 521 / 714 / 64 / 170 / 234
32 / 0.27 / 43 / 4 / - / 4 / 1 / - / 1 / - / - / - / - / - / - / -
33 / 0.24 / 354 / 233 / 1,022 / 1,255 / 57 / 250 / 307 / 379 / 235 / 1,022 / 1,257 / 59 / 250 / 309
39 / 0.24 / 32 / 364 / - / 364 / 88 / - / 88 / - / - / - / - / - / - / -
41 / 0.23 / 100 / 5 / 490 / 496 / 1 / 115 / 116 / 132 / 369 / 490 / 859 / 89 / 115 / 204
43 / 0.22 / 159 / - / 588 / 588 / - / 131 / 131 / 159 / - / 588 / 588 / - / 131 / 131
48 / 0.24 / 42 / 42 / - / 42 / 10 / - / 10 / - / - / - / - / - / - / -
49 / 0.25 / 109 / 50 / 666 / 716 / 13 / 167 / 179 / 151 / 93 / 666 / 759 / 23 / 167 / 190
50 / 0.26 / 0 / 1 / - / 1 / 0 / - / 0 / - / - / - / - / - / - / -
51 / 0.35 / 46 / 35 / - / 35 / 12 / - / 12 / - / - / - / - / - / - / -
82 / 0.36 / 14 / 66 / - / 66 / 24 / - / 24 / - / - / - / - / - / - / -
83 / 0.35 / 66 / 42 / 374 / 416 / 15 / 131 / 146 / 79 / 108 / 374 / 482 / 39 / 131 / 169
Total / 2,289 / 30,720 / 8,985 / 39,706 / 8,210 / 2,576 / 10,786 / 2,288 / 30,720 / 8,985 / 39,706 / 8,210 / 2,576 / 10,786

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Total ecosystem damage of the U.S. corn ethanol (excluding damage caused by water consumption)

To estimate the total ecosystem damage we applied a dataset from the ecoinvent database (v2.1) which provides a life cycle inventory for average corn-based bioethanol production in the U.S. (Frischknecht 2005).The cradle-to-gate bioethanol production system was assessed with the Eco-indicator 99 methodology (Goedkoop et al. 2000) returning an ecosystem damage score which considers the entire corn supply chain and bio-ethanol conversion including all upstream processes. The total ecosystem damage score integrates damages caused by ecotoxic and eutrophying substances as well as by land use.

Impact category / Ecotoxicity / Acidification/ Eutrophication / Land use
PDF*m2yr / PDF*m2yr / PDF*m2yr
Corn, at farm/US U / 3.13E-02 / 8.01E-02 / 3.00E+00
Tap water, at user/RER U / 4.24E-05 / 1.93E-05 / 6.13E-05
Sulphuric acid, liquid, at plant/RER U / 2.92E-04 / 5.37E-04 / 7.69E-05
Soda, powder, at plant/RER U / 6.86E-04 / 6.71E-04 / 2.83E-04
Ammonium sulphate, as N, at regional storehouse/RER U / 1.07E-03 / 2.75E-04 / 2.90E-04
Diammonium phosphate, as N, at regional storehouse/RER U / 1.33E-03 / 4.81E-04 / 3.15E-04
Transport, tractor and trailer/CH U / 3.52E-04 / 4.04E-04 / 5.73E-04
Transport, freight, rail/RER U / 6.48E-05 / 5.68E-05 / 5.63E-05
Transport, lorry >16t, fleet average/RER U / 3.16E-05 / 5.13E-05 / 1.64E-05
Transport, lorry 3.5-16t, fleet average/RER U / 1.63E-03 / 2.29E-03 / 1.35E-03
Heat, natural gas, at industrial furnace >100kW/RER U / 2.84E-04 / 1.02E-03 / 7.62E-04
Electricity, medium voltage, at grid/US U / 1.46E-03 / 1.74E-03 / 8.23E-04
Ethanol fermentation plant/CH/I U / 4.28E-04 / 2.86E-05 / 2.67E-04
Treatment, sewage, from residence, to wastewater treatment, class 2/CH U / 4.73E-05 / 2.00E-05 / 7.59E-06
Total / 3.90E-02 / 8.77E-02 / 3.01E+00

Total ecosystem damage for 1 kg of bioethanol produced from con in the U.S. (average value):

3.13 PDF·m2·yr per kg ethanol or 2.47 PDF·m2·yr per liter ethanol.

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