THE 1997 BENCHMARK VERSION OF THE ECONOMIC INPUT … · 2006-11-03 · 1 THE 1997 BENCHMARK VERSION OF THE ECONOMIC INPUT-OUTPUT LIFE CYCLE ASSESSMENT (EIO-LCA) MODEL BY GYORGYI CICAS,

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THE 1997 BENCHMARK VERSION OF THE ECONOMIC INPUT-OUTPUT LIFE CYCLE

ASSESSMENT (EIO-LCA) MODEL

BY GYORGYI CICAS, H. SCOTT MATTHEWS AND CHRIS HENDRICKSON GREEN DESIGN INSTITUTE, CARNEGIE MELLON UNIVERSITY

NOVEMBER 1, 2006

1. INTRODUCTION

The 1997 EIO-LCA benchmark model is based upon a variety of public data sources. The model is built upon the inter-sector transactions as compiled by the Bureau of Economic Analysis of the US Department of Commerce (BEA 2002). The benchmark model is based upon a variety of census data sources and represents more detailed estimates and provides the basis for the BEA’s annual input-output tables. To this basic Leontief model, we have added a series of emission and resource use vectors (Hendrickson 2005). This document describes the calculations and transformations used to produce these various impact vectors. Sections in this report include:

• 2. Transformation bridges from IO 1992, to SIC, to NAICS and to IO 1997 economic sector classification schemes.

• 3. Conventional Air Emission Pollutants • 4. Toxics Release Inventory (TRI) Emissions • 5. Global Warming Potential Emissions • 6. Energy Use • 7. References

Also included are four appendices in a separate volume: 1. Sector Mappings 2. 1997 Input-Output Sector Outputs 3. Conventional Air Emissions Adjustments 4. Global Warming Potential adjustments

2. DESCRIPTION OF THE IO 1992 – SIC – NAICS – IO 1997 BRIDGE USED IN CALCULATION

OF THE 1997 UPDATE OF EIO-LCA When EIO-LCA was originally made available to the public in 1999, it was based on the 1992 benchmark input-output (IO) commodity tables from the Department of Census, Bureau of Economic Analysis. The IO 1992 accounts were based on the Standard Industrial Classification (SIC) system. However the more recent 1997 benchmark industry-by-industry IO model is based on the North American Industry Classification System (NAICS). Much of the environmental emissions and resource use data used in the 1997 benchmark model is still being reported on the basis of SIC sectors. In addition, a few types of data were available for the 1992 emission and resource use vectors that were not publicly available for the 1997 model; as a result, some data from the 1992 model was updated to 1997 and incorporated in the 1997 benchmark model. For these updates, a transformation ‘bridge’ between the 1992 input-output sectors, SIC industries, NAICS industries and the 1997 benchmark sectors was developed. Bridge relationships serve as formal “maps” between entities, in this case they are lists of sectors in the various classification

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systems that map to each other. Figure 1 illustrates the mapping system transferring data from IO 1992 to IO 1997, with a transformation from IO 1992 sectors to SIC industries, followed by a transformation to NAICS industries, followed by the aggregation to 1997 IO sectors.

Figure 1: Illustration of the IO 1992 – SIC – NAICS – IO 1997 bridge

The benchmark input-output (IO) industry accounts for the U.S. economy for 1992 and 1997 and the bridge between SIC and NAICS provided by the Census Bureau were used to create a bridge between the 485 IO 1992 and 491 IO 1997 sector definitions [BEA 1997a, BEA 2002 and Census 2002a]. Appendix I presents the complete bridge that was used to allocate various datasets to IO 1997 sectors since the sources were based on different industry classification systems. Table 1 summarizes the 1997 industry benchmark model datasets, and the classification system used by the source data. All data was mapped to the IO 1997 basis.

Data Source classification system Toxics Release Inventory (2000) SIC RCRA Hazardous waste generation (1999) NAICS Emission of criteria pollutants (1999) SIC Electricity and fuel use – Mining (1997) NAICS Electricity and fuel use – Manufacturing (1998) SIC Electricity and fuel use – Non-mining, manufacturing and transportation sectors (1997)

IO 1992

Table 1: Classification systems used by various external datasets

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The Survey of Current Business provided the list of SIC codes related to each of the IO 1992 industries [BEA 2002]. 337 of the 485 (or 70%) IO 1992 sectors were mapped on a one-to-one basis to SIC sectors. All other IO 1992 sectors were linked to multiple SIC sectors and were equally distributed between the corresponding SIC industries. Table 2 presents an excerpt of the IO1992 – SIC bridge, which defined the corresponding mapping of impact in a given IO 1992 sector to a given SIC code. For example, IO 1992 sector 180300 (Knit fabric mills) is listed as being comprised of 2 SIC sectors, 2257 and 2258. Thus, half of each value associated with sector 180300 goes to each of the 2 SIC codes.

IO 1992 Ratio SIC 180201 1 2253 180202 1 2254 180300 0.5 2257 180300 0.5 2258 180203 1 2259 160100 0.2 2261

Table 2: Sample mappings in the IO 1992 – SIC Bridge The 1997 SIC-NAICS bridge available from the Census consists of two tables illustrated by Figures 2 and 3 below [Census 2002a]. Figure 2 presents NAICS codes and the corresponding SIC codes included entirely or partly in that NAICS sector. The percentage to the left of SIC codes indicates the fraction of SIC that is incorporated in the NAICS sector.

Figure 2: Excerpt of Table 1 of the bridge between NAICS and SIC [Census 2002a]

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Figure 3 illustrates SIC industries and the NAICS sectors included entirely or partly in that SIC. The percentage to the left of the NAICS code shows the fraction of this sector incorporated in the corresponding SIC sector.

Figure 3 Excerpt of Table 2 of the bridge between NAICS and SIC (Census 2002a)

Table 3 below shows an excerpt of the SIC – NAICS bridge created using the data provided by the Census Bureau (2005).

SIC Ratio NAICS 2253 0 313312 2254 0 313312 2257 0.37 313312 2258 0.22 313312 2269 1 313312 2284 0.5 313312

Table 3: Excerpt of the SIC – NAICS bridge Figure 4 illustrates the use of the SIC – NAICS bridge to support the estimation of toxic releases of NAICS sector 313312 (Textile and fabric finishing, except broadwoven fabric mills). SIC sector 2257 (Weft knit fabric mills) corresponds to two NAICS industries (313312 and 313241). Thus in accordance with the Census bridge, 37% of the toxic releases reported under SIC 2257

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goes to NAICS 313312 (shown in Figure 2) and 63% of it is mapped to NAICS 313241 (not shown in Figure 2).

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Figure 4: Example of estimation of toxic releases of NAICS sectors using the SIC – NAICS

bridge

Example: 0.1134×0.37 = 0.041958

for

Air non-point and Air point

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The IO 1997 accounts are based on NAICS. The Survey of Current Business provides the list of NAICS codes related to each of the IO 1997 industries [BEA 2002]. Sixteen NAICS industries were linked on a one-to-many basis to IO 1997 sectors. The ratio of outputs of IO 1997 industries were used to distribute those NAICS between the corresponding IO 1997 sectors. All other NAICS sectors were mapped on a many-to-one basis to IO 1997 industries. Table 4 presents an excerpt of the NAICS – IO 1997 bridge.

NAICS Ratio IO 1997 313241 1 313240 313249 1 313240 313311 1 313310 313312 1 313310 313320 1 313320 314110 1 314110 314121 1 314120

Table 4: Excerpt of the NAICS – IO 1997 bridge

Figure 5 illustrates the use of the NAICS – IO 1997 bridge through the estimation of TRI emissions of IO 1997 sector 313310 (Textile and fabric finishing mills). The sector comprises two NAICS industries (313311 and 313312), which are included entirely in it. Thus all toxic releases of each NAICS sector goes to the IO industry 313310.

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Figure 5: Example of estimation of toxic releases of IO 1997 sectors using the NAICS – IO

1997 bridge

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Using the same method as shown in Figures 4 and 5, all economic and external data used in the 1997 industry benchmark model was converted via this bridge. Details on validation of the data are given in subsequent parts of this document. Appendix 1 gives detail on the mapping ratios used. 3. CALCULATION OF THE CONVENTIONAL POLLUTANTS DATA IN THE 1997 UPDATE OF

EIO-LCA 3.1 Introduction

The 1992 benchmark version of the EIO-LCA model used the conventional pollutants emission data of the U.S. EPA’s 1996 AIRData NET SIC Report and emission estimates of the National Air Quality and Emissions Trends Report for 1996. As of 2005, the latest AIRData Report is available for 1999, so this year was chosen to update the conventional pollutants emissions in the 1997 EIO-LCA benchmark model. Since the report does not include lead emission information and does not cover all emission sources, the National Air Quality and Emission Trends Report for 1999 was used to augment and estimate the sectoral lead pollution and adjust the sectoral emission estimates. This section summarizes the process used. The AirData Facility SIC Report for 1999 [EPA 1999a] provides criteria air pollutants (i.e., CO, NH3, NOx, PM10, PM2.5, SO2 and VOC) emission estimates for point sources identified by Standard Industrial Classification (SIC) code [EPA 1999c]. Industrial facilities are examples of point sources. The facility emission estimates are calculated based on annual material consumption or the amount of product that was manufactured [EPA 1999d]. Figure 6 presents an excerpt of the data included in the report.

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Figure 6: Excerpt of the AirData Facility SIC Report for 1999 [EPA 1999a]

Appendix A of the 1999 National Air Quality and Emissions Trends Report (NAQETR) [EPA 1999b] includes estimates of emissions of criteria air pollutants by aggregated source categories, for example, “Organic chemical manufacturing” or “Fuel combustion in electric utilities” from 1970 to 1999. EPA uses air quality data measured by monitoring sites throughout the country and emission estimates based on vehicle use, fuel consumption, production level of industries, and other factors to incorporate area and line sources besides the facilities included in the Facility SIC Report [EPA 1999b]. The AirData Facility SIC Report summarizes emissions in short tons by 4-digit SIC codes. The SIC-NAICS-IO 1997 bridge described above was used to estimate the sectoral releases of the following pollutants:

CO, carbon monoxide

NOx, nitrogen oxides

SO2, sulfur dioxide

VOC, volatile organic compounds

PM10, particulate

The total annual emission estimates then were compared to those provided by categories in the NAQETR. Only about 10% of the emissions estimated by the NAQETR were included in the AirData report since the latter takes into account only the point sources. For example, 77% of total national CO emissions are due to transportation [EPA 1999b], an emission

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source not included in the AirData since it is from mobile sources. Thus, the sectoral emission table for the EIO-LCA model needed to be augmented based on sectors implicit in the emission trends report. When the emission of one NAQETR source category could be associated with many IO sectors, the ratio of sectoral total outputs [BEA 1997a] was used as a weighting factor except for the on-road and non-road transportation sources. Appendix 3 presents the NAQETR emission source categories that were mapped to IO 1997 sectors and the weighting factors. “NA” indicates that another allocation method was used that is described below. The emission estimates for transportation-related sources were provided in NAQETR for gas and diesel vehicles used by aggregated sectors, e.g., construction, thus the sectoral diesel fuel (or light fuel oil for agricultural and transportation sectors) and motor gasoline consumption estimated for the IO sectors in gallons was used to allocate the emissions. The economic value of consumption was obtained from the use table [BEA 1997b] adding up the purchases from the sectors listed in Table 5, made by the IO industries, e.g., construction and agricultural sectors, corresponding to the NAQETR source categories:

IO 1997 Sector name Shares of output 324110 Petroleum refineries 89.5% 324121 Asphalt paving mixture and block manufacturing 3.4% 324122 Asphalt shingle and coating materials manufacturing 2.7% 324191 Petroleum lubricating oil and grease manufacturing 3.4% 324199 All other petroleum and coal products manufacturing 1.0%

Table 5: Petroleum and coal product manufacturing sectors and their shares of output These sectors are included in the 324 “Petroleum and coal product manufacturing” subsector which is based on the transformation of crude petroleum and coal into usable products [Census 2005a]. The main process is petroleum refining that involves the separation of crude petroleum into component products through technologies like cracking and distillation. It was assumed that all types of petroleum fuels included in the EIO-LCA model (motor gasoline, diesel fuel, kerosene, aviation fuel, jet fuel, light and heavy fuel oil) were produced by the chosen five sectors. Since the purchases included all petroleum products another allocation was necessary to estimate the amount spent on motor gasoline and diesel by the on-road and non-road transportation sources. The ratio of sectoral fuel use factors (given in TJ per $million output, described in the document “Calculation of the electricity and fuel use data in the 1997 update of EIO-LCA”) was used to do the allocation. As an example, the calculations for the NAQETR source category “Transportation – Non-road engines and vehicles – farm” are shown below. In this case, light fuel oil (LFO) consumption factors were used instead of the usage of diesel fuel because the latter was zero for all agricultural sectors. Table 6 presents the use table entries for the agricultural IO sectors [BEA 1997b].

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Use table entries, [million dollars] EPA Source

category IO

1997 Sector name IO

324110 IO

324121 IO

324122 IO

324191 IO

324199

Total, [million$]

1111A0 Oilseed farming

621.4 0 0 16.3 0 637.7

1111B0 Grain farming 1075.6 0 0 23.7 0 1099.3

111200 Vegetable and melon farming

242.9 0 0 7.4 0 250.3

111335 Tree nut farming

47.4 0 0 1.3 0 48.7

1113A0 Fruit farming 240.5 0 0 5.9 0 246.4

111400 Greenhouse and nursery production

172.6 0 0 5.4 0 178.0

111910 Tobacco farming

144.5 0 0 3.4 0 147.9

111920 Cotton farming

217.8 0 0 4.5 0 222.3

1119A0 Sugarcane and sugar beet farming

88.5 0 0 2.4 0 90.9

1119B0 All other crop farming

652.5 0 0 14 0 666.5

Transportation – Non-road engines and vehicles – farm

112100 Cattle ranching and farming

1200.5 0 0 10.5 0 1211.0

Table 6: Use of petroleum products for agricultural sectors [BEA 1997b] Table 7 includes the calculations of the ratio of sectoral fuel use factors.

Sectoral fuel use factors (EIO-LCA), [TJ/dollar millions]

IO 1997 Motor gasoline

Diesel fuel

Kerosene Aviation fuel

Jet fuel

LFO HFO Sum MotGas/Sum LFO/Sum

1111A0 0.758 0 0.006 0.002 0 0.171 0.006 0.942 0.804 0.181 1111B0 1.283 0 0.011 0.003 0 0.243 0.011 1.552 0.827 0.157 111200 1.286 0 0.008 0.002 0 0.245 0.007 1.550 0.830 0.158 111335 0.205 0 0.281 0.056 0 0.524 0.173 1.238 0.165 0.423 1113A0 1.144 0 1.863 0.260 0 1.871 0.824 5.961 0.192 0.314 111400 0.459 0 0.039 0.011 0 0.096 0.018 0.623 0.736 0.154 111910 0.315 0 0.403 0.057 0 0.307 0.175 1.257 0.251 0.244 111920 0.239 0 0.000 0.000 0 0.079 0.000 0.318 0.753 0.247 1119A0 0.419 0 0.000 0.000 0 0.113 0.000 0.531 0.788 0.212 1119B0 1.649 0 0.301 0.049 0 0.849 0.144 2.991 0.551 0.284 112100 0.032 0 0.005 0.001 0 0.010 0.002 0.051 0.636 0.203

Table 7: Example for the calculation of the ratio of sectoral fuel use factors (LFO = light fuel oil, HFO = heavy fuel oil)

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The total purchase values obtained from the use table were multiplied with the ratios in column “MotGas/Sum” and “LFO/Sum” to get the amount spent on motor gasoline and LFO by the IO sectors. Then the volume of motor gasoline and LFO was estimated using the following wholesale prices: Motor gasoline: $0.70/gal (average of monthly prices for 1997) [EIA 1997a]

LFO: $0.39/gal [EIA 1997b]

For example, the motor gasoline and LFO consumption of IO sector 1111A0 “Oilseed farming” was calculated as shown in Figure 2.

Figure 7: Motor gasoline and Light Fuel Oil (LFO) use of the Oilseed farming sector

The ratio of estimated volume of gasoline used by one IO sector, e.g., 1111A0, to the total amount of gasoline used by the aggregated sector (in this case the agricultural sector) was then used to allocate the emission estimates to sectors. The same calculation was done for LFO. Table 8 presents the calculations described above for the agricultural sectors’ CO emissions.

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IO 1997 gasoline use,

[gal] LFO use, [gal]

CO from gasoline,

[sht] 1111A0 731,767,074 294,323,077 61,229 1111B0 1,298,757,173 450,994,872 108,670 111200 296,368,725 102,687,179 24,798 111335 11,327,715 52,446,154 948 1113A0 67,667,872 195,856,410 5,662 111400 187,170,041 68,461,538 15,661 111910 53,024,737 91,015,385 4,437 111920 239,630,639 142,500,000 20,050 1119A0 102,379,621 48,946,154 8,566 1119B0 525,045,679 478,512,821 43,932 112100 1,100,084,847 621,025,641 92,047 sum 4,613,224,122 2,546,769,231 386,000*

229,61122,224,613,4

074,767,731*000,386 =

*Note: Emission estimate from the National Air Quality and Emissions Trends Report (EPA 1999b)

Table 8: Example for allocation of CO emission to agricultural sectors For the construction sectors, the diesel consumption factors were used to do the same calculations, with the wholesale price $0.60/gal [EIA 1997c]. Then all estimated emissions were summed and converted into metric tons (1 short ton = 0.9072 metric ton) to get total annual releases for all industries for 1999. These estimates were compared to those provided by the NAQETR [EPA 1999b]. Table 9 presents the results of the comparison. The group of emissions referred as “not allocated” incorporates all source categories of the NAQETR that could not be mapped to any IO industry, e.g., Residential wood combustion.

CO NOx SO2 PM10 VOC Lead

Total for all IO sectors, thousand metric tons 42,558 16,636 14,810 2,729 7,137 3,104 EPA estimates for 1999, thousand short tons 117,229 23,671 17,651 21,632 19,378 4,199 EPA estimates for 1999, thousand metric tons 106,348 21,474 16,013 19,624 17,579 3,809 Not allocated, thousand metric tons 56,160 3,629 2,941 12,538 8,984 588 (EPA - not allocated)/Total for all sectors 1.18 1.07 0.88 2.60 1.20 1.04

Table 9: Comparison of estimated total sectoral emissions for 1999 to the EPA estimates [EPA 1999b]

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The estimated total PM10 emission in the EIO-LCA model differs from that provided by the EPA by a factor of 3. This resulted from the large amount of fugitive dust emission (58% of total PM10 emission in 1999) that could not be allocated to any IO sector. Finally, the emissions from gasoline and diesel fuel or LFO use were summed in every sector and divided by the industrial sector outputs for 1997 in order to obtain the emission factors in metric ton per $million output. The industry outputs are presented in Appendix 2 “Total industry outputs for 1997”. 4. CALCULATION OF THE TOXICS RELEASE INVENTORY DATA IN THE 1997 UPDATE OF

EIO-LCA The U.S. EPA Toxics Release Inventory (TRI) data for 2000 were used to update the toxic emission data for the 1997 benchmark EIO-LCA model [TRI 2000a]. The data are publicly available on the EPA website [TRI 2000a]. It is based on Standard Industry Classification (SIC) codes. Units are given in grams for dioxin and dioxin compounds, and in pounds for all the other chemicals. Table 10 lists the names of fields of the national database that were used to estimate the TRI emissions for 2000 [TRI 2000b] in EIO-LCA. Figure 8 presents an excerpt of the TRI database.

Field name EIO-LCA emission category

Primary SIC code

CAS number

Chemical name

Unit of measure

Total fugitive air emissions Non-Point Air

Total stack air emissions Point Air

Total air emissions Air Releases

Total surface water discharge Water Releases

Total underground injection U’ground Releases

Total on-site land releases Land releases

Transfers to POTWs (metals and metal compounds) POTW Transfers

Total transferred off-site to disposal Offsite Transfers

Transfers to POTWs (non-metals) POTW Transfers

Table 10: Fields of the TRI Database Used to Update the EIO-LCA

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Figure 8: Excerpt of the SIC-based TRI data used to update the EIO-LCA

The SIC-NAICS-IO 1997 bridge described earlier was used to obtain estimates of the toxic releases for the input-output sectors. All emissions were then converted into pounds (1 gram = 0.0022046 pound) and summed to get total annual toxic releases for all industries. Then these estimates were compared to those provided by the U.S. EPA TRI Explorer for 2000 [TRI 2005a]. Table 11 presents the results of the comparison. Our estimates differ from those provided by the EPA by less than 11% for all toxic release categories. The differences resulted most likely from (1) transferring the SIC-based TRI data through the SIC – NAICS bridge and (2) the data on TRI Explorer are more recent than those included in the 2000 database. The TRI Explorer is updated at least two times a year using the latest revised facility data [TRI 2005b].

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Air

Releases Water

Releases U’ground Releases

Land Releases

Total Releases

Offsite Transfers

POTW Transfers

Total All

Total for all I-O sectors, [106 lb]

1,917.2 262.3 303.4 4,127.6 6,610.5 618.5 361.7 7,590.7

EPA estimate, [106 lb]

1,920.5 267.8 279.2 3,664.5 6,132.0 616.3 344.4 7,093.2

EPA/Total 1.00 1.02 0.92 0.89 0.93 1.00 0.95 0.93

Table 11: Comparison of estimated total sectoral toxic releases for 2000 to the EPA estimates [TRI 2000a]

The sectoral estimates were then converted into metric tons (1 pound = 0.0004536 metric ton). The emission factors in metric tons per million U.S. dollars of output were obtained dividing the emission estimates by the corresponding industrial outputs for all industries except the IO 221100 “Power generation and supply” sector. Electricity generators, whether private, federal, state or local government facilities, report under the same SIC codes (SIC 4911, 4931, and 4939) [BEA 1997]; this means that all emissions get mapped into the same IO sector (#221100). Thus the estimated toxic releases of the IO 221100 “Power generation and supply” sector were divided by the sum of the outputs of three industries: IO S00101 “Federal electric utilities”, S00202 “State and local government electric utilities”, and the IO 221100 sector. This is convenient because the input-output table is not useful for the Federal and state utility sectors listed above (i.e., they have no requirement multipliers) so all results are contained in one sector.

5. CALCULATION OF THE GREENHOUSE GAS EMISSIONS DATA IN THE 1997 UPDATE OF EIO-LCA The greenhouse gas emissions data was estimated using heating values and emission factors from the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories [IPCC 1996], the Transportation Energy Data Book (edition 19) [DOE 1999], the U.S. EPA’s Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001 [EPA 2003b], and sectoral fuel use data of the updated 1997 industry benchmark EIO-LCA model (see Section 6). The emission factors from [IPCC 1996] are presented in Table 12.

Fuel CO2,

[mt/mt] Coal 2.6798 Natural gas 2.7500 LNG 2.9641 LPG 2.9837

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Motor gasoline 3.1723 Diesel fuel 3.1723 Kerosene 3.1832 Aviation fuel 3.1046 Jet fuel 3.1882 LFO 3.1766 HFO 3.1094

Table 12: Fuel Emission factors [IPCC 1996] The sectoral use of fuels in metric ton was calculated from the energy database of the updated 1997 industry benchmark EIO-LCA model using heating values presented in Table 13:

useHV

E=

!

!

3

6

10

10

where E = sectoral energy use factor of the updated EIO-LCA model, in TJ HV = heating value, in MJ/kg from Table 2

use = sectoral use of fuel, in metric ton

Fuel Heating value, [MJ/kg] Coal 24 Natural gas 57 LNG 47 LPG 50 Motor gasoline 47 Diesel fuel 46 Kerosene 46 Aviation fuel 47 Jet fuel 47 LFO 46 HFO 44

Table 13: Fuel Heating values [EPA 2003a and DOE 1999] The sectoral emissions of CO2 were estimated using the emission factors listed in Table 1. The sectoral emissions of halocarbons were estimated using the Toxics Release Inventory (TRI) data of the updated 1997 industry benchmark EIO-LCA model (see Section 4). Since 1987, when the Montreal Protocol froze the production and consumption levels of CFCs and of halons, the consumption of ozone depleting substances has been undergoing a phase-out [UNEP 2000 and EPA 2003b]. However, because these chemicals are highly potent greenhouse gases and some of them are still in use, we decided to include them in the

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updated EIO-LCA model. For example, the production of HCFC-22 has increased 30 percent between 1990 and 1998, and its GWP is 1,700 [UNEP 2000]. Class I and II ozone-depleting chemicals (CFCs and HCFCs) were exported from the TRI database [ODS 2002] as shown in Tables 14 and 15.

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Chemical Name CAS Number Chemical Name CAS Number

CFC-11 (CCl3F) 75694 CFC-211 (C3FCl7) 422786 Trichlorofluoromethane Heptachlorofluoropropane CFC-12 (CCl2F2) 75718 CFC-212 (C3F2Cl6) 3182261 Dichlorodifluoromethane Hexachlorodifluoropropane CFC-113 (C2F3Cl3) 76131 CFC-213 (C3F3Cl5) 6/5/2354 1,1,2-Trichlorotrifluoroethane Pentachlorotrifluoropropane CFC-114 (C2F4Cl2) 76142 CFC-214 (C3F4Cl4) 29255310 Dichlorotetrafluoroethane Tetrachlorotetrafluoropropane CFC-115 (C2F5Cl) 76153 CFC-215 (C3F5Cl3) 4259432 Monochloropentafluoroethane Trichloropentafluoropropane Halon 1211 (CF2ClBr) 353593 CFC-216 (C3F6Cl2) 661972 Bromochlorodifluoromethane Dichlorohexafluoropropane Halon 1301 (CF3Br) 75638 CFC-217 (C3F7Cl) 422866 Bromotrifluoromethane Chloroheptafluoropropane Halon 2402 (C2F4Br2) 124732 CCI4 56235 Dibromotetrafluoroethane Carbon tetrachloride

CFC-13 (CF3Cl) 75729 Methyl Chloroform (C2H3Cl3)

71556

Chlorotrifluoromethane 1,1,1-trichloroethane CFC-111 (C2FCl5) 354563 Methyl Bromide (CH3Br) 74839 Pentachlorofluoroethane CFC-112 (C2F2Cl4) 76120 Tetrachlorodifluoroethane Table 14: Class I Ozone Depleting Chemicals Included in EIO-LCA 1997.

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Chemical Name CAS Number Chemical Name CAS Number

HCFC-21 (CHFCl2) 75434 HCFC-225cb (C3HF5Cl2) 507551 Dichlorofluoromethane Dichloropentafluoropropane HCFC-22 (CHF2Cl) 75456 HCFC-226 (C3HF6Cl) 431878 Monochlorodifluoromethane Monochlorohexafluoropropane HCFC-31 (CH2FCl) 593704 HCFC-231 (C3H2FCl5) 421943 Monochlorofluoromethane Pentachlorofluoropropane HCFC-121 (C2HFCl4) 354143 HCFC-232 (C3H2F2Cl4) 460899 Tetrachlorofluoroethane Tetrachlorodifluoropropane HCFC-122 (C2HF2Cl3) 354212 HCFC-233 (C3H2F3Cl3) 7125840 Trichlorodifluoroethane Trichlorotrifluoropropane HCFC-123 (C2HF3Cl2) 306832 HCFC-234 (C3H2F4Cl2) 425945 Dichlorotrifluoroethane Dichlorotetrafluoropropane HCFC-124 (C2HF4Cl) 2837890 HCFC-235 (C3H2F5Cl) 460924 Monochlorotetrafluoroethane Monochloropentafluoropropane HCFC-131 (C2H2FCl3) 359284 HCFC-241 (C3H3FCl4) 666273 Trichlorofluoroethane Tetrachlorofluoropropane HCFC-132b (C2H2F2Cl2) 1649087 HCFC-242 (C3H3F2Cl3) 460639 Dichlorodifluoroethane Trichlorodifluoropropane HCFC-133a (C2H2F3Cl) 75887 HCFC-243 (C3H3F3Cl2) 460695 Monochlorotrifluoroethane Dichlorotrifluoropropane HCFC-141b (C2H3FCl2) 1717006 HCFC-244 (C3H3F4Cl) Dichlorofluoroethane Monochlorotetrafluoropropane HCFC-142b (C2H3F2Cl) 75683 HCFC-251 (C3H4FCl3) 421410 Monochlorodifluoroethane Trichlorofluoropropane HCFC-221 (C3HFCl6) 422264 HCFC-252 (C3H4F2Cl2) 819001 Hexachlorofluoropropane Dichlorodifluoropropane HCFC-222 (C3HF2Cl5) 422491 HCFC-253 (C3H4F3Cl) 460355 Pentachlorodifluoropropane Monochlorotrifluoropropane HCFC-223 (C3HF3Cl4) 422526 HCFC-261 (C3H5FCl2) 420973 Tetrachlorotrifluoropropane Dichlorofluoropropane HCFC-224 (C3HF4Cl3) 422548 HCFC-262 (C3H5F2Cl) 4210203 Trichlorotetrafluoropropane Monochlorodifluoropropane HCFC-225ca (C3HF5Cl2) 422560 HCFC-271 (C3H6FCl) 430557 Dichloropentafluoropropane Monochlorofluoropropane Table 15: Class II Ozone Depleting Chemicals Included in EIO-LCA 1997. The total global warming potential in metric tons of CO2 equivalent for each sector was estimated using 100-year GWP values given in the IPCC Third Assessment Report: Climate Change 2001 [ODS 2002]. The IPCC defined GWP as “the ratio of the time-integrated radiative forcing from the instantaneous release of 1 kg of a trace substance relative to that of 1 kg of a reference gas” [IPCC 2001]. In practice, these GWP values represent weighting factors for greenhouse gases as compare to CO2. Table 16 shows the GWP values used for greenhouse gases and class I and II ozone-depleting chemicals for which GWP was available.

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Gas 100-year GWP CO2 1 CH4 23 N2O 296 CAS number 000075729 14,000 000075718 10,600 000076142 9,800 000076153 7,200 000075638 6,900 000076131 6,000 000075694 4,600 000075683 2,400 000056235 1,800 000075456 1,700 000353593 1,300 001717006 700 000507551 620 002837890 620 000075434 210 000422560 180 000071556 140 000306832 120 000074839 5

Table 16: 100-year global warming potential values for greenhouse gases and class I and II ozone depleting substances [ODS 2002]

The sectoral total greenhouse gas emission values then were compared and adjusted to the EPA’s estimates for year 1997 included in the EPA 2003 inventory [EPA 2003b]. In the cases of CO2 and halocarbons our objective was to map the EPA emission sources to IO 1997 industrial activities and substitute our estimates with the EPA data where it was possible and necessary. Since we did not have good data on CH4 and N2O, we used only the EPA estimates. They were allocated to the IO sectors listed in Appendix 4, and we assumed that the emission of all other industries were 0. Appendix 4 presents the source categories that were linked to IO 1997 sectors and where adjustments were made. In general, if the emission of one source category was mapped to many IO sectors, the ratio of sectoral total outputs (from Appendix 2) was used as weighting factor.

23

Since approximately 50% of the CO2 emissions of the transportation activities resulted from motor gasoline use by personal vehicles [EPA 2003b], and they are not included in the EIO-LCA model since they are private consumption, only one-half of that emission was distributed between the transportation, wholesale and retail trade sectors. The GHG emission of IO1997 sector 814000 “Private households” was assumed to be 0. The modified emission data were summed to obtain total sectoral GHG emissions and they were compared again to the EPA estimates. Table 17 shows the results of the comparison. In this table, the Error row represents an allocation of unmapped GHG emissions. That is, Error is:

Error = estimateEPA

emissionGHGallocatedNottotalEstimated +!1

where the “Not allocated GHG emission” incorporates all emission estimates provided by the EPA’s sources and sinks report that cannot be mapped to any IO 1997 sector.

CO2 CH4 N2O CFCs, HCFCs Estimated total for all IO sectors, [Tg CO2 eq.] 4,273.8 595.3 307.6 73.2 EPA estimates, [Tg CO2 eq.] 5,595.8 689.5 421.0 116.8 Error 0.02 0.00 0.00 0.21

Table 17: Comparison of estimated total sectoral GHG emissions for 1997 after adjustment to the EPA estimates [EPA 2003b]

Once data for all GWP categories (CO2, CH4, N2O, HCFCs and CFCs) were validated with the above adjustments, the emission estimates were divided by the industrial sector outputs for 1997 in order to obtain the emission factors in metric tons of CO2 equivalent per $million output. 6. CALCULATION OF THE ELECTRICITY AND FUEL USE DATA IN THE 1997 UPDATE OF EIO-LCA The energy data used in EIO-LCA is derived from several primary sources, generally for four aggregated sectors, as described below: 1. Mineral sectors 2. Manufacturing sectors 3. Transportation sectors 4. All other sectors

24

6.1 Mineral Sectors The mineral sectors group includes the following industries: 211000 Oil and gas extraction 212100 Coal mining 212210 Iron ore mining 212230 Copper, nickel, lead, and zinc mining 2122A0 Gold, silver, and other metal ore mining 212310 Stone mining and quarrying 212320 Sand, gravel, clay, and refractory mining 212390 Other nonmetallic mineral mining 213111 Drilling oil and gas wells 213112 Support activities for oil and gas operations 21311A Support activities for other mining For the mineral sectors, the 1997 Fuel and Electric Energy Report published by the U.S. Census Bureau [Census 2002b] was used. This document reports fuel and electricity usage in physical units (e.g., short ton, barrel, cubic feet, gallon and kWh) for the 211 through 213 NAICS industry subsectors for 1997. Fuels presented in this report included electricity, coal, natural gas, distillate fuel oil, and residual fuel oil. Table 18 presents an excerpt of data included in the report.

Natural Gas Gasoline Quantity Cost Quantity Cost

NAICS code Description (109 cubic feet) ($1,000) (106 gallons) ($1,000)

All mineral industries . . . . . . . . . . . . . . . 353 904,984 244 272,715

211 Oil and gas extraction . . . . . . . . . . . . . . 230.2 597,596 100.2 107,499 2111 Oil and gas extraction . . . . . . . . . . . . . . 230.2 597,596 100.2 107,499

21111 Oil and gas extraction . . . . . . . . . . . . . . 230.2 597,596 100.2 107,499 211111 Crude petroleum and natural gas extraction 169.7 459,812 98.3 105,255 211112 Natural gas liquid extraction. . . . . . . . . . . . 60.5 137,784 1.9 2,244

Table 18: Excerpt of data from the Fuel and Electric Energy Report [Census 2002b] The NAICS-IO 1997 bridge (Section 2) was used to estimate the fuel use of I-O sectors. Then the sectoral fuel use was calculated in terajoules (TJ) using the conversion factors shown in Table 19 [EPA 2003a]:

25

Fuel Conversion factor Coal 20.2538*106 BTU/short ton Natural gas 1,027 BTU/cubic foot LNG 3.777*106 BTU/barrel LPG 5.825*106 BTU/barrel Motor gasoline 5.253*106 BTU/barrel Diesel fuel 5.825*106 BTU/barrel Kerosene 5.670*106 BTU/barrel Aviation fuel 5.048*106 BTU/barrel Jet fuel 5.670*106 BTU/barrel LFO 5.825*106 BTU/barrel HFO 6.287*106 BTU/barrel Table 19: Conversion factors [EPA 2003a]

The conversion factor of 947.8 million BTU/TJ was used to convert to metric units. Finally, the use of fuels for each sector were divided by the industry outputs to obtain the fuel use factors in TJ/$million. The industry outputs are presented in Appendix 2. 6.2 Manufacturing sectors (all sectors from IO 311111 to IO 33999A)

The electricity and fuel use of manufacturing sectors were estimated using the 1998 Manufacturing Energy Consumption Survey (MECS) [EIA 2002]. This report presents fuel and electricity usage in trillion BTU, in 2- and 4-digit SIC forms, with the same fuels as above. Table 20 presents an excerpt of data reported in MECS.

SIC Code

Major Group and Industry

Total Net

Electricity Residual Fuel Oil

Distillate Fuel Oil

Natural Gas

LPG and NGL

Coal Coke and

Breeze Other

20 Food and Kindred Products 1,118 230 15 18 603 6 144 2 100

21 Tobacco Products 26 5 1 * 6 * 14 0 *

22 Textile Mill Products 313 122 16 6 129 2 22 0 17

23 Apparel and Other Textile Products

45 18 * 1 24 * 2 0 *

24 Lumber and Wood Products 589 88 1 34 77 5 2 0 383

25 Furniture and Fixtures 79 26 * 1 25 1 2 0 24

26 Paper and Allied Products 2,761 251 151 9 589 6 277 0 1,478

2621 Paper Mills 1,227 124 92 4 233 2 143 0 629

2631 Paperboard Mills 945 51 35 2 225 1 97 0 535

Table 20: Excerpt of data reported in MECS [EIA 2002]

26

Those sectors listed only in 2-digit SIC form were mapped to 4-digit form by a weighted average method utilizing the 1992 fuel consumption data. The 1992 fuel use data in the EIO-LCA model were estimated from workfiles provided by the Bureau of Economic Analysis (BEA).Unfortunately, these workfiles are no longer publicly available with the benchmark input-output accounts. We used the SIC – NAICS – IO 1997 bridge to estimate the fuel use of 1997 I-O sectors. After that, all sectoral consumption data were converted into TJ, using the same conversion factor as above. Since MECS is available only for 1998 and our objective was to estimate the sectoral fuel use for 1997, we used the ratio of annual industry output for 1997 and for 1998, given for 18 aggregated NAICS-based IO sectors in millions of US dollars, as a deflation rate to obtain the energy consumption estimates for the year 1997 [BEA 2005]:

1998

1998

1997

1997

i

i

i

i EOutput

OutputE !=

where 1997

iE = electricity and fuel use of sector i in 1997

1998

iE = electricity and fuel use of sector i in 1998

1997

iOutput = annual output of sector i in 1997

1998

iOutput = annual output of sector i in 1998

Table 21 presents the estimated deflation rates.

NAICS-based IO sector Total Sector

Output $billion, 1998

Total Sector Output $billion,

1997

Output Deflator

Agriculture, forestry, fishing, and hunting 270.7 258.3 1.05 Mining 169.7 143.3 1.18 Utilities 289.9 291.9 0.99 Construction 676 730.8 0.93 Manufacturing 3779.7 3846.1 0.98 Wholesale trade 754 767.8 0.98 Retail trade 830.1 874.5 0.95 Transportation and warehousing 503.6 533.5 0.94 Information 669.5 758.8 0.88 Finance, insurance, real estate, rental, and leasing 2427.7 2593.3 0.94 Professional and business services 1333.7 1494.9 0.89 Management of companies and enterprises 242 260.5 0.93 Administrative and waste management services 348.2 394.3 0.88 Educational services, health care, and social assistance 927.9 984.4 0.94 Arts, entertainment, recreation, accommodation, and food services 533.8 562.8 0.95 Other services, except government 348 379.2 0.92 Federal government 541.4 540.5 1.00 State and local government 1085.5 1145 0.95

27

Table 21: Deflation rates used to estimate electricity and fuel use of manufacturing sectors for 1997

All 6-digit IO 1997 manufacturing sectors were covered by the MECS except the following six: IO 1997 Sector name 315190 Other apparel knitting mills 325314 Fertilizer, mixing only, manufacturing 331210 Iron, steel pipe and tube from purchased steel 33152B Nonferrous foundries, except aluminum 334611 Software reproducing 339116 Dental laboratories The energy consumption for these sectors was estimated from the 1997 use of the following commodities by the industries listed above. The data were obtained from the "Use of Commodities by Industries" table provided by the BEA [BEA 1997b]: Fuel IO 1997 Sector name

Coal 212100 Coal mining electricity 221100 Power generation and supply natural gas 221200 Natural gas distribution motor gasoline, diesel fuel, liquefied petroleum gas, kerosene, aviation fuel, jet fuel, light and heavy fuel oil

324110 Petroleum refineries

The sectoral economic values of consumption of coal, electricity, and natural gas were divided by the corresponding wholesale prices listed below to obtain the resource use in physical units. Coal: $32.4/short ton (average delivered price for industrial plants in 1997) [EIA 1997d] Electricity: industrial user ¢4.3/kWh, commercial and financial users ¢7.6/kWh [EIA

1997c] Natural gas: industrial user: $3.59/thousand cubic feet, commercial and financial users:

$5.8/thousand cubic feet, electric power price: $2.78/ thousand cubic feet [EIA 1997f] The following heat contents, provided in the Transportation Energy Data Book (edition 19), published by the U.S. Department of Energy [DOE 1999e, Table B.1], and the conversion factor of 947.8 million BTU/TJ was used to estimate the sectoral energy consumption in terajoules:

28

Coal: 21.015 × 106 BTU/short ton Natural gas: 1,027 BTU/ft3 Since we could estimate only the total petroleum use from the commodity use table, the sectoral consumption of the different petroleum products, e.g., motor gasoline, was calculated based on the fuel use data in the 1992 industry benchmark EIO-LCA model, estimated from the BEA's workfiles. The database includes the usage of motor gasoline, LPG, kerosene, aviation fuel, jet fuel, LFO and HFO for all 485 IO1992 industries in metric ton. The IO 1992 - SIC - NAICS - IO 1997 bridge was used to estimate the fuel consumption of the IO 1997 industries, and all data were converted into US dollars using the following wholesale prices [EIA 1991]: Motor gasoline: $239.70/mt LPG: $193.22/mt Kerosene: $188.61/mt Aviation fuel: $339.06/mt Jet fuel: $250.00/mt Light fuel oil: $175.43/mt Heavy fuel oil: $118.32/mt Then the ratio of the sectoral usage of one product to the total petroleum consumption of the same sector was used to partition the 1997 use table data among the petroleum product categories. Figures 9 and 10 illustrate the calculations described above.

29

Figure 9: Estimation of fuel use of the IO 315190 "Other apparel knitting mills" sector

Fuel use data in 1992 industry benchmark

EIO-LCA model

The IO 1992 – SIC – NAICS – IO 1997

bridge

The 1992 fuel use data allocated to IO

1997 sectors

30

Figure 10: Estimation of the apportionment of total petroleum use of the IO 315190

"Other apparel knitting mills" sector

The 1992 fuel use data allocated to IO

1997 sectors

31

The estimated proportion of the different petroleum products was then multiplied by the total sectoral petroleum purchase obtained from the use table. Once the economic value of the use of petroleum products was calculated, the sectoral consumption in terajoules was estimated applying the same method as described above using the following wholesale prices and heating values [DOE 1999, Table B.1]: Motor gasoline: $0.70/gallon (average of monthly prices for 1997) [EIA 1997a] LPG: $0.68/gal [EIA 2001] Kerosene: $0.65/gallon [EIA 2004] Aviation fuel: $1.07/gallon [EIA 2004] Jet fuel: $0.61/gallon [EIA 2004] Light fuel oil: $0.39/gallon [EIA 1997e] Heavy fuel oil: $0.42/gallon [EIA 1997b] Motor gasoline: 125,000 BTU/gal LPG: 5.825 × 106 BTU/bbl [EPA 2003a] Kerosene: 135,000 BTU/gal Aviation fuel: 120,200 BTU/gal Jet fuel: 127,500 BTU/gal LFO: 138,700 BTU/gal HFO: 149,700 BTU/gal Figure 11 illustrates the estimations described above.

32

Figure 11: Estimation of the use of LPG of the IO 315190 "Other apparel knitting mills" sector

LPG: 5.825 × 106 BTU/bbl 1 barrel = 42 gallon

1 TJ = 947.8 million BTU

Purchase from IO sector 324110 made by 315190 in 1997 = $7.94 million (from use

table, allocated using 1992 data)

LPG: $0.68/gal

Use of LPG in gallon by sector 315190 =

gal

gal

million35.882,705,29

68.0$

2.20$=

Use of LPG in TJ by sector 315190 =

TJ

TJ

BTUbbl

BTU

bbl

gal

gal83.346,4

108.947

110825.5

42

35.882,705,29

6

6=

!

!!!

33

Finally, the sectoral use of fuels were divided by the corresponding outputs to obtain the fuel use factors in TJ/$million.

6.3 Transportation sectors (IO 420000 – IO 4A0000) The following industries are included in the transportation sectors group:

420000 Wholesale trade 481000 Air transportation 482000 Rail transportation 483000 Water transportation 484000 Truck transportation 485000 Transit and ground passenger transportation 486000 Pipeline transportation 48A000 Scenic and sightseeing transportation and support activities for transportation 491000 Postal service 492000 Couriers and messengers 493000 Warehousing and storage 4A0000 Retail trade

Energy use of the transportation sectors in 1997 was estimated using data from the Transportation Energy Data Book (edition 19), published by the U.S. Department of Energy [USDOE 1999, Table 2.5] which reports consumption of energy by fuel type and transportation mode in trillion BTUs for 1997. The modes include Highway (auto, motorcycle, bus, light truck, other truck) and Non-Highway modes (air, water, pipeline, and rail) of transportation. Fuels presented were gasoline, diesel fuel, liquefied petroleum gas, jet fuel, residual fuel oil, natural gas, and electricity. Energy use by automobiles, motorcycles, and light trucks were assumed to be out of scope and excluded since these vehicles are not generally used for production of goods and services. Table 22 presents an excerpt of data included in the Transportation Energy Data Book.

Electricity Natural

Gas LPG

Motor Gasoline

Diesel Fuel Jet

Fuel Residual Fuel Oil

Buses 0.9 3.4 0.5 32.2 147.0 0.0 0.0 Other trucks 0.0 0.0 13.6 604.8 3,450.8 0.0 0.0 Air 0.0 0.0 0.0 34.8 0.0 2,290.0 0.0 Water (except recreational)

0.0 0.0 0.0 0.0 292.3 0.0 717.0

Pipeline 212.1 774.9 0.0 0.0 0.0 0.0 0.0 Rail 61.0 0.0 0.0 0.0 517.9 0.0 0.0

Table 22: Excerpt of data from Transportation Energy Data Book [DOE 1999], all values in trillion BTU

34

All energy usage from “Other trucks” was distributed between the sectors included in the U.S. Transportation Satellite Accounts for 1996 (TSA), published by the Bureau of Economic Analysis [BEA 2000]. The TSA provide the estimated use of different transportation commodities incorporated in the regular input-output use table and the use of one additional commodity, the own-account transportation activities for 101 aggregated industries, such as "Livestock and livestock products" [BEA 2000]. Own-account transportation includes all transportation activities within a non-transportation industry that support the production processes, e.g., the trucks owned and used by a company as opposed to that company paying a trucking company for the same services. We assumed that trucks provided all own-account transportation. The use of "Motor freight transportation and warehousing" and "Own-account transportation" commodities were summed for the sectors. Then the use of "Motor freight transportation and warehousing" was divided by the sum of total use of "Motor freight transportation and warehousing" and the total use of "Own-account transportation". The individual shares of "Truck transportation" and "Warehousing and storage" industries were calculated using the ratio of sectoral outputs as weighting factor. Similar allocation method was used to proportionate the use of "Own-account transportation" commodity and estimate the shares of other industries. Figure 12 illustrates the calculations described above.

35

Figure 12: Illustration of the allocation method used for proportionate the diesel fuel

used by "Other trucks"

36

Energy usage for pipelines was mapped to the sectors 'Natural gas distribution' and ‘Pipeline transportation’ because the latter does not include the transmission and distribution of natural gas to final consumers, which also involves use of pipelines [Census 2005b]. Since the majority of freight-rails are powered by diesel fuel the electricity usage from rail travel was mapped to the ‘Transit and ground passenger transportation’ sector and all diesel fuel usage went to ‘Rail transportation’ sector [DoT 2004; AAR 2004]. All energy usage for buses was mapped to the ‘Transit and ground passenger transportation’ and ‘Scenic and sightseeing transportation and support activities for transportation’ sectors using the ratio of sectoral outputs as weighting factor. All sectoral consumption data were converted into TJ. Finally, the sectoral use of fuels were divided by the corresponding industry outputs (from Appendix 2) to obtain the fuel use factors in TJ/$million. 6.4 All other sectors The electricity and fuel use of the 126 sectors which were not covered by the reports above were estimated using the same method described in 6.2, the estimation of electricity and fuel consumption of the 6 sectors not included in MECS.

6.5 Changes in Fuel Categories and Data Validation

The data sources used to conduct the calculations described above provided information about the consumption of either distillate fuel or diesel fuel. There was no additional information available to decide sector-by-sector about the type of distillate fuel, i.e., diesel fuel, light fuel oil. Thus, all sectoral consumption estimates for diesel and distillate fuel oil were included in one category, called "Distillate fuel". The annual consumption of aviation fuel was almost negligible compared to the use of jet fuel (5% of the sum of the use of jet and aviation fuels) [EIA 2004]. Thus all sectoral consumption estimates for aviation fuel were included in the fuel category "Jet fuel". The total consumption of electricity and fuels were calculated after estimating energy use factors for all IO sectors, and they were compared to EIA data. Table 23 presents the results of the comparison.

37

Fuel EIA Data Total for all IO sectors Total/EIA

Electricity, MkWh 2,070,000 2,054,220 0.99 Coal, TJ 21,986,848 22,277,943 1.01 Natural Gas, TJ 19,237,559 16,425,634 0.85 LPG, TJ 3,788,801 2,103,284 0.56 Motor Gas, TJ 16,215,908 2,650,943 0.16* Distillate Fuel, TJ 6,785,744 6,925,062 1.02 Kerosene, TJ 45,854 29,239 0.64 Jet Fuel, TJ 3,539,503 2,840,750 0.8 HFO, TJ 1,927,226 2,156,410 1.12

*Note that the EIO-LCA model does not include personal vehicle use that consumes approximately 95% of motor gasoline [EIA 2004].

Table 23: Comparison of the estimated total sectoral electricity and fuel use for 1997 to

the EIA estimates [EIA 2004]

38

7. References [AAR 2004] Association of American Railroads, Railroads Announce Surge in Intermodal

and Carload Freight, http://www.tomorrowsrailroads.org/media/display_release.cfm?ID=249, accessed August 14, 2005

[BEA 1997a] U.S. Department of Commerce, Bureau of Economic Analysis, Benchmark

Input-Output Data, http://www.bea.gov/bea/dn2/i-o.htm#benchmark; accessed February 14, 2005

[BEA 1997b] U.S. Department of Commerce, Bureau of Economic Analysis, The Use of

Commodities by Industries after Redefinitions (1987, 1992, 1997) http://www.bea.gov/bea/industry/iotables/prod/options_list.cfm?aggregations_id=0&get_results=show&goto=go_to_options&anon=145&CFID=8566&CFTOKEN=52734464; accessed February 7, 2005

[BEA 2000] U.S. Department of Commerce, Bureau of Economic Analysis,, Survey of

current business – U.S. Transportation satellite accounts for 1996, http://www.bea.gov/bea/ARTICLES/NATIONAL/Inputout/2000/0500tsa.pdf; accessed August 24, 2005

[BEA 2002] U.S. Department of Commerce, Bureau of Economic Analysis,, Survey of

current business, Benchmark Input-Output Accounts of the United States, 1997, December 2002

[BEA 2005] U.S. Department of Commerce, Bureau of Economic Analysis,, Gross-

Domestic-Product-by-Industry Accounts, http://www.bea.gov/bea/industry/gpotables/gpo_action.cfm; accessed July 6, 2005

[Census 2002a]U.S. Census Bureau, Bridge between NAICS and SIC,

http://www.census.gov/epcd/ec97brdg/; accessed August 30, 2004 [Census 2002b]U.S Census Bureau, Fuels and Electric Energy 1997,

http://www.census.gov/mcd/fuels97.pdf; accessed August 30, 2004 [Census 2005a]U.S. Census Bureau, 1997 NAICS Definitions, 324 Petroleum and Coal

Products Manufacturing http://www.census.gov/epcd/naics/NDEF324.HTM#N3241; accessed February 7, 2005

[Census 2005b] U.S. Census Bureau, 1997 NAICS Definitions, 486 Pipeline transportation,

http://www.census.gov/epcd/naics/NDEF486.HTM#N486; accessed August 25, 2005

39

[DOE 1999] Transportation Energy Data Book (19th Edition), United States Department of Energy, 1999

[DoT 2004] U.S. Department of Transportation, Bureau of Transportation Statistics,

Transportation Statistics Annual Report, http://www.bts.gov/publications/transportation_statistics_annual_report/2004/, accessed August 14, 2005

[EIA 1991] Energy Information Administration, U.S. Department of Energy, Annual

Energy Review 1991, (DOE/EIA-0384(91)), 1991 [EIA 1997a] Energy Information Administration, U.S. Department of Energy, Wholesale

price of motor gasoline, http://tonto.eia.doe.gov/steo_query/app/papage.htm; accessed May 1, 2005

[EIA 1997b] Energy Information Administration, U.S. Department of Energy,

http://www.eia.doe.gov/pub/oil_gas/petroleum/info_glance/residual.html; accessed August 17, 2003

[EIA 1997c] Energy Information Administration, U.S. Department of Energy, Annual

Energy Review 2003, http://www.eia.doe.gov/aer/petro.html; accessed July 12, 2005

[EIA 1997d] B.D. Hong, U.S. Coal Supply and Demand: 1997 Review, Energy Information

Administration, U.S. Department of Energy, 1997 [EIA 1997e] Energy Information Administration, U.S. Department of Energy,

http://www.eia.doe.gov/emeu/aer/txt/ptb0806.html; accessed August 17, 2003 [EIA 1997f] Energy Information Administration, U.S. Department of Energy,

http://tonto.eia.doe.gov/dnav/ng/ng_pri_sum_dcu_nus_a.htm; accessed May 1, 2005

[EIA 2001] Energy Information Administration, U.S. Department of Energy, State Energy

Data 2001: Prices and Expenditures, http://www.eia.doe.gov/emeu/states/sep_prices/total/pdf/pr_all.pdf; accessed August 19, 2005

[EIA 2002] Energy Information Administration, U.S. Department of Energy, 1998

Manufacturing Energy Consumption Survey (MECS) Consumption of Energy, http://www.eia.doe.gov/emeu/mecs/mecs98/datatables/d98s1_2.htm; accessed August 30, 2004

[EIA 2004] Energy Information Administration, U.S. Department of Energy, Annual

Energy Review 2003, http://www.eia.doe.gov/emeu/aer/contents.html, accessed July 6, 2005

40

[EPA 1999a] U.S. EPA, Facility SIC Report - Criteria Air Pollutants,

http://www.epa.gov/oar/data/netsic.html?us~USA~United%20States; accessed December 13, 2004

[EPA 1999b] U.S. EPA, National Air Quality and Emissions Trends Report, 1999;

http://www.epa.gov/airtrends/aqtrnd99; accessed December 13, 2004 [EPA 1999c] U.S. EPA, Facility SIC Report - About the Facility SIC Report - Criteria Air

Pollutants, http://www.epa.gov/oar/data/help/hnetsic.html?us~USA~United%20States; accessed July 12, 2005

[EPA 1999d] U.S. EPA, Facility SIC Report – About AirData,

http://www.epa.gov/oar/data/info.html; accessed July 12, 2005 [EPA 2003a] U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-

2001, Annex Y – Constants, Units, and Conversions, http://yosemite.epa.gov/oar/globalwarming.nsf/UniqueKeyLookup/LHOD5MJTCL/$File/2003-final-inventory_annex_y.pdf; accessed August 30, 2004

[EPA 2003b] U.S. EPA, Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-

2001, http://yosemite.epa.gov/oar/globalwarming.nsf/content/ResourceCenterPublicationsGHGEmissionsUSEmissionsInventory2003.html; accessed August 30, 2004

[Hendrickson 2005] Hendrickson, Chris T., Lester B. Lave, H. Scott Matthews, Arpad

Horvath, Satish Joshi, Francis C. McMichael, Heather MacLean, Gyorgyi Cicas, Deanna Matthews and Joule Bergerson, (2005) Environmental Life Cycle Assessment of Goods and Services: An Input-Output Approach, Resources for the Future.

[IPCC 1996] Intergovernmental Panel on Climate Change, Revised 1996 IPCC Guidelines

for National Greenhouse Gas Inventories, UNEP, OECD and IPCC, 1996 [IPCC 2001] Intergovernmental Panel on Climate Change; J.T. Houghton, Y. Ding, D.J.

Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds., Climate Change 2001: A Scientific Basis; Cambridge University Press, Cambridge, U.K.

[ODS 2002] U.S. EPA, Class I and II Ozone-Depleting Substances,

http://www.epa.gov/ozone/ods.html; accessed August 30, 2004

41

[TRI 2000a] U.S. EPA, Toxics Release Inventory Program - 2000 TRI Data Release, http://www.epa.gov/tri/tridata/tri00/data/index.htm; accessed June 28, 2005

[TRI 2000b] U.S. EPA, Toxics Release Inventory - State File Documentation for RY 2000,

http://www.epa.gov/tri/tridata/tri00/data/States2000.pdf; accessed July 13, 2005

[TRI 2005a] U.S. EPA, Toxics Release Inventory – TRI Explorer,

http://www.epa.gov/triexplorer/industry01.htm?year=2000; accessed July 13, 2005

[TRI 2005b] personal communication, Eileen M. Mayer, U.S. EPA Office of

Environmental Information, Toxics Release Inventory Program; July 13, 2005 [UNEP 2000] United Nations Environment Program, The Montreal Protocol

on Substances that Deplete the Ozone Layer, http://www.unep.org/ozone/Montreal-Protocol/Montreal-Protocol2000.shtml#_Toc483027785; accessed October 7, 2005