UNITED STATES ENVIRONMENTAL PROTECTION AGENCY ANN ARBOR, MI 48105

OFFICE OF AIR AND RADIATION

Date: September 14, 2009 Subject: Calculation of Upstream Emissions for the GHG Vehicle Rule From: Craig A. Harvey, Mechanical Engineer U.S. EPA, Office of Transportation and Air Quality To: Docket EPA-HQ-OAR-2009-0472

This memo documents the assumptions, data sources, and calculations used to estimate the emission impacts related to changes in fuel production and distribution (i.e., "upstream emissions") associated with the proposed rule: Proposed Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emissio n Standards and Corporate Average Fuel Economy Standards.

1.0 Introduction

As used here, the term "upstream emissions" refers to air pollutant emissions generated from all crude oil extraction, transport, refining, and finished fuel transport, storage, and distribution. As shown in Table 1 thi s includes all the stages prior to the final filling of vehicle fuel tanks at retail servi ce stations. Included in each of these processes are the lifecycle emissions and energy us e associated with that operation as well as upstream components that feed into it. For example, the crude oil transport stage includes emissions from production of the fuel used by oil tankers. Electricity production emissions are included in many of the stages shown. These impacts include operationrelated activities, but not infrastructure-related activities. Thus, while we include the emissions associated with the operation of trucks u sed for gasoline distribution, we do not include the emissions associated with the productio n of the vehicles themselves or with the construction of refineries or oil tankers.

Table 1 - Stages of Fuel Processing and Emissions

PROCESS UPSTREAM / DOWNSTREAM Crude Oil Extraction Upstream Crude Oil Transport Upstream Oil Refining Upstream Fuel Transport, Storage and Distribution Upstream Vehicle Tailpipe Emissions Downstream Air Conditioning System Leakage Downstream2 To estimate the upstream emission changes associate d with the decreased fuel consumption that would result from the proposed rul e we based our analysis on the GREET model. 1 Emission factors for GHGs and criteria emissions from certain sources are taken directly from GREET 1.8, while emission f actors for criteria pollutants from mobile sourcs and all toxic emissions were provided by EPA. Lifecycle energy use and associated emissions for petroleum-based fuels in G REET are calculated based on energy efficiency metrics for the different processes invo lved in petroleum-based fuels production. The energy efficiency metric is a meas ure of how many BTUs 1 of input energy are needed to make a BTU of output product. GREET has assumptions on energy efficiency for different finished petroleum product s as well as for different types of crude oil.

GREET also has assumptions on the mix of energy sou rces used to provide the energy input which determine GHG emissions. The em issions associated with petroleum fuels are based on the emissions from producing and combusting the input energy sources (with non-combustion sources included where applica ble). The following sections describe the GREET assumptions for different petrol eum-based fuels production processes and final products.

For GHGs the emission impacts include both internat ional and domestic reductions, since reduced imports of foreign finish ed gasoline and crude oil would make up a significant share of fuel savings. Thus signi ficant upstream GHG emission reductions would occur outside of the U.S. For non -GHG pollutants the emission impacts only include reductions in domestic U.S. em issions, thus excluding overseas crude oil extraction and refining as well as ocean transport of crude or finished gasoline to the U.S.

Unlike the analysis done for EPA's Renewable Fuel S tandard (RFS2) proposed rulemaking package 2 , the analysis done for this proposal assumes no ef fects on production volumes of biofuels, so there are no emi ssion impacts related to agricultural or land use changes.

2.0 GREET Energy-Based Analysis

2.1 Crude Oil Extraction

GREET has assumptions for different types of crude oil extraction, conventional crude and oil sands crude. 2 The values for conventional crude oil are assumed to represent average crude oil extraction, including d omestic and foreign production, and onshore, offshore and enhanced oil recovery process es. Oil sands recovery was used in this analysis to represent Canadian oil sands recov ery. The assumptions for each type of crude oil extraction are shown here.

1 British Thermal Unit
2 Oil sands crude is also commonly referred to as ta r sands.3 Conventional crude oil extraction is assumed to hav e an energy efficiency metric of 98%. This means that every one million BTU (mmB TU) of crude oil produced requires 1,020,408 BTU of energy input. One mmBTU of that input is crude oil feedstock (from the ground) that ends up in the fin al product and therefore only 20,408 BTU of additional process energy is required. Tabl e 2 shows the breakout of the energy sources used to provide the additional process ener gy.

Table 2. Conventional Crude Oil Production

Process Fuel Share of Input Energy (%) Energy use

(BTU/mmBTU of fuel throughput)

Crude oil 1.0% 204

Residual oil 1.0% 204

Diesel fuel 15.0% 3,057

Gasoline 2.0% 408
Natural gas 61.9% 12,635
Electricity 19.0% 3,872

Feed loss 0.1% 28

Total: 100% 20,408

The emissions from conventional crude oil extracti on are calculated by multiplying the BTUs of the different types of ener gy inputs by emission factors for combustion of those fuel sources. The emission fac tors for the different fuel types are from GREET based primarily on assumed carbon conten ts of the different process fuels. The emissions from producing electricity are also t aken from GREET and represent average U.S. grid electricity production emissions. In addition to process energy emissions, GREET also assumes there are emissions f rom associated flaring of natural gas at the oil well, assuming 16,800 BTU of natural gas is flared per mmBTU of crude oil produced. The emissions from flared natural gas ar e again based on emission factors for natural gas combustion. GREET also accounts for fu gitive methane emissions from crude oil extraction and processing, assuming that 13.15 grams of fugitive methane are released per mmBTU of crude oil produced.

Similar to the assumptions for conventional crude o il extraction, GREET has assumptions about oil sands crude oil extraction. Oil sands can be either mined or recovered in situ -- meaning in place; GREET has assumptions for bot h processes. The oil sands recovery processes include both extractio n (surface or in situ ) and separation systems to remove bitumen from sand and water.4 Surface mining of oil sands involves open-pit minin g techniques. About two metric tons of oil sands must be dug up, moved and processed to produce one barrel of oil. In situ recovery is used for bitumen deposits buried too d eeply for mining to be practical. Cyclic steam stimulation (CSS) and stea m-assisted gravity drainage (SAGD)

are in situ recovery methods, which include thermal injection through vertical or horizontal wells. Table 3 and Table 4 show the ene rgy efficiency metric and assumed energy sources used in oil sands extraction. Emiss ions from the oil sands extraction process are based on applying emission factors to t he different energy inputs.

Table 3. Oil Sands Recovery: Bitumen Extraction – Surface Mining

Energy Efficiency 94.8%

Process Fuel Share of Input Energy (%) Energy use

(BTU/mmBTU of fuel throughput)

Diesel fuel 0.6% 329
Natural gas 82.3% 45,132
Electricity 17.1% 9,377

Feed loss 0.03% 14

Total: 100% 54,852

Table 4. Oil Sands Recovery: Bitumen Extraction – In Situ Production
Energy Efficiency 84.3%

Process Fuel Share of Input Energy (%) Energy use

(BTU/mmBTU of fuel throughput)
Natural gas 97.2% 181,011
Electricity 2.8% 5,214

Feed loss 0.01% 14

Total: 100% 186,239

Once oil sands are extracted through either the sur face mining or in situ process they are further processed for transportation. The energy efficiency metric and assumed energy input sources for the bitumen upgrading are shown in Table 5.5 Table 5. Oil Sands Recovery: Bitumen Upgrading

Energy Efficiency 98.6%

Process Fuel Share of Input Energy (%) Energy use

(BTU/mmBTU of fuel throughput)
Natural gas 97.1% 13,787
Electricity 2.8% 397

Feed loss 0.1% 14

Total: 100% 14,198

In addition to the emissions from the process energ y used in the upgrading process, GREET also assumes hydrogen is needed as a n input to the upgrading process. Emissions from hydrogen production, based on GREET defaults, are included in the emissions of bitumen upgrading. GREET assumes 84,1 87 BTU of hydrogen is used per mmBTU of oil sand crude produced through surface mi ning, and 32,364 BTU of hydrogen is used per mmBTU of oil sand crude produc ed through the in situ process.

Emission factors from GREET were used for bitumen e xtracted in situ , bitumen extracted by surface mining, and light crude oil ex traction. Emission factors from McCann (1999) were used to calculate emissions from heavy oil and Venezuela extra heavy oil by considering the incremental extraction and processing emissions relative to the average of the light crudes analyzed by McCann. 3 Instead of using McCann values directly we used these results to determine a scali ng factor for the heavy crudes compared to the conventional crude types. We then applied t his scaling factor to the GREET conventional crude emissions to represent emissions from heavy crude production. The results of the crude oil production differentiation are shown below in Table 6.

Table 6. Scaling factors Used to Calculate Heavy C rude Extraction GHG Emissions

Crude Production Emissions (gCO2-eq. / mmBTU of fue l produced)

Canadian Light Brent

North Sea Saudi Light Average "conventional" Heavy

Oil Venezuela

Extra Heavy Oil

Production Emissions 6,617 5,081 7,746 6,482 6,962 15,524

Scaling Factor 0.07 2.406 The importation of heavy crude oil and extra heavy crude oil in the U.S. comprises a relatively small but growing fraction o f current total crude oil imports. Heavy crude oils are generally of higher density an d higher viscosities compared to lighter crude oils and similarly, are not as readil y extracted from reserves. The American Petroleum Institute’s “API Gravity” is commonly use d to delineate light, medium, heavy and extra heavy crude oils. Although definitions c an vary slightly, the U.S. Geological Survey (USGS) categorizes light crude oil as having an API gravity of at least 22° and viscosity less than 100 centipoise (cP). 4 Heavy oil, by contrast, is defined as an “asphaltic, dense, and viscous oil” with an upper A PI limit of 22° and viscosity between 100 – 10,000 cP. Heavy oil with an API less than 1 0° is defined as extra-heavy oil. Natural bitumen –also referred to in the literature as oil sand, tar sand, oil-impregnated sand, asphaltic sand, rock asphalt, bituminous rock , and bitumen-bearing rock– have a similar API range as extra-heavy oils but have visc osities greater than 10,000 cP. 5

EPA analyzed the types of crude oils used in the U. S. by examining crude oil import data from the Energy Information Administrat ion for 2005, which is based on reporting by refineries. 6 The amount of crude imports reported by refinerie s with API less than or equal to 22° – heavy oil – was approxi mately 2.9 million barrels per day (mmbd) in 2005 out of the 15.2 mmbd refinery net in put in the U.S. estimated by EIA. Figure 1 below displays the break-down of U.S. heav y crude imports by country.

Figure 1. U.S. Imports of Heavy Crude Oil in 2005 ( API of 22° or less)

2005 Heavy Oil Imports (<=22.0) Source: EIA Form 814 Data

- 200,000 400,000 600,000 800,000 1,000,000 1,200,000

Mexico

V e nezuel a C ana da Ecuador B r a z il Chad Norway R us si a

U ni ted K i ngd om Kuwait A ng ol a

S a udi Ar a bia Indo nes ia Guatamala Chi

n a P eru Col u mbia Nig e ria
M alays i a Oman

A rgen tin a B ol iv ia bbl/dayBarrels per Day

Note that this is an underestimate of the actual he avy crude oil, extra heavy crude oil, or bitumen used by U.S. refineries since a fra ction of these crudes are upgraded at the country of origin and/or diluted with diluents (gas condensate, natural gas liquids or light crude) and transported to the U.S. These upgraded crude oils would then appear as7

imports with an API greater than 22° (i.e. light or medium crude oil). EPA has identified that crude oil from Venezuela and Canada would like ly have the most upgrading of extra heavy crude oil or bitumen to synthetic crude, or s yncrude, due to the nature of the reserves and current information regarding the crud e oil types extracted. The International Energy Agency estimates that in 2005, Venezuela produced approximately 565,000 bpd of syncrude from its extra heavy oil re serves in the Orinoco oil belt. 7 An analysis of the production output from the four mem bers of the Orinoco Belt Strategic Association shows that roughly three-fourths of the upgraded syncrude has an API greater than 22°. 8 Thus, out of the 3 mmbd of crude oil produced in Venezuela, approximately 19% was syncrude (i.e. 14% with API g reater than 22° and 5% with API less than 22%). Applying these splits to the U.S. import data would result in roughly 145,000 bpd of syncrude from extra heavy oil, 715,0 00 heavy oil, and 684,000 light (or conventional) crude oils. This split would still li kely underestimate the extra heavy oil/syncrude used by the U.S. since Venezuela tends to ship a greater fraction of its heavier crude oils to U.S. refineries that are spec ifically configured to handle heavier crude oils.

Estimates on the types of crude oil imported from C anada were also adjusted based on available information. Canadian production information for 2005 was obtained from statistical information from the Canadian Asso ciation of Petroleum Producers. 9 Production of crude oil in Canada totaled 2.35 mmbd in 2005, with 35% of the volume comprised of light crude oil, 22% heavy crude oil, 23% from bitumen or synthetic crude obtained via surface mining, and 19% from bitumen p roduced from in situ methods. Surface mining comprised over half of the Canadian bitumen extraction, but use of in situ techniques is now growing at a faster rate due to t he lower availability of surface bitumen and improvements in in situ techniques.

Domestic production of heavy oil was not included i n the EIA import data analyzed by the EPA. 10 To account for this, various estimates were used from different sources. In 2005, we estimate that roughly 475,000 bpd of heavy oil was produced in the U.S. with the vast majority produced in California. 11

A fraction weighted estimate of the crude oil types used in the U.S., calculated based on the data sources and calculations describe d above, was used in our estimation of the 2005 gasoline and diesel baseline. Note that t his does not include crude-type breakdowns for finished products imported into the U.S. from overseas (e.g. Europe) or exported and consumed overseas, which may change th e fractions slightly. Out of the 15.3 mmbd of crude oil reported to be used in the U .S. in 2005 12 , approximately 5% was composed of bitumen-based syncrude (mainly from Can ada), 1% was extra heavy crude oil based syncrude (mainly from Venezuela), and 23% was heavy crude oil, as shown in Figure 28 Figure 2. Percent of U.S. Crude Oil by Source

U.S. Crude Oil Consumption

5% 1% 23% 72%

- 2.00 4.00 6.00 8.00 10.00 12.00

Bitumen-based

syncrude Extra heavy oil-based syncrude Heavy crude oil Light or medium crude oilmillion barrels per day . .

The emission factors for the 2005 baseline were adj usted based on the above weighting for the different types of crude oil.

2.2 Crude Transport

Transport of crude oil to the U.S. was based on GRE ET defaults, which are shown in Figure 3. The figure indicates the percen t of the different types of crude oil used (Canada and Mexico are assumed to include the Canadian oil sands imports) and associated modes of transportation and miles travel ed for each mode. The emissions are based on emission factors for each type of vehicle including capacity, fuel economy, and type of fuel used.9 Figure 3. Crude Oil Transportation Assumptions

7.0% 7.0%

2,100

35.0%

1.0%

500

50.0% 50.0%

5,500 92.0%

750

8.0%

750 0.0%

8.0% 800

0.0%

800 US Terminal Petroleum Refinery Domestic: Alaska

Domestic: US 48 States

Imported: Canada and Mexico Imported: Offshore Countries Ocean Tanker

Pipeline

Rail Ocean Tanker
Pipeline Barge

Rail

2.3 Refining

The emissions associated with petroleum refining ca n also be calculated based on the energy efficiency of the refinery and the type of process energy fuel sources used. However, the refinery is producing a number of diff erent petroleum-based products including different transportation fuels. Therefor e, the total energy use and emissions from the refinery needs to be allocated to the diff erent products.

The basis for the overall refinery energy efficienc y in GREET is a set of linear programming model runs representing energy use in a typical refinery. Different refinery configurations with different slates of products pr oduced will have different energy efficiencies. For calculating baseline emissions a ssociated with gasoline and diesel fuel we are assuming an average U.S. refinery, so defaul ts in GREET are reasonable for our analysis.

Allocation of the total refinery energy use and emi ssions to the different products can be done in a number of ways. Total energy use and emissions can be allocated based on the energy, mass, or economic value of the diffe rent output products. Alternately, energy use and emissions can be based on first brea king out total refinery energy use to the different refinery sub-processes (e.g., distill ation, cracking, alkylation, isomeration, desulfurization), and then allocating energy from e ach sub process to the different products, for example 100% of alkylation used for g asoline. This type of subprocess allocation would require a level of detail that was beyond the scope of this analysis. Therefore, we used the GREET default allocation whi ch in general allocated 60–65% of total refining process fuel use to gasoline product ion, 18–22% to diesel production, and the remaining 13–22% to other petroleum products.

The refinery modeling runs and the allocation to di fferent products results in the10

energy efficiency values for different types of gas oline and diesel fuel shown in Table 7.

Table 7. Refinery Energy Efficiency

Transportation Fuel Type Energy Efficiency

Conventional Gasoline 87.7%

Reformulated Gasoline Feedstock 87.2%

Low Sulfur Diesel Fuel 87%

The following table shows the process fuel breakout and BTUs of process fuel used per million BTU of finished transportation fuel produce d.

Table 8. Refinery Energy Use
Energy use (BTU/mmBTU of fuel throughput)

Process Fuel Share of

Input Energy Conventional

Gasoline RFG Feedstock Low Sulfur Diesel Fuel

Residual oil 3.0% 4,208 4,404 3,595
Natural gas 30.0% 42,075 44,037 35,946

Coal 13.0% 18,233 19,083 15,577
Electricity 4.0% 5,610 5,872 4,793
Refinery still gas 50.0% 70,125 73,395 59,910

Total: 100% 140,251 146,789 119,821

The emissions from refining are calculated by multi plying the BTUs of the different types of energy inputs by emissions facto rs for combustion of those fuel sources. The emission factors for the different fu el types are from GREET based primarily on assumed carbon contents of the differe nt process fuels. The emissions from producing electricity are also taken from GREET and represent average U.S. grid electricity production emissions. In addition to p rocess energy emissions, GREET also assumes there are non-combustion GHG emissions asso ciated with petroleum refining. These emissions are also allocated to the different fuels based on the same energy efficiency ratios used to allocate energy use. The non-combustion CO2 emissions amount to 1,172 g CO 2 per mmBTU of conventional gasoline, 1,214 g CO 2 per mmBTU of reformulated gasoline (RFG) blendstock, and 1,08 8 g CO 2 per mmBTU of low sulfur11

diesel fuel.

To represent baseline gasoline we considered the ty pes of gasoline used in 2005. Based on EIA data on sales of gasoline to end users in 2005, 57.4% was conventional gasoline, 28.4% was reformulated gasoline and 14.2% was California reformulated gasoline. The California reformulated gasoline is represented in GREET as reformulated with slightly different assumptions about crude tra nsport distances. We also considered imported finished product vs. domestically produced gasoline. According to EIA data, in 2005 6.0% of conventional gasoline used was importe d and 7.7% of reformulated gasoline was imported. Imported gasoline was model ed the same as domestic for refinery emissions for GHGs, except conventional cr ude was used to represent crude oil production impacts, instead of a domestic mix. To represent baseline diesel fuel use we used a similar analysis and assumed 100% low-sulfur diesel fuel and 8.0% imported finished product.

2.4 Fuel Transport

Transport of the finished petroleum product was als o included in the baseline values for gasoline and diesel fuel. Transport inc luded carriage from refinery to bulk terminal and from bulk terminal to retail location. Transport of imported finished product was also included and was assumed to be transported by ocean tanker 2,600 miles to the U.S. Once in the U.S. both domestic and imports we re assumed to be transported by the modes and distances shown in Table 9 and Table 10.

Table 9. Gasoline Transport Assumptions

Refinery to Bulk Terminal Bulk Terminal to

Refueling Station Mode

Percent Distance Percent Distance

Ocean Tanker 17 1,500 0 N/A
Barge 4 520 0 N/A
Pipeline 72 400 0 N/A

Rail 7 800 0 N/A

Truck 0 N/A 100 3012 Table 10. Diesel Fuel Transport Assumptions

Refinery to Bulk Terminal Bulk Terminal to

Refueling Station Mode

Percent Distance Percent Distance

Ocean Tanker 12 1,500 0 N/A
Barge 6 520 0 N/A
Pipeline 72 400 0 N/A

Rail 7 800 0 N/A

Truck 0 N/A 100 30

The GHG emissions from transport of gasoline and di esel fuel were based on GREET default emission factors for each type of veh icle including capacity, fuel economy, and type of fuel used.

2.5 Modifications of 2005 Analysis for Future Years

For the impacts analysis of the proposed light duty vehicle GHG rule we modified the petroleum baseline fuel assumptions described a bove to account for expected shifts in petroleum production and fuel imports. For this an alysis we considered the mix of crude oils and finished gasoline in 2022, since portions of the analysis were already available for that year in the Draft Regulatory Impact Analys is (DRIA) for the RFS2 proposed rule.

For this analysis we consider that 50% of the reduc tion in gasoline consumption will come from imported gasoline, and 90% of the re duction in domestically refined crude will come from imported crude.

We assume 65% of the reduction in gasoline consumpt ion will be conventional gasoline and 35% will be RFG blendstock gasoline, a nd all of the RFG reduction will come from domestic production.

In order to come up with emissions for average crud e oil used in producing the marginal gasoline that would be reduced by this pro posed rule we assumed for imported gasoline that 7.6% would be from tar sands and 3.8% would be from Venezuelan extra heavy crude, with the remainder from international light and heavy crude. For domestically refined gasoline, our assumption that only 10% of the crude oil reduction would be domestic crude shifted the allocation to 1 0.2% from tar sands and 5.1% from Venezuelan extra heavy crude, with the remaining 75 % from international light and heavy crude. The basis for this was EIA projection s for 2022. EIA projects that roughly 64% of total Canadian crude oil production will be oil sand production in 2022, and that roughly 40% of total Venezuelan crude oil productio n will be heavy crude production in 2022. EIA also has assumptions on how much crude o il will be imported into the U.S.13

from Canada and Venezuela in 2022. We assumed the percentage of this imported Canadian and Venezuelan crude oil that would be oil sands and heavy oil was the same percentage of total production that is unconvention al crude in those countries (~64% for Canada and ~41% for Venezuela). Based on the percen t of Canadian and Venezuelan imports to total crude oil projected in 2022, oil s ands represented 7.6% and heavy oil represented 3.8% of total crude oil use.

For this analysis we did not assume any efficiency improvements at the petroleum refining portion of the gasoline and diesel fuel li fecycle. Therefore the same refining energy use and emissions was assumed that was used to represent the 2005 petroleum fuel baseline. On the one hand this may be overest imating energy use and emissions from petroleum refining, however, this also does no t factor in recent regulations that might increase energy use and emissions, such as in creased desulfurization of both gasoline and diesel fuel.

3.0 Modifications and Additions to GREET Analysis

For this analysis certain updates and enhancements were made to GREET 13 and incorporated into an EPA spreadsheet model. 14 This section describes (1) the methods used to estimate evaporative emission impacts durin g gasoline distribution, (2) updates to the transport vehicle/equipment emission factors to account for applicable EPA emission standards, and (3) addition of air toxic emission e stimates. This analysis is adapted from the analysis done for the RFS2 proposed rule for ye ar 2022, but for this GHG proposed rule there are no expected impacts related to biofu els such as ethanol, as those volumes are assumed constant. The year 2022 is considered to represent a reasonable estimate of the emission factors (not total emissions) for the future years analyzed in this proposed rule.

3.1 Finished Fuel Transport and Distribution

VOC emissions are produced by transfer and storage activities associated with distribution of gasoline, gasoline/ethanol blends, and ethanol. These are referred to as Stage I emissions. 15 Stage I distribution begins at the point the fuel leaves the production facility and ends when it is loaded into the storag e tanks at dispensing facilities.

There are five types of facilities that make up thi s distribution chain for gasoline. Bulk gasoline terminals are large storage facilitie s that receive gasoline directly from the refineries via pipelines, barges, or tankers (or ar e collocated at refineries). Gasoline from the bulk terminal storage tanks is loaded into carg o tanks (tank trucks or railcars) for distribution to smaller intermediate storage facili ties (bulk plants), or directly to gasoline dispensing facilities (retail public service statio ns and private service stations). When ethanol is blended into gasoline it usually occurs in the pipes which supply the tank trucks.

There are two types of pipeline facilities found at various intervals along gasoline distribution pipelines: pipeline breakout stations and pipeline pumping stations. Pipeline14

breakout stations receive gasoline via pipelines, s tore it in storage tanks, and re-inject it into pipelines as needed to meet the demand from do wnstream facilities. Pipeline pumping stations are located along the entire lengt h of a pipeline at about 40 mile intervals. Their purpose is to provide the extra ‘‘ push’’ needed to move the product through the pipeline. They do not normally have gas oline storage capability.

Bulk plants are intermediate storage and distributi on facilities that normally receive gasoline or gasoline/ethanol blends from bu lk terminals via tank trucks or railcars. Gasoline and gasoline/ethanol blends from bulk plants are subsequently loaded into tank trucks for transport to local dispensing facilities.

Gasoline dispensing facilities include both retail public outlets and private dispensing operations such as rental car agencies, fleet vehicle refueling centers, and various government motor pool facilities. Dispensin g facilities receive gasoline and gasoline/ethanol blends via tank trucks from bulk t erminals or bulk plants. Inventory estimates for this source category only include the delivery of gasoline at dispensing facilities and does not include the vehicle or equi pment refueling activities.

Emission factors (EFs) for gasoline were based on i nventory estimates from the 2002 NEI. 16 We used these data to develop E0 gasoline emissio n factors even though the 2002 emissions included the E10 that was in the fue l pool at that time. In 2002 this was still a relatively small proportion of gasoline con sumption, so it should not substantially affect the national E0 estimates. Since ethanol is blended with gasoline at bulk terminals to produce E10 and E85 at the point fuel is loaded into tank trucks, we assumed bulk terminal emissions were associated with unblended g asoline. We then divided emissions into a refinery to bulk terminal component and a bu lk terminal to dispensing facility component. Total nationwide emissions for these tw o components were divided by the energy content of the total volume of gasoline dist ributed in 1999, to obtain the emission factor in g/mmBTU. Total volume of gasoline was ba sed on gasoline sales as reported by the Energy Information Administration. 17 These emission factors are provided in Table 11.

Table 11. VOC Emission Factors for Gasoline Storag e and Transfer Emissions (Stage 1)

Process EF

(g/mmBTU)
Refinery to Bulk Terminal 14.94
Bulk Terminal to Pump 27.79

3.2 Combustion Emissions from Transport and Distri bution of Fuel and Feedstock

Emissions are produced by the vehicles and equipme nt used to transport15

feedstocks such as crude oil to refineries, as well as the equipment and vehicles that distribute finished gasoline from refineries to dis tribution terminals and retail outlets. For example, foreign crude oil is transported to do mestic refineries by ocean tankers, and finished gasoline is then moved by pipeline to dist ribution terminals and from there by tank truck to retail outlets.. The emission factor s for the year 2022 in Table 12 take into account the mix of newer better controlled engines (including trucks meeting the standards for 2008 and later engines 18 and engines meeting the 2008 locomotive/marine diesel engine rule 19 ), as well as any remaining older engines subject t o less stringent standards. The truck EFs are given in terms of gra ms per vehicle mile traveled, while the other EFs are in grams per million BTU of fuel burn ed by the engine. Emission factors for these engines are taken from the respective rul emaking analyses.

To estimate the net emission rates for the assumed mix of transport modes for each fuel type, these emission factors were incorpo rated into a modified version of GREET 20 , since GREET 1.7 and 1.8 retained emission factors based only on earlier regulations. Thus, the miles traveled and quantiti es of fuel burned are those used by GREET for each transport mode and fuel being transp orted.16

Table 12. Criteria Emission Factors for Fuel and F eedstock Transport/Distribution
Transport Mode Year VOC CO NOx PM10 PM2.5

Class 2B HD Diesel Trucks (g/mile) 2005 0.282 1.303 3.594 0.163 0.139

2022 (2020) 0.137 0.205 0.483 0.033 0.019

Medium HD Diesel Trucks (g/mile) 2005 0.653 2.482 8.297 0.309 0.271

2022 (2020) 0.289 0.417 1.243 0.053 0.035

Locomotive (g/mmBTU of fuel burned) 2005 84.733 212.861 1620.376 51.575 50.028

2022 (2020) 34.070 203.984 815.271 19.015 18.445

Barge (avg of C1 & C2 vessels) 21 2005 26.761 237.513 1276.901 47.923 46.485

(g/mmBTU of fuel burned) 2022 (2020) 15.527 188.994 676.097 22.017 21.356

Ocean Tanker (C3 vessels) 2005 79.943 181.746 2177.881 181.410 166.930

(g/mmBTU of fuel burned) 2022 (2020) 79.891 181.526 2054.819 181.118 166.666

3.3 Upstream Air Toxics

3.3.1 Upstream Air Toxics Reference Case

Air toxic emissions are associated with a variety o f upstream processes. These processes include operation of petroleum refineries , operation of electrical production facilities which supply power to these facilities, and transport of feedstocks and distribution of finished gasoline.

Although a large number of compounds which are cons idered air toxics could be impacted by this rule, we focused on those which we re identified as national and regional-scale cancer and noncancer risk drivers in the 1999 NATA 22 and were also likely to be significantly impacted by this rule. These compounds include benzene, 1,3- butadiene, formaldehyde, acetaldehyde, and acrolein . Naphthalene was not included in this analysis since the impacts of the proposed pro gram on it would be minor relative to the other air toxics.17

Air toxic emissions for year 2002 for stationary so urces refineries, other than for fires, were obtained from the 2002 National Emissions Inve ntory (NEI), version 3. Future year emissions of benzene, 1,3-butadiene, formaldehyde, acetaldehyde, and acrolein were estimated for sectors only, rather than individual sources. These sectors included nonEGU (electric generating unit) point sources, EGU p oint sources, the nonpoint storage and transfer subsector, and other nonpoint sources. Emissions were estimated by applying future year to 2002 VOC ratios to 2002 air toxic estimates. More details on the methods and data used to develop these inventories are found in a memo included in the docket for the RFS2 proposed rule. 23

3.3.2 Upstream Air Toxics Control Case

As described below, we developed emission factors f or several air toxics using the most recent available data. These emission fac tors were used with estimates of changes in fuel volumes and associated energy outpu ts to estimate inventory changes associated with the proposed program. In general, emission factors are expressed as grams per million BTU (g/mmBTU) of energy produced or distributed as part of the process. Underlying data are available in the dock et for the rule.

Petroleum Refineries – Total nationwide emissions of air toxics for 153 U. S. petroleum refineries in 2002 were obtained from data collecte d as part of a risk and technology review (RTR) for EPA’s proposed rule, “National Emi ssion Standards for Hazardous Air Pollutants From Petroleum Refineries.” 24 These emissions were divided by BTUs of energy produced by those refineries in 2002 to obta in emission factors in g/mmBTU. Thus the resultant emission factors represent 2002 technology and emission standards. Energy output estimates included all refinery produ cts, such as conventional and reformulated gasoline, aviation gasoline, jet fuel, kerosene, distillate fuel oil, residual fuel oil, petrochemical feedstocks, naphthas, lubricants , and other miscellaneous products. Energy output was estimated by multiplying volume o f each product supplied 17 by its heating value in BTUs per gallon.

Resultant emission factors are provided below in Ta ble 13, along with those for electricity production.18

Table 13. Air Toxic Emission Factors for Petroleum Refineries and Electricity

Production (g/mmBTU of fuel or electricity produced )

Pollutant Petroleum

Refinery Electricity

Production
1,3-butadiene 0.0014 0.0001
Acetaldehyde 0.0002 0.0297

Acrolein 0.0001 0.0115

Benzene 0.0264 0.0443
Formaldehyde 0.0042 0.0629

Table 14. Benzene Evaporative Emission Factors for Gasoline Transport and

Distribution (g/mmBTU of fuel transported)

Process Year Benzene EF (g/mmBTU)
Refinery to Bulk Terminal 2002 0.0488

Refinery to Bulk Terminal 2022 0.0270

Bulk Terminal to Pump 2002 0.0908

Bulk Terminal to Pump 2022 0.0502

There are also toxic emissions associated with comb ustion of fuels used in transport and distribution of feedstocks and fuels. The emission factors for these are shown in Table 15 as fractions of exhaust VOC. The VOC emission factors that these fractions are applied to are presented above in Tab le 12. The locomotive, marine distillate, and residual boiler estimates come from a 2005 EPA report. 25 The heavy-duty diesel truck emission fractions come from a 2002 re port documenting the toxics module of EPA's MOBILE6.2 model, 26 and the pipeline values come from the EPA AP-42 document. 2719 Table 15. Toxic Fractions of Exhaust VOC (grams toxics per gram of VOC)

Mode Source 1,3- Butadiene Acetaldehyde Acrolein Benzene Formaldehyde

Rail Diesel

Locomotive 0.003246519 0.018786 0.0031238 0.002587511 0.04328653

Barge Marine

Diesel -- Distillate 0.00061 0.074298 0.0035 0.020344 0.1496

Ocean Tanker Residual

Boiler 0 0.003858 0 0.000165354 0.02645669

Truck HD Diesel

Trucks 0.00061 0.0288 0.0035 0.0105 0.0782

Pipeline Natural Gas

Turbines 0 0.019048 0.0030476 0.005714286 0.3380952420 1 Argonne National Laboratories, The Greenhouse Gas and Regulated Emissions from Transportation (GREET) Model, Version 1.8, June 200 7, available at http://www.transportation.anl.gov/software/GREET/in dex.html (accessed April 20, 2008).

2 U.S. EPA, Draft Regulatory Impact Analysis: Chang es to Renewable Fuel Standard Program, EPA-420-D-09-001, May 2009. Docket EPA-H Q-OAR-2005-0161. http://www.epa.gov/otaq/renewablefuels/420d09001.pd f

3 McCann, T., and Magee, P., Crude Oil Greenhouse G as Life Cycle Analysis Helps Assign Values For CO2 Emissions Trading . Oil and G as Journal. Vol. 97, no. 8, pp. 38- 44. Feb 1999.

4 USGS (November 2006), “Natural Assessment of Oil and Gas Fact Sheet: Natural Bitumen Resources of the United States,” Fact Sheet 2006-3133.

5 USGS (August 2003), “Heavy Oil and Natural Bitume n – Strategic Petroleum Resources,” Fact Sheet 70-03.

6 Energy Information Administration, EIA Survey For m 814, "Monthly Imports Report," http://www.eia.doe.gov/oss/forms.html#eia-814.

7 International Energy Agency (March 14, 2006), Oil M arket Report: A Monthly Oil Market and Stocks Assessment, www.oilmarketreport.o rg. pp. 18.

8 Energy Information Administration, “Country Analy sis Briefs,” Venezuela Oil. http://www.eia.doe.gov/emeu/cabs/Venezuela/Oil.html (last viewed 6/18/2008).

9 Canadian Association of Petroleum Producers (May 2008), Statistical Handbook for Canada’s Upstream Petroleum Industry.

10 National Petroleum Council (2007), "Working Docum ent of the NPC Global Oil & Gas Study" July 18, 2007, Topic Paper #22 Heavy Oil

.

11 California 2007 Annual Report of the State Oil & Gas Supervisor, http://www.conservation.ca.gov/dog/pubs_stats/annua l_reports/Pages/annual_reports.asp x (last viewed 6/18/2008).

12 Energy Information Administration, U.S. Imports b y Country of Origin, 2005 data. http://tonto.eia.doe.gov/dnav/pet/pet_move_impcus_a 2_nus_epc0_im0_mbbl_a.htm (last viewed 6/18/2008)

13 EPA Modified version of GREET 1.7 Argonne Nationa l Lab model for RFS2 NPRM Emission Factors, October 31, 2008, Docket ID: EPA- HQ-OAR-2005-0161-0428.21 14 U.S. EPA, GHG Vehicle NPRM Upstream (Production/D istribution) Emission Impacts Calculation Spreadsheet, September 9, 2009.

15 40 CFR Part 63 National Emission Standards for Ha zardous Air Pollutants for Source Categories: Gasoline Distribution Bulk Terminals, B ulk Plants, Pipeline Facilities, and Gasoline Dispensing Facilities; Proposed Rule, Thur sday, November 9, 2006, 66064- 66092.

16 E. H. Pechan. Documentation For The Final 2002 N onpoint Sector (Feb 06 Version) National Emission Inventory For Criteria And Hazard ous Air Pollutants, Appendix A, pp. A-89 to A-105. Prepared for Emissions Inventory an d Analysis Group (C339-02) Air Quality Assessment Division Office of Air Quality P lanning and Standards U.S. Environmental Protection Agency Research Triangle P ark, NC 27711, Report No. 05.10.001/9014.401 Jul-06. Available at ftp://ftp.epa.gov/EmisInventory/2002finalnei/docume ntation/nonpoint/2002nei_final_non point_documentation0206version.pdf.

17 Energy Information Administration. 2007. Product Supplied, Petroleum Supply Reporting System. http://tonto.eia.doe.gov/dnav/pe t/pet_cons_psup_dc_nus_mbbl_a.htm

18 U. S. EPA. 2001. Final Rule: Control of Air Pol lution From New Motor Vehicles: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements, January 18, 2001.

19 U. S. EPA. 2008. Final Rule: Control of Emissio ns of Air Pollution from Locomotives and Marine Compression-Ignition Engines Less than 30 Liters per Cylinder, Regulatory Impact Analysis, June 30, 2008. http://w ww.epa.gov/otaq/locomotives.htm

20 U.S. EPA. 2009. Modified version of GREET1.7/1. 8 upstream emissions spreadsheet model, September, 2009.

21 Emission Inventories for Ocean-Going Vessels Usin g Category 3 Propulsion Engines In or Near the United States, Draft Technical Suppo rt Document, EPA420-D-07-007, December 2007. This is available in Docket OAR-200 7-0121 at http://www.regulations.gov/ .

22 U. S. EPA. 2006. National-Scale Air Toxics Asse ssment for 1999: Estimated Emissions, Concentrations And Risk, Technical Fact Sheet. http://www.epa.gov/ttn/atw/nata1999.

23 U. S. EPA. 2008. Technical Support Document: Pr eparation of Emissions Inventories For the 2002-based Platform, Version 3, Criteria Ai r Pollutants, January 2008, Docket ID EPA-HQ-OAR-2004-0008-0857.22 24 Federal Register. 2007. National Emission Stand ards for Hazardous Air Pollutants From Petroleum Refineries. 72(170): 50715-50742. http://www.epa.gov/EPAAIR/2007/September/Day-04/a17009.htm.

25 Diesel Locomotives, Marine Distillate, Residual B oiler -- E. H. Pechan. 2005. Documentation For Aircraft, Commercial Marine Vesse l, Locomotive, And Other Nonroad Components Of The National Emissions Invent ory, Volume I - Methodology. Prepared for U. S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. http://www.epa.gov/ttn/chief/net/2002inventory.html

26 HDD Trucks -- R. Cook, E. Glover. 2002. Technic al Description of the Toxics Module for MOBILE6.2 and Guidance on Its Use for Em ission Inventory Preparation. U. S. Environmental Protection Agency, Office of Trans portation and Air Quality. Report No. EPA420-R-02-011. http://www.epa.gov/otaq/m6.ht m

27 Natural Gas Turbines -- U. S. EPA. 2000. AP-42, 5th Edition, Volume 1. Chapter 3: Stationary Internal Combustion Sources. http://www.epa.gov/ttn/chief/ap42/ch03/index.html