Analysis of Energy Use and CO2 Emissions in the ... - ACS Publications

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Analysis of Energy Use and CO2 Emissions in the U.S. Refining Sector, With Projections for 2025 David S. Hirshfeld* and Jeffrey A. Kolb MathPro Inc., P.O. Box 34404, Bethesda, Maryland 20827, United States S Supporting Information *

ABSTRACT: This analysis uses linear programming modeling of the U.S. refining sector to estimate total annual energy consumption and CO2 emissions in 2025, for four projected U.S. crude oil slates. The baseline is similar to the current U.S. crude slate; the other three contain larger proportions of higher density, higher sulfur crudes than the current or any previous U.S. crude slates. The latter cases reflect aggressive assumptions regarding the volumes of Canadian crudes in the U.S. crude slate in 2025. The analysis projects U.S. refinery energy use 3.7%−6.3% (≈ 0.13−0.22 quads/year) higher and refinery CO2 emissions 5.4%−9.3% (≈ 0.014−0.024 gigatons/year) higher in the study cases than in the baseline. Refining heavier crude slates would require significant investments in new refinery processing capability, especially coking and hydrotreating units. These findings differ substantially from a recent estimate asserting that processing heavy oil or bitumen blends could increase industry CO2 emissions by 1.6−3.7 gigatons/year.

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INTRODUCTION In transforming crude oil into finished products, refineries consume energy and consequently emit CO2. Refinery energy consumption and CO2 emissions are functions of crude slate properties, refinery configuration, operating efficiency, finished product demand, refined product specifications, and mandated biofuel content use. Since 1985, U.S. refinery energy use and CO2 emissions have fluctuated within narrow ranges, while the average density and sulfur content of the U.S. crude slate have gradually increased.1 Credible estimates of future energy use and CO2 emissions in the U.S. refining sector begin with credible projections of the future U.S. crude slate, product demand, and product specifications. The prevailing view among seasoned industry observers and refining professionals is that the average density and sulfur content of the U.S. crude slate will continue to increase gradually, due in part to increases expected in the volume of bitumen crudes produced in Western Canada and exported to U.S. refineries.2 However, some observers assume that the U.S. crude oil slate is set to shift precipitously and completely to heavy, high-sulfur crudes, and they assert that this shift would lead to steep increases in refinery energy use and CO2 emissions.3 The latter view is implausible. As shown in a recent analysis,4 the estimated per-barrel refinery energy use associated with Western Canadian bitumen crudes is comparable to that of some conventional crude oils already in the U.S. crude slate. More importantly, it is not clear where the assumed large volumes of very heavy, high-sulfur crude would come from or how these volumes could drive existing domestic and imported crudes out of the U.S. market. Running an all heavy, high sulfur crude slate in refineries configured to process lighter, lower © 2012 American Chemical Society

sulfur crudes would require substantial construction of new refinery processing capability. Credible forecasts of increases in the density and sulfur content of the U.S. crude slate (coupled with more stringent regulations governing refined product quality) imply modest increases in per-barrel energy consumption and CO2 emissions from U.S. refineries. These per-barrel increases may be offset by decreases in refined product demand and refinery crude runs resulting from mandated increases in the use of alternative fuels, improved fuel economy of the vehicle fleet, and improvements in refinery energy efficiency driven by prospective state and Federal limits on CO2 emissions (e.g., California’s Global Warming Solutions Act).5 This study establishes a set of plausible crude oil supply scenarios in 2025 and estimates energy use, CO2 emissions, aggregate crude oil throughput, and process capacity requirements for each. Each scenario includes forecast product demands and compliance with mobile and stationary source air quality standards expected in 2025. These include tighter sulfur specifications on gasoline (Tier 3) and marine diesel fuel (MARPOL Annex VI sulfur standards on marine diesel fuel6). (Lifecycle analysis including CO2 emissions from crude oil production through refined product use is beyond the scope of this analysis.) The analysis employs a linear programming (LP) model of the U.S. refining sector. Refinery LP models are detailed, process-oriented representations of refinery operations and economics. Such engineering models are the method of choice Received: Revised: Accepted: Published: 3697

December 13, 2011 February 17, 2012 March 5, 2012 March 5, 2012 dx.doi.org/10.1021/es204411c | Environ. Sci. Technol. 2012, 46, 3697−3704

Environmental Science & Technology

Policy Analysis

large molecules containing 50 or more carbon atoms. Some also contain “hetero” elementsnotably sulfur, as well as nitrogen and certain metals. See also SI Section 1.2. The chemical makeup of a crude oil determines, in large part, the yields and qualities of the refined products that a particular refinery (with fixed capital stock) can produce from that crude. Different crude oils require different refinery process facilities and operations to most efficiently produce the required product slates. The chemical makeup of a crude oil and its various boiling range fractions also has a limited effect on refinery energy use, and in turn, CO2 emissions. Two properties are widely used for classifying and comparing crude oils: API gravity (a measure of density) and sulfur content. API Gravity (Density). Less dense (i.e., lighter) crudes contain higher proportions of small molecules, which refineries can readily process into gasoline, jet fuel, and diesel. More dense (i.e., heavier) crudes contain higher proportions of large molecules, which refineries can either (i) use in heavy industrial fuels, asphalt, and other heavy products or (ii) processat some costinto the smaller, tailored molecules that go into the transportation fuels products. Sulfur Content. Of all the heteroelements in crude oil, sulfur has the most important effects on refinery energy use. Sulfur in crude oil is distributed across the various crude fractions. Most of it must be removed in the refining process to support refinery operations and to meet product sulfur specifications. Refineries remove sulfur primarily by hydrotreating. Low-sulfur crude oil is called sweet; high-sulfur crude oil is called sour. Sulfur content is often expressed in weight percent (wt%). Most sour crudes have sulfur levels in the range of 1.0− 2.0 wt %, but some have >4 wt %. Classifying Crude Oils by API Gravity and Sulfur Content. API gravity and sulfur content are the basis for a simple, widely used scheme for classifying crude oils (SI Section 1.2).11 Table 1 lists some crude oils that are important in the world oil trade and are used by U.S. refineries. The two Canadian

for assessing the technical and economic aspects of the refining sector’s responses to changes in operational requirements, such as a major change in crude slate.

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HISTORICAL CONTEXT: 1986−2010 The primary external factors influencing U.S. refinery energy use and CO2 emissions over the past quarter of a century have been • growth in demand for light refined products • increasing crude oil density and sulfur content • stringent new sulfur standards • biofuel mandates. See also Supporting Information (SI) Section 3. In 2010, the U.S. refining sector consumed about 3.3 quads of energy (≈ 3% of total U.S. consumption) and produced an estimated 260 MM MeT of CO2 (≈ 3.5% of total U.S. emissions), including CO2 emissions from production of merchant hydrogen supplied to U.S. refineries.7 This amounts to about 630 K Btu of energy and 0.046 MeT of CO2 emissions per Bbl of crude oil processed. Between 1986 and 2010, the density and sulfur content of the U.S. crude oil slate increased steadily (SI Figure SI-8). Average API gravity (a measure of density, defined as (141.5/ specific gravity) − 131.5)) declined from about 32.5° to about 30.5°; average sulfur content increased from about 0.9 wt % to about 1.4 wt %. Over the same period, U.S. net production of refined products grew from about 12 to a peak of about 16 MM Bbl/day.8 The increase in crude oil density and sulfur content, coupled with the growth in product demand and tighter sulfur specifications, triggered a general expansion in refining process capacity (SI Figure SI-9). Desulfurization capacity increased in response to both increasing crude oil sulfur content and imposition of stringent sulfur specifications for gasoline and diesel fuel. Conversion capacity increased in response to the increase in average crude oil density. (Conversion processescoking, catalytic cracking, and hydrocrackingfracture (“crack”) large, high-boiling hydrocarbon molecules into smaller, lighter molecules.) However, the decline in refined product (mainly gasoline) demand in recent years has led to underutilization of refining capacity, especially coking.9 Trends in Refining Sector Energy Use. U.S. refineries’ total energy use increased from about 3 quads to almost 3.4 quads between 1986 and 2000, but generally has declined since then. Refinery energy use per barrel of crude oil declined steadily from about 640 to about 570 K Btu between 1986 and 2005 (SI Figure SI-10).7 Refinery energy efficiency improved during the period, despite the increase in crude oil density and sulfur content. Since 2006, refinery energy use per barrel has increased slightly, reaching about 600 K Btu/Bbl in 2010. The reversal coincides with the imposition in 2006 of tighter federal standards on gasoline and diesel sulfur. Trends in Refining Sector CO2 Emissions. Energyrelated refinery CO2 emissions increased from about 200 MM (million) MeT in 1986 to about 220 MM MeT in 2010, but CO2 emissions per barrel of crude oil declined by 10% (SI Figure SI-11),8 reflecting the improvement in refinery energy efficiency.

Table 1. Average Properties of Some Crude Oils Run in U.S. Refineries properties country of orign

crude oil Brent West Texas Intermediate Synthetic Crude Oil (SCO) Arabian Extra Lt Export Alaskan North Slope (ANS) Forcados Export Arabian Light Export Kuwait Export Blend Marlim Export Cano Union Oriente Export Maya Heavy Export Western Canadian Select

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CRUDE OIL FUNDAMENTALS Hundreds of crude oils are in commerce; each a unique mixture of thousands of organic compounds, from methane (CH4) to 3698

API gravity (°)

sulfur (wt %)

40.0 39.8

0.5 0.3

Canada

32.2

0.2

Saudi Arabia light sour

38.1

1.1

U.S.

31.9

0.9

Nigeria Saudi Arabia medium sour

29.5 34.0

0.2 1. 9

Kuwait

30.9

2.5

20.1 25.2 25.0 21.3 21.0

0.7 0.9 1.4 3.4 3.5

U.K. U.S.

Brazil Colombia Ecuador Mexico Canada

crude oil class light sweet

medium medium sour

heavy sweet heavy sour

dx.doi.org/10.1021/es204411c | Environ. Sci. Technol. 2012, 46, 3697−3704


Policy Analysis

crudes shown in Table 1 are produced from Western Canadian oil sands. Though produced by unconventional means, they have properties similar to other conventional crude oils. The per-barrel refinery energy use of the Western Canadian crudes is comparable to that of conventional crudes of the same class.4,12,13 Light sweet crudes have higher refining value than heavier, sour crudes, because light crudes have higher natural yields (i.e., from crude distillation) of the components that go into the more valuable light products and because sweet crudes contain less sulfur. Light sweet crudes require somewhat less energy to process and call for lower capital investment to meet given product demand and quality specifications than heavy sour crudes. Refiners can either pay a price premium for less dense and/ or low sulfur crudes or incur higher investment in refinery capital stock and higher refining costs to take advantage of the relatively lower prices of heavier and/or higher sulfur crudes. Once a particular refinery has chosen a particular crude type (e.g., by density and sulfur content) for which to optimize its capital stock and operations, its crude purchase options are limited. A refinery configured to process light sweet crudes cannot efficiently or profitably process heavy and/or sour crudes. A refinery configured to process heavy crudes cannot process a large share of light crudes without under-utilizing its heavy crude processing capability. Accommodating a very large shift toward a heavier or higher sulfur crude requires significant investment to build new refining process capability. Each such project would require new permitting.

bottom-of-the-barrel”), converting it into light products and petroleum coke. Energy Use in U.S. Refineries. Energy use in the U.S. refining sector is equivalent to roughly 10% of the energy content of the crude oil processed. Approximately 2/3 of that refinery energy is generated internally, from the combustion of refinery byproduct; the rest comes from purchased natural gas, electricity, and steam.7 (SI Section 1.5). Refinery energy use tends to increase with increasing complexity, because complexity is a measure of the extent to which the refinery is modifying the natural yield pattern of its crude slate. Crude oil properties affect energy use in a given refinery because they influence the extent and severity of refinery processing needed to meet product volume and quality requirements. CO2 Emissions in U.S. Refineries. Refinery CO2 emissions are determined by total energy use and hydrogen consumption (SI Section 3.2), and (to a lesser extent) the mix of refinery energy sources. Refineries that rely most on the more-carbonintensive sources of energy (e.g., catalyst coke) tend to have higher CO2 emissions per barrel of crude throughput than refineries that rely on less-carbon-intensive sources (e.g., natural gas, still gas). (Catalyst coke is carbon that deposits on a process catalyst and subsequently is removed via a combustion process that is a source of refinery energy.)

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ASSESSING REFINERY ENERGY USE AND CO2 EMISSIONS USING LINEAR PROGRAMMING The technical factors that determine energy use and CO2 emissions can be captured in a suitably designed refinery LP model, such as those used throughout the refining industry for analyzing refining operations, economics, and capital requirements. Refinery LP models are detailed, engineering representations of the operations of the various refining processes and the material flows between processes.9 Such modelsnot econometric models or regression analysisare the appropriate method for analyzing relationships between crude oil characteristics, energy use, and CO2 emissions. See also SI Section 2. The estimates presented here of refinery energy use and CO2 emissions in the four crude slate scenarios were developed using an LP model of the aggregate U.S. refining sector. LP Models in the Refining Sector. Linear programming is a rigorous, widely used mathematical modeling technique for obtaining optimal solutions to technical and economic problems. Since the mid-1950s, LP modeling has been applied throughout the refining sector in a host of applications, including blend optimization, operations planning, and investment planning, as well as in techno-economic analysis of refining operations in general.15,16 Optimization models of refining (i) are based on fundamental engineering principles, (ii) represent refining operations processby-process, and (iii) embody process-specific data based on measurement. Lacking these attributes, regression models of refining operations are incapable of capturing refining’s complexity (and, in particular, the interplay between crude slate properties and refining operations.) Consequently, optimization modeling is the method of choice for analyzing refining operations and economics. Although it involves the application of complex scientific and engineering principles, oil refining is a mature and well-studied industry. Knowledgeable analysts can use publically available information to develop representative refinery LP models, such as the one used in this paper.17,18

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REFINING FUNDAMENTALS Petroleum refineries are large, capital-intensive, continuousflow manufacturing facilities that convert crude oils into dozens of products. The transportation fuels and other light products (e.g., liquified petroleum gases (LPG), lubricating oils, and petrochemical feedstocks) have the highest value; the heavy products (including home heating oil, fuel oil, and asphalt) generally have lower value. Most refineries in the U.S. are configured to maximize production of transportation fuels and to meet stringent environmental and industry standards. See also SI Sections 1.3, 1.4, and 1.5. Refinery Complexity. Each refinery is unique in terms of physical configuration, operating characteristics, and economics. Although no two are identical, they can be classified into groups based on refinery configuration and defined by complexity indexa numerical score that denotes the extent, capability, and capital intensity of a given refinery’s process units.14 The higher a refinery’s complexity, the greater the refinery’s capital investment intensity, and the greater the refinery’s ability to convert more of the heavy crude fractions into lighter, high-value products and to produce light products to more stringent quality specifications (e.g., ultralow sulfur fuels). (SI Section 1.3) The U.S. refining sector ranks highest in average refinery complexity; almost all U.S. refineries are either conversion or deep conversion refineries. Conversion refineries improve the natural yield patterns of the crudes they process to meet market demands for light products, but they produce some heavy, lowvalue products, such as residual fuel and asphalt. Deep conversion (or coking) refineries have additional capital stock in the form of process units (cokers) that enable the “destruction” of the heavy material in the crude slate (often referred to as “the 3699



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Rationale for Using a Refinery LP Model. Four aspects of refining operations must be explicitly addressed in delineating the relationship between crude slate properties and refinery energy use and CO2 emissions. First, refinery operations are extremely complex. Second, conversion and deep conversion refineries can adjust their operations in response to small changes in crude supply and product demand, but only within physical limits defined by the characteristics of these units and the properties of the crude oils. Exceeding these limits requires capital investment in new or expanded process capability. Third, refinery energy use is sensitive to crude slate properties and finished products specifications. Fourth, refinery energy use is distributed throughout the refinery. Refinery LP models capture and optimize these elements: complexity, limited flexibility, sensitivity to crude oil and product properties, and distributed energy use. Capturing Energy Use and CO2 Emissions in a Refinery LP Model. In refinery LP models, the standard representation of the various refining processes (which may be linear or nonlinear) includes each process’s per-barrel consumption (or production) of fuel, steam, and electricity. These elements are functions of operating conditions and feed properties. Energy inputs and outputs are usually expressed as foeb (fuel oil equivalent barrel = 6.3 million BTU), K lbs (thousand pounds) of steam, and Kwh (kilowatt-hours) of electricity, all per input barrel. Notably, the energy input/output coefficients for each process reflect information derived from plant test data (in a model of a specific refinery) or obtained from technology developers and public sources of operational data (in a generalized or notional model, such as the one used in this study). Refinery LP models embody an analytical framework for computing total refinery energy use and (by extension) refinery CO2 emissions. This framework involves • computing energy use by summing the direct energy inputs to each refining process (fuel, steam, and power); • selecting the least cost combination of internal and external energy sources available to the refinery; and • estimating refinery CO2 emissions by applying standard carbon emission factors to each of the energy sources. This framework includes electricity and natural gas used in the production of hydrogen. It does not include energy used in the production and transport of biofuels, energy used in the production and supply of purchased blendstocks, electricity used in nonprocess or off-site activities (such as oil movements, product blending, lighting, etc.), and incidental energy losses due to flaring, fugitive emissions, etc. Some elements of this framework do not match the U.S. Department of Energy’s Energy Information Administration (EIA) data collection and reporting scheme for refinery energy use. For example, EIA includes refinery energy used to produce electricity sold to the power grid, as well as refinery energy used in nonprocess and off-site activities and energy losses. EIA does not include energy used in the production of merchant hydrogen. Consequently, in studies such as this one, total refinery energy use returned by the aggregate refining model must be calibrated to the corresponding aggregate refinery energy use reported by EIA for the most recent year. (SI Section 5).

Policy Analysis

SCENARIOS FOR THE FUTURE U.S. CRUDE SLATE

Current U.S. Crude Slate. In 2010, the U.S. refining sector processed about 14.7 MM Bbl/day of crude oil: about 5.6 domestic and 9.1 MM Bbl/day imported. On average, the domestic crudes (33.1° API and 0.8 wt % sulfur) are lighter and sweeter than the imported crudes (28.3° API and 1.75 wt % sulfur). See also SI Section 4. In 2010, U.S. crude imports comprised • about 1.8 MM Bbl/day from Western Canada: about 33% conventional crudes, 51% bitumen crudes, and 16% light synthetic crude oils (SCO) produced by upgrading bitumen crudes • the bitumen crudes are delivered in the form of synbit and dilbitmixtures containing bitumen crudes and diluents (light hydrocarbons, conventional crudes, and/ or SCO) • about 5.1 MM Bbl/day from Caribbean and Atlantic Basin (CAB) sources: Eastern Canada, Mexico, South America, and West Africa • about 2.2 MM Bbl/day from more remote sources in the rest of the world (ROW) Of the CAB imports, about 2.6 MM Bbl/day (51%) were light and medium crudes and 2.5 MM Bbl/day (49%) were heavy crudes. On average, the CAB imports were heavier but lower in sulfur than the ROW imports. Of the combined CAB and ROW imports, about 4.7 MM Bbl/day were light and medium crudes, and about 2.6 MM Bbl/ day were heavy crudes. EIA Reference Case Crude Oil Forecast for 2025. The AEO 2011 Reference Case forecast for 2025 indicates the following crude oil sourcing:2 • domestic crude supply: 5.9 MM Bbl/day • foreign crude supply: 8.3 MM Bbl/day This forecast indicates a 0.55 MM Bbl/day decrease in total U.S. crude oil consumption, coupled with a 0.3 MM Bbl/day increase in domestic crude production (relative to 2010) and slight decreases in the density and sulfur content of the domestic crude. This is consistent with private sector forecasts,19,20 which indicate continuing decline of heavy, high sulfur crude volumes from Mexico (e.g., Maya) and increases in U.S. onshore crude production. Scenarios for the Future U.S. Crude Slate. To characterize a reasonably aggressive range of heavier and higher sulfur crudes in the U.S. crude slate, this study considers four scenarios. Each scenario recognizes (i) increased domestic crude oil production and (ii) decreased total U.S. crude oil consumption, as forecast for 2025 in the AEO 2011 Reference Case. The scenarios (S1, S2, S3, S4) are designed to define a broad yet plausible range of future U.S. crude slates, particularly with respect to the sourcing, density, and sulfur content of U.S. crude oil imports: S1. The sourcing and average properties of the imported crude slate are the same as in 2010. This is the baseline scenario. S2. An additional 2.4 MM Bbl/day of Western Canadian crudes enter the U.S., displacing all crude oil imports from ROW sourcesregardless of crude typeand some from CAB sources. Average properties of the remaining CAB imports are unchanged from 2010. 3700



Policy Analysis

S3. The additional 2.4 MM Bbl/day of Western Canadian crudes displaces only light and medium crude oils from CAB and ROW sources. Average properties of the remaining light and medium crudes and of heavy crudes imported from CAB and ROW sources are unchanged from 2010. S4. The additional 2.4 MM Bbl/day of Western Canadian crudes displaces all crude from ROW sources and a small amount from CAB sources, as in Scenario S2. At the same time, the volume share of heavy crudes imported from CAB increases to 75% (from 49%), resulting in a significant increase in the density of the imported crude oil slate. The additional 2.4 MM Bbl/day of Western Canadian crude oils in Scenarios S2, S3, and S4 corresponds to the optimistic production forecast by the Canadian Association of Petroleum Producers (CAPP).21 Table 2 summarizes the projected 2025 sourcing and average properties of the U.S. aggregate crude oil slate in each scenario.

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METHODOLOGY FOR ASSESSING THE 2025 SCENARIOS The LP model used in this study incorporates the energy and CO2 accounting framework described above. The model represents projected operations of the U.S. refining sector as a whole in 2025. This aggregate model, developed using MathPro Inc.’s proprietary refinery modeling system (ARMS),16 has been used in a number of previous studies, including other studies of refinery energy use and CO2 emissions.4 See SI Section 5. The refinery energy accounting in the model is based on process-by-process energy use data obtained from the open literature and from refinery process licensors. The refinery CO2 accounting uses standard, published carbon intensity factors for the various refinery fuels (SI Table SI-5).22 Calibration. The model was calibrated by configuring it to represent aggregate, year-round operations of the U.S. refining sector in 2010. The 2010 U.S. refinery crude oil slate was set by aggregating refinery-level crude oil import data, state and offshore crude oil production data, PADD-level crude oil property data, and total refinery input and output volumes, all reported by EIA.14 Solutions returned by the aggregate refining model were compared with EIA-reported data on refining sector operations to verify that the model adequately represented the U.S. refining sector’s aggregate operations, as of 2010. In particular, refining sector energy use and CO2 emissions returned by the model were compared with reported energy use and CO2 emissions for the U.S. refining sector, and refined product shadow prices returned by the model were compared with average prices of these products reported by EIA.7 Results returned by the calibrated model were then normalized to EIA’s reported values for U.S. refinery energy use and CO2 emissions for 2010. (SI Section 5) Scenario Analysis. The calibrated model was reconfigured to represent aggregate year-round operations of the U.S. refining sector in 2025 for each of the imported crude oil scenarios. Each model run incorporated (i) the appropriate imported crude slate; (ii) EIA’s AEO 2011 Reference Case forecasts of domestic refined product volumes, biofuels volumes, and energy prices; and (iii) all relevant quality specifications for refined products in effect now or scheduled to take effect before 2025. In each instance, the model was allowed to add refining process capacity and to increase crude throughput volume as needed to accommodate changes in crude slate quality at minimum total cost while maintaining product outputs at the specified volumes. (It is unlikely that the U.S. refining sector would alter its crude slate without providing the additional facilities needed to continue producing refined products volumes consistent with market demand.) To illustrate the separate effects of crude oil properties and finished product standards on refinery energy use and CO2 emissions, two variants were analyzed for each scenario: with and without the Tier 3 gasoline sulfur and MARPOL Annex VI sulfur standards. The results returned by the refining model for each scenario include estimates of crude oil use, capacity requirements, energy use, and CO2 emissions in 2025.

Table 2. Projected Sourcing and Average Properties of the 2025 U.S. Crude Slate, by Scenario 2025 scenarios baseline 2010 actual total U.S. crude slate volumes 14.7 (MM Bbl/day) domestic 5.6 imports 9.1 Western Canada 1.8 CAB 5.1 ROW 2.2 average properties API gravity (° API) 30.0 sulfur content (wt %) 1.39 imported crudes only average properties API gravity (° API) 28. 3 sulfur content (wt %) 1.75

lower quality imported crudes

S1

S2

S3

S4

14.2

14.2

14.2

14.2

5.9 8.3

5.9 8.3 4.2 4.1 0

5.9 8.3 4.2 3.4 0.7

5.9 8.3 4.2 4.1 0

30.6 1.30

28.4 1.60

27.6 1.76

27.1 1.76

28.3 1.75

27.7 1.46

24.9 1.99

23.4 2.01

• be heavier and higher in sulfur than current Western Canadian crude supplies.

Scenario S1 (the baseline) reflects properties of U.S. crude imports ca. 2010. Scenarios S2, S3, and S4 depict U.S. crude slates having higher density and sulfur content than the current U.S. crude slate. S4, the most extreme scenario, represents simultaneous and substantial growth in U.S. imports of both Western Canadian heavy crudes and CAB heavy crudes. This scenario is intended to represent the maximum feasible increase in the average density and sulfur content of U.S. crude oil imports by 2025, consistent with the potential for increased production of Western Canadian crudes. The increased production of Western Canadian crudes denoted in S2, S3, and S4 represents the highest growth forecast in the set of forecasts recently issued by Canadian oil producers.21 This forecast indicates that Western Canadian crude supplies to U.S. markets in 2025 would • increase by about 2.4 MM Bbl/day (i.e., no sales to other markets), • comprise approximately 11% conventional crude, 7% SCO, and 83% blended bitumen crude (i.e., dilbit and synbit), and 3701



Policy Analysis

Comparison of the estimated refinery energy use and CO2 emissions returned for each scenario indicate the extent to which the shifts to a higher density, higher sulfur crude slate would change the U.S. refining sector’s aggregate refinery energy use and CO2 emissions, relative to the baseline.

Table 4. Projected Change in U.S. Refining Capacity Use, Energy Use, and CO2 Emissions vs. 2010, by Scenario 2025 scenarios baseline

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S1

ESTIMATED U.S. REFINERY ENERGY USE AND CO2 EMISSIONS IN THE 2025 CRUDE SLATE SCENARIOS In the Baseline scenario (S1), estimated U.S. refinery energy use and CO2 emissions in 2025 are slightly higher than the reported values in 2010. This result reflects increased requirements for desulfurization and hydrogen production capacity, as well as the offsetting effects of the forecast reduction in U.S. refinery crude runs and the slight decrease in domestic crude oil density and sulfur content indicated in EIA’s Reference Case for 2025. For scenarios S2, S3, and S4, Tables 3 and 4 summarize the study’s primary results regarding estimated U.S. refinery crude

with new fuel sulfur standards Δ refining capacity required crude distillation K BBl/day coking K BBl/day hydrogen K foeb/day production (merchant) Δ refinery energy use quads/year MM BTU/Bbl % Δ refinery CO2 emissions MM MeT/year MeT/Bbl % ex new fuel sulfur standards Δ refining capacity required crude distillation K BBl/day coking K BBl/day hydrogen K foeb/day production (on purpose) Δ refinery energy use quads/year MM BTU/Bbl % Δ refinery CO2 emissions MM MeT/year MeT/Bbl %

Table 3. Projected U.S. Refining Capacity Use, Energy Use, and CO2 Emissions, by Scenario (2025) 2025 scenarios baseline S1 average crude quality API gravity ° API 30.6 sulfur content wt % 1.30 modeling results with new fuel sulfur standards refinery crude runs MM Bbl/day 14.16 refinery energy use quads/year 3.47 MM BTU/ 0.644 Bbl refinery CO2 MM MeT/ 258 emissions year MeT/Bbl 0.0478 modeling results: ex new fuel sulfur standards refinery crude runs MM Bbl/day 14.08 refinery energy use quads/year 3.38 MM BTU/ 0.631 Bbl refinery CO2 MM MeT/ 252 emissions year MeT/Bbl 0.0469

lower quality imported crudes S2

S3

S4

28.4 1.60

27.6 1.76

27.1 1.76

14.31 3.60 0.660

14.40 3.66 0.667

14.41 3.69 0.672

272

279

282

0.0499

0.0508

0.0514

14.2 3.48 0.643

14.29 3.55 0.651

14.31 3.57 0.654

264

270

272

0.0488

0.0497

0.0499

runs, energy use (SI Section 5), and CO2 emissions in 2025, relative to the S1 baseline. • In all three scenarios, estimated refinery energy use and CO2 emissions are higher than in 2010. However, even in the most extreme crude quality scenarios (S3 and S4), the increases are modest. • Estimated increases in refinery energy use range from 3.7% to 6.3%; estimated increases in CO2 emissions range from 5.4% to 9.3%. These estimates reflect the combined effects of changes in crude oil density and sulfur content and finished product sulfur specifications. • Tighter sulfur specifications on gasoline and marine diesel fuel account for about 10%−20% of the estimated increases in refinery energy use and about 25%−30% of the estimated increases CO2 emissions. The effects of

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lower quality imported crudes S2

S3

S4

base base base

148 391 42

240 627 59

246 645 74

base base base base base base

0.13 0.016 3.7 14 0.002 5.4

0.19 0.023 5.5 21 0.003 8.1

0.22 0.028 6.3 24 0.004 9.3

base base base

131 365 42

217 579 58

239 656 61

base base base base base base

0.10 0.012 3.0 12 0.0019 4.0

0.17 0.020 5.0 18 0.0028 5.9

0.19 0.023 5.6 20 0.003 6.3

tighter sulfur specifications increase with increasing crude slate density and sulfur content. • Estimated total U.S. refinery crude runs, energy use, and CO2 emissions all increase incrementally with average density and sulfur content of the crude slate. The more intensive refinery processing entailed by higher crude density and higher sulfur content leads to some reduction in refinery processing yields (and hence increased crude volume) in these scenarios. This effect accounts for the increased requirement for crude distillation capacity. • Processing the higher density, higher sulfur crude slates in scenarios S2, S3, and S4 calls for significant additions to refinery processing capacity, most notably distillation, coking, and hydrogen production. The estimated investment requirements for these three processes alone would range from about $11 billion in S2 to about $19 billion in S4 ($2010, U.S. Gulf Coast location).

DISCUSSION

Scenarios S2, S3, and S4 portray U.S. aggregate crude slates in 2025 that (i) are significantly heavier and higher in sulfur content than the current or any previous U.S. crude slate, (ii) imply significantly faster average annual growth rates in crude density and sulfur content than have been experienced over the past 25 years, and (iii) reflect the most ambitious forecast of growth in Canadian bitumen crude production (and the assumption that all production goes to U.S. markets). 3702



Policy Analysis

Figure 1. Refinery GHG emissions estimated in this analysis are consistent with estimates in State Department and CERA studies.

the results of this analysis indicate, refinery energy use and CO2 emissions are also related to the stringency of regulations governing finished product properties, such as sulfur content. Changes in refinery energy and CO2 intensity do not, in themselves, imply corresponding increases in emissions of criteria air pollutants and hazardous air pollutants. Refinery emissions of these substances are governed by environmental regulations and standards that are independent of the refinery crude slate. Individual refineries are configured to process a specific type of crude oil slate. Once its configuration has been established, a refinery’s crude purchase options are limited. A refinery configured to process light and/or sweet crudes cannot efficiently or profitably process heavy and/or sour crudes. A refinery configured to process heavy crudes cannot process light crudes without surrendering the economic benefits of its investments in heavy crude processing capability and leaving some capacity idle. Consequently, a refinery’s configuration allows one to infer the general type of crude slate the refinery is designed to process. Finally, assessments of refinery energy and CO2 intensity should employ established LP modeling tools and methods, and not econometric models or regression analysis. Such methods cannot capture the complexity of refinery operations and economics and therefore do not yield useful information.

The analysis indicates U.S. refinery energy use in Scenarios S2, S3, and S4 increasing by ≈3.8%−6.5% and CO2 emissions increasing by ≈5.5%−9.3% relative to the baseline. These estimates account for both changes in crude slate properties and imposition of new fuel sulfur specifications. Refinery emissions of CO2 (as well as those associated with production and any associated field upgrading) are a small component of the life-cycle CO2 emissions associated with crude oil use. The emissions associated with end-use combustion of refined products exceed by an order of magnitude those associated with refining. This analysis demonstrates that refining the maximum contemplated volume of Canadian oil sands crudes in U.S. refineries would lead to a small increase in a small component of life-cycle CO 2 emissions. Two factors not reflected in the analysis could work to reduce future refinery energy use and CO2 emissions, regardless of crude slate. These factors are continued improvements in overall refinery energy efficiency and further reductions in the volume of hydrocarbon-based gasoline and diesel fuel, in response to possible future mandates further increasing the biofuels content of U.S. gasoline and diesel fuel. The estimates of U.S. refinery CO2 emissions developed in this analysis are consistent with recent estimates of the life cycle emissions associated with Canadian bitumen crudes13,23 and are an order of magnitude less than the recent estimate3 that processing heavy oil or bitumen blends could increase CO2 emissions by 1.6−3.7 gigatons/year (Figure 1 and SI Section 7). The latter estimate appears to reflect, in part, the assumption that the entire refining sector processes nothing but high density, high sulfur crudes to the exclusion of all other crudes, domestic or imported. Crude slate density and sulfur content are not the sole predictors of refinery energy and CO2 emission intensity. As

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ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This information is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. 3703



Policy Analysis

Notes

(22) Toward a Consistent Methodology for Estimating Greenhouse Gas Emissions from Oil and Natural Gas Industry Operations; Table 3; American Petroleum Institute: Washington, DC. (23) Final Environmental Impact Statement for the Proposed Keystone XL Project; Executive Summary; U.S. Department of State, Bureau of Oceans and International Environmental Affairs: Washington, DC, August 26, 2011. (24) U.S. Energy Information Administration. Company-Level Petroleum Imports 2010; http://explore.data.gov/Energy-andUtilities/Company-Level-Petroleum-Imports-2009/bbpd-grve. (25) U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks; April 2011; http://www.epa. gov/climatechange/emissions/usinventoryreport.html. (26) Emissions of Greenhouse Gases in the United States 2009; U.S. Energy Information Administration: Washington, DC, March 2011.

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS

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REFERENCES

This work was funded by Chevron Energy Technology Company.

(1) U.S. Energy Information Administration Website; Crude Oil Input Qualities; http://www.eia.gov/dnav/pet/pet_pnp_crq_dcu_ nus_a.htm. (2) Annual Energy Outlook 2011; U.S. Energy Information Administration: Washington, DC, April 2011; http://www.eia.gov/ forecasts/aeo/data.cfm. (3) Karras, G. Combustion Emissions from Refining Lower Quality Oil: What is the Global Warming Potential? Environ. Sci. Technol. 2010, 41 (24), 9584−9589. (4) Comparison of North American and Imported Crude Oil Lifecycle GHG Emissions; TIAX Case No. D-5595; TIAX LLC: Palo Alto, CA, July 2009 (Prepared for Alberta Energy Research Institute). (5) Global Warming Solutions Act. California Assembly Bill 32: California Air Resources Board Website; http://www.arb.ca.gov/cc/ ab32/ab32.htm. (6) EPA Finalizes More Stringent Standards for Control of Emissions from New Marine Compression Ignition Engines at or Above 30 Liters per Cylinder; EPA-420-F-09-068; U.S. Environmental Protection Agency: Ann Arbor, MI, December 2009. (7) Petroleum Supply Annual 2010, Vol. 1; U.S. Energy Information Administration: Washington, DC, July 2011; http://www.eia.gov/ petroleum/supply/annual/volume1/. (8) U.S. Energy Information Administration. Refinery Net Production; http://www.eia.gov/dnav/pet/pet_pnp_refp2_dc_nus_ mbbl_m.htm. (9) U.S. Energy Information Administration. Refinery Capacity Report, Table 10a; http://www.eia.gov/petroleum/refinerycapacity/. (10) Bredeson, L.; et al. Factors Driving Refinery CO2 Intensity, With Allocation into Products. Int. J. Life Cycle Assess. 2010, 15, 817− 826. (11) World Oil and Gas Review, 2011; ENI Company, February 2011. (12) Life Cycle Assessment Comparison of North American and Imported Crudes; Jacobs File No. AERI 1747; Jacobs Consultancy and Life Cycle Associates, July 2009 (Prepared for Alberta Energy Research Institute). (13) Oil Sands, Greenhouse Gases, and European Oil Supply; IHS CERA Inc.: Cambridge, MA, 2011. (14) Nelson, W. L. Nelson Complexity Index. Oil Gas J. 1976, Sept. 13, 20, and 27. (15) Hirshfeld, D. S. Operations Research in Petroleum Refining. In Encyclopedia of Operations Research and Management Science, 3rd ed.; Gass, S. I., Ed.; Springer Science & Business Media: New York, to be published in 2012. (16) Overview of the Advanced Refinery Modeling System; MathPro, Inc.: Bethesda, MD, January 2003; http://www.mathproinc.com. (17) Parkash, S. Refining Processes Handbook; Elsevier: Burlingtion, MA, 2003. (18) Williams, H. P. Model Building in Mathematical Programming, 4th ed.; John Wiley & Sons: New York, 1999. (19) World Crude Oil Markets: Spotlight on Mexican Production and Exports; First Energy Capital, March 2009; http://www.firstenergy. com/. (20) Tight Oil in the Rocky Mountains; Upstream Insight North America; Wood McKenzie Limited, February 2011; http:// housemajority.org/coms/hes/27/BP_Response_tight_oil_20110225. pdf. (21) Crude Oil Forecast, Markets and Pipelines, 2011; Canadian Association of Petroleum Producers: Calgary, AL, Canada, June 2011. 3704


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