Greenhouse Gas Emission Reductions Through National Ambient Air Quality Standards: The Role of Regional Low Carbon Fuel Standards Abstract

Transcription

1 Greenhouse Gas Emission Reductions Through National Ambient Air Quality Standards: The Role of Regional Low Carbon Fuel Standards Jeff Kessler (University of California, Davis)*, Benjamin VanGessel (University of Michigan) *Corresponding Author: Jeff Kessler - Graduate Student Researcher University of California, Davis - Institute of Transportation Studies 1605 Tilia Street Davis, CA E- mail: jkessler@ucdavis.edu Primary Phone: Abstract Classification of carbon dioxide as a criteria pollutant under the National Ambient Air Quality Standard (NAAQS) may effectively trigger a form of cap and trade policy that promotes reduction of greenhouse gas (GHG) emissions on a regional basis over time. While economy- wide cap and trade policy supports abatement at the lowest possible cost, it is not the most effective option for reducing GHG emissions in the transportation sector. Instead, we propose that transportation emission reductions be addressed through a Low Carbon Fuel Standard (LCFS) implemented through State Implementation Plans. Regional LCFS implementations may interact differently in isolation than when they are harmonized. We have modeled LCFS implementation in New Jersey, Oregon, Vermont, and Washington in isolation and as an aggregated region to reflect what could occur under NAAQS- based LCFS implementation. Results indicate that harmonized standards across regions may substantially ease the burden of transitioning away from gasoline and diesel compared to isolated regional standards. Additionally, the existing implementation of the Environmental Protection Agency s Motor Vehicle Emissions Simulator model does not account for life- cycle GHG emissions, meaning that fuel policy will not factor into State Implementation Plans unless modifications to the model are made to account for life- cycle carbon dioxide emissions associated with fuel types. 1

2 1. Introduction Growing concerns over air pollution, energy independence, and climate change motivate the search for new transportation solutions. In the United States, transportation accounts for 27 percent of greenhouse gas (GHG) emissions (Metz, 2007; U.S. Environmental Protection Agency, 2011). In particular, light- duty vehicles (LDV), cars and trucks with gross vehicle weight of less than 8,500 lbs, produce nearly 60 percent of U.S. transportation sector GHG emissions (Olabisi et al., 2009). Therefore, the need to address GHG emissions from this subset of the transportation sector is crucial. While there are a variety of policy approaches to reduce GHG emissions, this paper examines the implications of regulating GHGs under the Clean Air Act (CAA) by establishing GHG National Ambient Air Quality Standards (NAAQS). Though this paper does not evaluate the technical or political feasibility of GHG NAAQS, transportation sector GHG reductions could be modeled after the successful reductions of nitrogen oxide and nitrogen dioxide (NOx) emissions through the nitrogen oxides NAAQS and the NOx Budget Trading Program (NBP). The NBP set regional emissions budgets that resulted in substantial reductions (Napolitano, Stevens, Schreifels, & Culligan, 2007). A similar program could be established for GHG emissions (Burtraw, Fraas, & Richardson, 2011; Richardson, Fraas, & Burtraw, 2010). A NAAQS- based approach would establish a GHG emissions threshold that would span the United States. To comply, states must develop a plan of action effectively promoting a harmonized national reduction plan with regionally specific goals similar to the NBP. As result, this may trigger a form of cap and trade policy, like the NBP, that promotes reduction of greenhouse gas emissions on a regional basis over time. While an economy- wide cap and trade policy can encourage reductions in GHG emissions, emission reductions from the transportation sector are higher on the marginal abatement cost curve than other emission sources in the near- term (Yeh, Farrell, Plevin, Sanstad, & Weyant, 2008). As such, a transportation- specific carbon policy, like a Low Carbon Fuel Standard (LCFS), is also necessary to motivate the transportation sector to pursue carbon abatement. Section 2 provides background on the National Ambient Air Quality Standard and the Low Carbon Fuel Standard. Section 3 goes on to discuss the modeling assumptions and methodology used to assess the role that a Low Carbon Fuel Standard may have in reducing GHG emissions at the regional level, and Section 4 provides the results from the model and relevant discussion. Section 5 assesses the implications and difficulties associated with complying with a Low Carbon Fuel Standard, including deployment of alternative fuel vehicles (AFVs) and infrastructure. Lastly, Section 6 is the conclusion and summary of our study. 2. Background The Clean Air Act and National Ambient Air Quality Standards Congress established the National Ambient Air Quality Standards in the 1970 Clean Air Act ("Clean Air Act Amendments of 1970," 1970). Rather than setting limits on individual emission sources, NAAQS set limits on specific pollutant concentration in the ambient air (42, USC 7409(a)). NAAQS are established to regulate six criteria pollutants considered harmful to public health and the environment. These pollutants include carbon monoxide, nitrogen dioxide, sulfur dioxide, particulate matter, ozone, and lead (22 40 C.F.R ; 40 C.F.R ). NAAQS are regularly reviewed and revised, reflecting improvements in the understanding of risk and exposure to various pollutants (42 USC, 7409(d)). Areas known as Air Quality Control Regions may be designated as non- attainment when ambient air monitoring indicates that an air quality standard (as defined by the NAAQS) is not being met.

3 States are required to compose State Implementation Plans (SIP) to attain and maintain the NAAQS for non- attainment Air Quality Control Regions. A SIP is essentially a roadmap to NAAQS attainment. It considers the current emissions inventory of the region, establishes an emission budget, and proposes strategies to achieve conformity. Failure to satisfy the SIP requirements may make the region ineligible for Federal transportation funds or result in the termination of near- term transportation projects (42 USC 7509) Clean Air Act and Greenhouse Gas Regulation On April 2, 2007, the Supreme Court ruled that greenhouse gases, such as carbon dioxide, are air pollutants covered by the Clean Air Act ("Massachusetts v. EPA, 549 U.S. 497," 2007). Massachusetts v. EPA spurred a national debate concerning how, if at all, the Environmental Protection Agency (EPA) should regulate greenhouse gases. Congressional efforts to enact comprehensive GHG legislation have stagnated forcing the EPA to develop and finalize a number of GHG regulations, each of which is or has been the subject of litigation. The EPA has explored many approaches to regulate mobile source greenhouse gases. In May 7, 2010, the EPA and the National Highway Traffic Safety Administration finalized the Light- Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards Rule (LDV Rule). This rule is simply a continuation of the longstanding Corporate Average Fuel Economy (CAFE) standards first enacted by the U.S. Congress in 1975 ("Light- Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards; Final Rule," 2010). This regulation now limits the amount of carbon that can be emitted from a vehicle per mile traveled, encouraging advancements in vehicle efficiency, but has limited impact on the carbon intensity of the fuel being used. As such, there is motivation to develop a greenhouse gas NAAQS. A greenhouse gas NAAQS would likely follow the well- worn path of other NAAQS development processes. The EPA has already established reporting infrastructure to report GHGs on a CO 2 equivalent (CO 2 e) basis. It would follow that a GHG NAAQS would use a CO 2 e basis for consistency. Using this equivalency, the EPA could structure a GHG NAAQS, using life- cycle GHG emissions. Similarly to the current NOx NAAQS, this approach effectively initiates a GHG credit trading process akin to the NOx Budget Trading Program. The success of the NBP provides many lessons for a similar GHG scheme. The NBP is an important example of cooperation between states, regional planning organizations, and the EPA to provide harmonized and consistent regional policies (Napolitano et al., 2007). The NBP further demonstrates how the EPA and states can work together to identify and implement solutions to address pollutant transport across state boundaries that impact public health and the environment. The program demonstrates that industry sectors can effectively participate and that keeping rules simple and clear delivers value. This market- based approach has led to highly cost effective improvements in air quality in the eastern United States, with dramatic improvements in attainment of the NAAQS (Napolitano et al., 2007). Creation of a GHG NAAQS may effectively trigger a form of cap and trade policy that promotes reduction of GHG emissions on a regional basis over time; however, emission reductions from the transportation sector are higher on the marginal abatement cost curve than other emission sources in the near- term (Yeh et al., 2008). As such, a transportation- specific carbon policy, like a Low Carbon Fuel Standard (LCFS), is a necessary, complementary component to motivate carbon abatement from the transportation sector. 3

4 2.3 - Low Carbon Fuel Standards Many different policy options have been considered to reduce GHG emissions from the transportation sector. These range from cap and trade regulations to volumetric fuel mandates (Holland, Hughes, Knittel, & Parker, 2011; Ross Morrow, Gallagher, Collantes, & Lee, 2010). Fuel policies like the California Low Carbon Fuel Standard have gained traction in recent years with LCFS- like policies being implemented in the European Union, British Columbia, and discussions for implementation taking place in Oregon and other states in the U.S. A LCFS is a technology- promoting, market- based mechanism that may be used to facilitate GHG emission reductions in the transportation sector by lowering the average fuel carbon intensity over time (Yeh & Sperling, 2010). Such a policy approach can be implemented under a state s SIP, and may work together with CAFE standards and cap and trade programs to promote reductions in carbon emissions (Farrell & Sperling, 2007). California s LCFS policy framework has set precedence in the United States, and other countries around the world have also turned to the California model as the basis for instituting their own LCFS. The European Union developed, in parallel, and imposed a Fuel Quality Directive (FQD) shortly after California instituted their LCFS, and British Columbia has also followed suit with a Renewable and Low- carbon Fuel Requirement Regulation (LCFRR). The Northeast and Mid- Atlantic states, Oregon, Washington and Midwestern states have also considered implementing LCFS policies (Yeh et al., 2012). All of the instituted LCFS policies create a baseline level for transportation fuel carbon intensity, and require a reduction (e.g. 10% for California) from that baseline level over a set period of time (e.g. within 10 years). The baseline level and fuel carbon intensities are determined through life- cycle assessment (LCA), which captures total GHG emissions across entire fuel production pathways, from extraction, processing, refining, transportation and distribution to end- uses (California Air Resources Board, 2011). This LCA approach is important as even though upstream emissions account for only 20 percent of most petroleum fuels, they can account for more than 90 percent of emissions for low- carbon fuels such as electricity and hydrogen from renewable sources. In the following sections we look at modeling LCFS policy implementation in select regions as independent policy implementations, as has happened in California, and as harmonized, regional implementations with a national scope as may happen if a NAAQS- LCFS strategy is adopted. These implementations are contingent on a number of political factors, and hinge on addressing carbon emissions throughout the full fuel lifecycle - - an emission reduction concern that has been weakly implemented at the Federal level. 3. Methodology and Data Technology Scenario Model The following four regions were selected for analysis: New Jersey, Oregon, Vermont, and Washington. These regions were chosen as they are within the top five states, excluding California (where considerable LCFS analysis has already been conducted), for on- road transportation- related carbon emissions as a percent of total greenhouse gases emitted on a statewide basis (Environmental Protection Agency, 2012b). Energy projections out to 2050 for each state were modeled on a 5- year basis using the U.S. Environmental Protection Agency s Motor Vehicle Emissions Simulator (MOVES) 2010b model. MOVES 2010b is the prescribed tool for estimating emissions from on- road vehicles. This model provides overall diesel and gasoline pool energy requirements in addition to the baseline ethanol demand for each state. For the purposes of this

5 evaluation, national default data and allocation factors for local fleet and activity inputs were used to make rough estimates of statewide emissions for the selected geographies. Each transportation energy profile was compared to overall GHG emissions given by the MOVES model, and the carbon intensity for 1990 and 2010 was calculated from MOVES outputs. MOVES does not take into account life- cycle GHG emissions; therefore, a constant 18.2 gco2e/mj was added to both gasoline and diesel carbon intensities to account for the emissions associated with fuel production (Environmental Protection Agency, 2012b). Ethanol carbon intensity was assumed to follow the Renewable Fuel Standard mandate, in which ethanol counts as a renewable fuel and has a carbon intensity that is at least 20 percent lower than the life- cycle GHG emissions of gasoline for corn- based ethanol, and 50 percent lower for sugarcane ethanol (Environmental Protection Agency, 2012a). The LCFS carbon intensity reduction schedule was modeled based on estimated technology diffusion for next- generation ethanol over the 40- year period of analysis starting with sugarcane ethanol values (50 percent reduction from gasoline, gco2e/mj) in 2015, and moving toward cellulosic ethanol values from farmed trees (2.4 gco2e/mj) by 2050 (California Air Resources Board, 2009). The standard National Energy Modeling System (NEMS) diffusion curve was utilized to limit the market penetration of new cellulosic fuels (U.S. Energy Information Administration, 2012). This resulted in a final achievable biofuel fuel carbon intensity of gco2e/mj by 2050 (Table 3.1). Table 3.1 Ethanol fuel carbon intensity schedule in g CO2e per Megajoule Year Carbon Intensity Based on this analysis, 23 g CO2e/MJ was selected to be an achievable target for the final fuel carbon intensity of the gasoline fuel pool by Given this value, LCFS policy would serve to reduce regional GHG emissions from transportation by 50 percent from 1990 levels by This amounts to a 74 percent reduction in the average fuel carbon intensity from the 2010 baseline by Rather than arbitrarily assigning a reduction schedule, Equation 1 is an objective function created to minimize the rate of change in carbon intensity over each year as a function of the standard deviation across each 5- year reduction timeframe such that an average fuel carbon intensity of 23 g CO2e/MJ was achieved by 2050 for the gasoline fuel pool. Solving this optimization problem led to a reduction schedule for each region that roughly corresponds to Table 3.2. If LCFS policy is implemented through NAAQS, the reduction schedule and final carbon intensity value may be substantially different than what was selected for analysis in this paper, and actual values and schedules will likely be influenced through the political process. 5

6 min max!!"#$#%,!!!!"#$#%,!!!,!!"#$%&'(,!!!!"#$%&'(,!!!!!"#$#%,!!!!!"#$%&'(,!!! + st. dev Y!"#$#% + st. dev(y!"#$%&'( ) (eq. 1) where Y is the LCFS reduction target for a given 5- year period, t, in either the gasoline or diesel fuel pool. Table 3.2 Carbon Intensity Reduction Schedule Year Gasoline AFCI Diesel AFCI % Change - 74% - 74% Similar to the California LCFS, separate pools for diesel fuel and gasoline have been created (California Air Resources Board, 2011). Each region has a slightly different carbon intensity reduction schedule due to marginally different combustion profiles given by the MOVES output. These carbon intensity reduction schedules were utilized to model scenarios for compliance in each of the four target geographies. Scenario models illustrate the feasibility of compliance and determine what the makeup of the transportation sector might need to look like from the present through 2050 to contribute to substantial decarbonization as specified by the LCFS reduction schedule. Cost was not endogenous to the model, and instead the model optimized fuel rollout and market penetration for alternative technologies based on minimizing the annual growth rate for ethanol/drop- in fuels and renewable diesel/biodiesel, subject to the percent market share of the fuel pool being substituted. That is, increases in the average fuel growth rate for the larger fuel pool (gasoline) received greater weight than increases in the average fuel growth rate for the diesel pool. Average annual growth rate for electric and hydrogen vehicle adoption was also factored in to the objective function without additional fuel pool weighting.!!"#$%&'(,!! min!"!!"#$,!!!!"!!"#$,!!! +!!"#$#%,!!!"#$"%&%',!!!!"#$"%&%',!!! +!!"!#$%&#,!!!!"!#$%&#,!!!!!"!#$,!!!"!!"#$,!!!!!"!#$,!!!"#$"%&%',!!!!!"!#$%&#,!!! (eq. 2) Where x is the energy provided by a fuel type in gallons of gasoline equivalent fuel for a given 5- year compliance period, t. This approach provides an alternative means of analyzing the impact that LCFS policy may have compared to other models in the literature (Chen & Morrison, 2011; Yeh & Sperling, 2010). The

7 objective function was minimized using the Solver Add- on for Microsoft Excel such that LCFS credit banking was allowed under the LCFS, but deficit banking was not (Rubin & Leiby, 2013). Additional constraints were provided for the early periods of implementation to prevent ethanol volumes from exceeding the 10- percent ethanol blend wall, and to prevent diesel fuel use from exceeding 15 percent of the fuel pool. These constraints were removed starting in 2020 and 2025 respectively. Natural Gas use was treated exogenously based on optimistic market penetration rates. Because deployment of natural gas vehicles is highly sensitive to market price, promotion of this fuel was not treated endogenously in the model (by minimizing market growth rate), and projections were made by modifying a diffusion curve assuming that natural gas prices remain attractive through 2025, at which point natural gas use remains constant through These projections are inline with Citi s projections for 30 percent use of natural gas vehicles in the heavy- duty vehicle fleet by 2020 (Citi GPS, 2013). Table Natural Gas Market Penetration Schedule Year Market Share (%) While we acknowledge the role that hydrogen fuel cell vehicles may play in the future, electric and hydrogen fuel cell vehicles were not treated distinctly, and market growth for this sector was defined predominantly by electric vehicle characteristics. Initial vehicle projection numbers were specified based on the Argonne VISION 2012 model for baseline electric vehicle adoption, and each state s carbon intensity from electricity generation was specified exogenously with carbon intensity values corresponding to the Renewable Electricity case scenario in the VISION model. As electric and hydrogen vehicles have not experienced substantial market penetration, the average growth rate for this sector was not weighted based on the fuel pool within the objective function; extreme increases in vehicle growth rate were not discounted relative to the fuel market share. 6 different model runs were utilized for this analysis. Each of the four regions was modeled independently. Here we assumed that global biofuel supply far exceeds independent regional demand. The results from these model runs were aggregated to yield the aggregated model results presented in figure 4.2A. Each of the four states baseline fuel requirements were combined to create a harmonized regional model (figure 4.2B), which was similarly not constrained by biofuel supply. A final model was considered in which biofuel supply constraints were imposed on the harmonized region model (Figure 4.3). Biofuel supply curves were taken from Parker (2012), and biofuel supply was proportionally allocated to the region based on transportation GHG emissions from this aggregate region compared to United States as whole. The Parker supply estimates were expanded by 5 percent to account for the expectation that international biofuel supply may be used to meet the standard in the short- term, and that algae based biofuels may be developed to provide additional biofuel supply in the long- term (Wigmosta, Coleman, Skaggs, Huesemann, & Lane, 2011) LCFS Innovation Potential and Economic Impacts Baseline cost estimates and innovation rates for electric vehicles were taken from the Argonne VISION model. An experience curve was fit to this data by minimizing the sum of squares error, 7

8 which yielded a progress ratio for electric vehicles of 97 percent. Increased vehicle deployment beyond the base case was utilized to determine the new price for electric vehicles relative to the base case. Each region s deployment expansion was compared against the base case, and an overall percent change in innovation was attributed to each region. Aggregated results were analyzed similarly, and under the biofuel- limited case electric vehicle demand was scaled to reflect the likely impact from regional LCFS- implementation at a national level under the NAAQS compared to independent regional implementations. This provides a basis for assessing the value of the LCFS as a policy to foster technological development and innovation for electric vehicles at the regional scale, and provides a starting point for discussion of local policies that may further influence innovation and motivate strategic niche management strategies (Kwon, 2012). Innovation in the biofuel sector has not been modeled as it is uncertain how resource scarcity and competition with food crops may impact overall prices and create deviations from an expected experience curve. Supply curves from Parker (2012) were used to determine the cost for biofuels in the biofuel supply limited case. For independent regional implementations and the harmonized and aggregated models, Annual Energy Outlook 2013 biofuel price forecasts out to 2040 were used, and the average annual growth rate was applied to estimate costs for 2045 and Low oil and baseline oil costs from the Annual Energy Outlook were utilized to provide estimates on the cost of carbon abatement out through 2050 (U.S. Energy Information Administration, 2013). 4. Discussion and Results Independent regional implementations of LCFS policy The scenario analysis model was run for New Jersey, Oregon, Vermont, and Washington. After the model converged, values were altered slightly from the converged state and the model was run again until convergence was unaffected; this was done in an attempt to find the global minimum. Fuel trends for each of the four states are presented below in figure 4.1. The overall trend observed for each of the four states is similar, with only slight differences in fuel composition and the deployment schedule.

9 Figure Converged fuel deployment results required to meet the LCFS reduction schedule for A) New Jersey, B) Oregon, C) Vermont, and D) Washington Results indicate that in the unconstrained biofuel case, the LCFS schedule will be met by fully displacing gasoline with biofuels and electric vehicles by Natural gas and biodiesel use will fully displace diesel use toward the later periods of compliance. As electric vehicles come to market, use of biofuels will begin to wane in favor of electric and hydrogen vehicles. These results are in agreement with other analyses (Transitions to Alternative Vehicles and Fuels, 2013) Harmonized and Aggregated Results To assess the total impact from each independently modeled LCFS implementation, the model outputs from each region were combined to provide the aggregated model results. Model inputs for each region were also combined and the model was run again to provide the harmonized policy results. While each state in the United States may implement different schedules for LCFS policy with different reduction timeframes and targets, to simplify analysis this paper looked at applying a fairly consistent LCFS policy across each of the four states. As such, the difference between the harmonized and aggregated results is insignificant (Figure 4.3). 9

10 Figure Converged fuel deployment results required to meet the LCFS reduction schedule for A) the aggregate supply for isolated regional- LCFS policy and B) the aggregate supply for harmonized regional- LCFS policy A standard student s t- test was utilized to compare the fuel schedule for the aggregated model and the harmonized LCFS model with the expected fuel trends for each of the four regions independently. The harmonized- LCFS aggregation did not show statistically significant market share deviations from the independently- converged state fuel pools. These results are encouraging in that they indicate that the model likely converged around a global minimum for deployment of alternative fuels for each region and the regional aggregation. If a harmonized LCFS were to be implemented, the independent fuel makeup of each individual state may differ widely relative to the aggregate market. As local state policies and resource attributes are not considered in our modeling approach, we are unable to provide quantitative assessment of an optimal, state- dependent fuel supply based on deviations in state characteristics Harmonized LCFS policies with biofuel limitations Although the regions in isolation and at the aggregate level look similar, the technology deployment schedule differs substantially when biofuel supply considerations are factored in. At the independent regional level and at the 4- region aggregate level, biofuel supply limitations were not considered. Using the percent share of GHG emissions from these regions compared to the total GHG emissions from transportation (7.1 percent of total GHG transportation emissions) allowed for an equitable apportionment of biofuel to the combined region. This leads to an estimated 3.55 billion gallons of gasoline equivalent biofuels for aggregate consumption each year. Adding this restriction in to the model yields the results presented in figure 4.3. Figure Converged fuel deployment results required to meet the LCFS reduction schedule for equitable regional apportionment of biofuel resources Biofuel supply constraints substantially impact the rate of deployment of electric vehicles, and most of the biofuel feedstock is delegated to biodiesel production to offset diesel use during later compliance periods.

11 4.4 - Economic analysis and contributions toward innovation The Energy Information Administration (EIA) Annual Energy Outlook price estimates for biofuels were utilized for the independent regional analysis and for the aggregated and harmonized model results. Biofuel supply curves from Parker (2012) were used to assess biofuel costs for the biofuel limited case, as would occur if regional LCFS policy were implemented and adopted at the national level through the NAAQS. Electricity costs came from the EIA Annual Energy Outlook and are considered to be independent of the increase in electric vehicle deployment. Oil and natural gas costs have been taken from the EIA Annual Energy Outlook reference case through 2040 and are assumed to follow a constant annual growth rate for 2045 and The low oil cost and baseline oil cost cases from the Annual Energy Outlook have been used to provide bounds for the relative cost of carbon abatement. Total costs have been summed for each of the 5- year compliance periods and compared to the costs that would otherwise be associated with the business- as- usual use of gasoline and diesel fuels as projected by the MOVES model. The difference in GHG emissions has been calculated between the modeled cases and business- as- usual case to determine the amount of carbon abated. This has been used to provide an estimate on the overall cost of abatement due to LCFS policy implementation for each of the analyzed cases (Table 4.1). Table Average carbon abatement costs Low Oil Price ($/tonne- CO2e) AEO Baseline ($/tonne- CO2e) New Jersey $95 $(10) Oregon $111 $(13) Vermont $122 $(10) Washington $96 $(42) Harmonized $84 $(29) Limit to Biofuel $67 $(172) Due to increased penetration of electric vehicles and the relative savings in fuel costs from switching to electricity, instead of gasoline, during periods of escalating oil prices, LCFS implementation may result in negative carbon abatement costs. As evident from the biofuel limited case compared to the non- limited biofuel case, adoption of electric vehicles is ultimately beneficial for reducing carbon emissions and reducing associated costs for transportation in the long run. Results for earlier compliance periods had much higher costs of abatement, and returns on investment are only realized toward the later compliance periods (Table 4.2). These results indicate the importance of long- term investment in technology. 11

12 Table Time series for abatement costs for the constrained biofuel supply case Year Cost of Abatement ($/tonne- CO2e) 2015 $ $ $ $ $(153) 2040 $(237) 2045 $(294) 2050 $(338) Average $(166) The relative contribution that each region makes toward innovation (cost reductions) for electric vehicles was found by determining the percent deviation from the business- as- usual deployment case in the Argonne VISION model for electric vehicles. Table 4.3 shows the results from this analysis. Table Regional contribution to cost reductions due to LCFS implementation Region Innovation Increase New Jersey 2.1% Oregon 1.5% Vermont 0.4% Washington 2.0% Harmonized 4.2% NAAQS- Biofuel- Limited 13.1% The relative cost of electric vehicle adoption at the aggregate level, or with biofuel restrictions and harmonized regional implementation as could happen through the NAAQS is shown in Figure 4.4. As biofuel supply is constrained, the market share for electric vehicles will increase, contributing to greater innovation within the field. Electric(Vehicle(Cost(!$45,000!!!$40,000!!!$35,000!!!$30,000!!!$25,000!! No!LCFS!policy! 45state!regional!adop>on! 45state!regional!adop>on!and!biofuel!limit! Full!na>onal!adop>on!under!NAAQS!!$20,000!! 2010! 2015! 2020! 2025! 2030! 2035! 2040! 2045! 2050! Year( Figure Projected reductions in electric vehicle costs due to different LCFS policy implementation approaches: No LCFS implementation, LCFS implementation in a few select regions,

13 LCFS implementation in select regions with limited biofuel supply, and national implementation of LCFS policy through NAAQS The NAAQS present an option for implementing LCFS policy at a regional level that is national in scope. Given the variation associated with regional carbon abatement costs, as well as technology cost reductions and learning that may occur from economies of scale, it is important for LCFS policies across regions to provide consistent market signals and work toward reduction goals while taking advantage of independent regional resources. In the next section we further analyze the national implications of meeting the LCFS reduction schedule put forward in this paper. 5. Vehicle Deployment and Infrastructure Vehicle Deployment Regulated parties must coordinate with automotive manufacturers to ensure increased use of low- carbon fuels to satisfy the LCFS. As a result, the on- road vehicle fleet must slowly phase out conventional gasoline and diesel vehicles to incorporate greater numbers of alternative fuel vehicles (AFVs). The most prominent alternative fuel vehicle types in the resultant LCFS scenarios are Flex- Fuel Vehicles (FFV), Natural Gas Vehicles (NGV), and Electric Vehicles (EV). The modeled fuel profiles in Section 4 dictate the estimated vehicle mix across the United States over the 50- year timeframe. Using the average fuel economy projections through 2050 from the Argonne VISION model, we estimate the number of AFVs for each modeled scenario over time. Fuel economy projections were broken down into three vehicle classes: spark ignition vehicles (conventional and FFVs), heavy- duty vehicles (natural gas and diesel), and electric vehicles. The average vehicle miles traveled by each class over the 40- year time frame were also used to provide an estimate on energy consumption by vehicle class. Figure 5.1 below shows the harmonized and biofuel limited analysis for vehicle projections, by type, scaled to apply to the entire U.S. Figure 5.1. A. Number of vehicles, by type, in the U.S. assuming biofuel supply is not limited. B. Number of vehicles, by type, in the U.S. assuming biofuel supply is limited. Achieving carbon reductions through ethanol in the non- limited biofuels case requires substantial consumer adoption of FFVs. However, the EIA s adoption forecast estimates sales of FFVs to be under 1.3 million vehicles annually through 2035 with a total fleet of under 18 million vehicles (U.S. Energy Information Administration, 2013). Therefore, without significant market incentives or a vehicle technology mandate, vehicle sales will fall significantly short of the number needed to meet the non- limited biofuels case. Alternatively, fuel producers would need to pioneer new, economical methods for producing drop- in fuels that yield similar carbon intensity benefits to ethanol. In the biofuel- limited case, additional policy intervention may similarly be necessary to encourage the 13

14 adoption and use of hydrogen fuel cell and electric vehicles. This may require additional regional planning and economic incentives, for which analysis is beyond the scope of this paper Vehicle Refueling Infrastructure Deployment of AFVs requires an expansive refueling infrastructure including fuel supply capabilities and vehicle refueling stations. AFV deployment must be coupled with alternative refueling infrastructure development to promote the technology to reach market maturity. However, the exact ratio of vehicles to stations varies highly by vehicle type due to the nature of the refueling. According to Janssen, Lienin, Gassmann, and Wokaun (2006), a Vehicle to Refueling Station Index (VRI) of NGVs per refueling station is the threshold for successful market adoption. Conversely, EVs rely on an extremely diffuse refueling infrastructure in which private vehicle owners frequently conduct charging within their residence (Smart & Schey, 2012). Lastly, FFVs have the advantage that they may consume fuels with no ethanol content, such as, conventional gasoline, to fuels such as E85, 85% ethanol, and above. However, ethanol blends above E10 but lower than E85 may only be dispensed by blender pumps, of which only approximately 300 exist today out of the roughly 2,000,000 pumps in service today in the United States (Renewable Fuels Association, 2011). While the LCFS may go a long way for incentivizing the use of alternative fuels, there still are considerable infrastructure concerns. Given the need to promote infrastructure development alongside alternative fuel expansion, there may be substantial costs in bringing these fuels to market. Given this concern, additional policies to incentivize infrastructure may aid in meeting the LCFS reduction schedule presented above. While the total vehicle penetration rate presented in figure 5.1 may be indicative of the level of infrastructure development that must also take place, such strategies may better be analyzed at the regional level, which stretches beyond the analysis presented in this paper. 6. Conclusions The National Ambient Air Quality Standard, if used to regulate greenhouse gas emissions, provides an interesting approach for addressing climate change from the transportation sector at the regional level. Implementation of a Low Carbon Fuel Standard as part of a State Implementation Plan, due to NAAQS regulation, may promote carbon emission reductions from the transportation sector beyond what is possible through economy- wide cap and trade policy or through fuel economy standards. Our modeling results indicate that harmonized, regional policies may allow for reduced abatement costs relative to independently implemented regional policies. If wide- scale deployment and adoption of electric vehicles occurs, substantial cost savings and social benefits relative to the fossil fuel base case may also be realized. Modeling indicates that substantial change will be necessary to transition the automotive fleet away from conventional vehicles to flex- fuel and electric vehicles to meet greenhouse gas emission reduction goals. Additionally, the existing implementation of the Environmental Protection Agency s Motor Vehicle Emissions Simulator model does not account for life- cycle GHG emissions. To allow for fuel policy to factor into State Implementation Plans, modifications to the model will be necessary to account for life- cycle greenhouse gas emissions associated with different fuel types. 7. References Burtraw, D., Fraas, A., & Richardson, N. (2011). Policy Monitor- - Greenhouse Gas Regulation under the Clean Air Act: A Guide for Economists. Review of Environmental Economics and Policy, 5(2), doi: /reep/rer009 California Air Resources Board. (2009). Detailed California- Modified GREET Pathway for Cellulosic Ethanol from Farmed Trees by Fermentation

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