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Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard Program
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PDF Version (50 pp, 978K, About PDF) [Federal Register: May 26, 2009 (Volume 74, Number 99)] [Proposed Rules] [Page 25053-25102] From the Federal Register Online via GPO Access [wais.access.gpo.gov] [DOCID:fr26my09-24] Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard Program [[Continued from page 25052]] [[Page 25053]] of biodiesel made from waste greases/oils met the 50% GHG threshold by a wide margin, and since it is common industry practice for biodiesel facilities to use these two feedstock sources, we believe it may be appropriate to allow a biodiesel production facility to average the GHG benefit generated through the use of waste grease with the lower GHG performance of biodiesel produced from soybean oil at the same facility. We recognize that an approach in which we allow a biodiesel production facility to average the GHG benefit of waste grease with that from soybean oil raises questions about whether similar averaging could be allowed for other combinations of feedstocks, other types of fuel, or across multiple facilities within the same company. While we believe that the circumstances surrounding biodiesel production are somewhat unique--two different feedstocks subjected to essentially the same production process in a single facility--we nevertheless request comment on the appropriateness of such an averaging approach for biodiesel. Based on our lifecycle analyses, biodiesel produced from waste grease has a GHG performance of 80% reduction from the conventional diesel baseline, while biodiesel produced from soybean oil has a GHG performance of 22% reduction. In order to meet the GHG threshold of 50% for biomass-based diesel, a biodiesel production facility would need to use a minimum of 48% waste grease and a maximum of 52% soybean oil. Thus, a pathway that would allow a biodiesel production facility to designate all of its biodiesel as biomass-based diesel would include a requirement that the producer demonstrate that every batch has been produced from no less than 48% waste grease and no more than 52% soybean oil. Although this approach would allow the total volume of biomass- based diesel to be larger than if waste greases/oils alone qualified, it is still possible than the 1.0 billion gallon requirement would not be met due to limits on the availability of waste greases and oils. For instance, we estimate that the total volume of waste greases and oils may be no larger than 0.3-0.4 billion gallons. As a result, we request comment on whether it would also be appropriate to lower the GHG threshold for biomass-based diesel. If this GHG threshold were lowered to 40%, a biodiesel production facility would only need to use a minimum of 31% waste greases/oils instead of 48%. We recognize that it may be difficult for a biodiesel production facility to process a consistent mixture of waste grease and soybean oil every day. Therefore, we request comment on alternative approaches. For instance, if a biodiesel production facility processed only waste grease for the first 175 days (48% x 365 days) of a calendar year, we could allow it to designate any biodiesel produced from soybean oil for the remainder of the year as biomass-based diesel. However, this may be difficult for some producers who must contend with cold temperature storage and blending issues in the early part of a calendar year by processing only soybean oil. Alternatively, we could allow a company to average the production at all of its facilities, where one facility processed only waste grease and another processed only soybean oil. Finally, we request comment on an alternative approach in which an obligated party, rather than the biodiesel production facility, would demonstrate that a minimum number of waste grease-based biodiesel RINs is used to meet the biomass-based diesel standard in comparison to the number of soybean oil-based biodiesel RINs. In essence, the averaging would be carried out by the obligated party instead of the biodiesel producer. In this approach, biodiesel RINs would not be placed into biomass-based diesel category shown in Table VI.E.1-1, but instead would be placed into two separate categories as waste grease RINs or soybean oil RINs. This designation would require that the list of applicable D codes for use in the RIN be expanded from four to six as shown in Table VI.E.3.c-1. Table VI.E.3.c-1--Alternative Approach to D Codes for Averaging Waste Grease and Soybean Oil Biodiesel RINs in Compliance ------------------------------------------------------------------------ Alternative approach D value Proposal meaning meaning ------------------------------------------------------------------------ 1................ Cellulosic biofuel........ Cellulosic biofuel 2................ Biomass-based diesel...... Biomass-based diesel 3................ Advanced biofuel.......... Biodiesel made from soybean oil 4................ Renewable fuel............ Biodiesel made from waste grease 5................ (Not applicable).......... Advanced biofuel 6................ (Not applicable).......... Renewable fuel ------------------------------------------------------------------------ Since other types of renewable fuel may still qualify as biomass- based diesel, we would retain a separate D code for this category under this approach. This could allow biodiesel producers who choose the process a minimum of 48% waste greases/oils each day to continue to assign a D code of 2 to their biodiesel. An obligated party could use any combination of RINs with a D code of 2, 3, or 4 in order to comply with the biomass-based diesel standard. However, he would also be subject to an additional requirement that the ratio of D=3 RINs to D=4 RINs must be less than 1.08. This criterion would ensure that a minimum of 47 RINs representing biodiesel from waste grease would be used for compliance purposes for every 53 RINs representing biodiesel from soybean oil that are also used for compliance. We request comment on these alternative approaches to the treatment of biodiesel. d. Renewable Diesel Through Hydrotreating We did not conduct a lifecycle analysis for the production of non- ester renewable diesel through a hydrotreating process. However, we believe that our analysis of biodiesel provides sufficient information to allow us to designate the renewable fuel category for various pathways leading to the production of renewable diesel. Renewable diesel is generally made from the same feedstocks as biodiesel, namely soybean oil, waste greases/oils, tallow, and chicken fat. Therefore, the GHG impacts associated with producing/collecting the feedstock and transporting it to the production facility would be the same regardless of whether the final product is biodiesel or renewable diesel. The fossil energy requirements of the production process contribute a relatively small amount to the overall GHG performance for biodiesel. For example, the 50% GHG threshold would still be met for biodiesel produced from waste grease even if the fossil energy requirements doubled. As a result, compared to the transesterification process used to produce biodiesel, any small variations in fossil energy requirements for renewable diesel production in a hydrotreater would be unlikely to change compliance with the broad categories created by the GHG thresholds for biomass-based diesel and generic renewable fuel. Therefore, we believe that it would be appropriate to assign applicable renewable fuel categories to renewable diesel pathways in parallel with the assignments we are proposing for biodiesel, including the potential for averaging of soyoil and waste grease derived volumes. Renewable diesel produced from waste grease, tallow, or chicken fat in a hydrotreater that does not coprocess petroleum feedstocks would be [[Page 25054]] categorized as biomass-based diesel. Renewable diesel produced from waste grease, tallow, or chicken fat in a hydrotreater that does coprocess petroleum feedstocks would be categorized as advanced biofuel. Finally, renewable diesel produced from soybean oil in a hydrotreater would be categorized as generic renewable fuel. 4. Summary Based on the discussion above, we have identified 15 pathways that we propose could be used to produce fuel that would meet the volume requirements in EISA assuming a 100 year analysis time frame and discounting GHG emissions over time by 2%. As noted above, these pathways would be adjusted should we adopt other time frames or discount rates (including a zero discount rate) for the final rule. Each pathway would be assigned a D code for use in generating RINs that corresponds to one of the four renewable fuel categories. Our proposed list of allowable pathways is shown in Table VI.E.4-1. Table VI.E.4-1--Applicable Categories for Each Fuel Pathway \a\ ---------------------------------------------------------------------------------------------------------------- Production process Fuel type Feedstock requirements Category ---------------------------------------------------------------------------------------------------------------- Ethanol.............................. Starch from corn, --Process heat derived Renewable fuel. wheat, barley, oats, from biomass. rice, or sorghum. Ethanol.............................. Starch from corn, --Dry mill plant....... Renewable fuel. wheat, barley, oats, rice, or sorghum. --Process heat derived from natural gas. --Combined heat and power (CHP). --Fractionation of feedstocks. --Some or all distillers grains are dried. Ethanol.............................. Starch from corn, --Dry mill plant....... Renewable fuel. wheat, barley, oats, rice, or sorghum. --Process heat derived from natural gas. --All distillers grains are wet. Ethanol.............................. Starch from corn, --Dry mill plant....... Renewable fuel. wheat, barley, oats, rice, or sorghum. --Process heat derived from coal. --Combined heat and power (CHP). --Fractionation of feedstocks. --Membrane separation of ethanol. --Raw starch hydrolysis --Some or all distillers grains are dried. Ethanol.............................. Starch from corn, --Dry mill plant....... Renewable fuel. wheat, barley, oats, rice, or sorghum. --Process heat derived from coal. --Combined heat and power (CHP). --Fractionation of feedstocks. --Membrane separation of ethanol. --All distillers grains are wet. Ethanol.............................. Cellulose and --Enzymatic hydrolysis Cellulosic biofuel. hemicellulose from of cellulose. corn stover, switchgrass, miscanthus, wheat straw, rice straw, sugarcane bagasse, forest waste, yard waste, or planted trees. --Fermentation of sugars. --Process heat derived from lignin. Ethanol.............................. Cellulose and --Thermochemical Cellulosic biofuel. hemicellulose from gasification of corn stover, biomass. switchgrass, miscanthus, wheat straw, rice straw, sugarcane bagasse, forest waste, yard waste, or planted trees. --Fischer-Tropsch process. Ethanol.............................. Sugarcane sugar........ --Process heat derived Advanced biofuel. from sugarcane bagasse. Biodiesel (mono alkyl ester)......... Waste grease, waste --Transesterification.. Biomass-based diesel. oils, tallow, chicken fat, or non-food grade corn oil. Biodiesel (mono alkyl ester)......... Soybean oil and other --Transesterification.. Renewable fuel. virgin plant oils. [[Page 25055]] Cellulosic diesel.................... Cellulose and --Thermochemical Cellulosic biofuel or hemicellulose from gasification of biomass-based diesel. corn stover, biomass. switchgrass, miscanthus, wheat straw, rice straw, sugarcane bagasse, forest waste, yard waste, or planted trees. --Fischer-Tropsch process. --Catalytic depolymerization. Non-ester renewable diesel........... Waste grease, waste --Hydrotreating........ oils, tallow, chicken fat, or corn oil. --Dedicated facility Biomass-based diesel. that processes only renewable biomass. Non-ester renewable diesel........... Waste grease, waste --Hydrotreating........ Advanced biofuel. oils, tallow, chicken fat, or non-food grade corn oil. --Coprocessing facility that also processes petroleum feedstocks. Non-ester renewable diesel........... Soybean oil and other --Hydrotreating........ Renewable fuel. virgin plant oils. Cellulosic gasoline.................. Cellulose and --Thermochemical Cellulosic biofuel. hemicellulose from gasification of corn stover, biomass. switchgrass, miscanthus, wheat straw, rice straw, sugarcane bagasse, forest waste, yard waste, or planted trees. --Fischer-Tropsch process. --Catalytic depolymerization. ---------------------------------------------------------------------------------------------------------------- \a\ Under our assumed 100-year timeframe and 2% discount rate. As stated earlier, there may be other potential pathways that could lead to qualifying renewable fuel. While we do not have sufficient information at this time to evaluate the likely lifecycle GHG impact and thus assign those pathways to one of the four renewable fuel categories, we do plan on doing these evaluations for the final rule. Pathways that we intend to subject to lifecycle analysis include butanol from starches or oils and renewable diesel from biomass using pyrolysis or catalytic reforming. We request comment on the inputs necessary to apply lifecycle analysis to these pathways. We also request comment on other pathways that should be analyzed and the data that would be necessary for those analyses. For pathways that are not included in the lookup table in the final rule, we are also proposing a regulatory mechanism whereby a producer could temporarily assign their renewable fuel to one of the four renewable fuel categories under certain conditions. For further discussion of this issue, see Section III.D.5. F. Total GHG Emission Reductions Our analysis of the overall GHG emission impacts of this proposed rulemaking was performed in parallel with the lifecycle analysis performed to develop the individual fuel thresholds described in previous sections. The same system boundaries apply such that this analysis includes the effects of three main areas: (a) emissions related to the production of biofuels, including the growing of feedstock (corn, soybeans, etc.) with associated domestic and international land use change impacts, transport of feedstock to fuel production plants, fuel production, and distribution of finished fuel; (b) emissions related to the extraction, production and distribution of petroleum gasoline and diesel fuel that is replaced by use of biofuels; and (c) difference in tailpipe combustion of the renewable and petroleum based fuels. As discussed in the previous sections we will be updating our lifecycle approach for the final rule and there are some areas that we were not able to quantify at this time, such as secondary impacts in the energy sector. We are working to include this for our final rule analysis. Consistent with the fuel volume feasibility analysis and criteria pollutant emissions, our analysis of the GHG impacts of increased renewable fuel use was conducted by comparing the impacts of the 2022 36 Bgal of renewable fuel volumes required by EISA to a projected 2022 reference case of approximately 14 Bgal of renewable fuel volumes. Similar to what was done to calculate lifecycle thresholds for individual fuels we considered the change in 2022 of these two volume scenarios of renewable fuels to determine overall GHG impacts of the rule. The reference case for the GHG emission comparisons was taken from the AEO 2007 projected renewable fuel production levels for 2022 prior to enactment of EISA. This scenario provided a point of comparison for assessing the impacts of the RFS2 standard volumes on GHG emissions. We ran these multi-fuel scenarios through our FASOM and FAPRI models and applied the Winrock land use change assumptions to determine to overall GHG impacts. We were only able to analyze 2022 reference and control cases. However, in reality the impacts of corn ethanol and soybean biodiesel will be experienced beginning in 2009, with the impacts of cellulosic ethanol and sugarcane ethanol growing in later years as their volumes increase. The main difference between this overall impacts analysis and the analysis conducted to develop the threshold values for the individual fuels is that we analyzed the total change in renewable fuels in one scenario as opposed to looking at individual fuel impacts. When analyzing the impact of the total 36 billion gallons of renewable fuel, we also took into account the agricultural sector interactions necessary to produce the full complement of feedstock. We also [[Page 25056]] considered a mix of plant types and configurations for the 2022 renewable fuel production representing the mix of plants we project to be in operation in 2022. This is based on the same analysis used in the plant location and fuel feasibility analysis described in Section V.B. For this overall impacts analysis we used a different petroleum baseline fuel that is offset from renewable fuel use. The lifecycle threshold values are required by EISA to be based on a 2005 petroleum fuel baseline. For this inventory analysis of the overall impacts of the rule we considered the crude oil and finished product that would be replaced in 2022. Displaced petroleum product analysis was consistent with work performed for the energy security analysis described in Section IX.B. For this analysis we consider that 25% of displaced gasoline will be imported gasoline. For the domestic production we assumed replacement of the 2022 crude mix which is projected to include 7.6% tar sands and 3.8% Venezuelan heavy crude which is higher then the projected mix in 2005 which includes 5% tar sands and 1% Venezuelan heavy crude. Given these many differences, simply adding up the individual lifecycle results determined in Section VI.C. multiplied by their respective volumes would yield a different assessment of the overall rule impacts. The two analyses are separate in that the overall rule impacts capture interactions between the different fuels that can not be broken out into per fuels impacts, while the threshold values represent impacts of specific fuels but do not account for all the interactions. For example, when we consider the combined impact of the different fuel volumes when analyzed separately, the overall land use change is 9.0 million acres. However, when we analyze the volume changes all together, the overall land use change is approximately 10% higher. The primary reason for the difference in acre change between the sum of the individual fuel scenarios and the combined fuel scenarios is that when looking at individual fuels there is some interaction between different crops (e.g., corn replacing soybeans), but with combined volume scenario when all mandates need to be met there is less opportunity for crop replacement (e.g., both corn and soybean acres needed) and therefore more land is required. Important findings of our analysis include: • As with the threshold lifecycle calculations, assumptions about timing to consider impacts over and discount rates will have a significant impact on results. • We estimate the largest overall agricultural sector impact is an increase in land use change impacts, reflecting the shift of crop production internationally to meet the biofuel demand in the U.S. Increased crop production internationally resulted in land use change emissions associated with converting land into crop production. • Our analysis indicates that overall domestic agriculture emissions would increase. There is a relatively small increase in total domestic crop acres however, there are additional inputs required due to the removal of crop residues. The assumption is that removal will require more inputs to make up for lost residue nutrients. These additional inputs result in GHG emissions from production and from N2O releases from application. This effect is somewhat offset by reductions due to lower livestock production. These results are dependent on our agricultural sector input and emission assumptions that are being updated for the final rule (e.g., N2O emission factor work). • In particular due to this international impact, the potential overall GHG emission reductions of biofuels produced from food crops such as corn ethanol and soy biodiesel are significantly impacted. Large near term emission increases due to land use change require a number of years before the emission reductions due to corn ethanol and soy biodiesel use will offset the near term emission increase as discussed in the threshold calculation section. • Cellulosic biofuels contribute by far the most to the total emission reductions due to both their superior per gallon emission reductions and the large volume of these fuels anticipated to be used by 2022. The timing of the impact of land use change and ongoing renewable fuels benefits were discussed in the previous lifecycle fuel threshold section. The issue is slightly different for this analysis since we are considering absolute tons of emissions and not determining a threshold comparison to petroleum fuels. However the results can be presented in a similar manner to our individual fuels analysis in that we can determine net benefits over time with different discount rates and over a different time frame for consideration. As discussed in previous sections on lifecycle GHG thresholds there is an initial one time release from land conversion and smaller ongoing releases but there are also ongoing benefits of using renewable fuels over time replacing petroleum fuel use. Based on the volume scenario considered, the one time land use change impacts result in 448 million metric tons of CO2-eq. emissions increase. There are, however, based on the biofuel use replacing petroleum fuels, GHG reductions in each year. When modeling the program as if all fuel volume changes occur in 2022, and considering 100 years of emission impacts that are discounted by 2% per year, we get an estimated total discounted NPV reduction in GHG emissions of 6.8 billion tons over 100 years. Totaling the emissions impacts over 30 years but assuming a 0% discount rate over this 30 year period would result in an estimated total NPV reduction in GHG emissions of 4.5 billion tons over 30 years. This total NPV reduction can be converted into annual average GHG reductions, which can be used for the calculations of the monetized GHG benefits as shown in Section IX.C.4. This annualized value is based on converting the lump sum present values described above into their annualized equivalents. For this analysis we convert the NPV results for the 100 year 2% discount rate into an annualized average such that the NPV of the annualized average emissions will equal the NPV of the actual emission stream over 100 years with a 2% discount rate. This results in an annualized average emission reduction of approximately160 million metric tons of CO2-eq. emissions. A comparable value assuming 30 years of GHG emissions changes but not applying a discount rate to those emissions results in an estimated annualized average emission reduction of approximately 150 million metrics tons of CO2-eq. emissions. G. Effects of GHG Emission Reductions and Changes in Global Temperature and Sea Level 1. Introduction The reductions in CO2 and other GHGs associated with the proposal will affect climate change projections. Because GHGs mix well in the atmosphere and have long atmospheric lifetimes, changes in GHG emissions will affect future climate for decades to centuries. One common indicator of climate change is global mean surface temperature and sea level rise. This section estimates the response in global mean surface temperature projections to the estimated net global GHG emissions reductions associated with the proposed rulemaking (See Section VI.F for the estimated net reductions in global emissions over time by GHG). [[Page 25057]] 2. Estimated Projected Reductions in Global Mean Surface Temperatures EPA estimated changes in projected global mean surface temperatures to 2100 using the MiniCAM (Mini Climate Assessment Model) integrated assessment model \320\ coupled with the MAGICC (Model for the Assessment of Greenhouse-gas Induced Climate Change) simple climate model.\321\ MiniCAM was used to create the globally and temporally consistent set of climate relevant variables required for running MAGICC. MAGICC was then used to estimate the change in the global mean surface temperature over time. Given the magnitude of the estimated emissions reductions associated with the proposed rule, a simple climate model such as MAGICC is reasonable for estimating the climate response. --------------------------------------------------------------------------- \320\ MiniCAM is a long-term, global integrated assessment model of energy, economy, agriculture and land use, that considers the sources of emissions of a suite of greenhouse gases (GHG's), emitted in 14 globally disaggregated global regions (i.e., U.S., Western Europe, China), the fate of emissions to the atmosphere, and the consequences of changing concentrations of greenhouse related gases for climate change. MiniCAM begins with a representation of demographic and economic developments in each region and combines these with assumptions about technology development to describe an internally consistent representation of energy, agriculture, land- use, and economic developments that in turn shape global emissions. Brenkert A, S. Smith, S. Kim, and H. Pitcher, 2003: Model Documentation for the MiniCAM. PNNL-14337, Pacific Northwest National Laboratory, Richland, Washington. For a recent report and detailed description and discussion of MiniCAM, see Clarke, L., J. Edmonds, H. Jacoby, H. Pitcher, J. Reilly, R. Richels, 2007. Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations. Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological & Environmental Research, Washington, DC., USA, 154 pp. \321\ MAGICC consists of a suite of coupled gas-cycle, climate and ice-melt models integrated into a single framework. The framework allows the user to determine changes in GHG concentrations, global-mean surface air temperature and sea-level resulting from anthropogenic emissions of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), reactive gases (e.g., CO, NOX, VOCs), the halocarbons (e.g. HCFCs, HFCs, PFCs) and sulfur dioxide (SO2). MAGICC emulates the global-mean temperature responses of more sophisticated coupled Atmosphere/Ocean General Circulation Models (AOGCMs) with high accuracy. Wigley, T.M.L. and Raper, S.C.B. 1992. Implications for Climate and Sea-Level of Revised IPCC Emissions Scenarios Nature 357, 293-300. Raper, S.C.B., Wigley T.M.L. and Warrick R.A. 1996. in Sea-Level Rise and Coastal Subsidence: Causes, Consequences and Strategies J.D. Milliman, B.U. Haq, Eds., Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 11-45. Wigley, T.M.L. and Raper, S.C.B. 2002. Reasons for larger warming projections in the IPCC Third Assessment Report J. Climate 15, 2945-2952. --------------------------------------------------------------------------- EPA applied the estimated annual GHG emissions changes for the proposal to the MiniCAM U.S. Climate Change Science Program (CCSP) Synthesis and Assessment Product baseline emissions.\322\ Specifically, the CO2, N2O, and CH4 annual emission changes from 2022-2121 from Section VI.F were applied as net reductions to the MiniCAM CCSP global baseline net emissions for each GHG. Post- 2121, we assumed no change in emissions from the baseline. This assumption is more conservative than allowing the emissions reductions to continue. --------------------------------------------------------------------------- \322\ Clarke et al., 2007. --------------------------------------------------------------------------- Table VI.G.2 provides our estimated reductions in projected global mean surface temperatures and sea level associated with the proposed increase in renewable fuels in 2022. To capture some of the uncertainty in the climate system, we estimated the changes in projected temperatures and sea level across the most current Intergovernmental Panel on Climate Change (IPCC) range of climate sensitivities, 1.5 [deg]C to 6.0 [deg]C.\323\ To illustrate the time profile of the estimated reductions in projected global mean surface temperatures and sea level, we have also provided Figures VI.G.2-1 and VI.G.2-2. --------------------------------------------------------------------------- \323\ In IPCC reports, equilibrium climate sensitivity refers to the equilibrium change in the annual mean global surface temperature following a doubling of the atmospheric equivalent carbon dioxide concentration. The IPCC states that climate sensitivity is ``likely'' to be in the range of 2 [deg]C to 4.5 [deg]C and described 3 [deg]C as a ``best estimate.'' The IPCC goes on to note that climate sensitivity is ``very unlikely'' to be less than 1.5 [deg]C and ``values substantially higher than 4.5 [deg]C cannot be excluded.'' IPCC WGI, 2007, Climate Change 2007--The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the IPCC, http://www.ipcc.ch/.Table VI.G.2-1--Estimated Reductions in Projected Global Mean Surface Temperature and Global Mean Sea Level From Baseline in 2030, 2050, 2100, and 2200 for the Proposed Standard in 2022 ---------------------------------------------------------------------------------------------------------------- Climate sensitivity ---------------------------------------------------------------- 1.5 2 3 4.5 6 ---------------------------------------------------------------------------------------------------------------- Change in global mean surface temperatures (degrees Celsius) ---------------------------------------------------------------------------------------------------------------- 2030........................................... 0.000 0.000 -0.001 -0.001 -0.001 2050........................................... -0.001 -0.002 -0.002 -0.002 -0.003 2100........................................... -0.003 -0.004 -0.005 -0.006 -0.007 2200........................................... -0.003 -0.004 -0.006 -0.008 -0.009 ---------------------------------------------------------------------------------------------------------------- Change in global mean sea level rise (centimeters) ---------------------------------------------------------------------------------------------------------------- 2030........................................... -0.002 -0.002 -0.003 -0.003 -0.003 2050........................................... -0.012 -0.014 -0.017 -0.020 -0.022 2100........................................... -0.045 -0.052 -0.063 -0.074 -0.082 2200........................................... -0.077 -0.091 -0.114 -0.143 -0.172 ---------------------------------------------------------------------------------------------------------------- The results in Table VI.G.2-1 and Figures VI.G.2-1 and VI.G.2-2 show small, but detectable, reductions in the global mean surface temperature and sea level rise projections across all climate sensitivities. Overall, the reductions are small relative to the IPCC's ``best estimate'' temperature increases by 2100 of 1.8 [deg]C to 4.0 [deg]C.\324\ Although IPCC does not issue ``best estimate'' sea level rise projections, the model-based range across SRES scenarios is 18 to 59 cm by 2099.\325\ Both figures illustrate that the overall emissions reductions can decrease projected annual temperature and sea level for all climate sensitivities. This means that the distribution of potential temperatures in any particular year is shifting down. However, the shift is not uniform. The magnitude of the decrease is larger for higher climate [[Page 25058]] sensitivities. Thus, the probability of a higher temperature or sea level in any year is lowered more than the probability of a lower temperature or sea level. For instance, in 2100, the reduction in projected temperature for climate sensitivities of 3 and 6 is approximately 65% and 140% greater than the reduction for a climate sensitivity of 1.5. This difference grows over time, to approximately 80% and 185% by 2200. The same pattern appears in the reductions in the sea level rise projections.\326\ Also noteworthy in Figures VI.G.2-1 and VI.G.2-2 is that the size of the decreases grows over time due to the cumulative effect of a lower stock of GHGs in the atmosphere (i.e., concentrations).\327\ --------------------------------------------------------------------------- \324\ IPCC WGI, 2007. The baseline increases by 2100 from our MiniCAM-MAGICC runs are 2 [deg]C to 5 [deg]C for global mean surface temperature and 35 to 74 centimeters for global mean sea level. \325\ ``Because understanding of some important effects driving sea level rise is too limited, this report does not assess the likelihood, nor provide a best estimate or an upper bound for sea level rise.'' IPCC Synthesis Report, p. 45 \326\ In 2100, the reduction in projected sea level rise for climate sensitivities of 3 and 6 is approximately 40% and 80% greater than the reduction for a climate sensitivity of 1.5. This difference grows over time, to approximately 50% and 120% by 2200. \327\ For global average temperature after 2100, the growth in the size of the decrease noticeable slows. This is because the emissions changes associated with the policy were only estimated for 100 years. Note that even with emissions reductions stopping after 100 years, there continues to be a decrease in projected temperatures due to reduced inertia in the climate system from the earlier emissions reductions. However, unlike temperature, after 2100, the size of the decrease in sea level rise increases as the projected reduction in warming has a continued effect on ice melt and ocean thermal expansion. --------------------------------------------------------------------------- The bottom line is that the risk of climate change is being lowered, as the probabilities of any level of temperature increase and sea level rise are reduced and the probabilities of the largest temperature increases and sea level rise are reduced even more. For the Final Rulemaking, we hope to more explicitly estimate the shapes of the distributions and the estimated shifts in the shapes in response to the Rulemakings. BILLING CODE 6560-50-P [GRAPHIC] [TIFF OMITTED] TP26MY09.009 [[Page 25059]] [GRAPHIC] [TIFF OMITTED] TP26MY09.010 BILLING CODE 6560-50-C VII. How Would the Proposal Impact Criteria and Toxic Pollutant Emissions and Their Associated Effects? A. Overview of Impacts Today's proposal would influence the emissions of ``criteria'' pollutants (those pollutants for which a National Ambient Air Quality Standard has been established), criteria pollutant precursors,\328\ and air toxics, which may affect overall air quality and health. Emissions would be affected by the processes required to produce and distribute large volumes of biofuels proposed in today's action and the direct effects of these fuels on vehicle and equipment emissions. As detailed in Chapter 3 of the Draft Regulatory Impact Analysis (DRIA), we have estimated emissions impacts of production and distribution-related emissions using the life cycle analysis methodology described in Section VI with emission factors for criteria and toxic emissions for each stage of the life cycle, including agriculture, feedstock transportation, and the production and distribution of biofuel; included in this analysis are the impacts of reduced gasoline and diesel refining as these fuels are displaced by biofuels. Emission impacts of tailpipe and evaporative emissions for on and off road sources have been estimated by incorporating ``per vehicle'' fuel effects from recent research into mobile source emission inventory estimation methods. --------------------------------------------------------------------------- \328\ NOX and VOC are precursors to the criteria pollutant ozone; we group them with criteria pollutants in this chapter for ease of discussion. --------------------------------------------------------------------------- For today's proposal we are presenting two sets of emission impacts meant to present a range of the possible effects of ethanol blends on light-duty vehicle emissions. This approach is carried forward from analysis supporting the first RFS rule, which presented ``primary'' and ``sensitivity'' fuel effects cases differentiated by E10 effects on cars and trucks. For this analysis we also analyze two fuel effects scenarios, now termed ``less sensitive'' and ``more sensitive,'' referring to the sensitivity of car and truck exhaust emissions to both E10 and E85 blends. As detailed in Section VII.C, the ``less sensitive'' case does not apply any E10 effects to NOx or HC emissions for later model year vehicles, or E85 effects for any pollutant, while the ``more sensitive'' case assumes that later model year vehicles have lower fuel sensitivity than earlier model vehicles. EPA and other parties are in the midst of gathering additional data to help clarify emissions impacts of ethanol on light-duty vehicles, and should be able to reflect the new data for the final rule. Analysis of criteria and toxic emission impacts was performed for calendar year 2022, since this year reflects the full implementation of today's proposal. Our 2022 projections account for projected growth in vehicle travel and the effects of applicable emission and fuel economy standards, including Tier 2 and Mobile Source Air Toxics (MSAT) rules for cars and light trucks and recently finalized controls on spark- ignited off-road engines. The impacts were analyzed relative to three different reference case ethanol volumes, ranging from 3.64 to 13.2 billion gallons per year, in order to understand the impacts of today's proposal in different contexts. To assess the total impact of the RFS program, emissions were analyzed relative to the RFS1 rule base case of 3.64 billion gallons in 2004. To assess the impact of today's proposal relative to the current mandated volumes, we analyzed impacts relative to RFS1 mandate of 7.5 billion gallons of renewable fuel use by 2012, which was estimated to include 6.7 billion gallons of ethanol.\329\ In order to assess the impact of today's proposal relative to the level of ethanol projected to already be in place by 2022, the AEO2007 projection of 13.2 billion gallons of [[Page 25060]] ethanol in 2022 was analyzed. For this analysis our modeling was based on the differences between the AEO2007 reference case and the control case; to generate impacts for the RFS1 base and mandated volumes we simply scaled the modeled AEO2007-based impacts up according to the larger increases in renewable fuel volumes relative to the other reference cases. For the final rule we plan to directly model the RFS1 mandate reference case as well as the AEO2007 case. --------------------------------------------------------------------------- \329\ For this analysis these RFS1 base and mandated ethanol levels were assumed constant to 2022. --------------------------------------------------------------------------- For the proposal we have only estimated the change in national emission totals that would result from today's proposal. These totals may not be a good indication of local or regional air quality and health impacts. These results are aggregated across highly localized sources, such as emissions from ethanol plants and evaporative emissions from cars, and reflect offsets such as decreased emissions from gasoline refineries. The location and composition of emissions from these disparate sources may strongly influence the air quality and health impacts of today's proposed action, and full-scale photochemical air quality modeling is necessary to accurately assess this. These localized impacts will be assessed in the final rule as discussed in Section VII.D. Our projected emission impacts for the ``less sensitive'' and ``more sensitive'' cases are shown in Table VII.A-1 and VII.A-2 for 2022. Shown relative to each reference case are the expected emission changes for the U.S. in that year, and the percent contribution of this impact relative to the total U.S. inventory. Overall we project the proposed program will result in significant increases in ethanol and acetaldehyde emissions--increasing the total U.S. inventories of these pollutants by 30-40% in 2022 relative to the RFS1 mandate case. We project more modest increases in NOx, HC, PM, SO2, formaldehyde, and acrolein relative to the RFS1 mandate case. We project a decrease in ammonia (NH3) emissions due to reductions in livestock agricultural activity, CO (due to impacts of ethanol on exhaust emissions from vehicles and nonroad equipment), and benzene (due to displacement of gasoline with ethanol in the fuel pool). As shown, the direction of changes for 1,3-butadiene and naphthalene depends on whether it is the ``less sensitive'' or ``more sensitive'' case. Table VII.A-1--RFS2 ``Less Sensitive'' Case Emission Impacts in 2022 Relative to Each Reference Case -------------------------------------------------------------------------------------------------------------------------------------------------------- RFS1 base RFS1 mandate AEO2007 ----------------------------------------------------------------------------------------------- Pollutant Percent of Percent of Percent of Annual short total U.S. Annual short total U.S. Annual short total U.S. tons inventory tons inventory tons inventory -------------------------------------------------------------------------------------------------------------------------------------------------------- NOx..................................................... 312,400 2.8 274,982 2.5 195,735 1.7 HC...................................................... 112,401 1.0 72,362 0.6 -8,193 -0.07 PM10.................................................... 50,305 1.4 37,147 1.0 9,276 0.3 PM2.5................................................... 14,321 0.4 11,452 0.3 5,376 0.16 CO...................................................... -2,344,646 -4.4 -1,669,872 -3.1 -240,943 -0.4 Benzene................................................. -2,791 -1.7 -2,507 -1.5 -1,894 -1.1 Ethanol................................................. 210,680 36.5 169,929 29.4 83,761 14.5 1,3-Butadiene........................................... 344 2.9 255 2.1 65 0.5 Acetaldehyde............................................ 12,516 33.7 10,369 27.9 5,822 15.7 Formaldehyde............................................ 1,647 2.3 1,348 1.9 714 1.0 Naphthalene............................................. 5 0.03 3 0.02 -1 -0.01 Acrolein................................................ 290 5.0 252 4.4 174 3.0 SO2..................................................... 28,770 0.3 4,461 0.05 -47,030 -0.5 NH3..................................................... -27,161 -0.6 -27,161 -0.6 -27,161 -0.6 -------------------------------------------------------------------------------------------------------------------------------------------------------- Table VII.A-2--RFS2 ``More Sensitive'' Case Emission Impacts in 2022 Relative to Each Reference Case -------------------------------------------------------------------------------------------------------------------------------------------------------- RFS1 base RFS1 Mandate AEO2007 ----------------------------------------------------------------------------------------------- Pollutant Percent of Percent of Percent of Annual short total U.S. Annual short total U.S. Annual short total U.S. tons inventory tons inventory tons inventory -------------------------------------------------------------------------------------------------------------------------------------------------------- NOx..................................................... 402,795 3.6 341,028 3.0 210,217 1.9 HC...................................................... 100,313 0.9 63,530 0.6 -15,948 -0.14 PM10.................................................... 46,193 1.3 33,035 0.9 5,164 0.15 PM2.5................................................... 10,535 0.3 7,666 0.2 1,589 0.05 CO...................................................... -3,779,572 -7.0 -3,104,798 -5.8 -1,675,869 -3.1 Benzene................................................. -5,962 -3.5 -5,494 -3.3 -4,489 -2.7 Ethanol................................................. 228,563 39.6 187,926 32.5 105,264 18.2 1,3-Butadiene........................................... -212 -1.8 -282 -2.4 -430 -3.6 Acetaldehyde............................................ 16,375 44.0 14,278 38.4 9,839 26.5 Formaldehyde............................................ 3,373 4.7 3,124 4.3 2,596 3.6 Naphthalene............................................. -175 -1.2 -178 -1.3 -187 -1.3 Acrolein................................................ 253 4.4 218 3.8 143 2.5 SO2..................................................... 28,770 0.3 4,461 0.05 -47,030 -0.5 NH3..................................................... -27,161 -0.6 -27,161 -0.6 -27,161 -0.6 -------------------------------------------------------------------------------------------------------------------------------------------------------- [[Page 25061]] The breakdown of these results by the fuel production/distribution (``well-to-pump'' emissions) and vehicle and equipment (``pump-to- wheel'') emissions is discussed in the following sections. B. Fuel Production & Distribution Impacts of the Proposed Program Fuel production and distribution emission impacts of the proposed program were estimated in conjunction with the development of life cycle GHG emission impacts and the GHG emission inventories discussed in Section VI. These emissions are calculated according to the breakdowns of agriculture, feedstock transport, fuel production, and fuel distribution; the basic calculation is a function of fuel volumes in the analysis year and the emission factors associated with each process or subprocess. Additionally, the emission impact of displaced petroleum is estimated, using the same domestic/import shares discussed in Section VI above. In general the basis for this life cycle evaluation was the analysis conducted as part of the Renewable Fuel Standard (RFS1) rulemaking, but enhanced significantly. While our approach for the RFS1 was to rely heavily on the ``Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation'' (GREET) model, developed by the Department of Energy's Argonne National Laboratory (ANL), we are now able to take advantage of additional information and models to significantly strengthen and expand our analysis for this proposed rule. In particular, the modeling of the agriculture sector was greatly expanded beyond the RFS1 analysis, employing economic and agriculture models to consider factors such as land-use impact, agricultural burning, fertilizer, pesticide use, livestock, crop allocation, and crop exports. Other updates and enhancements to the GREET model assumptions include updated feedstock energy requirements and estimates of excess electricity available for sale from new cellulosic ethanol plants, based on modeling by the National Renewable Energy Laboratory (NREL). EPA also updated the fuel and feedstock transport emission factors to account for recent EPA emission standards and modeling, such as the diesel truck standards published in 2001 and the locomotive and commercial marine standards finalized in 2008. Emission factors for new corn ethanol plants continue to use the values developed for the RFS1 rule, which were based on data submitted by states for dry mill plants. There are no new standards planned at this time that would offer any additional control of emissions from corn or cellulosic ethanol plants. In addition, GREET does not include air toxics or ethanol. Thus emission factors for ethanol and the following air toxics were added: benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein and naphthalene. Results of these calculations relative to each of the reference cases for 2022 are shown in Table VII.B-1 for the criteria pollutants, ammonia, ethanol and individual air toxic pollutants. It should be noted that the impacts relative to the two RFS1 reference cases (3.64 and 6.7 billion gallons) rely on applying ethanol volume proportions to the modeling results of the AEO2007 reference case (13.2 billion gallons). Due to the complex interactions involved in projections in the agricultural modeling, we did not attempt to adjust the agricultural inputs of the AEO reference case for the other two reference cases. So the fertilizer and pesticide quantities, livestock counts, and total agricultural acres were the same for all three reference cases. The agricultural modeling that had been done for the RFS1 rule itself was much simpler and inconsistent with the new modeling, so it would be inappropriate to use those estimates. Thus, we plan to conduct additional agricultural modeling specifically for the RFS1 mandate case prior to finalizing this rule. The fuel production and distribution impacts of the proposed program on VOC are mainly due to increases in emissions connected with biofuel production, countered by decreases in emissions associated with gasoline production and distribution as ethanol displaces some of the gasoline. Increases in NOX, PM2.5, and SOX are driven by combustion emissions from the substantial increase in corn and cellulosic ethanol production. Ethanol plants (corn and cellulosic) tend to have greater combustion emissions relative to petroleum refineries on a per-BTU of fuel produced basis. Increases in SOX emissions are primarily due to corn ethanol production. Ammonia emissions are expected to decrease substantially due to lower livestock counts, which more than offsets increased ammonia from fertilizer use. Ethanol vapor and most air toxic emissions associated with fuel production and distribution are projected to increase. Relative to the U.S. total reference case emissions with RFS1 mandate ethanol volumes, increases of 10-20% for acetaldehyde and ethanol vapor are especially significant because they are driven directly by the increased ethanol production and distribution. Formaldehyde and acrolein increases are smaller, on the order of 1-5%. Benzene emissions are estimated to decrease by 1% due to decreased gasoline production. There are also very small increases in 1,3-butadiene and decreases in naphthalene relative to the U.S. total emissions. Table VII.B-1--Fuel Production and Distribution Impacts in 2022 Relative to Each Reference Case ---------------------------------------------------------------------------------------------------------------- RFS1 base RFS1 mandate AEO2007 -------------------------------------------------------------------------------- Pollutant Percent of Percent of Percent of Annual total U.S. Annual total U.S. Annual total U.S. short tons inventory short tons inventory short tons inventory ---------------------------------------------------------------------------------------------------------------- NOX............................ 241,041 2.1 222,732 2.0 183,951 1.6 HC............................. 77,295 0.7 46,702 0.4 -17,501 -0.2 PM10........................... 50,482 1.4 37,324 1.1 9,453 0.3 PM2.5.......................... 14,419 0.4 11,550 0.3 5,473 0.16 CO............................. 186,559 0.3 179,855 0.3 165,656 -0.5 Benzene........................ -1,670 -1.0 -1,686 -1.0 -1,719 -1.0 Ethanol........................ 115,187 19.9 100,134 17.3 68,379 11.8 1,3-Butadiene.................. 16 0.13 16 0.14 17 0.14 Acetaldehyde................... 7,460 20.1 6,680 18.0 5,029 13.5 Formaldehyde................... 877 1.2 800 1.1 638 0.9 Naphthalene.................... -6 -0.04 -5 -0.04 -4 -0.03 Acrolein....................... 278 4.8 244 4.2 174 3.0 [[Page 25062]] SO2............................ 28,770 0.3 4,461 0.05 -47,030 -0.5 NH3............................ -27,161 -0.6 -27,161 -0.6 -27,161 -0.6 ---------------------------------------------------------------------------------------------------------------- C. Vehicle and Equipment Emission Impacts of Fuel Program The effects of the fuel program on vehicle and equipment emissions are a direct function of the effects of these fuels on exhaust and evaporative emissions from vehicles and off-road equipment, and evaporation of fuel from portable containers. To assess these impacts we conducted separate analyses to quantify the emission impacts of additional E10 due to today's proposal on gasoline vehicles, nonroad spark-ignited engines and portable fuel containers; E85 on cars and light trucks; biodiesel on diesel vehicles; and increased refueling events due to lower energy density of biofuels.\330\ --------------------------------------------------------------------------- \330\ The impact of renewable diesel was not estimated for the proposal; we expect little overall impact on criteria and toxic emissions due to the relatively small volume change, and because emission effects relative to conventional diesel are presumed to be negligible. --------------------------------------------------------------------------- For the proposal we have analyzed inventory impacts for two fuel effects scenarios to attempt to bound the potential impacts on ethanol on gasoline-fueled vehicle exhaust emissions: (1) ``Less Sensitive'': No exhaust VOC or NOX emission impact on Tier 1 and later vehicles due to E10, and no impact due to E85. This was termed the ``primary'' case in the RFS1 rule. (2) ``More Sensitive'': VOC and NOX emission impacts due to E10 based on limited test data from newer technology vehicles that were analyzed as part of the RFS1 rule. This data showed a 7% reduction in exhaust VOC emissions and an 8% increase in per-vehicle NOX emissions for Tier 1 and later vehicles using E10 relative to E0. The E10 effects are consistent with the ``sensitivity'' case from the RFS1 rule. For RFS2 this case also includes E85 effects reflecting significant increases in acetaldehyde, formaldehyde and ethanol emissions, and reductions in PM and CO. EPA and other parties are in the midst of gathering additional data on the emission impacts of ethanol fuels on later model vehicles, which we plan to consider in updating our final rule analysis. We have also estimated the E10 effects on permeation emissions from light-duty vehicles based on testing previously completed by the Coordinating Research Council (CRC). Nonroad spark ignition (SI) emission impacts of E10 were based on EPA's NONROAD model and show trends similar to light duty vehicles. Biodiesel effects for this analysis were based on a new analysis of recent biodiesel testing, detailed in the DRIA, showing a 2% increase in NOX with a 20% biodiesel blend, a 16% decrease in PM, and a 14% decrease in HC. These results essentially confirm the results of an earlier EPA analysis. Summarized vehicle and equipment emission impacts in 2022 are shown in Table VII.C-1 and VII.C-2 for the ``less sensitive'' and ``more sensitive'' cases. Table VII.C-3 shows the biodiesel contribution to these impacts, which are comparatively small. While the two fuel effect scenarios only differ with respect to exhaust emissions from cars and trucks, the totals shown below reflect the net impacts from all mobile sources, including car and truck evaporative emissions, off road emissions, and portable fuel containers, using the same emissions impacts for these sources in both cases. Additional breakdowns by mobile source category can be found in Chapter 3 of the DRIA. As shown in Tables VII.C-1 and VII.C-2, the vehicle and equipment ethanol impacts vary widely between the two fuel effects cases. Under the ``less sensitive'' case, CO and benzene are projected to decrease in 2022 under today's proposal, while NOX, HC and the other air toxics (except acrolein) are projected to increase due to the impacts of E10. For the ``more sensitive'' case, NOX impacts are higher and HC impacts lower due to the E10 effects on cars and trucks, and the inclusion of E85 effects leads to larger reductions in CO, benzene and 1,3-butadiene but more significant increases in ethanol, acetaldehyde and formaldehyde. The impacts on acrolein emissions in both cases, and on naphthalene in the ``more sensitive'' case depend on which reference case is considered, with small increases relative to the RFS1 base and mandate cases and a decrease relative to the AEO reference case. Table VII.C-1--2022 Vehicle and Equipment ``Less Sensitive'' Case Emission Impacts by Fuel Type Relative to Each Reference Case -------------------------------------------------------------------------------------------------------------------------------------------------------- RFS1 base RFS1 mandate AEO2007 ----------------------------------------------------------------------------------------------- Pollutant Percent of Percent of Percent of Annual short total U.S. Annual short total U.S. Annual short total U.S. tons inventory tons inventory tons inventory -------------------------------------------------------------------------------------------------------------------------------------------------------- NOX..................................................... 71,359 0.6 52,250 0.5 11,784 0.11 HC...................................................... 35,106 0.3 25,659 0.2 9,308 0.08 PM10.................................................... -177 0.00 -177 0.00 -177 0.00 PM2.5................................................... -98 0.00 -98 0.00 -98 0.00 CO...................................................... -2,531,205 -4.7 -1,849,728 -3.4 -406,599 -0.8 Benzene................................................. -1,122 -0.7 -821 -0.5 -174 -0.1 Ethanol................................................. 95,493 16.5 69,795 12.1 15,383 2.7 1,3-Butadiene........................................... 328 2.7 238 2.0 48 0.4 Acetaldehyde............................................ 5,057 13.6 3,689 9.9 793 2.1 [[Page 25063]] Formaldehyde............................................ 771 1.1 548 0.8 76 0.11 Naphthalene............................................. 10 0.07 8 0.05 3 0.02 Acrolein................................................ 12 0.2 8 0.14 -0.4 -0.01 SO2..................................................... 0 0.0 0 0.0 0 0.0 NH3..................................................... 0 0.0 0 0.0 0 0.0 -------------------------------------------------------------------------------------------------------------------------------------------------------- Table VII.C-2--2022 Vehicle and Equipment ``More Sensitive'' Case Emission Impacts by Fuel Type Relative to Each Reference Case -------------------------------------------------------------------------------------------------------------------------------------------------------- RFS1 base RFS1 mandate AEO2007 ----------------------------------------------------------------------------------------------- Pollutant Percent of Percent of Percent of Annual short total U.S. Annual short total U.S. Annual short total U.S. tons inventory tons inventory tons inventory -------------------------------------------------------------------------------------------------------------------------------------------------------- NOX..................................................... 161,754 1.4 118,295 1.1 26,266 0.2 HC...................................................... 23,018 0.2 16,828 0.15 1,553 0.01 PM10.................................................... -4,289 -0.12 -4,289 -0.12 -4,289 -0.12 PM2.5................................................... -3,884 -0.12 -3,884 -0.12 -3,884 -0.12 CO...................................................... -3,966,131 -7.4 -3,284,654 -6.1 -1,841,524 -3.4 Benzene................................................. -4,293 -2.6 -3,808 -2.3 -2,770 -1.6 Ethanol................................................. 113,376 19.6 87,792 15.2 36,886 6.4 1,3-Butadiene........................................... -228 -1.9 -298 -2.5 -446 -3.7 Acetaldehyde............................................ 8,915 24.0 7,598 20.4 4,809 12.9 Formaldehyde............................................ 2,497 3.5 2,324 3.2 1,958 2.7 Naphthalene............................................. -170 -1.2 -172 -1.2 -182 -1.3 Acrolein................................................ -25 -0.4 -27 -0.5 -31 -0.5 SO2..................................................... 0 0.0 0 0.0 0 0.0 NH3..................................................... 0 0.0 0 0.0 0 0.0 -------------------------------------------------------------------------------------------------------------------------------------------------------- Table VII.C-3--2022 Vehicle and Equipment Biodiesel Emission Impacts Relative to All Reference Cases [these impacts are included in Tables VII.C-1 and VII.C-2] ------------------------------------------------------------------------ Biodiesel impacts Pollutant ------------ Annual short tons ------------------------------------------------------------------------ NOX........................................................ 418 HC......................................................... -753 PM10....................................................... -177 PM2.5...................................................... -98 CO......................................................... -1,275 Benzene.................................................... -9.4 Ethanol.................................................... 0.0 1,3-Butadiene.............................................. -5.1 Acetaldehyde............................................... -21 Formaldehyde............................................... -57 Naphthalene................................................ -0.12 Acrolein................................................... -2.7 SO2........................................................ 0.0 NH3........................................................ 0.0 ------------------------------------------------------------------------ D. Air Quality Impacts Although the purpose of this proposal is to implement the renewable fuel requirements established by the Energy Independence and Security Act (EISA) of 2007, this proposed rule would also impact emissions of criteria and air toxic pollutants. We first present current levels of PM2.5, ozone and air toxics and then discuss the national- scale air quality modeling analysis that will be performed for the final rule. 1. Current Levels of PM2.5, Ozone and Air Toxics This proposal may have impacts on levels of PM2.5, ozone and air toxics.\331\ Nationally, levels of PM2.5, ozone and air toxics are declining.332 333 However, as of December 16, 2008, approximately 88 million people live in the 39 areas that are designated as nonattainment for the 1997 PM2.5 National Ambient Air Quality Standard (NAAQS) and approximately 132 million people live in the 57 areas that are designated as nonattainment for the 1997 8-hour ozone NAAQS. The 1997 PM2.5 NAAQS was recently revised and the 2006 24-hour PM2.5 NAAQS became effective on December 18, 2006. Area designations for the 2006 24-hour PM2.5 NAAQS are expected to be promulgated in 2009 and become effective 90 days after publication in the Federal Register. In addition, the majority of Americans continue to be exposed to ambient concentrations of air toxics at levels which have the potential to cause adverse health effects.\334\ The levels of air toxics to which people are exposed vary depending on where people live and work and the kinds of activities in which they engage, as discussed in [[Page 25064]] detail in U.S. EPA's recent Mobile Source Air Toxics Rule.\335\ --------------------------------------------------------------------------- \331\ The proposed standards may also impact levels of ambient CO, a criteria pollutant (see Table VII.A-1 above for co-pollutant emission impacts). For this analysis, however, we focus on the proposal's impacts on ambient PM2.5 and ozone formation, since CO is a relatively minor problem in comparison to some of the other criteria pollutants. For example, as of August 15, 2008 there are approximately 675,000 people living in 3 areas (which include 4 counties) that are designated as nonattainment for CO. \332\ \\ U.S. EPA (2003) National Air Quality and Trends Report, 2003 Special Studies Edition. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Publication No. EPA 454/R-03- 005. http://www.epa.gov/air/airtrends/aqtrnd03/. \333\ \\ U.S. EPA (2007) Final Regulatory Impact Analysis: Control of Hazardous Air Pollutants from Mobile Sources, Office of Transportation and Air Quality, Ann Arbor, MI, Publication No. EPA420-R-07-002. http://www.epa.gov/otaq/toxics.htm \334\ U.S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final Rule. 72 FR 8434, February 26, 2007. \335\ U.S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final Rule. 72 FR 8434, February 26, 2007. --------------------------------------------------------------------------- EPA has already adopted many emission control programs that are expected to reduce ambient PM2.5, ozone and air toxics levels. These control programs include the Small SI and Marine SI Engine Rule (73 FR 59034, October 8, 2008), Locomotive and Commercial Marine Rule (73 FR 25098, May 6, 2008), Mobile Source Air Toxics Rule (72 FR 8428, February 26, 2007), Clean Air Interstate Rule (70 FR 25162, May 12, 2005), Clean Air Nonroad Diesel Rule (69 FR 38957, June 29, 2004), Heavy Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements (66 FR 5002, Jan. 18, 2001) and the Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements (65 FR 6698, Feb. 10, 2000). As a result of these programs, the ambient concentration of air toxics, PM2.5 and ozone in the future is expected to decrease. 2. Impacts of Proposed Standards on Future Ambient Concentrations of PM2.5, Ozone and Air Toxics The atmospheric chemistry related to ambient concentrations of PM2.5, ozone and air toxics is very complex, making predictions based solely on emissions changes extremely difficult. For the final rule, a national-scale air quality modeling analysis will be performed to analyze the impacts of the proposed standards on ambient concentrations of PM2.5, ozone, and selected air toxics (i.e., benzene, formaldehyde, acetaldehyde, ethanol, acrolein and 1,3- butadiene). The length of time needed to prepare necessary inventory and model updates has precluded us from performing air quality modeling for this proposal. The air quality modeling we plan to perform (described more specifically below), will allow us to account for changes in the spatial distribution of PM and PM precursors, and changes in VOC speciation which could impact secondary PM formation. For example, reductions in aromatics in gasoline may reduce ambient PM concentrations by reducing secondary PM formation. Section 3.3 of the Draft Regulatory Impact Analysis (DRIA) for this proposal contains more information on aromatics and secondary aerosol formation. In addition, air quality modeling will account for changes in fuel type and spatial distribution of fuels that would change emissions of ozone precursor species and thus could affect ozone concentrations. Section 3.3 of the DRIA for this proposed rule provides more detail on the atmospheric chemistry and potential changes in ozone formation due to increased usage of ethanol fuels. Section VII.A above presents projections of the changes in air toxics emissions due to the proposed standards. The substantial increase in emissions of ethanol and acetaldehyde suggests a likely increase in ambient levels of acetaldehyde from both direct emissions and secondary formation as ethanol breaks down in the atmosphere. Formaldehyde and acrolein emissions would also increase somewhat, while emissions of benzene and 1,3-butadiene would decrease as a result of the proposed standards. Full-scale photochemical modeling is necessary to provide the needed spatial and temporal detail to more completely and accurately estimate the changes in ambient levels of these pollutants. For the final rule, EPA intends to use a 2005-based Community Multi-scale Air Quality (CMAQ) modeling platform as the tool for the air quality modeling. The CMAQ modeling system is a comprehensive three-dimensional grid-based Eulerian air quality model designed to estimate the formation and fate of oxidant precursors, primary and secondary PM concentrations and deposition, and air toxics, over regional and urban spatial scales (e.g., over the contiguous U.S.).336 337 338 The CMAQ model is a well-known and well- established tool and is commonly used by EPA for regulatory analyses, for instance the recent ozone NAAQS proposal, and by States in developing attainment demonstrations for their State Implementation Plans.\339\ The CMAQ model (version 4.6) was peer-reviewed in February of 2007 for EPA as reported in ``Third Peer Review of CMAQ Model,'' and the peer review report for version 4.7 (described below) is currently being finalized.\340\ --------------------------------------------------------------------------- \336\ U.S. Environmental Protection Agency, Byun, D.W., and Ching, J.K.S., Eds, 1999. Science algorithms of EPA Models-3 Community Multiscale Air Quality (CMAQ modeling system, EPA/600/R- 99/030, Office of Research and Development). \337\ Byun, D.W., and Schere, K.L., 2006. Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System, J. Applied Mechanics Reviews, 59 (2), 51-77. \338\ Dennis, R.L., Byun, D.W., Novak, J.H., Galluppi, K.J., Coats, C.J., and Vouk, M.A., 1996. The next generation of integrated air quality modeling: EPA's Models-3, Atmospheric Environment, 30, 1925-1938. \339\ U.S. EPA (2007). Regulatory Impact Analysis of the Proposed Revisions to the National Ambient Air Quality Standards for Ground-Level Ozone. EPA document number 442/R-07-008, July 2007. \340\ Aiyyer, A., Cohan, D., Russell, A., Stockwell, W., Tanrikulu, S., Vizuete, W., Wilczak, J., 2007. Final Report: Third Peer Review of the CMAQ Model. p. 23. --------------------------------------------------------------------------- CMAQ includes many science modules that simulate the emission, production, decay, deposition and transport of organic and inorganic gas-phase and particle-phase pollutants in the atmosphere. We intend to use the most recent CMAQ version (version 4.7) which was officially released by EPA's Office of Research and Development (ORD) in December 2008, and reflects updates to earlier versions in a number of areas to improve the underlying science. These include (1) enhanced secondary organic aerosol (SOA) mechanism to include chemistry of isoprene, sesquiterpene, and aged in-cloud biogenic SOA in addition to terpene; (2) improved vertical convective mixing; (3) improved heterogeneous reaction involving nitrate formation; and (4) an updated gas-phase chemistry mechanism, Carbon Bond 05 (CB05), with extensions to model explicit concentrations of air toxic species as well as chlorine and mercury. This mechanism, CB05-toxics, also computes concentrations of species that are involved in aqueous chemistry and that are precursors to aerosols. Section 3.3.3 of the DRIA for this proposal discusses SOA formation and details about the improvements made to the SOA mechanism within this recent release of CMAQ. E. Health Effects of Criteria and Air Toxic Pollutants 1. Particulate Matter a. Background Particulate matter (PM) represents a broad class of chemically and physically diverse substances. It can be principally characterized as discrete particles that exist in the condensed (liquid or solid) phase spanning several orders of magnitude in size. PM is further described by breaking it down into size fractions. PM10 refers to particles generally less than or equal to 10 micrometers (μm) in aerodynamic diameter. PM2.5 refers to fine particles, generally less than or equal to 2.5 μm in aerodynamic diameter. Inhalable (or ``thoracic'') coarse particles refer to those particles generally greater than 2.5 μm but less than or equal to 10 μm in aerodynamic diameter. Ultrafine PM refers to particles less than 100 nanometers (0.1 μm) in aerodynamic diameter. Larger particles tend to be removed by the respiratory clearance mechanisms (e.g., coughing), whereas [[Page 25065]] smaller particles are deposited deeper in the lungs. Fine particles are produced primarily by combustion processes and by transformations of gaseous emissions (e.g., SOX, NOX and VOC) in the atmosphere. The chemical and physical properties of PM2.5 may vary greatly with time, region, meteorology and source category. Thus, PM2.5 may include a complex mixture of different pollutants including sulfates, nitrates, organic compounds, elemental carbon and metal compounds. These particles can remain in the atmosphere for days to weeks and travel hundreds to thousands of kilometers. b. Health Effects of PM Scientific studies show ambient PM is associated with a series of adverse health effects. These health effects are discussed in detail in the 2004 EPA Particulate Matter Air Quality Criteria Document (PM AQCD), and the 2005 PM Staff Paper.341 342 Further discussion of health effects associated with PM can also be found in the DRIA for this rule. --------------------------------------------------------------------------- \341\ U.S. EPA (2004) Air Quality Criteria for Particulate Matter (Oct. 2004), Volume I Document No. EPA600/P-99/002aF and Volume II Document No. EPA600/P-99/002bF. This document is available in Docket EPA-HQ-OAR-2005-0161. \342\ U.S. EPA (2005) Review of the National Ambient Air Quality Standard for Particulate Matter: Policy Assessment of Scientific and Technical Information, OAQPS Staff Paper. EPA-452/R-05-005. This document is available in Docket EPA-HQ-OAR-2005-0161. --------------------------------------------------------------------------- Health effects associated with short-term exposures (hours to days) to ambient PM include premature mortality, increased hospital admissions, heart and lung diseases, increased cough, adverse lower- respiratory symptoms, decrements in lung function and changes in heart rate rhythm and other cardiac effects. Studies examining populations exposed to different levels of air pollution over a number of years, including the Harvard Six Cities Study and the American Cancer Society Study, show associations between long-term exposure to ambient PM2.5 and both total and cardiovascular and respiratory mortality.\343\ In addition, a reanalysis of the American Cancer Society Study shows an association between fine particle and sulfate concentrations and lung cancer mortality.\344\ --------------------------------------------------------------------------- \343\ Dockery, D.W.; Pope, C.A. III: Xu, X.; et al. 1993. An association between air pollution and mortality in six U.S. cities. N Engl J Med 329:1753-1759. \344\ Pope, C.A., III; Burnett, R.T.; Thun, M.J.; Calle, E.E.; Krewski, D.; Ito, K.; Thurston, G.D. (2002) Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. J. Am. Med. Assoc. 287:1132-1141. --------------------------------------------------------------------------- 2. Ozone a. Background Ground-level ozone pollution is typically formed by the reaction of volatile organic compounds (VOC) and nitrogen oxides (NOX) in the lower atmosphere in the presence of heat and sunlight. These pollutants, often referred to as ozone precursors, are emitted by many types of pollution sources, such as highway and nonroad motor vehicles and engines, power plants, chemical plants, refineries, makers of consumer and commercial products, industrial facilities, and smaller area sources. The science of ozone formation, transport, and accumulation is complex.\345\ Ground-level ozone is produced and destroyed in a cyclical set of chemical reactions, many of which are sensitive to temperature and sunlight. When ambient temperatures and sunlight levels remain high for several days and the air is relatively stagnant, ozone and its precursors can build up and result in more ozone than typically occurs on a single high-temperature day. Ozone can be transported hundreds of miles downwind from precursor emissions, resulting in elevated ozone levels even in areas with low local VOC or NOX emissions. --------------------------------------------------------------------------- \345\ U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental Protection Agency, Washington, D.C., EPA 600/R-05/004aF-cF, 2006. This document is available in Docket EPA-HQ-OAR-2005-0161. This document may be accessed electronically at: http://www.epa.gov/ttn/naaqs/standards/ ozone/s_o3_cr_cd.html. --------------------------------------------------------------------------- b. Health Effects of Ozone The health and welfare effects of ozone are well documented and are assessed in EPA's 2006 Ozone Air Quality Criteria Document (ozone AQCD) and 2007 Staff Paper.346 347 Ozone can irritate the respiratory system, causing coughing, throat irritation, and/or uncomfortable sensation in the chest. Ozone can reduce lung function and make it more difficult to breathe deeply; breathing may also become more rapid and shallow than normal, thereby limiting a person's activity. Ozone can also aggravate asthma, leading to more asthma attacks that require medical attention and/or the use of additional medication. In addition, there is suggestive evidence of a contribution of ozone to cardiovascular-related morbidity and highly suggestive evidence that short-term ozone exposure directly or indirectly contributes to non-accidental and cardiopulmonary-related mortality, but additional research is needed to clarify the underlying mechanisms causing these effects. In a recent report on the estimation of ozone- related premature mortality published by the National Research Council (NRC), a panel of experts and reviewers concluded that short-term exposure to ambient ozone is likely to contribute to premature deaths and that ozone-related mortality should be included in estimates of the health benefits of reducing ozone exposure.\348\ Animal toxicological evidence indicates that with repeated exposure, ozone can inflame and damage the lining of the lungs, which may lead to permanent changes in lung tissue and irreversible reductions in lung function. People who are more susceptible to effects associated with exposure to ozone can include children, the elderly, and individuals with respiratory disease such as asthma. Those with greater exposures to ozone, for instance due to time spent outdoors (e.g., children and outdoor workers), are also of particular concern. --------------------------------------------------------------------------- \346\ U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental Protection Agency, Washington, DC, EPA 600/R-05/004aF-cF, 2006. This document is available in Docket EPA-HQ-OAR-2005-0161. This document may be accessed electronically at: http://www.epa.gov/ttn/naaqs/standards/ ozone/s_o3_cr_cd.html. \347\ U.S. EPA (2007) Review of the National Ambient Air Quality Standards for Ozone, Policy Assessment of Scientific and Technical Information. OAQPS Staff Paper.EPA-452/R-07-003. This document is available in Docket EPA-HQ-OAR-2005-0161. This document is available electronically at: www.epa.gov/ttn/naaqs/standards/ozone/s_ o3_cr_sp.html. \348\ National Research Council (NRC), 2008. Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution. The National Academies Press: Washington, DC. --------------------------------------------------------------------------- The 2006 ozone AQCD also examined relevant new scientific information that has emerged in the past decade, including the impact of ozone exposure on such health effects as changes in lung structure and biochemistry, inflammation of the lungs, exacerbation and causation of asthma, respiratory illness-related school absence, hospital admissions and premature mortality. Animal toxicological studies have suggested potential interactions between ozone and PM, with increased responses observed to mixtures of the two pollutants compared to either ozone or PM alone. The respiratory morbidity observed in animal studies along with the evidence from epidemiologic studies supports a causal relationship between acute ambient ozone exposures and increased respiratory-related emergency room visits and hospitalizations in the warm season. In addition, there is [[Page 25066]] suggestive evidence of a contribution of ozone to cardiovascular- related morbidity and non-accidental and cardiopulmonary mortality. 3. Carbon Monoxide Carbon monoxide (CO) forms as a result of incomplete fuel combustion. CO enters the bloodstream through the lungs, forming carboxyhemoglobin and reducing the delivery of oxygen to the body's organs and tissues. The health threat from CO is most serious for those who suffer from cardiovascular disease, particularly those with angina or peripheral vascular disease. Healthy individuals also are affected, but only at higher CO levels. Exposure to elevated CO levels is associated with impairment of visual perception, work capacity, manual dexterity, learning ability and performance of complex tasks. Carbon monoxide also contributes to ozone nonattainment since carbon monoxide reacts photochemically in the atmosphere to form ozone.\349\ Additional information on CO related health effects can be found in the Carbon Monoxide Air Quality Criteria Document (CO AQCD).\350\ --------------------------------------------------------------------------- \349\ U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide, EPA/600/P-99/001F. This document is available in Docket EPA-HQ-OAR-2005-0161. \350\ U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide, EPA/600/P-99/001F. This document is available in Docket EPA-HQ-OAR-2005-0161. --------------------------------------------------------------------------- 4. Air Toxics The population experiences an elevated risk of cancer and noncancer health effects from exposure to the class of pollutants known collectively as ``air toxics.''\351\ Fuel combustion contributes to ambient levels of air toxics that can include, but are not limited to, acetaldehyde, acrolein, benzene, 1,3-butadiene, formaldehyde, ethanol, naphthalene and peroxyacetyl nitrate (PAN). Acrolein, benzene, 1,3- butadiene, formaldehyde and naphthalene have significant contributions from mobile sources and were identified as national or regional risk drivers in the 1999 National-scale Air Toxics Assessment (NATA).\352\ PAN, which is formed from precursor compounds by atmospheric processes, is not assessed in NATA. Emissions and ambient concentrations of compounds are discussed in the DRIA chapter on emission inventories and air quality (Chapter 3). --------------------------------------------------------------------------- \351\ U. S. EPA. 1999 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata1999/risksum.html \352\ U.S. EPA. 2006. National-Scale Air Toxics Assessment for 1999. http://www.epa.gov/ttn/atw/nata1999 --------------------------------------------------------------------------- a. Acetaldehyde Acetaldehyde is classified in EPA's IRIS database as a probable human carcinogen, based on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous routes.\353\ Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. DHHS in the 11th Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC.354 355 EPA is currently conducting a reassessment of cancer risk from inhalation exposure to acetaldehyde. --------------------------------------------------------------------------- \353\ U.S. EPA. 1991. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at. \354\ U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. \355\ International Agency for Research on Cancer (IARC). 1999. Re-evaluation of some organic chemicals, hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, Vol 71. Lyon, France. --------------------------------------------------------------------------- The primary noncancer effects of exposure to acetaldehyde vapors include irritation of the eyes, skin, and respiratory tract.\356\ In short-term (4 week) rat studies, degeneration of olfactory epithelium was observed at various concentration levels of acetaldehyde exposure.357 358 Data from these studies were used by EPA to develop an inhalation reference concentration. Some asthmatics have been shown to be a sensitive subpopulation to decrements in functional expiratory volume (FEV1 test) and bronchoconstriction upon acetaldehyde inhalation.\359\ The agency is currently conducting a reassessment of the health hazards from inhalation exposure to acetaldehyde. --------------------------------------------------------------------------- \356\ U.S. EPA. 1991. Integrated Risk Information System File of Acetaldehyde. This material is available electronically at http://www.epa.gov/iris/subst/0290.htm. \357\ Appleman, L. M., R. A. Woutersen, V. J. Feron, R. N. Hooftman, and W. R. F. Notten. 1986. Effects of the variable versus fixed exposure levels on the toxicity of acetaldehyde in rats. J. Appl. Toxicol. 6: 331-336. \358\ Appleman, L.M., R.A. Woutersen, and V.J. Feron. 1982. Inhalation toxicity of acetaldehyde in rats. I. Acute and subacute studies. Toxicology. 23: 293-297. \359\ Myou, S.; Fujimura, M.; Nishi, K.; Ohka, T.; and Matsuda, T. 1993. Aerosolized acetaldehyde induces histamine-mediated bronchoconstriction in asthmatics. Am. Rev. Respir. Dis. 148 (4 Pt 1): 940-3. --------------------------------------------------------------------------- b. Acrolein EPA determined in 2003 that the human carcinogenic potential of acrolein could not be determined because the available data were inadequate. No information was available on the carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of carcinogenicity.\360\ The IARC determined in 1995 that acrolein was not classifiable as to its carcinogenicity in humans.\361\ --------------------------------------------------------------------------- \360\ U.S. EPA. 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/subst/0364.htm. \361\ International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals, World Health Organization, Lyon, France. --------------------------------------------------------------------------- Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure resulting in upper respiratory tract irritation, mucus hypersecretion and congestion. Levels considerably lower than 1 ppm (2.3 mg/m\3\) elicit subjective complaints of eye and nasal irritation and a decrease in the respiratory rate.362 363 Lesions to the lungs and upper respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein. Based on animal data, individuals with compromised respiratory function (e.g., emphysema, asthma) are expected to be at increased risk of developing adverse responses to strong respiratory irritants such as acrolein. This was demonstrated in mice with allergic airway disease by comparison to non-diseased mice in a study of the acute respiratory irritant effects of acrolein.\364\ --------------------------------------------------------------------------- \362\ Weber-Tschopp, A.; Fischer, T.; Gierer, R.; et al. (1977) Experimentelle reizwirkungen von Acrolein auf den Menschen. Int Arch Occup Environ Hlth 40(2):117-130. In German. \363\ Sim, V.M.; Pattle, R.E. (1957) Effect of possible smog irritants on human subjects. J Am Med Assoc 165(15):1908-1913. \364\ Morris J.B., Symanowicz P.T., Olsen J.E., et al. 2003. Immediate sensory nerve-mediated respiratory responses to irritants in healthy and allergic airway-diseased mice. J Appl Physiol 94(4):1563-1571. --------------------------------------------------------------------------- The intense irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure.\365\ --------------------------------------------------------------------------- \365\ Sim V.M., Pattle R.E. Effect of possible smog irritants on human subjects. JAMA 165:1980-2010, 1957. --------------------------------------------------------------------------- c. Benzene The EPA's IRIS database lists benzene as a known human carcinogen (causing leukemia) by all routes of exposure, and concludes that exposure is associated with additional health effects, including [[Page 25067]] genetic changes in both humans and animals and increased proliferation of bone marrow cells in mice.366 367 368 EPA states in its IRIS database that data indicate a causal relationship between benzene exposure and acute lymphocytic leukemia and suggest a relationship between benzene exposure and chronic non-lymphocytic leukemia and chronic lymphocytic leukemia. The International Agency for Research on Carcinogens (IARC) has determined that benzene is a human carcinogen and the U.S. Department of Health and Human Services (DHHS) has characterized benzene as a known human carcinogen.369 370 --------------------------------------------------------------------------- \366\ U.S. EPA. 2000. Integrated Risk Information System File for Benzene. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. \367\ International Agency for Research on Cancer (IARC). 1982. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, World Health Organization, Lyon, France, p. 345-389. \368\ Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. 1992. Synergistic action of the benzene metabolite hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony-stimulating factor in vitro, Proc. Natl. Acad. Sci. 89:3691-3695. \369\ International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health Organization, Lyon, France. \370\ U.S. Department of Health and Human Services National Toxicology Program, 11th Report on Carcinogens, available at: http://ntp.niehs.nih.gov/go/16183. --------------------------------------------------------------------------- A number of adverse noncancer health effects including blood disorders, such as preleukemia and aplastic anemia, have also been associated with long-term exposure to benzene.371 372 The most sensitive noncancer effect observed in humans, based on current data, is the depression of the absolute lymphocyte count in blood.373 374 In addition, recent work, including studies sponsored by the Health Effects Institute (HEI), provides evidence that biochemical responses are occurring at lower levels of benzene exposure than previously known.375 376 377 378 EPA's IRIS program has not yet evaluated these new data. --------------------------------------------------------------------------- \371\ Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82:193-197. \372\ Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3:541-554. \373\ Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet, L.Q. Xi, W. Lu, M.T. Smith, N. Titenko- Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B. Hayes (1996) Hematotoxicity among Chinese workers heavily exposed to benzene. Am. J. Ind. Med. 29:236-246. \374\ U.S. EPA (2002) Toxicological Review of Benzene (Noncancer Effects). Environmental Protection Agency, Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental Assessment, Washington DC. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. \375\ Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.; Rupa, D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.; Zhang, X.; Li, K. (2003) HEI Report 115, Validation & Evaluation of Biomarkers in Workers Exposed to Benzene in China. \376\ Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002) Hematological changes among Chinese workers with a broad range of benzene exposures. Am. J. Industr. Med. 42:275-285. \377\ Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. (2004) Hematotoxicity in Workers Exposed to Low Levels of Benzene. Science 306:1774-1776. \378\ Turtletaub, K.W. and Mani, C. (2003) Benzene metabolism in rodents at doses relevant to human exposure from Urban Air. Research Reports Health Effect Inst. Report No. 113. --------------------------------------------------------------------------- d. 1,3-Butadiene EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation.379 380 The IARC has determined that 1,3- butadiene is a human carcinogen and the U.S. DHHS has characterized 1,3-butadiene as a known human carcinogen.381 382 There are numerous studies consistently demonstrating that 1,3-butadiene is metabolized into genotoxic metabolites by experimental animals and humans. The specific mechanisms of 1,3-butadiene-induced carcinogenesis are unknown; however, the scientific evidence strongly suggests that the carcinogenic effects are mediated by genotoxic metabolites. Animal data suggest that females may be more sensitive than males for cancer effects associated with 1,3-butadiene exposure; there are insufficient data in humans from which to draw conclusions about sensitive subpopulations. 1,3-butadiene also causes a variety of reproductive and developmental effects in mice; no human data on these effects are available. The most sensitive effect was ovarian atrophy observed in a lifetime bioassay of female mice.\383\ --------------------------------------------------------------------------- \379\ U.S. EPA (2002) Health Assessment of 1,3-Butadiene. Office of Research and Development, National Center for Environmental Assessment, Washington Office, Washington, DC. Report No. EPA600-P- 98-001F. This document is available electronically at http://www.epa.gov/iris/supdocs/buta-sup.pdf. \380\ U.S. EPA (2002) Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0). Environmental Protection Agency, Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental Assessment, Washington, DC, http://www.epa.gov/ iris/subst/0139.htm. \381\ International Agency for Research on Cancer (IARC) (1999) Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 71, Re-evaluation of some organic chemicals, hydrazine and hydrogen peroxide and Volume 97 (in preparation), World Health Organization, Lyon, France. \382\ U.S. Department of Health and Human Services (2005) National Toxicology Program, 11th Report on Carcinogens, available at: http://ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E- 7FCE50709CB4C932. \383\ Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996) Subchronic toxicity of 4-vinylcyclohexene in rats and mice by inhalation. Fundam. Appl. Toxicol. 32:1-10. --------------------------------------------------------------------------- e. Ethanol EPA is conducting an assessment of the cancer and noncancer effects of exposure to ethanol, a compound which is not currently listed in EPA's IRIS. A description of these effects to the extent that information is available will be presented, as required by Section 1505 of EPAct, in a report to Congress on public health, air quality and water resource impacts of fuel additives. We expect to release that report in 2009. Extensive data are available regarding adverse health effects associated with the ingestion of ethanol while data on inhalation exposure effects are sparse. As part of the IRIS assessment, pharmacokinetic models are being evaluated as a means of extrapolating across species (animal to human) and across exposure routes (oral to inhalation) to better characterize the health hazards and dose-response relationships for low levels of ethanol exposure in the environment. The IARC has classified ``alcoholic beverages'' as carcinogenic to humans based on sufficient evidence that malignant tumors of the mouth, pharynx, larynx, esophagus, and liver are causally related to the consumption of alcoholic beverages.\384\ The U.S. DHHS in the 11th Report on Carcinogens also identified ``alcoholic beverages'' as a known human carcinogen (they have not evaluated the cancer risks specifically from exposure to ethanol), with evidence for cancer of the mouth, pharynx, larynx, esophagus, liver and breast.\385\ There are no studies reporting carcinogenic effects from inhalation of ethanol. EPA is currently evaluating the available human and animal cancer data to identify which cancer type(s) are the most relevant to an assessment of risk to humans from a low-level oral and inhalation exposure to ethanol. --------------------------------------------------------------------------- \384\ International Agency for Research on Cancer (IARC). 1988. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 44, Alcohol Drinking, World Health Organization, Lyon, France. \385\ U.S. Department of Health and Human Services. 2005. National Toxicology Program 11th Report on Carcinogens available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. --------------------------------------------------------------------------- Noncancer health effects data are available from animal studies as well as epidemiologic studies. The epidemiologic data are obtained from studies of alcoholic beverage [[Page 25068]] consumption. Effects include neurological impairment, developmental effects, cardiovascular effects, immune system depression, and effects on the liver, pancreas and reproductive system.\386\ There is evidence that children prenatally exposed via mothers' ingestion of alcoholic beverages during pregnancy are at increased risk of hyperactivity and attention deficits, impaired motor coordination, a lack of regulation of social behavior or poor psychosocial functioning, and deficits in cognition, mathematical ability, verbal fluency, and spatial memory.387 388 389 390 391 392 393 394 In some people, genetic factors influencing the metabolism of ethanol can lead to differences in internal levels of ethanol and may render some subpopulations more susceptible to risks from the effects of ethanol. --------------------------------------------------------------------------- \386\ U.S. Department of Health and Human Services. 2000. 10th Special Report to the U.S. Congress on Alcohol and Health. June 2000. \387\ Goodlett CR, KH Horn, F Zhou. 2005. Alcohol teratogenesis: mechanisms of damage and strategies for intervention. Exp. Biol. Med. 230:394-406. \388\ Riley EP, CL McGee. 2005. Fetal alcohol spectrum disorders: an overview with emphasis on changes in brain and behavior. Exp. Biol. Med. 230:357-365. \389\ Zhang X, JH Sliwowska, J Weinberg. 2005. Prenatal alcohol exposure and fetal programming: effects on neuroendocrine and immune function. Exp. Biol. Med. 230:376-388. \390\ Riley EP, CL McGee, ER Sowell. 2004. Teratogenic effects of alcohol: a decade of brain imaging. Am. J. Med. Genet. Part C: Semin. Med. Genet. 127:35-41. \391\ Gunzerath L, V Faden, S Zakhari, K Warren. 2004. National Institute on Alcohol Abuse and Alcoholism report on moderate drinking. Alcohol. Clin. Exp. Res. 28:829-847. \392\ World Health Organization (WHO). 2004. Global status report on alcohol 2004. Geneva, Switzerland: Department of Mental Health and Substance Abuse. Available: http://www.who.int/substance_abuse/publications/global_status_report_2004_ overview.pdf.