Higher water temperatures, increased precipitation intensity, and longer periods of low flows will exacerbate many forms of water pollution, potentially making attainment of water quality goals more difficult.  As waters become warmer, the aquatic life they now support will be replaced by other species better adapted to warmer water.  In the long term, warmer water and changing flow may result in deterioration of aquatic ecosystems.
Ocean acidification is projected to continue, resulting in the reduced biological production of marine calcifiers, including corals.
Climate change is likely to affect U.S. energy use and energy production and physical and institutional infrastructures.  It will also likely interact with and possibly exacerbate ongoing environmental change and environmental pressures in settlements, particularly in Alaska where indigenous communities are facing major environmental and cultural impacts. The U.S. energy sector, which relies heavily on water for hydropower and cooling capacity, may be adversely impacted by changes to water supply and quality in reservoirs and other water bodies. Water infrastructure, including drinking water and wastewater treatment plants, and sewer and stormwater management systems, will be at greater risk of flooding, sea level rise and storm surge, low flows, and other factors that could impair performance.
Disturbances such as wildfires and insect outbreaks are increasing in the United States and are likely to intensify in a warmer future with warmer winters, drier soils, and longer growing seasons.  Although recent climate trends have increased vegetation growth, continuing increases in disturbances are likely to limit carbon storage, facilitate invasive species, and disrupt ecosystem services.
Over the 21[st] century, changes in climate will cause species to shift north and to higher elevations and fundamentally rearrange U.S. ecosystems.  Differential capacities for range shifts and constraints from development, habitat fragmentation, invasive species, and broken ecological connections will alter ecosystem structure, function, and services.
Present and Projected U.S. Regional Climate Change Impacts
Climate change impacts will vary in nature and magnitude across different regions of the United States.
Sustained high summer temperatures, heat waves, and declining air quality are projected in the Northeast, Southeast, Southwest, and Midwest.  Projected climate change would continue to cause loss of sea ice, glacier retreat, permafrost thawing, and coastal erosion in Alaska.
Reduced snowpack, earlier spring snowmelt, and increased likelihood of seasonal summer droughts are projected in the Northeast, Northwest, and Alaska.  More severe, sustained droughts and water scarcity are projected in the Southeast, Great Plains, and Southwest.
The Southeast, Midwest, and Northwest in particular are expected to be impacted by an increased frequency of heavy downpours and greater flood risk.
Ecosystems of the Southeast, Midwest, Great Plains, Southwest, Northwest, and Alaska are expected to experience altered distribution of native species (including local extinctions), more frequent and intense wildfires, and an increase in insect pest outbreaks and invasive species.
Sea level rise is expected to increase storm surge height and strength, flooding, erosion, and wetland loss along the coasts, particularly in the Northeast, Southeast, and islands.
Warmer water temperatures and ocean acidification are expected to degrade important aquatic resources of islands and coasts such as coral reefs and fisheries.
A longer growing season, low levels of warming, and fertilization effects of carbon dioxide may benefit certain crop species and forests, particularly in the Northeast and Alaska.  Projected summer rainfall increases in the Pacific islands may augment limited freshwater supplies.  Cold-related mortality is projected to decrease, especially in the Southeast.  In the Midwest in particular, heating oil demand and snow-related traffic accidents are expected to decrease.
Climate change impacts in certain regions of the world may exacerbate problems that raise humanitarian, trade, and national security issues for the United States.  The IPCC identifies the most vulnerable world regions as the Arctic, because of the effects of high rates of projected warming on natural systems; Africa, especially the sub-Saharan region, because of current low adaptive capacity as well as climate change; small islands, due to high exposure of population and infrastructure to risk of sea level rise and increased storm surge; and Asian mega-deltas, such as the Ganges-Brahmaputra and the Zhujiang, due to large populations and high exposure to sea level rise, storm surge and river flooding.  Climate change has been described as a potential threat multiplier with regard to national security issues.
Changes in Atmospheric CO2 Concentrations, Global Mean Temperature, Sea Level Rise, and Ocean pH Associated with the Program's GHG Emissions Reductions
EPA examined the reductions in CO2 and other GHGs associated with this rulemaking and analyzed the projected effects on atmospheric CO2 concentrations, global mean surface temperature, sea level rise, and ocean pH which are common variables used as indicators of climate change. The analysis projects that the preferred alternative of this program will reduce atmospheric concentrations of CO2, global climate warming and sea level rise relative to the reference case. Although the projected reductions and improvements are small in comparison to the total projected climate change, they are quantifiable, directionally consistent, and will contribute to reducing the risks associated with climate change.
EPA determines that the projected reductions in atmospheric CO2, global mean temperature and sea level rise are meaningful in the context of this final action.  In addition, EPA has conducted an analysis to evaluate the projected changes in ocean pH in the context of the changes in emissions from this rulemaking.  The results of the analysis demonstrate that relative to the reference case, projected atmospheric CO2 concentrations are estimated to be reduced by 0.691 to 0.787 part per million by volume (ppmv), global mean temperature is estimated to be reduced by 0.0017 to 0.0042°C, and sea-level rise is projected to be reduced by approximately 0.017-0.040 cm by 2100, based on a range of climate sensitivities. The analysis also demonstrates that ocean pH will increase by 0.0003 pH units by 2100 relative to the reference case.
Estimated Projected Reductions in Atmospheric CO2 Concentration, Global Mean Surface Temperatures, Sea Level Rise, and Ocean pH
EPA estimated changes in the atmospheric CO2 concentration, global mean temperature, and sea level rise out to 2100 resulting from the emissions reductions in this rulemaking using the GCAM (Global Change Assessment Model, formerly MiniCAM), integrated assessment model coupled with the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC, version 5.3v2). GCAM 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 projected change in these variables over time. Given the magnitude of the estimated emissions reductions associated with this action, a simple climate model such as MAGICC is reasonable for estimating the atmospheric and climate response.  This widely-used, peer reviewed modeling tool was also used to project temperature and sea level rise under different emissions scenarios in the Third and Fourth Assessments of the IPCC.
The integrated impact of the following pollutant and greenhouse gas emissions changes are considered: CO2, CH4, N2O, HFC-134a, NOX, CO2 and SO2, and volatile organic compounds (VOC).  For CO2, CH4, HFC-134a, and N2O an annual time-series of (upstream + downstream) emissions reductions estimated from the rulemaking were input directly. The GHG emissions reductions, from Section VI.C, were applied as net reductions to a global reference case (or baseline) emissions scenario in GCAM to generate an emissions scenario specific to this rulemaking.  For CO, VOCs, SO2, and NOX, emissions reductions were estimated for 2018, 2030, and 2050 (provided in Section VII.A). EPA then linearly scaled emissions reductions for these gases between a zero input value in 2013 and the value supplied for 2018 to produce the reductions for 2014-2018.  A similar scaling was used for 2019-2029 and 2031-2050.  The emissions reductions past 2050 for all gases were scaled with total U.S. road transportation fuel consumption from the GCAM reference scenario.  Road transport fuel consumption past 2050 does not change significantly and thus emissions reductions remain relatively constant from 2050 through 2100.  Specific details about the GCAM reference case scenario can be found in Chapter 8.4 of the RIA that accompanies this preamble.
MAGICC calculates the forcing response at the global scale from changes in atmospheric concentrations of CO2, CH4, N2O, HFCs, and tropospheric ozone.  It also includes the effects of temperature changes on stratospheric ozone and the effects of CH4 emissions on stratospheric water vapor. Changes in CH4, NOx, VOC, and CO emissions affect both O3 concentrations and CH4 concentrations. MAGICC includes the relative climate forcing effects of changes in sulfate concentrations due to changing SO2 emissions, including both the direct effect of sulfate particles and the indirect effects related to cloud interactions. However, MAGICC does not calculate the effect of changes in concentrations of other aerosols such as nitrates, black carbon, or organic carbon, making the assumption that the sulfate cooling effect is a proxy for the sum of all the aerosol effects. Therefore, the climate effects of changes in PM2.5 emissions and precursors (besides SO2) which are presented in the RIA Chapter 5 were not included in the calculations in this chapter. MAGICC also calculates all climate effects at the global scale. This global scale captures the climate effects of the long-lived, well-mixed greenhouse gases, but does not address the fact that short-lived climate forcers such as aerosols and ozone can have effects that vary with location and timing of emissions. Black carbon in particular is known to cause a positive forcing or warming effect by absorbing incoming solar radiation, but there are uncertainties about the magnitude of that warming effect and the interaction of black carbon (and other co-emitted aerosol species) with clouds.  While black carbon is likely to be an important contributor to climate change, it would be premature to include quantification of black carbon climate impacts in an analysis of the final standards at this time.

Changes in atmospheric CO2 concentration, global mean temperature, and sea level rise for both the reference case and the emissions scenarios associated with this action were computed using MAGICC. To calculate the reductions in the atmospheric CO2 concentrations as well as in temperature and sea level resulting from this action, the output from the policy scenario associated with the preferred approach of this action was subtracted from an existing Global Change Assessment Model (GCAM, formerly MiniCAM) reference emission scenario. To capture some key uncertainties in the climate system with the MAGICC model, changes in atmospheric CO2, global mean temperature and sea level rise were projected across the most current IPCC range of climate sensitivities, from 1.5°C to 6.0°C.  This range reflects the uncertainty for equilibrium climate sensitivity for how much global mean temperature would rise if the concentration of carbon dioxide in the atmosphere were to double. The information for this range come from constraints from past climate change on various time scales, and the spread of results for climate sensitivity from ensembles of models.  Details about this modeling analysis can be found in the RIA Chapter 8.4.
The results of this modeling, summarized in Table VI-8, show small, but quantifiable, reductions in atmospheric CO2 concentrations, projected global mean temperature and sea level resulting from this action, across all climate sensitivities. As a result of the emission reductions from the final standards for this action, relative to the reference case the atmospheric CO2 concentration is projected to be reduced by 0.691-0.787 ppmv, the global mean temperature is projected to be reduced by approximately 0.0017-0.0042°C by 2100, and global mean sea level rise is projected to be reduced by approximately 0.017-0.040 cm by 2100.  The range of reductions in global mean temperature and sea level rise is larger than that for CO2 concentrations because CO2 concentrations are only weakly coupled to climate sensitivity through the dependence on temperature of the rate of ocean absorption of CO2, whereas the magnitude of temperature change response to CO2 changes (and therefore sea level rise) is more tightly coupled to climate sensitivity in the MAGICC model.
Table VI-8: Impact of GHG Emissions Reductions on Projected Changes in Global Climate Associated with the Final Rulemaking (Based on a range of climate sensitivities from 1.5-6°C)
Variable
Units
Year
Projected Change
Atmospheric CO2 Concentration
ppmv
2100
 -0.691 to -0.787
Global Mean Surface Temperature
º C
2100
-0.0017 to -0.0042
Sea Level Rise
cm
2100
-0.017 to -0.040
Ocean pH
pH units
2100
0.0003[a]
  Note:
  [a] The value for projected change in ocean pH is based on a climate sensitivity of 3.0.
The projected reductions are small relative to the change in temperature (1.8  -  4.8 ºC), sea level rise (27  -  51 cm), and ocean acidity (-0.30 pH units) from 1990 to 2100 from the MAGICC simulations for the GCAM reference case. However, this is to be expected given the magnitude of emissions reductions expected from the program in the context of global emissions. This uncertainty range does not include the effects of uncertainty in future emissions. It should also be noted that the calculations in MAGICC do not include the possible effects of accelerated ice flow in Greenland and/or Antarctica: the recent NRC report estimated a likely sea level increase for the A1B SRES scenario of 0.5 to 1.0 meters.  Further discussion of EPA's modeling analysis is found in the RIA, Chapter 8.
EPA used the Program CO2SYS, version 1.05 to estimate projected changes in ocean pH for tropical waters based on the atmospheric CO2 concentration change (reduction) resulting from this action.  The program performs calculations relating parameters of the CO2 system in seawater. EPA used the program to calculate ocean pH as a function of atmospheric CO2 concentrations, among other specified input conditions. Based on the projected atmospheric CO2 concentration reductions resulting from this action, the program calculates an increase in ocean pH of 0.0003 pH units in 2100 relative to the reference case (compared to a decrease of 0.3 pH units from 1990 to 2100 in the reference case). Thus, this analysis indicates the projected decrease in atmospheric CO2 concentrations from the program will result in an increase in ocean pH.  For additional validation, results were generated using different known constants from the literature.  A comprehensive discussion of the modeling analysis associated with ocean pH is provided in the RIA, Chapter 8.
Program's Effect on Climate
As a substantial portion of CO2 emitted into the atmosphere is not removed by natural processes for millennia, each unit of CO2 not emitted into the atmosphere avoids essentially permanent climate change on centennial time scales.  Reductions in emissions in the near-term are important in determining long-term climate stabilization and associated impacts experienced not just over the next decades but in the coming centuries and millennia.  Though the magnitude of the avoided climate change projected here is small in comparison to the total projected changes, these reductions represent a reduction in the adverse risks associated with climate change (though these risks were not formally estimated for this action) across a range of equilibrium climate sensitivities.
EPA's analysis of the program's impact on global climate conditions is intended to quantify these potential reductions using the best available science.  EPA's modeling results show repeatable, consistent reductions relative to the reference case in changes of CO2 concentration, temperature, sea-level rise, and ocean pH over the next century.

How Will This Final Action Impact Non-GHG Emissions and Their Associated Effects?
Emissions Inventory Impacts
Upstream Impacts of the Program
Increasing efficiency in heavy-duty vehicles will result in reduced fuel demand and therefore reductions in the emissions associated with all processes involved in getting petroleum to the pump.  These projected upstream emission impacts on criteria pollutants are summarized in Table VII-1.  Table VII-2 shows the corresponding projected impacts on upstream air toxic emissions in 2030.
Table VII-1: Overall estimated upstream impacts on criteria pollutants for calendar years 2018, 2030, and 2050 (short tons)
Calendar Year
NOX
VOC
CO
PM2.5
2018
-6,475
-1,765
-2,217
-971
2030
-10,083
-4,430
-3,367
-1,394
2050
-14,243
-6,379
-4,785
-1,998

Table VII-2: Overall estimated upstream impacts on air toxics for calendar years 2018, 2030, and 2050 (short tons)
Calendar Year
Benzene
1,3-butadiene
Formaldehyde
Acetaldehyde
Acrolein
2018
-12
-0.6
-12
-1
-0.2
2030
-20
-0.9
-26
-3
-0.5
2050
-28
-1.2
-35
-5
-0.6

To project these impacts, EPA estimated the impact of reduced petroleum volumes on the extraction and transportation of crude oil as well as the production and distribution of finished gasoline and diesel. For the purpose of assessing domestic-only emission reductions it was necessary to estimate the fraction of fuel savings attributable to domestic finished gasoline and diesel, and of this fuel what fraction is produced from domestic crude. For this analysis EPA estimated that 50 percent of fuel savings is attributable to domestic finished gasoline and diesel and that 90 percent of this gasoline and diesel originated from imported crude. Emission factors for most upstream emission sources are based on the GREET1.8 model, developed by DOE's Argonne National Laboratory but in some cases the GREET values were modified or updated by EPA to be consistent with the National Emission Inventory. These updates are consistent with those used for the upstream analysis included in the Light-Duty GHG rulemaking. More information on the development of the emission factors used in this analysis can be found in RIA Chapter 5.
Downstream Impacts of the Program
While these final rules do not regulate non-GHG pollutants, EPA expects reductions in downstream emissions of most non-GHG pollutants.  These pollutants include NOX, SO2, VOC, CO, and PM.  The primary reason for this is the improvements in road load (aerodynamics and tire rolling resistance) under the program.  Another reason is that emissions from certain pollutants (e.g., SO2) are proportional to fuel consumption.  For vehicle types not affected by road load improvements, non-GHG emissions may increase very slightly due to VMT rebound.  EPA also anticipates the use of APUs in combination tractors for GHG reduction purposes during extended idling.  These units exhibit different non-GHG emissions characteristics compared to the on-road engines they would replace during extended idling.  EPA used MOVES to determine non-GHG emissions inventories for baseline and control cases.  Further information about the MOVES analysis is available in Section VI and RIA Chapter 5.  The improvements in road load, use of APUs, and VMT rebound were included in the MOVES runs and post-processing.  Table VII-3 summarizes the downstream criteria pollutant impacts of this program. Most of the impacts shown are through projected increased APU use.  Because APUs are required to meet much less stringent PM2.5 standards than on-road engines, the projected widespread use of APUs leads to higher PM2.5.  Table VII-4 summarizes the downstream air toxics impacts of this program.
Table VII-3: Overall Estimated Downstream Impacts on Criteria Pollutants (short tons)
Calendar Year
Downstream NOX
Downstream VOC
Downstream SO2
Downstream CO
Downstream PM2.5 [a]
2018
-107,273
-12,956

-25,629
808
2030
-235,400
-25,516

-52,242
1,760
2050
-326,975
-35,147

-72,099
2,456
Note:
[a] Positive number means emissions would increase from baseline to control case. PM2.5 from tire wear and brake wear is included.

Table VII-4: Overall Estimated Downstream Impacts on Air Toxics (short tons)
Calendar Year
Benzene
1,3-butadiene
Formaldehyde
Acetaldehyde
Acrolein
2018
-158
-0.3
-2,853
-871
-120
2030
-341
0.4
-6,255
-1,908
-263
2050
-472
0.8
-8,689
-2,650
-365

Total Impacts of the Program
    As shown in Table VII-5 and Table VII-6, the agencies estimate that this program would result in reductions of NOX, VOC, CO, PM, and air toxics.  For NOX, VOC, and CO, much of the net reductions are realized through the use of APUs, which emit these pollutants at a lower rate than on-road engines during extended idle operation.  Additional reductions are achieved in all pollutants through reduced road load (improved aerodynamics and tire rolling resistance), which reduces the amount of work required to travel a given distance.  For SOX, downstream emissions are roughly proportional to fuel consumption; therefore a decrease is seen in both upstream and downstream sources. The downstream increase in PM2.5 due to APU use is mostly negated by upstream PM2.5 reductions, though our calculations show a slight net increase in 2030 and 2050.
Table VII-5: Overall Estimated Total Impacts (Upstream Plus Downstream) on Criteria Pollutants Results are shown in both short tons and percent change from baseline to control case.
CY
                                      NOX
                                      VOC
                                      SO2
                                      CO
                                     PM2.5

short tons
%
short tons
%
short tons
%
short tons
%
short tons
%
2018
-113,748
-6.2
-14,721
-5.6

-27,846
-1.0
-163
-0.2
2030
-245,482
-21.0
-29,945
-16.0

-55,610
-2.1
366
1.1
2050
-341,218
-23.7
-41,526
-18.3

-76,883
-2.2
457
1.1

Table VII-6: Overall Estimated Total Impacts (Upstream Plus Downstream) Impacts on Air Toxics
CY
Benzene
1,3-butadiene
Formaldehyde
Acetaldehyde
Acrolein

short tons
%
short tons
%
short tons
%
short tons
%
short tons
%
2018
-170
-4.8
-0.9
-0.1
-2,865
-18.3
-873
-13.9
-120.0
-12.4
2030
-360
-15.0
-0.5
-0.1
-6,282
-46.2
-1,912
-40.2
-263.0
-40.0
2050
-500
-17.4
-0.4
-0.1
-8,725
-49.5
-2,655
-44.2
-365.4
-44.5

Health Effects of Non-GHG Pollutants
In this section we discuss health effects associated with exposure to some of the criteria and air toxic pollutants impacted by the final heavy-duty vehicle standards.
Particulate Matter
Background
Particulate matter is a generic term for 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.  Since 1987, EPA has delineated that subset of inhalable particles small enough to penetrate to the thoracic region (including the tracheobronchial and alveolar regions) of the respiratory tract (referred to as thoracic particles). Current National Ambient Air Quality Standards (NAAQS) use PM2.5 as the indicator for fine particles (with PM2.5 referring to particles with a nominal mean aerodynamic diameter less than or equal to 2.5 um), and use PM10 as the indicator for purposes of regulating the coarse fraction of PM10 (referred to as thoracic coarse particles or coarse-fraction particles; generally including particles with a nominal mean aerodynamic diameter greater than 2.5 um and less than or equal to 10 um, or PM10-2.5).  Ultrafine particles are a subset of fine particles, generally less than 100 nanometers (0.1 μm) in aerodynamic diameter.
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.
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 EPA's Integrated Science Assessment for Particulate Matter (ISA).  Further discussion of health effects associated with PM can also be found in the RIA for this final action.  The ISA summarizes evidence associated with PM2.5, PM10-2.5, and ultrafine particles.
The ISA concludes that health effects associated with short-term exposures (hours to days) to ambient PM2.5 include mortality, cardiovascular effects, such as altered vasomotor function and hospital admissions and emergency department visits for ischemic heart disease and congestive heart failure, and respiratory effects, such as exacerbation of asthma symptoms in children and hospital admissions and emergency department visits for chronic obstructive pulmonary disease and respiratory infections.  The ISA notes that long-term exposure to PM2.5 (months to years) is associated with the development/progression of cardiovascular disease, premature mortality, and respiratory effects, including reduced lung function growth, increased respiratory symptoms, and asthma development.  The ISA concludes that the currently available scientific evidence from epidemiologic, controlled human exposure, and toxicological studies supports a causal association between short- and long-term exposures to PM2.5 and cardiovascular effects and mortality.  Furthermore, the ISA concludes that the collective evidence supports likely causal associations between short- and long-term PM2.5 exposures and respiratory effects.  The ISA also concludes that the scientific evidence is suggestive of a causal association for reproductive and developmental effects and cancer, mutagenicity, and genotoxicity and long-term exposure to PM2.5.
For PM10-2.5, the ISA concludes that the current evidence is suggestive of a causal relationship between short-term exposures and cardiovascular effects, such as hospitalization for ischemic heart disease.  There is also suggestive evidence of a causal relationship between short-term PM10-2.5 exposure and mortality and respiratory effects.  Data are inadequate to draw conclusions regarding the health effects associated with long-term exposure to PM10-2.5.
For ultrafine particles, the ISA concludes that there is suggestive evidence of a causal relationship between short-term exposures and cardiovascular effects, such as changes in heart rhythm and blood vessel function.  It also concludes that there is suggestive evidence of association between short-term exposure to ultrafine particles and respiratory effects. Data are inadequate to draw conclusions regarding the health effects associated with long-term exposure to ultrafine particles.
Ozone
Background
Ground-level ozone pollution is typically formed by the reaction of VOC and NOX in the lower atmosphere in the presence of 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.  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.
Health Effects of Ozone
The health and welfare effects of ozone are well documented and are assessed in EPA's 2006 Air Quality Criteria Document and 2007 Staff Paper.[,]  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 of particular concern.  Ozone can irritate the respiratory system, causing coughing, throat irritation, and breathing discomfort.  Ozone can reduce lung function and cause pulmonary inflammation in healthy individuals.  Ozone can also aggravate asthma, leading to more asthma attacks that require medical attention and/or the use of additional medication.  Thus, ambient ozone may cause both healthy and asthmatic individuals to limit their outdoor activities.  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 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.  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.  The respiratory effects observed in controlled human exposure studies and animal studies are coherent with the evidence from epidemiologic studies supporting 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 suggestive evidence of a contribution of ozone to cardiovascular-related morbidity and non-accidental and cardiopulmonary mortality.
Nitrogen Oxides and Sulfur Oxides
Background
Nitrogen dioxide (NO2) is a member of the NOX family of gases.  Most NO2 is formed in the air through the oxidation of nitric oxide (NO) emitted when fuel is burned at a high temperature.  SO2, a member of the sulfur oxide (SOX) family of gases, is formed from burning fuels containing sulfur (e.g., coal or oil derived), extracting gasoline from oil, or extracting metals from ore.
SO2 and NO2 can dissolve in water droplets and further oxidize to form sulfuric and nitric acid which react with ammonia to form sulfates and nitrates, both of which are important components of ambient PM.  The health effects of ambient PM are discussed in Section VII. B. (1) (b) of this preamble.  NOX and NMHC are the two major precursors of ozone.  The health effects of ozone are covered in Section VII. B. (2) (b).
Health Effects of NO2
Information on the health effects of NO2 can be found in the EPA Integrated Science Assessment (ISA) for Nitrogen Oxides.  The EPA has concluded that the findings of epidemiologic, controlled human exposure, and animal toxicological studies provide evidence that is sufficient to infer a likely causal relationship between respiratory effects and short-term NO2 exposure. The ISA concludes that the strongest evidence for such a relationship comes from epidemiologic studies of respiratory effects including symptoms, emergency department visits, and hospital admissions.  The ISA also draws two broad conclusions regarding airway responsiveness following NO2 exposure.  First, the ISA concludes that NO2 exposure may enhance the sensitivity to allergen-induced decrements in lung function and increase the allergen-induced airway inflammatory response following 30-minute exposures of asthmatics to NO2 concentrations as low as 0.26 ppm.  In addition, small but significant increases in non-specific airway hyperresponsiveness were reported following 1-hour exposures of asthmatics to 0.1 ppm NO2.  Second, exposure to NO2 has been found to enhance the inherent responsiveness of the airway to subsequent nonspecific challenges in controlled human exposure studies of asthmatic subjects.  Enhanced airway responsiveness could have important clinical implications for asthmatics since transient increases in airway responsiveness following NO2 exposure have the potential to increase symptoms and worsen asthma control.  Together, the epidemiologic and experimental data sets form a plausible, consistent, and coherent description of a relationship between NO2 exposures and an array of adverse health effects that range from the onset of respiratory symptoms to hospital admission.
Although the weight of evidence supporting a causal relationship is somewhat less certain than that associated with respiratory morbidity, NO2 has also been linked to other health endpoints.  These include all-cause (nonaccidental) mortality, hospital admissions or emergency department visits for cardiovascular disease, and decrements in lung function growth associated with chronic exposure.
Health Effects of SO2
Information on the health effects of SO2 can be found in the EPA Integrated Science Assessment for Sulfur Oxides.  SO2 has long been known to cause adverse respiratory health effects, particularly among individuals with asthma.  Other potentially sensitive groups include children and the elderly. During periods of elevated ventilation, asthmatics may experience symptomatic bronchoconstriction within minutes of exposure.  Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the EPA has concluded that there is a causal relationship between respiratory health effects and short-term exposure to SO2.  Separately, based on an evaluation of the epidemiologic evidence of associations between short-term exposure to SO2 and mortality, the EPA has concluded that the overall evidence is suggestive of a causal relationship between short-term exposure to SO2 and mortality.
Carbon Monoxide
Information on the health effects of CO can be found in the EPA Integrated Science Assessment (ISA) for Carbon Monoxide.  The ISA concludes that ambient concentrations of CO are associated with a number of adverse health effects.  This section provides a summary of the health effects associated with exposure to ambient concentrations of CO.
Human clinical studies of subjects with coronary artery disease show a decrease in the time to onset of exercise-induced angina (chest pain) and electrocardiogram changes following CO exposure.  In addition, epidemiologic studies show associations between short-term CO exposure and cardiovascular morbidity, particularly increased emergency room visits and hospital admissions for coronary heart disease (including ischemic heart disease, myocardial infarction, and angina).  Some epidemiologic evidence is also available for increased hospital admissions and emergency room visits for congestive heart failure and cardiovascular disease as a whole.  The ISA concludes that a causal relationship is likely to exist between short-term exposures to CO and cardiovascular morbidity.  It also concludes that available data are inadequate to conclude that a causal relationship exists between long-term exposures to CO and cardiovascular morbidity.
Animal studies show various neurological effects with in-utero CO exposure.  Controlled human exposure studies report inconsistent neural and behavioral effects following low-level CO exposures.  The ISA concludes the evidence is suggestive of a causal relationship with both short- and long-term exposure to CO and central nervous system effects.
A number of epidemiologic and animal toxicological studies cited in the ISA have evaluated associations between CO exposure and birth outcomes such as preterm birth or cardiac birth defects.  The epidemiologic studies provide limited evidence of a CO-induced effect on preterm births and birth defects, with weak evidence for a decrease in birth weight.  Animal toxicological studies have found associations between perinatal CO exposure and decrements in birth weight, as well as other developmental outcomes.  The ISA concludes these studies are suggestive of a causal relationship between long-term exposures to CO and developmental effects and birth outcomes.
Epidemiologic studies provide evidence of effects on respiratory morbidity such as changes in pulmonary function, respiratory symptoms, and hospital admissions associated with ambient CO concentrations.  A limited number of epidemiologic studies considered copollutants such as ozone, SO2, and PM in two-pollutant models and found that CO risk estimates were generally robust, although this limited evidence makes it difficult to disentangle effects attributed to CO itself from those of the larger complex air pollution mixture.  Controlled human exposure studies have not extensively evaluated the effect of CO on respiratory morbidity.  Animal studies at levels of 50-100 ppm CO show preliminary evidence of altered pulmonary vascular remodeling and oxidative injury.  The ISA concludes that the evidence is suggestive of a causal relationship between short-term CO exposure and respiratory morbidity, and inadequate to conclude that a causal relationship exists between long-term exposure and respiratory morbidity.
Finally, the ISA concludes that the epidemiologic evidence is suggestive of a causal relationship between short-term exposures to CO and mortality.  Epidemiologic studies provide evidence of an association between short-term exposure to CO and mortality, but limited evidence is available to evaluate cause-specific mortality outcomes associated with CO exposure.  In addition, the attenuation of CO risk estimates which was often observed in copollutant models contributes to the uncertainty as to whether CO is acting alone or as an indicator for other combustion-related pollutants. The ISA also concludes that there is not likely to be a causal relationship between relevant long-term exposures to CO and mortality.
Air Toxics
Heavy-duty vehicle emissions contribute to ambient levels of air toxics known or suspected as human or animal carcinogens, or that have noncancer health effects.  The population experiences an elevated risk of cancer and other noncancer health effects from exposure to the class of pollutants known collectively as "air toxics."  These compounds include, but are not limited to, benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, diesel particulate matter and exhaust organic gases, polycyclic organic matter, and naphthalene.  These compounds were identified as national or regional risk drivers or contributors in the 2005 National-scale Air Toxics Assessment and have significant inventory contributions from mobile sources.
Diesel Exhaust
Heavy-duty diesel engines emit diesel exhaust, a complex mixture composed of carbon dioxide, oxygen, nitrogen, water vapor, carbon monoxide, nitrogen compounds, sulfur compounds and numerous low-molecular-weight hydrocarbons.  A number of these gaseous hydrocarbon components are individually known to be toxic, including aldehydes, benzene and 1,3-butadiene.  The diesel particulate matter present in diesel exhaust consists mostly of fine particles (< 2.5 um), including a significant fraction of ultrafine particles (< 0.1 um).  These particles have a large surface area which makes them an excellent medium for adsorbing organics and their small size makes them highly respirable. Many of the organic compounds present in the gases and on the particles, such as polycyclic organic matter, are individually known to have mutagenic and carcinogenic properties.
Diesel exhaust varies significantly in chemical composition and particle sizes between different engine types (heavy-duty, light-duty), engine operating conditions (idle, accelerate, decelerate), and fuel formulations (high/low sulfur fuel).  Also, there are emissions differences between on-road and nonroad engines because the nonroad engines are generally of older technology.  After being emitted in the engine exhaust, diesel exhaust undergoes dilution as well as chemical and physical changes in the atmosphere.  The lifetime for some of the compounds present in diesel exhaust ranges from hours to days.
Diesel Exhaust: Potential Cancer Effects
In EPA's 2002 Diesel Health Assessment Document (Diesel HAD), exposure to diesel exhaust was classified as likely to be carcinogenic to humans by inhalation from environmental exposures, in accordance with the revised draft 1996/1999 EPA cancer guidelines. A number of other agencies (National Institute for Occupational Safety and Health, the International Agency for Research on Cancer, the World Health Organization, California EPA, and the U.S. Department of Health and Human Services) have made similar classifications.  However, EPA also concluded in the Diesel HAD that it is not possible currently to calculate a cancer unit risk for diesel exhaust due to a variety of factors that limit the current studies, such as limited quantitative exposure histories in occupational groups investigated for lung cancer.
For the Diesel HAD, EPA reviewed 22 epidemiologic studies on the subject of the carcinogenicity of workers exposed to diesel exhaust in various occupations, finding increased lung cancer risk, although not always statistically significant, in 8 out of 10 cohort studies and 10 out of 12 case-control studies within several industries.  Relative risk for lung cancer associated with exposure ranged from 1.2 to 1.5, although a few studies show relative risks as high as 2.6.  Additionally, the Diesel HAD also relied on two independent meta-analyses, which examined 23 and 30 occupational studies respectively, which found statistically significant increases in smoking-adjusted relative lung cancer risk associated with exposure to diesel exhaust of 1.33 to 1.47.  These meta-analyses demonstrate the effect of pooling many studies and in this case show the positive relationship between diesel exhaust exposure and lung cancer across a variety of diesel exhaust-exposed occupations.[,]
In the absence of a cancer unit risk, the Diesel HAD sought to provide additional insight into the significance of the diesel exhaust-cancer hazard by estimating possible ranges of risk that might be present in the population.  An exploratory analysis was used to characterize a possible risk range by comparing a typical environmental exposure level for highway diesel sources to a selected range of occupational exposure levels.  The occupationally observed risks were then proportionally scaled according to the exposure ratios to obtain an estimate of the possible environmental risk.  A number of calculations are needed to accomplish this, and these can be seen in the EPA Diesel HAD.  The outcome was that environmental risks from diesel exhaust exposure could range from a low of 10[-4] to 10[-5] to as high as 10[-3], reflecting the range of occupational exposures that could be associated with the relative and absolute risk levels observed in the occupational studies.  Because of uncertainties, the analysis acknowledged that the risks could be lower than 10[-4] or 10[-5], and a zero risk from diesel exhaust exposure was not ruled out.
Diesel Exhaust: Other Health Effects
Noncancer health effects of acute and chronic exposure to diesel exhaust emissions are also of concern to the EPA.  EPA derived a diesel exhaust reference concentration (RfC) from consideration of four well-conducted chronic rat inhalation studies showing adverse pulmonary effects.,,,  The RfC is 5 ug/m[3] for diesel exhaust as measured by diesel particulate matter.  This RfC does not consider allergenic effects such as those associated with asthma or immunologic effects.  There is growing evidence, discussed in the Diesel HAD, that exposure to diesel exhaust can exacerbate these effects, but the exposure-response data are presently lacking to derive an RfC.  The EPA Diesel HAD states, "With [diesel particulate matter] being a ubiquitous component of ambient PM, there is an uncertainty about the adequacy of the existing [diesel exhaust] noncancer database to identify all of the pertinent [diesel exhaust]-caused noncancer health hazards." (p. 9-19).  The Diesel HAD concludes "that acute exposure to [diesel exhaust] has been associated with irritation of the eye, nose, and throat, respiratory symptoms (cough and phlegm), and neurophysiological symptoms such as headache, lightheadedness, nausea, vomiting, and numbness or tingling of the extremities."
Ambient PM2.5 Levels and Exposure to Diesel Exhaust PM
The Diesel HAD also briefly summarizes health effects associated with ambient PM and discusses the EPA's annual PM2.5 NAAQS of 15 ug/m[3].  There is a much more extensive body of human data showing a wide spectrum of adverse health effects associated with exposure to ambient PM, of which diesel exhaust is an important component.  The PM2.5 NAAQS is designed to provide protection from the noncancer and premature mortality effects of PM2.5 as a whole.
Diesel Exhaust PM Exposures
Exposure of people to diesel exhaust depends on their various activities, the time spent in those activities, the locations where these activities occur, and the levels of diesel exhaust pollutants in those locations.  The major difference between ambient levels of diesel particulate and exposure levels for diesel particulate is that exposure accounts for a person moving from location to location, proximity to the emission source, and whether the exposure occurs in an enclosed environment.
Occupational Exposures
Occupational exposures to diesel exhaust from mobile sources can be several orders of magnitude greater than typical exposures in the non-occupationally exposed population.
Over the years, diesel particulate exposures have been measured for a number of occupational groups.  A wide range of exposures have been reported, from 2 ug/m3 to 1,280 ug/m3, for a variety of occupations.  As discussed in the Diesel HAD, the National Institute of Occupational Safety and Health has estimated a total of 1,400,000 workers are occupationally exposed to diesel exhaust from on-road and nonroad vehicles.
Elevated Concentrations and Ambient Exposures in Mobile Source-Impacted Areas
Regions immediately downwind of highways or truck stops may experience elevated ambient concentrations of directly-emitted PM2.5 from diesel engines.  Due to the unique nature of highways and truck stops, emissions from a large number of diesel engines are concentrated in a small area.  Studies near roadways with high truck traffic indicate higher concentrations of components of diesel PM than other locations.[,][,]  High ambient particle concentrations have also been reported near trucking terminals, truck stops, and bus garages.[,][,]  Additional discussion of exposure and health effects associated with traffic is included below in Section VII. B. (5) (j).
Benzene
The EPA's Integrated Risk Information System (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 genetic changes in both humans and animals and increased proliferation of bone marrow cells in mice.,,  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.,
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.,  The most sensitive noncancer effect observed in humans, based on current data, is the depression of the absolute lymphocyte count in blood.,   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.,,,  EPA's IRIS program has not yet evaluated these new data.
1,3-Butadiene
EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation.,  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.,  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.
Formaldehyde
Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on evidence in humans and in rats, mice, hamsters, and monkeys.  EPA is currently reviewing recently published epidemiological data.  For instance, research conducted by the National Cancer Institute found an increased risk of nasopharyngeal cancer and lymphohematopoietic malignancies such as leukemia among workers exposed to formaldehyde.,   In an analysis of the lymphohematopoietic cancer mortality from an extended follow-up of these workers, the National Cancer Institute confirmed an association between lymphohematopoietic cancer risk and peak exposures.  A recent National Institute of Occupational Safety and Health study of garment workers also found increased risk of death due to leukemia among workers exposed to formaldehyde.  Extended follow-up of a cohort of British chemical workers did not find evidence of an increase in nasopharyngeal or lymphohematopoietic cancers, but a continuing statistically significant excess in lung cancers was reported.  Recently, the IARC re-classified formaldehyde as a human carcinogen (Group 1).
Formaldehyde exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of the eyes), nose and throat.  Effects from repeated exposure in humans include respiratory tract irritation, chronic bronchitis and nasal epithelial lesions such as metaplasia and loss of cilia.  Animal studies suggest that formaldehyde may also cause airway inflammation  -  including eosinophil infiltration into the airways.  There are several studies that suggest that formaldehyde may increase the risk of asthma  -  particularly in the young.[,]
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.  Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. DHHS in the 11[th] Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC.,  EPA is currently conducting a reassessment of cancer risk from inhalation exposure to acetaldehyde.
The primary noncancer effects of exposure to acetaldehyde vapors include irritation of the eyes, skin, and respiratory tract.  In short-term (4 week) rat studies, degeneration of olfactory epithelium was observed at various concentration levels of acetaldehyde exposure.[,]   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.  The agency is currently conducting a reassessment of the health hazards from inhalation exposure to acetaldehyde.
Acrolein
Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure resulting in upper respiratory tract irritation, mucus hypersecretion and congestion.  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.  These data and additional studies regarding acute effects of human exposure to acrolein are summarized in EPA's 2003 IRIS Human Health Assessment for acrolein.  Evidence available from studies in humans indicate that levels as low as 0.09 ppm (0.21 mg/m[3]) for five minutes may elicit subjective complaints of eye irritation with increasing concentrations leading to more extensive eye, nose and respiratory symptoms.  Lesions to the lungs and upper respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein.  Acute exposure effects in animal studies report bronchial hyper-responsiveness.  In a recent study, the acute respiratory irritant effects of exposure to 1.1 ppm acrolein were more pronounced in mice with allergic airway disease by comparison to non-diseased mice which also showed decreases in respiratory rate.  Based on these animal data and demonstration of similar effects in humans (e.g., reduction in respiratory rate), 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.
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.  The IARC determined in 1995 that acrolein was not classifiable as to its carcinogenicity in humans.
Polycyclic Organic Matter
The term polycyclic organic matter (POM) defines a broad class of compounds that includes the polycyclic aromatic hydrocarbon compounds (PAHs).  One of these compounds, naphthalene, is discussed separately below.  POM compounds are formed primarily from combustion and are present in the atmosphere in gas and particulate form.  Cancer is the major concern from exposure to POM.  Epidemiologic studies have reported an increase in lung cancer in humans exposed to diesel exhaust, coke oven emissions, roofing tar emissions, and cigarette smoke; all of these mixtures contain POM compounds.  Animal studies have reported respiratory tract tumors from inhalation exposure to benzo[a]pyrene and alimentary tract and liver tumors from oral exposure to benzo[a]pyrene.  EPA has classified seven PAHs (benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, dibenz[a,h]anthracene, and indeno[1,2,3-cd]pyrene) as Group B2, probable human carcinogens.  Recent studies have found that maternal exposures to PAHs in a population of pregnant women were associated with several adverse birth outcomes, including low birth weight and reduced length at birth, as well as impaired cognitive development in preschool children (3 years of age).[,] EPA has not yet evaluated these recent studies.
Naphthalene
Naphthalene is found in small quantities in gasoline and diesel fuels.  Naphthalene emissions have been measured in larger quantities in both gasoline and diesel exhaust compared with evaporative emissions from mobile sources, indicating it is primarily a product of combustion.  EPA released an external review draft of a reassessment of the inhalation carcinogenicity of naphthalene based on a number of recent animal carcinogenicity studies.  The draft reassessment completed external peer review.  Based on external peer review comments received, additional analyses are being undertaken.  This external review draft does not represent official agency opinion and was released solely for the purposes of external peer review and public comment.  The National Toxicology Program listed naphthalene as "reasonably anticipated to be a human carcinogen" in 2004 on the basis of bioassays reporting clear evidence of carcinogenicity in rats and some evidence of carcinogenicity in mice.  California EPA has released a new risk assessment for naphthalene, and the IARC has reevaluated naphthalene and re-classified it as Group 2B: possibly carcinogenic to humans.  Naphthalene also causes a number of chronic non-cancer effects in animals, including abnormal cell changes and growth in respiratory and nasal tissues.
Other Air Toxics
In addition to the compounds described above, other compounds in gaseous hydrocarbon and PM emissions from heavy-duty vehicles will be affected by this final action.  Mobile source air toxic compounds that would potentially be impacted include ethylbenzene, propionaldehyde, toluene, and xylene.  Information regarding the health effects of these compounds can be found in EPA's IRIS database.
Exposure and Health Effects Associated with Traffic
Populations who live, work, or attend school near major roads experience elevated exposure concentrations to a wide range of air pollutants, as well as higher risks for a number of adverse health effects.  While the previous sections of this preamble have focused on the health effects associated with individual criteria pollutants or air toxics, this section discusses the mixture of different exposures near major roadways, rather than the effects of any single pollutant.  As such, this section emphasizes traffic-related air pollution, in general, as the relevant indicator of exposure rather than any particular pollutant.
Concentrations of many traffic-generated air pollutants are elevated for up to 300-500 meters downwind of roads with high traffic volumes.  Numerous sources on roads contribute to elevated roadside concentrations, including exhaust and evaporative emissions, and resuspension of road dust and tire and brake wear.  Concentrations of several criteria and hazardous air pollutants are elevated near major roads.  Furthermore, different semi-volatile organic compounds and chemical components of particulate matter, including elemental carbon, organic material, and trace metals, have been reported at higher concentrations near major roads.
  Populations near major roads experience greater risk of certain adverse health effects.  The Health Effects Institute published a report on the health effects of traffic-related air pollution.  It concluded that evidence is "sufficient to infer the presence of a causal association" between traffic exposure and exacerbation of childhood asthma symptoms.  The HEI report also concludes that the evidence is either "sufficient" or "suggestive but not sufficient" for a causal association between traffic exposure and new childhood asthma cases.  A review of asthma studies by Salam et al. (2008) reaches similar conclusions.  The HEI report also concludes that there is "suggestive" evidence for pulmonary function deficits associated with traffic exposure, but concluded that there is "inadequate and insufficient" evidence for causal associations with respiratory health care utilization, adult-onset asthma, chronic obstructive pulmonary disease symptoms, and allergy.  A review by Holguin (2008) notes that the effects of traffic on asthma may be modified by nutrition status, medication use, and genetic factors.
The HEI report also concludes that evidence is "suggestive" of a causal association between traffic exposure and all-cause and cardiovascular mortality.  There is also evidence of an association between traffic-related air pollutants and cardiovascular effects such as changes in heart rhythm, heart attack, and cardiovascular disease.  The HEI report characterizes this evidence as "suggestive" of a causal association, and an independent epidemiological literature review by Adar and Kaufman (2007) concludes that there is "consistent evidence" linking traffic-related pollution and adverse cardiovascular health outcomes.
Some studies have reported associations between traffic exposure and other health effects, such as birth outcomes (e.g., low birth weight) and childhood cancer.  The HEI report concludes that there is currently "inadequate and insufficient" evidence for a causal association between these effects and traffic exposure.  A review by Raaschou-Nielsen and Reynolds (2006) concluded that evidence of an association between childhood cancer and traffic-related air pollutants is weak, but noted the inability to draw firm conclusions based on limited evidence.
There is a large population in the United States living in close proximity of major roads.  According to the Census Bureau's American Housing Survey for 2007, approximately 20 million residences in the United States, 15.6% of all homes, are located within 300 feet (91 m) of a highway with 4+ lanes, a railroad, or an airport.  Therefore, at current population of approximately 309 million, assuming that population and housing are similarly distributed, there are over 48 million people in the United States living near such sources.  The HEI report also notes that in two North American cities, Los Angeles and Toronto, over 40% of each city's population live within 500 meters of a highway or 100 meters of a major road.  It also notes that about 33% of each city's population resides within 50 meters of major roads.  Together, the evidence suggests that a large U.S. population lives in areas with elevated traffic-related air pollution.
People living near roads are often socioeconomically disadvantaged.  According to the 2007 American Housing Survey, a renter-occupied property is over twice as likely as an owner-occupied property to be located near a highway with 4+ lanes, railroad or airport.  In the same survey, the median household income of rental housing occupants was less than half that of owner-occupants ($28,921/$59,886).  Numerous studies in individual urban areas report higher levels of traffic-related air pollutants in areas with high minority or poor populations.[,][,]
Students may also be exposed in situations where schools are located near major roads.  In a study of nine metropolitan areas across the United States, Appatova et al. (2008) found that on average greater than 33% of schools were located within 400 m of an Interstate, U.S., or state highway, while 12% were located within 100 m.  The study also found that among the metropolitan areas studied, schools in the Eastern United States were more often sited near major roadways than schools in the Western United States.
Demographic studies of students in schools near major roadways suggest that this population is more likely than the general student population to be of non-white race or Hispanic ethnicity, and more often live in low socioeconomic status locations. [,][,]  There is some inconsistency in the evidence, which may be due to different local development patterns and measures of traffic and geographic scale used in the studies.[408]
Environmental Effects of Non-GHG Pollutants
In this section we discuss some of the environmental effects of PM and its precursors such as visibility impairment, atmospheric deposition, and materials damage and soiling, as well as environmental effects associated with the presence of ozone in the ambient air, such as impacts on plants, including trees, agronomic crops and urban ornamentals, and environmental effects associated with air toxics.
Visibility
Visibility can be defined as the degree to which the atmosphere is transparent to visible light.  Visibility impairment is caused by light scattering and absorption by suspended particles and gases.  Visibility is important because it has direct significance to people's enjoyment of daily activities in all parts of the country.  Individuals value good visibility for the well-being it provides them directly, where they live and work, and in places where they enjoy recreational opportunities.  Visibility is also highly valued in significant natural areas, such as national parks and wilderness areas, and special emphasis is given to protecting visibility in these areas.  For more information on visibility see the final 2009 PM ISA.
EPA is pursuing a two-part strategy to address visibility impairment.  First, EPA developed the regional haze program (64 FR 35714) which was put in place in July 1999 to protect the visibility in Mandatory Class I Federal areas.  There are 156 national parks, forests and wilderness areas categorized as Mandatory Class I Federal areas (62 FR 38680-38681, July 18, 1997).  These areas are defined in CAA section 162 as those national parks exceeding 6,000 acres, wilderness areas and memorial parks exceeding 5,000 acres, and all international parks which were in existence on August 7, 1977.  Second, EPA has concluded that PM2.5 causes adverse effects on visibility in other areas that are not protected by the Regional Haze Rule, depending on PM2.5 concentrations and other factors that control their visibility impact effectiveness such as dry chemical composition and relative humidity (i.e., an indicator of the water composition of the particles), and has set secondary PM2.5 standards to address these areas.  The existing annual primary and secondary PM2.5 standards have been remanded and are being addressed in the currently ongoing PM NAAQS review.  The secondary PM2.5 standards serve as a reasonable complement to the Regional Haze Program.
Plant and Ecosystem Effects of Ozone
Elevated ozone levels contribute to environmental effects, with impacts to plants and ecosystems being of most concern.  Ozone can produce both acute and chronic injury in sensitive species depending on the concentration level and the duration of the exposure.  Ozone effects also tend to accumulate over the growing season of the plant, so that even low concentrations experienced for a longer duration have the potential to create chronic stress on vegetation.  Ozone damage to plants includes visible injury to leaves and impaired photosynthesis, both of which can lead to reduced plant growth and reproduction, resulting in reduced crop yields, forestry production, and use of sensitive ornamentals in landscaping.  In addition, the impairment of photosynthesis, the process by which the plant makes carbohydrates (its source of energy and food), can lead to a subsequent reduction in root growth and carbohydrate storage below ground, resulting in other, more subtle plant and ecosystems impacts.
These latter impacts include increased susceptibility of plants to insect attack, disease, harsh weather, interspecies competition and overall decreased plant vigor.  The adverse effects of ozone on forest and other natural vegetation can potentially lead to species shifts and loss from the affected ecosystems, resulting in a loss or reduction in associated ecosystem goods and services.  Lastly, visible ozone injury to leaves can result in a loss of aesthetic value in areas of special scenic significance like national parks and wilderness areas.  The final 2006 Ozone Air Quality Criteria Document presents more detailed information on ozone effects on vegetation and ecosystems.
Atmospheric Deposition
Wet and dry deposition of ambient particulate matter delivers a complex mixture of metals (e.g., mercury, zinc, lead, nickel, aluminum, cadmium), organic compounds (e.g., polycyclic organic matter, dioxins, furans) and inorganic compounds (e.g., nitrate, sulfate) to terrestrial and aquatic ecosystems.  The chemical form of the compounds deposited depends on a variety of factors including ambient conditions (e.g., temperature, humidity, oxidant levels) and the sources of the material.  Chemical and physical transformations of the compounds occur in the atmosphere as well as the media onto which they deposit.  These transformations in turn influence the fate, bioavailability and potential toxicity of these compounds.  Atmospheric deposition has been identified as a key component of the environmental and human health hazard posed by several pollutants including mercury, dioxin and PCBs.
Adverse impacts on water quality can occur when atmospheric contaminants deposit to the water surface or when material deposited on the land enters a waterbody through runoff.  Potential impacts of atmospheric deposition to waterbodies include those related to both nutrient and toxic inputs.  Adverse effects to human health and welfare can occur from the addition of excess nitrogen via atmospheric deposition.  The nitrogen-nutrient enrichment contributes to toxic algae blooms and zones of depleted oxygen, which can lead to fish kills, frequently in coastal waters.  Deposition of heavy metals or other toxics may lead to the human ingestion of contaminated fish, impairment of drinking water, damage to the marine ecology, and limits to recreational uses.  Several studies have been conducted in U.S. coastal waters and in the Great Lakes Region in which the role of ambient PM deposition and runoff is investigated.[,][,][,][,]
Atmospheric deposition of nitrogen and sulfur contributes to acidification, altering biogeochemistry and affecting animal and plant life in terrestrial and aquatic ecosystems across the United States.  The sensitivity of terrestrial and aquatic ecosystems to acidification from nitrogen and sulfur deposition is predominantly governed by geology.  Prolonged exposure to excess nitrogen and sulfur deposition in sensitive areas acidifies lakes, rivers and soils.  Increased acidity in surface waters creates inhospitable conditions for biota and affects the abundance and nutritional value of preferred prey species, threatening biodiversity and ecosystem function.  Over time, acidifying deposition also removes essential nutrients from forest soils, depleting the capacity of soils to neutralize future acid loadings and negatively affecting forest sustainability.  Major effects include a decline in sensitive forest tree species, such as red spruce (Picea rubens) and sugar maple (Acer saccharum), and a loss of biodiversity of fishes, zooplankton, and macro invertebrates.
In addition to the role nitrogen deposition plays in acidification, nitrogen deposition also leads to nutrient enrichment and altered biogeochemical cycling.  In aquatic systems increased nitrogen can alter species assemblages and cause eutrophication.  In terrestrial systems nitrogen loading can lead to loss of nitrogen sensitive lichen species, decreased biodiversity of grasslands, meadows and other sensitive habitats, and increased potential for invasive species.  For a broader explanation of the topics treated here, refer to the description in Section 7.1.2 of the RIA.
Adverse impacts on soil chemistry and plant life have been observed for areas heavily influenced by atmospheric deposition of nutrients, metals and acid species, resulting in species shifts, loss of biodiversity, forest decline and damage to forest productivity.  Potential impacts also include adverse effects to human health through ingestion of contaminated vegetation or livestock (as in the case for dioxin deposition), reduction in crop yield, and limited use of land due to contamination.
Atmospheric deposition of pollutants can reduce the aesthetic appeal of buildings and culturally important articles through soiling, and can contribute directly (or in conjunction with other pollutants) to structural damage by means of corrosion or erosion.  Atmospheric deposition may affect materials principally by promoting and accelerating the corrosion of metals, by degrading paints, and by deteriorating building materials such as concrete and limestone.  Particles contribute to these effects because of their electrolytic, hygroscopic, and acidic properties, and their ability to adsorb corrosive gases (principally sulfur dioxide).
Environmental Effects of Air Toxics
Emissions from producing, transporting and combusting fuel contribute to ambient levels of pollutants that contribute to adverse effects on vegetation.  Volatile organic compounds, some of which are considered air toxics, have long been suspected to play a role in vegetation damage.  In laboratory experiments, a wide range of tolerance to VOCs has been observed.  Decreases in harvested seed pod weight have been reported for the more sensitive plants, and some studies have reported effects on seed germination, flowering and fruit ripening.  Effects of individual VOCs or their role in conjunction with other stressors (e.g., acidification, drought, temperature extremes) have not been well studied.  In a recent study of a mixture of VOCs including ethanol and toluene on herbaceous plants, significant effects on seed production, leaf water content and photosynthetic efficiency were reported for some plant species.
Research suggests an adverse impact of vehicle exhaust on plants, which has in some cases been attributed to aromatic compounds and in other cases to nitrogen oxides., ,   The impacts of VOCs on plant reproduction may have long-term implications for biodiversity and survival of native species near major roadways.  Most of the studies of the impacts of VOCs on vegetation have focused on short-term exposure and few studies have focused on long-term effects of VOCs on vegetation and the potential for metabolites of these compounds to affect herbivores or insects.
Air Quality Impacts of Non-GHG Pollutants
Air quality modeling was performed to assess the impact of the heavy-duty vehicle standards on criteria and air toxic pollutants.  In this section, we present information on current modeled levels of pollution as well as projections for 2030, with respect to ambient PM2.5, ozone, selected air toxics, visibility levels and nitrogen and sulfur deposition.  The results are discussed in more detail in Section 8.2 of the RIA.
We used the Community Multi-scale Air Quality (CMAQ) photochemical model, version 4.7.1, for our analysis.  This version of CMAQ includes a number of improvements to previous versions of the model.  These improvements are discussed in Section 8.2.2 of the RIA.
Ozone
Current Levels
8-hour ozone concentrations exceeding the level of the ozone NAAQS occur in many parts of the country.  In 2008, the EPA amended the ozone NAAQS (73 FR 16436, March 27, 2008).  The final 2008 ozone NAAQS rule set forth revisions to the previous 1997 NAAQS for ozone to provide increased protection of public health and welfare.  On January 6, 2010, EPA proposed to reconsider the 2008 ozone NAAQS to ensure that they are requisite to protect public health with an ample margin of safety, and requisite to protect public welfare (75 FR 2938, January 19, 2010).  EPA intends to complete the reconsideration by July 31, 2011.  If, as a result of the reconsideration, EPA promulgates different ozone standards, the new 2011 ozone standards would replace the 2008 ozone standards and the requirement to designate areas for the replaced 2008 standards would no longer apply.
As of April 21, 2011 there are 44 areas designated as nonattainment for the 1997 8-hour ozone NAAQS, comprising 242 full or partial counties with a total population of over 118 million people.  These numbers do not include the people living in areas where there is a future risk of failing to maintain or attain the 1997 8-hour ozone NAAQS.  The numbers above likely underestimate the number of counties that are not meeting the ozone NAAQS because the nonattainment areas associated with the more stringent 2008 8-hour ozone NAAQS have not yet been designated.  Table VII-7 provides an estimate, based on 2006-08 air quality data, of the counties with design values greater than the 2008 8-hour ozone NAAQS of 0.075 ppm.
Table VII-7 Counties with Design Values Greater Than the Ozone NAAQS

NUMBER OF COUNTIES
POPULATION1997 OZONE STANDARD:  COUNTIES WITHIN THE 54 AREAS CURRENTLY DESIGNATED AS NONATTAINMENT (AS OF 1/6/10)
266
122,343, 799
2008 Ozone Standard:  additional counties that would not meet the 2008 NAAQS (based on 2006-2008 air quality data)[b]
156
36,678,478
Total
422
159,022,277
Notes:
[a] Population numbers are from 2000 census data.
[b] Area designations for the 2008 ozone NAAQS have not yet been made.  Nonattainment for the 2008 Ozone NAAQS would be based on three years of air quality data from later years.  Also, the county numbers in this row include only the counties with monitors violating the 2008 Ozone NAAQS.  The numbers in this table may be an underestimate of the number of counties and populations that will eventually be included in areas with multiple counties designated nonattainment.
Projected Levels without this Final Action
States with 8-hour ozone nonattainment areas are required to take action to bring those areas into compliance in the future.  Based on the final rule designating and classifying 8-hour ozone nonattainment areas for the 1997 standard (69 FR 23951, April 30, 2004), most 8-hour ozone nonattainment areas will be required to attain the ozone NAAQS in the 2007 to 2013 time frame and then maintain the NAAQS thereafter.  As noted, EPA is reconsidering the 2008 ozone NAAQS.  If EPA promulgates different ozone NAAQS in 2011 as a result of the reconsideration, these standards would replace the 2008 ozone NAAQS and there would no longer be a requirement to designate areas for the 2008 NAAQS.  Attainment dates for any 2011 ozone NAAQS would range from 3 to 20 years from designation, depending on the area's classification.
EPA has already adopted many emission control programs that are expected to reduce ambient ozone levels and assist in reducing the number of areas that fail to achieve the ozone NAAQS.  Even so, our air quality modeling projects that in 2030, with all current controls but excluding the impacts of the heavy-duty standards, up to 10 counties with a population of over 30 million may not attain the 2008 ozone standard of 0.075 ppm (75 ppb).  These numbers do not account for those areas that are close to (e.g., within 10 percent of) the 2008 ozone standard.  These areas, although not violating the standards, will also be impacted by changes in ozone as they work to ensure long-term maintenance of the ozone NAAQS.
Projected Levels with this Final Action
Our modeling indicates ozone design value concentrations will decrease in many areas of the country.  The decreases in ozone design values are likely due to projected tailpipe reductions in NOX and projected upstream emissions decreases in NOX and VOCs from reduced gasoline production.  The majority of the ozone design value decreases are less than 1 ppb.  The maximum projected decrease in an 8-hour ozone design value is 1.57 ppb in Jefferson County, Tennessee.  On a population-weighted basis, the average modeled 8-hour ozone design values are projected to decrease by 0.39 ppb in 2030 and the design values for those counties that are projected to be above the 2008 ozone standard in 2030 will see population-weighted decreases of 0.16 ppb due to the heavy-duty standards.
Particulate Matter
Current Levels
PM2.5 concentrations exceeding the level of the PM2.5 NAAQS occur in many parts of the country.  In 2005, EPA designated 39 nonattainment areas for the 1997 PM2.5 NAAQS (70 FR 943, January 5, 2005).  These areas are composed of 208 full or partial counties with a total population exceeding 88 million.  The 1997 PM2.5 NAAQS was revised in 2006 and the 2006 24-hour PM2.5 NAAQS became effective on December 18, 2006.  On October 8, 2009, the EPA issued final nonattainment area designations for the 2006 24-hour PM2.5 NAAQS (74 FR 58688, November 13, 2009).  These designations include 32 areas composed of 121 full or partial counties with a population of over 70 million.  In total, there are 54 PM2.5 nonattainment areas composed of 243 counties with a population of almost 102 million people.
Projected Levels without this Final Action
States with PM2.5 nonattainment areas are required to take action to bring those areas into compliance in the future.  Areas designated as not attaining the 1997 PM2.5 NAAQS will need to attain the 1997 standards in the 2010 to 2015 time frame, and then maintain them thereafter.  The 2006 24-hour PM2.5 nonattainment areas will be required to attain the 2006 24-hour PM2.5 NAAQS in the 2014 to 2019 time frame and then be required to maintain the 2006 24-hour PM2.5 NAAQS thereafter.  The heavy-duty standards finalized in this action become effective in 2012 and therefore may be useful to states in attaining or maintaining the PM2.5 NAAQS.
       EPA has already adopted many emission control programs that are expected to reduce ambient PM2.5 levels and which will assist in reducing the number of areas that fail to achieve the PM2.5 NAAQS.  Even so, our air quality modeling projects that in 2030, with all current controls but excluding the impacts of the heavy-duty standards adopted here, at least 4 counties with a population of almost 7 million may not attain the 1997 annual PM2.5 standard of 15 ug/m[3] and 22 counties with a population of over 33 million may not attain the 2006 24-hour PM2.5 standard of 35 ug/m[3].  These numbers do not account for those areas that are close to (e.g., within 10 percent of) the PM2.5 standards.  These areas, although not violating the standards, will also benefit from any reductions in PM2.5 ensuring long-term maintenance of the PM2.5 NAAQS.

Projected Levels with this Final Action
Air quality modeling performed for this final action shows that in 2030 the majority of the modeled counties will see decreases of less than 0.01 ug/m[3] in their annual PM2.5 design values.  The decreases in annual PM2.5 design values that we see in some counties are likely due to emission reductions related to lower fuel production at existing oil refineries and/or reductions in PM2.5 precursor emissions (NOX, SOX, and VOCs) due to improvements in road load.  The maximum projected decrease in an annual PM2.5 design value is 0.03 ug/m[3] in Allen County, Indiana and Canyon County, Idaho.  On a population-weighted basis, the average modeled 2030 annual PM2.5 design value is projected to decrease by 0.01 ug/m[3] due to this final action.
In addition to looking at annual PM2.5 design values, we also modeled the impact of the standards on 24-hour PM2.5 design values.  Air quality modeling performed for this final action shows that in 2030 the majority of the modeled counties will see changes of between -0.05 ug/m[3] and 0 ug/m[3] in their 24-hour PM2.5 design values.  The decreases in annual PM2.5 design values that we see in some counties are likely due to emission reductions related to lower fuel production at existing oil refineries and/or reductions in PM2.5 precursor emissions (NOX, SOX, and VOCs) due to improvements in road load.  The maximum projected decrease in a 24-hour PM2.5 design value is 0.27 ug/m[3] in Canyon County, ID.  There are also some counties that are projected to see increases of less than 0.1 ug/m[3] in their 24-hour PM2.5 design values.  These small increases in 24-hour PM2.5 design values are likely related to downstream emission increases from APUs.  On a population-weighted basis, the average modeled 2030 24-hour PM2.5 design value is projected to decrease by 0.03 ug/m[3] due to this final action.  Those counties that are projected to be above the 24-hour PM2.5 standard in 2030 will see slightly smaller population-weighted decreases of 0.01 ug/m[3] in their design values due to this final action.
Air Toxics
Current Levels
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.  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 detail in U.S. EPA's most recent Mobile Source Air Toxics Rule.  According to the National Air Toxic Assessment (NATA) for 2005, mobile sources were responsible for 43 percent of outdoor toxic emissions and over 50 percent of the cancer risk and noncancer hazard.  Benzene is the largest contributor to cancer risk of all 124 pollutants quantitatively assessed in the 2002 NATA and mobile sources were responsible for 59 percent of benzene emissions in 2002.  Over the years, EPA has implemented a number of mobile source and fuel controls resulting in VOC reductions, which also reduce benzene and other air toxic emissions.
Projected Levels
Our modeling indicates that the heavy-duty standards have relatively little impact on national average ambient concentrations of the modeled air toxics.  Additional detail on the air toxics results can be found in Section <IP_ADDRESS> of the RIA.
Nitrogen and Sulfur Deposition
Current Levels
Over the past two decades, the EPA has undertaken numerous efforts to reduce nitrogen and sulfur deposition across the U.S.  Analyses of long-term monitoring data for the U.S. show that deposition of both nitrogen and sulfur compounds has decreased over the last 17 years although many areas continue to be negatively impacted by deposition.  Deposition of inorganic nitrogen and sulfur species routinely measured in the U.S. between 2005 and 2007 were as high as 9.6 kilograms of nitrogen per hectare (kg N/ha) averaged over three years and 20.8 kilograms of sulfur per hectare (kg S/ha) averaged over three years.  The data show that reductions were more substantial for sulfur compounds than for nitrogen compounds.  These numbers are generated by the U.S. national monitoring network and they likely underestimate nitrogen deposition because neither ammonia nor organic nitrogen is measured.  In the eastern U.S., where data are most abundant, total sulfur deposition decreased by about 44% between 1990 and 2007, while total nitrogen deposition decreased by 25% over the same time frame.
Projected Levels
Our air quality modeling projects decreases in nitrogen deposition, especially in the Midwest, as a result of the heavy-duty standards required by this final action.  The heavy-duty standards will result in annual percent decreases of 0.5% to more than 2% in some cities in the Midwest, Phoenix, Albuquerque, and some areas in Texas.  The remainder of the country will see only minimal changes in nitrogen deposition, ranging from decreases of less than 0.5% to increases of less than 0.5%.  For a map of 2030 nitrogen deposition impacts and additional information on these impacts, see Section <IP_ADDRESS> of the RIA.  The impacts of the heavy-duty standards on sulfur deposition are minimal, ranging from decreases of up to 0.5% to increases of up to 0.5%.
Visibility
Current Levels
As mentioned in Section VII.D(1)(a) , millions of people live in nonattainment areas for the PM2.5 NAAQS.   These populations, as well as large numbers of individuals who travel to these areas, are likely to experience visibility impairment.  In addition, while visibility trends have improved in mandatory class I federal areas, the most recent data show that these areas continue to suffer from visibility impairment.  In summary, visibility impairment is experienced throughout the U.S., in multi-state regions, urban areas, and remote mandatory class I federal areas.
Projected Levels
Air quality modeling conducted for this final action was used to project visibility conditions in 138 mandatory class I federal areas across the U.S. in 2030.  The results show that all the modeled areas will continue to have annual average deciview levels above background in 2030.  The results also indicate that the majority of the modeled mandatory class I federal areas will see very little change in their visibility, but some mandatory class I federal areas will see improvements in visibility due to the heavy-duty standards and a few mandatory class I federal areas will see visibility decreases.  The average visibility at all modeled mandatory class I federal areas on the 20% worst days is projected to improve by 0.01 deciviews, or 0.06%, in 2030.  Section <IP_ADDRESS> of the RIA contains more detail on the visibility portion of the air quality modeling.

What are the Agencies' Estimated Cost, Economic, and Other Impacts of the Final Program?
In this section, we present the costs and impacts of the final HD National Program.  It is important to note that NHTSA's final fuel consumption standards and EPA's final GHG emissions standards will both be in effect, and each will lead to average fuel efficiency increases and GHG emission reductions.  The two agencies' final standards comprise the HD National Program.
The net benefits of the final HD National Program consist of the effects of the program on:
the vehicle program costs (costs of complying with the vehicle CO2 standards)
fuel savings associated with reduced fuel usage resulting from the program
reductions in greenhouse gas emissions,
the reductions in other (non-GHG) pollutants,
costs associated with increases in noise, congestion, and accidents resulting from increased vehicle use,
improvements in U.S. energy security impacts,
benefits associated with increased vehicle use due to the "rebound" effect.
We also present the cost-effectiveness of the standards, or the cost per ton of emissions reduced.
The program may have other effects that are not included here.  The agencies sought comment on whether any costs or benefits were omitted from this analysis, so that they could be explicitly recognized in the final rules.  In particular, as discussed in Section III and in Chapter 2 of the RIA, the technology cost estimates developed here take into account the costs to hold other vehicle attributes, such as size and performance, constant.  In addition, the analysis assumes that the full technology costs are passed along to vehicle buyers.  With these assumptions, because welfare losses are monetary estimates of how much buyers would have to be compensated to be made as well off as in the absence of the change, the price increase measures the loss to the buyer.  Assuming that the full technology cost gets passed along to the buyer as an increase in price, the technology cost thus measures the welfare loss to the buyer.  Increasing fuel efficiency would have to lead to other changes in the vehicles that buyers find undesirable for there to be additional losses not included in the technology costs.
The agencies sought comments, including supporting data and quantitative analyses, of any additional impacts of the final standards on vehicle attributes and performance, and other potential aspects that could positively or negatively affect the welfare implications of this final rulemaking, not addressed in this analysis.
The comments received by the agencies did not provide any clear insights into this question.  Some comments noted the diversity of the trucking industry and expressed a request that the program continue the great variety of options for the industry, because of the variation in needs for different customers.  Additional comments noted that the separate engine and vehicle programs support the maintenance of variety and current market structure.  Though a few commenters raised concerns, no information was offered to indicate that choice will in fact be limited by the program, or that other vehicle attributes are adversely affected.
The total monetized benefits (excluding fuel savings) under the program are projected to be $1.5 to $8.6 billion in 2030, depending on the value used for the social cost of carbon.  These benefits are summarized below in Table VIII-25.  The costs of the program in 2030 are estimated to be approximately $2.7 billion for new engine and truck technology less $20.9 billion in savings realized by trucking operations through fewer fuel expenditures (calculated using pre-tax fuel prices).  These costs are summarized below in Table VIII-24.  The present value of the total monetized benefits (excluding fuel savings) under the program are expected to range from $25.8 billion to $158.4 billion with a 3% discount rate; with a 7% discount rate, the total monetized benefits are expected to range from $16.1 billion to $148.7 billion.  These values, summarized in Table VIII-25, depend on the value used for the social cost of carbon.  The present value of costs of the program for new engine and truck technology, in Table VIII-24, are expected to be $57 billion using a 3% discount rate, and $29.5 billion with a 7% discount rate, less fuel savings (calculated using pre-tax fuel prices) of $380 billion with a 3% discount rate, and $168.6 billion with a 7% discount rate.  Total net present benefits (in Table VIII-26) are thus expected to range from $348.8 billion to $481.4 billion with a 3% discount rate, and $155.2 billion to $287.8 billion with a 7% discount rate.
The estimates developed here are measured against a baseline fuel efficiency associated with MY 2010 vehicles.  The agencies also considered an alternate baseline associated with AEO 2011 projections, which is further discussed in Section IX. All calculations presented in Section VIII use the constant 2010 vehicle baseline.   The extent to which fuel efficiency improvements may have occurred in the absence of the rules affects the net benefits associated with the program.  If trucks wwere to install technologies to achieve the fuel savings and reduced GHG emissions in the absence of this program, then both the costs and benefits of these fuel savings could be attributed to market forces, not the rules.  As a baseline for estimates of the extent of fuel-saving technologies that might have been adopted in the absence of the program, the proposal used the level of these technologies in MY 2010 vehicles.  We sought comment on whether the agencies should use an alternative baseline based on data provided by commenters to estimate the degree to which the technologies discussed in the proposal would have been adopted in the absence of these rules. No comments were received on this issue (?).  One comment cites the EPA draft RIA as noting a historic 1% per year improvement in fuel efficiency, and argues that the rules are therefore not needed; the actual figure in the draft RIA, however, was a 0.09% per year improvement.
EPA has undertaken an analysis of the economy-wide impacts of the final heavy-duty truck fuel efficiency and GHG standards as an exploratory exercise that EPA believes could provide additional insights into the potential impacts of the program.  These results were not a factor regarding the appropriateness of the final standards.  It is important to note that the results of this modeling exercise are dependent on the assumptions associated with how manufacturers would make fuel efficiency improvements and how trucking operations would respond to increases in higher vehicle costs and improved vehicle fuel efficiency as a result of the final program.
Further information on these and other aspects of the economic impacts of our rules are summarized in the following sections and are presented in more detail in the RIA for this final rulemaking.
Conceptual Framework for Evaluating Impacts
This regulation is motivated primarily by the goals of reducing emissions of greenhouse gases and promoting U.S. energy security by reducing consumption and imports of petroleum-based fuels.  These motivations involve classic externalities, meaning that private decisions do not incorporate all of the costs associated with these problems; these costs are not borne completely by the households or businesses whose actions are responsible for them.  In the absence of some mechanism to "internalize" these costs  -  that is, to transfer their burden to individuals or firms whose decisions impose them  -  individuals and firms will consume more petroleum-based fuels than is socially optimal.  Externalities are a classic motivation for government intervention in markets.  These externalities, as well as effects due to changes in emissions of other pollutants and other impacts, are discussed in Sections VIII.H  -  VIII.K.
In some cases, these classic externalities are by themselves enough to justify the costs of imposing fuel efficiency standards.  For some discount rates and some projected social costs of carbon, however, the reductions in these external costs are less than the costs of new fuel saving technologies needed to meet the standards. (See Tables 9-18 and 9-19 in the RIA.) Nevertheless, this regulation reduces trucking companies' fuel costs; according to our estimates, these savings in fuel costs are by themselves sufficient to pay for the technologies over periods of time considerably shorter than vehicles' expected lifetimes under the assumptions used for this analysis (e.g., AEO 2011 projected fuel prices).  If these estimates are correct, then the entire value of the reductions in external costs represents additional net benefits of the program, beyond those resulting from the fact that the value of fuel savings exceeds the costs of technologies necessary to achieve them.
It is often asserted that there are cost-effective fuel-saving technologies that truck companies are not taking advantage of.  This is commonly known as the "energy gap" or "energy paradox."  Standard economic theory suggests that in normally functioning competitive markets, interactions between vehicle buyers and producers would lead producers to incorporate all cost-effective technology into the vehicles that they offer, without government intervention.  Unlike in the light-duty vehicle market, the vast majority of vehicles in the medium- and heavy-duty truck market are purchased and operated by businesses with narrow profit margins, and for which fuel costs represent a substantial operating expense.
Even in the presence of uncertainty and imperfect information  -  conditions that hold to some degree in every market  -  we generally expect firms to attempt to minimize their costs in an effort to survive in a competitive marketplace, and therefore to make decisions that are in the best interest of the company and its owners and/or shareholders.  In this case, the benefits of the rules would be due exclusively to reducing the economic costs of externalities resulting from fuel production and consumption.  However, as discussed below in Section VIII.E, the agencies have estimated that the application of fuel-saving technologies in response to the final standards would, on average, yield private returns to truck owners of 140% to 420% (see Table VIII-21 below).  The agencies have also estimated that the application of these technologies would be significantly lower in the absence of the final standards (i.e., under the "no action" regulatory alternative), meaning that truck buyers and operators ignore opportunities to make investments in higher fuel efficiency that appear to offer significant cost savings.
As discussed in the NPRM, there are several possible explanations in the economics literature for why trucking companies do not adopt technologies that would be expected to increase their profits: there could be a classic market failure in the trucking industry  -  market power, externalities, or asymmetric or incomplete (i.e., missing market) information; there could be institutional or behavioral rigidities in the industry (union rules, standard operating procedures, statutory requirements, loss aversion, etc.), whereby participants collectively do not minimize costs; or the engineering estimates of fuel savings and costs for these technologies might overstate their benefits or understate their costs in real-world applications.
To try to understand why trucking companies have not adopted these seemingly cost-effective fuel-saving technologies, the agencies surveyed published literature about the energy paradox, and held discussions with numerous truck market participants. The proposal discussed five categories of possible explanations derived from these sources. Collectively, these five hypotheses may explain the apparent inconsistency between the engineering analysis, which finds a number of cost-effective methods of improving fuel efficiency, and the observation that many of these technologies are not widely adopted.
These hypotheses include imperfect information in the original and resale markets, split incentives, uncertainty about future fuel prices, and adjustment and transactions costs.  As the discussion indicated, some of these explanations suggest failures in the private market for fuel-saving technology in addition to the externalities caused by producing and consuming fuel that are the primary motivation for the rules.  Other explanations suggest market-based behaviors that may imply additional costs of regulating truck fuel efficiency that are not accounted for in this analysis.  As noted above, an additional explanation  -  adverse effects on other vehicle attributes --  did not elicit supporting information in the public comments.  Anecdotal evidence from various segments of the trucking industry suggests that many of the hypotheses discussed here may play a role in explaining the puzzle of why truck purchasers appear to under-invest in fuel efficiency, although different explanations may apply to different segments, or even different companies. The published literature does not appear to include empirical analysis or data related to this question.
The agencies invited comment on these explanations, and on any data or information that could be used to investigate the role of any or all of these five hypotheses in explaining this energy paradox as it applies specifically to trucks.  Some comments expressed dissatisfaction about the explanations presented; they argued that these arguments were not sufficient to explain the phenomenon.  These comments argued that the truck owners and operators are better judges of the appropriate amount of fuel efficiency than are government agencies; they choose not to invest because of warranted skepticism about these technologies.  The agencies also requested comment and information regarding any other hypotheses that could explain the appearance that cost-effective fuel-saving technologies have not been widely incorporated into trucks.  The following discussion summarizes the fuller discussion provided in the NPRM and includes discussion of the comments received.
Information Issues in the Original Sale Markets
One potential hypothesis for why the trucking industry does not adopt what appear to be inexpensive fuel saving technologies is that there is inadequate or unreliable information available about the effectiveness of many fuel-saving technologies for new vehicles.  If reliable information on the effectiveness of many new technologies is absent, truck buyers will understandably be reluctant to spend additional money to purchase vehicles equipped with unproven technologies.
This lack of information can manifest itself in multiple ways. For instance, the problem may arise purely because collecting reliable information on technologies is costly (also see Section VIII.A.5 on transaction costs).  Moreover, information has aspects of a public good, in that no single firm has the incentive to do the costly experimentation to determine whether or not particular technologies are cost-effective, while all firms benefit from the knowledge that would be gained from that experimentation.  Similarly, if multiple firms must conduct the same tests to get the same information, costs could be reduced by some form of coordination of information gathering.
While its effect on information is indirect, we expect the requirement for the use of new technologies included in this program will circumvent these information issues, resulting in their adoption, thus providing more readily available information about their benefits.  The agencies appreciate, however, that the diversity of truck uses, driving situations, and driver behavior willl lead to variation in the fuel savings that individual trucks or fleets experience from using specific technologies.
One commenter noted that the SmartWay program targets semi-truck owners and thus should have the largest impact on that sector, rather than vocational or medium-duty trucks; however, that the gap between actual investment in fuel efficiency and the agencies' estimates of optimal investment are largest for the combination tractor.  Some of the difference in magnitude is likely to be due to the higher vehicle miles traveled for semi-trucks compared to medium-duty and vocational vehicles:  more driving means more fuel savings.  Additionally, not even a majority of semi-trucks are owned by participants in SmartWay; non-participants are unlikely to get all the benefits of participants.  Other explanations, noted below, are also likely to play a role.  This observation may also suggest some limitations of improved information provision as a means of addressing the "efficiency gap."
	Information Issues in the Resale Market
In addition to issues in the new vehicle market, a second hypothesis for why trucking companies may not adopt what appear to be cost-effective technologies to save fuel is that the resale market may not adequately reward the addition of fuel-saving technology to vehicles to ensure their original purchase by new truck buyers.  This inadequate payback for users beyond the original owner may contribute to the short payback period that new purchasers appear to expect.  The agencies requested data and information on the extent to which costs of fuel saving equipment can be recovered in the resale truck market.  No data were received.  One reviewer disputed this theory on the basis that people are willing to pay more for better vehicles, new or used.  It is not clear, however, whether buyers of used vehicles can tell which are the better vehicles.
Some of this unwillingness to pay for fuel-saving technology may be due to the extension of the information problems in the new vehicle market into resale markets.  Buyers in the resale market have no more reason to trust information on fuel-saving technologies than buyers in the original market.  Because actual fuel efficiency of trucks on the road depends on many factors, including geography and driving styles or habits, even objective sources such as logs of truck performance for used vehicles may not provide reliable information about the fuel efficiency that potential purchasers of used trucks will experience.
A related possibility is that vehicles will be used for different purposes by their second owners than those for which they were originally designed, and the fuel-saving technology  is therefore of less value.
It is possible, though, that the fuel savings experienced by the secondary purchasers may not match those experienced by their original owners if the optimal secondary new use of the vehicle does not earn as many benefits from the technologies.  One commenter asks whether the fuel-saving technology is unvalued because it is unproven or overrated.  In that case, the premium for fuel-saving technology in the secondary market should accurately reflect its value to potential buyers participating in that market, even if it is lower than its value in the original market, and the market has not failed.  Because the information necessary to optimize use in the secondary market may not be readily available or reliable, however, buyers in the resale market may have less ability than purchasers of new vehicles to identify and gain the advantages of new fuel-saving technologies, and may thus be even less likely to pay a premium for them.
For these reasons, purchasers' willingness to pay for fuel efficiency technologies may be even lower in the resale market than in the original equipment market.  Even when fuel-saving technologies will provide benefits in the resale markets, purchasers of used vehicles may not be willing to compensate their original owners fully for their remaining value.  As a result, the purchasers of original equipment may expect the resale market to provide inadequate appropriate compensation for the new technologies, even when those technologies would reduce costs for the new buyers.  This information issue may partially explain what appears to be the very short payback periods required for new technologies in the new vehicle market.
Split Incentives in the Medium- and Heavy-Duty Truck Industry
A third hypothesis explaining the energy paradox as applied to trucking involves split incentives.  When markets work effectively, signals provided by transactions in one market are quickly transmitted to related markets and influence the decisions of buyers and sellers in those related markets.  For instance, in a well-functioning market system, changes in the expected future price of fuel should be transmitted rapidly to those who purchase trucks, who will then reevaluate the amount of fuel-saving technology to purchase for new vehicles.  If for some reason a truck purchaser will not be directly responsible for future fuel costs, or the individual who will be responsible for fuel costs does not decide which truck characteristics to purchase, then those price signals may not be transmitted effectively, and incentives can be described as "split."
One place where such a split may occur is between the owners and operators of trucks.  Because they are generally responsible for purchasing fuel, truck operators have strong incentives to economize on its use, and are thus likely to support the use of fuel-saving technology.  However, the owners of trucks or trailers are often different from operators, and may be more concerned about their longevity or maintenance costs than about their fuel efficiency, when purchasing vehicles.  As a result, capital investments by truck owners may be channeled into equipment that improves vehicles' durability or reduces their maintenance costs, rather than into fuel-saving technology.  If operators can choose freely among the trucks they drive, competition among truck owners to employ operators would encourage owners to invest in fuel-saving technology.  However, if truck owners have more ability to choose among operators, then market signals for improved fuel savings that would normally be transmitted to truck owners may be muted.  Truck fleets that rent their vehicles may provide an example:  renters may observe the cost of renting the truck, but not its fuel efficiency; if so, then the purchasers will aim for vehicles with lower costs, to lower the cost of the rental.
One commenter noted that there are always tradeoffs in an investment decision:  a purchaser may prefer to invest in other vehicle attributes than fuel efficiency.  In an efficient market, however, a purchaser should invest in fuel-saving technology as long as the increase in fuel-saving technology costs less than the expected fuel savings.  This result should hold regardless of the level of investment in other attributes, unless there are constraints on a purchaser's access to investment capital.
Anecdotal information about large truck fleets suggests that, even within a company, the office or department responsible for truck purchases is often different from that responsible for purchasing fuel.  Therefore, the employees who purchase trucks may have strong incentives to lower their initial capital cost, but not equally strong incentives to lower operating costs.
In addition, the NAS report notes that split incentives can arise between tractor and trailer operators.  Trailers affect the fuel efficiency of shipping, but trailer owners do not face strong incentives to coordinate with truck owners.  EPA and NHTSA are not regulating trailers in this action.
By itself, information provision may be inadequate to address the potential underinvestment in fuel efficiency resulting from such split incentives.  In this setting, regulation may contribute to fuel savings that otherwise may be difficult to achieve.
Uncertainty About Future Cost Savings
Another hypothesis for the lack of adoption of seemingly fuel saving technologies may be uncertainty about future fuel prices or truck maintenance costs.  When purchasers have less than perfect foresight about future operating expenses, they may implicitly discount future savings in those costs due to uncertainty about potential returns from investments that reduce future costs.  In contrast, the immediate costs of the fuel-saving or maintenance-reducing technologies are certain and immediate, and thus not subject to discounting.  In this situation, both the expected return on capital investments in higher fuel efficiency and potential variance about its expected rate may play a role in a firm's calculation of its payback period on such investments.
In the context of energy efficiency investments for the home, Metcalf and Rosenthal (1995) and Metcalf and Hassett (1995) observe that households weigh known, up-front costs that are essentially irreversible against an unknown stream of future fuel savings.  Notably, in this situation, requiring households to adopt technologies more quickly may make them worse off by imposing additional risk on them.
Greene et al (2009) also finds support for this explanation in the context of light-duty fuel economy decisions:  a loss-averse consumer's expected net present value of increasing the fuel economy of a passenger car can be very close to zero, even if a risk-neutral expected value calculation shows that its buyer can expect significant net benefits from purchasing a more fuel-efficient car.  Supporting this hypothesis is a finding by Dasgupta et. al (2007) that consumers are more likely to lease than buy a vehicle with higher maintenance costs because it provides them with the option to return it before those costs become too high.  However, the agencies know of no studies that have estimated the impact of uncertainty on perceived future savings for medium- and heavy-duty vehicles.
Purchasers' uncertainty about future fuel prices implies that mandating improvements in fuel efficiency can reduce the expected utility associated with truck purchases.  This is because adopting such regulation requires purchasers to assume a greater level of risk than they would in its absence, even if the future fuel savings predicted by a risk-neutral calculation actually materialize.  One commenter expressed support for this argument.  Thus the mere existence of uncertainty about future savings in fuel costs does not by itself assure that regulations requiring improved fuel efficiency will necessarily provide economic benefits for truck purchasers and operators.  On the other hand, because risk aversion reduces expected returns for businesses, competitive pressures can reduce risk aversion:  risk-neutral companies can make higher average profits over time.  Thus, significant risk aversion is unlikely to survive competitive pressures.
Adjustment and Transactions Costs
Another hypothesis is that transactions costs of changing to new technologies (how easily drivers will adapt to the changes, e.g.) may slow or prevent their adoption.  Because of the diversity in the trucking industry, truck owners and fleets may like to see how a new technology works in the field, when applied to their specific operations, before they adopt it.  One commenter expressed support for this argument.  If a conservative approach to new technologies leads truck buyers to adopt new technologies slowly, then successful new technologies are likely to be adopted over time without market intervention, but with potentially significant delays in achieving fuel saving, environment, and energy security benefits.
In addition, there may be costs associated with training drivers to realize the potential fuel savings enabled by new technologies, or with accelerating fleet operators' scheduled fleet turnover and replacement to hasten their acquisition of vehicles equipped with new fuel-saving technologies.  Here, again, there may be no market failure; requiring the widespread use of these technologies may impose adjustment and transactions costs not included in this analysis.  As in the discussion of the role of risk, these adjustment and transactions costs are typically immediate and undiscounted, while their benefits are future and uncertain; risk or loss aversion may further discourage companies from adopting new technologies.
To the extent that there may be transactions costs associated with the new technologies, then regulation gives all new truck purchasers a level playing field, because it will require all of them to adjust on approximately the same time schedule.  If experience with the new technologies serves to reduce uncertainty and risk, the industry as a whole may become more accepting of new technologies.  This could increase demand for future new technologies and induce additional benefits in the legacy fleet through complementary efforts such as SmartWay.
Additional Hypotheses
In the public comments, two additional ideas were raised for the lack of adoption of what appears to be cost-effective fuel-saving technology.  The first suggestion is that tighter diesel emissions standards caused fuel efficiency for diesel trucks to decline in the past decade.  Because engine manufacturers would have to invest heavily (both financially and with personnel) in emissions reduction technologies, they would not invest in fuel efficiency.  The costs associated with the decline in fuel efficiency due to the emissions regulations were accounted for in that rulemaking.
A second suggestion is that a truck may be a "positional good"  -  that is, a good whose value depends on how it compares to the goods owned by others.  If trucks confer status on their owners or operators, and if that status depends on easily observable characteristics, then owners may invest disproportionately in status-granting characteristics rather than less visible characteristics, such as fuel efficiency.  Because status depends on comparisons to others, an "arms race" may develop in which all parties spend additional money on visible characteristics but may not manage to make themselves better off.  In this case, regulation may improve welfare:  by increasing the requirements for non-positional fuel efficiency, regulation could reduce expenditures made purely for competition rather than actual increase in welfare.  In a competitive business, cost reduction provides a major opportunity cost to investing in status rather than in fuel-saving technology; thus, this argument may play less of a role in the heavy-duty market than in the consumer market for vehicles.
Both these hypotheses leave open the question, though, why additional investments were not made in fuel efficiency if they would provide rapid payback.  Truck purchasers should, in principle, be willing to buy additional fuel-saving technology as long as it is cost-effective, regardless of other vehicle attributes.  Limited access to capital, if it is a problem in this sector, might provide some reason for the "crowding out" of the purchase of fuel-saving technology.
Summary
On the one hand, commercial vehicle operators are under competitive pressure to reduce operating costs, and thus their purchasers would be expected to pursue and rapidly adopt cost-effective fuel-saving technologies.  On the other hand, the short payback period required by buyers of new trucks is a symptom that suggests some combination of uncertainty about future cost savings, transactions costs, and imperfectly functioning markets.  In addition, widespread use of tractor-trailer combinations introduces the possibility that owners of trailers may have weaker incentives than truck owners or operators to adopt fuel-saving technology for their trailers.  The market for medium- and heavy-duty trucks may face these problems, both in the new vehicle market and in the resale market.
Provision of information about fuel-saving technologies through voluntary programs such as SmartWay will assist in the adoption of new cost-saving technologies, but diffusion of new technologies can still be obstructed.  Those who are willing to experiment with new technologies expect to find cost savings, but those may be difficult to prove.  As noted above, because individual results of new technologies vary, new truck purchasers may find it difficult to identify or verify the effects of fuel-saving technologies.  Those who are risk-averse are likely to avoid new technologies out of concerns over the possibility of inadequate returns on the investment, or with other adverse impacts.  Competitive pressures in the freight transport industry can provide a strong incentive to reduce fuel consumption and improve environmental performance.  However, not every driver or trucking fleet operating today has the requisite ability or interest to access the technical information, some of which is already provided by SmartWay, nor the resources necessary to evaluate this information within the context of his or her own freight operation.
It is unclear, as discussed above, whether some or many of the technologies would be adopted in the absence of the program.  To the extent that they would have been adopted, the costs and the benefits attributed to those technologies may not in fact be due to the program and may therefore be overstated.  Both baselines used project substantially less adoption than the agencies consider to be cost-effective.  The agencies will continue to explore reasons for this slow adoption of cost-effective technologies.
As noted at the beginning of this section, the agencies seek comments on all these hypotheses as well as any data that could inform our understanding of what appears to be slow adoption of cost-effective fuel-saving technologies in these industries.
Costs Associated With the Final Program
In this section, the agencies present the estimated costs associated with the final program.  The presentation here summarizes the costs associated with new technology expected to be added to meet the new GHG and fuel consumption standards.  The analysis summarized here provides the estimate of incremental costs on a per truck basis and on an annual total basis.
The presentation here summarizes the best estimate by EPA and NHTSA staff as to the technology mix expected to be employed for compliance.  For details behind the cost estimates associated with individual technologies, the reader is directed to Section III of this preamble and to Chapter 2 of the RIA.
With respect to the cost estimates presented here, the agencies note that, because these estimates relate to technologies which are in most cases already available, these cost estimates are technically robust.
Costs per Truck
For the Class 2b and 3 pickup trucks and vans, the agencies have used a methodology consistent with that used for our recent light-duty joint rulemaking since most of the technologies expected for Class 2b and 3 pickup trucks and vans is consistent with that expected for the larger light-duty trucks.  The cost estimates presented in the recent light-duty joint rulemaking were then scaled upward to account for the larger weight, towing capacity, and work demands of the trucks in these heavier classes.  For details on that scaling process and the resultant costs for individual technologies, the reader is directed to Section III of this preamble and to Chapter 2 of the RIA.  Note also that all cost estimates have been updated to 2009 dollars for this analysis while the heavy-duty GHG emissions and fuel efficiency proposal was presented in 2008 dollars and the 2012-2016 MY light-duty joint rulemaking was presented in 2007 dollars.
For the loose heavy-duty gasoline engines, we have generally used engine-related costs from the Class 2b and 3 pickup truck and van estimates since the loose heavy-duty gasoline engines are essentially the same engines as those sold into the Class 2b and 3 pickup truck and van market.
For heavy-duty diesel engines, the agencies have estimated costs using a different methodology than that employed in the recent light-duty joint rulemaking.  In the 2012-2016 MY light-duty joint rulemaking, the fixed costs were included in the hardware costs via an indirect cost multiplier.  As such, the hardware costs presented in that analysis, and in the cost estimates for Class 2b and 3 trucks, included both the actual hardware and the associated fixed costs.  For this analysis, some of the fixed costs are estimated separately for HD diesel engines and are presented separately from the hardware costs.  For details, the reader is directed to Chapter 2 of the RIA.  Importantly, both methodologies after the figures are totaled account for all the costs associated with the program.  As noted above, all costs are presented in 2009 dollars.
The estimates of vehicle compliance costs cover the years leading up to  -  2012 and 2013  -  and including implementation of the program  -  2014 through 2018.  Also presented are costs for the years following implementation to shed light on the long term (2022 and later) cost impacts of the program.   The year 2022 was chosen here consistent with the 2012-2016 MY light-duty joint rulemaking.  That year was considered long term in that analysis because the short-term and long-term markup factors described shortly below are applied in five year increments with the 2012 through 2016 implementation span and the 2017 through 2021 span both representing the short-term.  Since many of the costs used in this analysis are based on costs in the 2012-2016 MY light-duty joint rulemaking analysis, consistency with that analysis seems appropriate.