From: "Frey, Nathan J." <Nathan_J._Frey@omb.eop.gov>

To: Lydia Wegman/RTP/USEPA/US@EPA, "Mancini, Dominic J."

<Dominic_J._Mancini@omb.eop.gov> Cc: Michael Ling/RTP/USEPA/US@EPA, Anna Wood/RTP/USEPA/US@EPA, Joseph

- J

Dougherty/DC/USEPA/US@EPA, 03772158 <03772158@nss.eop.gov> Date: 12/14/2012 12:14 AM Subject: Summ ary of Interagency Comments Under EOs 12866 and 13563

-- PM NAAQs Final Rule RIA

Attached please find a summary of interagency comments under EOs 12866 and 13563 regarding the PM NAAQs final rule RIA. Please let me know if you have any questions or if you would like to discuss further tomorrow.

E.O. 12866_PM NAAQS_2060

- AO47_FRN_Welfare_Co

- Benefits_20121120

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- 2 CHAPTER 6
WELFARE CO

- BENEFITS OF THE PRIMARY STAND ARD

6

. 1 Synopsis

T he emission reductions to meet the revised primary standard will have “welfare” co

benefits in addition to human health benefits, including changes in visibility, materials damage, ecological effects from PM deposition, ecological effects from nitrogen and sulfur emissions, vegetation effects from ozone exposure, ecolog ical effects from mercury deposition, and climate effects. 1 Despite our goal to quantify and monetize as many of the benefits as possible for the revised primary standard, the welfare co

- benefits of the revised primary standard remain unquantified and nonm onetized in this RIA due to data, methodology, and resource limitations. Specifically, we do not have air quality model runs for the regulatory baseline and the alternative standard levels that would allow us to calculate the visibility co

- benefits of
atta ining the revised primary standard even though we have a complete methodology for estimating these co

- benefits. However, using the approach described in this chapter, we provide the results of an illustrative analysis in Appendix 6.B using the 2020 base ca se and 2020 control case simulation s that were used to develop the air quality ratios.

6

. 2 Introduction to Welfare Benefits

Illustrative e mission reduction strategies to attain the revised and alternative annual primary standard have numerous documented effects on environmental quality that affect human welfare. The Clean Air Act define s welfare effects to include any non

- health effects, including direct damages to property, either through impacts on material structures or by
soi ling of surfaces, direct economic damages in the form of lost productivity of crops and trees, indirect damages through alteration of ecosystem functions, and indirect economic damages through the loss in value of recreational experiences or the existence value of important

resources. The EPA ’ s Integrated Science Assessments for Particulate Matter (hereafter, “ PM ISA ” ) (U.S. EPA, 2009b ) and )
, NO X /SO X — Ecological Criteria (U.S. EPA, 2008), as well as the Criteria Document for ozone and Ozone (U.S. EPA, 2006 201 2a ) identify numerous physical and ecological effects known to be causally linked to these pollutants. This chapter describes these individual effects and how we would quantify and monetize them if there is enough data to do

1 While we understand that “welfare” can include health and non

- health effects in the economic sense, we use the term “welfare” in this RIA in the same context as the definitions in the Clean Air Act for NAAQS. In practice, welfare benefits represent non

- health effects.

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- 3 so. These welfare effects inclu de changes in visibility, materials damage, ecological effects from PM deposition, ecological effects from nitrogen and sulfur emissions, vegetation effects from ozone exposure, ecological effects from mercury deposition, and climate effects.

These welfare co

- benefits are associated with reductions in emissions of specific pollutants resulting from illustrative e mission reduction strategies to attain the revised and alternative annual primary standard , not the form or intent of any specific standard. Even though the primary standards are designed to protect against adverse effects to human health, the emission reductions have welfare co

- benefits in addition to the direct human health benefits.

The impacts of the illustrative emission reduction strategies ca n be grouped into four categories: directly emitted PM (e.g., metals, organic compounds, dust), reductions of PM 2.5 precursors (e.g., NO x , SO x , VOCs), other ancillary reductions from the illustrative emission reduction strategies (e.g., mercury and CO 2 )
, a nd secondary co

- pollutant formation from PM precursors (e.g., ozone from NO x and VOCs). Regardless of the category, these emission changes are anticipated to affect ambient concentrations and deposition, and consequently affect public welfare. It is theref ore appropriate and reasonable to include all the benefits and

co

- benefits associated with these emission reductions to provide a comprehensive understanding of the likely public impacts of attaining the revised or alternative annual standards. Table 6

- 1 shows the welfare effects associated with the various pollutants (either directly or as a precursor to secondary formation of PM or ozone) that would be reduced by the illustrative emission reduction strategies to attain the revised and alternative annual standard.

Based on the EPA’s previous analyses, we believe the welfare co

- benefits associated with these non

- health benefit categories could be significant (U.S. EPA, 2011b). Despite our goal to quantify and monetize as many of the benefits and co

- benefits as possible, w elfare co

benefits of the revised primary standard remain unquantified and nonmonetized in this RIA due to data, methodology, and resource limitations. Therefore, the total benefits would be larger than we have estimated

. The monetized value of these unquantified effects is represented by adding an unknown “ B, ” which includes both unmonetized health benefits and welfare co

benefits , to the aggregate total for the cost

- benefit comparison. These unquantified benefits and co

- benefits may be substantial, although the magnitude is highly uncertain. W e include a qualitative description of the anticipated welfare effects in this chapter to characterize the type and potential extent of those co

- benefits , as identified i n Table 6

- 2.

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- 4 Table 6

- 1. Welfare Effects by Pollutants Potentially Affected by Attainment of the PM

NAAQS

Pollutant Atmospheric Effects Atmospheric and Deposition Effects Deposition Effects

Visibility Impairment Vegetation

Injury (SO 2 ) Vegetation

Injury (Ozone) Materials

Damage Climate Ecosystem

Effects

— (Organics & Metals) Acidification

(freshwater) Nitrogen

Enrichment Mercury

Methylation

Direct PM 2.5    

NO x      

SO 2      

VOCs    

PM 10   
Hg  

CO 2 

 = Welfare category affected by this pollutant.
The remainder of this chapter is organized as follows: Section 6.3 provides a qualitative discussion of the visibility co

- benefits and describes the our approach to estimat e those visibility

co

- benefits . E ven though if we do not have had the data to quantify the visibility co

- benefits using this approach for the revised primary standard , we include this information as a reference for future analyses do so . Sections 6.4 through 6.6 provide qualitative co

- benefits for the unquantified benefits categories of materials damage, climate, and ecosystem effects

. References are provided in Section 6.7. Additional information regarding technical details of the visibility co

- benefits appr oach i s provided in Appendix 6A

. The illustrative visibility co

- benefits results for the specific modeled scenario (not the revised standard scenario) are provided in Appendix 6.B

.

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- 5 Table 6

- 2

. Quantified and Unquantified Welfare Co

- Benefits

Benefits Categ ory Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More

Information Improved Environment Reduced visibility impairment Visibility in Class 1 areas in SE, SW, and CA regions a a Section 6.3 , Appendix 6.B Visibility in Class 1 areas in other regions — a Section 6.3 , Appendix 6.B Visibility in 8 cities

— a Section 6.3 , Appendix 6.B Visibility in other residential areas

— a Section 6.3 , Appendix 6.B
Reduced climate effects Global climate impacts from CO 2 — — Section 6.5, SCC TSD b Climate impacts from ozone and PM — — Section 6.5, Ozone ISA, PM ISA c
Other climate impacts (e.g., other GHGs, other impacts) — — Section 6.5, IPCC c

Reduced effects on materials Household soiling

— — Section 6.4, PM ISA c Materials damage (e.g., corrosion, increased wear) — — Section 6.4, PM ISA c
Reduced effects from PM deposition (metals and organics) Effects on Individual organisms and ecosystems — — Section 6.6.1, PM ISA c

Reduced vegetation and ecosystem effects from exposure to ozone Visible foliar injury on vegetation

— — Section 6.6.4, Ozone ISA c Reduced vegetation growth and reproduction — — Section 6.6.4, Ozone ISA b Yield and quality of commercial forest products and crops — — Section 6.6.4, Ozone ISA b,d Damage to urban ornamental plants — — Section 6.6.4, Ozone ISA c Carbon sequestration in terrestrial ecosystems — — Ozone ISA c

Recreational demand associated with forest aesthetics — — Ozone ISA c

Other non

- use effects Ozone ISA c

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- 6 (continued) Benefits Categ ory Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More

Information Ecosystem functions (e.g., water cycling, biogeochemical cycles, net primary productivity, leaf

- gas exchange, community composition) — — Ozone ISA 2

Table 6

- 2. Quantified and Unquantified Welfare Co

- Benefits (Cont.)

Benefits Category Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More

Information Improved Environment (Cont.) Reduced effects from acid deposition Recreational fishing

— — Section 6.6.2, NO x SO x ISA b Tree mortality and decline

— — Section 6.6.2, NO x SO x ISA c Commercial fishing and forestry effects — — Section 6.6.2, NO x SO x ISA c
Recreational demand in terrestrial and aquatic ecosystems — — Section 6.6.2, NO x SO x ISA c
Other non

- use effects Section 6.6.2, NO x SO x ISA c Ecosystem functions (e.g., biogeochemical cycles) — — Section 6.6.2, NO x SO x ISA c
Reduced effects from nutrient enrichment Species composition and biodiversity in terrestrial and estuarine ecosystems — — Section 6.6.2, NO x SO x ISA c

Coastal eutrophication

— — Section 6.6.2, NO x SO x ISA c
Recreational demand in terrestrial and estuarine ecosystems — — Section 6.6.2, NO x SO x ISA c
Other non

- use effects Section 6.6.2, NO x SO x ISA c Ecosystem functions (e.g., biogeochemical cycles, fire regulation) — — Section 6.6.2, NO x SO x ISA c

Reduced vegetation effects from ambient exposure to SO 2 and NO x Injury to vegetation from SO 2 exposure — — Section 6.6.2, NO x SO x ISA c Injury to vegetation from NO x exposure — — Section 6.6.2, NO x SO x ISA c Reduced ecosystem effects from exposure to methylmercury (through the Effects on fish, birds, and mammals (e.g., reproductive effects) — — Section 6.2 and 6.6.3, Mercury Study RTC c,d

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- 7 Benefits Category Specific Effect Effect Has Been Quantified Effect Has

Been Monetized More

Information role of sulfate in methylation) Commercial, subsistence and recreational fishing — — Section 6.2 and 6.6.3, Mercury Study RTC c

a We quantify these co

- benefits in a n illustrative analysis using the methods discussed in this chapter for the specific modeled scenario. These results are provided in Appendix 6.B , but these results of that illustrative scenario are not an estimate of the co

- benefits for the revised primary standard

. b We assess these co

- benefits qualitative ly due to time and resource limitations for this RIA

. c We assess these co

- benefits qualitatively because we do not have sufficient confidence in available data or methods.
d We assess these co

- benefits qualitatively because current evidence is only suggestive of causality or there are other significant concerns over the strength of the association.

6

. 3 Visibility Co

- Benefits Approach

6

. 3 .1 Visibility and Light Extinction Background

The illustrative emission reduction strategies designed to attain the revised and alternative annual standards would reduce emissions of directly emitted PM 2.5 as well as
pr ecursor emissions such as NO x and SO 2 for an alternative annual standard at 11 μg/m 3

. These emission reductions would improve the level of visibility because these suspended particles and gases impair visibility by scattering and absorbing light (U.S. EPA, 2009b). Visibility is also referred to as visual air quality (VAQ)
, 2 and it directly affects people ’ s enjoyment of a variety of daily activities (U.S. EPA, 2009b). Good visibility increases quality of life where individuals live and work, and where they travel for recreational activities, including sites of unique public value, such as the Great Smoky Mountains National Park (U. S. EPA, 2009b). This section d iscusses the economic co

- benefits associated with improved visibility as a result of emission reductions associated with the revised and alternative annual standards.

Air pollution affects light extinction, a measure of how much the components of the
atmos phere scatter and absorb light. More light extinction means that the clarity of visual images and visual range is reduced, all else held constant

. Light extinction is the optical characteristic of the atmosphere that occurs when light is either scattered or absorbed, which converts the light to heat. Particulate matter and gases can both scatter and absorb light. Fine particles with significant light

- extinction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil (Sisler, 199 6). The extent to which any amount of light extinction

2 We use the term VAQ to refer to the visibility effects caused solely by air quality conditions, excluding fog.

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- 8 affects a person ’ s ability to view a scene depends on both scene and light characteristics. For example, the appearance of a nearby object (e.g., a building) is generally less sensitive to a change in light extinction than the appearance of a similar object at a greater distance. See Figure 6

- 1 for an illustration of the important factors affecting visibility.

According to the PM ISA, there is strong and consistent evidence that PM is the overwhelming s ource of visibility impairment in both urban and remote areas (U.S. EPA, 2009b). After reviewing all of the evidence, the PM ISA concluded that the evidence was sufficient to conclude that a causal relationship exists between PM and visibility impairment.

Figure 6

- 1. Important Factors Involved in Seeing a Scenic Vista (Malm, 1999)

Visibility is commonly measured as either light extinction (β ext ), which is defined as the loss of light per unit of distance in terms of inverse megameters (Mm - 1 ), or using the deciview (dv) metric, which is a logarithmic function of extinction (Pitchford and Malm, 1994). Deciviews, a unitless measure of visibility, are standardized for a reference distance in such a way that one

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- 9 deciview corresponds to a change o f about 10% in available light. 3 Pitchford and Malm (1994) characterize a change of one deciview as “ a small but perceptible scenic change under many
circumstances. ” 4 Extinction and deciviews are both physical measures of the amount of visibility impairmen t (e.g., the amount of “ haze ” ), with both extinction and deciview increasing as the amount of haze increases. Using the relationships derived by Pitchford and Malm (1994),

(6.1)

where VR denotes visual range ( in kilometers) and β ext denotes light extinction (in Mm - 1 ). 5

Annual average visibility conditions (reflecting light extinction due to both anthropogenic and non

- anthropogenic sources) vary regionally across the U.S. and by season (U.S. EPA, 2009b). Particulate sulfate is the dominant source of regional haze in the eastern U.S

. (>50% of the particulate light extinction) and an important contributor to haze elsewhere in the country (>20% of particulate light extinction) (U.S. EPA, 2009b). Particulate n itrate is an important contributor to light extinction in California and the upper Midwestern U.S., particularly during winter (U.S. EPA, 2009b). Smoke plumes from large wildfires dominate many of the worst haze periods in the western U.S., while Asian dus t only caused a few of the worst haze episodes, primarily in the more northerly regions of the west (U.S. EPA, 2009b). Higher visibility impairment levels in the East are due to generally higher concentrations of fine particles, particularly sulfates, and higher average relative humidity levels (U.S. EPA, 2009b). Humidity increases visibility impairment because some particles such as ammonium sulfate and ammonium nitrate absorb water and form droplets that become larger when relative humidity increases, thu s resulting in increased light scattering (U.S. EPA, 2009b).

3 Note that deciviews are inversely related to visual range, such that a decrease in deciviews implies an increase in visual range (i.e., improved visibility). Conversely, an increase in deciviews implies a decreas e in visual range (i.e., decreased visibility). Deciview, in effect, is a measure of the lack of visibility.
4 An instantaneous change of less than 1 deciview (i.e., less than 10% in the light extinction budget) represents a measurable improvement in visib ility but may not be perceptible to the eye. The visibility co

- benefits analysis approach described in this chapter reflects annual average changes in visibility, which are likely made up of periods with changes less than one deciview and periods with chang es exceeding one deciview. Annual averages appear to more closely correspond to the economic literature relied upon for valuation of visibility changes in this analysis. T he secondary PM NAAQS uses a different averaging time than the benefits analysis (see Chapter 13)

. 5 It has been noted that, for a given deciview value, there can be many different visual ranges, depending on the other factors that affect visual range

— such as light angle and altitude. See Appendix 6a for more detail.

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- 10 Reductions in air pollution from implementation of various programs associated with the Clean Air Act Amendments of 1990 (CAAA) provisions have resulted in substantial improvements in visibility, and will continue to do so in the future. Because trends in haze are closely associated with trends in particulate sulfate and nitrate due to the simple relationship between their concentration and light extinction, visibility trends have improved as emis sions of SO 2 and NO x have decreased over time due to air pollution regulations such as the Acid Rain Program (U.S. EPA, 2009b). For example, Figure 6

- 2 shows that visual range increased nearly 50% in the eastern U.S. since 1992. 6 The EPA’s r ecent regulatio ns such as the Cross

- State Air Pollution Rule (U.S. EPA, 2011 c ) and the Mercury and Air Toxics Standard (U.S. EPA, 2011 d ) are anticipated to reduce SO 2 emissions down to 2 million tons nationally, which would lead to substantial further improve ment in visi bility levels in the Eastern U.S

. Calculated from light extinction efficiencies from Trijonis et al. (1987, 1988), annual average visual range under natural conditions in the East is estimated to be 150 km ± 45 km (i.e., 65 to 120 miles) and 230 km ± 35 km (i.e., 120 to 165 miles) in the West (Irving, 1991). Figure 6

- 2 reflects the average trends in visual ranges at select monitors in the eastern and western areas of the U.S. since 1992 using data from the IMPROVE monitoring network (U.S. EPA (2008) updated ; IMPROVE (2010)). As an illustration of the improvements in visibility att ributable to the CAAA, Figure 6

- 3 depicts the modeled improvements in visibility associated with all the CAAA provisions in 2020 compared to a counterfactual scenario without the CA AA (U.S. EPA, 2011b). While visibility trends have improved in most National Parks, the recent data show that these areas continue to suffer from visibility impairment beyond natural background levels (U.S. EPA, 2009b).

6 In Figure 6

- 2, the “ best days ” are defined as the best 20% of days, the “ mid

- range days ” are defined as the middle 20%, and the “ worst days ” are defined as the worst 20% of days (IMPROVE, 2010).

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- 11 Figure 6

- 2. Visibility in Selected National Parks and Wilderness Areas in the U.S., 1992

–

20 08 a,b
(Source: U.S. EPA (2008) updated, IMPROVE (2010))

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- 12 Figure 6

- 3. Estimated Improvement in Annual Average Visibility Levels Associated with the

CAAA Provisions in 2020

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- 13 Source: U.S. EPA, 2011b 7

6. 3

. 3 Quantifying Light Extinction for Assessing Visibility Co

- benefits
For this RIA, we do not have air quality model runs for the regulatory baseline and the alternative standard levels that would allow us to calculate the visibility co

- benefits o f attaining the revised primary standard. However, we provide an illustrative analysis in Appendix 6.B using the 2020 base case and 2020 control case simulations that were used to develop the air quality ratios. 8 In our approach , we generate light extincti on estimates using the CMAQ model in conjunction with the IMPROVE (Interagency Monitoring of Protected Visual Environments) algorithm that estimates light extinction as a function of PM concentrations and relative humidity levels (U.S. EPA, 2009b). 9 The procedure for calculating light extinction associated with the revised and alternative annual s tandards is described in detail in Chapter 3 of th is RIA. In addition, Appendix 6.A describes how the spatial resolution of the light extinction estimates

w ould be adjusted in our approach

. It is important to note that the light extinction estimates used in our approach represent annual averages, which is different from the averaging times currently being considered for the secondary PM NAAQS. While the annua l averages are influenced by days with extremely impaired visibility, the light extinction data is not sufficient to provide higher temporal resolution than quarterly averages. While we suspect that the most impaired days would have disproportionately impr oved visibility from the emission reductions associated with attaining the revised or alternative primary standards, we are not able to quantify those impacts. These data gaps result in an underestimate of visibility co

- benefits associated with extreme day s. We recognize that recent advice from the Science Advisory Board’s Advisory Council on Clean Air Compliance Analysis ( SAB

- Council ) recommends estimating visibility co

- benefits considering daytime visibility on days with severe impairment (U.S. EPA

- SAB, 2 010 a ), but the available data and valuation studies do not allow such fine temporal resolution.

7 It is important to note that visibility levels shown in these maps were mo deled differently than the modeling conducted for this analysis using an earlier method that we would currently use , including coarser grid resolution (i.e., 36 km instead of 12 km). Please In addition, please note that these maps present annual average vis ibility levels , which are different than the short

- term averages being considered for the secondary standard

. 8 These simulations are described in Chapter 3.
9 According to the PM ISA, the IMPROVE algorithm performs reasonably well despite its simplicity ( U.S. EPA, 2009b).

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- 14 While our approach is a substantial improvement in the methods to estimat e light extinction nationally, we are still developing a method to estimate coarse particle concentrations for the entire continental U.S. for estimating light extinction. As an interim solution, our approach includes sensitivity analyses to show the potent ial impact of omitting coarse particles from the light extinction estimates for recreational and residential visibility . For the s e sensitivity analys e s, we selected the levels of coarse particles to represent the full range of possible annual concentration s from a recent report on the IMPROVE monitoring network (Debell et al., 2006). Specifically, for these sensitivity analyses, we assume four levels of coarse particles: no coarse particles, 5 μg/m 3 nationwide, 15 μg/m 3 in the Southwest with 5 μg/m 3 in the rest of the country, and 15 μg/m 3 in the Southwest with 8 μg/m 3 in the rest of the country. 10 In Table 6

- 3, we provide a qualitative assessment of how key assumptions in the estimation of light extinction would affect the visibility co

- benefits.

Table 6

- 3

. Key Assumptions in the Light Extinction Estimates Affecting the Visibility Co

Benefits Approach a

Key Assumption Direction of Bias Magnitude of Effect
The light extinction estimates are annual averages to correspond with the valuation studies. People may value large changes to the haziest days differently than small changes to many days. We assume that annual average light extinction is the most appropriate temporal scale for estimating visibility benefits. Potential Underestimate Medium

Coarse particles are a component of light extinction, but we were unable to include coarse particles in the light extinction estimates. We provide sensitivity analyses with up to 15 μg/m 3 in the Southwest and 8 μg/m 3 in the rest of the country. Potential Overestimate Very Low

a A description of the classifications for magnitude of effects can be found in Appendix 5.B of this RIA

.

10 We define “ Southwest ” for this sensitivity analysis to be the states of California, Nevada, Utah, Arizona, New Mexico, Colorado, and Texas.

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- 15 6

. 3

. 3 Visibility Valuation Overview In the Clean Air Act Amendments of 1977, the U.S. Government recognized visibility ’ s value to society by establishing a national goal to protect national parks and wilderness areas from visibility impairment caused by manmade pollution. 11 Air pollution impairs visibility in both residential and recreational settings, and an individual ’ s willingness to pay (WTP ) to improve visibility differs in these two settings. Benefits of residential visibility relate to the impact of visibility changes on an individual ’ s daily life (e.g., at home, at work, and while engaged in routine recreational activities). Benefits of r ecreational visibility relate to the impact of visibility changes manifested at parks and wilderness areas that are expected to be experienced by recreational visitors.

Both recreational and residential visibility benefits consist of use values and nonuse values. Use values include the aesthetic benefits of better visibility, improved road and air safety, and enhanced recreation in activities like hunting and birdwatching. Nonuse values are based on a belief that the environment ought to exist free of human

- induced haze. This includes the value of better visibility for use by others now and in the future (bequest value). Nonuse values may be more important for recreational areas, particularly national parks and
monuments.

The relationship between a household ’ s WTP and changes in visibility can be derived from a number of contingent valuation (CV) studies published in the peer

- reviewed economics literature. The studies used in the approach to estimate the residential and recreational visibility co

- benefits ass ociated with the revised and alternative annual standards are described in the following sections. In addition to CV studies, hedonic valuation studies ( Beron et al., 2001, 2004) also demonstrate that visibility has value, but we are unable to apply these valuation estimates in the context of estimating the visibility co

- benefits associated with national regulations that reduce air pollution (Leggett and Neumann, 2004)

.
6. 3

. 3.1 Visibility Valuation Approach

In our approach , we assume that individuals value visibility for aesthetic reasons rather than viewing visibility as a proxy for other impacts associated with air pollution, such as health or ecological improvements. Some studies in the literature indicate that individuals may have difficulty distinguishi ng visibility from other aspects of air pollution (e.g., McClelland et al.,

11 See Section 169(a) of the Clean Air Act.

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- 16 1993; Chestnut and Rowe, 1990c; Carson, Mitchell, and Rudd, 1990). Because visual air quality is inherently multi

- attribute, it is a challenge for all visibility valuation studies to isolate the value of visibility from the collection of intertwined benefits. Each study used in our approach attempts to isolate visibility from other effect categories, but the different studies take different approaches (U.S. EPA, 2009b). 12 Because we believe that residual potential for double

counting visibility and health effects is relatively minimal, we would not further adjust the visibility co

- benefits to account for potentially embedded health effects beyond what the studies have already done. Ho wever, t he degree to which the studies were successful in convincing respondents to focus solely on visibility is unclear

Similarly, it is important to try to distinguish residential visibility from recreational visibility co

- benefits, specifically whether these can these can be treated as distinct and additive benefit categories based on the available literature. In our approach , we assume that residential and recreational visibility co

- benefits are distinct and separable. It is conceivable that respondents to the recreational visibility survey may have partially included values for their own residential visibility when evaluating changes at national parks and wilderness areas located in their region of the country. In our app roach, we take care to minimize the number of overlapping areas and their contributions. Specifically, we believe that the potential for double

counting recreational and residential visibility is minimal for several reasons. First, in our approach, we only include a subset of areas in the primary estimates of recreational and residential visibility co

- benefits, which overlap in only a few places. 13 Second, a number of the overlapping counties are wilderness areas, which would contribute little to the overall monetized visibility co

- benefits due to low visitation rates, rather than highly visited national parks. For example, Los Angeles County is home to the San Gabriel Wilderness Area, which has 10 thousand annual visitors (NPS, 2008). If we were to exclude t he residential visibility co

benefits that accrue to 10 million residents in Los Angeles County and only include the very small recreational visibility co

- benefits for the wilderness area, we would be substantially biasing the overall estimates downward. F or these reasons, we believe that the potential for double

- counting is minimal.

In the next sections, we describe the methodology and limitations of the recreational and residential visibility approach . Consistent with the health benefits analysis, the mon etized

12 See Leggett and Neumann (2004) for a more detailed discussion of this issue.
13 As described in detail in Sections 6.3.3 and 6.3.4, our approach includes only a subset of visibility co

- benefits in the primary main benefits estimates, while providing the res t of the visibility co

- benefits in sensitivity analyses.

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- 17 visibility co

- benefits would be adjusted for inflation and income growth. These co

- benefits would be specific to the analysis year , and as population and income increase over time, these

co

- benefits would be expected to increase each year for the sa me incremental change in light
extinction.

6

. 3

. 4 Recreational Visibility

6

. 3

. 4 .1 Methodology

Our approach for estimating recreational visibility co

- benefits is well

- establis hed and has been used in numerous analyses by the EPA (U.S. EPA, 1999; 2005 ; 20 06 ; 2010; 2011b). In our approach , recreational visibility co

- benefits apply to Class 1 areas, such as National Parks and Wilderness Areas. 14 Although other recreational settings such as National Forests, state parks, or even hiking trails or roadside areas hav e important scenic vistas, a lack of suitable economic valuation literature to identify these other areas and/or a lack of visitation data prevents us from generating estimates for those recreational vista areas.

Under the 1999 Regional Haze Rule (64 FR 35 714), states are required to set goals develop long

- term strategies to improve visibility in Class 1 areas, with the goal of achieving natural background visibility levels by 2064. In conjunction with the U.S. National Park Service (NPS), the U.S. Forest S ervice (USFS), other Federal land managers, and State organizations in the U.S., the EPA has supported visibility monitoring in national parks and wilderness areas
since 1988. The monitoring network known as IMPROVE includes 156 sites that represent the Cl ass 1 areas across the country (U.S. EPA, 2009b). 15 The IMPROVE monitoring network measures fine particles, coarse particles, and key PM 2.5 constituents that affect visibility, such as sulfate, nitrate, organic and elemental carbon, soil dust, and several other elements. Figure 6

- 4 identifies where each of these parks are located in the U.S.

14 Hereafter referred to as Class 1 areas, which are defined as areas of the country such as national parks, national wilderness areas, and national monuments that have been set aside under Section 16 9(a) of the Clean Air Act to receive the most stringent degree of air quality protection. Mandatory Class 1 federal lands fall under the jurisdiction of three federal agencies, the National Park Service, the Fish and Wildlife Service, and the Forest Servic e. EPA has designated 156 areas as mandatory Class 1 federal areas for visibility protection, including national parks that exceed 6,000 acres and wilderness areas that exceed 5,000 acres (40 CFR § 81.400 ).
15 The formula used to estimate light extinction from concentrations of PM constituents and relative humidity is referred to as the IMPROVE algorithm.

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- 18 Figure 6

- 4. Mandatory Class 1 Areas in the U.S.

F or recreational visibility, the EPA has determined that only one existing study provides adequate monetary estimates of the value of changes in recreational visibility: relies upon a contingent valuation (CV) survey conducted in 1988 ( Chestnut and Rowe , 199 0a; 1990b ). ) to estimate the recreational visibility co

- benefits

. Although there are several other studies in the literature on recreational visibility valuation, they are even older and use less robust methods.
In the EPA ’ s judgment , despite the inherent limitations in the survey , the Chestnut and Rowe study contains many of the elements of a valid CV study and is sufficiently reliable to serve d as the basis for monetary estimates of the co

- benefits of visibility changes in recreational areas for a number of previous EPA rulemakings

. e E ven though this specific report has not been published in a peer

- reviewed journal

. , these data were subjected to peer review as part of the National Acid Precipitation Assessment Program (NAPAP) and have been applied to estimate visibility benefits in several peer

- reviewed journal articles (Chestnut and Dennis, 1997; Burtraw et al., 1998; Delucchi et al, 2002; Chestnut and Mills, 2005) , as well as several peer reviewed in

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- 19 reports ( NAPAP, 1991; SAMI, 2002 ; U.S. EPA, 1999b; 2011b )

. 16 This study serves as an essential input to our approach for estimating the co

- benefits from improving recreational visibility.

In our approach , we assume that the household WTP is higher if the Class 1 recreational area is located close to the person ’ s home (i.e., in the same region of the country). People appear to be willing to pay more for visibility improvements at parks and wilderness areas that are in the same region as their household than at tho se that are not in the same region as their household (Chestnut and Rowe, 1990a, 1990b). This is plausible, because people are more likely to visit, be familiar with, and care about parks and wilderness areas in their own part of the country. However, stud ies have also found many people who had never visited and never planned to visit the parks still had positive values for visibility improvements in those locations (Chestnut and Rowe, 1990b).

The Chestnut and Rowe survey measured the demand for visibility in Class 1 areas managed by the NPS in three broad regions of the country: California, the Colorado Plateau (Southwest), and the Southeast. 17 Respondents in five states were asked about their WTP to protect national parks or NPS

- managed wilderness areas wit hin a particular region. The survey used photographs reflecting different visibility levels in the specified recreational areas. The authors used the survey data to estimate household WTP values for improved visibility in each region.

16 In 1999, as part of The Benefits and Costs of the Clean Air Act, 1990

– 2010 (U.S. EPA, 1999b), the EPA asked the SAB

- Council whether they concurred wit h the EPA’s SAB stated, “ proposed use of the WTP values from Chestnut and Rowe (1990a,b) to support the main (“primary”) benefit estimate. The SAB

- Council responded, “[t]he Council believes that EPA should rely on the peer

- reviewed literature as the basis for its regulatory analyses. Although many members of the Council believe that the Chestnut and Rowe study is the best available [study for , we believe that the general principle should be adhered to.” ” (U.S. EPA

- SAB, 1999). In response to this comment
, the EPA clarified to the SAB

- Council that the visibility valuation functions and the sources of estimates for the coefficients for the functions were originally developed as part of NAPAP and were subjected to peer review as part of that program (Chestnu t and Rowe, 1990c). The Integrated Assessment Report , including the data contained therein, received several rounds of public and peer review (NAPAP, 1991). After this clarification, the SAB

- Council identified no concerns in their final review letter with the EPA using the Chestnut and Rowe data to quantify recreational visibility valuation]” benefits in the main benefits estimate (U.S. EPA

- SAB, 1999 b ). In July 2010, the SAB as part of The Benefits and Costs of the Clean Air Act 1990 to 2020 (U.S. EPA, 2011b ), the SAB

Council stated that the studies were dated, but the EPA “used what the Council understands to be the only relevant studies” (U.S. EPA

- SAB, 2010). 2010a). In addition, the SAB

- Council identified no concerns with quantifying recreational visibility benefits using these data in the main benefits estimate (U.S. EPA

- SAB, 2010a).
17 The Colorado Plateau (Southwest) region is defined as the states of Colorado, New Mexico, Arizona, and Utah. The Southeast region is defined as the states of West Virginia, Virginia, North Carolina, South Carolina, Georgia, Florida, Alabama, Mississippi, Louisiana, Tennessee, and Kentucky. The California region includes the state of California and one wilderness area in Nevada.

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- 20 The separate regions were developed to capture differences in household WTP values based on proximity to recreational areas. Chestnut (1997) also concluded that, for a given region, a substantial proportion of the WTP is attributable to one specific park within the region. Thi s so called “ indicator park ” is the most well

- known and frequently visited park within a particular region. The indicator parks for the three studied park regions are Yosemite National Park for the California region, the Grand Canyon National Park for the Southwest region, and Shenandoah National Park for the Southeast region. In accordance with the methodology in Chestnut (1997), our approach calculates the benefits from households for a particular region for a given change in visibility at a particular Class 1 area. In theory, summing benefits from households in all regions would yield the total monetary benefits associated with a given visibility improvement at a particular park, which could then be summed with other parks and regions to estimate nation al benefits. Because recreational visibility benefits may reflect the value an individual places on visibility improvements regardless of whether the person plans to visit the park, all households in the U.S. are assumed to derive some benefit from improve ments to Class 1 areas.
To value recreational visibility improvements associated with its rulemakings, the EPA developed a valuation WTP equation function based on the baseline of visibility, the magnitude of the visibility improvement, and household incom e. This function requires light extinction estimates measured as visual range. The behavioral parameters of this equation were taken from an analysis of the survey described in Chestnut and Rowe (1990a, 1990b). These parameters were used to calibrate WTP f or the visibility changes resulting from this rule. 18 As an example, household WTP for a visibility improvement at a park in its region takes the following form:

(6.2)

where:
i indexes region,

k indexes park,
m = household income,

18 The parameters for each region are available in Appendix 6a of this RIA.

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- 21 ρ = shape parameter (0.1),
γ = parameter corresponding to the visibility at in

- region parks,

Q 0 = starting visibility, and

Q 1 = visibility after change.

As discussed in more detail in Appendix 6 .A of this RIA, our approa ch to valuing recreational visibility changes is an application of the Constant Elasticity of Substitution (CES) utility function approach and is based on the preference calibration method developed by Smith, Van Houtven, and Pattanayak (2002). 19 Available evidence indicates that households are willing to pay more for a given visibility improvement as their income increases (Chestnut, 1997). Using the income elasticity calculated by Chestnut (1997), the recreational visibility benefits assume a 1% increase i n income is associated with a 0.9% increase in WTP for a given change in visibility. WTP responses reported in Chestnut and Rowe (1990a, 1990b) were also region

- specific, rather than park

- specific. As visibility improvements are not constant across all
par ks in a region, we must infer park

- specific visibility parameters in order to calculate WTP for projected visibility changes. As the quantity and quality of parks differs between regions, we apportion the regional WTP parameters based on relative visitatio n rates at the different parks, because this statistic likely captures both park quality (more people visit parks with more desirable attributes, so collective WTP is likely higher) and quantity (more people visit parks in a region if the parks are more nu merous, so collective WTP is likely higher). 20 We also adjust the

co

- benefits for inflation and growth in real income.

Recreational visibility co

- benefits can be calculated as the sum of the household WTPs for changes in light extinction. We assume that each household is valuing the first or only visibility change that occurs in a particular area. The co

- benefits at particular areas can be calculated by assuming that the subset of visibility changes of interest is the first or the only set

19 The Constant Elasticity of Substitution utility function has been chosen for use in this analysis due to its flexibility when illustrating the degree of substitutability present in various economic relationships (in this case, the tradeoff between income and improvements in visibility).
20 We use 2008 park visitation data from the National Park Service Statistical Abstracts (NPS, 2008), as this is the most current data available. Where the data for a particular park was not repr esentative of normal visitation rates at that park (for example due to fire damage that occurred during that year), we substitute data from the prior year. We use 1997 visitation data for those wilderness areas not included in the National Park Service Sta tistical Abstracts, as more current data is not readily available. As visitation rates for Wilderness Areas are small compared to visitation rates in National Parks, the inaccuracies generated by using 1997 data are likely to also be small.

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- 22 of changes bein g valued by households. Estimating benefit components in this way will yield slightly upwardly biased estimates of co

- benefits , because disposable income is not reduced by the WTPs for any prior visibility improvements. The upward bias should be extremely small, however, because all of the WTPs for visibility changes are very small relative to income.

In our approach, t he primary estimate for recreational visibility only includes co

- benefits for 86 Class 1 areas in the original study regions (i.e., Californ ia, the Southwest, and the Southeast). 21 These co

- benefits reflect the value to households living in the same region as the Class 1 area as well as values for all households in the United States living outside the state containing the Class 1 area.

The Ches tnut and Rowe study did not measure values for visibility improvement in Class
1 areas in the Northwest, Northern Rockies, and Rest of U.S. regions. 22 In order to obtain estimates of WTP for visibility changes for the 70 additional Class 1 areas in these no n

- studied regions, we have to transfer the WTP values from the studied regions. 23 This co

- benefits transfer approach introduces additional uncertainty into the estimates. However, we have taken steps to adjust the WTP values to account for the possibility that a visibility improvement in parks within one region may not necessarily represent the same visibility improvement at parks within a different region in terms of environmental improvement. This may be due to differences in the scenic vistas at differen t parks, uniqueness of the parks, or other factors, such as public familiarity with the park resource. To account for this potential difference, we adjusted the transferred WTP being transferred by the ratio of visitor days in the two regions. 24 A complete description of the co

- benefits transfer method used to infer values for visibility changes in Class 1 areas outside the study regions is provided in Appendix 6a of this RIA.

Table 6

- 4 indicates which studied park regions we used to estimate the value in the non

studied park regions in our approach

. Figure 6

- 5 shows how the visitation rates vary across Class 1 areas and regions and indicates whether each Class 1 area is located within one of the studied regions.

21 The 86 Class 1 areas in the three studied park regions represented 68% of the total visitor days to Class 1 areas in 2008 (NPS, 2008).
22 The Northwest region is defined as the states of Washington and Oregon. The Northern Rockies region include s the states of Idaho, M ontana, Wyoming, North Dakota, and South Dakota. The Rest of the U.S. region includes all other states not included in the other 5 regions.
23 The 70 additional Class 1 areas represented 32% of the total visitor days to Class 1 areas in 2008 (NPS, 2008).
24 For example, if total park visitation in a transfer region was less than visitation in a study region, transferred WTP would be adjusted downward by the ratio of the two.

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- 23 Table 6

- 4. WTP for Visibility Improvements in Class 1 Areas in Non

- Studied Park Regions

Park Region Source of WTP Estimate

1. Northwest Benefits trans fer from California

2. Northern Rockies Benefits transfer from Colorado Plateau

3. Rest of U.S. Benefits transfer from Southeast

Figure 6

- 5. Visitation Rates and Park Regions for Class 1 Areas a

a The a The colors in this map correspond to the park regions used in the valuation study and the extrapolation to parks in other regions. Red = California, light red = Northwest (extrapolated from California), blue = Colorado Plateau, light blue = Northern Rockies ( extrapolated from Colorado Plateau), green = Southeast, light green = Rest of U.S. (extrapolated from Southeast).
In a more recent study, Smith et al. (2005) conducted a contingent valuation survey that updated and expanded a portion of the 1988 survey by Chestnut and Rowe (1990). Specifically, the Smith et al. (2005) survey relied on a demographically representative national panel maintained by Knowledge Networks with 2,020 participants completing the survey. Similar to the Chestnut and Rowe survey, the Sm ith et al. survey assessed WTP for changes in summertime visibility using the base photograph of Shenandoah National Park. Unlike the ys

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- 24 Chestnut and Rowe survey, the Smith et al. survey only assessed the Shenandoah National Park, did not estimate in

- region e stimates of WTP, and evaluated several options for incorporating budgetary constraints into the survey. The authors concluded that WTP for recreational visibility is skewed and sensitive to information about budgetary constraints. We are still evaluating t he potential error identified by Smith et al. (2005) regarding the visibility levels in the photographs for Shenandoah National Park in the Chestnut and Rowe survey (1990a,b).

Even though this survey represents several advantages over the older survey (e.g ., more recent, national, demographically representative, larger sample, etc

. ), we are unable incorporate the results generated by this survey into our existing method for calculating recreational visibility co

- benefits because the survey did not account f or the differences between WTP for in

- region parks and out

- of

- region parks. This omission precludes us from combining this new survey for only 1 region of the country with the WTP for the other regions of the country from Chestnut and Rowe (1990). Furtherm ore, Smith et al. (2005) provide a variety of WTP estimates reflecting different versions of the survey and different methods of summarizing the typical response, which makes it difficult to select estimates to incorporate into the recreational visibility benefits calculation.

6

. 3

. 4 .2 Recreational Visibility Limitations, Caveats, and Uncertainties
Our approach relies upon several data sources as inputs, including emission inventories, air quality data from models (with their associated parameters and input s), relative humidity measurements, park information, economic data and assumptions for monetizing co

- benefits

. Each of these inputs may contain uncertainty that would affect the recreational visibility co

benefits estimates. Though we are unable to quanti fy the cumulative effect of all of these
uncertainties in our approach , we do provide information on uncertainty based on the available data, including model evaluation 25 and sensitivity analyses to characterize major omissions ( i.e., benefits from parks in non

- studied park regions and inclusion of coarse particles). Although we strive to incorporate as many quantitative assessments of uncertainty as possible, we are severely limited by the available data, and there are several aspects that we are only able to address qualitatively. A summary of the key assumptions including direction and magnitude of bias is provided in Table 6

- 5

.

25 See Chapter 4 for more information on model evaluation.

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- 25 One major source of uncertainty for the estimation of recreational visibility co

- benefits is the benefits transfer process. Choic es regarding the functional form and key parameters of the estimating equation for WTP for the affected population could have significant effects on the magnitude of the estimates. Assumptions about how individuals respond to changes in visibility that are either very small or outside the range covered in the Chestnut and Rowe study could also affect the estimates.

Table 6

- 5

. Summary of Key Assumptions in Estimating R ecreational Visibility Co

- benefits a

Key Assumption Direction of Bias Potential Magnitude of Effect
Chestnut and Rowe study covers parks in three regions: California, Southwest, and Southeast. Benefits to other regions in the U.S. are not included in the primary benefits estimate. Underestimate Medium

Benefits to other recreational settings, such as National Forests and state parks, are not included in our approach

. Underestimate Medium

- Low

Chestnut and Rowe study conducted on populations in five states. These results are applied to the entire U.S. population. Unclear Unclear

Individuals have a greater WTP for visibility changes in parks within their region. Unclear Unclear

WTP values reflect only visibility improvements and not overall air quality improvements. Potential Overestimate Unclear

W e assume that there are 2.68 people per household. Because this estimate has been decreasing over time, this may underestimate the number of households. Potential Underestimate Medium

- Low

a A a A description of the classifications for magnitude of effects can be found in Appendix 5.B of this RIA

. Since the valuation of recreational visibility co

- benefits relies upon one study (Chestnut and Rowe, 1990a; 1990b), all of the uncertainties within that study also pertain to any analysis that uses it

. In general, the survey design and implementation reflect the period in which the Chestnut and Rowe study was conducted. Since that time, many improvements to the design of stated preference surveys have been developed (e.g., Arrow, 1993) , but we are currently unaware of newer studies that we could incorporate into our visibility co

- benefits methodology

. Although Chestnut and Rowe still offers the best available WTP estimates, the study has a number of limitat ions, including:

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- 26  The vintage of the survey (late 1980s) invites questions whether the values would still be valid for current populations, or more importantly for our approach , future populations in 2020.

 The survey focused on visibility improvements in an d around specific national parks and wilderness areas. Given that national parks and wilderness areas exhibit unique characteristics, it is not clear whether the WTP estimate obtained from this survey can be transferred to other national parks and wilderne ss areas, even other parks within the studied park regions, without introducing additional uncertainty.

 The survey focused only on populations in five states, so the application of the estimated values to populations outside those states requires that pref erences of populations in the five surveyed states be similar to those of non

- surveyed states.

 There is an inherent difficulty in separating values expressed for visibility improvements from an overall value for improved air quality. The survey attempted t o control for this by informing respondents that “ other households are being asked about visibility, human health, and vegetation protections in urban areas and at national parks in other regions. ” However, most of the respondents did not feel that they we re able to segregate recreational visibility at national parks entirely from residential visibility and health effects.

 It is not clear exactly what visibility improvements the respondents to the survey were valuing. The WTP question asked about changes in average visibility, but the survey respondents were shown photographs of only daytime, summer conditions, when visibility is generally at its worst. It is possible that the respondents believed those visibility conditions held year

- round, in which case th ey would have been valuing much larger overall improvements in visibility than what otherwise would be the case. In our approach , the EPA assumed that respondents provided values for changes in annual average visibility. Because most policies would result in a shift in the distribution of visibility (usually affecting the worst days more than the best days), the annual average may not be the most relevant metric for policy analysis.

 The survey did not include reminders of possible substitutes (e.g., visibil ity at other parks) or budget constraints. These reminders are considered to be best practice for stated preference surveys.

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. 3

. 5 Residential Visibility

6

. 3

. 5 .1 Methodology Residential visibility co

- benefits are those that occur from visibility changes in urban, suburban, and rural areas where people live. These co

- benefits are important because s ome

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- 27 people living in certain urban areas may place a high value on unique scenic resources in or near these areas that are outside of Class 1 areas. For example, the State of Colorado established a local visibility standard for the Denver metropolitan area in 1990 (Ely et al., 1991). In our approach , residential visibility improvements are defined as those that occur specifically in Metropo litan Statistical Areas (MSAs).

In the Urban

-

focused Visibility Assessment (U.S. EPA, 2010b) and the Policy Assessment for the Review of the PM NAAQS (U.S. EPA, 2011a), several preference studies provide the foundation for the second ary PM NAAQS. 26 The three completed survey studies (all in the west) included Denver, Colorado (Ely et al., 1991), one in the lower Fraser River valley near Vancouver, British Columbia (BC), Canada (Pryor, 1996), and one in Phoenix, Arizona (BBC Research & Consulting, 2003). A pilot focus group study was conducted in Washington, DC on behalf of the EPA to inform the 2006 PM NAAQS review (Abt Associates Inc., 2001). Although
t hese studies indicate that some individuals considered the visual air quality associ ated with ambient levels of air pollution in urban areas to be unacceptable, the se studies do not provide sufficient information on which to develop monetized co

- benefits estimates. Specifically, the public perception studies do not provide preferences exp ressed in dollar values, even though they do suggest that the co

- benefits associated with improving residential visibility are positive

. Studies in the peer

- reviewed literature support a non

- zero value for residential visibility ( e.g., Brookshire et al., 1982; Loehman et al., 1994). Furthermore, Chestnut and Rowe (1990c) conclude that residential visibility co

- benefits are likely to be at least as high as recreational visibility co

- benefits because of the quantity of time most people spend in and near thei r homes and the substantial number of people affected. In previous assessments, the EPA used a study on residential visibility valuation conducted in 1990 (McClelland et al., 1993). Consistent with advice from SAB

- Council , the EPA designated the McClelland et al. study as significantly less reliable for regulatory benefit

- cost analysis, although it does provide useful estimates on the order of magnitude of residential visibility co

- benefits (U.S. EPA

- SAB, 1999). 27 In our

26 For more detail about the se preference studies, including information about study designs and sampling protocols, please see Section 2 of the Particulate Matter Urban

- Focused Visibility Assessment (U.S. EPA, 2010b).
27 EPA ’ s Advisory Council on Clean Air Compliance Analysis noted that the McClelland et al. (1993) study may not incorporate two potentially important adjustments. First, their study does not account for the “ warm glow ” effect, in which respondents may provide higher willingness to pay estimates simply because they favor “ good

causes ” such as environmental improvement. Second, while the study accounts for non

- response bias, it may not employ the best available methods. A s a result of these concerns, the Council recommended that reside ntial visibility be omitted from the overall primary benefits estimate. (U. S. EPA

- SAB, 1999)

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- 28 approach for estimating residential v isibility co

- benefits , we replaced the previous methodology with a new benefits transfer approach and incorporated additional valuation studies. This new approach was developed for The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Con gress (U.S. EPA, 2011) 28 and reviewed by the SAB

- Council (U. S. EPA

- SAB, 2004, 2010 a, 2010b ).

To value residential visibility improvements, the new approach draws upon information from reported in the Brookshire et al. (1979), Loehman et al. (1985) and Tolley et al. (198 4 6 ) studies. 29 Each of the studies provides estimates of household WTP to improve visibility conditions. While uncertainty exists regarding the precision of these older, stated

- preference residential valuation studies, we believe their res ults support the argument that individuals have a non

- zero value for residential visibility improvements. These studies provide primary visibility values for Atlanta, Boston, Chicago, Denver, Los Angeles, Mobile, San Francisco, and Washington D.C. 30

In acco rdance with Chestnut and Rowe (1990c), we utilize the WTP estimates and the associated change in visual range from each study to estimate the β parameter for the eight study areas. The β parameter represents the WTP for a specific improvement in visibility in a specific location. Where studies provide multiple estimates for visual range improvements, we estimate β by regressing the natural log of the ratio of visual range following and prior to improvement against WTP. To express these value estimates in co mparable terms across study

28 This report is also known as the Second Prospective 812 analysis. 29 Loehman et al. ( (1994) and Brookshire et al. (1982) published results in peer

- reviewed journals based on the same underlying data we obtained from Loehman et al. ( 1985) and Brookshire et al. (1979 ) were subsequently published in peer

- reviewed journals (see Loehman et al. (1994) and Brookshire et al. (1982 ). While t he specific details need to compute visibility benefits using Tolley et al. (198 4 6 ) were not included in the published study (likely due to length restrictions in the in a peer

- reviewed journal )
, , the overall work including study and survey design was subject to peer review during study development

. (see Leggett et al and Neumann , 2004 and Patterson et al., 2005 ) ). In addition, Tolley et al. subsequently published a book (Tolley and Fabian, 1988) based on this research, which notes in the preface that the methods were critiqued throughout by various external economists (Tolley et al., 1988). . The EPA does not claim that this external critique necessarily constituted a formal peer review process, but we provide this information for transparency regarding the review of this work. The use of these studies as the only available information to estimate residential visibility co

- benefits in the main estimate was supported by the SAB

- Council (U.S. EPA

- SAB, 1999a, 2010a).
30 Recognizin g potential fundamental issues associated with data collected in Cincinnati and Miami (e.g., see Chestnut et al. (1986) and Chestnut and Rowe (1990c), we do not include values for these cities in our analysis. The 8 MSAs where the valuation studies were co nducted represent 15% of the total US population in 2020 (U.S. Census).

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- 29 locations, we express household WTP for a change in visual range in a specific MSA using the following function:

(6.3)

where:

VR 0 = mean annual visual range in miles before the improvement,

VR 1 = mean an nual visual range in miles after the improvement, and
β = parameter.

Total residential visibility co

- benefits within a particular MSA are driven by visibility improvements, population density, and the WTP value applied. Only those people living within in an MSA are assumed to receive co

- benefits from improved residential visibility. In other words, unlike recreational visibility, we do not assume a non

- use value by people who live outside the MSA for residential visibilit y. Table 6

- 6 provides a summary of these valuation estimates for each study location, as well as an illustrative implied WTP value for a 10% improvement in visual range. As shown, the implied annual per

- household WTP estimates for a hypothetical 10% improv ement ranges from $21 to $220, depending on the study area. It is not surprising that such a range of values exists, as these study areas all feature different landscapes and vistas, populations and prevailing visibility conditions.

Table 6

- 6

. Summary of R esidential Visibility Valuation Estimates

City Study β Estimate Implied WTP for 10% Improvement in Visual Range (1990$, 1990 income) Implied WTP for 10%

Improvement in Visual Range (2006$, 2020 income)

Atlanta Tolley et al. ( 198 4 6 ) 321 $31 $72

Boston Tolley et al. ( 198 4 6 ) 398 $38 $89
Chicago Tolley et al. ( 198 4 6 ) 310 $30 $69

Denver Tolley et al. ( 198 4 6 ) 696 $66 $155
Los Angeles Brookshire et al. (1979) 94 $9 $21

Mobile Tolley et al. ( 198 4 6 ) 313 $30 $70

San Francisco Loehman et al. (1985) 989 $94 $220

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- 30 Washington, DC Tolley et al. ( 198 4 6 ) 614 $59 $137

Similar to recreational visibility co

- benefits , we then incorporate preference calibration using the method developed by Smith, Van Houtven, and Pattanayak (2002), which is discussed in more detail in Appendix 6a of this RIA. This preference calibration is a change since The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress (U.S. EPA, 2011 ) intended to address the SAB

- Council’s concern (U.S. EPA

- SAB, 2010a) regarding the
in consistency regarding household income in the estimation of recreational and residential visibility. To express these “ preference

- calibrated ” value estimates across study locations, we express household WTP for a change in visual range in a specific MSA us ing the following function:

(6

- 4)

where:
m = household income, ρ = shape parameter (0.1), θ = WTP parameter corresponding to the visibility at MSA,

VR 0 = starting visibility, and

VR 1 = visibility after change.

While the primary estimate for residential visibility includes co

- benefits in only the eight MSAs included in the valuation studies, people living in other urban areas also have non

- zero values for residential visibility. For this reason, our approach incl udes a sensitivity analysis for the extrapolated residential visibility in the 351 additional MSAs. 31 Because there is considerable uncertainty about the validity of this benefit transfer approach, these extrapolated co

- benefits are included in a sensitivit y analysis only. This is an important distinction between the approach used in The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress (U.S. EPA, 2011 ), where all cities were included in the total benefits approach. We believe that it is appropriate to deviate from the previous approach in order to be consistent with the approach used to estimate recreational visibility co

- benefits and

31 The 351 additional MSAs plus the 8 study area MSAs represent 84% of the total US population in 2020 (U.S. Census).

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- 31 to recognize the uncertainty associated with extrapolating beyond the studied citie s. Figure 6

- 6 indicates the study cities as well as the assignment of the other MSAs to the study cities.

The degree to which the three studies were successful in convincing respondents to focus solely on visibility is unclear, as none of the three studies includes follow

- up questions necessary to investigate the issue. Furthermore, no other residential visibility CV studies provide evidence regarding the degree to which health effects are embedded in visibility values. Although the McClelland et al. (1991) study has a follow

- up question designed to allocate WTP across several categories, the CV question in the McClelland et al. study was focused on air pollution generally rather than visibility. As a result, we do not adjust the results from these studies t o account for potentially embedded health effects.

There are many factors that could influence WTP for residential visibility, and these factors vary across urban areas. In our approach , we utilize the benefit transfer approach developed for The Benefits a nd Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress (U.S. EPA, 2011 ) report , but we recognize that there are alternative methods that we could have used. We assigned a valuation study area to each MSA based on two factors: geographic proximi ty to one of the eight study cities and elevation. Any MSA with a county elevation above
1 , 500 meters was assigned the Denver valuation instead of the nearest study area. 32 Because residents of Denver have a dramatic view of the Rocky Mountains that is rare ly obstructed by trees, it is plausible that they might have a greater interest in protecting visibility than a city without nearby mountains. The geographic proximity factor is constrained in two areas. The San Francisco valuation study is only assigned t o the six counties in the San Francisco Bay area MSAs because the study is unique among the three regarding the temporal description of visibility conditions, landscape/vistas, and prevailing weather conditions. In addition, the Los Angeles valuation was a ssigned to the Riverside MSA despite exceeding the elevation threshold. 33

32 Elevation data represent the county

- level maximum, which were calculated using the ArcGIS Spatial Analyst tool

“ Zonal Statistics ” using the geographic database HYDRO1K for North America (U.S. Geological Survey, 1997). This dataset and associated documenta tion are available on the Internet at DEMhttp://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/gtopo30/hydro/namerica

. 33 Riverside MSA is assigned to the Los Angeles study area because a significant portion of Riverside County itself is located in t he South Coast Air Quality Management District, which can be considered by to be part of the same regulated airshed as Los Angeles. The geographic assignment is preserved despite exceeding the elevation threshold because Riverside is adjacent to one of the study cities and this region has a particular set of location

specific characteristics that set it apart from Denver.

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- 32 Figure 6

- 6

. Residential Visibility Study City Assignment

6. 3

. 5 .2 Residential Visibility Limitations, Caveats, and Uncertainties
Similar to recreational visibility co

- benefits , there are many data inputs into the residential visibility co

- benefits that contribute to overall uncertainty. Our approach includes sensitivity analyses to characterize major omissions (i.e., co

- benefits in other MSAs and coarse particles). A summary of the key assumptions including direction and magnitude of bias in our approach is provided in Table 6

- 7.

The valuation studies relied upon for the residential visibility co

- benefits , although representing the best available estimates, have a number of limi tations. These include the following:

 The survey design and implementation reflects the period in which the surveys were conducted. Since that time, many improvements to the stated preference methods have been developed.

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- 33  The vintage of the surveys (1970s a nd 1980s) invites questions whether the values are still valid for current populations, or more importantly for our approach , future populations in 2020.

 The survey focused only on populations in eight cities, so the transfer of the WTP estimates values to populations outside those cities requires that their preferences be similar to those in non

- surveyed cities, as well as the visibility attributes be similar across study and transfer MSAs.

 There is an inherent difficulty in separating values expressed for visibility improvements from an overall value for improved air quality. The studies attempted to control for this, but most of the respondents did not feel that they were able to segregate residential visibility entirely from recreational visibility and h ealth effects.

Table 6

- 7

. Summary of Key Assumptions in the Residential Visibility Co

- benefits a

Key Assumption Direction of Bias Magnitude of Effect
Residential and recreational visibility benefits are distinct and separable. Potential Overestimate Medium

- Low

Estimates residential visibility benefits are limited to populations within the boundaries of MSAs. Areas outside of an MSA are not included in our approach

. Underestimate Low

WTP values reflect only visibility improvements and not overall air quality improvements. Potential Overestimate Medium

- Low

WTP values from studies in Atlanta, Boston, Chicago, Denver, Los Angeles, Mobile, San Francisco, and Washington D.C. can be accurately transferred to MSAs across the U.S. based on proximity and elevation Unclear Unclear

We assume that there are 2.68 people per household. Because this estimate has been decreasing over time, this may underestimate the number of households. Potential Underestimate Medium

- Low

a A description of the classifications for magnitude of effects can be found in Appendix 5.B of this RIA

.
6. 3

. 5.3 Using Hedonic Economic Literature to E stimate Visibility Co

- benefits

The hedonic model assumes that consumers d o not value the consumption of a good directly, but rather value the characteristics contained within a good. In the context of property values, the consumer values both the physical attributes of the property (i.e., number of rooms, square footage, etc.) as well as geographic and environmental attributes (e.g., proximity to parks, visibility, etc.). Following the technique developed by Rosen (1974), property

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- 34 characteristics are regressed on the observed price of the properties within a given housing market to estimate the contribution of each characteristic to the overall price.

Numerous studies have applied hedonic methods to estimate the willingness to pay (WTP) for air quality changes (see Smith and Huang (1995) and Boyle and Kiel (2001) for literature reviews), but fewer researchers have focused specifically on visibility. Studies that have estimated the WTP to improve visibility have focused on specific housing markets like Los Angeles (Murdoch and Thayer, 1998; Beron et al., 2001) or San Francisco (Gr aves et al., 1998), and it is unclear if these results would be more broadly applicable to the rest of the county. While the literature demonstrates a link between pollutant concentrations and home

- buying behavior, it is difficult to partition the WTP for changes in pollution between health and aesthetic concerns. Murdoch and Thayer (1998) use visibility as a surr ogate for environmental quality and Beron et al. (2001) acknowledge that their parameter estimates likely reflect a combination of visual aestheti cs and an absence of health effects. Delucchi et al. (2002) deals with this issue by partitioning WTP estimates from a hedonic model into health and visibility components using results from previous contingent valuation studies, and find that the
estimate of visibility co

- benefits is similar to estimates based on contingent valuation alone

.
In 2004, the Advisory Council on Clean Air Compliance Analysis ( SAB

- Council ) recommended that the EPA evaluate the available studies addressing residential visibility a nd consider the possibility of using hedonic property models to estimate residential visibility co

benefits (U.S. EPA

- SAB, 2004). In response to this recommendation, the EPA evaluated the existing economic literature, and determined that there were substan tial limitations that precluded the Agency from using these studies to make inferences regarding individuals ’ WTP for improved visibility (Leggett and Neumann, 2004). Specifically, the literature did not provide support for the assumption that market parti cipants are aware of the spatial variation in visibility, and consider this variation when purchasing a home, and can successfully separate visibility effects from health effects (Leggett and Neumann, 2004). This conclusion is also supported by Delucchi et al

. (2004), which found that hedonic price analysis does not capture all of the health effects of air pollution because homebuyers may not be fully informed about these effects .

Research since 2004 has attempted to address limitations of the hedonic meth od through the use of U.S. Census microdata (Bayer et al., 2009), spatial statistic al methods (Anselin and Le Gallo, 2006; Anselin and L ozana

- Gracia , 2009; Beron et al., 2004; Kim et al.,

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- 35 2010 ) and more complete air quality data and information about nonat tainment status (Chay and Greenstone, 2005). However, none of these studies specifically address visibility, and they are therefore of limited use at this time. While the current state of the literature does not provide a basis for using hedonics

- based app roaches , continued innovations in methodology and the further development of national, micro

- level housing and demographic datasets may open possibilities for national

- scale hedonics

- based benefit analysis in the future.

Regardless of whether we use hedon ic models or stated preference surveys to estimate

co

- benefits arising from improved visibility, it is important to emphasize that estimates of WTP for residential or recreational visibility improvements are not substitutes for health benefits. As previous ly mentioned, people often have difficulty separating their health concerns from their aesthetic concerns when evaluating preferences for visibility, which could overestimate visibility co

- benefits if not properly controlled. However, because we use a dama ge

- function approach to estimate health benefits (see Chapter 5 of this RIA), the health benefits estimates are unaffected by any potential confounding with visibility preferences.

6

. 3

. 6 Discussion of Visibility Co

- benefits
As described in the previous sections of this chapter, the estimation of visibility co

benefits is complex and suffers from unavoidable limitations. While we are confident that the underlying scientific literature supports a non

- zero estimate for visibilit y co

- benefits attributable to emission reductions, we are less confident in the magnitude of those co

- benefits outside of previously studied locations. While acknowledging these limitations, it is important
to note that this general approach was peer inclu ded in The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress (U.S. EPA, 2011 ) , which was reviewed by the SAB

Council (U.S. EPA

- SAB, 2010 a, 2010b ) , and we )

. Although the SAB

- Council highlighted concerns with the visibility approach used in the study, it did not recommend that visibility benefits be excluded. W e have addressed the SAB

- Council’s concern regarding inconsistency between estimation of residential and recreational visibility highlighted by the SAB

- Council in our

a pproach

. However, we do not have the data to address the SAB

- Council’s concern regarding inclu sion of night

- time benefits of visibility improvements in our annual average , which may lead to an underestimation of visibility benefits

. To minimize uncertainti es related to extrapolation and geographical double counting, our approach only include s a subset of monetized visibility co

- benefits in the core monetized visibility co

- benefits estimate to correspond with our higher level of confidence in recreational co

- benefits within the study

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- 36 regions and residential co

- benefits within the study cities. Although we are confident that visibility co

- benefits extend beyond these studied areas, we are less confident about the magnitude of those co

- benefits

. However, it is unclear the degree to which the visibility valuation surveys were successful in contro l l ing for potential double counting embedded health benefits.

Consistent with the approach described in the proposal RIA , we have described a revised approach for estimating visibility co

- benefits , including light extinction estimation methods, visitation data for Class 1 areas (used in extrapolating co

- benefits ) , valuation studies for residential visibility co

- benefits , and the benefit transfer technique for residential co

benefits

. Including residential visibility co

- benefits in the core visibility co

- benefits estimates reflects an evolution in our understanding of the nature and importance of the effect on public welfare from visibility impairment to a more multifaceted approach that includes non

- Class 1 areas, such as urban areas. This evolution has occurred in conjunction with the expansion of available PM data and information from associated studies of public perception, val uation and personal comfort and well

- being. While visibility preference studies ( Abt Associates Inc., 2001, Ely et al., 1991, Pryor, 1996, BBC Research & Consulting, 2003 ) also provide support for a non

zero benefits estimate, these surveys did not include questions that would enable monetization of those preferences.

Despite these improvements, we are limited by the available peer

- reviewed studies on visibility co

- benefits , which have not undergone a similar expansion as the health literature. Each of thes e valuation studies has limitations, which are identified in the section s 6.3.4.2 and
6.3.5.2. When the SAB

- Council reviewed the visibility benefits analysis for The Benefits and Costs of the Clean Air Act 1990 to 2020: EPA Report to Congress (U.S. EPA, 2011 ) , they also lamented on the need for additional research to improve methods and estimates (U.S. EPA

SAB, 2010 a, 2010b ). Because of time and resource constraints, performing original research for regulatory analyses of specific policy actio ns is infeasible. Most importantly, we are interested
in recently published national

- scale visibility valuation studies that incorporate current CV best practices, as the existing studies are limited to specific subset of geographic areas. Other important research questions that remain unresolved include identifying factors that affect valuation preferences in order to facilitate benefits transfer from the original studies to transfer sites across localities, disentangling health and ecosystem valuation fro m visibility valuation, usefulness of preference calibration, and potential role of hedonic valuation approaches. Many

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- 37 of these same research needs were identified by Cropper (2000), but they have yet to be addressed by the research community.

In Appendix 6.B, w e provide the results of an illustrative analysis of the visibility co

benefits associated with the 2020 base case 2020 control case simulation described in Chapter 3 that were used to develop the air quality ratios; however, we do not have air quali ty model runs for the regulatory baseline and the alternative standard levels that would allow us to calculate the visibility co

- benefits of attaining the revised primary standard.

6

. 4 Materials Damage Co

- benefits Building materials including metals, stones, cements, and paints undergo natural weathering processes from exposure to environmental elements (e.g., wind, moisture, temperature fluctuations, sunlight, etc. ). Pollution can worsen and accelerate these effect s. Deposition of PM is associated with both physical damage (materials damage effects) and impaired aesthetic qualities (soiling effects). Wet and dry deposition of PM can physically affect materials, adding to the effects of natural weathering processes, by potentially promoting or accelerating the corrosion of metals, by degrading paints and by deteriorating building materials such as stone, concrete and marble (U.S. EPA, 2009b). The effects of PM are exacerbated by the presence of acidic gases and can be additive or synergistic due to the complex mixture of pollutants in the air and surface characteristics of the material. Acidic deposition has been shown to have an effect on materials including zinc/galvanized steel and other metal, carbonate stone (as m onuments and building facings), and surface coatings (paints) (Irving, 1991). The effects on historic buildings and outdoor works of art are of particular concern because of the uniqueness and irreplaceability of many of these objects.

The PM ISA concludes that evidence is sufficient to support a causal relationship between PM and effects on materials (U.S. EPA, 2009b). Considerable research has been conducted on the effects of air pollutants on metal surfaces due to the economic importance of these materia ls, especially steel, zinc, aluminum, and copper. Moisture is the single greatest factor promoting metal corrosion; however, deposited PM can have additive, antagonistic or synergistic effects. In general, SO 2 is more corrosive than NO x although mixtures o f NO x , SO 2 and other particulate matter corrode some metals at a faster rate than either pollutant alone (U.S. EPA, 2008). Metal structures are usually coated by alkaline corrosion product layers and thus are subject to increased corrosion by acidic deposi tion. In addition, research has demonstrated that iron, copper, and aluminum

- based products are subject to increased

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- 38 corrosion due to pollution (Irving, 1991). Information from both the PM ISA (U.S. EPA, 2009b) and NO x /SO x ISA (U.S. EPA, 2008) suggest that the extent of damage to metals due to ambient PM is variable and dependent upon the type of metal, prevailing environmental conditions, rate of natural weathering and presence or absence of other pollutants

In addition, the deposition of PM can cause soil ing, which is the accumulation of dirt, dust, and ash on exposed surfaces such as metal, glass, stone and paint. Particles consisting primarily of carbonaceous compounds can cause soiling of commonly used building materials and culturally important items s uch as statues and works of art. Soiling occurs when PM accumulates on an object and alters the optical characteristics (appearance). The reflectivity of a surface may be changed or presence of particulates may alter light transmission. These effects can r educe the aesthetic value of a structure or result in reversible or irreversible damage to statues, artwork and architecturally or culturally significant buildings. Due to soiling of building surfaces by PM, the frequency and duration of cleaning or repain ting may be increased. In addition to natural factors, exposure to PM may give painted surfaces a dirty
appearance. Pigments in works of art can be degraded or discolored by atmospheric pollutants, especially sulfates (U.S. EPA, 2008). Previous assessments estimated household soiling co

benefits based on the Manuel et al. (1982) study of consumer expenditures on cleaning and household maintenance. However, the data used to estimate household soiling damages in the Manuel et al. study is from a 1972 consumer expenditure survey and as such may not accurately represent consumer preferences in the future. In light of this significant limitation, we believe that this study cannot provide reliable estimates of the likely magnitude of the co

ben efits of reduced PM household soiling.

In order to estimate the monetized co

- benefits associated with reducing materials damage and household soiling, quantitative relationships are needed between particle size, concentration, chemical concentrations and f requency of maintenance and repair. Such an analysis would require three steps:

1. Develop a national inventory of sensitive materials;

2. Derive concentration

- response functions that relate material damage to change in pollution concentration or depositio n; and,

3. Estimate the value of lost materials and/or repair of damage.

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- 39 Due to data limitations and uncertainties inherent in each of these steps, we have chosen not to include a monetized estimate of materials damage and household soiling in this analysi s. The PM ISA concluded that there is considerable uncertainty with regard to interaction of co

- pollutants in regards to materials damage and soiling processes (U.S. EPA, 2009b). Previous benefits analyses by the EPA have provided quantitative estimates of materials damage (U.S. EPA, 2011b) and household soiling damage (U.S. EPA, 1999). Consistent with SAB advice (U.S. EPA, 1998), we determined that the existing data are not sufficient to calculate a reliable estimate of future year household soiling damage s (U.S. EPA, 1998). These previous analyses have shown that materials damage co

- benefits are significantly smaller than the health benefits associated with reduced exposure to PM 2.5 and ozone, or even visibility co

benefits

. However, studies of materials d amage to historic buildings and outdoor artwork in Sweden (Grosclaude and Soguel, 1994) indicate that these co

- benefits could be an order of magnitude larger than household soiling co

- benefits

. In the absence of quantified co

- benefits , we provide a qualita tive description of the avoided damage associated with reducing PM and PM precursor pollutants. Table 6

- 8 shows the effect of various PM 2.5 precursor pollutants and other co

- pollutants on various materials.

Table 6

- 8

. Materials Damaged by Pollutants Affected by this Rule (U.S. EPA, 2011b)

Pollutant Unquantified Effects / Damage to:

Sulfur oxides Infrastructural materials

— galvanized and painted carbon steel Commercial buildings

— carbonate stone, metal, and painted wood surfaces Residential buildings

— carbonate stone, metal, and painted wood surfaces
Monuments

— carbonate stone and metal
Structural aesthetics Automotive finishes

— painted metal
Hydrogen ion and nitrogen oxides Infrastructural materials

— galvanized and painted carbon steel
Zinc

- based metal products, such as galvanized steel Commercial and residential buildings

— carbonate stone, metal, and wood surfaces
Monuments

— carbonate stone and metal
Structural aesthetics Automotive finishes

— painted metal

Carbon dioxide Zinc

- based metal products, such as galvanized steel
Formaldehyde Zinc

- based metal products, such as galvanized steel

Particulate matter Household cleanliness (i.e., household soiling)

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- 40 Pollutant Unquantified Effects / Damage to:

Ozone Rubber products (e.g., tires)

6. 5 Climate Co

- benefits
Actions taken by s tate and l ocal governments to implement the revised annual primary standard are likely to have implications for climate change because emission reductions ultimately implemented to meet the standard may have impacts on emissions of long

- lived greenhouse gas (GHG) su ch as carbon dioxide (CO 2 ), short

- lived climate forcers such as black carbon (BC), and cooling aerosols like organic carbon (OC). Our ability to quantify the climate effects of these revised standard is limited due to lack of available information on the c o

controlled GHG emission reductions, the energy and associated climate gas implications of control technologies assumed in the illustrative regulatory alternative s, and remaining uncertainties regarding the impact of long

- lived and short

- lived climate for cer impacts on climate change. For this RIA, we discuss qualitatively the implications of potential emission reductions in warming and cooling aerosols and changes in long

- lived GHG emissions such as
CO 2 for the regulatory alternative s. Implementation stra tegies undertaken by s tate and l ocal governments to comply with the standard s may differ from the illustrative emission reduction strategies in this RIA

. It is important to note that the net climate forcing depends on the specific combinations of emission reductions chosen to meet the revised standard because of the differences in warming and cooling potential of the difference pollutants

.
6

. 5 .1 Climate Eff

ects of Short Lived Climate Forcers
Pollutants that affect the energy balance of the earth are referred to as climate forcers. A pollutant that increases the amount of energy in the Earth ’ s climate system is said to exert

“ positive radiative forcing, ” whic h leads to warming and climate change. In contrast, a pollutant that exerts negative radiative forcing reduces the amount of energy in the Earth ’ s system and leads to cooling.

Long

- lived gases such as CO 2 differ from short

- lived pollutants such as BC in th e length of time they remain in the atmosphere affecting the earth ’ s energy balance. Long

- lived gases remain in the atmosphere for hundreds to thousands of years. Short

- lived climate forcers (SLCFs), in contrast, remain in the atmosphere for short periods of time ranging from days to weeks. The potential to affect near

- term climate change and the rate of climate change with

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- 41 policies to address these emissions is gaining attention nationally and internationally ( e.g., Black Carbon Report to Congress ( U.S. EP A, 2012b ), Arctic Council Task Force, Global Methane Initiative, and Convention on Long

- Range Trans

- boundary Air Pollution of the United Nations Economic Commission for Europe). A recent United Nations Environmental Programme (UNEP) study provides the most comprehensive analysis to date of the co

- benefits of measures to reduce SLCFs including methane, ozone, and black carbon assessing the health, climate, and agricultural co

- benefits of a suite of mitigation technologies. The report concludes that the climate is changing now, and these changes have the potential to “ trigger abrupt transitions such as the release of carbon from thawing permafrost and biodiversity loss. ” While reducing long

- lived GHGs such as CO 2 is necessary to protect against long

- term climate change, reducing SLCF gases including BC and ozone is beneficial and will slow the rate of climate change within the first half of this century (UNEP
, 2011).

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. 5 .1.1 Climate Effe cts of Black Carbon
Black carbon is the most strongly light

‐ absorbing component of PM 2.5 , and is formed by incomplete combustion of fossil fuels, biofuels, and biomass. The short atmospheric lifetime of BC lasting from days to weeks and the mechanisms by w hich BC affects climate distinguish it from long

‐ lived GHGs like CO 2 . This means that actions taken to reduce the BC constituents in direct PM 2.5 will have almost immediate effects on climate change. Emissions sources and ambient concentrations of BC vary geographically and temporally resulting in climate effects that are more regionally and seasonally dependent than the effects of long‐lived, well‐mixed GHGs. Likewise, mitigation actions for BC will produce different climate impacts depending on the region , season, and emission source category affected.

BC influences climate in multiple ways: directly absorbing light , reducing the reflectivity ( “ albedo ” ) of snow and ice through deposition, and interacting with clouds. BC affects climate directly by absorbing both incoming and outgoing radiation of all wavelengths. In contrast, GHGs mainly trap outgoing infrared radiation from the earth ’ s surface. Per unit of mass in the atmosphere, BC can absorb a million times more en ergy than CO 2 (Bond and Sun 2005). This strong absorptive capacity is the property most relevant to its potential to affect the Earth ’ s climate. W hen BC is deposited on snow and ice, it darkens the surface and decreases albedo , thereby increasing absorptio n and accelerating melting. Finally, BC also affects climate indirectly by altering the properties of clouds, affecting cloud reflectivity, precipitation, and

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- 42 surface dimming. These indirect impacts of BC are associated with all ambient particles and may l ead to cooling, but are not associated with long

- lived well mixed GHGs.

Regional climate impacts of BC are highly variable, and sensitive regions such as the Arctic and the Himalayas are particularly vulnerable to the warming and melting effects of BC.
Sn ow and ice cover in the Western U.S. has also been affected by BC. Specifically, deposition of BC on mountain glaciers and snow packs produces a positive snow and ice albedo effect, contributing to the melting of snowpack earlier in the spring and reducing the amount of snowmelt that normally would occur later in the spring and summer (Hadley et al. 2010). This has implications for freshwater resources in regions of the U.S. dependent on snow‐fed or glacier‐fed water systems. In the Sierra Nevada mountain r ange, Hadley et al. (2010) found BC at different depths in the snowpack, deposited over the winter months by snowfall. In the spring, the continuous uncovering of the BC contributed to the early melt. A model capturing the effects of soot on snow in the we stern U.S. shows significant decreases in snowpack between December and May (Qian et al., 2009). Snow water equivalent (the amount of water that would be produced by melting all the snow) is reduced 2‐50 millimeters (mm) in mountainous areas, particularly over the Central Rockies, Sierra Nevadas, and western Canada. A study found that biomass burning emissions in Alaska and the Rocky Mountain region during the summer can enhance snowmelt. Dust deposition on snow, at high concentrations, can have similar eff ects to BC (Koch et al., 2007). Similarly, a study done by Painter et al. (2007) in the San Juan Mountains in Colorado indicated a decrease in snow cover duration of 18‐35 days as a result of dust transported from non‐local desert sources.

The illustrative emission reduction strategies evaluated for this rule include reductions in BC emissions that will tend to have a beneficial cooling effect on the atmosphere. BC and elemental carbon ( EC ) (or particulate elemental carbon (PEC)) are used in terchangeably in this report because the EPA traditionally estimates EC emissions rather than BC and for the purpose of this analysis these measures are essentially equivalent.

6

. 5 .1.2 Climate Effects of Nitrates, Sulfate, and Organic Carbon (excluding BC)
The composition of the total emissions mixture is also relevant as to whether emissions are warming or cooling to the atmosphere . P ollutants such as SO 2 , NO X , and most OC particles tend to produce a cooling influence on climate

. Exceptions include OC d eposition on snow and
ice , which leads to increased melting.

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- 43 In addition, it is important to account for the indirect effects of all PM constituents on climate: all aerosols (including BC) affect climate indirectly by changing the reflectivity and lifetime of clouds. The net indirect effect of all aerosols is very uncertain but is thought to be a net cooling influence.

6

. 5 .1.3 Climate Effects of Ozone
Ozone changes due to this revised annual standard are not estimated for this analysis but may occur due to the NO x reductions estimated. Ozone is a well

- known SLCF (U.S. EPA, 2006). Stratospheric ozone (the upper ozone layer) is beneficial because it protects life on Earth from the sun ’ s harmful ultraviolet (UV) radiation. In contrast, tropospheric ozone (ozone in the lower atmosphere) is a harmful air pollutant that adversely affects human health and the environment and contributes significantly to regional and global climate change. Due to its short atmospheric lifetime, tropospheric ozone concentrations exhib it large spatial and temporal variability (U.S. EPA, 2009). The discernible influence of ground level ozone on climate leads to increases in global surface temperature and changes in hydrological cycles. While reducing long

- lived GHGs such as CO 2 is necess ary to protect against long

- term climate change, reducing SLCF gases including ozone is beneficial and will slow the rate of climate change within the first half of this century (UNEP
, 2011).

6

. 5 .1.4 SLCFs Summary and Conclusions
Assessing the net climate impact of SLCFs for the illustrative emission reduction strategies is outside the scope of this regulatory analysis and requires climate atmospheric modeling not undertaken due to time and resource constraints. Information about t he amount of BC relative to non

- BC constituents emitted from a source is important. In general, these non

BC constituents are emitted in greater volume than BC, counteracting the warming influence of
BC. Qualitatively, it seems likely that BC emission redu ctions associated with direct ly emitted
PM 2.5 reductions will be beneficial for the climate in terms of reduced radiative forcing and deposition on snow and ice. Reductions in OC, sulfates and nitrates are likely to produce warming in the atmosphere. The i ndirect impacts of aerosols on clouds and precipitation remain the subject of great uncertainty making it more difficult to estimate the quantitative impact of aerosol reductions on climate.

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- 44 6

. 5 .2 Climate Effects of Long

- Lived Greenhouse Gases

The EPA Admi nistrator found in 2009 that elevated concentrations of the six major GHGs, including CO 2 , endanger the public health and public welfare of current and future generations (FR 77 66496). While addressing short

- lived climate forcers can result in near

- term ( and sometimes regionally specific) co

- benefits as well as reductions in the rate of warming, reductions of long

- term warming would require mitigation of long

- lived GHGs. We are unable to quantify the impact of the illustrative emission reduction strategies for this rulemaking on long

- lived climate gases due lack of available data

. However, State and Local governments may want to consider human health, welfare, and climate implications of regulatory strategies undertaken to implement the promulgated PM standards.

6

. 6 Ecosystem Co

- benefits and Services
The effects of air pollution on the health and stability of ecosystems are potentially very important. At present, it is difficult to measure the impact of reducing air pollution in a national scale analysi s across different types of ecosystems and different pollutant effects. Previous science assessments by the EPA (U.S. EPA, 2006a; 2008c; 2009b) have determined that air pollution can be directly linked to aquatic and terrestrial acidification, nutrient enr ichment, vegetation injury, and metal bioaccumulation in animals. Ecosystem services are a useful conceptual framework for analyzing the impact of ecosystem changes on public welfare.

Ecosystem services can be generally defined as the benefits that individ uals and organizations obtain from ecosystems. The EPA has defined ecological goods and services as the “ outputs of ecological functions or processes that directly or indirectly contribute to social welfare or have the potential to do so in the future. Som e outputs may be bought and sold, but most are not marketed ” (U.S. EPA, 2006c). Figure 6

- 7 provides the Millennium Ecosystem
Assessment ’ s schematic demonstrating the connections between the categories of ecosystem services and human well

- being. The interre latedness of these categories means that any one ecosystem may provide multiple services. Changes in these services can affect human well

being by affecting security, health, social relationships, and access to basic material goods (MEA, 2005).

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- 45 Figure 6

- 7

. Linkages between Categories of Ecosystem Se rvices and Components of Human

Well

- Being from Millennium Ecosystem Assessment (MEA, 2005)

In the Millennium Ecosystem Assessment (MEA, 2005), ecosystem services are classified into four main categories:

1. Pr ovisioning: Products obtained from ecosystems, such as the production of food and water
2. Regulating: Benefits obtained from the regulation of ecosystem processes, such as the control of climate and disease
3. Cultural: Nonmaterial benefits that people ob tain from ecosystems through spiritual enrichment, cognitive development, reflection, recreation, and aesthetic experiences
4. Supporting: Services necessary for the production of all other ecosystem services, such as nutrient cycles and crop pollination
The monetization of ecosystem services generally involves estimating the value of ecological goods and services based on what people are willing to pay (WTP) to increase ecological services or by what people are willing to accept (WTA) in compensation for reductions in them (U.S. EPA, 2006c). There are three primary approaches for estimating the monetary value of ecosystem services: market

- based approaches, revealed preference methods, and stated preference methods (U.S. EPA, 2006c). Because economic valuat ion of

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- 46 ecosystem services can be difficult, nonmonetary valuation using biophysical measurements and concepts also can be used. An example of a nonmonetary valuation method is the use of relative

- value indicators (e.g., a flow chart indicating uses of a wa ter body, such as boatable, fishable, swimmable, etc.). It is necessary to recognize that in the analysis of the environmental responses associated with any particular policy or environmental management action, only a subset of the ecosystem services likel y to be affected are readily identified. Of those ecosystem services that are identified, only a subset of the changes can be quantified. Within those services whose changes can be quantified, only a few will likely be monetized, and many will
remain nonmo netized. The stepwise concept leading up to the valuation of ecosystems services is graphically depicted in Figure 6

- 8

.

Figure 6

- 8

. Schematic of the Benefits Assessment Pro cess (U.S. EPA, 2006c)

6

. 6 .1 Ecosystem Co

- benefits for Metallic and Organic Constituents of PM
Several significant ecological effects are associated with deposition of chemical constituents of ambient PM such as metals and organics (U.S. EPA, 2009b). The trace metal constituents of PM include cadmium, cop per, chromium, mercury, nickel, zinc, and lead. The organics include persistent organic pollutants (POPs), polyaromatic hydrocarbons (PAHs) and polybromiated diphenyl ethers (PBDEs). Exposure to PM for direct effects occur via deposition ( e.g., wet, dry or occult) to vegetation surfaces, while indirect effects occur via deposition to ecosystem soils or surface waters where the deposited constituents of PM then interacts with

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- 47 biological organisms. While both fine and coarse

- mode particles may affect plants a nd other organisms, more often the chemical constituents drive the ecosystem response to PM (Grantz et al., 2003). Ecological effects of PM include direct effects to metabolic processes of plant foliage; contribution to total metal loading resulting in alt eration of soil biogeochemistry and microbiology, plant and animal growth and reproduction; and contribution to total organics loading resulting in bioaccumulation and biomagnification across trophic levels.

The PM ISA concludes that a causal relationship is likely to exist between deposition of PM and a variety of effects on individual organisms and ecosystems (U.S. EPA 2009b). Most direct ecosystem effects associated with particulate pollution occur in severely polluted areas near industrial point sources (quarries, cement kilns, metal smelting) (U.S. EPA, 2009b). However the PM ISA also finds, in many cases, it is difficult to characterize the nature and magnitude of effects and to quantify relationships between ambient concentrations of PM and ecosystem response due to significant data gaps and uncertainties as well as considerable variability that exists in the components of PM and their various ecological effects (U.S. EPA, 2009b).

Particulate matter can adversely impact plants and ecosystem services pr ovided by plants by deposition to vegetative surfaces (U.S. EPA, 2009b). Particulates deposited on the surfaces of leaves and needles can block light, altering the radiation received by the plant. PM deposition near sources of heavy deposition can obstruct stomata limiting gas exchange, damage leaf cuticles and increase plant temperatures (U.S. EPA, 2009b). Plants growing on roadsides exhibit impact damage from near

- road PM deposition, having higher levels of organics and heavy metals, and accumulate salt f rom road de

- icing during winter months (U.S. EPA, 2009b). In addition, atmospheric PM can convert direct solar radiation to diffuse radiation, which is more uniformly distributed in a tree canopy, allowing radiation to reach lower leaves (U.S. EPA, 2009b). Decreases in crop yields (a provisioning service) due to reductions in solar radiation have been attributed to regional scale air pollution in other counties with especially severe regional haze (Chameides et al., 1999).

In addition to damage to plant sur faces, deposited PM can be taken up by plants from soil or foliage. Copper, zinc, and nickel have been shown to be directly toxic to vegetation under field conditions (U.S. EPA, 2009b). The ability of vegetation to take up heavy metals is dependent upon th e amount, solubility and chemical composition of the deposited PM. Uptake

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- 48 of PM by plants from soils and vegetative surfaces can disrupt photosynthesis, alter pigments and mineral content, reduce plant vigor, decrease frost hardiness and impair root develo pment.

Particulate matter can also contain organic air toxic pollutants, including PAHs, which are a class of polycyclic organic matter (POM). PAHs can accumulate in sediments and bioaccumulate in freshwater, flora and fauna. The uptake of organics depends on the plant species, site of deposition, physical and chemical properties of the organic compound and prevailing environmental conditions (U.S. EPA, 2009b). Different species can have different uptake rates of PAHs. For example, zucchini ( Cucurbita pepo ) accumulated significantly more PAHs than related plant species (Parrish et al., 2006). PAHs can accumulate to high enough concentrations in some coastal environments to pose an environmental health threat that includes cancer in fish populations, toxicity to organisms living in the sediment and risks to those (e.g., migratory birds) that consume these organisms (Simcik et al., 1996; Simcik et al., 1999). Atmospheric deposition of particles is thought to be the major source of PAHs to the sediments of Lake Michigan, Chesapeake Bay, Tampa Bay and other coastal areas of the U.S. (Arz avus, Dickhut, and Canuel, 2001 ).

Contamination of plant leaves by heavy metals can lead to elevated concentrations in the soil. Trace metals absorbed into the plant, frequently bi nd to the leaf tissue, and then are lost when the leaf drops. As the fallen leaves decompose, the heavy metals are transferred into the soil (Cotrufo et al

. , 1995; Niklinska et al., 1998). Many of the major indirect plant responses to PM deposition are chi efly soil

- mediated and depend on the chemical composition of individual components of deposited PM. Upon entering the soil environment, PM pollutants can alter ecological processes of energy flow and nutrient cycling, inhibit nutrient uptake to plants, cha nge microbial community structure and, affect biodiversity. Accumulation of heavy metals in soils depends on factors such as local soil characteristics, geologic origin of parent soils, and metal bioavailability. Heavy metals, such as zinc, copper, and cad mium, and some pesticides can interfere with microorganisms that are responsible for decomposition of soil litter, an important regulating ecosystem service that serves as a source of soil nutrients (U.S. EPA, 2009b). Surface litter decomposition is reduce d in soils having high metal concentrations. Soil communities have associated bacteria, fungi, and invertebrates that are essential to soil nutrient cycling processes. Changes to the relative species abundance and community composition are associated with deposited PM to soil biota (U.S. EPA, 2009b).

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- 49 Atmospheric deposition can be the primary source of some organics and metals to watersheds. Deposition of PM to surfaces in urban settings increases the metal and organic component of storm water runoff (U.S. E PA, 2009b). This atmospherically

- associated pollutant burden can then be toxic to aquatic biota. The contribution of atmospherically deposited PAHs to aquatic food webs was demonstrated in high elevation mountain lakes with no other anthropogenic contamina nt sources (U.S. EPA, 2009b). Metals associated with PM deposition limit phytoplankton growth, affecting aquatic trophic structure. Long

- range atmospheric transport of 47 pesticides and degradation products to the snowpack in seven national parks in the We stern U.S. was recently quantified indicating PM

- associated contaminant inputs to receiving waters during spring snowmelt (Hageman et al., 2006).

The recently completed Western Airborne Contaminants Assessment Project (WACAP) is the most comprehensive data base on contaminant transport and PM depositional effects on sensitive ecosystems in the Western U.S. (Landers et al., 2008). In this project, the transport, fate, and ecological impacts of anthropogenic contaminants from atmospheric sources were assessed from 2002 to 2007 in seven ecosystem components (air, snow, water, sediment, lichen, conifer needles and fish) in eight core national parks. The study concluded that bioaccumulation of semi

- volatile organic compounds occurred throughout park ecosystems, an elevational gradient in PM deposition exists with greater accumulation in higher altitude areas, and contaminants accumulate in proximity to individual agriculture and industry sources, which is counter to the original working hypothesis that most of the contaminants would originate from Eastern Europe and Asia.

Although there is considerable data on impacts of PM on ecological receptors, few studies link ambient PM levels to observed effect. This is due, in part, to the nature, deposition, transport and f ate of PM in ecosystems. Some of the difficulties in quantifying the ecosystem

co

- benefits associated with reduced PM deposition include the following:

 PM is not a single pollutant, but a heterogeneous mixture of particles differing in size, origin and che mical composition. Since vegetation and other ecosystem components are affected more by particulate chemistry than size fraction, exposure to a given mass concentration of airborne PM may lead to widely differing plant or ecosystem responses, depending on the particular mix of deposited particles.

 Composition of ambient PM varies in time and space and the particulate mixture may have synergistic, antagonistic or additive effects on ecological receptors depending upon the chemical species present.

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- 50  Presence o f co

- pollutants makes it difficult to attribute observed effects to ecological receptors to PM alone or one component of deposited PM.

 Ecosystem effects linked to PM are difficult to determine because the changes may not be observed until pollutant deposit ion has occurred for many decades. Furthermore, many PM components bioaccumulate over time in organisms or plants, making correlations to ambient levels of PM difficult.

 Multiple ecological stressors can confound attempts to link specific ecosystem respons es to PM deposition. These stressors can be anthropogenic ( e.g., habitat destruction, eutrophication, other pollutants) or natural ( e.g., drought, fire, disease). Deposited PM interacts with other stressors to affect ecosystem patterns and processes.

 Each ecosystem has a unique topography, underlying bedrock, soils, climate, meteorology, hydrologic regime, natural and land use history, and species composition. Sensitivity of ecosystem response can be highly variable in space and time. Because of this variet y and lack of data for most ecosystems, extrapolating these effects from one ecosystem to another is highly uncertain.

6

. 6 .2 Ecosystem Co

- benefits from Reductions in Nitrogen and Sulfur Emissions
Emissions of the PM precursors, such as n itrogen and sulfur oxides occur over large regions of North America. Once these pollutants are lofted to the middle and upper troposphere, they typically have a much longer lifetime and, with the generally stronger winds at these altitudes, can be transported long distances from their source regions. The length scale of this transport is highly variable owing to differing chemical and meteorological conditions encountered along the transport path (U.S. EPA, 2008c). Secondary particles are formed from
NO X and SO 2 gaseous emiss ions and associated chemical reactions in the atmosphere. Deposition can occur in either a wet (i.e., rain, snow, sleet, hail, clouds, or fog) or dry form (i.e., gases or particles). Together these emissions are deposited onto terrestrial and aquatic
ecosy stems across the U.S., contributing to the problems of acidification, nutrient enrichment, and methylmercury production as represented in Figures 6

- 9 and 6

- 1 0

. Although there is some evidence that nitrogen deposition may have positive effects on agricultur al and forest output through passive fertilization, it is likely that the overall value is very small relative to other health and welfare effects. In addition to deposition effects, SO 2 can affect vegetation at ambient levels near pollution sources.

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- 51 NO X Atmospheric Fate and Transport

Deposition Process

Acidification

Aquatic Ecosystems Terrestrial

Ecosystems Nutrient Enrichment

Aquatic Ecosystems Terrestrial

Ecosystems

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- 52 SO 2 Atmospheric Fate and Transport

Deposition Process

Acidification

Aquatic Ecosystems Terrestrial Ecosystems Methylmercury Production

NO X Atmospheric Fate and Transport

Deposition Process

Acidification

Aquatic Ecosystems Terrestrial

Ecosystems Nutrient Enrichment

Aquatic Ecosystems Terrestrial

Ecosystems

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- 53 Figure 6

- 9

. Schematics of Ecological Effects of Nitrogen and Sulfur Deposition SO 2 Atmospheric Fate and Transport

Deposition Process

Acidification

Aquatic Ecosystems Terrestrial Ecosystems Methylmercury Production

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- 54 Figure 6

- 1 0

. Nitrogen and Sulfur Cycling , and Interactions in the Environment
Source: U.S. EPA, 2008c
The atmospheric lifetimes of particles vary with particle size. Accumulation

- mode particles such as sulfates are kept in suspension by normal air motions and have a lower deposition velocity than coarse

- mode particles; they can be transported thousands of kilometers and remain in the atmosphere for a number of days. Th ey are removed from the atmosphere primarily by cloud processes. Particulates affect acid deposition by serving as cloud condensation nuclei and contribute directly to the acidification of rain. In addition, the gas

phase species that lead to the dry depos ition of acidity are also precursors of particles. Therefore, reductions in NO X and SO 2 emissions will decrease both acid deposition and PM concentrations, but not necessarily in a linear fashion (U.S. EPA, 2008c). Sulfuric acid is also deposited on surfac es by dry deposition and can contribute to environmental effects (U.S. EPA, 2008c).

6

. 6 .2.1 Ecological Effects of Acidification
Deposition of nitrogen and sulfur can cause acidification, which alters biogeochemistry and affects animal and plant life in ter restrial and aquatic ecosystems across the U.S. Soil

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- 55 acidification is a natural process, but is often accelerated by acidifying deposition, which can decrease concentrations of exchangeable base cations in soils (U.S. EPA, 2008c). Major terrestrial effects include a decline in sensitive tree species, such as red spruce ( Picea rubens ) and sugar maple ( Acer saccharum ) (U.S. EPA, 2008c). Biological effects of acidification in terrestrial ecosystems are generally linked to aluminum toxicity and decreased abilit y of plant roots to take up base cations (U.S. EPA, 2008c). Decreases in the acid neutralizing capacity and increases in inorganic aluminum concentration contribute to declines in zooplankton, macro invertebrates, and fish species richness in aquatic ecosy stems (U.S. EPA, 2008c).

Geology (particularly surficial geology) is the principal factor governing the sensitivity of terrestrial and aquatic ecosystems to acidification from nitrogen and sulfur deposition (U.S. EPA, 2008c). Geologic formations having low base cation supply generally underlie the watersheds of acid

- sensitive lakes and streams. Other factors contribute to the sensitivity of soils and surface waters to acidifying deposition, including topography, soil chemistry, land use, and hydrologic flow path (U.S. EPA, 2008c).

Aquatic Acidification. Aquatic effects of acidification have been well studied in the U.S. and elsewhere at various trophic levels. These studies indicate that aquatic biota have been affected by acidification at virtually all leve ls of the food web in acid sensitive aquatic ecosystems. The ISA for NO x /SO x — Ecological Criteria concluded that the evidence is sufficient to infer a causal relationship between acidifying deposition and effects on biogeochemistry related to aquatic ecosys tems and biota in aquatic ecosystems (U.S. EPA, 2008c). Effects have been most clearly documented for fish, aquatic insects, other invertebrates, and algae. Biological effects are primarily attributable to a combination of low pH and high inorganic aluminu m concentrations. Such conditions occur more frequently during rainfall and snowmelt that cause high flows of water and less commonly during low

- flow conditions, except where chronic acidity conditions are severe. Biological effects of episodes include red uced fish condition factor 34 , changes in species composition and declines in aquatic species richness across multiple taxa, ecosystems and regions. These conditions may also result in direct fish mortality (Van Sickle et al., 1996). Biological effects in aq uatic ecosystems can be divided into two major categories: effects on health, vigor, and reproductive success; and effects on biodiversity. Surface water with ANC values greater than 50 μeq/L generally provides moderate

34 Condition factor is an index that describes the relationship between fish weight and length, and is one measure of sublethal acidifica tion stress that has been used to quantify effects of acidification on an individual fish (U.S. EPA, 2008f).

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- 56 protection for most fish (i.e., broo k trout, others) and other aquatic organisms (U.S. EPA, 2009c). Table 6

- 9 provides a summary of the biological effects experienced at various ANC levels.

Table 6

- 9

. Aquatic Status Categories

Category Label ANC Levels Expected Ecological Effects

Acute Concern <0 micro

equivalent per Liter (μeq/L) Near complete loss of fish populations is expected. Planktonic communities have

extremely low diversity and are dominated by acidophilic forms. The number of individuals in plankton species that are present is greatly reduced.

Severe Concern 0

– 20 μeq/L Highly sensitive to episodic acidification. During episodes of high acidifying deposition, brook trout populations may experience lethal effects. Diversity and distribution of zooplankton communities decline sharply.

Elevated Concern 20

– 50 μeq/L Fish species richness is greatly reduced (i.e., more than half of expected species can be missing). On average, brook trout populations experience sublethal effects, including loss of health, reproduction capacity, and fitness. Diversity and distribution of zooplankton communities decline.

Moderate Concern 50

– 100 μeq/L Fish species richness begins to decline (i.e., sensitive species are lost from lakes). Brook trout populations are sensitive and variable, with possi ble sublethal effects. Diversity and distribution of zooplankton communities also begin to decline as species that are sensitive to acidifying deposition are affected.

Low Concern >100 μeq/L Fish species richness may be unaffected. Reproducing brook trout populations are expected where habitat is suitable. Zooplankton communities are unaffected and exhibit expected diversity and distribution.

A number of national and regional assessments have been conducted to estimate the distribution and extent of surf ace water acidity in the U.S. (U.S. EPA, 2008c). As a result, several regions of the U.S. have been identified as containing a large number of lakes and streams that are seriously impacted by acidification. Figure 6

- 11 illustrates those areas of the U.S. w here aquatic ecosystems are at risk from acidification.

Because acidification primarily affects the diversity and abundance of aquatic biota, it also affects the ecosystem services that are derived from the fish and other aquatic life found in these surfac e waters.

While acidification is unlikely to have serious negative effects on, for example, water supplies, it can limit the productivity of surface waters as a source of food (i.e., fish). In the northeastern United States, the surface waters affected by acidification are not a major source

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- 57 of commercially raised or caught fish; however, they are a source of food for some recreational and subsistence fishermen and for other consumers. For example, there is evidence that certain population subgroups in the northeastern United States, such as the Hmong and Chippewa ethnic groups, have particularly high rates of self

- caught fish consumption (Hutchison and Kraft, 1994; Peterson et al., 1994). However, it is not known if and how their consumption patterns are af fected by the reductions in available fish populations caused by surface water acidification.

Figure 6

- 11. Areas Potentially Sensitive to Aquatic Acidification
Source: U.S. EPA, 2008c
Inland surface waters support several cultural services, including aesthetic and educational services and recreational fishing. Recreational fishing in lakes and streams is among the most popular outdoor recreational activities in the northeastern United States. Based on studies conducted in the northeastern United States, Kaval and Loomis (2003) estimated average consumer surplus values per day of $36 for recreational fishing (in 2007 dollars); therefore, the implied total annual value of freshwater fishing in th e northeastern United States

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- 58 was $5.1 billion in 2006. 35 For recreation days, consumer surplus value is most commonly measured using recreation demand, travel cost models.

Another estimate of the overarching ecological co

- benefits associated with reducing l ake acidification levels in Adirondacks National Park can be derived from the contingent valuation (CV) survey (Banzhaf et al., 2006), which elicited values for specific improvements in acidification

- related water quality and ecological conditions in Adiro ndack lakes. The survey described a base version with minor improvements said to result from the program, and a scope version with large improvements due to the program and a gradually worsening status
quo. After adapting and transferring the results of th is study and converting the 10

- year annual payments to permanent annual payments using discount rates of 3% and 5%, the WTP estimates ranged from $48 to $107 per year per household (in 2004 dollars) for the base version and $54 to $154 for the scope versio n. Using these estimates, the aggregate annual benefits of eliminating all anthropogenic sources of NO x and SO x emissions were estimated to range from $291 million to $829 million (U.S. EPA, 2009c). 36

In addition, inland surface waters provide a number of r egulating services associated with hydrological and climate regulation by providing environments that sustain aquatic food webs. These services are disrupted by the toxic effects of acidification on fish and other aquatic life. Although it is difficult to quantify these services and how they are affected by acidification, some of these services may be captured through measures of provisioning and cultural services.

Terrestrial Acidification. Acidifying deposition has altered major biogeochemical processes i n the U.S. by increasing the nitrogen and sulfur content of soils, accelerating nitrate and sulfate leaching from soil to drainage waters, depleting base cations (especially calcium and magnesium) from soils, and increasing the mobility of aluminum. Inorga nic aluminum is toxic to
some tree roots. Plants affected by high levels of aluminum from the soil often have reduced root growth, which restricts the ability of the plant to take up water and nutrients, especially calcium (U. S. EPA, 2008c). These direct effects can, in turn, influence the response of these plants to climatic stresses such as droughts and cold temperatures. They can also influence the sensitivity of plants to other stresses, including insect pests and disease (Joslin et al., 1992)

35 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reduction s achieved by this rule.
36 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reductions achieved by this rule.

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- 59 leading to increased mortality of canopy trees. In the U.S., terrestrial effects of acidification are best described for forested ecosystems (especially red spruce and sugar maple ecosystems) with additional information on other plant communities, including shrubs and lichen (U.S. EPA, 2008c). The ISA for NO x /SO x — Ecological Criteria concluded that the evidence is sufficient to infer a causal relationship between acidifying deposition and effects on biogeochemistry related to terrestrial ecosystems and biota in terr estrial ecosystems (U.S. EPA, 2008c).

Certain ecosystems in the continental U.S. are potentially sensitive to terrestrial acidification, which is the greatest concern regarding nitrogen and sulfur deposition U.S. EPA (2008c). Figure 6

- 1 2 depicts the areas across the U.S. that are potentially sensitive to terrestrial acidification.

Figure 6

- 1 2

. Areas Potentially Sensitive to Terrestrial Acidification

Source: U.S. EPA, 2008c
Both coniferous and deciduous forests throughout the eastern U.S . are experiencing gradual losses of base cation nutrients from the soil due to accelerated leaching from acidifying

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- 60 deposition. This change in nutrient availability may reduce the quality of forest nutrition over the long term. Evidence suggests that red spruce and sugar maple in some areas in the eastern U.S. have experienced declining health because of this deposition. For red spruce, ( Picea rubens ) dieback or decline has been observed across high elevation landscapes of the northeastern U.S., and to a l esser extent, the southeastern U.S., and acidifying deposition has been implicated as a causal factor (DeHayes et al., 1999). Figure 6

- 1 3 shows the distribution of red spruce (brown) and sugar maple (green) in the eastern U.S.

Terrestrial acidification aff ects several important ecological endpoints, including declines in habitat for threatened and endangered species (cultural), declines in forest aesthetics (cultural), declines in forest productivity (provisioning), and increases in forest soil erosion and reductions in water retention (cultural and regulating).

Figure 6

- 1 3

. Distribution of Red Spruce (pink) and Sugar Maple (green) in the Eastern U.S.
Source: U.S. EPA, 2008c
Forests in the northeastern United States provide several important and valuable
p rovisioning services in the form of tree products. Sugar maples are a particularly important

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- 61 commercial hardwood tree species, providing timber and maple syrup. In the United States, sugar maple saw timber was nearly 900 million board feet in 2006 (USFS, 2 006), and annual production of maple syrup was nearly 1.4 million gallons, accounting for approximately 19% of worldwide production. The total annual value of U.S. production in these years was approximately $160 million (NASS, 2008). 37 Red spruce is also used in a variety of products including lumber, pulpwood, poles, plywood, and musical instruments. The total removal of red spruce saw timber from timberland in the United States was over 300 million board feet in 2006 (USFS, 2006).

Forests in the northeas tern United States are also an important source of cultural ecosystem services

— nonuse (i.e., existence value for threatened and endangered species), recreational, and aesthetic services. Red spruce forests are home to two federally listed species and one d elisted species:

1. Spruce

- fir moss spider ( Microhexura montivaga )

— endangered

2. Rock gnome lichen ( Gymnoderma lineare )

— endangered

3. Virginia northern flying squirrel ( Glaucomys sabrinus fuscus )

— delisted, but important

Forestlands support a wide variety o f outdoor recreational activities, including fishing, hiking, camping, off

- road driving, hunting, and wildlife viewing. Regional statistics on recreational activities that are specifically forest based are not available; however, more general data on outdo or recreation provide some insights into the overall level of recreational services provided by forests. More than 30% of the U.S. adult population visited a wilderness or primitive area during the previous year and engaged in day hiking (Cordell et al., 2 008). From 1999 to 2004, 16% of adults in the northeastern United States participated in off

- road vehicle recreation, for an average of 27 days per year (Cordell et al., 2005). The average consumer surplus value per day of off

- road driving in the United St ates was $25 (in 2007 dollars), and the implied total annual value of off

- road driving recreation in the northeastern United States was more than $9 billion (Kaval and Loomis, 2003). More than 5% of adults in the northeastern United States participated in nearly 84 million hunting days (U.S. FWS and U.S. Census Bureau, 2007). Ten percent of adults in northeastern states participated in wildlife viewing away from

37 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reductions achieved by this rule.

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- 62 home on 122 million days in 2006. For these recreational activities in the northeastern United
S tates, Kaval and Loomis (2003) estimated average consumer surplus values per day of $52 for hunting and $34 for wildlife viewing (in 2007 dollars). The implied total annual value of hunting and wildlife viewing in the northeastern United States was, theref ore, $4.4 billion and $4.2 billion, respectively, in 2006 (U.S. EPA, 2009c). 38

As previously mentioned, it is d ifficult to estimate the portion of these recreational services that are specifically attributabl e to forests and to the health of specific tree s pecies. However, one recreational activity that is directly dependent on forest conditions is fall color viewing. Sugar maple trees, in particular, are known for their bright colors and are, therefore, an essential aesthetic component of most fall color la ndscapes. A survey of residents in the Great Lakes area found that roughly 30% of residents reported at least one trip in the previous year involving fall color viewing (Spencer and Holecek, 2007). In a separate study conducted in Vermont, Brown (2002) rep orted that more than 22% of households visiting Vermont in 2001 made the trip primarily for viewing fall colors.

Two studies estimated values for protecting high

- elevation spruce forests in the southern Appalachian Mountains. Kramer et al. (2003) conducted a contingent valuation study estimating households ’ WTP for programs to protect remaining high

- elevation spruce forests from damages associated with air pollution and insect infestation. Median household WTP was estimated to be roughly $29 (in 2007 dollar s) for a smaller program, and $44 for the more extensive program. Jenkins et al. (2002) conducted a very similar study in seven Southern Appalachian states on a potential program to maintain forest conditions at status quo levels. The overall mean annual WTP for the forest protection programs was $208 (in 2007 dollars). Multiplying the average WTP estimate from these studies by the total number of households in the seven

- state Appalachian region results in an aggregate annual range of $470 million to $3.4 billion for avoiding a significant decline in the health of high

- elevation spruce forests in the Southern Appalachian region (U.S. EPA, 2009c). 39

Forests in the northeastern United States also support and provide a wide variety of valuable regulating servic es, including soil stabilization and erosion control, water regulation,

38 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission re ductions achieved by this rule.
39 These estimates reflect the marginal value of the service for the hypothetical program described in the survey, not the marginal change in the value of the service as a result of the emission reductions achieved by this r ule.

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- 63 and climate regulation. The total value of these ecosystem services is very difficult to quantify in a meaningful way, as is the reduction in the value of these services associated wit h total nitrogen and sulfur deposition. As terrestrial acidification contributes to root damages, reduced biomass growth, and tree mortality, all of these services are likely to be affected; however, the magnitude of these impacts is currently very uncerta in.

6

. 6 .2.2 Ecological Effects from Nitrogen Enrichment
Aquatic Enrichment

. The ISA for NO x /SO x — Ecological Criteria concluded that the evidence is sufficient to infer a causal relationship between nitrogen deposition and the alteration of species richness, species composition, and biodiversity in wetland, freshwater aquatic and coastal marine ecosystems (U.S. EPA, 2008c).

One of the main adverse ecological effects resulting from nitrogen deposition, particularly in the Mid

- Atlantic region of the United Stat es, is the effect associated with nutrient enrichment in estuarine waters. A recent assessment of 141 estuaries nationwide by the National Oceanic and Atmospheric Administration (NOAA) concluded that 19 estuaries (13%) suffered from moderately high or high levels of eutrophication due to excessive inputs of both N and phosphorus, and a majority of these estuaries are located in the coastal area from North Carolina to Massachusetts (NOAA, 2007). For estuaries in the Mid

- Atlantic region, the contribution of a tmospheric distribution to total N loads is estimated to range between 10% and 58% (Valigura et al., 2001).

Eutrophication in estuaries is associated with a range of adverse ecological effects. The conceptual framework developed by NOAA emphasizes four mai n types of eutrophication effects

— low dissolved oxygen (DO), harmful algal blooms (HABs), loss of submerged aquatic vegetation (SAV), and low water clarity. Low DO disrupts aquatic habitats, causing stress to fish and shellfish, which, in the short

- term, c an lead to episodic fish kills and, in the long

- term, can damage overall growth in fish and shellfish populations. Low DO also degrades the aesthetic qualities of surface water. In addition to often being toxic to fish and shellfish, and leading to fish kills and aesthetic impairments of estuaries, HABs can, in some instances, also be harmful to human health. SAV provides critical habitat for many aquatic species in estuaries and, in some instances, can also protect shorelines by reducing wave strength; t herefore, declines in SAV due to nutrient enrichment are an important source of concern. Low water clarity is in part the result of accumulations of both algae and sediments in estuarine waters. In addition to

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- 64 contributing to declines in SAV, high levels o f turbidity also degrade the aesthetic qualities of the estuarine environment.

Estuaries in the eastern United States are an important source of food production, in particular fish and shellfish production. The estuaries are capable of supporting large sto cks of resident commercial species, and they serve as the breeding grounds and interim habitat for several migratory species. To provide an indication of the magnitude of provisioning services associated with coastal fisheries, from 2005 to 2007, the avera ge value of total catch was $1.5 billion per year. It is not known, however, what percentage of this value is directly attributable to or dependent upon the estuaries in these states.

In addition to affecting provisioning services through commercial fish h arvests, eutrophication in estuaries may also affect the demand for seafood. For example, a well

publicized toxic pfiesteria bloom in the Maryland Eastern Shore in 1997, which involved thousands of dead and lesioned fish, led to an estimated $56 million (i n 2007 dollars) in lost seafood sales for 360 seafood firms in Maryland in the months following the outbreak (Lipton, 1999).

Estuaries in the United States also provide an important and substantial variety of cultural ecosystem services, including water

- ba sed recreational and aesthetic services. The water quality in the estuary directly affects the quality of these experiences. For example, there were 26 million days of saltwater fishing coastal states from North Carolina to Massachusetts in 2006 (FWA and C ensus, 2007). Assuming an average consumer surplus value for a fishing day at $36 (in 2007 dollars) in the Northeast and $87 in the Southeast (Kaval and Loomis, 2003), the aggregate value was approximately $1.3 billion (in 2007 dollars) (U.S. EPA, 2009c). 40 In addition, almost 6 million adults participated in motorboating in coastal states from North Carolina to Massachusetts, for a total of nearly 63 million days annually during 1999

– 2000 (Leeworthy and Wiley, 2001). Using a national daily value estimate o f $32 (in 2007 dollars) for motorboating (Kaval and Loomis (2003), the aggregate value of these coastal motorboating outings was $2 billion per year (U.S. EPA, 2009c). 41 Almost 7 million participated in birdwatching for 175 million

40 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reductions achieved by this rule.
41 These estimates reflect the total value of the service, not the marginal cha nge in the value of the service as a result of the emission reductions achieved by this rule.

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- 65 days per year, and more than 3 million participated in visits to non

- beach coastal waterside

areas.
Estuaries and marshes have the potential to support a wide range of regulating services, including climate, biological, and water regulation; pollution detoxification; erosion prev ention; and protection against natural hazards from declines in SAV (MEA, 2005). SAV can help reduce wave energy levels and thus protect shorelines against excessive erosion, which increases the risks of episodic flooding and associated damages to near

- sho re properties or public infrastructure or even contribute to shoreline retreat.

We are unable to provide an estimate of the aquatic enrichment co

- benefits associated with the revised or alternative annual standard s due to data, time, and resource limitations.

Terrestrial Enrichment

. Terrestrial enrichment occurs when terrestrial ecosystems receive N loadings in excess of natural background levels, through either atmospheric deposition or direct application. Evidence presented in the ISA for NO x /SO x (U.S. EPA, 2008c) supports a causal relationship between atmospheric N deposition and biogeochemical cycling and fluxes of N and carbon in terrestrial systems. Furthermore, evidence summarized in the report supports a causal link between atmospheric N dep osition and changes in the types and number of species and biodiversity in terrestrial systems. Nitrogen enrichment occurs over a long time period; as a result, it may take as much as 50 years or more to see changes in ecosystem conditions and indicators. This long time scale also affects the timing of the ecosystem service changes. The ISA for NO x /SO x — Ecological Criteria concluded that the evidence is sufficient to infer a causal relationship between nitrogen deposition and the alteration of species richne ss, species composition, and biodiversity in terrestrial ecosystems (U.S. EPA, 2008c).

One of the main provisioning services potentially affected by N deposition is grazing opportunities offered by grasslands for livestock production in the Central U.S. Al though N deposition on these grasslands can offer supplementary nutritive value and promote overall grass production, there are concerns that fertilization may favor invasive grasses and shift the species composition away from native grasses. This process may ultimately reduce the productivity of grasslands for livestock production. Losses due to invasive grasses can be significant; for example, based on a bioeconomic model of cattle grazing in the upper Great Plains, Leitch, Leistritz, and Bangsund (1996) and Leistritz, Bangsund, and Hodur (2004)

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- 66 estimated $130 million in losses due to a leafy spurge infestation in the Dakotas, Montana, and Wyoming. 42 However, the contribution of N deposition to these losses is still uncertain.

Terrestrial nutrient enrichmen t also affects cultural and regulating services. For example, in California, Coastal Sage Scrub (CSS) habitat concerns focus on a decline in CSS and an increase in nonnative grasses and other species, impacts on the viability of threatened and endangered s pecies associated with CSS, and an increase in fire frequency. Changes in Mixed Conifer Forest (MCF) include changes in habitat suitability and increased tree mortality, increased fire intensity, and a change in the forest ’ s nutrient cycling that may affec t surface water quality through nitrate leaching (U.S. EPA, 2008c). CSS and MCF are an integral part of the California landscape, and together the ranges of these habitats include the densely populated and valuable coastline and the mountain areas. Numerou s threatened and endangered species at both the state and federal levels reside in CSS and MCF. The value that California residents and the U.S. population as a whole place on CSS and MCF habitats is reflected in the various federal, state, and local gover nment measures that have been put in place to protect these habitats, including the Endangered Species Act, conservation planning programs, and private and local land trusts. CSS and MCF habitat are showcased in many popular recreation areas in California, including several national parks and monuments. In addition, millions of individuals are involved in fishing, hunting, and wildlife viewing in California every year (DOI, 2007). The quality of these trips depends in part on the health of the ecosystems and their ability to support the diversity of plants and animals found in important habitats found in CSS or MCF ecosystems and the parks associated with those ecosystems. Based on analyses in the NO x SO x REA average values of the total benefits in 2006 fr om fishing, hunting, and wildlife viewing away from home in California were approximately $950 million, $170 million, and $3.6 billion, respectively (U.S. EPA, 2009c). 43 In addition, data from California State Parks (2003) indicate that in 2002, 69% of adul t residents participated in trail hiking for an average of 24 days per year. The aggregate annual benefit for California residents from trail hiking in 2007 was $11 billion (U.S. EPA, 2009c). 44 It is not currently possible to quantify the loss in value of s ervices due to nitrogen deposition as those losses are already reflected in the

42 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reductions achieved by this rule.
43 These estimates reflect the total value of the service, not the marginal change in the value of the service as a result of the emission reductions achieved by this rule.
44 These estimates reflect the total value of the service, not the margi nal change in the value of the service as a result of the emission reductions achieved by this rule.

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- 67 estimates of the contemporaneous total value of these recreational activities. Restoration of services through decreases in nitrogen deposition would likely increase the total value of recreational services.

Fire regulation is also an important regulating service that could be affected by nutrient enrichment of the CSS and MCF ecosystems by encouraging growth of more flammable grasses, increasing fuel loads, and altering the fir e cycle. Over the 5

- year period from 2004 to 2008, Southern California experienced, on average, over 4,000 fires per year burning, on average, over 400,000 acres per year (National Association of State Foresters [NASF], 2009). It is not possible at this ti me to quantify the contribution of nitrogen deposition, among many other factors, to increased fire risk.

We are unable to provide an estimate of the terrestrial nutrient enrichment co

- benefits associated with the revised or alternative annual st andards du e to data, time, and resource limitations. Methods are not yet available to allow estimation of changes in ecosystem services due to nitrogen deposition.

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. 7 .2.3 Vegetation Effects Associated with Gaseous Sulfur Dioxide
Uptake of gaseous sulfur dioxide in a plant canopy is a complex process involving adsorption to surfaces (leaves, stems, and soil) and absorption into leaves. SO 2 penetrates into leaves through to the stomata, although there is evidence for limited pathways via the cuticle (U.S. EPA, 2008c). Pollutants must be transported from the bulk air to the leaf boundary layer in order to get to the stomata. When the stomata are closed, as occurs under dark or drought conditions, resistance to gas uptake is very high and the plant has a very low degree of susceptibility to injury. In contrast, mosses and lichens do not have a protective cuticle barrier to gaseous pollutants or stomates and are generally more sensitive to gaseous sulfur and nitrogen than vascular plants (U.S. EPA, 2008c). Acute foliar inj ury usually happens within hours of exposure, involves a rapid absorption of a toxic dose, and involves collapse or necrosis of plant tissues. Another type of visible injury is termed chronic injury and is usually a result of variable SO 2 exposures over th e growing season. Besides foliar injury, chronic exposure to low
SO 2 concentrations can result in reduced photosynthesis, growth, and yield of plants (U.S. EPA, 2008c). These effects are cumulative over the season and are often not associated with visible foliar injury. As with foliar injury, these effects vary among species and growing environment.
SO 2 is also considered the primary factor causing the death of lichens in many urban and industrial areas (Hutchinson et al., 1996). The ISA for NO x /SO x — Ecological Criteria concluded

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- 68 that the evidence is sufficient to infer a causal relationship between SO 2 injury to vegetation (U.S. EPA, 2008c).

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. 6 .2.4 Mercury

- Related Co

- benefits Associated with the Role of Sulfate in Mercury Methylation
Mercury is a per sistent, bioaccumulative toxic metal that is emitted from in three forms: gaseous elemental Hg (Hg 0 ), oxidized Hg compounds (Hg +2 ), and particle

- bound Hg (Hg P ). Methylmercury (MeHg) is formed by microbial action in the top layers of sediment and soils, aft er Hg has precipitated from the air and deposited into waterbodies or land. Once formed, MeHg is taken up by aquatic organisms and bioaccumulates up the aquatic food web. Larger predatory fish may have MeHg concentrations many times, typically on the order of one million times, that of the concentrations in the freshwater body in which they live.

The NO x SO x ISA

— Ecological Criteria concluded that evidence is sufficient to infer a causal relationship between sulfur deposition and increased mercury methylatio n in wetlands and aquatic environments (U.S. EPA, 2008c). Specifically, there appears to be a relationship between SO 4 2

- deposition and mercury methylation; however, the rate of mercury methylation varies according to several spatial and biogeochemical factors whose influence has not been fully quantified (see Figure 6

- 1 4 ). Therefore, the correlation between SO 4 2

- depositio n and MeHg could not be quantified for the purpose of interpolating the association across waterbodies or regions. Nevertheless, because changes in MeHg in ecosystems represent changes in significant human and ecological health risks, the association betwe en sulfur and mercury cannot be neglected (U.S. EPA, 2008c).

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- 69 Figure 6

- 1 4

. Spatial and Biogeochemical Factors Influencing MeHg Production

As research evolves and the computational capacity of models expands to meet the complexity of mercury methylation p rocesses in ecosystems, the role of interacting factors may be better parsed out to identify ecosystems or regions that are more likely to generate higher concentrations of MeHg. Figure 6

- 1 5 illustrates the type of current and forward

- looking research bein g developed by the U.S. Geological Survey (USGS) to synthesize the contributing factors of mercury and to develop a map of sensitive watersheds. The mercury score referenced in Figure 6

- 1 5 is based on SO 4 2

- concentrations, acid neutralizing capacity (ANC), levels of dissolved organic carbon and pH, mercury species concentrations, and soil types to gauge the methylation sensitivity (Myers et al., 2007).

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- 70 Figure 6

- 1 5

. Preliminary USGS Map of Mercury Methylation

– Sensitive Watersheds
Source: Myers et al., 2007
Interdependent biogeochemical factors preclude the existence of simple sulfate

- related mercury methylation models. It is clear that decreasing sulfate deposition is likely to result in decreased M eHg concentrations. Future research may allow for the characterization of a usable sulfate

- MeHg response curve; however, no regional or classification calculation scale can be created at this time because of the number of confounding factors.

Decreases in SO 4 2

- deposition have already shown promising reductions in MeHg. Observed decreases in MeHg fish tissue concentrations have been linked to decreased acidification and declining SO 4 2

- and mercury deposition in Little Rock Lake, WI (Hrabik and Watras, 2002) , and to decreased SO 4 2

- deposition in Isle Royale in Lake Superior, MI (Drevnick
et al., 2007). Although the possibility exists that reductions in SO 4 2

- emissions could generate a pulse in MeHg production because of decreased sulfide inhibition in sulfate

- saturated waters, this effect would likely involve a limited number of U.S. waters (Harmon et al., 2007). Also, because of the diffusion and outward flow of both mercury

- sulfide complexes and SO 4 2

- ,

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- 71 increased mercury methylation downstream may still occur in sulfate

- enriched ecosystems with increased organic matter and/or downstream transport capabilities.

Remediation of sediments heavily contaminated with mercury has yielded significant reductions of MeHg in biotic tissues. Establishing quantitative relat ions in biotic responses to MeHg levels as a result of changes in atmospheric mercury deposition, however, presents difficulties because direct associations can be confounded by all of the factors discussed in this section. Current research does suggest th at the levels of MeHg and total mercury in ecosystems are positively correlated, so that reductions in mercury deposited into ecosystems would also eventually lead to reductions in MeHg in biotic tissues. Ultimately, an integrated approach that involves th e reduction of both sulfur and mercury emissions may be most efficient because of the variability in ecosystem responses. Reducing SO X emissions could have a beneficial effect on levels of MeHg in many waters of the United States.

MeHg is the only form of mercury that biomagnifies in the food web. Concentrations of MeHg in fish are generally on the order of a million times the MeHg concentration in water. In addition to mercury deposition, key factors affecting MeHg production and accumulation in fish inclu de the amount and forms of sulfur and carbon species present in a given waterbody. Thus, two adjoining water bodies receiving the same deposition can have significantly different fish mercury concentrations.

Methylmercury builds up more in some types of fi sh and shellfish than in others. The levels of methylmercury in high and shellfish vary widely depending on what they eat, how long they live, and how high they are in the food chain. Most fish, including ocean species and local freshwater fish, contain so me methylmercury. In general, higher mercury concentrations are expected in top predators, which are often large fish relative to other species in a waterbody.

The ecosystem service most directly affected by sulfate

- mediated mercury methylation is the prov ision of fish for consumption as a food source. This service is of particular importance to groups engaged in subsistence fishing, pregnant women and young children.

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. 6 .3 Ecosystem Co

- benefits from Reductions in Mercury Emissions Deposition of mercury to waterbodies can also have an impact on ecosystems and wildlife. Mercury contamination is present in all environmental media with aquatic systems experiencing the greatest exposures due to bioaccumulation. Bioaccumulation refers to the net

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- 72 uptake of a contaminant from all possible pathways and includes the accumulation that may occur by direct exposure to contaminated media as well as uptake from food.

Atmospheric mercury enters freshwater ecosystems by direct deposition and through runoff from terrestrial watersheds. Once mercury deposits, it may be converted to organic methylmercury mediated primarily by sulfate

- reducing bacteria. Methylation is enhanced in anaerobic and acidic environments, greatly increasing mercury toxicity and p otential to bioaccumulate in aquatic foodwebs. A number of key biogeochemical controls influence the production of methylmercury in aquatic ecosystems. These include sulfur, pH, organic matter, iron, mercury “ aging , ” and bacteria type and activity (Munthe et al., 2007).

Wet and dry deposition of oxidized mercury is a dominant pathway for bringing mercury to terrestrial surfaces. In forest ecosystems, elemental mercury may also be absorbed by plants stomatally, incorporated by foliar tissues and released in litterfall (Ericksen et al., 2003). Mercury in throughfall, direct deposition in precipitation, and uptake of dissolved mercury by roots (Rea et al., 2002) are also important in mercury accumulation in terrestrial ecosystems.

Soils have significant capacit y to store large quantities of atmospherically deposited mercury where it can leach into groundwater and surface waters. The risk of mercury exposure extends to insectivorous terrestrial species such as songbirds, bats, spiders, and amphibians that receive mercury deposition or from aquatic systems near the forest areas they inhabit (Bergeron et al., 2010a, b; Cristol et al., 2008; Rimmer et al., 2005; Wada et al., 2009 & 2010).

Numerous studies have generated field data on the levels of mercury in a variet y of wild species. Many of the data from these environmental studies are anecdotal in nature rather than representative or statistically designed studies. The body of work examining the effects of these exposures is growing but still incomplete given the c omplexities of the natural world. A large portion of the adverse effect research conducted to date has been carried out in the laboratory setting rather than in the wild; thus, conclusions about overarching ecosystem health and population effects are diffi cult to make at this time. In the sections that follow numerous effects have been identified at d iffering exposure levels.

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. 6 .3.1 Mercury Effects on Fish A review of the literature on effects of mercury on fish (Crump and Trudeau, 2009) reports results fo r numerous species including trout, bass (large and smallmouth), northern

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- 73 pike, carp, walleye, salmon and others from laboratory and field studies. The effects studied are reproductive and include deficits in sperm and egg formation, histopathological chan ges in testes and ovaries, and disruption of reproductive hormone synthesis. These studies were conducted in areas from New York to Washington and while many were conducted by adding MeHg to water or diet many were conducted at current environmental levels . While we cannot determine at this time whether these reproductive deficits are affecting fish populations across the United States it should be noted that it is possible that over time reproductive deficits could have an effect on populations. Lower fish populations would conceivably impact the ecosystem services like recreational fishing derived from having healthy aquatic ecosystems quite apart from the effects of consumption advisories due to the human health effects of mercury.

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. 6 .3.2 Mercury Effects on Birds In addition to effects on fish, mercury also affects avian species. In previous reports (U.S.
EPA , 1997; 2005), much of the focus has been on large piscivorous species in particular the common loon. The loon is most visible to the public during t he summer breeding season on northern lakes and they have become an important symbol of wilderness in these areas (McIntyre and Barr, 1997). A multitude of loon watch, preservation, and protection groups have formed over the past few decades and have been instrumental in promoting conservation, education, monitoring, and research of breeding loons (McIntyre and Evers, 2000; Evers, 2006). Significant adverse effects on breeding loons from mercury have been found to occur including behavioral (reduced nest

- si tting), physiological (flight feather asymmetry) and reproductive (chicks fledged/territorial pair) effects (Evers, 2008). Additionally Evers, et al (2008) report that they believe that the weight of evidence indicates that population

- level effects occur i n parts of Maine and New Hampshire, and potentially in broad areas of the loon ’ s range.
Recently attention has turned to other piscivorous species such as the white ibis, and great snowy egret. While considered to be fish

- eating generally these wading bird s have a very wide diet including crayfish, crabs, snails, insects and frogs. These species are experiencing a range of adverse effects due to exposure to mercury. The white ibis has been observed to have decreased foraging efficiency (Adams and Frederick, 2008). Additionally ibises have been shown to exhibit decreased reproductive success and altered pair behavior (Frederick and Jayasena, 2010). These effects include significantly more unproductive nests, male/male pairing, reduced courtship behavior (head bobbing and pair bowing) and lower nestling production by exposed males. In this study, a worst

- case scenario suggested by the results could involve up to a 50%

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- 74 reduction in fledglings due to MeHg in diet. These estimates may be conservative if male/male pairing in the wild it could result in a shortage of partners for females and the effect of homosexual breeding would be magnified. In egrets, mercury has been implicated in the decline of the species in south Florida (Sepulveda, et al., 1999) and Hoffman (2010) has shown that egrets show liver and possibly kidney effects. While ibises and egrets are most abundant in coastal areas and these studies were conducted in south Florida and Nevada the ranges of ibises and egrets extend to a large portion of the Un ited States. Ibis territory can range inland to Oklahoma, Arkansas and Tennessee. Egret range covers virtually the entire United States except the mountain west.

Insectivorous birds have also been shown to suffer adverse effects due to mercury
exposure. Th ese songbirds such as Bicknell ’ s thrush, tree swallows and the great tit have shown reduced reproduction, survival, and changes in singing behavior. Exposed tree swallows produced fewer fledglings (Brasso, 2008), lower survival (Hallinger, 2010) and had compromised immune competence (Hawley, 2009). The great tit has exhibited reduced singing behavior and smaller song repertoire in an area of high contamination in the vicinity of a metallurgic smelter in Flanders (Gorissen, 2005).

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. 6 .3.3 Mercury Effects o n Mammals
In mammals, adverse effects have been observed in mink and river otter, both fish eating species. For otter from Maine and Vermont maximum concentrations on Hg in fur nearly equal or exceed a concentration associated with mortality and concentrat ion in liver for mink in Massachusetts/Connecticut and the levels in fur from mink in Maine exceed concentrations associated with acute mortality (Yates, 2005). Adverse sublethal effects may be associated with lower Hg concentrations and consequently be mo re widespread than potential acute effects. These effects may include increased activity, poorer maze performance, abnormal startle reflex, and impaired escape and avoidance behavior (Scheuhammer et al., 2007).

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. 6 .3.4 Mercury Ecological Conclusions

The st udies cited here provide a glimpse of the scope of mercury effects on wildlife particularly reproductive and survival effects. These effects range across species from fish to mammals and spatially across a wide area of the United States. The literature is far from complete however. Much more research is required to establish a link between the ecological effects on wildlife and the effect on ecosystem services (services that the environment provides

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- 75 to people) for example recreational fishing, bird watching and wildlife viewing. The EPA is not, however, currently able to quantify or monetize the co

- benefits of reducing mercury exposures affecting provision of ecosystem services.

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. 6 .4 Vegetation Co

- benefits from Reductions in Ambient Ozone

Illustrative emission reduction s trategies that include NO x emission reductions would affect ambient ozone concentrations. Ozone causes discernible injury to a wide array of vegetation (U.S. EPA, 2006a; Fox and Mickler, 1996). Air pollution can affect the environment

a nd affect eco logical systems, leading to changes in the ecological com munity and influencing the diversity, health, and vigor of individual species (U.S. EPA, 2006a). In terms of forest productivity and ecosystem diversity, ozone may be the pollutant wit h the greatest potential for regional

- scale forest impacts (U.S. EPA, 2006a). Studies have demonstrated repeatedly that ozone concentrations commonly observed in polluted areas can have substantial impacts on plant function (De Steiguer et al., 1990; Pye, 1988).

When ozone is present in the air, it can enter the leaves of plants, where it can cause significant cellular damage. Like carbon dioxide (CO 2 ) and other gaseous substances, ozone enters plant tissues primarily through the stomata in leaves in a proc ess called “ uptake ” (Winner and Atkinson, 1986). Once sufficient levels of ozone (a highly reactive substance), or its reaction products, reaches the interior of plant cells, it can inhibit or damage essential cellular components and functions, including enzyme activities, lipids, and cellular membranes, disrupting the plant ’ s osmotic (i.e., water) balance and energy utilization patterns (U.S. EPA, 2006a; Tingey and Taylor, 1982). With fewer resources available, the plant reallocates existing

resources awa y from root growth and storage, above ground growth or yield, and reproductive processes, toward leaf repair and maintenance, leading to reduced growth and/or reproduction. Studies have shown that plants stressed in these ways may exhibit a general loss of vigor, which can lead to secondary impacts that modify plants ’ responses to other environmental factors. Specifically, plants may become more sensitive to other air pollutants, or more susceptible to disease, pest infestation, harsh weather (e.g., drought , frost) and other environmental stresses, which can all produce a loss in plant vigor in ozone

- sensitive species that over time may lead to premature plant death. Furthermore, there is evidence that ozone can interfere with the formation of mycorrhiza, es sential symbiotic fungi associated with the roots of most terrestrial plants, by reducing the amount of carbon available for transfer from the host to the symbiont (U.S. EPA, 2006a).

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- 76 This ozone damage may or may not be accompanied by visible injury on leav es, and likewise, visible foliar injury may or may not be a symptom of the other types of plant damage described above. Foliar injury is usually the first visible sign of injury to plants from ozone exposure and indicates impaired physiological processes i n the leaves (Grulke, 2003). When visible injury is present, it is commonly manifested as chlorotic or necrotic spots, and/or increased leaf senescence (accelerated leaf aging). Visible foliar injury reduces the aesthetic value of ornamental vegetation and trees in urban landscapes and negatively affects scenic vistas in protected natural areas.

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 lower concentrations experienced for a longer duration have the potential to create chronic stress on sensitive vegetation. Not all plants, however, are equally sensitive to ozone. Much of th e variation in sensitivity between individual plants or whole species is related to the plant ’ s ability to regulate the extent of gas exchange via leaf stomata (e.g., avoidance of ozone uptake through closure of stomata) and the relative ability of species to detoxify ozone

- generated reactive oxygen free radicals (U.S. EPA, 2006a; Winner, 1994). After injuries have occurred, plants may be capable of repairing the damage to a limited extent (U.S. EPA, 2006a). Because of the differing sensitivities among plan ts to ozone, ozone pollution can also exert a selective pressure that leads to changes in plant community composition. Given the range of plant sensitivities and the fact that numerous other environmental factors modify plant uptake and response to ozone, it is not possible to identify threshold values above which ozone is consistently toxic for all plants.

Because plants are at the base of the food web in many ecosystems, changes to the plant community can affect associated organisms and ecosystems (includ ing the suitability of habitats that support threatened or endangered species and below ground organisms living in the root zone). Ozone impacts at the community and ecosystem level vary widely depending upon numerous factors, including concentration and t emporal variation of tropospheric ozone, species composition, soil properties and climatic factors (U.S. EPA, 2006a). In most instances, responses to chronic or recurrent exposure in forested ecosystems are subtle and not observable for many years. These i njuries can cause stand

- level forest decline in sensitive ecosystems (U.S. EPA, 2006a, McBride et al., 1985; Miller et al., 1982). It is not yet possible to predict ecosystem responses to ozone with certainty; however, considerable knowledge of

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- 77 potential e cosystem responses is available through long

- term observations in highly damaged forests in the U.S. ( U.S. EPA, 2006a).

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. 6 .4.1 Ozone Effects on Forests Air pollution can affect the environment and affect eco logical systems, leading to changes in the ecol ogical com munity and influencing the diversity, health, and vigor of individual species (U.S. EPA, 2006a). Ozone has been shown in numerous studies to have a strong effect on the health of many plants, including a variety of co mmercial and ecologically im por tant forest tree species throughout the United States (U.S. EPA, 2007b).

In the U.S., this data comes from the U.S. Department of Agriculture (USDA) Forest Service Forest Inventory and Analysis (FIA) program. As part of its Phase 3 program (formerly kno wn as Forest Health Monitoring), FIA looks for visible foliar injury of ozone

- sensitive forest plant species at each ground monitoring site across the country (excluding woodlots and urban trees) that meets certain minimum criteria. Because ozone injury is cumulative over the course of the growing season, examinations are conducted in July and August, when ozone concentrations and associated injury are typically highest.

Monitoring of ozone injury to plants by the U.S. Forest Service has expanded over the l ast 15 years from monitoring sites in 10 states in 1994 to nearly 1,000 monitoring sites in 41 states in 2002. Since 2002, the monitoring program has further expanded to 1,130 monitoring sites in 45 states. Figure 6

- 16 shows the results of this monitoring program for the year 2002 broken down by U.S. EPA Regions. 45 Figure 6

- 17 identifies the counties that were included in Figure 6

- 1 6 , and provides the county

- level data regarding the presence or absence of ozone

related i njury. As shown in Figure 6

- 1 6 , large geographic areas of EPA Regions 6, 8, and 10 were not included in the assessment. Ozone damage to forest plants is classified using a subjective five

- category biosite index based on expert opinion, but designed to be e quivalent from site to site. Ranges of biosite values translate to no injury, low or moderate foliar injury (visible foliar injury to highly sensi tive or moderately sensitive plants, respectively), and high or severe foliar injury, which would be expected to result in tree

- level or ecosystem

- level responses, respectively (U.S. EPA, 2006a; Coulston, 2004). The highest percentages of observed high and severe foliar injury, which are most likely to be associated with tree or ecosystem

- level responses, are pri marily found in the Mid

- Atlantic and Southeast regions. While the assessment showed considerable regional variation in ozone injury, this assessment targeted different

45 The data are based on averages of all observations collected in 2002, which is the last year for which data are publicly available. For more information , please consult EPA ’ s 2008 Report on the Environment (U.S. EPA, 2008b).

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- 78 ozone

- sensitive species in different parts of the country with varying ozone sensitivity , which contributes to the apparent regional differences. It is important to note that ozone can have other, more significant impacts on forest plants ( e.g., reduced biomass growth in trees) prior to showing signs of visible foliar injury (U.S. EPA, 2006a)

. Assessing the impact of ground

- level ozone on forests in the U.S. involves understanding the risks to sensitive tree species from ambient ozone concentrations and accounting for the prevalence of those species within the forest. As a way to quantify the risks to particular plants from ground

- level ozone, scientists have developed ozone

- exposure/tree

- response functions by exposing tree seedlings to different ozone levels and measuring reductions in growth as

“ biomass loss. ” Typically, seedlings are used be cause they are easy to manipulate and measure their growth loss from ozone pollution. The mechanisms of susceptibility to ozone within the leaves of seedlings and mature trees are identical, and the decreases predicted using the seedlings should be related to the decrease in overall plant fitness for mature trees, but the

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- 79 c Degree c Degree of Injury: These categories reflect a subjective index based on expert opinion. Ozone can have other, more significant impacts on forest plants (e.g., reduced biomass growth in trees) prior to showing signs of visible foliar injury.
Figure 6

- 16. Visible Foliar Injur y to Forest Plants from Ozone in U.S. by EPA Regions a,b,c

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- 80 Figure 6

- 17. Presence and Absence of Visible Foliar Injury, as Measured by U.S. Forest

Service, 2002
Source: U.S. EPA, 2007b
magnitude of the effect may be higher or lower depending on the tree sp ecies (Chappelka and Samuelson, 1998). In areas where certain ozone

- sensitive species dominate the forest community, the biomass loss from ozone can be sig nificant. Experts have identified 2% annual biomass loss as a level of concern, which would cause lo ng term ecological harm as the short

term negative effects on seedlings compound to affect long

- term forest health (Heck and Cowling, 1997).

Ozone damage to the plants including the trees and understory in a forest can affect the ability of the forest to s ustain suitable habitat for associated species particularly threatened and endangered species that have existence value

— a nonuse ecosystem service

— for the public. Similarly, damage to trees and the loss of biomass can affect the forest ’ s provisioning servi ces in the form of timber for various commercial uses. In addition, ozone can cause discoloration of leaves and more rapid senescence (early shedding of leaves), which could negatively affect fall

color tourism because the fall foliage would be less availa ble or less attractive. Beyond the aesthetic damage to fall color vistas, forests provide the public with many other recreational

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- 81 and educational services that may be affected by reduced forest health including hiking, wildlife viewing (including bird watc hing), camping, picnicking, and hunting. Another potential effect of biomass loss in forests is the subsequent loss of climate regulation service in the form of reduced ability to sequester carbon and alteration of hydrologic cycles.

Some of the common tree species in the United States that are sensitive to ozone are black cherry ( Prunus serotina ), tulip

- poplar ( Liriodendron tulipifera) , and eastern white pine ( Pinus strobus)

. Ozone

- exposure/tree

- response functions have been developed for each of these t ree species, as well as for aspen ( Populus tremuliodes ), and ponderosa pine ( Pinus ponderosa ) (U.S. EPA, 2007b).

6

. 6 .4.2 Ozone Effects on Crops
Laboratory and field experiments have shown reductions in yields for agronomic crops exposed to ozone, including vegetables (e.g., lettuce) and field crops (e.g., cotton and wheat). Damage to crops from ozone exposures includes yield losses (i.e., in terms of weight, number, or size of the plant part that is harvested), as well as changes in crop quality (i.e., phys ical appearance, chemical composition, or the ability to withstand storage) (U.S. EPA, 2007b). The most extensive field experiments, conducted under the National Crop Loss Assessment Network (NCLAN) examined 15 species and numerous cultivars. The NCLAN res ults show that

“ several economically important crop species are sensitive to ozone levels typical of those found in the United States ” (U.S. EPA, 2006a). In addition, economic studies have shown reduced economic co

- benefits as a result of predicted reducti ons in crop yields, directly affecting the amount and quality of the provisioning service provided by these crops, associated with observed ozone levels (Kopp et al., 1985; Adams et al., 1986; Adams et al., 1989). In addition, visible foliar injury by itse lf can reduce the market value of certain leafy crops (such as spinach, lettuce). According to the Ozone Staff Paper, there has been no evidence that crops are becoming more tolerant of ozone (U.S. EPA, 2007b). Using the Agriculture Simulation Model (AGSIM ) (Taylor, 1994) to calculate the agricultural benefits of reductions in ozone exposure, the EPA estimated that attaining a W126 standard of 13 ppm

- hr would produce monetized benefits of approximately $400 million to $620 million in 2006 (inflated to 2006 dollars) (U.S. EPA, 2007b). 46

46 These estimates illustrate the value of vegetation effects from a substantial reduction of ozone concentrations, not the marginal change in ozone concentrations anticipated a result of the emission reductions achieved by this rule.

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- 82 6

. 6 .4.3 Ozone Effects on Ornamental Plants
Urban ornamental plants are an additional vegetation category likely to experience some degree of negative effects associated with exposure to ambient ozone levels. Several ornamental species have been listed as sensitive to ozone (Abt Associates, 1995). Because ozone causes visible foliar injury, the aesthetic value of ornamental plants (such as petunia, geranium, and poinsettia) in urban landscapes would be reduced (U.S. EPA, 2007b). Sensitive ornamental species would require more frequent replacement and/or increased maintenance (fertilizer or pesticide application) to maintain the desired appearance because of exposure to ambient ozone (U.S. EPA, 2007b). In addition, many businesses rely on healthy

- looking vegetation for their livelihoods (e.g., horticulturalists, landscapers, Christmas tree growers, farmers of leafy crops, etc.). The ornamental landscaping industry is a multi

- billion dollar industry that affects both private property owners/tenants and governmental units responsible for public areas (Abt Associates, 1995). Preliminary data from the 2007 Economic Census indicate that the landscaping services industry, which is primarily engaged in providing landscape care and maintenan ce services and installing trees, shrubs, plants, lawns, or gardens, was valued at $53 billion (U.S. Census Bureau, 2010). Therefore, urban ornamentals represent a potentially large unquantified benefit category. This aesthetic damage may affect the enjoym ent of urban parks by the public and homeowners ’ enjoyment of their landscaping and gardening activities. In addition, homeowners may experience a reduction in home value or a home may linger on the market longer due to decreased aesthetic appeal. In the a bsence of adequate exposure

- response functions and economic damage functions for the potential range of effects relevant to ornamental plants, we cannot conduct a quantitative analysis to estimate these effects.

We are unable to provide an estimate of the ozone crop co

- benefits associated with the revised or alternative annual standard s due to data, time, and resource limitations.

6

. 7 References Abt Associates, Inc. 1995. Urban ornamental plants: sensitivity to ozone and potential economic losses. U.S. EPA, Office of Air Quality Planning and Standards, Research Triangle Park. Under contract to RADIAN Corporation, contract no. 68

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