From: Lydia Wegman/RTP/USEPA/US

To: "Frey, Nathan J." <Nathan_J._Frey@omb.eop.gov>, "Lee, Amanda I." 

<Amanda_I._Lee@omb.eop.gov>

Cc: Joseph-J Dougherty/DC/USEPA/US@EPA, Amy Lamson/RTP/USEPA/US@EPA, Darryl 

Weatherhead/RTP/USEPA/US@EPA

Date: 12/12/2012 05:00 PM

Subject: Fw: Revised Chapter 6 of PM RIA

Please find attached a revised version of Chapter 6 in track changes from the version previously sent to 

you. This version clarifies some of the language regarding visibility co-benefits, including the Chestnut 

and Rowe study. Please let us know if you have any questions. Thanks.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-2

E.O. 12866_PM NAAQS_2060-AO47_FRN_Welfare_Co-Benefits_20121120

CHAPTER 6

WELFARE CO-BENEFITS OF THE PRIMARY STANDARD

6.1 Synopsis

The emission reductions to meet the revised primary standard will have “welfare” cobenefits 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, ecological 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 nonmonetized 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 

attaining 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 case and 2020 

control case simulations that were used to develop the air quality ratios. 

6.2 Introduction to Welfare Benefits 

Illustrative emission 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 defines welfare effects to include any non-health effects, 

including direct damages to property, either through impacts on material structures or by 

soiling 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), NOX/SOX—Ecological Criteria (U.S. EPA, 2008), as well as the 

Criteria Document for ozoneand Ozone (U.S. EPA, 20062012a) 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 

so. These welfare effects include changes in visibility, materials damage, ecological effects from 

 

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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-3

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 emission 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 can be grouped into four 

categories: directly emitted PM (e.g., metals, organic compounds, dust), reductions of PM2.5 

precursors (e.g., NOx, SOx, VOCs), other ancillary reductions from the illustrative emission 

reduction strategies (e.g., mercury and CO2), and secondary co-pollutant formation from PM 

precursors (e.g., ozone from NOx and VOCs). Regardless of the category, these emission 

changes are anticipated to affect ambient concentrations and deposition, and consequently 

affect public welfare. It is therefore 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, welfare cobenefits 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 cobenefits, to the aggregate total for the cost-benefit comparison. These unquantified benefits 

and co-benefits may be substantial, although the magnitude is highly uncertain. We 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 in Table 6-2.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-4

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 

(SO2)

Vegetation 

Injury 

(Ozone)

Materials 

Damage Climate

Ecosystem 

Effects—

(Organics 

& Metals)

Acidification 

(freshwater)

Nitrogen 

Enrichment

Mercury 

Methylation

Direct

PM2.5

   

NOx      

SO2      

VOCs    

PM10   

Hg  

CO2 

 = 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 theour approach to estimate those visibility 

co-benefits. Even though if we do not havehad 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 analysesdo 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 approach is 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. 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-5

(continued)

Table 6-2. Quantified and Unquantified Welfare Co-Benefits

Benefits Category 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 CO2 — — Section 6.5, SCC 

TSDb

Climate impacts from ozone and 

PM

— — Section 6.5, 

Ozone ISA, PM 

ISAc

Other climate impacts (e.g., other 

GHGs, other impacts) 

— — Section 6.5, IPCCc

Reduced effects on materials Household soiling — — Section 6.4, PM 

ISAc

Materials damage (e.g., corrosion, 

increased wear)

— — Section 6.4, PM 

ISAc

Reduced effects from PM 

deposition (metals and 

organics)

Effects on Individual organisms 

and ecosystems

— — Section 6.6.1, PM 

ISAc

Reduced vegetation and 

ecosystem effects from 

exposure to ozone

Visible foliar injury on vegetation — — Section 6.6.4, 

Ozone ISAc

Reduced vegetation growth and 

reproduction

— — Section 6.6.4, 

Ozone ISAb

Yield and quality of commercial 

forest products and crops

— — Section 6.6.4, 

Ozone ISAb,d

Damage to urban ornamental 

plants

— — Section 6.6.4, 

Ozone ISAc

Carbon sequestration in terrestrial 

ecosystems

— — Ozone ISAc

Recreational demand associated 

with forest aesthetics

— — Ozone ISAc

Other non-use effects Ozone ISAc

Ecosystem functions (e.g., water 

cycling, biogeochemical cycles, 

net primary productivity, leaf-gas 

exchange, community 

composition)

— — Ozone ISA2
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-6

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, 

NOx SOxISAb

Tree mortality and decline — — Section 6.6.2, 

NOx SOxISAc

Commercial fishing and forestry 

effects

— — Section 6.6.2, 

NOx SOxISAc

Recreational demand in terrestrial 

and aquatic ecosystems

— — Section 6.6.2, 

NOx SOxISAc

Other non-use effects Section 6.6.2, 

NOx SOxISAc

Ecosystem functions (e.g., 

biogeochemical cycles)

— — Section 6.6.2, 

NOx SOxISAc

Reduced effects from 

nutrient enrichment

Species composition and 

biodiversity in terrestrial and 

estuarine ecosystems

— — Section 6.6.2, 

NOx SOxISAc

Coastal eutrophication — — Section 6.6.2, 

NOx SOxISAc

Recreational demand in terrestrial 

and estuarine ecosystems

— — Section 6.6.2, 

NOx SOxISAc

Other non-use effects Section 6.6.2, 

NOx SOxISAc

Ecosystem functions (e.g., 

biogeochemical cycles, fire 

regulation)

— — Section 6.6.2, 

NOx SOxISAc

Reduced vegetation effects 

from ambient exposure to 

SO2 and NOx

Injury to vegetation from SO2

exposure

— — Section 6.6.2, 

NOx SOxISAc

Injury to vegetation from NOx

exposure

— — Section 6.6.2, 

NOx SOxISAc

Reduced ecosystem effects 

from exposure to 

methylmercury (through the 

role of sulfate in 

methylation)

Effects on fish, birds, and 

mammals (e.g., reproductive 

effects)

— — Section 6.2 and 

6.6.3, Mercury 

Study RTCc,d

Commercial, subsistence and 

recreational fishing

— — Section 6.2 and 

6.6.3, Mercury 

Study RTCc

aWe quantify these co-benefits in an 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.

bWe assess these co-benefits qualitatively due to time and resource limitations for this RIA.

cWe assess these co-benefits qualitatively because we do not have sufficient confidence in available data or 

methods.

dWe 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-7

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 PM2.5 as well as 

precursor emissions such as NOx and SO2 for an alternative annualstandard at 11 μg/m3. 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 

discusses 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 

atmosphere 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, 1996). The extent to which any amount of light extinction 

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 source 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.

 

2 We use the term VAQ to refer to the visibility effects caused solely by air quality conditions, excluding fog.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-8

Figure 6-1. Important Factors Involved in Seeing a Scenic Vista (Malm, 1999)

Visibility is commonly measured as either light extinction (βext), 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 

deciview corresponds to a change of about 10% in available light.3Pitchford 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 

impairment (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),

 

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 decrease 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 visibility but may not be perceptible to the eye. The visibility co-benefits 

analysisapproach 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 changes exceeding one deciview. Annual 

averages appear to more closely correspond to the economic literature relied upon for valuation of visibility 

changes in this analysis. The secondary PM NAAQS uses a different averaging time than the benefits analysis (see 

Chapter 13).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-9

(6.1)

where VR denotes visual range (in kilometers) and βext 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 nitrate 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 dust 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, thus resulting in increased light scattering (U.S. EPA, 2009b).

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 emissions 

of SO2 and NOx 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 1992.6The EPA’s recent regulations such as the Cross-State Air 

Pollution Rule (U.S. EPA, 2011c) and the Mercury and Air Toxics Standard (U.S. EPA, 2011d) are 

anticipated to reduce SO2 emissions down to 2 million tons nationally, which would lead to 

substantial further improvement in visibility 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 

 

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.

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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-10

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 attributable 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 CAAA (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).

Figure 6-2. Visibility in Selected National Parks and Wilderness Areas in the U.S., 1992–

2008a,b

(Source: U.S. EPA (2008) updated, IMPROVE (2010))
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-11

Figure 6-3. Estimated Improvement in Annual Average Visibility Levels Associated with the 

CAAA Provisions in 2020

Source: U.S. EPA, 2011b7

 

7

It is important to note that visibility levels shown in these maps were modeled 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). PleaseIn addition, please note that these maps present annual average visibility 

levels, which are different than the short-term averages being considered for the secondary standard.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-12

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 of 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.8In our approach, we generate light extinction 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).9The procedure for calculating light extinction associated with 

the revised and alternative annual standards is described in detail in Chapter 3 of this RIA. In 

addition, Appendix 6.A describes how the spatial resolution of the light extinction estimates 

would 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 annual 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 improved 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 days. 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, 2010a), but the available data 

and valuation studies do not allow such fine temporal resolution.

 

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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-13

While our approach is a substantial improvement in the methods to estimate 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 potential impact of omitting 

coarse particles from the light extinction estimates for recreational and residential visibility. For 

these sensitivity analyses, we selected the levels of coarse particles to represent the full range 

of possible annual concentrations 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/m3nationwide, 15 μg/m3in the Southwest with 5 μg/m3in 

the rest of the country, and 15 μg/m3in the Southwest with 8 μg/m3in 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 CoBenefits Approacha

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/m3

in the Southwest and 8 μg/m3in 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-14

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 recreational 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 associated 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 distinguishing visibility from other aspects of air pollution (e.g., McClelland et al., 

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 

 

11 See Section 169(a) of the Clean Air Act.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-15

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 doublecounting 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. However, the 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 approach, we take care to minimize the number of 

overlapping areas and their contributions. Specifically, we believe that the potential for doublecounting 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 the residential visibility cobenefits 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. For 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 monetized 

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 

 

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 primarymain benefits estimates, while providing the rest of the visibility co-benefits in sensitivity analyses.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-16

co-benefits would be expected to increase each year for the same 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-established and 

has been used in numerous analyses by the EPA (U.S. EPA, 1999; 2005; 2006; 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 have 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 35714), 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 Service (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 

Class 1 areas across the country (U.S. EPA, 2009b).15 The IMPROVE monitoring network 

measures fine particles, coarse particles, and key PM2.5 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 169(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 

Service. 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-17

Figure 6-4. Mandatory Class 1 Areas in the U.S.

For 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, 1990a; 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 as 

the basis for monetary estimates of the co-benefits of visibility changes in recreational areas.

eEven 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 reports (NAPAP, 1991; SAMI, 2002; U.S. 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-18

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 those 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, studies 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 within 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 with 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 (Chestnut 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, 1999b). 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 SABCouncil 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-19

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. This 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 national 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 

improvements 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 income. 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 for 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,

ρ = shape parameter (0.1),

 

18 The parameters for each region are available in Appendix 6a of this RIA.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-20

γ = parameter corresponding to the visibility at in-region parks,

Q0 = starting visibility, and

Q1 = visibility after change.

As discussed in more detail in Appendix 6.A of this RIA, our approach 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 in 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 

parks 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 visitation 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 numerous, 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 

of changes being 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 

 

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 representative 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 

Statistical 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. 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-21

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, the primary estimate for recreational visibility only includes co-benefits

for 86 Class 1 areas in the original study regions (i.e., California, 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 Chestnut 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 non-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 different 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 nonstudied 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.

Table 6-4. WTP for Visibility Improvements in Class 1 Areas in Non-Studied Park Regions

Park Region Source of WTP Estimate

 

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 includes

the states of Idaho, Montana, 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-22

1. Northwest Benefits transfer 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 Areasa

a

TheaThe 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 Smith et al. survey assessed WTP for changes in 

summertime visibility using the base photograph of Shenandoah National Park. Unlike the 

Chestnut and Rowe survey, the Smith et al. survey only assessed the Shenandoah National Park, 

did not estimate in-region estimates 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 

ys
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-23

evaluating the 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 for 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). Furthermore, 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 inputs), 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 cobenefits estimates. Though we are unable to quantify the cumulative effect of all of these 

uncertainties in our approach, we do provide information on uncertainty based on the available 

data, including model evaluation25 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.

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

is the benefits transfer process. Choices 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.

 

25See Chapter 4 for more information on model evaluation.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-24

Table 6-5. Summary of Key Assumptions in Estimating Recreational Visibility Co-benefitsa

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

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

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 limitations, including:

 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 and 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 wilderness areas, even other parks 

within the studied park regions, without introducing additional uncertainty.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-25

 The survey focused only on populations in five states, so the application of the 

estimated values to populations outside those states requires that preferences 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 

to 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 were 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 they 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., visibility at other 

parks) or budget constraints. These reminders are considered to be best practice for 

stated preference surveys.

6.3.5 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 some 

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 Metropolitan 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-26

foundation for the secondary 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 

these studies indicate that some individuals considered the visual air quality associated with 

ambient levels of air pollution in urban areas to be unacceptable, these studies do not provide 

sufficient information on which to develop monetized co-benefits estimates. Specifically, the 

public perception studies do not provide preferences expressed 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 their 

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 

approach for estimating residential visibility 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 Congress (U.S. EPA, 2011)28 and reviewed by the SAB-Council (U. S. EPA-SAB, 2004, 

2010a, 2010b).

To value residential visibility improvements, the new approach draws upon information 

fromreported in the Brookshire et al. (1979), Loehman et al. (1985) and Tolley et al. (19846) 

 

26 For more detail about these 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. As a result of these concerns, the Council recommended that residential 

visibility be omitted from the overall primary benefits estimate. (U.S. EPA-SAB, 1999)

28 This report is also known as the Second Prospective 812 analysis.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-27

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 results 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 accordance 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 comparable terms across study 

locations, we express household WTP for a change in visual range in a specific MSA using the 

following function:

(6.3)

where:

VR0 = mean annual visual range in miles before the improvement,

VR1 = mean annual visual range in miles after the improvement, and

β = parameter.

 

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 the specific 

details need to compute visibility benefits using Tolley et al. (19846) were not included in the published study 

(likely due to length restrictions in thein a peer-reviewed journal),, the overall work including study and survey 

design was subject to peer review during study development. (see Leggett et aland 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 Recognizing 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 conducted represent 15% of the total US population in 2020 (U.S. 

Census).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-28

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 visibility. 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% improvement 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 Residential 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. (19846) 321 $31 $72

Boston Tolley et al. (19846) 398 $38 $89

Chicago Tolley et al. (19846) 310 $30 $69

Denver Tolley et al. (19846) 696 $66 $155

Los Angeles Brookshire et al. (1979) 94 $9 $21

Mobile Tolley et al. (19846) 313 $30 $70

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

Washington, DC Tolley et al. (19846) 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 

inconsistency 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 using the following 

function:

(6-4)
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-29

where:

m = household income,

ρ = shape parameter (0.1),

θ = WTP parameter corresponding to the visibility at MSA,

VR0 = starting visibility, and

VR1 = 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 includes 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 sensitivity 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 

to recognize the uncertainty associated with extrapolating beyond the studied cities. 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 to 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 and 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 

 

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

Census).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-30

have used. We assigned a valuation study area to each MSA based on two factors: geographic 

proximity 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 rarely 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 to 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 assigned 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 documentation 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 the 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 locationspecific characteristics that set it apart from Denver. 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-31

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 limitations. 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.

 The vintage of the surveys (1970s and 1980s) invites questions whether the values 

are still valid for current populations, or more importantly for our approach, future 

populations in 2020.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-32

 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 health effects.

Table 6-7. Summary of Key Assumptions in the Residential Visibility Co-benefitsa

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 Estimate Visibility Co-benefits

The hedonic model assumes that consumers do 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 

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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-33

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 (Graves 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 surrogate for environmental 

quality and Beron et al. (2001) acknowledge that their parameter estimates likely reflect a 

combination of visual aesthetics 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 and

consider the possibility of using hedonic property models to estimate residential visibility cobenefits (U.S. EPA-SAB, 2004). In response to this recommendation, the EPA evaluated the 

existing economic literature, and determined that there were substantial 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 participants 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 method 

through the use of U.S. Census microdata (Bayer et al., 2009), spatial statistical methods 

(Anselin and Le Gallo, 2006; Anselin and Lozana-Gracia, 2009; Beron et al., 2004; Kim et al., 

2010) and more complete air quality data and information about nonattainment 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 approaches, 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-34

Regardless of whether we use hedonic 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 

previously 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 damage-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 cobenefits is complex and suffers from unavoidable limitations. While we are confident that the 

underlying scientific literature supports a non-zero estimate for visibility 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 included 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 SABCouncil (U.S. EPA-SAB, 2010a, 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. We have addressed the SAB-Council’s concern regarding inconsistency between 

estimation of residential and recreational visibility highlighted by the SAB-Council in our 

approach. However, we do not have the data to address the SAB-Council’s concern regarding

inclusion of night-time benefits of visibility improvements in our annual average, which may 

lead to an underestimation of visibility benefits. To minimize uncertainties related to 

extrapolation and geographical double counting, our approach only includes 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 

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 controlling 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-35

for residential visibility co-benefits, and the benefit transfer technique for residential cobenefits. 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, valuation 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 nonzero 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 these valuation studies has limitations, which are identified in the sections 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. EPASAB, 2010a, 2010b). Because of time and resource constraints, performing original research for 

regulatory analyses of specific policy actions 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 from visibility valuation, 

usefulness of preference calibration, and potential role of hedonic valuation approaches. Many 

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, we provide the results of an illustrative analysis of the visibility cobenefits 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 quality 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-36

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 effects.

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 monuments 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 materials, 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, SO2 is more corrosive than NOx although mixtures of NOx, SO2

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 deposition. In addition, research has 

demonstrated that iron, copper, and aluminum-based products are subject to increased 

corrosion due to pollution (Irving, 1991). Information from both the PM ISA (U.S. EPA, 2009b) 

and NOx/SOx 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 soiling, 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 such as statues and works of art. Soiling occurs when PM 

accumulates on an object and alters the optical characteristics (appearance). The reflectivity of 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-37

a surface may be changed or presence of particulates may alter light transmission. These 

effects can reduce 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 repainting 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 cobenefits 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 cobenefits 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 frequency 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 deposition; and,

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

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 

analysis. 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 damages (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 PM2.5 and ozone, or even visibility cobenefits. However, studies of materials damage to historic buildings and outdoor artwork in 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-38

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 qualitative description of the 

avoided damage associated with reducing PM and PM precursor pollutants. Table 6-8 shows 

the effect of various PM2.5 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)

Ozone Rubber products (e.g., tires)

6.5 Climate Co-benefits

Actions taken by state and local 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) such as carbon dioxide (CO2), 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 cocontrolled GHG emission reductions, the energy and associated climate gas implications of 

control technologies assumed in the illustrative regulatory alternatives, and remaining 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-39

uncertainties regarding the impact of long-lived and short-lived climate forcer 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 

CO2 for the regulatory alternatives. Implementation strategies undertaken by state and local 

governments to comply with the standards 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 Effects 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,” which 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 CO2 differ from short-lived pollutants such as BC in the 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 

policies to address these emissions is gaining attention nationally and internationally (e.g., 

Black Carbon Report to Congress (U.S. EPA, 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 CO2 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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-40

6.5.1.1 Climate Effects of Black Carbon

Black carbon is the most strongly light‐absorbing component of PM2.5, 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 which BC affects climate distinguish it 

from long‐lived GHGs like CO2. This means that actions taken to reduce the BC constituents in 

direct PM2.5 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 energy than CO2 (Bond and Sun 2005). This 

strong absorptive capacity is the property most relevant to its potential to affect the Earth’s 

climate. When BC is deposited on snow and ice, it darkens the surface and decreases albedo, 

thereby increasing absorption and accelerating melting. Finally, BC also affects climate 

indirectly by altering the properties of clouds, affecting cloud reflectivity, precipitation, and 

surface dimming. These indirect impacts of BC are associated with all ambient particles and 

may lead 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. 

Snow 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 range, 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 western 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-41

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 effects 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 interchangeably 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. Pollutants such as SO2, NOX, and most OC particles 

tend to produce a cooling influence on climate. Exceptions include OC deposition on snow and 

ice, which leads to increased melting.

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 NOx 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 exhibit 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 CO2 is necessary 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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-42

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 the amount 

of BC relative to non-BC constituents emitted from a source is important. In general, these nonBC constituents are emitted in greater volume than BC, counteracting the warming influence of 

BC. Qualitatively, it seems likely that BC emission reductions associated with directly emitted 

PM2.5 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 indirect 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.

6.5.2 Climate Effects of Long-Lived Greenhouse Gases

The EPA Administrator found in 2009 that elevated concentrations of the six major 

GHGs, including CO2, 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 analysis 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 enrichment, 

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 individuals 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-43

welfare or have the potential to do so in the future. Some 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 interrelatedness of these categories means that any one 

ecosystem may provide multiple services. Changes in these services can affect human wellbeing by affecting security, health, social relationships, and access to basic material goods 

(MEA, 2005).

Figure 6-7. Linkages between Categories of Ecosystem Services 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. Provisioning: 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 obtain 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
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-44

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 valuation of 

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 water 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 likely 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 nonmonetized. 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 Process (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, copper, chromium, mercury, nickel, zinc, and lead. The 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-45

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 

biological organisms. While both fine and coarse-mode particles may affect plants and 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 alteration 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 provided 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 from 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 surfaces, 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-46

dependent upon the amount, solubility and chemical composition of the deposited PM. Uptake 

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 development.

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. 

(Arzavus, 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 bind 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 chiefly 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, change 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 cadmium, 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 reduced 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).

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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-47

component of storm water runoff (U.S. EPA, 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 contaminant 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 Western 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 database 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 fate 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 chemical 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.

 Presence of co-pollutants makes it difficult to attribute observed effects to 

ecological receptors to PM alone or one component of deposited PM.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-48

 Ecosystem effects linked to PM are difficult to determine because the changes may 

not be observed until pollutant deposition 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 

responses 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 variety 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 nitrogen 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 

NOX and SO2 gaseous emissions 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 

ecosystems across the U.S., contributing to the problems of acidification, nutrient enrichment, 

and methylmercury production as represented in Figures 6-9 and 6-10. Although there is some 

evidence that nitrogen deposition may have positive effects on agricultural 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, SO2 can affect vegetation at 

ambient levels near pollution sources.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-49

NOX 

Atmospheric 

Fate and 

Transport

Deposition 

Process

Acidification

Aquatic 

Ecosystems

Terrestrial 

Ecosystems

Nutrient 

Enrichment

Aquatic 

Ecosystems

Terrestrial 

Ecosystems
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-50

SO2 

Atmospheric 

Fate and 

Transport

Deposition 

Process

Acidification

Aquatic 

Ecosystems

Terrestrial 

Ecosystems

Methylmercury 

Production

NOX 

Atmospheric 

Fate and 

Transport

Deposition 

Process

Acidification

Aquatic 

Ecosystems

Terrestrial 

Ecosystems

Nutrient 

Enrichment

Aquatic 

Ecosystems

Terrestrial 

Ecosystems
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-51

Figure 6-9. Schematics of Ecological Effects of Nitrogen and Sulfur Deposition

Figure 6-10. Nitrogen and Sulfur Cycling, and Interactions in the Environment

Source: U.S. EPA, 2008c

SO2 

Atmospheric 

Fate and 

Transport

Deposition 

Process

Acidification

Aquatic 

Ecosystems

Terrestrial 

Ecosystems

Methylmercury 

Production
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-52

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. They 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 gasphase species that lead to the dry deposition of acidity are also precursors of particles. 

Therefore, reductions in NOX and SO2 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 surfaces 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 terrestrial and aquatic ecosystems across the U.S. Soil 

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 ability 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 ecosystems (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 levels of the food web in acid sensitive aquatic 

ecosystems. The ISA for NOx/SOx—Ecological Criteria concluded that the evidence is sufficient 

to infer a causal relationship between acidifying deposition and effects on biogeochemistry 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-53

related to aquatic ecosystems 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 

aluminum 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 reduced fish 

condition factor34, 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 aquatic 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 

protection for most fish (i.e., brook 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 possible 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.

 

34 Condition factor is an index that describes the relationship between fish weight and length, and is one measure 

of sublethal acidification stress that has been used to quantify effects of acidification on an individual fish (U.S.

EPA, 2008f).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-54

A number of national and regional assessments have been conducted to estimate the 

distribution and extent of surface 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. where 

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 surface 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 

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 affected by the reductions in available fish populations caused by surface water 

acidification.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-55

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 the northeastern United States 

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 

lake 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 Adirondack lakes. The survey 

described a base version with minor improvements said to result from the program, and a 

 

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 reductions achieved by this rule.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-56

scope version with large improvements due to the program and a gradually worsening status 

quo. After adapting and transferring the results of this 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 version. Using these estimates, the aggregate annual 

benefits of eliminating all anthropogenic sources of NOx and SOx 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 regulating 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 in 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. Inorganic 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) 

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 NOx/SOx—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 terrestrial 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 6-12 depicts the areas across the U.S. that are potentially sensitive to terrestrial 

acidification.

 

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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-57

Figure 6-12. 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 

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 lesser extent, the southeastern U.S., and acidifying deposition has 

been implicated as a causal factor (DeHayes et al., 1999). Figure 6-13 shows the distribution of 

red spruce (brown) and sugar maple (green) in the eastern U.S.

Terrestrial acidification affects 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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-58

Figure 6-13. 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 

provisioning services in the form of tree products. Sugar maples are a particularly important 

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, 2006), 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 northeastern United States are also an important source of cultural 

ecosystem services—nonuse (i.e., existence value for threatened and endangered species), 

 

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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-59

recreational, and aesthetic services. Red spruce forests are home to two federally listed species 

and one delisted 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 of 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 outdoor 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., 2008). 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 States 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 

home on 122 million days in 2006. For these recreational activities in the northeastern United 

States, 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, therefore, $4.4 billion and $4.2 

billion, respectively, in 2006 (U.S. EPA, 2009c).38

As previously mentioned, it is difficult to estimate the portion of these recreational 

services that are specifically attributable to forests and to the health of specific tree species.

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 landscapes. 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 

 

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 reductions achieved by this rule.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-60

Vermont, Brown (2002) reported 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 dollars) 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 services, including soil stabilization and erosion control, water regulation, 

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 with 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 uncertain.

6.6.2.2 Ecological Effects from Nitrogen Enrichment

Aquatic Enrichment. The ISA for NOx/SOx—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 States, 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 

 

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 rule.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-61

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 atmospheric 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 main 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, can 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; therefore, 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 

contributing to declines in SAV, high levels of 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 stocks 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 average 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 harvests, 

eutrophication in estuaries may also affect the demand for seafood. For example, a wellpublicized toxic pfiesteria bloom in the Maryland Eastern Shore in 1997, which involved 

thousands of dead and lesioned fish, led to an estimated $56 million (in 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-based recreational and aesthetic services. The 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-62

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 Census, 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 of $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 

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 prevention; 

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-shore 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 standards 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 NOx/SOx (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 deposition 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 NOx/SOx—Ecological Criteria concluded that the 

 

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 change in the value of the service as a 

result of the emission reductions achieved by this rule.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-63

evidence is sufficient to infer a causal relationship between nitrogen deposition and the 

alteration of species richness, 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. Although 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) 

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 enrichment 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 species 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 affect 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. Numerous 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 government 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. 

 

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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-64

Based on analyses in the NOx SOx REA average values of the total benefits in 2006 from 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 adult 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 services due to nitrogen deposition as those losses are already reflected in the 

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 fire 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 time 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 standards due to data, time, and resource 

limitations. Methods are not yet available to allow estimation of changes in ecosystem services 

due to nitrogen deposition.

6.7.2.3 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. SO2 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 

 

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 marginal change in the value of the service as a 

result of the emission reductions achieved by this rule.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-65

nitrogen than vascular plants (U.S. EPA, 2008c). Acute foliar injury 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 SO2 exposures over the growing season. Besides foliar injury, chronic exposure to low 

SO2 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.

SO2 is also considered the primary factor causing the death of lichens in many urban and 

industrial areas (Hutchinson et al., 1996). The ISA for NOx/SOx—Ecological Criteria concluded 

that the evidence is sufficient to infer a causal relationship between SO2 injury to vegetation 

(U.S. EPA, 2008c).

6.6.2.4 Mercury-Related Co-benefits Associated with the Role of Sulfate in Mercury Methylation

Mercury is a persistent, bioaccumulative toxic metal that is emitted from in three forms:

gaseous elemental Hg (Hg0), oxidized Hg compounds (Hg+2), and particle-bound Hg (HgP).

Methylmercury (MeHg) is formed by microbial action in the top layers of sediment and soils, 

after 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 NOx SOx ISA—Ecological Criteria concluded that evidence is sufficient to infer a 

causal relationship between sulfur deposition and increased mercury methylation in wetlands 

and aquatic environments (U.S. EPA, 2008c). Specifically, there appears to be a relationship 

between SO4

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 6-14). Therefore, the correlation between SO4

2-

deposition 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 between sulfur and 

mercury cannot be neglected (U.S. EPA, 2008c).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-66

Figure 6-14. Spatial and Biogeochemical Factors Influencing MeHg Production

As research evolves and the computational capacity of models expands to meet the 

complexity of mercury methylation processes 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 6-15 illustrates the type of current and forward-looking 

research being 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 6-15 is based on SO4

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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-67

Figure 6-15. 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 MeHg 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 SO4

2-

deposition have already shown promising reductions in MeHg. 

Observed decreases in MeHg fish tissue concentrations have been linked to decreased 

acidification and declining SO4

2-

and mercury deposition in Little Rock Lake, WI (Hrabik and 

Watras, 2002), and to decreased SO4

2-

deposition in Isle Royale in Lake Superior, MI (Drevnick 

et al., 2007). Although the possibility exists that reductions in SO4

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 SO4

2-

, 

increased mercury methylation downstream may still occur in sulfate-enriched ecosystems with 

increased organic matter and/or downstream transport capabilities.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-68

Remediation of sediments heavily contaminated with mercury has yielded significant 

reductions of MeHg in biotic tissues. Establishing quantitative relations 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 that 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 the reduction of both sulfur and mercury emissions may be most efficient because of 

the variability in ecosystem responses. Reducing SOX 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 

include 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 fish 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 some 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 provision 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.

6.6.3 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 

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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-69

methylmercury mediated primarily by sulfate-reducing bacteria. Methylation is enhanced in 

anaerobic and acidic environments, greatly increasing mercury toxicity and potential 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 capacity 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 variety 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 complexities 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 difficult to make at this time. In the sections that follow numerous 

effects have been identified at differing exposure levels.

6.6.3.1 Mercury Effects on Fish

A review of the literature on effects of mercury on fish (Crump and Trudeau, 2009) 

reports results for numerous species including trout, bass (large and smallmouth), northern 

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 changes 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 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-70

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.

6.6.3.2 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 the 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-sitting), 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 in 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 birds 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% 

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 United States. Ibis territory can range inland 

to Oklahoma, Arkansas and Tennessee. Egret range covers virtually the entire United States 

except the mountain west.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-71

Insectivorous birds have also been shown to suffer adverse effects due to mercury 

exposure. These 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).

6.6.3.3 Mercury Effects on 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 concentration 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 more 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).

6.6.3.4 Mercury Ecological Conclusions

The studies 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 

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.

6.6.4 Vegetation Co-benefits from Reductions in Ambient Ozone

Illustrative emission reduction strategies that include NOx 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 

and affect ecological systems, leading to changes in the ecological community 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 with the greatest potential 

for regional-scale forest impacts (U.S. EPA, 2006a). Studies have demonstrated repeatedly that 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-72

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 (CO2) and other gaseous substances, ozone 

enters plant tissues primarily through the stomata in leaves in a process 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 away 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, essential 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).

This ozone damage may or may not be accompanied by visible injury on leaves, 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 in 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 the variation in sensitivity between 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-73

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 

plants 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 (including 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 temporal 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 injuries 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 

potential ecosystem responses is available through long-term observations in highly damaged 

forests in the U.S. (U.S. EPA, 2006a).

6.6.4.1 Ozone Effects on Forests

Air pollution can affect the environment and affect ecological systems, leading to 

changes in the ecological community 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 commercial and ecologically 

important 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 

known 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-74

Monitoring of ozone injury to plants by the U.S. Forest Service has expanded over the 

last 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 6-16, and provides the county-level data regarding the presence or absence of ozonerelated injury. As shown in Figure 6-16, 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 equivalent from site to 

site. Ranges of biosite values translate to no injury, low or moderate foliar injury (visible foliar 

injury to highly sensitive 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 primarily found in the Mid-Atlantic and Southeast regions. While the assessment 

showed considerable regional variation in ozone injury, this assessment targeted different 

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 because 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

 

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).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-75

c

DegreecDegree 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 Injury to Forest Plants from Ozone in U.S. by EPA Regionsa,b,c
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-76

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 species (Chappelka and 

Samuelson, 1998). In areas where certain ozone-sensitive species dominate the forest 

community, the biomass loss from ozone can be significant. Experts have identified 2% annual 

biomass loss as a level of concern, which would cause long term ecological harm as the shortterm 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 sustain 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 services 

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 fallcolor tourism because the fall foliage would be less available or less attractive. Beyond the 

aesthetic damage to fall color vistas, forests provide the public with many other recreational 

and educational services that may be affected by reduced forest health including hiking, wildlife 
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-77

viewing (including bird watching), 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 tree 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., physical 

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 results 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 reductions 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 itself 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

 

46These 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.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-78

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 maintenance 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 

enjoyment 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 absence 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 standards 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-D3-0033, WA no. 6. pp. 9-10. 

Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/abt1995.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-79

Abt Associates, Inc. 2001. Assessing Public Opinions on Visibility Impairment due to Air 

Pollution: Summary Report. Prepared for EPA Office of Air Quality Planning and 

Standards; funded under EPA Contract No. 68-D-98-001. Abt Associates Inc., Bethesda, 

MD. January. Available on the Internet at 

<http://www.epa.gov/ttncaaa1/t1/reports/vis_rpt_final.pdf>.

Adams, Evan M., and Frederick, Peter C. 2008. “Effects of methylmercury and spatial complexity 

on foraging behavior and foraging efficiency in juvenile white ibises (Eudocimus albus).”

Environmental Toxicology and Chemistry. Vol 27, No. 8.

Adams, R. M., Glyer, J. D., Johnson, S. L., McCarl, B. A. 1989. “A reassessment of the economic 

effects of ozone on U.S. agriculture.” Journal of the Air Pollution Control Association, 39, 

960-968.

Adams, R. M., Hamilton, S. A., McCarl, B. A. 1986. “The benefits of pollution control: the case of 

ozone and U.S. agriculture.” American Journal of Agricultural Economics, 34, 3-19.

Anselin, L., Le Gallo, J. 2006. “Interpolation of air quality measures in hedonic house price 

models: Spatial aspects.” Spatial Economic Analysis 1: 31–52

Anselin, L., Lozano-Gracia, N. 2008. “Errors in variables and spatial effects in hedonic house 

price models of ambient air quality.” Empirical Economics 34: 5–34.

Arrow, K.J., et al. 1993. Report of the NOAA Panel on Contingent Valuation. Federal Register. 

Volume 58, Number 10. Pages 4601 to 4614. Available on the Internet at 

<http://www.darp.noaa.gov/library/pdf/cvblue.pdf>.

Arzavus K.M., Dickhut R.M., and Canuel E.A. 2001. “Fate of Atmospherically Deposited 

Polycyclic Aromatic Hydrocarbons (PAHs) in Chesapeake Bay.” Environmental Science & 

Technology, 35, 2178-2183.

Banzhaf, S., D. Burtraw, D. Evans, and A. Krupnick. 2006. “Valuation of Natural Resource 

Improvements in the Adirondacks.” Land Economics 82:445-464.

Bayer, P., Keohane, N.O. and Timmins, C. 2009. “Migration and hedonic valuation: the case of 

air quality,” Journal of Environmental Economics and Management, 58 (2009) 1–14.

BBC Research & Consulting. 2003. Phoenix Area Visibility Survey. Draft Report. Available on the 

Internet at <http://www.azdeq.gov/environ/air/download/vis_021903f.pdf>.

Bergeron, CM., Bodinof, CM., Unrine, JM., Hopkins, WA. 2010a. “Mercury accumulation along a 

contamination gradient and nondestructive indices of bioaccumulation in amphibians.”

Environmental Toxicology and Chemistry 29(4), 980-988.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-80

Bergeron, CM., Bodinof, CM., Unrine, JM., Hopkins, WA. 2010b. “Bioaccumulation and maternal 

transfer of mercury and selenium in amphibians.” Environmental Toxicology and 

Chemistry 29(4), 989-997.

Beron KJ, Murdoch J, Thayer M. 2001. “The benefits of visibility improvement: New evidence 

from Los Angeles metropolitan area.” J Real Estate Finance Econ 22(2–3):319–337.

Beron KJ, Hanson Y, Murdoch JC, Thayer MA. 2004. “Hedonic price functions and spatial 

dependence: implications for the demand for urban air quality.” In: Anselin L, Florax RJ, 

Rey SJ (eds) Advances in spatial econometrics: methodology, tools and applications. 

Springer-Verlag, Berlin, pp 267–281.

Bond, T.C., and Sun H.L. (2005) Can reducing BC emissions counteract global warming? 

Environmental Science & Technology 39 (16).

Brasso, Rebecka L., and Cristol, Daniel A. 2008. “Effects of mercury exposure in the reproductive 

success of tree swallows (Tachycineta bicolor).” Ecotoxicology. 17:133-141.

Brookshire, D.S., R.C. d’Arge, W.D. Schulze and M.A. Thayer. 1979. Methods Development for 

Assessing Tradeoffs in Environmental Management, Vol. II: Experiments in Valuing NonMarket Goods: A Case Study of Alternative Benefit Measures of Air Pollution Control in 

the South Coast Air Basin of Southern California. Prepared for the U.S. Environmental 

Protection Agency, Office of Research and Development. Available on the Internet at 

<http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0271B-1.pdf/$file/EE-0271B1.pdf>.

Brookshire, D.S., Thayer, M.A., Schulze, W.D. & D’Arge, R.C. 1982. “Valuing Public Goods: A 

Comparison of Survey and Hedonic Approaches.” The American Economic Review. 72(1): 

165-177.

Burgess, Neil M., and Meyer, Michael W. 2008. “Methylmercury exposure associated with 

reduced productivity in common loons.” Ecotoxicology. 17:83-91.

Burtraw, Dallas, Alan J. Krupnick, Erin Mansur, David Austin and Deirdre Farrell, 1998. "The 

Costs and Benefits of Reducing Air Pollutants Related to Acid Rain." Contemporary 

Economic Policy 16: 379-400.

California State Parks. 2003. Public Opinions and Attitudes on Outdoor Recreation in California 

2002. California State Parks, Sacramento, California. December 2003. Available on the 

Internet at <http://parks.ca.gov/pages/795/files/poa2002final.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-81

Carson, R.T., R.C. Mitchell, and P.A. Rudd. 1990. “Valuing Air Quality Improvements: Simulating 

a Hedonic Pricing Equation in the Context of a Contingent Valuation Scenario.” In 

Visibility and Fine Particles, Transactions of an AWMA/EPA International Specialty 

Conference, C.V. Mathai, ed. Air and Waste Management Association, Pittsburgh. 

Available on the Internet at 

<http://www.econ.ucsd.edu/~rcarson/papers/AirQuality.pdf>.

Chameides. W.L., Yu, H., Liu, S.C., Bergin, M., Zhou, X., Mearns, L., Wang, G., Kiang, C.S., Saylor,

R.D., Luo, C. Huang, Y., Steiner, A., and Giorgi, F. 1999. “Case study of the effects of 

atmospheric aerosols and regional haze on agriculture: an opportunity to enhance crop 

yields in China through emission controls?” PNAS, 96: 13626-13633.

Chappelka, A.H., Samuelson, L.J. 1998. “Ambient ozone effects on forest trees of the eastern 

United States: a review.” New Phytologist, 139, 91-108.

Chay KY, Greenstone M. 2005. “Does air quality matter? evidence form the housing market.” J 

Polit Econ 113(2):376–424.

Chestnut, L.G. 1997. Methodology for Estimating Values for Changes in Visibility in National 

Parks. Prepared for Office of Policy, Planning and Evaluation, May. Available on the 

Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/chestnut1997.pdf>.

Chestnut, L.G. and D.M. Mills. 2005. “A fresh look at the benefits and cost of the US acid rain 

program.” J Environ Manage 77:252–66. 

Chestnut, L.G. and R. Dennis. 1997. “Economic Benefits of Improvements in Visibility: Acid Rain 

Provisions of the 1990 Clean Air Act Amendments.” Journal of Air and Waste 

Management Association 47: 395-402.

Chestnut, L.G., and R.D. Rowe. 1990a. “New National Park Visibility Value Estimates.” In 

Visibility and Fine Particles, Transactions of an AWMA/EPA International Specialty 

Conference, C.V. Mathai, ed. Air and Waste Management Association, Pittsburgh.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-82

Chestnut, L.G. and R.D. Rowe. 1990b. Preservation Values for Visibility Protection at the 

National Parks. Prepared for U.S. Environmental Protection Agency, Office of Air Quality 

Planning and Standards, and National Park Service, Air Quality Management Division. 

Available on the Internet at 

<http://www.google.com/url?sa=t&source=web&cd=2&ved=0CBkQFjAB&url=http%3A

%2F%2Fyosemite.epa.gov%2Fee%2Fepa%2Feerm.nsf%2FvwAN%2FEE-0405-

01.pdf%2F%24file%2FEE-0405-

01.pdf&rct=j&q=%22Preservation%20Values%20for%20Visibility%20Protection%20at%2

0the%20National%20Parks%22&ei=IAH4TOOlFM3MswaHsozaCA&usg=AFQjCNFcUMZPo

2v9nNOwLVJneZkGSJSYpg&cad=rjaAvailable on the Internet at 

<http://yosemite.epa.gov/ee/epa/eerm.nsf/vwGA/EE97D10D71E3FAD08525662400766

534 >.

Chestnut, L.G. and R.D. Rowe. 1990c. “Economic Valuation of Changes in Visibility: A State of 

the Science Assessment for NAPAP.” Section B5 in Irving, Patricia M., e.d., 1991. Acid 

Deposition: State of Science and Technology, Volume IV, Control Technologies, Future 

Emissions, and Effects Valuation, The U.S. National Acid Precipitation Assessment 

Program, Report 27, page 27–153.

Chestnut, L.G., R.D. Rowe and J. Murdoch. 1986. Review of ‘Establishing and Valuing the Effects 

of Improved Visibility in Eastern United States.’ Prepared for the U.S. Environmental 

Protection Agency. October. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/chestnut1986.pdf>.

Cordell, H.K., C.J. Betz, G. Green, and M. Owens. 2005. Off-Highway Vehicle Recreation in the 

United States, Regions and States: A National Report from the National Survey on 

Recreation and the Environment (NSRE). Prepared for the U.S. Department of 

Agriculture Forest Service, Southern Research Station, National OHV Policy and 

Implementation Teams, Athens, GA. Available on the Internet at 

<http://www.fs.fed.us/recreation/programs/ohv/OHV_final_report.pdf>

Cordell, K., B. Leeworthy, G.T. Green, C. Betz, B. Stephens. 2008. The National Survey on 

Recreation & the Environment. Research Work Unit 4953. Pioneering Research on 

Changing Forest Values in the South and Nation, U.S. Department of Agriculture Forest 

Service, Southern Research Station, Athens, GA. Available on the Internet at 

<http://www.srs.fs.fed.us/trends>.

Cotrufo, M.F., De Santo A.V., Alfani A., Bartoli G., De Cristofaro A. 1995. “Effects of urban heavy 

metal pollution on organic matter decomposition in Quercus ilex L. Woods.”

Environmental Pollution, 89(1), 81-87.

Coulston, J.W., Riitters, K.H., Smith, G.C. 2004. “A preliminary assessment of the Montreal 

process indicators of air pollution for the United States.” Environmental Monitoring and 

Assessment, 95, 57-74.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-83

Cristol D. A., Brasso R. L., Condon A. M., Fovargue R. E., Friedman S. L., Hallinger K. K., Monroe 

A. P., White A. E. 2008. “The movement of aquatic mercury through terrestrial food 

webs.” Science 320, 335–335.

Cropper, Maureen. 2000. “Has Economic Research Answered the Needs of Environmental 

Policy?” Journal of Environmental Economics and Management 39, 328-350.

Crump, Kate L., and Trudeau, Vance L. 2009. “Mercury-induced reproductive impairment in 

fish.” Environmental Toxicology and Chemistry. Vol. 28, No. 5.

De Steiguer, J., Pye, J., Love, C. 1990. “Air Pollution Damage to U.S. Forests.” Journal of Forestry, 

88(8), 17-22.

DeBell, L. J.; Gebhart, K. A.; Hand, J. L.; Malm, W. C.; Pitchford, M. L.; Schichtel, B. A.; White, W. 

H. 2006. Spatial and Seasonal Patterns and Temporal Variability of Haze and its 

Constituents in the United States, Report IV; Cooperative Institute for Research in the 

Atmosphere, Nov; ISSN 0737-5352-74. Available on the Internet at 

<http://vista.cira.colostate.edu/improve/Publications/Reports/2006/2006.htm>.

DeHayes, D.H., P.G. Schaberg, G.J. Hawley, and G.R. Strimbeck. 1999. “Acid rain impacts on 

calcium nutrition and forest health.” Bioscience 49(10):789–800.

DeLucchi, M.A., J.J. Murphy, D.R. McCubbin. 2002. “The health and visibility cost of air 

pollution: A comparison of estimation methods,” Journal of Environmental 

Management, 64 (2), pp. 139–152.

Ely, D.W., Leary, J.T., Stewart, T.R., Ross, D.M. 1991. “The Establishment of the Denver Visibility 

Standard.” Presented at Air and Waste Management Association 84th Annual Meeting, 

June 16-21, Paper 91-48.4, 17pp. Available on the Internet at 

<http://www.albany.edu/cpr/stewart/Papers/T0210-ElyDenverVisStandard1991cap.pdf>.

Ericksen, J. A., Gustin, M. S., Schorran, D. E., Johnson, D. W., Lindberg, S. E., & Coleman, J. S. 

(2003). “Accumulation of atmospheric mercury in forest foliage.” Atmospheric 

Environment 37(12), 1613-1622.

Evers, D.C., 2006. Status assessment and conservation plan for the common loon (Gavia immer) 

in North America. U.S. Fish and Wildlife Service, Hadley, MA, USA.

Evers, David C., Savoy, Lucas J., DeSorbo, Christopher R., Yates, David E., Hanson, William, 

Taylor, Kate M., Siegel, Lori S., Cooley, John H. Jr., Bank, Michael S., Major, Andrew, 

Munney, Kenneth, Mower, Barry F., Vogel, Harry S., Schoch, Nina, Pokras, Mark, 

Goodale, Morgan W., Fair, Jeff. 2008. “Adverse effects from environmental mercury 

loads on breeding common loons.” Ecotoxicology. 17:69-81.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-84

Fox, S., Mickler, R. A. (Eds.). 1996. Impact of Air Pollutants on Southern Pine Forests, Ecological 

Studies. (Vol. 118, 513 pp.) New York: Springer-Verlag.

Frederick, Peter, and Jayasena, Nilmini. 2010. “Altered pairing behavior and reproductive 

success in white ibises exposed to environmentally relevant concentrations of 

methylmercury.” Proceedings of the Royal Society B. doi: 10-1098.

Gorissen, Leen, Snoeijs, Tinne, Van Duyse, Els, and Eens, Marcel. 2005. “Heavy metal pollution 

affects dawn singing behavior in a small passerine bird.” Oecologia. 145: 540-509.

Grantz DA; Garner JHB; Johnson DW. 2003. “Ecological effects of particulate matter.” Environ 

Int, 29: 213-239.

Graves, Phil, James C. Murdoch, Mark A. Thayer, and Don Waldman. 1988. “The Robustness of 

Hedonic Price Estimation: Urban Air Quality.” Land Economics, 64: 220-33. 

Grosclaude P. and N. Soguel. 1994. “Valuing damage to historic buildings using a contingent 

market: a case study of road traffic externalities,” Journal of Environmental Planning and 

Management 37 (1994) (3), pp. 279–287.

Grulke, N.E. 2003. “The physiological basis of ozone injury assessment attributes in Sierran

conifers.” In A. Bytnerowicz, M.J. Arbaugh, & R. Alonso (Eds.), Ozone air pollution in the 

Sierra Nevada: Distribution and effects on forests. (pp. 55-81). New York, NY: Elsevier 

Science, Ltd.

Hadley O.L., Corrigan C.E., Kirchstetter T.W., Cliff S.S., and Ramanathan V. (2010) Measured 

black carbon deposition on the Sierra Nevada snow pack and implication for snow pack 

retreat. Atmos. Chem. Phys. Discuss. 10, 10463‐10485 

(doi:10.5194/acpd‐10‐10463‐2010).

Hageman KJ; Simonich SL; Campbell DH; Wilson GR; Landers DH. 2006. “Atmospheric deposition 

of current-use and historic-use pesticides in snow at national parks in the western 

United States.” Environ Sci Technol, 40: 3174-3180

Hallinger, Kelly K., Cornell, Kerri L., Brasso, Rebecka L., and Cristol, Daniel A. 2010. “Mercury 

exposure and survival in free-living tree swallows (Tachycineta bicolor).” Ecotoxicology. 

Doi: 10.1007/s10646-010-0554-4.

Hawley, Dana M., Hallinger, Kelly K., Cristol, Daniel A. 2009. “Compromised immune 

competence in free-living tree swallows exposed to mercury.” Ecotoxicology. 18:499-

503.

Heck, W.W. &Cowling E.B. 1997. “The need for a long term cumulative secondary ozone 

standard—an ecological perspective.” Environmental Management, January, 23-33.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-85

Hoffman, David J., Henny, Charles J., Hill, Elwood F., Grover, Robert A., Kaiser, James L., 

Stebbins, Katherine R. 2009. “Mercury and drought along the lower Carson River, 

Nevada: III. Effects on blood and organ biochemistry and histopathology of snowy egrets 

and black-crowned night-herons on Lahontan Reservoir, 2002–2006.” Journal of 

Toxicology and Environmental Health, Part A. 72: 20, 1223-1241.

Hutchison, R., and C.E. Kraft. 1994. “Hmong Fishing Activity and Fish Consumption.” Journal of 

Great Lakes Research 20(2):471–487.

Intergovernmental Panel on Climate Change 4th Assessment Report: Climate Change 2007 

Synthesis Report Summary for Policy Makers Pachauri, R.K. and Reisinger, A. (Eds.). 

Available on the Internet at 

<http://ipcc.ch/publications_and_data/ar4/syr/en/spm.html>.

IMPROVE (Interagency Monitoring of Protected Visual Environments). 2010. 1992–2008 data 

from the IMPROVE network based on the “New IMPROVE algorithm” (updated 

November, 2008). Available on the Internet at 

<http://vista.cira.colostate.edu/improve/Data/IMPROVE/summary_data.htm.>

Irving, P.M., e.d. 1991. Acid Deposition: State of Science and Technology, Volume III, Terrestrial, 

Materials, Health, and Visibility Effects, The U.S. National Acid Precipitation Assessment 

Program, Chapter 24, page 24–76.

Joslin, J.D., Kelly, J.M., and van Miegroet, H. 1992. “Soil chemistry and nutrition of North 

American spruce-fir stands: evidence for recent change. “ Journal of Environmental 

Quality, 21, 12-30.

Kaval, P., and J. Loomis. 2003. Updated Outdoor Recreation Use Values With Emphasis On 

National Park Recreation. Final Report October 2003, under Cooperative Agreement CA 

1200-99-009, Project number IMDE-02-0070. Available on the Internet at 

<http://www.mngt.waikato.ac.nz/departments/staff/pkaval/Kaval%26LoomisNPSRepor

t10-03.pdf>.

Kim, CW, Phipps, T, and Anselin L. 2003. “Measuring the benefits of air quality improvement: a 

spatial hedonic approach.” J Environ Econ Manage 45:24–39.

Koch, D., Bond, T.C., Streets D., and Unger N. (2007) Linking future aerosol radiative forcing to 

shifts in source activities. Geophys. Res. Lett. 34 (L05821), AGU 

(doi:10.1029/2006GL028360, 2007). Available on the Internet at 

<http://dx.doi.org/10.1029/2006GL028360>.

Koch D., Bond T.C., Streets D., Unger N., and van der Werf G.R. (2007) Global impacts of 

aerosols from particular source regions and sectors. Journal of Geophysical 

Research‐Atmospheres 112 (D02205).
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-86

Kopp, R. J., Vaughn, W. J., Hazilla, M., Carson, R. 1985. “Implications of environmental policy for 

U.S. agriculture: the case of ambient ozone standards.” Journal of Environmental 

Management, 20, 321-331.

Kramer, A., T. Holmes, and M. Haefel. 2003. Contingent valuation of forest ecosystem 

protection. Pp. 303–320 in Forests in a Market Economy. Edited by E.O. Sills and K.L. Abt. 

Dordrecht, The Netherlands: Kluwer Academic Publishers.

Landers DH; Simonich SL; Jaffe DA; Geiser LH; Campbell DH; Schwindt AR; Schreck CB; Kent ML; 

Hafner WD; Taylor HE; Hageman KJ; Usenko S; Ackerman LK; Schrlau JE; Rose NL; Blett 

TF; Erway MM. (2008). The Fate, Transport and Ecological Impacts of Airborne 

Contaminants in Western National Parks (USA). EPA/600/R-07/138. U.S. Environmental 

Protection Agency, Office of Research and Development, NHEERL, Western Ecology 

Division. Corvallis, Oregon.

Leeworthy, V.R., and P.C. Wiley. 2001. Current Participation Patterns in Marine Recreation. 

Silver Spring, MD: U.S. Department of Commerce, National Oceanic and Atmospheric 

Administration, National Ocean Service, Special Projects. November. Available on the 

Internet at < http://www.naturetourismplanning.com/pdfs/NSRE_2.pdf>.

Leggett, C.G. and J.E. Neumann. 2004. Responding to SAB Council Comments on the May 2003 

Draft Analytical Plan for the Section 812 Second Prospective—Visibility Benefits.

Prepared for U.S. Environmental Protection Agency OPAR. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/leggettandneumann2004.

pdf>.

Leistritz, F. L., D. A. Bangsund, and N. M. Hodur. 2004. “Assessing the Economic Impact of 

Invasive Weeds: The Case of Leafy Spurge (Euphorbia esula).” Weed Technology

18:1392-1395.

Leitch, J. A, F. L Leistritz, and D. A Bangsund. 1996. “Economic effect of leafy spurge in the 

upper Great Plains: methods, models, and results.” Impact Assessment 14: 419–434.

Lipton, D. W. 1999. “Pfiesteria’s economic impact on seafood industry sales and recreational 

fishing, p. 35–38.” In B. L. Gardner and L. Koch (ed.), Proceedings of the Conference, 

Economics of Policy Options for Nutrient Management and Pfiesteria. Center for 

Agricultural and Natural Resource Policy, University of Maryland, College Park.

Loehman, E.T., D. Boldt, K. Chaikin. 1985. Measuring the Benefits of Air Quality Improvements

in the San Francisco Bay Area. From Methods Development for Environmental Control 

Benefits Assessment, Volume IV. Prepared for the U.S. Environmental Protection 

Agency, Office of Policy, Planning and Evaluation, September. Grant #R805059-01-0 

Available on the Internet at 

<http://yosemite.epa.gov/ee/epa/eerm.nsf/vwGA/e85705387833398f8525644d0053bd

d0!OpenDocument#_Section6>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-87

Loehman, E.T., S. Park, and D. Boldt. 1994. “Willingness to Pay for Gains and Losses in Visibility 

and Health.” Land Economics 70(4): 478-498.

Malm, WC. 1999. Introduction to visibility. Colorado State University, Fort Collins, CO, USA, 

1983, Revised edition, 1999. Available on the Internet at 

<vista.cira.colostate.edu/improve/Education/IntroToVisinstr.htm>.

McBride, J.R., Miller, P.R., Laven, R.D. 1985. “Effects of oxidant air pollutants on forest 

succession in the mixed conifer forest type of southern California.” In: Air Pollutants 

Effects on Forest Ecosystems, Symposium Proceedings, St. P, 1985, p. 157-167.

McClelland, G., W. Schulze, D. Waldman, J. Irwin, D. Schenk, T. Stewart, L. Deck and M. Thayer. 

1993. Valuing Eastern Visibility: A Field Test of the Contingent Valuation Method. 

Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and 

Evaluation. September. Available on the Internet at 

<http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0008-1.pdf/$file/EE-0008-1.pdf >.

McIntyre, J.W., Barr, J.F. 1997. “Common Loon (Gavia immer)” in: Pool A, Gill F (eds.) The Birds 

of North America. Academy of Natural Sciences, Philadelphia, PA, 313

McIntrye, J.W., and Evers, D.C.,(eds). 2000. “Loons: old history and new finding.” Proceedings of 

a Symposium from the 1997 meeting, American Ornithologists’ Union. North American 

Loon Fund, 15 August 1997, Holderness, NH, USA.

Millennium Ecosystem Assessment Board (MEA). 2005. Ecosystems and Human Well-being: 

Synthesis. Washington, DC: World Resources Institute. Available on the Internet at 

<http://www.who.int/globalchange/ecosystems/ecosystems05/en/index.html>.

Miller, P.R., O.C. Taylor, R.G. Wilhour. 1982. Oxidant air pollution effects on a western 

coniferous forest ecosystem. Corvallis, OR: U.S. Environmental Protection Agency, 

Environmental Research Laboratory (EPA600-D-82-276).

Mitro, Matthew G., Evers, David C., Meyer, Michael W., and Piper, Walter H. 2008. “Common 

loon survival rates and mercury in New England and Wisconsin.” Journal of Wildlife 

Management 72(3): 665-673.

Munthe, J., Bodaly, R. A., Branfireun, B. A., Driscoll, C. T., Gilmour, C. C., Harris, R., et al. (2007). 

“Recovery of Mercury-Contaminated Fisheries.” Environmental Science & Technology

36(1), 33-44.

Murdoch, J. C. and M. A. Thayer. 1988. “Hedonic price estimation of variable urban air quality,”

J. Environ. Econ. Management 15, 143-146. 

National Acid Precipitation Assessment Program (NAPAP). 1991. 1990 Integrated Assessment 

Report. NAPAP Office of the Director. Washington, DC. November.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-88

National Agricultural Statistics Service (NASS). 2008. Maple Syrup—June 12, 2008: Maple Syrup 

Production Up 30 Percent Nationwide. U.S. Department of Agriculture, National 

Agricultural Statistics Service, New England Agricultural Statistics, Concord, NH.

National Association of State Foresters (NASF). 2009. Quadrennial Fire Review 

2009.Washington, DC: NASF. Quadrennial Fire and Fuel Review Final Report 2009. 

National Wildfire Coordinating Group Executive Board. January.

National Oceanic and Atmospheric Administration (NOAA). 2007. Annual Commercial Landing 

Statistics. August. Available on the Internet at <http://www.st.nmfs.noaa.gov/ 

st1/commercial/landings/annual_landings.html>.

National Park Service (NPS). 1997. Statistical Abstract: 1997. Department of Interior, National 

Park Service Social Science Program, Public Use Statistics Office, Denver, Colorado. 

Available on the Internet at 

<http://www.nature.nps.gov/stats/abstracts/abst1997.pdf>.

National Park Service (NPS). 2008. Statistical Abstract: 2008. Department of Interior, National 

Park Service Social Science Program, Public Use Statistics Office, Denver, Colorado. 

Available on the Internet at 

<http://www.nature.nps.gov/stats/abstracts/abst2008.pdf>.

Neill, Helen R., David M. Hassenzahl and Djeto D. Assane. 2007. “Estimating the Effect of Air 

Quality: Spatial versus Traditional Hedonic Price Models,” Southern Economic Journal

73, No. 4, pp. 1088-1111.

Neumann, J.E. and R.W. Patterson. 2009. Alternative Approach to Estimating Monetized 

Benefits of Residential Visibility for the Section 812 Second Prospective. Prepared for U.S. 

Environmental Protection Agency OAR/OPAR. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/neumannpaterson2009.p

df>.

Niklinska M., Laskowski R., Maryanski M. (1998). “Effect of heavy metals and storage time on 

two types of forest litter: basal respiration rate and exchangeable metals”

Ecotoxicological Environmental Safety, 41, 8-18.

Office of Management and Budget (OMB). 2003. Circular A-4: Regulatory Analysis. Washington, 

DC. Available on the internet at <http://www.whitehouse.gov/omb/circulars/a004/a4.html>.

Painter, et al. 2007. “Impact of disturbed desert soils on duration of mountain snow cover.”

Geophys. Res. Lett. 34, L12502.

Parrish ZD; White JC; Isleyen M; Gent MPN; Iannucci-Berger W; Eitzer BD; Kelsey JW; Mattina 

MI. 2006. “Accumulation of weathered polycyclic aromatic hydrocarbons (PAHs) by 

plant and earthworm species.” Chemosphere, 64: 609-618.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-89

Patterson, R.W., J.E. Neumann, and C.G. Leggett. 2005. Recommended Residential Visibility 

Values for the Section 812 Second Prospective Analysis. Prepared for U.S. Environmental 

Protection Agency OPAR. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/Benefits/background/patersonneumanleggett2

005.pdf>.

Peterson, D.E., M.S. Kanarek, M.A. Kuykendall, J.M. Diedrich, H.A. Anderson, P.L. Remington, 

and T.B. Sheffy. 1994. “Fish Consumption Patterns and Blood Mercury Levels in 

Wisconsin Chippewa Indians.” Archives of Environmental Health 49(1):53–58.

Pitchford, M and W. Malm. 1994. “Development and Application of a Standard Visual Index.”

Atmospheric Environment 28(5): 1049-1054.

Prasad, A.M. and Iverson, L.R. 2003. “Little’s range and FIA importance value database for 135 

eastern U.S. tree species.” Northeastern Research Station, USDA Forest Service.

Available on the Internet at 

<http://www.fs.fed.us/ne/delaware/4153/global/littlefia/index.html>.

Pryor, S.C. 1996. “Assessing Public Perception of Visibility for Standard Setting Exercises.”

Atmospheric Environment 30, no. 15, pp. 2705-2716.

Pye, J.M. 1988. “Impact of ozone on the growth and yield of trees: A review.” Journal of 

Environmental Quality, 17, 347-360.

Qian Y., Gustafson W.I., Leung L.R., and Ghan S.J. 2009. “Effects of soot-induced snow albedo 

change on snowpack and hydrological cycle in western United States based on Weather 

Research Forecasting Chemistry and Regional Climate Simulations.” Journal of 

Geophysical Research 114 (DO2108).

Rae, D.A. 1983. Benefits of Visual Air Quality in Cincinnati Results of a Contingent Ranking 

Survey. Prepared for Electric Power Research Institute. May.

Rea, A. W., Lindberg, S. E., Scherbatskoy, T., & Keeler, G. J. 2002. “Mercury Accumulation in 

Foliage over Time in Two Northern Mixed-Hardwood Forests.” Water, Air, & Soil

Pollution 133(1), 49-67.

Rimmer, C. C., McFarland, K. P., Evers, D. C., Miller, E. K., Aubry, Y., Busby, D., et al. 2005. 

“Mercury Concentrations in Bicknell’s Thrush and Other Insectivorous Passerines in 

Montane Forests of Northeastern North America.” Ecotoxicology 14(1), 223-240.

Rosen, S. 1974. “Hedonic prices and implicit markets: product differentiation in pure 

competition.” Journal of Political Economy 82(1): 34-55.

Scheuhammer, Anton M., Meyer Michael W., Sandheinrich, Mark B., and Murray, Michael W. 

2007. “Effects of environmental methylmercury on the health of wild birds, mammals, 

and fish,” Ambio Vol.36, No.1.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-90

Sepulveda, Maria S., Frederick, Peter C., Spalding, Marilyn G., and Williams, Gary E. Jr. 1999. 

“Mercury contamination in free-ranging great egret nestlings (Ardea albus) from 

southern Florida, USA,” Environmental Toxicology and Chemistry Vol. 18, No.5.

Simcik M.F., Eisenreich S.J., Lioy P.J. 1999. “Source apportionment and source/sink relationship 

of PAHs in the coastal atmosphere of Chicago and Lake Michigan.” Atmospheric 

Environment, 33, 5071-5079.

Simcik M.F., Eisenreich, S.J., Golden K.A., et al. 1996. “Atmospheric Loading of Polycyclic 

Aromatic Hydrocarbons to Lake Michigan as Recorded in the Sediments.” Environmental 

Science and Technology, 30, 3039-3046.

Sisler, J.F. 1996. Spatial and seasonal patterns and long-term variability of the composition of 

the haze in the United States: an analysis of data from the IMPROVE network. CIRA 

Report, ISSN 0737-5352-32, Colorado State University.

Smith, G., Coulston, J., Jepsen, E., Prichard, T. 2003. “A national ozone biomonitoring program—

results from field surveys of ozone sensitive plants in Northeastern forests (1994–

2000).” Environmental Monitoring and Assessment, 87, 271-291.

Smith, A.E.; Kemp, M.A.; Savage, T.H.; Taylor, C.L. 2005. “Methods and Results from a New 

Survey of Values for Eastern Regional Haze Improvements,” J. Air & Waste Manage 

Assoc 55, 1767-1779.

Smith, V.K., G. Van Houtven, and S.K. Pattanayak. 2002. “Benefit Transfer via Preference 

Calibration.” Land Economics 78:132-152.

Smith, V.K., and J.C. Huang. 1995. “Can markets value air quality? A meta-analysis of hedonic 

property value models,” J. Polit. Econ, 103, pp. 209–227.

Southern Appalachian Mountains Initiative (SAMI). 2002. Southern Appalachian Mountains 

Initiative: Final Report. Asheville, NC. 172pp. Available on the Internet at 

<http://www.nature.nps.gov/air/pubs/pdf/SAMI_Final_Report_0802.pdf>.

Spencer, D.M., and D.F. Holecek. 2007. “Basic characteristics of the fall tourism market.”

Tourism Management 28:491–504.

Taylor R. 1994. “Deterministic versus stochastic evaluation of the aggregate economic effects of 

price support programs.” Agricultural Systems 44: 461-473.

Tingey, D.T., and Taylor, G.E. 1982. “Variation in plant response to ozone: a conceptual model 

of physiological events.” In M.H. Unsworth & D.P. Omrod (Eds.), Effects of Gaseous Air 

Pollution in Agriculture and Horticulture. (pp.113-138). London, UK: Butterworth 

Scientific.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-91

Tolley, G., A. Randall, G. Blomquist, M. Brien, R. Fabian, G. Fishelson, A. Frankel, M. Grenchik, J. 

Hoehn, A. Kelly, R. Krumm, E. Mensah, and T. Smith. 19846. Establishing and Valuing the 

Effects of Improved Visibility in Eastern United States. Prepared for U.S. Environmental 

Protection Agency, Office of Policy, Planning and Evaluation. March. U.S. Environmental 

Protection Agency Grant #807768-01-0. Available on the Internet at 

<http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0003-01.pdf/$file/EE-0003-

01.pdfvwGA/e673ccafbda23639852565f00007412f!OpenDocument&ExpandSection=3>.

Tolley, George and Robert Fabian (eds). 1988. The Economic Value of Visibility. Series : Studies 

in urban and resource economics. Mount Pleasant, MO: Blackstone.

Trijonis, J.C. et al. 1987. “Preliminary extinction budget results from the RESOLVE program,” pp. 

872-883. In: P.J. Bhardwaja, et al. Visibility Protection Research and Policy Aspects. Air 

Pollution Control Assoc., Pittsburgh, PA.

Trijonis, J.C. et al. 1988. RESOLVE Project Final Report: Visibility conditions and Causes of 

Visibility Degradation in the Mojave Desert of California. NWC TP #6869. Naval Weapons 

Center, China Lake, CA. Available on the Internet at 

<www.dtic.mil/dtic/tr/fulltext/u2/a206322.pdf>.

United Nations Environmental Programme, World Meteorological Organization and Stockholm 

Environment Institute (UNEP). 2011. Integrated Assessment of Black Carbon and 

Tropospheric Ozone Summary for Decision Makers. Available on the Internet at 

<http://www.unep.org/dewa/Portals/67/pdf/Black_Carbon.pdf>.

U.S. Census Bureau. 2010. “Sector 56: EC075612: Administrative Support and Waste 

Management and Remediation Services: Industry Series: Preliminary Comparative 

Statistics for the United States (2002 NAICS Basis): 2007 and 2002.” American FactFinder 

Available on the Internet at http://factfinder.census.gov (accessed August 25, 2010)

U.S. Department of the Interior (DOI). 2007. 2006 National Survey of Fishing, Hunting, and 

Wildlife-Associated Recreation. U.S. Department of the Interior, Fish and Wildlife 

Service, and U.S. Department of Commerce, U.S. Census Bureau. Washington, DC. 

Available on the Internet at <http://www.census.gov/prod/2008pubs/fhw06-nat.pdf>.

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 1999a. The 

Clean Air Act Amendments (CAAA) Section 812 Prospective Study of Costs and Benefits 

(1999): Advisory by the Advisory Council on Clean Air Compliance Analysis: Costs and 

Benefits of the CAAA. EPA-SAB-COUNCIL-ADV-00-002. October. Available on the Internet 

at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/E992F918DF32131A852571B9004571F7/

$File/coua0002.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-92

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 1999b. Final 

Advisory by the Advisory Council on Clean Air Compliance Analysis on the 1999 

Prospective Study of Costs and Benefits (1999) of Implementation of the Clean Air Act 

Amendments (CAAA). EPA-SAB-COUNCIL-ADV-00-003. November. Available on the 

Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/93BE842F5CBA7BEF852571B900461197/

$File/coua0003.pdf>.

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2004. Review of 

the Draft Analytical Plan for EPA’s Second Prospective Analysis—Benefits and Costs of 

the Clean Air Act, 1990-2020: An Advisory by the Advisory Council for Clean Air 

Compliance Analysis. EPA-SAB-COUNCIL-ADV-04-004. May. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/7CCBBFE15.BD4C8B185256F17005E3079

/$File/council_adv_04004.pdf>.

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2007. Clean Air 

Scientific Advisory Committee’s (CASAC) Review of the Agency’s Final Ozone Staff Paper.

EPA-CASAC-07-002. Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/FE915E916333D776852572AC007397B5/

$File/casac-07-002.pdf>.

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2010a. Advisory 

on a Preliminary Draft of the Second Section 812 Prospective Study of the Benefits and 

Costs of the Clean Air Act (April 2010). EPA-COUNCIL-10-004. July. Available on the 

Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/553D59A280CDCF388525776D005EE83A

/$File/EPA-COUNCIL-10-004-unsigned.pdf>.

U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2010b. Review 

of the Final Integrated Report for the Second Section 812 Prospective Study of the 

Benefits and Costs of the Clean Air Act (August 2010). EPA-COUNCIL-11-001. December. 

Available on the Internet at 

<http://yosemite.epa.gov/sab%5CSABPRODUCT.NSF/1E6218DE3BFF682E852577FB005

D46F1/$File/EPA-COUNCIL-11-001-unsigned.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 1997. Mercury Study Report to Congress. 

Volume V: Health Effects of Mercury and Mercury Compounds. EPA-452/R-97-007. U.S. 

EPA Office of Air Quality Planning and Standards, and Office of Research and 

Development. Available on the Internet at 

<http://www.epa.gov/ttncaaa1/t3/reports/volume5.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-93

U.S. Environmental Protection Agency (U.S. EPA). 1998. Advisory Council on Clean Air 

Compliance Analysis Advisory on the Clean Air Act Amendments (CAAA) of 1990 Section 

812 Prospective Study: Overview of Air Quality and Emissions Estimates: Modeling, 

Health and Ecological Valuation Issues Initial Studies. EPA-SAB-COUNCIL-ADV-98-003.

Available on the Internet at 

<http://yosemite.epa.gov/sab/sabproduct.nsf/D20F5AE06F98883F852571AF00474927/

$File/coad9803.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 1999a. Regional Haze Regulations, July 1, 

1999. (64 FR 35714, July 1, 1999).

U.S. Environmental Protection Agency (U.S. EPA). 1999b. The Benefits and Costs of the Clean Air 

Act, 1990–2010. Prepared for U.S. Congress by U.S. EPA, Office of Air and Radiation, 

Office of Policy Analysis and Review, Washington, DC, November; EPA report no.

EPA410-R-99-001. Available on the Internet at <http://www.epa.gov/oar/sect812/1990-

2010/chap1130.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2004. Air Quality Criteria for Particulate 

Matter Volume II of II. National Center for Environmental Assessment, Office of 

Research and Development, U.S. Environmental Protection Agency, Research Triangle 

Park, NC EPA/600/P-99/002bF. Available on the Internet at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=87903>.

U.S. Environmental Protection Agency (U.S. EPA). 2005. Regulatory Impact Analysis of the Final 

Clean Air Mercury Rule. Office of Air Quality Planning and Standards, Research Triangle 

Park, NC., March; EPA report no. EPA-452/R-05-003. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/mercury_ria_final.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2006.B2006b. Regulatory Impact Analysis, 

2006 National Ambient Air Quality Standards for Particulate Matter. Office of Air Quality 

Planning and Standards, Research Triangle Park, NC. October. Available on the Internet 

at < http://www.epa.gov/ttn/ecas/regdata/RIAs/Appendix%20I--

Visibility%20Benefits%20Methodology.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2006c. Ecological Benefits Assessment 

Strategic Plan. EPA-240-R-06-001. Office of the Administrator. Washington, DC. October.

Available on the Internet at 

<http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/EcologBenefitsPlan.html>.

U.S. Environmental Protection Agency (U.S. EPA). 2007a. Guidance on the Use of Models and 

Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and 

Regional Haze. Office of Air Quality Planning and Standards. EPA-454/B-07-002. April.

<Available on the Internet at http://www.epa.gov/scram001/guidance/guide/final-03-

pm-rh-guidance.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-94

U.S. Environmental Protection Agency (U.S. EPA). 2007b. Review of the National Ambient Air 

Quality Standards for Ozone: Policy assessment of scientific and technical information.

Staff Paper. Office of Air Quality Planning and Standards. EPA-452/R-07-007a. July.

Available on the Internet at 

<http://www.epa.gov/ttn/naaqs/standards/ozone/data/2007_07_ozone_staff_paper.p

df>.

U.S. Environmental Protection Agency (U.S. EPA). 2007c. Technical Report on Ozone Exposure, 

Risk, and Impact Assessments for Vegetation. Office of Air Quality Planning and 

Standards. EPA-452/R-07-002. January. Available on the Internet at 

http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_pr.html

U.S. Environmental Protection Agency (U.S. EPA). 2008a. Regulatory Impact Analysis, 2008 

National Ambient Air Quality Standards for Ground-level Ozone, Chapter 6. Office of Air 

Quality Planning and Standards, Research Triangle Park, NC. March. Available at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2008b. U.S. EPA’s 2008 Report on the 

Environment (Final Report). Washington, D.C., EPA/600/R-07/045F (NTIS PB2008-

112484). May. Available on the Internet at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=190806>. Updated in 

December 2010, available on the Internet at 

<http://cfpub.epa.gov/eroe/index.cfm?fuseaction=detail.viewInd&showQues=Air&ch=4

7&lShowInd=0,287&subtop=341&lv=list.listByQues&r=188207>.

U.S. Environmental Protection Agency (U.S. EPA). 2008c. Integrated Science Assessment for 

Oxides of Nitrogen and Sulfur—Ecological Criteria National (Final Report). National 

Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-08/139.

December. Available on the Internet at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485>.

U.S. Environmental Protection Agency (U.S. EPA). 2009a. The NOx Budget Trading Program: 

2008 Environmental Results. Clean Air Markets Division. September. Available on the 

Internet at <http://www.epa.gov/airmarkt/progress/NBP_3/

NBP_2008_Environmental_Results.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2009b. Integrated Science Assessment for 

Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for 

Environmental Assessment—RTP Division. December. Available on the Internet at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-95

U.S. Environmental Protection Agency (U.S. EPA). 2009c. Risk and Exposure Assessment for 

Review of the Secondary National Ambient Air Quality Standards for Oxides of Nitrogen 

and Oxides of Sulfur (Final Report). EPA-452/R-09-008a. Office of Air Quality Planning 

and Standards, Research Triangle Park, NC. September. Available on the Internet at 

<http://www.epa.gov/ttn/naaqs/standards/no2so2sec/data/NOxSOxREASep2009MainC

ontent.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2009d. Endangerment and Cause or 

Contribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act. 

December 15, 2009. (74 Fed. Reg. 66,496, December 15, 2009).

U.S. Environmental Protection Agency (U.S. EPA). 2010a. Updated Regulatory Impact Analysis 

(RIA) for the Reconsideration of the 2008 Ozone National Ambient Air Quality Standard 

(NAAQS). Office of Air Quality Planning and Standards, Research Triangle Park, NC. 

January. Available on the Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/s1-

supplemental_analysis_full.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2010b. Particulate Matter Urban-Focused 

Visibility Assessment—Final Document (Corrected). Office of Air Quality Planning and 

Standards, Research Triangle Park, NC. July. Available on the Internet at <Particulate

Matter Urban-Focused Visibility Assessment—Final Document>.

U.S. Environmental Protection Agency (U.S. EPA). 2011a. Policy Assessment for the Review of 

the PM NAAQS—Final Document. Office of Air Quality Planning and Standards, Research 

Triangle Park, NC. April. Available on the Internet at 

<http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pa.html>.

U.S. Environmental Protection Agency (U.S. EPA). 2011b. The Benefits and Costs of the Clean Air 

Act 1990 to 2020: EPA Report to Congress. Office of Air and Radiation, Washington, DC.

March. Available on the Internet at 

<http://www.epa.gov/air/sect812/feb11/fullreport.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2011c. Regulatory Impact Analysis for the 

Federal Implementation Plans to Reduce Interstate Transport of Fine Particulate Matter 

and Ozone in 27 States; Correction of SIP Approvals for 22 States. June. Available on the 

Internet at: <http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf>

U.S. Environmental Protection Agency (U.S. EPA). 2011d. Regulatory Impact Analysis for the 

Final Mercury and Air Toxics Standards. EPA-452/R-11-011. December. Available on the 

Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf>.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-96

U.S. Environmental Protection Agency (U.S. EPA). 2012a. Integrated Science Assessment for 

Particulate Ozone and Related Photochemical Oxidants (Final Report).Third External 

Review Draft). EPA-/600-/R-08-139F10/076C. National Center for Environmental 

Assessment—RTP Division. December ?.June. Available on the Internet at 

<http://cfpub.epa.gov/ncea/isa/recordisplay.cfm?deid=242490>.

U.S. Environmental Protection Agency (U.S. EPA). 2012b. Black Carbon Report to Congress. EPA450/R-12-001. March. Available on the Internet at 

<http://www.epa.gov/blackcarbon/2012report/fullreport.pdf>.

U.S. Fish and Wildlife Service and U.S. Census Bureau (FWS and Census). 2007. 2006 National 

Survey of Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR). FHW/06-NAT. 

U.S. Department of the Interior, U.S. Fish and Wildlife Service, Washington, DC, and U.S. 

Department of Commerce, U.S. Census Bureau, Washington, DC.

U.S. Forest Service (USFS). 2006. Forest Inventory and Analysis National Program: Forest 

Inventory Data Online. Online database. U.S. Department of Agriculture Forest Service, 

Forest Inventory and Analysis, Arlington, VA. Available on the Internet at 

<http://fia.fs.fed.us/tools-data>.

Valigura, R.A., R.B. Alexander, M.S. Castro, T.P. Meyers, H.W. Paerl, P.E. Stacy, and R.E. Turner. 

2001. Nitrogen Loading in Coastal Water Bodies: An Atmospheric Perspective. 

Washington, DC: American Geophysical Union.

Van Sickle, J., Baker, J.P., Simonin, H.A., Baldigo, B.P., Kretser, W.A., Sharpe, W.E. 1996.

“Episodic acidification of small streams in the northeastern United States: Fish mortality 

in field bioassays.” Ecological Applications, 6, 408-421.

Wada, H. and Cristol, D.A. and McNabb, F.M.A. and Hopkins, W.A. 2009. “Suppressed 

adrenocortical responses and thyroid hormone levels in birds near a mercurycontaminated river.” Environmental Science & Technology 43(15), 6031-6038.

Wada, H., Yates, DE., Evers, DC., Taylor, RJ., Hopkins, WA. 2010. “Tissue mercury concentrations 

and adrenocortical responses of female big brown bats (Eptesicus fuscus) near a 

contaminated river.” Ecotoxicology 19(7), 1277-1284.

Winner, W.E. 1994. “Mechanistic analysis of plant responses to air pollution.” Ecological 

Applications, 4(4), 651-661.

Winner, W.E., and C.J. Atkinson. 1986. “Absorption of air pollution by plants, and consequences 

for growth.” Trends in Ecology and Evolution 1:15-18.

Wiscombe W. and Warren S. 1980. “A model for the spectral albedo of snow. Snow containing 

atmospheric aerosols.” J. Atmos. Sci. 37, 2734-2274.
*** E.O. 12866 Review - Draft - Do Not Cite, Quote, or Release During Review ***

6-97

Yates, David E., Mayack, David T., Munney, Kenneth, Evers David C., Major, Andrew, Kaur, 

Taranjit, and Taylor, Robert J. 2005. “Mercury levels in mink (Mustela vison) and river 

otter (Lonra canadensis) from northeastern North America,” Ecotoxicology 14, 263-274.