Trends in Excess Morbidity and Mortality …Trends in Excess Morbidity and Mortality Associated with Air Pollution above ATS-Recommended Standards, 2008 to 2017 Kevin R. Cromar1,2,

Trends in Excess Morbidity and Mortality Associated with Air Pollution above ATS-Recommended Standards, 2008 to 2017Kevin R. Cromar1,2, Laura A. Gladson1, Gary Ewart3

1Marron Institute of Urban Management, New York University, New York, NY2New York University School of Medicine, New York, NY3American Thoracic Society, Washington, DC

Corresponding Author: Kevin Cromar, PhD60 5th Avenue, 2nd Floor, New York, NY 10011Email: [email protected]

Author Contributions: Kevin Cromar oversaw and contributed significantly to all stages of the study. Laura Gladson was involved in data acquisition, analysis, and interpretation, and in drafting and revising the manuscript. Gary Ewart contributed to the study’s conceptual design and manuscript revisions.

Sources of Support: Financial support provided by the Marron Institute of Urban Management at New York University and the American Thoracic Society.

Running Head: Trends in Health Impacts from Air Pollution in the U.S.

Subject Category: “6.1 Air Pollution: Epidemiology”

Keywords: Ozone, Particulate Matter, Risk Assessment, Environmental Policy

Word Count: 3,914

This article has a data supplement, which is accessible from this issue's table of contents online at www.atsjournals.org.

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Abstract

Rationale: Air quality improvements are increasingly difficult to come by as modern pollution

control technologies and measures have been widely implemented in the United States. While

there has been dramatic improvements in air quality over the last several decades, it is

important to evaluate the changes in health impacts of air pollution for a more recent time

period in order to better understand the current trajectory of air quality improvements.

Objectives): To provide county-level estimates of annual air pollution-related health outcomes

across the U.S. and to evaluate these trends from 2008-2017, presented as part of the annual

ATS/Marron Institute “Health of the Air” report.

Methods: Daily air pollution values were obtained from the EPA Air Quality System for monitors

in the U.S. from 2008-2017. Concentration-response functions used in the ATS/Marron Institute

"Health of the Air" report were applied to the pollution increments corresponding to

differences between the rolling three-year design values (reported as the third year) and ATS-

recommended levels for annual PM2.5 (11 µg/m3), short-term PM2.5 (25 µg/m3), and O3 (60

ppb). Health impacts were estimated at the county level in locations with valid monitor data.

Results: Annual excess mortality in the United States, from air pollution levels greater than

recommended by the ATS, decreased from approximately 12,600 (95% CI: 5,470 - 21,040) in

2010 to 7,140 (95% CI: 2,290 - 14,040) in 2017. This improvement can be attributed almost

entirely to reductions in PM2.5-related mortality which decreased approximately 60% (reduced

from 8,330 to 3,260 annual deaths) while O3-related mortality remained largely unchanged,

other than year-to-year variability, over the same time period (from 4,270 to 3,880 annual

deaths).

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Conclusions: Improvements in health impacts attributable to ambient PM2.5 concentrations

have been observed across most regions of the United States over the last decade, although the

rate of these improvements has leveled off in recent years. Despite two revisions of the

National Ambient Air Quality Standards strengthening the standard for O3 in 2008 and 2015,

there has not yet been a substantial improvement in the health impacts attributable to O3

during this time period. In many U.S. cities, an increase in the exposed population over the last

decade has outpaced the improvements in ambient O3 concentrations resulting in a net

increase in O3-related health impacts over time.

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Government and scientific institutions commonly state that air quality has improved

dramatically in the U.S. since the passage of the Clean Air Act (1970) and its subsequent

amendments. The U.S. Environmental Protection Agency (EPA) reports that between 1970 and

1990, Clean Air Act implementations prevented approximately 184,000 particulate matter

(PM)-associated deaths, over ten million cases of PM- and ozone (O3)-associated respiratory

and cardiovascular disease, and over 200 million lost school or work days (1). Following 1990

revisions to the Clean Air Act, the EPA found that by 2010 another nearly 165,000 mortalities

were prevented from reductions in fine particles (PM2.5) and O3 concentrations across the U.S.

as well as millions of additional morbidities and impacted days (2). Published studies in the

scientific literature have also concluded that reduced concentrations of PM2.5 and O3 in the U.S.

since the passage of federal air quality standards have resulted in the prevention of associated

mortalities and morbidities as well as significant improvements in life expectancy over the last

several decades (3-5).

However, there has been much less evaluation of changes in ambient air pollution and

its associated health impacts that have occurred more recently, in particular over the last ten

years (6, 7). Many of the policy actions and regulations that have resulted in dramatic

reductions in ambient pollution concentrations since the 1970 passage of the Clean Air Act and

the 1990 revisions to the Act have already been fully implemented, making additional

improvements in air quality increasingly difficult to come by (8, 9). Additionally, O3, produced

from reactions of precursor pollutants in the presence of sunlight, is predicted to increase in

the U.S. due to rising global temperatures (10). While it is not inevitable that there will be a

slowdown in further improvement in ambient air quality, it is important to evaluate the

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changes in health impacts of air pollution for a more recent time period in order to better

understand the current trajectory of air quality improvements in the U.S.

The annual "Health of the Air" report is well positioned to evaluate the trends in air

pollution and health in recent years by providing county-level estimates of annual air pollution-

related health outcomes that have occurred from 2008-2017. The systematic approach that has

been developed in the "Health of the Air" report allows for an in-depth understanding of local

air quality impacts, allowing local policymakers and pollution managers to track progress over

time. This information can serve as a valuable resource to the public, as well as decision makers

at the federal and local level, in crafting policies and implementation strategies to best address

the public health impacts of ambient air pollution concentrations greater than levels

recommended by the American Thoracic Society (ATS).

Methods

Methods described in the most recent "Health of the Air" report were applied in this study to

calculate health estimates from air pollution levels above ATS recommendations (11, 12). The

approach mimics the one utilized by the U.S. EPA in its regulatory review processes to estimate

health impacts from PM2.5 and O3 in monitored counties across the nation. In addition to

predicting health impacts from air pollution exceeding ATS recommendations for the most

recently available data (design values for 2015-2017), this year’s report incorporates an analysis

examining air pollution trends from the past ten years. These methods are summarized below.

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Daily O3 and PM2.5 measurements were obtained from the EPA Air Quality System for

design value monitors for each year from 2008-2017. These values were used to create annual

baseline and control datasets using a 24-hour metric for PM2.5 and three separate metrics (1-

hour maximum, 8-hour maximum, and 24-hour mean) for O3. Baseline values were equivalent

to the rolling 3-year design values for each monitor. These design values correspond to the 3-

year average of the annual mean concentration for PM2.5; the 3-year average of the 24-hour

98th percentile value for PM2.5; and the 3-year average of the fourth highest daily 8-hour

maximum O3 concentration. Control values were based on ATS recommendations of 11 µg/m3

for annual PM2.5, 25 µg/m3 for 24-hour PM2.5, and 60 ppb for O3 (13, 14). These cutoffs are

lower than the existing National Ambient Air Quality Standards (NAAQS) of 12 µg/m3 for annual

PM2.5, 35 µg/m3 for 24-hour PM2.5, and 70 ppb for O3. The ATS-recommended levels used in this

analysis are in accordance with previous ATS publications, which find that existing NAAQS are

insufficient in protecting human health and emphasize the need for more health-protective

regulations (15, 16).

For each year from 2010-2017, baseline concentrations (corresponding to 3-year county

design values) and control concentrations (corresponding to ATS recommendations) were

paired by county and run through BenMAP-CE (version 1.4.14.1). Given that design values are

three-year rolling estimates, the reported year corresponds to the third year in each grouping

(i.e., pollution levels from 2008-2010 are reported in the results as 2010). Figures E1-E3 in the

supplement show design value trends for each pollutant over the last three “Health of the Air”

report years (2011-2013, 2013-2015, and 2015-2017). Concentration-response relationships

from epidemiological studies, based on EPA standard health functions, were used to calculate

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the health impacts of pollution levels above ATS recommendations for each county (see Table

E1 in the data supplement for a full list of studies used). These health impacts include mortality;

major morbidity (acute myocardial infarction, chronic bronchitis, cardiovascular and respiratory

hospital admissions, and asthma-related emergency department visits); and adversely impacted

days (restricted activity days, work loss days, and school loss days). Additionally, excess lung

cancer incidence from PM2.5 exceeding ATS recommendations was estimated outside of

BenMAP-CE using a pooled risk value derived from a separate meta-analysis (see Table E2 in the

data supplement) and based on 2011-2015 statistics available from the National Cancer

Institute (17).

All health estimates were aggregated to the county, city, state, and national levels and

compared across years in R software (version 3.5.1). Health estimates, searchable by city or zip

code, are available to the public using this report’s accompanying online tool

(HealthoftheAir.org).

Results

Table 1 summarizes the 2017 estimated national health impacts from PM2.5 and O3 in excess of

ATS-recommended levels. The combined health impacts of these pollutants in 2017 is

estimated to have resulted in approximately 7,140 excess mortalities (95% CI: 2,290 – 14,040),

15,680 major morbidities (95% CI: -19,940 – 55,070), and 14,404,000 adversely impacted days

(95% CI: 5,119,000 – 26,768,000). An additional 640 (95% CI: 330-950) excess cases of lung

cancer incidence were also attributed to PM2.5 in 2017.

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The air pollution-related mortality impacts in the U.S. in 2017 for PM2.5 was estimated at

3,260 excess deaths (95% CI: 2,210 – 4,310), which is similar in magnitude to the estimated

3,880 excess deaths (95% CI: 83 – 14,040) attributable to O3. The geographic distribution of

these estimated health impacts was more evenly spread across the United States for O3 as

compared to PM2.5. Of the 530 counties with valid PM2.5 design values, only 78 (15%) did not

meet ATS-recommended concentrations; in contrast, 599 (83%) of the 726 counties with valid

O3 design values did not meet ATS recommendations.

It is important to note that while there are over 3,000 counties in the U.S., estimates of

health impacts were only made in those areas with valid design values. Unmonitored counties

are typically more rural and have lower population densities than monitored counties. While

lower population counties are required to have air quality monitors if their design values

measure at least 85% of NAAQS, there are undoubtedly some counties exceeding

recommended levels that remain unmonitored (18). As a result, additional health impacts that

would otherwise be included are not estimated in this report due to the lack of air quality

monitors in all counties that exceed ATS-recommended levels.

While the national mortality estimates were generally comparable in magnitude

between the two pollutants in 2017, PM2.5 estimates were about two-thirds of O3 for morbidity

and one-fourth of O3 for impacted days. Major morbidity estimates were 5,600 (95% CI: 1,800 –

9,270) for PM2.5 and 10,080 (95% CI: -21,740 – 45,800) for O3; impacted days were 2,804,000

(95% CI: 2,303,000 – 3,302,000) for PM2.5 and 11,600,000 (95% CI: 2,816,000 – 23,467,000) for

O3.

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Tables 2 and 3 show the top 25 cities (more specifically, metropolitan statistical areas

and metropolitan districts) with the most to gain from meeting ATS-recommended air pollution

standards for PM2.5 and O3. The rankings for these cities are most heavily based on mortality

estimates, followed by lung cancer incidence, major morbidities, and finally impacted days

(weightings for each category are described in Tables 2 and 3). The top two cities for both

pollutants are Los Angeles (Long Beach-Glendale) and Riverside (San Bernardino-Ontario) in

California. Together, these two cities make up 89% of the estimated air pollution-related deaths

in California, and nearly a third of estimated excess deaths across the entire country. Health

estimates and design values in 2017 for every U.S. county with a validated air quality monitor

are shown in Table E4 in the data supplement.

Trends in national health impacts from 2008-2017 (reported by the third year of each

three-year rolling average) are shown in Figure 1. Trends in annual excess mortality in the U.S.

from air pollution levels above ATS-recommended standards show that there has been a

combined reduction from PM2.5 and O3 of approximately 12,600 excess deaths (95% CI: 5,470 -

21,040) in 2010 to 7,140 excess deaths (95% CI: 2,290 - 14,040) in 2017. Most of this

improvement is attributed to reductions in PM2.5-related mortality (with changes in O3-related

mortality being best described as year-to-year variability). Similar trends are reported in Table

E3 in the supplement showing annual mortality, major morbidity, adversely impacted days, and

lung cancer incidence from 2010-2017, in aggregate and broken down by each pollutant.

The difference in trends for PM2.5 and O3 is also observed when comparing cities with

the highest numbers of excess deaths in 2010 and 2017 as shown in Figures 2 and 3 for PM2.5

and O3, respectively. Figure 2 shows that total number of excess deaths in the top 10 ranked

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cities dropped substantially between these two years, with four cities (Chicago, IL; Houston, TX;

New York City, NY; and Cincinnati, OH) no longer appearing in the top 10 places most impacted

by PM2.5 by 2017. Instead, four new cities (Visalia, CA; Modesto, CA; Hanford, CA; and Seattle,

WA) rose in the ranks and are currently among the top 10. In contrast, the top 10 cities most

impacted by O3 remained largely similar between these two time points, with estimated deaths

remaining relatively unchanged or even slightly increased for many of the cities. Tables E5 and

E6 in the data supplement show ranks and deaths attributable to PM2.5 and O3, respectively, for

all cities with estimates from 2010-2017.

Lastly, Figure 4 compares the time trends between the two study pollutants at the state

level. Showing the two-year intervals in the percent of air pollution-related excess deaths

attributable to PM2.5 and O3 from 2011 to 2017, these maps reveal that PM2.5 went from

contributing to excess health impacts across much of the country to only comprising a majority

of excess air pollution-related health impacts in the western (particularly the northwestern)

parts of the U.S. Additionally, many parts of the country now meet ATS recommendations for

PM2.5. An examination of county-level data over the entire study period reveals that the

proportion of counties with valid design values failing to meet ATS recommendations for PM2.5

fell from 33% in 2010 to 15% in 2017, while the proportion of failing counties for O3 went from

93% in 2010 to 83% in 2017.

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Discussion

Recent trends examined in this year’s "Health of the Air" report indicate that the mortality

impacts of air pollution above ATS-recommended levels fell by nearly half in the last decade.

This improvement can be attributed almost entirely to reductions in PM2.5-related mortality

which decreased by approximately 60% (reduced from 8,330 to 3,260 annual deaths), while O3-

related mortality remained largely unchanged, other than year-to-year variability, over the

same time period (from 4,270 to 3,880 annual deaths) as shown in Figure 1. This phenomenon

is observed nationwide, particularly in those cities with the highest pollution health impacts

(see Figures 2 and 3). However, the rate of PM2.5 improvement appears to have leveled off

since 2014; future reports will be able to determine whether this is a temporary slow-down or if

it represents a true leveling off of pollution impacts in the U.S.

While the magnitude of mortality impacts for air pollution levels greater than ATS

recommendations are quantitatively similar for PM2.5 and O3 for years 2015-2017, the

morbidity and impacted days are much greater in magnitude for O3. This is due to PM2.5 having

a much higher ratio of mortality to morbidity risk than O3 on a per unit basis (19-22).

Figure 4 displays these trends at the state level, showing how the contribution of PM2.5

and O3 across the country went from being essentially geographically equal in 2011 to heavily

weighted towards O3 by 2017. The most recent estimates show excess PM2.5 mortality impacts

confined primarily to the Northwest, parts of the Rocky Mountain West, and California. Most of

the rest of the country is meeting ATS-recommended levels, and therefore measurable excess

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PM2.5-associated mortality has been reduced to zero. Those few places outside of the West still

seeing impacts from PM2.5 each attribute less than 50% of these outcomes to this pollutant.

From the summary in Figure 1 it appears that PM2.5 reductions were far less drastic in

California than across the nation as a whole. However, Figure 2 reveals that in those California

cities with the highest health impacts from PM2.5 (Los Angeles, Riverside, and Bakersfield),

mortality decreased substantially in the last decade. The lack of larger improvements in PM2.5

impacts in California may be explained by a combination of cities throughout the state that saw

marked improvements in air quality with others that saw an increase in air pollution related

health events over time. Consequentially, the vast majority of health impacts from particle

pollution exceeding ATS recommendations are now concentrated in the state of California. In

2010, mortalities from PM2.5 in California represented a full 43% of national PM2.5 impacts. This

grew to 78% in 2017 as PM2.5 impacts fell throughout the rest of the country. In contrast,

mortality impacts attributable O3 levels above ATS standards in California have stayed at

around 30% of national O3 impacts over the past decade. Meanwhile, O3 is now the primary

pollutant attributed to air pollution-related mortality impacts everywhere in the U.S., excluding

the most western states.

While the frequency and severity of wildland fires have been observed to increase in

recent years (23, 24), the emissions from these events are not responsible for the trends

observed in this study. The design values used in this study exclude exceptional events with

regulatory significance, including elevated pollution from wildland fires. Therefore while the

health impacts from wildland fires are an important public health issue that merits further

attention, they are not included in the health impacts estimated in this study.

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The national health impacts attributable to O3 in this report have remained stubbornly

high in the last ten years despite two revisions of the NAAQS strengthening the standard for O3

in 2008 and 2015 (25, 26). Given the large number of locations that currently do not meet the

federal standard for O3, much less the more stringent recommendation from the ATS, it is clear

that local management of ambient O3 will be a pressing issue over the next several years. In

some locations the percentage increase in exposed populations has even grown faster than the

improvements in ambient O3 concentrations, leading to a net increase in air pollution-related

health impacts. While the total contribution of population growth on health estimates remains

small (see Figure E4 in the data supplement) it does represent the need for continued

improvements in air quality to even maintain the same level of health impacts.

A variety of federal and state policies have led to the improvement of air quality in

recent U.S. history. Establishment of NAAQS under the 1970 Clean Air Act amendments was the

turning point for air quality abatement measures in the U.S., establishing the framework of air

quality regulations still in use today. The 1970 amendments mandated the creation of State

Implementation Plans in order to meet federal pollutant standards, jumpstarting new research

in air quality and experimentation in a number of pollution reduction programs. These

regulations were revised and improved over the decades with advances in air quality science

and technology alongside consistent monitoring and assessment of programs. Another

breakthrough came with the 1990 Clean Air Act amendments, which encouraged the use of

market-based measures to meet NAAQS. The resulting multistate cap-and-trade programs used

to meet federal standards may be the greatest contributors to pollution reductions in U.S.

history (9). This included the Acid Rain Program (ARP), which set a cap on SO2 emissions from

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electrical generating units in the U.S. and permitted the buying and selling of emission

allowances. Resulting health benefits in the first two decades of ARP implementation have been

estimated at $50 billion (27).

More recently, reductions in air pollution have come from a number of technology

conversions. One significant conversion has been the transition from coal-fired power to

natural gas energy production. With recent improvements in technology, natural gas now

outpaces coal in energy efficiency, lowering its cost and resulting in natural gas being the

primary electricity source in the U.S. (28, 29). These improvements in energy efficiency have led

to the retirement of a number of high-polluting power plants across the U.S. in the last decade.

Nearly all of these now-closed plants were powered by fossil fuels; specifically, from 2008 to

2017 national coal capacity decreased by 17%, in addition to the shutdown of a significant

number of older natural gas plants (30). These closures have also been a result of requirements

laid out by the EPA’s Mercury and Air Toxics Standards, with power plant retirements projected

to increase through 2020 (31).

Other technology conversions have occurred among mobile sources. The

implementation of Tier II standards in 2000, regulating tailpipe emissions in all passenger

vehicles and limiting fuel sulfur content, have led to dramatic improvements in air quality and

emission technology. Updates to these standards in the 2017 Tier III requirements are

anticipated to provide even greater reductions of a number of air pollutants while preventing

thousands of excess health impacts (32). Additionally, cleaner diesel fuel and trucks rules were

announced in 2000 (33) and implemented over the next decade; these include a 2004 rule

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regulating heavy diesel equipment (34), a 2008 rule for diesel locomotives and marine vessels

(35), and the development of an international program to cleanup oceangoing vessels (36).

All these programs initially led to further reductions in particle pollution, supported by

data from ground monitors and satellite instruments. Long-term trends of particle pollution in

the U.S. show dramatic reductions since the 1980s (37, 38); other studies have shown dramatic

reductions in PM2.5 among major U.S. cities since the early 21st century (39, 40). These

reductions have proved most dramatic in key industrial regions in both the eastern and western

U.S., and include decreases in a number of PM2.5 precursors such as NO2 and SO2 (41-43).

Findings from the present study support these results, with PM2.5 reductions occurring from

2010-2014. However, these improvements leveled off in most recent years as federal rules

became more fully implemented and pollution concentrations targets were met.

Additional improvements in both PM2.5 and O3 emissions may be jeopardized by

changing regulatory priorities at the EPA. Under the Trump Administration, the EPA has

proposed to rollback or weaken several EPA policies that have a direct and indirect impact on

PM2.5 emissions (44). Of great significance is the recent repeal of the Clean Power Plan, which

would have implemented federal requirements on the best system of emission reductions of

carbon pollution from the energy generating sector. These measures are being replaced by the

Affordable Clean Energy Rule, which will significantly relax energy sector requirements (45).

Data from the EPA itself predicts that this repeal will result in hundreds of deaths and

thousands of morbidities that would have been prevented under the Clean Power Plan (46).

Additional efforts are being made by the current administration to freeze the Corporate

Average Fuel Economy standards and replace them with a Safer Affordable Fuel-Efficient

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vehicular rule, weakening existing fuel efficiency standards (47, 48). Other moves to deregulate

air quality abatement include a delayed implementation of the 2015 ozone standard (49), a

potential revision of the Mercury Air Toxics rule (50), and several bills passed by Congress that

would weaken EPA’s authority to regulate air pollution, including O3 and PM2.5 (51, 52). With

such government actions in direct opposition to the efforts of existing air quality regulations, it

is not a given that past trends towards improving air quality will inevitably continue in the

future.

The present report is one of a number of studies assessing the health impacts of air

pollution in recent years. While these types of health impact assessments are continuously

performed for regions of the U.S. (53-56), a considerable number of these studies examine the

increasing health impacts from air pollution in China (57-61) as well as a number of other global

cities and regions (62-67). These studies assess a range of air quality scenarios based on

national and international air quality standards, source-specific impacts, and various

researcher-determined levels. Like the present study, these often rely on ground-based monitor

measurements, though as satellite data is becoming increasingly refined more and more studies

are relying on these measurements to estimate health impacts. Others utilize chemical

transport models based on atmospheric chemistry to make air pollution estimates used in

health assessments. A number of recent studies have also taken advantage of the EPA’s

BenMAP software and provided concentration-response functions to make local air pollution-

associated health impact estimates (53, 54, 67). However, the “Health of the Air” report is

uniquely useful in its county-specific diagnoses provided for all monitored locations across the

continental U.S. Since this report is updated each year, local environmental managers and

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policymakers can use “Health of the Air” data to more accurately track local air quality

improvements and make decisions based on uniform, up-to-date estimates.

Finally, it is important to emphasize that the annual “Health of the Air” report only

presents health impacts from pollution levels above ATS-recommended levels. These numbers

do not reflect the health impacts that have been observed at levels below current ATS

recommendations. For instance, significant mortality impacts have been observed from PM2.5

and O3 concentrations well below the existing national standards (68-70), and long-term O3

mortality effects have been observed (71) but are not yet incorporated into legal standards or

the present report. As such, even those counties meeting current ATS recommendations can

expect to see further health benefits as they continue to make targeted efforts to improve local

air quality.

Conclusion

Improvements in health impacts attributable to ambient PM2.5 concentrations have been

observed across most regions of the United States over the last decade, while O3 impacts have

remained relatively unchanged. Even maintaining current pollution levels will ultimately result

in increasing numbers of mortalities and other health impacts as populations grow over time.

As state and city leaders determine which policy decisions are best suited for reducing air

pollution and keeping up with population growth, they can utilize “Health of the Air” data to

target areas and design policies to best address those pollutants causing the greatest health

impacts among their locales.

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Table 1. 2017 National Annual Excess Health Impacts

Health Endpoint PM2.5 (95% CI) O3 (95% CI) Total (95% CI)Mortality 3,260 (2,210 - 4,310) 3,880 (83 - 9,730) 7,140 (2,290 - 14,040)Lung Cancer Incidence 640 (330 - 950) — 640 (330 - 950)Major Morbidity 5,600 (1,800 - 9,270) 10,080 (-21,740 - 45,800) 15,680 (-19,940 - 55,070)Impacted Days 2,804,000 (2,303,000 - 3,302,000) 11,600,000 (2,816,000 - 23,467,000) 14,404,000 (5,119,000 - 26,768,000)

Note. Confidence intervals are notably wider for O3 due to a larger standard error in the underlying concentration response function.

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Table 2. Top 25 cities with the most to gain by attaining the ATS recommendations for PM2.5 in 2017

PM2.5 Rank City Excess

DeathsLung Cancer

IncidenceExcess

MorbiditiesAdversely

Impacted Days1 Los Angeles (Long Beach-Glendale), CA 877 153 1,700 853,9662 Riverside (San Bernardino-Ontario), CA 698 125 1,211 612,7013 Bakersfield, CA 252 46 470 228,1154 Pittsburgh, PA 184 52 259 103,9675 Fresno, CA 177 34 248 154,7366 Visalia (Porterville), CA 109 17 194 95,4757 Modesto, CA 84 17 150 68,4148 Cleveland (Elyria), OH 71 19 90 39,3849 Hanford (Corcoran), CA 70 11 62 74,614

10 Seattle (Bellevue-Everett), WA 66 16 109 67,61511 Eugene, OR 66 14 74 41,55912 Stockton (Lodi), CA 61 13 112 50,98313 Oakland (Hayward-Berkeley), CA 59 12 105 56,26214 Salt Lake City, UT 46 7 74 51,46215 Detroit (Dearborn-Livonia), MI* 41 13 - -16 Medford, OR 42 10 46 21,793

17 Sacramento (Roseville-Arden-Arcade), CA 27 6 43 21,935

18 Merced, CA 24 5 42 24,17719 Phoenix (Mesa-Scottsdale), AZ 23 5 41 19,33620 San Jose (Sunnyvale-Santa Clara), CA 22 5 33 18,41221 Grants Pass, OR 19 6 17 7,43122 Boise City, ID 19 5 33 17,03723 Madera, CA 17 4 149 14,88424 Yakima, WA 14 3 23 10,81225 Missoula, MT 13 3 19 11,034

* Morbidity and impacted days data unavailable in 2017.

Note. Rank values were determined from a sum value calculated using a 50,000 to 30,000 to 100 to 1 ratio of deaths, lung cancer incidence, morbidities, and impacted days, respectively.

Page 25 of 86

Table 3. Top 25 cities with the most to gain by attaining the ATS recommendations for O3 in 2017

O3 Rank City Excess

DeathsExcess

MorbiditiesAdversely

Impacted Days1 Los Angeles (Long Beach-Glendale), CA 445 1,400 1,789,9262 Riverside (San Bernardino-Ontario), CA 242 587 865,6703 New York (Jersey City-White Plains), NY-NJ 188 678 551,5544 Phoenix (Mesa-Scottsdale), AZ 128 289 376,2905 Chicago (Naperville-Arlington Heights), IL 122 388 370,2806 Houston (The Woodlands-Sugar Land), TX 118 367 475,6997 San Diego (Carlsbad), CA 112 250 375,1798 Sacramento (Roseville-Arden-Arcade), CA 80 157 223,0329 Anaheim (Santa Ana-Irvine), CA 77 165 256,444

10 Dallas (Plano-Irving), TX 76 234 290,07411 Las Vegas (Henderson-Paradise), NV 63 128 154,42512 Atlanta (Sandy Springs-Roswell), GA 52 161 201,98513 Fort Worth (Arlington), TX 50 133 156,04614 Fresno, CA 48 116 162,65815 Warren (Troy-Farmington Hills), MI 48 115 104,95416 Pittsburgh, PA 48 105 80,08617 St. Louis, MO-IL 46 110 104,92918 Denver (Aurora-Lakewood), CO 45 84 150,80819 Cleveland (Elyria), OH 45 93 82,67020 Philadelphia, PA 43 119 126,13921 Montgomery County (Bucks County-Chester County), PA 42 122 107,86422 Bakersfield, CA 42 110 137,87723 Oakland (Hayward-Berkeley), CA 36 101 128,87224 Baltimore (Columbia-Towson), MD 35 124 86,69625 Cincinnati, OH-KY-IN 35 80 89,329

Note. Rank values were determined from a sum value calculated using a 50,000 to 100 to 1 ratio of deaths, morbidities, and impacted days, respectively.

Page 26 of 86

Figure Legends:

Figure 1. Trends in excess mortality attributable to air pollution greater than ATS

recommendations. ATS currently makes recommendations for ambient air quality: 12 µg/m3 for

annual PM2.5; 35 µg/m3 for short-term PM2.5; and 60 ppb for O3. Values are shown for the entire

United States as well as California. Each data point corresponds to pollution concentrations

from the three-year rolling design values.

Figure 2. Excess mortality from the top 10 cities with the most to gain by attaining the ATS

recommendations for PM2.5, 2010 vs. 2017. Y-axis values follow a binary logarithmic scale. Cities

in 2017 marked (*) were not among the top 10 for 2010 and have mortality counts that are

higher in 2017 than previous years.

Figure 3. Excess mortality from the top 10 cities with the most to gain by attaining the ATS

recommendations for O3, 2010 vs. 2017. Y-axis values follow a binary logarithmic scale.

Figure 4. Percent of air pollution-related excess deaths attributable to PM2.5 and O3, 2011-2017.

The percentages are mutually exclusive and sum to a total of 100% for each state. States

showing 0% contribution for a pollutant indicates that it is already meeting ATS-recommended

levels. Some states did not have validated design values for certain years which is indicated by

the gray color on the maps.

Page 27 of 86

Figure 1. Trends in excess mortality attributable to air pollution greater than ATS recommendations. ATS currently makes recommendations for ambient air quality: 12 µg/m3 for annual PM2.5; 35 µg/m3 for short-term PM2.5; and 60 ppb for O3. Values are shown for the entire United States as well as California. Each data point corresponds to pollution concentrations from the three-year rolling design values.

Page 28 of 86

Figure 2. Excess mortality from the top 10 cities with the most to gain by attaining the ATS recommendations for PM2.5, 2010 vs. 2017. Y-axis values follow a binary logarithmic scale. Cities in 2017 marked (*) were not among the top 10 for 2010 and have mortality counts that are higher in 2017 than previous years.

Page 29 of 86

Figure 3. Excess mortality from the top 10 cities with the most to gain by attaining the ATS recommendations for O3, 2010 vs. 2017. Y-axis values follow a binary logarithmic scale.

Page 30 of 86

PM2.5 O3

2011

2013

2015

2017

Percent of Air Pollution-Associated Excess Deaths Attributable to Pollutant

Figure 4. Percent of air pollution-related excess deaths attributable to PM2.5 and O3, 2011-2017. The percentages are mutually exclusive and sum to a total of 100% for each state. States showing 0% contribution for a pollutant indicates that it is already meeting ATS-recommended levels. Some states did not have validated design values for certain years which is indicated by the gray color on the maps.

Page 31 of 86

DATA SUPPLEMENT

Trends in excess morbidity and mortality associated with air pollution above ATS-recommended standards,

2008 to 2017

Kevin R. Cromar, Laura A. Gladson, Gary Ewart

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TABLE E1: EPA standard health functions used in this study by pollutant and metric.

Pollutant Metric Category Health endpoint Ages Study Reference

PM2.5 Mortality Mortality, Chronic Exposure 30-99 (E1)

PM2.5 Morbidity Chronic Bronchitis 27-99 (E2)

PM2.5 Morbidity ED Visit, Asthma 0-17 (E3)

PM2.5 Morbidity Hospital Admission, Asthma 0-17 (E4)

PM2.5 Morbidity Hospital Admission, Chronic Lung Disease

18-64 (E5)

PM2.5 Morbidity Hospital Admission, All Respiratory

65-99 (E6)

PM2.5 Morbidity Acute Myocardial Infarction 0-99 (E6)

PM2.5 Morbidity Hospital Admission, CVD (less Myocardial Infarction)

18-64 (E7)

PM2.5

PM2.5

Morbidity

Morbidity

Hospital Admission, CVD (less Myocardial Infarction)Lung Cancer Incidence

65-99 (E8)

See Table E3

PM2.5 Impacted Days Restricted Activity Days 18-64 (E9)

PM2.5 Impacted Days Work Loss Days 18-64 (E10)

O3 24-hour Mortality Mortality, Acute Exposure 0-99 (E11)

O3

O3

8-hour max

8-hour max

Mortality

Mortality

Mortality, Chronic Exposure

Mortality, Chronic Exposure

30-99

0-99

(E12)

(E13)

O3 1-hour max Mortality Mortality, Chronic Exposure 30-99 (E12)

O3 24-hour Morbidity Hospital Admission, All Respiratory 65-99 (E14)†

O3 8-hour max Morbidity Hospital Admission, All Respiratory 65-99 (E14)†

O3 8-hour max Morbidity Hospital Admission, Chronic Lung Disease

65-99 (E15)

O3 8-hour max Morbidity Hospital Admission, Chronic Lung Disease (less Asthma)

65-99 (E16)

O3 8-hour max Morbidity ED Visit, Asthma 0-99 (E17)†

O3 8-hour max Morbidity ED Visit, Asthma 0-99 (E18)

O3 8-hour max Impacted Days Restricted Activity Days 18-64 (E9)

O3 1-hour max Impacted Days Restricted Activity Days 18-64 (E9)

O3 8-hour max Impacted Days School Loss Days 5-17 (E19)

O3 1-hour max Impacted Days School Loss Days 5-17 (E20)

†Indicates that two health functions were used from the same published study.

Page 33 of 86

TABLE E2: Lung cancer incidence pooled risk used in this study.

Relative and pooled risk values were derived from a meta-analysis of studies examining the relationship of PM2.5 exposure and lung cancer incidence. Relative risk values are reported for a 10 µg/m3 change in PM2.5 exposure. Because an additional study was included this year, risk values below differ from those used in a previous “Health of the Air” report (E21).

Study Reference Region Relative Risk (95% CI) for lung cancer incidence

Pooled Risk (95% CI) for lung cancer incidence

(E22) North America 1.29 (0.95 – 1.76)

(E23) North America 1.06 (0.91 – 1.25)

(E24) North America 1.43 (1.11 – 1.84)

(E25) North America 1.43 (1.10 – 1.65)

(E26) Europe 1.39 (0.91 – 2.13)

(E27) Europe 1.37 (0.86 – 2.17)

1.25 (1.12 – 1.40)

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TABLE E3: National annual excess health impacts from air pollutants in the US, 2010-2017.

Mortality

Year PM2.5 (95% CI) O3 (95% CI) Total (95% CI)2010 8,330 (5,640 - 10,990) 4,270 (93 - 10,050) 12,600 (5,740 - 21,040)2011 6,040 (4,090 - 7,970) 3,240 (34 - 9,640) 9,280 (4,120 - 17,600)2012 5,390 (3,650 - 7,110) 5,150 (109 - 12,700) 10,540 (3,760 - 19,820)2013 4,150 (2,810 - 5,480) 4,940 (103 - 12,100) 9,080 (2,910 - 17,570)2014 2,770 (1,880 - 3,650) 4,260 (87 - 10,350) 7,030 (1,960 - 14,000)2015 3,710 (2,510 - 4,890) 3,380 (71 - 8,340) 7,0909 (2,590 - 13,230)2016 2,590 (1,760 - 3,420) 3,590 (76 - 8,880) 6,180 (1,830 - 12,290)2017 3,260 (2,210 - 4,310) 3,880 (83 - 9,730) 7,140 (2,290 - 14,040)

Major Morbidity

Year PM2.5 (95% CI) O3 (95% CI) Total (95% CI)2010 15,050 (4,850 - 24,890) 11,850 (-27,190 - 51,260) 26,900 (-22,340 - 76,150)2011 11,040 (3,610 - 18,220) 10,540 (-26,510 - 49,750) 21,580 (-22,900 - 67,970)2012 7,990 (2,330 - 13,460) 13,940 (-31,500 - 61,320) 21,930 (-29,170 - 74,780)2013 8,010 (2,710 - 13,120) 13,070 (-29,280 - 57,800) 21,080 (-26,570 - 70,920)2014 4,060 (1,190 - 6,820) 11,020 (-24,180 - 49,090) 15,080 (-22,990 - 55,910)2015 6,560 (2,140 - 10,820) 8,800 (-19,300 - 39,610) 15,360 (-17,160 - 50,430)2016 4,270 (1,360 - 7,070) 9,350 (-20,350 - 42,300) 13,620 (-18,990 - 49,370)2017 5,600 (1,800 - 9,270) 10,080 (-21,740 - 45,800) 15,680 (-19,940 - 55,070)

Adversely Impacted Days

Year PM2.5 (95% CI) O3 (95% CI) Total (95% CI)2010 6,916,000 (5,678,000 - 8,143,000) 14,514,000 (3,441,000 - 29,262,000) 21,431,000 (9,120,000 - 37,405,000)2011 5,367,000 (4,407,000 - 6,320,000) 14,004,000 (3,339,000 - 28,025,000) 19,371,000 (7,746,000 - 34,346,000)2012 3,267,000 (2,681,000 - 3,847,000) 17,897,000 (3,267,000 - 32,183,000) 21,163,000 (5,948,000 - 36,030,000)2013 4,224,000 (3,483,000 - 4,959,000) 16,950,000 (3,203,000 - 30,210,000) 21,174,000 (6,686,000 - 35,169,000)2014 1,661,000 (1,365,000 - 1,954,000) 14,956,000 (3,009,000 - 25,682,000) 16,617,000 (4,374,000 - 27,636,000)2015 3,246,000 (2,667,000 - 3,821,000) 11,563,000 (2,182,000 - 20,839,000) 14,809,000 (4,849,000 - 24,659,000)2016 2,078,000 (1,707,000 - 2,447,000) 12,054,000 (2,298,000 - 21,677,000) 14,132,000 (4,005,000 - 24,124,000)2017 2,804,000 (2,303,000 - 3,302,000) 11,600,000 (2,816,000 - 23,467,000) 14,404,000 (5,119,000 - 26,768,000)

Lung Cancer Incidence

Year PM2.5 (95% CI)2010 2,170 (1,120 - 3,187)2011 1,520 (780 - 2,240)2012 1,340 (690 - 1,970)2013 950 (490 - 1,390)2014 610 (320 - 900)2015 790 (410 - 1,160)2016 550 (280 - 800)2017 640 (330 - 950)

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TABLE E4: Health impacts and design values, by pollutant, for counties with at least one valid design value.

The 2017 design values for O3 (ppm) represent the 4th highest daily 8-hour maximum value averaged over three years from 2015-2017. The 2017 annual (or long-term) design value for PM2.5 (µg/m3) represents the annual concentration averaged over the same three years, while the daily (or short-term) PM2.5 design value represents the daily 98th percentile averaged over this same time. Counties with design values listed as "NA" indicate that valid monitoring data was not available for this three year period. The design value listed for each state represents that maximum design value among all listed counties for that state, while the health estimates listed for each state represent the sums of all listed counties.

Counties with valid monitoring concentrations below the current ATS recommendations have a "—" symbol listed under the health impacts. While further improvements in air quality in these counties is expected to result in additional public health benefits, this analysis only estimates health impacts associated with meeting ATS-recommended concentrations. Health estimates for counties without valid monitoring data is listed as "NA."

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Alabama 0.068 22 57 47,685 11.0 22 — — — —

Baldwin 0.063 1 4 2,318 7.7 17 — — — —

Clay NA NA NA NA 7.8 18 — — — —

Colbert 0.058 — — — 7.9 16 — — — —

DeKalb 0.062 0 1 632 8.3 16 — — — —

Etowah 0.061 0 1 542 8.7 17 — — — —

Houston 0.058 — — — 7.7 15 — — — —

Jefferson 0.068 11 28 23,774 11.0 22 — — — —

Madison 0.064 3 8 6,654 7.7 16 — — — —

Mobile 0.063 3 6 4,899 8.1 17 — — — —

Montgomery 0.061 0 1 1,029 8.8 20 — — — —

Morgan 0.063 1 2 1,595 7.9 15 — — — —

Russell 0.062 0 1 497 NA NA NA NA NA NA

Shelby 0.066 2 6 5,747 NA NA NA NA NA NA

Talladega NA NA NA NA 9.1 18 — — — —

Tuscaloosa 0.060 — — — 8.1 16 — — — —

Arizona 0.076 168 348 447,770 9.6 32 24 5 42 20,022

Cochise 0.065 2 3 2,977 NA NA NA NA NA NA

Coconino 0.066 1 2 4,500 NA NA NA NA NA NA

Gila 0.073 3 4 2,802 NA NA NA NA NA NA

La Paz 0.068 1 1 571 3.0 9 — — — —

Maricopa 0.076 117 264 350,380 9.6 27 23 5 39 18,736

Navajo 0.063 1 1 1,609 NA NA NA NA NA NA

Pima 0.069 22 32 42,245 6.1 15 — — — —

Pinal 0.074 11 24 25,911 8.6 32 1 0 1 600

Page 36 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Santa Cruz NA NA NA NA 9.2 28 1 0 1 686

Yavapai 0.067 6 7 6,274 NA NA NA NA NA NA

Yuma 0.072 5 9 10,502 7.5 19 — — — —

Arkansas 0.066 4 8 7,605 9.8 21 — — — —

Arkansas NA NA NA NA 8.3 18 — — — —

Ashley NA NA NA NA 8.2 16 — — — —

Clark 0.057 — — — NA NA NA NA NA NA

Crittenden 0.066 1 1 1,396 8.3 16 — — — —

Garland NA NA NA NA 8.5 17 — — — —

Jackson NA NA NA NA 8.2 19 — — — —

Newton 0.057 — — — NA NA NA NA NA NA

Polk 0.062 0 0 214 8.2 18 — — — —

Pulaski 0.063 3 7 5,996 9.8 21 — — — —

Union NA NA NA NA 8.9 18 — — — —

Washington 0.060 — — — 7.9 17 — — — —

California 0.112 1,266 3,336 4,473,107 22.2 72 2,539 463 4,616 2,321,961

Alameda 0.075 27 74 93,490 10.6 28 43 9 79 42,821

Amador 0.072 1 2 1,970 NA NA NA NA NA NA

Butte 0.076 10 27 16,922 8.6 28 3 1 4 1,652

Calaveras 0.078 2 3 3,519 NA NA NA NA NA NA

Colusa 0.063 0 0 355 7.6 24 — — — —

Contra Costa 0.068 9 27 35,382 9.3 30 16 3 26 13,441

El Dorado 0.083 10 12 20,322 NA NA NA NA NA NA

Fresno 0.092 48 116 162,658 14.0 54 177 34 248 154,736

Glenn 0.063 0 0 378 NA NA NA NA NA NA

Humboldt 0.043 — — — 6.8 21 — — — —

Imperial 0.077 4 16 14,796 12.0 31 10 2 27 9,306

Inyo 0.061 0 0 86 7.2 29 0 0 0 225

Kern 0.090 42 110 137,877 17.3 59 252 46 470 228,115

Kings 0.084 5 3 18,605 22.2 72 70 11 62 74,614

Lake 0.057 — — — 4.3 19 — — — —

Los Angeles 0.101 445 1,400 1,789,926 12.6 39 877 153 1,700 853,966

Madera 0.084 6 41 17,864 12.8 42 17 4 149 14,884

Marin 0.058 — — — 8.2 27 4 1 5 2,738

Mariposa 0.075 1 0 1,097 NA NA NA NA NA NA

Mendocino 0.052 — — — 8.1 24 — — — —

Merced 0.081 8 19 29,077 12.7 39 24 5 42 24,177

Monterey 0.059 — — — 6.1 28 1 0 2 1,064

Napa 0.063 1 1 1,715 10.9 35 7 1 8 4,426

Page 37 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Nevada 0.086 7 14 11,435 4.7 18 — — — —

Orange 0.078 77 165 256,444 7.5 15 — — — —

Placer 0.084 12 17 33,929 7.4 19 — — — —

Plumas NA NA NA NA 15.1 50 8 2 10 3,616

Riverside 0.101 146 322 447,042 13.6 39 312 60 464 258,748

Sacramento 0.082 55 124 158,706 9.6 34 27 6 43 21,935

San Benito 0.068 1 1 2,434 4.6 14 — — — —

San Bernardino 0.112 96 265 418,628 14.7 37 386 65 748 353,953

San Diego 0.084 112 250 375,179 8.9 22 — — — —

San Francisco 0.047 — — — 8.3 26 9 2 13 8,226

San Joaquin 0.077 21 58 58,305 12.2 39 61 13 112 50,983

San Luis Obispo 0.072 8 11 15,971 9.6 24 — — — —

San Mateo 0.056 — — — 7.7 23 — — — —

Santa Barbara 0.065 3 5 8,589 8.2 24 — — — —

Santa Clara 0.069 20 42 82,067 9.4 28 22 5 33 18,412

Santa Cruz 0.056 — — — 5.7 17 — — — —

Shasta 0.076 9 17 13,091 6.8 21 — — — —

Siskiyou NA NA NA NA 7.8 34 4 1 3 1,604

Solano 0.067 6 13 14,453 9.5 30 10 2 15 8,154

Sonoma 0.058 — — — 6.5 21 — — — —

Stanislaus 0.084 21 67 64,562 13.2 45 84 17 150 68,414

Sutter 0.071 2 2 6,065 9.0 28 1 0 1 864

Tehama 0.079 4 6 5,875 NA NA NA NA NA NA

Tulare 0.089 23 56 70,256 15.7 54 109 17 194 95,475

Tuolumne 0.080 2 3 4,067 NA NA NA NA NA NA

Ventura 0.077 21 44 69,898 9.7 43 6 1 9 5,411

Yolo 0.069 3 4 10,074 7.5 25 — — — —

Colorado 0.079 70 134 226,556 8.5 26 3 1 6 3,262

Adams 0.067 3 7 15,330 NA NA NA NA NA NA

Arapahoe 0.067 8 15 23,771 5.9 18 — — — —

Boulder NA NA NA NA 6.7 23 — — — —

Denver 0.069 6 11 25,845 8.5 23 — — — —

Douglas 0.077 6 17 32,148 5.4 19 — — — —

El Paso 0.068 9 17 27,895 5.7 17 — — — —

Garfield 0.062 0 0 589 NA NA NA NA NA NA

Gunnison 0.065 0 0 392 NA NA NA NA NA NA

Jefferson 0.079 23 34 53,715 NA NA NA NA NA NA

La Plata 0.069 1 2 2,577 4.9 9 — — — —

Larimer 0.075 8 17 25,421 7.1 21 — — — —

Mesa 0.064 2 2 3,159 6.1 19 — — — —

Montezuma 0.066 1 1 758 NA NA NA NA NA NA

Page 38 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Pueblo NA NA NA NA 5.2 16 — — — —

Rio Blanco 0.063 0 0 103 7.8 14 — — — —

Weld 0.070 4 10 14,854 8.3 26 3 1 6 3,262

Connecticut 0.083 96 269 242,585 8.6 22 — — — —

Fairfield 0.083 32 98 86,654 8.6 22 — — — —

Hartford 0.072 18 50 42,390 8.2 20 — — — —

Litchfield 0.072 5 12 8,714 4.6 13 — — — —

Middlesex 0.079 5 14 11,286 NA NA NA NA NA NA

New Haven 0.082 22 64 66,730 7.0 20 — — — —

New London 0.076 8 19 15,689 5.5 15 — — — —

Tolland 0.071 3 8 6,913 NA NA NA NA NA NA

Windham 0.070 2 5 4,211 NA NA NA NA NA NA

Delaware 0.074 15 36 39,190 7.4 17 — — — —

Kent 0.066 2 5 4,677 NA NA NA NA NA NA

New Castle 0.074 8 22 28,484 NA NA NA NA NA NA

Sussex 0.067 4 9 6,028 7.4 17 — — — —

D.C. 0.071 9 29 33,650 9.2 21 — — — —

Florida 0.067 65 174 143,655 8.0 18 — — — —

Alachua 0.059 — — — 6.1 14 — — — —

Baker 0.060 — — — NA NA NA NA NA NA

Bay 0.060 — — — NA NA NA NA NA NA

Brevard 0.060 — — — 5.7 14 — — — —

Broward 0.062 5 15 12,953 6.6 16 — — — —

Collier 0.059 — — — NA NA NA NA NA NA

Columbia 0.060 — — — NA NA NA NA NA NA

Escambia 0.063 2 5 3,774 7.4 15 — — — —

Flagler 0.059 — — — NA NA NA NA NA NA

Highlands 0.060 — — — NA NA NA NA NA NA

Hillsborough 0.067 14 37 35,675 8.0 17 — — — —

Holmes 0.058 — — — NA NA NA NA NA NA

Lake 0.063 2 5 3,177 NA NA NA NA NA NA

Lee 0.060 — — — 6.1 13 — — — —

Leon 0.061 0 1 1,040 7.4 17 — — — —

Liberty 0.056 — — — NA NA NA NA NA NA

Manatee 0.063 2 4 3,444 NA NA NA NA NA NA

Marion 0.061 1 2 1,052 NA NA NA NA NA NA

Martin 0.061 0 0 292 NA NA NA NA NA NA

Page 39 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Miami-Dade 0.063 10 29 24,775 7.5 16 — — — —

Okaloosa 0.060 — — — NA NA NA NA NA NA

Orange 0.064 5 19 17,888 7.1 16 — — — —

Osceola 0.064 1 7 5,090 NA NA NA NA NA NA

Palm Beach 0.061 2 6 4,017 6.0 13 — — — —

Pasco 0.061 1 3 2,040 NA NA NA NA NA NA

Pinellas 0.062 4 9 6,316 7.1 18 — — — —

Polk 0.066 7 21 11,634 6.5 14 — — — —

St. Lucie 0.061 1 2 1,129 NA NA NA NA NA NA

Santa Rosa 0.061 0 1 877 NA NA NA NA NA NA

Sarasota 0.063 3 4 3,244 6.4 14 — — — —

Seminole 0.063 2 4 5,238 5.9 14 — — — —

Volusia 0.059 — — — 6.1 13 — — — —

Wakulla 0.059 — — — NA NA NA NA NA NA

Georgia 0.075 56 168 210,161 10.5 29 1 0 1 377

Bibb 0.065 2 3 3,128 9.6 20 — — — —

Chatham 0.057 — — — 8.2 20 — — — —

Chattooga 0.061 0 0 110 NA NA NA NA NA NA

Clarke 0.064 1 2 2,392 8.2 16 — — — —

Clayton NA NA NA NA 9.6 18 — — — —

Cobb 0.067 7 20 24,602 9.0 18 — — — —


Coweta 0.063 1 2 1,923 NA NA NA NA NA NA

Dawson 0.065 0 0 445 NA NA NA NA NA NA

DeKalb 0.071 8 29 35,664 9.0 19 — — — —

Dougherty NA NA NA NA 9.0 22 — — — —

Douglas 0.069 2 5 5,865 NA NA NA NA NA NA

Fulton 0.075 18 55 68,162 10.5 23 — — — —

Glynn 0.056 — — — 7.5 22 — — — —

Gwinnett 0.071 10 37 49,955 8.7 20 — — — —

Hall NA NA NA NA 8.0 19 — — — —

Henry 0.071 4 9 11,160 NA NA NA NA NA NA

Houston NA NA NA NA 8.3 18 — — — —

Lowndes NA NA NA NA 7.8 18 — — — —

Murray 0.065 1 1 846 NA NA NA NA NA NA

Muscogee 0.061 0 1 854 9.5 29 1 0 1 377

Pike 0.067 0 1 575 NA NA NA NA NA NA

Richmond 0.061 0 1 845 9.3 23 — — — —

Rockdale 0.069 1 3 3,635 NA NA NA NA NA NA

Sumter 0.060 — — — NA NA NA NA NA NA

Walker NA NA NA NA 9.0 18 — — — —

Page 40 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Washington NA NA NA NA 8.3 23 — — — —

Idaho 0.070 7 15 21,071 12.6 47 26 7 41 20,643

Ada 0.070 7 15 21,071 7.6 31 12 3 20 11,076

Bannock NA NA NA NA 7.7 27 1 0 2 994

Benewah NA NA NA NA 10.5 39 1 0 1 502

Butte 0.060 — — — NA NA NA NA NA NA

Canyon NA NA NA NA 9.4 34 7 2 12 5,961

Franklin NA NA NA NA 7.0 30 0 0 0 81

Lemhi NA NA NA NA 12.6 47 2 0 2 802

Shoshone NA NA NA NA 12.4 41 3 1 3 1,225

Illinois 0.073 169 523 492,417 10.5 25 — — — —

Adams 0.063 1 1 866 NA NA NA NA NA NA

Champaign 0.066 2 5 5,567 7.9 17 — — — —

Clark 0.065 0 0 346 NA NA NA NA NA NA

Cook 0.073 97 309 295,066 10.5 25 — — — —

DuPage 0.070 16 50 45,616 8.3 20 — — — —

Effingham 0.066 1 1 929 NA NA NA NA NA NA

Hamilton 0.065 0 0 193 8.2 18 — — — —

Jo Daviess 0.064 0 1 368 NA NA NA NA NA NA

Kane 0.069 7 24 22,890 8.3 19 — — — —

Lake 0.073 13 41 39,903 NA NA NA NA NA NA

McHenry 0.069 5 13 12,798 NA NA NA NA NA NA

McLean 0.064 1 4 3,483 8.0 18 — — — —

Macon 0.066 2 4 2,903 8.4 17 — — — —

Macoupin 0.065 1 1 948 NA NA NA NA NA NA

Madison 0.070 7 15 12,737 9.7 22 — — — —

Peoria 0.065 2 5 4,256 8.2 17 — — — —

Randolph 0.066 1 1 878 8.5 18 — — — —

Rock Island 0.063 1 3 1,944 8.1 20 — — — —

Saint Clair 0.068 4 11 10,213 9.8 19 — — — —

Sangamon 0.067 3 8 6,220 8.2 20 — — — —

Will 0.065 5 17 16,799 7.9 19 — — — —

Winnebago 0.066 4 9 7,493 8.3 18 — — — —

Indiana 0.071 65 86 141,679 10.5 25 — — — —

Allen 0.064 3 4 7,006 8.9 22 — — — —

Bartholomew 0.067 1 3 2,603 8.3 18 — — — —

Boone 0.066 1 1 1,776 NA NA NA NA NA NA

Carroll 0.063 0 0 258 NA NA NA NA NA NA

Page 41 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Clark 0.071 3 5 5,766 9.6 22 — — — —

Delaware 0.062 1 1 922 8.1 17 — — — —

Dubois NA NA NA NA 8.9 20 — — — —

Elkhart 0.064 2 3 3,662 9.1 25 — — — —

Floyd 0.071 2 3 3,501 8.5 19 — — — —

Greene 0.067 1 1 1,025 8.1 18 — — — —

Hamilton 0.067 3 4 10,222 8.3 19 — — — —

Hendricks 0.063 1 1 2,174 NA NA NA NA NA NA

Henry NA NA NA NA 7.5 16 — — — —

Howard NA NA NA NA 9.5 21 — — — —

Huntington 0.060 — — — NA NA NA NA NA NA

Jackson 0.065 1 1 983 NA NA NA NA NA NA

Johnson 0.062 1 1 1,157 NA NA NA NA NA NA

Knox 0.066 1 1 1,026 NA NA NA NA NA NA

Lake 0.068 8 10 17,148 9.3 23 — — — —

LaPorte 0.067 2 3 3,239 8.1 20 — — — —

Madison 0.062 1 1 1,069 8.2 19 — — — —

Marion 0.070 18 18 42,365 10.5 22 — — — —

Monroe NA NA NA NA 7.9 17 — — — —

Morgan 0.062 0 1 659 NA NA NA NA NA NA

Perry 0.067 0 1 626 NA NA NA NA NA NA

Porter 0.069 3 4 6,677 8.3 20 — — — —

Posey 0.067 0 1 779 NA NA NA NA NA NA

Shelby 0.064 0 1 791 NA NA NA NA NA NA

Spencer NA NA NA NA 8.7 19 — — — —

St. Joseph 0.070 5 7 11,716 8.7 22 — — — —

Tippecanoe NA NA NA NA 8.2 19 — — — —

Vanderburgh 0.069 4 7 7,581 9.3 19 — — — —

Vigo 0.067 2 2 3,291 9.0 20 — — — —

Wabash 0.068 1 1 1,067 NA NA NA NA NA NA

Warrick 0.069 1 2 2,590 NA NA NA NA NA NA

Whitley NA NA NA NA 8.1 20 — — — —

Iowa 0.062 1 3 3,117 8.7 23 — — — —

Black Hawk NA NA NA NA 7.9 20 — — — —

Bremer 0.060 — — — NA NA NA NA NA NA

Clinton 0.062 0 0 307 8.6 21 — — — —

Harrison 0.062 0 0 118 NA NA NA NA NA NA

Johnson NA NA NA NA 7.7 19 — — — —

Lee NA NA NA NA 8.4 19 — — — —

Linn 0.061 0 0 663 8.1 20 — — — —

Montgomery 0.060 — — — 6.5 16 — — — —

Page 42 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Muscatine NA NA NA NA 8.3 21 — — — —

Palo Alto 0.061 0 0 47 6.8 16 — — — —

Polk 0.059 — — — 7.4 18 — — — —

Pottawattamie NA NA NA NA 7.7 18 — — — —

Scott 0.062 1 2 1,981 8.7 23 — — — —

Van Buren 0.059 — — — 6.9 18 — — — —

Kansas 0.064 5 11 11,411 8.8 21 — — — —

Johnson 0.059 — — — 7.3 17 — — — —

Leavenworth 0.060 — — — NA NA NA NA NA NA

Neosho 0.061 0 0 95 7.8 18 — — — —

Sedgwick 0.063 3 7 7,369 7.9 21 — — — —

Shawnee 0.062 1 2 1,560 7.7 19 — — — —

Sumner 0.064 0 0 402 7.0 17 — — — —

Trego 0.061 0 0 8 NA NA NA NA NA NA

Wyandotte 0.062 1 2 1,977 8.8 21 — — — —

Kentucky 0.074 37 85 76,711 9.7 25 — — — —

Bell 0.060 — — — 8.8 25 — — — —


Boyd 0.065 1 2 1,033 8.0 18 — — — —

Bullitt 0.065 1 2 1,953 NA NA NA NA NA NA

Campbell 0.069 2 4 3,703 8.4 19 — — — —

Carter 0.062 0 0 289 6.7 16 — — — —

Christian 0.061 0 0 430 8.5 19 — — — —

Daviess 0.065 1 2 2,272 8.8 19 — — — —

Edmonson 0.064 0 0 207 NA NA NA NA NA NA

Fayette 0.066 3 7 9,089 8.2 18 — — — —

Greenup 0.062 0 0 324 NA NA NA NA NA NA

Hancock 0.067 0 0 277 NA NA NA NA NA NA

Hardin 0.064 1 3 2,152 8.5 18 — — — —

Henderson 0.068 1 2 1,662 8.9 18 — — — —

Jefferson 0.074 23 56 45,834 9.7 21 — — — —

Jessamine 0.064 0 1 1,046 NA NA NA NA NA NA

Livingston 0.064 0 0 174 NA NA NA NA NA NA

Madison NA NA NA NA 7.7 17 — — — —

McCracken 0.062 0 1 620 8.6 18 — — — —

Morgan 0.064 0 0 231 NA NA NA NA NA NA

Oldham 0.068 1 2 2,617 NA NA NA NA NA NA

Perry 0.058 — — — 8.0 19 — — — —

Pike 0.059 — — — 7.4 20 — — — —

Page 43 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Pulaski 0.061 0 0 233 7.9 17 — — — —

Simpson 0.064 0 0 333 NA NA NA NA NA NA

Trigg 0.061 0 0 47 NA NA NA NA NA NA

Warren 0.061 0 1 725 8.2 17 — — — —

Washington 0.064 0 0 193 NA NA NA NA NA NA

Louisiana 0.070 23 51 55,280 10.2 21 — — — —

Ascension 0.070 2 4 4,726 NA NA NA NA NA NA

Bossier 0.065 1 3 2,735 NA NA NA NA NA NA

Caddo 0.063 2 3 3,133 10.2 21 — — — —

Calcasieu 0.066 3 5 4,672 7.6 18 — — — —East Baton

Rouge 0.067 4 10 11,072 9.0 20 — — — —

Iberville 0.066 0 1 757 8.2 19 — — — —

Jefferson 0.066 4 9 10,518 7.5 19 — — — —

Lafayette 0.065 2 4 4,613 7.6 16 — — — —

Lafourche 0.063 1 1 1,191 NA NA NA NA NA NA

Livingston 0.068 2 4 4,248 NA NA NA NA NA NA

Orleans NA NA NA NA 8.2 18 — — — —

Pointe Coupee 0.067 0 1 505 NA NA NA NA NA NA

St. Bernard 0.064 0 1 708 8.5 19 — — — —

St. James 0.063 0 0 234 NA NA NA NA NA NASt. John the

Baptist 0.065 0 1 874 NA NA NA NA NA NA

St. Tammany 0.065 2 5 4,658 NA NA NA NA NA NA

Tangipahoa NA NA NA NA 7.5 16 — — — —

Terrebonne NA NA NA NA 7.1 16 — — — —West Baton

Rouge 0.067 0 1 635 9.1 19 — — — —

Maine 0.071 7 2 3,305 7.3 20 — — — —

Androscoggin 0.059 — — — 7.0 17 — — — —

Aroostook 0.052 — — — 7.3 19 — — — —

Cumberland* 0.064 3 NA NA 7.0 17 — — — —

Hancock* 0.071 2 NA NA 4.1 12 — — — —

Kennebec 0.063 1 1 1,278 NA NA NA NA NA NA

Knox 0.064 0 1 546 NA NA NA NA NA NA

Oxford NA NA NA NA 6.6 20 — — — —

Penobscot 0.060 — — — 6.4 15 — — — —

Washington 0.060 — — — NA NA NA NA NA NA

York 0.062 1 1 1,481 NA NA NA NA NA NA

Maryland 0.075 71 218 201,855 9.1 23 — — — —

Page 44 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Baltimore 0.073 13 44 39,616 8.9 23 — — — —

Calvert 0.067 1 3 3,236 NA NA NA NA NA NA

Carroll 0.069 4 6 7,131 NA NA NA NA NA NA

Cecil 0.074 3 6 5,965 8.4 21 — — — —

Charles 0.069 2 8 6,930 NA NA NA NA NA NA

Dorchester 0.065 0 2 701 7.8 17 — — — —

Frederick 0.069 4 9 10,536 NA NA NA NA NA NA

Garrett 0.066 0 1 806 5.5 14 — — — —

Harford 0.075 7 15 15,671 8.1 21 — — — —

Howard NA NA NA NA 9.1 20 — — — —

Kent 0.070 1 2 761 7.9 18 — — — —

Montgomery 0.068 10 22 37,286 7.4 18 — — — —

Prince George's 0.071 12 36 44,094 8.4 18 — — — —

Washington 0.067 3 6 4,844 8.6 20 — — — —

Baltimore (City) 0.069 11 59 24,279 8.7 22 — — — —

Massachusetts 0.073 71 188 160,549 7.2 18 — — — —

Berkshire NA NA NA NA 6.3 15 — — — —

Bristol 0.073 14 43 27,790 6.1 15 — — — —

Essex 0.066 8 23 17,927 5.3 15 — — — —

Franklin 0.065 1 2 1,348 5.5 15 — — — —

Hampden 0.071 9 30 19,853 6.9 18 — — — —

Hampshire 0.070 2 4 6,404 NA NA NA NA NA NA


Norfolk 0.070 12 26 26,548 NA NA NA NA NA NA

Plymouth 0.068 7 19 14,984 5.3 16 — — — —

Suffolk 0.061 1 3 3,051 7.2 16 — — — —

Worcester 0.066 8 20 19,133 5.9 15 — — — —

Michigan 0.074 132 304 313,447 11.2 28 41 NA 32 NA

Allegan 0.073 2 4 6,139 7.5 21 — — — —

Bay NA NA NA NA 7.1 22 — — — —

Benzie 0.068 0 1 528 NA NA NA NA NA NA

Berrien 0.073 5 8 8,600 7.8 21 — — — —

Cass 0.072 2 2 2,578 NA NA NA NA NA NA

Chippewa 0.057 — — — NA NA NA NA NA NA

Genesee 0.067 7 15 12,810 7.5 19 — — — —

Huron 0.067 1 1 835 NA NA NA NA NA NA

Ingham 0.067 3 8 9,424 7.7 20 — — — —

Kalamazoo 0.069 4 8 10,699 8.4 22 — — — —

Kent 0.068 8 18 23,735 9.1 25 — — — —

Page 45 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Lenawee 0.066 2 2 2,680 7.8 19 — — — —

Macomb 0.071 21 47 42,770 8.2 23 — — — —

Manistee 0.067 1 1 642 5.9 17 — — — —

Mason 0.068 1 1 926 NA NA NA NA NA NA

Missaukee 0.066 0 0 364 5.1 15 — — — —

Monroe NA NA NA NA 8.2 22 — — — —

Muskegon 0.074 5 7 9,680 NA NA NA NA NA NA

Oakland 0.070 23 57 54,680 8.5 23 — — — —

Ottawa 0.068 4 8 10,711 NA NA NA NA NA NA

Schoolcraft 0.067 0 0 210 NA NA NA NA NA NA

St. Clair 0.071 5 10 7,504 8.4 22 — — — —

Tuscola 0.065 1 2 1,207 NA NA NA NA NA NA

Washtenaw 0.069 4 12 14,589 8.4 21 — — — —

Wayne** 0.073 34 89 91,375 11.2 28 41 13 20 NA

Wexford 0.066 0 1 762 NA NA NA NA NA NA

Minnesota 0.062 1 2 3,916 8.0 19 — — — —

Anoka 0.062 1 2 2,777 6.7 18 — — — —

Becker 0.059 — — — 4.8 16 — — — —

Beltrami NA NA NA NA 5.2 15 — — — —

Carlton 0.059 — — — NA NA NA NA NA NA

Crow Wing 0.059 — — — 5.8 16 — — — —

Dakota NA NA NA NA 6.7 17 — — — —

Goodhue 0.060 — — — NA NA NA NA NA NA

Hennepin 0.055 — — — 8.0 18 — — — —

Lake 0.055 — — — 4.0 12 — — — —

Lyon NA NA NA NA 5.0 17 — — — —

Mille Lacs 0.060 — — — NA NA NA NA NA NA

Olmsted 0.061 0 0 420 6.7 17 — — — —

Ramsey NA NA NA NA 7.5 19 — — — —

Saint Louis 0.054 — — — 5.2 16 — — — —

Scott 0.061 0 0 720 6.4 16 — — — —

Stearns 0.059 — — — 5.7 16 — — — —

Washington 0.060 — — — 6.4 19 — — — —

Wright 0.060 — — — 6.3 17 — — — —

Mississippi 0.064 4 9 7,790 8.9 19 — — — —

Forrest NA NA NA NA 8.9 17 — — — —

Grenada NA NA NA NA 7.2 14 — — — —

Bolivar 0.062 0 0 242 NA NA NA NA NA NA

DeSoto 0.062 1 1 1,728 8.1 16 — — — —

Page 46 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Hancock 0.060 — — — 8.1 18 — — — —

Harrison 0.064 2 4 3,275 8.1 17 — — — —

Hinds 0.061 0 1 842 8.9 19 — — — —

Jackson 0.063 1 2 1,704 8.3 18 — — — —

Lauderdale 0.056 — — — NA NA NA NA NA NA

Lee 0.058 — — — NA NA NA NA NA NA

Yalobusha 0.055 — — — NA NA NA NA NA NA

Missouri 0.072 42 99 97,815 9.5 21 — — — —

Andrew 0.062 0 0 160 NA NA NA NA NA NA


Buchanan NA NA NA NA 8.8 19 — — — —

Callaway 0.062 0 0 394 NA NA NA NA NA NA

Cass 0.063 1 2 1,484 7.3 17 — — — —

Cedar 0.060 — — — 6.8 16 — — — —

Clay 0.069 4 10 9,964 7.1 16 — — — —

Clinton 0.067 1 1 689 NA NA NA NA NA NA

Greene 0.060 — — — NA NA NA NA NA NA

Jackson NA NA NA NA 9.0 20 — — — —

Jasper 0.060 — — — NA NA NA NA NA NA

Jefferson 0.068 4 8 7,939 9.3 20 — — — —

Monroe 0.059 — — — NA NA NA NA NA NA

Perry 0.067 0 1 616 NA NA NA NA NA NA

Saint Charles 0.072 5 15 20,101 NA NA NA NA NA NA

Saint Louis 0.069 22 51 43,625 9.5 21 — — — —Sainte

Genevieve 0.065 0 1 430 NA NA NA NA NA NA

St. Louis City 0.066 4 8 9,367 9.0 21 — — — —

Taney 0.057 — — — NA NA NA NA NA NA

Montana 0.058 — — — 13.0 72 46 12 58 28,823

Fergus 0.057 — — — 5.1 29 0 0 0 172

Flathead 0.053 — — — 9.1 49 8 2 11 5,189

Lewis and Clark 0.058 — — — 9.8 47 6 1 8 3,777

Lincoln NA NA NA NA 13.0 48 5 2 5 2,114

Missoula 0.055 — — — 11.4 55 13 3 19 11,034

Phillips 0.056 — — — 5.7 27 0 0 0 62

Powder River 0.057 — — — 7.8 30 0 0 0 39

Ravalli NA NA NA NA 11.7 72 10 2 11 4,750

Rosebud 0.057 — — — 6.5 29 0 0 0 163

Silver Bow NA NA NA NA 10.3 40 3 1 3 1,525

Page 47 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Nebraska 0.064 3 5 6,783 8.9 20 — — — —

Douglas 0.063 3 5 6,651 8.9 20 — — — —

Hall NA NA NA NA 5.9 14 — — — —

Knox 0.064 0 0 132 NA NA NA NA NA NA

Lancaster 0.060 — — — 6.4 17 — — — —

Sarpy NA NA NA NA 8.7 19 — — — —

Washington NA NA NA NA 6.6 15 — — — —

Nevada 0.074 78 154 182,626 9.8 24.0 — — — —

Churchill 0.068 1 2 919 NA NA NA NA NA NA

Clark 0.074 63 128 154,425 9.8 24 — — — —

Douglas NA NA NA NA 7.9 NA — — — —

Lyon 0.069 1 2 2,175 NA NA NA NA NA NA

Washoe 0.070 11 20 23,282 7.6 24 — — — —

White Pine 0.064 0 0 189 NA NA NA NA NA NA

Carson City 0.066 1 2 1,636 5.0 15 — — — —

New Hampshire 0.068 11 27 22,822 6.5 20 — — — —

Belknap 0.059 — — — 4.7 10 — — — —

Cheshire 0.063 0 1 812 6.5 20 — — — —

Coos 0.068 1 2 996 NA NA NA NA NA NA

Grafton 0.057 — — — 5.8 15 — — — —

Hillsborough 0.067 6 14 12,484 4.6 12 — — — —

Merrimack 0.063 1 2 1,662 NA NA NA NA NA NA

Rockingham 0.066 3 8 6,867 5.8 14 — — — —

New Jersey 0.077 129 370 328,192 10.3 25 — — — —

Atlantic 0.064 3 8 5,352 7.3 16 — — — —

Bergen 0.074 19 40 51,183 8.5 22 — — — —

Camden 0.077 14 57 35,311 10.3 25 — — — —

Cumberland 0.066 2 8 4,200 NA NA NA NA NA NA

Essex 0.068 8 36 26,047 8.6 20 — — — —

Gloucester 0.074 8 18 16,887 NA NA NA NA NA NA

Hudson 0.070 7 28 28,654 8.4 21 — — — —

Hunterdon 0.072 2 4 6,050 NA NA NA NA NA NA

Mercer 0.073 7 27 19,491 7.7 20 — — — —


Monmouth 0.068 10 23 20,668 NA NA NA NA NA NA

Morris 0.069 7 12 17,890 6.4 16 — — — —

Ocean 0.073 19 43 27,547 6.9 18 — — — —

Passaic 0.068 6 23 16,803 8.0 19 — — — —

Page 48 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Union NA NA NA NA 9.7 23 — — — —

Warren 0.065 1 2 1,996 8.6 22 — — — —

New Mexico 0.072 22 41 55,268 9.0 27 1 0 1 765

Bernalillo 0.067 10 16 24,175 7.2 18 — — — —

Dona Ana 0.072 5 11 13,185 9.0 27 1 0 1 765

Eddy 0.068 1 2 2,216 NA NA NA NA NA

Lea 0.067 1 2 2,522 7.5 15 — — — —

Rio Arriba 0.065 0 1 945 NA NA NA NA NA NA

Sandoval 0.065 2 3 3,692 NA NA NA NA NA NA

San Juan 0.068 1 2 4,499 NA NA NA NA NA NA

Santa Fe 0.063 1 2 2,097 NA NA NA NA NA NA

Valencia 0.065 1 2 1,936 NA NA NA NA NA NA

New York 0.076 181 625 533,594 9.7 23 — — — —

Albany 0.064 2 5 5,652 7.0 18 — — — —

Bronx 0.070 18 168 62,387 8.6 21 — — — —

Chautauqua 0.068 3 4 4,500 6.6 15 — — — —

Dutchess 0.067 4 7 8,316 NA NA NA NA NA NA

Erie 0.070 20 35 38,422 7.8 18 — — — —

Essex 0.065 1 1 729 3.9 11 — — — —

Hamilton 0.062 0 0 31 NA NA NA NA NA NA

Herkimer 0.063 0 1 717 NA NA NA NA NA NA

Kings NA NA NA NA 8.2 20 — — — —

Monroe 0.066 8 15 17,977 7.0 17 — — — —

New York 0.070 17 85 64,563 9.7 23 — — — —

Niagara 0.066 2 5 5,086 NA NA NA NA NA NA

Onondaga 0.064 4 6 7,723 5.5 14 — — — —

Orange 0.065 3 8 7,493 6.6 16 — — — —

Oswego 0.061 0 1 573 NA NA NA NA NA NA

Putnam 0.070 1 3 3,891 NA NA NA NA NA NA

Queens 0.074 35 118 123,241 7.3 19 — — — —

Richmond 0.076 13 37 31,776 7.7 19 — — — —

Rockland 0.072 6 12 16,205 NA NA NA NA NA NA

Saratoga 0.062 1 1 1,749 NA NA NA NA NA NA

Steuben 0.059 — — — 5.0 12 — — — —

Suffolk 0.076 24 62 79,433 6.9 17 — — — —

Tompkins 0.062 0 0 815 NA NA NA NA NA NA

Wayne 0.064 1 1 1,393 NA NA NA NA NA NA

Westchester 0.073 18 49 50,921 NA NA NA NA NA NA

Page 49 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

North Carolina 0.070 49 126 142,661 8.8 27 1 0 2 730

Alexander 0.064 0 1 679 NA NA NA NA NA NA

Avery 0.061 0 0 97 NA NA NA NA NA NA

Buncombe 0.062 1 3 2,296 7.4 23 — — — —

Caldwell 0.064 1 2 1,574 NA NA NA NA NA NA

Caswell 0.061 0 0 84 NA NA NA NA NA NA

Catawba NA NA NA NA 8.7 20 — — — —

Cumberland 0.063 2 4 4,675 8.3 17 — — — —

Davidson NA NA NA NA 8.4 19 — — — —

Durham 0.061 1 2 1,753 8.8 19 — — — —

Edgecombe 0.062 0 1 565 NA NA NA NA NA NA

Forsyth 0.067 6 13 12,555 7.6 16 — — — —

Graham 0.063 0 0 126 NA NA NA NA NA NA

Granville 0.064 1 1 1,060 NA NA NA NA NA NA

Guilford 0.065 5 12 12,549 8.2 16 — — — —

Haywood 0.064 1 2 1,156 NA NA NA NA NA NA

Jackson NA NA NA NA 7.8 27 1 0 2 730

Johnston 0.063 1 2 2,642 7.4 15 — — — —

Lee 0.061 0 0 242 NA NA NA NA NA NA

Lenoir 0.062 0 1 469 NA NA NA NA NA NA

Lincoln 0.067 1 3 2,634 NA NA NA NA NA NA

Macon 0.061 0 0 140 NA NA NA NA NA NA

Martin 0.060 — — — NA NA NA NA NA NA

Mecklenburg 0.070 13 42 52,218 8.7 18 — — — —

Mitchell NA NA NA NA 7.5 20 — — — —

Montgomery NA NA NA NA 6.5 15 — — — —

New Hanover 0.058 — — — 5.7 14 — — — —

Person 0.061 0 0 213 NA NA NA NA NA NA

Pitt 0.062 1 2 2,051 6.9 14 — — — —

Rockingham 0.065 2 2 2,119 NA NA NA NA NA NA

Rowan 0.064 2 3 2,777 NA NA NA NA NA NA

Swain 0.060 — — — 8.1 25 — — — —

Union 0.067 3 7 7,864 NA NA NA NA NA NA

Wake 0.066 7 25 30,121 8.8 18 — — — —

North Dakota 0.060 — — — 5.8 24 — — — —

Billings 0.060 — — — NA NA NA NA NA NA

Burke 0.059 — — — 4.3 24 — — — —

Burleigh NA NA NA NA 5.4 21 — — — —

Cass 0.057 — — — NA NA NA NA NA NA

Dunn 0.058 — — — 5.8 0 — — — —

McKenzie 0.058 — — — 3.7 20 — — — —

Page 50 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Mercer 0.057 — — — NA NA NA NA NA NA

Oliver 0.060 — — — 4.9 18 — — — —

Williams 0.057 — — — 4.1 23 — — — —

Ohio 0.074 167 354 343,967 11.7 25 75 20 96 42,208

Allen 0.067 2 4 3,157 8.3 18 — — — —

Ashtabula 0.070 3 5 4,280 NA NA NA NA NA NA

Athens NA NA NA NA 6.7 14 — — — —

Butler 0.071 8 19 19,343 11.1 23 4 1 6 2,824

Clark 0.070 4 7 5,602 8.5 19 — — — —

Clermont 0.070 4 10 9,616 NA NA NA NA NA NA

Clinton 0.070 1 2 1,857 NA NA NA NA NA NA

Cuyahoga 0.070 31 63 54,409 11.7 25 71 19 90 39,384

Delaware 0.065 1 4 4,842 NA NA NA NA NA NA

Fayette 0.067 1 1 896 NA NA NA NA NA NA

Franklin 0.071 25 58 65,053 9.0 20 — — — —

Geauga 0.073 3 7 5,293 NA NA NA NA NA NA

Greene 0.068 3 6 5,969 7.8 16 — — — —

Hamilton 0.073 15 35 43,387 10.1 22 — — — —

Jefferson 0.062 0 1 595 10.7 25 — — — —

Knox 0.066 1 2 1,627 NA NA NA NA NA NA

Lake 0.074 6 12 12,926 7.4 17 — — — —

Lawrence 0.066 1 2 1,625 6.8 16 — — — —

Licking 0.066 2 5 4,717 NA NA NA NA NA NA

Lorain 0.065 4 8 6,731 7.6 18 — — — —

Lucas 0.066 6 12 11,633 9.0 21 — — — —

Madison 0.067 1 1 1,502 NA NA NA NA NA NA

Mahoning 0.059 — — — 9.0 20 — — — —

Medina 0.064 2 4 3,311 8.4 19 — — — —

Miami 0.068 2 4 3,738 NA NA NA NA NA NA

Montgomery 0.070 13 26 22,339 8.9 20 — — — —

Noble 0.065 0 0 285 NA NA NA NA NA NA

Portage 0.062 1 1 1,456 7.8 18 — — — —

Preble 0.067 1 1 1,228 7.7 17 — — — —

Stark 0.069 9 18 14,832 10.1 22 — — — —

Summit 0.064 6 11 9,424 10.2 22 — — — —

Trumbull 0.068 5 9 7,008 NA NA NA NA NA NA

Warren 0.071 5 12 12,014 NA NA NA NA NA NA

Washington 0.064 1 1 1,080 NA NA NA NA NA NA

Wood 0.064 1 2 2,192 NA NA NA NA NA NA

Oklahoma 0.069 26 59 60,457 8.8 20 — — — —

Page 51 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Adair 0.059 — — — NA NA NA NA NA NA

Canadian 0.065 1 3 3,251 NA NA NA NA NA NA

Cherokee 0.059 — — — NA NA NA NA NA NA

Cleveland 0.066 2 5 6,887 7.9 17 — — — —

Comanche 0.064 1 2 2,388 7.1 15 — — — —

Creek 0.063 1 1 904 NA NA NA NA NA NA

Dewey 0.065 0 0 108 NA NA NA NA NA NA

Kay 0.062 0 1 399 NA NA NA NA NA NA

McClain 0.066 1 1 1,124 NA NA NA NA NA NA

Mayes 0.062 0 0 390 NA NA NA NA NA NA

Oklahoma 0.069 15 33 32,762 8.1 18 — — — —

Ottawa 0.056 — — — NA NA NA NA NA NA

Pittsburg 0.060 — — — 7.7 18 — — — —

Sequoyah 0.059 — — — 8.1 17 — — — —

Tulsa 0.064 6 13 12,244 8.8 20 — — — —

Oregon 0.072 22 34 52,079 11.6 59 141 34 156 81,282

Clackamas 0.072 7 10 16,558 NA NA NA NA NA NA


Crook NA NA NA NA 9.2 41 2 1 2 1,072

Harney NA NA NA NA 9.2 34 0 0 0 128

Jackson 0.065 3 4 4,140 11.6 59 42 10 46 21,793

Josephine NA NA NA NA 10.0 50 19 6 17 7,431

Klamath NA NA NA NA 9.3 36 4 1 5 2,207

Lake NA NA NA NA 8.6 37 1 0 1 312

Lane 0.066 4 5 7,348 9.5 52 66 14 74 41,559

Marion 0.069 4 7 10,551 NA NA NA NA NA NA

Multnomah 0.060 — — — 6.9 25 — — — —

Umatilla 0.068 1 2 2,732 NA NA NA NA NA NA

Washington 0.065 3 6 10,750 7.4 28 6 1 11 6,780

Pennsylvania 0.080 206 532 462,177 13.0 37 199 56 286 113,597

Adams 0.066 2 4 2,676 8.3 20 — — — —

Allegheny 0.070 32 71 54,105 13.0 37 184 52 259 103,967

Armstrong 0.069 2 4 2,600 10.4 21 — — — —

Beaver 0.069 5 9 6,494 9.5 21 — — — —

Berks 0.070 7 21 17,372 9.1 26 3 1 6 2,157

Blair 0.064 1 3 2,216 9.2 23 — — — —

Bradford 0.057 — — — NA NA NA NA NA NA

Bucks 0.080 15 40 40,010 NA NA NA NA NA NA

Cambria 0.063 1 2 1,638 10.8 25 — — — —

Page 52 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Centre 0.065 1 4 3,821 8.0 20 — — — —

Chester 0.073 11 34 28,535 10.1 24 — — — —

Clearfield 0.066 1 3 2,049 NA NA NA NA NA NA

Cumberland NA NA NA NA 8.7 25 — — — —

Dauphin 0.066 3 9 7,404 9.5 26 3 1 5 2,044

Delaware 0.071 13 31 26,651 10.3 24 — — — —

Elk 0.066 0 1 728 NA NA NA NA NA NA

Erie 0.065 3 8 6,213 8.3 19 — — — —

Franklin 0.059 — — — NA NA NA NA NA NA

Greene 0.068 1 2 1,225 NA NA NA NA NA NA

Indiana 0.070 2 5 3,724 NA NA NA NA NA NA

Lackawanna 0.067 4 8 6,140 9.1 20 — — — —

Lancaster 0.070 10 28 22,693 10.8 28 7 1 12 4,205

Lawrence 0.066 2 3 2,319 NA NA NA NA NA NA

Lebanon 0.069 3 7 5,243 10.1 30 2 1 4 1,225

Lehigh 0.070 6 18 14,638 NA NA NA NA NA NA

Luzerne 0.064 3 7 5,196 NA NA NA NA NA NA

Lycoming 0.064 1 3 2,005 NA NA NA NA NA NA

Mercer 0.068 3 5 3,829 9.8 22 — — — —

Monroe 0.067 2 6 4,862 7.1 18 — — — —

Montgomery 0.072 17 49 39,320 NA NA NA NA NA NA

Northampton 0.070 6 16 12,301 9.0 24 — — — —

Philadelphia 0.078 30 88 99,488 10.6 24 — — — —

Tioga* 0.064 1 NA NA 8.5 17 — — — —

Washington 0.068 3 7 6,456 9.4 20 — — — —

Westmoreland 0.067 7 15 10,432 9.4 20 — — — —

York 0.070 9 24 19,796 9.6 23 — — — —

Rhode Island 0.072 15 38 35,750 9.1 20 — — — —

Kent 0.072 4 8 6,735 4.8 13 — — — —

Providence 0.070 10 27 23,869 9.1 20 — — — —

Washington 0.071 2 4 5,146 5.7 15 — — — —

South Carolina 0.066 15 27 33,905 9.1 23 — — — —

Aiken 0.059 — — — NA NA NA NA NA NA

Anderson 0.059 — — — NA NA NA NA NA NA

Berkeley 0.057 — — — NA NA NA NA NA NA

Charleston 0.059 — — — 7.1 0 — — — —

Chesterfield 0.060 — — — 7.2 15 — — — —

Colleton 0.056 — — — NA NA NA NA NA NA

Darlington 0.061 0 0 372 NA NA NA NA NA NA

Page 53 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Edgefield 0.061 0 0 134 8.3 18 — — — —

Greenville 0.065 5 7 11,607 9.1 23 — — — —

Lexington NA NA NA NA 8.8 19 — — — —

Oconee 0.063 1 1 906 NA NA NA NA NA NA

Pickens 0.063 1 2 1,826 NA NA NA NA NA NA

Richland 0.064 3 5 8,222 8.1 17 — — — —

Spartanburg 0.066 5 9 8,416 8.3 16 — — — —

York 0.062 1 1 2,422 NA NA NA NA NA NA

South Dakota 0.064 1 3 3,722 7.7 23 — — — —

Brookings 0.062 0 0 274 5.0 15 — — — —

Brown NA NA NA NA 5.8 14 — — — —

Codington NA NA NA NA 6.5 16 — — — —

Custer 0.061 0 0 34 3.7 16 — — — —

Hughes NA NA NA NA 4.1 13 — — — —

Jackson 0.061 0 0 15 3.5 15 — — — —

Meade 0.054 — — — NA NA NA NA NA NA

Minnehaha 0.064 1 3 3,266 6.9 17 — — — —

Pennington NA NA NA NA 7.7 23 — — — —

Union 0.062 0 0 133 6.8 17 — — — —

Tennessee 0.067 45 176 97,358 10.0 34 7 2 15 4,924

Anderson 0.064 1 3 1,343 NA NA NA NA NA NA

Blount 0.067 3 10 4,143 8.0 24 — — — —

Claiborne* 0.062 0 NA NA NA NA NA NA NA NA

Davidson 0.066 6 27 19,182 8.9 18 — — — —

DeKalb 0.061 0 0 53 NA NA NA NA NA NA

Dyer NA NA NA NA 6.9 14 — — — —

Hamilton 0.067 6 24 11,253 8.7 18 — — — —


Knox 0.067 7 27 14,429 10.0 34 7 2 15 4,924

Lawrence NA NA NA NA 6.7 14 — — — —

Madison NA NA NA NA 6.9 14 — — — —

McMinn NA NA NA NA 8.3 20 — — — —

Montgomery NA NA NA NA 8.1 16 — — — —

Putnam NA NA NA NA 7.3 16 — — — —

Roane NA NA NA NA 8.1 17 — — — —

Sevier 0.067 2 8 3,312 NA NA NA NA NA NA

Shelby 0.067 11 48 30,603 7.6 15 — — — —

Sullivan 0.066 3 12 4,266 7.5 16 — — — —

Sumner 0.066 2 9 5,074 7.9 16 — — — —

Page 54 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Williamson 0.060 — — — NA NA NA NA NA NA

Wilson 0.063 1 3 1,959 NA NA NA NA NA NA

Texas 0.081 314 936 1,155,163 10.7 26 5 1 15 5,971

Bell 0.069 4 11 13,354 NA NA NA NA NA NA

Bexar 0.074 33 93 106,929 8.4 20 — — — —

Brazoria 0.077 7 18 21,827 NA NA NA NA NA NA

Brewster 0.062 0 0 70 NA NA NA NA NA NA

Cameron 0.057 — — — NA NA NA NA NA NA

Collin 0.074 14 52 63,260 NA NA NA NA NA NA

Dallas 0.074 41 119 147,102 8.9 18 — — — —

Denton 0.079 17 56 72,371 NA NA NA NA NA NA

Ellis 0.065 1 3 3,849 8.7 18 — — — —

El Paso 0.071 13 42 46,473 8.9 23 — — — —

Galveston 0.077 9 18 19,753 6.7 22 — — — —

Gregg 0.065 1 3 2,719 NA NA NA NA NA NA

Harris 0.081 92 305 405,650 10.7 22 — — — —

Harrison 0.061 0 0 303 8.6 17 — — — —

Hidalgo 0.055 — — — 10.2 26 5 1 15 5,971

Hood 0.067 1 2 1,617 NA NA NA NA NA NA

Hunt 0.062 0 1 705 NA NA NA NA NA NA


Johnson 0.073 4 9 9,562 NA NA NA NA NA NA

Kaufman 0.061 0 0 370 NA NA NA NA NA NA

Montgomery 0.074 10 26 28,469 NA NA NA NA NA NA

Navarro 0.063 0 1 668 NA NA NA NA NA NA

Nueces 0.062 1 3 2,856 9.3 24 — — — —

Orange 0.060 — — — NA NA NA NA NA NA

Parker 0.070 3 6 5,851 NA NA NA NA NA NA

Polk 0.060 — — — NA NA NA NA NA NA

Randall 0.065 2 3 3,277 NA NA NA NA NA NA

Rockwall 0.066 1 2 2,418 NA NA NA NA NA NA

Smith 0.064 2 4 3,974 NA NA NA NA NA NA

Tarrant 0.075 41 115 139,016 8.7 17 — — — —

Travis 0.069 10 34 44,509 9.6 20 — — — —

Victoria 0.065 1 2 1,755 NA NA NA NA NA NA

Utah 0.088 48 71 198,811 8.8 37 64 9 99 73,216

Box Elder 0.067 1 1 1,978 7.2 0 — — — —

Cache NA NA NA NA 7.5 34 2 0 3 3,165

Carbon 0.067 0 0 785 NA NA NA NA NA NA

Page 55 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Davis 0.075 6 7 27,345 7.8 29 4 0 6 5,012

Duchesne 0.077 1 1 1,452 6.1 24 — — — —

Salt Lake 0.078 25 42 100,593 8.7 37 46 7 74 51,462

San Juan 0.064 0 0 327 NA NA NA NA NA NA

Tooele 0.073 1 2 4,188 NA NA NA NA NA NA

Uintah 0.088 1 2 3,802 NA NA NA NA NA NA

Utah 0.072 6 7 37,268 8.2 31 6 1 9 8,547

Washington 0.066 2 2 4,437 4.9 13 — — — —

Weber 0.073 5 6 16,635 8.8 33 6 1 7 5,030

Vermont 0.065 1 2 1,887 7.5 22 — — — —

Bennington 0.065 0 1 635 5.5 14 — — — —

Chittenden 0.062 0 1 1,253 5.6 14 — — — —

Rutland NA NA NA NA 7.5 22 — — — —

Virginia 0.071 29 100 117,271 8.1 19 — — — —

Albemarle 0.060 — — — 6.9 15 — — — —

Arlington 0.071 3 9 11,767 8.1 18 — — — —

Bristol City NA NA NA NA 7.6 18 — — — —

Caroline 0.061 0 0 172 NA NA NA NA NA NA

Charles 0.061 0 0 35 7.0 15 — — — —

Chesterfield 0.062 1 3 3,156 NA NA NA NA NA NA

Fairfax 0.071 13 50 57,444 7.2 17 — — — —

Fauquier 0.058 — — — NA NA NA NA NA NA

Frederick 0.062 0 1 940 8.0 19 — — — —

Giles 0.062 0 0 155 NA NA NA NA NA NA

Hampton City 0.065 1 3 3,335 6.6 15 — — — —

Hanover 0.063 0 1 1,246 NA NA NA NA NA NA

Henrico 0.065 3 7 7,539 7.4 16 — — — —

Loudoun 0.068 3 12 15,057 7.8 17 — — — —

Lynchburg City NA NA NA NA 6.8 14 — — — —

Madison 0.063 0 0 195 NA NA NA NA NA NA

Norfolk City NA NA NA NA 7.1 14 — — — —

Prince Edward 0.058 — — — NA NA NA NA NA NA

Prince William 0.066 3 10 13,784 NA NA NA NA NA NA

Roanoke 0.061 0 1 415 7.0 16 — — — —

Rockbridge 0.057 — — — NA NA NA NA NA NA

Rockingham 0.060 — — — 7.5 18 — — — —

Salem City NA NA NA NA 7.7 16 — — — —

Stafford 0.062 0 1 1,522 NA NA NA NA NA NA

Suffolk City 0.061 0 0 510 NA NA NA NA NA NA

Page 56 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour Virginia Beach

City NA NA NA NA 7.1 15 — — — —

Wythe 0.060 — — — NA NA NA NA NA NA

Washington 0.076 40 74 130,722 9.5 41 90 23 147 86,691

Clallam 0.052 — — — NA NA NA NA NA NA

Clark 0.063 2 4 5,248 NA NA NA NA NA NA

King 0.076 32 60 109,124 8.7 27 52 12 86 54,550

Kitsap NA NA NA NA 4.7 16 — — — —

Kittitas NA NA NA NA 7.6 NA — — — —

Pierce 0.063 3 6 11,137 7.4 31 10 3 15 8,264

Skagit 0.046 — — — 5.9 13 — — — —

Snohomish NA NA NA NA 7.4 34 14 4 22 13,065

Spokane 0.062 2 3 4,188 NA NA NA NA NA NA

Thurston 0.061 0 1 1,026 NA NA NA NA NA NA

Whatcom 0.047 — — — 5.5 20 — — — —

Yakima NA NA NA NA 9.5 41 14 3 23 10,812

West Virginia 0.067 8 26 13,896 9.8 24 — — — —

Berkeley 0.062 1 1 1,117 9.3 24 — — — —

Brooke NA NA NA NA 9.8 22 — — — —

Cabell 0.064 1 4 1,752 8.2 18 — — — —

Gilmer 0.057 — — — NA NA NA NA NA NA

Greenbrier 0.060 — — — NA NA NA NA NA NA

Hancock 0.066 0 1 741 8.7 20 — — — —

Harrison NA NA NA NA 8.0 17 — — — —

Kanawha 0.067 3 10 5,254 8.2 17 — — — —

Marshall NA NA NA NA 9.6 22 — — — —

Monongalia 0.063 1 2 1,690 7.6 18 — — — —

Ohio 0.067 1 4 1,322 8.8 18 — — — —

Tucker 0.062 0 0 54 NA NA NA NA NA NA

Wood 0.065 1 3 1,967 8.5 19 — — — —

Wisconsin 0.080 61 131 141,924 8.3 22 — — — —

Ashland 0.058 — — — 4.1 12 — — — —

Brown 0.065 2 3 5,512 7.0 19 — — — —

Columbia 0.065 1 1 1,285 NA NA NA NA NA NA

Dane 0.065 4 6 12,197 8.0 21 — — — —

Dodge 0.065 1 2 1,961 6.8 18 — — — —

Door 0.073 1 1 1,194 NA NA NA NA NA NA

Eau Claire 0.061 0 0 294 6.6 17 — — — —

Fond du Lac 0.064 1 1 1,717 NA NA NA NA NA NA

Page 57 of 86

O3 PM2.5

State [County]2017

Design Value

Annual Mortality

Annual Morbidity

AnnualImpacted

Days

2017 Design Value

AnnualMortality

AnnualLung

Cancer Incidence

AnnualMorbidity

AnnualImpacted

Days

Annual 24-hour

Forest 0.062 0 0 65 4.6 14 — — — —

Grant NA NA NA NA 7.2 20 — — — —


Kenosha 0.078 6 14 13,156 7.4 19 — — — —

Kewaunee 0.069 0 0 740 NA NA NA NA NA NA

La Crosse 0.062 0 0 1,019 6.7 18 — — — —

Manitowoc 0.074 2 3 4,190 NA NA NA NA NA NA

Marathon 0.063 1 1 1,769 NA NA NA NA NA NA

Milwaukee 0.071 18 60 47,047 8.3 22 — — — —

Outagamie 0.065 2 2 4,161 6.6 19 — — — —

Ozaukee 0.073 2 3 4,565 6.8 19 — — — —

Racine 0.074 6 11 10,922 NA NA NA NA NA NA

Rock 0.066 2 5 4,506 NA NA NA NA NA NA

Sauk 0.063 0 1 903 6.6 17 — — — —

Sheboygan 0.080 5 6 9,498 NA NA NA NA NA NA

Taylor 0.060 — — — 5.5 15 — — — —

Vilas 0.061 0 0 88 4.5 15 — — — —

Walworth 0.068 2 3 3,734 NA NA NA NA NA NA

Waukesha 0.065 4 5 8,742 8.3 21 — — — —

Wyoming 0.067 2 4 6,106 7.3 24 — — — —

Albany 0.064 0 1 842 4.3 13 — — — —

Campbell 0.063 0 0 792 4.8 19 — — — —

Carbon 0.060 — — — NA NA NA NA NA NA

Converse 0.061 0 0 72 NA NA NA NA NA NA

Fremont 0.062 0 0 362 6.8 23 — — — —

Laramie 0.063 1 1 1,458 4.2 15 — — — —

Natrona 0.061 0 0 446 4.9 16 — — — —

Park NA NA NA NA 4.3 23 — — — —

Sheridan NA NA NA NA 7.3 24 — — — —

Sublette 0.063 0 0 159 5.1 16 — — — —

Sweetwater 0.067 0 1 1,564 5.1 19 — — — —

Teton 0.061 0 0 116 4.6 15 — — — —

Uinta 0.062 0 0 263 NA NA NA NA NA NA

Weston 0.061 0 0 33 NA NA NA NA NA NA

* O3 morbidity and impacted days data unavailable for this county. ** PM2.5 impacted days data unavailable for this county.

Page 58 of 86

TABLE E5: Rank and air pollution-related deaths attributable to PM2.5 from 2010-2017 in U.S. cities.

Cities listed are based on US metropolitan statistical areas and metropolitan divisions. A rank of 1 indicates that this city suffers the highest number of excess air pollution-related health impacts associated with PM2.5. Cities that met the ATS recommendation for PM2.5 were not ranked, as indicated by a dash. It is possible that cities with no deaths in a given year still have a ranking due to rounding methods. NA indicates no data was available for this city in the given year.

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Akron, OH 22 86 21 56 26 38 - 0 - 0 38 9 - 0 - 0

Albany, NY - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Albany, GA 78 8 NA NA NA NA 70 1 - 0 - 0 - 0 - 0

Albuquerque, NM - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Alexandria, LA - 0 - 0 - 0 - 0 - 0 - 0 NA NA NA NA

Allentown, PA-NJ 37 31 24 45 23 43 22 27 - 0 51 4 - 0 - 0

Altoona, PA NA NA NA NA NA NA 43 10 25 7 47 5 - 0 - 0

Anaheim, CA 14 131 22 51 29 29 - 0 - 0 - 0 NA NA - 0

Ann Arbor, MI 127 1 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Appleton, WI 110 3 99 2 91 1 - 0 - 0 - 0 - 0 - 0

Asheville, NC - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Atlanta, GA 18 104 30 33 11 112 69 1 - 0 - 0 - 0 - 0

Atlantic City, NJ - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Austin, TX - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Bakersfield, CA 5 369 4 274 7 185 4 262 3 320 3 401 3 309 3 252

Baltimore, MD 20 90 35 23 41 20 45 9 - 0 54 4 - 0 - 0

Bangor, ME NA NA NA NA NA NA - 0 - 0 - 0 - 0 - 0

Baton Rouge, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Bay City, MI 138 1 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Beckley, WV - 0 - 0 - 0 - 0 NA NA NA NA NA NA NA NA

Bellingham, WA NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

Birmingham, AL 16 119 15 83 13 89 18 41 22 14 - 0 26 9 - 0

Bismarck, ND - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Bloomington, IL - 0 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Bloomington, IN NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Boise City, ID - 0 NA NA NA NA NA NA NA NA NA NA NA NA 22 19

Boston, MA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Page 59 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Boulder, CO - 0 - 0 NA NA NA NA NA NA - 0 - 0 - 0

Bowling Green, KY 116 3 - 0 NA NA NA NA NA NA - 0 - 0 - 0

Bremerton, WA NA NA NA NA NA NA NA NA NA NA NA NA NA NA - 0

Bridgeport, CT 70 11 70 6 - 0 - 0 - 0 - 0 - 0 - 0

Bristol City, VA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Brownsville, TX - 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Brunswick, GA - 0 NA NA NA NA NA NA NA NA - 0 - 0 - 0

Buffalo, NY 86 7 77 5 - 0 - 0 - 0 - 0 - 0 - 0

Burlington, VT - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Burlington, NC - 0 - 0 - 0 - 0 - 0 NA NA NA NA NA NA

Cambridge, MA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Camden, NJ - 0 - 0 - 0 - 0 - 0 57 3 - 0 - 0

Canton, OH NA NA 20 60 22 50 23 27 19 18 28 17 - 0 - 0

Cape Coral, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Carson City, NV NA NA NA NA NA NA NA NA NA NA 60 3 - 0 - 0

Casper, WY NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Cedar Rapids, IA 117 3 101 2 87 2 - 0 - 0 - 0 - 0 - 0

Champaign, IL - 0 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Charleston, SC - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Charleston, WV 35 34 36 23 46 14 - 0 - 0 - 0 - 0 - 0

Charlotte, NC-SC 33 35 60 9 - 0 - 0 - 0 - 0 - 0 - 0

Chattanooga, TN-GA 61 13 75 5 51 11 - 0 - 0 - 0 - 0 - 0

Cheyenne, WY - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Chicago, IL 4 505 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Chico, CA 40 30 53 13 88 1 56 5 - 0 58 3 39 2 43 3

Cincinnati, OH-KY-IN 9 226 7 185 10 147 10 116 14 39 33 13 - 0 38 4

Clarksville, TN-KY NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Cleveland, OH 8 245 8 188 6 184 7 138 6 116 7 128 7 111 8 71

Colorado Springs, CO - 0 - 0 NA NA NA NA NA NA - 0 NA NA - 0

Columbia, SC 71 11 81 5 85 2 - 0 - 0 - 0 - 0 - 0

Columbus, GA-AL 34 35 83 4 38 22 68 1 - 0 - 0 - 0 50 1

Columbus, IN NA NA NA NA NA NA NA NA NA NA NA NA NA NA - 0

Page 60 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Columbus, OH 21 85 18 70 19 52 - 0 - 0 - 0 - 0 - 0

Corpus Christi, TX - 0 - 0 - 0 53 6 - 0 66 2 - 0 - 0

Dallas, TX - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Daphne, AL NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Davenport, IA-IL 56 18 54 12 75 4 71 1 - 0 64 2 - 0 - 0

Dayton, OH 24 77 19 67 20 51 - 0 - 0 - 0 - 0 - 0

Decatur, AL - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Decatur, IL 92 5 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Deltona, FL NA NA NA NA - 0 - 0 NA NA - 0 - 0 - 0

Denver, CO - 0 - 0 NA NA NA NA NA NA - 0 - 0 - 0

Des Moines, IA 104 4 92 3 - 0 - 0 - 0 - 0 - 0 - 0

Detroit, MI 12 169 14 93 16 75 15 48 12 57 14 58 13 49 15 41

Dothan, AL - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Dover, DE - 0 - 0 - 0 - 0 - 0 - 0 NA NA NA NA

Duluth, MN-WI - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Durham, NC - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

East Stroudsburg, PA NA NA NA NA NA NA - 0 - 0 - 0 - 0 - 0

Eau Claire, WI NA NA NA NA NA NA NA NA - 0 - 0 - 0 - 0

El Centro, CA - 0 114 1 42 20 25 25 17 25 26 19 20 18 27 10

El Paso, TX - 0 74 6 43 20 26 25 - 0 36 11 - 0 - 0

Elgin, IL 106 4 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Elizabethtown, KY 109 3 117 1 NA NA NA NA NA NA - 0 - 0 - 0

Elkhart, IN 67 11 65 8 77 4 72 0 - 0 63 2 40 2 - 0

Erie, PA 105 4 98 3 60 7 40 12 26 7 - 0 - 0 - 0

Eugene, OR 65 12 45 16 52 12 34 16 - 0 30 15 27 9 11 66

Evansville, IN-KY 44 24 38 22 45 15 58 4 - 0 - 0 - 0 - 0

Fargo, ND-MN - 0 - 0 - 0 - 0 - 0 - 0 NA NA NA NA

Farmington, NM NA NA - 0 - 0 - 0 - 0 - 0 NA NA NA NA

Fayetteville, AR-MO - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Fayetteville, NC 125 2 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Flagstaff, AZ - 0 - 0 - 0 - 0 NA NA NA NA NA NA NA NA

Flint, MI 123 2 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Page 61 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Florence, AL - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Florence, SC NA NA - 0 - 0 - 0 - 0 - 0 - 0 NA NA

Fort Collins, CO - 0 - 0 NA NA NA NA NA NA - 0 NA NA - 0

Fort Lauderdale, FL - 0 NA NA - 0 NA NA NA NA NA NA - 0 - 0

Fort Smith, AR-OK 139 1 NA NA NA NA - 0 - 0 - 0 - 0 - 0

Fort Wayne, IN 72 10 103 2 103 0 - 0 - 0 - 0 - 0 - 0

Fort Worth, TX - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Fresno, CA 10 220 5 253 8 174 5 249 5 182 4 233 5 179 5 177

Gadsden, AL 103 4 110 1 - 0 - 0 - 0 - 0 - 0 - 0

Gainesville, FL - 0 NA NA - 0 - 0 NA NA NA NA NA NA - 0

Gainesville, GA 118 3 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Gary, IN 30 48 23 47 24 41 30 18 21 15 42 6 - 0 - 0

Gettysburg, PA 108 3 78 5 73 4 63 2 - 0 - 0 - 0 - 0

Goldsboro, NC - 0 - 0 - 0 - 0 - 0 NA NA NA NA NA NA

Grand Island, NE - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Grand Junction, CO 101 4 87 4 NA NA NA NA NA NA 67 1 - 0 - 0

Grand Rapids, MI 107 4 96 3 - 0 - 0 - 0 - 0 - 0 - 0

Grants Pass, OR 122 2 106 2 - 0 55 4 - 0 50 5 - 0 21 19

Greeley, CO - 0 - 0 NA NA NA NA NA NA 65 2 - 0 41 3

Green Bay, WI 89 6 82 4 82 2 - 0 - 0 - 0 - 0 - 0

Greensboro, NC - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Greenville, SC 81 8 71 6 - 0 - 0 - 0 - 0 - 0 - 0

Greenville, NC NA NA - 0 - 0 - 0 - 0 - 0 - 0 - 0

Gulfport, MS - 0 - 0 NA NA NA NA NA NA - 0 NA NA - 0

Hagerstown, MD-WV 64 12 68 6 58 8 61 3 - 0 59 2 42 1 - 0

Hammond, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Hanford, CA 39 33 39 20 30 29 20 36 16 32 13 68 11 67 9 70

Harrisburg, PA 32 37 32 25 37 22 27 23 - 0 53 4 30 6 42 3

Hartford, CT - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Hattiesburg, MS 97 5 95 3 NA NA NA NA NA NA - 0 NA NA - 0

Hickory, NC 102 4 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Homosassa Springs, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 NA NA

Page 62 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Hot Springs, AR - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Houma, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Houston, TX 6 279 6 204 9 166 9 128 9 97 10 105 14 41 - 0

Huntington, WV-KY-OH 45 22 56 10 63 6 - 0 - 0 - 0 - 0 - 0

Huntsville, AL 100 4 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Indianapolis, IN 15 122 13 101 14 83 14 47 13 39 17 42 15 30 - 0

Iowa City, IA 137 1 118 1 97 1 - 0 - 0 - 0 - 0 - 0

Jackson, MS 94 5 108 1 - 0 NA NA NA NA NA NA NA NA - 0

Jackson, TN NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

Jacksonville, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 NA NA

Johnstown, PA 53 19 42 17 44 16 35 16 27 7 39 9 41 1 - 0

Kalamazoo, MI 132 1 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Kansas City, MO-KS 77 9 76 5 102 1 - 0 - 0 - 0 - 0 - 0

Kingsport, TN-VA NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

Knoxville, TN NA NA NA NA NA NA NA NA NA NA - 0 22 15 31 7

Kokomo, IN 95 5 88 4 NA NA NA NA NA NA NA NA NA NA - 0

La Crosse, WI-MN 124 2 113 1 - 0 - 0 - 0 - 0 - 0 - 0

Lafayette, IN 111 3 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Lafayette, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Lake Charles, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Lakeland, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Lancaster, PA 28 52 29 35 25 39 19 38 18 19 25 19 10 67 33 7

Lansing, MI - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Las Cruces, NM 91 6 59 10 34 24 - 0 - 0 - 0 - 0 49 1

Las Vegas, NV - 0 - 0 - 0 - 0 - 0 31 17 - 0 - 0

Lawton, OK NA NA NA NA NA NA NA NA NA NA NA NA - 0 - 0

Lebanon, PA NA NA NA NA NA NA 37 14 20 16 44 6 32 5 44 2

Lewiston, ME NA NA NA NA NA NA - 0 - 0 NA NA - 0 - 0

Lexington, KY 69 11 91 3 - 0 - 0 - 0 - 0 - 0 - 0

Lima, OH NA NA NA NA NA NA NA NA NA NA NA NA - 0 - 0

Lincoln, NE - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Little Rock, AR 47 22 34 24 32 27 32 17 28 2 - 0 - 0 - 0

Page 63 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Logan, UT-ID 88 8 93 4 86 2 57 4 - 0 56 4 NA NA 45 2

Los Angeles, CA 1 1,389 1 1,212 1 922 1 903 2 558 1 699 1 485 1 877

Lynchburg City, VA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Macon, GA 55 18 33 25 39 21 46 8 - 0 - 0 - 0 - 0

Madera, CA NA NA NA NA 21 52 16 47 15 32 19 33 19 21 23 17

Madison, WI 66 12 84 4 80 3 - 0 - 0 - 0 - 0 - 0

Manchester, NH - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

McAllen, TX - 0 - 0 - 0 NA NA NA NA NA NA - 0 37 5

Medford, OR 96 5 90 4 84 2 31 17 - 0 18 33 24 10 16 42

Memphis, TN-MS-AR 142 0 124 0 100 1 - 0 - 0 - 0 - 0 - 0

Merced, CA 50 20 51 13 27 37 24 27 24 7 21 27 21 15 18 24

Miami, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Michigan City, IN 135 1 - 0 98 1 - 0 - 0 - 0 - 0 - 0

Milwaukee, WI 23 83 28 40 33 24 50 6 - 0 - 0 - 0 - 0

Minneapolis, MN-WI 41 33 37 26 71 6 - 0 - 0 - 0 - 0 - 0

Missoula, MT - 0 - 0 NA NA 62 2 - 0 55 4 37 4 25 13

Mobile, AL - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Modesto, CA 27 58 12 115 12 108 8 134 11 76 11 97 9 72 7 84

Monroe, LA - 0 - 0 - 0 - 0 - 0 NA NA NA NA NA NA

Monroe, MI 131 1 - 0 - 0 NA NA NA NA NA NA - 0 - 0

Montgomery, AL NA NA - 0 89 1 - 0 - 0 - 0 - 0 - 0

Morgantown, WV 121 2 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Mount Vernon, WA NA NA NA NA NA NA NA NA NA NA NA NA NA NA - 0

Muncie, IN 82 7 69 6 83 2 - 0 - 0 - 0 - 0 - 0

Muskegon, MI 141 0 - 0 - 0 NA NA NA NA NA NA NA NA NA NA

Napa, CA NA NA NA NA NA NA NA NA NA NA 52 4 - 0 32 7

Nashville, TN NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

New Haven, CT 60 14 62 8 - 0 - 0 - 0 - 0 - 0 - 0

New Orleans, LA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

New York, NY-NJ 7 262 10 137 18 67 54 4 - 0 29 14 - 0 - 0

Newark, NJ-PA 51 20 49 15 54 10 42 10 - 0 48 5 - 0 - 0

Niles, MI - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Page 64 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

North Port, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Norwich, CT - 0 - 0 - 0 - 0 NA NA NA NA - 0 - 0

Oakland, CA 46 22 50 14 55 10 44 10 - 0 23 21 - 0 13 59

Ogden, UT 59 15 43 18 49 14 33 17 - 0 40 9 34 5 29 10

Oklahoma City, OK - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Omaha, NE-IA - 0 - 0 67 5 - 0 - 0 - 0 - 0 - 0

Orlando, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Owensboro, KY 80 7 61 8 64 6 - 0 - 0 - 0 - 0 - 0

Oxnard, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 35 6

Palm Bay, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Parkersburg, WV 62 13 64 8 70 5 - 0 - 0 - 0 - 0 - 0

Pensacola, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Peoria, IL 126 2 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Philadelphia, PA 11 185 9 136 4 316 13 75 10 94 9 117 8 74 - 0

Phoenix, AZ 29 51 16 80 15 78 6 140 - 0 12 78 16 27 19 23

Pittsburgh, PA 3 595 3 428 3 434 3 255 4 190 5 179 4 194 4 184

Pittsfield, MA 134 1 115 1 - 0 - 0 - 0 - 0 - 0 - 0

Pocatello, ID NA NA - 0 - 0 66 1 - 0 68 1 - 0 46 1

Port St. Lucie, FL - 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Portland, ME NA NA NA NA NA NA - 0 - 0 NA NA NA NA - 0

Portland, OR-WA 98 4 55 10 81 3 29 21 - 0 20 32 - 0 34 6

Prescott, AZ - 0 - 0 - 0 - 0 NA NA NA NA NA NA NA NA

Providence, RI-MA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Provo, UT 76 10 58 10 69 5 36 16 - 0 27 19 35 5 36 6

Pueblo, CO NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

Raleigh, NC - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Rapid City, SD - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Reading, PA 79 8 85 4 72 5 60 3 - 0 41 7 36 4 40 3

Redding, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Reno, NV 63 15 97 3 - 0 - 0 - 0 32 16 31 6 - 0

Richmond, VA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Riverside, CA 2 879 2 759 2 651 2 607 1 553 2 528 2 444 2 698

Page 65 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Roanoke, VA - 0 - 0 - 0 NA NA NA NA NA NA NA NA NA NA

Rochester, MN 129 2 116 1 - 0 - 0 - 0 - 0 - 0 - 0

Rochester, NY - 0 NA NA NA NA NA NA - 0 - 0 - 0 - 0

Rockford, IL - 0 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Rocky Mount, NC - 0 - 0 - 0 - 0 NA NA NA NA NA NA NA NA

Rome, GA 74 10 NA NA 59 7 - 0 - 0 - 0 - 0 NA NA

Sacramento, CA 25 61 27 40 31 28 17 47 - 0 16 44 17 27 17 27

Salem City, VA NA NA - 0 - 0 - 0 - 0 - 0 - 0 - 0

Salinas, CA - 0 - 0 - 0 - 0 - 0 - 0 29 7 48 1

Salisbury, MD-DE - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Salt Lake City, UT 31 48 26 44 35 24 21 34 - 0 15 50 18 25 14 46

San Antonio, TX - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

San Diego, CA 13 155 11 121 5 235 - 0 - 0 - 0 - 0 - 0

San Francisco, CA 85 7 72 6 - 0 - 0 - 0 - 0 - 0 30 9

San Jose, CA 58 16 52 12 47 15 28 22 - 0 22 24 - 0 20 22

San Luis Obispo, CA - 0 - 0 - 0 47 7 23 9 24 19 38 2 - 0

San Rafael, CA NA NA NA NA - 0 - 0 - 0 62 2 - 0 39 4

Santa Cruz, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Santa Fe, NM 143 0 123 0 - 0 - 0 NA NA NA NA NA NA NA NA

Santa Maria, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Santa Rosa, CA 136 1 - 0 - 0 - 0 NA NA NA NA - 0 - 0

Savannah, GA - 0 89 4 68 5 NA NA - 0 - 0 - 0 - 0

Scranton, PA 128 1 - 0 - 0 - 0 NA NA NA NA NA NA - 0

Seattle, WA 87 7 67 7 66 6 49 6 - 0 37 9 28 8 10 66

Shreveport, LA - 0 105 2 48 14 41 11 - 0 - 0 - 0 - 0

Sierra Vista, AZ - 0 - 0 - 0 - 0 - 0 - 0 - 0 NA NA

Silver Spring, MD 112 3 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Sioux City, IA-NE-SD NA NA 112 1 95 1 - 0 - 0 - 0 - 0 - 0

Sioux Falls, SD - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

South Bend, IN-MI 84 7 102 2 93 1 - 0 - 0 - 0 - 0 - 0

Spartanburg, SC NA NA - 0 NA NA - 0 - 0 - 0 - 0 - 0

Spokane, WA NA NA NA NA - 0 51 6 - 0 46 5 NA NA NA NA

Page 66 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

Springfield, IL - 0 NA NA NA NA NA NA NA NA NA NA NA NA - 0

Springfield, MA 90 6 80 5 - 0 - 0 - 0 - 0 - 0 - 0

Springfield, MO - 0 - 0 - 0 - 0 - 0 NA NA NA NA NA NA

Springfield, OH 54 18 44 16 56 9 - 0 - 0 - 0 - 0 - 0

St. Cloud, MN 130 2 120 1 - 0 - 0 - 0 - 0 - 0 - 0

St. George, UT NA NA - 0 - 0 NA NA NA NA NA NA NA NA - 0

St. Joseph, MO-KS 120 3 NA NA NA NA NA NA - 0 - 0 - 0 - 0

St. Louis, MO-IL 17 112 25 44 36 22 59 3 - 0 - 0 - 0 - 0

State College, PA 140 1 121 1 96 1 - 0 - 0 - 0 - 0 - 0

Stockton, CA 26 60 31 26 28 30 12 107 8 100 8 127 12 59 12 61

Syracuse, NY - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Tacoma, WA 49 20 40 16 57 9 38 13 - 0 34 12 25 9 26 10

Tallahassee, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Tampa, FL - 0 NA NA - 0 - 0 NA NA - 0 - 0 - 0

Terre Haute, IN 75 10 57 10 62 7 65 2 - 0 - 0 - 0 - 0

Texarkana, TX-AR 133 1 119 1 101 1 - 0 - 0 - 0 NA NA NA NA

Toledo, OH 57 17 48 15 79 4 - 0 - 0 - 0 - 0 - 0

Topeka, KS - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Trenton, NJ 115 3 104 2 - 0 - 0 - 0 - 0 - 0 - 0

Tucson, AZ - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Tulsa, OK - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Tuscaloosa, AL - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Valdosta, GA - 0 - 0 NA NA NA NA - 0 - 0 - 0 - 0

Vallejo, CA 99 4 94 3 78 4 48 7 - 0 43 6 - 0 28 10

Virginia Beach, VA-NC 93 5 122 1 99 1 - 0 - 0 - 0 - 0 - 0

Visalia, CA 19 102 17 81 17 80 11 119 7 115 6 145 6 116 6 109

Warner Robins, GA 113 3 100 2 - 0 - 0 - 0 - 0 - 0 - 0

Warren, MI 52 19 66 7 - 0 - 0 - 0 35 12 23 12 - 0

Washington, DC-VA-MD-WV 36 34 86 4 53 11 - 0 - 0 - 0 - 0 - 0

Waterloo, IA 119 3 107 2 94 1 - 0 - 0 - 0 - 0 - 0

Weirton, WV-OH 48 22 47 15 50 11 52 5 30 0 70 1 - 0 - 0

Wenatchee, WA NA NA NA NA NA NA NA NA NA NA NA NA - 0 NA NA

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2010 2011 2012 2013 2014 2015 2016 2017City City

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

MortalityCity

RankPM2.5

Mortality

West Palm Beach, FL - 0 - 0 - 0 - 0 NA NA - 0 - 0 - 0

Wheeling, WV-OH 73 10 63 8 61 7 64 2 29 0 - 0 - 0 - 0

Wichita, KS - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Wilmington, DE-MD-NJ 43 24 73 5 74 4 - 0 - 0 61 2 - 0 - 0

Wilmington, NC NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Winston, NC 68 11 111 1 90 1 - 0 - 0 - 0 - 0 - 0

Worcester, MA-CT - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Yakima, WA 83 7 79 5 76 4 - 0 - 0 45 6 33 5 24 14

York, PA 38 30 46 15 40 19 39 12 - 0 49 5 - 0 - 0

Youngstown, OH-PA 42 29 41 17 65 6 - 0 - 0 - 0 - 0 - 0

Yuba City, CA 114 3 109 1 92 1 67 1 - 0 69 1 43 1 47 1

Yuma, AZ NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Page 68 of 86

TABLE E6: Rank and air pollution-related deaths attributable to O3 from 2010-2017 in U.S. cities.

Cities listed are based on US metropolitan statistical areas and metropolitan divisions. A rank of 1 indicates that this city suffers the highest number of excess air pollution-related health impacts associated with O3. Cities that met the ATS recommendation for O3 were not ranked, as indicated by a dash. It is possible that cities with no deaths in a given year still have a ranking due to rounding methods. NA indicates no data was available for this city in the given year.

2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Akron, OH 55 19 55 15 60 21 80 12 152 4 177 2 168 2 97 6

Albany, NY 68 14 96 7 95 10 129 6 137 5 175 2 132 4 141 3

Albuquerque, NM 88 10 76 9 61 20 58 19 62 13 54 11 66 9 57 13

Allentown, PA-NJ 60 17 68 11 63 19 64 15 70 12 61 10 56 12 55 13

Altoona, PA 167 3 188 2 178 4 172 4 185 3 195 1 204 1 193 1

Amarillo, TX NA NA NA NA NA NA NA NA 180 3 167 2 195 1 184 2

Ames, IA - 0 - 0 260 0 258 0 256 0 - 0 - 0 NA NA

Anaheim, CA 7 78 19 39 29 38 24 44 16 52 11 61 8 72 9 77

Ann Arbor, MI 179 3 154 3 129 6 112 7 116 6 135 3 127 4 120 4

Appleton, WI 247 1 218 1 207 3 182 3 176 3 157 2 163 2 186 2

Asheville, NC 120 6 125 4 139 6 167 4 159 4 145 3 140 3 165 2

Atlanta, GA 13 63 10 51 14 74 16 66 21 45 21 34 13 47 12 52

Atlantic City, NJ 113 7 119 4 110 8 114 7 120 6 129 4 153 3 152 3

Austin, TX 80 10 72 9 79 13 71 13 78 10 75 8 84 7 70 10

Bakersfield, CA 18 50 23 31 24 43 31 36 23 40 17 37 20 40 21 42

Baltimore, MD 17 52 14 49 13 78 11 79 18 49 24 34 21 40 23 35

Bangor, ME - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Barnstable Town, MA 107 8 112 5 116 8 117 7 122 6 NA NA NA NA NA NA

Baton Rouge, LA 69 13 54 15 73 16 75 13 79 10 58 10 61 11 78 9

Beaumont, TX 108 7 82 9 93 12 101 9 119 6 114 4 128 4 137 3

Bellingham, WA NA NA - 0 - 0 - 0 - 0 - 0 - 0 - 0

Bend, OR NA NA NA NA - 0 - 0 - 0 - 0 NA NA NA NA

Birmingham, AL 50 21 50 16 48 26 48 23 57 16 59 10 55 12 54 13

Bismarck, ND - 0 - 0 - 0 - 0 - 0 246 0 - 0 - 0

Blacksburg, VA NA NA NA NA NA NA 261 0 262 0 247 0 245 0 247 0

Bloomington, IL 191 2 200 1 199 3 184 3 179 3 174 2 202 1 201 1

Boise City, ID 149 4 223 1 173 4 169 4 108 6 101 5 114 5 89 7

Page 69 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Boston, MA 35 26 45 17 55 22 53 21 52 18 67 9 53 13 46 20

Boulder, CO 133 4 146 3 145 5 121 6 109 6 89 6 NA NA NA NA

Bowling Green, KY 227 1 228 1 258 0 255 0 255 0 235 0 225 1 233 0

Bridgeport, CT 40 24 40 18 38 32 32 37 32 31 26 30 29 29 28 32

Brownsville, TX 205 2 212 1 230 2 - 0 - 0 - 0 - 0 - 0

Brunswick, GA 248 0 258 0 264 0 - 0 - 0 - 0 - 0 - 0

Buffalo, NY 45 22 56 14 43 28 43 27 38 26 44 17 43 19 39 22

Burlington, VT 235 1 - 0 259 0 262 0 246 0 225 0 239 0 230 0

Cambridge, MA 27 40 34 21 40 30 39 29 36 28 39 19 50 14 51 16

Camden, NJ 37 25 39 18 35 34 33 33 42 24 45 16 39 21 38 22

Canton, OH 78 11 74 10 68 18 67 15 80 10 71 9 69 9 73 9

Cape Coral, FL 127 5 162 3 169 4 162 4 129 5 148 3 - 0 - 0

Carson City, NV NA NA NA NA 244 1 NA NA NA NA 185 1 183 1 198 1

Casper, WY NA NA NA NA NA NA NA NA NA NA 226 0 - 0 240 0

Cedar Rapids, IA 237 1 224 1 206 3 204 2 222 1 - 0 230 0 236 0

Chambersburg, PA 185 2 210 1 198 3 189 3 187 3 182 1 - 0 - 0

Champaign, IL NA NA NA NA NA NA 185 3 208 2 168 2 169 2 178 2

Charleston, SC 169 3 174 2 187 3 238 1 - 0 - 0 - 0 - 0

Charleston, WV 139 4 133 4 117 8 125 7 140 5 126 4 138 3 136 3

Charlotte, NC-SC 29 34 31 22 33 35 38 30 43 23 49 14 42 19 45 20

Chattanooga, TN-GA 82 10 91 7 90 12 99 9 101 7 107 5 83 7 101 6

Cheyenne, WY NA NA NA NA NA NA 214 2 207 2 193 1 212 1 219 1

Chicago, IL 9 71 6 66 5 119 5 139 5 117 8 71 7 87 5 122

Chico, CA 84 10 93 7 98 10 94 9 86 9 70 9 67 9 69 10

Cincinnati, OH-KY-IN 21 45 18 42 19 60 19 55 22 42 30 27 23 34 24 35

Clarksville, TN-KY 208 2 183 2 214 2 218 2 210 2 212 1 226 1 241 0

Cleveland, OH 15 55 21 39 16 72 15 69 15 55 23 35 22 40 19 45

Coeur d'Alene, ID - 0 - 0 NA NA NA NA NA NA NA NA NA NA NA NA

Colorado Springs, CO 101 8 95 7 76 14 68 14 67 12 68 9 89 7 75 9

Columbia, MO NA NA 216 1 200 3 205 2 202 2 213 1 209 1 212 1

Columbia, SC 126 5 117 5 122 7 138 5 186 3 187 1 145 3 151 3

Columbus, GA-AL 154 4 166 3 188 4 208 2 229 1 230 0 203 1 223 1

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2010 2011 2012 2013 2014 2015 2016 2017City City

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MortalityCity

RankO3

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MortalityCity

RankO3

MortalityCity

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MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Columbus, IN NA NA NA NA NA NA NA NA NA NA NA NA 180 1 189 1

Columbus, OH 25 40 27 31 21 55 21 50 25 40 28 29 27 30 30 30

Corpus Christi, TX 146 4 141 4 149 5 158 4 182 3 153 2 161 2 200 1

Crestview, FL NA NA 191 2 211 2 225 1 218 1 214 1 216 1 - 0

Dallas, TX 10 69 7 61 7 96 6 113 6 94 7 74 10 69 10 76

Dalton, GA 226 1 234 1 243 1 247 1 244 1 229 0 227 1 227 1

Daphne, AL 159 3 149 3 177 4 196 3 194 2 158 2 157 2 195 1

Davenport, IA-IL 233 1 235 1 223 2 209 2 216 1 - 0 175 2 172 2

Dayton, OH 42 23 37 19 41 30 44 27 49 21 47 15 48 17 49 18

Decatur, AL 211 2 197 2 201 3 206 2 219 1 238 0 198 1 210 1

Decatur, IL 197 2 194 2 194 3 186 3 193 2 184 1 174 2 180 2

Deltona, FL 155 3 152 3 157 5 174 4 166 3 - 0 - 0 - 0

Denver, CO 51 20 29 26 26 41 26 43 24 39 14 45 18 42 18 45

Des Moines, IA 255 0 257 0 234 1 231 1 201 2 - 0 - 0 - 0

Detroit, MI 28 39 17 43 22 54 22 49 27 38 29 29 25 33 25 34

Dothan, AL 245 1 243 1 245 1 249 1 258 0 - 0 - 0 - 0

Dover, DE 152 4 173 2 160 5 156 5 153 4 173 2 160 2 166 2

Duluth, MN-WI NA NA 239 1 235 1 - 0 - 0 - 0 - 0 - 0

Durham, NC 117 6 123 4 138 6 171 4 169 3 216 1 200 1 221 1

East Stroudsburg, PA 178 3 209 1 203 3 233 1 233 1 205 1 177 2 168 2

Eau Claire, WI NA NA NA NA NA NA 254 0 243 1 - 0 242 0 246 0

El Centro, CA 162 3 160 3 163 4 145 5 138 5 117 4 119 4 127 4

El Paso, TX 89 9 85 8 77 13 74 13 63 13 52 12 51 13 53 13

Elgin, IL 158 3 134 4 130 6 136 5 126 5 132 3 100 5 93 7

Elizabethtown, KY 198 2 213 1 213 2 210 2 NA NA 219 1 206 1 208 1

Elkhart, IN 219 1 198 2 191 3 192 3 253 0 - 0 234 0 185 2

Elmira, NY 216 1 215 1 236 1 NA NA NA NA NA NA NA NA NA NA

Erie, PA 112 7 111 5 106 9 103 8 105 7 123 4 124 4 135 3

Eugene, OR 244 1 252 0 - 0 - 0 - 0 217 1 218 1 133 4

Evansville, IN-KY 110 7 104 6 102 10 90 10 88 9 96 5 92 6 96 7

Fargo, ND-MN - 0 - 0 263 0 NA NA - 0 NA NA NA NA - 0

Farmington, NM 241 1 244 1 205 3 221 2 224 1 202 1 211 1 196 1

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2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

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MortalityCity

RankO3

MortalityCity

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MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

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Mortality

Fayetteville, AR-MO 223 1 190 2 170 4 164 4 175 3 203 1 - 0 - 0

Fayetteville, NC 125 5 121 4 136 6 152 5 181 3 218 1 155 2 175 2

Flagstaff, AZ 212 1 219 1 216 2 200 2 197 2 164 2 164 2 192 1

Flint, MI 111 7 106 6 83 13 70 14 73 11 84 7 71 8 87 7

Florence, AL 240 1 242 1 249 1 250 1 248 0 - 0 - 0 - 0

Florence, SC 214 1 220 1 231 1 236 1 237 1 244 0 238 0 243 0

Fond du Lac, WI 242 1 230 1 222 2 198 3 198 2 199 1 192 1 215 1

Fort Collins, CO 119 6 113 5 109 8 98 9 83 9 72 8 77 7 80 8

Fort Lauderdale, FL 142 4 - 0 - 0 - 0 184 3 106 5 102 5 111 5

Fort Smith, AR-OK NA NA NA NA NA NA 229 1 235 1 233 0 - 0 - 0

Fort Wayne, IN 140 4 127 4 121 7 124 6 131 5 183 1 158 2 144 3

Fort Worth, TX 14 54 11 49 15 75 14 70 14 54 12 54 15 45 13 50

Fresno, CA 22 44 22 33 23 50 23 46 19 48 15 44 12 48 14 48

Gadsden, AL 232 1 240 1 254 1 257 0 - 0 - 0 235 0 235 0

Gainesville, FL 228 1 236 1 233 1 244 1 239 1 - 0 - 0 - 0

Gary, IN 99 8 94 7 91 12 83 11 66 12 79 8 65 10 66 10

Gettysburg, PA 183 2 NA NA NA NA NA NA 204 2 192 1 170 2 187 2

Grand Junction, CO NA NA 189 2 195 3 188 3 188 3 176 2 186 1 173 2

Grand Rapids, MI 77 11 73 10 67 18 57 19 58 15 57 10 57 12 60 12

Greeley, CO 153 4 148 3 142 6 122 6 117 6 98 5 115 4 118 4

Green Bay, WI 202 2 195 2 176 4 161 4 145 4 154 2 152 3 159 2

Greensboro, NC 58 18 60 13 71 17 73 13 77 10 118 4 86 7 92 7

Greenville, NC 187 2 203 1 208 2 207 2 217 1 220 1 222 1 222 1

Greenville, SC 180 3 69 11 72 16 81 12 111 6 119 4 125 4 105 6

Gulfport, MS 98 9 90 8 105 9 113 7 103 7 91 6 95 6 156 3

Hagerstown, MD-WV 123 6 124 4 127 7 147 5 162 4 152 3 148 3 143 3

Hanford, CA 130 4 158 3 151 5 153 4 141 4 104 5 107 5 114 5

Harrisburg, PA 114 7 115 5 111 8 108 7 128 5 141 3 133 3 142 3

Hartford, CT 32 28 38 18 39 30 35 31 28 35 20 36 26 30 33 26

Hickory, NC 181 3 186 2 217 2 230 1 245 0 224 1 182 1 188 1

Houma, LA 215 1 204 1 227 2 220 2 225 1 211 1 215 1 226 1

Houston, TX 8 75 4 77 6 102 7 101 8 85 6 83 5 101 6 118

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2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Huntington, WV-KY-OH 132 5 145 4 120 8 134 6 151 4 160 2 141 3 147 3

Huntsville, AL 124 5 126 4 118 8 123 6 124 5 161 2 147 3 149 3

Idaho Falls, ID 256 0 262 0 267 0 265 0 263 0 249 0 - 0 - 0

Indianapolis, IN 30 34 28 30 25 44 27 42 33 29 62 9 46 19 34 25

Ithaca, NY NA NA NA NA NA NA NA NA 236 1 234 0 229 0 238 0

Jackson, MS 200 2 180 2 196 3 201 2 250 0 NA NA 228 0 234 0

Jacksonville, FL 86 10 89 8 114 8 187 3 215 1 - 0 - 0 - 0

Janesville, WI 210 2 192 2 181 4 NA NA NA NA 150 3 146 3 163 2

Jefferson City, MO NA NA 248 0 248 1 243 1 242 1 237 0 232 0 242 0

Johnstown, PA 193 2 187 2 202 3 202 2 213 2 215 1 217 1 216 1

Joplin, MO NA NA 143 4 159 5 149 5 164 4 179 2 240 0 - 0

Kalamazoo, MI 147 4 144 4 132 6 116 7 113 6 134 3 120 4 122 4

Kansas City, MO-KS 83 10 63 12 44 27 45 26 48 21 74 8 94 6 98 6

Kennewick, WA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 123 4

Killeen, TX NA NA NA NA 141 6 128 6 125 5 124 4 142 3 126 4

Kingsport, TN-VA 128 5 130 4 133 6 142 5 157 4 166 2 144 3 140 3

Kingston, NY 176 3 171 2 193 3 NA NA NA NA NA NA NA NA NA NA

Knoxville, TN 46 22 49 16 51 23 60 18 82 9 103 5 60 11 63 11

La Crosse, WI-MN 253 0 256 0 242 1 237 1 234 1 239 0 231 0 231 0

Lafayette, IN 251 0 254 0 257 0 253 0 251 0 242 0 241 0 245 0

Lafayette, LA 164 3 175 2 186 4 191 3 190 2 156 2 159 2 183 2

Lake Charles, LA 138 4 120 4 156 5 175 4 173 3 143 3 143 3 158 3

Lakeland, FL 90 10 86 8 101 10 97 9 99 7 122 4 126 4 90 7

Lancaster, PA 67 15 77 9 64 18 66 14 71 11 81 7 68 9 71 10

Lansing, MI 173 3 163 3 185 4 150 5 155 4 163 2 151 3 139 3

Laredo, TX - 0 NA NA NA NA NA NA NA NA - 0 - 0 NA NA

Las Cruces, NM 166 3 181 2 174 4 139 5 130 5 115 4 108 5 116 5

Las Vegas, NV 16 54 20 38 20 58 18 64 11 68 10 63 11 63 11 63

Lawton, OK 190 2 178 2 192 3 170 4 168 3 155 2 185 1 203 1

Lebanon, PA NA NA NA NA NA NA 148 5 163 4 130 4 135 3 148 3

Lewiston, ME 225 1 253 0 - 0 260 0 257 0 - 0 - 0 - 0

Lexington, KY 134 4 135 4 112 8 110 7 139 5 142 3 116 4 128 4

Page 73 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Lima, OH 177 3 161 3 182 4 178 4 172 3 170 2 173 2 170 2

Lincoln, NE - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Little Rock, AR 115 6 103 6 87 12 78 12 90 8 108 5 149 3 155 3

Logan, UT-ID 252 0 260 0 255 1 242 1 241 1 NA NA NA NA NA NA

Longview, TX 171 3 157 3 164 4 166 4 183 3 165 2 176 2 191 1

Los Angeles, CA 1 429 1 270 1 405 1 481 1 460 1 435 1 418 1 445

Macon, GA 143 4 139 4 168 4 177 4 192 2 198 1 172 2 179 2

Madera, CA 163 3 153 3 147 5 181 3 161 4 131 3 129 3 103 6

Madison, WI 195 2 193 2 144 6 109 7 98 7 111 5 118 4 121 4

Manchester, NH 95 9 109 6 126 7 163 4 104 7 93 6 93 6 106 6

McAllen, TX 243 1 221 1 237 1 - 0 - 0 - 0 - 0 - 0

Medford, OR 184 2 245 0 256 1 223 2 195 2 147 3 - 0 154 3

Memphis, TN-MS-AR 34 26 41 18 37 33 34 31 44 22 50 13 54 12 56 12

Merced, CA 102 8 108 5 113 8 115 7 93 7 77 8 72 8 82 8

Miami, FL 48 22 66 11 70 17 79 12 81 10 63 9 76 8 68 10

Michigan City, IN 222 1 179 2 165 4 131 6 136 5 159 2 220 1 182 2

Milwaukee, WI 49 21 75 10 30 39 29 38 29 35 41 19 32 23 35 24

Minneapolis, MN-WI 234 1 206 1 190 3 173 4 142 4 149 3 178 1 205 1

Missoula, MT NA NA NA NA NA NA NA NA NA NA - 0 - 0 - 0

Mobile, AL 97 9 81 9 115 8 154 5 156 4 120 4 121 4 157 3

Modesto, CA 47 21 58 13 56 21 50 21 47 21 43 18 44 19 41 21

Monroe, LA 229 1 207 1 251 1 256 0 - 0 - 0 NA NA NA NA

Montgomery, AL 144 4 142 4 154 5 193 3 206 2 207 1 213 1 228 0

Morgantown, WV 224 1 222 1 228 2 232 1 232 1 208 1 221 1 225 1

Morristown, TN 209 2 208 1 218 2 215 2 212 2 201 1 194 1 202 1

Mount Vernon, WA NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Muncie, IN 213 1 182 2 197 3 199 3 231 1 - 0 - 0 224 1

Muskegon, MI 137 4 132 4 128 7 111 7 110 6 102 5 104 5 112 5

Napa, CA 220 1 229 1 250 1 - 0 - 0 241 0 224 1 220 1

Naples, FL NA NA NA NA - 0 - 0 - 0 - 0 - 0 - 0

Nashville, TN 56 18 52 15 42 29 55 20 53 17 65 9 59 11 72 9

New Haven, CT 57 17 35 20 36 33 36 31 37 26 38 20 31 23 37 22

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2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

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MortalityCity

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Mortality

New Orleans, LA 70 13 44 18 59 21 63 15 61 13 60 10 63 10 95 7

New York, NY-NJ 2 208 3 148 2 264 2 241 3 165 3 166 3 186 3 188

Newark, NJ-PA 71 13 43 17 34 35 37 30 39 25 42 19 40 20 50 17

Niles, MI 150 4 136 4 123 7 104 8 106 7 100 5 103 5 110 5

North Port, FL 79 11 87 8 75 15 69 14 74 11 73 9 130 4 109 5

Norwich, CT 105 8 107 6 103 10 84 11 72 11 76 8 88 7 81 8

Oakland, CA 24 42 25 31 32 36 40 28 34 28 25 30 24 33 22 36

Ocala, FL 135 5 155 3 158 5 245 1 - 0 - 0 214 1 209 1

Ogden, UT 94 9 105 6 104 9 92 10 76 10 64 9 62 10 59 12

Oklahoma City, OK 39 24 30 24 31 37 30 38 35 28 37 20 49 17 48 18

Olympia, WA - 0 - 0 - 0 - 0 - 0 - 0 - 0 229 0

Omaha, NE-IA 231 1 238 1 153 5 118 7 118 6 137 3 165 2 153 3

Orlando, FL 61 17 46 16 46 26 47 23 54 16 86 6 87 7 64 11

Owensboro, KY 182 2 172 2 171 4 159 5 171 3 186 1 188 1 190 1

Oxnard, CA 38 24 48 16 53 22 51 21 56 16 46 15 36 21 42 21

Palm Bay, FL 118 6 131 4 131 7 146 5 144 5 194 1 171 2 - 0

Panama City, FL 161 3 165 3 189 3 203 2 199 2 190 1 210 1 - 0

Parkersburg, WV 201 2 211 1 210 2 213 2 200 2 178 2 162 2 194 1

Pensacola, FL 74 12 80 9 92 12 100 9 94 8 116 4 122 4 161 2

Peoria, IL 172 3 164 3 161 5 151 5 154 4 169 2 179 1 162 2

Philadelphia, PA 12 68 15 46 11 87 12 73 13 56 22 35 19 42 20 43

Phoenix, AZ 5 98 5 66 4 133 4 143 4 138 4 125 4 138 4 128

Pittsburgh, PA 11 72 12 51 12 81 13 74 12 69 13 52 16 46 16 48

Pittsfield, MA NA NA 184 2 184 4 190 3 189 2 NA NA NA NA NA NA

Port St. Lucie, FL NA NA NA NA NA NA NA NA NA NA NA NA 208 1 211 1

Portland, ME 106 8 100 7 96 11 126 6 112 6 92 6 91 6 131 4

Portland, OR-WA 160 3 167 2 212 2 228 1 221 1 162 2 136 3 58 12

Prescott, AZ NA NA 147 3 134 6 120 7 97 7 83 7 81 7 102 6

Providence, RI-MA 31 29 32 22 58 22 49 23 30 35 31 26 45 19 31 30

Provo, UT 145 4 156 3 166 4 133 5 107 6 87 5 82 7 99 6

Racine, WI 151 4 122 4 124 7 119 7 NA NA NA NA NA NA 108 6

Raleigh, NC 64 16 61 12 62 18 65 14 91 8 109 4 78 7 79 8

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2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

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MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Rapid City, SD - 0 - 0 266 0 264 0 259 0 - 0 - 0 250 0

Reading, PA 73 12 79 9 82 13 91 10 87 9 82 7 74 8 85 7

Redding, CA 116 6 150 3 162 5 195 3 160 4 128 4 109 5 74 9

Reno, NV 103 8 137 4 172 4 165 4 123 5 88 6 96 6 65 11

Richmond, VA 62 17 64 12 66 18 76 13 133 5 172 2 181 1 113 5

Riverside, CA 3 196 2 151 3 210 3 216 2 210 2 202 2 218 2 242

Rochester, MN NA NA NA NA 253 1 241 1 228 1 245 0 243 0 244 0

Rochester, NY 76 11 247 0 238 1 235 1 89 8 136 3 113 5 77 9

Rockford, IL 207 2 170 2 167 4 155 5 134 5 127 4 117 4 132 4

Rocky Mount, NC 221 1 231 1 239 1 234 1 240 1 236 0 NA NA 239 0

Sacramento, CA 6 92 8 61 10 89 10 85 9 79 9 64 9 72 8 80

Salem, OR 206 2 246 0 - 0 - 0 - 0 200 1 150 3 124 4

Salinas, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Salisbury, MD-DE 109 7 114 5 108 9 105 8 95 8 105 5 106 5 125 4

Salt Lake City, UT 230 1 233 1 74 15 59 17 46 21 35 20 38 20 32 26

San Antonio, TX 33 26 33 21 28 39 25 44 20 46 19 36 30 28 26 33

San Diego, CA 4 113 9 60 8 94 8 95 7 90 5 91 6 100 7 112

San Francisco, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

San Jose, CA 41 22 36 18 52 22 62 16 50 19 36 20 37 20 43 21

San Luis Obispo, CA 75 11 97 7 100 10 96 9 85 9 80 8 75 8 84 8

San Rafael, CA - 0 - 0 - 0 - 0 - 0 231 0 233 0 - 0

Santa Cruz, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Santa Fe, NM 238 1 251 0 232 1 219 2 205 2 189 1 207 1 207 1

Santa Maria, CA 93 9 99 7 143 6 180 3 143 4 110 5 101 5 138 3

Santa Rosa, CA - 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Savannah, GA 204 2 201 1 229 2 240 1 - 0 - 0 - 0 - 0

Scranton, PA 72 13 88 8 94 11 93 9 115 6 97 5 85 7 88 7

Seattle, WA 44 22 62 12 80 13 143 5 65 12 48 14 47 17 27 32

Sebastian, FL NA NA NA NA NA NA 212 2 211 2 232 0 236 0 NA NA

Sebring, FL 192 2 217 1 240 1 251 1 254 0 - 0 - 0 - 0

Sheboygan, WI 157 3 151 3 152 5 135 6 135 5 125 4 123 4 115 5

Shreveport, LA 104 8 83 8 86 12 89 10 121 6 113 5 139 3 150 3

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2010 2011 2012 2013 2014 2015 2016 2017City City

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MortalityCity

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Mortality

Sierra Vista, AZ 186 2 177 2 175 4 168 4 165 4 144 3 166 2 176 2

Silver Spring, MD 53 19 47 16 45 26 54 20 59 14 51 12 52 13 52 14

Sioux City, IA-NE-SD NA NA 261 0 265 0 NA NA NA NA 248 0 246 0 249 0

Sioux Falls, SD 246 1 237 1 221 2 197 2 191 2 196 1 189 1 199 1

South Bend, IN-MI 174 3 159 3 119 8 88 10 92 8 112 5 98 5 94 7

Spartanburg, SC 92 10 92 7 99 10 107 8 148 4 NA NA 105 5 119 5

Spokane, WA - 0 - 0 - 0 - 0 226 1 188 1 - 0 164 2

Springfield, IL NA NA NA NA NA NA 140 5 196 2 227 0 191 1 146 3

Springfield, MA 65 15 71 10 81 13 77 12 75 10 69 8 70 8 62 11

Springfield, MO 129 5 118 5 107 9 106 8 127 5 210 1 - 0 - 0

Springfield, OH 136 5 129 4 140 6 137 6 147 4 133 3 134 3 130 4

St. Cloud, MN NA NA NA NA 262 0 252 0 249 0 240 0 - 0 - 0

St. George, UT 175 3 185 2 183 4 176 4 167 3 151 3 167 2 167 2

St. Joseph, MO-KS NA NA 249 0 252 1 248 1 252 0 243 0 244 0 248 0

St. Louis, MO-IL 20 47 13 50 9 94 9 89 10 75 16 45 14 48 17 46

State College, PA 189 2 202 1 209 2 194 3 203 2 197 1 196 1 197 1

Stockton, CA 52 20 57 14 57 21 52 21 45 22 40 19 34 22 44 21

Syracuse, NY 96 9 102 6 89 12 95 9 100 7 138 3 131 4 129 4

Tacoma, WA 188 2 - 0 - 0 - 0 - 0 NA NA NA NA 145 3

Tallahassee, FL 217 1 226 1 220 2 217 2 238 1 - 0 - 0 237 0

Tampa, FL 23 45 26 32 27 42 28 41 31 34 27 30 35 22 47 20

Terre Haute, IN 236 1 232 1 224 2 211 2 209 2 221 1 190 1 177 2

Toledo, OH 91 10 78 9 85 12 85 11 69 12 90 6 79 7 91 7

Topeka, KS 199 2 168 2 148 6 141 5 158 4 171 2 187 1 217 1

Trenton, NJ 100 8 101 6 97 10 102 8 102 7 85 6 80 7 86 7

Tucson, AZ 54 20 53 15 50 25 41 28 40 25 34 22 41 19 40 22

Tulsa, OK 59 17 51 16 47 26 42 27 51 19 56 11 112 5 100 6

Tuscaloosa, AL 249 0 - 0 - 0 - 0 - 0 - 0 - 0 - 0

Tyler, TX 131 5 116 5 137 6 127 6 146 4 140 3 156 2 169 2

Utica, NY 218 1 250 0 226 2 263 0 261 0 - 0 237 0 232 0

Vallejo, CA 121 6 128 4 150 5 157 4 150 4 121 4 110 5 107 6

Victoria, TX 239 1 227 1 241 1 239 1 247 0 223 1 219 1 218 1

Page 77 of 86

2010 2011 2012 2013 2014 2015 2016 2017City City

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

MortalityCity

RankO3

Mortality

Vineland, NJ 141 4 176 2 180 4 183 3 177 3 180 2 154 2 171 2

Virginia Beach, VA-NC 203 2 214 1 135 6 160 4 174 3 181 1 193 1 181 2

Visalia, CA 36 25 42 17 49 25 46 24 41 24 33 22 33 22 36 23

Waco, TX 156 3 138 4 155 5 130 6 149 4 139 3 184 1 NA NA

Warren, MI 19 49 16 43 17 70 17 66 17 52 18 38 17 44 15 48

Washington, DC-VA-MD-WV 26 39 24 30 18 60 20 51 26 38 32 24 28 29 29 30

Waterloo, IA 254 0 259 0 261 0 259 0 260 0 - 0 - 0 - 0

Watertown, NY 196 2 205 1 215 2 216 2 220 1 222 1 223 1 NA NA

Wausau, WI 250 0 255 0 246 1 227 1 223 1 209 1 197 1 214 1

Weirton, WV-OH 165 3 169 3 179 4 179 4 170 3 191 1 201 1 213 1

West Palm Beach, FL 122 6 110 6 125 7 144 5 132 5 - 0 NA NA 160 2

Wheeling, WV-OH 194 2 196 2 219 2 224 1 230 1 206 1 199 1 204 1

Wichita, KS 81 10 67 12 69 17 61 17 60 14 66 9 97 5 134 3

Williamsport, PA 168 3 225 1 225 2 222 2 214 1 204 1 205 1 206 1

Wilmington, DE-MD-NJ 66 15 70 11 65 18 72 13 68 12 78 8 58 11 61 11

Wilmington, NC NA NA 241 1 247 1 226 1 227 1 228 0 - 0 - 0

Winston, NC 85 10 84 8 78 13 86 11 84 9 94 5 90 6 104 6

Worcester, MA-CT 43 23 65 12 88 12 87 10 64 13 53 11 73 8 67 10

York, PA 87 10 98 7 84 13 82 11 96 7 99 5 111 5 76 9

Youngstown, OH-PA 63 17 59 13 54 23 56 21 55 17 55 11 64 10 83 8

Yuba City, CA 170 3 199 2 204 3 246 1 178 3 146 3 137 3 174 2

Yuma, AZ 148 4 140 4 146 6 132 6 114 6 95 5 99 5 117 5

Page 78 of 86

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FIGURE LEGENDS

Figure E1. Trends in design values for short-term PM2.5 in monitored counties across “Health of the Air”

study years. Colors are shown for areas already meeting ATS-recommended levels and areas that meet

NAAQS levels but not ATS-recommended levels, as well as two additional colors for areas not meeting NAAQS

levels.

Figure E2. Trends in design values for long-term PM2.5 in monitored counties across “Health of the Air” study

years. Colors are shown for areas already meeting ATS-recommended levels and areas that meet NAAQS

levels but not ATS-recommended levels, as well as two additional colors for areas not meeting NAAQS levels.

Figure E3. Trends in design values for O3 in monitored counties across “Health of the Air” study years. Colors

are shown for areas already meeting ATS-recommended levels and areas that meet NAAQS levels but not ATS-

recommended levels, as well as two additional colors for areas not meeting NAAQS levels.

Figure E4: National annual air pollution-related excess deaths attributable to O3 above ATS recommended

standards, 2010-2017. The trends in excess mortality attributable to O3 concentrations greater than

recommended by the ATS are shown with and without accounting for changes in population that occurred

over the same time period.

Page 82 of 86

2011-2013

2013-2015

2015-2017

Figure E1. Trends in design values for short-term PM2.5 in monitored counties across “Health of the Air” study years. Colors are shown for areas already meeting ATS-recommended levels and areas that meet NAAQS levels but not ATS-recommended levels, as well as two additional colors for areas not meeting NAAQS levels.

Page 83 of 86

2011-2013

2013-2015

2015-2017

Figure E2. Trends in design values for long-term PM2.5 in monitored counties across “Health of the Air” study years. Colors are shown for areas already meeting ATS-recommended levels and areas that meet NAAQS levels but not ATS-recommended levels, as well as two additional colors for areas not meeting NAAQS levels.

Page 84 of 86

2011-2013

2013-2015

2015-2017

Figure E3. Trends in design values for O3 in monitored counties across “Health of the Air” study years. Colors are shown for areas already meeting ATS-recommended levels and areas that meet NAAQS levels but not ATS-recommended levels, as well as two additional colors for areas not meeting NAAQS levels.

Page 85 of 86

Figure E4: National annual air pollution-related excess deaths attributable to O3 above ATS recommended standards, 2010-2017. The trends in excess mortality attributable to O3 concentrations greater than recommended by the ATS are shown with and without accounting for changes in population that occurred over the same time period.

Page 86 of 86

Documents

Trends in Excess Morbidity and Mortality …Trends in Excess Morbidity and Mortality Associated with Air Pollution above ATS-Recommended Standards, 2008 to 2017 Kevin R. Cromar1,2,