Overview of Ozone (O3) Air Quality in the United States

Updated: June 29, 2023

1.	Introduction

The overall purpose of this document is to maintain an up-to-date graphical summary of air quality information that
supports the review of the National Ambient Air Quality Standards (NAAQS) for ozone (O3). In previous reviews of the O3
NAAQS, this type of information has generally been included in atmospheric sections of the Integrated Science Assessment
(ISA) and Policy Assessment (PA) for O3 and related photochemical oxidants. This stand-alone document will either replace
or complement the air quality emissions and monitoring data in the atmospheric sections of future O3 NAAQS review
supporting documents and will be updated at regular intervals as new data becomes available.

The content of past NAAQS documents' atmospheric sections has included major sections on emissions and concentration
trends utilizing maps and data from the Environmental Protection Agency's (EPA's) National Emissions Inventory (NEI) and
the EPA's Air Quality System (AQS) database. In past NAAQS reviews, this often involved adaptation of figures and tables
prepared for other reports or development of new figures and tables using data analysis and mapping software. Additionally,
the release of updated emission inventories and ambient air monitoring data may not coincide with the schedule for the
development of NAAQS review supporting documents. As a result, data access and resources can limit the availability of the
most recent information for inclusion in NAAQS review supporting documents.

This stand-alone document allows the content to be updated as soon as new data becomes available, rather than relying
on information that is available at the time of development of the NAAQS review supporting documents. It also ensures that
the public will have access to a consistent set of maps and figures for each NAAQS pollutant that are updated on a routine
basis, rather than separated by several years because of the disparate schedules of the various NAAQS reviews for each
pollutant. Moreover, a stand-alone document can be expanded to include new air quality analyses as they are completed,
rather than following the timeline for the public release of the NAAQS review supporting documents. Finally, this document
takes advantage of a more flexible digital format for the routinely prepared maps and trends figures with an end product that
more strongly emphasizes visual presentation of data and reduces the amount of text, while also creating a more interactive
presentation of the information through the use of external links.

This document follows an organizational structure similar to that of the atmospheric sections of past O3 NAAQS
review supporting documents. The subsequent sections are as follows: 2. Atmospheric Chemistry; 3. Sources and Emissions
of O3 Precursors; 4. Ambient Air Monitoring Requirements and Monitoring Networks; 5. Data Handling Conventions
and Computations for Determining Whether the Standards are Met; and 6. O3 Concentrations Measured at Ambient Air
Monitoring Sites Across the U.S. These sections are broad enough in scope to communicate relevant information about O3 air
quality, including scientific advances, but specific enough that the information needed to develop NAAQS review supporting
documents can be quickly and readily retrieved.

2.	Atmospheric Chemistry

O3 is one of a group of photochemical oxidants formed in the troposphere1 by photochemical reactions of precursor gases
in the presence of sunlight and is generally not directly emitted from specific sources.2 Tropospheric O3 and other oxidants,
such as peroxyacetyl nitrate (PAN) and hydrogen peroxide, form in polluted areas by atmospheric reactions involving two
main classes of precursor pollutants: volatile organic compounds (VOCs) and nitrogen oxides (NOx). This occurs especially
during the summer, as a result of the photolysis of primary pollutants such as nitrogen dioxide (NO2). The reaction is
disrupted by the presence of VOCs, the radical that results from methane (CH4) oxidation; or a reaction between carbon
monoxide (CO) and the hydroxyl radical (OH) in the atmosphere. Thus, the substances NOx, VOC, CH4 and CO are
considered to be the primary precursors of tropospheric O3. The formation of O3, other oxidants, and oxidation products
from these precursors is a complex, nonlinear function of many factors including (1) the intensity and spectral distribution

(also occurs ill the stratosphere, where it serves the beneficial role of absorbing the sun's harmful ultraviolet radiation and preventing the
majority of this radiation from reaching the Earth's surface.

2 The only other appreciable source of O3 to the troposphere is transport from the stratosphere.

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of sunlight; (2) atmospheric mixing; (3) concentrations of precursors in the ambient air and the rates of chemical reactions
of these precursors; and (4) processing on cloud and aerosol particles.

O3 is present not only in polluted urban atmospheres, but throughout the troposphere, even in remote areas of the globe.
The same basic processes involving photochemical reactions of NOx, VOCs, and CO contribute to O3 formation throughout
the troposphere. These processes also lead to the formation of other photochemical products, such as PAN, HNO3, and
H2SO4, and to other gaseous compounds, such as HCHO and other carbonyl compounds, as well as a number of particulate
compounds.

Prior to 1979, the indicator for the NAAQS for photochemical oxidants was total photochemical oxidants. Early ambient
air monitoring indicated similarities between O3 measurements and the photochemical oxidant measurements, as well as
reduced precision and accuracy of the latter. To address these issues, the EPA established O3 as the indicator for the
NAAQS for photochemical oxidants in 1979, and it is currently the only photochemical oxidant other than NO2 that is
routinely monitored in a national ambient air monitoring network.

Rather than varying directly with emissions of its precursors, O3 changes in a nonlinear fashion with the concentrations
of its precursors. Emissions of NOx lead to both the formation and destruction of O3, depending on the local quantities
of NOx, VOCs, radicals, and sunlight. O3 chemistry is often described in terms of which precursors most directly impact
formation rates. A NOx-limited regime indicates that O3 concentrations will decrease in response to decreases in ambient
NOx concentrations and vice-versa. These conditions tend to occur when NOx concentrations are generally low compared
to VOC concentrations and during warm, sunny conditions when NOx photochemistry is relatively fast. NOx-limited
conditions are more common during daylight hours, in the summertime, in suburban and rural areas, and in portions of the
country with high biogenic VOC emissions like the Southeast. In contrast, NOx-saturated conditions (also referred to as
VOC-limited or radical-limited) indicate that O3 will increase as a result of NOx reductions but will decrease as a result of
VOC reductions. NOx-saturated conditions occur at times and locations with lower levels of available sunlight, resulting in
slower photochemical formation of O3, and when NOx concentrations are in excess compared to VOC concentrations. NOx-
saturated conditions are more common during nighttime hours, in the wintertime, and in densely populated urban areas or
industrial plumes. These varied relationships between precursor emissions and O3 chemistry result in localized areas in which
O3 concentrations are suppressed compared to surrounding areas, but which contain NO2 that contributes to subsequent O3
formation further downwind. Consequently, O3 response to reductions in NOx emissions is complex and may include decreases
in O3 concentrations at some times and locations and increases in O3 concentrations at other times and locations. Over the
past decade, there have been substantial decreases in NOx emissions in the U.S. and many locations have transitioned from
NOx-saturated to NOx-limited during times of year that are conducive to O3 formation (generally summer). As these NOx
emissions reductions have occurred, lower O3 concentrations have generally increased while the higher O3 concentrations
have generally decreased, resulting in a compressed O3 distribution, relative to historical conditions.

As mentioned above, the formation of O3 from precursor emissions is also affected by meteorological parameters such
as the intensity of sunlight and atmospheric mixing. Major episodes of high O3 concentrations in the eastern U.S. are often
associated with slow-moving high-pressure systems which can persist for several days. High pressure systems during the
warmer seasons are associated with the sinking of air, resulting in warm, generally cloudless skies, with light winds. The
sinking of air results in the development of stable conditions near the surface which inhibit or reduce the vertical mixing of
O3 precursors, concentrating them near the surface. Photochemical activity involving these precursors is enhanced because
of higher temperatures and the availability of sunlight during the warmer seasons. In the eastern U.S., concentrations of O3
and other photochemical oxidants are determined by meteorological and chemical processes extending typically over areas
of several hundred thousand square kilometers. Therefore, O3 episodes are often regarded as regional in nature, although
more localized episodes often occur in some areas, largely the result of local pollution sources during summer. In addition,
in some parts of the U.S. (e.g., Los Angeles, CA), mountain barriers limit O3 dispersion and result in a higher frequency and
duration of days with elevated O3 concentrations.

More recently, high O3 concentrations of up to 150 parts per billion (ppb) have been measured during the wintertime
in two western U.S. mountain basins. Wintertime mountain basin O3 episodes occur on cold winter days with low wind
speeds, clear skies, substantial snow cover, extremely shallow boundary layers driven by strong temperature inversions, and
substantial precursor emissions activity from the oil and gas sector. The results of recent modeling studies suggest that
photolysis of VOCs provides the source of reactive chemical species (radicals) needed to initiate the chemistry driving these
wintertime O3 episodes. This mechanism is markedly different from the chemistry driving summertime O3 formation, which
is initiated with the photolysis of NO2 followed by the formation of the OH radicals.

O3 concentrations in a region are affected both by local formation and by transport of O3 and its precursors from
upwind areas. O3 transport occurs on many spatial scales including local transport within urban areas, regional transport
over large regions of the U.S., and long-range transport which may also include international transport. In addition, O3 can
be transferred into the troposphere from the stratosphere, which is rich in naturally occurring O3, through stratosphere-
troposphere exchange (STE). These intrusions usually occur behind cold fronts, bringing stratospheric air with them and

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typically affect O3 concentrations in higher elevation areas (e.g., above 1500 m) more than areas at lower elevations.

3. Sources and Emissions of O3 Precursors

Sources of emissions of O3 precursor compounds can be divided into anthropogenic and natural source categories,
with natural sources further divided into emissions from biological processes of living organisms (e.g., plants, microbes,
and animals) and emissions from chemical or physical processes (e.g., biomass burning, lightning, and geogenic sources).
Anthropogenic emissions associated with combustion processes, including mobile sources and power plants, accounted for the
majority of U.S. NOx and GO emissions in 2020 (Figure 1). Anthropogenic sources are also important for VOG emissions,
though in some locations and times of the year (e.g., southeastern states during summer) the majority of VOG emissions come
from vegetation.3 CH4 is mostly emitted from anthropogenic sources, including production and consumption of fossil fuels
for energy, agriculture and waste disposal systems. In practice, the distinction between natural and anthropogenic sources
is often unclear, as human activities directly or indirectly affect emissions from what would have been considered natural
sources during the preindustrial era. Thus, precursor emissions from plants, animals, and wildfires could be considered either
natural or anthropogenic, depending on whether emissions result from agricultural practices, forest management practices,
lightning strikes, or other types of events. Additional challenges are presented because much O3 results from reactions
between anthropogenic and natural precursors.

The National Emissions Inventory (NEI) is a comprehensive and detailed estimate of air emissions of criteria pollutants,
precursors to criteria pollutants, and hazardous air pollutants from air emissions sources. The NEI is released every three
years based primarily upon data provided by State, Local, and Tribal air agencies for sources in their jurisdictions and
supplemented by data developed by the EPA. The NEI is built using the EPA's Emissions Inventory System (EIS) first to
collect the data from State, Local, and Tribal air agencies and then to blend that data with other data sources.

Accuracy in an emissions inventory reflects the extent to which the inventory represents the actual emissions that occurred.
Anthropogenic emissions of air pollutants result from a variety of sources such as power plants, industrial sources, motor
vehicles and agriculture. The emissions from any individual source typically vary in both time and space. For the thousands
of sources that make up the NEI, there is uncertainty in one or both of these factors. For some sources, such as power plants,
direct emission measurements enable the emission factors derived from them to be more certain than sources without such
direct measurements. However, it is not practically possible to directly monitor each of the emission sources individually and,
therefore, emission inventories necessarily contain assumptions, interpolation and extrapolation from a limited set of sample
data.

3It should be noted that the definition of VOC's used in this section does not include CH4 because it is excluded from the EPA's regulatory
definition of VOGs in 40 GFR 51.100(s).

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A) NOx (8,916 kTon/yr)

Stationary Fuel Combustion 25%

All Fires 5%

Biogenics 12%

Industrial
Processes 12%

Other 1%

Highway
Vehicles 26%

B) VOCs (46,189 kTon/yr)

Biogenics 64%

Wildfires 10%

Industrial
Processes 7%

Solvent Utilization 6%
Agricultural & Prescribed Fires 4%

C) CO (66,153 kTon/yr)

Wildfires 30%

Stationary Fuel
Combustion 7%

Industrial
Processes 2%

Biogenics 6%
Other 3%

D) CH4 (34,983 kTon/yr)

Energy/Fossil Fuels 38%

Agriculture 35%

Other 6

Highway Vehicles 22%

Waste Disposal/
Landfills 18%

Figure 1. U.S. O3 precursor emissions by sector: A) NOx; B) GO; G) VOGs; D) CH4. Source: 2020 NEI for panels A)-C),
Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2021 for panel D).

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Figure 2, Figure 3 and Figure 4 show county-level estimates of U.S. emissions densities (in tons/year/mi2) for GO,
NOx, and VOGs, respectively. In general, GO and NOx emissions tend to be highest in urban areas which typically have
the most anthropogenic sources of these precursors, however, GO emissions may be higher in some rural areas due to fires,
and similarly NOx emissions may be higher in some rural areas due to sources such as electricity generation, oil and gas
extraction, and traffic along major highways. While there are some significant anthropogenic sources of VOG emissions in
urban areas, in rural areas the vast majority of VOG emissions come from plants and trees (biogenics), particularly in the
southeastern U.S. In other areas of the U.S., such as the Great Plains region and parts of the inter-mountain west, areas with
higher levels of VOG emissions are largely due to oil and gas extraction.

It should be noted that O3 levels in a given area are impacted by both local emissions of precursors that form O3 in
the area as well as remote emissions of precursors that form O3 which is then transported into the area. Biogenic VOG
emissions that lead to O3 formation may vary greatly depending on the type and amount of vegetation, which is generally
much lower in urban areas than in rural areas. However, biogenic VOG emissions that are upwind of an urban area can
have a significant impact on urban O3 levels. Thus, while the county-level maps shown in Figure 2, Figure 3 and Figure 4
illustrate the variability in precursor emissions in the U.S., it is not sufficient to look only at the patterns in local emissions
when considering the impact on O3 concentrations.

~ 0-19.9(2128) ~ 20-49.9 (681) ~ 50-99.9 (230) ¦ 100-199.9 (110) ¦ 200-3484 (72)

Figure 2. U.S. county-level GO emissions density estimates in tons/yeax/mi2. Source: 2020 NEI

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Nitrogen Oxides Emissions Density in tons/year/miA2 (# Counties)
~ 0-1.9 (1356) ~ 2-4.9(1130) ~ 5-9.9(412) ¦ 10-19.9(196) ¦ 20-648(127)

Figure 3. U.S. county-level NOx emissions density estimates in tons/year/mi2. Source: 2020 NEI

Volatile Organic Compounds Emissions Density in tons/year/miA2 (# Counties)
~ 0-9.9 (984) ~ 10-19.9 (793) ~ 20-49.9 (1317) ¦ 50-99.9 (75) ¦ 100-737 (52)

Figure 4. U.S. county-level YOG emissions density estimates in tons/yeax/mi2. Source: 2020 NEI

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Figure 5 below shows the national trend in U.S. anthropogenic NOx, VOC, GO, and CH4 emissions from 2002 to 2022.4
Anthropogenic emissions of NOx from mobile and stationary sources have declined appreciably since 2002, largely as a
result of multiple regulatory programs implemented over the past two decades, including the NOx SIP Call, the Cross-State
Air Pollution Rule (CSAPR), and the Tier 3 Light-duty Vehicle Emissions and Fuel Standards. Similarly, EPA regulatory
programs have contributed to a substantial reduction in mobile source CO emissions over the past two decades. The EPA's
regulatory programs have also led to reductions in VOC emissions from mobile sources, however, industrial sources, which
are the largest anthropogenic source of VOCs, have stayed relatively constant during this time period. Anthropogenic CH4
emissions have decreased only slightly since 2002, as reductions in the energy sector have largely been offset by increasing
emissions in the agricultural sector.



Inventory Year

Inventory Year

90000



Inventory Year

Legend: CO, NOx, VOC

Inventory Year

Legend: CH4

~	Highway Vehicles

~	Non-Road Mobile

~	Stationary Fuel Combustion

~	Industrial and Other Processes

~	Other Anthropogenic Sources

~	Energy/Fossil Fuels

~	Agriculture

~	Waste Disposal/Landfills

~	Other Anthropogenic Sources

Figure 5. U.S. anthropogenic O3 precursor emissions trends for: A) NOx; B) CO; C) VOCs; and D) CH4. Source: EPA's
Air Pollutant Emissions Trends Data for panels A)-C), Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2021
for panel D).

4NOx, VOC', and GO data for Figure 5 come from the EPA's Air Pollutant. Emissions Trends Data. Note that emissions for some sectors are
interpolated between inventory years, and the emissions for some sectors are held constant beyond the most recent inventory year (for details,
see the "Development of Data" table in the national emissions trends data file. For the purposes of this document, wildfires are considered to be
natural emissions and thus are not included in Figure 2.

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4. Ambient Air Monitoring Requirements and Monitoring Networks

Ambient O3 concentrations are measured by monitoring networks operated by State, Local and Tribal air agencies, which
are typically funded in part by the EPA. The EPA provides monitoring requirements for O3 and other pollutants in 40 GFR
Part 58. Nearly all of the air monitoring stations that currently report data to the EPA use ultraviolet Federal Equivalent
Methods (FEMs). The Federal Reference Method (FRM) was revised in 2015 to include a new chemiluminescence by nitric
oxide (NO-GL) method. The previous ethylene (ET-GL) method, while still included in the GFR as an acceptable method,
is no longer used due to lack of availability and safety concerns with ethylene.

In 2022, there were over 1,300 monitors reporting O3 concentrations to the EPA. Figure 6 shows the locations of such
monitoring sites that reported data to the EPA at any time during the 2020-2022 period. The main network of monitors
providing ambient data for use in implementation activities related to the NAAQS is the State and Local Air Monitoring
Stations (SLAMS) network, which comprises over 80% of all O3 monitoring sites. The requirements for the SLAMS network
depend on the population and most recent O3 design values5 in the area. The minimum number of O3 monitors required
in a metropolitan statistical area (MSA) ranges from zero monitors for areas with a population less than 350,000 and no
recent history of an O3 design value greater than 85 percent of the level of the standard, to four monitors for areas with a
population greater than 10 million and an O3 design value greater than 85 percent of the standard level.6 At least one site
in each MSA must be designed to record the maximum concentration for that particular metropolitan area.

Two important subsets of SLAMS sites separately make up the National Gore (NCore) multi-pollutant monitoring network
and the Photochemical Assessment Monitoring Stations (PAMS) network. Each State is required to have at least one NCore
station, and O3 monitors at NCore sites are required to operate year-round. At each NCore site located in a MSA with
a population of 1 million or more (based on the most recent census), a PAMS network site is required.7 At a minimum,
monitoring sites in the PAMS network are required to measure certain O3 precursors during the months of June, July and
August, although some precursor monitoring may be required for longer periods of time to improve the usefulness of data
collected during an area's O3 season. In addition to reporting O3 concentrations, the NCore and PAMS networks provide
data on O3 precursor chemicals. The NCore sites feature co-located measurements of chemical species such as nitrogen oxide
and total reactive nitrogen, along with various meteorological measurements. The additional data collected at the PAMS
sites include measurements of NOx, and a target set of VOCs. The enhanced monitoring at sites in these two networks
informs our understanding of local O3 formation.

While the SLAMS network has a largely urban and population-based focus, there are monitoring sites in other networks
that can be used to track compliance with the NAAQS in rural areas. For example, the Clean Air Status and Trends Network
(CASTNET) sites are located in rural areas. There were 83 CASTNET sites operating in 2022, with most of the sites in
the eastern U.S. being operated by the EPA, and most of the sites in the western U.S. being operated by the National
Park Service (NPS). Finally, there are also a number of Special Purpose Monitors (SPMs), which are not required but are
often operated by air agencies for short periods of time (i.e., less than 3 years) to collect data for human health and welfare
studies, as well as other types of monitoring sites, including monitors operated by tribes and industrial sources. The SPMs
are typically not used to assess compliance with the NAAQS.8

bA design value is a statistic that summarizes the air quality data for a given area in terms of the indicator, averaging time, and form of the
standard. Design values can be compared to the level of the standard and are typically used to designate areas as meeting or not meeting the
standard and assess progress towards meeting the NAAQS.

6The SLAMS minimum monitoring requirements to meet the O3 design criteria are specified in Appendix D to 40 CFR Part 58.

7The requirements for PAMS, which were most recently updated in 2015, is fully described in section 5 of Appendix D to 40 CFR Part 58.

8SPMs that use federal reference or equivalent methods, meet all applicable requirements in 40 CFR Part 58, and operate continuously for at
least 3 years may be used to assess compliance with the NAAQS.

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• SLAMS (925)	• NCORE/PAMS (126) O CASTNET (83) • SPM/OTHER (140)

Figure 6: Map of U.S. O3 monitoring sites reporting data to the EPA during the 2020-2022 period. Source: AQS.

Since the highest O3 concentrations tend to be associated with a particular season for various locations, the EPA requires
O3 monitoring only during specific O3 monitoring seasons, as shown in Figure 7. The O3 monitoring seasons vary by State
and range in length from five months (May to September in Oregon and Washington) to all twelve months (in 11 states),
with the most common season being March to October (in 27 states).9

To provide an assessment of data quality, monitoring agencies must perform quality assurance (QA) checks at least once
every two weeks to derive estimates of precision and bias for O3 and the other gaseous criteria pollutant measurements using
calibration gas. For O3 monitors, the data quality goal for precision and bias is 7 percent. Ambient air quality data and
associated QA data are reported to the EPA via the Air Quality System (AQS).10 Data are reported quarterly and must be
submitted to AQS within 90 days after the end of each calendar quarter (i.e. Jan/Feb/Max, Apr/May/Jun, Jul/Aug/Sep,
Oct/Nov/Dec). Additionally, each monitoring agency is required to certify all FRM/FEM data that is submitted to AQS
annually, taking into consideration any QA findings, and a data certification letter must be sent to the EPA Regional
Administrator by May 1st of the following year.

9The required O3 monitoring seasons for each State are listed in Table D-3 of Appendix D to 40 CFR Part 58.

10 Quality assurance requirements for monitors used in evaluations of the NAAQS are provided in Appendix A to 40 CFR Part 58. Annual
summary reports of precision and bias can be obtained for each monitoring site at the EPA's Air Data website.

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Figure 7: Current O3 monitoring seasons in the U.S. Numbers in each State indicate: the months of t he year the State :is
required to monitor for O3 (e.g., 3-10 means O3, monitoring is required from March through October).

5. Data Handling Conventions and Computations for Determining Whether the Standards
are Met

To assess whether a. monitoring site or geographic area (usually a county or urban area) meets or exceeds a NAAQS, the
monitoring data are analyzed consistent with the established regulatory requirements for the handling of monitoring data
for the purposes of deriving a design value. A design value summarizes ambient air concentrations for an area in terms of
the indicator, averaging time and form for a given standard such that its comparison to the level of the standard indicates
whether the area meets or exceeds the standard. The procedures, for calculating design values for the current O3 NAAQS
(established in 2015) are detailed in Appendix U to 40 CFR Part 50 and are summarized below.

Hourly average O3 concentrations at the monitoring sites used for assessing whether an area meets or exceeds the NAAQS
are; required to be rejtflrted in parts per million (ppm) to the third decimal place, with additional digits truncated, consistent
with the typical measurement precision associated with most O3 monitoring instruments^ Monitored hourly O3 concentrations
flagged by the States as having been affected by an exceptional event, having been the subject of a demonstration submitted
by the State,, and having received concurrence: from the appropriate EPA Regional Office, are excluded from design value
Calculations consistent with 40 CFR 50.14.11 The hourly concentrations are used to compute moving 8-hour averages, which
are stored in the first hour of ea.ch 8-hour period (e.g., the 8-hour average for the 7:00 AM to 3:00 PM period is stored in
the 7:00 AM hour), and digits to the right of the third decimal place are truncated. Each 8-hour average rs considered valid
if six or more hourly concentrations are available for the 8-hour period.

Next, the daily maximum 8-hour average (MDA8) concentration for each day Is identified as the highest of the 17
consecutive, valid 8-hour average concentrations beginning at 7:00 AM and ending at 11:00 PM (which includes hourly O3
concentrations from the subsequent day). MDA8 values are considered valid if at least 13 valid 8-hour averages are available
for the day, or if the: MDA8 value rs greater than the level of the NAAQS. Finally, the O3 design value is calculated as the

11A variety of resources and guidance documents related to..identification and consideration .of exceptional events in design value calculations are
available at [littps://www.epa.gov/air-quality-analysis/final-2016-exceptioiial-events-rule-supporting-guidance-.documents-updated-faqs].

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3-year average of the annual 4th highest MDA8 value.12 An O3 design value less than or equal to the level of the NAAQS
is considered to be valid if valid MDA8 values are available for at least 90% of the days in the O3 monitoring season (as
defined for each State and shown in Figure 7) on average over the 3 years, with a minimum of 75% data completeness in any
individual year. Design values greater than the level of the NAAQS are always considered to be valid. The current level of
the O3 NAAQS is 70 ppb.

An O3 monitoring site meets the NAAQS if it has a valid design value less than or equal to the level of the standard, and
it exceeds the NAAQS if it has a design value greater than the level of the standard. A geographic area meets the NAAQS
if all ambient air monitoring sites in the area have valid design values meeting the standard. Conversely, if one or more
monitoring sites has a design value exceeding the standard, then the area exceeds the NAAQS.

6. O3 Concentrations Measured at Ambient Air Monitoring Sites Across the U.S.

Table 1 below presents summary statistics based on three daily O3 metrics commonly used in health studies, the
daily maximum 1-hour (MDA1) metric, the daily maximum 8-hour (MDA8) metric, and the daily 24-hour average (DA24)
metric. These statistics are presented for year-round and each season (winter=Dec/Jan/Feb, spring=Mar/Apr/May, sum-
mer=Jun/Jul/Aug, autumn=Sep/Oct/Nov) for monitors that have complete year-round data (defined as having at least 75%
data completeness based on a year-round O3 monitoring season) in AQS for 2020-2022. Table 2 presents the same summary
statistics as Table 1 for each NOAA Climate Region13 based on monitoring sites with at least 75% data completeness during
the May - September period (i.e., the months where every State is required to monitor for O3). Finally, Table 3 the same
set of summary statistics based on the May-September period for the three daily O3 metrics for four subsets of sites: urban
NCore and PAMS sites versus rural CASTNET sites, both in the eastern U.S. versus the in western U.S.14

Table 1 shows that the distribution of O3 concentrations observed in the U.S. in recent years is nearly symmetric: the mean
and median concentrations are within 2 ppb of each other for all combinations of metric and season. The highest median
and mean O3 concentrations generally occur in the spring and summer months, while the highest peak O3 concentrations
generally occur in the summer, and sometimes in the late spring or early fall when sunlight and temperature conditions
are most favorable to O3 production. Winter O3 concentrations are generally lower, except for sporadic episodes occurring
in mountain basins in the western U.S. under the right conditions as noted in section 2. Fewer low O3 concentrations are
observed in the spring, when background O3 concentrations tend to be highest.

Table 1. National distribution of O3 concentrations in ppb from the year-round dataset for 2020-2022.15 Source: AQS.

metric

season

N. sites

N.obs

mean

SD

min

Pi

p5

plO

p25

p50

p75

p90

p95

p98

p99

max

max.site

MDA1

all

764

808,052

45

14

-3

18

25

29

36

44

52

62

68

78

85

275

060570005

MDA1

winter

709

187,504

37

9

-3

14

22

26

32

38

43

48

51

54

57

275

060570005

MDA1

spring

754

204,480

48

10

0

24

32

36

42

48

54

60

65

72

77

146

080677003

MDA1

summer

745

201,918

50

16

0

19

25

30

39

50

60

71

78

88

95

179

300750001

MDA1

autumn

734

195,184

43

14

0

18

24

28

34

42

50

60

68

78

86

185

060371103

MDA8

all

764

805,491

40

12

-3

14

21

25

32

40

48

56

61

68

73

139

060710005

MDA8

winter

707

186,593

33

9

-3

10

18

22

28

34

40

44

47

50

52

93

060570005

MDA8

spring

753

203,630

44

10

0

21

28

32

38

44

50

56

59

64

68

116

060714003

MDA8

summer

744

201,029

45

15

0

16

22

25

34

45

55

63

68

76

81

139

060710005

MDA8

autumn

730

193,810

38

12

0

14

20

24

30

37

45

54

60

67

73

138

060370016

DA24

all

764

808,052

30

10

-4

8

14

17

23

30

38

44

48

52

56

102

060570005

DA24

winter

709

187,504

26

9

-4

5

10

13

19

26

33

38

41

44

46

62

560350099

DA24

spring

754

204,480

35

8

-2

16

21

24

30

35

41

45

48

52

55

81

060714003

DA24

summer

745

201,918

33

11

0

11

15

18

24

33

41

48

52

57

60

102

060570005

DA24

autumn

734

195,184

28

10

-1

8

13

16

21

27

34

40

44

49

53

100

490037001

N.sites = number of sites; N.obs = number of observations; SD = standard deviation; min = minimum; pi, p5, plO, p25,
p50, p90, p95, p98, p99 = 1st, 5th, 10th, 25th, 50th, 90th, 95th, 98th, 99th percentiles; max = maximum; max.site = AQS ID
number for the monitoring site corresponding to the observation in the max column, winter = December/January/February;
spring = March/April/May; summer = June/July/August; autumn = September/October/November.

12Design values are reported ill ppm to the third decimal place, with additional digits truncated. This truncation step also applies to the initially
calculated 8-hour average concentrations.

13 For Table 2, monitoring sites in Alaska were assigned to the Northwest Region and monitoring sites in Hawaii were assigned to the West region.

14For Table 3, the eastern U.S. is defined as east of 100 degrees West longitude and the western U.S. is defined as west of 100 degrees West
longitude.

15 Negative concentration values may appear in AQS datasets down to the negative of the lower detection limit (LDL) to allow for normal
instrument variability at very low concentrations. Data that exceed the negative of the LDL is typically indicative of a malfunction or another
issue that affects the data defensibility.

11


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Table 2 shows that the Southwest region typically measures the highest mean and median O3 concentrations during the
May-September period, while the highest peak O3 concentrations are typically measured in California, in the West region.
The distributions in the five eastern and central U.S. regions are all fairly similar, with the lowest concentrations occurring
in the Southeast region. According to Table 3, the median and mean May-September MDA1 and MDA8 O3 concentrations
are roughly 10 ppb higher in the western U.S. than in the eastern U.S, with even greater differences seen in the upper tail of
the distribution. In the eastern U.S., MDA1 and MDA8 O3 concentrations in the lower half of the distribution tend to be
similar across rural and urban areas, while concentrations in the upper half of the distribution tend to be higher in urban
areas. In the Western U.S., MDA1 and MDA8 O3 concentrations in the lower half of the distribution tend to be higher in
rural areas, while concentrations in the upper half of the distribution tend to be higher in urban areas. This pattern reflects
the compression of the O3 distribution with lower levels of precursor emissions as noted in Section 2. Meanwhile, the DA24
metric tends to be higher in rural areas than in urban areas across the full distribution, owing to the tendency for more
nighttime O3 titration to occur in areas with higher precursor emissions.

Table 2. National distribution of O3 concentrations in ppb from the May-September dataset for 2020-2022.15 Source: AQS.

metric

region

N.sites

N.obs

mean

SD

min

Pi

p5

plO

p25

p50

p75

p90

p95

p98

p99

max

max.site

MDA1

all

1,141

513,S16

49

15

-4

20

2T

31

39

4S

5T

66

T3

S3

90

190

04021T030

MDA1

Central

ITS

S0,T45

4S

11

0

25

31

34

40

4T

55

63

6T

T3

TS

115

2951000S5

MDA1

East North Central

ST

3S,952

46

12

3

21

2S

31

3S

46

54

62

6S

T4

T9

11S

260050003

MDA1

Northeast

ITS

T9,990

46

13

0

20

27

31

3T

45

53

62

6T

T5

SI

144

230112001

MDA1

Northwest

2T

11,92S

43

13

0

19

25

2S

35

42

51

60

66

T3

TS

110

410050004

MDA1

South

134

59,944

45

15

-4

IS

23

26

35

45

54

64

TO

TS

S4

135

201T30010

MDA1

Southeast

191

S6,462

42

12

0

19

23

26

33

42

50

5T

61

6T

TO

134

120550003

MDA1

Southwest

120

54,055

59

11

2

35

43

4T

52

5S

65

T4

T9

S6

91

190

04021T030

MDA1

West

ITS

SO,163

56

19

0

19

2S

33

43

55

6T

SO

S9

100

109

1S5

0603T1103

MDA1

West North Central

4S

21,5TT

50

10

4

26

34

3S

44

50

56

62

66

T1

T4

1T9

300T50001

MDAS

all

1,141

512,1T5

43

13

0

IT

23

27

34

43

52

60

65

72

77

139

060T10005

MDAS

Central

ITS

S0,49T

43

11

0

21

27

30

36

43

50

5T

61

66

TO

100

2951000S5

MDAS

East North Central

ST

3S,901

42

11

1

IS

24

2S

34

41

49

5T

62

6T

T1

104

550590019

MDAS

Northeast

ITS

T9,564

41

11

0

IT

23

2T

33

40

4S

55

60

65

69

99

090019003

MDAS

Northwest

2T

11,ST4

39

11

0

15

21

25

31

3S

46

54

5S

64

6S

96

530330023

MDAS

South

134

59,T42

40

13

0

15

20

23

30

40

49

5T

62

6T

T1

114

4S43900T5

MDAS

Southeast

191

S6,1S9

3T

11

0

16

20

22

2S

3T

45

52

55

60

62

93

131210055

MDAS

Southwest

120

53,93T

54

9

2

31

39

43

4S

54

60

66

TO

T5

T9

10S

040131004

MDAS

West

ITS

T9,95T

49

16

0

IT

25

30

39

49

59

69

T6

S4

90

139

060T10005

MDAS

West North Central

4S

21,514

46

10

3

22

30

34

40

46

52

5S

61

66

69

S9

560019991

DA24

all

1,141

513,S16

32

10

-4

11

16

19

24

32

39

46

50

55

5S

102

0605T0005

DA24

Central

ITS

S0,T45

31

s

0

14

IS

21

25

31

36

42

45

49

52

T6

1T031T002

DA24

East North Central

ST

3S,952

32

9

3

14

IS

21

26

32

3S

44

4S

52

56

T9

260050003

DA24

Northeast

ITS

T9,990

30

9

0

12

IT

19

24

30

36

41

45

49

52

T3

44009000S

DA24

Northwest

2T

11,92S

29

9

0

10

15

IS

22

2S

35

41

44

49

51

65

160230101

DA24

South

134

59,944

2S

10

-4

10

14

16

21

2S

35

42

45

49

52

T2

4S43900T5

DA24

Southeast

191

S6,462

26

9

0

10

13

15

19

25

32

3S

42

46

49

65

3T1990004

DA24

Southwest

120

54,055

42

S

2

22

2S

32

3T

42

4T

52

55

5S

61

TS

0S0590011

DA24

West

ITS

SO,163

36

11

0

13

19

22

2S

36

44

51

56

62

66

102

0605T0005

DA24

West North Central

4S

21,5TT

3T

9

2

16

23

26

32

3T

43

4S

52

56

5S

T6

560019991

N.sites = number of sites; N.obs = number of observations; SD = standard deviation; min = minimum; pi, p5, plO, p25,
p50, p90, p95, p98, p99 = 1st, 5th, 10th, 25th, 50th, 90th, 95th, 98th, 99th percentiles; max = maximum; max.site =
AQS ID number for the monitoring site corresponding to the observation in the max column. Central = Illinois, Indiana,
Kentucky, Missouri, Ohio, Tennessee, West Virginia; East North Central = Iowa, Minnesota, Michigan, Wisconsin; Northeast
= Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode
Island, Vermont; Northwest = Alaska, Idaho, Oregon, Washington; South = Arkansas, Kansas, Louisiana, Mississippi,
Oklahoma, Texas; Southeast = Alabama, Florida, Georgia, North Carolina, South Carolina, Virginia; Southwest = Arizona,
Colorado, New Mexico, Utah; West = California, Hawaii, Nevada; West North Central = Montana, Nebraska, North Dakota,
South Dakota, Wyoming.

12


-------
Table 3. Distribution of O3 concentrations in ppb from the May-September dataset by eastern vs. western U.S. and urban
vs. rural sites for 2020-2022.15 Source: AQS.

metric

region

site.type

N.sites

N.obs

mean

SD

min

Pi

p5

plO

p25

p50

p75

p90

p95

p98

p99

max

max.site

MDA1

All Sites

All Sites

1,141

513,816

49

15

-4

20

27

31

39

48

57

66

73

83

90

190

040217030

MDA1

Eastern U.S.

Urban

65

29,244

46

14

0

19

25

29

36

46

55

64

71

79

85

130

482011039

MDA1

Eastern U.S.

Rural

42

18,937

44

11

1

20

26

30

37

44

51

58

62

68

72

98

240339991

MDA1

Western U.S.

Urban

34

15,057

55

17

0

19

28

34

44

54

65

77

85

94

100

185

060371103

MDA1

Western U.S.

Rural

32

14,516

55

11

14

27

36

41

48

54

60

68

74

83

88

130

061070009

MDA8

All Sites

All Sites

1,141

512,175

43

13

0

17

23

27

34

43

52

60

65

72

77

139

060710005

MDA8

Eastern U.S.

Urban

65

29,157

41

13

0

16

21

24

32

41

49

57

62

68

72

102

484391002

MDA8

Eastern U.S.

Rural

42

18,839

40

11

1

17

22

26

32

40

47

53

58

62

65

84

171199991

MDA8

Western U.S.

Urban

34

15,003

49

14

0

16

25

30

39

49

58

67

72

79

83

118

060371103

MDA8

Western U.S.

Rural

32

14,469

51

11

12

24

32

37

45

51

57

63

68

75

79

114

061070009

DA24

All Sites

All Sites

1,141

513,816

32

10

-4

11

16

19

24

32

39

46

50

55

58

102

060570005

DA24

Eastern U.S.

Urban

65

29,244

29

9

0

11

15

17

22

29

35

41

45

48

51

71

170971007

DA24

Eastern U.S.

Rural

42

18,937

30

9

0

11

15

18

24

30

37

43

46

50

53

66

361099991

DA24

Western U.S.

Urban

34

15,057

35

10

0

12

18

22

28

35

41

47

50

54

57

75

060731006

DA24

Western U.S.

Rural

32

14,516

44

10

6

18

26

30

38

44

50

56

59

64

67

91

061070009

N.sites = number of sites; N.obs = number of observations; SD = standard deviation; min = minimum; pi, p5, plO, p25,
p50, p90, p95, p98, p99 = 1st, 5th, 10th, 25th, 50th, 90th, 95th, 98th, 99th percentiles; max = maximum; max.site = AQS
ID number for the monitoring site corresponding to the observation in the max column. Region is defined such that the
eastern U.S. includes sites east of 100 degrees west longitude and the western U.S. includes sites west of 100 degrees west
longitude; site.type = Urban includes Urban NCore and PAMS sites; Site.type = Rural includes GASTNET sites.

Figure 8 below shows a map of the O3 design values at U.S. ambient air monitoring sites based on data from the 2020-2022
period. From the figure it is apparent that many monitoring sites have design values exceeding the current NAAQS, and
that most of these sites are located in or near urban areas. The highest design values occurred in California, Texas, along
the shoreline of Lake Michigan, and near large urban areas in the northeastern and western U.S. There are also high design
values associated with wintertime O3 in the Uinta Basin in Utah. The lowest design values occurred in the north central
region of the U.S., rural parts of New England and the southeastern U.S., and along the Pacific Ocean, including Alaska and
Hawaii.

• 32-60 ppb (316 sites) o 66-70 ppb (215 sites) • 76- 84 ppb (76 sites)
o 61-65 ppb (336 sites) o 71-75 ppb (104 sites) • 85-113 ppb (25 sites)

Figure 8: O3 design values in ppb for the 2020-2022 period. Source: AQS.

13


-------
Figure 9 below shows a map of the site-level trends in the O3 design values at U.S. monitoring sites having valid design
values in at least 16 of the 21 3-year periods from 2000 through 2022. The trends were computed using the Thiel-Sen
estimator, and tests for significance (p-value < 0.05) were computed using the Mann-Kendall test. From this figure it is
apparent that design values have decreased significantly over most of the eastern U.S. during this period. These decreases are
in part due to EPA programs such as the Glean Air Interstate Rule (GAIR) and the Gross-State Air Pollution Rule (GSAPR)
with the goal of achieving broad, regional reductions in summertime NOx emissions, as well as mobile emission reductions
from federal motor vehicle emissions and fuel standards and local controls resulting from implementation of the existing O3
standards. Other areas of the country have also experienced decreases in design values, most notably in California and near
urban areas in the inter mountain west.

V Decreasing < 1 ppb/yr(271 sites) A Increasing < 1 ppb/yr(9 sites)

Figure 9: Site-level trends in O3 design values based on data from 2000 through 2022. Source: AQS, trends computed
using R statistical software.

14


-------
Figure 10 below shows the national trend in the design values based on the 781 monitoring sites shown in Figure 9. The
U.S. median design value decreased by 26% from 2000 (86 ppb) to 2022 (64 ppb). Additional information from the published
literature has examined trends in MDA8 concentrations across the distribution of high and low O3 days. O3 metrics impacted
by high hourly O3 concentrations, such as the design value, decreased at most U.S. sites during the time periods studied.
Concurrently, metrics that are impacted by averaging longer time periods of hourly O3 measurements were more varied with
fewer sites exhibiting decreases and most other sites exhibiting no trend.

— 10th/90th Percentile 8-hour DV
Median 8-hour DV

O t- CM
000
000
CM CM CM

Figure 10: National trend in O3 design values in ppb, 2000 to 2022. Source: AQS.

15


-------
Figure 11 below shows the national distribution ol the annual 4th highest MDA8 O3 concentrations reported in each
year from 1980 to 2022.16 The red line shows the number ol sites included in the boxplot lor each year. The median annual
4th highest MDA8 O3 concentration decreased by 31%, from 93 ppb in 1980 to 64 ppb in 2022. While the magnitude ol
the highest O3 concentrations declined between 1980 and the early 2000s, the center ol the distribution stayed relatively
constant, with over 75% ol sites measuring annual 4th highest MDA8 O3 concentrations above the current NAAQS level.
Since 2003, regional control programs such as the NOx SIP Gall and GSAPR have contributed to reduced concentrations
over the eastern U.S., so that roughly 75% ol all sites have been meeting the NAAQS each year since 2013. The size ol the
O3 monitoring network increased from 1980 through the early 2000s and has stayed relatively constant at around 1,200 sites
since then.

250

1500

I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

OOOOOOOOOOOOOOOOOOOOCT)CT)CT)CT)CT)CT)CT)CT)CT)CT)OOOOOOOOOOt-t-t-t-t-t-t-t-t-t-(M(M(M
0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)00000000000000000000000
t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-t-CMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCMCM

Figure 11: Distribution ol annual 4th highest MDA8 O3 concentrations measured at U.S. monitoring sites, 1980 to 2022.
Boxes represent the median and interquartile range, whiskers extend to the 1st and 99th percentiles, and values outside
this range are shown as circles. The red line shows the number ol O3 monitoring sites reporting data to EPA in each year.
Source: AQS.

16For this analysis, the annual 4t.li highest MDA8 O3 concentrations were retrieved from AQS for all U.S. sites for years that had at least 75%
annual data completeness during the O3 monitoring season.

16


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References

U.S. EPA. Integrated Science Assessment for Ozone and Related Photochemical Oxidants (Final Report, April 2020). U.S.
Environmental Protection Agency, Washington, DC, EPA/600/R-20/012, 2020.

U.S. EPA. Policy Assessment for the Review of the Ozone NAAQS (Final Report, May 2020). U.S. Environmental Protection
Agency, Research Triangle Park, NG, EPA-452/R-20-001, 2020.

Additional Resources

•	Ground-level Ozone Pollution

•	Ozone (O3) Air Quality Standards

•	National Emissions Inventory (NEI)

•	Ambient Monitoring Technology Information Center (AMTIG)

•	Air Quality Design Values

•	National Air Quality: Status and Trends of Key Air Pollutants

•	Air Data: Air Quality Data Collected at Outdoor Monitors Across the U.S.

17


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