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CHAPTER 2: DEFINING THE OZONE AIR QUALITY PROBLEM

Overview

This section provides overviews of ozone precursor emissions and atmospheric chemistry 

(section 2.1); ambient ozone concentrations (section 2.2); ambient ozone monitoring in the U.S. 

(section 2.3); and available evidence and information related to background ozone (section 2.4).

2.1 Emissions and Atmospheric Chemistry

Ozone is formed through photochemical reactions of precursor gases and is not directly 

emitted from specific sources. In the stratosphere, ozone occurs naturally and provides protection 

against harmful solar ultraviolet radiation. In the troposphere, near ground level, ozone forms 

through atmospheric reactions involving two main classes of precursor pollutants: volatile 

organic compounds (VOCs) and nitrogen oxides (NOX). Carbon monoxide (CO) and methane 

(CH4) are also important for ozone formation over longer time periods (US EPA, 2013, section 

3.2.2).

Emissions of ozone precursor compounds can be divided into anthropogenic and natural 

source categories, with natural sources further divided into biogenic emissions (from vegetation, 

microbes, and animals) and abiotic emissions (from biomass burning, lightning, and geogenic 

sources). Anthropogenic sources, including mobile sources and power plants, account for the 

majority of NOX and CO emissions. Anthropogenic sources are also important for VOC 

emissions, though in some locations and at certain times of the year (e.g., southeastern states 

during summer) the majority of VOC emissions comes from vegetation (US EPA, 2013, section 

3.2.1). In practice, the distinction between natural and anthropogenic sources is often unclear, as 

human activities may directly or indirectly affect emissions from what would have been 

considered natural sources during the preindustrial era. Thus, 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 (US EPA, 2013, sections 3.2 and 3.7.1).
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Rather than varying directly with emissions of its precursors, ozone changes in a nonlinear 

fashion with the concentrations of its precursors. NOX emissions lead to both the formation and 

destruction of ozone, depending on the local quantities of NOX, VOC, free radicals, and sunlight. 

In areas dominated by fresh emissions of NOX, radicals are removed, which lowers the ozone

formation rate. In addition, the scavenging of ozone by reaction with NO is called “titration” and 

is often found in downtown metropolitan areas, especially near busy streets and roads, as well as 

in power plant plumes. This short-lived titration results in localized areas in which ozone

concentrations are suppressed compared to surrounding areas, but which contain NO2 that 

contributes to subsequent ozone formation further downwind. The NOx titration effect is most 

pronounced in urban core areas that have a high volume of mobile source NOx emissions from 

vehicles. In areas with relatively low NOX concentrations, such as those found in remote 

continental areas and rural and suburban areas downwind of urban centers, ozone production 

typically responds linearly to NOX concentrations (e.g., ozone decreases with decreasing NOX

emissions). Consequently, ozone response to reductions in NOX emissions is complex and may 

include ozone decreases at some times and locations and increases of ozone at other times and 

locations. As a general rule, as NOx emissions reductions occur, you can expect lower ozone

values to increase while the higher ozone values would be expected to decrease. NOx reductions 

are expected to result in a compressed ozone distribution, relative to current conditions (EPA, 

2014a).

The formation of ozone from precursor emissions is also affected by meteorological 

parameters such as the intensity of sunlight and atmospheric mixing. Major episodes of high

ground-level ozone concentrations in the eastern United States are often associated with slowmoving high pressure systems. 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 that inhibit or 

reduce the vertical mixing of ozone precursors. The combination of inhibited vertical mixing and 

light winds minimizes the dispersal of pollutants, allowing their concentrations to build up. In 

addition, in some parts of the United States (e.g., in Los Angeles), mountain barriers limit mixing 

and result in a higher frequency and duration of days with elevated ozone concentrations. 

Photochemical activity involving precursors is enhanced during warmer seasons because of the 

greater availability of sunlight and higher temperatures (US EPA, 2013, section 3.2).
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Elevated wintertime ozone concentrations have recently been measured in mountain 

valleys in the Western U.S. (Schnell et al, 2009; Rappengluck et al., 2014; Helmig et al., 2014). 

Hourly ozone concentrations during these winter events have been observed to reach 160 ppb. 

This phenomenon is believed to result from the combination of several factors: 1) strong 

wintertime inversions or “cold pools”, which trap air in a shallow layer close to the ground, 2) 

substantial emissions of NOx and VOC from nearby oil and gas operations, 3) high albedo of 

deep snow, which leads to enhanced UV intensity and photochemical activity, and 4) possible 

uncharacterized sources of radicals. These wintertime ozone events have currently only been 

observed in a limited number of locations in Wyoming, Utah, and Colorado. Events can last for 

multiple days and can occur several times a year, but do not occur every winter in these 

locations.

Ozone concentrations in a region are affected both by local formation and by transport of 

ozone and its precursors from upwind areas. Ozone transport occurs on many spatial scales 

including local transport between cities, regional transport over large regions of the U.S. and 

international/long-range transport. In addition, ozone can be transferred into the troposphere 

from the stratosphere, which is rich in ozone, through stratosphere-troposphere exchange (STE).

These intrusions usually occur behind cold fronts, bringing stratospheric air with them and 

typically affect ozone concentrations in higher elevation areas (e.g. > 1500 m) more than areas at 

lower elevations (U.S. EPA, 2013, section 3.4.1.1). The role of long-range transport of ozone and 

other elements of ozone background are discussed in more detail in Section 2.4.

2.2 Spatial and Temporal Variations in Ambient Ozone Concentrations

Because ozone is a secondary pollutant formed in the atmosphere from precursor 

emissions, concentrations are generally more regionally homogeneous than concentrations of 

primary pollutants emitted directly from stationary and mobile sources (US EPA, 2013, section 

3.6.2.1). However, variation in local emissions characteristics, meteorological conditions, and 

topography can result in daily and seasonal temporal variability in ambient ozone concentrations, 

as well as local and national-scale spatial variability.

Temporal variation in ambient ozone concentrations results largely from daily and seasonal 

patterns in sunlight, precursor emissions, atmospheric stability, wind direction, and temperature 
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(US EPA, 2013, section 3.7.5). On average, ambient ozone concentrations follow wellrecognized daily and seasonal patterns, particularly in urban areas. Specifically, daily maximum 

1-hour ozone concentrations in urban areas tend to occur in mid-afternoon, with more 

pronounced peaks in the warm months of the ozone season than in the colder months (US EPA, 

2013, Figures 3-54, 3-156 to 3-157). Rural sites also follow this general pattern, though it is less 

pronounced in colder months (US EPA, 2013, Figure 3-55). With regard to day-to-day 

variability, median maximum daily 8-hour average (MDA8) ozone concentrations in U.S. cities 

from 2007 through 2009 were approximately 47 ppb, with typical ranges between 35 to 60 ppb 

and the highest MDA8 concentrations above 100 ppb in several U.S. cities (as noted further 

below).

In addition to temporal variability, there is considerable spatial variability in ambient 

ozone concentrations within cities and across different cities in the United States. With regard to 

spatial variability within a city, local emissions characteristics, geography, and topography can 

have important impacts. For example, as noted above, fresh NO emissions from motor vehicles 

titrate ozone present in the urban background air, resulting in an ozone gradient around roadways

with ozone concentrations increasing as distance from the road increases (US EPA, 2013, section 

3.6.2.1). Measured ozone concentrations are relatively uniform and well-correlated within some 

cities (e.g., Atlanta) while they are more variable in others (e.g., Los Angeles) (US EPA, 2013, 

section 3.6.2.1 and Figures 3-28 to 3-36). 

Ozone concentrations also vary considerably across cities. Several cities had very high 

measured ozone concentrations in 2007 through 2009 when the maximum recorded MDA8 was 

137 ppb in Los Angeles, and was near or above 120 ppb in Atlanta, Baltimore, Dallas, New York 

City, Philadelphia, and St. Louis (US EPA, 2013, Table 3-10). These same cities also had high 

98th percentile ozone concentrations, with Los Angeles recording the highest 98th percentile 

concentration (91 ppb) and many eastern and southern cities reporting 98th percentile 

concentrations near or above 75 ppb. In contrast, somewhat lower 98th percentile ozone 

concentrations were recorded in cities in the western United States outside of California (US 

EPA, 2013, Table 3-10).
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Rural sites can be affected by transport of ozone or ozone precursors from upwind urban 

areas and by local anthropogenic sources such as motor vehicles, power generation, biomass 

combustion, or oil and gas operations (US EPA, 2013, section 3.6.2.2). In addition, ozone tends 

to persist longer in rural than in urban areas due to lower rates of chemical scavenging in nonurban environments. At higher elevations, increased ozone concentrations can also result from 

stratospheric intrusions (US EPA, 2013, sections 3.4, 3.6.2.2). As a result, ozone concentrations 

measured in some rural sites can be higher than those measured in nearby urban areas (US EPA, 

2013, section 3.6.2.2).

2.3 Ozone Monitoring

2.3.1 Ozone Monitoring Network

To monitor compliance with the National Ambient Air Quality Standards (NAAQS), state 

and local environmental agencies operate ozone monitoring sites at various locations, depending 

on the population of the area and typical peak ozone concentrations.1 All of the state and local 

monitoring stations that report data to the EPA Air Quality System (AQS) use ultraviolet (UV) 

Federal Equivalent Methods (FEMs). In 2013, there were over 1,300 state, local, and tribal ozone

monitors reporting concentrations to EPA. The “State and Local Monitoring Stations” (SLAMS)

minimum monitoring requirements to meet the ozone design criteria are specified in 40 CFR Part 

58, Appendix D. The requirements are both population and design value based.

2 The minimum 

number of ozone monitors required in a Metropolitan Statistical Area (MSA) ranges from zero 

for areas with a population of at least 50,000 and under 350,000 with no recent history of an 

ozone design value greater than 85 percent of the NAAQS, to four for areas with a population 

greater than 10 million and an ozone design value greater than 85 percent of the NAAQS. At

least one site for each MSA, or Combined Statistical Area (CSA), must be sited to record the 

maximum concentration for that particular metropolitan area. Since highest ozone concentrations 

 

1 The minimum ozone monitoring network requirements for urban areas are listed in Table D-2 of Appendix D to 40 

CFR Part 58.

2 A design value is a statistic that describes the air quality status of a given area relative to the level of the NAAQS. 

Design values are typically used to classify nonattainment areas, assess progress towards meeting the NAAQS, 

and develop control strategies. See http://epa.gov/airtrends/values.html (U, 2010, 677582) for guidance on how 

these values are defined.
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tend to be associated with particular seasons for various locations, EPA requires ozone 

monitoring during specific ozone monitoring seasons, which vary by state.

3

Figure 2-1 shows the locations of the U.S. ambient ozone monitoring sites reporting data to 

EPA at any time during the 2009-2013 period. The gray dots that make up over 80% of the 

ozone monitoring network are SLAMS monitors, which are operated by state and local 

governments to meet regulatory requirements and provide air quality information to public health 

agencies. Thus, the SLAMS monitoring sites are largely focused on urban and suburban areas. 

The blue dots highlight two important subsets of monitoring sites within the SLAMS network: 

the “National Core” (NCore) multi-pollutant monitoring network and the “Photochemical 

Assessment Monitoring Stations” (PAMS) network.

While the existing U.S. ozone monitoring network has a largely urban focus, to address 

ecosystem impacts of ozone, such as biomass loss and foliar injury, it is equally important to 

focus on ozone monitoring in rural areas. The green dots in Figure 2-1 represent the Clean Air 

Status and Trends Network (CASTNET) monitors, which are located in rural areas. There were 

about 80 CASTNET sites operating in 2013, with sites in the eastern U.S. being operated by 

EPA and sites in the western U.S. being operated by the National Park Service (NPS).4In total, 

there were about 120 rural ozone monitoring sites operating in the U.S. in 2013.

 

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

Revised monitoring seasons are being proposed along with the proposed revision of the ozone NAAQS level.

4 Additionally, the black dots represent “Special Purpose Monitoring Stations” (SPMS), which include about 20 

rural monitors as part of the “Portable O3 Monitoring System” (POMS) network operated by the NPS.
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Figure 2-1. Map of U.S. Ambient O3 Monitoring Sites Reporting Data to EPA During the 

2009-2013 Period

2.3.2 Recent Ozone Monitoring Data and Trends

To determine whether or not the ozone NAAQS has been met at an ambient monitoring 

site, a statistic commonly referred to as a “design value” must be calculated based on three 

consecutive years of data collected from that site. The form of the existing ozone NAAQS design 

value (DV) statistic is the 3-year average of the annual 4th highest daily maximum 8-hour ozone 

concentration in parts per billion (ppb), with decimal digits truncated. The existing primary and 

secondary ozone NAAQS are met at an ambient monitoring site when the DV is less than or 

equal to 75 ppb.5In counties or other geographic areas with multiple monitoring sites, the areawide DV is defined as the DV at the highest individual monitoring site, and the area is said to 

have met the NAAQS only if all monitoring sites in the area are meeting the NAAQS.

Figure 2-2 shows the trend in the annual 4th highest daily maximum 8-hour ozone 

concentrations in ppb based on 910 “trends” sites with complete data records over the 2000 to 

 

5 For more details on the data handling procedures used to calculate design values for the existing ozone NAAQS, 

see 40 CFR Part 50, Appendix P.
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2013 period. The center line in this figure represents the median value across the trends sites, 

while the dashed lines represent the 25th and 75th percentiles, and the bottom and top lines 

represent the 10th and 90th percentiles. Figure 2-3 shows a map of the ozone DVs (in ppb) 

averaged across the 2009-2011, 2010-2012, and 2011-2013 periods at all monitoring sites in the 

contiguous U.S.6 The trend figure shows that the annual 4th highest daily maximum values 

decreased for the vast majority of monitoring sites in the U.S. between 2000 and 2013. The 

decreasing trend is especially sharp from 2002 to 2004, when EPA implemented the “NOX SIP 

Call”, a program designed to reduce summertime emissions of NOX in the eastern U.S., but has 

continued to decrease since then, in part due to ongoing reductions in mobile source NOx 

emissions. Within the overall downward trend, there are periodic short-term increases. These 

variations from the overall trend are the result of inter-annual variability in meteorological 

conditions.

Figure 2-2. Trend in U.S. Annual 4th Highest Daily Maximum 8-hour Ozone 

Concentrations in ppb, 2000 to 2013. Solid center line represents the median 

value across monitoring sites, dashed lines represent 25th and 75th percentile 

values, and top/bottom lines represent 10th and 90th percentile values.

 

6 All monitoring sites in Alaska, Hawaii, and Puerto Rico had DVs below 60 ppb.
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Figure 2-3. Map of 8-hour Ozone Design Values in ppb, Averaged Across the 2009-2011, 

2010-2012, and 2011-2013 Periods

In addition to the DV described above, another ozone metric of interest is the W126 index 

value, which has been found to correlate with ozone-related damage to plants and ecosystems 

(EPA, 2014c). The W126 metric is a seasonal aggregate of daytime (8:00 AM to 8:00 PM) 

hourly ozone concentrations designed to measure the cumulative effects of ozone exposure on 

plant and tree species, with units in parts per million-hours (ppm-hrs). The W126 metric uses a 

logistic weighting function to place less emphasis on exposure to low hourly ozone 

concentrations and more emphasis on exposure to high hourly ozone concentrations (Lefohn et 

al, 1988). 

Figure 2-4 shows the trend in annual W126 concentrations in ppm-hrs based on 900 

“trends” sites with complete data records over the 2000 to 2013 period. The center line in this 

figure represents the median value across the trends sites, while the dashed lines represent the 

25th and 75th percentiles, and the bottom and top lines represent the 10th and 90thpercentiles. 

Figure 2-5 shows a map of the 3-year average annual W126 concentrations in ppm-hrs averaged 

across the 2009-2011, 2010-2012, and 2011-2013 periods at all monitoring sites in the 
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contiguous U.S. The general patterns seen in these figures are similar to those seen in the DV 

metric for the existing standard.

Figure 2-4. Trend in U.S. Annual W126 Concentrations in ppm-hrs, 2000 to 2013. Solid 

center line represents the median value across monitoring sites, dashed lines 

represent 25th and 75th percentile values, and top/bottom lines represent 10th 

and 90th percentile values.
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Figure 2-5. Map of 3-year Average W126 Values in ppm-hrs, Averaged Across the 2009-

2011, 2010-2012, and 2011-2013 Periods

2.4 Background Ozone 

One of the aspects of ozone that is unusual relative to the other pollutants with NAAQS is 

that, periodically, in some locations, an appreciable fraction of the observed ozone results from 

sources or processes other than local and domestic regional anthropogenic emissions of ozone

precursors (Fiore et al., 2002). Any ozone formed by processes other than the chemical 

conversion of local or regional ozone precursor emissions is generically referred to as 

“background” ozone. Background ozone can originate from natural sources of ozone and ozone

precursors, as well as from manmade international emissions of ozone precursors. Natural 

sources of ozone precursor emissions such as wildfires, lightning, and vegetation can lead to 

ozone formation by chemical reactions with other natural sources. Another important component 

of background is ozone that is naturally formed in the stratosphere through interactions of 

ultraviolet light with molecular oxygen. Stratospheric ozone can mix down to the surface at high 

concentrations in discrete events called intrusions, especially at higher-altitude locations. The 
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manmade portion of the background includes any ozone formed due to anthropogenic sources of 

ozone precursors emitted far away from the local area (e.g., international emissions). Finally, 

both biogenic and international anthropogenic emissions of methane, which can be chemically 

converted to ozone over relatively long time scales, can also contribute to global background 

ozone levels. Away from the surface, ozone can have an atmospheric lifetime on the order of 

weeks. As a result, background ozone can be transported long distances in the upper troposphere 

and, when meteorological conditions are favorable, be available to mix down to the surface and 

add to the ozone loading from non-background sources. 

The definition of background ozone can vary depending upon context, but it generally 

refers to ozone that is formed by sources or processes that cannot be influenced by actions within 

the jurisdiction of concern. In the Policy Assessment for the Review of the Ozone National 

Ambient Air Quality Standards (US EPA, 2014c), EPA identified three specific definitions of 

background ozone: natural background (NB), North American background (NAB), and United 

States background (USB). Natural background is the narrowest definition of background, and it 

is defined as the ozone that would exist in the absence of any manmade ozone precursor 

emissions. The other two definitions of background are based on a presumption that the U.S. has 

little influence over anthropogenic emissions outside either our continental or domestic borders.

North American background is defined as that ozone that would exist in the absence of any 

manmade ozone precursor emissions from North America. U.S. background is defined as that 

ozone that would exist in the absence of any manmade emissions inside the United States.

Modeling studies have estimated what background levels would be in the absence of 

certain sets of emissions by simply assessing the remaining ozone in a simulation in which 

certain emissions were removed (Zhang et al. (2011), Emery et al. (2012), US EPA (2014c)).

This basic approach is often referred to as “zero-out” modeling or “emissions perturbation” 

modeling. While the zero-out approach has traditionally been used to estimate natural 

background, North American background, and U.S. background, the methodology has an

acknowledged limitation. It cannot answer the question of how much of the existing observed 

ozone results from background sources or processes.
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A separate modeling technique can be used to estimate the contribution of background 

ozone and other contributing source terms to total ozone within a model. This approach, referred 

to as “source apportionment” modeling, has been described and evaluated in the peer-reviewed 

literature (Dunker et al., 2002; Kemball-Cook et al., 2009). Source apportionment modeling has 

frequently been used in other regulatory settings to estimate the “contribution” to ozone of 

certain sets of emissions (EPA 2005, EPA 2011). The source apportionment technique provides a 

means of estimating the contributions of each user-identified source category to ozone formation 

in a single model simulation. This is achieved by using multiple tracer species to track the fate of 

ozone precursor emissions (VOC and NOX) and the ozone formation resulting from these 

emissions. The methodology is designed so that all ozone and precursor concentrations are 

tracked and apportioned to the selected source categories at all times without perturbing the 

inherent chemistry. The primary limitation of the source apportionment modeling is that its 

estimations of background ozone are explicitly linked to the emissions scenarios modeled and 

would change with different emissions scenarios. 

2.4.1 Seasonal Mean Background Ozone in the U.S.

The ISA (US EPA 2013, section 3.4) previously established that background ozone

concentrations vary spatially and temporally and that simulated mean background concentrations 

are highest at high-elevation sites within the western U.S. Background levels typically are 

greatest over the U.S. in the spring and early summer. EPA modeling presented in the Policy 

Assessment for the Review of the Ozone National Ambient Air Quality Standards (US EPA, 

2014c) focused on the months from April to October for 2007 (note that the 2007 modeling is 

separate from the 2011 modeling described in Chapter 3 and used as the basis of cost and benefit 

numbers in this RIA). Emissions and model set-up for the 2007 analysis are described in more 

detail in the Policy Assessment. Briefly, the emissions for 2007 were derived from the 2008 

National Emissions Inventory but included 2007 year-specific emissions where available. Fire 

emissions were based on a multi-year climatological average as this analysis was mean to 

capture seasonal mean background and typical ranges rather than explicitly quantify background 

ozone on specific days. Figure 2-6 displays the spatial patterns of seasonal mean natural 

background ozone as estimated by a 2007 zero-out scenario using the Community Multiscale Air 

Quality (CMAQ) model. Seasonal means are computed over those seven months. This figure 
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shows the average daily maximum 8-hour ozone concentration that would exist in the absence of 

any anthropogenic ozone precursor emissions at monitor locations. As shown, seasonal mean NB 

levels range from approximately 15-35 ppb (i.e., +/- 1 standard deviation) with the highest values 

at higher-elevation sites in the western U.S. The median value over these locations is 24.2 ppb, 

and more than 50 percent of the locations have natural background levels of 20-25 ppb. The 

highest modeled estimate of seasonal average, natural background, 8-hr daily maximum ozone is 

34.3 ppb at the high-elevation CASTNET site (Gothic) in Gunnison County, CO. Natural 

background ozone levels are higher at these high-elevation locations primarily because of natural 

stratospheric ozone impacts and international transport impacts that increase with altitude (where 

ozone lifetimes are longer).

Figure 2-6. Map of 2007 CMAQ-estimated Seasonal Mean of 8-hour Daily Maximum 

Ozone from Natural Background (ppb) based on Zero-Out Modeling

Figures 2-7 and 2-8 show the same information for the NAB and USB scenarios. In these 

model runs, all anthropogenic ozone precursor emissions were removed from the U.S., Canada, 

and Mexico portions of the modeling domain (NAB scenario) and then only from the U.S. (USB 

scenario). The figures show that there is not a large difference between the NAB and USB 

scenarios. Seasonal mean NAB and USB ozone levels range from 25-50 ppb, with the most 

frequent values estimated in the 30-35 ppb range. The median seasonal mean background levels 

are 31.5 and 32.7 ppb (NAB and USB, respectively). Again, the highest levels of seasonal mean 

background ozone are predicted over the intermountain western U.S. Locations with NAB and 
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USB concentrations greater than 40 ppb are confined to Colorado, Nevada, Utah, Wyoming, 

northern Arizona, eastern California, and parts of New Mexico. The 2007 EPA modeling 

suggests that seasonal mean USB concentrations are on average 1-3 ppb higher than NAB 

background. These results were similar to those reported by Wang et al. (2009). From a seasonal 

mean perspective, background ozone levels are typically well-below the NAAQS thresholds.

Figure 2-7. Map of 2007 CMAQ-estimated Seasonal Mean of 8-hour Daily Maximum 

Ozone from North American Background (ppb) based on Zero-out Modeling

Figure 2-8. Map of 2007 CMAQ-estimated Seasonal Mean of 8-hour Daily Maximum 

Ozone from United States Background (ppb) based on Zero-Out Modeling
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2.4.2 Seasonal Mean Background Ozone in the U.S. as a Proportion of Total Ozone

Another informative way to assess the importance of background ozone as part of

seasonal mean ozone levels across the U.S. is to consider the ratios of NB, NAB, and USB to 

total modeled ozone at each monitoring location. Considering the proportional impact of 

background ozone allows for an initial assessment of the relative importance of background and 

non-background sources. Because ozone chemistry is non-linear, one should not assume that 

individual perturbations (e.g., zero-out runs) are additive in all locations. Figures 2-9 and 2-10 

show the ratio of U.S. background to total ozone using the metric of the seasonal mean 8-hr daily 

maximum ozone concentrations as estimated by both the zero-out and source apportionment 

modeling methodologies. Recall that the terms NB, NAB, and USB are explicitly linked to the 

zero-out modeling approach. For comparison, in Figure 2-101 we are extending the definition of 

USB to also include the source apportionment model estimates of the ozone that are attributable 

to sources other than U.S. anthropogenic emissions. To preserve the original definition of USB, 

this second term will be hereafter referred to as “apportionment-based USB”. As noted earlier, 

the advantage of the source apportionment modeling is that all of the modeled ozone is attributed 

to various source terms without perturbing the inherent chemistry. Thus, this approach is not 

affected by the confounding occurrences of background ozone values exceeding the base ozone

values as can happen in the zero-out modeling (i.e., background proportions > 100%).

Consequently, one would expect the fractional background levels to be lower in the source 

apportionment methodology as a result of removing this artifact.

When averaged over all sites, ozone from sources other than U.S. anthropogenic 

emissions is estimated to comprise 66 (zero-out) and 59 (source apportionment) percent of the 

total seasonal ozone mean. The spatial patterns of USB and apportionment-based USB are 

similar across the two modeling exercises. Background ozone is a relatively larger percentage 

(e.g., 70-80%) of the total seasonal mean ozone in locations within the intermountain western 

U.S. and along the U.S. border. In locations where ozone levels are generally higher, like 

California and the eastern U.S., the seasonal mean background fractions are relatively smaller 

(e.g., 40-60%). The additional 2007 modeling confirms that background ozone, while generally 

not approaching levels of the ozone standard, can comprise a considerable fraction of total 

seasonal mean ozone across the U.S (EPA, 2014c).
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2.4.3 Daily Distributions of Background Ozone within the Seasonal Mean

As a first-order understanding, it is valuable to be able to characterize seasonal mean 

levels of background ozone. However, it is well established that background levels can vary 

substantially from day-to-day within the seasonal mean. From an implementation perspective, 

the values of background ozone on possible exceedance days are a more meaningful 

consideration. The Policy Assessment for the Review of the Ozone National Ambient Air 

Quality Standards (US EPA, 2014c) concluded that “anthropogenic sources within the U.S. are

largely responsible for 4th highest 8-hour daily maximum O3 concentrations” based on modeling 

using a 2007 base year and the two distinct modeling methodologies described above. Figure 2-

110 and 2-121 show the distribution of daily MDA8 apportionment-based USB levels (absolute 

magnitudes and relative fractions, respectively) from the CAMx simulation. The 2007 modeling 

shows that the days with highest ozone levels have similar distributions (i.e., means, interquartile ranges) of background ozone levels as days with lower values, down to approximately 

40 ppb. As a result, the proportion of total ozone that has background origins is smaller on high 

ozone days (e.g., days > 60 ppb) than on the more common lower ozone days that tend to drive 

seasonal means. Figure 2-11 also indicates that there are cases in which the model predicts much 

larger background proportions, as shown by the upper outliers in the figure. These infrequent 

episodes usually occur in relation to a specific event, and occur more often in specific 

geographical locations, such as at high elevations or wildfire prone areas during the local dry 

season.

It should be noted here that EPA has policies for treatment of air quality monitoring data 

affected by these types of events. EPA’s exceptional events policy allows exclusion of certain air 

quality monitoring data from regulatory determinations if a State adequately demonstrates that an 

exceptional event has caused the exceedance or violation of a NAAQS. In addition, Section 

179B of the Clean Air Act (CAA) also provides for treatment of air quality data from 

international transport when an exceedance or violation of a NAAQS would not have occurred 

but for the emissions emanating from outside of the United States. Finally, CAA section 182(h) 

authorizes the EPA Administrator to determine that an area designated nonattainment can be 

treated as a “rural transport area”. In accordance with the statute, a nonattainment area may 

qualify for this distinction if it meets the following criteria: 1) the area does not contain 
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emissions sources that make a significant contribution to monitored ozone concentrations in the 

area, or in other areas; and 2) the area does not include and is not adjacent to an MSA. More 

information regarding how background ozone is addressed in Clean Air Act implementation is 

provided in Section VII.F of the notice of proposed rulemaking.

Figure 2-98. Map of Site-Specific Ratios of U.S. Background to Total Seasonal Mean 

Ozone based on 2007 CMAQ Zero-Out Modeling
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Figure 2-109. Map of Site-Specific Ratios of Apportionment-Based U.S. Background to 

Seasonal Mean Ozone based on 2007 CAMx Source Apportionment Modeling

Figure 2-110. Distributions of Absolute Estimates of Apportionment-Based U.S. 

Background (all site-days), Binned by Modeled MDA8 from the 2007 Source 

Apportionment Simulation

Figure 2-121. Distributions of the Relative Proportion of Apportionment-Based U.S. 

Background to Total Ozone (all site-days), Binned by Modeled MDA8 from the 

2007 Source Apportionment Simulation
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2.5 References

Camalier, L.; Cox, W.; Dolwick, P. (2007). The Effects of Meteorology on Ozone in Urban Areas and their use in 

Assessing Ozone Trends. Atmos Environ 41: 7127-7137. 

Dunker, A.M.; Yarwood, G; Ortmann, J.P.; Wilson, G.M. (2002). Comparison of source apportionment and source 

sensitivity of ozone in a three-dimensional air quality model. Environmental Science & Technology 36: 2953-

2964.

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