2

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CHAPTER 2 : DEFINING THE OZONE A IR QUALITY PROBLEM

Overview This section provides overviews of ozone precursor emissions and at mospheric chemistry (section 2.1); ambien t ozone concentrations (section 2.2 ) ; ambient ozone mon itoring 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 str atosphere, 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 com pounds (VOCs) and nitrogen oxides (NO X ). Carbon monoxide (CO) and methane (CH 4 ) 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 natu ral source categories , with n atural 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 NO X 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 sourc es 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)

.2

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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. NO X emissions lead to both the formation and destru ction o f ozone, depending on the local quantities of NO X , VOC, free radicals, and sunlight. In areas dominated by fresh emissions of NO X , radicals are removed, which lower s 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 ro ads, as well as in power plant plumes. This short

- lived titration results in localized areas in which ozone concentrations are suppressed compared t o surrounding areas, but which contain NO 2 that contributes to subsequent ozone formation further downwind. The NOx titration effect i s most pronounced in ur

ban core areas that have a high volume of mobile sou rce NOx emissions from vehicles. In areas with relatively low NO X concentrations, such as those found in remote continental areas and rural and suburban areas downwind of urban centers, ozone production typically responds linearly to NO X concentrations (e.g., ozone decreases with de creasing NO X emissions). Consequently, ozone response to reductions in NO X 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 c an 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 precurs or emissions is also affected by meteorological parameters such as the inte nsity of sunlight and atmospheric mixing

. Major episodes of high ground

- level ozone concentrations in the eastern United States are often associated with slow

moving high pressure s ystems. 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 combina tion of inhibited vertical mixing and light winds min imizes the dispersal of p ollutants , 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. Photochemi cal activity involving precursors is enhanced during warmer seasons because of the greater availa bility of sunligh t and hig her temperatures (US EPA, 2013, section 3.2).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 concentr ations 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 hav e 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 af fected 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 transfe rred 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 transp ort 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 t he atmosphere from precursor emissions, c oncentrations 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 con ditions, 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 season al patterns in sunlight, precursor emissions , atmospheric stability, wind direction, and temperature2

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(US EPA, 2013, section 3.7.5)

. On average, ambient ozone concentrations follow well

recognized daily and seasonal patterns, particularly in urban areas. Sp ecifically, daily m ax imum 1

- hour ozone concentrations in urban areas tend to occur in mid

- afternoon , with more pronounced peaks in the warm mo nths 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 approx imately 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 conc entrations 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, f resh NO emissi ons 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 concentration s 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, 20 13, Table 3

- 10). These same cities also had high 98 th percentile ozone concentrations, with Los Angeles recording the highest 98 th percentile concentration (91 ppb) and many eastern and southern cities reporting 98 th percentile concentrations near or above 75 ppb. In contrast, somewhat lower 98 th percentile ozone concentrations were recorded in cities in the western United States outside of California (US EPA, 2013, Table 3

- 10).2

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Rural sites can be affected by transport of ozone o r ozone p re cursors from upwi nd 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 non

urban 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 agenc ies 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, l ocal , 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 bo th 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 pop ulation 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. Sin ce 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 val ues 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.2

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tend to be associated with particular seasons for various locations, EPA re quires ozone monitoring during specific ozone monitoring seasons , which vary by state

. 3 Figure 2

- 1 shows the locations of the U.S. ambient ozone moni toring 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 provid e 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) m ulti

- 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 inju ry, 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 201 3, 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). 4 In 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 O 3 Monitoring System” (POMS) network operated by the NPS.2

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Figure 2
- 1. Map of U.S. A mbient O 3 Monitoring Sites R eporting D ata to EPA D uring the

200 9
- 201 3 P eriod 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 4 th 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. 5 In counties or other geographic areas with multiple monitoring sites, the area wide 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 4 th highest daily maximum 8

- hou r 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 proced ures used to calculate design values for the existing ozone NAAQS, see 40 CFR Part 50, Appendix P.2

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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 25 th and 75 th percentiles, and the bottom and top lines represent the 10 th and 90 th 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 f igure shows that the annual 4 th 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 “NO X SIP Call”, a progr am designed to reduce summertime emissions of NO X 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 th e 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.2

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Figure 2
- 3. Map of 8
- hour O zone D esign V alues in ppb , Averaged A cross the 2009
- 2011 ,

2010
- 2012 , and 2011
- 2013 P eriod s 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 aggreg ate 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 p lace less emphasis on exposure to low hourly ozone concentrations and more emphasis on exposure to high hourly ozone concentrations (Lefohn et al, 1988).

F igure 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 25 th and 75 th percentiles, and the bottom and top lines represent the 10 th and 90 t h percentiles. Figure 2

- 5 shows a map of the 3

- year average annual W1 26 concentrations in ppm

- hrs averaged across the 2009

- 2011, 2010

- 2012, and 2011

- 2013 periods at all monitoring sites in the2

- 10

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.2

- 11

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 ozo ne that is unusual relative to the other pollutants with NAAQS is that, periodically, in some locations, an appreciable fraction of the observed ozone result s 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. B ackground ozone can originate from natural sources of ozone and ozone precur sors, as well as from manmade international e missions of ozone precursors. Natural sources of ozone precursor emissions such as wildfires, lightning, and vegetation can lead to

ozone formation by chemical react ions with other natural sourc es
. 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 c alled intrusions , especially at higher

- altitude locations. The2

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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 sou rces.
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 Rev iew of the Ozone National Ambient Air Quality Standards (US EPA, 2014c), EPA identified three specific definitions of background ozone : natural background (NB) , N orth American background (NAB), and United S tates 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 presum ption that the U.S. has little influence over anthropo genic 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 tha t 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

ce rtain 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 estima te 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.2

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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). T he 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 precurs or emissions (VOC and NO X ) 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 B ackground O zone 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 wester n 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, 2014 c) focused on the months from Apri l 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)

. Emi ssions and model set

- up for th e 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 wa s 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 usi ng the Community Multiscale Air Quality (CMAQ) model. Seasonal means are computed over those seven months. This figure2

- 14

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 m ore 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. Nat ural 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 emissio ns 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 and2

- 15

USB concentrations greater than 40 ppb are confined to Colorado, Nevada, Utah, Wyoming, northern Arizona, eastern Califo rnia, 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 Modeling2

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2.4.2 Seasonal Mean Background O zone in the U.S. as a Proportion of Total O zone Another informative way to assess the importance of background ozone as part of seasonal mean ozone levels across the U.S. is to co nsider 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

m aximum 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 th e
zero - out modeling approach. For comparison, in Figure 2

- 1 0 1 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. T hus , this approach is not affected by th e 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 oz one 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 wester n 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 backgroun d 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).2

- 17

2.4.3 Daily Distributions of Background Ozone within the Seasonal Mean As a first

- order u nderstanding, it is valuable to be abl e to characterize seasonal mean l evels 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, th e 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, 2014 c ) concluded that “anthropogenic sources within the U.S. are largely responsible for 4 th highest 8

- hour daily maximum O 3 concentrations ” based on modeling using a 2007 base year and the two distinct modeling methodologies described above. Figure 2

- 1 1 0 and 2

- 1 2 1 show the distribution of daily MDA8 apportionment

- base d 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, inter

quartile 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 episod es usually occur in relation to a specific event, and occur more often i n 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 exceptio nal 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) aut horizes 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 ar ea does not contain2

- 18

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
- 9 8 . Map of Site
- Specific Ratios of U.S. Background to Total Seasonal M ean

O zone based on 2007 CMAQ Zero
- Out Modeling2

- 19

Figure 2
- 10 9 . Map of Site
- Specific Ratios of Apportionment
- Based U.S. Background to

S easonal M ean O zone based on 2007 CAMx Source Apportionment Modeling

Figure 2
- 1 1 0 . 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
- 1 2 1 . Distributions of the Relative Proportion of Apportionment
- Based U.S.

Background to T otal O zone (all site
- days), Binned by Modeled MDA8 from the 2007 Source Apportionment Simulatio n2

- 20

2.5 R eferences 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. Emery, C; Jung, J; Downey, N; Johnson, J; Jimenez, M; Yarwood, G; Morris, R. (2012). Regional and global mod eling estimates of policy relevant background ozone over the United States. Atmos Environ 47: 206

- 217. http://dx.doi.org/10.1016/j.atmosenv.2011.11.012

. Helmig, D., Thompson, C.R., Evans, J., Boylan, P., Hueber, J., Park, J.H. (2014). Highly elevated atmo spheric levels of volatile organic compounds in the Uintah Basin, Utah, Environmental Science & Technology, 48, 4707

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Kemball

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