1

MEMORANDUM 

TO: Docket No. EPA-HQ-OAR-2012-0918 

Air Quality Designations for the 2012 PM2.5 Standard 

 

FROM: Beth W. Palma 

 Air Quality Policy Division, OAQPS 

SUBJECT: Georgia Deferred Area - Air Quality Designations for the 2012 PM2.5 National 

Ambient Air Quality Standard (SAN 5706) 

This memorandum provides the rationale for the U.S. Environmental Protection Agency’s 

decision to use the additional time available to it under section 107(d)(1)(B) of the Clean Air Act 

(CAA) to obtain additional information and further evaluate air quality monitoring data before 

promulgating initial area designations for the 2012 primary annual fine particle National 

Ambient Air Quality Standard (2012 annual PM2.5 NAAQS)1

 for certain areas in Georgia and 

relevant nearby counties in Alabama and South Carolina. 

Upon promulgation of a NAAQS, section 107(d) of the CAA requires the EPA to subsequently 

promulgate area designations based on that NAAQS. Specifically, EPA must designate as 

“nonattainment” those areas that are violating a NAAQS, or that are contributing to a violation of 

the NAAQS in a nearby area. By contrast, the EPA designates as “unclassifiable/attainment” 

those areas where air quality monitoring data indicate attainment of the NAAQS, and for areas 

that do not have monitors but which the EPA has reason to believe are likely to be in attainment 

and are not contributing to nearby violations. Finally, the EPA reserves the category of 

“unclassifiable” for areas where the EPA cannot determine based on available information 

whether an area is meeting the NAAQS or contributing to a nearby violation. 

As described in more detail in the memorandum, Data Quality Issues in Georgia Affecting Air 

Quality Designations for the 2012 PM2.5 National Ambient Air Quality Standards, Georgia’s 

monitoring program has experienced data completeness issues for several areas across the State.2

Given these data completeness issues, for several counties the EPA cannot calculate a valid 

design value for the 2011-2013 time period (the data that the EPA is using to determine areas 

that violate the 2012 annual PM2.5 NAAQS). Without a valid design value, the EPA has 

insufficient information to determine whether these areas are meeting or are not meeting the 

                                                      

1

 On December 14, 2012, the EPA promulgated a revised primary annual PM2.5 NAAQS (78 FR 3086, January 15, 

2013). In that action, the EPA revised the primary annual PM2.5 standard, strengthening it from 15.0 micrograms per 

cubic meter (μg/m3

) to 12.0 μg/m3. 

2

 Memorandum from Liz P. Naess, Group Leader, Air Quality Analysis Group, US EPA Office of Air Quality 

Planning and Standard, to EPA Docket EPA-HQ-OAR-2012-0918, Air Quality Designations for the 2012 PM2.5

Standards, titled “Data Quality Issues in Georgia Affecting Air Quality Designations for the 2012 PM2.5 National 

Ambient Air Quality Standard.” 
2

NAAQS. However, the EPA believes that forthcoming monitoring data will likely result in the 

three years of complete and valid data needed to assess compliance with the standard and 

promulgate designations for the areas identified below. Accordingly, the EPA is deferring 

designations for these areas, and using the additional time available under section 107(d)(1)(B) 

of the CAA to assess that forthcoming data, and to promulgate initial area designations for the 

identified areas. 

Table 1a identifies the counties for which the EPA is exercising its discretionary authority to 

defer designations. Figure 1 displays a map of the areas being deferred. Counties being deferred 

either contain monitors with incomplete 2011-2013 data, or are in the same Core Based 

Statistical Areas (CBSA) as such counties and would be most likely to contribute to a violation 

of the NAAQS should forthcoming data reveal such a violation. Accordingly, the EPA has 

determined that it currently lacks sufficient information to promulgate designations for these 

counties. The additional time afforded EPA by the decision to defer designations for these 

counties will allow the EPA to collect and assess that forthcoming information (including air 

quality monitoring data) before designations for these areas are promulgated. 

Table 1a. Counties* for which the EPA is Deferring Designations 

County with 

Incomplete Data 

Adjacent County Associated Area Name 

Dougherty --- Albany 

Cobb 

Fulton 

Gwinnett 

Paulding 

Bartow 

Clayton 

Cherokee 

Coweta 

DeKalb 

Douglas 

Forsyth 

Henry 

Atlanta 

Richmond Aiken (South Carolina) 

Columbia 

Augusta 

Glynn --- Brunswick 

Muscogee Russell (Alabama) Columbus 

Chatham Effingham Savannah 

Lowndes Brooks Valdosta 

Washington --- Washington County 

*Unless otherwise noted, the counties listed in this table are in Georgia. 
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Figure 1. Map of Georgia Counties (including Adjacent Counties in Alabama and South 

Carolina) that the EPA is Deferring 

This memorandum also provides information regarding certain counties nearby the deferred 

counties listed in Table 1a, which the EPA is not deferring designations for. Instead, the EPA is, 

for the time being, designating these counties “unclassifiable/attainment,” based on the EPA’s 

determination that these counties are less likely to contribute to nearby affected monitors than the 

counties that the EPA is deferring designations for within the same CBSA. Because these 

unclassifiable/attainment counties are relatively less likely to be contributing to a hypothetical 

NAAQS violations that may be revealed by forthcoming monitoring data, there is comparatively 

less justification to defer designations for these counties. 

In conducting the contribution analyses described in this memorandum, the EPA focused only on 

counties located within the same CBSA as an affected monitor, because such counties would be 

most likely to contain nearby sources that would contribute to any hypothetical violation at that 

monitor. In the event that complete data at any affected monitor ultimately reveals a violation of 

the NAAQS, the EPA intends to conduct the full five-factor analysis to analyze potential 
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contribution, as described in the April 2013 memorandum issued for this designation process.3

Such an analysis would reevaluate contribution from all counties within the violating monitor’s 

CBSA (including those currently being designated unclassifiable/attainment in this action), as 

well as from additional nearby areas with the potential to contribute to that violating monitor. As 

a result of any such future analyses, the boundaries of any future nonattainment areas may differ 

from the boundaries of the areas for which the EPA currently is deferring designations.

Table 1b shows information on the available, but incomplete, PM2.5 annual average concentration 

data from 2012, 2013 and 2014 at the highest reading monitors in the Georgia areas for which 

the EPA is currently deferring designations. This data is not directly relevant to the analyses 

contained in this memorandum, but serves as context to show that it is less likely that any of 

these areas is violating the 2012 PM2.5 standard of 12.0 micrograms per cubic meter (μg/m3

), and 

that complete data collected after 2013 will demonstrate these areas all meet the NAAQS. 

Nonetheless, as a regulatory matter, at this time the EPA cannot determine that areas with 

affected monitors are attaining the standards, and is thus invoking its discretionary right to defer 

designations for those areas. 

Table 1b: PM2.5 Annual Averages 2012-2014 for the Deferred Areas in Georgia 

Area 2012 Annual 

Average (μg/m3) 

2013 Annual 

Average (μg/m3) 

Preliminary 2014 

Annual Average for 

Q1-Q3 (μg/m3)

4

Savannah 9.2 9.0 9.5 

Atlanta 11.35 10.4 11.3 

Albany 10.6 10.0 10.2 

Brunswick 7.56 8.2 8.3 

Valdosta 8.6 8.5 8.9 

Columbus 10.4 9.7 10.4 

Augusta 10.4 9.2 10.2 

Washington 9.8 9.4 10.2 

The EPA will work with Georgia, Alabama, and South Carolina to finalize the designations for 

these counties as soon as complete certified PM2.5 monitoring data are available, which the EPA 

anticipates will allow for prompt promulgation of these designations. When complete air quality 

                                                      

3

 Memorandum dated April 16, 2013, from Gina McCarthy, Assistant Administrator, to Regional Administrators, 

Regions 1-10, titled “Initial Area Designations for the 2012 Revised Primary Annual Fine Particle National Ambient 

Air Quality Standard.” 

4

 Preliminary 2014 data is based on uncertified data in AQS for the first three quarters of 2014. 

5

 This annual average contains a quarter with less than 50% of the required data. 

6

 This annual average contains a quarter with less than 50% of the required data.
5

monitoring data are available and have been certified, the EPA invites the affected states to 

submit revised designation and boundary recommendations, as appropriate. If at that time the 

EPA believes that it is necessary to modify a state’s recommendation and to promulgate a 

designation different from the state’s recommendation, then the EPA will notify the state at least 

120 days prior to promulgating the final designation and the EPA will provide the state an 

opportunity to comment on the potential modification. Each state will then have an opportunity 

to respond to the EPA’s proposed designations and boundaries. Pursuant to section 107(d), the 

EPA cannot promulgate the designation for these areas less than 120 days from the date of the 

EPA’s announced intention to modify the recommendation. The EPA will promulgate the 

designations for these deferred areas at a later date, in a separate final rule. 

Approach 

In determining the appropriate set of neighboring counties to include with the set of monitored 

counties for which the EPA is deferring designations, the EPA conducted a hypothetical analysis 

assuming that the monitors with the incomplete data were violating the 2012 standard of 12.0 

μg/m3

. The EPA is proceeding under this assumption under the precautionary principle that 

because it is unclear whether there is a violation in this area due to data incompleteness, then for 

purposes of conducting the contribution analysis the EPA will presume that there may be such a 

violation. The EPA’s contribution analysis for these hypothetical violations focused on counties 

within the same CBSA as the affected monitor because these counties would be most likely to 

contain nearby sources that contribute to any violations. Specifically, the EPA evaluated all 

counties in the same CBSA as the county with the monitors in question, and assessed the 

relatively likelihood that these presumptively “nearby” counties could contribute to any 

hypothetical violation of the standard at the affected monitors. Using information similar to the 

information used for determining nonattainment area boundaries,7

 the EPA evaluated the 

information available for these CBSAs, including the more limited Air Quality Data, as well as 

emissions and emissions-related data; meteorology; and geography/topography.8

 One of the 

EPA’s primary boundary considerations for determining whether to defer a final designation 

decision for these counties is whether the agency believes the emissions in those nearby counties 

are likely to contribute to the potential violations, and whether the meteorological data indicate 

that those emissions would be likely to impact an affected monitor. Where available evidence 

indicates that emissions in adjacent counties could likely have the potential to contribute to 

                                                      

7

 Memorandum dated April 16, 2013, from Gina McCarthy, Assistant Administrator, to Regional Administrators, 

Regions 1-10, titled “Initial Area Designations for the 2012 Revised Primary Annual Fine Particle National Ambient 

Air Quality Standard.” 

8

 The EPA did not consider jurisdictional boundaries for purposes of deferred designations because jurisdictional 

boundaries are most helpful for nonattainment planning purposes, whereas these evaluations merely concern EPA’s 

best assessment of an appropriate dividing line between deferred and unclassifiable/attainment counties. No areas in 

Georgia are being designated nonattainment pursuant to this analysis, although this would change in the future if 

forthcoming data reveal a NAAQS violation. This and other circumstances described in this memorandum and other 

deferral memoranda being released today further highlight critical differences between the considerations and 

analysis for designating areas nonattainment or unclassifiable, versus the process for deferring designations. 
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monitors with data incompleteness, the EPA is deferring the designation for those counties as 

well as for the county with the affected monitor. 

Albany Area (Albany, GA CBSA) 

Albany is located in a CBSA that includes five counties in Georgia (Baker, Dougherty, Lee, 

Terrell, and Worth). The most populated and industrialized portion of the Albany area, where 

most of the emissions and emissions activities occur, is primarily contained in Dougherty 

County. More information on the EPA’s evaluation of the emissions for the counties in the 

Albany CBSA is provided below. The Albany area does not have any geographical or 

topographical barriers meaningfully limiting air pollution transport within its air shed. Therefore, 

this factor did not play a meaningful role in this evaluation. The Albany CBSA is outlined in 

green in Figure 2, along with the location of point sources and air quality monitors.

Figure 2. Albany CBSA with Point Sources and Air Quality Monitor Location
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The Dougherty County monitor located in the Albany area has incomplete 2011-2013 data. 

Based on incomplete data, the incomplete Dougherty County design value (DV) is 10.9 μg/m3

. 

The EPA evaluated PM2.5 and the precursor emissions, along with other related data from the 

counties in the Albany CBSA. The Albany area has three major point sources, all of which are in 

Dougherty County: MillerCoors, LLC, Procter & Gamble Paper Products Co., and GA Power 

Company Plant Mitchell. Other sources in the CBSA include county level emissions from nonpoint sources, nonroad mobile, on-road mobile, fires and local traffic. As can be seen in Table 2 

below, Dougherty County has the largest SO2 emissions (1,703 tpy) and NOx emissions (4,962 

tpy) of any of the counties in the CBSA and a large amount of direct PM2.5 emissions (2,183 tpy). 

Dougherty is the most populous county in the Albany CBSA with approximately 60 % of the 

population residing this county. Although the remainder of the CBSA accounts for 40 % of the 

populations in the CBSA, the areas outside of Dougherty are mainly rural. While the population 

density in Dougherty is 287 people per square mile, the population density in the remainder of 

the counties ranges from 10 to 80 people per square mile. The highest category of emissions 

from the other counties in the CBSA are total direct PM2.5, with Worth County having the 

highest level at (3,027 tpy).9

 A further evaluation of the direct PM2.5 emissions for Baker, Lee, 

Terrell and Worth counties indicates that the majority of these emissions are contributed by fires, 

and most of the fire emissions are from prescribed fires. 

Table 2. Summary Statistics for the Albany, GA CBSA10 

Dougherty Baker Lee Terrell Worth 

Core urbanized 

county or outlying? Core11 Outlying Outlying Outlying Outlying 

SO2 emissions (tpy) 1,703 138 116 105 145 

PM2.5 emissions (tpy) 2,183 1,958 1,718 1,741 3,027 

NOx emissions (tpy) 4,962 704 1,246 933 1,625 

NH3 emissions (tpy) 302 560 340 423 829 

VOC emissions (tpy) 4,157 1,458 1,708 1,451 2,592 

                                                      

9 The majority of these direct PM2.5 emissions are from non-point sources and may be event-related. If a violation of 

the NAAQS occurs when three years of complete data becomes available, the potential impacts of these eventrelated emissions may be further evaluated. 

10 Emissions from this table are generated from the 2011 National Emissions Inventory (NEI). Sulfur dioxide is 

denoted by SO2, oxides of nitrogen is denoted by NOx, ammonia is denoted by NH3 and volatile organic compounds 

is denoted by VOC in this table. 

11 In this document, the EPA’s reference to a county as a Core county is an indication of whether most of the 

urbanized area and population in is within a CBSA. 
8

Population 94,755 3,437 28,440 9,322 21,626 

VMT (Millions) 956 59 278 157 310 

VMT (% of CBSA) 54% 3% 16% 9% 18% 

The EPA also evaluated the meteorology in the area by evaluating wind data collected at the 

monitor located in the Albany CBSA as shown in Figure 3. As shown, the winds blow from all 

directions at times throughout the year, with a lower frequency from the northerly directions. 

These variable winds occur mostly at mid-level speeds of 2 to 6 meters per second. This 

indicates that emissions sources in Lee County to the north are less likely to contribute to the 

Albany monitor.

Figure 3. Wind Rose in the Area of Analysis for the Albany Area 

Albany GA CBSA Conclusion 

Based on the information summarized in Table 2 and the wind rose data, the EPA is concluding 

that of the five counties in the Albany CBSA, Dougherty County has the greatest potential to 
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contribute to potential future violations of the standard at the Dougherty County monitor 

currently lacking complete data. For all other counties in the Albany CBSA, the EPA believes 

that it is relatively less likely that emissions from these counties would contribute to any 

hypothetical violation of the 2012 annual PM2.5 NAAQS. 

With the exception of direct PM2.5 and NH3 emissions, Dougherty County has the most emissions 

of any county in the CBSA. The NH3 emissions are most likely related to agricultural activities. 

The relative potential for particles traveling from agricultural activities is less likely than from 

industrial sources because of their proximity to the ground. More than 50 percent of the direct 

PM2.5 emissions in the outlying counties (i.e., Baker, Lee, Terrell and Worth counties) in the 

Albany CBSA are due to prescribed fires. In general, the carbonaceous fractions of direct 

emissions of PM2.5 (i.e., particulate organic carbon and particulate elemental carbon) are an 

important “local” contributor to ambient PM2.5 concentrations and are comparatively less likely 

to travel great distances. In Baker, Lee, Terrell, and Worth Counties – just as in other parts of 

southern Georgia and some nearby areas of southeast Alabama and northern Florida – large 

amounts of direct PM2.5 emissions are associated with prescribed and managed fires, which can 

be an annual activity. Although these emission totals are higher than direct PM2.5 emissions in 

other parts of the country, emissions associated with such fires are different than emissions from 

stationary and mobile sources. In general, these fires are only allowed to occur during conditions 

and times of the year that minimize their air quality impact, and emissions from these prescribed 

fires therefore tend to have lower ambient PM2.5 potential than is implied by their mass. 

Furthermore, most prescribed fires are low-intensity fires performed in accordance with burn 

permits issued by the Georgia Forestry Commission, which limit these fires to circumstances 

with “good smoke dispersion conditions.” Therefore, the potential for large quantities of smoke 

(direct PM2.5 emissions) from Baker, Lee, Terrell and Worth counties to be transported long 

distances and to contribute to potential violations at the monitor in Albany is relatively less 

likely. 

Of particular importance to the EPA’s conclusion are the population and emissions of SO2 and 

PM2.5 in Baker, Lee, Terrell and Worth Counties, which are relatively low when compared to 

Dougherty County. Although the county-level NOx, VOC and ammonia emissions appear 

sizable in the Table 2 above, ambient PM2.5 concentrations in the southeastern U.S. tend to be 

impacted most significantly by emissions of direct PM2.5 emissions and SO2 emissions. 

Furthermore, although the outlying counties account for 40% of the population in the Albany 

CBSA, the 60% located in Dougherty County are more densely concentrated and thus correlate 

more strongly with an increased likelihood of contribution. Emissions in Dougherty County, for 

the most part, are much higher than emissions in the other counties with the exceptions noted 

above. Additionally, the wind rose data suggest that emissions from Lee County are less likely to 

contribute at the Dougherty County monitor. Accordingly, the EPA is not deferring designations 

for Baker, Lee, Terrell, or Worth Counties, and is designating them unclassifiable/attainment 

based on the available data. 
10

Atlanta Area (Atlanta-Sandy Springs-Roswell, GA CBSA) 

1.0 Atlanta Area Summary 

Atlanta-Sandy Springs-Roswell, Georgia is a 29-county CBSA in which the EPA has determined 

that designations for 12 full counties of this area should be deferred for the 2012 annual PM2.5

NAAQS. Designations for the following counties are being deferred due to existing PM2.5

monitoring sites in these counties that have invalid design values for 2013: Fulton, Cobb, 

Gwinnett and Paulding. In addition, the EPA has determined that the following adjacent counties 

would have the potential to contribute to a violating monitor, if there were one, at one of the 

invalid sites: Bartow, Cherokee, Clayton, Coweta, DeKalb, Douglas, Forsyth and Henry. 

As shown in Figure 4, below, for 2013 in the Atlanta CBSA, there are two attaining monitors 

with complete data and four monitors with incomplete data. The EPA focused much of its 

analysis on the Fire Station #8 monitor because it has historically been the highest reading 

monitor in Atlanta. The Fire Station #8 site is three miles downwind of Georgia Power 

Company’s Plant McDonough-Atkinson, and less than a mile away from a major rail hub. The 

only other monitor in the Atlanta area that was violating in 2012 was the Clayton County 

monitor. The Clayton County monitor currently has a complete, valid 2013 design value that is 

below the standard at 11.1 μg/m3. 

Most of the urbanized portion of the Atlanta CBSA is located within five central counties. 

Pockets of urbanization around these core counties exist in adjacent counties as well. 

Due to data completeness issues, the EPA is unable at this time to calculate valid design values 

for four counties within the Atlanta CBSA – the counties of Cobb, Fulton, Gwinnett and 

Paulding. Without valid design values, the EPA has insufficient information to determine 

whether these areas are meeting the NAAQS. However, the EPA believes that forthcoming 

monitoring data for these counties will likely result in the three years of complete and valid data 

necessary to make such a determination. Accordingly, the EPA has decided to defer designations 

for Cobb, Fulton, Gwinnett and Paulding Counties, pursuant to CAA section 107(d)(1)(B). 

In determining whether to defer designations for other portions of the Atlanta CBSA, the EPA 

considered the relatively likelihood that any counties in the CBSA could potentially contribute to 

violations in Cobb, Fulton, Gwinnett or Paulding Counties, in the event that complete data 

subsequently shows that monitors in any of those four counties violates the standard. The EPA 

has determined that eight counties – Bartow, Clayton, Coweta, DeKalb, Cherokee, Henry, 

Forsyth, and Douglas – would be the counties most likely to contribute to any violation that may 

be identified in the future. Both Clayton and DeKalb counties have valid attaining 2011-2013 

design values, but the designations for these counties are being deferred because these counties 

have high emissions, are upwind of the deferred monitored counties, and overall would be 

relatively more likely to contribute to a hypothetical violation at an affected monitor. Generally, 

these counties have similar features with respect to high SO2 and PM emissions, point sources, 

high population and VMT, relative to other counties in the CBSA. 

Substantial emission reductions have been realized in the Atlanta area since the time the EPA 

evaluated the area for the 1997 PM2.5 standards. This is evident by the smaller footprint of 
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recently violating monitors for this area. Specifically, based on 2010-2012 data, only two 

monitors in the Atlanta area (one in Fulton County and one in Clayton County) had violating 

design values. In 2005, when the designations for the 1997 annual PM2.5 NAAQS were finalized, 

there were five monitors scattered throughout the metropolitan area with design values violating 

the 1997 standards. In contrast, there were only two monitors in the area with 2012 design 

values exceeding the 2012 annual PM2.5 NAAQS, and these two monitors are located 14 miles 

apart. 

The South DeKalb monitor (traditionally one of the higher reading monitors for this area) has 

complete data for the entire period as the data collected there was not impacted by a 2011 snow 

storm that impacted data completeness for other monitors in Georgia. For 2013, this monitor has 

a valid attaining design value of 10.5 μg.m3

, well below the 2012 standard. 

For purposes of this contribution analysis, the EPA has assumed that the four monitors with 

incomplete data – Fire Station #8, Cobb-Kennesaw, Gwinnett-Gwinnett Tech and PauldingYorkville – may be in violation of the standard. The EPA notes that Cobb-Kennesaw, GwinnettGwinnett Tech and Paulding-Yorkville monitors all had steadily declining design values from 

2008 through 2011 and recorded valid 2011 design values of 12.3, 12.1 and 11.0 μg/m3, 

respectively. The EPA believes that Table 3 below and Figure 6 below, show that these three 

monitors were likely on a trajectory for recording attaining design values by the year 2011, 

notwithstanding the data completeness issues that led to invalid design values for 2011, 2012 and 

2013. Nevertheless, these counties lacked the complete data necessary to develop a valid 2011-

2013 design value, and are thus being deferred on that basis. 

Figure 4: Map of the Atlanta Area.
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2.0 Deferred Boundary Determination 

As noted above, the EPA’s starting point, for an area that has monitors with incomplete data and 

no violating monitors, is the CBSA where one exists. The Atlanta area had invalid data at several 

monitoring sites in 2011. For the period 2010-2012, Atlanta had valid design values at five 

monitors, with two violating the standard (Clayton and Fulton Counties). For 2011-2013, the 

Area has only three valid design values, all attaining the standard; the remaining four monitors in 

operation have invalid data. Although the monitor readings have been trending downward, the 

EPA has determined that it lacks sufficient information at this time to promulgate designations 

for the four counties with incomplete monitoring data, as well for several nearby counties that 

could potentially contribute to the four counties with data completeness issues. However, 

because the EPA believes that these data incompleteness issues can be rectified with forthcoming 

data, the EPA is deferring designations for these counties. 

3.0 Technical Analysis for the Atlanta CBSA 

In this technical analysis, the EPA used the latest data and information available to the EPA (and 

to the states and tribes through the PM2.5 Designations Mapping Tool12 and the EPA PM 

Designations Guidance and Data web page13) and/or data provided to the EPA by states or tribes. 

This technical analysis identifies the areas with emissions that could contribute to a potential 

violation of the 2012 annual PM2.5 standard at the incomplete monitors. The EPA evaluated the 

relevant information for these areas and other nearby areas with emissions sources or activities 

that potentially contribute to ambient fine particle concentrations at the monitors with invalid 

2013 design values in the area based on the using a weight of evidence of the five factors 

recommended in the EPA guidance.

                                                      

12The EPA’s PM2.5 Designations Mapping Tool can be found at http://geoplatform2.epa.gov/PM_MAP/index.html. 

13 The EPA’s PM Designations Guidance and Data web page can be found at 

http://www.epa.gov/pmdesignations/2012standards/techinfo.htm.  
13

Figure 5: Map of EPA’s Deferred Area for the Atlanta Area.

Figure 5 is a map of the boundary within which that the EPA is deferring designations for in the 

Atlanta Region. For purposes of the 1997 annual PM2.5 NAAQS, portions of this area were 

designated nonattainment. The boundary for the nonattainment area for the 1997 annual PM2.5 

NAAQS included the entire counties of Barrow, Bartow, Carroll, Cherokee, Clayton, Cobb, 

Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Hall,14 Henry, Newton, Paulding, 

Rockdale, Spalding, Walton, and partial counties of Heard and Putnam.15

Air Quality Data 

All data collected during the year are important when determining contributions to an annual 

standard such as the 2012 annual PM2.5 NAAQS. Compliance with an annual NAAQS depends 

on monitor readings throughout the year, including days with monitored ambient concentrations 

                                                      

14 Hall County is not a part of the Atlanta CBSA. 

15 Putnam County is not a part of the Atlanta CBSA. 
14

below the level of the NAAQS. For the 2012 annual PM2.5 NAAQS, the annual mean is 

calculated as the mean of quarterly means. A high quarter can drive the mean for an entire year, 

which, in turn, can drive an elevated 3-year DV. Although all data are important, seasonal or 

episodic emissions can provide insight as to relative contributors to measured PM2.5

concentrations. For these reasons, for this air quality analysis, the EPA assessed and 

characterized air quality at, and in the proximity of, the monitoring site locations with invalid 

data first, by evaluating trends and the spatial extent of measured concentrations at monitors in 

the area of analysis, and then, by identifying the conditions most associated with high average 

concentration levels of PM2.5 mass in the area of analysis. 

In most cases, the EPA assessed air quality data on a seasonal, or quarterly, basis.16 The EPA 

also identified the spatial extent of these high PM2.5 concentrations. The mass and composition at 

the design value location represents contributions from various emission sources including local, 

area-wide (which may comprise nearby urban and rural areas) and regional sources. To 

determine the source mix (by mass) at the design value monitoring site, the EPA examined the 

chemical composition of the monitored PM2.5 concentrations by pairing each violating 

FRM/FEM/ARM monitoring site with a collocated or nearby Chemical Speciation Network 

(CSN) monitoring site or sites. Then, the EPA contrasted the approximated mass composition at 

the design value monitoring site with data collected at IMPROVE17 and other monitoring 

locations whose data are representative of regional background.18,19 This comparison of 

                                                      

16 Although compliance with the annual NAAQS depends on contributions from all days of the year, examining data 

on a quarterly or seasonal basis can inform the relationship between the temporal variability of emissions and 

meteorology and the resulting PM2.5 mass and composition. In some areas of the country where there may be 

noticeable month-to-month variations in average PM2.5, the quarterly averages may not adequately represent 

seasonal variability. In these areas, air quality data may be aggregated and presented by those months that best 

correspond to the local “seasons” in these areas. 

  

17 IMPROVE stands for Interagency Monitoring for Protected Visual Environments and is an aerosol monitoring 

network in mostly rural and remote areas. 

18 The “urban increment” analysis assesses and characterizes the increase in seasonal and annual average PM2.5 mass 

and chemical constituents observed at violating monitoring site(s) relative to monitoring sites outside the area of 

analysis (which represent background concentrations). Developing the urban increment involves pairing a violating 

FRM/FEM/ARM monitor with a collocated monitor or nearby monitor with speciation data. The EPA made every 

effort to pair these data to represent the same temporal and spatial scales. However, in some cases, the paired 

violating and CSN “urban” monitoring locations were separated by some distance such that the included urban CSN 

site(s) reflect(s) a different mixture of emissions sources, which could lead to misinterpretations. To generally 

account for differences in PM2.5 mass between the violating site and the nearby CSN site(s), the EPA determined 

material balance of the PM2.5 composition at the violating site by assigning the extra measured PM2.5 mass to the 

carbon components of PM2.5. Where the general urban increment approach may be misleading, or in situations 

where non-carbonaceous emissions are believed to be responsible for a local PM2.5 concentration gradient, the EPA 

used alternative analyses to reflect the mix of urban and rural sources contributing to the measured concentrations at 

violating monitoring sites. 

19 The urban monitors were paired with any rural sites within a 150 mile radius of an urban site to calculate spatial 

means of the quarterly averages of each species. If there were no rural sites within 150 miles, then the nearest rural 

site was used alone. That rural mean was then subtracted from the quarterly mean of the urban site to get the 

increment. Negative values were simply replaced with zeros. 
15

local/area-wide chemical composition data to regional chemical composition data derives an 

“urban increment,” which helps differentiate the influence of more distant emissions sources 

from the influence of closer emissions sources, thus representing the portion of the measured 

potential violation that is associated with nearby emission contributions.20,21,22 

PM2.5 Design Values and Total Mass Measurements – The EPA examined ambient PM2.5 air 

quality monitoring data represented by the DVs at the monitoring sites with invalid data and at 

other monitors in the area of analysis. The EPA calculated DVs based on air quality data for the 

most recent 3 consecutive calendar years of air quality data from suitable FEM/FRM/ARM 

monitoring sites in the EPA’s Air Quality System (AQS). For this designations analysis, the EPA 

generally reviewed data for the 2011-2013 period (i.e., the 2013 design value), which are the 

most recent years with air quality data. A monitor’s DV is the metric or statistic that indicates 

whether that monitor attains a specified air quality standard. The 2012 annual PM2.5 NAAQS is 

met at a monitoring site when the 3-year average annual mean concentration is 12.0 μg/m3

 or 

less (e.g., 12.1 μg/m3

 or greater is a violation). A DV is only valid if minimum data 

completeness criteria are met or when other regulatory data processing provisions are satisfied 

(See 40 CFR part 50 Appendix N). Table 3 identifies the current design values (i.e., the 2013 

DV) where available, and the recent design values from 2008 to 2012 for all monitoring sites in 

the Atlanta CBSA.23 

There is currently not enough verifiable data from the monitors in the Atlanta area to obtain an 

accurate determination of air quality in the Atlanta CBSA. As noted in an August 8, 2014, 

memorandum from Gregg M. Worley, Chief of Region 4’s Air Toxics & Monitoring Branch, to 

R. Scott Davis, Chief of Region 4’s Air Planning Branch, the Atlanta area had less than 50% data 

completeness in the first quarter of 2011 and, therefore, does not meet the data handling 

requirements of 40 CFR Part 58, Appendix N, 4.1(c)(ii), for conducting data substitution during 

the period 2011 through 2013. 

                                                      

20 In most, but not all, cases, the violating design value monitoring site is located in an urban area. Where the 

violating monitor is not located in an urban area, the “urban increment” represents the difference between local and 

other nearby emission sources in the vicinity of the violating monitoring location and more regional sources. 

21 Hand, et. al. Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United 

States: Report V, June 2011. Chapter 7 – Urban Excess in PM2.5 Speciated Aerosol Concentrations, 

http://vista.cira.colostate.edu/improve/Publications/Reports/2011/PDF/Chapter7.pdf

22 US EPA, Office of Air Quality Planning and Standards, December 2004. (2004) Area Designations for 1997 Fine 

Particle (PM2.5) Standards, Technical Support Document for State and Tribal Air Quality Fine Particle (PM2.5) 

Designations, Chapter 3, Urban Excess Methodology. Available at 

www.epa.gov/pmdesignations/1997standards/documents/final/TSD/Ch3.pdf

23 In certain circumstances, one or more monitoring locations within a monitoring network may not meet the 

network technical requirements set forth in 40 CFR 58.11(e), which states, “State and local governments must assess 

data from Class III PM2.5 FEM and ARM monitors operated within their network using the performance criteria 

described in table C-4 to subpart C of part 53 of this chapter, for cases where the data are identified as not of 

sufficient comparability to a collocated FRM, and the monitoring agency requests that the FEM or ARM data should 

not be used in comparison to the NAAQS. These assessments are required in the monitoring agency's annual 

monitoring network plan described in §58.10(b) for cases where the FEM or ARM is identified as not of sufficient 

comparability to a collocated FRM....” 
16

Table 3. Air Quality Data Collected at Regulatory Monitors in the Atlanta CBSA (all DV 

levels in μg/m3)

a,b

County - Site name Monitor Site 

ID 

06-08 

DV 

07-09 

DV 

08-10 

DV 

09-11 

DV 

10-12 

DV 

11-13 

DV 

Clayton-Forest Park 13-063-

0091 15.3 13.6 12.9 12.6 12.3 11.1 

DeKalb-South DeKalb 13-089-

0002 14.4 13.0 12.1 11.9 11.5 10.5 

Fulton-Fire Station #8 13-121-

0039 NV NV NV 13.2 13.0 NV 

Cobb-Kennesaw 13-067-

0003 15.3 13.5 12.3 NV NV NV 

Gwinnett-Gwinnett 

Tech 

13-135-

0002 14.5 12.7 12.1 NV NV NV 

Paulding-Yorkville 13-223-

0003 13.5 12.2 11.0 NV NV NV 

Cobb - Powder Springs 13-067-

0004 14.7 12.8 NV NV 11.1 - 

DeKalb – Doraville 13-089-

2001 14.4 13.4 12.3 NV NV - 

Fulton - E. Rivers Sch. 13-121-

0032 14.8 13.5 12.3 NV NV - 

NV: Not valid 

a This design value does not include data from Class III FEM monitors that are not eligible for comparison to the 

NAAQS, as approved by the EPA pursuant to 40 CFR 58.11(e). 

b

 Site approved for shutdown during network plan review at the end of 2012. 

The Figure 5 map, shown previously, identifies the Atlanta CBSA boundary and monitoring 

locations with 2013 attaining DVs and invalid DVs; there are no valid violating DVs for 2013. 

The Fire Station #8 monitor has consistently been the highest DV in the region, including for the 

1997 PM designation, when valid data have been available for the site. There are a total of six 

monitors in the CBSA, and all but two have invalid DVs for 2013. 

Figure 6, below, shows the history of design values for the monitoring data that is available for 

the Atlanta area since 2002. The Fire Station #8 monitor in Fulton County exceeded the 2012 

PM2.5 NAAQS in 2012, but for 2013 the design value is invalid due to incomplete data issues. In 

the years that Fire Station #8 site had valid design values, the site recorded the highest annual 

PM2.5 design values in the Atlanta area. (Note that the last three sites shown, Cobb-Powder 

Springs, DeKalb-Doraville and Fulton-E. Rivers School all ceased operation in 2012 in 

accordance with Georgia’s approved monitoring plan.) 
17

Figure 6. Atlanta PM2.5 Valid Design Values for 2002-2013 

Seasonal variation can highlight those conditions most associated with high average 

concentration levels of PM2.5. Figure 7, below, shows quarterly mean PM2.5 concentrations for 

the 3-year period 2010-2012 for the highest DV monitoring site and the other, non-violating, 

monitoring sites in each county within the area of analysis. This graphical representation is 

particularly relevant when assessing air quality data for an annual standard, such as the 2012 

annual PM2.5 NAAQS, because, as previously stated, the annual mean is calculated as the mean 

of quarterly means and a high quarter can drive the mean for an entire year, which, in turn, can 

drive an elevated 3-year DV. 

8

12

16

20

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

μg/m3

DV Year

Atlanta Area Valid Design Value Trends

2012 PM2.5 NAAQS

Clayton ‐ Forest Park

DeKalb ‐ South DeKalb

Fulton ‐ Firestation #8

Cobb ‐ Kennesaw

Gwinnett ‐ Gwinnett Tech

Paulding ‐ Yorkville

Cobb ‐ Powder Springs

DeKalb ‐ Doraville

Fulton ‐ E. Rivers Sch.
18

Figure 7. Atlanta PM2.5 Quarterly Means for 2010-2012 

As context, Quarterly values across the period have peaked in Q2. Overall, the quarterly means 

from year to year are also trending down at all of these sites. 

PM2.5 Composition Measurements - To assess potential emissions contributions for each 

monitoring location with invalid data, the EPA determined the various chemical species 

comprising total PM2.5 to identify the chemical constituents over the analysis area, which can 

provide insight into the types of emission sources impacting the monitored concentration. To 

best describe the PM2.5 at the monitoring sites that were violating in 2012 (none of the three 

monitoring sites with valid 2013 design values are violating), the EPA first adjusted the chemical 

speciation measurement data from a monitoring location at or near the violating FRM monitoring 

sites using the SANDWICH approach to account for the amount of PM2.5 mass constituents 

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

'10 Q1 '10 Q2 '10 Q3 '10 Q4 '11 Q1 '11 Q2 '11 Q3 '11 Q4 '12 Q1 '12 Q2 '12 Q3 '12 Q4

PM2.5 Concentrations

μg/m3

Atlanta PM2.5 Quarterly Means 2010‐2012

Clayton Fulton Dekalb Cobb
19

retained in the FRM measurement.24,25,26,27 In particular, this approach accounts for losses in fine 

particle nitrate and increases in sulfate mass associated with particle bound water. Figure 4a, 

below, illustrates the fraction of each PM2.5 chemical constituent at the Fulton (131210039) 

monitoring site based on annual averages for the years 2010-2012. 

Figure 8. Atlanta Annual Average PM2.5 Chemical Constituents (2010-2012) 

Figure 9 shows annual and quarterly chemical composition profiles and illustrates any seasonal 

or episodic contributors to PM2.5 mass. This “increment analysis,” combined with the other 

                                                      

24 SANDWICH stands for measured Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous mass Hybrid 

Material Balance Approach.” The SANDWICH adjustment uses an FRM mass construction methodology that 

results in reduced nitrates (relative to the amount measured by routine speciation networks), higher mass associated 

with sulfates (reflecting water included in gravimetric FRM measurements) and a measure of organic carbonaceous 

mass derived from the difference between measured PM2.5 and its non-carbon components. This characterization of 

PM2.5 mass also reflects crustal material and other minor constituents. The resulting characterization provides a 

complete mass closure for the measured FRM PM2.5 mass, which can be different than the data provided directly by 

the speciation measurements from the CSN network. 

25 Frank, N. H., SANDWICH Material Balance Approach for PM2.5 Data Analysis, National Air Monitoring 

Conference, Las Vegas, Nevada, November 6-9, 2006. http://www.epa.gov/ttn/amtic/files/2006conference/frank.pdf. 

26 Frank, N. H., The Chemical Composition of PM2.5 to support PM Implementation, the EPA State /Local/Tribal 

Training Workshop: PM2.5 Final Rule Implementation and 2006 PM2.5 Designation Process, Chicago IL, June 20-21, 

2007, http://www.epa.gov/ttn/naaqs/pm/presents/pm2.5_chemical_composition.pdf. 

27 Frank, N. H. Retained Nitrate, Hydrated Sulfates, and Carbonaceous Mass in Federal Reference Method Fine 

Particulate Matter for Six Eastern U.S. Cities. J. Air & Waste Manage. Assoc. 2006 56:500–511.

6.74

1.84

0.10

3.61

0.53

Annual Average PM2.5 Chemical Constituents

2010‐2012 (μg/m3) for Fulton County

Organic Mass from DV monitor Elemental Carbon from DV monitor

Nitrates from SANDWICH Sulfates from SANDWICH

Crustal from SANDWICH
20

relevant information, can provide additional insight as to which sources may contribute to 

observed PM levels. Simply stated, this analysis can help identify nearby sources of emissions 

that contribute to the violation at the violating monitoring site. 

Figure 9. Atlanta Annual and Quarterly Average PM2.5 Species (2010-2012)a 

a Adjusted to FRM Total PM2.5 indicates that the speciation profile and total mass depicted in this figure are the result 

of the urban increment calculation for the particular FRM monitor. 

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Annual Q1 Q2 Q3 Q4

Fulton County‐Annual and Quarterly Average PM2.5 Species

2010‐2012 Adjusted to FRM Total PM2.5

Organic Mass Elemental Carbon Nitrates Sulfates Crustal

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Organic Mass Elemental Carbon Nitrates Sulfates Crustal

Fulton County‐ Annual and Quarterly Average PM2.5 Species

2010‐2012 Adjusted to FRM Total PM2.5

Annual Q1 Q2 Q3 Q4
21

Figures 8 and 9 show that sulfate and OM are the predominant species overall. Crustal and 

elemental carbon comprise a small percentage in all four quarters. Sulfate peaks in the third 

quarter. Nitrate is a relatively small component, but is slightly higher in the first quarter. It is 

more likely that the large sulfate component is caused by SOx emissions from large electric 

generating units in the area. High levels of organic mass are typically associated with mobile 

sources, wood or biomass burning and localized combustion sources.28 

The EPA assessed seasonal and annual average PM2.5 constituents at monitoring sites within the 

area relative to monitoring sites outside of the analysis area to account for the difference between 

regional background concentrations of PM2.5, and the concentrations of PM2.5 in the area of 

analysis, also known as the “urban increment.” This analysis differentiates between the 

influences of emissions from sources in nearby areas and in more distant areas on the violating 

monitor. Estimating the urban increment in the area helps to illuminate the amount and type of 

particles at the violating monitor that are most likely to be the result of sources of emissions in 

nearby areas, as opposed to impacts of more distant or regional sources of emissions. Figure 10, 

below, includes pie charts showing the annual and quarterly chemical mass constituents of the 

urban increment. Note that in these charts, sulfates and nitrates have been adjusted to represent 

their mass in measured PM. 

Figure 10. Atlanta CBSA Urban Increment Analysis for 2010-2012.

                                                      

28 The EPA Guidance Memorandum, “Initial Area Designations for the 2012 Revised Primary Annual Fire Particulate

National Ambient Air Quality Standard,” dated April 16, 2013, Attachment 3.

57%

40%

0% 3% 0%

Fulton‐Annual Average Urban Increment

2010‐2012 (μg/m3)

Organic Mass

Elemental Carbon

Nitrates

Sulfates

Crustal
22

 

Figure 11. Atlanta CBSA Average Urban Increment Analysis for 2010-2012. 

1.27

1.36

0.01

0.20 0.02

Fulton Q‐1 Average Urban

Increment

2010‐2012 (μg/m3)

Organic Mass

Elemental

Carbon

Nitrates

Sulfates

1.53

0.88

0.00 0.00 0.00

Fulton Q‐2 Average Urban

Increment

2010‐2012 (μg/m3)

Organic Mass

Elemental Carbon

Nitrates

Sulfates

Crustal

1.49

1.01

0.00 0.09 0.00

Fulton Q‐3 Average Urban

Increment

2010‐2012 (μg/m3)

Organic Mass

Elemental

Carbon

Nitrates

Sulfates

2.17

1.24

0.03

0.00 0.04

Fulton Q‐4 Average Urban

Increment

2010‐2012 (μg/m3)

Organic Mass

Elemental Carbon

Nitrates

Sulfates

Crustal

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

Annual Q1 Q2 Q3 Q4

Fulton‐ Average Urban Increment

2010‐2012 (μg/m3)

Organic Mass Elemental Carbon Nitrates Sulfates Crustal
23

For 2012, Clayton County and Fulton County each had one monitoring site with a DV exceeding 

the NAAQS. For 2013, the Clayton County design value is below the standard at 11.1 μg/m3

, 

however, the Fulton County monitor has an invalid design value. 

A comparison of the average urban increment to the total measured PM2.5 for the Atlanta area 

indicates that the urban increment is less than one-third of the total. This indicates a meaningful 

contribution from regional sources. In addition, Fulton and adjoining counties have clear 

seasonal peaks in ambient PM2.5 concentrations in quarters 1 and 4. Looking at speciated 

components of the urban increment for the Fulton County monitor, the organic mass component 

appears to have the largest urban contribution for quarters 2, 3 and 4. Elemental carbon is the 

second highest urban increment component and peaks during Q1. Carbonaceous mass (Organic 

Carbon + Elemental Carbon) is typically associated with mobile sources, wood or biomass 

combustion, and localized combustion sources. The relatively high elemental carbon component 

could be an indicator of contribution from diesel combustion sources in the area. This analysis 

points to contribution from both regional and local PM2.5 sources. 

Emissions and emissions-related data 

In this designations process, for each area with a violating monitoring site or a monitoring site 

with invalid data, the EPA evaluated the emissions data from nearby areas using emissions 

related-data for the relevant counties to assess each county’s potential contribution to PM2.5 

concentrations at the monitoring sites in the area under evaluation. Similar to the air quality 

analysis, these data were examined on a seasonal basis. The EPA examined emissions of 

identified sources or source categories of direct PM2.5, the major components of direct PM2.5

(organic mass, elemental carbon, crustal material (and/or individual trace metal compounds)), 

primary nitrate and primary sulfate, and precursor gaseous pollutants (i.e., SO2, NOX, total VOC, 

and NH3). The EPA also considered the distance of those sources of emissions from the violating 

monitoring site. While direct PM2.5 emissions and its major carbonaceous components are 

generally associated with sources near violating PM2.5 monitoring sites, the gaseous precursors 

tend to have a more regional influence (although the EPA is mindful of the potential local NOx 

and VOC emissions contributions to PM2.5 from mobile and stationary sources) and transport 

from neighboring areas can contribute to higher PM2.5 levels at the monitoring sites. 

Emissions Data 

For each county in the Atlanta CBSA, the EPA examined the magnitude of county-level 

emissions reported in the 2011 NEI version 1 (see 

http://www.epa.gov/ttn/chief/net/2011inventory.html). These county-level emissions represent 

the sum of emissions from the following general source categories: point sources, non-point (i.e., 

area) sources, nonroad mobile, on-road mobile, and fires. The EPA also looked at the geographic 

distribution of major point sources of the relevant pollutants.29 Substantial emissions levels from 

sources in a nearby area indicate the potential for the area to contribute to monitored violations. 

                                                      

29 For purposes of this designations effort, “major” point sources are those whose sum of PM precursor emissions 

(PM2.5 + NOx + SO2 + VOC + NH3) are greater than 500 tons per year based on NEI 2011v1. 
24

To further analyze area emissions data, the EPA also developed a summary of direct PM2.5, 

components of direct PM2.5, and precursor pollutants, which is available at 

http://www.epa.gov/pmdesignations/2012standards/docs/nei2011v1pointnei2008v3county.xlsx. 

When considered with the urban increment analysis above, evaluating the components of direct 

PM2.5 and precursor gases can help identify specific sources or source types contributing to 

elevated concentrations at potentially violating monitoring sites and thus assist in identifying 

appropriate area boundaries. In general, directly emitted particulate organic carbon (POC) and 

VOCs30 contribute to PM2.5 organic mass (OM); directly emitted EC contributes to PM2.5 EC; 

NOX, NH3 and directly emitted nitrate contribute to PM2.5 nitrate mass; SO2, NH3 and directly 

emitted sulfate contribute to PM2.5 sulfate mass; and directly emitted crustal material and metal 

oxides contribute to PM2.5 crustal matter. 31,32 The EPA believes that the quantities of those 

nearby emissions as potential contributors to the PM2.5 monitors with invalid data are somewhat 

proportional to the PM2.5 chemical constituents in the estimated urban increment. Thus, directly 

emitted POC is more important per ton than SO2, partially because POC emissions are already 

PM2.5 whereas SO2 must convert to PM2.5 and not all of the emitted SO2 undergoes this 

conversion. 

Table 4, below, provides a county-level emissions summary (i.e., the sum of emissions from the 

following general source categories: point sources, non-point (i.e., area) sources, nonroad 

mobile, on-road mobile, and fires) of directly emitted PM2.5 and precursor species for the county 

with the monitoring sites with invalid data and nearby counties in the Atlanta CBSA. Table 5 

summarizes the directly emitted components of PM2.5 for the same counties in the Atlanta 

CBSA. This information will be paired with the Urban Increment composition previously shown 

in Figures 10 and 11. 

Table 4. County-Level Emissions of Directly Emitted PM2.5 and Precursors in the Atlanta 

CBSA (tons/year) 

County Total 

NH3

Total 

NOx 

Total 

Direct 

PM2.5

Total 

SO2

Total 

VOC Total 

Coweta 277 10,545 1,615 47,614 3,053 63,104

Cobb 430 17,404 1,859 19,127 15,837 54,657

Fulton 706 24,444 2,614 607 20,237 48,608

Gwinnett 477 16,271 1,504 234 17,862 36,348

DeKalb 466 14,240 1,348 247 14,595 30,895

Bartow 1,200 13,988 2,147 6,716 4,085 28,137

Clayton 180 10,045 550 621 6,232 17,629

                                                      

30 As previously mentioned, nearby VOCs are presumed to be a less important contributor to PM2.5 OM than POC. 

31 See, Seinfeld J. H. and Pandis S. N. (2006) Atmospheric Chemistry and Physics: From Air Pollution to Climate 

Change, 2nd edition, J. Wiley, New York. See also, Seinfeld J. H. and Pandis S. N. (1998) Atmospheric Chemistry 

and Physics: From Air Pollution to Climate Change, 1st edition, J. Wiley, New York. 

32 USEPA Report (2004), The Particle Pollution Report: Current Understanding of Air Quality and Emissions 

through 2003, found at: http://www.epa.gov/airtrends/aqtrnd04/pm.html.
25

County Total 

NH3

Total 

NOx 

Total 

Direct 

PM2.5

Total 

SO2

Total 

VOC Total 

Henry 187 7,477 580 76 4,448 12,769

Carroll 2,136 4,085 645 98 3,714 10,678

Cherokee 539 4,530 505 61 4,464 10,098

Heard 786 3,429 1,561 3,116 635 9,526

Forsyth 713 3,737 435 73 4,340 9,297

Newton 147 3,067 663 65 3,170 7,113

Douglas 104 3,006 294 38 2,812 6,254

Walton 583 2,556 480 25 2,482 6,125

Paulding 265 2,332 340 25 2,306 5,267

Barrow 549 2,172 351 25 1,927 5,024

Fayette 85 2,057 275 31 2,402 4,850

Rockdale 89 2,181 253 72 1,915 4,509

Spalding 178 1,642 405 36 1,780 4,042

Butts 69 1,505 256 26 856 2,713

Dawson 1,169 718 191 8 722 2,809

Haralson 397 1,452 320 19 1,678 3,866

Jasper 321 593 651 38 828 2,432

Lamar 694 847 247 10 762 2,559

Meriwether 223 1,691 948 70 1,294 4,226

Morgan 1,129 2,256 598 55 1,335 5,373

Pickens 1,212 1,017 389 12 1,088 3,717

Pike 279 574 384 17 808 2,062

Table 5. County-Level Emissions for Components of Directly Emitted PM2.5 in the Atlanta 

CBSA (tons/year) 33

County POM EC PSO4 PNO3 Crustal Residual Total 

Direct 

Fulton 1,111 628 50 9 299 517 2,614

Bartow 268 196 132 3 683 865 2,147

Cobb 582 344 62 3 381 487 1,859

Coweta 463 180 73 4 392 503 1,615

Heard 257 153 111 7 446 587 1,561

Gwinnett 708 440 17 3 130 206 1,504

DeKalb 611 337 19 3 170 208 1,348

                                                      

33 Data are based on the 2011 and 2018 Emissions Modeling Platform Data Files and Summaries

(ftp://ftp.epa.gov/EmisInventory/2011v6/v1platform) available at:

http://www.epa.gov/ttn/chief/emch/index.html#2011 (accessed 02/26/14).
26

County POM EC PSO4 PNO3 Crustal Residual Total 

Direct 

Meriwether 637 117 11 6 45 132 948

Newton 207 89 9 2 91 266 663

Jasper 449 76 11 5 24 86 651

Carroll 255 115 10 2 108 155 645

Morgan 334 95 8 4 54 103 598

Henry 200 178 11 2 87 102 580

Clayton 211 216 7 1 51 64 550

Cherokee 201 131 5 1 76 90 505

Walton 205 76 6 2 80 111 480

Forsyth 157 105 5 1 76 91 435

Spalding 192 56 5 1 60 91 405

Pickens 105 36 14 1 79 154 389

Pike 228 42 4 2 39 69 384

Barrow 129 60 4 1 50 107 351

Paulding 149 72 4 1 48 66 340

Haralson 159 55 4 1 35 65 320

Douglas 117 74 4 1 47 51 294

Fayette 99 57 3 1 55 61 275

Butts 115 55 3 1 35 47 256

Rockdale 91 60 3 1 46 52 253

Lamar 126 38 3 1 28 51 247

Dawson 94 28 2 1 27 40 191

Table 5 breaks down the direct PM2.5 emissions value from Table 4 into its components. These 

data will also be compared with the previously presented Urban Increment composition. 

Using the previously described relationship between directly emitted and precursor gases and the 

measured mass to evaluate data presented in Tables 4 and 5 the EPA identified the following 

components warranting additional review: POM, EC and SO2. The EPA then looked at the 

contribution of these constituents of interest from each of the counties included in the area of 

analysis as shown in Tables 6 a-c. 
27

Table 6a. County-Level [POM] Emissions (tons/year) 

Emissions in average tons/yr 

County POM Pct. Cumulative 

% 

Fulton 1,111 13% 13% 

Gwinnett 708 8% 22% 

Meriwether 637 8% 29% 

DeKalb 611 7% 36% 

Cobb 582 7% 43% 

Coweta 463 5% 49% 

Jasper 449 5% 54% 

Morgan 334 4% 58% 

Bartow 268 3% 61% 

Heard 257 3% 64% 

Carroll 255 3% 67% 

Pike 228 3% 70% 

Clayton 211 2% 72% 

Newton 207 2% 75% 

Walton 205 2% 77% 

Cherokee 201 2% 80% 

Henry 200 2% 82% 

Spalding 192 2% 84% 

Haralson 159 2% 86% 

Forsyth 157 2% 88% 

Paulding 149 2% 90% 

Barrow 129 2% 91% 

Lamar 126 1% 93% 

Douglas 117 1% 94% 

Butts 115 1% 95% 

Pickens 105 1% 97% 

Fayette 99 1% 98% 

Dawson 94 1% 99% 

Rockdale 91 1% 100% 
28

Table 6b. County-Level [EC] Emissions 

Emissions in average tons/yr 

County EC Pct. Cumulative 

% 

Fulton 628 15% 15% 

Gwinnett 440 11% 26% 

Cobb 344 8% 34% 

DeKalb 337 8% 43% 

Clayton 216 5% 48% 

Bartow 196 5% 53% 

Coweta 180 4% 57% 

Henry 178 4% 61% 

Heard 153 4% 65% 

Cherokee 131 3% 68% 

Meriwether 117 3% 71% 

Carroll 115 3% 74% 

Forsyth 105 3% 76% 

Morgan 95 2% 79% 

Newton 89 2% 81% 

Walton 76 2% 83% 

Jasper 76 2% 85% 

Douglas 74 2% 86% 

Paulding 72 2% 88% 

Rockdale 60 1% 90% 

Barrow 60 1% 91% 

Fayette 57 1% 92% 

Spalding 56 1% 94% 

Butts 55 1% 95% 

Haralson 55 1% 96% 

Pike 42 1% 98% 

Lamar 38 1% 98% 

Pickens 36 1% 99% 

Dawson 28 1% 100% 
29

Table 6c. County-Level [SO2] Emissions 

Emissions in average tons/yr 

County SO2 Pct. Cumulative 

% 

Coweta 47,614 60% 60% 

Cobb 19,127 24% 84% 

Bartow 6,716 8% 93% 

Heard 3,116 4% 97% 

Clayton 621 1% 98% 

Fulton 607 1% 98% 

DeKalb 247 0% 99% 

Gwinnett 234 0% 99% 

Carroll 98 0% 99% 

Henry 76 0% 99% 

Forsyth 73 0% 99% 

Rockdale 72 0% 99% 

Meriwether 70 0% 99% 

Newton 65 0% 99% 

Cherokee 61 0% 100% 

Morgan 55 0% 100% 

Jasper 38 0% 100% 

Douglas 38 0% 100% 

Spalding 36 0% 100% 

Fayette 31 0% 100% 

Butts 26 0% 100% 

Barrow 25 0% 100% 

Paulding 25 0% 100% 

Walton 25 0% 100% 

Haralson 19 0% 100% 

Pike 17 0% 100% 

Pickens 12 0% 100% 

Lamar 10 0% 100% 

Dawson 8 0% 100% 

In addition to reviewing county-wide emissions of PM2.5 and PM2.5 precursors in the area of 

analysis, the EPA also reviewed emissions from major point sources located in the area of 

analysis. The magnitude and location of these sources can help inform boundaries. Table 7 

provides facility-level emissions of direct PM2.5, components of direct PM2.5, and precursor 

pollutants (given in tons per year) from major point sources located in the Atlanta CBSA. Table 

7 also shows the distance from the facility to the closest PM2.5 monitor with incomplete data. 
30

Table 7. NEI 2011 v1 Point Source Emissions (tons/year) 

County Facility Name (Facility ID) 

Distance to NEI 2011 v1 Emissions - Tons/Year 

monitor 

(miles) NH3 NOx PM2.5 SO2 VOC Total 

Bartow 

Chemical Products 

Corporation 31 1 23 25 557 2 607 

Bartow 

Ga Power Company - Plant 

Bowen 36 15 8,371 1,161 5,889 188 15,623 

Clayton 

The William B Hartsfield 

International Airport 11 - 4,316 90 537 788 5,731 

Cobb Caraustar Industries Inc 12 - 176 44 564 15 799 

Cobb 

Ga Power Company - Plant 

McDonough/Atkinson 3 14 3,162 424 18,307 27 21,934 

Coweta 

Ga Power Company - Plant 

Yates 36 7 6,763 626 47,530 61 54,987 

Fulton 

Owens Brockway Glass 

Container Inc. 9 1 350 84 214 3 654 

Heard 

Ga Power Company - Plant 

Wansley 44 216 2,831 1,017 3,097 141 7,303 

Henry 

Transcontinental Gas Pipe 

Line Company, LLC - 

Compressor Station 120 19 - 2,259 59 - 404 2,722 

Morgan 

Georgia-Pacific Wood 

Products LLC (Madison 

Plywood) 60 - 207 139 16 199 562 

Figure 12, below, shows the major point source emissions (from the 2011 NEI in tons per year) 

in the area of analysis for the Atlanta CBSA and the relative distances of these sources from the 

monitoring location(s) with invalid data, as depicted by blue dots. The actual distance from the 

point sources to the PM monitoring location is presented in Table 7). The distance from the 

monitoring location with invalid data is particularly important for directly emitted PM2.5. The 

influence of directly emitted PM2.5 on ambient PM2.5 diminishes more than that of gaseous 

precursors as a function of distance.34 

As indicated in Figure 12, there are 12 point sources located within 60 miles of the highest 

reading invalid monitor (i.e., Fire Station #8). Plant Wansley in Heard County had SO2 and PM2.5

emissions of 75,650 tpy and 3,823 tpy, respectively, at the time of the 1997 PM2.5 designation. 

As context, Georgia Power installed emissions control technology beginning in 2002, and SO2

and PM2.5 emissions have decreased by 96 percent and 73 percent, respectively. Morgan County 

has one point source located 60 miles away from the Fire Station #8 monitor, and SO2 and PM2.5

emissions from the source are low. 

                                                      

34 Baker, K. R. and K. M. Foley. A nonlinear regression model estimating single source concentrations of primary 

and secondarily formed PM2.5. Atmospheric Environment. 45 (2011) 3758-3767. 
31

Figure 12. Major Point Source Locations in the Atlanta Area

 Population density and degree of urbanization 

The EPA evaluated the population and vehicle use characteristics and trends of the area as 

indicators of the probable location and magnitude of non-point source emissions. Population 

levels and rapid population growth in a county on the urban perimeter signifies increasing 

integration with the core urban area, and indicates that it may be appropriate to examine the 

county associated with area source and mobile source emissions for potential contribution to the 

invalid monitors. Table 8 shows the 2000 and 2010 population, population growth since 2000, 

and population density for each county in the Atlanta CBSA. 

Table 8. Population Growth and Population Density. 

County 

Population 

2000 

Population 

2010 

% 

Change 

from 

2000 

Land 

Area 

(Sq. 

Miles) 

Population 

Density 

(per Sq. 

Mile) % 

Cumul. 

% 

Fulton 816,006 926,119 13.5% 529 1,752 17% 17%

Gwinnett 588,448 808,409 37.4% 433 1,868 15% 33%

DeKalb 665,865 692,546 4.0% 268 2,582 13% 46%

Cobb 607,751 689,695 13.5% 340 2,028 13% 59%

Clayton 236,517 259,832 9.9% 143 1,822 5% 64%

Cherokee 141,903 215,248 51.7% 424 508 4% 68%
32

County 

Population 

2000 

Population 

2010 

% 

Change 

from 

2000 

Land 

Area 

(Sq. 

Miles) 

Population 

Density 

(per Sq. 

Mile) % 

Cumul. 

% 

Henry 119,341 205,283 72.0% 323 636 4% 72%

Forsyth 98,407 176,820 79.7% 226 783 3% 75%

Paulding 81,678 142,788 74.8% 313 456 3% 78%

Douglas 92,174 132,646 43.9% 199 666 3% 80%

Coweta 89,215 127,906 43.4% 443 289 2% 83%

Carroll 87,268 110,723 26.9% 499 222 2% 85%

Fayette 91,263 107,064 17.3% 197 543 2% 87%

Bartow 76,019 100,161 31.8% 459 218 2% 89%

Newton 62,001 100,130 61.5% 276 362 2% 90%

Rockdale 70,111 85,400 21.8% 131 654 2% 92%

Walton 60,687 84,092 38.6% 329 255 2% 94%

Barrow 46,144 69,732 51.1% 162 430 1% 95%

Spalding 58,417 64,111 9.7% 198 324 1% 96%

Pickens 22,983 29,454 28.2% 232 127 1% 97%

Haralson 25,690 28,786 12.1% 282 102 1% 97%

Butts 19,522 23,756 21.7% 187 127 <1% 98%

Dawson 15,999 22,304 39.4% 211 106 <1% 98%

Meriwether 22,534 21,846 -3.1% 503 43 <1% 98%

Lamar 15,912 18,250 14.7% 185 99 <1% 99%

Pike 13,688 17,905 30.8% 218 82 <1% 99%

Morgan 15,457 17,901 15.8% 350 51 <1% 100%

Jasper 11,426 13,900 21.7% 370 38 <1% 100%

Heard 11,012 11,858 7.7% 296 40 <1% 100%

Total 4,263,438 5,304,665 

Source: U.S. Census Bureau population estimates for 2000 and 2010 

The most densely populated counties are in and adjacent to the monitors with invalid data. 

Clayton, Cobb, DeKalb, Fulton and Gwinnett Counties had the highest population density (over 

1,700 persons per square mile). Barrow, Cherokee, Coweta, Douglas, Forsyth, Henry, Newton 

and Paulding have seen substantial growth (over 40 percent) since 2000. 
33

Figure 13. 2010 County-Level Population in the Area of Analysis for the Atlanta CBSA 

Area.

Traffic and VMT 

High VMT and/or a high number of commuters associated with a county is generally an 

indicator that the county is an integral part of an urban area. Mobile source emissions of NOx, 

VOC, and direct PM may contribute to ambient particulate matter that contributes to potential 

monitored violations of the NAAQS in the area. In combination with the population/population 

density data and the location of main transportation arteries, an assessment of VMT helps 

identify the probable location of nonpoint source emissions that contribute to potential violations 

in the area. Table 9 shows 2011 VMT while Figure 8 overlays 2011 county-level VMT with a 

map of the transportation arteries. This data is from the Federal Highway Administration. 
34

Table 9. 2011 VMT by County for the Atlanta CBSA.

County Total 2011 VMT Percent Cumulative % 

Fulton 12,221,928,709 22% 22% 

DeKalb 7,644,333,957 13% 35% 

Gwinnett 7,421,564,338 13% 48% 

Cobb 6,617,102,885 12% 60% 

Clayton 2,881,122,333 5% 65% 

Henry 2,214,706,881 4% 69% 

Cherokee 1,872,284,829 3% 72% 

Forsyth 1,689,888,438 3% 75% 

Bartow 1,651,438,196 3% 78% 

Douglas 1,587,530,332 3% 81% 

Coweta 1,459,781,612 3% 83% 

Carroll 1,249,251,642 2% 85% 

Rockdale 984,757,532 2% 87% 

Paulding 940,307,960 2% 89% 

Fayette 887,949,158 2% 90% 

Newton 869,539,158 2% 92% 

Barrow 703,578,903 1% 93% 

Walton 697,510,275 1% 94% 

Spalding 550,494,314 1% 95% 

Morgan 464,799,942 1% 96% 

Haralson 343,417,806 1% 97% 

Butts 333,055,273 1% 97% 

Pickens 315,317,952 1% 98% 

Meriwether 296,860,449 1% 98% 

Lamar 248,137,330 0% 99% 

Dawson 220,141,830 0% 99% 

Pike 167,900,073 0% 100% 

Jasper 135,538,407 0% 100% 

Heard 124,143,180 0% 100% 

Total 56,794,383,694 

http://www.census.gov/hhes/commuting/data/commuting.html
35

Figure 14. Overlay of 2011 County-level VMT with Transportation Arteries. 

Cherokee, Clayton, Cobb, DeKalb, Fulton, Gwinnett, and Henry Counties had the largest VMT. 

More than half of all the VMT in the CBSA are in Cobb, DeKalb, Fulton, and Gwinnett. It is 

reasonable to infer that a substantial amount of the traffic is due to inter-county commuters, 

mainly from the inner core and highly urbanized counties, most of it adjacent to the monitors 

with invalid data. 

Cherokee, Clayton, Cobb, DeKalb, Douglas, Forsyth, Fulton, Gwinnett, Henry, and Paulding 

Counties consistently rank highest in direct PM2.5/key precursor emissions (i.e., VMT and 

population). Bartow, Clayton, Cobb, Coweta, and Fulton Counties have large PM2.5 precursor 

emissions from stationary sources in the CBSA. Carroll, Newton, and Rockdale Counties are 

mid-ranked in emissions and mid-ranked for population and VMT. Barrow, Butts, Dawson, 

Fayette, Haralson, Heard, Jasper, Lamar, Meriwether, Morgan, Pickens, Pike, Spalding, and 

Walton Counties have relatively low emissions and relatively low VMT/population counts, and 

lack large singular point source contributors. 
36

Meteorology 

The EPA evaluated available meteorological data to determine how meteorological conditions, 

including, but not limited to, weather, transport patterns, and stagnation conditions, could affect 

the fate and transport of directly emitted particulate matter and precursor emissions from sources 

in the area of analysis. The EPA used two primary tools for this assessment: wind roses and 

kernel density estimation (KDE). When considered in combination with area PM2.5 composition 

and county-level and facility emissions source location information, wind roses and KDE can 

help to identify nearby areas contributing to violations at violating monitoring sites. 

Wind roses are graphic illustrations of the frequency of wind direction and wind speed. Wind 

direction can indicate the direction from which contributing emissions are transported; wind 

speed can indicate the force of the wind and thus the distance from which those emissions are 

transported. The EPA constructed wind roses from hourly observations of wind direction and 

wind speed using 2009-2012 data from National Weather Service locations archived at the 

National Climate Data Center.35 When developing these wind roses, the EPA also used wind 

observations collected at meteorological sampling stations collocated at air quality monitoring 

sites, where these data were available. Figure 15 shows wind roses that the EPA generated from 

data relevant in the Atlanta CBSA. 

Figure 15. Wind Roses in the Atlanta Area.

                                                      

35 ftp.ncdc.noaa.gov/pub/data/noaa or 

http://gis.ncdc.noaa.gov/map/viewer/#app=cdo&cfg=cdo&theme=hourly&layers=1&node=gis Quality assurance 

of the National Weather Service data is described here: http://www1.ncdc.noaa.gov/pub/data/inventories/ish-qc.pdf 
37

As shown in Figure 15, there is a pattern across the CBSA of predominantly northwest winds 

and a smaller component of east winds, mostly at mid-level speeds of 4 to 10 meters per second, 

suggesting that potential emission sources in the north-through-west upwind direction and to a 

lesser extent in the east upwind direction have potential to contribute to PM levels at the invalid 

monitors. 

In addition to wind roses, the EPA also generated KDE plots to represent the frequency of 

HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) backward trajectories at 

monitoring sites with invalid data.36,37 These KDEs are graphical statistical estimations to 

determine the density of trajectory endpoints at a particular location represented by a grid cell. 

The EPA used KDEs to characterize and analyze the collection of individual HYSPLIT 

backward trajectories.38 Higher density values, indicated by darker blue colors, indicate a greater 

frequency of observed trajectory endpoints within a particular grid cell. Figure 16 shows 

HYSPLIT KDE plots for the Atlanta area summarized by calendar quarter for the 2010-2012 

period. The HYSPLIT KDE is weighted in the northwesterly direction, indicating a greater 

frequency of trajectories passing over grid cells to the northwest, but the plots also indicate a 

high frequency of trajectories passing over the primary metro-Atlanta counties as well. 

                                                      

36 In some past initial area designations efforts, the EPA has used HYSPLIT backward trajectories to assist in 

determining nonattainment area boundaries. A HYSPLIT backward trajectory is usually depicted on a standard map 

as a single line, representing the centerline of an air parcel’s motion, extending in two dimensional (x,y) space from 

a starting point and regressing backward in time to a point of origin. Backward trajectories may be an appropriate 

tool to assist in determining an air parcel’s point of origin on a day in which a short-term standard, such as an 8-hour 

standard or a 24-hour standard, was exceeded. However, for an annual standard, such as the 2012 annual PM2.5

NAAQS, every trajectory on every day is important to consider. Plotting a mass of individual daily (e.g., 365 

individual back trajectories), or more frequent, HYSPLIT trajectories may not be helpful as this process is likely to 

result in depicting air parcels originating in all directions from the violating monitoring site. 

37 HYSPLIT - Hybrid Single Particle Lagrangian Integrated Trajectory Model, 

http://www.arl.noaa.gov/HYSPLIT_info.php

38 The KDEs graphically represent the aggregate of HYSPLIT backward trajectories for the years 2010-2012, run 

every third day (beginning on the first day of monitoring), four times each day, and ending at four endpoint heights.  
38

Figure 16. HYSPLIT Kernel Density Estimation Plots for the Atlanta CBSA Area. 
39
40

In summary, for the monitors with invalid data in the Atlanta Area, the HYPSPLIT KDE plots 

and wind roses suggest greatest potential contribution of emissions from Clayton, Cobb, DeKalb, 

Douglas, and Paulding. 

 

Geography/topography 

To evaluate the geography/topography factor, the EPA assessed physical features of the area of 

analysis that might define the airshed and thus affect the formation and distribution of PM2.5

concentrations over the area. The Atlanta Area does not have any geographical or topographical 

barriers meaningfully limiting air pollution transport within its air shed. Therefore, this factor did 

not play a meaningful role in this evaluation.

Conclusion for the Counties in the Atlanta CBSA for which the EPA is Deferring 

Designations 

Speciation and urban increment data show high OM and sulfur content. Organic Compounds and 

SOx components are the most important portions of the total PM2.5 mass throughout the year. 

Organic Compounds are predominately attributed to biogenic emissions sources. The 

predominant source of SOx and PM emission are point sources. 

Based on the assessment of factors described above, both individually and in combination, the 

EPA has preliminarily concluded that designations for the following counties in Georgia as a part 
41

of the Atlanta should be deferred because there are incomplete design values with the 

surrounding monitors and based on analysis of the information above the EPA concludes that 

these counties contain emissions that would be relatively more likely to contribute to any 

potential violations: Bartow, Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Forsyth, 

Fulton, Gwinnett, Henry, and Paulding Counties. These counties are also part of in the Atlanta 

nonattainment area for the 1997 annual PM2.5 NAAQS. 

Bartow County – This nearby county does not have a monitoring site, but has the second highest 

PM2.5 emissions in the CBSA with 2,147 tpy and third highest SO2 emissions in the CBSA with 

6,716 tpy. There are two point sources with substantial SO2 emissions- Georgia Power 

Company’s Plant Bowen (5,889 tpy), and Chemical Products Corporation (557 tpy). Although 

all winds are relevant when designating areas for an annual NAAQS, here the predominant 

winds blow in the direction from Bartow County, toward the monitors with invalid data. 

Cherokee County – This nearby county does not have a monitoring site, but the meteorology 

analysis indicates a high frequency of winds blowing from Cherokee County toward monitors 

with invalid data. This county has more than 10,000 tons of PM2.5 related emissions (5th highest 

in the CBSA), including significant population-related sources (including over 1.8 billion miles 

VMT). 

Clayton County – This nearby county has an attaining monitoring site, but the EPA has 

concluded that the county would be relatively likely to contribute to particulate matter 

concentrations at monitors in the CBSA with invalid data in the Atlanta area, particularly in light 

of the high level of emissions from the Hartsfield-Jackson International Airport. Furthermore, 

the meteorology analysis indicates that winds blow from Clayton County toward monitors with 

invalid data during some time periods. 

Cobb County – This county has a monitor with invalid data for 2011-2013, and is being deferred 

on that basis. Additionally, Cobb County has the third highest PM2.5 emissions in the CBSA 

with 1,859 tpy and the second highest SO2 emissions in the CBSA with 19,127 tpy. There are 

two point sources with substantial SO2 emissions: Georgia Power Company’s Plant 

McDonough/Atkinson (18,307 tpy), and Caraustar Industries Inc (564 tpy). 

Coweta County – This nearby county does not have a monitoring site, but has the highest SO2 

emissions in the CBSA with 47,614 tpy, and fourth highest PM2.5 emissions in the CBSA with 

1,615 tpy. There is one point source with substantial SO2 and PM2.5 emissions- Georgia Power 

Company’s Plant Yates (47,530 and 626 tpy, respectively). The meteorology analysis indicates 

that winds blow from Coweta County toward monitors with invalid data during some time 

periods. The EPA has determined that a designation for Coweta should be deferred because of 

the relative likelihood that emissions from this large point source could to contribute to invalid 

monitors in the Atlanta CBSA, should those monitors subsequently show a violation. 

DeKalb County – This nearby county has a valid attaining design value. However, the EPA has 

concluded that the county is less likely to contribute to particulate matter concentrations at 

monitors with invalid data through emissions from non-point sources (e.g., area sources) and 

from mobile source emissions. The county has the seventh highest level of PM2.5 emissions in 
42

the CBSA (1,348 tpy), and the second largest VMT (7.6 billion miles). The county is highly 

urbanized and has 13 percent of the CBSA population, and is 12 miles from the highest reading 

invalid monitor. The meteorology analysis indicates that winds blow from Dekalb County 

toward monitors with invalid data during some time periods. 

Douglas County – This nearby county does not have a monitoring site, but the EPA has 

concluded that the county is relatively more likely to contribute to the particulate matter 

concentrations to monitors with invalid data through emissions from non-point sources (e.g., area 

sources) and from mobile source emissions. The County is the seventh fastest population growth 

(43 percent). Although all winds are relevant when designating areas for an annual NAAQS, here 

the predominant winds blow in the direction from Douglas County, toward the highest reading 

invalid monitor. 

Forsyth County – This nearby county does not have a monitoring site, but the EPA has 

concluded that the county likely contributes to the particulate matter concentrations in violation 

of the 2012 annual PM2.5 NAAQS through emissions from non-point sources (e.g., area sources) 

and from mobile source emissions. The County is the fastest population growth (79 percent) and 

eighth largest VMT (over 1.6 billion miles). 

Fulton County – This county has a monitor with invalid data for 2011-2013, and is being 

deferred on that basis. Furthermore, Plant McDonough/Atkinson power plant is less than three 

miles from the Fulton County monitor. In addition, there is a major rail yard within a mile of the 

monitor. The county has the highest PM2.5 emissions with 2,614 tpy. There is one point sourceOwens Brockway Glass Container Inc., which has a modest 84 tpy of SO2 emissions. Although 

all winds are relevant when designating areas for an annual NAAQS, here the predominant 

winds blow in the direction from Fulton County, toward monitors with invalid data. 

Gwinnett County – This county has a monitor with invalid data for 2011-2013, and is being 

deferred on that basis. Additionally, Gwinnett County has the sixth highest level of PM2.5

emissions in the CBSA with 1,504 tpy and third largest VMT (7.4 billion miles). The county is 

highly urbanized and has 15 percent of the CBSA population. 

Henry County – This nearby county does not have a monitoring site, but the EPA has concluded 

that the county likely contributes to the particulate matter concentrations at the incomplete 

monitors in the Atlanta CBSA through emissions from non-point sources (e.g., area sources) and 

from mobile sources The county is highly urbanized as part of the Atlanta metropolitan area, has 

the third largest population growth (72 percent), and sixth largest VMT (2.2 billion miles). The 

meteorology analysis indicates that winds blow from Henry County toward monitors with invalid 

data during some time periods. 

Paulding County – This county has a monitor with invalid data for 2011-2013, and is being 

deferred on that basis. The county is highly urbanized as part of the Atlanta metropolitan area, 

and has the second largest population growth (74 percent). Although all winds are relevant when 

designating areas for an annual NAAQS, here the predominant winds blow from the direction of 

Paulding County toward monitors with invalid data. 
43

The EPA has made the determination not to include seven counties in the Atlanta Area CBSA in 

the boundary for the Atlanta Area that the EPA is deferring designations for the 2012 PM2.5 

NAAQS. Based on currently available information, the EPA believes that these counties would 

be relatively less likely to be contributing to a hypothetical NAAQS violation at any of the 

monitors with affected data. Accordingly, the EPA believes there is comparatively less of a 

justification to defer designations for these counties at this time. Discussed as follows, these 

counties include: Barrow, Carroll, Fayette, Heard, Newton, Rockdale, Spalding and Walton. 

Barrow County – There are low emissions; low population; low VMT. This rural county has no 

major emission sources and is 44 miles away from the Fire Station #8 monitor. As context, SO2

and PM emissions have decreased 80 percent and 50 percent, respectively, since 2001. 

Carroll County – There are low emissions; moderate population growth; moderate VMT and 

commuters. The predominantly rural county has no major emission sources and is 27 miles 

away from the Fire Station # 8 monitor. As context, SO2 and PM emissions have decreased 88 

percent and 75 percent, respectively since 2001. 

Fayette County – There are low emissions; moderate population growth; moderate VMT and 

commuters in this county. The county is partially urbanized, has no major emission sources and 

it is 40 miles away from the Fire Station #8 monitor. As context, SO2 and PM emissions have 

decreased 67 percent and 60 percent, respectively, since 2001. 

Heard County– A portion of this county was included in the previous nonattainment area in 2005 

because of emissions from Plant Wansley. As context, Plant Wansley had SO2 scrubber controls 

installed in early 2008; this achieved a 96 percent SO2 reduction. Otherwise this county has low 

population; and low VMT. 

Newton County – There are low emissions; moderate VMT and low commuters. The 

predominantly rural county contains no major emission sources and is 37 miles away from the 

Fire Station #8 monitor. As context, SO2 and PM emissions have decreased 71 percent and 42 

percent, respectively, since 2001. 

Rockdale County – There are relatively low emissions; moderate population growth; moderate 

VMT and low commuters. The County is partially urbanized, has no major emission sources and 

is 26 miles away from the Fire Station #8 monitor. As context, SO2 and PM emissions have 

decreased 68 percent and 67 percent, respectively, since 2001. 

Spalding County – There are low emissions; low population; and low VMT. This mostly rural 

county has no major emission sources and is 39 miles away from the Fire Station #8 monitor. As 

context, SO2 and PM emissions have decreased 80 percent and 49 percent, respectively, since 

2001. 

Walton County – There are low emissions; low population; and low VMT. The mostly rural 

county has no major emission sources and it is 40 miles away from the Fire Station #8 monitor. 

As context, Walkton County is adjacent to DeKalb County (which has a valid attaining design 
44

value for 2011-2013), and SO2 and PM emissions in Walton County have decreased 86 percent 

and 48 percent, respectively, since 2001. 

Brunswick Area 

The Brunswick, Georgia CBSA is wholly contained in Georgia and includes three counties – 

Brantley, Glynn and McIntosh. The most populated and industrialized portion of Brunswick is 

contained within Glynn County. More information on the EPA’s evaluation of the emissions for 

the counties in the CBSA is provided below. The Brunswick area does not have any geographical 

or topographical barriers meaningfully limiting air pollution transport within its air shed. 

Therefore, this factor did not play a meaningful role in this evaluation. The Brunswick CBSA is 

outlined in green in Figure 17 along with the location of point sources and air quality monitors. 

The Glynn County monitor located in the Albany area has incomplete 2011-2013 data. Based on 

incomplete data, the incomplete Glynn County DV is 8.2 μg/m3

. 

The City of Brunswick, in Glynn County, Georgia, has one major point source – Brunswick 

Cellulose Inc. Other sources include county level emissions from non-point sources, nonroad 

Figure 17. Brunswick CBSA with Point Sources and Air Quality Monitor Locations
45

mobile, on-road mobile, fires and local traffic. Brantley and McIntosh Counties are the other 

counties in the Brunswick CBSA. The emissions in each of these counties are relatively lower 

than comparable emissions in Glynn County, particularly for the precursors that tend to drive 

PM2.5 problems in the southern part of Georgia. Additionally, most of the population in the 

CBSA is concentrated in Glynn County. Summary information on emissions and population can 

be found in the Table 10 below. 

Table 10. Summary statistics for the Brunswick, Georgia CBSA 

Glynn Brantley McIntosh 

Core urbanized 

county or outlying? Core Outlying Outlying 

SO2 emissions (tpy) 647 41 18 

PM2.5 emissions (tpy) 1,013 68639 373 

NOx emissions (tpy) 5,983 746 2,219 

NH3 emissions (tpy) 174 216 47 

VOC emissions (tpy) 5,636 822 2,100 

Population 79,863 18,487 14,287 

Population (% of 

CBSA) 71% 16% 13% 

VMT (Millions) 1,046 166 441 

VMT (% of CBSA) 63% 10% 27% 

The EPA also evaluated the meteorology in the area by evaluating wind data collected at two 

locations in the Brunswick CBSA as shown in Figure 18 below. As shown in the figure, there are 

two airports near the Brunswick area, Brunswick Golden Isles Airport and Malcolm McKinnon 

Airport, with available surface level wind speed and direction data. The wind rose from each 

airport indicates that there is a pattern across the CBSA of winds blowing from all directions, but 

with a higher frequency from the west-southwest, southeast and northeast, mostly at low to midlevel speeds of 2 to 6 meters per second. The wind patterns suggest that potential emission 

sources in Brantley and McIntosh counties, generally in the west-southwest, southeast and 

northeast upwind directions should be considered for analysis. 

                                                      

39 The majority of these direct PM2.5 emissions are from non-point sources and are event related. If a violation of the 

NAAQS occurs when three years of complete data becomes available, the potential impacts of these event-related 

emissions will be further evaluated for potential exclusion from the design value calculations. 
46

Figure 18. Wind Roses in the Brunswick Area

Brunswick, Georgia CBSA Conclusion 

WIND ROSE PLOT:

Brunswick Golden Isle Airport

2009-2012

NORTH

SOUTH

WEST EAST

2%

4%

6%

8%

10%

WIND SPEED 

(m/s)

 >= 11.1

 8.8 - 11.1

 5.7 - 8.8

 3.6 - 5.7

 2.1 - 3.6

 0.5 - 2.1

Calms: 29.24%

DISPLAY:

 Wind Speed

Direction (blowing from)

WIND ROSE PLOT:

Malcolm McKinnon Airport

2009-2012

NORTH

SOUTH

WEST EAST

2%

4%

6%

8%

10%

WIND SPEED 

(m/s)

 >= 11.1

 8.8 - 11.1

 5.7 - 8.8

 3.6 - 5.7

 2.1 - 3.6

 0.5 - 2.1

Calms: 14.30%

DISPLAY:

 Wind Speed

Direction (blowing from)
47

The EPA is concluding that Glynn County in the Brunswick CBSA has the most likelihood of all 

the counties to contribute to a hypothetical violation of the standard at the Glynn County monitor 

that currently has incomplete data. The EPA identified Glynn County because the monitor with 

incomplete data is located in the southeast portion of this county and Glynn County contains the 

majority of emissions, VMT, and is the population center of the CBSA. The outlying counties of 

Brantley and McIntosh have low population, and low VOC and SO2 emissions in comparison to 

Glynn County. The direct PM2.5 emissions from Brantley and McIntosh counties are primarily 

non-point source emissions largely from fire events and road dust sources. The direct PM2.5 

emissions from these non-point sources are generally local in nature and are less likely to be 

transported large distances due to their close proximity to the ground. Accordingly, because of 

incomplete data at the Glynn County monitor in the Brunswick CBSA, the EPA is deferring a 

designation for Glynn County. Furthermore, the EPA is not deferring a designation for Brantley 

and McIntosh counties, and is designating these counties as unclassifiable/attainment based on 

the reduced likelihood that emissions from these counties would contribute to a hypothetical 

violation at the Glynn County monitor. Should such violation be identified in the future, the 

EPA will further evaluate Brantley and McIntosh counties for potential contribution to emissions 

at the Glynn County monitor. 

Augusta Area (Augusta, GA-SC CBSA) 

Augusta is located in a bi-state CBSA that includes seven counties – five in Georgia (Burke, 

Columbia, McDuffie, Lincoln, and Richmond) and two in South Carolina (Aiken and Edgefield). 

The most populated and industrialized portion of the Augusta area where most of the emissions 

and emissions activities occur is primarily contained in three of the seven counties – Richmond 

and the southern region of Columbia County in Georgia, and the western region of Aiken County 

in South Carolina. More information on the EPA’s evaluation of the emissions for the counties in 

the CBSA is provided below. The Augusta area does not have any geographical or topographical 

barriers meaningfully limiting air pollution transport within its air shed. Therefore, this factor did 

not play a meaningful role in this evaluation. The Augusta CBSA is outlined in green in Figure 

19, along with the location of point sources and air quality monitors. 
48

The Richmond County monitor located in the Georgia portion of the Augusta area has 

incomplete 2011-2013 data. Based on incomplete data, the incomplete Richmond County DV is 

10.5 μg/m3. As context, the monitor in Edgefield County, South Carolina (also part of this 

CBSA) attains the 2012 annual PM2.5 NAAQS with a DV of 9.3 μg/m3

. 

The EPA evaluated PM2.5 and precursor emissions, along with other related data from the 

counties in the Augusta CBSA. As shown in Table 11, Richmond and Aiken Counties account 

for 98 percent of SO2 emissions (45 and 53 percent, respectively) and 67 percent (26 and 41 

percent, respectively) of PM2.5 emissions. Richmond, Columbia and Aiken Counties, together 

account for 85 percent of the population and 83 percent of the VMT. Population within the 

CBSA is sharply divided between core and outlying counties. The largest outlying county 

(Edgefield County) accounts for only 5% of the CBSA population, and all four outlying counties 

combined comprise only 14% of the CBSA’s population. By contrast, even the smallest core 

county (Columbia County) comprises 22% of the CBSA population, and the core counties 

cumulatively comprise 85% of the CBSA’s population. 

Figure 19. Augusta CBSA with Point Sources and Air Quality Monitor Locations
49

Table 11. Summary statistics for the Augusta, GA-SC CBSA 

 Aiken Columbia Richmond Burke Lincoln McDuffie Edgefield 

State South 

Carolina

Georgia Georgia Georgia Georgia Georgia South 

Carolina

Core 

urbanized 

county or 

outlying? 

Core Core Core Outlying Outlying Outlying Outlying

SO2 

Emissions 

(tpy) 

5,020 28 4,294 73 6 100 45

PM2.5 

emissions 

(tpy) 

3,660 447 2,364 1,510 203 429 419

NOx 

emissions 

(tpy) 

7,144 3,758 10,110 1,414 405 1,655 664 

NH3 

emissions 

(tpy) 

2,605 118 1,798 672 72 138 434 

VOC 

emissions 

(tpy) 

7,156 3,946 8,471 1,693 1,014 1,252 1,222 

Population 160,622 124,965 201,056 23,350 7,966 21,852 26,970

Population 

(% of 

CBSA) 

28% 22% 35% 4% 1% 4% 5%

VMT 

(Millions) 

1,717 1,014 1,990 299 86 333 225 

VMT (% of 

CBSA) 

30% 18% 35% 5% 2% 6% 4% 

The EPA also evaluated the meteorology in the area by evaluating wind data collected at three 

locations in the Augusta CBSA as shown in Figure 20. As shown, the frequency and intensity of 

wind from any given direction is variable. 
50

Augusta GA-SC CBSA Conclusion 

Based on the information summarized in Table 11 and the wind rose data, the EPA has 

concluded that of the five counties in the Augusta CBSA, Columbia and Richmond Counties in 

Georgia, and Aiken County, South Carolina, are the most likely to contribute to potential 

violations of the standard at the Richmond County monitor, which currently has incomplete data. 

The EPA identified Aiken County as a county with relatively higher potential to contribute to the 

invalid monitor because of Aiken County’s high population, and the fact that nearly half of SO2

and PM2.5 emissions in the CBSA originate in Aiken County. Two point sources in Aiken 

County have combined SO2 emissions greater than 5,000 tpy, and countywide direct PM2.5

emissions exceed 3,600 tpy. While wind rose data may suggest a lesser contribution from Aiken 

County, there remains the potential for transport of these emissions into Richmond County 

because winds blow from the northeast at times and the point sources have elevated stack 

releases which may be transported longer distances. 

Although Columbia County has somewhat lower emissions, this county is home to roughly onethird of the population of the CBSA, is experiencing high population growth, and has VMT 

Figure 20. Augusta GA-SC CBSA Wind Rose Data
51

comparative to Richmond and Aiken Counties. Wind rose data indicate the potential for transport 

of emissions from Columbia County to the affected monitor in Richmond County. 

Accordingly, because of the affected monitor in Richmond County, and the potential for 

contribution to that monitor from Aiken County and Columbia County, the EPA is deferring its 

decision on designations for these three counties. 

However, the EPA is designating the remaining counties unclassifiable/attainment for the 

following reasons. Although Burke County has comparatively higher direct PM2.5 emissions due 

to non-point sources than the other outlying counties, these are still meaningfully lower than the 

emissions from the core counties of Richmond and Aiken. These non-point source emissions are 

primarily from fire events, agricultural and road dust, and waste disposal sources. The direct 

PM2.5 emissions from these non-point sources are generally local in nature and are relatively less 

likely to be transported large distances. The distance from Burke County to the Richmond 

County monitor is large compared to the emission sources in Richmond, Columbia and Aiken 

Counties. The small population and low VMT of Burke County and the outlying counties of 

Lincoln, McDuffie, and Edgefield Counties lead the EPA to believe that these counties would be 

relatively likely to be contributing to any nearby violations that may be identified with 

forthcoming data. Accordingly, the EPA will not defer designations for the counties of Burke, 

Lincoln, McDuffie, or Edgefield Counties, but will instead designate them 

unclassifiable/attainment based on the data available at this time. 

Columbus Area (Columbus, GA-AL CBSA) 

Columbus is in a bi-state CBSA that includes five counties – four in Georgia (Chattahoochee, 

Harris, Marion, and Muscogee) and one in Alabama (Russell). The most populated and 

industrialized portion of the Columbus area is mostly contained in two of the five counties – 

Muscogee County in Georgia, and Russell County in Alabama. The Columbus CBSA is outlined 

in green in Figure 21, along with the location of point sources and air quality monitors. 
52

The Muscogee County monitor located in the Georgia portion of the Columbus area has 

incomplete 2011-2013 data. As context, the monitor in Russell County, Alabama (also part of 

this CBSA) attains the 2012 annual PM2.5 NAAQS with a DV of 11.2 μg/m3

. As further context, 

based on incomplete data, the incomplete Muscogee County DV is 10.8 μg/m3

. 

The EPA evaluated PM2.5 and precursor emissions, along with other related data from the 

counties in the Columbus area. As shown in Table 3, Russell County alone accounts for 94 

percent of SO2 emissions and 52 percent of PM2.5 emissions. The most populous area is located 

in the Georgia portion of the CBSA in Muscogee County, which accounts for 64 percent of the 

population, followed by Russell County, Alabama with 18 percent. A similar pattern in VMT is 

also noted with Muscogee and Russell Counties together accounting for 82 percent of the VMT 

(64 percent and 18 percent, respectively). By comparison, the outlying Georgia counties of 

Chattahoochee, Harris, and Marion account for approximately 35 percent of PM2.5 emissions and 

less than 5 percent of SO2 emissions and have no major point sources.40 Only 18 percent of the 

                                                      

40 For purposes of this designations analysis, “major” point sources are those whose sum of PM precursor 

emissions (PM2.5 + NOx + SO2 + VOC + NH3) are greater than 500 tpy based on (NEI 2011v1. NOx is 

nitrogen oxides; VOC is volatile organic compounds; and NH3 is ammonia. The EPA notes that emissions 

from all source categories are relevant in the context of designations, but the presence or absence of major 
53

CBSA population resides in these outlying counties, which is also reflected in a low proportion 

of VMT (20 percent). 

Table 12. Summary statistics for the Columbus, GA-AL CBSA 

 Muscogee Russell Chattahoochee Harris Marion 

State Georgia Alabama Georgia Georgia Georgia

Core 

urbanized 

county or 

outlying? 

Core Core Outlying Outlying Outlying 

SO2 emissions 

(tpy) 

84 3,487 51 43 29

PM2.5 

emissions 

(tpy) 

729 3,083 714 809 554 

NOx 

emissions 

(tpy) 

4,969 5,324 429 2,335 349 

NH3 

emissions 

(tpy) 

144 583 68 109 572 

VOC 

emissions 

(tpy) 

6,105 6,591 619 1,848 502 

Population 190,484 53,238 11,131 32,146 8,742 

Population 

(% of CBSA) 

64% 18% 4% 11% 3% 

VMT 

(Millions) 

1,655 738 74 428 78 

VMT (% of 

CBSA) 

56% 25% 2% 14% 3% 

The EPA also evaluated the meteorology in the area by evaluating wind data collected at three 

locations in the Columbus CBSA as shown in Figure 22. The wind roses indicate that wind 

                                                      

point sources helps to identify nearby areas with emissions that are likely to be contributing to violations 

of the NAAQS. 
54

direction is less likely to originate from the southwest or from the northeast. North-northwest 

winds are more frequently observed. 

Figure 22. Wind Rose Data for Columbus GA-AL CBSA

Columbus GA-AL CBSA Conclusion 

Based on the wind rose data and the information summarized in Table 12, the EPA has 

concluded that of the five counties in the Columbus CBSA, Muscogee County, Georgia and 

Russell County, Alabama have relatively higher potential to contribute to potential violations of 

the standard at the Muscogee County monitor, currently has incomplete data. The EPA identified 

Muscogee County because the monitor with incomplete data is located in this county. The EPA 

identified Russell County as a potentially contributing county because it accounts for the 

majority of emissions in the CBSA, despite the fact that its population is less than one-third of 

Muscogee County’s. Wind rose data further indicate that fairly frequent winds from the southerly 

direction increase the potential for transport of these emissions from Russell County to 

Muscogee County. Because of incomplete data at the Muscogee County monitor in the 

Columbus CBSA, the EPA is deferring a designation for Russell and Muscogee Counties. 
55

By contrast, the outlying counties of Chattahoochee and Marion have low emissions, population, 

and VMT. The wind rose data also indicate infrequent and low intensity winds impacting the 

Muscogee County monitor from the southeasterly direction (i.e., from these counties). The third 

outlying county, Harris County, has comparatively higher VMT than Chattahoochee or Marion 

County. However, Harris County nevertheless has relatively low emissions compared to the two 

core counties. This information leads the EPA to believe that these Chattahoochee, Marion and 

Harris Counties are relatively less likely to contribute to any potential violation that may exist at 

the Muscogee County, Georgia monitor. Accordingly, the EPA will not defer designation for the 

Chattahoochee, Harris, or Marion Counties, and is instead at this time designating them 

unclassifiable/attainment based on the available data. 

Savannah Area (Savannah, Georgia CBSA) 

The Savannah, Georgia CBSA is wholly contained in Georgia and includes three counties – 

Bryan, Chatham, and Effingham. Most of the most populated and industrialized portion of 

Savannah is contained within Chatham County. More information on the EPA’s evaluation of the 

emissions for the counties in the CBSA is provided below. The Savannah area does not have any 

geographical or topographical barriers meaningfully limiting air pollution transport within its air 

shed. Therefore, this factor did not play a meaningful role in this evaluation. The Savannah 

CBSA is outlined in green in Figure 8, along with the location of point sources and air quality 

monitors. 
56

Figure 23. Savannah, Georgia CBSA with Point Sources and Air Quality Monitor Locations 

The Chatham County monitor has incomplete 2011-2013 data that do not allow calculation of a 

valid 2011-2013 DV. Based on incomplete data, the incomplete Chatham County DV is 10.2 

μg/m3

. 

In particular, the EPA evaluated PM2.5 and SO2 emissions and related data from the counties in 

the Savannah CBSA. As shown in Table 4, Chatham and Effingham Counties account for 99 

percent of SO2 emissions (69 and 30 percent, respectively) and 70 percent of PM2.5 emissions (42 

percent and 28 percent, respectively). Bryan County has 30 percent of PM2.5 emissions from nonpoint sources. Chatham County is the most populous area with 76 percent of the CBSA 

population followed by Effingham (15 percent) and Bryan (9 percent). A similar pattern in VMT 

is also noted with Chatham County accounting for 73 percent of VMT and Effingham and Bryan 

Counties contributing 11 percent and 15 percent, respectively to VMT. 
57

Table 13. Summary statistics for the Savannah, Georgia CBSA 

Chatham Effingham Bryan 

Core urbanized county 

or outlying? Core Outlying Outlying 

SO2 Emissions (tpy) 10,312 4,567 97 

PM2.5 emissions (tpy) 2,039 1,332 1,43941

NOx emissions (tpy) 17,000 3,819 2,784 

NH3 emissions (tpy) 452 280 123 

VOC emissions (tpy) 12,215 2,550 2,147 

Population 265,998 52,420 30,412 

Population (% of 

CBSA) 76% 15% 9% 

VMT (Millions) 2,804 437 582 

VMT (% of CBSA) 73% 11% 15% 

The EPA also evaluated the meteorology in the area by evaluating wind data collected at two 

locations in the Savannah CBSA as shown in Figure 24. The wind rose data shows that the 

frequency of wind direction and intensity is variable. 

                                                      

41 The majority of these direct PM2.5 emissions are from non-point sources and are event related. If a violation of the 

NAAQS occurs when three years of complete data becomes available, the potential impacts of these event-related 

emissions will be further evaluated. 
58

Figure 24. Wind Rose Data for the Savannah, Georgia CBSA 

Savannah Georgia CBSA Conclusion 

Based on the wind rose data that shows consistently variable wind direction and intensity and the 

information summarized in Table 13, the EPA is concluding that two of the three counties in the 

Savannah CBSA are more likely to have the potential to contribute to any violations of the 

standard at the Chatham County monitor, which currently has incomplete data. The EPA 

identified Chatham County because the monitor with incomplete data is located in this county 

and Chatham County contributes the majority of emissions, VMT, and is the population center of 

the CBSA. The EPA identified Effingham County as a potentially contributing county because 

Effingham County has three point sources having combined SO2 emissions greater than 4,500 

tpy (30 percent of CBSA SO2 emissions) and over 1,300 tpy of direct PM2.5 emissions. In 

addition, the EPA’s analysis of meteorology indicates potential transport of these emissions to 

the PM2.5 monitoring site in Chatham County. 

By contrast, outlying Bryan County has low SO2 emissions (97 tpy) in comparison to Chatham 

and Effingham Counties (respectively, 10,312 tpy and 4,567 tpy). Bryan County also has the 

lowest population of any county in the CBSA. Although Bryan County does have a similar level 

of direct PM2.5 emissions as Effingham County, Bryan County is located a substantial distance 

from the Chatham County monitor in Savannah and direct PM2.5 emissions generally have more 
59

localized impacts. Accordingly, because of incomplete data at the Chatham County monitor in 

the Savannah CBSA, and the potential for Effingham County to contribute to that monitor, the 

EPA is deferring a designation for Chatham and Effingham Counties. However, the EPA is not 

deferring a designation for Bryan County and is instead designating this county as 

unclassifiable/attainment based on the available data. 

Valdosta Area (Valdosta, Georgia CBSA) 

The Valdosta, Georgia CBSA is wholly contained in Georgia and includes four counties – 

Brooks, Echols, Lanier, and Lowndes. The Valdosta CBSA and surrounding counties are shown 

in Figure 25 along with the location of point sources and air quality monitors. 

 Figure 25. Valdosta CBSA Point Source and Air Quality Monitor Locations 

The Lowndes County monitor has incomplete 2011-2013 data that do not allow calculation of a 

valid 2011-2013 DV. Based on incomplete data, the incomplete Lowndes County DV is 8.9 

μg/m3

. 
60

In particular, the EPA evaluated PM2.5 and SO2 emissions and related data from the counties in 

the Valdosta CBSA. As shown in Table 5, Brooks and Lowndes Counties account for 96 percent 

of SO2 emissions (20% and 76%, respectively) and 86% of PM2.5 emissions (52 % and 34%, 

respectively). Lowndes County is the most populous area with 78% of the CBSA population, 

followed by Brooks (12%), Lanier (7%) and Echols (3%). A similar pattern in VMT is also noted 

with Lowndes and Brooks Counties accounting for 93% (81% and 12%, respectively) to CBSA 

VMT, and Echols and Lanier together contributing 7% of VMT. 

Table 14. Summary statistics for the Valdosta, Georgia CBSA 

Lowndes Brooks Echols Lanier 

Core urbanized county 

or outlying? 

Core Outlying Outlying Outlying 

SO2 emissions (tpy) 784 209 18 22

PM2.5 emissions (tpy) 1,941 2,959 309 478

NOx emissions (tpy) 6,255 1,596 321 408

NH3 emissions (tpy) 273 867 56 159

VOC emissions (tpy) 6,307 2,260 633 723

Population 109,761 16,189 4,037 10,103

Population (% of 

CBSA) 

78% 12% 3% 7%

VMT 1,324 195 39 80

VMT (% of CBSA) 81% 12% 2% 5%

The EPA also evaluated the meteorology in the area by evaluating wind data collected in the 

Valdosta CBSA as shown in Figure 26. These data indicate frequency of wind direction and 

intensity is variable. 
61

Figure 26. Wind Rose Data for the Valdosta, Georgia CBSA 

Valdosta Georgia CBSA Conclusion 

Based on the wind rose data and the information summarized in Table 14, the EPA is concluding 

that of the four counties in the Valdosta CBSA, Lowndes and Brooks Counties are the most 

likely to potentially contribute to hypothetical violations of the standard at the Lowndes County 

monitor, which that currently has incomplete data. The EPA identified Lowndes County because 

the monitor with incomplete data is located in this county and Lowndes County contributes the 

majority of emissions, VMT, and is the population center of the CBSA. The EPA identified 

Brooks County as a potentially contributing county because it has a countywide total of over 

2,900 tpy of direct PM2.5 emissions from a major point source and other non-point sources, and 

the EPA’s analysis of meteorology indicates possible transport of these emissions from the 

west/southwest toward the PM2.5 monitoring site in Lowndes County. Consequently, because of 

incomplete data at the Lowndes County monitor in the Valdosta CBSA, and the potential for 

contribution to that monitor from Lowndes and Brooks Counties, the EPA is deferring a 

designation for Lowndes and Brooks Counties. Although the meteorological information 

suggests possible transport from Lanier County, the county has low emissions, no major point 

sources, and low VMT relative to Lowndes and Brooks Counties. The same is true of Echols 

County, for which the wind rose data suggest even less likelihood of contribution from this 

easterly county to the affected monitor in Lowndes County. This information leads the EPA to 
62

believe that Echols and Lanier Counties would be less likely to contribute to a potential violation 

at the Lowndes County monitor. Accordingly, the EPA is not deferring a designation for either 

Echols or Lanier Counties and is at this time designating them unclassifiable/attainment based on 

the available data. 

Washington County, GA 

Washington County is a single county that is not a part of a larger CBSA. Due to a snow storm in 

2011, the Washington County monitor has incomplete 2011-2013 data that do not allow 

calculation of a valid 2011-2013 DV.42 Based on incomplete data, the incomplete Washington 

County DV is 8.9 μg/m3

. 

Washington County, Georgia Conclusion 

The EPA is deferring a designation for Washington County because the monitor with incomplete 

data is located in this county. 

As discussed above, the EPA’s limited contribution analyses in this deferral memorandum 

evaluate only those counties in the same CBSA as an affected monitor. Because Washington 

County is not part of a larger CBSA, the EPA is not at this time assessing the likelihood that any 

other areas could potentially contribute to a hypothetical violation at the Washington County 

monitor. 

                                                      

42 Memorandum from Liz P. Naess, Group Leader, Air Quality Analysis Group, US EPA Office of Air Quality 

Planning and Standards, to EPA Docket EPA-HQ-OAR-2012-0918, Air Quality Designations for the 2012 PM2.5

Standards, titled “Data Quality Issues in Georgia Affecting Air Quality Designations for the 2012 PM2.5 National 

Ambient Air Quality Standard.”