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Cincinnati-Hamilton, Ohio–Kentucky Area Designations for the 

2012 Primary Annual PM2.5 National Ambient Air Quality Standard

Technical Support Document

1.0 Summary

In accordance with Section 107(d) of the Clean Air Act (CAA), the EPA must promulgate designations for all 

areas of the country. In particular, the EPA must identify those areas that are violating a National Ambient Air 

Quality Standard (NAAQS) or contributing to a violation of the NAAQS in a nearby area. The EPA must 

complete this process within 2 years of promulgating a new or revised NAAQS, or may do so within 3 years 

under circumstances not relevant to these designations.1 This technical support document (TSD) describes the 

EPA’s decision to designate areas in Ohio and Kentucky as nonattainment for the 2012 primary annual fine 

particle NAAQS (2012 annual PM2.5 NAAQS).2

Consistent with section 107(d), states are required to submit area designation recommendations to the EPA for 

the 2012 annual PM2.5 NAAQS no later than 1 year following promulgation of the standard, or by December 13, 

2013. In December 2013, Ohio recommended that the counties identified in Table 1 be designated as 

nonattainment for the 2012 annual PM2.5 NAAQS based on air quality data from 2010-2012. Kentucky also 

submitted recommendations in December 2013, recommending a designation of attainment for the counties 

listed in Table 1 based on 2010-2012 air quality data. 

After considering these recommendations and based on the EPA’s technical analysis as described in this TSD, 

the EPA is designating the areas listed in Table 1 as nonattainment for the 2012 annual PM2.5 standard. The 

EPA must designate an area nonattainment if it has an air quality monitoring site3that is violating the standard 

or if it has sources of emissions that are contributing to a violation of the NAAQS in a nearby area. Legal 

descriptions (e.g., county boundaries, townships and ranges) of these areas are found below in the supporting 

technical analysis for each area. As provided in CAA section 188(a), the EPA is initially classifying all 

nonattainment areas as “Moderate” areas.

Table 1. States’ Recommended Nonattainment Areas and the EPA’s Final Designated Nonattainment 

Areas for the 2012 annual PM2.5 NAAQS

Area State’s Recommended 

Nonattainment Counties

EPA’s Final Designated 

Nonattainment Counties

 

1 Section 107(d) of the CAA requires the EPA to complete the initial designation process within 2 years of promulgation of 

a new or revised NAAQS, unless the Administrator has insufficient information to make initial designation decisions in the 

2-year time frame. In such circumstances, the EPA may take up to 1 additional year to make initial area designation 

decisions (i.e., no later than 3 years after promulgation of the standard).

2 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.

3

In accordance with 40 CFR 50 Appendix N, PM2.5 measurements from the primary monitor and suitable collocated PM2.5 

FRM, FEM or ARMs may be used in a “combined site data record” to establish a PM2.5 design value to determine whether

the NAAQS is met or not met at a particular PM2.5 monitoring site.
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Cincinnati- Hamilton, OH*

Butler

Clermont

Hamilton

Butler

Clermont

Hamilton

Warren (partial)

Cincinnati-Hamilton, KY None—

recommended attainment

Boone (partial)

Campbell (partial)

Kenton (partial)

*Cincinnati-Hamilton is a multi-state nonattainment area composed of counties and/or partial counties 

in Ohio and Kentucky. The technical analysis for this multi-state area is discussed in a separate and 

stand-alone Technical Support Document for the final Cincinnati-Hamilton Area. There are additional 

TSDs for the rest of the state for both Kentucky and Ohio.

2.0 Nonattainment Area Analyses and Final Boundary Determination

The EPA evaluated and determined the final boundaries for each nonattainment area on a case-by-case basis 

considering the specific facts and circumstances unique to the area. In accordance with the CAA section 107(d), 

the EPA is designating as nonattainment not only the area with the monitoring sites that violate the 2012 annual 

PM2.5 NAAQS, but also those nearby areas with emissions sources that contribute to the violation in the 

nonattainment area. As described in the EPA guidance,

4

after identifying each monitoring site indicating a 

violation of the standard in an area, the EPA analyzed those areas with emissions contributing to that violating 

area by considering those counties in the entire metropolitan area (e.g., Core Based Statistical Area (CBSA) or 

Combined Statistical Area (CSA)) in which the violating monitoring sites are located. The EPA also evaluated

counties adjacent to the CBSA or CSA that have emissions sources with the potential to contribute to the 

violations. The EPA uses the CBSA or CSA as a starting point for the contribution analysis because those areas 

are nearby for purposes of the PM2.5 NAAQS. Based upon relevant facts and circumstances in each area, the 

designated nonattainment area could be larger or smaller than the CBSA or CSA. The EPA’s analytical 

approach is described in section 3 of this technical support document.

3.0 Technical Analysis 

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 Tool5and the EPA PM Designations Guidance and Data 

web page6) and/or data provided to the EPA by states or tribes. This technical analysis identifies the area with

monitoring sites that violate the 2012 annual PM2.5 NAAQS. The EPA evaluated this area and other nearby 

areas with emissions sources or activities that potentially contribute to ambient fine particle concentrations at 

the violating monitors in the area based on the weight of evidence of the five factors recommended in the EPA 

guidance and any other relevant information.

 

4 EPA issued guidance on April 16, 2013, that identified important factors that EPA final to evaluate, in making a 

recommendation for area designations and nonattainment boundaries for the 2012 annual PM2.5 NAAQS. Available at

http://www.epa.gov/pmdesignations/2012standards/docs/april2013guidance.pdf.

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

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

http://www.epa.gov/pmdesignations/2012standards/techinfo.htm.
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These five factors are:

Factor 1: Air Quality Data. The air quality data analysis involves examining available ambient PM2.5 air quality 

monitoring data at, and in the proximity of, the violating monitoring locations. This includes reviewing the 

design values (DV) calculated for each monitoring location in the area based on air quality data for the most 

recent complete 3 consecutive calendar years of quality-assured, certified air quality data in the EPA’s Air 

Quality System (AQS). In general, the EPA identifies violations using data from suitable Federal Reference 

Method (FRM), Federal Equivalent Method (FEM), and/or Approved Regional Method (ARM) monitors sited 

and operated in accordance with 40 CFR Part 58.7 Procedures for using the air quality data to determine whether 

a violation has occurred are given in 40 CFR part 50 Appendix N, as revised by a final action published in the 

Federal Register on January 15, 2013 (78 FR 3086).8In addition to reviewing data from violating monitor sites, 

the EPA also assesses the air quality data from other monitoring locations to help ascertain the potential 

contribution of sources in areas nearby to the violating monitoring site[s]. Examples include using chemical 

speciation data to help characterize contributing emissions sources and the determination of nearby 

contributions through analyses that differentiate local and regional source contributions.

Factor 2: Emissions and emissions-related data. The emissions analysis examines identified sources of direct 

PM2.5, the major components of direct PM2.5, e.g., primary organic carbon (POC) and PM2.5 organic mass 

(POM), elemental carbon (EC), crustal material (and/or individual trace metal compounds)), primary nitrate and 

primary sulfate, and precursor gaseous pollutants (e.g., sulfur dioxide (SO2), nitrogen oxides (NOx), total 

volatile organic compounds (VOC), and ammonia (NH3). Emissions data are generally derived from the most 

recent National Emissions Inventory (NEI) (i.e., 2011 NEI version 1), and are given in tons per year. In some 

cases, the EPA may also evaluate emissions information from states, tribes, or other relevant sources that may 

not be reflected in the NEI. One example of “other information” could include an inventory or assessment of 

local/regional area sources that individually does not meet the current threshold for reporting to the NEI but 

collectively contributes to area PM2.5 concentrations. Emissions data indicate the potential for a source to 

contribute to observed violations, making it useful in assessing boundaries of nonattainment areas. 

Factor 3: Meteorology. Evaluating meteorological data helps to determine the effect on the fate and transport of 

emissions contributing to PM2.5 concentrations and to identify areas potentially contributing to the violations at 

monitoring sites. The Factor 3 analysis includes assessing potential source-receptor relationships in the area 

identified for evaluation using summaries of air trajectories, wind speed, wind direction, and other 

meteorological data, as available.

Factor 4: Geography/topography. The geography/topography analysis includes examining the physical features 

of the land that might define the airshed and, therefore, affect the formation and distribution of PM2.5 over an 

area. Mountains or other physical features may influence the fate and transport of emissions and PM2.5

concentrations. Additional analyses may consider topographical features that cause local stagnation episodes via 

 

7 Suitable monitors include all FEM and/or ARMs except those specific continuous FEMs/ARMs used in the monitoring 

agency's network where the data are not of sufficient quality such that data are not to be compared to the NAAQS in 

accordance with 40 CFR part 58.10(b)(13) and approved by the EPA Regional Administrator per 40 CFR part 58.11(e).

8 As indicated in Appendix N to 40 CFR part 50, Interpretation of the National Ambient Air Quality Standards for PM2.5, 

section 3(a) indicates “Except as otherwise provided in this appendix, all valid FRM/FEM/ARM PM2.5 mass concentration 

data produced by suitable monitors that are required to be submitted to AQS, or otherwise available to EPA, meeting the 

requirements of part 58 of this chapter including appendices A, C, and E shall be used in the DV (design value)

calculations. Generally, EPA will only use such data if they have been certified by the reporting organization (as prescribed

by § 58.15 of this chapter); however, data not certified by the reporting organization can nevertheless be used, if the 

deadline for certification has passed and EPA judges the data to be complete and accurate.”
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inversions, such as valley-type features that effectively “trap” air pollution, leading to periods of elevated PM2.5

concentrations. 

Factor 5: Jurisdictional boundaries. The analysis of jurisdictional boundaries identifies the governmental 

planning and organizational structure of an area that may be relevant for designations purposes. These 

jurisdictional boundaries provide insight into how the governing air agencies conduct or might conduct air 

quality planning and enforcement in a potential nonattainment area. Examples of jurisdictional boundaries 

include counties, air districts, areas of Indian country, CBSA or CSA, metropolitan planning organizations 

(MPOs), and existing nonattainment areas.

3.1 Area Background and Overview Cincinnati-Hamilton 

Figure 1 is a map of the EPA’s final nonattainment boundary for the Cincinnati-Hamilton Area. The map shows 

the location and design values of ambient air quality monitoring locations, county, and existing 1997 annual 

and/or 2006 24-hour PM2.5 NAAQS nonattainment boundaries.

For purposes of the 1997 annual PM2.5 NAAQS, this area was designated nonattainment. The boundary for the 

1997 annual PM2.5 NAAQS nonattainment area included the entire counties of Butler, Clermont, and Hamilton 

(Ohio), and Bonne, Campbell, and Kenton (Kentucky), and parts of Dearborn County, Indiana. For the 2006 

PM2.5 NAAQS, the Cincinnati-Hamilton area was designated attainment. Today’s final boundaries for the 

Cincinnati-Hamilton nonattainment area are similar to the 1997 boundaries, with the exception of the counties 

of Boone, Kenton, Campbell (Kentucky), and Warren (Ohio) having partial boundaries rather than entire 

counties, capturing the contribution of the urban area and for Boone the point sources. The partial county of 

Dearborn (Indiana) is also not included in the final nonattainment area for 2012 due to the closure of the 

Tanners Creek power plant as a result of a permanent and enforceable consent decree, which results in the 

county no longer contributing to the Cincinnati-Hamilton nonattainment area.
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Figure 1. Final Nonattainment Boundary for the Cincinnati-Hamilton Area

EPA must designate as nonattainment areas that violate the NAAQS and nearby areas that contribute to the 

violation in the violating area. Hamilton County shows two violations, and Butler County one violation of the 

2012 PM2.5 NAAQS based on 2011-2013 data; therefore Hamilton and Butler Counties are included in the 

nonattainment area. As shown in Figure 1b, EPA evaluated each county without a violating monitoring site

located near the counties with a violating monitoring site. Based on the five factors and other relevant 

information, the EPA determined that Warren, Clermont, Boone, Campbell, and Kenton contribute to the 

nearby violation. The following sections describe this five factor analysis process. While the factors are 

presented individually, they are not independent. The five factor analysis process carefully considers the

interconnections between the factors and the dependence of each factor on one or more of the others.
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Figure 1b. Area of Analysis for the Cincinnati-Hamilton Final Nonattainment Area

Factor 1: 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 is dependent upon monitor readings 

throughout the year, including days with monitored ambient concentrations 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 the Factor 1 air quality analysis, the EPA assessed and characterized air 

quality at, and in the proximity of, the violating monitoring site locations 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.

9 EPA also identified the 

spatial extent of these high PM2.5 concentrations. The mass and composition at the design value location 

 

9 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 
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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, 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, EPA contrasted the approximated mass composition at the design value 

monitoring site with data collected at IMPROVE10 and other monitoring locations whose data are representative

of regional background. This comparison of local/area-wide chemical composition data to regional chemical 

composition data derives an “urban increment,”

11,12 which helps differentiate the influence of more distant 

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

violation that is associated with nearby emission contributions.13,14,15

PM2.5 Design Values and Total Mass Measurements -The EPA examined ambient PM2.5 air quality monitoring 

data represented by the DVs at the violating monitoring site 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 qualityassured, certified air quality data from suitable FEM/FRM/ARM monitoring sites in the EPA’s Air Quality 

System (AQS). For this designations analysis, the EPA used data for the 2011-2013 period (i.e., the 2013 design 

value), which are the most recent years with fully-certified air quality data. A monitor’s DV is the metric or 

 

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. 

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

in mostly rural and remote areas.

11 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. 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), 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, EPA used alternative analyses to reflect the mix of urban and rural sources 

contributing to the measured concentrations at violating monitoring sites. 

12 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.

13 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.

14 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

15 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
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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 micrograms per 

cubic meter (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 2 identifies the current design value(s) (i.e., the 2013 DV) and the most recent two 

design values based on all monitoring sites in the area of analysis for the Cincinnati-Hamilton final 

nonattainment area.16 Where a county has more than one monitoring location, the county design value is 

indicated in red type.

Table 2. Air Quality Data collected at Regulatory Monitors (all DV levels in μg/m3)

a,b

County, State

Monitor Site 

ID

State Rec 

NA? 09-11 DV 10-12 DV 11-13 DV

Dearborn, IN N/A N No monitor

Decatur, IN N/A N No monitor

Fayette, IN N/A N No monitor

Franklin, IN N/A N No monitor

Ripley, IN N/A N No monitor

Rush, IN N/A N No monitor

Switzerland, 

IN N/A N No monitor

Union, IN N/A N No monitor

Adams, OH N/A N No monitor

Brown, OH N/A N No monitor

Butler, OH 390170003 Y 13.0 12.5 11.7

Butler, OH 390170016 Y 13.0 12.2 11.3

Butler, OH 390170019 Y 12.7

N/A 

(incomplete) 11.7

Butler, OH 390170020 Y 13.6

Clermont, OH N/A N No monitor

Green, OH N 12 11.4 10.2

Hamilton, OH 390610006 Y 12.2 11.6 10.7

Hamilton, OH 390610010 Y 11.8 11.2 11

Hamilton, OH 390610014 Y 13.8 13.4 12.3

Hamilton, OH 390610040 Y 12.8 12.8 11.1

Hamilton, OH 390610042 Y 13.8 13.2 12.2

Hamilton, OH 390617001 Y 13.5 14.1 N/A*

Hamilton, OH 390618001 Y 15.5 17.6 N/A*

 

16 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 C4 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....”
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Highland, OH N/A N No monitor

Montgomery, 

OH 390610042 N 12.9 12.3 11.0

Preble, OH 390617001 N 11.3 10.7 10.0

Warren, OH 391650007 N 11.5 11.5 11.0

Wilmington, 

OH N/A N No monitor

Braden, KY N/A N No monitor

Boon, KY N/A N No monitor

Campbell, KY 210373002 N 11.1 10.6 9.9

Carroll, KY N/A N No monitor

Gallatin, KY N/A N No monitor

Grant, KY N/A N No monitor

Harrison, KY N/A N No monitor

Kenton, KY 211170007 N 11.6 12.1 N/A*

Madison, KY N/A N No monitor

Ohio, KY N/A N No monitor

Owen, KY N/A N No monitor

Pendleton, KY N/A N No monitor

Robertson, KY N/A N No monitor

Scott, KY N/A N No monitor

aWhere a county has more than one monitoring location, the county design value is indicated in red type.

bThese design values do not include data from Class III FEM monitors that the EPA has approved as not 

eligible for comparison to the NAAQS per 40 CFR 58.11(e).

*Monitor was closed in 2010, design values noted for 2009-2011 and 2010-2012 are incomplete and only 

represent 1-2 years of data.

Site # 39-017-0020, known as the Yankee Road site in Butler County, OH, began in the middle of 2011 as a 

special purpose monitor as required by a permit for the nearby steel facility. Because the monitor has continued 

to run past the 2 –year special purpose monitor time-frame (40 CFR part 58 subpart C), this monitor 

automatically becomes comparable to the NAAQS. Given that the monitor had incomplete data, the EPA has 

performed a substitution analysis as defined under 40 CFR part 58 subpart N, resulting in a design value for 

2011-2013 of 13.6 mg/m3. However, the 2015 Annual Ambient Monitoring Plan from the local agency that 

operates the site includes a request that the site be exempted from comparison to the annual standard given that 

the intention of the monitor is to measure concentrations specifically at the facility that is a continued 

requirement of the facilities operating permit. The EPA has not yet evaluated this issue, but is considering the 

very close proximity to the facility as an important factor. The EPA's analysis for the Cincinnati area not only 

took into account this monitor, but also the two other violating monitors in Hamilton County, the Cincinnati 

area and sources in that area that are contributing to 39-017-0020 are also contributing to the violations in 

Hamilton County. Therefore, consideration or non-consideration of this monitor does not change the outcome 

of the final nonattainment area boundaries.

The Figure 1 map, shown previously, identifies the Cincinnati-Hamilton final nonattainment area and 

monitoring locations with 2011-2013 violating DVs. As indicated on the map, there is one violation in Butler 
Page 10 of 36

County located near a steel facility, and there are 2 violating monitoring locations located in the city of 

Cincinnati, both just north of the Ohio River.

Seasonal variation can highlight those conditions most associated with high average concentration levels of 

PM2.5. Figure 2 shows quarterly mean PM2.5 concentrations for the most recent 3-year period for the highest DV 

monitoring sites, and other 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.

Figure 2. Cincinnati-Hamilton PM2.5 Quarterly Means for 2011-2013.

As shown, over the design value period of 2011-2013, quarter 3 (Q3) has consistent peaks for every monitor in 

the nonattainment area, with a high peak in 2011 Q3 and a smaller peak in 2013 Q1 outside that pattern. Note 

the high degree of temporal pattern for the 3-year period and across all Cincinnati-Hamilton area monitors. 

Quarterly values across the period vary by 1-5 μg/m3at each site, with consistent annual peaks occurring in Q3.

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

location, 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 violating monitoring location, the EPA first adjusted 

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

site using the SANDWICH approach to account for the amount of PM2.5 mass constituents retained in the FRM 

0

2

4

6

8

10

12

14

16

18

11 Q1 11 Q2 11 Q3 11 Q4 12 Q1 12 Q2 12 Q3 12 Q4 13 Q1 13 Q2 13 Q3 13 Q4

PM2.5 Concentrations

μg/m3

Cincinnati-Hamilton PM2.5 Quarterly Means 2011-

2013

Campbell Butler Butler Butler Butler Hamilton

Hamilton Hamilton Hamilton Hamilton Warren
Page 11 of 36

measurement.17,18,19,20 In particular, this approach accounts for losses in fine particle nitrate and increases in 

sulfate mass associated with particle bound water. Figure 3a illustrates the fraction of each PM2.5 chemical 

constituent based on annual averages for the years 2010-2012.

Figure 3a. Cincinnati-Hamilton Annual Average PM2.5 Chemical Constituents (2010-2012) 

Figure 3b 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 factor analyses, can provide 

additional insight as to which sources or factors may contribute at a greater level. Simply stated, this analysis 

can help identify nearby sources of emissions that contribute to the violation at the violating monitoring site. 

 

17 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.

18 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.

19 Frank, N. H., The Chemical Composition of PM2.5 to support PM Implementation, 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.

20 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.

5.5

1.3 1.2

4.9

0.5

Annual Average PM2.5 Chemical Constituents 2010-2012 

(μg/m3)

Oragnic Mass

Elemental Carbon

Nitrate

Sulfate

Crustal
Page 12 of 36

Figure 3b. Cincinnati-Hamilton Annual and Quarterly Average PM2.5 Species (2010-2012)a

aAdjusted 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.

Figure 3b shows that sulfate and organic mass are the predominant species overall, with an exception in Q1 

when nitrate comprises an equal fraction to sulfates and organic mass. Crustal and elemental carbon are

relatively small components, but is largest in Q2 and Q3, respectively. Figure 3b suggests that sulfate, organic 

mass, VOCs and nitrate sources have the highest impact on the monitored values for the Cincinnati-Hamilton 

area. 

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 4a includes pie 

charts showing the annual and quarterly chemical mass constituents of the urban increment. The quarterly pie 

charts correspond to the high-concentration quarters identified in Figure 2. Evaluating these high concentration 

quarters can help identify composition of PM2.5 during these times. Note that in these charts, sulfates and 

nitrates have been adjusted to represent their mass in measured PM2.5.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

Annual Q1 Q2 Q3 Q4

μg/m3

Annual and Quarterly Average PM2.5 Species 2010-

2012 Adjusted to FRM Total PM2.5

Sulfates Organic mass Nitrates Elemental Carbon Crustal
Page 13 of 36

Figure 4a. Cincinnati-Hamilton Urban Increment Analysis for 2010-2012.

1.36

0.56

0.44

0.34

0.03

Average Urban Increment 2010-2012 

(μg/m3)

Organic

Carbon

Elemental

Carbon

Nitrates

Sulfates

Crustal

2.01

0.00

1.24

0.08

Q-1 Average Urban Increment 2010-2012 

(μg/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal

1.53

0.06

0.39

0.05

Q-2 Average Urban Increment 2010-2012 

(μg/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal
Page 14 of 36

0.68

0.22

0.71

0.01

Q-3 Average Urban Increment 2010-2012 

(μg/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal

2.75

0.50

0.44

0.180.06

Q-4 Average Urban Increment 2010-2012 

(μg/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal
Page 15 of 36

Figure 4b. Cincinnati-Hamilton Average Urban Increment Analysis for 2010-2012. 

Hamilton County has two monitoring sites and Butler County with one with a DV exceeding the NAAQS. In 

addition, Hamilton and adjoining counties have clear seasonal peaks in ambient PM2.5 concentrations in Q1. 

Butler, Campbell, Hamilton, and Warren Counties during the 2011 Q3 monitored PM2.5 concentrations 

exceeding the NAAQS. 

In reviewing the urban increment analysis for the Cincinnati-Hamilton CBSA DV monitor, carbon species are 

the dominant contribution from the urban area with the sulfate component having small urban contribution –

except in Q3 – although conversely a large regional contribution. Nitrate is second highest urban increment 

component for the Q1 peak, but is quite low in the Q3 peak season, during which carbon components comprise 

a higher percentage. This analysis points to contribution from local direct PM2.5 sources nearby the violating 

monitor (including motor vehicles that have traveled near the monitor), but sulfate and nitrate reflect 

contributing sources across a broader area. 

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

Annual Q1 Q2 Q3 Q4

μg/m3

Average Urban Increment 2010-2012 (μg/m3)

Organic Carbon Elemental Carbon Nitrates Sulfates Crustal
Page 16 of 36

Factor 2: Emissions and emissions-related data

In this designations process, for each area with a violating monitoring site, 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 violating monitoring site or monitoring sites in the area under 

evaluation. Similar to the air quality analysis, these data were examined on a seasonal basis. Seasonal air quality 

patterns are not sufficiently different to warrant analysis on a seasonal basis. (Although nitrate is much higher 

in the cooler months, NOx emissions have similar importance all year due to their role in fostering the 

photochemistry that causes secondary particulate matter.) Furthermore, for all major emitted pollutants, the mix 

of sources is similar in all seasons. Therefore, the EPA only analyzed annual emissions data. 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 (or, in the case of motor vehicles, that have traveled to near the 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 violating monitoring sites. 

Emissions Data

For this factor, the EPA reviewed data from the 2011 National Emissions Inventory (NEI) version 1 (see 

http://www.epa.gov/ttn/chief/net/2011inventory.html). For each county in the area of analysis, the EPA 

examined the magnitude of county-level emissions reported in the NEI. 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.21 Substantial emissions levels from sources in a nearby area indicate the 

potential for the area to contribute to monitored violations.

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 in Factor 1, evaluating the components of direct PM2.5 and 

precursor gases can help identify specific sources or source types contributing to elevated concentrations at 

violating monitoring sites and thus assist in identifying appropriate area boundaries. In general, directly emitted

POC (POC) and VOCs22 contribute to (POM); directly emitted EC contributes to PM2.5 EC; NOX, NH3 and 

directly emitted nitrate contribute to PM2.5 nitrate mass (PNO3); SO2, NH3 and directly emitted sulfate 

contribute to PM2.5 sulfate mass (PSO4); and, directly emitted crustal material and metal oxides contribute to 

PM2.5 crustal matter (PCrustal).

23,24 The EPA believes that the quantities of those nearby emissions as potential 

contributors to the PM2.5 violating monitors 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 

 

21 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.

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

23 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.

24 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.
Page 17 of 36

POC emissions are already PM2.5 whereas SO2 must convert to PM2.5 and not all of the emitted SO2 undergoes 

this conversion. 

Table 3a 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, non-road mobile, on-road mobile, and fires) of 

directly emitted PM2.5 and precursor species for the county with the violating monitoring site and nearby 

counties considered for inclusion in the Cincinnati-Hamilton area. Table 3b summarizes the directly emitted 

components of PM2.5 for the same counties in the area of analysis for the Cincinnati-Hamilton area. This 

information will be considered in conjunction with the Urban Increment composition information previously 

shown in Figures 4a and 4b.

Table 3a. County-Level Emissions of Directly Emitted PM2.5 and Precursors (tons/year)

County, State Total 

NH3

Total 

NOx

Total 

VOC

Total 

SO2

Total 

Direct PM Total

Clermont , OH 240 21,423 4,820 109,009 8,507 143,999

Hamilton, OH 895 35,541 20,268 31,498 5,657 93,860

Dearborn, IN 175 8,074 3,106 26,895 705 38,955

Montgomery, OH 852 19,158 13,779 2,543 2,091 38,423

Adams, OH 663 13,140 1,669 16,216 3,803 35,491

Butler, OH 762 13,972 9,012 5,792 2,476 32,014

Boone, KY 224 8,394 5,231 2,181 757 16,789

Ohio, KY 1,251 2,335 1,656 9,761 584 15,587

Greene, OH 801 6,996 3,976 1,207 963 13,943

Warren, OH 350 6,950 5,168 116 841 13,425

Kenton, KY 180 5,106 3,843 53 483 9,665

Decatur, IN 2,918 2,387 2,060 19 577 7,960

Scott, KY 352 2,492 3,862 19 386 7,110

Preble, OH 1,144 2,230 2,051 49 719 6,193

Campbell, KY 132 2,628 2,143 33 306 5,242

Rush, IN 1,527 1,464 1,223 12 582 4,809

Highland, OH 640 1,544 1,774 46 597 4,601

Ripley, IN 668 1,314 1,932 26 580 4,520

Brown, OH 569 1,560 1,621 50 563 4,364

Pendleton, KY 135 1,572 621 869 327 3,524

Gallatin, KY 135 1,784 664 85 330 2,998

Franklin, IN 492 878 998 18 394 2,780

Harrison, KY 471 599 924 13 158 2,165

Fayette, IN 452 617 753 11 288 2,121

Caldwell, KY 483 552 710 14 235 1,994

Union, IN 413 365 511 10 244 1,542

Switzerland, IN 169 342 446 7 155 1,118

Owen, KY 268 321 411 9 105 1,114

Bracken, KY 107 552 319 7 75 1,059
Page 18 of 36

Table 3b. County-Level Emissions for Components of Directly Emitted PM2.5 (tons/year) 25

County, State PNO3 PSO4 EC POM PCrustal Residual

Total 

Direct

Clermont , OH 4.9 627.4 434.6 663.5 3060.0 3716.5 8506.8

Hamilton, OH 7.5 289.8 771.9 1463.3 1381.4 1743.4 5657.3

Adams, OH 3.0 261.3 169.7 514.9 1289.6 1564.4 3802.8

Butler, OH 8.2 224.1 386.0 787.4 476.5 593.8 2476.1

Montgomery, OH 3.2 44.8 479.0 869.4 340.1 354.0 2090.5

Greene, OH 2.7 18.9 161.4 281.6 268.8 229.7 963.0

Warren, OH 1.2 20.3 184.0 317.2 163.7 154.6 841.0

Boone, KY 2.2 14.3 167.2 294.8 115.0 163.2 756.7

Preble, OH 1.3 5.0 76.6 293.2 194.2 148.5 718.7

Dearborn, IN 2.5 46.1 83.1 309.0 98.9 165.5 705.1

Highland, OH 1.0 4.5 66.9 297.3 120.2 106.6 596.6

Ohio, KY 2.5 15.1 63.0 273.0 92.2 138.4 584.2

Rush, IN 0.6 8.2 33.1 99.6 252.4 188.6 582.5

Ripley, IN 0.9 4.5 56.1 273.2 126.7 118.7 580.1

Decatur, IN 0.7 8.2 49.1 144.2 210.9 163.4 576.5

Brown, OH 1.0 4.3 65.2 275.1 114.8 102.5 563.0

Kenton, KY 0.8 5.0 124.8 248.1 43.2 61.2 483.2

Franklin, IN 0.6 2.6 33.7 158.7 105.5 93.3 394.3

Scott, KY 1.0 10.2 66.8 157.2 44.6 106.5 386.4

Gallatin, KY 0.9 20.9 29.8 70.5 96.0 112.2 330.4

Pendleton, KY 0.9 12.8 27.6 80.4 85.0 120.7 327.5

Campbell, KY 1.0 10.0 64.5 144.6 34.6 51.7 306.4

Fayette, IN 0.3 1.5 22.1 81.6 106.6 75.8 287.9

Union, IN 0.2 1.0 15.9 60.0 98.7 67.9 243.7

Caldwell, KY 1.2 2.0 28.5 121.6 42.1 39.8 235.3

Harrison, KY 0.6 2.1 24.1 77.5 22.7 31.0 158.0

Switzerland, IN 0.3 1.2 15.7 81.6 25.2 30.7 154.6

Owen, KY 0.4 0.9 15.1 61.5 11.3 15.7 104.8

Bracken, KY 0.1 0.7 17.2 30.5 12.2 14.0 74.8

Table 3b breaks down the direct PM2.5 emissions value from Table 3a 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 3a and 3b, the EPA identified the following components warranting 

additional review: The constituents of interest are POM, direct PM, and NOx. 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 

 

25 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).
Page 19 of 36

in Tables 4a-d. Tables 4a and b indicate that Boone, Campbell, Kenton, and Warren Counties are smaller 

relative contributors, which was one factor that was considered when proposing the partial county areas for 

these counties. However, Table 4c shows that all counties in the nonattainment area are contributing to the high 

organic carbon mass concentrations shown to dominate the urban increment (Figure 4a and b). This indicates 

that the urbanized portions of Kenton and Campbell Counties are contributing to the concentrations at the 

violating monitors in the Cincinnati-Hamilton nonattainment area. 

Table 4a. County-Level NOx Emissions (tons/year) for the Final Nonattainment Area

County, State

Total 

NOx

Clermont, OH 21,423 23%

Hamilton, OH 35,541 38%

Butler , OH 13,972 15%

Boone , KY 8,394 9%

Warren, OH 6,950 7%

Kenton , KY 5,106 5%

Campbell , KY 2,628 3%

Total 94,014 100%

Table 4b. County-Level PM Emissions (tons/year) for the Final Nonattainment Area

County, State

Total 

Direct 

PM

Percent 

of Total 

Area

Clermont , OH 8,507 45%

Hamilton, OH 5,657 30%

Butler, OH 2,476 13%

Boone, KY 757 4%

Warren, OH 841 4%

Kenton, KY 483 3%

Campbell, KY 306 2%

Total 19027.5 100%

Table 4c. County-Level POM Emissions (tons/year) for the Final Nonattainment Area

County, State POM

Percent 

of Total 

Area

Clermont , OH 663.5 17%

Hamilton, OH 1463.3 37%

Butler, OH 787.4 20%

Warren, OH 317.2 8%

Boone, KY 294.8 8%

Kenton, KY 248.1 6%

Campbell, KY 144.6 4%

Total 3919.0 100%
Page 20 of 36

Table 4d. County-Level EC Emissions (tons/year) for the Final Nonattainment Area

County, State EC Percent of 

Total Area

Clermont , OH 434.6 20%

Hamilton, OH 771.9 36%

 Butler, OH 386.0 18%

 Warren, OH 184.0 9%

 Boone, KY 167.2 8%

 Kenton, KY 124.8 6%

Campbell, KY 64.5 3%

Total 2132.9 100%

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 final nonattainment area. The magnitude and 

location of these sources can help inform nonattainment boundaries. Table 5 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 area of analysis for the Cincinnati-Hamilton area. Table 5 also shows the distance from 

the facility to the DV monitor for the respective county.

Table 5. NEI 2011 v1 Point Source Emissions (tons/year) 

NEI 2011 v1 Emissions - Tons/Year

County, 

State Facility Name (Facility ID)

Distance

monitor 

(miles)

NH3 NOx PM2.5 SO2 VOC Total

Adams, OH

DP&L, J.M. Stuart 

Generating Station 

(0701000007)

57 2 7,764 1,935 8,441 189 18,331

Adams, OH DP&L, Killen Generating 

Station (0701000060)

64 1 3,616 606 7,721 52 11,996

Adams, OH

General Electric Aircraft 

Engines: Peebles Facility 

(0701000001)

65 760 6 5 24 795

Boone, KY Duke Energy KY East Bend 28 28 2,667 99 2,000 61 4,855

Boone, KY Cincinnati/Northern Ken 15 740 27 90 151 1,009

Butler, OH AK Steel Corporation 

(1409010006) 20 16 2,276 855 2,046 675 5,868

Butler, OH MillerCoors LLC 

(1409000353) 18 0 380 41 880 173 1,474

Butler, OH Wausau Paper Towel & 

Tissue, LLC (1409010043)

23 0 426 24 540 43 1,033

Butler, OH Smart Papers - Hamilton Mill 

(1409040212) 16 24 140 13 724 16 917
Page 21 of 36

Butler, OH

City of Hamilton Department 

of Public Utilities 

(1409040243)

15 0 214 6 577 2 798

Butler, OH SunCoke Energy Middletown 

Operations (1409011031)

20 60 23 476 6 564

Carroll, KY KY Utilities Co - Ghent 

Station 43 81 7,831 2,346 10,982 177 21,417

Carroll, KY North American Stainless 45 529 96 2 55 683

Clermont, 

OH

Duke Energy Ohio, W.C. 

Beckjord Station 

(1413100008)

17 1 7,538 5,297 90,840 47 103,724

Clermont, 

OH

Duke Energy Ohio, Wm. H. 

Zimmer Station 

(1413090154)

26 5 8,460 767 18,042 55 27,328

Dearborn, IN AMERICAN ELECTRIC 

POWER-TANNERS CREEK

22 1 5,367 67 27,331 97 32,863

Dearborn, IN Lawrenceburg Distillers 

Indiana, LLC

21 0 536 6 785 961 2,288

Dearborn, IN ANCHOR GLASS -

LAWRENCEBURG

20 296 62 162 10 529

Dearborn, IN

AURORA CASKET CO INC

28 3 2 0 496 501

Greene, OH

CEMEX Construction 

Materials Atlantic, LLC 

(0829700165)

49 24 1,175 34 213 1,446

Greene, OH Wright-Patterson Air Force 

Base (0829700441)

49 0 336 99 918 6 1,359

Hamilton, 

OH

Duke Energy Ohio, Miami 

Fort Station (1431350093)

18 2 6,490 2,106 26,911 96 35,605

Hamilton, 

OH

DEGS of St. Bernard, LLC 

(1431394148)

2 0 737 114 2,033 4 2,889

Hamilton, 

OH

Emery Oleochemicals LLC 

(1431074278)

2 4 647 25 888 26 1,589

Hamilton, 

OH

INEOS ABS (USA) 

Corporation (1431010054)

13 0 190 15 387 24 616

Madison, KY AGC Flat Glass N America 

Inc

104 634 14 138 33 819

Montgomery, 

OH

Cargill, Inc. - Dayton 

(0857041124)

46 1 468 55 747 357 1,629

Montgomery, 

OH

Appleton Papers Inc. 

(0857190001)

35 1 538 58 938 24 1,559
Page 22 of 36

Montgomery, 

OH

DP&L, O.H. Hutchings 

Generating Station 

(0857780013)

30 1 220 27 649 1 897

Ohio, KY Big Rivers Electric Corp -

Wilson Station 186 263 1,117 76 9,720 54 11,230

Pendleton, 

KY Carmeuse Lime Inc

28 821 89 699 1,609

Scott, KY Toyota Motor Manufacturing 

Usa Inc 65 62 72 0 1,351 1,486

Figure 5 shows the major point source emissions (from the 2011 NEI in tons per year) in the area of analysis for 

the Cincinnati-Hamilton Area and the relative distances of these sources from the violating monitoring 

locations, as depicted by red dots. The actual distance from the point sources to the DV monitoring location is 

presented in Table 5. The distance from the violating monitoring location 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.26

As indicated in Figure 5, there are 32 major point sources located within the area of analysis, and 14 of those 

source are in the final nonattainment area. Four coal-fired power plants are found in the nonattainment area, 

two in Clermont County, OH, one in Boone County, KY, and one in Hamilton County, OH. A fifth power plant 

(American Electric Power Tanners Creek) is located in Dearborn County, IN, but due to its retirement, as 

outlined in a 2013 Federal consent decree, emissions at that point source will go to zero. Major Hamilton 

County sources include: Duke Energy which has relatively high NOx, SO2, and direct PM located 18 miles from 

the DV monitor, and DEGs of St. Bernard and Emery Oleochemicals, both higher NOx and SO2 and both 2 

miles away from the DV monitor. These very local sources of SO2 are potentially impacting the higher SO2 

speciation data in some quarters, as noted above (Figure 3a and 3b). Butler County has major sources including

AK Steel with high direct PM2.5 emissions located 20 miles from the Hamilton county design value monitor, 

Miller Coors with SO2 emissions 18 miles from the monitor, and Wausau Paper Towel & Tissue, LLC with 

moderate SO2 emissions 23 miles from the monitor. Clermont County major sources are two Duke power 

plants emitting high levels of NOx, SO2, and direct PM, located 17 and 26 miles away from the monitor. 

Although the wind roses in Figure 8 do not show substantial winds from this direction the kernel density (Figure 

9) of trajectories suggest contribution to the violation, plus the magnitude of the sources likely impact the 

monitors located in Hamilton County. Finally, Boone County has two major sources, Duke Energy with high 

NOx, SO2 and direct PM, 28 miles from the monitor, and Cincinnati/Northern with high NOx and PM2.5

emissions, 15 miles from the DV monitor. Wind roses from the South/South West (Figure 8) would indicate 

that the Boone County sources are impacting the monitors in Hamilton County. Prior PM2.5 designations have 

added the partial Dearborn County, Indiana, because of the American Electric Power, Tanners Creek facility. 

However, the EPA is excluding this partial county from the 2012 nonattainment area due to the retirement of 

the facility which is considered permanent and enforceable since it is required in a Federal consent decree. 

Emissions from this facility will be at zero when the facility shuts down in 2015. 

Figure 5. Major Point Source Emissions in the Area of Analysis for the Cincinnati-Hamilton Area.

 

26 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.
Page 23 of 36

In summary, the EPA’s analysis of relevant county-level emissions and the geographic locations of the relevant 

pollutants showed that Clermont, Hamilton, Butler, and Boone Counties had the highest overall county 

emissions, with most of the emissions from Clermont, Butler, Hamilton, and Boone Counties being linked to 

point source emissions from either power plants or steel industry located within the counties. County-wide 

emissions from Warren, Kenton, and Campbell also ranked high in total emissions relative to the rest of the area 

of analysis; however, the emissions from these three counties are primarily from area and mobile sources, with 

Campbell and Kenton Counties contributing 4% and 6%, respectively, of the total area POM, and 3% and 6% of 

EC, which constituted a large portion of the urban increments (Figures 4a and 4b). Although the area of 

analysis looked at county emissions for counties including and surrounding the violating monitor, counties not 

listed above either had low overall emissions, or were counties that were downwind of the area, such as Adams 

and Montgomery Counties in Ohio. 
Page 24 of 36

Population density and degree of urbanization

In this part of the factor analysis, 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. 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 include the county associated with area source and mobile source 

emissions as part of the nonattainment area. Table 6 shows the 2000 and 2010 population, population growth 

since 2000, and population density for each county in the area.

Table 6. Population Growth and Population Density.

County, 

State

Population 

2000

Population 

2010

% Change 

from 2000

Land 

Area 

(Sq. 

Miles)

Populatio

n Density 

(per Sq. 

Mile) %

Cumulativ

e

%

Hamilton, 

OH

 

845,303 802,034 -5.1%

 

407 

 

1,969 25% 25%

Montgomery

, OH

 

559,062 535,905 -4.1%

 

462 

 

1,161 17% 42%

Butler, OH

 

332,807 368,814 10.8%

 

467 

 

789 12% 54%

Warren, OH

 

158,383 213,269 34.7%

 

400 

 

534 7% 60%

Clermont, 

OH

 

177,977 197,759 11.1%

 

452 

 

438 6% 67%

Greene, OH

 

147,886 161,625 9.3%

 

415 

 

390 5% 72%

Kenton, KY

 

151,464 159,880 5.6%

 

162 

 

987 5% 77%

Boone, KY

 

85,991 119,306 38.7%

 

246 

 

484 4% 80%

Campbell, 

KY

 

88,616 90,522 2.2%

 

152 

 

597 3% 83%

Madison, 

KY

 

70,872 83,143 17.3%

 

441 

 

189 3% 86%

Scott, KY

 

33,061 47,437 43.5%

 

285 

 

167 1% 87%

Brown, OH

 

42,285 44,867 6.1%

 

492 

 

91 1% 89%

Highland, 

OH

 

40,875 43,584 6.6%

 

553 

 

79 1% 90%

Preble, OH

 

42,337 42,181 -0.4%

 

425 

 

99 1% 91%

Ripley, IN

 

26,523 28,825 8.7%

 

446 

 

65 1% 92%

Adams, OH

 

27,330 28,584 4.6%

 

584 

 

49 1% 93%

Decatur, IN

 

24,555 25,774 5.0%

 

373 

 

69 1% 94%
Page 25 of 36

Grant, KY

 

22,384 24,675 10.2%

 

260 

 

95 1% 95%

Fayette, IN

 

25,588 24,284 -5.1%

 

215 

 

113 1% 96%

Ohio, KY

 

22,916 23,851 4.1%

 

594 

 

40 1% 96%

Franklin, IN

 

22,151 23,066 4.1%

 

386 

 

60 1% 97%

Harrison, 

KY

 

17,983 18,818 4.6%

 

310 

 

61 1% 98%

Pendleton, 

KY

 

14,390 14,907 3.6%

 

281 

 

53 0% 98%

Owen, KY

 

10,547 10,830 2.7%

 

352 

 

31 0% 98%

Carroll, KY

 

10,155 10,798 6.3%

 

130 

 

83 0% 99%

Switzerland, 

IN

 

9,065 10,624 17.2%

 

221 

 

48 0% 99%

Gallatin, KY

 

7,870 8,587 9.1%

 

99 

 

87 0% 99%

Bracken, KY

 

8,279 8,489 2.5%

 

203 

 

42 0% 100%

Union, IN

 

7,349 7,516 2.3%

 

162 

 

47 0% 100%

Robertson, 

KY

 

2,266 2,265 0.0%

 

100 

 

23 0% 100%

Total

 

3,036,270 

 

3,182,219 

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

Population density comparison for the final nonattainment area counties shows that Hamilton is the densest, 

followed by Kenton, Butler, Campbell, and Warren as moderately dense, and Boone and Clermont as low 

relative population density (Figure 6a and Table 6). Population in the moderate and low densely populated 

counties is centered around the Cincinnati-metropolitan area, and was one factor that was taken into account in 

creating boundaries for the final partial counties of Kenton, Butler, Campbell (KY) and Warren (OH) (Figure 

6b). Although Clermont has the lowest relative density and has only a small portion of the county associated 

with the urbanized area, Clermont’s contribution to the nonattainment area is associated with the two Duke 

power plants located in the county (Figure 5). High growth rate is seen in Boone and Warren Counties, but 

growth and sources are still captured in the final partial counties. 
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Figure 6a. 2010 County-Level Population in the Area of Analysis for the Cincinnati-Hamilton Area.
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Figure 6b. Topographic map showing urbanized area for the Cincinnati-Hamilton Area.

Traffic and Vehicle Miles Travelled

High vehicle miles travelled (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 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 violations in the area. Comparatively high VMT in a county outside of the CBSA or CSA signifies

integration with the core urban area contained within the CSA or CBSA, and indicates that a county with the 

high VMT may be appropriate to include in the nonattainment area because emissions from mobile sources in 

that county contribute to violations in the area. Table 7 shows 2011 VMT while Figure 7 overlays 2011 countylevel VMT with a map of the transportation arteries. The VMT used in this analysis was obtained from the

Federal Highway Administration.

Table 7. 2011 VMT for the Cincinnati-Hamilton Area.
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County, State Total 2011 

VMT

Percent Cumulative 

%

Hamilton, OH

 

9,004,357,566 25% 25%

Montgomery, OH

 

6,178,222,941 17% 41%

Butler, OH

 

3,099,030,997 8% 50%

Warren, OH

 

2,139,774,797 6% 56%

Greene, OH

 

2,108,654,417 6% 62%

Clermont, OH

 

1,951,343,156 5% 67%

Kenton, KY

 

1,720,886,038 5% 72%

Boone, KY

 

1,558,794,112 4% 76%

Madison, KY

 

1,017,391,787 3% 79%

Campbell, KY

 

1,010,009,434 3% 81%

Dearborn, IN

 

690,348,611 2% 83%

Scott, KY

 

661,626,556 2% 85%

Preble, OH

 

562,558,622 2% 87%

Grant, KY

 

529,145,674 1% 88%

Brown, OH

 

468,171,663 1% 89%

Ripley, IN

 

447,014,794 1% 91%

Highland, OH

 

439,103,611 1% 92%

Decatur, IN

 

410,435,547 1% 93%

Adams, OH

 

323,514,179 1% 94%

Franklin, IN

 

311,990,458 1% 95%

Ohio, KY

 

311,628,830 1% 95%

Gallatin, KY

 

245,765,593 1% 96%

Carroll, KY

 

201,464,322 1% 97%

Fayette, IN

 

199,216,106 1% 97%
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Rush, IN

 

196,891,227 1% 98%

Pendleton, KY

 

184,074,537 1% 98%

Harrison, KY

 

172,653,729 0% 99%

Owen, KY

 

130,203,987 0% 99%

Switzerland, IN

 

124,623,272 0% 99%

Union, IN

 

105,444,221 0% 100%

Bracken, KY

 

104,160,119 0% 100%

Robertson, KY

 

17,539,124 0% 100%

Total

 

36,626,040,026

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

Figure 7. Overlay of 2011 County-level VMT with Transportation Arteries.
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Hamilton County consistently rank highest in direct PM2.5/key precursor emissions (VMT and population), 

followed by Butler, Warren, Kenton, Boone, and Campbell counties. All counties in the final nonattainment 

area have greater than 1,000, 000 VMT and contain urbanized areas of high population density (Figure 6a and 

6b). In Kenton, Boone, Campbell, and Warren counties – the population and associated VMT are found around 

the metro-Cincinnati area, and warrant including only the parts of these counties that are relatively urbanized, 

that have higher VMT and more population, and that are thus emitting direct PM emissions and thereby 

contributing to the observed violations. (See figure 6b). 

Factor 3: 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. 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.27 When developing these wind roses, EPA also used 

wind observations collected at meteorological sampling stations collocated at air quality monitoring sites, where 

these data were available. Figure 8 shows wind roses that EPA generated from data relevant in the CincinnatiHamilton area.

 

27 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
Page 31 of 36

Figure 8. Wind Roses in the Area of Analysis for the Cincinnati-Hamilton Area

.

As shown in Figure 8, there is a slightly varying pattern across the CBSA of predominantly south to 

southwesterly winds, mostly at mid-level speeds of 4 to 8 meters per second, south of the Ohio River in 

Northern Kentucky and southwesterly to westerly winds, mostly at mid-level speeds of 4-8 meters per second, 

in the northern part of the Ohio portion of the area. The middle region of the area in Butler County has 

predominantly westerly winds mostly at mid-level speeds of 4 to 8 meters per second. This generally suggests

that potential emission sources in the south-through-west upwind direction most warrant analysis. Emission 

sources in Clermont County, discussed above, although not from the predominate wind direction, are extremely 

high in relative magnitude and as shown in the high SO2 component of the speciation and urban increment, as 

well as the trajectory discussion below, are contributing to the Hamilton County violations. Montgomery and 

Green Counties are shown to be downwind of the violating monitors, and in fact are upwind of the attaining 

Montgomery monitor, leading to the conclusion that these two counties are not contributing to the Hamilton 

County violating monitors. 
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Figure 9. HYSPLIT Kernel Density Estimation Plots for the Cincinnati-Hamilton Area
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In summary, for the violating Hamilton County monitors, the HYPSPLIT KDE plots and wind roses suggest 

greatest potential contribution of emissions from Boone, Kenton, Campbell (KY) and Hamilton, Butler, 

Franklin and Clermont (OH) Counties. The HYSPLIT KDE plots indicate low density values in part of Warren 

County the EPA is not including in the nonattainment area, and shows medium or low density in the excluded 

partial counties for Boone, Kenton, and Campbell Counties.

Factor 4: 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.

While the Cincinnati-Middletown-Wilmington, Ohio-Kentucky-Indiana CSA does not appear to have major 

geographical or topographical barriers meaningfully limiting air pollution transport within its air shed, the EPA 

notes that geographically, the northern portions of Kenton and Campbell Counties in Kentucky area are in very 

close proximity (just across Ohio River) from the core of the downtown Cincinnati area.

Factor 5: Jurisdictional boundaries

In defining the boundaries of the final Cincinnati-Hamilton nonattainment area, the EPA considered existing 

jurisdictional boundaries, which can provide easily identifiable and recognized boundaries for purposes of 

implementing the NAAQS. Existing jurisdictional boundaries often signify the state governmental organization 

with the necessary legal authority for carrying out air quality planning and enforcement functions for the final 

area. Examples of such jurisdictional boundaries include existing/prior nonattainment area boundaries for 

particulate matter, county lines, air district boundaries, township boundaries, areas covered by a metropolitan 

planning organization, state lines, and Reservation boundaries, if applicable. Where existing jurisdictional 

boundaries were not adequate or appropriate to describe the nonattainment area, the EPA considered other 

clearly defined and permanent landmarks or geographic coordinates for purposes of identifying the boundaries 

of the final designated areas.

The Cincinnati-Hamilton area has previously established nonattainment boundaries associated with the 1997 

annual PM2.5 NAAQS. The states have recommended different boundaries for the 2012 annual PM2.5 NAAQS. 

Prior PM designations have added the partial Dearborn County, Indiana, because of the American Electric 

Power, Tanners Creek facility. However, the EPA is excluding this partial county from the 2012 nonattainment 

area due to the retirement of the facility which is considered permanent and enforceable since it is required in a 

Federal consent decree. The remainder of the county is relatively rural with a low population and VMT 

compared to the counties included in the nonattainment area. 

For the final partial counties in the Ohio portion of the Cincinnati-Hamilton nonattainment area, i.e. in Warren 

County, the EPA has used townships to define the area included and excluded, with the areas included 

encompassing the urbanized area and the contributing point sources of the counties. Kentucky does not have 

defined townships, and so final partial county boundaries in Boone, Campbell, and Kenton County were defined 

on the basis of census tracts. The boundaries of the final nonattainment area within Kentucky are identical to 

the boundaries of the area designated as nonattainment for the 2008 ozone NAAQS, because the same sources 

are impacting the PM concentrations. 

Conclusion for the Cincinnati-Hamilton Area

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

designating the following counties as part of the Cincinnati-Hamilton Ohio-Kentucky nonattainment area 

because they are either violating the 2012 annual PM2.5 NAAQS or contributing to a violation in a nearby area: 

Hamilton, Butler, Clermont, and partial Warren Counties in Ohio, and partial Boone, Kenton, and Campbell 

Counties in Kentucky. These are not the same counties that are included in the Cincinnati-Hamilton 

nonattainment area for the 1997 annual PM2.5 NAAQS. The air quality monitoring sites in Butler and Hamilton 
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Counties indicate violations of the 2012 annual PM2.5 NAAQS based on the 2011-2013 DVs; therefore these 

counties are included in the nonattainment area. The rest of the counties are nearby counties that do not have 

violating monitoring sites, but the EPA has concluded that these areas contribute to the particulate matter 

concentrations in violation of the 2012 annual PM2.5 NAAQS through emissions from point sources, non-point 

sources (e.g., area sources), and from mobile source emissions. 

Ohio

Based on the assessment of factors described above for Ohio, the EPA has concluded that Hamilton, Butler, and 

Clermont Counties, and portions of Warren County be included as part of the Cincinnati-Hamilton OhioKentucky nonattainment area. Hamilton and Butler Counties contribute 30% and 13% of total direct PM for the 

areas total PM emissions. Hamilton and Butler Counties also contain point sources that are contributing to PM 

precursors, as well as having high population and VMT that are contributing to the monitored PM violations. 

Most of these emissions are coming from area sources and the urbanized area in these two counties. Clermont 

County contains two major power plants that are contributing 73% of total SO2, which has a high impact on the 

urban increment in Q3, 10% of the total area VOCs, 23% of the areas NOx, and 43% of direct PM for the area. 

SO2, NOx, direct PM, and VOCs are primarily associated with the power plants – with some of the VOC, NOx, 

and direct PM being associated with the urbanized area and VMT in Clermont County that are associated with 

the Cincinnati-metro area. Clermont point sources are found downwind of the violating monitors and are 

contributors to the violations currently monitored. Warren County remains as a partial county as it has no point 

source emissions; with the main contributor to the nonattainment being mobile sources contributing to the direct 

PM emissions, and reflected in the urban increment. Warren County has similar overall emissions of NOx and 

direct PM as Campbell and Kenton – contributing 10% of the areas total direct PM, where mobile and area 

sources dominate the sources contributing. The EPA has finalized the partial counties based on the urbanized 

areas that are correlated with the total VMT, and PM emissions. Taken in isolation, wind roses and KDEs 

militate against including Warren County in the Cincinnati-Hamilton nonattainment area. However, those 

meteorological factors are overwhelmed by the localized impact of direct PM associated with VMT in parts of 

Warren County, and additional VMT data indicating strong commuting patterns from parts of Warren County 

into the Cincinnati area. The EPA, therefore, is designating Hamilton, Boone, and Clermont Counties, and 

partial Warren County (all townships except Harlan, Massie, Salem, Washington, and Wayne townships).

Kentucky

Based on the assessment of factors described above for Kentucky, the EPA has concluded that portions of 

Boone, Campbell, and Kenton Counties must be included as part of the Cincinnati-Hamilton, Ohio-Kentucky

nonattainment area because they are contributing to a violation in a nearby area. The total of mobile source and 

area source emissions from these counties comprise approximately 40% of the total mobile source and area 

source NOx emissions in the Cincinnati-Hamilton, Ohio-Kentucky area. The total of mobile source and area 

source emissions from these counties comprise approximately 75% of the total mobile source and area source 

VOC emissions in the Cincinnati-Hamilton, Ohio-Kentucky area. Point sources in these counties comprise 

approximately 50% of the total NOx emissions and 10% of the total VOC emissions with Boone County 

containing two smaller power plants, and 4% of the total PM emissions in the Cincinnati-Hamilton, OhioKentucky area. As indicated in the factors above, Boone, Campbell, and Kenton Counties have sources of 

direct PM, NOx and VOC emissions; rank among the highest VMT contributors for the Cincinnati-Hamilton, 

Ohio-Kentucky nonattainment area; have high population densities and high population growth in Boone 

County. The northern portions of these counties urbanized and associated with the Cincinnati-Hamilton area, as 

well as being directly upwind of the violating monitors and having strong association with the trajectories

shown in the kernel density. As such, the EPA is designating portions of Boone, Campbell, and Kenton 

Counties as part of the Cincinnati-Hamilton, Ohio-Kentucky nonattainment area. The partial county boundary 

for Boone, Campbell, and Kenton Counties includes all of the census tracts in these counties except the census 
Page 36 of 36

tracts 706.01 and 706.04 in Boone County, 637.01 and 637.02 in Kenton County, and 520.01 and 520.02 in 

Campbell County.