Page 1 of 36 Cincinnati

- Hamilton, Ohio

– Kentucky Area Designations for the

2012 Primary Annual PM 2.5 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 violati on 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 PM 2.5 NAAQS). 2

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

the 2012 annual PM 2.5 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 PM 2.5 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 te chnical analysis as described in this TSD,

the EPA is designating the areas listed in Table 1 as no n attain ment for the 2012 annual PM 2.5 standard. The EPA must designate an area nonattainment if it has an air quality monitor ing site 3 that 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

techni cal analysis for each area. As provided in CAA section 188(a), the EPA is initially classify ing all

nonattainment areas as “Moderate” areas.

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

Areas for the 2012 annual PM 2.5 NAAQS

Area State’s Recommended

Nonattainment Counties EPA’s Final Designated

Nonattainment Counties

1 Section 107(d) of th e 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 des ignation

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 PM 2.5 NAAQS (78 FR 3086, January 15, 2013).
In that action, the EPA revised the primary annual PM 2.5 standard, strengthening it from 15.0 micrograms per cubic meter
(μg/m 3 ) to 12.0 μg/m 3

.
3 In accordance with 40 CFR 50 Appendix N, PM 2.5 measurements from the primary monitor and suitable collocated PM 2.5 FRM, FEM or ARMs may be used in a “combined site da ta record” to establish a PM 2.5 design value to determine whether
the NAAQS is met or not met at a particular PM 2.5 monitoring site.Page 2 of 36

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 evaluate d 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 designat ing as nonattainment not only the a rea with the monitoring site s that violate t he 2012 annual

PM 2.5 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 monitor ing site indicat ing a violation of the standard in an area, the EPA analyzed those areas with emissions contribut ing to that violating area by considering those counties in the entire metropolitan area (e.g., Core Based Statistical Area (CBSA) or

Combined Statisti cal Area (CSA)) in which the violating monitor ing site s are located. The EPA also evaluate d

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

violation s. The EPA uses the CBSA or CSA as a starting point for the contribution analysis because those areas are nearby for purposes of the PM 2.5 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 analy tical approach is described in section 3 of this technical support document.

3.0 Technical Analysis

In this technical analysis, the EPA us ed the latest data and information available to the EPA (and to the states and tribes through the PM 2.5 Designations Mapping Tool 5 and the EPA PM Designations Guidance and Data web page 6 ) and/or data provided to the EPA by states or tribes. This technical analysis identifies the area with

monitor ing site s that violate the 2012 annual PM 2.5 NAAQS

. The EPA e valuated this area and other nearby

areas with emissions sources or activities that potentially contribute to ambient fine particle concentrations at the violating monitor s 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

recommen dation for area designations and nonattainment boundaries for the 2012 annual PM 2.5 NAAQS. Available at
http://www.epa.gov/pmdesignations/2012standards/docs/april2013guidance.pdf.

5 EPA’s PM 2.5 Designations Mapping Too l 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

.Page 3 of 36

These five factors are:

Factor 1: Air Quality Data

. The air quality data analysis involve s examining available ambient PM 2.5 air quality monitoring data at, and in the proximity of, the violating monitoring locations. This include s reviewing the design value s (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 Ai r 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 ha s occurred are given in 40 CFR p art 50 Appendix N, as revised by a final action published in the Federal Register on January 15, 2013 (78 FR 3086). 8 In 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 near by to the violating monitor ing site [ s ] . Examples in clude 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 d ata

. The emissions analysis examines identified sources of direct

PM 2.5 , the major components of direct PM 2.5 , e.g., primary organic carbon (POC) and PM 2.5 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 (SO 2 ), nitrogen oxides (NO

x ), total volatile organic compounds (VOC), and ammonia (NH 3 ). Emissions data are generally derived from the most

recent Nat ional 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 do es not meet the current threshold for reporting to the NEI but collectively contributes to area PM 2.5 concentrations. Emissions data indicate th e potential for a source to contribute to observed violations, making it useful in assessing boundaries of nonattainment areas.

Factor 3: Meteorology

. E valuatin g meteorological data help s to determine the effect on the fate and transport of

emissions cont ributing to PM 2.5 concentrations and to identify areas potentially contributing to the violations at

monitor ing sites . The Factor 3 analysis include s 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 include s examin ing the physical features of the land that might define the airshed and, therefore, affect the formation and distribution of PM 2.5 over an area. Mountains or other physical features may influence the fate and transport of emissions and PM 2.5 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 Regi onal 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 PM 2.5 , section 3(a) indicates “Except as otherwise provided in this appendix, all valid FRM/FEM/AR M PM 2.5 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 valu e)
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

deadlin e for certification has passed and EPA judges the data to be complete and accurate.”Page 4 of 36

inversions, such as valley

- type features that effectively “trap” air pollution, leading to periods of elevated PM 2.5 concentrations.

Factor 5: Jurisdictional boundaries . The analysis of jurisd ictional boundaries identifie s the governmental planning and organizational stru cture 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, metro politan 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 des ign values of ambient air quality monitoring locations, county, and existing 1997 annual

and/or 2006 24

- hour PM 2.5 NAAQS nonattainment boundaries.

For purposes of the 1997 annual PM 2.5 NAAQS, this area was designated nonattainment. The boundary for the

1997 annual PM 2.5 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

PM 2.5 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 (K entucky ), and Warren (O hio ) having partial boundaries rathe r than entire counties, capturing the contribution of the urban area and for Boone the point sources. The partial county of Dearborn (I ndiana ) is also not included in the final nonattainment area for 2012 due to the closure of the Tanners Creek power plan t as a result of a permanent and enforceable consent decree, which results in the county no longer contributing to the Cincinnati

- Hamilton nonattainment area.Page 5 of 36

Figure 1. Final Nonattainment Bo undary 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 show s two violation s , and Butler County one violation of the

2012 PM 2.5 NAAQS based on 2011

- 2013 data; therefore Hamilton and Butler Count ies are included in the

nonattainment area. As shown in Figure 1 b

, EPA evaluated each county without a violating monitor ing site

located near the count ies with a violating monitor ing site . B ased on the five factors and other relevant

information , the EPA determine d 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.Page 6 of 36

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 PM 2.5 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 PM 2.5 NAAQS , the annual mean is calculated as the mean of quarter ly 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 PM 2.5 concentration s. For these reasons, for the Factor 1 a ir q uality analysis, the EPA assesse d and characterize d air quality at, and in the proximity of, the violating monitor ing 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 PM 2.5 mass in the area of analysis.

In most cases, the EPA assessed air quality data on a season al, or quarterly, basis

. 9 EPA also identifie d the spatial extent of these high PM 2.5 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, examin ing data on a
quarterly or seasonal basis can inform the relationshi p between the temporal variability of emissions and mete o rology andPage 7 of 36

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 c omposition of the monitored PM 2.5 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 des ign value monitoring site with data collected at IMPROVE 10 and other monitoring locations whose data are representative

o f 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

PM 2.5 Design Values and Total Mass Measurements

- The EPA examin ed ambient PM 2.5 air quality monitoring data represented by the DV s at the violating monitoring site and at other monitors in the area of analysis

. The

EPA calculate d DVs based on air quality data for the most recent 3 consecutive calendar years of quality

assured, certified air quality data from suitable FEM/FRM/ARM monitor ing sites in the EPA’s Air Quality System (AQS). For this designations analysis, the EPA used data f or the 201 1

- 201 3 period (i.e., the 201 3 design value), which are the most recent years with fully

- certified air quality data. A monitor’s DV is the metric or

the resulting PM 2.5 mass and composition . In some areas of the country where there may be noticeable month

- to

- month
variations in average PM 2.5 , 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 Monit oring 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 PM 2.5 mass and

chemical constituents obse rved 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 includ ed urban CSN site(s) reflect(s) a different
mixture of emissions sources, which could lead to misinterpretations. To generally account for differences in PM 2.5 mass between the violating site and the nearby CSN site(s), EPA determined material balance of t he PM 2.5 composition at the
violating site by assigning the extra measured PM 2.5 mass to the carbon components of PM 2.5 . Where the general urban
increment approach may be misleading, or in situations where non

- carbonaceous emissions are believed to be resp onsible

for a local PM 2.5 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 use d
alone. That rural mean was then subtracted from the quarterl y 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 ar ea, 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 Ha ze and its Constituents in the United

States: Report V, June 2011. Chapter 7

– Urban Excess in PM 2.5 Speciated Aerosol Concentrations,
http://vista.cira.colostate.edu/improve/Publications/Reports/2011/PDF/Chapter7.pdf

15 US EPA, Office of Air Quality Plan ning and Standards, December 2004. (2004) Area Designations for 1997 Fine

Particle (PM 2.5 ) Standards, Technical Support Document for State and Tribal Air Quality Fine Particle (PM 2.5 )
Designations, Chapter 3, Urban Excess Methodology. Available at

www.epa. gov/pmdesignations/1997standards/documents/final/TSD/Ch3.pdfPage 8 of 36

statistic that indicates whether that monitor attains a specified air quality standard. The 2012 a nnual PM 2.5 NAAQS is met at a monitor ing site when the 3

- year average annual mean concentration is 12.0 micrograms per cubic meter (μg/m 3 ) or less (e.g., 12.1 μg/m 3 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 201 3 DV ) and the most recent two design values based on all monitor ing s ites in the area of ana lysis 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/m 3 ) 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 PM 2.5 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 suff icient 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

§58.1 0(b) for cases where the FEM or ARM is identified as not of sufficient comparability to a collocated FRM ....”Page 9 of 36

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

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

b Th ese design value s 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 inco mplete 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 purpo se 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/m 3 . 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 fact or. 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 nona ttainment area and monitoring locations with 2011

- 2013 violating DVs. As indicated on the map, there is one violation in ButlerPage 10 of 36

County located near a steel facility, and there are 2 violating monitoring locations located in the city of Cincinnati, both jus t north of the Ohio River.

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

PM 2.5

. Figure 2 shows quarterly mean PM 2.5 concentrations for the most recent 3

- year period for the highest DV

m onitor ing 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 PM 2.5 NAAQS, because , as previously state d, 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 PM 2.5 Quarterly Means for 20 11

- 201 3

.

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 μ g/m 3 at each site, with consistent annual peaks occurring in Q3.

PM 2.5 Composition Measurements

- To assess potential emission s contribution s for each violating monitor ing

location , the EPA determined the various chemical species comprising total PM 2.5 to identify the chemical

constituents over the analysis area , which can provide insight into the types of emission sources impacting the

monitor ed concentration

. To best describe the PM 2.5 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 PM 2.5 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

μ g/m3 

# Cincinnati

- Hamilton PM 2.5 

# Quarterly Means 2011

- 2013

Campbell Butler Butler Butler Butler Hamilton

Hamilton Hamilton Hamilton Hamilton WarrenPage 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 PM 2.5 chemical

constituent based on annual averages for the years 20 10

- 2012

.

Figure 3a. Cincinnati

- Hamilton Annual Average PM 2.5 Chemical Constituents (2010

- 2012)

Figure 3b shows annual and quarterly chemical composition profiles and illustrates any seasonal or episodic

contributors to PM 2.5 mass. This “ increment analysis

, ” combin ed with the other factor analyses, can provide additional insight as to which sources or factors may contribute at a greater level. Simply stated, t his analysis

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

.

17 SANDWICH stands for measured S ulfate, A djusted N itrate, D erived W ater, I nferred C arbonaceous mass H ybrid
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 PM 2.5 and its non

- carbon components. This characterization of PM 2.5 mass also reflects
crustal material and other minor constituents. The resulting characterization provides a complete mass closure for the

measured FRM PM 2.5 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 PM 2.5 Data Analysis, National Air Mo nitoring 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 PM 2.5 to support PM Implementation, EPA State /Local/Tribal Training
Workshop: PM 2.5 Final Rule Implementation and 2006 PM 2.5 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 Me thod Fine
Particulate Matter for Six Eastern U.S. Cities . J. Air & Waste Manage. Assoc. 2006 56:500

– 511. 5.5

1.2 1.3 4.9 0.5 

### Annual Average PM 2.5 

### Chemical Constituents 2010

- 2012

( μ g/m3)

Oragnic Mass

Elemental Carbon

Nitrate

Sulfate

CrustalPage 12 of 36

Figure 3b. Cincinnati

- Hamilton Annual and Quarterly Average PM 2.5 Species (2010

- 2012) a

a Adjusted to FRM Total PM 2.5 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 component s , 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 PM 2.5 constituents at monit oring sites within the area relative to monitoring sites outside of the analysis area to account for the difference between regional background

concentrations of PM 2.5 , and the concentrations of PM 2.5 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 4 a includes pie charts showing the annual and quar terly chemical mass co nstituents of the urban increment. The quarterly pie

chart s correspond to the high

- concentration quarters identified in Figure 2 . Evaluating these high concentration quarters can help identify composition of PM 2.5 during these times. Note that in these charts, sulfates and nitrates have been adjusted to represent their mass in measured PM 2.5

.

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 PM 2.5 

## Species 2010

-

2012 Adjusted to FRM Total PM 2.5

Sulfates Organic mass Nitrates Elemental Carbon CrustalPage 13 of 36

Figure 4 a

. Cincinnati

- Hamilton Urban Increment Analysis for 2010

- 2012

.

1.36

0.56 0.44 0.34 0.03 

### Average Urban Increment 2010

- 2012

( μ g/m3)

Organic

Carbon

Elemental

Carbon

Nitrates

Sulfates

Crustal

2.01

0.00 1.24 0.08 

### Q

- 1 Average Urban Increment 2010

- 2012



### ( μ g/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal

1.53 0.06 0.39 0.05 

### Q

- 2 Average Urban Increment 2010

- 2012

( μ g/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

CrustalPage 14 of 36 0.68

0.22 0.71 0.01 

### Q

- 3 Average Urban Increment 2010

- 2012

( μ g/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

Crustal

2.75 0.50 0.44 0.18 0.06 

### Q

- 4 Average Urban Increment 2010

- 2012

( μ g/m3)

Organic Carbon

Elemental Carbon

Nitrates

Sulfates

CrustalPage 15 of 36

Figure 4 b

. Cincinnati

- Hamilton Average Urban Increment Analysis for 2010

- 2012

.

Hamilton County has two monitoring site s and Butler County with one with a DV exceeding the NAAQS. In addition, Hamilton and adjoining counties have clear seasonal peaks in ambient PM 2.5 concentrations in Q1

. Butler, Campbell, Hamilton, and Warren Counties during the 2011 Q3 monitored PM 2.5 concentrations

exceed ing 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 PM 2.5 so urces 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 μ g/m3 

## Average Urban Increment 2010

- 2012 ( μ g/m3)

Organic Carbon Elemental Carbon Nitrates Sulfates CrustalPage 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 PM 2.5 concentrations at the violating m onitoring 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. (Alth ough 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 analyz ed annual emissions data. The EPA examined emissions of identified sources or source categories of direct PM 2.5 , the major components of direct

PM 2.5 (organic mass, elemental carbon, crustal materi al (and/or individual trace metal compounds)), primary nitrate and primary sulfate, and precursor gaseous pollutants (i.e., SO 2 , NO

x , total VOC, and NH 3 ). The EPA also considered the distance of those sources of emissions from the violating monitoring site . While direct PM 2.5 emissions and its major carbonaceous components are generally associated with sources near violating PM 2.5 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 NO

x and VOC

emissions contributions to PM 2.5 from mobile and stationary sources) and transport from neighboring areas can contribute to higher PM 2.5 levels at the violating monit oring sites.

Emissions Data

For this factor, the EPA reviewed data from the 2011 National Emissions Inventory (NEI) version 1 ( s ee http://www.epa.gov/ttn/chief/net/2011inventory.html ). For each county in the area of analysis, the EPA

examin ed 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 PM 2.5 , components of

direct PM 2.5 , 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 PM 2.5 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 VOCs 22 contribute to ( P OM); directly emitted EC contributes to PM 2.5 EC; NO X , NH 3 and directly emitted nitrate contribute to PM 2.5 nitrate mass (PNO 3 ) ; SO 2 , NH 3 and directly emitted sulfate

contribute to PM 2.5 sulfate mass (PSO 4 ) ; and

, directly emitted crustal material and metal oxides contribute to

PM 2.5 crustal matter (PCrustal)

. 23

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

contributors to the PM 2.5 violating monitor s are somewhat proportional to the PM 2.5 chemical constituents in the estimated urban increment. Thus, directly emitted POC is more important per ton than SO 2 , partially because

21 For purposes of this designations effort, “major” point sources are those whose sum of PM precursor emissions ( PM 2.5 +

NO

x + SO 2 + VOC + NH 3 ) 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 PM 2.5 OM than POC.

23 See , Seinfeld J. H. and Pandis S. N. (2006) Atmospheric Chemistry and Physics: From Ai r 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 P ollution 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 PM 2.5 whe reas SO 2 must conver t to PM 2.5 and not all of the emitted SO 2 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 PM 2.5 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 PM 2.5 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 PM 2.5 and Precursors (tons/year)

County, State Total

NH 3 Total

N O

x Total

VOC Total

SO 2 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 1,059Page 18 of 36

Table 3b. County

- Level Emissions for Components of Directly Emitted PM 2.5 (tons/year) 25

County, State PNO 3 PSO 4 EC POM P Crustal 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 PM 2.5 emissions value from Table 3a into its components. Th ese 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 i dentified the following components warranting

additional review: The constituents of in terest are POM, direct PM, and NO

x . 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 W arren 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 non attainment area.

Table 4a. County

- Level NOx Emissions (tons/year) for the Final Nonattainment Area

County, State Total

NO

x 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 PM 2.5 and PM 2.5 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 fac ility

- level emissions of

direct PM 2.5 , components of direct PM 2.5 , 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 facilit y 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) NH 3 NO

x PM 2.5 SO 2 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 917Page 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 1,559Page 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 s ources from the violating monitoring

location s , 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 monitor ing location is particularly important for dir ectly

emitted PM 2.5 . The influence of directly emitted PM 2.5 on ambient PM 2.5 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

- fire d 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 NO

x , SO 2 , and direct PM located 18 miles from the DV monitor, and DEGs of St. Bernard a nd Emery Oleochemicals, both higher NO

x and SO 2 and both 2 miles away from the DV monitor. These very local sources of SO 2 are potentially impacting the higher SO2 speciation data in some quarters, as noted above (Figure 3a and 3b). Butler County has maj or sources including AK Steel with high direct PM 2.5 emissions located 20 miles from the Hamilton county design value monitor,

Miller Coors with SO 2 emissions 18 miles from the monitor, and Wausau Paper Towel & Tissue, LLC with

moderate SO 2 emissions 23 miles from the monitor. Clermont County major sources are two Duke power plants emitting high levels of NO

x , SO 2 , and direct PM, located 17 and 26 miles away from the monitor. Although the wind roses in Figure 8 do not show substantial wind s 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 wi th high

NO

x , SO 2 and direct PM, 28 miles from the monitor, and Cincinnati/Northern with high NO

x and PM 2.5 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 PM 2.5 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 Emission s in the Area of Analysis for the Cincinnati

- Hamilton Area.

26 Baker, K

. R. and K . M. Foley

. A nonlinear regression model es timating single source concentrations of primary and

seco ndarily formed PM 2.5

. 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 sour ces, 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 increment s (Figures 4a and 4b). Although the area of analysis looked at county emission s for counties including and surrounding the violating monitor , counties not
listed above either had low over all 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 lo cated 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.Page 26 of 36

Figure 6 a . 2010 County

- Level Population in the Area of Analysis for the Cincinnati

- Hamilton A rea.Page 27 of 36

Figure 6b. Topogra phic map showing urbanized area for the Cincinnati

- Hamilton Area.

Traffic and Vehicle Miles Travelled

H igh vehicle mile s 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 NO

x , VOC, and direct PM may contribute to ambient particulate matter that contributes to monitored violations of the NAAQS

in the area

. In combination w ith the population/population density data and the location of main transportation arteries, an assessment of VMT help s identify the probable location of nonpoint source emissions that

contribute to violations in the area

. Comparatively high VMT in a count y outside of the CBSA or CSA signifie s integration with the core urban area contained within the CSA or CBSA , and indicate s that a county with the high VMT may be appropriate to include in the nonattainment area because emissions from mobile sources in

tha t county contribute to violations in the area

. Table 7 shows 2011 VMT while Figure 7 overlays 2011 county

level 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

.Page 28 of 36

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%Page 29 of 36

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.Page 30 of 36

Hamilton County consistently rank highest in direct PM 2.5 /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 ar eas 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 ur banized, 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 pr ecursor 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 PM 2.5 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

indica te 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 w ind roses from hourly observations of wind direction and wi nd 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 Cincinnati

Hamilton 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.pdfPage 31 of 36

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

- Hamilton A rea

.

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
predomina n tly westerly winds mostly at mid

- level speeds of 4 to 8 meters per second. This generally suggest s that pot ential 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 SO 2 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 u pwind of the attaining
Montgomery monitor, leading to the conclusion that these two counties are not contributing to the Hamilton
County violating monitors.Page 32 of 36

Figure 9. HYSPLIT K ernel Density Estimation Plo ts for the Cincinnati

- Hamilton AreaPage 33 of 36Page 34 of 36

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 Coun ties.

Factor 4: Geography/topography

To evaluate the geography/topography factor, the EPA assessed physical features of the a rea of analysis that might define the airshed and thus affect the formation and distribution of PM 2.5 concentrations over the area

. While the Cincinnati

- Middletown

- Wilmington, O hio

- 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 t he 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 necessa ry 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 bounda ries, 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 t he 1997

annual PM 2.5 NAAQS

. The states have recommended different boundar ies for the 2012 annual PM 2.5 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 co ntributing 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 wit hin 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 de scribed above, both individually and in combination, the EPA is designating the following counties as part of the Cincinnati

- Hamilton O hio

- Kentucky nonattainment area because they are either violating the 2012 annual PM 2.5 NAAQS or contributing to a violat ion 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 199 7 annual PM 2.5 NAAQS. The air quality monitoring sites in Butler and HamiltonPage 35 of 36

Count ies indicate violations of the 2012 annual PM 2.5 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 t he EPA has concluded that these areas contribute to the parti culate matter

concentrations in violation of the 2012 annual PM 2.5 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 O hio

Kentucky 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 fro m area sources and the urbanized area in these two counties. Clermont County contains two major power plants that are contributing 73% of total SO 2 , which has a high impact on the urban increment in Q3, 10% of the total area VOCs, 23% of the areas NO

x , and 43% of direct PM for the area.

SO 2 , NO

x , dir e ct PM, and VOCs are primarily associated with the power plants

– with some of the VOC, NO

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

the Cincin nati

- 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 th e nonattainment being mobile sources contributing to the direct PM emissions, and reflected in the urban increment. Warren County has similar overall emissions of NO

x and direct PM as Campbell and Kenton

– contributing 10% of the areas total direct PM, whe re mobile and area sources dominate the sources contributing. The EPA has final ized 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 includi ng 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 p atterns 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

Base d 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 , O hio

- 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 NO

x emissions in the Cincinnat i

- Hamilton , O hio

- 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 , O hio

- Kentucky area . Point so urces in th ese 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, O hio

Kentucky area. As indicated in the factors above, Boone, Campbell, and Kenton Counties have sources of direct PM, NO

x and VOC emissions; rank among the highest VMT contributors for the Cincinnati

- Hamilton

, O hio

- 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 , O hio

- Kentucky nonattainment area. The partial county boundary for Boone, Campbell, and Kenton Counties includ es all of the census tract s in these counties except the censusPage 36 of 36

tract s 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.