Technical Support Document (TSD) 

for the Transport Rule 

Docket ID No. EPA-HQ-OAR-2009-0491 

Air Quality Modeling 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Assessment Division 

Research Triangle Park, NC 27711 

June 2010 
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i

Table of Contents 

I. Introduction ................................................................................................................................. 1 

II. Air Quality Modeling Platform.................................................................................................. 3 

A. Air Quality Model.......................................................................................................... 3

B. Modeling Domains......................................................................................................... 3 

C. Model Simulation Periods.............................................................................................. 4 

D. Meteorological Input Data ............................................................................................. 5 

E. Initial and Boundary Concentrations.............................................................................. 7 

F. Model Performance Evaluation for Ozone and PM2.5 .................................................... 8 

III. Projection of Future Nonattainment and Maintenance for Annual PM2.5, 24-

Hour PM2.5, and 8-Hour Ozone .......................................................................................... 8 

A. Procedures for Processing Ambient Ozone and PM2.5 Data.......................................... 9 

B. Projection of Future Design Values and Determination of 

Nonattainment and Maintenance for Annual and 24-Hour PM2.5 .............................. 11 

1. Methodology for Projecting Future Annual PM2.5 Nonattainment 

and Maintenance ................................................................................................... 12 

2. Methodology for Projecting Future 24-Hour PM2.5 Nonattainment 

and Maintenance ................................................................................................... 14 

C. Projection of Future Design Values and Determination of 

Nonattainment and Maintenance for 8-Hour Ozone................................................... 18 

IV. State by State Source Contribution Modeling and Results..................................................... 20 

A. Nonattainment and Maintenance Receptors for the Assessment of PM2.5

and Ozone Contributions ............................................................................................ 21 

B. Overview of Approach for Source Apportionment Modeling .................................... 29 

C. Approach to Calculating Contributions for Annual and 24-Hour PM2.5..................... 30 

D. Approach to Calculating Contributions for 8-Hour Ozone......................................... 34 

E. Evaluation of Interstate Contributions......................................................................... 35 

1. Contributions to Annual PM2.5 Nonattainment and Maintenance .......................... 37 

2. Contributions to 24-Hour PM2.5 Nonattainment and Maintenance......................... 38 

3. Contributions to 8-Hour Ozone Nonattainment and Maintenance ......................... 40 

V. Air Quality Impacts of the Proposed SO2 and NOX Emissions Reductions ............................ 42 

A. Characterization of Emissions in 2014 for the Proposed Remedy 

Scenario....................................................................................................................... 42 

B. Impacts on Projected PM2.5 Design Value Concentrations......................................... 46 

C. Impacts on Annual and 24-Hour PM2.5 Nonattainment and 

Maintenance................................................................................................................ 49 

D. Analysis of Residual Nonattainment for 24-Hour PM2.5 ............................................. 53 

E. Impacts on Projected 8-Hour Ozone Design Value .................................................... 58 

F. Impacts on 8-Hour Ozone Nonattainment and Maintenance ...................................... 59 

G. Impacts on Visibility in Class 1 Areas......................................................................... 63 
ii

List of Appendices 

Appendix A. 

Air Quality Model Performance Evaluation 

Appendix B. 

2003-2007 Base Period and Projected 2012 and 2014 Design Values for Monitoring Sites 

in the Eastern Modeling Domain 

Appendix C. 

Ozone and PM2.5 Contribution Calculation Examples 

Appendix D. 

2012 Base Case State-by-State Contributions to Nonattainment and Maintenance for 

8-Hour Ozone, Annual PM2.5, and 24-Hour PM2.5

Appendix E. 

Upwind States to Downwind Nonattainment and Maintenance Linkages 

Appendix F. 

Summary of Aggregated Emissions of SO2 and NOX for States Included in the Transport 

Rule 

Appendix G. 

Concentration and Difference Maps for Annual PM2.5, 24-Hour PM2.5, and 8-Hour Ozone 

Appendix H. 

Quarterly “Exceedances” of the 24-Hour PM2.5 NAAQS for the 2014 Base Case and 2014 

Remedy Scenario 

Appendix I. 

Impacts on Visibility in Class I Areas of the West 
1

I. Introduction

In this technical support document (TSD) we describe the air quality modeling 

performed to support the Environmental Protection Agency’s Transport Rule proposal 

(TR). For this rule we used air quality modeling to: 

(1) identify locations expected to be nonattainment or have maintenance problems 

for annual (average) PM2.5, 24-hour PM2.5, and/or 8-hour ozone for the analytic 

years chosen for the TR, 

(2) quantify the impacts (i.e., air quality contributions) of SO2 and NOX emissions 

from upwind states on downwind annual and 24-hour PM2.5 concentrations at 

monitoring sites projected to be nonattainment or have maintenance problems in 

2012 for the 1997 annual and 2006 24-hour PM2.5 NAAQS1, respectively, 

(3) quantify the contributions of NOX emissions from upwind states on downwind 

8-hour ozone concentrations at monitoring sites projected to be nonattainment or 

have maintenance problems in 2012 for the 1997 ozone NAAQS, and 

(4) assess the health and welfare benefits of the emissions reductions expected to 

result from this rule. 

This TSD includes information on the following analytical aspects of the TR air quality 

modeling: 

(1) a description of the modeling platform, 

(2) an evaluation of model predictions compared to measured concentrations, 

(3) the procedures and results of projecting ozone and PM2.5 concentrations for 

future year scenarios, 

(4) the procedures used to quantify interstate contributions for annual and 24-hour 

PM2.5, and 8-hour ozone, 

(5) the results of evaluating the interstate contributions using concentration 

thresholds, and 

(6) the air quality impacts from the SO2 and NOX emissions reductions expected 

from the “State Budgets/Limited Trading” remedy (i.e., remedy scenario), as 

described in section IV.D of the proposed rule preamble. 

 

1

 National Ambient Air Quality Standards (NAAQS). 
2

Air quality modeling was performed for four emissions scenarios: a 2005 base 

year, a 2012 “no CAIR” base case, a 2014 “no CAIR” base case, and the 2014 remedy 

scenario. The modeling for 2005 was used as the base year for projecting air quality for 

each of the three future year scenarios. The year 2005 was selected for the Transport 

Rule base year because this is the most recent year for which EPA has a complete 

national emissions inventory. The 2012 base case modeling was used to identify future 

nonattainment and maintenance locations and to quantify the contributions of emissions 

in upwind states to annual and 24-hour PM2.5, and 8-hour ozone at downwind receptors. 

The 2014 base case and 2014 remedy case modeling were used to quantify the benefits of 

the emissions reductions from the rule. The rationale for selecting 2012 and 2014 as the 

analytic years for the TR is provided in the preamble. 

Section II of this TSD describes the air quality modeling platform and the 

evaluation of model predictions of PM2.5 and ozone using corresponding ambient 

measurements. Section III defines the procedures for projecting future case PM2.5 and 

ozone concentrations and the approach for determining locations with projected 

nonattainment and/or maintenance problems. Section IV describes (1) the source 

apportionment (i.e., contribution) modeling, (2) the procedures for quantifying 

contributions to nonattainment and/or maintenance, and (3) the evaluation of 

contributions to determine which State are covered by this rule. In section V we present 

the results of modeling performed for 2014 to assess the impacts on air quality of the 

emissions reductions expected from this rule. Information on the development of 

emissions inventories for the TR and the steps and data used in creating emissions inputs 

for air quality modeling can be found in the Transport Rule Emissions Inventory TSD 

(EITSD). The EITSD also contains State/sector/pollutant emissions summaries for each 

of the emissions scenarios modeled. 
3

II. Air Quality Modeling Platform 

A. Air Quality Model 

 We used the Comprehensive Air Quality Model with Extension2 (CAMx) version 

5 to simulate ozone and PM2.5 concentrations for the 2005 base year and the 2012 and 

2014 future year scenarios modeled for the TR. CAMx was also used for the source 

apportionment modeling to quantify interstate transport of ozone and PM2.5. CAMx is a 

three-dimensional grid-based photochemical model designed to simulate the formation, 

chemical transformation, transport, and removal of ozone, secondary and directly emitted 

PM2.5, and their precursor species on national, regional, and local scales for short-term 

episodes up to annual time periods. 

B. Modeling Domains 

The CAMx model applications for the TR focus on States in the Eastern U.S. 

using a horizontal grid resolution of 12 x 12 km. The Eastern modeling region (i.e., 

Eastern modeling domain) extends from Texas northward to North Dakota and eastward 

to the East Coast. Thirty seven States and the District of Columbia are wholly contained 

with this modeling domain. The Eastern modeling domain was nested within a coarse 

grid, 36 x 36 km modeling domain which covers the lower 48 states and adjacent portions 

of Canada and Mexico. The 36 km and 12 km modeling domains extend vertically from 

the surface to 100 millibars (approximately 15 km) using a sigma-pressure coordinate 

system. Predictions from the 36 km Continental U.S. (CONUS) domain were used to 

provide initial and boundary concentrations for simulations in the 12 km domain. Each 

of the emissions scenarios were modeled for the 36 km and 12 km domains. However, 

as described below, the source apportionment modeling was performed for the 37 States 

wholly within the 12 km Eastern domain only. The 36 km and 12 km modeling domains 

are shown in Figure II-1. Table II-1 provides geographic specifications for these 

domains. 

In addition to the CAMx model, the TR modeling platform includes (1) emissions 

for the 2005 base year, 2012 base case, 2014 base case and 2014 remedy scenario, (2) 

meteorology for the year 2005, and (3) estimates of intercontinental transport (i.e., 

boundary concentrations) from a global photochemical model. Using these input data, 

 

2

 Comprehensive Air Quality Model with Extensions Version 5 User’s Guide. Environ 

International Corporation. Novato, CA. March 2009. 
4

CAMx was run to generate hourly predictions of ozone and PM2.5 component species 

concentrations for each grid cell in the modeling domains. The development of 2005 

meteorological inputs and initial and boundary concentrations for the CONUS domain 

are described below. The emissions inventories used in the TR air quality modeling are 

described in the EITSD. 

Figure II-1. Transport Rule air quality modeling domains. 

Table II-1. Specifications of the air quality modeling domains. 

36 x 36 km Domain 12 x 12 km Domain 

Map Projection Lambert Conformal Projection 

Grid Resolution 36 km 12 km 

Coordinate Center 97 deg W, 40 deg N 

True Latitudes 33 deg N and 45 deg N 

Dimensions 148 x 112 x 14 279 x 240 x 14 

Vertical extent 14 Layers: Surface to 100 millibar level 

 (see Table II-2) 

C. Model Simulation Periods 

Annual simulations of CAMx were performed in quarterly segments (i.e., January 

through March, April through June, July through September, and October through 

December) for each emissions scenario. The CONUS domain simulations included a 

“ramp-up” period, comprised of 10 days before the beginning of each quarter, to mitigate 

CONUS 36 km Domain 

Eastern 12 km Domain 
5

the effects of initial concentrations. For the 12 km Eastern domain simulations we used a 

3-day ramp-up period for each quarter. Fewer ramp-up days were used for the 12 km 

simulations because the initial concentrations were derived from the parent 36 km 

simulations. 

D. Meteorological Input Data

All of the TR CAMx simulations used meteorology for 2005. The gridded 

meteorological input data for 2005 were derived from simulations of the Pennsylvania 

State University / National Center for Atmospheric Research Mesoscale Model. This 

model, commonly referred to as MM5, is a limited-area, nonhydrostatic, terrainfollowing system that solves for the full set of physical and thermodynamic equations 

which govern atmospheric motions.3

 Meteorological model input fields were prepared 

separately for each of the domains shown in Figure II-1 using MM5 version 3.7.4. The 

MM5 simulations were run on the same map projection as CAMx. 

The CONUS and Eastern meteorological model runs were configured similarly. 

The selections for key MM5 physics options are as follows: 

• Pleim-Xiu PBL and land surface schemes 

• Kain-Fritsh 2 cumulus parameterization 

• Reisner 2 mixed phase moisture scheme 

• RRTM longwave radiation scheme 

• Dudhia shortwave radiation scheme 

Three dimensional analysis nudging for temperature and moisture was applied 

above the boundary layer only. Analysis nudging for the wind field was applied above 

and below the boundary layer. The 36 km domain nudging weighting factors were 3.0 x 

104 for wind fields and temperatures and 1.0 x 105 for moisture fields. The 12 km domain 

nudging weighting factors were 1.0 x 104

 for wind fields and temperatures and 1.0 x 105

for moisture fields. 

The meteorological model runs were conducted in 5.5 day segments with 12 

hours of overlap for spin-up purposes. The meteorological modeling domains contain 34 

vertical layers with an approximately 38 m deep surface layer and a 100 millibar top. 

The MM5 and CAMx vertical structures are shown in Table II-2 and do not vary by 

horizontal grid resolution. The meteorological outputs from the MM5 simulations were 

 

3

 Grell, G., J. Dudhia, and D. Stauffer, 1994: A Description of the Fifth-Generation Penn 

State/NCAR Mesoscale Model (MM5), NCAR/TN-398+STR., 138 pp, National Center for 

Atmospheric Research, Boulder CO. 
6

processed to create model-ready inputs for CAMx using the MM5CAMx meteorological 

processor. 

Table II-2. Vertical layer structure for MM5 and CAMx (heights are layer top). 

CAMx Layers MM5 Layers Sigma P Approximate 

Height (m)

Approximate 

Pressure (mb)

0 0 1.000 0 1000 

1 1 0.995 38 995 

2 2 0.990 77 991 

3 0.985 115 987 3 4 0.980 154 982 

5 0.970 232 973 4 6 0.960 310 964 

7 0.950 389 955 5 8 0.940 469 946 

9 0.930 550 937 

6 10 0.920 631 928 

11 0.910 712 919 

12 0.900 794 910 

7 13 0.880 961 892 

14 0.860 1,130 874 

15 0.840 1,303 856 

8 16 0.820 1,478 838 

17 0.800 1,657 820 

18 0.770 1,930 793 9 19 0.740 2,212 766 

20 0.700 2,600 730 10 21 0.650 3,108 685 

22 0.600 3,644 640 11 23 0.550 4,212 595 

24 0.500 4,816 550 

12 25 0.450 5,461 505 

26 0.400 6,153 460 

27 0.350 6,903 415 

28 0.300 7,720 370 

29 0.250 8,621 325 13 

30 0.200 9,625 280 

31 0.150 10,764 235 

32 0.100 12,085 190 

33 0.050 13,670 145 14 

34 0.000 15,674 100 

The 2005 MM5 meteorological predictions were compared to the corresponding 

observations as part of a model performance evaluation to assess the adequacy of the 

MM5 simulated fields. The qualitative aspects of this evaluation included the 

comparison of the model-estimated synoptic patterns against observed patterns from 

historical weather chart archives for 2005. Additionally, the evaluation compared spatial 

patterns of monthly average rainfall and monthly maximum planetary boundary layer 

(PBL) heights. Qualitatively, the model fields closely matched the observed synoptic 
7

patterns, which is not unexpected given the use of nudging. An operational evaluation 

was performed using statistical comparisons of model/observed pairs (e.g., mean 

normalized bias, mean normalized error, index of agreement, root mean square errors, 

etc.) for multiple meteorological parameters. For this portion of the evaluation, five 

meteorological parameters were investigated: temperature, humidity, shortwave 

downward radiation, wind speed, and wind direction. The three individual MM5 

evaluations are described elsewhere.4,5,6 The results of these analyses indicate that the 

bias and error values associated with the 2005 meteorological data were generally within 

the range of past meteorological modeling results that have been used for air quality 

applications. 

E. Initial and Boundary Concentrations 

The lateral boundary and initial species concentrations are provided by a threedimensional global atmospheric chemistry model, the GEOS-CHEM model7

 (standard 

version 7-04-118). The global GEOS-CHEM model simulates atmospheric chemical and 

physical processes driven by assimilated meteorological observations from the NASA’s 

Goddard Earth Observing System (GEOS). The GEOS-CHEM model was run for 2005 

with a grid resolution of 2.0 degree x 2.5 degree (latitude-longitude) and 30 vertical 

layers up to 100 mb. The predictions were used to provide one-way dynamic boundary 

conditions at three-hour intervals and an initial concentration field for the 36 km CAMx 

simulations. The concentrations from the 36 km CONUS domain model simulations 

were used to develop the initial/boundary concentrations for the corresponding 12 km 

Eastern domain model simulations. 

 

4

Baker K. and P. Dolwick. Meteorological Modeling Performance Evaluation for the Annual 

2005 Eastern U.S. 12-km Domain Simulation, USEPA/OAQPS, February 2, 2009. 

http://www.epa.gov/scram001/meteorology/metgridmodeling/met.2005.12EUS1.pdf 5

 Baker K. and P. Dolwick. Meteorological Modeling Performance Evaluation for the Annual 

2005 Western U.S. 12-km Domain Simulation, USEPA/OAQPS, February 2, 2009. 

http://www.epa.gov/scram001/meteorology/metgridmodeling/met.2005.12WUS1.pdf

6

 Baker K. and P. Dolwick. Meteorological Modeling Performance Evaluation for the Annual 

2005 Continental U.S. 36-km Domain Simulation, USEPA/OAQPS, February 2, 2009. 

http://www.epa.gov/scram001/meteorology/metgridmodeling/met.2005.36US1.pdf

7

 Yantosca, B., 2006. GEOS-CHEMv7-04112 User’s Guide, Atmospheric Chemistry Modeling 

Group, Harvard University, Cambridge, MA, March 05, 2006. 

8

 Henze, D.K., J.H. Seinfeld, N.L. Ng, J.H. Kroll, T-M. Fu, D.J. Jacob, C.L. Heald, 2008. Global 

modeling of secondary organic aerosol formation from aromatic hydrocarbons: high-vs.low-yield 

pathways. Atmos. Chem. Phys., 8, 2405-2420. 
8

F. Model Performance Evaluation for Ozone and PM2.5 

The 2005 base year model predictions for ozone and fine particulate sulfate, 

nitrate, ammonium, organic carbon, elemental carbon, and crustal material were 

compared to measured concentrations in order to evaluate the performance of the 

modeling platform for replicating observed concentrations. This evaluation was 

comprised of statistical comparisons of paired modeled and observed data. Details on the 

model performance evaluation including a description of the methodology and model 

performance statistics are provided in the Appendix A. 

The most relevant pollutants for the TR are ozone and the sulfate and nitrate 

components of PM2.5. Overall, the model performance statistics for these pollutants are 

within or close to the ranges found in other recent applications. The normalized mean 

bias for 8-hour daily maximum ozone concentrations was -2.9 percent and the normalized 

mean error was 13.2 percent for the months of May through September 2005, based on an 

aggregate of observed-predicted pairs within the 12 km modeling domain. For the 

summer months of June though August, when observed sulfate concentrations are highest 

in the East, the model predictions of 24-hour average sulfate were lower than the 

corresponding measured values by 7 percent at urban sites and 9 to 10 percent at rural 

sites in the IMPROVE9

 and CASTNET10 monitoring networks, respectively. For the 

winter months of December through February, when observed nitrate concentrations are 

highest in the East, the model predictions of 24-hour average particulate nitrate were 

lower than the corresponding measured values by 12 percent at urban sites and by 4 

percent at rural sites in the IMPROVE monitoring network. 

III. Projection of Future Nonattainment and Maintenance for Annual 

PM2.5, 24-Hour PM2.5, and 8-Hour Ozone 

In this section we describe the approach for projecting future concentrations of 

ozone and PM2.5 to identify locations that are expected to be nonattainment or have a 

maintenance problem in the 2012 and 2014 future year scenarios modeled for the TR. 

The nonattainment and maintenance locations are based on projections of future air 

quality at existing ozone and PM2.5 monitoring sites. The nonattainment and 

 

9

 Interagency Monitoring of PROtected Visual Environments (IMPROVE). Debell, L.J., et. al. 

Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United 

States: Report IV. November 2006. 

10 Clean Air Status and Trends Network (CASTNET) 2005 Annual Report. EPA Office of Air 

and Radiation, Clean Air Markets Division. Washington, DC. December 2006. 
9

maintenance sites for the 2012 base case are used as the “receptors” for quantifying the 

contributions of emissions in upwind states to nonattainment and maintenance in 

downwind locations. Future year concentrations for the 2014 base case and 2014 remedy 

scenario were used to assess the impacts of the emissions reductions from the TR on 

ozone and PM2.5 air quality. 

For this analysis we are using the air quality modeling results in a “relative” sense 

to project future concentrations of ozone and PM2.5. Rather than use the absolute modelpredicted future year ozone and PM2.5 concentrations, the base year and future year 

predictions are used to calculate a (relative) percent change in ozone and PM2.5

concentrations. In this approach, the ratio of future year model predictions to base year 

model predictions are used to adjust ambient measured data up or down depending on the 

relative (percent) change in model predictions for each location. The use of ambient data 

as part of the calculation helps to constrain the future year predictions, even if the 

absolute model concentrations are over-predicted or under-predicted. As described 

below, the procedures for projecting annual and 24-hour PM2.5 and 8-hour ozone conform 

to the methodologies contained in the final guidance for attainment demonstration 

modeling11 (referred to below as “the modeling guidance”). 

A. Procedures for Processing Ambient Ozone and PM2.5 Data 

In this analysis we use measurements of ambient ozone and PM2.5 data from 

several State and Federal monitoring networks. This includes data from over 500 ozone 

monitoring sites as well as over 500 Federal Reference Method (FRM) PM2.5 sites in the 

Eastern U.S.. In addition, speciated PM2.5 data from the Chemical Speciation Network 

(CSN) and IMPROVE network are used to estimate PM2.5 species concentrations at each 

FRM site. The ambient data used in this analysis were obtained from EPA’s Air Quality 

System (AQS). 

In order to use the ambient data, the raw measurements must be processed into a 

form pertinent for useful interpretations. The ozone data were processed consistent with 

the formats associated with the 1997 8-hour NAAQS for ozone. The level of the 1997 8-

hour O3 NAAQS is 0.08 ppm. The 8-hour ozone standard is not met if the 3-year 

 

11 U.S. EPA, 2007: Guidance on the Use of Models and Other Analyses for Demonstrating 

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze; Office of Air Quality 

Planning and Standards, Research Triangle Park, NC. 

http://www.epa.gov/ttn/scram/guidance/guide/final-03-pm-rh-guidance.pdf
10

average of the annual 4th highest daily maximum 8-hour O3 concentration is greater than 

0.08 ppm (0.085 ppm when rounded up). This 3-year average is referred to as the design 

value. 

The PM2.5 ambient data were processed consistent with the formats associated 

with the NAAQS for PM2.5. For PM2.5, we evaluated concentrations of both the annual 

PM2.5 NAAQS and the 24-hour PM2.5 NAAQS. The annual PM2.5 standard is not met if 

the 3-year average of the annual mean concentration is greater than 15.0 μg/m3 (15.05 

μg/m3

 when rounded up). The 3-year average annual mean concentration is computed at 

each site by averaging the daily Federal Reference Method (FRM) samples by quarter, 

averaging these quarterly averages to obtain an annual average, and then averaging the 

three annual averages. The 3-year average annual mean concentration is referred to as 

the annual design value. 

The 24-hour standard is not met when the 3-year average of the annual 98th

percentile PM2.5 concentration is greater than 35 μg/m3 (35.5 μg/m3 when rounded up). 

The 3-year average mean 98th percentile concentration is computed at each site by 

averaging the 3 individual annual 98th percentile values at each site. The 3-year average 

98th percentile concentration is referred to as the 24-hour design value. 

The modeling guidance recommends using the average of the three design value 

periods centered on the year of the base year emissions. Since 2005 was the base 

emissions year for the TR modeling, we used the design value for 2003-2005, 2004-2006, 

and 2005-2007 to represent the base period ozone and PM2.5 concentrations. Specifically, 

we used ambient ozone and annual and 24-hour PM2.5 design values for the periods 2003-

2005, 2004-2006, and 2005-2007 as the starting point for our projections of design values 

for each of the future year scenarios modeled. The 2003–2005, 2004-2006, and 2005-

2007 design values are accessible at www.epa.gov/airtrends/values.html. 

Ambient design values from monitoring sites were included in our analysis if the 

site had at least one complete12 design value in the 2003-2007 period.13 There were 721 

monitoring sites in the 12 km Eastern modeling domain which had at least one complete 

design value period for the annual PM2.5 NAAQS, and 736 sites which met this criteria 

 

12 Design value completeness was determined according to the monitoring rules in CFR 40 Part 

50 Appendix I (8-hour ozone) and Appendix N (annual and 24-hr PM2.5). 

13 If there is only one complete design value, then the nonattainment and maintenance design 

values are the same. 
11

for the 24-hour NAAQS14 and 787 sites which met the criteria for the 8-hour ozone 

NAAQS. 

B. Projection of Future Design Values and Determination of Nonattainment and 

Maintenance for Annual and 24-Hour PM2.5 

As noted above, the projection methodology for PM2.5 involves using the model 

predictions in a relative sense to estimate the change in PM2.5 between 2005 and each 

future year scenario. For a particular location, the percent change in modeled 

concentration is multiplied by the corresponding observed base period ambient 

concentration to estimate the future year design value for that location. The procedure 

for calculating future year annual and 24-hour PM2.5 design values is called the Speciated 

Modeled Attainment Test (SMAT). The SMAT approach is codified in a software tool 

available from EPA called MATS15. The software (including documentation) is available 

at: http://www.epa.gov/scram001/modelingapps_mats.htm. 

 As described below, design values of PM2.5 in 2012 and 2014 were estimated by 

applying the 2005 to 2012 or 2005 to 2014 relative change in model-predicted PM2.5

species concentrations to the measured (2003-2007) PM2.5 species concentrations. The 

PM2.5 species include sulfate, nitrate, ammonium, particle bound water, elemental carbon, 

salt, other primary PM2.5, and organic aerosol mass (by difference). Organic aerosol 

mass by difference is defined as the difference between FRM PM2.5 and the sum of the 

other components. 

For each FRM PM2.5 monitoring site, all valid design values (up to 3) from this 

period were averaged together. Since 2005 is included in all three design value periods, 

this has the effect of creating a 5-year weighted average, where the middle year is 

weighted 3 times, the 2nd and 4th years are weighted twice, and the 1st and 5th years are 

weighted once. We refer to this as the 5-year weighted average design value 

concentration. 

The 5-year weighted average design values were used to project concentrations 

for the 2012 and 2014 scenarios in order to determine which monitoring sites are 

expected to be nonattainment for these future year scenarios. For the 2012 base case we 

 

14 Design values were only used if they were deemed to be officially complete based on CFR 40 

Part 50 Appendix N. The completeness criteria for the annual and 24-hour PM2.5 NAAQS are 

different. Therefore, there are fewer complete sites for the annual NAAQS. 

15 U.S. EPA, 2009: Modeled Attainment Test Software; User’s Manual 

http://www.epa.gov/ttn/scram/guidance/guide/MATS%20manual-1-5-1.pdf
12

also projected design values for each of the individual 3-year design value periods (i.e., 

2003-2005, 2004-2006, and 2003-2007). The projection of design values for these 

individual periods was used in the interstate contribution analysis to determine sites 

expected to have maintenance problems, as described below. 

1. Methodology for Projecting Future Annual PM2.5 Nonattainment and 

Maintenance 

The following is a summary of the method used to project future year annual 

PM2.5 design values. Additional details are provided in the modeling guidance and 

MATS documentation. 

Base period (i.e., 2003 – 2007) FRM data are the starting point for projecting 

future design values since these data are used to determine attainment status. In order to 

apply SMAT to the FRM data, information on PM2.5 speciation is needed for the location 

of each FRM monitoring site. Since co-located PM2.5 speciation data are only available 

at ~15 percent of FRM monitoring sites, spatial interpolation techniques are used to 

calculate species concentrations for each FRM monitoring site. Speciation data from the 

IMPROVE and CSN were interpolated to each FRM monitor location by applying the 

Voronoi Neighbor Averaging (VNA) technique (using MATS). Additional information 

on the VNA interpolation techniques and data handling procedures can be found in the 

MATS User’s Guide. After the species fractions are calculated for each FRM site, the 

following procedures were used to estimate future year design values: 

Step 1: Calculate quarterly mean concentrations for each of the major species 

components of PM2.5 (i.e., sulfate, nitrate, ammonium, elemental carbon, organic carbon 

mass, particle bound water, salt, and blank mass). This is done by multiplying the 

monitored quarterly mean concentration of FRM-derived total PM2.5 by the monitored 

fractional composition of PM2.5 species for each quarter averaged over 3 years16 (e.g., 20 

percent sulfate fraction multiplied by 15 μg/m3

 PM2.5 equals 3 μg/m3 sulfate). 

Step 2: For each quarter, calculate the ratio of future year to base year model 

predictions for sulfate, nitrate, elemental carbon, organic carbon, and other primary 

PM2.5. The result is a set of species-specific relative response factors (RRF) (e.g., 

assume that the model-predicted 2005 base year sulfate for a particular location is 10.0 

μg/m3

 and the 2012 future concentration is 8.0 μg/m3, then RRF for sulfate is 0.8). The 

 

16 For this analysis, species fractions were calculated using FRM and speciation data for the 2004-

2006 time period. This was deemed to be representative of the 2005 base year period. 
13

RRFs are calculated based on the modeled concentrations averaged over the nine grid 

cells17 centered at the location of the monitor. 

Step 3: For each quarter and each of the species, multiply the base year quarterly 

mean component concentration (Step 1) by the species-specific RRF obtained in Step 2. 

This results in an estimated future year quarterly mean concentration for each species 

(e.g., 3 μg/m3 sulfate multiplied by the 0.8 RRF equals a future sulfate concentration of 

2.4 μg/m3). 

Step 4: The future year concentrations for the remaining species are then 

calculated18. The future year ammonium is calculated based on the calculated future year 

sulfate and nitrate concentrations, using a constant value for the degree of neutralization 

of sulfate (from the ambient data). The future year particle bound water concentration is 

calculated from an empirical formula derived from the Aerosol Inorganic Model (AIM). 

The inputs to the formula are the future year concentrations of sulfate, nitrate, and 

ammonium (from step 3). 

Step 5: Average the four quarterly mean future concentrations to obtain the future 

year annual design value concentration for each of the component species. Sum the 

species concentrations to obtain the future year annual design value for PM2.5. 

Step 6: Calculate the maximum future design value by processing each of the 

three base design value periods (2003-2005, 2004-2006, and 2005-2007) separately. The 

highest of the three future values is the maximum design value. The maximum design 

values are used to determine future year maintenance sites. 

The preceding procedures for determining future year PM2.5 concentrations were 

applied for each FRM site. The calculated annual PM2.5 design values are truncated after 

the second decimal place19. This is consistent with the truncation and rounding 

procedures for the annual PM2.5 NAAQS. Any value that is greater than or equal to 15.05 

μg/m3

 is rounded to 15.1 μg/m3 and is considered to be violating the NAAQS. Thus, 

sites with future year annual PM2.5 design values of 15.05 μg/m3 or greater, based on the 

 

17 The modeling guidance recommends calculating annual PM2.5 RRFs using a 3 X 3 grid cell 

array (9 grid cells) when using a model resolution of 12km. 

18 All of the calculations and assumptions are consistent with the default MATS settings (as 

described in the MATS user’s guide and the photochemical modeling guidance). Additionally, 

we did not explicitly model salt and therefore the salt concentration was held constant from the 

base to future. Blank mass was assumed to be a constant mass of 0.5 ug/m3 in both the base and 

future year. 

19 For example, a calculated annual average concentration of 14.94753 becomes 14.94 when 

digits beyond two places to the right are truncated. 
14

projection of 5-year weighted average concentrations, are predicted to be nonattainment 

sites. Sites with future year maximum design values of 15.05 μg/m3 or greater are 

predicted to be maintenance sites. Note that nonattainment sites are also maintenance 

sites because the maximum design value at a site is always greater than or equal to the 5-

year weighted average at that site. For ease of reference we use the term “nonattainment 

sites” to refer to those sites that are projected to exceed the NAAQS based on both the 

average and maximum design values. Those sites that are projected to be attainment 

based on the average design value but exceed the NAAQS based on the maximum design 

value are referred to as maintenance sites. The monitoring sites that we project to be 

nonattainment and/or maintenance for the annual PM2.5 NAAQS in the 2012 base case 

are used as the nonattainment/maintenance receptors for assessing the contribution of 

emissions in upwind states to downwind nonattainment and maintenance of the annual 

PM2.5 NAAQS (see section IV, below). The 2003-2007 base period and projected annual 

PM2.5 design values for each site for the 2012 and 2014 scenarios are provided in 

Appendix B. 

2. Methodology for Projecting Future 24-Hour PM2.5 Nonattainment and 

Maintenance 

The following is a summary of the procedures used for calculating future year 24-

hour PM2.5 design values. Additional details are provided in the modeling guidance and 

in the MATS documentation. Similar to the annual PM2.5 calculations, we are using the 

2003-2007 base period FRM data for projecting future year design values. The 24-hour 

PM2.5 calculations are computationally similar to the annual average calculations. The 

main difference is that the base period 24-hour 98th percentile PM2.5 concentrations are 

projected to the future year, instead of the annual average concentrations. Also, the PM2.5

species fractions and relative response factors are calculated from observed and modeled 

high concentration days, instead of quarterly average data. 

Both the annual PM2.5 and 24-hour PM2.5 calculations are performed on a calendar 

quarter basis. Since all years and quarters are averaged together in the annual PM2.5 

calculations, the individual years can be averaged together early in the calculations. 

However, in the 24-hour PM2.5 calculations, only the high quarter from each year is used 

in the final calculations. This represents the 98th percentile value, which can come from 

any of the 4 quarters in any of the five years (i.e. 2003 through 2007). Therefore all 

quarters and years (4 quarters per year x 5 years = 20 total quarters) must be carried 
15

through to near the end of the calculations when the individual future year high quarter 

values are selected. To calculate final future year design values, the high quarter for each 

year is identified and then a five year weighted average of the high quarters for each site 

was calculated to derive the future year design value. Table III-1 below provides an 

example of how the 24 hr PM2.5 design values are calculated from the 20 quarterly 

values. The table shows the PM2.5 concentrations for the base year for each of the 20 

quarters (from ambient measurements) and the corresponding future year concentrations 

for each of the 20 quarters. These quarterly data represent “potential” 98th percentile 

values. To calculate a design value, the highest quarterly value from each year is selected 

and then used to calculate a 5 year weighted average concentration. In Table III-1, the 

high quarters in each year are indicated by an asterisk. The base year and future year 5-

year weighted average design values are shown at the bottom of the table. 

Table III-1. Example 24-hour PM2.5 design value calculation at a single monitoring site. 

AIRS ID State County Year Quarter

Base Year 

PM2.5 (ug/m3) 

Future Year 

PM2.5 (ug/m3) 

10030010 Alabama Baldwin 2003 1 19.7 16.32 

10030010 Alabama Baldwin 2003 2 29.1* 22.29* 

10030010 Alabama Baldwin 2003 3 22.7 15.45 

10030010 Alabama Baldwin 2003 4 28.4 20.82 

10030010 Alabama Baldwin 2004 1 25.5 21.09* 

10030010 Alabama Baldwin 2004 2 18.1 13.91 

10030010 Alabama Baldwin 2004 3 27.5* 18.68 

10030010 Alabama Baldwin 2004 4 24.6 18.06 

10030010 Alabama Baldwin 2005 1 23.4 19.36 

10030010 Alabama Baldwin 2005 2 26.0* 19.93* 

10030010 Alabama Baldwin 2005 3 23.7 16.12 

10030010 Alabama Baldwin 2005 4 25.0 18.35 

10030010 Alabama Baldwin 2006 1 25.1 20.76* 

10030010 Alabama Baldwin 2006 2 25.6 19.62 

10030010 Alabama Baldwin 2006 3 25.7* 17.47 

10030010 Alabama Baldwin 2006 4 15.9 11.72 

10030010 Alabama Baldwin 2007 1 18.9 15.66 

10030010 Alabama Baldwin 2007 2 22.4* 17.18* 

10030010 Alabama Baldwin 2007 3 17.7 12.08 

10030010 Alabama Baldwin 2007 4 19.7 14.49 

 5 year weighted average = 26.2 20.3 
16

The following are the individual steps followed for calculating the future year 24-

hour PM2.5 design values: 

Step 1: At each FRM monitoring site, identify the maximum 24-hour PM2.5

concentration in each quarter that is less than or equal to the 98th percentile20 value over 

the entire year. This results in a data set for each year (for up to 5 years) for each site 

containing one quarter with the observed 98th percentile value and three quarters with the 

maximum highest values from each quarter that are less than or equal to the 98th 

percentile value for the year. All 20 quarters (i.e., 4 quarters in each of 5 years) of data 

are carried through the calculations until the high future year quarter value is identified in 

step 6. 

Step 2: In this step we calculate quarterly ambient concentrations on “high”21

days for each of the major component species of PM2.5 (sulfate, nitrate, ammonium, 

elemental carbon, organic carbon mass, particle-bound water, salt and blank mass). This 

calculation is performed by multiplying the monitored concentrations of FRM-derived 

total PM2.5 mass on the 10 percent highest days from each quarter, by the monitored 

fractional composition22 of PM2.5 species on the 10 percent highest PM2.5 days for each 

quarter, averaged over 3 years23 (e.g., 20 percent sulfate fraction multiplied by 40 μg/m3

PM2.5 equals 8 μg/m3 sulfate). 

Step 3: For each quarter, calculate the ratio of future year (i.e., 2012) to base year 

(i.e., 2005) predictions for sulfate, nitrate, elemental carbon, organic carbon, and other 

primary PM2.5 for the top 10 percent of days24 based on predicted concentrations of 24-

hour PM2.5. The result is a set of species-specific relative response factors (RRF) for the 

high PM2.5 days in each quarter (e.g., assume that 2005 predicted sulfate on the 10 

 

20 The 98th percentile values for each monitoring site used in the analysis were the values used in 

the “official” design value calculations. 

21 High ambient data and model days were defined as the top 10 percent days in each quarter 

based on 24-hour average concentrations of PM2.5 mass. 

22 Similar to the annual average calculations, the quarterly species fractions are calculated at each 

FRM site using interpolated species data (using VNA). For the 24-hour species interpolations, 

the highest 10% of monitor days in each quarter are interpolated. 

23 For this analysis, species fractions were calculated using an average of FRM and speciation 

data for the 2004-2006 time period. This was deemed to be representative of the 2005 modeling 

year. 

24 The calculation of the top 10% of modeled PM2.5 days in each quarter did not include “other 

primary PM2.5” (crustal) concentrations. As indicated in Appendix A, the crustal component of 

PM2.5 was severely over-predicted. Therefore, we did not want the selection of the “high” 

modeled days (which are used for the RRF calculations) to be unduly influenced by the overpredicted crustal concentrations. However, the modeled crustal concentrations were used to 

calculate the “crustal” component RRF. 
17

percent highest PM2.5 days for a quarter for a particular location is 20 μg/m3

 and the 2012 

base case concentration is 16 μg/m3, then RRF for sulfate is 0.8). The RRFs are 

calculated based on the modeled concentrations at the single25 grid cell where the monitor 

is located. 

Step 4: For each quarter, multiply the quarterly species concentration (step 2) by 

the quarterly26 species-specific RRF obtained in step 3. This leads to an estimated future 

quarterly concentration for each component. (e.g., 21.0 μg/m3 nitrate x 0.75 = future 

nitrate of 15.75 μg/m3

). 

Step 5: The future year concentrations for the remaining species are then 

calculated27. The future year ammonium is calculated based on the calculated future year 

sulfate and nitrate concentrations, using a constant value for the degree of neutralization 

of sulfate (from the ambient data). The future year particle bound water concentration is 

calculated from an empirical formula derived from the AIM. The inputs to the formula 

are the calculated future year concentrations of sulfate, nitrate, and ammonium (from step 

4). 

Step 6: Sum the species concentrations to obtain quarterly PM2.5 values. This 

step is repeated for each quarter and for each of the 5 years of ambient data. The highest 

daily value (from the 4 quarterly values) for each year at each monitor is considered to be 

the estimated future year 98th percentile 24-hour value for that year.

Step 7: The estimated 98th percentile values for each of the 5 years are averaged 

over 3 year intervals to create the 3 year average design values (e.g. the high quarter from 

2003, 2004, and 2005 are averaged. Then the high quarter from 2004, 2005, and 2006 

are averaged, etc.). These (up to 3) design values are averaged to create a 5 year 

weighted average for each monitoring site. 

Step 8: Calculate the maximum future design value by processing each of the 

three base design value periods (2003-2005, 2004-2006, and 2005-2007) separately. The 

 

25 The modeling guidance recommends using a single grid cell to calculate RRFs for the 24-hr 

PM2.5 NAAQS. 

26 Since there is only one modeled base year (2005), there are four quarterly RRFs at each 

monitor. The modeled quarterly RRF for quarter 1 is multiplied by the ambient data for quarter 1 

for each of the 5 years of ambient data. The same procedure is applied for the other 3 quarters. 

27 All of the calculations and assumptions are consistent with the default MATS settings (as 

described in the MATS user’s guide and the photochemical modeling guidance). Additionally, 

we did not explicitly model salt and therefore the salt concentration was held constant from the 

base to future. Blank mass was assumed to be a constant mass of 0.5 ug/m3 in both the base and 

future year. 
18

highest of the three future values is the maximum design value. The maximum design 

values are used to determine future year 24-hour PM2.5 maintenance receptors. 

The preceding procedures for determining future year 24-hour PM2.5

concentrations were applied for each FRM site. The 24-hour PM2.5 design values are 

truncated after the first decimal place. This approach is consistent with the truncation 

and rounding procedures for the 24-hour PM2.5 NAAQS. Any value that is greater than 

or equal to 35.5 μg/m3 is rounded to 36 μg/m3 and is violating the NAAQS. Sites with 

future year 5 year weighted average design values of 35.5 μg/m3

 or greater, based on the 

projection of 5-year weighted average concentrations, are predicted to be nonattainment. 

Sites with future year maximum design values of 35.5 μg/m3

 or greater are predicted to 

be maintenance sites. Note that nonattainment sites for the 24-hour NAAQS are also 

maintenance sites because the maximum design value is at a site is always greater than or 

equal to the 5-year weighted average for that site. For ease of reference we use the term 

“nonattainment sites” to refer to those sites that are projected to exceed the NAAQS 

based on both the average and maximum design values. Those sites that are projected to 

be attainment based on the average design value but exceed the NAAQS based on the 

maximum design value are referred to as maintenance sites. The monitoring sites that we 

project to be nonattainment and/or maintenance for the 24-hour PM2.5 NAAQS in the 

2012 base case are used as the nonattainment/maintenance receptors for assessing the 

contribution of emissions in upwind states to downwind nonattainment and maintenance 

of 24-hour PM2.5 NAAQS (see section IV, below). The 2003-2007 base period and 

projected 24-hour PM2.5 design values for each site for the 2012 and 2014 scenarios are 

provided in Appendix B. 

C. Projection of Future Design Values and Determination of Nonattainment and 

Maintenance for 8-Hour Ozone 

The following is a summary of the future year 8-hour ozone calculations. 

Additional details are provided in the modeling guidance and MATS documentation. 

Base period 2003-2007 ambient ozone design value data are the starting point for 

projecting future year design values. Since ozone is a single species, the ozone projection 

procedure is relatively simple (compared to the PM2.5 projection methodologies). It is not 

necessary to interpolate ambient ozone data, since ambient ozone design values and 

gridded, modeled ozone data are all that are needed for the projections. 
19

To project 8-hour ozone design values we used the 2005 base year, the 2012 

future base case, and 2014 future base and control case model-predicted ozone 

concentrations to calculate relative response factors. The methodology we followed is 

consistent with the attainment demonstration modeling guidance. The RRFs were 

applied to the 2003-2007 ozone design values through the following steps: 

Step 1: For each monitoring site calculate the mean of the modeled 8-hour daily 

maximum predictions across all days with 8-hour daily maximum predictions greater 

than or equal to 85 ppb28. The mean concentrations are calculated using the predictions 

in the nine grid cells that include or surround the location of the monitoring site. The 

RRF for a site is the ratio of the mean prediction in the future year to the mean prediction 

in the 2005 base year. The RRFs were calculated on a site-by-site basis. 

Step 2: The RRF for each site is then multiplied by the 2003-2007 5-year 

weighted average ambient design value for that site, yielding an estimate of the future 

year (2012) design value at that particular monitoring location. 

Step 3: We calculate the maximum future design value by projecting design 

values for each of the three base periods (2003-2005, 2004-2006, and 2005-2007) 

separately. The highest of the three future values is the maximum design value. This 

maximum value is used to identify the 8-hour ozone maintenance receptors. 

The preceding procedures for determining future year 8-hour ozone design values 

were applied for each ozone monitoring site. The future year design values are truncated 

to integers in units of ppb. This approach is consistent with the truncation and rounding 

procedures for the 8-hour ozone NAAQS. Future year design values that are greater than 

or equal to 85 ppb are considered to be violating the NAAQS. Sites with future year 5 

year weighted average design values of 85 ppb or greater are predicted to be 

nonattainment. Sites with future year maximum design values of 85 ppb or greater are 

predicted to be future year maintenance sites. Note that, as described previously for the 

annual and 24-hour PM2.5 NAAQS, nonattainment sites for the ozone NAAQS are also 

maintenance sites because the maximum design value is always greater than or equal to 

the 5-year weighted average. For ease of reference we use the term “nonattainment sites” 

to refer to those sites that are projected to exceed the NAAQS based on both the average 

 

28 As specified in the attainment demonstration modeling guidance, if there are less than 10 

modeled days > 85 ppb, then the threshold is lowered in 1 ppb increments (to as low as 70 ppb) 

until there 10 days. If there are less than 5 days > 70 ppb, then an RRF calculation is not 

completed for that site. 
20

and maximum design values. Those sites that are projected to be attainment based on the 

average design value but exceed the NAAQS based on the maximum design value are 

referred to as maintenance sites. The monitoring sites that we project to be 

nonattainment and/or maintenance for the ozone NAAQS in the 2012 base case are the 

nonattainment/maintenance receptors used for assessing the contribution of emissions in 

upwind states to downwind nonattainment and maintenance of ozone NAAQS as part of 

this proposal. The 2003-2007 base period and projected 8-hour ozone design values for 

all sites for the 2012 and 2014 scenarios are provided in Appendix B. 

IV. State by State Source Contribution Modeling and Results 

This section documents the procedures used to quantify the impacts (i.e., 

contributions) of emissions in individual States on annual PM2.5, 24-hour PM2.5, and/or 8-

hour ozone concentrations at projected 2012 nonattainment and maintenance sites in the 

East. The purpose of this assessment is to determine which States contribute to ozone, 

and/or annual PM2.5, and/or 24-hour PM2.5 nonattainment and/or maintenance problems 

in other States29 in amounts at or above thresholds based on 1 percent of the 

corresponding NAAQS. The air quality contributions were quantified using source 

apportionment techniques in CAMx. In general, these techniques track the formation and 

transport of ozone and particulate matter from specific emissions sources and calculate 

the contribution of sources and precursors to ozone and PM2.5 at individual receptor 

locations. The strength of the photochemical model source apportionment technique is 

that all modeled ozone and/or PM2.5 mass at a given receptor location in the modeling 

domain can be tracked back to specific sources of emissions and boundary conditions in 

order to fully characterize culpable sources. This type of source apportionment is useful 

for understanding both the types of sources or regions and the magnitude of the 

contributions that are associated with ozone and PM2.5, as estimated by the model. More 

details on the implementation of source apportionment in CAMx can be found in the 

CAMx user’s guide30. 

 

29 In this assessment we refer to source States as “upwind” States and nonattainment and/or 

maintenance sites in other States as “downwind” nonattainment and/or maintenance and 

“downwind” receptors. 

30 Comprehensive Air Quality Model with Extensions Version 5 User’s Guide. Environ 

International Corporation. Novato, CA. March 2009. 
21

A. Nonattainment and Maintenance Receptors for the Assessment of PM2.5 and Ozone 

Contributions 

As described above in section III, we identified monitoring sites in the East that 

are expected to be nonattainment and/or have maintenance problems for the 2012 base 

case for the 1997 annual and 2006 24-hour PM2.5 standards and the 1997 8-hour 

standard31. These 2012 nonattainment and/or maintenance sites are used as the receptors 

in the analysis of interstate contributions. Note that counties with multiple monitoring 

sites can have both nonattainment sites and maintenance only sites. 

Table IV-1 contains the 2003-2007 base period average and maximum annual 

PM2.5 design values and the corresponding 2012 base case average and maximum design 

values for sites projected to be nonattainment of the annual PM2.5 NAAQS in 2012. Table 

IV-2 contains this same information for projected 2012 base case maintenance-only sites. 

There are 32 sites in 21 counties projected to be nonattainment for the annual PM2.5

NAAQS in 2012. There are 16 sites in 14 counties projected to have maintenance only 

problems for the annual PM2.5 NAAQS in 2012. The 2012 base case annual PM2.5

nonattainment and/or maintenance sites in the East are shown in Figure IV-1. 

Table IV-1. Average and maximum 2003-2007 and 2012 base case annual PM2.5 design 

values (μg/m3

) at projected nonattainment sites. 

Monitor ID State County 

Average 

Design 

Value 2003-

2007 

ug/m3 

Maximum 

Design 

Value 2003-

2007 

ug/m3 

Average 

Design 

Value 

2012 

ug/m3 

Maximum 

Design 

Value 2012 

ug/m3 

10730023 Alabama Jefferson 18.48 18.67 17.15 17.33 

10732003 Alabama Jefferson 17.07 17.45 15.99 16.35 

130210007 Georgia Bibb 16.47 16.78 15.33 15.62 

130630091 Georgia Clayton 16.47 16.71 15.07 15.29 

131210039 Georgia Fulton 17.43 17.47 16.01 16.04 

170310052 Illinois Cook 15.75 16.02 15.16 15.43 

171191007 Illinois Madison 16.72 17.01 16.56 16.85 

171630010 Illinois Saint Clair 15.58 15.74 15.48 15.63 

180190006 Indiana Clark 16.40 16.60 15.96 16.16 

180372001 Indiana Dubois 15.18 15.68 15.07 15.57 

180970078 Indiana Marion 15.26 15.43 15.18 15.36 

180970081 Indiana Marion 16.05 16.36 15.93 16.25 

180970083 Indiana Marion 15.90 16.27 15.77 16.15 

211110043 Kentucky Jefferson 15.53 15.75 15.19 15.41 

261630015 Michigan Wayne 15.88 16.40 15.05 15.55 

 

31 As indicated previously, average design values are used to indentify sites that are 

nonattainment and maximum design values are used to identify sites that have a maintenance 

problem. 
22

Monitor ID State County 

Average 

Design 

Value 2003-

2007 

ug/m3 

Maximum 

Design 

Value 2003-

2007 

ug/m3 

Average 

Design 

Value 

2012 

ug/m3 

Maximum 

Design 

Value 2012 

ug/m3 

261630033 Michigan Wayne 17.50 18.16 16.57 17.19 

390170016 Ohio Butler 15.74 16.11 15.25 15.61 

390350038 Ohio Cuyahoga 17.37 18.10 16.26 16.95 

390350045 Ohio Cuyahoga 16.47 16.98 15.42 15.91 

390350060 Ohio Cuyahoga 17.11 17.66 16.02 16.55 

390610014 Ohio Hamilton 17.29 17.53 16.69 16.93 

390610042 Ohio Hamilton 16.85 17.25 16.33 16.71 

390610043 Ohio Hamilton 15.55 15.82 15.05 15.32 

390617001 Ohio Hamilton 16.17 16.56 15.65 16.03 

390618001 Ohio Hamilton 17.54 17.90 16.93 17.27 

420030064 Pennsylvania Allegheny 20.31 20.75 18.90 19.31 

420031301 Pennsylvania Allegheny 16.26 16.57 15.13 15.42 

420070014 Pennsylvania Beaver 16.38 16.45 15.23 15.30 

420710007 Pennsylvania Lancaster 16.55 17.46 15.19 16.01 

421330008 Pennsylvania York 16.52 17.25 15.25 15.94 

540110006 West Virginia Cabell 16.30 16.57 15.25 15.50 

540391005 West Virginia Kanawha 16.52 16.59 15.28 15.34 

Table IV-2. Average and maximum 2003-2007 and 2012 base case annual PM2.5 design 

values (μg/m3) at projected maintenance-only sites. 

Monitor ID State County 

Average 

Design 

Value 2003-

2007 

Maximum 

Design 

Value 2003-

2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 

2012 

170313301 Illinois Cook 15.24 15.59 14.73 15.06 

170316005 Illinois Cook 15.48 16.07 14.92 15.48 

211110044 Kentucky Jefferson 15.31 15.47 14.93 15.09 

360610056 New York New York 16.18 17.02 14.98 15.74 

390350027 Ohio Cuyahoga 15.46 16.13 14.50 15.13 

390350065 Ohio Cuyahoga 15.97 16.44 14.96 15.40 

390610040 Ohio Hamilton 15.50 15.88 15.03 15.40 

390811001 Ohio Jefferson 16.51 17.17 14.95 15.54 

391130032 Ohio Montgomery 15.54 15.92 15.01 15.37 

391510017 Ohio Stark 16.15 16.59 14.99 15.40 

420110011 Pennsylvania Berks 15.82 16.19 14.77 15.11 

482011035 Texas Harris 15.42 15.84 14.74 15.14 

540030003 West Virginia Berkeley 15.93 16.19 14.95 15.20 

540090005 West Virginia Brooke 16.52 16.80 14.95 15.22 

540291004 West Virginia Hancock 15.76 16.64 14.34 15.15 

540490006 West Virginia Marion 15.03 15.25 14.96 15.18 
23

Figure IV-1. Projected 2012 base case annual PM2.5 nonattainment and/or maintenance 

sites in the East. 

Table IV-3 contains the 2003-2007 base period average and maximum 24-hour 

PM2.5 design values and the 2012 base case average and maximum design values for sites 

projected to be 2012 nonattainment of the 24-hour PM2.5 NAAQS in 2012. Table IV-4 

contains this same information for projected 2012 24-hour maintenance-only sites. There 

are 92 sites in 43 counties projected to be nonattainment for the 24-hour PM2.5 NAAQS 

in 2012. There are 38 sites in 31 counties projected to have maintenance only problems 

for the 24-hour PM2.5 NAAQS in 2012. The 2012 base case 24-hour PM2.5

nonattainment and/or maintenance site in the East are shown in Figure IV-2. 
24

Table IV-3. Average and maximum 2003-2007 and 2012 base case 24-hour PM2.5 design 

values (μg/m3

) at projected nonattainment sites. 

Monitor ID State County 

Average 

Design 

Value 

2003-2007 

Maximum 

Design 

Value 

2003-2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 2012 

10730023 Alabama Jefferson 44.0 44.2 40.0 40.7 

10732003 Alabama Jefferson 40.3 40.8 38.1 38.9 

90091123 Connecticut New Haven 38.3 40.3 35.7 36.6 

170310052 Illinois Cook 40.2 41.4 38.5 39.7 

170310057 Illinois Cook 37.3 38.6 35.7 37.0 

170310076 Illinois Cook 38.0 39.1 36.3 37.3 

170311016 Illinois Cook 43.0 46.3 41.0 44.1 

170312001 Illinois Cook 37.7 40.6 35.6 38.2 

170313103 Illinois Cook 39.6 40.3 38.1 38.7 

170313301 Illinois Cook 40.2 43.3 38.2 41.0 

170316005 Illinois Cook 39.1 41.8 37.4 39.8 

171190023 Illinois Madison 37.3 38.1 39.4 40.2 

171191007 Illinois Madison 39.1 40.1 40.0 40.6 

171192009 Illinois Madison 34.9 35.9 37.2 38.2 

171193007 Illinois Madison 34.0 34.6 36.5 37.3 

180190006 Indiana Clark 37.5 39.4 38.1 40.2 

180372001 Indiana Dubois 35.3 36.9 36.5 38.0 

180830004 Indiana Knox 35.9 36.3 35.9 36.5 

180890022 Indiana Lake 38.9 44.0 37.3 42.1 

180890026 Indiana Lake 38.4 41.3 36.3 39.3 

180970042 Indiana Marion 34.2 35.3 36.3 37.2 

180970043 Indiana Marion 38.4 39.9 40.5 42.0 

180970066 Indiana Marion 38.3 39.6 40.3 41.8 

180970078 Indiana Marion 36.6 37.6 38.7 39.7 

180970079 Indiana Marion 35.6 36.7 37.2 38.3 

180970081 Indiana Marion 38.2 39.2 40.1 41.1 

180970083 Indiana Marion 36.6 37.0 39.0 39.3 

181570008 Indiana Tippecanoe 35.6 36.7 35.9 36.9 

191630019 Iowa Scott 37.1 37.1 36.8 36.8 

210590005 Kentucky Daviess 33.8 33.8 37.0 37.0 

211110043 Kentucky Jefferson 35.4 36.1 35.8 36.4 

211110044 Kentucky Jefferson 36.1 36.6 36.0 36.5 

211110048 Kentucky Jefferson 36.4 37.2 35.6 36.4 

245100040 Maryland Baltimore City 39.0 40.9 36.3 38.3 

245100049 Maryland Baltimore City 38.1 38.1 35.5 35.5 

261150005 Michigan Monroe 38.8 39.6 37.0 38.0 

261250001 Michigan Oakland 39.9 40.4 37.9 38.4 

261470005 Michigan St. Clair 39.6 40.6 38.4 39.4 

261610008 Michigan Washtenaw 39.4 40.8 38.1 39.8 

261630015 Michigan Wayne 40.1 40.6 38.5 39.1 

261630016 Michigan Wayne 42.9 45.4 40.6 43.0 

261630019 Michigan Wayne 40.9 41.4 38.6 39.1 

261630033 Michigan Wayne 43.8 44.2 42.1 42.6 

261630036 Michigan Wayne 37.1 37.9 36.3 36.9 

290990012 Missouri Jefferson 33.4 34.2 35.7 36.5 
25

Monitor ID State County 

Average 

Design 

Value 

2003-2007 

Maximum 

Design 

Value 

2003-2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 2012 

291831002 Missouri Saint Charles 33.1 34.7 35.5 37.1 

295100007 Missouri St. Louis City 33.1 33.5 36.0 36.3 

295100087 Missouri St. Louis City 34.3 34.7 36.4 36.9 

340171003 New Jersey Hudson 39.0 40.5 35.7 36.1 

340172002 New Jersey Hudson 41.4 41.4 38.2 38.2 

340390004 New Jersey Union 40.4 41.4 36.7 37.2 

360050080 New York Bronx 38.8 40.2 35.9 36.2 

360610056 New York New York 39.7 40.6 37.1 38.0 

360610128 New York New York 39.4 41.8 36.2 38.0 

390170003 Ohio Butler 39.2 41.1 40.3 42.3 

390170016 Ohio Butler 37.1 37.7 37.5 37.8 

390170017 Ohio Butler 37.9 37.9 38.5 38.5 

390171004 Ohio Butler 37.1 38.1 37.8 38.6 

390350038 Ohio Cuyahoga 44.2 47.0 41.2 44.0 

390350045 Ohio Cuyahoga 38.5 41.5 36.0 39.0 

390350060 Ohio Cuyahoga 42.1 45.7 39.4 42.8 

390350065 Ohio Cuyahoga 38.6 41.0 36.5 38.9 

390490024 Ohio Franklin 38.5 39.7 36.6 37.6 

390490025 Ohio Franklin 38.4 39.1 36.1 36.4 

390610006 Ohio Hamilton 37.6 37.6 38.0 38.0 

390610014 Ohio Hamilton 38.2 39.4 37.5 38.5 

390610040 Ohio Hamilton 36.7 37.7 35.8 36.8 

390610042 Ohio Hamilton 37.3 38.2 37.2 38.0 

390610043 Ohio Hamilton 35.9 36.2 36.0 36.4 

390617001 Ohio Hamilton 38.8 39.6 37.7 38.1 

390618001 Ohio Hamilton 40.6 40.9 39.6 40.3 

390811001 Ohio Jefferson 41.9 45.5 36.5 39.9 

391130032 Ohio Montgomery 37.8 40.0 36.3 38.5 

391530017 Ohio Summit 38.0 39.6 35.6 37.2 

420030008 Pennsylvania Allegheny 39.4 39.9 35.9 36.3 

420030064 Pennsylvania Allegheny 64.2 68.2 58.8 62.3 

420030093 Pennsylvania Allegheny 45.6 51.5 41.1 46.2 

420030116 Pennsylvania Allegheny 42.5 42.5 37.1 37.1 

420031008 Pennsylvania Allegheny 41.3 42.8 38.0 39.3 

420031301 Pennsylvania Allegheny 40.3 42.4 36.6 38.6 

420070014 Pennsylvania Beaver 43.4 44.6 37.7 39.1 

420110011 Pennsylvania Berks 37.7 39.1 35.8 37.0 

420210011 Pennsylvania Cambria 39.0 39.4 40.3 40.7 

420430401 Pennsylvania Dauphin 38.0 39.0 35.7 37.1 

420710007 Pennsylvania Lancaster 40.8 44.0 37.7 40.1 

421330008 Pennsylvania York 38.2 40.7 35.9 38.8 

471251009 Tennessee Montgomery 36.3 37.5 36.6 37.9 

540090011 West Virginia Brooke 43.9 44.9 39.9 40.8 

550790010 Wisconsin Milwaukee 38.6 40.0 37.7 39.0 

550790026 Wisconsin Milwaukee 37.3 41.3 36.3 40.1 

550790043 Wisconsin Milwaukee 39.9 40.8 38.8 39.7 

550790099 Wisconsin Milwaukee 37.7 38.7 36.8 37.7 
26

Table IV-4. Average and maximum 2003-2007 and 2012 base case 24-hour PM2.5 design 

values (μg/m3

) at projected maintenance-only sites. 

Monitor ID State County 

Average 

Design 

Value 

2003-2007 

Maximum 

Design 

Value 

2003-2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 2012 

110010041 Washington D.C. Washington D.C. 36.3 37.8 34.0 35.6 

110010042 Washington D.C. Washington D.C. 34.9 37.0 33.0 35.6 

170310022 Illinois Cook 36.6 38.6 34.9 36.6 

170310050 Illinois Cook 36.1 38.0 34.1 35.8 

170314007 Illinois Cook 34.3 36.4 33.6 35.7 

171630010 Illinois Saint Clair 33.7 34.1 35.3 35.9 

171971002 Illinois Will 36.4 37.1 35.1 35.8 

180390003 Indiana Elkhart 34.4 36.3 33.8 35.6 

180431004 Indiana Floyd 33.2 34.5 34.3 35.7 

181670023 Indiana Vigo 34.8 36.1 35.1 36.5 

191390015 Iowa Muscatine 36.0 37.7 34.5 36.0 

210290006 Kentucky Bullitt 34.6 35.8 35.0 36.3 

211451004 Kentucky McCracken 33.6 35.9 34.4 36.8 

212270007 Kentucky Warren 33.1 35.1 33.7 36.3 

240031003 Maryland Anne Arundel 35.5 37.4 33.8 36.7 

245100035 Maryland Baltimore (City) 37.7 39.2 34.7 35.5 

261630001 Michigan Wayne 37.8 40.1 35.4 37.8 

295100085 Missouri St. Louis City 33.2 33.8 35.3 35.7 

360610062 New York New York 38.8 41.6 35.3 37.0 

360610079 New York New York 37.9 40.2 34.2 36.4 

390350027 Ohio Cuyahoga 36.6 38.8 34.5 36.6 

390350034 Ohio Cuyahoga 36.5 37.9 33.7 35.7 

390810017 Ohio Jefferson 40.7 42.4 35.3 36.8 

390950024 Ohio Lucas 36.3 38.6 34.2 36.5 

390950026 Ohio Lucas 34.9 36.7 33.6 35.6 

390990014 Ohio Mahoning 36.8 38.2 34.2 35.8 

391130031 Ohio Montgomery 35.7 37.1 34.3 35.6 

391351001 Ohio Preble 32.8 33.9 34.3 35.5 

391550007 Ohio Trumbull 36.2 37.8 33.9 35.6 

420030095 Pennsylvania Allegheny 38.7 40.7 34.3 36.6 

420033007 Pennsylvania Allegheny 37.5 43.1 33.8 38.5 

420410101 Pennsylvania Cumberland 38.0 40.2 35.3 37.0 

421255001 Pennsylvania Washington 38.1 39.9 33.9 35.5 

471650007 Tennessee Sumner 33.6 34.5 35.1 36.0 

540090005 West Virginia Brooke 39.4 41.5 33.9 36.1 

550250047 Wisconsin Dane 35.5 36.9 35.1 36.1 

550790059 Wisconsin Milwaukee 35.5 37.0 34.8 36.3 

551330027 Wisconsin Waukesha 35.4 36.2 34.9 35.6 
27

Figure IV-2. Projected 2012 base case 24-hour PM2.5 nonattainment and/or maintenance 

sites in the East. 

Table IV-5 contains the 2003-2007 base period average and maximum 8-hour 

ozone design values and the 2012 base case average and maximum design values for sites 

projected to be 2012 nonattainment of the 8-hour ozone NAAQS in 2012. Table IV-6 

contains this same information for projected 2012 8-hour ozone maintenance-only sites. 

There are 11 sites in 6 counties projected to be nonattainment for the 1997 8-hour ozone 

NAAQS in 2012. There are 16 sites in 9 counties projected to have maintenance only 

problems for the 1997 8-hour ozone NAAQS in 2012. The 2012 base case 8-hour ozone 

nonattainment and/or maintenance sites in the East are shown in Figure IV-3. 
28

Table IV-5. Average and maximum 2003-2007 and 2012 base case 8-hour ozone design 

values (ppb) at projected nonattainment sites. 

Monitor ID State County 

Average 

Design 

Value 

2003-2007 

Maximum 

Design 

Value 

2003-2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 2012 

220330003 Louisiana 

East Baton 

Rouge 92.0 96.0 87.8 91.6 

361030002 New York Suffolk 90.0 91.0 86.3 87.2 

361030009 New York Suffolk 90.3 91.0 85.1 85.8 

421010024 Pennsylvania Philadelphia 90.3 91.0 85.3 86.0 

480391004 Texas Brazoria 94.7 97.0 88.8 91.0 

482010051 Texas Harris 93.0 98.0 88.4 93.1 

482010055 Texas Harris 100.7 103.0 95.7 97.9 

482010062 Texas Harris 95.7 99.0 90.5 93.7 

482010066 Texas Harris 92.3 96.0 89.9 93.5 

482011039 Texas Harris 96.3 100.0 90.5 93.9 

484391002 Texas Tarrant 93.3 95.0 85.1 86.7 

Table IV-6. Average and maximum 2003-2007 and 2012 base case 8-hour ozone design 

values (ppb) at projected maintenance-only sites. 

Monitor ID State County 

Average 

Design 

Value 

2003-2007 

Maximum 

Design 

Value 

2003-2007 

Average 

Design 

Value 2012 

Maximum 

Design 

Value 2012 

90010017 Connecticut Fairfield 88.0 90.0 83.1 85.0 

90011123 Connecticut Fairfield 92.3 94.0 84.8 86.4 

90013007 Connecticut Fairfield 90.0 92.0 84.5 86.4 

90093002 Connecticut New Haven 90.3 93.0 82.9 85.4 

130890002 Georgia DeKalb 88.7 93.0 81.6 85.6 

131210055 Georgia Fulton 91.7 94.0 84.4 86.5 

361192004 New York Westchester 87.7 90.0 84.7 86.9 

420170012 Pennsylvania Bucks 88.0 92.0 81.8 85.6 

481130069 Texas Dallas 87.0 90.0 82.9 85.8 

481130087 Texas Dallas 87.0 88.0 84.6 85.6 

482010024 Texas Harris 88.0 92.0 83.3 87.1 

482010029 Texas Harris 91.7 93.0 84.4 85.6 

482011015 Texas Harris 89.0 96.0 83.7 90.3 

482011035 Texas Harris 86.3 95.0 82.0 90.3 

482011050 Texas Harris 89.3 92.0 83.9 86.5 

484392003 Texas Tarrant 93.7 95.0 84.0 85.2 
29

Figure IV-3. Projected 2012 base case 8-hour ozone nonattainment and/or maintenance 

sites in the East. 

B. Overview of Approach for Source Apportionment Modeling 

Source apportionment modeling for both ozone and PM2.5 was performed using 

the 2012 base case emissions. In this modeling we tracked ozone and PM2.5 formed from 

anthropogenic emissions in each State that is wholly within the 12 km modeling domain. 

The modeling results were used to calculate the contributions of the emissions in these 

States to concentrations at nonattainment and maintenance sites in other (i.e., downwind) 

States. The States included in the source apportionment modeling for ozone and PM2.5

are: Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia, Illinois, Indiana, 

Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, 

Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New Jersey, New York, 

North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South 
30

Carolina, South Dakota, Tennessee, Texas, Vermont, Virginia, West Virginia, 

Washington D.C.32, and Wisconsin. 

There are several other States that are only partially contained within the 12 km 

modeling domain (i.e., Colorado, Montana, New Mexico, and Wyoming). We did not 

track the emissions or assess the contribution from emissions in these States individually. 

Rather, the emissions from these States were tracked as a combined set of emissions 

together with emissions from sources in Canada and Mexico in a category named “other”. 

Emissions from wild fires in all States were also included in the “other” category. In our 

CAMx source apportionment techniques we also tracked the contributions from biogenic 

emissions (regionally) and initial and boundary concentrations (IC/BCs). The 

contributions from these three categories (i.e., other, biogenic, and IC/BCs) were not used 

in the analysis to determine which State to include in the TR. 

C. Approach to Calculating Contributions for Annual and 24-Hour PM2.5 

 We used the CAMx Particulate Source Apportionment Technique (PSAT) to 

calculate contributions to annual and 24-hour PM2.5 nonattainment and maintenance. The 

CAMx PSAT is capable of “tagging” (i.e., tracking) source category emissions for certain 

PM species and precursor emissions. For the Transport Rule, we ran PSAT to tag 

emissions of NOX, SO2, and primary PM2.5 from the individual States listed above. 

Each State was a separate tag, and the tagged emissions followed state boundaries (not 

grid cells). Information on the creation of tagged emissions can be found in the Transport 

Rule EITSD. Due to the relatively small modeled concentrations of secondary organic 

aerosols (SOA), and the relatively large runtime penalty of the SOA PSAT mechanism, 

we chose not to track SOA. 

 In the PSAT simulation, NOX emissions are tracked to contributions to particulate 

nitrate concentrations, SO2 emissions are tracked to contributions to particulate sulfate 

concentrations, and primary particulates (organic carbon, elemental carbon, and other, 

unspeciated PM2.5) are tracked as contributions to primary particulates. We combined the 

contributions of nitrate and sulfate in calculating the net contributions to PM2.5 for the 

purpose of evaluating the interstate contributions against specific threshold criteria, as 

described in section IV.E, below. The rationale for including mass associated with nitrate 

 

32 Although contributions from emissions in Washington, D.C. were tracked in the source 

apportionment modeling these contributions were combined with those of Maryland as a single 

entity. This is a logical approach because of the small size of the District of Columbia and, hence, 

its emissions and its close proximity to Maryland, as described in the TR preamble. 
31

plus sulfate and excluding primary PM2.5 and SOA in the contributions for the TR is 

articulated in section IV.B of the TR preamble. 

 We developed and applied several post-processing steps to transform the PSAT 

modeling outputs to PM2.5 contributions. The approach involved processing the PSAT 

model outputs using MATS along with other post-processing software to calculate the 

contribution of each upwind state to each nonattainment and/or maintenance site (i.e., 

receptor). 

The following is a description of the procedures for calculating contributions for 

annual PM2.5. These procedures were applied separately for each source State. 

1. Receptor sites include the 2012 base case annual PM2.5 nonattainment and maintenance 

sites in the 12km Eastern modeling domain. 

2. Contributions for each of the PM2.5 species from each State, as predicted by PSAT, are 

subtracted from the standard 2012 base case CAMx model output to generate a new set of 

model output files for each source region. 

3. Daily, 24-hr average PM2.5 species are calculated for the “standard” model output files 

and newly generated source contribution output files. 

4. The relative response factors (RRFs) for each of the PM2.5 species is calculated for 

each source region at all receptors using the MATS model attainment software. In this 

approach, the MATS “baseline” model file is defined as the standard 2012 base case 

CAMx model output file and the “future case” model file is defined as the 2012 State 

contribution model output file (from step 3). 

5. The species-specific annual average RRFs (generated by MATS in step 4) for each 

source State are multiplied by the annual average future year (2012) species 

concentrations generated for the 2012 base case to estimate PM2.5 species contributions in 

ug/m3 from each species for each source region33,34. 

 

33 The calculations in step 5 use MATS outputs and additional post-processing software 

developed for this rule. More details on the post-processing steps and software can be found in 

Appendix C. 

34 Due to precision issues in MATS it is possible to have RRFs for ammonium and water that are 

slightly greater than 1 which can result in very small negative values in the calculation of 

contributions of sulfate. Any negative contribution values were reset to zero. 
32

6. The annual average contributions of sulfate ion, nitrate ion, ammonium, and water for 

each source State are combined to calculate the nitrate plus sulfate PM2.5 contribution 

used in the TR analysis35. 

7. Annual PM2.5 (i.e., nitrate plus sulfate) contributions are expressed in units of μg/m3. 

Values of annual PM2.5 contribution are truncated after two places to the right of the 

decimal (e.g. a contribution of 0.149 μg/m3

 is truncated to 0.14 μg/m3). 

The 24-hour PM2.5 contributions were calculated in a manner similar to the 

procedures for annual PM2.5. However, there are several more steps in the 24-hour 

calculations which are designed to retain the contributions in each quarter through most 

of the post-processing. For 24-hour PM2.5, the contributions are calculated as the five 

year average contributions to the “high” concentration quarters at each site. 

The following is a description of the procedures for calculating contributions for 

24-hour PM2.5. These procedures were applied separately for each source State. 

1. Receptor sites include the 2012 base case 24-hour PM2.5 nonattainment and 

maintenance sites in the 12km photochemical modeling domain. 

2. Contributions for each of the PM2.5 species from each State, as predicted by PSAT, are 

subtracted from the standard 2012 CAMx model output to generate a new set of model 

output files for each source region. 

3. Daily, 24-hr average PM2.5 species model output files are generated for the “standard” 

2012 base case model output files and newly generated source contribution output files. 

 

35 Particulate ammonium and particle bound water are attached to the nitrate and sulfate. 

Therefore, they are counted as part of the downwind contribution of total sulfate and total nitrate. 

As in the design value calculations in section III, the ammonium contribution is calculated based 

on the calculated sulfate and nitrate concentrations, using a constant value for the degree of 

neutralization of sulfate (from the ambient data). The particle bound water contribution 

concentration is calculated from the empirical formula contained in MATS. The following 

equations were used to calculate ammonium nitrate and ammonium sulfate: 

Ammonium nitrate = (1.29 x 1.12 x nitrate ion); where the 1.29 factor represents the ammonium 

associated with nitrate ion (assuming that nitrate exists as ammonium nitrate) and the 1.12 factor 

is applied to subtract out the particle bound water attached to the ammonium nitrate. 

Ammonium sulfate = ((ammonium ion + sulfate ion) – (0.29 x nitrate ion) + (particle bound water 

– (0.12 * 1.29* nitrate ion))); where the 0.29 and 1.29 factors are included to subtract out the 

ammonium associated with nitrate ion (assuming that nitrate exists as ammonium nitrate) and the 

1.12 factor is applied to subtract out the particle bound water attached to the ammonium nitrate. 

The remaining ammonium and water is added to the sulfate ion and is assumed to be attached to 

sulfate. 
33

4. Relative response factors (RRFs) are calculated for each of the PM2.5 species36 for each 

source State at all receptors using the MATS model attainment software. Quarterly RRFs 

are calculated using the “high” concentration model days in each quarter. The high 

concentration days are based on the highest 10% of modeled PM2.5 days37 (in each grid 

cell) in the 2012 base case. The MATS “baseline” model file is defined as the standard 

2012 base case CAMx model output file and the “future case” model file is defined as the 

2012 State contribution region model output file (from step 3). 

5. The species “high days” quarterly average RRFs (generated by MATS in step 4) for 

each source region are multiplied38 by the high days quarterly average future year (2012) 

species concentrations from the 24-hr PM2.5 2012 base case. This calculation is done for 

(up to) 5 years of data for each quarter (for a total of up to 20 quarters). The result of this 

calculation is the contribution of each of the species from the upwind source to each of 

the 20 quarters. 

6. For each receptor, the contributions during the high future year quarters for each year 

are identified and selected for use in the analysis. The high quarter for each year (based 

on the 2012 base case) is already known from the 2012 base case 24-hr PM2.5 design 

value calculations. The contributions of each species for the (up to) 5 high quarters are 

averaged39 together. This represents the species contributions to 24-hour PM2.5 

concentrations. 

 

36 As in the design value calculations in section III, the ammonium contribution is calculated 

based on the calculated sulfate and nitrate contribution concentrations, using a constant value for 

the degree of neutralization of sulfate (from the ambient data). The particle bound water 

contribution concentration is calculated from the empirical formula contained in MATS. 

37 Due to large over-predictions of crustal PM (other primary PM2.5), the modeled PM2.5 

concentrations used to determine the high modeled days in each quarter do not include crustal 

PM2.5. We did not want the crustal PM2.5 to unduly influence the selection of the high modeled 

days. The model performance for crustal PM2.5 and all other PM2.5 components is documented 

in Appendix A. 

38 The calculations in steps 5 and 6 use MATS outputs and post-processing software written for 

this rule. More details on the post-processing steps and software can be found in Appendix C. 

39 For the 24-hr PM2.5 NAAQs contribution calculations, the five year average contributions are 

not weighted towards the middle year of the period. Since the high quarter for each year can be 

in a different season, EPA did not want to weight the upwind contribution to a particular season. 

Upwind states should not be penalized for having a large contribution in the high season for 2005, 

compared to other years. Likewise, upwind states should not be rewarded for having a small 

contribution to 2005 compared to other years 
34

7. The 24-hour contributions of sulfate ion, nitrate ion, ammonium, and water40 for each 

source State are combined to calculate the total PM2.5 contribution used in the TR 

analysis, as in the calculations for annual PM2.5 , described above.. 

8. 24-hour PM2.5 contributions are expressed in units of μg/m3. Values of 24-hour PM2.5

contribution are truncated after two places to the right of the decimal (e.g. a contribution 

of 0.349 μg/m3

 is truncated to 0.34 μg/m3). 

D. Approach to Calculating Contributions for 8-Hour Ozone 

We used the CAMx Anthropogenic Precursor Culpability Assessment (APCA) 

source apportionment technique to calculate the contributions to 8-hour ozone 

nonattainment and maintenance in the 2012 base case. APCA tracks the formation of 

ozone from NOX and VOC emissions. Through emissions pre-processing procedures, we 

tagged all of the anthropogenic NOX and VOC emissions in each State wholly within the 

Eastern modeling domain. A separate tag was created for each State, and the tagged 

emissions followed state boundaries. 

All anthropogenic sources of NOX and VOC were tracked in the APCA 

simulation. Several post-processing steps were developed to transform the raw model 

outputs to ozone contributions. The approach for calculating ozone contributions was 

similar to the approach used for PM2.5, except that the APCA model outputs were 

processed using MATS instead of the PSAT outputs used for PM2.5.

The following is a description of the procedures for calculating contributions for 

8-hour ozone. These procedures were applied separately for each source State. 

1. Receptor sites include the 2012 base case ozone nonattainment and maintenance sites 

in the 12km photochemical modeling domain. 

2. Contributions from each source State are subtracted from the standard 2012 CAMx 

model output to generate a new set of model output files for each State. 

3. Daily 8-hr maximum ozone model output files are generated from hourly ozone 

predictions in the “standard” model output files and newly generated source contribution 

output files. 

4. Relative response factors (RRFs) are calculated for each source State for all receptors 

using MATS. The “baseline” ozone values in this calculation are the 2012 base case 8-

 

40 Particulate ammonium and particle bound water are attached to the nitrate and sulfate. 

Therefore, they are counted as part of the downwind contribution of total sulfate and total nitrate. 
35

hour daily maximum concentrations and the “future case” ozone values are the 8-hour 

daily maximum concentrations in the 2012 source State file created in step 3. 

5. The model attainment test is applied with MATS using an initial ozone criterion of 85 

ppb and a minimum allowable criterion of 70 ppb. A minimum number of 5 days at or 

above the 85 ppb criterion or 5 days of modeled ozone greater than the minimum 

allowable criterion (70 ppb) are required41 for a relative response factor to be estimated at 

a receptor site. For sites at which there are not 5 modeled days with predicted 8-hour 

daily maximum concentrations above the initial ozone criterion, the criterion is decreased 

by 1 ppb until 5 days are included in the RRF calculation until the minimum threshold 

(70 ppb) is reached. If there are less than 5 modeled days above 70 ppb, then a 

contribution to the receptor is not calculated and the receptor is not used in the 

contribution analysis. 

 6. The relative response factor (from step 4) is multiplied by the 2012 base case design 

value to estimate ozone contribution in ppb from the source State42. 

7. Ozone contributions are expressed in units of ppb. Ozone contribution values are 

truncated after 1 place to the right of the decimal (e.g. a contribution of 0.79 ppb is 

truncated to 0.7 ppb). 

E. Evaluation of Interstate Contributions 

The previous section describes the procedures for calculating 8-hour ozone and 

annual and 24-hour PM2.5 contributions to the nonattainment and maintenance receptor 

sites43. The contributions to each 2012 nonattainment receptor and each maintenance 

receptor are provided in Appendix D44. For annual PM2.5 we calculated each State’s 

contribution to each of the 32 monitoring sites that are projected to be nonattainment and 

 

41 The contribution analysis uses a minimum number of days above the threshold of 5 days. This 

differs from the default attainment test minimum number of 10 days > 85 ppb. It was reasoned 

that the contribution should be averaged over multiple days, but requiring a minimum of 10 days 

was not necessary. Since the attainment test uses an absolute minimum of 5 days in order to 

perform an RRF calculation, we chose to use 5 days as the default minimum number of days 

needed for each contribution calculation. 

42 The calculation in step 6 uses MATS outputs and post-processing software written for this rule. 

More details on the post-processing steps and software can be found in Appendix C. 

43 As noted previously, the nonattainment receptors are those monitoring sites which are projected 

to exceed the NAAQS in the 2012 base case, based on the 5-year weighted average design values. 

The maintenance receptors are those monitoring sites which are projected to exceed the NAAQS 

in the 2012 base case based on projections of the maximum design value in the 5-year period. 

Monitoring sites with average design values at or below the level of the NAAQS, but with 

maximum design values exceeding the NAAQS are referred to as maintenance only receptors. 

44 The contributions to all monitoring sites in the 12 km Eastern modeling domain are provided in 

the TR docket. 
36

each of the 16 sites that are projected to have maintenance problems for the annual PM2.5

NAAQS in the 2012 base case. For 24-hour PM2.5, we calculated each state’s 

contribution to each of the 92 monitoring sites that are projected to be nonattainment and 

each of the 38 sites that are projected to have maintenance problems for the 24-hour 

PM2.5 NAAQS in the 2012 base case. Similarly, for ozone we calculated each state’s 

contribution to each of the 11 monitoring sites that are projected to be nonattainment and 

each of 1445 sites that are projected to have maintenance problems for the 8-hour ozone 

NAAQS in the 2012 Base Case. 

The upwind State-to-downwind receptor combinations (i.e., linkages) were 

evaluated to determine if the contributions to downwind nonattainment and/or 

maintenance are at or above specific contribution thresholds. As described in section 

IV.B of the TR preamble, EPA is using 1 percent of the NAAQS as the threshold for 

determining which States to include in this rule. The thresholds for the 1997 annual 

PM2.5 NAAQS, 2006 24-hour PM2.5 NAAQS, and 1997 8-hour ozone NAAQS are shown 

in Table IV-7. 

Table IV-7. Threshold concentrations used for evaluating interstate contributions to 

annual and 24-hour PM2.5 and 8-hour ozone. 

Pollutant Level of the NAAQS 1 Percent Threshold 

 

Annual PM2.5 15.0 μg/m3 0.15 μg/m3

 

24-Hour PM2.5 35 μg/m3

 0.35 μg/m3

 

8-Hour Ozone 0.08 ppm 0.0008 ppm (0.8 ppb) 

To determine which States contribute amounts at or above these thresholds to 

nonattainment and/or maintenance, we examined the amount of contribution from each 

State to each downwind nonattainment receptor and each maintenance only receptor for 

the three NAAQS and noted the magnitude of the contribution relative to the threshold. 

States that contribute amounts at or above the threshold to at least one downwind 

nonattainment receptor or one maintenance receptor for the annual PM2.5 NAAQS or the 

24-hour PM2.5 NAAQS are included in the TR for annual SO2 and NOX emissions 

 

45 For two of the 16 projected maintenance sites (Harris Co., Texas sites 482011015 and 

482011035) there were less than 5 days with 8-hour ozone predictions of at least 70 ppb. Thus, 

based on recommendations in the modeling guidance we did not calculate contributions for these 

two maintenance sites. 
37

budgets. States that contribute amounts that are at or above the threshold to at least one 

8-hour ozone downwind nonattainment or maintenance receptor are included in the TR 

for summer season NOX emissions budgets. 

1. Contributions to Annual PM2.5 Nonattainment and Maintenance 

 The largest contribution from each State to annual PM2.5 across all downwind 

nonattainment receptors is provided in Table IV-8. The largest contribution from each 

State to annual PM2.5 across all downwind maintenance-only receptors is also provided in 

Table IV-8. 

Table IV-8. Largest contribution to downwind annual PM2.5 (μg/m3) nonattainment and 

maintenance for each of 37 States. 

 

Upwind State 

Largest Downwind 

Contribution to 

Nonattainment for 

Annual PM2.5 (μg/m3

) 

Largest Downwind 

Contribution to 

Maintenance for 

Annual PM2.5 (μg/m3) 

Alabama 0.46 0.18 

Arkansas 0.09 0.04 

Connecticut 0.04 0.09 

Delaware 0.20 0.14 

Florida 0.29 0.07 

Georgia 0.63 0.18 

Illinois 1.01 0.63 

Indiana 2.09 1.78 

Iowa 0.31 0.30 

Kansas 0.09 0.05 

Kentucky 1.68 1.01 

Louisiana 0.11 0.34 

Maine 0.01 0.02 

Maryland/ 

Washington, D.C. 0.63 0.56 

Massachusetts 0.07 0.13 

Michigan 0.72 0.71 

Minnesota 0.19 0.17 

Mississippi 0.07 0.03 

Missouri 1.38 0.27 

Nebraska 0.08 0.06 

New Hampshire 0.01 0.02 

New Jersey 0.34 0.68 

New York 0.49 0.47 

North Carolina 0.19 0.11 

North Dakota 0.05 0.05 

Ohio 1.49 2.03 

Oklahoma 0.08 0.05 

Pennsylvania 0.83 1.60 

Rhode Island 0.01 0.01 

South Carolina 0.26 0.04 

South Dakota 0.02 0.02 
38

Upwind State 

Largest Downwind 

Contribution to 

Nonattainment for 

Annual PM2.5 (μg/m3

) 

Largest Downwind 

Contribution to 

Maintenance for 

Annual PM2.5 (μg/m3) 

Tennessee 0.68 0.64 

Texas 0.13 0.06 

Vermont 0.00 0.00 

Virginia 0.36 0.37 

West Virginia 0.98 1.17 

Wisconsin 0.46 0.42 

 Based on the State-by-State contribution analysis, there are 22 States (and the 

District of Columbia) which contribute 0.15 μg/m3 or more to downwind annual PM2.5

nonattainment. These states are: Alabama, the District of Columbia, Delaware, Florida, 

Georgia, Illinois, Indiana, Iowa, Kentucky, Maryland, Michigan, Minnesota, Missouri, 

New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, 

Virginia, West Virginia, and Wisconsin. A list of the downwind nonattainment sites to 

which each upwind State contributes 0.15 μg/m3 or more (i.e., the upwind State-todownwind nonattainment “linkages”) are provided in Appendix E. 

 There are 19 States (and the District of Columbia) which contribute 0.15 μg/m3 

or more to downwind annual PM2.5 maintenance. These states are: Alabama, the District 

of Columbia, Georgia, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maryland, Michigan, 

Minnesota, Missouri, New Jersey, New York, Ohio, Pennsylvania, Tennessee, Virginia, 

West Virginia, and Wisconsin. A list of the downwind maintenance sites to which each 

upwind State contributes 0.15 μg/m3 or more (i.e., the upwind State-to-downwind 

maintenance “linkages”) are provided in Appendix E. 

2. Contributions to 24-Hour PM2.5 Nonattainment and Maintenance 

The largest contribution from each State to 24-hour PM2.5 across all downwind 

nonattainment receptors is provided in Table IV-9. The largest contribution from each 

State to 24-hour PM2.5 across all downwind maintenance-only receptors is also provided 

in Table IV-9. 
39

Table IV-9. Largest contribution to downwind 24-hour PM2.5 (μg/m3

) nonattainment and 

maintenance for each of 37 States. 

Upwind State 

Largest Downwind 

Contribution to Nonattainment 

for 24-Hour PM2.5 (ug/m3

) 

Largest Downwind Contribution 

to Maintenance 

for 24-Hour PM2.5 (ug/m3) 

Alabama 0.48 0.32 

Arkansas 0.20 0.17 

Connecticut 0.41 0.70 

Delaware 0.50 0.36 

Florida 0.08 0.08 

Georgia 0.95 0.41 

Illinois 7.28 6.57 

Indiana 9.91 8.94 

Iowa 1.87 1.67 

Kansas 0.77 0.45 

Kentucky 6.53 6.91 

Louisiana 0.23 0.18 

Maine 0.19 0.19 

Maryland/ 

Washington, D.C. 2.63 1.82 

Massachusetts 0.67 0.71 

Michigan 2.35 3.35 

Minnesota 0.91 0.86 

Mississippi 0.09 0.04 

Missouri 5.03 4.82 

Nebraska 0.62 0.39 

New Hampshire 0.21 0.23 

New Jersey 2.69 4.74 

New York 5.82 1.17 

North Carolina 0.50 0.45 

North Dakota 0.27 0.15 

Ohio 5.84 5.56 

Oklahoma 0.16 0.21 

Pennsylvania 3.67 4.86 

Rhode Island 0.05 0.06 

South Carolina 0.19 0.19 

South Dakota 0.13 0.09 

Tennessee 3.92 4.70 

Texas 0.21 0.28 

Vermont 0.06 0.07 

Virginia 1.32 2.26 

West Virginia 3.51 4.83 

Wisconsin 0.80 1.01 

 Based on the State-by-State contribution analysis, there are 24 States (and the 

District of Columbia) which contribute 0.35 μg/m3 or more to downwind 24-hour PM2.5

nonattainment. These States are: Alabama, the District of Columbia, Connecticut, 
40

Delaware, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Maryland, Massachusetts, 

Michigan, Minnesota, Missouri, Nebraska, New Jersey, New York, North Carolina, Ohio, 

Pennsylvania, Tennessee, Virginia, West Virginia, and Wisconsin. A list of the 

downwind nonattainment counties to which each upwind State contributes 0.35 μg/m3 or 

more (i.e., the upwind State-to-downwind nonattainment “linkages”) are provided in 

Appendix E. 

 There are 23 states and the District of Columbia which contribute (individually) 

0.35 μg/m3 or more to downwind 24-hour PM2.5 maintenance. These states are: 

Connecticut, Delaware, the District of Columbia, Georgia, Illinois, Indiana, Iowa, 

Kansas, Kentucky, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nebraska, 

New Jersey, New York, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, West 

Virginia, and Wisconsin. A list of the downwind maintenance sites to which each 

upwind State contributes 0.35 μg/m3 or more (i.e., the upwind State-to-downwind 

maintenance “linkages”) are provided in Appendix E. 

3. Contributions to 8-Hour Ozone Nonattainment and Maintenance 

The largest contribution from each State to 8-hour ozone across all downwind 

nonattainment receptors is provided in Table IV-10. The largest contribution from each 

State to 8-hour ozone across all downwind maintenance-only receptors is also provided in 

Table IV-10. 

Table IV-10. Largest contribution to downwind 8-hour ozone nonattainment and 

maintenance for each of 37 States. 

Upwind State 

Largest Downwind 

Contribution to 

Nonattainment for 

Ozone (ppb) 

Largest Downwind 

Contribution to 

Maintenance for 

Ozone (ppb) 

Alabama 4.7 4.7 

Arkansas 1.4 1.8 

Connecticut 1.7 1.6 

Delaware 3.3 2.5 

Florida 0.8 2.1 

Georgia 2.1 1.7 

Illinois 0.8 0.6 

Indiana 1.1 1.0 

Iowa 0.3 0.3 

Kansas 0.6 0.8 

Kentucky 2.3 1.8 

Louisiana 11.4 10.6 

Maine 0.0 0.0 

Maryland/Washington,DC 6.1 4.2 

Massachusetts 0.6 0.5 
41

Upwind State 

Largest Downwind 

Contribution to 

Nonattainment for 

Ozone (ppb) 

Largest Downwind 

Contribution to 

Maintenance for 

Ozone (ppb) 

Michigan 0.9 0.5 

Minnesota 0.1 0.2 

Mississippi 5.2 2.5 

Missouri 0.7 0.6 

Nebraska 0.2 0.2 

New Hampshire 0.1 0.1 

New Jersey 16.8 15.8 

New York 0.4 22.7 

North Carolina 1.7 2.0 

North Dakota 0.1 0.0 

Ohio 2.8 2.6 

Oklahoma 2.1 2.7 

Pennsylvania 8.9 8.1 

Rhode Island 0.1 0.1 

South Carolina 0.6 0.8 

South Dakota 0.0 0.0 

Tennessee 1.6 3.0 

Texas 1.6 0.6 

Vermont 0.0 0.1 

Virginia 4.2 4.5 

West Virginia 2.7 2.3 

Wisconsin 0.3 0.2 

Based on the State-by-State contribution analysis, there are 22 States (and the 

District of Columbia) which contribute 0.8 ppb or more to downwind 8-hour ozone 

nonattainment. These States are: Alabama, Arkansas, Connecticut, Delaware, the 

District of Columbia, Florida, Georgia, Illinois, Indiana, Kentucky, Louisiana, Maryland, 

Michigan, Mississippi, New Jersey, North Carolina, Ohio, Oklahoma, Pennsylvania, 

Tennessee, Texas, Virginia, and West Virginia. A list of the downwind nonattainment 

counties to which each upwind State contributes 0.8 ppb or more (i.e., the upwind Stateto-downwind nonattainment “linkages”) is provided in Appendix E. 

There are 22 States and the District of Columbia which contribute 0.8 ppb or 

more to downwind 8-hour ozone maintenance. These States are: Alabama, Arkansas, 

Connecticut, Delaware, the District of Columbia, Florida, Georgia, Indiana, Kansas, 

Kentucky, Louisiana, Maryland, Mississippi, New Jersey, New York, North Carolina, 

Ohio, Oklahoma, Pennsylvania, South Carolina, Tennessee, Virginia, and West Virginia. 

A list of the downwind nonattainment counties to which each upwind State contributes 

0.8 ppb or more (i.e., the upwind State-to-downwind nonattainment “linkages”) is 

provided in Appendix E. 
42

V. Air Quality Impacts of the Proposed SO2 and NOX Emissions 

Reductions

In this section we present the air quality impacts of the SO2 and NOX emissions 

reductions in the 2014 remedy scenario in comparison to air quality predicted for the 

2012 base case and 2014 base case scenarios46. We first describe the magnitude and 

spatial patterns in emissions reductions (and increases) in the East. Then we quantify the 

impacts of these emissions changes on projected design value concentrations for annual 

PM2.5, 24-hour PM2.5, and 8-hour ozone at monitoring sites in the Eastern modeling 

domain47. We also provide the impacts on visibility for the 20 percent worst days in 

Class I Areas in the East. 

A. Characterization of Emissions in 2014 for the Proposed Remedy Scenario 

The approach for developing the 2014 remedy scenario is described in section 

IV.D of the TR preamble. The methods for projecting emissions for the 2012 and 2014 

base case scenarios, including the baseline control programs, are presented in the 

EITSD48. The 27 States and Washington, D.C. that are included in the TR for annual SO2

and NOX emissions controls to reduce interstate contributions of PM2.5 are shown on the 

map in Figure V-1. These States are divided into two groups with different levels of SO2

emissions reductions. The States in Group 1 have deeper reductions than those in Group 

249. The 25 States (plus Washington, D.C.) subject to summer season (May through 

September) NOX controls to reduce interstate transport of ozone are shown on the map in 

Figure V-2. The aggregate emissions of annual SO2, annual NOX, and summer NOX for 

the States covered by the TR are provided in Appendix F for the 2014 base case and 

remedy scenarios. 

 

46 Note that the comparisons between the 2012 base case and the 2014 remedy scenario include 

the impacts of emissions reductions from other rules and control programs that are projected to 

come into effect between 2012 and 2014, in addition to the impacts of the emissions reductions in 

the TR proposal. The comparison between the 2014 base case and the 2014 remedy reflects the 

SO2 and NOx emissions reductions in the TR proposal, only. 

47 This analysis does not include projections for monitoring sites that do not meet certain 

completeness criteria or other projection criteria, as described in section III of this TSD. 

48 State/sector/pollutant emissions summaries for all of the scenarios simulated with CAMx can 

be found in the EITSD. 

49 See section IV.D of the TR preamble for details on the SO2 emissions reduction requirements 

for Group 1 and Group 2 States. 
43

Figure V-1. States included in the Transport Rule for annual SO2 and NOX emission 

reductions. 

Figure V-2. States included in the Transport Rule for summer NOX emission reductions. 

For the Group 1 States as a whole, annual SO2 emissions from electric generating 

units (EGUs) are projected to be 68 percent lower in 2014 with the TR controls compared 

to those in the 2014 base case. The reduction in EGU emissions yields a net 53 percent 

reduction in total SO2 for the Group 1 States. Overall, for both Group 1 and Group 2 
44

States, total SO2 emissions across all source categories are 45 percent lower in the 2014 

remedy scenario, compared to the 2014 base case. 

The difference in annual total SO2 emissions between the 2014 base and remedy 

scenarios at individual facilities is shown in Figure V-3. This figure reveals that 

substantial SO2 emissions reductions will occur at facilities in the States covered by the 

TR with the largest reductions in portions of the Midwest, Tennessee Valley, and Ohio 

Valley extending across Pennsylvania. Some increases in SO2 emissions are noted in a 

few States not included in the TR for annual SO2 reductions, most notably at several 

facilities in Arkansas, Texas, and Colorado. 

Figure V-3. Change in annual EGU SO2 emissions between the 2014 base and control 

scenarios at individual facilities. 

Annual emissions of NOX from EGUs are lower by 36 percent in the remedy 

scenario compared to the 2014 base case for the 27 States and Washington, D.C. that are 

included in the TR for annual NOX emissions reductions. The reduction in EGU NOX

produces an 8 percent net reduction in total NOX for these States. For the 25 States and 

Washington, D.C. included for ozone season NOX controls, summer EGU NOX emission 

are 16 percent lower in the 2014 remedy scenario, compared to the 2014 base case. 
45

The changes in winter and summer NOX emissions between the 2014 remedy and 

2014 base case at individual facilities are presented in Figures V-4 and V-5, respectively. 

As is evident from Figure V-4, the largest reductions in winter NOX are at facilities 

located in the area extending from Florida to Louisiana northward to Minnesota and 

Wisconsin and across Tennessee to States along the Ohio River, then eastward to 

Pennsylvania and New Jersey. Increases in EGU NOX emissions are seen in locations 

scattered across the East. Comparing Figures V-4 and V-5 indicates that the there is a 

different pattern in NOX emissions reductions between the summer and the winter. In the 

winter, many states in the East have sizable NOX reductions. But in the summer, most of 

the NOX reductions occur outside of the NOX SIP call states. This is due to the fact that 

the NOX reductions from the SIP call are included as part of the future base case and 

remedy scenarios. 

Figure V- 4. Change in winter season EGU NOX emissions between the 2014 base and 

control scenarios at individual facilities. 
46

Figure V-5. Change in summer season EGU NOX emissions between the 2014 base and 

control scenarios at individual facilities. 

B. Impacts on Projected PM2.5 Design Value Concentrations 

The projected annual and 24-hour PM2.5 design values for the 2014 base case and 

2014 remedy scenario are provided in Appendix B. The impacts of the annual SO2 and 

NOX emissions reductions on annual and 24-hour PM2.5 design values are also provided 

in Appendix B. The impacts on annual and 24-hour PM2.5 design values for each 

monitored county are shown in Figures V-6 and V-7, respectively50,51. The results, as 

shown in these figures indicate that the emissions reductions from the TR will 

substantially lower annual and 24-hour PM2.5 concentrations at most locations in the 

Eastern U.S, compared to the 2014 base case. Annual PM2.5 is lower by more than 2 

ug/m3

 in areas of the East extending from Tennessee northward to Indiana and Ohio, and 

 

50 These maps, which show the difference between the 2014 remedy scenario and the 2014 base 

case, are based upon 5-year weighted average design values. Additional maps showing average 

design value concentrations for 2003-2007, the 2012 and 2014 base cases, and the 2014 remedy 

scenario for annual and 24-hour PM2.5 are provided in Appendix G. Maps showing the predicted 

change in annual and 24-hour PM2.5 between the 2014 remedy and the 2012 base case are also 

provided in Appendix G. 

51 For counties with multiple monitoring sites, the maps show the largest difference from among 

the sites in a county. 
47

eastward across Pennsylvania. Along the highly populated Northeast Corridor, across the 

Southeast and in the upper Midwest, including the cities of Atlanta, Birmingham, St. 

Louis, Chicago, and Detroit annual PM2.5 concentrations are lower by 1 to 2 ug/m3. 

As shown in Figure V-7, the predicted reductions in 24-hour PM2.5 are greater 

than those for annual PM2.5 concentrations. Daily PM2.5 concentrations in the remedy 

scenario are lower than in the 2014 base case by 2 to 6 ug/m3 across much of the 

Southeast and along portions of the Northeast Corridor. In the multi-State area from 

Tennessee to western Pennsylvania, our modeling predicts 24-hour PM2.5 concentrations 

that are 6 to 10 ug/m3 lower than those in the 2014 base case. 

Figure V-6. Impacts on annual average PM2.5 concentrations in 2014 resulting from the 

emissions reductions in the 2014 remedy scenario. 
48

Figure V-7. Impacts on 24-hour PM2.5 concentrations in 2014 resulting from the 

emissions reductions in the 2014 remedy scenario. 

The spatial patterns of the magnitude of reduction in annual and 24-hour PM2.5

across the East are generally consistent with the patterns in annual SO2 and winter NOX

emissions reductions from EGUs, as evident by comparing Figures V-6 and V-7 to 

Figures V-3 and V-4, respectively. These figures also indicate that PM2.5 concentrations 

are lower in the remedy scenario in those States in the East not included in the TR for 

annual SO2 and NOX reductions, like Arkansas, Mississippi, Oklahoma, Texas and 

several northern New England. In Texas and Arkansas, the reductions in transported 

PM2.5 are large enough to more than offset the forecasted increases in local emissions of 

SO2 in these two States. 

There are a few locations mainly in the West where SO2 emissions and, therefore, 

PM2.5 is predicted to be higher in the 2014 remedy scenario compared to the 2014 base 

case. Locations where PM2.5 levels are higher in the remedy scenario are evident in 

counties near Denver, CO. 
49

C. Impacts on Annual and 24-Hour PM2.5 Nonattainment and Maintenance 

The number of projected nonattainment and/or maintenance sites in the East for 

the 2003-2007 base period, 2012 base case, 2014 base case, and 2014 remedy scenario 

for annual PM2.5 and 24-hour PM2.5 are provided in Table V-1. The percent difference in 

the number of nonattainment and maintenance sites between the 2014 remedy scenario 

and both the 2012 and 2014 base case scenarios are also provided in this table. The 

average and peak reductions in annual PM2.5 and 24-hour PM2.5 concentrations for those 

sites with 2012 nonattainment and/or maintenance problems are provided in Table V-2. 

The annual PM2.5 nonattainment and/or maintenance sites in the East for the 2014 base 

case and 2014 remedy scenario are shown in Figures V-8 and V-9, respectively. Similar 

maps are provided in Figures V-10 and V-11 for 24-hour PM2.5. 

 

Table V-1. Percent reduction in annual and 24-hour PM2.5 nonattainment and/or 

maintenance in the Eastern U.S. 

Number of Nonattainment and Maintenance 

Sites 

Percent Reduction in 

Nonattainment/Maintenance 

Sites 

 

Ambient 

(2003-2007) 

 2012 

Base Case 

2014 

Base Case 

2014 

Remedy 

2012 Base vs 

2014 Remedy 

2014 Base vs 

2014 Remedy 

Annual PM2.5

Nonattainment Sitesa 102 32 15 1 97% 93% 

Annual PM2.5

Maintenance-Only 

Sites 21 16 7 1 94% 86% 

 

Daily PM2.5

Nonattainment Sites 151 92 54 17 82% 69% 

Daily PM2.5

Maintenance-Only 

Sites 48 38 28 11 71% 61% a

 As indicated in section III, the term “nonattainment” is used to denote sites that are projected to 

have both nonattainment and maintenance problems. 
50

Table V-2. Average and peak reductions in annual PM2.5 and 24-hour PM2.5 for the 2012 

base case nonattainment and/or maintenance sites. 

2014 Remedy vs 

2012 Base Case 

2014 Remedy vs 

2014 Base Case 

 Average 

Reduction 

Peak 

Reduction 

Average 

Reduction 

Peak 

Reduction 

Annual PM2.5

Nonattainment Sites 2.8 μg/m3 3.9 μg/m3 2.3 μg/m3 3.3 μg/m3 

Annual PM2.5

Maintenance-Only Sites 2.8 μg/m3 4.2 μg/m3 2.3 μg/m3 3.6 μg/m3 

 

24-Hour PM2.5

Nonattainment Sites 5.8 μg/m3 15.3 μg/m3 4.5 μg/m3 13.8 μg/m3 

24-Hour PM2.5

Maintenance-Only Sites 5.5 μg/m3 15.3 μg/m3 4.2 μg/m3 13.8 μg/m3 

The information in Table V-1 shows that the extent of nonattainment and 

maintenance problems for annual PM2.5 and 24-hour PM2.5 is significantly lower in the 

2014 remedy scenario compared to both the 2012 base case and the 2014 base case. All 

but 1 site52 is projected to be in attainment and only 1 site53 is projected to have a 

maintenance problem for annual PM2.5 with the emissions reductions expected from the 

remedy by 2014. Annual PM2.5 concentrations are, on average, more than 2 μg/m3 lower 

across the 32 sites that were nonattainment in the 2012 base case. The impacts on annual 

PM2.5 at maintenance-only sites are comparable to those at the nonattainment sites. 

For 24-hour PM2.5, there are significantly fewer nonattainment and/or 

maintenance sites in the 2014 remedy scenario compared to both the 2012 and 2014 base 

cases. For example, in the 2014 remedy scenario the number of nonattainment sites is 69 

percent less than in the 2014 base case. The average reduction in 24-hour PM2.5 across 

the 92 2012 nonattainment sites is 5.8 μg/m3 and the peak reduction at an individual 

nonattainment site is 15.3 μg/m3. Comparable reductions are projected at 24-hour PM2.5

maintenance-only sites. 

 

52 Allegheny Co., PA site 420030064. 

53 Jefferson Co., AL site 010730023. 
51

Figure V-8. Projected annual PM2.5 nonattainment and/or maintenance sites in the East 

for the 2014 base case. 

Figure V-9. Projected annual PM2.5 nonattainment and/or maintenance sites in the East 

for the 2014 remedy scenario. 
52

Figure V-10. Projected 24-hour PM2.5 nonattainment and/or maintenance sites in the East 

for the 2014 base case. 

Figure V-11. Projected 24-hour PM2.5 nonattainment and/or maintenance sites in the East 

for the 2014 remedy scenario. 
53

D. Analysis of Residual Nonattainment for 24-Hour PM2.5

As indicated in Table V-1, there are 28 sites that are predicted to have 

nonattainment and/or maintenance problems for the 24-hour the PM2.5 standard in the 

2014 remedy scenario. The average and maximum 24-hour PM2.5 design values at these 

28 sites are provided in Table V-3. Although these sites are predicted to have 

nonattainment/maintenance problems, the emissions reductions in the TR will result in 

considerable progress toward attainment and maintenance at these 28 sites. On average, 

the predicted amount of PM2.5 reduction at these sites is more than half of what is needed 

for the sites to attain and/or maintain the 24-hour standard. 

Table V-3. Average and maximum 24-hour PM2.5 design values (μg/m3

) for projected 

nonattainment and/or maintenance sites in the 2014 remedy scenario. 

Urban Area County 

Monitoring 

Site ID 

2014 Remedy 

Scenario 

Average 

Design Valuea

 

2014 Remedy 

Scenario 

Maximum Design 

Valueb

Ann Arbor, MI Washtenaw Co 261610008 35.6 36.2 

Anne Arundel Co 240031003 32.9 36.1 Baltimore, MD 

Baltimore City 245100040 35.0 36.8 

Birmingham, AL Jefferson Co 10730023 35.6 36.8 

Cook Co 170310052 36.6 37.4 

Cook Co 170311016 37.7 41.2 

Cook Co 170313103 35.9 36.5 

Cook Co 170313301 34.9 37.3 

Chicago, IL 

Cook Co 170316005 35.6 38.2 

Cuyahoga Co 390350038 35.7 38.2 Cleveland, OH 

Cuyahoga Co 390350060 36.3 38.0 

Oakland Co 261250001 35.1 36.2 

Wayne Co 261630016 38.2 40.8 

Wayne Co 261630019 37.0 37.5 

Wayne Co 261630033 39.1 39.4 

Detroit, MI 

Wayne Co 261630036 34.4 35.5 

E. St. Louis, MO Madison Co 171191007 34.3 37.0 

Lake Co 180890022 35.3 39.8 Gary, IN Lake Co 180890026 32.7 35.8 

Jersey City, NJ Hudson Co 340172002 36.6 36.6 

Lancaster, PA Lancaster Co 420710007 36.0 38.2 

Milwaukee Co 550790010 36.3 37.5 

Milwaukee Co 550790026 34.4 38.3 

Milwaukee Co 550790043 36.3 37.7 

Milwaukee, WI 

Milwaukee Co 550790099 33.3 35.9 
54

Urban Area County 

Monitoring 

Site ID 

2014 Remedy 

Scenario 

Average 

Design Valuea

 

2014 Remedy 

Scenario 

Maximum Design 

Valueb

New York City, NY New York Co 360610056 35.3 36.0 

Pittsburgh, PA Allegheny Co 420030064 55.8 58.9 

Steubenville, OH Brooke Co, WV 540090011 36.4 37.1 a

 Sites with average projected design values >= 35.5 μg/m3 are projected to be nonattainment. 

b

 Sites with maximum projected design values >= 35.5 μg/m3 and average design values <35.5 

μg/m3 are projected to be maintenance-only. 

To further characterize the nature of the residual nonattainment and/or 

maintenance problems at these 28 sites we examined the 24-hour concentrations by 

quarter that were developed as part of the projection of 24-hour PM2.5 design values, as 

described in section III.B.2, above. The quarterly data set for each site includes a 

projected 24-hour PM2.5 concentration for each of 4 the quarters for each of the 5 base 

years of ambient data (i.e., 2003 through 2007)54. Using these data we identified the 

number of quarterly values that exceed the level of 24-hour PM2.5 NAAQS at each site 

for the 2014 base case and 2014 remedy scenario. The quarterly data reveal that the 

residual nonattainment/maintenance problems at the 28 sites are primarily due to 

exceedances during the 1st and 4th quarters (i.e., the cool season). Exceedances predicted 

during the 2nd and 3rd quarters (i.e., warm season) in the 2014 base case are completely 

eliminated by the emissions reductions in the 2014 remedy scenario at all sites except for 

the single remaining high sites in both Birmingham and Pittsburgh. 

 As part of our analysis of quarterly exceedances we calculated the average percent 

reduction in sulfate by quarter for the residual nonattainment/maintenance sites in each of 

the 14 urban areas in Table V-3, above. The results are displayed in Figures V-12 and V13. These figures indicate that there are significant differences in the reduction in sulfate 

by quarter and from city to city. In general, our modeling results indicate that the 

response of sulfate during the 2nd and 3rd quarters (warm season) is generally proportional 

to the overall regional reduction in SO2 emissions. However, during the 1st and 4th

quarters (cool season) the relationship between the change in SO2 emissions and the 

change in sulfate is non-proportional. In 11 of the 14 urban areas the percent reduction in 

 

54 The quarterly concentrations by site for the 2014 base case and 2014 remedy scenario can be 

found in Appendix H. 
55

sulfate during the 2nd and/or 3rd quarters ranges from 38 to 48 percent55. This level of 

reduction in sulfate is consistent with the net 45 percent reduction in SO2 emissions, in 

aggregate, for the States covered by the TR. In the other 3 urban areas (i.e., Birmingham, 

Jersey City, and New York City), 2nd and/or 3rd quarter reductions in sulfate are in the 

range of 25 to 30 percent which is generally consistent with the SO2 emissions reduction 

in these States56. 

0

5

10

15

20

25

30

35

40

45

50

Birmingham, AL 

E. St. Louis, MO

Milwaukee, WI

Chicago, IL

Gary, IN 

Ann Arbor, MI

Detroit, MI 

Percent Reduction

Qtr 1 Qtr 2 Qtr 3 Qtr 4

Figure V-12. Percent reduction in sulfate concentrations by quarter at residual 

nonattainment/maintenance sites in Birmingham, East St. Louis, Milwaukee, Chicago, 

Gary, Ann Arbor, and Detroit. 

As indicated in Figures V-12 and V-13, the percent reduction in sulfate during the 

1st and 4th quarters is much less than in 2nd and 3rd quarters. Sulfate concentrations during 

the 1st quarter show the least response to emissions changes. The percent reduction in 

sulfate during this quarter ranges from 7 to 25 percent. Comparing the percent reduction 

in 1st quarter sulfate to that in the 3rd quarter indicates that 1st quarter reduction is only 

about a third (or less) of the reduction in the 3rd quarter for 9 of the 14 

 

55 The reduction in sulfate during the 3rd quarter tends to be somewhat greater than in the 2nd

quarter in most, but not all, of these urban areas. This may be due to a combination of differences 

between spring and summer in meteorological conditions in combination with chemical processes 

that associated with the formation of sulfate. 

56 See Table 6-2 in the TR EITSD. 
56

0

5

10

15

20

25

30

35

40

45

50

Cleveland, OH 

Steubenville, OH

Pittsburgh, PA 

Lancaster, PA

Baltimore, MD 

Jersey City, NJ

New York City, NY

Percent Reduction 

Qtr 1 Qtr 2 Qtr 3 Qtr 4

Figure V-13. Percent reduction in sulfate concentrations by quarter at residual 

nonattainment/maintenance sites in Cleveland, Steubenville, Pittsburgh, Lancaster, 

Baltimore, Jersey City, and New York City. 

urban areas. In the other 5 areas (i.e., Birmingham, East St. Louis, Pittsburgh, and 

Steubenville), the percent reduction in 1st quarter sulfate is approximately 50 to 60 

percent of the reduction predicted in the 3rd quarter. During the 4th quarter, the response 

of sulfate to emissions reductions is somewhat greater than the response in the 1st quarter 

in all but 5 of the 14 areas (Jersey City, Milwaukee, New York City, Pittsburgh, and 

Steubenville). 

Our results are consistent with the findings of Tsimpidi, et.al.57 They found that a 

50 percent reduction in SO2 emissions produced a 46 percent reduction in sulfate based 

on a model simulation for July. However, during a January simulation sulfate responded 

nonlinearly with an average sulfate reduction of 17 percent for a 50 percent reduction in 

SO2 emissions. Thus, in their analysis the January response of sulfate was only 37 

percent of the reduction predicted for July (17 percent / 46 percent). They conclude that 

the response of sulfate in January was limited by the availability of hydrogen peroxide. 

 

57 Tsimpidi, A.P.; Karydis, V.A.; Pandis, S.N.; Response of Inorganic Fine Particulate Matter to 

Emission Changes of Sulfur Dioxide and Ammonia: The Eastern Unites States as a Case Study; J. 

Air & Waste Manage. Assoc. 2007, 44, 1489-1498. 
57

Hydrogen peroxide, a strong oxidizing agent that is important in the formation of sulfate 

from SO2, is low in the winter and more abundant the summer when photochemistry is at 

a maximum. 

In addition to the lower response of sulfate to SO2 emissions reductions in the 

cool season months, there are several other factors which contribute to residual 

nonattainment predicted at sites in the 14 urban areas despite the large reductions in SO2

emissions. Examining the composition of 24-hour PM2.5 concentrations provides insight 

into these factors. Figure V-14 shows the average PM2.5 species concentrations by 

quarter for the 2014 remedy scenario at three sites selected as illustrative examples. The 

figure indicates that, in all 4 quarters, a significant portion of the 24-hour PM2.5 at the 

sites in Pittsburgh and Birmingham are associated with organic carbon. An analysis of 

ambient measurements for the Birmingham site indicates that approximately 70 percent 

of the organic carbon during the cool season and 60 percent during the warm season is 

associated with local sources58. Thus, we believe that a large portion of the residual 

maintenance problem at this site is due to local sources. The site in Pittsburgh is known 

to be heavily influenced by emissions from local sources59. The PM2.5 species 

concentrations at the Detroit site indicate that nitrate and organic carbon concentrations 

during the 1st and 4th quarters are greater contributors to the residual nonattainment 

problem than sulfate. During the 2nd and 3rd quarter sulfate is the dominant species. The 

relative amount of PM2.5 species at the other residual nonattainment/maintenance sites are 

generally similar to what is seen at the Detroit site. That is, in the 1st and 4th quarter, 

nitrate and organic carbon concentrations combined represent a much larger portion of 

total 24-hour PM2.5 than sulfate. This analysis is part of an on-going effort to understand 

the seasonal variations in the response of sulfate and nitrate to SO2 and NOX emissions 

reductions and the underlying factors that contribute to exceeedances in the 1st and 4th

quarters which lead to residual nonattainment/maintenance problems at the 28 sites. 

 

58 Derivation of the Contributing Emissions Score. U.S. Environmental Protection Agency, Office 

of Air Quality Planning and Standards. Research Triangle Park, NC. December 15, 2008. 

http://www.epa.gov/ttn/naaqs/pm/docs/tsd_ces_methodology.pdf 

59 Proposed Revision to the Allegheny County Portion of the Pennsylvania State Implementation 

Plan. Attainment Demonstration for the Liberty-Clairton PM2.5 Nonattainment Area. Allegheny 

County Health Department. February 22, 2010. 
58

Figure V-14. Average PM2.5 species concentrations by quarter at sites in Pittsburgh, 

Birmingham, and Detroit. 

E. Impacts on Projected 8-Hour Ozone Design Value 

The projected 8-hour ozone design values for the 2014 base case and 2014 

remedy scenario are provided in Appendix B. The impacts of the summer season NOX

emissions reductions on 8-hour ozone design values for monitored counties in the Eastern 

12 km modeling domain are also provided in Appendix B. The impacts are shown in 

Figure V-1560. This figure indicates that the emissions reductions from the TR will result 

in lower ozone concentrations in most counties in the Eastern U.S., compared to the 2014 

base case. Concentrations of 8-hour ozone are lower by 0.5 ppb or more for the 2014 

remedy scenario in portions of the Southeast and from Texas northeastward into 

Pennsylvania. Reductions in ozone of 2 ppb or more are predicted at sites in 22 counties 

in portions of Alabama, Florida, Mississippi, Missouri, Oklahoma, and Pennsylvania. 

The spatial patterns of the magnitude of reduction in 8-hour ozone across the East are 

 

60 These maps, which show the difference between the 2014 remedy scenario and the 2014 base 

case, are based upon 5-year weighted average design values. Additional maps showing average 

design value concentrations for 2003-2007, the 2012 and 2014 base cases, and the 2014 remedy 

scenario for 8-hour are provided in Appendix G. Maps showing the predicted change in 8-hour 

between the 2014 remedy and the 2012 base case are also provided in Appendix G.. 

0

10

20

30

40

50

60

1234 1234 1234

Pittsburgh, PA

(Allegheny Co 420030064)

Birmingham, AL

(Jefferson Co 10730023)

Detroit, MI

(Wayne Co 261630033)

PM2.5 (ug/m3)

Crustal Elemental Carbon Organic Carbon Nitrate Sulfate
59

generally consistent with the patterns in summer NOX emissions reductions from EGUs, 

as evident by comparing Figures V-5 to Figures V-15. 

One county in southern Illinois is predicted to have higher ozone of 0.2 ppb or 

more in the 2014 remedy scenario compared to the 2014 base case. This increase appears 

to be related to predicted increases in summer NOX emissions at EGUs near this county61. 

Figure V-15. Impacts on 8-hour ozone concentrations in 2014 resulting from the 

emissions reductions in the 2014 remedy scenario. 

F. Impacts on 8-Hour Ozone Nonattainment and Maintenance 

The number of projected 8-hour ozone nonattainment and/or maintenance sites in 

the East for the 2012 base case, 2014 base case, and 2014 remedy for 8-hour ozone are 

provided in Table V-4. The percent difference in the number of nonattainment and 

maintenance sites between the 2014 remedy scenario and both the 2012 and 2014 base 

case scenarios are also provided in this table. The average and peak reductions in 8-hour 

 

61 Increases in ozone between the 2014 base case and the 2014 remedy are also predicted in other 

unmonitored areas as evident in the ozone spatial fields prepared for the calculation of benefits in 

the Regulatory Impact Analysis (RIA). These other increases occur in oxidant-limited areas 

where reductions in NOx emissions can result in predicted increases in ozone (see the RIA for 

additional details). 
60

ozone concentrations for those sites with 2012 nonattainment and/or maintenance 

problems are provided in Table V-5. The location of 8-hour ozone nonattainment and/or 

maintenance sites in the East for the 2014 base case and 2014 remedy scenario are shown 

in Figures V-16 and V-17, respectively. 

Table V-4. Percent reduction in 8-hour ozone nonattainment and/or maintenance in the 

Eastern U.S. 

Number of Nonattainment and Maintenance Sites

Percent Reduction in 

Nonattainment/ 

Maintenance Sites 

8-Hour Ozone Ambient 

(2003-2007) 

 2012 

Base Case 

2014 

Base Case 

2014 

Remedy 

2012 Base vs 

2014 Remedy 

2014 Base vs 

2014 Remedy 

Nonattainment 

Sites 103 11 7 7 36% 0% 

Maintenance-Only 

Sites 67 16 6 5 69% 17% 

Table V-5. Average and peak reductions in 8-hour ozone for the 2012 base case 

nonattainment and/or maintenance sites. 

2014 Remedy vs 2012 Base Case 2014 Remedy vs 2014 Base Case 8- Hour Ozone

Average 

Reduction 

Greatest 

Reduction 

Average 

Reduction 

Greatest 

Reduction 

Nonattainment Sites 2.0 ppb 3.2 ppb 0.3 ppb 0.4 ppb 

Maintenance-Only Sites 2.2 ppb 3.8 ppb 0.3 ppb 0.5 ppb 

The information in Table V-4 shows that the extent of nonattainment and 

maintenance problems for 8-hour ozone is predicted to be lower by 36 percent and the 

number maintenance-only sites by 69 percent in the 2014 remedy scenario compared to 

the 2012 base case. The 2014 remedy scenario has 17 percent fewer maintenance sites 

than in the 2014 base case. 

For the 12 sites with residual nonattainment and/or maintenance problems in the 

2014 remedy scenario, the predicted ozone reductions provide nearly 10 percent of the 

amount needed for these sites to attain and/or maintain the ozone standard. Of these 12 

sites, 7 are predicted to be nonattainment and 5 are predicted to have maintenance 

problems. Six of the nonattainment sites are located in Houston and 1 is in Baton Rouge. 

Two of the residual maintenance only sites are in New York City and 3 are in Houston. 
61

The average and maximum 8-hour ozone design values at these sites for the 2014 remedy 

scenario are provided in Table V-6. 

Table V-6. Average and maximum 8-hour ozone design values (ppb) for monitoring sites 

projected to have nonattainment and/or have maintenance problems in the 2014 remedy 

scenario. 

Urban Area County 

Monitoring 

Site ID 

Average 

Design Valuea 

Maximum Design 

Valueb

Baton Rouge, LA E. Baton Rouge 261610008 86.0 89.7 

Brazoria Co 480391004 86.6 88.7 

Harris Co 482010024 81.9 85.6 

Harris Co 482010051 86.3 90.9 

Harris Co 482010055 93.4 95.5 

Harris Co 482010062 88.6 91.6 

Harris Co 482010066 88.6 92.1 

Harris Co 482011015 81.8 88.2 

Harris Co 482011035 80.7 88.8 

Houston, TX 

Harris Co 482011039 88.5 91.9 

Suffolk Co 361030002 84.8 85.7 New York City, NY Westchester Co 361192004 83.4 85.5 a

 Sites with average projected design values >= 85 ppb are projected to be nonattainment. 

b

 Sites with maximum projected design values >= 85 ppb and average design values <85 ppb are 

projected to be maintenance-only. 
62

Figure V-16. Projected 8-hour ozone nonattainment and/or maintenance sites in the East 

for the 2014 base case. 

Figure V-17. Projected 8-hour ozone nonattainment and/or maintenance sites in the East 

for the 2014 remedy scenario. 
63

G. Impacts on Visibility in Class 1 Areas 

The impacts of the TR regional SO2 and NOX emissions reductions were 

examined in terms of the projected improvements in visibility on the 20 percent worst 

visibility days at Class I areas62. We quantified visibility impacts at the 60 Class I areas 

in the Eastern modeling domain which have complete IMPROVE ambient data for 2005 

or are represented by IMPROVE monitors with complete data. Sites were used in this 

analysis if they had at least 3 years of complete data for the 2002-2006 period63. 

Visibility for the 2012 base case, 2014 base case and 2014 remedy scenario were 

calculated using the regional haze modeling guidance methodology, which applies 

modeling results in a relative sense, using base year ambient data. The PM2.5 and 

regional haze modeling guidance recommends the calculation of future year changes in 

visibility in a similar manner to the calculation of changes in PM2.5 design values. The 

regional haze methodology for calculating future year visibility impairment is included in 

MATS (as previously documented in section III). 

 In calculating visibility impairment, the extinction coefficient and deciview 

values are made up of individual component species (sulfate, nitrate, organics, etc). The 

predicted change in visibility (on the 20 percent worst days) is calculated as the modeled 

percent change in the mass for each of the PM2.5 species (on the 20% worst observed 

days) multiplied by the observed concentrations. The future mass is converted to 

extinction and then daily species extinction coefficients are summed to get a daily total 

extinction value. The daily extinction coefficients are converted to deciviews and then 

averaged across all 20 percent worst days. In this way, we calculate an average change in 

deciviews from the base case to a future case at each IMPROVE site. Subtracting the 

2014 remedy scenario deciview values from the corresponding 2014 base case deciview 

values gives an estimate of the visibility benefits in Class I areas that are expected to 

occur from the TR. 

 

62 The focus of this analysis is on visibility impacts at Class I areas within our 12 km Eastern 

modeling domain. We have also calculated visibility impacts for Class I areas farther to the west 

using results of the 2014 base case and remedy modeling for the 36 km modeling domain. These 

results can be found in Appendix I. 

63 Since the base case modeling used meteorology for 2005, one of the complete years must be 

2005. 
64

The following options were chosen in MATS for calculating the future year 

visibility values for the rule: 

New IMPROVE algorithm 

Use model grid cells at Class 1 area Centroid 

Temporal adjustment at monitor- 3x3 for 12km grid, 1x1 for 36km grid 

Start monitor year- 2002 

End monitor year- 2006 

Base model year 2005 

Minimum years required for a valid monitor- 3 

 The “base model year” was chosen as 2005 because it is the base case 

meteorological year for the Transport Rule modeling. The start and end years were 

chosen as 2002 and 2006 because that is the most recent 5 year period of IMPROVE data 

in the MATS database. These choices are consistent with using a 5 year base period for 

regional haze calculations. The predicted change in visibility (on the 20 percent worst 

days) is provided in Table V-7 for each Class I area in the Eastern modeling domain. 

Table V-7. Visibility (deciviews) impacts on 20 percent worst days at Class I areas in the 

Eastern modeling domain. 

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 20% 

Worst Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 Visibility 

Change from 

2014 Base Case 

(dv) 

Acadia NP ACAD Maine 23.19 21.91 21.79 20.55 -1.24 

Badlands NP BADL 

South 

Dakota 16.73 16.39 16.24 15.90 -0.34 

Bandelier NM BAND 

New 

Mexico 11.87 11.57 11.49 11.29 -0.20 

Big Bend NP BIBE Texas 17.39 17.07 16.91 16.38 -0.53 

Black Canyon of the 

Gunnison NM BLCA Colorado 10.18 9.80 9.75 9.77 0.02 

Bosque del Apache BOAP 

New 

Mexico 13.89 13.41 13.28 13.08 -0.20 

Bridger Wilderness BRID Wyoming 10.93 10.67 10.64 10.66 0.02 

Brigantine BRIG New Jersey 29.28 28.01 27.72 25.04 -2.68 

Caney Creek 

Wilderness CACR Arkansas 26.78 26.56 25.89 22.63 -3.26 

Carlsbad Caverns NP CAVE 

New 

Mexico 16.98 16.51 16.38 15.79 -0.59 

Dolly Sods 

Wilderness DOSO 

West 

Virginia 29.73 28.76 28.09 22.02 -6.07 

Eagles Nest 

Wilderness EANE Colorado 9.38 8.97 8.92 8.96 0.04 

Everglades NP EVER Florida 22.48 21.54 21.35 20.47 -0.88 

Fitzpatrick Wilderness FITZ Wyoming 10.93 10.69 10.63 10.65 0.02 

Flat Tops Wilderness FLTO Colorado 9.38 9.04 9.01 9.03 0.02 

Great Gulf Wilderness GRGU 

New 

Hampshire 22.13 21.23 20.97 19.11 -1.86 
65

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 20% 

Worst Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 Visibility 

Change from 

2014 Base Case 

(dv) 

Great Sand Dunes 

NM GRSA Colorado 12.49 12.13 12.10 12.14 0.04 

Great Smoky 

Mountains NP GRSM Tennessee 30.43 28.08 26.99 23.29 -3.70 

Guadalupe Mountains 

NP GUMO Texas 16.98 16.50 16.38 15.89 -0.49 

Hercules-Glades 

Wilderness HEGL Missouri 27.15 27.02 26.30 23.75 -2.55 

Isle Royale NP ISLE Michigan 21.33 20.90 20.45 19.40 -1.05 

James River Face 

Wilderness JARI Virginia 29.32 27.34 26.69 22.60 -4.09 

Joyce-KilmerSlickrock Wilderness JOYC Tennessee 30.43 28.28 27.22 23.55 -3.67 

La Garita Wilderness LAGA Colorado 10.18 9.93 9.91 9.93 0.02 

Linville Gorge 

Wilderness LIGO 

North 

Carolina 29.40 27.10 26.35 22.45 -3.90 

Lostwood LOST 

North 

Dakota 19.50 18.95 18.84 18.71 -0.13 

Lye Brook Wilderness LYBR Vermont 24.17 22.57 22.21 19.55 -2.66 

Maroon BellsSnowmass Wilderness MABE Colorado 9.38 9.04 9.02 9.03 0.01 

Mammoth Cave NP MACA Kentucky 31.76 31.90 31.21 25.08 -6.13 

Medicine Lake MELA Montana 17.78 17.45 17.38 17.32 -0.06 

Mesa Verde NP MEVE Colorado 12.78 12.16 12.09 12.12 0.03 

Moosehorn MOOS Maine 21.94 20.91 20.75 19.61 -1.14 

Mount Zirkel 

Wilderness MOZI Colorado 10.19 9.98 9.92 9.94 0.02 

North Absaroka 

Wilderness NOAB Wyoming 11.12 10.96 10.94 10.94 0.00 

Okefenokee OKEF Georgia 27.24 25.84 25.11 22.97 -2.14 

Otter Creek 

Wilderness OTCR 

West 

Virginia 29.73 28.86 28.15 21.85 -6.30 

Pecos Wilderness PECO 

New 

Mexico 10.10 9.79 9.71 9.68 -0.03 

Presidential RangeDry River Wilderness PRRA New 

Hampshire 22.13 21.28 21.00 19.03 -1.97 

Rawah Wilderness RAWA Colorado 10.19 9.91 9.87 9.88 0.01 

Roosevelt 

Campobello 

International Park ROCA Maine 21.94 20.95 20.82 19.63 -1.19 

Cape Romain ROMA 

South 

Carolina 27.14 25.83 25.32 23.16 -2.16 

Rocky Mountain NP ROMO Colorado 13.54 13.17 13.10 13.07 -0.03 

Salt Creek SACR 

New 

Mexico 18.20 17.71 17.56 17.05 -0.51 

San Pedro Parks 

Wilderness SAPE 

New 

Mexico 10.39 10.07 9.99 9.95 -0.04 

Seney SENE Michigan 24.71 24.60 23.81 22.08 -1.73 

Shenandoah NP SHEN Virginia 29.66 27.92 27.33 22.62 -4.71 

Shining Rock 

Wilderness SHRO 

North 

Carolina 28.72 26.43 25.46 22.05 -3.41 

Sipsey Wilderness SIPS Alabama 29.62 28.02 26.67 23.23 -3.44 
66

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 20% 

Worst Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 Visibility 

Change from 

2014 Base Case 

(dv) 

Theodore Roosevelt 

NP THRO 

North 

Dakota 17.69 17.20 17.08 16.97 -0.11 

UL Bend ULBE Montana 14.92 14.75 14.72 14.71 -0.01 

Upper Buffalo 

Wilderness UPBU Arkansas 27.09 26.93 26.15 22.73 -3.42 

Voyageurs NP VOYA Minnesota 19.82 19.32 19.02 18.16 -0.86 

Washakie Wilderness WASH Wyoming 11.12 10.96 10.94 10.94 0.00 

West Elk Wilderness WEEL Colorado 9.38 9.00 8.98 9.00 0.02 

Weminuche 

Wilderness WEMI Colorado 10.18 9.90 9.88 9.89 0.01 

White Mountain 

Wilderness WHIT 

New 

Mexico 13.52 13.23 13.06 12.45 -0.61 

Wheeler Peak 

Wilderness WHPE 

New 

Mexico 10.10 9.75 9.70 9.67 -0.03 

Wind Cave NP WICA 

South 

Dakota 15.96 15.49 15.37 15.24 -0.13 

Wichita Mountains WIMO Oklahoma 23.79 23.09 22.69 21.21 -1.48 

Wolf Island WOLF Georgia 27.24 25.79 25.19 23.20 -1.99 
 

Transport Rule Air Quality Modeling Technical Support Document 

Appendix A 

Air Quality Model Performance Evaluation 
A-2

A. Introduction 

An operational model performance evaluation was conducted for ozone and PM2.5 and its 

components species predicted by CAMx for the 2005 base year model simulation. The purpose 

of this evaluation was to examine the ability of the CAMx modeling system to replicate the base 

year concentrations measured at monitoring sites in the 12 km Eastern modeling domain1

. This 

evaluation includes statistical assessments of model versus observed data that were paired in 

space and time on a daily or weekly basis, depending on the sampling frequency of each 

monitoring network included in the analysis2,3

. The Atmospheric Model Evaluation Tool 

(AMET) was used to calculate the performance statistics described in this document.4

The evaluation of ozone predictions focuses on 8-hour daily maximum ozone 

concentrations during the months of May through September when 8-hour daily maximum ozone 

concentrations are typically highest in the East. Observed ozone data for 2005 were obtained 

from the Air Quality System (AQS) Aerometric Information Retrieval System (AIRS). 

Model performance statistics for ozone were calculated using the daily pairs of predicted and 

measured 8-hour daily maximum concentrations. As is the common practice for evaluating 

ozone, we calculated performance statistics both with and without a concentration cut-off. For 

this analysis we calculated one set statistics using all observed-predicted pairs, irrespective of 

concentration, and a second set based on observed concentrations > 60 ppb. 

The evaluation of PM2.5 component species includes comparisons of predicted and 

observed concentrations of sulfate (SO4), nitrate (NO3), total nitrate5

 (TNO3), ammonium (NH4), 

elemental carbon (EC), and organic carbon (OC). The PM2.5 performance statistics were 

calculated for each of the four seasons6. PM2.5 ambient measurements for 2005 were obtained 

from the following networks: the Chemical Speciation Network (CSN), the Interagency 

Monitoring of PROtected Visual Environments (IMPROVE), and the Clean Air Status and 

Trends Network (CASTNet). The CSN sites are generally located within urban areas, CASTNet 

sites in suburban/rural locations, and the IMPROVE sites are, for the most part, in rural/remote 

areas. 

The PM2.5 species included in the evaluation for each network are listed in Table A-1. 

For species that are measured by more than one network, we calculated separate sets of statistics 

for each network. The measurements at CSN and IMPROVE sites represent 24-hour average 

concentrations, whereas measurements at CASTNet sites represent weekly averages. In 

calculating the model performance statistics, the CAMx hourly species predictions were 

aggregated to the averaging times of the measurements in each network: 24-hour averages for 

comparison to CSN and IMPROVE measurements and weekly average for comparison to 

CASTNet measurements. 

 

1

 The 12 km modeling domain is shown in Figure II-1. 

2

 Time periods with missing ozone or PM25 species measurements we excluded from the data sets used in the 

calculation of performance statistics. 

3

 It should be noted that each modeled concentration represents a grid-cell volume-averaged value, while the 

ambient network measurements are made at specific locations. 

4

 Gilliam, R. C., W. Appel, and S. Phillips. The Atmospheric Model Evaluation Tool (AMET): Meteorology 

Module. Presented at 4th Annual CMAS Models-3 Users Conference, Chapel Hill, NC, September 26 - 28, 2005. 

(http://www.cmascenter.org/) 

5

 Total nitrate includes particulate nitrate and nitric acid gas (HNO3) 6

 Seasons were defined as follows: winter (December-January-February), spring (March-April-May), summer (JuneJuly-August), and fall (September-October-November). 
A-3

Table A-1. PM2.5 monitoring networks and pollutants species included in the CAMx 

performance evaluation. 

Particulate 

Species Ambient 

Monitoring 

Networks 

SO4 NO3 TNO3 EC NH4 OC 

IMPROVE X X - X X X 

CSN X X - X X X 

CASTNet X - X - X - 

There are various statistical metrics available and used by the modeling community for 

model performance evaluation. For a robust evaluation, the principal evaluation statistics used to 

evaluate CAMx performance were two bias metrics, normalized mean bias and mean fractional 

bias; and two error metrics, normalized mean error and mean fractional error. 

Normalized mean bias (NMB) is the ratio of the difference (model - observed) to the sum of 

observed values. NMB is a useful model performance indicator because it avoids over-inflating 

the observed range of values, especially at low concentrations. Normalized mean bias is defined 

as:

NMB = 

( )

( )

P O

O

n

n

∑ −

∑

1

1

*100 

Normalized mean error (NME) is the ratio of the absolute value of the difference (model - 

observed) to the sum of observed values. Normalized mean error is defined as: 

NME = 

( )

P O

O

n

n

∑ −

∑

1

1

*100 

Mean fractional bias is defined as: 

MFB = 

1

2

n 1

P O

P O

n

∑ −

⎛ +

⎝

⎜ ⎞

⎠

⎟

⎛

⎝

⎜

⎜

⎜

⎜

⎞

⎠

⎟

⎟

⎟

⎟

( )

( ) *100, where P = predicted concentrations and O = observed values. 

MFB is a useful model performance indicator because it has the advantage of equally weighting 

positive and negative bias estimates. The single largest disadvantage in this estimate of model 

performance is that the estimated concentration (i.e., prediction, P) is found in both the 

numerator and denominator. Mean fractional error (MFE) is similar to fractional bias except the 
A-4

absolute value of the difference is used so that the error is always positive. Mean fractional error 

is defined as: 

MFE = 

1

2

n 1

P O

P O

n

∑ −

⎛ +

⎝

⎜ ⎞

⎠

⎟

⎛

⎝

⎜

⎜

⎜

⎜

⎞

⎠

⎟

⎟

⎟

⎟ ( ) *100 

Both MFB and MFE do not require a threshold in order to be appropriate for analyses.7

 The “acceptability” of model performance was judged by comparing the CAMx 2005 

performance results to the range of performance found in recent regional ozone and PM2.5 model 

applications (e.g., Revised Renewable Fuel Standards Final Rule,8

 Clean Air Interstate Rule9, 

Final PM NAAQS Rule10, and EPA’s Proposal to Designate an Emissions Control Area for 

Nitrogen Oxides11). These other modeling studies represent a wide range of modeling analyses 

which cover various models, model configurations, domains, years and/or episodes, chemical 

mechanisms, and aerosol modules. Ozone bias and error in these studies are typically in the 

range of + 10 percent for bias and within 20 percent for error. For sulfate and nitrate, the two 

key PM2.5 species for this rule, mean fractional bias is typically in the range of – 10 percent to + 

30 percent for summer sulfate and +50 to + 70 percent for winter nitrate. The error for summer 

sulfate based on these other studies was within 35 to 50 percent and the error for winter nitrate 

was within 85 to 105 percent. Also, Boylan, et.al.12 have recently completed a study of model 

performance results from numerous PM2.5 air quality model applications. In their paper they 

discuss model performance goals and criteria13 for evaluating PM2.5 air quality modeling. Their 

proposed performance criteria are MFB of < + 60 percent and MFE of < +75 percent; but that 

“less stringent” performance criteria should be applied to species at low concentration levels. 

 The model performance statistics for ozone and PM2.5 species based on the 2005 CAMx 

 

7

 Seigneur, C., Pun, B., Prasad, P., Louis, J.-F., Solomon, P., Emery, C., Morris, R., Zahniser, M., Worsnop, D., 

Koutrakis, P., White, W., and Tombach, I., 2000. Guidance for the performance evaluation of three-dimensional air 

quality modeling systems for particulate matter and visibility. J. Air Waste Ma. 50: 588-599. 

8

 EPA 2010, Renewable Fuel Standard Program (RFS2) Regulatory Impact Analysis. EPA-420-R-10-006. February 

2010. Sections 3.4.2.1.2 and 3.4.3.3. Docket EPA-HQ-OAR-2009-0472-11332. 

9

 See: U.S. Environmental Protection Agency; Technical Support Document for the Final Clean Air Interstate Rule: 

Air Quality Modeling; Office of Air Quality Planning and Standards; RTP, NC; March 2005 (CAIR Docket OAR2005-0053-2149). 

10 U.S. Environmental Protection Agency, 2006. Technical Support Document for the Final PM NAAQS Rule: 

Office of Air Quality Planning and Standards, Research Triangle Park, NC. 

11 U.S. Environmental Protection Agency, Proposal to Designate an Emissions Control Area for Nitrogen Oxides, 

Sulfur Oxides, and Particulate Matter: Technical Support Document. EPA-420-R-007, 329pp., 2009. 

(http://www.epa.gov/otaq/regs/nonroad/marine/ci/420r09007.pdf) 

12 Boylan, J.W. and Russell, A.G., PM and light extinction model performance metrics, goals, and criteria for threedimensional air quality models. Atmos. Environment;40; 26; August 2006, 4946-4959. 

13 Performance goal is defined as “the level of accuracy that is considered to be close to the best a model can be 

expected to achieve.” Performance criteria is defined as “the level of accuracy that is considered to be acceptable for 

modeling applications.” 
A-5

modeling for the Eastern U.S. are provided in Tables A-2 and A-3, respectively. The number of 

observed-predicted pairs used in the calculation of the various statistics is also provided in these 

tables. 

 Overall, the model performance statistics for ozone, sulfate, and nitrate from the CAMx 

2005 simulation are within or close to the ranges found in other recent applications, as described 

above. These model performance results give us confidence that our applications of CAMx 

using this 2005 modeling platform provide a scientifically credible approach for assessing ozone 

and PM2.5 concentrations for the purposes of the Transport Rule. The model performance results 

for ozone and several of the PM2.5 component species are highlighted in the discussion below. 

Table A-2. Model performance statistics for 8-hour daily maximum ozone concentrations. 

 Month 

No. of 

Obs. 

NMB 

(%) 

NME 

(%) 

MFB 

(%) 

MFE 

 (%) 

May 5429 -13.9 15.5 -15.4 16.9 

June 7648 -2.7 12.1 -3.4 12.3 

July 6388 2.1 14.2 0.9 13.9 

August 6020 3.7 13.4 2.6 13.0 

September 5786 -5.9 11.3 -6.6 11.7 

 

8-Hour Daily Max: 

Observed > 60 ppb 

May - Sept 31271 -2.9 13.2 -4.0 13.5 

 

May 24362 -1.2 15.2 0.5 15.8 

June 23449 11.3 20.7 13.5 21.7 

July 23609 21.0 27.7 21.0 26.9 

August 23749 20.8 26.2 20.4 25.2 

September 22716 8.4 17.9 10.8 18.9 

 

8-Hour Daily Max: 

All Observed 

May - Sept 117885 12.0 21.5 13.2 21.7 
A-6

Table A-3. Model performance statistics for PM2.5 component species concentrations. 

Species Network Season 

No. of 

Obs. 

NMB 

(%) 

NME 

(%) 

MFB 

(%) 

MFE 

(%) 

Winter 2076 63.2 73.1 43.4 55.7 

Spring 2435 38.5 51.3 35.2 44.9 

Summer 2324 -9.0 44.2 -6.5 49.8 

IMPROVE 

Fall 2199 21.3 49.4 28.6 48.5 

Winter 3390 58.9 71.3 34.6 49.7 

Spring 3626 35.6 48.0 29.2 39.7 

Summer 3516 -7.2 40.9 -8.0 46.6 

CSN 

Fall 3365 18.2 44.1 24.2 41.8 

Winter 760 39.7 44.3 31.6 38.1 

Spring 832 25.3 33.0 24.7 31.3 

Summer 792 -10.0 27.1 -10.3 33.5 

Sulfate 

CASTNet 

Fall 786 14.4 33.0 19.9 32.7 

Winter 2076 -5.3 56.6 -48.0 96.0 

Spring 2435 9.2 71.0 -70.3 113.4 

Summer 2324 -21.9 94.2

-

118.0 142.1 

IMPROVE 

Fall 2192 59.5 122.7 -72.3 127.6 

Winter 3099 -11.5 48.4 -29.8 67.7 

Spring 3254 19.0 66.2 -34.7 84.9 

Summer 3150 -6.4 86.5 -80.3 116.2 

Nitrate 

CSN 

Fall 3238 42.1 96.1 -47.9 104.0 

Winter 760 7.3 26.5 13.7 29.8 

Spring 832 4.8 27.0 -2.3 28.0 

Summer 792 17.4 36.9 4.1 33.9 

Total 

Nitrate CASTNet 

Fall 786 49.6 57.4 31.8 43.9 

Winter 206 33.1 51.8 26.3 44.4 

Spring 92 20.7 46.9 21.5 41.7 

Summer 85 -25.1 44.6 -28.0 56.0 

IMPROVE 

Fall 89 21.4 60.0 29.0 58.2 

Winter 3390 20.2 44.1 19.1 41.6 

Spring 3626 35.0 50.9 29.5 44.2 

Summer 3516 -3.6 42.6 3.3 51.5 

CSN 

Fall 3365 21.9 51.6 31.5 51.7 

Winter 760 18.1 30.5 22.6 32.1 

Spring 832 30.6 40.2 26.4 35.4 

Summer 792 -19.3 30.9 -21.8 37.1 

Ammonium 

CASTNet 

Fall 786 14.2 42.1 19.2 41.1 

Elemental IMPROVE Winter 2072 18.6 55.4 11.1 49.7 
A-7

Spring 2296 -0.2 48.8 9.6 46.3 

Summer 2182 -23.8 44.5 -23.3 50.8 

Fall 2118 -6.4 47.1 -9.1 46.6 

Winter 3441 67.6 93.1 47.3 63.8 

Spring 3672 57.3 82.7 40.7 59.8 

Summer 3529 55.3 81.7 36.8 62.7 

Carbon 

CSN 

Fall 3396 27.9 65.1 24.8 51.8 

Winter 2071 32.3 60.6 20.2 50.9 

Spring 2290 4.5 44.2 11.5 42.7 

Summer 2183 -0.1 39.0 1.1 40.2 

IMPROVE 

Fall 2118 4.1 42.7 1.9 43.0 

Winter 3051 19.8 60.6 29.7 58.6 

Spring 3243 -8.1 47.5 4.0 52.2 

Summer 3228 -24.2 38.5 -25.2 45.8 

Organic 

Carbon 

CSN 

Fall 3097 -9.1 42.4 2.0 49.2 

Winter 2172 761.2 768.4 137.4 142.7 

Spring 2334 182.0 226.7 77.1 105.8 

Summer 2246 96.0 153.2 61.2 89.1 

IMPROVE 

Fall 2229 247.0 269.7 98.6 111.7 

Winter 3392 1017.4 1022.4 163.7 164.3 

Spring 3597 461.5 479.0 133.9 138.1 

Summer 3510 263.3 306.4 111.6 125.6 

Crustal 

STN 

Fall 3362 459.7 471.5 136.8 139.2 

 For ozone, the CAMx 2005 simulation shows a tendency to under predict observed 8-

hour daily maximum values to some extent at high concentration levels and over predict at low 

observed concentration levels. Observed sulfate concentrations tend to be slightly under 

predicted during the summer (by ~10 percent, or less), but generally over predicted during the 

other seasons. Particle nitrate tends to be under predicted somewhat during the winter at both 

urban and rural/remote sites. The negative fractional bias statistics in all seasons for particle 

nitrate suggest that under prediction may be occurring at lower concentration levels. For 

ammonium, model performance is generally consistent at both urban and suburban/rural 

locations with a tendency for under prediction during the summer and over prediction during 

other seasons. The model performance statistics for crustal material indicate that this component 

of PM2.5 is over predicted by a large amount in each season14. 

 The model performance results reported here are being used by EPA’s Office of Air 

Quality Planning and Standards and Office of Research and Development in an on-going 

coordinated effort to understand and improve model performance for research and regulatory 

applications. 

 

14 The performance results for crustal material provided the basis for excluding this species in the procedures used 

for calculating PM2.5 contributions, as noted in Section IV. 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix B 

2003-2007 Base Period and Projected 2012 and 2014 Design Values 

for Monitoring Sites in the Eastern Modeling Domain 
B-2

The tables in this appendix provide the 5-year weighted average and maximum 

design values for 8-hour ozone, annual PM2.5, and 24-hour PM2.5 for monitoring 

sites in the 12 km Eastern U.S. modeling domain1

. Design values are provided for 

the 2003-2007 base period, 2012 base case, 2014 base case, and 2014 remedy 

scenario. 

Also included in this appendix are tables of the differences (i.e., increases and 

decreases) by site in average design values between the 2014 remedy scenario and 

both the 2012 base case and 2014 base case. Note that increases and decreases 

reported as + 0.1 ppb for ozone, + 0.01 μg/m3

 for annual PM2.5, and + 0.1 μg/m3

for 24-hour PM2.5 may overstate the actual difference in concentrations because 

the design value concentrations are truncated before the differences are calculated. 

 1

 Design values are provided for those sites which meet the data completeness and projection 

criteria described in Section III of the TSD. 
B-3

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

10030010 Alabama Baldwin 77.3 78.0 70.7 71.4 69.0 6910270001 Alabama Clay 74.0 76.0 64.8 66.5 61.2 6210331002 Alabama Colbert 72.0 74.0 64.5 66.3 62.7 6410510001 Alabama Elmore 70.7 71.0 62.0 62.3 59.6 5910550011 Alabama Etowah 71.7 73.0 61.6 62.7 58.7 5910690004 Alabama Houston 71.0 71.0 62.8 62.8 60.1 6010730023 Alabama Jefferson 78.7 86.0 69.6 76.1 67.1 7310731003 Alabama Jefferson 79.0 84.0 69.7 74.1 67.1 7110731005 Alabama Jefferson 81.0 86.0 71.0 75.4 68.1 7210731009 Alabama Jefferson 77.0 82.0 66.4 70.7 64.0 6810731010 Alabama Jefferson 73.0 75.0 63.8 65.6 61.2 6210732006 Alabama Jefferson 83.7 89.0 74.0 78.7 71.3 7510735002 Alabama Jefferson 74.0 77.0 65.3 67.9 62.8 6510735003 Alabama Jefferson 77.0 82.0 66.6 71.0 64.2 6810736002 Alabama Jefferson 81.3 89.0 72.0 78.8 69.4 7610790002 Alabama Lawrence 72.0 74.0 63.2 64.9 60.6 6210890014 Alabama Madison 77.3 78.0 67.9 68.6 64.6 6510970003 Alabama Mobile 76.7 78.0 69.8 71.0 68.1 6910972005 Alabama Mobile 76.7 77.0 70.0 70.3 68.2 6811011002 Alabama Montgomery 69.3 74.0 60.6 64.7 58.2 6211030011 Alabama Morgan 77.3 79.0 70.2 71.8 67.9 6911130002 Alabama Russell 71.3 75.0 63.0 66.3 59.8 6211170004 Alabama Shelby 85.7 88.0 75.2 77.2 72.2 7411190002 Alabama Sumter 64.0 66.0 58.2 60.1 56.4 5811210003 Alabama Talladega 72.0 72.0 62.4 62.4 59.7 5911250010 Alabama Tuscaloosa 73.3 77.0 63.3 66.5 60.6 6350350005 Arkansas Crittenden 87.3 89.0 77.3 78.8 74.5 7651190007 Arkansas Pulaski 78.3 80.0 69.0 70.5 66.6 68
B-4

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

51191002 Arkansas Pulaski 79.7 83.0 70.2 73.1 67.6 7051191005 Arkansas Pulaski 74.0 75.0 65.4 66.3 63.1 6480013001 Colorado Adams 69.0 70.0 66.8 67.7 66.2 6780050002 Colorado Arapahoe 78.7 81.0 76.0 78.2 75.1 7780130011 Colorado Boulder 77.0 81.0 73.4 77.2 72.2 7680310002 Colorado Denver 56.0 56.0 54.2 54.2 53.7 5380310014 Colorado Denver 73.0 75.0 70.7 72.6 70.0 7180350004 Colorado Douglas 83.0 84.0 79.3 80.3 78.0 7980590002 Colorado Jefferson 76.3 79.0 73.9 76.6 73.2 7580590005 Colorado Jefferson 70.3 75.0 67.9 72.4 67.0 7180590006 Colorado Jefferson 81.7 85.0 78.1 81.3 76.9 8080590011 Colorado Jefferson 80.7 82.0 78.2 79.5 77.5 7880691004 Colorado Larimer 72.3 74.0 68.4 70.0 67.3 6881230009 Colorado Weld 76.7 78.0 72.7 73.9 71.6 7290010017 Connecticut Fairfield 88.0 90.0 83.1 85.0 81.4 8390011123 Connecticut Fairfield 92.3 94.0 84.8 86.4 82.7 8490013007 Connecticut Fairfield 90.0 92.0 84.5 86.4 82.7 8490019003 Connecticut Fairfield 87.7 89.0 82.8 84.0 81.1 8290031003 Connecticut Hartford 84.3 90.0 75.0 80.1 72.7 7790050005 Connecticut Litchfield 87.7 89.0 78.0 79.1 75.5 7690070007 Connecticut Middlesex 90.3 92.0 81.8 83.4 79.6 8190090027 Connecticut New Haven 79.3 81.0 73.3 74.9 71.5 7390093002 Connecticut New Haven 90.3 93.0 82.9 85.4 80.7 8390110008 Connecticut New London 85.3 88.0 77.1 79.5 75.0 7790131001 Connecticut Tolland 88.7 91.0 78.0 80.1 75.5 77

100010002 Delaware Kent 80.3 81.0 70.8 71.4 68.8 69100031007 Delaware New Castle 80.0 82.0 70.5 72.3 68.7 70100031010 Delaware New Castle 82.3 83.0 74.4 75.0 72.6 73100031013 Delaware New Castle 81.3 82.0 72.7 73.3 70.9 71100051002 Delaware Sussex 81.3 82.0 71.4 72.0 69.3 69
B-5

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

100051003 Delaware Sussex 82.7 84.0 73.9 75.0 72.0 73110010025 

District Of Columbia 

District of Columbia 79.7 81.0 74.3 75.5 72.6 73

110010041 

District Of Columbia 

District of Columbia 80.3 85.0 75.4 79.8 73.7 78

110010043 

District Of Columbia 

District of Columbia 84.7 87.0 79.5 81.7 77.7 79

120010025 Florida Alachua 72.0 72.0 65.7 65.7 63.2 63120030002 Florida Baker 68.7 70.0 62.0 63.2 59.6 60120050006 Florida Bay 78.7 81.0 72.1 74.3 69.7 71120090007 Florida Brevard 69.0 69.0 63.9 63.9 60.8 60120094001 Florida Brevard 71.3 72.0 66.3 66.9 62.9 63120110031 Florida Broward 62.0 63.0 60.7 61.6 60.4 61120112003 Florida Broward 61.3 63.0 58.1 59.7 57.1 58120118002 Florida Broward 65.0 67.0 62.3 64.2 61.5 63120210004 Florida Collier 68.3 69.0 60.4 61.0 58.1 58120230002 Florida Columbia 72.0 72.0 65.0 65.0 62.4 62120310077 Florida Duval 77.0 77.0 72.2 72.2 70.2 70120310100 Florida Duval 77.7 79.0 72.3 73.5 70.0 71120330004 Florida Escambia 79.7 81.0 75.9 77.2 74.3 75120330018 Florida Escambia 82.7 83.0 78.5 78.8 76.8 77120330024 Florida Escambia 80.7 81.0 76.6 76.9 74.9 75120570081 Florida Hillsborough 78.7 80.0 75.3 76.6 73.5 74120570110 Florida Hillsborough 76.0 76.0 70.5 70.5 68.9 68120571035 Florida Hillsborough 74.0 76.0 72.0 73.9 70.4 72120571065 Florida Hillsborough 80.7 81.0 77.9 78.2 76.0 76120573002 Florida Hillsborough 77.5 78.0 72.3 72.7 70.7 71120574004 Florida Hillsborough 74.0 74.0 68.1 68.1 66.4 66120690002 Florida Lake 76.7 77.0 69.9 70.2 66.8 67120712002 Florida Lee 70.3 72.0 62.8 64.4 60.7 62120713002 Florida Lee 70.3 71.0 62.8 63.4 60.6 61
B-6

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

120730012 Florida Leon 70.0 70.0 61.5 61.5 59.0 59120730013 Florida Leon 71.0 72.0 62.2 63.1 59.5 60120813002 Florida Manatee 77.3 79.0 71.9 73.5 70.0 71120814012 Florida Manatee 76.3 77.0 69.4 70.0 67.5 68120814013 Florida Manatee 72.7 73.0 65.9 66.2 64.3 64120830003 Florida Marion 71.7 72.0 63.4 63.7 60.8 61120830004 Florida Marion 73.0 73.0 65.2 65.2 63.0 63120860027 Florida Miami-Dade 71.3 74.0 69.4 72.1 69.2 71120860029 Florida Miami-Dade 67.7 69.0 66.0 67.2 65.4 66120950008 Florida Orange 79.3 81.0 73.6 75.2 70.4 71120952002 Florida Orange 79.3 80.0 74.6 75.3 71.6 72120972002 Florida Osceola 72.0 73.0 66.1 67.0 63.3 64120990020 Florida Palm Beach 65.0 65.0 61.5 61.5 59.7 59121010005 Florida Pasco 76.3 77.0 70.5 71.1 68.8 69121012001 Florida Pasco 73.3 75.0 67.7 69.2 65.8 67121030004 Florida Pinellas 72.3 73.0 68.4 69.0 66.7 67121030018 Florida Pinellas 69.7 71.0 66.3 67.5 64.8 66121035002 Florida Pinellas 72.7 74.0 68.9 70.2 67.2 68121056005 Florida Polk 73.3 75.0 66.7 68.3 64.9 66121056006 Florida Polk 74.7 75.0 68.0 68.3 66.0 66121111002 Florida St. Lucie 66.5 68.0 60.9 62.3 58.7 60121130015 Florida Santa Rosa 80.0 80.0 76.3 76.3 74.5 74121151005 Florida Sarasota 77.3 78.0 69.4 70.1 67.5 68121151006 Florida Sarasota 73.3 74.0 65.9 66.6 64.1 64121152002 Florida Sarasota 72.0 74.0 63.5 65.3 61.7 63121171002 Florida Seminole 76.0 77.0 70.4 71.4 66.8 67121272001 Florida Volusia 68.3 69.0 61.4 62.0 57.6 58121275002 Florida Volusia 68.3 69.0 60.8 61.4 57.0 57121290001 Florida Wakulla 71.3 74.0 64.1 66.5 62.0 64130210012 Georgia Bibb 81.0 83.0 71.1 72.8 66.1 67
B-7

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

130210013 Georgia Bibb 81.0 81.0 71.4 71.4 66.0 66130510021 Georgia Chatham 68.3 69.0 62.2 62.9 59.9 60130550001 Georgia Chattooga 75.0 76.0 64.3 65.2 60.8 61130590002 Georgia Clarke 80.7 83.0 68.7 70.6 64.5 66130670003 Georgia Cobb 82.7 87.0 73.8 77.6 69.9 73130730001 Georgia Columbia 73.0 73.0 64.5 64.5 61.7 61130770002 Georgia Coweta 82.0 85.0 74.3 77.0 69.7 72130850001 Georgia Dawson 76.3 79.0 66.1 68.5 62.4 64130890002 Georgia DeKalb 88.7 93.0 81.6 85.6 78.2 82130893001 Georgia DeKalb 87.5 88.0 80.7 81.2 77.7 78130970004 Georgia Douglas 87.3 90.0 77.8 80.2 73.2 75131130001 Georgia Fayette 85.7 89.0 78.2 81.2 74.9 77131210055 Georgia Fulton 91.7 94.0 84.4 86.5 80.9 82131270006 Georgia Glynn 67.0 68.0 61.7 62.6 59.6 60131350002 Georgia Gwinnett 88.7 90.0 79.1 80.3 75.3 76131510002 Georgia Henry 89.7 95.0 79.7 84.5 75.7 80132130003 Georgia Murray 78.0 79.0 68.9 69.8 65.6 66132150008 Georgia Muscogee 75.7 80.0 65.5 69.2 61.9 65132151003 Georgia Muscogee 70.7 73.0 61.4 63.4 58.0 59132230003 Georgia Paulding 80.3 83.0 69.2 71.5 65.1 67132450091 Georgia Richmond 80.3 81.0 70.8 71.4 67.8 68132470001 Georgia Rockdale 90.0 95.0 78.8 83.2 74.5 78132611001 Georgia Sumter 72.3 74.0 64.4 65.9 61.3 62170010006 Illinois Adams 70.0 70.0 64.8 64.8 63.4 63170190004 Illinois Champaign 68.3 70.0 62.3 63.8 60.9 62170230001 Illinois Clark 66.0 66.0 59.8 59.8 58.4 58170310001 Illinois Cook 77.3 82.0 75.9 80.5 74.8 79170310032 Illinois Cook 74.3 77.0 71.1 73.7 70.1 72170310064 Illinois Cook 71.3 77.0 68.2 73.7 67.2 72170310072 Illinois Cook 71.0 73.0 67.7 69.6 66.7 68
B-8

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

170310076 Illinois Cook 77.0 79.0 75.8 77.8 75.0 77170311003 Illinois Cook 76.3 79.0 73.6 76.2 72.7 75170311601 Illinois Cook 76.7 80.0 74.8 78.0 73.6 76170314002 Illinois Cook 66.3 68.0 65.9 67.6 65.4 67170314007 Illinois Cook 71.7 74.0 69.2 71.4 68.3 70170314201 Illinois Cook 74.3 76.0 71.7 73.4 70.8 72170317002 Illinois Cook 77.7 79.0 74.7 76.0 73.7 74170436001 Illinois DuPage 69.0 70.0 67.4 68.3 66.5 67170491001 Illinois Effingham 70.0 72.0 63.8 65.6 62.3 64170650002 Illinois Hamilton 73.0 73.0 66.2 66.2 64.5 64170831001 Illinois Jersey 78.7 80.0 71.4 72.6 69.4 70170890005 Illinois Kane 74.3 77.0 69.9 72.4 68.5 71170971002 Illinois Lake 76.7 79.0 73.7 75.9 72.6 74170971007 Illinois Lake 78.0 79.0 75.0 75.9 73.8 74171110001 Illinois McHenry 73.3 78.0 68.3 72.7 66.7 71171132003 Illinois McLean 73.0 74.0 65.7 66.6 63.8 64171150013 Illinois Macon 71.3 74.0 64.8 67.2 63.3 65171170002 Illinois Macoupin 73.0 74.0 64.4 65.3 62.3 63171190008 Illinois Madison 82.7 84.0 75.8 77.0 73.7 74171191009 Illinois Madison 83.0 84.0 76.5 77.4 74.4 75171193007 Illinois Madison 81.0 83.0 74.3 76.1 72.2 74171430024 Illinois Peoria 68.3 71.0 61.9 64.3 59.9 62171431001 Illinois Peoria 72.7 76.0 65.9 68.9 63.7 66171570001 Illinois Randolph 72.0 75.0 65.5 68.2 63.8 66171613002 Illinois Rock Island 65.3 68.0 60.8 63.3 59.5 61171630010 Illinois Saint Clair 81.7 82.0 76.5 76.8 74.9 75171670010 Illinois Sangamon 70.0 71.0 61.6 62.5 59.9 60171971011 Illinois Will 71.7 72.0 67.5 67.8 66.0 66172010009 Illinois Winnebago 69.0 71.0 62.4 64.2 60.5 62172012001 Illinois Winnebago 68.3 70.0 61.8 63.3 59.9 61
B-9

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

180030002 Indiana Allen 79.3 83.0 71.6 74.9 69.4 72180030004 Indiana Allen 74.3 76.0 67.1 68.6 65.0 66180110001 Indiana Boone 79.7 81.0 72.1 73.3 69.8 70180150002 Indiana Carroll 74.0 75.0 67.1 68.0 65.2 66180190008 Indiana Clark 80.3 83.0 74.4 76.9 72.4 74180350010 Indiana Delaware 76.3 78.0 68.3 69.8 65.9 67180390007 Indiana Elkhart 79.0 83.0 71.0 74.6 68.8 72180431004 Indiana Floyd 77.7 79.0 72.6 73.8 70.8 72180550001 Indiana Greene 78.3 80.0 71.0 72.5 69.3 70180570005 Indiana Hamilton 82.7 87.0 75.3 79.2 72.8 76180590003 Indiana Hancock 78.0 81.0 71.3 74.0 69.0 71180630004 Indiana Hendricks 75.3 76.0 68.8 69.5 66.8 67180690002 Indiana Huntington 75.0 76.0 67.6 68.5 65.5 66180710001 Indiana Jackson 74.7 76.0 66.5 67.6 64.7 65180810002 Indiana Johnson 76.7 78.0 69.3 70.5 67.2 68180890022 Indiana Lake 77.7 82.0 73.6 77.7 72.5 76180890030 Indiana Lake 81.0 85.0 76.9 80.7 75.9 79180892008 Indiana Lake 77.7 79.0 73.8 75.0 72.8 74180910005 Indiana LaPorte 77.0 78.0 71.5 72.4 70.0 70180910010 Indiana LaPorte 78.5 79.0 72.6 73.0 70.9 71180950010 Indiana Madison 76.7 80.0 69.2 72.1 66.8 69180970042 Indiana Marion 72.7 76.0 68.0 71.1 66.3 69180970050 Indiana Marion 78.7 81.0 72.4 74.5 70.4 72180970057 Indiana Marion 75.0 77.0 69.7 71.5 67.9 69180970073 Indiana Marion 75.7 77.0 70.0 71.2 68.1 69181090005 Indiana Morgan 77.0 79.0 70.3 72.1 68.1 69181230009 Indiana Perry 81.0 81.0 75.5 75.5 73.1 73181270024 Indiana Porter 78.3 81.0 73.7 76.2 72.4 74181270026 Indiana Porter 75.3 77.0 69.9 71.5 68.5 70181290003 Indiana Posey 71.7 75.0 64.8 67.8 62.8 65
B-10

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

181410010 Indiana St. Joseph 74.7 77.0 67.5 69.6 65.6 67181410015 Indiana St. Joseph 74.3 79.0 67.1 71.4 65.1 69181411007 Indiana St. Joseph 79.3 82.0 71.6 74.1 69.5 71181450001 Indiana Shelby 77.3 80.0 71.8 74.3 70.0 72181630012 Indiana Vanderburgh 77.3 80.0 70.3 72.8 68.1 70181630013 Indiana Vanderburgh 67.7 75.0 61.1 67.7 59.1 65181670018 Indiana Vigo 63.0 67.0 57.7 61.3 56.2 59181670024 Indiana Vigo 74.0 76.0 68.1 69.9 66.5 68181730008 Indiana Warrick 77.7 80.0 71.8 73.9 69.9 72181730009 Indiana Warrick 72.7 75.0 66.0 68.1 64.1 66181730011 Indiana Warrick 76.7 77.0 71.0 71.3 69.1 69190450021 Iowa Clinton 71.3 73.0 66.0 67.5 64.5 66190851101 Iowa Harrison 74.7 75.0 69.5 69.8 68.2 68191130028 Iowa Linn 67.7 71.0 63.0 66.1 61.6 64191130033 Iowa Linn 68.3 70.0 63.7 65.3 62.2 63191530058 Iowa Polk 63.0 66.0 58.2 61.0 56.6 59191630014 Iowa Scott 70.3 74.0 64.8 68.2 63.2 66191632011 Iowa Scott 72.0 72.0 66.6 66.6 65.0 65191690011 Iowa Story 61.0 66.0 56.1 60.7 54.7 59200450004 Kansas Douglas 73.0 73.0 66.6 66.6 65.1 65200910010 Kansas Johnson 75.3 76.0 70.4 71.0 68.9 69201030003 Kansas Leavenworth 75.0 77.0 69.5 71.4 68.0 69201070002 Kansas Linn 73.3 74.0 68.3 69.0 67.1 67201730001 Kansas Sedgwick 64.3 66.0 58.6 60.2 56.9 58201730010 Kansas Sedgwick 71.3 74.0 65.5 68.0 63.6 66201910002 Kansas Sumner 71.7 76.0 64.9 68.8 62.9 66202090021 Kansas Wyandotte 75.3 77.0 71.1 72.7 69.8 71210130002 Kentucky Bell 71.7 74.0 61.9 63.9 59.2 61210150003 Kentucky Boone 75.7 77.0 67.8 68.9 66.0 67210190017 Kentucky Boyd 77.3 79.0 69.5 71.0 68.0 69
B-11

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

210290006 Kentucky Bullitt 74.0 76.0 68.8 70.7 67.0 68210370003 Kentucky Campbell 75.0 83.0 70.2 77.7 68.7 76210430500 Kentucky Carter 71.0 72.0 62.8 63.7 61.2 62210470006 Kentucky Christian 78.0 81.0 67.9 70.5 65.6 68210590005 Kentucky Daviess 75.7 81.0 70.3 75.3 68.3 73210610501 Kentucky Edmonson 73.7 76.0 65.7 67.7 63.5 65210670001 Kentucky Fayette 62.7 65.0 56.8 58.8 54.9 56210670012 Kentucky Fayette 70.3 73.0 63.6 66.1 61.5 63210890007 Kentucky Greenup 76.7 78.0 69.1 70.3 67.6 68210910012 Kentucky Hancock 74.0 76.0 68.9 70.7 66.8 68210930006 Kentucky Hardin 74.7 78.0 67.6 70.6 65.6 68211010014 Kentucky Henderson 75.3 78.0 69.2 71.7 67.2 69211110027 Kentucky Jefferson 75.3 79.0 70.5 73.9 68.5 71211110051 Kentucky Jefferson 78.3 82.0 73.3 76.7 71.7 75211111021 Kentucky Jefferson 71.0 73.0 66.9 68.8 65.3 67211130001 Kentucky Jessamine 73.3 77.0 66.6 70.0 64.6 67211170007 Kentucky Kenton 78.7 81.0 73.1 75.3 71.5 73211390003 Kentucky Livingston 73.7 75.0 68.2 69.4 66.3 67211451024 Kentucky McCracken 73.3 76.0 68.2 70.7 66.5 69211490001 Kentucky McLean 73.0 73.0 67.1 67.1 65.0 65211850004 Kentucky Oldham 83.0 85.0 75.3 77.1 72.8 74211950002 Kentucky Pike 66.7 70.0 58.6 61.5 56.7 59211990003 Kentucky Pulaski 70.3 72.0 65.1 66.7 60.8 62212130004 Kentucky Simpson 75.7 78.0 65.9 67.9 63.3 65212210013 Kentucky Trigg 70.0 70.0 63.8 63.8 61.8 61212270008 Kentucky Warren 72.0 73.0 63.6 64.5 61.6 62220050004 Louisiana Ascension 82.0 84.0 76.9 78.8 75.3 77220110002 Louisiana Beauregard 75.0 75.0 71.3 71.3 70.4 70220150008 Louisiana Bossier 78.0 79.0 69.6 70.5 67.2 68220170001 Louisiana Caddo 79.0 80.0 70.7 71.6 68.3 69
B-12

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

220190002 Louisiana Calcasieu 82.0 83.0 78.0 78.9 76.8 77220190008 Louisiana Calcasieu 70.0 71.0 66.8 67.7 65.9 66220190009 Louisiana Calcasieu 78.7 80.0 73.3 74.5 71.9 73220330003 Louisiana East Baton Rouge 92.0 96.0 87.8 91.6 86.4 90220330009 Louisiana East Baton Rouge 80.3 81.0 76.5 77.2 75.3 75220330013 Louisiana East Baton Rouge 81.3 82.0 76.4 77.1 75.0 75220331001 Louisiana East Baton Rouge 86.0 87.0 82.9 83.8 81.7 82220430001 Louisiana Grant 73.0 73.0 68.7 68.7 66.9 66220470007 Louisiana Iberville 84.0 86.0 79.1 81.0 77.6 79220470009 Louisiana Iberville 80.0 81.0 75.5 76.5 74.2 75220470012 Louisiana Iberville 85.0 86.0 80.3 81.3 78.9 79220511001 Louisiana Jefferson 83.0 84.0 78.5 79.4 76.9 77220550005 Louisiana Lafayette 82.0 82.0 76.0 76.0 74.0 74220550007 Louisiana Lafayette 66.0 66.0 61.1 61.1 59.6 59220570004 Louisiana Lafourche 79.3 80.0 74.4 75.1 73.0 73220630002 Louisiana Livingston 78.3 80.0 72.9 74.5 71.3 72220710012 Louisiana Orleans 70.0 70.0 66.9 66.9 65.7 65220730004 Louisiana Ouachita 75.3 77.0 68.8 70.3 66.8 68220770001 Louisiana Pointe Coupee 83.7 86.0 78.8 81.0 77.4 79220870002 Louisiana St. Bernard 78.0 78.0 74.7 74.7 73.6 73220890003 Louisiana St. Charles 77.3 78.0 73.1 73.8 71.8 72220930002 Louisiana St. James 76.3 77.0 71.9 72.6 70.7 71220950002 Louisiana 

St. John the Baptist 79.0 80.0 74.8 75.7 73.7 74

221010003 Louisiana St. Mary 76.0 76.0 70.3 70.3 68.6 68221210001 Louisiana 

West Baton Rouge 84.3 85.0 80.3 81.0 79.0 79

230050027 Maine Cumberland 60.0 61.0 52.5 53.3 50.8 51230052003 Maine Cumberland 72.0 75.0 63.0 65.6 60.9 63230090102 Maine Hancock 82.0 83.0 72.3 73.2 70.4 71
B-13

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

230090103 Maine Hancock 73.0 74.0 64.4 65.3 62.6 63230090301 Maine Hancock 68.7 70.0 60.4 61.6 58.7 59230112005 Maine Kennebec 69.7 71.0 60.9 62.1 59.1 60230130004 Maine Knox 75.3 77.0 65.8 67.3 63.8 65230173001 Maine Oxford 61.0 63.0 54.3 56.1 52.6 54230194008 Maine Penobscot 67.0 68.0 59.2 60.0 57.5 58230230004 Maine Sagadahoc 68.5 70.0 59.8 61.1 57.9 59230310038 Maine York 73.7 75.0 64.2 65.3 62.0 63230312002 Maine York 74.0 74.0 65.3 65.3 63.2 63230313002 Maine York 74.0 77.0 65.2 67.8 63.1 65240030014 Maryland Anne Arundel 89.7 90.0 79.7 79.9 77.1 77240051007 Maryland Baltimore 77.3 78.0 71.2 71.8 69.6 70240053001 Maryland Baltimore 85.3 87.0 78.5 80.1 76.9 78240090011 Maryland Calvert 81.0 81.0 69.8 69.8 67.7 67240130001 Maryland Carroll 83.3 86.0 73.0 75.4 70.5 72240150003 Maryland Cecil 90.7 93.0 79.1 81.1 76.9 78240170010 Maryland Charles 86.0 88.0 73.8 75.5 71.2 72240210037 Maryland Frederick 80.3 83.0 70.4 72.7 67.9 70240230002 Maryland Garrett 75.5 76.0 68.4 68.8 66.9 67240251001 Maryland Harford 92.7 94.0 83.5 84.7 81.6 82240259001 Maryland Harford 88.3 91.0 78.3 80.7 76.5 78240290002 Maryland Kent 82.0 83.0 71.6 72.5 69.7 70240313001 Maryland Montgomery 83.0 86.0 76.4 79.1 74.5 77240330030 Maryland Prince George's 85.0 85.0 77.3 77.3 75.1 75240338003 Maryland Prince George's 91.0 91.0 81.2 81.2 78.7 78240430009 Maryland Washington 78.3 79.0 68.4 69.0 66.1 66250010002 Massachusetts Barnstable 84.7 86.0 75.1 76.2 73.1 74250034002 Massachusetts Berkshire 79.7 81.0 70.8 72.0 68.7 69250051002 Massachusetts Bristol 82.7 86.0 73.6 76.5 71.7 74250070001 Massachusetts Dukes 83.0 84.0 74.8 75.7 72.9 73
B-14

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

250092006 Massachusetts Essex 83.3 84.0 76.7 77.3 74.8 75250094004 Massachusetts Essex 77.7 79.0 69.0 70.2 66.8 68250095005 Massachusetts Essex 77.5 80.0 68.3 70.5 66.1 68250130008 Massachusetts Hampden 87.3 92.0 76.9 81.0 74.4 78250150103 Massachusetts Hampshire 71.7 77.0 62.4 67.0 60.2 64250154002 Massachusetts Hampshire 85.0 87.0 74.6 76.4 72.2 73250170009 Massachusetts Middlesex 79.0 79.0 69.4 69.4 67.0 67250171102 Massachusetts Middlesex 77.3 81.0 67.8 71.1 65.6 68250213003 Massachusetts Norfolk 84.7 86.0 76.5 77.7 74.2 75250250041 Massachusetts Suffolk 80.3 81.0 72.8 73.5 70.8 71250250042 Massachusetts Suffolk 67.3 68.0 61.7 62.3 60.1 60250270015 Massachusetts Worcester 80.0 83.0 69.7 72.3 67.4 69260050003 Michigan Allegan 90.0 93.0 82.0 84.7 79.9 82260190003 Michigan Benzie 81.7 83.0 74.7 75.9 72.7 73260210014 Michigan Berrien 82.3 84.0 75.5 77.0 73.6 75260270003 Michigan Cass 80.7 84.0 72.4 75.4 70.3 73260370001 Michigan Clinton 75.7 78.0 67.0 69.1 64.8 66260490021 Michigan Genesee 77.3 80.0 69.7 72.2 67.6 70260492001 Michigan Genesee 79.3 82.0 71.9 74.4 69.9 72260630007 Michigan Huron 75.7 78.0 69.3 71.4 67.6 69260650012 Michigan Ingham 76.0 78.0 67.5 69.2 65.2 66260770008 Michigan Kalamazoo 75.3 78.0 67.8 70.3 65.8 68260810020 Michigan Kent 79.3 83.0 71.3 74.7 69.1 72260810022 Michigan Kent 81.0 83.0 72.2 74.0 69.9 71260890001 Michigan Leelanau 75.7 77.0 69.7 70.9 68.0 69260910007 Michigan Lenawee 78.7 81.0 71.4 73.4 69.7 71260990009 Michigan Macomb 86.0 90.0 80.1 83.8 78.6 82260991003 Michigan Macomb 84.0 87.0 79.7 82.5 78.3 81261050007 Michigan Mason 79.7 81.0 72.4 73.6 70.5 71261130001 Michigan Missaukee 73.7 75.0 66.6 67.8 64.9 66
B-15

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

261210039 Michigan Muskegon 85.0 88.0 77.5 80.2 75.5 78261250001 Michigan Oakland 78.0 81.0 73.7 76.6 72.6 75261390005 Michigan Ottawa 81.7 85.0 73.8 76.8 71.7 74261470005 Michigan St. Clair 82.3 85.0 75.0 77.4 73.0 75261530001 Michigan Schoolcraft 79.3 82.0 72.0 74.4 70.1 72261610008 Michigan Washtenaw 78.3 81.0 72.5 75.0 71.1 73261630001 Michigan Wayne 73.0 75.0 68.2 70.0 66.9 68261630016 Michigan Wayne 73.5 76.0 68.0 70.3 66.6 68261630019 Michigan Wayne 82.0 83.0 77.1 78.0 75.7 76270031002 Minnesota Anoka 67.7 69.0 66.9 68.2 66.4 67280330002 Mississippi DeSoto 82.7 85.0 73.5 75.6 70.8 72280450001 Mississippi Hancock 79.0 79.0 72.2 72.2 70.2 70280470008 Mississippi Harrison 83.0 83.0 76.9 76.9 75.0 75280470009 Mississippi Harrison 77.0 77.0 71.8 71.8 70.4 70280490010 Mississippi Hinds 71.3 73.0 59.4 60.8 56.6 57280590006 Mississippi Jackson 80.3 81.0 74.5 75.2 72.8 73280590007 Mississippi Jackson 74.0 74.0 68.8 68.8 67.3 67280750003 Mississippi Lauderdale 74.3 76.0 65.2 66.6 62.3 63280810005 Mississippi Lee 73.7 75.0 64.2 65.3 61.3 62290370003 Missouri Cass 74.7 77.0 69.2 71.3 67.9 70290390001 Missouri Cedar 75.7 76.0 70.0 70.3 68.3 68290470003 Missouri Clay 79.0 81.0 72.2 74.0 70.4 72290470005 Missouri Clay 84.3 87.0 78.2 80.7 76.5 78290470006 Missouri Clay 83.0 87.0 76.8 80.5 75.0 78290490001 Missouri Clinton 83.0 85.0 76.4 78.2 74.5 76290770036 Missouri Greene 73.0 77.0 66.2 69.8 64.6 68290990012 Missouri Jefferson 82.3 86.0 77.5 80.9 75.6 79291130003 Missouri Lincoln 87.0 87.0 78.8 78.8 76.6 76291370001 Missouri Monroe 71.7 75.0 66.0 69.0 64.5 67291570001 Missouri Perry 77.5 80.0 70.3 72.5 68.4 70
B-16

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

291650023 Missouri Platte 77.0 77.0 71.8 71.8 70.3 70291831002 Missouri Saint Charles 86.3 89.0 79.9 82.4 77.9 80291831004 Missouri Saint Charles 87.0 89.0 79.9 81.8 77.7 79291860005 Missouri Sainte Genevieve 79.7 83.0 72.5 75.5 70.5 73291890004 Missouri Saint Louis 82.3 86.0 78.5 82.1 77.0 80291890005 Missouri Saint Louis 83.0 83.0 77.0 77.0 74.9 74291890006 Missouri Saint Louis 78.0 78.0 73.3 73.3 71.6 71291890014 Missouri Saint Louis 88.0 88.0 83.0 83.0 81.1 81295100085 Missouri St. Louis City 84.0 84.0 80.3 80.3 78.8 78295100086 Missouri St. Louis City 83.0 86.0 79.4 82.2 77.8 80310550028 Nebraska Douglas 68.7 70.0 64.5 65.7 63.6 64310550032 Nebraska Douglas 64.7 66.0 60.5 61.7 59.4 60310550035 Nebraska Douglas 66.3 68.0 62.4 64.0 61.3 62311090016 Nebraska Lancaster 56.0 57.0 51.6 52.5 50.5 51330012004 New Hampshire Belknap 71.3 73.0 63.3 64.8 61.1 62330050007 New Hampshire Cheshire 70.7 71.0 62.2 62.5 60.2 60330074001 New Hampshire Coos 77.0 77.0 69.1 69.1 67.1 67330074002 New Hampshire Coos 65.0 67.0 58.3 60.1 56.7 58330090010 New Hampshire Grafton 67.0 67.0 59.0 59.0 57.0 57330110020 New Hampshire Hillsborough 70.3 71.0 61.2 61.8 59.0 59330111011 New Hampshire Hillsborough 78.7 80.0 68.6 69.7 66.1 67330115001 New Hampshire Hillsborough 78.3 80.0 68.9 70.4 66.6 68330131007 New Hampshire Merrimack 71.7 72.0 62.4 62.6 60.3 60330150014 New Hampshire Rockingham 74.7 75.0 65.8 66.0 63.7 63330150016 New Hampshire Rockingham 75.0 79.0 66.0 69.6 63.9 67330190003 New Hampshire Sullivan 70.0 72.0 61.9 63.7 59.9 61340010005 New Jersey Atlantic 79.3 82.0 70.7 73.1 68.7 71340030005 New Jersey Bergen 86.0 86.0 82.2 82.2 80.8 80340070003 New Jersey Camden 85.7 88.0 79.6 81.8 78.2 80340071001 New Jersey Camden 89.3 91.0 80.9 82.4 78.7 80
B-17

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

340110007 New Jersey Cumberland 83.3 84.0 73.5 74.1 71.4 72340150002 New Jersey Gloucester 87.0 88.0 79.5 80.4 77.7 78340170006 New Jersey Hudson 85.7 89.0 80.1 83.2 78.6 81340190001 New Jersey Hunterdon 89.0 90.0 79.3 80.2 76.6 77340210005 New Jersey Mercer 88.0 91.0 81.4 84.1 79.3 82340230011 New Jersey Middlesex 88.3 91.0 80.2 82.6 77.8 80340250005 New Jersey Monmouth 87.3 89.0 79.5 81.0 77.5 79340273001 New Jersey Morris 83.3 86.0 75.0 77.5 72.7 75340290006 New Jersey Ocean 93.0 94.0 83.3 84.2 80.8 81340315001 New Jersey Passaic 81.0 83.0 75.0 76.9 73.2 75350130008 New Mexico Dona Ana 70.7 72.0 66.9 68.1 66.5 67350130017 New Mexico Dona Ana 71.3 72.0 67.3 67.9 66.7 67350130021 New Mexico Dona Ana 75.3 77.0 71.0 72.7 70.4 72350130022 New Mexico Dona Ana 72.7 74.0 68.5 69.8 67.9 69350450009 New Mexico San Juan 69.7 72.0 66.4 68.6 65.9 68350451005 New Mexico San Juan 71.3 72.0 68.1 68.8 67.6 68360010012 New York Albany 73.7 76.0 65.9 67.9 63.9 65360050110 New York Bronx 74.0 76.0 68.9 70.8 67.6 69360050133 New York Bronx 74.7 75.0 72.0 72.3 71.0 71360130006 New York Chautauqua 86.7 89.0 79.3 81.4 77.4 79360130011 New York Chautauqua 77.3 79.0 70.5 72.1 68.8 70360150003 New York Chemung 68.7 70.0 61.2 62.4 59.6 60360270007 New York Dutchess 75.7 79.0 67.3 70.2 65.4 68360290002 New York Erie 85.0 86.0 77.5 78.4 75.6 76360410005 New York Hamilton 71.7 73.0 65.5 66.7 64.1 65360430005 New York Herkimer 68.3 70.0 63.0 64.6 61.9 63360450002 New York Jefferson 78.0 80.0 71.2 73.0 69.6 71360530006 New York Madison 72.0 73.0 64.1 64.9 62.5 63360551007 New York Monroe 75.0 80.0 68.9 73.5 67.4 71360631006 New York Niagara 82.7 86.0 76.1 79.2 74.7 77
B-18

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

360650004 New York Oneida 68.3 72.0 61.5 64.8 59.9 63360671015 New York Onondaga 73.7 76.0 66.6 68.7 65.0 67360715001 New York Orange 82.0 84.0 73.3 75.1 71.0 72360750003 New York Oswego 78.0 82.0 71.1 74.8 69.6 73360790005 New York Putnam 84.3 86.0 76.8 78.4 74.7 76360810098 New York Queens 69.0 69.0 64.3 64.3 63.1 63360810124 New York Queens 80.0 82.0 75.1 77.0 73.8 75360830004 New York Rensselaer 77.3 80.0 69.1 71.5 67.1 69360850067 New York Richmond 88.3 89.0 82.6 83.2 80.8 81360910004 New York Saratoga 79.7 82.0 71.3 73.4 69.2 71360930003 New York Schenectady 70.0 74.0 62.8 66.4 60.9 64361030002 New York Suffolk 90.0 91.0 86.3 87.2 84.9 85361030004 New York Suffolk 84.7 90.0 78.6 83.6 76.8 81361030009 New York Suffolk 90.3 91.0 85.1 85.8 83.7 84361111005 New York Ulster 77.3 79.0 68.4 69.9 66.3 67361173001 New York Wayne 68.0 71.0 62.1 64.8 60.7 63361192004 New York Westchester 87.7 90.0 84.7 86.9 83.5 85370030004 North Carolina Alexander 77.0 79.0 67.8 69.6 65.5 67370110002 North Carolina Avery 70.0 72.0 60.0 61.8 57.7 59370210030 North Carolina Buncombe 74.0 74.0 63.8 63.8 61.2 61370270003 North Carolina Caldwell 74.3 76.0 63.7 65.1 61.1 62370330001 North Carolina Caswell 76.3 77.0 65.5 66.1 62.7 63370370004 North Carolina Chatham 73.3 74.0 63.1 63.7 60.5 61370510008 North Carolina Cumberland 78.0 80.0 67.3 69.1 64.4 66370511003 North Carolina Cumberland 81.7 83.0 70.5 71.7 67.6 68370590002 North Carolina Davie 81.3 83.0 71.0 72.5 68.4 69370630013 North Carolina Durham 77.0 78.0 66.8 67.7 63.8 64370650099 North Carolina Edgecombe 77.0 79.0 67.3 69.0 64.6 66370670022 North Carolina Forsyth 78.0 79.0 66.9 67.8 64.5 65370670028 North Carolina Forsyth 73.0 74.0 62.3 63.2 60.0 60
B-19

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

370670030 North Carolina Forsyth 76.0 76.0 65.7 65.7 63.3 63370671008 North Carolina Forsyth 80.0 81.0 68.9 69.7 66.3 67370690001 North Carolina Franklin 78.7 81.0 67.7 69.7 64.4 66370750001 North Carolina Graham 78.3 79.0 68.4 69.0 65.4 65370770001 North Carolina Granville 82.0 85.0 70.8 73.4 67.6 70370810011 North Carolina Guilford 77.0 77.0 67.3 67.3 64.3 64370810013 North Carolina Guilford 82.0 82.0 71.6 71.6 68.4 68370870004 North Carolina Haywood 71.3 73.0 62.4 63.9 60.0 61370870035 North Carolina Haywood 78.3 79.0 68.3 68.9 65.4 66370870036 North Carolina Haywood 77.3 78.0 68.4 69.0 65.9 66370990005 North Carolina Jackson 76.0 76.0 66.6 66.6 64.0 64371010002 North Carolina Johnston 77.3 79.0 66.9 68.4 63.9 65371070004 North Carolina Lenoir 75.3 77.0 66.6 68.1 64.3 65371090004 North Carolina Lincoln 81.0 83.0 71.5 73.2 69.2 70371170001 North Carolina Martin 75.0 77.0 67.9 69.7 66.2 68371190041 North Carolina Mecklenburg 88.0 90.0 78.5 80.3 75.9 77371191005 North Carolina Mecklenburg 80.3 83.0 72.1 74.6 69.8 72371191009 North Carolina Mecklenburg 89.3 93.0 78.3 81.6 75.4 78371290002 North Carolina New Hanover 72.3 73.0 66.7 67.3 64.8 65371450003 North Carolina Person 77.3 79.0 65.5 67.0 63.5 64371470099 North Carolina Pitt 76.3 77.0 66.9 67.5 64.4 65371570099 North Carolina Rockingham 77.0 78.0 66.1 66.9 63.4 64371590021 North Carolina Rowan 86.7 89.0 75.7 77.7 72.7 74371590022 North Carolina Rowan 86.7 90.0 75.9 78.8 72.9 75371730002 North Carolina Swain 66.3 68.0 57.6 59.1 55.0 56371790003 North Carolina Union 79.3 81.0 68.8 70.3 66.0 67371830014 North Carolina Wake 80.3 82.0 70.1 71.6 67.0 68371830016 North Carolina Wake 80.0 83.0 69.4 72.0 66.3 68371990003 North Carolina Yancey 76.0 76.0 66.3 66.3 63.7 63390030002 Ohio Allen 78.7 81.0 70.7 72.8 68.5 70
B-20

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

390071001 Ohio Ashtabula 89.0 91.0 81.1 83.0 79.0 80390170004 Ohio Butler 83.3 85.0 76.2 77.8 74.2 75390171004 Ohio Butler 82.3 85.0 74.6 77.0 72.4 74390230001 Ohio Clark 81.0 83.0 72.4 74.2 70.2 72390230003 Ohio Clark 77.0 78.0 69.9 70.8 67.9 68390250022 Ohio Clermont 81.0 83.0 74.2 76.0 72.2 74390271002 Ohio Clinton 82.3 85.0 73.4 75.8 71.1 73390350034 Ohio Cuyahoga 71.0 76.0 65.0 69.6 63.4 67390350064 Ohio Cuyahoga 73.0 76.0 67.3 70.0 65.6 68390355002 Ohio Cuyahoga 79.7 81.0 73.3 74.5 71.5 72390410002 Ohio Delaware 78.3 81.0 69.7 72.1 67.2 69390490028 Ohio Franklin 80.3 82.0 73.6 75.2 71.6 73390490029 Ohio Franklin 86.3 88.0 77.4 78.9 75.0 76390490037 Ohio Franklin 80.3 81.0 74.2 74.9 72.1 72390490081 Ohio Franklin 79.7 80.0 71.9 72.1 69.6 69390550004 Ohio Geauga 79.3 86.0 71.3 77.3 69.2 75390570006 Ohio Greene 80.3 83.0 71.7 74.1 69.6 72390610006 Ohio Hamilton 84.7 86.0 78.1 79.3 76.1 77390610010 Ohio Hamilton 82.0 84.0 75.7 77.6 74.1 75390610040 Ohio Hamilton 81.7 83.0 76.0 77.2 74.3 75390810017 Ohio Jefferson 78.0 80.0 68.5 70.3 67.1 68390830002 Ohio Knox 77.7 79.0 68.6 69.7 66.2 67390850003 Ohio Lake 86.3 89.0 78.7 81.2 76.7 79390853002 Ohio Lake 80.7 81.0 73.4 73.7 71.5 71390870006 Ohio Lawrence 70.7 73.0 63.7 65.8 62.3 64390870011 Ohio Lawrence 63.3 69.0 55.3 60.3 53.9 58390890005 Ohio Licking 78.0 81.0 68.9 71.6 66.4 68390930018 Ohio Lorain 76.7 80.0 70.4 73.4 68.6 71390950024 Ohio Lucas 76.3 78.0 70.3 71.9 68.7 70390950027 Ohio Lucas 77.7 82.0 72.1 76.1 70.5 74
B-21

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

390950034 Ohio Lucas 81.3 86.0 74.8 79.1 73.0 77390950081 Ohio Lucas 80.7 84.0 74.4 77.4 72.6 75390970007 Ohio Madison 79.7 82.0 70.6 72.6 68.4 70390990013 Ohio Mahoning 78.7 80.0 70.7 71.9 69.0 70391030003 Ohio Medina 80.3 84.0 71.5 74.8 69.3 72391090005 Ohio Miami 76.7 80.0 68.1 71.1 65.9 68391130037 Ohio Montgomery 74.0 75.0 66.3 67.2 64.4 65391331001 Ohio Portage 83.7 88.0 75.3 79.1 73.0 76391351001 Ohio Preble 73.0 75.0 65.1 66.9 63.1 64391510016 Ohio Stark 78.0 79.0 68.7 69.6 66.6 67391510022 Ohio Stark 77.3 80.0 68.9 71.3 67.0 69391514005 Ohio Stark 81.0 82.0 71.3 72.2 69.3 70391530020 Ohio Summit 83.7 85.0 74.7 75.8 72.3 73391550009 Ohio Trumbull 80.0 83.0 71.3 73.9 69.3 71391550011 Ohio Trumbull 84.3 86.0 75.8 77.4 74.0 75391650007 Ohio Warren 87.7 89.0 79.0 80.1 76.6 77391670004 Ohio Washington 82.7 85.0 75.2 77.2 73.8 75391730003 Ohio Wood 80.0 83.0 73.4 76.2 71.6 74400170101 Oklahoma Canadian 76.0 76.0 71.1 71.1 68.5 68400219002 Oklahoma Cherokee 75.7 76.0 72.1 72.3 70.5 70400270049 Oklahoma Cleveland 74.7 75.0 69.1 69.4 66.7 67400310647 Oklahoma Comanche 77.5 78.0 71.3 71.7 68.8 69400370144 Oklahoma Creek 76.7 77.0 70.7 71.0 68.6 68400719010 Oklahoma Kay 78.0 79.0 72.7 73.6 70.6 71400871073 Oklahoma McClain 72.0 72.0 66.4 66.4 64.0 64400979014 Oklahoma Mayes 78.5 79.0 75.0 75.4 73.6 74401090033 Oklahoma Oklahoma 77.0 77.0 72.3 72.3 70.3 70401090096 Oklahoma Oklahoma 76.3 78.0 71.1 72.7 68.9 70401091037 Oklahoma Oklahoma 80.0 81.0 73.5 74.4 70.6 71401159004 Oklahoma Ottawa 78.0 79.0 72.9 73.9 71.4 72
B-22

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

401210415 Oklahoma Pittsburg 72.0 73.0 67.6 68.5 65.9 66401430137 Oklahoma Tulsa 79.3 80.0 73.1 73.7 70.7 71401430174 Oklahoma Tulsa 74.0 76.0 68.9 70.8 67.0 68401430178 Oklahoma Tulsa 79.3 80.0 74.4 75.1 72.5 73401431127 Oklahoma Tulsa 77.0 78.0 71.6 72.5 69.3 70420010002 Pennsylvania Adams 76.3 78.0 65.8 67.3 63.7 65420030008 Pennsylvania Allegheny 79.3 81.0 73.5 75.1 72.4 74420030010 Pennsylvania Allegheny 82.3 84.0 76.3 77.9 75.2 76420030067 Pennsylvania Allegheny 80.3 82.0 73.3 74.8 72.0 73420031005 Pennsylvania Allegheny 83.7 87.0 75.4 78.4 73.9 76420050001 Pennsylvania Armstrong 83.0 84.0 73.9 74.8 72.2 73420070002 Pennsylvania Beaver 83.0 84.0 74.6 75.5 73.2 74420070005 Pennsylvania Beaver 79.3 81.0 71.6 73.1 70.2 71420070014 Pennsylvania Beaver 74.0 75.0 66.6 67.5 65.4 66420110009 Pennsylvania Berks 76.0 80.0 67.8 71.4 65.9 69420130801 Pennsylvania Blair 74.3 77.0 66.1 68.5 64.6 66420170012 Pennsylvania Bucks 88.0 92.0 81.8 85.6 79.9 83420210011 Pennsylvania Cambria 74.7 77.0 67.0 69.0 65.3 67420270100 Pennsylvania Centre 78.3 79.0 69.4 70.0 67.4 68420290100 Pennsylvania Chester 86.0 87.0 75.1 76.0 73.0 73420334000 Pennsylvania Clearfield 78.3 82.0 69.4 72.7 67.8 71420430401 Pennsylvania Dauphin 79.3 81.0 72.2 73.8 70.5 72420431100 Pennsylvania Dauphin 79.3 81.0 72.4 73.9 70.6 72420450002 Pennsylvania Delaware 83.3 85.0 75.5 77.1 73.8 75420490003 Pennsylvania Erie 81.3 83.0 73.9 75.5 72.0 73420550001 Pennsylvania Franklin 72.3 75.0 62.8 65.1 60.6 62420590002 Pennsylvania Greene 80.0 81.0 73.4 74.3 72.3 73420630004 Pennsylvania Indiana 80.0 80.0 71.1 71.1 69.5 69420690101 Pennsylvania Lackawanna 74.3 75.0 66.0 66.6 64.1 64420692006 Pennsylvania Lackawanna 75.3 76.0 66.8 67.4 64.8 65
B-23

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

420710007 Pennsylvania Lancaster 83.3 84.0 74.3 74.9 72.3 72420730015 Pennsylvania Lawrence 72.3 73.0 64.4 65.1 62.9 63420770004 Pennsylvania Lehigh 83.3 85.0 74.7 76.3 72.5 74420791100 Pennsylvania Luzerne 69.3 73.0 61.8 65.1 60.0 63420791101 Pennsylvania Luzerne 76.3 77.0 67.9 68.5 65.9 66420810100 Pennsylvania Lycoming 77.3 79.0 68.7 70.2 66.7 68420850100 Pennsylvania Mercer 82.0 83.0 74.0 74.9 72.3 73420910013 Pennsylvania Montgomery 85.7 86.0 79.1 79.4 77.5 77420950025 Pennsylvania Northampton 84.3 87.0 75.4 77.9 73.2 75420958000 Pennsylvania Northampton 80.0 82.0 71.4 73.2 69.2 70420990301 Pennsylvania Perry 77.0 78.0 69.2 70.1 67.1 68421010004 Pennsylvania Philadelphia 64.3 68.0 61.0 64.5 59.8 63421010014 Pennsylvania Philadelphia 79.7 81.0 76.0 77.3 74.9 76421010024 Pennsylvania Philadelphia 90.3 91.0 85.3 86.0 83.6 84421010136 Pennsylvania Philadelphia 77.0 77.0 71.3 71.3 70.1 70421174000 Pennsylvania Tioga 77.7 81.0 68.8 71.8 66.9 69421250005 Pennsylvania Washington 78.3 80.0 71.5 73.1 70.3 71421250200 Pennsylvania Washington 77.3 81.0 70.1 73.5 68.8 72421255001 Pennsylvania Washington 78.0 78.0 70.0 70.0 68.5 68421290006 Pennsylvania Westmoreland 78.3 80.0 72.2 73.7 70.9 72421290008 Pennsylvania Westmoreland 79.0 82.0 72.1 74.8 70.6 73421330008 Pennsylvania York 82.0 83.0 73.6 74.5 71.7 72440030002 Rhode Island Kent 84.3 86.0 75.4 77.0 73.3 74440071010 Rhode Island Providence 82.3 84.0 73.5 75.0 71.3 72440090007 Rhode Island Washington 86.0 89.0 77.2 79.9 75.2 77450010001 South Carolina Abbeville 79.0 81.0 69.1 70.8 66.1 67450030003 South Carolina Aiken 76.0 77.0 66.4 67.3 63.3 64450070003 South Carolina Anderson 76.5 78.0 66.7 68.1 63.8 65450110001 South Carolina Barnwell 73.0 73.0 65.0 65.0 61.9 61450150002 South Carolina Berkeley 67.3 70.0 60.3 62.7 58.5 60
B-24

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

450190046 South Carolina Charleston 74.0 75.0 67.2 68.1 65.0 65450210002 South Carolina Cherokee 74.0 75.0 63.8 64.7 61.1 61450230002 South Carolina Chester 75.7 76.0 66.1 66.4 63.5 63450250001 South Carolina Chesterfield 75.0 75.0 65.8 65.8 63.4 63450290002 South Carolina Colleton 72.3 74.0 65.6 67.2 63.0 64450310003 South Carolina Darlington 76.3 77.0 67.0 67.7 64.6 65450370001 South Carolina Edgefield 70.0 70.0 61.0 61.0 58.1 58450730001 South Carolina Oconee 73.0 76.0 63.4 66.0 60.4 62450770002 South Carolina Pickens 78.7 81.0 68.0 70.0 64.8 66450790007 South Carolina Richland 80.3 82.0 69.9 71.3 66.5 67450790021 South Carolina Richland 72.7 73.0 61.7 61.9 58.7 58450791001 South Carolina Richland 82.3 83.0 71.6 72.2 68.1 68450830009 South Carolina Spartanburg 82.3 83.0 71.5 72.1 68.6 69450870001 South Carolina Union 76.0 77.0 66.7 67.6 64.1 64450890001 South Carolina Williamsburg 69.3 70.0 62.3 62.9 60.2 60450910006 South Carolina York 76.7 79.0 67.2 69.2 64.5 66470010101 Tennessee Anderson 77.3 80.0 66.2 68.5 63.2 65470090101 Tennessee Blount 85.3 86.0 73.4 74.0 70.0 70470090102 Tennessee Blount 68.5 70.0 59.6 60.9 57.0 58470370011 Tennessee Davidson 68.7 72.0 60.7 63.6 58.4 61470370026 Tennessee Davidson 77.7 79.0 68.5 69.6 65.8 66470651011 Tennessee Hamilton 80.0 83.0 70.6 73.2 66.8 69470654003 Tennessee Hamilton 81.0 84.0 71.6 74.2 67.8 70470890002 Tennessee Jefferson 82.3 84.0 71.3 72.8 68.0 69470930021 Tennessee Knox 78.7 81.0 68.3 70.3 65.1 67470931020 Tennessee Knox 85.0 88.0 74.0 76.6 70.7 73471050109 Tennessee Loudon 83.0 85.0 70.6 72.3 67.5 69471210104 Tennessee Meigs 80.0 81.0 70.1 71.0 66.3 67471490101 Tennessee Rutherford 76.3 80.0 66.1 69.3 63.2 66471550101 Tennessee Sevier 79.0 82.0 68.7 71.3 65.8 68
B-25

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

471550102 Tennessee Sevier 80.7 83.0 70.6 72.6 67.6 69471570021 Tennessee Shelby 80.0 82.0 71.0 72.8 68.5 70471571004 Tennessee Shelby 80.7 81.0 70.5 70.8 67.8 68471632002 Tennessee Sullivan 80.3 83.0 74.1 76.6 72.3 74471632003 Tennessee Sullivan 80.0 83.0 73.7 76.5 72.0 74471650007 Tennessee Sumner 83.0 84.0 73.0 73.9 70.1 70471650101 Tennessee Sumner 79.0 82.0 68.0 70.6 65.1 67471870106 Tennessee Williamson 75.3 77.0 65.2 66.7 62.3 63471890103 Tennessee Wilson 78.7 82.0 67.9 70.7 64.9 67480290032 Texas Bexar 82.0 85.0 76.3 79.1 74.0 76480290052 Texas Bexar 85.0 87.0 79.7 81.6 77.5 79480391004 Texas Brazoria 94.7 97.0 88.8 91.0 87.0 89480391016 Texas Brazoria 80.0 85.0 74.0 78.6 72.4 77480850005 Texas Collin 90.3 92.0 81.4 83.0 78.4 79481130069 Texas Dallas 87.0 90.0 82.9 85.8 80.5 83481130075 Texas Dallas 88.3 90.0 82.9 84.5 80.3 81481130087 Texas Dallas 87.0 88.0 84.6 85.6 82.3 83481133003 Texas Dallas 78.5 84.0 73.1 78.2 70.9 75481210034 Texas Denton 94.0 95.0 83.2 84.1 79.9 80481390015 Texas Ellis 81.7 84.0 73.8 75.9 70.9 72481410029 Texas El Paso 74.7 77.0 70.6 72.7 70.2 72481410037 Texas El Paso 77.7 79.0 73.9 75.1 73.2 74481410044 Texas El Paso 73.0 74.0 69.4 70.4 68.8 69481410055 Texas El Paso 76.0 77.0 72.3 73.2 71.6 72481410057 Texas El Paso 75.0 76.0 70.5 71.5 70.0 71481410058 Texas El Paso 74.3 75.0 70.4 71.0 69.8 70481670014 Texas Galveston 80.3 87.0 75.1 81.4 73.6 79481830001 Texas Gregg 84.3 85.0 78.3 79.0 76.8 77482010024 Texas Harris 88.0 92.0 83.3 87.1 82.2 85482010026 Texas Harris 85.7 89.0 80.6 83.7 79.1 82
B-26

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

482010029 Texas Harris 91.7 93.0 84.4 85.6 82.3 83482010046 Texas Harris 78.7 82.0 74.5 77.6 73.5 76482010047 Texas Harris 78.7 80.0 75.8 77.0 74.8 76482010051 Texas Harris 93.0 98.0 88.4 93.1 86.6 91482010055 Texas Harris 100.7 103.0 95.7 97.9 93.8 95482010062 Texas Harris 95.7 99.0 90.5 93.7 89.0 92482010066 Texas Harris 92.3 96.0 89.9 93.5 88.8 92482010070 Texas Harris 84.3 88.0 81.3 84.8 80.2 83482010075 Texas Harris 83.3 88.0 80.3 84.8 79.3 83482011015 Texas Harris 89.0 96.0 83.7 90.3 82.1 88482011034 Texas Harris 82.7 87.0 78.6 82.7 77.7 81482011035 Texas Harris 86.3 95.0 82.0 90.3 81.1 89482011039 Texas Harris 96.3 100.0 90.5 93.9 88.9 92482011050 Texas Harris 89.3 92.0 83.9 86.5 82.5 85482030002 Texas Harrison 79.0 80.0 70.9 71.8 68.5 69482210001 Texas Hood 83.0 84.0 72.7 73.6 69.4 70482311006 Texas Hunt 78.0 79.0 69.9 70.8 67.8 68482450009 Texas Jefferson 81.7 82.0 75.6 75.9 74.0 74482450011 Texas Jefferson 80.0 81.0 74.8 75.7 73.2 74482450018 Texas Jefferson 83.3 84.0 77.4 78.0 75.8 76482450022 Texas Jefferson 79.7 81.0 73.5 74.7 71.8 72482450101 Texas Jefferson 84.7 88.0 79.7 82.8 78.1 81482450628 Texas Jefferson 78.0 78.0 72.9 72.9 71.3 71482510003 Texas Johnson 87.0 89.0 76.4 78.2 73.2 74482570005 Texas Kaufman 74.7 76.0 68.1 69.3 65.9 67483390078 Texas Montgomery 85.0 86.0 77.8 78.8 75.5 76483550025 Texas Nueces 72.3 75.0 68.3 70.9 67.2 69483611001 Texas Orange 78.0 80.0 72.3 74.1 70.8 72483611100 Texas Orange 73.0 74.0 67.2 68.2 65.9 66483670081 Texas Parker 88.7 91.0 76.0 78.0 72.6 74
B-27

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

483970001 Texas Rockwall 79.7 81.0 73.3 74.5 70.9 72484230007 Texas Smith 81.0 82.0 74.5 75.4 72.4 73484390075 Texas Tarrant 95.3 96.0 84.2 84.8 80.9 81484391002 Texas Tarrant 93.3 95.0 85.1 86.7 82.1 83484392003 Texas Tarrant 93.7 95.0 84.0 85.2 80.9 82484393009 Texas Tarrant 92.7 93.0 84.3 84.5 81.2 81484393011 Texas Tarrant 86.0 87.0 79.6 80.5 77.0 77484530014 Texas Travis 81.3 82.0 73.6 74.3 71.1 71484530020 Texas Travis 79.3 81.0 71.7 73.2 69.2 70484530613 Texas Travis 76.0 76.0 69.3 69.3 67.6 67500030004 Vermont Bennington 72.0 73.0 63.9 64.8 61.9 62500070007 Vermont Chittenden 69.7 71.0 63.2 64.4 61.6 62510130020 Virginia Arlington 86.7 87.0 81.8 82.0 80.0 80510330001 Virginia Caroline 80.0 81.0 69.3 70.1 66.7 67510360002 Virginia Charles 80.3 82.0 71.2 72.7 69.2 70510410004 Virginia Chesterfield 76.7 77.0 68.0 68.2 66.1 66510590005 Virginia Fairfax 78.3 79.0 70.5 71.1 68.3 68510590018 Virginia Fairfax 90.0 91.0 83.2 84.1 81.3 82510590030 Virginia Fairfax 88.0 89.0 81.4 82.3 79.6 80510591005 Virginia Fairfax 85.7 87.0 79.3 80.5 77.5 78510595001 Virginia Fairfax 82.0 84.0 76.0 77.8 74.1 75510610002 Virginia Fauquier 72.7 73.0 62.4 62.7 60.1 60510690010 Virginia Frederick 72.3 73.0 63.6 64.2 61.6 62510850003 Virginia Hanover 81.3 82.0 71.4 72.0 69.1 69510870014 Virginia Henrico 82.0 85.0 72.6 75.3 70.4 73511071005 Virginia Loudoun 80.7 82.0 72.8 74.0 70.6 71511130003 Virginia Madison 77.7 80.0 68.0 70.0 65.8 67511390004 Virginia Page 74.0 76.0 64.9 66.7 62.9 64511530009 Virginia Prince William 78.7 79.0 70.0 70.3 67.7 68511611004 Virginia Roanoke 74.7 76.0 67.4 68.5 64.9 66
B-28

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

511630003 Virginia Rockbridge 69.7 71.0 62.0 63.1 59.7 60511790001 Virginia Stafford 81.7 85.0 72.0 74.9 69.5 72511970002 Virginia Wythe 72.7 75.0 63.8 65.8 61.3 63515100009 Virginia Alexandria City 81.7 83.0 75.5 76.7 73.8 75516500004 Virginia Hampton City 76.7 78.0 71.7 72.9 70.5 71518000004 Virginia Suffolk City 76.7 78.0 71.9 73.1 70.8 72518000005 Virginia Suffolk City 75.3 77.0 66.8 68.3 64.7 66540030003 West Virginia Berkeley 75.0 76.0 66.4 67.3 64.2 65540110006 West Virginia Cabell 78.7 84.0 70.9 75.7 69.3 73540291004 West Virginia Hancock 75.7 77.0 66.8 68.0 65.6 66540390010 West Virginia Kanawha 77.3 79.0 66.3 67.7 64.6 66540610003 West Virginia Monongalia 75.3 78.0 71.4 74.0 70.2 72540690010 West Virginia Ohio 78.3 82.0 69.3 72.5 68.0 71541071002 West Virginia Wood 79.0 82.0 70.3 73.0 69.0 71550090026 Wisconsin Brown 73.7 75.0 67.7 68.9 66.0 67550210015 Wisconsin Columbia 72.7 74.0 65.7 66.9 64.1 65550250041 Wisconsin Dane 72.0 74.0 65.6 67.4 64.0 65550270007 Wisconsin Dodge 74.7 77.0 68.4 70.5 66.5 68550290004 Wisconsin Door 88.7 90.0 80.5 81.7 78.2 79550370001 Wisconsin Florence 66.3 68.0 60.5 62.1 59.1 60550390006 Wisconsin Fond du Lac 73.7 75.0 68.1 69.3 66.3 67550410007 Wisconsin Forest 69.5 71.0 63.3 64.7 61.8 63550550002 Wisconsin Jefferson 74.3 76.0 68.0 69.5 66.0 67550590019 Wisconsin Kenosha 84.7 86.0 81.3 82.5 79.9 81550610002 Wisconsin Kewaunee 82.7 86.0 75.4 78.4 73.4 76550710007 Wisconsin Manitowoc 85.0 87.0 78.0 79.8 75.9 77550790010 Wisconsin Milwaukee 69.3 70.0 65.6 66.2 64.1 64550790026 Wisconsin Milwaukee 76.0 77.0 71.9 72.9 70.3 71550790041 Wisconsin Milwaukee 81.3 83.0 77.0 78.6 75.2 76550790044 Wisconsin Milwaukee 71.0 71.0 69.9 69.9 68.9 68
B-29

8-Hour Ozone Design Values (ppb

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

550790085 Wisconsin Milwaukee 82.7 86.0 78.0 81.1 76.2 79550870009 Wisconsin Outagamie 74.0 75.0 67.9 68.8 66.2 67550890008 Wisconsin Ozaukee 81.3 85.0 76.3 79.8 74.6 77550890009 Wisconsin Ozaukee 83.3 88.0 77.6 81.9 75.5 79551010017 Wisconsin Racine 80.3 82.0 76.3 77.9 74.8 76551050024 Wisconsin Rock 74.0 76.0 67.2 69.1 65.3 67551091002 Wisconsin St. Croix 69.0 71.0 64.1 66.0 62.8 64551110007 Wisconsin Sauk 69.7 71.0 62.9 64.1 61.6 62551170006 Wisconsin Sheboygan 88.0 89.0 80.8 81.8 78.6 79551270005 Wisconsin Walworth 75.7 77.0 69.0 70.2 67.0 68551310009 Wisconsin Washington 72.3 75.0 67.1 69.7 65.2 67551330017 Wisconsin Waukesha 75.0 75.0 69.2 69.2 67.3 67551330027 Wisconsin Waukesha 71.5 72.0 66.0 66.5 64.2 64
B-30

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

10030010 Alabama Baldwin 11.44 11.75 10.81 11.11 10.46 10.10270001 Alabama Clay 13.21 13.32 12.00 12.11 11.32 11.10331002 Alabama Colbert 12.67 12.88 12.13 12.33 11.65 11.10491003 Alabama DeKalb 14.09 14.42 12.75 13.06 12.14 12.10530002 Alabama Escambia 13.12 13.18 12.55 12.61 12.21 12.10550010 Alabama Etowah 14.80 15.01 13.45 13.64 12.76 12.10690003 Alabama Houston 12.86 12.86 12.10 12.10 11.73 11.10730023 Alabama Jefferson 18.48 18.67 17.15 17.32 16.48 16.10731005 Alabama Jefferson 15.36 15.60 14.27 14.50 13.67 13.10731009 Alabama Jefferson 13.42 13.74 12.58 12.89 12.04 12.10731010 Alabama Jefferson 15.76 15.92 14.37 14.53 13.66 13.10732003 Alabama Jefferson 17.07 17.45 15.99 16.35 15.42 15.10732006 Alabama Jefferson 15.00 15.13 13.90 14.02 13.31 13.10735002 Alabama Jefferson 14.33 14.59 13.12 13.36 12.47 12.10735003 Alabama Jefferson 14.43 14.58 13.34 13.48 12.69 12.10890014 Alabama Madison 13.73 13.85 12.86 12.98 12.26 12.10970002 Alabama Mobile 12.90 12.90 12.33 12.33 11.90 11.10970003 Alabama Mobile 12.36 12.49 11.80 11.92 11.38 11.10972005 Alabama Mobile 11.51 11.92 10.88 11.27 10.51 10.11010007 Alabama Montgomery 14.14 14.22 13.27 13.33 12.75 12.11030011 Alabama Morgan 13.23 13.47 12.47 12.69 11.91 12.11130001 Alabama Russell 15.63 15.83 14.51 14.68 13.83 14.11170006 Alabama Shelby 14.28 14.32 13.17 13.21 12.55 12.11190002 Alabama Sumter 11.92 11.92 11.33 11.33 10.87 10.11210002 Alabama Talladega 14.51 14.51 13.03 13.03 12.38 12.11250004 Alabama Tuscaloosa 13.44 13.56 12.63 12.74 12.07 12.11270002 Alabama Walker 13.77 14.05 12.90 13.16 12.28 12.50010011 Arkansas Arkansas 12.45 12.54 12.24 12.33 11.80 11.50030005 Arkansas Ashley 12.83 13.30 12.58 13.04 12.23 12.50350005 Arkansas Crittenden 13.27 13.27 12.93 12.93 12.32 12.
B-31

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

50450002 Arkansas Faulkner 12.79 13.10 12.57 12.87 12.13 12.50510003 Arkansas Garland 12.40 12.67 12.12 12.37 11.72 11.50930007 Arkansas Mississippi 12.61 12.61 12.51 12.51 12.00 12.51070001 Arkansas Phillips 12.08 12.33 11.84 12.08 11.33 11.51130002 Arkansas Polk 11.65 12.04 11.26 11.64 10.96 11.51150003 Arkansas Pope 12.79 13.14 12.52 12.86 12.14 12.51190007 Arkansas Pulaski 13.17 13.27 12.84 12.93 12.37 12.51191004 Arkansas Pulaski 14.05 14.23 13.71 13.89 13.24 13.51191005 Arkansas Pulaski 13.59 13.62 13.24 13.28 12.78 12.51390006 Arkansas Union 12.86 13.09 12.55 12.77 12.19 12.51450001 Arkansas White 12.57 12.74 12.40 12.56 11.98 12.80010006 Colorado Adams 10.06 10.16 9.63 9.73 9.44 9.580050005 Colorado Arapahoe 7.96 8.10 7.64 7.77 7.48 7.680130003 Colorado Boulder 8.32 8.54 7.91 8.13 7.80 8.080130012 Colorado Boulder 6.96 7.06 6.67 6.77 6.58 6.680290004 Colorado Delta 7.44 7.62 6.97 7.14 6.86 7.080310002 Colorado Denver 9.37 9.74 8.97 9.32 8.79 9.180310023 Colorado Denver 9.76 9.76 9.34 9.34 9.16 9.180390001 Colorado Elbert 4.40 4.54 4.23 4.37 4.18 4.380410008 Colorado El Paso 6.73 6.73 6.34 6.34 6.24 6.280410011 Colorado El Paso 7.94 8.11 7.49 7.65 7.38 7.580690009 Colorado Larimer 7.33 7.40 7.02 7.09 6.94 7.080770017 Colorado Mesa 9.28 9.48 8.78 8.97 8.65 8.881010012 Colorado Pueblo 7.45 7.65 7.08 7.28 7.00 7.181130004 Colorado San Miguel 4.65 4.81 4.48 4.64 4.46 4.681230006 Colorado Weld 8.19 8.35 7.73 7.89 7.62 7.781230008 Colorado Weld 8.78 9.28 8.31 8.77 8.19 8.690010010 Connecticut Fairfield 13.18 13.18 12.36 12.36 12.18 12.90011123 Connecticut Fairfield 12.49 12.59 11.68 11.77 11.50 11.90013005 Connecticut Fairfield 12.43 12.72 11.65 11.92 11.48 11.
B-32

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

90019003 Connecticut Fairfield 11.48 11.73 10.75 10.97 10.59 10.90031003 Connecticut Hartford 11.03 11.36 10.28 10.58 10.11 10.90050005 Connecticut Litchfield 8.01 8.01 7.47 7.47 7.36 7.390090026 Connecticut New Haven 12.12 12.13 11.32 11.33 11.14 11.90090027 Connecticut New Haven 12.45 12.57 11.60 11.71 11.41 11.90091123 Connecticut New Haven 13.12 13.54 12.26 12.65 12.05 12.90092008 Connecticut New Haven 11.17 11.22 10.41 10.45 10.24 10.90092123 Connecticut New Haven 12.74 12.91 11.91 12.06 11.72 11.90113002 Connecticut New London 10.96 11.33 10.18 10.52 10.03 10.

100010002 Delaware Kent 12.61 12.84 11.60 11.82 11.47 11.100010003 Delaware Kent 12.52 12.66 11.58 11.72 11.43 11.100031003 Delaware New Castle 13.73 14.33 12.71 13.26 12.52 13.100031007 Delaware New Castle 12.92 13.41 11.83 12.29 11.69 12.100031012 Delaware New Castle 13.69 13.88 12.58 12.75 12.42 12.100032004 Delaware New Castle 14.87 15.11 13.81 14.03 13.61 13.100051002 Delaware Sussex 13.39 13.45 12.25 12.31 12.11 12.110010041 

District Of Columbia 

District of Columbia 14.16 14.38 12.96 13.16 12.78 12.

110010042 

District Of Columbia 

District of Columbia 14.41 14.52 13.14 13.24 12.97 13.

110010043 

District Of Columbia 

District of Columbia 13.99 14.44 12.80 13.23 12.63 13.

120010023 Florida Alachua 9.32 9.51 8.49 8.66 8.26 8.4120010024 Florida Alachua 9.59 9.64 8.75 8.80 8.52 8.5120051004 Florida Bay 11.46 11.69 10.69 10.89 10.39 10.120090007 Florida Brevard 8.32 8.64 7.63 7.93 7.46 7.7120111002 Florida Broward 8.22 8.30 7.77 7.85 7.64 7.7120112004 Florida Broward 8.18 8.28 7.68 7.77 7.55 7.6120113002 Florida Broward 8.21 8.21 7.76 7.76 7.63 7.6120170005 Florida Citrus 9.00 9.14 7.96 8.07 7.77 7.8120310098 Florida Duval 9.90 9.99 9.14 9.24 8.90 9.0
B-33

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

120310099 Florida Duval 10.44 10.53 9.75 9.82 9.52 9.5120330004 Florida Escambia 11.72 11.91 11.20 11.37 10.94 11.120570030 Florida Hillsborough 10.74 10.95 9.50 9.68 9.31 9.4120573002 Florida Hillsborough 10.52 10.75 9.34 9.55 9.16 9.3120710005 Florida Lee 8.36 8.41 7.51 7.56 7.39 7.4120730012 Florida Leon 12.56 12.71 11.56 11.69 11.25 11.120814012 Florida Manatee 8.81 8.91 7.61 7.70 7.51 7.5120830003 Florida Marion 10.11 10.20 9.17 9.25 8.94 9.0120861016 Florida Miami-Dade 9.45 9.54 8.93 9.01 8.77 8.8120866001 Florida Miami-Dade 8.14 8.28 7.68 7.81 7.59 7.7120951004 Florida Orange 9.61 9.76 8.73 8.87 8.46 8.5120952002 Florida Orange 9.50 9.60 8.60 8.69 8.34 8.4120990009 Florida Palm Beach 7.84 7.84 7.28 7.28 7.14 7.1120992005 Florida Palm Beach 7.70 7.81 7.22 7.31 7.08 7.1121030018 Florida Pinellas 9.82 9.85 8.65 8.67 8.52 8.5121031009 Florida Pinellas 9.52 9.69 8.39 8.54 8.24 8.3121056006 Florida Polk 9.55 9.65 8.48 8.57 8.34 8.4121111002 Florida St. Lucie 8.34 8.47 7.66 7.78 7.54 7.6121150013 Florida Sarasota 8.77 8.86 7.69 7.77 7.58 7.6121171002 Florida Seminole 9.51 9.64 8.62 8.73 8.35 8.4121275002 Florida Volusia 9.27 9.34 8.47 8.53 8.22 8.2130210007 Georgia Bibb 16.47 16.78 15.33 15.61 14.52 14.130210012 Georgia Bibb 13.87 14.17 12.90 13.18 12.07 12.130510017 Georgia Chatham 13.70 13.87 12.79 12.94 12.38 12.130510091 Georgia Chatham 13.88 14.11 12.98 13.19 12.55 12.130590002 Georgia Clarke 14.90 14.90 13.83 13.83 12.94 12.130630091 Georgia Clayton 16.47 16.71 15.07 15.29 14.12 14.130670003 Georgia Cobb 16.09 16.19 14.63 14.72 13.86 13.130670004 Georgia Cobb 15.36 15.50 13.96 14.08 13.10 13.130890002 Georgia DeKalb 15.46 15.66 14.13 14.31 13.16 13.
B-34

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

130892001 Georgia DeKalb 15.33 15.56 13.97 14.19 13.07 13.130950007 Georgia Dougherty 14.35 14.53 13.56 13.73 13.14 13.131150005 Georgia Floyd 16.10 16.15 14.61 14.67 14.01 14.131210032 Georgia Fulton 15.81 16.02 14.44 14.63 13.48 13.131210039 Georgia Fulton 17.43 17.47 16.01 16.04 15.03 15.131270006 Georgia Glynn 12.18 12.30 11.38 11.50 11.10 11.131350002 Georgia Gwinnett 16.07 16.36 14.72 14.99 13.87 14.131390003 Georgia Hall 14.12 14.37 12.97 13.21 12.21 12.131530001 Georgia Houston 13.99 14.25 12.95 13.18 12.27 12.131850003 Georgia Lowndes 12.49 12.83 11.70 12.01 11.38 11.132150001 Georgia Muscogee 14.86 14.98 13.76 13.87 13.10 13.132150008 Georgia Muscogee 15.16 15.16 14.07 14.07 13.40 13.132150011 Georgia Muscogee 14.07 14.30 13.07 13.28 12.47 12.132230003 Georgia Paulding 14.08 14.30 12.58 12.77 11.85 12.132450005 Georgia Richmond 15.61 15.82 14.67 14.87 14.10 14.132450091 Georgia Richmond 15.68 15.88 14.76 14.95 14.18 14.132950002 Georgia Walker 15.49 15.75 14.39 14.63 13.76 13.133030001 Georgia Washington 15.14 15.54 14.36 14.73 13.44 13.133190001 Georgia Wilkinson 15.23 15.50 14.32 14.57 13.37 13.170010006 Illinois Adams 12.50 12.87 12.21 12.57 11.70 12.170190004 Illinois Champaign 12.50 12.89 12.25 12.63 11.70 12.170191001 Illinois Champaign 12.53 12.92 12.32 12.70 11.75 12.170310022 Illinois Cook 15.21 15.55 14.70 15.04 14.22 14.170310050 Illinois Cook 14.81 15.22 14.32 14.71 13.82 14.170310052 Illinois Cook 15.75 16.02 15.16 15.42 14.64 14.170310057 Illinois Cook 15.03 15.34 14.50 14.79 13.98 14.170310076 Illinois Cook 14.89 15.18 14.41 14.68 13.87 14.170312001 Illinois Cook 14.77 15.14 14.28 14.63 13.80 14.170313301 Illinois Cook 15.24 15.59 14.73 15.06 14.20 14.170314007 Illinois Cook 12.78 13.15 12.45 12.80 11.92 12.
B-35

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

170314201 Illinois Cook 12.76 13.18 12.44 12.86 11.91 12.170316005 Illinois Cook 15.48 16.07 14.92 15.48 14.40 14.170434002 Illinois DuPage 13.82 14.01 13.51 13.69 12.95 13.170831001 Illinois Jersey 12.89 13.20 13.05 13.37 12.41 12.170890003 Illinois Kane 13.32 13.54 12.94 13.15 12.36 12.170890007 Illinois Kane 14.34 14.34 13.95 13.95 13.39 13.170971007 Illinois Lake 11.81 12.10 11.57 11.86 11.06 11.171110001 Illinois McHenry 12.40 12.47 12.08 12.15 11.53 11.171132003 Illinois McLean 12.39 12.39 12.26 12.26 11.61 11.171150013 Illinois Macon 13.24 13.57 13.11 13.43 12.50 12.171191007 Illinois Madison 16.72 17.01 16.56 16.85 15.90 16.171192009 Illinois Madison 14.01 14.66 14.20 14.85 13.57 14.171193007 Illinois Madison 14.32 14.45 14.48 14.62 13.87 14.171430037 Illinois Peoria 13.34 13.66 13.43 13.76 12.47 12.171570001 Illinois Randolph 13.11 13.64 13.07 13.58 12.44 12.171613002 Illinois Rock Island 12.01 12.31 11.69 11.99 11.19 11.171630010 Illinois Saint Clair 15.58 15.74 15.48 15.63 14.83 14.171634001 Illinois Saint Clair 14.29 14.49 14.21 14.41 13.57 13.171670012 Illinois Sangamon 13.13 13.29 13.37 13.55 12.79 12.171971002 Illinois Will 13.63 14.05 13.33 13.74 12.79 13.171971011 Illinois Will 11.52 11.78 11.26 11.51 10.77 11.172010013 Illinois Winnebago 13.57 13.57 13.10 13.10 12.61 12.180030004 Indiana Allen 13.67 14.08 13.18 13.58 12.81 13.180030014 Indiana Allen 13.55 13.91 13.07 13.42 12.70 13.180190006 Indiana Clark 16.40 16.60 15.96 16.16 15.46 15.180350006 Indiana Delaware 13.66 13.81 13.43 13.58 13.00 13.180372001 Indiana Dubois 15.18 15.68 15.07 15.57 14.50 14.180431004 Indiana Floyd 14.80 14.94 14.50 14.64 14.04 14.180650003 Indiana Henry 13.64 13.64 13.52 13.52 13.08 13.180670003 Indiana Howard 13.93 14.29 13.66 14.01 13.18 13.
B-36

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

180830004 Indiana Knox 14.03 14.21 13.94 14.11 13.33 13.180890006 Indiana Lake 14.27 14.51 13.83 14.06 13.35 13.180890027 Indiana Lake 13.83 14.13 13.44 13.73 12.97 13.180891003 Indiana Lake 14.02 14.25 13.61 13.84 13.15 13.180892004 Indiana Lake 14.05 14.41 13.66 14.01 13.19 13.180892010 Indiana Lake 13.89 14.10 13.47 13.67 12.99 13.180910011 Indiana LaPorte 12.49 12.84 12.03 12.36 11.60 11.180910012 Indiana LaPorte 12.69 13.07 12.23 12.60 11.79 12.180950009 Indiana Madison 13.96 14.37 13.80 14.21 13.35 13.180970042 Indiana Marion 14.24 14.51 14.26 14.53 13.78 14.180970078 Indiana Marion 15.26 15.43 15.18 15.35 14.69 14.180970079 Indiana Marion 14.71 14.99 14.61 14.89 14.12 14.180970081 Indiana Marion 16.05 16.36 15.93 16.24 15.43 15.180970083 Indiana Marion 15.90 16.27 15.77 16.15 15.27 15.181270020 Indiana Porter 12.66 13.01 12.18 12.52 11.73 12.181270024 Indiana Porter 13.21 13.39 12.73 12.91 12.26 12.181410014 Indiana St. Joseph 13.28 13.65 12.79 13.14 12.45 12.181411008 Indiana St. Joseph 13.69 13.69 13.17 13.17 12.83 12.181412004 Indiana St. Joseph 12.82 13.22 12.36 12.74 12.02 12.181470009 Indiana Spencer 14.32 14.55 14.21 14.45 13.65 13.181570008 Indiana Tippecanoe 13.69 14.06 13.39 13.75 12.87 13.181630006 Indiana Vanderburgh 14.69 14.89 14.55 14.75 14.02 14.181630012 Indiana Vanderburgh 14.82 15.00 14.64 14.82 14.09 14.181630016 Indiana Vanderburgh 14.99 15.14 14.84 14.99 14.30 14.181670018 Indiana Vigo 13.99 14.17 13.51 13.68 12.95 13.181670023 Indiana Vigo 13.45 13.66 13.04 13.25 12.48 12.190130008 Iowa Black Hawk 11.16 11.52 10.68 11.03 10.37 10.190450021 Iowa Clinton 12.52 12.63 12.08 12.19 11.57 11.191032001 Iowa Johnson 12.08 12.26 11.64 11.81 11.28 11.191130037 Iowa Linn 10.79 10.95 10.37 10.52 10.03 10.
B-37

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

191370002 Iowa Montgomery 10.02 10.33 9.55 9.85 9.32 9.6191390015 Iowa Muscatine 12.92 13.29 12.53 12.90 12.15 12.191471002 Iowa Palo Alto 9.53 9.53 9.01 9.01 8.80 8.8191530030 Iowa Polk 10.41 10.54 9.87 10.00 9.59 9.7191532510 Iowa Polk 9.95 10.14 9.44 9.62 9.17 9.3191532520 Iowa Polk 10.64 10.64 10.08 10.08 9.79 9.7191550009 Iowa Pottawattamie 11.13 11.52 10.55 10.92 10.36 10.191630015 Iowa Scott 11.86 12.06 11.56 11.75 11.06 11.191630018 Iowa Scott 11.64 11.89 11.35 11.59 10.85 11.191630019 Iowa Scott 14.42 14.42 14.00 14.00 13.50 13.191770006 Iowa Van Buren 10.84 10.84 10.46 10.46 10.16 10.191930017 Iowa Woodbury 10.32 10.53 9.81 10.01 9.69 9.8191970004 Iowa Wright 10.37 10.51 9.84 9.97 9.57 9.6200910007 Kansas Johnson 10.59 10.86 10.09 10.35 9.81 10.200910009 Kansas Johnson 11.10 11.10 10.62 10.62 10.30 10.200910010 Kansas Johnson 9.68 9.74 9.28 9.34 9.01 9.0201070002 Kansas Linn 10.47 10.62 10.16 10.31 9.86 10.201730008 Kansas Sedgwick 10.26 10.85 9.72 10.28 9.49 10.201730009 Kansas Sedgwick 10.29 10.95 9.75 10.36 9.51 10.201730010 Kansas Sedgwick 10.36 10.96 9.81 10.38 9.57 10.201770010 Kansas Shawnee 10.79 10.79 10.27 10.27 10.04 10.201770011 Kansas Shawnee 10.93 10.93 10.42 10.42 10.19 10.201910002 Kansas Sumner 9.89 10.31 9.44 9.84 9.22 9.6202090021 Kansas Wyandotte 12.73 13.37 12.09 12.69 11.78 12.202090022 Kansas Wyandotte 10.93 11.25 10.41 10.70 10.11 10.210130002 Kentucky Bell 14.28 14.64 13.28 13.61 12.70 13.210190017 Kentucky Boyd 14.49 14.70 13.54 13.74 12.96 13.210290006 Kentucky Bullitt 14.90 15.21 14.58 14.88 14.07 14.210370003 Kentucky Campbell 13.67 13.67 13.30 13.30 12.81 12.210430500 Kentucky Carter 12.22 12.61 11.38 11.74 10.87 11.
B-38

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

210470006 Kentucky Christian 13.20 13.55 13.44 13.78 12.90 13.210590005 Kentucky Daviess 14.10 14.10 14.14 14.14 13.59 13.210670012 Kentucky Fayette 14.33 14.53 13.74 13.93 13.22 13.210670014 Kentucky Fayette 14.85 15.13 14.23 14.50 13.70 13.210730006 Kentucky Franklin 13.37 13.52 12.88 13.03 12.39 12.210930006 Kentucky Hardin 13.58 14.04 13.34 13.79 12.82 13.211010014 Kentucky Henderson 13.93 14.28 13.69 14.03 13.17 13.211110043 Kentucky Jefferson 15.53 15.75 15.19 15.41 14.71 14.211110044 Kentucky Jefferson 15.31 15.47 14.93 15.09 14.45 14.211110048 Kentucky Jefferson 15.25 15.32 14.87 14.93 14.38 14.211110051 Kentucky Jefferson 14.70 15.17 14.43 14.89 13.95 14.211170007 Kentucky Kenton 14.36 14.52 13.98 14.14 13.50 13.211250004 Kentucky Laurel 12.55 12.55 11.77 11.77 11.25 11.211451004 Kentucky McCracken 13.38 13.84 13.40 13.86 12.79 13.211510003 Kentucky Madison 13.61 13.70 12.94 13.03 12.43 12.211930003 Kentucky Perry 13.06 13.42 12.18 12.51 11.66 11.211950002 Kentucky Pike 13.46 13.89 12.48 12.87 11.94 12.212270007 Kentucky Warren 13.83 13.92 13.89 13.97 13.32 13.220171002 Louisiana Caddo 12.53 12.53 12.01 12.01 11.68 11.220190009 Louisiana Calcasieu 10.58 10.78 10.32 10.52 10.06 10.220190010 Louisiana Calcasieu 11.07 11.24 10.83 10.99 10.55 10.220290003 Louisiana Concordia 11.42 11.42 11.08 11.08 10.68 10.220330009 Louisiana 

East Baton Rouge 13.38 13.57 12.85 13.04 12.43 12.

220331001 Louisiana 

East Baton Rouge 12.08 12.18 11.62 11.70 11.23 11.

220470005 Louisiana Iberville 12.90 12.98 12.43 12.50 11.91 11.220470009 Louisiana Iberville 11.02 11.16 10.67 10.80 10.29 10.220511001 Louisiana Jefferson 11.52 11.68 11.02 11.17 10.65 10.220550006 Louisiana Lafayette 11.08 11.18 10.73 10.83 10.42 10.
B-39

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

220730004 Louisiana Ouachita 11.97 12.21 11.69 11.91 11.34 11.220790002 Louisiana Rapides 11.03 11.04 10.75 10.77 10.45 10.221050001 Louisiana Tangipahoa 12.03 12.39 11.50 11.85 11.09 11.221090001 Louisiana Terrebonne 10.74 10.83 10.37 10.45 10.03 10.221210001 Louisiana 

West Baton Rouge 13.51 13.68 12.98 13.15 12.55 12.

230010011 Maine Androscoggin 9.90 10.62 9.30 9.98 9.15 9.8230030013 Maine Aroostook 9.74 10.27 9.53 10.05 9.46 9.9230031011 Maine Aroostook 8.27 8.92 7.98 8.61 7.90 8.5230050015 Maine Cumberland 11.06 11.68 10.33 10.91 10.14 10.230050027 Maine Cumberland 11.13 11.53 10.40 10.78 10.22 10.230090103 Maine Hancock 5.76 6.17 5.39 5.77 5.33 5.7230110016 Maine Kennebec 9.99 10.70 9.37 10.04 9.23 9.8230172011 Maine Oxford 10.13 10.38 9.64 9.88 9.51 9.7230190002 Maine Penobscot 9.12 9.65 8.53 9.03 8.41 8.9240030014 Maryland Anne Arundel 11.91 11.91 10.78 10.78 10.76 10.240031003 Maryland Anne Arundel 14.82 15.26 13.63 14.03 13.73 14.240032002 Maryland Anne Arundel 14.57 14.57 13.38 13.38 13.50 13.240051007 Maryland Baltimore 13.77 14.04 12.61 12.85 12.56 12.240053001 Maryland Baltimore 14.76 15.05 13.50 13.78 13.56 13.240150003 Maryland Cecil 12.68 12.82 11.59 11.72 11.45 11.240251001 Maryland Harford 12.51 12.62 11.34 11.44 11.34 11.240313001 Maryland Montgomery 12.47 12.70 11.41 11.62 11.28 11.240330030 Maryland Prince George's 12.24 12.24 11.20 11.20 11.13 11.240338003 Maryland Prince George's 13.03 13.23 11.78 11.98 11.70 11.240430009 Maryland Washington 13.70 14.14 12.83 13.23 12.56 12.245100006 Maryland Baltimore (City) 14.12 14.37 12.92 13.15 12.96 13.245100007 Maryland Baltimore (City) 14.38 15.01 13.18 13.74 13.15 13.245100008 Maryland Baltimore (City) 15.76 15.87 14.47 14.57 14.57 14.245100049 Maryland Baltimore (City) 15.63 15.63 14.36 14.36 14.48 14.
B-40

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

250035001 Massachusetts Berkshire 10.65 11.15 10.05 10.52 9.90 10.250051004 Massachusetts Bristol 9.58 10.16 8.78 9.33 8.71 9.2250092006 Massachusetts Essex 9.03 9.09 8.31 8.37 8.21 8.2250095005 Massachusetts Essex 9.10 9.32 8.41 8.60 8.29 8.4250096001 Massachusetts Essex 9.58 9.74 8.87 9.02 8.74 8.8250130008 Massachusetts Hampden 9.85 10.14 9.22 9.49 9.08 9.3250130016 Massachusetts Hampden 12.17 12.52 11.41 11.73 11.22 11.250132009 Massachusetts Hampden 11.85 11.90 11.10 11.15 10.92 10.250230004 Massachusetts Plymouth 9.87 10.14 9.09 9.34 8.97 9.2250250002 Massachusetts Suffolk 12.34 13.00 11.48 12.09 11.32 11.250250027 Massachusetts Suffolk 11.86 12.27 10.99 11.38 10.84 11.250250042 Massachusetts Suffolk 10.88 11.36 10.08 10.53 9.95 10.250250043 Massachusetts Suffolk 13.07 13.88 12.16 12.92 11.98 12.250270016 Massachusetts Worcester 10.55 10.70 9.80 9.94 9.64 9.7250270023 Massachusetts Worcester 11.29 11.32 10.50 10.52 10.33 10.260050003 Michigan Allegan 11.84 11.99 11.44 11.58 11.01 11.260170014 Michigan Bay 10.93 11.05 10.40 10.52 10.06 10.260210014 Michigan Berrien 11.72 11.91 11.32 11.51 10.92 11.260490021 Michigan Genesee 11.61 11.79 11.06 11.24 10.72 10.260650012 Michigan Ingham 12.23 12.51 11.68 11.95 11.30 11.260770008 Michigan Kalamazoo 12.84 13.06 12.30 12.50 11.92 12.260810020 Michigan Kent 12.89 13.09 12.21 12.40 11.80 11.260990009 Michigan Macomb 12.70 13.04 12.13 12.46 11.81 12.261130001 Michigan Missaukee 8.26 8.36 8.04 8.13 7.78 7.8261150005 Michigan Monroe 13.92 14.13 13.29 13.50 12.88 13.261210040 Michigan Muskegon 11.61 11.70 11.19 11.28 10.79 10.261250001 Michigan Oakland 13.78 14.26 13.07 13.53 12.70 13.261390005 Michigan Ottawa 12.55 12.67 11.94 12.05 11.53 11.261450018 Michigan Saginaw 10.61 10.61 10.11 10.11 9.78 9.7261470005 Michigan St. Clair 13.34 13.75 12.85 13.25 12.53 12.
B-41

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

261610005 Michigan Washtenaw 12.30 12.30 11.77 11.77 11.42 11.261610008 Michigan Washtenaw 13.88 14.29 13.21 13.60 12.83 13.261630001 Michigan Wayne 14.52 15.11 13.72 14.29 13.33 13.261630015 Michigan Wayne 15.88 16.40 15.05 15.55 14.64 15.261630016 Michigan Wayne 14.57 15.17 13.83 14.40 13.46 14.261630019 Michigan Wayne 14.32 14.77 13.64 14.07 13.29 13.261630025 Michigan Wayne 13.39 13.88 12.73 13.20 12.35 12.261630033 Michigan Wayne 17.50 18.16 16.57 17.19 16.12 16.261630036 Michigan Wayne 14.67 15.44 13.92 14.65 13.53 14.270210001 Minnesota Cass 5.70 5.80 5.48 5.58 5.40 5.5270370470 Minnesota Dakota 9.30 9.55 8.86 9.10 8.66 8.8270530050 Minnesota Hennepin 9.76 9.82 9.28 9.33 9.08 9.1270530961 Minnesota Hennepin 9.14 9.27 8.69 8.81 8.49 8.6270530963 Minnesota Hennepin 9.59 9.81 9.10 9.31 8.90 9.1270530965 Minnesota Hennepin 9.54 9.58 9.06 9.10 8.86 8.9270531007 Minnesota Hennepin 9.56 9.75 9.08 9.26 8.87 9.0270532006 Minnesota Hennepin 9.33 9.39 8.87 8.91 8.67 8.7270953051 Minnesota Mille Lacs 6.54 6.67 6.28 6.41 6.17 6.2271095008 Minnesota Olmsted 10.13 10.13 9.64 9.64 9.40 9.4271230866 Minnesota Ramsey 11.32 11.61 10.81 11.09 10.58 10.271230868 Minnesota Ramsey 11.02 11.31 10.49 10.77 10.27 10.271230871 Minnesota Ramsey 9.63 9.80 9.17 9.33 8.97 9.1271377001 Minnesota Saint Louis 6.10 6.15 5.93 5.98 5.76 5.8271377550 Minnesota Saint Louis 6.19 6.25 5.94 6.00 5.80 5.8271377551 Minnesota Saint Louis 7.51 7.62 7.19 7.29 7.02 7.1271390505 Minnesota Scott 9.00 9.16 8.57 8.71 8.37 8.5271453052 Minnesota Stearns 8.58 8.80 8.19 8.40 8.02 8.2280010004 Mississippi Adams 11.29 11.46 10.93 11.10 10.53 10.280110001 Mississippi Bolivar 12.36 12.58 12.13 12.35 11.65 11.280330002 Mississippi DeSoto 12.43 12.51 12.06 12.13 11.47 11.
B-42

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

280350004 Mississippi Forrest 13.62 13.99 12.84 13.19 12.40 12.280470008 Mississippi Harrison 12.20 12.34 11.60 11.74 11.23 11.280490010 Mississippi Hinds 12.56 12.66 11.98 12.07 11.50 11.280590006 Mississippi Jackson 12.04 12.16 11.29 11.41 10.89 11.280670002 Mississippi Jones 14.39 14.59 13.55 13.75 13.07 13.280750003 Mississippi Lauderdale 13.07 13.09 12.44 12.45 11.92 11.280810005 Mississippi Lee 12.57 12.83 12.15 12.40 11.57 11.280870001 Mississippi Lowndes 12.79 13.11 12.27 12.57 11.69 11.281090001 Mississippi Pearl River 12.14 12.14 11.60 11.60 11.22 11.281490004 Mississippi Warren 12.32 12.32 11.90 11.90 11.43 11.290190004 Missouri Boone 11.84 11.84 11.68 11.68 11.22 11.290210005 Missouri Buchanan 12.80 12.80 12.28 12.28 12.01 12.290370003 Missouri Cass 10.67 10.83 10.25 10.41 9.94 10.290390001 Missouri Cedar 11.12 11.12 10.82 10.82 10.51 10.290470005 Missouri Clay 11.03 11.25 10.51 10.73 10.23 10.290770032 Missouri Greene 11.75 11.87 11.51 11.63 11.12 11.290950034 Missouri Jackson 12.78 13.19 12.12 12.50 11.79 12.290990012 Missouri Jefferson 13.79 13.97 13.72 13.90 13.15 13.291370001 Missouri Monroe 10.87 10.87 10.69 10.69 10.21 10.291831002 Missouri Saint Charles 13.29 13.70 13.50 13.92 12.89 13.291860006 Missouri Sainte Genevieve 13.34 13.66 13.29 13.60 12.64 12.291890004 Missouri Saint Louis 13.04 13.04 13.00 13.00 12.42 12.291892003 Missouri Saint Louis 13.46 13.79 13.43 13.76 12.83 13.295100007 Missouri St. Louis City 14.27 14.45 14.17 14.34 13.57 13.295100085 Missouri St. Louis City 14.36 14.45 14.32 14.40 13.69 13.295100086 Missouri St. Louis City 13.44 13.60 13.44 13.61 12.82 12.295100087 Missouri St. Louis City 14.56 14.70 14.51 14.65 13.86 14.300870307 Montana Rosebud 6.58 6.58 6.48 6.48 6.45 6.4301111065 Montana Yellowstone 8.14 8.18 7.89 7.92 7.84 7.8310250002 Nebraska Cass 9.99 9.99 9.46 9.46 9.25 9.2
B-43

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

310550019 Nebraska Douglas 9.88 10.06 9.37 9.55 9.19 9.3310550052 Nebraska Douglas 9.85 10.18 9.35 9.66 9.15 9.4310790004 Nebraska Hall 7.95 7.95 7.56 7.56 7.40 7.4311090022 Nebraska Lancaster 8.90 9.28 8.43 8.79 8.22 8.5311111002 Nebraska Lincoln 7.57 7.57 7.28 7.28 7.19 7.1311530007 Nebraska Sarpy 9.79 9.86 9.27 9.34 9.08 9.1311570003 Nebraska Scotts Bluff 6.04 6.04 5.78 5.78 5.72 5.7311770002 Nebraska Washington 9.29 9.35 8.85 8.91 8.66 8.7330012004 New Hampshire Belknap 7.28 7.33 6.76 6.80 6.65 6.6330050007 New Hampshire Cheshire 11.53 11.61 10.81 10.88 10.63 10.330070014 New Hampshire Coos 10.24 10.39 9.81 9.96 9.68 9.8330090010 New Hampshire Grafton 8.43 8.43 7.94 7.94 7.81 7.8330110020 New Hampshire Hillsborough 10.18 10.18 9.36 9.36 9.22 9.2330111015 New Hampshire Hillsborough 10.01 10.01 9.27 9.27 9.13 9.1330115001 New Hampshire Hillsborough 6.27 6.27 5.78 5.78 5.69 5.6330131006 New Hampshire Merrimack 9.72 9.73 8.95 8.96 8.80 8.8330150014 New Hampshire Rockingham 9.00 9.20 8.30 8.48 8.18 8.3330190003 New Hampshire Sullivan 9.86 10.17 9.27 9.56 9.12 9.4340011006 New Jersey Atlantic 11.47 11.47 10.73 10.73 10.59 10.340030003 New Jersey Bergen 13.09 13.29 12.00 12.17 11.78 11.340070003 New Jersey Camden 13.31 13.40 12.32 12.40 12.10 12.340071007 New Jersey Camden 13.51 13.78 12.48 12.72 12.24 12.340130015 New Jersey Essex 13.27 13.29 12.15 12.18 11.90 11.340155001 New Jersey Gloucester 13.46 13.46 12.48 12.48 12.25 12.340171003 New Jersey Hudson 14.24 14.66 13.15 13.54 12.91 13.340210008 New Jersey Mercer 12.71 12.97 11.83 12.05 11.61 11.340218001 New Jersey Mercer 11.14 11.66 10.34 10.81 10.14 10.340230006 New Jersey Middlesex 12.15 12.52 11.31 11.65 11.10 11.340270004 New Jersey Morris 11.50 11.92 10.62 11.00 10.43 10.340273001 New Jersey Morris 10.21 10.59 9.49 9.83 9.33 9.6
B-44

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

340292002 New Jersey Ocean 10.92 11.27 10.19 10.51 10.02 10.340310005 New Jersey Passaic 12.88 13.09 11.76 11.93 11.53 11.340390004 New Jersey Union 14.94 15.53 13.73 14.28 13.43 13.340390006 New Jersey Union 13.32 13.64 12.16 12.45 11.90 12.340392003 New Jersey Union 13.06 13.32 11.98 12.21 11.72 11.340410006 New Jersey Warren 12.72 13.11 11.82 12.17 11.63 11.350010023 New Mexico Bernalillo 7.03 7.13 6.59 6.68 6.50 6.5350010024 New Mexico Bernalillo 6.64 6.81 6.22 6.39 6.13 6.3350050005 New Mexico Chaves 6.54 6.58 6.29 6.33 6.24 6.2350130017 New Mexico Dona Ana 9.95 10.40 9.55 9.97 9.50 9.9350130025 New Mexico Dona Ana 6.31 6.35 6.03 6.07 5.99 6.0350431003 New Mexico Sandoval 5.00 5.02 4.69 4.71 4.63 4.6350439011 New Mexico Sandoval 7.99 8.34 7.74 8.08 7.69 8.0350450006 New Mexico San Juan 5.92 6.08 5.75 5.91 5.73 5.8350490020 New Mexico Santa Fe 4.76 4.81 4.59 4.64 4.55 4.6360010005 New York Albany 11.83 11.83 11.29 11.29 11.15 11.360050080 New York Bronx 15.43 15.72 14.28 14.55 14.03 14.360050083 New York Bronx 13.09 13.35 12.07 12.30 11.85 12.360050110 New York Bronx 13.45 14.06 12.44 13.01 12.21 12.360130011 New York Chautauqua 9.80 10.09 9.22 9.49 8.99 9.2360290005 New York Erie 12.62 12.79 11.98 12.15 11.76 11.360291007 New York Erie 12.64 13.00 11.99 12.34 11.76 12.360310003 New York Essex 5.94 5.98 5.71 5.75 5.62 5.6360470122 New York Kings 14.20 14.64 13.19 13.60 12.95 13.360551007 New York Monroe 10.64 10.64 10.17 10.17 9.99 9.9360590008 New York Nassau 11.66 12.07 10.89 11.27 10.72 11.360610056 New York New York 16.18 17.02 14.98 15.74 14.70 15.360610062 New York New York 14.80 15.31 13.70 14.16 13.44 13.360610079 New York New York 13.61 14.00 12.59 12.95 12.36 12.360610128 New York New York 15.41 15.80 14.33 14.68 14.08 14.
B-45

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

360632008 New York Niagara 11.96 12.29 11.45 11.76 11.23 11.360671015 New York Onondaga 10.08 10.46 9.61 9.97 9.46 9.8360710002 New York Orange 10.99 11.43 10.20 10.60 10.05 10.360810124 New York Queens 12.18 12.69 11.30 11.78 11.10 11.360850055 New York Richmond 13.31 13.37 12.23 12.29 11.97 12.360850067 New York Richmond 11.59 11.82 10.66 10.88 10.44 10.360893001 New York St. Lawrence 7.29 7.71 7.06 7.45 6.96 7.3361010003 New York Steuben 9.00 9.38 8.46 8.81 8.31 8.6361030001 New York Suffolk 11.52 11.52 10.78 10.78 10.62 10.361191002 New York Westchester 11.73 11.94 10.85 11.03 10.67 10.370010002 North Carolina Alamance 13.94 14.07 12.39 12.52 12.00 12.370210034 North Carolina Buncombe 12.60 12.65 11.32 11.36 10.88 10.370330001 North Carolina Caswell 13.19 13.33 11.66 11.78 11.31 11.370350004 North Carolina Catawba 15.31 15.37 13.35 13.41 12.90 12.370370004 North Carolina Chatham 11.99 12.15 10.72 10.87 10.34 10.370510009 North Carolina Cumberland 13.73 13.85 12.62 12.73 12.22 12.370570002 North Carolina Davidson 15.17 15.24 13.47 13.53 13.07 13.370610002 North Carolina Duplin 11.30 11.54 10.33 10.56 10.04 10.370630001 North Carolina Durham 13.57 13.67 12.23 12.32 11.84 11.370650004 North Carolina Edgecombe 12.37 12.38 11.40 11.40 11.05 11.370670022 North Carolina Forsyth 14.28 14.45 12.48 12.63 12.09 12.370710016 North Carolina Gaston 14.26 14.40 12.39 12.51 11.97 12.370810013 North Carolina Guilford 13.79 13.79 12.24 12.24 11.87 11.370870010 North Carolina Haywood 12.98 13.00 11.84 11.86 11.39 11.370990006 North Carolina Jackson 12.09 12.43 10.97 11.29 10.44 10.371070004 North Carolina Lenoir 11.12 11.29 10.21 10.37 9.92 10.371110004 North Carolina McDowell 14.24 14.35 12.73 12.83 12.31 12.371170001 North Carolina Martin 10.86 11.12 9.95 10.20 9.69 9.9371190010 North Carolina Mecklenburg 15.31 15.31 13.42 13.42 13.03 13.371190041 North Carolina Mecklenburg 14.74 14.94 12.92 13.10 12.52 12.
B-46

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

371190042 North Carolina Mecklenburg 14.80 14.93 12.98 13.09 12.58 12.371210001 North Carolina Mitchell 12.75 13.00 11.34 11.56 10.93 11.371230001 North Carolina Montgomery 12.24 12.35 10.95 11.05 10.55 10.371290002 North Carolina New Hanover 9.96 10.18 9.20 9.40 8.95 9.1371330005 North Carolina Onslow 10.98 11.26 10.12 10.39 9.85 10.371350007 North Carolina Orange 13.12 13.25 11.77 11.88 11.36 11.371470005 North Carolina Pitt 11.59 11.90 10.65 10.94 10.35 10.371550005 North Carolina Robeson 12.78 12.79 11.72 11.75 11.40 11.371590021 North Carolina Rowan 14.02 14.02 12.48 12.48 12.11 12.371730002 North Carolina Swain 12.65 12.82 11.51 11.67 10.94 11.371830014 North Carolina Wake 13.54 13.57 12.25 12.29 11.85 11.371890003 North Carolina Watauga 12.05 12.06 10.65 10.66 10.24 10.371910005 North Carolina Wayne 12.96 13.14 11.99 12.16 11.62 11.380070002 North Dakota Billings 4.61 4.68 4.47 4.54 4.45 4.5380130002 North Dakota Burke 5.90 5.90 5.76 5.76 5.74 5.7380130003 North Dakota Burke 5.78 5.78 5.62 5.62 5.60 5.6380150003 North Dakota Burleigh 6.61 6.71 6.21 6.30 6.15 6.2380171004 North Dakota Cass 7.72 7.75 7.36 7.40 7.25 7.2380530002 North Dakota McKenzie 5.01 5.09 4.88 4.96 4.85 4.9380570004 North Dakota Mercer 6.04 6.15 5.97 6.08 5.94 6.0390090003 Ohio Athens 12.39 12.67 11.40 11.66 10.89 11.390170016 Ohio Butler 15.74 16.11 15.25 15.61 14.76 15.390170017 Ohio Butler 15.36 15.36 14.93 14.93 14.48 14.390171004 Ohio Butler 14.90 15.14 14.51 14.74 14.06 14.390230005 Ohio Clark 14.64 14.77 14.08 14.21 13.65 13.390250022 Ohio Clermont 14.15 14.15 13.69 13.69 13.20 13.390350027 Ohio Cuyahoga 15.46 16.13 14.50 15.13 14.06 14.390350034 Ohio Cuyahoga 13.76 14.07 12.93 13.23 12.54 12.390350038 Ohio Cuyahoga 17.37 18.10 16.26 16.95 15.79 16.390350045 Ohio Cuyahoga 16.47 16.98 15.42 15.91 14.96 15.
B-47

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

390350060 Ohio Cuyahoga 17.11 17.66 16.02 16.54 15.55 16.390350065 Ohio Cuyahoga 15.97 16.44 14.96 15.40 14.51 14.390351002 Ohio Cuyahoga 14.14 14.64 13.30 13.77 12.92 13.390490024 Ohio Franklin 15.27 15.95 14.33 14.97 13.85 14.390490025 Ohio Franklin 15.08 15.45 14.12 14.47 13.64 13.390490081 Ohio Franklin 14.33 14.33 13.51 13.51 13.03 13.390570005 Ohio Greene 13.36 13.55 12.83 13.02 12.41 12.390610006 Ohio Hamilton 14.84 14.84 14.36 14.36 13.88 13.390610014 Ohio Hamilton 17.29 17.53 16.69 16.93 16.14 16.390610040 Ohio Hamilton 15.50 15.88 15.03 15.40 14.51 14.390610042 Ohio Hamilton 16.85 17.25 16.33 16.71 15.80 16.390610043 Ohio Hamilton 15.55 15.82 15.05 15.32 14.56 14.390617001 Ohio Hamilton 16.17 16.56 15.65 16.03 15.12 15.390618001 Ohio Hamilton 17.54 17.90 16.93 17.27 16.38 16.390810017 Ohio Jefferson 15.41 15.46 13.95 13.99 13.53 13.390811001 Ohio Jefferson 16.51 17.17 14.95 15.54 14.50 15.390851001 Ohio Lake 13.02 13.02 12.33 12.33 11.96 11.390870010 Ohio Lawrence 15.14 15.44 14.19 14.47 13.63 13.390930016 Ohio Lorain 13.87 14.13 13.13 13.37 12.74 12.390933002 Ohio Lorain 12.78 12.98 12.12 12.31 11.79 11.390950024 Ohio Lucas 14.38 14.68 13.72 14.00 13.29 13.390950025 Ohio Lucas 13.95 14.37 13.32 13.72 12.90 13.390950026 Ohio Lucas 14.08 14.30 13.48 13.68 13.05 13.390990005 Ohio Mahoning 14.68 14.99 13.80 14.10 13.38 13.390990014 Ohio Mahoning 15.12 15.53 14.23 14.62 13.79 14.391130031 Ohio Montgomery 14.58 14.58 14.09 14.09 13.66 13.391130032 Ohio Montgomery 15.54 15.92 15.01 15.37 14.55 14.391330002 Ohio Portage 13.37 13.56 12.62 12.79 12.23 12.391351001 Ohio Preble 13.70 13.88 13.46 13.64 13.04 13.391450013 Ohio Scioto 14.65 14.84 13.68 13.86 13.14 13.
B-48

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

391510017 Ohio Stark 16.15 16.59 14.99 15.40 14.60 15.391510020 Ohio Stark 15.14 15.14 14.07 14.07 13.71 13.391530017 Ohio Summit 15.17 15.61 14.28 14.71 13.91 14.391530023 Ohio Summit 14.26 14.58 13.42 13.73 13.07 13.391550007 Ohio Trumbull 14.53 14.73 13.75 13.94 13.32 13.400159008 Oklahoma Caddo 9.22 9.77 8.69 9.21 8.57 9.0400219002 Oklahoma Cherokee 11.79 12.28 11.41 11.88 11.10 11.400719010 Oklahoma Kay 10.26 10.62 9.96 10.32 9.76 10.400819005 Oklahoma Lincoln 10.28 10.28 9.83 9.83 9.60 9.6400970186 Oklahoma Mayes 11.70 11.83 11.46 11.59 11.17 11.400979014 Oklahoma Mayes 11.44 11.62 11.18 11.36 10.89 11.401010169 Oklahoma Muskogee 11.89 12.10 11.61 11.81 11.32 11.401090035 Oklahoma Oklahoma 10.07 10.23 9.47 9.62 9.25 9.4401091037 Oklahoma Oklahoma 9.86 10.07 9.29 9.48 9.07 9.2401159004 Oklahoma Ottawa 11.69 11.95 11.31 11.56 11.02 11.401210415 Oklahoma Pittsburg 11.06 11.28 10.63 10.84 10.37 10.401359015 Oklahoma Sequoyah 12.99 12.99 12.56 12.56 12.25 12.401430110 Oklahoma Tulsa 11.52 11.52 11.13 11.13 10.86 10.401431127 Oklahoma Tulsa 11.37 11.56 10.99 11.17 10.72 10.420010001 Pennsylvania Adams 13.05 13.59 12.13 12.64 11.90 12.420030008 Pennsylvania Allegheny 15.24 15.48 14.11 14.33 13.70 13.420030021 Pennsylvania Allegheny 14.66 14.66 13.65 13.65 13.26 13.420030064 Pennsylvania Allegheny 20.31 20.75 18.90 19.31 18.38 18.420030067 Pennsylvania Allegheny 12.86 12.94 11.82 11.89 11.45 11.420030095 Pennsylvania Allegheny 13.84 14.54 12.77 13.42 12.41 13.420030116 Pennsylvania Allegheny 15.36 15.36 14.17 14.17 13.78 13.420031008 Pennsylvania Allegheny 15.25 15.49 14.26 14.49 13.89 14.420031301 Pennsylvania Allegheny 16.26 16.57 15.13 15.42 14.70 14.420033007 Pennsylvania Allegheny 15.30 15.72 14.20 14.59 13.76 14.420039002 Pennsylvania Allegheny 14.44 14.44 13.44 13.44 13.06 13.
B-49

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

420070014 Pennsylvania Beaver 16.38 16.45 15.23 15.30 14.87 14.420110011 Pennsylvania Berks 15.82 16.19 14.77 15.11 14.57 14.420170012 Pennsylvania Bucks 13.42 13.93 12.45 12.92 12.21 12.420210011 Pennsylvania Cambria 15.40 15.55 14.88 15.02 14.53 14.420270100 Pennsylvania Centre 12.78 13.42 11.95 12.55 11.70 12.420290100 Pennsylvania Chester 15.22 15.22 14.03 14.03 13.84 13.420410101 Pennsylvania Cumberland 14.45 15.12 13.48 14.12 13.26 13.420430401 Pennsylvania Dauphin 15.13 15.78 13.98 14.59 13.75 14.420450002 Pennsylvania Delaware 15.23 15.69 14.16 14.58 13.91 14.420490003 Pennsylvania Erie 12.54 12.57 11.86 11.88 11.54 11.420692006 Pennsylvania Lackawanna 11.73 12.17 10.77 11.17 10.60 11.420710007 Pennsylvania Lancaster 16.55 17.46 15.18 16.01 14.98 15.420770004 Pennsylvania Lehigh 14.50 14.50 13.48 13.48 13.28 13.420791101 Pennsylvania Luzerne 12.76 12.76 11.76 11.76 11.59 11.420850100 Pennsylvania Mercer 13.28 13.74 12.51 12.94 12.11 12.420950025 Pennsylvania Northampton 13.68 14.07 12.69 13.06 12.48 12.420990301 Pennsylvania Perry 12.81 12.81 11.98 11.98 11.78 11.421010047 Pennsylvania Philadelphia 15.19 15.19 14.10 14.10 13.82 13.421250005 Pennsylvania Washington 15.17 15.48 14.10 14.39 13.63 13.421250200 Pennsylvania Washington 14.92 14.92 13.74 13.74 13.29 13.421255001 Pennsylvania Washington 13.37 13.61 12.21 12.44 11.87 12.421290008 Pennsylvania Westmoreland 15.49 15.68 14.49 14.67 14.05 14.421330008 Pennsylvania York 16.52 17.25 15.25 15.93 15.06 15.440070022 Rhode Island Providence 10.07 10.07 9.34 9.34 9.22 9.2440070026 Rhode Island Providence 12.14 12.41 11.29 11.54 11.13 11.440070028 Rhode Island Providence 10.82 11.10 10.06 10.32 9.92 10.440071010 Rhode Island Providence 9.93 10.23 9.20 9.48 9.08 9.3450130007 South Carolina Beaufort 11.52 11.71 10.66 10.84 10.29 10.450190048 South Carolina Charleston 12.21 12.48 11.26 11.51 10.92 11.450190049 South Carolina Charleston 11.60 11.83 10.79 11.00 10.44 10.
B-50

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

450250001 South Carolina Chesterfield 12.53 12.75 11.49 11.69 11.11 11.450370001 South Carolina Edgefield 13.14 13.38 12.24 12.47 11.70 11.450410002 South Carolina Florence 12.62 12.73 11.60 11.69 11.24 11.450430009 South Carolina Georgetown 12.85 12.90 11.74 11.78 11.45 11.450450008 South Carolina Greenville 15.65 15.92 14.09 14.34 13.55 13.450450009 South Carolina Greenville 14.66 14.82 13.16 13.30 12.63 12.450470003 South Carolina Greenwood 13.53 13.70 12.41 12.56 11.73 11.450510002 South Carolina Horry 12.00 12.16 11.03 11.17 10.71 10.450630008 South Carolina Lexington 14.64 15.07 13.49 13.88 12.97 13.450730001 South Carolina Oconee 10.95 11.24 9.80 10.06 9.28 9.5450790007 South Carolina Richland 13.56 13.79 12.44 12.65 11.95 12.450790019 South Carolina Richland 14.24 14.45 13.09 13.30 12.59 12.450830010 South Carolina Spartanburg 14.17 14.33 12.62 12.76 12.14 12.460110002 South Dakota Brookings 9.37 9.77 8.91 9.28 8.76 9.1460130003 South Dakota Brown 8.42 8.48 8.01 8.07 7.90 7.9460290002 South Dakota Codington 10.14 10.34 9.67 9.86 9.54 9.7460330132 South Dakota Custer 5.64 5.64 5.48 5.48 5.45 5.4460710001 South Dakota Jackson 5.39 5.45 5.24 5.29 5.21 5.2460990006 South Dakota Minnehaha 10.18 10.39 9.63 9.82 9.44 9.6460990007 South Dakota Minnehaha 9.58 9.82 9.07 9.28 8.89 9.1461030016 South Dakota Pennington 7.48 7.59 7.09 7.19 7.04 7.1461030020 South Dakota Pennington 8.77 8.83 8.34 8.40 8.29 8.3461031001 South Dakota Pennington 7.32 7.35 6.95 6.98 6.91 6.9470090011 Tennessee Blount 14.30 14.71 13.20 13.57 12.64 12.470370023 Tennessee Davidson 14.18 14.27 14.02 14.11 13.45 13.470370025 Tennessee Davidson 13.92 14.04 13.71 13.83 13.13 13.470370036 Tennessee Davidson 12.97 12.98 12.82 12.82 12.24 12.470450004 Tennessee Dyer 12.28 12.57 12.22 12.51 11.68 11.470650031 Tennessee Hamilton 15.48 16.05 14.36 14.89 13.72 14.470651011 Tennessee Hamilton 13.62 13.78 12.63 12.77 12.01 12.
B-51

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

470654002 Tennessee Hamilton 15.07 15.21 13.98 14.09 13.34 13.470930028 Tennessee Knox 15.47 15.74 14.18 14.42 13.57 13.470931017 Tennessee Knox 15.64 15.71 14.37 14.43 13.76 13.470931020 Tennessee Knox 15.18 15.26 13.92 13.99 13.30 13.470990002 Tennessee Lawrence 11.69 12.13 11.32 11.75 10.87 11.471050108 Tennessee Loudon 15.49 15.72 14.26 14.47 13.69 13.471071002 Tennessee McMinn 14.29 14.70 13.22 13.61 12.64 13.471192007 Tennessee Maury 13.21 13.51 12.94 13.23 12.41 12.471251009 Tennessee Montgomery 13.79 13.89 14.17 14.27 13.59 13.471410001 Tennessee Putnam 13.37 13.37 12.76 12.76 12.20 12.471450004 Tennessee Roane 14.49 14.77 13.32 13.58 12.75 13.471570014 Tennessee Shelby 13.71 13.79 13.27 13.35 12.63 12.471570038 Tennessee Shelby 13.43 13.57 13.00 13.14 12.36 12.471570047 Tennessee Shelby 13.68 13.79 13.26 13.37 12.60 12.471571004 Tennessee Shelby 12.04 12.08 11.75 11.79 11.16 11.471631007 Tennessee Sullivan 14.16 14.46 12.95 13.23 12.47 12.471650007 Tennessee Sumner 13.68 13.83 13.76 13.91 13.13 13.480370004 Texas Bowie 12.85 12.95 12.30 12.39 12.03 12.481130069 Texas Dallas 11.80 12.26 10.86 11.29 10.66 11.481130087 Texas Dallas 11.15 11.61 10.21 10.63 10.02 10.481350003 Texas Ector 7.78 7.99 7.44 7.64 7.38 7.5481410037 Texas El Paso 9.09 9.09 8.71 8.71 8.66 8.6482010058 Texas Harris 11.77 12.39 11.24 11.84 10.96 11.482011035 Texas Harris 15.42 15.84 14.74 15.14 14.36 14.482030002 Texas Harrison 11.69 11.79 11.05 11.14 10.82 10.482150043 Texas Hidalgo 10.98 11.16 10.61 10.78 10.47 10.482450021 Texas Jefferson 11.51 11.55 11.23 11.26 10.91 10.483550032 Texas Nueces 10.42 10.87 9.99 10.42 9.66 10.483611001 Texas Orange 11.51 11.72 11.19 11.40 10.92 11.484391002 Texas Tarrant 11.41 11.79 10.51 10.86 10.31 10.
B-52

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

484391006 Texas Tarrant 12.23 12.81 11.28 11.81 11.07 11.500010002 Vermont Addison 8.94 8.94 8.57 8.57 8.46 8.4500010003 Vermont Addison 8.91 8.91 8.54 8.54 8.43 8.4500030004 Vermont Bennington 8.52 9.00 8.10 8.55 7.99 8.4500070012 Vermont Chittenden 9.27 9.56 8.89 9.17 8.75 9.0500070014 Vermont Chittenden 10.02 10.02 9.61 9.61 9.46 9.4500210002 Vermont Rutland 11.08 11.13 10.58 10.63 10.43 10.510130020 Virginia Arlington 14.27 14.62 13.07 13.40 12.87 13.510360002 Virginia Charles 12.37 12.48 10.97 11.08 10.69 10.510410003 Virginia Chesterfield 13.44 13.59 11.93 12.07 11.60 11.510590030 Virginia Fairfax 13.33 13.59 12.18 12.43 11.97 12.510591005 Virginia Fairfax 13.62 13.77 12.48 12.63 12.26 12.510595001 Virginia Fairfax 13.88 14.12 12.79 13.02 12.56 12.510870014 Virginia Henrico 13.51 13.83 11.98 12.27 11.66 11.510870015 Virginia Henrico 12.93 12.99 11.64 11.70 11.30 11.511071005 Virginia Loudoun 13.57 13.90 12.52 12.82 12.27 12.511390004 Virginia Page 12.79 12.85 11.76 11.80 11.40 11.515200006 Virginia Bristol City 13.93 14.00 12.61 12.66 12.09 12.516500004 Virginia Hampton City 12.17 12.35 11.18 11.35 10.90 11.516800015 Virginia Lynchburg City 12.84 13.00 11.60 11.74 11.22 11.517100024 Virginia Norfolk City 12.78 13.01 11.81 12.02 11.52 11.517700014 Virginia Roanoke City 14.27 14.48 12.97 13.17 12.50 12.517750010 Virginia Salem City 14.69 14.69 13.42 13.42 12.96 12.518100008 Virginia 

Virginia Beach City 12.40 12.57 11.46 11.62 11.19 11.

540030003 West Virginia Berkeley 15.93 16.19 14.95 15.20 14.64 14.540090005 West Virginia Brooke 16.52 16.80 14.95 15.22 14.51 14.540090011 West Virginia Brooke 16.04 16.37 14.49 14.79 14.05 14.540110006 West Virginia Cabell 16.30 16.57 15.25 15.50 14.65 14.540291004 West Virginia Hancock 15.76 16.64 14.34 15.15 13.93 14.
B-53

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

540330003 West Virginia Harrison 13.99 14.19 13.82 14.02 13.30 13.540390010 West Virginia Kanawha 15.15 15.38 14.01 14.22 13.45 13.540390011 West Virginia Kanawha 13.17 13.17 12.23 12.23 11.74 11.540391005 West Virginia Kanawha 16.52 16.59 15.28 15.34 14.69 14.540490006 West Virginia Marion 15.03 15.25 14.96 15.18 14.41 14.540511002 West Virginia Marshall 15.19 15.33 13.96 14.09 13.44 13.540610003 West Virginia Monongalia 14.35 14.47 13.72 13.84 13.14 13.540690010 West Virginia Ohio 14.58 14.58 13.18 13.18 12.72 12.540810002 West Virginia Raleigh 12.90 13.03 11.88 12.00 11.40 11.541071002 West Virginia Wood 15.40 15.44 14.31 14.35 13.77 13.550030010 Wisconsin Ashland 6.07 6.21 5.85 5.98 5.74 5.8550090005 Wisconsin Brown 11.39 11.86 11.03 11.47 10.75 11.550250047 Wisconsin Dane 12.20 12.65 11.80 12.23 11.52 11.550270007 Wisconsin Dodge 11.04 11.26 10.61 10.82 10.24 10.550410007 Wisconsin Forest 7.41 7.41 7.17 7.17 6.98 6.9550430009 Wisconsin Grant 11.79 12.24 11.34 11.76 10.99 11.550590019 Wisconsin Kenosha 11.98 12.93 11.72 12.65 11.22 12.550710007 Wisconsin Manitowoc 10.20 10.89 9.92 10.58 9.63 10.550790010 Wisconsin Milwaukee 13.32 13.94 12.98 13.57 12.48 13.550790026 Wisconsin Milwaukee 12.88 13.83 12.52 13.44 12.05 12.550790043 Wisconsin Milwaukee 14.08 14.62 13.71 14.24 13.20 13.550790059 Wisconsin Milwaukee 13.68 14.87 13.33 14.48 12.83 13.550790099 Wisconsin Milwaukee 13.54 14.40 13.18 14.02 12.70 13.550870009 Wisconsin Outagamie 10.96 11.45 10.57 11.03 10.29 10.550890009 Wisconsin Ozaukee 11.60 12.22 11.26 11.86 10.85 11.551091002 Wisconsin St. Croix 10.09 10.09 9.63 9.63 9.42 9.4551110007 Wisconsin Sauk 10.22 10.57 9.81 10.14 9.49 9.8551198001 Wisconsin Taylor 8.24 8.43 7.91 8.10 7.74 7.9551250001 Wisconsin Vilas 6.78 6.87 6.54 6.64 6.39 6.4551330027 Wisconsin Waukesha 13.91 14.34 13.51 13.93 13.06 13.
B-54

Annual PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

560050877 Wyoming Campbell 6.29 6.29 6.16 6.16 6.14 6.1560050892 Wyoming Campbell 5.00 5.04 4.91 4.95 4.92 4.9560050899 Wyoming Campbell 5.37 5.49 5.25 5.37 5.24 5.3560090819 Wyoming Converse 3.52 3.60 3.41 3.48 3.40 3.4560131003 Wyoming Fremont 8.17 8.50 7.89 8.21 7.84 8.1560210001 Wyoming Laramie 4.48 4.69 4.28 4.48 4.22 4.4560330002 Wyoming Sheridan 9.70 9.84 9.41 9.54 9.34 9.4
B-55

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

10030010 Alabama Baldwin 26.2 27.5 24.9 26.1 24.1 2510270001 Alabama Clay 31.8 32.4 27.6 29.0 25.7 2710331002 Alabama Colbert 30.4 30.4 28.0 28.7 26.5 2710491003 Alabama DeKalb 32.0 32.6 27.2 27.8 25.3 2510530002 Alabama Escambia 29.0 29.7 27.0 27.8 26.1 2610550010 Alabama Etowah 35.1 35.7 29.4 29.5 27.8 2710690003 Alabama Houston 28.6 28.6 26.3 26.3 25.3 2510730023 Alabama Jefferson 44.0 44.2 40.0 40.7 38.8 3910731005 Alabama Jefferson 34.8 35.5 31.3 31.8 29.8 3010731009 Alabama Jefferson 34.5 34.9 31.5 32.5 29.9 3110731010 Alabama Jefferson 34.1 34.3 29.1 29.3 27.6 2710732003 Alabama Jefferson 40.3 40.8 38.1 38.9 37.2 3710732006 Alabama Jefferson 33.1 34.1 29.8 30.4 28.5 2810735002 Alabama Jefferson 33.0 34.8 29.4 30.7 27.6 2810735003 Alabama Jefferson 35.8 36.5 32.1 33.2 30.5 3110890014 Alabama Madison 33.5 34.1 30.3 30.5 28.4 2810970002 Alabama Mobile 30.0 30.0 28.3 28.3 26.8 2610970003 Alabama Mobile 28.5 29.4 27.2 27.9 25.8 2610972005 Alabama Mobile 26.4 27.9 24.7 26.2 23.5 2411010007 Alabama Montgomery 32.0 33.5 29.2 30.0 28.0 2811030011 Alabama Morgan 31.5 31.9 27.8 28.2 25.9 2611130001 Alabama Russell 35.5 36.9 32.8 33.8 31.4 3211170006 Alabama Shelby 32.0 32.8 28.8 29.0 27.4 2711190002 Alabama Sumter 28.9 28.9 26.6 26.6 25.1 2511210002 Alabama Talladega 33.4 33.4 28.2 28.2 26.5 2611250004 Alabama Tuscaloosa 29.8 30.1 27.3 28.1 26.2 2711270002 Alabama Walker 32.8 33.3 27.7 29.7 26.3 2850010011 Arkansas Arkansas 29.1 29.6 28.8 29.3 27.8 2850030005 Arkansas Ashley 28.9 29.9 28.4 29.2 27.3 2850350005 Arkansas Crittenden 35.0 35.0 34.3 34.3 32.7 32
B-56

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

50450002 Arkansas Faulkner 29.8 30.6 28.8 29.4 27.9 2850510003 Arkansas Garland 29.2 29.3 28.9 29.0 27.9 2850930007 Arkansas Mississippi 30.3 30.3 30.8 30.8 29.2 2951070001 Arkansas Phillips 29.1 30.2 28.8 29.8 27.6 2851130002 Arkansas Polk 26.1 27.7 25.3 26.8 24.3 2551150003 Arkansas Pope 28.3 29.1 27.5 28.0 26.6 2751190007 Arkansas Pulaski 31.1 31.4 30.8 31.3 29.8 3051191004 Arkansas Pulaski 31.9 32.4 30.9 31.3 29.9 3051191005 Arkansas Pulaski 31.9 32.3 31.1 31.4 30.0 3051390006 Arkansas Union 28.7 29.6 27.9 28.3 26.8 2751450001 Arkansas White 29.9 31.1 29.4 30.7 28.2 2980010006 Colorado Adams 25.3 29.2 23.9 27.8 23.4 2780050005 Colorado Arapahoe 21.2 22.2 20.2 21.1 19.8 2080130003 Colorado Boulder 21.1 22.3 19.9 21.0 19.5 2080130012 Colorado Boulder 18.7 19.7 17.5 18.5 17.2 1880290004 Colorado Delta 20.7 22.3 18.7 20.1 18.2 1980310002 Colorado Denver 26.4 27.6 25.6 26.7 25.3 2680310023 Colorado Denver 26.3 26.3 25.6 25.6 25.2 2580390001 Colorado Elbert 13.1 15.1 12.4 14.2 12.2 1480410008 Colorado El Paso 16.4 16.7 15.3 15.5 15.0 1580410011 Colorado El Paso 16.5 17.4 15.5 16.3 15.2 1680690009 Colorado Larimer 18.3 18.8 17.1 17.6 16.9 1780770017 Colorado Mesa 23.5 24.6 22.7 23.7 22.3 2381010012 Colorado Pueblo 15.4 15.8 14.4 14.8 14.1 1481130004 Colorado San Miguel 10.1 11.3 9.8 11.0 9.8 1181230006 Colorado Weld 22.9 23.9 21.4 22.5 21.2 2281230008 Colorado Weld 20.1 23.7 18.4 21.5 18.1 2190010010 Connecticut Fairfield 36.2 37.3 32.9 33.4 32.2 3290011123 Connecticut Fairfield 32.2 32.7 30.4 30.8 29.8 3090013005 Connecticut Fairfield 34.9 35.6 32.8 33.1 32.2 32
B-57

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

90019003 Connecticut Fairfield 34.2 36.7 30.9 32.7 30.2 3190031003 Connecticut Hartford 31.8 32.6 28.8 29.6 28.2 2890050005 Connecticut Litchfield 27.1 27.1 23.6 23.6 23.0 2390090026 Connecticut New Haven 35.6 37.9 32.3 33.7 31.6 3290090027 Connecticut New Haven 35.5 36.0 32.9 33.0 32.2 3290091123 Connecticut New Haven 38.3 40.3 35.7 36.6 34.9 3590092008 Connecticut New Haven 33.6 36.4 30.9 32.5 30.2 3190092123 Connecticut New Haven 34.4 34.7 31.2 32.0 30.5 3190113002 Connecticut New London 32.0 34.4 28.4 29.8 27.7 29

100010002 Delaware Kent 32.1 32.2 28.0 28.8 27.6 28100010003 Delaware Kent 31.5 32.4 27.1 28.2 26.6 27100031003 Delaware New Castle 33.5 34.3 30.0 30.8 29.6 30100031007 Delaware New Castle 32.6 34.5 28.2 29.8 27.9 29100031012 Delaware New Castle 32.4 33.5 28.3 29.3 27.9 28100032004 Delaware New Castle 36.6 36.7 34.1 34.2 33.7 33100051002 Delaware Sussex 33.7 34.3 29.6 30.0 29.1 29110010041 

District Of Columbia 

District of Columbia 36.3 37.8 34.0 35.6 33.6 35

110010042 

District Of Columbia 

District of Columbia 34.9 37.0 33.0 35.6 32.7 35

110010043 

District Of Columbia 

District of Columbia 34.1 34.8 32.5 33.5 32.3 33

120010023 Florida Alachua 23.4 27.6 21.0 24.7 20.3 23120010024 Florida Alachua 21.9 25.0 19.5 22.2 18.8 21120051004 Florida Bay 28.4 29.2 26.2 26.7 25.2 25120090007 Florida Brevard 20.7 22.0 18.2 19.4 17.7 18120111002 Florida Broward 18.8 20.3 17.5 18.7 16.9 18120112004 Florida Broward 19.1 20.3 18.2 19.0 17.6 18120113002 Florida Broward 18.4 18.4 16.8 16.8 16.3 16120170005 Florida Citrus 21.7 21.9 19.1 19.3 18.3 18120310098 Florida Duval 24.6 25.8 22.2 23.1 21.7 22
B-58

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

120310099 Florida Duval 25.2 26.7 24.0 25.3 23.6 24120330004 Florida Escambia 28.8 30.6 27.5 29.2 26.8 28120570030 Florida Hillsborough 23.6 24.0 21.5 22.1 20.8 21120573002 Florida Hillsborough 23.2 23.9 20.9 21.2 20.2 20120710005 Florida Lee 17.8 18.2 16.0 16.2 15.3 15120730012 Florida Leon 29.0 31.5 26.3 28.2 25.5 27120814012 Florida Manatee 19.9 20.2 16.2 16.6 15.7 16120830003 Florida Marion 23.2 24.1 20.8 21.3 20.1 20120861016 Florida Miami-Dade 19.4 19.5 18.6 18.7 18.2 18120866001 Florida Miami-Dade 19.0 19.3 17.5 17.7 16.8 17120951004 Florida Orange 21.7 21.8 19.1 19.3 18.4 18120952002 Florida Orange 21.6 22.5 18.9 19.5 18.1 18120990009 Florida Palm Beach 18.9 18.9 18.2 18.2 17.6 17120992005 Florida Palm Beach 18.2 18.4 16.7 17.1 16.2 16121030018 Florida Pinellas 21.9 23.0 20.0 20.6 19.5 20121031009 Florida Pinellas 21.2 22.0 18.1 18.8 17.8 18121056006 Florida Polk 19.5 19.9 17.7 18.2 17.0 17121111002 Florida St. Lucie 18.7 19.5 16.9 17.6 16.2 16121150013 Florida Sarasota 19.8 20.3 17.2 17.6 16.5 16121171002 Florida Seminole 22.8 23.0 19.2 19.4 18.2 18121275002 Florida Volusia 22.6 25.8 19.2 21.7 18.1 20130210007 Georgia Bibb 33.5 33.6 30.2 30.7 28.5 29130210012 Georgia Bibb 30.7 31.4 28.3 28.9 26.1 26130510017 Georgia Chatham 28.4 28.9 26.5 26.7 25.5 25130510091 Georgia Chatham 27.9 28.6 25.9 26.6 24.9 25130630091 Georgia Clayton 35.8 37.7 32.2 33.4 31.2 31130670003 Georgia Cobb 35.0 36.3 31.1 31.8 29.6 29130670004 Georgia Cobb 34.1 35.7 29.5 30.7 27.0 28130890002 Georgia DeKalb 33.4 33.7 29.2 29.7 28.0 28130892001 Georgia DeKalb 33.9 35.4 31.0 32.3 29.7 31
B-59

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

130950007 Georgia Dougherty 34.1 35.2 31.6 32.6 30.4 31131150005 Georgia Floyd 35.1 36.4 31.2 32.4 29.9 31131210032 Georgia Fulton 34.1 35.0 30.8 31.8 29.4 30131210039 Georgia Fulton 37.6 37.6 34.3 34.3 31.7 31131270006 Georgia Glynn 26.1 26.7 24.5 24.9 23.5 23131350002 Georgia Gwinnett 32.8 35.0 29.2 29.9 28.1 28131390003 Georgia Hall 30.6 31.7 29.1 29.3 26.4 26131530001 Georgia Houston 29.6 30.6 26.7 28.9 24.8 27131850003 Georgia Lowndes 25.9 26.3 23.8 25.1 22.9 24132150001 Georgia Muscogee 31.3 32.9 29.1 29.8 28.0 28132150008 Georgia Muscogee 34.5 37.6 30.3 32.3 28.5 30132150011 Georgia Muscogee 30.4 30.9 27.7 28.1 26.4 26132230003 Georgia Paulding 33.0 33.3 27.5 28.0 25.7 26132450005 Georgia Richmond 32.7 33.4 31.3 31.9 30.5 31132450091 Georgia Richmond 31.9 32.6 30.2 30.5 28.9 29132950002 Georgia Walker 30.9 32.5 27.2 28.7 25.8 27133030001 Georgia Washington 30.8 31.4 29.0 29.8 25.1 25133190001 Georgia Wilkinson 33.1 33.7 31.0 31.5 28.9 29170010006 Illinois Adams 31.4 32.3 30.8 32.0 29.2 30170190004 Illinois Champaign 31.3 32.5 29.7 31.1 28.6 30170191001 Illinois Champaign 30.0 31.7 28.9 30.3 27.8 29170310022 Illinois Cook 36.6 38.6 34.9 36.6 34.3 36170310050 Illinois Cook 36.1 38.0 34.1 35.8 32.3 33170310052 Illinois Cook 40.2 41.4 38.5 39.7 37.3 38170310057 Illinois Cook 37.3 38.6 35.7 37.0 34.4 35170310076 Illinois Cook 38.0 39.1 36.3 37.3 34.8 35170311016 Illinois Cook 43.0 46.3 41.0 44.1 39.4 42170312001 Illinois Cook 37.7 40.6 35.6 38.2 34.4 37170313103 Illinois Cook 39.6 40.3 38.1 38.7 37.3 37170313301 Illinois Cook 40.2 43.3 38.2 41.0 36.8 39
B-60

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

170314007 Illinois Cook 34.3 36.4 33.6 35.7 32.2 34170314201 Illinois Cook 32.0 33.8 31.1 32.9 29.2 31170316005 Illinois Cook 39.1 41.8 37.4 39.8 36.5 39170434002 Illinois DuPage 34.6 35.9 33.7 35.2 32.9 34170650002 Illinois Hamilton 31.6 31.6 32.1 32.1 30.2 30170831001 Illinois Jersey 32.1 33.2 33.5 34.7 30.7 31170890003 Illinois Kane 33.8 35.4 32.7 34.3 31.0 32170890007 Illinois Kane 34.8 34.8 33.6 33.6 32.1 32170971007 Illinois Lake 33.0 35.0 33.2 35.2 31.1 33170990007 Illinois La Salle 28.9 29.9 27.8 28.8 26.4 27171110001 Illinois McHenry 31.5 32.6 30.8 31.8 29.7 30171132003 Illinois McLean 33.4 33.4 32.6 32.6 30.7 30171150013 Illinois Macon 33.2 34.4 33.0 34.7 31.3 32171190023 Illinois Madison 37.3 38.1 39.4 40.2 36.6 37171191007 Illinois Madison 39.1 40.1 40.0 40.6 38.0 38171192009 Illinois Madison 34.9 35.9 37.2 38.2 35.4 36171193007 Illinois Madison 34.0 34.6 36.5 37.3 34.6 35171430037 Illinois Peoria 32.7 34.1 34.2 35.2 30.6 32171570001 Illinois Randolph 28.9 29.9 29.9 31.0 27.9 28171613002 Illinois Rock Island 30.9 31.4 29.8 30.4 28.7 29171630010 Illinois Saint Clair 33.7 34.1 35.3 35.9 32.8 33171634001 Illinois Saint Clair 32.2 32.9 34.3 35.1 31.5 32171670012 Illinois Sangamon 33.4 34.1 34.0 34.9 32.0 32171971002 Illinois Will 36.4 37.1 35.1 35.8 33.6 34171971011 Illinois Will 30.7 31.7 29.3 30.2 27.6 28172010013 Illinois Winnebago 34.7 34.7 33.7 33.7 31.9 31180030004 Indiana Allen 33.1 34.6 32.2 33.6 31.5 32180030014 Indiana Allen 31.0 32.1 30.1 31.2 29.5 30180190006 Indiana Clark 37.5 39.4 38.1 40.2 36.1 37180350006 Indiana Delaware 32.0 33.6 32.8 34.3 31.5 32
B-61

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

180372001 Indiana Dubois 35.3 36.9 36.5 38.0 35.3 36180390003 Indiana Elkhart 34.4 36.3 33.8 35.6 32.7 34180431004 Indiana Floyd 33.2 34.5 34.3 35.7 32.7 34180650003 Indiana Henry 31.8 31.8 33.1 33.1 32.0 32180670003 Indiana Howard 32.2 32.9 32.3 33.0 30.9 31180830004 Indiana Knox 35.9 36.3 35.9 36.5 34.8 35180890006 Indiana Lake 34.9 35.5 33.3 33.8 32.6 33180890022 Indiana Lake 38.9 44.0 37.3 42.1 36.4 41180890026 Indiana Lake 38.4 41.3 36.3 39.3 34.9 38180890027 Indiana Lake 32.6 34.2 31.2 32.8 30.3 32180890031 Indiana Lake 34.0 34.0 33.2 33.2 31.6 31180891003 Indiana Lake 32.7 33.5 31.4 32.1 30.6 31180892004 Indiana Lake 32.9 33.9 31.2 32.0 30.6 31180892010 Indiana Lake 34.2 35.6 32.8 34.0 31.9 33180910011 Indiana LaPorte 33.6 33.6 31.8 31.8 30.3 30180910012 Indiana LaPorte 30.6 31.8 29.2 30.0 28.1 28180950009 Indiana Madison 32.8 34.0 34.2 35.4 33.1 34180970042 Indiana Marion 34.2 35.3 36.3 37.2 34.5 35180970043 Indiana Marion 38.4 39.9 40.5 42.0 38.8 40180970066 Indiana Marion 38.3 39.6 40.3 41.8 38.7 40180970078 Indiana Marion 36.6 37.6 38.7 39.7 37.1 38180970079 Indiana Marion 35.6 36.7 37.2 38.3 35.5 36180970081 Indiana Marion 38.2 39.2 40.1 41.1 38.7 39180970083 Indiana Marion 36.6 37.0 39.0 39.3 37.3 37181270020 Indiana Porter 32.5 34.6 30.9 33.4 29.4 31181270024 Indiana Porter 31.8 32.4 30.3 31.2 29.1 29181410014 Indiana St. Joseph 32.4 33.9 31.5 33.1 30.8 32181411008 Indiana St. Joseph 33.1 33.1 31.3 31.3 30.4 30181412004 Indiana St. Joseph 30.0 31.4 28.6 29.7 28.0 29181470009 Indiana Spencer 32.3 33.1 34.0 35.3 32.5 33
B-62

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

181570008 Indiana Tippecanoe 35.6 36.7 35.9 36.9 34.4 35181630006 Indiana Vanderburgh 34.8 35.5 34.3 35.0 33.3 33181630012 Indiana Vanderburgh 33.2 34.4 33.5 34.7 32.5 33181630016 Indiana Vanderburgh 32.6 33.7 32.2 33.5 31.2 32181670018 Indiana Vigo 35.1 35.1 35.3 35.3 33.9 33181670023 Indiana Vigo 34.8 36.1 35.1 36.5 33.7 35190130008 Iowa Black Hawk 30.1 30.2 28.3 28.4 27.8 28190450021 Iowa Clinton 33.9 35.9 33.4 35.1 31.1 32191032001 Iowa Johnson 34.6 35.2 33.2 33.9 32.6 33191130037 Iowa Linn 30.6 33.3 30.3 32.7 28.7 31191370002 Iowa Montgomery 27.5 27.7 26.1 26.4 25.2 25191390015 Iowa Muscatine 36.0 37.7 34.5 36.0 33.8 35191471002 Iowa Palo Alto 25.7 25.7 25.1 25.1 24.1 24191530030 Iowa Polk 28.4 29.0 27.5 27.8 26.6 27191532510 Iowa Polk 27.2 29.5 26.0 27.7 25.1 26191532520 Iowa Polk 31.4 31.4 29.1 29.1 28.6 28191550009 Iowa Pottawattamie 28.6 28.9 27.0 27.3 26.5 26191630015 Iowa Scott 31.0 32.1 30.3 31.6 29.2 29191630018 Iowa Scott 32.3 33.3 31.3 32.1 30.2 31191630019 Iowa Scott 37.1 37.1 36.8 36.8 34.0 34191770006 Iowa Van Buren 28.3 28.3 26.9 26.9 25.9 25191930017 Iowa Woodbury 26.4 28.4 24.6 26.2 24.3 26191970004 Iowa Wright 28.6 28.8 27.1 27.2 26.1 26200910007 Kansas Johnson 25.3 26.5 24.8 25.5 23.8 24200910009 Kansas Johnson 29.3 29.3 28.0 28.0 27.0 27200910010 Kansas Johnson 23.5 23.6 22.6 22.6 21.5 21201070002 Kansas Linn 25.3 26.2 24.8 25.6 23.8 24201730008 Kansas Sedgwick 23.7 25.3 23.3 24.9 22.0 23201730009 Kansas Sedgwick 25.0 26.4 23.2 24.3 22.7 24201730010 Kansas Sedgwick 25.3 27.0 24.1 25.6 23.3 24
B-63

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

201770010 Kansas Shawnee 29.1 29.1 28.1 28.1 26.7 26201770011 Kansas Shawnee 29.1 29.1 28.0 28.0 26.7 26201910002 Kansas Sumner 22.8 23.7 21.9 22.7 20.8 21202090021 Kansas Wyandotte 29.5 32.1 28.4 31.0 27.6 30202090022 Kansas Wyandotte 26.6 28.6 25.8 27.5 25.1 26210130002 Kentucky Bell 29.5 31.0 27.2 28.4 25.6 26210190017 Kentucky Boyd 33.1 34.4 30.7 31.9 29.1 30210290006 Kentucky Bullitt 34.6 35.8 35.0 36.3 33.1 34210370003 Kentucky Campbell 31.2 31.2 31.1 31.1 29.9 29210430500 Kentucky Carter 29.9 31.2 27.1 28.3 25.5 26210470006 Kentucky Christian 33.6 33.6 33.4 33.4 31.8 31210590005 Kentucky Daviess 33.8 33.8 37.0 37.0 34.9 34210670012 Kentucky Fayette 31.9 33.2 31.6 32.8 29.6 30210670014 Kentucky Fayette 32.7 33.2 32.5 33.0 30.4 30210730006 Kentucky Franklin 32.1 33.8 32.9 34.8 30.9 32210930006 Kentucky Hardin 32.8 35.1 33.0 35.4 31.2 33211010014 Kentucky Henderson 31.8 32.7 30.6 31.3 29.7 30211110043 Kentucky Jefferson 35.4 36.1 35.8 36.4 34.3 34211110044 Kentucky Jefferson 36.1 36.6 36.0 36.5 34.3 34211110048 Kentucky Jefferson 36.4 37.2 35.6 36.4 34.0 34211110051 Kentucky Jefferson 32.4 33.8 32.3 33.8 30.8 32211170007 Kentucky Kenton 34.7 35.4 34.7 35.3 33.4 34211250004 Kentucky Laurel 25.1 25.1 22.5 22.5 21.2 21211451004 Kentucky McCracken 33.6 35.9 34.4 36.8 32.5 34211510003 Kentucky Madison 30.1 30.9 27.3 27.8 25.6 26211930003 Kentucky Perry 28.5 29.8 25.3 26.4 23.7 24211950002 Kentucky Pike 30.5 31.4 27.3 28.1 25.9 26212270007 Kentucky Warren 33.1 35.1 33.7 36.3 31.6 34220171002 Louisiana Caddo 27.5 27.5 25.9 25.9 24.8 24220190009 Louisiana Calcasieu 24.2 25.8 23.9 25.5 23.1 24
B-64

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

220190010 Louisiana Calcasieu 26.3 27.2 25.8 26.6 24.9 25220290003 Louisiana Concordia 26.1 26.1 25.9 25.9 24.9 24220330009 Louisiana 

East Baton Rouge 29.3 30.5 27.8 28.8 26.5 27

220331001 Louisiana 

East Baton Rouge 25.4 26.1 24.3 24.8 23.2 23

220470005 Louisiana Iberville 28.6 29.3 27.1 27.7 25.5 26220470009 Louisiana Iberville 26.1 27.8 25.0 26.3 23.8 25220511001 Louisiana Jefferson 27.0 27.9 26.1 27.0 24.9 25220550006 Louisiana Lafayette 24.2 24.4 23.8 23.8 22.5 22220730004 Louisiana Ouachita 28.9 30.6 28.3 29.9 27.4 28220790002 Louisiana Rapides 30.2 34.3 29.8 33.8 28.5 32221050001 Louisiana Tangipahoa 29.6 30.3 27.7 28.1 26.2 26221090001 Louisiana Terrebonne 26.2 26.4 25.1 25.6 23.7 24221210001 Louisiana 

West Baton Rouge 29.0 29.8 27.5 28.2 26.3 27

230010011 Maine Androscoggin 26.5 29.0 24.9 26.9 24.5 26230030013 Maine Aroostook 24.2 25.4 23.4 24.6 23.0 24230031011 Maine Aroostook 22.9 24.3 21.7 23.1 21.3 22230050015 Maine Cumberland 27.7 30.1 25.2 27.9 24.7 27230050027 Maine Cumberland 29.2 31.1 26.7 28.4 26.0 27230090103 Maine Hancock 19.4 19.7 15.9 16.1 15.8 16230110016 Maine Kennebec 26.2 28.1 24.4 26.2 23.9 25230172011 Maine Oxford 28.3 30.4 26.4 27.7 25.9 27230190002 Maine Penobscot 22.0 24.3 19.9 22.1 19.5 21240030014 Maryland Anne Arundel 33.2 33.2 29.6 29.6 29.6 29240031003 Maryland Anne Arundel 35.5 37.4 33.8 36.7 34.4 37240032002 Maryland Anne Arundel 36.1 36.1 33.7 33.7 33.9 33240051007 Maryland Baltimore 33.3 34.1 31.2 32.1 31.0 32240053001 Maryland Baltimore 35.8 37.0 33.0 33.8 33.0 33240150003 Maryland Cecil 30.8 32.5 28.0 29.5 27.7 29
B-65

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

240251001 Maryland Harford 31.2 31.4 26.3 26.4 26.1 26240313001 Maryland Montgomery 30.9 31.8 27.8 28.5 27.3 27240330030 Maryland Prince George's 31.7 31.7 28.7 28.7 28.3 28240338003 Maryland Prince George's 33.4 34.6 29.6 30.3 29.5 30240430009 Maryland Washington 33.4 35.5 32.2 34.5 31.5 33245100006 Maryland Baltimore (City) 33.3 33.8 30.5 30.8 30.5 30245100007 Maryland Baltimore (City) 34.7 36.1 31.0 31.7 30.8 31245100008 Maryland Baltimore (City) 37.2 37.3 34.6 34.8 34.5 34245100035 Maryland Baltimore (City) 37.7 39.2 34.7 35.5 34.5 35245100040 Maryland Baltimore (City) 39.0 40.9 36.3 38.3 36.1 38245100049 Maryland Baltimore (City) 38.1 38.1 35.5 35.5 35.3 35250035001 Massachusetts Berkshire 31.0 33.5 29.4 31.7 28.9 31250051004 Massachusetts Bristol 25.0 26.8 21.6 22.5 21.5 22250092006 Massachusetts Essex 28.7 33.4 26.0 30.4 25.6 30250095005 Massachusetts Essex 27.7 29.6 24.0 25.5 23.6 25250096001 Massachusetts Essex 27.8 27.9 25.3 25.7 24.9 25250130008 Massachusetts Hampden 27.4 27.9 25.0 25.4 24.5 24250130016 Massachusetts Hampden 32.3 33.5 30.5 31.6 29.8 30250132009 Massachusetts Hampden 33.1 33.3 31.1 31.5 30.3 30250230004 Massachusetts Plymouth 28.4 28.8 24.0 24.5 23.6 24250250002 Massachusetts Suffolk 29.4 29.7 27.3 27.7 27.0 27250250027 Massachusetts Suffolk 29.2 29.5 26.9 27.0 26.7 26250250042 Massachusetts Suffolk 28.6 29.1 26.3 26.8 25.9 26250250043 Massachusetts Suffolk 32.1 33.9 29.6 31.3 29.2 30250270016 Massachusetts Worcester 30.0 30.0 26.9 27.1 26.3 26250270023 Massachusetts Worcester 30.5 30.6 27.2 27.3 26.5 26260050003 Michigan Allegan 33.8 34.0 32.3 32.9 31.1 31260170014 Michigan Bay 31.6 32.1 30.2 30.7 29.2 29260210014 Michigan Berrien 31.3 32.3 29.7 30.4 28.7 29260490021 Michigan Genesee 30.4 32.0 28.7 30.1 28.0 29
B-66

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

260650012 Michigan Ingham 31.9 32.1 30.6 31.0 29.7 30260770008 Michigan Kalamazoo 31.1 32.8 29.5 31.1 28.7 30260810020 Michigan Kent 36.5 37.1 34.1 34.7 32.7 33260990009 Michigan Macomb 35.3 35.9 33.8 34.2 33.0 33261130001 Michigan Missaukee 24.8 25.2 24.1 24.4 22.6 22261150005 Michigan Monroe 38.8 39.6 37.0 38.0 35.6 36261210040 Michigan Muskegon 34.7 36.6 32.9 34.7 31.3 32261250001 Michigan Oakland 39.9 40.4 37.9 38.4 36.9 37261390005 Michigan Ottawa 34.2 34.7 32.7 33.3 31.9 32261450018 Michigan Saginaw 30.6 30.6 29.3 29.3 28.2 28261470005 Michigan St. Clair 39.6 40.6 38.4 39.4 37.6 38261610005 Michigan Washtenaw 33.6 33.6 32.0 32.0 30.7 30261610008 Michigan Washtenaw 39.4 40.8 38.1 39.8 37.0 38261630001 Michigan Wayne 37.8 40.1 35.4 37.8 34.2 36261630015 Michigan Wayne 40.1 40.6 38.5 39.1 37.1 37261630016 Michigan Wayne 42.9 45.4 40.6 43.0 39.7 42261630019 Michigan Wayne 40.9 41.4 38.6 39.1 37.7 38261630025 Michigan Wayne 35.1 36.8 33.1 34.6 31.9 33261630033 Michigan Wayne 43.8 44.2 42.1 42.6 41.1 41261630036 Michigan Wayne 37.1 37.9 36.3 36.9 35.5 36261630039 Michigan Wayne 37.0 37.0 35.0 35.0 34.2 34270210001 Minnesota Cass 18.0 19.1 17.0 18.0 16.5 17270370470 Minnesota Dakota 25.4 25.6 24.6 24.9 23.5 23270530050 Minnesota Hennepin 27.2 28.0 25.7 26.4 24.9 25270530961 Minnesota Hennepin 25.5 26.2 24.1 24.7 23.6 24270530963 Minnesota Hennepin 26.0 27.8 24.6 26.2 23.8 25270530965 Minnesota Hennepin 24.7 25.5 23.0 23.8 22.6 23270531007 Minnesota Hennepin 25.4 25.7 24.1 24.4 23.4 23270532006 Minnesota Hennepin 26.7 27.5 25.5 26.3 24.8 25270953051 Minnesota Mille Lacs 22.0 22.2 21.4 21.8 20.9 21
B-67

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

271230866 Minnesota Ramsey 28.0 29.4 26.7 28.0 26.3 27271230868 Minnesota Ramsey 28.3 30.5 27.0 29.0 26.2 28271230871 Minnesota Ramsey 26.3 26.8 25.2 25.9 24.2 24271377001 Minnesota Saint Louis 20.3 21.2 19.4 20.3 18.7 19271377550 Minnesota Saint Louis 19.5 20.1 18.9 19.3 18.0 18271377551 Minnesota Saint Louis 23.5 23.8 22.0 22.1 21.3 21271390505 Minnesota Scott 24.9 25.8 23.9 24.6 23.2 24271453052 Minnesota Stearns 20.9 20.9 19.6 19.6 19.0 19280010004 Mississippi Adams 27.4 27.8 27.0 27.3 25.8 26280110001 Mississippi Bolivar 28.9 29.9 28.8 29.6 27.5 28280330002 Mississippi DeSoto 30.8 31.3 29.7 29.8 28.0 28280350004 Mississippi Forrest 30.4 31.1 29.0 29.4 27.9 28280470008 Mississippi Harrison 30.5 31.5 29.1 29.8 27.7 28280490010 Mississippi Hinds 28.8 29.1 27.1 27.2 26.0 26280590006 Mississippi Jackson 28.2 29.4 26.7 27.8 25.3 26280670002 Mississippi Jones 31.2 31.6 29.9 30.6 28.9 29280750003 Mississippi Lauderdale 29.8 29.8 29.6 29.9 28.3 28280810005 Mississippi Lee 32.1 33.4 30.0 31.0 28.3 29280870001 Mississippi Lowndes 32.4 33.0 28.6 29.1 26.9 27281090001 Mississippi Pearl River 28.5 28.5 27.1 27.1 25.9 25281490004 Mississippi Warren 30.2 30.2 29.9 29.9 28.8 28290190004 Missouri Boone 30.2 30.2 29.9 29.9 28.5 28290210005 Missouri Buchanan 30.1 30.1 28.6 28.6 27.7 27290370003 Missouri Cass 25.6 26.1 25.0 25.5 24.1 24290390001 Missouri Cedar 28.7 28.7 28.5 28.5 27.0 27290470005 Missouri Clay 28.0 28.6 26.7 27.3 25.7 26290770032 Missouri Greene 28.2 29.4 29.1 30.2 26.9 28290950034 Missouri Jackson 28.9 30.9 27.4 29.3 26.7 28290990012 Missouri Jefferson 33.4 34.2 35.7 36.5 32.6 33291370001 Missouri Monroe 27.8 27.8 26.9 26.9 25.6 25
B-68

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

291831002 Missouri Saint Charles 33.1 34.7 35.5 37.1 33.6 35291860006 Missouri Sainte Genevieve 31.4 32.0 32.1 33.1 29.7 30291890004 Missouri Saint Louis 32.0 32.0 34.3 34.3 31.7 31291892003 Missouri Saint Louis 33.2 33.8 33.7 34.4 32.3 33295100007 Missouri St. Louis City 33.1 33.5 36.0 36.3 33.3 33295100085 Missouri St. Louis City 33.2 33.8 35.3 35.7 32.9 33295100086 Missouri St. Louis City 32.5 32.6 34.3 34.5 32.0 32295100087 Missouri St. Louis City 34.3 34.7 36.4 36.9 33.7 34300870307 Montana Rosebud 19.7 19.7 19.2 19.2 19.1 19301111065 Montana Yellowstone 19.3 19.4 18.6 18.8 18.5 18310550019 Nebraska Douglas 26.6 28.8 26.1 28.6 25.5 27310550052 Nebraska Douglas 25.7 26.8 24.4 25.4 24.0 24310790004 Nebraska Hall 19.1 19.1 17.7 17.7 17.2 17311090022 Nebraska Lancaster 24.7 26.6 23.3 25.0 22.9 24311111002 Nebraska Lincoln 23.7 23.7 21.9 21.9 21.6 21311530007 Nebraska Sarpy 24.1 24.4 23.9 24.2 23.3 23311570003 Nebraska Scotts Bluff 16.6 16.6 15.9 15.9 15.7 15311770002 Nebraska Washington 24.1 24.8 23.2 24.1 22.7 23330012004 New Hampshire Belknap 20.5 21.4 17.6 18.3 17.1 17330050007 New Hampshire Cheshire 30.2 31.0 28.2 28.7 27.7 28330070014 New Hampshire Coos 26.5 26.9 24.7 25.1 24.2 24330090010 New Hampshire Grafton 23.0 23.0 20.3 20.3 19.8 19330110020 New Hampshire Hillsborough 28.6 28.6 26.5 26.5 26.1 26330111015 New Hampshire Hillsborough 27.3 27.3 25.7 25.7 25.3 25330115001 New Hampshire Hillsborough 25.9 25.9 22.4 22.4 21.9 21330131006 New Hampshire Merrimack 25.6 26.1 22.9 23.1 22.5 22330150014 New Hampshire Rockingham 26.3 27.8 23.6 24.9 23.2 24330190003 New Hampshire Sullivan 28.9 30.8 24.8 26.8 24.1 26340030003 New Jersey Bergen 37.0 37.7 33.6 34.1 33.0 33340070003 New Jersey Camden 36.5 38.6 32.7 34.3 31.9 33
B-69

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

340071007 New Jersey Camden 37.3 38.8 34.1 35.1 33.3 34340130015 New Jersey Essex 38.3 38.4 33.9 34.4 33.1 33340155001 New Jersey Gloucester 32.1 32.1 28.2 28.2 27.7 27340171003 New Jersey Hudson 39.0 40.5 35.7 36.1 34.9 35340172002 New Jersey Hudson 41.4 41.4 38.2 38.2 37.5 37340210008 New Jersey Mercer 34.7 35.8 30.9 31.4 30.2 30340218001 New Jersey Mercer 30.1 30.1 26.3 26.3 25.6 25340230006 New Jersey Middlesex 34.8 38.1 31.0 34.0 30.3 33340270004 New Jersey Morris 32.3 33.6 29.2 30.3 28.6 29340273001 New Jersey Morris 31.5 32.9 27.8 29.1 27.0 28340292002 New Jersey Ocean 31.5 33.9 28.0 29.7 27.2 28340310005 New Jersey Passaic 36.3 37.1 32.6 33.5 31.9 32340390004 New Jersey Union 40.4 41.4 36.7 37.2 35.6 36340390006 New Jersey Union 37.3 37.7 34.8 35.1 34.2 34340392003 New Jersey Union 36.8 37.4 33.7 34.1 32.8 33340410006 New Jersey Warren 34.0 34.7 32.0 32.8 31.6 32350010023 New Mexico Bernalillo 18.6 18.8 17.6 17.8 17.4 17350010024 New Mexico Bernalillo 16.4 17.1 15.5 16.3 15.4 16350050005 New Mexico Chaves 15.6 16.5 14.9 15.6 14.7 15350130017 New Mexico Dona Ana 32.9 35.5 31.1 33.5 30.8 33350130025 New Mexico Dona Ana 13.8 14.1 13.1 13.5 12.9 13350431003 New Mexico Sandoval 10.3 10.9 9.6 10.2 9.5 10350439011 New Mexico Sandoval 15.6 16.2 15.2 15.8 15.0 15350450006 New Mexico San Juan 12.4 12.6 12.1 12.3 12.0 12350490020 New Mexico Santa Fe 9.7 10.2 9.4 9.8 9.3 9.360010005 New York Albany 34.2 34.2 32.9 32.9 32.4 32360050080 New York Bronx 38.8 40.2 35.9 36.2 35.2 35360050083 New York Bronx 34.7 35.3 32.1 32.9 31.5 32360050110 New York Bronx 36.1 36.6 33.6 34.6 33.1 34360130011 New York Chautauqua 29.1 30.1 26.9 27.7 25.7 26
B-70

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

360290005 New York Erie 35.3 37.0 33.1 34.8 32.8 34360291007 New York Erie 33.6 35.2 31.9 33.8 31.5 33360310003 New York Essex 22.4 22.8 21.0 21.3 20.4 20360470122 New York Kings 36.9 38.0 33.5 34.3 32.6 33360551007 New York Monroe 32.2 33.0 30.4 31.2 29.9 30360590008 New York Nassau 34.0 35.0 30.4 31.0 29.4 29360610056 New York New York 39.7 40.6 37.1 38.0 36.5 37360610062 New York New York 38.8 41.6 35.3 37.0 34.6 36360610079 New York New York 37.9 40.2 34.2 36.4 33.4 35360610128 New York New York 39.4 41.8 36.2 38.0 35.4 37360632008 New York Niagara 33.6 33.7 31.7 31.9 30.5 30360671015 New York Onondaga 27.3 28.5 25.4 26.2 24.8 25360710002 New York Orange 28.9 29.4 26.3 26.9 25.7 26360810124 New York Queens 35.5 35.5 33.0 33.0 32.2 32360850055 New York Richmond 34.9 37.0 32.0 34.3 31.2 33360850067 New York Richmond 32.1 32.9 28.8 29.5 27.9 28360893001 New York St. Lawrence 22.1 22.5 20.7 21.3 20.2 20361010003 New York Steuben 27.8 28.2 25.2 25.6 24.6 25361030001 New York Suffolk 34.6 34.6 30.5 30.5 29.4 29361191002 New York Westchester 33.5 34.3 30.4 30.8 29.7 29370010002 North Carolina Alamance 31.7 32.1 27.0 27.5 26.2 26370210034 North Carolina Buncombe 30.0 30.2 26.1 26.5 25.4 25370330001 North Carolina Caswell 29.4 29.5 25.8 26.1 24.9 25370350004 North Carolina Catawba 34.5 35.5 27.5 28.1 26.9 27370370004 North Carolina Chatham 26.9 27.4 24.1 24.8 23.1 23370510009 North Carolina Cumberland 30.7 31.2 27.7 28.4 26.6 27370570002 North Carolina Davidson 31.3 32.1 27.0 27.4 26.3 26370610002 North Carolina Duplin 28.3 29.6 25.0 26.1 24.2 25370630001 North Carolina Durham 31.0 32.0 26.3 26.7 25.3 25370650004 North Carolina Edgecombe 26.7 26.9 24.8 24.9 23.8 23
B-71

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

370670022 North Carolina Forsyth 31.9 32.2 28.1 28.4 27.2 27370710016 North Carolina Gaston 30.8 30.9 24.3 24.5 23.8 23370810013 North Carolina Guilford 30.6 30.6 27.2 27.2 26.2 26370870010 North Carolina Haywood 27.7 28.5 24.6 25.3 23.5 24370990006 North Carolina Jackson 25.5 26.8 22.1 22.9 20.5 21371070004 North Carolina Lenoir 25.2 25.5 22.6 23.1 21.9 22371110004 North Carolina McDowell 31.5 32.0 26.0 26.5 25.1 25371170001 North Carolina Martin 24.8 26.2 23.2 24.1 22.4 23371190010 North Carolina Mecklenburg 32.3 32.3 28.2 28.2 27.5 27371190041 North Carolina Mecklenburg 31.7 32.1 26.7 27.2 25.9 26371190042 North Carolina Mecklenburg 30.7 31.4 24.9 25.7 24.0 24371210001 North Carolina Mitchell 30.2 31.6 25.3 27.1 24.3 26371230001 North Carolina Montgomery 28.2 29.0 24.5 25.1 23.6 24371290002 North Carolina New Hanover 24.0 25.4 21.2 22.4 20.5 21371330005 North Carolina Onslow 24.6 25.1 22.6 23.1 21.9 22371350007 North Carolina Orange 29.3 29.8 25.1 25.6 24.1 24371470005 North Carolina Pitt 26.2 26.9 23.9 24.3 23.1 23371550005 North Carolina Robeson 29.9 30.4 26.1 26.2 25.2 25371590021 North Carolina Rowan 30.2 30.2 25.4 25.4 25.1 25371730002 North Carolina Swain 27.3 28.3 23.6 24.3 22.1 22371830014 North Carolina Wake 31.6 32.2 27.6 27.8 26.5 26371890003 North Carolina Watauga 30.4 30.5 25.9 26.0 25.3 25371910005 North Carolina Wayne 29.7 30.4 26.6 27.4 25.5 26380070002 North Dakota Billings 13.0 13.6 12.6 13.1 12.6 12380130003 North Dakota Burke 16.7 16.7 16.2 16.2 16.1 16380150003 North Dakota Burleigh 17.6 18.7 16.4 17.3 16.2 17380171004 North Dakota Cass 21.2 22.5 20.5 21.7 19.8 21380530002 North Dakota McKenzie 11.9 13.0 11.4 12.5 11.4 12380570004 North Dakota Mercer 16.9 17.9 17.2 18.2 17.1 18390090003 Ohio Athens 32.3 33.2 28.9 29.4 27.3 27
B-72

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

390170003 Ohio Butler 39.2 41.1 40.3 42.3 38.3 40390170016 Ohio Butler 37.1 37.7 37.5 37.8 35.7 36390170017 Ohio Butler 37.9 37.9 38.5 38.5 36.8 36390171004 Ohio Butler 37.1 38.1 37.8 38.6 36.1 37390230005 Ohio Clark 35.3 36.4 33.6 34.7 32.1 33390250022 Ohio Clermont 34.4 34.4 34.4 34.4 32.9 32390350027 Ohio Cuyahoga 36.6 38.8 34.5 36.6 34.0 36390350034 Ohio Cuyahoga 36.5 37.9 33.7 35.7 33.2 35390350038 Ohio Cuyahoga 44.2 47.0 41.2 44.0 40.0 42390350045 Ohio Cuyahoga 38.5 41.5 36.0 39.0 35.0 38390350060 Ohio Cuyahoga 42.1 45.7 39.4 42.8 38.7 41390350065 Ohio Cuyahoga 38.6 41.0 36.5 38.9 35.4 38390351002 Ohio Cuyahoga 34.6 34.6 32.9 32.9 32.2 32390490024 Ohio Franklin 38.5 39.7 36.6 37.6 35.2 36390490025 Ohio Franklin 38.4 39.1 36.1 36.4 34.8 35390490081 Ohio Franklin 34.1 34.1 30.9 30.9 29.2 29390570005 Ohio Greene 33.0 33.0 32.1 32.1 30.9 30390610006 Ohio Hamilton 37.6 37.6 38.0 38.0 36.5 36390610014 Ohio Hamilton 38.2 39.4 37.5 38.5 36.1 37390610040 Ohio Hamilton 36.7 37.7 35.8 36.8 34.3 35390610042 Ohio Hamilton 37.3 38.2 37.2 38.0 35.9 36390610043 Ohio Hamilton 35.9 36.2 36.0 36.4 34.7 35390617001 Ohio Hamilton 38.8 39.6 37.7 38.1 36.2 36390618001 Ohio Hamilton 40.6 40.9 39.6 40.3 38.2 39390810017 Ohio Jefferson 40.7 42.4 35.3 36.8 34.0 35390811001 Ohio Jefferson 41.9 45.5 36.5 39.9 35.3 38390851001 Ohio Lake 37.1 37.1 35.0 35.0 34.4 34390870010 Ohio Lawrence 33.7 34.8 30.3 31.5 28.8 29390933002 Ohio Lorain 31.5 32.1 30.0 30.6 29.1 29390950024 Ohio Lucas 36.3 38.6 34.2 36.5 33.5 35
B-73

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

390950025 Ohio Lucas 35.1 36.8 33.4 34.5 32.6 33390950026 Ohio Lucas 34.9 36.7 33.6 35.6 32.6 34390990005 Ohio Mahoning 35.1 35.7 32.2 32.7 30.7 31390990014 Ohio Mahoning 36.8 38.2 34.2 35.8 33.1 34391130031 Ohio Montgomery 35.7 37.1 34.3 35.6 33.1 34391130032 Ohio Montgomery 37.8 40.0 36.3 38.5 34.9 36391330002 Ohio Portage 34.3 34.5 32.9 33.1 31.7 31391351001 Ohio Preble 32.8 33.9 34.3 35.5 33.2 34391450013 Ohio Scioto 34.5 36.1 31.6 33.1 30.1 31391510017 Ohio Stark 36.9 37.6 34.4 35.3 33.6 34391530017 Ohio Summit 38.0 39.6 35.6 37.2 34.6 36391530023 Ohio Summit 35.8 37.5 33.5 35.1 32.6 34391550007 Ohio Trumbull 36.2 37.8 33.9 35.6 33.0 34400159008 Oklahoma Caddo 23.9 26.0 22.1 23.9 21.7 23400219002 Oklahoma Cherokee 27.5 28.0 25.9 26.2 25.1 25400710602 Oklahoma Kay 31.8 31.8 30.8 30.8 29.9 29400719010 Oklahoma Kay 27.9 32.2 26.7 30.7 26.0 30400819005 Oklahoma Lincoln 27.8 27.8 26.4 26.4 25.7 25400970186 Oklahoma Mayes 28.7 29.1 27.7 28.1 26.8 27400979014 Oklahoma Mayes 26.1 26.3 25.1 25.2 24.1 24401010169 Oklahoma Muskogee 29.5 30.5 28.6 29.5 28.0 28401090035 Oklahoma Oklahoma 23.4 24.0 21.8 22.4 21.3 21401091037 Oklahoma Oklahoma 27.1 28.2 25.0 26.3 24.2 25401159004 Oklahoma Ottawa 29.1 29.6 27.8 28.4 26.7 27401210415 Oklahoma Pittsburg 26.3 27.2 25.1 26.1 24.4 25401359015 Oklahoma Sequoyah 31.4 31.4 30.4 30.4 29.9 29401430110 Oklahoma Tulsa 28.4 28.4 27.5 27.5 26.7 26401431127 Oklahoma Tulsa 30.3 31.0 29.6 30.3 28.7 29420010001 Pennsylvania Adams 34.9 36.2 32.1 32.8 31.5 32420030008 Pennsylvania Allegheny 39.4 39.9 35.9 36.3 34.7 35
B-74

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

420030021 Pennsylvania Allegheny 35.1 35.1 32.2 32.2 31.4 31420030064 Pennsylvania Allegheny 64.2 68.2 58.8 62.3 57.2 60420030067 Pennsylvania Allegheny 37.2 39.4 33.0 34.7 31.5 33420030093 Pennsylvania Allegheny 45.6 51.5 41.1 46.2 39.7 44420030095 Pennsylvania Allegheny 38.7 40.7 34.3 36.6 33.0 35420030116 Pennsylvania Allegheny 42.5 42.5 37.1 37.1 35.5 35420030133 Pennsylvania Allegheny 39.2 39.2 34.5 34.5 33.1 33420031008 Pennsylvania Allegheny 41.3 42.8 38.0 39.3 36.7 37420031301 Pennsylvania Allegheny 40.3 42.4 36.6 38.6 35.5 37420033007 Pennsylvania Allegheny 37.5 43.1 33.8 38.5 32.6 36420039002 Pennsylvania Allegheny 37.8 37.8 34.3 34.3 33.0 33420070014 Pennsylvania Beaver 43.4 44.6 37.7 39.1 36.6 38420110011 Pennsylvania Berks 37.7 39.1 35.8 37.0 35.4 36420170012 Pennsylvania Bucks 34.0 34.8 31.6 32.1 30.8 31420210011 Pennsylvania Cambria 39.0 39.4 40.3 40.7 39.4 39420270100 Pennsylvania Centre 36.2 37.6 33.9 35.0 33.2 34420290100 Pennsylvania Chester 36.7 36.7 33.0 33.0 32.5 32420410101 Pennsylvania Cumberland 38.0 40.2 35.3 37.0 35.0 36420430401 Pennsylvania Dauphin 38.0 39.0 35.7 37.1 35.3 36420450002 Pennsylvania Delaware 35.2 35.9 33.0 33.3 32.3 32420490003 Pennsylvania Erie 34.4 34.4 32.7 32.7 32.0 32420692006 Pennsylvania Lackawanna 31.5 32.6 28.8 29.7 28.1 29420710007 Pennsylvania Lancaster 40.8 44.0 37.7 40.1 37.5 39420770004 Pennsylvania Lehigh 36.4 36.4 34.6 34.6 34.1 34420791101 Pennsylvania Luzerne 32.4 32.4 28.9 28.9 28.1 28420850100 Pennsylvania Mercer 36.3 36.3 33.5 33.5 32.2 32420950025 Pennsylvania Northampton 36.7 37.4 33.8 34.3 33.1 33420990301 Pennsylvania Perry 30.4 30.4 28.9 28.9 28.7 28421010004 Pennsylvania Philadelphia 36.5 36.7 33.6 34.1 32.8 33421010024 Pennsylvania Philadelphia 35.9 35.9 32.9 32.9 32.1 32
B-75

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

421010047 Pennsylvania Philadelphia 37.3 37.7 33.3 33.7 32.5 32421250005 Pennsylvania Washington 35.5 36.3 31.6 32.3 30.7 31421250200 Pennsylvania Washington 33.4 33.5 29.2 29.2 28.4 28421255001 Pennsylvania Washington 38.1 39.9 33.9 35.5 32.7 34421290008 Pennsylvania Westmoreland 37.1 37.5 33.4 33.7 32.3 32421330008 Pennsylvania York 38.2 40.7 35.9 38.8 35.5 38440070022 Rhode Island Providence 29.4 29.4 26.9 26.9 26.5 26440070026 Rhode Island Providence 30.6 32.2 28.0 29.0 27.5 28440070028 Rhode Island Providence 28.2 28.4 25.6 25.7 25.2 25440071010 Rhode Island Providence 28.8 29.7 26.6 27.0 26.2 26450130007 South Carolina Beaufort 30.2 32.6 26.8 28.6 25.4 27450190048 South Carolina Charleston 27.8 28.0 25.2 25.5 24.2 24450190049 South Carolina Charleston 27.9 27.9 26.2 26.3 24.9 25450250001 South Carolina Chesterfield 28.7 29.9 25.5 26.5 24.8 25450370001 South Carolina Edgefield 32.2 33.7 29.5 31.0 27.2 29450410002 South Carolina Florence 28.8 28.9 26.0 26.0 24.9 24450430009 South Carolina Georgetown 29.2 29.5 26.5 26.9 25.5 26450450008 South Carolina Greenville 32.1 32.4 29.4 29.4 28.1 28450450009 South Carolina Greenville 32.5 33.5 29.0 29.3 27.7 28450470003 South Carolina Greenwood 30.0 31.0 26.6 26.9 24.5 25450510002 South Carolina Horry 28.6 29.2 26.1 26.7 25.2 25450630008 South Carolina Lexington 32.8 33.4 29.8 30.6 28.7 29450730001 South Carolina Oconee 28.4 29.3 25.2 26.2 23.1 23450790007 South Carolina Richland 31.3 32.0 27.8 28.2 26.5 26450790019 South Carolina Richland 33.2 33.8 30.2 31.0 28.8 29450830010 South Carolina Spartanburg 32.4 32.4 26.9 26.9 26.1 26460110002 South Dakota Brookings 23.5 24.9 22.4 23.7 21.6 22460130003 South Dakota Brown 18.7 19.2 17.8 18.0 17.2 17460290002 South Dakota Codington 23.6 24.0 23.0 23.4 22.2 22460330132 South Dakota Custer 14.3 14.3 13.9 13.9 13.9 13
B-76

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

460710001 South Dakota Jackson 12.7 13.4 12.2 12.9 12.1 12460990006 South Dakota Minnehaha 24.1 25.5 23.1 24.5 22.3 23460990007 South Dakota Minnehaha 23.9 25.1 22.4 23.3 21.8 22461030016 South Dakota Pennington 17.2 17.2 16.1 16.2 15.9 16461030020 South Dakota Pennington 18.5 19.2 17.6 18.2 17.5 18461031001 South Dakota Pennington 15.9 16.6 15.0 15.8 14.8 15470090011 Tennessee Blount 32.5 34.2 30.4 32.0 29.1 30470370023 Tennessee Davidson 33.5 34.3 34.4 35.1 32.9 33470370025 Tennessee Davidson 30.9 31.5 31.5 32.1 29.9 30470370036 Tennessee Davidson 32.7 33.5 33.9 34.8 32.2 33470450004 Tennessee Dyer 31.9 33.3 32.9 34.4 31.0 32470650031 Tennessee Hamilton 33.2 35.2 29.7 30.7 28.4 29470651011 Tennessee Hamilton 29.7 31.3 26.7 28.1 25.5 26470654002 Tennessee Hamilton 33.5 34.3 29.2 30.5 27.9 29470930028 Tennessee Knox 36.6 36.6 33.9 33.9 32.4 32470931017 Tennessee Knox 33.4 33.9 31.2 31.6 30.0 30470990002 Tennessee Lawrence 28.4 31.7 27.3 31.0 26.1 29471050108 Tennessee Loudon 32.2 33.3 30.4 31.3 28.8 29471071002 Tennessee McMinn 32.4 33.9 30.1 31.5 28.4 29471192007 Tennessee Maury 30.8 31.7 30.8 31.9 29.4 30471251009 Tennessee Montgomery 36.3 37.5 36.6 37.9 35.2 36471410001 Tennessee Putnam 32.6 32.6 31.0 31.0 29.0 29471450004 Tennessee Roane 30.2 31.4 27.8 28.9 26.6 27471570014 Tennessee Shelby 32.2 33.5 31.0 31.8 29.3 30471570038 Tennessee Shelby 32.5 33.5 32.0 33.0 30.3 31471570047 Tennessee Shelby 33.5 33.8 32.4 32.9 30.9 31471571004 Tennessee Shelby 29.8 30.4 29.6 30.4 28.2 28471631007 Tennessee Sullivan 31.1 32.0 28.0 28.8 27.2 28471650007 Tennessee Sumner 33.6 34.5 35.1 36.0 33.1 34480370004 Texas Bowie 29.4 30.0 28.3 28.6 27.2 27
B-77

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

481130069 Texas Dallas 25.7 27.7 24.3 25.8 23.9 25481130087 Texas Dallas 24.2 27.0 21.7 24.3 21.0 23481350003 Texas Ector 17.8 18.2 18.8 19.2 17.1 17481410037 Texas El Paso 22.9 22.9 22.0 22.0 21.9 21482010058 Texas Harris 25.4 26.3 24.5 25.2 23.6 24482011035 Texas Harris 30.8 31.4 29.9 30.2 28.7 29482030002 Texas Harrison 25.9 26.2 24.6 24.9 24.0 24482150043 Texas Hidalgo 26.4 27.9 26.4 28.2 25.8 27482450021 Texas Jefferson 26.0 26.8 25.4 26.3 24.4 25483550032 Texas Nueces 27.5 30.2 27.0 29.9 25.9 28483611001 Texas Orange 27.7 28.7 27.2 28.0 26.2 27484391002 Texas Tarrant 25.3 26.8 23.3 24.9 22.9 24484391006 Texas Tarrant 25.7 27.9 24.0 26.1 23.7 25500010002 Vermont Addison 28.2 28.2 26.1 26.1 25.6 25500010003 Vermont Addison 31.7 31.7 29.4 29.4 28.8 28500030004 Vermont Bennington 26.4 28.5 24.2 26.3 23.6 25500070012 Vermont Chittenden 29.8 30.3 27.5 27.8 26.7 27500070014 Vermont Chittenden 30.1 30.1 28.3 28.3 27.6 27500210002 Vermont Rutland 30.6 31.3 29.1 29.4 28.6 28510130020 Virginia Arlington 34.1 36.3 30.9 33.5 30.1 32510360002 Virginia Charles 31.7 32.1 27.3 27.8 26.5 27510410003 Virginia Chesterfield 31.2 32.6 25.7 27.0 24.9 26510590030 Virginia Fairfax 34.4 35.0 30.9 31.7 30.5 31510591005 Virginia Fairfax 33.7 35.2 30.4 32.8 30.0 32510595001 Virginia Fairfax 33.3 33.7 30.8 31.2 30.1 30510870014 Virginia Henrico 31.9 32.9 27.1 28.2 26.3 27510870015 Virginia Henrico 29.1 29.6 25.6 26.2 24.9 25511071005 Virginia Loudoun 34.4 35.7 30.9 32.3 30.6 32511390004 Virginia Page 30.0 30.9 28.1 29.0 27.2 28515200006 Virginia Bristol City 30.2 30.5 26.2 26.5 25.3 25
B-78

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

516500004 Virginia Hampton City 29.0 29.2 26.8 27.6 25.9 26516800015 Virginia Lynchburg City 30.7 31.1 26.6 26.9 25.6 25517100024 Virginia Norfolk City 29.6 29.9 27.3 27.6 26.4 26517700014 Virginia Roanoke City 32.7 33.2 28.5 28.7 27.2 27517750010 Virginia Salem City 34.0 34.0 29.4 29.4 28.4 28518100008 Virginia 

Virginia Beach City 30.0 30.2 27.7 27.8 26.8 26

540030003 West Virginia Berkeley 34.5 35.8 32.0 32.7 31.6 32540090005 West Virginia Brooke 39.4 41.5 33.9 36.1 33.0 35540090011 West Virginia Brooke 43.9 44.9 39.9 40.8 39.2 40540110006 West Virginia Cabell 35.1 36.6 32.1 33.6 30.8 32540291004 West Virginia Hancock 40.6 41.2 34.3 34.6 32.7 33540330003 West Virginia Harrison 33.5 34.6 33.0 34.0 31.3 32540390010 West Virginia Kanawha 34.7 35.5 32.2 32.9 30.9 31540390011 West Virginia Kanawha 33.1 33.1 30.8 30.8 29.6 29540391005 West Virginia Kanawha 36.9 37.7 34.3 35.1 33.0 33540490006 West Virginia Marion 33.6 33.7 34.3 34.4 32.8 32540511002 West Virginia Marshall 33.9 34.8 30.0 30.9 28.7 29540610003 West Virginia Monongalia 35.6 36.2 33.7 34.3 31.2 31540690010 West Virginia Ohio 32.0 32.0 27.9 27.9 26.9 26540810002 West Virginia Raleigh 30.6 31.3 27.8 28.3 26.7 27540890001 West Virginia Summers 31.2 31.2 27.9 27.9 26.6 26541071002 West Virginia Wood 35.4 36.7 32.7 33.9 31.1 32550030010 Wisconsin Ashland 18.6 20.5 17.8 19.4 17.1 18550090005 Wisconsin Brown 36.5 37.0 35.0 35.4 34.7 35550090009 Wisconsin Brown 35.8 35.8 34.4 34.4 34.2 34550250047 Wisconsin Dane 35.5 36.9 35.1 36.1 34.2 35550270007 Wisconsin Dodge 31.8 33.1 30.8 32.3 29.6 30550410007 Wisconsin Forest 25.2 25.2 23.9 23.9 23.2 23550430009 Wisconsin Grant 34.3 35.0 32.5 33.0 31.7 32
B-79

24-Hour PM2.5 Design Values (μg/m

Monitor ID State County 

2003 - 2007 

Average 

Ambient 

Values 

2003 - 2007 

Maximum 

Ambient 

Values 

2012 

Base Case 

Average 

Values 

2012 

Base Case 

Maximum 

Values 

2014 

Base Case 

Average 

Values 

20

Base 

Maxi

Val

550590019 Wisconsin Kenosha 32.7 34.0 32.2 33.5 31.4 32550710007 Wisconsin Manitowoc 29.7 31.6 29.0 30.8 28.3 30550790010 Wisconsin Milwaukee 38.6 40.0 37.7 39.0 37.0 38550790026 Wisconsin Milwaukee 37.3 41.3 36.3 40.1 35.3 39550790043 Wisconsin Milwaukee 39.9 40.8 38.8 39.7 37.3 38550790059 Wisconsin Milwaukee 35.5 37.0 34.8 36.3 33.5 35550790099 Wisconsin Milwaukee 37.7 38.7 36.8 37.7 35.5 37550870009 Wisconsin Outagamie 32.8 34.4 31.2 32.8 30.9 32550890009 Wisconsin Ozaukee 32.5 34.0 31.8 33.2 30.9 32551091002 Wisconsin St. Croix 26.6 26.6 25.5 25.5 24.7 24551110007 Wisconsin Sauk 28.6 28.8 27.5 27.7 26.7 27551198001 Wisconsin Taylor 25.3 26.0 23.9 24.7 23.3 24551250001 Wisconsin Vilas 22.6 23.8 21.4 22.6 20.7 21551330027 Wisconsin Waukesha 35.4 36.2 34.9 35.6 33.3 33560050877 Wyoming Campbell 18.6 18.6 18.0 18.0 17.9 17560050892 Wyoming Campbell 12.1 12.2 11.9 12.0 11.9 12560050899 Wyoming Campbell 12.7 13.5 12.5 13.2 12.5 13560090819 Wyoming Converse 10.0 10.5 9.7 10.3 9.7 10560131003 Wyoming Fremont 29.8 31.9 28.3 30.5 28.0 30560210001 Wyoming Laramie 11.9 12.7 11.5 12.2 11.4 12560330002 Wyoming Sheridan 30.8 32.5 29.8 31.3 29.6 31
B-80

Differences in 8-Hour Ozone Average Design Values (ppb) by Site: 

2014 Remedy Scenario Compared to the 2012 Base Case and the 2014 Base Ca

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

10030010 Alabama Baldwin -3.9 -2.2 10270001 Alabama Clay -4.2 -0.6 10331002 Alabama Colbert -2.0 -0.2 10510001 Alabama Elmore -2.7 -0.3 10550011 Alabama Etowah -3.3 -0.4 10690004 Alabama Houston -3.0 -0.3 10730023 Alabama Jefferson -2.7 -0.2 10731003 Alabama Jefferson -2.8 -0.2 10731005 Alabama Jefferson -3.1 -0.2 10731009 Alabama Jefferson -2.6 -0.2 10731010 Alabama Jefferson -2.8 -0.2 10732006 Alabama Jefferson -2.9 -0.2 10735002 Alabama Jefferson -2.7 -0.2 10735003 Alabama Jefferson -2.7 -0.3 10736002 Alabama Jefferson -2.8 -0.2 10790002 Alabama Lawrence -2.7 -0.1 10890014 Alabama Madison -3.4 -0.1 10970003 Alabama Mobile -3.4 -1.7 10972005 Alabama Mobile -3.7 -1.9 11011002 Alabama Montgomery -2.6 -0.2 11030011 Alabama Morgan -2.5 -0.2 11130002 Alabama Russell -3.6 -0.4 11170004 Alabama Shelby -3.2 -0.2 11190002 Alabama Sumter -1.9 -0.1 11210003 Alabama Talladega -3.0 -0.3 11250010 Alabama Tuscaloosa -2.8 -0.1 50350005 Arkansas Crittenden -2.9 -0.1 51190007 Arkansas Pulaski -3.6 -1.2 
B-81

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

51191002 Arkansas Pulaski -3.7 -1.1 51191005 Arkansas Pulaski -3.4 -1.1 80013001 Colorado Adams -0.6 0.0 80050002 Colorado Arapahoe -0.9 0.0 80130011 Colorado Boulder -1.1 0.1 80310002 Colorado Denver -0.5 0.0 80310014 Colorado Denver -0.7 0.0 80350004 Colorado Douglas -1.2 0.1 80590002 Colorado Jefferson -0.6 0.1 80590005 Colorado Jefferson -0.8 0.1 80590006 Colorado Jefferson -1.1 0.1 80590011 Colorado Jefferson -0.7 0.0 80691004 Colorado Larimer -1.0 0.1 81230009 Colorado Weld -1.0 0.1 90010017 Connecticut Fairfield -1.8 -0.1 90011123 Connecticut Fairfield -2.2 -0.1 90013007 Connecticut Fairfield -2.0 -0.2 90019003 Connecticut Fairfield -1.8 -0.1 90031003 Connecticut Hartford -2.3 0.0 90050005 Connecticut Litchfield -2.5 0.0 90070007 Connecticut Middlesex -2.3 -0.1 90090027 Connecticut New Haven -1.9 -0.1 90093002 Connecticut New Haven -2.3 -0.1 90110008 Connecticut New London -2.2 -0.1 90131001 Connecticut Tolland -2.6 -0.1 

100010002 Delaware Kent -2.1 -0.1 100031007 Delaware New Castle -1.9 -0.1 100031010 Delaware New Castle -1.8 0.0 100031013 Delaware New Castle -1.9 -0.1 100051002 Delaware Sussex -2.2 -0.1 100051003 Delaware Sussex -1.9 0.0 110010025 

District Of Columbia District of Columbia -1.7 0.0 
B-82

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

110010041 

District Of Columbia District of Columbia -1.9 -0.2 

110010043 

District Of Columbia District of Columbia -1.9 -0.1 

120010025 Florida Alachua -5.8 -3.3 120030002 Florida Baker -3.8 -1.4 120050006 Florida Bay -5.2 -2.8 120090007 Florida Brevard -3.9 -0.8 120094001 Florida Brevard -4.3 -0.9 120110031 Florida Broward -0.4 -0.1 120112003 Florida Broward -1.2 -0.2 120118002 Florida Broward -1.0 -0.2 120210004 Florida Collier -2.6 -0.3 120230002 Florida Columbia -3.7 -1.1 120310077 Florida Duval -3.7 -1.7 120310100 Florida Duval -4.1 -1.8 120330004 Florida Escambia -6.3 -4.7 120330018 Florida Escambia -7.3 -5.6 120330024 Florida Escambia -7.2 -5.5 120570081 Florida Hillsborough -2.4 -0.6 120570110 Florida Hillsborough -2.2 -0.6 120571035 Florida Hillsborough -2.2 -0.6 120571065 Florida Hillsborough -2.8 -0.9 120573002 Florida Hillsborough -1.9 -0.3 120574004 Florida Hillsborough -2.1 -0.4 120690002 Florida Lake -3.8 -0.7 120712002 Florida Lee -2.5 -0.4 120713002 Florida Lee -2.7 -0.5 120730012 Florida Leon -3.2 -0.7 120730013 Florida Leon -3.4 -0.7 120813002 Florida Manatee -2.6 -0.7 120814012 Florida Manatee -2.7 -0.8 120814013 Florida Manatee -2.4 -0.8 
B-83

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

120830003 Florida Marion -4.3 -1.7 120830004 Florida Marion -4.6 -2.4 120860027 Florida Miami-Dade -0.5 -0.3 120860029 Florida Miami-Dade -0.8 -0.2 120950008 Florida Orange -4.1 -0.9 120952002 Florida Orange -3.6 -0.6 120972002 Florida Osceola -3.5 -0.7 120990020 Florida Palm Beach -1.9 -0.1 121010005 Florida Pasco -3.1 -1.4 121012001 Florida Pasco -2.8 -0.9 121030004 Florida Pinellas -2.5 -0.8 121030018 Florida Pinellas -2.2 -0.7 121035002 Florida Pinellas -2.4 -0.7 121056005 Florida Polk -2.8 -1.0 121056006 Florida Polk -3.1 -1.1 121111002 Florida St. Lucie -2.6 -0.4 121130015 Florida Santa Rosa -7.3 -5.5 121151005 Florida Sarasota -2.6 -0.7 121151006 Florida Sarasota -2.5 -0.7 121152002 Florida Sarasota -2.6 -0.8 121171002 Florida Seminole -4.2 -0.6 121272001 Florida Volusia -4.6 -0.8 121275002 Florida Volusia -4.4 -0.6 121290001 Florida Wakulla -2.8 -0.7 130210012 Georgia Bibb -5.3 -0.3 130210013 Georgia Bibb -5.7 -0.3 130510021 Georgia Chatham -2.8 -0.5 130550001 Georgia Chattooga -3.7 -0.2 130590002 Georgia Clarke -4.4 -0.2 130670003 Georgia Cobb -4.1 -0.2 130730001 Georgia Columbia -3.1 -0.3 130770002 Georgia Coweta -5.6 -1.0 130850001 Georgia Dawson -3.9 -0.2 
B-84

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

130890002 Georgia DeKalb -3.5 -0.1 130893001 Georgia DeKalb -3.2 -0.2 130970004 Georgia Douglas -4.8 -0.2 131130001 Georgia Fayette -3.5 -0.2 131210055 Georgia Fulton -3.7 -0.2 131270006 Georgia Glynn -4.0 -1.9 131350002 Georgia Gwinnett -4.0 -0.2 131510002 Georgia Henry -4.2 -0.2 132130003 Georgia Murray -4.0 -0.7 132150008 Georgia Muscogee -4.0 -0.4 132151003 Georgia Muscogee -3.7 -0.3 132230003 Georgia Paulding -4.3 -0.2 132450091 Georgia Richmond -3.4 -0.4 132470001 Georgia Rockdale -4.5 -0.2 132611001 Georgia Sumter -3.5 -0.4 170010006 Illinois Adams -2.2 -0.8 170190004 Illinois Champaign -1.7 -0.3 170230001 Illinois Clark -1.8 -0.4 170310001 Illinois Cook -1.2 -0.1 170310032 Illinois Cook -1.2 -0.2 170310064 Illinois Cook -1.2 -0.2 170310072 Illinois Cook -1.2 -0.2 170310076 Illinois Cook -1.0 -0.2 170311003 Illinois Cook -1.1 -0.2 170311601 Illinois Cook -1.3 -0.1 170314002 Illinois Cook -0.7 -0.2 170314007 Illinois Cook -1.0 -0.1 170314201 Illinois Cook -1.0 -0.1 170317002 Illinois Cook -1.3 -0.3 170436001 Illinois DuPage -1.0 -0.1 170491001 Illinois Effingham -1.7 -0.2 170650002 Illinois Hamilton -1.6 0.1 170831001 Illinois Jersey -2.5 -0.5 
B-85

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

170890005 Illinois Kane -1.6 -0.2 170971002 Illinois Lake -1.4 -0.3 170971007 Illinois Lake -1.5 -0.3 171110001 Illinois McHenry -1.8 -0.2 171132003 Illinois McLean -2.2 -0.3 171150013 Illinois Macon -2.0 -0.5 171170002 Illinois Macoupin -2.7 -0.6 171190008 Illinois Madison -2.8 -0.7 171191009 Illinois Madison -2.7 -0.6 171193007 Illinois Madison -2.8 -0.7 171430024 Illinois Peoria -2.2 -0.2 171431001 Illinois Peoria -2.4 -0.2 171570001 Illinois Randolph -1.8 -0.1 171613002 Illinois Rock Island -2.4 -1.1 171630010 Illinois Saint Clair -2.2 -0.6 171670010 Illinois Sangamon -2.1 -0.4 171971011 Illinois Will -1.6 -0.1 172010009 Illinois Winnebago -2.1 -0.2 172012001 Illinois Winnebago -2.1 -0.2 180030002 Indiana Allen -2.4 -0.2 180030004 Indiana Allen -2.3 -0.2 180110001 Indiana Boone -2.7 -0.4 180150002 Indiana Carroll -2.2 -0.3 180190008 Indiana Clark -2.8 -0.8 180350010 Indiana Delaware -2.8 -0.4 180390007 Indiana Elkhart -2.6 -0.4 180431004 Indiana Floyd -2.5 -0.7 180550001 Indiana Greene -2.2 -0.5 180570005 Indiana Hamilton -3.0 -0.5 180590003 Indiana Hancock -2.8 -0.5 180630004 Indiana Hendricks -2.4 -0.4 180690002 Indiana Huntington -2.2 -0.1 180710001 Indiana Jackson -2.3 -0.5 
B-86

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

180810002 Indiana Johnson -2.7 -0.6 180890022 Indiana Lake -1.4 -0.3 180890030 Indiana Lake -1.4 -0.4 180892008 Indiana Lake -1.3 -0.3 180910005 Indiana LaPorte -1.8 -0.3 180910010 Indiana LaPorte -2.0 -0.3 180950010 Indiana Madison -2.9 -0.5 180970042 Indiana Marion -2.4 -0.7 180970050 Indiana Marion -2.5 -0.5 180970057 Indiana Marion -2.3 -0.5 180970073 Indiana Marion -2.4 -0.5 181090005 Indiana Morgan -2.9 -0.7 181230009 Indiana Perry -2.5 -0.1 181270024 Indiana Porter -1.6 -0.3 181270026 Indiana Porter -1.8 -0.4 181290003 Indiana Posey -2.0 0.0 181410010 Indiana St. Joseph -2.4 -0.5 181410015 Indiana St. Joseph -2.4 -0.4 181411007 Indiana St. Joseph -2.6 -0.5 181450001 Indiana Shelby -2.5 -0.7 181630012 Indiana Vanderburgh -2.0 0.2 181630013 Indiana Vanderburgh -1.9 0.1 181670018 Indiana Vigo -2.1 -0.6 181670024 Indiana Vigo -2.5 -0.9 181730008 Indiana Warrick -1.6 0.3 181730009 Indiana Warrick -2.0 -0.1 181730011 Indiana Warrick -1.6 0.3 190450021 Iowa Clinton -2.3 -0.8 190851101 Iowa Harrison -3.1 -1.8 191130028 Iowa Linn -2.0 -0.6 191130033 Iowa Linn -2.6 -1.1 191530058 Iowa Polk -2.1 -0.5 191630014 Iowa Scott -2.5 -0.9 
B-87

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

191632011 Iowa Scott -2.7 -1.1 191690011 Iowa Story -2.3 -0.9 200450004 Kansas Douglas -3.4 -1.9 200910010 Kansas Johnson -3.7 -2.2 201030003 Kansas Leavenworth -3.0 -1.5 201070002 Kansas Linn -5.3 -4.1 201730001 Kansas Sedgwick -2.5 -0.8 201730010 Kansas Sedgwick -2.7 -0.8 201910002 Kansas Sumner -2.6 -0.6 202090021 Kansas Wyandotte -3.0 -1.7 210130002 Kentucky Bell -2.9 -0.2 210150003 Kentucky Boone -2.6 -0.8 210190017 Kentucky Boyd -1.7 -0.2 210290006 Kentucky Bullitt -2.5 -0.7 210370003 Kentucky Campbell -2.2 -0.7 210430500 Kentucky Carter -1.8 -0.2 210470006 Kentucky Christian -2.6 -0.3 210590005 Kentucky Daviess -2.0 0.0 210610501 Kentucky Edmonson -2.3 -0.1 210670001 Kentucky Fayette -2.2 -0.3 210670012 Kentucky Fayette -2.4 -0.3 210890007 Kentucky Greenup -1.7 -0.2 210910012 Kentucky Hancock -2.1 0.0 210930006 Kentucky Hardin -2.4 -0.4 211010014 Kentucky Henderson -1.8 0.2 211110027 Kentucky Jefferson -2.6 -0.6 211110051 Kentucky Jefferson -2.5 -0.9 211111021 Kentucky Jefferson -2.2 -0.6 211130001 Kentucky Jessamine -2.3 -0.3 211170007 Kentucky Kenton -2.3 -0.7 211390003 Kentucky Livingston -1.9 0.0 211451024 Kentucky McCracken -1.9 -0.2 211490001 Kentucky McLean -1.9 0.2 
B-88

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

211850004 Kentucky Oldham -3.2 -0.7 211950002 Kentucky Pike -1.9 0.0 211990003 Kentucky Pulaski -4.8 -0.5 212130004 Kentucky Simpson -2.7 -0.1 212210013 Kentucky Trigg -2.0 0.0 212270008 Kentucky Warren -2.2 -0.2 220050004 Louisiana Ascension -1.9 -0.3 220110002 Louisiana Beauregard -1.6 -0.7 220150008 Louisiana Bossier -2.7 -0.3 220170001 Louisiana Caddo -2.8 -0.4 220190002 Louisiana Calcasieu -1.8 -0.6 220190008 Louisiana Calcasieu -1.3 -0.4 220190009 Louisiana Calcasieu -2.1 -0.7 220330003 Louisiana East Baton Rouge -1.8 -0.4 220330009 Louisiana East Baton Rouge -1.6 -0.4 220330013 Louisiana East Baton Rouge -1.6 -0.2 220331001 Louisiana East Baton Rouge -1.4 -0.2 220430001 Louisiana Grant -4.9 -3.1 220470007 Louisiana Iberville -2.0 -0.5 220470009 Louisiana Iberville -1.8 -0.5 220470012 Louisiana Iberville -1.8 -0.4 220511001 Louisiana Jefferson -2.0 -0.4 220550005 Louisiana Lafayette -2.7 -0.7 220550007 Louisiana Lafayette -2.1 -0.6 220570004 Louisiana Lafourche -1.9 -0.5 220630002 Louisiana Livingston -1.8 -0.2 220710012 Louisiana Orleans -1.6 -0.4 220730004 Louisiana Ouachita -2.7 -0.7 220770001 Louisiana Pointe Coupee -1.6 -0.2 220870002 Louisiana St. Bernard -1.4 -0.3 220890003 Louisiana St. Charles -1.7 -0.4 220930002 Louisiana St. James -1.6 -0.4 220950002 Louisiana St. John the Baptist -1.5 -0.4 
B-89

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

221010003 Louisiana St. Mary -2.2 -0.5 221210001 Louisiana West Baton Rouge -1.6 -0.3 230050027 Maine Cumberland -1.7 0.0 230052003 Maine Cumberland -2.1 0.0 230090102 Maine Hancock -1.9 0.0 230090103 Maine Hancock -1.8 0.0 230090301 Maine Hancock -1.7 0.0 230112005 Maine Kennebec -1.8 0.0 230130004 Maine Knox -2.0 0.0 230173001 Maine Oxford -1.6 0.1 230194008 Maine Penobscot -1.7 0.0 230230004 Maine Sagadahoc -1.9 0.0 230310038 Maine York -2.2 0.0 230312002 Maine York -2.1 0.0 230313002 Maine York -2.1 0.0 240030014 Maryland Anne Arundel -2.7 -0.1 240051007 Maryland Baltimore -1.7 -0.1 240053001 Maryland Baltimore -1.7 -0.1 240090011 Maryland Calvert -2.2 -0.1 240130001 Maryland Carroll -2.6 -0.1 240150003 Maryland Cecil -2.3 -0.1 240170010 Maryland Charles -2.7 -0.1 240210037 Maryland Frederick -2.5 0.0 240230002 Maryland Garrett -2.3 -0.8 240251001 Maryland Harford -2.0 -0.1 240259001 Maryland Harford -1.9 -0.1 240290002 Maryland Kent -2.0 -0.1 240313001 Maryland Montgomery -2.0 -0.1 240330030 Maryland Prince George's -2.3 -0.1 240338003 Maryland Prince George's -2.7 -0.2 240430009 Maryland Washington -2.4 -0.1 250010002 Massachusetts Barnstable -2.0 0.0 250034002 Massachusetts Berkshire -2.2 -0.1 
B-90

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

250051002 Massachusetts Bristol -2.0 -0.1 250070001 Massachusetts Dukes -1.9 0.0 250092006 Massachusetts Essex -1.8 0.1 250094004 Massachusetts Essex -2.1 0.1 250095005 Massachusetts Essex -2.2 0.0 250130008 Massachusetts Hampden -2.6 -0.1 250150103 Massachusetts Hampshire -2.2 0.0 250154002 Massachusetts Hampshire -2.4 0.0 250170009 Massachusetts Middlesex -2.4 0.0 250171102 Massachusetts Middlesex -2.3 -0.1 250213003 Massachusetts Norfolk -2.3 0.0 250250041 Massachusetts Suffolk -2.0 0.0 250250042 Massachusetts Suffolk -1.6 0.0 250270015 Massachusetts Worcester -2.4 -0.1 260050003 Michigan Allegan -2.6 -0.5 260190003 Michigan Benzie -2.4 -0.4 260210014 Michigan Berrien -2.3 -0.4 260270003 Michigan Cass -2.7 -0.6 260370001 Michigan Clinton -2.5 -0.3 260490021 Michigan Genesee -2.4 -0.3 260492001 Michigan Genesee -2.3 -0.3 260630007 Michigan Huron -1.9 -0.2 260650012 Michigan Ingham -2.6 -0.3 260770008 Michigan Kalamazoo -2.4 -0.4 260810020 Michigan Kent -2.7 -0.5 260810022 Michigan Kent -2.8 -0.5 260890001 Michigan Leelanau -2.1 -0.4 260910007 Michigan Lenawee -2.2 -0.5 260990009 Michigan Macomb -1.8 -0.3 260991003 Michigan Macomb -1.5 -0.1 261050007 Michigan Mason -2.5 -0.6 261130001 Michigan Missaukee -2.3 -0.6 261210039 Michigan Muskegon -2.4 -0.4 
B-91

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

261250001 Michigan Oakland -1.4 -0.3 261390005 Michigan Ottawa -2.6 -0.5 261470005 Michigan St. Clair -2.3 -0.3 261530001 Michigan Schoolcraft -2.2 -0.3 261610008 Michigan Washtenaw -1.7 -0.3 261630001 Michigan Wayne -1.6 -0.3 261630016 Michigan Wayne -1.7 -0.3 261630019 Michigan Wayne -1.7 -0.3 270031002 Minnesota Anoka -1.2 -0.7 280330002 Mississippi DeSoto -3.0 -0.3 280450001 Mississippi Hancock -3.3 -1.3 280470008 Mississippi Harrison -5.4 -3.5 280470009 Mississippi Harrison -3.7 -2.3 280490010 Mississippi Hinds -3.1 -0.3 280590006 Mississippi Jackson -4.6 -2.9 280590007 Mississippi Jackson -5.3 -3.8 280750003 Mississippi Lauderdale -3.1 -0.2 280810005 Mississippi Lee -3.0 -0.1 290370003 Missouri Cass -4.4 -3.1 290390001 Missouri Cedar -3.9 -2.2 290470003 Missouri Clay -4.1 -2.3 290470005 Missouri Clay -3.9 -2.2 290470006 Missouri Clay -3.8 -2.0 290490001 Missouri Clinton -4.0 -2.1 290770036 Missouri Greene -2.7 -1.1 290990012 Missouri Jefferson -2.2 -0.3 291130003 Missouri Lincoln -2.6 -0.4 291370001 Missouri Monroe -2.4 -0.9 291570001 Missouri Perry -2.0 -0.1 291650023 Missouri Platte -3.2 -1.7 291831002 Missouri Saint Charles -2.7 -0.7 291831004 Missouri Saint Charles -2.6 -0.4 291860005 Missouri Sainte Genevieve -2.5 -0.5 
B-92

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

291890004 Missouri Saint Louis -1.9 -0.4 291890005 Missouri Saint Louis -2.5 -0.4 291890006 Missouri Saint Louis -2.1 -0.4 291890014 Missouri Saint Louis -2.3 -0.4 295100085 Missouri St. Louis City -2.1 -0.6 295100086 Missouri St. Louis City -2.2 -0.6 310550028 Nebraska Douglas -2.0 -1.1 310550032 Nebraska Douglas -2.1 -1.0 310550035 Nebraska Douglas -2.2 -1.1 311090016 Nebraska Lancaster -1.8 -0.7 330012004 New Hampshire Belknap -2.2 0.0 330050007 New Hampshire Cheshire -2.1 -0.1 330074001 New Hampshire Coos -2.0 0.0 330074002 New Hampshire Coos -1.6 0.0 330090010 New Hampshire Grafton -2.0 0.0 330110020 New Hampshire Hillsborough -2.2 0.0 330111011 New Hampshire Hillsborough -2.5 0.0 330115001 New Hampshire Hillsborough -2.3 0.0 330131007 New Hampshire Merrimack -2.2 -0.1 330150014 New Hampshire Rockingham -2.1 0.0 330150016 New Hampshire Rockingham -2.1 0.0 330190003 New Hampshire Sullivan -2.0 0.0 340010005 New Jersey Atlantic -2.1 -0.1 340030005 New Jersey Bergen -1.5 -0.1 340070003 New Jersey Camden -1.4 0.0 340071001 New Jersey Camden -2.3 -0.1 340110007 New Jersey Cumberland -2.2 -0.1 340150002 New Jersey Gloucester -1.9 -0.1 340170006 New Jersey Hudson -1.6 -0.1 340190001 New Jersey Hunterdon -2.8 -0.1 340210005 New Jersey Mercer -2.1 0.0 340230011 New Jersey Middlesex -2.4 0.0 340250005 New Jersey Monmouth -2.1 -0.1 
B-93

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

340273001 New Jersey Morris -2.4 -0.1 340290006 New Jersey Ocean -2.6 -0.1 340315001 New Jersey Passaic -1.8 0.0 350130008 New Mexico Dona Ana -0.4 0.0 350130017 New Mexico Dona Ana -0.6 0.0 350130021 New Mexico Dona Ana -0.6 0.0 350130022 New Mexico Dona Ana -0.7 -0.1 350450009 New Mexico San Juan -0.5 0.0 350451005 New Mexico San Juan -0.5 0.0 360010012 New York Albany -2.0 0.0 360050110 New York Bronx -1.4 -0.1 360050133 New York Bronx -1.2 -0.2 360130006 New York Chautauqua -2.1 -0.2 360130011 New York Chautauqua -2.0 -0.3 360150003 New York Chemung -1.8 -0.2 360270007 New York Dutchess -2.0 -0.1 360290002 New York Erie -2.1 -0.2 360410005 New York Hamilton -1.6 -0.2 360430005 New York Herkimer -1.3 -0.2 360450002 New York Jefferson -1.6 0.0 360530006 New York Madison -1.7 -0.1 360551007 New York Monroe -1.7 -0.2 360631006 New York Niagara -1.5 -0.1 360650004 New York Oneida -1.7 -0.1 360671015 New York Onondaga -1.7 -0.1 360715001 New York Orange -2.3 0.0 360750003 New York Oswego -1.7 -0.2 360790005 New York Putnam -2.2 -0.1 360810098 New York Queens -1.4 -0.2 360810124 New York Queens -1.4 -0.1 360830004 New York Rensselaer -2.0 0.0 360850067 New York Richmond -1.9 -0.1 360910004 New York Saratoga -2.1 0.0 
B-94

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

360930003 New York Schenectady -1.9 0.0 361030002 New York Suffolk -1.5 -0.1 361030004 New York Suffolk -2.0 -0.2 361030009 New York Suffolk -1.5 -0.1 361111005 New York Ulster -2.2 -0.1 361173001 New York Wayne -1.5 -0.1 361192004 New York Westchester -1.3 -0.1 370030004 North Carolina Alexander -2.4 -0.1 370110002 North Carolina Avery -2.5 -0.2 370210030 North Carolina Buncombe -2.8 -0.2 370270003 North Carolina Caldwell -2.8 -0.2 370330001 North Carolina Caswell -3.0 -0.2 370370004 North Carolina Chatham -2.8 -0.2 370510008 North Carolina Cumberland -3.1 -0.2 370511003 North Carolina Cumberland -3.1 -0.2 370590002 North Carolina Davie -2.9 -0.3 370630013 North Carolina Durham -3.1 -0.1 370650099 North Carolina Edgecombe -3.0 -0.3 370670022 North Carolina Forsyth -2.6 -0.2 370670028 North Carolina Forsyth -2.5 -0.2 370670030 North Carolina Forsyth -2.7 -0.3 370671008 North Carolina Forsyth -2.9 -0.3 370690001 North Carolina Franklin -3.4 -0.1 370750001 North Carolina Graham -3.4 -0.4 370770001 North Carolina Granville -3.3 -0.1 370810011 North Carolina Guilford -3.1 -0.1 370810013 North Carolina Guilford -3.4 -0.2 370870004 North Carolina Haywood -2.6 -0.2 370870035 North Carolina Haywood -3.1 -0.2 370870036 North Carolina Haywood -2.7 -0.2 370990005 North Carolina Jackson -2.9 -0.3 371010002 North Carolina Johnston -3.2 -0.2 371070004 North Carolina Lenoir -3.0 -0.7 
B-95

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

371090004 North Carolina Lincoln -2.5 -0.2 371170001 North Carolina Martin -1.7 0.0 371190041 North Carolina Mecklenburg -2.8 -0.2 371191005 North Carolina Mecklenburg -2.5 -0.2 371191009 North Carolina Mecklenburg -3.1 -0.2 371290002 North Carolina New Hanover -2.1 -0.2 371450003 North Carolina Person -1.9 0.1 371470099 North Carolina Pitt -3.1 -0.6 371570099 North Carolina Rockingham -3.0 -0.3 371590021 North Carolina Rowan -3.2 -0.2 371590022 North Carolina Rowan -3.2 -0.2 371730002 North Carolina Swain -2.9 -0.3 371790003 North Carolina Union -2.9 -0.1 371830014 North Carolina Wake -3.2 -0.1 371830016 North Carolina Wake -3.2 -0.1 371990003 North Carolina Yancey -2.9 -0.3 390030002 Ohio Allen -2.3 -0.1 390071001 Ohio Ashtabula -2.5 -0.4 390170004 Ohio Butler -2.6 -0.6 390171004 Ohio Butler -2.7 -0.5 390230001 Ohio Clark -2.6 -0.4 390230003 Ohio Clark -2.3 -0.3 390250022 Ohio Clermont -2.9 -0.9 390271002 Ohio Clinton -3.1 -0.8 390350034 Ohio Cuyahoga -1.9 -0.3 390350064 Ohio Cuyahoga -2.0 -0.3 390355002 Ohio Cuyahoga -2.1 -0.3 390410002 Ohio Delaware -2.7 -0.2 390490028 Ohio Franklin -2.3 -0.3 390490029 Ohio Franklin -2.7 -0.3 390490037 Ohio Franklin -2.4 -0.3 390490081 Ohio Franklin -2.6 -0.3 390550004 Ohio Geauga -2.5 -0.4 
B-96

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

390570006 Ohio Greene -2.6 -0.5 390610006 Ohio Hamilton -2.6 -0.6 390610010 Ohio Hamilton -2.4 -0.8 390610040 Ohio Hamilton -2.4 -0.7 390810017 Ohio Jefferson -2.0 -0.6 390830002 Ohio Knox -2.7 -0.3 390850003 Ohio Lake -2.4 -0.4 390853002 Ohio Lake -2.3 -0.4 390870006 Ohio Lawrence -1.6 -0.2 390870011 Ohio Lawrence -1.5 -0.1 390890005 Ohio Licking -2.8 -0.3 390930018 Ohio Lorain -2.2 -0.4 390950024 Ohio Lucas -2.0 -0.4 390950027 Ohio Lucas -2.0 -0.4 390950034 Ohio Lucas -2.3 -0.5 390950081 Ohio Lucas -2.2 -0.4 390970007 Ohio Madison -2.6 -0.4 390990013 Ohio Mahoning -2.3 -0.6 391030003 Ohio Medina -2.6 -0.4 391090005 Ohio Miami -2.5 -0.3 391130037 Ohio Montgomery -2.3 -0.4 391331001 Ohio Portage -2.6 -0.3 391351001 Ohio Preble -2.6 -0.6 391510016 Ohio Stark -2.4 -0.3 391510022 Ohio Stark -2.3 -0.4 391514005 Ohio Stark -2.3 -0.3 391530020 Ohio Summit -2.7 -0.3 391550009 Ohio Trumbull -2.5 -0.5 391550011 Ohio Trumbull -2.4 -0.6 391650007 Ohio Warren -3.0 -0.6 391670004 Ohio Washington -2.9 -1.5 391730003 Ohio Wood -2.2 -0.4 400170101 Oklahoma Canadian -3.2 -0.6 
B-97

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

400219002 Oklahoma Cherokee -6.4 -4.8 400270049 Oklahoma Cleveland -3.3 -0.9 400310647 Oklahoma Comanche -3.0 -0.5 400370144 Oklahoma Creek -4.1 -2.0 400719010 Oklahoma Kay -5.0 -2.9 400871073 Oklahoma McClain -3.2 -0.8 400979014 Oklahoma Mayes -5.7 -4.3 401090033 Oklahoma Oklahoma -2.9 -0.9 401090096 Oklahoma Oklahoma -3.5 -1.3 401091037 Oklahoma Oklahoma -3.4 -0.5 401159004 Oklahoma Ottawa -4.9 -3.4 401210415 Oklahoma Pittsburg -3.3 -1.6 401430137 Oklahoma Tulsa -4.2 -1.8 401430174 Oklahoma Tulsa -3.9 -2.0 401430178 Oklahoma Tulsa -3.9 -2.0 401431127 Oklahoma Tulsa -4.0 -1.7 420010002 Pennsylvania Adams -2.2 -0.1 420030008 Pennsylvania Allegheny -1.5 -0.4 420030010 Pennsylvania Allegheny -1.6 -0.5 420030067 Pennsylvania Allegheny -1.7 -0.4 420031005 Pennsylvania Allegheny -2.3 -0.8 420050001 Pennsylvania Armstrong -2.4 -0.7 420070002 Pennsylvania Beaver -2.0 -0.6 420070005 Pennsylvania Beaver -1.9 -0.5 420070014 Pennsylvania Beaver -1.7 -0.5 420110009 Pennsylvania Berks -2.2 -0.3 420130801 Pennsylvania Blair -2.0 -0.5 420170012 Pennsylvania Bucks -2.0 -0.1 420210011 Pennsylvania Cambria -2.2 -0.5 420270100 Pennsylvania Centre -2.3 -0.3 420290100 Pennsylvania Chester -2.2 -0.1 420334000 Pennsylvania Clearfield -2.2 -0.6 420430401 Pennsylvania Dauphin -2.3 -0.6 
B-98

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

420431100 Pennsylvania Dauphin -2.3 -0.5 420450002 Pennsylvania Delaware -1.7 0.0 420490003 Pennsylvania Erie -2.1 -0.2 420550001 Pennsylvania Franklin -2.3 -0.1 420590002 Pennsylvania Greene -3.2 -2.1 420630004 Pennsylvania Indiana -2.3 -0.7 420690101 Pennsylvania Lackawanna -2.1 -0.2 420692006 Pennsylvania Lackawanna -2.2 -0.2 420710007 Pennsylvania Lancaster -2.3 -0.3 420730015 Pennsylvania Lawrence -2.1 -0.6 420770004 Pennsylvania Lehigh -2.2 0.0 420791100 Pennsylvania Luzerne -2.0 -0.2 420791101 Pennsylvania Luzerne -2.2 -0.2 420810100 Pennsylvania Lycoming -2.2 -0.2 420850100 Pennsylvania Mercer -2.3 -0.6 420910013 Pennsylvania Montgomery -1.7 -0.1 420950025 Pennsylvania Northampton -2.2 0.0 420958000 Pennsylvania Northampton -2.2 0.0 420990301 Pennsylvania Perry -2.4 -0.3 421010004 Pennsylvania Philadelphia -1.2 0.0 421010014 Pennsylvania Philadelphia -1.1 0.0 421010024 Pennsylvania Philadelphia -1.7 0.0 421010136 Pennsylvania Philadelphia -1.3 -0.1 421174000 Pennsylvania Tioga -2.1 -0.2 421250005 Pennsylvania Washington -1.5 -0.3 421250200 Pennsylvania Washington -1.6 -0.3 421255001 Pennsylvania Washington -2.0 -0.5 421290006 Pennsylvania Westmoreland -1.9 -0.6 421290008 Pennsylvania Westmoreland -2.0 -0.5 421330008 Pennsylvania York -2.3 -0.4 440030002 Rhode Island Kent -2.2 -0.1 440071010 Rhode Island Providence -2.2 0.0 440090007 Rhode Island Washington -2.1 -0.1 
B-99

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

450010001 South Carolina Abbeville -3.4 -0.4 450030003 South Carolina Aiken -3.4 -0.3 450070003 South Carolina Anderson -3.2 -0.3 450110001 South Carolina Barnwell -3.3 -0.2 450150002 South Carolina Berkeley -2.2 -0.4 450190046 South Carolina Charleston -2.7 -0.5 450210002 South Carolina Cherokee -2.8 -0.1 450230002 South Carolina Chester -2.7 -0.1 450250001 South Carolina Chesterfield -2.6 -0.2 450290002 South Carolina Colleton -3.2 -0.6 450310003 South Carolina Darlington -2.8 -0.4 450370001 South Carolina Edgefield -3.2 -0.3 450730001 South Carolina Oconee -3.3 -0.3 450770002 South Carolina Pickens -3.5 -0.3 450790007 South Carolina Richland -3.8 -0.4 450790021 South Carolina Richland -3.3 -0.3 450791001 South Carolina Richland -3.8 -0.3 450830009 South Carolina Spartanburg -3.0 -0.1 450870001 South Carolina Union -2.8 -0.2 450890001 South Carolina Williamsburg -2.4 -0.3 450910006 South Carolina York -2.8 -0.1 470010101 Tennessee Anderson -3.1 -0.1 470090101 Tennessee Blount -3.6 -0.2 470090102 Tennessee Blount -2.9 -0.3 470370011 Tennessee Davidson -2.5 -0.2 470370026 Tennessee Davidson -2.9 -0.2 470651011 Tennessee Hamilton -4.1 -0.3 470654003 Tennessee Hamilton -4.0 -0.2 470890002 Tennessee Jefferson -3.5 -0.2 470930021 Tennessee Knox -3.3 -0.1 470931020 Tennessee Knox -3.4 -0.1 471050109 Tennessee Loudon -3.2 -0.1 471210104 Tennessee Meigs -4.0 -0.2 
B-100

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

471490101 Tennessee Rutherford -3.1 -0.2 471550101 Tennessee Sevier -3.1 -0.2 471550102 Tennessee Sevier -3.4 -0.4 471570021 Tennessee Shelby -2.8 -0.3 471571004 Tennessee Shelby -3.0 -0.3 471632002 Tennessee Sullivan -1.9 -0.1 471632003 Tennessee Sullivan -1.8 -0.1 471650007 Tennessee Sumner -3.2 -0.3 471650101 Tennessee Sumner -3.2 -0.3 471870106 Tennessee Williamson -3.1 -0.2 471890103 Tennessee Wilson -3.4 -0.4 480290032 Texas Bexar -2.7 -0.4 480290052 Texas Bexar -2.7 -0.5 480391004 Texas Brazoria -2.2 -0.4 480391016 Texas Brazoria -1.9 -0.3 480850005 Texas Collin -3.2 -0.2 481130069 Texas Dallas -2.7 -0.3 481130075 Texas Dallas -2.9 -0.3 481130087 Texas Dallas -2.5 -0.2 481133003 Texas Dallas -2.5 -0.3 481210034 Texas Denton -3.6 -0.3 481390015 Texas Ellis -3.3 -0.4 481410029 Texas El Paso -0.4 0.0 481410037 Texas El Paso -0.7 0.0 481410044 Texas El Paso -0.6 0.0 481410055 Texas El Paso -0.7 0.0 481410057 Texas El Paso -0.5 0.0 481410058 Texas El Paso -0.6 0.0 481670014 Texas Galveston -1.8 -0.3 481830001 Texas Gregg -1.9 -0.4 482010024 Texas Harris -1.4 -0.3 482010026 Texas Harris -1.8 -0.3 482010029 Texas Harris -2.4 -0.3 
B-101

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

482010046 Texas Harris -1.3 -0.3 482010047 Texas Harris -1.2 -0.2 482010051 Texas Harris -2.1 -0.3 482010055 Texas Harris -2.3 -0.4 482010062 Texas Harris -1.9 -0.4 482010066 Texas Harris -1.3 -0.2 482010070 Texas Harris -1.3 -0.2 482010075 Texas Harris -1.3 -0.3 482011015 Texas Harris -1.9 -0.3 482011034 Texas Harris -1.3 -0.4 482011035 Texas Harris -1.3 -0.4 482011039 Texas Harris -2.0 -0.4 482011050 Texas Harris -1.8 -0.4 482030002 Texas Harrison -2.8 -0.4 482210001 Texas Hood -3.7 -0.4 482311006 Texas Hunt -2.4 -0.3 482450009 Texas Jefferson -2.3 -0.7 482450011 Texas Jefferson -2.2 -0.6 482450018 Texas Jefferson -2.3 -0.7 482450022 Texas Jefferson -2.4 -0.7 482450101 Texas Jefferson -2.2 -0.6 482450628 Texas Jefferson -2.1 -0.5 482510003 Texas Johnson -3.6 -0.4 482570005 Texas Kaufman -2.6 -0.4 483390078 Texas Montgomery -2.4 -0.1 483550025 Texas Nueces -1.3 -0.2 483611001 Texas Orange -2.3 -0.8 483611100 Texas Orange -1.8 -0.5 483670081 Texas Parker -3.7 -0.3 483970001 Texas Rockwall -2.8 -0.4 484230007 Texas Smith -2.4 -0.3 484390075 Texas Tarrant -3.6 -0.3 484391002 Texas Tarrant -3.2 -0.2 
B-102

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

484392003 Texas Tarrant -3.4 -0.3 484393009 Texas Tarrant -3.4 -0.3 484393011 Texas Tarrant -2.9 -0.3 484530014 Texas Travis -2.9 -0.4 484530020 Texas Travis -3.0 -0.5 484530613 Texas Travis -2.1 -0.4 500030004 Vermont Bennington -2.1 -0.1 500070007 Vermont Chittenden -1.6 0.0 510130020 Virginia Arlington -1.9 -0.1 510330001 Virginia Caroline -2.6 0.0 510360002 Virginia Charles -2.1 -0.1 510410004 Virginia Chesterfield -2.0 -0.1 510590005 Virginia Fairfax -2.3 -0.1 510590018 Virginia Fairfax -2.1 -0.2 510590030 Virginia Fairfax -1.9 -0.1 510591005 Virginia Fairfax -1.9 -0.1 510595001 Virginia Fairfax -2.0 -0.1 510610002 Virginia Fauquier -2.3 0.0 510690010 Virginia Frederick -2.0 0.0 510850003 Virginia Hanover -2.3 0.0 510870014 Virginia Henrico -2.3 -0.1 511071005 Virginia Loudoun -2.3 -0.1 511130003 Virginia Madison -2.3 -0.1 511390004 Virginia Page -2.1 -0.1 511530009 Virginia Prince William -2.3 0.0 511611004 Virginia Roanoke -2.7 -0.2 511630003 Virginia Rockbridge -2.5 -0.2 511790001 Virginia Stafford -2.6 -0.1 511970002 Virginia Wythe -2.7 -0.2 515100009 Virginia Alexandria City -1.9 -0.2 516500004 Virginia Hampton City -1.3 -0.1 518000004 Virginia Suffolk City -1.2 -0.1 518000005 Virginia Suffolk City -2.2 -0.1 
B-103

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

540030003 West Virginia Berkeley -2.2 0.0 540110006 West Virginia Cabell -1.8 -0.2 540291004 West Virginia Hancock -1.9 -0.7 540390010 West Virginia Kanawha -1.9 -0.2 540610003 West Virginia Monongalia -3.1 -1.9 540690010 West Virginia Ohio -2.5 -1.2 541071002 West Virginia Wood -2.2 -0.9 550090026 Wisconsin Brown -2.1 -0.4 550210015 Wisconsin Columbia -2.2 -0.6 550250041 Wisconsin Dane -2.1 -0.5 550270007 Wisconsin Dodge -2.3 -0.4 550290004 Wisconsin Door -2.7 -0.4 550370001 Wisconsin Florence -1.8 -0.4 550390006 Wisconsin Fond du Lac -2.1 -0.3 550410007 Wisconsin Forest -2.1 -0.6 550550002 Wisconsin Jefferson -2.4 -0.4 550590019 Wisconsin Kenosha -1.7 -0.3 550610002 Wisconsin Kewaunee -2.4 -0.4 550710007 Wisconsin Manitowoc -2.4 -0.3 550790010 Wisconsin Milwaukee -1.7 -0.2 550790026 Wisconsin Milwaukee -1.8 -0.2 550790041 Wisconsin Milwaukee -2.1 -0.3 550790044 Wisconsin Milwaukee -1.2 -0.2 550790085 Wisconsin Milwaukee -2.1 -0.3 550870009 Wisconsin Outagamie -2.1 -0.4 550890008 Wisconsin Ozaukee -2.1 -0.4 550890009 Wisconsin Ozaukee -2.4 -0.3 551010017 Wisconsin Racine -1.8 -0.3 551050024 Wisconsin Rock -2.4 -0.5 551091002 Wisconsin St. Croix -2.2 -0.9 551110007 Wisconsin Sauk -1.9 -0.6 551170006 Wisconsin Sheboygan -2.5 -0.3 551270005 Wisconsin Walworth -2.3 -0.3 
B-104

8-Hour Ozone (ppb) 

Monitor ID State County 

Difference: 

2014 Remedy - 

2012 Base Case 

Difference: 

2014 Remedy - 

2014 Base Case 

551310009 Wisconsin Washington -2.2 -0.3 551330017 Wisconsin Waukesha -2.2 -0.3 551330027 Wisconsin Waukesha -2.1 -0.3 
B-105

Differences in Annual PM2.5 Design Values (μg/m3) by Site: 

2014 Remedy Scenario Compared to the 2012 Base Case and the 2014 Base Ca

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

10030010 Alabama Baldwin -1.66 -1.31 10270001 Alabama Clay -2.05 -1.37 10331002 Alabama Colbert -2.45 -1.97 10491003 Alabama DeKalb -2.37 -1.76 10530002 Alabama Escambia -1.61 -1.27 10550010 Alabama Etowah -2.35 -1.66 10690003 Alabama Houston -1.50 -1.13 10730023 Alabama Jefferson -2.20 -1.53 10731005 Alabama Jefferson -2.14 -1.54 10731009 Alabama Jefferson -2.18 -1.64 10731010 Alabama Jefferson -2.33 -1.62 10732003 Alabama Jefferson -2.00 -1.43 10732006 Alabama Jefferson -2.03 -1.44 10735002 Alabama Jefferson -2.18 -1.53 10735003 Alabama Jefferson -2.37 -1.72 10890014 Alabama Madison -2.72 -2.12 10970002 Alabama Mobile -1.74 -1.31 10970003 Alabama Mobile -1.71 -1.29 10972005 Alabama Mobile -1.63 -1.26 11010007 Alabama Montgomery -1.86 -1.34 11030011 Alabama Morgan -2.49 -1.93 11130001 Alabama Russell -2.10 -1.42 11170006 Alabama Shelby -2.14 -1.52 11190002 Alabama Sumter -2.00 -1.54 11210002 Alabama Talladega -2.14 -1.49 
B-106

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

11250004 Alabama Tuscaloosa -2.19 -1.63 11270002 Alabama Walker -2.42 -1.80 50010011 Arkansas Arkansas -1.97 -1.53 50030005 Arkansas Ashley -1.59 -1.24 50350005 Arkansas Crittenden -2.60 -1.99 50450002 Arkansas Faulkner -1.82 -1.38 50510003 Arkansas Garland -1.71 -1.31 50930007 Arkansas Mississippi -2.65 -2.14 51070001 Arkansas Phillips -2.26 -1.75 51130002 Arkansas Polk -1.36 -1.06 51150003 Arkansas Pope -1.64 -1.26 51190007 Arkansas Pulaski -1.92 -1.45 51191004 Arkansas Pulaski -1.92 -1.45 51191005 Arkansas Pulaski -1.89 -1.43 51390006 Arkansas Union -1.60 -1.24 51450001 Arkansas White -1.82 -1.40 80010006 Colorado Adams -0.09 0.10 80050005 Colorado Arapahoe -0.10 0.06 80130003 Colorado Boulder -0.07 0.04 80130012 Colorado Boulder -0.05 0.04 80290004 Colorado Delta -0.11 0.00 80310002 Colorado Denver -0.08 0.10 80310023 Colorado Denver -0.09 0.09 80390001 Colorado Elbert -0.04 0.01 80410008 Colorado El Paso -0.08 0.02 80410011 Colorado El Paso -0.08 0.03 80690009 Colorado Larimer -0.06 0.02 80770017 Colorado Mesa -0.12 0.01 81010012 Colorado Pueblo -0.09 -0.01 
B-107

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

81130004 Colorado San Miguel -0.02 0.00 81230006 Colorado Weld -0.08 0.03 81230008 Colorado Weld -0.08 0.04 90010010 Connecticut Fairfield -1.24 -1.06 90011123 Connecticut Fairfield -1.23 -1.05 90013005 Connecticut Fairfield -1.25 -1.08 90019003 Connecticut Fairfield -1.22 -1.06 90031003 Connecticut Hartford -1.00 -0.83 90050005 Connecticut Litchfield -1.00 -0.89 90090026 Connecticut New Haven -1.20 -1.02 90090027 Connecticut New Haven -1.22 -1.03 90091123 Connecticut New Haven -1.22 -1.01 90092008 Connecticut New Haven -1.16 -0.99 90092123 Connecticut New Haven -1.17 -0.98 90113002 Connecticut New London -0.92 -0.77 

100010002 Delaware Kent -1.64 -1.51 100010003 Delaware Kent -1.61 -1.46 100031003 Delaware New Castle -1.69 -1.50 100031007 Delaware New Castle -1.68 -1.54 100031012 Delaware New Castle -1.68 -1.52 100032004 Delaware New Castle -1.73 -1.53 100051002 Delaware Sussex -1.65 -1.51 110010041

District Of Columbia District of Columbia -2.00 -1.82 

110010042

District Of Columbia District of Columbia -1.97 -1.80 

110010043

District Of Columbia District of Columbia -2.08 -1.91 

120010023 Florida Alachua -1.21 -0.98 120010024 Florida Alachua -1.18 -0.95 
B-108

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

120051004 Florida Bay -1.24 -0.94 120090007 Florida Brevard -0.81 -0.64 120111002 Florida Broward -0.50 -0.37 120112004 Florida Broward -0.51 -0.38 120113002 Florida Broward -0.50 -0.37 120170005 Florida Citrus -0.98 -0.79 120310098 Florida Duval -1.09 -0.85 120310099 Florida Duval -1.02 -0.79 120330004 Florida Escambia -1.33 -1.07 120570030 Florida Hillsborough -0.64 -0.45 120573002 Florida Hillsborough -0.60 -0.42 120710005 Florida Lee -0.64 -0.52 120730012 Florida Leon -1.26 -0.95 120814012 Florida Manatee -0.62 -0.52 120830003 Florida Marion -1.04 -0.81 120861016 Florida Miami-Dade -0.53 -0.37 120866001 Florida Miami-Dade -0.47 -0.38 120951004 Florida Orange -0.98 -0.71 120952002 Florida Orange -0.97 -0.71 120990009 Florida Palm Beach -0.57 -0.43 120992005 Florida Palm Beach -0.56 -0.42 121030018 Florida Pinellas -0.62 -0.49 121031009 Florida Pinellas -0.64 -0.49 121056006 Florida Polk -0.64 -0.50 121111002 Florida St. Lucie -0.70 -0.58 121150013 Florida Sarasota -0.65 -0.54 121171002 Florida Seminole -1.00 -0.73 121275002 Florida Volusia -1.10 -0.85 130210007 Georgia Bibb -2.16 -1.35 
B-109

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

130210012 Georgia Bibb -2.12 -1.29 130510017 Georgia Chatham -1.47 -1.06 130510091 Georgia Chatham -1.48 -1.05 130590002 Georgia Clarke -2.32 -1.43 130630091 Georgia Clayton -2.34 -1.39 130670003 Georgia Cobb -2.22 -1.45 130670004 Georgia Cobb -2.27 -1.41 130890002 Georgia DeKalb -2.36 -1.39 130892001 Georgia DeKalb -2.32 -1.42 130950007 Georgia Dougherty -1.73 -1.31 131150005 Georgia Floyd -2.18 -1.58 131210032 Georgia Fulton -2.35 -1.39 131210039 Georgia Fulton -2.36 -1.38 131270006 Georgia Glynn -1.22 -0.94 131350002 Georgia Gwinnett -2.29 -1.44 131390003 Georgia Hall -2.24 -1.48 131530001 Georgia Houston -1.99 -1.31 131850003 Georgia Lowndes -1.25 -0.93 132150001 Georgia Muscogee -2.09 -1.43 132150008 Georgia Muscogee -2.03 -1.36 132150011 Georgia Muscogee -1.89 -1.29 132230003 Georgia Paulding -2.25 -1.52 132450005 Georgia Richmond -1.84 -1.27 132450091 Georgia Richmond -1.87 -1.29 132950002 Georgia Walker -2.58 -1.95 133030001 Georgia Washington -2.23 -1.31 133190001 Georgia Wilkinson -2.27 -1.32 170010006 Illinois Adams -1.65 -1.14 170190004 Illinois Champaign -2.31 -1.76 
B-110

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

170191001 Illinois Champaign -2.34 -1.77 170310022 Illinois Cook -1.67 -1.19 170310050 Illinois Cook -1.61 -1.11 170310052 Illinois Cook -1.57 -1.05 170310057 Illinois Cook -1.60 -1.08 170310076 Illinois Cook -1.65 -1.11 170312001 Illinois Cook -1.56 -1.08 170313301 Illinois Cook -1.63 -1.10 170314007 Illinois Cook -1.61 -1.08 170314201 Illinois Cook -1.62 -1.09 170316005 Illinois Cook -1.58 -1.06 170434002 Illinois DuPage -1.64 -1.08 170831001 Illinois Jersey -2.43 -1.79 170890003 Illinois Kane -1.69 -1.11 170890007 Illinois Kane -1.64 -1.08 170971007 Illinois Lake -1.56 -1.05 171110001 Illinois McHenry -1.59 -1.04 171132003 Illinois McLean -2.07 -1.42 171150013 Illinois Macon -2.26 -1.65 171191007 Illinois Madison -2.34 -1.68 171192009 Illinois Madison -2.49 -1.86 171193007 Illinois Madison -2.44 -1.83 171430037 Illinois Peoria -2.15 -1.19 171570001 Illinois Randolph -2.49 -1.86 171613002 Illinois Rock Island -1.53 -1.03 171630010 Illinois Saint Clair -2.30 -1.65 171634001 Illinois Saint Clair -2.29 -1.65 171670012 Illinois Sangamon -2.22 -1.64 171971002 Illinois Will -1.72 -1.18 
B-111

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

171971011 Illinois Will -1.81 -1.32 172010013 Illinois Winnebago -1.42 -0.93 180030004 Indiana Allen -1.87 -1.50 180030014 Indiana Allen -1.86 -1.49 180190006 Indiana Clark -3.59 -3.09 180350006 Indiana Delaware -2.78 -2.35 180372001 Indiana Dubois -3.96 -3.39 180431004 Indiana Floyd -3.63 -3.17 180650003 Indiana Henry -2.98 -2.54 180670003 Indiana Howard -2.58 -2.10 180830004 Indiana Knox -3.54 -2.93 180890006 Indiana Lake -1.68 -1.20 180890027 Indiana Lake -1.73 -1.26 180891003 Indiana Lake -1.69 -1.23 180892004 Indiana Lake -1.67 -1.20 180892010 Indiana Lake -1.66 -1.18 180910011 Indiana LaPorte -1.68 -1.25 180910012 Indiana LaPorte -1.75 -1.31 180950009 Indiana Madison -2.94 -2.49 180970042 Indiana Marion -3.38 -2.90 180970078 Indiana Marion -3.33 -2.84 180970079 Indiana Marion -3.25 -2.76 180970081 Indiana Marion -3.33 -2.83 180970083 Indiana Marion -3.33 -2.83 181270020 Indiana Porter -1.71 -1.26 181270024 Indiana Porter -1.74 -1.27 181410014 Indiana St. Joseph -1.40 -1.06 181411008 Indiana St. Joseph -1.38 -1.04 181412004 Indiana St. Joseph -1.38 -1.04 
B-112

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

181470009 Indiana Spencer -3.96 -3.40 181570008 Indiana Tippecanoe -2.57 -2.05 181630006 Indiana Vanderburgh -3.16 -2.63 181630012 Indiana Vanderburgh -3.16 -2.61 181630016 Indiana Vanderburgh -3.17 -2.63 181670018 Indiana Vigo -3.02 -2.46 181670023 Indiana Vigo -3.05 -2.49 190130008 Iowa Black Hawk -1.03 -0.72 190450021 Iowa Clinton -1.44 -0.93 191032001 Iowa Johnson -1.21 -0.85 191130037 Iowa Linn -1.12 -0.78 191370002 Iowa Montgomery -0.90 -0.67 191390015 Iowa Muscatine -1.38 -1.00 191471002 Iowa Palo Alto -0.75 -0.54 191530030 Iowa Polk -0.96 -0.68 191532510 Iowa Polk -0.93 -0.66 191532520 Iowa Polk -0.95 -0.66 191550009 Iowa Pottawattamie -0.81 -0.62 191630015 Iowa Scott -1.52 -1.02 191630018 Iowa Scott -1.50 -1.00 191630019 Iowa Scott -1.49 -0.99 191770006 Iowa Van Buren -1.04 -0.74 191930017 Iowa Woodbury -0.63 -0.51 191970004 Iowa Wright -0.92 -0.65 200910007 Kansas Johnson -1.02 -0.74 200910009 Kansas Johnson -1.15 -0.83 200910010 Kansas Johnson -1.02 -0.75 201070002 Kansas Linn -1.15 -0.85 201730008 Kansas Sedgwick -0.82 -0.59 
B-113

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

201730009 Kansas Sedgwick -0.83 -0.59 201730010 Kansas Sedgwick -0.82 -0.58 201770010 Kansas Shawnee -0.90 -0.67 201770011 Kansas Shawnee -0.89 -0.66 201910002 Kansas Sumner -0.83 -0.61 202090021 Kansas Wyandotte -1.11 -0.80 202090022 Kansas Wyandotte -1.05 -0.75 210130002 Kentucky Bell -2.82 -2.24 210190017 Kentucky Boyd -3.19 -2.61 210290006 Kentucky Bullitt -3.60 -3.09 210370003 Kentucky Campbell -3.44 -2.95 210430500 Kentucky Carter -2.88 -2.37 210470006 Kentucky Christian -3.83 -3.29 210590005 Kentucky Daviess -4.32 -3.77 210670012 Kentucky Fayette -3.38 -2.86 210670014 Kentucky Fayette -3.37 -2.84 210730006 Kentucky Franklin -3.36 -2.87 210930006 Kentucky Hardin -3.66 -3.14 211010014 Kentucky Henderson -3.31 -2.79 211110043 Kentucky Jefferson -3.68 -3.20 211110044 Kentucky Jefferson -3.59 -3.11 211110048 Kentucky Jefferson -3.62 -3.13 211110051 Kentucky Jefferson -3.72 -3.24 211170007 Kentucky Kenton -3.44 -2.96 211250004 Kentucky Laurel -2.76 -2.24 211451004 Kentucky McCracken -3.29 -2.68 211510003 Kentucky Madison -3.25 -2.74 211930003 Kentucky Perry -2.67 -2.15 211950002 Kentucky Pike -2.99 -2.45 
B-114

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

212270007 Kentucky Warren -3.96 -3.39 220171002 Louisiana Caddo -1.46 -1.13 220190009 Louisiana Calcasieu -1.16 -0.90 220190010 Louisiana Calcasieu -1.17 -0.89 220290003 Louisiana Concordia -1.71 -1.31 220330009 Louisiana East Baton Rouge -1.36 -0.94 220331001 Louisiana East Baton Rouge -1.33 -0.94 220470005 Louisiana Iberville -1.43 -0.91 220470009 Louisiana Iberville -1.45 -1.07 220511001 Louisiana Jefferson -1.48 -1.11 220550006 Louisiana Lafayette -1.52 -1.21 220730004 Louisiana Ouachita -1.52 -1.17 220790002 Louisiana Rapides -1.46 -1.16 221050001 Louisiana Tangipahoa -1.61 -1.20 221090001 Louisiana Terrebonne -1.48 -1.14 221210001 Louisiana West Baton Rouge -1.36 -0.93 230010011 Maine Androscoggin -0.47 -0.32 230030013 Maine Aroostook -0.31 -0.24 230031011 Maine Aroostook -0.31 -0.23 230050015 Maine Cumberland -0.53 -0.34 230050027 Maine Cumberland -0.52 -0.34 230090103 Maine Hancock -0.35 -0.29 230110016 Maine Kennebec -0.46 -0.32 230172011 Maine Oxford -0.46 -0.33 230190002 Maine Penobscot -0.48 -0.36 240030014 Maryland Anne Arundel -1.58 -1.56 240031003 Maryland Anne Arundel -1.38 -1.48 240032002 Maryland Anne Arundel -1.36 -1.48 240051007 Maryland Baltimore -1.83 -1.78 
B-115

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

240053001 Maryland Baltimore -1.56 -1.62 240150003 Maryland Cecil -1.69 -1.55 240251001 Maryland Harford -1.58 -1.58 240313001 Maryland Montgomery -1.84 -1.71 240330030 Maryland Prince George's -1.67 -1.60 240338003 Maryland Prince George's -1.75 -1.67 240430009 Maryland Washington -2.42 -2.15 245100006 Maryland Baltimore (City) -1.57 -1.61 245100007 Maryland Baltimore (City) -1.72 -1.69 245100008 Maryland Baltimore (City) -1.48 -1.58 245100049 Maryland Baltimore (City) -1.39 -1.51 250035001 Massachusetts Berkshire -0.98 -0.83 250051004 Massachusetts Bristol -0.71 -0.64 250092006 Massachusetts Essex -0.65 -0.55 250095005 Massachusetts Essex -0.64 -0.52 250096001 Massachusetts Essex -0.67 -0.54 250130008 Massachusetts Hampden -0.92 -0.78 250130016 Massachusetts Hampden -0.98 -0.79 250132009 Massachusetts Hampden -0.96 -0.78 250230004 Massachusetts Plymouth -0.75 -0.63 250250002 Massachusetts Suffolk -0.75 -0.59 250250027 Massachusetts Suffolk -0.75 -0.60 250250042 Massachusetts Suffolk -0.72 -0.59 250250043 Massachusetts Suffolk -0.77 -0.59 250270016 Massachusetts Worcester -0.88 -0.72 250270023 Massachusetts Worcester -0.88 -0.71 260050003 Michigan Allegan -1.80 -1.37 260170014 Michigan Bay -1.41 -1.07 260210014 Michigan Berrien -1.67 -1.27 
B-116

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

260490021 Michigan Genesee -1.63 -1.29 260650012 Michigan Ingham -1.72 -1.34 260770008 Michigan Kalamazoo -1.72 -1.34 260810020 Michigan Kent -1.57 -1.16 260990009 Michigan Macomb -1.70 -1.38 261130001 Michigan Missaukee -0.91 -0.65 261150005 Michigan Monroe -2.16 -1.75 261210040 Michigan Muskegon -1.49 -1.09 261250001 Michigan Oakland -1.78 -1.41 261390005 Michigan Ottawa -1.63 -1.22 261450018 Michigan Saginaw -1.38 -1.05 261470005 Michigan St. Clair -1.70 -1.38 261610005 Michigan Washtenaw -1.80 -1.45 261610008 Michigan Washtenaw -1.79 -1.41 261630001 Michigan Wayne -1.85 -1.46 261630015 Michigan Wayne -2.04 -1.63 261630016 Michigan Wayne -1.82 -1.45 261630019 Michigan Wayne -1.78 -1.43 261630025 Michigan Wayne -1.88 -1.50 261630033 Michigan Wayne -2.14 -1.69 261630036 Michigan Wayne -1.96 -1.57 270210001 Minnesota Cass -0.30 -0.22 270370470 Minnesota Dakota -0.61 -0.41 270530050 Minnesota Hennepin -0.58 -0.38 270530961 Minnesota Hennepin -0.59 -0.39 270530963 Minnesota Hennepin -0.59 -0.39 270530965 Minnesota Hennepin -0.57 -0.37 270531007 Minnesota Hennepin -0.60 -0.39 270532006 Minnesota Hennepin -0.59 -0.39 
B-117

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

270953051 Minnesota Mille Lacs -0.36 -0.25 271095008 Minnesota Olmsted -0.80 -0.56 271230866 Minnesota Ramsey -0.61 -0.38 271230868 Minnesota Ramsey -0.58 -0.36 271230871 Minnesota Ramsey -0.56 -0.36 271377001 Minnesota Saint Louis -0.37 -0.20 271377550 Minnesota Saint Louis -0.37 -0.23 271377551 Minnesota Saint Louis -0.40 -0.23 271390505 Minnesota Scott -0.62 -0.42 271453052 Minnesota Stearns -0.50 -0.33 280010004 Mississippi Adams -1.73 -1.33 280110001 Mississippi Bolivar -2.11 -1.63 280330002 Mississippi DeSoto -2.51 -1.92 280350004 Mississippi Forrest -1.84 -1.40 280470008 Mississippi Harrison -1.55 -1.18 280490010 Mississippi Hinds -1.85 -1.37 280590006 Mississippi Jackson -1.57 -1.17 280670002 Mississippi Jones -1.97 -1.49 280750003 Mississippi Lauderdale -2.10 -1.58 280810005 Mississippi Lee -2.50 -1.92 280870001 Mississippi Lowndes -2.32 -1.74 281090001 Mississippi Pearl River -1.61 -1.23 281490004 Mississippi Warren -1.83 -1.36 290190004 Missouri Boone -1.60 -1.14 290210005 Missouri Buchanan -0.99 -0.72 290370003 Missouri Cass -1.17 -0.86 290390001 Missouri Cedar -1.30 -0.99 290470005 Missouri Clay -1.12 -0.84 290770032 Missouri Greene -1.57 -1.18 
B-118

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

290950034 Missouri Jackson -1.13 -0.80 290990012 Missouri Jefferson -2.12 -1.55 291370001 Missouri Monroe -1.67 -1.19 291831002 Missouri Saint Charles -2.47 -1.86 291860006 Missouri Sainte Genevieve -2.35 -1.70 291890004 Missouri Saint Louis -2.15 -1.57 291892003 Missouri Saint Louis -2.24 -1.64 295100007 Missouri St. Louis City -2.17 -1.57 295100085 Missouri St. Louis City -2.28 -1.65 295100086 Missouri St. Louis City -2.26 -1.64 295100087 Missouri St. Louis City -2.31 -1.66 300870307 Montana Rosebud -0.01 0.02 301111065 Montana Yellowstone -0.04 0.01 310250002 Nebraska Cass -0.82 -0.61 310550019 Nebraska Douglas -0.81 -0.63 310550052 Nebraska Douglas -0.81 -0.61 310790004 Nebraska Hall -0.56 -0.40 311090022 Nebraska Lancaster -0.76 -0.55 311111002 Nebraska Lincoln -0.31 -0.22 311530007 Nebraska Sarpy -0.82 -0.63 311570003 Nebraska Scotts Bluff -0.10 -0.04 311770002 Nebraska Washington -0.78 -0.59 330012004 New Hampshire Belknap -0.62 -0.51 330050007 New Hampshire Cheshire -0.84 -0.66 330070014 New Hampshire Coos -0.54 -0.41 330090010 New Hampshire Grafton -0.67 -0.54 330110020 New Hampshire Hillsborough -0.72 -0.58 330111015 New Hampshire Hillsborough -0.75 -0.61 330115001 New Hampshire Hillsborough -0.56 -0.47 
B-119

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

330131006 New Hampshire Merrimack -0.72 -0.57 330150014 New Hampshire Rockingham -0.56 -0.44 330190003 New Hampshire Sullivan -0.75 -0.60 340011006 New Jersey Atlantic -1.40 -1.26 340030003 New Jersey Bergen -1.28 -1.06 340070003 New Jersey Camden -1.58 -1.36 340071007 New Jersey Camden -1.60 -1.36 340130015 New Jersey Essex -1.33 -1.08 340155001 New Jersey Gloucester -1.66 -1.43 340171003 New Jersey Hudson -1.31 -1.07 340210008 New Jersey Mercer -1.54 -1.32 340218001 New Jersey Mercer -1.47 -1.27 340230006 New Jersey Middlesex -1.43 -1.22 340270004 New Jersey Morris -1.38 -1.19 340273001 New Jersey Morris -1.34 -1.18 340292002 New Jersey Ocean -1.34 -1.17 340310005 New Jersey Passaic -1.32 -1.09 340390004 New Jersey Union -1.44 -1.14 340390006 New Jersey Union -1.34 -1.08 340392003 New Jersey Union -1.37 -1.11 340410006 New Jersey Warren -1.61 -1.42 350010023 New Mexico Bernalillo -0.14 -0.05 350010024 New Mexico Bernalillo -0.14 -0.05 350050005 New Mexico Chaves -0.20 -0.15 350130017 New Mexico Dona Ana -0.15 -0.10 350130025 New Mexico Dona Ana -0.15 -0.11 350431003 New Mexico Sandoval -0.11 -0.05 350439011 New Mexico Sandoval -0.09 -0.04 350450006 New Mexico San Juan -0.03 -0.01 
B-120

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

350490020 New Mexico Santa Fe -0.07 -0.03 360010005 New York Albany -0.99 -0.85 360050080 New York Bronx -1.32 -1.07 360050083 New York Bronx -1.27 -1.05 360050110 New York Bronx -1.27 -1.04 360130011 New York Chautauqua -1.81 -1.58 360290005 New York Erie -1.60 -1.38 360291007 New York Erie -1.69 -1.46 360310003 New York Essex -0.73 -0.64 360470122 New York Kings -1.31 -1.07 360551007 New York Monroe -1.40 -1.22 360590008 New York Nassau -1.15 -0.98 360610056 New York New York -1.42 -1.14 360610062 New York New York -1.36 -1.10 360610079 New York New York -1.28 -1.05 360610128 New York New York -1.33 -1.08 360632008 New York Niagara -1.62 -1.40 360671015 New York Onondaga -1.43 -1.28 360710002 New York Orange -1.22 -1.07 360810124 New York Queens -1.17 -0.97 360850055 New York Richmond -1.33 -1.07 360850067 New York Richmond -1.15 -0.93 360893001 New York St. Lawrence -0.79 -0.69 361010003 New York Steuben -1.55 -1.40 361030001 New York Suffolk -1.20 -1.04 361191002 New York Westchester -1.24 -1.06 370010002 North Carolina Alamance -2.18 -1.79 370210034 North Carolina Buncombe -2.07 -1.63 370330001 North Carolina Caswell -2.17 -1.82 
B-121

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

370350004 North Carolina Catawba -2.32 -1.87 370370004 North Carolina Chatham -2.02 -1.64 370510009 North Carolina Cumberland -1.87 -1.47 370570002 North Carolina Davidson -2.30 -1.90 370610002 North Carolina Duplin -1.67 -1.38 370630001 North Carolina Durham -2.07 -1.68 370650004 North Carolina Edgecombe -1.97 -1.62 370670022 North Carolina Forsyth -2.35 -1.96 370710016 North Carolina Gaston -2.08 -1.66 370810013 North Carolina Guilford -2.15 -1.78 370870010 North Carolina Haywood -1.82 -1.37 370990006 North Carolina Jackson -2.10 -1.57 371070004 North Carolina Lenoir -1.68 -1.39 371110004 North Carolina McDowell -2.15 -1.73 371170001 North Carolina Martin -1.68 -1.42 371190010 North Carolina Mecklenburg -2.00 -1.61 371190041 North Carolina Mecklenburg -2.04 -1.64 371190042 North Carolina Mecklenburg -2.04 -1.64 371210001 North Carolina Mitchell -2.21 -1.80 371230001 North Carolina Montgomery -2.00 -1.60 371290002 North Carolina New Hanover -1.46 -1.21 371330005 North Carolina Onslow -1.63 -1.36 371350007 North Carolina Orange -2.12 -1.71 371470005 North Carolina Pitt -1.76 -1.46 371550005 North Carolina Robeson -1.73 -1.41 371590021 North Carolina Rowan -2.09 -1.72 371730002 North Carolina Swain -2.23 -1.66 371830014 North Carolina Wake -2.05 -1.65 371890003 North Carolina Watauga -2.37 -1.96 
B-122

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

371910005 North Carolina Wayne -1.88 -1.51 380070002 North Dakota Billings -0.04 -0.02 380130002 North Dakota Burke -0.04 -0.02 380130003 North Dakota Burke -0.04 -0.02 380150003 North Dakota Burleigh -0.11 -0.05 380171004 North Dakota Cass -0.29 -0.18 380530002 North Dakota McKenzie -0.04 -0.01 380570004 North Dakota Mercer -0.06 -0.03 390090003 Ohio Athens -2.83 -2.32 390170016 Ohio Butler -3.31 -2.82 390170017 Ohio Butler -2.95 -2.50 390171004 Ohio Butler -3.07 -2.62 390230005 Ohio Clark -2.82 -2.39 390250022 Ohio Clermont -3.37 -2.88 390350027 Ohio Cuyahoga -2.65 -2.21 390350034 Ohio Cuyahoga -2.42 -2.03 390350038 Ohio Cuyahoga -2.67 -2.20 390350045 Ohio Cuyahoga -2.68 -2.22 390350060 Ohio Cuyahoga -2.67 -2.20 390350065 Ohio Cuyahoga -2.66 -2.21 390351002 Ohio Cuyahoga -2.38 -2.00 390490024 Ohio Franklin -2.81 -2.33 390490025 Ohio Franklin -2.81 -2.33 390490081 Ohio Franklin -2.82 -2.34 390570005 Ohio Greene -2.85 -2.43 390610006 Ohio Hamilton -3.29 -2.81 390610014 Ohio Hamilton -3.54 -2.99 390610040 Ohio Hamilton -3.55 -3.03 390610042 Ohio Hamilton -3.51 -2.98 
B-123

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

390610043 Ohio Hamilton -3.28 -2.79 390617001 Ohio Hamilton -3.52 -2.99 390618001 Ohio Hamilton -3.52 -2.97 390810017 Ohio Jefferson -2.75 -2.33 390811001 Ohio Jefferson -2.99 -2.54 390851001 Ohio Lake -2.30 -1.93 390870010 Ohio Lawrence -2.99 -2.43 390930016 Ohio Lorain -2.49 -2.10 390933002 Ohio Lorain -1.94 -1.61 390950024 Ohio Lucas -2.19 -1.76 390950025 Ohio Lucas -2.21 -1.79 390950026 Ohio Lucas -2.20 -1.77 390990005 Ohio Mahoning -2.50 -2.08 390990014 Ohio Mahoning -2.52 -2.08 391130031 Ohio Montgomery -2.86 -2.43 391130032 Ohio Montgomery -2.94 -2.48 391330002 Ohio Portage -2.43 -2.04 391351001 Ohio Preble -3.09 -2.67 391450013 Ohio Scioto -3.08 -2.54 391510017 Ohio Stark -2.73 -2.34 391510020 Ohio Stark -2.34 -1.98 391530017 Ohio Summit -2.37 -2.00 391530023 Ohio Summit -2.29 -1.94 391550007 Ohio Trumbull -2.48 -2.05 400159008 Oklahoma Caddo -0.62 -0.50 400219002 Oklahoma Cherokee -1.25 -0.94 400719010 Oklahoma Kay -0.77 -0.57 400819005 Oklahoma Lincoln -0.92 -0.69 400970186 Oklahoma Mayes -1.13 -0.84 
B-124

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

400979014 Oklahoma Mayes -1.15 -0.86 401010169 Oklahoma Muskogee -1.15 -0.86 401090035 Oklahoma Oklahoma -0.82 -0.60 401091037 Oklahoma Oklahoma -0.83 -0.61 401159004 Oklahoma Ottawa -1.19 -0.90 401210415 Oklahoma Pittsburg -1.09 -0.83 401359015 Oklahoma Sequoyah -1.26 -0.95 401430110 Oklahoma Tulsa -1.06 -0.79 401431127 Oklahoma Tulsa -1.03 -0.76 420010001 Pennsylvania Adams -2.30 -2.07 420030008 Pennsylvania Allegheny -2.82 -2.41 420030021 Pennsylvania Allegheny -2.85 -2.46 420030064 Pennsylvania Allegheny -3.02 -2.50 420030067 Pennsylvania Allegheny -2.68 -2.31 420030095 Pennsylvania Allegheny -2.65 -2.29 420030116 Pennsylvania Allegheny -2.67 -2.28 420031008 Pennsylvania Allegheny -3.05 -2.68 420031301 Pennsylvania Allegheny -2.99 -2.56 420033007 Pennsylvania Allegheny -3.06 -2.62 420039002 Pennsylvania Allegheny -2.98 -2.60 420070014 Pennsylvania Beaver -2.58 -2.22 420110011 Pennsylvania Berks -1.99 -1.79 420170012 Pennsylvania Bucks -1.62 -1.38 420210011 Pennsylvania Cambria -3.55 -3.20 420270100 Pennsylvania Centre -2.44 -2.19 420290100 Pennsylvania Chester -1.90 -1.71 420410101 Pennsylvania Cumberland -2.22 -2.00 420430401 Pennsylvania Dauphin -2.45 -2.22 420450002 Pennsylvania Delaware -1.73 -1.48 
B-125

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

420490003 Pennsylvania Erie -2.07 -1.75 420692006 Pennsylvania Lackawanna -1.64 -1.47 420710007 Pennsylvania Lancaster -2.24 -2.04 420770004 Pennsylvania Lehigh -1.67 -1.47 420791101 Pennsylvania Luzerne -1.63 -1.46 420850100 Pennsylvania Mercer -2.43 -2.03 420950025 Pennsylvania Northampton -1.64 -1.43 420990301 Pennsylvania Perry -2.01 -1.81 421010047 Pennsylvania Philadelphia -1.64 -1.36 421250005 Pennsylvania Washington -3.21 -2.74 421250200 Pennsylvania Washington -3.13 -2.68 421255001 Pennsylvania Washington -2.43 -2.09 421290008 Pennsylvania Westmoreland -3.36 -2.92 421330008 Pennsylvania York -2.39 -2.20 440070022 Rhode Island Providence -0.75 -0.63 440070026 Rhode Island Providence -0.82 -0.66 440070028 Rhode Island Providence -0.78 -0.64 440071010 Rhode Island Providence -0.77 -0.65 450130007 South Carolina Beaufort -1.53 -1.16 450190048 South Carolina Charleston -1.46 -1.12 450190049 South Carolina Charleston -1.54 -1.19 450250001 South Carolina Chesterfield -1.76 -1.38 450370001 South Carolina Edgefield -1.83 -1.29 450410002 South Carolina Florence -1.69 -1.33 450430009 South Carolina Georgetown -1.44 -1.15 450450008 South Carolina Greenville -2.07 -1.53 450450009 South Carolina Greenville -2.09 -1.56 450470003 South Carolina Greenwood -2.14 -1.46 450510002 South Carolina Horry -1.54 -1.22 
B-126

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

450630008 South Carolina Lexington -1.86 -1.34 450730001 South Carolina Oconee -1.97 -1.45 450790007 South Carolina Richland -1.86 -1.37 450790019 South Carolina Richland -1.85 -1.35 450830010 South Carolina Spartanburg -2.04 -1.56 460110002 South Dakota Brookings -0.50 -0.35 460130003 South Dakota Brown -0.30 -0.19 460290002 South Dakota Codington -0.38 -0.25 460330132 South Dakota Custer -0.05 -0.02 460710001 South Dakota Jackson -0.10 -0.07 460990006 South Dakota Minnehaha -0.60 -0.41 460990007 South Dakota Minnehaha -0.59 -0.41 461030016 South Dakota Pennington -0.07 -0.02 461030020 South Dakota Pennington -0.07 -0.02 461031001 South Dakota Pennington -0.06 -0.02 470090011 Tennessee Blount -2.40 -1.84 470370023 Tennessee Davidson -3.29 -2.72 470370025 Tennessee Davidson -3.29 -2.71 470370036 Tennessee Davidson -3.29 -2.71 470450004 Tennessee Dyer -2.97 -2.43 470650031 Tennessee Hamilton -2.61 -1.97 470651011 Tennessee Hamilton -2.74 -2.12 470654002 Tennessee Hamilton -2.72 -2.08 470930028 Tennessee Knox -2.59 -1.98 470931017 Tennessee Knox -2.58 -1.97 470931020 Tennessee Knox -2.64 -2.02 470990002 Tennessee Lawrence -2.48 -2.03 471050108 Tennessee Loudon -2.46 -1.89 471071002 Tennessee McMinn -2.53 -1.95 
B-127

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

471192007 Tennessee Maury -2.94 -2.41 471251009 Tennessee Montgomery -3.87 -3.29 471410001 Tennessee Putnam -3.02 -2.46 471450004 Tennessee Roane -2.58 -2.01 471570014 Tennessee Shelby -2.70 -2.06 471570038 Tennessee Shelby -2.69 -2.05 471570047 Tennessee Shelby -2.77 -2.11 471571004 Tennessee Shelby -2.65 -2.06 471631007 Tennessee Sullivan -2.51 -2.03 471650007 Tennessee Sumner -3.97 -3.34 480370004 Texas Bowie -1.37 -1.10 481130069 Texas Dallas -0.81 -0.61 481130087 Texas Dallas -0.81 -0.62 481350003 Texas Ector -0.32 -0.26 481410037 Texas El Paso -0.15 -0.10 482010058 Texas Harris -1.00 -0.72 482011035 Texas Harris -1.05 -0.67 482030002 Texas Harrison -1.33 -1.10 482150043 Texas Hidalgo -0.71 -0.57 482450021 Texas Jefferson -1.23 -0.91 483550032 Texas Nueces -1.09 -0.76 483611001 Texas Orange -1.22 -0.95 484391002 Texas Tarrant -0.81 -0.61 484391006 Texas Tarrant -0.82 -0.61 500010002 Vermont Addison -0.73 -0.62 500010003 Vermont Addison -0.72 -0.61 500030004 Vermont Bennington -0.81 -0.70 500070012 Vermont Chittenden -0.74 -0.60 500070014 Vermont Chittenden -0.77 -0.62 
B-128

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

500210002 Vermont Rutland -0.76 -0.61 510130020 Virginia Arlington -2.06 -1.86 510360002 Virginia Charles -1.89 -1.61 510410003 Virginia Chesterfield -2.05 -1.72 510590030 Virginia Fairfax -2.03 -1.82 510591005 Virginia Fairfax -2.07 -1.85 510595001 Virginia Fairfax -2.09 -1.86 510870014 Virginia Henrico -2.07 -1.75 510870015 Virginia Henrico -2.19 -1.85 511071005 Virginia Loudoun -2.14 -1.89 511390004 Virginia Page -2.57 -2.21 515200006 Virginia Bristol City -2.66 -2.14 516500004 Virginia Hampton City -1.84 -1.56 516800015 Virginia Lynchburg City -2.29 -1.91 517100024 Virginia Norfolk City -1.88 -1.59 517700014 Virginia Roanoke City -2.57 -2.10 517750010 Virginia Salem City -2.51 -2.05 518100008 Virginia Virginia Beach City -1.84 -1.57 540030003 West Virginia Berkeley -2.51 -2.20 540090005 West Virginia Brooke -2.93 -2.49 540090011 West Virginia Brooke -2.93 -2.49 540110006 West Virginia Cabell -3.16 -2.56 540291004 West Virginia Hancock -2.86 -2.45 540330003 West Virginia Harrison -3.88 -3.36 540390010 West Virginia Kanawha -3.24 -2.68 540390011 West Virginia Kanawha -2.99 -2.50 540391005 West Virginia Kanawha -3.31 -2.72 540490006 West Virginia Marion -4.17 -3.62 540511002 West Virginia Marshall -3.22 -2.70 
B-129

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

540610003 West Virginia Monongalia -3.71 -3.13 540690010 West Virginia Ohio -3.03 -2.57 540810002 West Virginia Raleigh -2.87 -2.39 541071002 West Virginia Wood -2.91 -2.37 550030010 Wisconsin Ashland -0.39 -0.28 550090005 Wisconsin Brown -0.78 -0.50 550250047 Wisconsin Dane -1.19 -0.91 550270007 Wisconsin Dodge -1.12 -0.75 550410007 Wisconsin Forest -0.58 -0.39 550430009 Wisconsin Grant -1.14 -0.79 550590019 Wisconsin Kenosha -1.55 -1.05 550710007 Wisconsin Manitowoc -0.86 -0.57 550790010 Wisconsin Milwaukee -1.47 -0.97 550790026 Wisconsin Milwaukee -1.42 -0.95 550790043 Wisconsin Milwaukee -1.49 -0.98 550790059 Wisconsin Milwaukee -1.45 -0.95 550790099 Wisconsin Milwaukee -1.43 -0.95 550870009 Wisconsin Outagamie -0.80 -0.52 550890009 Wisconsin Ozaukee -1.26 -0.85 551091002 Wisconsin St. Croix -0.62 -0.41 551110007 Wisconsin Sauk -1.06 -0.74 551198001 Wisconsin Taylor -0.58 -0.41 551250001 Wisconsin Vilas -0.50 -0.35 551330027 Wisconsin Waukesha -1.29 -0.84 560050877 Wyoming Campbell -0.01 0.01 560050892 Wyoming Campbell 0.01 0.00 560050899 Wyoming Campbell 0.00 0.01 560090819 Wyoming Converse 0.00 0.01 560131003 Wyoming Fremont -0.04 0.01 
B-130

Annual PM2.5 (μg/m3) 

Monitor ID State County 

Difference: 

2014 Remedy -

2012 Base Case

Difference: 

2014 Remedy -

2014 Base Case

560210001 Wyoming Laramie -0.05 0.01 560330002 Wyoming Sheridan -0.06 0.01 
B-131

Differences in 24-Hour PM2.5 Design Values (μg/m3) by Site: 

2014 Remedy Scenario Compared to the 2012 Base Case and the 2014 Base Ca

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

10030010 Alabama Baldwin -4.6 -3.8 10270001 Alabama Clay -6.1 -4.2 10331002 Alabama Colbert -8.3 -6.8 10491003 Alabama DeKalb -6.0 -4.1 10530002 Alabama Escambia -4.3 -3.4 10550010 Alabama Etowah -6.2 -4.6 10690003 Alabama Houston -3.6 -2.6 10730023 Alabama Jefferson -4.4 -3.2 10731005 Alabama Jefferson -5.6 -4.1 10731009 Alabama Jefferson -6.5 -4.9 10731010 Alabama Jefferson -6.2 -4.7 10732003 Alabama Jefferson -3.7 -2.8 10732006 Alabama Jefferson -6.1 -4.8 10735002 Alabama Jefferson -7.2 -5.4 10735003 Alabama Jefferson -7.0 -5.4 10890014 Alabama Madison -8.6 -6.7 10970002 Alabama Mobile -4.6 -3.1 10970003 Alabama Mobile -4.7 -3.3 10972005 Alabama Mobile -5.3 -4.1 11010007 Alabama Montgomery -5.4 -4.2 11030011 Alabama Morgan -8.7 -6.8 11130001 Alabama Russell -4.4 -3.0 11170006 Alabama Shelby -6.0 -4.6 11190002 Alabama Sumter -5.9 -4.4 11210002 Alabama Talladega -5.7 -4.0 11250004 Alabama Tuscaloosa -5.1 -4.0 11270002 Alabama Walker -5.4 -4.0 50010011 Arkansas Arkansas -7.1 -6.1 50030005 Arkansas Ashley -4.6 -3.5 
B-132

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

50350005 Arkansas Crittenden -12.0 -10.4 50450002 Arkansas Faulkner -5.7 -4.8 50510003 Arkansas Garland -7.1 -6.1 50930007 Arkansas Mississippi -8.4 -6.8 51070001 Arkansas Phillips -7.2 -6.0 51130002 Arkansas Polk -6.2 -5.2 51150003 Arkansas Pope -3.2 -2.3 51190007 Arkansas Pulaski -6.0 -5.0 51191004 Arkansas Pulaski -4.9 -3.9 51191005 Arkansas Pulaski -4.7 -3.6 51390006 Arkansas Union -4.7 -3.6 51450001 Arkansas White -6.6 -5.4 80010006 Colorado Adams -0.1 0.4 80050005 Colorado Arapahoe -0.4 0.0 80130003 Colorado Boulder -0.2 0.2 80130012 Colorado Boulder -0.3 0.0 80290004 Colorado Delta -0.6 -0.1 80310002 Colorado Denver 0.1 0.4 80310023 Colorado Denver 0.1 0.5 80390001 Colorado Elbert -0.3 -0.1 80410008 Colorado El Paso -0.3 0.0 80410011 Colorado El Paso -0.3 0.0 80690009 Colorado Larimer -0.2 0.0 80770017 Colorado Mesa -0.4 0.0 81010012 Colorado Pueblo -0.3 0.0 81130004 Colorado San Miguel 0.0 0.0 81230006 Colorado Weld 0.1 0.3 81230008 Colorado Weld -0.1 0.2 90010010 Connecticut Fairfield -3.1 -2.4 90011123 Connecticut Fairfield -2.1 -1.5 90013005 Connecticut Fairfield -3.4 -2.8 90019003 Connecticut Fairfield -4.7 -4.0 90031003 Connecticut Hartford -3.3 -2.7 
B-133

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

90050005 Connecticut Litchfield -5.5 -4.9 90090026 Connecticut New Haven -4.0 -3.3 90090027 Connecticut New Haven -2.7 -2.0 90091123 Connecticut New Haven -3.4 -2.6 90092008 Connecticut New Haven -4.4 -3.7 90092123 Connecticut New Haven -2.6 -1.9 90113002 Connecticut New London -4.0 -3.3 

100010002 Delaware Kent -3.0 -2.6 100010003 Delaware Kent -3.2 -2.7 100031003 Delaware New Castle -2.7 -2.3 100031007 Delaware New Castle -2.2 -1.9 100031012 Delaware New Castle -1.7 -1.3 100032004 Delaware New Castle -2.4 -2.0 100051002 Delaware Sussex -2.9 -2.4 110010041 

District Of Columbia District of Columbia -2.8 -2.4 

110010042 

District Of Columbia District of Columbia -2.5 -2.2 

110010043 

District Of Columbia District of Columbia -2.5 -2.3 

120010023 Florida Alachua -3.8 -3.1 120010024 Florida Alachua -3.4 -2.7 120051004 Florida Bay -3.2 -2.2 120090007 Florida Brevard -1.8 -1.3 120111002 Florida Broward -1.6 -1.0 120112004 Florida Broward -1.3 -0.7 120113002 Florida Broward -1.4 -0.9 120170005 Florida Citrus -3.1 -2.3 120310098 Florida Duval -2.1 -1.6 120310099 Florida Duval -1.1 -0.7 120330004 Florida Escambia -3.3 -2.6 120570030 Florida Hillsborough -1.3 -0.6 120573002 Florida Hillsborough -1.6 -0.9 
B-134

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

120710005 Florida Lee -1.8 -1.1 120730012 Florida Leon -3.3 -2.5 120814012 Florida Manatee -1.8 -1.3 120830003 Florida Marion -2.7 -2.0 120861016 Florida Miami-Dade -1.1 -0.7 120866001 Florida Miami-Dade -2.1 -1.4 120951004 Florida Orange -1.8 -1.1 120952002 Florida Orange -1.9 -1.1 120990009 Florida Palm Beach -1.7 -1.1 120992005 Florida Palm Beach -1.5 -1.0 121030018 Florida Pinellas -1.1 -0.6 121031009 Florida Pinellas -1.3 -1.0 121056006 Florida Polk -1.7 -1.0 121111002 Florida St. Lucie -2.6 -1.9 121150013 Florida Sarasota -2.3 -1.6 121171002 Florida Seminole -2.9 -1.9 121275002 Florida Volusia -3.8 -2.7 130210007 Georgia Bibb -3.8 -2.1 130210012 Georgia Bibb -5.7 -3.5 130510017 Georgia Chatham -3.1 -2.1 130510091 Georgia Chatham -2.6 -1.6 130630091 Georgia Clayton -3.8 -2.8 130670003 Georgia Cobb -4.3 -2.8 130670004 Georgia Cobb -4.9 -2.4 130890002 Georgia DeKalb -3.3 -2.1 130892001 Georgia DeKalb -3.0 -1.7 130950007 Georgia Dougherty -4.0 -2.8 131150005 Georgia Floyd -4.2 -2.9 131210032 Georgia Fulton -3.1 -1.7 131210039 Georgia Fulton -4.2 -1.6 131270006 Georgia Glynn -3.1 -2.1 131350002 Georgia Gwinnett -3.6 -2.5 131390003 Georgia Hall -4.3 -1.6 
B-135

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

131530001 Georgia Houston -4.8 -2.9 131850003 Georgia Lowndes -3.0 -2.1 132150001 Georgia Muscogee -3.1 -2.0 132150008 Georgia Muscogee -4.9 -3.1 132150011 Georgia Muscogee -3.0 -1.7 132230003 Georgia Paulding -4.9 -3.1 132450005 Georgia Richmond -1.8 -1.0 132450091 Georgia Richmond -3.3 -2.0 132950002 Georgia Walker -4.3 -2.9 133030001 Georgia Washington -6.8 -2.9 133190001 Georgia Wilkinson -4.6 -2.5 170010006 Illinois Adams -5.3 -3.7 170190004 Illinois Champaign -6.3 -5.2 170191001 Illinois Champaign -4.7 -3.6 170310022 Illinois Cook -1.7 -1.1 170310050 Illinois Cook -3.8 -2.0 170310052 Illinois Cook -1.9 -0.7 170310057 Illinois Cook -4.5 -3.2 170310076 Illinois Cook -4.0 -2.5 170311016 Illinois Cook -3.3 -1.7 170312001 Illinois Cook -4.0 -2.8 170313103 Illinois Cook -2.2 -1.4 170313301 Illinois Cook -3.3 -1.9 170314007 Illinois Cook -3.2 -1.8 170314201 Illinois Cook -3.0 -1.1 170316005 Illinois Cook -1.8 -0.9 170434002 Illinois DuPage -1.6 -0.8 170650002 Illinois Hamilton -10.2 -8.3 170831001 Illinois Jersey -8.0 -5.2 170890003 Illinois Kane -3.2 -1.5 170890007 Illinois Kane -2.5 -1.0 170971007 Illinois Lake -7.0 -4.9 170990007 Illinois La Salle -3.3 -1.9 
B-136

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

171110001 Illinois McHenry -2.3 -1.2 171132003 Illinois McLean -7.3 -5.4 171150013 Illinois Macon -8.9 -7.2 171190023 Illinois Madison -7.2 -4.4 171191007 Illinois Madison -5.7 -3.7 171192009 Illinois Madison -8.6 -6.8 171193007 Illinois Madison -9.3 -7.4 171430037 Illinois Peoria -6.1 -2.5 171570001 Illinois Randolph -4.4 -2.4 171613002 Illinois Rock Island -2.2 -1.1 171630010 Illinois Saint Clair -5.9 -3.4 171634001 Illinois Saint Clair -6.0 -3.2 171670012 Illinois Sangamon -6.2 -4.2 171971002 Illinois Will -5.5 -4.0 171971011 Illinois Will -8.0 -6.3 172010013 Illinois Winnebago -3.3 -1.5 180030004 Indiana Allen -2.4 -1.7 180030014 Indiana Allen -2.9 -2.3 180190006 Indiana Clark -9.5 -7.5 180350006 Indiana Delaware -6.7 -5.4 180372001 Indiana Dubois -8.6 -7.4 180390003 Indiana Elkhart -4.8 -3.7 180431004 Indiana Floyd -10.5 -8.9 180650003 Indiana Henry -7.0 -5.9 180670003 Indiana Howard -7.6 -6.2 180830004 Indiana Knox -7.1 -6.0 180890006 Indiana Lake -2.0 -1.3 180890022 Indiana Lake -2.0 -1.1 180890026 Indiana Lake -3.6 -2.2 180890027 Indiana Lake -2.2 -1.3 180890031 Indiana Lake -6.2 -4.6 180891003 Indiana Lake -1.9 -1.1 180892004 Indiana Lake -1.9 -1.3 
B-137

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

180892010 Indiana Lake -3.8 -2.9 180910011 Indiana LaPorte -5.2 -3.7 180910012 Indiana LaPorte -3.5 -2.4 180950009 Indiana Madison -7.7 -6.6 180970042 Indiana Marion -7.7 -5.9 180970043 Indiana Marion -7.3 -5.6 180970066 Indiana Marion -8.4 -6.8 180970078 Indiana Marion -6.3 -4.7 180970079 Indiana Marion -8.6 -6.9 180970081 Indiana Marion -9.2 -7.8 180970083 Indiana Marion -10.0 -8.3 181270020 Indiana Porter -5.2 -3.7 181270024 Indiana Porter -3.3 -2.1 181410014 Indiana St. Joseph -3.5 -2.8 181411008 Indiana St. Joseph -2.3 -1.4 181412004 Indiana St. Joseph -2.0 -1.4 181470009 Indiana Spencer -8.7 -7.2 181570008 Indiana Tippecanoe -6.4 -4.9 181630006 Indiana Vanderburgh -7.3 -6.3 181630012 Indiana Vanderburgh -7.1 -6.1 181630016 Indiana Vanderburgh -4.4 -3.4 181670018 Indiana Vigo -2.4 -1.0 181670023 Indiana Vigo -4.3 -2.9 190130008 Iowa Black Hawk -1.3 -0.8 190450021 Iowa Clinton -3.1 -0.8 191032001 Iowa Johnson -2.1 -1.5 191130037 Iowa Linn -2.6 -1.0 191370002 Iowa Montgomery -3.6 -2.7 191390015 Iowa Muscatine -2.4 -1.7 191471002 Iowa Palo Alto -4.2 -3.2 191530030 Iowa Polk -3.1 -2.2 191532510 Iowa Polk -3.4 -2.5 191532520 Iowa Polk -2.2 -1.7 
B-138

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

191550009 Iowa Pottawattamie -2.4 -1.9 191630015 Iowa Scott -1.6 -0.5 191630018 Iowa Scott -1.7 -0.6 191630019 Iowa Scott -4.9 -2.1 191770006 Iowa Van Buren -2.4 -1.4 191930017 Iowa Woodbury -1.4 -1.1 191970004 Iowa Wright -2.9 -1.9 200910007 Kansas Johnson -2.7 -1.7 200910009 Kansas Johnson -2.0 -1.0 200910010 Kansas Johnson -2.9 -1.8 201070002 Kansas Linn -3.7 -2.7 201730008 Kansas Sedgwick -3.3 -2.0 201730009 Kansas Sedgwick -0.8 -0.3 201730010 Kansas Sedgwick -1.4 -0.6 201770010 Kansas Shawnee -3.0 -1.6 201770011 Kansas Shawnee -3.8 -2.5 201910002 Kansas Sumner -2.5 -1.4 202090021 Kansas Wyandotte -3.0 -2.2 202090022 Kansas Wyandotte -2.5 -1.8 210130002 Kentucky Bell -5.9 -4.3 210190017 Kentucky Boyd -10.2 -8.6 210290006 Kentucky Bullitt -11.0 -9.1 210370003 Kentucky Campbell -5.3 -4.1 210430500 Kentucky Carter -9.8 -8.2 210470006 Kentucky Christian -12.7 -11.1 210590005 Kentucky Daviess -15.3 -13.2 210670012 Kentucky Fayette -7.9 -5.9 210670014 Kentucky Fayette -8.7 -6.6 210730006 Kentucky Franklin -10.5 -8.5 210930006 Kentucky Hardin -12.6 -10.8 211010014 Kentucky Henderson -7.1 -6.2 211110043 Kentucky Jefferson -8.6 -7.1 211110044 Kentucky Jefferson -8.4 -6.7 
B-139

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

211110048 Kentucky Jefferson -9.3 -7.7 211110051 Kentucky Jefferson -11.6 -10.1 211170007 Kentucky Kenton -9.4 -8.1 211250004 Kentucky Laurel -5.8 -4.5 211451004 Kentucky McCracken -11.3 -9.4 211510003 Kentucky Madison -7.8 -6.1 211930003 Kentucky Perry -7.6 -6.0 211950002 Kentucky Pike -8.1 -6.7 212270007 Kentucky Warren -12.1 -10.0 220171002 Louisiana Caddo -3.6 -2.5 220190009 Louisiana Calcasieu -4.0 -3.2 220190010 Louisiana Calcasieu -4.5 -3.6 220290003 Louisiana Concordia -5.8 -4.8 220330009 Louisiana East Baton Rouge -2.8 -1.5 220331001 Louisiana East Baton Rouge -3.2 -2.1 220470005 Louisiana Iberville -2.2 -0.6 220470009 Louisiana Iberville -4.7 -3.5 220511001 Louisiana Jefferson -4.2 -3.0 220550006 Louisiana Lafayette -5.7 -4.4 220730004 Louisiana Ouachita -5.3 -4.4 220790002 Louisiana Rapides -7.0 -5.7 221050001 Louisiana Tangipahoa -4.2 -2.7 221090001 Louisiana Terrebonne -5.4 -4.0 221210001 Louisiana West Baton Rouge -2.5 -1.3 230010011 Maine Androscoggin -1.2 -0.8 230030013 Maine Aroostook -0.9 -0.5 230031011 Maine Aroostook -1.2 -0.8 230050015 Maine Cumberland -1.4 -0.9 230050027 Maine Cumberland -1.5 -0.8 230090103 Maine Hancock -2.0 -1.9 230110016 Maine Kennebec -1.4 -0.9 230172011 Maine Oxford -1.6 -1.1 230190002 Maine Penobscot -1.5 -1.1 
B-140

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

240030014 Maryland Anne Arundel -2.5 -2.5 240031003 Maryland Anne Arundel -0.9 -1.5 240032002 Maryland Anne Arundel -1.4 -1.6 240051007 Maryland Baltimore -2.8 -2.6 240053001 Maryland Baltimore -1.9 -1.9 240150003 Maryland Cecil -2.9 -2.6 240251001 Maryland Harford -2.9 -2.7 240313001 Maryland Montgomery -3.5 -3.0 240330030 Maryland Prince George's -4.9 -4.5 240338003 Maryland Prince George's -4.1 -4.0 240430009 Maryland Washington -4.6 -3.9 245100006 Maryland Baltimore (City) -1.9 -1.9 245100007 Maryland Baltimore (City) -2.4 -2.2 245100008 Maryland Baltimore (City) -1.4 -1.3 245100035 Maryland Baltimore (City) -1.3 -1.1 245100040 Maryland Baltimore (City) -1.3 -1.1 245100049 Maryland Baltimore (City) -1.2 -1.0 250035001 Massachusetts Berkshire -1.9 -1.4 250051004 Massachusetts Bristol -2.1 -2.0 250092006 Massachusetts Essex -2.1 -1.7 250095005 Massachusetts Essex -3.4 -3.0 250096001 Massachusetts Essex -2.2 -1.8 250130008 Massachusetts Hampden -2.4 -1.9 250130016 Massachusetts Hampden -2.2 -1.5 250132009 Massachusetts Hampden -2.1 -1.3 250230004 Massachusetts Plymouth -2.9 -2.5 250250002 Massachusetts Suffolk -1.1 -0.8 250250027 Massachusetts Suffolk -1.1 -0.9 250250042 Massachusetts Suffolk -1.0 -0.6 250250043 Massachusetts Suffolk -1.2 -0.8 250270016 Massachusetts Worcester -2.9 -2.3 250270023 Massachusetts Worcester -2.1 -1.4 260050003 Michigan Allegan -2.7 -1.5 
B-141

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

260170014 Michigan Bay -2.9 -1.9 260210014 Michigan Berrien -3.7 -2.7 260490021 Michigan Genesee -1.7 -1.0 260650012 Michigan Ingham -2.4 -1.5 260770008 Michigan Kalamazoo -3.1 -2.3 260810020 Michigan Kent -3.5 -2.1 260990009 Michigan Macomb -2.2 -1.4 261130001 Michigan Missaukee -4.3 -2.8 261150005 Michigan Monroe -5.8 -4.4 261210040 Michigan Muskegon -4.4 -2.8 261250001 Michigan Oakland -2.8 -1.8 261390005 Michigan Ottawa -2.0 -1.2 261450018 Michigan Saginaw -3.3 -2.2 261470005 Michigan St. Clair -3.7 -2.9 261610005 Michigan Washtenaw -4.0 -2.7 261610008 Michigan Washtenaw -2.5 -1.4 261630001 Michigan Wayne -2.6 -1.4 261630015 Michigan Wayne -4.5 -3.1 261630016 Michigan Wayne -2.4 -1.5 261630019 Michigan Wayne -1.6 -0.7 261630025 Michigan Wayne -3.6 -2.4 261630033 Michigan Wayne -3.0 -2.0 261630036 Michigan Wayne -1.9 -1.1 261630039 Michigan Wayne -2.4 -1.6 270210001 Minnesota Cass -1.5 -1.0 270370470 Minnesota Dakota -2.6 -1.5 270530050 Minnesota Hennepin -2.6 -1.8 270530961 Minnesota Hennepin -1.7 -1.2 270530963 Minnesota Hennepin -2.2 -1.4 270530965 Minnesota Hennepin -1.3 -0.9 270531007 Minnesota Hennepin -2.0 -1.3 270532006 Minnesota Hennepin -2.3 -1.6 270953051 Minnesota Mille Lacs -2.0 -1.5 
B-142

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

271230866 Minnesota Ramsey -1.4 -1.0 271230868 Minnesota Ramsey -2.4 -1.6 271230871 Minnesota Ramsey -2.3 -1.3 271377001 Minnesota Saint Louis -1.8 -1.1 271377550 Minnesota Saint Louis -2.6 -1.7 271377551 Minnesota Saint Louis -2.6 -1.9 271390505 Minnesota Scott -2.4 -1.7 271453052 Minnesota Stearns -1.3 -0.7 280010004 Mississippi Adams -7.1 -5.9 280110001 Mississippi Bolivar -6.8 -5.5 280330002 Mississippi DeSoto -9.2 -7.5 280350004 Mississippi Forrest -4.1 -3.0 280470008 Mississippi Harrison -5.5 -4.1 280490010 Mississippi Hinds -6.0 -4.9 280590006 Mississippi Jackson -4.9 -3.5 280670002 Mississippi Jones -4.6 -3.6 280750003 Mississippi Lauderdale -6.8 -5.5 280810005 Mississippi Lee -8.1 -6.4 280870001 Mississippi Lowndes -6.9 -5.2 281090001 Mississippi Pearl River -4.5 -3.3 281490004 Mississippi Warren -6.9 -5.8 290190004 Missouri Boone -4.6 -3.2 290210005 Missouri Buchanan -3.1 -2.2 290370003 Missouri Cass -3.7 -2.8 290390001 Missouri Cedar -6.1 -4.6 290470005 Missouri Clay -2.1 -1.1 290770032 Missouri Greene -7.0 -4.8 290950034 Missouri Jackson -2.5 -1.8 290990012 Missouri Jefferson -6.0 -2.9 291370001 Missouri Monroe -4.2 -2.9 291831002 Missouri Saint Charles -6.9 -5.0 291860006 Missouri Sainte Genevieve -6.8 -4.4 291890004 Missouri Saint Louis -8.3 -5.7 
B-143

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

291892003 Missouri Saint Louis -2.7 -1.3 295100007 Missouri St. Louis City -6.9 -4.2 295100085 Missouri St. Louis City -5.5 -3.1 295100086 Missouri St. Louis City -4.9 -2.6 295100087 Missouri St. Louis City -5.6 -2.9 300870307 Montana Rosebud -0.1 0.0 301111065 Montana Yellowstone -0.1 0.0 310550019 Nebraska Douglas -3.0 -2.4 310550052 Nebraska Douglas -2.1 -1.7 310790004 Nebraska Hall -1.4 -0.9 311090022 Nebraska Lancaster -1.6 -1.2 311111002 Nebraska Lincoln -0.7 -0.4 311530007 Nebraska Sarpy -2.9 -2.3 311570003 Nebraska Scotts Bluff -0.6 -0.4 311770002 Nebraska Washington -2.2 -1.7 330012004 New Hampshire Belknap -3.2 -2.7 330050007 New Hampshire Cheshire -1.8 -1.3 330070014 New Hampshire Coos -2.4 -1.9 330090010 New Hampshire Grafton -2.2 -1.7 330110020 New Hampshire Hillsborough -1.3 -0.9 330111015 New Hampshire Hillsborough -1.2 -0.8 330115001 New Hampshire Hillsborough -5.3 -4.8 330131006 New Hampshire Merrimack -2.5 -2.1 330150014 New Hampshire Rockingham -1.7 -1.3 330190003 New Hampshire Sullivan -3.8 -3.1 340030003 New Jersey Bergen -2.1 -1.5 340070003 New Jersey Camden -5.5 -4.7 340071007 New Jersey Camden -4.1 -3.3 340130015 New Jersey Essex -3.6 -2.8 340155001 New Jersey Gloucester -3.1 -2.6 340171003 New Jersey Hudson -2.8 -2.0 340172002 New Jersey Hudson -1.6 -0.9 340210008 New Jersey Mercer -4.9 -4.2 
B-144

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

340218001 New Jersey Mercer -5.3 -4.6 340230006 New Jersey Middlesex -4.9 -4.2 340270004 New Jersey Morris -4.0 -3.4 340273001 New Jersey Morris -6.6 -5.8 340292002 New Jersey Ocean -7.2 -6.4 340310005 New Jersey Passaic -4.5 -3.8 340390004 New Jersey Union -2.8 -1.7 340390006 New Jersey Union -1.6 -1.0 340392003 New Jersey Union -3.2 -2.3 340410006 New Jersey Warren -2.9 -2.5 350010023 New Mexico Bernalillo -0.5 -0.3 350010024 New Mexico Bernalillo -0.5 -0.4 350050005 New Mexico Chaves -0.9 -0.7 350130017 New Mexico Dona Ana -0.6 -0.3 350130025 New Mexico Dona Ana -0.8 -0.6 350431003 New Mexico Sandoval -0.4 -0.3 350439011 New Mexico Sandoval -0.3 -0.1 350450006 New Mexico San Juan -0.1 0.0 350490020 New Mexico Santa Fe -0.2 -0.1 360010005 New York Albany -2.0 -1.5 360050080 New York Bronx -2.4 -1.7 360050083 New York Bronx -1.8 -1.2 360050110 New York Bronx -1.3 -0.8 360130011 New York Chautauqua -6.1 -4.9 360290005 New York Erie -1.3 -1.0 360291007 New York Erie -1.9 -1.5 360310003 New York Essex -3.7 -3.1 360470122 New York Kings -2.8 -1.9 360551007 New York Monroe -3.0 -2.5 360590008 New York Nassau -5.0 -4.0 360610056 New York New York -1.8 -1.2 360610062 New York New York -2.1 -1.4 360610079 New York New York -2.8 -2.0 
B-145

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

360610128 New York New York -3.2 -2.4 360632008 New York Niagara -3.2 -2.0 360671015 New York Onondaga -5.2 -4.6 360710002 New York Orange -3.1 -2.5 360810124 New York Queens -1.9 -1.1 360850055 New York Richmond -2.5 -1.7 360850067 New York Richmond -3.8 -2.9 360893001 New York St. Lawrence -2.1 -1.6 361010003 New York Steuben -5.1 -4.5 361030001 New York Suffolk -6.6 -5.5 361191002 New York Westchester -4.0 -3.3 370010002 North Carolina Alamance -5.2 -4.4 370210034 North Carolina Buncombe -5.7 -5.0 370330001 North Carolina Caswell -5.9 -5.0 370350004 North Carolina Catawba -4.4 -3.8 370370004 North Carolina Chatham -4.3 -3.3 370510009 North Carolina Cumberland -3.7 -2.6 370570002 North Carolina Davidson -4.0 -3.3 370610002 North Carolina Duplin -4.4 -3.6 370630001 North Carolina Durham -4.0 -3.0 370650004 North Carolina Edgecombe -3.5 -2.5 370670022 North Carolina Forsyth -2.7 -1.8 370710016 North Carolina Gaston -4.2 -3.7 370810013 North Carolina Guilford -3.8 -2.8 370870010 North Carolina Haywood -3.8 -2.7 370990006 North Carolina Jackson -4.9 -3.3 371070004 North Carolina Lenoir -2.4 -1.7 371110004 North Carolina McDowell -4.5 -3.6 371170001 North Carolina Martin -2.6 -1.8 371190010 North Carolina Mecklenburg -3.5 -2.8 371190041 North Carolina Mecklenburg -3.6 -2.8 371190042 North Carolina Mecklenburg -3.3 -2.4 371210001 North Carolina Mitchell -4.7 -3.7 
B-146

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

371230001 North Carolina Montgomery -4.9 -4.0 371290002 North Carolina New Hanover -3.7 -3.0 371330005 North Carolina Onslow -3.2 -2.5 371350007 North Carolina Orange -5.2 -4.2 371470005 North Carolina Pitt -2.1 -1.3 371550005 North Carolina Robeson -5.2 -4.3 371590021 North Carolina Rowan -3.5 -3.2 371730002 North Carolina Swain -3.9 -2.4 371830014 North Carolina Wake -3.5 -2.4 371890003 North Carolina Watauga -6.3 -5.7 371910005 North Carolina Wayne -5.0 -3.9 380070002 North Dakota Billings -0.2 -0.2 380130003 North Dakota Burke -0.2 -0.1 380150003 North Dakota Burleigh -0.6 -0.4 380171004 North Dakota Cass -2.3 -1.6 380530002 North Dakota McKenzie -0.2 -0.2 380570004 North Dakota Mercer -0.2 -0.1 390090003 Ohio Athens -9.2 -7.6 390170003 Ohio Butler -11.2 -9.2 390170016 Ohio Butler -9.6 -7.8 390170017 Ohio Butler -10.1 -8.4 390171004 Ohio Butler -10.4 -8.7 390230005 Ohio Clark -7.0 -5.5 390250022 Ohio Clermont -9.6 -8.1 390350027 Ohio Cuyahoga -2.4 -1.9 390350034 Ohio Cuyahoga -3.8 -3.3 390350038 Ohio Cuyahoga -5.5 -4.3 390350045 Ohio Cuyahoga -6.6 -5.6 390350060 Ohio Cuyahoga -3.1 -2.4 390350065 Ohio Cuyahoga -6.3 -5.2 390351002 Ohio Cuyahoga -3.2 -2.5 390490024 Ohio Franklin -4.3 -2.9 390490025 Ohio Franklin -5.5 -4.2 
B-147

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

390490081 Ohio Franklin -6.3 -4.6 390570005 Ohio Greene -5.9 -4.7 390610006 Ohio Hamilton -10.8 -9.3 390610014 Ohio Hamilton -12.1 -10.7 390610040 Ohio Hamilton -10.9 -9.4 390610042 Ohio Hamilton -7.9 -6.6 390610043 Ohio Hamilton -8.1 -6.8 390617001 Ohio Hamilton -7.6 -6.1 390618001 Ohio Hamilton -8.6 -7.2 390810017 Ohio Jefferson -6.2 -4.9 390811001 Ohio Jefferson -6.5 -5.3 390851001 Ohio Lake -5.5 -4.9 390870010 Ohio Lawrence -8.3 -6.8 390933002 Ohio Lorain -5.5 -4.6 390950024 Ohio Lucas -2.2 -1.5 390950025 Ohio Lucas -2.3 -1.5 390950026 Ohio Lucas -3.4 -2.4 390990005 Ohio Mahoning -5.2 -3.7 390990014 Ohio Mahoning -3.9 -2.8 391130031 Ohio Montgomery -4.5 -3.3 391130032 Ohio Montgomery -5.2 -3.8 391330002 Ohio Portage -7.0 -5.8 391351001 Ohio Preble -7.8 -6.7 391450013 Ohio Scioto -9.3 -7.8 391510017 Ohio Stark -5.8 -5.0 391530017 Ohio Summit -4.2 -3.2 391530023 Ohio Summit -5.1 -4.2 391550007 Ohio Trumbull -3.7 -2.8 400159008 Oklahoma Caddo -2.5 -2.1 400219002 Oklahoma Cherokee -2.9 -2.1 400710602 Oklahoma Kay -2.8 -1.9 400719010 Oklahoma Kay -2.3 -1.6 400819005 Oklahoma Lincoln -3.7 -3.0 
B-148

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

400970186 Oklahoma Mayes -2.3 -1.4 400979014 Oklahoma Mayes -3.8 -2.8 401010169 Oklahoma Muskogee -2.8 -2.2 401090035 Oklahoma Oklahoma -1.3 -0.8 401091037 Oklahoma Oklahoma -2.4 -1.6 401159004 Oklahoma Ottawa -4.4 -3.3 401210415 Oklahoma Pittsburg -3.2 -2.5 401359015 Oklahoma Sequoyah -3.7 -3.2 401430110 Oklahoma Tulsa -2.9 -2.1 401431127 Oklahoma Tulsa -3.1 -2.2 420010001 Pennsylvania Adams -3.7 -3.1 420030008 Pennsylvania Allegheny -7.4 -6.2 420030021 Pennsylvania Allegheny -6.3 -5.5 420030064 Pennsylvania Allegheny -3.0 -1.4 420030067 Pennsylvania Allegheny -11.5 -10.0 420030093 Pennsylvania Allegheny -9.7 -8.3 420030095 Pennsylvania Allegheny -7.8 -6.5 420030116 Pennsylvania Allegheny -8.5 -6.9 420030133 Pennsylvania Allegheny -10.2 -8.8 420031008 Pennsylvania Allegheny -10.8 -9.5 420031301 Pennsylvania Allegheny -6.5 -5.4 420033007 Pennsylvania Allegheny -8.2 -7.0 420039002 Pennsylvania Allegheny -9.6 -8.3 420070014 Pennsylvania Beaver -7.7 -6.6 420110011 Pennsylvania Berks -2.5 -2.1 420170012 Pennsylvania Bucks -2.9 -2.1 420210011 Pennsylvania Cambria -14.7 -13.8 420270100 Pennsylvania Centre -5.1 -4.4 420290100 Pennsylvania Chester -3.0 -2.5 420410101 Pennsylvania Cumberland -2.3 -2.0 420430401 Pennsylvania Dauphin -2.1 -1.7 420450002 Pennsylvania Delaware -4.3 -3.6 420490003 Pennsylvania Erie -3.3 -2.6 
B-149

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

420692006 Pennsylvania Lackawanna -3.4 -2.7 420710007 Pennsylvania Lancaster -1.7 -1.5 420770004 Pennsylvania Lehigh -2.0 -1.5 420791101 Pennsylvania Luzerne -2.7 -1.9 420850100 Pennsylvania Mercer -3.8 -2.5 420950025 Pennsylvania Northampton -2.4 -1.7 420990301 Pennsylvania Perry -2.8 -2.6 421010004 Pennsylvania Philadelphia -2.1 -1.3 421010024 Pennsylvania Philadelphia -3.9 -3.1 421010047 Pennsylvania Philadelphia -4.2 -3.4 421250005 Pennsylvania Washington -7.9 -7.0 421250200 Pennsylvania Washington -5.9 -5.1 421255001 Pennsylvania Washington -7.9 -6.7 421290008 Pennsylvania Westmoreland -9.5 -8.4 421330008 Pennsylvania York -3.1 -2.7 440070022 Rhode Island Providence -2.5 -2.1 440070026 Rhode Island Providence -2.0 -1.5 440070028 Rhode Island Providence -2.3 -1.9 440071010 Rhode Island Providence -2.3 -1.9 450130007 South Carolina Beaufort -5.3 -3.9 450190048 South Carolina Charleston -2.2 -1.2 450190049 South Carolina Charleston -3.6 -2.3 450250001 South Carolina Chesterfield -4.2 -3.5 450370001 South Carolina Edgefield -6.1 -3.8 450410002 South Carolina Florence -4.1 -3.0 450430009 South Carolina Georgetown -3.9 -2.9 450450008 South Carolina Greenville -2.8 -1.5 450450009 South Carolina Greenville -3.9 -2.6 450470003 South Carolina Greenwood -4.7 -2.6 450510002 South Carolina Horry -4.4 -3.5 450630008 South Carolina Lexington -4.0 -2.9 450730001 South Carolina Oconee -5.7 -3.6 450790007 South Carolina Richland -4.2 -2.9 
B-150

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

450790019 South Carolina Richland -3.9 -2.5 450830010 South Carolina Spartanburg -3.9 -3.1 460110002 South Dakota Brookings -2.5 -1.7 460130003 South Dakota Brown -1.6 -1.0 460290002 South Dakota Codington -2.5 -1.7 460330132 South Dakota Custer -0.3 -0.3 460710001 South Dakota Jackson -0.6 -0.5 460990006 South Dakota Minnehaha -2.5 -1.7 460990007 South Dakota Minnehaha -2.4 -1.8 461030016 South Dakota Pennington -0.4 -0.2 461030020 South Dakota Pennington -0.2 -0.1 461031001 South Dakota Pennington -0.4 -0.2 470090011 Tennessee Blount -7.9 -6.6 470370023 Tennessee Davidson -10.7 -9.2 470370025 Tennessee Davidson -9.7 -8.1 470370036 Tennessee Davidson -12.4 -10.7 470450004 Tennessee Dyer -10.2 -8.3 470650031 Tennessee Hamilton -3.9 -2.6 470651011 Tennessee Hamilton -6.0 -4.8 470654002 Tennessee Hamilton -3.7 -2.4 470930028 Tennessee Knox -7.8 -6.3 470931017 Tennessee Knox -5.4 -4.2 470990002 Tennessee Lawrence -8.6 -7.4 471050108 Tennessee Loudon -7.0 -5.4 471071002 Tennessee McMinn -8.2 -6.5 471192007 Tennessee Maury -9.9 -8.5 471251009 Tennessee Montgomery -9.8 -8.4 471410001 Tennessee Putnam -11.0 -9.0 471450004 Tennessee Roane -6.2 -5.0 471570014 Tennessee Shelby -9.1 -7.4 471570038 Tennessee Shelby -10.0 -8.3 471570047 Tennessee Shelby -9.5 -8.0 471571004 Tennessee Shelby -9.7 -8.3 
B-151

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

471631007 Tennessee Sullivan -5.4 -4.6 471650007 Tennessee Sumner -14.6 -12.6 480370004 Texas Bowie -5.4 -4.3 481130069 Texas Dallas -1.6 -1.2 481130087 Texas Dallas -2.5 -1.8 481350003 Texas Ector -3.1 -1.4 481410037 Texas El Paso -0.5 -0.4 482010058 Texas Harris -3.5 -2.6 482011035 Texas Harris -3.0 -1.8 482030002 Texas Harrison -3.8 -3.2 482150043 Texas Hidalgo -2.6 -2.0 482450021 Texas Jefferson -5.2 -4.2 483550032 Texas Nueces -4.5 -3.4 483611001 Texas Orange -5.8 -4.8 484391002 Texas Tarrant -1.8 -1.4 484391006 Texas Tarrant -1.1 -0.8 500010002 Vermont Addison -3.0 -2.5 500010003 Vermont Addison -3.8 -3.2 500030004 Vermont Bennington -2.1 -1.5 500070012 Vermont Chittenden -5.2 -4.4 500070014 Vermont Chittenden -2.4 -1.7 500210002 Vermont Rutland -1.2 -0.7 510130020 Virginia Arlington -3.2 -2.4 510360002 Virginia Charles -5.3 -4.5 510410003 Virginia Chesterfield -4.6 -3.8 510590030 Virginia Fairfax -4.3 -3.9 510591005 Virginia Fairfax -4.6 -4.2 510595001 Virginia Fairfax -3.7 -3.0 510870014 Virginia Henrico -5.2 -4.4 510870015 Virginia Henrico -6.0 -5.3 511071005 Virginia Loudoun -6.1 -5.8 511390004 Virginia Page -7.7 -6.8 515200006 Virginia Bristol City -5.7 -4.8 
B-152

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

516500004 Virginia Hampton City -3.8 -2.9 516800015 Virginia Lynchburg City -7.1 -6.1 517100024 Virginia Norfolk City -3.6 -2.7 517700014 Virginia Roanoke City -5.1 -3.8 517750010 Virginia Salem City -5.1 -4.1 518100008 Virginia Virginia Beach City -3.2 -2.3 540030003 West Virginia Berkeley -2.7 -2.3 540090005 West Virginia Brooke -5.0 -4.1 540090011 West Virginia Brooke -3.5 -2.8 540110006 West Virginia Cabell -8.8 -7.5 540291004 West Virginia Hancock -8.3 -6.7 540330003 West Virginia Harrison -12.8 -11.1 540390010 West Virginia Kanawha -10.0 -8.7 540390011 West Virginia Kanawha -9.3 -8.1 540391005 West Virginia Kanawha -9.8 -8.5 540490006 West Virginia Marion -14.2 -12.7 540511002 West Virginia Marshall -7.1 -5.8 540610003 West Virginia Monongalia -13.3 -10.8 540690010 West Virginia Ohio -3.9 -2.9 540810002 West Virginia Raleigh -8.2 -7.1 540890001 West Virginia Summers -8.7 -7.4 541071002 West Virginia Wood -9.7 -8.1 550030010 Wisconsin Ashland -2.7 -2.0 550090005 Wisconsin Brown -0.5 -0.2 550090009 Wisconsin Brown -0.2 0.0 550250047 Wisconsin Dane -3.4 -2.5 550270007 Wisconsin Dodge -2.2 -1.0 550410007 Wisconsin Forest -2.6 -1.9 550430009 Wisconsin Grant -1.8 -1.0 550590019 Wisconsin Kenosha -2.3 -1.5 550710007 Wisconsin Manitowoc -1.3 -0.6 550790010 Wisconsin Milwaukee -1.4 -0.7 550790026 Wisconsin Milwaukee -1.9 -0.9 
B-153

24-Hour PM2.5 (μg/m3) 

Monitor ID State County 

Differences: 

2014 Remedy - 

2012 Base Case 

Differences: 

2014 Remedy - 

2014 Base Case 

550790043 Wisconsin Milwaukee -2.5 -1.0 550790059 Wisconsin Milwaukee -3.2 -1.9 550790099 Wisconsin Milwaukee -3.5 -2.2 550870009 Wisconsin Outagamie -0.5 -0.2 550890009 Wisconsin Ozaukee -1.8 -0.9 551091002 Wisconsin St. Croix -1.8 -1.0 551110007 Wisconsin Sauk -1.2 -0.4 551198001 Wisconsin Taylor -1.2 -0.6 551250001 Wisconsin Vilas -2.2 -1.5 551330027 Wisconsin Waukesha -3.3 -1.7 560050877 Wyoming Campbell -0.1 0.0 560050892 Wyoming Campbell 0.0 0.0 560050899 Wyoming Campbell 0.0 0.0 560090819 Wyoming Converse 0.0 0.0 560131003 Wyoming Fremont -0.2 0.1 560210001 Wyoming Laramie -0.2 -0.1 560330002 Wyoming Sheridan -0.2 0.0 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix C 

Ozone and PM2.5 Contribution Calculation Examples 
C-2

As described in Section IV, the contribution of ozone and PM2.5 from upwind states to downwind nonatt

maintenance receptors was calculated using a combination of MATS and other post-processing software. This ap

calculations in more detail. 

8-Hour Ozone [All example concentrations are in ppb]The 2012 future year base case ozone design value calculations are described in Section III.C. The 2012 design calculated by running MATS using the CAMx 2005 base year and 2012 future base case model outputs. The con

were calculated as described in Section IV.B. There are several pieces of information needed to calculate the up

contributions to downwind ozone receptor sites. 

1) The 2012 base case 8-hr design values at each receptor. 2) The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportio

described in Section IV.B steps 4 and 5. The source apportionment MATS runs specify the “base” year mCAMx base case and the “future” year model file as the 2012 CAMx source apportionment case. A sepaapportionment MATS case is run for each upwind state. 

The 2012 future year design values are shown in the example below as the variable “f_o3_DV” (from the MATS “scenario_name - Ozone Monitors -- monitor data, temporally adjusted 2012.csv”) 

_id lat Long referencecell f_o3_DV _state_name _county_name 

10331002 34.76056 -87.6506 155091 64.5 Alabama Colbert 10731003 33.48556 -86.915 162080 69.7 Alabama Jefferson 10731005 33.33111 -87.0036 162078 71 Alabama Jefferson 10731009 33.45972 -87.3056 159079 66.4 Alabama Jefferson 

These values are multiplied by the RRFs calculated from each source apportionment MATS run (for each upwinin the orange column (below) represent the relative ozone contribution from an upwind state to each downwind rexample, an RRF value of 0.9569 for Colbert County means that the upwind state contributes 4.31% [(1 – 0.9569

in Colbert County (averaged across all high1 ozone days) 

1 The high ozone day threshold for the MATS ozone contribution runs are defined in Section IV.B. step 5. 
C-3

_id lat long referencecell f_o3_DV _state_name _county_name SA_rrf 

10331002 34.76056 -87.6506 155091 64.5 Alabama Colbert 0.9569 10731003 33.48556 -86.915 162080 69.7 Alabama Jefferson 0.9944 10731005 33.33111 -87.0036 162078 71 Alabama Jefferson 0.9979 10731009 33.45972 -87.3056 159079 66.4 Alabama Jefferson 0.9986 

The 2012 future year design value (f_o3_DV) is multiplied by the RRF and then subtracted from the 2012 design upwind contribution in ppb (the values in blue below). Here is the formula: Ozone Contribution = f_o3_dv – (f_o3_dv * RRF) The future design values and RRFs were derived from MATS. The calculation of the contribution was accompli

post-processing software (using the formula above). The final 8-hr ozone contributions (in ppb) are truncated to consistent with the NAAQS. 

_id lat long referencecell f_o3_DV _state_name _county_name SA_rrf C

10331002 34.76056 -87.6506 155091 64.5 Alabama Colbert 0.9569 10731003 33.48556 -86.915 162080 69.7 Alabama Jefferson 0.9944 10731005 33.33111 -87.0036 162078 71 Alabama Jefferson 0.9979 10731009 33.45972 -87.3056 159079 66.4 Alabama Jefferson 0.9986 
C-4

Annual Average PM2.5 [All example concentrations are in ug/m3] The 2012 future year base case annual average PM2.5 design value calculations are described in Section III.B. Tvalues were calculated by running MATS using the CAMx 2005 base year and 2012 future base case model outp

PM2.5 contribution metrics were calculated as described in Section IV.A. The information needed to calculate thPM2.5 contributions to downwind annual PM2.5 receptor sites is as follows: 

1) The 2012 base case annual average PM2.5 design values and component species concentrations at each r2) The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportio

described in Section IV.A step 4. The source apportionment MATS runs specify the “base” year model fbase case and the “future” year model file as the 2012 CAMx source apportionment case. A separate souMATS case is run for each upwind state. 

The 2012 future year annual average PM2.5 design values are shown in the example below as the variable “f_pmthe MATS output file “scenario_name Annual PM25 Point.csv”). 

_id 

_STATE_NAME 

_COUNTY_NAME monitor_lat monitor_long 

monitor_gridcell 

b_pm25_ann_DV 

f_pm25_ann_DV 

10030010 Alabama Baldwin 30.498 -87.8814 158051 11.44 10.81 10270001 Alabama Clay 33.28126 -85.8022 171079 13.21 12 10331002 Alabama Colbert 34.76056 -87.6506 155091 12.67 12.13 10491003 Alabama DeKalb 34.28763 -85.9683 169088 14.09 12.75 

The 2012 future design value is comprised of a number of component PM2.5 species. The following table show

concentrations. 

_id _STATE_NAME 

_COUNTY_NAME 

f_blank_mass 

f_crustal_mass 

f_EC_mass 

f_NH4_mass 

f_Ocmb_mass 

f_SO4_mass 

f_NO3_mass 

f_water_mass 

f_salt_mass 

10030010 Alabama Baldwin 0.5 0.4838 0.4564 1.0612 3.2319 4.0003 0.0042 1.0489 0.0315 10270001 Alabama Clay 0.5 0.7034 0.5973 1.1121 4.3653 3.5529 0.0675 1.0888 0.02 10331002 Alabama Colbert 0.5 0.3902 0.3137 1.2683 4.2728 4.0396 0.1537 1.1984 0.0024 10491003 Alabama DeKalb 0.5 0.6574 0.4713 1.3423 4.2096 4.0967 0.1444 1.314 0.0163 
C-5

The source apportionment RRFs (in orange below) are derived from the source apportionment MATS runs. The

relative PM2.5 species contribution from an upwind state to each downwind receptor. For example, an RRF valu

Baldwin County for sulfate means that the upwind state contributes 3.44% [(1 – 0.9656)* 100)] of the sulfate ion (averaged across all days). 

_id _STATE_NAME _COUNTY_NAME SA_rrf_crustal SA_rrf_ec SA_rrf_nh4 SA_rrf_oc SA_rrf_so4 SA_rrf_no3 SA_r

10030010 Alabama Baldwin 0.9949 0.9947 0.964 0.9985 0.9656 0.9996 10270001 Alabama Clay 0.9895 0.9897 0.9535 0.9972 0.9529 0.9929 10331002 Alabama Colbert 0.9863 0.9871 0.9322 0.9954 0.928 0.9899 10491003 Alabama DeKalb 0.9862 0.9859 0.9371 0.9961 0.9364 0.9913 

The annual RRFs from the source apportionment MATS run are multiplied by the 2012 species concentrations an

from the 2012 species concentrations to get species contributions. Here is the formula: Annual PM2.5 Contribution (SO4) = f_SO4_mass – (f_SO4_mass * SA_rrf_SO4) The calculation is completed for each of the 7 species2 which have an RRF. The yellow and orange columns are 

MATS output files. The species contributions from upwind state “A” to the example downwind receptors are shown in blue below. Tthe final species contributions which are calculated using additional post-processing software (using the formula 

_id _STATE_NAME 

_COUNTY_NAME 

crustal_mass_SA 

EC_mass_SA 

NH4_mass_SA 

Ocmb_mass_SA 

SO4_mass_SA 

NO3_mass_SA 

water__SA 

10030010 Alabama Baldwin 0.002 0.002 0.038 0.005 0.138 0.000 10270001 Alabama Clay 0.007 0.006 0.052 0.012 0.167 0.000 10331002 Alabama Colbert 0.005 0.004 0.086 0.020 0.291 0.002 10491003 Alabama DeKalb 0.009 0.007 0.084 0.016 0.261 0.001 

2 The RRF for salt is not used because it is always equal to 1. 
C-6

For the transport rule contributions, the sulfate and nitrate and related species (ammonium and water) concentratget the total PM2.5 contribution used in the proposed rule. These are the values in the blue column below. The f

PM2.5 contributions (in ug/m3) are truncated to the hundredths digit, consistent with the NAAQS. 

_id _STATE_NAME _COUNTY_NAME 

Total Annual PM2.5 Mass Contribution 

10030010 Alabama Baldwin 0.20 10270001 Alabama Clay 0.26 10331002 Alabama Colbert 0.43 10491003 Alabama DeKalb 0.40 
C-7

24-Hour Average PM2.5 [All example concentrations are in ug/m3]

The 2012 future year base case 24 hr. average PM2.5 design value calculations are described in Section III.B. Th

were calculated by running MATS using the CAMx 2005 base year and 2012 future base case model outputs. Thcontribution metrics were calculated as described in Section IV.A. The 24-hr. PM2.5 contribution calculations a

complicated than the annual average calculations. High 24-hr values can occur at different times of the year at eTherefore, we must calculate the contributions to the downwind receptor for each of the quarters and years. The 

5 year average of the contribution to the high quarters for each year. The high future quarters vary by receptor an“scenario_name Daily All Years High Quarters PM25 PointAll years, all quarters.csv” MATS output file. 

The information needed to calculate the upwind 24-hr. PM2.5 contributions to downwind 24-hr. PM2.5 receptor 

1) The 2012 base case 24-hour average PM2.5 and component species concentrations for each quarter for (u

each receptor. 3) The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportio

described in Section IV.A step 4. The source apportionment MATS runs specify the “base” year model fbase case and the “future” year model file as the 2012 CAMx source apportionment case. A separate souMATS case is run for each upwind state. 

The 2012 future year 24-hr. quarterly peak PM2.5 values are shown in the example below as the variable “f_pm2the MATS output file “scenario_name Daily All Years All Quarters PM25 PointAnnual PM25 Point.csv”). This file used in the calculation of the future year 5-year weighted average design values. For the design value calculquarters for each year (in bold) are averaged together to create a 5 year weighted average (year 1 is weighted onc

three times, year 4 twice, and year 5 once). 

_id _state_name 

_county_name monitor_lat monitor_long 

monitor_gridcell year quarter 

b_pm25_d_q_conc 

10030010 Alabama Baldwin 30.498 -87.8814 158051 2003 1 19.7 10030010 Alabama Baldwin 30.498 -87.8814 158051 2003 2 29.1 10030010 Alabama Baldwin 30.498 -87.8814 158051 2003 3 22.7 10030010 Alabama Baldwin 30.498 -87.8814 158051 2003 4 28.4 10030010 Alabama Baldwin 30.498 -87.8814 158051 2004 1 25.5 10030010 Alabama Baldwin 30.498 -87.8814 158051 2004 2 18.1 
C-8

10030010 Alabama Baldwin 30.498 -87.8814 158051 2004 3 27.5 10030010 Alabama Baldwin 30.498 -87.8814 158051 2004 4 24.6 10030010 Alabama Baldwin 30.498 -87.8814 158051 2005 1 23.4 10030010 Alabama Baldwin 30.498 -87.8814 158051 2005 2 26 10030010 Alabama Baldwin 30.498 -87.8814 158051 2005 3 23.7 10030010 Alabama Baldwin 30.498 -87.8814 158051 2005 4 25 10030010 Alabama Baldwin 30.498 -87.8814 158051 2006 1 25.1 10030010 Alabama Baldwin 30.498 -87.8814 158051 2006 2 25.6 10030010 Alabama Baldwin 30.498 -87.8814 158051 2006 3 25.7 10030010 Alabama Baldwin 30.498 -87.8814 158051 2006 4 15.9 10030010 Alabama Baldwin 30.498 -87.8814 158051 2007 1 18.9 10030010 Alabama Baldwin 30.498 -87.8814 158051 2007 2 22.4 10030010 Alabama Baldwin 30.498 -87.8814 158051 2007 3 17.7 10030010 Alabama Baldwin 30.498 -87.8814 158051 2007 4 19.7 

The 2012 future 24-hr PM2.5 design value is comprised of a number of component PM2.5 species. The followin2012 species concentrations for each quarter. 

_id _state_name _county_name year quarter 

f_blank_mass_q 

f_crustal_mass_q 

f_EC_mass_q 

f_NH4_mass_q 

f_Ocmb_mass_q 

f_SO4_mass_q 

f_Nma

10030010 Alabama Baldwin 2003 1 0.5 0.4229 0.7735 1.8495 8.3227 5.467 10030010 Alabama Baldwin 2003 2 0.5 0.717 0.6498 2.8397 10.6108 10.3037 10030010 Alabama Baldwin 2003 3 0.5 0.6878 0.5218 1.7423 7.602 7.6151 10030010 Alabama Baldwin 2003 4 0.5 0.689 0.706 2.7188 10.0991 9.3557 10030010 Alabama Baldwin 2004 1 0.5 0.5507 1.0072 2.4082 10.8368 7.1185 10030010 Alabama Baldwin 2004 2 0.5 0.4413 0.3999 1.7475 6.5297 6.3407 10030010 Alabama Baldwin 2004 3 0.5 0.8365 0.6346 2.1191 9.2457 9.2617 10030010 Alabama Baldwin 2004 4 0.5 0.5952 0.6098 2.3485 8.7236 8.0815 10030010 Alabama Baldwin 2005 1 0.5 0.5044 0.9226 2.2059 9.9266 6.5206 10030010 Alabama Baldwin 2005 2 0.5 0.6393 0.5794 2.5319 9.4606 9.1869 10030010 Alabama Baldwin 2005 3 0.5 0.7188 0.5453 1.8208 7.9445 7.9582 10030010 Alabama Baldwin 2005 4 0.5 0.605 0.62 2.3875 8.8684 8.2156 10030010 Alabama Baldwin 2006 1 0.5 0.5419 0.9911 2.3697 10.6635 7.0046 10030010 Alabama Baldwin 2006 2 0.5 0.6293 0.5703 2.4922 9.3122 9.0428 
C-9

10030010 Alabama Baldwin 2006 3 0.5 0.7808 0.5923 1.9778 8.6293 8.6442 10030010 Alabama Baldwin 2006 4 0.5 0.3803 0.3897 1.5007 5.5744 5.1641 10030010 Alabama Baldwin 2007 1 0.5 0.4053 0.7413 1.7724 7.9759 5.2392 10030010 Alabama Baldwin 2007 2 0.5 0.5491 0.4976 2.1745 8.125 7.8899 10030010 Alabama Baldwin 2007 3 0.5 0.5329 0.4043 1.3499 5.8899 5.9 10030010 Alabama Baldwin 2007 4 0.5 0.4742 0.4859 1.871 6.9499 6.4383 

The source apportionment RRFs3 (in orange below) are derived from the source apportionment MATS runs. Therelative PM2.5 species contribution from an upwind state to each downwind receptor in each quarter4. For exam

0.8881 for Baldwin County for quarter 1 sulfate means that the upwind state contributes 11.19% [(1 – 0.8881)* 1in Baldwin County in quarter 1 (averaged across all high5 days in each quarter). 

_id _state_name _county_name year quarter SA_rrf_crustal_q SA_rrf_ec_q SA_rrf_nh4_q SA_rrf_oc_q SA_rrf_so

10030010 Alabama Baldwin 2003 1 0.9663 0.9772 0.9965 0.9852 0.810030010 Alabama Baldwin 2003 2 0.9912 0.9934 0.9996 0.9978 0.910030010 Alabama Baldwin 2003 3 0.9897 0.9914 0.9993 0.9985 010030010 Alabama Baldwin 2003 4 0.9715 0.971 0.9981 0.9918 0.910030010 Alabama Baldwin 2004 1 0.9663 0.9772 0.9965 0.9852 0.810030010 Alabama Baldwin 2004 2 0.9912 0.9934 0.9996 0.9978 0.910030010 Alabama Baldwin 2004 3 0.9897 0.9914 0.9993 0.9985 010030010 Alabama Baldwin 2004 4 0.9715 0.971 0.9981 0.9918 0.910030010 Alabama Baldwin 2005 1 0.9663 0.9772 0.9965 0.9852 0.810030010 Alabama Baldwin 2005 2 0.9912 0.9934 0.9996 0.9978 0.910030010 Alabama Baldwin 2005 3 0.9897 0.9914 0.9993 0.9985 010030010 Alabama Baldwin 2005 4 0.9715 0.971 0.9981 0.9918 0.910030010 Alabama Baldwin 2006 1 0.9663 0.9772 0.9965 0.9852 0.810030010 Alabama Baldwin 2006 2 0.9912 0.9934 0.9996 0.9978 0.9

3 One additional step is needed to calculate the water RRF. Since the MATS output file does not contain the quarterly wate

calculated from the base and future year water concentrations (f_water_mass_q / b_water_mass_q) 

4 There is a single species RRF for each of the 4 quarters. 5 Consistent with the 24-hr PM2.5 design value calculations, the “high” days are defined as the 10% highest modeled PM2

for each quarter at each receptor. 
C-10

10030010 Alabama Baldwin 2006 3 0.9897 0.9914 0.9993 0.9985 010030010 Alabama Baldwin 2006 4 0.9715 0.971 0.9981 0.9918 0.910030010 Alabama Baldwin 2007 1 0.9663 0.9772 0.9965 0.9852 0.810030010 Alabama Baldwin 2007 2 0.9912 0.9934 0.9996 0.9978 0.910030010 Alabama Baldwin 2007 3 0.9897 0.9914 0.9993 0.9985 010030010 Alabama Baldwin 2007 4 0.9715 0.971 0.9981 0.9918 0.9

The quarterly RRFs from the source apportionment MATS run are multiplied by the 2012 species concentrations from the 2012 species concentrations to get species contributions for each quarter. Here is the formula: 

Quarterly PM2.5 Contribution (SO4) = f_SO4_mass_q – (f_SO4_mass_q * SA_rrf_SO4_q) The calculation is completed for each quarter for each of the 7 species6 which have an RRF. The yellow and ora

taken directly from MATS output files. The species contributions from upwind state “A” to the example downwind receptor is shown in blue below. Ththe species contributions which are calculated using additional post-processing software (using the contribution f

_id _state_name _county_name year quarter 

crustal_mass_SA 

EC_mass_SA 

NH4_mass_SA 

Ocmb_mass_SA 

SO4_mass_SA 

NO3SA 

10030010 Alabama Baldwin 2003 1 0.014 0.017 0.006 0.121 0.543 10030010 Alabama Baldwin 2003 2 0.006 0.004 0.001 0.023 0.342 10030010 Alabama Baldwin 2003 3 0.007 0.004 0.001 0.011 0.416 10030010 Alabama Baldwin 2003 4 0.019 0.020 0.005 0.082 0.780 10030010 Alabama Baldwin 2004 1 0.018 0.022 0.008 0.158 0.707 10030010 Alabama Baldwin 2004 2 0.004 0.003 0.001 0.014 0.211 10030010 Alabama Baldwin 2004 3 0.009 0.005 0.001 0.014 0.506 10030010 Alabama Baldwin 2004 4 0.016 0.017 0.004 0.071 0.674 10030010 Alabama Baldwin 2005 1 0.016 0.021 0.008 0.145 0.648 10030010 Alabama Baldwin 2005 2 0.006 0.004 0.001 0.021 0.305 10030010 Alabama Baldwin 2005 3 0.007 0.005 0.001 0.012 0.435 

6 The RRF for salt is ignored because it is always equal to 1. 
C-11

10030010 Alabama Baldwin 2005 4 0.017 0.017 0.005 0.072 0.685 10030010 Alabama Baldwin 2006 1 0.018 0.022 0.008 0.155 0.696 10030010 Alabama Baldwin 2006 2 0.005 0.004 0.001 0.020 0.300 10030010 Alabama Baldwin 2006 3 0.008 0.005 0.001 0.013 0.472 10030010 Alabama Baldwin 2006 4 0.011 0.011 0.003 0.045 0.431 10030010 Alabama Baldwin 2007 1 0.013 0.017 0.006 0.116 0.521 10030010 Alabama Baldwin 2007 2 0.005 0.003 0.001 0.018 0.262 10030010 Alabama Baldwin 2007 3 0.005 0.003 0.001 0.009 0.322 10030010 Alabama Baldwin 2007 4 0.013 0.014 0.004 0.057 0.537 

The next step is to average the contributions for the high quarter in each of the 5 years (bolded values above). T

quarters for the receptor site were previously identified in the first step. The high future quarters for the 5 years areceptor site (Baldwin) are: Year 1 (2003) quarter 2 Year 2 (2004) quarter 1 Year 3 (2005) quarter 2 Year 4 (2006) quarter 2 Year 5 (2007) quarter 2 The contributions (from the blue columns in the table above) are averaged7 across the 5 high quarters (bolded row

result: 

crustal_mass_SA EC_mass_SA NH4_mass_SA Ocmb_mass_SA SO4_mass_SA NO3_mass_SA 

10030010 Alabama Baldwin 0.0080 0.0075 0.0025 0.0481 0.3835 0.0000 

7 The 5 year average for the contribution calculations is a “straight” 5 year average, not a weighted average. 
C-12

For the transport rule contributions, the sulfate and nitrate and related species (ammonium and water) concentratget the total PM2.5 contribution used in the proposed rule. The sum of these values is shown as the 24-hr PM2.5 

blue column below. The final 24 hr. PM2.5 contributions (in ug/m3) are truncated to the hundredths digit, consisNAAQS. 

_id _STATE_NAME _COUNTY_NAME 

Total 24 Hr. PM2.5 Mass Contribution 

10030010 Alabama Baldwin 0.49 
Transport Rule Air Quality Modeling Technical Support 

Document 

Appendix D 

2012 Base Case State-by-State Contributions to 

Nonattainment and Maintenance for 

8-Hour Ozone, Annual PM2.5, and 24-Hour PM2.5 
D-2

This Appendix provides tabular summaries of the State-by-State 

contributions to 8-hour ozone, annual PM2.5, and 24-hour PM2.5 at 

projected 2012 base case nonattainment receptors. 

The contributions from a State to nonattainment in another (i.e., 

“downwind”) State were used to identify States to be covered by the 

Transport Rule. 

The largest contribution from each State to nonattainment in a downwind 

State is provided at the bottom of the table. 

Contributions to downwind nonattainment that are at or above the following 

thresholds are shown in red. 

Ozone Threshold: 0.8 ppb 

Annual PM2.5 Threshold: 0.15 μg/m3

24-Hour PM2.5 Threshold: 0.35 μg/m3 

In-State contributions (i.e., the contribution from a State to nonattainment 

within the State itself) are provided in the tables in this Appendix for 

completeness. The in-State contributions were not used to identify States to 

be covered by the Transport Rule. 

The tabular summaries are provided by pollutant starting with 8-hour ozone, 

then annual PM2.5, and finally 24-hour PM2.5. For each pollutant the 

contributions to nonattainment sites are provided in “Part 1” and the 

contributions to maintenance sites are provided in “Part 2”. Note that the 

tabular summaries for each NAAQS span multiple pages. Also, note that 

some counties have multiple sites that are projected to be nonattainment as 

well as other sites that are projected to have a maintenance problem.
D-3

State-by-State Contributions to 8-Hour Ozone (ppb) Nonattainment Recept

Part 1a. 

Source States: Alabama through Missouri

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC MA 

220330003 Louisiana 

E.Baton Rouge 1.3 1.4 0.0 0.0 0.4 0.5 0.1 0.1 0.0 0.2 0.1 54.2 0.0 0.0 0.0 

361030002 New York Suffolk 0.0 0.2 0.7 1.0 0.1 0.0 0.7 1.1 0.1 0.1 1.2 0.1 0.0 2.3 0.4 361030009 New York Suffolk 0.1 0.1 1.7 1.6 0.1 0.1 0.8 0.9 0.2 0.1 0.7 0.2 0.0 2.9 0.6 421010024 Pennsylvania Philadelphia 0.4 0.2 0.0 3.3 0.2 0.3 0.5 0.9 0.1 0.1 2.3 0.2 0.0 6.1 0.0 480391004 Texas Brazoria 2.9 1.3 0.0 0.0 0.6 1.4 0.6 0.4 0.3 0.1 0.7 8.3 0.0 0.0 0.0 482010051 Texas Harris 3.6 0.5 0.0 0.0 0.6 1.9 0.7 0.6 0.3 0.1 0.9 8.4 0.0 0.0 0.0 482010055 Texas Harris 3.9 0.5 0.0 0.0 0.6 2.1 0.8 0.7 0.3 0.1 1.0 9.1 0.0 0.0 0.0 482010062 Texas Harris 4.0 0.7 0.0 0.0 0.8 2.0 0.7 0.6 0.2 0.1 0.9 10.0 0.0 0.0 0.0 482010066 Texas Harris 4.7 0.2 0.0 0.0 0.6 1.9 0.6 0.5 0.2 0.0 0.7 10.5 0.0 0.1 0.0 482011039 Texas Harris 3.5 0.7 0.0 0.0 0.7 1.7 0.6 0.5 0.2 0.1 0.8 11.4 0.0 0.0 0.0 484391002 Texas Tarrant 1.0 1.2 0.0 0.0 0.8 0.9 0.1 0.0 0.1 0.6 0.2 2.9 0.0 0.0 0.0 

Largest Contribution to Downwind Nonattainment => 4.7 1.4 1.7 3.3 0.8 2.1 0.8 1.1 0.3 0.6 2.3 11.4 0.0 6.1 0.6 
D-4

State-by-State Contributions to 8-Hour Ozone (ppb) Nonattainment Recept

Part 1b. 

Source States: Nebraska through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX VT V

220330003 Louisiana 

E.Baton Rouge 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.0 0.0 0.1 0.0 0.3 1.6 0.0 0

361030002 New York Suffolk 0.0 0.1 16.8 17.7 1.4 0.0 2.8 0.1 8.8 0.0 0.1 0.0 0.4 0.2 0.0 4361030009 New York Suffolk 0.1 0.1 14.7 15.4 1.7 0.1 2.1 0.1 8.9 0.1 0.1 0.0 0.3 0.2 0.0 4421010024 Pennsylvania Philadelphia 0.0 0.0 8.0 0.4 1.3 0.0 2.2 0.1 32.7 0.0 0.2 0.0 1.4 0.2 0.0 4480391004 Texas Brazoria 0.1 0.0 0.0 0.0 0.3 0.0 0.1 0.3 0.1 0.0 0.3 0.0 1.3 41.6 0.0 0482010051 Texas Harris 0.1 0.0 0.0 0.0 0.5 0.0 0.1 0.1 0.1 0.0 0.6 0.0 1.5 38.8 0.0 0482010055 Texas Harris 0.1 0.0 0.0 0.0 0.6 0.0 0.1 0.1 0.1 0.0 0.6 0.0 1.6 42.0 0.0 0482010062 Texas Harris 0.1 0.0 0.0 0.0 0.4 0.0 0.1 0.1 0.1 0.0 0.4 0.0 1.6 38.0 0.0 0482010066 Texas Harris 0.0 0.0 0.0 0.1 0.4 0.0 0.1 0.1 0.2 0.0 0.4 0.0 1.6 33.0 0.0 0482011039 Texas Harris 0.1 0.0 0.0 0.0 0.3 0.0 0.1 0.1 0.1 0.0 0.3 0.0 1.4 37.5 0.0 0484391002 Texas Tarrant 0.2 0.0 0.0 0.0 0.3 0.0 0.0 2.1 0.0 0.0 0.3 0.0 0.6 52.1 0.0 0

Largest Contribution to Downwind Nonattainment => 0.2 0.1 16.8 0.4 1.7 0.1 2.8 2.1 8.9 0.1 0.6 0.0 1.6 1.6 0.0 4
D-5

State-by-State Contributions to 8-Hour Ozone (ppb) Maintenance Recepto

Part 2a. 

Source States: Alabama through Missouri 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC MA 

90010017 Connecticut Fairfield 0.1 0.3 2.0 0.6 0.0 0.0 0.6 1.0 0.1 0.1 1.5 0.1 0.0 2.2 0.4 90011123 Connecticut Fairfield 0.1 0.3 5.6 0.5 0.2 0.1 0.5 0.7 0.1 0.1 1.4 0.1 0.0 1.7 0.4 90013007 Connecticut Fairfield 0.1 0.1 5.3 0.7 0.1 0.1 0.4 0.7 0.1 0.1 0.9 0.1 0.0 2.0 0.5 90093002 Connecticut New Haven 0.1 0.1 6.1 0.7 0.1 0.0 0.5 0.8 0.1 0.1 0.8 0.1 0.0 2.3 0.1 

130890002 Georgia DeKalb 4.5 0.3 0.0 0.0 1.1 51.8 0.1 0.2 0.0 0.0 0.5 0.7 0.0 0.0 0.0 131210055 Georgia Fulton 4.7 0.3 0.0 0.0 1.1 53.6 0.1 0.2 0.0 0.0 0.6 0.7 0.0 0.0 0.0 361192004 New York Westchester 0.0 0.2 1.6 0.4 0.2 0.0 0.6 0.9 0.2 0.1 1.2 0.1 0.0 1.5 0.5 420170012 Pennsylvania Bucks 0.3 0.4 0.2 2.5 0.1 0.2 0.6 0.9 0.1 0.1 1.8 0.3 0.0 4.2 0.1 481130069 Texas Dallas 0.5 1.5 0.0 0.0 0.3 0.6 0.2 0.3 0.1 0.8 0.2 1.5 0.0 0.0 0.0 481130087 Texas Dallas 0.6 1.8 0.0 0.0 0.4 0.6 0.4 0.2 0.2 0.7 0.2 2.5 0.0 0.0 0.0 482010024 Texas Harris 2.6 0.1 0.0 0.0 0.8 1.0 0.5 0.4 0.1 0.0 0.4 10.3 0.0 0.1 0.0 482010029 Texas Harris 1.4 0.0 0.0 0.0 2.1 1.7 0.1 0.2 0.0 0.0 0.2 7.4 0.0 0.1 0.0 482011050 Texas Harris 2.0 1.0 0.0 0.0 0.7 1.1 0.5 0.4 0.3 0.2 0.6 10.6 0.0 0.0 0.0 484392003 Texas Tarrant 1.3 1.0 0.0 0.0 0.6 1.2 0.0 0.0 0.0 0.4 0.1 2.8 0.0 0.0 0.0 

Largest Contribution to Downwind Maintenance => 4.7 1.8 1.6 2.5 2.1 1.7 0.6 1.0 0.3 0.8 1.8 10.6 0.0 4.2 0.5 
D-6

State-by-State Contributions to 8-Hour Ozone (ppb) Maintenance Recepto

Part 2b. 

Source States: Nebraska through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX VT V

90010017 Connecticut Fairfield 0.0 0.1 15.8 17.7 0.7 0.0 2.6 0.1 8.1 0.0 0.1 0.0 0.6 0.1 0.0 390011123 Connecticut Fairfield 0.0 0.1 13.9 21.0 2.0 0.0 1.7 0.1 5.3 0.0 0.3 0.0 0.6 0.1 0.0 390013007 Connecticut Fairfield 0.0 0.1 12.0 22.1 1.9 0.0 1.9 0.1 6.6 0.1 0.2 0.0 0.3 0.1 0.0 390093002 Connecticut New Haven 0.0 0.0 11.8 22.7 1.8 0.0 2.0 0.1 6.4 0.0 0.2 0.0 0.3 0.1 0.0 4

130890002 Georgia DeKalb 0.0 0.0 0.0 0.0 0.6 0.0 0.2 0.1 0.0 0.0 0.7 0.0 2.9 0.6 0.0 0131210055 Georgia Fulton 0.0 0.0 0.0 0.0 0.6 0.0 0.2 0.1 0.0 0.0 0.8 0.0 3.0 0.6 0.0 0361192004 New York Westchester 0.1 0.1 14.6 25.3 1.4 0.0 2.1 0.1 5.8 0.1 0.1 0.0 0.5 0.1 0.1 2420170012 Pennsylvania Bucks 0.0 0.1 15.2 2.6 0.9 0.0 2.0 0.1 23.8 0.0 0.1 0.0 1.1 0.3 0.1 3481130069 Texas Dallas 0.2 0.0 0.0 0.0 0.1 0.0 0.1 2.7 0.1 0.0 0.1 0.0 0.4 47.9 0.0 0481130087 Texas Dallas 0.2 0.0 0.0 0.0 0.2 0.0 0.0 2.5 0.1 0.0 0.2 0.0 0.2 47.7 0.0 0482010024 Texas Harris 0.0 0.0 0.0 0.1 0.4 0.0 0.1 0.0 0.2 0.0 0.3 0.0 0.8 35.6 0.0 0482010029 Texas Harris 0.0 0.0 0.0 0.0 0.7 0.0 0.1 0.0 0.1 0.0 0.8 0.0 0.3 40.1 0.0 0482011050 Texas Harris 0.1 0.0 0.0 0.0 0.3 0.0 0.0 0.7 0.1 0.0 0.3 0.0 1.0 38.6 0.0 0484392003 Texas Tarrant 0.1 0.0 0.0 0.0 0.4 0.0 0.1 1.8 0.1 0.0 0.4 0.0 0.6 50.1 0.0 0

Largest Contribution to Downwind Maintenance => 0.2 0.1 15.8 22.7 2.0 0.0 2.6 2.7 8.1 0.1 0.8 0.0 3.0 0.6 0.1 4
D-7

State-by-State Contributions to Annual PM2.5 (μg/m3) Nonattainment Recep

Part 1a. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Alabama through Michigan 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC M

10730023 Alabama Jefferson 3.48 0.03 0.00 0.01 0.15 0.61 0.18 0.28 0.04 0.02 0.28 0.11 0.00 0.02 010732003 Alabama Jefferson 2.62 0.02 0.00 0.00 0.14 0.63 0.18 0.29 0.04 0.01 0.29 0.11 0.00 0.01 0130210007 Georgia Bibb 0.42 0.02 0.00 0.01 0.29 1.63 0.16 0.23 0.04 0.01 0.22 0.08 0.00 0.04 0130630091 Georgia Clayton 0.46 0.02 0.00 0.01 0.18 2.02 0.19 0.28 0.04 0.02 0.29 0.07 0.00 0.04 0131210039 Georgia Fulton 0.40 0.01 0.00 0.00 0.14 2.30 0.18 0.27 0.03 0.01 0.28 0.06 0.00 0.03 0170310052 Illinois Cook 0.03 0.02 0.00 0.00 0.00 0.04 2.00 1.00 0.31 0.05 0.22 0.02 0.00 0.00 0171191007 Illinois Madison 0.08 0.09 0.00 0.00 0.01 0.08 1.82 0.79 0.28 0.09 0.35 0.08 0.00 0.00 0171630010 Illinois 

Saint Clair 0.08 0.09 0.00 0.00 0.02 0.08 1.74 0.77 0.27 0.09 0.35 0.08 0.00 0.01 0

180190006 Indiana Clark 0.18 0.04 0.00 0.00 0.04 0.18 0.66 1.92 0.12 0.03 1.68 0.06 0.00 0.02 0180372001 Indiana Dubois 0.18 0.06 0.00 0.00 0.04 0.18 1.01 2.66 0.18 0.04 1.52 0.07 0.00 0.02 0180970078 Indiana Marion 0.10 0.04 0.00 0.00 0.01 0.10 0.76 3.49 0.14 0.03 0.78 0.04 0.00 0.02 0180970081 Indiana Marion 0.10 0.04 0.00 0.00 0.02 0.10 0.77 3.49 0.14 0.03 0.78 0.04 0.00 0.02 0180970083 Indiana Marion 0.10 0.04 0.00 0.00 0.02 0.10 0.76 3.49 0.14 0.03 0.78 0.04 0.00 0.02 0211110043 Kentucky Jefferson 0.17 0.04 0.00 0.00 0.04 0.17 0.61 2.09 0.12 0.03 1.85 0.06 0.00 0.02 0261630015 Michigan Wayne 0.05 0.02 0.00 0.00 0.01 0.06 0.45 0.67 0.10 0.02 0.28 0.01 0.00 0.02 0261630033 Michigan Wayne 0.04 0.01 0.00 0.00 0.00 0.06 0.47 0.70 0.11 0.01 0.29 0.01 0.00 0.02 0
D-8

State-by-State Contributions to Annual PM2.5 (μg/m3) Nonattainment Recep

Part 1b. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Ohio through West Virginia 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

390170016 Ohio Butler 0.13 0.03 0.00 0.00 0.02 0.13 0.58 1.36 0.11 0.02 0.99 0.03 0.00 0.03 390350038 Ohio Cuyahoga 0.06 0.02 0.00 0.01 0.01 0.08 0.42 0.64 0.09 0.02 0.33 0.02 0.00 0.05 390350045 Ohio Cuyahoga 0.06 0.02 0.00 0.01 0.02 0.09 0.42 0.64 0.10 0.02 0.34 0.02 0.00 0.05 390350060 Ohio Cuyahoga 0.05 0.01 0.00 0.00 0.01 0.08 0.41 0.63 0.09 0.01 0.33 0.01 0.00 0.05 390610014 Ohio Hamilton 0.13 0.04 0.00 0.01 0.03 0.14 0.57 1.29 0.11 0.03 1.00 0.04 0.00 0.04 390610042 Ohio Hamilton 0.13 0.03 0.00 0.00 0.02 0.13 0.55 1.33 0.10 0.02 1.15 0.03 0.00 0.03 390610043 Ohio Hamilton 0.12 0.03 0.00 0.00 0.02 0.13 0.56 1.27 0.11 0.02 0.94 0.03 0.00 0.03 390617001 Ohio Hamilton 0.13 0.04 0.00 0.01 0.03 0.14 0.57 1.29 0.11 0.03 1.00 0.04 0.00 0.04 390618001 Ohio Hamilton 0.12 0.03 0.00 0.00 0.02 0.13 0.56 1.28 0.10 0.02 0.99 0.03 0.00 0.03 420030064 Pennsylvania Allegheny 0.04 0.01 0.00 0.01 0.01 0.07 0.26 0.41 0.05 0.01 0.27 0.01 0.00 0.12 420031301 Pennsylvania Allegheny 0.05 0.01 0.00 0.01 0.01 0.07 0.28 0.43 0.06 0.01 0.29 0.01 0.00 0.12 420070014 Pennsylvania Beaver 0.05 0.01 0.00 0.01 0.01 0.08 0.30 0.45 0.07 0.01 0.29 0.01 0.00 0.09 420710007 Pennsylvania Lancaster 0.03 0.01 0.04 0.20 0.01 0.07 0.22 0.28 0.05 0.01 0.16 0.01 0.01 0.63 421330008 Pennsylvania York 0.03 0.01 0.03 0.16 0.01 0.07 0.23 0.30 0.05 0.01 0.18 0.01 0.01 0.62 540110006 

West Virginia Cabell 0.12 0.02 0.00 0.00 0.04 0.19 0.35 0.64 0.07 0.01 0.79 0.03 0.00 0.05 

540391005 

West Virginia Kanawha 0.12 0.02 0.00 0.01 0.03 0.18 0.33 0.59 0.07 0.01 0.61 0.03 0.00 0.08 

Largest Contribution to Downwind Nonattainment => 0.46 0.09 0.04 0.20 0.29 0.63 1.01 2.09 0.31 0.09 1.68 0.11 0.01 0.63 
D-9

State-by-State Contributions to Annual PM2.5 (μg/m3) Nonattainment Recep

Part 1c. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Alabama through Michigan 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX VT 

10730023 Alabama Jefferson 0.02 0.00 0.01 0.02 0.08 0.01 0.24 0.02 0.14 0.00 0.11 0.00 0.33 0.06 0.010732003 Alabama Jefferson 0.01 0.00 0.00 0.01 0.08 0.00 0.25 0.01 0.14 0.00 0.10 0.00 0.34 0.05 0.0130210007 Georgia Bibb 0.01 0.00 0.01 0.04 0.17 0.00 0.27 0.02 0.26 0.00 0.26 0.00 0.27 0.05 0.0130630091 Georgia Clayton 0.02 0.00 0.01 0.04 0.19 0.01 0.30 0.02 0.23 0.00 0.25 0.00 0.36 0.05 0.0131210039 Georgia Fulton 0.01 0.00 0.01 0.03 0.19 0.00 0.29 0.01 0.22 0.00 0.26 0.00 0.36 0.04 0.0170310052 Illinois Cook 0.06 0.00 0.00 0.02 0.01 0.05 0.37 0.04 0.17 0.00 0.01 0.02 0.12 0.04 0.0171191007 Illinois Madison 0.08 0.00 0.00 0.02 0.02 0.04 0.40 0.08 0.15 0.00 0.02 0.02 0.25 0.13 0.0171630010 Illinois 

Saint Clair 0.08 0.00 0.00 0.02 0.02 0.04 0.39 0.07 0.15 0.00 0.02 0.02 0.25 0.12 0.0

180190006 Indiana Clark 0.03 0.00 0.00 0.06 0.05 0.02 1.08 0.03 0.39 0.00 0.05 0.01 0.67 0.06 0.0180372001 Indiana Dubois 0.05 0.00 0.00 0.05 0.05 0.03 0.94 0.04 0.33 0.00 0.05 0.01 0.68 0.08 0.0180970078 Indiana Marion 0.03 0.00 0.00 0.07 0.03 0.03 1.02 0.03 0.32 0.00 0.02 0.01 0.41 0.05 0.0180970081 Indiana Marion 0.04 0.00 0.00 0.07 0.03 0.03 1.02 0.03 0.32 0.00 0.02 0.01 0.41 0.05 0.0180970083 Indiana Marion 0.03 0.00 0.00 0.07 0.03 0.03 1.02 0.03 0.32 0.00 0.02 0.01 0.41 0.05 0.0211110043 Kentucky Jefferson 0.03 0.00 0.01 0.05 0.05 0.02 0.98 0.03 0.35 0.00 0.05 0.01 0.63 0.06 0.0261630015 Michigan Wayne 0.03 0.00 0.00 0.13 0.02 0.02 1.00 0.02 0.39 0.00 0.01 0.00 0.15 0.03 0.0261630033 Michigan Wayne 0.02 0.00 0.00 0.13 0.01 0.02 1.04 0.02 0.40 0.00 0.01 0.00 0.15 0.03 0.0
D-10

State-by-State Contributions to Annual PM2.5 (μg/m3) Nonattainment Recep

Part 1d. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Ohio through West Virginia 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX V

390170016 Ohio Butler 0.03 0.00 0.00 0.10 0.04 0.02 2.16 0.02 0.52 0.00 0.03 0.00 0.50 0.05 0390350038 Ohio Cuyahoga 0.03 0.00 0.01 0.23 0.03 0.02 2.76 0.02 0.79 0.00 0.01 0.01 0.18 0.03 0390350045 Ohio Cuyahoga 0.03 0.00 0.01 0.23 0.04 0.02 2.77 0.02 0.80 0.00 0.02 0.01 0.19 0.03 0390350060 Ohio Cuyahoga 0.02 0.00 0.01 0.22 0.03 0.02 2.76 0.02 0.79 0.00 0.01 0.00 0.18 0.03 0390610014 Ohio Hamilton 0.03 0.00 0.01 0.10 0.05 0.03 2.51 0.03 0.54 0.00 0.03 0.01 0.51 0.05 0390610042 Ohio Hamilton 0.03 0.00 0.00 0.09 0.04 0.02 2.43 0.02 0.51 0.00 0.03 0.00 0.50 0.04 0390610043 Ohio Hamilton 0.03 0.00 0.00 0.10 0.04 0.02 2.27 0.02 0.53 0.00 0.03 0.00 0.48 0.05 0390617001 Ohio Hamilton 0.03 0.00 0.01 0.10 0.05 0.03 2.50 0.03 0.54 0.00 0.03 0.01 0.50 0.05 0390618001 Ohio Hamilton 0.02 0.00 0.00 0.09 0.04 0.02 2.49 0.02 0.53 0.00 0.03 0.00 0.49 0.04 0420030064 Pennsylvania Allegheny 0.01 0.00 0.02 0.19 0.05 0.01 1.26 0.01 2.35 0.00 0.02 0.00 0.17 0.02 0420031301 Pennsylvania Allegheny 0.01 0.00 0.02 0.20 0.05 0.01 1.36 0.01 2.33 0.00 0.02 0.00 0.17 0.02 0420070014 Pennsylvania Beaver 0.02 0.00 0.02 0.21 0.05 0.01 1.49 0.01 1.61 0.00 0.02 0.00 0.17 0.02 0420710007 Pennsylvania Lancaster 0.02 0.01 0.34 0.49 0.12 0.01 0.59 0.01 3.17 0.01 0.04 0.00 0.10 0.02 0421330008 Pennsylvania York 0.02 0.01 0.28 0.45 0.12 0.01 0.64 0.01 2.96 0.00 0.04 0.00 0.11 0.02 0540110006 

West Virginia Cabell 0.02 0.00 0.01 0.10 0.09 0.01 1.40 0.02 0.69 0.00 0.05 0.00 0.40 0.04 0

540391005 

West Virginia Kanawha 0.02 0.00 0.02 0.11 0.12 0.01 1.38 0.02 0.83 0.00 0.06 0.00 0.38 0.04 0

Largest Contribution to Downwind Nonattainment => 0.08 0.01 0.34 0.49 0.19 0.05 1.49 0.08 0.83 0.01 0.26 0.02 0.68 0.13 0
D-11

State-by-State Contributions to Annual PM2.5 (μg/m3) Maintenance Recept

Part 2a. 

Source States: Alabama through Missouri 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/D

170313301 Illinois Cook 0.03 0.02 0.00 0.00 0.00 0.04 1.99 1.07 0.25 0.04 0.22 0.02 0.00 0.0170316005 Illinois Cook 0.03 0.03 0.00 0.00 0.00 0.05 2.14 1.02 0.30 0.05 0.22 0.02 0.00 0.0211110044 Kentucky Jefferson 0.18 0.04 0.00 0.00 0.04 0.18 0.63 1.78 0.12 0.02 1.88 0.05 0.00 0.0360610056 New York New York 0.01 0.00 0.09 0.07 0.00 0.04 0.13 0.16 0.03 0.00 0.09 0.00 0.02 0.1390350027 Ohio Cuyahoga 0.05 0.01 0.00 0.00 0.01 0.08 0.41 0.63 0.09 0.01 0.33 0.01 0.00 0.0390350065 Ohio Cuyahoga 0.06 0.02 0.00 0.01 0.01 0.08 0.41 0.63 0.09 0.01 0.33 0.01 0.00 0.0390610040 Ohio Hamilton 0.14 0.04 0.01 0.01 0.03 0.14 0.58 1.31 0.12 0.03 1.01 0.04 0.01 0.0390811001 Ohio Jefferson 0.06 0.02 0.00 0.01 0.02 0.10 0.33 0.50 0.07 0.01 0.34 0.02 0.00 0.1391130032 Ohio Montgomery 0.10 0.02 0.00 0.00 0.02 0.11 0.57 1.21 0.11 0.02 0.76 0.02 0.00 0.0391510017 Ohio Stark 0.06 0.02 0.00 0.01 0.02 0.09 0.41 0.66 0.09 0.02 0.40 0.02 0.00 0.0420110011 Pennsylvania Berks 0.02 0.00 0.03 0.14 0.01 0.06 0.20 0.25 0.05 0.01 0.14 0.00 0.01 0.3482011035 Texas Harris 0.11 0.04 0.00 0.00 0.07 0.09 0.16 0.16 0.04 0.02 0.13 0.34 0.00 0.0540030003 

West Virginia Berkeley 0.04 0.01 0.01 0.05 0.01 0.08 0.23 0.34 0.05 0.01 0.22 0.01 0.00 0.5

540090005 

West Virginia Brooke 0.06 0.01 0.00 0.01 0.02 0.09 0.32 0.49 0.07 0.01 0.33 0.02 0.00 0.0

540291004 

West Virginia Hancock 0.07 0.02 0.01 0.02 0.02 0.10 0.33 0.50 0.08 0.02 0.34 0.03 0.01 0.1

540490006 

West Virginia Marion 0.06 0.01 0.00 0.01 0.02 0.10 0.28 0.44 0.06 0.01 0.34 0.02 0.00 0.1

Largest Contribution to Downwind Maintenance => 0.18 0.04 0.09 0.14 0.07 0.18 0.63 1.78 0.30 0.05 1.01 0.34 0.02 0.5
D-12

State-by-State Contributions to Annual PM2.5 (μg/m3) Maintenance Recept

Part 2b. 

Source States: Nebraska through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

170313301 Illinois Cook 0.05 0.00 0.00 0.02 0.01 0.03 0.36 0.03 0.17 0.00 0.01 0.01 0.12 0.04 170316005 Illinois Cook 0.06 0.00 0.00 0.03 0.01 0.05 0.37 0.04 0.17 0.00 0.01 0.02 0.13 0.05 211110044 Kentucky Jefferson 0.03 0.00 0.00 0.05 0.05 0.02 1.03 0.03 0.37 0.00 0.04 0.00 0.64 0.06 360610056 New York New York 0.01 0.02 0.68 2.72 0.10 0.01 0.30 0.00 0.74 0.01 0.03 0.00 0.06 0.01 390350027 Ohio Cuyahoga 0.02 0.00 0.01 0.22 0.03 0.02 2.75 0.02 0.78 0.00 0.01 0.00 0.18 0.02 390350065 Ohio Cuyahoga 0.02 0.00 0.01 0.23 0.03 0.02 2.75 0.02 0.79 0.00 0.01 0.01 0.18 0.03 390610040 Ohio Hamilton 0.04 0.00 0.01 0.10 0.05 0.03 2.53 0.03 0.55 0.00 0.04 0.01 0.51 0.05 390811001 Ohio Jefferson 0.02 0.00 0.02 0.20 0.06 0.02 2.07 0.02 1.30 0.00 0.03 0.01 0.21 0.03 391130032 Ohio Montgomery 0.03 0.00 0.00 0.11 0.03 0.02 2.05 0.02 0.50 0.00 0.02 0.00 0.41 0.04 391510017 Ohio Stark 0.03 0.00 0.01 0.21 0.04 0.02 2.36 0.02 0.94 0.00 0.02 0.00 0.23 0.03 420110011 Pennsylvania Berks 0.01 0.01 0.30 0.47 0.10 0.01 0.49 0.01 2.86 0.00 0.03 0.00 0.09 0.01 482011035 Texas Harris 0.02 0.00 0.00 0.01 0.02 0.01 0.08 0.05 0.05 0.00 0.02 0.00 0.14 2.78 540030003 

West Virginia Berkeley 0.01 0.00 0.11 0.27 0.11 0.01 0.77 0.01 1.60 0.00 0.04 0.00 0.14 0.02 

540090005 

West Virginia Brooke 0.02 0.00 0.02 0.20 0.05 0.01 2.03 0.01 1.26 0.00 0.03 0.00 0.20 0.03 

540291004 

West Virginia Hancock 0.03 0.01 0.03 0.21 0.06 0.02 1.80 0.02 1.33 0.00 0.03 0.01 0.21 0.03 

540490006 

West Virginia Marion 0.02 0.00 0.02 0.15 0.08 0.01 1.23 0.01 1.34 0.00 0.04 0.00 0.23 0.03 

Largest Contribution to Downwind Maintenance => 0.06 0.02 0.68 0.47 0.11 0.05 2.03 0.05 1.60 0.01 0.04 0.02 0.64 0.06 
D-13

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1a. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Alabama through Illinois 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

10730023 Alabama Jefferson 7.54 0.05 0.00 0.01 0.06 0.95 0.49 0.83 0.05 0.02 0.87 0.23 0.00 0.06 10732003 Alabama Jefferson 4.62 0.02 0.01 0.01 0.07 0.76 0.40 0.91 0.04 0.02 0.79 0.08 0.01 0.04 90091123 Connecticut 

New Haven 0.09 0.04 2.08 0.30 0.03 0.20 0.47 0.64 0.08 0.03 0.55 0.02 0.19 0.63 

170310052 Illinois Cook 0.06 0.10 0.00 0.01 0.01 0.10 7.69 3.32 0.93 0.26 0.68 0.04 0.00 0.04 170310057 Illinois Cook 0.05 0.05 0.01 0.01 0.01 0.08 8.75 3.78 1.00 0.33 0.42 0.03 0.01 0.06 170310076 Illinois Cook 0.03 0.04 0.01 0.01 0.01 0.04 6.58 4.42 0.44 0.16 0.65 0.02 0.01 0.09 170311016 Illinois Cook 0.03 0.07 0.00 0.00 0.00 0.06 6.38 3.92 0.56 0.11 0.75 0.02 0.00 0.04 170312001 Illinois Cook 0.04 0.05 0.01 0.01 0.01 0.06 4.31 6.33 0.41 0.07 0.72 0.02 0.01 0.08 170313103 Illinois Cook 0.04 0.07 0.00 0.00 0.00 0.05 9.16 3.37 0.90 0.30 0.49 0.02 0.00 0.02 170313301 Illinois Cook 0.04 0.05 0.02 0.02 0.02 0.04 7.34 4.44 0.61 0.26 0.52 0.03 0.02 0.09 170316005 Illinois Cook 0.04 0.06 0.00 0.00 0.00 0.08 7.85 3.68 0.82 0.29 0.52 0.02 0.00 0.03 171190023 Illinois Madison 0.20 0.08 0.00 0.00 0.00 0.25 7.07 3.43 0.30 0.03 1.83 0.02 0.00 0.01 171191007 Illinois Madison 0.16 0.20 0.01 0.01 0.02 0.16 5.70 2.64 0.43 0.25 1.34 0.06 0.01 0.05 171192009 Illinois Madison 0.15 0.18 0.01 0.02 0.02 0.19 6.69 3.18 0.34 0.12 1.69 0.06 0.01 0.06 171193007 Illinois Madison 0.14 0.16 0.00 0.01 0.01 0.21 6.82 3.64 0.23 0.04 1.98 0.03 0.00 0.03 
D-14

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1b. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Indiana through Maryland 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

180190006 Indiana Clark 0.12 0.06 0.00 0.01 0.01 0.07 2.60 6.30 0.19 0.03 6.19 0.02 0.00 0.03 180372001 Indiana Dubois 0.17 0.06 0.00 0.01 0.01 0.17 2.62 8.79 0.28 0.08 5.97 0.04 0.00 0.03 180830004 Indiana Knox 0.09 0.05 0.00 0.00 0.01 0.09 2.09 8.11 0.26 0.08 4.51 0.01 0.00 0.02 180890022 Indiana Lake 0.03 0.03 0.00 0.00 0.00 0.03 4.16 6.88 0.64 0.24 0.30 0.01 0.00 0.01 180890026 Indiana Lake 0.04 0.02 0.00 0.00 0.00 0.04 3.59 5.56 0.45 0.18 0.75 0.01 0.00 0.06 180970042 Indiana Marion 0.13 0.05 0.00 0.00 0.00 0.12 2.16 10.91 0.15 0.01 5.48 0.01 0.00 0.03 180970043 Indiana Marion 0.18 0.08 0.01 0.02 0.02 0.19 1.92 10.83 0.16 0.03 4.99 0.04 0.01 0.08 180970066 Indiana Marion 0.11 0.04 0.00 0.00 0.00 0.09 2.08 11.37 0.14 0.01 5.06 0.01 0.00 0.04 180970078 Indiana Marion 0.18 0.08 0.01 0.02 0.02 0.20 1.91 10.75 0.16 0.03 4.97 0.04 0.01 0.08 180970079 Indiana Marion 0.11 0.04 0.00 0.00 0.00 0.08 2.13 9.85 0.15 0.01 5.20 0.01 0.00 0.04 180970081 Indiana Marion 0.21 0.08 0.01 0.02 0.02 0.26 1.64 9.91 0.14 0.03 4.76 0.04 0.01 0.08 180970083 Indiana Marion 0.14 0.04 0.00 0.00 0.00 0.15 1.98 11.35 0.13 0.01 5.21 0.01 0.00 0.04 181570008 Indiana Tippecanoe 0.24 0.11 0.02 0.02 0.02 0.29 1.56 5.91 0.12 0.03 3.11 0.04 0.01 0.16 191630019 Iowa Scott 0.19 0.11 0.00 0.00 0.00 0.23 3.91 3.49 2.25 0.08 2.29 0.02 0.00 0.06 210590005 Kentucky Daviess 0.17 0.07 0.00 0.00 0.01 0.09 2.96 9.91 0.13 0.02 10.03 0.03 0.00 0.01 211110043 Kentucky Jefferson 0.18 0.07 0.02 0.03 0.03 0.18 2.30 7.78 0.14 0.04 6.89 0.06 0.02 0.08 211110044 Kentucky Jefferson 0.13 0.06 0.00 0.01 0.01 0.10 2.42 6.66 0.12 0.02 7.35 0.04 0.00 0.05 211110048 Kentucky Jefferson 0.13 0.07 0.01 0.02 0.02 0.10 2.18 5.98 0.12 0.02 6.59 0.05 0.01 0.06 245100040 Maryland 

Baltimore City 0.15 0.02 0.07 0.20 0.08 0.40 0.25 0.33 0.07 0.02 0.30 0.05 0.03 6.65 

245100049 Maryland 

Baltimore City 0.14 0.02 0.08 0.21 0.07 0.38 0.23 0.31 0.06 0.01 0.29 0.04 0.03 6.63 
D-15

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1c. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Michigan through New York 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

261150005 Michigan Monroe 0.36 0.09 0.01 0.02 0.03 0.31 1.30 3.53 0.14 0.04 2.46 0.11 0.00 0.17 261250001 Michigan Oakland 0.21 0.03 0.00 0.01 0.00 0.18 1.51 3.21 0.16 0.03 1.62 0.10 0.00 0.12 261470005 Michigan St. Clair 0.13 0.02 0.00 0.01 0.00 0.11 1.10 1.91 0.12 0.02 0.96 0.08 0.00 0.13 261610008 Michigan Washtenaw 0.31 0.05 0.00 0.02 0.01 0.26 1.48 3.30 0.16 0.04 1.71 0.14 0.00 0.12 261630015 Michigan Wayne 0.35 0.06 0.00 0.01 0.06 0.29 1.31 3.03 0.12 0.03 1.95 0.16 0.00 0.08 261630016 Michigan Wayne 0.04 0.01 0.01 0.02 0.01 0.05 1.73 2.99 0.21 0.04 0.67 0.01 0.01 0.11 261630019 Michigan Wayne 0.03 0.01 0.00 0.01 0.00 0.04 1.54 2.82 0.16 0.02 0.71 0.00 0.00 0.08 261630033 Michigan Wayne 0.27 0.05 0.01 0.02 0.05 0.22 1.69 3.24 0.19 0.05 1.49 0.12 0.01 0.11 261630036 Michigan Wayne 0.31 0.09 0.01 0.03 0.07 0.26 1.71 3.01 0.21 0.06 1.52 0.17 0.01 0.12 290990012 Missouri Jefferson 0.11 0.08 0.00 0.00 0.00 0.08 6.47 3.43 0.43 0.04 1.66 0.03 0.00 0.01 291831002 Missouri 

Saint Charles 0.13 0.14 0.01 0.01 0.01 0.19 6.10 3.67 0.32 0.04 2.01 0.03 0.01 0.04 

295100007 Missouri 

St. Louis City 0.10 0.07 0.00 0.00 0.00 0.07 6.83 3.29 0.40 0.03 1.60 0.03 0.00 0.00 

295100087 Missouri 

St. Louis City 0.22 0.11 0.00 0.00 0.01 0.25 6.42 3.20 0.34 0.04 1.73 0.03 0.00 0.03 

340171003 

New Jersey Hudson 0.07 0.03 0.08 0.34 0.02 0.25 0.25 0.38 0.04 0.02 0.40 0.02 0.01 0.76 

340172002 

New Jersey Hudson 0.09 0.02 0.38 0.34 0.04 0.26 0.20 0.34 0.04 0.02 0.34 0.03 0.02 0.71 

340390004 

New Jersey Union 0.15 0.03 0.25 0.36 0.05 0.37 0.37 0.58 0.07 0.01 0.46 0.05 0.06 0.57 

360050080 

New York Bronx 0.09 0.03 0.19 0.32 0.03 0.27 0.28 0.44 0.05 0.02 0.41 0.03 0.01 0.64 

360610056 

New York New York 0.12 0.05 0.41 0.33 0.06 0.32 0.28 0.40 0.08 0.03 0.32 0.06 0.04 0.68 

360610128 

New York New York 0.11 0.04 0.35 0.29 0.03 0.22 0.51 0.81 0.07 0.02 0.58 0.04 0.08 0.60 
D-16

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1d. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Ohio 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

390170003 Ohio Butler 0.26 0.04 0.00 0.01 0.00 0.33 1.84 6.09 0.09 0.00 6.53 0.03 0.00 0.08 390170016 Ohio Butler 0.29 0.06 0.01 0.03 0.02 0.35 1.59 5.22 0.15 0.02 5.05 0.04 0.01 0.16 390170017 Ohio Butler 0.22 0.02 0.00 0.00 0.00 0.27 1.52 5.02 0.07 0.00 5.38 0.02 0.00 0.06 390171004 Ohio Butler 0.28 0.03 0.00 0.01 0.00 0.35 1.36 4.82 0.06 0.00 5.25 0.03 0.00 0.06 390350038 Ohio Cuyahoga 0.16 0.04 0.01 0.02 0.04 0.19 0.70 1.69 0.09 0.02 1.23 0.03 0.01 0.30 390350045 Ohio Cuyahoga 0.12 0.02 0.01 0.02 0.01 0.14 0.56 1.39 0.09 0.02 0.91 0.02 0.01 0.25 390350060 Ohio Cuyahoga 0.09 0.00 0.00 0.01 0.00 0.10 0.59 1.32 0.10 0.01 0.73 0.01 0.00 0.20 390350065 Ohio Cuyahoga 0.11 0.04 0.01 0.02 0.04 0.13 0.71 1.50 0.11 0.02 0.89 0.03 0.01 0.22 390490024 Ohio Franklin 0.15 0.07 0.01 0.02 0.01 0.21 0.90 2.74 0.13 0.03 1.92 0.08 0.01 0.14 390490025 Ohio Franklin 0.16 0.07 0.01 0.03 0.02 0.20 0.99 2.65 0.16 0.05 1.84 0.08 0.01 0.18 390610006 Ohio Hamilton 0.38 0.07 0.00 0.02 0.02 0.38 1.53 5.12 0.13 0.02 5.12 0.11 0.00 0.11 390610014 Ohio Hamilton 0.48 0.06 0.00 0.02 0.03 0.54 0.95 3.68 0.07 0.01 4.28 0.13 0.00 0.12 390610040 Ohio Hamilton 0.19 0.04 0.00 0.00 0.00 0.13 1.57 4.27 0.13 0.00 4.40 0.03 0.00 0.08 390610042 Ohio Hamilton 0.23 0.05 0.00 0.00 0.01 0.19 1.29 3.67 0.12 0.01 4.29 0.06 0.00 0.05 390610043 Ohio Hamilton 0.23 0.09 0.01 0.03 0.03 0.17 1.91 5.54 0.19 0.03 5.19 0.07 0.01 0.11 390617001 Ohio Hamilton 0.31 0.07 0.01 0.02 0.02 0.29 1.42 4.16 0.14 0.02 4.44 0.09 0.01 0.13 390618001 Ohio Hamilton 0.36 0.06 0.00 0.01 0.03 0.38 1.13 3.58 0.12 0.02 3.68 0.10 0.00 0.11 390811001 Ohio Jefferson 0.04 0.02 0.00 0.01 0.00 0.09 0.63 1.37 0.08 0.02 0.85 0.00 0.00 0.08 391130032 Ohio Montgomery 0.32 0.04 0.00 0.02 0.01 0.39 1.30 4.38 0.08 0.01 4.99 0.05 0.00 0.16 391530017 Ohio Summit 0.10 0.06 0.00 0.01 0.00 0.14 1.04 1.91 0.14 0.02 0.90 0.02 0.00 0.19 
D-17

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1e. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Pennsylvania through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/D

420030008 Pennsylvania Allegheny 0.01 0.01 0.00 0.01 0.00 0.02 0.33 0.70 0.03 0.00 0.47 0.00 0.00 0.1420030064 Pennsylvania Allegheny 0.05 0.02 0.00 0.01 0.00 0.06 0.51 0.98 0.07 0.02 0.68 0.01 0.00 0.0420030093 Pennsylvania Allegheny 0.17 0.06 0.01 0.02 0.02 0.15 0.60 1.22 0.07 0.02 1.10 0.09 0.00 0.1420030116 Pennsylvania Allegheny 0.03 0.04 0.00 0.02 0.00 0.05 0.62 1.26 0.07 0.02 0.99 0.01 0.00 0.1420031008 Pennsylvania Allegheny 0.14 0.05 0.00 0.01 0.01 0.15 0.65 1.43 0.07 0.02 1.17 0.06 0.00 0.1420031301 Pennsylvania Allegheny 0.06 0.04 0.01 0.03 0.02 0.07 0.53 1.06 0.07 0.03 0.82 0.02 0.01 0.1420070014 Pennsylvania Beaver 0.08 0.03 0.00 0.01 0.00 0.08 0.64 1.34 0.09 0.01 0.81 0.01 0.00 0.1420110011 Pennsylvania Berks 0.13 0.03 0.17 0.33 0.06 0.28 0.45 0.57 0.12 0.03 0.43 0.05 0.09 1.8420210011 Pennsylvania Cambria 0.03 0.04 0.01 0.01 0.01 0.02 0.62 1.55 0.07 0.02 0.84 0.02 0.01 0.1420430401 Pennsylvania Dauphin 0.10 0.02 0.17 0.50 0.05 0.24 0.25 0.39 0.06 0.02 0.29 0.04 0.08 2.1420710007 Pennsylvania Lancaster 0.13 0.03 0.19 0.31 0.07 0.27 0.22 0.26 0.08 0.03 0.20 0.06 0.11 2.6421330008 Pennsylvania York 0.16 0.02 0.16 0.34 0.05 0.35 0.34 0.57 0.07 0.01 0.49 0.06 0.08 2.0471251009 Tennessee Montgomery 0.27 0.06 0.00 0.02 0.02 0.24 2.73 3.32 0.24 0.03 3.49 0.03 0.00 0.1540090011 

West Virginia Brooke 0.04 0.03 0.02 0.03 0.02 0.06 0.89 1.37 0.20 0.05 0.42 0.02 0.02 0.2

550790010 Wisconsin Milwaukee 0.01 0.01 0.00 0.00 0.00 0.02 7.28 2.70 1.87 0.77 0.62 0.00 0.00 0.0550790026 Wisconsin Milwaukee 0.04 0.03 0.01 0.01 0.01 0.06 5.24 2.24 1.57 0.38 0.56 0.01 0.01 0.0550790043 Wisconsin Milwaukee 0.04 0.02 0.00 0.00 0.00 0.10 5.53 3.92 0.94 0.25 1.02 0.01 0.00 0.0550790099 Wisconsin Milwaukee 0.02 0.02 0.00 0.00 0.00 0.05 6.17 2.82 1.63 0.45 0.73 0.00 0.00 0.0

Largest Contribution to Downwind Nonattainment => 0.48 0.20 0.41 0.50 0.08 0.95 7.28 9.91 1.87 0.77 6.53 0.23 0.19 2.6
D-18

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1f. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Alabama through Illinois 

Source States 

Receptor 

Monitor ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

10730023 Alabama Jefferson 0.02 0.00 0.01 0.06 0.16 0.01 1.00 0.03 0.60 0.00 0.13 0.00 1.03 0.110732003 Alabama Jefferson 0.02 0.01 0.01 0.03 0.09 0.01 0.79 0.02 0.35 0.01 0.12 0.01 0.92 0.04 90091123 Connecticut 

New Haven 0.03 0.21 1.24 3.47 0.30 0.01 1.20 0.05 2.57 0.05 0.12 0.00 0.35 0.0

170310052 Illinois Cook 0.20 0.00 0.01 0.21 0.04 0.07 1.38 0.16 0.71 0.00 0.03 0.05 0.26 0.1170310057 Illinois Cook 0.25 0.01 0.01 0.20 0.03 0.06 1.17 0.16 0.78 0.01 0.03 0.05 0.16 0.1170310076 Illinois Cook 0.13 0.01 0.01 0.19 0.03 0.03 1.95 0.08 1.39 0.01 0.02 0.02 0.21 0.0170311016 Illinois Cook 0.14 0.00 0.00 0.24 0.01 0.02 1.74 0.07 1.16 0.00 0.00 0.01 0.30 0.0170312001 Illinois Cook 0.10 0.01 0.01 0.14 0.03 0.03 1.82 0.04 1.20 0.01 0.02 0.02 0.24 0.0170313103 Illinois Cook 0.24 0.00 0.00 0.15 0.02 0.05 0.95 0.11 0.43 0.00 0.01 0.03 0.21 0.1170313301 Illinois Cook 0.19 0.02 0.02 0.18 0.03 0.04 1.45 0.12 1.01 0.02 0.02 0.04 0.18 0.0170316005 Illinois Cook 0.21 0.00 0.00 0.16 0.03 0.04 1.14 0.13 0.63 0.00 0.02 0.03 0.20 0.1171190023 Illinois Madison 0.02 0.00 0.00 0.01 0.02 0.00 1.78 0.08 0.35 0.00 0.02 0.00 1.15 0.1171191007 Illinois Madison 0.05 0.01 0.01 0.12 0.04 0.03 2.01 0.08 0.93 0.01 0.03 0.02 1.01 0.2171192009 Illinois Madison 0.10 0.01 0.02 0.09 0.04 0.03 1.72 0.12 0.70 0.01 0.04 0.03 1.03 0.1171193007 Illinois Madison 0.03 0.00 0.01 0.04 0.03 0.01 1.76 0.11 0.59 0.00 0.03 0.01 1.12 0.14 
D-19

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1g. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Indiana through Maryland 

Source States 

Receptor 

Monitor ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

180190006 Indiana Clark 0.03 0.00 0.01 0.09 0.03 0.01 1.98 0.06 0.72 0.00 0.02 0.01 2.04 0.08 180372001 Indiana Dubois 0.05 0.00 0.01 0.09 0.03 0.03 2.73 0.06 0.58 0.00 0.03 0.01 1.86 0.07 180830004 Indiana Knox 0.05 0.00 0.00 0.14 0.02 0.03 3.68 0.05 0.46 0.00 0.02 0.02 1.12 0.04 180890022 Indiana Lake 0.18 0.00 0.00 0.11 0.01 0.03 0.51 0.11 0.22 0.00 0.01 0.02 0.07 0.04 180890026 Indiana Lake 0.14 0.00 0.00 0.15 0.02 0.03 1.72 0.06 0.98 0.00 0.01 0.02 0.24 0.04 180970042 Indiana Marion 0.01 0.00 0.00 0.06 0.04 0.00 3.71 0.01 0.74 0.00 0.03 0.00 1.96 0.0180970043 Indiana Marion 0.03 0.01 0.02 0.09 0.07 0.02 3.51 0.03 0.82 0.01 0.06 0.01 2.29 0.04 180970066 Indiana Marion 0.01 0.00 0.00 0.06 0.04 0.00 3.74 0.01 0.76 0.00 0.03 0.00 1.81 0.0180970078 Indiana Marion 0.03 0.01 0.02 0.10 0.07 0.02 3.48 0.03 0.82 0.01 0.06 0.01 2.30 0.04 180970079 Indiana Marion 0.01 0.00 0.00 0.07 0.04 0.00 4.13 0.01 0.84 0.00 0.03 0.00 1.81 0.0180970081 Indiana Marion 0.03 0.01 0.02 0.09 0.06 0.02 3.11 0.02 0.84 0.01 0.05 0.01 2.75 0.04 180970083 Indiana Marion 0.01 0.00 0.00 0.06 0.03 0.00 3.65 0.01 0.82 0.00 0.02 0.00 2.36 0.0181570008 Indiana Tippecanoe 0.02 0.01 0.03 0.20 0.08 0.02 3.64 0.03 1.79 0.01 0.05 0.01 1.96 0.04 191630019 Iowa Scott 0.04 0.00 0.00 0.11 0.06 0.02 3.06 0.14 2.10 0.00 0.03 0.00 1.16 0.07 210590005 Kentucky Daviess 0.01 0.00 0.00 0.02 0.02 0.00 1.38 0.03 0.17 0.00 0.02 0.00 1.76 0.05 211110043 Kentucky Jefferson 0.03 0.02 0.03 0.08 0.07 0.03 1.51 0.04 0.45 0.02 0.06 0.02 1.57 0.06 211110044 Kentucky Jefferson 0.01 0.00 0.02 0.03 0.04 0.01 1.21 0.03 0.45 0.00 0.03 0.00 1.65 0.05 211110048 Kentucky Jefferson 0.02 0.01 0.02 0.04 0.04 0.01 1.09 0.03 0.42 0.01 0.03 0.01 1.49 0.06 245100040 Maryland 

Baltimore City 0.03 0.03 0.33 0.44 0.49 0.01 0.50 0.04 1.93 0.01 0.19 0.00 0.21 0.10 

245100049 Maryland 

Baltimore City 0.02 0.03 0.35 0.49 0.50 0.00 0.48 0.02 2.05 0.01 0.19 0.00 0.20 0.08 
D-20

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1h. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Michigan through New York 

Source States 

Receptor 

Monitor ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

261150005 Michigan Monroe 0.04 0.00 0.03 0.26 0.08 0.01 5.39 0.04 1.73 0.00 0.05 0.01 1.64 0.06 261250001 Michigan Oakland 0.04 0.00 0.02 0.33 0.06 0.00 4.66 0.02 1.84 0.00 0.01 0.00 1.10 0.03 261470005 Michigan St. Clair 0.03 0.00 0.02 0.78 0.04 0.00 3.45 0.02 1.83 0.00 0.01 0.00 0.65 0.02 261610008 Michigan Washtenaw 0.05 0.00 0.03 0.36 0.06 0.01 4.56 0.04 1.49 0.00 0.03 0.00 1.30 0.05 261630015 Michigan Wayne 0.03 0.00 0.02 0.26 0.06 0.01 4.09 0.04 1.31 0.00 0.03 0.00 1.42 0.05 261630016 Michigan Wayne 0.07 0.01 0.02 0.60 0.02 0.01 3.71 0.02 1.73 0.01 0.01 0.01 0.33 0.02 261630019 Michigan Wayne 0.04 0.00 0.01 0.55 0.01 0.00 3.37 0.01 1.50 0.00 0.00 0.00 0.33 0.0261630033 Michigan Wayne 0.06 0.01 0.03 0.46 0.06 0.02 3.98 0.04 1.44 0.01 0.03 0.01 1.07 0.05 261630036 Michigan Wayne 0.07 0.01 0.04 0.59 0.05 0.02 4.02 0.07 1.31 0.01 0.03 0.01 1.02 0.09 290990012 Missouri Jefferson 0.02 0.00 0.00 0.01 0.02 0.01 2.28 0.11 0.55 0.00 0.01 0.00 1.11 0.17 291831002 Missouri 

Saint Charles 0.03 0.01 0.01 0.04 0.03 0.02 1.70 0.06 0.62 0.01 0.03 0.02 1.14 0.06 

295100007 Missouri 

St. Louis City 0.02 0.00 0.00 0.01 0.01 0.00 2.17 0.10 0.55 0.00 0.01 0.00 0.99 0.15 

295100087 Missouri 

St. Louis City 0.03 0.00 0.01 0.03 0.03 0.01 1.87 0.08 0.52 0.00 0.03 0.01 1.19 0.12 

340171003 

New Jersey Hudson 0.02 0.02 4.67 4.06 0.40 0.01 0.85 0.04 2.28 0.03 0.17 0.01 0.26 0.07 

340172002 

New Jersey Hudson 0.02 0.03 4.20 5.82 0.37 0.01 0.70 0.03 2.23 0.05 0.16 0.00 0.21 0.06 

340390004 

New Jersey Union 0.02 0.07 3.28 2.42 0.40 0.00 1.07 0.02 2.84 0.02 0.18 0.00 0.37 0.06 

360050080 

New York Bronx 0.02 0.02 2.69 6.67 0.38 0.01 0.94 0.03 2.55 0.02 0.17 0.01 0.29 0.05 

360610056 

New York New York 0.04 0.11 2.56 7.99 0.37 0.02 0.74 0.05 2.40 0.05 0.18 0.01 0.25 0.09 

360610128 

New York New York 0.02 0.09 2.67 5.66 0.28 0.00 1.48 0.03 3.29 0.02 0.12 0.00 0.40 0.05 
D-21

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1i. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Ohio 

Source States 

Receptor 

Monitor ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

390170003 Ohio Butler 0.00 0.00 0.01 0.07 0.06 0.00 7.48 0.00 1.08 0.00 0.04 0.00 3.92 0.0390170016 Ohio Butler 0.02 0.01 0.03 0.10 0.07 0.02 5.13 0.02 1.26 0.01 0.05 0.01 3.29 0.0390170017 Ohio Butler 0.00 0.00 0.01 0.05 0.05 0.00 6.16 0.00 0.89 0.00 0.03 0.00 3.23 0.0390171004 Ohio Butler 0.00 0.00 0.01 0.05 0.04 0.00 6.45 0.00 0.89 0.00 0.03 0.00 3.19 0.0390350038 Ohio Cuyahoga 0.02 0.00 0.03 0.53 0.09 0.02 9.09 0.02 3.62 0.00 0.04 0.01 0.56 0.0390350045 Ohio Cuyahoga 0.03 0.01 0.03 0.78 0.07 0.02 9.48 0.01 2.94 0.01 0.03 0.01 0.40 0.0390350060 Ohio Cuyahoga 0.02 0.00 0.03 0.99 0.05 0.01 9.68 0.00 2.74 0.00 0.02 0.00 0.30 0.0390350065 Ohio Cuyahoga 0.03 0.01 0.04 0.83 0.06 0.02 8.92 0.02 3.13 0.01 0.03 0.01 0.38 0.0390490024 Ohio Franklin 0.04 0.01 0.03 0.35 0.09 0.02 7.45 0.02 2.12 0.00 0.04 0.01 1.01 0.0390490025 Ohio Franklin 0.05 0.01 0.05 0.41 0.12 0.04 7.07 0.04 2.15 0.01 0.05 0.02 0.97 0.0390610006 Ohio Hamilton 0.02 0.00 0.02 0.10 0.06 0.01 6.26 0.02 1.08 0.00 0.04 0.00 3.48 0.0390610014 Ohio Hamilton 0.01 0.00 0.02 0.13 0.06 0.01 6.59 0.02 1.43 0.00 0.05 0.00 3.10 0.0390610040 Ohio Hamilton 0.01 0.00 0.01 0.11 0.03 0.00 6.35 0.01 1.60 0.00 0.01 0.00 3.20 0.0390610042 Ohio Hamilton 0.01 0.00 0.00 0.13 0.02 0.00 7.08 0.01 0.90 0.00 0.02 0.00 2.83 0.0390610043 Ohio Hamilton 0.03 0.01 0.03 0.09 0.07 0.02 5.49 0.04 0.88 0.01 0.04 0.01 3.43 0.0390617001 Ohio Hamilton 0.02 0.01 0.02 0.14 0.06 0.01 6.53 0.02 1.59 0.01 0.04 0.01 3.23 0.0390618001 Ohio Hamilton 0.02 0.00 0.02 0.18 0.05 0.01 6.42 0.02 1.42 0.00 0.04 0.00 2.53 0.0390811001 Ohio Jefferson 0.03 0.00 0.02 0.18 0.04 0.02 5.87 0.01 2.34 0.00 0.02 0.00 0.37 0.0391130032 Ohio Montgomery 0.01 0.00 0.03 0.14 0.10 0.00 7.00 0.00 1.43 0.00 0.05 0.00 3.10 0.0391530017 Ohio Summit 0.04 0.00 0.03 0.38 0.06 0.03 8.82 0.04 2.97 0.00 0.02 0.00 0.48 0.0
D-22

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Nonattainment Recep

Part 1j. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Pennsylvania through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

420030008 Pennsylvania Allegheny 0.00 0.00 0.01 0.13 0.02 0.00 3.24 0.00 4.83 0.00 0.00 0.00 0.18 0.0420030064 Pennsylvania Allegheny 0.03 0.00 0.01 0.11 0.06 0.02 3.66 0.01 4.90 0.00 0.03 0.00 0.27 0.0420030093 Pennsylvania Allegheny 0.03 0.00 0.03 0.14 0.06 0.02 4.13 0.03 4.49 0.00 0.02 0.01 0.56 0.0420030116 Pennsylvania Allegheny 0.02 0.00 0.02 0.15 0.07 0.01 4.04 0.02 4.85 0.00 0.02 0.00 0.37 0.0420031008 Pennsylvania Allegheny 0.02 0.00 0.02 0.21 0.06 0.01 5.21 0.02 6.02 0.00 0.01 0.00 0.60 0.0420031301 Pennsylvania Allegheny 0.03 0.01 0.03 0.19 0.05 0.02 4.45 0.03 5.23 0.01 0.02 0.01 0.39 0.0420070014 Pennsylvania Beaver 0.02 0.00 0.03 0.23 0.07 0.01 4.99 0.02 4.07 0.00 0.01 0.00 0.33 0.0420110011 Pennsylvania Berks 0.04 0.07 0.86 1.02 0.36 0.03 1.00 0.03 9.02 0.03 0.14 0.02 0.29 0.0420210011 Pennsylvania Cambria 0.02 0.01 0.02 0.32 0.06 0.02 4.74 0.03 13.38 0.01 0.01 0.01 0.39 0.0420430401 Pennsylvania Dauphin 0.02 0.09 1.02 1.15 0.36 0.02 1.08 0.02 10.88 0.04 0.15 0.01 0.19 0.0420710007 Pennsylvania Lancaster 0.04 0.10 0.94 1.02 0.37 0.03 0.58 0.04 9.97 0.05 0.14 0.02 0.18 0.0421330008 Pennsylvania York 0.02 0.08 0.83 1.17 0.35 0.01 1.41 0.01 12.16 0.02 0.16 0.00 0.36 0.0471251009 Tennessee Montgomery 0.04 0.00 0.02 0.11 0.10 0.02 2.75 0.04 1.13 0.00 0.04 0.01 5.25 0.0540090011 

West Virginia Brooke 0.07 0.02 0.05 0.31 0.05 0.07 5.84 0.04 3.67 0.01 0.03 0.03 0.12 0.0

550790010 Wisconsin Milwaukee 0.62 0.00 0.00 0.04 0.01 0.20 0.44 0.14 0.23 0.00 0.00 0.08 0.13 0.0550790026 Wisconsin Milwaukee 0.42 0.01 0.01 0.12 0.02 0.27 0.95 0.15 0.47 0.01 0.02 0.13 0.17 0.1550790043 Wisconsin Milwaukee 0.25 0.00 0.00 0.10 0.02 0.14 2.12 0.11 0.89 0.00 0.03 0.06 0.28 0.0550790099 Wisconsin Milwaukee 0.43 0.00 0.00 0.07 0.01 0.18 1.11 0.14 0.51 0.00 0.01 0.09 0.18 0.0

Largest Contribution to Downwind Nonattainment => 0.62 0.21 2.69 5.82 0.50 0.27 5.84 0.16 3.67 0.05 0.19 0.13 3.92 0.2
D-23

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Maintenance Recep

Part 2a. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in the District of Columbia through New Y

Source States 

Receptor 

Monitor ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/DC 

110010041 

District Of Columbia 

District Of Columbia 0.11 0.04 0.13 0.17 0.06 0.19 0.43 0.65 0.11 0.06 0.49 0.05 0.06 3.67 

110010042 

District Of Columbia 

District Of Columbia 0.09 0.02 0.10 0.13 0.03 0.20 0.41 0.60 0.08 0.05 0.48 0.03 0.05 3.40 

170310022 Illinois Cook 0.01 0.03 0.00 0.00 0.00 0.03 4.23 8.94 0.56 0.24 0.41 0.01 0.00 0.00 170310050 Illinois Cook 0.06 0.07 0.01 0.02 0.01 0.07 4.88 5.09 0.41 0.17 0.97 0.03 0.01 0.09 170314007 Illinois Cook 0.07 0.06 0.00 0.01 0.01 0.13 8.29 4.39 0.84 0.32 1.17 0.04 0.00 0.06 171630010 Illinois Saint Clair 0.22 0.11 0.00 0.00 0.01 0.26 6.59 3.26 0.34 0.04 1.76 0.04 0.00 0.02 171971002 Illinois Will 0.07 0.10 0.00 0.00 0.00 0.09 6.48 3.82 0.68 0.13 0.98 0.05 0.00 0.05 180390003 Indiana Elkhart 0.20 0.10 0.00 0.00 0.02 0.31 2.19 6.34 0.39 0.10 1.87 0.18 0.00 0.05 180431004 Indiana Floyd 0.14 0.05 0.00 0.01 0.01 0.09 2.39 7.24 0.13 0.01 6.91 0.02 0.00 0.03 181670023 Indiana Vigo 0.12 0.09 0.01 0.01 0.02 0.05 3.10 9.11 0.34 0.12 3.19 0.03 0.01 0.04 191390015 Iowa Muscatine 0.14 0.17 0.00 0.01 0.03 0.15 4.35 1.71 3.57 0.42 0.69 0.10 0.00 0.03 210290006 Kentucky Bullitt 0.19 0.09 0.03 0.04 0.04 0.16 2.44 5.99 0.13 0.04 7.11 0.07 0.03 0.12 211451004 Kentucky 

McCracken 0.22 0.07 0.00 0.00 0.00 0.16 2.61 6.47 0.06 0.01 4.99 0.02 0.00 0.02 

212270007 Kentucky Warren 0.22 0.07 0.01 0.02 0.02 0.20 2.92 5.75 0.14 0.02 4.78 0.03 0.01 0.10 240031003 Maryland 

Anne Arundel 0.08 0.02 0.20 0.33 0.04 0.18 0.29 0.41 0.09 0.02 0.39 0.02 0.08 6.84 

245100035 Maryland 

Baltimore City 0.14 0.02 0.05 0.17 0.07 0.38 0.24 0.33 0.06 0.02 0.28 0.04 0.02 6.45 

261630001 Michigan Wayne 0.19 0.02 0.00 0.01 0.01 0.17 1.12 2.86 0.10 0.01 1.75 0.05 0.00 0.10 295100085 Missouri 

St. Louis City 0.17 0.10 0.02 0.02 0.03 0.19 6.57 3.48 0.49 0.08 1.73 0.06 0.02 0.05 

360610062 New York New York 0.12 0.03 0.70 0.32 0.06 0.31 0.32 0.44 0.07 0.03 0.37 0.05 0.19 0.67 360610079 New York New York 0.10 0.04 0.07 0.35 0.04 0.29 0.38 0.53 0.07 0.03 0.49 0.04 0.01 0.73 
D-24

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Maintenance Recep

Part 2b. 

Source States: Alabama through Missouri 

Receptors: Nonattainment Sites in Ohio through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County AL AR CT DE FL GA IL IN IA KS KY LA ME MD/D

390350027 Ohio Cuyahoga 0.05 0.01 0.00 0.00 0.01 0.07 0.69 1.35 0.11 0.01 0.62 0.01 0.00 0.1390350034 Ohio Cuyahoga 0.08 0.01 0.00 0.00 0.00 0.08 0.72 1.86 0.11 0.01 0.86 0.01 0.00 0.1390810017 Ohio Jefferson 0.03 0.03 0.00 0.02 0.00 0.06 0.72 1.48 0.08 0.02 0.94 0.01 0.00 0.1390950024 Ohio Lucas 0.06 0.01 0.00 0.01 0.00 0.12 1.49 3.33 0.19 0.02 1.03 0.00 0.00 0.1390950026 Ohio Lucas 0.25 0.06 0.01 0.02 0.08 0.36 1.20 3.56 0.13 0.04 2.05 0.07 0.01 0.1390990014 Ohio Mahoning 0.07 0.03 0.00 0.01 0.03 0.13 0.70 1.32 0.11 0.02 0.68 0.01 0.00 0.1391130031 Ohio Montgomery 0.23 0.03 0.00 0.01 0.00 0.29 1.13 3.47 0.09 0.01 3.57 0.03 0.00 0.1391351001 Ohio Preble 0.32 0.08 0.01 0.03 0.02 0.41 1.40 5.14 0.11 0.03 4.79 0.04 0.01 0.1391550007 Ohio Trumbull 0.08 0.02 0.00 0.02 0.01 0.13 0.65 1.23 0.12 0.02 0.58 0.01 0.00 0.2420030095 Pennsylvania Allegheny 0.04 0.04 0.01 0.02 0.01 0.06 0.65 1.22 0.10 0.02 0.80 0.02 0.01 0.1420033007 Pennsylvania Allegheny 0.05 0.04 0.01 0.02 0.01 0.06 0.58 1.21 0.07 0.02 0.89 0.02 0.00 0.1420410101 Pennsylvania Cumberland 0.10 0.01 0.12 0.36 0.04 0.25 0.23 0.37 0.03 0.01 0.29 0.03 0.05 1.8421255001 Pennsylvania Washington 0.07 0.03 0.01 0.01 0.01 0.20 0.70 1.48 0.12 0.03 0.85 0.01 0.00 0.1471650007 Tennessee Sumner 0.23 0.09 0.02 0.03 0.03 0.20 2.10 4.29 0.19 0.04 4.27 0.05 0.02 0.1540090005 

West Virginia Brooke 0.03 0.02 0.01 0.02 0.00 0.07 0.67 1.27 0.12 0.02 0.62 0.01 0.00 0.1

550250047 Wisconsin Dane 0.05 0.05 0.00 0.00 0.00 0.09 3.87 1.81 1.67 0.29 0.71 0.01 0.00 0.0550790059 Wisconsin Milwaukee 0.04 0.05 0.00 0.00 0.00 0.08 5.93 3.41 1.17 0.45 0.93 0.08 0.00 0.0551330027 Wisconsin Waukesha 0.05 0.08 0.01 0.01 0.01 0.11 3.26 2.43 0.65 0.09 0.79 0.08 0.01 0.0

Largest Contribution to Downwind Maintenance => 0.32 0.17 0.70 0.36 0.08 0.41 6.57 8.94 1.67 0.45 6.91 0.18 0.19 1.8
D-25

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Maintenance Recep

Part 2c. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in the District of Columbia through New Y

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

110010041 

District Of Columbia 

District Of Columbia 0.06 0.06 0.37 0.80 0.29 0.04 1.92 0.06 4.34 0.04 0.13 0.03 0.24 0.08 

110010042 

District Of Columbia 

District Of Columbia 0.05 0.04 0.31 0.74 0.28 0.02 1.44 0.04 3.34 0.02 0.11 0.01 0.20 0.07 

170310022 Illinois Cook 0.14 0.00 0.00 0.11 0.01 0.01 0.73 0.09 0.37 0.00 0.00 0.01 0.16 0.03 170310050 Illinois Cook 0.12 0.01 0.02 0.13 0.04 0.03 2.18 0.08 1.20 0.01 0.02 0.02 0.29 0.05 170314007 Illinois Cook 0.23 0.00 0.01 0.08 0.04 0.04 1.88 0.13 0.89 0.00 0.04 0.03 0.38 0.08 171630010 Illinois Saint Clair 0.03 0.00 0.01 0.02 0.04 0.01 1.84 0.09 0.47 0.00 0.03 0.01 1.18 0.13 171971002 Illinois Will 0.16 0.00 0.00 0.23 0.03 0.03 1.79 0.09 0.96 0.00 0.01 0.02 0.41 0.09 180390003 Indiana Elkhart 0.10 0.00 0.01 0.28 0.07 0.03 2.24 0.07 0.89 0.00 0.06 0.01 1.01 0.10 180431004 Indiana Floyd 0.01 0.00 0.01 0.05 0.03 0.01 1.56 0.03 0.44 0.00 0.02 0.00 2.32 0.04 181670023 Indiana Vigo 0.07 0.01 0.01 0.17 0.04 0.04 3.45 0.07 0.74 0.01 0.02 0.03 1.36 0.06 191390015 Iowa Muscatine 0.39 0.00 0.01 0.10 0.06 0.15 1.08 0.21 0.61 0.00 0.04 0.09 0.46 0.28 210290006 Kentucky Bullitt 0.03 0.03 0.04 0.09 0.08 0.03 2.20 0.05 0.65 0.03 0.06 0.03 2.04 0.08 211451004 Kentucky McCracken 0.01 0.00 0.01 0.03 0.05 0.00 1.13 0.02 0.29 0.00 0.04 0.00 2.66 0.03 212270007 Kentucky Warren 0.02 0.01 0.03 0.06 0.07 0.01 1.83 0.03 0.60 0.01 0.03 0.01 4.70 0.03 240031003 Maryland 

Anne Arundel 0.04 0.08 0.65 1.17 0.30 0.01 1.23 0.04 4.86 0.03 0.12 0.01 0.24 0.06 

245100035 Maryland 

Baltimore (City 0.03 0.02 0.30 0.38 0.44 0.01 0.50 0.04 1.75 0.00 0.17 0.00 0.20 0.10 

261630001 Michigan Wayne 0.02 0.00 0.01 0.30 0.05 0.00 5.29 0.01 1.87 0.00 0.01 0.00 1.08 0.02 295100085 Missouri 

St. Louis City 0.06 0.02 0.02 0.03 0.04 0.03 1.52 0.14 0.24 0.02 0.04 0.03 0.96 0.18 

360610062 New York New York 0.03 0.23 4.74 5.76 0.45 0.01 0.79 0.04 2.21 0.06 0.19 0.01 0.24 0.08 360610079 New York New York 0.03 0.01 2.68 7.30 0.42 0.02 1.11 0.05 2.60 0.03 0.19 0.01 0.33 0.08 
D-26

State-by-State Contributions to 24-Hour PM2.5 (μg/m3) Maintenance Recep

Part 2d. 

Source States: Nebraska through Wisconsin 

Receptors: Nonattainment Sites in Ohio through Wisconsin 

Source States 

Receptor 

Monitor 

ID 

Receptor 

State 

Receptor 

County NE NH NJ NY NC ND OH OK PA RI SC SD TN TX 

390350027 Ohio Cuyahoga 0.02 0.00 0.03 1.10 0.02 0.01 9.31 0.01 2.79 0.00 0.01 0.00 0.22 0.01 390350034 Ohio Cuyahoga 0.03 0.00 0.00 0.72 0.04 0.01 8.52 0.01 2.34 0.00 0.01 0.00 0.33 0.01 390810017 Ohio Jefferson 0.02 0.00 0.03 0.22 0.05 0.02 5.57 0.01 2.52 0.00 0.01 0.00 0.35 0.02 390950024 Ohio Lucas 0.05 0.00 0.01 0.51 0.03 0.00 5.67 0.01 1.54 0.00 0.01 0.00 0.47 0.01 390950026 Ohio Lucas 0.05 0.01 0.02 0.48 0.09 0.01 6.14 0.04 1.89 0.01 0.05 0.01 1.52 0.04 390990014 Ohio Mahoning 0.03 0.00 0.02 0.30 0.06 0.03 7.13 0.02 3.04 0.00 0.02 0.01 0.37 0.03 391130031 Ohio Montgomery 0.02 0.00 0.02 0.17 0.06 0.00 6.05 0.01 1.26 0.00 0.03 0.00 2.13 0.01 391351001 Ohio Preble 0.02 0.01 0.03 0.16 0.09 0.02 5.52 0.02 1.03 0.01 0.06 0.01 2.99 0.03 391550007 Ohio Trumbull 0.03 0.00 0.02 0.27 0.09 0.02 6.73 0.02 3.17 0.00 0.03 0.01 0.37 0.02 420030095 Pennsylvania Allegheny 0.03 0.01 0.03 0.22 0.07 0.03 3.97 0.02 5.18 0.01 0.02 0.01 0.30 0.03 420033007 Pennsylvania Allegheny 0.02 0.00 0.03 0.18 0.08 0.02 4.61 0.02 5.56 0.00 0.04 0.00 0.36 0.02 420410101 Pennsylvania Cumberland 0.01 0.06 0.83 0.91 0.33 0.00 0.91 0.01 8.23 0.02 0.16 0.00 0.19 0.03 421255001 Pennsylvania Washington 0.05 0.00 0.02 0.16 0.17 0.02 5.13 0.03 3.42 0.00 0.08 0.01 0.40 0.04 471650007 Tennessee Sumner 0.04 0.02 0.04 0.09 0.10 0.02 2.27 0.05 0.86 0.02 0.05 0.02 6.45 0.05 540090005 

West Virginia Brooke 0.03 0.00 0.03 0.24 0.04 0.03 5.56 0.02 3.00 0.00 0.02 0.01 0.24 0.02 

550250047 Wisconsin Dane 0.31 0.00 0.00 0.09 0.02 0.12 1.27 0.20 0.77 0.00 0.02 0.07 0.34 0.11 550790059 Wisconsin Milwaukee 0.36 0.00 0.00 0.09 0.02 0.13 1.43 0.11 0.63 0.00 0.02 0.05 0.27 0.09 551330027 Wisconsin Waukesha 0.13 0.01 0.01 0.16 0.04 0.13 1.63 0.09 0.73 0.01 0.03 0.06 0.28 0.12 

Largest Contribution to Downwind Maintenance => 0.39 0.23 4.74 1.17 0.45 0.15 5.56 0.21 4.86 0.06 0.19 0.09 4.70 0.28 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix E 

Upwind States to Downwind Nonattainment and 

Maintenance Linkages 
E-2

Table E-1. Upwind State-to-Downwind Nonattainment Site “Linkages” for Annu

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Nonattainment Sites (Monito

Alabama 6 

Bibb, GA (130210007)

Clayton, GA (130630091)

Fulton, GA (131210039)

Clark, IN (180190006) 

Dubois, IN (180372001)

JeffersoKY (2111100

Delaware 2 

Lancaster, PA (420710007)

York, PA (421330008)

Florida 3 

Jefferson, AL (10730023) 

Bibb, GA (130210007)

Clayton, GA (130630091) 

Georgia 7 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Clark, IN (180190006)

Dubois, IN (180372001) 

Jefferson, KY (211110043)

Kanawha(5403910

Illinois 29 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Fulton, GA (131210039)

Bibb, GA (130210007) 

Clayton, GA (130630091)

Clark, I(1801900

Marion, IN (180970078)

Marion, IN (180970081)

Marion, IN (180970083)

Jefferson, KY (211110043) 

Wayne, MI (261630015)

Wayne, M(2616300

Cuyahoga, OH (390350038)

Cuyahoga, OH (390350045)

Cuyahoga, OH (390350060)

Hamilton, OH (390610014) 

Hamilton, OH (390610042)

HamiltonOH (3906100

Hamilton, OH (390618001)

Allegheny, PA (420030064)

Allegheny, PA (420031301)

Beaver, PA (420070014) 

Lancaster, PA (420710007)

York, PA (4213300

Kanawha, WV (540391005)

Indiana 27 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Bibb, GA (130210007)

Clayton, GA (130630091) 

Fulton, GA (131210039)

Cook, IL (1703100

Saint Clair, IL (171630010)

Jefferson, KY (211110043)

Wayne, MI (261630015)

Wayne, MI (261630033) 

Butler, OH (390170016)

CuyahogaOH (3903500

Cuyahoga, OH (390350060)

Hamilton, OH (390618001)

Hamilton, OH (390610014)

Hamilton, OH (390610042) 

Hamilton, OH (390610043)

HamiltonOH (3906170
E-3

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Nonattainment Sites (Monito

Allegheny, PA (420031301)

Beaver, PA (420070014)

Lancaster, PA (420710007)

York, PA (421330008) 

Cabell, WV (540110006)

Kanawha(5403910

Iowa 4 

Cook, IL (170310052)

Madison, IL (171191007)

Saint Clair, IL (171630010)

Dubois, IN (180372001) 

Kentucky 31 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Bibb, GA (130210007)

Clayton, GA (130630091) 

Fulton, GA (131210039)

Cook, IL (1703100

Saint Clair, IL (171630010)

Clark, IN (180190006)

Dubois, IN (180372001)

Marion, IN (180970078) 

Marion, IN (180970081)

Marion, (1809700

Wayne, MI (261630033)

Butler, OH (390170016)

Cuyahoga, OH (390350038)

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060)

HamiltonOH (3906100

Hamilton, OH (390610043)

Hamilton, OH (390617001)

Hamilton, OH (390618001)

Allegheny, PA (420030064) 

Allegheny, PA (420031301)

Beaver, (4200700

York, PA (421330008)

Cabell, WV (540110006)

Kanawha, WV (540391005)

Maryland/DC 2 

Lancaster, PA (420710007)

York, PA (421330008) 

Michigan 25 

Cook, IL (170310052)

Madison, IL (171191007)

Saint Clair, IL (171630010)

Clark, IN (180190006) 

Dubois, IN (180372001)

Marion, (1809700

Marion, IN (180970083)

Jefferson, KY (211110043)

Butler, OH (390170016)

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045)

CuyahogaOH (3903500

Hamilton, OH (390610042)

Hamilton, OH (390610043)

Hamilton, OH (390617001)

Hamilton, OH (390618001) 

Allegheny, PA (420030064)

AlleghenPA (4200313

Lancaster, PA (420710007)

York, PA (421330008)

Cabell, WV (540110006)

Kanawha, WV (540391005) 

Minnesota 1 

Cook, IL (170310052)
E-4

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Nonattainment Sites (Monito

Missouri 17 

Cook, IL (170310052)

Madison, IL (171191007)

Saint Clair, IL (171630010)

Clark, IN (180190006) 

Dubois, IN (180372001)

Marion, (1809700

Marion, IN (180970083)

Jefferson, KY (211110043)

Butler, OH (390170016)

Hamilton, OH (390610014) 

Hamilton, OH (390610042)

HamiltonOH (3906100

Hamilton, OH (390618001)

Cabell, WV (540110006)

Kanawha, WV (540391005)

New Jersey 2 

Lancaster, PA (420710007)

York, PA (421330008)

New York 8 

Cuyahoga, OH (390350038)

Cuyahoga, OH (390350045)

Cuyahoga, OH (390350060)

Allegheny, PA (420030064) 

Allegheny, PA (420031301)

Beaver, (4200700

York, PA (421330008)

North Carolina 3 

Bibb, GA (130210007)

Clayton, GA (130630091)

Fulton, GA (131210039) 

Ohio 23 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Bibb, GA (130210007)

Clayton, GA (130630091) 

Fulton, GA (131210039)

Cook, IL (1703100

Saint Clair, IL (171630010)

Clark, IN (180190006)

Dubois, IN (180372001)

Marion, IN (180970078) 

Marion, IN (180970081)

Marion, (1809700

Wayne, MI (261630015)

Wayne, MI (261630033)

Allegheny, PA (420030064)

Allegheny, PA (420031301) 

Beaver, PA (420070014)

LancastePA (4207100

Cabell, WV (540110006)

Kanawha, WV (540391005)

Pennsylvania 25 

Bibb, GA (130210007)

Clayton, GA (130630091)

Fulton, GA (131210039)

Cook, IL (170310052) 

Madison, IL (171191007)

Saint Clair, I(1716300

Dubois, IN (180372001)

Marion, IN (180970078)

Marion, IN (180970081)

Marion, IN (180970083) 

Jefferson, KY (211110043)

Wayne, M(2616300
E-5

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Nonattainment Sites (Monito

Butler, OH (390170016)

Cuyahoga, OH (390350038)

Cuyahoga, OH (390350045)

Cuyahoga, OH (390350060) 

Hamilton, OH (390610014)

HamiltonOH (3906100

Hamilton, OH (390617001)

Hamilton, OH (390618001)

Cabell, WV (540110006)

Kanawha, WV (540391005) 

South Carolina 3 

Bibb, GA (130210007)

Clayton, GA (130630091)

Fulton, GA (131210039) 

Tennessee 29 

Jefferson, AL (10730023) 

Jefferson, AL (10732003) 

Bibb, GA (130210007)

Clayton, GA (130630091) 

Fulton, GA (131210039)

Clark, I(1801900

Saint Clair, IL (171630010)

Dubois, IN (180372001)

Marion, IN (180970078)

Marion, IN (180970081) 

Marion, IN (180970083)

JeffersoKY (2111100

Wayne, MI (261630033)

Butler, OH (390170016)

Cuyahoga, OH (390350038)

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060)

HamiltonOH (3906100

Hamilton, OH (390610043)

Hamilton, OH (390617001)

Hamilton, OH (390618001)

Allegheny, PA (420030064) 

Allegheny, PA (420031301)

Beaver, (4200700

Kanawha, WV (540391005)

Virginia 4 

Lancaster, PA (420710007)

York, PA (421330008)

Cabell, WV (540110006)

Kanawha, WV (540391005) 

West Virginia 25 

Fulton, GA (131210039)

Bibb, GA (130210007)

Clayton, GA (130630091)

Clark, IN (180190006) 

Marion, IN (180970078)

Marion, (1809700

Dubois, IN (180372001)

Jefferson, KY (211110043)

Wayne, MI (261630015)

Wayne, MI (261630033) 

Butler, OH (390170016)

CuyahogaOH (3903500

Cuyahoga, OH (390350060)

Hamilton, OH (390610014)

Hamilton, OH (390610042)

Hamilton, OH (390610043) 

Hamilton, OH (390617001)

HamiltonOH (3906180

Allegheny, PA (420031301)

Beaver, PA (420070014)

Lancaster, PA (420710007)

York, PA (421330008) 
E-6

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Nonattainment Sites (Monito

Wisconsin 8 

Cook, IL (170310052)

Dubois, IN (180372001)

Marion, IN (180970078)

Marion, IN (180970081) 

Marion, IN (180970083)

Wayne, M(2616300

Cuyahoga, OH (390350045)
E-7

Table E-2. Upwind State-to-Downwind Maintenance Site “Linkages” for Annual 

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Maintenance Sites (Monitoring 

Alabama 1 

Jefferson, KY (211110044) 

Georgia 1 

Jefferson, KY (211110044) 

Illinois 13 

Jefferson, KY (211110044) 

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350065) 

Hamilton, OH (390610040) 

Jefferson, OH (390811001)

MontgomOH (391130

Berks, PA (420110011) 

Harris, TX (482011035) 

Berkeley, WV (540030003) 

Brooke, WV (540090005) 

Hancock, WV (540291004)

Marion, (540490

Indiana 16 

Cook, IL (170313301) 

Cook, IL (170316005) 

Jefferson, KY (211110044) 

New York, NY (360610056) 

Cuyahoga, OH (390350027)

Cuyahog(390350

Jefferson, OH (390811001) 

Montgomery, OH (391130032) 

Stark, OH (391510017) 

Berks, PA (420110011) 

Harris, TX (482011035)

Berkele(540030

Hancock, WV (540291004) 

 Marion, WV (540490006) 

Iowa 2 

Cook, IL (170313301) 

Cook, IL (170316005) 

Kentucky 12 

Cook, IL (170313301) 

Cook, IL (170316005) 

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350065) 

Hamilton, OH (390610040)

JeffersOH (390811

Stark, OH (391510017) 

Berkeley, WV (540030003) 

Brooke, WV (540090005) 

Hancock, WV (540291004) 

Marion, WV (540490006)

Louisiana 1 

Harris, TX (482011035) 

Maryland/DC 2 

Berks, PA (420110011) 

 Berkeley, WV (540030003) 

Michigan 15 

Cook, IL (170313301) 

Cook, IL (170316005) 

Jefferson, KY (211110044) 

New York, NY (360610056) 

Cuyahoga, OH (390350027)

Cuyahog(390350
E-8

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Maintenance Sites (Monitoring 

Jefferson, OH (390811001) 

Montgomery, OH (391130032) 

Stark, OH (391510017) 

Berks, PA (420110011) 

Berkeley, WV (540030003)

Brooke, (540090

Marion, WV (540490006) 

Minnesota 1 

Cook, IL (170316005) 

Missouri 6 

Cook, IL (170313301) 

Cook, IL (170316005) 

Jefferson, KY (211110044) 

Hamilton, OH (390610040) 

Montgomery, OH (391130032)

Stark, (391510

New Jersey 2 

New York, NY (360610056) 

 Berks, PA (420110011) 

New York 9 

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350065) 

Jefferson, OH (390811001) 

Stark, OH (391510017) 

 Berks, PA (420110011)

Berkele(540030

Hancock, WV (540291004) 

 Marion, WV (540490006) 

Ohio 9 

Cook, IL (170313301) 

Cook, IL (170316005) 

Jefferson, KY (211110044) 

New York, NY (360610056) 

Berks, PA (420110011)

Berkele(540030

Hancock, WV (540291004) 

 Marion, WV (540490006) 

Pennsylvania 14 

Cook, IL (170313301) 

Cook, IL (170316005) 

Jefferson, KY (211110044) 

New York, NY (360610056) 

Cuyahoga, OH (390350027)

Cuyahog(390350

Jefferson, OH (390811001) 

Montgomery, OH (391130032) 

Stark, OH (391510017) 

Berkeley, WV (540030003) 

Brooke, WV (540090005)

Hancock(540291

Tennessee 10 

Jefferson, KY (211110044) 

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350065) 

Hamilton, OH (390610040) 

Jefferson, OH (390811001)

MontgomOH (391130

Brooke, WV (540090005) 

Hancock, WV (540291004) 

Marion, WV (540490006) 

Virginia 4 

New York, NY (360610056) 

Berks, PA (420110011) 

Berkeley, WV (540030003

Marion, WV (540490006) 
E-9

Upwind State 

Number of Linkages Counties Containing Downwind Annual PM2.5 Maintenance Sites (Monitoring 

) 

West Virginia 9 

Jefferson, KY (211110044) 

New York, NY (360610056) 

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350065) 

Hamilton, OH (390610040)

JeffersOH (390811

Stark, OH (391510017) 

 Berks, PA (420110011) 

Wisconsin 2 

Cook, IL (170313301) 

Cook, IL (170316005) 
E-10

Table E-3. Upwind State-to-Downwind Nonattainment Site “Linkages” for 24-H

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Alabama 5 

Monroe, MI (261150005) 

Wayne, MI (261630015) 

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilt(39061

Connecticut 3 

Hudson, NJ (340172002) 

New York, NY (360610056) 

New York, NY (360610128) 

Delaware 2 

Union, NJ (340390004) 

Dauphin, PA (420430401) 

Georgia 12 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

Baltimore City, MD (245100040) 

Baltimore City, MD (245100049) 

Union, (34039

Butler, OH (390171004) 

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilton, OH (390618001) 

MontgoOH (39113

Illinois 70 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Clark, IN (180190006) 

Dubois(18037

Lake, IN (180890022) 

Lake, IN (180890026) 

Marion, IN (180970042) 

Marion, IN (180970043) 

Marion(18097

Marion, IN (180970079) 

Marion, IN (180970081) 

Marion, IN (180970083) 

Tippecanoe, IN (181570008) 

Scott, (19163

Jefferson, KY (211110043) 

Jefferson, KY 

(211110044) 

Jefferson, KY (211110048) 

Monroe, MI (261150005) 

Oaklan(26125

Washtenaw, MI (261610008) 

Wayne, MI (261630015) 

Wayne, MI (261630016) 

Wayne, MI (261630019) 

Wayne, (26163

Jefferson, MO (290990012) 

Saint Charles, MO (291831002) 

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

Union, (34039

Butler, OH (390170003) 

Butler, OH (390170016) 

Butler, OH (390170017) 

Butler, OH (390171004) 

Cuyaho(39035

Cuyahoga, OH (390350060) 

Cuyahoga, OH (390350065) 

Franklin, OH (390490024) 

Franklin, OH (390490025) 

Hamilt(39061

Hamilton, OH (390610040) 

Hamilton, OH (390610042) 

Hamilton, OH (390610043) 

Hamilton, OH (390617001) 

Hamilt(39061

Montgomery, OH 

Summit, OH (391530017) 

Allegheny, PA (420030064) 

Allegheny, PA (420030093) 

Allegh(42003
E-11

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

(391130032) 

Allegheny, PA (420031301) 

Beaver, PA (420070014) 

Berks, PA (420110011) 

Cambria, PA (420210011) 

MontgoTN (47125

Milwaukee, WI (550790010) 

Milwaukee, WI 

(550790026) 

Milwaukee, WI (550790043) 

Milwaukee, WI (550790099) 

Indiana 75 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Cook, IL (170310052) 

Cook, (17031

Cook, IL (170311016) 

Cook, IL (170312001) 

Cook, IL (170313103) 

Cook, IL (170313301) 

Cook, (17031

Madison, IL (171191007) 

Madison, IL (171192009) 

Madison, IL (171193007) 

Scott, IA (191630019) 

Davies(21059

Jefferson, KY (211110044) 

Jefferson, KY 

(211110048) 

Monroe, MI (261150005) 

Oakland, MI (261250001) 

St. Cl(26147

Wayne, MI (261630015) 

Wayne, MI (261630016) 

Wayne, MI (261630019) 

Wayne, MI (261630033) 

Wayne, (26163

Saint Charles, MO (291831002) 

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

Hudson, NJ (340171003) 

Union, (34039

New York, NY (360610056) 

New York, NY (360610128) 

Butler, OH (390170003) 

Butler, OH (390170016) 

Butler(39017

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060) 

Cuyahoga, OH (390350065) 

Frankl(39049

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilton, OH (390610040) 

Hamilton, OH (390610042) 

Hamilt(39061

Hamilton, OH (390618001) 

Jefferson, OH 

(390811001) 

Montgomery, OH (391130032) 

Summit, OH (391530017) 

Allegh(42003

Allegheny, PA (420030093) 

Allegheny, PA 

(420030116) 

Allegheny, PA (420031008) 

Allegheny, PA (420031301) 

Beaver(42007

Cambria, PA (420210011) 

Dauphin, PA (420430401) 

York, PA (421330008) 

Montgomery, TN (471251009) 

Brooke(54009

Milwaukee, WI (550790026) 

Milwaukee, WI 

(550790043) 

Milwaukee, WI (550790099) 

Iowa 17 

Cook, IL (170310052) 

Cook, IL (170310057) 

Cook, IL (170310076) 

Cook, IL (170311016) 

Cook, (17031
E-12

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Cook, IL (170313301) 

Cook, IL (170316005) 

Madison, IL (171191007) 

Lake, IN (180890022) 

Lake, (18089

St. Louis City, MO (295100007) 

Milwaukee, WI 

(550790010) 

Milwaukee, WI (550790026) 

Milwaukee, WI (550790043) 

Milwau(55079

Kansas 3 

Milwaukee, WI (550790010) 

Milwaukee, WI 

(550790026) 

Milwaukee, WI (550790099) 

Kentucky 81 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Cook, IL (170310052) 

Cook, (17031

Cook, IL (170311016) 

Cook, IL (170312001) 

Cook, IL (170313103) 

Cook, IL (170313301) 

Cook, (17031

Madison, IL (171191007) 

Madison, IL (171192009) 

Madison, IL (171193007) 

Clark, IN (180190006) 

Dubois(18037

Lake, IN (180890026) 

Marion, IN (180970042) 

Marion, IN (180970043) 

Marion, IN (180970066) 

Marion(18097

Marion, IN (180970081) 

Marion, IN (180970083) 

Tippecanoe, IN (181570008) 

Scott, IA (191630019) 

Monroe(26115

St. Clair, MI (261470005) 

Washtenaw, MI 

(261610008) 

Wayne, MI (261630015) 

Wayne, MI (261630016) 

Wayne, (26163

Wayne, MI (261630036) 

Jefferson, MO 

(290990012) 

Saint Charles, MO (291831002) 

St. Louis City, MO (295100007) 

St. LoCity, (29510

Union, NJ (340390004) 

Bronx, NY (360050080) 

New York, NY (360610128) 

Butler, OH (390170003) 

Butler(39017

Butler, OH (390171004) 

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060) 

Cuyaho(39035

Franklin, OH (390490025) 

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilton, OH (390610040) 

Hamilt(39061

Hamilton, OH (390617001) 

Hamilton, OH (390618001) 

Jefferson, OH (390811001) 

Montgomery, OH (391130032) 

Summit(39153

Allegheny, PA (420030064) 

Allegheny, PA 

(420030093) 

Allegheny, PA (420030116) 

Allegheny, PA (420031008) 

Allegh(42003

Berks, PA (420110011) 

Cambria, PA (420210011) 

York, PA (421330008) 

Montgomery, TN (471251009) 

Brooke(54009

Milwaukee, WI (550790026) 

Milwaukee, WI 

(550790043) 

Milwaukee, WI (550790099) 
E-13

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Maryland/DC 11 

New Haven, CT (90091123) 

Hudson, NJ (340171003) 

Hudson, NJ (340172002) 

Union, NJ (340390004) 

Bronx, (36005

New York, NY (360610128) 

Berks, PA (420110011) 

Dauphin, PA (420430401) 

Lancaster, PA (420710007) 

York, (42133

Massachusetts 3 

New Haven, CT (90091123) 

New York, NY (360610056) 

New York, NY (360610128) 

Michigan 48 

Cook, IL (170310052) 

Cook, IL (170310057) 

Cook, IL (170310076) 

Cook, IL (170311016) 

Cook, (17031

Cook, IL (170313301) 

Cook, IL (170316005) 

Madison, IL (171190023) 

Madison, IL (171191007) 

Madiso(17119

Knox, IN (180830004) 

Lake, IN (180890022) 

Lake, IN (180890026) 

Scott, IA (191630019) 

Jeffer(29099

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

New York, NY (360610128) 

Cuyahoga, OH (390350038) 

Cuyaho(39035

Cuyahoga, OH (390350065) 

Franklin, OH (390490024) 

Franklin, OH (390490025) 

Hamilton, OH (390610014) 

Hamilt(39061

Jefferson, OH (390811001) 

Montgomery, OH (391130032) 

Summit, OH (391530017) 

Allegheny, PA (420030008) 

Allegh(42003

Allegheny, PA (420030116) 

Allegheny, PA 

(420031008) 

Allegheny, PA (420031301) 

Beaver, PA (420070014) 

Cambri(42021

Montgomery, TN (471251009) 

Brooke, WV (540090011) 

Milwaukee, WI (550790010) 

Milwaukee, WI (550790026) 

Milwau(55079

Milwaukee, WI (550790099) 

Minnesota 4 

Milwaukee, WI (550790010) 

Milwaukee, WI(550790026) 

Milwaukee, WI (550790043) 

Milwaukee, WI (550790099) 

Missouri 56 

Cook, IL (170310052) 

Cook, IL (170310057) 

Cook, IL (170310076) 

Cook, IL (170311016) 

Cook, (17031

Cook, IL (170313301) 

Cook, IL (170316005) 

Madison, IL (171190023) 

Madison, IL (171191007) 

Madiso(17119

Clark, IN (180190006) 

Dubois, IN (180372001) 

Knox, IN (180830004) 

Lake, IN (180890022) 

Lake, (18089
E-14

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Marion, IN (180970043) 

Marion, IN (180970066) 

Marion, IN (180970078) 

Marion, IN (180970079) 

Marion(18097

Tippecanoe, IN (181570008) 

Scott, IA (191630019) 

Daviess, KY (210590005) 

Jefferson, KY (211110043) 

Jeffer(21111

Monroe, MI (261150005) 

Oakland, MI (261250001) 

Washtenaw, MI (261610008) 

Wayne, MI (261630015) 

Wayne, (26163

Butler, OH (390170003) 

Butler, OH (390170016) 

Butler, OH (390170017) 

Butler, OH (390171004) 

Frankl(39049

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilton, OH (390610040) 

Hamilton, OH (390610042) 

Hamilt(39061

Hamilton, OH (390618001) 

Montgomery, OH (391130032) 

Allegheny, PA (420030116) 

Montgomery, TN (471251009) 

Milwau(55079

Milwaukee, WI (550790043) 

Milwaukee, WI 

(550790099) 

Nebraska 3 

Milwaukee, WI (550790010) 

Milwaukee, WI 

(550790026) 

Milwaukee, WI (550790099) 

New Jersey 9 

New Haven, CT (90091123) 

Baltimore City, MD (245100049) 

Bronx, NY (360050080) 

New York, NY (360610056) 

New Yo(36061

Dauphin, PA (420430401) 

Lancaster, PA 

(420710007) 

York, PA (421330008) 

New York 23 

New Haven, CT (90091123) 

Baltimore City, MD (245100040) 

Baltimore City, MD (245100049) 

St. Clair, MI (261470005) 

Washte(26161

Wayne, MI (261630019) 

Wayne, MI (261630033) 

Wayne, MI (261630036) 

Hudson, NJ (340171003) 

Hudson(34017

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060) 

Cuyahoga, OH (390350065) 

Frankl(39049

Summit, OH (391530017) 

Berks, PA (420110011) 

Dauphin, PA (420430401) 

Lancaster, PA (420710007) 

York, (42133

North Carolina 11 

Baltimore City, MD (245100040) 

Baltimore City, MD (245100049) 

Hudson, NJ (340171003) 

Hudson, NJ (340172002) 

Union(34039
E-15

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

New York, NY (360610056) 

Berks, PA (420110011) 

Dauphin, PA (420430401) 

Lancaster, PA (420710007) 

York, (42133

Ohio 72 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Cook, IL (170310052) 

Cook, (17031

Cook, IL (170311016) 

Cook, IL (170312001) 

Cook, IL (170313103) 

Cook, IL (170313301) 

Cook, (17031

Madison, IL (171191007) 

Madison, IL (171192009) 

Madison, IL (171193007) 

Clark, IN (180190006) 

Dubois(18037

Lake, IN (180890022) 

Lake, IN (180890026) 

Marion, IN (180970042) 

Marion, IN (180970043) 

Marion(18097

Marion, IN (180970079) 

Marion, IN (180970081) 

Marion, IN (180970083) 

Tippecanoe, IN (181570008) 

Scott(19163

Jefferson, KY (211110043) 

Jefferson, KY 

(211110044) 

Jefferson, KY (211110048) 

Baltimore (City, MD (245100040) 

Baltim(City(24510

Oakland, MI (261250001) 

St. Clair, MI 

(261470005) 

Washtenaw, MI (261610008) 

Wayne, MI (261630015) 

Wayne(26163

Wayne, MI (261630033) 

Wayne, MI (261630036) 

Jefferson, MO (290990012) 

Saint Charles, MO (291831002) 

St. LoCity, (29510

Hudson, NJ (340171003) 

Hudson, NJ (340172002) 

Union, NJ (340390004) 

Bronx, NY (360050080) 

New Yo(36061

Allegheny, PA (420030008) 

Allegheny, PA 

(420030064) 

Allegheny, PA (420030093) 

Allegheny, PA (420030116) 

Allegh(42003

Beaver, PA (420070014) 

Berks, PA (420110011) 

Cambria, PA (420210011) 

Dauphin, PA (420430401) 

Lancas(42071

Montgomery, TN (471251009) 

Brooke, WV (540090011) 

Milwaukee, WI (550790010) 

Milwaukee, WI (550790026) 

Milwau(55079

Pennsylvania 77 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Cook, IL (170310052) 

Cook, (17031

Cook, IL (170311016) 

Cook, IL (170312001) 

Cook, IL (170313103) 

Cook, IL (170313301) 

Cook, (17031

Madison, IL (171192009) 

Madison, IL (171193007) 

Madison, IL (171190023) 

Clark, IN (180190006) 

Dubois(18037
E-16

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Lake, IN (180890026) 

Marion, IN (180970042) 

Marion, IN (180970043) 

Marion, IN (180970066) 

Marion(18097

Marion, IN (180970081) 

Marion, IN (180970083) 

Tippecanoe, IN 

(181570008) 

Scott, IA (191630019) 

Jeffer(21111

Jefferson, KY (211110048) 

Baltimore City, MD (245100040) 

Baltimore City, MD (245100049) 

Monroe, MI (261150005) 

Oaklan(26125

Washtenaw, MI (261610008) 

Wayne, MI (261630015) 

Wayne, MI (261630016) 

Wayne, MI (261630019) 

Wayne(26163

Jefferson, MO (290990012) 

Saint Charles, MO (291831002) 

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

Hudson(34017

Union, NJ (340390004) 

Bronx, NY (360050080) 

New York, NY (360610056) 

New York, NY (360610128) 

Butler(39017

Butler, OH (390170017) 

Butler, OH (390171004) 

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045) 

Cuyaho(39035

Franklin, OH (390490024) 

Franklin, OH (390490025) 

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilt(39061

Hamilton, OH (390610043) 

Hamilton, OH (390617001) 

Hamilton, OH (390618001) 

Jefferson, OH (390811001) 

MontgoOH (39113

Montgomery, TN (471251009) 

Brooke, WV (540090011) 

Milwaukee, WI (550790026) 

Milwaukee, WI (550790043) 

Milwau(55079

Tennessee 61 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Madison, IL (171190023) 

Madiso(17119

Madison, IL (171193007) 

Clark, IN (180190006) 

Dubois, IN (180372001) 

Knox, IN (180830004) 

Marion(18097

Marion, IN (180970066) 

Marion, IN (180970078) 

Marion, IN (180970079) 

Marion, IN (180970081) 

Marion(18097

Scott, IA (191630019) 

Daviess, KY (210590005) 

Jefferson, KY (211110043) 

Jefferson, KY (211110044) 

Jeffer(21111

Oakland, MI (261250001) 

St. Clair, MI 

(261470005) 

Washtenaw, MI (261610008) 

Wayne, MI (261630015) 

Wayne(26163
E-17

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Jefferson, MO (290990012) 

Saint Charles, MO (291831002) 

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

Union(34039

Butler, OH (390170003) 

Butler, OH (390170016) 

Butler, OH (390170017) 

Butler, OH (390171004) 

Cuyaho(39035

Cuyahoga, OH (390350065) 

Franklin, OH (390490024) 

Franklin, OH (390490025) 

Hamilton, OH (390610006) 

Hamilt(39061

Hamilton, OH (390610042) 

Hamilton, OH (390610043) 

Hamilton, OH (390617001) 

Hamilton, OH (390618001) 

Jeffer(39081

Summit, OH (391530017) 

Allegheny, PA 

(420030093) 

Allegheny, PA (420030116) 

Allegheny, PA (420031008) 

Allegh(42003

York, PA (421330008) 

Virginia 13 

New Haven, CT (90091123) 

Baltimore City, MD (245100040) 

Baltimore City, MD (245100049) 

Hudson, NJ (340171003) 

Hudson(34017

Bronx, NY (360050080) 

New York, NY (360610056) 

New York, NY (360610128) 

Berks, PA (420110011) 

Dauphi(42043

York, PA (421330008) 

West Virginia 84 

Jefferson, AL (10730023) 

Jefferson, AL 

(10732003) 

New Haven, CT (90091123) 

Cook, IL (170310052) 

Cook, (17031

Cook, IL (170311016) 

Cook, IL (170312001) 

Cook, IL (170313301) 

Cook, IL (170316005) 

Madiso(17119

Madison, IL (171192009) 

Madison, IL (171193007) 

Clark, IN (180190006) 

Dubois, IN (180372001) 

Lake, (18089

Marion, IN (180970043) 

Marion, IN (180970066) 

Marion, IN (180970078) 

Marion, IN (180970079) 

Marion(18097

Tippecanoe, IN (181570008) 

Scott, IA (191630019) 

Jefferson, KY (211110043) 

Jefferson, KY (211110044) 

Jeffer(21111

Baltimore City, MD (245100049) 

Monroe, MI (261150005) 

Oakland, MI (261250001) 

St. Clair, MI (261470005) 

Washte(26161
E-18

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Mo

Wayne, MI (261630016) 

Wayne, MI (261630019) 

Wayne, MI (261630033) 

Wayne, MI (261630036) 

Jeffer(29099

St. Louis City, MO (295100007) 

St. Louis City, MO (295100087) 

Hudson, NJ (340171003) 

Hudson, NJ (340172002) 

Union(34039

New York, NY (360610056) 

New York, NY (360610128) 

Butler, OH (390170003) 

Butler, OH (390170016) 

Butler(39017

Cuyahoga, OH (390350038) 

Cuyahoga, OH (390350045) 

Cuyahoga, OH (390350060) 

Cuyahoga, OH (390350065) 

Frankl(39049

Hamilton, OH (390610006) 

Hamilton, OH (390610014) 

Hamilton, OH (390610040) 

Hamilton, OH (390610042) 

Hamilt(39061

Hamilton, OH (390618001) 

Jefferson, OH 

(390811001) 

Montgomery, OH 

(391130032) 

Summit, OH (391530017) 

Allegh(42003

Allegheny, PA (420030093) 

Allegheny, PA 

(420030116) 

Allegheny, PA (420031008) 

Allegheny, PA (420031301) 

Beaver(42007

Cambria, PA (420210011) 

Dauphin, PA (420430401) 

Lancaster, PA (420710007) 

York, PA (421330008) 

MontgoTN (47125

Wisconsin 12 

Cook, IL (170310052) 

Cook, IL (170310057) 

Cook, IL (170310076) 

Cook, IL (170311016) 

Cook, (17031

Cook, IL (170313301) 

Cook, IL (170316005) 

Lake, IN (180890022) 

Lake, IN (180890026) 

Scott(19163
E-19

Table E-4. Upwind State-to-Downwind Maintenance Site “Linkages” for 24-Hou

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Moni

Connecticut 1 

New York, NY (360610062) 

Delaware 2 

Cumberland, PA (420410101) 

 New York, NY (360610079) 

Georgia 3 

Baltimore City, MD (245100035) 

Lucas, OH (390950026) 

Preble, OH (391351001) 

Illinois 29 

District of Columbia (110010041) 

District of Columbia (110010042) 

Elkhart, IN (180390003) 

Floyd, IN (180431004) 

Vigo, (1816

Bullitt, KY (210290006) 

McCracken, KY (211451004) 

Warren, KY (212270007) 

Wayne, MI (261630001) 

St. LoCity, (2951

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350034) 

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas(3909

Montgomery, OH (391130031) 

Preble, OH (391351001) 

Trumbull, OH (391550007) 

Allegheny, PA (420030095) 

AlleghPA (4200

Sumner, TN (471650007) 

Brooke, WV (540090005) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukes(5513

Indiana 34 

District of Columbia (110010041) 

District of Columbia (110010042) 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, (1703

Will, IL (171971002) 

Muscatine, IA (191390015) 

Bullitt, KY (210290006) 

McCracken, KY (211451004) 

Warren(2122

Wayne, MI (261630001) 

St. Louis City, MO (295100085) 

New York, NY (360610062) 

New York, NY (360610079) 

Cuyaho(3903

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas, OH (390950026) 

Mahoning, OH (390990014) 

MontgoOH (3911

Trumbull, OH (391550007) 

Allegheny, PA (420030095) 

Allegheny, PA (420033007) 

Cumberland, PA (420410101) 

WashinPA (4212
E-20

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Moni

Brooke, WV (540090005) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Iowa 9 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, IL (170314007) 

Will, IL (171971002) 

Elkhar(1803

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Kansas 2 

Muscatine, IA (191390015) 

Milwaukee, WI (550790059) 

Kentucky 33 

District of Columbia (110010041) 

District of Columbia (110010042) 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, (1703

Will, IL (171971002) 

Elkhart, IN (180390003) 

Floyd, IN (180431004) 

Vigo, IN (181670023) 

MuscatIA (1913

Wayne, MI (261630001) 

St. Louis City, MO (295100085) 

New York, NY (360610062) 

New York, NY (360610079) 

Cuyaho(3903

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas, OH (390950026) 

Mahoning, OH (390990014) 

MontgoOH (3911

Trumbull, OH (391550007) 

Allegheny, PA (420030095) 

Allegheny, PA (420033007) 

Washington, PA (421255001) 

Sumner(4716

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Maryland/DC 5 

New York, NY (360610062) 

New York, NY (360610079) 

Cumberland, PA 

(420410101) 

Massachusetts 1 

New York, NY (360610062) 

Michigan 28 

District of Columbia (110010041) 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, IL (170314007) 

Saint IL (1716

Elkhart, IN (180390003) 

Vigo, IN (181670023) 

Muscatine, IA (191390015) 

Warren, KY (212270007) 

St. LoCity, (2951
E-21

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Moni

Cuyahoga, OH (390350034) 

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas, OH (390950026) 

Mahon(3909

Preble, OH (391351001) 

Trumbull, OH (391550007) 

Allegheny, PA (420030095) 

Allegheny, PA (420033007) 

WashinPA (4212

Brooke, WV (540090005) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Minnesota 4 

Muscatine, IA (191390015) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Missouri 20 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, IL (170314007) 

Saint Clair, IL (171630010)

Will, (1719

Floyd, IN (180431004) 

Vigo, IN (181670023) 

Muscatine, IA (191390015) 

Bullitt, KY (210290006) 

McCracKY (2114

Jefferson, OH (390810017) 

Lucas, OH (390950026) 

Montgomery, OH 

(391130031) 

Preble, OH (391351001) 

Sumner(4716

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Nebraska 2 

Muscatine, IA (191390015) 

Milwaukee, WI (550790059) 

New Jersey 5 

District of Columbia (110010041) 

Anne Arundel, MD (240031003)

New York, NY (360610062) 

New York, NY (360610079) 

CumberPA (4204

New York 9 

District of Columbia (110010041) 

District of Columbia (110010042) 

Anne Arundel, MD (240031003) 

Baltimore City, MD (245100035) 

Cuyaho(3903

Lucas, OH (390950024) 

Lucas, OH (390950026) 

Cumberland, PA 

(420410101) 

North Carolina 3 

Baltimore City, MD (245100035) 

New York, NY (360610062) 

New York, NY (360610079) 

Ohio 29 

District of Columbia (110010041) 

District of Columbia (110010042) 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, (1703
E-22

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Moni

Will, IL (171971002) 

Elkhart, IN (180390003) 

Floyd, IN (180431004) 

Vigo, IN (181670023) 

MuscatIA (1913

McCracken, KY (211451004) 

Warren, KY (212270007) 

Anne Arundel, MD (240031003) 

Baltimore City, MD (245100035) 

Wayne(2616

New York, NY (360610062) 

New York, NY (360610079) 

Allegheny, PA (420030095) 

Allegheny, PA (420033007) 

CumberPA (4204

Sumner, TN (471650007) 

Brooke, WV (540090005) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukes(5513

Pennsylvania 32 

District of Columbia (110010041) 

District of Columbia (110010042) 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, (1703

Will, IL (171971002) 

Elkhart, IN (180390003) 

Floyd, IN (180431004) 

Vigo, IN (181670023) 

MuscatIA (1913

Warren, KY (212270007) 

Anne Arundel, MD (240031003)

Baltimore City, MD (245100035) 

Wayne, MI (261630001) 

New Yo(3606

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350034) 

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas(3909

Montgomery, OH (391130031) 

Preble, OH (391351001) 

Trumbull, OH (391550007) 

Sumner, TN (471650007) 

Brooke(5400

Milwaukee, WI (550790059) 

Waukesha, WI (551330027) 

Tennessee 21 

Cook, IL (170314007) 

Saint Clair, IL (171630010)

Will, IL (171971002) 

Elkhart, IN (180390003) 

Floyd(1804

Muscatine, IA (191390015) 

Bullitt, KY (210290006) 

McCracken, KY (211451004) 

Warren, KY (212270007) 

Wayne(2616

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas, OH (390950026) 

Mahoning, OH (390990014) 

MontgoOH (3911

Trumbull, OH (391550007) 

Allegheny, PA (420033007) 

Washington, PA 

(421255001) 
E-23

Upwind State 

Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Moni

Virginia 7 

District of Columbia (110010041) 

District of Columbia (110010042) 

Anne Arundel, MD (240031003) 

Baltimore City, MD (245100035) 

New Yo(3606

Cumberland, PA (420410101) 

West Virginia 35 

District of Columbia (110010041) 

District of Columbia (110010042) 

Cook, IL (170310050) 

Cook, IL (170314007) 

Saint IL (1716

Elkhart, IN (180390003) 

Floyd, IN (180431004) 

Vigo, IN (181670023) 

Muscatine, IA (191390015) 

Bullit(2102

Anne Arundel, MD (240031003)

Baltimore City, MD (245100035) 

Wayne, MI (261630001) 

St. Louis City, MO (295100085) 

New Yo(3606

Cuyahoga, OH (390350027) 

Cuyahoga, OH (390350034) 

Jefferson, OH (390810017) 

Lucas, OH (390950024) 

Lucas(3909

Montgomery, OH (391130031) 

Preble, OH (391351001) 

Trumbull, OH (391550007) 

Allegheny, PA (420030095) 

AlleghPA (4200

Washington, PA (421255001) 

Sumner, TN (471650007) 

Dane, WI (550250047) 

Milwaukee, WI (550790059) 

Waukes(5513

Wisconsin 6 

Cook, IL (170310022) 

Cook, IL (170310050) 

Cook, IL (170314007) 

Will, IL (171971002) 

Elkhar(1803
E-24

Table E-5. Upwind State-to-Downwind Nonattainment “Linkages” for 8-hour Oz

Upwind State 

Number of Linkages 

Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (MonitSite ID) 

Alabama 8 

East Baton Rouge, LA (220330003) 

Brazoria, TX (480391004) 

Harris, TX (482010051) 

Harris, TX (482010055)

Harris, TX (482010062)

Ha(4

Harris, TX (482011039) 

Tarrant, TX (484391002) 

Arkansas 3 

East Baton Rouge, LA (220330003) 

Brazoria, TX (480391004) 

Tarrant, TX (484391002) 

Connecticut 1 

Suffolk, NY (361030009) 

Delaware 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

Florida 2 

Harris, TX (482010062) 

Tarrant, TX (484391002) 

Georgia 7 

Brazoria, TX (480391004) 

Harris, TX (482010051) 

Harris, TX (482010055) 

Harris, TX (482010062)

Harris, TX (482010066)

Ha(4

Tarrant, TX (484391002) 

Illinois 2 

Suffolk, NY (361030009) 

Harris, TX (482010055) 

Indiana 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

Kentucky 6 

Suffolk, NY (361030002) 

Philadelphia, PA (421010024) 

Harris, TX (482010051) 

Harris, TX (482010055)

Harris, TX (482010062)

Ha(4

Louisiana 7 

Brazoria, TX (480391004) 

Harris, TX (482010051) 

Harris, TX (482010055) 

Harris, TX (482010062)

Harris, TX (482010066)

Ha(4

Tarrant, TX (484391002) 
E-25

Upwind State 

Number of Linkages 

Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (MonitSite ID) 

Maryland/DC 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

Michigan 1 

Suffolk, NY (361030009) 

Mississippi 8 

East Baton Rouge, LA (220330003) 

Brazoria, TX (480391004) 

Harris, TX (482010051) 

Harris, TX (482010055)

Harris, TX (482010062)

Ha(4

Harris, TX (482011039) 

Tarrant, TX (484391002) 

New Jersey 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

North Carolina 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

Ohio 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 

Oklahoma 1 

Tarrant, TX (484391002) 

Pennsylvania 2 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Tennessee 7 

Philadelphia, PA (421010024) 

Brazoria, TX (480391004) 

Harris, TX (482010051) 

Harris, TX (482010055)

Harris, TX (482010062)

Ha(4

Harris, TX (482011039) 

Texas 1 

East Baton Rouge, LA (220330003) 

Virginia 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 
E-26

Upwind State 

Number of Linkages 

Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (MonitSite ID) 

West Virginia 3 

Suffolk, NY (361030002) 

Suffolk, NY (361030009) 

Philadelphia, PA (421010024) 
E-27

Table E-6. Upwind State-to-Downwind Maintenance “Linkages” for 8-Hour Ozon

Upwind State 

Number of Linkages Counties Containing Downwind 8-Hour Ozone Maintenance Sites (Monitor

Alabama 6 

DeKalb, GA (130890002) 

Fulton, GA (131210055) 

Harris, TX (482010024) 

Harris, TX (482010029) 

Harris, TX (482011050) 

Arkansas 4 

Dallas, TX (481130069) 

Dallas, TX (481130087) 

Harris, TX (482011050) 

Tarrant, TX (484392003) 

Connecticut 1 

Westchester, NY (361192004) 

Delaware 1 

Bucks, PA (420170012) 

Florida 4 

DeKalb, GA (130890002) 

Fulton, GA (131210055) 

Harris, TX (482010024) 

Harris, TX (482010029) 

Georgia 4 

Harris, TX (482010024) 

Harris, TX (482010029) 

Harris, TX (482011050) 

Tarrant, TX (484392003) 

Indiana 4 

Fairfield, CT (90010017) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

Bucks, PA (420170012) 

Kansas 1 

Dallas, TX (481130069) 

Kentucky 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

Louisiana 6 

Dallas, TX (481130069) 

Dallas, TX (481130087) 

Harris, TX (482010024) 

Harris, TX (482010029) 

Harris, TX (482011050) 

Maryland/DC 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

Mississippi 7 

DeKalb, GA (130890002) 

Fulton, GA (131210055) 

Dallas, TX (481130087) 

Harris, TX (482010024) 

Harris, TX (482010029) 

Tarrant, TX (484392003) 
E-28

New Jersey 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

New York 5 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Bucks, PA (420170012) 

North Carolina 5 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

Bucks, PA (420170012) 

Ohio 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

Oklahoma 3 

Dallas, TX (481130069) 

Dallas, TX (481130087) 

Tarrant, TX (484392003) 

Pennsylvania 5 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

South Carolina 2 

Fulton, GA (131210055) 

Harris, TX (482010029) 

Tennessee 5 

DeKalb, GA (130890002) 

Fulton, GA (131210055) 

Bucks, PA (420170012) 

Harris, TX (482010024) 

Harris, TX (482011050) 

Virginia 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 

West Virginia 6 

Fairfield, CT (90010017) 

Fairfield, CT (90011123) 

Fairfield, CT (90013007) 

New Haven, CT (90093002) 

Westchester, NY (361192004) 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix F 

Summary of Aggregated Emissions of SO2 and NOx 

For States Included in the Transport Rule 
F-2

Table F-1. Group1 and Group 2 States NOX Total Emissions (not including fires) for each Modeling 

2005 Base 

Year 

2012 Base 

Case 

2014 Base 

Case 

2014 

Remedy 

2014 

Remedy - 

2012 Base 

Case 

Percen

Change

2014 

Remed

vs 2012 

Base 

Case 

Annual Total NOx Emissions for 15 States in Group 1 8,111,227 5,952,260 5,531,877 5,018,570 -933,690 -15.7% Annual Total NOx Emissions for 12 States + DC in Group 2 4,610,746 3,574,961 3,361,673 3,137,064 -437,897 -12.2% Annual Total NOx for 27 States + DC 12,721,973 9,527,221 8,893,550 8,155,634 -1,371,587 -14.4% Annual Total NOx Emissions for All States Fully within the Eastern Modeling Domain 15,862,117 11,997,188 11,207,626 10,388,190 -1,608,998 -13.4% Annual Total NOx Emissions for All Western States 3,669,688 2,882,771 2,699,187 2,699,522 -183,249 -6.4% 
F-3

Table F-2. Group1 and Group 2 States SO2 Total Emissions (not including fires) for each Modeling 

2005 Base 

Year 

2012 Base 

Case 

2014 Base 

Case 

2014 

Remedy 

2014 

Remedy - 

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

Annual Total SO2 Emissions for 15 States in Group 1 9,040,217 9,146,651 8,087,579 3,792,063 -5,354,589 -58.5% Annual Total SO2 Emissions for 12 States + DC in Group 2 3,133,554 2,243,946 2,198,166 1,869,543 -374,403 -16.7% Annual Total SO2 for 27 States + DC Covered for PM2.5 12,173,771 11,390,598 10,285,746 5,661,606 -5,728,992 -50.3% Annual Total SO2 Emissions for All States Fully within the Eastern Modeling Domain 13,810,921 12,639,283 11,583,637 7,123,638 -5,515,645 -43.6% Annual Total SO2 Emissions for All Western States 852,154 700,400 697,838 733,479 33,079 4.7% 
F-4

Table F-3. Group1 and Group 2 States NOX EGU Sector Emissions for each Modeling Scena

2005 Base 

Year 

2012 Base 

Case 

2014 Base 

Case 

2014 

Remedy 

2014 

Remedy 

- 2012 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

Annual EGU NOx Emissions for 15 States in Group 1 1,945,446 1,445,575 1,432,270 918,963 -526,613 -36.4% Annual EGU NOx Emissions for 12 States + DC in Group 2 831,991 632,031 626,150 401,542 -230,489 -36.5% Annual EGU NOx for 27 States + DC Covered for PM2.5 2,777,437 2,077,606 2,058,421 1,320,505 -757,101 -36.4% Annual EGU NOx Emissions for All States Fully within the Eastern Modeling Domain 3,223,184 2,485,856 2,468,057 1,648,621 -837,234 -33.7% Annual EGU NOx Emissions for All Western States 504,928 440,572 440,787 441,121 550 0.1% 
F-5

Table F-4. Group1 and Group 2 States SO2 EGU Sector Emissions for each Modeling Scena

2005 Base 

Year 

2012 Base 

Case 

2014 Base 

Case 

2014 

Remedy 

2014 

Remedy - 

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

Annual EGU SO2 Emissions for 15 States in Group 1 7,040,088 7,349,814 6,303,300 2,007,783 -5,342,031 -72.7% Annual EGU SO2 Emissions for 12 States + DC in Group 2 1,989,050 1,164,259 1,118,141 789,518 -374,740 -32.2% Annual EGU SO2 for 27 States + DC Covered for PM2.5 9,029,138 8,514,073 7,421,441 2,797,302 -5,716,771 -67.1% Annual EGU SO2 Emissions for All States Fully within the Eastern Modeling Domain 10,019,774 9,243,362 8,209,536 3,749,537 -5,493,825 -59.4% Annual EGU SO2 Emissions for All Western States 361,634 256,561 260,283 295,924 39,364 15.3% 
F-6

Table F-5. 26-State Total and Electric Generating Unit Sector Summer NOX Emissions for each Mode

2005 Base 

Year 

2012 Base 

Case 

2014 Base 

Case 

2014 

Remedy 

2014 

Remedy 

- 2012 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

Summer EGU NOx Emissions for 26 States Included for Ozone 905,345 718,142 698,827 585,584 -132,559 -18.5% Summer Total NOx Emissions for 26 States Included for Ozone 5,363,278 4,085,516 3,784,430 3,671,187 -414,329 -10.1% 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix G 

Concentration and Difference Maps for 

Annual PM2.5, 24-Hour PM2.5, and 8-Hour Ozone 
Annual PM2.5 Maps 
2003-2007 Average Ambient Annual PM2.5 Concentrations 

2012 Base Case Annual PM2.5 Concentrations
2014 Base Case Annual PM2.5 Concentrations

2014 Remedy Annual PM2.5 Concentrations
2014 Remedy – 2012 Base Case Difference in Annual PM2.5 Concentrations

2014 Remedy – 2014 Base Case Difference in Annual PM2.5 Concentrations
24-Hour PM2.5 Maps 
2003-2007 Average Ambient 24-Hour PM2.5 Concentrations 

2012 Base Case 24-Hour PM2.5 Concentrations 
2014 Base Case 24-Hour PM2.5 Concentrations 

2014 Remedy 24-Hour PM2.5 Concentrations
2014 Remedy – 2012 Base Case Difference in 24-Hour PM2.5 Concentrations

2014 Remedy – 2014 Base Case Difference in 24-Hour PM2.5 Concentrations
8-Hour Ozone Maps 
2003-2007 Average Ambient 8-Hour Ozone Concentrations 

2012 Base Case 8-Hour Ozone Concentrations 
2014 Base Case 8-Hour Ozone Concentrations 

2014 Remedy 8-Hour Ozone Concentrations 
2014 Remedy – 2012 Base Case Difference in 8-Hour Ozone Concentrations 

2014 Remedy – 2014 Base Case Difference in 8-Hour Ozone Concentrations 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix H 

Quarterly “Exceedances” of the 

24-Hour PM2.5 NAAQS for the 

2014 Base Case and 2014 Remedy Scenario 
H-2

As described in Section III of the Air Quality Modeling Technical Support 

Document, EPA projected a 24-hour PM2.5 concentration for each calendar quarter 

for each of 5 years of ambient quarterly data (2003 through 2007). These projected 

quarterly concentrations were used in the calculation of future case design values 

for the 24-hour PM2.5 NAAQS. This appendix provides the quarterly 24-hour 

PM2.5 concentrations for the 2014 Base Case and 2014 Remedy scenario for the 

monitoring sites projected to be nonattainment and/or maintenance sites based on 

modeling of the 2014 Remedy scenario. The quarterly values that exceed the 35 

μg.m3

 24-hour PM2.5 NAAQS are in red. 
H-3

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 28.70 27.89 37.84 24.65 30.28 22.07 2004 27.95 27.16 27.31 17.84 27.53 20.07 2005 48.84 47.45 26.83 17.53 35.70 25.99 2006 26.45 25.70 29.65 19.36 25.30 18.46 

Ann Arbor, MI (Washtenaw Co) 261610008 

2007 19.24 18.70 26.44 17.28 30.73 22.39 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 39.26 37.83 26.92 21.97 32.84 24.81 2004 37.06 35.71 26.92 21.97 28.55 21.59 2005 36.26 34.94 24.24 19.79 30.69 23.20 2006 29.15 28.09 25.85 21.10 27.26 20.62 

Baltimore, MD (Anne Arundel Co) 240031003 

2007 27.54 26.54 24.60 20.08 29.92 22.62 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 35.78 34.67 35.89 29.73 34.71 27.18 2004 35.97 34.86 35.98 29.80 34.45 26.99 2005 37.95 36.78 28.44 23.57 31.57 24.74 2006 33.41 32.38 30.68 25.42 30.64 24.01 

Baltimore, MD (Baltimore City) 245100040 

2007 31.61 30.64 30.50 25.28 29.88 23.42 
H-4

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 29.55 28.54 35.27 31.61 33.43 29.87 2004 34.82 33.62 36.74 32.93 36.16 32.30 2005 34.82 33.62 43.46 38.93 42.98 38.39 2006 27.49 26.54 33.89 30.37 33.51 29.94 

Birmingham, AL (Jefferson Co) 10730023 

2007 40.27 38.88 38.86 34.82 36.24 32.38 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 34.79 33.79 34.71 30.35 33.39 25.69 2004 30.96 30.07 21.97 19.24 34.73 26.71 2005 36.94 35.88 30.15 26.38 39.65 30.48 2006 28.99 28.17 26.53 23.21 26.06 20.07 

Chicago, IL (Cook Co) 170310052 

2007 36.84 35.79 34.90 30.51 31.34 24.11 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 42.17 41.34 37.47 31.67 30.36 23.07 2004 34.30 33.63 24.15 20.45 26.45 20.11 2005 45.26 44.37 36.07 30.50 45.83 34.75 2006 26.34 25.83 25.73 21.78 27.43 20.85 

Chicago, IL (Cook Co)  170311016 

2007 29.43 28.86 34.30 29.00 30.54 23.20 
H-5

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2004 35.21 34.47 20.18 16.99 33.31 24.29 2005 47.47 46.47 31.61 26.57 41.62 30.32 2006 25.12 24.59 28.14 23.66 25.26 18.46 

Chicago, IL (Cook Co) 170313103 

2007 34.55 33.82 32.92 27.66 23.67 17.30 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 35.64 34.94 21.78 18.39 29.89 22.54 2004 33.23 32.57 21.13 17.84 38.05 28.66 2005 45.55 44.66 33.45 28.20 38.85 29.26 2006 24.14 23.67 23.18 19.57 24.61 18.58 

Chicago, IL (Cook Co) 170313301 

2007 28.50 27.94 31.12 26.24 27.92 21.06 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 36.02 35.17 31.63 28.03 32.29 24.52 2004 39.76 38.82 21.38 18.96 35.15 26.68 2005 40.22 39.28 29.21 25.88 38.99 29.58 2006 27.14 26.50 23.15 20.53 26.13 19.86 

Chicago, IL (Cook Co) 170316005 

2007 24.15 23.58 34.43 30.50 29.70 22.56 
H-6

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 41.69 40.51 43.69 33.18 39.77 28.64 2004 36.21 35.19 34.37 26.13 37.98 27.36 2005 40.11 38.97 33.35 25.36 45.85 33.00 2006 33.52 32.58 31.78 24.17 26.89 19.41 

Cleveland, OH (Cuyahoga Co) 390350038 

2007 23.97 23.30 31.78 24.17 35.56 25.63 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 32.43 31.54 32.97 24.95 40.64 28.46 2004 39.10 38.02 32.97 24.95 30.74 21.57 2005 45.86 44.59 34.91 26.41 43.23 30.27 2006 28.73 27.94 27.25 20.64 27.44 19.27 

Cleveland, OH (Cuyahoga Co) 390350060 

2007 25.58 24.88 29.19 22.10 34.57 24.24 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 32.75 32.11 31.36 20.97 32.34 22.63 2004 28.58 28.03 27.32 18.28 28.73 20.12 2005 49.39 48.42 27.32 18.28 38.69 27.05 2006 28.30 27.75 31.08 20.78 20.26 14.23 

Detroit, MI (Oakland Co) 261250001 

2007 20.26 19.87 31.18 20.84 31.20 21.84 
H-7

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 43.47 42.81 40.03 29.18 38.35 27.99 2004 30.31 29.85 29.61 21.61 34.16 24.95 2005 48.74 47.99 36.72 26.77 41.29 30.12 2006 34.73 34.20 31.98 23.33 23.39 17.12 

Detroit, MI (Wayne Co) 261630016 

2007 24.48 24.11 27.52 20.10 30.60 22.36 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 34.89 34.24 29.88 20.40 28.21 19.71 2004 30.85 30.28 26.92 18.40 30.66 21.41 2005 49.18 48.26 47.15 32.10 38.71 26.99 2006 34.05 33.41 29.88 20.40 18.95 13.29 

Detroit, MI (Wayne Co) 261630019 

2007 23.15 22.72 25.87 17.69 27.95 19.53 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 38.26 37.68 36.67 26.81 38.31 28.17 2004 32.62 32.13 37.43 27.36 31.34 23.07 2005 47.18 46.46 34.20 25.01 40.10 29.48 2006 40.51 39.90 30.88 22.59 27.23 20.06 

Detroit, MI (Wayne Co) 261630033 

2007 30.27 29.82 34.77 25.43 32.77 24.12 
H-8

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 33.28 32.57 33.12 22.31 27.42 18.26 2004 30.89 30.23 27.76 18.73 27.68 18.44 2005 44.65 43.70 29.39 19.82 39.26 26.08 2006 30.60 29.95 31.78 21.42 24.17 16.12 

Detroit, MI (Wayne Co) 261630036 

2007 26.97 26.40 27.38 18.47 24.79 16.53 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 39.21 38.42 36.45 29.75 31.32 24.53 2004 34.02 33.34 27.07 22.12 31.71 24.83 2005 40.17 39.36 43.09 35.15 41.92 32.79 2006 27.01 26.47 35.47 28.95 32.50 25.45 

East St Louis, MO (Madison Co, IL) 171191007 

2007 25.76 25.25 34.49 28.16 35.35 27.67 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 43.12 41.96 26.83 20.62 27.94 20.86 2004 40.31 39.22 22.73 17.48 30.95 23.10 2005 37.39 36.39 29.50 22.66 35.82 26.71 2006 26.79 26.07 22.54 17.34 24.40 18.23 

Gary, IN (Lake Co, IN) 180890022 

2007 33.08 32.19 32.17 24.70 27.41 20.47 
H-9

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 39.06 37.65 27.17 20.62 32.15 24.71 2004 36.15 34.86 27.07 20.55 33.22 25.53 2005 36.34 35.04 32.73 24.82 39.01 29.96 2006 26.89 25.93 24.86 18.89 27.15 20.89 

Gary, IN (Lake Co, IN) 180890026 

2007 27.73 26.74 29.95 22.72 29.29 22.53 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2006 38.67 37.97 35.94 29.48 36.29 29.94 2007 32.23 31.65 28.31 23.24 30.21 24.94 

Jersey City, NJ (Hudson Co) 340172002 2008 No Data No Data No Data No Data 32.62 26.93 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 45.22 43.44 40.72 30.96 36.70 24.70 2004 33.46 32.15 32.04 24.39 28.51 19.23 2005 39.72 38.16 25.63 19.53 38.22 25.72 2006 33.65 32.33 28.97 22.06 29.19 19.68 

Lancaster, PA (Lancaster Co) 420710007 

2007 38.18 36.68 25.17 19.18 28.01 18.89 
H-10

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 31.80 31.21 20.47 17.02 26.34 20.04 2004 36.77 36.09 20.57 17.10 32.57 24.75 2005 37.06 36.38 24.02 19.96 31.40 23.87 2006 38.97 38.25 25.23 20.96 23.90 18.19 

Milwaukee, WI (Milwaukee Co) 550790010 

2007 38.88 38.16 27.19 22.58 28.87 21.95 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 27.73 27.01 22.92 19.05 24.57 17.94 2004 26.48 25.80 21.61 17.97 25.55 18.65 2005 39.67 38.63 24.31 20.21 30.97 22.58 2006 34.60 33.70 24.87 20.67 24.66 18.01 

Milwaukee, WI (Milwaukee Co) 550790026 

2007 38.04 37.05 28.50 23.67 25.19 18.39 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 32.54 31.96 22.64 19.07 35.47 27.10 2004 27.38 26.89 22.18 18.67 36.65 27.99 2005 32.83 32.24 23.67 19.93 33.58 25.65 2006 42.11 41.35 27.69 23.30 23.54 18.03 

MIlwaukee, WI (Milwaukee Co) 550790043 

2007 28.72 28.20 26.19 22.04 25.17 19.26 
H-11

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 29.36 28.56 23.56 19.98 27.90 20.42 2004 29.17 28.38 21.69 18.40 34.66 25.33 2005 35.48 34.51 25.43 21.55 32.70 23.91 2006 36.62 35.63 27.20 23.05 23.27 17.06 

Milwaukee, WI (Milwaukee Co) 550790099 

2007 38.92 37.86 26.36 22.34 26.83 19.64 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 32.17 31.63 24.53 20.77 31.33 25.37 2004 34.55 33.98 36.64 30.98 25.61 20.75 2005 32.93 32.38 29.96 25.35 34.32 27.78 2006 33.60 33.04 36.28 30.68 30.48 24.68 

New York, NY (New York Co) 360610056 

2007 35.13 34.54 29.69 25.13 29.80 24.13 

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 55.27 53.24 58.42 49.46 54.83 46.35 2004 58.74 56.58 52.29 44.27 57.89 48.93 2005 47.95 46.19 61.05 51.68 56.45 47.72 2006 47.50 45.75 47.47 40.20 49.33 41.71 

Pittsburgh, PA (Allegheny Co) 420030064 

2007 49.51 47.69 47.82 40.50 49.33 41.71 
H-12

 Quarter 1 Quarter 2 Quarter 3 

Ambient 

Data Year 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2014 

Base Case 

2014 

Remedy 

2003 28.43 26.07 25.90 16.95 27.12 21.32 2004 40.34 36.97 37.23 24.29 34.08 26.76 2005 28.81 26.42 34.88 22.77 29.69 23.33 2006 33.59 30.79 20.12 13.21 30.68 24.11 

Steubenville, OH (Brooke Co, WV) 540090011 

2007 46.62 42.72 35.74 23.33 32.17 25.27 
Transport Rule Air Quality Modeling Technical Support Document 

Appendix I 

Impacts on Visibility in Class I Areas of the West 
I-2

Impact on visibility (in deciviews) for all Western Class I areas included 

(only) in the 36 km modeling domain. See section V for a description of the 

procedures used in calculating these data. 

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 

20% Worst 

Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 

Visibility 

Change 

from 

Remedy 

(dv) 

Agua Tibia 

Wilderness AGTI California 23.09 22.75 22.51 22.51 0.00 

Alpine Lake 

Wilderness ALLA Washington 17.35 17.17 17.03 17.02 -0.01 

Anaconda-Pintler 

Wilderness ANAC Montana 13.91 13.82 13.79 13.80 0.01 

Ansel Adams 

Wilderness (Minarets) ANAD California 14.90 14.65 14.60 14.60 0.00 

Arches NP ARCH Utah 11.04 10.10 10.14 10.11 -0.03 

Mount Baldy 

Wilderness BALD Arizona 11.27 10.95 10.96 10.82 -0.14 

Bob Marshall 

Wilderness BOMA Montana 14.54 14.43 14.4 14.41 0.01 

Bryce Canyon NP BRCA Utah 11.73 11.38 11.23 11.32 0.09 

Cabinet Mountains 

Wilderness CABI Montana 14.15 13.98 13.94 13.95 0.01 

Canyonlands NP CANY Utah 11.04 10.38 10.35 10.35 0.00 

Capitol Reef NP CAPI Utah 10.63 10.06 10.00 9.98 -0.02 

Caribou Wilderness CARI California 14.19 13.89 13.81 13.81 0.00 

Chiricahua NM CHIR Arizona 13.33 13.05 13.10 12.99 -0.11 

Chiricahua Wilderness CHIW Arizona 13.33 13.05 13.10 12.99 -0.11 

Crater Lake NP CRLA Oregon 14.04 13.86 13.75 13.76 0.01 

Craters of the Moon 

NM CRMO Idaho 14.19 13.89 13.78 13.78 0.00 

Cucamonga 

Wilderness CUCA California 19.35 18.30 17.78 17.80 0.02 

Desolation Wilderness DESO California 12.52 12.31 12.26 12.27 0.01 

Diamond Peak 

Wilderness DIPE Oregon 14.04 13.87 13.79 13.78 -0.01 

Eagle Cap Wilderness EACA Oregon 18.25 18.01 17.85 17.85 0.00 

Emigrant Wilderness EMIG California 17.37 17.11 17.04 17.04 0.00 

Galiuro Wilderness GALI Arizona 13.33 12.95 12.89 12.92 0.03 

Gates of the 

Mountains Wilderness GAMO Montana 11.67 11.54 11.52 11.53 0.01 

Gearhart Mountain 

Wilderness GEMO Oregon 14.04 13.82 13.61 13.6 -0.01 

Gila Wilderness GICL 

New 

Mexico 13.32 13.15 13.11 12.97 -0.14 
I-3

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 

20% Worst 

Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 

Visibility 

Change 

from 

Remedy 

(dv) 

Glacier NP GLAC Montana 19.13 18.80 18.71 18.73 0.02 

Glacier Peak 

Wilderness GLPE Washington 13.78 13.55 13.54 13.54 0.00 

Goat Rocks 

Wilderness GORO Washington 12.88 12.60 11.95 11.97 0.02 

Grand Canyon NP GRCA Arizona 11.85 11.37 11.31 11.32 0.01 

Grand Teton NP GRTE Wyoming 10.94 10.74 10.71 10.72 0.01 

Hells Canyon 

Wilderness HECA Oregon 18.73 18.27 18.02 18.02 0.00 

Hoover Wilderness HOOV California 11.92 11.74 11.72 11.72 0.00 

Jarbidge Wilderness JARB Nevada 12.13 12.03 12.04 12.04 0.00 

John Muir Wilderness JOMU California 14.90 14.53 14.46 14.46 0.00 

Joshua Tree NM JOSH California 19.40 18.22 17.79 17.76 -0.03 

Kaiser Wilderness KAIS California 14.90 14.63 14.57 14.57 0.00 

Kalmiopsis 

Wilderness KALM Oregon 16.31 16.33 16.30 16.38 0.08 

Kings Canyon NP KICA California 23.41 22.50 22.21 22.20 -0.01 

Lava Beds NM LABE California 14.77 14.38 14.31 14.32 0.01 

Lassen Volcanic NP LAVO California 14.19 13.95 13.87 13.88 0.01 

Mazatzal Wilderness MAZA Arizona 13.8 13.25 13.16 13.15 -0.01 

Mount Hood 

Wilderness MOHO Oregon 14.79 14.61 14.51 14.53 0.02 

Mount Jefferson 

Wilderness MOJE Oregon 15.93 15.89 15.84 15.85 0.01 

Mokelumne 

Wilderness MOKE California 12.52 12.36 12.33 12.33 0.00 

Mountain Lakes 

Wilderness MOLA Oregon 14.04 14.02 13.82 13.84 0.02 

Mount Rainier NP MORA Washington 17.56 17.32 17.20 17.23 0.03 

Mount Washington 

Wilderness MOWA Oregon 15.93 15.91 15.87 15.89 0.02 

North Cascades NP NOCA Washington 13.78 13.62 13.60 13.60 0.00 

Olympic NP OLYM Washington 16.14 16.40 16.40 16.41 0.01 

Pasayten Wilderness PASA Washington 15.39 15.11 14.54 14.55 0.01 

Petrified Forest NP PEFO Arizona 13.73 13.11 13.24 13.21 -0.03 

Pine Mountain 

Wilderness PIMO Arizona 13.8 13.19 13.03 12.89 -0.14 

Pinnacles NM PINN California 18.22 17.92 17.80 17.81 0.01 

Point Reyes NS PORE California 22.89 22.82 22.73 22.73 0.00 

San Rafael Wilderness RAFA California 19.04 18.77 18.62 18.63 0.01 

Red Rock Lakes REDR Wyoming 10.94 10.75 10.71 10.72 0.01 

Redwood NP REDW California 18.66 18.81 18.81 18.82 0.01 

San Gabriel SAGA California 19.35 18.30 17.78 17.80 0.02 
I-4

Class I Area 

(IMPROVE Site) 

Site 

Code State 

2002-2006 

Baseline 

Visibility 

20% Worst 

Days 

(dv) 

2012 Base 

Case 

Visibility 

(dv) 

2014 Base 

Case 

Visibility 

(dv) 

2014 

Remedy 

Visibility 

(dv) 

2014 

Visibility 

Change 

from 

Remedy 

(dv) 

Wilderness 

San Gorgonio 

Wilderness SAGO California 21.8 20.66 20.15 20.14 -0.01 

Saguaro NM SAGU Arizona 14.53 13.69 13.43 13.40 -0.03 

San Jacinto 

Wilderness SAJA California 21.8 20.08 19.49 19.49 0.00 

Sawtooth Wilderness SAWT Idaho 14.33 14.25 14.24 14.25 0.01 

Scapegoat Wilderness SCAP Montana 14.54 14.40 14.36 14.38 0.02 

Selway-Bitterroot 

Wilderness SELW Idaho 13.91 13.84 13.83 13.81 -0.02 

Sequoia NP SEQU California 23.41 22.30 21.95 21.95 0.00 

Sierra Ancha 

Wilderness SIAN Arizona 14.37 14.06 13.97 13.92 -0.05 

South Warner 

Wilderness SOWA California 14.77 14.43 14.43 14.43 0.00 

Strawberry Mountain 

Wilderness STMO Oregon 18.25 17.96 17.83 17.82 -0.01 

Superstition 

Wilderness SUPE Arizona 14.01 13.61 13.49 13.47 -0.02 

Sycamore Canyon 

Wilderness SYCA Arizona 15.34 15.02 14.96 15.01 0.05 

Teton Wilderness TETO Wyoming 10.94 10.78 10.76 10.75 -0.01 

Three Sisters 

Wilderness THIS Oregon 15.93 15.91 15.87 15.89 0.02 

Thousand Lakes 

Wilderness THLA California 14.19 13.95 13.87 13.88 0.01 

Ventana Wilderness VENT California 18.22 18.25 18.20 18.20 0.00 

Mount Adams 

Wilderness WHPA Washington 12.88 12.63 12.12 12.15 0.03 

Yellowstone NP YELL Wyoming 10.94 10.77 10.74 10.74 0.00 

Yosemite NP YOSE California 17.37 17.12 17.05 17.05 0.00