# Technical Support Document (TSD)

for the Transport Rule

Docket ID No. EP A-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

# (This page intentionally left blank)

# 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 PM 2.5 

# .................................................... 8

III. Projection of Future Nonattainment and Maintenance for Annual PM 2.5 

# , 24-

Hour PM 2.5 

# , and 8-Hour Ozone .......................................................................................... 8

A. Procedures for Processing Ambient Ozone and PM 2.5 

# Data.......................................... 9

B. Projection of Future Design Values and Determination of

Nonattainment and Maintenance for Annual and 24-Hour PM 2.5 

# .............................. 11

1. Methodology for Projecting Future Annual PM 2.5 

# Nonattainment

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

2. Methodology for Projecting Future 24-Hour PM 2.5 

# Nonattainment

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

C. Projection of Future Desi gn Values and Determination of

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

IV. State by State Source Cont ribution Modeling and Results..................................................... 20

A. Nonattainment and Maintenance Receptors for the Assessment of PM 2.5



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

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

C. Approach to Calculating Cont ributions for Annual and 24-Hour PM 2.5 

# ..................... 30

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

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

1. Contributions to Annual PM 2.5 

# Nonattainment and Maintenance .......................... 37

2. Contributions to 24-Hour PM 2.5 

# Nonattainment and Maintenance......................... 38

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

V. Air Quality Impacts of the Proposed SO 2 

# and NO X 

# Emissions Reductions ............................ 42

A. Characterization of Emissions in 2014 for the Proposed Remedy

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

B. Impacts on Projected PM 2.5 

# Design Value Concentrations......................................... 46

C. Impacts on Annual and 24-Hour PM 2.5 

# Nonattainment and

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

D. Analysis of Residual N onattainment for 24-Hour PM 2.5 

# ............................................. 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 PM 2.5 

# Contribution Calculation Examples

Appendix D.

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

8-Hour Ozone, Annual PM 2.5 

# , and 24-Hour PM 2.5



# Appendix E.

Upwind States to Downwind Nonattainment and Maintenance Linkages

Appendix F.

Summary of Aggregated Emissions of SO 2 

# and NO X 

# for States Included in the Transport

Rule

Appendix G.

Concentration and Difference Maps for Annual PM 2.5 

# , 24-Hour PM 2.5 

# , and 8-Hour Ozone

Appendix H.

Quarterly “Exceedances” of the 24-Hour PM 2.5 

# NAAQS for the 2014 Base Case and 2014

Remedy Scenario

Appendix I.

Impacts on Visibility in Cl ass 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 Prot ection Agency’s Transport Rule proposal

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

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

for annual (average) PM 2.5 

# , 24-hour PM 2.5 

# , and/or 8-hour ozone for the analytic

years chosen for the TR,

(2) quantify the impacts (i.e., ai r quality contributions) of SO 2 

# and NO X 

# emissions

from upwind states on downwind annual and 24-hour PM 2.5 

# concentrations at

monitoring sites projected to be nonattainme nt or have maintenance problems in

2012 for the 1997 annual and 2006 24-hour PM 2.5 

# NAAQS 1 

# , respectively,

(3) quantify the contributions of NO X 

# 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 PM 2.5 

# concentrations for

future year scenarios,

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

PM 2.5 

# , and 8-hour ozone,

(5) the results of evaluating the inters tate contributions using concentration

thresholds, and

(6) the air quality impacts from the SO 2 

# and NO X 

# 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 f our 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 th e 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 PM 2.5 

# , 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. Th e 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 PM 2.5 

# and ozone using corresponding ambient

measurements. Section III defines the pr ocedures for projecting future case PM 2.5 

# and

ozone concentrations and the approach fo r determining locations with projected

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

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

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

contributions to determine which State are cove red 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 step s 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 Extension 2 

# (CAMx) version

5 to simulate ozone and PM 2.5 

# 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 inte rstate transport of ozone and PM 2.5 

# . CAMx is a

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

chemical transformation, transport, and rem oval of ozone, secondary and directly emitted

PM 2.5 

# , 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 Texa s 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 mode ling domain was nested within a coarse

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

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

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

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

provide initial and boundary c oncentrations 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 apportionmen t modeling was performed for the 37 States

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

are shown in Figure II-1. Table II-1 pr ovides 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) estima tes of intercontinen tal transport (i.e.,

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

2 

# Comprehensive Air Quality Model with Exte nsions Version 5 User’s Guide. Environ

International Corporation. Novato, CA. March 2009.

# 4 CAMx was run to generate hourly predictions of ozone and PM 2.5 

# component species

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

meteorological inputs and in itial and boundary concentratio ns for the CONUS domain

are described below. The emissions inventor ies used in the TR ai r 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. Th e 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 concentra tions were derived from the parent 36 km

simulations.

D. Meteorological Input Data

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

meteorological input data for 2005 were deri ved from simulations of the Pennsylvania

State University / National Center for Atmo spheric 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 m odel 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 te mperature and moisture was applied

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

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

10 4 

# for wind fields and temperatures and 1.0 x 10 5 

# for moisture fields. The 12 km domain

nudging weighting factors were 1.0 x 10 4 

# for wind fields and temperatures and 1.0 x 10 5



# 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 ar e shown in Table II-2 and do not vary by

horizontal grid resolution. Th e 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 fo r 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

10 0.920 631 928 6

11 0.910 712 919

12 0.900 794 910

13 0.880 961 892 7

14 0.860 1,130 874

15 0.840 1,303 856

16 0.820 1,478 838 8

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

25 0.450 5,461 505 12

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 performan ce evaluation to assess the adequacy of the

MM5 simulated fields. The qualitative as pects of this evaluation included the

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

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

patterns of monthly average rainfall and monthly maximum planetary boundary layer

(PBL) heights. Qualitatively, the model fi elds closely matched the observed synoptic

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

was performed using statistical comparis ons of model/observe d 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 investig ated: temperature, humidity, shortwave

downward radiation, wind speed, and wind di rection. 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 we re generally within

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

applications.

E. Initial and Boundary Concentrations

The lateral boundary and init ial species concentrations are provided by a threedimensional global atmospheric chem istry model, the GEOS-CHEM model 7 

# (standard

version 7-04-11 8 

# ). The global GEOS-CHEM model simulates atmospheric chemical and

physical processes driven by assimilated me teorological 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 de gree (latitude-longitude ) and 30 vertical

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

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

simulations. The concentrations from th e 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 Simu lation, 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. Kro ll, T-M. Fu, D.J. Jacob, C.L. Heald, 2008. Global

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

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

# 8 F. Model Performance Evaluation for Ozone and PM 2.5



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

nitrate, ammonium, organic carbon, elemen tal carbon, and crustal material were

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

modeling platform for replic ating observed concentrati ons. This evaluation was

comprised of statistical compar isons of paired modeled and ob served 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 PM 2.5



# . Overall, the model performance statistics for these pollutants are

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

bias for 8-hour daily maximum ozone concentr ations 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 with in the 12 km modeling domain. For the

summer months of June though August, when obs erved 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 an d 9 to 10 percent at rural

sites in the IMPROVE 9 

# and CASTNET 10 

# monitoring networks, respectively. For the

winter months of December through Februar y, when observed nitrate concentrations are

highest in the East, the mode l predictions of 24-hour averag e particulate nitrate were

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

percent at rural sites in the IMPROVE monitoring network.



# III. Projection of Future Nonatta inment and Maintenance for Annual

PM 2.5 

# , 24-Hour PM 2.5 

# , and 8-Hour Ozone

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

ozone and PM 2.5 

# to identify locations that are exp ected 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 PM 2.5 

# monitoring sites. The nonattainment and

9 

# I nteragency M onitoring of PRO tected V isual E nvironments (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 (CA STNET) 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 “receptor s” for quantifying the

contributions of emissions in upwind stat es to nonattainment and maintenance in

downwind locations. Future year concentr ations 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 PM 2.5 

# air quality.

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

to project future concentrations of ozone and PM 2.5 

# . Rather than use the absolute modelpredicted future year ozone and PM 2.5 

# concentrations, the base year and future year

predictions are used to ca lculate a (relative) percen t change in ozone and PM 2.5



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

model predictions are used to adjust ambient measured da ta 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 he lps to constrain the future year predictions, even if the

absolute model concentrations are over-pre dicted or under-predict ed. As described

below, the procedures for pr ojecting annual and 24-hour PM 2.5 

# and 8-hour ozone conform

to the methodologies contained in the fina l guidance for attainment demonstration

modeling 11 

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

A. Procedures for Processing Ambient Ozone and PM 2.5 

# Data

In this analysis we use measurements of ambient ozone and PM 2.5 

# 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) PM 2.5 

# sites in the

Eastern U.S.. In addition, speciated PM 2.5 

# data from the Chemical Speciation Network

(CSN) and IMPROVE network are used to estimate PM 2.5 

# 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. Th e 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 M odels and Other Analyses for Demonstrating

Attainment of Air Quality Goals for Ozone, PM 2.5 

# , 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 maximu m 8-hour O3 concentra tion is greater than

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

value.

The PM 2.5 

# ambient data were processed consis tent with the formats associated

with the NAAQS for PM 2.5 

# . For PM 2.5 

# , we evaluated concentra tions of both the annual

PM 2.5 

# NAAQS and the 24-hour PM 2.5 

# NAAQS. The annual PM 2.5 

# standard is not met if

the 3-year average of the annual mean concentration is greater than 15.0 μg/m 3 

# (15.05

μg/m 3 

# when rounded up). The 3-year average annu al 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 a nnual mean concentrati on is referred to as

the annual design value.

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



# percentile PM 2.5 

# concentration is greater than 35 μg/m 3 

# (35.5 μg/m 3 

# when rounded up).

The 3-year average mean 98 th 

# percentile concentration is computed at each site by

averaging the 3 individual annual 98 th 

# percentile values at each site. The 3-year average

98 th 

# percentile concentra tion 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 th e base period ozone and PM 2.5 

# concentrations. Specifically,

we used ambient ozone and annual and 24-hour PM 2.5 

# design values for the periods 2003-

2005, 2004-2006, and 2005-2007 as the starting point fo r 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 complete 12 

# design value in the 2003-2007 period. 13 

# There were 721

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

design value period for the annual PM 2.5 

# NAAQS, and 736 sites which met this criteria

12 

# Design value completeness was determined acco rding to the monitoring rules in CFR 40 Part

50 Appendix I (8-hour ozone) and A ppendix 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 NAAQS 14 

# 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 PM 2.5



# As noted above, the projection methodology for PM 2.5 

# involves using the model

predictions in a relative sense to estimate the change in PM 2.5 

# between 2005 and each

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

concentration is multiplied by the corre sponding 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 PM 2.5 

# design values is called the Speciated

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

available from EPA called MATS 15 

# . The software (including do cumentation) is available

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

.

As described below, design values of PM 2.5 

# in 2012 and 2014 were estimated by

applying the 2005 to 2012 or 2005 to 2014 rela tive change in model-predicted PM 2.5



# species concentrations to the measured (2003-2007) PM 2.5 

# species concentrations. The

PM 2.5 

# species include sulfate, nitrate, amm onium, particle bound wa ter, elemental carbon,

salt, other primary PM 2.5 

# , and organic aerosol mass (by difference). Organic aerosol

mass by difference is defined as the difference between FRM PM 2.5 

# and the sum of the

other components.

For each FRM PM 2.5 

# 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 we ighted average, where the middle year is

weighted 3 times, the 2 nd 

# and 4 th 

# years are weighted twice, and the 1 st 

# and 5 th 

# 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 PM 2.5 

# NAAQS are

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

15 

# U.S. EPA, 2009: Modeled Attainme nt Test Software; User’s Manual

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

# 12 also projected design values fo r each of the individual 3-year design value periods (i.e.,

2003-2005, 2004-2006, and 2003-2007). The project ion 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 PM 2.5 

# Nonattainment and

Maintenance

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

PM 2.5 

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

MATS documentation.

Base period (i.e., 2003 – 2007) FRM data are the starting po int 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 PM 2.5 

# speciation is needed for the location

of each FRM monitoring site. Since co-located PM 2.5 

# speciation data are only available

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

calculate species concentrations for each FR M 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 techni ques and data handling proc edures can be found in the

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

following procedures were used to es timate future year design values:

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

components of PM 2.5 

# (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 concen tration of FRM-derived total PM 2.5 

# by the monitored

fractional composition of PM 2.5 

# species for each quarter averaged over 3 years 16 

# (e.g., 20

percent sulfate fraction multiplied by 15 μg/m 3 

# PM 2.5 

# equals 3 μg/m 3 

# sulfate).

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

predictions for sulfate, nitrate, elemen tal carbon, organic carbon, and other primary

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

assume that the model-predicted 2005 base ye ar sulfate for a partic ular location is 10.0

μg/m 3 

# and the 2012 future concentration is 8.0 μg/m 3 

# , then RRF for sulfate is 0.8). The

16 

# For this analysis, species fractions were calcula ted using FRM and speciation data for the 2004-

2006 time period. This was deemed to be re presentative of the 2005 base year period.

# 13 RRFs are calculated based on the modeled conc entrations averaged over the nine grid

cells 17 

# centered at the location of the monitor.

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

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

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

(e.g., 3 μ g/m 3 

# sulfate multiplied by the 0.8 RRF equals a future sulfate concentration of

2.4 μ g/m 3 

# ).

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

calculated 18 

# . The future year ammonium is calculate d based on the calculated future year

sulfate and nitrate concentrations, using a c onstant value for the de gree of neutralization

of sulfate (from the ambient data). The futu re 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 su lfate, 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 fu ture year annual design value for PM 2.5



# .

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

three base design value periods (200 3-2005, 2004-2006, and 2005-2007) separately. The

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

values are used to determine future year maintenance sites.

The preceding procedures for determining future year PM 2.5 

# concentrations were

applied for each FRM site . The calculated annual PM 2.5 

# design values are truncated after

the second decimal place 19 

# . This is consistent with the truncation and rounding

procedures for the annual PM 2.5 

# NAAQS. Any value that is gr eater than or equal to 15.05

μg/m 3 

# is rounded to 15.1 μg/m 3 

# and is considered to be violating the NAAQS. Thus,

sites with future year annual PM 2.5 

# design values of 15.05 μg/m 3 

# or greater, based on the

17 

# The modeling guidance recommends calculating annual PM 2.5 

# 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 c onsistent with the default MATS settings (as

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

we did not explicitly model salt and therefore th e 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 c oncentration of 14.94753 becomes 14.94 when

digits beyond two places to the right are truncated.

# 14 projection of 5-year weighted average concen trations, are predicted to be nonattainment

sites. Sites with future year maximum design values of 15.05 μg/m 3 

# or greater are

predicted to be maintenance sites. Note th at 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 eas e of reference we use the term “nonattainment

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

average and maximum design values. Those si tes 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 PM 2.5 

# NAAQS in the 2012 base case

are used as the nonattainment/maintenance re ceptors for assessing the contribution of

emissions in upwind states to downwind nona ttainment and maintenance of the annual

PM 2.5 

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

PM 2.5 

# design values for each site for the 2012 and 2014 scenarios are provided in

Appendix B.

2. Methodology for Projecting Future 24-Hour PM 2.5 

# Nonattainment and

Maintenance

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

hour PM 2.5 

# design values. Additional details ar e provided in the modeling guidance and

in the MATS documentation. Similar to the annual PM 2.5 

# calculations, we are using the

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

PM 2.5 

# calculations are computati onally similar to the annual average calculations. The

main difference is that the base period 24-hour 98 th 

# percentile PM 2.5 

# concentrations are

projected to the future year, instead of th e annual average concentr ations. Also, the PM 2.5



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

high concentration days, instead of quarterly average data.

Both the annual PM 2.5 

# and 24-hour PM 2.5 

# calculations are performed on a calendar

quarter basis. Since all years and quarters are averaged together in the annual PM 2.5



# calculations, the individual years can be aver aged together early inthe calculations.

However, in the 24-hour PM 2.5 

# calculations, only the high quart er from each year is used

in the final calculations. This represents the 98 th 

# 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 quarte rs) must be carried

# 15 through to near the end of the calculations when the individu al 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 wei ghted average of the high quarters for each site

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

example of how the 24 hr PM 2.5 

# design values are calculated from the 20 quarterly

values. The table shows the PM 2.5 

# 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” 98 th 

# 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 as terisk. 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 PM 2.5 

# design value calculation at a single monitoring site.

AIRS ID State County Year Quarter Base Year

PM 2.5 

# (ug/m3) Future Year

PM 2.5 

# (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 follo wed for calculating the future year 24-

hour PM 2.5 

# design values:

Step 1 : At each FRM monitoring site , identify the maximum 24-hour PM 2.5



# concentration in each quarter that is less than or equal to the 98th percentile 20 

# 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 pe rcentile 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 quar terly ambient concen trations on “high” 21



# days for each of the major component species of PM 2.5 

# (sulfate, nitrate, ammonium,

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

calculation is performed by multiplying the m onitored concentrations of FRM-derived

total PM 2.5 

# mass on the 10 percent highest days from each quarter, by the monitored

fractional composition 22 

# of PM 2.5 

# species on the 10 percent highest PM 2.5 

# days for each

quarter, averaged over 3 years 23 

# (e.g., 20 percent sulfate fraction multiplied by 40 μg/m 3



# PM 2.5 

# equals 8 μg/m 3 

# 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 PM 2.5 

# for the top 10 percent of days 24 

# based on predicted concentrations of 24-

hour PM 2.5 

# . The result is a set of species-specif ic relative response f actors (RRF) for the

high PM 2.5 

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

20 

# The 98 th 

# 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 define d as the top 10 percent days in each quarter

based on 24-hour average concentrations of PM 2.5 

# mass.

22 

# Similar to the annual average calculations, the qua rterly species fractions ar e calculated at each

FRM site using interpolated species data (usi ng 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 calcu lated using an average of FRM and speciation

data for the 2004-2006 time period. This was d eemed 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 indi cated 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 calcu lations) 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 PM 2.5 

# days for a quarter for a particular location is 20 μg/m 3 

# and the 2012

base case concentration is 16 μg/m 3 

# , then RRF for sulfate is 0.8). The RRFs are

calculated based on the modeled concentrations at the single 25 

# grid cell where the monitor

is located.

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

the quarterly 26 

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

quarterly concentration for each component. (e.g., 21.0 μg/m 3 

# nitrate x 0.75 = future

nitrate of 15.75 μg/m 3 

# ).

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

calculated 27 

# . The future year ammonium is calculate d based on the calculated future year

sulfate and nitrate concentrations, using a c onstant value for the de gree of neutralization

of sulfate (from the ambient data). The futu re 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 concentrati ons to obtain quarterly PM 2.5 

# 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 perc entile 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 av erage design values (e .g. the high quarter from

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

are averaged, etc.). These (up to 3) desi gn 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 (200 3-2005, 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 c onsistent with the default MATS settings (as

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

we did not explicitly model salt and therefore th e 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 th e maximum design value. The maximum design

values are used to determine future year 24-hour PM 2.5 

# maintenance receptors.

The preceding procedures for determining future year 24-hour PM 2.5



# concentrations were applied for each FRM site. The 24-hour PM 2.5 

# design values are

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

and rounding procedures for the 24-hour PM 2.5 

# NAAQS. Any value that is greater than

or equal to 35.5 μg/m 3 

# is rounded to 36 μg/m 3 

# and is violating the NAAQS. Sites with

future year 5 year weighted average design values of 35.5 μg/m 3 

# 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/m 3 

# or greater are predicted to

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

maintenance sites because the maximum design valu e 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 refe r to those sites that are projected to exceed the NAAQS

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

be attainment based on the average desi gn value but exceed the NAAQS based on the

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

project to be nonattainment and/or maintenance for the 24-hour PM 2.5 

# NAAQS in the

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

contribution of emissions in upwind states to downwind nonattainment and maintenance

of 24-hour PM 2.5 

# NAAQS (see section IV, below). The 2003-2007 base period and

projected 24-hour PM 2.5 

# 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 futu re year 8-hour ozone calculations.

Additional details are provided in the m odeling guidance and MATS documentation.

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

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

procedure is relatively simple (compared to the PM 2.5 

# projection methodologi es). It is not

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

gridded, modeled ozone data are all th at 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 res ponse factors. The methodology we followed is

consistent with the attainment demonstr ation 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 al l days with 8-hour daily ma ximum predictions greater

than or equal to 85 ppb 28 

# . The mean concentrations are calculated using the predictions

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

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

in the 2005 base year. The RRFs were ca lculated on a site-b y-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 ba se 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 th e 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 vi olating 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 maxi mum design values of 85 ppb or greater are

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

annual and 24-hour PM 2.5 

# 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 oz one NAAQS in the 2012 base case are the

nonattainment/maintenance receptors used for assessing the contributi on 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 Contr ibution Modeling and Results

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

contributions) of emissions in individual States on annual PM 2.5 

# , 24-hour PM 2.5 

# , and/or 8-

hour ozone concentrations at projected 2012 nonattainment a nd maintenance sites in the

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

and/or annual PM 2.5 

# , and/or 24-hour PM 2.5 

# nonattainment and/or maintenance problems

in other States 29 

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

corresponding NAAQS. The air quality cont ributions were quantified using source

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

transport of ozone and particulate matter fr om specific emissions sources and calculate

the contribution of sources a nd precursors to ozone and PM 2.5 

# at individual receptor

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

that all modeled ozone and/or PM 2.5 

# mass at a given receptor location in the modeling

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

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

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

contributions that are asso ciated with ozone and PM 2.5 

# , as estimated by the model. More

details on the implementation of source a pportionment in CAMx can be found in the

CAMx user’s guide 30



# .

29 

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

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

“downwind” receptors.

30 

# Comprehensive Air Quality Model with Exte nsions Version 5 User’s Guide. Environ

International Corporation. Novato, CA. March 2009.

# 21 A. Nonattainment and Maintenance Receptors for the Assessment of PM 2.5 

# and Ozone

Contributions

As described above in section III, we iden tified monitoring site s 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 PM 2.5 

# standards and the 1997 8-hour

standard 31 

# . These 2012 nonattainment and/or mainte nance 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

PM 2.5 

# design values and the corresponding 2012 base case average and maximum design

values for sites projected to be nonattainment of the annual PM 2.5 

# NAAQS in 2012. Table

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

There are 32 sites in 21 counties projected to be nonattainment for the annual PM 2.5



# NAAQS in 2012. There are 16 sites in 14 coun ties projected to have maintenance only

problems for the annual PM 2.5 

# NAAQS in 2012. The 2012 base case annual PM 2.5



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

Table IV-1. Average and maximu m 2003-2007 and 2012 base case annual PM 2.5 

# design

values (μg/m 3 

# ) 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 va lues 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 maximu m 2003-2007 and 2012 base case annual PM 2.5 

# design

values (μg/m 3 

# ) 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 PM 2.5 

# nonattainment and/or maintenance

sites in the East.

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

PM 2.5 

# design values and the 2012 base case aver age and maximum design values for sites

projected to be 2012 nonattainment of the 24-hour PM 2.5 

# NAAQS in 2012. Table IV-4

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

are 92 sites in 43 counties projected to be nonattainment for the 24-hour PM 2.5 

# NAAQS

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

for the 24-hour PM 2.5 

# NAAQS in 2012. The 2012 base case 24-hour PM 2.5



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

# 24 Table IV-3. Average and maximu m 2003-2007 and 2012 base case 24-hour PM 2.5 

# design

values (μg/m 3 

# ) 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. Clai r 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 maximu m 2003-2007 and 2012 base case 24-hour PM 2.5 

# design

values (μg/m 3 

# ) 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 PM 2.5 

# 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 av erage and maximum design values for sites

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

contains this same information for projecte d 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 count ies 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 PM 2.5 

# was performed using

the 2012 base case emissions. In this modeling we tracked ozone and PM 2.5 

# 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 th e emissions in these

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

States. The States included in the so urce apportionment modeling for ozone and PM 2.5



# are: Alabama, Arkansas, Connecticut, Delawa re, Florida, Georgia, Illinois, Indiana,

Iowa, Kansas, Kentucky, Louisiana, Ma ine, Maryland, Massachusetts, Michigan,

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

North Carolina, North Dakota, Ohio, Okla homa, Pennsylvania, Rhode Island, South

# 30 Carolina, South Dakota, Tennessee, Texa s, Vermont, Virginia, West Virginia,

Washington D.C. 32 

# , and Wisconsin.

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

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

track the emissions or assess th e 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 Cana da and Mexico in a category named “other”.

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

CAMx source apportionment techniques we also tracked the contributions from biogenic

emissions (regionally) a nd initial and boundary concen trations (IC/BCs). The

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

in the analysis to determine whic h State to include in the TR.

C. Approach to Calculating Contributions for Annual and 24-Hour PM 2.5



# We used the CAMx Particulate Sour ce Apportionment Technique (PSAT) to

calculate contributions to annual and 24-hour PM 2.5 

# nonattainment and maintenance. The

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

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

emissions of NO X 

# , SO 2 

# , and primary PM 2.5 

# from the individual States listed above.

Each State was a separate tag, and the ta gged 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 m odeled concentrations of secondary organic

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

we chose not to track SOA.

In the PSAT simulation, NO X 

# emissions are tracked to c ontributions to particulate

nitrate concentrations, SO 2 

# emissions are tracked to contri butions to particulate sulfate

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

unspeciated PM 2.5 

# ) are tracked as contributions to prim ary particulates. We combined the

contributions of nitrate and sulfate in calculating the net contributions to PM 2.5 

# for the

purpose of evaluating the intersta te contributions against spec ific threshold criteria, as

described in section IV.E, below. The rationa le 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 sm all size of the District of Columbia and, hence,

its emissions and its close proximity to Mary land, as described in the TR preamble.

# 31 plus sulfate and excluding primary PM 2.5 

# 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 PM 2.5 

# 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 nonatta inment and/or maintenance site (i.e.,

receptor).

The following is a description of the pro cedures for calculating contributions for

annual PM 2.5. 

# These procedures were applied se parately for each source State.

1. Receptor sites include th e 2012 base case annual PM 2.5 

# nonattainment and maintenance

sites in the 12km Eastern modeling domain.

2. Contributions for each of the PM 2.5 

# species from each State, as predicted by PSAT, are

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

model output files for each source region.

3. Daily, 24-hr average PM 2.5 

# species are calculated for th e “standard” model output files

and newly generated source co ntribution output files.

4. The relative response factor s (RRFs) for each of the PM 2.5 

# 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 (g enerated 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 PM 2.5 

# species contributions in

ug/m3 from each species for each source region 33,34



# .

33 

# The calculations in step 5 use MATS out puts and additional post-processing software

developed for this rule. More details on the pos t-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 ve ry small negative values in the calculation of

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

# 32 6. The annual average contributi ons of sulfate ion, nitrate ion, ammonium, and water for

each source State are combined to ca lculate the nitrate plus sulfate PM 2.5 

# contribution

used in the TR analysis 35



# .

7. Annual PM 2.5 

# (i.e., nitrate plus sulf ate) contributions are expressed in units of μg/m 3



# .

Values of annual PM 2.5 

# contribution are truncated after two places to the right of the

decimal (e.g. a contribution of 0.149 μg/m 3 

# is truncated to 0.14 μg/m 3 

# ).

The 24-hour PM 2.5 

# contributions were calculate d in a manner similar to the

procedures for annual PM 2.5 

# . 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 PM 2.5 

# , the contributions are ca lculated as the five

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

The following is a description of the pro cedures for calculating contributions for

24-hour PM 2.5. 

# These procedures were applied sepa rately for each source State.

1. Receptor sites include th e 2012 base case 24-hour PM 2.5 

# nonattainment and

maintenance sites in the 12k m photochemical modeling domain.

2. Contributions for each of the PM 2.5 

# species from each State, as predicted by PSAT, are

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

output files for each source region.

3. Daily, 24-hr average PM 2.5 

# species model output files are generated for the “standard”

2012 base case model output files and newly ge nerated 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 concentrati ons, using a constant value for the degree of

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

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

equations were used to calculate amm onium 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 ex ists as ammonium nitrate) and the 1.12 factor

is applied to subtract out the particle bound wa ter 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 a nd 1.29 factors are included to subtract out the

ammonium associated with nitrate ion (assuming th at 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 th e sulfate ion and is assumed to be attached to

sulfate.

# 33 4. Relative response factors (RRFs) are calculated for each of the PM 2.5 

# species 36 

# for each

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

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

concentration days are based on the highest 10% of modeled PM 2.5 

# days 37 

# (in each grid

cell) in the 2012 base case. The MATS “base line” 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 mode l output file (from step 3).

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

each source region are multiplied 38 

# by the high days quarterly average future year (2012)

species concentrati ons from the 24-hr PM 2.5 

# 2012 base case. This cal culation is done for

(up to) 5 years of data for each quarter (for a to tal 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 anal ysis. The high quarter for each year (based

on the 2012 base case) is already known from the 2012 base case 24-hr PM 2.5 

# design

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

averaged 39 

# together. This repr esents the species cont ributions to 24-hour PM 2.5



# concentrations.

36 

# As in the design value calculations in secti on III, the ammonium contribution is calculated

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

the degree of neutralization of sulfate (from th e 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 mode led 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 st eps and software can be found in Appendix C.

39 

# For the 24-hr PM2.5 NAAQs contribution calculati ons, the five year average contributions are

not weighted towards the middle year of the period. Si nce 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, a mmonium, and water 40 

# for each

source State are combined to calculate the total PM 2.5 

# contribution used in the TR

analysis, as in the calculations for annual PM 2.5 

# , described above..

8. 24-hour PM 2.5 

# contributions are expr essed in units of μg/m 3 

# . Values of 24-hour PM 2.5



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

of 0.349 μg/m 3 

# is truncated to 0.34 μg/m 3 

# ).

D. Approach to Calculating Contributions for 8-Hour Ozone

We used the CAMx Anthropogenic Precursor Culpability Assessment (APCA)

source apportionment technique to calcul ate the contributions to 8-hour ozone

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

ozone from NO X 

# and VOC emissions. Through emissions pre-processing procedures, we

tagged all of the anthropogenic NO X 

# 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 anthropogeni c sources of NO X 

# and VOC were tracked in the APCA

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

outputs to ozone contributions. The appro ach for calculating ozone contributions was

similar to the approach used for PM 2.5 

# , except that the APCA model outputs were

processed using MATS instead of the PSAT outputs used for PM 2.5.



# The following is a description of the pro cedures for calculating contributions for

8-hour ozone. These procedures were appl ied 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 genera ted source contribution

output files.

4. Relative response factors (RRFs) are calcul ated 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 required 41 

# for a relative response f actor to be estimated at

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

daily maximum concentrations above the initial ozone criteri on, 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 calculat ed and the receptor is not used in the

contribution analysis.

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

value to estimate ozone contributio n in ppb from the source State 42



# .

7. Ozone contributions are e xpressed in units of ppb. Oz one 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 pro cedures for calculating 8-hour ozone and

annual and 24-hour PM 2.5 

# contributions to the nonattain ment and maintenance receptor

sites 43 

# . The contributions to each 2012 nonatta inment receptor and each maintenance

receptor are provided in Appendix D 44 

# . For annual PM 2.5 

# 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 po st-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 b ase case, based on the 5-year wei ghted 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 PM 2.5



# NAAQS in the 2012 base case. For 24-hour PM 2.5 

# , 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 ar e projected to have maintenance problems for the 24-hour

PM 2.5 

# NAAQS in the 2012 base case. Similarl y, for ozone we calculated each state’s

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

each of 14 45 

# sites that are projected to have ma intenance problems for the 8-hour ozone

NAAQS in the 2012 Base Case.

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

evaluated to determine if the contribu tions to downwind nonattainment and/or

maintenance are at or above specific contribu tion 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

PM 2.5 

# NAAQS, 2006 24-hour PM 2.5 

# NAAQS, and 1997 8-hour ozone NAAQS are shown

in Table IV-7.

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

annual and 24-hour PM 2.5 

# and 8-hour ozone.

Pollutant Level of the NAAQS 1 Percent Threshold

Annual 

# PM 2.5 

# 15.0 μg/m 3 

# 0.15 μg/m 3



# 24-Hour 

# PM 2.5 

# 35 μg/m 3 

# 0.35 μg/m 3



# 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 examin ed 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 relativ e to the threshold.

States that contribute amount s at or above the threshol d to at least one downwind

nonattainment receptor or one maintenance receptor for the annual PM 2.5 

# NAAQS or the

24-hour PM 2.5 

# NAAQS are included in the TR for annual SO 2 

# and NO X 

# 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 ar e at or above the threshold to at least one

8-hour ozone downwind nonattainment or mainte nance receptor are included in the TR

for summer season NO X 

# emissions budgets.

1. Contributions to Annual PM 2.5 

# Nonattainment and Maintenance

The largest contribution from each State to annual PM 2.5 

# across all downwind

nonattainment receptors is provided in Table IV-8. The largest contribution from each

State to annual PM 2.5 

# across all downwind maintenance-only receptors is also provided in

Table IV-8.

Table IV-8. Largest contri bution to downwind annual PM 2.5 

# (μg/m 3 

# ) nonattainment and

maintenance for each of 37 States.

Upwind State Largest Downwind

Contribution to

Nonattainment for

Annual PM 2.5 

# (μg/m 3 

# ) Largest Downwind

Contribution to

Maintenance for

Annual PM 2.5 

# (μg/m 3 

# )

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 PM 2.5 

# (μg/m 3 

# ) Largest Downwind

Contribution to

Maintenance for

Annual PM 2.5 

# (μg/m 3 

# )

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/m 3 

# or more to downwind annual PM 2.5



# nonattainment. These states are: Alabama, th e District of Columbia, Delaware, Florida,

Georgia, Illinois, Indiana, Iowa, Kentuc ky, Maryland, Michigan, Minnesota, Missouri,

New Jersey, New York, North Carolina, Ohi o, 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/m 3 

# 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 PM 2.5 

# maintenance. These states are: Alabama, the District

of Columbia, Georgia, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maryland, Michigan,

Minnesota, Missouri, New Jers ey, New York, Ohio, Pennsylva nia, Tennessee, Virginia,

West Virginia, and Wisconsin. A list of the downwind maintenan ce sites to which each

upwind State contributes 0.15 μg/m3 or mo re (i.e., the upwind State-to-downwind

maintenance “linkages”) are provided in Appendix E.

2. Contributions to 24-Hour PM 2.5 

# Nonattainment and Maintenance

The largest contribution from each State to 24-hour PM 2.5 

# across all downwind

nonattainment receptors is provided in Table IV-9. The largest contribution from each

State to 24-hour PM 2.5 

# across all downwind maintenance-on ly receptors is also provided

in Table IV-9.

# 39 Table IV-9. Largest contri bution to downwind 24-hour PM 2.5 

# (μg/m 3 

# ) nonattainment and

maintenance for each of 37 States.

Upwind State Largest Downwind

Contribution to Nonattainment

for 24-Hour PM 2.5 

# (ug/m 3 

# ) Largest Downwind Contribution

to Maintenance

for 24-Hour PM 2.5 

# (ug/m 3 

# )

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 PM 2.5



# nonattainment. These States are: Alabama, the District of Columbia, Connecticut,

# 40 Delaware, Georgia, Illinois, Indiana, Iowa , Kansas, Kentucky, Maryland, Massachusetts,

Michigan, Minnesota, Missouri, Nebraska, Ne w 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 PM 2.5 

# maintenance. These states are:

Connecticut, Delaware, the District of Colu mbia, Georgia, Illinois, Indiana, Iowa,

Kansas, Kentucky, Maryland, Massachusetts, Mi chigan, Minnesota, Missouri, Nebraska,

New Jersey, New York, North Carolina, Ohi o, Pennsylvania, Tenness ee, Virginia, West

Virginia, and Wisconsin. A list of the downwind maintenance sites to which each

upwind State contributes 0.35 μg/m3 or mo re (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 Stat e 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 main tenance-only receptors is also provided in

Table IV-10.

Table IV-10. Largest cont ribution 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 c ontribution 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, Illi nois, Indiana, Kentucky, Louisiana, Maryland,

Michigan, Mississippi, New Jersey, North Carolina, Ohio, Oklahoma, Pennsylvania,

Tennessee, Texas, Virginia, and West Virg inia. A list of the downwind nonattainment

counties to which each upwind State contribut es 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 Colu mbia, 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 nonattain ment 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 SO 2 

# and NO X 

# Emissions

Reductions

In this section we present th e air quality impacts of the SO 2 

# and NO X 

# emissions

reductions in the 2014 remedy scenario in co mparison to air quality predicted for the

2012 base case and 2014 base case scenarios 46 

# . We first describe the magnitude and

spatial patterns in emissions reductions (and in creases) in the East. Then we quantify the

impacts of these emissions changes on proj ected design value concentrations for annual

PM 2.5 

# , 24-hour PM 2.5 

# , and 8-hour ozone at monitoring sites in the Eastern modeling

domain 47 

# . We also provide the impacts on visibi lity 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 reme dy 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

EITSD 48 

# . The 27 States and Washington, D.C. that are included in the TR for annual SO 2



# and NO X 

# emissions controls to reduce interstate contributions of PM 2.5 

# are shown on the

map in Figure V-1. These States are divided into two groups with di fferent levels of SO 2



# emissions reductions. The States in Group 1 ha ve deeper reductions than those in Group

2 49 

# . The 25 States (plus Washington, D.C. ) subject to summer season (May through

September) NO X 

# controls to reduce interstate trans port of ozone are shown on the map in

Figure V-2. The aggregate emissions of annual SO 2 

# , annual NO X 

# , and summer NO X 

# 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 b ase 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 additi on 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 criteri a, 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 de tails 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 SO 2 

# and NO X 

# emission

reductions.

Figure V-2. States included in the Transport Rule for summer NO X 

# emission reductions.

For the Group 1 States as a whole, annual SO 2 

# emissions from electric generating

units (EGUs) are projected to be 68 percent lo wer in 2014 with the TR controls compared

to those in the 2014 base case. The reducti on in EGU emissions yi elds a net 53 percent

reduction in total SO 2 

# for the Group 1 States. Overall, for both Group 1 and Group 2

# 44 States, total SO 2 

# emissions across all source categorie s are 45 percent lower in the 2014

remedy scenario, compared to the 2014 base case.

The difference in annual total SO 2 

# emissions between the 2014 base and remedy

scenarios at individual faci lities is shown in Figure V- 3. This figure reveals that

substantial SO 2 

# emissions reductions will occur at f acilities in the States covered by the

TR with the largest reductions in portions of the Midwest, Tennessee Valley, and Ohio

Valley extending across Pennsylva nia. Some increases in SO 2 

# emissions are noted in a

few States not included in the TR for annual SO 2 

# reductions, most notably at several

facilities in Arkansas, Texas, and Colorado.

Figure V-3. Change in annual EGU SO 2 

# emissions between the 2014 base and control

scenarios at individual facilities.

Annual emissions of NO X 

# from EGUs are lower by 36 percent in the remedy

scenario compared to the 2014 base case for the 27 States an d Washington, D.C. that are

included in the TR for annual NO X 

# emissions reductions. The reduction in EGU NO X



# produces an 8 percent ne t reduction in total NO X 

# for these States. For the 25 States and

Washington, D.C. included for ozone season NO X 

# controls, summer EGU NO X 

# emission

are 16 percent lower in the 2014 remedy scenar io, compared to the 2014 base case.

# 45 The changes in winter and summer NO X 

# emissions between the 2014 remedy and

2014 base case at individual faci lities are presented in Figures V-4 and V-5, respectively.

As is evident from Figure V-4, th e largest reductions in winter NO X 

# 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 NO X 

# 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 NO X 

# emissions reductions between the summer and the winter. In the

winter, many states in th e East have sizable NO X 

# reductions. But in the summer, most of

the NO X 

# reductions occur outside of the NO X 

# SIP call states. This is due to the fact that

the NO X 

# 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 NO X 

# emissions between the 2014 base and

control scenarios at individual facilities.

# 46 Figure V-5. Change in summer season EGU NO X 

# emissions between the 2014 base and

control scenarios at individual facilities.

B. Impacts on Projected PM 2.5 

# Design Value Concentrations

The projected annual and 24-hour PM 2.5 

# design values for the 2014 base case and

2014 remedy scenario are provided in Appe ndix B. The impacts of the annual SO 2 

# and

NO X 

# emissions reductions on annual and 24-hour PM 2.5 

# design values are also provided

in Appendix B. The impacts on annual and 24-hour PM 2.5 

# design values for each

monitored county are shown in Fi gures V-6 and V-7, respectively 50,51 

# . The results, as

shown in these figures indicate that the emissions reductions from the TR will

substantially lower a nnual and 24-hour PM 2.5 

# concentrations at most locations in the

Eastern U.S, compared to the 2014 base case. Annual PM 2.5 

# is lower by more than 2

ug/m 3 

# in areas of the East extending from Te nnessee northward to Indiana and Ohio, and

50 

# These maps, which show the difference betw een the 2014 remedy scenario and the 2014 base

case, are based upon 5-year weighted average d esign 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 PM 2.5 

# are provided in Appendix G. Maps showing the predicted

change in annual and 24-hour PM 2.5 

# between the 2014 remedy and the 2012 base case are also

provided in Appendix G.

51 

# For counties with multiple monitoring sites, th e maps show the largest difference from among

the sites in a county.

# 47 eastward across Pennsylvania. Along the high ly populated Northeast Corridor, across the

Southeast and in the upper Mi dwest, including the cities of Atlanta, Birmingham, St.

Louis, Chicago, and Detroit annual PM 2.5 

# concentrations are lower by 1 to 2 ug/m3.

As shown in Figure V-7, the pr edicted reductions in 24-hour PM 2.5 

# are greater

than those for annual PM 2.5 

# concentrations. Daily PM 2.5 

# 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 Northeas t Corridor. In the multi-State area from

Tennessee to western Pennsylvania, our modeling predicts 24-hour PM 2.5 

# concentrations

that are 6 to 10 ug/m3 lower than those in the 2014 base case.

Figure V-6. Impacts on annual average PM 2.5 

# concentrations in 2014 resulting from the

emissions reductions in the 2014 remedy scenario.

# 48 Figure V-7. Impacts on 24-hour PM 2.5 

# 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 PM 2.5



# across the East are generally consistent with the patterns in annual SO 2 

# and winter NO X



# emissions reductions from EGUs, as evid ent by comparing Figures V-6 and V-7 to

Figures V-3 and V-4, respectively. Th ese figures also indicate that PM 2.5 

# concentrations

are lower in the remedy scenario in those Stat es in the East not in cluded in the TR for

annual SO 2 

# and NO X 

# reductions, like Arkansas, Missi ssippi, Oklahoma, Texas and

several northern New England. In Texas a nd Arkansas, the reductions in transported

PM 2.5 

# are large enough to more than offset the forecasted increases in local emissions of

SO 2 

# in these two States.

There are a few locations ma inly in the West where SO 2 

# emissions and, therefore,

PM 2.5 

# is predicted to be higher in the 2014 re medy scenario compared to the 2014 base

case. Locations where PM 2.5 

# levels are higher in the remedy scenario are evident in

counties near Denver, CO.

# 49 C. Impacts on Annual and 24-Hour PM 2.5 

# 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 PM 2.5 

# and 24-hour PM 2.5 

# are provided in Table V-1. The percent difference in

the number of nonattainment and maintenan ce 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 PM 2.5 

# and 24-hour PM 2.5 

# concentrations for those

sites with 2012 nonattainment and/or maintena nce problems are provided in Table V-2.

The annual PM 2.5 

# nonattainment and/or maintenance sites in the East for the 2014 base

case and 2014 remedy scenario are shown in Figures V-8 an d V-9, respectively. Similar

maps are provided in Figures V-10 and V-11 for 24-hour PM 2.5



# .

Table V-1. Percent reduction in annual and 24-hour PM 2.5 

# 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 

# PM 2.5



# Nonattainment Sites a 

# 102 32 15 1 97% 93%

Annual 

# PM 2.5 

# Maintenance-Only

Sites 21 16 7 1 94% 86%

Daily 

# PM 2.5



# Nonattainment Sites 151 92 54 17 82% 69%

Daily 

# PM 2.5 

# 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 PM 2.5 

# and 24-hour PM 2.5 

# for the 2012

base case nonattainment a nd/or maintenance sites.

2014 Remedy vs

2012 Base Case 2014 Remedy vs

2014 Base Case

Average

Reduction Peak

Reduction Average

Reduction Peak

Reduction

Annual PM 2.5 

# Nonattainment Sites 2.8 μg/m3 3.9 μg/m3 2.3 μg/m3 3.3 μg/m3

Annual PM 2.5 

# Maintenance-Only Sites 2.8 μg/m3 4.2 μg/m3 2.3 μg/m3 3.6 μg/m3

24-Hour PM 2.5 

# Nonattainment Sites 5.8 μg/m3 15.3 μg/m3 4.5 μg/m3 13.8 μg/m3

24-Hour PM 2.5 

# 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 th at the extent of nonattainment and

maintenance problems for annual PM 2.5 

# and 24-hour PM 2.5 

# is significantly lower in the

2014 remedy scenario compared to both the 201 2 base case and the 201 4 base case. All

but 1 site 52 

# is projected to be in attainment and only 1 site 53 

# is projected to have a

maintenance problem for annual PM 2.5 

# with the emissions reductions expected from the

remedy by 2014. Annual PM 2.5 

# concentrations are, on average, more than 2 μg/m 3 

# lower

across the 32 sites that were nonattainment in the 2012 base case. The impacts on annual

PM 2.5 

# at maintenance-only sites are comparable to those at the nonattainment sites.

For 24-hour PM 2.5 

# , there are significantly fewer nonattainment and/or

maintenance sites in the 2014 remedy scenar io compared to both the 2012 and 2014 base

cases. For example, in the 2014 remedy scenar io the number of nonattainment sites is 69

percent less than in the 2014 base cas e. The average reduction in 24-hour PM 2.5 

# across

the 92 2012 nonattainment sites is 5.8 μg/m3 an d the peak reduction at an individual

nonattainment site is 15.3 μg/m3. Comparab le reductions are pr ojected at 24-hour PM 2.5



# maintenance-only sites.

52 

# Allegheny Co., PA site 420030064.

53 

# Jefferson Co., AL site 010730023.

# 51 Figure V-8. Projected annual PM 2.5 

# nonattainment and/or maintenance sites in the East

for the 2014 base case.

Figure V-9. Projected annual PM 2.5 

# nonattainment and/or main tenance sites in the East

for the 2014 remedy scenario.

# 52 Figure V-10. Projected 24-hour PM 2.5 

# nonattainment and/or maintenance sites in the East

for the 2014 base case.

Figure V-11. Projected 24-hour PM 2.5 

# nonattainment and/or maintenance sites in the East

for the 2014 remedy scenario.

# 53 D. Analysis of Residual Nonattainment for 24-Hour PM 2.5



# 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 PM 2.5 

# standard in the

2014 remedy scenario. The average and maximum 24-hour PM 2.5 

# design values at these

28 sites are provided in Table V-3. Alt hough these sites are predicted to have

nonattainment/maintenance problems, the emissi ons reductions in the TR will result in

considerable progress toward at tainment and maintenance at these 28 sites. On average,

the predicted amount of PM 2.5 

# 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 PM 2.5 

# design values (μg/m 3 

# ) for projected

nonattainment and/or maintenance s ites in the 2014 remedy scenario.

Urban Area County Monitoring

Site ID 2014 Remedy

Scenario

Average

Design Value a 

# 2014 Remedy

Scenario

Maximum Design

Value b



# 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 Value a 

# 2014 Remedy

Scenario

Maximum Design

Value b



# New York City, NY New York Co 360610056 35.3 36.0

Pittsburgh, PA Alleghe ny 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/m 3 

# are projected to be nonattainment.

b 

# Sites with maximum projected design values >= 35.5 μg/m 3 

# and average design values <35.5

μg/m 3 

# 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 pa rt of the projection of 24-hour PM 2.5 

# design values, as

described in section III.B.2, above. The qua rterly data set for each site includes a

projected 24-hour PM 2.5 

# 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 th at exceed the level of 24-hour PM 2.5 

# 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 1 st 

# and 4 th 

# quarters (i.e., the cool season). Exceedances predicted

during the 2 nd 

# and 3 rd 

# 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 fo r the residual nonattainment/mai ntenance 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 signif icant differences in the reduction in sulfate

by quarter and from city to city. In gene ral, our modeling results indicate that the

response of sulfate during the 2 nd 

# and 3 rd 

# quarters (warm season) is generally proportional

to the overall regional reduction in SO 2 

# emissions. However, during the 1 st 

# and 4 th



# quarters (cool season) the relatio nship between the change in SO 2 

# emissions and the

change in sulfate is non-proportional. In 11 of the 14 urban areas th e 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 2 nd 

# and/or 3 rd 

# quarters ranges from 38 to 48 percent 55 

# . This level of

reduction in sulfate is consistent w ith the net 45 percent reduction in SO 2 

# 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), 2 nd 

# and/or 3 rd 

# quarter reductions in sulfate are in the

range of 25 to 30 percent which is generally consistent with the SO 2 

# emissions reduction

in these States 56



# .

0 5 10 15 20 25 30 35 40 45 50

Birming h

a m

, AL

E . St.

Lo

uis, MO

M i l w

au

k

ee,

WI

Ch ic

ag

o,

I L Gar y , IN

An n A r bo

r

, M

I Detroit , M

IPercent Reduction



# Qtr 1 Qtr 2 Qtr 3 Qtr 4



# Figure V-12. Percent reducti on in sulfate concentrati ons 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 reduc tion in sulfate during the

1 st



# and 4 th 

# quarters is much less than in 2 nd 

# and 3 rd 

# quarters. Sulfate concentrations during

the 1 st 

# quarter show the least res ponse to emissions changes. The percent reduction in

sulfate during this quarter ranges from 7 to 25 percent. Comparing the percent reduction

in 1 st 

# quarter sulfate to that in the 3 rd 

# quarter indicates that 1 st 

# quarter reduction is only

about a third (or less) of the reduction in the 3 rd 

# quarter for 9 of the 14

55 

# The reduction in sulfate during the 3 rd 

# quarter tends to be somewhat greater than in the 2 nd



# 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

Steub e n v i l le, OH

P it tsb

urgh , PA Lancaster, PA Baltimore, MD

Je r sey C i ty, NJ New York C

i ty,

N

YPercent Reduction



# Qtr 1 Qtr 2 Qtr 3 Qtr 4



# Figure V-13. Percent reducti on in sulfate concentrati ons by quarter at residual

nonattainment/maintenance sites in Clevel and, 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 pe rcent reduction in 1 st 

# quarter sulfate is approximately 50 to 60

percent of the reducti on predicted in the 3 rd 

# quarter. During the 4 th 

# quarter, the response

of sulfate to emissions reduc tions is somewhat greater than the response in the 1 st 

# 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 SO 2 

# emissions produced a 46 percen t reduction in sulfate based

on a model simulation for July. However, dur ing a January simulati on sulfate responded

nonlinearly with an average su lfate reduction of 17 percent fo r a 50 percent reduction in

SO 2 

# 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 sulfat e in January was limited by the ava ilability of hydrogen peroxide.

57 

# Tsimpidi, A.P.; Karydis, V.A.; Pandis, S.N.; R esponse 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 oxidi zing agent that is important in the formation of sulfate

from SO 2 

# , 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 SO 2 

# emissions reductions in the

cool season months, there are several ot her factors which contribute to residual

nonattainment predicted at site s in the 14 urban areas despit e the large reductions in SO 2



# emissions. Examining the composition of 24-hour PM 2.5 

# concentrations provides insight

into these factors. Figu re V-14 shows the average PM 2.5 

# 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 significa nt portion of the 24-hour PM 2.5 

# at the

sites in Pittsburgh and Birmingham are associat ed with organic car bon. 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 sources 58 

# . 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 sources 59 

# . The PM 2.5 

# species

concentrations at the Detroit site indicate that nitrate and organic carbon concentrations

during the 1 st 

# and 4 th 

# quarters are greater contributors to the residual nonattainment

problem than sulfate. During the 2 nd 

# and 3 rd 

# quarter sulfate is the dominant species. The

relative amount of PM 2.5 

# species at the other residual nona ttainment/maintenance sites are

generally similar to what is seen at the Detroit site. That is, in the 1 st 

# and 4 th 

# quarter,

nitrate and organic carbon concentrations co mbined represent a much larger portion of

total 24-hour PM 2.5 

# than sulfate. This analysis is pa rt of an on-going effort to understand

the seasonal variations in the res ponse of sulfate and nitrate to SO 2 

# and NO X 

# emissions

reductions and the underlying factors that contribute to exceeedances in the 1 st 

# and 4 th



# quarters which lead to residual nonattainme nt/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. Rese arch 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 Por tion 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 PM 2.5 

# species concentrations by qua rter at sites in Pittsburgh,

Birmingham, and Detroit.

E. Impacts on Projected 8-Hour Ozone Design Value

The projected 8-hour ozone design valu es for the 2014 base case and 2014

remedy scenario are provided in Appendix B. The impacts of the summer season NO X



# emissions reductions on 8-hour ozone design valu es for monitored counties in the Eastern

12 km modeling domain are also provided in Appendix B. The impacts are shown in

Figure V-15 60 

# . This figure indicates that the emissi ons reductions from the TR will result

in lower ozone concentrations in most countie s in the Eastern U.S., compared to the 2014

base case. Concentrations of 8-hour oz one are lower by 0.5 ppb or more for the 2014

remedy scenario in portions of the Sout heast 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, Mississipp i, Missouri, Oklahoma, and Pennsylvania.

The spatial patterns of the magnitude of re duction in 8-hour ozone across the East are

60 

# These maps, which show the difference betw een the 2014 remedy scenario and the 2014 base

case, are based upon 5-year weighted average d esign 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 predic ted 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 NO X 

# emissions reductions from EGUs,

as evident by comparing Fi gures V-5 to Figures V-15.

One county in southern Illinois is pred icted 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 NO X 

# emissions at EGUs near this county 61



# .

Figure V-15. Impacts on 8-hour ozone con centrations 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 nonatt ainment 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 a nd the 2014 remedy are also predicted in other

unmonitored areas as evident in the ozone spatial fiel ds 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 w ith 2012 nonattainment and/or maintenance

problems are provided in Table V-5. The lo cation of 8-hour ozone nonattainment and/or

maintenance sites in the East for the 2014 ba se 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 th at the extent of nonattainment and

maintenance problems for 8-hour ozone is pr edicted to be lower by 36 percent and the

number maintenance-only sites by 69 percen t 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 nonattainmen t and/or maintenance problems in the

2014 remedy scenario, the predicted ozone re ductions 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 nonattainme nt sites are located in Housto n and 1 is in Baton Rouge.

Two of the residual maintenance only sites are in New York C ity 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 maximu m 8-hour ozone design values (ppb) for monitoring sites

projected to have nonattainment and/or ha ve maintenance problems in the 2014 remedy

scenario.

Urban Area County Monitoring

Site ID Average

Design Value a 

# Maximum Design

Value b



# 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 main tenance sites in the East

for the 2014 base case.

Figure V-17. Projected 8-hour oz one nonattainment and/or main tenance sites in the East

for the 2014 remedy scenario.

# 63 G. Impacts on Visibility in Class 1 Areas

The impacts of the TR regional SO 2 

# and NO X 

# emissions reductions were

examined in terms of the projected improve ments in visibility on the 20 percent worst

visibility days at Class I areas 62 

# . We quantified visibility im pacts at the 60 Class I areas

in the Eastern modeling domain which have complete IMPROVE ambient data for 2005

or are represented by IMPROVE mo nitors with complete data. Sites were used in this

analysis if they had at least 3 years of complete data for the 2002-2006 period 63



# .

Visibility for the 2012 base case, 2014 base case and 2014 remedy scenario were

calculated using the regional haze mode ling guidance methodology, which applies

modeling results in a relative sense, us ing base year ambient data. The PM 2.5 

# and

regional haze modeling guidance recommends th e calculation of future year changes in

visibility in a similar manner to the calculation of changes in PM 2.5 

# design values. The

regional haze methodology for calculating future y ear visibility impairment is included in

MATS (as previously document ed in section III).

In calculating visibility impairment, the extinction coefficient and deciview

values are made up of individual component sp ecies (sulfate, nitrate, organics, etc). The

predicted change in vi sibility (on the 20 percent worst da ys) is calculated as the modeled

percent change in the mass for each of the PM 2.5 

# species (on the 20% worst observed

days) multiplied by the observed concentratio ns. The future mass is converted to

extinction and then daily species extinction co efficients 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 th is way, we calculate an average change in

deciviews from the base case to a future cas e 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 be nefits in Class I areas that are expected to

occur from the TR.

62 

# The focus of this analysis is on visibility im pacts at Class I areas within our 12 km Eastern

modeling domain. We have also calculated visib ility 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 fo r 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 cons istent with using a 5 year base period for

regional haze calculations. The predicted ch ange 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 (deciview s) impacts on 20 percent worst da ys 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 Co lorado 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 Mode ling Technical Support Document

Appendix A

Air Quality Model Performance Evaluation

# A-2 A. Introduction

An operational model performance eval uation was conducted for ozone and PM 2.5 

# and its

components species predicted by CAMx for the 2 005 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 monitori ng sites in the 12 km Eastern modeling domain 1 

# . This

evaluation includes statistical asse ssments 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 incl uded in the analysis 2



# , 3 

# . The Atmospheric Model Evaluation Tool

(AMET) was used to calculate the performa nce statistics describe d in this document. 4



# The evaluation of ozone predictions focuses on 8-hour daily maximum ozone

concentrations during the months of May through September wh en 8-hour daily maximum ozone

concentrations are typically hi ghest 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 calc ulated 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 us ing all observed-predicted pairs, irrespective of

concentration, and a second set based on observed concentrations > 60 ppb.

The evaluation of PM 2.5 

# component species includes comparisons of predicted and

observed concentrations of sulfate (SO 4 

# ), nitrate (NO 3 

# ), total nitrate 5 

# (TNO 3 

# ), ammonium (NH 4 

# ),

elemental carbon (EC), and or ganic carbon (OC). The PM 2.5 

# performance statistics were

calculated for each of the four seasons 6 

# . PM 2.5 

# ambient measurements for 2005 were obtained

from the following networks: the C hemical S peciation N etwork (CSN), the I nteragency

M onitoring of PRO tected V isual E nvironments (IMPROVE), and the C lean A ir S tatus and

T rends Net work (CASTNet). The CSN sites are genera lly located within urban areas, CASTNet

sites in suburban/rural locations, and the IMPROVE sites are, for the most part, in rural/remote

areas.

The PM 2.5 

# species included in the evaluation for each network are listed in Table A-1.

For species that are measured by more than one ne twork, we calculated separate sets of statistics

for each network. The measurements at CSN and IMPROVE sites represent 24-hour average

concentrations, whereas measurements at CAST Net 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 PM 25 

# 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 At mospheric Model Evaluation Tool (AMET): Meteorology

Module. Presented at 4th Annual CMAS Models-3 Users Co nference, Chapel Hill, NC, September 26 - 28, 2005.

(http://www.cmascenter.org/)

5 

# Total nitrate includes particulate nitrate and nitric acid gas (HNO 3 

# )

6 

# Seasons were defined as follows: winter (December-J anuary-February), spring (March-April-May), summer (JuneJuly-August), and fall (Sep tember-October-November).

# A-3 Table A-1. PM 2.5 

# monitoring networks and pollutants species included in the CAMx

performance evaluation.

Particulate

Species Ambient

Monitoring

Networks

SO 4 

# NO 3 

# TNO 3 

# EC NH 4 

# OC

IMPROVE X X



# - X X X

CSN X X



# - X X X

CASTNet X



# - X



# - X



# -

There are various statistical metrics availa ble 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 metric s, normalized mean bias and mean fractional

bias; and two error metrics, normalized m ean 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 perfor mance indicator because it avoids over-inflating

the observed range of values, especi ally at low concentrations. No rmalized 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 1 

# n P O

P O n 

# ∑ −

+ ⎛

⎝ ⎜ ⎞

⎠ ⎟ ⎛

⎝ ⎜ ⎜ ⎜ ⎜ ⎞

⎠ ⎟ ⎟ ⎟ ⎟ ( )

( ) 

# *100, where P = predicted concentra tions and O = observed values.

MFB is a useful model performance indicator beca use it has the advantage of equally weighting

positive and negative bias estimates. The single larg est disadvantage in this estimate of model

performance is that the estimated concentra tion (i.e., prediction, P) is found in both the

numerator and denominator. Mean fractional error (MFE) is simila r 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 1 

# n 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 performan ce was judged by comparing the CAMx 2005

performance results to the range of perfor mance found in recent regional ozone and PM 2.5 

# model

applications (e.g., Revised Renewa ble Fuel Standards Final Rule, 8 

# Clean Air Interstate Rule 9



# , Final PM NAAQS Rule 10 

# , and EPA’s Proposal to Designate an Emissions Control Area for

Nitrogen Oxides 11 

# ). These other modeling studies repres ent a wide range of modeling analyses

which cover various models, model configuratio ns, domains, years and/or episodes, chemical

mechanisms, and aerosol modules. Ozone bias an d error in these studie s are typically in the

range of + 10 percent for bias and within 20 percent fo r error. For sulfate and nitrate, the two

key PM 2.5 

# 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 studie s was within 35 to 50 percent a nd 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 PM 2.5 

# air quality model applicati ons. In their paper they

discuss model performance goals and criteria 13 

# for evaluating PM 2.5 

# 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 a pplied to species at low concentration levels.

The model performance statistics for ozone and PM 2.5 

# 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) Regul atory 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 Ag ency; 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 Stan dards, 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 Ta bles A-2 and A-3, respecti vely. The number of

observed-predicted pairs used in th e calculation of the various statisti cs is also provided in these

tables.

Overall, the model performance statistics fo r ozone, sulfate, and nitrate from the CAMx

2005 simulation are within or close to the ranges found in other recent app lications, as described

above. These model performance results give us confidence that our applications of CAMx

using this 2005 modeling platform provide a scien tifically credible approach for assessing ozone

and PM 2.5 

# concentrations for the purposes of the Tran sport Rule. The model performance results

for ozone and several of the PM2.5 component speci es 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 PM 2.5 

# 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 hi gh 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 nitrat e tends to be under predicted some what during the winter at both

urban and rural/remote sites. The negative fractio nal bias statistics in all seasons for particle

nitrate suggest that under pred iction may be occurring at lowe r concentration levels. For

ammonium, model performance is generally c onsistent at both urban and suburban/rural

locations with a tendency for under predicti on during the summer and over prediction during

other seasons. The model perfor mance statistics for crus tal material indicate that this component

of PM 2.5 

# is over predicted by a large amount in each season 14



# .

The model performance results reported he re 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 PM 2.5 

# contributions, as noted in Section IV.

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix B

2003-2007 Base Period and Projected 2012 and 2014 Design Values

for Monitoring Sites in th e Eastern Modeling Domain

# B-2 

# The tables in this appendix provide th e 5-year weighted average and maximum

design values for 8-hour ozone, annual PM 2.5, and 24-hour PM2.5 for monitoring

sites in the 12 km Eastern U.S. modeling domain 1 

# . Design values are provided for

the 2003-2007 base period, 2012 base case, 2014 ba se 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 va lues 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/m 3 

# for annual PM2.5, and + 0.1 μg/m 3



# for 24-hour PM2.5 may oversta te 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 wh ich meet the data completeness and projection

criteria described in Section III of the TSD.B-38-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues10030010 Alabama Baldwin 77.3 78.0 70.7 71.4 69.0 69.7 66.8 67.510270001 Alabama Clay 74.0 76.0 64.8 66.5 61.2 62.9 60.6 62.310331002 Alabama Colbert 72.0 74.0 64.5 66.3 62.7 64.4 62.5 64.210510001 Alabama Elmore 70.7 71.0 62.0 62.3 59.6 59.9 59.3 59.610550011 Alabama Etowah 71.7 73.0 61.6 62.7 58.7 59.7 58.3 59.410690004 Alabama Houston 71.0 71.0 62.8 62.8 60.1 60.1 59.8 59.810730023 Alabama Jefferson 78.7 86.0 69.6 76.1 67.1 73.3 66.9 73.110731003 Alabama Jefferson 79.0 84.0 69.7 74.1 67.1 71.4 66.9 71.210731005 Alabama Jefferson 81.0 86.0 71.0 75.4 68.1 72.3 67.9 72.110731009 Alabama Jefferson 77.0 82.0 66.4 70.7 64.0 68.1 63.8 67.910731010 Alabama Jefferson 73.0 75.0 63.8 65.6 61.2 62.9 61.0 62.710732006 Alabama Jefferson 83.7 89.0 74.0 78.7 71.3 75.8 71.1 75.610735002 Alabama Jefferson 74.0 77.0 65.3 67.9 62.8 65.4 62.6 65.110735003 Alabama Jefferson 77.0 82.0 66.6 71.0 64.2 68.4 63.9 68.110736002 Alabama Jefferson 81.3 89.0 72.0 78.8 69.4 76.0 69.2 75.810790002 Alabama Lawrence 72.0 74.0 63.2 64.9 60.6 62.3 60.5 62.210890014 Alabama Madison 77.3 78.0 67.9 68.6 64.6 65.2 64.5 65.110970003 Alabama Mobile 76.7 78.0 69.8 71.0 68.1 69.3 66.4 67.610972005 Alabama Mobile 76.7 77.0 70.0 70.3 68.2 68.5 66.3 66.611011002 Alabama Montgomery 69.3 74.0 60.6 64.7 58.2 62.1 58.0 61.911030011 Alabama Morgan 77.3 79.0 70.2 71.8 67.9 69.4 67.7 69.211130002 Alabama Russell 71.3 75.0 63.0 66.3 59.8 62.9 59.4 62.511170004 Alabama Shelby 85.7 88.0 75.2 77.2 72.2 74.1 72.0 73.911190002 Alabama Sumter 64.0 66.0 58.2 60.1 56.4 58.1 56.3 58.111210003 Alabama Talladega 72.072.0 62.4 62.4 59.7 59.7 59.4 59.411250010 Alabama Tuscaloosa 73.3 77.0 63.3 66.5 60.6 63.7 60.5 63.550350005 Arkansas Crittenden 87.3 89.0 77.3 78.8 74.5 76.0 74.4 75.851190007 Arkansas Pulaski 78.3 80.0 69.0 70.5 66.6 68.0 65.4 66.8B-48-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues51191002 Arkansas Pulaski 79.7 83.0 70.2 73.1 67.6 70.4 66.5 69.351191005 Arkansas Pulaski 74.0 75.0 65.4 66.3 63.1 64.0 62.0 62.980013001 Colorado Adams 69.0 70.0 66.8 67.7 66.2 67.1 66.2 67.180050002 Colorado Arapahoe 78.7 81.0 76.0 78.2 75.1 77.3 75.1 77.380130011 Colorado Boulder 77.0 81.0 73.4 77.2 72.2 76.0 72.3 76.080310002 Colorado Denver 56.0 56.0 54.2 54.2 53.7 53.7 53.7 53.780310014 Colorado Denver 73.0 75.0 70.7 72.6 70.0 71.9 70.0 71.980350004 Colorado Douglas 83.0 84.0 79.3 80.3 78.0 79.0 78.1 79.080590002 Colorado Jefferson 76.3 79.0 73.9 76.6 73.2 75.8 73.3 75.980590005 Colorado Jefferson 70.3 75.0 67.9 72.4 67.0 71.5 67.1 71.580590006 Colorado Jefferson 81.7 85.0 78.1 81.3 76.9 80.1 77.0 80.180590011 Colorado Jefferson 80.7 82.0 78.2 79.5 77.5 78.7 77.5 78.780691004 Colorado Larimer 72.3 74.0 68.4 70.0 67.3 68.9 67.4 69.081230009 Colorado Weld 76.7 78.0 72.7 73.9 71.6 72.9 71.7 72.990010017 Connecticut Fairfield 88.0 90.0 83.1 85.0 81.4 83.3 81.3 83.290011123 Connecticut Fairfield 92.3 94.0 84.8 86.4 82.7 84.2 82.6 84.190013007 Connecticut Fairfield 90.0 92.0 84.5 86.4 82.7 84.5 82.5 84.490019003 Connecticut Fairfield 87.7 89.0 82.8 84.0 81.1 82.3 81.0 82.290031003 Connecticut Hartford 84.3 90.0 75.0 80.1 72.7 77.7 72.7 77.690050005 Connecticut Litchfield 87.7 89.0 78.0 79.1 75.5 76.7 75.5 76.690070007 Connecticut Middlesex 90.392.0 81.8 83.4 79.6 81.1 79.5 81.090090027 Connecticut New Haven 79.3 81.0 73.3 74.9 71.5 73.0 71.4 72.990093002 Connecticut New Haven 90.3 93.0 82.9 85.4 80.7 83.2 80.6 83.090110008 Connecticut New London 85.3 88.0 77.1 79.5 75.0 77.4 74.9 77.390131001 Connecticut Tolland 88.7 91.0 78.0 80.1 75.5 77.5 75.4 77.4100010002 Delaware Kent 80.3 81.0 70.8 71.4 68.8 69.4 68.7 69.3100031007 Delaware New Castle 80.0 82.0 70.5 72.3 68.7 70.4 68.6 70.3100031010 Delaware New Castle 82.3 83.0 74.4 75.0 72.6 73.3 72.6 73.2100031013 Delaware New Castle 81.3 82.0 72.7 73.3 70.9 71.5 70.8 71.4100051002 Delaware Sussex 81.3 82.0 71.4 72.0 69.3 69.9 69.2 69.8B-58-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues100051003 Delaware Sussex 82.7 84.0 73.9 75.0 72.0 73.2 72.0 73.1110010025District OfColumbiaDistrict ofColumbia 79.7 81.0 74.3 75.5 72.6 73.8 72.6 73.7110010041District OfColumbiaDistrict ofColumbia80.3 85.0 75.4 79.8 73.7 78.0 73.5 77.8110010043District OfColumbiaDistrict ofColumbia 84.7 87.0 79.5 81.7 77.7 79.8 77.6 79.7120010025 Florida Alachua 72.0 72.0 65.7 65.7 63.2 63.2 59.9 59.9120030002 Florida Baker 68.7 70.0 62.0 63.2 59.6 60.8 58.2 59.3120050006 Florida Bay 78.7 81.0 72.1 74.3 69.7 71.8 66.9 68.8120090007 Florida Brevard 69.0 69.0 63.9 63.9 60.8 60.8 60.0 60.0120094001 Florida Brevard 71.3 72.0 66.3 66.9 62.9 63.5 62.0 62.6120110031 Florida Broward 62.0 63.0 60.7 61.6 60.4 61.3 60.3 61.2120112003 Florida Broward 61.3 63.0 58.1 59.7 57.1 58.7 56.9 58.5120118002 Florida Broward 65.0 67.0 62.3 64.2 61.5 63.4 61.3 63.1120210004 Florida Collier 68.3 69.0 60.4 61.0 58.1 58.7 57.8 58.3120230002 Florida Columbia 72.0 72.0 65.0 65.0 62.4 62.4 61.3 61.3120310077 Florida Duval 77.0 77.0 72.2 72.2 70.2 70.2 68.5 68.5120310100 Florida Duval 77.7 79.0 72.3 73.5 70.0 71.2 68.2 69.4120330004 Florida Escambia 79.7 81.0 75.9 77.2 74.3 75.6 69.6 70.8120330018 Florida Escambia 82.7 83.0 78.5 78.8 76.8 77.0 71.2 71.4120330024 Florida Escambia 80.7 81.0 76.6 76.9 74.9 75.2 69.4 69.7120570081 Florida Hillsborough 78.780.0 75.3 76.6 73.5 74.7 72.9 74.1120570110 Florida Hillsborough 76.076.0 70.5 70.5 68.9 68.9 68.3 68.3120571035 Florida Hillsborough 74.076.0 72.0 73.9 70.4 72.3 69.8 71.7120571065 Florida Hillsborough 80.781.0 77.9 78.2 76.0 76.2 75.1 75.4120573002 Florida Hillsborough 77.578.0 72.3 72.7 70.7 71.1 70.4 70.8120574004 Florida Hillsborough 74.074.0 68.1 68.1 66.4 66.4 66.0 66.0120690002 Florida Lake 76.7 77.0 69.9 70.2 66.8 67.1 66.1 66.4120712002 Florida Lee 70.3 72.0 62.8 64.4 60.7 62.1 60.3 61.7120713002 Florida Lee 70.3 71.0 62.8 63.4 60.6 61.2 60.1 60.7B-68-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues120730012 Florida Leon 70.0 70.0 61.5 61.5 59.0 59.0 58.3 58.3120730013 Florida Leon 71.0 72.0 62.2 63.1 59.5 60.3 58.8 59.6120813002 Florida Manatee 77.3 79.0 71.9 73.5 70.0 71.6 69.3 70.9120814012 Florida Manatee 76.3 77.0 69.4 70.0 67.5 68.1 66.7 67.4120814013 Florida Manatee 72.7 73.0 65.9 66.2 64.3 64.6 63.5 63.8120830003 Florida Marion 71.7 72.0 63.4 63.7 60.8 61.0 59.1 59.3120830004 Florida Marion 73.0 73.0 65.2 65.2 63.0 63.0 60.6 60.6120860027 Florida Miami-Dade 71.3 74.0 69.4 72.1 69.2 71.8 68.9 71.6120860029 Florida Miami-Dade 67.7 69.0 66.0 67.2 65.4 66.7 65.2 66.5120950008 Florida Orange 79.3 81.0 73.6 75.2 70.4 71.9 69.5 71.0120952002 Florida Orange 79.3 80.0 74.6 75.3 71.6 72.2 71.0 71.6120972002 Florida Osceola 72.0 73.0 66.1 67.0 63.3 64.2 62.6 63.5120990020 Florida Palm Beach 65.0 65.0 61.5 61.5 59.7 59.7 59.6 59.6121010005 Florida Pasco 76.3 77.0 70.5 71.1 68.8 69.5 67.4 68.0121012001 Florida Pasco 73.3 75.0 67.7 69.2 65.8 67.3 64.9 66.4121030004 Florida Pinellas 72.3 73.0 68.4 69.0 66.7 67.3 65.9 66.5121030018 Florida Pinellas 69.7 71.0 66.3 67.5 64.8 66.0 64.1 65.3121035002 Florida Pinellas 72.7 74.0 68.9 70.2 67.2 68.4 66.5 67.7121056005 Florida Polk 73.3 75.0 66.7 68.3 64.9 66.4 63.9 65.4121056006 Florida Polk 74.7 75.0 68.0 68.3 66.0 66.3 64.9 65.2121111002 Florida St. Lucie 66.5 68.0 60.9 62.3 58.7 60.1 58.3 59.6121130015 Florida Santa Rosa 80.0 80.0 76.3 76.3 74.5 74.5 69.0 69.0121151005 Florida Sarasota 77.3 78.0 69.4 70.1 67.5 68.1 66.8 67.4121151006 Florida Sarasota 73.3 74.0 65.9 66.6 64.1 64.7 63.4 64.0121152002 Florida Sarasota 72.0 74.0 63.5 65.3 61.7 63.4 60.9 62.6121171002 Florida Seminole 76.0 77.0 70.4 71.4 66.8 67.7 66.2 67.0121272001 Florida Volusia 68.3 69.0 61.4 62.0 57.6 58.2 56.8 57.3121275002 Florida Volusia 68.3 69.0 60.8 61.4 57.0 57.6 56.4 57.0121290001 Florida Wakulla 71.3 74.0 64.1 66.5 62.0 64.3 61.3 63.6130210012 Georgia Bibb 81.0 83.0 71.1 72.8 66.1 67.8 65.8 67.5B-78-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues130210013 Georgia Bibb 81.0 81.0 71.4 71.4 66.0 66.0 65.7 65.7130510021 Georgia Chatham 68.3 69.0 62.2 62.9 59.9 60.5 59.4 60.0130550001 Georgia Chattooga 75.0 76.0 64.3 65.2 60.8 61.6 60.6 61.4130590002 Georgia Clarke 80.7 83.0 68.7 70.6 64.5 66.4 64.3 66.2130670003 Georgia Cobb 82.7 87.0 73.8 77.6 69.9 73.5 69.7 73.4130730001 Georgia Columbia 73.0 73.0 64.5 64.5 61.7 61.7 61.4 61.4130770002 Georgia Coweta 82.0 85.0 74.3 77.0 69.7 72.2 68.7 71.2130850001 Georgia Dawson 76.3 79.0 66.1 68.5 62.4 64.6 62.2 64.4130890002 Georgia DeKalb 88.7 93.0 81.6 85.6 78.2 82.0 78.1 81.8130893001 Georgia DeKalb 87.5 88.0 80.7 81.2 77.7 78.1 77.5 77.9130970004 Georgia Douglas 87.3 90.0 77.8 80.2 73.2 75.4 73.0 75.2131130001 Georgia Fayette 85.7 89.0 78.2 81.2 74.9 77.8 74.7 77.6131210055 Georgia Fulton 91.7 94.0 84.4 86.5 80.9 82.9 80.7 82.7131270006 Georgia Glynn 67.0 68.0 61.7 62.6 59.6 60.5 57.7 58.5131350002 Georgia Gwinnett 88.7 90.0 79.1 80.3 75.3 76.4 75.1 76.2131510002 Georgia Henry 89.7 95.0 79.7 84.5 75.7 80.2 75.5 80.0132130003 Georgia Murray 78.0 79.0 68.9 69.8 65.6 66.5 64.9 65.7132150008 Georgia Muscogee 75.7 80.0 65.5 69.2 61.9 65.4 61.5 65.0132151003 Georgia Muscogee 70.7 73.0 61.4 63.4 58.0 59.9 57.7 59.5132230003 Georgia Paulding 80.3 83.0 69.2 71.5 65.1 67.2 64.9 67.1132450091 Georgia Richmond 80.3 81.0 70.8 71.4 67.8 68.4 67.4 68.0132470001 Georgia Rockdale 90.095.0 78.8 83.2 74.5 78.6 74.3 78.4132611001 Georgia Sumter 72.3 74.0 64.4 65.9 61.3 62.8 60.9 62.3170010006 Illinois Adams 70.0 70.0 64.8 64.8 63.4 63.4 62.6 62.6170190004 Illinois Champaign 68.370.0 62.3 63.8 60.9 62.4 60.6 62.1170230001 Illinois Clark 66.0 66.0 59.8 59.8 58.4 58.4 58.0 58.0170310001 Illinois Cook 77.3 82.075.9 80.5 74.8 79.4 74.7 79.2170310032 Illinois Cook 74.3 77.071.1 73.7 70.1 72.6 69.9 72.4170310064 Illinois Cook 71.3 77.068.2 73.7 67.2 72.6 67.0 72.4170310072 Illinois Cook 71.0 73.067.7 69.6 66.7 68.6 66.5 68.4B-88-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues170310076 Illinois Cook 77.0 79.075.8 77.8 75.0 77.0 74.8 76.8170311003 Illinois Cook 76.3 79.073.6 76.2 72.7 75.3 72.5 75.1170311601 Illinois Cook 76.7 80.074.8 78.0 73.6 76.7 73.5 76.6170314002 Illinois Cook 66.3 68.065.9 67.6 65.4 67.0 65.2 66.9170314007 Illinois Cook 71.7 74.069.2 71.4 68.3 70.5 68.2 70.4170314201 Illinois Cook 74.3 76.071.7 73.4 70.8 72.4 70.7 72.3170317002 Illinois Cook 77.7 79.074.7 76.0 73.7 74.9 73.4 74.6170436001 Illinois DuPage 69.0 70.0 67.4 68.3 66.5 67.5 66.4 67.4170491001 Illinois Effingham 70.0 72.0 63.8 65.6 62.3 64.1 62.1 63.9170650002 Illinois Hamilton 73.0 73.0 66.2 66.2 64.5 64.5 64.6 64.6170831001 Illinois Jersey 78.7 80.0 71.4 72.6 69.4 70.6 68.9 70.0170890005 Illinois Kane 74.3 77.0 69.9 72.4 68.5 71.0 68.3 70.8170971002 Illinois Lake 76.7 79.0 73.7 75.9 72.6 74.7 72.3 74.5170971007 Illinois Lake 78.0 79.0 75.0 75.9 73.8 74.7 73.5 74.5171110001 Illinois McHenry 73.3 78.0 68.3 72.7 66.7 71.0 66.5 70.7171132003 Illinois McLean 73.0 74.0 65.7 66.6 63.8 64.7 63.5 64.4171150013 Illinois Macon 71.3 74.0 64.8 67.2 63.3 65.7 62.8 65.2171170002 Illinois Macoupin 73.0 74.0 64.4 65.3 62.3 63.1 61.7 62.5171190008 Illinois Madison 82.7 84.0 75.8 77.0 73.7 74.9 73.0 74.2171191009 Illinois Madison 83.0 84.0 76.5 77.4 74.4 75.3 73.8 74.7171193007 Illinois Madison 81.0 83.0 74.3 76.1 72.2 74.0 71.5 73.3171430024 Illinois Peoria 68.3 71.0 61.9 64.3 59.9 62.2 59.7 62.0171431001 Illinois Peoria 72.7 76.0 65.9 68.9 63.7 66.6 63.5 66.4171570001 Illinois Randolph 72.0 75.0 65.5 68.2 63.8 66.4 63.7 66.4171613002 Illinois Rock Island 65.368.0 60.8 63.3 59.5 61.9 58.4 60.8171630010 Illinois Saint Clair 81.782.0 76.5 76.8 74.9 75.2 74.3 74.6171670010 Illinois Sangamon 70.0 71.0 61.6 62.5 59.9 60.7 59.5 60.4171971011 Illinois Will 71.7 72.0 67.5 67.8 66.0 66.3 65.9 66.1172010009 Illinois Winnebago 69.0 71.0 62.4 64.2 60.5 62.3 60.3 62.0172012001 Illinois Winnebago 68.3 70.0 61.8 63.3 59.9 61.4 59.7 61.1B-98-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues180030002 Indiana Allen 79.3 83.0 71.6 74.9 69.4 72.6 69.2 72.4180030004 Indiana Allen 74.3 76.0 67.1 68.6 65.0 66.5 64.8 66.3180110001 Indiana Boone 79.7 81.0 72.1 73.3 69.8 70.9 69.4 70.5180150002 Indiana Carroll 74.0 75.0 67.1 68.0 65.2 66.1 64.9 65.7180190008 Indiana Clark 80.3 83.0 74.4 76.9 72.4 74.8 71.6 74.0180350010 Indiana Delaware 76.378.0 68.3 69.8 65.9 67.3 65.5 67.0180390007 Indiana Elkhart 79.0 83.0 71.0 74.6 68.8 72.3 68.4 71.8180431004 Indiana Floyd 77.7 79.0 72.6 73.8 70.8 72.0 70.1 71.2180550001 Indiana Greene 78.3 80.0 71.0 72.5 69.3 70.8 68.8 70.2180570005 Indiana Hamilton 82.7 87.0 75.3 79.2 72.8 76.6 72.3 76.1180590003 Indiana Hancock 78.0 81.0 71.3 74.0 69.0 71.7 68.5 71.1180630004 Indiana Hendricks 75.3 76.0 68.8 69.5 66.8 67.4 66.4 67.0180690002 Indiana Huntington 75.0 76.0 67.6 68.5 65.5 66.4 65.4 66.2180710001 Indiana Jackson 74.7 76.0 66.5 67.6 64.7 65.8 64.2 65.3180810002 Indiana Johnson 76.7 78.0 69.3 70.5 67.2 68.3 66.6 67.8180890022 Indiana Lake 77.7 82.0 73.6 77.7 72.5 76.5 72.2 76.2180890030 Indiana Lake 81.0 85.0 76.9 80.7 75.9 79.6 75.5 79.3180892008 Indiana Lake 77.7 79.0 73.8 75.0 72.8 74.0 72.5 73.7180910005 Indiana LaPorte 77.0 78.0 71.5 72.4 70.0 70.9 69.7 70.6180910010 Indiana LaPorte 78.5 79.0 72.6 73.0 70.9 71.4 70.6 71.1180950010 Indiana Madison 76.7 80.0 69.2 72.1 66.8 69.7 66.3 69.2180970042 Indiana Marion 72.7 76.0 68.0 71.1 66.3 69.3 65.6 68.5180970050 Indiana Marion 78.7 81.0 72.4 74.5 70.4 72.4 69.9 72.0180970057 Indiana Marion 75.0 77.0 69.7 71.5 67.9 69.7 67.4 69.2180970073 Indiana Marion 75.7 77.0 70.0 71.2 68.1 69.3 67.6 68.8181090005 Indiana Morgan 77.0 79.0 70.3 72.1 68.1 69.9 67.4 69.2181230009 Indiana Perry 81.0 81.0 75.5 75.5 73.1 73.1 73.0 73.0181270024 Indiana Porter 78.3 81.0 73.7 76.2 72.4 74.9 72.1 74.6181270026 Indiana Porter 75.3 77.0 69.9 71.5 68.5 70.0 68.1 69.6181290003 Indiana Posey 71.7 75.0 64.8 67.8 62.8 65.7 62.8 65.7B-108-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues181410010 Indiana St. Joseph 74.7 77.0 67.5 69.6 65.6 67.6 65.1 67.1181410015 Indiana St. Joseph 74.3 79.0 67.1 71.4 65.1 69.3 64.7 68.8181411007 Indiana St. Joseph 79.3 82.0 71.6 74.1 69.5 71.9 69.0 71.4181450001 Indiana Shelby 77.3 80.0 71.8 74.3 70.0 72.4 69.3 71.7181630012 Indiana Vanderburgh 77.3 80.0 70.3 72.8 68.1 70.5 68.3 70.7181630013 Indiana Vanderburgh 67.7 75.0 61.1 67.7 59.1 65.5 59.2 65.6181670018 Indiana Vigo 63.0 67.0 57.7 61.3 56.2 59.8 55.6 59.1181670024 Indiana Vigo 74.0 76.0 68.1 69.9 66.5 68.3 65.6 67.4181730008 Indiana Warrick 77.7 80.0 71.8 73.9 69.9 72.0 70.2 72.3181730009 Indiana Warrick 72.7 75.0 66.0 68.1 64.1 66.1 64.0 66.0181730011 Indiana Warrick 76.7 77.0 71.0 71.3 69.1 69.3 69.4 69.7190450021 Iowa Clinton 71.3 73.0 66.0 67.5 64.5 66.0 63.7 65.2190851101 Iowa Harrison 74.7 75.0 69.5 69.8 68.2 68.4 66.4 66.7191130028 Iowa Linn 67.7 71.0 63.0 66.1 61.6 64.6 61.0 63.9191130033 Iowa Linn 68.3 70.0 63.7 65.3 62.2 63.8 61.1 62.6191530058 Iowa Polk 63.0 66.0 58.2 61.0 56.6 59.3 56.1 58.7191630014 Iowa Scott 70.3 74.0 64.8 68.2 63.2 66.5 62.3 65.6191632011 Iowa Scott 72.0 72.0 66.6 66.6 65.0 65.0 63.9 63.9191690011 Iowa Story 61.0 66.0 56.1 60.7 54.7 59.1 53.8 58.2200450004 Kansas Douglas 73.0 73.0 66.6 66.6 65.1 65.1 63.2 63.2200910010 Kansas Johnson 75.3 76.070.4 71.0 68.9 69.6 66.7 67.4201030003 Kansas Leavenworth 75.0 77.0 69.5 71.4 68.0 69.8 66.5 68.3201070002 Kansas Linn 73.3 74.0 68.3 69.0 67.1 67.7 63.0 63.6201730001 Kansas Sedgwick 64.3 66.0 58.6 60.2 56.9 58.4 56.1 57.6201730010 Kansas Sedgwick 71.3 74.0 65.5 68.0 63.6 66.1 62.8 65.2201910002 Kansas Sumner 71.7 76.0 64.9 68.8 62.9 66.7 62.3 66.0202090021 Kansas Wyandotte 75.3 77.0 71.1 72.7 69.8 71.4 68.1 69.6210130002 Kentucky Bell 71.7 74.0 61.9 63.9 59.2 61.1 59.0 60.9210150003 Kentucky Boone 75.7 77.0 67.8 68.9 66.0 67.1 65.2 66.3210190017 Kentucky Boyd 77.3 79.0 69.5 71.0 68.0 69.4 67.8 69.2B-118-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues210290006 Kentucky Bullitt 74.0 76.0 68.8 70.7 67.0 68.8 66.3 68.1210370003 Kentucky Campbell 75.0 83.0 70.2 77.7 68.7 76.1 68.0 75.3210430500 Kentucky Carter 71.0 72.0 62.8 63.7 61.2 62.0 61.0 61.8210470006 Kentucky Christian 78.081.0 67.9 70.5 65.6 68.1 65.3 67.8210590005 Kentucky Daviess 75.7 81.0 70.3 75.3 68.3 73.1 68.3 73.1210610501 Kentucky Edmonson 73.7 76.0 65.7 67.7 63.5 65.5 63.4 65.4210670001 Kentucky Fayette 62.7 65.0 56.8 58.8 54.9 56.9 54.6 56.6210670012 Kentucky Fayette 70.3 73.0 63.6 66.1 61.5 63.9 61.2 63.6210890007 Kentucky Greenup 76.7 78.0 69.1 70.3 67.6 68.7 67.4 68.6210910012 Kentucky Hancock 74.076.0 68.9 70.7 66.8 68.6 66.8 68.6210930006 Kentucky Hardin 74.7 78.0 67.6 70.6 65.6 68.5 65.2 68.1211010014 Kentucky Henderson 75.378.0 69.2 71.7 67.2 69.7 67.4 69.8211110027 Kentucky Jefferson 75.379.0 70.5 73.9 68.5 71.9 67.9 71.2211110051 Kentucky Jefferson 78.382.0 73.3 76.7 71.7 75.1 70.8 74.1211111021 Kentucky Jefferson 71.073.0 66.9 68.8 65.3 67.2 64.7 66.5211130001 Kentucky Jessamine 73.377.0 66.6 70.0 64.6 67.8 64.3 67.5211170007 Kentucky Kenton 78.7 81.0 73.1 75.3 71.5 73.6 70.8 72.9211390003 Kentucky Livingston 73.775.0 68.2 69.4 66.3 67.5 66.3 67.5211451024 Kentucky McCracken 73.3 76.0 68.2 70.7 66.5 69.0 66.3 68.7211490001 Kentucky McLean 73.0 73.0 67.1 67.1 65.0 65.0 65.2 65.2211850004 Kentucky Oldham 83.0 85.0 75.3 77.1 72.8 74.5 72.1 73.9211950002 Kentucky Pike 66.7 70.0 58.6 61.5 56.7 59.5 56.7 59.5211990003 Kentucky Pulaski 70.3 72.0 65.1 66.7 60.8 62.3 60.3 61.8212130004 Kentucky Simpson 75.7 78.0 65.9 67.9 63.3 65.3 63.2 65.1212210013 Kentucky Trigg 70.0 70.0 63.8 63.8 61.8 61.8 61.8 61.8212270008 Kentucky Warren 72.0 73.0 63.6 64.5 61.6 62.5 61.4 62.3220050004 Louisiana Ascension 82.0 84.0 76.9 78.8 75.3 77.2 75.0 76.9220110002 Louisiana Beauregard 75.0 75.0 71.3 71.3 70.4 70.4 69.7 69.7220150008 Louisiana Bossier 78.0 79.0 69.6 70.5 67.2 68.0 66.9 67.8220170001 Louisiana Caddo 79.0 80.0 70.7 71.6 68.3 69.2 67.9 68.7B-128-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues220190002 Louisiana Calcasieu 82.083.0 78.0 78.9 76.8 77.8 76.2 77.1220190008 Louisiana Calcasieu 70.071.0 66.8 67.7 65.9 66.9 65.5 66.4220190009 Louisiana Calcasieu 78.780.0 73.3 74.5 71.9 73.1 71.2 72.4220330003 Louisiana East Baton Rouge 92.0 96.0 87.8 91.6 86.4 90.2 86.0 89.7220330009 Louisiana East Baton Rouge 80.3 81.0 76.5 77.2 75.3 75.9 74.9 75.6220330013 Louisiana East Baton Rouge 81.3 82.0 76.4 77.1 75.0 75.7 74.8 75.5220331001 Louisiana East Baton Rouge 86.0 87.0 82.9 83.8 81.7 82.7 81.5 82.5220430001 Louisiana Grant 73.0 73.0 68.7 68.7 66.9 66.9 63.8 63.8220470007 Louisiana Iberville 84.0 86.0 79.1 81.0 77.6 79.4 77.1 78.9220470009 Louisiana Iberville 80.0 81.0 75.5 76.5 74.2 75.1 73.7 74.6220470012 Louisiana Iberville 85.0 86.0 80.3 81.3 78.9 79.8 78.5 79.5220511001 Louisiana Jefferson 83.0 84.0 78.5 79.4 76.9 77.9 76.5 77.4220550005 Louisiana Lafayette 82.0 82.0 76.0 76.0 74.0 74.0 73.3 73.3220550007 Louisiana Lafayette 66.0 66.0 61.1 61.1 59.6 59.6 59.0 59.0220570004 Louisiana Lafourche 79.3 80.0 74.4 75.1 73.0 73.6 72.5 73.2220630002 Louisiana Livingston 78.3 80.0 72.9 74.5 71.3 72.8 71.1 72.6220710012 Louisiana Orleans 70.0 70.0 66.9 66.9 65.7 65.7 65.3 65.3220730004 Louisiana Ouachita 75.3 77.0 68.8 70.3 66.8 68.3 66.1 67.6220770001 Louisiana Pointe Coupee 83.7 86.0 78.8 81.0 77.4 79.5 77.2 79.3220870002 Louisiana St. Bernard 78.0 78.0 74.7 74.7 73.6 73.6 73.3 73.3220890003 Louisiana St. Charles 77.3 78.0 73.1 73.8 71.8 72.4 71.4 72.0220930002 Louisiana St. James 76.3 77.0 71.9 72.6 70.7 71.3 70.3 71.0220950002 LouisianaSt. John theBaptist 79.0 80.0 74.8 75.7 73.7 74.6 73.3 74.3221010003 Louisiana St. Mary 76.0 76.0 70.3 70.3 68.6 68.6 68.1 68.1221210001 LouisianaWest BatonRouge 84.3 85.0 80.3 81.0 79.0 79.7 78.7 79.3230050027 Maine Cumberland 60.0 61.0 52.5 53.3 50.8 51.6 50.8 51.6230052003 Maine Cumberland 72.0 75.0 63.0 65.6 60.9 63.5 60.9 63.5230090102 Maine Hancock 82.0 83.0 72.3 73.2 70.4 71.2 70.4 71.2B-138-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues230090103 Maine Hancock 73.0 74.0 64.4 65.3 62.6 63.4 62.6 63.4230090301 Maine Hancock 68.7 70.0 60.4 61.6 58.7 59.8 58.7 59.8230112005 Maine Kennebec 69.7 71.0 60.9 62.1 59.1 60.2 59.1 60.2230130004 Maine Knox 75.3 77.0 65.8 67.3 63.8 65.3 63.8 65.3230173001 Maine Oxford 61.0 63.0 54.3 56.1 52.6 54.4 52.7 54.4230194008 Maine Penobscot 67.0 68.0 59.2 60.0 57.5 58.4 57.5 58.4230230004 Maine Sagadahoc 68.5 70.0 59.8 61.1 57.9 59.2 57.9 59.2230310038 Maine York 73.7 75.0 64.2 65.3 62.0 63.1 62.0 63.1230312002 Maine York 74.0 74.0 65.3 65.3 63.2 63.2 63.2 63.2230313002 Maine York 74.0 77.0 65.2 67.8 63.1 65.6 63.1 65.6240030014 Maryland Anne Arundel 89.790.0 79.7 79.9 77.1 77.4 77.0 77.2240051007 Maryland Baltimore 77.3 78.0 71.2 71.8 69.6 70.3 69.5 70.2240053001 Maryland Baltimore 85.3 87.0 78.5 80.1 76.9 78.4 76.8 78.3240090011 Maryland Calvert 81.0 81.0 69.8 69.8 67.7 67.7 67.6 67.6240130001 Maryland Carroll 83.3 86.0 73.0 75.4 70.5 72.8 70.4 72.7240150003 Maryland Cecil 90.7 93.0 79.1 81.1 76.9 78.9 76.8 78.8240170010 Maryland Charles 86.0 88.0 73.8 75.5 71.2 72.9 71.1 72.8240210037 Maryland Frederick 80.3 83.0 70.4 72.7 67.9 70.2 67.9 70.2240230002 Maryland Garrett 75.5 76.0 68.4 68.8 66.9 67.3 66.1 66.5240251001 Maryland Harford 92.7 94.0 83.5 84.7 81.6 82.8 81.5 82.7240259001 Maryland Harford 88.3 91.0 78.3 80.7 76.5 78.8 76.4 78.7240290002 Maryland Kent 82.0 83.0 71.6 72.5 69.7 70.6 69.6 70.4240313001 Maryland Montgomery 83.0 86.0 76.4 79.1 74.5 77.1 74.4 77.1240330030 Maryland Prince George's 85.0 85.0 77.3 77.3 75.1 75.1 75.0 75.0240338003 Maryland Prince George's 91.0 91.0 81.2 81.2 78.7 78.7 78.5 78.5240430009 Maryland Washington 78.3 79.0 68.4 69.0 66.1 66.7 66.0 66.6250010002 Massachusetts Barnstable84.7 86.0 75.1 76.2 73.1 74.2 73.1 74.2250034002 Massachusetts Berkshire 79.7 81.0 70.8 72.0 68.7 69.8 68.6 69.7250051002 Massachusetts Bristol 82.7 86.0 73.6 76.5 71.7 74.5 71.6 74.5250070001 Massachusetts Dukes 83.0 84.0 74.8 75.7 72.9 73.8 72.9 73.8B-148-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues250092006 Massachusetts Essex 83.3 84.0 76.7 77.3 74.8 75.5 74.9 75.5250094004 Massachusetts Essex 77.7 79.0 69.0 70.2 66.8 68.0 66.9 68.0250095005 Massachusetts Essex 77.5 80.0 68.3 70.5 66.1 68.2 66.1 68.2250130008 Massachusetts Hampden 87.3 92.0 76.9 81.0 74.4 78.4 74.3 78.3250150103 Massachusetts Hampshire 71.7 77.0 62.4 67.0 60.2 64.7 60.2 64.7250154002 Massachusetts Hampshire 85.0 87.0 74.6 76.4 72.2 73.9 72.2 73.9250170009 Massachusetts Middlesex 79.0 79.0 69.4 69.4 67.0 67.0 67.0 67.0250171102 Massachusetts Middlesex 77.3 81.0 67.8 71.1 65.6 68.7 65.5 68.6250213003 Massachusetts Norfolk 84.7 86.0 76.5 77.7 74.2 75.4 74.2 75.3250250041 Massachusetts Suffolk 80.3 81.0 72.8 73.5 70.8 71.4 70.8 71.4250250042 Massachusetts Suffolk 67.3 68.0 61.7 62.3 60.1 60.7 60.1 60.7250270015 Massachusetts Worcester 80.0 83.0 69.7 72.3 67.4 69.9 67.3 69.9260050003 Michigan Allegan 90.0 93.0 82.0 84.7 79.9 82.5 79.4 82.1260190003 Michigan Benzie 81.7 83.0 74.7 75.9 72.7 73.9 72.3 73.5260210014 Michigan Berrien 82.3 84.0 75.5 77.0 73.6 75.1 73.2 74.7260270003 Michigan Cass 80.7 84.0 72.4 75.4 70.3 73.2 69.7 72.5260370001 Michigan Clinton 75.7 78.0 67.0 69.1 64.8 66.7 64.5 66.4260490021 Michigan Genesee 77.3 80.0 69.7 72.2 67.6 70.0 67.3 69.7260492001 Michigan Genesee 79.3 82.0 71.9 74.4 69.9 72.3 69.6 72.0260630007 Michigan Huron 75.7 78.0 69.3 71.4 67.6 69.7 67.4 69.4260650012 Michigan Ingham 76.0 78.0 67.5 69.2 65.2 66.9 64.9 66.6260770008 Michigan Kalamazoo 75.3 78.0 67.8 70.3 65.8 68.1 65.4 67.7260810020 Michigan Kent 79.3 83.0 71.3 74.7 69.1 72.3 68.6 71.9260810022 Michigan Kent 81.0 83.0 72.2 74.0 69.9 71.6 69.4 71.1260890001 Michigan Leelanau 75.7 77.0 69.7 70.9 68.0 69.1 67.6 68.7260910007 Michigan Lenawee 78.7 81.0 71.4 73.4 69.7 71.8 69.2 71.2260990009 Michigan Macomb 86.0 90.0 80.1 83.8 78.6 82.3 78.3 82.0260991003 Michigan Macomb 84.0 87.0 79.7 82.5 78.3 81.1 78.2 81.0261050007 Michigan Mason 79.7 81.0 72.4 73.6 70.5 71.6 69.9 71.0261130001 Michigan Missaukee 73.7 75.0 66.6 67.8 64.9 66.0 64.3 65.5B-158-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues261210039 Michigan Muskegon 85.0 88.0 77.5 80.2 75.5 78.2 75.1 77.7261250001 Michigan Oakland 78.0 81.0 73.7 76.6 72.6 75.4 72.3 75.1261390005 Michigan Ottawa 81.7 85.0 73.8 76.8 71.7 74.6 71.2 74.1261470005 Michigan St. Clair 82.3 85.0 75.0 77.4 73.0 75.4 72.7 75.1261530001 Michigan Schoolcraft 79.3 82.0 72.0 74.4 70.1 72.4 69.8 72.2261610008 Michigan Washtenaw 78.3 81.0 72.5 75.0 71.1 73.6 70.8 73.2261630001 Michigan Wayne 73.0 75.0 68.2 70.0 66.9 68.7 66.6 68.4261630016 Michigan Wayne 73.5 76.0 68.0 70.3 66.6 68.8 66.3 68.6261630019 Michigan Wayne 82.0 83.0 77.1 78.0 75.7 76.6 75.4 76.3270031002 Minnesota Anoka 67.7 69.0 66.9 68.2 66.4 67.7 65.7 67.0280330002 Mississippi DeSoto 82.7 85.0 73.5 75.6 70.8 72.8 70.5 72.4280450001 Mississippi Hancock 79.0 79.0 72.2 72.2 70.2 70.2 68.9 68.9280470008 Mississippi Harrison 83.0 83.0 76.9 76.9 75.0 75.0 71.5 71.5280470009 Mississippi Harrison 77.0 77.0 71.8 71.8 70.4 70.4 68.1 68.1280490010 Mississippi Hinds 71.3 73.0 59.4 60.8 56.6 57.9 56.3 57.6280590006 Mississippi Jackson 80.3 81.0 74.5 75.2 72.8 73.4 69.9 70.5280590007 Mississippi Jackson 74.0 74.0 68.8 68.8 67.3 67.3 63.5 63.5280750003 Mississippi Lauderdale 74.3 76.0 65.2 66.6 62.3 63.7 62.1 63.5280810005 Mississippi Lee 73.7 75.0 64.2 65.3 61.3 62.4 61.2 62.2290370003 Missouri Cass 74.7 77.0 69.2 71.3 67.9 70.0 64.8 66.8290390001 Missouri Cedar 75.7 76.0 70.0 70.3 68.3 68.6 66.1 66.3290470003 Missouri Clay 79.0 81.0 72.2 74.0 70.4 72.2 68.1 69.8290470005 Missouri Clay 84.3 87.0 78.2 80.7 76.5 78.9 74.3 76.7290470006 Missouri Clay 83.0 87.0 76.8 80.5 75.0 78.6 73.0 76.5290490001 Missouri Clinton 83.0 85.0 76.4 78.2 74.5 76.3 72.4 74.1290770036 Missouri Greene 73.0 77.0 66.2 69.8 64.6 68.1 63.5 67.0290990012 Missouri Jefferson 82.3 86.0 77.5 80.9 75.6 79.1 75.3 78.7291130003 Missouri Lincoln 87.0 87.0 78.8 78.8 76.6 76.6 76.2 76.2291370001 Missouri Monroe 71.7 75.0 66.0 69.0 64.5 67.4 63.6 66.6291570001 Missouri Perry 77.5 80.0 70.3 72.5 68.4 70.6 68.3 70.5B-168-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues291650023 Missouri Platte 77.0 77.0 71.8 71.8 70.3 70.3 68.6 68.6291831002 Missouri Saint Charles 86.3 89.0 79.9 82.4 77.9 80.3 77.2 79.6291831004 Missouri Saint Charles 87.0 89.0 79.9 81.8 77.7 79.5 77.3 79.1291860005 Missouri Sainte Genevieve79.7 83.0 72.5 75.5 70.5 73.4 70.0 72.9291890004 Missouri Saint Louis 82.3 86.0 78.5 82.1 77.0 80.4 76.6 80.1291890005 Missouri Saint Louis 83.0 83.0 77.0 77.0 74.9 74.9 74.5 74.5291890006 Missouri Saint Louis 78.0 78.0 73.3 73.3 71.6 71.6 71.2 71.2291890014 Missouri Saint Louis 88.0 88.0 83.0 83.0 81.1 81.1 80.7 80.7295100085 Missouri St. Louis City 84.0 84.0 80.3 80.3 78.8 78.8 78.2 78.2295100086 Missouri St. Louis City 83.0 86.0 79.4 82.2 77.8 80.6 77.2 80.0310550028 Nebraska Douglas 68.7 70.0 64.5 65.7 63.6 64.8 62.5 63.6310550032 Nebraska Douglas 64.7 66.0 60.5 61.7 59.4 60.6 58.4 59.6310550035 Nebraska Douglas 66.3 68.0 62.4 64.0 61.3 62.9 60.2 61.7311090016 Nebraska Lancaster 56.0 57.0 51.6 52.5 50.5 51.4 49.8 50.7330012004 New Hampshire Belknap 71.3 73.0 63.3 64.8 61.1 62.5 61.1 62.5330050007 New Hampshire Cheshire 70.7 71.0 62.2 62.5 60.2 60.4 60.1 60.4330074001 New Hampshire Coos 77.0 77.0 69.1 69.1 67.1 67.1 67.1 67.1330074002 New Hampshire Coos 65.0 67.0 58.3 60.1 56.7 58.4 56.7 58.4330090010 New Hampshire Grafton 67.0 67.0 59.0 59.0 57.0 57.0 57.0 57.0330110020 New Hampshire Hillsborough 70.3 71.0 61.2 61.8 59.0 59.6 59.0 59.6330111011 New Hampshire Hillsborough 78.7 80.0 68.6 69.7 66.1 67.2 66.1 67.2330115001 New Hampshire Hillsborough 78.3 80.0 68.9 70.4 66.6 68.1 66.6 68.0330131007 New Hampshire Merrimack 71.7 72.0 62.4 62.6 60.3 60.5 60.2 60.5330150014 New Hampshire Rockingham 74.7 75.0 65.8 66.0 63.7 63.9 63.7 63.9330150016 New Hampshire Rockingham 75.0 79.0 66.0 69.6 63.9 67.3 63.9 67.3330190003 New Hampshire Sullivan 70.0 72.0 61.9 63.7 59.9 61.7 59.9 61.6340010005 New Jersey Atlantic 79.3 82.0 70.7 73.1 68.7 71.0 68.6 71.0340030005 New Jersey Bergen 86.0 86.0 82.2 82.2 80.8 80.8 80.7 80.7340070003 New Jersey Camden 85.7 88.0 79.6 81.8 78.2 80.3 78.2 80.3340071001 New Jersey Camden 89.3 91.0 80.9 82.4 78.7 80.1 78.6 80.1B-178-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues340110007 New Jersey Cumberland 83.3 84.0 73.5 74.1 71.4 72.0 71.3 71.9340150002 New Jersey Gloucester 87.0 88.0 79.5 80.4 77.7 78.6 77.6 78.5340170006 New Jersey Hudson 85.7 89.0 80.1 83.2 78.6 81.7 78.5 81.5340190001 New Jersey Hunterdon 89.0 90.0 79.3 80.2 76.6 77.4 76.5 77.4340210005 New Jersey Mercer 88.0 91.0 81.4 84.1 79.3 82.0 79.3 82.0340230011 New Jersey Middlesex 88.3 91.0 80.2 82.6 77.8 80.2 77.8 80.2340250005 New Jersey Monmouth 87.3 89.0 79.5 81.0 77.5 79.0 77.4 78.9340273001 New Jersey Morris 83.3 86.0 75.0 77.5 72.7 75.0 72.6 75.0340290006 New Jersey Ocean 93.094.0 83.3 84.2 80.8 81.7 80.7 81.6340315001 New Jersey Passaic 81.0 83.0 75.0 76.9 73.2 75.1 73.2 75.0350130008 New Mexico Dona Ana 70.7 72.0 66.9 68.1 66.5 67.8 66.5 67.7350130017 New Mexico Dona Ana 71.3 72.0 67.3 67.9 66.7 67.3 66.7 67.3350130021 New Mexico Dona Ana 75.3 77.0 71.0 72.7 70.4 72.0 70.4 72.0350130022 New Mexico Dona Ana 72.7 74.0 68.5 69.8 67.9 69.1 67.8 69.0350450009 New Mexico San Juan 69.7 72.0 66.4 68.6 65.9 68.1 65.9 68.1350451005 New Mexico San Juan 71.3 72.0 68.1 68.8 67.6 68.3 67.6 68.3360010012 New York Albany 73.7 76.0 65.9 67.9 63.9 65.9 63.9 65.9360050110 New York Bronx 74.0 76.0 68.9 70.8 67.6 69.5 67.5 69.3360050133 New York Bronx 74.7 75.0 72.0 72.3 71.0 71.2 70.8 71.1360130006 New York Chautauqua 86.7 89.0 79.3 81.4 77.4 79.5 77.2 79.2360130011 New York Chautauqua 77.3 79.0 70.5 72.1 68.8 70.3 68.5 70.0360150003 New York Chemung 68.7 70.0 61.2 62.4 59.6 60.7 59.4 60.5360270007 New York Dutchess 75.7 79.0 67.3 70.2 65.4 68.2 65.3 68.2360290002 New York Erie 85.0 86.0 77.5 78.4 75.6 76.5 75.4 76.2360410005 New York Hamilton 71.7 73.0 65.5 66.7 64.1 65.2 63.9 65.1360430005 New York Herkimer 68.3 70.0 63.0 64.6 61.9 63.4 61.7 63.2360450002 New York Jefferson 78.0 80.0 71.2 73.0 69.6 71.4 69.6 71.4360530006 New York Madison 72.0 73.0 64.1 64.9 62.5 63.4 62.4 63.2360551007 New York Monroe 75.0 80.0 68.9 73.5 67.4 71.9 67.2 71.7360631006 New York Niagara 82.7 86.0 76.1 79.2 74.7 77.7 74.6 77.5B-188-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues360650004 New York Oneida 68.3 72.0 61.5 64.8 59.9 63.2 59.8 63.0360671015 New York Onondaga 73.7 76.0 66.6 68.7 65.0 67.0 64.9 66.9360715001 New York Orange 82.0 84.0 73.3 75.1 71.0 72.7 71.0 72.7360750003 New York Oswego 78.0 82.0 71.1 74.8 69.6 73.1 69.4 73.0360790005 New York Putnam 84.3 86.0 76.8 78.4 74.7 76.2 74.6 76.1360810098 New York Queens 69.0 69.0 64.3 64.3 63.1 63.1 62.9 62.9360810124 New York Queens 80.0 82.0 75.1 77.0 73.8 75.7 73.7 75.5360830004 New York Rensselaer 77.3 80.0 69.1 71.5 67.1 69.4 67.1 69.4360850067 New York Richmond 88.3 89.0 82.6 83.2 80.8 81.4 80.7 81.3360910004 New York Saratoga 79.7 82.0 71.3 73.4 69.2 71.2 69.2 71.2360930003 New York Schenectady 70.0 74.0 62.8 66.4 60.9 64.4 60.9 64.4361030002 New York Suffolk 90.0 91.0 86.3 87.2 84.9 85.9 84.8 85.7361030004 New York Suffolk 84.7 90.0 78.6 83.6 76.8 81.6 76.6 81.4361030009 New York Suffolk 90.3 91.0 85.1 85.8 83.7 84.4 83.6 84.3361111005 New York Ulster 77.3 79.0 68.4 69.9 66.3 67.7 66.2 67.6361173001 New York Wayne 68.0 71.0 62.1 64.8 60.7 63.4 60.6 63.2361192004 New York Westchester 87.7 90.0 84.7 86.9 83.5 85.6 83.4 85.5370030004 North Carolina Alexander 77.0 79.0 67.8 69.6 65.5 67.2 65.4 67.1370110002 North Carolina Avery 70.0 72.0 60.0 61.8 57.7 59.3 57.5 59.2370210030 North Carolina Buncombe 74.0 74.0 63.8 63.8 61.2 61.2 61.0 61.0370270003 North Carolina Caldwell 74.3 76.0 63.7 65.1 61.1 62.5 60.9 62.3370330001 North Carolina Caswell 76.3 77.0 65.5 66.1 62.7 63.3 62.5 63.0370370004 North Carolina Chatham 73.3 74.0 63.1 63.7 60.5 61.1 60.3 60.9370510008 North Carolina Cumberland 78.0 80.0 67.3 69.1 64.4 66.1 64.2 65.9370511003 North Carolina Cumberland 81.7 83.0 70.5 71.7 67.6 68.7 67.4 68.5370590002 North Carolina Davie 81.3 83.0 71.0 72.5 68.4 69.8 68.1 69.6370630013 North Carolina Durham 77.0 78.0 66.8 67.7 63.8 64.6 63.7 64.5370650099 North Carolina Edgecombe 77.0 79.0 67.3 69.0 64.6 66.3 64.3 65.9370670022 North Carolina Forsyth 78.0 79.0 66.9 67.8 64.5 65.3 64.3 65.1370670028 North Carolina Forsyth 73.0 74.0 62.3 63.2 60.0 60.8 59.8 60.7B-198-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues370670030 North Carolina Forsyth 76.0 76.0 65.7 65.7 63.3 63.3 63.0 63.0370671008 North Carolina Forsyth 80.0 81.0 68.9 69.7 66.3 67.1 66.0 66.8370690001 North Carolina Franklin 78.7 81.0 67.7 69.7 64.4 66.3 64.3 66.1370750001 North Carolina Graham 78.3 79.0 68.4 69.0 65.4 65.9 65.0 65.6370770001 North Carolina Granville 82.0 85.0 70.8 73.4 67.6 70.1 67.5 69.9370810011 North Carolina Guilford 77.0 77.0 67.3 67.3 64.3 64.3 64.2 64.2370810013 North Carolina Guilford 82.0 82.0 71.6 71.6 68.4 68.4 68.2 68.2370870004 North Carolina Haywood 71.3 73.0 62.4 63.9 60.0 61.5 59.8 61.2370870035 North Carolina Haywood 78.3 79.0 68.3 68.9 65.4 66.0 65.2 65.8370870036 North Carolina Haywood 77.3 78.0 68.4 69.0 65.9 66.5 65.7 66.3370990005 North Carolina Jackson 76.076.0 66.6 66.6 64.0 64.0 63.7 63.7371010002 North Carolina Johnston 77.3 79.0 66.9 68.4 63.9 65.3 63.7 65.1371070004 North Carolina Lenoir 75.3 77.0 66.6 68.1 64.3 65.7 63.6 65.1371090004 North Carolina Lincoln 81.0 83.0 71.5 73.2 69.2 70.9 69.0 70.7371170001 North Carolina Martin 75.0 77.0 67.9 69.7 66.2 68.0 66.2 67.9371190041 North Carolina Mecklenburg 88.0 90.0 78.5 80.3 75.9 77.6 75.7 77.5371191005 North Carolina Mecklenburg 80.3 83.0 72.1 74.6 69.8 72.1 69.6 72.0371191009 North Carolina Mecklenburg 89.3 93.0 78.3 81.6 75.4 78.5 75.2 78.3371290002 North Carolina New Hanover 72.3 73.0 66.7 67.3 64.8 65.5 64.6 65.2371450003 North Carolina Person 77.3 79.0 65.5 67.0 63.5 64.9 63.6 65.0371470099 North Carolina Pitt 76.377.0 66.9 67.5 64.4 65.0 63.8 64.4371570099 North Carolina Rockingham 77.0 78.0 66.1 66.9 63.4 64.2 63.1 64.0371590021 North Carolina Rowan 86.7 89.0 75.7 77.7 72.7 74.7 72.5 74.4371590022 North Carolina Rowan 86.7 90.0 75.9 78.8 72.9 75.7 72.7 75.5371730002 North Carolina Swain 66.3 68.0 57.6 59.1 55.0 56.4 54.7 56.1371790003 North Carolina Union 79.3 81.0 68.8 70.3 66.0 67.4 65.9 67.3371830014 North Carolina Wake 80.3 82.0 70.1 71.6 67.0 68.5 66.9 68.3371830016 North Carolina Wake 80.0 83.0 69.4 72.0 66.3 68.8 66.2 68.7371990003 North Carolina Yancey 76.0 76.0 66.3 66.3 63.7 63.7 63.4 63.4390030002 Ohio Allen 78.7 81.0 70.7 72.8 68.5 70.5 68.4 70.4B-208-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues390071001 Ohio Ashtabula 89.0 91.0 81.1 83.0 79.0 80.8 78.6 80.4390170004 Ohio Butler 83.3 85.0 76.2 77.8 74.2 75.7 73.6 75.1390171004 Ohio Butler 82.3 85.0 74.6 77.0 72.4 74.8 71.9 74.2390230001 Ohio Clark 81.0 83.0 72.4 74.2 70.2 72.0 69.8 71.6390230003 Ohio Clark 77.0 78.0 69.9 70.8 67.9 68.8 67.6 68.4390250022 Ohio Clermont 81.0 83.0 74.2 76.0 72.2 74.0 71.3 73.0390271002 Ohio Clinton 82.3 85.0 73.4 75.8 71.1 73.4 70.3 72.6390350034 Ohio Cuyahoga 71.0 76.0 65.0 69.6 63.4 67.9 63.1 67.5390350064 Ohio Cuyahoga 73.0 76.0 67.3 70.0 65.6 68.3 65.3 68.0390355002 Ohio Cuyahoga 79.7 81.0 73.3 74.5 71.5 72.7 71.2 72.3390410002 Ohio Delaware 78.3 81.0 69.7 72.1 67.2 69.6 67.0 69.3390490028 Ohio Franklin 80.3 82.0 73.6 75.2 71.6 73.1 71.3 72.8390490029 Ohio Franklin 86.3 88.0 77.4 78.9 75.0 76.4 74.7 76.2390490037 Ohio Franklin 80.3 81.0 74.2 74.9 72.1 72.7 71.8 72.4390490081 Ohio Franklin 79.7 80.0 71.9 72.1 69.6 69.8 69.3 69.6390550004 Ohio Geauga 79.3 86.0 71.3 77.3 69.2 75.0 68.8 74.6390570006 Ohio Greene 80.3 83.0 71.7 74.1 69.6 72.0 69.1 71.5390610006 Ohio Hamilton 84.7 86.0 78.1 79.3 76.1 77.2 75.5 76.7390610010 Ohio Hamilton 82.0 84.0 75.7 77.6 74.1 75.9 73.3 75.1390610040 Ohio Hamilton 81.7 83.0 76.0 77.2 74.3 75.4 73.6 74.7390810017 Ohio Jefferson 78.0 80.0 68.5 70.3 67.1 68.9 66.5 68.2390830002 Ohio Knox 77.7 79.0 68.6 69.7 66.2 67.3 65.9 67.0390850003 Ohio Lake 86.3 89.0 78.7 81.2 76.7 79.1 76.3 78.7390853002 Ohio Lake 80.7 81.0 73.4 73.7 71.5 71.8 71.1 71.4390870006 Ohio Lawrence 70.7 73.0 63.7 65.8 62.3 64.3 62.1 64.2390870011 Ohio Lawrence 63.3 69.0 55.3 60.3 53.9 58.8 53.8 58.7390890005 Ohio Licking 78.0 81.0 68.9 71.6 66.4 68.9 66.1 68.7390930018 Ohio Lorain 76.7 80.0 70.4 73.4 68.6 71.6 68.2 71.1390950024 Ohio Lucas 76.3 78.0 70.3 71.9 68.7 70.2 68.3 69.8390950027 Ohio Lucas 77.7 82.0 72.1 76.1 70.5 74.4 70.1 74.0B-218-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues390950034 Ohio Lucas 81.3 86.0 74.8 79.1 73.0 77.2 72.5 76.7390950081 Ohio Lucas 80.7 84.0 74.4 77.4 72.6 75.6 72.2 75.1390970007 Ohio Madison 79.7 82.0 70.6 72.6 68.4 70.3 68.0 70.0390990013 Ohio Mahoning 78.7 80.0 70.7 71.9 69.0 70.2 68.4 69.6391030003 Ohio Medina 80.3 84.0 71.5 74.8 69.3 72.5 68.9 72.1391090005 Ohio Miami 76.7 80.0 68.1 71.1 65.9 68.8 65.6 68.4391130037 Ohio Montgomery 74.0 75.0 66.3 67.2 64.4 65.3 64.0 64.9391331001 Ohio Portage 83.7 88.0 75.3 79.1 73.0 76.8 72.7 76.4391351001 Ohio Preble 73.0 75.0 65.1 66.9 63.1 64.8 62.5 64.3391510016 Ohio Stark 78.0 79.0 68.7 69.6 66.6 67.5 66.3 67.2391510022 Ohio Stark 77.3 80.0 68.9 71.3 67.0 69.4 66.6 68.9391514005 Ohio Stark 81.0 82.0 71.3 72.2 69.3 70.2 69.0 69.8391530020 Ohio Summit 83.7 85.0 74.7 75.8 72.3 73.4 72.0 73.1391550009 Ohio Trumbull 80.0 83.0 71.3 73.9 69.3 71.9 68.8 71.3391550011 Ohio Trumbull 84.3 86.0 75.8 77.4 74.0 75.5 73.4 74.8391650007 Ohio Warren 87.7 89.0 79.0 80.1 76.6 77.7 76.0 77.1391670004 Ohio Washington 82.7 85.0 75.2 77.2 73.8 75.9 72.3 74.4391730003 Ohio Wood 80.0 83.0 73.4 76.2 71.6 74.3 71.2 73.8400170101 Oklahoma Canadian 76.0 76.0 71.1 71.1 68.5 68.5 67.9 67.9400219002 Oklahoma Cherokee 75.7 76.0 72.1 72.3 70.5 70.8 65.7 65.9400270049 Oklahoma Cleveland 74.7 75.0 69.1 69.4 66.7 67.0 65.8 66.1400310647 Oklahoma Comanche 77.5 78.0 71.3 71.7 68.8 69.3 68.3 68.7400370144 Oklahoma Creek 76.7 77.0 70.7 71.0 68.6 68.9 66.6 66.9400719010 Oklahoma Kay 78.0 79.0 72.7 73.6 70.6 71.5 67.7 68.5400871073 Oklahoma McClain 72.0 72.0 66.4 66.4 64.0 64.0 63.2 63.2400979014 Oklahoma Mayes 78.5 79.0 75.0 75.4 73.6 74.1 69.3 69.7401090033 Oklahoma Oklahoma 77.0 77.0 72.3 72.3 70.3 70.3 69.4 69.4401090096 Oklahoma Oklahoma 76.3 78.0 71.1 72.7 68.9 70.4 67.6 69.1401091037 Oklahoma Oklahoma 80.0 81.0 73.5 74.4 70.6 71.5 70.1 71.0401159004 Oklahoma Ottawa 78.0 79.0 72.9 73.9 71.4 72.3 68.0 68.9B-228-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues401210415 Oklahoma Pittsburg 72.0 73.0 67.6 68.5 65.9 66.8 64.3 65.2401430137 Oklahoma Tulsa 79.3 80.0 73.1 73.7 70.7 71.3 68.9 69.5401430174 Oklahoma Tulsa 74.0 76.0 68.9 70.8 67.0 68.8 65.0 66.7401430178 Oklahoma Tulsa 79.3 80.0 74.4 75.1 72.5 73.2 70.5 71.2401431127 Oklahoma Tulsa 77.0 78.0 71.6 72.5 69.3 70.2 67.6 68.5420010002 Pennsylvania Adams 76.3 78.0 65.8 67.3 63.7 65.1 63.6 65.0420030008 Pennsylvania Allegheny 79.3 81.0 73.5 75.1 72.4 74.0 72.0 73.5420030010 Pennsylvania Allegheny 82.3 84.0 76.3 77.9 75.2 76.7 74.7 76.2420030067 Pennsylvania Allegheny 80.3 82.0 73.3 74.8 72.0 73.5 71.6 73.1420031005 Pennsylvania Allegheny 83.7 87.0 75.4 78.4 73.9 76.8 73.1 76.0420050001 Pennsylvania Armstrong 83.0 84.0 73.9 74.8 72.2 73.1 71.5 72.3420070002 Pennsylvania Beaver 83.0 84.0 74.6 75.5 73.2 74.1 72.6 73.5420070005 Pennsylvania Beaver 79.3 81.0 71.6 73.1 70.2 71.7 69.7 71.2420070014 Pennsylvania Beaver 74.0 75.0 66.6 67.5 65.4 66.2 64.9 65.8420110009 Pennsylvania Berks 76.0 80.0 67.8 71.4 65.9 69.4 65.6 69.1420130801 Pennsylvania Blair 74.3 77.0 66.1 68.5 64.6 66.9 64.1 66.4420170012 Pennsylvania Bucks 88.0 92.0 81.8 85.6 79.9 83.5 79.8 83.5420210011 Pennsylvania Cambria 74.7 77.0 67.0 69.0 65.3 67.4 64.8 66.8420270100 Pennsylvania Centre 78.379.0 69.4 70.0 67.4 68.0 67.1 67.7420290100 Pennsylvania Chester 86.0 87.0 75.1 76.0 73.0 73.9 72.9 73.8420334000 Pennsylvania Clearfield 78.3 82.0 69.4 72.7 67.8 71.0 67.2 70.4420430401 Pennsylvania Dauphin 79.381.0 72.2 73.8 70.5 72.0 69.9 71.4420431100 Pennsylvania Dauphin 79.381.0 72.4 73.9 70.6 72.1 70.1 71.6420450002 Pennsylvania Delaware 83.3 85.0 75.5 77.1 73.8 75.4 73.8 75.3420490003 Pennsylvania Erie 81.383.0 73.9 75.5 72.0 73.5 71.8 73.3420550001 Pennsylvania Franklin 72.3 75.0 62.8 65.1 60.6 62.9 60.5 62.8420590002 Pennsylvania Greene 80.0 81.0 73.4 74.3 72.3 73.2 70.2 71.1420630004 Pennsylvania Indiana 80.0 80.0 71.1 71.1 69.5 69.5 68.8 68.8420690101 Pennsylvania Lackawanna 74.3 75.0 66.0 66.6 64.1 64.7 63.9 64.5420692006 Pennsylvania Lackawanna 75.3 76.0 66.8 67.4 64.8 65.4 64.6 65.2B-238-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues420710007 Pennsylvania Lancaster 83.3 84.0 74.3 74.9 72.3 72.9 72.0 72.6420730015 Pennsylvania Lawrence 72.3 73.0 64.4 65.1 62.9 63.5 62.3 62.9420770004 Pennsylvania Lehigh 83.385.0 74.7 76.3 72.5 74.0 72.5 74.0420791100 Pennsylvania Luzerne 69.373.0 61.8 65.1 60.0 63.2 59.8 63.0420791101 Pennsylvania Luzerne 76.377.0 67.9 68.5 65.9 66.5 65.7 66.3420810100 Pennsylvania Lycoming 77.3 79.0 68.7 70.2 66.7 68.2 66.5 68.0420850100 Pennsylvania Mercer 82.083.0 74.0 74.9 72.3 73.2 71.7 72.5420910013 Pennsylvania Montgomery 85.7 86.0 79.1 79.4 77.5 77.7 77.4 77.7420950025 Pennsylvania Northampton 84.3 87.0 75.4 77.9 73.2 75.6 73.2 75.5420958000 Pennsylvania Northampton 80.0 82.0 71.4 73.2 69.2 70.9 69.2 70.9420990301 Pennsylvania Perry 77.0 78.0 69.2 70.1 67.1 68.0 66.8 67.7421010004 Pennsylvania Philadelphia 64.3 68.0 61.0 64.5 59.8 63.3 59.8 63.3421010014 Pennsylvania Philadelphia 79.7 81.0 76.0 77.3 74.9 76.1 74.9 76.1421010024 Pennsylvania Philadelphia 90.3 91.0 85.3 86.0 83.6 84.3 83.6 84.3421010136 Pennsylvania Philadelphia 77.0 77.0 71.3 71.3 70.1 70.1 70.0 70.0421174000 Pennsylvania Tioga 77.781.0 68.8 71.8 66.9 69.7 66.7 69.5421250005 Pennsylvania Washington 78.3 80.0 71.5 73.1 70.3 71.8 70.0 71.5421250200 Pennsylvania Washington 77.3 81.0 70.1 73.5 68.8 72.1 68.5 71.8421255001 Pennsylvania Washington 78.0 78.0 70.0 70.0 68.5 68.5 68.0 68.0421290006 Pennsylvania Westmoreland 78.3 80.0 72.2 73.7 70.9 72.4 70.3 71.8421290008 Pennsylvania Westmoreland 79.0 82.0 72.1 74.8 70.6 73.2 70.1 72.8421330008 Pennsylvania York 82.0 83.0 73.6 74.5 71.7 72.6 71.3 72.2440030002 Rhode Island Kent 84.386.0 75.4 77.0 73.3 74.8 73.2 74.7440071010 Rhode Island Providence 82.3 84.0 73.5 75.0 71.3 72.8 71.3 72.7440090007 Rhode Island Washington 86.0 89.0 77.2 79.9 75.2 77.8 75.1 77.7450010001 South CarolinaAbbeville 79.0 81.0 69.1 70.8 66.1 67.7 65.7 67.4450030003 South Carolina Aiken 76.0 77.0 66.4 67.3 63.3 64.1 63.0 63.8450070003 South Carolina Anderson 76.5 78.0 66.7 68.1 63.8 65.0 63.5 64.7450110001 South Carolina Barnwell 73.0 73.0 65.0 65.0 61.9 61.9 61.7 61.7450150002 South Carolina Berkeley 67.3 70.0 60.3 62.7 58.5 60.9 58.1 60.4B-248-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues450190046 South Carolina Charleston 74.0 75.0 67.2 68.1 65.0 65.8 64.5 65.4450210002 South Carolina Cherokee 74.0 75.0 63.8 64.7 61.1 61.9 61.0 61.8450230002 South Carolina Chester 75.7 76.0 66.1 66.4 63.5 63.7 63.4 63.6450250001 South Carolina Chesterfield 75.0 75.0 65.8 65.8 63.4 63.4 63.2 63.2450290002 South Carolina Colleton 72.3 74.0 65.6 67.2 63.0 64.5 62.4 63.9450310003 South Carolina Darlington76.3 77.0 67.0 67.7 64.6 65.2 64.2 64.8450370001 South Carolina Edgefield70.0 70.0 61.0 61.0 58.1 58.1 57.8 57.8450730001 South Carolina Oconee 73.0 76.0 63.4 66.0 60.4 62.9 60.1 62.6450770002 South Carolina Pickens 78.7 81.0 68.0 70.0 64.8 66.7 64.5 66.4450790007 South Carolina Richland 80.3 82.0 69.9 71.3 66.5 67.9 66.1 67.5450790021 South Carolina Richland 72.7 73.0 61.7 61.9 58.7 58.9 58.4 58.7450791001 South Carolina Richland 82.3 83.0 71.6 72.2 68.1 68.7 67.8 68.3450830009 South Carolina Spartanburg82.3 83.0 71.5 72.1 68.6 69.2 68.5 69.1450870001 South Carolina Union 76.0 77.0 66.7 67.6 64.1 64.9 63.9 64.8450890001 South Carolina Williamsburg69.3 70.0 62.3 62.9 60.2 60.8 59.9 60.5450910006 South Carolina York 76.7 79.0 67.2 69.2 64.5 66.4 64.4 66.3470010101 Tennessee Anderson 77.3 80.0 66.2 68.5 63.2 65.4 63.1 65.3470090101 Tennessee Blount 85.3 86.0 73.4 74.0 70.0 70.6 69.8 70.4470090102 Tennessee Blount 68.5 70.0 59.6 60.9 57.0 58.2 56.7 58.0470370011 Tennessee Davidson 68.7 72.0 60.7 63.6 58.4 61.3 58.2 61.0470370026 Tennessee Davidson 77.7 79.0 68.5 69.6 65.8 66.9 65.6 66.7470651011 Tennessee Hamilton 80.0 83.0 70.6 73.2 66.8 69.3 66.5 69.0470654003 Tennessee Hamilton 81.0 84.0 71.6 74.2 67.8 70.3 67.6 70.1470890002 Tennessee Jefferson 82.3 84.0 71.3 72.8 68.0 69.4 67.8 69.2470930021 Tennessee Knox 78.7 81.0 68.3 70.3 65.1 67.0 65.0 66.9470931020 Tennessee Knox 85.0 88.0 74.0 76.6 70.7 73.2 70.6 73.1471050109 Tennessee Loudon 83.0 85.070.6 72.3 67.5 69.1 67.4 69.0471210104 Tennessee Meigs 80.0 81.0 70.1 71.0 66.3 67.1 66.1 66.9471490101 Tennessee Rutherford 76.3 80.0 66.1 69.3 63.2 66.2 63.0 66.0471550101 Tennessee Sevier 79.0 82.0 68.7 71.3 65.8 68.3 65.6 68.1B-258-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues471550102 Tennessee Sevier 80.7 83.0 70.6 72.6 67.6 69.5 67.2 69.2471570021 Tennessee Shelby 80.0 82.0 71.0 72.8 68.5 70.2 68.2 69.9471571004 Tennessee Shelby 80.7 81.0 70.5 70.8 67.8 68.1 67.5 67.7471632002 Tennessee Sullivan 80.3 83.0 74.1 76.6 72.3 74.8 72.2 74.6471632003 Tennessee Sullivan 80.0 83.0 73.7 76.5 72.0 74.7 71.9 74.6471650007 Tennessee Sumner 83.0 84.0 73.0 73.9 70.1 70.9 69.8 70.6471650101 Tennessee Sumner 79.0 82.0 68.0 70.6 65.1 67.6 64.8 67.2471870106 Tennessee Williamson 75.3 77.0 65.2 66.7 62.3 63.7 62.1 63.5471890103 Tennessee Wilson 78.7 82.0 67.9 70.7 64.9 67.6 64.5 67.2480290032 Texas Bexar 82.0 85.0 76.3 79.1 74.0 76.7 73.6 76.2480290052 Texas Bexar 85.0 87.0 79.7 81.6 77.5 79.3 77.0 78.9480391004 Texas Brazoria 94.7 97.0 88.8 91.0 87.0 89.1 86.6 88.7480391016 Texas Brazoria 80.0 85.0 74.0 78.6 72.4 77.0 72.1 76.7480850005 Texas Collin 90.3 92.0 81.4 83.0 78.4 79.9 78.2 79.6481130069 Texas Dallas 87.0 90.0 82.9 85.8 80.5 83.3 80.2 83.0481130075 Texas Dallas 88.3 90.0 82.9 84.5 80.3 81.8 80.0 81.6481130087 Texas Dallas 87.0 88.0 84.6 85.6 82.3 83.3 82.1 83.0481133003 Texas Dallas 78.5 84.0 73.1 78.2 70.9 75.9 70.6 75.5481210034 Texas Denton 94.0 95.0 83.2 84.1 79.9 80.8 79.6 80.4481390015 Texas Ellis 81.7 84.073.8 75.9 70.9 72.9 70.5 72.5481410029 Texas El Paso 74.7 77.0 70.6 72.7 70.2 72.4 70.2 72.4481410037 Texas El Paso 77.7 79.0 73.9 75.1 73.2 74.5 73.2 74.4481410044 Texas El Paso 73.0 74.0 69.4 70.4 68.8 69.7 68.8 69.7481410055 Texas El Paso 76.0 77.0 72.3 73.2 71.6 72.6 71.6 72.6481410057 Texas El Paso 75.0 76.0 70.5 71.5 70.0 71.0 70.0 70.9481410058 Texas El Paso 74.3 75.0 70.4 71.0 69.8 70.5 69.8 70.5481670014 Texas Galveston 80.3 87.0 75.1 81.4 73.6 79.7 73.3 79.4481830001 Texas Gregg 84.3 85.0 78.3 79.0 76.8 77.4 76.4 77.1482010024 Texas Harris 88.0 92.0 83.3 87.1 82.2 85.9 81.9 85.6482010026 Texas Harris 85.7 89.0 80.6 83.7 79.1 82.1 78.8 81.8B-268-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues482010029 Texas Harris 91.7 93.0 84.4 85.6 82.3 83.5 82.0 83.2482010046 Texas Harris 78.7 82.0 74.5 77.6 73.5 76.6 73.2 76.3482010047 Texas Harris 78.7 80.0 75.8 77.0 74.8 76.0 74.6 75.8482010051 Texas Harris 93.0 98.0 88.4 93.1 86.6 91.2 86.3 90.9482010055 Texas Harris 100.7 103.0 95.7 97.9 93.8 95.9 93.4 95.5482010062 Texas Harris 95.7 99.0 90.5 93.7 89.0 92.1 88.6 91.6482010066 Texas Harris 92.3 96.0 89.9 93.5 88.8 92.4 88.6 92.1482010070 Texas Harris 84.3 88.0 81.3 84.8 80.2 83.8 80.0 83.5482010075 Texas Harris 83.3 88.0 80.3 84.8 79.3 83.8 79.0 83.5482011015 Texas Harris 89.0 96.0 83.7 90.3 82.1 88.6 81.8 88.2482011034 Texas Harris 82.7 87.0 78.6 82.7 77.7 81.7 77.3 81.4482011035 Texas Harris 86.3 95.0 82.0 90.3 81.1 89.3 80.7 88.8482011039 Texas Harris 96.3 100.0 90.5 93.9 88.9 92.3 88.5 91.9482011050 Texas Harris 89.3 92.0 83.9 86.5 82.5 85.0 82.1 84.6482030002 Texas Harrison 79.0 80.0 70.9 71.8 68.5 69.4 68.1 69.0482210001 Texas Hood 83.0 84.0 72.7 73.6 69.4 70.2 69.0 69.8482311006 Texas Hunt 78.0 79.0 69.9 70.8 67.8 68.7 67.5 68.3482450009 Texas Jefferson 81.7 82.0 75.6 75.9 74.0 74.3 73.3 73.6482450011 Texas Jefferson 80.0 81.0 74.8 75.7 73.2 74.1 72.6 73.5482450018 Texas Jefferson 83.3 84.0 77.4 78.0 75.8 76.4 75.1 75.7482450022 Texas Jefferson 79.7 81.0 73.5 74.7 71.8 72.9 71.1 72.3482450101 Texas Jefferson 84.7 88.0 79.7 82.8 78.1 81.1 77.5 80.5482450628 Texas Jefferson 78.0 78.0 72.9 72.9 71.3 71.3 70.8 70.8482510003 Texas Johnson 87.0 89.0 76.4 78.2 73.2 74.9 72.8 74.4482570005 Texas Kaufman 74.7 76.0 68.1 69.3 65.9 67.0 65.5 66.7483390078 Texas Montgomery 85.0 86.0 77.8 78.8 75.5 76.4 75.4 76.3483550025 Texas Nueces 72.3 75.0 68.3 70.9 67.2 69.8 67.0 69.5483611001 Texas Orange 78.0 80.0 72.3 74.1 70.8 72.6 70.0 71.8483611100 Texas Orange 73.0 74.0 67.2 68.2 65.9 66.8 65.4 66.3483670081 Texas Parker 88.7 91.0 76.0 78.0 72.6 74.5 72.3 74.2B-278-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues483970001 Texas Rockwall 79.7 81.0 73.3 74.5 70.9 72.1 70.5 71.7484230007 Texas Smith 81.0 82.0 74.5 75.4 72.4 73.3 72.1 73.0484390075 Texas Tarrant 95.3 96.0 84.2 84.8 80.9 81.5 80.6 81.2484391002 Texas Tarrant 93.3 95.0 85.1 86.7 82.1 83.6 81.9 83.4484392003 Texas Tarrant 93.7 95.0 84.0 85.2 80.9 82.0 80.6 81.8484393009 Texas Tarrant 92.7 93.0 84.3 84.5 81.2 81.5 80.9 81.2484393011 Texas Tarrant 86.0 87.0 79.6 80.5 77.0 77.9 76.7 77.6484530014 Texas Travis 81.3 82.0 73.6 74.3 71.1 71.7 70.7 71.3484530020 Texas Travis 79.3 81.0 71.7 73.2 69.2 70.7 68.7 70.2484530613 Texas Travis 76.0 76.0 69.3 69.3 67.6 67.6 67.2 67.2500030004 Vermont Bennington 72.0 73.0 63.9 64.8 61.9 62.7 61.8 62.7500070007 Vermont Chittenden 69.7 71.0 63.2 64.4 61.6 62.8 61.6 62.7510130020 Virginia Arlington 86.7 87.0 81.8 82.0 80.0 80.3 79.9 80.1510330001 Virginia Caroline 80.0 81.0 69.3 70.1 66.7 67.6 66.7 67.5510360002 Virginia Charles 80.3 82.0 71.2 72.7 69.2 70.7 69.1 70.6510410004 Virginia Chesterfield 76.7 77.0 68.0 68.2 66.1 66.3 66.0 66.2510590005 Virginia Fairfax 78.3 79.0 70.5 71.1 68.3 68.9 68.2 68.8510590018 Virginia Fairfax 90.0 91.0 83.2 84.1 81.3 82.2 81.1 82.0510590030 Virginia Fairfax 88.0 89.0 81.4 82.3 79.6 80.5 79.5 80.4510591005 Virginia Fairfax 85.7 87.0 79.3 80.5 77.5 78.7 77.4 78.6510595001 Virginia Fairfax 82.0 84.0 76.0 77.8 74.1 75.9 74.0 75.8510610002 Virginia Fauquier 72.7 73.0 62.4 62.7 60.1 60.3 60.1 60.3510690010 Virginia Frederick 72.3 73.0 63.6 64.2 61.6 62.2 61.6 62.2510850003 Virginia Hanover 81.3 82.0 71.4 72.0 69.1 69.7 69.1 69.7510870014 Virginia Henrico 82.0 85.0 72.6 75.3 70.4 73.0 70.3 72.9511071005 Virginia Loudoun 80.7 82.0 72.8 74.0 70.6 71.7 70.5 71.7511130003 Virginia Madison 77.7 80.0 68.0 70.0 65.8 67.7 65.7 67.7511390004 Virginia Page 74.0 76.0 64.9 66.7 62.9 64.6 62.8 64.5511530009 Virginia Prince William 78.7 79.0 70.0 70.3 67.7 68.0 67.7 68.0511611004 Virginia Roanoke 74.7 76.0 67.4 68.5 64.9 66.0 64.7 65.8B-288-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues511630003 Virginia Rockbridge 69.7 71.0 62.0 63.1 59.7 60.8 59.5 60.6511790001 Virginia Stafford 81.7 85.0 72.0 74.9 69.5 72.3 69.4 72.2511970002 Virginia Wythe 72.7 75.0 63.8 65.8 61.3 63.2 61.1 63.0515100009 Virginia Alexandria City 81.7 83.0 75.5 76.7 73.8 75.0 73.6 74.8516500004 Virginia Hampton City 76.7 78.0 71.7 72.9 70.5 71.7 70.4 71.6518000004 Virginia Suffolk City 76.7 78.0 71.9 73.1 70.8 72.0 70.7 71.9518000005 Virginia Suffolk City 75.3 77.0 66.8 68.3 64.7 66.2 64.6 66.1540030003 West Virginia Berkeley 75.0 76.0 66.4 67.3 64.2 65.1 64.2 65.0540110006 West Virginia Cabell 78.7 84.0 70.9 75.7 69.3 73.9 69.1 73.8540291004 West Virginia Hancock 75.7 77.0 66.8 68.0 65.6 66.7 64.9 66.0540390010 West Virginia Kanawha 77.3 79.0 66.3 67.7 64.6 66.0 64.4 65.9540610003 West Virginia Monongalia 75.3 78.0 71.4 74.0 70.2 72.7 68.3 70.8540690010 West Virginia Ohio 78.3 82.0 69.3 72.5 68.0 71.2 66.8 70.0541071002 West Virginia Wood 79.0 82.0 70.3 73.0 69.0 71.6 68.1 70.7550090026 Wisconsin Brown 73.7 75.0 67.7 68.9 66.0 67.1 65.6 66.8550210015 Wisconsin Columbia 72.7 74.0 65.7 66.9 64.1 65.3 63.5 64.7550250041 Wisconsin Dane 72.0 74.0 65.6 67.4 64.0 65.8 63.5 65.2550270007 Wisconsin Dodge 74.7 77.0 68.4 70.5 66.5 68.5 66.1 68.2550290004 Wisconsin Door 88.7 90.0 80.5 81.7 78.2 79.4 77.8 79.0550370001 Wisconsin Florence 66.3 68.0 60.5 62.1 59.1 60.6 58.7 60.2550390006 Wisconsin Fond du Lac 73.7 75.0 68.1 69.3 66.3 67.5 66.0 67.2550410007 Wisconsin Forest 69.5 71.0 63.3 64.7 61.8 63.1 61.2 62.5550550002 Wisconsin Jefferson 74.376.0 68.0 69.5 66.0 67.5 65.6 67.1550590019 Wisconsin Kenosha 84.786.0 81.3 82.5 79.9 81.1 79.6 80.9550610002 Wisconsin Kewaunee 82.7 86.0 75.4 78.4 73.4 76.3 73.0 75.9550710007 Wisconsin Manitowoc 85.0 87.0 78.0 79.8 75.9 77.7 75.6 77.4550790010 Wisconsin Milwaukee 69.3 70.0 65.6 66.2 64.1 64.8 63.9 64.5550790026 Wisconsin Milwaukee 76.0 77.0 71.9 72.9 70.3 71.3 70.1 71.0550790041 Wisconsin Milwaukee 81.3 83.0 77.0 78.6 75.2 76.8 74.9 76.5550790044 Wisconsin Milwaukee 71.0 71.0 69.9 69.9 68.9 68.9 68.7 68.7B-298-Hour Ozone Design Values (ppb)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues550790085 Wisconsin Milwaukee 82.7 86.0 78.0 81.1 76.2 79.2 75.9 78.9550870009 Wisconsin Outagamie 74.0 75.0 67.9 68.8 66.2 67.1 65.8 66.7550890008 Wisconsin Ozaukee 81.3 85.0 76.3 79.8 74.6 77.9 74.2 77.6550890009 Wisconsin Ozaukee 83.3 88.0 77.6 81.9 75.5 79.8 75.2 79.4551010017 Wisconsin Racine 80.3 82.0 76.3 77.9 74.8 76.4 74.5 76.1551050024 Wisconsin Rock 74.0 76.0 67.2 69.1 65.3 67.1 64.8 66.6551091002 Wisconsin St. Croix 69.0 71.0 64.1 66.0 62.8 64.6 61.9 63.7551110007 Wisconsin Sauk 69.7 71.0 62.9 64.1 61.6 62.8 61.0 62.2551170006 Wisconsin Sheboygan 88.0 89.0 80.8 81.8 78.6 79.5 78.3 79.1551270005 Wisconsin Walworth 75.777.0 69.0 70.2 67.0 68.2 66.7 67.9551310009 Wisconsin Washington 72.3 75.0 67.1 69.7 65.2 67.7 64.9 67.3551330017 Wisconsin Waukesha 75.0 75.0 69.2 69.2 67.3 67.3 67.0 67.0551330027 Wisconsin Waukesha 71.5 72.0 66.0 66.5 64.2 64.6 63.9 64.3B-30Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues10030010 Alabama Baldwin 11.44 11.75 10.81 11.11 10.46 10.75 9.15 9.4010270001 Alabama Clay 13.21 13.32 12.00 12.11 11.32 11.43 9.95 10.0610331002 Alabama Colbert 12.67 12.88 12.13 12.33 11.65 11.83 9.68 9.8210491003 Alabama DeKalb 14.09 14.42 12.75 13.06 12.14 12.43 10.38 10.6310530002 Alabama Escambia 13.12 13.18 12.55 12.61 12.21 12.28 10.94 11.0010550010 Alabama Etowah 14.80 15.01 13.45 13.64 12.76 12.94 11.10 11.2610690003 Alabama Houston 12.86 12.86 12.10 12.10 11.73 11.73 10.60 10.6010730023 Alabama Jefferson 18.48 18.67 17.15 17.32 16.48 16.64 14.95 15.0910731005 Alabama Jefferson 15.36 15.60 14.27 14.50 13.67 13.89 12.13 12.3310731009 Alabama Jefferson 13.42 13.74 12.58 12.89 12.04 12.33 10.40 10.6610731010 Alabama Jefferson 15.76 15.92 14.37 14.53 13.66 13.82 12.04 12.1710732003 Alabama Jefferson 17.07 17.45 15.99 16.35 15.42 15.77 13.99 14.3110732006 Alabama Jefferson 15.00 15.13 13.90 14.02 13.31 13.42 11.87 11.9710735002 Alabama Jefferson 14.33 14.59 13.12 13.36 12.47 12.70 10.94 11.1410735003 Alabama Jefferson 14.43 14.58 13.34 13.48 12.69 12.83 10.97 11.0910890014 Alabama Madison 13.73 13.85 12.86 12.98 12.26 12.38 10.14 10.2510970002 Alabama Mobile 12.90 12.90 12.33 12.33 11.90 11.90 10.59 10.5910970003 Alabama Mobile 12.36 12.49 11.80 11.92 11.38 11.50 10.09 10.1910972005 Alabama Mobile 11.51 11.92 10.88 11.27 10.51 10.88 9.25 9.5711010007 Alabama Montgomery 14.14 14.22 13.27 13.33 12.75 12.80 11.41 11.4611030011 Alabama Morgan 13.23 13.47 12.47 12.69 11.91 12.11 9.98 10.1411130001 Alabama Russell 15.63 15.83 14.51 14.68 13.83 14.00 12.41 12.5511170006 Alabama Shelby 14.28 14.32 13.17 13.21 12.55 12.59 11.03 11.0711190002 Alabama Sumter 11.92 11.92 11.33 11.33 10.87 10.87 9.33 9.3311210002 Alabama Talladega 14.51 14.51 13.03 13.03 12.38 12.38 10.89 10.8911250004 Alabama Tuscaloosa 13.44 13.56 12.63 12.74 12.07 12.18 10.44 10.5311270002 Alabama Walker 13.77 14.05 12.90 13.16 12.28 12.53 10.48 10.7050010011 Arkansas Arkansas 12.45 12.54 12.24 12.33 11.80 11.89 10.27 10.3450030005 Arkansas Ashley 12.83 13.30 12.58 13.04 12.23 12.67 10.99 11.3850350005 Arkansas Crittenden 13.27 13.27 12.93 12.93 12.32 12.32 10.33 10.33B-31Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues50450002 Arkansas Faulkner 12.79 13.10 12.57 12.87 12.13 12.43 10.75 11.0150510003 Arkansas Garland 12.40 12.67 12.12 12.37 11.72 11.98 10.41 10.6450930007 Arkansas Mississippi 12.61 12.61 12.51 12.51 12.00 12.00 9.86 9.8651070001 Arkansas Phillips 12.08 12.33 11.84 12.08 11.33 11.56 9.58 9.7651130002 Arkansas Polk 11.65 12.04 11.26 11.64 10.96 11.33 9.90 10.2451150003 Arkansas Pope 12.79 13.14 12.52 12.86 12.14 12.46 10.88 11.1851190007 Arkansas Pulaski 13.17 13.27 12.84 12.93 12.37 12.46 10.92 10.9951191004 Arkansas Pulaski 14.05 14.23 13.71 13.89 13.24 13.41 11.79 11.9451191005 Arkansas Pulaski 13.59 13.62 13.24 13.28 12.78 12.81 11.35 11.3851390006 Arkansas Union 12.86 13.09 12.55 12.77 12.19 12.41 10.95 11.1551450001 Arkansas White 12.57 12.74 12.40 12.56 11.98 12.15 10.58 10.7180010006 Colorado Adams 10.06 10.16 9.63 9.73 9.44 9.54 9.54 9.6380050005 Colorado Arapahoe 7.96 8.10 7.64 7.77 7.48 7.61 7.54 7.6880130003 Colorado Boulder 8.32 8.54 7.91 8.13 7.80 8.01 7.84 8.0580130012 Colorado Boulder 6.96 7.06 6.67 6.77 6.58 6.67 6.62 6.7280290004 Colorado Delta 7.44 7.62 6.97 7.14 6.86 7.03 6.86 7.0380310002 Colorado Denver 9.37 9.74 8.97 9.32 8.79 9.14 8.89 9.2480310023 Colorado Denver 9.76 9.76 9.34 9.34 9.16 9.16 9.25 9.2580390001 Colorado Elbert 4.40 4.54 4.23 4.37 4.18 4.32 4.19 4.3380410008 Colorado El Paso 6.73 6.73 6.34 6.34 6.24 6.24 6.26 6.2780410011 Colorado El Paso 7.94 8.11 7.49 7.65 7.38 7.53 7.41 7.5680690009 Colorado Larimer 7.33 7.40 7.02 7.09 6.94 7.00 6.96 7.0380770017 Colorado Mesa 9.28 9.48 8.78 8.97 8.65 8.84 8.66 8.8581010012 Colorado Pueblo 7.45 7.65 7.08 7.28 7.00 7.19 6.99 7.1981130004 Colorado San Miguel 4.65 4.81 4.48 4.64 4.46 4.61 4.46 4.6181230006 Colorado Weld 8.19 8.35 7.73 7.89 7.62 7.78 7.65 7.8081230008 Colorado Weld 8.78 9.28 8.31 8.77 8.19 8.65 8.23 8.6990010010 Connecticut Fairfield 13.18 13.18 12.36 12.36 12.18 12.18 11.12 11.1290011123 Connecticut Fairfield 12.49 12.59 11.68 11.77 11.50 11.59 10.45 10.5390013005 Connecticut Fairfield 12.43 12.72 11.65 11.92 11.48 11.75 10.40 10.62B-32Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues90019003 Connecticut Fairfield 11.48 11.73 10.75 10.97 10.59 10.81 9.53 9.7290031003 Connecticut Hartford 11.03 11.36 10.28 10.58 10.11 10.40 9.28 9.5590050005 Connecticut Litchfield 8.01 8.01 7.47 7.47 7.36 7.36 6.47 6.4790090026 Connecticut New Haven 12.12 12.1311.32 11.33 11.14 11.15 10.12 10.1390090027 Connecticut New Haven 12.45 12.5711.60 11.71 11.41 11.52 10.38 10.4890091123 Connecticut New Haven 13.12 13.5412.26 12.65 12.05 12.44 11.04 11.3890092008 Connecticut New Haven 11.17 11.22 10.41 10.45 10.24 10.28 9.25 9.2790092123 Connecticut New Haven 12.74 12.9111.91 12.06 11.72 11.87 10.74 10.8790113002 Connecticut New London 10.96 11.33 10.18 10.52 10.03 10.36 9.26 9.56100010002 Delaware Kent 12.61 12.84 11.60 11.82 11.47 11.68 9.96 10.16100010003 Delaware Kent 12.52 12.66 11.58 11.72 11.43 11.57 9.97 10.10100031003 Delaware New Castle 13.73 14.3312.71 13.26 12.52 13.06 11.02 11.48100031007 Delaware New Castle 12.92 13.4111.83 12.29 11.69 12.15 10.15 10.55100031012 Delaware New Castle 13.69 13.8812.58 12.75 12.42 12.59 10.90 11.05100032004 Delaware New Castle 14.87 15.1113.81 14.03 13.61 13.83 12.08 12.28100051002 Delaware Sussex 13.39 13.45 12.25 12.31 12.11 12.16 10.60 10.64110010041District OfColumbiaDistrict ofColumbia 14.16 14.38 12.96 13.16 12.78 12.98 10.96 11.13110010042District OfColumbiaDistrict ofColumbia 14.41 14.52 13.14 13.24 12.97 13.07 11.17 11.26110010043District OfColumbiaDistrict ofColumbia 13.99 14.44 12.80 13.23 12.63 13.05 10.72 11.08120010023 Florida Alachua 9.32 9.51 8.49 8.66 8.26 8.42 7.28 7.42120010024 Florida Alachua 9.59 9.64 8.75 8.80 8.52 8.57 7.57 7.62120051004 Florida Bay 11.46 11.69 10.69 10.89 10.39 10.59 9.45 9.62120090007 Florida Brevard 8.32 8.64 7.63 7.93 7.46 7.74 6.82 7.08120111002 Florida Broward 8.22 8.30 7.77 7.85 7.64 7.72 7.27 7.35120112004 Florida Broward 8.18 8.28 7.68 7.77 7.55 7.64 7.17 7.25120113002 Florida Broward 8.21 8.21 7.76 7.76 7.63 7.63 7.26 7.26120170005 Florida Citrus 9.00 9.14 7.96 8.07 7.77 7.88 6.98 7.09120310098 Florida Duval 9.90 9.99 9.14 9.24 8.90 9.00 8.05 8.15B-33Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues120310099 Florida Duval 10.44 10.53 9.75 9.82 9.52 9.59 8.73 8.79120330004 Florida Escambia 11.72 11.91 11.20 11.37 10.94 11.11 9.87 10.02120570030 Florida Hillsborough 10.7410.95 9.50 9.68 9.31 9.49 8.86 9.03120573002 Florida Hillsborough 10.5210.75 9.34 9.55 9.16 9.37 8.74 8.93120710005 Florida Lee 8.36 8.41 7.51 7.56 7.39 7.43 6.87 6.91120730012 Florida Leon 12.56 12.71 11.56 11.69 11.25 11.38 10.30 10.41120814012 Florida Manatee 8.81 8.91 7.61 7.70 7.51 7.59 6.99 7.06120830003 Florida Marion 10.11 10.20 9.17 9.25 8.94 9.02 8.13 8.20120861016 Florida Miami-Dade 9.45 9.54 8.93 9.01 8.77 8.85 8.40 8.48120866001 Florida Miami-Dade 8.14 8.28 7.68 7.81 7.59 7.72 7.21 7.33120951004 Florida Orange 9.61 9.76 8.73 8.87 8.46 8.59 7.75 7.87120952002 Florida Orange 9.50 9.60 8.60 8.69 8.34 8.43 7.63 7.72120990009 Florida Palm Beach 7.84 7.84 7.28 7.28 7.14 7.14 6.71 6.71120992005 Florida Palm Beach 7.70 7.81 7.22 7.31 7.08 7.18 6.66 6.75121030018 Florida Pinellas 9.82 9.85 8.65 8.67 8.52 8.54 8.03 8.05121031009 Florida Pinellas 9.52 9.69 8.39 8.54 8.24 8.38 7.75 7.89121056006 Florida Polk 9.55 9.65 8.48 8.57 8.34 8.43 7.84 7.92121111002 Florida St. Lucie 8.34 8.47 7.66 7.78 7.54 7.65 6.96 7.06121150013 Florida Sarasota 8.77 8.86 7.69 7.77 7.58 7.67 7.04 7.11121171002 Florida Seminole 9.51 9.64 8.62 8.73 8.35 8.46 7.62 7.72121275002 Florida Volusia 9.27 9.34 8.47 8.53 8.22 8.28 7.37 7.41130210007 Georgia Bibb 16.47 16.78 15.33 15.61 14.52 14.79 13.17 13.41130210012 Georgia Bibb 13.87 14.17 12.90 13.18 12.07 12.33 10.78 11.01130510017 Georgia Chatham 13.70 13.87 12.79 12.94 12.38 12.52 11.32 11.45130510091 Georgia Chatham 13.88 14.11 12.98 13.19 12.55 12.75 11.50 11.68130590002 Georgia Clarke 14.90 14.90 13.83 13.83 12.94 12.94 11.51 11.51130630091 Georgia Clayton 16.47 16.71 15.07 15.29 14.12 14.32 12.73 12.91130670003 Georgia Cobb 16.09 16.19 14.63 14.72 13.86 13.94 12.41 12.49130670004 Georgia Cobb 15.36 15.50 13.96 14.08 13.10 13.21 11.69 11.79130890002 Georgia DeKalb 15.46 15.66 14.13 14.31 13.16 13.33 11.77 11.93B-34Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues130892001 Georgia DeKalb 15.33 15.56 13.97 14.19 13.07 13.28 11.65 11.83130950007 Georgia Dougherty 14.35 14.53 13.56 13.73 13.14 13.31 11.83 11.97131150005 Georgia Floyd 16.10 16.15 14.61 14.67 14.01 14.06 12.43 12.48131210032 Georgia Fulton 15.81 16.02 14.44 14.63 13.48 13.66 12.09 12.25131210039 Georgia Fulton 17.43 17.47 16.01 16.04 15.03 15.07 13.65 13.68131270006 Georgia Glynn 12.18 12.30 11.38 11.50 11.10 11.21 10.16 10.26131350002 Georgia Gwinnett 16.07 16.36 14.72 14.99 13.87 14.12 12.43 12.66131390003 Georgia Hall 14.12 14.37 12.97 13.21 12.21 12.44 10.73 10.94131530001 Georgia Houston 13.99 14.25 12.95 13.18 12.27 12.49 10.96 11.15131850003 Georgia Lowndes 12.49 12.83 11.70 12.01 11.38 11.68 10.45 10.72132150001 Georgia Muscogee 14.86 14.98 13.76 13.87 13.10 13.19 11.67 11.76132150008 Georgia Muscogee 15.16 15.16 14.07 14.07 13.40 13.40 12.04 12.04132150011 Georgia Muscogee 14.07 14.30 13.07 13.28 12.47 12.67 11.18 11.35132230003 Georgia Paulding 14.08 14.30 12.58 12.77 11.85 12.03 10.33 10.49132450005 Georgia Richmond 15.61 15.82 14.67 14.87 14.10 14.29 12.83 13.00132450091 Georgia Richmond 15.68 15.88 14.76 14.95 14.18 14.35 12.89 13.05132950002 Georgia Walker 15.49 15.75 14.39 14.63 13.76 13.99 11.81 12.00133030001 Georgia Washington 15.14 15.54 14.36 14.73 13.44 13.78 12.13 12.44133190001 Georgia Wilkinson 15.23 15.50 14.32 14.57 13.37 13.60 12.05 12.25170010006 Illinois Adams 12.50 12.87 12.21 12.57 11.70 12.04 10.56 10.85170190004 Illinois Champaign 12.50 12.89 12.25 12.63 11.70 12.07 9.94 10.29170191001 Illinois Champaign 12.53 12.92 12.32 12.70 11.75 12.13 9.98 10.38170310022 Illinois Cook 15.21 15.55 14.70 15.04 14.22 14.54 13.03 13.33170310050 Illinois Cook 14.81 15.22 14.32 14.71 13.82 14.21 12.71 13.08170310052 Illinois Cook 15.75 16.02 15.16 15.42 14.64 14.90 13.59 13.85170310057 Illinois Cook 15.03 15.34 14.50 14.79 13.98 14.27 12.90 13.19170310076 Illinois Cook 14.89 15.18 14.41 14.68 13.87 14.13 12.76 13.02170312001 Illinois Cook 14.77 15.14 14.28 14.63 13.80 14.15 12.72 13.05170313301 Illinois Cook 15.24 15.59 14.73 15.06 14.20 14.52 13.10 13.41170314007 Illinois Cook 12.78 13.15 12.45 12.80 11.92 12.26 10.84 11.16B-35Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues170314201 Illinois Cook 12.76 13.18 12.44 12.86 11.91 12.29 10.82 11.15170316005 Illinois Cook 15.48 16.07 14.92 15.48 14.40 14.94 13.34 13.85170434002 Illinois DuPage 13.82 14.01 13.51 13.69 12.95 13.13 11.87 12.03170831001 Illinois Jersey 12.89 13.20 13.05 13.37 12.41 12.72 10.62 10.88170890003 Illinois Kane 13.32 13.54 12.94 13.15 12.36 12.56 11.25 11.45170890007 Illinois Kane 14.34 14.34 13.95 13.95 13.39 13.39 12.31 12.31170971007 Illinois Lake 11.81 12.10 11.57 11.86 11.06 11.34 10.01 10.26171110001 Illinois McHenry 12.40 12.47 12.08 12.15 11.53 11.59 10.49 10.56171132003 Illinois McLean 12.39 12.39 12.26 12.26 11.61 11.61 10.19 10.19171150013 Illinois Macon 13.24 13.57 13.11 13.43 12.50 12.81 10.85 11.13171191007 Illinois Madison 16.72 17.01 16.56 16.85 15.90 16.18 14.22 14.48171192009 Illinois Madison 14.01 14.66 14.20 14.85 13.57 14.20 11.71 12.25171193007 Illinois Madison 14.32 14.45 14.48 14.62 13.87 14.00 12.04 12.14171430037 Illinois Peoria 13.34 13.66 13.43 13.76 12.47 12.77 11.28 11.55171570001 Illinois Randolph 13.11 13.64 13.07 13.58 12.44 12.94 10.58 11.00171613002 Illinois Rock Island 12.01 12.31 11.69 11.99 11.19 11.47 10.16 10.40171630010 Illinois Saint Clair 15.58 15.74 15.48 15.63 14.83 14.98 13.18 13.33171634001 Illinois Saint Clair 14.29 14.49 14.21 14.41 13.57 13.75 11.92 12.07171670012 Illinois Sangamon 13.13 13.29 13.37 13.55 12.79 12.95 11.15 11.26171971002 Illinois Will 13.63 14.05 13.33 13.74 12.79 13.19 11.61 11.97171971011 Illinois Will 11.52 11.78 11.26 11.51 10.77 11.00 9.45 9.63172010013 Illinois Winnebago 13.57 13.57 13.10 13.10 12.61 12.61 11.68 11.68180030004 Indiana Allen 13.67 14.08 13.18 13.58 12.81 13.20 11.31 11.67180030014 Indiana Allen 13.55 13.91 13.07 13.42 12.70 13.04 11.21 11.52180190006 Indiana Clark 16.40 16.60 15.96 16.16 15.46 15.65 12.37 12.49180350006 Indiana Delaware 13.66 13.81 13.43 13.58 13.00 13.14 10.65 10.76180372001 Indiana Dubois 15.18 15.68 15.07 15.57 14.50 14.98 11.11 11.51180431004 Indiana Floyd 14.80 14.94 14.50 14.64 14.04 14.17 10.87 10.99180650003 Indiana Henry 13.64 13.64 13.52 13.52 13.08 13.08 10.54 10.54180670003 Indiana Howard 13.93 14.29 13.66 14.01 13.18 13.52 11.08 11.39B-36Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues180830004 Indiana Knox 14.03 14.21 13.94 14.11 13.33 13.49 10.40 10.50180890006 Indiana Lake 14.27 14.51 13.83 14.06 13.35 13.57 12.15 12.36180890027 Indiana Lake 13.83 14.13 13.44 13.73 12.97 13.25 11.71 11.97180891003 Indiana Lake 14.02 14.25 13.61 13.84 13.15 13.37 11.92 12.13180892004 Indiana Lake 14.05 14.41 13.66 14.01 13.19 13.53 11.99 12.31180892010 Indiana Lake 13.89 14.10 13.47 13.67 12.99 13.20 11.81 12.01180910011 Indiana LaPorte 12.49 12.84 12.03 12.36 11.60 11.93 10.35 10.65180910012 Indiana LaPorte 12.69 13.07 12.23 12.60 11.79 12.15 10.48 10.81180950009 Indiana Madison 13.96 14.37 13.80 14.21 13.35 13.75 10.86 11.19180970042 Indiana Marion 14.24 14.51 14.26 14.53 13.78 14.04 10.88 11.11180970078 Indiana Marion 15.26 15.43 15.18 15.35 14.69 14.85 11.85 11.98180970079 Indiana Marion 14.71 14.99 14.61 14.89 14.12 14.39 11.36 11.59180970081 Indiana Marion 16.05 16.36 15.93 16.24 15.43 15.73 12.60 12.87180970083 Indiana Marion 15.90 16.27 15.77 16.15 15.27 15.63 12.44 12.75181270020 Indiana Porter 12.66 13.01 12.18 12.52 11.73 12.06 10.47 10.78181270024 Indiana Porter 13.21 13.39 12.73 12.91 12.26 12.44 10.99 11.12181410014 Indiana St. Joseph 13.28 13.65 12.79 13.14 12.45 12.79 11.39 11.71181411008 Indiana St. Joseph 13.69 13.69 13.17 13.17 12.83 12.83 11.79 11.79181412004 Indiana St. Joseph 12.82 13.22 12.36 12.74 12.02 12.40 10.98 11.34181470009 Indiana Spencer 14.32 14.55 14.21 14.45 13.65 13.87 10.25 10.38181570008 Indiana Tippecanoe 13.69 14.06 13.39 13.75 12.87 13.22 10.82 11.13181630006 Indiana Vanderburgh 14.69 14.89 14.55 14.75 14.02 14.21 11.39 11.56181630012 Indiana Vanderburgh 14.82 15.00 14.64 14.82 14.09 14.27 11.48 11.64181630016 Indiana Vanderburgh 14.99 15.14 14.84 14.99 14.30 14.45 11.67 11.80181670018 Indiana Vigo 13.99 14.17 13.51 13.68 12.95 13.12 10.49 10.62181670023 Indiana Vigo 13.45 13.66 13.04 13.25 12.48 12.68 9.99 10.14190130008 Iowa Black Hawk 11.16 11.52 10.68 11.03 10.37 10.71 9.65 9.96190450021 Iowa Clinton 12.52 12.63 12.08 12.19 11.57 11.67 10.64 10.72191032001 Iowa Johnson 12.08 12.26 11.64 11.81 11.28 11.44 10.43 10.58191130037 Iowa Linn 10.79 10.95 10.37 10.52 10.03 10.18 9.25 9.39B-37Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues191370002 Iowa Montgomery 10.02 10.33 9.55 9.85 9.32 9.61 8.65 8.91191390015 Iowa Muscatine 12.92 13.29 12.53 12.90 12.15 12.50 11.15 11.47191471002 Iowa Palo Alto 9.53 9.53 9.01 9.01 8.80 8.80 8.26 8.26191530030 Iowa Polk 10.41 10.54 9.87 10.00 9.59 9.71 8.91 9.03191532510 Iowa Polk 9.95 10.14 9.44 9.62 9.17 9.34 8.51 8.69191532520 Iowa Polk 10.64 10.64 10.08 10.08 9.79 9.79 9.13 9.13191550009 Iowa Pottawattamie 11.13 11.52 10.55 10.92 10.36 10.73 9.74 10.07191630015 Iowa Scott 11.86 12.06 11.56 11.75 11.06 11.25 10.04 10.21191630018 Iowa Scott 11.64 11.89 11.35 11.59 10.85 11.08 9.85 10.05191630019 Iowa Scott 14.42 14.42 14.00 14.00 13.50 13.50 12.51 12.51191770006 Iowa Van Buren 10.84 10.84 10.46 10.46 10.16 10.16 9.42 9.42191930017 Iowa Woodbury 10.32 10.53 9.81 10.01 9.69 9.89 9.18 9.37191970004 Iowa Wright 10.37 10.51 9.84 9.97 9.57 9.69 8.92 9.04200910007 Kansas Johnson 10.59 10.86 10.09 10.35 9.81 10.05 9.07 9.31200910009 Kansas Johnson 11.10 11.10 10.62 10.62 10.30 10.30 9.47 9.47200910010 Kansas Johnson 9.68 9.749.28 9.34 9.01 9.06 8.26 8.30201070002 Kansas Linn 10.47 10.62 10.16 10.31 9.86 10.00 9.01 9.12201730008 Kansas Sedgwick 10.26 10.85 9.72 10.28 9.49 10.03 8.90 9.42201730009 Kansas Sedgwick 10.29 10.95 9.75 10.36 9.51 10.11 8.92 9.48201730010 Kansas Sedgwick 10.36 10.96 9.81 10.38 9.57 10.13 8.99 9.51201770010 Kansas Shawnee 10.79 10.79 10.27 10.27 10.04 10.04 9.37 9.37201770011 Kansas Shawnee 10.93 10.93 10.42 10.42 10.19 10.19 9.53 9.53201910002 Kansas Sumner 9.89 10.31 9.44 9.84 9.22 9.61 8.61 8.98202090021 Kansas Wyandotte 12.73 13.37 12.09 12.69 11.78 12.36 10.98 11.54202090022 Kansas Wyandotte 10.93 11.25 10.41 10.70 10.11 10.41 9.36 9.65210130002 Kentucky Bell 14.28 14.64 13.28 13.61 12.70 13.01 10.46 10.70210190017 Kentucky Boyd 14.49 14.70 13.54 13.74 12.96 13.15 10.35 10.49210290006 Kentucky Bullitt 14.90 15.21 14.58 14.88 14.07 14.36 10.98 11.20210370003 Kentucky Campbell 13.67 13.67 13.30 13.30 12.81 12.81 9.86 9.86210430500 Kentucky Carter 12.22 12.61 11.38 11.74 10.87 11.21 8.50 8.76B-38Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues210470006 Kentucky Christian 13.20 13.55 13.44 13.78 12.90 13.24 9.61 9.84210590005 Kentucky Daviess 14.10 14.10 14.14 14.14 13.59 13.59 9.82 9.82210670012 Kentucky Fayette 14.33 14.53 13.74 13.93 13.22 13.40 10.36 10.48210670014 Kentucky Fayette 14.85 15.13 14.23 14.50 13.70 13.97 10.86 11.10210730006 Kentucky Franklin 13.37 13.52 12.88 13.03 12.39 12.53 9.52 9.60210930006 Kentucky Hardin 13.58 14.04 13.34 13.79 12.82 13.25 9.68 9.98211010014 Kentucky Henderson 13.93 14.2813.69 14.03 13.17 13.50 10.38 10.63211110043 Kentucky Jefferson 15.53 15.7515.19 15.41 14.71 14.93 11.51 11.69211110044 Kentucky Jefferson 15.31 15.4714.93 15.09 14.45 14.59 11.34 11.43211110048 Kentucky Jefferson 15.25 15.3214.87 14.93 14.38 14.45 11.25 11.30211110051 Kentucky Jefferson 14.70 15.1714.43 14.89 13.95 14.40 10.71 11.05211170007 Kentucky Kenton 14.36 14.52 13.98 14.14 13.50 13.65 10.54 10.67211250004 Kentucky Laurel 12.55 12.55 11.77 11.77 11.25 11.25 9.01 9.01211451004 Kentucky McCracken 13.38 13.84 13.40 13.86 12.79 13.23 10.11 10.41211510003 Kentucky Madison 13.61 13.7012.94 13.03 12.43 12.52 9.69 9.78211930003 Kentucky Perry 13.06 13.42 12.18 12.51 11.66 11.97 9.51 9.76211950002 Kentucky Pike 13.46 13.89 12.48 12.87 11.94 12.31 9.49 9.79212270007 Kentucky Warren 13.83 13.92 13.89 13.97 13.32 13.40 9.93 9.98220171002 Louisiana Caddo 12.53 12.53 12.01 12.01 11.68 11.68 10.55 10.55220190009 Louisiana Calcasieu 10.58 10.78 10.32 10.52 10.06 10.26 9.16 9.35220190010 Louisiana Calcasieu 11.07 11.24 10.83 10.99 10.55 10.71 9.66 9.80220290003 Louisiana Concordia 11.42 11.42 11.08 11.08 10.68 10.68 9.37 9.37220330009 LouisianaEast BatonRouge 13.38 13.57 12.85 13.04 12.43 12.60 11.49 11.65220331001 LouisianaEast BatonRouge 12.08 12.18 11.62 11.70 11.23 11.31 10.29 10.37220470005 Louisiana Iberville 12.90 12.98 12.43 12.50 11.91 11.98 11.00 11.06220470009 Louisiana Iberville 11.02 11.16 10.67 10.80 10.29 10.42 9.22 9.33220511001 Louisiana Jefferson 11.52 11.68 11.02 11.17 10.65 10.79 9.54 9.67220550006 Louisiana Lafayette 11.08 11.18 10.73 10.83 10.42 10.52 9.21 9.30B-39Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues220730004 Louisiana Ouachita 11.97 12.21 11.69 11.91 11.34 11.56 10.17 10.36220790002 Louisiana Rapides 11.03 11.04 10.75 10.77 10.45 10.47 9.29 9.31221050001 Louisiana Tangipahoa 12.03 12.39 11.50 11.85 11.09 11.43 9.89 10.19221090001 Louisiana Terrebonne 10.74 10.83 10.37 10.45 10.03 10.11 8.89 8.96221210001 LouisianaWest BatonRouge 13.51 13.68 12.98 13.15 12.55 12.72 11.62 11.77230010011 Maine Androscoggin 9.90 10.62 9.30 9.98 9.15 9.82 8.83 9.48230030013 Maine Aroostook 9.74 10.27 9.53 10.05 9.46 9.98 9.22 9.72230031011 Maine Aroostook 8.27 8.92 7.98 8.61 7.90 8.51 7.67 8.27230050015 Maine Cumberland 11.06 11.68 10.33 10.91 10.14 10.71 9.80 10.35230050027 Maine Cumberland 11.13 11.53 10.40 10.78 10.22 10.59 9.88 10.24230090103 Maine Hancock 5.76 6.17 5.39 5.77 5.33 5.71 5.04 5.40230110016 Maine Kennebec 9.99 10.70 9.37 10.04 9.23 9.88 8.91 9.54230172011 Maine Oxford 10.13 10.38 9.64 9.88 9.51 9.74 9.18 9.40230190002 Maine Penobscot 9.12 9.65 8.53 9.03 8.41 8.90 8.05 8.52240030014 Maryland Anne Arundel 11.91 11.9110.78 10.78 10.76 10.76 9.20 9.20240031003 Maryland Anne Arundel 14.82 15.26 13.63 14.03 13.73 14.14 12.25 12.61240032002 Maryland Anne Arundel 14.57 14.57 13.38 13.38 13.50 13.50 12.02 12.02240051007 Maryland Baltimore 13.77 14.04 12.61 12.85 12.56 12.80 10.78 10.98240053001 Maryland Baltimore 14.76 15.05 13.50 13.78 13.56 13.83 11.94 12.19240150003 Maryland Cecil 12.68 12.82 11.59 11.72 11.45 11.58 9.90 10.00240251001 Maryland Harford 12.51 12.62 11.34 11.44 11.34 11.44 9.76 9.85240313001 Maryland Montgomery 12.47 12.70 11.41 11.62 11.28 11.49 9.57 9.75240330030 Maryland Prince George's 12.24 12.24 11.20 11.20 11.13 11.13 9.53 9.53240338003 Maryland Prince George's 13.03 13.23 11.78 11.98 11.70 11.89 10.03 10.21240430009 Maryland Washington 13.70 14.14 12.83 13.23 12.56 12.96 10.41 10.74245100006 Maryland Baltimore (City) 14.12 14.37 12.92 13.15 12.96 13.19 11.35 11.55245100007 Maryland Baltimore (City) 14.38 15.01 13.18 13.74 13.15 13.71 11.46 11.93245100008 Maryland Baltimore (City) 15.76 15.87 14.47 14.57 14.57 14.67 12.99 13.08245100049 Maryland Baltimore (City) 15.63 15.63 14.36 14.36 14.48 14.48 12.97 12.97B-40Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues250035001 Massachusetts Berkshire 10.65 11.15 10.05 10.52 9.90 10.37 9.07 9.51250051004 Massachusetts Bristol 9.58 10.16 8.78 9.33 8.71 9.25 8.07 8.57250092006 Massachusetts Essex 9.03 9.09 8.31 8.37 8.21 8.27 7.66 7.71250095005 Massachusetts Essex 9.10 9.32 8.41 8.60 8.29 8.49 7.77 7.95250096001 Massachusetts Essex 9.58 9.74 8.87 9.02 8.74 8.89 8.20 8.34250130008 Massachusetts Hampden 9.8510.14 9.22 9.49 9.08 9.34 8.30 8.54250130016 Massachusetts Hampden 12.17 12.52 11.41 11.73 11.22 11.54 10.43 10.73250132009 Massachusetts Hampden 11.85 11.90 11.10 11.15 10.92 10.97 10.14 10.18250230004 Massachusetts Plymouth 9.87 10.14 9.09 9.34 8.97 9.22 8.34 8.57250250002 Massachusetts Suffolk 12.34 13.0011.48 12.09 11.32 11.92 10.73 11.30250250027 Massachusetts Suffolk 11.86 12.2710.99 11.38 10.84 11.22 10.24 10.61250250042 Massachusetts Suffolk 10.88 11.36 10.08 10.53 9.95 10.39 9.36 9.78250250043 Massachusetts Suffolk 13.07 13.8812.16 12.92 11.98 12.73 11.39 12.11250270016 Massachusetts Worcester 10.55 10.70 9.80 9.94 9.64 9.78 8.92 9.04250270023 Massachusetts Worcester 11.29 11.32 10.50 10.52 10.33 10.35 9.62 9.63260050003 Michigan Allegan 11.84 11.99 11.44 11.58 11.01 11.14 9.64 9.74260170014 Michigan Bay 10.93 11.05 10.40 10.52 10.06 10.17 8.99 9.08260210014 Michigan Berrien 11.72 11.91 11.32 11.51 10.92 11.10 9.65 9.78260490021 Michigan Genesee 11.61 11.79 11.06 11.24 10.72 10.89 9.43 9.57260650012 Michigan Ingham 12.23 12.51 11.68 11.95 11.30 11.56 9.96 10.19260770008 Michigan Kalamazoo 12.84 13.06 12.30 12.50 11.92 12.11 10.58 10.76260810020 Michigan Kent 12.89 13.09 12.21 12.40 11.80 11.98 10.64 10.80260990009 Michigan Macomb 12.70 13.04 12.13 12.46 11.81 12.12 10.43 10.67261130001 Michigan Missaukee 8.26 8.36 8.04 8.13 7.78 7.87 7.13 7.21261150005 Michigan Monroe 13.92 14.13 13.29 13.50 12.88 13.07 11.13 11.29261210040 Michigan Muskegon 11.61 11.70 11.19 11.28 10.79 10.87 9.70 9.75261250001 Michigan Oakland 13.78 14.26 13.07 13.53 12.70 13.15 11.29 11.69261390005 Michigan Ottawa 12.55 12.67 11.94 12.05 11.53 11.63 10.31 10.39261450018 Michigan Saginaw 10.61 10.61 10.11 10.11 9.78 9.78 8.73 8.73261470005 Michigan St. Clair 13.34 13.75 12.85 13.25 12.53 12.92 11.15 11.47B-41Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues261610005 Michigan Washtenaw 12.30 12.30 11.77 11.77 11.42 11.42 9.97 9.97261610008 Michigan Washtenaw 13.88 14.29 13.21 13.60 12.83 13.22 11.42 11.74261630001 Michigan Wayne 14.52 15.11 13.72 14.29 13.33 13.88 11.87 12.35261630015 Michigan Wayne 15.88 16.40 15.05 15.55 14.64 15.12 13.01 13.42261630016 Michigan Wayne 14.57 15.17 13.83 14.40 13.46 14.02 12.01 12.50261630019 Michigan Wayne 14.32 14.77 13.64 14.07 13.29 13.71 11.86 12.21261630025 Michigan Wayne 13.39 13.88 12.73 13.20 12.35 12.80 10.85 11.21261630033 Michigan Wayne 17.50 18.16 16.57 17.19 16.12 16.72 14.43 14.94261630036 Michigan Wayne 14.67 15.44 13.92 14.65 13.53 14.23 11.96 12.54270210001 Minnesota Cass 5.70 5.80 5.48 5.58 5.40 5.50 5.18 5.28270370470 Minnesota Dakota 9.30 9.55 8.86 9.10 8.66 8.89 8.25 8.47270530050 Minnesota Hennepin 9.76 9.82 9.28 9.33 9.08 9.13 8.70 8.75270530961 Minnesota Hennepin 9.14 9.27 8.69 8.81 8.49 8.61 8.10 8.21270530963 Minnesota Hennepin 9.59 9.81 9.10 9.31 8.90 9.10 8.51 8.71270530965 Minnesota Hennepin 9.54 9.58 9.06 9.10 8.86 8.90 8.49 8.53270531007 Minnesota Hennepin 9.56 9.75 9.08 9.26 8.87 9.05 8.48 8.65270532006 Minnesota Hennepin 9.33 9.39 8.87 8.91 8.67 8.71 8.28 8.32270953051 Minnesota Mille Lacs 6.54 6.67 6.28 6.41 6.17 6.29 5.92 6.03271095008 Minnesota Olmsted 10.13 10.13 9.64 9.64 9.40 9.40 8.84 8.84271230866 Minnesota Ramsey 11.32 11.61 10.81 11.09 10.58 10.85 10.20 10.46271230868 Minnesota Ramsey 11.02 11.31 10.49 10.77 10.27 10.53 9.91 10.17271230871 Minnesota Ramsey 9.63 9.80 9.17 9.33 8.97 9.13 8.61 8.76271377001 Minnesota Saint Louis 6.10 6.15 5.93 5.98 5.76 5.81 5.56 5.60271377550 Minnesota Saint Louis 6.19 6.25 5.94 6.00 5.80 5.86 5.57 5.63271377551 Minnesota Saint Louis 7.51 7.62 7.19 7.29 7.02 7.13 6.79 6.88271390505 Minnesota Scott 9.00 9.16 8.57 8.71 8.37 8.51 7.95 8.08271453052 Minnesota Stearns 8.58 8.80 8.19 8.40 8.02 8.23 7.69 7.89280010004 Mississippi Adams 11.29 11.46 10.93 11.10 10.53 10.69 9.20 9.35280110001 Mississippi Bolivar 12.36 12.58 12.13 12.35 11.65 11.86 10.02 10.20280330002 Mississippi DeSoto 12.43 12.51 12.06 12.13 11.47 11.54 9.55 9.61B-42Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues280350004 Mississippi Forrest 13.62 13.99 12.84 13.19 12.40 12.74 11.00 11.30280470008 Mississippi Harrison 12.20 12.34 11.60 11.74 11.23 11.36 10.05 10.17280490010 Mississippi Hinds 12.56 12.66 11.98 12.07 11.50 11.59 10.13 10.21280590006 Mississippi Jackson 12.04 12.16 11.29 11.41 10.89 11.01 9.72 9.82280670002 Mississippi Jones 14.39 14.59 13.55 13.75 13.07 13.25 11.58 11.74280750003 Mississippi Lauderdale 13.07 13.09 12.44 12.45 11.92 11.93 10.34 10.35280810005 Mississippi Lee 12.57 12.83 12.15 12.40 11.57 11.81 9.65 9.83280870001 Mississippi Lowndes 12.79 13.11 12.27 12.57 11.69 11.98 9.95 10.18281090001 Mississippi Pearl River 12.14 12.14 11.60 11.60 11.22 11.22 9.99 9.99281490004 Mississippi Warren 12.32 12.32 11.90 11.90 11.43 11.43 10.07 10.07290190004 Missouri Boone 11.84 11.84 11.68 11.68 11.22 11.22 10.08 10.08290210005 Missouri Buchanan 12.80 12.80 12.28 12.28 12.01 12.01 11.29 11.29290370003 Missouri Cass 10.67 10.83 10.25 10.41 9.94 10.09 9.08 9.20290390001 Missouri Cedar 11.12 11.12 10.82 10.82 10.51 10.51 9.52 9.52290470005 Missouri Clay 11.03 11.25 10.51 10.73 10.23 10.44 9.39 9.56290770032 Missouri Greene 11.75 11.87 11.51 11.63 11.12 11.24 9.94 10.05290950034 Missouri Jackson 12.78 13.19 12.12 12.50 11.79 12.17 10.99 11.35290990012 Missouri Jefferson 13.79 13.97 13.72 13.90 13.15 13.33 11.60 11.77291370001 Missouri Monroe 10.87 10.87 10.69 10.69 10.21 10.21 9.02 9.02291831002 Missouri Saint Charles 13.29 13.70 13.50 13.92 12.89 13.29 11.03 11.38291860006 Missouri Sainte Genevieve 13.34 13.66 13.29 13.60 12.64 12.93 10.94 11.19291890004 Missouri Saint Louis 13.04 13.04 13.00 13.00 12.42 12.42 10.85 10.85291892003 Missouri Saint Louis 13.46 13.79 13.43 13.76 12.83 13.14 11.19 11.47295100007 Missouri St. Louis City 14.27 14.45 14.17 14.34 13.57 13.74 12.00 12.16295100085 Missouri St. Louis City 14.36 14.45 14.32 14.40 13.69 13.77 12.04 12.11295100086 Missouri St. Louis City 13.44 13.60 13.44 13.61 12.82 12.98 11.18 11.32295100087 Missouri St. Louis City 14.56 14.70 14.51 14.65 13.86 14.00 12.20 12.33300870307 Montana Rosebud 6.58 6.58 6.48 6.48 6.45 6.45 6.47 6.47301111065 Montana Yellowstone 8.14 8.18 7.89 7.92 7.84 7.87 7.85 7.88310250002 Nebraska Cass 9.99 9.99 9.46 9.46 9.25 9.25 8.64 8.64B-43Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues310550019 Nebraska Douglas 9.88 10.06 9.37 9.55 9.19 9.36 8.56 8.72310550052 Nebraska Douglas 9.85 10.18 9.35 9.66 9.15 9.45 8.54 8.83310790004 Nebraska Hall 7.95 7.95 7.56 7.56 7.40 7.40 7.00 7.00311090022 Nebraska Lancaster 8.90 9.28 8.43 8.79 8.22 8.57 7.67 8.01311111002 Nebraska Lincoln 7.57 7.57 7.28 7.28 7.19 7.19 6.97 6.97311530007 Nebraska Sarpy 9.79 9.86 9.27 9.34 9.08 9.14 8.45 8.52311570003 Nebraska Scotts Bluff 6.04 6.04 5.78 5.78 5.72 5.72 5.68 5.68311770002 Nebraska Washington 9.29 9.35 8.85 8.91 8.66 8.72 8.07 8.13330012004 New Hampshire Belknap 7.28 7.33 6.76 6.80 6.65 6.69 6.14 6.19330050007 New Hampshire Cheshire 11.53 11.61 10.81 10.88 10.63 10.70 9.97 10.03330070014 New Hampshire Coos 10.24 10.39 9.81 9.96 9.68 9.83 9.27 9.41330090010 New Hampshire Grafton 8.43 8.43 7.94 7.94 7.81 7.81 7.27 7.27330110020 New Hampshire Hillsborough 10.1810.18 9.36 9.36 9.22 9.22 8.64 8.64330111015 New Hampshire Hillsborough 10.0110.01 9.27 9.27 9.13 9.13 8.52 8.52330115001 New Hampshire Hillsborough 6.27 6.27 5.78 5.78 5.69 5.69 5.22 5.22330131006 New Hampshire Merrimack 9.72 9.73 8.95 8.96 8.80 8.82 8.23 8.24330150014 New Hampshire Rockingham 9.00 9.20 8.30 8.48 8.18 8.36 7.74 7.91330190003 New Hampshire Sullivan 9.86 10.17 9.27 9.56 9.12 9.40 8.52 8.77340011006 New Jersey Atlantic 11.47 11.47 10.73 10.73 10.59 10.59 9.33 9.33340030003 New Jersey Bergen 13.09 13.29 12.00 12.17 11.78 11.94 10.72 10.86340070003 New Jersey Camden 13.31 13.40 12.32 12.40 12.10 12.18 10.74 10.82340071007 New Jersey Camden 13.51 13.78 12.48 12.72 12.24 12.48 10.88 11.08340130015 New Jersey Essex 13.27 13.29 12.15 12.18 11.90 11.92 10.82 10.84340155001 New Jersey Gloucester 13.46 13.46 12.48 12.48 12.25 12.25 10.82 10.82340171003 New Jersey Hudson 14.24 14.66 13.15 13.54 12.91 13.28 11.84 12.17340210008 New Jersey Mercer 12.71 12.97 11.83 12.05 11.61 11.83 10.29 10.46340218001 New Jersey Mercer 11.14 11.66 10.34 10.81 10.14 10.61 8.87 9.26340230006 New Jersey Middlesex 12.15 12.52 11.31 11.65 11.10 11.44 9.88 10.17340270004 New Jersey Morris 11.50 11.92 10.62 11.00 10.43 10.80 9.24 9.56340273001 New Jersey Morris 10.21 10.59 9.49 9.83 9.33 9.67 8.15 8.44B-44Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues340292002 New Jersey Ocean 10.92 11.27 10.19 10.51 10.02 10.34 8.85 9.13340310005 New Jersey Passaic 12.88 13.09 11.76 11.93 11.53 11.71 10.44 10.57340390004 New Jersey Union 14.94 15.53 13.73 14.28 13.43 13.97 12.29 12.79340390006 New Jersey Union 13.32 13.64 12.16 12.45 11.90 12.17 10.82 11.06340392003 New Jersey Union 13.06 13.32 11.98 12.21 11.72 11.94 10.61 10.80340410006 New Jersey Warren 12.72 13.11 11.82 12.17 11.63 11.97 10.21 10.50350010023 New Mexico Bernalillo 7.03 7.13 6.59 6.68 6.50 6.59 6.45 6.54350010024 New Mexico Bernalillo 6.64 6.81 6.22 6.39 6.13 6.30 6.08 6.25350050005 New Mexico Chaves 6.54 6.58 6.29 6.33 6.24 6.28 6.09 6.13350130017 New Mexico Dona Ana 9.95 10.40 9.55 9.97 9.50 9.93 9.40 9.82350130025 New Mexico Dona Ana 6.31 6.35 6.03 6.07 5.99 6.03 5.88 5.93350431003 New Mexico Sandoval 5.00 5.02 4.69 4.71 4.63 4.65 4.58 4.61350439011 New Mexico Sandoval 7.99 8.34 7.74 8.08 7.69 8.02 7.65 7.97350450006 New Mexico San Juan 5.92 6.08 5.75 5.91 5.73 5.88 5.72 5.87350490020 New Mexico Santa Fe 4.76 4.81 4.59 4.64 4.55 4.60 4.52 4.57360010005 New York Albany 11.83 11.83 11.29 11.29 11.15 11.15 10.30 10.30360050080 New York Bronx 15.43 15.72 14.28 14.55 14.03 14.29 12.96 13.19360050083 New York Bronx 13.09 13.35 12.07 12.30 11.85 12.08 10.80 11.00360050110 New York Bronx 13.45 14.06 12.44 13.01 12.21 12.77 11.17 11.68360130011 New York Chautauqua 9.80 10.09 9.22 9.49 8.99 9.25 7.41 7.61360290005 New York Erie 12.62 12.79 11.98 12.15 11.76 11.92 10.38 10.52360291007 New York Erie 12.64 13.00 11.99 12.34 11.76 12.11 10.30 10.62360310003 New York Essex 5.94 5.98 5.71 5.75 5.62 5.66 4.98 5.02360470122 New York Kings 14.20 14.64 13.19 13.60 12.95 13.35 11.88 12.25360551007 New York Monroe 10.64 10.64 10.17 10.17 9.99 9.99 8.77 8.77360590008 New York Nassau 11.66 12.07 10.89 11.27 10.72 11.09 9.74 10.08360610056 New York New York 16.18 17.02 14.98 15.74 14.70 15.45 13.56 14.22360610062 New York New York 14.80 15.31 13.70 14.16 13.44 13.90 12.34 12.76360610079 New York New York 13.61 14.00 12.59 12.95 12.36 12.71 11.31 11.62360610128 New York New York 15.41 15.80 14.33 14.68 14.08 14.42 13.00 13.31B-45Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues360632008 New York Niagara 11.96 12.29 11.45 11.76 11.23 11.54 9.83 10.09360671015 New York Onondaga 10.08 10.46 9.61 9.97 9.46 9.81 8.18 8.47360710002 New York Orange 10.99 11.43 10.20 10.60 10.05 10.45 8.98 9.33360810124 New York Queens 12.18 12.69 11.30 11.78 11.10 11.57 10.13 10.56360850055 New York Richmond 13.31 13.37 12.23 12.29 11.97 12.03 10.90 10.95360850067 New York Richmond 11.59 11.82 10.66 10.88 10.44 10.64 9.51 9.70360893001 New York St. Lawrence 7.29 7.71 7.06 7.45 6.96 7.35 6.27 6.61361010003 New York Steuben 9.00 9.38 8.46 8.81 8.31 8.65 6.91 7.18361030001 New York Suffolk 11.52 11.52 10.78 10.78 10.62 10.62 9.58 9.58361191002 New York Westchester 11.73 11.94 10.85 11.03 10.67 10.84 9.61 9.76370010002 North Carolina Alamance 13.94 14.07 12.39 12.52 12.00 12.13 10.21 10.32370210034 North Carolina Buncombe 12.60 12.65 11.32 11.36 10.88 10.92 9.25 9.28370330001 North Carolina Caswell 13.19 13.33 11.66 11.78 11.31 11.43 9.49 9.59370350004 North Carolina Catawba 15.31 15.37 13.35 13.41 12.90 12.96 11.03 11.08370370004 North Carolina Chatham 11.99 12.15 10.72 10.87 10.34 10.48 8.70 8.82370510009 North Carolina Cumberland 13.73 13.85 12.62 12.73 12.22 12.33 10.75 10.85370570002 North Carolina Davidson 15.17 15.24 13.47 13.53 13.07 13.13 11.17 11.23370610002 North Carolina Duplin 11.30 11.54 10.33 10.56 10.04 10.25 8.66 8.85370630001 North Carolina Durham 13.57 13.67 12.23 12.32 11.84 11.93 10.16 10.25370650004 North Carolina Edgecombe 12.37 12.38 11.40 11.40 11.05 11.05 9.43 9.44370670022 North Carolina Forsyth 14.28 14.45 12.48 12.63 12.09 12.23 10.13 10.25370710016 North Carolina Gaston 14.26 14.40 12.39 12.51 11.97 12.09 10.31 10.41370810013 North Carolina Guilford 13.79 13.79 12.24 12.24 11.87 11.87 10.09 10.09370870010 North Carolina Haywood 12.98 13.00 11.84 11.86 11.39 11.40 10.02 10.04370990006 North Carolina Jackson 12.09 12.43 10.97 11.29 10.44 10.74 8.87 9.13371070004 North Carolina Lenoir 11.12 11.29 10.21 10.37 9.92 10.08 8.53 8.67371110004 North Carolina McDowell 14.24 14.35 12.73 12.83 12.31 12.40 10.58 10.66371170001 North Carolina Martin 10.86 11.12 9.95 10.20 9.69 9.93 8.27 8.47371190010 North Carolina Mecklenburg 15.31 15.31 13.42 13.42 13.03 13.03 11.42 11.42371190041 North Carolina Mecklenburg 14.74 14.94 12.92 13.10 12.52 12.69 10.88 11.04B-46Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues371190042 North Carolina Mecklenburg 14.80 14.93 12.98 13.09 12.58 12.68 10.94 11.04371210001 North Carolina Mitchell 12.75 13.00 11.34 11.56 10.93 11.14 9.13 9.30371230001 North Carolina Montgomery 12.24 12.35 10.95 11.05 10.55 10.64 8.95 9.03371290002 North Carolina New Hanover 9.96 10.18 9.20 9.40 8.95 9.15 7.74 7.91371330005 North Carolina Onslow 10.98 11.26 10.12 10.39 9.85 10.11 8.49 8.72371350007 North Carolina Orange 13.12 13.25 11.77 11.88 11.36 11.47 9.65 9.74371470005 North Carolina Pitt 11.59 11.90 10.65 10.94 10.35 10.63 8.89 9.13371550005 North Carolina Robeson 12.78 12.79 11.72 11.75 11.40 11.42 9.99 10.01371590021 North Carolina Rowan 14.02 14.02 12.48 12.48 12.11 12.11 10.39 10.39371730002 North Carolina Swain 12.65 12.82 11.51 11.67 10.94 11.09 9.28 9.41371830014 North Carolina Wake 13.54 13.57 12.25 12.29 11.85 11.88 10.20 10.22371890003 North Carolina Watauga 12.05 12.06 10.65 10.66 10.24 10.25 8.28 8.30371910005 North Carolina Wayne 12.96 13.14 11.99 12.16 11.62 11.78 10.11 10.25380070002 North Dakota Billings 4.614.68 4.47 4.54 4.45 4.52 4.43 4.50380130002 North Dakota Burke 5.90 5.90 5.76 5.76 5.74 5.74 5.72 5.72380130003 North Dakota Burke 5.78 5.78 5.62 5.62 5.60 5.60 5.58 5.58380150003 North Dakota Burleigh 6.61 6.71 6.21 6.30 6.15 6.24 6.10 6.18380171004 North Dakota Cass 7.72 7.75 7.36 7.40 7.25 7.28 7.07 7.10380530002 North Dakota McKenzie 5.01 5.09 4.88 4.96 4.85 4.94 4.84 4.92380570004 North Dakota Mercer 6.04 6.15 5.97 6.08 5.94 6.05 5.91 6.02390090003 Ohio Athens 12.39 12.67 11.40 11.66 10.89 11.15 8.57 8.77390170016 Ohio Butler 15.74 16.11 15.25 15.61 14.76 15.12 11.94 12.23390170017 Ohio Butler 15.36 15.36 14.93 14.93 14.48 14.48 11.98 11.98390171004 Ohio Butler 14.90 15.14 14.51 14.74 14.06 14.29 11.44 11.62390230005 Ohio Clark 14.64 14.77 14.08 14.21 13.65 13.78 11.26 11.37390250022 Ohio Clermont 14.15 14.15 13.69 13.69 13.20 13.20 10.32 10.32390350027 Ohio Cuyahoga 15.46 16.13 14.50 15.13 14.06 14.67 11.85 12.35390350034 Ohio Cuyahoga 13.76 14.07 12.93 13.23 12.54 12.82 10.51 10.76390350038 Ohio Cuyahoga 17.37 18.10 16.26 16.95 15.79 16.45 13.59 14.17390350045 Ohio Cuyahoga 16.47 16.98 15.42 15.91 14.96 15.43 12.74 13.15B-47Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues390350060 Ohio Cuyahoga 17.11 17.66 16.02 16.54 15.55 16.06 13.35 13.81390350065 Ohio Cuyahoga 15.97 16.44 14.96 15.40 14.51 14.94 12.30 12.65390351002 Ohio Cuyahoga 14.14 14.64 13.30 13.77 12.92 13.38 10.92 11.32390490024 Ohio Franklin 15.27 15.95 14.33 14.97 13.85 14.47 11.52 12.05390490025 Ohio Franklin 15.08 15.45 14.12 14.47 13.64 13.98 11.31 11.59390490081 Ohio Franklin 14.33 14.33 13.51 13.51 13.03 13.03 10.69 10.69390570005 Ohio Greene 13.36 13.55 12.83 13.02 12.41 12.59 9.98 10.14390610006 Ohio Hamilton 14.84 14.84 14.36 14.36 13.88 13.88 11.07 11.07390610014 Ohio Hamilton 17.29 17.53 16.69 16.93 16.14 16.37 13.15 13.32390610040 Ohio Hamilton 15.50 15.88 15.03 15.40 14.51 14.87 11.48 11.78390610042 Ohio Hamilton 16.85 17.25 16.33 16.71 15.80 16.18 12.82 13.14390610043 Ohio Hamilton 15.55 15.82 15.05 15.32 14.56 14.82 11.77 12.00390617001 Ohio Hamilton 16.17 16.56 15.65 16.03 15.12 15.49 12.13 12.46390618001 Ohio Hamilton 17.54 17.90 16.93 17.27 16.38 16.71 13.41 13.68390810017 Ohio Jefferson 15.41 15.46 13.95 13.99 13.53 13.58 11.20 11.25390811001 Ohio Jefferson 16.51 17.17 14.95 15.54 14.50 15.07 11.96 12.42390851001 Ohio Lake 13.02 13.02 12.33 12.33 11.96 11.96 10.03 10.03390870010 Ohio Lawrence 15.14 15.44 14.19 14.47 13.63 13.89 11.20 11.41390930016 Ohio Lorain 13.87 14.13 13.13 13.37 12.74 12.98 10.64 10.83390933002 Ohio Lorain 12.78 12.98 12.12 12.31 11.79 11.98 10.18 10.34390950024 Ohio Lucas 14.38 14.68 13.72 14.00 13.29 13.57 11.53 11.78390950025 Ohio Lucas 13.95 14.37 13.32 13.72 12.90 13.29 11.11 11.46390950026 Ohio Lucas 14.08 14.30 13.48 13.68 13.05 13.26 11.28 11.47390990005 Ohio Mahoning 14.68 14.99 13.80 14.10 13.38 13.66 11.30 11.53390990014 Ohio Mahoning 15.12 15.53 14.23 14.62 13.79 14.16 11.71 12.04391130031 Ohio Montgomery 14.58 14.58 14.09 14.09 13.66 13.66 11.23 11.23391130032 Ohio Montgomery 15.54 15.92 15.01 15.37 14.55 14.90 12.07 12.37391330002 Ohio Portage 13.37 13.56 12.62 12.79 12.23 12.39 10.19 10.33391351001 Ohio Preble 13.70 13.88 13.46 13.64 13.04 13.20 10.37 10.51391450013 Ohio Scioto 14.65 14.84 13.68 13.86 13.14 13.31 10.60 10.73B-48Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues391510017 Ohio Stark 16.15 16.59 14.99 15.40 14.60 15.00 12.26 12.60391510020 Ohio Stark 15.14 15.14 14.07 14.07 13.71 13.71 11.73 11.73391530017 Ohio Summit 15.17 15.61 14.28 14.71 13.91 14.32 11.91 12.27391530023 Ohio Summit 14.26 14.58 13.42 13.73 13.07 13.38 11.13 11.40391550007 Ohio Trumbull 14.53 14.73 13.75 13.94 13.32 13.51 11.27 11.44400159008 Oklahoma Caddo 9.22 9.77 8.69 9.21 8.57 9.08 8.07 8.54400219002 Oklahoma Cherokee 11.79 12.28 11.41 11.88 11.10 11.56 10.16 10.58400719010 Oklahoma Kay 10.26 10.62 9.96 10.32 9.76 10.11 9.19 9.52400819005 Oklahoma Lincoln 10.28 10.28 9.83 9.83 9.60 9.60 8.91 8.91400970186 Oklahoma Mayes 11.70 11.83 11.46 11.59 11.17 11.30 10.33 10.45400979014 Oklahoma Mayes 11.44 11.62 11.18 11.36 10.89 11.07 10.03 10.19401010169 Oklahoma Muskogee 11.89 12.10 11.61 11.81 11.32 11.52 10.46 10.66401090035 Oklahoma Oklahoma 10.07 10.23 9.47 9.62 9.25 9.40 8.65 8.79401091037 Oklahoma Oklahoma 9.86 10.07 9.29 9.48 9.07 9.26 8.46 8.64401159004 Oklahoma Ottawa 11.69 11.95 11.31 11.56 11.02 11.25 10.12 10.32401210415 Oklahoma Pittsburg 11.06 11.28 10.63 10.84 10.37 10.57 9.54 9.72401359015 Oklahoma Sequoyah 12.99 12.99 12.56 12.56 12.25 12.25 11.30 11.30401430110 Oklahoma Tulsa 11.52 11.52 11.13 11.13 10.86 10.86 10.07 10.07401431127 Oklahoma Tulsa 11.37 11.56 10.99 11.17 10.72 10.90 9.96 10.11420010001 Pennsylvania Adams 13.05 13.59 12.13 12.64 11.90 12.41 9.83 10.26420030008 Pennsylvania Allegheny 15.24 15.4814.11 14.33 13.70 13.92 11.29 11.49420030021 Pennsylvania Allegheny 14.66 14.6613.65 13.65 13.26 13.26 10.80 10.80420030064 Pennsylvania Allegheny 20.31 20.7518.90 19.31 18.38 18.78 15.88 16.23420030067 Pennsylvania Allegheny 12.86 12.94 11.82 11.89 11.45 11.52 9.14 9.19420030095 Pennsylvania Allegheny 13.84 14.5412.77 13.42 12.41 13.04 10.12 10.63420030116 Pennsylvania Allegheny 15.36 15.3614.17 14.17 13.78 13.78 11.50 11.50420031008 Pennsylvania Allegheny 15.25 15.4914.26 14.49 13.89 14.11 11.21 11.40420031301 Pennsylvania Allegheny 16.26 16.5715.13 15.42 14.70 14.98 12.14 12.36420033007 Pennsylvania Allegheny 15.30 15.7214.20 14.59 13.76 14.13 11.14 11.44420039002 Pennsylvania Allegheny 14.44 14.4413.44 13.44 13.06 13.06 10.46 10.46B-49Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues420070014 Pennsylvania Beaver 16.38 16.45 15.23 15.30 14.87 14.93 12.65 12.72420110011 Pennsylvania Berks 15.82 16.19 14.77 15.11 14.57 14.91 12.78 13.08420170012 Pennsylvania Bucks 13.42 13.93 12.45 12.92 12.21 12.66 10.83 11.22420210011 Pennsylvania Cambria 15.40 15.55 14.88 15.02 14.53 14.67 11.33 11.41420270100 Pennsylvania Centre 12.78 13.42 11.95 12.55 11.70 12.30 9.51 10.02420290100 Pennsylvania Chester 15.22 15.22 14.03 14.03 13.84 13.84 12.13 12.13420410101 Pennsylvania Cumberland 14.45 15.12 13.48 14.12 13.26 13.89 11.26 11.79420430401 Pennsylvania Dauphin 15.13 15.78 13.98 14.59 13.75 14.35 11.53 12.05420450002 Pennsylvania Delaware 15.23 15.6914.16 14.58 13.91 14.33 12.43 12.80420490003 Pennsylvania Erie 12.54 12.57 11.86 11.88 11.54 11.57 9.79 9.81420692006 Pennsylvania Lackawanna 11.73 12.17 10.77 11.17 10.60 11.00 9.13 9.47420710007 Pennsylvania Lancaster 16.55 17.46 15.18 16.01 14.98 15.79 12.94 13.64420770004 Pennsylvania Lehigh 14.50 14.50 13.48 13.48 13.28 13.28 11.81 11.81420791101 Pennsylvania Luzerne 12.76 12.76 11.76 11.76 11.59 11.59 10.13 10.13420850100 Pennsylvania Mercer 13.28 13.74 12.51 12.94 12.11 12.52 10.08 10.43420950025 Pennsylvania Northampton 13.68 14.07 12.69 13.06 12.48 12.85 11.05 11.38420990301 Pennsylvania Perry 12.81 12.81 11.98 11.98 11.78 11.78 9.97 9.97421010047 Pennsylvania Philadelphia 15.19 15.19 14.10 14.10 13.82 13.82 12.46 12.46421250005 Pennsylvania Washington 15.17 15.48 14.10 14.39 13.63 13.91 10.89 11.12421250200 Pennsylvania Washington 14.92 14.92 13.74 13.74 13.29 13.29 10.61 10.61421255001 Pennsylvania Washington 13.37 13.61 12.21 12.44 11.87 12.09 9.78 9.97421290008 Pennsylvania Westmoreland 15.49 15.6814.49 14.67 14.05 14.23 11.13 11.28421330008 Pennsylvania York 16.52 17.25 15.25 15.93 15.06 15.73 12.86 13.43440070022 Rhode Island Providence 10.0710.07 9.34 9.34 9.22 9.22 8.59 8.59440070026 Rhode Island Providence 12.14 12.41 11.29 11.54 11.13 11.38 10.47 10.70440070028 Rhode Island Providence 10.8211.10 10.06 10.32 9.92 10.19 9.28 9.53440071010 Rhode Island Providence 9.93 10.23 9.20 9.48 9.08 9.35 8.43 8.68450130007 South Carolina Beaufort 11.52 11.71 10.66 10.84 10.29 10.47 9.13 9.28450190048 South Carolina Charleston 12.21 12.48 11.26 11.51 10.92 11.17 9.80 10.02450190049 South Carolina Charleston 11.60 11.83 10.79 11.00 10.44 10.65 9.25 9.43B-50Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues450250001 South Carolina Chesterfield 12.53 12.75 11.49 11.69 11.11 11.30 9.73 9.89450370001 South Carolina Edgefield 13.14 13.38 12.24 12.47 11.70 11.91 10.41 10.60450410002 South Carolina Florence 12.62 12.73 11.60 11.69 11.24 11.34 9.91 9.99450430009 South Carolina Georgetown 12.85 12.90 11.74 11.78 11.45 11.49 10.30 10.34450450008 South Carolina Greenville 15.65 15.92 14.09 14.34 13.55 13.79 12.02 12.23450450009 South Carolina Greenville 14.66 14.82 13.16 13.30 12.63 12.77 11.07 11.20450470003 South Carolina Greenwood 13.53 13.70 12.41 12.56 11.73 11.87 10.27 10.39450510002 South Carolina Horry 12.00 12.16 11.03 11.17 10.71 10.85 9.49 9.61450630008 South Carolina Lexington 14.64 15.07 13.49 13.88 12.97 13.35 11.63 11.97450730001 South Carolina Oconee 10.95 11.24 9.80 10.06 9.28 9.53 7.83 8.03450790007 South Carolina Richland 13.56 13.79 12.44 12.65 11.95 12.15 10.58 10.76450790019 South Carolina Richland 14.24 14.45 13.09 13.30 12.59 12.79 11.24 11.42450830010 South Carolina Spartanburg 14.17 14.33 12.62 12.76 12.14 12.28 10.58 10.70460110002 South Dakota Brookings 9.37 9.77 8.91 9.28 8.76 9.12 8.41 8.76460130003 South Dakota Brown 8.42 8.48 8.01 8.07 7.90 7.96 7.71 7.77460290002 South Dakota Codington 10.14 10.34 9.67 9.86 9.54 9.72 9.29 9.47460330132 South Dakota Custer 5.64 5.64 5.48 5.48 5.45 5.45 5.43 5.43460710001 South Dakota Jackson 5.395.45 5.24 5.29 5.21 5.26 5.14 5.20460990006 South Dakota Minnehaha 10.1810.39 9.63 9.82 9.44 9.63 9.03 9.22460990007 South Dakota Minnehaha 9.58 9.82 9.07 9.28 8.89 9.10 8.48 8.68461030016 South Dakota Pennington 7.48 7.59 7.09 7.19 7.04 7.14 7.02 7.12461030020 South Dakota Pennington 8.77 8.83 8.34 8.40 8.29 8.34 8.27 8.32461031001 South Dakota Pennington 7.32 7.35 6.95 6.98 6.91 6.94 6.89 6.92470090011 Tennessee Blount 14.30 14.71 13.20 13.57 12.64 12.99 10.80 11.09470370023 Tennessee Davidson 14.18 14.27 14.02 14.11 13.45 13.53 10.73 10.79470370025 Tennessee Davidson 13.92 14.04 13.71 13.83 13.13 13.24 10.42 10.50470370036 Tennessee Davidson 12.97 12.98 12.82 12.82 12.24 12.25 9.53 9.55470450004 Tennessee Dyer 12.28 12.57 12.22 12.51 11.68 11.95 9.25 9.44470650031 Tennessee Hamilton 15.48 16.05 14.36 14.89 13.72 14.23 11.75 12.17470651011 Tennessee Hamilton 13.62 13.78 12.63 12.77 12.01 12.15 9.89 9.99B-51Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues470654002 Tennessee Hamilton 15.07 15.21 13.98 14.09 13.34 13.45 11.26 11.35470930028 Tennessee Knox 15.47 15.74 14.18 14.42 13.57 13.81 11.59 11.79470931017 Tennessee Knox 15.64 15.71 14.37 14.43 13.76 13.81 11.79 11.82470931020 Tennessee Knox 15.18 15.26 13.92 13.99 13.30 13.37 11.28 11.33470990002 Tennessee Lawrence 11.69 12.13 11.32 11.75 10.87 11.28 8.84 9.17471050108 Tennessee Loudon 15.49 15.72 14.26 14.47 13.69 13.89 11.80 11.97471071002 Tennessee McMinn 14.29 14.70 13.22 13.61 12.64 13.01 10.69 11.00471192007 Tennessee Maury 13.21 13.51 12.94 13.23 12.41 12.69 10.00 10.21471251009 Tennessee Montgomery 13.79 13.89 14.17 14.27 13.59 13.68 10.30 10.38471410001 Tennessee Putnam 13.37 13.37 12.76 12.76 12.20 12.20 9.74 9.74471450004 Tennessee Roane 14.49 14.77 13.32 13.58 12.75 13.01 10.74 10.95471570014 Tennessee Shelby 13.71 13.79 13.27 13.35 12.63 12.70 10.57 10.65471570038 Tennessee Shelby 13.43 13.57 13.00 13.14 12.36 12.49 10.31 10.39471570047 Tennessee Shelby 13.68 13.79 13.26 13.37 12.60 12.71 10.49 10.60471571004 Tennessee Shelby 12.04 12.08 11.75 11.79 11.16 11.20 9.10 9.15471631007 Tennessee Sullivan 14.16 14.46 12.95 13.23 12.47 12.74 10.44 10.66471650007 Tennessee Sumner 13.68 13.83 13.76 13.91 13.13 13.27 9.79 9.88480370004 Texas Bowie 12.85 12.95 12.30 12.39 12.03 12.11 10.93 11.00481130069 Texas Dallas 11.80 12.26 10.86 11.29 10.66 11.08 10.05 10.45481130087 Texas Dallas 11.15 11.61 10.21 10.63 10.02 10.43 9.40 9.79481350003 Texas Ector 7.78 7.99 7.44 7.64 7.38 7.57 7.12 7.31481410037 Texas El Paso 9.09 9.09 8.71 8.71 8.66 8.66 8.56 8.56482010058 Texas Harris 11.77 12.39 11.24 11.84 10.96 11.54 10.24 10.78482011035 Texas Harris 15.42 15.84 14.74 15.14 14.36 14.75 13.69 14.06482030002 Texas Harrison 11.69 11.79 11.05 11.14 10.82 10.90 9.72 9.80482150043 Texas Hidalgo 10.98 11.16 10.61 10.78 10.47 10.64 9.90 10.07482450021 Texas Jefferson 11.51 11.55 11.23 11.26 10.91 10.95 10.00 10.03483550032 Texas Nueces 10.42 10.87 9.99 10.42 9.66 10.08 8.90 9.29483611001 Texas Orange 11.51 11.72 11.19 11.40 10.92 11.12 9.97 10.16484391002 Texas Tarrant 11.41 11.79 10.51 10.86 10.31 10.66 9.70 10.03B-52Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues484391006 Texas Tarrant 12.23 12.81 11.28 11.81 11.07 11.60 10.46 10.96500010002 Vermont Addison 8.94 8.94 8.57 8.57 8.46 8.46 7.84 7.84500010003 Vermont Addison 8.91 8.91 8.54 8.54 8.43 8.43 7.82 7.82500030004 Vermont Bennington 8.52 9.00 8.10 8.55 7.99 8.43 7.29 7.69500070012 Vermont Chittenden 9.27 9.56 8.89 9.17 8.75 9.03 8.15 8.41500070014 Vermont Chittenden 10.02 10.02 9.61 9.61 9.46 9.46 8.84 8.84500210002 Vermont Rutland 11.08 11.13 10.58 10.63 10.43 10.48 9.82 9.86510130020 Virginia Arlington 14.27 14.62 13.07 13.40 12.87 13.20 11.01 11.30510360002 Virginia Charles 12.37 12.48 10.97 11.08 10.69 10.79 9.08 9.17510410003 Virginia Chesterfield 13.44 13.59 11.93 12.07 11.60 11.74 9.88 10.00510590030 Virginia Fairfax 13.33 13.59 12.18 12.43 11.97 12.22 10.15 10.37510591005 Virginia Fairfax 13.62 13.77 12.48 12.63 12.26 12.41 10.41 10.54510595001 Virginia Fairfax 13.88 14.12 12.79 13.02 12.56 12.79 10.70 10.90510870014 Virginia Henrico 13.51 13.83 11.98 12.27 11.66 11.94 9.91 10.15510870015 Virginia Henrico 12.93 12.99 11.64 11.70 11.30 11.36 9.45 9.50511071005 Virginia Loudoun 13.57 13.90 12.52 12.82 12.27 12.56 10.38 10.62511390004 Virginia Page 12.79 12.85 11.76 11.80 11.40 11.44 9.19 9.21515200006 Virginia Bristol City 13.93 14.00 12.61 12.66 12.09 12.14 9.95 9.99516500004 Virginia Hampton City 12.17 12.35 11.18 11.35 10.90 11.07 9.34 9.49516800015 Virginia Lynchburg City 12.84 13.00 11.60 11.74 11.22 11.36 9.31 9.42517100024 Virginia Norfolk City 12.78 13.01 11.81 12.02 11.52 11.73 9.93 10.11517700014 Virginia Roanoke City 14.27 14.48 12.97 13.17 12.50 12.70 10.40 10.57517750010 Virginia Salem City 14.69 14.69 13.42 13.42 12.96 12.96 10.91 10.91518100008 VirginiaVirginia BeachCity12.40 12.57 11.46 11.62 11.19 11.35 9.62 9.76540030003 West Virginia Berkeley 15.93 16.19 14.95 15.20 14.64 14.88 12.44 12.62540090005 West Virginia Brooke 16.52 16.80 14.95 15.22 14.51 14.76 12.02 12.24540090011 West Virginia Brooke 16.04 16.37 14.49 14.79 14.05 14.34 11.56 11.81540110006 West Virginia Cabell 16.30 16.57 15.25 15.50 14.65 14.89 12.09 12.28540291004 West Virginia Hancock 15.76 16.64 14.34 15.15 13.93 14.72 11.48 12.15B-53Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues540330003 West Virginia Harrison 13.99 14.19 13.82 14.02 13.30 13.49 9.94 10.08540390010 West Virginia Kanawha 15.15 15.38 14.01 14.22 13.45 13.65 10.77 10.92540390011 West Virginia Kanawha 13.17 13.17 12.23 12.23 11.74 11.74 9.24 9.24540391005 West Virginia Kanawha 16.52 16.59 15.28 15.34 14.69 14.75 11.97 12.03540490006 West Virginia Marion 15.03 15.25 14.96 15.18 14.41 14.62 10.79 10.94540511002 West Virginia Marshall 15.19 15.33 13.96 14.09 13.44 13.56 10.74 10.85540610003 West Virginia Monongalia 14.35 14.47 13.72 13.84 13.14 13.26 10.01 10.13540690010 West Virginia Ohio 14.58 14.58 13.18 13.18 12.72 12.72 10.15 10.15540810002 West Virginia Raleigh 12.90 13.03 11.88 12.00 11.40 11.51 9.01 9.09541071002 West Virginia Wood 15.40 15.44 14.31 14.35 13.77 13.81 11.40 11.43550030010 Wisconsin Ashland 6.076.21 5.85 5.98 5.74 5.87 5.46 5.58550090005 Wisconsin Brown 11.39 11.86 11.03 11.47 10.75 11.19 10.25 10.68550250047 Wisconsin Dane 12.20 12.65 11.80 12.23 11.52 11.94 10.61 11.01550270007 Wisconsin Dodge 11.04 11.26 10.61 10.82 10.24 10.45 9.49 9.69550410007 Wisconsin Forest 7.41 7.41 7.17 7.17 6.98 6.98 6.59 6.59550430009 Wisconsin Grant 11.79 12.24 11.34 11.76 10.99 11.41 10.20 10.59550590019 Wisconsin Kenosha 11.98 12.9311.72 12.65 11.22 12.11 10.17 10.99550710007 Wisconsin Manitowoc 10.20 10.89 9.92 10.58 9.63 10.27 9.06 9.66550790010 Wisconsin Milwaukee 13.32 13.94 12.98 13.57 12.48 13.06 11.51 12.06550790026 Wisconsin Milwaukee 12.88 13.83 12.52 13.44 12.05 12.94 11.10 11.92550790043 Wisconsin Milwaukee 14.08 14.62 13.71 14.24 13.20 13.71 12.22 12.70550790059 Wisconsin Milwaukee 13.68 14.87 13.33 14.48 12.83 13.94 11.88 12.91550790099 Wisconsin Milwaukee 13.54 14.40 13.18 14.02 12.70 13.51 11.75 12.50550870009 Wisconsin Outagamie 10.96 11.45 10.57 11.03 10.29 10.74 9.77 10.20550890009 Wisconsin Ozaukee 11.60 12.22 11.26 11.86 10.85 11.43 10.00 10.54551091002 Wisconsin St. Croix 10.09 10.09 9.63 9.63 9.42 9.42 9.01 9.01551110007 Wisconsin Sauk 10.22 10.57 9.81 10.14 9.49 9.81 8.75 9.05551198001 Wisconsin Taylor 8.24 8.43 7.91 8.10 7.74 7.92 7.33 7.50551250001 Wisconsin Vilas 6.78 6.87 6.54 6.64 6.39 6.48 6.04 6.12551330027 Wisconsin Waukesha 13.91 14.34 13.51 13.93 13.06 13.47 12.22 12.61B-54Annual PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues560050877 Wyoming Campbell 6.29 6.29 6.16 6.16 6.14 6.14 6.15 6.15560050892 Wyoming Campbell 5.00 5.04 4.91 4.95 4.92 4.96 4.92 4.96560050899 Wyoming Campbell 5.37 5.49 5.25 5.37 5.24 5.37 5.25 5.37560090819 Wyoming Converse 3.52 3.60 3.41 3.48 3.40 3.47 3.41 3.48560131003 Wyoming Fremont 8.17 8.50 7.89 8.21 7.84 8.15 7.85 8.16560210001 Wyoming Laramie 4.48 4.69 4.28 4.48 4.22 4.42 4.23 4.42560330002 Wyoming Sheridan 9.70 9.84 9.41 9.54 9.34 9.47 9.35 9.48B-5524-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues10030010 Alabama Baldwin 26.2 27.5 24.9 26.1 24.1 25.2 20.3 21.110270001 Alabama Clay 31.8 32.4 27.6 29.0 25.7 27.2 21.5 22.910331002 Alabama Colbert 30.4 30.4 28.0 28.7 26.5 27.3 19.7 21.110491003 Alabama DeKalb 32.0 32.6 27.2 27.8 25.3 25.7 21.2 21.510530002 Alabama Escambia 29.0 29.7 27.0 27.8 26.1 26.8 22.7 23.210550010 Alabama Etowah 35.1 35.7 29.4 29.5 27.8 27.8 23.2 23.310690003 Alabama Houston 28.6 28.6 26.3 26.3 25.3 25.3 22.7 22.710730023 Alabama Jefferson 44.0 44.2 40.0 40.7 38.8 39.6 35.6 36.810731005 Alabama Jefferson 34.8 35.5 31.3 31.8 29.8 30.2 25.7 26.010731009 Alabama Jefferson 34.5 34.9 31.5 32.5 29.9 31.2 25.0 26.510731010 Alabama Jefferson 34.1 34.3 29.1 29.3 27.6 27.8 22.9 23.210732003 Alabama Jefferson 40.3 40.8 38.1 38.9 37.2 37.9 34.4 35.010732006 Alabama Jefferson 33.1 34.1 29.8 30.4 28.5 28.9 23.7 24.110735002 Alabama Jefferson 33.0 34.8 29.4 30.7 27.6 28.9 22.2 24.010735003 Alabama Jefferson 35.8 36.5 32.1 33.2 30.5 31.8 25.1 26.110890014 Alabama Madison 33.5 34.1 30.3 30.5 28.4 28.6 21.7 22.410970002 Alabama Mobile 30.0 30.0 28.3 28.3 26.8 26.8 23.7 23.710970003 Alabama Mobile 28.5 29.4 27.2 27.9 25.8 26.5 22.5 23.110972005 Alabama Mobile 26.4 27.9 24.7 26.2 23.5 24.9 19.4 20.511010007 Alabama Montgomery 32.0 33.5 29.2 30.0 28.0 28.5 23.8 24.011030011 Alabama Morgan 31.5 31.9 27.8 28.2 25.9 26.2 19.1 19.611130001 Alabama Russell 35.5 36.9 32.8 33.8 31.4 32.3 28.4 29.411170006 Alabama Shelby 32.0 32.8 28.8 29.0 27.4 27.4 22.8 23.411190002 Alabama Sumter 28.9 28.9 26.6 26.6 25.1 25.1 20.7 20.711210002 Alabama Talladega 33.433.4 28.2 28.2 26.5 26.5 22.5 22.511250004 Alabama Tuscaloosa 29.8 30.1 27.3 28.1 26.2 27.1 22.2 23.311270002 Alabama Walker 32.8 33.3 27.7 29.7 26.3 28.8 22.3 24.750010011 Arkansas Arkansas 29.1 29.6 28.8 29.3 27.8 28.2 21.7 22.050030005 Arkansas Ashley 28.9 29.9 28.4 29.2 27.3 28.0 23.8 24.550350005 Arkansas Crittenden 35.0 35.0 34.3 34.3 32.7 32.7 22.3 22.3B-5624-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues50450002 Arkansas Faulkner 29.8 30.6 28.8 29.4 27.9 28.5 23.1 23.550510003 Arkansas Garland 29.2 29.3 28.9 29.0 27.9 28.0 21.8 21.950930007 Arkansas Mississippi 30.3 30.3 30.8 30.8 29.2 29.2 22.4 22.451070001 Arkansas Phillips 29.1 30.2 28.8 29.8 27.6 28.5 21.6 23.351130002 Arkansas Polk 26.1 27.7 25.3 26.8 24.3 25.5 19.1 19.251150003 Arkansas Pope 28.3 29.1 27.5 28.0 26.6 27.0 24.3 24.551190007 Arkansas Pulaski 31.1 31.4 30.8 31.3 29.8 30.4 24.8 25.151191004 Arkansas Pulaski 31.9 32.4 30.9 31.3 29.9 30.3 26.0 26.851191005 Arkansas Pulaski 31.9 32.3 31.1 31.4 30.0 30.4 26.4 26.851390006 Arkansas Union 28.7 29.6 27.9 28.3 26.8 27.1 23.2 23.751450001 Arkansas White 29.9 31.1 29.4 30.7 28.2 29.6 22.8 23.180010006 Colorado Adams 25.3 29.2 23.9 27.8 23.4 27.3 23.8 27.780050005 Colorado Arapahoe 21.2 22.2 20.2 21.1 19.8 20.7 19.8 20.780130003 Colorado Boulder 21.1 22.3 19.9 21.0 19.5 20.6 19.7 20.880130012 Colorado Boulder 18.7 19.7 17.5 18.5 17.2 18.1 17.2 18.280290004 Colorado Delta 20.7 22.3 18.7 20.1 18.2 19.5 18.1 19.580310002 Colorado Denver 26.4 27.6 25.6 26.7 25.3 26.4 25.7 26.880310023 Colorado Denver 26.3 26.3 25.6 25.6 25.2 25.2 25.7 25.780390001 Colorado Elbert 13.1 15.1 12.4 14.2 12.2 14.0 12.1 13.980410008 Colorado El Paso 16.4 16.7 15.3 15.5 15.0 15.2 15.0 15.280410011 Colorado El Paso 16.5 17.4 15.5 16.3 15.2 16.0 15.2 15.980690009 Colorado Larimer 18.3 18.8 17.1 17.6 16.9 17.4 16.9 17.580770017 Colorado Mesa 23.5 24.6 22.7 23.7 22.3 23.3 22.3 23.381010012 Colorado Pueblo 15.4 15.8 14.4 14.8 14.1 14.5 14.1 14.581130004 Colorado San Miguel 10.1 11.3 9.8 11.0 9.8 11.0 9.8 11.081230006 Colorado Weld 22.9 23.9 21.4 22.5 21.2 22.3 21.5 22.681230008 Colorado Weld 20.1 23.7 18.4 21.5 18.1 21.1 18.3 21.490010010 Connecticut Fairfield 36.2 37.3 32.9 33.4 32.2 32.6 29.8 30.990011123 Connecticut Fairfield 32.2 32.7 30.4 30.8 29.8 30.1 28.3 28.690013005 Connecticut Fairfield 34.9 35.6 32.8 33.1 32.2 32.4 29.4 29.9B-5724-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues90019003 Connecticut Fairfield 34.2 36.7 30.9 32.7 30.2 31.9 26.2 26.690031003 Connecticut Hartford 31.8 32.6 28.8 29.6 28.2 28.9 25.5 26.590050005 Connecticut Litchfield 27.1 27.1 23.6 23.6 23.0 23.0 18.1 18.190090026 Connecticut New Haven 35.6 37.9 32.3 33.7 31.6 32.8 28.3 29.090090027 Connecticut New Haven 35.5 36.0 32.9 33.0 32.2 32.3 30.2 30.290091123 Connecticut New Haven 38.3 40.3 35.7 36.6 34.9 35.8 32.3 32.790092008 Connecticut New Haven 33.6 36.4 30.9 32.5 30.2 31.7 26.5 27.190092123 Connecticut New Haven 34.4 34.7 31.2 32.0 30.5 31.3 28.6 29.890113002 Connecticut New London 32.0 34.4 28.4 29.8 27.7 29.1 24.4 25.4100010002 Delaware Kent 32.1 32.2 28.0 28.8 27.6 28.4 25.0 26.0100010003 Delaware Kent 31.5 32.4 27.1 28.2 26.6 27.9 23.9 25.8100031003 Delaware New Castle 33.5 34.3 30.0 30.8 29.6 30.3 27.3 28.1100031007 Delaware New Castle 32.6 34.5 28.2 29.8 27.9 29.5 26.0 27.1100031012 Delaware New Castle 32.4 33.5 28.3 29.3 27.9 28.9 26.6 27.5100032004 Delaware New Castle 36.6 36.7 34.1 34.2 33.7 33.7 31.7 32.1100051002 Delaware Sussex 33.7 34.3 29.6 30.0 29.1 29.6 26.7 27.6110010041District OfColumbiaDistrict ofColumbia 36.3 37.8 34.0 35.6 33.6 35.3 31.2 32.9110010042District OfColumbiaDistrict ofColumbia 34.9 37.0 33.0 35.6 32.7 35.5 30.5 33.2110010043District OfColumbiaDistrict ofColumbia 34.1 34.8 32.5 33.5 32.3 33.4 30.0 31.3120010023 Florida Alachua 23.4 27.6 21.0 24.7 20.3 23.8 17.2 20.5120010024 Florida Alachua 21.9 25.0 19.5 22.2 18.8 21.5 16.1 18.0120051004 Florida Bay 28.4 29.2 26.2 26.7 25.2 25.8 23.0 23.7120090007 Florida Brevard 20.7 22.0 18.2 19.4 17.7 18.8 16.4 17.4120111002 Florida Broward 18.8 20.3 17.5 18.7 16.9 18.1 15.9 17.1120112004 Florida Broward 19.1 20.3 18.2 19.0 17.6 18.5 16.9 17.6120113002 Florida Broward 18.4 18.4 16.8 16.8 16.3 16.3 15.4 15.4120170005 Florida Citrus 21.7 21.9 19.1 19.3 18.3 18.4 16.0 16.2120310098 Florida Duval 24.6 25.8 22.2 23.1 21.7 22.4 20.1 20.8B-5824-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues120310099 Florida Duval 25.2 26.7 24.0 25.3 23.6 24.9 22.9 24.0120330004 Florida Escambia 28.8 30.6 27.5 29.2 26.8 28.1 24.2 25.0120570030 Florida Hillsborough 23.624.0 21.5 22.1 20.8 21.3 20.2 20.7120573002 Florida Hillsborough 23.223.9 20.9 21.2 20.2 20.6 19.3 19.7120710005 Florida Lee 17.8 18.2 16.0 16.2 15.3 15.5 14.2 14.4120730012 Florida Leon 29.0 31.5 26.3 28.2 25.5 27.2 23.0 24.4120814012 Florida Manatee 19.9 20.2 16.2 16.6 15.7 16.0 14.4 14.6120830003 Florida Marion 23.2 24.1 20.8 21.3 20.1 20.7 18.1 18.4120861016 Florida Miami-Dade 19.4 19.5 18.6 18.7 18.2 18.3 17.5 17.5120866001 Florida Miami-Dade 19.0 19.3 17.5 17.7 16.8 17.1 15.4 15.7120951004 Florida Orange 21.7 21.8 19.1 19.3 18.4 18.6 17.3 17.6120952002 Florida Orange 21.6 22.5 18.9 19.5 18.1 18.7 17.0 17.6120990009 Florida Palm Beach 18.9 18.9 18.2 18.2 17.6 17.6 16.5 16.5120992005 Florida Palm Beach 18.2 18.4 16.7 17.1 16.2 16.5 15.2 15.7121030018 Florida Pinellas 21.9 23.0 20.0 20.6 19.5 20.0 18.9 19.2121031009 Florida Pinellas 21.2 22.0 18.1 18.8 17.8 18.4 16.8 17.4121056006 Florida Polk 19.5 19.9 17.7 18.2 17.0 17.5 16.0 16.5121111002 Florida St. Lucie 18.7 19.5 16.9 17.6 16.2 16.9 14.3 14.9121150013 Florida Sarasota 19.8 20.3 17.2 17.6 16.5 16.9 14.9 15.3121171002 Florida Seminole 22.8 23.0 19.2 19.4 18.2 18.5 16.3 16.5121275002 Florida Volusia 22.6 25.8 19.2 21.7 18.1 20.4 15.4 16.8130210007 Georgia Bibb 33.5 33.6 30.2 30.7 28.5 29.5 26.4 28.0130210012 Georgia Bibb 30.7 31.4 28.3 28.9 26.1 26.5 22.6 23.6130510017 Georgia Chatham 28.4 28.9 26.5 26.7 25.5 25.7 23.4 23.8130510091 Georgia Chatham 27.9 28.6 25.9 26.6 24.9 25.4 23.3 23.6130630091 Georgia Clayton 35.8 37.7 32.2 33.4 31.2 31.9 28.4 28.9130670003 Georgia Cobb 35.0 36.3 31.1 31.8 29.6 29.7 26.8 27.0130670004 Georgia Cobb 34.1 35.7 29.5 30.7 27.0 28.2 24.6 25.7130890002 Georgia DeKalb 33.4 33.7 29.2 29.7 28.0 28.5 25.9 26.2130892001 Georgia DeKalb 33.9 35.4 31.0 32.3 29.7 31.1 28.0 29.5B-5924-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues130950007 Georgia Dougherty 34.1 35.2 31.6 32.6 30.4 31.7 27.6 28.9131150005 Georgia Floyd 35.1 36.4 31.2 32.4 29.9 31.3 27.0 28.2131210032 Georgia Fulton 34.1 35.0 30.8 31.8 29.4 30.7 27.7 29.3131210039 Georgia Fulton 37.6 37.6 34.3 34.3 31.7 31.7 30.1 30.1131270006 Georgia Glynn 26.1 26.7 24.5 24.9 23.5 23.9 21.4 21.7131350002 Georgia Gwinnett 32.8 35.0 29.2 29.9 28.1 28.7 25.6 26.6131390003 Georgia Hall 30.6 31.7 29.1 29.3 26.4 26.9 24.8 25.6131530001 Georgia Houston 29.6 30.6 26.7 28.9 24.8 27.4 21.9 25.4131850003 Georgia Lowndes 25.9 26.3 23.8 25.1 22.9 24.4 20.8 22.5132150001 Georgia Muscogee 31.3 32.9 29.1 29.8 28.0 28.3 26.0 26.2132150008 Georgia Muscogee 34.5 37.6 30.3 32.3 28.5 30.0 25.4 25.8132150011 Georgia Muscogee 30.4 30.9 27.7 28.1 26.4 26.7 24.7 24.9132230003 Georgia Paulding 33.0 33.3 27.5 28.0 25.7 26.4 22.6 23.3132450005 Georgia Richmond 32.7 33.4 31.3 31.9 30.5 31.1 29.5 30.1132450091 Georgia Richmond 31.9 32.6 30.2 30.5 28.9 29.2 26.9 27.9132950002 Georgia Walker 30.9 32.5 27.2 28.7 25.8 27.2 22.9 24.2133030001 Georgia Washington 30.8 31.4 29.0 29.8 25.1 25.5 22.2 22.5133190001 Georgia Wilkinson 33.1 33.7 31.0 31.5 28.9 29.8 26.4 28.0170010006 Illinois Adams 31.4 32.3 30.8 32.0 29.2 30.2 25.5 25.8170190004 Illinois Champaign 31.332.5 29.7 31.1 28.6 30.2 23.4 26.5170191001 Illinois Champaign 30.031.7 28.9 30.3 27.8 29.0 24.2 26.4170310022 Illinois Cook 36.6 38.634.9 36.6 34.3 36.0 33.2 35.0170310050 Illinois Cook 36.1 38.034.1 35.8 32.3 33.9 30.3 32.2170310052 Illinois Cook 40.2 41.438.5 39.7 37.3 38.2 36.6 37.4170310057 Illinois Cook 37.3 38.635.7 37.0 34.4 35.6 31.2 32.3170310076 Illinois Cook 38.0 39.136.3 37.3 34.8 35.5 32.3 32.7170311016 Illinois Cook 43.0 46.341.0 44.1 39.4 42.5 37.7 41.2170312001 Illinois Cook 37.7 40.635.6 38.2 34.4 37.1 31.6 34.5170313103 Illinois Cook 39.6 40.338.1 38.7 37.3 37.9 35.9 36.5170313301 Illinois Cook 40.2 43.338.2 41.0 36.8 39.7 34.9 37.3B-6024-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues170314007 Illinois Cook 34.3 36.433.6 35.7 32.2 34.0 30.4 32.9170314201 Illinois Cook 32.0 33.831.1 32.9 29.2 31.3 28.1 29.6170316005 Illinois Cook 39.1 41.837.4 39.8 36.5 39.1 35.6 38.2170434002 Illinois DuPage 34.6 35.9 33.7 35.2 32.9 34.6 32.1 33.7170650002 Illinois Hamilton 31.6 31.6 32.1 32.1 30.2 30.2 21.9 21.9170831001 Illinois Jersey 32.1 33.2 33.5 34.7 30.7 31.9 25.5 25.6170890003 Illinois Kane 33.8 35.4 32.7 34.3 31.0 32.2 29.5 30.3170890007 Illinois Kane 34.8 34.8 33.6 33.6 32.1 32.1 31.1 31.1170971007 Illinois Lake 33.0 35.0 33.2 35.2 31.1 33.4 26.2 28.6170990007 Illinois La Salle 28.929.9 27.8 28.8 26.4 27.3 24.5 25.3171110001 Illinois McHenry 31.5 32.6 30.8 31.8 29.7 30.7 28.5 29.4171132003 Illinois McLean 33.4 33.4 32.6 32.6 30.7 30.7 25.3 25.3171150013 Illinois Macon 33.2 34.4 33.0 34.7 31.3 32.7 24.1 25.3171190023 Illinois Madison 37.3 38.1 39.4 40.2 36.6 37.4 32.2 33.5171191007 Illinois Madison 39.1 40.1 40.0 40.6 38.0 38.7 34.3 37.0171192009 Illinois Madison 34.9 35.9 37.2 38.2 35.4 36.1 28.6 29.3171193007 Illinois Madison 34.0 34.6 36.5 37.3 34.6 35.2 27.2 28.2171430037 Illinois Peoria 32.7 34.1 34.2 35.2 30.6 32.2 28.1 29.2171570001 Illinois Randolph 28.9 29.9 29.9 31.0 27.9 28.9 25.5 26.8171613002 Illinois Rock Island 30.931.4 29.8 30.4 28.7 29.2 27.6 28.5171630010 Illinois Saint Clair 33.734.1 35.3 35.9 32.8 33.4 29.4 30.1171634001 Illinois Saint Clair 32.232.9 34.3 35.1 31.5 32.2 28.3 28.6171670012 Illinois Sangamon 33.4 34.1 34.0 34.9 32.0 32.6 27.8 28.5171971002 Illinois Will 36.4 37.1 35.1 35.8 33.6 34.4 29.6 31.1171971011 Illinois Will 30.7 31.7 29.3 30.2 27.6 28.4 21.3 21.9172010013 Illinois Winnebago 34.7 34.7 33.7 33.7 31.9 31.9 30.4 30.4180030004 Indiana Allen 33.1 34.6 32.2 33.6 31.5 32.9 29.8 31.1180030014 Indiana Allen 31.0 32.1 30.1 31.2 29.5 30.5 27.2 28.6180190006 Indiana Clark 37.5 39.4 38.1 40.2 36.1 37.9 28.6 29.5180350006 Indiana Delaware 32.033.6 32.8 34.3 31.5 32.9 26.1 26.3B-6124-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues180372001 Indiana Dubois 35.3 36.9 36.5 38.0 35.3 36.8 27.9 30.6180390003 Indiana Elkhart 34.4 36.3 33.8 35.6 32.7 34.4 29.0 30.5180431004 Indiana Floyd 33.2 34.5 34.3 35.7 32.7 34.1 23.8 25.3180650003 Indiana Henry 31.8 31.8 33.1 33.1 32.0 32.0 26.1 26.1180670003 Indiana Howard 32.2 32.9 32.3 33.0 30.9 31.7 24.7 25.8180830004 Indiana Knox 35.9 36.3 35.9 36.5 34.8 35.1 28.8 30.5180890006 Indiana Lake 34.9 35.5 33.3 33.8 32.6 33.2 31.3 32.1180890022 Indiana Lake 38.9 44.0 37.3 42.1 36.4 41.1 35.3 39.8180890026 Indiana Lake 38.4 41.3 36.3 39.3 34.9 38.0 32.7 35.8180890027 Indiana Lake 32.6 34.2 31.2 32.8 30.3 32.0 29.0 30.8180890031 Indiana Lake 34.0 34.0 33.2 33.2 31.6 31.6 27.0 27.0180891003 Indiana Lake 32.7 33.5 31.4 32.1 30.6 31.5 29.5 30.3180892004 Indiana Lake 32.9 33.9 31.2 32.0 30.6 31.6 29.3 30.6180892010 Indiana Lake 34.2 35.6 32.8 34.0 31.9 33.2 29.0 31.0180910011 Indiana LaPorte 33.6 33.6 31.8 31.8 30.3 30.3 26.6 26.6180910012 Indiana LaPorte 30.6 31.8 29.2 30.0 28.1 28.9 25.7 27.2180950009 Indiana Madison 32.8 34.0 34.2 35.4 33.1 34.1 26.5 26.8180970042 Indiana Marion 34.2 35.3 36.3 37.2 34.5 35.4 28.6 30.4180970043 Indiana Marion 38.4 39.9 40.5 42.0 38.8 40.3 33.2 34.4180970066 Indiana Marion 38.3 39.6 40.3 41.8 38.7 40.0 31.9 33.1180970078 Indiana Marion 36.6 37.6 38.7 39.7 37.1 38.0 32.4 33.7180970079 Indiana Marion 35.6 36.7 37.2 38.3 35.5 36.6 28.6 28.9180970081 Indiana Marion 38.2 39.2 40.1 41.1 38.7 39.7 30.9 31.0180970083 Indiana Marion 36.6 37.0 39.0 39.3 37.3 37.7 29.0 29.4181270020 Indiana Porter 32.5 34.6 30.9 33.4 29.4 31.9 25.7 27.1181270024 Indiana Porter 31.8 32.4 30.3 31.2 29.1 29.7 27.0 27.4181410014 Indiana St. Joseph 32.4 33.9 31.5 33.1 30.8 32.4 28.0 29.6181411008 Indiana St. Joseph 33.1 33.1 31.3 31.3 30.4 30.4 29.0 29.0181412004 Indiana St. Joseph 30.0 31.4 28.6 29.7 28.0 29.3 26.6 28.3181470009 Indiana Spencer 32.3 33.1 34.0 35.3 32.5 33.8 25.3 25.9B-6224-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues181570008 Indiana Tippecanoe 35.636.7 35.9 36.9 34.4 35.3 29.5 29.9181630006 Indiana Vanderburgh 34.8 35.5 34.3 35.0 33.3 33.9 27.0 27.7181630012 Indiana Vanderburgh 33.2 34.4 33.5 34.7 32.5 33.6 26.4 27.2181630016 Indiana Vanderburgh 32.6 33.7 32.2 33.5 31.2 32.3 27.8 28.9181670018 Indiana Vigo 35.1 35.1 35.3 35.3 33.9 33.9 32.9 32.9181670023 Indiana Vigo 34.8 36.1 35.1 36.5 33.7 35.0 30.8 32.1190130008 Iowa Black Hawk 30.1 30.2 28.3 28.4 27.8 28.0 27.0 27.3190450021 Iowa Clinton 33.9 35.9 33.4 35.1 31.1 32.8 30.3 31.6191032001 Iowa Johnson 34.6 35.2 33.2 33.9 32.6 33.2 31.1 32.7191130037 Iowa Linn 30.6 33.3 30.3 32.7 28.7 31.3 27.7 30.0191370002 Iowa Montgomery 27.5 27.7 26.1 26.4 25.2 25.3 22.5 23.2191390015 Iowa Muscatine 36.0 37.7 34.5 36.0 33.8 35.4 32.1 33.2191471002 Iowa Palo Alto 25.7 25.7 25.1 25.1 24.1 24.1 20.9 20.9191530030 Iowa Polk 28.4 29.0 27.5 27.8 26.6 27.1 24.4 25.1191532510 Iowa Polk 27.2 29.5 26.0 27.7 25.1 26.9 22.6 25.0191532520 Iowa Polk 31.4 31.4 29.1 29.1 28.6 28.6 26.9 26.9191550009 Iowa Pottawattamie 28.6 28.9 27.0 27.3 26.5 26.8 24.6 25.0191630015 Iowa Scott 31.0 32.1 30.3 31.6 29.2 29.7 28.7 29.3191630018 Iowa Scott 32.3 33.3 31.3 32.1 30.2 31.3 29.6 30.8191630019 Iowa Scott 37.1 37.1 36.8 36.8 34.0 34.0 31.9 31.9191770006 Iowa Van Buren 28.3 28.3 26.9 26.9 25.9 25.9 24.5 24.5191930017 Iowa Woodbury 26.4 28.4 24.6 26.2 24.3 26.1 23.2 25.1191970004 Iowa Wright 28.6 28.8 27.1 27.2 26.1 26.3 24.2 24.5200910007 Kansas Johnson 25.3 26.524.8 25.5 23.8 24.7 22.1 23.0200910009 Kansas Johnson 29.3 29.328.0 28.0 27.0 27.0 26.0 26.0200910010 Kansas Johnson 23.5 23.622.6 22.6 21.5 21.6 19.7 19.8201070002 Kansas Linn 25.3 26.2 24.8 25.6 23.8 24.4 21.1 21.5201730008 Kansas Sedgwick 23.7 25.3 23.3 24.9 22.0 23.5 20.0 21.4201730009 Kansas Sedgwick 25.0 26.4 23.2 24.3 22.7 24.0 22.4 23.7201730010 Kansas Sedgwick 25.3 27.0 24.1 25.6 23.3 24.8 22.7 24.1B-6324-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues201770010 Kansas Shawnee 29.1 29.1 28.1 28.1 26.7 26.7 25.1 25.1201770011 Kansas Shawnee 29.1 29.1 28.0 28.0 26.7 26.7 24.2 24.2201910002 Kansas Sumner 22.8 23.7 21.9 22.7 20.8 21.6 19.4 20.2202090021 Kansas Wyandotte 29.5 32.1 28.4 31.0 27.6 30.1 25.4 27.3202090022 Kansas Wyandotte 26.6 28.6 25.8 27.5 25.1 26.8 23.3 25.4210130002 Kentucky Bell 29.5 31.0 27.2 28.4 25.6 26.5 21.3 21.8210190017 Kentucky Boyd 33.1 34.4 30.7 31.9 29.1 30.3 20.5 21.3210290006 Kentucky Bullitt 34.6 35.8 35.0 36.3 33.1 34.2 24.0 24.6210370003 Kentucky Campbell 31.2 31.2 31.1 31.1 29.9 29.9 25.8 25.8210430500 Kentucky Carter 29.9 31.2 27.1 28.3 25.5 26.6 17.3 18.6210470006 Kentucky Christian 33.633.6 33.4 33.4 31.8 31.8 20.7 20.7210590005 Kentucky Daviess 33.8 33.8 37.0 37.0 34.9 34.9 21.7 21.7210670012 Kentucky Fayette 31.9 33.2 31.6 32.8 29.6 30.7 23.7 24.8210670014 Kentucky Fayette 32.7 33.2 32.5 33.0 30.4 30.8 23.8 24.6210730006 Kentucky Franklin 32.1 33.8 32.9 34.8 30.9 32.6 22.4 23.9210930006 Kentucky Hardin 32.8 35.1 33.0 35.4 31.2 33.5 20.4 22.9211010014 Kentucky Henderson 31.832.7 30.6 31.3 29.7 30.5 23.5 24.5211110043 Kentucky Jefferson 35.436.1 35.8 36.4 34.3 34.8 27.2 29.4211110044 Kentucky Jefferson 36.136.6 36.0 36.5 34.3 34.7 27.6 28.5211110048 Kentucky Jefferson 36.437.2 35.6 36.4 34.0 34.8 26.3 27.0211110051 Kentucky Jefferson 32.433.8 32.3 33.8 30.8 32.2 20.7 20.9211170007 Kentucky Kenton 34.7 35.4 34.7 35.3 33.4 34.0 25.3 25.7211250004 Kentucky Laurel 25.1 25.1 22.5 22.5 21.2 21.2 16.7 16.7211451004 Kentucky McCracken 33.6 35.9 34.4 36.8 32.5 34.8 23.1 23.6211510003 Kentucky Madison 30.130.9 27.3 27.8 25.6 26.3 19.5 21.5211930003 Kentucky Perry 28.5 29.8 25.3 26.4 23.7 24.7 17.7 18.5211950002 Kentucky Pike 30.5 31.4 27.3 28.1 25.9 26.7 19.2 20.2212270007 Kentucky Warren 33.1 35.1 33.7 36.3 31.6 34.0 21.6 24.2220171002 Louisiana Caddo 27.5 27.5 25.9 25.9 24.8 24.8 22.3 22.3220190009 Louisiana Calcasieu 24.225.8 23.9 25.5 23.1 24.7 19.9 21.4B-6424-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues220190010 Louisiana Calcasieu 26.327.2 25.8 26.6 24.9 25.7 21.3 22.1220290003 Louisiana Concordia 26.1 26.1 25.9 25.9 24.9 24.9 20.1 20.1220330009 LouisianaEast BatonRouge 29.3 30.5 27.8 28.8 26.5 27.6 25.0 26.1220331001 LouisianaEast BatonRouge 25.4 26.1 24.3 24.8 23.2 23.6 21.1 21.6220470005 Louisiana Iberville 28.6 29.3 27.1 27.7 25.5 26.1 24.9 25.7220470009 Louisiana Iberville 26.1 27.8 25.0 26.3 23.8 25.0 20.3 21.3220511001 Louisiana Jefferson 27.0 27.9 26.1 27.0 24.9 25.8 21.9 22.7220550006 Louisiana Lafayette 24.2 24.4 23.8 23.8 22.5 22.6 18.1 18.2220730004 Louisiana Ouachita 28.9 30.6 28.3 29.9 27.4 28.9 23.0 24.0220790002 Louisiana Rapides 30.2 34.3 29.8 33.8 28.5 32.4 22.8 25.9221050001 Louisiana Tangipahoa 29.6 30.3 27.7 28.1 26.2 26.7 23.5 24.6221090001 Louisiana Terrebonne 26.2 26.4 25.1 25.6 23.7 24.2 19.7 19.9221210001 LouisianaWest BatonRouge 29.0 29.8 27.5 28.2 26.3 27.0 25.0 26.0230010011 Maine Androscoggin 26.5 29.0 24.9 26.9 24.5 26.6 23.7 25.4230030013 Maine Aroostook 24.2 25.4 23.4 24.6 23.0 24.2 22.5 23.8230031011 Maine Aroostook 22.9 24.3 21.7 23.1 21.3 22.7 20.5 22.2230050015 Maine Cumberland 27.7 30.1 25.2 27.9 24.7 27.2 23.8 26.3230050027 Maine Cumberland 29.2 31.1 26.7 28.4 26.0 27.7 25.2 26.8230090103 Maine Hancock 19.4 19.7 15.9 16.1 15.8 16.0 13.9 14.0230110016 Maine Kennebec 26.2 28.1 24.4 26.2 23.9 25.6 23.0 24.6230172011 Maine Oxford 28.3 30.4 26.4 27.7 25.9 27.2 24.8 26.0230190002 Maine Penobscot 22.0 24.3 19.9 22.1 19.5 21.6 18.4 20.4240030014 Maryland Anne Arundel 33.233.2 29.6 29.6 29.6 29.6 27.1 27.1240031003 Maryland Anne Arundel 35.537.4 33.8 36.7 34.4 37.5 32.9 36.1240032002 Maryland Anne Arundel 36.136.1 33.7 33.7 33.9 33.9 32.3 32.3240051007 Maryland Baltimore 33.3 34.1 31.2 32.1 31.0 32.0 28.4 29.9240053001 Maryland Baltimore 35.8 37.0 33.0 33.8 33.0 33.9 31.1 31.9240150003 Maryland Cecil 30.8 32.5 28.0 29.5 27.7 29.1 25.1 25.9B-6524-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues240251001 Maryland Harford 31.2 31.4 26.3 26.4 26.1 26.2 23.4 23.8240313001 Maryland Montgomery 30.9 31.8 27.8 28.5 27.3 27.9 24.3 24.9240330030 Maryland Prince George's 31.7 31.7 28.7 28.7 28.3 28.3 23.8 23.8240338003 Maryland Prince George's 33.4 34.6 29.6 30.3 29.5 30.3 25.5 26.0240430009 Maryland Washington 33.4 35.5 32.2 34.5 31.5 33.7 27.6 28.9245100006 Maryland Baltimore (City)33.3 33.8 30.5 30.8 30.5 30.7 28.6 29.0245100007 Maryland Baltimore (City)34.7 36.1 31.0 31.7 30.8 31.2 28.6 29.1245100008 Maryland Baltimore (City)37.2 37.3 34.6 34.8 34.5 34.7 33.2 33.6245100035 Maryland Baltimore (City)37.7 39.2 34.7 35.5 34.5 35.3 33.4 34.2245100040 Maryland Baltimore (City)39.0 40.9 36.3 38.3 36.1 38.0 35.0 36.8245100049 Maryland Baltimore (City)38.1 38.1 35.5 35.5 35.3 35.3 34.3 34.3250035001 Massachusetts Berkshire 31.0 33.5 29.4 31.7 28.9 31.2 27.5 29.6250051004 Massachusetts Bristol 25.0 26.8 21.6 22.5 21.5 22.4 19.5 20.2250092006 Massachusetts Essex 28.7 33.4 26.0 30.4 25.6 30.0 23.9 27.6250095005 Massachusetts Essex 27.7 29.6 24.0 25.5 23.6 25.0 20.6 22.1250096001 Massachusetts Essex 27.8 27.9 25.3 25.7 24.9 25.2 23.1 23.5250130008 Massachusetts Hampden 27.4 27.9 25.0 25.4 24.5 24.9 22.6 23.1250130016 Massachusetts Hampden 32.3 33.5 30.5 31.6 29.8 30.9 28.3 29.2250132009 Massachusetts Hampden 33.1 33.3 31.1 31.5 30.3 30.8 29.0 29.4250230004 Massachusetts Plymouth 28.4 28.8 24.0 24.5 23.6 24.0 21.1 22.1250250002 Massachusetts Suffolk 29.4 29.7 27.3 27.7 27.0 27.4 26.2 26.7250250027 Massachusetts Suffolk 29.2 29.5 26.9 27.0 26.7 26.8 25.8 25.9250250042 Massachusetts Suffolk 28.6 29.1 26.3 26.8 25.9 26.3 25.3 25.8250250043 Massachusetts Suffolk 32.1 33.9 29.6 31.3 29.2 30.9 28.4 30.0250270016 Massachusetts Worcester 30.0 30.0 26.9 27.1 26.3 26.5 24.0 24.5250270023 Massachusetts Worcester 30.5 30.6 27.2 27.3 26.5 26.7 25.1 25.2260050003 Michigan Allegan 33.8 34.0 32.3 32.9 31.1 31.4 29.6 30.0260170014 Michigan Bay 31.6 32.1 30.2 30.7 29.2 29.8 27.3 28.1260210014 Michigan Berrien 31.3 32.3 29.7 30.4 28.7 29.4 26.0 27.0260490021 Michigan Genesee 30.4 32.0 28.7 30.1 28.0 29.5 27.0 28.3B-6624-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues260650012 Michigan Ingham 31.9 32.1 30.6 31.0 29.7 30.0 28.2 28.8260770008 Michigan Kalamazoo 31.1 32.8 29.5 31.1 28.7 30.3 26.4 27.8260810020 Michigan Kent 36.5 37.1 34.1 34.7 32.7 33.2 30.6 31.1260990009 Michigan Macomb 35.3 35.9 33.8 34.2 33.0 33.5 31.6 32.7261130001 Michigan Missaukee 24.8 25.2 24.1 24.4 22.6 22.8 19.8 19.9261150005 Michigan Monroe 38.8 39.6 37.0 38.0 35.6 36.3 31.2 31.6261210040 Michigan Muskegon 34.7 36.6 32.9 34.7 31.3 32.9 28.5 29.4261250001 Michigan Oakland 39.9 40.4 37.9 38.4 36.9 37.2 35.1 36.2261390005 Michigan Ottawa 34.2 34.7 32.7 33.3 31.9 32.3 30.7 31.2261450018 Michigan Saginaw 30.6 30.6 29.3 29.3 28.2 28.2 26.0 26.0261470005 Michigan St. Clair 39.6 40.6 38.4 39.4 37.6 38.7 34.7 35.4261610005 Michigan Washtenaw 33.6 33.6 32.0 32.0 30.7 30.7 28.0 28.0261610008 Michigan Washtenaw 39.4 40.8 38.1 39.8 37.0 38.7 35.6 36.2261630001 Michigan Wayne 37.8 40.1 35.4 37.8 34.2 36.3 32.8 34.9261630015 Michigan Wayne 40.1 40.6 38.5 39.1 37.1 37.6 34.0 34.7261630016 Michigan Wayne 42.9 45.4 40.6 43.0 39.7 42.1 38.2 40.8261630019 Michigan Wayne 40.9 41.4 38.6 39.1 37.7 38.3 37.0 37.5261630025 Michigan Wayne 35.1 36.8 33.1 34.6 31.9 33.1 29.5 30.5261630033 Michigan Wayne 43.8 44.2 42.1 42.6 41.1 41.7 39.1 39.4261630036 Michigan Wayne 37.1 37.9 36.3 36.9 35.5 36.2 34.4 35.5261630039 Michigan Wayne 37.0 37.0 35.0 35.0 34.2 34.2 32.6 32.6270210001 Minnesota Cass 18.0 19.1 17.0 18.0 16.5 17.5 15.5 16.5270370470 Minnesota Dakota 25.4 25.6 24.6 24.9 23.5 23.7 22.0 22.2270530050 Minnesota Hennepin 27.2 28.0 25.7 26.4 24.9 25.7 23.1 23.8270530961 Minnesota Hennepin 25.5 26.2 24.1 24.7 23.6 24.1 22.4 22.9270530963 Minnesota Hennepin 26.0 27.8 24.6 26.2 23.8 25.5 22.4 24.0270530965 Minnesota Hennepin 24.7 25.5 23.0 23.8 22.6 23.4 21.7 22.5270531007 Minnesota Hennepin 25.4 25.7 24.1 24.4 23.4 23.7 22.1 22.4270532006 Minnesota Hennepin 26.7 27.5 25.5 26.3 24.8 25.4 23.2 23.9270953051 Minnesota Mille Lacs 22.0 22.2 21.4 21.8 20.9 21.2 19.4 19.6B-6724-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues271230866 Minnesota Ramsey 28.0 29.4 26.7 28.0 26.3 27.6 25.3 26.6271230868 Minnesota Ramsey 28.3 30.5 27.0 29.0 26.2 28.2 24.6 26.7271230871 Minnesota Ramsey 26.3 26.8 25.2 25.9 24.2 24.8 22.9 23.5271377001 Minnesota Saint Louis 20.3 21.2 19.4 20.3 18.7 19.6 17.6 18.6271377550 Minnesota Saint Louis 19.5 20.1 18.9 19.3 18.0 18.3 16.3 16.6271377551 Minnesota Saint Louis 23.5 23.8 22.0 22.1 21.3 21.4 19.4 19.5271390505 Minnesota Scott 24.9 25.8 23.9 24.6 23.2 24.0 21.5 22.7271453052 Minnesota Stearns 20.9 20.9 19.6 19.6 19.0 19.0 18.3 18.3280010004 Mississippi Adams 27.4 27.8 27.0 27.3 25.8 26.2 19.9 20.3280110001 Mississippi Bolivar 28.9 29.9 28.8 29.6 27.5 28.4 22.0 23.0280330002 Mississippi DeSoto 30.8 31.3 29.7 29.8 28.0 28.1 20.5 21.7280350004 Mississippi Forrest 30.4 31.1 29.0 29.4 27.9 28.2 24.9 25.5280470008 Mississippi Harrison 30.5 31.5 29.1 29.8 27.7 28.4 23.6 24.2280490010 Mississippi Hinds 28.8 29.1 27.1 27.2 26.0 26.0 21.1 21.2280590006 Mississippi Jackson 28.2 29.4 26.7 27.8 25.3 26.3 21.8 22.7280670002 Mississippi Jones 31.2 31.6 29.9 30.6 28.9 29.6 25.3 26.0280750003 Mississippi Lauderdale 29.8 29.8 29.6 29.9 28.3 28.5 22.8 23.0280810005 Mississippi Lee 32.1 33.4 30.0 31.0 28.3 29.2 21.9 22.5280870001 Mississippi Lowndes 32.4 33.0 28.6 29.1 26.9 27.7 21.7 22.9281090001 Mississippi Pearl River 28.5 28.5 27.1 27.1 25.9 25.9 22.6 22.6281490004 Mississippi Warren 30.2 30.2 29.9 29.9 28.8 28.8 23.0 23.0290190004 Missouri Boone 30.2 30.2 29.9 29.9 28.5 28.5 25.3 25.3290210005 Missouri Buchanan 30.1 30.1 28.6 28.6 27.7 27.7 25.5 25.5290370003 Missouri Cass 25.6 26.1 25.0 25.5 24.1 24.6 21.3 21.5290390001 Missouri Cedar 28.7 28.7 28.5 28.5 27.0 27.0 22.4 22.4290470005 Missouri Clay 28.0 28.6 26.7 27.3 25.7 26.3 24.6 25.5290770032 Missouri Greene 28.2 29.4 29.1 30.2 26.9 28.0 22.1 22.9290950034 Missouri Jackson 28.9 30.9 27.4 29.3 26.7 28.6 24.9 26.6290990012 Missouri Jefferson 33.4 34.2 35.7 36.5 32.6 33.6 29.7 30.2291370001 Missouri Monroe 27.8 27.8 26.9 26.9 25.6 25.6 22.7 22.7B-6824-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues291831002 Missouri Saint Charles 33.1 34.7 35.5 37.1 33.6 35.3 28.6 29.9291860006 Missouri Sainte Genevieve31.4 32.0 32.1 33.1 29.7 30.6 25.3 26.9291890004 Missouri Saint Louis 32.0 32.0 34.3 34.3 31.7 31.7 26.0 26.0291892003 Missouri Saint Louis 33.2 33.8 33.7 34.4 32.3 33.1 31.0 31.6295100007 Missouri St. Louis City 33.1 33.5 36.0 36.3 33.3 33.6 29.1 30.2295100085 Missouri St. Louis City 33.2 33.8 35.3 35.7 32.9 33.3 29.8 30.4295100086 Missouri St. Louis City 32.5 32.6 34.3 34.5 32.0 32.2 29.4 29.5295100087 Missouri St. Louis City 34.3 34.7 36.4 36.9 33.7 34.1 30.8 31.3300870307 Montana Rosebud 19.7 19.7 19.2 19.2 19.1 19.1 19.1 19.1301111065 Montana Yellowstone 19.3 19.4 18.6 18.8 18.5 18.8 18.5 18.8310550019 Nebraska Douglas 26.6 28.8 26.1 28.6 25.5 27.9 23.1 24.8310550052 Nebraska Douglas 25.7 26.8 24.4 25.4 24.0 24.9 22.3 23.4310790004 Nebraska Hall 19.1 19.1 17.7 17.7 17.2 17.2 16.3 16.3311090022 Nebraska Lancaster 24.7 26.6 23.3 25.0 22.9 24.7 21.7 23.8311111002 Nebraska Lincoln 23.7 23.7 21.9 21.9 21.6 21.6 21.2 21.2311530007 Nebraska Sarpy 24.1 24.4 23.9 24.2 23.3 23.6 21.0 21.2311570003 Nebraska Scotts Bluff 16.6 16.6 15.9 15.9 15.7 15.7 15.3 15.3311770002 Nebraska Washington 24.1 24.8 23.2 24.1 22.7 23.5 21.0 21.6330012004 New Hampshire Belknap 20.5 21.4 17.6 18.3 17.1 17.8 14.4 14.9330050007 New Hampshire Cheshire 30.2 31.0 28.2 28.7 27.7 28.1 26.4 26.8330070014 New Hampshire Coos 26.5 26.9 24.7 25.1 24.2 24.6 22.3 22.6330090010 New Hampshire Grafton 23.0 23.0 20.3 20.3 19.8 19.8 18.1 18.1330110020 New Hampshire Hillsborough 28.6 28.6 26.5 26.5 26.1 26.1 25.2 25.2330111015 New Hampshire Hillsborough 27.3 27.3 25.7 25.7 25.3 25.3 24.5 24.5330115001 New Hampshire Hillsborough 25.9 25.9 22.4 22.4 21.9 21.9 17.1 17.1330131006 New Hampshire Merrimack 25.6 26.1 22.9 23.1 22.5 22.7 20.4 20.7330150014 New Hampshire Rockingham 26.3 27.8 23.6 24.9 23.2 24.5 21.9 22.9330190003 New Hampshire Sullivan 28.9 30.8 24.8 26.8 24.1 26.0 21.0 22.8340030003 New Jersey Bergen 37.0 37.7 33.6 34.1 33.0 33.5 31.5 32.1340070003 New Jersey Camden 36.5 38.6 32.7 34.3 31.9 33.6 27.2 28.9B-6924-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues340071007 New Jersey Camden 37.3 38.8 34.1 35.1 33.3 34.3 30.0 31.0340130015 New Jersey Essex 38.3 38.4 33.9 34.4 33.1 33.7 30.3 31.8340155001 New Jersey Gloucester 32.1 32.1 28.2 28.2 27.7 27.7 25.1 25.1340171003 New Jersey Hudson 39.0 40.5 35.7 36.1 34.9 35.3 32.9 33.9340172002 New Jersey Hudson 41.4 41.4 38.2 38.2 37.5 37.5 36.6 36.6340210008 New Jersey Mercer 34.7 35.8 30.9 31.4 30.2 30.5 26.0 26.6340218001 New Jersey Mercer 30.1 30.1 26.3 26.3 25.6 25.6 21.0 21.0340230006 New Jersey Middlesex 34.8 38.1 31.0 34.0 30.3 33.2 26.1 27.2340270004 New Jersey Morris 32.3 33.6 29.2 30.3 28.6 29.5 25.2 26.5340273001 New Jersey Morris 31.5 32.9 27.8 29.1 27.0 28.2 21.2 21.3340292002 New Jersey Ocean 31.533.9 28.0 29.7 27.2 28.9 20.8 22.0340310005 New Jersey Passaic 36.3 37.1 32.6 33.5 31.9 32.9 28.1 29.5340390004 New Jersey Union 40.4 41.4 36.7 37.2 35.6 36.2 33.9 34.8340390006 New Jersey Union 37.3 37.7 34.8 35.1 34.2 34.4 33.2 33.5340392003 New Jersey Union 36.8 37.4 33.7 34.1 32.8 33.2 30.5 31.7340410006 New Jersey Warren 34.0 34.7 32.0 32.8 31.6 32.3 29.1 30.3350010023 New Mexico Bernalillo 18.6 18.8 17.6 17.8 17.4 17.7 17.1 17.3350010024 New Mexico Bernalillo 16.4 17.1 15.5 16.3 15.4 16.1 15.0 15.8350050005 New Mexico Chaves 15.6 16.5 14.9 15.6 14.7 15.3 14.0 14.3350130017 New Mexico Dona Ana 32.9 35.5 31.1 33.5 30.8 33.2 30.5 32.9350130025 New Mexico Dona Ana 13.8 14.1 13.1 13.5 12.9 13.3 12.3 12.8350431003 New Mexico Sandoval 10.3 10.9 9.6 10.2 9.5 10.0 9.2 9.7350439011 New Mexico Sandoval 15.6 16.2 15.2 15.8 15.0 15.7 14.9 15.5350450006 New Mexico San Juan 12.4 12.6 12.1 12.3 12.0 12.2 12.0 12.2350490020 New Mexico Santa Fe 9.7 10.2 9.4 9.8 9.3 9.7 9.2 9.6360010005 New York Albany 34.2 34.2 32.9 32.9 32.4 32.4 30.9 30.9360050080 New York Bronx 38.8 40.2 35.9 36.2 35.2 35.4 33.5 33.9360050083 New York Bronx 34.7 35.3 32.1 32.9 31.5 32.3 30.3 31.1360050110 New York Bronx 36.1 36.6 33.6 34.6 33.1 34.0 32.3 33.2360130011 New York Chautauqua 29.1 30.1 26.9 27.7 25.7 26.5 20.8 21.5B-7024-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues360290005 New York Erie 35.3 37.0 33.1 34.8 32.8 34.3 31.8 33.4360291007 New York Erie 33.6 35.2 31.9 33.8 31.5 33.5 30.0 32.4360310003 New York Essex 22.4 22.8 21.0 21.3 20.4 20.6 17.3 17.6360470122 New York Kings 36.9 38.0 33.5 34.3 32.6 33.4 30.7 30.8360551007 New York Monroe 32.2 33.0 30.4 31.2 29.9 30.6 27.4 28.1360590008 New York Nassau 34.0 35.0 30.4 31.0 29.4 29.9 25.4 25.5360610056 New York New York 39.7 40.6 37.1 38.0 36.5 37.3 35.3 36.0360610062 New York New York 38.8 41.6 35.3 37.0 34.6 36.3 33.2 33.6360610079 New York New York 37.9 40.2 34.2 36.4 33.4 35.4 31.4 33.3360610128 New York New York 39.4 41.8 36.2 38.0 35.4 37.0 33.0 33.1360632008 New York Niagara 33.6 33.7 31.7 31.9 30.5 30.7 28.5 28.5360671015 New York Onondaga 27.3 28.5 25.4 26.2 24.8 25.4 20.2 21.2360710002 New York Orange 28.9 29.4 26.3 26.9 25.7 26.3 23.2 23.8360810124 New York Queens 35.5 35.5 33.0 33.0 32.2 32.2 31.1 31.1360850055 New York Richmond 34.9 37.0 32.0 34.3 31.2 33.3 29.5 31.2360850067 New York Richmond 32.1 32.9 28.8 29.5 27.9 28.5 25.0 25.5360893001 New York St. Lawrence 22.1 22.5 20.7 21.3 20.2 20.9 18.6 19.7361010003 New York Steuben 27.8 28.2 25.2 25.6 24.6 25.0 20.1 21.1361030001 New York Suffolk 34.6 34.6 30.5 30.5 29.4 29.4 23.9 23.9361191002 New York Westchester 33.5 34.3 30.4 30.8 29.7 29.9 26.4 26.9370010002 North Carolina Alamance 31.7 32.1 27.0 27.5 26.2 26.7 21.8 22.2370210034 North Carolina Buncombe 30.0 30.2 26.1 26.5 25.4 25.8 20.4 21.2370330001 North Carolina Caswell 29.4 29.5 25.8 26.1 24.9 25.2 19.9 20.1370350004 North Carolina Catawba 34.5 35.5 27.5 28.1 26.9 27.5 23.1 23.2370370004 North Carolina Chatham 26.9 27.4 24.1 24.8 23.1 23.8 19.8 20.5370510009 North Carolina Cumberland 30.7 31.2 27.7 28.4 26.6 27.3 24.0 24.6370570002 North Carolina Davidson 31.3 32.1 27.0 27.4 26.3 26.7 23.0 23.4370610002 North Carolina Duplin 28.3 29.6 25.0 26.1 24.2 25.4 20.6 21.6370630001 North Carolina Durham 31.0 32.0 26.3 26.7 25.3 25.7 22.3 22.5370650004 North Carolina Edgecombe 26.7 26.9 24.8 24.9 23.8 23.9 21.3 21.9B-7124-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues370670022 North Carolina Forsyth 31.9 32.2 28.1 28.4 27.2 27.5 25.4 25.7370710016 North Carolina Gaston 30.8 30.9 24.3 24.5 23.8 23.9 20.1 20.4370810013 North Carolina Guilford 30.6 30.6 27.2 27.2 26.2 26.2 23.4 23.4370870010 North Carolina Haywood 27.7 28.5 24.6 25.3 23.5 24.0 20.8 21.2370990006 North Carolina Jackson 25.526.8 22.1 22.9 20.5 21.4 17.2 18.2371070004 North Carolina Lenoir 25.2 25.5 22.6 23.1 21.9 22.4 20.2 20.6371110004 North Carolina McDowell 31.5 32.0 26.0 26.5 25.1 25.6 21.5 21.8371170001 North Carolina Martin 24.8 26.2 23.2 24.1 22.4 23.3 20.6 21.5371190010 North Carolina Mecklenburg 32.3 32.3 28.2 28.2 27.5 27.5 24.7 24.7371190041 North Carolina Mecklenburg 31.7 32.1 26.7 27.2 25.9 26.4 23.1 23.3371190042 North Carolina Mecklenburg 30.7 31.4 24.9 25.7 24.0 24.7 21.6 22.3371210001 North Carolina Mitchell 30.2 31.6 25.3 27.1 24.3 26.0 20.6 22.0371230001 North Carolina Montgomery 28.2 29.0 24.5 25.1 23.6 24.2 19.6 20.1371290002 North Carolina New Hanover 24.0 25.4 21.2 22.4 20.5 21.6 17.5 18.3371330005 North Carolina Onslow 24.6 25.1 22.6 23.1 21.9 22.3 19.4 19.8371350007 North Carolina Orange 29.3 29.8 25.1 25.6 24.1 24.5 19.9 20.3371470005 North Carolina Pitt 26.226.9 23.9 24.3 23.1 23.6 21.8 22.2371550005 North Carolina Robeson 29.9 30.4 26.1 26.2 25.2 25.4 20.9 21.1371590021 North Carolina Rowan 30.2 30.2 25.4 25.4 25.1 25.1 21.9 21.9371730002 North Carolina Swain 27.3 28.3 23.6 24.3 22.1 22.8 19.7 20.8371830014 North Carolina Wake 31.6 32.2 27.6 27.8 26.5 26.9 24.1 24.5371890003 North Carolina Watauga 30.4 30.5 25.9 26.0 25.3 25.4 19.6 19.9371910005 North Carolina Wayne 29.7 30.4 26.6 27.4 25.5 26.3 21.6 22.5380070002 North Dakota Billings 13.013.6 12.6 13.1 12.6 12.9 12.4 12.8380130003 North Dakota Burke 16.7 16.7 16.2 16.2 16.1 16.1 16.0 16.0380150003 North Dakota Burleigh 17.6 18.7 16.4 17.3 16.2 17.1 15.8 16.7380171004 North Dakota Cass 21.2 22.5 20.5 21.7 19.8 21.0 18.2 19.6380530002 North Dakota McKenzie 11.9 13.0 11.4 12.5 11.4 12.4 11.2 12.2380570004 North Dakota Mercer 16.9 17.9 17.2 18.2 17.1 18.1 17.0 18.0390090003 Ohio Athens 32.3 33.2 28.9 29.4 27.3 27.6 19.7 20.5B-7224-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues390170003 Ohio Butler 39.2 41.1 40.3 42.3 38.3 40.3 29.1 31.4390170016 Ohio Butler 37.1 37.7 37.5 37.8 35.7 36.2 27.9 28.3390170017 Ohio Butler 37.9 37.9 38.5 38.5 36.8 36.8 28.4 28.4390171004 Ohio Butler 37.1 38.1 37.8 38.6 36.1 37.0 27.4 28.3390230005 Ohio Clark 35.3 36.4 33.6 34.7 32.1 33.1 26.6 27.5390250022 Ohio Clermont 34.4 34.4 34.4 34.4 32.9 32.9 24.8 24.8390350027 Ohio Cuyahoga 36.6 38.8 34.5 36.6 34.0 36.2 32.1 35.0390350034 Ohio Cuyahoga 36.5 37.9 33.7 35.7 33.2 35.4 29.9 33.3390350038 Ohio Cuyahoga 44.2 47.0 41.2 44.0 40.0 42.6 35.7 38.2390350045 Ohio Cuyahoga 38.5 41.5 36.0 39.0 35.0 38.2 29.4 33.2390350060 Ohio Cuyahoga 42.1 45.7 39.4 42.8 38.7 41.8 36.3 38.0390350065 Ohio Cuyahoga 38.6 41.0 36.5 38.9 35.4 38.1 30.2 33.9390351002 Ohio Cuyahoga 34.6 34.6 32.9 32.9 32.2 32.2 29.7 29.7390490024 Ohio Franklin 38.5 39.7 36.6 37.6 35.2 36.5 32.3 33.9390490025 Ohio Franklin 38.4 39.1 36.1 36.4 34.8 35.2 30.6 32.6390490081 Ohio Franklin 34.1 34.1 30.9 30.9 29.2 29.2 24.6 24.6390570005 Ohio Greene 33.0 33.0 32.1 32.1 30.9 30.9 26.2 26.2390610006 Ohio Hamilton 37.6 37.6 38.0 38.0 36.5 36.5 27.2 27.2390610014 Ohio Hamilton 38.2 39.4 37.5 38.5 36.1 37.1 25.4 27.1390610040 Ohio Hamilton 36.7 37.7 35.8 36.8 34.3 35.3 24.9 25.2390610042 Ohio Hamilton 37.3 38.2 37.2 38.0 35.9 36.7 29.3 30.0390610043 Ohio Hamilton 35.9 36.2 36.0 36.4 34.7 35.0 27.9 28.4390617001 Ohio Hamilton 38.8 39.6 37.7 38.1 36.2 36.6 30.1 31.9390618001 Ohio Hamilton 40.6 40.9 39.6 40.3 38.2 39.0 31.0 32.3390810017 Ohio Jefferson 40.7 42.4 35.3 36.8 34.0 35.5 29.1 30.5390811001 Ohio Jefferson 41.9 45.5 36.5 39.9 35.3 38.8 30.0 33.3390851001 Ohio Lake 37.1 37.1 35.0 35.0 34.4 34.4 29.5 29.5390870010 Ohio Lawrence 33.7 34.8 30.3 31.5 28.8 29.8 22.0 22.5390933002 Ohio Lorain 31.5 32.1 30.0 30.6 29.1 29.7 24.5 24.8390950024 Ohio Lucas 36.3 38.6 34.2 36.5 33.5 35.7 32.0 34.4B-7324-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues390950025 Ohio Lucas 35.1 36.8 33.4 34.5 32.6 33.8 31.1 32.5390950026 Ohio Lucas 34.9 36.7 33.6 35.6 32.6 34.5 30.2 32.3390990005 Ohio Mahoning 35.1 35.7 32.2 32.7 30.7 31.3 27.0 28.8390990014 Ohio Mahoning 36.8 38.2 34.2 35.8 33.1 34.6 30.3 31.9391130031 Ohio Montgomery 35.7 37.1 34.3 35.6 33.1 34.2 29.8 30.9391130032 Ohio Montgomery 37.8 40.0 36.3 38.5 34.9 36.9 31.1 33.3391330002 Ohio Portage 34.3 34.5 32.9 33.1 31.7 31.9 25.9 26.3391351001 Ohio Preble 32.8 33.9 34.3 35.5 33.2 34.4 26.5 26.6391450013 Ohio Scioto 34.5 36.1 31.6 33.1 30.1 31.6 22.3 23.2391510017 Ohio Stark 36.9 37.6 34.4 35.3 33.6 34.7 28.6 29.6391530017 Ohio Summit 38.0 39.6 35.6 37.2 34.6 36.4 31.4 34.2391530023 Ohio Summit 35.8 37.5 33.5 35.1 32.6 34.3 28.4 30.4391550007 Ohio Trumbull 36.2 37.8 33.9 35.6 33.0 34.5 30.2 32.1400159008 Oklahoma Caddo 23.9 26.0 22.1 23.9 21.7 23.3 19.6 20.6400219002 Oklahoma Cherokee 27.5 28.0 25.9 26.2 25.1 25.5 23.0 23.8400710602 Oklahoma Kay 31.8 31.8 30.8 30.8 29.9 29.9 28.0 28.0400719010 Oklahoma Kay 27.9 32.2 26.7 30.7 26.0 30.0 24.4 28.7400819005 Oklahoma Lincoln 27.8 27.8 26.4 26.4 25.7 25.7 22.7 22.7400970186 Oklahoma Mayes 28.7 29.1 27.7 28.1 26.8 27.2 25.4 25.9400979014 Oklahoma Mayes 26.1 26.3 25.1 25.2 24.1 24.3 21.3 21.4401010169 Oklahoma Muskogee 29.5 30.5 28.6 29.5 28.0 28.7 25.8 26.3401090035 Oklahoma Oklahoma 23.4 24.0 21.8 22.4 21.3 21.9 20.5 21.0401091037 Oklahoma Oklahoma 27.1 28.2 25.0 26.3 24.2 25.5 22.6 23.9401159004 Oklahoma Ottawa 29.1 29.6 27.8 28.4 26.7 27.5 23.4 24.5401210415 Oklahoma Pittsburg 26.3 27.2 25.1 26.1 24.4 25.4 21.9 23.3401359015 Oklahoma Sequoyah 31.4 31.4 30.4 30.4 29.9 29.9 26.7 26.7401430110 Oklahoma Tulsa 28.4 28.4 27.5 27.5 26.7 26.7 24.6 24.6401431127 Oklahoma Tulsa 30.3 31.0 29.6 30.3 28.7 29.3 26.5 27.9420010001 Pennsylvania Adams 34.9 36.2 32.1 32.8 31.5 32.3 28.4 29.7420030008 Pennsylvania Allegheny 39.4 39.9 35.9 36.3 34.7 35.1 28.5 28.8B-7424-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues420030021 Pennsylvania Allegheny 35.1 35.1 32.2 32.2 31.4 31.4 25.9 25.9420030064 Pennsylvania Allegheny 64.2 68.2 58.8 62.3 57.2 60.4 55.8 58.9420030067 Pennsylvania Allegheny 37.2 39.4 33.0 34.7 31.5 33.1 21.5 22.5420030093 Pennsylvania Allegheny 45.6 51.5 41.1 46.2 39.7 44.5 31.4 35.2420030095 Pennsylvania Allegheny 38.7 40.7 34.3 36.6 33.0 35.2 26.5 29.1420030116 Pennsylvania Allegheny 42.5 42.5 37.1 37.1 35.5 35.5 28.6 28.6420030133 Pennsylvania Allegheny 39.2 39.2 34.5 34.5 33.1 33.1 24.3 24.3420031008 Pennsylvania Allegheny 41.3 42.8 38.0 39.3 36.7 37.8 27.2 27.9420031301 Pennsylvania Allegheny 40.3 42.4 36.6 38.6 35.5 37.4 30.1 31.0420033007 Pennsylvania Allegheny 37.5 43.1 33.8 38.5 32.6 36.9 25.6 28.4420039002 Pennsylvania Allegheny 37.8 37.8 34.3 34.3 33.0 33.0 24.7 24.7420070014 Pennsylvania Beaver 43.4 44.6 37.7 39.1 36.6 38.0 30.0 30.8420110011 Pennsylvania Berks 37.7 39.1 35.8 37.0 35.4 36.6 33.3 34.4420170012 Pennsylvania Bucks 34.0 34.8 31.6 32.1 30.8 31.3 28.7 28.8420210011 Pennsylvania Cambria 39.0 39.4 40.3 40.7 39.4 39.8 25.6 26.0420270100 Pennsylvania Centre 36.237.6 33.9 35.0 33.2 34.1 28.8 29.3420290100 Pennsylvania Chester 36.7 36.7 33.0 33.0 32.5 32.5 30.0 30.0420410101 Pennsylvania Cumberland 38.0 40.2 35.3 37.0 35.0 36.7 33.0 34.6420430401 Pennsylvania Dauphin 38.039.0 35.7 37.1 35.3 36.8 33.6 35.1420450002 Pennsylvania Delaware 35.2 35.9 33.0 33.3 32.3 32.7 28.7 29.6420490003 Pennsylvania Erie 34.434.4 32.7 32.7 32.0 32.0 29.4 29.4420692006 Pennsylvania Lackawanna 31.5 32.6 28.8 29.7 28.1 29.0 25.4 26.2420710007 Pennsylvania Lancaster 40.8 44.0 37.7 40.1 37.5 39.7 36.0 38.2420770004 Pennsylvania Lehigh 36.436.4 34.6 34.6 34.1 34.1 32.6 32.6420791101 Pennsylvania Luzerne 32.432.4 28.9 28.9 28.1 28.1 26.2 26.2420850100 Pennsylvania Mercer 36.336.3 33.5 33.5 32.2 32.2 29.7 29.7420950025 Pennsylvania Northampton 36.7 37.4 33.8 34.3 33.1 33.5 31.4 31.7420990301 Pennsylvania Perry 30.4 30.4 28.9 28.9 28.7 28.7 26.1 26.1421010004 Pennsylvania Philadelphia 36.5 36.7 33.6 34.1 32.8 33.4 31.5 32.1421010024 Pennsylvania Philadelphia 35.9 35.9 32.9 32.9 32.1 32.1 29.0 29.0B-7524-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues421010047 Pennsylvania Philadelphia 37.3 37.7 33.3 33.7 32.5 32.9 29.1 29.5421250005 Pennsylvania Washington 35.5 36.3 31.6 32.3 30.7 31.4 23.7 24.7421250200 Pennsylvania Washington 33.4 33.5 29.2 29.2 28.4 28.5 23.3 23.7421255001 Pennsylvania Washington 38.1 39.9 33.9 35.5 32.7 34.1 26.0 27.0421290008 Pennsylvania Westmoreland 37.1 37.5 33.4 33.7 32.3 32.6 23.9 24.9421330008 Pennsylvania York 38.2 40.7 35.9 38.8 35.5 38.4 32.8 35.4440070022 Rhode Island Providence 29.4 29.4 26.9 26.9 26.5 26.5 24.4 24.4440070026 Rhode Island Providence 30.6 32.2 28.0 29.0 27.5 28.5 26.0 26.8440070028 Rhode Island Providence 28.2 28.4 25.6 25.7 25.2 25.3 23.3 23.4440071010 Rhode Island Providence 28.8 29.7 26.6 27.0 26.2 26.6 24.3 24.5450130007 South Carolina Beaufort 30.2 32.6 26.8 28.6 25.4 27.0 21.5 22.1450190048 South Carolina Charleston 27.8 28.0 25.2 25.5 24.2 24.4 23.0 23.1450190049 South Carolina Charleston 27.9 27.9 26.2 26.3 24.9 25.0 22.6 22.7450250001 South Carolina Chesterfield 28.7 29.9 25.5 26.5 24.8 25.8 21.3 22.1450370001 South Carolina Edgefield32.2 33.7 29.5 31.0 27.2 29.0 23.4 25.1450410002 South Carolina Florence 28.8 28.9 26.0 26.0 24.9 24.9 21.9 21.9450430009 South Carolina Georgetown29.2 29.5 26.5 26.9 25.5 26.0 22.6 23.2450450008 South Carolina Greenville32.1 32.4 29.4 29.4 28.1 28.2 26.6 26.8450450009 South Carolina Greenville32.5 33.5 29.0 29.3 27.7 28.0 25.1 25.4450470003 South Carolina Greenwood 30.0 31.0 26.6 26.9 24.5 25.4 21.9 22.2450510002 South Carolina Horry 28.6 29.2 26.1 26.7 25.2 25.8 21.7 22.1450630008 South Carolina Lexington 32.8 33.4 29.8 30.6 28.7 29.4 25.8 26.7450730001 South Carolina Oconee 28.4 29.3 25.2 26.2 23.1 23.8 19.5 20.2450790007 South Carolina Richland 31.3 32.0 27.8 28.2 26.5 26.8 23.6 24.1450790019 South Carolina Richland 33.2 33.8 30.2 31.0 28.8 29.5 26.3 27.0450830010 South Carolina Spartanburg32.4 32.4 26.9 26.9 26.1 26.1 23.0 23.0460110002 South Dakota Brookings 23.5 24.9 22.4 23.7 21.6 22.9 19.9 21.1460130003 South Dakota Brown 18.7 19.2 17.8 18.0 17.2 17.5 16.2 16.7460290002 South Dakota Codington 23.6 24.0 23.0 23.4 22.2 22.6 20.5 20.7460330132 South Dakota Custer 14.3 14.3 13.9 13.9 13.9 13.9 13.6 13.6B-7624-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues460710001 South Dakota Jackson 12.713.4 12.2 12.9 12.1 12.8 11.6 12.2460990006 South Dakota Minnehaha 24.1 25.5 23.1 24.5 22.3 23.6 20.6 21.7460990007 South Dakota Minnehaha 23.9 25.1 22.4 23.3 21.8 22.7 20.0 21.0461030016 South Dakota Pennington 17.2 17.2 16.1 16.2 15.9 16.0 15.7 15.8461030020 South Dakota Pennington 18.5 19.2 17.6 18.2 17.5 18.0 17.4 17.9461031001 South Dakota Pennington 15.9 16.6 15.0 15.8 14.8 15.6 14.6 15.5470090011 Tennessee Blount 32.5 34.2 30.4 32.0 29.1 30.6 22.5 23.7470370023 Tennessee Davidson 33.5 34.3 34.4 35.1 32.9 33.5 23.7 24.7470370025 Tennessee Davidson 30.9 31.5 31.5 32.1 29.9 30.5 21.8 22.7470370036 Tennessee Davidson 32.7 33.5 33.9 34.8 32.2 33.0 21.5 22.0470450004 Tennessee Dyer 31.9 33.3 32.9 34.4 31.0 32.3 22.7 23.9470650031 Tennessee Hamilton 33.2 35.2 29.7 30.7 28.4 29.0 25.8 26.2470651011 Tennessee Hamilton 29.7 31.3 26.7 28.1 25.5 26.6 20.7 22.2470654002 Tennessee Hamilton 33.5 34.3 29.2 30.5 27.9 29.1 25.5 26.8470930028 Tennessee Knox 36.6 36.6 33.9 33.9 32.4 32.4 26.1 26.1470931017 Tennessee Knox 33.4 33.9 31.2 31.6 30.0 30.4 25.8 25.8470990002 Tennessee Lawrence 28.4 31.7 27.3 31.0 26.1 29.5 18.7 20.6471050108 Tennessee Loudon 32.2 33.330.4 31.3 28.8 29.7 23.4 24.1471071002 Tennessee McMinn 32.4 33.9 30.1 31.5 28.4 29.8 21.9 23.2471192007 Tennessee Maury 30.8 31.7 30.8 31.9 29.4 30.5 20.9 21.9471251009 Tennessee Montgomery 36.3 37.5 36.6 37.9 35.2 36.4 26.8 27.7471410001 Tennessee Putnam 32.6 32.6 31.0 31.0 29.0 29.0 20.0 20.0471450004 Tennessee Roane 30.2 31.4 27.8 28.9 26.6 27.6 21.6 22.5471570014 Tennessee Shelby 32.2 33.5 31.0 31.8 29.3 30.3 21.9 23.9471570038 Tennessee Shelby 32.5 33.5 32.0 33.0 30.3 31.2 22.0 23.7471570047 Tennessee Shelby 33.5 33.8 32.4 32.9 30.9 31.2 22.9 24.7471571004 Tennessee Shelby 29.8 30.4 29.6 30.4 28.2 28.8 19.9 21.1471631007 Tennessee Sullivan 31.1 32.0 28.0 28.8 27.2 28.0 22.6 23.3471650007 Tennessee Sumner 33.6 34.5 35.1 36.0 33.1 34.0 20.5 22.5480370004 Texas Bowie 29.4 30.0 28.3 28.6 27.2 27.7 22.9 23.2B-7724-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues481130069 Texas Dallas 25.7 27.7 24.3 25.8 23.9 25.2 22.7 23.6481130087 Texas Dallas 24.2 27.0 21.7 24.3 21.0 23.5 19.2 21.8481350003 Texas Ector 17.8 18.2 18.8 19.2 17.1 17.6 15.7 16.2481410037 Texas El Paso 22.9 22.9 22.0 22.0 21.9 21.9 21.5 21.5482010058 Texas Harris 25.4 26.3 24.5 25.2 23.6 24.2 21.0 21.2482011035 Texas Harris 30.8 31.4 29.9 30.2 28.7 29.1 26.9 27.1482030002 Texas Harrison 25.9 26.2 24.6 24.9 24.0 24.4 20.8 21.3482150043 Texas Hidalgo 26.4 27.9 26.4 28.2 25.8 27.6 23.8 25.4482450021 Texas Jefferson 26.0 26.8 25.4 26.3 24.4 25.3 20.2 20.9483550032 Texas Nueces 27.5 30.2 27.0 29.9 25.9 28.7 22.5 25.2483611001 Texas Orange 27.7 28.7 27.2 28.0 26.2 27.0 21.4 22.2484391002 Texas Tarrant 25.3 26.8 23.3 24.9 22.9 24.5 21.5 23.1484391006 Texas Tarrant 25.7 27.9 24.0 26.1 23.7 25.7 22.9 25.0500010002 Vermont Addison 28.2 28.2 26.1 26.1 25.6 25.6 23.1 23.1500010003 Vermont Addison 31.7 31.7 29.4 29.4 28.8 28.8 25.6 25.6500030004 Vermont Bennington 26.4 28.5 24.2 26.3 23.6 25.6 22.1 24.0500070012 Vermont Chittenden 29.8 30.3 27.5 27.8 26.7 27.0 22.3 23.8500070014 Vermont Chittenden 30.1 30.1 28.3 28.3 27.6 27.6 25.9 25.9500210002 Vermont Rutland 30.6 31.3 29.1 29.4 28.6 28.8 27.9 28.0510130020 Virginia Arlington 34.1 36.3 30.9 33.5 30.1 32.9 27.7 30.5510360002 Virginia Charles 31.7 32.1 27.3 27.8 26.5 27.0 22.0 22.3510410003 Virginia Chesterfield 31.2 32.6 25.7 27.0 24.9 26.1 21.1 22.2510590030 Virginia Fairfax 34.4 35.0 30.9 31.7 30.5 31.4 26.6 27.4510591005 Virginia Fairfax 33.7 35.2 30.4 32.8 30.0 32.6 25.8 29.3510595001 Virginia Fairfax 33.3 33.7 30.8 31.2 30.1 30.5 27.1 27.5510870014 Virginia Henrico 31.9 32.9 27.1 28.2 26.3 27.3 21.9 22.7510870015 Virginia Henrico 29.1 29.6 25.6 26.2 24.9 25.5 19.6 20.5511071005 Virginia Loudoun 34.4 35.7 30.9 32.3 30.6 32.0 24.8 26.2511390004 Virginia Page 30.0 30.9 28.1 29.0 27.2 28.1 20.4 22.2515200006 Virginia Bristol City 30.2 30.5 26.2 26.5 25.3 25.5 20.5 20.6B-7824-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues516500004 Virginia Hampton City 29.0 29.2 26.8 27.6 25.9 26.6 23.0 24.3516800015 Virginia Lynchburg City 30.7 31.1 26.6 26.9 25.6 25.9 19.5 19.9517100024 Virginia Norfolk City 29.6 29.9 27.3 27.6 26.4 26.7 23.7 24.0517700014 Virginia Roanoke City 32.7 33.2 28.5 28.7 27.2 27.6 23.4 24.4517750010 Virginia Salem City 34.0 34.0 29.4 29.4 28.4 28.4 24.3 24.3518100008 VirginiaVirginia BeachCity30.0 30.2 27.7 27.8 26.8 26.9 24.5 24.5540030003 West Virginia Berkeley 34.5 35.8 32.0 32.7 31.6 32.2 29.3 30.0540090005 West Virginia Brooke 39.4 41.5 33.9 36.1 33.0 35.2 28.9 30.6540090011 West Virginia Brooke 43.9 44.9 39.9 40.8 39.2 40.1 36.4 37.1540110006 West Virginia Cabell 35.1 36.6 32.1 33.6 30.8 32.2 23.3 24.6540291004 West Virginia Hancock 40.6 41.2 34.3 34.6 32.7 33.2 26.0 26.6540330003 West Virginia Harrison 33.5 34.6 33.0 34.0 31.3 32.3 20.2 20.5540390010 West Virginia Kanawha 34.7 35.5 32.2 32.9 30.9 31.6 22.2 22.9540390011 West Virginia Kanawha 33.1 33.1 30.8 30.8 29.6 29.6 21.5 21.5540391005 West Virginia Kanawha 36.9 37.7 34.3 35.1 33.0 33.7 24.5 25.5540490006 West Virginia Marion 33.6 33.7 34.3 34.4 32.8 32.8 20.1 20.2540511002 West Virginia Marshall 33.9 34.8 30.0 30.9 28.7 29.6 22.9 23.9540610003 West Virginia Monongalia 35.6 36.2 33.7 34.3 31.2 31.7 20.4 21.2540690010 West Virginia Ohio 32.0 32.0 27.9 27.9 26.9 26.9 24.0 24.0540810002 West Virginia Raleigh 30.6 31.3 27.8 28.3 26.7 27.2 19.6 19.9540890001 West Virginia Summers 31.2 31.2 27.9 27.9 26.6 26.6 19.2 19.2541071002 West Virginia Wood 35.4 36.7 32.7 33.9 31.1 32.2 23.0 23.4550030010 Wisconsin Ashland 18.620.5 17.8 19.4 17.1 18.8 15.1 16.4550090005 Wisconsin Brown 36.5 37.0 35.0 35.4 34.7 35.1 34.5 34.8550090009 Wisconsin Brown 35.8 35.8 34.4 34.4 34.2 34.2 34.2 34.2550250047 Wisconsin Dane 35.5 36.9 35.1 36.1 34.2 35.3 31.7 32.9550270007 Wisconsin Dodge 31.8 33.1 30.8 32.3 29.6 30.9 28.6 29.7550410007 Wisconsin Forest 25.2 25.2 23.9 23.9 23.2 23.2 21.3 21.3550430009 Wisconsin Grant 34.3 35.0 32.5 33.0 31.7 32.1 30.7 31.4B-7924-Hour PM2.5 Design Values (μg/m3)Monitor ID State County2003 - 2007AverageAmbientValues2003 - 2007MaximumAmbientValues2012Base CaseAverageValues2012Base CaseMaximumValues2014Base CaseAverageValues2014Base CaseMaximumValues2014RemedyAverageValues2014RemedyMaximumValues550590019 Wisconsin Kenosha 32.734.0 32.2 33.5 31.4 32.6 29.9 31.0550710007 Wisconsin Manitowoc 29.7 31.6 29.0 30.8 28.3 30.1 27.7 29.3550790010 Wisconsin Milwaukee 38.6 40.0 37.7 39.0 37.0 38.3 36.3 37.5550790026 Wisconsin Milwaukee 37.3 41.3 36.3 40.1 35.3 39.2 34.4 38.3550790043 Wisconsin Milwaukee 39.9 40.8 38.8 39.7 37.3 38.4 36.3 37.7550790059 Wisconsin Milwaukee 35.5 37.0 34.8 36.3 33.5 35.1 31.6 33.4550790099 Wisconsin Milwaukee 37.7 38.7 36.8 37.7 35.5 37.0 33.3 35.9550870009 Wisconsin Outagamie 32.8 34.4 31.2 32.8 30.9 32.5 30.7 32.3550890009 Wisconsin Ozaukee 32.5 34.0 31.8 33.2 30.9 32.4 30.0 31.6551091002 Wisconsin St. Croix 26.6 26.6 25.5 25.5 24.7 24.7 23.7 23.7551110007 Wisconsin Sauk 28.6 28.8 27.5 27.7 26.7 27.1 26.3 26.8551198001 Wisconsin Taylor 25.3 26.0 23.9 24.7 23.3 24.0 22.7 23.1551250001 Wisconsin Vilas 22.6 23.8 21.4 22.6 20.7 21.8 19.2 20.0551330027 Wisconsin Waukesha 35.4 36.2 34.9 35.6 33.3 33.9 31.6 31.8560050877 Wyoming Campbell 18.6 18.6 18.0 18.0 17.9 17.9 17.9 17.9560050892 Wyoming Campbell 12.1 12.2 11.9 12.0 11.9 12.0 11.9 12.0560050899 Wyoming Campbell 12.7 13.5 12.5 13.2 12.5 13.2 12.5 13.3560090819 Wyoming Converse 10.0 10.5 9.7 10.3 9.7 10.2 9.7 10.2560131003 Wyoming Fremont 29.8 31.9 28.3 30.5 28.0 30.2 28.1 30.3560210001 Wyoming Laramie 11.9 12.7 11.5 12.2 11.4 12.1 11.3 12.0560330002 Wyoming Sheridan 30.8 32.5 29.8 31.3 29.6 31.0 29.6 31.0B-80Differences in 8-Hour Ozone AverageDesign Values (ppb) by Site:2014 Remedy Scenario Compared to the2012 Base Case and the 2014 Base Case8-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case10030010 Alabama Baldwin -3.9 -2.210270001 Alabama Clay -4.2 -0.610331002 Alabama Colbert -2.0 -0.210510001 Alabama Elmore -2.7 -0.310550011 Alabama Etowah -3.3 -0.410690004 Alabama Houston -3.0 -0.310730023 Alabama Jefferson -2.7 -0.210731003 Alabama Jefferson -2.8 -0.210731005 Alabama Jefferson -3.1 -0.210731009 Alabama Jefferson -2.6 -0.210731010 Alabama Jefferson -2.8 -0.210732006 Alabama Jefferson -2.9 -0.210735002 Alabama Jefferson -2.7 -0.210735003 Alabama Jefferson -2.7 -0.310736002 Alabama Jefferson -2.8 -0.210790002 Alabama Lawrence -2.7 -0.110890014 Alabama Madison -3.4 -0.110970003 Alabama Mobile -3.4 -1.710972005 Alabama Mobile -3.7 -1.911011002 Alabama Montgomery -2.6 -0.211030011 Alabama Morgan -2.5 -0.211130002 Alabama Russell -3.6 -0.411170004 Alabama Shelby -3.2 -0.211190002 Alabama Sumter -1.9 -0.111210003 Alabama Talladega -3.0 -0.311250010 Alabama Tuscaloosa -2.8 -0.150350005 Arkansas Crittenden -2.9 -0.151190007 Arkansas Pulaski -3.6 -1.2B-818-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case51191002 Arkansas Pulaski -3.7 -1.151191005 Arkansas Pulaski -3.4 -1.180013001 Colorado Adams -0.6 0.080050002 Colorado Arapahoe -0.9 0.080130011 Colorado Boulder -1.1 0.180310002 Colorado Denver -0.5 0.080310014 Colorado Denver -0.7 0.080350004 Colorado Douglas -1.2 0.180590002 Colorado Jefferson -0.6 0.180590005 Colorado Jefferson -0.8 0.180590006 Colorado Jefferson -1.1 0.180590011 Colorado Jefferson -0.7 0.080691004 Colorado Larimer -1.0 0.181230009 Colorado Weld -1.0 0.190010017 Connecticut Fairfield -1.8 -0.190011123 Connecticut Fairfield -2.2 -0.190013007 Connecticut Fairfield -2.0 -0.290019003 Connecticut Fairfield -1.8 -0.190031003 Connecticut Hartford -2.3 0.090050005 Connecticut Litchfield -2.5 0.090070007 Connecticut Middlesex -2.3 -0.190090027 Connecticut New Haven -1.9 -0.190093002 Connecticut New Haven -2.3 -0.190110008 Connecticut New London -2.2 -0.190131001 Connecticut Tolland -2.6 -0.1100010002 Delaware Kent -2.1 -0.1100031007 Delaware New Castle -1.9 -0.1100031010 Delaware New Castle -1.8 0.0100031013 Delaware New Castle -1.9 -0.1100051002 Delaware Sussex -2.2 -0.1100051003 Delaware Sussex -1.9 0.0110010025District OfColumbiaDistrict of Columbia -1.7 0.0B-828-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case110010041District OfColumbia District of Columbia -1.9 -0.2110010043District OfColumbiaDistrict of Columbia -1.9 -0.1120010025 Florida Alachua -5.8 -3.3120030002 Florida Baker -3.8 -1.4120050006 Florida Bay -5.2 -2.8120090007 Florida Brevard -3.9 -0.8120094001 Florida Brevard -4.3 -0.9120110031 Florida Broward -0.4 -0.1120112003 Florida Broward -1.2 -0.2120118002 Florida Broward -1.0 -0.2120210004 Florida Collier -2.6 -0.3120230002 Florida Columbia -3.7 -1.1120310077 Florida Duval -3.7 -1.7120310100 Florida Duval -4.1 -1.8120330004 Florida Escambia -6.3 -4.7120330018 Florida Escambia -7.3 -5.6120330024 Florida Escambia -7.2 -5.5120570081 Florida Hillsborough -2.4 -0.6120570110 Florida Hillsborough -2.2 -0.6120571035 Florida Hillsborough -2.2 -0.6120571065 Florida Hillsborough -2.8 -0.9120573002 Florida Hillsborough -1.9 -0.3120574004 Florida Hillsborough -2.1 -0.4120690002 Florida Lake -3.8 -0.7120712002 Florida Lee -2.5 -0.4120713002 Florida Lee -2.7 -0.5120730012 Florida Leon -3.2 -0.7120730013 Florida Leon -3.4 -0.7120813002 Florida Manatee -2.6 -0.7120814012 Florida Manatee -2.7 -0.8120814013 Florida Manatee -2.4 -0.8B-838-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case120830003 Florida Marion -4.3 -1.7120830004 Florida Marion -4.6 -2.4120860027 Florida Miami-Dade -0.5 -0.3120860029 Florida Miami-Dade -0.8 -0.2120950008 Florida Orange -4.1 -0.9120952002 Florida Orange -3.6 -0.6120972002 Florida Osceola -3.5 -0.7120990020 Florida Palm Beach -1.9 -0.1121010005 Florida Pasco -3.1 -1.4121012001 Florida Pasco -2.8 -0.9121030004 Florida Pinellas -2.5 -0.8121030018 Florida Pinellas -2.2 -0.7121035002 Florida Pinellas -2.4 -0.7121056005 Florida Polk -2.8 -1.0121056006 Florida Polk -3.1 -1.1121111002 Florida St. Lucie -2.6 -0.4121130015 Florida Santa Rosa -7.3 -5.5121151005 Florida Sarasota -2.6 -0.7121151006 Florida Sarasota -2.5 -0.7121152002 Florida Sarasota -2.6 -0.8121171002 Florida Seminole -4.2 -0.6121272001 Florida Volusia -4.6 -0.8121275002 Florida Volusia -4.4 -0.6121290001 Florida Wakulla -2.8 -0.7130210012 Georgia Bibb -5.3 -0.3130210013 Georgia Bibb -5.7 -0.3130510021 Georgia Chatham -2.8 -0.5130550001 Georgia Chattooga -3.7 -0.2130590002 Georgia Clarke -4.4 -0.2130670003 Georgia Cobb -4.1 -0.2130730001 Georgia Columbia -3.1 -0.3130770002 Georgia Coweta -5.6 -1.0130850001 Georgia Dawson -3.9 -0.2B-848-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case130890002 Georgia DeKalb -3.5 -0.1130893001 Georgia DeKalb -3.2 -0.2130970004 Georgia Douglas -4.8 -0.2131130001 Georgia Fayette -3.5 -0.2131210055 Georgia Fulton -3.7 -0.2131270006 Georgia Glynn -4.0 -1.9131350002 Georgia Gwinnett -4.0 -0.2131510002 Georgia Henry -4.2 -0.2132130003 Georgia Murray -4.0 -0.7132150008 Georgia Muscogee -4.0 -0.4132151003 Georgia Muscogee -3.7 -0.3132230003 Georgia Paulding -4.3 -0.2132450091 Georgia Richmond -3.4 -0.4132470001 Georgia Rockdale -4.5 -0.2132611001 Georgia Sumter -3.5 -0.4170010006 Illinois Adams -2.2 -0.8170190004 Illinois Champaign -1.7 -0.3170230001 Illinois Clark -1.8 -0.4170310001 Illinois Cook -1.2 -0.1170310032 Illinois Cook -1.2 -0.2170310064 Illinois Cook -1.2 -0.2170310072 Illinois Cook -1.2 -0.2170310076 Illinois Cook -1.0 -0.2170311003 Illinois Cook -1.1 -0.2170311601 Illinois Cook -1.3 -0.1170314002 Illinois Cook -0.7 -0.2170314007 Illinois Cook -1.0 -0.1170314201 Illinois Cook -1.0 -0.1170317002 Illinois Cook -1.3 -0.3170436001 Illinois DuPage -1.0 -0.1170491001 Illinois Effingham -1.7 -0.2170650002 Illinois Hamilton -1.6 0.1170831001 Illinois Jersey -2.5 -0.5B-858-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case170890005 Illinois Kane -1.6 -0.2170971002 Illinois Lake -1.4 -0.3170971007 Illinois Lake -1.5 -0.3171110001 Illinois McHenry -1.8 -0.2171132003 Illinois McLean -2.2 -0.3171150013 Illinois Macon -2.0 -0.5171170002 Illinois Macoupin -2.7 -0.6171190008 Illinois Madison -2.8 -0.7171191009 Illinois Madison -2.7 -0.6171193007 Illinois Madison -2.8 -0.7171430024 Illinois Peoria -2.2 -0.2171431001 Illinois Peoria -2.4 -0.2171570001 Illinois Randolph -1.8 -0.1171613002 Illinois Rock Island -2.4 -1.1171630010 Illinois Saint Clair -2.2 -0.6171670010 Illinois Sangamon -2.1 -0.4171971011 Illinois Will -1.6 -0.1172010009 Illinois Winnebago -2.1 -0.2172012001 Illinois Winnebago -2.1 -0.2180030002 Indiana Allen -2.4 -0.2180030004 Indiana Allen -2.3 -0.2180110001 Indiana Boone -2.7 -0.4180150002 Indiana Carroll -2.2 -0.3180190008 Indiana Clark -2.8 -0.8180350010 Indiana Delaware -2.8 -0.4180390007 Indiana Elkhart -2.6 -0.4180431004 Indiana Floyd -2.5 -0.7180550001 Indiana Greene -2.2 -0.5180570005 Indiana Hamilton -3.0 -0.5180590003 Indiana Hancock -2.8 -0.5180630004 Indiana Hendricks -2.4 -0.4180690002 Indiana Huntington -2.2 -0.1180710001 Indiana Jackson -2.3 -0.5B-868-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case180810002 Indiana Johnson -2.7 -0.6180890022 Indiana Lake -1.4 -0.3180890030 Indiana Lake -1.4 -0.4180892008 Indiana Lake -1.3 -0.3180910005 Indiana LaPorte -1.8 -0.3180910010 Indiana LaPorte -2.0 -0.3180950010 Indiana Madison -2.9 -0.5180970042 Indiana Marion -2.4 -0.7180970050 Indiana Marion -2.5 -0.5180970057 Indiana Marion -2.3 -0.5180970073 Indiana Marion -2.4 -0.5181090005 Indiana Morgan -2.9 -0.7181230009 Indiana Perry -2.5 -0.1181270024 Indiana Porter -1.6 -0.3181270026 Indiana Porter -1.8 -0.4181290003 Indiana Posey -2.0 0.0181410010 Indiana St. Joseph -2.4 -0.5181410015 Indiana St. Joseph -2.4 -0.4181411007 Indiana St. Joseph -2.6 -0.5181450001 Indiana Shelby -2.5 -0.7181630012 Indiana Vanderburgh -2.0 0.2181630013 Indiana Vanderburgh -1.9 0.1181670018 Indiana Vigo -2.1 -0.6181670024 Indiana Vigo -2.5 -0.9181730008 Indiana Warrick -1.6 0.3181730009 Indiana Warrick -2.0 -0.1181730011 Indiana Warrick -1.6 0.3190450021 Iowa Clinton -2.3 -0.8190851101 Iowa Harrison -3.1 -1.8191130028 Iowa Linn -2.0 -0.6191130033 Iowa Linn -2.6 -1.1191530058 Iowa Polk -2.1 -0.5191630014 Iowa Scott -2.5 -0.9B-878-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case191632011 Iowa Scott -2.7 -1.1191690011 Iowa Story -2.3 -0.9200450004 Kansas Douglas -3.4 -1.9200910010 Kansas Johnson -3.7 -2.2201030003 Kansas Leavenworth -3.0 -1.5201070002 Kansas Linn -5.3 -4.1201730001 Kansas Sedgwick -2.5 -0.8201730010 Kansas Sedgwick -2.7 -0.8201910002 Kansas Sumner -2.6 -0.6202090021 Kansas Wyandotte -3.0 -1.7210130002 Kentucky Bell -2.9 -0.2210150003 Kentucky Boone -2.6 -0.8210190017 Kentucky Boyd -1.7 -0.2210290006 Kentucky Bullitt -2.5 -0.7210370003 Kentucky Campbell -2.2 -0.7210430500 Kentucky Carter -1.8 -0.2210470006 Kentucky Christian -2.6 -0.3210590005 Kentucky Daviess -2.0 0.0210610501 Kentucky Edmonson -2.3 -0.1210670001 Kentucky Fayette -2.2 -0.3210670012 Kentucky Fayette -2.4 -0.3210890007 Kentucky Greenup -1.7 -0.2210910012 Kentucky Hancock -2.1 0.0210930006 Kentucky Hardin -2.4 -0.4211010014 Kentucky Henderson -1.8 0.2211110027 Kentucky Jefferson -2.6 -0.6211110051 Kentucky Jefferson -2.5 -0.9211111021 Kentucky Jefferson -2.2 -0.6211130001 Kentucky Jessamine -2.3 -0.3211170007 Kentucky Kenton -2.3 -0.7211390003 Kentucky Livingston -1.9 0.0211451024 Kentucky McCracken -1.9 -0.2211490001 Kentucky McLean -1.9 0.2B-888-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case211850004 Kentucky Oldham -3.2 -0.7211950002 Kentucky Pike -1.9 0.0211990003 Kentucky Pulaski -4.8 -0.5212130004 Kentucky Simpson -2.7 -0.1212210013 Kentucky Trigg -2.0 0.0212270008 Kentucky Warren -2.2 -0.2220050004 Louisiana Ascension -1.9 -0.3220110002 Louisiana Beauregard -1.6 -0.7220150008 Louisiana Bossier -2.7 -0.3220170001 Louisiana Caddo -2.8 -0.4220190002 Louisiana Calcasieu -1.8 -0.6220190008 Louisiana Calcasieu -1.3 -0.4220190009 Louisiana Calcasieu -2.1 -0.7220330003 Louisiana East Baton Rouge -1.8 -0.4220330009 Louisiana East Baton Rouge -1.6 -0.4220330013 Louisiana East Baton Rouge -1.6 -0.2220331001 Louisiana East Baton Rouge -1.4 -0.2220430001 Louisiana Grant -4.9 -3.1220470007 Louisiana Iberville -2.0 -0.5220470009 Louisiana Iberville -1.8 -0.5220470012 Louisiana Iberville -1.8 -0.4220511001 Louisiana Jefferson -2.0 -0.4220550005 Louisiana Lafayette -2.7 -0.7220550007 Louisiana Lafayette -2.1 -0.6220570004 Louisiana Lafourche -1.9 -0.5220630002 Louisiana Livingston -1.8 -0.2220710012 Louisiana Orleans -1.6 -0.4220730004 Louisiana Ouachita -2.7 -0.7220770001 Louisiana Pointe Coupee -1.6 -0.2220870002 Louisiana St. Bernard -1.4 -0.3220890003 Louisiana St. Charles -1.7 -0.4220930002 Louisiana St. James -1.6 -0.4220950002 Louisiana St. John the Baptist -1.5 -0.4B-898-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case221010003 Louisiana St. Mary -2.2 -0.5221210001 Louisiana West Baton Rouge -1.6 -0.3230050027 Maine Cumberland -1.7 0.0230052003 Maine Cumberland -2.1 0.0230090102 Maine Hancock -1.9 0.0230090103 Maine Hancock -1.8 0.0230090301 Maine Hancock -1.7 0.0230112005 Maine Kennebec -1.8 0.0230130004 Maine Knox -2.0 0.0230173001 Maine Oxford -1.6 0.1230194008 Maine Penobscot -1.7 0.0230230004 Maine Sagadahoc -1.9 0.0230310038 Maine York -2.2 0.0230312002 Maine York -2.1 0.0230313002 Maine York -2.1 0.0240030014 Maryland Anne Arundel -2.7 -0.1240051007 Maryland Baltimore -1.7 -0.1240053001 Maryland Baltimore -1.7 -0.1240090011 Maryland Calvert -2.2 -0.1240130001 Maryland Carroll -2.6 -0.1240150003 Maryland Cecil -2.3 -0.1240170010 Maryland Charles -2.7 -0.1240210037 Maryland Frederick -2.5 0.0240230002 Maryland Garrett -2.3 -0.8240251001 Maryland Harford -2.0 -0.1240259001 Maryland Harford -1.9 -0.1240290002 Maryland Kent -2.0 -0.1240313001 Maryland Montgomery -2.0 -0.1240330030 Maryland Prince George's -2.3 -0.1240338003 Maryland Prince George's -2.7 -0.2240430009 Maryland Washington -2.4 -0.1250010002 Massachusetts Barnstable -2.0 0.0250034002 Massachusetts Berkshire -2.2 -0.1B-908-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case250051002 Massachusetts Bristol -2.0 -0.1250070001 Massachusetts Dukes -1.9 0.0250092006 Massachusetts Essex -1.8 0.1250094004 Massachusetts Essex -2.1 0.1250095005 Massachusetts Essex -2.2 0.0250130008 Massachusetts Hampden -2.6 -0.1250150103 Massachusetts Hampshire -2.2 0.0250154002 Massachusetts Hampshire -2.4 0.0250170009 Massachusetts Middlesex -2.4 0.0250171102 Massachusetts Middlesex -2.3 -0.1250213003 Massachusetts Norfolk -2.3 0.0250250041 Massachusetts Suffolk -2.0 0.0250250042 Massachusetts Suffolk -1.6 0.0250270015 Massachusetts Worcester -2.4 -0.1260050003 Michigan Allegan -2.6 -0.5260190003 Michigan Benzie -2.4 -0.4260210014 Michigan Berrien -2.3 -0.4260270003 Michigan Cass -2.7 -0.6260370001 Michigan Clinton -2.5 -0.3260490021 Michigan Genesee -2.4 -0.3260492001 Michigan Genesee -2.3 -0.3260630007 Michigan Huron -1.9 -0.2260650012 Michigan Ingham -2.6 -0.3260770008 Michigan Kalamazoo -2.4 -0.4260810020 Michigan Kent -2.7 -0.5260810022 Michigan Kent -2.8 -0.5260890001 Michigan Leelanau -2.1 -0.4260910007 Michigan Lenawee -2.2 -0.5260990009 Michigan Macomb -1.8 -0.3260991003 Michigan Macomb -1.5 -0.1261050007 Michigan Mason -2.5 -0.6261130001 Michigan Missaukee -2.3 -0.6261210039 Michigan Muskegon -2.4 -0.4B-918-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case261250001 Michigan Oakland -1.4 -0.3261390005 Michigan Ottawa -2.6 -0.5261470005 Michigan St. Clair -2.3 -0.3261530001 Michigan Schoolcraft -2.2 -0.3261610008 Michigan Washtenaw -1.7 -0.3261630001 Michigan Wayne -1.6 -0.3261630016 Michigan Wayne -1.7 -0.3261630019 Michigan Wayne -1.7 -0.3270031002 Minnesota Anoka -1.2 -0.7280330002 Mississippi DeSoto -3.0 -0.3280450001 Mississippi Hancock -3.3 -1.3280470008 Mississippi Harrison -5.4 -3.5280470009 Mississippi Harrison -3.7 -2.3280490010 Mississippi Hinds -3.1 -0.3280590006 Mississippi Jackson -4.6 -2.9280590007 Mississippi Jackson -5.3 -3.8280750003 Mississippi Lauderdale -3.1 -0.2280810005 Mississippi Lee -3.0 -0.1290370003 Missouri Cass -4.4 -3.1290390001 Missouri Cedar -3.9 -2.2290470003 Missouri Clay -4.1 -2.3290470005 Missouri Clay -3.9 -2.2290470006 Missouri Clay -3.8 -2.0290490001 Missouri Clinton -4.0 -2.1290770036 Missouri Greene -2.7 -1.1290990012 Missouri Jefferson -2.2 -0.3291130003 Missouri Lincoln -2.6 -0.4291370001 Missouri Monroe -2.4 -0.9291570001 Missouri Perry -2.0 -0.1291650023 Missouri Platte -3.2 -1.7291831002 Missouri Saint Charles -2.7 -0.7291831004 Missouri Saint Charles -2.6 -0.4291860005 Missouri Sainte Genevieve -2.5 -0.5B-928-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case291890004 Missouri Saint Louis -1.9 -0.4291890005 Missouri Saint Louis -2.5 -0.4291890006 Missouri Saint Louis -2.1 -0.4291890014 Missouri Saint Louis -2.3 -0.4295100085 Missouri St. Louis City -2.1 -0.6295100086 Missouri St. Louis City -2.2 -0.6310550028 Nebraska Douglas -2.0 -1.1310550032 Nebraska Douglas -2.1 -1.0310550035 Nebraska Douglas -2.2 -1.1311090016 Nebraska Lancaster -1.8 -0.7330012004 New Hampshire Belknap -2.2 0.0330050007 New Hampshire Cheshire -2.1 -0.1330074001 New Hampshire Coos -2.0 0.0330074002 New Hampshire Coos -1.6 0.0330090010 New Hampshire Grafton -2.0 0.0330110020 New Hampshire Hillsborough -2.2 0.0330111011 New Hampshire Hillsborough -2.5 0.0330115001 New Hampshire Hillsborough -2.3 0.0330131007 New Hampshire Merrimack -2.2 -0.1330150014 New Hampshire Rockingham -2.1 0.0330150016 New Hampshire Rockingham -2.1 0.0330190003 New Hampshire Sullivan -2.0 0.0340010005 New Jersey Atlantic -2.1 -0.1340030005 New Jersey Bergen -1.5 -0.1340070003 New Jersey Camden -1.4 0.0340071001 New Jersey Camden -2.3 -0.1340110007 New Jersey Cumberland -2.2 -0.1340150002 New Jersey Gloucester -1.9 -0.1340170006 New Jersey Hudson -1.6 -0.1340190001 New Jersey Hunterdon -2.8 -0.1340210005 New Jersey Mercer -2.1 0.0340230011 New Jersey Middlesex -2.4 0.0340250005 New Jersey Monmouth -2.1 -0.1B-938-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case340273001 New Jersey Morris -2.4 -0.1340290006 New Jersey Ocean -2.6 -0.1340315001 New Jersey Passaic -1.8 0.0350130008 New Mexico Dona Ana -0.4 0.0350130017 New Mexico Dona Ana -0.6 0.0350130021 New Mexico Dona Ana -0.6 0.0350130022 New Mexico Dona Ana -0.7 -0.1350450009 New Mexico San Juan -0.5 0.0350451005 New Mexico San Juan -0.5 0.0360010012 New York Albany -2.0 0.0360050110 New York Bronx -1.4 -0.1360050133 New York Bronx -1.2 -0.2360130006 New York Chautauqua -2.1 -0.2360130011 New York Chautauqua -2.0 -0.3360150003 New York Chemung -1.8 -0.2360270007 New York Dutchess -2.0 -0.1360290002 New York Erie -2.1 -0.2360410005 New York Hamilton -1.6 -0.2360430005 New York Herkimer -1.3 -0.2360450002 New York Jefferson -1.6 0.0360530006 New York Madison -1.7 -0.1360551007 New York Monroe -1.7 -0.2360631006 New York Niagara -1.5 -0.1360650004 New York Oneida -1.7 -0.1360671015 New York Onondaga -1.7 -0.1360715001 New York Orange -2.3 0.0360750003 New York Oswego -1.7 -0.2360790005 New York Putnam -2.2 -0.1360810098 New York Queens -1.4 -0.2360810124 New York Queens -1.4 -0.1360830004 New York Rensselaer -2.0 0.0360850067 New York Richmond -1.9 -0.1360910004 New York Saratoga -2.1 0.0B-948-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case360930003 New York Schenectady -1.9 0.0361030002 New York Suffolk -1.5 -0.1361030004 New York Suffolk -2.0 -0.2361030009 New York Suffolk -1.5 -0.1361111005 New York Ulster -2.2 -0.1361173001 New York Wayne -1.5 -0.1361192004 New York Westchester -1.3 -0.1370030004 North Carolina Alexander -2.4 -0.1370110002 North Carolina Avery -2.5 -0.2370210030 North Carolina Buncombe -2.8 -0.2370270003 North Carolina Caldwell -2.8 -0.2370330001 North Carolina Caswell -3.0 -0.2370370004 North Carolina Chatham -2.8 -0.2370510008 North Carolina Cumberland -3.1 -0.2370511003 North Carolina Cumberland -3.1 -0.2370590002 North Carolina Davie -2.9 -0.3370630013 North Carolina Durham -3.1 -0.1370650099 North Carolina Edgecombe -3.0 -0.3370670022 North Carolina Forsyth -2.6 -0.2370670028 North Carolina Forsyth -2.5 -0.2370670030 North Carolina Forsyth -2.7 -0.3370671008 North Carolina Forsyth -2.9 -0.3370690001 North Carolina Franklin -3.4 -0.1370750001 North Carolina Graham -3.4 -0.4370770001 North Carolina Granville -3.3 -0.1370810011 North Carolina Guilford -3.1 -0.1370810013 North Carolina Guilford -3.4 -0.2370870004 North Carolina Haywood -2.6 -0.2370870035 North Carolina Haywood -3.1 -0.2370870036 North Carolina Haywood -2.7 -0.2370990005 North Carolina Jackson -2.9 -0.3371010002 North Carolina Johnston -3.2 -0.2371070004 North Carolina Lenoir -3.0 -0.7B-958-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case371090004 North Carolina Lincoln -2.5 -0.2371170001 North Carolina Martin -1.7 0.0371190041 North Carolina Mecklenburg -2.8 -0.2371191005 North Carolina Mecklenburg -2.5 -0.2371191009 North Carolina Mecklenburg -3.1 -0.2371290002 North Carolina New Hanover -2.1 -0.2371450003 North Carolina Person -1.9 0.1371470099 North Carolina Pitt -3.1 -0.6371570099 North Carolina Rockingham -3.0 -0.3371590021 North Carolina Rowan -3.2 -0.2371590022 North Carolina Rowan -3.2 -0.2371730002 North Carolina Swain -2.9 -0.3371790003 North Carolina Union -2.9 -0.1371830014 North Carolina Wake -3.2 -0.1371830016 North Carolina Wake -3.2 -0.1371990003 North Carolina Yancey -2.9 -0.3390030002 Ohio Allen -2.3 -0.1390071001 Ohio Ashtabula -2.5 -0.4390170004 Ohio Butler -2.6 -0.6390171004 Ohio Butler -2.7 -0.5390230001 Ohio Clark -2.6 -0.4390230003 Ohio Clark -2.3 -0.3390250022 Ohio Clermont -2.9 -0.9390271002 Ohio Clinton -3.1 -0.8390350034 Ohio Cuyahoga -1.9 -0.3390350064 Ohio Cuyahoga -2.0 -0.3390355002 Ohio Cuyahoga -2.1 -0.3390410002 Ohio Delaware -2.7 -0.2390490028 Ohio Franklin -2.3 -0.3390490029 Ohio Franklin -2.7 -0.3390490037 Ohio Franklin -2.4 -0.3390490081 Ohio Franklin -2.6 -0.3390550004 Ohio Geauga -2.5 -0.4B-968-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case390570006 Ohio Greene -2.6 -0.5390610006 Ohio Hamilton -2.6 -0.6390610010 Ohio Hamilton -2.4 -0.8390610040 Ohio Hamilton -2.4 -0.7390810017 Ohio Jefferson -2.0 -0.6390830002 Ohio Knox -2.7 -0.3390850003 Ohio Lake -2.4 -0.4390853002 Ohio Lake -2.3 -0.4390870006 Ohio Lawrence -1.6 -0.2390870011 Ohio Lawrence -1.5 -0.1390890005 Ohio Licking -2.8 -0.3390930018 Ohio Lorain -2.2 -0.4390950024 Ohio Lucas -2.0 -0.4390950027 Ohio Lucas -2.0 -0.4390950034 Ohio Lucas -2.3 -0.5390950081 Ohio Lucas -2.2 -0.4390970007 Ohio Madison -2.6 -0.4390990013 Ohio Mahoning -2.3 -0.6391030003 Ohio Medina -2.6 -0.4391090005 Ohio Miami -2.5 -0.3391130037 Ohio Montgomery -2.3 -0.4391331001 Ohio Portage -2.6 -0.3391351001 Ohio Preble -2.6 -0.6391510016 Ohio Stark -2.4 -0.3391510022 Ohio Stark -2.3 -0.4391514005 Ohio Stark -2.3 -0.3391530020 Ohio Summit -2.7 -0.3391550009 Ohio Trumbull -2.5 -0.5391550011 Ohio Trumbull -2.4 -0.6391650007 Ohio Warren -3.0 -0.6391670004 Ohio Washington -2.9 -1.5391730003 Ohio Wood -2.2 -0.4400170101 Oklahoma Canadian -3.2 -0.6B-978-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case400219002 Oklahoma Cherokee -6.4 -4.8400270049 Oklahoma Cleveland -3.3 -0.9400310647 Oklahoma Comanche -3.0 -0.5400370144 Oklahoma Creek -4.1 -2.0400719010 Oklahoma Kay -5.0 -2.9400871073 Oklahoma McClain -3.2 -0.8400979014 Oklahoma Mayes -5.7 -4.3401090033 Oklahoma Oklahoma -2.9 -0.9401090096 Oklahoma Oklahoma -3.5 -1.3401091037 Oklahoma Oklahoma -3.4 -0.5401159004 Oklahoma Ottawa -4.9 -3.4401210415 Oklahoma Pittsburg -3.3 -1.6401430137 Oklahoma Tulsa -4.2 -1.8401430174 Oklahoma Tulsa -3.9 -2.0401430178 Oklahoma Tulsa -3.9 -2.0401431127 Oklahoma Tulsa -4.0 -1.7420010002 Pennsylvania Adams -2.2 -0.1420030008 Pennsylvania Allegheny -1.5 -0.4420030010 Pennsylvania Allegheny -1.6 -0.5420030067 Pennsylvania Allegheny -1.7 -0.4420031005 Pennsylvania Allegheny -2.3 -0.8420050001 Pennsylvania Armstrong -2.4 -0.7420070002 Pennsylvania Beaver -2.0 -0.6420070005 Pennsylvania Beaver -1.9 -0.5420070014 Pennsylvania Beaver -1.7 -0.5420110009 Pennsylvania Berks -2.2 -0.3420130801 Pennsylvania Blair -2.0 -0.5420170012 Pennsylvania Bucks -2.0 -0.1420210011 Pennsylvania Cambria -2.2 -0.5420270100 Pennsylvania Centre -2.3 -0.3420290100 Pennsylvania Chester -2.2 -0.1420334000 Pennsylvania Clearfield -2.2 -0.6420430401 Pennsylvania Dauphin -2.3 -0.6B-988-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case420431100 Pennsylvania Dauphin -2.3 -0.5420450002 Pennsylvania Delaware -1.7 0.0420490003 Pennsylvania Erie -2.1 -0.2420550001 Pennsylvania Franklin -2.3 -0.1420590002 Pennsylvania Greene -3.2 -2.1420630004 Pennsylvania Indiana -2.3 -0.7420690101 Pennsylvania Lackawanna -2.1 -0.2420692006 Pennsylvania Lackawanna -2.2 -0.2420710007 Pennsylvania Lancaster -2.3 -0.3420730015 Pennsylvania Lawrence -2.1 -0.6420770004 Pennsylvania Lehigh -2.2 0.0420791100 Pennsylvania Luzerne -2.0 -0.2420791101 Pennsylvania Luzerne -2.2 -0.2420810100 Pennsylvania Lycoming -2.2 -0.2420850100 Pennsylvania Mercer -2.3 -0.6420910013 Pennsylvania Montgomery -1.7 -0.1420950025 Pennsylvania Northampton -2.2 0.0420958000 Pennsylvania Northampton -2.2 0.0420990301 Pennsylvania Perry -2.4 -0.3421010004 Pennsylvania Philadelphia -1.2 0.0421010014 Pennsylvania Philadelphia -1.1 0.0421010024 Pennsylvania Philadelphia -1.7 0.0421010136 Pennsylvania Philadelphia -1.3 -0.1421174000 Pennsylvania Tioga -2.1 -0.2421250005 Pennsylvania Washington -1.5 -0.3421250200 Pennsylvania Washington -1.6 -0.3421255001 Pennsylvania Washington -2.0 -0.5421290006 Pennsylvania Westmoreland -1.9 -0.6421290008 Pennsylvania Westmoreland -2.0 -0.5421330008 Pennsylvania York -2.3 -0.4440030002 Rhode Island Kent -2.2 -0.1440071010 Rhode Island Providence -2.2 0.0440090007 Rhode Island Washington -2.1 -0.1B-998-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case450010001 South CarolinaAbbeville -3.4 -0.4450030003 South Carolina Aiken -3.4 -0.3450070003 South Carolina Anderson -3.2 -0.3450110001 South Carolina Barnwell -3.3 -0.2450150002 South Carolina Berkeley -2.2 -0.4450190046 South Carolina Charleston -2.7 -0.5450210002 South Carolina Cherokee -2.8 -0.1450230002 South Carolina Chester -2.7 -0.1450250001 South Carolina Chesterfield -2.6 -0.2450290002 South Carolina Colleton -3.2 -0.6450310003 South Carolina Darlington -2.8 -0.4450370001 South Carolina Edgefield -3.2 -0.3450730001 South Carolina Oconee -3.3 -0.3450770002 South Carolina Pickens -3.5 -0.3450790007 South Carolina Richland -3.8 -0.4450790021 South Carolina Richland -3.3 -0.3450791001 South Carolina Richland -3.8 -0.3450830009 South Carolina Spartanburg -3.0 -0.1450870001 South Carolina Union -2.8 -0.2450890001 South Carolina Williamsburg -2.4 -0.3450910006 South Carolina York -2.8 -0.1470010101 Tennessee Anderson -3.1 -0.1470090101 Tennessee Blount -3.6 -0.2470090102 Tennessee Blount -2.9 -0.3470370011 Tennessee Davidson -2.5 -0.2470370026 Tennessee Davidson -2.9 -0.2470651011 Tennessee Hamilton -4.1 -0.3470654003 Tennessee Hamilton -4.0 -0.2470890002 Tennessee Jefferson -3.5 -0.2470930021 Tennessee Knox -3.3 -0.1470931020 Tennessee Knox -3.4 -0.1471050109 Tennessee Loudon -3.2 -0.1471210104 Tennessee Meigs -4.0 -0.2B-1008-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case471490101 Tennessee Rutherford -3.1 -0.2471550101 Tennessee Sevier -3.1 -0.2471550102 Tennessee Sevier -3.4 -0.4471570021 Tennessee Shelby -2.8 -0.3471571004 Tennessee Shelby -3.0 -0.3471632002 Tennessee Sullivan -1.9 -0.1471632003 Tennessee Sullivan -1.8 -0.1471650007 Tennessee Sumner -3.2 -0.3471650101 Tennessee Sumner -3.2 -0.3471870106 Tennessee Williamson -3.1 -0.2471890103 Tennessee Wilson -3.4 -0.4480290032 Texas Bexar -2.7 -0.4480290052 Texas Bexar -2.7 -0.5480391004 Texas Brazoria -2.2 -0.4480391016 Texas Brazoria -1.9 -0.3480850005 Texas Collin -3.2 -0.2481130069 Texas Dallas -2.7 -0.3481130075 Texas Dallas -2.9 -0.3481130087 Texas Dallas -2.5 -0.2481133003 Texas Dallas -2.5 -0.3481210034 Texas Denton -3.6 -0.3481390015 Texas Ellis -3.3 -0.4481410029 Texas El Paso -0.4 0.0481410037 Texas El Paso -0.7 0.0481410044 Texas El Paso -0.6 0.0481410055 Texas El Paso -0.7 0.0481410057 Texas El Paso -0.5 0.0481410058 Texas El Paso -0.6 0.0481670014 Texas Galveston -1.8 -0.3481830001 Texas Gregg -1.9 -0.4482010024 Texas Harris -1.4 -0.3482010026 Texas Harris -1.8 -0.3482010029 Texas Harris -2.4 -0.3B-1018-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case482010046 Texas Harris -1.3 -0.3482010047 Texas Harris -1.2 -0.2482010051 Texas Harris -2.1 -0.3482010055 Texas Harris -2.3 -0.4482010062 Texas Harris -1.9 -0.4482010066 Texas Harris -1.3 -0.2482010070 Texas Harris -1.3 -0.2482010075 Texas Harris -1.3 -0.3482011015 Texas Harris -1.9 -0.3482011034 Texas Harris -1.3 -0.4482011035 Texas Harris -1.3 -0.4482011039 Texas Harris -2.0 -0.4482011050 Texas Harris -1.8 -0.4482030002 Texas Harrison -2.8 -0.4482210001 Texas Hood -3.7 -0.4482311006 Texas Hunt -2.4 -0.3482450009 Texas Jefferson -2.3 -0.7482450011 Texas Jefferson -2.2 -0.6482450018 Texas Jefferson -2.3 -0.7482450022 Texas Jefferson -2.4 -0.7482450101 Texas Jefferson -2.2 -0.6482450628 Texas Jefferson -2.1 -0.5482510003 Texas Johnson -3.6 -0.4482570005 Texas Kaufman -2.6 -0.4483390078 Texas Montgomery -2.4 -0.1483550025 Texas Nueces -1.3 -0.2483611001 Texas Orange -2.3 -0.8483611100 Texas Orange -1.8 -0.5483670081 Texas Parker -3.7 -0.3483970001 Texas Rockwall -2.8 -0.4484230007 Texas Smith -2.4 -0.3484390075 Texas Tarrant -3.6 -0.3484391002 Texas Tarrant -3.2 -0.2B-1028-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case484392003 Texas Tarrant -3.4 -0.3484393009 Texas Tarrant -3.4 -0.3484393011 Texas Tarrant -2.9 -0.3484530014 Texas Travis -2.9 -0.4484530020 Texas Travis -3.0 -0.5484530613 Texas Travis -2.1 -0.4500030004 Vermont Bennington -2.1 -0.1500070007 Vermont Chittenden -1.6 0.0510130020 Virginia Arlington -1.9 -0.1510330001 Virginia Caroline -2.6 0.0510360002 Virginia Charles -2.1 -0.1510410004 Virginia Chesterfield -2.0 -0.1510590005 Virginia Fairfax -2.3 -0.1510590018 Virginia Fairfax -2.1 -0.2510590030 Virginia Fairfax -1.9 -0.1510591005 Virginia Fairfax -1.9 -0.1510595001 Virginia Fairfax -2.0 -0.1510610002 Virginia Fauquier -2.3 0.0510690010 Virginia Frederick -2.0 0.0510850003 Virginia Hanover -2.3 0.0510870014 Virginia Henrico -2.3 -0.1511071005 Virginia Loudoun -2.3 -0.1511130003 Virginia Madison -2.3 -0.1511390004 Virginia Page -2.1 -0.1511530009 Virginia Prince William -2.3 0.0511611004 Virginia Roanoke -2.7 -0.2511630003 Virginia Rockbridge -2.5 -0.2511790001 Virginia Stafford -2.6 -0.1511970002 Virginia Wythe -2.7 -0.2515100009 Virginia Alexandria City -1.9 -0.2516500004 Virginia Hampton City -1.3 -0.1518000004 Virginia Suffolk City -1.2 -0.1518000005 Virginia Suffolk City -2.2 -0.1B-1038-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case540030003 West Virginia Berkeley -2.2 0.0540110006 West Virginia Cabell -1.8 -0.2540291004 West Virginia Hancock -1.9 -0.7540390010 West Virginia Kanawha -1.9 -0.2540610003 West Virginia Monongalia -3.1 -1.9540690010 West Virginia Ohio -2.5 -1.2541071002 West Virginia Wood -2.2 -0.9550090026 Wisconsin Brown -2.1 -0.4550210015 Wisconsin Columbia -2.2 -0.6550250041 Wisconsin Dane -2.1 -0.5550270007 Wisconsin Dodge -2.3 -0.4550290004 Wisconsin Door -2.7 -0.4550370001 Wisconsin Florence -1.8 -0.4550390006 Wisconsin Fond du Lac -2.1 -0.3550410007 Wisconsin Forest -2.1 -0.6550550002 Wisconsin Jefferson -2.4 -0.4550590019 Wisconsin Kenosha -1.7 -0.3550610002 Wisconsin Kewaunee -2.4 -0.4550710007 Wisconsin Manitowoc -2.4 -0.3550790010 Wisconsin Milwaukee -1.7 -0.2550790026 Wisconsin Milwaukee -1.8 -0.2550790041 Wisconsin Milwaukee -2.1 -0.3550790044 Wisconsin Milwaukee -1.2 -0.2550790085 Wisconsin Milwaukee -2.1 -0.3550870009 Wisconsin Outagamie -2.1 -0.4550890008 Wisconsin Ozaukee -2.1 -0.4550890009 Wisconsin Ozaukee -2.4 -0.3551010017 Wisconsin Racine -1.8 -0.3551050024 Wisconsin Rock -2.4 -0.5551091002 Wisconsin St. Croix -2.2 -0.9551110007 Wisconsin Sauk -1.9 -0.6551170006 Wisconsin Sheboygan -2.5 -0.3551270005 Wisconsin Walworth -2.3 -0.3B-1048-Hour Ozone (ppb)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case551310009 Wisconsin Washington -2.2 -0.3551330017 Wisconsin Waukesha -2.2 -0.3551330027 Wisconsin Waukesha -2.1 -0.3B-105Differences in Annual PM2.5 Design Values (μg/m3) by Site:2014 Remedy Scenario Compared to the2012 Base Case and the 2014 Base CaseAnnual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case10030010 Alabama Baldwin -1.66 -1.3110270001 Alabama Clay -2.05 -1.3710331002 Alabama Colbert -2.45 -1.9710491003 Alabama DeKalb -2.37 -1.7610530002 Alabama Escambia -1.61 -1.2710550010 Alabama Etowah -2.35 -1.6610690003 Alabama Houston -1.50 -1.1310730023 Alabama Jefferson -2.20 -1.5310731005 Alabama Jefferson -2.14 -1.5410731009 Alabama Jefferson -2.18 -1.6410731010 Alabama Jefferson -2.33 -1.6210732003 Alabama Jefferson -2.00 -1.4310732006 Alabama Jefferson -2.03 -1.4410735002 Alabama Jefferson -2.18 -1.5310735003 Alabama Jefferson -2.37 -1.7210890014 Alabama Madison -2.72 -2.1210970002 Alabama Mobile -1.74 -1.3110970003 Alabama Mobile -1.71 -1.2910972005 Alabama Mobile -1.63 -1.2611010007 Alabama Montgomery -1.86 -1.3411030011 Alabama Morgan -2.49 -1.9311130001 Alabama Russell -2.10 -1.4211170006 Alabama Shelby -2.14 -1.5211190002 Alabama Sumter -2.00 -1.5411210002 Alabama Talladega -2.14 -1.49B-106Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case11250004 Alabama Tuscaloosa -2.19 -1.6311270002 Alabama Walker -2.42 -1.8050010011 Arkansas Arkansas -1.97 -1.5350030005 Arkansas Ashley -1.59 -1.2450350005 Arkansas Crittenden -2.60 -1.9950450002 Arkansas Faulkner -1.82 -1.3850510003 Arkansas Garland -1.71 -1.3150930007 Arkansas Mississippi -2.65 -2.1451070001 Arkansas Phillips -2.26 -1.7551130002 Arkansas Polk -1.36 -1.0651150003 Arkansas Pope -1.64 -1.2651190007 Arkansas Pulaski -1.92 -1.4551191004 Arkansas Pulaski -1.92 -1.4551191005 Arkansas Pulaski -1.89 -1.4351390006 Arkansas Union -1.60 -1.2451450001 Arkansas White -1.82 -1.4080010006 Colorado Adams -0.09 0.1080050005 Colorado Arapahoe -0.10 0.0680130003 Colorado Boulder -0.07 0.0480130012 Colorado Boulder -0.05 0.0480290004 Colorado Delta -0.11 0.0080310002 Colorado Denver -0.08 0.1080310023 Colorado Denver -0.09 0.0980390001 Colorado Elbert -0.04 0.0180410008 Colorado El Paso -0.08 0.0280410011 Colorado El Paso -0.08 0.0380690009 Colorado Larimer -0.06 0.0280770017 Colorado Mesa -0.12 0.0181010012 Colorado Pueblo -0.09 -0.01B-107Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case81130004 Colorado San Miguel -0.02 0.0081230006 Colorado Weld -0.08 0.0381230008 Colorado Weld -0.08 0.0490010010 Connecticut Fairfield -1.24 -1.0690011123 Connecticut Fairfield -1.23 -1.0590013005 Connecticut Fairfield -1.25 -1.0890019003 Connecticut Fairfield -1.22 -1.0690031003 Connecticut Hartford -1.00 -0.8390050005 Connecticut Litchfield -1.00 -0.8990090026 Connecticut New Haven -1.20 -1.0290090027 Connecticut New Haven -1.22 -1.0390091123 Connecticut New Haven -1.22 -1.0190092008 Connecticut New Haven -1.16 -0.9990092123 Connecticut New Haven -1.17 -0.9890113002 Connecticut New London -0.92 -0.77100010002 Delaware Kent -1.64 -1.51100010003 Delaware Kent -1.61 -1.46100031003 Delaware New Castle -1.69 -1.50100031007 Delaware New Castle -1.68 -1.54100031012 Delaware New Castle -1.68 -1.52100032004 Delaware New Castle -1.73 -1.53100051002 Delaware Sussex -1.65 -1.51110010041District OfColumbiaDistrict of Columbia -2.00 -1.82110010042District OfColumbiaDistrict of Columbia -1.97 -1.80110010043District OfColumbiaDistrict of Columbia -2.08 -1.91120010023 Florida Alachua -1.21 -0.98120010024 Florida Alachua -1.18 -0.95B-108Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case120051004 Florida Bay -1.24 -0.94120090007 Florida Brevard -0.81 -0.64120111002 Florida Broward -0.50 -0.37120112004 Florida Broward -0.51 -0.38120113002 Florida Broward -0.50 -0.37120170005 Florida Citrus -0.98 -0.79120310098 Florida Duval -1.09 -0.85120310099 Florida Duval -1.02 -0.79120330004 Florida Escambia -1.33 -1.07120570030 Florida Hillsborough -0.64 -0.45120573002 Florida Hillsborough -0.60 -0.42120710005 Florida Lee -0.64 -0.52120730012 Florida Leon -1.26 -0.95120814012 Florida Manatee -0.62 -0.52120830003 Florida Marion -1.04 -0.81120861016 Florida Miami-Dade -0.53 -0.37120866001 Florida Miami-Dade -0.47 -0.38120951004 Florida Orange -0.98 -0.71120952002 Florida Orange -0.97 -0.71120990009 Florida Palm Beach -0.57 -0.43120992005 Florida Palm Beach -0.56 -0.42121030018 Florida Pinellas -0.62 -0.49121031009 Florida Pinellas -0.64 -0.49121056006 Florida Polk -0.64 -0.50121111002 Florida St. Lucie -0.70 -0.58121150013 Florida Sarasota -0.65 -0.54121171002 Florida Seminole -1.00 -0.73121275002 Florida Volusia -1.10 -0.85130210007 Georgia Bibb -2.16 -1.35B-109Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case130210012 Georgia Bibb -2.12 -1.29130510017 Georgia Chatham -1.47 -1.06130510091 Georgia Chatham -1.48 -1.05130590002 Georgia Clarke -2.32 -1.43130630091 Georgia Clayton -2.34 -1.39130670003 Georgia Cobb -2.22 -1.45130670004 Georgia Cobb -2.27 -1.41130890002 Georgia DeKalb -2.36 -1.39130892001 Georgia DeKalb -2.32 -1.42130950007 Georgia Dougherty -1.73 -1.31131150005 Georgia Floyd -2.18 -1.58131210032 Georgia Fulton -2.35 -1.39131210039 Georgia Fulton -2.36 -1.38131270006 Georgia Glynn -1.22 -0.94131350002 Georgia Gwinnett -2.29 -1.44131390003 Georgia Hall -2.24 -1.48131530001 Georgia Houston -1.99 -1.31131850003 Georgia Lowndes -1.25 -0.93132150001 Georgia Muscogee -2.09 -1.43132150008 Georgia Muscogee -2.03 -1.36132150011 Georgia Muscogee -1.89 -1.29132230003 Georgia Paulding -2.25 -1.52132450005 Georgia Richmond -1.84 -1.27132450091 Georgia Richmond -1.87 -1.29132950002 Georgia Walker -2.58 -1.95133030001 Georgia Washington -2.23 -1.31133190001 Georgia Wilkinson -2.27 -1.32170010006 Illinois Adams -1.65 -1.14170190004 Illinois Champaign -2.31 -1.76B-110Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case170191001 Illinois Champaign -2.34 -1.77170310022 Illinois Cook -1.67 -1.19170310050 Illinois Cook -1.61 -1.11170310052 Illinois Cook -1.57 -1.05170310057 Illinois Cook -1.60 -1.08170310076 Illinois Cook -1.65 -1.11170312001 Illinois Cook -1.56 -1.08170313301 Illinois Cook -1.63 -1.10170314007 Illinois Cook -1.61 -1.08170314201 Illinois Cook -1.62 -1.09170316005 Illinois Cook -1.58 -1.06170434002 Illinois DuPage -1.64 -1.08170831001 Illinois Jersey -2.43 -1.79170890003 Illinois Kane -1.69 -1.11170890007 Illinois Kane -1.64 -1.08170971007 Illinois Lake -1.56 -1.05171110001 Illinois McHenry -1.59 -1.04171132003 Illinois McLean -2.07 -1.42171150013 Illinois Macon -2.26 -1.65171191007 Illinois Madison -2.34 -1.68171192009 Illinois Madison -2.49 -1.86171193007 Illinois Madison -2.44 -1.83171430037 Illinois Peoria -2.15 -1.19171570001 Illinois Randolph -2.49 -1.86171613002 Illinois Rock Island -1.53 -1.03171630010 Illinois Saint Clair -2.30 -1.65171634001 Illinois Saint Clair -2.29 -1.65171670012 Illinois Sangamon -2.22 -1.64171971002 Illinois Will -1.72 -1.18B-111Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case171971011 Illinois Will -1.81 -1.32172010013 Illinois Winnebago -1.42 -0.93180030004 Indiana Allen -1.87 -1.50180030014 Indiana Allen -1.86 -1.49180190006 Indiana Clark -3.59 -3.09180350006 Indiana Delaware -2.78 -2.35180372001 Indiana Dubois -3.96 -3.39180431004 Indiana Floyd -3.63 -3.17180650003 Indiana Henry -2.98 -2.54180670003 Indiana Howard -2.58 -2.10180830004 Indiana Knox -3.54 -2.93180890006 Indiana Lake -1.68 -1.20180890027 Indiana Lake -1.73 -1.26180891003 Indiana Lake -1.69 -1.23180892004 Indiana Lake -1.67 -1.20180892010 Indiana Lake -1.66 -1.18180910011 Indiana LaPorte -1.68 -1.25180910012 Indiana LaPorte -1.75 -1.31180950009 Indiana Madison -2.94 -2.49180970042 Indiana Marion -3.38 -2.90180970078 Indiana Marion -3.33 -2.84180970079 Indiana Marion -3.25 -2.76180970081 Indiana Marion -3.33 -2.83180970083 Indiana Marion -3.33 -2.83181270020 Indiana Porter -1.71 -1.26181270024 Indiana Porter -1.74 -1.27181410014 Indiana St. Joseph -1.40 -1.06181411008 Indiana St. Joseph -1.38 -1.04181412004 Indiana St. Joseph -1.38 -1.04B-112Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case181470009 Indiana Spencer -3.96 -3.40181570008 Indiana Tippecanoe -2.57 -2.05181630006 Indiana Vanderburgh -3.16 -2.63181630012 Indiana Vanderburgh -3.16 -2.61181630016 Indiana Vanderburgh -3.17 -2.63181670018 Indiana Vigo -3.02 -2.46181670023 Indiana Vigo -3.05 -2.49190130008 Iowa Black Hawk -1.03 -0.72190450021 Iowa Clinton -1.44 -0.93191032001 Iowa Johnson -1.21 -0.85191130037 Iowa Linn -1.12 -0.78191370002 Iowa Montgomery -0.90 -0.67191390015 Iowa Muscatine -1.38 -1.00191471002 Iowa Palo Alto -0.75 -0.54191530030 Iowa Polk -0.96 -0.68191532510 Iowa Polk -0.93 -0.66191532520 Iowa Polk -0.95 -0.66191550009 Iowa Pottawattamie -0.81 -0.62191630015 Iowa Scott -1.52 -1.02191630018 Iowa Scott -1.50 -1.00191630019 Iowa Scott -1.49 -0.99191770006 Iowa Van Buren -1.04 -0.74191930017 Iowa Woodbury -0.63 -0.51191970004 Iowa Wright -0.92 -0.65200910007 Kansas Johnson -1.02 -0.74200910009 Kansas Johnson -1.15 -0.83200910010 Kansas Johnson -1.02 -0.75201070002 Kansas Linn -1.15 -0.85201730008 Kansas Sedgwick -0.82 -0.59B-113Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case201730009 Kansas Sedgwick -0.83 -0.59201730010 Kansas Sedgwick -0.82 -0.58201770010 Kansas Shawnee -0.90 -0.67201770011 Kansas Shawnee -0.89 -0.66201910002 Kansas Sumner -0.83 -0.61202090021 Kansas Wyandotte -1.11 -0.80202090022 Kansas Wyandotte -1.05 -0.75210130002 Kentucky Bell -2.82 -2.24210190017 Kentucky Boyd -3.19 -2.61210290006 Kentucky Bullitt -3.60 -3.09210370003 Kentucky Campbell -3.44 -2.95210430500 Kentucky Carter -2.88 -2.37210470006 Kentucky Christian -3.83 -3.29210590005 Kentucky Daviess -4.32 -3.77210670012 Kentucky Fayette -3.38 -2.86210670014 Kentucky Fayette -3.37 -2.84210730006 Kentucky Franklin -3.36 -2.87210930006 Kentucky Hardin -3.66 -3.14211010014 Kentucky Henderson -3.31 -2.79211110043 Kentucky Jefferson -3.68 -3.20211110044 Kentucky Jefferson -3.59 -3.11211110048 Kentucky Jefferson -3.62 -3.13211110051 Kentucky Jefferson -3.72 -3.24211170007 Kentucky Kenton -3.44 -2.96211250004 Kentucky Laurel -2.76 -2.24211451004 Kentucky McCracken -3.29 -2.68211510003 Kentucky Madison -3.25 -2.74211930003 Kentucky Perry -2.67 -2.15211950002 Kentucky Pike -2.99 -2.45B-114Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case212270007 Kentucky Warren -3.96 -3.39220171002 Louisiana Caddo -1.46 -1.13220190009 Louisiana Calcasieu -1.16 -0.90220190010 Louisiana Calcasieu -1.17 -0.89220290003 Louisiana Concordia -1.71 -1.31220330009 Louisiana East Baton Rouge -1.36 -0.94220331001 Louisiana East Baton Rouge -1.33 -0.94220470005 Louisiana Iberville -1.43 -0.91220470009 Louisiana Iberville -1.45 -1.07220511001 Louisiana Jefferson -1.48 -1.11220550006 Louisiana Lafayette -1.52 -1.21220730004 Louisiana Ouachita -1.52 -1.17220790002 Louisiana Rapides -1.46 -1.16221050001 Louisiana Tangipahoa -1.61 -1.20221090001 Louisiana Terrebonne -1.48 -1.14221210001 Louisiana West Baton Rouge -1.36 -0.93230010011 Maine Androscoggin -0.47 -0.32230030013 Maine Aroostook -0.31 -0.24230031011 Maine Aroostook -0.31 -0.23230050015 Maine Cumberland -0.53 -0.34230050027 Maine Cumberland -0.52 -0.34230090103 Maine Hancock -0.35 -0.29230110016 Maine Kennebec -0.46 -0.32230172011 Maine Oxford -0.46 -0.33230190002 Maine Penobscot -0.48 -0.36240030014 Maryland Anne Arundel -1.58 -1.56240031003 Maryland Anne Arundel -1.38 -1.48240032002 Maryland Anne Arundel -1.36 -1.48240051007 Maryland Baltimore -1.83 -1.78B-115Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case240053001 Maryland Baltimore -1.56 -1.62240150003 Maryland Cecil -1.69 -1.55240251001 Maryland Harford -1.58 -1.58240313001 Maryland Montgomery -1.84 -1.71240330030 Maryland Prince George's -1.67 -1.60240338003 Maryland Prince George's -1.75 -1.67240430009 Maryland Washington -2.42 -2.15245100006 Maryland Baltimore (City) -1.57 -1.61245100007 Maryland Baltimore (City) -1.72 -1.69245100008 Maryland Baltimore (City) -1.48 -1.58245100049 Maryland Baltimore (City) -1.39 -1.51250035001 Massachusetts Berkshire -0.98 -0.83250051004 Massachusetts Bristol -0.71 -0.64250092006 Massachusetts Essex -0.65 -0.55250095005 Massachusetts Essex -0.64 -0.52250096001 Massachusetts Essex -0.67 -0.54250130008 Massachusetts Hampden -0.92 -0.78250130016 Massachusetts Hampden -0.98 -0.79250132009 Massachusetts Hampden -0.96 -0.78250230004 Massachusetts Plymouth -0.75 -0.63250250002 Massachusetts Suffolk -0.75 -0.59250250027 Massachusetts Suffolk -0.75 -0.60250250042 Massachusetts Suffolk -0.72 -0.59250250043 Massachusetts Suffolk -0.77 -0.59250270016 Massachusetts Worcester -0.88 -0.72250270023 Massachusetts Worcester -0.88 -0.71260050003 Michigan Allegan -1.80 -1.37260170014 Michigan Bay -1.41 -1.07260210014 Michigan Berrien -1.67 -1.27B-116Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case260490021 Michigan Genesee -1.63 -1.29260650012 Michigan Ingham -1.72 -1.34260770008 Michigan Kalamazoo -1.72 -1.34260810020 Michigan Kent -1.57 -1.16260990009 Michigan Macomb -1.70 -1.38261130001 Michigan Missaukee -0.91 -0.65261150005 Michigan Monroe -2.16 -1.75261210040 Michigan Muskegon -1.49 -1.09261250001 Michigan Oakland -1.78 -1.41261390005 Michigan Ottawa -1.63 -1.22261450018 Michigan Saginaw -1.38 -1.05261470005 Michigan St. Clair -1.70 -1.38261610005 Michigan Washtenaw -1.80 -1.45261610008 Michigan Washtenaw -1.79 -1.41261630001 Michigan Wayne -1.85 -1.46261630015 Michigan Wayne -2.04 -1.63261630016 Michigan Wayne -1.82 -1.45261630019 Michigan Wayne -1.78 -1.43261630025 Michigan Wayne -1.88 -1.50261630033 Michigan Wayne -2.14 -1.69261630036 Michigan Wayne -1.96 -1.57270210001 Minnesota Cass -0.30 -0.22270370470 Minnesota Dakota -0.61 -0.41270530050 Minnesota Hennepin -0.58 -0.38270530961 Minnesota Hennepin -0.59 -0.39270530963 Minnesota Hennepin -0.59 -0.39270530965 Minnesota Hennepin -0.57 -0.37270531007 Minnesota Hennepin -0.60 -0.39270532006 Minnesota Hennepin -0.59 -0.39B-117Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case270953051 Minnesota Mille Lacs -0.36 -0.25271095008 Minnesota Olmsted -0.80 -0.56271230866 Minnesota Ramsey -0.61 -0.38271230868 Minnesota Ramsey -0.58 -0.36271230871 Minnesota Ramsey -0.56 -0.36271377001 Minnesota Saint Louis -0.37 -0.20271377550 Minnesota Saint Louis -0.37 -0.23271377551 Minnesota Saint Louis -0.40 -0.23271390505 Minnesota Scott -0.62 -0.42271453052 Minnesota Stearns -0.50 -0.33280010004 Mississippi Adams -1.73 -1.33280110001 Mississippi Bolivar -2.11 -1.63280330002 Mississippi DeSoto -2.51 -1.92280350004 Mississippi Forrest -1.84 -1.40280470008 Mississippi Harrison -1.55 -1.18280490010 Mississippi Hinds -1.85 -1.37280590006 Mississippi Jackson -1.57 -1.17280670002 Mississippi Jones -1.97 -1.49280750003 Mississippi Lauderdale -2.10 -1.58280810005 Mississippi Lee -2.50 -1.92280870001 Mississippi Lowndes -2.32 -1.74281090001 Mississippi Pearl River -1.61 -1.23281490004 Mississippi Warren -1.83 -1.36290190004 Missouri Boone -1.60 -1.14290210005 Missouri Buchanan -0.99 -0.72290370003 Missouri Cass -1.17 -0.86290390001 Missouri Cedar -1.30 -0.99290470005 Missouri Clay -1.12 -0.84290770032 Missouri Greene -1.57 -1.18B-118Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case290950034 Missouri Jackson -1.13 -0.80290990012 Missouri Jefferson -2.12 -1.55291370001 Missouri Monroe -1.67 -1.19291831002 Missouri Saint Charles -2.47 -1.86291860006 Missouri Sainte Genevieve -2.35 -1.70291890004 Missouri Saint Louis -2.15 -1.57291892003 Missouri Saint Louis -2.24 -1.64295100007 Missouri St. Louis City -2.17 -1.57295100085 Missouri St. Louis City -2.28 -1.65295100086 Missouri St. Louis City -2.26 -1.64295100087 Missouri St. Louis City -2.31 -1.66300870307 Montana Rosebud -0.01 0.02301111065 Montana Yellowstone -0.04 0.01310250002 Nebraska Cass -0.82 -0.61310550019 Nebraska Douglas -0.81 -0.63310550052 Nebraska Douglas -0.81 -0.61310790004 Nebraska Hall -0.56 -0.40311090022 Nebraska Lancaster -0.76 -0.55311111002 Nebraska Lincoln -0.31 -0.22311530007 Nebraska Sarpy -0.82 -0.63311570003 Nebraska Scotts Bluff -0.10 -0.04311770002 Nebraska Washington -0.78 -0.59330012004 New Hampshire Belknap -0.62 -0.51330050007 New Hampshire Cheshire -0.84 -0.66330070014 New Hampshire Coos -0.54 -0.41330090010 New Hampshire Grafton -0.67 -0.54330110020 New Hampshire Hillsborough -0.72 -0.58330111015 New Hampshire Hillsborough -0.75 -0.61330115001 New Hampshire Hillsborough -0.56 -0.47B-119Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case330131006 New Hampshire Merrimack -0.72 -0.57330150014 New Hampshire Rockingham -0.56 -0.44330190003 New Hampshire Sullivan -0.75 -0.60340011006 New Jersey Atlantic -1.40 -1.26340030003 New Jersey Bergen -1.28 -1.06340070003 New Jersey Camden -1.58 -1.36340071007 New Jersey Camden -1.60 -1.36340130015 New Jersey Essex -1.33 -1.08340155001 New Jersey Gloucester -1.66 -1.43340171003 New Jersey Hudson -1.31 -1.07340210008 New Jersey Mercer -1.54 -1.32340218001 New Jersey Mercer -1.47 -1.27340230006 New Jersey Middlesex -1.43 -1.22340270004 New Jersey Morris -1.38 -1.19340273001 New Jersey Morris -1.34 -1.18340292002 New Jersey Ocean -1.34 -1.17340310005 New Jersey Passaic -1.32 -1.09340390004 New Jersey Union -1.44 -1.14340390006 New Jersey Union -1.34 -1.08340392003 New Jersey Union -1.37 -1.11340410006 New Jersey Warren -1.61 -1.42350010023 New Mexico Bernalillo -0.14 -0.05350010024 New Mexico Bernalillo -0.14 -0.05350050005 New Mexico Chaves -0.20 -0.15350130017 New Mexico Dona Ana -0.15 -0.10350130025 New Mexico Dona Ana -0.15 -0.11350431003 New Mexico Sandoval -0.11 -0.05350439011 New Mexico Sandoval -0.09 -0.04350450006 New Mexico San Juan -0.03 -0.01B-120Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case350490020 New Mexico Santa Fe -0.07 -0.03360010005 New York Albany -0.99 -0.85360050080 New York Bronx -1.32 -1.07360050083 New York Bronx -1.27 -1.05360050110 New York Bronx -1.27 -1.04360130011 New York Chautauqua -1.81 -1.58360290005 New York Erie -1.60 -1.38360291007 New York Erie -1.69 -1.46360310003 New York Essex -0.73 -0.64360470122 New York Kings -1.31 -1.07360551007 New York Monroe -1.40 -1.22360590008 New York Nassau -1.15 -0.98360610056 New York New York -1.42 -1.14360610062 New York New York -1.36 -1.10360610079 New York New York -1.28 -1.05360610128 New York New York -1.33 -1.08360632008 New York Niagara -1.62 -1.40360671015 New York Onondaga -1.43 -1.28360710002 New York Orange -1.22 -1.07360810124 New York Queens -1.17 -0.97360850055 New York Richmond -1.33 -1.07360850067 New York Richmond -1.15 -0.93360893001 New York St. Lawrence -0.79 -0.69361010003 New York Steuben -1.55 -1.40361030001 New York Suffolk -1.20 -1.04361191002 New York Westchester -1.24 -1.06370010002 North Carolina Alamance -2.18 -1.79370210034 North Carolina Buncombe -2.07 -1.63370330001 North Carolina Caswell -2.17 -1.82B-121Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case370350004 North Carolina Catawba -2.32 -1.87370370004 North Carolina Chatham -2.02 -1.64370510009 North Carolina Cumberland -1.87 -1.47370570002 North Carolina Davidson -2.30 -1.90370610002 North Carolina Duplin -1.67 -1.38370630001 North Carolina Durham -2.07 -1.68370650004 North Carolina Edgecombe -1.97 -1.62370670022 North Carolina Forsyth -2.35 -1.96370710016 North Carolina Gaston -2.08 -1.66370810013 North Carolina Guilford -2.15 -1.78370870010 North Carolina Haywood -1.82 -1.37370990006 North Carolina Jackson -2.10 -1.57371070004 North Carolina Lenoir -1.68 -1.39371110004 North Carolina McDowell -2.15 -1.73371170001 North Carolina Martin -1.68 -1.42371190010 North Carolina Mecklenburg -2.00 -1.61371190041 North Carolina Mecklenburg -2.04 -1.64371190042 North Carolina Mecklenburg -2.04 -1.64371210001 North Carolina Mitchell -2.21 -1.80371230001 North Carolina Montgomery -2.00 -1.60371290002 North Carolina New Hanover -1.46 -1.21371330005 North Carolina Onslow -1.63 -1.36371350007 North Carolina Orange -2.12 -1.71371470005 North Carolina Pitt -1.76 -1.46371550005 North Carolina Robeson -1.73 -1.41371590021 North Carolina Rowan -2.09 -1.72371730002 North Carolina Swain -2.23 -1.66371830014 North Carolina Wake -2.05 -1.65371890003 North Carolina Watauga -2.37 -1.96B-122Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case371910005 North Carolina Wayne -1.88 -1.51380070002 North Dakota Billings -0.04 -0.02380130002 North Dakota Burke -0.04 -0.02380130003 North Dakota Burke -0.04 -0.02380150003 North Dakota Burleigh -0.11 -0.05380171004 North Dakota Cass -0.29 -0.18380530002 North Dakota McKenzie -0.04 -0.01380570004 North Dakota Mercer -0.06 -0.03390090003 Ohio Athens -2.83 -2.32390170016 Ohio Butler -3.31 -2.82390170017 Ohio Butler -2.95 -2.50390171004 Ohio Butler -3.07 -2.62390230005 Ohio Clark -2.82 -2.39390250022 Ohio Clermont -3.37 -2.88390350027 Ohio Cuyahoga -2.65 -2.21390350034 Ohio Cuyahoga -2.42 -2.03390350038 Ohio Cuyahoga -2.67 -2.20390350045 Ohio Cuyahoga -2.68 -2.22390350060 Ohio Cuyahoga -2.67 -2.20390350065 Ohio Cuyahoga -2.66 -2.21390351002 Ohio Cuyahoga -2.38 -2.00390490024 Ohio Franklin -2.81 -2.33390490025 Ohio Franklin -2.81 -2.33390490081 Ohio Franklin -2.82 -2.34390570005 Ohio Greene -2.85 -2.43390610006 Ohio Hamilton -3.29 -2.81390610014 Ohio Hamilton -3.54 -2.99390610040 Ohio Hamilton -3.55 -3.03390610042 Ohio Hamilton -3.51 -2.98B-123Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case390610043 Ohio Hamilton -3.28 -2.79390617001 Ohio Hamilton -3.52 -2.99390618001 Ohio Hamilton -3.52 -2.97390810017 Ohio Jefferson -2.75 -2.33390811001 Ohio Jefferson -2.99 -2.54390851001 Ohio Lake -2.30 -1.93390870010 Ohio Lawrence -2.99 -2.43390930016 Ohio Lorain -2.49 -2.10390933002 Ohio Lorain -1.94 -1.61390950024 Ohio Lucas -2.19 -1.76390950025 Ohio Lucas -2.21 -1.79390950026 Ohio Lucas -2.20 -1.77390990005 Ohio Mahoning -2.50 -2.08390990014 Ohio Mahoning -2.52 -2.08391130031 Ohio Montgomery -2.86 -2.43391130032 Ohio Montgomery -2.94 -2.48391330002 Ohio Portage -2.43 -2.04391351001 Ohio Preble -3.09 -2.67391450013 Ohio Scioto -3.08 -2.54391510017 Ohio Stark -2.73 -2.34391510020 Ohio Stark -2.34 -1.98391530017 Ohio Summit -2.37 -2.00391530023 Ohio Summit -2.29 -1.94391550007 Ohio Trumbull -2.48 -2.05400159008 Oklahoma Caddo -0.62 -0.50400219002 Oklahoma Cherokee -1.25 -0.94400719010 Oklahoma Kay -0.77 -0.57400819005 Oklahoma Lincoln -0.92 -0.69400970186 Oklahoma Mayes -1.13 -0.84B-124Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case400979014 Oklahoma Mayes -1.15 -0.86401010169 Oklahoma Muskogee -1.15 -0.86401090035 Oklahoma Oklahoma -0.82 -0.60401091037 Oklahoma Oklahoma -0.83 -0.61401159004 Oklahoma Ottawa -1.19 -0.90401210415 Oklahoma Pittsburg -1.09 -0.83401359015 Oklahoma Sequoyah -1.26 -0.95401430110 Oklahoma Tulsa -1.06 -0.79401431127 Oklahoma Tulsa -1.03 -0.76420010001 Pennsylvania Adams -2.30 -2.07420030008 Pennsylvania Allegheny -2.82 -2.41420030021 Pennsylvania Allegheny -2.85 -2.46420030064 Pennsylvania Allegheny -3.02 -2.50420030067 Pennsylvania Allegheny -2.68 -2.31420030095 Pennsylvania Allegheny -2.65 -2.29420030116 Pennsylvania Allegheny -2.67 -2.28420031008 Pennsylvania Allegheny -3.05 -2.68420031301 Pennsylvania Allegheny -2.99 -2.56420033007 Pennsylvania Allegheny -3.06 -2.62420039002 Pennsylvania Allegheny -2.98 -2.60420070014 Pennsylvania Beaver -2.58 -2.22420110011 Pennsylvania Berks -1.99 -1.79420170012 Pennsylvania Bucks -1.62 -1.38420210011 Pennsylvania Cambria -3.55 -3.20420270100 Pennsylvania Centre -2.44 -2.19420290100 Pennsylvania Chester -1.90 -1.71420410101 Pennsylvania Cumberland -2.22 -2.00420430401 Pennsylvania Dauphin -2.45 -2.22420450002 Pennsylvania Delaware -1.73 -1.48B-125Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case420490003 Pennsylvania Erie -2.07 -1.75420692006 Pennsylvania Lackawanna -1.64 -1.47420710007 Pennsylvania Lancaster -2.24 -2.04420770004 Pennsylvania Lehigh -1.67 -1.47420791101 Pennsylvania Luzerne -1.63 -1.46420850100 Pennsylvania Mercer -2.43 -2.03420950025 Pennsylvania Northampton -1.64 -1.43420990301 Pennsylvania Perry -2.01 -1.81421010047 Pennsylvania Philadelphia -1.64 -1.36421250005 Pennsylvania Washington -3.21 -2.74421250200 Pennsylvania Washington -3.13 -2.68421255001 Pennsylvania Washington -2.43 -2.09421290008 Pennsylvania Westmoreland -3.36 -2.92421330008 Pennsylvania York -2.39 -2.20440070022 Rhode Island Providence -0.75 -0.63440070026 Rhode Island Providence -0.82 -0.66440070028 Rhode Island Providence -0.78 -0.64440071010 Rhode Island Providence -0.77 -0.65450130007 South Carolina Beaufort -1.53 -1.16450190048 South Carolina Charleston -1.46 -1.12450190049 South Carolina Charleston -1.54 -1.19450250001 South Carolina Chesterfield -1.76 -1.38450370001 South Carolina Edgefield -1.83 -1.29450410002 South Carolina Florence -1.69 -1.33450430009 South Carolina Georgetown -1.44 -1.15450450008 South Carolina Greenville -2.07 -1.53450450009 South Carolina Greenville -2.09 -1.56450470003 South Carolina Greenwood -2.14 -1.46450510002 South Carolina Horry -1.54 -1.22B-126Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case450630008 South Carolina Lexington -1.86 -1.34450730001 South Carolina Oconee -1.97 -1.45450790007 South Carolina Richland -1.86 -1.37450790019 South Carolina Richland -1.85 -1.35450830010 South Carolina Spartanburg -2.04 -1.56460110002 South Dakota Brookings -0.50 -0.35460130003 South Dakota Brown -0.30 -0.19460290002 South Dakota Codington -0.38 -0.25460330132 South Dakota Custer -0.05 -0.02460710001 South Dakota Jackson -0.10 -0.07460990006 South Dakota Minnehaha -0.60 -0.41460990007 South Dakota Minnehaha -0.59 -0.41461030016 South Dakota Pennington -0.07 -0.02461030020 South Dakota Pennington -0.07 -0.02461031001 South Dakota Pennington -0.06 -0.02470090011 Tennessee Blount -2.40 -1.84470370023 Tennessee Davidson -3.29 -2.72470370025 Tennessee Davidson -3.29 -2.71470370036 Tennessee Davidson -3.29 -2.71470450004 Tennessee Dyer -2.97 -2.43470650031 Tennessee Hamilton -2.61 -1.97470651011 Tennessee Hamilton -2.74 -2.12470654002 Tennessee Hamilton -2.72 -2.08470930028 Tennessee Knox -2.59 -1.98470931017 Tennessee Knox -2.58 -1.97470931020 Tennessee Knox -2.64 -2.02470990002 Tennessee Lawrence -2.48 -2.03471050108 Tennessee Loudon -2.46 -1.89471071002 Tennessee McMinn -2.53 -1.95B-127Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case471192007 Tennessee Maury -2.94 -2.41471251009 Tennessee Montgomery -3.87 -3.29471410001 Tennessee Putnam -3.02 -2.46471450004 Tennessee Roane -2.58 -2.01471570014 Tennessee Shelby -2.70 -2.06471570038 Tennessee Shelby -2.69 -2.05471570047 Tennessee Shelby -2.77 -2.11471571004 Tennessee Shelby -2.65 -2.06471631007 Tennessee Sullivan -2.51 -2.03471650007 Tennessee Sumner -3.97 -3.34480370004 Texas Bowie -1.37 -1.10481130069 Texas Dallas -0.81 -0.61481130087 Texas Dallas -0.81 -0.62481350003 Texas Ector -0.32 -0.26481410037 Texas El Paso -0.15 -0.10482010058 Texas Harris -1.00 -0.72482011035 Texas Harris -1.05 -0.67482030002 Texas Harrison -1.33 -1.10482150043 Texas Hidalgo -0.71 -0.57482450021 Texas Jefferson -1.23 -0.91483550032 Texas Nueces -1.09 -0.76483611001 Texas Orange -1.22 -0.95484391002 Texas Tarrant -0.81 -0.61484391006 Texas Tarrant -0.82 -0.61500010002 Vermont Addison -0.73 -0.62500010003 Vermont Addison -0.72 -0.61500030004 Vermont Bennington -0.81 -0.70500070012 Vermont Chittenden -0.74 -0.60500070014 Vermont Chittenden -0.77 -0.62B-128Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case500210002 Vermont Rutland -0.76 -0.61510130020 Virginia Arlington -2.06 -1.86510360002 Virginia Charles -1.89 -1.61510410003 Virginia Chesterfield -2.05 -1.72510590030 Virginia Fairfax -2.03 -1.82510591005 Virginia Fairfax -2.07 -1.85510595001 Virginia Fairfax -2.09 -1.86510870014 Virginia Henrico -2.07 -1.75510870015 Virginia Henrico -2.19 -1.85511071005 Virginia Loudoun -2.14 -1.89511390004 Virginia Page -2.57 -2.21515200006 Virginia Bristol City -2.66 -2.14516500004 Virginia Hampton City -1.84 -1.56516800015 Virginia Lynchburg City -2.29 -1.91517100024 Virginia Norfolk City -1.88 -1.59517700014 Virginia Roanoke City -2.57 -2.10517750010 Virginia Salem City -2.51 -2.05518100008 Virginia Virginia Beach City -1.84 -1.57540030003 West Virginia Berkeley -2.51 -2.20540090005 West Virginia Brooke -2.93 -2.49540090011 West Virginia Brooke -2.93 -2.49540110006 West Virginia Cabell -3.16 -2.56540291004 West Virginia Hancock -2.86 -2.45540330003 West Virginia Harrison -3.88 -3.36540390010 West Virginia Kanawha -3.24 -2.68540390011 West Virginia Kanawha -2.99 -2.50540391005 West Virginia Kanawha -3.31 -2.72540490006 West Virginia Marion -4.17 -3.62540511002 West Virginia Marshall -3.22 -2.70B-129Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case540610003 West Virginia Monongalia -3.71 -3.13540690010 West Virginia Ohio -3.03 -2.57540810002 West Virginia Raleigh -2.87 -2.39541071002 West Virginia Wood -2.91 -2.37550030010 Wisconsin Ashland -0.39 -0.28550090005 Wisconsin Brown -0.78 -0.50550250047 Wisconsin Dane -1.19 -0.91550270007 Wisconsin Dodge -1.12 -0.75550410007 Wisconsin Forest -0.58 -0.39550430009 Wisconsin Grant -1.14 -0.79550590019 Wisconsin Kenosha -1.55 -1.05550710007 Wisconsin Manitowoc -0.86 -0.57550790010 Wisconsin Milwaukee -1.47 -0.97550790026 Wisconsin Milwaukee -1.42 -0.95550790043 Wisconsin Milwaukee -1.49 -0.98550790059 Wisconsin Milwaukee -1.45 -0.95550790099 Wisconsin Milwaukee -1.43 -0.95550870009 Wisconsin Outagamie -0.80 -0.52550890009 Wisconsin Ozaukee -1.26 -0.85551091002 Wisconsin St. Croix -0.62 -0.41551110007 Wisconsin Sauk -1.06 -0.74551198001 Wisconsin Taylor -0.58 -0.41551250001 Wisconsin Vilas -0.50 -0.35551330027 Wisconsin Waukesha -1.29 -0.84560050877 Wyoming Campbell -0.01 0.01560050892 Wyoming Campbell 0.01 0.00560050899 Wyoming Campbell 0.00 0.01560090819 Wyoming Converse 0.00 0.01560131003 Wyoming Fremont -0.04 0.01B-130Annual PM2.5 (μg/m3)Monitor ID State CountyDifference:2014 Remedy -2012 Base CaseDifference:2014 Remedy -2014 Base Case560210001 Wyoming Laramie -0.05 0.01560330002 Wyoming Sheridan -0.06 0.01B-131Differences in 24-Hour PM2.5 Design Values (μg/m3) by Site:2014 Remedy Scenario Compared to the2012 Base Case and the 2014 Base Case24-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case10030010 Alabama Baldwin -4.6 -3.810270001 Alabama Clay -6.1 -4.210331002 Alabama Colbert -8.3 -6.810491003 Alabama DeKalb -6.0 -4.110530002 Alabama Escambia -4.3 -3.410550010 Alabama Etowah -6.2 -4.610690003 Alabama Houston -3.6 -2.610730023 Alabama Jefferson -4.4 -3.210731005 Alabama Jefferson -5.6 -4.110731009 Alabama Jefferson -6.5 -4.910731010 Alabama Jefferson -6.2 -4.710732003 Alabama Jefferson -3.7 -2.810732006 Alabama Jefferson -6.1 -4.810735002 Alabama Jefferson -7.2 -5.410735003 Alabama Jefferson -7.0 -5.410890014 Alabama Madison -8.6 -6.710970002 Alabama Mobile -4.6 -3.110970003 Alabama Mobile -4.7 -3.310972005 Alabama Mobile -5.3 -4.111010007 Alabama Montgomery -5.4 -4.211030011 Alabama Morgan -8.7 -6.811130001 Alabama Russell -4.4 -3.011170006 Alabama Shelby -6.0 -4.611190002 Alabama Sumter -5.9 -4.411210002 Alabama Talladega -5.7 -4.011250004 Alabama Tuscaloosa -5.1 -4.011270002 Alabama Walker -5.4 -4.050010011 Arkansas Arkansas -7.1 -6.150030005 Arkansas Ashley -4.6 -3.5B-13224-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case50350005 Arkansas Crittenden -12.0 -10.450450002 Arkansas Faulkner -5.7 -4.850510003 Arkansas Garland -7.1 -6.150930007 Arkansas Mississippi -8.4 -6.851070001 Arkansas Phillips -7.2 -6.051130002 Arkansas Polk -6.2 -5.251150003 Arkansas Pope -3.2 -2.351190007 Arkansas Pulaski -6.0 -5.051191004 Arkansas Pulaski -4.9 -3.951191005 Arkansas Pulaski -4.7 -3.651390006 Arkansas Union -4.7 -3.651450001 Arkansas White -6.6 -5.480010006 Colorado Adams -0.1 0.480050005 Colorado Arapahoe -0.4 0.080130003 Colorado Boulder -0.2 0.280130012 Colorado Boulder -0.3 0.080290004 Colorado Delta -0.6 -0.180310002 Colorado Denver 0.1 0.480310023 Colorado Denver 0.1 0.580390001 Colorado Elbert -0.3 -0.180410008 Colorado El Paso -0.3 0.080410011 Colorado El Paso -0.3 0.080690009 Colorado Larimer -0.2 0.080770017 Colorado Mesa -0.4 0.081010012 Colorado Pueblo -0.3 0.081130004 Colorado San Miguel 0.0 0.081230006 Colorado Weld 0.1 0.381230008 Colorado Weld -0.1 0.290010010 Connecticut Fairfield -3.1 -2.490011123 Connecticut Fairfield -2.1 -1.590013005 Connecticut Fairfield -3.4 -2.890019003 Connecticut Fairfield -4.7 -4.090031003 Connecticut Hartford -3.3 -2.7B-13324-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case90050005 Connecticut Litchfield -5.5 -4.990090026 Connecticut New Haven -4.0 -3.390090027 Connecticut New Haven -2.7 -2.090091123 Connecticut New Haven -3.4 -2.690092008 Connecticut New Haven -4.4 -3.790092123 Connecticut New Haven -2.6 -1.990113002 Connecticut New London -4.0 -3.3100010002 Delaware Kent -3.0 -2.6100010003 Delaware Kent -3.2 -2.7100031003 Delaware New Castle -2.7 -2.3100031007 Delaware New Castle -2.2 -1.9100031012 Delaware New Castle -1.7 -1.3100032004 Delaware New Castle -2.4 -2.0100051002 Delaware Sussex -2.9 -2.4110010041District OfColumbia District of Columbia -2.8 -2.4110010042District OfColumbia District of Columbia -2.5 -2.2110010043District OfColumbia District of Columbia -2.5 -2.3120010023 Florida Alachua -3.8 -3.1120010024 Florida Alachua -3.4 -2.7120051004 Florida Bay -3.2 -2.2120090007 Florida Brevard -1.8 -1.3120111002 Florida Broward -1.6 -1.0120112004 Florida Broward -1.3 -0.7120113002 Florida Broward -1.4 -0.9120170005 Florida Citrus -3.1 -2.3120310098 Florida Duval -2.1 -1.6120310099 Florida Duval -1.1 -0.7120330004 Florida Escambia -3.3 -2.6120570030 Florida Hillsborough -1.3 -0.6120573002 Florida Hillsborough -1.6 -0.9B-13424-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case120710005 Florida Lee -1.8 -1.1120730012 Florida Leon -3.3 -2.5120814012 Florida Manatee -1.8 -1.3120830003 Florida Marion -2.7 -2.0120861016 Florida Miami-Dade -1.1 -0.7120866001 Florida Miami-Dade -2.1 -1.4120951004 Florida Orange -1.8 -1.1120952002 Florida Orange -1.9 -1.1120990009 Florida Palm Beach -1.7 -1.1120992005 Florida Palm Beach -1.5 -1.0121030018 Florida Pinellas -1.1 -0.6121031009 Florida Pinellas -1.3 -1.0121056006 Florida Polk -1.7 -1.0121111002 Florida St. Lucie -2.6 -1.9121150013 Florida Sarasota -2.3 -1.6121171002 Florida Seminole -2.9 -1.9121275002 Florida Volusia -3.8 -2.7130210007 Georgia Bibb -3.8 -2.1130210012 Georgia Bibb -5.7 -3.5130510017 Georgia Chatham -3.1 -2.1130510091 Georgia Chatham -2.6 -1.6130630091 Georgia Clayton -3.8 -2.8130670003 Georgia Cobb -4.3 -2.8130670004 Georgia Cobb -4.9 -2.4130890002 Georgia DeKalb -3.3 -2.1130892001 Georgia DeKalb -3.0 -1.7130950007 Georgia Dougherty -4.0 -2.8131150005 Georgia Floyd -4.2 -2.9131210032 Georgia Fulton -3.1 -1.7131210039 Georgia Fulton -4.2 -1.6131270006 Georgia Glynn -3.1 -2.1131350002 Georgia Gwinnett -3.6 -2.5131390003 Georgia Hall -4.3 -1.6B-13524-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case131530001 Georgia Houston -4.8 -2.9131850003 Georgia Lowndes -3.0 -2.1132150001 Georgia Muscogee -3.1 -2.0132150008 Georgia Muscogee -4.9 -3.1132150011 Georgia Muscogee -3.0 -1.7132230003 Georgia Paulding -4.9 -3.1132450005 Georgia Richmond -1.8 -1.0132450091 Georgia Richmond -3.3 -2.0132950002 Georgia Walker -4.3 -2.9133030001 Georgia Washington -6.8 -2.9133190001 Georgia Wilkinson -4.6 -2.5170010006 Illinois Adams -5.3 -3.7170190004 Illinois Champaign -6.3 -5.2170191001 Illinois Champaign -4.7 -3.6170310022 Illinois Cook -1.7 -1.1170310050 Illinois Cook -3.8 -2.0170310052 Illinois Cook -1.9 -0.7170310057 Illinois Cook -4.5 -3.2170310076 Illinois Cook -4.0 -2.5170311016 Illinois Cook -3.3 -1.7170312001 Illinois Cook -4.0 -2.8170313103 Illinois Cook -2.2 -1.4170313301 Illinois Cook -3.3 -1.9170314007 Illinois Cook -3.2 -1.8170314201 Illinois Cook -3.0 -1.1170316005 Illinois Cook -1.8 -0.9170434002 Illinois DuPage -1.6 -0.8170650002 Illinois Hamilton -10.2 -8.3170831001 Illinois Jersey -8.0 -5.2170890003 Illinois Kane -3.2 -1.5170890007 Illinois Kane -2.5 -1.0170971007 Illinois Lake -7.0 -4.9170990007 Illinois La Salle -3.3 -1.9B-13624-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case171110001 Illinois McHenry -2.3 -1.2171132003 Illinois McLean -7.3 -5.4171150013 Illinois Macon -8.9 -7.2171190023 Illinois Madison -7.2 -4.4171191007 Illinois Madison -5.7 -3.7171192009 Illinois Madison -8.6 -6.8171193007 Illinois Madison -9.3 -7.4171430037 Illinois Peoria -6.1 -2.5171570001 Illinois Randolph -4.4 -2.4171613002 Illinois Rock Island -2.2 -1.1171630010 Illinois Saint Clair -5.9 -3.4171634001 Illinois Saint Clair -6.0 -3.2171670012 Illinois Sangamon -6.2 -4.2171971002 Illinois Will -5.5 -4.0171971011 Illinois Will -8.0 -6.3172010013 Illinois Winnebago -3.3 -1.5180030004 Indiana Allen -2.4 -1.7180030014 Indiana Allen -2.9 -2.3180190006 Indiana Clark -9.5 -7.5180350006 Indiana Delaware -6.7 -5.4180372001 Indiana Dubois -8.6 -7.4180390003 Indiana Elkhart -4.8 -3.7180431004 Indiana Floyd -10.5 -8.9180650003 Indiana Henry -7.0 -5.9180670003 Indiana Howard -7.6 -6.2180830004 Indiana Knox -7.1 -6.0180890006 Indiana Lake -2.0 -1.3180890022 Indiana Lake -2.0 -1.1180890026 Indiana Lake -3.6 -2.2180890027 Indiana Lake -2.2 -1.3180890031 Indiana Lake -6.2 -4.6180891003 Indiana Lake -1.9 -1.1180892004 Indiana Lake -1.9 -1.3B-13724-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case180892010 Indiana Lake -3.8 -2.9180910011 Indiana LaPorte -5.2 -3.7180910012 Indiana LaPorte -3.5 -2.4180950009 Indiana Madison -7.7 -6.6180970042 Indiana Marion -7.7 -5.9180970043 Indiana Marion -7.3 -5.6180970066 Indiana Marion -8.4 -6.8180970078 Indiana Marion -6.3 -4.7180970079 Indiana Marion -8.6 -6.9180970081 Indiana Marion -9.2 -7.8180970083 Indiana Marion -10.0 -8.3181270020 Indiana Porter -5.2 -3.7181270024 Indiana Porter -3.3 -2.1181410014 Indiana St. Joseph -3.5 -2.8181411008 Indiana St. Joseph -2.3 -1.4181412004 Indiana St. Joseph -2.0 -1.4181470009 Indiana Spencer -8.7 -7.2181570008 Indiana Tippecanoe -6.4 -4.9181630006 Indiana Vanderburgh -7.3 -6.3181630012 Indiana Vanderburgh -7.1 -6.1181630016 Indiana Vanderburgh -4.4 -3.4181670018 Indiana Vigo -2.4 -1.0181670023 Indiana Vigo -4.3 -2.9190130008 Iowa Black Hawk -1.3 -0.8190450021 Iowa Clinton -3.1 -0.8191032001 Iowa Johnson -2.1 -1.5191130037 Iowa Linn -2.6 -1.0191370002 Iowa Montgomery -3.6 -2.7191390015 Iowa Muscatine -2.4 -1.7191471002 Iowa Palo Alto -4.2 -3.2191530030 Iowa Polk -3.1 -2.2191532510 Iowa Polk -3.4 -2.5191532520 Iowa Polk -2.2 -1.7B-13824-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case191550009 Iowa Pottawattamie -2.4 -1.9191630015 Iowa Scott -1.6 -0.5191630018 Iowa Scott -1.7 -0.6191630019 Iowa Scott -4.9 -2.1191770006 Iowa Van Buren -2.4 -1.4191930017 Iowa Woodbury -1.4 -1.1191970004 Iowa Wright -2.9 -1.9200910007 Kansas Johnson -2.7 -1.7200910009 Kansas Johnson -2.0 -1.0200910010 Kansas Johnson -2.9 -1.8201070002 Kansas Linn -3.7 -2.7201730008 Kansas Sedgwick -3.3 -2.0201730009 Kansas Sedgwick -0.8 -0.3201730010 Kansas Sedgwick -1.4 -0.6201770010 Kansas Shawnee -3.0 -1.6201770011 Kansas Shawnee -3.8 -2.5201910002 Kansas Sumner -2.5 -1.4202090021 Kansas Wyandotte -3.0 -2.2202090022 Kansas Wyandotte -2.5 -1.8210130002 Kentucky Bell -5.9 -4.3210190017 Kentucky Boyd -10.2 -8.6210290006 Kentucky Bullitt -11.0 -9.1210370003 Kentucky Campbell -5.3 -4.1210430500 Kentucky Carter -9.8 -8.2210470006 Kentucky Christian -12.7 -11.1210590005 Kentucky Daviess -15.3 -13.2210670012 Kentucky Fayette -7.9 -5.9210670014 Kentucky Fayette -8.7 -6.6210730006 Kentucky Franklin -10.5 -8.5210930006 Kentucky Hardin -12.6 -10.8211010014 Kentucky Henderson -7.1 -6.2211110043 Kentucky Jefferson -8.6 -7.1211110044 Kentucky Jefferson -8.4 -6.7B-13924-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case211110048 Kentucky Jefferson -9.3 -7.7211110051 Kentucky Jefferson -11.6 -10.1211170007 Kentucky Kenton -9.4 -8.1211250004 Kentucky Laurel -5.8 -4.5211451004 Kentucky McCracken -11.3 -9.4211510003 Kentucky Madison -7.8 -6.1211930003 Kentucky Perry -7.6 -6.0211950002 Kentucky Pike -8.1 -6.7212270007 Kentucky Warren -12.1 -10.0220171002 Louisiana Caddo -3.6 -2.5220190009 Louisiana Calcasieu -4.0 -3.2220190010 Louisiana Calcasieu -4.5 -3.6220290003 Louisiana Concordia -5.8 -4.8220330009 Louisiana East Baton Rouge -2.8 -1.5220331001 Louisiana East Baton Rouge -3.2 -2.1220470005 Louisiana Iberville -2.2 -0.6220470009 Louisiana Iberville -4.7 -3.5220511001 Louisiana Jefferson -4.2 -3.0220550006 Louisiana Lafayette -5.7 -4.4220730004 Louisiana Ouachita -5.3 -4.4220790002 Louisiana Rapides -7.0 -5.7221050001 Louisiana Tangipahoa -4.2 -2.7221090001 Louisiana Terrebonne -5.4 -4.0221210001 Louisiana West Baton Rouge -2.5 -1.3230010011 Maine Androscoggin -1.2 -0.8230030013 Maine Aroostook -0.9 -0.5230031011 Maine Aroostook -1.2 -0.8230050015 Maine Cumberland -1.4 -0.9230050027 Maine Cumberland -1.5 -0.8230090103 Maine Hancock -2.0 -1.9230110016 Maine Kennebec -1.4 -0.9230172011 Maine Oxford -1.6 -1.1230190002 Maine Penobscot -1.5 -1.1B-14024-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case240030014 Maryland Anne Arundel -2.5 -2.5240031003 Maryland Anne Arundel -0.9 -1.5240032002 Maryland Anne Arundel -1.4 -1.6240051007 Maryland Baltimore -2.8 -2.6240053001 Maryland Baltimore -1.9 -1.9240150003 Maryland Cecil -2.9 -2.6240251001 Maryland Harford -2.9 -2.7240313001 Maryland Montgomery -3.5 -3.0240330030 Maryland Prince George's -4.9 -4.5240338003 Maryland Prince George's -4.1 -4.0240430009 Maryland Washington -4.6 -3.9245100006 Maryland Baltimore (City) -1.9 -1.9245100007 Maryland Baltimore (City) -2.4 -2.2245100008 Maryland Baltimore (City) -1.4 -1.3245100035 Maryland Baltimore (City) -1.3 -1.1245100040 Maryland Baltimore (City) -1.3 -1.1245100049 Maryland Baltimore (City) -1.2 -1.0250035001 Massachusetts Berkshire -1.9 -1.4250051004 Massachusetts Bristol -2.1 -2.0250092006 Massachusetts Essex -2.1 -1.7250095005 Massachusetts Essex -3.4 -3.0250096001 Massachusetts Essex -2.2 -1.8250130008 Massachusetts Hampden -2.4 -1.9250130016 Massachusetts Hampden -2.2 -1.5250132009 Massachusetts Hampden -2.1 -1.3250230004 Massachusetts Plymouth -2.9 -2.5250250002 Massachusetts Suffolk -1.1 -0.8250250027 Massachusetts Suffolk -1.1 -0.9250250042 Massachusetts Suffolk -1.0 -0.6250250043 Massachusetts Suffolk -1.2 -0.8250270016 Massachusetts Worcester -2.9 -2.3250270023 Massachusetts Worcester -2.1 -1.4260050003 Michigan Allegan -2.7 -1.5B-14124-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case260170014 Michigan Bay -2.9 -1.9260210014 Michigan Berrien -3.7 -2.7260490021 Michigan Genesee -1.7 -1.0260650012 Michigan Ingham -2.4 -1.5260770008 Michigan Kalamazoo -3.1 -2.3260810020 Michigan Kent -3.5 -2.1260990009 Michigan Macomb -2.2 -1.4261130001 Michigan Missaukee -4.3 -2.8261150005 Michigan Monroe -5.8 -4.4261210040 Michigan Muskegon -4.4 -2.8261250001 Michigan Oakland -2.8 -1.8261390005 Michigan Ottawa -2.0 -1.2261450018 Michigan Saginaw -3.3 -2.2261470005 Michigan St. Clair -3.7 -2.9261610005 Michigan Washtenaw -4.0 -2.7261610008 Michigan Washtenaw -2.5 -1.4261630001 Michigan Wayne -2.6 -1.4261630015 Michigan Wayne -4.5 -3.1261630016 Michigan Wayne -2.4 -1.5261630019 Michigan Wayne -1.6 -0.7261630025 Michigan Wayne -3.6 -2.4261630033 Michigan Wayne -3.0 -2.0261630036 Michigan Wayne -1.9 -1.1261630039 Michigan Wayne -2.4 -1.6270210001 Minnesota Cass -1.5 -1.0270370470 Minnesota Dakota -2.6 -1.5270530050 Minnesota Hennepin -2.6 -1.8270530961 Minnesota Hennepin -1.7 -1.2270530963 Minnesota Hennepin -2.2 -1.4270530965 Minnesota Hennepin -1.3 -0.9270531007 Minnesota Hennepin -2.0 -1.3270532006 Minnesota Hennepin -2.3 -1.6270953051 Minnesota Mille Lacs -2.0 -1.5B-14224-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case271230866 Minnesota Ramsey -1.4 -1.0271230868 Minnesota Ramsey -2.4 -1.6271230871 Minnesota Ramsey -2.3 -1.3271377001 Minnesota Saint Louis -1.8 -1.1271377550 Minnesota Saint Louis -2.6 -1.7271377551 Minnesota Saint Louis -2.6 -1.9271390505 Minnesota Scott -2.4 -1.7271453052 Minnesota Stearns -1.3 -0.7280010004 Mississippi Adams -7.1 -5.9280110001 Mississippi Bolivar -6.8 -5.5280330002 Mississippi DeSoto -9.2 -7.5280350004 Mississippi Forrest -4.1 -3.0280470008 Mississippi Harrison -5.5 -4.1280490010 Mississippi Hinds -6.0 -4.9280590006 Mississippi Jackson -4.9 -3.5280670002 Mississippi Jones -4.6 -3.6280750003 Mississippi Lauderdale -6.8 -5.5280810005 Mississippi Lee -8.1 -6.4280870001 Mississippi Lowndes -6.9 -5.2281090001 Mississippi Pearl River -4.5 -3.3281490004 Mississippi Warren -6.9 -5.8290190004 Missouri Boone -4.6 -3.2290210005 Missouri Buchanan -3.1 -2.2290370003 Missouri Cass -3.7 -2.8290390001 Missouri Cedar -6.1 -4.6290470005 Missouri Clay -2.1 -1.1290770032 Missouri Greene -7.0 -4.8290950034 Missouri Jackson -2.5 -1.8290990012 Missouri Jefferson -6.0 -2.9291370001 Missouri Monroe -4.2 -2.9291831002 Missouri Saint Charles -6.9 -5.0291860006 Missouri Sainte Genevieve -6.8 -4.4291890004 Missouri Saint Louis -8.3 -5.7B-14324-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case291892003 Missouri Saint Louis -2.7 -1.3295100007 Missouri St. Louis City -6.9 -4.2295100085 Missouri St. Louis City -5.5 -3.1295100086 Missouri St. Louis City -4.9 -2.6295100087 Missouri St. Louis City -5.6 -2.9300870307 Montana Rosebud -0.1 0.0301111065 Montana Yellowstone -0.1 0.0310550019 Nebraska Douglas -3.0 -2.4310550052 Nebraska Douglas -2.1 -1.7310790004 Nebraska Hall -1.4 -0.9311090022 Nebraska Lancaster -1.6 -1.2311111002 Nebraska Lincoln -0.7 -0.4311530007 Nebraska Sarpy -2.9 -2.3311570003 Nebraska Scotts Bluff -0.6 -0.4311770002 Nebraska Washington -2.2 -1.7330012004 New Hampshire Belknap -3.2 -2.7330050007 New Hampshire Cheshire -1.8 -1.3330070014 New Hampshire Coos -2.4 -1.9330090010 New Hampshire Grafton -2.2 -1.7330110020 New Hampshire Hillsborough -1.3 -0.9330111015 New Hampshire Hillsborough -1.2 -0.8330115001 New Hampshire Hillsborough -5.3 -4.8330131006 New Hampshire Merrimack -2.5 -2.1330150014 New Hampshire Rockingham -1.7 -1.3330190003 New Hampshire Sullivan -3.8 -3.1340030003 New Jersey Bergen -2.1 -1.5340070003 New Jersey Camden -5.5 -4.7340071007 New Jersey Camden -4.1 -3.3340130015 New Jersey Essex -3.6 -2.8340155001 New Jersey Gloucester -3.1 -2.6340171003 New Jersey Hudson -2.8 -2.0340172002 New Jersey Hudson -1.6 -0.9340210008 New Jersey Mercer -4.9 -4.2B-14424-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case340218001 New Jersey Mercer -5.3 -4.6340230006 New Jersey Middlesex -4.9 -4.2340270004 New Jersey Morris -4.0 -3.4340273001 New Jersey Morris -6.6 -5.8340292002 New Jersey Ocean -7.2 -6.4340310005 New Jersey Passaic -4.5 -3.8340390004 New Jersey Union -2.8 -1.7340390006 New Jersey Union -1.6 -1.0340392003 New Jersey Union -3.2 -2.3340410006 New Jersey Warren -2.9 -2.5350010023 New Mexico Bernalillo -0.5 -0.3350010024 New Mexico Bernalillo -0.5 -0.4350050005 New Mexico Chaves -0.9 -0.7350130017 New Mexico Dona Ana -0.6 -0.3350130025 New Mexico Dona Ana -0.8 -0.6350431003 New Mexico Sandoval -0.4 -0.3350439011 New Mexico Sandoval -0.3 -0.1350450006 New Mexico San Juan -0.1 0.0350490020 New Mexico Santa Fe -0.2 -0.1360010005 New York Albany -2.0 -1.5360050080 New York Bronx -2.4 -1.7360050083 New York Bronx -1.8 -1.2360050110 New York Bronx -1.3 -0.8360130011 New York Chautauqua -6.1 -4.9360290005 New York Erie -1.3 -1.0360291007 New York Erie -1.9 -1.5360310003 New York Essex -3.7 -3.1360470122 New York Kings -2.8 -1.9360551007 New York Monroe -3.0 -2.5360590008 New York Nassau -5.0 -4.0360610056 New York New York -1.8 -1.2360610062 New York New York -2.1 -1.4360610079 New York New York -2.8 -2.0B-14524-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case360610128 New York New York -3.2 -2.4360632008 New York Niagara -3.2 -2.0360671015 New York Onondaga -5.2 -4.6360710002 New York Orange -3.1 -2.5360810124 New York Queens -1.9 -1.1360850055 New York Richmond -2.5 -1.7360850067 New York Richmond -3.8 -2.9360893001 New York St. Lawrence -2.1 -1.6361010003 New York Steuben -5.1 -4.5361030001 New York Suffolk -6.6 -5.5361191002 New York Westchester -4.0 -3.3370010002 North Carolina Alamance -5.2 -4.4370210034 North Carolina Buncombe -5.7 -5.0370330001 North Carolina Caswell -5.9 -5.0370350004 North Carolina Catawba -4.4 -3.8370370004 North Carolina Chatham -4.3 -3.3370510009 North Carolina Cumberland -3.7 -2.6370570002 North Carolina Davidson -4.0 -3.3370610002 North Carolina Duplin -4.4 -3.6370630001 North Carolina Durham -4.0 -3.0370650004 North Carolina Edgecombe -3.5 -2.5370670022 North Carolina Forsyth -2.7 -1.8370710016 North Carolina Gaston -4.2 -3.7370810013 North Carolina Guilford -3.8 -2.8370870010 North Carolina Haywood -3.8 -2.7370990006 North Carolina Jackson -4.9 -3.3371070004 North Carolina Lenoir -2.4 -1.7371110004 North Carolina McDowell -4.5 -3.6371170001 North Carolina Martin -2.6 -1.8371190010 North Carolina Mecklenburg -3.5 -2.8371190041 North Carolina Mecklenburg -3.6 -2.8371190042 North Carolina Mecklenburg -3.3 -2.4371210001 North Carolina Mitchell -4.7 -3.7B-14624-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case371230001 North Carolina Montgomery -4.9 -4.0371290002 North Carolina New Hanover -3.7 -3.0371330005 North Carolina Onslow -3.2 -2.5371350007 North Carolina Orange -5.2 -4.2371470005 North Carolina Pitt -2.1 -1.3371550005 North Carolina Robeson -5.2 -4.3371590021 North Carolina Rowan -3.5 -3.2371730002 North Carolina Swain -3.9 -2.4371830014 North Carolina Wake -3.5 -2.4371890003 North Carolina Watauga -6.3 -5.7371910005 North Carolina Wayne -5.0 -3.9380070002 North Dakota Billings -0.2 -0.2380130003 North Dakota Burke -0.2 -0.1380150003 North Dakota Burleigh -0.6 -0.4380171004 North Dakota Cass -2.3 -1.6380530002 North Dakota McKenzie -0.2 -0.2380570004 North Dakota Mercer -0.2 -0.1390090003 Ohio Athens -9.2 -7.6390170003 Ohio Butler -11.2 -9.2390170016 Ohio Butler -9.6 -7.8390170017 Ohio Butler -10.1 -8.4390171004 Ohio Butler -10.4 -8.7390230005 Ohio Clark -7.0 -5.5390250022 Ohio Clermont -9.6 -8.1390350027 Ohio Cuyahoga -2.4 -1.9390350034 Ohio Cuyahoga -3.8 -3.3390350038 Ohio Cuyahoga -5.5 -4.3390350045 Ohio Cuyahoga -6.6 -5.6390350060 Ohio Cuyahoga -3.1 -2.4390350065 Ohio Cuyahoga -6.3 -5.2390351002 Ohio Cuyahoga -3.2 -2.5390490024 Ohio Franklin -4.3 -2.9390490025 Ohio Franklin -5.5 -4.2B-14724-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case390490081 Ohio Franklin -6.3 -4.6390570005 Ohio Greene -5.9 -4.7390610006 Ohio Hamilton -10.8 -9.3390610014 Ohio Hamilton -12.1 -10.7390610040 Ohio Hamilton -10.9 -9.4390610042 Ohio Hamilton -7.9 -6.6390610043 Ohio Hamilton -8.1 -6.8390617001 Ohio Hamilton -7.6 -6.1390618001 Ohio Hamilton -8.6 -7.2390810017 Ohio Jefferson -6.2 -4.9390811001 Ohio Jefferson -6.5 -5.3390851001 Ohio Lake -5.5 -4.9390870010 Ohio Lawrence -8.3 -6.8390933002 Ohio Lorain -5.5 -4.6390950024 Ohio Lucas -2.2 -1.5390950025 Ohio Lucas -2.3 -1.5390950026 Ohio Lucas -3.4 -2.4390990005 Ohio Mahoning -5.2 -3.7390990014 Ohio Mahoning -3.9 -2.8391130031 Ohio Montgomery -4.5 -3.3391130032 Ohio Montgomery -5.2 -3.8391330002 Ohio Portage -7.0 -5.8391351001 Ohio Preble -7.8 -6.7391450013 Ohio Scioto -9.3 -7.8391510017 Ohio Stark -5.8 -5.0391530017 Ohio Summit -4.2 -3.2391530023 Ohio Summit -5.1 -4.2391550007 Ohio Trumbull -3.7 -2.8400159008 Oklahoma Caddo -2.5 -2.1400219002 Oklahoma Cherokee -2.9 -2.1400710602 Oklahoma Kay -2.8 -1.9400719010 Oklahoma Kay -2.3 -1.6400819005 Oklahoma Lincoln -3.7 -3.0B-14824-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case400970186 Oklahoma Mayes -2.3 -1.4400979014 Oklahoma Mayes -3.8 -2.8401010169 Oklahoma Muskogee -2.8 -2.2401090035 Oklahoma Oklahoma -1.3 -0.8401091037 Oklahoma Oklahoma -2.4 -1.6401159004 Oklahoma Ottawa -4.4 -3.3401210415 Oklahoma Pittsburg -3.2 -2.5401359015 Oklahoma Sequoyah -3.7 -3.2401430110 Oklahoma Tulsa -2.9 -2.1401431127 Oklahoma Tulsa -3.1 -2.2420010001 Pennsylvania Adams -3.7 -3.1420030008 Pennsylvania Allegheny -7.4 -6.2420030021 Pennsylvania Allegheny -6.3 -5.5420030064 Pennsylvania Allegheny -3.0 -1.4420030067 Pennsylvania Allegheny -11.5 -10.0420030093 Pennsylvania Allegheny -9.7 -8.3420030095 Pennsylvania Allegheny -7.8 -6.5420030116 Pennsylvania Allegheny -8.5 -6.9420030133 Pennsylvania Allegheny -10.2 -8.8420031008 Pennsylvania Allegheny -10.8 -9.5420031301 Pennsylvania Allegheny -6.5 -5.4420033007 Pennsylvania Allegheny -8.2 -7.0420039002 Pennsylvania Allegheny -9.6 -8.3420070014 Pennsylvania Beaver -7.7 -6.6420110011 Pennsylvania Berks -2.5 -2.1420170012 Pennsylvania Bucks -2.9 -2.1420210011 Pennsylvania Cambria -14.7 -13.8420270100 Pennsylvania Centre -5.1 -4.4420290100 Pennsylvania Chester -3.0 -2.5420410101 Pennsylvania Cumberland -2.3 -2.0420430401 Pennsylvania Dauphin -2.1 -1.7420450002 Pennsylvania Delaware -4.3 -3.6420490003 Pennsylvania Erie -3.3 -2.6B-14924-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case420692006 Pennsylvania Lackawanna -3.4 -2.7420710007 Pennsylvania Lancaster -1.7 -1.5420770004 Pennsylvania Lehigh -2.0 -1.5420791101 Pennsylvania Luzerne -2.7 -1.9420850100 Pennsylvania Mercer -3.8 -2.5420950025 Pennsylvania Northampton -2.4 -1.7420990301 Pennsylvania Perry -2.8 -2.6421010004 Pennsylvania Philadelphia -2.1 -1.3421010024 Pennsylvania Philadelphia -3.9 -3.1421010047 Pennsylvania Philadelphia -4.2 -3.4421250005 Pennsylvania Washington -7.9 -7.0421250200 Pennsylvania Washington -5.9 -5.1421255001 Pennsylvania Washington -7.9 -6.7421290008 Pennsylvania Westmoreland -9.5 -8.4421330008 Pennsylvania York -3.1 -2.7440070022 Rhode Island Providence -2.5 -2.1440070026 Rhode Island Providence -2.0 -1.5440070028 Rhode Island Providence -2.3 -1.9440071010 Rhode Island Providence -2.3 -1.9450130007 South Carolina Beaufort -5.3 -3.9450190048 South Carolina Charleston -2.2 -1.2450190049 South Carolina Charleston -3.6 -2.3450250001 South Carolina Chesterfield -4.2 -3.5450370001 South Carolina Edgefield -6.1 -3.8450410002 South Carolina Florence -4.1 -3.0450430009 South Carolina Georgetown -3.9 -2.9450450008 South Carolina Greenville -2.8 -1.5450450009 South Carolina Greenville -3.9 -2.6450470003 South Carolina Greenwood -4.7 -2.6450510002 South Carolina Horry -4.4 -3.5450630008 South Carolina Lexington -4.0 -2.9450730001 South Carolina Oconee -5.7 -3.6450790007 South Carolina Richland -4.2 -2.9B-15024-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case450790019 South Carolina Richland -3.9 -2.5450830010 South Carolina Spartanburg -3.9 -3.1460110002 South Dakota Brookings -2.5 -1.7460130003 South Dakota Brown -1.6 -1.0460290002 South Dakota Codington -2.5 -1.7460330132 South Dakota Custer -0.3 -0.3460710001 South Dakota Jackson -0.6 -0.5460990006 South Dakota Minnehaha -2.5 -1.7460990007 South Dakota Minnehaha -2.4 -1.8461030016 South Dakota Pennington -0.4 -0.2461030020 South Dakota Pennington -0.2 -0.1461031001 South Dakota Pennington -0.4 -0.2470090011 Tennessee Blount -7.9 -6.6470370023 Tennessee Davidson -10.7 -9.2470370025 Tennessee Davidson -9.7 -8.1470370036 Tennessee Davidson -12.4 -10.7470450004 Tennessee Dyer -10.2 -8.3470650031 Tennessee Hamilton -3.9 -2.6470651011 Tennessee Hamilton -6.0 -4.8470654002 Tennessee Hamilton -3.7 -2.4470930028 Tennessee Knox -7.8 -6.3470931017 Tennessee Knox -5.4 -4.2470990002 Tennessee Lawrence -8.6 -7.4471050108 Tennessee Loudon -7.0 -5.4471071002 Tennessee McMinn -8.2 -6.5471192007 Tennessee Maury -9.9 -8.5471251009 Tennessee Montgomery -9.8 -8.4471410001 Tennessee Putnam -11.0 -9.0471450004 Tennessee Roane -6.2 -5.0471570014 Tennessee Shelby -9.1 -7.4471570038 Tennessee Shelby -10.0 -8.3471570047 Tennessee Shelby -9.5 -8.0471571004 Tennessee Shelby -9.7 -8.3B-15124-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case471631007 Tennessee Sullivan -5.4 -4.6471650007 Tennessee Sumner -14.6 -12.6480370004 Texas Bowie -5.4 -4.3481130069 Texas Dallas -1.6 -1.2481130087 Texas Dallas -2.5 -1.8481350003 Texas Ector -3.1 -1.4481410037 Texas El Paso -0.5 -0.4482010058 Texas Harris -3.5 -2.6482011035 Texas Harris -3.0 -1.8482030002 Texas Harrison -3.8 -3.2482150043 Texas Hidalgo -2.6 -2.0482450021 Texas Jefferson -5.2 -4.2483550032 Texas Nueces -4.5 -3.4483611001 Texas Orange -5.8 -4.8484391002 Texas Tarrant -1.8 -1.4484391006 Texas Tarrant -1.1 -0.8500010002 Vermont Addison -3.0 -2.5500010003 Vermont Addison -3.8 -3.2500030004 Vermont Bennington -2.1 -1.5500070012 Vermont Chittenden -5.2 -4.4500070014 Vermont Chittenden -2.4 -1.7500210002 Vermont Rutland -1.2 -0.7510130020 Virginia Arlington -3.2 -2.4510360002 Virginia Charles -5.3 -4.5510410003 Virginia Chesterfield -4.6 -3.8510590030 Virginia Fairfax -4.3 -3.9510591005 Virginia Fairfax -4.6 -4.2510595001 Virginia Fairfax -3.7 -3.0510870014 Virginia Henrico -5.2 -4.4510870015 Virginia Henrico -6.0 -5.3511071005 Virginia Loudoun -6.1 -5.8511390004 Virginia Page -7.7 -6.8515200006 Virginia Bristol City -5.7 -4.8B-15224-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case516500004 Virginia Hampton City -3.8 -2.9516800015 Virginia Lynchburg City -7.1 -6.1517100024 Virginia Norfolk City -3.6 -2.7517700014 Virginia Roanoke City -5.1 -3.8517750010 Virginia Salem City -5.1 -4.1518100008 Virginia Virginia Beach City -3.2 -2.3540030003 West Virginia Berkeley -2.7 -2.3540090005 West Virginia Brooke -5.0 -4.1540090011 West Virginia Brooke -3.5 -2.8540110006 West Virginia Cabell -8.8 -7.5540291004 West Virginia Hancock -8.3 -6.7540330003 West Virginia Harrison -12.8 -11.1540390010 West Virginia Kanawha -10.0 -8.7540390011 West Virginia Kanawha -9.3 -8.1540391005 West Virginia Kanawha -9.8 -8.5540490006 West Virginia Marion -14.2 -12.7540511002 West Virginia Marshall -7.1 -5.8540610003 West Virginia Monongalia -13.3 -10.8540690010 West Virginia Ohio -3.9 -2.9540810002 West Virginia Raleigh -8.2 -7.1540890001 West Virginia Summers -8.7 -7.4541071002 West Virginia Wood -9.7 -8.1550030010 Wisconsin Ashland -2.7 -2.0550090005 Wisconsin Brown -0.5 -0.2550090009 Wisconsin Brown -0.2 0.0550250047 Wisconsin Dane -3.4 -2.5550270007 Wisconsin Dodge -2.2 -1.0550410007 Wisconsin Forest -2.6 -1.9550430009 Wisconsin Grant -1.8 -1.0550590019 Wisconsin Kenosha -2.3 -1.5550710007 Wisconsin Manitowoc -1.3 -0.6550790010 Wisconsin Milwaukee -1.4 -0.7550790026 Wisconsin Milwaukee -1.9 -0.9B-15324-Hour PM2.5 (μg/m3)Monitor ID State CountyDifferences:2014 Remedy -2012 Base CaseDifferences:2014 Remedy -2014 Base Case550790043 Wisconsin Milwaukee -2.5 -1.0550790059 Wisconsin Milwaukee -3.2 -1.9550790099 Wisconsin Milwaukee -3.5 -2.2550870009 Wisconsin Outagamie -0.5 -0.2550890009 Wisconsin Ozaukee -1.8 -0.9551091002 Wisconsin St. Croix -1.8 -1.0551110007 Wisconsin Sauk -1.2 -0.4551198001 Wisconsin Taylor -1.2 -0.6551250001 Wisconsin Vilas -2.2 -1.5551330027 Wisconsin Waukesha -3.3 -1.7560050877 Wyoming Campbell -0.1 0.0560050892 Wyoming Campbell 0.0 0.0560050899 Wyoming Campbell 0.0 0.0560090819 Wyoming Converse 0.0 0.0560131003 Wyoming Fremont -0.2 0.1560210001 Wyoming Laramie -0.2 -0.1560330002 Wyoming Sheridan -0.2 0.0

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix C

Ozone and PM2.5 Contribution Calculation ExamplesC-2As described in Section IV, the contribution of ozone and PM2.5 from upwindstates to downwind nonattainment andmaintenance receptors was calculated using a combination of MATSand other post-processing software. This appendix describes thecalculations 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 values werecalculated by running MATS using the CAMx 2005 base year and 2012future base case model outputs. The contribution metricswere calculated as described in Section IV.B. There are several pieces of information needed to calculate the upwind ozonecontributions to downwind ozone receptor sites.1)The 2012 base case 8-hr designvalues at each receptor.2)The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportionment MATS run isdescribed in Section IV.B steps 4 and 5.The source apportionment MATS runs specify the “base” year model file as the 2012CAMx base case and the “future” year model file as the 2012 CAMx source apportionment case. A separate sourceapportionment 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 output file“scenario_name- Ozone Monitors -- monitor data, temporally adjusted 2012.csv”)_idlatLongreferencecellf_o3_DV_state_name_county_name1033100234.76056-87.650615509164.5AlabamaColbert1073100333.48556-86.91516208069.7AlabamaJefferson1073100533.33111-87.003616207871AlabamaJefferson1073100933.45972-87.305615907966.4AlabamaJeffersonThese values are multiplied by the RRFs calculated from each source apportionment MATS run (for each upwind state). The valuesin the orange column (below) represent the relative ozone contribution from an upwind state toeach downwind receptor. Forexample, an RRF value of 0.9569 for Colbert County means thatthe upwind state contributes4.31% [(1 – 0.9569)* 100)] of the ozonein Colbert County (averaged across all high1ozone days)1The high ozone day threshold for the MATS ozone contribution runs are defined in Section IV.B. step 5.C-3_idlatlongreferencecellf_o3_DV_state_name_county_nameSA_rrf1033100234.76056-87.650615509164.5AlabamaColbert0.95691073100333.48556-86.91516208069.7AlabamaJefferson0.99441073100533.33111-87.003616207871AlabamaJefferson0.99791073100933.45972-87.305615907966.4AlabamaJefferson0.9986The 2012 future year design value (f_o3_DV) is multiplied by theRRF and then subtracted fromthe 2012 design value to get thetotalupwind 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 contributionwas accomplished with additionalpost-processing software (using the formula above). The final 8-hr ozone contributions(in ppb) are truncatedto the tenths digit,consistent with the NAAQS._idlatlongreferencecellf_o3_DV_state_name_county_nameSA_rrfContribution1033100234.76056-87.650615509164.5AlabamaColbert0.95692.71073100333.48556-86.91516208069.7AlabamaJefferson0.99440.31073100533.33111-87.003616207871AlabamaJefferson0.99790.11073100933.45972-87.305615907966.4AlabamaJefferson0.99860.0C-4Annual Average PM2.5[All example concentrations are in ug/m3]The 2012 future year base case annual average PM2.5 design valuecalculations are described inSection III.B. The 2012 designvalues were calculated by running MATS using the CAMx 2005 base year and 2012 futurebase case model outputs. The annualPM2.5 contribution metrics were calculated asdescribed in Section IV.A. The information needed to calculate the upwind annualPM2.5 contributions to downwind annualPM2.5 receptor sites is as follows:1) The 2012 base case annual average PM2.5 design valuesandcomponent species concentrations at each receptor.2)The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportionment MATS run isdescribed in Section IV.A step 4. Thesource apportionment MATS runs specify the“base” year model file as the 2012 CAMxbase case and the “future” year model file as the 2012 CAMx source apportionmentcase. A separate source apportionmentMATS case is run for each upwind state.The 2012 future year annual average PM2.5 design values are shownin the example below as the variable “f_pm25_ann_DV” (fromthe MATS output file “scenario_nameAnnual PM25 Point.csv”)._id_STATE_NAME_COUNTY_NAMEmonitor_latmonitor_longmonitor_gridcellb_pm25_ann_DVf_pm25_ann_DV10030010AlabamaBaldwin30.498-87.881415805111.4410.8110270001AlabamaClay33.28126-85.802217107913.211210331002AlabamaColbert34.76056-87.650615509112.6712.1310491003AlabamaDeKalb34.28763-85.968316908814.0912.75The 2012 future design value is comprisedof a number of component PM2.5 species.The following table shows the 2012 speciesconcentrations._id_STATE_NAME_COUNTY_NAMEf_blank_massf_crustal_massf_EC_massf_NH4_massf_Ocmb_massf_SO4_massf_NO3_massf_water_massf_salt_mass10030010AlabamaBaldwin0.50.48380.45641.06123.23194.00030.00421.04890.031510270001AlabamaClay0.50.70340.59731.11214.36533.55290.06751.08880.0210331002AlabamaColbert0.50.39020.31371.26834.27284.03960.15371.19840.002410491003AlabamaDeKalb0.50.65740.47131.34234.20964.09670.14441.3140.0163C-5The source apportionment RRFs (in orange below) are derived fromthe source apportionment MATSruns. They represent therelative PM2.5 species contribution from anupwind state to each downwind receptor.For example, an RRF value of 0.9656 forBaldwin County for sulfate means that the upwind state contributes 3.44% [(1 – 0.9656)*100)] of the sulfate ion in Baldwin County(averaged across all days)._id_STATE_NAME_COUNTY_NAMESA_rrf_crustalSA_rrf_ecSA_rrf_nh4SA_rrf_ocSA_rrf_so4SA_rrf_no3SA_rrf_water10030010AlabamaBaldwin0.99490.99470.9640.99850.96560.99960.963410270001AlabamaClay0.98950.98970.95350.99720.95290.99290.951410331002AlabamaColbert0.98630.98710.93220.99540.9280.98990.929210491003AlabamaDeKalb0.98620.98590.93710.99610.93640.99130.9357The annual RRFs from the source apportionmentMATS run are multiplied by the 2012 speciesconcentrations and then subtractedfrom the 2012 species concentrationsto 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 species2which have an RRF. The yellow and orange columns are taken directly fromMATS output files.The species contributions from upwind state “A” to the example downwind receptors are shown in blue below. The blue columns arethe final species contributions which are calculated usingadditional post-processing software (using the formula above)._id_STATE_NAME_COUNTY_NAMEcrustal_mass_SAEC_mass_SANH4_mass_SAOcmb_mass_SASO4_mass_SANO3_mass_SAwater_mass_SAsalt_mass_SA10030010AlabamaBaldwin0.0020.0020.0380.0050.1380.0000.0380.00010270001AlabamaClay0.0070.0060.0520.0120.1670.0000.0530.00010331002AlabamaColbert0.0050.0040.0860.0200.2910.0020.0850.00010491003AlabamaDeKalb0.0090.0070.0840.0160.2610.0010.0840.0002The RRF for salt is not used because it is always equal to 1.C-6For the transport rule contributions, the sulfate and nitrate and related species (ammonium andwater) concentrations were summed toget the total PM2.5 contribution usedin the proposed rule. These are the values inthe blue column below. The final annual averagePM2.5 contributions (in ug/m3) aretruncated to the hundredths digit,consistent with the NAAQS._id_STATE_NAME_COUNTY_NAMETotal AnnualPM2.5 MassContribution10030010AlabamaBaldwin0.2010270001AlabamaClay0.2610331002AlabamaColbert0.4310491003AlabamaDeKalb0.40C-724-Hour Average PM2.5[All example concentrations are in ug/m3]The 2012 future year base case 24 hr. average PM2.5 design valuecalculations are described inSection III.B. The 2012 designvalueswere calculated by running MATS using the CAMx 2005 base year and 2012 future base case model outputs. The 24-hr. PM2.5contribution metrics were calculated as described in Section IV.A. The 24-hr.PM2.5 contribution calculations are considerablymorecomplicated than the annual average calculations. High 24-hr valuescan occur at different timesof the year at each receptor.Therefore, we must calculate the contributions to the downwind receptor for each of the quarters and years. The final contribution is a5 year average of the contribution to the high quarters for eachyear. The high future quarters vary by receptor and are identified in the“scenario_nameDaily All Years High Quarters PM25 PointAllyears, all quarters.csv” MATS output file.The information needed to calculate theupwind 24-hr. PM2.5 contributions to downwind24-hr. PM2.5 receptorsites is as follows:1) The 2012 base case 24-hour average PM2.5and component species concentrations foreach quarter for (up to) five years ateach receptor.3)The relative response factors (RRFs) from each “source apportionment” MATS run. The source apportionment MATS run isdescribed in Section IV.A step 4. Thesource apportionment MATS runs specify the“base” year model file as the 2012 CAMxbase case and the “future” year model file as the 2012 CAMx source apportionmentcase. A separate source apportionmentMATS case is run for each upwind state.The 2012 future year 24-hr. quarterly peak PM2.5 values are shown in the example below asthe variable “f_pm25__d_q_conc” (fromthe MATS output file “scenario_nameDaily All Years All Quarters PM25 PointAnnual PM25 Point.csv”). This is an intermediatefile used in the calculation of the futureyear 5-year weighted average design values. For the design value calculations, thehigh futurequarters for each year (in bold) are averagedtogether to create a 5 year weighted average (year 1 is weighted once, year 2 twice, year 3three times, year 4 twice, and year 5 once)._id_state_name_county_namemonitor_latmonitor_longmonitor_gridcellyearquarterb_pm25_d_q_concf_pm25_d_q_conc10030010AlabamaBaldwin30.498-87.88141580512003119.719.34310030010AlabamaBaldwin30.498-87.88141580512003229.128.165310030010AlabamaBaldwin30.498-87.88141580512003322.720.100110030010AlabamaBaldwin30.498-87.88141580512003428.426.753810030010AlabamaBaldwin30.498-87.88141580512004125.525.035210030010AlabamaBaldwin30.498-87.88141580512004218.117.5248C-810030010AlabamaBaldwin30.498-87.88141580512004327.524.33810030010AlabamaBaldwin30.498-87.88141580512004424.623.17810030010AlabamaBaldwin30.498-87.88141580512005123.422.974310030010AlabamaBaldwin30.498-87.8814158051200522625.166610030010AlabamaBaldwin30.498-87.88141580512005323.720.98310030010AlabamaBaldwin30.498-87.8814158051200542523.554410030010AlabamaBaldwin30.498-87.88141580512006125.124.642710030010AlabamaBaldwin30.498-87.88141580512006225.624.779710030010AlabamaBaldwin30.498-87.88141580512006325.722.748810030010AlabamaBaldwin30.498-87.88141580512006415.914.991310030010AlabamaBaldwin30.498-87.88141580512007118.918.557910030010AlabamaBaldwin30.498-87.88141580512007222.421.684310030010AlabamaBaldwin30.498-87.88141580512007317.715.685710030010AlabamaBaldwin30.498-87.88141580512007419.718.5671The 2012 future 24-hr PM2.5 design value iscomprised of a number of component PM2.5species. The following table shows the2012 species concentrations for each quarter._id_state_name_county_nameyearquarterf_blank_mass_qf_crustal_mass_qf_EC_mass_qf_NH4_mass_qf_Ocmb_mass_qf_SO4_mass_qf_NO3_mass_qf_water_mass_qf_salt_mass_q10030010AlabamaBaldwin200310.50.42290.77351.84958.32275.46702.00160.005810030010AlabamaBaldwin200320.50.7170.64982.839710.610810.303702.53290.011410030010AlabamaBaldwin200330.50.68780.52181.74237.6027.615101.42660.004410030010AlabamaBaldwin200340.50.6890.7062.718810.09919.355702.64060.044610030010AlabamaBaldwin200410.50.55071.00722.408210.83687.118502.60630.007510030010AlabamaBaldwin200420.50.44130.39991.74756.52976.340701.55870.00710030010AlabamaBaldwin200430.50.83650.63462.11919.24579.261701.7350.005410030010AlabamaBaldwin200440.50.59520.60982.34858.72368.081502.2810.038610030010AlabamaBaldwin200510.50.50440.92262.20599.92666.520602.38740.006910030010AlabamaBaldwin200520.50.63930.57942.53199.46069.186902.25830.010210030010AlabamaBaldwin200530.50.71880.54531.82087.94457.958201.49080.004610030010AlabamaBaldwin200540.50.6050.622.38758.86848.215602.31880.039210030010AlabamaBaldwin200610.50.54190.99112.369710.66357.004602.56460.007410030010AlabamaBaldwin200620.50.62930.57032.49229.31229.042802.22290.01C-910030010AlabamaBaldwin200630.50.78080.59231.97788.62938.644201.61940.00510030010AlabamaBaldwin200640.50.38030.38971.50075.57445.164101.45750.024610030010AlabamaBaldwin200710.50.40530.74131.77247.97595.239201.91820.005510030010AlabamaBaldwin200720.50.54910.49762.17458.1257.889901.93950.008810030010AlabamaBaldwin200730.50.53290.40431.34995.88995.901.10530.003410030010AlabamaBaldwin200740.50.47420.48591.8716.94996.438301.81720.0307The source apportionment RRFs3(in orange below) are derived from the sourceapportionment MATS runs. They represent therelative PM2.5 species contributionfrom an upwind state to each downwind receptor in each quarter4. For example, an RRF value of0.8881 for Baldwin County for quarter 1 sulfate means that the upwind state contributes 11.19% [(1 – 0.8881)* 100)] of the sulfate ionin Baldwin County in quarter1 (averaged across all high5days in each quarter)._id_state_name_county_nameyearquarterSA_rrf_crustal_qSA_rrf_ec_qSA_rrf_nh4_qSA_rrf_oc_qSA_rrf_so4_qSA_rrf_no3_qSA_rrf_water_q10030010AlabamaBaldwin200310.96630.97720.99650.98520.88810.99580.888210030010AlabamaBaldwin200320.99120.99340.99960.99780.96560.99850.965510030010AlabamaBaldwin200330.98970.99140.99930.99850.94210.941910030010AlabamaBaldwin200340.97150.9710.99810.99180.90820.99810.908210030010AlabamaBaldwin200410.96630.97720.99650.98520.88810.99580.888210030010AlabamaBaldwin200420.99120.99340.99960.99780.96560.99850.965510030010AlabamaBaldwin200430.98970.99140.99930.99850.94210.941910030010AlabamaBaldwin200440.97150.9710.99810.99180.90820.99810.908210030010AlabamaBaldwin200510.96630.97720.99650.98520.88810.99580.888210030010AlabamaBaldwin200520.99120.99340.99960.99780.96560.99850.965510030010AlabamaBaldwin200530.98970.99140.99930.99850.94210.941910030010AlabamaBaldwin200540.97150.9710.99810.99180.90820.99810.908310030010AlabamaBaldwin200610.96630.97720.99650.98520.88810.99580.888210030010AlabamaBaldwin200620.99120.99340.99960.99780.96560.99850.96553One additional step is needed to calculate the water RRF. Since the MATS output file does not contain the quarterly water RRF, it must be backcalculated from the base and future year water concentrations (f_water_mass_q / b_water_mass_q)4There is a single species RRF for each of the 4 quarters.5Consistent with the 24-hr PM2.5 design value calculations, the“high” days are defined as the 10% highest modeled PM2.5 concentration daysfor each quarter at each receptor.C-1010030010AlabamaBaldwin200630.98970.99140.99930.99850.94210.941910030010AlabamaBaldwin200640.97150.9710.99810.99180.90820.99810.908310030010AlabamaBaldwin200710.96630.97720.99650.98520.88810.99580.888210030010AlabamaBaldwin200720.99120.99340.99960.99780.96560.99850.965510030010AlabamaBaldwin200730.98970.99140.99930.99850.94210.941910030010AlabamaBaldwin200740.97150.9710.99810.99180.90820.99810.9082The quarterly RRFs from the source apportionment MATS run aremultiplied by the 2012 species concentrations and then subtractedfrom the 2012 species concentrations toget 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 species6which have an RRF. The yellow and orange columns aretaken directly from MATS output files.The species contributions from upwind state “A” to the example downwind receptor is shown in blue below. The blue columns arethe species contributions which are calculated using additional post-processing software (using the contribution formula above)._id_state_name_county_nameyearquartercrustal_mass_SAEC_mass_SANH4_mass_SAOcmb_mass_SASO4_mass_SANO3_mass_SAwater_mass_SA10030010AlabamaBaldwin200310.0140.0170.0060.1210.5430.0000.19910030010AlabamaBaldwin200320.0060.0040.0010.0230.3420.0000.08410030010AlabamaBaldwin200330.0070.0040.0010.0110.4160.0000.07810030010AlabamaBaldwin200340.0190.0200.0050.0820.7800.0000.22010030010AlabamaBaldwin200410.0180.0220.0080.1580.7070.0000.25910030010AlabamaBaldwin200420.0040.0030.0010.0140.2110.0000.05210030010AlabamaBaldwin200430.0090.0050.0010.0140.5060.0000.09510030010AlabamaBaldwin200440.0160.0170.0040.0710.6740.0000.19010030010AlabamaBaldwin200510.0160.0210.0080.1450.6480.0000.23710030010AlabamaBaldwin200520.0060.0040.0010.0210.3050.0000.07510030010AlabamaBaldwin200530.0070.0050.0010.0120.4350.0000.0826The RRF for salt is ignored because it is always equal to 1.C-1110030010AlabamaBaldwin200540.0170.0170.0050.0720.6850.0000.19310030010AlabamaBaldwin200610.0180.0220.0080.1550.6960.0000.25510030010AlabamaBaldwin200620.0050.0040.0010.0200.3000.0000.07410030010AlabamaBaldwin200630.0080.0050.0010.0130.4720.0000.08910030010AlabamaBaldwin200640.0110.0110.0030.0450.4310.0000.12110030010AlabamaBaldwin200710.0130.0170.0060.1160.5210.0000.19010030010AlabamaBaldwin200720.0050.0030.0010.0180.2620.0000.06510030010AlabamaBaldwin200730.0050.0030.0010.0090.3220.0000.06010030010AlabamaBaldwin200740.0130.0140.0040.0570.5370.0000.151The next step is to average the contributions for thehigh quarterin each of the 5 years (bolded values above). The high PM2.5quarters for the receptor site were previously identified in thefirst step. The high future quarters for the 5 years at the examplereceptor site (Baldwin) are:Year 1 (2003) quarter 2Year 2 (2004) quarter 1Year 3 (2005) quarter 2Year 4 (2006) quarter 2Year 5 (2007) quarter 2The contributions (from the blue columns in the table above) are averaged7across the 5 high quarters (bolded rows) with the followingresult:crustal_mass_SAEC_mass_SANH4_mass_SAOcmb_mass_SASO4_mass_SANO3_mass_SAwater_mass_SA10030010AlabamaBaldwin0.00800.00750.00250.04810.38350.00000.11147The 5 year average for thecontributioncalculations is a “straight” 5 year average, not a weighted average.C-12For the transport rule contributions, the sulfate and nitrate and related species (ammonium andwater) concentrations were summed toget the total PM2.5 contribution usedin the proposed rule. The sum of these values is shown as the 24-hr PM2.5 contribution in theblue column below. The final 24 hr. PM2.5contributions (in ug/m3) are truncated tothe hundredths digit, consistent with theNAAQS._id_STATE_NAME_COUNTY_NAMETotal 24 Hr. PM2.5Mass Contribution10030010AlabamaBaldwin0.49

# Transport Rule Air Quality Modeling Technical Support

Document

Appendix D

2012 Base Case State-by-S tate Contributions to

Nonattainment and Maintenance for

8-Hour Ozone, Annual PM 2.5, and 24-Hour PM2.5

# D-2 

# This Appendix provides tabular summaries of the State-by-State

contributions to 8-hour ozone, a nnual 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 id entify 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/m 3



# 24-Hour PM2.5 Threshold: 0.35 μg/m 3



# In-State contributions (i.e., the cont ribution 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 fi nally 24-hour PM2.5. For each pollutant the

contributions to nonattainment site s 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 projec ted to have a maintenance problem.D-3State-by-State Contributions to 8-Hour Ozone (ppb)NonattainmentReceptorsPart 1a.Source States: Alabama through MissouriSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO220330003LouisianaE.BatonRouge1.31.40.00.00.40.50.10.10.00.20.154.20.00.00.00.00.03.10.4361030002New YorkSuffolk0.00.20.71.00.10.00.71.10.10.11.20.10.02.30.40.60.10.10.4361030009New YorkSuffolk0.10.11.71.60.10.10.80.90.20.10.70.20.02.90.60.90.10.10.4421010024PennsylvaniaPhiladelphia0.40.20.03.30.20.30.50.90.10.12.30.20.06.10.00.30.00.40.5480391004TexasBrazoria2.91.30.00.00.61.40.60.40.30.10.78.30.00.00.00.00.13.90.7482010051TexasHarris3.60.50.00.00.61.90.70.60.30.10.98.40.00.00.00.00.14.00.5482010055TexasHarris3.90.50.00.00.62.10.80.70.30.11.09.10.00.00.00.00.14.30.6482010062TexasHarris4.00.70.00.00.82.00.70.60.20.10.910.00.00.00.00.10.15.20.6482010066TexasHarris4.70.20.00.00.61.90.60.50.20.00.710.50.00.10.00.10.14.40.2482011039TexasHarris3.50.70.00.00.71.70.60.50.20.10.811.40.00.00.00.10.04.80.5484391002TexasTarrant1.01.20.00.00.80.90.10.00.10.60.22.90.00.00.00.00.01.10.2Largest Contributionto DownwindNonattainment =>4.71.41.73.30.82.10.81.10.30.62.311.40.06.10.60.90.15.20.7D-4State-by-State Contributions to 8-Hour Ozone (ppb)NonattainmentReceptorsPart 1b.Source States: Nebraska through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI220330003LouisianaE.BatonRouge0.00.00.00.00.00.10.00.20.00.00.10.00.31.60.00.00.00.0361030002New YorkSuffolk0.00.116.817.71.40.02.80.18.80.00.10.00.40.20.04.22.30.1361030009New YorkSuffolk0.10.114.715.41.70.12.10.18.90.10.10.00.30.20.04.11.50.3421010024PennsylvaniaPhiladelphia0.00.08.00.41.30.02.20.132.70.00.20.01.40.20.04.22.70.0480391004TexasBrazoria0.10.00.00.00.30.00.10.30.10.00.30.01.341.60.00.10.00.1482010051TexasHarris0.10.00.00.00.50.00.10.10.10.00.60.01.538.80.00.20.00.0482010055TexasHarris0.10.00.00.00.60.00.10.10.10.00.60.01.642.00.00.20.00.1482010062TexasHarris0.10.00.00.00.40.00.10.10.10.00.40.01.638.00.00.10.00.0482010066TexasHarris0.00.00.00.10.40.00.10.10.20.00.40.01.633.00.00.20.00.1482011039TexasHarris0.10.00.00.00.30.00.10.10.10.00.30.01.437.50.00.10.00.0484391002TexasTarrant0.20.00.00.00.30.00.02.10.00.00.30.00.652.10.00.10.00.0Largest Contributionto DownwindNonattainment =>0.20.116.80.41.70.12.82.18.90.10.60.01.61.60.04.22.70.3D-5State-by-State Contributions to 8-Hour Ozone (ppb)MaintenanceReceptorsPart 2a.Source States: Alabama through MissouriSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO90010017ConnecticutFairfield0.10.32.00.60.00.00.61.00.10.11.50.10.02.20.40.50.10.20.490011123ConnecticutFairfield0.10.35.60.50.20.10.50.70.10.11.40.10.01.70.40.30.10.20.490013007ConnecticutFairfield0.10.15.30.70.10.10.40.70.10.10.90.10.02.00.50.40.10.10.390093002ConnecticutNew Haven0.10.16.10.70.10.00.50.80.10.10.80.10.02.30.10.50.00.10.3130890002GeorgiaDeKalb4.50.30.00.01.151.80.10.20.00.00.50.70.00.00.00.00.00.90.1131210055GeorgiaFulton4.70.30.00.01.153.60.10.20.00.00.60.70.00.00.00.00.00.90.1361192004New YorkWestchester0.00.21.60.40.20.00.60.90.20.11.20.10.01.50.50.50.20.10.5420170012PennsylvaniaBucks0.30.40.22.50.10.20.60.90.10.11.80.30.04.20.10.50.00.40.6481130069TexasDallas0.51.50.00.00.30.60.20.30.10.80.21.50.00.00.00.10.00.70.5481130087TexasDallas0.61.80.00.00.40.60.40.20.20.70.22.50.00.00.00.00.00.90.6482010024TexasHarris2.60.10.00.00.81.00.50.40.10.00.410.30.00.10.00.10.02.50.1482010029TexasHarris1.40.00.00.02.11.70.10.20.00.00.27.40.00.10.00.10.01.60.0482011050TexasHarris2.01.00.00.00.71.10.50.40.30.20.610.60.00.00.00.00.22.50.6484392003TexasTarrant1.31.00.00.00.61.20.00.00.00.40.12.80.00.00.00.00.01.20.2Largest Contributionto DownwindMaintenance =>4.71.81.62.52.11.70.61.00.30.81.810.60.04.20.50.50.22.50.6D-6State-by-State Contributions to 8-Hour Ozone (ppb)MaintenanceReceptorsPart 2b.Source States: Nebraska through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI90010017ConnecticutFairfield0.00.115.817.70.70.02.60.18.10.00.10.00.60.10.03.12.10.190011123ConnecticutFairfield0.00.113.921.02.00.01.70.15.30.00.30.00.60.10.03.21.40.190013007ConnecticutFairfield0.00.112.022.11.90.01.90.16.60.10.20.00.30.10.03.81.50.190093002ConnecticutNew Haven0.00.011.822.71.80.02.00.16.40.00.20.00.30.10.04.51.60.1130890002GeorgiaDeKalb0.00.00.00.00.60.00.20.10.00.00.70.02.90.60.00.20.10.0131210055GeorgiaFulton0.00.00.00.00.60.00.20.10.00.00.80.03.00.60.00.20.10.0361192004New YorkWestchester0.10.114.625.31.40.02.10.15.80.10.10.00.50.10.12.41.40.2420170012PennsylvaniaBucks0.00.115.22.60.90.02.00.123.80.00.10.01.10.30.13.02.30.1481130069TexasDallas0.20.00.00.00.10.00.12.70.10.00.10.00.447.90.00.10.00.0481130087TexasDallas0.20.00.00.00.20.00.02.50.10.00.20.00.247.70.00.10.00.0482010024TexasHarris0.00.00.00.10.40.00.10.00.20.00.30.00.835.60.00.20.00.1482010029TexasHarris0.00.00.00.00.70.00.10.00.10.00.80.00.340.10.00.20.00.0482011050TexasHarris0.10.00.00.00.30.00.00.70.10.00.30.01.038.60.00.10.00.0484392003TexasTarrant0.10.00.00.00.40.00.11.80.10.00.40.00.650.10.00.20.10.0Largest Contributionto DownwindMaintenance =>0.20.115.822.72.00.02.62.78.10.10.80.03.00.60.14.52.30.2D-7State-by-State Contributions to Annual PM2.5 (μg/m3)NonattainmentReceptorsPart 1a.Source States: Alabama through MissouriReceptors: Nonattainment Sites in Alabama through MichiganSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO10730023AlabamaJefferson3.480.030.000.010.150.610.180.280.040.020.280.110.000.020.000.050.010.070.1310732003AlabamaJefferson2.620.020.000.000.140.630.180.290.040.010.290.110.000.010.000.050.010.060.13130210007GeorgiaBibb0.420.020.000.010.291.630.160.230.040.010.220.080.000.040.000.070.010.030.12130630091GeorgiaClayton0.460.020.000.010.182.020.190.280.040.020.290.070.000.040.000.060.010.030.14131210039GeorgiaFulton0.400.010.000.000.142.300.180.270.030.010.280.060.000.030.000.050.000.020.13170310052IllinoisCook0.030.020.000.000.000.042.001.000.310.050.220.020.000.000.000.520.190.000.28171191007IllinoisMadison0.080.090.000.000.010.081.820.790.280.090.350.080.000.000.000.250.120.011.38171630010IllinoisSaintClair0.080.090.000.000.020.081.740.770.270.090.350.080.000.010.000.250.110.021.32180190006IndianaClark0.180.040.000.000.040.180.661.920.120.031.680.060.000.020.000.240.050.020.29180372001IndianaDubois0.180.060.000.000.040.181.012.660.180.041.520.070.000.020.000.280.080.030.43180970078IndianaMarion0.100.040.000.000.010.100.763.490.140.030.780.040.000.020.000.430.070.010.28180970081IndianaMarion0.100.040.000.000.020.100.773.490.140.030.780.040.000.020.000.430.080.010.28180970083IndianaMarion0.100.040.000.000.020.100.763.490.140.030.780.040.000.020.000.430.070.010.28211110043KentuckyJefferson0.170.040.000.000.040.170.612.090.120.031.850.060.000.020.000.210.050.030.27261630015MichiganWayne0.050.020.000.000.010.060.450.670.100.020.280.010.000.020.002.610.070.000.13261630033MichiganWayne0.040.010.000.000.000.060.470.700.110.010.290.010.000.020.002.710.070.000.13D-8State-by-State Contributions to Annual PM2.5 (μg/m3)NonattainmentReceptorsPart 1b.Source States: Alabama through MissouriReceptors: Nonattainment Sites inOhio through West VirginiaSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO390170016OhioButler0.130.030.000.000.020.130.581.360.110.020.990.030.000.030.000.380.050.010.24390350038OhioCuyahoga0.060.020.000.010.010.080.420.640.090.020.330.020.000.050.000.710.060.010.14390350045OhioCuyahoga0.060.020.000.010.020.090.420.640.100.020.340.020.000.050.000.720.060.010.14390350060OhioCuyahoga0.050.010.000.000.010.080.410.630.090.010.330.010.000.050.000.710.050.000.14390610014OhioHamilton0.130.040.000.010.030.140.571.290.110.031.000.040.000.040.000.360.060.020.24390610042OhioHamilton0.130.030.000.000.020.130.551.330.100.021.150.030.000.030.000.330.050.010.23390610043OhioHamilton0.120.030.000.000.020.130.561.270.110.020.940.030.000.030.000.370.050.010.23390617001OhioHamilton0.130.040.000.010.030.140.571.290.110.031.000.040.000.040.000.360.060.020.24390618001OhioHamilton0.120.030.000.000.020.130.561.280.100.020.990.030.000.030.000.350.050.010.23420030064PennsylvaniaAllegheny0.040.010.000.010.010.070.260.410.050.010.270.010.000.120.000.320.020.000.10420031301PennsylvaniaAllegheny0.050.010.000.010.010.070.280.430.060.010.290.010.000.120.000.350.030.000.11420070014PennsylvaniaBeaver0.050.010.000.010.010.080.300.450.070.010.290.010.000.090.000.380.030.010.11420710007PennsylvaniaLancaster0.030.010.040.200.010.070.220.280.050.010.160.010.010.630.070.280.030.000.08421330008PennsylvaniaYork0.030.010.030.160.010.070.230.300.050.010.180.010.010.620.060.270.030.000.09540110006WestVirginiaCabell0.120.020.000.000.040.190.350.640.070.010.790.030.000.050.000.240.030.010.16540391005WestVirginiaKanawha0.120.020.000.010.030.180.330.590.070.010.610.030.000.080.000.240.020.010.15Largest Contributionto DownwindNonattainment =>0.460.090.040.200.290.631.012.090.310.091.680.110.010.630.070.720.190.071.38D-9State-by-State Contributions to Annual PM2.5 (μg/m3)NonattainmentReceptorsPart 1c.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites in Alabama through MichiganSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI10730023AlabamaJefferson0.020.000.010.020.080.010.240.020.140.000.110.000.330.060.000.060.120.0310732003AlabamaJefferson0.010.000.000.010.080.000.250.010.140.000.100.000.340.050.000.050.120.02130210007GeorgiaBibb0.010.000.010.040.170.000.270.020.260.000.260.000.270.050.000.120.160.02130630091GeorgiaClayton0.020.000.010.040.190.010.300.020.230.000.250.000.360.050.000.110.170.03131210039GeorgiaFulton0.010.000.010.030.190.000.290.010.220.000.260.000.360.040.000.100.160.02170310052IllinoisCook0.060.000.000.020.010.050.370.040.170.000.010.020.120.040.000.010.110.46171191007IllinoisMadison0.080.000.000.020.020.040.400.080.150.000.020.020.250.130.000.010.110.12171630010IllinoisSaintClair0.080.000.000.020.020.040.390.070.150.000.020.020.250.120.000.020.110.12180190006IndianaClark0.030.000.000.060.050.021.080.030.390.000.050.010.670.060.000.060.310.10180372001IndianaDubois0.050.000.000.050.050.030.940.040.330.000.050.010.680.080.000.050.250.15180970078IndianaMarion0.030.000.000.070.030.031.020.030.320.000.020.010.410.050.000.040.200.15180970081IndianaMarion0.040.000.000.070.030.031.020.030.320.000.020.010.410.050.000.040.200.16180970083IndianaMarion0.030.000.000.070.030.031.020.030.320.000.020.010.410.050.000.040.200.16211110043KentuckyJefferson0.030.000.010.050.050.020.980.030.350.000.050.010.630.060.000.050.290.10261630015MichiganWayne0.030.000.000.130.020.021.000.020.390.000.010.000.150.030.000.040.240.19261630033MichiganWayne0.020.000.000.130.010.021.040.020.400.000.010.000.150.030.000.040.240.19D-10State-by-State Contributions to Annual PM2.5 (μg/m3)NonattainmentReceptorsPart 1d.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites inOhio through West VirginiaSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI390170016OhioButler0.030.000.000.100.040.022.160.020.520.000.030.000.500.050.000.060.340.12390350038OhioCuyahoga0.030.000.010.230.030.022.760.020.790.000.010.010.180.030.000.070.450.14390350045OhioCuyahoga0.030.000.010.230.040.022.770.020.800.000.020.010.190.030.000.070.450.15390350060OhioCuyahoga0.020.000.010.220.030.022.760.020.790.000.010.000.180.030.000.060.440.14390610014OhioHamilton0.030.000.010.100.050.032.510.030.540.000.030.010.510.050.000.070.370.12390610042OhioHamilton0.030.000.000.090.040.022.430.020.510.000.030.000.500.040.000.060.350.11390610043OhioHamilton0.030.000.000.100.040.022.270.020.530.000.030.000.480.050.000.060.340.12390617001OhioHamilton0.030.000.010.100.050.032.500.030.540.000.030.010.500.050.000.070.360.12390618001OhioHamilton0.020.000.000.090.040.022.490.020.530.000.030.000.490.040.000.060.360.11420030064PennsylvaniaAllegheny0.010.000.020.190.050.011.260.012.350.000.020.000.170.020.000.120.980.06420031301PennsylvaniaAllegheny0.010.000.020.200.050.011.360.012.330.000.020.000.170.020.000.120.960.07420070014PennsylvaniaBeaver0.020.000.020.210.050.011.490.011.610.000.020.000.170.020.000.100.760.08420710007PennsylvaniaLancaster0.020.010.340.490.120.010.590.013.170.010.040.000.100.020.000.360.400.08421330008PennsylvaniaYork0.020.010.280.450.120.010.640.012.960.000.040.000.110.020.000.340.460.08540110006WestVirginiaCabell0.020.000.010.100.090.011.400.020.690.000.050.000.400.040.000.151.210.08540391005WestVirginiaKanawha0.020.000.020.110.120.011.380.020.830.000.060.000.380.040.000.251.320.07Largest Contributionto DownwindNonattainment =>0.080.010.340.490.190.051.490.080.830.010.260.020.680.130.000.360.980.46D-11State-by-State Contributions to Annual PM2.5 (μg/m3)MaintenanceReceptorsPart 2a.Source States: Alabama through MissouriSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO170313301IllinoisCook0.030.020.000.000.000.041.991.070.250.040.220.020.000.000.000.470.130.000.25170316005IllinoisCook0.030.030.000.000.000.052.141.020.300.050.220.020.000.010.000.500.170.000.27211110044KentuckyJefferson0.180.040.000.000.040.180.631.780.120.021.880.050.000.020.000.220.050.020.27360610056New YorkNew York0.010.000.090.070.000.040.130.160.030.000.090.000.020.130.130.160.020.000.05390350027OhioCuyahoga0.050.010.000.000.010.080.410.630.090.010.330.010.000.040.000.710.050.000.13390350065OhioCuyahoga0.060.020.000.010.010.080.410.630.090.010.330.010.000.050.000.710.050.010.14390610040OhioHamilton0.140.040.010.010.030.140.581.310.120.031.010.040.010.040.010.370.060.020.24390811001OhioJefferson0.060.020.000.010.020.100.330.500.070.010.340.020.000.100.010.380.040.010.13391130032OhioMontgomery0.100.020.000.000.020.110.571.210.110.020.760.020.000.020.000.450.050.010.21391510017OhioStark0.060.020.000.010.020.090.410.660.090.020.400.020.000.060.000.600.050.010.15420110011PennsylvaniaBerks0.020.000.030.140.010.060.200.250.050.010.140.000.010.370.060.250.030.000.07482011035TexasHarris0.110.040.000.000.070.090.160.160.040.020.130.340.000.000.000.020.010.030.13540030003WestVirginiaBerkeley0.040.010.010.050.010.080.230.340.050.010.220.010.000.560.020.230.020.000.10540090005WestVirginiaBrooke0.060.010.000.010.020.090.320.490.070.010.330.020.000.090.000.370.030.000.13540291004WestVirginiaHancock0.070.020.010.020.020.100.330.500.080.020.340.030.010.100.010.380.040.010.13540490006WestVirginiaMarion0.060.010.000.010.020.100.280.440.060.010.340.020.000.130.000.270.030.000.12Largest Contributionto DownwindMaintenance =>0.180.040.090.140.070.180.631.780.300.051.010.340.020.560.130.710.170.030.27D-12State-by-State Contributions to Annual PM2.5 (μg/m3)MaintenanceReceptorsPart 2b.Source States: Nebraska through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI170313301IllinoisCook0.050.000.000.020.010.030.360.030.170.000.010.010.120.040.000.010.110.34170316005IllinoisCook0.060.000.000.030.010.050.370.040.170.000.010.020.130.050.000.010.110.42211110044KentuckyJefferson0.030.000.000.050.050.021.030.030.370.000.040.000.640.060.000.050.300.10360610056New YorkNew York0.010.020.682.720.100.010.300.000.740.010.030.000.060.010.000.170.190.05390350027OhioCuyahoga0.020.000.010.220.030.022.750.020.780.000.010.000.180.020.000.060.440.14390350065OhioCuyahoga0.020.000.010.230.030.022.750.020.790.000.010.010.180.030.000.070.450.14390610040OhioHamilton0.040.000.010.100.050.032.530.030.550.000.040.010.510.050.000.080.370.13390811001OhioJefferson0.020.000.020.200.060.022.070.021.300.000.030.010.210.030.000.121.170.09391130032OhioMontgomery0.030.000.000.110.030.022.050.020.500.000.020.000.410.040.000.050.320.13391510017OhioStark0.030.000.010.210.040.022.360.020.940.000.020.000.230.030.000.090.720.12420110011PennsylvaniaBerks0.010.010.300.470.100.010.490.012.860.000.030.000.090.010.000.280.310.07482011035TexasHarris0.020.000.000.010.020.010.080.050.050.000.020.000.142.780.000.010.030.02540030003WestVirginiaBerkeley0.010.000.110.270.110.010.770.011.600.000.040.000.140.020.000.370.960.06540090005WestVirginiaBrooke0.020.000.020.200.050.012.030.011.260.000.030.000.200.030.000.111.150.08540291004WestVirginiaHancock0.030.010.030.210.060.021.800.021.330.000.030.010.210.030.000.121.120.09540490006WestVirginiaMarion0.020.000.020.150.080.011.230.011.340.000.040.000.230.030.000.172.430.07Largest Contributionto DownwindMaintenance =>0.060.020.680.470.110.052.030.051.600.010.040.020.640.060.000.371.170.42D-13State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1a.Source States: Alabama through MissouriReceptors: Nonattainment Sites in Alabama through IllinoisSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO10730023AlabamaJefferson7.540.050.000.010.060.950.490.830.050.020.870.230.000.060.000.140.010.090.2810732003AlabamaJefferson4.620.020.010.010.070.760.400.910.040.020.790.080.010.040.010.100.010.090.1790091123ConnecticutNewHaven0.090.042.080.300.030.200.470.640.080.030.550.020.190.630.670.280.020.010.29170310052IllinoisCook0.060.100.000.010.010.107.693.320.930.260.680.040.000.040.001.150.160.020.92170310057IllinoisCook0.050.050.010.010.010.088.753.781.000.330.420.030.010.060.011.830.140.010.84170310076IllinoisCook0.030.040.010.010.010.046.584.420.440.160.650.020.010.090.011.800.100.010.59170311016IllinoisCook0.030.070.000.000.000.066.383.920.560.110.750.020.000.040.001.580.100.010.65170312001IllinoisCook0.040.050.010.010.010.064.316.330.410.070.720.020.010.080.012.350.080.010.38170313103IllinoisCook0.040.070.000.000.000.059.163.370.900.300.490.020.000.020.002.060.140.010.89170313301IllinoisCook0.040.050.020.020.020.047.344.440.610.260.520.030.020.090.021.910.120.020.69170316005IllinoisCook0.040.060.000.000.000.087.853.680.820.290.520.020.000.030.001.580.110.010.77171190023IllinoisMadison0.200.080.000.000.000.257.073.430.300.031.830.020.000.010.000.500.030.015.03171191007IllinoisMadison0.160.200.010.010.020.165.702.640.430.251.340.060.010.050.011.180.070.033.72171192009IllinoisMadison0.150.180.010.020.020.196.693.180.340.121.690.060.010.060.010.610.120.034.68171193007IllinoisMadison0.140.160.000.010.010.216.823.640.230.041.980.030.000.030.000.560.040.014.86D-14State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1b.Source States: Alabama through MissouriReceptors: Nonattainment Sitesin Indiana through MarylandSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO180190006IndianaClark0.120.060.000.010.010.072.606.300.190.036.190.020.000.030.000.310.020.010.99180372001IndianaDubois0.170.060.000.010.010.172.628.790.280.085.970.040.000.030.000.340.080.011.13180830004IndianaKnox0.090.050.000.000.010.092.098.110.260.084.510.010.000.020.000.460.100.011.04180890022IndianaLake0.030.030.000.000.000.034.166.880.640.240.300.010.000.010.001.450.060.010.67180890026IndianaLake0.040.020.000.000.000.043.595.560.450.180.750.010.000.060.002.100.100.010.61180970042IndianaMarion0.130.050.000.000.000.122.1610.910.150.015.480.010.000.030.000.190.010.011.22180970043IndianaMarion0.180.080.010.020.020.191.9210.830.160.034.990.040.010.080.010.230.030.021.16180970066IndianaMarion0.110.040.000.000.000.092.0811.370.140.015.060.010.000.040.000.210.010.001.18180970078IndianaMarion0.180.080.010.020.020.201.9110.750.160.034.970.040.010.080.010.230.030.031.15180970079IndianaMarion0.110.040.000.000.000.082.139.850.150.015.200.010.000.040.000.250.010.001.20180970081IndianaMarion0.210.080.010.020.020.261.649.910.140.034.760.040.010.080.010.190.030.021.06180970083IndianaMarion0.140.040.000.000.000.151.9811.350.130.015.210.010.000.040.000.190.010.001.18181570008IndianaTippecanoe0.240.110.020.020.020.291.565.910.120.033.110.040.010.160.020.310.030.030.97191630019IowaScott0.190.110.000.000.000.233.913.492.250.082.290.020.000.060.001.130.090.011.84210590005KentuckyDaviess0.170.070.000.000.010.092.969.910.130.0210.030.030.000.010.000.330.010.011.27211110043KentuckyJefferson0.180.070.020.030.030.182.307.780.140.046.890.060.020.080.030.150.030.030.84211110044KentuckyJefferson0.130.060.000.010.010.102.426.660.120.027.350.040.000.050.010.140.010.010.93211110048KentuckyJefferson0.130.070.010.020.020.102.185.980.120.026.590.050.010.060.010.140.020.020.84245100040MarylandBaltimoreCity0.150.020.070.200.080.400.250.330.070.020.300.050.036.650.100.090.020.010.18245100049MarylandBaltimoreCity0.140.020.080.210.070.380.230.310.060.010.290.040.036.630.120.070.010.010.16D-15State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1c.Source States: Alabama through MissouriReceptors: Nonattainment Sites inMichigan through New YorkSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO261150005MichiganMonroe0.360.090.010.020.030.311.303.530.140.042.460.110.000.170.012.450.020.040.58261250001MichiganOakland0.210.030.000.010.000.181.513.210.160.031.620.100.000.120.004.340.020.020.35261470005MichiganSt. Clair0.130.020.000.010.000.111.101.910.120.020.960.080.000.130.003.290.020.010.23261610008MichiganWashtenaw0.310.050.000.020.010.261.483.300.160.041.710.140.000.120.003.880.030.040.38261630015MichiganWayne0.350.060.000.010.060.291.313.030.120.031.950.160.000.080.005.340.020.050.45261630016MichiganWayne0.040.010.010.020.010.051.732.990.210.040.670.010.010.110.016.590.040.010.18261630019MichiganWayne0.030.010.000.010.000.041.542.820.160.020.710.000.000.080.004.530.020.000.21261630033MichiganWayne0.270.050.010.020.050.221.693.240.190.051.490.120.010.110.016.350.040.040.38261630036MichiganWayne0.310.090.010.030.070.261.713.010.210.061.520.170.010.120.014.300.040.060.57290990012MissouriJefferson0.110.080.000.000.000.086.473.430.430.041.660.030.000.010.000.510.080.016.82291831002MissouriSaintCharles0.130.140.010.010.010.196.103.670.320.042.010.030.010.040.010.610.070.025.54295100007MissouriSt. LouisCity0.100.070.000.000.000.076.833.290.400.031.600.030.000.000.000.450.070.017.74295100087MissouriSt. LouisCity0.220.110.000.000.010.256.423.200.340.041.730.030.000.030.000.560.030.024.76340171003NewJerseyHudson0.070.030.080.340.020.250.250.380.040.020.400.020.010.760.170.170.010.010.17340172002NewJerseyHudson0.090.020.380.340.040.260.200.340.040.020.340.030.020.710.330.160.010.010.13340390004NewJerseyUnion0.150.030.250.360.050.370.370.580.070.010.460.050.060.570.260.200.010.010.19360050080NewYorkBronx0.090.030.190.320.030.270.280.440.050.020.410.030.010.640.140.190.020.010.15360610056NewYorkNew York0.120.050.410.330.060.320.280.400.080.030.320.060.040.680.370.230.030.030.16360610128NewYorkNew York0.110.040.350.290.030.220.510.810.070.020.580.040.080.600.360.390.010.010.27D-16State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1d.Source States: Alabama through MissouriReceptors: Nonattainment Sites in OhioSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO390170003OhioButler0.260.040.000.010.000.331.846.090.090.006.530.030.000.080.000.260.000.010.96390170016OhioButler0.290.060.010.030.020.351.595.220.150.025.050.040.010.160.010.280.020.020.91390170017OhioButler0.220.020.000.000.000.271.525.020.070.005.380.020.000.060.000.210.000.000.79390171004OhioButler0.280.030.000.010.000.351.364.820.060.005.250.030.000.060.000.240.000.010.75390350038OhioCuyahoga0.160.040.010.020.040.190.701.690.090.021.230.030.010.300.011.650.030.020.29390350045OhioCuyahoga0.120.020.010.020.010.140.561.390.090.020.910.020.010.250.011.920.040.010.14390350060OhioCuyahoga0.090.000.000.010.000.100.591.320.100.010.730.010.000.200.001.930.050.000.12390350065OhioCuyahoga0.110.040.010.020.040.130.711.500.110.020.890.030.010.220.011.570.050.010.26390490024OhioFranklin0.150.070.010.020.010.210.902.740.130.031.920.080.010.140.010.980.040.030.43390490025OhioFranklin0.160.070.010.030.020.200.992.650.160.051.840.080.010.180.021.060.060.030.44390610006OhioHamilton0.380.070.000.020.020.381.535.120.130.025.120.110.000.110.010.330.010.040.94390610014OhioHamilton0.480.060.000.020.030.540.953.680.070.014.280.130.000.120.000.380.010.050.65390610040OhioHamilton0.190.040.000.000.000.131.574.270.130.004.400.030.000.080.000.320.010.010.93390610042OhioHamilton0.230.050.000.000.010.191.293.670.120.014.290.060.000.050.000.340.010.020.80390610043OhioHamilton0.230.090.010.030.030.171.915.540.190.035.190.070.010.110.020.280.030.031.12390617001OhioHamilton0.310.070.010.020.020.291.424.160.140.024.440.090.010.130.010.370.020.030.88390618001OhioHamilton0.360.060.000.010.030.381.133.580.120.023.680.100.000.110.000.530.020.040.62390811001OhioJefferson0.040.020.000.010.000.090.631.370.080.020.850.000.000.080.000.940.040.000.26391130032OhioMontgomery0.320.040.000.020.010.391.304.380.080.014.990.050.000.160.000.350.010.020.70391530017OhioSummit0.100.060.000.010.000.141.041.910.140.020.900.020.000.190.011.800.090.010.33D-17State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1e.Source States: Alabama through MissouriReceptors: Nonattainment Sites inPennsylvania through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO420030008PennsylvaniaAllegheny0.010.010.000.010.000.020.330.700.030.000.470.000.000.110.000.520.010.000.12420030064PennsylvaniaAllegheny0.050.020.000.010.000.060.510.980.070.020.680.010.000.070.000.620.040.010.26420030093PennsylvaniaAllegheny0.170.060.010.020.020.150.601.220.070.021.100.090.000.120.010.440.020.030.34420030116PennsylvaniaAllegheny0.030.040.000.020.000.050.621.260.070.020.990.010.000.170.010.470.010.010.35420031008PennsylvaniaAllegheny0.140.050.000.010.010.150.651.430.070.021.170.060.000.120.000.720.010.020.34420031301PennsylvaniaAllegheny0.060.040.010.030.020.070.531.060.070.030.820.020.010.120.010.730.030.020.28420070014PennsylvaniaBeaver0.080.030.000.010.000.080.641.340.090.010.810.010.000.180.010.840.030.000.26420110011PennsylvaniaBerks0.130.030.170.330.060.280.450.570.120.030.430.050.091.870.240.300.060.020.18420210011PennsylvaniaCambria0.030.040.010.010.010.020.621.550.070.020.840.020.010.140.011.200.030.010.26420430401PennsylvaniaDauphin0.100.020.170.500.050.240.250.390.060.020.290.040.082.150.260.390.040.020.10420710007PennsylvaniaLancaster0.130.030.190.310.070.270.220.260.080.030.200.060.112.630.280.250.040.030.11421330008PennsylvaniaYork0.160.020.160.340.050.350.340.570.070.010.490.060.082.040.230.300.030.020.15471251009TennesseeMontgomery0.270.060.000.020.020.242.733.320.240.033.490.030.000.110.000.640.070.021.20540090011WestVirginiaBrooke0.040.030.020.030.020.060.891.370.200.050.420.020.020.250.021.190.140.020.30550790010WisconsinMilwaukee0.010.010.000.000.000.027.282.701.870.770.620.000.000.010.001.640.880.001.09550790026WisconsinMilwaukee0.040.030.010.010.010.065.242.241.570.380.560.010.010.030.011.380.910.010.93550790043WisconsinMilwaukee0.040.020.000.000.000.105.533.920.940.251.020.010.000.030.001.180.530.000.90550790099WisconsinMilwaukee0.020.020.000.000.000.056.172.821.630.450.730.000.000.010.001.680.710.001.17Largest Contributionto DownwindNonattainment =>0.480.200.410.500.080.957.289.911.870.776.530.230.192.630.672.350.910.095.03D-18State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1f.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites in Alabama through IllinoisSource StatesReceptorMonitor IDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI10730023AlabamaJefferson0.020.000.010.060.160.011.000.030.600.000.130.001.030.100.000.150.650.0210732003AlabamaJefferson0.020.010.010.030.090.010.790.020.350.010.120.010.920.040.010.080.350.0290091123ConnecticutNewHaven0.030.211.243.470.300.011.200.052.570.050.120.000.350.080.060.721.010.07170310052IllinoisCook0.200.000.010.210.040.071.380.160.710.000.030.050.260.160.000.060.500.67170310057IllinoisCook0.250.010.010.200.030.061.170.160.780.010.030.050.160.130.010.050.470.79170310076IllinoisCook0.130.010.010.190.030.031.950.081.390.010.020.020.210.050.010.080.900.46170311016IllinoisCook0.140.000.000.240.010.021.740.071.160.000.000.010.300.070.000.060.770.49170312001IllinoisCook0.100.010.010.140.030.031.820.041.200.010.020.020.240.030.010.090.840.36170313103IllinoisCook0.240.000.000.150.020.050.950.110.430.000.010.030.210.100.000.050.340.71170313301IllinoisCook0.190.020.020.180.030.041.450.121.010.020.020.040.180.060.020.070.650.55170316005IllinoisCook0.210.000.000.160.030.041.140.130.630.000.020.030.200.100.000.060.450.65171190023IllinoisMadison0.020.000.000.010.020.001.780.080.350.000.020.001.150.130.000.030.370.16171191007IllinoisMadison0.050.010.010.120.040.032.010.080.930.010.030.021.010.210.010.050.530.12171192009IllinoisMadison0.100.010.020.090.040.031.720.120.700.010.040.031.030.160.010.070.540.24171193007IllinoisMadison0.030.000.010.040.030.011.760.110.590.000.030.011.120.140.000.050.540.16D-19State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1g.Source States: Nebraska through WisconsinReceptors: Nonattainment Sitesin Indiana through MarylandSource StatesReceptorMonitor IDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI180190006IndianaClark0.030.000.010.090.030.011.980.060.720.000.020.012.040.080.000.050.630.06180372001IndianaDubois0.050.000.010.090.030.032.730.060.580.000.030.011.860.070.000.050.390.12180830004IndianaKnox0.050.000.000.140.020.033.680.050.460.000.020.021.120.040.000.030.250.15180890022IndianaLake0.180.000.000.110.010.030.510.110.220.000.010.020.070.040.000.010.100.45180890026IndianaLake0.140.000.000.150.020.031.720.060.980.000.010.020.240.040.000.050.690.46180970042IndianaMarion0.010.000.000.060.040.003.710.010.740.000.030.001.960.010.000.070.820.03180970043IndianaMarion0.030.010.020.090.070.023.510.030.820.010.060.012.290.040.010.100.850.06180970066IndianaMarion0.010.000.000.060.040.003.740.010.760.000.030.001.810.010.000.070.830.04180970078IndianaMarion0.030.010.020.100.070.023.480.030.820.010.060.012.300.040.010.100.850.07180970079IndianaMarion0.010.000.000.070.040.004.130.010.840.000.030.001.810.010.000.080.930.04180970081IndianaMarion0.030.010.020.090.060.023.110.020.840.010.050.012.750.040.010.090.810.06180970083IndianaMarion0.010.000.000.060.030.003.650.010.820.000.020.002.360.010.000.060.850.03181570008IndianaTippecanoe0.020.010.030.200.080.023.640.031.790.010.050.011.960.040.010.151.660.07191630019IowaScott0.040.000.000.110.060.023.060.142.100.000.030.001.160.070.000.111.210.80210590005KentuckyDaviess0.010.000.000.020.020.001.380.030.170.000.020.001.760.050.000.020.160.03211110043KentuckyJefferson0.030.020.030.080.070.031.510.040.450.020.060.021.570.060.020.090.600.05211110044KentuckyJefferson0.010.000.020.030.040.011.210.030.450.000.030.001.650.050.000.100.650.03211110048KentuckyJefferson0.020.010.020.040.040.011.090.030.420.010.030.011.490.060.010.100.590.03245100040MarylandBaltimoreCity0.030.030.330.440.490.010.500.041.930.010.190.000.210.100.011.290.640.04245100049MarylandBaltimoreCity0.020.030.350.490.500.000.480.022.050.010.190.000.200.080.011.320.650.02D-20State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1h.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites inMichigan through New YorkSource StatesReceptorMonitor IDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI261150005MichiganMonroe0.040.000.030.260.080.015.390.041.730.000.050.011.640.060.000.171.320.13261250001MichiganOakland0.040.000.020.330.060.004.660.021.840.000.010.001.100.030.000.151.350.26261470005MichiganSt. Clair0.030.000.020.780.040.003.450.021.830.000.010.000.650.020.000.141.040.13261610008MichiganWashtenaw0.050.000.030.360.060.014.560.041.490.000.030.001.300.050.000.141.020.24261630015MichiganWayne0.030.000.020.260.060.014.090.041.310.000.030.001.420.050.000.110.960.17261630016MichiganWayne0.070.010.020.600.020.013.710.021.730.010.010.010.330.020.010.080.890.38261630019MichiganWayne0.040.000.010.550.010.003.370.011.500.000.000.000.330.010.000.070.700.26261630033MichiganWayne0.060.010.030.460.060.023.980.041.440.010.030.011.070.050.010.110.870.28261630036MichiganWayne0.070.010.040.590.050.024.020.071.310.010.030.011.020.090.010.100.690.16290990012MissouriJefferson0.020.000.000.010.020.012.280.110.550.000.010.001.110.170.000.030.550.22291831002MissouriSaintCharles0.030.010.010.040.030.021.700.060.620.010.030.021.140.060.010.050.570.21295100007MissouriSt. LouisCity0.020.000.000.010.010.002.170.100.550.000.010.000.990.150.000.030.550.20295100087MissouriSt. LouisCity0.030.000.010.030.030.011.870.080.520.000.030.011.190.120.000.050.430.15340171003NewJerseyHudson0.020.024.674.060.400.010.850.042.280.030.170.010.260.070.010.910.820.03340172002NewJerseyHudson0.020.034.205.820.370.010.700.032.230.050.160.000.210.060.010.740.690.03340390004NewJerseyUnion0.020.073.282.420.400.001.070.022.840.020.180.000.370.060.020.760.900.04360050080NewYorkBronx0.020.022.696.670.380.010.940.032.550.020.170.010.290.050.010.720.860.04360610056NewYorkNew York0.040.112.567.990.370.020.740.052.400.050.180.010.250.090.040.720.620.06360610128NewYorkNew York0.020.092.675.660.280.001.480.033.290.020.120.000.400.050.020.591.200.07D-21State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1i.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites in OhioSource StatesReceptorMonitor IDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI390170003OhioButler0.000.000.010.070.060.007.480.001.080.000.040.003.920.010.000.151.260.02390170016OhioButler0.020.010.030.100.070.025.130.021.260.010.050.013.290.040.010.151.000.09390170017OhioButler0.000.000.010.050.050.006.160.000.890.000.030.003.230.010.000.121.030.01390171004OhioButler0.000.000.010.050.040.006.450.000.890.000.030.003.190.010.000.100.980.01390350038OhioCuyahoga0.020.000.030.530.090.029.090.023.620.000.040.010.560.020.000.242.530.09390350045OhioCuyahoga0.030.010.030.780.070.029.480.012.940.010.030.010.400.010.010.202.140.11390350060OhioCuyahoga0.020.000.030.990.050.019.680.002.740.000.020.000.300.000.000.151.670.13390350065OhioCuyahoga0.030.010.040.830.060.028.920.023.130.010.030.010.380.020.010.161.630.11390490024OhioFranklin0.040.010.030.350.090.027.450.022.120.000.040.011.010.030.000.192.100.11390490025OhioFranklin0.050.010.050.410.120.047.070.042.150.010.050.020.970.050.010.281.740.13390610006OhioHamilton0.020.000.020.100.060.016.260.021.080.000.040.003.480.050.000.140.880.07390610014OhioHamilton0.010.000.020.130.060.016.590.021.430.000.050.003.100.040.000.141.010.06390610040OhioHamilton0.010.000.010.110.030.006.350.011.600.000.010.003.200.020.000.101.130.08390610042OhioHamilton0.010.000.000.130.020.007.080.010.900.000.020.002.830.040.000.060.590.09390610043OhioHamilton0.030.010.030.090.070.025.490.040.880.010.040.013.430.070.010.140.790.10390617001OhioHamilton0.020.010.020.140.060.016.530.021.590.010.040.013.230.050.010.141.130.09390618001OhioHamilton0.020.000.020.180.050.016.420.021.420.000.040.002.530.050.000.130.890.08390811001OhioJefferson0.030.000.020.180.040.025.870.012.340.000.020.000.370.020.000.103.410.10391130032OhioMontgomery0.010.000.030.140.100.007.000.001.430.000.050.003.100.010.000.291.770.05391530017OhioSummit0.040.000.030.380.060.038.820.042.970.000.020.000.480.040.000.152.440.26D-22State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)NonattainmentReceptorsPart 1j.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites inPennsylvania through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI420030008PennsylvaniaAllegheny0.000.000.010.130.020.003.240.004.830.000.000.000.180.010.000.172.970.03420030064PennsylvaniaAllegheny0.030.000.010.110.060.023.660.014.900.000.030.000.270.020.000.142.310.11420030093PennsylvaniaAllegheny0.030.000.030.140.060.024.130.034.490.000.020.010.560.040.000.193.510.05420030116PennsylvaniaAllegheny0.020.000.020.150.070.014.040.024.850.000.020.000.370.020.000.263.420.04420031008PennsylvaniaAllegheny0.020.000.020.210.060.015.210.026.020.000.010.000.600.040.000.153.110.07420031301PennsylvaniaAllegheny0.030.010.030.190.050.024.450.035.230.010.020.010.390.040.010.143.070.07420070014PennsylvaniaBeaver0.020.000.030.230.070.014.990.024.070.000.010.000.330.030.000.222.800.13420110011PennsylvaniaBerks0.040.070.861.020.360.031.000.039.020.030.140.020.290.060.031.020.940.12420210011PennsylvaniaCambria0.020.010.020.320.060.024.740.0313.380.010.010.010.390.040.010.142.260.11420430401PennsylvaniaDauphin0.020.091.021.150.360.021.080.0210.880.040.150.010.190.050.041.040.980.11420710007PennsylvaniaLancaster0.040.100.941.020.370.030.580.049.970.050.140.020.180.070.051.200.590.09421330008PennsylvaniaYork0.020.080.831.170.350.011.410.0112.160.020.160.000.360.050.031.161.480.10471251009TennesseeMontgomery0.040.000.020.110.100.022.750.041.130.000.040.015.250.050.000.191.460.12540090011WestVirginiaBrooke0.070.020.050.310.050.075.840.043.670.010.030.030.120.040.020.172.250.33550790010WisconsinMilwaukee0.620.000.000.040.010.200.440.140.230.000.000.080.130.040.000.010.126.21550790026WisconsinMilwaukee0.420.010.010.120.020.270.950.150.470.010.020.130.170.100.010.030.295.19550790043WisconsinMilwaukee0.250.000.000.100.020.142.120.110.890.000.030.060.280.080.000.040.613.93550790099WisconsinMilwaukee0.430.000.000.070.010.181.110.140.510.000.010.090.180.070.000.020.325.23Largest Contributionto DownwindNonattainment =>0.620.212.695.820.500.275.840.163.670.050.190.133.920.210.061.323.510.80D-23State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)MaintenanceReceptorsPart 2a.Source States: Alabama through MissouriReceptors: Nonattainment Sites in the District of Columbiathrough New YorkSource StatesReceptorMonitor IDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO110010041District OfColumbiaDistrict OfColumbia0.110.040.130.170.060.190.430.650.110.060.490.050.063.670.180.360.050.030.27110010042District OfColumbiaDistrict OfColumbia0.090.020.100.130.030.200.410.600.080.050.480.030.053.400.170.280.030.010.28170310022IllinoisCook0.010.030.000.000.000.034.238.940.560.240.410.010.000.000.001.870.050.000.65170310050IllinoisCook0.060.070.010.020.010.074.885.090.410.170.970.030.010.090.011.660.080.020.69170314007IllinoisCook0.070.060.000.010.010.138.294.390.840.321.170.040.000.060.011.240.120.011.13171630010IllinoisSaint Clair0.220.110.000.000.010.266.593.260.340.041.760.040.000.020.000.550.040.024.82171971002IllinoisWill0.070.100.000.000.000.096.483.820.680.130.980.050.000.050.001.430.100.020.70180390003IndianaElkhart0.200.100.000.000.020.312.196.340.390.101.870.180.000.050.000.680.090.030.60180431004IndianaFloyd0.140.050.000.010.010.092.397.240.130.016.910.020.000.030.000.140.010.010.98181670023IndianaVigo0.120.090.010.010.020.053.109.110.340.123.190.030.010.040.010.770.100.021.47191390015IowaMuscatine0.140.170.000.010.030.154.351.713.570.420.690.100.000.030.000.800.860.041.08210290006KentuckyBullitt0.190.090.030.040.040.162.445.990.130.047.110.070.030.120.030.220.030.040.99211451004KentuckyMcCracken0.220.070.000.000.000.162.616.470.060.014.990.020.000.020.000.320.000.011.76212270007KentuckyWarren0.220.070.010.020.020.202.925.750.140.024.780.030.010.100.010.740.020.020.99240031003MarylandAnneArundel0.080.020.200.330.040.180.290.410.090.020.390.020.086.840.310.210.020.010.18245100035MarylandBaltimoreCity0.140.020.050.170.070.380.240.330.060.020.280.040.026.450.070.110.020.010.17261630001MichiganWayne0.190.020.000.010.010.171.122.860.100.011.750.050.000.100.003.940.010.010.32295100085MissouriSt. LouisCity0.170.100.020.020.030.196.573.480.490.081.730.060.020.050.020.400.110.037.41360610062New YorkNew York0.120.030.700.320.060.310.320.440.070.030.370.050.190.670.710.220.020.020.19360610079New YorkNew York0.100.040.070.350.040.290.380.530.070.030.490.040.010.730.110.290.020.020.24D-24State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)MaintenanceReceptorsPart 2b.Source States: Alabama through MissouriReceptors: Nonattainment Sites in Ohio through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyALARCTDEFLGAILINIAKSKYLAMEMD/DCMAMIMNMSMO390350027OhioCuyahoga0.050.010.000.000.010.070.691.350.110.010.620.010.000.140.001.650.040.000.20390350034OhioCuyahoga0.080.010.000.000.000.080.721.860.110.010.860.010.000.180.002.780.060.000.18390810017OhioJefferson0.030.030.000.020.000.060.721.480.080.020.940.010.000.160.010.780.030.000.37390950024OhioLucas0.060.010.000.010.000.121.493.330.190.021.030.000.000.110.003.350.020.000.19390950026OhioLucas0.250.060.010.020.080.361.203.560.130.042.050.070.010.150.012.000.020.030.42390990014OhioMahoning0.070.030.000.010.030.130.701.320.110.020.680.010.000.190.011.480.070.010.24391130031OhioMontgomery0.230.030.000.010.000.291.133.470.090.013.570.030.000.110.000.540.020.010.51391351001OhioPreble0.320.080.010.030.020.411.405.140.110.034.790.040.010.130.010.760.030.030.84391550007OhioTrumbull0.080.020.000.020.010.130.651.230.120.020.580.010.000.240.001.540.080.010.16420030095PennsylvaniaAllegheny0.040.040.010.020.010.060.651.220.100.020.800.020.010.170.010.640.050.010.30420033007PennsylvaniaAllegheny0.050.040.010.020.010.060.581.210.070.020.890.020.000.130.010.710.010.010.28420410101PennsylvaniaCumberland0.100.010.120.360.040.250.230.370.030.010.290.030.051.820.190.240.010.010.11421255001PennsylvaniaWashington0.070.030.010.010.010.200.701.480.120.030.850.010.000.190.010.890.050.010.29471650007TennesseeSumner0.230.090.020.030.030.202.104.290.190.044.270.050.020.140.020.800.030.030.95540090005WestVirginiaBrooke0.030.020.010.020.000.070.671.270.120.020.620.010.000.160.010.950.070.000.24550250047WisconsinDane0.050.050.000.000.000.093.871.811.670.290.710.010.000.020.000.990.770.001.31550790059WisconsinMilwaukee0.040.050.000.000.000.085.933.411.170.450.930.080.000.030.001.380.530.010.96551330027WisconsinWaukesha0.050.080.010.010.010.113.262.430.650.090.790.080.010.060.010.960.350.020.71Largest Contributionto DownwindMaintenance =>0.320.170.700.360.080.416.578.941.670.456.910.180.191.820.713.350.860.044.82D-25State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)MaintenanceReceptorsPart 2c.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites in the District of Columbiathrough New YorkSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI110010041District OfColumbiaDistrict OfColumbia0.060.060.370.800.290.041.920.064.340.040.130.030.240.080.032.262.320.11110010042District OfColumbiaDistrict OfColumbia0.050.040.310.740.280.021.440.043.340.020.110.010.200.070.012.121.730.09170310022IllinoisCook0.140.000.000.110.010.010.730.090.370.000.000.010.160.030.000.020.230.44170310050IllinoisCook0.120.010.020.130.040.032.180.081.200.010.020.020.290.050.010.090.880.36170314007IllinoisCook0.230.000.010.080.040.041.880.130.890.000.040.030.380.080.000.080.730.70171630010IllinoisSaint Clair0.030.000.010.020.040.011.840.090.470.000.030.011.180.130.000.050.420.16171971002IllinoisWill0.160.000.000.230.030.031.790.090.960.000.010.020.410.090.000.070.690.57180390003IndianaElkhart0.100.000.010.280.070.032.240.070.890.000.060.011.010.100.000.110.720.35180431004IndianaFloyd0.010.000.010.050.030.011.560.030.440.000.020.002.320.040.000.050.580.03181670023IndianaVigo0.070.010.010.170.040.043.450.070.740.010.020.031.360.060.010.070.440.21191390015IowaMuscatine0.390.000.010.100.060.151.080.210.610.000.040.090.460.280.000.060.401.01210290006KentuckyBullitt0.030.030.040.090.080.032.200.050.650.030.060.032.040.080.030.150.980.06211451004KentuckyMcCracken0.010.000.010.030.050.001.130.020.290.000.040.002.660.030.000.050.220.03212270007KentuckyWarren0.020.010.030.060.070.011.830.030.600.010.030.014.700.030.010.160.940.05240031003MarylandAnneArundel0.040.080.651.170.300.011.230.044.860.030.120.010.240.060.031.421.690.05245100035MarylandBaltimore(City0.030.020.300.380.440.010.500.041.750.000.170.000.200.100.001.230.590.05261630001MichiganWayne0.020.000.010.300.050.005.290.011.870.000.010.001.080.020.000.151.500.24295100085MissouriSt. LouisCity0.060.020.020.030.040.031.520.140.240.020.040.030.960.180.020.060.360.23360610062New YorkNew York0.030.234.745.760.450.010.790.042.210.060.190.010.240.080.070.800.720.05360610079New YorkNew York0.030.012.687.300.420.021.110.052.600.030.190.010.330.080.010.890.980.06D-26State-by-State Contributionsto 24-Hour PM2.5 (μg/m3)MaintenanceReceptorsPart 2d.Source States: Nebraska through WisconsinReceptors: Nonattainment Sites in Ohio through WisconsinSource StatesReceptorMonitorIDReceptorStateReceptorCountyNENHNJNYNCNDOHOKPARISCSDTNTXVTVAWVWI390350027OhioCuyahoga0.020.000.031.100.020.019.310.012.790.000.010.000.220.010.000.091.040.12390350034OhioCuyahoga0.030.000.000.720.040.018.520.012.340.000.010.000.330.010.000.131.320.23390810017OhioJefferson0.020.000.030.220.050.025.570.012.520.000.010.000.350.020.000.193.300.09390950024OhioLucas0.050.000.010.510.030.005.670.011.540.000.010.000.470.010.000.101.030.22390950026OhioLucas0.050.010.020.480.090.016.140.041.890.010.050.011.520.040.010.171.530.13390990014OhioMahoning0.030.000.020.300.060.037.130.023.040.000.020.010.370.030.000.171.620.21391130031OhioMontgomery0.020.000.020.170.060.006.050.011.260.000.030.002.130.010.000.191.310.06391351001OhioPreble0.020.010.030.160.090.025.520.021.030.010.060.012.990.030.010.161.120.11391550007OhioTrumbull0.030.000.020.270.090.026.730.023.170.000.030.010.370.020.000.242.070.26420030095PennsylvaniaAllegheny0.030.010.030.220.070.033.970.025.180.010.020.010.300.030.010.202.610.14420033007PennsylvaniaAllegheny0.020.000.030.180.080.024.610.025.560.000.040.000.360.020.000.213.560.06420410101PennsylvaniaCumberland0.010.060.830.910.330.000.910.018.230.020.160.000.190.030.020.991.050.05421255001PennsylvaniaWashington0.050.000.020.160.170.025.130.033.420.000.080.010.400.040.000.224.830.12471650007TennesseeSumner0.040.020.040.090.100.022.270.050.860.020.050.026.450.050.020.241.590.08540090005WestVirginiaBrooke0.030.000.030.240.040.035.560.023.000.000.020.010.240.020.000.132.840.19550250047WisconsinDane0.310.000.000.090.020.121.270.200.770.000.020.070.340.110.000.030.383.64550790059WisconsinMilwaukee0.360.000.000.090.020.131.430.110.630.000.020.050.270.090.000.040.524.30551330027WisconsinWaukesha0.130.010.010.160.040.131.630.090.730.010.030.060.280.120.010.090.652.32Largest Contributionto DownwindMaintenance =>0.390.234.741.170.450.155.560.214.860.060.190.094.700.280.072.264.831.01

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix E

Upwind States to Downwind Nonattainment and

Maintenance LinkagesE-2**Table E-1. Upwind State-to-Downwind Nonattainment Site “Linkages” for Annual PM 2.5** **. Upwind** **State Number** **of Linkages Counties Containing Downwind Annual PM** **2.5 Nonattainment Sites (Monitoring Site ID)** Alabama6Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Clark, IN(180190006)Dubois, IN(180372001)Jefferson,KY(211110043)Delaware2Lancaster,PA(420710007)York, PA(421330008)Florida3Jefferson,AL(10730023)Bibb, GA(130210007)Clayton, GA(130630091)Georgia7Jefferson,AL(10730023)Jefferson,AL(10732003)Clark, IN(180190006)Dubois, IN(180372001)Jefferson,KY(211110043)Kanawha, WV(540391005)Cabell, WV(540110006)Illinois29Jefferson,AL(10730023)Jefferson,AL(10732003)Fulton, GA(131210039)Bibb, GA(130210007)Clayton, GA(130630091)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)Indiana27Jefferson,AL(10730023)Jefferson,AL(10732003)Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390618001)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Allegheny,PA(420030064)E-3**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Nonattainment Sites (Monitoring Site ID)**Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)Iowa4Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Dubois, IN(180372001)Kentucky31Jefferson,AL(10730023)Jefferson,AL(10732003)Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Wayne, MI(261630015)Wayne, MI(261630033)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)Maryland/DC2Lancaster,PA(420710007)York, PA(421330008)Michigan25Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)Minnesota1Cook, IL(170310052)E-4**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Nonattainment Sites (Monitoring Site ID)**Missouri17Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Butler, OH(390170016)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Cabell, WV(540110006)Kanawha, WV(540391005)New Jersey2Lancaster,PA(420710007)York, PA(421330008)New York8Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)NorthCarolina3Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Ohio23Jefferson,AL(10730023)Jefferson,AL(10732003)Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)Pennsylvania25Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Cook, IL(170310052)Madison, IL(171191007)SaintClair, IL(171630010)Clark, IN(180190006)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)E-5**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Nonattainment Sites (Monitoring Site ID)**Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Cabell, WV(540110006)Kanawha, WV(540391005)SouthCarolina3Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Tennessee29Jefferson,AL(10730023)Jefferson,AL(10732003)Bibb, GA(130210007)Clayton, GA(130630091)Fulton, GA(131210039)Clark, IN(180190006)Madison, IL(171191007)SaintClair, IL(171630010)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Cabell, WV(540110006)Kanawha, WV(540391005)Virginia4Lancaster,PA(420710007)York, PA(421330008)Cabell, WV(540110006)Kanawha, WV(540391005)WestVirginia25Fulton, GA(131210039)Bibb, GA(130210007)Clayton, GA(130630091)Clark, IN(180190006)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Dubois, IN(180372001)Jefferson,KY(211110043)Wayne, MI(261630015)Wayne, MI(261630033)Butler, OH(390170016)Cuyahoga,OH(390350038)Cuyahoga,OH(390350045)Cuyahoga,OH(390350060)Hamilton,OH(390610014)Hamilton,OH(390610042)Hamilton,OH(390610043)Hamilton,OH(390617001)Hamilton,OH(390618001)Allegheny,PA(420030064)Allegheny,PA(420031301)Beaver, PA(420070014)Lancaster,PA(420710007)York, PA(421330008)E-6**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Nonattainment Sites (Monitoring Site ID)**Wisconsin8Cook, IL(170310052)Dubois, IN(180372001)Marion, IN(180970078)Marion, IN(180970081)Marion, IN(180970083)Wayne, MI(261630015)Wayne, MI(261630033)Cuyahoga,OH(390350045)E-7**Table E-2. Upwind State-to-Downwind Maintenance Site “Linkages” for Annual PM 2.5** **. Upwind** **State Number** **of Linkages Counties Containing Downwind Annual PM** **2.5 Maintenance Sites (Monitoring Site ID)** Alabama1Jefferson, KY(211110044)Georgia1Jefferson, KY(211110044)Illinois13Jefferson, KY(211110044)Cuyahoga,OH(390350027)Cuyahoga,OH(390350065)Hamilton, OH(390610040)Jefferson,OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berks, PA(420110011)Harris, TX(482011035)Berkeley,WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Indiana16Cook, IL(170313301)Cook, IL(170316005)Jefferson,KY(211110044)New York, NY(360610056)Cuyahoga,OH(390350027)Cuyahoga, OH(390350065)Hamilton, OH(390610040)Jefferson, OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berks, PA(420110011)Harris, TX(482011035)Berkeley, WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Iowa2Cook, IL(170313301)Cook, IL(170316005)Kentucky12Cook, IL(170313301)Cook, IL(170316005)Cuyahoga,OH(390350027)Cuyahoga, OH(390350065)Hamilton,OH(390610040)Jefferson,OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berkeley,WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Louisiana1Harris, TX(482011035)Maryland/DC2Berks, PA(420110011)Berkeley,WV(540030003)Michigan15Cook, IL(170313301)Cook, IL(170316005)Jefferson,KY(211110044)New York, NY(360610056)Cuyahoga,OH(390350027)Cuyahoga, OH(390350065)Hamilton, OH(390610040)E-8**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Maintenance Sites (Monitoring Site ID)**Jefferson, OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berks, PA(420110011)Berkeley,WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Minnesota1Cook, IL(170316005)Missouri6Cook, IL(170313301)Cook, IL(170316005)Jefferson,KY(211110044)Hamilton, OH(390610040)Montgomery,OH(391130032)Stark, OH(391510017)New Jersey2New York, NY(360610056)Berks, PA(420110011)New York9Cuyahoga, OH(390350027)Cuyahoga,OH(390350065)Jefferson,OH(390811001)Stark, OH(391510017)Berks, PA(420110011)Berkeley, WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Ohio9Cook, IL(170313301)Cook, IL(170316005)Jefferson,KY(211110044)New York, NY(360610056)Berks, PA(420110011)Berkeley, WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Pennsylvania14Cook, IL(170313301)Cook, IL(170316005)Jefferson,KY(211110044)New York, NY(360610056)Cuyahoga,OH(390350027)Cuyahoga, OH(390350065)Hamilton, OH(390610040)Jefferson, OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berkeley, WV(540030003)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Tennessee10Jefferson, KY(211110044)Cuyahoga,OH(390350027)Cuyahoga,OH(390350065)Hamilton, OH(390610040)Jefferson,OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Brooke, WV(540090005)Hancock, WV(540291004)Marion, WV(540490006)Virginia4New York, NY(360610056)Berks, PA(420110011)Berkeley,WV(540030003Marion, WV(540490006)E-9**Upwind State** **Number of** **Linkages Counties Containing Downwind Annual PM 2.5** **Maintenance Sites (Monitoring Site ID)**)WestVirginia9Jefferson, KY(211110044)New York,NY(360610056)Cuyahoga,OH(390350027)Cuyahoga, OH(390350065)Hamilton,OH(390610040)Jefferson,OH(390811001)Montgomery,OH(391130032)Stark, OH(391510017)Berks, PA(420110011)Wisconsin2Cook, IL(170313301)Cook, IL(170316005)E-10**Table E-3. Upwind State-to-Downwind Nonattainment Site “Linkages” for 24-Hour PM 2.5** **. Upwind** **State Number of** **Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Alabama5Monroe, MI(261150005)Wayne, MI(261630015)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390618001)Connecticut3Hudson, NJ(340172002)New York, NY(360610056)New York, NY(360610128)Delaware2Union, NJ(340390004)Dauphin, PA(420430401)Georgia12Jefferson, AL(10730023)Jefferson, AL(10732003)BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)Union, NJ(340390004)Butler, OH(390170016)Butler, OH(390171004)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390618001)Montgomery,OH(391130032)York, PA(421330008)Illinois70Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)Lake, IN(180890022)Lake, IN(180890026)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe, IN(181570008)Scott, IA(191630019)Daviess, KY(210590005)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson, KY(211110048)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Union, NJ(340390004)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery,OHSummit, OH(391530017)Allegheny, PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)E-11**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** (391130032)Allegheny, PA(420031301)Beaver, PA(420070014)Berks, PA(420110011)Cambria, PA(420210011)Montgomery,TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Indiana75Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Scott, IA(191630019)Daviess, KY(210590005)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson,KY(211110048)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Hudson, NJ(340171003)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery, OH(391130032)Summit, OH(391530017)Allegheny, PA(420030008)Allegheny, PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny, PA(420031301)Beaver, PA(420070014)Berks, PA(420110011)Cambria, PA(420210011)Dauphin, PA(420430401)York, PA(421330008)Montgomery, TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Iowa17Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)E-12**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171191007)Lake, IN(180890022)Lake, IN(180890026)Jefferson, MO(290990012)St. LouisCity, MO(295100007)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Kansas3Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790099)Kentucky81Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)Lake, IN(180890026)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe, IN(181570008)Scott, IA(191630019)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)Saint Charles,MO (291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Hudson, NJ(340171003)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery, OH(391130032)Summit, OH(391530017)Allegheny, PA(420030008)Allegheny, PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny, PA(420031301)Beaver, PA(420070014)Berks, PA(420110011)Cambria, PA(420210011)York, PA(421330008)Montgomery, TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790010)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 (Monitoring Site ID)** Maryland/DC11New Haven, CT(90091123)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Berks, PA(420110011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)Massachusetts3New Haven, CT(90091123)New York, NY(360610056)New York, NY(360610128)Michigan48Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Knox, IN(180830004)Lake, IN(180890022)Lake, IN(180890026)Scott, IA(191630019)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)New York, NY(360610128)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610014)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery,OH(391130032)Summit, OH(391530017)Allegheny, PA(420030008)Allegheny, PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny, PA(420031301)Beaver, PA(420070014)Cambria, PA(420210011)Dauphin, PA(420430401)Montgomery,TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Minnesota4Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Missouri56Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)Lake, IN(180890022)Lake, IN(180890026)Marion, IN(180970042)E-14**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe,IN(181570008)Scott, IA(191630019)Daviess, KY(210590005)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson, KY(211110048)Monroe, MI(261150005)Oakland, MI(261250001)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630033)Wayne, MI(261630036)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Montgomery,OH(391130032)Allegheny, PA(420030116)Montgomery, TN(471251009)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Nebraska3Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790099)New Jersey9New Haven, CT(90091123)BaltimoreCity, MD(245100049)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Berks, PA(420110011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)New York23New Haven, CT(90091123)BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Summit, OH(391530017)Berks, PA(420110011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)NorthCarolina11BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)E-15**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** New York, NY(360610056)Berks, PA(420110011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)Ohio72Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)Lake, IN(180890022)Lake, IN(180890026)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe,IN(181570008)Scott, IA(191630019)Daviess, KY(210590005)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson, KY(211110048)Baltimore(City, MD(245100040)Baltimore(City, MD(245100049)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Allegheny, PA(420030008)Allegheny, PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny,PA(420031301)Beaver, PA(420070014)Berks, PA(420110011)Cambria, PA(420210011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)Montgomery,TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790010)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee,WI(550790099)Pennsylvania77Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Madison, IL(171190023)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)E-16**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Lake, IN(180890026)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe, IN(181570008)Scott, IA(191630019)Jefferson, KY(211110043)Jefferson,KY(211110044)Jefferson, KY(211110048)BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair,MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery,OH(391130032)Summit, OH(391530017)Montgomery,TN(471251009)Brooke, WV(540090011)Milwaukee, WI(550790026)Milwaukee, WI(550790043)Milwaukee, WI(550790099)Tennessee61Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Clark, IN(180190006)Dubois, IN(180372001)Knox, IN(180830004)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe,IN(181570008)Scott, IA(191630019)Daviess, KY(210590005)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson, KY(211110048)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)Wayne, MI(261630033)Wayne, MI(261630036)E-17**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Union, NJ(340390004)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery,OH(391130032)Summit, OH(391530017)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny, PA(420031301)Cambria, PA(420210011)York, PA(421330008)Virginia13New Haven, CT(90091123)BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Berks, PA(420110011)Dauphin, PA(420430401)Lancaster,PA(420710007)York, PA(421330008)WestVirginia84Jefferson, AL(10730023)Jefferson, AL(10732003)New Haven, CT(90091123)Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313301)Cook, IL(170316005)Madison, IL(171190023)Madison, IL(171191007)Madison, IL(171192009)Madison, IL(171193007)Clark, IN(180190006)Dubois, IN(180372001)Lake, IN(180890026)Marion, IN(180970042)Marion, IN(180970043)Marion, IN(180970066)Marion, IN(180970078)Marion, IN(180970079)Marion, IN(180970081)Marion, IN(180970083)Tippecanoe,IN(181570008)Scott, IA(191630019)Jefferson, KY(211110043)Jefferson, KY(211110044)Jefferson, KY(211110048)BaltimoreCity, MD(245100040)BaltimoreCity, MD(245100049)Monroe, MI(261150005)Oakland, MI(261250001)St. Clair, MI(261470005)Washtenaw, MI(261610008)Wayne, MI(261630015)E-18**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Nonattainment Sites (Monitoring Site ID)** Wayne, MI(261630016)Wayne, MI(261630019)Wayne, MI(261630033)Wayne, MI(261630036)Jefferson, MO(290990012)SaintCharles, MO(291831002)St. LouisCity, MO(295100007)St. LouisCity, MO(295100087)Hudson, NJ(340171003)Hudson, NJ(340172002)Union, NJ(340390004)Bronx, NY(360050080)New York, NY(360610056)New York, NY(360610128)Butler, OH(390170003)Butler, OH(390170016)Butler, OH(390170017)Butler, OH(390171004)Cuyahoga, OH(390350038)Cuyahoga, OH(390350045)Cuyahoga, OH(390350060)Cuyahoga, OH(390350065)Franklin, OH(390490024)Franklin, OH(390490025)Hamilton, OH(390610006)Hamilton, OH(390610014)Hamilton, OH(390610040)Hamilton, OH(390610042)Hamilton, OH(390610043)Hamilton, OH(390617001)Hamilton, OH(390618001)Jefferson, OH(390811001)Montgomery, OH(391130032)Summit, OH(391530017)Allegheny, PA(420030008)Allegheny,PA(420030064)Allegheny, PA(420030093)Allegheny, PA(420030116)Allegheny, PA(420031008)Allegheny, PA(420031301)Beaver, PA(420070014)Berks, PA(420110011)Cambria, PA(420210011)Dauphin, PA(420430401)Lancaster, PA(420710007)York, PA(421330008)Montgomery,TN(471251009)Milwaukee,WI(550790043)Wisconsin12Cook, IL(170310052)Cook, IL(170310057)Cook, IL(170310076)Cook, IL(170311016)Cook, IL(170312001)Cook, IL(170313103)Cook, IL(170313301)Cook, IL(170316005)Lake, IN(180890022)Lake, IN(180890026)Scott, IA(191630019)Wayne, MI(261630016)E-19**Table E-4. Upwind State-to-Downwind Maintenance Site “Linkages” for 24-Hour PM 2.5** **. Upwind** **State Number of** **Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Monitoring Site ID)** Connecticut 1New York, NY(360610062)Delaware 2Cumberland, PA(420410101)New York, NY(360610079)Georgia 3BaltimoreCity, MD(245100035)Lucas, OH(390950026)Preble, OH(391351001)Illinois 29District ofColumbia(110010041)District ofColumbia(110010042)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine, IA(191390015)Bullitt, KY(210290006)McCracken, KY(211451004)Warren, KY(212270007)Wayne, MI(261630001)St. LouisCity, MO(295100085)New York, NY(360610079)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery, OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Allegheny, PA(420030095)Allegheny,PA(420033007)Washington, PA(421255001)Sumner, TN(471650007)Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Indiana 34District ofColumbia(110010041)District ofColumbia(110010042)Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL (171630010)Will, IL(171971002)Muscatine, IA(191390015)Bullitt, KY(210290006)McCracken, KY(211451004)Warren, KY(212270007)Anne Arundel,MD (240031003)Wayne, MI(261630001)St. LouisCity, MO(295100085)New York, NY(360610062)New York, NY(360610079)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery,OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Allegheny, PA(420030095)Allegheny, PA(420033007)Cumberland, PA(420410101)Washington,PA(421255001)Sumner, TN(471650007)E-20**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Monitoring Site ID)** Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Iowa 9Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Will, IL(171971002)Elkhart, IN(180390003)St. LouisCity, MO(295100085)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Kansas 2Muscatine, IA(191390015)Milwaukee, WI(550790059)Kentucky 33District ofColumbia(110010041)District ofColumbia(110010042)Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL (171630010)Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine,IA(191390015)Anne Arundel,MD (240031003)Wayne, MI(261630001)St. LouisCity, MO(295100085)New York, NY(360610062)New York, NY(360610079)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery,OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Allegheny, PA(420030095)Allegheny, PA(420033007)Washington, PA(421255001)Sumner, TN(471650007)Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Maryland/DC 5New York, NY(360610062)New York, NY(360610079)Cumberland, PA(420410101)Massachusetts 1New York, NY(360610062)Michigan 28District ofColumbia(110010041)Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL(171630010)Will, IL(171971002)Elkhart, IN(180390003)Vigo, IN(181670023)Muscatine, IA(191390015)Warren, KY(212270007)St. LouisCity, MO(295100085)Cuyahoga, OH(390350027)E-21**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Monitoring Site ID)** Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery, OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Allegheny, PA(420030095)Allegheny, PA(420033007)Washington,PA(421255001)Sumner, TN(471650007)Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Minnesota 4Muscatine, IA(191390015)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Missouri 20Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL (171630010)Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine, IA(191390015)Bullitt, KY(210290006)McCracken,KY(211451004)Warren, KY(212270007)Jefferson, OH(390810017)Lucas, OH(390950026)Montgomery, OH(391130031)Preble, OH(391351001)Sumner, TN(471650007)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Nebraska 2Muscatine, IA(191390015)Milwaukee, WI(550790059)New Jersey 5District ofColumbia(110010041)Anne Arundel,MD (240031003)New York, NY(360610062)New York, NY(360610079)Cumberland,PA(420410101)New York 9District ofColumbia(110010041)District ofColumbia(110010042)Anne Arundel,MD (240031003)BaltimoreCity, MD(245100035)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Lucas, OH(390950024)Lucas, OH(390950026)Cumberland, PA(420410101)NorthCarolina 3BaltimoreCity, MD(245100035)New York, NY(360610062)New York, NY(360610079)Ohio 29District ofColumbia(110010041)District ofColumbia(110010042)Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL (171630010)E-22**Upwind State** **Number of Linkages Counties Containing Downwind 24-Hour PM2.5 Maintenance Sites (Monitoring Site ID)** Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine,IA(191390015)Bullitt, KY(210290006)McCracken, KY(211451004)Warren, KY(212270007)Anne Arundel,MD (240031003)BaltimoreCity, MD(245100035)Wayne, MI(261630001)St. LouisCity, MO(295100085)New York, NY(360610062)New York, NY(360610079)Allegheny, PA(420030095)Allegheny, PA(420033007)Cumberland,PA(420410101)Washington, PA(421255001)Sumner, TN(471650007)Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Pennsylvania 32District ofColumbia(110010041)District ofColumbia(110010042)Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL (171630010)Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine,IA(191390015)Bullitt, KY(210290006)Warren, KY(212270007)Anne Arundel,MD (240031003)BaltimoreCity, MD(245100035)Wayne, MI(261630001)New York, NY(360610062)New York, NY(360610079)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery, OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Sumner, TN(471650007)Brooke, WV(540090005)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Tennessee 21Cook, IL(170314007)Saint Clair,IL (171630010)Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine, IA(191390015)Bullitt, KY(210290006)McCracken, KY(211451004)Warren, KY(212270007)Wayne, MI(261630001)St. LouisCity, MO(295100085)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery,OH(391130031)Preble, OH(391351001)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 (Monitoring Site ID)** Virginia 7District ofColumbia(110010041)District ofColumbia(110010042)Anne Arundel,MD (240031003)BaltimoreCity, MD(245100035)New York, NY(360610062)New York, NY(360610079)Cumberland, PA(420410101)West Virginia 35District ofColumbia(110010041)District ofColumbia(110010042)Cook, IL(170310050)Cook, IL(170314007)Saint Clair,IL(171630010)Will, IL(171971002)Elkhart, IN(180390003)Floyd, IN(180431004)Vigo, IN(181670023)Muscatine, IA(191390015)Bullitt, KY(210290006)Warren, KY(212270007)Anne Arundel,MD (240031003)BaltimoreCity, MD(245100035)Wayne, MI(261630001)St. LouisCity, MO(295100085)New York, NY(360610062)New York, NY(360610079)Cuyahoga, OH(390350027)Cuyahoga, OH(390350034)Jefferson, OH(390810017)Lucas, OH(390950024)Lucas, OH(390950026)Mahoning, OH(390990014)Montgomery, OH(391130031)Preble, OH(391351001)Trumbull, OH(391550007)Allegheny, PA(420030095)Allegheny,PA(420033007)Cumberland, PA(420410101)Washington, PA(421255001)Sumner, TN(471650007)Dane, WI(550250047)Milwaukee, WI(550790059)Waukesha, WI(551330027)Wisconsin 6Cook, IL(170310022)Cook, IL(170310050)Cook, IL(170314007)Will, IL(171971002)Elkhart, IN(180390003)Muscatine, IA(191390015)E-24**Table E-5. Upwind State-to-Downwind Nonattainment “Linkages” for 8-hour Ozone. Upwind** **State Number** **of Linkages** **Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (Monitoring Site ID)** Alabama8East BatonRouge, LA(220330003)Brazoria, TX(480391004)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482010066)Harris, TX(482011039)Tarrant, TX(484391002)Arkansas3East BatonRouge, LA(220330003)Brazoria, TX(480391004)Tarrant, TX(484391002)Connecticut1Suffolk, NY(361030009)Delaware3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)Florida2Harris, TX(482010062)Tarrant, TX(484391002)Georgia7Brazoria, TX(480391004)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482010066)Harris, TX(482011039)Tarrant, TX(484391002)Illinois2Suffolk, NY(361030009)Harris, TX(482010055)Indiana3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)Kentucky6Suffolk, NY(361030002)Philadelphia,PA(421010024)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482011039)Louisiana7Brazoria, TX(480391004)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482010066)Harris, TX(482011039)Tarrant, TX(484391002)E-25**Upwind State** **Number of** **Linkages Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (Monitoring** **Site ID)**Maryland/DC3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)Michigan1Suffolk, NY(361030009)Mississippi8East BatonRouge, LA(220330003)Brazoria, TX(480391004)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482010066)Harris, TX(482011039)Tarrant, TX(484391002)New Jersey3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)NorthCarolina3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)Ohio3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)Oklahoma1Tarrant, TX(484391002)Pennsylvania2Suffolk, NY(361030002)Suffolk, NY(361030009)Tennessee7Philadelphia,PA(421010024)Brazoria, TX(480391004)Harris, TX(482010051)Harris, TX(482010055)Harris, TX(482010062)Harris, TX(482010066)Harris, TX(482011039)Texas1East BatonRouge, LA(220330003)Virginia3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)E-26**Upwind State** **Number of** **Linkages Counties Containing Downwind 8-Hour Ozone Nonattainment Sites (Monitoring** **Site ID)**WestVirginia3Suffolk, NY(361030002)Suffolk, NY(361030009)Philadelphia,PA(421010024)E-27**Table E-6. Upwind State-to-Downwind Maintenance “Linkages” for 8-Hour Ozone. Upwind** **State Number** **of Linkages Counties Containing Downwind 8-Hour Ozone Maintenance Sites (Monitoring Site ID)** Alabama6DeKalb, GA(130890002)Fulton, GA(131210055)Harris, TX(482010024)Harris, TX(482010029)Harris, TX(482011050)Tarrant, TX(484392003)Arkansas4Dallas, TX(481130069)Dallas, TX(481130087)Harris, TX(482011050)Tarrant, TX(484392003)Connecticut1Westchester,NY(361192004)Delaware1Bucks, PA(420170012)Florida4DeKalb, GA(130890002)Fulton, GA(131210055)Harris, TX(482010024)Harris, TX(482010029)Georgia4Harris, TX(482010024)Harris, TX(482010029)Harris, TX(482011050)Tarrant, TX(484392003)Indiana4Fairfield,CT(90010017)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)Kansas1Dallas, TX(481130069)Kentucky6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)Louisiana6Dallas, TX(481130069)Dallas, TX(481130087)Harris, TX(482010024)Harris, TX(482010029)Harris, TX(482011050)Tarrant, TX(484392003)Maryland/DC6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)Mississippi7DeKalb, GA(130890002)Fulton, GA(131210055)Dallas, TX(481130087)Harris, TX(482010024)Harris, TX(482010029)Harris, TX(482011050)Tarrant, TX(484392003)E-28New Jersey6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)New York5Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Bucks, PA(420170012)NorthCarolina5Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)Ohio6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)Oklahoma3Dallas, TX(481130069)Dallas, TX(481130087)Tarrant, TX(484392003)Pennsylvania5Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)SouthCarolina2Fulton, GA(131210055)Harris, TX(482010029)Tennessee5DeKalb, GA(130890002)Fulton, GA(131210055)Bucks, PA(420170012)Harris, TX(482010024)Harris, TX(482011050)Virginia6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)WestVirginia6Fairfield,CT(90010017)Fairfield,CT(90011123)Fairfield,CT(90013007)New Haven,CT(90093002)Westchester,NY(361192004)Bucks, PA(420170012)

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix F

Summary of Aggregated Em issions of SO2 and NOx

For States Included in the Transport RuleF-2Table F-1. Group1 and Group 2 States NOXTotal Emissions (not including fires) for each Modeling Scenario.2005 BaseYear2012 BaseCase2014 BaseCase2014Remedy2014Remedy -2012 BaseCasePercentChange:2014Remedyvs 2012BaseCase2014Remedy- 2014BaseCasePercentChange:2014Remedyvs 2014BaseCaseAnnual Total NOx Emissions for 15 Statesin Group 1 8,111,227 5,952,260 5,531,877 5,018,570 -933,690 -15.7% -513,308 -9.3%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% -224,608 -6.7%Annual Total NOx for 27 States + DC 12,721,973 9,527,221 8,893,550 8,155,634 -1,371,587 -14.4% -737,916 -8.3%Annual Total NOx Emissions for All StatesFully within the Eastern Modeling Domain15,862,117 11,997,188 11,207,626 10,388,190 -1,608,998 -13.4% -819,435 -7.3%Annual Total NOx Emissions for AllWestern States3,669,688 2,882,771 2,699,187 2,699,522 -183,249 -6.4% 334 0.0%F-3Table F-2.Group1 and Group 2 States SO2Total Emissions (not including fires) for each Modeling Scenario.2005 BaseYear2012 BaseCase2014 BaseCase2014Remedy2014Remedy -2012 BaseCasePercentChange:2014Remedyvs 2012BaseCase2014Remedy -2014 BaseCasePercentChange:2014Remedyvs 2014BaseCaseAnnual Total SO2 Emissions for 15 Statesin Group 1 9,040,217 9,146,651 8,087,579 3,792,063 -5,354,589 -58.5% -4,295,516 -53.1%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% -328,623 -14.9%Annual Total SO2 for 27 States + DCCovered for PM2.5 12,173,771 11,390,598 10,285,746 5,661,606 -5,728,992 -50.3% -4,624,139 -45.0%Annual Total SO2 Emissions for All StatesFully within the Eastern Modeling Domain 13,810,921 12,639,283 11,583,637 7,123,638 -5,515,645 -43.6% -4,459,999 -38.5%Annual Total SO2 Emissions for AllWestern States 852,154 700,400 697,838 733,479 33,079 4.7% 35,641 5.1%F-4Table F-3.Group1 and Group 2 States NOXEGU Sector Emissions for each Modeling Scenario.2005BaseYear2012BaseCase2014BaseCase2014Remedy2014Remedy- 2012BaseCasePercentChange:2014Remedyvs 2012BaseCase2014Remedy- 2014BaseCasePercentChange:2014Remedyvs 2014BaseCaseAnnual EGU NOx Emissions for 15 States inGroup 1 1,945,446 1,445,575 1,432,270 918,963 -526,613 -36.4% -513,308 -35.8%Annual EGU NOx Emissions for 12 States + DCin Group 2 831,991 632,031 626,150 401,542 -230,489 -36.5% -224,608 -35.9%Annual EGU NOx for 27 States + DC Coveredfor PM2.5 2,777,437 2,077,606 2,058,421 1,320,505 -757,101 -36.4% -737,916 -35.8%Annual EGU NOx Emissions for All States Fullywithin the Eastern Modeling Domain 3,223,184 2,485,856 2,468,057 1,648,621 -837,234 -33.7% -819,435 -33.2%Annual EGU NOx Emissions for All WesternStates 504,928 440,572 440,787 441,121 550 0.1% 334 0.1%F-5Table F-4.Group1 and Group 2 States SO2EGU Sector Emissions for each Modeling Scenario.2005 BaseYear2012BaseCase2014BaseCase2014Remedy2014Remedy -2012 BaseCasePercentChange:2014Remedyvs 2012BaseCase2014Remedy -2014 BaseCasePercentChange:2014Remedyvs 2014BaseCaseAnnual EGU SO2 Emissions for 15 States inGroup 1 7,040,088 7,349,814 6,303,300 2,007,783 -5,342,031 -72.7% -4,295,516 -68.1%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% -328,623 -29.4%Annual EGU SO2 for 27 States + DCCovered for PM2.5 9,029,138 8,514,073 7,421,441 2,797,302 -5,716,771 -67.1% -4,624,139 -62.3%Annual EGU SO2 Emissions for All StatesFully within the Eastern Modeling Domain 10,019,774 9,243,362 8,209,536 3,749,537 -5,493,825 -59.4% -4,459,999 -54.3%Annual EGU SO2 Emissions for All WesternStates 361,634 256,561 260,283 295,924 39,364 15.3% 35,641 13.7%F-6Table F-5.26-State Total and Electric Generating Unit Sector Summer NOXEmissions for each Modeling Scenario.2005BaseYear2012BaseCase2014BaseCase2014Remedy2014Remedy- 2012BaseCasePercentChange:2014Remedyvs 2012BaseCase2014Remedy- 2014BaseCasePercentChange:2014Remedyvs 2014BaseCaseSummer EGU NOx Emissions for 26 StatesIncluded for Ozone 905,345 718,142 698,827 585,584 -132,559 -18.5% -113,243 -16.2%Summer Total NOx Emissions for 26 StatesIncluded for Ozone 5,363,278 4,085,516 3,784,430 3,671,187 -414,329 -10.1% -113,243 -3.0%

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix G

Concentration and Difference Maps for

Annual PM2.5, 24-Hour PM 2.5, and 8-Hour Ozone

# Annual PM2.5 Maps

# 2003-2007 Average Ambient A nnual 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 Differe nce in Annual PM2.5 Concentrations

2014 Remedy – 2014 Base Case Differe nce in Annual PM2.5 Concentrations

# 24-Hour PM2.5 Maps

# 2003-2007 Average Ambient 24-Ho ur 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 Differen ce in 24-Hour PM2.5 Concentrations

2014 Remedy – 2014 Base Case Differen ce in 24-Hour PM2.5 Concentrations

# 8-Hour Ozone Maps

# 2003-2007 Average Ambient 8-Ho ur 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 Differen ce in 8-Hour Ozone Concentrations

2014 Remedy – 2014 Base Case Differen ce in 8-Hour Ozone Concentrations

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix H

Quarterly “Exceedances” of the

24-Hour PM2.5 NAAQS for the

2014 Base Case and 20 14 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 th e calculation of future case design values

for the 24-hour PM2.5 NAAQS. This a ppendix provides the quarterly 24-hour

PM2.5 concentrations for the 2014 Base Case and 2014 Remedy scenario for the

monitoring sites projected to be nonattain ment and/or maintenance sites based on

modeling of the 2014 Remedy scenario. Th e quarterly values that exceed the 35

μg.m 3 

# 24-hour PM2.5 NAAQS are in red.H-3Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 28.70 27.8937.8424.65 30.28 22.07 31.60 31.542004 27.95 27.16 27.31 17.84 27.53 20.07 29.71 29.66200548.84 47.4526.83 17.5335.7025.99 35.37 35.302006 26.45 25.70 29.65 19.36 25.30 18.46 29.52 29.47Ann Arbor, MI(Washtenaw Co)2616100082007 19.24 18.70 26.44 17.28 30.73 22.39 29.15 29.09Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200339.26 37.8326.92 21.97 32.84 24.81 29.44 27.87200437.06 35.7126.92 21.97 28.55 21.59 30.01 28.40200536.2634.94 24.24 19.79 30.69 23.20 29.63 28.052006 29.15 28.09 25.85 21.10 27.26 20.62 28.50 26.98Baltimore, MD(Anne Arundel Co)2400310032007 27.54 26.54 24.60 20.08 29.92 22.62 25.12 23.78Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200335.7834.6735.8929.73 34.71 27.1839.15 37.96200435.9734.8635.9829.80 34.45 26.9936.93 35.80200537.95 36.7828.44 23.57 31.57 24.7436.0034.912006 33.41 32.38 30.68 25.42 30.64 24.01 33.13 32.12Baltimore, MD(Baltimore City)2451000402007 31.61 30.64 30.50 25.28 29.88 23.42 31.00 30.06H-4Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 29.55 28.54 35.27 31.61 33.43 29.87 34.57 32.162004 34.82 33.6236.7432.9336.1632.30 33.85 31.502005 34.82 33.6243.46 38.93 42.98 38.39 37.6835.062006 27.49 26.54 33.89 30.37 33.51 29.94 35.28 32.82Birmingham, AL(Jefferson Co)10730023200740.27 38.88 38.8634.8236.2432.38 29.76 27.70Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 34.79 33.79 34.71 30.35 33.39 25.69 34.00 33.462004 30.96 30.07 21.97 19.24 34.73 26.71 34.75 34.19200536.94 35.8830.15 26.3839.6530.4845.23 44.502006 28.99 28.17 26.53 23.21 26.06 20.07 29.60 29.13Chicago, IL(Cook Co)170310052200736.84 35.7934.90 30.51 31.34 24.1135.8735.30Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200342.17 41.34 37.4731.67 30.36 23.07 34.45 33.042004 34.30 33.63 24.15 20.45 26.45 20.1139.77 38.14200545.26 44.37 36.0730.5045.8334.75 34.92 33.492006 26.34 25.83 25.73 21.78 27.43 20.85 30.72 29.47Chicago, IL(Cook Co)1703110162007 29.43 28.86 34.30 29.00 30.54 23.20 31.28 30.00H-5Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2004 35.21 34.47 20.18 16.99 33.31 24.2938.17 37.40200547.47 46.4731.61 26.5741.6230.3238.17 37.402006 25.12 24.59 28.14 23.66 25.26 18.46 26.37 25.84Chicago, IL(Cook Co)1703131032007 34.55 33.82 32.92 27.66 23.67 17.30 27.40 26.85Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200335.6434.94 21.78 18.39 29.89 22.54 30.31 29.052004 33.23 32.57 21.13 17.8438.0528.66 29.94 28.69200545.55 44.6633.45 28.2038.8529.2636.5935.062006 24.14 23.67 23.18 19.57 24.61 18.58 22.16 21.24Chicago, IL(Cook Co)1703133012007 28.50 27.94 31.12 26.24 27.92 21.06 34.44 33.00Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200336.0235.17 31.63 28.03 32.29 24.52 33.98 33.28200439.76 38.8221.38 18.96 35.15 26.68 30.44 29.81200540.22 39.2829.21 25.8838.9929.5841.63 40.762006 27.14 26.50 23.15 20.53 26.13 19.86 23.91 23.42Chicago, IL(Cook Co)1703160052007 24.15 23.58 34.43 30.50 29.70 22.56 33.89 33.18H-6Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200341.69 40.51 43.6933.1839.7728.64 32.92 30.04200436.2135.19 34.37 26.1337.9827.3638.4335.06200540.11 38.9733.35 25.3645.8533.00 27.32 24.942006 33.52 32.58 31.78 24.17 26.89 19.41 25.43 23.21Cleveland, OH(Cuyahoga Co)3903500382007 23.97 23.30 31.78 24.1735.5625.63 31.93 29.14Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 32.43 31.54 32.97 24.9540.6428.46 29.26 25.98200439.10 38.0232.97 24.95 30.74 21.57 23.45 20.84200545.86 44.5934.91 26.4143.2330.27 25.18 22.362006 28.73 27.94 27.25 20.64 27.44 19.27 20.46 18.18Cleveland, OH(Cuyahoga Co)3903500602007 25.58 24.88 29.19 22.10 34.57 24.24 33.43 29.68Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 32.75 32.11 31.36 20.97 32.34 22.63 30.55 29.422004 28.58 28.03 27.32 18.28 28.73 20.12 29.19 28.10200549.39 48.4227.32 18.2838.6927.0536.2034.852006 28.30 27.75 31.08 20.78 20.26 14.23 29.92 28.80Detroit, MI(Oakland Co)2612500012007 20.26 19.87 31.18 20.84 31.20 21.84 26.37 25.39H-7Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200343.47 42.81 40.0329.1838.3527.99 35.38 34.672004 30.31 29.85 29.61 21.61 34.16 24.95 32.42 31.77200548.74 47.99 36.7226.7741.2930.1242.32 41.472006 34.73 34.20 31.98 23.33 23.39 17.12 29.37 28.78Detroit, MI(Wayne Co)2616300162007 24.48 24.11 27.52 20.10 30.60 22.36 25.76 25.24Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 34.89 34.24 29.88 20.40 28.21 19.71 29.87 29.352004 30.85 30.28 26.92 18.40 30.66 21.41 29.87 29.35200549.18 48.26 47.1532.1038.7126.9938.73 38.052006 34.05 33.41 29.88 20.40 18.95 13.29 32.11 31.55Detroit, MI(Wayne Co)2616300192007 23.15 22.72 25.87 17.69 27.95 19.53 27.26 26.79Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200338.26 37.68 36.6726.8138.3128.17 31.99 31.542004 32.62 32.1337.4327.36 31.34 23.07 32.55 32.09200547.18 46.4634.20 25.0140.1029.48 34.68 34.19200640.51 39.9030.88 22.59 27.23 20.06 32.46 32.00Detroit, MI(Wayne Co)2616300332007 30.27 29.82 34.77 25.43 32.77 24.12 31.81 31.36H-8Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 33.28 32.57 33.12 22.31 27.42 18.26 30.68 28.992004 30.89 30.23 27.76 18.73 27.68 18.44 25.18 23.80200544.65 43.7029.39 19.8239.2626.0838.79 36.642006 30.60 29.95 31.78 21.42 24.17 16.12 26.98 25.50Detroit, MI(Wayne Co)2616300362007 26.97 26.40 27.38 18.47 24.79 16.53 23.56 22.27Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200339.21 38.42 36.4529.75 31.32 24.53 34.02 32.072004 34.02 33.34 27.07 22.12 31.71 24.83 25.90 24.42200540.17 39.36 43.0935.1541.9232.79 28.73 27.092006 27.01 26.47 35.47 28.95 32.50 25.45 25.52 24.06East St Louis, MO(Madison Co, IL)1711910072007 25.76 25.25 34.49 28.16 35.35 27.67 24.10 22.73Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200343.12 41.9626.83 20.62 27.94 20.8642.77 41.26200440.31 39.2222.73 17.48 30.95 23.1042.86 41.35200537.39 36.3929.50 22.6635.8226.71 32.48 31.342006 26.79 26.07 22.54 17.34 24.40 18.23 21.26 20.52Gary, IN(Lake Co, IN)1808900222007 33.08 32.19 32.17 24.70 27.41 20.47 29.39 28.36H-9Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200339.06 37.6527.17 20.62 32.15 24.7135.6133.30200436.1534.86 27.07 20.55 33.22 25.53 28.79 26.93200536.3435.04 32.73 24.8239.0129.96 31.55 29.512006 26.89 25.93 24.86 18.89 27.15 20.89 23.17 21.68Gary, IN(Lake Co, IN)1808900262007 27.73 26.74 29.95 22.72 29.29 22.53 32.29 30.20Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200638.67 37.97 35.9429.4836.2929.9441.29 40.182007 32.23 31.65 28.31 23.24 30.21 24.9438.12 37.10Jersey City, NJ(Hudson Co)3401720022008 No Data No Data No Data No Data 32.62 26.93 32.63 31.76Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200345.22 43.44 40.7230.9636.7024.7046.07 44.332004 33.46 32.15 32.04 24.39 28.51 19.23 31.78 30.58200539.72 38.1625.63 19.5338.2225.72 32.58 31.362006 33.65 32.33 28.97 22.06 29.19 19.68 22.21 21.39Lancaster, PA(Lancaster Co)420710007200738.18 36.6825.17 19.18 28.01 18.89 32.67 31.44H-10Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 31.80 31.21 20.47 17.02 26.34 20.04 28.55 28.08200436.77 36.0920.57 17.10 32.57 24.75 23.17 22.79200537.06 36.3824.02 19.96 31.40 23.87 34.32 33.75200638.97 38.2525.23 20.96 23.90 18.19 24.49 24.09Milwaukee, WI(Milwaukee Co)550790010200738.88 38.1627.19 22.58 28.87 21.95 33.65 33.10Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 27.73 27.01 22.92 19.05 24.57 17.94 27.88 27.312004 26.48 25.80 21.61 17.97 25.55 18.65 24.96 24.46200539.67 38.6324.31 20.21 30.97 22.58 33.62 32.932006 34.60 33.70 24.87 20.67 24.66 18.0140.11 39.29Milwaukee, WI(Milwaukee Co)550790026200738.04 37.0528.50 23.67 25.19 18.3936.63 35.88Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 32.54 31.96 22.64 19.07 35.47 27.10 27.32 26.882004 27.38 26.89 22.18 18.6736.6527.9939.12 38.482005 32.83 32.24 23.67 19.93 33.58 25.65 34.02 33.47200642.11 41.3527.69 23.30 23.54 18.03 24.58 24.18MIlwaukee, WI(Milwaukee Co)5507900432007 28.72 28.20 26.19 22.04 25.17 19.2635.9135.33H-11Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 29.36 28.56 23.56 19.98 27.90 20.42 31.74 31.122004 29.17 28.38 21.69 18.40 34.66 25.33 28.45 27.892005 35.48 34.51 25.43 21.55 32.70 23.91 34.00 33.33200636.62 35.6327.20 23.05 23.27 17.06 25.25 24.76Milwaukee, WI(Milwaukee Co)550790099200738.92 37.8626.36 22.34 26.83 19.64 31.93 31.30Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 32.17 31.63 24.53 20.77 31.33 25.37 29.88 29.142004 34.55 33.9836.6430.98 25.61 20.75 28.19 27.492005 32.93 32.38 29.96 25.35 34.32 27.7837.42 36.482006 33.60 33.0436.2830.68 30.48 24.6838.08 37.13New York, NY(New York Co)3606100562007 35.13 34.54 29.69 25.13 29.80 24.13 30.17 29.41Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy200355.27 53.24 58.42 49.46 54.83 46.35 58.20 56.90200458.74 56.58 52.29 44.27 57.89 48.93 61.53 60.15200547.95 46.19 61.05 51.68 56.45 47.72 61.26 59.88200647.50 45.75 47.47 40.20 49.33 41.71 50.04 48.92Pittsburgh, PA(Allegheny Co)420030064200749.51 47.69 47.82 40.50 49.33 41.71 41.15 40.23H-12Quarter 1Quarter 2Quarter 3Quarter 4AmbientData Year2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2014Base Case2014Remedy2003 28.43 26.07 25.90 16.95 27.12 21.3238.21 36.02200440.34 36.97 37.2324.29 34.08 26.76 21.87 20.632005 28.81 26.42 34.88 22.77 29.69 23.3340.18 37.882006 33.59 30.79 20.12 13.21 30.68 24.11 29.77 28.07Steubenville, OH(Brooke Co, WV)540090011200746.62 42.72 35.7423.33 32.17 25.27 24.47 23.08

# Transport Rule Air Quality Mode ling Technical Support Document

Appendix I

Impacts on Visibility in Cl ass I Areas of the West

# I-2 

# Impact on visibility (in deciviews) fo r all Western Class I areas included

(only) in the 36 km modeling domain. S ee 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