Technical Support Document for the Final LocomotiveMarine Rule Air

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					Technical Support Document for the Final Locomotive/Marine Rule: Air Quality Modeling Analyses

EPA 454/R-08-002 January 2008

Technical Support Document for the Final Locomotive/Marine Rule: Air Quality Modeling Analyses

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Assessment Division Research Triangle Park, NC 27711 January 2008

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I. Introduction
This document describes the air quality modeling performed by EPA in support of the final Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression-Ignition Engines Less than 20 Liters per Cylinder (Locomotive/Marine) rule. A national scale air quality modeling analysis was performed to estimate the effect of the rule on future annual fine particulate matter (PM2.5) concentrations, future 8-hour ozone concentrations, and future visibility levels. To estimate the air quality changes expected to result from this rule we used the Community Multiscale Air Quality (CMAQ) model1. The CMAQ model simulates the multiple physical and chemical processes involved in the formation, transport, and destruction of fine particulate matter and ozone. The overall CMAQ modeling platform has been revised from what was used at proposal. A modeling platform is a structured system of connected modeling-related tools and data that provide a consistent and transparent basis for assessing the air quality response to changes in emissions and/or meteorology. A platform typically consists of a specific air quality model, base year and future year baseline emissions estimates, and a set of meteorological model inputs. The final Locomotive/Marine rule modeling analyses were based on a 2002 modeling platform which reflects: a) an updated version of the CMAQ model, b) higher resolution PM2.5 modeling, c) a longer period of ozone modeling, and d) updated emissions and meteorological data. These updates from the previous 2001 platform will be described in more detail in subsequent sections of this technical support document (TSD).

II. CMAQ Model Version, Inputs and Configuration
A. Model version CMAQ is a non-proprietary computer model that simulates the formation and fate of photochemical oxidants, including PM2.5 and ozone, for given input sets of meteorological conditions and emissions. This analysis employed a version of CMAQ based on the latest publicly-released version of CMAQ available at the time of the final Locomotive/Marine rule modeling (i.e., version 4.6)2. CMAQ version 4.6 reflects recent updates intended to improve the underlying science from version 4.5, which was used in the proposal. These model enhancements include: 1) an updated Carbon Bond chemical mechanism (CB-05) and associated Euler Backward Iterative (EBI) solver was added;

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Byun, D.W., and K. L. Schere, 2006: Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System. Applied Mechanics Reviews, Volume 59, Number 2 (March 2006), pp. 51-77. CMAQ version 4.6 was released on September 30, 2006. It is available from the Community Modeling and Analysis System (CMAS) at: http://www.cmascenter.org .

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2) an updated version of the ISORROPIA aerosol thermodynamics module was added; 3) the heterogeneous N2O5 reaction probability is now temperature- and humiditydependent; 4) the gas-phase reactions involving N2O5 and H2O are now included; and 5) an updated version of the vertical diffusion module was added (ACM2). Additionally, there were a few minor changes made to the release version of CMAQ v4.6 by the EPA model developers subsequent to its release. The relatively minor changes and new features of this internal version that was ultimately used in this analysis (version 4.6.1i) are described elsewhere.3 B. Model domain and grid resolution The CMAQ modeling analyses were performed for a domain covering the continental United States, as shown in Figure II-1. This domain has a parent horizontal grid of 36 km with two finer-scale 12 km grids over portions of the eastern and western U.S. The model extends vertically from the surface to 100 millibars (approximately 15 km) using a sigma-pressure coordinate system. Air quality conditions at the outer boundary of the 36 km domain were taken from a global model and did not change over the simulations. In turn, the 36 km grid was only used to establish the incoming air quality concentrations along the boundaries of the 12 km grids. All of the modeling results assessing the emissions reductions from the Locomotive/Marine rule were taken from the 12 km grids. Table II-1 provides some basic geographic information regarding the CMAQ domains. Table II-1. Geographic elements of domains used in Locomotive/Marine modeling.
CMAQ Modeling Configuration
National Grid Map Projection Grid Resolution Coordinate Center True Latitudes Dimensions Vertical extent 148 x 112 x 14 36 km Western U.S. Fine Grid Lambert Conformal Projection 12 km 97 deg W, 40 deg N 33 deg N and 45 deg N 213 x 192 x 14 279 x 240 x 14 12 km Eastern U.S. Fine Grid

14 Layers: Surface to 100 millibar level (see Table II-3)

See the 4/09/07 e-mail from Shawn Roselle, Office of Research and Development to Carey Jang, Office of Air Quality Planning and Standards which is included in the docket for this rulemaking.

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Figure II-1. Map of the CMAQ modeling domain. The black outer box denotes the 36 km national modeling domain; the red inner box is the 12 km western U.S. fine grid; and the blue inner box is the 12 km eastern U.S. fine grid.

C. Modeling Period / Ozone Episodes The 36 km and both 12 km CMAQ modeling domains were modeled for the entire year of 2002.4 All 365 model days were used in the calculations of the impacts of the locomotive/marine controls on annual average levels of PM2.5. For the 8-hour ozone results, we are only using modeling results from the period between May 1 and September 30, 2002. This 153-day period generally conforms to the ozone season across most parts of the U.S. and contains the majority of days with observed high ozone concentrations in 2002. D. Model Inputs: Emissions, Meteorology and Boundary Conditions 1. Base Year and Future Baseline Emissions: As noted in the introduction section, a 2001-based platform was used for the proposed rule modeling and a 2002based platform was used for the final rule modeling. The 2002-based platform builds upon the general concepts, tools and emissions modeling data from the 2001-based
We also modeled 10 days at the end of December 2001 as a modeled "ramp up" period. These days are used to minimize the effects of initial conditions and are not considered as part of the output analyses.
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platform, while updating and enhancing many of the emission inputs and tools. A summary of the emissions inventory development is described below. More detailed documentation on the methods and data summaries of the 2002-based platform emissions for base and future years is also available separately.5 We used version 3 of the 2002-based platform which takes emission inventories from the 2002 National Emissions Inventory (NEI) version 3.0. These inventories, with the exception of California, include monthly onroad and nonroad emissions generated from the National Mobile Inventory Model (NMIM) using versions of MOBILE6.0 and NONROAD2005 consistent with recent national rule analyses.6,7,8 The locomotive and marine inventories are based on national level estimates developed for the proposed rule making.9 That is, the base year emissions for locomotive and marine sectors did not change between the proposal and final modeling. The 2002-based platform and its associated chemical mechanism (CB05) employs updated speciation profiles using data included in the SPECIATE4.0 database.10 In addition, the 2002-based platform incorporates several temporal profile updates for both mobile and stationary sources. The 2002-based platform includes emissions for a 2002 base year model evaluation case, a 2002 base case and several projection years. The projection years include 2020 and 2030, which were used as the future years for the locomotive/marine rule analyses. The model evaluation case uses prescribed burning and wildfire emissions specific to 2002, which were developed and modeled as day-specific, location-specific emissions using an updated version of Sparse Matrix Operator Kernel Emissions (SMOKE) system, version 2.3, which computes plume rise and vertically allocates the fire emissions. It also includes continuous emissions monitoring (CEM) data for 2002 for electric generating units (EGUs) with CEMs. The 2002 and projection year baselines
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Technical Support Document: Preparation of Emissions Inventories for the 2002-based Platform, Version 3.0, Criteria Air Pollutants, January 2008. This file is available in the docket for this rulemaking. The California Air Resources Board submitted annual emissions for California. These were allocated to monthly resolution prior to emissions modeling using data from the National Mobile Inventory Model (NMIM).

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MOBILE6 version was used in the Mobile Source Air Toxics Rule: Regulatory Impact Analysis for Final Rule: Control of Hazardous Air Pollutants from Mobile Sources, U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI 48105, EPA420-R-07-002, February 2007. NONROAD2005 version was used in the proposed rule for small spark ignition (SI) and marine SI rule: Draft Regulatory Impact Analysis: Control of Emissions from Marine SI and Small SI Engines, Vessels, and Equipment , U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI, EPA420-D-07004, April 2007. U.S. Environmental Protection Agency, Draft Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotive Engines and Marine Compression-Ignition Engines Less than 30 Liters per Cylinder, EPA420-D-07-001, January 2007.
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See http://www.epa.gov/ttn/chief/software/speciate/index.html for more details.

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include an average fire sector and temporally averaged emissions (i.e., no CEM data) for EGUs. Projections from 2002 were developed to account for the expected impact of national regulations, consent decrees or settlements, known plant closures, and, for some sectors, activity growth. For 2030, stationary sources used 2020 projections (i.e., no activity growth between 2020 and 2030). For the locomotive and marine sectors, the baseline emissions have not changed from the proposal modeling. Percent reductions were applied to the 2020 and 2030 baseline emissions to reflect the impacts of the final Locomotive/Marine rulemaking as shown in Tables II-2a and II-2b. The first five source sectors are locomotive sectors and the last three are marine sectors. Table II-2a. Percentage reductions applied to locomotive/marine sectors in 2020 to reflect the impacts of the final rule. Pollutant VOC NOX PM10 PM2.5 SO2 Class I Railroads 49% 19% 41% 41% 0% Class II/III Railroads 0% 0% 0% 0% 0% Commuter Railroads 51% 19% 43% 43% 0% Passenger Railroads 51% 19% 43% 43% 0% Switch Railroads 19% 8% 21% 21% 0% Commercial Marine Vessels 28% 26% 29% 29% 5% Pleasure Craft: Inboard 7% 5% 3% 3% 0% Pleasure Craft: Outboard 13% 13% 8% 8% 0% Table II-2b. Percentage reductions applied to locomotive/marine sectors in 2030 to reflect the impacts of the final rule. NOX PM10 PM2.5 SO2 Pollutant VOC Class I Railroads 69% 52% 63% 63% 0% Class II/III Railroads 0% 0% 0% 0% 0% Commuter Railroads 72% 53% 66% 66% 0% Passenger Railroads 72% 53% 66% 66% 0% Switch Railroads 35% 23% 38% 38% 0% Commercial Marine Vessels 60% 54% 58% 58% 16% Pleasure Craft: Inboard 14% 11% 8% 8% 0% Pleasure Craft: Outboard 23% 29% 17% 17% 0% 2. Meteorological Input Data: The gridded meteorological input data for the entire year of 2002 were derived from simulations of the Pennsylvania State University / National Center for Atmospheric Research Mesoscale Model. This model, commonly referred to as MM5, is a limited-area, nonhydrostatic, terrain-following system that solves for the full set of physical and thermodynamic equations which govern atmospheric motions.11 Meteorological model input fields were prepared separately for each of the domains shown in Figure II-1. The MM5 simulations were run on the same
11

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.

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map projection as CMAQ. The 36 km national domain was modeled using MM5 v.3.6.0 using land-surface modifications that were added in v3.6.3. The 12 km eastern U.S grid was modeled with MM5 v3.7.2. These two sets of meteorological inputs were developed by EPA. For the 12 km western U.S. domain, we utilized existing MM5 meteorological model data prepared by the Western Regional Air Partnership (WRAP).12 The three meteorological model runs used similar sets of physics options. All three simulations used the Pleim-Xiu planetary boundary layer and vertical diffusion scheme, the RRTM longwave radiation scheme, and the Reisner 1 microphysics scheme. The EPA simulations used the Kain-Fritsch 2 subgrid convection scheme while the WRAP simulation used the Betts-Miller scheme for subgrid convection. In the EPA simulations, analysis nudging was utilized above the boundary layer for temperature and water vapor, and in all locations for the wind components using relatively weak nudging coefficients. The WRAP runs employed similar four-dimensional data assimilation, but also included observational nudging of surface winds. All three sets of model runs were conducted in 5.5 day segments with 12 hours of overlap for spin-up purposes. All three domains contained 34 vertical layers with an approximately 38 m deep surface layer and a 100 millibar top. The MM5 and CMAQ vertical structures are shown in Table II-3 and do not vary by horizontal grid resolution. Table II-3. Vertical layer structure for MM5 and CMAQ (heights are layer top).
CMAQ Layers
0 1 2 3 4 5 6

MM5 Layers
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Sigma P
1.000 0.995 0.990 0.985 0.980 0.970 0.960 0.950 0.940 0.930 0.920 0.910 0.900 0.880 0.860 0.840 0.820 0.800 0.770 0.740

Approximate Height (m)
0 38 77 115 154 232 310 389 469 550 631 712 794 961 1,130 1,303 1,478 1,657 1,930 2,212

Approximate Pressure (mb)
1000 995 991 987 982 973 964 955 946 937 928 919 910 892 874 856 838 820 793 766

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Kemball-Cook, S., Y. Jia, C. Emery, R. Morris, Z. Wang and G. Tonnesen. 2004. 2002 Annual MM5 Simulation to Support WRAP CMAQ Visibility Modeling for the Section 308 SIP/TIP – MM5 Sensitivity Simulations to Identify a More Optimal MM5 Configuration for Simulating Meteorology in the Western United States. Western Regional Air Partnership, Regional Modeling Center. December 10. (http://pah.cert.ucr.edu/aqm/308/reports/mm5/MM5SensitivityRevRep_Dec_10_2004.pdf)

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10 11 12

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20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

0.700 0.650 0.600 0.550 0.500 0.450 0.400 0.350 0.300 0.250 0.200 0.150 0.100 0.050 0.000

2,600 3,108 3,644 4,212 4,816 5,461 6,153 6,903 7,720 8,621 9,625 10,764 12,085 13,670 15,674

730 685 640 595 550 505 460 415 370 325 280 235 190 145 100

The meteorological outputs from all three MM5 sets were processed to create model-ready inputs for CMAQ using the Meteorology-Chemistry Interface Processor (MCIP), version 3.1, to derive the specific inputs to CMAQ.13 Before initiating the air quality simulations, it is important to identify the biases and errors associated with the meteorological modeling inputs. The 2002 MM5 model performance evaluations used an approach which included a combination of qualitative and quantitative analyses to assess the adequacy of the MM5 simulated fields. The qualitative aspects involved comparisons of the model-estimated synoptic patterns against observed patterns from historical weather chart archives. Qualitatively, the model fields closely matched the observed synoptic patterns, which is expected given the use of nudging. The operational evaluation included statistical comparisons of model/observed pairs (e.g., mean normalized bias, mean normalized error, index of agreement, root mean square errors, etc.) for multiple meteorological parameters. For this portion of the evaluation, four meteorological parameters were investigated: temperature, humidity, wind speed, and wind direction. The operational piece of the analyses focuses on surface parameters. The Atmospheric Model Evaluation Tool (AMET) was used to conduct the analyses as described in this report.14 The three individual MM5 evaluations are described elsewhere.15,16,17 It was ultimately determined that the bias and error values
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Byun, D.W., and Ching, J.K.S., Eds, 1999. Science algorithms of EPA Models-3 Community Multiscale Air Quality (CMAQ modeling system, EPA/600/R-99/030, Office of Research and Development). Gilliam, R. C., W. Appel, and S. Phillips. The Atmospheric Model Evaluation Tool (AMET): Meteorology Module. Presented at 4th Annual CMAS Models-3 Users Conference, Chapel Hill, NC, September 26 - 28, 2005. Brewer J., P. Dolwick, and R. Gilliam. Regional and Local Scale Evaluation of MM5 Meteorological Fields for Various Air Quality Modeling Applications, Presented at the 87th Annual American Meteorological Society Annual Meeting, San Antonio, TX, January 15-18, 2007.

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Dolwick, P, R. Gilliam, L. Reynolds, and A. Huffman. Regional and Local-scale Evaluation of 2002 MM5 Meteorological Fields for Various Air Quality Modeling Applications, Presented at 6th Annual CMAS Models-3 Users Conference, Chapel Hill, NC, October 1 - 3, 2007.

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associated with all three sets of 2002 meteorological data were generally within the range of past meteorological modeling results that have been used for air quality applications.18 3. Initial and Boundary Conditions: The lateral boundary and initial species concentrations are provided by a three-dimensional global atmospheric chemistry model, the GEOS-CHEM model.19 The global GEOS-CHEM model simulates atmospheric chemical and physical processes driven by assimilated meteorological observations from the NASA’s Goddard Earth Observing System (GEOS). This model was run for 2002 with a grid resolution of 2.0 degree x 2.5 degree (latitude-longitude) and 20 vertical layers. The predictions were used to provide one-way dynamic boundary conditions at three-hour intervals and an initial concentration field for the CMAQ simulations. More information is available about the GEOS-CHEM model and other applications using this tool at: http://www-as.harvard.edu/chemistry/trop/geos. E. CMAQ Base Case Model Performance Evaluation An operational model performance evaluation for ozone and PM2.5 and its related speciated components was conducted using 2002 State/local monitoring sites data in order to estimate the ability of the CMAQ modeling system to replicate the base year concentrations for the 12-km eastern and western domains. In summary, model performance statistics were calculated for observed-predicted pairs of daily, monthly, seasonal, and annual concentrations. Statistics were generated for the following geographic groupings: the entire 12-km Eastern US domain (EUS), the entire 12-km Western US domain (WUS), and five large subregions: Midwest, Northeast, Southeast, Central, and West U.S.20 The “acceptability” of model performance was judged by comparing our CMAQ 2002 performance results to the range of performance found in the 2001 CMAQ results used in the proposal, as well as recent regional ozone and PM2.5 model applications (e.g., Clean Air Interstate Rule, Final PM NAAQS Rule).21 These
Kemball-Cook, S., Y. Jia, C. Emery, R. Morris, Z. Wang, and G. Tonnesen. Annual 2002 MM5 Meteorological Modeling to Support Regional Haze Modeling of the Western United States, Prepared for The Western Regional Air Partnership (WRAP), 1515 Cleveland Place, Suite 200 Denver, CO 80202, March 2005. Environ, Enhanced Meteorological Modeling and Performance Evaluation for Two Texas Episodes, August 2001.
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Yantosca, B., 2004. GEOS-CHEMv7-01-02 User’s Guide, Atmospheric Chemistry Modeling Group, Harvard University, Cambridge, MA, October 15, 2004. The subregions are defined by States where: Midwest is IL, IN, MI, OH, and WI; Northeast is CT, DE, MA, MD, ME, NH, NJ, NY, PA, RI, and VT; Southeast is AL, FL, GA, KY, MS, NC, SC, TN, VA, and WV; Central is AR, IA, KS, LA, MN, MO, NE, OK, and TX; West is CA, OR, WA, AZ, NM, CO, UT, WY, SD, ND, MT, ID, and NV.

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See: U.S. Environmental Protection Agency; Technical Support Document for the Final Clean Air Interstate Rule: Air Quality Modeling; Office of Air Quality Planning and Standards; RTP, NC; March 2005 (CAIR Docket OAR-2005-0053-2149); and U.S. Environmental Protection Agency, 2006. Technical Support Document for the Final PM NAAQS Rule: Office of Air Quality Planning and Standards, Research Triangle Park, NC

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other modeling studies represent a wide range of modeling analyses which cover various models, model configurations, domains, years and/or episodes, chemical mechanisms, and aerosol modules. There are various statistical metrics available and used by the scientific community for model performance evaluation. The principal evaluation statistics used to evaluate CMAQ performance were two bias metrics, normalized mean bias and fractional bias; and two error metrics, normalized mean error and fractional error. Normalized mean bias (NMB) is used as a normalization to facilitate a range of concentration magnitudes. This statistic averages the difference (model - observed) over the sum of observed values. NMB is a useful model performance indicator because it avoids over inflating the observed range of values, especially at low concentrations. Normalized mean bias is defined as:

∑ ( P − O)
NMB =
1

n

∑ ( O)
1

n

*100, where P = predicted concentrations and O = observed

Normalized mean error (NME) is also similar to NMB, where the performance statistic is used as a normalization of the mean error. NME calculates the absolute value of the difference (model - observed) over the sum of observed values. Normalized mean error is defined as:

∑
NME =
1 n 1

n

P− O

∑ ( O)

*100, where P = predicted concentrations and O = observed

Fractional bias is defined as:
 n   ∑ ( P − O)  1  FB =  n 1   ( P + O)   *100, where P = predicted concentrations and O = observed n ∑  2   1 

FB is a useful model performance indicator because it has the advantage of equally weighting positive and negative bias estimates. The single largest disadvantage in this estimate of model performance is that the estimated concentration (i.e., prediction, P) is found in both the numerator and denominator.

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Fractional error (FE) is similar to fractional bias except the absolute value of the difference is used so that the error is always positive. Fractional error is defined as:
 n   ∑ P− O  1  FE =  n 1 *100, where P = predicted concentrations and O = observed n   ( P + O)   ∑  2   1 

Overall, the bias and error statistics shown in Table II-4 below indicate that the base case model ozone and PM2.5 concentrations are within the range or close to that found in recent OAQPS applications. The CMAQ model performance results give us confidence that our applications of CMAQ using this 2002 modeling platform provide a scientifically credible approach for assessing ozone and PM2.5 concentrations for the purposes of the final Locomotive/Marine rule. A detailed summary of the CMAQ model performance evaluation is available in the docket for this rulemaking.22 A summary of the PM2.5 and ozone evaluation is presented here. 1. PM2.5: The PM2.5 evaluation focuses on PM2.5 total mass and its components including sulfate (SO4), nitrate (NO3), total nitrate (TNO3=NO3+HNO3), ammonium (NH4), elemental carbon (EC), and organic carbon (OC). The PM2.5 performance statistics were calculated for each month and season individually and for the entire year, as a whole. Seasons were defined as: winter (December-January-February), spring (March-April-May), summer (June-July-August), and fall (September-OctoberNovember). PM2.5 ambient measurements for 2002 were obtained from the following networks for model evaluation: Speciation Trends Network (STN- total of 199 sites), Interagency Monitoring of PROtected Visual Environments (IMPROVE- total of 150), and Clean Air Status and Trends Network (CASTNet- total of 83). For PM2.5 species that are measured by more than one network, we calculated separate sets of statistics for each network. For brevity, Table II-4 provides annual model performance statistics for PM2.5 and its component species for the 12-km Eastern domain, 12-km Western domain, and five subregions defined above (Midwest, Northeast, Southeast, Central, and West U.S.). Table II-4. Summary of 2002 CMAQ annual PM2.5 species model performance statistics.

CMAQ 2002 Annual PM2.5 Total Mass STN 12-km EUS 12-km WUS

No. of Obs. 10307 3000

NMB (%) 10.8 -5.8

NME (%) 42.8 46.9

FB (%) 5.4 -3.1

FE (%) 42.6 45.0

Technical Support Document: 2002 CMAQ Model Performance Evaluation for Ozone and Particulate Matter, January 2008. This file is available in the docket for this rulemaking.

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Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast IMPROVE Midwest Southeast Central West 12-km EUS 12-km WUS Northeast STN Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Sulfate IMPROVE Midwest Southeast Central West 12-km EUS 12-km WUS Northeast CASTNet Midwest Southeast Central West Nitrate 12-km EUS 12-km WUS Northeast STN Midwest Southeast Central West IMPROVE 12-km EUS 12-km WUS

1516 2780 2554 2738 2487 8436 10123 592 2060 1803 1624 9543 10157 2926 1487 2730 2541 2686 2446 8532 10232 597 2070 1805 1671 9645 3173 1158 663 839 1085 229 1118 8770 2726 1488 2731 2540 1298 2446 8514 10110

14.9 20.5 -3.9 14.5 -7.4 -2.3 -26.4 8.6 21.0 -13.1 -13.1 -27.8 -3.9 -20.6 3.6 -4.3 -7.6 -3.2 -26.1 -10.8 -7.5 -4.9 -12.3 -9.5 -16.1 -5.5 -11.3 -21.3 -8.3 -12.3 -11.2 -20.7 -20.4 18.3 -45.0 17.4 32.7 8.6 12.7 -47.5 48.4 -34.8

35.6 48.2 36.0 49.1 46.8 49.0 53.5 41.5 59.4 41.2 49.4 53.1 33.6 41.9 34.9 29.1 33.4 39.2 44.9 33.0 42.4 29.9 30.1 32.9 35.0 43.5 20.5 34.6 19.3 17.9 21.5 27.3 35.3 65.9 63.1 59.1 70.4 84.6 52.5 62.8 106.8 80.67

13.2 16.6 -10.0 6.0 -4.5 -5.7 -26.3 2.4 17.4 -19.8 -17.6 -27.1 -9.7 -12.2 -2.9 -8.8 -16.3 -7.2 -15.8 -7.2 7.6 -10.0 -9.9 -16.8 -16.0 8.6 -16.3 -11.2 -16.3 -15.6 -17.8 -27.4 -10.7 -29.1 -70.6 -5.0 -10.9 -64.7 -13.4 -73.8 -52.8 -101.0

34.4 42.6 39.7 49.4 44.8 51.4 57.5 41.0 51.6 49.9 57.0 57.2 38.4 43.5 36.2 33.6 38.8 44.3 44.8 40.6 45.7 35.7 36.1 40.5 42.4 45.9 26.1 35.9 24.3 21.6 27.2 33.6 36.1 84.5 95.0 67.3 78.1 107.5 69.1 95.4 116.4 130.0

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Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Total Nitrate (NO3+HNO3) CASTNet Midwest Southeast Central West 12-km EUS 12-km WUS Northeast STN Midwest Southeast Central Ammonium West 12-km EUS 12-km WUS Northeast CASTNet Midwest Southeast Central West 12-km EUS 12-km WUS Northeast STN Midwest Southeast Central Elemental Carbon West 12-km EUS 12-km WUS Northeast IMPROVE Midwest Southeast Central West Organic Carbon STN 12-km EUS 12-km WUS

597 2069 1803 1672 9522 3171 1157 662 839 1085 229 1117 10157 2926 1488 2731 2540 2685 2446 3166 1156 661 837 1085 229 1116 10031 2975 1498 2744 2506 2570 2475 8282 10069 599 2056 1795 1532 9493 9726 2903

43.0 122.2 33.5 18.1 -39.6 24.4 -19.5 20.5 39.1 22.9 6.2 -20.4 11.9 -23.6 16.0 12.3 7.3 15.0 -30.6 5.3 -16.8 15.3 9.8 -7.7 7.4 -21.1 45.0 43.1 37.1 53.1 16.9 91.7 49.0 -15.0 -14.1 -22.6 11.6 -32.4 -24.3 -15.5 -39.9 -37.6

86.0 153.8 112.2 81.0 81.1 37.3 44.2 29.4 46.5 39.5 35.6 45.8 40.6 55.7 39.6 38.4 38.4 46.6 56.7 30.8 42.5 27.6 34.7 30.1 33.1 43.5 78.9 82.6 58.9 76.7 66.0 118.0 86.2 49.2 67.2 37.5 57.5 44.6 47.6 67.8 58.0 60.3

-37.0 3.5 -78.5 -59.6 -104.0 16.8 -12.0 16.3 29.0 15.8 0.6 -12.1 14.4 7.2 21.8 19.2 6.0 14.3 2.9 2.7 -13.0 13.6 11.9 -9.7 3.0 -14.4 22.1 18.2 24.5 26.3 7.2 41.0 17.1 -23.4 -29.5 -27.4 0.5 -42.0 -29.8 -31.3 -41.1 -40.4

102.8 107.5 130.8 114.1 131.1 35.1 46.0 25.3 39.7 37.2 36.2 46.6 45.2 58.1 42.8 42.4 41.8 52.1 59.7 31.6 41.1 25.2 33.9 33.6 35.6 41.4 56.9 61.3 48.3 54.7 51.7 68.1 62.7 52.8 62.1 46.5 50.8 55.6 55.9 62.7 70.5 69.3

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Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast IMPROVE Midwest Southeast Central West

1447 2641 2474 2504 2408 8287 10082 598 2057 1800 1531 9508

-45.2 -26.5 -47.4 -43.6 -36.3 -32.4 -34.8 -42.4 -6.4 -46.1 -47.9 -34.5

60.9 61.7 55.3 54.0 61.4 60.5 60.0 54.8 68.2 58.4 61.6 59.6

-41.6 -19.7 -53.7 -51.3 -37.9 -37.1 -31.2 -40.2 -0.7 -69.7 -61.2 -29.7

73.1 67.6 70.7 69.7 70.2 67.9 63.0 63.8 60.8 81.3 79.6 61.9

2. Ozone: The ozone evaluation focuses on the observed and predicted hourly ozone concentrations and eight-hour daily maximum ozone concentrations using a (observation) threshold of 40 ppb. This ozone model performance was limited to the period used in the calculation of projected design values within the analysis, that is: May, June, July, August, and September. Ozone ambient measurements for 2002 were obtained from the Air Quality System (AQS) Aerometric Information Retrieval System (AIRS). A total of 1178 ozone measurement sites were included for evaluation. These ozone data were measured and reported on an hourly basis. Table II-5 and II-6 provide hourly and eight-hour daily maximum ozone model performance statistics, respectively, for the 12-km Eastern and Western U.S. domain and the five subregions. Generally, hourly and eight-hour ozone model performance are under-predicted in both the 12-km EUS and WUS when applying a threshold of 40 ppb for the modeled ozone season (May-September). For the 12-km EUS and WUS domain, the bias and error statistics are comparable for the aggregate of the ozone season and for each individual ozone month modeled. Table II-5. Summary of CMAQ 2002 hourly ozone model performance statistics
CMAQ 2002 Hourly Ozone: Threshold of 40 ppb 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast No. of Obs. 241185 124931 51055 55859 69073 41728 111385 256263 125662 61354 NMB (%) -0.7 -3.7 1.2 3.3 -2.5 -6.4 -3.9 -7.5 -8.4 -8.5 NME (%) 15.9 15.9 17.1 16.2 14.1 17.3 16.1 16.8 17.7 17.3 FB (%) -2.0 -5.0 -0.3 2.4 -3.1 -9.2 -5.2 -9.0 -9.3 -9.9 FE (%) 17.1 17.3 18.2 16.9 14.8 20.3 17.6 18.6 19.1 19.1

May

June

15

Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Seasonal Aggregate Midwest Southeast Central U West

54515 67867 46026 109157 257076 116785 66774 59360 68619 36021 104321 235090 125575 53837 54179 62506 41456 110225 179156 99710 44678 34285 41627 41549 83921 1168770 592663 277698 258198 309692 206780 519009

-7.2 -7.2 -10.0 -8.8 -5.3 -12.0 -3.9 -10.5 -3.6 -3.6 -13.6 -8.7 -7.9 -6.4 -10.8 -9.4 -9.3 -8.5 -9.9 -10.7 -8.7 -11.4 -8.2 -12.8 -11.7 -6.4 -8.4 -5.4 -7.3 -6.0 -8.6 -9.2

17.9 15.3 17.5 18.2 17.7 21.5 17.0 19.4 16.5 18.7 21.8 17.8 20.1 16.7 19.1 17.3 18.7 20.6 17.2 19.0 16.3 18.5 16.5 18.8 20.0 17.1 18.8 16.9 18.3 15.9 18.2 19.3

-8.3 -7.6 -13.5 -9.9 -6.6 -14.9 -4.8 -12.3 -3.9 -6.3 -16.8 -10.2 -10.2 -7.4 -12.4 -9.9 -12.8 -11.1 -11.8 -12.7 -10.6 -12.9 -9.0 -16.6 -13.8 -7.7 -10.3 -6.5 -8.4 -6.4 -11.9 -11.2

19.6 16.3 21.2 19.7 19.2 24.3 18.0 21.7 17.2 21.1 24.9 19.7 22.1 18.0 21.4 18.5 22.4 22.8 19.5 21.1 18.4 20.4 17.8 22.8 22.1 18.8 20.7 18.4 20.0 16.8 21.6 21.3

July

August

September

Table II-6. Summary of CMAQ 2002 eight-hour daily maximum ozone model performance statistics.
CMAQ 2002 Eight-Hour Maximum Ozone: Threshold of 40 ppb May 12-km EUS 12-km WUS Northeast Midwest Southeast No. of Obs. 19172 9223 4255 4198 5470 NMB (%) 3.9 0.2 6.7 7.8 0.6 NME (%) 12.7 12.6 14.3 13.7 10.9 FB (%) 4.3 0.6 6.8 8.2 1.1 FE (%) 12.6 12.8 14.2 13.5 11.0

16

Central West 12-km EUS 12-km WUS June Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West 12-km EUS 12-km WUS Northeast Midwest Southeast Central West

3379 8155 19462 9029 4608 4104 5110 3603 7818 20565 8809 5380 4368 5633 3114 7784 19260 9551 4667 4012 5067 3543 8311 15865 8185 4074 3120 3671 3492 6911 94324 44797 22984 19802 24951 17131 38979

0.3 -0.1 -3.9 -4.9 -5.3 -3.2 -4.8 -4.5 -5.3 -1.6 -7.4 -0.7 -6.5 -0.9 1.3 -9.0 -5.1 -2.8 -2.9 -8.1 -6.4 -4.0 -3.2 -6.2 -6.7 -6.0 -7.2 -4.5 -8.5 -7.3 -2.6 -4.3 -1.9 -3.6 -3.1 -3.3 -4.9

12.3 12.8 12.3 14.1 12.5 12.7 11.8 12.2 14.5 13.5 17.1 13.0 14.2 13.0 14.4 17.2 13.2 15.8 12.4 13.9 13.4 13.5 16.1 12.6 15.0 11.8 13.3 12.6 13.8 15.9 12.9 14.9 12.8 13.6 12.4 13.2 15.3

0.7 0.3 -3.3 -4.2 -4.7 -2.2 -4.1 -4.4 -4.7 -1.0 -8.1 -0.2 -5.8 -0.1 1.2 -9.9 -4.4 -3.1 -2.2 -7.5 -5.4 -3.9 -3.6 -5.9 -6.9 -6.0 -6.5 -3.8 -8.7 -7.6 -1.9 -4.2 -1.2 -2.5 -2.3 -3.1 -5.0

12.4 12.9 12.4 14.2 12.7 12.8 11.9 12.7 14.7 13.6 18.0 12.9 14.4 13.0 14.7 18.2 13.4 16.1 12.4 14.2 13.4 14.1 16.5 12.9 15.5 12.3 13.3 12.7 14.5 16.4 13.0 15.3 12.9 13.7 12.4 13.7 15.7

July

August

September

Seasonal Aggregate

F. CMAQ Locomotive/Marine Modeling Scenarios The CMAQ modeling system was used to calculate annual PM2.5 concentrations, daily 8-hour ozone concentrations, and visibility estimates for each of the following seven emissions scenarios:

17

1) 2002 base case 2) 2020 future baseline 3) 2020 future control case – locomotive and marine controls 4) 2020 future control case – marine controls only 5) 2030 future baseline 6) 2030 future control case – locomotive and marine controls 7) 2030 future control case – marine controls only Model predictions are used in a relative sense to estimate scenario-specific, future-year design values of PM2.5 and ozone. This is done by calculating the simulated air quality ratios between any particular future year simulation and the 2002 base. These predicted change ratios are then applied to ambient base year design values. The design value projection methodology used in this analysis followed EPA guidance for such analyses23 We used the 5-year weighted average 2000-2004 design values as the starting point for the projections. Additionally, the raw model outputs are also used in a relative sense for creating inputs to the health and welfare impact functions of the benefits analysis.

III. CMAQ Model Results
A. Impacts of Locomotive/Marine Rule on Future PM2.5 Annual Averages This section summarizes the results of our modeling of PM2.5 air quality impacts in the future due to the reductions in locomotive and commercial marine diesel emissions. Appendix A contains annual average PM2.5 design values by county for each modeling scenario. The modeling results indicate that the emissions reductions from this rule will contribute to lower ambient PM2.5 levels in future years. Tables III-1 and III-2 show the projected improvements in average annual PM2.5 design values, for various years as a result of the Locomotive/Marine control scenarios discussed in Section II.F.

23

U.S. EPA, Guidance on the Use of Models and Other Analyses in Attainment Demonstrations for the 8hour Ozone NAAQS; EPA-454/R-05-002; Research Triangle Park, NC; October 2005.

18

Table III-1. Model-projected change in annual average PM2.5 design values resulting from the Locomotive/Marine modeling scenarios for several categories of counties. Units are µg/m3.
2020 marine controls only -0.02 -0.03 -0.03 -0.06 -0.04 2020 locomotive and marine controls -0.04 -0.06 -0.06 -0.10 -0.09 2030 marine controls only -0.04 -0.05 -0.06 -0.14 -0.09 2030 locomotive and marine controls -0.08 -0.11 -0.12 -0.22 -0.18

Average change

Average change in all counties Average change in counties whose base year design value is above the NAAQS Average change in counties whose base year design value is within 10% of the NAAQS Average change in counties whose projection year design value is above the NAAQS Average change in counties whose projection year design value is within 10% of the NAAQS

Table III-2. Model-projected, population-weighted, change in annual average PM2.5 design values resulting from the Locomotive/Marine modeling scenarios for several categories of counties. Units are µg/m3.
2020 marine controls only -0.03 -0.05 -0.04 -0.07 -0.05 2020 locomotive and marine controls -0.06 -0.08 -0.08 -0.11 -0.09 2030 marine controls only -0.08 -0.11 -0.10 -0.16 -0.12 2030 locomotive and marine controls -0.12 -0.16 -0.16 -0.21 -0.18

Average change

Average change in all counties Average change in counties whose base year design value is above the NAAQS Average change in counties whose base year design value is within 10% of the NAAQS Average change in counties whose projection year design value is above the NAAQS Average change in counties whose projection year design value is within 10% of the NAAQS

The modeling projects that 11 counties will have design values greater than 15.0 g/m3 in 2020 and 2030. Over 24 million people are projected to live in a PM2.5 nonattainment county in the future. The controls from the final Locomotive/Marine rule modeling are enough to bring one of those counties (Merced Co., CA) into attainment by 2030. As can be seen from Table III-1, the final Locomotive/Marine rule controls will lower PM2.5 concentrations on average by 0.04 g/m3 in 2020 and 0.08 g/m3 in 2030. Greater improvements in PM2.5 air quality are projected in areas where present-day and future-projected PM2.5 levels are above or near the NAAQS. For instance, when considering only those counties whose future year design values are projected to exceed the NAAQS, the average improvement resulting from this rule is 0.10 g/m3 in 2020 and 0.22 g/m3 in 2030. Additionally, as shown in Table III-2, the improvements resulting from the rule are larger when population-weighted. The greatest impacts from the final 19

Locomotive/Marine rule emissions reductions tend to occur in areas with high populations. The largest reduction in annual average PM2.5 occurs in Houston TX (Harris Co.) where the rule is projected to result in a 0.38 g/m3 improvement in 2020 and 0.81 g/m3 in 2030. The largest reduction in an area that is projected to exceed the PM2.5 NAAQS in 2020 and 2030 is in the Los Angeles region (Riverside Co.) where the annual average PM2.5 design value is projected to drop from 22.67 to 22.48 g/m3 in 2020, and 22.54 to 22.13 g/m3 in 2030 as a result of the final Locomotive/Marine rule. The modeling indicated that both the locomotive and marine components of the rule improved PM2.5 air quality relatively equally. Figures III-1 through III-4 display the projected county-level, annual PM2.5 design value changes expected from various locomotive/marine control scenarios and years associated with this rule. The largest impacts tend to be in areas near water, where commercial marine source contributions can be large.

20

Figure III-1. Model-projected change in annual PM2.5 design values from the Locomotive/Marine control scenario in 2020. Units are µg/m3.

Legend
-1.00 to -0.50 -0.49 to -0.25 -0.24 to -0.10 -0.09 to -0.05 -0.04 to 0.00 > 0.00

Number of Counties 0 4 43 142 367 0 Differences due to scenario 2020cc Locomarine

Figure III-2. Model-projected change in annual PM2.5 design values from the Marine-only control scenario in 2020. Units are µg/m3.

Legend
-1.00 to -0.50 -0.49 to -0.25 -0.24 to -0.10 -0.09 to -0.05 -0.04 to 0.00 > 0.00

Number of Counties 0 3 19 37 496 1 Differences due to scenario 2020cc Marine-only

21

Figure III-3. Model-projected change in annual PM2.5 design values from the Locomotive/Marine control scenario in 2030. Units are µg/m3.

Legend
-1.00 to -0.50 -0.49 to -0.25 -0.24 to -0.10 -0.09 to -0.05 -0.04 to 0.00 > 0.00

Number of Counties 4 20 143 193 196 0 Differences due to scenario 2030cc Locomarine

Figure III-4. Model-projected change in annual PM2.5 design values from the Marine-only control scenario in 2030. Units are µg/m3.

Legend
-1.00 to -0.50 -0.49 to -0.25 -0.24 to -0.10 -0.09 to -0.05 -0.04 to 0.00 > 0.00

Number of Counties 4 11 46 46 449 0 Differences due to scenario 2030cc Marine-only

22

B. Impacts of the Locomotive/Marine Rule on Future 8-Hour Ozone Levels This section summarizes the results of our modeling of ozone air quality impacts in the future due to the reductions in locomotive and commercial marine diesel emissions. Appendix B contains 8-hour ozone design values by county for each modeling scenario. The modeling results indicate that the emissions reductions from this rule will contribute to lower ambient 8-hour ozone design values in future years. Tables III-3 and III-4 show the projected improvements in average 8-hour ozone design values, for various years as a result of the four Locomotive/Marine control scenarios. Table III-3. Model-projected change in average 8-hour ozone design values resulting from the Locomotive/Marine modeling scenarios for several categories of counties. Units are ppb.
2020 marine controls only -0.23 -0.22 -0.23 0.00 -0.20 2020 locomotive and marine controls -0.45 -0.45 -0.46 -0.19 -0.41 2030 marine controls only -0.51 -0.51 -0.53 0.00 -0.65 2030 locomotive and marine controls -1.15 -1.18 -1.18 -0.50 -1.24

Average change

Average change in all counties Average change in counties whose base year design value is above the NAAQS Average change in counties whose base year design value is within 10% of the NAAQS Average change in counties whose projection year design value is above the NAAQS Average change in counties whose projection year design value is within 10% of the NAAQS

Table III-4. Model-projected, population-weighted, change in average 8-hour ozone design values resulting from the Locomotive/Marine modeling scenarios for several categories of counties. Units are ppb.
2020 marine controls only -0.12 -0.09 -0.12 -0.01 +0.05 2020 locomotive and marine controls -0.30 -0.27 -0.31 -0.13 -0.08 2030 marine controls only -0.32 -0.26 -0.32 -0.24 -0.42 2030 locomotive and marine controls -0.85 -0.78 -0.86 -0.62 -0.79

Average change

Average change in all counties Average change in counties whose base year design value is above the NAAQS Average change in counties whose base year design value is within 10% of the NAAQS Average change in counties whose projection year design value is above the NAAQS Average change in counties whose projection year design value is within 10% of the NAAQS

23

The modeling projects that 9 counties will have design values greater than 0.08 ppm in 2020 and 6 counties will exceed that level in 2030. Based on this modeling, over 22 million people are projected to live in a ozone nonattainment county in 2020. The controls from the final Locomotive/Marine rule modeling are enough to bring one of those counties (Kenosha Co., WI) into attainment by 2020. Further, two of the nine counties will be at least 10 percent closer to a design value of less than 85 ppb, and on average all nine counties will be about 18 percent closer to a design value of less than 85 ppb (including Kenosha Co., WI). As can be seen from Table III-3, the final Locomotive/Marine rule controls will lower ozone design values on average by 0.30 ppb in 2020 and 0.85 ppb in 2030. Unlike PM2.5, there are instances in which the final Locomotive/Marine rule controls are projected to increase ozone levels. As a result of where these "disbenefit" areas are located, the improvements resulting from the rule are smaller when population-weighted. The largest increase in a county-level 8-hour ozone design values occurs in the Los Angeles area (Orange Co.) where the rule is projected to result in an increase of 2.6 ppb in 2020 and 5.5 ppb in 2030. This increase is highly localized. The county with the second largest increase from the rule is Riverside Co. CA which is projected to have an 0.5 ppb increase from the rule in 2030. The largest county-level decrease resulting from the rule is north of the Los Angeles area (Santa Barbara Co.) where ozone levels are projected to drop by 1.8 and 4.6 ppb, respectively, in 2020 and 2030. Again, the modeling indicated that both the locomotive and marine components of the rule improved air quality relatively equally, but it was the marine reductions that tended to lead to the "disbenefit" regions. Figures III-5 through III-8 display the projected county-level, 8-hour ozone design value changes expected from the final Locomotive/Marine rule control scenarios. The largest impacts tend to be in areas near water, where commercial marine source contributions can be large.

24

Figure III-5. Model-projected change in annual 8-hour ozone design values from the Locomotive/Marine control scenario in 2020. Units are ppb.

Legend
<= -2.0

Number of Counties 0 14 241 315 5 3 1 Effect of Locomarine in 2020

> -2.0 to <= -1.0 > -1.0 to <= -0.5 > -0.5 to <= -0.1 = 0.0 > 0.0 to <= 1.0 > 1.0

Figure III-6. Model-projected change in annual 8-hour ozone design values from the marine-only control scenario in 2020. Units are ppb.

Legend
<= -2.0

Number of Counties 0 9 63 450 48 8 1 Effect of Marine-only in 2020

> -2.0 to <= -1.0 > -1.0 to <= -0.5 > -0.5 to <= -0.1 = 0.0 > 0.0 to <= 1.0 > 1.0

25

Figure III-7. Model-projected change in annual 8-hour ozone design values from the Locomotive/Marine control scenario in 2030. Units are ppb.

Legend
<= -2.0

Number of Counties 27 338 190 18 1 4 1 Effect of LocoMarine in 2030

> -2.0 to <= -1.0 > -1.0 to <= -0.5 > -0.5 to <= -0.1 = 0.0 > 0.0 to <= 1.0 > 1.0

Figure III-8. Model-projected change in annual 8-hour ozone design values from the marine-only control scenario in 2030. Units are ppb.

Legend
<= -2.0

Number of Counties 9 71 170 306 13 9 1 Effect of Marine-only in 2030

> -2.0 to <= -1.0 > -1.0 to <= -0.5 > -0.5 to <= -0.1 = 0.0 > 0.0 to <= 1.0 > 1.0

26

C. Impacts of the Locomotive/Marine Rule on Visibility The modeling conducted for the Locomotive/Marine rule was also used to project the impacts of the reductions on visibility conditions over 133 mandatory class I federal areas across the U.S. in 2020 and 2030. The results indicate that reductions in regional haze would occur in all 133 of these federal areas. The model projects that average visibility on the 20% worst days would improve by 0.02 deciviews.24 The average deciview improvement on the 20% worst days is 0.06 in 2030. The greatest visibility improvement due to this rule would occur at the San Gorgonio Wilderness where a 0.24 deciview improvement is projected by 2030 as a result of the locomotive/marine controls in this rule. Appendix C contains the visibility results from the locomotive/marine scenario over the 133 Class 1 areas.

The level of visibility impairment in an area is based on the light-extinction coefficient and a unit less visibility index, called a “deciview”, which is used in the valuation of visibility. The deciview metric provides a scale for perceived visual changes over the entire range of conditions, from clear to hazy. Under many scenic conditions, the average person can generally perceive a change of one deciview. The higher the deciview value, the worse the visibility. Thus, an improvement in visibility is a decrease in deciview value.

24

27

Appendix A: Annual Average PM2.5 Design Values for Locomotive/Marine Scenarios (units are µg/m3)
State Name
Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Arizona Arizona Arizona Arizona Arizona Arizona Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas Arkansas California

County Name
Baldwin Co Clay Co Colbert Co DeKalb Co Escambia Co Etowah Co Jefferson Co Madison Co Mobile Co Montgomery Co Morgan Co Russell Co Shelby Co Sumter Co Talladega Co Cochise Co Gila Co Maricopa Co Pima Co Pinal Co Santa Cruz Co Arkansas Co Ashley Co Crittenden Co Faulkner Co Mississippi Co Phillips Co Polk Co Pope Co Pulaski Co Sebastian Co Union Co White Co Alameda Co

Baseline DV
11.38 13.50 13.02 14.86 12.82 15.69 18.36 14.20 12.80 14.50 13.36 16.04 14.50 12.26 14.96 6.97 9.52 11.45 6.75 8.14 11.74 12.13 12.14 12.91 12.40 11.84 12.16 11.08 12.23 14.12 12.33 12.64 11.63 11.76

2020 Base
9.14 10.45 10.23 11.21 10.48 12.02 15.00 10.74 10.72 11.76 10.35 13.15 11.36 9.78 11.48 6.60 8.89 10.30 6.13 7.45 11.24 10.08 10.28 10.66 10.33 9.66 10.20 9.02 10.13 11.63 10.33 11.01 9.57 10.77

2020 Marine only
9.13 10.44 10.22 11.20 10.47 12.01 14.99 10.74 10.58 11.75 10.34 13.14 11.36 9.77 11.48 6.60 8.89 10.30 6.13 7.45 11.24 10.06 10.26 10.60 10.32 9.62 10.12 9.02 10.12 11.61 10.33 10.99 9.56 10.75

2020 Locomotive / Marine
9.12 10.41 10.20 11.18 10.46 11.98 14.95 10.72 10.56 11.72 10.32 13.13 11.32 9.75 11.44 6.60 8.88 10.29 6.12 7.42 11.23 10.03 10.24 10.55 10.28 9.60 10.10 9.00 10.10 11.55 10.31 10.98 9.52 10.73

2030 Base
9.19 10.45 10.24 11.20 10.50 11.99 14.95 10.75 10.95 11.75 10.36 13.14 11.38 9.81 11.47 6.61 8.87 10.31 6.12 7.59 11.27 10.09 10.33 10.93 10.34 9.73 10.38 9.04 10.12 11.60 10.33 11.04 9.57 10.68

2030 Marine only
9.15 10.44 10.22 11.19 10.48 11.98 14.94 10.73 10.64 11.75 10.34 13.13 11.37 9.78 11.46 6.61 8.87 10.31 6.12 7.59 11.27 10.06 10.29 10.81 10.33 9.65 10.19 9.02 10.11 11.57 10.32 11.01 9.54 10.64

2030 Locomotive / Marine
9.14 10.38 10.19 11.15 10.44 11.92 14.88 10.71 10.62 11.69 10.30 13.10 11.31 9.74 11.38 6.60 8.86 10.28 6.10 7.55 11.27 10.00 10.26 10.73 10.26 9.62 10.17 8.99 10.06 11.46 10.29 10.97 9.48 10.60

28

California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California Colorado

Butte Co Calaveras Co Colusa Co Contra Costa Co Fresno Co Humboldt Co Imperial Co Inyo Co Kern Co Kings Co Lake Co Los Angeles Co Mendocino Co Merced Co Monterey Co Nevada Co Orange Co Placer Co Riverside Co Sacramento Co San Bernardino Co San Diego Co San Francisco Co San Joaquin Co San Luis Obispo Co San Mateo Co Santa Barbara Co Santa Clara Co Santa Cruz Co Shasta Co Solano Co Sonoma Co Stanislaus Co Sutter Co Tulare Co Ventura Co Yolo Co Adams Co

13.69 8.85 9.44 11.32 20.02 8.48 14.44 6.17 21.77 18.77 5.03 23.16 8.00 16.47 8.23 7.97 18.27 11.65 27.15 12.56 24.63 15.65 11.58 14.84 9.20 10.58 9.32 11.33 8.17 9.01 12.03 9.91 16.49 11.39 21.33 14.34 10.04 10.29

11.84 7.83 8.78 10.53 17.54 7.34 13.92 5.94 19.28 16.82 4.73 20.69 7.22 15.15 7.74 7.25 15.73 10.21 22.67 11.47 21.79 14.64 11.08 13.58 8.79 9.77 9.06 10.10 7.38 7.74 11.64 9.22 14.57 10.14 18.71 12.54 9.11 8.91

11.83 7.82 8.78 10.50 17.52 7.33 13.91 5.95 19.26 16.80 4.72 20.64 7.21 15.14 7.73 7.25 15.60 10.20 22.53 11.46 21.69 14.61 10.94 13.54 8.79 9.76 9.05 10.09 7.38 7.74 11.58 9.21 14.54 10.13 18.69 12.45 9.10 8.91

11.80 7.80 8.77 10.49 17.47 7.33 13.87 5.94 19.21 16.76 4.72 20.61 7.21 15.11 7.72 7.23 15.58 10.17 22.48 11.43 21.66 14.60 10.93 13.51 8.78 9.74 9.05 10.08 7.37 7.73 11.57 9.21 14.50 10.10 18.64 12.44 9.08 8.87

11.76 7.84 8.75 10.57 17.14 7.36 13.97 5.96 18.87 16.55 4.73 20.86 7.20 15.11 7.75 7.31 15.93 10.07 22.54 11.36 21.97 14.91 11.58 13.57 8.85 9.70 9.12 9.95 7.30 7.76 11.88 9.21 14.30 10.07 18.24 12.59 8.99 8.80

11.75 7.82 8.74 10.50 17.09 7.34 13.95 5.96 18.83 16.52 4.73 20.75 7.19 15.08 7.74 7.31 15.68 10.04 22.21 11.33 21.75 14.83 11.27 13.48 8.84 9.68 9.10 9.93 7.29 7.76 11.76 9.21 14.23 10.06 18.19 12.40 8.97 8.80

11.69 7.79 8.72 10.48 16.97 7.33 13.88 5.95 18.70 16.43 4.72 20.72 7.18 15.02 7.73 7.26 15.65 9.97 22.13 11.27 21.71 14.82 11.26 13.41 8.82 9.65 9.09 9.91 7.28 7.73 11.74 9.20 14.13 9.98 18.07 12.38 8.92 8.74

29

Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Colorado Connecticut Connecticut Connecticut Connecticut Delaware Delaware Delaware District of Columbia Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida

Arapahoe Co Archuleta Co Boulder Co Delta Co Denver Co El Paso Co Elbert Co Gunnison Co Larimer Co Pueblo Co Routt Co San Miguel Co Weld Co Fairfield Co Hartford Co New Haven Co New London Co Kent Co New Castle Co Sussex Co District of Columbia Alachua Co Bay Co Brevard Co Broward Co Citrus Co Duval Co Escambia Co Hillsborough Co Lee Co Leon Co Manatee Co Marion Co Miami-Dade Co Orange Co Palm Beach Co Pinellas Co Polk Co

8.70 5.99 9.27 8.26 10.58 7.86 4.33 6.69 7.88 7.79 7.40 5.33 9.33 12.85 11.50 13.71 11.57 12.81 15.96 13.65 15.75 10.12 11.04 7.88 8.30 9.13 10.64 11.56 11.25 8.42 12.67 9.31 10.04 9.66 10.19 7.54 10.46 10.36

7.76 5.55 8.20 7.44 9.22 7.16 3.92 6.26 7.21 7.16 6.98 4.99 8.14 11.39 9.84 11.48 9.60 9.54 12.35 10.52 11.72 7.71 9.01 5.65 6.29 6.73 8.49 9.63 8.40 6.10 10.19 6.56 7.56 7.51 7.37 5.75 7.84 7.49

7.76 5.55 8.19 7.44 9.22 7.16 3.92 6.26 7.21 7.16 6.98 4.99 8.14 11.38 9.84 11.47 9.60 9.53 12.33 10.51 11.71 7.71 8.98 5.64 6.23 6.73 8.43 9.62 8.31 6.10 10.18 6.55 7.56 7.39 7.37 5.75 7.83 7.49

7.74 5.55 8.17 7.42 9.19 7.14 3.91 6.26 7.19 7.13 6.98 4.99 8.10 11.37 9.84 11.46 9.60 9.52 12.30 10.50 11.69 7.71 8.98 5.64 6.23 6.72 8.43 9.62 8.30 6.10 10.16 6.55 7.56 7.39 7.37 5.75 7.82 7.49

7.80 5.54 8.19 7.40 9.12 7.14 3.98 6.25 7.16 7.16 6.96 4.98 8.16 11.54 9.86 11.52 9.66 9.61 12.52 10.54 11.73 7.70 9.03 5.65 6.40 6.73 8.62 9.63 8.57 6.08 10.13 6.57 7.54 7.60 7.39 5.80 7.84 7.52

7.80 5.54 8.19 7.40 9.11 7.14 3.98 6.25 7.16 7.16 6.96 4.98 8.16 11.52 9.85 11.48 9.65 9.58 12.46 10.52 11.73 7.70 8.98 5.64 6.27 6.72 8.49 9.62 8.38 6.08 10.12 6.55 7.54 7.37 7.39 5.79 7.83 7.51

7.75 5.54 8.14 7.35 9.06 7.09 3.95 6.25 7.13 7.11 6.94 4.97 8.08 11.51 9.85 11.48 9.64 9.56 12.42 10.50 11.69 7.69 8.97 5.64 6.26 6.72 8.48 9.60 8.37 6.08 10.08 6.54 7.53 7.36 7.39 5.79 7.82 7.50

30

Florida Florida Florida Florida Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Idaho Idaho Idaho Idaho Idaho Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois

Sarasota Co Seminole Co St. Lucie Co Volusia Co Bibb Co Chatham Co Clarke Co Clayton Co Cobb Co DeKalb Co Dougherty Co Floyd Co Fulton Co Glynn Co Gwinnett Co Hall Co Houston Co Lowndes Co Muscogee Co Paulding Co Richmond Co Walker Co Washington Co Wilkinson Co Ada Co Bannock Co Canyon Co Power Co Shoshone Co Adams Co Champaign Co Cook Co DuPage Co Kane Co Lake Co Macon Co Madison Co McHenry Co

9.28 9.31 8.61 9.28 15.69 13.87 15.75 16.48 16.29 16.22 14.24 15.71 18.29 11.89 16.20 15.14 13.04 12.14 14.86 14.30 15.05 15.44 14.21 15.15 9.17 8.56 9.26 9.82 12.72 12.88 12.56 17.06 14.36 13.93 12.54 13.87 17.27 12.73

6.70 6.63 6.26 6.73 12.37 11.94 11.51 12.38 12.28 12.43 11.65 11.77 14.22 9.67 12.29 11.71 10.15 9.85 12.15 10.48 12.13 11.79 11.09 11.77 8.56 8.31 8.31 9.53 12.02 10.63 10.26 13.85 11.52 11.27 10.56 11.29 14.38 10.32

6.70 6.62 6.26 6.73 12.36 11.81 11.51 12.38 12.28 12.43 11.65 11.77 14.21 9.63 12.28 11.71 10.15 9.85 12.15 10.48 12.13 11.77 11.08 11.77 8.55 8.31 8.31 9.53 12.02 10.61 10.25 13.84 11.51 11.26 10.55 11.28 14.31 10.31

6.70 6.62 6.26 6.73 12.34 11.79 11.49 12.36 12.26 12.42 11.64 11.74 14.18 9.62 12.27 11.69 10.13 9.83 12.14 10.45 12.12 11.74 11.06 11.75 8.54 8.29 8.28 9.51 12.01 10.54 10.21 13.74 11.42 11.18 10.51 11.23 14.27 10.27

6.69 6.61 6.26 6.72 12.33 12.10 11.46 12.35 12.26 12.48 11.62 11.76 14.27 9.71 12.21 11.70 10.14 9.82 12.15 10.50 12.11 11.79 11.08 11.77 8.53 8.30 8.22 9.52 11.99 10.58 10.21 13.79 11.46 11.19 10.59 11.23 14.53 10.28

6.68 6.61 6.26 6.72 12.33 11.82 11.46 12.35 12.25 12.48 11.61 11.75 14.26 9.61 12.20 11.70 10.13 9.82 12.14 10.50 12.11 11.76 11.07 11.77 8.52 8.30 8.22 9.52 11.98 10.53 10.19 13.75 11.43 11.16 10.56 11.21 14.36 10.26

6.68 6.60 6.25 6.72 12.28 11.80 11.42 12.30 12.20 12.45 11.59 11.70 14.21 9.60 12.18 11.67 10.10 9.78 12.11 10.44 12.08 11.71 11.03 11.72 8.49 8.27 8.15 9.48 11.96 10.41 10.11 13.57 11.28 11.03 10.47 11.11 14.27 10.16

31

Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Iowa Iowa Iowa Iowa Iowa Iowa Iowa Iowa Iowa Iowa Iowa Kansas

McLean Co Peoria Co Randolph Co Rock Island Co Sangamon Co St. Clair Co Will Co Winnebago Co Allen Co Clark Co Delaware Co Dubois Co Elkhart Co Floyd Co Henry Co Howard Co Knox Co La Porte Co Lake Co Madison Co Marion Co Porter Co Spencer Co St. Joseph Co Vanderburgh Co Vigo Co Black Hawk Co Clinton Co Emmet Co Johnson Co Linn Co Muscatine Co Polk Co Pottawattamie Co Scott Co Van Buren Co Woodbury Co Johnson Co

13.41 13.83 12.41 12.04 13.14 16.19 14.50 12.87 14.29 16.33 14.34 15.84 14.99 14.90 13.26 14.55 13.75 13.25 15.01 14.54 16.54 13.75 14.02 14.08 15.29 14.51 11.16 12.06 8.82 11.43 11.00 12.80 10.52 10.43 12.33 10.33 10.07 11.54

10.80 11.35 9.78 9.80 10.65 13.36 11.80 10.56 11.41 12.96 11.08 12.46 12.27 11.38 10.08 11.49 10.60 10.88 12.88 11.21 13.02 11.48 10.67 11.43 12.06 11.51 9.25 9.75 7.31 9.44 9.15 10.56 8.60 8.72 10.00 8.39 8.46 9.59

10.79 11.33 9.76 9.77 10.63 13.29 11.79 10.55 11.40 12.92 11.06 12.44 12.26 11.31 10.07 11.48 10.58 10.86 12.86 11.20 13.00 11.46 10.64 11.42 11.99 11.49 9.25 9.73 7.30 9.43 9.14 10.54 8.60 8.71 9.97 8.38 8.46 9.59

10.74 11.29 9.71 9.74 10.60 13.25 11.70 10.51 11.35 12.91 11.03 12.41 12.21 11.29 10.04 11.44 10.54 10.80 12.75 11.16 12.97 11.39 10.62 11.37 11.96 11.43 9.21 9.67 7.27 9.39 9.08 10.49 8.56 8.66 9.93 8.33 8.41 9.53

10.73 11.27 9.78 9.72 10.55 13.49 11.82 10.44 11.35 13.13 11.02 12.45 12.21 11.52 10.04 11.43 10.58 10.86 12.87 11.15 12.94 11.51 10.69 11.38 12.09 11.43 9.14 9.69 7.21 9.37 9.07 10.50 8.47 8.64 9.92 8.32 8.38 9.52

10.70 11.23 9.73 9.67 10.52 13.34 11.79 10.42 11.32 13.05 10.99 12.41 12.18 11.38 10.01 11.40 10.54 10.82 12.83 11.12 12.91 11.47 10.63 11.35 11.96 11.40 9.12 9.65 7.20 9.35 9.05 10.45 8.46 8.63 9.87 8.30 8.38 9.51

10.61 11.15 9.65 9.58 10.44 13.25 11.63 10.33 11.23 13.02 10.91 12.37 12.08 11.34 9.95 11.33 10.46 10.70 12.64 11.05 12.83 11.34 10.60 11.26 11.90 11.30 9.04 9.53 7.13 9.26 8.93 10.35 8.37 8.53 9.78 8.21 8.28 9.41

32

Kansas Kansas Kansas Kansas Kansas Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Maine Maine

Linn Co Sedgwick Co Shawnee Co Sumner Co Wyandotte Co Bell Co Boyd Co Bullitt Co Campbell Co Carter Co Christian Co Daviess Co Fayette Co Franklin Co Hardin Co Jefferson Co Kenton Co Laurel Co Madison Co McCracken Co Perry Co Pike Co Warren Co Caddo Parish Calcasieu Parish Concordia Parish East Baton Rouge Parish Iberville Parish Jefferson Parish Lafayette Parish Orleans Parish Ouachita Parish St. Bernard Parish Tangipahoa Parish Terrebonne Parish West Baton Rouge Parish Androscoggin Co Aroostook Co

10.66 11.06 10.86 10.19 13.55 14.64 14.88 14.88 14.00 12.18 13.47 14.70 15.60 13.67 13.97 16.58 14.88 12.20 13.53 13.39 13.14 13.67 13.81 12.63 11.35 11.10 13.11 12.55 12.17 11.02 12.23 11.46 10.69 11.17 10.40 12.81 10.73 11.29

8.92 9.58 9.17 8.79 11.42 10.97 11.41 11.43 10.24 8.84 10.47 11.52 11.94 10.03 10.50 13.65 11.03 8.89 9.86 10.61 9.62 10.02 10.55 10.77 9.83 9.48 11.99 11.41 10.32 9.38 10.13 9.80 8.74 9.21 8.69 11.72 9.40 10.60

8.92 9.58 9.17 8.79 11.41 10.97 11.34 11.41 10.19 8.83 10.46 11.49 11.93 10.01 10.48 13.62 10.99 8.88 9.85 10.59 9.62 10.01 10.54 10.76 9.79 9.41 11.72 11.20 10.08 9.37 10.02 9.79 8.66 9.19 8.66 11.46 9.40 10.59

8.86 9.55 9.11 8.76 11.33 10.94 11.31 11.39 10.15 8.80 10.44 11.48 11.89 9.99 10.46 13.61 10.95 8.85 9.81 10.57 9.59 9.98 10.53 10.73 9.78 9.40 11.71 11.19 10.07 9.36 10.01 9.76 8.65 9.18 8.66 11.45 9.40 10.59

8.90 9.53 9.07 8.79 11.51 10.97 11.65 11.52 10.31 8.89 10.49 11.55 11.72 10.04 10.51 13.92 11.16 8.88 9.93 10.63 9.60 10.02 10.55 10.83 9.95 9.65 12.85 12.06 10.87 9.49 10.44 9.84 8.94 9.35 8.85 12.58 9.38 10.59

8.89 9.52 9.07 8.78 11.48 10.96 11.50 11.48 10.22 8.85 10.46 11.49 11.70 10.01 10.49 13.87 11.06 8.87 9.91 10.57 9.59 10.01 10.54 10.81 9.87 9.51 12.28 11.63 10.37 9.46 10.22 9.81 8.76 9.29 8.78 12.02 9.38 10.59

8.78 9.47 8.95 8.72 11.32 10.92 11.46 11.43 10.15 8.81 10.43 11.46 11.64 9.97 10.45 13.84 11.01 8.81 9.84 10.55 9.54 9.95 10.51 10.75 9.86 9.50 12.26 11.62 10.35 9.46 10.21 9.77 8.74 9.28 8.78 12.01 9.38 10.59

33

Maine Maine Maine Maine Maine Maryland Maryland Maryland Maryland Maryland Maryland Massachusetts Massachusetts Massachusetts Massachusetts Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Minnesota Minnesota Minnesota Minnesota Minnesota Minnesota

Cumberland Co Hancock Co Kennebec Co Oxford Co Penobscot Co Anne Arundel Co Baltimore city Baltimore Co Harford Co Montgomery Co Washington Co Berkshire Co Hampden Co Plymouth Co Suffolk Co Allegan Co Bay Co Berrien Co Chippewa Co Genesee Co Ingham Co Kalamazoo Co Kent Co Macomb Co Monroe Co Muskegon Co Oakland Co Ottawa Co Saginaw Co St. Clair Co Washtenaw Co Wayne Co Dakota Co Hennepin Co Mille Lacs Co Olmsted Co Ramsey Co Scott Co

11.59 6.25 10.49 10.13 10.06 15.36 16.63 15.01 13.01 12.82 14.25 11.72 13.30 10.86 13.68 12.29 10.94 12.35 8.09 12.37 13.13 14.38 13.55 13.13 14.99 11.99 14.64 13.14 10.70 13.77 14.39 19.32 9.43 10.29 7.12 10.72 11.91 9.98

10.27 5.37 9.12 8.99 8.71 11.87 13.17 11.15 9.67 9.39 10.38 10.46 11.59 9.02 11.79 10.14 9.34 10.07 7.45 10.29 10.77 11.78 10.95 10.68 11.74 10.06 11.73 10.73 9.06 11.65 11.31 16.60 8.05 8.85 6.18 9.14 10.19 8.48

10.21 5.37 9.12 8.99 8.71 11.86 13.13 11.14 9.67 9.38 10.37 10.45 11.59 9.02 11.77 10.13 9.33 10.06 7.44 10.29 10.76 11.77 10.94 10.67 11.70 10.06 11.72 10.72 9.05 11.64 11.30 16.59 8.05 8.84 6.18 9.13 10.15 8.47

10.20 5.37 9.12 8.99 8.71 11.84 13.09 11.11 9.64 9.37 10.34 10.44 11.58 9.01 11.76 10.10 9.32 10.02 7.44 10.26 10.73 11.72 10.90 10.65 11.65 10.03 11.69 10.69 9.04 11.62 11.27 16.55 8.02 8.80 6.15 9.10 10.11 8.44

10.43 5.39 9.10 8.98 8.73 11.96 13.38 11.19 9.71 9.39 10.36 10.46 11.60 9.12 11.83 10.15 9.34 10.05 7.49 10.23 10.75 11.72 10.84 10.67 11.78 10.03 11.70 10.67 9.07 11.68 11.30 16.59 7.98 8.77 6.13 9.03 10.20 8.40

10.30 5.38 9.10 8.97 8.72 11.94 13.30 11.17 9.69 9.38 10.35 10.45 11.59 9.11 11.79 10.12 9.32 10.03 7.49 10.22 10.73 11.70 10.82 10.65 11.71 10.01 11.68 10.65 9.05 11.66 11.27 16.56 7.97 8.74 6.12 9.01 10.13 8.38

10.30 5.38 9.10 8.97 8.72 11.91 13.22 11.13 9.65 9.35 10.29 10.43 11.58 9.10 11.78 10.06 9.30 9.95 7.48 10.18 10.67 11.60 10.75 10.60 11.60 9.95 11.63 10.58 9.03 11.62 11.21 16.49 7.90 8.67 6.06 8.93 10.03 8.31

34

Minnesota Minnesota Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Montana Montana Montana Montana Montana Montana Montana Montana Montana Montana

St. Louis Co Stearns Co Adams Co Bolivar Co DeSoto Co Forrest Co Hancock Co Harrison Co Hinds Co Jackson Co Jones Co Lauderdale Co Lee Co Lowndes Co Pearl River Co Rankin Co Scott Co Warren Co Cass Co Cedar Co Clay Co Greene Co Jefferson Co Monroe Co St. Charles Co St. Louis city St. Louis Co Ste. Genevieve Co Cascade Co Flathead Co Gallatin Co Lake Co Lincoln Co Missoula Co Rosebud Co Sanders Co Silver Bow Co Yellowstone Co

8.14 9.21 11.20 12.56 12.60 13.37 10.34 11.57 13.38 11.84 14.48 13.16 12.48 13.36 11.70 13.10 11.82 12.26 11.22 11.45 11.73 12.11 14.43 11.03 14.08 15.16 14.02 13.66 5.70 10.01 8.40 9.41 15.85 10.20 6.78 6.48 8.30 7.43

7.30 7.93 9.34 10.74 10.23 11.04 8.33 9.59 11.19 9.75 11.81 10.57 9.98 10.75 9.59 10.94 9.56 10.61 9.33 9.38 9.74 10.08 11.90 8.94 11.43 12.45 11.46 10.94 5.26 9.36 7.96 8.69 14.72 9.39 6.55 6.17 7.61 6.86

7.27 7.92 9.29 10.72 10.22 11.03 8.32 9.53 11.18 9.66 11.80 10.57 9.97 10.74 9.57 10.93 9.55 10.45 9.33 9.37 9.74 10.08 11.88 8.93 11.40 12.38 11.44 10.90 5.26 9.36 7.96 8.69 14.71 9.39 6.55 6.17 7.61 6.86

7.26 7.88 9.28 10.71 10.18 11.00 8.30 9.52 11.14 9.65 11.77 10.54 9.95 10.73 9.55 10.89 9.52 10.44 9.26 9.33 9.67 10.04 11.85 8.88 11.36 12.34 11.41 10.86 5.25 9.32 7.95 8.68 14.55 9.39 6.54 6.16 7.61 6.85

7.36 7.86 9.49 10.79 10.34 11.07 8.42 9.75 11.22 9.97 11.87 10.60 9.99 10.75 9.66 10.97 9.61 10.97 9.31 9.35 9.72 10.04 11.92 8.89 11.46 12.57 11.46 10.98 5.25 9.34 7.94 8.66 14.66 9.38 6.54 6.15 7.59 6.86

7.30 7.85 9.38 10.75 10.32 11.04 8.39 9.62 11.20 9.76 11.84 10.59 9.97 10.74 9.62 10.95 9.59 10.62 9.30 9.33 9.70 10.03 11.88 8.87 11.39 12.42 11.42 10.88 5.25 9.34 7.93 8.66 14.65 9.37 6.54 6.15 7.59 6.86

7.28 7.77 9.37 10.73 10.25 10.99 8.36 9.61 11.14 9.75 11.79 10.54 9.94 10.71 9.58 10.89 9.53 10.60 9.17 9.25 9.57 9.96 11.81 8.78 11.31 12.34 11.35 10.80 5.23 9.25 7.93 8.64 14.34 9.35 6.51 6.14 7.58 6.84

35

Nebraska Nebraska Nebraska Nebraska Nebraska Nebraska Nebraska Nevada Nevada New Hampshire New Hampshire New Hampshire New Hampshire New Hampshire New Hampshire New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New York New York

Cass Co Douglas Co Lancaster Co Lincoln Co Sarpy Co Scotts Bluff Co Washington Co Clark Co Washoe Co Belknap Co Cheshire Co Coos Co Hillsborough Co Rockingham Co Sullivan Co Atlantic Co Bergen Co Camden Co Essex Co Gloucester Co Hudson Co Mercer Co Middlesex Co Morris Co Ocean Co Passaic Co Union Co Warren Co Bernalillo Co Chaves Co Dona Ana Co Grant Co Lea Co San Juan Co Sandoval Co Santa Fe Co Bronx Co Chautauqua Co

10.26 10.55 9.58 7.13 10.07 5.96 9.71 9.51 8.86 7.15 11.68 9.68 10.33 9.49 9.86 11.41 13.65 14.31 13.68 13.68 14.93 13.91 12.46 12.38 11.16 13.09 15.66 13.36 6.55 6.70 11.29 6.13 6.75 6.49 4.98 4.93 15.78 10.71

8.61 8.82 8.06 6.30 8.44 5.41 8.15 8.74 8.32 5.96 10.07 8.78 8.77 8.05 8.44 8.79 10.94 11.12 10.75 10.45 12.48 10.74 9.52 9.52 8.57 10.26 12.40 10.03 6.03 6.17 10.29 5.84 6.13 6.14 4.59 4.59 13.01 8.17

8.61 8.82 8.06 6.30 8.43 5.41 8.15 8.74 8.32 5.96 10.07 8.78 8.77 8.03 8.44 8.78 10.92 11.04 10.72 10.39 12.33 10.72 9.51 9.52 8.57 10.25 12.32 10.03 6.03 6.17 10.29 5.84 6.13 6.14 4.59 4.59 12.98 8.16

8.55 8.78 8.01 6.17 8.38 5.33 8.10 8.73 8.30 5.95 10.07 8.78 8.76 8.02 8.44 8.77 10.91 11.03 10.70 10.38 12.31 10.71 9.50 9.51 8.56 10.23 12.29 10.01 6.02 6.16 10.23 5.84 6.12 6.14 4.58 4.58 12.97 8.14

8.58 8.72 8.01 6.26 8.43 5.38 8.09 8.68 8.26 5.96 10.08 8.77 8.77 8.13 8.45 8.86 11.01 11.33 10.84 10.72 12.88 10.87 9.58 9.59 8.62 10.30 12.68 10.06 6.02 6.17 10.14 5.84 6.12 6.14 4.58 4.60 13.05 8.16

8.58 8.72 8.01 6.26 8.42 5.38 8.09 8.68 8.26 5.96 10.08 8.76 8.76 8.08 8.45 8.84 10.97 11.16 10.77 10.58 12.55 10.83 9.56 9.57 8.61 10.27 12.49 10.04 6.02 6.17 10.14 5.84 6.12 6.14 4.58 4.60 12.99 8.14

8.47 8.62 7.92 6.06 8.32 5.25 7.99 8.66 8.22 5.95 10.07 8.76 8.76 8.08 8.44 8.83 10.94 11.14 10.74 10.56 12.52 10.81 9.55 9.55 8.60 10.25 12.46 10.02 6.01 6.16 10.06 5.83 6.12 6.13 4.57 4.60 12.97 8.10

36

New York New York New York New York New York New York New York New York New York New York New York New York New York New York North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina

Erie Co Essex Co Kings Co Nassau Co New York Co Niagara Co Onondaga Co Orange Co Queens Co Richmond Co St. Lawrence Co Steuben Co Suffolk Co Westchester Co Alamance Co Buncombe Co Cabarrus Co Caswell Co Catawba Co Chatham Co Cumberland Co Davidson Co Duplin Co Durham Co Forsyth Co Gaston Co Guilford Co Haywood Co Jackson Co Lenoir Co McDowell Co Mecklenburg Co Mitchell Co Montgomery Co Onslow Co Orange Co Pitt Co Robeson Co

13.90 6.39 14.65 12.21 17.16 12.03 10.56 11.50 13.23 12.13 8.49 9.83 12.11 12.33 13.93 13.19 14.68 13.43 15.60 12.34 14.17 15.94 12.08 14.09 14.79 14.23 14.27 13.48 12.27 11.57 14.41 15.19 13.56 12.40 11.27 13.24 12.40 12.69

11.07 5.48 12.06 9.86 14.35 9.85 10.13 9.95 10.76 10.80 7.78 7.42 10.05 10.06 10.15 9.95 10.75 9.61 11.52 9.00 10.81 11.96 9.35 10.44 10.96 10.55 10.25 10.58 9.32 8.84 10.72 12.48 10.22 9.08 8.66 9.82 9.85 10.06

11.05 5.47 12.02 9.85 14.34 9.84 10.13 9.94 10.75 10.73 7.77 7.42 10.04 10.05 10.14 9.95 10.74 9.61 11.52 9.00 10.80 11.96 9.34 10.44 10.96 10.55 10.25 10.58 9.32 8.83 10.72 12.48 10.22 9.08 8.66 9.82 9.85 10.06

11.02 5.47 12.01 9.84 14.33 9.83 10.10 9.93 10.75 10.72 7.77 7.42 10.03 10.04 10.13 9.93 10.72 9.60 11.50 8.99 10.79 11.93 9.34 10.43 10.95 10.53 10.24 10.57 9.32 8.83 10.69 12.48 10.19 9.07 8.65 9.81 9.84 10.05

10.98 5.49 12.20 10.00 14.37 9.93 10.11 10.02 10.96 10.97 7.77 7.43 10.65 10.32 10.12 9.90 10.76 9.62 11.47 9.04 10.78 12.01 9.36 10.38 10.92 10.55 10.22 10.57 9.33 8.86 10.71 12.89 10.23 9.09 8.66 9.81 9.88 10.05

10.94 5.49 12.13 9.97 14.33 9.91 10.10 10.01 10.94 10.83 7.76 7.42 10.63 10.29 10.12 9.90 10.75 9.61 11.47 9.03 10.77 12.01 9.35 10.38 10.92 10.55 10.21 10.56 9.33 8.85 10.71 12.89 10.22 9.09 8.65 9.81 9.88 10.05

10.88 5.49 12.11 9.95 14.31 9.89 10.06 9.99 10.93 10.81 7.75 7.41 10.62 10.27 10.10 9.86 10.72 9.59 11.43 9.02 10.74 11.97 9.34 10.36 10.90 10.52 10.19 10.55 9.32 8.84 10.65 12.87 10.17 9.06 8.64 9.80 9.86 10.03

37

North Carolina North Carolina North Carolina North Carolina North Dakota North Dakota North Dakota North Dakota North Dakota North Dakota Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma

Swain Co Wake Co Watauga Co Wayne Co Billings Co Burke Co Burleigh Co Cass Co McKenzie Co Mercer Co Athens Co Butler Co Clark Co Cuyahoga Co Franklin Co Hamilton Co Jefferson Co Lake Co Lawrence Co Lorain Co Lucas Co Mahoning Co Montgomery Co Portage Co Preble Co Scioto Co Stark Co Summit Co Trumbull Co Caddo Co Canadian Co Carter Co Cherokee Co Garfield Co Kay Co Lincoln Co Mayes Co Muskogee Co

12.67 13.96 11.55 13.76 4.57 5.74 6.63 7.78 5.26 6.20 12.31 16.12 14.69 18.36 16.52 17.76 17.48 13.25 15.70 13.60 14.70 15.11 15.73 14.19 13.34 17.11 17.26 16.42 14.96 8.79 8.96 10.10 11.56 9.85 10.64 9.96 11.87 12.05

9.52 10.85 8.30 10.83 4.27 4.36 5.89 6.65 4.82 4.98 8.70 12.68 11.20 14.52 12.50 13.35 13.38 10.49 12.55 10.47 11.51 11.18 12.09 10.72 10.07 13.07 13.16 12.61 11.40 7.30 7.45 8.27 9.66 8.58 9.43 8.34 10.13 10.26

9.52 10.85 8.30 10.83 4.27 4.36 5.89 6.65 4.82 4.98 8.68 12.66 11.18 14.44 12.49 13.32 13.33 10.45 12.48 10.40 11.43 11.16 12.08 10.71 10.06 13.04 13.14 12.60 11.39 7.30 7.45 8.27 9.65 8.58 9.43 8.34 10.12 10.25

9.51 10.84 8.29 10.82 4.23 4.36 5.86 6.61 4.81 4.97 8.67 12.62 11.16 14.39 12.44 13.27 13.31 10.42 12.42 10.36 11.36 11.12 12.05 10.67 10.03 12.97 13.10 12.57 11.36 7.28 7.43 8.25 9.63 8.55 9.40 8.32 10.08 10.21

9.52 10.97 8.28 10.83 4.26 4.34 5.85 6.56 4.81 4.96 8.74 12.68 11.21 14.60 12.41 13.37 13.42 10.54 12.67 10.59 11.51 11.17 12.01 10.74 10.11 13.13 13.11 12.61 11.40 7.31 7.48 8.29 9.66 8.56 9.44 8.37 10.12 10.25

9.51 10.96 8.28 10.83 4.26 4.34 5.85 6.56 4.81 4.96 8.70 12.64 11.18 14.42 12.38 13.30 13.32 10.46 12.52 10.44 11.34 11.13 11.99 10.71 10.08 13.05 13.08 12.59 11.37 7.31 7.48 8.28 9.65 8.56 9.44 8.36 10.11 10.24

9.50 10.95 8.27 10.81 4.20 4.33 5.80 6.48 4.79 4.93 8.67 12.57 11.12 14.34 12.29 13.21 13.28 10.40 12.43 10.37 11.22 11.06 11.94 10.64 10.03 12.95 13.00 12.54 11.31 7.28 7.44 8.24 9.61 8.51 9.38 8.33 10.04 10.17

38

Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oregon Oregon Oregon Oregon Oregon Oregon Oregon Oregon Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Rhode Island

Oklahoma Co Ottawa Co Pittsburg Co Seminole Co Tulsa Co Columbia Co Jackson Co Klamath Co Lane Co Linn Co Multnomah Co Wasco Co Washington Co Adams Co Allegheny Co Beaver Co Berks Co Bucks Co Cambria Co Centre Co Chester Co Cumberland Co Dauphin Co Delaware Co Erie Co Lackawanna Co Lancaster Co Lehigh Co Luzerne Co Mercer Co Montgomery Co Northampton Co Perry Co Philadelphia Co Washington Co Westmoreland Co York Co Kent Co

10.44 11.73 11.37 9.64 11.73 6.29 11.39 10.69 13.28 8.23 8.67 7.53 7.77 13.31 20.99 15.79 16.41 14.10 15.62 12.95 14.80 14.93 15.57 15.31 13.14 12.32 16.95 14.21 12.70 14.00 13.74 14.33 12.83 15.97 15.37 15.38 16.92 8.62

8.49 9.66 9.56 8.04 9.87 5.87 10.68 10.09 12.51 7.90 8.31 7.03 7.39 9.37 16.21 11.97 12.25 11.04 11.47 9.38 10.74 10.88 11.17 11.91 10.18 9.17 12.01 10.68 9.45 10.48 10.36 10.86 9.49 12.73 11.14 10.77 12.53 6.98

8.49 9.66 9.55 8.04 9.86 5.84 10.68 10.09 12.51 7.90 8.24 7.01 7.37 9.36 16.08 11.95 12.24 11.01 11.46 9.37 10.72 10.87 11.16 11.80 10.16 9.16 12.00 10.67 9.45 10.47 10.35 10.85 9.48 12.63 11.11 10.76 12.52 6.98

8.47 9.63 9.51 8.02 9.84 5.83 10.67 10.07 12.44 7.89 8.23 6.98 7.37 9.34 16.03 11.90 12.21 11.00 11.42 9.35 10.70 10.84 11.12 11.78 10.13 9.15 11.96 10.65 9.44 10.44 10.33 10.83 9.42 12.61 11.07 10.72 12.49 6.97

8.42 9.65 9.57 8.06 9.85 5.99 10.67 10.07 12.48 7.90 8.51 7.01 7.44 9.36 16.34 12.00 12.26 11.35 11.47 9.37 10.79 10.83 11.12 12.26 10.18 9.14 11.99 10.66 9.43 10.48 10.55 10.84 9.51 13.00 11.31 10.77 12.51 7.03

8.41 9.64 9.56 8.05 9.84 5.94 10.66 10.06 12.47 7.90 8.36 6.98 7.39 9.35 16.06 11.95 12.23 11.27 11.45 9.36 10.75 10.82 11.10 12.03 10.14 9.13 11.96 10.64 9.42 10.45 10.52 10.82 9.49 12.76 11.24 10.74 12.48 7.03

8.37 9.58 9.49 8.03 9.80 5.91 10.66 10.02 12.29 7.89 8.34 6.90 7.39 9.31 15.98 11.88 12.17 11.25 11.38 9.32 10.70 10.76 11.01 11.99 10.08 9.10 11.89 10.60 9.39 10.40 10.49 10.78 9.40 12.74 11.17 10.68 12.42 7.02

39

Rhode Island South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota South Dakota Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee

Providence Co Beaufort Co Charleston Co Chesterfield Co Edgefield Co Florence Co Georgetown Co Greenville Co Greenwood Co Horry Co Lexington Co Oconee Co Richland Co Spartanburg Co Brookings Co Brookings Co Brown Co Brown Co Jackson Co Jackson Co Meade Co Meade Co Minnehaha Co Minnehaha Co Pennington Co Pennington Co Blount Co Davidson Co Dyer Co Hamilton Co Knox Co Lawrence Co Maury Co McMinn Co Montgomery Co Putnam Co Roane Co Shelby Co

12.60 10.91 11.80 12.37 12.71 12.66 12.75 15.73 13.36 11.22 13.87 10.76 13.86 13.82 9.44 9.44 8.22 8.22 5.44 5.44 6.28 6.28 9.84 9.84 7.55 7.55 14.36 14.44 12.05 16.34 16.67 11.94 12.90 14.85 13.21 13.43 14.31 14.12

10.57 8.52 9.23 9.34 9.57 10.20 10.28 11.94 9.99 8.79 10.62 7.72 10.65 10.30 8.05 8.04 7.17 7.14 5.06 5.06 5.87 5.87 8.12 8.12 7.05 7.05 10.86 11.25 9.77 12.58 12.58 9.12 10.78 10.89 10.40 10.00 10.44 11.68

10.56 8.51 9.22 9.34 9.57 10.20 10.25 11.94 9.99 8.78 10.62 7.71 10.65 10.30 8.05 8.04 7.17 7.14 5.06 5.06 5.87 5.87 8.12 8.12 7.05 7.05 10.86 11.23 9.75 12.56 12.57 9.11 10.78 10.89 10.39 9.99 10.43 11.60

10.56 8.51 9.21 9.33 9.55 10.19 10.24 11.92 9.96 8.78 10.60 7.71 10.63 10.28 8.03 8.02 7.15 7.12 5.04 5.05 5.86 5.87 8.09 8.10 7.04 7.05 10.84 11.21 9.73 12.53 12.53 9.10 10.77 10.86 10.38 9.98 10.38 11.56

10.61 8.54 9.24 9.34 9.57 10.18 10.32 11.89 9.98 8.78 10.57 7.70 10.60 10.29 7.97 7.95 7.10 7.06 5.04 5.05 5.84 5.85 8.02 8.01 7.02 7.03 10.92 11.30 9.80 12.58 12.51 9.14 10.80 10.88 10.43 9.98 10.47 11.84

10.60 8.52 9.22 9.33 9.57 10.17 10.25 11.89 9.97 8.77 10.56 7.70 10.59 10.29 7.97 7.95 7.10 7.06 5.04 5.05 5.84 5.85 8.01 8.01 7.02 7.02 10.90 11.26 9.77 12.55 12.49 9.13 10.79 10.87 10.40 9.97 10.44 11.65

10.59 8.51 9.20 9.31 9.53 10.16 10.24 11.87 9.93 8.76 10.54 7.68 10.56 10.26 7.91 7.91 7.06 7.02 5.02 5.03 5.83 5.84 7.95 7.96 7.01 7.01 10.87 11.22 9.73 12.49 12.43 9.12 10.76 10.81 10.37 9.95 10.36 11.59

40

Tennessee Tennessee Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Utah Utah Utah Utah Utah Vermont Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Washington

Sullivan Co Sumner Co Bowie Co Brewster Co Cameron Co Dallas Co Ector Co Galveston Co Gregg Co Harris Co Harrison Co Hidalgo Co Jefferson Co Montgomery Co Nueces Co Orange Co Potter Co Tarrant Co Box Elder Co Cache Co Salt Lake Co Utah Co Weber Co Chittenden Co Arlington Co Bristol city Charles City Co Chesterfield Co Fairfax Co Hampton city Henrico Co Loudoun Co Norfolk city Page Co Roanoke city Salem city Virginia Beach city Clark Co

14.59 13.58 13.67 4.98 9.88 13.67 7.67 9.79 12.37 14.22 11.46 10.81 11.20 11.23 10.02 11.43 6.17 12.73 9.14 12.82 12.89 10.89 12.81 9.38 14.61 14.51 12.80 13.73 14.15 12.51 13.80 13.63 12.97 12.96 14.36 14.78 12.58 9.74

12.12 10.45 11.60 4.52 8.79 11.35 6.76 7.96 10.36 12.88 9.52 9.67 9.91 9.70 8.54 9.66 5.27 10.63 8.65 11.89 11.81 9.80 11.78 7.96 10.72 10.99 9.33 9.73 10.34 9.82 10.04 9.71 10.56 9.24 10.51 10.93 9.98 8.77

12.12 10.44 11.59 4.52 8.78 11.35 6.76 7.86 10.35 12.51 9.51 9.67 9.73 9.69 8.50 9.64 5.27 10.63 8.64 11.89 11.81 9.80 11.78 7.96 10.72 10.98 9.32 9.72 10.34 9.73 10.03 9.70 10.38 9.24 10.51 10.93 9.96 8.76

12.10 10.42 11.55 4.51 8.78 11.34 6.76 7.86 10.33 12.50 9.49 9.66 9.73 9.68 8.49 9.63 5.25 10.60 8.64 11.88 11.78 9.78 11.76 7.95 10.70 10.96 9.30 9.70 10.32 9.72 9.99 9.68 10.37 9.22 10.41 10.86 9.95 8.75

12.06 10.47 11.59 4.52 8.80 11.43 6.77 8.19 10.40 13.61 9.57 9.65 10.35 9.84 8.73 9.79 5.26 10.65 8.64 11.85 11.63 9.87 11.84 7.91 10.66 10.92 9.35 9.73 10.37 9.96 10.05 9.75 10.84 9.25 10.45 10.90 10.03 8.86

12.05 10.44 11.57 4.52 8.79 11.42 6.77 7.98 10.38 12.81 9.55 9.65 9.97 9.81 8.51 9.75 5.26 10.65 8.64 11.85 11.62 9.86 11.84 7.91 10.65 10.92 9.34 9.72 10.37 9.77 10.04 9.74 10.44 9.25 10.45 10.90 9.98 8.84

12.02 10.41 11.50 4.51 8.78 11.41 6.76 7.98 10.36 12.80 9.52 9.64 9.96 9.80 8.51 9.73 5.23 10.60 8.62 11.83 11.55 9.80 11.78 7.89 10.63 10.88 9.30 9.67 10.34 9.76 9.98 9.70 10.43 9.23 10.30 10.79 9.97 8.82

41

Washington Washington Washington Washington Washington West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wyoming Wyoming Wyoming Wyoming Wyoming

King Co Pierce Co Snohomish Co Spokane Co Yakima Co Berkeley Co Brooke Co Cabell Co Hancock Co Harrison Co Kanawha Co Marion Co Marshall Co Mercer Co Monongalia Co Ohio Co Raleigh Co Summers Co Wood Co Brown Co Dane Co Dodge Co Grant Co Kenosha Co Manitowoc Co Milwaukee Co Outagamie Co Vilas Co Waukesha Co Campbell Co Converse Co Fremont Co Laramie Co Sheridan Co

11.37 10.92 11.20 10.19 10.38 16.23 16.69 16.54 17.30 13.99 17.08 15.32 15.61 12.67 14.81 15.08 13.05 10.10 16.07 11.27 12.36 11.12 11.36 11.50 9.81 13.10 10.70 6.40 13.11 6.30 3.66 9.12 4.95 10.49

10.84 10.66 11.14 9.09 9.08 12.35 12.70 13.07 13.65 10.28 13.32 11.25 11.47 9.20 10.44 11.03 9.55 7.19 11.82 9.91 10.50 9.24 9.45 9.54 8.25 11.08 9.17 5.63 11.01 6.09 3.51 8.38 4.57 9.87

10.72 10.65 11.13 9.09 9.08 12.35 12.65 13.04 13.61 10.28 13.30 11.24 11.42 9.20 10.43 10.98 9.55 7.19 11.77 9.90 10.49 9.23 9.44 9.53 8.25 11.07 9.17 5.62 11.00 6.09 3.51 8.38 4.57 9.87

10.71 10.64 11.12 9.06 9.07 12.31 12.63 13.00 13.59 10.27 13.27 11.23 11.40 9.18 10.42 10.97 9.53 7.17 11.75 9.88 10.46 9.19 9.38 9.49 8.22 11.03 9.14 5.61 10.97 6.07 3.49 8.38 4.53 9.79

11.06 10.72 11.21 9.07 9.06 12.33 12.74 13.33 13.68 10.29 13.37 11.25 11.55 9.26 10.44 11.06 9.55 7.20 11.89 9.87 10.45 9.20 9.38 9.57 8.24 11.10 9.16 5.61 10.99 6.09 3.50 8.37 4.57 9.82

10.82 10.70 11.18 9.07 9.05 12.32 12.64 13.25 13.60 10.28 13.31 11.23 11.43 9.26 10.42 10.97 9.54 7.19 11.79 9.86 10.42 9.18 9.35 9.55 8.22 11.08 9.14 5.60 10.97 6.09 3.50 8.37 4.57 9.82

10.80 10.69 11.16 9.02 9.04 12.25 12.61 13.20 13.56 10.27 13.28 11.21 11.41 9.22 10.40 10.94 9.52 7.16 11.76 9.81 10.35 9.11 9.24 9.47 8.16 10.99 9.08 5.57 10.88 6.04 3.47 8.36 4.49 9.69

42

Appendix B: 8-Hour Ozone Design Values for Locomotive/Marine Scenarios (units are ppb)
State Name
Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Alabama Arizona Arizona Arizona Arizona Arkansas Arkansas California California California California California California California California California California California California California California California

County Name
Baldwin Clay Elmore Etowah Jefferson Lawrence Madison Mobile Montgomery Morgan Shelby Sumter Tuscaloosa Maricopa Pima Pinal Yavapai Crittenden Pulaski Alameda Amador Butte Calaveras Colusa Contra Costa El Dorado Fresno Glenn Imperial Inyo Kern Kings Lake Los Angeles

Baseline DV
78.0 79.3 76.7 75.0 83.7 76.3 79.7 79.0 75.0 82.0 88.0 71.7 75.5 85.7 74.0 82.0 78.7 91.0 81.7 82.7 85.7 88.7 91.0 73.3 79.3 105.0 110.0 72.3 86.0 80.7 114.3 95.7 64.3 121.3

2020 Base
66.1 57.7 55.9 55.2 60.8 56.2 58.8 66.6 55.7 61.8 62.6 52.3 53.3 71.8 64.5 66.5 67.8 70.9 63.1 72.6 71.6 73.1 76.8 61.5 72.9 86.2 96.1 61.2 74.8 71.4 100.9 81.5 56.2 109.0

2020 Marine only
65.8 57.6 55.8 55.1 60.7 56.0 58.6 66.3 55.6 61.6 62.6 52.2 53.2 71.7 64.4 66.4 67.5 70.1 62.8 72.3 71.3 72.9 76.4 61.3 72.7 86.0 95.9 61.1 74.5 71.3 100.8 81.3 56.2 108.8

2020 Locomotive / Marine
65.7 57.3 55.4 54.8 60.3 55.7 58.3 66.2 55.3 61.3 62.1 52.0 52.9 71.6 64.3 66.2 67.3 69.7 62.5 72.1 71.0 72.5 76.1 61.1 72.6 85.6 95.6 60.9 74.3 71.1 100.6 81.1 56.1 108.7

2030 Base
67.0 56.3 53.9 53.8 58.9 54.9 56.9 67.6 54.0 60.6 60.6 51.2 51.8 69.3 63.0 64.6 66.0 70.3 61.3 70.0 67.9 68.7 73.4 58.4 71.1 80.7 92.4 58.3 72.8 69.5 97.6 77.8 54.5 105.5

2030 Marine only
66.3 56.1 53.7 53.6 58.7 54.6 56.4 66.9 53.9 60.1 60.4 50.9 51.5 69.2 63.0 64.5 65.4 68.4 60.7 69.2 67.1 68.3 72.4 58.1 70.4 80.2 92.0 58.0 72.1 69.1 97.4 77.4 54.3 104.7

2030 Locomotive / Marine
65.9 55.3 52.7 52.8 57.5 53.8 55.7 66.5 52.9 59.2 59.1 50.2 50.5 68.6 62.6 63.9 64.9 67.4 59.6 68.8 66.4 67.1 71.6 57.5 70.1 78.9 91.0 57.4 71.5 68.6 96.7 76.8 54.0 104.4

43

California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California California Colorado Colorado Colorado Colorado Colorado Colorado Colorado

Madera Marin Mariposa Mendocino Merced Monterey Napa Nevada Orange Placer Riverside Sacramento San Benito San Bernardino San Diego San Joaquin San Luis Obispo San Mateo Santa Barbara Santa Clara Santa Cruz Shasta Solano Sonoma Stanislaus Sutter Tehama Tulare Tuolumne Ventura Yolo Adams Arapahoe Boulder Denver Douglas El Paso Jefferson

91.0 48.0 89.7 56.7 101.7 66.0 64.7 97.7 85.3 98.3 115.0 99.0 81.0 128.7 92.3 81.0 73.3 56.7 82.7 84.0 65.0 72.3 70.3 62.0 95.0 87.3 84.0 105.7 91.0 94.7 81.7 65.3 78.7 75.3 74.0 83.0 72.3 84.7

79.5 42.1 76.3 47.9 84.9 57.2 53.3 80.4 76.7 80.7 103.1 82.1 69.6 124.7 80.5 71.0 63.1 52.5 72.7 70.1 57.1 60.8 59.9 50.7 81.9 72.2 69.7 88.8 77.3 81.5 68.3 57.7 70.4 63.9 65.4 73.8 63.2 74.2

79.3 42.1 75.9 47.8 84.6 57.1 53.1 80.2 79.2 80.5 103.5 81.9 69.4 125.3 80.2 70.7 63.0 52.5 71.1 70.0 57.0 60.7 59.7 50.6 81.6 72.0 69.6 88.6 76.9 80.9 68.1 57.7 70.4 63.9 65.4 73.8 63.2 74.2

79.0 42.1 75.7 47.7 84.4 57.0 53.0 79.7 79.3 80.2 103.5 81.6 69.3 125.1 80.1 70.5 62.8 52.4 70.9 69.9 56.9 60.4 59.6 50.5 81.5 71.8 69.1 88.4 76.7 80.8 67.9 57.6 70.3 63.7 65.3 73.7 63.0 74.0

76.5 40.8 73.2 45.6 80.6 54.9 50.7 75.8 76.3 75.6 101.9 76.8 66.6 123.0 78.0 68.6 60.5 51.4 70.5 66.4 55.0 57.7 57.8 47.6 78.4 68.3 66.0 84.6 74.0 78.7 64.6 57.1 69.5 62.9 64.7 72.7 62.6 73.2

76.1 40.9 72.2 45.4 79.9 54.6 50.3 75.2 81.5 75.0 102.5 76.2 66.2 123.9 77.2 67.7 60.2 51.2 66.3 66.1 54.8 57.5 57.5 47.5 77.7 67.8 65.8 84.1 73.0 77.0 64.2 57.1 69.4 62.9 64.7 72.7 62.6 73.2

75.3 40.8 71.7 45.0 79.2 54.3 50.0 73.8 81.8 73.9 102.4 75.3 65.8 123.4 76.9 67.3 59.8 51.0 65.9 65.7 54.5 56.6 57.2 47.1 77.1 67.0 64.4 83.4 72.4 76.7 63.6 56.7 69.1 62.4 64.3 72.3 62.1 72.8

44

Colorado Colorado Colorado Colorado Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut Connecticut D.C. Delaware Delaware Delaware Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Florida Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia

La Plata Larimer Montezuma Weld Fairfield Hartford Litchfield Middlesex New Haven New London Tolland Washington Kent New Castle Sussex Bay Brevard Duval Escambia Hillsborough Lake Manatee Miami-Dade Orange Pasco Pinellas Polk Santa Rosa Sarasota Seminole Bibb Chatham Cherokee Clarke Cobb Coweta Dawson De Kalb

59.0 80.3 68.0 76.7 98.3 88.0 86.0 95.7 98.3 90.0 92.3 92.7 88.3 92.7 90.0 79.3 72.7 74.0 81.0 78.7 76.0 76.3 67.0 76.3 76.7 74.7 76.3 81.3 79.7 77.5 88.0 68.3 78.0 78.0 91.0 88.7 80.0 91.0

52.2 67.8 63.0 64.9 81.7 67.9 66.7 75.6 79.1 70.9 70.6 70.5 71.8 72.4 71.9 62.9 52.8 54.3 66.5 67.1 56.3 62.3 54.4 57.6 58.8 62.1 59.8 65.3 62.2 58.3 65.8 54.4 54.7 55.0 64.9 66.3 57.3 68.3

52.2 67.8 62.9 64.9 81.6 67.6 66.3 75.3 78.8 70.6 70.3 70.4 71.3 72.1 71.7 62.7 52.5 53.9 66.4 67.0 56.2 62.1 54.3 57.5 58.6 61.9 59.5 65.2 61.8 58.2 65.7 54.1 54.6 55.0 64.9 66.3 57.3 68.3

52.1 67.6 62.9 64.7 81.5 67.5 66.2 75.2 78.6 70.5 70.1 70.1 71.2 71.9 71.5 62.6 52.5 53.6 66.2 66.9 56.1 62.1 54.3 57.4 58.5 61.9 59.4 65.0 61.7 58.1 65.4 53.9 54.4 54.8 64.7 66.1 57.1 68.0

51.9 66.8 62.6 64.9 81.3 66.8 66.2 74.8 78.4 70.2 69.2 68.9 71.4 71.7 71.1 61.8 51.7 53.4 66.2 66.2 55.4 61.6 53.6 56.6 57.7 61.4 59.0 65.0 61.6 57.2 64.3 53.6 52.0 52.6 61.8 64.4 55.0 65.9

51.8 66.8 62.5 64.9 81.0 66.1 65.4 74.1 77.7 69.6 68.5 68.6 70.6 71.1 70.7 61.4 51.2 52.5 65.8 65.9 55.2 61.0 53.2 56.4 57.3 60.9 58.3 64.6 60.8 56.9 64.2 52.8 51.9 52.4 61.6 64.2 54.9 65.7

51.6 66.3 62.3 64.3 80.7 65.7 65.1 73.8 77.3 69.3 68.1 68.0 70.2 70.5 70.4 60.9 50.9 51.9 65.4 65.7 55.0 60.8 53.1 56.1 57.0 60.7 58.1 64.1 60.6 56.7 63.3 52.3 51.3 51.8 61.0 63.6 54.3 65.0

45

Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Georgia Idaho Idaho Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Illinois Indiana Indiana

Douglas Fayette Fulton Glynn Gwinnett Henry Murray Muscogee Paulding Richmond Rockdale Sumter Ada Canyon Adams Champaign Clark Cook Du Page Effingham Hamilton Jersey Kane Lake Macon Macoupin Madison McHenry McLean Peoria Randolph Rock Island Sangamon St Clair Will Winnebago Allen Boone

91.0 85.3 94.3 72.3 87.7 91.7 85.0 75.0 88.0 84.3 91.0 75.0 76.0 68.0 75.3 75.0 73.0 85.3 71.7 74.7 79.3 87.7 77.0 84.7 75.0 78.0 85.7 82.0 76.0 78.0 77.7 68.7 75.3 83.0 78.3 75.0 87.0 88.0

65.1 63.4 71.8 55.8 62.8 65.9 60.7 54.9 61.4 65.3 65.6 55.2 69.9 59.6 61.4 59.8 54.4 75.0 63.1 58.3 60.6 69.5 65.3 73.7 59.3 58.6 68.0 69.7 59.4 65.2 60.9 56.3 54.8 67.7 63.9 60.2 68.7 69.4

65.0 63.3 71.8 55.5 62.8 65.8 60.6 54.8 61.3 65.2 65.5 55.0 69.9 59.6 61.0 59.6 54.2 75.1 63.0 58.1 60.0 68.9 65.1 73.6 59.1 58.3 67.5 69.5 59.2 65.0 60.5 56.1 54.6 67.3 63.8 60.0 68.5 69.2

64.8 63.1 71.5 55.3 62.6 65.6 60.3 54.6 61.1 65.0 65.3 54.7 69.8 59.5 60.7 59.3 54.0 75.1 62.8 57.9 59.8 68.7 64.7 73.4 58.9 58.1 67.3 69.1 58.9 64.7 60.2 55.8 54.4 67.0 63.4 59.6 68.1 68.9

62.5 60.8 69.2 54.9 59.6 63.2 58.9 53.4 59.2 63.3 62.9 54.0 68.7 58.0 60.8 58.9 53.8 74.3 62.7 57.4 60.2 68.5 64.7 73.2 58.6 57.7 67.0 69.0 58.4 64.3 60.2 55.1 53.6 66.7 63.1 59.0 67.4 68.2

62.3 60.7 69.1 54.3 59.5 63.1 58.7 53.2 59.0 63.1 62.7 53.8 68.6 58.0 59.8 58.5 53.4 74.6 62.4 57.0 58.9 67.1 64.3 73.0 58.1 57.0 65.8 68.7 57.9 63.7 59.3 54.6 53.2 65.5 62.8 58.6 66.9 67.8

61.6 60.0 68.3 53.6 58.9 62.3 57.9 52.4 58.4 62.6 62.0 52.8 68.4 57.8 58.9 57.6 52.9 74.5 61.9 56.3 58.3 66.5 63.2 72.3 57.4 56.3 65.2 67.5 57.1 63.1 58.6 53.8 52.6 64.9 61.8 57.5 65.8 67.1

46

Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Indiana Iowa Iowa Iowa Iowa Iowa Iowa Kansas Kansas Kansas Kansas Kentucky Kentucky Kentucky

Carroll Clark Delaware Elkhart Floyd Gibson Greene Hamilton Hancock Hendricks Huntington Jackson Johnson La Porte Lake Madison Marion Morgan Porter Posey Shelby St Joseph Vanderburgh Vigo Warrick Clinton Harrison Montgomery Polk Scott Story Linn Sedgwick Sumner Wyandotte Bell Boone Boyd

83.0 90.0 85.5 87.0 84.3 73.0 87.0 93.7 91.3 84.7 83.3 83.3 85.3 90.3 88.3 91.7 90.0 85.0 86.3 84.0 91.3 90.3 82.7 85.0 84.0 76.3 75.7 67.0 57.3 77.7 60.7 74.3 79.0 75.7 79.0 82.3 83.7 88.3

64.2 70.3 66.2 69.2 68.1 52.5 63.9 72.0 69.4 66.8 65.7 64.0 66.3 76.1 78.5 69.5 70.7 67.4 76.0 63.5 71.0 72.5 62.0 68.0 65.5 64.2 63.5 57.0 47.5 63.0 49.6 61.3 65.0 63.6 64.2 57.4 64.8 73.1

63.9 69.8 66.0 69.0 67.6 52.2 63.6 71.8 69.2 66.6 65.5 63.6 66.1 76.0 78.6 69.3 70.5 67.2 76.1 62.9 70.8 72.3 61.4 67.8 65.1 63.9 63.4 57.0 47.5 62.7 49.5 61.2 64.9 63.5 64.1 57.3 64.3 72.5

63.6 69.5 65.6 68.6 67.4 52.1 63.3 71.6 69.0 66.4 65.2 63.4 65.9 75.8 78.5 69.1 70.3 67.0 76.0 62.6 70.6 71.8 61.2 67.5 64.9 63.6 63.1 56.7 47.2 62.4 49.3 60.9 64.7 63.3 63.7 57.0 64.1 72.2

63.1 69.7 64.9 68.1 67.5 51.7 63.0 70.4 67.8 65.3 64.5 63.3 65.2 75.4 77.7 67.9 69.2 66.2 75.3 62.7 69.3 71.5 61.1 67.1 64.9 63.4 62.8 56.5 45.7 61.8 47.8 60.6 63.2 62.5 63.0 55.5 64.4 73.3

62.6 68.4 64.4 67.7 66.3 51.2 62.3 69.9 67.2 64.9 64.1 62.4 64.7 75.2 77.9 67.4 68.7 65.8 75.4 61.4 68.8 71.0 59.9 66.7 64.1 62.9 62.6 56.3 45.5 61.2 47.6 60.4 63.1 62.3 62.8 55.3 63.3 72.2

61.8 67.8 63.5 66.6 65.8 50.7 61.6 69.3 66.6 64.2 63.1 61.7 64.1 74.6 77.8 66.7 68.1 65.1 75.2 60.7 68.1 69.8 59.4 65.9 63.6 62.0 61.7 55.4 45.0 60.4 47.0 59.5 62.3 61.5 61.7 54.5 62.7 71.4

47

Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Kentucky Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana

Bullitt Campbell Carter Christian Daviess Edmonson Fayette Graves Greenup Hancock Hardin Henderson Jefferson Jessamine Kenton Livingston McCracken McLean Oldham Perry Pike Pulaski Scott Simpson Trigg Warren Ascension Bossier Caddo Calcasieu East Baton Rouge Iberville Jefferson Lafayette Lafourche Livingston Orleans Ouachita

81.0 90.7 77.0 84.0 75.3 80.3 75.0 79.0 81.3 81.7 78.3 79.3 82.7 76.3 85.0 82.7 79.0 82.0 85.3 75.7 73.3 77.3 68.7 79.7 73.0 82.0 79.3 79.7 77.3 78.7 87.0 84.3 83.0 79.3 78.0 79.7 69.7 77.7

63.3 72.3 59.7 59.1 60.1 60.5 58.6 61.1 67.2 64.9 59.3 61.8 66.4 58.6 67.7 63.2 65.3 60.5 65.0 56.7 56.1 59.9 51.9 57.9 54.6 61.4 70.8 62.2 60.0 68.1 78.1 75.0 72.3 68.1 67.4 70.8 60.2 62.6

62.8 71.8 59.2 58.7 59.6 60.1 58.4 60.7 66.6 64.4 58.8 61.4 66.0 58.4 67.1 62.7 64.9 60.2 64.4 56.5 55.8 59.8 51.6 57.6 53.9 61.1 70.0 62.0 59.7 67.5 77.7 74.1 71.7 67.1 66.6 69.8 59.6 62.2

62.6 71.6 59.0 58.5 59.5 59.9 58.1 60.5 66.3 64.2 58.6 61.2 65.8 58.1 66.9 62.5 64.7 60.0 64.2 56.2 55.6 59.4 51.3 57.4 53.8 60.8 69.9 61.6 59.4 67.3 77.6 74.0 71.5 66.9 66.5 69.7 59.5 62.0

62.5 71.6 60.1 58.7 59.7 59.6 57.1 60.3 67.6 64.6 58.6 61.2 65.7 57.4 67.1 62.8 64.7 59.9 64.5 55.9 55.3 59.0 51.5 56.6 54.4 60.5 70.9 60.9 58.9 68.1 77.9 75.1 72.4 68.6 67.5 70.9 60.3 61.8

61.5 70.5 59.1 57.8 58.7 58.9 56.6 59.3 66.6 63.5 57.6 60.4 64.7 56.9 65.9 61.6 63.8 59.1 63.2 55.5 54.9 58.6 50.7 56.1 52.8 59.8 69.1 60.4 58.3 66.9 77.1 73.2 71.0 66.4 65.9 69.0 59.0 60.9

60.9 69.7 58.3 57.2 58.3 58.2 55.8 58.7 65.8 63.0 57.1 59.9 64.2 56.1 65.1 61.0 63.4 58.6 62.5 54.7 54.1 57.7 49.9 55.4 52.3 59.1 68.8 59.5 57.4 66.4 76.8 72.9 70.6 66.0 65.5 68.6 58.7 60.2

48

Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Louisiana Maine Maine Maine Maine Maine Maine Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Maryland Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Massachusetts Michigan Michigan Michigan Michigan

Pointe Coupee St Bernard St Charles St James St John The Baptist St Mary West Baton Rouge Cumberland Hancock Kennebec Knox Sagadahoc York Anne Arundel Baltimore Carroll Cecil Charles Frederick Harford Kent Montgomery Prince Georges Washington Barnstable Berkshire Bristol Essex Hampden Hampshire Middlesex Norfolk Suffolk Worcester Allegan Benzie Berrien Cass

73.3 78.0 78.7 74.0 78.7 74.7 84.0 84.3 91.7 78.0 83.7 79.0 88.3 98.3 91.3 88.7 97.7 93.0 87.3 100.3 95.3 86.7 94.0 85.3 92.0 87.0 91.0 90.0 92.0 86.7 85.7 91.0 88.7 85.5 94.0 85.7 88.0 90.7

65.1 65.9 69.3 65.4 69.9 63.9 75.6 65.2 73.1 61.6 65.0 61.2 68.5 74.1 72.4 66.8 73.2 66.7 67.2 78.9 71.7 65.8 71.0 65.4 73.8 70.3 71.9 72.8 70.3 68.1 66.5 76.2 71.6 66.9 77.2 69.7 74.0 71.7

64.6 65.3 68.5 65.2 69.6 62.6 74.9 65.0 72.8 61.4 64.8 61.1 68.3 74.0 72.3 66.6 73.0 66.5 67.0 78.7 71.5 65.7 70.9 65.2 73.4 70.1 71.7 72.7 70.1 67.9 66.3 76.2 71.5 66.6 77.0 69.5 73.9 71.5

64.5 65.1 68.4 65.1 69.5 62.5 74.8 64.9 72.6 61.3 64.6 60.9 68.1 73.7 72.1 66.3 72.7 66.3 66.8 78.5 71.2 65.5 70.7 64.9 73.2 70.0 71.5 72.5 69.9 67.8 66.1 76.1 71.4 66.5 76.5 69.2 73.6 71.0

65.0 65.8 69.5 65.2 69.4 64.5 75.6 64.2 72.2 60.6 64.1 60.4 67.5 72.8 71.6 65.5 72.1 65.2 66.1 78.0 70.6 64.6 69.4 64.1 73.4 69.1 71.5 72.0 69.0 67.0 65.2 75.4 70.9 65.9 76.4 68.9 73.4 70.5

64.1 64.6 68.1 64.6 69.1 61.8 74.0 63.8 71.6 60.2 63.7 60.0 67.0 72.5 71.3 65.1 71.7 64.9 65.6 77.6 70.2 64.3 69.1 63.6 72.6 68.7 70.8 71.7 68.4 66.5 64.8 75.3 70.8 65.3 75.9 68.5 73.1 70.0

63.8 64.2 67.7 64.3 68.8 61.4 73.7 63.3 71.1 59.8 63.2 59.6 66.5 71.9 70.7 64.4 70.9 64.2 64.9 77.0 69.5 63.6 68.4 62.8 72.2 68.1 70.4 71.4 68.0 66.1 64.2 74.9 70.4 64.9 74.5 67.5 72.4 68.7

49

Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Michigan Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Mississippi Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri Missouri

Clinton Genesee Huron Ingham Kalamazoo Kent Lenawee Macomb Mason Missaukee Muskegon Oakland Ottawa Schoolcraft St Clair Washtenaw Wayne Adams De Soto Hancock Harrison Hinds Jackson Lauderdale Lee Madison Warren Cass Cedar Clay Greene Jefferson Monroe Platte St Charles St Louis St Louis City Ste Genevieve

82.7 86.3 83.0 82.3 82.7 84.7 85.0 92.3 86.0 78.3 90.0 87.7 86.0 77.0 88.0 87.3 86.0 77.7 83.3 81.0 80.3 72.7 80.0 73.3 78.3 74.3 73.7 77.7 79.7 83.7 74.5 84.7 76.7 80.3 90.0 88.3 87.7 82.7

66.7 68.5 70.8 65.9 65.1 67.4 69.4 76.6 68.9 64.0 73.4 74.2 69.3 65.0 72.5 71.4 72.9 63.1 64.0 66.1 65.1 52.1 68.6 52.3 57.4 55.2 54.9 61.9 64.8 66.7 59.8 68.9 61.9 65.0 73.0 72.6 72.9 66.8

66.5 68.3 70.7 65.8 64.9 67.2 69.2 76.5 68.7 63.8 73.2 74.1 69.1 64.9 72.3 71.3 72.8 61.9 63.6 65.4 64.4 51.8 68.3 52.1 57.1 54.9 53.6 61.8 64.6 66.5 59.6 68.4 61.6 64.9 72.6 72.1 72.4 66.4

66.2 68.0 70.5 65.5 64.5 66.9 69.0 76.3 68.3 63.5 72.7 73.9 68.7 64.6 72.1 71.1 72.6 61.7 63.2 65.1 64.2 51.4 68.1 51.8 56.8 54.5 53.4 61.5 64.2 66.0 59.3 68.2 61.3 64.5 72.4 71.8 72.2 66.1

65.5 67.1 70.3 64.8 63.9 66.2 68.6 75.6 67.8 63.1 72.5 73.3 68.3 64.5 71.5 70.5 71.9 63.2 62.8 65.7 65.0 50.1 68.5 50.9 56.2 53.7 54.9 60.9 63.7 65.0 58.6 67.6 61.2 64.0 71.6 71.3 71.8 66.0

65.2 66.8 70.0 64.4 63.5 65.8 68.2 75.4 67.4 62.7 72.0 73.1 67.8 64.1 71.2 70.2 71.7 60.8 61.8 64.1 63.5 49.5 67.9 50.6 55.6 53.1 52.4 60.7 63.4 64.6 58.2 66.4 60.5 63.7 70.5 70.0 70.5 65.1

64.3 65.9 69.6 63.5 62.4 64.8 67.4 74.8 66.1 61.9 70.7 72.6 66.7 63.3 70.6 69.5 71.2 60.2 60.8 63.5 62.9 48.3 67.5 49.8 54.7 51.9 51.7 59.7 62.3 63.3 57.4 65.8 59.5 62.6 69.9 69.4 69.9 64.4

50

Nebraska Nebraska Nevada Nevada Nevada New Hampshire New Hampshire New Hampshire New Hampshire New Hampshire New Hampshire New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Jersey New Mexico New Mexico New Mexico New Mexico New Mexico New York New York New York New York New York New York New York New York

Douglas Lancaster Clark Douglas Washoe Belknap Cheshire Hillsborough Merrimack Rockingham Strafford Atlantic Bergen Camden Cumberland Essex Gloucester Hudson Hunterdon Mercer Middlesex Monmouth Morris Ocean Passaic Bernalillo Dona Ana San Juan Sandoval Valencia Albany Bronx Chautauqua Chemung Dutchess Erie Essex Herkimer

67.3 55.0 84.7 69.0 73.3 76.5 74.3 85.3 74.7 83.5 78.5 88.0 91.3 99.7 94.0 67.0 98.0 84.0 94.7 97.7 96.0 95.3 95.3 105.7 86.7 76.3 78.3 74.3 74.0 67.5 83.0 82.7 93.0 80.3 92.0 95.7 89.0 74.0

57.3 46.6 74.9 61.1 65.0 61.5 58.4 66.7 59.1 65.9 61.1 69.9 76.2 79.6 73.7 54.1 77.9 67.7 73.6 78.2 75.4 75.6 73.2 82.1 69.2 66.4 70.2 70.4 64.9 58.0 66.2 71.1 75.4 63.1 71.0 77.7 70.6 60.3

57.2 46.5 74.8 61.0 65.0 61.4 58.2 66.5 58.9 65.7 60.9 69.3 76.0 79.1 73.2 54.1 77.6 67.8 73.1 77.7 75.0 75.3 72.9 81.5 69.0 66.3 70.2 70.4 64.8 58.0 66.0 71.1 75.0 63.0 70.7 77.3 70.4 60.1

57.0 46.3 74.6 60.9 64.9 61.2 58.1 66.3 58.8 65.5 60.8 69.2 75.9 78.9 73.0 54.0 77.4 67.7 73.0 77.5 74.9 75.1 72.7 81.3 68.9 66.1 70.0 70.3 64.6 57.7 65.8 70.9 74.7 62.7 70.5 77.0 70.2 59.9

56.6 45.8 74.0 59.4 63.6 60.4 57.6 65.6 58.2 65.2 60.2 69.5 75.5 78.9 73.3 53.5 77.4 66.9 72.5 77.5 74.4 75.0 72.2 81.1 68.3 64.5 66.8 70.0 63.1 56.6 64.9 70.7 75.0 61.9 70.4 77.1 69.6 59.4

56.4 45.6 73.8 59.2 63.5 60.2 57.1 65.1 57.8 64.7 59.8 68.3 75.3 77.9 72.2 53.4 76.7 67.1 71.5 76.2 73.5 74.2 71.3 79.8 67.8 64.4 66.8 70.0 63.0 56.5 64.4 70.6 74.1 61.6 69.5 76.3 69.2 59.1

55.7 45.0 73.3 58.8 63.1 59.8 56.8 64.7 57.3 64.3 59.4 68.0 74.9 77.4 71.7 53.1 76.1 66.7 71.1 75.8 73.1 73.8 70.8 79.3 67.3 63.7 66.2 69.7 62.3 55.7 63.8 70.2 73.2 60.9 69.1 75.5 68.6 58.6

51

New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York New York North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina

Jefferson Madison Monroe Niagara Oneida Onondaga Orange Oswego Putnam Queens Rensselaer Richmond Saratoga Schenectady Suffolk Ulster Wayne Westchester Alexander Avery Buncombe Caldwell Caswell Chatham Cumberland Davie Duplin Durham Edgecombe Forsyth Franklin Granville Guilford Haywood Jackson Johnston Lenoir Lincoln

91.3 79.7 84.0 91.7 79.7 84.0 84.7 68.0 91.3 84.5 86.0 93.0 87.0 77.7 97.0 81.3 84.0 91.3 87.0 77.7 80.0 83.3 87.7 81.3 86.0 91.3 80.0 88.7 87.3 91.3 89.7 92.3 88.7 84.7 86.0 84.3 80.0 90.7

74.9 63.7 68.8 77.2 64.5 68.8 65.6 55.1 73.4 71.6 68.4 75.3 68.8 62.8 82.0 65.2 67.5 76.3 63.2 60.1 61.6 61.8 62.0 59.9 63.1 65.5 60.6 62.8 64.6 64.8 64.7 65.8 61.3 65.8 64.9 61.4 61.2 65.7

74.7 63.6 68.7 77.0 64.3 68.7 65.3 55.0 73.1 71.5 68.2 75.4 68.6 62.6 82.1 65.0 67.3 76.1 63.1 60.0 61.5 61.7 61.9 59.8 63.0 65.4 60.5 62.7 64.5 64.7 64.6 65.7 61.2 65.7 64.8 61.3 61.1 65.6

74.5 63.3 68.5 76.8 64.1 68.5 65.2 54.8 72.9 71.4 68.0 75.2 68.4 62.4 82.0 64.8 67.1 76.0 62.9 59.8 61.3 61.4 61.7 59.6 62.7 65.2 60.3 62.5 64.3 64.5 64.3 65.5 61.0 65.5 64.5 61.1 60.9 65.4

74.3 62.5 67.5 76.8 63.6 67.9 64.5 54.4 72.9 71.1 67.0 74.1 67.4 61.2 81.4 64.2 66.3 75.7 61.5 58.8 59.9 60.2 60.1 58.5 61.1 63.7 59.2 60.6 62.7 62.7 62.2 64.2 58.7 64.5 63.6 59.1 59.8 63.8

73.9 62.3 67.3 76.4 63.2 67.6 63.9 54.1 72.1 70.8 66.5 74.2 66.8 60.8 81.6 63.8 66.0 75.3 61.3 58.6 59.8 59.9 59.9 58.3 60.9 63.5 59.0 60.4 62.5 62.6 62.0 63.9 58.5 64.2 63.3 58.9 59.5 63.6

73.3 61.6 66.7 75.9 62.6 67.0 63.4 53.6 71.7 70.4 65.8 73.8 66.1 60.2 81.3 63.3 65.4 74.9 60.8 57.9 59.3 59.3 59.3 57.7 60.1 62.9 58.3 59.8 61.8 62.1 61.4 63.3 57.9 63.6 62.5 58.3 58.9 63.1

52

North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina North Carolina Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio Ohio

Martin Mecklenburg New Hanover Northampton Person Pitt Randolph Rockingham Rowan Swain Union Wake Yancey Allen Ashtabula Butler Clark Clermont Clinton Cuyahoga Delaware Franklin Geauga Greene Hamilton Jefferson Knox Lake Lawrence Licking Lorain Lucas Madison Mahoning Medina Miami Montgomery Portage

81.0 97.3 77.3 84.0 89.3 82.0 83.5 88.3 97.3 73.0 87.0 92.5 83.0 88.0 95.7 89.7 88.3 89.3 94.3 88.0 89.0 93.0 99.0 87.7 90.3 84.3 87.0 92.7 81.7 88.0 87.0 90.0 88.7 87.0 87.0 87.0 86.5 91.0

61.3 73.0 58.0 63.2 64.0 60.5 58.9 63.0 70.1 54.6 63.5 65.8 64.1 69.7 78.9 70.1 68.1 70.8 71.4 70.4 68.4 70.8 79.5 68.0 71.3 65.0 66.5 75.3 67.5 67.2 69.8 72.8 67.2 67.1 69.7 66.5 67.5 71.1

61.2 72.9 57.7 63.1 63.9 60.4 58.8 62.9 70.0 54.5 63.4 65.7 64.0 69.4 78.6 69.6 67.9 70.3 71.0 70.3 68.2 70.5 79.2 67.6 70.8 64.7 66.3 75.2 66.9 67.0 69.8 72.8 66.9 66.8 69.5 66.2 67.3 70.7

61.0 72.7 57.5 62.9 63.8 60.2 58.6 62.7 69.8 54.2 63.2 65.5 63.8 69.2 78.3 69.3 67.6 70.1 70.6 70.1 67.9 70.2 78.9 67.3 70.5 64.5 66.0 75.0 66.6 66.7 69.6 72.5 66.7 66.5 69.2 66.0 67.0 70.4

60.0 70.8 56.9 62.0 63.1 58.6 56.7 61.6 67.8 53.4 61.1 62.9 62.5 68.7 78.6 69.2 67.4 70.0 70.4 70.1 67.0 69.0 78.6 67.2 70.3 64.5 65.1 75.0 68.0 65.7 69.3 71.9 66.3 66.0 69.3 65.2 66.4 70.0

59.7 70.6 56.2 61.6 62.8 58.4 56.5 61.5 67.7 53.1 61.0 62.7 62.2 68.2 77.9 68.1 66.7 69.0 69.4 69.8 66.5 68.5 77.9 66.4 69.3 63.8 64.7 74.7 66.9 65.2 69.2 71.8 65.6 65.4 68.7 64.7 65.8 69.2

59.1 70.1 55.7 61.0 62.4 57.7 55.9 60.9 66.9 52.5 60.3 62.1 61.6 67.4 77.1 67.3 66.0 68.2 68.5 69.2 65.6 67.5 77.0 65.6 68.4 63.3 63.8 74.1 66.1 64.3 68.7 71.1 64.9 64.5 68.0 63.9 65.0 68.3

53

Ohio Ohio Ohio Ohio Ohio Ohio Ohio Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Oklahoma Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania

Preble Stark Summit Trumbull Warren Washington Wood Canadian Cleveland Comanche Dewey Kay Mc Clain Oklahoma Ottawa Pittsburg Tulsa Adams Allegheny Armstrong Beaver Berks Blair Bucks Cambria Centre Chester Clearfield Dauphin Delaware Erie Franklin Greene Lackawanna Lancaster Lawrence Lehigh Luzerne

80.0 88.3 93.3 92.0 90.7 85.7 87.7 76.0 75.3 77.3 71.0 75.0 77.0 80.3 78.0 73.0 83.0 80.0 91.3 90.7 91.3 88.7 83.3 99.0 85.0 84.7 95.0 87.3 86.7 91.7 89.0 90.7 87.7 83.3 91.0 78.3 90.7 83.7

62.0 67.8 73.6 70.8 70.3 63.2 70.4 58.1 61.3 62.4 59.3 61.6 63.0 62.4 63.5 61.6 67.7 61.0 73.9 70.3 72.8 67.4 62.3 80.7 65.1 63.7 72.9 66.7 66.6 72.7 73.2 68.8 65.5 63.3 69.2 59.2 68.6 63.5

61.7 67.6 73.4 70.5 70.0 62.7 70.1 58.0 61.1 62.2 59.1 61.5 62.8 62.3 63.4 61.4 67.6 60.7 73.6 69.6 72.5 67.2 62.0 80.1 64.8 63.5 72.7 66.3 66.4 72.4 72.7 68.5 65.0 63.2 69.1 59.0 68.4 63.4

61.5 67.3 73.1 70.2 69.7 62.5 69.7 57.8 60.9 62.0 59.0 61.2 62.6 62.1 63.1 61.1 67.4 60.5 73.3 69.4 72.3 67.0 61.8 80.0 64.5 63.2 72.5 66.1 66.2 72.2 72.5 68.2 64.8 63.0 68.8 58.7 68.2 63.2

61.1 66.5 72.7 69.7 69.3 63.1 69.5 56.0 60.3 61.7 58.9 61.0 62.2 59.8 62.7 61.0 65.6 59.9 73.3 69.8 72.1 66.2 61.5 80.1 64.4 62.7 71.9 66.0 65.4 72.2 72.9 67.3 65.2 62.0 68.0 58.3 67.3 62.3

60.6 66.0 72.1 69.0 68.5 61.8 68.9 55.7 59.9 61.4 58.5 60.8 61.8 59.6 62.4 60.5 65.4 59.5 72.4 68.4 71.5 65.8 60.9 78.9 63.7 62.2 71.4 65.2 65.1 71.6 72.0 66.8 64.2 61.6 67.6 57.8 66.8 61.9

59.9 65.2 71.2 68.0 67.7 61.3 67.8 55.1 59.4 60.8 58.1 60.1 61.3 58.9 61.5 59.7 64.8 58.8 71.8 67.8 71.0 65.1 60.1 78.4 63.0 61.4 70.6 64.6 64.4 71.1 71.2 66.0 63.7 61.1 66.8 57.0 66.3 61.3

54

Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Pennsylvania Rhode Island Rhode Island Rhode Island South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina South Carolina Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee

Lycoming Mercer Montgomery Northampton Perry Philadelphia Tioga Washington Westmoreland York Kent Providence Washington Abbeville Aiken Anderson Barnwell Berkeley Charleston Cherokee Chester Chesterfield Colleton Darlington Edgefield Oconee Pickens Richland Spartanburg Union Williamsburg York Anderson Blount Davidson Hamilton Haywood Jefferson

82.0 91.3 92.3 90.0 83.3 96.7 85.0 86.3 88.0 89.0 93.0 92.0 92.7 82.3 82.7 85.3 79.3 71.5 72.5 83.7 82.7 80.0 77.7 82.7 79.7 83.7 83.0 89.3 87.0 79.7 71.7 83.0 87.0 92.3 77.7 88.3 83.5 91.0

62.7 70.1 73.4 68.2 63.1 79.7 66.4 68.2 70.9 68.5 72.6 72.0 73.7 61.5 62.7 64.8 60.0 54.5 56.3 62.2 60.6 60.1 59.4 62.5 60.3 61.8 61.0 67.8 63.7 59.9 53.4 60.8 60.2 66.6 58.2 63.7 61.5 63.4

62.5 69.7 73.1 68.0 63.0 79.2 66.2 68.0 70.3 68.4 72.2 71.5 73.2 61.4 62.6 64.8 59.9 54.1 55.9 62.2 60.5 60.0 59.3 62.4 60.2 61.7 61.0 67.7 63.7 59.8 53.3 60.8 60.0 66.4 57.9 63.5 61.2 63.3

62.3 69.4 72.9 67.8 62.7 79.0 66.0 67.8 70.1 68.1 72.0 71.4 73.1 61.2 62.3 64.6 59.6 53.9 55.7 62.0 60.3 59.7 59.1 62.2 60.0 61.5 60.8 67.5 63.4 59.6 53.1 60.6 59.7 66.1 57.6 63.1 61.0 63.0

61.7 69.0 72.7 66.8 62.0 79.2 65.4 67.7 70.3 67.4 72.1 71.4 73.3 59.6 60.9 62.3 58.4 53.6 55.5 60.6 58.9 58.6 58.2 61.0 58.7 59.8 58.9 65.3 61.4 58.1 52.3 59.1 57.6 64.4 56.7 61.3 60.4 60.2

61.3 68.3 72.1 66.2 61.6 78.0 65.0 67.1 69.1 67.0 71.0 70.4 72.2 59.4 60.7 62.2 58.2 52.8 54.6 60.4 58.7 58.4 57.9 60.8 58.5 59.6 58.7 65.1 61.3 57.9 52.0 58.9 57.3 64.0 56.1 60.9 59.8 59.9

60.7 67.3 71.6 65.7 60.8 77.6 64.4 66.5 68.5 66.3 70.7 70.0 71.8 58.7 60.1 61.6 57.5 52.2 54.0 59.8 58.2 57.7 57.3 60.1 57.9 59.1 58.1 64.4 60.6 57.3 51.4 58.4 56.4 63.0 55.4 59.6 59.1 59.0

55

Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Tennessee Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Texas Utah Utah

Knox Lawrence Meigs Putnam Rutherford Sevier Shelby Sullivan Sumner Williamson Wilson Bexar Brazoria Collin Dallas Denton El Paso Ellis Galveston Gregg Harris Harrison Hood Jefferson Johnson Kaufman Montgomery Nueces Orange Parker Rockwall Smith Tarrant Travis Victoria Webb Box Elder Cache

92.0 77.0 89.0 84.0 80.7 92.3 87.7 86.7 85.7 84.3 82.0 88.7 94.0 90.0 90.0 97.3 79.3 85.0 89.7 84.3 102.0 78.5 83.0 91.0 89.7 72.0 88.3 80.3 81.0 87.0 82.0 82.0 98.7 84.7 77.7 64.7 77.5 69.3

63.4 57.8 62.8 63.1 59.5 68.0 68.3 67.3 63.5 62.1 61.6 70.6 80.2 71.4 70.5 76.2 70.5 64.4 76.6 69.0 92.4 62.8 59.6 78.6 67.3 56.0 77.3 68.9 69.6 64.8 63.2 65.1 77.0 65.7 65.1 55.3 67.0 58.7

63.3 57.6 62.7 63.0 59.3 67.8 67.5 67.3 63.3 61.8 61.4 70.4 79.1 71.2 70.4 76.1 70.5 64.3 76.6 68.8 92.4 62.5 59.5 77.4 67.2 55.9 76.7 68.0 68.6 64.7 63.1 64.9 76.9 65.4 64.4 54.8 67.0 58.7

62.9 57.3 62.3 62.8 59.1 67.5 67.2 67.0 63.0 61.6 61.2 70.1 78.9 71.0 70.2 75.9 70.3 64.1 76.4 68.6 92.3 62.3 59.2 77.2 67.0 55.6 76.6 67.8 68.4 64.5 62.9 64.7 76.7 65.2 64.2 54.7 66.7 58.4

59.9 56.9 60.8 61.9 58.1 66.3 67.6 66.0 61.9 60.5 60.2 69.4 80.6 70.3 69.7 75.4 67.3 63.3 76.6 68.2 92.1 62.1 58.1 79.0 66.0 55.3 77.3 69.2 69.8 63.6 62.2 64.2 76.2 64.5 65.0 55.2 66.2 57.5

59.6 56.3 60.5 61.6 57.6 65.9 65.8 65.8 61.3 59.9 59.8 68.9 78.1 70.0 69.4 75.1 67.2 63.1 76.0 67.8 92.0 61.5 57.8 76.5 65.7 55.0 76.0 67.2 67.7 63.4 61.9 63.8 75.9 63.9 63.5 54.1 66.1 57.4

58.5 55.6 59.5 60.9 56.9 65.0 64.9 65.1 60.6 59.2 59.1 68.3 77.7 69.4 68.8 74.5 66.5 62.5 75.5 67.2 91.6 60.8 57.1 76.0 65.1 54.4 75.7 66.7 67.2 62.8 61.3 63.0 75.4 63.3 63.0 53.8 65.2 56.7

56

Utah Utah Utah Utah Vermont Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia West Virginia Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin

Davis Salt Lake Utah Weber Bennington Alexandria City Arlington Caroline Charles City Chesterfield Fairfax Fauquier Frederick Hampton City Hanover Henrico Loudoun Madison Page Prince William Roanoke Rockbridge Stafford Suffolk City Berkeley Cabell Hancock Kanawha Monongalia Ohio Wood Brown Columbia Dane Dodge Door Fond Du Lac Jefferson

81.0 79.7 77.7 79.3 79.3 90.0 96.7 82.3 89.3 84.7 96.7 79.3 82.7 88.3 92.0 88.3 90.0 84.7 79.7 85.0 83.7 76.7 86.0 87.0 83.0 85.7 84.7 84.0 78.7 83.3 85.7 80.3 76.3 76.0 79.3 91.0 77.3 80.0

72.8 72.8 69.3 68.1 62.5 68.1 74.2 60.7 70.2 67.6 73.2 59.7 63.3 72.9 71.2 68.9 68.5 64.2 59.3 64.9 63.2 58.0 64.8 72.0 63.7 70.9 65.5 63.6 56.7 64.6 63.9 67.9 62.1 62.6 65.7 75.0 63.7 65.0

72.8 72.7 69.3 68.1 62.3 68.0 74.1 60.6 70.1 67.5 73.1 59.5 63.1 72.7 71.1 68.8 68.3 64.1 59.1 64.7 63.1 57.9 64.7 71.8 63.5 70.5 65.3 63.2 56.5 64.2 63.3 67.8 61.9 62.5 65.5 74.8 63.6 64.9

72.6 72.4 69.0 67.8 62.1 67.8 73.8 60.3 69.9 67.4 72.8 59.3 62.8 72.5 70.9 68.6 68.1 63.9 58.9 64.5 62.8 57.7 64.2 71.6 63.2 70.3 65.1 63.0 56.4 64.1 63.1 67.5 61.7 62.2 65.3 74.4 63.4 64.6

71.7 72.2 68.3 66.8 61.1 66.7 72.6 59.5 69.1 66.7 71.6 58.8 62.2 72.4 70.0 67.7 67.4 63.2 58.3 63.8 61.6 57.0 63.5 71.7 62.5 71.7 65.0 63.1 56.2 64.3 63.8 67.4 61.1 61.6 65.1 74.4 63.0 64.1

71.6 72.1 68.3 66.7 60.7 66.5 72.3 59.2 68.9 66.4 71.4 58.4 61.7 72.0 69.7 67.4 67.0 62.9 57.9 63.4 61.3 56.7 63.3 71.3 62.0 71.1 64.4 62.4 55.8 63.5 62.5 67.1 60.7 61.2 64.7 74.0 62.8 63.7

70.9 71.2 67.7 65.9 60.0 65.8 71.6 58.5 68.4 66.0 70.7 57.7 61.0 71.6 69.2 67.0 66.3 62.4 57.5 62.6 60.5 56.1 62.1 70.8 61.2 70.4 63.9 61.8 55.3 63.0 62.0 66.4 60.0 60.5 64.0 72.9 62.1 62.9

57

Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin Wisconsin

Kenosha Kewaunee Manitowoc Milwaukee Ozaukee Racine Rock Sauk Sheboygan St Croix Walworth Washington Waukesha

98.3 89.3 87.0 91.0 93.0 91.7 81.7 72.0 97.0 71.3 81.3 80.3 79.0

85.0 74.3 72.2 77.2 78.0 78.0 66.1 59.4 81.1 61.2 66.3 67.4 66.0

84.9 74.1 72.0 77.1 77.9 77.9 65.9 59.3 80.9 61.1 66.2 67.2 65.9

84.7 73.8 71.6 76.8 77.5 77.7 65.5 59.0 80.5 61.0 65.8 67.0 65.6

84.4 73.9 71.6 76.6 77.3 77.4 64.7 58.6 80.4 60.7 65.4 66.9 65.5

84.2 73.4 71.2 76.3 77.0 77.1 64.2 58.3 79.9 60.5 65.0 66.5 65.1

83.4 72.3 70.2 75.4 75.9 76.4 63.1 57.6 78.7 60.0 64.1 65.9 64.4

58

Appendix C: Visibility Levels on 20% Worst Days for Locomotive/Marine Scenario (units are deciviews)
Baseline Visibility 29.03 26.36 26.27 13.43 13.43 13.43 11.66 13.35 13.21 13.35 14.83 13.67 15.25 23.50 14.15 19.94 12.63 19.43 17.63 12.87 19.62 14.15 15.05 12.63 18.46 22.81 18.45 19.94 22.17 22.17 15.05 2020 Locomotive / Marine 23.73 22.05 22.35 13.09 13.09 13.07 11.09 12.72 12.83 12.58 14.47 13.20 14.94 21.14 13.60 17.36 12.13 18.34 17.21 12.72 17.93 13.54 14.42 12.30 17.36 21.99 17.86 17.25 20.22 19.87 14.59 2030 Locomotive / Marine 23.66 21.92 22.19 13.09 13.09 13.09 11.08 12.73 12.75 12.54 14.44 13.15 14.93 20.94 13.51 17.10 12.12 18.11 17.19 12.74 17.71 13.43 14.32 12.31 17.09 21.79 17.79 16.93 19.70 19.55 14.52 Natural Background 10.99 11.58 11.57 7.21 7.21 7.21 7.14 6.68 6.49 6.68 6.46 6.59 6.69 7.64 7.31 7.06 6.12 7.46 7.64 7.91 7.19 7.31 7.86 6.12 7.99 15.77 13.91 7.06 7.30 7.30 7.86

Class 1 Area

State

2020 Base

2030 Base

Sipsey Wilderness Caney Creek Wilderness Upper Buffalo Wilderness Chiricahua NM Chiricahua Wilderness Galiuro Wilderness Grand Canyon NP Mazatzal Wilderness Petrified Forest NP Pine Mountain Wilderness Saguaro NM Sierra Ancha Wilderness Sycamore Canyon Wilderness Agua Tibia Wilderness Caribou Wilderness Cucamonga Wilderness Desolation Wilderness Dome Land Wilderness Emigrant Wilderness Hoover Wilderness Joshua Tree NM Lassen Volcanic NP Lava Beds NM Mokelumne Wilderness Pinnacles NM Point Reyes NS Redwood NP San Gabriel Wilderness San Gorgonio Wilderness San Jacinto Wilderness South Warner Wilderness

AL AR AR AZ AZ AZ AZ AZ AZ AZ AZ AZ AZ CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA CA

23.78 22.11 22.41 13.09 13.09 13.08 11.13 12.74 12.90 12.59 14.50 13.22 14.96 21.23 13.62 17.42 12.15 18.37 17.22 12.73 17.95 13.56 14.45 12.32 17.37 22.01 17.89 17.30 20.28 19.92 14.61

23.77 22.06 22.34 13.10 13.10 13.11 11.15 12.77 12.87 12.59 14.49 13.18 14.98 21.16 13.55 17.14 12.15 18.20 17.24 12.75 17.85 13.48 14.40 12.34 17.16 21.87 17.86 17.01 19.94 19.61 14.57

59

Thousand Lakes Wilderness Ventana Wilderness Yosemite NP Black Canyon of the Gunnison NM Eagles Nest Wilderness Flat Tops Wilderness Great Sand Dunes NM La Garita Wilderness Maroon Bells-Snowmass Wilderness Mesa Verde NP Mount Zirkel Wilderness Rawah Wilderness Rocky Mountain NP Weminuche Wilderness West Elk Wilderness Chassahowitzka Everglades NP St. Marks Cohutta Wilderness Okefenokee Wolf Island Craters of the Moon NM Sawtooth Wilderness Mammoth Cave NP Acadia NP Moosehorn Roosevelt Campobello International Park Isle Royale NP Seney Voyageurs NP Hercules-Glades Wilderness Anaconda-Pintler Wilderness Bob Marshall Wilderness Cabinet Mountains Wilderness Gates of the Mountains Wilderness Medicine Lake Mission Mountains Wilderness Scapegoat Wilderness

CA CA CA CO CO CO CO CO CO CO CO CO CO CO CO FL FL FL GA GA GA ID ID KY ME ME ME MI MI MN MO MT MT MT MT MT MT MT

14.15 18.46 17.63 10.33 9.61 9.61 12.78 10.33 9.61 13.03 10.52 10.52 13.83 10.33 9.61 26.09 22.30 26.03 30.30 27.13 27.13 14.00 13.78 31.37 22.89 21.72 21.72 20.74 24.16 19.27 26.75 13.41 14.48 14.09 11.29 17.72 14.48 14.48

13.54 17.67 17.16 9.80 9.05 9.31 12.36 9.90 9.24 12.40 10.06 10.04 13.10 9.86 9.24 21.96 19.75 21.84 23.36 23.46 23.40 13.00 13.64 25.53 19.79 18.65 18.47 19.15 21.77 17.62 23.00 13.15 14.14 13.57 10.92 16.25 14.06 14.17

13.52 17.64 17.14 9.79 9.03 9.31 12.36 9.89 9.24 12.39 10.05 10.04 13.08 9.86 9.24 21.94 19.77 21.82 23.33 23.42 23.37 12.97 13.63 25.48 19.77 18.63 18.45 19.10 21.72 17.58 22.93 13.14 14.13 13.54 10.91 16.22 14.04 14.16

13.46 17.67 17.15 9.79 8.99 9.32 12.37 9.89 9.24 12.40 10.07 10.06 13.06 9.86 9.24 21.96 19.97 21.88 23.34 23.50 23.40 12.90 13.64 25.54 19.86 18.68 18.51 19.16 21.78 17.53 22.96 13.13 14.11 13.52 10.89 16.18 14.02 14.14

13.41 17.62 17.11 9.77 8.96 9.31 12.36 9.88 9.24 12.37 10.04 10.04 13.01 9.86 9.23 21.91 19.94 21.83 23.28 23.40 23.32 12.82 13.63 25.44 19.81 18.64 18.47 19.04 21.66 17.43 22.81 13.11 14.08 13.46 10.87 16.12 13.99 14.12

7.31 7.99 7.64 6.24 6.54 6.54 6.66 6.24 6.54 6.83 6.44 6.44 7.24 6.24 6.54 11.21 12.15 11.53 11.14 11.44 11.44 7.53 6.43 11.08 12.43 12.01 12.01 12.37 12.65 12.06 11.30 7.43 7.74 7.53 6.45 7.90 7.74 7.74

60

Selway-Bitterroot Wilderness UL Bend Linville Gorge Wilderness Swanquarter Lostwood Theodore Roosevelt NP Great Gulf Wilderness Presidential Range-Dry River Wilderness Brigantine Bandelier NM Bosque del Apache Gila Wilderness Pecos Wilderness Salt Creek San Pedro Parks Wilderness Wheeler Peak Wilderness White Mountain Wilderness Jarbidge Wilderness Wichita Mountains Crater Lake NP Diamond Peak Wilderness Eagle Cap Wilderness Gearhart Mountain Wilderness Hells Canyon Wilderness Kalmiopsis Wilderness Mount Hood Wilderness Mount Jefferson Wilderness Mount Washington Wilderness Mountain Lakes Wilderness Strawberry Mountain Wilderness Three Sisters Wilderness Cape Romain Badlands NP Wind Cave NP Great Smoky Mountains NP Joyce-Kilmer-Slickrock Wilderness Big Bend NP Carlsbad Caverns NP

MT MT NC NC ND ND NH NH NJ NM NM NM NM NM NM NM NM NV OK OR OR OR OR OR OR OR OR OR OR OR OR SC SD SD TN TN TX TX

13.41 15.14 28.77 25.49 19.57 17.74 22.82 22.82 29.01 12.22 13.80 13.11 10.41 18.03 10.17 10.41 13.70 12.07 23.81 13.74 13.74 18.57 13.74 18.55 15.51 14.86 15.33 15.33 13.74 18.57 15.33 26.48 17.14 15.84 30.28 30.28 17.30 17.19

13.06 14.66 22.48 21.17 17.73 16.65 19.48 19.48 24.88 11.43 12.96 12.55 10.01 16.61 9.53 9.96 13.07 11.86 20.67 13.29 13.25 17.86 13.39 17.26 15.00 14.19 14.80 14.77 13.26 17.77 14.84 22.77 15.87 14.94 23.96 23.46 16.15 15.93

13.04 14.64 22.45 21.15 17.70 16.54 19.45 19.45 24.85 11.41 12.90 12.54 10.00 16.59 9.52 9.95 13.05 11.86 20.62 13.27 13.20 17.83 13.37 17.20 14.98 14.13 14.77 14.75 13.24 17.73 14.82 22.74 15.84 14.91 23.93 23.43 16.13 15.92

13.02 14.62 22.47 21.20 17.67 16.61 19.50 19.50 24.99 11.38 12.94 12.55 10.02 16.58 9.53 9.97 13.07 11.86 20.68 13.26 13.22 17.79 13.36 17.18 14.97 14.28 14.82 14.78 13.23 17.69 14.84 22.77 15.80 14.94 23.93 23.43 16.18 15.92

12.99 14.58 22.41 21.15 17.60 16.42 19.46 19.46 24.91 11.34 12.81 12.54 10.01 16.52 9.52 9.96 13.04 11.85 20.55 13.20 13.12 17.71 13.33 17.04 14.93 14.14 14.76 14.72 13.17 17.60 14.79 22.71 15.75 14.87 23.86 23.37 16.15 15.90

7.43 8.16 11.22 11.94 8.00 7.79 11.99 11.99 12.24 6.26 6.73 6.69 6.44 6.81 6.08 6.44 6.86 7.87 7.53 7.84 7.84 8.92 7.84 8.32 9.44 8.44 8.79 8.79 7.84 8.92 8.79 12.12 8.06 7.71 11.24 11.24 7.16 6.68

61

Guadalupe Mountains NP Arches NP Bryce Canyon NP Canyonlands NP Zion NP James River Face Wilderness Shenandoah NP Lye Brook Wilderness Alpine Lake Wilderness Glacier Peak Wilderness Goat Rocks Wilderness Mount Adams Wilderness Mount Rainier NP North Cascades NP Olympic NP Pasayten Wilderness Dolly Sods Wilderness Otter Creek Wilderness Bridger Wilderness Fitzpatrick Wilderness Grand Teton NP North Absaroka Wilderness Red Rock Lakes Teton Wilderness Washakie Wilderness Yellowstone NP

TX UT UT UT UT VA VA VT WA WA WA WA WA WA WA WA WV WV WY WY WY WY WY WY WY WY

17.19 11.24 11.65 11.24 13.24 29.12 29.31 24.45 17.84 13.96 12.76 12.76 18.24 13.96 16.74 15.23 29.04 29.04 11.12 11.12 11.76 11.45 11.76 11.76 11.45 11.76

15.89 11.14 11.36 10.84 12.96 23.43 22.83 21.10 16.77 13.62 12.06 12.03 17.27 13.58 15.85 14.85 22.38 22.31 10.81 10.86 11.36 11.17 11.44 11.41 11.18 11.39

15.88 11.11 11.34 10.81 12.92 23.34 22.80 21.08 16.71 13.60 12.05 12.01 17.24 13.57 15.82 14.84 22.35 22.29 10.81 10.85 11.35 11.16 11.43 11.40 11.17 11.38

15.89 11.05 11.34 10.83 12.89 23.43 22.83 21.17 16.72 13.69 12.07 12.02 17.27 13.68 15.95 14.83 22.38 22.32 10.80 10.86 11.33 11.15 11.42 11.39 11.16 11.36

15.86 11.03 11.31 10.82 12.81 23.26 22.76 21.11 16.60 13.67 12.03 11.97 17.21 13.67 15.89 14.81 22.33 22.27 10.80 10.84 11.31 11.13 11.39 11.36 11.14 11.34

6.68 6.43 6.86 6.43 6.99 11.13 11.35 11.73 8.43 8.01 8.36 8.36 8.55 8.01 8.44 8.26 10.39 10.39 6.58 6.58 6.51 6.86 6.51 6.51 6.86 6.51

62

United States Environmental Protection Agency

Office of Air Quality Planning and Standards Air Quality Assessment Division Research Triangle Park, NC

Publication No. EPA 454/R-08-002 January 2008

63