# Technical Support Document for the Final

**Locomotive/Marine Rule: Air Quality**

**Modeling Analyses**

# 2 **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**

# 3



# I. Introduction

**This document describes the air quality modeling p erformed by EPA in support of** 

**the final Control of Emissions of Air Pollution fro m Locomotive Engines and Marine** 

**Compression-Ignition Engines Less than 20 Liters pe r Cylinder (Locomotive/Marine)** 

**rule. A national scale air quality modeling analys is was performed to estimate the effect** 

**of the rule on future annual fine particulate matte r (PM**  **2.5** 

# ) 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 Commu nity Multiscale Air Quality (CMAQ)** 

**model 1**  

# . The CMAQ model simulates the multiple physical a **nd chemical processes**

**involved in the formation, transport, and destructi on of fine particulate matter and ozone.** 

**The overall CMAQ modeling platform has been revise d from what was used at** 

**proposal. A modeling platform is a structured syst em of connected modeling-related** 

**tools and data that provide a consistent and transp arent 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 ye ar baseline emissions estimates, and a** 

**set of meteorological model inputs. The final Loco motive/Marine rule modeling analyses** 

**were based on a 2002 modeling platform which reflec ts: a) an updated version of the** 

**CMAQ model, b) higher resolution PM 2.5**  

# modeling, c) a longer period of ozone

**modeling, and d) updated emissions and meteorologic al data. These updates from the** 

**previous 2001 platform will be described in more de tail 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 simul ates the formation and fate** 

**of photochemical oxidants, including PM 2.5**  

# and ozone, for given input sets of

**meteorological conditions and emissions. This anal ysis employed a version of CMAQ** 

**based on the latest publicly-released version of CM AQ 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;**

**1** 

# Byun, D.W., and K. L. Schere, 2006: Review of the **Governing Equations, Computational Algorithms,**

**and Other Components of the Models-3 Community Mult iscale Air Quality (CMAQ) Modeling System.** 

**Applied Mechanics Reviews, Volume 59, Number 2 (Mar ch 2006), pp. 51-77.** 

**2** 

# CMAQ version 4.6 was released on September 30, 200 **6. It is available from the Community Modeling**

**and Analysis System (CMAS) at: http://www.cmascente r.org .** 

# 4 **2) an updated version of the ISORROPIA aerosol ther modynamics module was** 

**added;**

**3) the heterogeneous N 2**  

# O **5** 

# reaction probability is now temperature- and humid **ity**

**dependent;**

**4) the gas-phase reactions involving N 2**  

# O **5** 

# and H **2** 

# O are now included; and

**5) an updated version of the vertical diffusion mod ule 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 ver sion 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 dom ain 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 glob al 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 basi c geographic information regarding** 

**the CMAQ domains.**

Table II-1. Geographic elements of domains used in Locomotive/Marine modeling.

CMAQ Modeling Configuration

National Grid Western U.S. Fine Grid Eastern U.S. F ine Grid

Map Projection **Lambert Conformal Projection**

Grid Resolution **36 km 12 km 12 km**

Coordinate Center **97 deg W, 40 deg N**

True Latitudes **33 deg N and 45 deg N**

Dimensions **148 x 112 x 14 213 x 192 x 14 279 x 240 x 14**

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

**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 incl uded in the docket for this rulemaking.** 

# 5

Figure II-1. Map of the CMAQ modeling domain. The black outer box denotes the

36 km national modeling domain; the red inner box i s 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 wer e 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 le vels of PM**  **2.5** 

# . For the 8-hour ozone

**results, we are only using modeling results from th e 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 Bounda ry Conditions

1. Base Year and Future Baseline Emissions: **As noted in the introduction**

**section, a 2001-based platform was used for the pro posed rule modeling and a 2002-** 

**based platform was used for the final rule modeling . The 2002-based platform builds** 

**upon the general concepts, tools and emissions mode ling data from the 2001-based** 

**4** 

# We also modeled 10 days at the end of December 20 **01 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 analys**  **es.**

# 6

**platform, while updating and enhancing many of the emission inputs and tools. A** 

**summary of the emissions inventory development is d escribed below. More detailed** 

**documentation on the methods and data summaries of the 2002-based platform emissions** 

**for base and future years is also available separat ely.**  **5**



# We used version 3 of the 2002-based platform which **takes emission inventories**

**from the 2002 National Emissions Inventory (NEI) ve rsion 3.0. These inventories, with** 

**the exception of California, include monthly onroad and nonroad emissions generated** 

**from the National Mobile Inventory Model (NMIM) usi ng versions of MOBILE6.0 and** 

**NONROAD2005 consistent with recent national rule an alyses.**  **6,7,8** 

# The locomotive and

**marine inventories are based on national level esti mates developed for the proposed rule** 

**making. 9**  

# That is, the base year emissions for locomotive a **nd marine sectors did not**

**change between the proposal and final modeling. Th e 2002-based platform and its** 

**associated chemical mechanism (CB05) employs update d speciation profiles using data** 

**included in the SPECIATE4.0 database. 10**  

# In addition, the 2002-based platform

**incorporates several temporal profile updates for b oth mobile and stationary sources.** 

**The 2002-based platform includes emissions for a 20 02 base year model** 

**evaluation case, a 2002 base case and several proje ction years. The projection years** 

**include 2020 and 2030, which were used as the futur e years for the locomotive/marine** 

**rule analyses. The model evaluation case uses pres cribed 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 r ise and vertically allocates the** 

**fire emissions. It also includes continuous emissi ons monitoring (CEM) data for 2002 for** 

**electric generating units (EGUs) with CEMs. The 20 02 and projection year baselines** 

**5** 

# Technical Support Document: Preparation of Emiss **ions Inventories for the 2002-based Platform,**

**Version 3.0, Criteria Air Pollutants, January 2008. This file is available in the docket for this rul**  **emaking.**

**6** 

# The California Air Resources Board submitted annua **l emissions for California. These were allocated t o** 

**monthly resolution prior to emissions modeling usin g data from the National Mobile Inventory Model** 

**(NMIM).**

**7** 

# MOBILE6 version was used in the Mobile Source Air **Toxics Rule:** Regulatory Impact Analysis for Final

Rule: Control of Hazardous Air Pollutants from Mobi le Sources **, U.S. Environmental Protection Agency,**

**Office of Transportation and Air Quality, Assessmen t and Standards Division, Ann Arbor, MI 48105,** 

**EPA420-R-07-002, February 2007.**

**8** 

# 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 En gines, Vessels,

and Equipment **, U.S. Environmental Protection Agency, Office of T ransportation and Air Quality, Office** 

**of Transportation and Air Quality, Assessment and S tandards Division, Ann Arbor, MI, EPA420-D-07-** 

**004, April 2007.**

**9** 

# U.S. Environmental Protection Agency, Draft Regulat **ory Impact Analysis: Control of Emissions of Air**

**Pollution from Locomotive Engines and Marine Compre ssion-Ignition Engines Less than 30 Liters per** 

**Cylinder, EPA420-D-07-001, January 2007.**

**10** 

# See http://www.epa.gov/ttn/chief/software/speciate **/index.html for more details.**

# 7

**include an average fire sector and temporally avera ged emissions (i.e., no CEM data) for** 

**EGUs. Projections from 2002 were developed to acco unt for the expected impact of** 

**national regulations, consent decrees or settlement s, known plant closures, and, for some** 

**sectors, activity growth. For 2030, stationary sou rces used 2020 projections (i.e., no** 

**activity growth between 2020 and 2030). For the lo comotive and marine sectors, the** 

**baseline emissions have not changed from the propos al modeling. Percent reductions** 

**were applied to the 2020 and 2030 baseline emission s 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 a re marine sectors.** 

Table II-2a. Percentage reductions applied to loco motive/marine sectors in 2020 to

reflect the impacts of the final rule.

**Pollutant VOC NO**  **X** 

# PM10 PM **2.5** 

# SO **2**



# 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 loco motive/marine sectors in 2030 to

reflect the impacts of the final rule.

**Pollutant VOC NO**  **X** 

# PM10 PM **2.5** 

# SO **2**



# 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 o f the Pennsylvania State University /** 

**National Center for Atmospheric Research Mesoscale Model. This model, commonly** 

**referred to as MM5, is a limited-area, nonhydrostat ic, terrain-following system that** 

**solves for the full set of physical and thermodynam ic equations which govern** 

**atmospheric motions. 11**  

# Meteorological model input fields were prepared s **eparately 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 Des **cription of the Fifth-Generation Penn State/NCAR**

**Mesoscale Model (MM5), NCAR/TN-398+STR., 138 pp, Na tional Center for Atmospheric Research,** 

**Boulder CO.**

# 8

**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 met eorological inputs were developed** 

**by EPA. For the 12 km western U.S. domain, we util ized existing MM5 meteorological** 

**model data prepared by the Western Regional Air Par tnership (WRAP).**  **12**



# The three meteorological model runs used similar se **ts of physics options. All**

**three simulations used the Pleim-Xiu planetary boun dary 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 su bgrid convection. In the EPA** 

**simulations, analysis nudging was utilized above th e boundary layer for temperature and** 

**water vapor, and in all locations for the wind comp onents using relatively weak nudging** 

**coefficients. The WRAP runs employed similar four- dimensional data assimilation, but** 

**also included observational nudging of surface wind s. All three sets of model runs were** 

**conducted in 5.5 day segments with 12 hours of over lap for spin-up purposes. All three** 

**domains contained 34 vertical layers with an approx imately 38 m deep surface layer and** 

**a 100 millibar top. The MM5 and CMAQ vertical stru ctures are shown in Table II-3 and** 

**do not vary by horizontal grid resolution.**

Table II-3. Vertical layer structure for MM5 and CM AQ (heights are layer top).

CMAQ Layers MM5 Layers Sigma P Approximate

Height (m) Approximate

Pressure (mb)

**0 0 1.000 0 1000**

**1 1 0.995 38 995**

**2 2 0.990 77 991**

**3 0.985 115 987 3**  **4 0.980 154 982**

**5 0.970 232 973 4**  **6 0.960 310 964**

**7 0.950 389 955 5**  **8 0.940 469 946**

**9 0.930 550 937**

**10 0.920 631 928 6** 

**11 0.910 712 919**

**12 0.900 794 910**

**13 0.880 961 892 7** 

**14 0.860 1,130 874**

**15 0.840 1,303 856**

**16 0.820 1,478 838 8** 

**17 0.800 1,657 820**

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

**12** 

# 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 Configur ation for Simulating Meteorology in the Western** 

**United States. Western Regional Air Partnership, R egional Modeling Center. December 10.** 

**(http://pah.cert.ucr.edu/aqm/308/reports/mm5/MM5Sen sitivityRevRep_Dec_10_2004.pdf)** 

# 9 **20 0.700 2,600 730 10**  **21 0.650 3,108 685**

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

**24 0.500 4,816 550**

**25 0.450 5,461 505 12** 

**26 0.400 6,153 460**

**27 0.350 6,903 415**

**28 0.300 7,720 370**

**29 0.250 8,621 325 13** 

**30 0.200 9,625 280**

**31 0.150 10,764 235**

**32 0.100 12,085 190**

**33 0.050 13,670 145 14** 

**34 0.000 15,674 100**



# The meteorological outputs from all three MM5 sets **were processed to create**

**model-ready inputs for CMAQ using the Meteorology-C hemistry Interface Processor** 

**(MCIP), version 3.1, to derive the specific inputs to CMAQ.**  **13**



# Before initiating the air quality simulations, it i **s important to identify the biases**

**and errors associated with the meteorological model ing inputs. The 2002 MM5 model** 

**performance evaluations used an approach which incl uded a combination of qualitative** 

**and quantitative analyses to assess the adequacy of the MM5 simulated fields. The** 

**qualitative aspects involved comparisons of the mod el-estimated synoptic patterns** 

**against observed patterns from historical weather c hart archives. Qualitatively, the model** 

**fields closely matched the observed synoptic patter ns, which is expected given the use of** 

**nudging. The operational evaluation included stati stical comparisons of model/observed** 

**pairs (e.g., mean normalized bias, mean normalized error, index of agreement, root mean** 

**square errors, etc.) for multiple meteorological pa rameters. For this portion of the** 

**evaluation, four meteorological parameters were inv estigated: temperature, humidity,** 

**wind speed, and wind direction. The operational pie ce 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 er **ror values**

**13** 

# 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).** 

**14** 

# Gilliam, R. C., W. Appel, and S. Phillips. The Atm **ospheric Model Evaluation Tool (AMET):**

**Meteorology Module. Presented at 4th Annual CMAS Mo dels-3 Users Conference, Chapel Hill, NC,** 

**September 26 - 28, 2005.**

**15** 

# Brewer J., P. Dolwick, and R. Gilliam. Regional a **nd Local Scale Evaluation of MM5 Meteorological**

**Fields for Various Air Quality Modeling Application s, Presented at the 87th Annual American** 

**Meteorological Society Annual Meeting, San Antonio, TX, January 15-18, 2007.** 

**16** 

# Dolwick, P, R. Gilliam, L. Reynolds, and A. Huffma **n. Regional and Local-scale Evaluation of 2002**

**MM5 Meteorological Fields for Various Air Quality M odeling Applications, Presented at 6th Annual** 

**CMAS Models-3 Users Conference, Chapel Hill, NC, Oc tober 1 - 3, 2007.** 

# 10

**associated with all three sets of 2002 meteorologic al data were generally within the range** 

**of past meteorological modeling results that have b een 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 assimilat ed 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-wa y dynamic boundary conditions at** 

**three-hour intervals and an initial concentration f ield 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/g eos.** 

E. CMAQ Base Case Model Performance Evaluation

**An operational model performance evaluation for oz one and PM**  **2.5** 

# 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 do mains. In summary, model** 

**performance statistics were calculated for observed -predicted pairs of daily, monthly,** 

**seasonal, and annual concentrations. Statistics we re generated for the following** 

**geographic groupings: the entire 12-km Eastern US d omain (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 judg **ed 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 PM**  **2.5** 

# model applications (e.g., Clean Air Interstate Rule **, Final PM NAAQS Rule). 21**  

# These

**17** 

# Kemball-Cook, S., Y. Jia, C. Emery, R. Morris, Z. **Wang, and G. Tonnesen. Annual 2002 MM5**

**Meteorological Modeling to Support Regional Haze Mo deling of the Western United States,** 

**Prepared for The Western Regional Air Partnership ( WRAP), 1515 Cleveland Place, Suite 200** 

**Denver, CO 80202, March 2005.**

**18** 

# Environ, Enhanced Meteorological Modeling and Perf **ormance Evaluation for Two Texas Episodes,**

**August 2001.**

**19** 

# Yantosca, B., 2004. GEOS-CHEMv7-01-02 User’s Guide **, Atmospheric Chemistry Modeling**

**Group, Harvard University, Cambridge, MA, October 1 5, 2004.** 

**20** 

# The subregions are defined by States where: Midwes **t is IL, IN, MI, OH, and WI; Northeast is CT, DE,**

**MA, MD, ME, NH, NJ, NY, PA, RI, and VT; Southeast i s 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.**

**21** 

# See: U.S. Environmental Protection Agency; Technic **al Support Document for the Final Clean Air**

**Interstate Rule: Air Quality Modeling; Office of Ai r Quality Planning and Standards; RTP, NC; March** 

**2005 (CAIR Docket OAR-2005-0053-2149); and U.S. Env ironmental Protection Agency, 2006. Technical** 

**Support Document for the Final PM NAAQS Rule: Offic e of Air Quality Planning and Standards, Research** 

**Triangle Park, NC**

# 11

**other modeling studies represent a wide range of mo deling analyses which cover various** 

**models, model configurations, domains, years and/or episodes, chemical mechanisms,** 

**and aerosol modules.**

**There are various statistical metrics available an d used by the scientific** 

**community for model performance evaluation. The pr incipal evaluation statistics used to** 

**evaluate CMAQ performance were two bias metrics, no rmalized 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 facil itate 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:**

**NMB =** 

# ( )

( ) P O

O n

n 

# − 

# ∑

∑ **1**

**1** 

# *100, where P = predicted concentrations and O = ob **served**

**Normalized mean error (NME) is also similar to NMB, where the performance statistic is** 

**used as a normalization of the mean error. NME ca lculates the absolute value of the** 

**difference (model - observed) over the sum of obser ved values. Normalized mean error** 

**is defined as:**

**NME =**



# ( )

P O

O n

n 

# − 

# ∑

∑ **1**

**1** 

# *100, where P = predicted concentrations and O = ob **served**

**Fractional bias is defined as:**

**FB =** 

# ( )

( ) **1**

**2 1** 

**1** 

# n P O

P O n

n 

# −

+ 

  

  

     

     

# ∑

∑ ***100, where P = predicted concentrations and O = ob served** 

**FB is a useful model performance indicator because it has the advantage of equally** 

**weighting positive and negative bias estimates. Th e 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.**

# 12

**Fractional error (FE) is similar to fractional bias except the absolute value of the** 

**difference is used so that the error is always posi tive. Fractional error is defined as:** 

**FE =** 

# ( ) **1**

**2**

**1**

**1** 

# n P O

P O n

n 

# −

+ 

  

  

     

     

# ∑

∑ ***100, where P = predicted concentrations and O = ob served** 

**Overall, the bias and error statistics shown in Ta ble II-4 below indicate that the** 

**base case model ozone and PM 2.5**  

# concentrations are within the range or close to th **at**

**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 ozon e and PM**  **2.5** 

# concentrations for the

**purposes of the final Locomotive/Marine rule. A de tailed summary of the CMAQ model** 

**performance evaluation is available in the docket f or this rulemaking.**  **22** 

# A summary of

**the PM 2.5**  

# and ozone evaluation is presented here.

1. PM 2.5 

# : **The PM 2.5**  

# evaluation focuses on PM **2.5** 

# total mass and its components

**including sulfate (SO 4**  

# ), nitrate (NO **3** 

# ), total nitrate (TNO **3** 

# =NO **3** 

# +HNO **3** 

# ), ammonium

**(NH 4**  

# ), elemental carbon (EC), and organic carbon (OC). **The PM 2.5**  

# performance

**statistics were calculated for each month and seaso n individually and for the entire year,** 

**as a whole. Seasons were defined as: winter (Decem ber-January-February), spring** 

**(March-April-May), summer (June-July-August), and f all (September-October** 

**November). PM 2.5**  

# ambient measurements for 2002 were obtained from t **he following**

**networks for model evaluation:** S **peciation** T **rends** N **etwork (STN- total of 199 sites),**

I **nteragency** M **onitoring of** PRO **tected** V **isual** E **nvironments (IMPROVE- total of 150),**

**and** C **lean** A **ir** S **tatus and** T **rends** Net **work (CASTNet- total of 83). For PM 2.5**  

# species

**that are measured by more than one network, we calc ulated separate sets of statistics for** 

**each network. For brevity, Table II-4 provides ann ual model performance statistics for** 

**PM 2.5**  

# and its component species for the 12-km Eastern do **main, 12-km Western domain,**

**and five subregions defined above (Midwest, Northea st, Southeast, Central, and West** 

**U.S.).**

Table II-4. Summary of 2002 CMAQ annual PM 2.5 

# species model performance

statistics.

CMAQ 2002 Annual No. of Obs. NMB (%) NME (%) FB (%) FE (%)

**12-km EUS** 10307 10.8 42.8 5.4 42.6 **PM 2.5** 



# Total Mass **STN**

**12-km WUS** 3000 -5.8 46.9 -3.1 45.0

**22** 

# Technical Support Document: 2002 CMAQ Model Perfor **mance Evaluation for Ozone and Particulate**

**Matter, January 2008. This file is available in th e docket for this rulemaking.** 

# 13 **Northeast** 1516 14.9 35.6 13.2 34.4

**Midwest** 2780 20.5 48.2 16.6 42.6

**Southeast** 2554 -3.9 36.0 -10.0 39.7

**Central** 2738 14.5 49.1 6.0 49.4

**West** 2487 -7.4 46.8 -4.5 44.8

**12-km EUS** 8436 -2.3 49.0 -5.7 51.4

**12-km WUS** 10123 -26.4 53.5 -26.3 57.5

**Northeast** 592 8.6 41.5 2.4 41.0

**Midwest** 2060 21.0 59.4 17.4 51.6

**Southeast** 1803 -13.1 41.2 -19.8 49.9

**Central** 1624 -13.1 49.4 -17.6 57.0 **IMPROVE**

**West** 9543 -27.8 53.1 -27.1 57.2

**12-km EUS** 10157 -3.9 33.6 -9.7 38.4

**12-km WUS** 2926 -20.6 41.9 -12.2 43.5

**Northeast** 1487 3.6 34.9 -2.9 36.2

**Midwest** 2730 -4.3 29.1 -8.8 33.6

**Southeast** 2541 -7.6 33.4 -16.3 38.8

**Central** 2686 -3.2 39.2 -7.2 44.3 **STN**

**West** 2446 -26.1 44.9 -15.8 44.8

**12-km EUS** 8532 -10.8 33.0 -7.2 40.6

**12-km WUS** 10232 -7.5 42.4 7.6 45.7

**Northeast** 597 -4.9 29.9 -10.0 35.7

**Midwest** 2070 -12.3 30.1 -9.9 36.1

**Southeast** 1805 -9.5 32.9 -16.8 40.5

**Central** 1671 -16.1 35.0 -16.0 42.4 **IMPROVE**

**West** 9645 -5.5 43.5 8.6 45.9

**12-km EUS** 3173 -11.3 20.5 -16.3 26.1

**12-km WUS** 1158 -21.3 34.6 -11.2 35.9

**Northeast** 663 -8.3 19.3 -16.3 24.3

**Midwest** 839 -12.3 17.9 -15.6 21.6

**Southeast** 1085 -11.2 21.5 -17.8 27.2

**Central** 229 -20.7 27.3 -27.4 33.6 **Sulfate**

**CASTNet**

**West** 1118 -20.4 35.3 -10.7 36.1

**12-km EUS** 8770 18.3 65.9 -29.1 84.5

**12-km WUS** 2726 -45.0 63.1 -70.6 95.0

**Northeast** 1488 17.4 59.1 -5.0 67.3

**Midwest** 2731 32.7 70.4 -10.9 78.1

**Southeast** 2540 8.6 84.6 -64.7 107.5

**Central** 1298 12.7 52.5 -13.4 69.1 **STN**

**West** 2446 -47.5 62.8 -73.8 95.4

**12-km EUS** 8514 48.4 106.8 -52.8 116.4 **Nitrate**

**IMPROVE**

**12-km WUS** 10110 -34.8 80.67 -101.0 130.0

# 14 **Northeast** 597 43.0 86.0 -37.0 102.8

**Midwest** 2069 122.2 153.8 3.5 107.5

**Southeast** 1803 33.5 112.2 -78.5 130.8

**Central** 1672 18.1 81.0 -59.6 114.1

**West** 9522 -39.6 81.1 -104.0 131.1

**12-km EUS** 3171 24.4 37.3 16.8 35.1

**12-km WUS** 1157 -19.5 44.2 -12.0 46.0

**Northeast** 662 20.5 29.4 16.3 25.3

**Midwest** 839 39.1 46.5 29.0 39.7

**Southeast** 1085 22.9 39.5 15.8 37.2

**Central** 229 6.2 35.6 0.6 36.2 **Total Nitrate**

**(NO 3**  

# +HNO **3** 

# ) **CASTNet**

**West** 1117 -20.4 45.8 -12.1 46.6

**12-km EUS** 10157 11.9 40.6 14.4 45.2

**12-km WUS** 2926 -23.6 55.7 7.2 58.1

**Northeast** 1488 16.0 39.6 21.8 42.8

**Midwest** 2731 12.3 38.4 19.2 42.4

**Southeast** 2540 7.3 38.4 6.0 41.8

**Central** 2685 15.0 46.6 14.3 52.1 **STN**

**West** 2446 -30.6 56.7 2.9 59.7

**12-km EUS** 3166 5.3 30.8 2.7 31.6

**12-km WUS** 1156 -16.8 42.5 -13.0 41.1

**Northeast** 661 15.3 27.6 13.6 25.2

**Midwest** 837 9.8 34.7 11.9 33.9

**Southeast** 1085 -7.7 30.1 -9.7 33.6

**Central** 229 7.4 33.1 3.0 35.6 **Ammonium**

**CASTNet**

**West** 1116 -21.1 43.5 -14.4 41.4

**12-km EUS** 10031 45.0 78.9 22.1 56.9

**12-km WUS** 2975 43.1 82.6 18.2 61.3

**Northeast** 1498 37.1 58.9 24.5 48.3

**Midwest** 2744 53.1 76.7 26.3 54.7

**Southeast** 2506 16.9 66.0 7.2 51.7

**Central** 2570 91.7 118.0 41.0 68.1 **STN**

**West** 2475 49.0 86.2 17.1 62.7

**12-km EUS** 8282 -15.0 49.2 -23.4 52.8

**12-km WUS** 10069 -14.1 67.2 -29.5 62.1

**Northeast** 599 -22.6 37.5 -27.4 46.5

**Midwest** 2056 11.6 57.5 0.5 50.8

**Southeast** 1795 -32.4 44.6 -42.0 55.6

**Central** 1532 -24.3 47.6 -29.8 55.9 **Elemental**

**Carbon**

**IMPROVE**

**West** 9493 -15.5 67.8 -31.3 62.7

**12-km EUS** 9726 -39.9 58.0 -41.1 70.5 **Organic**

**Carbon STN** 

**12-km WUS** 2903 -37.6 60.3 -40.4 69.3

# 15 **Northeast** 1447 -45.2 60.9 -41.6 73.1

**Midwest** 2641 -26.5 61.7 -19.7 67.6

**Southeast** 2474 -47.4 55.3 -53.7 70.7

**Central** 2504 -43.6 54.0 -51.3 69.7

**West** 2408 -36.3 61.4 -37.9 70.2

**12-km EUS** 8287 -32.4 60.5 -37.1 67.9

**12-km WUS** 10082 -34.8 60.0 -31.2 63.0

**Northeast** 598 -42.4 54.8 -40.2 63.8

**Midwest** 2057 -6.4 68.2 -0.7 60.8

**Southeast** 1800 -46.1 58.4 -69.7 81.3

**Central** 1531 -47.9 61.6 -61.2 79.6 **IMPROVE**

**West** 9508 -34.5 59.6 -29.7 61.9



# 2. Ozone: **The ozone evaluation focuses on the observed and p redicted hourly** 

**ozone concentrations and eight-hour daily maximum o zone concentrations using a** 

**(observation) threshold of 40 ppb. This ozone mode l 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 m easurements for 2002 were** 

**obtained from the Air Quality System (AQS) Aerometr ic Information Retrieval System** 

**(AIRS). A total of 1178 ozone measurement sites we re 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 d aily maximum ozone model** 

**performance statistics, respectively, for the 12-km Eastern and Western U.S. domain and** 

**the five subregions. Generally, hourly and eight-h our 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 th e aggregate of the ozone season and for** 

**each individual ozone month modeled.**

Table II-5. Summary of CMAQ 2002 hourly ozone mode l performance statistics

CMAQ 2002 Hourly Ozone:

Threshold of 40 ppb No. of Obs. NMB (%) NME (%) FB (%) FE (%)

**12-km EUS** 241185 -0.7 15.9 -2.0 17.1

**12-km WUS** 124931 -3.7 15.9 -5.0 17.3

**Northeast** 51055 1.2 17.1 -0.3 18.2

**Midwest** 55859 3.3 16.2 2.4 16.9

**Southeast** 69073 -2.5 14.1 -3.1 14.8

**Central** 41728 -6.4 17.3 -9.2 20.3 May

**West** 111385 -3.9 16.1 -5.2 17.6

**12-km EUS** 256263 -7.5 16.8 -9.0 18.6

**12-km WUS** 125662 -8.4 17.7 -9.3 19.1 June

**Northeast** 61354 -8.5 17.3 -9.9 19.1

# 16 **Midwest** 54515 -7.2 17.9 -8.3 19.6

**Southeast** 67867 -7.2 15.3 -7.6 16.3

**Central** 46026 -10.0 17.5 -13.5 21.2

**West** 109157 -8.8 18.2 -9.9 19.7

**12-km EUS** 257076 -5.3 17.7 -6.6 19.2

**12-km WUS** 116785 -12.0 21.5 -14.9 24.3

**Northeast** 66774 -3.9 17.0 -4.8 18.0

**Midwest** 59360 -10.5 19.4 -12.3 21.7

**Southeast** 68619 -3.6 16.5 -3.9 17.2

**Central** 36021 -3.6 18.7 -6.3 21.1 July

**West** 104321 -13.6 21.8 -16.8 24.9

**12-km EUS** 235090 -8.7 17.8 -10.2 19.7

**12-km WUS** 125575 -7.9 20.1 -10.2 22.1

**Northeast** 53837 -6.4 16.7 -7.4 18.0

**Midwest** 54179 -10.8 19.1 -12.4 21.4

**Southeast** 62506 -9.4 17.3 -9.9 18.5

**Central** 41456 -9.3 18.7 -12.8 22.4 August

**West** 110225 -8.5 20.6 -11.1 22.8

**12-km EUS** 179156 -9.9 17.2 -11.8 19.5

**12-km WUS** 99710 -10.7 19.0 -12.7 21.1

**Northeast** 44678 -8.7 16.3 -10.6 18.4

**Midwest** 34285 -11.4 18.5 -12.9 20.4

**Southeast** 41627 -8.2 16.5 -9.0 17.8

**Central** 41549 -12.8 18.8 -16.6 22.8 September

**West** 83921 -11.7 20.0 -13.8 22.1

**12-km EUS** 1168770 -6.4 17.1 -7.7 18.8

**12-km WUS** 592663 -8.4 18.8 -10.3 20.7

**Northeast** 277698 -5.4 16.9 -6.5 18.4

**Midwest** 258198 -7.3 18.3 -8.4 20.0

**Southeast** 309692 -6.0 15.9 -6.4 16.8

**Central U** 206780 -8.6 18.2 -11.9 21.6 Seasonal Aggregate

**West** 519009 -9.2 19.3 -11.2 21.3



# 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 No. of Obs. NMB (%) NME (%) FB (%) FE (%)

**12-km EUS** 19172 3.9 12.7 4.3 12.6

**12-km WUS** 9223 0.2 12.6 0.6 12.8

**Northeast** 4255 6.7 14.3 6.8 14.2

**Midwest** 4198 7.8 13.7 8.2 13.5 May

**Southeast** 5470 0.6 10.9 1.1 11.0

# 17 **Central** 3379 0.3 12.3 0.7 12.4

**West** 8155 -0.1 12.8 0.3 12.9

**12-km EUS** 19462 -3.9 12.3 -3.3 12.4

**12-km WUS** 9029 -4.9 14.1 -4.2 14.2

**Northeast** 4608 -5.3 12.5 -4.7 12.7

**Midwest** 4104 -3.2 12.7 -2.2 12.8

**Southeast** 5110 -4.8 11.8 -4.1 11.9

**Central** 3603 -4.5 12.2 -4.4 12.7 June

**West** 7818 -5.3 14.5 -4.7 14.7

**12-km EUS** 20565 -1.6 13.5 -1.0 13.6

**12-km WUS** 8809 -7.4 17.1 -8.1 18.0

**Northeast** 5380 -0.7 13.0 -0.2 12.9

**Midwest** 4368 -6.5 14.2 -5.8 14.4

**Southeast** 5633 -0.9 13.0 -0.1 13.0

**Central** 3114 1.3 14.4 1.2 14.7 July

**West** 7784 -9.0 17.2 -9.9 18.2

**12-km EUS** 19260 -5.1 13.2 -4.4 13.4

**12-km WUS** 9551 -2.8 15.8 -3.1 16.1

**Northeast** 4667 -2.9 12.4 -2.2 12.4

**Midwest** 4012 -8.1 13.9 -7.5 14.2

**Southeast** 5067 -6.4 13.4 -5.4 13.4

**Central** 3543 -4.0 13.5 -3.9 14.1 August

**West** 8311 -3.2 16.1 -3.6 16.5

**12-km EUS** 15865 -6.2 12.6 -5.9 12.9

**12-km WUS** 8185 -6.7 15.0 -6.9 15.5

**Northeast** 4074 -6.0 11.8 -6.0 12.3

**Midwest** 3120 -7.2 13.3 -6.5 13.3

**Southeast** 3671 -4.5 12.6 -3.8 12.7

**Central** 3492 -8.5 13.8 -8.7 14.5 September

**West** 6911 -7.3 15.9 -7.6 16.4

**12-km EUS** 94324 -2.6 12.9 -1.9 13.0

**12-km WUS** 44797 -4.3 14.9 -4.2 15.3

**Northeast** 22984 -1.9 12.8 -1.2 12.9

**Midwest** 19802 -3.6 13.6 -2.5 13.7

**Southeast** 24951 -3.1 12.4 -2.3 12.4

**Central** 17131 -3.3 13.2 -3.1 13.7 Seasonal Aggregate

**West** 38979 -4.9 15.3 -5.0 15.7



# F. CMAQ Locomotive/Marine Modeling Scenarios

**The CMAQ modeling system was used to calculate annu al PM**  **2.5** 

# concentrations,

**daily 8-hour ozone concentrations, and visibility e stimates for each of the following** 

**seven emissions scenarios:**

# 18 **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 e stimate scenario-specific,** 

**future-year design values of PM 2.5**  

# and ozone. This is done by calculating the simula **ted**

**air quality ratios between any particular future ye ar 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** 

**analyses 23**  

# We used the 5-year weighted average 2000-2004 des **ign values as the starting**

**point for the projections. Additionally, the raw m odel 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 PM 2.5 

# Annual Averages

**This section summarizes the results of our modeling of PM**  **2.5** 

# air quality impacts

**in the future due to the reductions in locomotive a nd commercial marine diesel emissions.** 

**Appendix A contains annual average PM 2.5**  

# design values by county for each modeling

**scenario. The modeling results indicate that the e missions reductions from this rule will** 

**contribute to lower ambient PM 2.5**  

# levels in future years. Tables III-1 and III-2 sh **ow the**

**projected improvements in average annual PM 2.5**  

# design values, for various years as a

**result of the Locomotive/Marine control scenarios d iscussed in Section II.F.** 

**23** 

# U.S. EPA, Guidance on the Use of Models and Other **Analyses in Attainment Demonstrations for the 8-**

**hour Ozone NAAQS; EPA-454/R-05-002; Research Triang le Park, NC; October 2005.** 

# 19

Table III-1. Model-projected change in annual aver age PM 2.5 

# design values

resulting from the Locomotive/Marine modeling scena rios for several categories of

counties. Units are μg/m 3



# .

Average change 2020

marine

controls

only 2020

locomotive

and

marine

controls 2030

marine

controls

only 2030

locomotive

and

marine

controls

**Average change in all counties -0.02 -0.04 -0.04 -0 .08** 

**Average change in counties whose base year**

**design value is above the NAAQS -0.03 -0.06 -0.05 -0.11** 

**Average change in counties whose base year**

**design value is within 10% of the NAAQS -0.03 -0.06 -0.06 -0.12** 

**Average change in counties whose projection year**

**design value is above the NAAQS -0.06 -0.10 -0.14 -0.22** 

**Average change in counties whose projection year**

**design value is within 10% of the NAAQS -0.04 -0.09 -0.09 -0.18** 



# Table III-2. Model-projected, population-weighted, change in annual average PM 2.5 

# design values resulting from the Locomotive/Marine modeling scenarios for several

categories of counties. Units are μg/m 3



# .

Average change 2020

marine

controls

only 2020

locomotive

and

marine

controls 2030

marine

controls

only 2030

locomotive

and

marine

controls

**Average change in all counties -0.03 -0.06 -0.08 -0 .12** 

**Average change in counties whose base year**

**design value is above the NAAQS -0.05 -0.08 -0.11 -0.16** 

**Average change in counties whose base year**

**design value is within 10% of the NAAQS -0.04 -0.08 -0.10 -0.16** 

**Average change in counties whose projection year**

**design value is above the NAAQS -0.07 -0.11 -0.16 -0.21** 

**Average change in counties whose projection year**

**design value is within 10% of the NAAQS -0.05 -0.09 -0.12 -0.18** 



# The modeling projects that 11 counties will have de **sign values greater than 15.0**

**μg/m 3**  

# in 2020 and 2030. Over 24 million people are proj **ected to live in a PM 2.5**  

# nonattainment county in the future. The controls f **rom 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 L ocomotive/Marine rule controls will** 

**lower PM 2.5**  

# concentrations on average by 0.04 μg/m **3** 

# in 2020 and 0.08 μg/m **3** 

# in 2030.

**Greater improvements in PM 2.5**  

# air quality are projected in areas where present-d **ay and**

**future-projected PM 2.5**  

# levels are above or near the NAAQS. For instance, **when**

**considering only those counties whose future year d esign values are projected to exceed** 

**the NAAQS, the average improvement resulting from t his rule is 0.10 μg/m**  **3** 

# in 2020 and

**0.22 μg/m 3**  

# in 2030. Additionally, as shown in Table III-2, t **he improvements resulting**

**from the rule are larger when population-weighted. The greatest impacts from the final** 

# 20

**Locomotive/Marine rule emissions reductions tend to occur in areas with high** 

**populations. The largest reduction in annual avera ge PM**  **2.5** 

# occurs in Houston TX (Harris

**Co.) where the rule is projected to result in a 0.3 8 μg/m**  **3** 

# improvement in 2020 and 0.81

**μg/m 3**  

# in 2030. The largest reduction in an area that is **projected to exceed the PM 2.5**  

# NAAQS in 2020 and 2030 is in the Los Angeles region **(Riverside Co.) where the annual**

**average PM 2.5**  

# design value is projected to drop from 22.67 to 22 **.48 μg/m 3**  

# in 2020, and

**22.54 to 22.13 μg/m 3**  

# in 2030 as a result of the final Locomotive/Marine **rule. The**

**modeling indicated that both the locomotive and mar ine components of the rule improved** 

**PM 2.5**  

# air quality relatively equally.

**Figures III-1 through III-4 display the projected c ounty-level, annual PM**  **2.5** 

# design

**value changes expected from various locomotive/mari ne control scenarios and years** 

**associated with this rule. The largest impacts ten d to be in areas near water, where** 

**commercial marine source contributions can be large**

**.**

# 21

Figure III-1. Model-projected change in annual PM 2.5 

# design values from the

Locomotive/Marine control scenario in 2020. Units are μg/m 3



# .

Number of Counties

0

4

43

142

367

0 Differences due to scenario 2020cc Locomarine 

# 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



# Figure III-2. Model-projected change in annual PM 2.5 

# design values from the

Marine-only control scenario in 2020. Units are μg /m 3



# .

Number of Counties

0

3

19

37

496

1 Differences due to scenario 2020cc Marine-only 

# 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

# 22

Figure III-3. Model-projected change in annual PM 2.5 

# design values from the

Locomotive/Marine control scenario in 2030. Units are μg/m 3



# .

Number of Counties

4

20

143

193

196

0 Differences due to scenario 2030cc Locomarine 

# 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



# Figure III-4. Model-projected change in annual PM 2.5 

# design values from the

Marine-only control scenario in 2030. Units are μg /m 3



# .

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

# 23

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 a nd commercial marine diesel emissions.** 

**Appendix B contains 8-hour ozone design values by c ounty for each modeling scenario.** 

**The modeling results indicate that the emissions re ductions from this rule will contribute** 

**to lower ambient 8-hour ozone design values in futu re 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 scenar ios.** 

Table III-3. Model-projected change in average 8-h our ozone design values

resulting from the Locomotive/Marine modeling scena rios for several categories of

counties. Units are ppb.

Average change 2020

marine

controls

only 2020

locomotive

and

marine

controls 2030

marine

controls

only 2030

locomotive

and

marine

controls

**Average change in all counties -0.23 -0.45 -0.51 -1 .15** 

**Average change in counties whose base year**

**design value is above the NAAQS -0.22 -0.45 -0.51 -1.18** 

**Average change in counties whose base year**

**design value is within 10% of the NAAQS -0.23 -0.46 -0.53 -1.18** 

**Average change in counties whose projection year**

**design value is above the NAAQS 0.00 -0.19 0.00 -0.50** 

**Average change in counties whose projection year**

**design value is within 10% of the NAAQS -0.20 -0.41 -0.65 -1.24** 



# 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.

Average change 2020

marine

controls

only 2020

locomotive

and

marine

controls 2030

marine

controls

only 2030

locomotive

and

marine

controls

**Average change in all counties -0.12 -0.30 -0.32 -0 .85** 

**Average change in counties whose base year**

**design value is above the NAAQS -0.09 -0.27 -0.26 -0.78** 

**Average change in counties whose base year**

**design value is within 10% of the NAAQS -0.12 -0.31 -0.32 -0.86** 

**Average change in counties whose projection year**

**design value is above the NAAQS -0.01 -0.13 -0.24 -0.62** 

**Average change in counties whose projection year**

**design value is within 10% of the NAAQS +0.05 -0.08 -0.42 -0.79** 

# 24 **The modeling projects that 9 counties will have des ign values greater than 0.08** 

**ppm in 2020 and 6 counties will exceed that level i n 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 mode ling 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 de sign 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 Locomoti ve/Marine rule controls will** 

**lower ozone design values on average by 0.30 ppb in 2020 and 0.85 ppb in 2030. Unlike** 

**PM 2.5**  

# , 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 a re 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 project ed to result in an increase of 2.6 ppb** 

**in 2020 and 5.5 ppb in 2030. This increase is high ly 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 larges t county-level decrease resulting from** 

**the rule is north of the Los Angeles area (Santa Ba rbara 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 mar ine components of the rule improved** 

**air quality relatively equally, but it was the mari ne reductions that tended to lead to the** 

**"disbenefit" regions.**

**Figures III-5 through III-8 display the projected c ounty-level, 8-hour ozone** 

**design value changes expected from the final Locomo tive/Marine rule control scenarios.** 

**The largest impacts tend to be in areas near water, where commercial marine source** 

**contributions can be large.**

# 25

Figure III-5. Model-projected change in annual 8-h our ozone design values from

the Locomotive/Marine control scenario in 2020. Un its are ppb.

Number of Counties

0

14

241

315

5

3

Effect of Locomarine in 2020 1 

# Legend

<= -2.0

> -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-h our ozone design values from

the marine-only control scenario in 2020. Units ar e ppb.

Number of Counties

0

9

63

450

48

8

Effect of Marine-only in 2020 1 

# Legend

<= -2.0

> -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

Figure III-7. Model-projected change in annual 8-h our ozone design values from

the Locomotive/Marine control scenario in 2030. Un its are ppb.

Number of Counties

27

338

190

18

1

4

Effect of LocoMarine in 2030 1 

# Legend

<= -2.0

> -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-h our ozone design values from

the marine-only control scenario in 2030. Units ar e ppb.

Number of Counties

9

71

170

306

13

9

Effect of Marine-only in 2030 1 

# Legend

<= -2.0

> -2.0 to <= -1.0

> -1.0 to <= -0.5

> -0.5 to <= -0.1

= 0.0

> 0.0 to <= 1.0

> 1.0

# 27

C. Impacts of the Locomotive/Marine Rule on Visibi lity

**The modeling conducted for the Locomotive/Marine ru le was also used to project** 

**the impacts of the reductions on visibility conditi ons over 133 mandatory class I federal** 

**areas across the U.S. in 2020 and 2030. The result s 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 resu lt of the locomotive/marine controls** 

**in this rule. Appendix C contains the visibility r esults from the locomotive/marine** 

**scenario over the 133 Class 1 areas.**

**24** 

# The level of visibility impairment in an area is b **ased on the light-extinction coefficient and a unit less** 

**visibility index, called a “deciview”, which is use d in the valuation of visibility. The deciview met**  **ric**

**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 gene rally perceive a change of one deciview. The highe**  **r**

**the deciview value, the worse the visibility. Thus , an improvement in visibility is a decrease in dec**  **iview**

**value. 28** Appendix A: Annual Average PM2.5Design Values for Locomotive/Marine Scenarios (units are μg/m3)State Name County Name Baseline DV 2020 Base 2020 Marine only 2020 Locomotive/ Marine2030 Base 2030 Marine only 2030 Locomotive/ MarineAlabama Baldwin Co 11.389.14 9.13 9.129.19 9.15 9.14Alabama Clay Co 13.5010.45 10.44 10.4110.45 10.44 10.38Alabama Colbert Co 13.0210.23 10.22 10.2010.24 10.22 10.19Alabama DeKalb Co 14.8611.21 11.20 11.1811.20 11.19 11.15Alabama Escambia Co 12.8210.48 10.47 10.4610.50 10.48 10.44Alabama Etowah Co 15.6912.02 12.01 11.9811.99 11.98 11.92Alabama Jefferson Co 18.3615.00 14.99 14.9514.95 14.94 14.88Alabama Madison Co 14.2010.74 10.74 10.7210.75 10.73 10.71Alabama Mobile Co 12.8010.72 10.58 10.5610.95 10.64 10.62Alabama Montgomery Co 14.5011.76 11.75 11.7211.75 11.75 11.69Alabama Morgan Co 13.3610.35 10.34 10.3210.36 10.34 10.30Alabama Russell Co 16.0413.15 13.14 13.1313.14 13.13 13.10Alabama Shelby Co 14.5011.36 11.36 11.3211.38 11.37 11.31Alabama Sumter Co 12.269.78 9.77 9.759.81 9.78 9.74Alabama Talladega Co 14.9611.48 11.48 11.4411.47 11.46 11.38Arizona Cochise Co 6.976.60 6.60 6.606.61 6.61 6.60Arizona Gila Co9.528.89 8.89 8.888.87 8.87 8.86Arizona Maricopa Co 11.4510.30 10.30 10.2910.31 10.31 10.28Arizona Pima Co6.756.13 6.13 6.126.12 6.12 6.10Arizona Pinal Co8.147.45 7.45 7.427.59 7.59 7.55Arizona Santa Cruz Co 11.7411.24 11.24 11.2311.27 11.27 11.27Arkansas Arkansas Co 12.1310.08 10.06 10.0310.09 10.06 10.00Arkansas Ashley Co 12.1410.28 10.26 10.2410.33 10.29 10.26Arkansas Crittenden Co 12.9110.66 10.60 10.5510.93 10.81 10.73Arkansas Faulkner Co 12.4010.33 10.32 10.2810.34 10.33 10.26Arkansas Mississippi Co 11.849.66 9.62 9.609.73 9.65 9.62Arkansas Phillips Co 12.1610.20 10.12 10.1010.38 10.19 10.17Arkansas Polk Co 11.089.02 9.02 9.009.04 9.02 8.99Arkansas Pope Co 12.2310.13 10.12 10.1010.12 10.11 10.06Arkansas Pulaski Co 14.1211.63 11.61 11.5511.60 11.57 11.46Arkansas Sebastian Co 12.3310.33 10.33 10.3110.33 10.32 10.29Arkansas Union Co 12.6411.01 10.99 10.9811.04 11.01 10.97Arkansas White Co 11.639.57 9.56 9.529.57 9.54 9.48California Alameda Co 11.7610.77 10.75 10.7310.68 10.64 10.60**29**California Butte Co 13.6911.84 11.83 11.8011.76 11.75 11.69California Calaveras Co 8.857.83 7.82 7.807.84 7.82 7.79California Colusa Co 9.448.78 8.78 8.778.75 8.74 8.72California Contra Costa Co 11.3210.53 10.50 10.4910.57 10.50 10.48California Fresno Co 20.0217.54 17.52 17.4717.14 17.09 16.97California Humboldt Co 8.487.34 7.33 7.337.36 7.34 7.33California Imperial Co 14.4413.92 13.91 13.8713.97 13.95 13.88California Inyo Co6.175.94 5.95 5.945.96 5.96 5.95California Kern Co 21.7719.28 19.26 19.2118.87 18.83 18.70California Kings Co 18.7716.82 16.80 16.7616.55 16.52 16.43California Lake Co5.034.73 4.72 4.724.73 4.73 4.72California Los Angeles Co 23.1620.69 20.64 20.6120.86 20.75 20.72California Mendocino Co 8.007.22 7.21 7.217.20 7.19 7.18California Merced Co 16.4715.15 15.14 15.1115.11 15.08 15.02California Monterey Co 8.237.74 7.73 7.727.75 7.74 7.73California Nevada Co 7.977.25 7.25 7.237.31 7.31 7.26California Orange Co 18.2715.73 15.60 15.5815.93 15.68 15.65California Placer Co 11.6510.21 10.20 10.1710.07 10.04 9.97California Riverside Co 27.1522.67 22.53 22.4822.54 22.21 22.13California Sacramento Co 12.5611.47 11.46 11.4311.36 11.33 11.27California San Bernardino Co 24.6321.79 21.69 21.6621.97 21.75 21.71California San Diego Co 15.6514.64 14.61 14.6014.91 14.83 14.82California San Francisco Co 11.5811.08 10.94 10.9311.58 11.27 11.26California San Joaquin Co 14.8413.58 13.54 13.5113.57 13.48 13.41California San Luis Obispo Co 9.208.79 8.79 8.788.85 8.84 8.82California San Mateo Co 10.589.77 9.76 9.749.70 9.68 9.65California Santa Barbara Co 9.329.06 9.05 9.059.12 9.10 9.09California Santa Clara Co 11.3310.10 10.09 10.089.95 9.93 9.91California Santa Cruz Co 8.177.38 7.38 7.377.30 7.29 7.28California Shasta Co 9.017.74 7.74 7.737.76 7.76 7.73California Solano Co 12.0311.64 11.58 11.5711.88 11.76 11.74California Sonoma Co 9.919.22 9.21 9.219.21 9.21 9.20California Stanislaus Co 16.4914.57 14.54 14.5014.30 14.23 14.13California Sutter Co 11.3910.14 10.13 10.1010.07 10.06 9.98California Tulare Co 21.3318.71 18.69 18.6418.24 18.19 18.07California Ventura Co 14.3412.54 12.45 12.4412.59 12.40 12.38California Yolo Co 10.049.11 9.10 9.088.99 8.97 8.92Colorado Adams Co 10.298.91 8.91 8.878.80 8.80 8.74**30**Colorado Arapahoe Co 8.707.76 7.76 7.747.80 7.80 7.75Colorado Archuleta Co 5.995.55 5.55 5.555.54 5.54 5.54Colorado Boulder Co 9.278.20 8.19 8.178.19 8.19 8.14Colorado Delta Co8.267.44 7.44 7.427.40 7.40 7.35Colorado Denver Co 10.589.22 9.22 9.199.12 9.11 9.06Colorado El Paso Co 7.867.16 7.16 7.147.14 7.14 7.09Colorado Elbert Co 4.333.92 3.92 3.913.98 3.98 3.95Colorado Gunnison Co 6.696.26 6.26 6.266.25 6.25 6.25Colorado Larimer Co 7.887.21 7.21 7.197.16 7.16 7.13Colorado Pueblo Co 7.797.16 7.16 7.137.16 7.16 7.11Colorado Routt Co 7.406.98 6.98 6.986.96 6.96 6.94Colorado San Miguel Co 5.334.99 4.99 4.994.98 4.98 4.97Colorado Weld Co9.338.14 8.14 8.108.16 8.16 8.08Connecticut Fairfield Co 12.8511.39 11.38 11.3711.54 11.52 11.51Connecticut Hartford Co 11.509.84 9.84 9.849.86 9.85 9.85Connecticut New Haven Co 13.7111.48 11.47 11.4611.52 11.48 11.48Connecticut New London Co 11.579.60 9.60 9.609.66 9.65 9.64Delaware Kent Co 12.819.54 9.53 9.529.61 9.58 9.56Delaware New Castle Co 15.9612.35 12.33 12.3012.52 12.46 12.42Delaware Sussex Co 13.6510.52 10.51 10.5010.54 10.52 10.50District ofColumbia District of Columbia 15.7511.72 11.71 11.6911.73 11.73 11.69Florida Alachua Co 10.127.71 7.71 7.717.70 7.70 7.69Florida Bay Co11.049.01 8.98 8.989.03 8.98 8.97Florida Brevard Co 7.885.65 5.64 5.645.65 5.64 5.64Florida Broward Co 8.306.29 6.23 6.236.40 6.27 6.26Florida Citrus Co 9.136.73 6.73 6.726.73 6.72 6.72Florida Duval Co 10.648.49 8.43 8.438.62 8.49 8.48Florida Escambia Co 11.569.63 9.62 9.629.63 9.62 9.60Florida Hillsborough Co 11.258.40 8.31 8.308.57 8.38 8.37Florida Lee Co8.426.10 6.10 6.106.08 6.08 6.08Florida Leon Co 12.6710.19 10.18 10.1610.13 10.12 10.08Florida Manatee Co 9.316.56 6.55 6.556.57 6.55 6.54Florida Marion Co 10.047.56 7.56 7.567.54 7.54 7.53Florida Miami-Dade Co 9.667.51 7.39 7.397.60 7.37 7.36Florida Orange Co 10.197.37 7.37 7.377.39 7.39 7.39Florida Palm Beach Co 7.545.75 5.75 5.755.80 5.79 5.79Florida Pinellas Co 10.467.84 7.83 7.827.84 7.83 7.82Florida Polk Co 10.367.49 7.49 7.497.52 7.51 7.50**31**Florida Sarasota Co 9.286.70 6.70 6.706.69 6.68 6.68Florida Seminole Co 9.316.63 6.62 6.626.61 6.61 6.60Florida St. Lucie Co 8.616.26 6.26 6.266.26 6.26 6.25Florida Volusia Co 9.286.73 6.73 6.736.72 6.72 6.72Georgia Bibb Co 15.6912.37 12.36 12.3412.33 12.33 12.28Georgia Chatham Co 13.8711.94 11.81 11.7912.10 11.82 11.80Georgia Clarke Co 15.7511.51 11.51 11.4911.46 11.46 11.42Georgia Clayton Co 16.4812.38 12.38 12.3612.35 12.35 12.30Georgia Cobb Co 16.2912.28 12.28 12.2612.26 12.25 12.20Georgia DeKalb Co 16.2212.43 12.43 12.4212.48 12.48 12.45Georgia Dougherty Co 14.2411.65 11.65 11.6411.62 11.61 11.59Georgia Floyd Co 15.7111.77 11.77 11.7411.76 11.75 11.70Georgia Fulton Co 18.2914.22 14.21 14.1814.27 14.26 14.21Georgia Glynn Co 11.899.67 9.63 9.629.71 9.61 9.60Georgia Gwinnett Co 16.2012.29 12.28 12.2712.21 12.20 12.18Georgia Hall Co15.1411.71 11.71 11.6911.70 11.70 11.67Georgia Houston Co 13.0410.15 10.15 10.1310.14 10.13 10.10Georgia Lowndes Co 12.149.85 9.85 9.839.82 9.82 9.78Georgia Muscogee Co 14.8612.15 12.15 12.1412.15 12.14 12.11Georgia Paulding Co 14.3010.48 10.48 10.4510.50 10.50 10.44Georgia Richmond Co 15.0512.13 12.13 12.1212.11 12.11 12.08Georgia Walker Co 15.4411.79 11.77 11.7411.79 11.76 11.71Georgia Washington Co 14.2111.09 11.08 11.0611.08 11.07 11.03Georgia Wilkinson Co 15.1511.77 11.77 11.7511.77 11.77 11.72Idaho Ada Co9.178.56 8.55 8.548.53 8.52 8.49Idaho Bannock Co 8.568.31 8.31 8.298.30 8.30 8.27Idaho Canyon Co 9.268.31 8.31 8.288.22 8.22 8.15Idaho Power Co 9.829.53 9.53 9.519.52 9.52 9.48Idaho Shoshone Co 12.7212.02 12.02 12.0111.99 11.98 11.96Illinois Adams Co 12.8810.63 10.61 10.5410.58 10.53 10.41Illinois Champaign Co 12.5610.26 10.25 10.2110.21 10.19 10.11Illinois Cook Co 17.0613.85 13.84 13.7413.79 13.75 13.57Illinois DuPage Co 14.3611.52 11.51 11.4211.46 11.43 11.28Illinois Kane Co 13.9311.27 11.26 11.1811.19 11.16 11.03Illinois Lake Co 12.5410.56 10.55 10.5110.59 10.56 10.47Illinois Macon Co 13.8711.29 11.28 11.2311.23 11.21 11.11Illinois Madison Co 17.2714.38 14.31 14.2714.53 14.36 14.27Illinois McHenry Co 12.7310.32 10.31 10.2710.28 10.26 10.16**32**Illinois McLean Co 13.4110.80 10.79 10.7410.73 10.70 10.61Illinois Peoria Co 13.8311.35 11.33 11.2911.27 11.23 11.15Illinois Randolph Co 12.419.78 9.76 9.719.78 9.73 9.65Illinois Rock Island Co 12.049.80 9.77 9.749.72 9.67 9.58Illinois Sangamon Co 13.1410.65 10.63 10.6010.55 10.52 10.44Illinois St. Clair Co 16.1913.36 13.29 13.2513.49 13.34 13.25Illinois Will Co14.5011.80 11.79 11.7011.82 11.79 11.63Illinois Winnebago Co 12.8710.56 10.55 10.5110.44 10.42 10.33Indiana Allen Co 14.2911.41 11.40 11.3511.35 11.32 11.23Indiana Clark Co 16.3312.96 12.92 12.9113.13 13.05 13.02Indiana Delaware Co 14.3411.08 11.06 11.0311.02 10.99 10.91Indiana Dubois Co 15.8412.46 12.44 12.4112.45 12.41 12.37Indiana Elkhart Co 14.9912.27 12.26 12.2112.21 12.18 12.08Indiana Floyd Co 14.9011.38 11.31 11.2911.52 11.38 11.34Indiana Henry Co 13.2610.08 10.07 10.0410.04 10.01 9.95Indiana Howard Co 14.5511.49 11.48 11.4411.43 11.40 11.33Indiana Knox Co 13.7510.60 10.58 10.5410.58 10.54 10.46Indiana La Porte Co 13.2510.88 10.86 10.8010.86 10.82 10.70Indiana Lake Co 15.0112.88 12.86 12.7512.87 12.83 12.64Indiana Madison Co 14.5411.21 11.20 11.1611.15 11.12 11.05Indiana Marion Co 16.5413.02 13.00 12.9712.94 12.91 12.83Indiana Porter Co 13.7511.48 11.46 11.3911.51 11.47 11.34Indiana Spencer Co 14.0210.67 10.64 10.6210.69 10.63 10.60Indiana St. Joseph Co 14.0811.43 11.42 11.3711.38 11.35 11.26Indiana Vanderburgh Co 15.2912.06 11.99 11.9612.09 11.96 11.90Indiana Vigo Co 14.5111.51 11.49 11.4311.43 11.40 11.30Iowa Black Hawk Co 11.169.25 9.25 9.219.14 9.12 9.04Iowa Clinton Co 12.069.75 9.73 9.679.69 9.65 9.53Iowa Emmet Co 8.827.31 7.30 7.277.21 7.20 7.13Iowa Johnson Co 11.439.44 9.43 9.399.37 9.35 9.26Iowa Linn Co 11.009.15 9.14 9.089.07 9.05 8.93Iowa Muscatine Co 12.8010.56 10.54 10.4910.50 10.45 10.35Iowa Polk Co 10.528.60 8.60 8.568.47 8.46 8.37Iowa Pottawattamie Co 10.438.72 8.71 8.668.64 8.63 8.53Iowa Scott Co 12.3310.00 9.97 9.939.92 9.87 9.78Iowa Van Buren Co 10.338.39 8.38 8.338.32 8.30 8.21Iowa Woodbury Co 10.078.46 8.46 8.418.38 8.38 8.28Kansas Johnson Co 11.549.59 9.59 9.539.52 9.51 9.41**33**Kansas Linn Co 10.668.92 8.92 8.868.90 8.89 8.78Kansas Sedgwick Co 11.069.58 9.58 9.559.53 9.52 9.47Kansas Shawnee Co 10.869.17 9.17 9.119.07 9.07 8.95Kansas Sumner Co 10.198.79 8.79 8.768.79 8.78 8.72Kansas Wyandotte Co 13.5511.42 11.41 11.3311.51 11.48 11.32Kentucky Bell Co14.6410.97 10.97 10.9410.97 10.96 10.92Kentucky Boyd Co 14.8811.41 11.34 11.3111.65 11.50 11.46Kentucky Bullitt Co 14.8811.43 11.41 11.3911.52 11.48 11.43Kentucky Campbell Co 14.0010.24 10.19 10.1510.31 10.22 10.15Kentucky Carter Co 12.188.84 8.83 8.808.89 8.85 8.81Kentucky Christian Co 13.4710.47 10.46 10.4410.49 10.46 10.43Kentucky Daviess Co 14.7011.52 11.49 11.4811.55 11.49 11.46Kentucky Fayette Co 15.6011.94 11.93 11.8911.72 11.70 11.64Kentucky Franklin Co 13.6710.03 10.01 9.9910.04 10.01 9.97Kentucky Hardin Co 13.9710.50 10.48 10.4610.51 10.49 10.45Kentucky Jefferson Co 16.5813.65 13.62 13.6113.92 13.87 13.84Kentucky Kenton Co 14.8811.03 10.99 10.9511.16 11.06 11.01Kentucky Laurel Co 12.208.89 8.88 8.858.88 8.87 8.81Kentucky Madison Co 13.539.86 9.85 9.819.93 9.91 9.84Kentucky McCracken Co 13.3910.61 10.59 10.5710.63 10.57 10.55Kentucky Perry Co 13.149.62 9.62 9.599.60 9.59 9.54Kentucky Pike Co 13.6710.02 10.01 9.9810.02 10.01 9.95Kentucky Warren Co 13.8110.55 10.54 10.5310.55 10.54 10.51Louisiana Caddo Parish 12.6310.77 10.76 10.7310.83 10.81 10.75Louisiana Calcasieu Parish 11.359.83 9.79 9.789.95 9.87 9.86Louisiana Concordia Parish 11.109.48 9.41 9.409.65 9.51 9.50Louisiana East Baton Rouge Parish 13.1111.99 11.72 11.7112.85 12.28 12.26Louisiana Iberville Parish 12.5511.41 11.20 11.1912.06 11.63 11.62Louisiana Jefferson Parish 12.1710.32 10.08 10.0710.87 10.37 10.35Louisiana Lafayette Parish 11.029.38 9.37 9.369.49 9.46 9.46Louisiana Orleans Parish 12.2310.13 10.02 10.0110.44 10.22 10.21Louisiana Ouachita Parish 11.469.80 9.79 9.769.84 9.81 9.77Louisiana St. Bernard Parish 10.698.74 8.66 8.658.94 8.76 8.74Louisiana Tangipahoa Parish 11.179.21 9.19 9.189.35 9.29 9.28Louisiana Terrebonne Parish 10.408.69 8.66 8.668.85 8.78 8.78Louisiana West Baton Rouge Parish 12.8111.72 11.46 11.4512.58 12.02 12.01Maine Androscoggin Co 10.739.40 9.40 9.409.38 9.38 9.38Maine Aroostook Co 11.2910.60 10.59 10.5910.59 10.59 10.59**34**Maine Cumberland Co 11.5910.27 10.21 10.2010.43 10.30 10.30Maine Hancock Co 6.255.37 5.37 5.375.39 5.38 5.38Maine Kennebec Co 10.499.12 9.12 9.129.10 9.10 9.10Maine Oxford Co 10.138.99 8.99 8.998.98 8.97 8.97Maine Penobscot Co 10.068.71 8.71 8.718.73 8.72 8.72Maryland Anne Arundel Co 15.3611.87 11.86 11.8411.96 11.94 11.91Maryland Baltimore city 16.6313.17 13.13 13.0913.38 13.30 13.22Maryland Baltimore Co 15.0111.15 11.14 11.1111.19 11.17 11.13Maryland Harford Co 13.019.67 9.67 9.649.71 9.69 9.65Maryland Montgomery Co 12.829.39 9.38 9.379.39 9.38 9.35Maryland Washington Co 14.2510.38 10.37 10.3410.36 10.35 10.29Massachusetts Berkshire Co 11.7210.46 10.45 10.4410.46 10.45 10.43Massachusetts Hampden Co 13.3011.59 11.59 11.5811.60 11.59 11.58Massachusetts Plymouth Co 10.869.02 9.02 9.019.12 9.11 9.10Massachusetts Suffolk Co 13.6811.79 11.77 11.7611.83 11.79 11.78Michigan Allegan Co 12.2910.14 10.13 10.1010.15 10.12 10.06Michigan Bay Co10.949.34 9.33 9.329.34 9.32 9.30Michigan Berrien Co 12.3510.07 10.06 10.0210.05 10.03 9.95Michigan Chippewa Co 8.097.45 7.44 7.447.49 7.49 7.48Michigan Genesee Co 12.3710.29 10.29 10.2610.23 10.22 10.18Michigan Ingham Co 13.1310.77 10.76 10.7310.75 10.73 10.67Michigan Kalamazoo Co 14.3811.78 11.77 11.7211.72 11.70 11.60Michigan Kent Co 13.5510.95 10.94 10.9010.84 10.82 10.75Michigan Macomb Co 13.1310.68 10.67 10.6510.67 10.65 10.60Michigan Monroe Co 14.9911.74 11.70 11.6511.78 11.71 11.60Michigan Muskegon Co 11.9910.06 10.06 10.0310.03 10.01 9.95Michigan Oakland Co 14.6411.73 11.72 11.6911.70 11.68 11.63Michigan Ottawa Co 13.1410.73 10.72 10.6910.67 10.65 10.58Michigan Saginaw Co 10.709.06 9.05 9.049.07 9.05 9.03Michigan St. Clair Co 13.7711.65 11.64 11.6211.68 11.66 11.62Michigan Washtenaw Co 14.3911.31 11.30 11.2711.30 11.27 11.21Michigan Wayne Co 19.3216.60 16.59 16.5516.59 16.56 16.49Minnesota Dakota Co 9.438.05 8.05 8.027.98 7.97 7.90Minnesota Hennepin Co 10.298.85 8.84 8.808.77 8.74 8.67Minnesota Mille Lacs Co 7.126.18 6.18 6.156.13 6.12 6.06Minnesota Olmsted Co 10.729.14 9.13 9.109.03 9.01 8.93Minnesota Ramsey Co 11.9110.19 10.15 10.1110.20 10.13 10.03Minnesota Scott Co9.988.48 8.47 8.448.40 8.38 8.31**35**Minnesota St. Louis Co 8.147.30 7.27 7.267.36 7.30 7.28Minnesota Stearns Co 9.217.93 7.92 7.887.86 7.85 7.77Mississippi Adams Co 11.209.34 9.29 9.289.49 9.38 9.37Mississippi Bolivar Co 12.5610.74 10.72 10.7110.79 10.75 10.73Mississippi DeSoto Co 12.6010.23 10.22 10.1810.34 10.32 10.25Mississippi Forrest Co 13.3711.04 11.03 11.0011.07 11.04 10.99Mississippi Hancock Co 10.348.33 8.32 8.308.42 8.39 8.36Mississippi Harrison Co 11.579.59 9.53 9.529.75 9.62 9.61Mississippi Hinds Co 13.3811.19 11.18 11.1411.22 11.20 11.14Mississippi Jackson Co 11.849.75 9.66 9.659.97 9.76 9.75Mississippi Jones Co 14.4811.81 11.80 11.7711.87 11.84 11.79Mississippi Lauderdale Co 13.1610.57 10.57 10.5410.60 10.59 10.54Mississippi Lee Co12.489.98 9.97 9.959.99 9.97 9.94Mississippi Lowndes Co 13.3610.75 10.74 10.7310.75 10.74 10.71Mississippi Pearl River Co 11.709.59 9.57 9.559.66 9.62 9.58Mississippi Rankin Co 13.1010.94 10.93 10.8910.97 10.95 10.89Mississippi Scott Co 11.829.56 9.55 9.529.61 9.59 9.53Mississippi Warren Co 12.2610.61 10.45 10.4410.97 10.62 10.60Missouri Cass Co 11.229.33 9.33 9.269.31 9.30 9.17Missouri Cedar Co 11.459.38 9.37 9.339.35 9.33 9.25Missouri Clay Co 11.739.74 9.74 9.679.72 9.70 9.57Missouri Greene Co 12.1110.08 10.08 10.0410.04 10.03 9.96Missouri Jefferson Co 14.4311.90 11.88 11.8511.92 11.88 11.81Missouri Monroe Co 11.038.94 8.93 8.888.89 8.87 8.78Missouri St. Charles Co 14.0811.43 11.40 11.3611.46 11.39 11.31Missouri St. Louis city 15.1612.45 12.38 12.3412.57 12.42 12.34Missouri St. Louis Co 14.0211.46 11.44 11.4111.46 11.42 11.35Missouri Ste. Genevieve Co 13.6610.94 10.90 10.8610.98 10.88 10.80Montana Cascade Co 5.705.26 5.26 5.255.25 5.25 5.23Montana Flathead Co 10.019.36 9.36 9.329.34 9.34 9.25Montana Gallatin Co 8.407.96 7.96 7.957.94 7.93 7.93Montana Lake Co9.418.69 8.69 8.688.66 8.66 8.64Montana Lincoln Co 15.8514.72 14.71 14.5514.66 14.65 14.34Montana Missoula Co 10.209.39 9.39 9.399.38 9.37 9.35Montana Rosebud Co 6.786.55 6.55 6.546.54 6.54 6.51Montana Sanders Co 6.486.17 6.17 6.166.15 6.15 6.14Montana Silver Bow Co 8.307.61 7.61 7.617.59 7.59 7.58Montana Yellowstone Co 7.436.86 6.86 6.856.86 6.86 6.84**36**Nebraska Cass Co 10.268.61 8.61 8.558.58 8.58 8.47Nebraska Douglas Co 10.558.82 8.82 8.788.72 8.72 8.62Nebraska Lancaster Co 9.588.06 8.06 8.018.01 8.01 7.92Nebraska Lincoln Co 7.136.30 6.30 6.176.26 6.26 6.06Nebraska Sarpy Co 10.078.44 8.43 8.388.43 8.42 8.32Nebraska Scotts Bluff Co 5.965.41 5.41 5.335.38 5.38 5.25Nebraska Washington Co 9.718.15 8.15 8.108.09 8.09 7.99Nevada Clark Co9.518.74 8.74 8.738.68 8.68 8.66Nevada Washoe Co 8.868.32 8.32 8.308.26 8.26 8.22New Hampshire Belknap Co 7.155.96 5.96 5.955.96 5.96 5.95New Hampshire Cheshire Co 11.6810.07 10.07 10.0710.08 10.08 10.07New Hampshire Coos Co9.688.78 8.78 8.788.77 8.76 8.76New Hampshire Hillsborough Co 10.338.77 8.77 8.768.77 8.76 8.76New Hampshire Rockingham Co 9.498.05 8.03 8.028.13 8.08 8.08New Hampshire Sullivan Co 9.868.44 8.44 8.448.45 8.45 8.44New Jersey Atlantic Co 11.418.79 8.78 8.778.86 8.84 8.83New Jersey Bergen Co 13.6510.94 10.92 10.9111.01 10.97 10.94New Jersey Camden Co 14.3111.12 11.04 11.0311.33 11.16 11.14New Jersey Essex Co 13.6810.75 10.72 10.7010.84 10.77 10.74New Jersey Gloucester Co 13.6810.45 10.39 10.3810.72 10.58 10.56New Jersey Hudson Co 14.9312.48 12.33 12.3112.88 12.55 12.52New Jersey Mercer Co 13.9110.74 10.72 10.7110.87 10.83 10.81New Jersey Middlesex Co 12.469.52 9.51 9.509.58 9.56 9.55New Jersey Morris Co 12.389.52 9.52 9.519.59 9.57 9.55New Jersey Ocean Co 11.168.57 8.57 8.568.62 8.61 8.60New Jersey Passaic Co 13.0910.26 10.25 10.2310.30 10.27 10.25New Jersey Union Co 15.6612.40 12.32 12.2912.68 12.49 12.46New Jersey Warren Co 13.3610.03 10.03 10.0110.06 10.04 10.02New Mexico Bernalillo Co 6.556.03 6.03 6.026.02 6.02 6.01New Mexico Chaves Co 6.706.17 6.17 6.166.17 6.17 6.16New Mexico Dona Ana Co 11.2910.29 10.29 10.2310.14 10.14 10.06New Mexico Grant Co 6.135.84 5.84 5.845.84 5.84 5.83New Mexico Lea Co6.756.13 6.13 6.126.12 6.12 6.12New Mexico San Juan Co 6.496.14 6.14 6.146.14 6.14 6.13New Mexico Sandoval Co 4.984.59 4.59 4.584.58 4.58 4.57New Mexico Santa Fe Co 4.934.59 4.59 4.584.60 4.60 4.60New York Bronx Co 15.7813.01 12.98 12.9713.05 12.99 12.97New York Chautauqua Co 10.718.17 8.16 8.148.16 8.14 8.10**37**New York Erie Co13.9011.07 11.05 11.0210.98 10.94 10.88New York Essex Co 6.395.48 5.47 5.475.49 5.49 5.49New York Kings Co 14.6512.06 12.02 12.0112.20 12.13 12.11New York Nassau Co 12.219.86 9.85 9.8410.00 9.97 9.95New York New York Co 17.1614.35 14.34 14.3314.37 14.33 14.31New York Niagara Co 12.039.85 9.84 9.839.93 9.91 9.89New York Onondaga Co 10.5610.13 10.13 10.1010.11 10.10 10.06New York Orange Co 11.509.95 9.94 9.9310.02 10.01 9.99New York Queens Co 13.2310.76 10.75 10.7510.96 10.94 10.93New York Richmond Co 12.1310.80 10.73 10.7210.97 10.83 10.81New York St. Lawrence Co 8.497.78 7.77 7.777.77 7.76 7.75New York Steuben Co 9.837.42 7.42 7.427.43 7.42 7.41New York Suffolk Co 12.1110.05 10.04 10.0310.65 10.63 10.62New York Westchester Co 12.3310.06 10.05 10.0410.32 10.29 10.27North Carolina Alamance Co 13.9310.15 10.14 10.1310.12 10.12 10.10North Carolina Buncombe Co 13.199.95 9.95 9.939.90 9.90 9.86North Carolina Cabarrus Co 14.6810.75 10.74 10.7210.76 10.75 10.72North Carolina Caswell Co 13.439.61 9.61 9.609.62 9.61 9.59North Carolina Catawba Co 15.6011.52 11.52 11.5011.47 11.47 11.43North Carolina Chatham Co 12.349.00 9.00 8.999.04 9.03 9.02North Carolina Cumberland Co 14.1710.81 10.80 10.7910.78 10.77 10.74North Carolina Davidson Co 15.9411.96 11.96 11.9312.01 12.01 11.97North Carolina Duplin Co 12.089.35 9.34 9.349.36 9.35 9.34North Carolina Durham Co 14.0910.44 10.44 10.4310.38 10.38 10.36North Carolina Forsyth Co 14.7910.96 10.96 10.9510.92 10.92 10.90North Carolina Gaston Co 14.2310.55 10.55 10.5310.55 10.55 10.52North Carolina Guilford Co 14.2710.25 10.25 10.2410.22 10.21 10.19North Carolina Haywood Co 13.4810.58 10.58 10.5710.57 10.56 10.55North Carolina Jackson Co 12.279.32 9.32 9.329.33 9.33 9.32North Carolina Lenoir Co 11.578.84 8.83 8.838.86 8.85 8.84North Carolina McDowell Co 14.4110.72 10.72 10.6910.71 10.71 10.65North Carolina Mecklenburg Co 15.1912.48 12.48 12.4812.89 12.89 12.87North Carolina Mitchell Co 13.5610.22 10.22 10.1910.23 10.22 10.17North Carolina Montgomery Co 12.409.08 9.08 9.079.09 9.09 9.06North Carolina Onslow Co 11.278.66 8.66 8.658.66 8.65 8.64North Carolina Orange Co 13.249.82 9.82 9.819.81 9.81 9.80North Carolina Pitt Co12.409.85 9.85 9.849.88 9.88 9.86North Carolina Robeson Co 12.6910.06 10.06 10.0510.05 10.05 10.03**38**North Carolina Swain Co 12.679.52 9.52 9.519.52 9.51 9.50North Carolina Wake Co 13.9610.85 10.85 10.8410.97 10.96 10.95North Carolina Watauga Co 11.558.30 8.30 8.298.28 8.28 8.27North Carolina Wayne Co 13.7610.83 10.83 10.8210.83 10.83 10.81North Dakota Billings Co 4.574.27 4.27 4.234.26 4.26 4.20North Dakota Burke Co 5.744.36 4.36 4.364.34 4.34 4.33North Dakota Burleigh Co 6.635.89 5.89 5.865.85 5.85 5.80North Dakota Cass Co7.786.65 6.65 6.616.56 6.56 6.48North Dakota McKenzie Co 5.264.82 4.82 4.814.81 4.81 4.79North Dakota Mercer Co 6.204.98 4.98 4.974.96 4.96 4.93Ohio Athens Co 12.318.70 8.68 8.678.74 8.70 8.67Ohio Butler Co 16.1212.68 12.66 12.6212.68 12.64 12.57Ohio Clark Co 14.6911.20 11.18 11.1611.21 11.18 11.12Ohio Cuyahoga Co 18.3614.52 14.44 14.3914.60 14.42 14.34Ohio Franklin Co 16.5212.50 12.49 12.4412.41 12.38 12.29Ohio Hamilton Co 17.7613.35 13.32 13.2713.37 13.30 13.21Ohio Jefferson Co 17.4813.38 13.33 13.3113.42 13.32 13.28Ohio Lake Co 13.2510.49 10.45 10.4210.54 10.46 10.40Ohio Lawrence Co 15.7012.55 12.48 12.4212.67 12.52 12.43Ohio Lorain Co 13.6010.47 10.40 10.3610.59 10.44 10.37Ohio Lucas Co 14.7011.51 11.43 11.3611.51 11.34 11.22Ohio Mahoning Co 15.1111.18 11.16 11.1211.17 11.13 11.06Ohio Montgomery Co 15.7312.09 12.08 12.0512.01 11.99 11.94Ohio Portage Co 14.1910.72 10.71 10.6710.74 10.71 10.64Ohio Preble Co 13.3410.07 10.06 10.0310.11 10.08 10.03Ohio Scioto Co 17.1113.07 13.04 12.9713.13 13.05 12.95Ohio Stark Co 17.2613.16 13.14 13.1013.11 13.08 13.00Ohio Summit Co 16.4212.61 12.60 12.5712.61 12.59 12.54Ohio Trumbull Co 14.9611.40 11.39 11.3611.40 11.37 11.31Oklahoma Caddo Co 8.797.30 7.30 7.287.31 7.31 7.28Oklahoma Canadian Co 8.967.45 7.45 7.437.48 7.48 7.44Oklahoma Carter Co 10.108.27 8.27 8.258.29 8.28 8.24Oklahoma Cherokee Co 11.569.66 9.65 9.639.66 9.65 9.61Oklahoma Garfield Co 9.858.58 8.58 8.558.56 8.56 8.51Oklahoma Kay Co10.649.43 9.43 9.409.44 9.44 9.38Oklahoma Lincoln Co 9.968.34 8.34 8.328.37 8.36 8.33Oklahoma Mayes Co 11.8710.13 10.12 10.0810.12 10.11 10.04Oklahoma Muskogee Co 12.0510.26 10.25 10.2110.25 10.24 10.17**39**Oklahoma Oklahoma Co 10.448.49 8.49 8.478.42 8.41 8.37Oklahoma Ottawa Co 11.739.66 9.66 9.639.65 9.64 9.58Oklahoma Pittsburg Co 11.379.56 9.55 9.519.57 9.56 9.49Oklahoma Seminole Co 9.648.04 8.04 8.028.06 8.05 8.03Oklahoma Tulsa Co 11.739.87 9.86 9.849.85 9.84 9.80Oregon Columbia Co 6.295.87 5.84 5.835.99 5.94 5.91Oregon Jackson Co 11.3910.68 10.68 10.6710.67 10.66 10.66Oregon Klamath Co 10.6910.09 10.09 10.0710.07 10.06 10.02Oregon Lane Co 13.2812.51 12.51 12.4412.48 12.47 12.29Oregon Linn Co8.237.90 7.90 7.897.90 7.90 7.89Oregon Multnomah Co 8.678.31 8.24 8.238.51 8.36 8.34Oregon Wasco Co 7.537.03 7.01 6.987.01 6.98 6.90Oregon Washington Co 7.777.39 7.37 7.377.44 7.39 7.39Pennsylvania Adams Co 13.319.37 9.36 9.349.36 9.35 9.31Pennsylvania Allegheny Co 20.9916.21 16.08 16.0316.34 16.06 15.98Pennsylvania Beaver Co 15.7911.97 11.95 11.9012.00 11.95 11.88Pennsylvania Berks Co 16.4112.25 12.24 12.2112.26 12.23 12.17Pennsylvania Bucks Co 14.1011.04 11.01 11.0011.35 11.27 11.25Pennsylvania Cambria Co 15.6211.47 11.46 11.4211.47 11.45 11.38Pennsylvania Centre Co 12.959.38 9.37 9.359.37 9.36 9.32Pennsylvania Chester Co 14.8010.74 10.72 10.7010.79 10.75 10.70Pennsylvania Cumberland Co 14.9310.88 10.87 10.8410.83 10.82 10.76Pennsylvania Dauphin Co 15.5711.17 11.16 11.1211.12 11.10 11.01Pennsylvania Delaware Co 15.3111.91 11.80 11.7812.26 12.03 11.99Pennsylvania Erie Co13.1410.18 10.16 10.1310.18 10.14 10.08Pennsylvania Lackawanna Co 12.329.17 9.16 9.159.14 9.13 9.10Pennsylvania Lancaster Co 16.9512.01 12.00 11.9611.99 11.96 11.89Pennsylvania Lehigh Co 14.2110.68 10.67 10.6510.66 10.64 10.60Pennsylvania Luzerne Co 12.709.45 9.45 9.449.43 9.42 9.39Pennsylvania Mercer Co 14.0010.48 10.47 10.4410.48 10.45 10.40Pennsylvania Montgomery Co 13.7410.36 10.35 10.3310.55 10.52 10.49Pennsylvania Northampton Co 14.3310.86 10.85 10.8310.84 10.82 10.78Pennsylvania Perry Co 12.839.49 9.48 9.429.51 9.49 9.40Pennsylvania Philadelphia Co 15.9712.73 12.63 12.6113.00 12.76 12.74Pennsylvania Washington Co 15.3711.14 11.11 11.0711.31 11.24 11.17Pennsylvania Westmoreland Co 15.3810.77 10.76 10.7210.77 10.74 10.68Pennsylvania York Co 16.9212.53 12.52 12.4912.51 12.48 12.42Rhode Island Kent Co8.626.98 6.98 6.977.03 7.03 7.02**40**Rhode Island Providence Co 12.6010.57 10.56 10.5610.61 10.60 10.59South Carolina Beaufort Co 10.918.52 8.51 8.518.54 8.52 8.51South Carolina Charleston Co 11.809.23 9.22 9.219.24 9.22 9.20South Carolina Chesterfield Co 12.379.34 9.34 9.339.34 9.33 9.31South Carolina Edgefield Co 12.719.57 9.57 9.559.57 9.57 9.53South Carolina Florence Co 12.6610.20 10.20 10.1910.18 10.17 10.16South Carolina Georgetown Co 12.7510.28 10.25 10.2410.32 10.25 10.24South Carolina Greenville Co 15.7311.94 11.94 11.9211.89 11.89 11.87South Carolina Greenwood Co 13.369.99 9.99 9.969.98 9.97 9.93South Carolina Horry Co 11.228.79 8.78 8.788.78 8.77 8.76South Carolina Lexington Co 13.8710.62 10.62 10.6010.57 10.56 10.54South Carolina Oconee Co 10.767.72 7.71 7.717.70 7.70 7.68South Carolina Richland Co 13.8610.65 10.65 10.6310.60 10.59 10.56South Carolina Spartanburg Co 13.8210.30 10.30 10.2810.29 10.29 10.26South Dakota Brookings Co 9.448.05 8.05 8.037.97 7.97 7.91South Dakota Brookings Co 9.448.04 8.04 8.027.95 7.95 7.91South Dakota Brown Co 8.227.17 7.17 7.157.10 7.10 7.06South Dakota Brown Co 8.227.14 7.14 7.127.06 7.06 7.02South Dakota Jackson Co 5.445.06 5.06 5.045.04 5.04 5.02South Dakota Jackson Co 5.445.06 5.06 5.055.05 5.05 5.03South Dakota Meade Co 6.285.87 5.87 5.865.84 5.84 5.83South Dakota Meade Co 6.285.87 5.87 5.875.85 5.85 5.84South Dakota Minnehaha Co 9.848.12 8.12 8.098.02 8.01 7.95South Dakota Minnehaha Co 9.848.12 8.12 8.108.01 8.01 7.96South Dakota Pennington Co 7.557.05 7.05 7.047.02 7.02 7.01South Dakota Pennington Co 7.557.05 7.05 7.057.03 7.02 7.01Tennessee Blount Co 14.3610.86 10.86 10.8410.92 10.90 10.87Tennessee Davidson Co 14.4411.25 11.23 11.2111.30 11.26 11.22Tennessee Dyer Co 12.059.77 9.75 9.739.80 9.77 9.73Tennessee Hamilton Co 16.3412.58 12.56 12.5312.58 12.55 12.49Tennessee Knox Co 16.6712.58 12.57 12.5312.51 12.49 12.43Tennessee Lawrence Co 11.949.12 9.11 9.109.14 9.13 9.12Tennessee Maury Co 12.9010.78 10.78 10.7710.80 10.79 10.76Tennessee McMinn Co 14.8510.89 10.89 10.8610.88 10.87 10.81Tennessee Montgomery Co 13.2110.40 10.39 10.3810.43 10.40 10.37Tennessee Putnam Co 13.4310.00 9.99 9.989.98 9.97 9.95Tennessee Roane Co 14.3110.44 10.43 10.3810.47 10.44 10.36Tennessee Shelby Co 14.1211.68 11.60 11.5611.84 11.65 11.59**41**Tennessee Sullivan Co 14.5912.12 12.12 12.1012.06 12.05 12.02Tennessee Sumner Co 13.5810.45 10.44 10.4210.47 10.44 10.41Texas Bowie Co 13.6711.60 11.59 11.5511.59 11.57 11.50Texas Brewster Co 4.984.52 4.52 4.514.52 4.52 4.51Texas Cameron Co 9.888.79 8.78 8.788.80 8.79 8.78Texas Dallas Co 13.6711.35 11.35 11.3411.43 11.42 11.41Texas Ector Co7.676.76 6.76 6.766.77 6.77 6.76Texas Galveston Co 9.797.96 7.86 7.868.19 7.98 7.98Texas Gregg Co 12.3710.36 10.35 10.3310.40 10.38 10.36Texas Harris Co 14.2212.88 12.51 12.5013.61 12.81 12.80Texas Harrison Co 11.469.52 9.51 9.499.57 9.55 9.52Texas Hidalgo Co 10.819.67 9.67 9.669.65 9.65 9.64Texas Jefferson Co 11.209.91 9.73 9.7310.35 9.97 9.96Texas Montgomery Co 11.239.70 9.69 9.689.84 9.81 9.80Texas Nueces Co 10.028.54 8.50 8.498.73 8.51 8.51Texas Orange Co 11.439.66 9.64 9.639.79 9.75 9.73Texas Potter Co 6.175.27 5.27 5.255.26 5.26 5.23Texas Tarrant Co 12.7310.63 10.63 10.6010.65 10.65 10.60Utah Box Elder Co 9.148.65 8.64 8.648.64 8.64 8.62Utah Cache Co 12.8211.89 11.89 11.8811.85 11.85 11.83Utah Salt Lake Co 12.8911.81 11.81 11.7811.63 11.62 11.55Utah Utah Co 10.899.80 9.80 9.789.87 9.86 9.80Utah Weber Co 12.8111.78 11.78 11.7611.84 11.84 11.78Vermont Chittenden Co 9.387.96 7.96 7.957.91 7.91 7.89Virginia Arlington Co 14.6110.72 10.72 10.7010.66 10.65 10.63Virginia Bristol city 14.5110.99 10.98 10.9610.92 10.92 10.88Virginia Charles City Co 12.809.33 9.32 9.309.35 9.34 9.30Virginia Chesterfield Co 13.739.73 9.72 9.709.73 9.72 9.67Virginia Fairfax Co 14.1510.34 10.34 10.3210.37 10.37 10.34Virginia Hampton city 12.519.82 9.73 9.729.96 9.77 9.76Virginia Henrico Co 13.8010.04 10.03 9.9910.05 10.04 9.98Virginia Loudoun Co 13.639.71 9.70 9.689.75 9.74 9.70Virginia Norfolk city 12.9710.56 10.38 10.3710.84 10.44 10.43Virginia Page Co 12.969.24 9.24 9.229.25 9.25 9.23Virginia Roanoke city 14.3610.51 10.51 10.4110.45 10.45 10.30Virginia Salem city 14.7810.93 10.93 10.8610.90 10.90 10.79Virginia Virginia Beach city 12.589.98 9.96 9.9510.03 9.98 9.97Washington Clark Co9.748.77 8.76 8.758.86 8.84 8.82**42**Washington King Co 11.3710.84 10.72 10.7111.06 10.82 10.80Washington Pierce Co 10.9210.66 10.65 10.6410.72 10.70 10.69Washington Snohomish Co 11.2011.14 11.13 11.1211.21 11.18 11.16Washington Spokane Co 10.199.09 9.09 9.069.07 9.07 9.02Washington Yakima Co 10.389.08 9.08 9.079.06 9.05 9.04West Virginia Berkeley Co 16.2312.35 12.35 12.3112.33 12.32 12.25West Virginia Brooke Co 16.6912.70 12.65 12.6312.74 12.64 12.61West Virginia Cabell Co 16.5413.07 13.04 13.0013.33 13.25 13.20West Virginia Hancock Co 17.3013.65 13.61 13.5913.68 13.60 13.56West Virginia Harrison Co 13.9910.28 10.28 10.2710.29 10.28 10.27West Virginia Kanawha Co 17.0813.32 13.30 13.2713.37 13.31 13.28West Virginia Marion Co 15.3211.25 11.24 11.2311.25 11.23 11.21West Virginia Marshall Co 15.6111.47 11.42 11.4011.55 11.43 11.41West Virginia Mercer Co 12.679.20 9.20 9.189.26 9.26 9.22West Virginia Monongalia Co 14.8110.44 10.43 10.4210.44 10.42 10.40West Virginia Ohio Co 15.0811.03 10.98 10.9711.06 10.97 10.94West Virginia Raleigh Co 13.059.55 9.55 9.539.55 9.54 9.52West Virginia Summers Co 10.107.19 7.19 7.177.20 7.19 7.16West Virginia Wood Co 16.0711.82 11.77 11.7511.89 11.79 11.76Wisconsin Brown Co 11.279.91 9.90 9.889.87 9.86 9.81Wisconsin Dane Co 12.3610.50 10.49 10.4610.45 10.42 10.35Wisconsin Dodge Co 11.129.24 9.23 9.199.20 9.18 9.11Wisconsin Grant Co 11.369.45 9.44 9.389.38 9.35 9.24Wisconsin Kenosha Co 11.509.54 9.53 9.499.57 9.55 9.47Wisconsin Manitowoc Co 9.818.25 8.25 8.228.24 8.22 8.16Wisconsin Milwaukee Co 13.1011.08 11.07 11.0311.10 11.08 10.99Wisconsin Outagamie Co 10.709.17 9.17 9.149.16 9.14 9.08Wisconsin Vilas Co6.405.63 5.62 5.615.61 5.60 5.57Wisconsin Waukesha Co 13.1111.01 11.00 10.9710.99 10.97 10.88Wyoming Campbell Co 6.306.09 6.09 6.076.09 6.09 6.04Wyoming Converse Co 3.663.51 3.51 3.493.50 3.50 3.47Wyoming Fremont Co 9.128.38 8.38 8.388.37 8.37 8.36Wyoming Laramie Co 4.954.57 4.57 4.534.57 4.57 4.49Wyoming Sheridan Co 10.499.87 9.87 9.799.82 9.82 9.69**43**Appendix B: 8-Hour OzoneDesign Values for Locomotive/Marine Scenarios (units are ppb)State Name County Name Baseline DV 2020 Base 2020 Marine only 2020 Locomotive/ Marine2030 Base 2030 Marine only 2030 Locomotive/ MarineAlabama Baldwin78.066.1 65.8 65.767.0 66.3 65.9Alabama Clay79.357.7 57.6 57.356.3 56.1 55.3Alabama Elmore76.755.9 55.8 55.453.9 53.7 52.7Alabama Etowah75.055.2 55.1 54.853.8 53.6 52.8Alabama Jefferson 83.760.8 60.7 60.358.9 58.7 57.5Alabama Lawrence 76.356.2 56.0 55.754.9 54.6 53.8Alabama Madison79.758.8 58.6 58.356.9 56.4 55.7Alabama Mobile79.066.6 66.3 66.267.6 66.9 66.5Alabama Montgomery 75.055.7 55.6 55.354.0 53.9 52.9Alabama Morgan82.061.8 61.6 61.360.6 60.1 59.2Alabama Shelby88.062.6 62.6 62.160.6 60.4 59.1Alabama Sumter71.752.3 52.2 52.051.2 50.9 50.2Alabama Tuscaloosa 75.553.3 53.2 52.951.8 51.5 50.5Arizona Maricopa 85.771.8 71.7 71.669.3 69.2 68.6Arizona Pima74.064.5 64.4 64.363.0 63.0 62.6Arizona Pinal82.066.5 66.4 66.264.6 64.5 63.9Arizona Yavapai78.767.8 67.5 67.366.0 65.4 64.9Arkansas Crittenden 91.070.9 70.1 69.770.3 68.4 67.4Arkansas Pulaski81.763.1 62.8 62.561.3 60.7 59.6California Alameda 82.772.6 72.3 72.170.0 69.2 68.8California Amador85.771.6 71.3 71.067.9 67.1 66.4California Butte88.773.1 72.9 72.568.7 68.3 67.1California Calaveras 91.076.8 76.4 76.173.4 72.4 71.6California Colusa73.361.5 61.3 61.158.4 58.1 57.5California Contra Costa 79.372.9 72.7 72.671.1 70.4 70.1California El Dorado 105.086.2 86.0 85.680.7 80.2 78.9California Fresno110.096.1 95.9 95.692.4 92.0 91.0California Glenn72.361.2 61.1 60.958.3 58.0 57.4California Imperial86.074.8 74.5 74.372.8 72.1 71.5California Inyo80.771.4 71.3 71.169.5 69.1 68.6California Kern114.3100.9 100.8 100.697.6 97.4 96.7California Kings95.781.5 81.3 81.177.8 77.4 76.8California Lake64.356.2 56.2 56.154.5 54.3 54.0California Los Angeles 121.3109.0 108.8 108.7105.5 104.7 104.4**44**California Madera91.079.5 79.3 79.076.5 76.1 75.3California Marin48.042.1 42.1 42.140.8 40.9 40.8California Mariposa 89.776.3 75.9 75.773.2 72.2 71.7California Mendocino 56.747.9 47.8 47.745.6 45.4 45.0California Merced101.784.9 84.6 84.480.6 79.9 79.2California Monterey 66.057.2 57.1 57.054.9 54.6 54.3California Napa64.753.3 53.1 53.050.7 50.3 50.0California Nevada97.780.4 80.2 79.775.8 75.2 73.8California Orange85.376.7 79.2 79.376.3 81.5 81.8California Placer98.380.7 80.5 80.275.6 75.0 73.9California Riverside 115.0103.1 103.5 103.5101.9 102.5 102.4California Sacramento 99.082.1 81.9 81.676.8 76.2 75.3California San Benito 81.069.6 69.4 69.366.6 66.2 65.8California San Bernardino 128.7124.7 125.3 125.1123.0 123.9 123.4California San Diego 92.380.5 80.2 80.178.0 77.2 76.9California San Joaquin 81.071.0 70.7 70.568.6 67.7 67.3California San Luis Obispo 73.363.1 63.0 62.860.5 60.2 59.8California San Mateo 56.752.5 52.5 52.451.4 51.2 51.0California Santa Barbara 82.772.7 71.1 70.970.5 66.3 65.9California Santa Clara 84.070.1 70.0 69.966.4 66.1 65.7California Santa Cruz 65.057.1 57.0 56.955.0 54.8 54.5California Shasta72.360.8 60.7 60.457.7 57.5 56.6California Solano70.359.9 59.7 59.657.8 57.5 57.2California Sonoma62.050.7 50.6 50.547.6 47.5 47.1California Stanislaus 95.081.9 81.6 81.578.4 77.7 77.1California Sutter87.372.2 72.0 71.868.3 67.8 67.0California Tehama84.069.7 69.6 69.166.0 65.8 64.4California Tulare105.788.8 88.6 88.484.6 84.1 83.4California Tuolumne 91.077.3 76.9 76.774.0 73.0 72.4California Ventura94.781.5 80.9 80.878.7 77.0 76.7California Yolo81.768.3 68.1 67.964.6 64.2 63.6Colorado Adams65.357.7 57.7 57.657.1 57.1 56.7Colorado Arapahoe 78.770.4 70.4 70.369.5 69.4 69.1Colorado Boulder75.363.9 63.9 63.762.9 62.9 62.4Colorado Denver74.065.4 65.4 65.364.7 64.7 64.3Colorado Douglas83.073.8 73.8 73.772.7 72.7 72.3Colorado El Paso72.363.2 63.2 63.062.6 62.6 62.1Colorado Jefferson 84.774.2 74.2 74.073.2 73.2 72.8**45**Colorado La Plata59.052.2 52.2 52.151.9 51.8 51.6Colorado Larimer80.367.8 67.8 67.666.8 66.8 66.3Colorado Montezuma 68.063.0 62.9 62.962.6 62.5 62.3Colorado Weld76.764.9 64.9 64.764.9 64.9 64.3Connecticut Fairfield98.381.7 81.6 81.581.3 81.0 80.7Connecticut Hartford88.067.9 67.6 67.566.8 66.1 65.7Connecticut Litchfield 86.066.7 66.3 66.266.2 65.4 65.1Connecticut Middlesex 95.775.6 75.3 75.274.8 74.1 73.8Connecticut New Haven 98.379.1 78.8 78.678.4 77.7 77.3Connecticut New London 90.070.9 70.6 70.570.2 69.6 69.3Connecticut Tolland92.370.6 70.3 70.169.2 68.5 68.1D.C. Washington 92.770.5 70.4 70.168.9 68.6 68.0Delaware Kent88.371.8 71.3 71.271.4 70.6 70.2Delaware New Castle 92.772.4 72.1 71.971.7 71.1 70.5Delaware Sussex90.071.9 71.7 71.571.1 70.7 70.4Florida Bay79.362.9 62.7 62.661.8 61.4 60.9Florida Brevard72.752.8 52.5 52.551.7 51.2 50.9Florida Duval74.054.3 53.9 53.653.4 52.5 51.9Florida Escambia 81.066.5 66.4 66.266.2 65.8 65.4Florida Hillsborough 78.767.1 67.0 66.966.2 65.9 65.7Florida Lake76.056.3 56.2 56.155.4 55.2 55.0Florida Manatee76.362.3 62.1 62.161.6 61.0 60.8Florida Miami-Dade 67.054.4 54.3 54.353.6 53.2 53.1Florida Orange76.357.6 57.5 57.456.6 56.4 56.1Florida Pasco76.758.8 58.6 58.557.7 57.3 57.0Florida Pinellas74.762.1 61.9 61.961.4 60.9 60.7Florida Polk76.359.8 59.5 59.459.0 58.3 58.1Florida Santa Rosa 81.365.3 65.2 65.065.0 64.6 64.1Florida Sarasota 79.762.2 61.8 61.761.6 60.8 60.6Florida Seminole 77.558.3 58.2 58.157.2 56.9 56.7Georgia Bibb88.065.8 65.7 65.464.3 64.2 63.3Georgia Chatham 68.354.4 54.1 53.953.6 52.8 52.3Georgia Cherokee 78.054.7 54.6 54.452.0 51.9 51.3Georgia Clarke78.055.0 55.0 54.852.6 52.4 51.8Georgia Cobb91.064.9 64.9 64.761.8 61.6 61.0Georgia Coweta88.766.3 66.3 66.164.4 64.2 63.6Georgia Dawson80.057.3 57.3 57.155.0 54.9 54.3Georgia De Kalb91.068.3 68.3 68.065.9 65.7 65.0**46**Georgia Douglas91.065.1 65.0 64.862.5 62.3 61.6Georgia Fayette85.363.4 63.3 63.160.8 60.7 60.0Georgia Fulton94.371.8 71.8 71.569.2 69.1 68.3Georgia Glynn72.355.8 55.5 55.354.9 54.3 53.6Georgia Gwinnett87.762.8 62.8 62.659.6 59.5 58.9Georgia Henry91.765.9 65.8 65.663.2 63.1 62.3Georgia Murray85.060.7 60.6 60.358.9 58.7 57.9Georgia Muscogee 75.054.9 54.8 54.653.4 53.2 52.4Georgia Paulding88.061.4 61.3 61.159.2 59.0 58.4Georgia Richmond 84.365.3 65.2 65.063.3 63.1 62.6Georgia Rockdale 91.065.6 65.5 65.362.9 62.7 62.0Georgia Sumter75.055.2 55.0 54.754.0 53.8 52.8Idaho Ada76.069.9 69.9 69.868.7 68.6 68.4Idaho Canyon68.059.6 59.6 59.558.0 58.0 57.8Illinois Adams75.361.4 61.0 60.760.8 59.8 58.9Illinois Champaign 75.059.8 59.6 59.358.9 58.5 57.6Illinois Clark73.054.4 54.2 54.053.8 53.4 52.9Illinois Cook85.375.0 75.1 75.174.3 74.6 74.5Illinois Du Page71.763.1 63.0 62.862.7 62.4 61.9Illinois Effingham 74.758.3 58.1 57.957.4 57.0 56.3Illinois Hamilton 79.360.6 60.0 59.860.2 58.9 58.3Illinois Jersey87.769.5 68.9 68.768.5 67.1 66.5Illinois Kane77.065.3 65.1 64.764.7 64.3 63.2Illinois Lake84.773.7 73.6 73.473.2 73.0 72.3Illinois Macon75.059.3 59.1 58.958.6 58.1 57.4Illinois Macoupin 78.058.6 58.3 58.157.7 57.0 56.3Illinois Madison85.768.0 67.5 67.367.0 65.8 65.2Illinois McHenry 82.069.7 69.5 69.169.0 68.7 67.5Illinois McLean76.059.4 59.2 58.958.4 57.9 57.1Illinois Peoria78.065.2 65.0 64.764.3 63.7 63.1Illinois Randolph 77.760.9 60.5 60.260.2 59.3 58.6Illinois Rock Island 68.756.3 56.1 55.855.1 54.6 53.8Illinois Sangamon 75.354.8 54.6 54.453.6 53.2 52.6Illinois St Clair83.067.7 67.3 67.066.7 65.5 64.9Illinois Will78.363.9 63.8 63.463.1 62.8 61.8Illinois Winnebago 75.060.2 60.0 59.659.0 58.6 57.5Indiana Allen87.068.7 68.5 68.167.4 66.9 65.8Indiana Boone88.069.4 69.2 68.968.2 67.8 67.1**47**Indiana Carroll83.064.2 63.9 63.663.1 62.6 61.8Indiana Clark90.070.3 69.8 69.569.7 68.4 67.8Indiana Delaware 85.566.2 66.0 65.664.9 64.4 63.5Indiana Elkhart87.069.2 69.0 68.668.1 67.7 66.6Indiana Floyd84.368.1 67.6 67.467.5 66.3 65.8Indiana Gibson73.052.5 52.2 52.151.7 51.2 50.7Indiana Greene87.063.9 63.6 63.363.0 62.3 61.6Indiana Hamilton 93.772.0 71.8 71.670.4 69.9 69.3Indiana Hancock91.369.4 69.2 69.067.8 67.2 66.6Indiana Hendricks 84.766.8 66.6 66.465.3 64.9 64.2Indiana Huntington 83.365.7 65.5 65.264.5 64.1 63.1Indiana Jackson83.364.0 63.6 63.463.3 62.4 61.7Indiana Johnson85.366.3 66.1 65.965.2 64.7 64.1Indiana La Porte90.376.1 76.0 75.875.4 75.2 74.6Indiana Lake88.378.5 78.6 78.577.7 77.9 77.8Indiana Madison91.769.5 69.3 69.167.9 67.4 66.7Indiana Marion90.070.7 70.5 70.369.2 68.7 68.1Indiana Morgan85.067.4 67.2 67.066.2 65.8 65.1Indiana Porter86.376.0 76.1 76.075.3 75.4 75.2Indiana Posey84.063.5 62.9 62.662.7 61.4 60.7Indiana Shelby91.371.0 70.8 70.669.3 68.8 68.1Indiana St Joseph 90.372.5 72.3 71.871.5 71.0 69.8Indiana Vanderburgh 82.762.0 61.4 61.261.1 59.9 59.4Indiana Vigo85.068.0 67.8 67.567.1 66.7 65.9Indiana Warrick84.065.5 65.1 64.964.9 64.1 63.6Iowa Clinton76.364.2 63.9 63.663.4 62.9 62.0Iowa Harrison75.763.5 63.4 63.162.8 62.6 61.7Iowa Montgomery 67.057.0 57.0 56.756.5 56.3 55.4Iowa Polk57.347.5 47.5 47.245.7 45.5 45.0Iowa Scott77.763.0 62.7 62.461.8 61.2 60.4Iowa Story60.749.6 49.5 49.347.8 47.6 47.0Kansas Linn74.361.3 61.2 60.960.6 60.4 59.5Kansas Sedgwick 79.065.0 64.9 64.763.2 63.1 62.3Kansas Sumner75.763.6 63.5 63.362.5 62.3 61.5Kansas Wyandotte 79.064.2 64.1 63.763.0 62.8 61.7Kentucky Bell82.357.4 57.3 57.055.5 55.3 54.5Kentucky Boone83.764.8 64.3 64.164.4 63.3 62.7Kentucky Boyd88.373.1 72.5 72.273.3 72.2 71.4**48**Kentucky Bullitt81.063.3 62.8 62.662.5 61.5 60.9Kentucky Campbell 90.772.3 71.8 71.671.6 70.5 69.7Kentucky Carter77.059.7 59.2 59.060.1 59.1 58.3Kentucky Christian 84.059.1 58.7 58.558.7 57.8 57.2Kentucky Daviess75.360.1 59.6 59.559.7 58.7 58.3Kentucky Edmonson 80.360.5 60.1 59.959.6 58.9 58.2Kentucky Fayette75.058.6 58.4 58.157.1 56.6 55.8Kentucky Graves79.061.1 60.7 60.560.3 59.3 58.7Kentucky Greenup81.367.2 66.6 66.367.6 66.6 65.8Kentucky Hancock81.764.9 64.4 64.264.6 63.5 63.0Kentucky Hardin78.359.3 58.8 58.658.6 57.6 57.1Kentucky Henderson 79.361.8 61.4 61.261.2 60.4 59.9Kentucky Jefferson 82.766.4 66.0 65.865.7 64.7 64.2Kentucky Jessamine 76.358.6 58.4 58.157.4 56.9 56.1Kentucky Kenton85.067.7 67.1 66.967.1 65.9 65.1Kentucky Livingston 82.763.2 62.7 62.562.8 61.6 61.0Kentucky McCracken 79.065.3 64.9 64.764.7 63.8 63.4Kentucky McLean82.060.5 60.2 60.059.9 59.1 58.6Kentucky Oldham85.365.0 64.4 64.264.5 63.2 62.5Kentucky Perry75.756.7 56.5 56.255.9 55.5 54.7Kentucky Pike73.356.1 55.8 55.655.3 54.9 54.1Kentucky Pulaski77.359.9 59.8 59.459.0 58.6 57.7Kentucky Scott68.751.9 51.6 51.351.5 50.7 49.9Kentucky Simpson79.757.9 57.6 57.456.6 56.1 55.4Kentucky Trigg73.054.6 53.9 53.854.4 52.8 52.3Kentucky Warren82.061.4 61.1 60.860.5 59.8 59.1Louisiana Ascension 79.370.8 70.0 69.970.9 69.1 68.8Louisiana Bossier79.762.2 62.0 61.660.9 60.4 59.5Louisiana Caddo77.360.0 59.7 59.458.9 58.3 57.4Louisiana Calcasieu 78.768.1 67.5 67.368.1 66.9 66.4Louisiana East Baton Rouge 87.078.1 77.7 77.677.9 77.1 76.8Louisiana Iberville84.375.0 74.1 74.075.1 73.2 72.9Louisiana Jefferson 83.072.3 71.7 71.572.4 71.0 70.6Louisiana Lafayette 79.368.1 67.1 66.968.6 66.4 66.0Louisiana Lafourche 78.067.4 66.6 66.567.5 65.9 65.5Louisiana Livingston 79.770.8 69.8 69.770.9 69.0 68.6Louisiana Orleans69.760.2 59.6 59.560.3 59.0 58.7Louisiana Ouachita 77.762.6 62.2 62.061.8 60.9 60.2**49**Louisiana Pointe Coupee 73.365.1 64.6 64.565.0 64.1 63.8Louisiana St Bernard 78.065.9 65.3 65.165.8 64.6 64.2Louisiana St Charles 78.769.3 68.5 68.469.5 68.1 67.7Louisiana St James 74.065.4 65.2 65.165.2 64.6 64.3Louisiana St John The Baptist 78.769.9 69.6 69.569.4 69.1 68.8Louisiana St Mary74.763.9 62.6 62.564.5 61.8 61.4Louisiana West Baton Rouge 84.075.6 74.9 74.875.6 74.0 73.7Maine Cumberland 84.365.2 65.0 64.964.2 63.8 63.3Maine Hancock91.773.1 72.8 72.672.2 71.6 71.1Maine Kennebec 78.061.6 61.4 61.360.6 60.2 59.8Maine Knox83.765.0 64.8 64.664.1 63.7 63.2Maine Sagadahoc 79.061.2 61.1 60.960.4 60.0 59.6Maine York88.368.5 68.3 68.167.5 67.0 66.5Maryland Anne Arundel 98.374.1 74.0 73.772.8 72.5 71.9Maryland Baltimore 91.372.4 72.3 72.171.6 71.3 70.7Maryland Carroll88.766.8 66.6 66.365.5 65.1 64.4Maryland Cecil97.773.2 73.0 72.772.1 71.7 70.9Maryland Charles93.066.7 66.5 66.365.2 64.9 64.2Maryland Frederick 87.367.2 67.0 66.866.1 65.6 64.9Maryland Harford100.378.9 78.7 78.578.0 77.6 77.0Maryland Kent95.371.7 71.5 71.270.6 70.2 69.5Maryland Montgomery 86.765.8 65.7 65.564.6 64.3 63.6Maryland Prince Georges 94.071.0 70.9 70.769.4 69.1 68.4Maryland Washington 85.365.4 65.2 64.964.1 63.6 62.8Massachusetts Barnstable 92.073.8 73.4 73.273.4 72.6 72.2Massachusetts Berkshire 87.070.3 70.1 70.069.1 68.7 68.1Massachusetts Bristol91.071.9 71.7 71.571.5 70.8 70.4Massachusetts Essex90.072.8 72.7 72.572.0 71.7 71.4Massachusetts Hampden 92.070.3 70.1 69.969.0 68.4 68.0Massachusetts Hampshire 86.768.1 67.9 67.867.0 66.5 66.1Massachusetts Middlesex 85.766.5 66.3 66.165.2 64.8 64.2Massachusetts Norfolk91.076.2 76.2 76.175.4 75.3 74.9Massachusetts Suffolk88.771.6 71.5 71.470.9 70.8 70.4Massachusetts Worcester 85.566.9 66.6 66.565.9 65.3 64.9Michigan Allegan94.077.2 77.0 76.576.4 75.9 74.5Michigan Benzie85.769.7 69.5 69.268.9 68.5 67.5Michigan Berrien88.074.0 73.9 73.673.4 73.1 72.4Michigan Cass90.771.7 71.5 71.070.5 70.0 68.7**50**Michigan Clinton82.766.7 66.5 66.265.5 65.2 64.3Michigan Genesee 86.368.5 68.3 68.067.1 66.8 65.9Michigan Huron83.070.8 70.7 70.570.3 70.0 69.6Michigan Ingham82.365.9 65.8 65.564.8 64.4 63.5Michigan Kalamazoo 82.765.1 64.9 64.563.9 63.5 62.4Michigan Kent84.767.4 67.2 66.966.2 65.8 64.8Michigan Lenawee 85.069.4 69.2 69.068.6 68.2 67.4Michigan Macomb92.376.6 76.5 76.375.6 75.4 74.8Michigan Mason86.068.9 68.7 68.367.8 67.4 66.1Michigan Missaukee 78.364.0 63.8 63.563.1 62.7 61.9Michigan Muskegon 90.073.4 73.2 72.772.5 72.0 70.7Michigan Oakland87.774.2 74.1 73.973.3 73.1 72.6Michigan Ottawa86.069.3 69.1 68.768.3 67.8 66.7Michigan Schoolcraft 77.065.0 64.9 64.664.5 64.1 63.3Michigan St Clair88.072.5 72.3 72.171.5 71.2 70.6Michigan Washtenaw 87.371.4 71.3 71.170.5 70.2 69.5Michigan Wayne86.072.9 72.8 72.671.9 71.7 71.2Mississippi Adams77.763.1 61.9 61.763.2 60.8 60.2Mississippi De Soto83.364.0 63.6 63.262.8 61.8 60.8Mississippi Hancock81.066.1 65.4 65.165.7 64.1 63.5Mississippi Harrison80.365.1 64.4 64.265.0 63.5 62.9Mississippi Hinds72.752.1 51.8 51.450.1 49.5 48.3Mississippi Jackson80.068.6 68.3 68.168.5 67.9 67.5Mississippi Lauderdale 73.352.3 52.1 51.850.9 50.6 49.8Mississippi Lee78.357.4 57.1 56.856.2 55.6 54.7Mississippi Madison74.355.2 54.9 54.553.7 53.1 51.9Mississippi Warren73.754.9 53.6 53.454.9 52.4 51.7Missouri Cass77.761.9 61.8 61.560.9 60.7 59.7Missouri Cedar79.764.8 64.6 64.263.7 63.4 62.3Missouri Clay83.766.7 66.5 66.065.0 64.6 63.3Missouri Greene74.559.8 59.6 59.358.6 58.2 57.4Missouri Jefferson 84.768.9 68.4 68.267.6 66.4 65.8Missouri Monroe76.761.9 61.6 61.361.2 60.5 59.5Missouri Platte80.365.0 64.9 64.564.0 63.7 62.6Missouri St Charles 90.073.0 72.6 72.471.6 70.5 69.9Missouri St Louis88.372.6 72.1 71.871.3 70.0 69.4Missouri St Louis City 87.772.9 72.4 72.271.8 70.5 69.9Missouri Ste Genevieve 82.766.8 66.4 66.166.0 65.1 64.4**51**Nebraska Douglas67.357.3 57.2 57.056.6 56.4 55.7Nebraska Lancaster 55.046.6 46.5 46.345.8 45.6 45.0Nevada Clark84.774.9 74.8 74.674.0 73.8 73.3Nevada Douglas69.061.1 61.0 60.959.4 59.2 58.8Nevada Washoe73.365.0 65.0 64.963.6 63.5 63.1New Hampshire Belknap76.561.5 61.4 61.260.4 60.2 59.8New Hampshire Cheshire 74.358.4 58.2 58.157.6 57.1 56.8New Hampshire Hillsborough 85.366.7 66.5 66.365.6 65.1 64.7New Hampshire Merrimack 74.759.1 58.9 58.858.2 57.8 57.3New Hampshire Rockingham 83.565.9 65.7 65.565.2 64.7 64.3New Hampshire Strafford78.561.1 60.9 60.860.2 59.8 59.4New Jersey Atlantic88.069.9 69.3 69.269.5 68.3 68.0New Jersey Bergen91.376.2 76.0 75.975.5 75.3 74.9New Jersey Camden99.779.6 79.1 78.978.9 77.9 77.4New Jersey Cumberland 94.073.7 73.2 73.073.3 72.2 71.7New Jersey Essex67.054.1 54.1 54.053.5 53.4 53.1New Jersey Gloucester 98.077.9 77.6 77.477.4 76.7 76.1New Jersey Hudson84.067.7 67.8 67.766.9 67.1 66.7New Jersey Hunterdon 94.773.6 73.1 73.072.5 71.5 71.1New Jersey Mercer97.778.2 77.7 77.577.5 76.2 75.8New Jersey Middlesex 96.075.4 75.0 74.974.4 73.5 73.1New Jersey Monmouth 95.375.6 75.3 75.175.0 74.2 73.8New Jersey Morris95.373.2 72.9 72.772.2 71.3 70.8New Jersey Ocean105.782.1 81.5 81.381.1 79.8 79.3New Jersey Passaic86.769.2 69.0 68.968.3 67.8 67.3New Mexico Bernalillo 76.366.4 66.3 66.164.5 64.4 63.7New Mexico Dona Ana 78.370.2 70.2 70.066.8 66.8 66.2New Mexico San Juan 74.370.4 70.4 70.370.0 70.0 69.7New Mexico Sandoval 74.064.9 64.8 64.663.1 63.0 62.3New Mexico Valencia67.558.0 58.0 57.756.6 56.5 55.7New York Albany83.066.2 66.0 65.864.9 64.4 63.8New York Bronx82.771.1 71.1 70.970.7 70.6 70.2New York Chautauqua 93.075.4 75.0 74.775.0 74.1 73.2New York Chemung 80.363.1 63.0 62.761.9 61.6 60.9New York Dutchess 92.071.0 70.7 70.570.4 69.5 69.1New York Erie95.777.7 77.3 77.077.1 76.3 75.5New York Essex89.070.6 70.4 70.269.6 69.2 68.6New York Herkimer 74.060.3 60.1 59.959.4 59.1 58.6**52**New York Jefferson 91.374.9 74.7 74.574.3 73.9 73.3New York Madison79.763.7 63.6 63.362.5 62.3 61.6New York Monroe84.068.8 68.7 68.567.5 67.3 66.7New York Niagara91.777.2 77.0 76.876.8 76.4 75.9New York Oneida79.764.5 64.3 64.163.6 63.2 62.6New York Onondaga 84.068.8 68.7 68.567.9 67.6 67.0New York Orange84.765.6 65.3 65.264.5 63.9 63.4New York Oswego68.055.1 55.0 54.854.4 54.1 53.6New York Putnam91.373.4 73.1 72.972.9 72.1 71.7New York Queens84.571.6 71.5 71.471.1 70.8 70.4New York Rensselaer 86.068.4 68.2 68.067.0 66.5 65.8New York Richmond 93.075.3 75.4 75.274.1 74.2 73.8New York Saratoga 87.068.8 68.6 68.467.4 66.8 66.1New York Schenectady 77.762.8 62.6 62.461.2 60.8 60.2New York Suffolk97.082.0 82.1 82.081.4 81.6 81.3New York Ulster81.365.2 65.0 64.864.2 63.8 63.3New York Wayne84.067.5 67.3 67.166.3 66.0 65.4New York Westchester 91.376.3 76.1 76.075.7 75.3 74.9North Carolina Alexander 87.063.2 63.1 62.961.5 61.3 60.8North Carolina Avery77.760.1 60.0 59.858.8 58.6 57.9North Carolina Buncombe 80.061.6 61.5 61.359.9 59.8 59.3North Carolina Caldwell83.361.8 61.7 61.460.2 59.9 59.3North Carolina Caswell87.762.0 61.9 61.760.1 59.9 59.3North Carolina Chatham 81.359.9 59.8 59.658.5 58.3 57.7North Carolina Cumberland 86.063.1 63.0 62.761.1 60.9 60.1North Carolina Davie91.365.5 65.4 65.263.7 63.5 62.9North Carolina Duplin80.060.6 60.5 60.359.2 59.0 58.3North Carolina Durham88.762.8 62.7 62.560.6 60.4 59.8North Carolina Edgecombe 87.364.6 64.5 64.362.7 62.5 61.8North Carolina Forsyth91.364.8 64.7 64.562.7 62.6 62.1North Carolina Franklin89.764.7 64.6 64.362.2 62.0 61.4North Carolina Granville92.365.8 65.7 65.564.2 63.9 63.3North Carolina Guilford88.761.3 61.2 61.058.7 58.5 57.9North Carolina Haywood 84.765.8 65.7 65.564.5 64.2 63.6North Carolina Jackson86.064.9 64.8 64.563.6 63.3 62.5North Carolina Johnston 84.361.4 61.3 61.159.1 58.9 58.3North Carolina Lenoir80.061.2 61.1 60.959.8 59.5 58.9North Carolina Lincoln90.765.7 65.6 65.463.8 63.6 63.1**53**North Carolina Martin81.061.3 61.2 61.060.0 59.7 59.1North Carolina Mecklenburg 97.373.0 72.9 72.770.8 70.6 70.1North Carolina New Hanover 77.358.0 57.7 57.556.9 56.2 55.7North Carolina Northampton 84.063.2 63.1 62.962.0 61.6 61.0North Carolina Person89.364.0 63.9 63.863.1 62.8 62.4North Carolina Pitt82.060.5 60.4 60.258.6 58.4 57.7North Carolina Randolph 83.558.9 58.8 58.656.7 56.5 55.9North Carolina Rockingham 88.363.0 62.9 62.761.6 61.5 60.9North Carolina Rowan97.370.1 70.0 69.867.8 67.7 66.9North Carolina Swain73.054.6 54.5 54.253.4 53.1 52.5North Carolina Union87.063.5 63.4 63.261.1 61.0 60.3North Carolina Wake92.565.8 65.7 65.562.9 62.7 62.1North Carolina Yancey83.064.1 64.0 63.862.5 62.2 61.6Ohio Allen88.069.7 69.4 69.268.7 68.2 67.4Ohio Ashtabula 95.778.9 78.6 78.378.6 77.9 77.1Ohio Butler89.770.1 69.6 69.369.2 68.1 67.3Ohio Clark88.368.1 67.9 67.667.4 66.7 66.0Ohio Clermont 89.370.8 70.3 70.170.0 69.0 68.2Ohio Clinton94.371.4 71.0 70.670.4 69.4 68.5Ohio Cuyahoga 88.070.4 70.3 70.170.1 69.8 69.2Ohio Delaware 89.068.4 68.2 67.967.0 66.5 65.6Ohio Franklin93.070.8 70.5 70.269.0 68.5 67.5Ohio Geauga99.079.5 79.2 78.978.6 77.9 77.0Ohio Greene87.768.0 67.6 67.367.2 66.4 65.6Ohio Hamilton 90.371.3 70.8 70.570.3 69.3 68.4Ohio Jefferson 84.365.0 64.7 64.564.5 63.8 63.3Ohio Knox87.066.5 66.3 66.065.1 64.7 63.8Ohio Lake92.775.3 75.2 75.075.0 74.7 74.1Ohio Lawrence 81.767.5 66.9 66.668.0 66.9 66.1Ohio Licking88.067.2 67.0 66.765.7 65.2 64.3Ohio Lorain87.069.8 69.8 69.669.3 69.2 68.7Ohio Lucas90.072.8 72.8 72.571.9 71.8 71.1Ohio Madison88.767.2 66.9 66.766.3 65.6 64.9Ohio Mahoning 87.067.1 66.8 66.566.0 65.4 64.5Ohio Medina87.069.7 69.5 69.269.3 68.7 68.0Ohio Miami87.066.5 66.2 66.065.2 64.7 63.9Ohio Montgomery 86.567.5 67.3 67.066.4 65.8 65.0Ohio Portage91.071.1 70.7 70.470.0 69.2 68.3**54**Ohio Preble80.062.0 61.7 61.561.1 60.6 59.9Ohio Stark88.367.8 67.6 67.366.5 66.0 65.2Ohio Summit93.373.6 73.4 73.172.7 72.1 71.2Ohio Trumbull92.070.8 70.5 70.269.7 69.0 68.0Ohio Warren90.770.3 70.0 69.769.3 68.5 67.7Ohio Washington 85.763.2 62.7 62.563.1 61.8 61.3Ohio Wood87.770.4 70.1 69.769.5 68.9 67.8Oklahoma Canadian 76.058.1 58.0 57.856.0 55.7 55.1Oklahoma Cleveland 75.361.3 61.1 60.960.3 59.9 59.4Oklahoma Comanche 77.362.4 62.2 62.061.7 61.4 60.8Oklahoma Dewey71.059.3 59.1 59.058.9 58.5 58.1Oklahoma Kay75.061.6 61.5 61.261.0 60.8 60.1Oklahoma Mc Clain77.063.0 62.8 62.662.2 61.8 61.3Oklahoma Oklahoma 80.362.4 62.3 62.159.8 59.6 58.9Oklahoma Ottawa78.063.5 63.4 63.162.7 62.4 61.5Oklahoma Pittsburg 73.061.6 61.4 61.161.0 60.5 59.7Oklahoma Tulsa83.067.7 67.6 67.465.6 65.4 64.8Pennsylvania Adams80.061.0 60.7 60.559.9 59.5 58.8Pennsylvania Allegheny 91.373.9 73.6 73.373.3 72.4 71.8Pennsylvania Armstrong 90.770.3 69.6 69.469.8 68.4 67.8Pennsylvania Beaver91.372.8 72.5 72.372.1 71.5 71.0Pennsylvania Berks88.767.4 67.2 67.066.2 65.8 65.1Pennsylvania Blair83.362.3 62.0 61.861.5 60.9 60.1Pennsylvania Bucks99.080.7 80.1 80.080.1 78.9 78.4Pennsylvania Cambria85.065.1 64.8 64.564.4 63.7 63.0Pennsylvania Centre84.763.7 63.5 63.262.7 62.2 61.4Pennsylvania Chester95.072.9 72.7 72.571.9 71.4 70.6Pennsylvania Clearfield 87.366.7 66.3 66.166.0 65.2 64.6Pennsylvania Dauphin86.766.6 66.4 66.265.4 65.1 64.4Pennsylvania Delaware 91.772.7 72.4 72.272.2 71.6 71.1Pennsylvania Erie89.073.2 72.7 72.572.9 72.0 71.2Pennsylvania Franklin90.768.8 68.5 68.267.3 66.8 66.0Pennsylvania Greene87.765.5 65.0 64.865.2 64.2 63.7Pennsylvania Lackawanna 83.363.3 63.2 63.062.0 61.6 61.1Pennsylvania Lancaster 91.069.2 69.1 68.868.0 67.6 66.8Pennsylvania Lawrence 78.359.2 59.0 58.758.3 57.8 57.0Pennsylvania Lehigh90.768.6 68.4 68.267.3 66.8 66.3Pennsylvania Luzerne83.763.5 63.4 63.262.3 61.9 61.3**55**Pennsylvania Lycoming 82.062.7 62.5 62.361.7 61.3 60.7Pennsylvania Mercer91.370.1 69.7 69.469.0 68.3 67.3Pennsylvania Montgomery 92.373.4 73.1 72.972.7 72.1 71.6Pennsylvania Northampton 90.068.2 68.0 67.866.8 66.2 65.7Pennsylvania Perry83.363.1 63.0 62.762.0 61.6 60.8Pennsylvania Philadelphia 96.779.7 79.2 79.079.2 78.0 77.6Pennsylvania Tioga85.066.4 66.2 66.065.4 65.0 64.4Pennsylvania Washington 86.368.2 68.0 67.867.7 67.1 66.5Pennsylvania Westmoreland 88.070.9 70.3 70.170.3 69.1 68.5Pennsylvania York89.068.5 68.4 68.167.4 67.0 66.3Rhode Island Kent93.072.6 72.2 72.072.1 71.0 70.7Rhode Island Providence 92.072.0 71.5 71.471.4 70.4 70.0Rhode Island Washington 92.773.7 73.2 73.173.3 72.2 71.8South Carolina Abbeville 82.361.5 61.4 61.259.6 59.4 58.7South Carolina Aiken82.762.7 62.6 62.360.9 60.7 60.1South Carolina Anderson 85.364.8 64.8 64.662.3 62.2 61.6South Carolina Barnwell79.360.0 59.9 59.658.4 58.2 57.5South Carolina Berkeley71.554.5 54.1 53.953.6 52.8 52.2South Carolina Charleston 72.556.3 55.9 55.755.5 54.6 54.0South Carolina Cherokee 83.762.2 62.2 62.060.6 60.4 59.8South Carolina Chester82.760.6 60.5 60.358.9 58.7 58.2South Carolina Chesterfield 80.060.1 60.0 59.758.6 58.4 57.7South Carolina Colleton77.759.4 59.3 59.158.2 57.9 57.3South Carolina Darlington 82.762.5 62.4 62.261.0 60.8 60.1South Carolina Edgefield 79.760.3 60.2 60.058.7 58.5 57.9South Carolina Oconee83.761.8 61.7 61.559.8 59.6 59.1South Carolina Pickens83.061.0 61.0 60.858.9 58.7 58.1South Carolina Richland89.367.8 67.7 67.565.3 65.1 64.4South Carolina Spartanburg 87.063.7 63.7 63.461.4 61.3 60.6South Carolina Union79.759.9 59.8 59.658.1 57.9 57.3South Carolina Williamsburg 71.753.4 53.3 53.152.3 52.0 51.4South Carolina York83.060.8 60.8 60.659.1 58.9 58.4Tennessee Anderson 87.060.2 60.0 59.757.6 57.3 56.4Tennessee Blount92.366.6 66.4 66.164.4 64.0 63.0Tennessee Davidson 77.758.2 57.9 57.656.7 56.1 55.4Tennessee Hamilton 88.363.7 63.5 63.161.3 60.9 59.6Tennessee Haywood 83.561.5 61.2 61.060.4 59.8 59.1Tennessee Jefferson 91.063.4 63.3 63.060.2 59.9 59.0**56**Tennessee Knox92.063.4 63.3 62.959.9 59.6 58.5Tennessee Lawrence 77.057.8 57.6 57.356.9 56.3 55.6Tennessee Meigs89.062.8 62.7 62.360.8 60.5 59.5Tennessee Putnam84.063.1 63.0 62.861.9 61.6 60.9Tennessee Rutherford 80.759.5 59.3 59.158.1 57.6 56.9Tennessee Sevier92.368.0 67.8 67.566.3 65.9 65.0Tennessee Shelby87.768.3 67.5 67.267.6 65.8 64.9Tennessee Sullivan86.767.3 67.3 67.066.0 65.8 65.1Tennessee Sumner85.763.5 63.3 63.061.9 61.3 60.6Tennessee Williamson 84.362.1 61.8 61.660.5 59.9 59.2Tennessee Wilson82.061.6 61.4 61.260.2 59.8 59.1Texas Bexar88.770.6 70.4 70.169.4 68.9 68.3Texas Brazoria94.080.2 79.1 78.980.6 78.1 77.7Texas Collin90.071.4 71.2 71.070.3 70.0 69.4Texas Dallas90.070.5 70.4 70.269.7 69.4 68.8Texas Denton97.376.2 76.1 75.975.4 75.1 74.5Texas El Paso79.370.5 70.5 70.367.3 67.2 66.5Texas Ellis85.064.4 64.3 64.163.3 63.1 62.5Texas Galveston 89.776.6 76.6 76.476.6 76.0 75.5Texas Gregg84.369.0 68.8 68.668.2 67.8 67.2Texas Harris102.092.4 92.4 92.392.1 92.0 91.6Texas Harrison78.562.8 62.5 62.362.1 61.5 60.8Texas Hood83.059.6 59.5 59.258.1 57.8 57.1Texas Jefferson 91.078.6 77.4 77.279.0 76.5 76.0Texas Johnson89.767.3 67.2 67.066.0 65.7 65.1Texas Kaufman 72.056.0 55.9 55.655.3 55.0 54.4Texas Montgomery 88.377.3 76.7 76.677.3 76.0 75.7Texas Nueces80.368.9 68.0 67.869.2 67.2 66.7Texas Orange81.069.6 68.6 68.469.8 67.7 67.2Texas Parker87.064.8 64.7 64.563.6 63.4 62.8Texas Rockwall 82.063.2 63.1 62.962.2 61.9 61.3Texas Smith82.065.1 64.9 64.764.2 63.8 63.0Texas Tarrant98.777.0 76.9 76.776.2 75.9 75.4Texas Travis84.765.7 65.4 65.264.5 63.9 63.3Texas Victoria77.765.1 64.4 64.265.0 63.5 63.0Texas Webb64.755.3 54.8 54.755.2 54.1 53.8Utah Box Elder 77.567.0 67.0 66.766.2 66.1 65.2Utah Cache69.358.7 58.7 58.457.5 57.4 56.7**57**Utah Davis81.072.8 72.8 72.671.7 71.6 70.9Utah Salt Lake 79.772.8 72.7 72.472.2 72.1 71.2Utah Utah77.769.3 69.3 69.068.3 68.3 67.7Utah Weber79.368.1 68.1 67.866.8 66.7 65.9Vermont Bennington 79.362.5 62.3 62.161.1 60.7 60.0Virginia Alexandria City 90.068.1 68.0 67.866.7 66.5 65.8Virginia Arlington 96.774.2 74.1 73.872.6 72.3 71.6Virginia Caroline82.360.7 60.6 60.359.5 59.2 58.5Virginia Charles City 89.370.2 70.1 69.969.1 68.9 68.4Virginia Chesterfield 84.767.6 67.5 67.466.7 66.4 66.0Virginia Fairfax96.773.2 73.1 72.871.6 71.4 70.7Virginia Fauquier79.359.7 59.5 59.358.8 58.4 57.7Virginia Frederick 82.763.3 63.1 62.862.2 61.7 61.0Virginia Hampton City 88.372.9 72.7 72.572.4 72.0 71.6Virginia Hanover92.071.2 71.1 70.970.0 69.7 69.2Virginia Henrico88.368.9 68.8 68.667.7 67.4 67.0Virginia Loudoun90.068.5 68.3 68.167.4 67.0 66.3Virginia Madison84.764.2 64.1 63.963.2 62.9 62.4Virginia Page79.759.3 59.1 58.958.3 57.9 57.5Virginia Prince William 85.064.9 64.7 64.563.8 63.4 62.6Virginia Roanoke 83.763.2 63.1 62.861.6 61.3 60.5Virginia Rockbridge 76.758.0 57.9 57.757.0 56.7 56.1Virginia Stafford86.064.8 64.7 64.263.5 63.3 62.1Virginia Suffolk City 87.072.0 71.8 71.671.7 71.3 70.8West Virginia Berkeley83.063.7 63.5 63.262.5 62.0 61.2West Virginia Cabell85.770.9 70.5 70.371.7 71.1 70.4West Virginia Hancock84.765.5 65.3 65.165.0 64.4 63.9West Virginia Kanawha 84.063.6 63.2 63.063.1 62.4 61.8West Virginia Monongalia 78.756.7 56.5 56.456.2 55.8 55.3West Virginia Ohio83.364.6 64.2 64.164.3 63.5 63.0West Virginia Wood85.763.9 63.3 63.163.8 62.5 62.0Wisconsin Brown80.367.9 67.8 67.567.4 67.1 66.4Wisconsin Columbia 76.362.1 61.9 61.761.1 60.7 60.0Wisconsin Dane76.062.6 62.5 62.261.6 61.2 60.5Wisconsin Dodge79.365.7 65.5 65.365.1 64.7 64.0Wisconsin Door91.075.0 74.8 74.474.4 74.0 72.9Wisconsin Fond Du Lac 77.363.7 63.6 63.463.0 62.8 62.1Wisconsin Jefferson 80.065.0 64.9 64.664.1 63.7 62.9**58**Wisconsin Kenosha 98.385.0 84.9 84.784.4 84.2 83.4Wisconsin Kewaunee 89.374.3 74.1 73.873.9 73.4 72.3Wisconsin Manitowoc 87.072.2 72.0 71.671.6 71.2 70.2Wisconsin Milwaukee 91.077.2 77.1 76.876.6 76.3 75.4Wisconsin Ozaukee 93.078.0 77.9 77.577.3 77.0 75.9Wisconsin Racine91.778.0 77.9 77.777.4 77.1 76.4Wisconsin Rock81.766.1 65.9 65.564.7 64.2 63.1Wisconsin Sauk72.059.4 59.3 59.058.6 58.3 57.6Wisconsin Sheboygan 97.081.1 80.9 80.580.4 79.9 78.7Wisconsin St Croix71.361.2 61.1 61.060.7 60.5 60.0Wisconsin Walworth 81.366.3 66.2 65.865.4 65.0 64.1Wisconsin Washington 80.367.4 67.2 67.066.9 66.5 65.9Wisconsin Waukesha 79.066.0 65.9 65.665.5 65.1 64.4**59**Appendix C: Visibility Levels on 20% Worst Days forLocomotive/Marine Scenario (units are deciviews)Class 1 Area StateBaselineVisibility2020 Base2020Locomotive /Marine2030 Base2030Locomotive /MarineNaturalBackgroundSipsey Wilderness AL 29.0323.7823.7323.7723.6610.99Caney Creek Wilderness AR 26.3622.1122.0522.0621.9211.58Upper Buffalo Wilderness AR 26.2722.4122.3522.3422.1911.57Chiricahua NM AZ 13.4313.0913.0913.1013.097.21Chiricahua Wilderness AZ 13.4313.0913.0913.1013.097.21Galiuro Wilderness AZ 13.4313.0813.0713.1113.097.21Grand Canyon NP AZ 11.6611.1311.0911.1511.087.14Mazatzal Wilderness AZ 13.3512.7412.7212.7712.736.68Petrified Forest NP AZ 13.2112.9012.8312.8712.756.49Pine Mountain Wilderness AZ 13.3512.5912.5812.5912.546.68Saguaro NM AZ 14.8314.5014.4714.4914.446.46Sierra Ancha Wilderness AZ 13.6713.2213.2013.1813.156.59Sycamore Canyon Wilderness AZ 15.2514.9614.9414.9814.936.69Agua Tibia Wilderness CA 23.5021.2321.1421.1620.947.64Caribou Wilderness CA 14.1513.6213.6013.5513.517.31Cucamonga Wilderness CA 19.9417.4217.3617.1417.107.06Desolation Wilderness CA 12.6312.1512.1312.1512.126.12Dome Land Wilderness CA 19.4318.3718.3418.2018.117.46Emigrant Wilderness CA 17.6317.2217.2117.2417.197.64Hoover Wilderness CA 12.8712.7312.7212.7512.747.91Joshua Tree NM CA 19.6217.9517.9317.8517.717.19Lassen Volcanic NP CA 14.1513.5613.5413.4813.437.31Lava Beds NM CA 15.0514.4514.4214.4014.327.86Mokelumne Wilderness CA 12.6312.3212.3012.3412.316.12Pinnacles NM CA 18.4617.3717.3617.1617.097.99Point Reyes NS CA 22.8122.0121.9921.8721.7915.77Redwood NP CA 18.4517.8917.8617.8617.7913.91San Gabriel Wilderness CA 19.9417.3017.2517.0116.937.06San Gorgonio Wilderness CA 22.1720.2820.2219.9419.707.30San Jacinto Wilderness CA 22.1719.9219.8719.6119.557.30South Warner Wilderness CA 15.0514.6114.5914.5714.527.86**60**Thousand Lakes Wilderness CA 14.1513.5413.5213.4613.417.31Ventana Wilderness CA 18.4617.6717.6417.6717.627.99Yosemite NP CA 17.6317.1617.1417.1517.117.64Black Canyon of the Gunnison NM CO 10.339.809.799.799.776.24Eagles Nest Wilderness CO 9.619.059.038.998.966.54Flat Tops Wilderness CO 9.619.319.319.329.316.54Great Sand Dunes NM CO 12.7812.3612.3612.3712.366.66La Garita Wilderness CO 10.339.909.899.899.886.24Maroon Bells-Snowmass Wilderness CO 9.619.249.249.249.246.54Mesa Verde NP CO 13.0312.4012.3912.4012.376.83Mount Zirkel Wilderness CO 10.5210.0610.0510.0710.046.44Rawah Wilderness CO 10.5210.0410.0410.0610.046.44Rocky Mountain NP CO 13.8313.1013.0813.0613.017.24Weminuche Wilderness CO 10.339.869.869.869.866.24West Elk Wilderness CO 9.619.249.249.249.236.54Chassahowitzka FL 26.0921.9621.9421.9621.9111.21Everglades NP FL 22.3019.7519.7719.9719.9412.15St. MarksFL 26.0321.8421.8221.8821.8311.53Cohutta Wilderness GA 30.3023.3623.3323.3423.2811.14Okefenokee GA 27.1323.4623.4223.5023.4011.44Wolf Island GA 27.1323.4023.3723.4023.3211.44Craters of the Moon NM ID 14.0013.0012.9712.9012.827.53Sawtooth Wilderness ID 13.7813.6413.6313.6413.636.43Mammoth Cave NP KY 31.3725.5325.4825.5425.4411.08Acadia NP ME 22.8919.7919.7719.8619.8112.43Moosehorn ME 21.7218.6518.6318.6818.6412.01Roosevelt Campobello International Park ME 21.7218.4718.4518.5118.4712.01Isle Royale NP MI 20.7419.1519.1019.1619.0412.37SeneyMI 24.1621.7721.7221.7821.6612.65Voyageurs NP MN 19.2717.6217.5817.5317.4312.06Hercules-Glades Wilderness MO 26.7523.0022.9322.9622.8111.30Anaconda-Pintler Wilderness MT 13.4113.1513.1413.1313.117.43Bob Marshall Wilderness MT 14.4814.1414.1314.1114.087.74Cabinet Mountains Wilderness MT 14.0913.5713.5413.5213.467.53Gates of the Mountains Wilderness MT 11.2910.9210.9110.8910.876.45Medicine Lake MT 17.7216.2516.2216.1816.127.90Mission Mountains Wilderness MT 14.4814.0614.0414.0213.997.74Scapegoat Wilderness MT 14.4814.1714.1614.1414.127.74**61**Selway-Bitterroot Wilderness MT 13.4113.0613.0413.0212.997.43UL BendMT 15.1414.6614.6414.6214.588.16Linville Gorge Wilderness NC 28.7722.4822.4522.4722.4111.22Swanquarter NC 25.4921.1721.1521.2021.1511.94LostwoodND 19.5717.7317.7017.6717.608.00Theodore Roosevelt NP ND 17.7416.6516.5416.6116.427.79Great Gulf Wilderness NH 22.8219.4819.4519.5019.4611.99Presidential Range-Dry River Wilderness NH 22.8219.4819.4519.5019.4611.99BrigantineNJ 29.0124.8824.8524.9924.9112.24Bandelier NM NM 12.2211.4311.4111.3811.346.26Bosque del Apache NM 13.8012.9612.9012.9412.816.73Gila Wilderness NM 13.1112.5512.5412.5512.546.69Pecos Wilderness NM 10.4110.0110.0010.0210.016.44Salt Creek NM 18.0316.6116.5916.5816.526.81San Pedro Parks Wilderness NM 10.179.539.529.539.526.08Wheeler Peak Wilderness NM 10.419.969.959.979.966.44White Mountain Wilderness NM 13.7013.0713.0513.0713.046.86Jarbidge Wilderness NV 12.0711.8611.8611.8611.857.87Wichita Mountains OK 23.8120.6720.6220.6820.557.53Crater Lake NP OR 13.7413.2913.2713.2613.207.84Diamond Peak Wilderness OR 13.7413.2513.2013.2213.127.84Eagle Cap Wilderness OR 18.5717.8617.8317.7917.718.92Gearhart Mountain Wilderness OR 13.7413.3913.3713.3613.337.84Hells Canyon Wilderness OR 18.5517.2617.2017.1817.048.32Kalmiopsis Wilderness OR 15.5115.0014.9814.9714.939.44Mount Hood Wilderness OR 14.8614.1914.1314.2814.148.44Mount Jefferson Wilderness OR 15.3314.8014.7714.8214.768.79Mount Washington Wilderness OR 15.3314.7714.7514.7814.728.79Mountain Lakes Wilderness OR 13.7413.2613.2413.2313.177.84Strawberry Mountain Wilderness OR 18.5717.7717.7317.6917.608.92Three Sisters Wilderness OR 15.3314.8414.8214.8414.798.79Cape Romain SC 26.4822.7722.7422.7722.7112.12Badlands NP SD 17.1415.8715.8415.8015.758.06Wind Cave NP SD 15.8414.9414.9114.9414.877.71Great Smoky Mountains NP TN 30.2823.9623.9323.9323.8611.24Joyce-Kilmer-Slickrock Wilderness TN 30.2823.4623.4323.4323.3711.24Big Bend NP TX 17.3016.1516.1316.1816.157.16Carlsbad Caverns NP TX 17.1915.9315.9215.9215.906.68**62**Guadalupe Mountains NP TX 17.1915.8915.8815.8915.866.68Arches NP UT 11.2411.1411.1111.0511.036.43Bryce Canyon NP UT 11.6511.3611.3411.3411.316.86Canyonlands NP UT 11.2410.8410.8110.8310.826.43Zion NPUT 13.2412.9612.9212.8912.816.99James River Face Wilderness VA 29.1223.4323.3423.4323.2611.13Shenandoah NP VA 29.3122.8322.8022.8322.7611.35Lye Brook Wilderness VT 24.4521.1021.0821.1721.1111.73Alpine Lake Wilderness WA 17.8416.7716.7116.7216.608.43Glacier Peak Wilderness WA 13.9613.6213.6013.6913.678.01Goat Rocks Wilderness WA 12.7612.0612.0512.0712.038.36Mount Adams Wilderness WA 12.7612.0312.0112.0211.978.36Mount Rainier NP WA 18.2417.2717.2417.2717.218.55North Cascades NP WA 13.9613.5813.5713.6813.678.01Olympic NP WA 16.7415.8515.8215.9515.898.44Pasayten Wilderness WA 15.2314.8514.8414.8314.818.26Dolly Sods Wilderness WV 29.0422.3822.3522.3822.3310.39Otter Creek Wilderness WV 29.0422.3122.2922.3222.2710.39Bridger Wilderness WY 11.1210.8110.8110.8010.806.58Fitzpatrick Wilderness WY 11.1210.8610.8510.8610.846.58Grand Teton NP WY 11.7611.3611.3511.3311.316.51North Absaroka Wilderness WY 11.4511.1711.1611.1511.136.86Red Rock Lakes WY 11.7611.4411.4311.4211.396.51Teton Wilderness WY 11.7611.4111.4011.3911.366.51Washakie Wilderness WY 11.4511.1811.1711.1611.146.86Yellowstone NP WY 11.7611.3911.3811.3611.346.51**63 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**