&EPA
United States
Environmental Protection
Agency
Technical Support Document for the Final
Locomotive/Marine Rule: Air Quality
Modeling Analyses
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EPA 454/R-08-002
January 2008
Technical Support Document for the Final
Locomotive/Marine Rule: Air Quality Modeling
Analyses
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Research Triangle Park, NC 27711
January 2008
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I. Introduction
This document describes the air quality modeling performed by EPA in support of
the final Control of Emissions of Air Pollution from Locomotive Engines and Marine
Compression-Ignition Engines Less than 20 Liters per Cylinder (Locomotive/Marine)
rule. A national scale air quality modeling analysis was performed to estimate the effect
of the rule on future annual fine particulate matter (PM^.s) concentrations, future 8-hour
ozone concentrations, and future visibility levels. To estimate the air quality changes
expected to result from this rule we used the Community Multiscale Air Quality (CMAQ)
model1. The CMAQ model simulates the multiple physical and chemical processes
involved in the formation, transport, and destruction of fine parti culate matter and ozone.
The overall CMAQ modeling platform has been revised from what was used at
proposal. A modeling platform is a structured system of connected modeling-related
tools and data that provide a consistent and transparent basis for assessing the air quality
response to changes in emissions and/or meteorology. A platform typically consists of a
specific air quality model, base year and future year baseline emissions estimates, and a
set of meteorological model inputs. The final Locomotive/Marine rule modeling analyses
were based on a 2002 modeling platform which reflects: a) an updated version of the
CMAQ model, b) higher resolution PM2.5 modeling, c) a longer period of ozone
modeling, and d) updated emissions and meteorological data. These updates from the
previous 2001 platform will be described in more detail in subsequent sections of this
technical support document (TSD).
II. CMAQ Model Version, Inputs and Configuration
A. Model version
CMAQ is a non-proprietary computer model that simulates the formation and fate
of photochemical oxidants, including PM2.5 and ozone, for given input sets of
meteorological conditions and emissions. This analysis employed a version of CMAQ
based on the latest publicly-released version of CMAQ available at the time of the final
Locomotive/Marine rule modeling (i.e., version 4.6) . 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 Multiscale Air Quality (CMAQ) Modeling System.
Applied Mechanics Reviews, Volume 59, Number 2 (March 2006), pp. 51-77.
2
CMAQ version 4.6 was released on September 30, 2006. It is available from the Community Modeling
and Analysis System (CMAS) at: http://www.cmascenter.org .
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added;
2) an updated version of the ISORROPIA aerosol thermodynamics module was
3) the heterogeneous ^Os reaction probability is now temperature- and humidity-
dependent;
4) the gas-phase reactions involving ^Os and H2O are now included; and
5) an updated version of the vertical diffusion module was added (ACM2).
Additionally, there were a few minor changes made to the release version of
CMAQ v4.6 by the EPA model developers subsequent to its release. The relatively
minor changes and new features of this internal version that was ultimately used in this
analysis (version 4.6.H) are described elsewhere.3
B. Model domain and grid resolution
The CMAQ modeling analyses were performed for a domain covering the
continental United States, as shown in Figure II- 1. This domain has a parent horizontal
grid of 36 km with two finer-scale 12 km grids over portions of the eastern and western
U.S. The model extends vertically from the surface to 100 millibars (approximately 15
km) using a sigma-pressure coordinate system. Air quality conditions at the outer
boundary of the 36 km domain were taken from a global model and did not change over
the simulations. In turn, the 36 km grid was only used to establish the incoming air
quality concentrations along the boundaries of the 12 km grids. All of the modeling
results assessing the emissions reductions from the Locomotive/Marine rule were taken
from the 12 km grids. Table II- 1 provides some basic geographic information regarding
the CMAQ domains.
Table II- 1. Geographic elements of domains used in Locomotive/Marine modeling.
Map Projection
Grid Resolution
Coordinate Center
True Latitudes
Dimensions
Vertical extent
CMAQ Modeling Configuration
National Grid
Western U.S. Fine Grid
Eastern U.S. Fine Grid
Lambert Conformal Projection
36km
12km
12km
97degW, 40degN
33 deg N and 45 deg N
148x112x14
213x192x14
279x240x14
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 included in the docket for this rulemaking.
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Figure II-l. Map of the CMAQ modeling domain. The black outer box denotes the
36 km national modeling domain; the red inner box is the 12 km western U.S. fine
grid; and the blue inner box is the 12 km eastern U.S. fine grid.
C. Modeling Period / Ozone Episodes
The 36 km and both 12 km CMAQ modeling domains were modeled for the
entire year of 2002.4 All 365 model days were used in the calculations of the impacts of
the locomotive/marine controls on annual average levels of PM2.5. For the 8-hour ozone
results, we are only using modeling results from the period between May 1 and
September 30, 2002. This 153-day period generally conforms to the ozone season across
most parts of the U.S. and contains the majority of days with observed high ozone
concentrations in 2002.
D. Model Inputs: Emissions, Meteorology and Boundary Conditions
1. Base Year and Future Baseline Emissions: As noted in the introduction
section, a 2001-based platform was used for the proposed rule modeling and a 2002-
based platform was used for the final rule modeling. The 2002-based platform builds
upon the general concepts, tools and emissions modeling data from the 2001-based
We also modeled 10 days at the end of December 2001 as a modeled "ramp up" period. These days are
used to minimize the effects of initial conditions and are not considered as part of the output analyses.
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platform, while updating and enhancing many of the emission inputs and tools. A
summary of the emissions inventory development is described below. More detailed
documentation on the methods and data summaries of the 2002-based platform emissions
for base and future years is also available separately.
We used version 3 of the 2002-based platform which takes emission inventories
from the 2002 National Emissions Inventory (NEI) version 3.0. These inventories, with
the exception of California, include monthly onroad and nonroad emissions generated
from the National Mobile Inventory Model (NMIM) using versions of MOBILE6.0 and
NONROAD2005 consistent with recent national rule analyses.6'7'8 The locomotive and
marine inventories are based on national level estimates developed for the proposed rule
making.9 That is, the base year emissions for locomotive and marine sectors did not
change between the proposal and final modeling. The 2002-based platform and its
associated chemical mechanism (CB05) employs updated speciation profiles using data
included in the SPECIATE4.0 database.10 In addition, the 2002-based platform
incorporates several temporal profile updates for both mobile and stationary sources.
The 2002-based platform includes emissions for a 2002 base year model
evaluation case, a 2002 base case and several projection years. The projection years
include 2020 and 2030, which were used as the future years for the locomotive/marine
rule analyses. The model evaluation case uses prescribed burning and wildfire emissions
specific to 2002, which were developed and modeled as day-specific, location-specific
emissions using an updated version of Sparse Matrix Operator Kernel Emissions
(SMOKE) system, version 2.3, which computes plume rise and vertically allocates the
fire emissions. It also includes continuous emissions monitoring (CEM) data for 2002 for
electric generating units (EGUs) with CEMs. The 2002 and projection year baselines
5 Technical Support Document: Preparation of Emissions Inventories for the 2002-based Platform,
Version 3.0, Criteria Air Pollutants, January 2008. This file is available in the docket for this rulemaking.
6 The California Air Resources Board submitted annual emissions for California. These were allocated to
monthly resolution prior to emissions modeling using data from the National Mobile Inventory Model
(NMIM).
7 MOBILE6 version was used in the Mobile Source Air Toxics Rule: Regulatory Impact Analysis for Final
Rule: Control of Hazardous Air Pollutants from Mobile Sources, U. S. Environmental Protection Agency,
Office of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI 48105,
EPA420-R-07-002, February 2007.
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 Engines, Vessels,
and Equipment, U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Office
of Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI, EPA420-D-07-
004, April 2007.
9
U.S. Environmental Protection Agency, Draft Regulatory Impact Analysis: Control of Emissions of Air
Pollution from Locomotive Engines and Marine Compression-Ignition Engines Less than 30 Liters per
Cylinder, EPA420-D-07-001, January 2007.
10 See http://www.epa.gov/ttn/chief/software/speciate/index.html for more details.
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include an average fire sector and temporally averaged emissions (i.e., no CEM data) for
EGUs. Projections from 2002 were developed to account for the expected impact of
national regulations, consent decrees or settlements, known plant closures, and, for some
sectors, activity growth. For 2030, stationary sources used 2020 projections (i.e., no
activity growth between 2020 and 2030). For the locomotive and marine sectors, the
baseline emissions have not changed from the proposal modeling. Percent reductions
were applied to the 2020 and 2030 baseline emissions to reflect the impacts of the final
Locomotive/Marine rulemaking as shown in Tables II-2a and II-2b. The first five source
sectors are locomotive sectors and the last three are marine sectors.
Table II-2a. Percentage reductions applied to locomotive/marine sectors in 2020 to
reflect the impacts of the final rule.
Pollutant
Class I Railroads
Class Will Railroads
Commuter Railroads
Passenger Railroads
Switch Railroads
Commercial Marine Vessels
Pleasure Craft: Inboard
Pleasure Craft: Outboard
voc
49%
0%
51%
51%
19%
28%
7%
13%
NOX
19%
0%
19%
19%
8%
26%
5%
13%
PM10
41%
0%
43%
43%
21%
29%
3%
8%
PM2.5
41%
0%
43%
43%
21%
29%
3%
8%
S02
0%
0%
0%
0%
0%
5%
0%
0%
Table II-2b. Percentage reductions applied to locomotive/marine sectors in 2030 to
reflect the impacts of the final rule.
Pollutant
Class I Railroads
Class II/III Railroads
Commuter Railroads
Passenger Railroads
Switch Railroads
Commercial Marine Vessels
Pleasure Craft: Inboard
Pleasure Craft: Outboard
VOC
69%
0%
72%
72%
35%
60%
14%
23%
NOX
52%
0%
53%
53%
23%
54%
11%
29%
PM10
63%
0%
66%
66%
38%
58%
8%
17%
PM2.5
63%
0%
66%
66%
38%
58%
8%
17%
SO2
0%
0%
0%
0%
0%
16%
0%
0%
2. Meteorological Input Data: The gridded meteorological input data for the
entire year of 2002 were derived from simulations of the Pennsylvania State University /
National Center for Atmospheric Research Mesoscale Model. This model, commonly
referred to as MM5, is a limited-area, nonhydrostatic, terrain-following system that
solves for the full set of physical and thermodynamic equations which govern
atmospheric motions.11 Meteorological model input fields were prepared separately for
each of the domains shown in Figure II-1. The MM5 simulations were run on the same
11 Grell, G., J. Dudhia, and D. Stauffer, 1994: A Description of the Fifth-Generation Penn State/NCAR
Mesoscale Model (MM5), NCAR/TN-398+STR., 138 pp, National Center for Atmospheric Research,
Boulder CO.
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map projection as CMAQ. The 36 km national domain was modeled using MM5 v.3.6.0
using land-surface modifications that were added in v3.6.3. The 12 km eastern U.S grid
was modeled with MM5 v3.7.2. These two sets of meteorological inputs were developed
by EPA. For the 12 km western U.S. domain, we utilized existing MM5 meteorological
model data prepared by the Western Regional Air Partnership (WRAP).
12
The three meteorological model runs used similar sets of physics options. All
three simulations used the Pleim-Xiu planetary boundary layer and vertical diffusion
scheme, the RRTM longwave radiation scheme, and the Reisner 1 microphysics scheme.
The EPA simulations used the Kain-Fritsch 2 subgrid convection scheme while the
WRAP simulation used the Berts-Miller scheme for subgrid convection. In the EPA
simulations, analysis nudging was utilized above the boundary layer for temperature and
water vapor, and in all locations for the wind components using relatively weak nudging
coefficients. The WRAP runs employed similar four-dimensional data assimilation, but
also included observational nudging of surface winds. All three sets of model runs were
conducted in 5.5 day segments with 12 hours of overlap for spin-up purposes. All three
domains contained 34 vertical layers with an approximately 38m deep surface layer and
a 100 millibar top. The MM5 and CMAQ vertical structures are shown in Table II-3 and
do not vary by horizontal grid resolution.
Table II-3. Vertical layer structure for MM5 and CMAQ (heights are layer top).
CMAQ Layers
0
1
2
3
4
5
6
7
8
9
MM5 Layers
0
1
2
o
J
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Sigma P
1.000
0.995
0.990
0.985
0.980
0.970
0.960
0.950
0.940
0.930
0.920
0.910
0.900
0.880
0.860
0.840
0.820
0.800
0.770
0.740
Approximate
Height (m)
0
38
77
115
154
232
310
389
469
550
631
712
794
961
1,130
1,303
1,478
1,657
1,930
2,212
Approximate
Pressure (mb)
1000
995
991
987
982
973
964
955
946
937
928
919
910
892
874
856
838
820
793
766
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 Configuration for Simulating Meteorology in the Western
United States. Western Regional Air Partnership, Regional Modeling Center. December 10.
(http://pah.cert.ucr.edu/aqm/308/reports/mm5 MM5SensitivityRevRep_Dec_10_2004.pdf)
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10
11
12
13
14
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
0.700
0.650
0.600
0.550
0.500
0.450
0.400
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
2,600
3,108
3,644
4,212
4,816
5,461
6,153
6,903
7,720
8,621
9,625
10,764
12,085
13,670
15,674
730
685
640
595
550
505
460
415
370
325
280
235
190
145
100
The meteorological outputs from all three MM5 sets were processed to create
model-ready inputs for CMAQ using the Meteorology-Chemistry Interface Processor
(MCIP), version 3.1, to derive the specific inputs to CMAQ.
13
Before initiating the air quality simulations, it is important to identify the biases
and errors associated with the meteorological modeling inputs. The 2002 MM5 model
performance evaluations used an approach which included a combination of qualitative
and quantitative analyses to assess the adequacy of the MM5 simulated fields. The
qualitative aspects involved comparisons of the model-estimated synoptic patterns
against observed patterns from historical weather chart archives. Qualitatively, the model
fields closely matched the observed synoptic patterns, which is expected given the use of
nudging. The operational evaluation included statistical comparisons of model/observed
pairs (e.g., mean normalized bias, mean normalized error, index of agreement, root mean
square errors, etc.) for multiple meteorological parameters. For this portion of the
evaluation, four meteorological parameters were investigated: temperature, humidity,
wind speed, and wind direction. The operational piece of the analyses focuses on surface
parameters. The Atmospheric Model Evaluation Tool (AMET) was used to conduct the
analyses as described in this report.14 The three individual MM5 evaluations are
described elsewhere.15'16'17 It was ultimately determined that the bias and error values
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 Atmospheric Model Evaluation Tool (AMET):
Meteorology Module. Presented at 4th Annual CMAS Models-3 Users Conference, Chapel Hill, NC,
September 26 - 28, 2005.
15 Brewer J., P. Dolwick, and R. Gilliam. Regional and Local Scale Evaluation of MM5 Meteorological
Fields for Various Air Quality Modeling Applications, Presented at the 87th Annual American
Meteorological Society Annual Meeting, San Antonio, TX, January 15-18, 2007.
16 Dolwick, P, R. Gilliam, L. Reynolds, and A. Huffman. Regional and Local-scale Evaluation of 2002
MM5 Meteorological Fields for Various Air Quality Modeling Applications, Presented at 6th Annual
CMAS Models-3 Users Conference, Chapel Hill, NC, October 1 - 3, 2007.
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associated with all three sets of 2002 meteorological data were generally within the range
of past meteorological modeling results that have been used for air quality applications.18
3. Initial and Boundary Conditions: The lateral boundary and initial species
concentrations are provided by a three-dimensional global atmospheric chemistry model,
the GEOS-CHEM model.19 The global GEOS-CHEM model simulates atmospheric
chemical and physical processes driven by assimilated meteorological observations from
the NASA's Goddard Earth Observing System (GEOS). This model was run for 2002
with a grid resolution of 2.0 degree x 2.5 degree (latitude-longitude) and 20 vertical
layers. The predictions were used to provide one-way dynamic boundary conditions at
three-hour intervals and an initial concentration field for the CMAQ simulations. More
information is available about the GEOS-CHEM model and other applications using this
tool at: http://www-as.harvard.edu/chemistry/trop/geos.
E. CMAQ Base Case Model Performance Evaluation
An operational model performance evaluation for ozone and PM2.5 and its related
speciated components was conducted using 2002 State/local monitoring sites data in
order to estimate the ability of the CMAQ modeling system to replicate the base year
concentrations for the 12-km eastern and western domains. In summary, model
performance statistics were calculated for observed-predicted pairs of daily, monthly,
seasonal, and annual concentrations. Statistics were generated for the following
geographic groupings: the entire 12-km Eastern US domain (EUS), the entire 12-km
Western US domain (WUS), and five large subregions: Midwest, Northeast, Southeast,
Central, and West U.S.20 The "acceptability" of model performance was judged by
comparing our CMAQ 2002 performance results to the range of performance found in the
2001 CMAQ results used in the proposal, as well as recent regional ozone and PM2.s
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 Modeling 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 Performance 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 15, 2004.
20 The subregions are defined by States where: Midwest is IL, IN, MI, OH, and WI; Northeast is CT, DE,
MA, MD, ME, NH, NJ, NY, PA, RI, and VT; Southeast is AL, FL, GA, KY, MS, NC, SC, TN, VA, and
WV; Central is AR, IA, KS, LA, MN, MO, NE, OK, and TX; West is CA, OR, WA, AZ, NM, CO, UT,
WY, SD, ND, MT, ID, and NV.
21 See: U.S. Environmental Protection Agency; Technical Support Document for the Final Clean Air
Interstate Rule: Air Quality Modeling; Office of Air Quality Planning and Standards; RTF, NC; March
2005 (CAIR Docket OAR-2005-0053-2149); and U.S. Environmental Protection Agency, 2006. Technical
Support Document for the Final PM NAAQS Rule: Office of Air Quality Planning and Standards, Research
Triangle Park, NC
10
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other modeling studies represent a wide range of modeling analyses which cover various
models, model configurations, domains, years and/or episodes, chemical mechanisms,
and aerosol modules.
There are various statistical metrics available and used by the scientific
community for model performance evaluation. The principal evaluation statistics used to
evaluate CMAQ performance were two bias metrics, normalized mean bias and fractional
bias; and two error metrics, normalized mean error and fractional error. Normalized
mean bias (NMB) is used as a normalization to facilitate a range of concentration
magnitudes. This statistic averages the difference (model - observed) over the sum of
observed values. NMB is a useful model performance indicator because it avoids over
inflating the observed range of values, especially at low concentrations. Normalized
mean bias is defined as:
NMB = — !— - - *100, where P = predicted concentrations and O = observed
1(0)
Normalized mean error (NME) is also similar to NMB, where the performance statistic is
used as a normalization of the mean error. NME calculates the absolute value of the
difference (model - observed) over the sum of observed values. Normalized mean error
is defined as:
NME = -^—n - *100, where P = predicted concentrations and O = observed
1(0)
Fractional bias is defined as:
FB= -
n
V
M(P+0)
2
*100, where P = predicted concentrations and O = observed
FB is a useful model performance indicator because it has the advantage of equally
weighting positive and negative bias estimates. The single largest disadvantage in this
estimate of model performance is that the estimated concentration (i.e., prediction, P) is
found in both the numerator and denominator.
11
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Fractional error (FE) is similar to fractional bias except the absolute value of the
difference is used so that the error is always positive. Fractional error is defined as:
i
\ 1
*100, where P = predicted concentrations and O = observed
Overall, the bias and error statistics shown in Table II-4 below indicate that the
base case model ozone and PM2.5 concentrations are within the range or close to that
found in recent OAQPS applications. The CMAQ model performance results give us
confidence that our applications of CMAQ using this 2002 modeling platform provide a
scientifically credible approach for assessing ozone and PM2.5 concentrations for the
purposes of the final Locomotive/Marine rule. A detailed summary of the CMAQ model
performance evaluation is available in the docket for this rulemaking.
the PM2.5 and ozone evaluation is presented here.
22
A summary of
L PM2.5- The PM2.5 evaluation focuses on PM2.5 total mass and its components
including sulfate (SO4), nitrate (NO3), total nitrate (TNO3=NO3+HNO3), ammonium
(NH/i), elemental carbon (EC), and organic carbon (OC). The PM2.5 performance
statistics were calculated for each month and season individually and for the entire year,
as a whole. Seasons were defined as: winter (December-January-February), spring
(March-April-May), summer (June-July-August), and fall (September-October-
November). PM2.5 ambient measurements for 2002 were obtained from the following
networks for model evaluation: Speciation Trends Network (STN- total of 199 sites),
Interagency Monitoring of PROtected Visual Environments (IMPROVE- total of 150),
and Clean Air Status and Trends Network (CASTNet- total of 83). For PM2.5 species
that are measured by more than one network, we calculated separate sets of statistics for
each network. For brevity, Table II-4 provides annual model performance statistics for
PM2.5 and its component species for the 12-km Eastern domain, 12-km Western domain,
and five subregions defined above (Midwest, Northeast, Southeast, Central, and West
U.S.).
Table II-4. Summary of 2002 CMAQ annual PMi.s species model performance
statistics.
CMAQ 2002 Annual
PM2.5
Total Mass
STN
12-km BUS
12-km WUS
No. of Obs.
10307
3000
NMB (%)
10.8
-5.8
NME (%)
42.8
46.9
FB (%)
5.4
-3.1
FE (%)
42.6
45.0
Technical Support Document: 2002 CMAQ Model Performance Evaluation for Ozone and Paniculate
Matter, January 2008. This file is available in the docket for this rulemaking.
12
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Sulfate
Nitrate
IMPROVE
STN
IMPROVE
CASTNet
STN
IMPROVE
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-km WUS
1516
2780
2554
2738
2487
8436
10123
592
2060
1803
1624
9543
10157
2926
1487
2730
2541
2686
2446
8532
10232
597
2070
1805
1671
9645
3173
1158
663
839
1085
229
1118
8770
2726
1488
2731
2540
1298
2446
8514
10110
14.9
20.5
-3.9
14.5
-7.4
-2.3
-26.4
8.6
21.0
-13.1
-13.1
-27.8
-3.9
-20.6
3.6
-4.3
-7.6
-3.2
-26.1
-10.8
-7.5
-4.9
-12.3
-9.5
-16.1
-5.5
-11.3
-21.3
-8.3
-12.3
-11.2
-20.7
-20.4
18.3
-45.0
17.4
32.7
8.6
12.7
-47.5
48.4
-34.8
35.6
48.2
36.0
49.1
46.8
49.0
53.5
41.5
59.4
41.2
49.4
53.1
33.6
41.9
34.9
29.1
33.4
39.2
44.9
33.0
42.4
29.9
30.1
32.9
35.0
43.5
20.5
34.6
19.3
17.9
21.5
27.3
35.3
65.9
63.1
59.1
70.4
84.6
52.5
62.8
106.8
80.67
13.2
16.6
-10.0
6.0
-4.5
-5.7
-26.3
2.4
17.4
-19.8
-17.6
-27.1
-9.7
-12.2
-2.9
-8.8
-16.3
-7.2
-15.8
-7.2
7.6
-10.0
-9.9
-16.8
-16.0
8.6
-16.3
-11.2
-16.3
-15.6
-17.8
-27.4
-10.7
-29.1
-70.6
-5.0
-10.9
-64.7
-13.4
-73.8
-52.8
-101.0
34.4
42.6
39.7
49.4
44.8
51.4
57.5
41.0
51.6
49.9
57.0
57.2
38.4
43.5
36.2
33.6
38.8
44.3
44.8
40.6
45.7
35.7
36.1
40.5
42.4
45.9
26.1
35.9
24.3
21.6
27.2
33.6
36.1
84.5
95.0
67.3
78.1
107.5
69.1
95.4
116.4
130.0
13
-------
Total Nitrate
(N03+HN03)
Ammonium
Elemental
Carbon
Organic
Carbon
CASTNet
STN
CASTNet
STN
IMPROVE
STN
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
597
2069
1803
1672
9522
3171
1157
662
839
1085
229
1117
10157
2926
1488
2731
2540
2685
2446
3166
1156
661
837
1085
229
1116
10031
2975
1498
2744
2506
2570
2475
8282
10069
599
2056
1795
1532
9493
9726
2903
43.0
122.2
33.5
18.1
-39.6
24.4
-19.5
20.5
39.1
22.9
6.2
-20.4
11.9
-23.6
16.0
12.3
7.3
15.0
-30.6
5.3
-16.8
15.3
9.8
-7.7
7.4
-21.1
45.0
43.1
37.1
53.1
16.9
91.7
49.0
-15.0
-14.1
-22.6
11.6
-32.4
-24.3
-15.5
-39.9
-37.6
86.0
153.8
112.2
81.0
81.1
37.3
44.2
29.4
46.5
39.5
35.6
45.8
40.6
55.7
39.6
38.4
38.4
46.6
56.7
30.8
42.5
27.6
34.7
30.1
33.1
43.5
78.9
82.6
58.9
76.7
66.0
118.0
86.2
49.2
67.2
37.5
57.5
44.6
47.6
67.8
58.0
60.3
-37.0
3.5
-78.5
-59.6
-104.0
16.8
-12.0
16.3
29.0
15.8
0.6
-12.1
14.4
7.2
21.8
19.2
6.0
14.3
2.9
2.7
-13.0
13.6
11.9
-9.7
3.0
-14.4
22.1
18.2
24.5
26.3
7.2
41.0
17.1
-23.4
-29.5
-27.4
0.5
-42.0
-29.8
-31.3
-41.1
-40.4
102.8
107.5
130.8
114.1
131.1
35.1
46.0
25.3
39.7
37.2
36.2
46.6
45.2
58.1
42.8
42.4
41.8
52.1
59.7
31.6
41.1
25.2
33.9
33.6
35.6
41.4
56.9
61.3
48.3
54.7
51.7
68.1
62.7
52.8
62.1
46.5
50.8
55.6
55.9
62.7
70.5
69.3
14
-------
IMPROVE
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
1447
2641
2474
2504
2408
8287
10082
598
2057
1800
1531
9508
-45.2
-26.5
-47.4
-43.6
-36.3
-32.4
-34.8
-42.4
-6.4
-46.1
-47.9
-34.5
60.9
61.7
55.3
54.0
61.4
60.5
60.0
54.8
68.2
58.4
61.6
59.6
-41.6
-19.7
-53.7
-51.3
-37.9
-37.1
-31.2
-40.2
-0.7
-69.7
-61.2
-29.7
73.1
67.6
70.7
69.7
70.2
67.9
63.0
63.8
60.8
81.3
79.6
61.9
2. Ozone: The ozone evaluation focuses on the observed and predicted hourly
ozone concentrations and eight-hour daily maximum ozone concentrations using a
(observation) threshold of 40 ppb. This ozone model performance was limited to the
period used in the calculation of projected design values within the analysis, that is: May,
June, July, August, and September. Ozone ambient measurements for 2002 were
obtained from the Air Quality System (AQS) Aerometric Information Retrieval System
(AIRS). A total of 1178 ozone measurement sites were included for evaluation. These
ozone data were measured and reported on an hourly basis.
Table II-5 and II-6 provide hourly and eight-hour daily maximum ozone model
performance statistics, respectively, for the 12-km Eastern and Western U.S. domain and
the five subregions. Generally, hourly and eight-hour ozone model performance are
under-predicted in both the 12-km BUS and WUS when applying a threshold of 40 ppb
for the modeled ozone season (May-September). For the 12-km BUS and WUS domain,
the bias and error statistics are comparable for the aggregate of the ozone season and for
each individual ozone month modeled.
Table II-5. Summary of CMAQ 2002 hourly ozone model performance statistics
CMAQ 2002 Hourly Ozone:
Threshold of 40 ppb
May
June
12-kmEUS
12-km WUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-km WUS
Northeast
No. of Obs.
241185
124931
51055
55859
69073
41728
111385
256263
125662
61354
NMB (%)
-0.7
-3.7
1.2
3.3
-2.5
-6.4
-3.9
-7.5
-8.4
-8.5
NME (%)
15.9
15.9
17.1
16.2
14.1
17.3
16.1
16.8
17.7
17.3
FB (%)
-2.0
-5.0
-0.3
2.4
-3.1
-9.2
-5.2
-9.0
-9.3
-9.9
FE (%)
17.1
17.3
18.2
16.9
14.8
20.3
17.6
18.6
19.1
19.1
15
-------
July
August
September
Seasonal Aggregate
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central U
West
54515
67867
46026
109157
257076
116785
66774
59360
68619
36021
104321
235090
125575
53837
54179
62506
41456
110225
179156
99710
44678
34285
41627
41549
83921
1168770
592663
277698
258198
309692
206780
519009
-7.2
-7.2
-10.0
-8.8
-5.3
-12.0
-3.9
-10.5
-3.6
-3.6
-13.6
-8.7
-7.9
-6.4
-10.8
-9.4
-9.3
-8.5
-9.9
-10.7
-8.7
-11.4
-8.2
-12.8
-11.7
-6.4
-8.4
-5.4
-7.3
-6.0
-8.6
-9.2
17.9
15.3
17.5
18.2
17.7
21.5
17.0
19.4
16.5
18.7
21.8
17.8
20.1
16.7
19.1
17.3
18.7
20.6
17.2
19.0
16.3
18.5
16.5
18.8
20.0
17.1
18.8
16.9
18.3
15.9
18.2
19.3
-8.3
-7.6
-13.5
-9.9
-6.6
-14.9
-4.8
-12.3
-3.9
-6.3
-16.8
-10.2
-10.2
-7.4
-12.4
-9.9
-12.8
-11.1
-11.8
-12.7
-10.6
-12.9
-9.0
-16.6
-13.8
-7.7
-10.3
-6.5
-8.4
-6.4
-11.9
-11.2
19.6
16.3
21.2
19.7
19.2
24.3
18.0
21.7
17.2
21.1
24.9
19.7
22.1
18.0
21.4
18.5
22.4
22.8
19.5
21.1
18.4
20.4
17.8
22.8
22.1
18.8
20.7
18.4
20.0
16.8
21.6
21.3
Table II-6. Summary of CMAQ 2002 eight-hour daily maximum ozone model
performance statistics.
CMAQ 2002 Eight-Hour Maximum Ozone:
Threshold of 40 ppb
May
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
No. of Obs.
19172
9223
4255
4198
5470
NMB (%)
3.9
0.2
6.7
7.8
0.6
NME (%)
12.7
12.6
14.3
13.7
10.9
FB (%)
4.3
0.6
6.8
8.2
1.1
FE (%)
12.6
12.8
14.2
13.5
11.0
16
-------
June
July
August
September
Seasonal Aggregate
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
12-kmEUS
12-kmWUS
Northeast
Midwest
Southeast
Central
West
3379
8155
19462
9029
4608
4104
5110
3603
7818
20565
8809
5380
4368
5633
3114
7784
19260
9551
4667
4012
5067
3543
8311
15865
8185
4074
3120
3671
3492
6911
94324
44797
22984
19802
24951
17131
38979
0.3
-0.1
-3.9
-4.9
-5.3
-3.2
-4.8
-4.5
-5.3
-1.6
-7.4
-0.7
-6.5
-0.9
1.3
-9.0
-5.1
-2.8
-2.9
-8.1
-6.4
-4.0
-3.2
-6.2
-6.7
-6.0
-7.2
-4.5
-8.5
-7.3
-2.6
-4.3
-1.9
-3.6
-3.1
-3.3
-4.9
12.3
12.8
12.3
14.1
12.5
12.7
11.8
12.2
14.5
13.5
17.1
13.0
14.2
13.0
14.4
17.2
13.2
15.8
12.4
13.9
13.4
13.5
16.1
12.6
15.0
11.8
13.3
12.6
13.8
15.9
12.9
14.9
12.8
13.6
12.4
13.2
15.3
0.7
0.3
-3.3
-4.2
-4.7
-2.2
-4.1
-4.4
-4.7
-1.0
-8.1
-0.2
-5.8
-0.1
1.2
-9.9
-4.4
-3.1
-2.2
-7.5
-5.4
-3.9
-3.6
-5.9
-6.9
-6.0
-6.5
-3.8
-8.7
-7.6
-1.9
-4.2
-1.2
-2.5
-2.3
-3.1
-5.0
12.4
12.9
12.4
14.2
12.7
12.8
11.9
12.7
14.7
13.6
18.0
12.9
14.4
13.0
14.7
18.2
13.4
16.1
12.4
14.2
13.4
14.1
16.5
12.9
15.5
12.3
13.3
12.7
14.5
16.4
13.0
15.3
12.9
13.7
12.4
13.7
15.7
F. CMAQ Locomotive/Marine Modeling Scenarios
The CMAQ modeling system was used to calculate annual PM2.5 concentrations,
daily 8-hour ozone concentrations, and visibility estimates for each of the following
seven emissions scenarios:
17
-------
1) 2002 base case
2) 2020 future baseline
3) 2020 future control case - locomotive and marine controls
4) 2020 future control case - marine controls only
5) 2030 future baseline
6) 2030 future control case - locomotive and marine controls
7) 2030 future control case - marine controls only
Model predictions are used in a relative sense to estimate scenario-specific,
future-year design values of PM2.5 and ozone. This is done by calculating the simulated
air quality ratios between any particular future year simulation and the 2002 base. These
predicted change ratios are then applied to ambient base year design values. The design
value projection methodology used in this analysis followed EPA guidance for such
analyses23 We used the 5-year weighted average 2000-2004 design values as the starting
point for the projections. Additionally, the raw model outputs are also used in a relative
sense for creating inputs to the health and welfare impact functions of the benefits
analysis.
III. CMAQ Model Results
A. Impacts of Locomotive/Marine Rule on Future PMi.s Annual Averages
This section summarizes the results of our modeling of PM2.5 air quality impacts
in the future due to the reductions in locomotive and commercial marine diesel emissions.
Appendix A contains annual average PM2.5 design values by county for each modeling
scenario. The modeling results indicate that the emissions reductions from this rule will
contribute to lower ambient PM2.5 levels in future years. Tables III-l and III-2 show the
projected improvements in average annual PM2.5 design values, for various years as a
result of the Locomotive/Marine control scenarios discussed in Section II.F.
23 U.S. EPA, Guidance on the Use of Models and Other Analyses in Attainment Demonstrations for the 8-
hour Ozone NAAQS; EPA-454/R-05-002; Research Triangle Park, NC; October 2005.
18
-------
Table III-l. Model-projected change in annual average PMi.s design values
resulting from the Locomotive/Marine modeling scenarios for several categories of
counties. Units are ug/m3.
Average change
Average change in all counties
Average change in counties whose base year
design value is above the NAAQS
Average change in counties whose base year
design value is within 10% of the NAAQS
Average change in counties whose projection year
design value is above the NAAQS
Average change in counties whose projection year
design value is within 10% of the NAAQS
2020
marine
controls
only
-0.02
-0.03
-0.03
-0.06
-0.04
2020
locomotive
and
marine
controls
-0.04
-0.06
-0.06
-0.10
-0.09
2030
marine
controls
only
-0.04
-0.05
-0.06
-0.14
-0.09
2030
locomotive
and
marine
controls
-0.08
-0.11
-0.12
-0.22
-0.18
Table III-2. Model-projected, population-weighted, change in annual average
design values resulting from the Locomotive/Marine modeling scenarios for several
categories of counties. Units are ug/m3.
Average change
Average change in all counties
Average change in counties whose base year
design value is above the NAAQS
Average change in counties whose base year
design value is within 10% of the NAAQS
Average change in counties whose projection year
design value is above the NAAQS
Average change in counties whose projection year
design value is within 10% of the NAAQS
2020
marine
controls
only
-0.03
-0.05
-0.04
-0.07
-0.05
2020
locomotive
and
marine
controls
-0.06
-0.08
-0.08
-0.11
-0.09
2030
marine
controls
only
-0.08
-0.11
-0.10
-0.16
-0.12
2030
locomotive
and
marine
controls
-0.12
-0.16
-0.16
-0.21
-0.18
The modeling projects that 11 counties will have design values greater than 15.0
|ig/m3 in 2020 and 2030. Over 24 million people are projected to live in a PM2.5
nonattainment county in the future. The controls from the final Locomotive/Marine rule
modeling are enough to bring one of those counties (Merced Co., CA) into attainment by
2030. As can be seen from Table III-l, the final Locomotive/Marine rule controls will
lower PM2.5 concentrations on average by 0.04 |ig/m3 in 2020 and 0.08 |ig/m3 in 2030.
Greater improvements in PM2.5 air quality are projected in areas where present-day and
future-projected PM2.5 levels are above or near the NAAQS. For instance, when
considering only those counties whose future year design values are projected to exceed
the NAAQS, the average improvement resulting from this rule is 0.10 |ig/m3 in 2020 and
0.22 |ig/m3 in 2030. Additionally, as shown in Table III-2, the improvements resulting
from the rule are larger when population-weighted. The greatest impacts from the final
19
-------
Locomotive/Marine rule emissions reductions tend to occur in areas with high
populations. The largest reduction in annual average PM2.5 occurs in Houston TX (Harris
Co.) where the rule is projected to result in a 0.38 |ig/m3 improvement in 2020 and 0.81
|ig/m3 in 2030. The largest reduction in an area that is projected to exceed the PM2.5
NAAQS in 2020 and 2030 is in the Los Angeles region (Riverside Co.) where the annual
average PM2.5 design value is projected to drop from 22.67 to 22.48 |ig/m3 in 2020, and
22.54 to 22.13 |ig/m3 in 2030 as a result of the final Locomotive/Marine rule. The
modeling indicated that both the locomotive and marine components of the rule improved
PM2.5 air quality relatively equally.
Figures III-l through III-4 display the projected county-level, annual PM2.5 design
value changes expected from various locomotive/marine control scenarios and years
associated with this rule. The largest impacts tend to be in areas near water, where
commercial marine source contributions can be large.
20
-------
Figure III-l. Model-projected change in annual PMi.s design values from the
Locomotive/Marine control scenario in 2020. Units are ug/m3.
Legend
^B -1.00 to-0.50 0
^|-0.49 to-0.25 4
|-0.24 to-0.10 43
|-0.09 to-0.05 142
|-0.04 to 0.00 367
0.00 0
Number of Counties
Differences due to scenario 2020cc Locomarine
Figure III-2. Model-projected change in annual PMi.s design values from the
Marine-only control scenario in 2020. Units are jig/m3.
-0.24 to-0.10 19
-0.09 to -0.05 37
-0.04 to 0.00 496
> 0.00 1
Differences due to scenario 2020cc Marine-only
21
-------
Figure III-3. Model-projected change in annual PMi.s design values from the
Locomotive/Marine control scenario in 2030. Units are ug/m3.
Legend
Number of Counties
L_H-1.00 to-0.50 4
^B-0.49 to-0.25 20
|-0.24 to-0.10 143
|-0.09 to-0.05 193
|-0.04 to 0.00 196
I I > 0.00 0
Differences due to scenario 2030cc Locomarine
Figure III-4. Model-projected change in annual PMi.s design values from the
Marine-only control scenario in 2030. Units are jig/m3.
Legend Number of Counties
^B -1.0°lo -O-50 4
^|-0.49 to-0.25 11
|-0.24 to-0.10 46
Q^ -0.09 to -0.05 46
Q^ -0.04 to 0.00 449
| > 0.00 0
Differences due to scenario 2030cc Marine-only
22
-------
B. Impacts of the Locomotive/Marine Rule on Future 8-Hour Ozone Levels
This section summarizes the results of our modeling of ozone air quality impacts
in the future due to the reductions in locomotive and commercial marine diesel emissions.
Appendix B contains 8-hour ozone design values by county for each modeling scenario.
The modeling results indicate that the emissions reductions from this rule will contribute
to lower ambient 8-hour ozone design values in future years. Tables III-3 and III-4 show
the projected improvements in average 8-hour ozone design values, for various years as a
result of the four Locomotive/Marine control scenarios.
Table III-3. Model-projected change in average 8-hour ozone design values
resulting from the Locomotive/Marine modeling scenarios for several categories of
counties. Units are ppb.
Average change
Average change in all counties
Average change in counties whose base year
design value is above the NAAQS
Average change in counties whose base year
design value is within 10% of the NAAQS
Average change in counties whose projection year
design value is above the NAAQS
Average change in counties whose projection year
design value is within 10% of the NAAQS
2020
marine
controls
only
-0.23
-0.22
-0.23
0.00
-0.20
2020
locomotive
and
marine
controls
-0.45
-0.45
-0.46
-0.19
-0.41
2030
marine
controls
only
-0.51
-0.51
-0.53
0.00
-0.65
2030
locomotive
and
marine
controls
-1.15
-1.18
-1.18
-0.50
-1.24
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
Average change in all counties
Average change in counties whose base year
design value is above the NAAQS
Average change in counties whose base year
design value is within 10% of the NAAQS
Average change in counties whose projection year
design value is above the NAAQS
Average change in counties whose projection year
design value is within 10% of the NAAQS
2020
marine
controls
only
-0.12
-0.09
-0.12
-0.01
+0.05
2020
locomotive
and
marine
controls
-0.30
-0.27
-0.31
-0.13
-0.08
2030
marine
controls
only
-0.32
-0.26
-0.32
-0.24
-0.42
2030
locomotive
and
marine
controls
-0.85
-0.78
-0.86
-0.62
-0.79
23
-------
The modeling projects that 9 counties will have design values greater than 0.08
ppm in 2020 and 6 counties will exceed that level in 2030. Based on this modeling, over
22 million people are projected to live in a ozone nonattainment county in 2020. The
controls from the final Locomotive/Marine rule modeling are enough to bring one of
those counties (Kenosha Co., WI) into attainment by 2020. Further, two of the nine
counties will be at least 10 percent closer to a design value of less than 85 ppb, and on
average all nine counties will be about 18 percent closer to a design value of less than 85
ppb (including Kenosha Co., WI).
As can be seen from Table III-3, the final Locomotive/Marine rule controls will
lower ozone design values on average by 0.30 ppb in 2020 and 0.85 ppb in 2030. Unlike
PM2.5, there are instances in which the final Locomotive/Marine rule controls are
projected to increase ozone levels. As a result of where these "disbenefit" areas are
located, the improvements resulting from the rule are smaller when population-weighted.
The largest increase in a county-level 8-hour ozone design values occurs in the Los
Angeles area (Orange Co.) where the rule is projected to result in an increase of 2.6 ppb
in 2020 and 5.5 ppb in 2030. This increase is highly localized. The county with the
second largest increase from the rule is Riverside Co. CA which is projected to have an
0.5 ppb increase from the rule in 2030. The largest county-level decrease resulting from
the rule is north of the Los Angeles area (Santa Barbara Co.) where ozone levels are
projected to drop by 1.8 and 4.6 ppb, respectively, in 2020 and 2030. Again, the
modeling indicated that both the locomotive and marine components of the rule improved
air quality relatively equally, but it was the marine reductions that tended to lead to the
"disbenefit" regions.
Figures III-5 through III-8 display the projected county-level, 8-hour ozone
design value changes expected from the final Locomotive/Marine rule control scenarios.
The largest impacts tend to be in areas near water, where commercial marine source
contributions can be large.
24
-------
Figure III-5. Model-projected change in annual 8-hour ozone design values from
the Locomotive/Marine control scenario in 2020. Units are ppb.
Legend
Q^ <= -2.0
^B >-2.0to<=-1.0 14
^f >-1.0to<=-0.5 241
>-0.5to<=-0.1 315
1=0.0 5
^f >0.0to<= 1.0 3
Effect of Locomarine in 2020
Figure III-6. Model-projected change in annual 8-hour ozone design values from
the marine-only control scenario in 2020. Units are ppb.
Legend Number of Counties
^H >-2.0to<=-1.0 9
| >-1.Qto<=-0.5 63
| >-0.5to<=-0.1 450
Effect of Marine-only in 2020
25
-------
Figure III-7. Model-projected change in annual 8-hour ozone design values from
the Locomotive/Marine control scenario in 2030. Units are ppb.
Effect of LocoMarine in 2030
Figure III-8. Model-projected change in annual 8-hour ozone design values from
the marine-only control scenario in 2030. Units are ppb.
Legend Number of Counties
^H >-2.0to<=-1.0 71
| >-1.Qto<=-0.5 170
| >-0.5to<=-0.1 306
^B=°-° 13
^f > 0.0 to <= 1.0 9
Effect of Marine-only in 2030
26
-------
C. Impacts of the Locomotive/Marine Rule on Visibility
The modeling conducted for the Locomotive/Marine rule was also used to project
the impacts of the reductions on visibility conditions over 133 mandatory class I federal
areas across the U.S. in 2020 and 2030. The results indicate that reductions in regional
haze would occur in all 133 of these federal areas. The model projects that average
visibility on the 20% worst days would improve by 0.02 deciviews.24 The average
deciview improvement on the 20% worst days is 0.06 in 2030. The greatest visibility
improvement due to this rule would occur at the San Gorgonio Wilderness where a 0.24
deciview improvement is projected by 2030 as a result of the locomotive/marine controls
in this rule. Appendix C contains the visibility results from the locomotive/marine
scenario over the 133 Class 1 areas.
24 The level of visibility impairment in an area is based on the light-extinction coefficient and a unit less
visibility index, called a "deciview", which is used in the valuation of visibility. The deciview metric
provides a scale for perceived visual changes over the entire range of conditions, from clear to hazy. Under
many scenic conditions, the average person can generally perceive a change of one deciview. The higher
the deciview value, the worse the visibility. Thus, an improvement in visibility is a decrease in deciview
value.
27
-------
Appendix A: Annual Average PM2.s Design Values for Locomotive/Marine Scenarios (units are ug/m )
State Name
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
Arkansas
California
County Name
Baldwin Co
Clay Co
Colbert Co
DeKalb Co
Escambia Co
Etowah Co
Jefferson Co
Madison Co
Mobile Co
Montgomery Co
Morgan Co
Russell Co
Shelby Co
Sumter Co
Talladega Co
Cochise Co
Gila Co
Maricopa Co
Pima Co
Final Co
Santa Cruz Co
Arkansas Co
Ashley Co
Crittenden Co
Faulkner Co
Mississippi Co
Phillips Co
Polk Co
Pope Co
Pulaski Co
Sebastian Co
Union Co
White Co
Alameda Co
Baseline DV
11.38
13.50
13.02
14.86
12.82
15.69
18.36
14.20
12.80
14.50
13.36
16.04
14.50
12.26
14.96
6.97
9.52
11.45
6.75
8.14
11.74
12.13
12.14
12.91
12.40
11.84
12.16
11.08
12.23
14.12
12.33
12.64
11.63
11.76
2020 Base
9.14
10.45
10.23
11.21
10.48
12.02
15.00
10.74
10.72
11.76
10.35
13.15
11.36
9.78
11.48
6.60
8.89
10.30
6.13
7.45
11.24
10.08
10.28
10.66
10.33
9.66
10.20
9.02
10.13
11.63
10.33
11.01
9.57
10.77
2020 Marine only
9.13
10.44
10.22
11.20
10.47
12.01
14.99
10.74
10.58
11.75
10.34
13.14
11.36
9.77
11.48
6.60
8.89
10.30
6.13
7.45
11.24
10.06
10.26
10.60
10.32
9.62
10.12
9.02
10.12
11.61
10.33
10.99
9.56
10.75
2020 Locomotive
/ Marine
9.12
10.41
10.20
11.18
10.46
11.98
14.95
10.72
10.56
11.72
10.32
13.13
11.32
9.75
11.44
6.60
8.88
10.29
6.12
7.42
11.23
10.03
10.24
10.55
10.28
9.60
10.10
9.00
10.10
11.55
10.31
10.98
9.52
10.73
2030 Base
9.19
10.45
10.24
11.20
10.50
11.99
14.95
10.75
10.95
11.75
10.36
13.14
11.38
9.81
11.47
6.61
8.87
10.31
6.12
7.59
11.27
10.09
10.33
10.93
10.34
9.73
10.38
9.04
10.12
11.60
10.33
11.04
9.57
10.68
2030 Marine only
9.15
10.44
10.22
11.19
10.48
11.98
14.94
10.73
10.64
11.75
10.34
13.13
11.37
9.78
11.46
6.61
8.87
10.31
6.12
7.59
11.27
10.06
10.29
10.81
10.33
9.65
10.19
9.02
10.11
11.57
10.32
11.01
9.54
10.64
2030 Locomotive
/ Marine
9.14
10.38
10.19
11.15
10.44
11.92
14.88
10.71
10.62
11.69
10.30
13.10
11.31
9.74
11.38
6.60
8.86
10.28
6.10
7.55
11.27
10.00
10.26
10.73
10.26
9.62
10.17
8.99
10.06
11.46
10.29
10.97
9.48
10.60
28
-------
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
Colorado
Butte Co
Calaveras Co
Colusa Co
Contra Costa Co
Fresno Co
Humboldt Co
Imperial Co
Inyo Co
Kern Co
Kings Co
Lake Co
Los Angeles Co
Mendocino Co
Merced Co
Monterey Co
Nevada Co
Orange Co
Placer Co
Riverside Co
Sacramento Co
San Bernardino Co
San Diego Co
San Francisco Co
San Joaquin Co
San Luis Obispo Co
San Mateo Co
Santa Barbara Co
Santa Clara Co
Santa Cruz Co
Shasta Co
Solano Co
Sonoma Co
Stanislaus Co
Sutler Co
Tulare Co
Ventura Co
Yolo Co
Adams Co
13.69
8.85
9.44
11.32
20.02
8.48
14.44
6.17
21.77
18.77
5.03
23.16
8.00
16.47
8.23
7.97
18.27
11.65
27.15
12.56
24.63
15.65
11.58
14.84
9.20
10.58
9.32
11.33
8.17
9.01
12.03
9.91
16.49
11.39
21.33
14.34
10.04
10.29
11.84
7.83
8.78
10.53
17.54
7.34
13.92
5.94
19.28
16.82
4.73
20.69
7.22
15.15
7.74
7.25
15.73
10.21
22.67
11.47
21.79
14.64
11.08
13.58
8.79
9.77
9.06
10.10
7.38
7.74
11.64
9.22
14.57
10.14
18.71
12.54
9.11
8.91
11.83
7.82
8.78
10.50
17.52
7.33
13.91
5.95
19.26
16.80
4.72
20.64
7.21
15.14
7.73
7.25
15.60
10.20
22.53
11.46
21.69
14.61
10.94
13.54
8.79
9.76
9.05
10.09
7.38
7.74
11.58
9.21
14.54
10.13
18.69
12.45
9.10
8.91
11.80
7.80
8.77
10.49
17.47
7.33
13.87
5.94
19.21
16.76
4.72
20.61
7.21
15.11
7.72
7.23
15.58
10.17
22.48
11.43
21.66
14.60
10.93
13.51
8.78
9.74
9.05
10.08
7.37
7.73
11.57
9.21
14.50
10.10
18.64
12.44
9.08
8.87
11.76
7.84
8.75
10.57
17.14
7.36
13.97
5.96
18.87
16.55
4.73
20.86
7.20
15.11
7.75
7.31
15.93
10.07
22.54
11.36
21.97
14.91
11.58
13.57
8.85
9.70
9.12
9.95
7.30
7.76
11.88
9.21
14.30
10.07
18.24
12.59
8.99
8.80
11.75
7.82
8.74
10.50
17.09
7.34
13.95
5.96
18.83
16.52
4.73
20.75
7.19
15.08
7.74
7.31
15.68
10.04
22.21
11.33
21.75
14.83
11.27
13.48
8.84
9.68
9.10
9.93
7.29
7.76
11.76
9.21
14.23
10.06
18.19
12.40
8.97
8.80
11.69
7.79
8.72
10.48
16.97
7.33
13.88
5.95
18.70
16.43
4.72
20.72
7.18
15.02
7.73
7.26
15.65
9.97
22.13
11.27
21.71
14.82
11.26
13.41
8.82
9.65
9.09
9.91
7.28
7.73
11.74
9.20
14.13
9.98
18.07
12.38
8.92
8.74
29
-------
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Connecticut
Connecticut
Connecticut
Connecticut
Delaware
Delaware
Delaware
District of
Columbia
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Arapahoe Co
Archuleta Co
Boulder Co
Delta Co
Denver Co
El Paso Co
Elbert Co
Gunnison Co
Larimer Co
Pueblo Co
Routt Co
San Miguel Co
Weld Co
Fairfield Co
Hartford Co
New Haven Co
New London Co
Kent Co
New Castle Co
Sussex Co
District of Columbia
Alachua Co
Bay Co
Brevard Co
Broward Co
Citrus Co
Duval Co
Escambia Co
Hillsborough Co
Lee Co
Leon Co
Manatee Co
Marion Co
Miami-Dade Co
Orange Co
Palm Beach Co
Pinellas Co
Polk Co
8.70
5.99
9.27
8.26
10.58
7.86
4.33
6.69
7.88
7.79
7.40
5.33
9.33
12.85
11.50
13.71
11.57
12.81
15.96
13.65
15.75
10.12
11.04
7.88
8.30
9.13
10.64
11.56
11.25
8.42
12.67
9.31
10.04
9.66
10.19
7.54
10.46
10.36
7.76
5.55
8.20
7.44
9.22
7.16
3.92
6.26
7.21
7.16
6.98
4.99
8.14
11.39
9.84
11.48
9.60
9.54
12.35
10.52
11.72
7.71
9.01
5.65
6.29
6.73
8.49
9.63
8.40
6.10
10.19
6.56
7.56
7.51
7.37
5.75
7.84
7.49
7.76
5.55
8.19
7.44
9.22
7.16
3.92
6.26
7.21
7.16
6.98
4.99
8.14
11.38
9.84
11.47
9.60
9.53
12.33
10.51
11.71
7.71
8.98
5.64
6.23
6.73
8.43
9.62
8.31
6.10
10.18
6.55
7.56
7.39
7.37
5.75
7.83
7.49
7.74
5.55
8.17
7.42
9.19
7.14
3.91
6.26
7.19
7.13
6.98
4.99
8.10
11.37
9.84
11.46
9.60
9.52
12.30
10.50
11.69
7.71
8.98
5.64
6.23
6.72
8.43
9.62
8.30
6.10
10.16
6.55
7.56
7.39
7.37
5.75
7.82
7.49
7.80
5.54
8.19
7.40
9.12
7.14
3.98
6.25
7.16
7.16
6.96
4.98
8.16
11.54
9.86
11.52
9.66
9.61
12.52
10.54
11.73
7.70
9.03
5.65
6.40
6.73
8.62
9.63
8.57
6.08
10.13
6.57
7.54
7.60
7.39
5.80
7.84
7.52
7.80
5.54
8.19
7.40
9.11
7.14
3.98
6.25
7.16
7.16
6.96
4.98
8.16
11.52
9.85
11.48
9.65
9.58
12.46
10.52
11.73
7.70
8.98
5.64
6.27
6.72
8.49
9.62
8.38
6.08
10.12
6.55
7.54
7.37
7.39
5.79
7.83
7.51
7.75
5.54
8.14
7.35
9.06
7.09
3.95
6.25
7.13
7.11
6.94
4.97
8.08
11.51
9.85
11.48
9.64
9.56
12.42
10.50
11.69
7.69
8.97
5.64
6.26
6.72
8.48
9.60
8.37
6.08
10.08
6.54
7.53
7.36
7.39
5.79
7.82
7.50
30
-------
Florida
Florida
Florida
Florida
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Idaho
Idaho
Idaho
Idaho
Idaho
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Sarasota Co
Seminole Co
St. Lucie Co
Volusia Co
Bibb Co
Chatham Co
Clarke Co
Clayton Co
Cobb Co
DeKalb Co
Dougherty Co
Floyd Co
Fulton Co
Glynn Co
Gwinnett Co
Hall Co
Houston Co
Lowndes Co
Muscogee Co
Paulding Co
Richmond Co
Walker Co
Washington Co
Wilkinson Co
Ada Co
Bannock Co
Canyon Co
Power Co
Shoshone Co
Adams Co
Champaign Co
Cook Co
DuPage Co
Kane Co
Lake Co
Macon Co
Madison Co
McHenry Co
9.28
9.31
8.61
9.28
15.69
13.87
15.75
16.48
16.29
16.22
14.24
15.71
18.29
11.89
16.20
15.14
13.04
12.14
14.86
14.30
15.05
15.44
14.21
15.15
9.17
8.56
9.26
9.82
12.72
12.88
12.56
17.06
14.36
13.93
12.54
13.87
17.27
12.73
6.70
6.63
6.26
6.73
12.37
11.94
11.51
12.38
12.28
12.43
11.65
11.77
14.22
9.67
12.29
11.71
10.15
9.85
12.15
10.48
12.13
11.79
11.09
11.77
8.56
8.31
8.31
9.53
12.02
10.63
10.26
13.85
11.52
11.27
10.56
11.29
14.38
10.32
6.70
6.62
6.26
6.73
12.36
11.81
11.51
12.38
12.28
12.43
11.65
11.77
14.21
9.63
12.28
11.71
10.15
9.85
12.15
10.48
12.13
11.77
11.08
11.77
8.55
8.31
8.31
9.53
12.02
10.61
10.25
13.84
11.51
11.26
10.55
11.28
14.31
10.31
6.70
6.62
6.26
6.73
12.34
11.79
11.49
12.36
12.26
12.42
11.64
11.74
14.18
9.62
12.27
11.69
10.13
9.83
12.14
10.45
12.12
11.74
11.06
11.75
8.54
8.29
8.28
9.51
12.01
10.54
10.21
13.74
11.42
11.18
10.51
11.23
14.27
10.27
6.69
6.61
6.26
6.72
12.33
12.10
11.46
12.35
12.26
12.48
11.62
11.76
14.27
9.71
12.21
11.70
10.14
9.82
12.15
10.50
12.11
11.79
11.08
11.77
8.53
8.30
8.22
9.52
11.99
10.58
10.21
13.79
11.46
11.19
10.59
11.23
14.53
10.28
6.68
6.61
6.26
6.72
12.33
11.82
11.46
12.35
12.25
12.48
11.61
11.75
14.26
9.61
12.20
11.70
10.13
9.82
12.14
10.50
12.11
11.76
11.07
11.77
8.52
8.30
8.22
9.52
11.98
10.53
10.19
13.75
11.43
11.16
10.56
11.21
14.36
10.26
6.68
6.60
6.25
6.72
12.28
11.80
11.42
12.30
12.20
12.45
11.59
11.70
14.21
9.60
12.18
11.67
10.10
9.78
12.11
10.44
12.08
11.71
11.03
11.72
8.49
8.27
8.15
9.48
11.96
10.41
10.11
13.57
11.28
11.03
10.47
11.11
14.27
10.16
-------
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Kansas
McLean Co
Peoria Co
Randolph Co
Rock Island Co
Sangamon Co
St. Clair Co
Will Co
Winnebago Co
Allen Co
Clark Co
Delaware Co
Dubois Co
Elkhart Co
Floyd Co
Henry Co
Howard Co
Knox Co
La Porte Co
Lake Co
Madison Co
Marion Co
Porter Co
Spencer Co
St. Joseph Co
Vanderburgh Co
Vigo Co
Black Hawk Co
Clinton Co
Emmet Co
Johnson Co
Linn Co
Muscatine Co
Polk Co
Pottawattamie Co
Scott Co
Van Buren Co
Woodbury Co
Johnson Co
13.41
13.83
12.41
12.04
13.14
16.19
14.50
12.87
14.29
16.33
14.34
15.84
14.99
14.90
13.26
14.55
13.75
13.25
15.01
14.54
16.54
13.75
14.02
14.08
15.29
14.51
11.16
12.06
8.82
11.43
11.00
12.80
10.52
10.43
12.33
10.33
10.07
11.54
10.80
11.35
9.78
9.80
10.65
13.36
11.80
10.56
11.41
12.96
11.08
12.46
12.27
11.38
10.08
11.49
10.60
10.88
12.88
11.21
13.02
11.48
10.67
11.43
12.06
11.51
9.25
9.75
7.31
9.44
9.15
10.56
8.60
8.72
10.00
8.39
8.46
9.59
10.79
11.33
9.76
9.77
10.63
13.29
11.79
10.55
11.40
12.92
11.06
12.44
12.26
11.31
10.07
11.48
10.58
10.86
12.86
11.20
13.00
11.46
10.64
11.42
11.99
11.49
9.25
9.73
7.30
9.43
9.14
10.54
8.60
8.71
9.97
8.38
8.46
9.59
10.74
11.29
9.71
9.74
10.60
13.25
11.70
10.51
11.35
12.91
11.03
12.41
12.21
11.29
10.04
11.44
10.54
10.80
12.75
11.16
12.97
11.39
10.62
11.37
11.96
11.43
9.21
9.67
7.27
9.39
9.08
10.49
8.56
8.66
9.93
8.33
8.41
9.53
10.73
11.27
9.78
9.72
10.55
13.49
11.82
10.44
11.35
13.13
11.02
12.45
12.21
11.52
10.04
11.43
10.58
10.86
12.87
11.15
12.94
11.51
10.69
11.38
12.09
11.43
9.14
9.69
7.21
9.37
9.07
10.50
8.47
8.64
9.92
8.32
8.38
9.52
10.70
11.23
9.73
9.67
10.52
13.34
11.79
10.42
11.32
13.05
10.99
12.41
12.18
11.38
10.01
11.40
10.54
10.82
12.83
11.12
12.91
11.47
10.63
11.35
11.96
11.40
9.12
9.65
7.20
9.35
9.05
10.45
8.46
8.63
9.87
8.30
8.38
9.51
10.61
11.15
9.65
9.58
10.44
13.25
11.63
10.33
11.23
13.02
10.91
12.37
12.08
11.34
9.95
11.33
10.46
10.70
12.64
11.05
12.83
11.34
10.60
11.26
11.90
11.30
9.04
9.53
7.13
9.26
8.93
10.35
8.37
8.53
9.78
8.21
8.28
9.41
32
-------
Kansas
Kansas
Kansas
Kansas
Kansas
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Maine
Maine
Linn Co
Sedgwick Co
Shawnee Co
Sumner Co
Wyandotte Co
Bell Co
Boyd Co
Bullitt Co
Campbell Co
Carter Co
Christian Co
Daviess Co
Fayette Co
Franklin Co
Hardin Co
Jefferson Co
Kenton Co
Laurel Co
Madison Co
McCracken Co
Perry Co
Pike Co
Warren Co
Caddo Parish
Calcasieu Parish
Concordia Parish
East Baton Rouge Parish
Iberville Parish
Jefferson Parish
Lafayette Parish
Orleans Parish
Ouachita Parish
St. Bernard Parish
Tangipahoa Parish
Terrebonne Parish
West Baton Rouge Parish
Androscoggin Co
Aroostook Co
10.66
11.06
10.86
10.19
13.55
14.64
14.88
14.88
14.00
12.18
13.47
14.70
15.60
13.67
13.97
16.58
14.88
12.20
13.53
13.39
13.14
13.67
13.81
12.63
11.35
11.10
13.11
12.55
12.17
11.02
12.23
11.46
10.69
11.17
10.40
12.81
10.73
11.29
8.92
9.58
9.17
8.79
11.42
10.97
11.41
11.43
10.24
8.84
10.47
11.52
11.94
10.03
10.50
13.65
11.03
8.89
9.86
10.61
9.62
10.02
10.55
10.77
9.83
9.48
11.99
11.41
10.32
9.38
10.13
9.80
8.74
9.21
8.69
11.72
9.40
10.60
8.92
9.58
9.17
8.79
11.41
10.97
11.34
11.41
10.19
8.83
10.46
11.49
11.93
10.01
10.48
13.62
10.99
8.88
9.85
10.59
9.62
10.01
10.54
10.76
9.79
9.41
11.72
11.20
10.08
9.37
10.02
9.79
8.66
9.19
8.66
11.46
9.40
10.59
8.86
9.55
9.11
8.76
11.33
10.94
11.31
11.39
10.15
8.80
10.44
11.48
11.89
9.99
10.46
13.61
10.95
8.85
9.81
10.57
9.59
9.98
10.53
10.73
9.78
9.40
11.71
11.19
10.07
9.36
10.01
9.76
8.65
9.18
8.66
11.45
9.40
10.59
8.90
9.53
9.07
8.79
11.51
10.97
11.65
11.52
10.31
8.89
10.49
11.55
11.72
10.04
10.51
13.92
11.16
8.88
9.93
10.63
9.60
10.02
10.55
10.83
9.95
9.65
12.85
12.06
10.87
9.49
10.44
9.84
8.94
9.35
8.85
12.58
9.38
10.59
8.89
9.52
9.07
8.78
11.48
10.96
11.50
11.48
10.22
8.85
10.46
11.49
11.70
10.01
10.49
13.87
11.06
8.87
9.91
10.57
9.59
10.01
10.54
10.81
9.87
9.51
12.28
11.63
10.37
9.46
10.22
9.81
8.76
9.29
8.78
12.02
9.38
10.59
8.78
9.47
8.95
8.72
11.32
10.92
11.46
11.43
10.15
8.81
10.43
11.46
11.64
9.97
10.45
13.84
11.01
8.81
9.84
10.55
9.54
9.95
10.51
10.75
9.86
9.50
12.26
11.62
10.35
9.46
10.21
9.77
8.74
9.28
8.78
12.01
9.38
10.59
33
-------
Maine
Maine
Maine
Maine
Maine
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Minnesota
Minnesota
Minnesota
Minnesota
Minnesota
Minnesota
Cumberland Co
Hancock Co
Kennebec Co
Oxford Co
Penobscot Co
Anne Arundel Co
Baltimore city
Baltimore Co
Harford Co
Montgomery Co
Washington Co
Berkshire Co
Hampden Co
Plymouth Co
Suffolk Co
Allegan Co
Bay Co
Berrien Co
Chippewa Co
Genesee Co
Ing ham Co
Kalamazoo Co
Kent Co
Macomb Co
Monroe Co
Muskegon Co
Oakland Co
Ottawa Co
Saginaw Co
St. Clair Co
Washtenaw Co
Wayne Co
Dakota Co
Hennepin Co
Mille Lacs Co
Olmsted Co
Ramsey Co
Scott Co
11.59
6.25
10.49
10.13
10.06
15.36
16.63
15.01
13.01
12.82
14.25
11.72
13.30
10.86
13.68
12.29
10.94
12.35
8.09
12.37
13.13
14.38
13.55
13.13
14.99
11.99
14.64
13.14
10.70
13.77
14.39
19.32
9.43
10.29
7.12
10.72
11.91
9.98
10.27
5.37
9.12
8.99
8.71
11.87
13.17
11.15
9.67
9.39
10.38
10.46
11.59
9.02
11.79
10.14
9.34
10.07
7.45
10.29
10.77
11.78
10.95
10.68
11.74
10.06
11.73
10.73
9.06
11.65
11.31
16.60
8.05
8.85
6.18
9.14
10.19
8.48
10.21
5.37
9.12
8.99
8.71
11.86
13.13
11.14
9.67
9.38
10.37
10.45
11.59
9.02
11.77
10.13
9.33
10.06
7.44
10.29
10.76
11.77
10.94
10.67
11.70
10.06
11.72
10.72
9.05
11.64
11.30
16.59
8.05
8.84
6.18
9.13
10.15
8.47
10.20
5.37
9.12
8.99
8.71
11.84
13.09
11.11
9.64
9.37
10.34
10.44
11.58
9.01
11.76
10.10
9.32
10.02
7.44
10.26
10.73
11.72
10.90
10.65
11.65
10.03
11.69
10.69
9.04
11.62
11.27
16.55
8.02
8.80
6.15
9.10
10.11
8.44
10.43
5.39
9.10
8.98
8.73
11.96
13.38
11.19
9.71
9.39
10.36
10.46
11.60
9.12
11.83
10.15
9.34
10.05
7.49
10.23
10.75
11.72
10.84
10.67
11.78
10.03
11.70
10.67
9.07
11.68
11.30
16.59
7.98
8.77
6.13
9.03
10.20
8.40
10.30
5.38
9.10
8.97
8.72
11.94
13.30
11.17
9.69
9.38
10.35
10.45
11.59
9.11
11.79
10.12
9.32
10.03
7.49
10.22
10.73
11.70
10.82
10.65
11.71
10.01
11.68
10.65
9.05
11.66
11.27
16.56
7.97
8.74
6.12
9.01
10.13
8.38
10.30
5.38
9.10
8.97
8.72
11.91
13.22
11.13
9.65
9.35
10.29
10.43
11.58
9.10
11.78
10.06
9.30
9.95
7.48
10.18
10.67
11.60
10.75
10.60
11.60
9.95
11.63
10.58
9.03
11.62
11.21
16.49
7.90
8.67
6.06
8.93
10.03
8.31
34
-------
Minnesota
Minnesota
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Montana
Montana
Montana
Montana
Montana
Montana
Montana
Montana
Montana
Montana
St. Louis Co
Stearns Co
Adams Co
Bolivar Co
DeSoto Co
Forrest Co
Hancock Co
Harrison Co
Hinds Co
Jackson Co
Jones Co
Lauderdale Co
Lee Co
Lowndes Co
Pearl River Co
Rankin Co
Scott Co
Warren Co
Cass Co
Cedar Co
Clay Co
Greene Co
Jefferson Co
Monroe Co
St. Charles Co
St. Louis city
St. Louis Co
Ste. Genevieve Co
Cascade Co
Flathead Co
Gallatin Co
Lake Co
Lincoln Co
Missoula Co
Rosebud Co
Sanders Co
Silver Bow Co
Yellowstone Co
8.14
9.21
11.20
12.56
12.60
13.37
10.34
11.57
13.38
11.84
14.48
13.16
12.48
13.36
11.70
13.10
11.82
12.26
11.22
11.45
11.73
12.11
14.43
11.03
14.08
15.16
14.02
13.66
5.70
10.01
8.40
9.41
15.85
10.20
6.78
6.48
8.30
7.43
7.30
7.93
9.34
10.74
10.23
11.04
8.33
9.59
11.19
9.75
11.81
10.57
9.98
10.75
9.59
10.94
9.56
10.61
9.33
9.38
9.74
10.08
11.90
8.94
11.43
12.45
11.46
10.94
5.26
9.36
7.96
8.69
14.72
9.39
6.55
6.17
7.61
6.86
7.27
7.92
9.29
10.72
10.22
11.03
8.32
9.53
11.18
9.66
11.80
10.57
9.97
10.74
9.57
10.93
9.55
10.45
9.33
9.37
9.74
10.08
11.88
8.93
11.40
12.38
11.44
10.90
5.26
9.36
7.96
8.69
14.71
9.39
6.55
6.17
7.61
6.86
7.26
7.88
9.28
10.71
10.18
11.00
8.30
9.52
11.14
9.65
11.77
10.54
9.95
10.73
9.55
10.89
9.52
10.44
9.26
9.33
9.67
10.04
11.85
8.88
11.36
12.34
11.41
10.86
5.25
9.32
7.95
8.68
14.55
9.39
6.54
6.16
7.61
6.85
7.36
7.86
9.49
10.79
10.34
11.07
8.42
9.75
11.22
9.97
11.87
10.60
9.99
10.75
9.66
10.97
9.61
10.97
9.31
9.35
9.72
10.04
11.92
8.89
11.46
12.57
11.46
10.98
5.25
9.34
7.94
8.66
14.66
9.38
6.54
6.15
7.59
6.86
7.30
7.85
9.38
10.75
10.32
11.04
8.39
9.62
11.20
9.76
11.84
10.59
9.97
10.74
9.62
10.95
9.59
10.62
9.30
9.33
9.70
10.03
11.88
8.87
11.39
12.42
11.42
10.88
5.25
9.34
7.93
8.66
14.65
9.37
6.54
6.15
7.59
6.86
7.28
7.77
9.37
10.73
10.25
10.99
8.36
9.61
11.14
9.75
11.79
10.54
9.94
10.71
9.58
10.89
9.53
10.60
9.17
9.25
9.57
9.96
11.81
8.78
11.31
12.34
11.35
10.80
5.23
9.25
7.93
8.64
14.34
9.35
6.51
6.14
7.58
6.84
35
-------
Nebraska
Nebraska
Nebraska
Nebraska
Nebraska
Nebraska
Nebraska
Nevada
Nevada
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New York
New York
Cass Co
Douglas Co
Lancaster Co
Lincoln Co
Sarpy Co
Scotts Bluff Co
Washington Co
Clark Co
Washoe Co
Belknap Co
Cheshire Co
Coos Co
Hillsborough Co
Rockingham Co
Sullivan Co
Atlantic Co
Bergen Co
Camden Co
Essex Co
Gloucester Co
Hudson Co
Mercer Co
Middlesex Co
Morris Co
Ocean Co
Passaic Co
Union Co
Warren Co
Bernalillo Co
Chaves Co
Dona Ana Co
Grant Co
Lea Co
San Juan Co
Sandoval Co
Santa Fe Co
Bronx Co
Chautauqua Co
10.26
10.55
9.58
7.13
10.07
5.96
9.71
9.51
8.86
7.15
11.68
9.68
10.33
9.49
9.86
11.41
13.65
14.31
13.68
13.68
14.93
13.91
12.46
12.38
11.16
13.09
15.66
13.36
6.55
6.70
11.29
6.13
6.75
6.49
4.98
4.93
15.78
10.71
8.61
8.82
8.06
6.30
8.44
5.41
8.15
8.74
8.32
5.96
10.07
8.78
8.77
8.05
8.44
8.79
10.94
11.12
10.75
10.45
12.48
10.74
9.52
9.52
8.57
10.26
12.40
10.03
6.03
6.17
10.29
5.84
6.13
6.14
4.59
4.59
13.01
8.17
8.61
8.82
8.06
6.30
8.43
5.41
8.15
8.74
8.32
5.96
10.07
8.78
8.77
8.03
8.44
8.78
10.92
11.04
10.72
10.39
12.33
10.72
9.51
9.52
8.57
10.25
12.32
10.03
6.03
6.17
10.29
5.84
6.13
6.14
4.59
4.59
12.98
8.16
8.55
8.78
8.01
6.17
8.38
5.33
8.10
8.73
8.30
5.95
10.07
8.78
8.76
8.02
8.44
8.77
10.91
11.03
10.70
10.38
12.31
10.71
9.50
9.51
8.56
10.23
12.29
10.01
6.02
6.16
10.23
5.84
6.12
6.14
4.58
4.58
12.97
8.14
8.58
8.72
8.01
6.26
8.43
5.38
8.09
8.68
8.26
5.96
10.08
8.77
8.77
8.13
8.45
8.86
11.01
11.33
10.84
10.72
12.88
10.87
9.58
9.59
8.62
10.30
12.68
10.06
6.02
6.17
10.14
5.84
6.12
6.14
4.58
4.60
13.05
8.16
8.58
8.72
8.01
6.26
8.42
5.38
8.09
8.68
8.26
5.96
10.08
8.76
8.76
8.08
8.45
8.84
10.97
11.16
10.77
10.58
12.55
10.83
9.56
9.57
8.61
10.27
12.49
10.04
6.02
6.17
10.14
5.84
6.12
6.14
4.58
4.60
12.99
8.14
8.47
8.62
7.92
6.06
8.32
5.25
7.99
8.66
8.22
5.95
10.07
8.76
8.76
8.08
8.44
8.83
10.94
11.14
10.74
10.56
12.52
10.81
9.55
9.55
8.60
10.25
12.46
10.02
6.01
6.16
10.06
5.83
6.12
6.13
4.57
4.60
12.97
8.10
36
-------
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
Erie Co
Essex Co
Kings Co
Nassau Co
New York Co
Niagara Co
Onondaga Co
Orange Co
Queens Co
Richmond Co
St. Lawrence Co
Steuben Co
Suffolk Co
Westchester Co
Alamance Co
Buncombe Co
Cabarrus Co
Caswell Co
Catawba Co
Chatham Co
Cumberland Co
Davidson Co
Duplin Co
Durham Co
Forsyth Co
Gaston Co
Guilford Co
Haywood Co
Jackson Co
Lenoir Co
McDowell Co
Mecklenburg Co
Mitchell Co
Montgomery Co
Onslow Co
Orange Co
Pitt Co
Robeson Co
13.90
6.39
14.65
12.21
17.16
12.03
10.56
11.50
13.23
12.13
8.49
9.83
12.11
12.33
13.93
13.19
14.68
13.43
15.60
12.34
14.17
15.94
12.08
14.09
14.79
14.23
14.27
13.48
12.27
11.57
14.41
15.19
13.56
12.40
11.27
13.24
12.40
12.69
11.07
5.48
12.06
9.86
14.35
9.85
10.13
9.95
10.76
10.80
7.78
7.42
10.05
10.06
10.15
9.95
10.75
9.61
11.52
9.00
10.81
11.96
9.35
10.44
10.96
10.55
10.25
10.58
9.32
8.84
10.72
12.48
10.22
9.08
8.66
9.82
9.85
10.06
11.05
5.47
12.02
9.85
14.34
9.84
10.13
9.94
10.75
10.73
7.77
7.42
10.04
10.05
10.14
9.95
10.74
9.61
11.52
9.00
10.80
11.96
9.34
10.44
10.96
10.55
10.25
10.58
9.32
8.83
10.72
12.48
10.22
9.08
8.66
9.82
9.85
10.06
11.02
5.47
12.01
9.84
14.33
9.83
10.10
9.93
10.75
10.72
7.77
7.42
10.03
10.04
10.13
9.93
10.72
9.60
11.50
8.99
10.79
11.93
9.34
10.43
10.95
10.53
10.24
10.57
9.32
8.83
10.69
12.48
10.19
9.07
8.65
9.81
9.84
10.05
10.98
5.49
12.20
10.00
14.37
9.93
10.11
10.02
10.96
10.97
7.77
7.43
10.65
10.32
10.12
9.90
10.76
9.62
11.47
9.04
10.78
12.01
9.36
10.38
10.92
10.55
10.22
10.57
9.33
8.86
10.71
12.89
10.23
9.09
8.66
9.81
9.88
10.05
10.94
5.49
12.13
9.97
14.33
9.91
10.10
10.01
10.94
10.83
7.76
7.42
10.63
10.29
10.12
9.90
10.75
9.61
11.47
9.03
10.77
12.01
9.35
10.38
10.92
10.55
10.21
10.56
9.33
8.85
10.71
12.89
10.22
9.09
8.65
9.81
9.88
10.05
10.88
5.49
12.11
9.95
14.31
9.89
10.06
9.99
10.93
10.81
7.75
7.41
10.62
10.27
10.10
9.86
10.72
9.59
11.43
9.02
10.74
11.97
9.34
10.36
10.90
10.52
10.19
10.55
9.32
8.84
10.65
12.87
10.17
9.06
8.64
9.80
9.86
10.03
37
-------
North Carolina
North Carolina
North Carolina
North Carolina
North Dakota
North Dakota
North Dakota
North Dakota
North Dakota
North Dakota
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Swain Co
Wake Co
Watauga Co
Wayne Co
Billings Co
Burke Co
Burleigh Co
Cass Co
McKenzie Co
Mercer Co
Athens Co
Butler Co
Clark Co
Cuyahoga Co
Franklin Co
Hamilton Co
Jefferson Co
Lake Co
Lawrence Co
Lorain Co
Lucas Co
Mahoning Co
Montgomery Co
Portage Co
Preble Co
Scioto Co
Stark Co
Summit Co
Trumbull Co
Caddo Co
Canadian Co
Carter Co
Cherokee Co
Garfield Co
Kay Co
Lincoln Co
Mayes Co
Muskogee Co
12.67
13.96
11.55
13.76
4.57
5.74
6.63
7.78
5.26
6.20
12.31
16.12
14.69
18.36
16.52
17.76
17.48
13.25
15.70
13.60
14.70
15.11
15.73
14.19
13.34
17.11
17.26
16.42
14.96
8.79
8.96
10.10
11.56
9.85
10.64
9.96
11.87
12.05
9.52
10.85
8.30
10.83
4.27
4.36
5.89
6.65
4.82
4.98
8.70
12.68
11.20
14.52
12.50
13.35
13.38
10.49
12.55
10.47
11.51
11.18
12.09
10.72
10.07
13.07
13.16
12.61
11.40
7.30
7.45
8.27
9.66
8.58
9.43
8.34
10.13
10.26
9.52
10.85
8.30
10.83
4.27
4.36
5.89
6.65
4.82
4.98
8.68
12.66
11.18
14.44
12.49
13.32
13.33
10.45
12.48
10.40
11.43
11.16
12.08
10.71
10.06
13.04
13.14
12.60
11.39
7.30
7.45
8.27
9.65
8.58
9.43
8.34
10.12
10.25
9.51
10.84
8.29
10.82
4.23
4.36
5.86
6.61
4.81
4.97
8.67
12.62
11.16
14.39
12.44
13.27
13.31
10.42
12.42
10.36
11.36
11.12
12.05
10.67
10.03
12.97
13.10
12.57
11.36
7.28
7.43
8.25
9.63
8.55
9.40
8.32
10.08
10.21
9.52
10.97
8.28
10.83
4.26
4.34
5.85
6.56
4.81
4.96
8.74
12.68
11.21
14.60
12.41
13.37
13.42
10.54
12.67
10.59
11.51
11.17
12.01
10.74
10.11
13.13
13.11
12.61
11.40
7.31
7.48
8.29
9.66
8.56
9.44
8.37
10.12
10.25
9.51
10.96
8.28
10.83
4.26
4.34
5.85
6.56
4.81
4.96
8.70
12.64
11.18
14.42
12.38
13.30
13.32
10.46
12.52
10.44
11.34
11.13
11.99
10.71
10.08
13.05
13.08
12.59
11.37
7.31
7.48
8.28
9.65
8.56
9.44
8.36
10.11
10.24
9.50
10.95
8.27
10.81
4.20
4.33
5.80
6.48
4.79
4.93
8.67
12.57
11.12
14.34
12.29
13.21
13.28
10.40
12.43
10.37
11.22
11.06
11.94
10.64
10.03
12.95
13.00
12.54
11.31
7.28
7.44
8.24
9.61
8.51
9.38
8.33
10.04
10.17
38
-------
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oregon
Oregon
Oregon
Oregon
Oregon
Oregon
Oregon
Oregon
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Rhode Island
Oklahoma Co
Ottawa Co
Pittsburg Co
Seminole Co
Tulsa Co
Columbia Co
Jackson Co
Klamath Co
Lane Co
Linn Co
Multnomah Co
Wasco Co
Washington Co
Adams Co
Allegheny Co
Beaver Co
Berks Co
Bucks Co
Cambria Co
Centre Co
Chester Co
Cumberland Co
Dauphin Co
Delaware Co
Erie Co
Lackawanna Co
Lancaster Co
Lehigh Co
Luzerne Co
Mercer Co
Montgomery Co
Northampton Co
Perry Co
Philadelphia Co
Washington Co
Westmoreland Co
York Co
Kent Co
10.44
11.73
11.37
9.64
11.73
6.29
11.39
10.69
13.28
8.23
8.67
7.53
7.77
13.31
20.99
15.79
16.41
14.10
15.62
12.95
14.80
14.93
15.57
15.31
13.14
12.32
16.95
14.21
12.70
14.00
13.74
14.33
12.83
15.97
15.37
15.38
16.92
8.62
8.49
9.66
9.56
8.04
9.87
5.87
10.68
10.09
12.51
7.90
8.31
7.03
7.39
9.37
16.21
11.97
12.25
11.04
11.47
9.38
10.74
10.88
11.17
11.91
10.18
9.17
12.01
10.68
9.45
10.48
10.36
10.86
9.49
12.73
11.14
10.77
12.53
6.98
8.49
9.66
9.55
8.04
9.86
5.84
10.68
10.09
12.51
7.90
8.24
7.01
7.37
9.36
16.08
11.95
12.24
11.01
11.46
9.37
10.72
10.87
11.16
11.80
10.16
9.16
12.00
10.67
9.45
10.47
10.35
10.85
9.48
12.63
11.11
10.76
12.52
6.98
8.47
9.63
9.51
8.02
9.84
5.83
10.67
10.07
12.44
7.89
8.23
6.98
7.37
9.34
16.03
11.90
12.21
11.00
11.42
9.35
10.70
10.84
11.12
11.78
10.13
9.15
11.96
10.65
9.44
10.44
10.33
10.83
9.42
12.61
11.07
10.72
12.49
6.97
8.42
9.65
9.57
8.06
9.85
5.99
10.67
10.07
12.48
7.90
8.51
7.01
7.44
9.36
16.34
12.00
12.26
11.35
11.47
9.37
10.79
10.83
11.12
12.26
10.18
9.14
11.99
10.66
9.43
10.48
10.55
10.84
9.51
13.00
11.31
10.77
12.51
7.03
8.41
9.64
9.56
8.05
9.84
5.94
10.66
10.06
12.47
7.90
8.36
6.98
7.39
9.35
16.06
11.95
12.23
11.27
11.45
9.36
10.75
10.82
11.10
12.03
10.14
9.13
11.96
10.64
9.42
10.45
10.52
10.82
9.49
12.76
11.24
10.74
12.48
7.03
8.37
9.58
9.49
8.03
9.80
5.91
10.66
10.02
12.29
7.89
8.34
6.90
7.39
9.31
15.98
11.88
12.17
11.25
11.38
9.32
10.70
10.76
11.01
11.99
10.08
9.10
11.89
10.60
9.39
10.40
10.49
10.78
9.40
12.74
11.17
10.68
12.42
7.02
39
-------
Rhode Island
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
South Dakota
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Providence Co
Beaufort Co
Charleston Co
Chesterfield Co
Edgefield Co
Florence Co
Georgetown Co
Greenville Co
Greenwood Co
Horry Co
Lexington Co
Oconee Co
Richland Co
Spartanburg Co
Brookings Co
Brookings Co
Brown Co
Brown Co
Jackson Co
Jackson Co
Meade Co
Meade Co
Minnehaha Co
Minnehaha Co
Pennington Co
Pennington Co
Blount Co
Davidson Co
Dyer Co
Hamilton Co
Knox Co
Lawrence Co
Maury Co
McMinn Co
Montgomery Co
Putnam Co
Roane Co
Shelby Co
12.60
10.91
11.80
12.37
12.71
12.66
12.75
15.73
13.36
11.22
13.87
10.76
13.86
13.82
9.44
9.44
8.22
8.22
5.44
5.44
6.28
6.28
9.84
9.84
7.55
7.55
14.36
14.44
12.05
16.34
16.67
11.94
12.90
14.85
13.21
13.43
14.31
14.12
10.57
8.52
9.23
9.34
9.57
10.20
10.28
11.94
9.99
8.79
10.62
7.72
10.65
10.30
8.05
8.04
7.17
7.14
5.06
5.06
5.87
5.87
8.12
8.12
7.05
7.05
10.86
11.25
9.77
12.58
12.58
9.12
10.78
10.89
10.40
10.00
10.44
11.68
10.56
8.51
9.22
9.34
9.57
10.20
10.25
11.94
9.99
8.78
10.62
7.71
10.65
10.30
8.05
8.04
7.17
7.14
5.06
5.06
5.87
5.87
8.12
8.12
7.05
7.05
10.86
11.23
9.75
12.56
12.57
9.11
10.78
10.89
10.39
9.99
10.43
11.60
10.56
8.51
9.21
9.33
9.55
10.19
10.24
11.92
9.96
8.78
10.60
7.71
10.63
10.28
8.03
8.02
7.15
7.12
5.04
5.05
5.86
5.87
8.09
8.10
7.04
7.05
10.84
11.21
9.73
12.53
12.53
9.10
10.77
10.86
10.38
9.98
10.38
11.56
10.61
8.54
9.24
9.34
9.57
10.18
10.32
11.89
9.98
8.78
10.57
7.70
10.60
10.29
7.97
7.95
7.10
7.06
5.04
5.05
5.84
5.85
8.02
8.01
7.02
7.03
10.92
11.30
9.80
12.58
12.51
9.14
10.80
10.88
10.43
9.98
10.47
11.84
10.60
8.52
9.22
9.33
9.57
10.17
10.25
11.89
9.97
8.77
10.56
7.70
10.59
10.29
7.97
7.95
7.10
7.06
5.04
5.05
5.84
5.85
8.01
8.01
7.02
7.02
10.90
11.26
9.77
12.55
12.49
9.13
10.79
10.87
10.40
9.97
10.44
11.65
10.59
8.51
9.20
9.31
9.53
10.16
10.24
11.87
9.93
8.76
10.54
7.68
10.56
10.26
7.91
7.91
7.06
7.02
5.02
5.03
5.83
5.84
7.95
7.96
7.01
7.01
10.87
11.22
9.73
12.49
12.43
9.12
10.76
10.81
10.37
9.95
10.36
11.59
40
-------
Tennessee
Tennessee
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Utah
Utah
Utah
Utah
Utah
Vermont
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Washington
Sullivan Co
Sumner Co
Bowie Co
Brewster Co
Cameron Co
Dallas Co
Ector Co
Galveston Co
Gregg Co
Harris Co
Harrison Co
Hidalgo Co
Jefferson Co
Montgomery Co
Nueces Co
Orange Co
Potter Co
Tarrant Co
Box Elder Co
Cache Co
Salt Lake Co
Utah Co
Weber Co
Chittenden Co
Arlington Co
Bristol city
Charles City Co
Chesterfield Co
Fairfax Co
Hampton city
Henrico Co
Loudoun Co
Norfolk city
Page Co
Roanoke city
Salem city
Virginia Beach city
Clark Co
14.59
13.58
13.67
4.98
9.88
13.67
7.67
9.79
12.37
14.22
11.46
10.81
11.20
11.23
10.02
11.43
6.17
12.73
9.14
12.82
12.89
10.89
12.81
9.38
14.61
14.51
12.80
13.73
14.15
12.51
13.80
13.63
12.97
12.96
14.36
14.78
12.58
9.74
12.12
10.45
11.60
4.52
8.79
11.35
6.76
7.96
10.36
12.88
9.52
9.67
9.91
9.70
8.54
9.66
5.27
10.63
8.65
11.89
11.81
9.80
11.78
7.96
10.72
10.99
9.33
9.73
10.34
9.82
10.04
9.71
10.56
9.24
10.51
10.93
9.98
8.77
12.12
10.44
11.59
4.52
8.78
11.35
6.76
7.86
10.35
12.51
9.51
9.67
9.73
9.69
8.50
9.64
5.27
10.63
8.64
11.89
11.81
9.80
11.78
7.96
10.72
10.98
9.32
9.72
10.34
9.73
10.03
9.70
10.38
9.24
10.51
10.93
9.96
8.76
12.10
10.42
11.55
4.51
8.78
11.34
6.76
7.86
10.33
12.50
9.49
9.66
9.73
9.68
8.49
9.63
5.25
10.60
8.64
11.88
11.78
9.78
11.76
7.95
10.70
10.96
9.30
9.70
10.32
9.72
9.99
9.68
10.37
9.22
10.41
10.86
9.95
8.75
12.06
10.47
11.59
4.52
8.80
11.43
6.77
8.19
10.40
13.61
9.57
9.65
10.35
9.84
8.73
9.79
5.26
10.65
8.64
11.85
11.63
9.87
11.84
7.91
10.66
10.92
9.35
9.73
10.37
9.96
10.05
9.75
10.84
9.25
10.45
10.90
10.03
8.86
12.05
10.44
11.57
4.52
8.79
11.42
6.77
7.98
10.38
12.81
9.55
9.65
9.97
9.81
8.51
9.75
5.26
10.65
8.64
11.85
11.62
9.86
11.84
7.91
10.65
10.92
9.34
9.72
10.37
9.77
10.04
9.74
10.44
9.25
10.45
10.90
9.98
8.84
12.02
10.41
11.50
4.51
8.78
11.41
6.76
7.98
10.36
12.80
9.52
9.64
9.96
9.80
8.51
9.73
5.23
10.60
8.62
11.83
11.55
9.80
11.78
7.89
10.63
10.88
9.30
9.67
10.34
9.76
9.98
9.70
10.43
9.23
10.30
10.79
9.97
8.82
41
-------
Washington
Washington
Washington
Washington
Washington
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wyoming
Wyoming
Wyoming
Wyoming
Wyoming
King Co
Pierce Co
Snohomish Co
Spokane Co
Yakima Co
Berkeley Co
Brooke Co
Cabell Co
Hancock Co
Harrison Co
Kanawha Co
Marion Co
Marshall Co
Mercer Co
Monongalia Co
Ohio Co
Raleigh Co
Summers Co
Wood Co
Brown Co
Dane Co
Dodge Co
Grant Co
Kenosha Co
Manitowoc Co
Milwaukee Co
Outagamie Co
Vilas Co
Waukesha Co
Campbell Co
Converse Co
Fremont Co
Laramie Co
Sheridan Co
11.37
10.92
11.20
10.19
10.38
16.23
16.69
16.54
17.30
13.99
17.08
15.32
15.61
12.67
14.81
15.08
13.05
10.10
16.07
11.27
12.36
11.12
11.36
11.50
9.81
13.10
10.70
6.40
13.11
6.30
3.66
9.12
4.95
10.49
10.84
10.66
11.14
9.09
9.08
12.35
12.70
13.07
13.65
10.28
13.32
11.25
11.47
9.20
10.44
11.03
9.55
7.19
11.82
9.91
10.50
9.24
9.45
9.54
8.25
11.08
9.17
5.63
11.01
6.09
3.51
8.38
4.57
9.87
10.72
10.65
11.13
9.09
9.08
12.35
12.65
13.04
13.61
10.28
13.30
11.24
11.42
9.20
10.43
10.98
9.55
7.19
11.77
9.90
10.49
9.23
9.44
9.53
8.25
11.07
9.17
5.62
11.00
6.09
3.51
8.38
4.57
9.87
10.71
10.64
11.12
9.06
9.07
12.31
12.63
13.00
13.59
10.27
13.27
11.23
11.40
9.18
10.42
10.97
9.53
7.17
11.75
9.88
10.46
9.19
9.38
9.49
8.22
11.03
9.14
5.61
10.97
6.07
3.49
8.38
4.53
9.79
11.06
10.72
11.21
9.07
9.06
12.33
12.74
13.33
13.68
10.29
13.37
11.25
11.55
9.26
10.44
11.06
9.55
7.20
11.89
9.87
10.45
9.20
9.38
9.57
8.24
11.10
9.16
5.61
10.99
6.09
3.50
8.37
4.57
9.82
10.82
10.70
11.18
9.07
9.05
12.32
12.64
13.25
13.60
10.28
13.31
11.23
11.43
9.26
10.42
10.97
9.54
7.19
11.79
9.86
10.42
9.18
9.35
9.55
8.22
11.08
9.14
5.60
10.97
6.09
3.50
8.37
4.57
9.82
10.80
10.69
11.16
9.02
9.04
12.25
12.61
13.20
13.56
10.27
13.28
11.21
11.41
9.22
10.40
10.94
9.52
7.16
11.76
9.81
10.35
9.11
9.24
9.47
8.16
10.99
9.08
5.57
10.88
6.04
3.47
8.36
4.49
9.69
42
-------
Appendix B: 8-Hour Ozone Design Values for Locomotive/Marine Scenarios (units are ppb)
State Name
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Arizona
Arizona
Arizona
Arizona
Arkansas
Arkansas
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
County Name
Baldwin
Clay
Elmore
Etowah
Jefferson
Lawrence
Madison
Mobile
Montgomery
Morgan
Shelby
Sumter
Tuscaloosa
Maricopa
Pima
Final
Yavapai
Crittenden
Pulaski
Alameda
Amador
Butte
Calaveras
Colusa
Contra Costa
El Dorado
Fresno
Glenn
Imperial
Inyo
Kern
Kings
Lake
Los Angeles
Baseline DV
78.0
79.3
76.7
75.0
83.7
76.3
79.7
79.0
75.0
82.0
88.0
71.7
75.5
85.7
74.0
82.0
78.7
91.0
81.7
82.7
85.7
88.7
91.0
73.3
79.3
105.0
110.0
72.3
86.0
80.7
114.3
95.7
64.3
121.3
2020 Base
66.1
57.7
55.9
55.2
60.8
56.2
58.8
66.6
55.7
61.8
62.6
52.3
53.3
71.8
64.5
66.5
67.8
70.9
63.1
72.6
71.6
73.1
76.8
61.5
72.9
86.2
96.1
61.2
74.8
71.4
100.9
81.5
56.2
109.0
2020 Marine only
65.8
57.6
55.8
55.1
60.7
56.0
58.6
66.3
55.6
61.6
62.6
52.2
53.2
71.7
64.4
66.4
67.5
70.1
62.8
72.3
71.3
72.9
76.4
61.3
72.7
86.0
95.9
61.1
74.5
71.3
100.8
81.3
56.2
108.8
2020 Locomotive
/ Marine
65.7
57.3
55.4
54.8
60.3
55.7
58.3
66.2
55.3
61.3
62.1
52.0
52.9
71.6
64.3
66.2
67.3
69.7
62.5
72.1
71.0
72.5
76.1
61.1
72.6
85.6
95.6
60.9
74.3
71.1
100.6
81.1
56.1
108.7
2030 Base
67.0
56.3
53.9
53.8
58.9
54.9
56.9
67.6
54.0
60.6
60.6
51.2
51.8
69.3
63.0
64.6
66.0
70.3
61.3
70.0
67.9
68.7
73.4
58.4
71.1
80.7
92.4
58.3
72.8
69.5
97.6
77.8
54.5
105.5
2030 Marine only
66.3
56.1
53.7
53.6
58.7
54.6
56.4
66.9
53.9
60.1
60.4
50.9
51.5
69.2
63.0
64.5
65.4
68.4
60.7
69.2
67.1
68.3
72.4
58.1
70.4
80.2
92.0
58.0
72.1
69.1
97.4
77.4
54.3
104.7
2030 Locomotive
/ Marine
65.9
55.3
52.7
52.8
57.5
53.8
55.7
66.5
52.9
59.2
59.1
50.2
50.5
68.6
62.6
63.9
64.9
67.4
59.6
68.8
66.4
67.1
71.6
57.5
70.1
78.9
91.0
57.4
71.5
68.6
96.7
76.8
54.0
104.4
43
-------
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
California
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Colorado
Madera
Marin
Mariposa
Mendocino
Merced
Monterey
Napa
Nevada
Orange
Placer
Riverside
Sacramento
San Benito
San Bernardino
San Diego
San Joaquin
San Luis Obispo
San Mateo
Santa Barbara
Santa Clara
Santa Cruz
Shasta
Solano
Sonoma
Stanislaus
Sutler
Tehama
Tulare
Tuolumne
Ventura
Yolo
Adams
Arapahoe
Boulder
Denver
Douglas
El Paso
Jefferson
91.0
48.0
89.7
56.7
101.7
66.0
64.7
97.7
85.3
98.3
115.0
99.0
81.0
128.7
92.3
81.0
73.3
56.7
82.7
84.0
65.0
72.3
70.3
62.0
95.0
87.3
84.0
105.7
91.0
94.7
81.7
65.3
78.7
75.3
74.0
83.0
72.3
84.7
79.5
42.1
76.3
47.9
84.9
57.2
53.3
80.4
76.7
80.7
103.1
82.1
69.6
124.7
80.5
71.0
63.1
52.5
72.7
70.1
57.1
60.8
59.9
50.7
81.9
72.2
69.7
88.8
77.3
81.5
68.3
57.7
70.4
63.9
65.4
73.8
63.2
74.2
79.3
42.1
75.9
47.8
84.6
57.1
53.1
80.2
79.2
80.5
103.5
81.9
69.4
125.3
80.2
70.7
63.0
52.5
71.1
70.0
57.0
60.7
59.7
50.6
81.6
72.0
69.6
88.6
76.9
80.9
68.1
57.7
70.4
63.9
65.4
73.8
63.2
74.2
79.0
42.1
75.7
47.7
84.4
57.0
53.0
79.7
79.3
80.2
103.5
81.6
69.3
125.1
80.1
70.5
62.8
52.4
70.9
69.9
56.9
60.4
59.6
50.5
81.5
71.8
69.1
88.4
76.7
80.8
67.9
57.6
70.3
63.7
65.3
73.7
63.0
74.0
76.5
40.8
73.2
45.6
80.6
54.9
50.7
75.8
76.3
75.6
101.9
76.8
66.6
123.0
78.0
68.6
60.5
51.4
70.5
66.4
55.0
57.7
57.8
47.6
78.4
68.3
66.0
84.6
74.0
78.7
64.6
57.1
69.5
62.9
64.7
72.7
62.6
73.2
76.1
40.9
72.2
45.4
79.9
54.6
50.3
75.2
81.5
75.0
102.5
76.2
66.2
123.9
77.2
67.7
60.2
51.2
66.3
66.1
54.8
57.5
57.5
47.5
77.7
67.8
65.8
84.1
73.0
77.0
64.2
57.1
69.4
62.9
64.7
72.7
62.6
73.2
75.3
40.8
71.7
45.0
79.2
54.3
50.0
73.8
81.8
73.9
102.4
75.3
65.8
123.4
76.9
67.3
59.8
51.0
65.9
65.7
54.5
56.6
57.2
47.1
77.1
67.0
64.4
83.4
72.4
76.7
63.6
56.7
69.1
62.4
64.3
72.3
62.1
72.8
44
-------
Colorado
Colorado
Colorado
Colorado
Connecticut
Connecticut
Connecticut
Connecticut
Connecticut
Connecticut
Connecticut
D.C.
Delaware
Delaware
Delaware
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Florida
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
La Plata
Larimer
Montezuma
Weld
Fairfield
Hartford
Litchfield
Middlesex
New Haven
New London
Tolland
Washington
Kent
New Castle
Sussex
Bay
Brevard
Duval
Escambia
Hillsborough
Lake
Manatee
Miami-Dade
Orange
Pasco
Pinellas
Polk
Santa Rosa
Sarasota
Seminole
Bibb
Chatham
Cherokee
Clarke
Cobb
Coweta
Dawson
De Kalb
59.0
80.3
68.0
76.7
98.3
88.0
86.0
95.7
98.3
90.0
92.3
92.7
88.3
92.7
90.0
79.3
72.7
74.0
81.0
78.7
76.0
76.3
67.0
76.3
76.7
74.7
76.3
81.3
79.7
77.5
88.0
68.3
78.0
78.0
91.0
88.7
80.0
91.0
52.2
67.8
63.0
64.9
81.7
67.9
66.7
75.6
79.1
70.9
70.6
70.5
71.8
72.4
71.9
62.9
52.8
54.3
66.5
67.1
56.3
62.3
54.4
57.6
58.8
62.1
59.8
65.3
62.2
58.3
65.8
54.4
54.7
55.0
64.9
66.3
57.3
68.3
52.2
67.8
62.9
64.9
81.6
67.6
66.3
75.3
78.8
70.6
70.3
70.4
71.3
72.1
71.7
62.7
52.5
53.9
66.4
67.0
56.2
62.1
54.3
57.5
58.6
61.9
59.5
65.2
61.8
58.2
65.7
54.1
54.6
55.0
64.9
66.3
57.3
68.3
52.1
67.6
62.9
64.7
81.5
67.5
66.2
75.2
78.6
70.5
70.1
70.1
71.2
71.9
71.5
62.6
52.5
53.6
66.2
66.9
56.1
62.1
54.3
57.4
58.5
61.9
59.4
65.0
61.7
58.1
65.4
53.9
54.4
54.8
64.7
66.1
57.1
68.0
51.9
66.8
62.6
64.9
81.3
66.8
66.2
74.8
78.4
70.2
69.2
68.9
71.4
71.7
71.1
61.8
51.7
53.4
66.2
66.2
55.4
61.6
53.6
56.6
57.7
61.4
59.0
65.0
61.6
57.2
64.3
53.6
52.0
52.6
61.8
64.4
55.0
65.9
51.8
66.8
62.5
64.9
81.0
66.1
65.4
74.1
77.7
69.6
68.5
68.6
70.6
71.1
70.7
61.4
51.2
52.5
65.8
65.9
55.2
61.0
53.2
56.4
57.3
60.9
58.3
64.6
60.8
56.9
64.2
52.8
51.9
52.4
61.6
64.2
54.9
65.7
51.6
66.3
62.3
64.3
80.7
65.7
65.1
73.8
77.3
69.3
68.1
68.0
70.2
70.5
70.4
60.9
50.9
51.9
65.4
65.7
55.0
60.8
53.1
56.1
57.0
60.7
58.1
64.1
60.6
56.7
63.3
52.3
51.3
51.8
61.0
63.6
54.3
65.0
45
-------
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Georgia
Idaho
Idaho
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Indiana
Indiana
Douglas
Fayette
Fulton
Glynn
Gwinnett
Henry
Murray
Muscogee
Paulding
Richmond
Rockdale
Sumter
Ada
Canyon
Adams
Champaign
Clark
Cook
Du Page
Effing ham
Hamilton
Jersey
Kane
Lake
Macon
Macoupin
Madison
McHenry
McLean
Peoria
Randolph
Rock Island
Sangamon
St Clair
Will
Winnebago
Allen
Boone
91.0
85.3
94.3
72.3
87.7
91.7
85.0
75.0
88.0
84.3
91.0
75.0
76.0
68.0
75.3
75.0
73.0
85.3
71.7
74.7
79.3
87.7
77.0
84.7
75.0
78.0
85.7
82.0
76.0
78.0
77.7
68.7
75.3
83.0
78.3
75.0
87.0
88.0
65.1
63.4
71.8
55.8
62.8
65.9
60.7
54.9
61.4
65.3
65.6
55.2
69.9
59.6
61.4
59.8
54.4
75.0
63.1
58.3
60.6
69.5
65.3
73.7
59.3
58.6
68.0
69.7
59.4
65.2
60.9
56.3
54.8
67.7
63.9
60.2
68.7
69.4
65.0
63.3
71.8
55.5
62.8
65.8
60.6
54.8
61.3
65.2
65.5
55.0
69.9
59.6
61.0
59.6
54.2
75.1
63.0
58.1
60.0
68.9
65.1
73.6
59.1
58.3
67.5
69.5
59.2
65.0
60.5
56.1
54.6
67.3
63.8
60.0
68.5
69.2
64.8
63.1
71.5
55.3
62.6
65.6
60.3
54.6
61.1
65.0
65.3
54.7
69.8
59.5
60.7
59.3
54.0
75.1
62.8
57.9
59.8
68.7
64.7
73.4
58.9
58.1
67.3
69.1
58.9
64.7
60.2
55.8
54.4
67.0
63.4
59.6
68.1
68.9
62.5
60.8
69.2
54.9
59.6
63.2
58.9
53.4
59.2
63.3
62.9
54.0
68.7
58.0
60.8
58.9
53.8
74.3
62.7
57.4
60.2
68.5
64.7
73.2
58.6
57.7
67.0
69.0
58.4
64.3
60.2
55.1
53.6
66.7
63.1
59.0
67.4
68.2
62.3
60.7
69.1
54.3
59.5
63.1
58.7
53.2
59.0
63.1
62.7
53.8
68.6
58.0
59.8
58.5
53.4
74.6
62.4
57.0
58.9
67.1
64.3
73.0
58.1
57.0
65.8
68.7
57.9
63.7
59.3
54.6
53.2
65.5
62.8
58.6
66.9
67.8
61.6
60.0
68.3
53.6
58.9
62.3
57.9
52.4
58.4
62.6
62.0
52.8
68.4
57.8
58.9
57.6
52.9
74.5
61.9
56.3
58.3
66.5
63.2
72.3
57.4
56.3
65.2
67.5
57.1
63.1
58.6
53.8
52.6
64.9
61.8
57.5
65.8
67.1
46
-------
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Kansas
Kansas
Kansas
Kansas
Kentucky
Kentucky
Kentucky
Carroll
Clark
Delaware
Elkhart
Floyd
Gibson
Greene
Hamilton
Hancock
Hend ricks
Huntington
Jackson
Johnson
La Porte
Lake
Madison
Marion
Morgan
Porter
Posey
Shelby
St Joseph
Vanderburgh
Vigo
Warrick
Clinton
Harrison
Montgomery
Polk
Scott
Story
Linn
Sedgwick
Sumner
Wyandotte
Bell
Boone
Boyd
83.0
90.0
85.5
87.0
84.3
73.0
87.0
93.7
91.3
84.7
83.3
83.3
85.3
90.3
88.3
91.7
90.0
85.0
86.3
84.0
91.3
90.3
82.7
85.0
84.0
76.3
75.7
67.0
57.3
77.7
60.7
74.3
79.0
75.7
79.0
82.3
83.7
88.3
64.2
70.3
66.2
69.2
68.1
52.5
63.9
72.0
69.4
66.8
65.7
64.0
66.3
76.1
78.5
69.5
70.7
67.4
76.0
63.5
71.0
72.5
62.0
68.0
65.5
64.2
63.5
57.0
47.5
63.0
49.6
61.3
65.0
63.6
64.2
57.4
64.8
73.1
63.9
69.8
66.0
69.0
67.6
52.2
63.6
71.8
69.2
66.6
65.5
63.6
66.1
76.0
78.6
69.3
70.5
67.2
76.1
62.9
70.8
72.3
61.4
67.8
65.1
63.9
63.4
57.0
47.5
62.7
49.5
61.2
64.9
63.5
64.1
57.3
64.3
72.5
63.6
69.5
65.6
68.6
67.4
52.1
63.3
71.6
69.0
66.4
65.2
63.4
65.9
75.8
78.5
69.1
70.3
67.0
76.0
62.6
70.6
71.8
61.2
67.5
64.9
63.6
63.1
56.7
47.2
62.4
49.3
60.9
64.7
63.3
63.7
57.0
64.1
72.2
63.1
69.7
64.9
68.1
67.5
51.7
63.0
70.4
67.8
65.3
64.5
63.3
65.2
75.4
77.7
67.9
69.2
66.2
75.3
62.7
69.3
71.5
61.1
67.1
64.9
63.4
62.8
56.5
45.7
61.8
47.8
60.6
63.2
62.5
63.0
55.5
64.4
73.3
62.6
68.4
64.4
67.7
66.3
51.2
62.3
69.9
67.2
64.9
64.1
62.4
64.7
75.2
77.9
67.4
68.7
65.8
75.4
61.4
68.8
71.0
59.9
66.7
64.1
62.9
62.6
56.3
45.5
61.2
47.6
60.4
63.1
62.3
62.8
55.3
63.3
72.2
61.8
67.8
63.5
66.6
65.8
50.7
61.6
69.3
66.6
64.2
63.1
61.7
64.1
74.6
77.8
66.7
68.1
65.1
75.2
60.7
68.1
69.8
59.4
65.9
63.6
62.0
61.7
55.4
45.0
60.4
47.0
59.5
62.3
61.5
61.7
54.5
62.7
71.4
47
-------
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Bullitt
Campbell
Carter
Christian
Daviess
Edmonson
Fayette
Graves
Greenup
Hancock
Hardin
Henderson
Jefferson
Jessamine
Kenton
Livingston
McCracken
McLean
Oldham
Perry
Pike
Pulaski
Scott
Simpson
Trigg
Warren
Ascension
Bossier
Caddo
Calcasieu
East Baton Rouge
Iberville
Jefferson
Lafayette
Lafourche
Livingston
Orleans
Ouachita
81.0
90.7
77.0
84.0
75.3
80.3
75.0
79.0
81.3
81.7
78.3
79.3
82.7
76.3
85.0
82.7
79.0
82.0
85.3
75.7
73.3
77.3
68.7
79.7
73.0
82.0
79.3
79.7
77.3
78.7
87.0
84.3
83.0
79.3
78.0
79.7
69.7
77.7
63.3
72.3
59.7
59.1
60.1
60.5
58.6
61.1
67.2
64.9
59.3
61.8
66.4
58.6
67.7
63.2
65.3
60.5
65.0
56.7
56.1
59.9
51.9
57.9
54.6
61.4
70.8
62.2
60.0
68.1
78.1
75.0
72.3
68.1
67.4
70.8
60.2
62.6
62.8
71.8
59.2
58.7
59.6
60.1
58.4
60.7
66.6
64.4
58.8
61.4
66.0
58.4
67.1
62.7
64.9
60.2
64.4
56.5
55.8
59.8
51.6
57.6
53.9
61.1
70.0
62.0
59.7
67.5
77.7
74.1
71.7
67.1
66.6
69.8
59.6
62.2
62.6
71.6
59.0
58.5
59.5
59.9
58.1
60.5
66.3
64.2
58.6
61.2
65.8
58.1
66.9
62.5
64.7
60.0
64.2
56.2
55.6
59.4
51.3
57.4
53.8
60.8
69.9
61.6
59.4
67.3
77.6
74.0
71.5
66.9
66.5
69.7
59.5
62.0
62.5
71.6
60.1
58.7
59.7
59.6
57.1
60.3
67.6
64.6
58.6
61.2
65.7
57.4
67.1
62.8
64.7
59.9
64.5
55.9
55.3
59.0
51.5
56.6
54.4
60.5
70.9
60.9
58.9
68.1
77.9
75.1
72.4
68.6
67.5
70.9
60.3
61.8
61.5
70.5
59.1
57.8
58.7
58.9
56.6
59.3
66.6
63.5
57.6
60.4
64.7
56.9
65.9
61.6
63.8
59.1
63.2
55.5
54.9
58.6
50.7
56.1
52.8
59.8
69.1
60.4
58.3
66.9
77.1
73.2
71.0
66.4
65.9
69.0
59.0
60.9
60.9
69.7
58.3
57.2
58.3
58.2
55.8
58.7
65.8
63.0
57.1
59.9
64.2
56.1
65.1
61.0
63.4
58.6
62.5
54.7
54.1
57.7
49.9
55.4
52.3
59.1
68.8
59.5
57.4
66.4
76.8
72.9
70.6
66.0
65.5
68.6
58.7
60.2
48
-------
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Louisiana
Maine
Maine
Maine
Maine
Maine
Maine
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Maryland
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Massachusetts
Michigan
Michigan
Michigan
Michigan
Pointe Coupee
St Bernard
St Charles
St James
St John The Baptist
St Mary
West Baton Rouge
Cumberland
Hancock
Kennebec
Knox
Sagadahoc
York
Anne Arundel
Baltimore
Carroll
Cecil
Charles
Frederick
Harford
Kent
Montgomery
Prince Georges
Washington
Barnstable
Berkshire
Bristol
Essex
Hampden
Hampshire
Middlesex
Norfolk
Suffolk
Worcester
Allegan
Benzie
Berrien
Cass
73.3
78.0
78.7
74.0
78.7
74.7
84.0
84.3
91.7
78.0
83.7
79.0
88.3
98.3
91.3
88.7
97.7
93.0
87.3
100.3
95.3
86.7
94.0
85.3
92.0
87.0
91.0
90.0
92.0
86.7
85.7
91.0
88.7
85.5
94.0
85.7
88.0
90.7
65.1
65.9
69.3
65.4
69.9
63.9
75.6
65.2
73.1
61.6
65.0
61.2
68.5
74.1
72.4
66.8
73.2
66.7
67.2
78.9
71.7
65.8
71.0
65.4
73.8
70.3
71.9
72.8
70.3
68.1
66.5
76.2
71.6
66.9
77.2
69.7
74.0
71.7
64.6
65.3
68.5
65.2
69.6
62.6
74.9
65.0
72.8
61.4
64.8
61.1
68.3
74.0
72.3
66.6
73.0
66.5
67.0
78.7
71.5
65.7
70.9
65.2
73.4
70.1
71.7
72.7
70.1
67.9
66.3
76.2
71.5
66.6
77.0
69.5
73.9
71.5
64.5
65.1
68.4
65.1
69.5
62.5
74.8
64.9
72.6
61.3
64.6
60.9
68.1
73.7
72.1
66.3
72.7
66.3
66.8
78.5
71.2
65.5
70.7
64.9
73.2
70.0
71.5
72.5
69.9
67.8
66.1
76.1
71.4
66.5
76.5
69.2
73.6
71.0
65.0
65.8
69.5
65.2
69.4
64.5
75.6
64.2
72.2
60.6
64.1
60.4
67.5
72.8
71.6
65.5
72.1
65.2
66.1
78.0
70.6
64.6
69.4
64.1
73.4
69.1
71.5
72.0
69.0
67.0
65.2
75.4
70.9
65.9
76.4
68.9
73.4
70.5
64.1
64.6
68.1
64.6
69.1
61.8
74.0
63.8
71.6
60.2
63.7
60.0
67.0
72.5
71.3
65.1
71.7
64.9
65.6
77.6
70.2
64.3
69.1
63.6
72.6
68.7
70.8
71.7
68.4
66.5
64.8
75.3
70.8
65.3
75.9
68.5
73.1
70.0
63.8
64.2
67.7
64.3
68.8
61.4
73.7
63.3
71.1
59.8
63.2
59.6
66.5
71.9
70.7
64.4
70.9
64.2
64.9
77.0
69.5
63.6
68.4
62.8
72.2
68.1
70.4
71.4
68.0
66.1
64.2
74.9
70.4
64.9
74.5
67.5
72.4
68.7
49
-------
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Michigan
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Missouri
Clinton
Genesee
Huron
Ing ham
Kalamazoo
Kent
Lenawee
Macomb
Mason
Missaukee
Muskegon
Oakland
Ottawa
Schoolcraft
St Clair
Washtenaw
Wayne
Adams
De Soto
Hancock
Harrison
Hinds
Jackson
Lauderdale
Lee
Madison
Warren
Cass
Cedar
Clay
Greene
Jefferson
Monroe
Platte
St Charles
St Louis
St Louis City
Ste Genevieve
82.7
86.3
83.0
82.3
82.7
84.7
85.0
92.3
86.0
78.3
90.0
87.7
86.0
77.0
88.0
87.3
86.0
77.7
83.3
81.0
80.3
72.7
80.0
73.3
78.3
74.3
73.7
77.7
79.7
83.7
74.5
84.7
76.7
80.3
90.0
88.3
87.7
82.7
66.7
68.5
70.8
65.9
65.1
67.4
69.4
76.6
68.9
64.0
73.4
74.2
69.3
65.0
72.5
71.4
72.9
63.1
64.0
66.1
65.1
52.1
68.6
52.3
57.4
55.2
54.9
61.9
64.8
66.7
59.8
68.9
61.9
65.0
73.0
72.6
72.9
66.8
66.5
68.3
70.7
65.8
64.9
67.2
69.2
76.5
68.7
63.8
73.2
74.1
69.1
64.9
72.3
71.3
72.8
61.9
63.6
65.4
64.4
51.8
68.3
52.1
57.1
54.9
53.6
61.8
64.6
66.5
59.6
68.4
61.6
64.9
72.6
72.1
72.4
66.4
66.2
68.0
70.5
65.5
64.5
66.9
69.0
76.3
68.3
63.5
72.7
73.9
68.7
64.6
72.1
71.1
72.6
61.7
63.2
65.1
64.2
51.4
68.1
51.8
56.8
54.5
53.4
61.5
64.2
66.0
59.3
68.2
61.3
64.5
72.4
71.8
72.2
66.1
65.5
67.1
70.3
64.8
63.9
66.2
68.6
75.6
67.8
63.1
72.5
73.3
68.3
64.5
71.5
70.5
71.9
63.2
62.8
65.7
65.0
50.1
68.5
50.9
56.2
53.7
54.9
60.9
63.7
65.0
58.6
67.6
61.2
64.0
71.6
71.3
71.8
66.0
65.2
66.8
70.0
64.4
63.5
65.8
68.2
75.4
67.4
62.7
72.0
73.1
67.8
64.1
71.2
70.2
71.7
60.8
61.8
64.1
63.5
49.5
67.9
50.6
55.6
53.1
52.4
60.7
63.4
64.6
58.2
66.4
60.5
63.7
70.5
70.0
70.5
65.1
64.3
65.9
69.6
63.5
62.4
64.8
67.4
74.8
66.1
61.9
70.7
72.6
66.7
63.3
70.6
69.5
71.2
60.2
60.8
63.5
62.9
48.3
67.5
49.8
54.7
51.9
51.7
59.7
62.3
63.3
57.4
65.8
59.5
62.6
69.9
69.4
69.9
64.4
50
-------
Nebraska
Nebraska
Nevada
Nevada
Nevada
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Hampshire
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Mexico
New Mexico
New Mexico
New Mexico
New Mexico
New York
New York
New York
New York
New York
New York
New York
New York
Douglas
Lancaster
Clark
Douglas
Washoe
Belknap
Cheshire
Hillsborough
Merrimack
Rockingham
Strafford
Atlantic
Bergen
Camden
Cumberland
Essex
Gloucester
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
Ocean
Passaic
Bernalillo
Dona Ana
San Juan
Sandoval
Valencia
Albany
Bronx
Chautauqua
Chemung
Dutchess
Erie
Essex
Herkimer
67.3
55.0
84.7
69.0
73.3
76.5
74.3
85.3
74.7
83.5
78.5
88.0
91.3
99.7
94.0
67.0
98.0
84.0
94.7
97.7
96.0
95.3
95.3
105.7
86.7
76.3
78.3
74.3
74.0
67.5
83.0
82.7
93.0
80.3
92.0
95.7
89.0
74.0
57.3
46.6
74.9
61.1
65.0
61.5
58.4
66.7
59.1
65.9
61.1
69.9
76.2
79.6
73.7
54.1
77.9
67.7
73.6
78.2
75.4
75.6
73.2
82.1
69.2
66.4
70.2
70.4
64.9
58.0
66.2
71.1
75.4
63.1
71.0
77.7
70.6
60.3
57.2
46.5
74.8
61.0
65.0
61.4
58.2
66.5
58.9
65.7
60.9
69.3
76.0
79.1
73.2
54.1
77.6
67.8
73.1
77.7
75.0
75.3
72.9
81.5
69.0
66.3
70.2
70.4
64.8
58.0
66.0
71.1
75.0
63.0
70.7
77.3
70.4
60.1
57.0
46.3
74.6
60.9
64.9
61.2
58.1
66.3
58.8
65.5
60.8
69.2
75.9
78.9
73.0
54.0
77.4
67.7
73.0
77.5
74.9
75.1
72.7
81.3
68.9
66.1
70.0
70.3
64.6
57.7
65.8
70.9
74.7
62.7
70.5
77.0
70.2
59.9
56.6
45.8
74.0
59.4
63.6
60.4
57.6
65.6
58.2
65.2
60.2
69.5
75.5
78.9
73.3
53.5
77.4
66.9
72.5
77.5
74.4
75.0
72.2
81.1
68.3
64.5
66.8
70.0
63.1
56.6
64.9
70.7
75.0
61.9
70.4
77.1
69.6
59.4
56.4
45.6
73.8
59.2
63.5
60.2
57.1
65.1
57.8
64.7
59.8
68.3
75.3
77.9
72.2
53.4
76.7
67.1
71.5
76.2
73.5
74.2
71.3
79.8
67.8
64.4
66.8
70.0
63.0
56.5
64.4
70.6
74.1
61.6
69.5
76.3
69.2
59.1
55.7
45.0
73.3
58.8
63.1
59.8
56.8
64.7
57.3
64.3
59.4
68.0
74.9
77.4
71.7
53.1
76.1
66.7
71.1
75.8
73.1
73.8
70.8
79.3
67.3
63.7
66.2
69.7
62.3
55.7
63.8
70.2
73.2
60.9
69.1
75.5
68.6
58.6
51
-------
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
New York
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
Jefferson
Madison
Monroe
Niagara
Oneida
Onondaga
Orange
Oswego
Putnam
Queens
Rensselaer
Richmond
Saratoga
Schenectady
Suffolk
Ulster
Wayne
Westchester
Alexander
Avery
Buncombe
Caldwell
Caswell
Chatham
Cumberland
Da vie
Duplin
Durham
Edgecombe
Forsyth
Franklin
Granville
Guilford
Haywood
Jackson
Johnston
Lenoir
Lincoln
91.3
79.7
84.0
91.7
79.7
84.0
84.7
68.0
91.3
84.5
86.0
93.0
87.0
77.7
97.0
81.3
84.0
91.3
87.0
77.7
80.0
83.3
87.7
81.3
86.0
91.3
80.0
88.7
87.3
91.3
89.7
92.3
88.7
84.7
86.0
84.3
80.0
90.7
74.9
63.7
68.8
77.2
64.5
68.8
65.6
55.1
73.4
71.6
68.4
75.3
68.8
62.8
82.0
65.2
67.5
76.3
63.2
60.1
61.6
61.8
62.0
59.9
63.1
65.5
60.6
62.8
64.6
64.8
64.7
65.8
61.3
65.8
64.9
61.4
61.2
65.7
74.7
63.6
68.7
77.0
64.3
68.7
65.3
55.0
73.1
71.5
68.2
75.4
68.6
62.6
82.1
65.0
67.3
76.1
63.1
60.0
61.5
61.7
61.9
59.8
63.0
65.4
60.5
62.7
64.5
64.7
64.6
65.7
61.2
65.7
64.8
61.3
61.1
65.6
74.5
63.3
68.5
76.8
64.1
68.5
65.2
54.8
72.9
71.4
68.0
75.2
68.4
62.4
82.0
64.8
67.1
76.0
62.9
59.8
61.3
61.4
61.7
59.6
62.7
65.2
60.3
62.5
64.3
64.5
64.3
65.5
61.0
65.5
64.5
61.1
60.9
65.4
74.3
62.5
67.5
76.8
63.6
67.9
64.5
54.4
72.9
71.1
67.0
74.1
67.4
61.2
81.4
64.2
66.3
75.7
61.5
58.8
59.9
60.2
60.1
58.5
61.1
63.7
59.2
60.6
62.7
62.7
62.2
64.2
58.7
64.5
63.6
59.1
59.8
63.8
73.9
62.3
67.3
76.4
63.2
67.6
63.9
54.1
72.1
70.8
66.5
74.2
66.8
60.8
81.6
63.8
66.0
75.3
61.3
58.6
59.8
59.9
59.9
58.3
60.9
63.5
59.0
60.4
62.5
62.6
62.0
63.9
58.5
64.2
63.3
58.9
59.5
63.6
73.3
61.6
66.7
75.9
62.6
67.0
63.4
53.6
71.7
70.4
65.8
73.8
66.1
60.2
81.3
63.3
65.4
74.9
60.8
57.9
59.3
59.3
59.3
57.7
60.1
62.9
58.3
59.8
61.8
62.1
61.4
63.3
57.9
63.6
62.5
58.3
58.9
63.1
52
-------
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Martin
Mecklenburg
New Hanover
Northampton
Person
Pitt
Randolph
Rockingham
Rowan
Swain
Union
Wake
Yancey
Allen
Ashtabula
Butler
Clark
Clermont
Clinton
Cuyahoga
Delaware
Franklin
Geauga
Greene
Hamilton
Jefferson
Knox
Lake
Lawrence
Licking
Lorain
Lucas
Madison
Mahoning
Medina
Miami
Montgomery
Portage
81.0
97.3
77.3
84.0
89.3
82.0
83.5
88.3
97.3
73.0
87.0
92.5
83.0
88.0
95.7
89.7
88.3
89.3
94.3
88.0
89.0
93.0
99.0
87.7
90.3
84.3
87.0
92.7
81.7
88.0
87.0
90.0
88.7
87.0
87.0
87.0
86.5
91.0
61.3
73.0
58.0
63.2
64.0
60.5
58.9
63.0
70.1
54.6
63.5
65.8
64.1
69.7
78.9
70.1
68.1
70.8
71.4
70.4
68.4
70.8
79.5
68.0
71.3
65.0
66.5
75.3
67.5
67.2
69.8
72.8
67.2
67.1
69.7
66.5
67.5
71.1
61.2
72.9
57.7
63.1
63.9
60.4
58.8
62.9
70.0
54.5
63.4
65.7
64.0
69.4
78.6
69.6
67.9
70.3
71.0
70.3
68.2
70.5
79.2
67.6
70.8
64.7
66.3
75.2
66.9
67.0
69.8
72.8
66.9
66.8
69.5
66.2
67.3
70.7
61.0
72.7
57.5
62.9
63.8
60.2
58.6
62.7
69.8
54.2
63.2
65.5
63.8
69.2
78.3
69.3
67.6
70.1
70.6
70.1
67.9
70.2
78.9
67.3
70.5
64.5
66.0
75.0
66.6
66.7
69.6
72.5
66.7
66.5
69.2
66.0
67.0
70.4
60.0
70.8
56.9
62.0
63.1
58.6
56.7
61.6
67.8
53.4
61.1
62.9
62.5
68.7
78.6
69.2
67.4
70.0
70.4
70.1
67.0
69.0
78.6
67.2
70.3
64.5
65.1
75.0
68.0
65.7
69.3
71.9
66.3
66.0
69.3
65.2
66.4
70.0
59.7
70.6
56.2
61.6
62.8
58.4
56.5
61.5
67.7
53.1
61.0
62.7
62.2
68.2
77.9
68.1
66.7
69.0
69.4
69.8
66.5
68.5
77.9
66.4
69.3
63.8
64.7
74.7
66.9
65.2
69.2
71.8
65.6
65.4
68.7
64.7
65.8
69.2
59.1
70.1
55.7
61.0
62.4
57.7
55.9
60.9
66.9
52.5
60.3
62.1
61.6
67.4
77.1
67.3
66.0
68.2
68.5
69.2
65.6
67.5
77.0
65.6
68.4
63.3
63.8
74.1
66.1
64.3
68.7
71.1
64.9
64.5
68.0
63.9
65.0
68.3
53
-------
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Oklahoma
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Preble
Stark
Summit
Trumbull
Warren
Washington
Wood
Canadian
Cleveland
Comanche
Dewey
Kay
Me Clain
Oklahoma
Ottawa
Pittsburg
Tulsa
Adams
Allegheny
Armstrong
Beaver
Berks
Blair
Bucks
Cambria
Centre
Chester
Clearfield
Dauphin
Delaware
Erie
Franklin
Greene
Lackawanna
Lancaster
Lawrence
Lehigh
Luzerne
80.0
88.3
93.3
92.0
90.7
85.7
87.7
76.0
75.3
77.3
71.0
75.0
77.0
80.3
78.0
73.0
83.0
80.0
91.3
90.7
91.3
88.7
83.3
99.0
85.0
84.7
95.0
87.3
86.7
91.7
89.0
90.7
87.7
83.3
91.0
78.3
90.7
83.7
62.0
67.8
73.6
70.8
70.3
63.2
70.4
58.1
61.3
62.4
59.3
61.6
63.0
62.4
63.5
61.6
67.7
61.0
73.9
70.3
72.8
67.4
62.3
80.7
65.1
63.7
72.9
66.7
66.6
72.7
73.2
68.8
65.5
63.3
69.2
59.2
68.6
63.5
61.7
67.6
73.4
70.5
70.0
62.7
70.1
58.0
61.1
62.2
59.1
61.5
62.8
62.3
63.4
61.4
67.6
60.7
73.6
69.6
72.5
67.2
62.0
80.1
64.8
63.5
72.7
66.3
66.4
72.4
72.7
68.5
65.0
63.2
69.1
59.0
68.4
63.4
61.5
67.3
73.1
70.2
69.7
62.5
69.7
57.8
60.9
62.0
59.0
61.2
62.6
62.1
63.1
61.1
67.4
60.5
73.3
69.4
72.3
67.0
61.8
80.0
64.5
63.2
72.5
66.1
66.2
72.2
72.5
68.2
64.8
63.0
68.8
58.7
68.2
63.2
61.1
66.5
72.7
69.7
69.3
63.1
69.5
56.0
60.3
61.7
58.9
61.0
62.2
59.8
62.7
61.0
65.6
59.9
73.3
69.8
72.1
66.2
61.5
80.1
64.4
62.7
71.9
66.0
65.4
72.2
72.9
67.3
65.2
62.0
68.0
58.3
67.3
62.3
60.6
66.0
72.1
69.0
68.5
61.8
68.9
55.7
59.9
61.4
58.5
60.8
61.8
59.6
62.4
60.5
65.4
59.5
72.4
68.4
71.5
65.8
60.9
78.9
63.7
62.2
71.4
65.2
65.1
71.6
72.0
66.8
64.2
61.6
67.6
57.8
66.8
61.9
59.9
65.2
71.2
68.0
67.7
61.3
67.8
55.1
59.4
60.8
58.1
60.1
61.3
58.9
61.5
59.7
64.8
58.8
71.8
67.8
71.0
65.1
60.1
78.4
63.0
61.4
70.6
64.6
64.4
71.1
71.2
66.0
63.7
61.1
66.8
57.0
66.3
61.3
54
-------
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Rhode Island
Rhode Island
Rhode Island
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
South Carolina
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Lycoming
Mercer
Montgomery
Northampton
Perry
Philadelphia
Tioga
Washington
Westmoreland
York
Kent
Providence
Washington
Abbeville
Aiken
Anderson
Barnwell
Berkeley
Charleston
Cherokee
Chester
Chesterfield
Colleton
Darlington
Edgefield
Oconee
Pickens
Richland
Spartanburg
Union
Williamsburg
York
Anderson
Blount
Davidson
Hamilton
Haywood
Jefferson
82.0
91.3
92.3
90.0
83.3
96.7
85.0
86.3
88.0
89.0
93.0
92.0
92.7
82.3
82.7
85.3
79.3
71.5
72.5
83.7
82.7
80.0
77.7
82.7
79.7
83.7
83.0
89.3
87.0
79.7
71.7
83.0
87.0
92.3
77.7
88.3
83.5
91.0
62.7
70.1
73.4
68.2
63.1
79.7
66.4
68.2
70.9
68.5
72.6
72.0
73.7
61.5
62.7
64.8
60.0
54.5
56.3
62.2
60.6
60.1
59.4
62.5
60.3
61.8
61.0
67.8
63.7
59.9
53.4
60.8
60.2
66.6
58.2
63.7
61.5
63.4
62.5
69.7
73.1
68.0
63.0
79.2
66.2
68.0
70.3
68.4
72.2
71.5
73.2
61.4
62.6
64.8
59.9
54.1
55.9
62.2
60.5
60.0
59.3
62.4
60.2
61.7
61.0
67.7
63.7
59.8
53.3
60.8
60.0
66.4
57.9
63.5
61.2
63.3
62.3
69.4
72.9
67.8
62.7
79.0
66.0
67.8
70.1
68.1
72.0
71.4
73.1
61.2
62.3
64.6
59.6
53.9
55.7
62.0
60.3
59.7
59.1
62.2
60.0
61.5
60.8
67.5
63.4
59.6
53.1
60.6
59.7
66.1
57.6
63.1
61.0
63.0
61.7
69.0
72.7
66.8
62.0
79.2
65.4
67.7
70.3
67.4
72.1
71.4
73.3
59.6
60.9
62.3
58.4
53.6
55.5
60.6
58.9
58.6
58.2
61.0
58.7
59.8
58.9
65.3
61.4
58.1
52.3
59.1
57.6
64.4
56.7
61.3
60.4
60.2
61.3
68.3
72.1
66.2
61.6
78.0
65.0
67.1
69.1
67.0
71.0
70.4
72.2
59.4
60.7
62.2
58.2
52.8
54.6
60.4
58.7
58.4
57.9
60.8
58.5
59.6
58.7
65.1
61.3
57.9
52.0
58.9
57.3
64.0
56.1
60.9
59.8
59.9
60.7
67.3
71.6
65.7
60.8
77.6
64.4
66.5
68.5
66.3
70.7
70.0
71.8
58.7
60.1
61.6
57.5
52.2
54.0
59.8
58.2
57.7
57.3
60.1
57.9
59.1
58.1
64.4
60.6
57.3
51.4
58.4
56.4
63.0
55.4
59.6
59.1
59.0
55
-------
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Texas
Utah
Utah
Knox
Lawrence
Meigs
Putnam
Rutherford
Sevier
Shelby
Sullivan
Sumner
Williamson
Wilson
Bexar
Brazoria
Collin
Dallas
Denton
El Paso
Ellis
Galveston
Gregg
Harris
Harrison
Hood
Jefferson
Johnson
Kaufman
Montgomery
Nueces
Orange
Parker
Rockwall
Smith
Tarrant
Travis
Victoria
Webb
Box Elder
Cache
92.0
77.0
89.0
84.0
80.7
92.3
87.7
86.7
85.7
84.3
82.0
88.7
94.0
90.0
90.0
97.3
79.3
85.0
89.7
84.3
102.0
78.5
83.0
91.0
89.7
72.0
88.3
80.3
81.0
87.0
82.0
82.0
98.7
84.7
77.7
64.7
77.5
69.3
63.4
57.8
62.8
63.1
59.5
68.0
68.3
67.3
63.5
62.1
61.6
70.6
80.2
71.4
70.5
76.2
70.5
64.4
76.6
69.0
92.4
62.8
59.6
78.6
67.3
56.0
77.3
68.9
69.6
64.8
63.2
65.1
77.0
65.7
65.1
55.3
67.0
58.7
63.3
57.6
62.7
63.0
59.3
67.8
67.5
67.3
63.3
61.8
61.4
70.4
79.1
71.2
70.4
76.1
70.5
64.3
76.6
68.8
92.4
62.5
59.5
77.4
67.2
55.9
76.7
68.0
68.6
64.7
63.1
64.9
76.9
65.4
64.4
54.8
67.0
58.7
62.9
57.3
62.3
62.8
59.1
67.5
67.2
67.0
63.0
61.6
61.2
70.1
78.9
71.0
70.2
75.9
70.3
64.1
76.4
68.6
92.3
62.3
59.2
77.2
67.0
55.6
76.6
67.8
68.4
64.5
62.9
64.7
76.7
65.2
64.2
54.7
66.7
58.4
59.9
56.9
60.8
61.9
58.1
66.3
67.6
66.0
61.9
60.5
60.2
69.4
80.6
70.3
69.7
75.4
67.3
63.3
76.6
68.2
92.1
62.1
58.1
79.0
66.0
55.3
77.3
69.2
69.8
63.6
62.2
64.2
76.2
64.5
65.0
55.2
66.2
57.5
59.6
56.3
60.5
61.6
57.6
65.9
65.8
65.8
61.3
59.9
59.8
68.9
78.1
70.0
69.4
75.1
67.2
63.1
76.0
67.8
92.0
61.5
57.8
76.5
65.7
55.0
76.0
67.2
67.7
63.4
61.9
63.8
75.9
63.9
63.5
54.1
66.1
57.4
58.5
55.6
59.5
60.9
56.9
65.0
64.9
65.1
60.6
59.2
59.1
68.3
77.7
69.4
68.8
74.5
66.5
62.5
75.5
67.2
91.6
60.8
57.1
76.0
65.1
54.4
75.7
66.7
67.2
62.8
61.3
63.0
75.4
63.3
63.0
53.8
65.2
56.7
56
-------
Utah
Utah
Utah
Utah
Vermont
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Davis
Salt Lake
Utah
Weber
Bennington
Alexandria City
Arlington
Caroline
Charles City
Chesterfield
Fairfax
Fauquier
Frederick
Hampton City
Hanover
Henri co
Loudoun
Madison
Page
Prince William
Roanoke
Rockbridge
Stafford
Suffolk City
Berkeley
Cabell
Hancock
Kanawha
Monongalia
Ohio
Wood
Brown
Columbia
Dane
Dodge
Door
Fond Du Lac
Jefferson
81.0
79.7
77.7
79.3
79.3
90.0
96.7
82.3
89.3
84.7
96.7
79.3
82.7
88.3
92.0
88.3
90.0
84.7
79.7
85.0
83.7
76.7
86.0
87.0
83.0
85.7
84.7
84.0
78.7
83.3
85.7
80.3
76.3
76.0
79.3
91.0
77.3
80.0
72.8
72.8
69.3
68.1
62.5
68.1
74.2
60.7
70.2
67.6
73.2
59.7
63.3
72.9
71.2
68.9
68.5
64.2
59.3
64.9
63.2
58.0
64.8
72.0
63.7
70.9
65.5
63.6
56.7
64.6
63.9
67.9
62.1
62.6
65.7
75.0
63.7
65.0
72.8
72.7
69.3
68.1
62.3
68.0
74.1
60.6
70.1
67.5
73.1
59.5
63.1
72.7
71.1
68.8
68.3
64.1
59.1
64.7
63.1
57.9
64.7
71.8
63.5
70.5
65.3
63.2
56.5
64.2
63.3
67.8
61.9
62.5
65.5
74.8
63.6
64.9
72.6
72.4
69.0
67.8
62.1
67.8
73.8
60.3
69.9
67.4
72.8
59.3
62.8
72.5
70.9
68.6
68.1
63.9
58.9
64.5
62.8
57.7
64.2
71.6
63.2
70.3
65.1
63.0
56.4
64.1
63.1
67.5
61.7
62.2
65.3
74.4
63.4
64.6
71.7
72.2
68.3
66.8
61.1
66.7
72.6
59.5
69.1
66.7
71.6
58.8
62.2
72.4
70.0
67.7
67.4
63.2
58.3
63.8
61.6
57.0
63.5
71.7
62.5
71.7
65.0
63.1
56.2
64.3
63.8
67.4
61.1
61.6
65.1
74.4
63.0
64.1
71.6
72.1
68.3
66.7
60.7
66.5
72.3
59.2
68.9
66.4
71.4
58.4
61.7
72.0
69.7
67.4
67.0
62.9
57.9
63.4
61.3
56.7
63.3
71.3
62.0
71.1
64.4
62.4
55.8
63.5
62.5
67.1
60.7
61.2
64.7
74.0
62.8
63.7
70.9
71.2
67.7
65.9
60.0
65.8
71.6
58.5
68.4
66.0
70.7
57.7
61.0
71.6
69.2
67.0
66.3
62.4
57.5
62.6
60.5
56.1
62.1
70.8
61.2
70.4
63.9
61.8
55.3
63.0
62.0
66.4
60.0
60.5
64.0
72.9
62.1
62.9
57
-------
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Kenosha
Kewaunee
Manitowoc
Milwaukee
Ozaukee
Racine
Rock
Sauk
Sheboygan
St Croix
Walworth
Washington
Waukesha
98.3
89.3
87.0
91.0
93.0
91.7
81.7
72.0
97.0
71.3
81.3
80.3
79.0
85.0
74.3
72.2
77.2
78.0
78.0
66.1
59.4
81.1
61.2
66.3
67.4
66.0
84.9
74.1
72.0
77.1
77.9
77.9
65.9
59.3
80.9
61.1
66.2
67.2
65.9
84.7
73.8
71.6
76.8
77.5
77.7
65.5
59.0
80.5
61.0
65.8
67.0
65.6
84.4
73.9
71.6
76.6
77.3
77.4
64.7
58.6
80.4
60.7
65.4
66.9
65.5
84.2
73.4
71.2
76.3
77.0
77.1
64.2
58.3
79.9
60.5
65.0
66.5
65.1
83.4
72.3
70.2
75.4
75.9
76.4
63.1
57.6
78.7
60.0
64.1
65.9
64.4
58
-------
Appendix C: Visibility Levels on 20% Worst Days for Locomotive/Marine Scenario (units are deciviews)
Class 1 Area
Sipsey Wilderness
Caney Creek Wilderness
Upper Buffalo Wilderness
Chiricahua NM
Chiricahua Wilderness
Galiuro Wilderness
Grand Canyon NP
Mazatzal Wilderness
Petrified Forest NP
Pine Mountain Wilderness
Saguaro NM
Sierra Ancha Wilderness
Sycamore Canyon Wilderness
Agua Tibia Wilderness
Caribou Wilderness
Cucamonga Wilderness
Desolation Wilderness
Dome Land Wilderness
Emigrant Wilderness
Hoover Wilderness
Joshua Tree NM
Lassen Volcanic NP
Lava Beds NM
Mokelumne Wilderness
Pinnacles NM
Point Reyes NS
Redwood NP
San Gabriel Wilderness
San Gorgonio Wilderness
San Jacinto Wilderness
South Warner Wilderness
State
AL
AR
AR
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
AZ
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
Baseline
Visibility
29.03
26.36
26.27
13.43
13.43
13.43
11.66
13.35
13.21
13.35
14.83
13.67
15.25
23.50
14.15
19.94
12.63
19.43
17.63
12.87
19.62
14.15
15.05
12.63
18.46
22.81
18.45
19.94
22.17
22.17
15.05
2020 Base
23.78
22.11
22.41
13.09
13.09
13.08
11.13
12.74
12.90
12.59
14.50
13.22
14.96
21.23
13.62
17.42
12.15
18.37
17.22
12.73
17.95
13.56
14.45
12.32
17.37
22.01
17.89
17.30
20.28
19.92
14.61
2020
Locomotive /
Marine
23.73
22.05
22.35
13.09
13.09
13.07
11.09
12.72
12.83
12.58
14.47
13.20
14.94
21.14
13.60
17.36
12.13
18.34
17.21
12.72
17.93
13.54
14.42
12.30
17.36
21.99
17.86
17.25
20.22
19.87
14.59
2030 Base
23.77
22.06
22.34
13.10
13.10
13.11
11.15
12.77
12.87
12.59
14.49
13.18
14.98
21.16
13.55
17.14
12.15
18.20
17.24
12.75
17.85
13.48
14.40
12.34
17.16
21.87
17.86
17.01
19.94
19.61
14.57
2030
Locomotive /
Marine
23.66
21.92
22.19
13.09
13.09
13.09
11.08
12.73
12.75
12.54
14.44
13.15
14.93
20.94
13.51
17.10
12.12
18.11
17.19
12.74
17.71
13.43
14.32
12.31
17.09
21.79
17.79
16.93
19.70
19.55
14.52
Natural
Background
10.99
11.58
11.57
7.21
7.21
7.21
7.14
6.68
6.49
6.68
6.46
6.59
6.69
7.64
7.31
7.06
6.12
7.46
7.64
7.91
7.19
7.31
7.86
6.12
7.99
15.77
13.91
7.06
7.30
7.30
7.86
59
-------
Thousand Lakes Wilderness
Ventana Wilderness
Yosemite NP
Black Canyon of the Gunnison NM
Eagles Nest Wilderness
Flat Tops Wilderness
Great Sand Dunes NM
La Garita Wilderness
Maroon Bells-Snowmass Wilderness
Mesa Verde NP
Mount Zirkel Wilderness
Rawah Wilderness
Rocky Mountain NP
Weminuche Wilderness
West Elk Wilderness
Chassahowitzka
Everglades NP
St. Marks
Cohutta Wilderness
Okefenokee
Wolf Island
Craters of the Moon NM
Sawtooth Wilderness
Mammoth Cave NP
Acadia NP
Moosehorn
Roosevelt Campobello International Park
Isle Royale NP
Seney
Voyageurs NP
Hercules-Glades Wilderness
Anaconda-Pintler Wilderness
Bob Marshall Wilderness
Cabinet Mountains Wilderness
Gates of the Mountains Wilderness
Medicine Lake
Mission Mountains Wilderness
Scapegoat Wilderness
CA
CA
CA
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
CO
FL
FL
FL
GA
GA
GA
ID
ID
KY
ME
ME
ME
Ml
Ml
MN
MO
MT
MT
MT
MT
MT
MT
MT
14.15
18.46
17.63
10.33
9.61
9.61
12.78
10.33
9.61
13.03
10.52
10.52
13.83
10.33
9.61
26.09
22.30
26.03
30.30
27.13
27.13
14.00
13.78
31.37
22.89
21.72
21.72
20.74
24.16
19.27
26.75
13.41
14.48
14.09
11.29
17.72
14.48
14.48
13.54
17.67
17.16
9.80
9.05
9.31
12.36
9.90
9.24
12.40
10.06
10.04
13.10
9.86
9.24
21.96
19.75
21.84
23.36
23.46
23.40
13.00
13.64
25.53
19.79
18.65
18.47
19.15
21.77
17.62
23.00
13.15
14.14
13.57
10.92
16.25
14.06
14.17
13.52
17.64
17.14
9.79
9.03
9.31
12.36
9.89
9.24
12.39
10.05
10.04
13.08
9.86
9.24
21.94
19.77
21.82
23.33
23.42
23.37
12.97
13.63
25.48
19.77
18.63
18.45
19.10
21.72
17.58
22.93
13.14
14.13
13.54
10.91
16.22
14.04
14.16
13.46
17.67
17.15
9.79
8.99
9.32
12.37
9.89
9.24
12.40
10.07
10.06
13.06
9.86
9.24
21.96
19.97
21.88
23.34
23.50
23.40
12.90
13.64
25.54
19.86
18.68
18.51
19.16
21.78
17.53
22.96
13.13
14.11
13.52
10.89
16.18
14.02
14.14
13.41
17.62
17.11
9.77
8.96
9.31
12.36
9.88
9.24
12.37
10.04
10.04
13.01
9.86
9.23
21.91
19.94
21.83
23.28
23.40
23.32
12.82
13.63
25.44
19.81
18.64
18.47
19.04
21.66
17.43
22.81
13.11
14.08
13.46
10.87
16.12
13.99
14.12
7.31
7.99
7.64
6.24
6.54
6.54
6.66
6.24
6.54
6.83
6.44
6.44
7.24
6.24
6.54
11.21
12.15
11.53
11.14
11.44
11.44
7.53
6.43
11.08
12.43
12.01
12.01
12.37
12.65
12.06
11.30
7.43
7.74
7.53
6.45
7.90
7.74
7.74
60
-------
Selway-Bitterroot Wilderness
UL Bend
Linville Gorge Wilderness
Swanquarter
Lostwood
Theodore Roosevelt NP
Great Gulf Wilderness
Presidential Range-Dry River Wilderness
Brigantine
Bandelier NM
Bosque del Apache
Gila Wilderness
Pecos Wilderness
Salt Creek
San Pedro Parks Wilderness
Wheeler Peak Wilderness
White Mountain Wilderness
Jarbidge Wilderness
Wichita Mountains
Crater Lake NP
Diamond Peak Wilderness
Eagle Cap Wilderness
Gearhart Mountain Wilderness
Hells Canyon Wilderness
Kalmiopsis Wilderness
Mount Hood Wilderness
Mount Jefferson Wilderness
Mount Washington Wilderness
Mountain Lakes Wilderness
Strawberry Mountain Wilderness
Three Sisters Wilderness
Cape Remain
Badlands NP
Wind Cave NP
Great Smoky Mountains NP
Joyce-Kilmer-Slickrock Wilderness
Big Bend NP
Carlsbad Caverns NP
MT
MT
NC
NC
ND
ND
NH
NH
NJ
NM
NM
NM
NM
NM
NM
NM
NM
NV
OK
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
SC
SD
SD
TN
TN
TX
TX
13.41
15.14
28.77
25.49
19.57
17.74
22.82
22.82
29.01
12.22
13.80
13.11
10.41
18.03
10.17
10.41
13.70
12.07
23.81
13.74
13.74
18.57
13.74
18.55
15.51
14.86
15.33
15.33
13.74
18.57
15.33
26.48
17.14
15.84
30.28
30.28
17.30
17.19
13.06
14.66
22.48
21.17
17.73
16.65
19.48
19.48
24.88
11.43
12.96
12.55
10.01
16.61
9.53
9.96
13.07
11.86
20.67
13.29
13.25
17.86
13.39
17.26
15.00
14.19
14.80
14.77
13.26
17.77
14.84
22.77
15.87
14.94
23.96
23.46
16.15
15.93
13.04
14.64
22.45
21.15
17.70
16.54
19.45
19.45
24.85
11.41
12.90
12.54
10.00
16.59
9.52
9.95
13.05
11.86
20.62
13.27
13.20
17.83
13.37
17.20
14.98
14.13
14.77
14.75
13.24
17.73
14.82
22.74
15.84
14.91
23.93
23.43
16.13
15.92
13.02
14.62
22.47
21.20
17.67
16.61
19.50
19.50
24.99
11.38
12.94
12.55
10.02
16.58
9.53
9.97
13.07
11.86
20.68
13.26
13.22
17.79
13.36
17.18
14.97
14.28
14.82
14.78
13.23
17.69
14.84
22.77
15.80
14.94
23.93
23.43
16.18
15.92
12.99
14.58
22.41
21.15
17.60
16.42
19.46
19.46
24.91
11.34
12.81
12.54
10.01
16.52
9.52
9.96
13.04
11.85
20.55
13.20
13.12
17.71
13.33
17.04
14.93
14.14
14.76
14.72
13.17
17.60
14.79
22.71
15.75
14.87
23.86
23.37
16.15
15.90
7.43
8.16
11.22
11.94
8.00
7.79
11.99
11.99
12.24
6.26
6.73
6.69
6.44
6.81
6.08
6.44
6.86
7.87
7.53
7.84
7.84
8.92
7.84
8.32
9.44
8.44
8.79
8.79
7.84
8.92
8.79
12.12
8.06
7.71
11.24
11.24
7.16
6.68
61
-------
Guadalupe Mountains NP
Arches NP
Bryce Canyon NP
Canyonlands NP
Zion NP
James River Face Wilderness
Shenandoah NP
Lye Brook Wilderness
Alpine Lake Wilderness
Glacier Peak Wilderness
Goat Rocks Wilderness
Mount Adams Wilderness
Mount Rainier NP
North Cascades NP
Olympic NP
Pasayten Wilderness
Dolly Sods Wilderness
Otter Creek Wilderness
Bridger Wilderness
Fitzpatrick Wilderness
Grand Teton NP
North Absaroka Wilderness
Red Rock Lakes
Teton Wilderness
Washakie Wilderness
Yellowstone NP
TX
UT
UT
UT
UT
VA
VA
VT
WA
WA
WA
WA
WA
WA
WA
WA
WV
WV
WY
WY
WY
WY
WY
WY
WY
WY
17.19
11.24
11.65
11.24
13.24
29.12
29.31
24.45
17.84
13.96
12.76
12.76
18.24
13.96
16.74
15.23
29.04
29.04
11.12
11.12
11.76
11.45
11.76
11.76
11.45
11.76
15.89
11.14
11.36
10.84
12.96
23.43
22.83
21.10
16.77
13.62
12.06
12.03
17.27
13.58
15.85
14.85
22.38
22.31
10.81
10.86
11.36
11.17
11.44
11.41
11.18
11.39
15.88
11.11
11.34
10.81
12.92
23.34
22.80
21.08
16.71
13.60
12.05
12.01
17.24
13.57
15.82
14.84
22.35
22.29
10.81
10.85
11.35
11.16
11.43
11.40
11.17
11.38
15.89
11.05
11.34
10.83
12.89
23.43
22.83
21.17
16.72
13.69
12.07
12.02
17.27
13.68
15.95
14.83
22.38
22.32
10.80
10.86
11.33
11.15
11.42
11.39
11.16
11.36
15.86
11.03
11.31
10.82
12.81
23.26
22.76
21.11
16.60
13.67
12.03
11.97
17.21
13.67
15.89
14.81
22.33
22.27
10.80
10.84
11.31
11.13
11.39
11.36
11.14
11.34
6.68
6.43
6.86
6.43
6.99
11.13
11.35
11.73
8.43
8.01
8.36
8.36
8.55
8.01
8.44
8.26
10.39
10.39
6.58
6.58
6.51
6.86
6.51
6.51
6.86
6.51
62
-------
United States
Environmental Protection
Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Research Triangle Park, NC
Publication No. EPA 454/R-08-002
January 2008
63
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