Photochemical Model Estimated Relationships Between Offshore Wind Energy Project Precursor Emissions and Downwind Air Quality (O3 and PM2.5) Impacts


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Photochemical Model Estimated Relationships
Between Offshore Wind Energy Project
Precursor Emissions and Downwind Air Quality
(03 and PM2.5) Impacts

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EPA-454/R-22-007
December 2022

Photochemical Model Estimated Relationships Between Offshore Wind Energy Project
Precursor Emissions and Downwind Air Quality (03 and PM2.5) Impacts

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

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BACKGROUND

This document is intended to provide information for permitting authorities and permit applicants
relating precursor emissions from offshore wind energy projects to ozone (03) and secondarily formed
particulate matter less than 2.5 microns in diameter (PM2.5) impacts. Primarily emitted PM2.5 should be
estimated with tools intended for that purpose. Section 4.2.2.3 of the Guideline on Air Quality Models
(the "Guideline/' published as Appendix W to 40 CFR part 51) states that the impacts of offshore primary
pollutants should be modeled using the Offshore and Coastal Dispersion (OCD) model (or other case
specific alternative model approved by EPA) for distances out to 50 km (section 8.1.2) from the source.
The Guideline recommends a two-tiered approach for addressing single-source impacts on 03 and
secondary PM2.5 (U.S. Environmental Protection Agency, 2021). The first tier (or Tier 1) involves use of
appropriate and technically credible relationships between emissions and ambient impacts developed
from existing modeling studies deemed sufficient for evaluating impacts from a project. The second tier
(or Tier 2) involves more sophisticated case-specific application of chemical transport modeling (e.g.,
with an Eulerian grid or Lagrangian model) (U.S. Environmental Protection Agency, 2021).

The document is intended to provide relationships between precursors and maximum downwind
impacts of 03 and PM2.5 for the purposes of developing a technically credible Tier 1 demonstration tool
for sources offshore of the Atlantic coast. Specifically, the emissions sources in this assessment
represent areas offshore of the United States that have been leased for the purpose of constructing
wind energy projects. This approach is similar to Modeled Emission Rates for Precursors (MERPs), which
is also a Tier 1 demonstration tool (U.S. Environmental Protection Agency, 2019b) under the Prevention
of Significant Deterioration (PSD) permitting program that provides a simple way to relate maximum
downwind impacts with a critical air quality threshold (e.g., a significant impact level or SIL) (U.S.
Environmental Protection Agency, 2018). Relationships between emissions and downwind impacts of
primarily emitted PM2.5 are provided for distances beyond 50 km for permit related assessments where
that information may be useful (e.g., Class I increment for the PSD program). New relationships between
emissions and downwind impacts were needed to represent the offshore chemical and physical
environment which was not reasonably reflected in the existing Tier 1 MERPs database.

03 formation is a complicated, nonlinear process that depends on meteorological conditions in addition
to volatile organic compounds (VOC) and nitrogen oxides (NOx) concentrations (Seinfeld and Pandis,
2008). Warm temperatures, clear skies (abundant levels of solar radiation), and stagnant air masses (low
wind speeds) increase 03 formation potential (Seinfeld and Pandis, 2008). In the case of PM2.5, total
mass is often categorized into two groups: primary (i.e., emitted directly as PM2.5 from sources) and
secondary (i.e., PM2.5 formed in the atmosphere by precursor emissions from sources). PM2.5 sulfate,
nitrate, and ammonium are predominantly the result of chemical reactions of the oxidized products of
sulfur dioxide (S02) and NOx emissions and direct ammonia (NH3) emissions (Seinfeld and Pandis, 2008).
PM2.5 organic aerosol (primary and secondary), nitrate, and ammonium are also impacted by
semivolatile partitioning that is influenced by both the meteorological conditions and the chemical
environment.

EPA believes that use of photochemical models for estimating single source secondary pollutant impacts
is scientifically appropriate (U.S. Environmental Protection Agency, 2019b, 2021). Photochemical models
treat emissions, chemical transformation and partitioning, transport, and deposition using time and
space variant meteorology. These modeling systems simulate primarily emitted species and secondarily
formed pollutants such as 03 and PM2.5 (Kelly et al., 2019; Simon et al., 2012). Even though single source
emissions are injected into a grid volume, photochemical transport models have been shown to

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adequately capture single source impacts when compared with downwind in-plume measurements
(Baker and Kelly, 2014; Baker and Woody, 2017).

Some photochemical models have been instrumented with source apportionment capabilities which
tracks emissions from specific sources through chemical transformation, transport, and deposition
processes to estimate source-specific impacts to predicted air quality at downwind receptors (Kwok et
al., 2015; Kwok et al., 2013). Source apportionment has been used to differentiate the air quality impact
from single sources on model predicted 03 and PM2.5 (Baker and Foley, 2011; Baker and Kelly, 2014;
Baker et al., 2016; Baker and Woody, 2017). Photochemical grid model source apportionment and
source sensitivity simulation of single-source downwind impacts compare well against field study
primary and secondary ambient in-plume measurements (Baker and Kelly, 2014; Baker and Woody,
2017; ENVIRON International Corporation, 2012). This work indicates photochemical grid models using
source apportionment or source sensitivity approaches provide meaningful estimates of single source
impacts.

This document presents an overview of EPA photochemical modeling of hypothetical offshore emissions
sources with 2017 National Emission Inventory (NEI) based emissions on downwind 03 and secondary
PM2.5. Ozone contributions were estimated using Ozone Source Apportionment Technology and PM2.5
contributions using Particulate Source Apportionment Technology as implemented in the CAMx
photochemical model (Ramboll, 2022). The contribution from each of these emissions sources to model
predicted 03 and inorganic PM2.5 ions (sulfate, nitrate, ammonium) were tracked using reactive tracers
which track impacts of chemistry, atmospheric transport and deposition in the photochemical model
(Kwok et al., 2015; Kwok et al., 2013; Ramboll, 2022). Primary emitted PM2.5 was tracked with inert
tracers which track impacts of atmospheric transport and deposition in the photochemical model. All
precursor impacts on PM2.5 and 03 are tracked separately (e.g., NOx to 03, VOC to 03, etc.).

MODEL CONFIGURATION & APPLICATION

Wind farm construction and operation includes the use of multiple categories of commercial marine
vessels. Category 1 (CI) and Category 2 (C2) vessels have marine diesel engines above 800 horsepower
(hp) with displacement less than 30 liters per cylinder. Category 3 (C3) engines are those at or above 30
liters per cylinder, typically these are the largest engines rated at 3,000 to 100,000 hp. C3 engines are
typically used for propulsion on ocean-going vessels. CI and C2 marine diesel engines typically range in
size from about 700 to 11,000 hp. These engines are used to provide propulsion power on many kinds of
vessels including tugboats, towboats, supply vessels, fishing vessels, and other commercial vessels in
and around ports. They are also used as stand-alone generators for auxiliary electrical power on many
types of vessels.

The locations tracked for contribution are shown in Figure 1. These locations were selected based on a
review of areas offshore that were leased to private entities for the purpose of wind farm construction
and operation.

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Figure 1. Location of hypothetical emissions sources tracked for contribution as part of this project.
The gray lines indicate nominal distance increments of 50 km and do not represent grid cell size
used for the photochemical model applications.

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Annual emission totals in tons per year (tpy) were provided for total primarily emitted PM2.5, coarse
fraction PM, VOC, NH3, S02, and NOx for each hypothetical source. Primarily emitted PM2.5 was tracked
with 4 separate emission rates for each source: 20, 215, 1100, and 3700 tpy. Primarily emitted coarse
fraction PM was tracked with 2 separate emission rates for each source: 215 and 870 tpy. An emission
rate of 5,000 tpy was used for NOx and 50 tpy for S02 and VOC. Ammonia emissions were 5 tpy based on
the 2017 NEI totals for commercial marine vessels. The hypothetical sources were assigned a surface
level stack height. NOx, VOC, and primary PM emissions were speciated consistent with profiles used for
the commercial marine sector. Temporal profiles were unique to each hypothetical source location and
based on nearby commercial marine vessel activity reported in the 2017 AIS database (NOAA Office for
Coastal Management, 2022).

Model Configuration

Annual 2017 photochemical model simulations were performed for a domain covering the contiguous
United States with 12 km sized grid cells (Figure 2). Each simulation tracked a different combination of
pollutants. All simulations were conducted using version 7.20 of the Comprehensive Air Quality Model
with Extensions (CAMx) photochemical grid model (www.camx.com). This CAMx application includes
ISORROPIA inorganic chemistry (Nenes et al., 1998), gas phase reactions based on the Carbon Bond
(CB6r5) mechanism (Ramboll, 2016, 2022), and aqueous phase reactions (Ramboll, 2022). Chemical
boundary inflow was extracted from a photochemical model simulation for 2017 with a larger
geographic domain covering the northern hemisphere (U.S. Environmental Protection Agency, 2019a).

A total of 35 layers were used to represent the vertical atmosphere to 50 mb with thinner layers nearer
the surface (the height of the layer closest to the surface is approximately 20 m). The meteorological
model configuration, application, and evaluation are available in a separate document (U.S.
Environmental Protection Agency, 2022). Baseline emissions include anthropogenic sources based on
the "2017gb" version of the 2017 National Emission Inventory (U.S. Environmental Protection Agency,
2020) and biogenic sources estimated with the Biogenic Emission Inventory System version 3.6.1 (Bash
et al., 2016). Mobile emissions were based on the MOVES2014b model. Wildland fire emissions were
day specific for 2017 (U.S. Environmental Protection Agency, 2020).

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Figure 2. Photochemical model domain. The location of offshore leased and planning areas are also
shown as well as hypothetical sources modeled as part of this assessment.

Model Application

The photochemical model was applied for the entire year of 2017 at 12 km grid resolution. A total of 27
hypothetical offshore emissions sources were included in addition to the 2017 NEl emissions and
tracked for contribution to air quality impacts using source apportionment. Table 1 shows the
relationship between precursor emissions and contribution to modeled primary and secondary
pollutants. The model was applied so that primary and secondary precursors were tracked for
contribution to modeled PM2.5 components. NOx emissions were tracked for contribution to PM2.5
nitrate ion, NH3 emissions were tracked for contribution to PM2.5 ammonium ion, and S02 emissions
were tracked for contribution to PM2.5 sulfate ion.

Primarily emitted elemental carbon, organic aerosol, and crustal components were tracked to model
predicted PM2.5 emitted as primary only. Primarily emitted coarse PM components were tracked to
model predicted coarse PM. The contribution to PM2.5 nitrate does not include primarily emitted PM2.5
nitrate and the contribution to PM2.5 sulfate does not include primarily emitted PM2.5 sulfate.

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Table 1. Relationship between emissions species and tracked primary and secondarily formed PM2.5
and 03 in the modeling system.

Precursor

Tagged Pollutant

voc

NOx

S02
NOx
NH3

Primary PM2 5
Coarse PM

Secondarily formed PM2.5 sulfate ion
Secondarily formed PM2.5 nitrate ion
Secondarily formed PM2.5 ammonium ion
Primary PM2 5: FCRS, FPRM, PEC, POA
Primary coarse PM: CCRS, CPRM
Ozone
Ozone

MODEL PERFORMANCE EVALUATION
Particulate Matter

An operational model performance evaluation for the speciated components of PM2.5 (e.g., sulfate,
nitrate, elemental carbon, organic carbon, etc.) was conducted using 2017 monitoring data in order to
estimate the ability of the modeling system to predict ambient concentrations. The evaluation of PM2 5
component species includes comparisons of predicted and observed concentrations of sulfate (S04),
nitrate (N03), elemental carbon (EC), and organic carbon (OC). Chemically speciated PM2.5 ambient
measurements for 2017 were obtained from the Chemical Speciation Network (CSN) and the
Interagency Monitoring of PROtected Visual Environments (IMPROVE). The CSN sites are generally
located within urban areas and the IMPROVE sites are typically in rural/remote areas. The
measurements at CSN and IMPROVE sites represent 24-hour average concentrations. In calculating the
model performance metrics, the modeled hourly species predictions were aggregated to the averaging
times of the measurements.

Model performance statistics were calculated for observed/predicted pairs of all daily concentrations
measured in 2017 (Simon et al., 2012). Aggregated metrics and number (N) of prediction-observation
pairs are shown by chemical specie in Table 2. PM2.5 ammonium ion is not measured at most IMPROVE
monitors, so metrics were not generated for that network. Model performance was compared to the
performance found in recent regional PM2.5 model applications for other assessments. Overall, the mean
bias (bias) and mean error (error) statistics are within the range or close to that found by other groups in
recent applications (Kelly et al., 2019; Simon et al., 2012; Wilson et al., 2019). The average bias and error
for PM2.5 organic carbon are slightly larger than other recent assessments and are related to
overestimation of organic aerosol in the continental scale model simulation used to provide boundary
inflow conditions. This performance feature is not expected to systematically impact primary or
secondary PM2 5 or 03 predictions for the offshore wind sources modeled as part of this assessment.

Overall, the model performance results provide confidence that this application of CAMx provides a
scientifically credible approach for estimating PM2.5 concentrations for the purposes of this assessment.

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Table 2. Aggregated model performance metrics for speciated components of PM2.5 for the
IMPROVE and CSN monitor networks.

Mean Bias

Mean Error

Normalized

Specie

Network

(Hg/m3)

Mean Bias (%)

Mean Error (%)

PM2.5 sulfate ion

CSN

6,725

0.32

0.50

0.31

PM2.5 sulfate ion

IMPROVE

3,506

0.20

0.36

0.44

PM2.5 nitrate ion

CSN

6,712

0.55

0.77

0.38

PM2.5 nitrate ion

IMPROVE

3,508

0.38

0.51

129

0.28

PM2.5 elemental carbon

CSN

6,502

-0.02

0.28

-3

0.24

PM2.5 elemental carbon

IMPROVE

3,582

0.00

0.10

-2

0.58

PM2.5 organic carbon

CSN

6,510

2.77

2.82

139

141

0.33

PM2.5 organic carbon

IMPROVE

3,591

1.58

1.61

122

125

0.49

Ozone

An operational model performance evaluation for eight-hour daily maximum (MDA8) ozone was
conducted in order to estimate the ability of the modeling system to replicate the 2017 base year
concentrations. Ozone measurements were taken from 2017 monitoring site data in the Air Quality
System (AQS). The ozone metrics covered in this evaluation include eight-hour average daily maximum
ozone bias and error (Simon et al., 2012). The evaluation principally consists of statistical assessments of
model versus observed pairs that are paired in time and space. Aggregated metrics and number (N) of
prediction-observation pairs are shown in Table 3.

Table 3. Aggregated model performance metrics for MDA8 03. Metrics are shown for all prediction-
observation pairs, pairs where the model predictions exceed 60 ppb, and pairs where the
observations exceed 60 ppb.

Mean Bias

Mean Error

Normalized

Averaging Time & Specie

Data Subset

(ppb)

Mean Bias (%)

Mean Error (%)

MDA803

ALL

76,475

2.28

7.44

0.49

MDA803

MODEL >60

8,593

9.43

10.50

0.19

MDA803

OBS > 60

4,519

-2.66

7.15

-4

0.19

Only prediction-observation pairs from April through October were included in the aggregated metrics.
This ozone model performance includes all prediction-observation pairs, a subset of prediction-
observation pairs where observed ozone exceeded 60 ppb, and a subset of prediction-observation pairs
where predicted ozone exceeded 60 ppb. This cutoff was applied to evaluate the model on days of
elevated ozone which are more policy relevant. Overall, the mean bias (bias) and mean error (error)
statistics are within the range or close to that found by other groups in recent applications (Simon et al.,
2012; Wilson et al., 2019). The model performance results provide confidence that this application of
CAMx provides a scientifically credible approach for estimating 03 mixing ratios for the purposes of this
assessment.

Model predictions paired with observation data for multiple species are provided in Figure 3. PM2.5
species are shown separately for the IMPROVE and CSN monitor networks. PM2.5 ammonium ion is only
shown for the CSN network because it is not measured at sites in the IMPROVE network.

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Figure 3. Paired observations with model predictions. Comparisons shown for PM2.5 species: sulfate
ion, nitrate ion, elemental carbon, organic carbon, ammonium ion, and hourly 03.

Sulfate	Sulfate

• CSN network

ggWh. .

• IMPROVE network



Measured
Nitrate

• CSN network



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Measured
Nitrate

• IMPROVE network



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Measured

EC

• CSN network

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Measured
EC

• IMPROVE network

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Measured

oc

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Ammonium

• CSN network

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Measured

Measured
OC

• IMPROVE network

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Measured
MDA8 Ozone

8

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SOURCE IMPACT OVERVIEW

Ammonia reacts with sulfuric acid to form aerosol and with nitric acid to form ammonium nitrate when
meteorological conditions are favorable (Seinfeld and Pandis, 2008). Ammonia has been measured in
oceanic environments (Nair and Yu, 2020) but tends to be more abundant over land due to the larger
amounts of sources.

The distribution of emission rates of NOx and S02 that form PM2.5 equivalent to the SIL are shown in
Figure 4. This comparison includes hypothetical sources modeled over land (U.S. Environmental
Protection Agency, 2019b) and offshore sources modeled as part of this assessment. The land-based
distributions are differentiated by climate zone.

Figure 4. The distribution of emission rates equivalent to the relevant SIL level for daily average
PM2.5 (left) and annual average PM2.5 (right) for hypothetical single sources modeled over land and
the sources modeled offshore in this assessment. Results are shown for PM2.5 nitrate ion (top row)
and PM2.5 sulfate ion (bottom row).

24-hr PM2.5 MERPs - NOX precursor

OV UM RP
NOAA Climate Zone

24-hr PM2.5 MERPs - S02 precursor

Annual PM2.5 MERPs - NOX precursor

NOAA Climate Zone
Annual PM2.5 MERPs - S02 precursor

-s r

Offshore

tons/year
150000 250000

0 50000

I 1

Based on the information shown in Figure 4, the offshore sources modeled in this assessment indicate
that much greater S02 emissions are needed to form PM2.5 sulfate ion equivalent ot the SIL compared to
over-land sources. Offshore emissions of NOx needed to form PM2.5 nitrate ion equivalent to the SIL are
like the southwestern U.S. where ammonia emissions are more scarce compared to other regions. This
is most pronounced for the daily form of the NAAQS.

Other anions (such as sodium or calcium) already in the aerosol phase can also react with nitric acid
resulting in nitrate condensing into the particle phase. This switching would have limited (or small)
influence on aerosol mass because the water content would not be identical for N03 and CI and the
molar mass of N03 and CI is different. This type of anion substitution can also lead to the release of
sequestered hydrochloric acid that could participate in atmospheric reactions and increase the
anthropogenic contribution to aerosol at the expense of geogenic (e.g., sea salt) sources.

Figure 5 shows the distribution of NOx and VOC emissions needed to generate a modeled MDA8 03
impact equivalent to the SIL for over land hypothetical sources (U.S. Environmental Protection Agency,

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2019b) and offshore sources modeled as part of this assessment. The results shown in Figure 5 suggests
areas offshore of the Atlantic coast tend to be much more conducive to MDA8 03 formation from VOC
than NOx emissions. This is likely due to the sparse nature of chemically reactive VOC offshore compared
to over land where biogenic VOC is typically abundant, especially in the eastern U.S.

Figure 5. The distribution of emission rates equivalent to the relevant SIL level for MDA8 03 for
hypothetical single sources modeled over land and the sources modeled offshore in this
assessment. Results are shown for NOx (top row) and VOC (bottom row).

8-hr Ozone MERPs - NOX precursor	Offshore

03
0
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7/5
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7/5
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NOAA Climate Zone

8-hr Ozone MERPs - VOC precursor

Offshore

03


7/5
c
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in
o

Oceanic emissions of halogens in aerosol and gas phase forms can influence the lifetime of NOx, 03, and
some inorganic particulates. Some of these processes are included as part of the chemical mechanism
developed for the photochemical model. However, others are more novel and have not been fully
implemented. The potential impacts of chemical and physical processes related to oceanic emissions on
03 and PM2.5 model predictions follow.

A chlorine mediated nitrate photolysis pathway could allow for NOx recycling in the marine environment
(Kasibhatla et al., 2018). This process is highly uncertain but could be a source of nitrous acid (HONO)

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and N0X in remote areas (Zhang et al., 2020). Both iodine and bromine chemistry can affect NOx in the
marine environment but would not be expected to have a large impact on NOx.

NOx can react in the atmosphere to form N205 (Equation 1) and be converted to nitric acid (HN03)
(Equation 2) through heterogeneous chemistry and subsequently removed from participation in 03
formation reactions (McDuffie et al., 2018).

(1) no2 + no3-> n2o5

(2) N205 + H20(p) -> 2HN03

Another heterogenous N205 hydrolysis pathway (Equation 3) can act as a reservoir for N02 overnight
and potentially result in regenerated N02 at sunrise (Equation 4) (McDuffie et al., 2018).

(3) N2O5 + H+ + CI" -> HNO3 + CINO2

(4) CINO2 + hv -> N02 + CL"

In environments without chlorine 2 nitric acid molecules form from N205 heterogenous reactions, which
have a short atmospheric lifetime. In marine environments with chlorine emissions, N205 heterogeneous
reactions make one nitric acid and one CIN02. The CIN02 photolyzes during the daytime to form CI" and
N02. These marine environment processes can act as a nighttime NOx reservoir which would then
regenerate N02 on sunrise (McDuffie et al., 2018).

However, it is important to consider that the presence of chlorine speeds up the N205 hydrolysis
reaction (Equation 3) rate (Bertram and Thornton, 2009). Therefore, it is not clear how much N02 would
convert to HN03 rather than CIN02 in the presence of chlorine containing aerosol.

Photochemical modeling that incorporates the full suite of chemical reactions would be needed to fully
understand the implications of the various reactions and processes noted in this section. However,
important chemical and physical processes are included in the modeling system and the impacts
provided here are considered a reasonable representation of 03 and PM2 5 impacts from precursors for
the intended purpose of supporting permit program related demonstrations.

PRODUCTS

PM2.5 nitrate impacts were linked to secondary formation attributed to NOx emissions only and
therefore these outputs do not include the impacts from primarily emitted PM2 5 nitrate. PM2 5 sulfate
impacts were linked to secondary formation attributed to S02 emissions only and similarly do not
include the impacts from primarily emitted PM2 5 sulfate. PM2 5 ammonium impacts were linked to
secondary formation attributed to NH3 emissions only and do not include the impacts from primarily
emitted PM2 5 ammonium.

The modeled contributions from each source were processed to match metrics relevant for permit
program related demonstrations. PM2 5 impacts were estimated as annual average and annual maximum
daily average. 03 impacts were estimated as maximum daily average of 8-hr rolling averages for April
through October. The air quality impacts were then normalized by precursor emissions as a function of
distance bins from the hypothetical source to develop transfer coefficients. These transfer coefficients

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were intended to be paired with project specific emissions to develop an approximation of project
specific air quality impacts by distance. Since the modeling was done using 12 km sized grid cells, no
information is available for source impacts at distances less than the size of the grid cell.

The relationship between estimated project impacts, project emissions, and transfer coefficients is
shown in Equation 1.

Equation (1) Air quality impact = Project Emissions x Transfer Coefficient

Where the screening level air quality impact would have units ng/m3 for PM2.5 and ppb for MDA8 03
calculations. The project emissions should be expressed as tons per year. The transfer coefficients are
provided in for each precursor to secondary pollutant in Tables 4 to 15. The transfer coefficients are
expressed as (ng/m3)/tpy for PM2.5 and ppb/tpy for 03 calculations.

It is expected that the screening level air quality impacts would be compared to appropriate SIL and
increment values (U.S. Environmental Protection Agency, 2018, 2019b, 2021). These screening level air
quality impacts could also be used in combination with appropriate estimates of ambient air and nearby
sources as part of a cumulative demonstration comparison with NAAQS levels (U.S. Environmental
Protection Agency, 2018, 2019b, 2021). Offshore projects should select the values from the table for
areas that represent that particular project. If a new offshore project has a location that was not
included in this assessment the applicant should consult with the appropriate Regional Office to discuss
how this information might be used for that situation.

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Table 4. Transfer	coefficients (ppb/tpy) relating NOx	emissions	(tpy) with maximum MDA8 03 impacts

(ppb) at distance	bins downwind for each hypothetical source.

NOX to 03 coefficients (ppb/tpy) by distance from the source (km)

SOURCE LAT LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150	150 to 200 200 to 250	>250

1	38.674	-74.701	1.41E-04	1.27E-04	1.34E-04	1.23E-04	1.50E-04	1.23E-04	1.24E-04	9.53E-05

2	36.908	-75.349	2.33E-04	3.59E-04	3.35E-04	2.78E-04	2.08E-04	2.08E-04	1.76E-04	1.59E-04

3	41.154	-71.080	1.22E-04	7.17E-05	5.48E-05	6.02E-05	6.88E-05	6.94E-05	6.37E-05	6.02E-05

4	40.985	-71.045	1.37E-04	8.58E-05	7.19E-05	9.13E-05	1.01E-04	9.63E-05	8.56E-05	6.08E-05

5	38.347	-74.761	2.58E-04	2.59E-04	2.53E-04	1.90E-04	1.76E-04	1.50E-04	1.50E-04	1.21E-04

6	36.896	-75.522	1.36E-04	2.95E-04	2.42E-04	2.70E-04	1.84E-04	1.81E-04	1.69E-04	1.58E-04

7	39.122	-74.242	1.06E-04	5.92E-05	4.84E-05	1.07E-04	1.02E-04	9.75E-05	8.55E-05	8.64E-05

8	39.273	-74.093	1.40E-04	1.33E-04	7.85E-05	7.58E-05	9.84E-05	9.56E-05	7.87E-05	8.33E-05

9	40.969	-70.792	1.01E-04	5.50E-05	5.85E-05	6.76E-05	7.37E-05	6.90E-05	7.49E-05	5.32E-05

10	41.043	-70.482	1.20E-04	9.35E-05	6.09E-05	1.39E-04	1.26E-04	7.90E-05	7.17E-05	6.76E-05

11	41.269	-71.436	1.06E-04	1.47E-04	1.63E-04	1.48E-04	1.06E-04	8.62E-05	6.82E-05	4.34E-05

12	36.339	-75.127	2.75E-04	3.08E-04	3.92E-04	3.60E-04	3.46E-04	2.66E-04	1.72E-04	1.65E-04

13	40.295	-73.315	1.76E-04	2.07E-04	1.96E-04	1.67E-04	1.38E-04	8.70E-05	7.16E-05	5.63E-05

14	41.089	-71.133	1.26E-04	9.36E-05	5.75E-05	6.74E-05	7.56E-05	7.49E-05	6.24E-05	5.54E-05

15	38.565	-74.665	1.33E-04	5.51E-05	1.03E-04	1.24E-04	1.47E-04	1.43E-04	1.45E-04	1.10E-04

16	40.824	-70.523	9.69E-05	6.26E-05	5.54E-05	1.33E-04	1.40E-04	1.33E-04	1.21E-04	1.14E-04

17	40.747	-70.416	1.31E-04	7.77E-05	8.80E-05	1.76E-04	1.87E-04	1.78E-04	1.61E-04	1.35E-04

18	40.682	-70.228	1.31E-04	1.16E-04	1.65E-04	1.74E-04	1.91E-04	1.90E-04	1.85E-04	1.21E-04

19	39.065	-74.379	1.79E-04	1.27E-04	8.06E-05	9.92E-05	1.04E-04	9.45E-05	9.02E-05	8.90E-05

20	40.895	-70.658	1.19E-04	5.21E-05	3.29E-05	8.88E-05	9.59E-05	9.72E-05	9.88E-05	8.91E-05

21	39.976	-72.740	2.03E-04	2.22E-04	2.67E-04	3.29E-04	3.72E-04	1.82E-04	1.19E-04	1.12E-04

22	39.718	-73.170	1.49E-04	2.13E-04	2.80E-04	3.06E-04	2.55E-04	1.29E-04	1.26E-04	9.22E-05

23	39.541	-73.304	1.73E-04	2.73E-04	2.62E-04	2.72E-04	2.27E-04	1.27E-04	7.50E-05	6.88E-05

24	39.361	-73.579	1.07E-04	8.42E-05	7.95E-05	8.34E-05	1.08E-04	1.00E-04	9.74E-05	1.01E-04

25	39.304	-73.461	1.28E-04	9.98E-05	1.01E-04	1.07E-04	1.06E-04	9.26E-05	1.02E-04	9.65E-05

26	40.242	-73.079	1.06E-04	1.57E-04	1.58E-04	1.93E-04	1.33E-04	1.05E-04	7.08E-05	7.16E-05

27	39.472	-74.004	8.58E-05	8.05E-05	1.10E-04	1.37E-04	9.91E-05	9.27E-05	7.85E-05	8.22E-05

13

-------
Table 5. Transfer coefficients (ppb/tpy) relating VOC emissions (tpy) with maximum MDA8 03	impacts
(ppb) at distance bins downwind for each hypothetical source.

VOC to 03 coefficients (ppb/tpy) by distance from the source (km)

POL	SOURCE LAT	LONG	<15	15 to 30	30 to 50	50 to 100 100 to 150	150 to 200 200 to 250	>250

03V	1	38.674	-74.701	1.29E-02	4.94E-03	4.95E-03	2.18E-03	6.58E-04	4.99E-04	4.15E-04	3.27E-04

03V	2	36.908	-75.349	1.02E-02	7.43E-03	4.64E-03	2.48E-03	1.84E-03	9.99E-04	5.45E-04	3.66E-04

03V	3	41.154	-71.080	1.23E-02	7.19E-03	4.62E-03	1.51E-03	1.00E-03	6.60E-04	3.39E-04	2.54E-04

03V	4	40.985	-71.045	1.35E-02	7.24E-03	5.22E-03	1.47E-03	5.91E-04	4.19E-04	3.24E-04	2.99E-04

03V	5	38.347	-74.761	8.91E-03	5.05E-03	2.51E-03	1.83E-03	1.02E-03	5.39E-04	3.29E-04	3.07E-04

03V	6	36.896	-75.522	1.14E-02	6.79E-03	4.78E-03	2.34E-03	1.18E-03	6.96E-04	4.47E-04	3.28E-04

03V	7	39.122	-74.242	9.97E-03	4.79E-03	3.44E-03	2.06E-03	7.25E-04	5.03E-04	2.96E-04	2.78E-04

03V	8	39.273	-74.093	9.04E-03	4.68E-03	1.73E-03	1.55E-03	9.17E-04	5.20E-04	2.74E-04	2.56E-04

03V	9	40.969	-70.792	1.01E-02	5.53E-03	4.69E-03	3.02E-03	1.03E-03	5.47E-04	3.33E-04	3.06E-04

03V	10	41.043	-70.482	1.20E-02	9.23E-03	5.57E-03	4.19E-03	1.08E-03	5.34E-04	3.60E-04	3.15E-04

03V	11	41.269	-71.436	8.82E-03	1.00E-02	4.33E-03	2.90E-03	7.85E-04	4.95E-04	4.20E-04	2.04E-04

03V	12	36.339	-75.127	1.11E-02	9.49E-03	5.22E-03	3.66E-03	1.60E-03	1.03E-03	5.83E-04	4.09E-04

03V	13	40.295	-73.315	5.60E-03	3.18E-03	3.83E-03	1.77E-03	5.45E-04	4.93E-04	3.05E-04	2.47E-04

03V	14	41.089	-71.133	1.25E-02	9.01E-03	3.39E-03	2.26E-03	9.11E-04	5.24E-04	3.09E-04	2.76E-04

03V	15	38.565	-74.665	1.28E-02	4.73E-03	2.95E-03	1.84E-03	7.49E-04	5.11E-04	4.22E-04	3.33E-04

03V	16	40.824	-70.523	9.16E-03	5.78E-03	3.38E-03	2.28E-03	9.49E-04	5.49E-04	4.36E-04	4.43E-04

03V	17	40.747	-70.416	1.14E-02	5.97E-03	3.77E-03	2.73E-03	1.04E-03	7.27E-04	5.51E-04	5.08E-04

03V	18	40.682	-70.228	9.23E-03	6.48E-03	3.99E-03	3.97E-03	1.25E-03	7.51E-04	5.60E-04	4.95E-04

03V	19	39.065	-74.379	1.06E-02	4.22E-03	2.47E-03	1.59E-03	7.04E-04	5.13E-04	3.19E-04	2.90E-04

03V	20	40.895	-70.658	1.13E-02	3.63E-03	2.54E-03	1.68E-03	7.63E-04	3.94E-04	3.15E-04	3.29E-04

03V	21	39.976	-72.740	1.29E-02	6.25E-03	4.97E-03	3.59E-03	1.93E-03	5.98E-04	3.70E-04	2.87E-04

03V	22	39.718	-73.170	1.03E-02	4.87E-03	2.44E-03	1.65E-03	1.18E-03	5.22E-04	3.14E-04	2.30E-04

03V	23	39.541	-73.304	1.25E-02 5.32E-03	2.05E-03	1.58E-03	1.48E-03	5.12E-04	3.74E-04	2.88E-04

03V	24	39.361	-73.579	7.04E-03 4.99E-03	2.62E-03	1.67E-03	1.40E-03	9.81E-04	3.30E-04	2.23E-04

03V	25	39.304	-73.461	8.65E-03 5.90E-03	3.00E-03	2.23E-03	1.59E-03	1.10E-03	3.72E-04	2.60E-04

03V	26	40.242	-73.079	6.43E-03 4.48E-03	2.64E-03	1.55E-03	8.07E-04	4.02E-04	2.40E-04	2.17E-04

03V	27	39.472	-74.004	8.58E-03 5.29E-03	2.62E-03	1.89E-03	7.56E-04	5.77E-04	3.85E-04	2.00E-04

14

-------
Table 6.	Transfer coefficients ((ng/m3)*tpy)	relating S02 emissions (tpy) with annual maximum daily

average	PM2.5 impacts (ng/m3) at distance bins downwind for each hypothetical source.

S02 to PM25 coefficients ((ng/m3)/tpy) by distance from the source (km)

SOURCE	LAT	LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150	150 to 200 200 to 250	>250

1	38.674	-74.701	8.67E-05	7.16E-05	5.04E-05	2.83E-05	1.24E-05	1.19E-05	1.19E-05	1.10E-05

2	36.908	-75.349	1.08E-04 7.24E-05	6.10E-05	5.01E-05	3.82E-05	2.63E-05	1.92E-05	1.53E-05

3	41.154	-71.08	4.06E-05	2.15E-05	1.84E-05	1.43E-05	1.24E-05	1.00E-05	9.32E-06	8.76E-06

4	40.985	-71.045	8.74E-06	8.64E-06	1.05E-05	2.26E-05	2.16E-05	1.51E-05	9.16E-06	8.26E-06

5	38.347	-74.761	1.74E-04 1.07E-04	7.74E-05	4.96E-05	3.44E-05	2.45E-05	1.97E-05	1.58E-05

6	36.896	-75.522	9.34E-05	1.01E-04	9.46E-05	9.48E-05	6.58E-05	4.29E-05	3.16E-05	2.50E-05

7	39.122	-74.242	2.71E-05	2.78E-05	2.17E-05	2.17E-05	1.96E-05	1.32E-05	1.13E-05	1.04E-05

8	39.273	-74.093	1.97E-05	2.14E-05	2.89E-05	3.76E-05	2.33E-05	1.41E-05	1.09E-05	9.82E-06

9	40.969	-70.792	1.80E-05	1.90E-05	3.29E-05	4.18E-05	2.59E-05	1.54E-05	9.48E-06	8.97E-06

10	41.043	-70.482	1.96E-04 1.78E-04	1.34E-04	1.13E-04	4.46E-05	1.88E-05	1.31E-05	9.90E-06

11	41.269	-71.436	2.75E-05	3.08E-05	3.36E-05	3.13E-05	1.68E-05	1.35E-05	9.14E-06	7.81E-06

12	36.339	-75.127	1.69E-04 2.03E-04	1.44E-04	1.16E-04	5.91E-05	3.97E-05	2.81E-05	2.26E-05

13	40.295	-73.315	2.28E-05	2.16E-05	3.61E-05	5.98E-05	3.65E-05	3.11E-05	1.21E-05	9.26E-06

14	41.089	-71.133	1.41E-05	1.26E-05	1.07E-05	1.98E-05	1.96E-05	1.17E-05	8.18E-06	8.04E-06

15	38.565	-74.665	8.50E-05	4.92E-05	4.60E-05	4.10E-05	2.14E-05	1.88E-05	1.38E-05	1.24E-05

16	40.824	-70.523	4.13E-05	3.57E-05	4.79E-05	4.96E-05	3.89E-05	2.44E-05	1.04E-05	9.82E-06

17	40.747	-70.416	2.49E-05	2.00E-05	3.14E-05	2.63E-05	2.30E-05	1.75E-05	1.15E-05	8.99E-06

18	40.682	-70.228	5.57E-05	3.66E-05	3.84E-05	3.50E-05	3.36E-05	2.43E-05	1.23E-05	8.91E-06

19	39.065	-74.379	2.96E-05	3.43E-05	2.84E-05	2.12E-05	2.11E-05	1.46E-05	1.22E-05	1.01E-05

20	40.895	-70.658	1.78E-05	2.72E-05	3.93E-05	4.51E-05	3.56E-05	2.31E-05	1.03E-05	8.94E-06

21	39.976	-72.74	7.07E-06	1.13E-05	1.08E-05	1.48E-05	1.51E-05	1.47E-05	1.33E-05	1.07E-05

22	39.718	-73.17	3.90E-05	3.65E-05	2.73E-05	2.93E-05	2.95E-05	1.78E-05	1.30E-05	9.15E-06

23	39.541	-73.304	4.48E-05	5.60E-05	4.30E-05	3.43E-05	1.98E-05	1.52E-05	1.26E-05	9.27E-06

24	39.361	-73.579	2.07E-05	2.30E-05	3.62E-05	3.14E-05	1.93E-05	1.69E-05	1.31E-05	9.65E-06

25	39.304	-73.461	1.77E-05	2.68E-05	4.11E-05	3.64E-05	1.97E-05	1.70E-05	1.31E-05	9.71E-06

26	40.242	-73.079	2.36E-05	2.19E-05	2.07E-05	4.83E-05	4.07E-05	2.44E-05	1.47E-05	9.05E-06

27	39.472	-74.004	1.93E-05	4.87E-05	5.13E-05	4.74E-05	3.31E-05	1.62E-05	1.12E-05	9.34E-06

15

-------
Table 7. Transfer coefficients ((ng/m3)*tpy) relating NOx emissions (tpy) with annual maximum daily

average PM2.5 impacts	(ng/m3) at distance bins downwind for each hypothetical source.

NOX to PM25 coefficients ((|ig/m3)/tpy) by distance from the source (km)

SOURCE LAT	LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150	150 to 200	200 to 250	>250

1	38.674	-74.7	4.25E-05	3.36E-05	2.52E-05	3.06E-05	3.07E-05	2.90E-05	1.51E-05	1.45E-05

2	36.908	-75.35	1.35E-05	1.72E-05	1.95E-05	2.91E-05	2.79E-05	2.90E-05	2.08E-05	2.23E-05

3	41.154	-71.08	2.08E-05	1.45E-05	1.24E-05	1.79E-05	1.51E-05	1.29E-05	1.05E-05	7.26E-06

4	40.985	-71.04	1.64E-05	1.69E-05	1.59E-05	1.43E-05	1.44E-05	1.10E-05	9.89E-06	6.39E-06

5	38.347	-74.76	2.76E-05	2.85E-05	4.36E-05	6.13E-05	2.99E-05	1.38E-05	1.28E-05	1.19E-05

6	36.896	-75.52	2.25E-05	2.46E-05	3.25E-05	3.30E-05	2.98E-05	2.46E-05	1.95E-05	1.97E-05

7	39.122	-74.24	2.96E-05	3.18E-05	4.64E-05	4.86E-05	8.41E-05	3.15E-05	1.57E-05	1.28E-05

8	39.273	-74.09	1.47E-05	2.72E-05	4.82E-05	4.09E-05	8.47E-05	2.14E-05	1.43E-05	1.17E-05

9	40.969	-70.79	1.74E-05	1.72E-05	1.57E-05	1.33E-05	1.30E-05	1.18E-05	1.05E-05	6.12E-06

10	41.043	-70.48	1.15E-05	7.39E-06	7.29E-06	1.49E-05	1.50E-05	1.39E-05	1.06E-05	5.75E-06

11	41.269	-71.44	4.85E-05	4.70E-05	3.46E-05	2.75E-05	1.48E-05	1.15E-05	8.84E-06	5.97E-06

12	36.339	-75.13	2.62E-05	2.29E-05	1.90E-05	2.43E-05	2.03E-05	2.39E-05	2.05E-05	1.75E-05

13	40.295	-73.32	1.46E-05	1.31E-05	2.46E-05	5.65E-05	3.89E-05	2.02E-05	1.65E-05	1.19E-05

14	41.089	-71.13	1.75E-05	1.59E-05	1.39E-05	1.66E-05	1.46E-05	1.16E-05	9.60E-06	6.38E-06

15	38.565	-74.67	2.74E-05	2.49E-05	2.59E-05	3.00E-05	2.54E-05	2.25E-05	1.14E-05	1.22E-05

16	40.824	-70.52	7.57E-06	6.67E-06	7.34E-06	9.42E-06	1.40E-05	1.24E-05	1.08E-05	5.98E-06

17	40.747	-70.42	7.19E-06	5.85E-06	7.67E-06	8.80E-06	1.29E-05	1.17E-05	9.83E-06	5.81E-06

18	40.682	-70.23	7.55E-06	6.34E-06	5.81E-06	7.04E-06	1.21E-05	1.11E-05	8.71E-06	5.77E-06

19	39.065	-74.38	3.94E-05	3.43E-05	3.90E-05	3.92E-05	7.36E-05	2.65E-05	1.52E-05	1.24E-05

20	40.895	-70.66	7.00E-06	7.54E-06	8.39E-06	1.36E-05	1.33E-05	1.13E-05	9.61E-06	5.32E-06

21	39.976	-72.74	1.49E-05	1.44E-05	1.37E-05	9.91E-06	1.98E-05	2.09E-05	1.48E-05	8.81E-06

22	39.718	-73.17	1.25E-05	1.00E-05	7.49E-06	5.06E-05	4.05E-05	3.13E-05	1.87E-05	1.19E-05

23	39.541	-73.3	9.84E-06	8.65E-06	6.92E-06	3.21E-05	3.24E-05	2.46E-05	1.52E-05	1.27E-05

24	39.361	-73.58	5.39E-06	7.32E-06	1.00E-05	2.81E-05	3.31E-05	2.44E-05	1.23E-05	1.35E-05

25	39.304	-73.46	5.85E-06	8.13E-06	8.08E-06	2.83E-05	3.28E-05	3.13E-05	1.48E-05	1.36E-05

26	40.242	-73.08	1.27E-05	1.15E-05	9.44E-06	3.96E-05	3.22E-05	2.14E-05	1.39E-05	9.03E-06

27	39.472 -74	1.72E-05	2.70E-05	2.90E-05	6.21E-05	8.04E-05	2.34E-05	1.37E-05	1.03E-05

16

-------
Table 8. Transfer coefficients ((ng/m3)*tpy) relating NH3 emissions (tpy) with annual maximum daily

average PM2.5 impacts (ng/m3) at distance bins downwind for	each hypothetical source.

NH3 to PM25	coefficients ((Mg/m3)/tpy) by distance from the source (km)

SOURCE LAT	LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150	150 to 200 200 to 250	>250

1	38.674	-74.701	7.16E-03	4.19E-03	2.43E-03	9.74E-04	2.62E-04	1.01E-04	5.14E-05	2.50E-05

2	36.908	-75.349	1.05E-02	2.60E-03	1.06E-03	4.43E-04	1.64E-04	9.40E-05	6.14E-05	4.65E-05

3	41.154	-71.08	2.79E-03	6.36E-04	2.86E-04	1.68E-04	9.22E-05	5.80E-05	3.54E-05	2.20E-05

4	40.985	-71.045	2.45E-03	6.00E-04	3.09E-04	1.86E-04	1.16E-04	7.55E-05	4.59E-05	2.85E-05

5	38.347	-74.761	6.06E-03	2.91E-03	1.71E-03	7.80E-04	2.75E-04	1.21E-04	7.93E-05	4.65E-05

6	36.896	-75.522	1.36E-02	4.05E-03	1.70E-03	6.36E-04	2.80E-04	1.76E-04	1.18E-04	8.66E-05

7	39.122	-74.242	6.49E-03	3.36E-03	1.73E-03	5.43E-04	1.79E-04	7.52E-05	3.44E-05	2.67E-05

8	39.273	-74.093	6.51E-03	3.00E-03	8.34E-04	5.41E-04	1.27E-04	6.22E-05	3.21E-05	2.36E-05

9	40.969	-70.792	2.65E-03	7.16E-04	2.91E-04	2.15E-04	1.05E-04	6.67E-05	3.96E-05	2.41E-05

10	41.043	-70.482	4.45E-03	1.50E-03	4.64E-04	3.15E-04	8.05E-05	5.39E-05	3.38E-05	2.10E-05

11	41.269	-71.436	3.23E-03	7.21E-04	3.77E-04	2.84E-04	1.12E-04	5.58E-05	4.00E-05	3.08E-05

12	36.339	-75.127	7.95E-03	1.75E-03	5.22E-04	3.49E-04	1.11E-04	5.56E-05	3.92E-05	3.04E-05

13	40.295	-73.315	2.91E-03	9.17E-04	4.28E-04	1.57E-04	9.03E-05	5.06E-05	3.78E-05	2.98E-05

14	41.089	-71.133	2.40E-03	6.08E-04	3.21E-04	1.89E-04	1.06E-04	6.80E-05	4.11E-05	2.56E-05

15	38.565	-74.665	5.47E-03	2.96E-03	1.67E-03	7.39E-04	2.31E-04	1.08E-04	6.05E-05	3.06E-05

16	40.824	-70.523	3.46E-03	1.07E-03	5.34E-04	2.45E-04	1.06E-04	6.79E-05	4.12E-05	2.44E-05

17	40.747	-70.416	3.06E-03	9.49E-04	5.97E-04	2.34E-04	1.14E-04	7.99E-05	4.81E-05	2.80E-05

18	40.682	-70.228	3.02E-03	1.40E-03	5.80E-04	3.11E-04	1.10E-04	7.36E-05	4.53E-05	2.50E-05

19	39.065	-74.379	6.62E-03	3.12E-03	1.68E-03	5.90E-04	1.33E-04	5.84E-05	3.09E-05	2.46E-05

20	40.895	-70.658	2.65E-03	7.99E-04	4.73E-04	2.26E-04	1.11E-04	7.35E-05	4.31E-05	2.55E-05

21	39.976	-72.74	2.37E-03	6.42E-04	2.87E-04	1.52E-04	8.21E-05	5.02E-05	3.24E-05	2.44E-05

22	39.718	-73.17	4.09E-03	9.52E-04	4.40E-04	2.33E-04	1.24E-04	5.43E-05	3.64E-05	2.27E-05

23	39.541	-73.304	5.69E-03	1.40E-03	4.81E-04	1.99E-04	1.20E-04	5.28E-05	3.59E-05	2.38E-05

24	39.361	-73.579	4.40E-03	1.69E-03	6.83E-04	2.10E-04	1.09E-04	5.07E-05	3.34E-05	2.18E-05

25	39.304	-73.461	4.36E-03	1.77E-03	7.45E-04	2.14E-04	1.35E-04	5.17E-05	3.33E-05	2.13E-05

26	40.242	-73.079	2.94E-03	7.00E-04	2.99E-04	1.62E-04	7.51E-05	4.99E-05	3.23E-05	2.53E-05

27	39.472	-74.004	7.73E-03	3.31E-03	9.21E-04	5.39E-04	1.35E-04	7.61E-05	3.47E-05	2.35E-05

17

-------
Table 9. Transfer coefficients ((ng/m3)*tpy) relating primary PM2.5 emissions (tpy) with annual
maximum daily average PM2.5 impacts (ng/m3) at distance bins downwind for each hypothetical
source.

Primary PM25 coefficients ((|ig/m3)/tpy) by distance from the source (km)

IURCE

LAT

LONG < 15

15 to 30 30 to 50 50 to 100

100 to 150

150 to 200

200 to 250

>250

1

38.674

-74.701

1.02E-03

2.52E-04

9.80E-05

5.99E-05

3.44E-05

2

36.908

-75.349

5.65E-04

2.15E-04

1.23E-04

8.02E-05

6.34E-05

3

41.154

-71.08

2.23E-04

1.19E-04

7.28E-05

4.59E-05

3.02E-05

4

40.985

-71.045

2.39E-04

1.33E-04

8.48E-05

5.29E-05

3.35E-05

5

38.347

-74.761

8.37E-04

2.79E-04

1.26E-04

8.37E-05

5.21E-05

6

36.896

-75.522

6.88E-04

2.89E-04

1.68E-04

1.18E-04

9.02E-05

7

39.122

-74.242

6.27E-04

1.72E-04

8.37E-05

4.55E-05

3.20E-05

8

39.273

-74.093

5.93E-04

1.70E-04

7.16E-05

4.07E-05

2.80E-05

9

40.969

-70.792

2.33E-04

1.25E-04

7.94E-05

4.74E-05

2.81E-05

10

41.043

-70.482

3.07E-04

1.00E-04

6.87E-05

4.41E-05

2.49E-05

11

41.269

-71.436

3.45E-04

1.47E-04

6.00E-05

4.39E-05

4.28E-05

12

36.339

-75.127

4.48E-04

1.67E-04

1.03E-04

7.61E-05

5.59E-05

13

40.295

-73.315

2.29E-04

1.14E-04

5.47E-05

4.29E-05

2.92E-05

14

41.089

-71.133

2.38E-04

1.25E-04

7.67E-05

4.62E-05

2.92E-05

15

38.565

-74.665

7.89E-04

2.39E-04

1.03E-04

6.40E-05

3.90E-05

16

40.824

-70.523

2.75E-04

1.32E-04

8.61E-05

5.28E-05

2.99E-05

17

40.747

-70.416

2.85E-04

1.38E-04

1.03E-04

6.16E-05

3.42E-05

18

40.682

-70.228

2.94E-04

1.22E-04

9.23E-05

5.76E-05

3.08E-05

19

39.065

-74.379

6.36E-04

1.55E-04

8.88E-05

4.58E-05

3.43E-05

20

40.895

-70.658

2.71E-04

1.36E-04

8.97E-05

5.36E-05

3.04E-05

21

39.976

-72.74

2.20E-04

1.13E-04

6.95E-05

5.29E-05

3.51E-05

22

39.718

-73.17

2.61E-04

1.46E-04

7.12E-05

5.13E-05

3.14E-05

23

39.541

-73.304

2.91E-04

1.68E-04

8.40E-05

5.35E-05

3.27E-05

24

39.361

-73.579

2.91E-04

1.36E-04

7.64E-05

4.74E-05

2.77E-05

25

39.304

-73.461

3.59E-04

1.76E-04

6.86E-05

4.74E-05

3.02E-05

26

40.242

-73.079

2.35E-04

9.33E-05

5.38E-05

3.60E-05

2.97E-05

27

39.472

-74.004

4.67E-04

1.71E-04

7.80E-05

4.14E-05

2.82E-05

18

-------
Table 10. Transfer coefficients ((ng/m3)*tpy) relating primary coarse PM emissions (tpy) with annual
maximum daily average coarse PM impacts (ng/m3) at distance bins downwind for each hypothetical
source.

Primary Coarse PM coefficients ((ng/m3)/tpy) by distance from the source (km)

< 15 15 to 30 30 to 50 50 to 100 100 to 150	150 to 200 200 to 250	> 250

5.37E-04	1.27E-04	6.12E-05	3.70E-05	2.63E-05

3.93E-04	1.67E-04	9.39E-05	5.49E-05	3.48E-05

1.92E-04	9.64E-05	5.76E-05	3.69E-05	2.68E-05

2.12E-04	1.18E-04	7.29E-05	4.28E-05	2.64E-05

5.28E-04	1.68E-04	7.20E-05	4.30E-05	3.43E-05

4.29E-04	1.52E-04	8.53E-05	5.21E-05	3.77E-05

3.13E-04	1.34E-04	6.68E-05	3.87E-05	2.74E-05

3.44E-04	1.24E-04	6.08E-05	3.60E-05	2.44E-05

1.77E-04	1.04E-04	6.43E-05	3.70E-05	2.46E-05

1.81E-04	7.85E-05	5.27E-05	3.32E-05	2.16E-05

2.98E-04	1.21E-04	5.26E-05	3.73E-05	3.36E-05

3.32E-04	1.39E-04	7.09E-05	4.37E-05	2.97E-05

1.73E-04	8.28E-05	4.64E-05	3.28E-05	2.47E-05

2.15E-04	1.10E-04	6.57E-05	3.84E-05	2.61E-05

4.64E-04	1.46E-04	6.51E-05	3.86E-05	2.86E-05

2.15E-04	1.15E-04	6.61E-05	4.02E-05	2.48E-05

2.24E-04	1.20E-04	7.85E-05	4.73E-05	2.76E-05

1.98E-04	1.10E-04	7.27E-05	4.50E-05	2.45E-05

3.89E-04	1.29E-04	7.14E-05	3.89E-05	2.95E-05

1.97E-04	1.12E-04	7.14E-05	4.10E-05	2.47E-05

1.60E-04	8.13E-05	5.16E-05	3.59E-05	2.73E-05

2.10E-04	8.90E-05	5.29E-05	3.57E-05	2.52E-05

2.26E-04	8.66E-05	6.11E-05	3.75E-05	2.22E-05

2.75E-04	1.03E-04	5.86E-05	3.51E-05	2.51E-05

2.75E-04	9.70E-05	5.15E-05	3.50E-05	2.52E-05

1.79E-04	7.60E-05	4.71E-05	3.29E-05	2.78E-05

2.80E-04	1.18E-04	5.82E-05	3.86E-05	2.63E-05

SOURCE

LAT

LONG

1

38.674

-74.701

2

36.908

-75.349

3

41.154

-71.08

4

40.985

-71.045

5

38.347

-74.761

6

36.896

-75.522

7

39.122

-74.242

8

39.273

-74.093

9

40.969

-70.792

10

41.043

-70.482

11

41.269

-71.436

12

36.339

-75.127

13

40.295

-73.315

14

41.089

-71.133

15

38.565

-74.665

16

40.824

-70.523

17

40.747

-70.416

18

40.682

-70.228

19

39.065

-74.379

20

40.895

-70.658

21

39.976

-72.74

22

39.718

-73.17

23

39.541

-73.304

24

39.361

-73.579

25

39.304

-73.461

26

40.242

-73.079

27

39.472

-74.004

19

-------
Table 11. Transfer coefficients ((ng/m3)*tpy) relating S02 emissions (tpy) with annual average PM2.5
impacts (ng/m3) at distance bins downwind for each hypothetical source.

S02 to PM25 coefficients ((|ig/m3)/tpy) by distance from the source (km)

SOURCE LAT LONG	< 15	15 to 30	30 to 50	50 to 100	100 to 150	150 to 200 200 to 250	> 250

1	38.674	-74.701	7.01E-06	5.22E-06 3.86E-06 2.37E-06	1.24E-06	9.92E-07	8.10E-07	7.36E-07

2	36.908	-75.349	5.03E-06	2.96E-06 2.35E-06 1.93E-06	1.53E-06	1.11E-06	9.84E-07	8.31E-07

3	41.154	-71.08	2.34E-06	1.63E-06	1.37E-06 1.20E-06	1.16E-06	1.04E-06	1.01E-06	6.57E-07

4	40.985	-71.045	1.14E-06	9.50E-07	9.18E-07	1.18E-06	1.15E-06	1.07E-06	1.04E-06	6.98E-07

5	38.347	-74.761	1.10E-05	8.06E-06	5.89E-06 3.78E-06	2.17E-06	1.40E-06	1.09E-06	7.75E-07

6	36.896	-75.522	4.78E-06	4.02E-06	3.64E-06 3.63E-06	2.82E-06	2.16E-06	1.68E-06	1.28E-06

7	39.122	-74.242	3.61E-06	2.87E-06	2.34E-06 1.94E-06	1.59E-06	9.98E-07	7.70E-07	6.62E-07

8	39.273	-74.093	3.28E-06	2.84E-06	2.44E-06 2.46E-06	1.50E-06	8.94E-07	7.40E-07	5.79E-07

9	40.969	-70.792	1.44E-06	1.14E-06	1.60E-06 1.94E-06	1.51E-06	1.21E-06	9.88E-07	6.48E-07

10	41.043	-70.482	7.16E-06	6.68E-06	5.18E-06 4.53E-06	2.06E-06	1.31E-06	8.43E-07	6.88E-07

11	41.269	-71.436	2.83E-06	2.22E-06	1.80E-06 1.65E-06	1.04E-06	7.07E-07	6.24E-07	6.02E-07

12	36.339	-75.127	7.36E-06	7.27E-06	4.97E-06 4.00E-06	2.08E-06	1.42E-06	1.00E-06	8.16E-07

13	40.295	-73.315	2.30E-06	1.86E-06	1.81E-06 2.87E-06	1.93E-06	1.32E-06	1.02E-06	7.93E-07

14	41.089	-71.133	1.41E-06	1.20E-06	1.09E-06 1.25E-06	1.24E-06	1.02E-06	1.00E-06	6.63E-07

15	38.565	-74.665	7.39E-06	5.68E-06	4.55E-06	3.24E-06	1.69E-06	1.28E-06	9.21E-07	7.00E-07

16	40.824	-70.523	2.01E-06	1.68E-06	2.06E-06	1.97E-06	1.42E-06	1.28E-06	7.87E-07	6.56E-07

17	40.747	-70.416	1.76E-06	1.29E-06	1.58E-06	1.43E-06	1.24E-06	1.09E-06	8.54E-07	6.69E-07

18	40.682	-70.228	3.74E-06	1.99E-06	1.87E-06	1.24E-06	1.25E-06	1.18E-06	8.64E-07	6.51E-07

19	39.065	-74.379	3.72E-06	3.35E-06	2.70E-06	2.01E-06	1.64E-06	1.09E-06	7.88E-07	6.67E-07

20	40.895	-70.658	1.15E-06	1.12E-06	1.62E-06	1.79E-06	1.38E-06	1.30E-06	8.86E-07	6.32E-07

21	39.976	-72.74	1.10E-06	9.65E-07	1.08E-06	1.12E-06	1.15E-06	1.16E-06	1.11E-06	9.33E-07

22	39.718	-73.17	2.37E-06	1.78E-06	1.33E-06	1.60E-06	1.67E-06	9.77E-07	7.70E-07	5.90E-07

23	39.541	-73.304	2.59E-06	2.41E-06	1.74E-06	1.42E-06	1.28E-06	9.26E-07	7.34E-07	5.85E-07

24	39.361	-73.579	2.08E-06	1.83E-06	1.90E-06	1.48E-06	1.25E-06	8.76E-07	6.83E-07	5.43E-07

25	39.304	-73.461	2.14E-06	1.95E-06	2.07E-06	1.66E-06	1.25E-06	9.33E-07	6.86E-07	5.29E-07

26	40.242	-73.079	2.29E-06	1.86E-06	1.65E-06	2.32E-06	2.27E-06	1.13E-06	7.93E-07	6.21E-07

27	39.472	-74.004	3.19E-06	3.47E-06	3.33E-06	3.02E-06	1.60E-06	9.95E-07	7.62E-07	6.22E-07

20

-------
Table 12. Transfer coefficients ((ng/m3)*tpy) relating NOx emissions (tpy) with annual average PM2.5

impacts (ng/m3)	at distance bins downwind for each hypothetical source.

NOX to PM25 coefficients ((|ig/m3)/tpy) by distance from the source (km)

SOURCE LAT	LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150 150 to 200	200 to 250	>250

1	38.674	-74.701	4.99E-06	4.08E-06	4.03E-06	3.44E-06	2.78E-06	2.40E-06	1.66E-06	1.18E-06

2	36.908	-75.349	3.26E-06	2.87E-06	2.54E-06	2.17E-06	1.93E-06	2.38E-06	2.33E-06	2.35E-06

3	41.154	-71.08	3.53E-06	2.09E-06	1.43E-06	1.00E-06	7.46E-07	6.44E-07	5.44E-07	4.04E-07

4	40.985	-71.045	2.17E-06	1.52E-06	1.29E-06	9.66E-07	7.48E-07	5.70E-07	4.91E-07	3.40E-07

5	38.347	-74.761	3.90E-06	3.17E-06	2.94E-06	3.66E-06	2.17E-06	1.53E-06	1.54E-06	1.13E-06

6	36.896	-75.522	4.29E-06	3.61E-06	3.56E-06	3.06E-06	2.50E-06	2.68E-06	2.88E-06	2.85E-06

7	39.122	-74.242	3.96E-06	3.07E-06	4.07E-06	4.19E-06	4.76E-06	2.28E-06	1.83E-06	1.09E-06

8	39.273	-74.093	3.00E-06	2.28E-06	4.45E-06	3.58E-06	4.93E-06	2.02E-06	1.66E-06	9.82E-07

9	40.969	-70.792	2.33E-06	1.38E-06	1.18E-06	8.73E-07	7.47E-07	6.04E-07	5.00E-07	3.31E-07

10	41.043	-70.482	2.25E-06	1.42E-06	1.08E-06	1.01E-06	7.94E-07	6.83E-07	4.72E-07	2.44E-07

11	41.269	-71.436	6.07E-06	4.09E-06	2.68E-06	1.65E-06	1.07E-06	6.99E-07	5.16E-07	3.91E-07

12	36.339	-75.127	3.91E-06	3.26E-06	2.48E-06	1.77E-06	2.03E-06	2.05E-06	1.78E-06	1.67E-06

13	40.295	-73.315	3.11E-06	2.25E-06	2.02E-06	3.74E-06	2.97E-06	2.27E-06	1.40E-06	9.58E-07

14	41.089	-71.133	2.80E-06	1.83E-06	1.52E-06	1.00E-06	7.28E-07	5.95E-07	5.24E-07	3.60E-07

15	38.565	-74.665	3.54E-06	2.98E-06	2.51E-06	2.42E-06	2.27E-06	1.80E-06	1.39E-06	1.10E-06

16	40.824	-70.523	1.45E-06	9.60E-07	8.24E-07	8.00E-07	7.24E-07	6.23E-07	4.82E-07	2.85E-07

17	40.747	-70.416	1.39E-06	1.01E-06	8.07E-07	7.90E-07	6.67E-07	6.08E-07	4.50E-07	2.49E-07

18	40.682	-70.228	1.29E-06	9.47E-07	9.00E-07	8.03E-07	6.67E-07	6.16E-07	4.44E-07	2.64E-07

19	39.065	-74.379	4.23E-06	3.09E-06	3.38E-06	3.58E-06	4.11E-06	1.95E-06	1.63E-06	9.23E-07

20	40.895	-70.658	1.60E-06	1.10E-06	9.45E-07	7.88E-07	7.24E-07	5.96E-07	4.51E-07	2.92E-07

21	39.976	-72.74	1.89E-06	1.45E-06	1.18E-06	8.67E-07	1.65E-06	1.32E-06	1.06E-06	5.84E-07

22	39.718	-73.17	2.21E-06	1.25E-06	1.09E-06	3.46E-06	3.05E-06	2.53E-06	1.29E-06	1.08E-06

23	39.541	-73.304	1.93E-06	1.37E-06	1.12E-06	2.53E-06	2.34E-06	2.26E-06	1.03E-06	9.42E-07

24	39.361	-73.579	1.60E-06	1.12E-06	9.57E-07	2.25E-06	2.40E-06	2.12E-06	1.02E-06	8.62E-07

25	39.304	-73.461	1.66E-06	1.14E-06	8.54E-07	2.28E-06	2.32E-06	2.39E-06	1.03E-06	9.54E-07

26	40.242	-73.079	2.47E-06	1.77E-06	1.41E-06	3.02E-06	2.96E-06	2.15E-06	1.27E-06	8.03E-07

27	39.472	-74.004	3.46E-06	3.05E-06	3.55E-06	4.38E-06	5.35E-06	2.32E-06	1.85E-06	8.95E-07

21

-------
Table 13. Transfer coefficients ((ng/m3)*tpy) relating NH3 emissions (tpy) with annual average PM2.5

impacts	(ng/m3)	at distance bins downwind for each	hypothetical source.

NH3 to PM25	coefficients ((ng/m3)/tpy) by distance from the source (km)

SOURCE	LAT	LONG	<15	15 to 30	30 to 50	50 to 100	100 to 150 150 to 200	200 to 250	>250

1	38.674	-74.701	2.00E-03	5.08E-04	2.46E-04	9.43E-05	2.33E-05	1.03E-05	5.32E-06	3.49E-06

2	36.908	-75.349	1.75E-03	3.77E-04	1.49E-04	5.04E-05	1.36E-05	7.12E-06	4.47E-06	3.16E-06

3	41.154	-71.08	1.24E-03	2.88E-04	1.06E-04	3.91E-05	1.60E-05	9.57E-06	5.16E-06	2.00E-06

4	40.985	-71.045	1.18E-03	2.75E-04	1.03E-04	3.96E-05	1.63E-05	8.90E-06	3.92E-06	2.09E-06

5	38.347	-74.761	1.80E-03	4.13E-04	1.87E-04	7.26E-05	2.39E-05	1.18E-05	6.46E-06	3.61E-06

6	36.896	-75.522	2.00E-03	4.24E-04	1.81E-04	6.84E-05	2.27E-05	1.17E-05	7.08E-06	4.70E-06

7	39.122	-74.242	2.01E-03	4.71E-04	2.05E-04	6.49E-05	1.63E-05	7.70E-06	5.17E-06	3.80E-06

8	39.273	-74.093	1.85E-03	4.16E-04	9.38E-05	5.79E-05	1.37E-05	7.89E-06	5.30E-06	3.86E-06

9	40.969	-70.792	1.20E-03	2.83E-04	6.30E-05	4.37E-05	1.49E-05	8.01E-06	3.26E-06	1.94E-06

10	41.043	-70.482	1.29E-03	3.15E-04	7.46E-05	5.18E-05	1.61E-05	6.92E-06	2.71E-06	1.88E-06

11	41.269	-71.436	1.39E-03	3.20E-04	6.68E-05	4.38E-05	1.35E-05	8.39E-06	5.84E-06	2.41E-06

12	36.339	-75.127	1.69E-03	2.85E-04	7.18E-05	3.26E-05	1.18E-05	5.73E-06	3.74E-06	2.30E-06

13	40.295	-73.315	1.38E-03	3.07E-04	6.79E-05	4.59E-05	1.75E-05	8.56E-06	5.32E-06	3.80E-06

14	41.089	-71.133	1.21E-03	2.85E-04	1.07E-04	4.09E-05	1.63E-05	9.35E-06	5.50E-06	1.95E-06

15	38.565	-74.665	1.78E-03	4.17E-04	1.91E-04	7.48E-05	2.30E-05	1.08E-05	5.40E-06	3.25E-06

16	40.824	-70.523	1.23E-03	2.92E-04	1.15E-04	4.76E-05	1.74E-05	6.40E-06	3.08E-06	2.11E-06

17	40.747	-70.416	1.23E-03	2.91E-04	1.20E-04	4.73E-05	1.63E-05	6.20E-06	3.57E-06	2.27E-06

18	40.682	-70.228	1.23E-03	2.99E-04	1.18E-04	4.60E-05	1.53E-05	6.24E-06	3.51E-06	2.18E-06

19	39.065	-74.379	1.88E-03	4.35E-04	1.96E-04	6.95E-05	1.78E-05	8.28E-06	5.42E-06	3.93E-06

20	40.895	-70.658	1.17E-03	2.76E-04	1.09E-04	4.51E-05	1.72E-05	7.86E-06	3.08E-06	2.10E-06

21	39.976	-72.74	1.15E-03	2.70E-04	1.02E-04	3.98E-05	1.57E-05	8.65E-06	5.46E-06	3.60E-06

22	39.718	-73.17	1.39E-03	1.77E-04	6.66E-05	3.23E-05	1.32E-05	7.26E-06	4.66E-06	3.38E-06

23	39.541	-73.304	1.44E-03 3.08E-04	1.12E-04	4.20E-05	1.57E-05	8.42E-06	4.91E-06	3.56E-06

24	39.361	-73.579	1.34E-03 2.93E-04	1.07E-04	4.00E-05	1.51E-05	8.29E-06	5.36E-06	3.83E-06

25	39.304	-73.461	1.34E-03 2.95E-04	7.84E-05	2.97E-05	1.30E-05	7.55E-06	5.03E-06	3.67E-06

26	40.242	-73.079	1.27E-03 2.86E-04	1.07E-04	4.24E-05	1.64E-05	8.95E-06	5.70E-06	3.90E-06

27	39.472	-74.004 2.04E-03 4.51E-04	9.49E-05	5.68E-05	1.38E-05	7.85E-06	5.17E-06	3.70E-06

22

-------
Table 14. Transfer coefficients ((ng/m3)*tpy) relating primary PM2.5 emissions (tpy) with annual
average PM2.5 impacts (ng/m3) at distance bins downwind for each hypothetical source.

Primary PM25 coefficients ((|ig/m3)/tpy) by distance from the source (km)

SOURCE

LAT

LONG < 15

15 to 30 30 to 50 50 to 100

100 to 150

150 to 200 200 to 250

>250

1

38.674

-74.701

1.00E-04

2.72E-05

1.12E-05

6.62E-06

5.07E-06

2

36.908

-75.349

7.66E-05

2.20E-05

1.10E-05

7.84E-06

6.32E-06

3

41.154

-71.08

4.65E-05

1.91E-05

1.14E-05

6.41E-06

2.62E-06

4

40.985

-71.045

5.28E-05

2.02E-05

1.08E-05

5.46E-06

2.52E-06

5

38.347

-74.761

9.49E-05

2.77E-05

1.32E-05

7.44E-06

5.06E-06

6

36.896

-75.522

8.30E-05

2.52E-05

1.29E-05

9.40E-06

7.03E-06

7

39.122

-74.242

6.67E-05

1.80E-05

1.02E-05

7.05E-06

5.33E-06

8

39.273

-74.093

6.68E-05

1.82E-05

1.07E-05

7.35E-06

5.47E-06

9

40.969

-70.792

5.18E-05

1.76E-05

9.41E-06

4.02E-06

2.41E-06

10

41.043

-70.482

5.99E-05

1.90E-05

8.71E-06

3.44E-06

2.44E-06

11

41.269

-71.436

5.48E-05

1.69E-05

1.04E-05

7.25E-06

3.43E-06

12

36.339

-75.127

5.36E-05

1.94E-05

9.94E-06

7.31E-06

5.18E-06

13

40.295

-73.315

5.79E-05

2.30E-05

1.11E-05

7.25E-06

5.04E-06

14

41.089

-71.133

5.02E-05

1.97E-05

1.12E-05

6.64E-06

2.45E-06

15

38.565

-74.665

8.32E-05

2.55E-05

1.13E-05

6.78E-06

4.86E-06

16

40.824

-70.523

5.51E-05

2.01E-05

8.07E-06

3.78E-06

2.60E-06

17

40.747

-70.416

5.76E-05

1.92E-05

7.60E-06

4.38E-06

2.82E-06

18

40.682

-70.228

5.21E-05

1.77E-05

7.67E-06

4.39E-06

2.83E-06

19

39.065

-74.379

8.17E-05

2.00E-05

1.11E-05

7.40E-06

5.50E-06

20

40.895

-70.658

5.49E-05

2.06E-05

9.36E-06

3.79E-06

2.67E-06

21

39.976

-72.74

5.11E-05

2.12E-05

1.17E-05

7.48E-06

4.97E-06

22

39.718

-73.17

4.30E-05

1.81E-05

1.00E-05

6.54E-06

4.80E-06

23

39.541

-73.304

5.46E-05

2.11E-05

1.15E-05

6.84E-06

5.02E-06

24

39.361

-73.579

5.08E-05

2.00E-05

1.12E-05

7.39E-06

5.40E-06

25

39.304

-73.461

3.79E-05

1.71E-05

1.01E-05

6.83E-06

5.10E-06

26

40.242

-73.079

5.27E-05

2.13E-05

1.18E-05

7.63E-06

4.87E-06

27

39.472

-74.004

6.04E-05

1.84E-05

1.07E-05

7.20E-06

5.24E-06

23

-------
Table 15. Transfer coefficients ((ng/m3)*tpy) relating primary coarse PM emissions (tpy) with annual
average coarse PM impacts (ng/m3) at distance bins downwind for each hypothetical source.

Primary Coarse PM coefficients ((|ig/m3)/tpy) by distance from the source (km)

SOURCE

LAT

LONG < 15

15 to 30 30 to 50 50 to 100

100 to 150

150 to 200

200 to 250

>250

1

38.674

-74.701

6.80E-05

1.69E-05

8.83E-06

5.99E-06

4.52E-06

2

36.908

-75.349

6.10E-05

1.88E-05

9.44E-06

5.82E-06

3.81E-06

3

41.154

-71.08

4.47E-05

1.79E-05

1.04E-05

5.66E-06

2.33E-06

4

40.985

-71.045

4.77E-05

1.77E-05

9.55E-06

4.67E-06

2.29E-06

5

38.347

-74.761

6.79E-05

1.76E-05

9.13E-06

6.00E-06

4.39E-06

6

36.896

-75.522

6.79E-05

1.65E-05

9.16E-06

5.74E-06

3.82E-06

7

39.122

-74.242

4.88E-05

1.62E-05

9.39E-06

6.38E-06

4.75E-06

8

39.273

-74.093

5.37E-05

1.68E-05

9.81E-06

6.65E-06

4.89E-06

9

40.969

-70.792

4.69E-05

1.55E-05

8.61E-06

3.67E-06

2.18E-06

10

41.043

-70.482

5.24E-05

1.68E-05

7.31E-06

2.96E-06

2.09E-06

11

41.269

-71.436

5.27E-05

1.61E-05

9.72E-06

6.66E-06

2.84E-06

12

36.339

-75.127

4.50E-05

1.63E-05

7.78E-06

4.55E-06

3.66E-06

13

40.295

-73.315

5.39E-05

2.11E-05

1.01E-05

6.55E-06

4.58E-06

14

41.089

-71.133

4.61E-05

1.77E-05

9.96E-06

6.08E-06

2.22E-06

15

38.565

-74.665

6.00E-05

1.74E-05

9.31E-06

6.16E-06

4.30E-06

16

40.824

-70.523

4.89E-05

1.79E-05

7.32E-06

3.33E-06

2.34E-06

17

40.747

-70.416

5.00E-05

1.75E-05

6.55E-06

3.85E-06

2.52E-06

18

40.682

-70.228

4.64E-05

1.64E-05

6.71E-06

3.86E-06

2.44E-06

19

39.065

-74.379

5.61E-05

1.86E-05

1.02E-05

6.74E-06

4.95E-06

20

40.895

-70.658

4.85E-05

1.80E-05

8.71E-06

3.34E-06

2.32E-06

21

39.976

-72.74

4.83E-05

1.95E-05

1.08E-05

6.91E-06

4.53E-06

22

39.718

-73.17

3.98E-05

1.68E-05

9.29E-06

6.03E-06

4.38E-06

23

39.541

-73.304

5.17E-05

1.98E-05

1.07E-05

6.34E-06

4.60E-06

24

39.361

-73.579

4.92E-05

1.90E-05

1.06E-05

6.91E-06

4.99E-06

25

39.304

-73.461

3.64E-05

1.62E-05

9.47E-06

6.37E-06

4.67E-06

26

40.242

-73.079

4.95E-05

1.97E-05

1.08E-05

6.95E-06

4.50E-06

27

39.472

-74.004

5.59E-05

1.69E-05

9.74E-06

6.48E-06

4.68E-06

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26

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APPENDIX A

Annual Maximum MDA8 Ozone and Speciated PM2.5 Impacts Based on Hypothetical Emission Rates

27

-------
Figure Al. Maximum MDA8 03 impacts from 5000 tpy of NOx emissions from sources 1-9.

MDA8 03 tr6m sdurce;

MDA8 03 tr6m scfurce.

MDA8 03 tr6m sdurcet

Maxva

MDA8 03 fr6m sdurceft

MDA8 03 fr6m source;

MDA8 03

Ma*yalus«2.57|

MDA8 03 fr6m source;

MDA8 03 fr6m scrurce .

MDA8 03 (r6m sdurce .

Maxvj

: 0.83 ppb

28

-------
Figure A2. Maximum MDA8 03 impacts from 5000 tpy of NOx emissions from sources 10-18.

29

-------
30

-------
Figure A4. Maximum MDA8 03 impacts from 50 tpy of VOC emissions from sources 1-9.

31

-------
Figure A5. Maximum MDA8 03 impacts from 50 tpy of VOC emissions from sources 10-18.

32

-------
Figure A6. Maximum MDA8 03 impacts from 50 tpy of VOC emissions from sources 19-27.

33

-------
Figure A7. Annual Maximum Daily Average PM2 s sulfate ion impacts from 50 tpy of S02 emissions from
sources 1-9.

PM25

34

-------
Figure A8. Annual Maximum Daily Average PM2 s sulfate ion impacts from 50 tpy of S02 emissions from
sources 10-18.

PM25

35

-------
Figure A9. Annual Maximum Daily Average PM2 s sulfate ion impacts from 50 tpy of S02 emissions from
sources 19-27.

PM25 from source 21. S02

2e-04

ie-04

36

-------
Figure A10. Annuai Maximum Daily Average PM2 5 nitrate ion impacts from 5000 tpy of NOx emissions
from sources 1-9.

PM25

37

-------
Figure All. Annuai Maximum Daily Average PM2 5 nitrate ion impacts from 5000 tpy of NOx emissions
from sources 10-18.

PM25

PM25

38

-------
Figure A12. Annuai Maximum Daily Average PM2 5 nitrate ion impacts from 5000 tpy of NOx emissions
from sources 19-27.

PM25

39

-------
Figure A13. Annuai Maximum Daily Average PM2 5 ammonium ion impacts from 5 tpy of NH3 emissions
from sources 1-9.

40

-------
Figure A14. Annuai Maximum Daily Average PM2 5 ammonium ion impacts from 5 tpy of NH3 emissions
from sources 10-18.

41

-------
Figure A15. Annuai Maximum Daily Average PM2 5 ammonium ion impacts from 5 tpy of NH3 emissions
from sources 19-27.

42

-------
Figure A16. Annual Maximum Daily Average PM2 5 impacts from 215 tpy of primary PM2.5 emissions from
sources 1-9.

43

-------
Figure A17. Annual Maximum Daily Average PM2 5 impacts from 215 tpy of primary PM2.5 emissions from
sources 10-18.

PM25

PM25 fronr'sourc'e 18 jFCRS,

: ug/m3

44

-------
Figure A18. Annual Maximum Daily Average PM2 5 impacts from 215 tpy of primary PM2.5 emissions from
sources 19-27.

PM25

45

-------
Figure A19. Annuai Maximum Daily Average Coarse PM impacts from 215 tpy of coarse PM emissions
from sources 1-9.

46

-------
Figure A20. Annuai Maximum Daily Average Coarse PM impacts from 215 tpy of coarse PM emissions
from sources 10-18.

47

-------
Figure A21. Annuai Maximum Daily Average Coarse PM impacts from 215 tpy of coarse PM emissions
from sources 19-27.

48

-------
APPENDIX B

Annual Average Speciated PM2.5 Impacts Based on Hypothetical Emission Rates

49

-------
PM25

PM25 frofti source 6j

PM25 frarffsource 7\

PM25 frc

50

-------
Figure B2. Annual Average PM2.5 sulfate ion impacts from 50 tpy of SO2 emissions from sources 10-18.

PM25

PM25

51

-------
Figure B3. Annual Average PM2.5 sulfate ion impacts from 50 tpy of S02 emissions from sources 19-27.

52

-------
Figure B4. Annual Average PM2.5 nitrate ion impacts from 5000 tpy of NOx emissions from sources 1-9.

53

-------
Figure B5. Annual Average PM2.5 nitrate ion impacts from 5000 tpy of NOx emissions from sources 10-18.

54

-------
Figure B6. Annual Average PM2.5 nitrate ion impacts from 5000 tpy of NOx emissions from sources 19-27.

55

-------
Figure B7. Annual Average PM2.5 ammonium ion impacts from 5 tpy of NH3 emissions from sources 1-9.

56

-------
Figure B8. Annual Average PM2.5 ammonium ion impacts from 5 tpy of NH3 emissions from sources 10-
18.

57

-------
Figure B9. Annual Average PM2.5 ammonium ion impacts from 5 tpy of NH3 emissions from sources 19-
27.

58

-------
Figure BIO. Annual Average PM2 5 impacts from 215 tpy of primary PM2 5 emissions from sources 1-9.

59

-------
Figure Bll. Annual Average PM2 5 impacts from 215 tpy of primary PM2 5 emissions from sources 10-18.

60

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Figure B12. Annual Average PM2 5 impacts from 215 tpy of primary PM2 5 emissions from sources 19-27.

61

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Figure B13. Annual Average Coarse PM impacts from 215 tpy of coarse PM emissions from sources 1-9.

62

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Figure B14. Annual Average Coarse PM impacts from 215 tpy of coarse PM emissions from sources 10-
18.

63

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Figure B15. Annual Average Coarse PM impacts from 215 tpy of coarse PM emissions from sources 19-
27.

64

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United States	Office of Air Quality Planning and Standards	Publication No. EPA-454/R-22-007

Environmental Protection	Air Quality Assessment Division	December 2022

Agency	Research Triangle Park, NC

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