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Technical Support Document for the Modeling Portions of the 

State of Maryland’s Regional Haze State Implementation Plan

(SIP) Entitled “State of Maryland Regional Haze

State Implementation Plan 

SIP Number: 12-01 

February 9, 2012”

TSD Prepared February, 2012

Todd A. Ellsworth

Office of Air Monitoring and Analysis, 3AP40

U.S. Environmental Protection Agency, Region 3

1650 Arch Street

Philadelphia, Pennsylvania 19103

_____________________/s/_______________________

Reviewed by Andrew Hass, Acting Associate Director,

Office of Air Monitoring and Analysis (3AP40)

_______2/15/12__________

Date Signed
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Technical Support Document for the Modeling Portions of the 

State of Maryland’s Regional Haze State Implementation Plan 

(SIP) Entitled “State of Maryland Regional Haze 

State Implementation Plan SIP Number: 12-01 

February 9, 2012”

Purpose of the Technical Support Document

This Technical Support Document (TSD) describes the Environmental Protection 

Agency’s (EPA’s) evaluation of the modeling portions of Maryland’s State 

Implementation Plan (SIP) revision entitled “State of Maryland Regional Haze State 

Implementation Plan SIP Number: 12-01 February 9, 2012”. This SIP revision will 

hereafter be referred to as the Maryland (MD) Haze SIP.

The purpose of this TSD is to provide more detailed information than can be contained in 

the official notice published in the Federal Register. Readers who need more information 

than we provide in this TSD or want to review the modeling in more detail should read 

the above referenced MD Haze SIP. 

The Regulatory Framework

In section 169A(a)(1) of the 1977 Amendments to the CAA, Congress created a program 

for protecting visibility in the nation’s national parks and wilderness areas. This section 

of the CAA establishes as a national goal the “prevention of any future, and the 

remedying of any existing, impairment of visibility in mandatory Class I Federal areas1

which impairment results from manmade air pollution.” On December 2, 1980, EPA 

promulgated regulations to address visibility impairment in Class I areas that is 

“reasonably attributable” to a single source or small group of sources, i.e., “reasonably 

attributable visibility impairment” (RAVI). See 45 FR 80084. These regulations 

represented the first phase in addressing visibility impairment. EPA deferred action on 

regional haze that emanates from a variety of sources until monitoring, modeling and 

scientific knowledge about the relationships between pollutants and visibility impairment 

were improved. 

 

1Areas designated as mandatory Class I Federal areas consist of national parks exceeding 6000 acres, 

wilderness areas and national memorial parks exceeding 5000 acres, and all international parks that were in 

existence on August 7, 1977 (42 U.S.C. 7472(a)). In accordance with section 169A of the CAA, EPA, in 

consultation with the Department of Interior, promulgated a list of 156 areas where visibility is identified as 

an important value (see 44 FR 69122, November 30, 1979). The extent of a mandatory Class I area includes 

subsequent changes in boundaries, such as park expansions (42 U.S.C. 7472(a)). Although states and tribes 

may designate as Class I additional areas which they consider to have visibility as an important value, the 

requirements of the visibility program set forth in section 169A of the CAA apply only to ‘‘mandatory 

Class I Federal areas.” Each mandatory Class I Federal area is the responsibility of a ‘‘Federal Land 

Manager’’ (FLM). (42 U.S.C. 7602(i)) 
3

Congress added section 169B to the CAA in 1990 to address regional haze issues. EPA 

promulgated a rule to address regional haze on July 1, 1999 (see 64 FR 35713), the 

Regional Haze Rule (RHR). The RHR revised the existing visibility regulations to 

integrate into the regulation provisions addressing regional haze impairment and 

established a comprehensive visibility protection program for Class I areas. The 

requirements for regional haze, found at 40 CFR 51.308 and 51.309, are included in 

EPA’s visibility protection regulations at 40 CFR 51.300-309. 

The RHR addressed the combined visibility effects of various pollution sources over a 

wide geographic region. 40 CFR 51.308(b) requires states to submit the first 

implementation plan addressing regional haze visibility impairment no later than 

December 17, 2007. Consequently, all 50 states, including those without Class I areas, 

Washington, D.C., and the Virgin Islands, are required to submit Regional Haze SIPs2. 

The USEPA designated five Regional Planning Organizations (RPOs) to assist with the 

coordination and cooperation needed to address the visibility issue. The Mid-Atlantic 

Region Air Management Association (MARAMA), the Northeast States for Coordinated 

Air Use Management (NESCAUM) and the Ozone Transport Commission (OTC) 

established the Mid-Atlantic/Northeast Visibility Union (MANE-VU)8 regional planning 

organization to coordinate efforts to address visibility impairment at seven Class I areas 

located in the Mid-Atlantic and Northeast corridor: Acadia National Park, ME; 

Brigantine Wilderness, NJ; Great Gulf Wilderness, NH; Lye Brook Wilderness, VT; 

Moosehorn Wilderness, ME; Presidential Range – Dry River Wilderness, NH; and 

Roosevelt Campobello International Park, New Brunswick.

Figure 1. Geographical Areas of Regional Planning Organizations

 

2Albuquerque/Bernalillo County in New Mexico must also submit a regional haze SIP to completely satisfy 

the requirements of section 110(a)(2)(D) of the CAA for the entire State of New Mexico under the New 

Mexico Air Quality Control Act (section 74-2-4).
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Figure 2. Class I Areas in the MANE-VU Region 

 

The State of Maryland is a member of the Mid-Atlantic / Northeast Visibility Union 

(MANE-VU) RPO. Members of MANE –VU are listed in Table 1.

Table 1 MANE-VU Members

Connecticut Pennsylvania 

Delaware Penobscot Nation 

District of 

Columbia 

Rhode Island 

Maine St. Regis Mohawk Tribe 

Maryland Vermont 

Massachusetts U.S. Environmental Protection 

Agency*

New Hampshire U.S. National Park Service*

New Jersey U.S. Fish and Wildlife Service* 

New York U.S. Forest Service*

*Non-voting members
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MANE-VU’s work is managed by the Ozone Transport Commission (OTC) and carried 

out by OTC, the Mid-Atlantic Regional Air Management Association (MARAMA), and 

the Northeast States for Coordinated Air Quality Management (NESCAUM). The states 

along with federal agencies and professional staff from OTC, MARAMA and 

NESCAUM are members of the various committees and workgroups. 

Since its inception on July 24, 2001, MANE-VU established an active committee 

structure to address both technical and non-technical issues related to regional haze. The 

primary committees are the Technical Support Committee (TSC) charged with assessing 

the nature and magnitude of the regional haze problem within MANE-VU, interpreting 

the results of technical work, and report on such work to the MANE-VU Board. In 

addition to the formal working committees, there are also three standing working groups 

of the TSC. They are broken down by topic area: Emissions Inventory, Modeling, and 

Monitoring/Data Analysis Workgroups. 

Introduction to Maryland’s Regional Haze State Implementation 

Plan 

EPA promulgated a rule to address regional haze on July 1, 1999 (see 64 FR 35713), the 

RHR. The RHR addressed the combined visibility effects of various pollution sources 

over a wide geographic region. 40 CFR 51.308(b) requires states to submit the first 

implementation plan addressing regional haze visibility impairment no later than 

December 17, 2007.

This SIP was developed based on consultations and work-products of the MidAtlantic/Northeast Visibility Union (MANE-VU) Regional Planning Organization (RPO). It 

encompasses 1) monitoring strategies for evaluating visibility impacts, 2) baselines and 

trends, 3) long-term strategies (LTS), 4) how Maryland meets its fair share of the “reasonable 

progress goals” (RPG) towards reducing visibility impairment in Class I areas, and 5) Best 

Available Retrofit Technology (BART). MANE-VU states agreed upon a ≥ 2 percent sulfate 

attribution to a Class I area in order for an upwind state to meet the definition of 

“significantly contributing” to visibility impairment for that Class I area. A contribution 

assessment analysis was completed by the Northeast States for Coordinated Air Use 

(NESCAUM), entitled Contributions to Regional Haze in the Northeast and Mid-Atlantic 

States and can be found in Appendix A of the MD Haze SIP. The MANE-VU 

Contribution Assessment indicates that emission sources located in Maryland may impact 

visibility at the following Class I areas in MANE-VU: Acadia National Park, Brigantine 

Wildlife Refuge, Great Gulf Wilderness Area, Lye Brook Wilderness Area, Moosehorn 

Wildlife Refuge, Presidential Range-Dry River Wilderness Area, and RooseveltCampobello International Park as well as Dolly Sods Wilderness, Otter Creek Wilderness 

and Shenandoah National Park which lie outside of the MANE-VU region.

The VISTAS Contribution Assessment states that the MANE-VU states contribute to SO2

emissions in both the Dolly Sods Wilderness and Shenandoah National Park Class I

areas. The Contribution Assessment states that reductions in SO2 emissions from electric 

generating units would produce the greatest improvements in visibility. Maryland will 

fulfill its commitment to reduce SO2 emissions through reductions from the Healthy Air 

Act as described in section 11 of the MD Haze SIP. 
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Therefore, this SIP focuses on how Maryland control measures will improve visibility at 

Acadia National Park, Brigantine Wildlife Refuge, Great Gulf Wilderness Area, Lye 

Brook Wilderness Area, Moosehorn Wildlife Refuge, Presidential Range-Dry River 

Wilderness Area, and Roosevelt-Campobello International Park as well as Dolly Sods 

Wilderness, Otter Creek Wilderness and Shenandoah National Park. 

Maryland believes their Regional Haze SIP demonstrates that it has met its BART, RPG and 

LTS obligations for the first visibility impairment planning period through existing 

Maryland/Federal regulations and on-the-books/on-the-way federal emission controls. In 

addition to extensive consultation with the MANE-VU states and the EPA, Maryland, 

through MANE-VU, has consulted with Federal Land Managers (FLMs) responsible for the 

Class I areas, Midwest RPO(MPRO) and VISTAS in the development of this SIP.

What Are The Components Of A Modeled Regional Haze 

Demonstration?

Modeling Process Overview 

The goal of the regional haze program is to return to natural conditions by 2064, and

States are required to demonstrate, by the end of the first planning period (by 2018), 

reasonable progress toward meeting that goal. 

Maryland is a member of the Mid-Atlantic/Northeast Visibility Union (MANE-VU) 

Regional Planning Organization (RPO). The MANE-VU RPO was tasked with the 

assignment of preparing a PM2.5 modeling platform that all member states could use to 

model their LTSs to demonstrate reasonable progress by 2018 in meeting the ultimate 

goal of natural visibility conditions by 2064. 

The New York State Department of Environmental Conservation (NYSDEC) was the 

lead agency for coordinating and running the modeling platform used by the MAVE-VU 

RPO. Modeling centers responsible for running the platform included the NYSDEC, the 

University of Maryland at College Park (UMD), the Northeast States for Coordinated Air 

Use Management (NESCAUM), the New Jersey Department of Environmental 

Protection (NJ DEP), and the Virginia Department of Environmental Quality (VA DEQ). 

Each modeling center was responsible for installing the modeling platform, conducting 

diagnostic tests and completing a benchmark run to ensure accurate results. 

 

The MANE-VU RPO used the Community Multi-scale Air Quality model (CMAQ) 

version 4.5.1 as its photochemical grid model. The model uses simulations of chemical 

reactions, emission of PM2.5 and PM2.5 precursors and a sophisticated meteorological 

model (The Pennsylvania State University/National Center for Atmospheric Research 

Mesoscale Meteorological Model (MM5)) to produce speciated PM2.5 concentrations over 

the eastern United States. The meteorological data used in the meteorological model was 

for the 2002 base year. The photochemical grid model was run with the base year 

meteorology and base year emissions to determine if the model performance was 
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satisfactory. Once the model performance was determined to be adequate, PM 2.5

concentrations were modeled by running the model with projected emissions for 2018 

and the original 2002 meteorology. The meteorology was held constant so that the results 

of changing the emissions would not be influenced by changing meteorology.

The EPA modeling guidance3recommends that modeling be used to develop relative 

response factors for each of 6 components of particulate matter between a base period 

(2000-2004) and a future 5-year period which will be reviewed in 2018. PM components 

used for regional haze-related applications are:

- mass associated with sulfates;

- mass associated with nitrates;

- mass associated with organic carbon;

- mass associated with elemental carbon;

- mass associated with fine soil (i.e., crustal material);

- mass associated with coarse particulate matter (i.e., PM10 - PM2.5).

Current speciated measurements in a Class I area are used in an empirically derived 

equation to estimate light extinction for each day with measurements. Days are ranked 

according to their resulting light extinction (measured in deciviews). This ranking is used 

to identify the 20% of days with worst and 20% of days with best visibility during each 

year in the base period. The 20% worst and best days are examined to estimate 

appropriate observed concentrations for the components of PM on “best” and “worst” 

days. Observed component concentrations are multiplied by the corresponding relative

response factors to estimate future concentrations for each component on “best” and 

“worst” days. Future component concentrations are then inserted into the equation 

relating light extinction to concentrations of particulate matter. The resulting estimates 

for future light extinction on “best” and “worst” days are compared with observations 

made during the base period to assess the future year visibility improvement and 

demonstrate reasonable progress by 2018 in meeting the ultimate goal of natural visibility

conditions by 2064. 

 

Steps Required in Modeling Future Year Visibility Improvement

The modeling guidance lists nine steps for preparing modeling to demonstrate reasonable 

progress toward visibility improvement goals. 

1. Develop a conceptual description of the problem to be addressed.

2. Select an appropriate model to support the demonstration.

3. Select appropriate meteorological time periods to model.

4. Choose an appropriate area to model with appropriate horizontal/vertical resolution 

and establish the initial and boundary conditions that are suitable for the application.

5. Generate meteorological inputs to the air quality model.

6. Generate emissions inputs to the air quality model.

7. Run the air quality model with base case emissions and evaluate the performance.

 Perform diagnostic tests to improve the model, as necessary.

 

3 Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals 

for Ozone, PM2.5, and Regional Haze, EPA -454/B-07-002, April 2007
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8. Perform future year modeling (including additional control strategies, if necessary) and 

 use the results to calculate future year visibility and visibility improvement.

How Did Maryland Address All Of The Components a Modeled 

Demonstration Of Future Year Visibility Improvement?

The MD Haze SIP addresses each of the required elements of a modeling analysis used to 

predict visibility improvement that is expected by 2018. 

Conceptual Description of the Problem

A conceptual model describes how weather patterns affect the formation and transport of 

PM2.5, accounting for emissions and photochemistry.

The conceptual model for the MD Haze SIP is described in the document entitled: The 

Nature of the Fine Particle and Regional Haze Air Quality Problems in the Mid-Atlantic 

Northeast Visibility Union(MANE-VU) Region: A Conceptual Description (NESCAUM), 

November 2006 (see Appendix I of the MD Haze SIP). This document was prepared by

Northeast States for Coordinated Air Use Management (NESCAUM) for use by the 

MANE-VU member States, and it provides the conceptual description of the fine particle 

issues in these states, consistent with the EPA’s guidance.

The NSCAUM document contains a conceptual description that explains how elevated 

regional PM2.5 peak concentrations in the summer differ significantly from the largely 

urban peak concentrations observed during winter. On average, summertime 

concentrations of sulfate in the northeastern United States are more than twice that of the 

next most important fine particle constituent, organic carbon (OC), and more than four 

times the combined concentration of nitrate and black carbon (BC) constituents. Episodes 

of high summertime sulfate concentrations are consistent with stagnant meteorological 

flow conditions upwind of the Philadelphia-Wilmington, PA-NJ-DE PM2.5 NAA and the 

accumulation of airborne sulfate (via atmospheric oxidation of SO2) followed by longrange transport of sulfur emissions from industrialized areas within and outside the area. 

National assessments have indicated that in the winter, sulfate levels in urban areas are 

higher than background sulfate levels across the eastern U.S., indicating that the local 

urban contribution to wintertime sulfate levels is significant relative to the regional 

sulfate contribution from long-range transport. A network analysis for the winter of 2002 

suggests that the local enhancement of sulfate in urban areas of the MANE-VU region 

ranges from 25 to 40% and that the long-range transport component of PM2.5 sulfate is 

still the dominant contributor in most eastern cities.

In the winter, urban organic carbon (OC) and sulfate each account for about a third of the 

overall PM2.5 mass concentration observed in Philadelphia and New York City areas. 

Nitrate also makes a significant contribution to urban PM2.5 levels observed in the 

northeastern United States during the winter months. Wintertime concentrations of OC 

and nitrate in urban areas can be twice the average regional concentrations of these 

pollutants, indicating the importance of local source contributions. This is likely because 

winter conditions are more conducive to the formation of local inversion layers which 

prevent vertical mixing. Under these conditions, emissions from tailpipe, industrial and 
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other local sources become concentrated near the Earth’s surface, adding to background 

pollution levels associated with regionally transported emissions.

In summary, the presence of fine particulate matter in ambient air significantly obscures

visibility during most parts of the year at sites across the MANE-VU region. Particle

pollution generally, and its sulfate component specifically, constitute the principle driver

for regional visibility impacts. While the broad region experiences visibility impairment,

it is most severe in the southern and western portions of MANE-VU that are closest to

large power plant SO2 sources in the Ohio River and Tennessee Valleys.

The presence or absence of regional sulfate almost exclusively drives summer visibility

impairment, whereas winter visibility depends on a combination of regional and local 

influences coupled with local meteorological conditions (inversions) that lead to the 

concentrated build-up of pollution.

Sulfate is the key particle constituent from the standpoint of designing control strategies 

to improve visibility conditions in the northeastern United States. Significant further 

reductions in ambient sulfate levels are achievable, though they will require more than 

proportional reductions in SO2 emissions.

Long-range pollutant transport and local pollutant emissions are important, especially 

along the eastern seaboard, so one must also look beyond the achievement of further 

sulfate reductions. During the winter months, in particular, consideration also needs to be 

given to reducing urban sources of SO2, as well as NOX and OC (North American 

Research Strategy for Tropospheric Ozone (NARSTO), 2003).

Modeling Platforms

Currently two regional-scale air quality models have been evaluated and used by

NESCAUM to perform air quality simulations. These are the Community Multi-scale

Air Quality modeling system (CMAQ; Byun and Ching, 1999) and the Regional 

Modeling System for Aerosols and Deposition (REMSAD; SAI, 2002). CMAQ was 

developed by USEPA, while REMSAD was developed by ICF Consulting/Systems 

Applications International (ICF/SAI) with USEPA support. CMAQ has undergone 

extensive community development and peer review (Amar et al., 2005) and has been 

successfully used in a number of regional air quality studies (Bell and Ellis, 2003;

Hogrefe et al., 2004; Jimenez and Baldasano, 2004; Mao and Talbot, 2003; Mebust et al.,

2003). REMSAD has also has been peer reviewed (Seigneur et al., 1999) and used by

USEPA for regulatory applications (www.epa.gov/otaq/regs/hd2007/frm/r00028.pdf and 

www.epa.gov/clearskies/air_quality_tech.html) to study ambient concentrations and 

deposition of sulfate and other PM species.

Five modeling centers, worked collectively to maximize efficiency of computing 

resources in MANE-VU for SIP modeling. These centers include NY DEC, NJ 

DEP/Rutgers, VA DEQ, UMD, and NESCAUM. 
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Meteorological Time Periods Used in the Modeling

All of 2002, which represents the baseline period from 2000 to 2004, was included in 

CMAQ modeling. 2002 was divided into five periods. UMD is responsible for modeling 

the period from January 1 to February 28; NJ DEP/Rutgers are responsible for the period 

from March 1 to May 14; NY DEC is responsible for the period from May 15 to 

September 30; VA DEQ is responsible for the period from October 1 to October 31; and 

NESCAUM is responsible for the period from November 1 to December 31. Each period 

uses a 15 day spin up run to minimize the impact of the default initial concentration 

fields. Each group performs CMAQ simulations on its period for a series of scenarios 

including 2002 Base Case, 2009 Base Case, 2018 Base Case, 2009 Control Case, and 

2018 Control Case. All scenarios adopt the same meteorological field (2002) and 

boundary conditions, varying only emission inputs. To ensure consistency between 

modeling groups, a benchmark test was conducted by each group.

Meteorological Data Used in the Air Quality Model

The MANE-VU states decided to use a prognostic meteorological model that provides

life-like meteorological inputs to the photochemical grid model. The Pennsylvania State 

University/National Center for Atmospheric Research Mesoscale Meteorological Model 

(MM5) version 3.6 was chosen for the modeling analysis. The MM5 model provides a 

reasonable representation of weather conditions at the surface and aloft. 

Domain of the Model, Horizontal/Vertical Resolution and the Initial and Boundary 

Conditions

MANE-VU has adopted the Inter-RPO domain description for its modeling runs. 

This 36-km domain covers the continental United States, southern Canada and northern

Mexico. The dimensions of this domain are 145 and 102 cells in the east-west and northsouth directions, respectively. A 12-km inner domain was selected to better characterize

air quality in MANE-VU and surrounding RPO regions. This domain covers the eastern

region, which includes the northeastern, central, and southeastern U.S., as well as 

southeastern Canada. It extends from 66oW~94oW in longitude and 29oN~50oN in

latitude with 172 × 172 grid cells (Figure 3).
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Figure 3. Modeling domains used in MANE-VU air quality modeling studies with

CMAQ. Outer (blue) domain grid is 36 km and inner (red) domain is 12 km grid.

The gridlines are shown at 180 km intervals (5 × 5 36 km cells/15 × 15 12 km cells).

 

Vertical resolution is the number of layers and the size of each layer in the model. The 

layers in the photochemical grid model were set up to be compatible with the model that 

produced weather conditions for the photochemical grid model. The vertical resolution 

used in the modeling exercise followed EPA’s modeling guidance and therefore 

adequately represents the atmosphere where PM2.5 is emitted, forms and is transported. 

Baseline and Future Year Emission Inventories for Modeling 

Section 51.308(d)(3)(iii) of EPA’s Regional Haze Rule requires the States to identify the 

baseline emission inventory on which strategies are based. The baseline inventory is 

intended to be used to assess progress in making emission reductions. Based on EPA 

guidance entitled, 2002 Base Year Emission Inventory SIP Planning: 8-hour Ozone, PM 

2.5, and Regional Haze Programs, which identifies 2002 as the anticipated baseline 

emission inventory year for regional haze. The MANE-VU states are using 2002 as the 

baseline year. Future year inventories were developed for the years 2009, 2012 and 2018 

based on the 2002 base year. These future year emission inventories include emissions 

growth due to projected increases in economic activity as well as the emissions 

reductions due to the implementation of control measures. 

The 2002 emissions were first generated by the individual states in the MANE-VU area. 

MARAMA then coordinated and quality assured the 2002 inventory data. The 2002 

emissions from non-MANE-VU areas within the modeling domain were obtained from 
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other Regional Planning Organizations for their corresponding areas. These Regional 

Planning Organizations included the Visibility Improvement State and Tribal Association 

of the Southeast (VISTAS), the Midwest Regional Planning Organization and the Central 

Regional Air Planning Association. 

Version 3 of the 2002 base year emission inventory was used in the regional modeling 

exercise. Technical support documentation for the MANE-VU 2002 base inventory is 

presented in Appendix D of the MD Haze SIP. This document explains the data sources, 

methods, and results for preparing this version of the 2002 base year criteria air pollutant 

and ammonia emissions inventory. Documentation for the future year estimations of 

EGUs is presented in Appendix E of the MD Haze SIP. Documentation for the future 

year estimations of the remaining source sectors (non-EGU sectors) is also presented in 

Appendix E of the MD Haze SIP.

Model Performance Evaluation

NESCAUM evaluated the 2002 annual 12 km resolution meteorological fields generated by 

MM5 using ENVIRON's METSTAT program. Model results of surface wind speed, wind

direction, temperature, and humidity were paired with measurements from EPA’s Clean Air 

Status and Trends Network (CASTNET) and National Center for Atmospheric Research’s 

Techniques Data Laboratory (TDL) network by hour and by location and then statistically 

compared. Based on this statistical comparison between model prediction and data from the 

two networks for wind speed, wind direction, temperature, and humidity, MM5 performs 

well. An acceptable small bias, high index of agreement and strong correlation with 

CASTNET and TDL data are shown. Since MM5 uses TDL data for nudging, the model 

predictions are in better agreement with TDL data than with CASTNET data. MM5 performs 

better in Midwest and Northeast than Southeastern US.

CMAQ modeling was conducted for year 2002 by cooperative modeling efforts from 

NYDEC, UMD, NJDEP, Rutgers, VADEP, and NESCAUM. CMAQ Performance for PM 

2.5 species and visibility was examined based on this CMAQ run on a 12 km resolution 

domain. Measurements from IMPROVE and STN networks were paired with model 

predictions by location and time for evaluation. The goal and the criteria for PM2.5 evaluation 

suggested by Boylan and Baker (2004) were adopted by every RPO for SIP modeling. The 

performance goals are: Mean Fractional Error (MFE) ≤ +50%, and Mean Fraction Bias 

(MFB) ≤ ±30%; while the criteria are proposed as: MFE ≤ +75%, and MFB ≤ ±60%. CMAQ 

prediction of PM2.5 species from 40 STN sites and 17 IMPROVE sites within the MANE-VU 

Region were paired with measurements and statistically analyzed to generate MFE and MFB 

values. Considering CMAQ performance in terms of MFE and MFB goals, sulfate, nitrate, 

OC, EC, and PM2.5 all had the majority of data points within the goal curve, some were 

between the goal and acceptable criteria, and only a few were outside the criteria curve. Only 

fine soil has the majority of points outside the criteria curve, but there were some sites still 

within the goal. For the MANE-VU region, CMAQ performs best for PM2.5 sulfate, followed 

by PM2.5, EC, nitrate, OC, and then fine soil. Regional haze modeling also requires CMAQ 

performance evaluation for aerosol extinction coefficient (Bext) and the haze index. Modeled 

daily aerosol extinction at each improve site was calculated following the IMPROVE formula 

with modeled daily PM2.5 species concentration and relative humidity factors from 

IMPROVE. The approach used natural background visibility estimates and the haze index 

following EPA Guidance. The modeled Bext showed a near 1:1 linear relationship (slope of 
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0.78 and r2 of 0.46) with IMPROVE observed Bext. The regression excluded three points from 

July 7, 2002; the monitors were directly impacted by Canadian fires whose emissions were 

not modeled. 

Uniform Rate of Progress Goals

The key difference between SIPs from States with Class I areas and those States without 

Class I areas, but may have sources that impact visibility on Class I areas, is the 

calculation of the baseline and natural visibility for their Class I areas and the 

determination of uniform rate of progress goals - expressed in deciviews - that provide 

for reasonable progress towards achieving natural visibility by 2064. It is the Class I

states responsibility assess these calculations. The Class I States must also consult with 

those States, which may reasonably be anticipated to cause or contribute to visibility

impairment in their Class I areas (40 CFR 51.308 (d)(1)(i-vi)). 

The baseline visibility conditions are calculated for the baseline period between 2002 and 

2004. The average impairment for the 20 most and 20 least impaired days are determined 

for each calendar year and compiled into the average of three annual averages (40 CFR 

51.308 (d)(2)(i)). The natural visibility conditions are determined for the same baseline 

period with the most and least impaired days determined by available monitoring data or 

an appropriate data analysis technique (40 CFR 51.308 (d)(iii-iv)). 

U.S. Environmental Protection Agency (EPA) released guidance on June 7, 2007 to use 

in setting reasonable progress goals. The goals must provide improvement in visibility for 

the most impaired days, and ensure no degradation in visibility for the least impaired 

days over the State Implementation Plan (SIP) period. The State must also provide an 

assessment of the number of years it would take to attain natural visibility condition if 

improvement continues at the rate represented by the reasonable progress goal. Figure 4 

illustrates an example of how Uniform Rate of Progress is calculated. 

 
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Figure 4. Example calculation of Uniform Rate of Progress

Modeled Visibility Projections for 2018

The CMAQ air quality model was used to simulate base period emissions and future 

emissions. The modeling results for the base year period (2002) and the year 

representing the end of the first planning period (2018) are used to develop relative 

response factors (RRF) for each component of particulate matter identified previously in 

this TSD. The relative response factors are multiplied by the measured species 

concentration data during the base period (for the measured 20% best and worst days). 

This results in daily future year species concentrations data. The projected concentrations 

are then used to derive daily visibility in deciviews and are averaged across all best and 

worst days to create the projected future visibility. The results of this procedure are 

plotted along with the uniform progress glide slope in Appendix M of the MD Haze SIP. 

The modeling results presented in Appendix M of the MD Haze SIP show all MANE-VU 

sites are projected to meet or exceed the uniform rate of progress goals for 2018 on the 20 

percent worst days. In addition, no site anticipates increases in visibility impairment 

relative to the baseline on the 20 percent best days. 

Summary of Photochemical Grid Modeling Results

In summary, the photochemical grid modeling, presented in the MD Haze SIP, follow

EPA’s modeling guidance and is acceptable to EPA. All MANE-VU sites are projected 

to meet or exceed the uniform rate of progress goal for 2018 on the 20 percent worst 

days. In addition, no site anticipates increases visibility impairment relative to the 

baseline on the 20 percent best days (see Appendix M of the MD Haze SIP). 

Contribution Assessment

The 1999 Regional Haze Rule requires States and Tribes to submit State Implementation 

Plans (SIPs) to the U.S. Environmental Protection Agency (USEPA) for approval by
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January 2008 at the latest. The haze SIPs must include a “contribution assessment” to 

identify those states or regions that may be influencing specially protected federal lands 

known as Federal Class I areas.4These states or regions would then be subject to the 

consultation provisions of the Haze Rule. The Haze Rule also requires a “pollution 

apportionment” analysis as part of the long-term emissions management strategy for each 

site.

As described in the Conceptual Description portion of this TSD, sulfate alone accounts 

for anywhere from one-half to two-thirds of total fine particle mass on the 20 percent 

haziest days at MANE-VU Class I sites. As a result of the dominant role of sulfate in the 

formation of regional haze in the Northeast and Mid-Atlantic region, MANE-VU 

concluded that an effective emissions management approach would rely heavily on 

broad-based regional SO2 control efforts in the eastern United States.

Area of Influence for MANE-VU Class I Areas 

The key difference between SIPs from States with Class I areas and States without Class 

I areas is the calculation of the baseline and natural visibility for their Class I areas, and 

the determination of reasonable progress goals. Class I States calculate baseline visibility

conditions for the period between 2002 and 2004. The average impairment for the most 

and least impaired days are determined for each calendar year and compiled into the 

average of three annual averages (40 CFR 51.308 (d)(2)(i)). The natural visibility

conditions are determined for the same baseline period with the most and least impaired 

days determined by available monitoring data or an appropriate data analysis technique 

(40 CFR 51.308 (d)(iii-iv)). In contrast, States without Class I areas are responsible for 

doing their fair share to help meet the reasonable progress goals established by the 

impacted Class I States, and for maintaining their emissions monitoring network. 

There are seven Class I areas located in the Mid-Atlantic and Northeast. As a result, the 

Regional Haze Rule requires Maryland, in consultation with MANE-VU and others, to 

identify where its emissions are most likely to influence visibility in Class I areas. In 

order to identify states whose emissions are most likely to influence visibility in MANEVU Class I areas, MANE-VU prepared the Contributions to Regional Haze in the 

Northeast and Mid-Atlantic United States (Contribution Assessment). The full report can 

be found in Appendix A of the MD Haze SIP. 

Based on that work, MANE-VU concluded that it was appropriate to define an “Area of 

Influence” (AOI) including all of the states participating in MANE-VU plus other states 

outside MANE-VU for which modeling indicated they contributed at least two percent 

(2%) of the sulfate ion in MANE-VU Class I areas in 2002. The Visibility Improvement 

 

4

The Class I designation applies to national parks exceeding 6,000 acres, wilderness areas and national 

memorial parks exceeding 5,000 acres, and all international parks that were in existence prior to 1977. In

the MANE-VU area, this includes: Acadia National Park, Maine; Brigantine Wilderness (within the Edwin

B. Forsythe National Wildlife Refuge), New Jersey; Great Gulf Wilderness, New Hampshire; Lye Brook

Wilderness, Vermont; Moosehorn Wilderness (within the Moosehorn National Wildlife Refuge), Maine;

Presidential Range – Dry River Wilderness, New Hampshire; and Roosevelt Campobello International

Park, New Brunswick.
16

State and Tribal Association of the Southeast (VISTAS)5also conducted an AOI analysis, 

which used a level of one percent (1%) to assess whether an upwind state significantly

contributed. 

The primary contribution assessment tool used in the MD Haze SIP was the Regional 

Modeling System for Aerosols and Deposition (REMSAD) (SAI, 2002). A significant 

feature of the REMSAD work used to evaluate regional contributions is that NESCAUM 

reprocessed the SO2 emission data from each state to take advantage of REMSAD’s 

tagging capabilities. Thus, all SO2 emissions included in the model for the eastern half of 

the country were tagged according to state of origin, and emissions from Canada and the 

boundary conditions were also tagged. This allowed for a rough estimation of the total 

contribution from elevated point sources in each state to simulated sulfate concentrations 

at eastern receptor sites. Using identical emission and meteorological inputs to those 

prepared for the CMAQ SIP modeling platform, described earlier in this TSD, REMSAD 

was used to simulate the annual average impact of each state’s SO2emission sources on 

the sulfate fraction of PM

2.5 

over the northeastern United States. A more in-depth 

description of the REMSAD modeling used for contribution assessment can be found in 

Appendix L of the MD Haze SIP.

The REMSAD contribution assessment modeling contained in the MD Haze SIP 

conforms to EPA modeling requirements and is acceptable to EPA. 

REMSAD Contribution Assessment Results

MANE-VU States decided that any state or region that contributed at least 2 percent of 

total sulfate observed on 20 percent worst visibility days in 2002 is contributing 

significantly to the haze problem in that particular Class I area. Based on the MANE-VU 

Contribution Assessment and the application of the “≥ 2% SO2 rule,” emissions from 

Maryland were determined to contribute to visibility degradation in the following Class I 

Areas in MANE-VU: Acadia National Park, Maine; Brigantine Wilderness (within the 

Edwin B. Forsythe National Wildlife Refuge), New Jersey; Great Gulf Wilderness, New 

Hampshire; Lye Brook Wilderness, Vermont; Moosehorn Wilderness (within the 

Moosehorn National Wildlife Refuge), Maine; Presidential Range – Dry River 

Wilderness, New Hampshire; and Roosevelt Campobello International Park, New 

Brunswick. 

The MANE-VU Contribution Assessment indicates that emission sources located in 

Maryland may also impact visibility at the following Class I areas outside MANE-VU: 

Dolly Sods Wilderness/Otter Creek Wilderness Area (the Dolly Sods IMPROVE monitor 

is also representative of Otter Creek) in West Virginia; and Shenandoah National Park.

The Maryland Department of the Environment has conferred with regional haze planning 

 

5

VISTAS is comprised of the following states: Alabama, Florida, Georgia, Kentucky, Mississippi, North 

Carolina, South Carolina, Tennessee, Virginia, West Virginia, the Eastern Band of Cherokee Indians, and 

Knox County, TN 
17

staff in both Virginia and West Virginia regarding Maryland’s impacts as described in 

sections 4.2.2 and 4.3.3 and Appendix Q of the MD Haze SIP. 

BART

On July 6, 2005 (70 FR 39104) EPA finalized 40 CFR 51 – Regional Haze Regulations 

and Guidelines for Best Available Retrofit Technology (BART) Determinations 

addressing the issues from the Circuit Court decisions. The BART requirements were 

most recently updated on October 5, 2006. BART is defined as an emission limitation 

based on the degree of reduction achievable through the application of the best system of 

continuous emission reduction for each pollutant, which is emitted by a BART-eligible 

source. The changes to the rule included how the States would identify the best system of 

continuous emission control technology and by which States can consider an individual 

facility’s contribution to regional haze when determining to require controls, and what 

the level of control should be met. The rule changes also clarified the requirements 

associated with demonstrating how emissions trading or alternative programs may be 

used as an alternative to applying Best Available Retrofit Technology (BART) 

Requirements. 

Congress defined sources potentially subject to BART - as major stationary sources, 

including reconstructed sources; from one of 26 identified source categories which 

included utility and industrial boilers, and large industrial plants such as pulp mills, 

refineries and smelters; which have the potential to emit 250 tons per year or more of any 

air pollutant, and which were placed in operation between August 1962 and August 1977. 

[CAA 169A (b)(2)(A) & (g)(7)]. A list of BART-eligible sources within the MANE-VU 

region and in Maryland is contained in Appendix G of the MD Haze SIP.

Maryland Sources Subject to BART

Source Unit/Point 

ID(s) Pollutant Location(County)

Facility 

I.D

Facility 

MW

EGU

Mirant - Chalk Point 1, 2 & 3 NOX , SOX Prince George’s 033-0014 2647

Mirant – Morgantown 1 & 2 NOX , SOX Charles 017-0014 1548

CPSG – Crane 2 NOX , SOX Baltimore 005-0079 415.8

CPSG – Wagner 3 NOX , SOX Anne Arundel 003-0014 1058.5

Non – EGU

New Page/Westvaco/Luke 

Paper

25 SOX Allegany 001-0011

Independent/St. Lawrence 

Cement

24 SOX Washington 043-0008

Mettiki Coal 1 SOX Garrett 023-0042
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Five Factor Analysis for Each BART Source 

States are required to determine BART for each BART-eligible source. According to 40 

CFR 51.308(e)(1)(ii)(A) the determination of BART must be based on an analysis of the 

best system of continuous emission control technology available and associated emission 

reductions achievable. 40 CFR 51.308(e)(1)(ii)(A) requires the analysis to take into 

consideration the following five factors for the technology available : 

1) The costs of compliance, 

2) The energy and non-air quality environmental impacts of compliance, any

3) Pollution control equipment in use at the source, 

4) The remaining useful life of the source, and 

5) The degree of improvement in visibility which may reasonably be anticipated to result 

from use of the technology.

The BART-eligible sources were identified using the methodology in the Guidelines for 

Best Available Retrofit Technology (BART) Determinations under the Regional Haze 

Rule (40 CFR Part 51, Appendix Y.) A detailed description of each BART-eligible 

source and the identification analysis is included in Appendix G of the MD Haze SIP. 

The Maryland Department of the Environmental (MDE) conducted BART 

determinations for each BART-eligible source using the 5-Factor Analysis, for PM only. 

Consistent with the MANE-VU Board (June, 2004) decision, this analysis would include 

consideration of potential visibility impacts as a result of installing various controls for 

primary particulate matter. 

MANE-VU conducted modeling analyses of individual BART-eligible sources using 

CALPUFF – a model preferred by EPA for assessing long range transport of pollutants 

and their impacts - in order to provide a regionally consistent foundation for assessing the 

degree of visibility improvement (Factor 5) that could result from installation of BART 

controls. Summary spreadsheets of the MANE-VU CALPUFF modeling results for the 

Maryland BART sources are included in Appendix G of the MD Haze SIP. CALPUFF 

was promulgated by the USEPA on April 15, 2003 as a preferred dispersion model to 

assess long-range transport applications (i.e. transport distances exceeding 50 km to 

approximately 300 km). Up to this distance, a non-steady-state modeling approach which 

considers spatial and time variations in meteorological conditions, such as CALPUFF, is 

appropriate. For this modeling demonstration, CALPUFF was used, consistent with the 

approved BART version. 

CALPUFF is a multi-layer, multi-species, non-steady state puff dispersion model which 

can simulate the time and space varying meteorological conditions on pollutant transport, 

transformation and removal. CALPUFF uses three dimensional meteorological fields 

developed by the meteorological processing program CALMET. 

CALPUFF contain algorithms for near source effects such as building downwash, 

traditional plume rise, partial plume penetration, sub-grid scale terrain interactions, as 

well as long range effects such as pollutant removal (dry and wet deposition), chemical 

transformation, vertical wind shear, over-water transport, and coastal interaction effects.
19

The CALPUFF modeling performed for all of Maryland’s BART sources conforms to 

EPA modeling guidance. A detailed description of the CALPUFF modeling can be found 

in Appendix G of the MD Haze SIP.

The BART determinations for the sources subject to BART in Maryland are summarized 

in Table 8.6 of the MD Haze SIP. BART is the emission limit for each pollutant based 

on the degree of reduction achievable through the application of the best system of 

continuous emission control technology available, taking into consideration: the costs of 

compliance, the energy and the non-air quality environmental impacts of compliance, any 

pollution control equipment in use or in existence at the source, the remaining useful life 

of the source, and the degree of improvement in visibility which may reasonably be 

anticipated to result from the use of such technology. The Department’s BART analyses 

for each source subject to BART are included in Appendix G of the MD Haze SIP. The 

BART analyses identified the best system of continuous emission control technology

available and include the consideration of these five factors: the costs of compliance, the 

energy and non-air quality environmental impacts, any existing pollution controls at the 

source, the remaining useful life of the source and the degree of improvement in 

visibility, the latter of which is determined in the Visibility Impacts portion of each 

review memo. The consideration of the degree of improvement in visibility is based on 

the maximum 24-hour NESCAUM-modeled impact at the Class I area of maximum 

impact. However, if an affected BART source conducted a CALPUFF modeling analysis 

that used three years of meteorological data input, a BART determination was performed 

using the 98th percentile deciview modeled impact, as allowed in the Regional Haze 

Regulations and Guidelines for Best Available Retrofit Technology (BART) 

Determinations, Final Rule (40 CFR Part 51, July 6, 2005).

The BART for each source subject to BART was determined based on the methodology 

in the Guidelines for Best Available Retrofit Technology (BART) Determinations Under 

the Regional Haze Rule (40 CFR Part 51, Appendix Y). Table 9.6, table 9.10 and 

Appendix G-2 of the MD Haze SIP summarize the level of control determined to be 

BART for the non-EGU and EGU BART-eligible sources in Maryland.

Summary of EPA’s Technical Findings

The technical analyses and modeling used to assess uniform rate of progress and to 

support the LTS were successfully developed consistent with EPA’s interim and final 

modeling guidance. All MANE-VU sites are projected to meet or exceed the uniform 

rate of progress goal for 2018 on the 20 percent worst days. In addition, no site 

anticipates increases visibility impairment relative to the baseline on the 20 percent best 

days. The technical analyses and modeling used in the MD Haze SIP’s contribution 

assessment and prediction of visibility impacts from BART controls comply with EPA 

modeling guidance and recommendations. EPA finds the MANE-VU technical modeling 

analyses presented in the MD Haze SIP to be acceptable because the models that were 

used were applied according to EPA modeling guidance.