1



## Te **chnical Support Document for the Modeling Portions of the**  **St ate of Maryland’**  **s Regional Haze S** **tate Implementation Plan (SIP) Entitled**  **“** 

## St **ate of Maryland Regional Haze** 

**St ate**  **I mplementation**  **Plan SIP**  **Number: 12**  **- 0**  **1 February**  **9 , 20**  **12 ”** 

TSD Prepared February , 201 2 Todd A. Ellsworth Office of Air Monitoring and Anal ys is, 3AP40 U.S. Environmental Protection Agency , Region 3

1650 Arch Street Philadelphia, Pennsylvania 19103

_____________________ /s/

_______________________ Reviewed b y Andrew Hass , Acting Associate Director, Office of Air Monitoring and Anal ys is (3AP40)

_______2/15/12

__________ Date Signed2



### Technical Support Docum **ent for the Modeling Portions of the State of Maryland’s Regional Haze State Im**  **plementation Plan (SIP) Entitle**  **d “ State of Maryland Regional Haze**  **State Im plementation**  **Plan SIP Number:**  **12 -**  **0 1** 

**February 9**  **, 20 12**  **”**
**Purpose of the Technical Support Document** This Technical Support Document (TSD) describes the Environmental Protection Agency ’s (EPA’s) evaluation of the modeling portion s of Maryland ’s State Implementation Plan (SIP) revision entitled “ **State of Maryland Regional Haze State Implementation**  **Plan SIP Number:**  **12 -**  **0 1**  **February 9 , 20**  **12** ” . T his SI P revi sion will h ereafter 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 pr ovide in this TSD or want to review the modeling in more detail should read the above referenced MD Haze SIP . 

### The Regulatory Fram **ew ork**  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 an y future, and the remed yi ng of an y existing, impairment of visibility in mandatory

Class I Federal areas 1 which impairment results fr om manmade air pollution.” On December 2, 1980, EPA promulgated regulations to address visibility impairment in Class Iareas that is “reasonabl y attributable” to a single source or small group of sources, i.e., “reasonabl y attributable visibility

impairm ent” (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 variet y of sources until monitoring, modeling and scientific knowledge about the r elationships between pollutants and visibility impairment were improved.
1 Areas designated as mandatory Class I Federal areas consist of national parks exceeding 6000 acres, wilderness areas and nationa l mem orial 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 s ection 169A of the CAA , EPA , in consultation with the Department of Interior, promulgate d a list of 156 ar eas 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 de signate 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 Fed eral 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) requi res 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 Iareas , Washington, D.C., and the Virgin Islands, are required t o submit Regional Haze SIPs 2

. 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 Northeas t 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 Iareas located in the Mid
- Atlantic and Northeast corridor: Acadia National Park, ME; Brigantine Wilderness, NJ; Great Gulf Wilderness, NH; Ly e Brook Wilderness, VT; Moosehorn Wilderness, ME; Presidential Range

– Dry River Wilderness, NH; and Roo sev elt Campobello International Park, New Brunswick. **Figure 1. Geographical Areas of Regional Planning Organizations**

2 Albuquerque/Bernalillo County in Ne w 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 Ne w Mexico under the New Mexico Air Quality Control Act (section 74
- 2 - 4).4

**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 I sland Maine St. Regis Mohawk Tribe Maryland Vermont Massachusetts U.S. Environmental Protection

Agency* New Hampsh ire U.S. National Park Service* New Jersey U.S. Fish and Wildlife Service* New York U.S. Forest Service* *Non
- voting members5

MANE - VU’s work is managed by the Ozone Transport Commission (OTC) and carried out by OTC, the Mid
- Atlantic Regional Air M anagement Association (MARAMA), and the Northeast States for Coordinated Air Qualit y Management (NESCAUM). The states along with federal agencies and professional staff from OTC, MARAMA and NESCAUM are members of the various committees and workgroups. Sin ce 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 Anal ys is Workgroups. 

### Introduction to **Maryland ’**  **s Regional Haze**  **State Im plementation**  **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 C FR 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 Mid
Atlantic/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 anal ys is was comple ted b y 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 SI P. The MANE
- VU Contribution Assessment indicates that emissio n sources located in Maryland may impact visibility at the following Class Iareas 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 Roosevelt
Campobello International Park as well as Doll y 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 SO 2 emissions in both the Dolly Sods Wilderness and Shenandoah National Park Class I areas. The Contribution Assessment states that reductions in SO 2 emissions from electric generating units would produce the greatest improvements in visibil ity . Maryland will fulfill its commitment to reduce SO 2 emissions through reductions from the Health y Air Act as described in section 11 of the MD Haze SIP.6

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 Wildli fe 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 h as 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 VI STAS in the development of this SIP. 

### What Are The Components Of A Modeled Regional Haze **Dem onstration?**  **Mode ling Process Overview**  The goal of the regional haze program is to return to natural conditions by 2064, and States ar e 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 PM 2.5 modeling platform that all member states could use to model their L TSs 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 fo r 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 PM 2.5 and PM 2.5 precursors and a sophisticated meteorological mode l ( The P enns yl vania State University /National Center for Atmospheric Research Mesoscale Meteorological Model (MM5) ) to produce speciated PM 2.5 concentrations over the eastern United States. The meteorological data used in the meteorological model was for the 2002 base y ear. The photochemical grid model was run with the base y ear meteorology

and base y ear emissions to determine if the model performance was7

satisfactory . Once the model performance was determined to be adequate, PM 2.5 concentrations were m odeled 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 guidance 3 re commends 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
- ye ar period which will be reviewed in 2018. PM components used for regional haze
- related ap plications 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 part iculate matter (i.e., PM 10 - PM 2.5 ). 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 (m easured in deciviews). This ranking is used to identify

the 20% of day s with worst and 20% of day s with best visibility during each ye ar in the base period. The 20% worst and best day s are examined to estimate appropriate observed concentrations for the co mponents of PM on “best” and “worst” day s. Observed component concentrations are multiplied by the corresponding relative response factors to estimate future concentrations for each component on “best” and “worst” day s. 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” day s are compared with observations made during the base period to assess the futur e year visibility improvement and demonstrate reasonable progress b y 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, PM 2.5 , and Regional Haze, EPA **-** 454 /B
- 07 - 002 , April 20078

8. Perform future year modeling (including additional control strategies, if necessary) and use the results to calculate fut ure ye ar visibility

and visibility

improvement. 

### How **Did Maryland**  **Address All Of The Com ponents a Modeled**  **Dem onstration Of Future Year Visibility Im**  **provement?** The MD Haze SI P addresses each of the required elements of a model ing analy sis used to predict v isibility

improvement that is expected by 2018. **Conceptual D**  **escription of the P**  **roblem** A conceptual model describes how weather patterns affect the formation and transport of PM 2.5 , accounting for emissions and photochemistry. The conceptual model for the MD Haze SI P 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 o f the MD Haze SIP) . Th is 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 the se states, consistent with th e EPA’s guidance . The NSCAUM document contains a conceptual description that explains how elevated regional PM 2.5 peak concentrations in the summer differ significantl y from the largel y urban peak concentrations observed during winter. On average, summert ime 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) constit uents. Episodes of high summertime sulfate concentrations are consistent with stagnant meteorological flow conditions upwind of the Philadelphia
- Wilmington, PA
- NJ - DE PM 2.5 NAA and the accumulation of airborne sulfate (via atmospheric oxidation of SO 2 ) foll owed by long
range 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 anal ys is 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 PM 2.5 sulfate is still the dominant contributor in most eastern cities. In the winter, urban organic carbon (OC) and sulfate each account for about a th ird of the overall PM 2.5 mass concentration observed in Philadelphia and New York City areas. Nitrate also makes a significant contribution to urban PM 2.5 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 lay ers which prevent vertical mixing. Under these conditions, emissions from tailpipe, industrial and9

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 y ear at sites across the MANE
- VU region. Particle pollution generally , and its sulfate component specificall y, constitute the p rinciple 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 SO 2 sources in the Ohio River and Tennessee V alley s. 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 SO 2 emissions. Long - range pollutant transport and local pollutant emissions are important, especiall y along the eastern seaboard, so one must also look bey ond the achi evement of further sulfate reductions. During the winter months, in particular, consideration also needs to be given to reducing urban sources of SO 2 , as well as NO X 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 s ys tem (CMAQ; By un and Ching, 1999) and the Regional Modeling S y stem for Aerosols and Deposition (REMSAD; SAI , 2002). CMAQ was developed b y USEPA, while REMSAD was developed by IC F Consulting/Sy stems Applications International (I CF/SAI) with USEPA support. CMAQ has undergone extensive community

development and peer rev iew (Amar et al., 2005) and has been successfull y 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 conce ntrations and deposition of sulfate and other PM species. Five modeling centers, worked collectivel y to maximize efficiency of computing resources in MANE
- VU for SI P modeling. These centers include NY DEC, NJ DEP/Rutgers, VA DEQ, UMD, and NESCAUM.10

**Met eorological**  **T ime**  **P eriods**  **U sed in the**  **M odeling**  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, varyingonl y emission inputs. To ensure consistency between modeling groups, a benchmark test was conducted by each group. **M eteorological**  **D ata**  **U sed in the**  **A ir**  **Q uality**  **M odel**  The MANE - VU states decided to use a prognostic meteorological model that provid es life
- like meteorological inputs to the photochemical grid model . The Pennsyl vania State University

/National Center for Atmos pheric Research Mesoscale Meteorological Model (MM5) version 3.6 was chosen for the modeling analy sis . The MM5 model provide s a reasonable representation of weather conditions at the surface and aloft. **Domain of the M**  **odel, H**  **orizontal/ V**  **ertical R**  **esolutio n and the**  **I nitial and**  **B oundary**  **C onditions**  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 1 02 cells in the east
- west and north
south 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 66 oW~94 oW in longitude and 29 o N~50 o N in latitude with 172 × 172 grid cells (Figure 3).11

**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 lay ers and the size of each lay er in the model. The lay ers in the photochemical grid model were set up to be compatible with the model that produced weather conditions for the phot ochemical grid model. T he vertical resolution used in the modeling exercise followed EPA’s modeling guidance and therefore adequatel y represent s the atmosphere where PM 2.5 is emitted, forms and is transported. **Baseline and Future Year Emission Inventor ies for Modeling**  Section 51.308(d)(3)(iii) of EPA’s Regional Haze Rule requires the State s t o identify the baseline emission inventory on which strategies are based. The baseline inventory is intended to be used to assess progress in making emission reduc tions. 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

y ear for regional haze . The MANE - VU states are us ing 2002 as the baseline year. Future ye ar inventories were developed for the y ears 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 b y the individual states in the MANE
- VU area. MARAMA then coordinated and qualit y assured the 2002 inventory data. The 2002 emissions from non
- MANE - VU areas within the modeling domain were obtained from12

other Regional Planning Organizations for their corresponding areas. These Regional Planning Organizations included the Visibility I mprovement State and Tribal Association of the Southeast (VISTA S), the Midwest Regional Planning Organization and the Central Regional Air Planning Association. Version 3 of the 2002 base y ear emission inventory was used in the regional modeling exercise. Technical support documentation for the MANE
- VU 2002 base inv entory is presented in Appendix D of the MD Haze SI P . This document explains the data sources, methods, and results for preparing this version of the 2002 base ye ar criteria air pollutant and ammonia emissions inventory . Documentation for the future y ear e stimations of EGUs is presented in Appendix E of the MD Haze SIP . Documentation for the future ye ar estimations of the remaining source sectors (non
- EGU sectors) is also presented in Appendix E of the MD Haze SIP . **Model Performance Evaluation** NESCAUM eval uated the 2002 annual 12 km resolution meteorological fields generated by M M 5 using ENVIRON's METSTAT program. M odel results of surface wind speed, wind direction, temperature, and humidity were paired with measurements from EPA’s Clean Air Status and Tre nds Network (CASTNET) and National Center for Atmospheric Research’s T echniques 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 conducte d for y ear 2002 by cooperative modeling efforts from NYDEC, UMD, NJDEP, Rutgers, VADEP, and NESCAUM. C MAQ 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 PM 2.5 evaluation suggested by

Boylan and Baker (2004) were adopted by every RPO for SIP modeling. The performance goal s 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 PM 2.5 species from 40 STN sites and 17 IMPROVE sites within the MANE
- VU Region were paired wi th 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 PM 2.5 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 PM 2.5 sulfate, f ollowed by PM 2.5 , EC, nitrate, OC, and then fine soil. Regional haze modeling also requires CMAQ performance evaluation for aerosol extinction coefficient (B ext ) and the haze index. Modeled daily aerosol extinction at each improve site was calculated fol lowing the IMPROVE formula with modeled daily PM 2.5 species concentration and relative humidity factors from IMPROVE. The approach used natural background visibility estimates and the haze index following EPA Guidance. The modeled B ext showed a near 1:1 li near relationship (slope of13

0.78 and r

2 of 0.46) with IMPROVE observed B ext . The regression excluded three points from July 7, 2002; the monitors were directly impacted by Canadian fires whose emissions were not modeled. **Uniform Rate o**  **f Progress Goals** Th e key difference between SIPs from States with Class Iareas and those States without Class Iareas , 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 det ermination 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 IStates must also cons ult with those States, which may

reasonabl y be anticipated to cause or contribute to visibility impairment in their Class Iareas (40 CFR 51.308 (d)(1)(i
- vi)). The baseline visibility

conditions are calculated for the baseline period between 2002 and 200 4. The average impairment for the 20 most and 20 least impaired day s are determined for each calendar ye ar 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 basel ine period with the most and least impaired day s determined by available monitoring data or an appropriate data anal ysis 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 day s, and ensure no degradation in visibility for the least impaired day s over the State Implementation Plan (SIP) period. The State must also provide an ass essment of the number of years it would take to attain natural visibility condition if improvement continues at the rate represented b y the reasonable progress goal. Figure 4 illustrates an example of how Uniform Rate of Progress is calculated.14

**Figure 4. Example calculation of Uniform Rate of Progress** 

**Modeled Visibility Projections for 2018** The CMAQ air qualit y m odel 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 particul ate 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 day s). This results in daily

future y ear species concentratio ns data. The projected concentrations are then used to derive daily visibility in deciviews and are averaged across all best and worst day s 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 day s. 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 day s. In addition, no site anticipates increases visibility impairment relative to the baseline on the 20 percent best day s (see Appendix M of the MD Haze SI P) . 

### Contribution Assessment The 1999 Regional Haze Rule requires States and Tribes to submit State Implementation Plans (SI Ps) to the U.S. Environmental Protection Agency (USEPA) for approval by15

January 2008 at the latest. The haze SIPs must include a “contribution assessment” to identify those states or regions that may be influencing speciall y protected federal lands known as Federal Class I areas. 4 These states or regions would then be subject to th e consultation provisions of the Haze Rule. The Haze Rule also requires a “pollution apportionment” anal ys is as part of the long
- term emissions management strategy for each site. As described in the Conceptual Description portion of this TSD, s ulfate alon e accounts for an ywh ere from one
- half to two
- thirds of total fine particle mass on the 20 percent haziest day s at MANE - VU Class Isites. 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 rel y 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 C lass Iareas and States without Class I areas is the calculation of the baseline and natural visibility for their Class Iareas, and the determination of reasonable progress goals. Class I States calculate baseline visibility conditions for the period betw een 2002 and 2004. The average impairment for the most and least impaired day s are determined for each calendar y ear 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 day s determined by

available monitoring data or an appropriate data anal ys is technique (40 CFR 51.308 (d)(iii
- iv)). In contrast, States without Class Iareas are responsible for doing their fair share t o 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 r equires 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 MANE
VU Class Iarea s, 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 SI P. Based on that work, MANE
- VU concluded that it was appropriate to define an “Area of In fluence” (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 I mprovement
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

Ham pshire; and Roosevelt Campobello International Park, New

Brunswick.16

State and Tribal Association of the Southeast (VISTAS) 5 also conducted an AOI analy sis, which used a level of one percent (1%) to assess whether an upwind state significantly contributed. The primary

contribution assessment tool us ed in the MD Haze SIP was the Regional Modeling S ys tem for Aerosols and Deposition (REMSAD) (SAI, 2002). A significant feature of the REMSAD work used to evaluate regional contributions is that N ESCAUM reprocessed the SO2 emission data from each state to t ake advantage of REMSAD’s tagging capabilities. Thus, all SO 2 emissions included in the model for the e astern 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 platfo rm, described earlier in this TSD, REMSAD was used to simulate the annual average impact of each state’s SO 2 emission 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 day s in 2002 is contributing significantl y to the haze problem in that particular Class I area. Based on the MANE
- VU Co ntribution Assessment and the application of the “ ≥ 2% SO 2 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 Edwi n B. Fors ythe National Wildlife Refuge), New Jersey ; Great Gulf Wilderness, New Hampshire; Ly e 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 C reek Wilderness Area (the Doll y 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, TN17

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 SI P. **BART** On July 6, 2005 (70 FR 39104) EPA finalized 40 CFR 51

– Regional Haze Regulations and Guidelines for Best Available Retrofit Techno logy (BART) Determinations addressing the issues from the Circuit Court decisions. The BART requirements were most recentl y updated on October 5, 2006. BART is defined as an emission limitation based on the degree of reduction achievable through the applic ation of the best sy stem 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 sy stem 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 tradi ng 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 y ear or more of an y 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 NO X , SO X Prince George’s 033 - 0014 2647 Mirant

– Morgantown 1 & 2 NO X , SO X Charles 017 - 0014 1548 CPSG

– Crane 2 NO X , SO X Baltimore 005 - 0079 415.8 CPSG

– Wagner 3 NO X , SO X Anne Arundel 003 - 0014 1058.5 **Non**
**– EGU**  New Page/Westvaco/Luke Paper 25 SO X Allegany 001 - 0011 Independent/St. Lawrence Cement 24 SO X Washington 043 - 0008 Mettiki Coal 1 SO X Garrett 023 - 004218

**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 anal ys is of the best sy stem of continuous emission control technology available and associated emission reductions achievable. 40 CFR 51.308(e)(1)(ii)(A) requires the anal ys is 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 analy sis is included in Appendix G of the MD Haze SIP . The Maryland Department of the Environmental (MDE ) conduct ed BART determinations for each BART
- eligible source using the 5
- Factor Anal ys is, for PM only . Consistent with the MANE
- VU Board (June, 2004) decision, this anal ys is would include consideration of potential visibility impacts as a result of installing various controls for primary particulate matter. MANE - VU conducted modeling anal ys es of individual BART - eligible sources us ing CAL PUFF

– a model preferred by E PA for assessing long range transport of pollutants and their impacts
- in order to provide a regionally consistent foundation for assessing the degree of visibility

i mprovement (Factor 5) that could result from installation of BART controls. S ummary

s preadsheets of the MANE - VU CAL PUFF modeling results for the Maryland BART sources are included in Appendix G of the MD Haze SI P . CAL PUFF was promulgated by

the USEPA on April 15, 2003 as a preferred dispersion model to ass ess long
- range transport applications (i.e. transport distances exceeding 50 km to approximately

300 km). Up to this distance, a non
- stead y - state modeling approach which considers spatial and time variations in meteorological conditions, such as CAL PUFF, i s appropriate. For this modeling demonstration, CAL PUFF was used, consistent with the approved BART version. CAL PUFF is a multi
- layer, multi
- species, non - steady s tate puff dispersion model which can simulate the time and space varying meteorological condi tions on pollutant transport, transformation and removal. CAL PUFF uses three dimensional meteorological fields developed b y the meteorological processing program CALMET. CAL PUFF contain algorithms for near source effects such as building downwash, traditi onal 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 e ffects.19

The CAL PUFF modeling performed for all of Maryland ’s BART sources conforms to EPA modeling guidance. A detailed description of the CAL PUFF 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 T able 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 s ystem of continuous emission control technology available, taki ng into consideration: the costs of compliance, the energy

and the non
- air qualit y environmental impacts of compliance, an y pollution control equipment in use or in existence at the source, the remaining useful life of the source, and the degree of improve ment in visibility which may

reasonably

be anticipated to result from the use of such technology . The Department’s BART anal ys es for each source subject to BART are included in Appendix G of the MD Haze SI P . The BART analy ses identified the best sy stem 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 lif e of the source and the degree of improvement in visibility , the latter of which is determined in the Visibility I mpacts portion of each review memo . The consideration of the degree of improvement in visibility is based on the maximum 24
- hour NESCAUM
- mode led impact at the Class I area of maximum impact. However, if an affected BART source conducted a CALPUFF modeling anal ys is that used three ye ars of meteorological data input, a BART determination was performed using the 98 th percentile deciview modeled i mpact, 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). T able 9 .6 , table 9.10 and Appendix G - 2 of the MD Haze SIP s ummarize the level of control determined to be BART for the n on - EGU and EGU BART - eligible sources in Maryland . 

### Summary of EPA’s Technical Findings The technical anal ys es and modeling used to assess uniform rate of progress and to support the L TS were successfull y developed consistent with EPA’s interim and final m odeling guidance. All MANE
- VU sites are projected to meet or exceed the uniform rate of progress goal for 2018 on the 20 percent worst day s. In addition, no site anticipates increases visibility impairment relative to the baseline on the 20 percent best d ay s. 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 anal ys es pre sented in the MD Haze SIP to be acceptable because the models that were used were applied according to EPA modeling guidance .