, 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

REGION 10 

1200 Sixth ~venue. Suite 900 


Seattle, Washington 98101-3140 


I 

OFFICE OF THE A~R REGIONAL ADMINISTRATOR 

04 2011 

The Honorable Sean Parnell 

Governor of the State ofAlaska 

P. O. Box 110001 

Juneau, Alaska 99811-0001 

Dear Governor Parnell: 

On June 3,2010, the U.S. Environmental Protection Agency (EPA) revised the heathbased National Ambient Air Quality Standard (NAAQS) for sulfur dioxide (S~) by establishing 

a new I-hour standard at a level of75 parts per billion (ppb). This new 1-hour standard will 

protect public health by reducing people's exPosure to high short-term (5-minutes to 24-hours) 

concentrations ofS02• An area meets the new standard when the 3-year average ofthe 99th 

percentile of I-hour daily maximum concentrations does not exceed 75 ppb. 

Section 107(d)(1) ofthe Clean Air Act (CAA) describes the process EPA follows for 

designating areas as meeting or not meeting new or revised NAAQS. Within one year of 

establishing a new or revised standard, each ~overnor must recommend a designation of 

attainment, nonattainment or unclassifiable, ~ith appropriate boundaries, for areas within their 

jurisdiction. Therefore, we ask that your state provide designation recommendations, including 

appropriate area boundaries, for all areas by June 3, 2011, with respect to the I-hour 802 

NAAQS. , 

The enclosed memorandum provides ~dance to state and local air pollution control 

agencies and tribes on the timeline and process for designating areas under the revised S02 

standard. We plan to announce our intended'designations no later than 120 days prior to 

promulgating final designations. Following the announcement ofintended designations, states 

and tribes will have the opportunity to comment on any modifications EPA proposes to their 

recommendations. EPA intends to complete~designations by no later than June 3,2012. 

I 

Establishing area designations is a key step in the process of providing the health 

protection intended by the CAA. Should you have questions regarding this matter, please do not 

hesitate to contact me or Steve Body ofthe State & Tribal Air Programs Unit at 206-553-0782 or 

body.steve@epa.gov. 

Sincerdly, 

Dennisi J. Mclerran ~ Regio$! Administrator 

Enclosure I 

·~~t~~~ 
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

RESEARCH TRIANGLE PARK, NC 27711 

MAR 242011 

OFFICE OF 


AIR ()UAUTY PLANNING 


AND STANDARDS 


MEMORANDUM 

SUBJECT: A.rea. Des ..ignation.S for th ..e 20 I 0 Rev12'~.) imary Sulfur Dioxide National 

Ambient Air Quality Standard . ~ 

"_",Ne ,/ 

FROM: 	 Stephen D. Page, Direct' ~ 

Ofllce of Air Quality Pla ni g and St~ards 

TO: 	 Regional Air Division Directors, Regions I-X 

This memorandum provides infonnation on the schedule and process for designating 

areas for the purpose of implementing the 2010 revised primary sulfur dioxide (S02) national 

ambient air quality standard (NAAQS). In addition, it identiHes factors EPA intends to evaluate 

in determining boundaries tor arcas designated nOllattainment. We recommend that slates and 

tribes consider and address these factors when identifying boundaries tl.x their area designation 

recommendations. Please share this ini'{)nnation with the state and tribal agencies in your 

Region. 

On June 2, 20 I 0, Administrator Jackson signed the revised primary SO:: NAAQS (75 FR 

35520. published on Junc 22,2010) after review of the existing two primary S02 standards. 

promulgated on April 30, 1971 (36 FR 8187). EPA established the revised primary S02 

standard at 75 parts per billion (ppb) which is attained when the 3-year average ofthe 991h 

percentile of I-hour dally maximum concentrations does not exceed 75 ppb. The Administrator 

has detenllined that this is the leveillcccssary to provide protection of public health with an 

adequate margin ofsafelY, espcciafly tor children, the elderly and those with asthma. These 

groups are particularly susceptible to the health effects associated with breathing SO;;. 

Gc@ral approach and schedule. Clean Air Act (CAA) section 107(d) directs states to 

submit their S02 designation recommendations to EPA by June 3. 2011. If EPA intends to 

modifY any state's boundary recommendation, l:PA will notify the state no later than 120 days 

prior to its action to promulgate designations (Le., February 2012 for designations to be 

promulgated in June 2012), and the state will have an opportunhy to comment on EPA's 

intended modifications and provide additional intormation for EPA to consider. Section 107(d) 
requires EPA to promulgate initial area designations by June 3, 2012, which is 2 years after 

promulgation ofthe revised primary standard. While the language in section 107 specifically 

addresses states, we intend to follow the same process for tribes, pursuant to section 30 1 (d) of 

the CAA and the Tribal Authority Rule (40 CFR Part 49). Therefore, we intend to designate 

tribal areas, in consultation with the tribes, on the same schedule as state designations. If a state 

or tribe does not submit designation recommendations, EPA will promulgate the designations 

that it deems appropriate. 

Sections 111 through VI of the preamble to the final rule promulgating the revised primary 

S02 NAAQS describe the approach EPA anticipates using for designations for the I-hour S02 

standard. EPA anticipates taking an analytic approach that uses both air quality monitoring and 

modeling information for designations. Such an approach, if adopted, would be consistent with 

EPA's historic practices for S02 NAAQS implementation. In that preamble we acknowledged 

that in some cases, monitoring data may be the more technically appropriate information for 

determining compliance with the I-hour NAAQS. (See e.g., 75 FR at 35552, n. 22). We also 

recognized that a single monitor may generally not be adequate to fully characterize ambient 

concentrations of S02, including the maximum ground level concentrations that exist around 

stationary S02 sources, particularly when measuring for a 1-hour standard. (See 75 FR at 

35551). Refined dispersion models are able to characterize S02 air quality impacts from the 

modeled sources across the domain of interest on an hourly basis with a high degree ofspatial 

resolution, thus overcoming the limitations of an approach based solely on monitoring. 

Attachment 2 summarizes three possible designations and the criteria for initial 

designations ofthe I-hour S02 primary standard that EPA expects to apply. As stated in the 

preamble, we do not believe it would be realistic or appropriate to expect states to complete 

modeling for all significant sources of S02 and assess the results .in time for the designation 

recommendations the Act requires be submitted to EPA by June 3, 2011. (See 75 FR at 35570­

71). Therefore, we do not generally expect states to provide refined dispersion modeling 

information along with their initial designation recommendations. However, EPA does intend to 

consider, as appropriate, available air quality monitoring and modeling information submitted by 

states or tribes in support of their recommendations. 

States and tribes should identify areas as attairunent, nonattainment or unclassifiable on 

the basis of available information. Given the currently limited network of S02 monitors, and our 

expectation that states will not yet have completed appropriate modeling of all significant S02 

sources, we anticipate that most areas ofthe country will be designated "unclassifiable." I f a 

state or tribe, following receipt of an EPA 120-day letter, has additional infonnation that it wants 

EPA to consider with respect to a designation recommendation that EPA plans to modify. we 

request that such information be submitted within 60 days after receiving EPA's letter. This will 

help ensure that EPA can fully consider any such information prior to issuing tinal designations. 

2 
Also, although not required by statute. in order to consider public input in the designation 

process, we plan to provide a 30-day public comment period immediately following issuance of 

EPA's letters responding to the recommendations made by states and tribes. Attachment 1 is this 

anticipated schedule. 

The preamble to the final NAAQS rulemaking includes a general discussion of states' 

statutory planning and emissions control responsibilities under each ofthe three possible 

designations. The CAA directs states with areas designated as "nonattainment" for S02 to 

develop and submit a plan within 18 months after designation providing for attainment as 

expeditiously as practicable, but no later than 5 years after the initial designation date. (See 

CAA sections 191-193). The CAA also directs states to submit by June 3, 2013, a SIP 

demonstrating an adequate program to implement, maintain and enforce the S02 NAAQS. 

Generally, these infrastructure plans for attainment areas are not expected to include an 

attainment demonstration. However, in light of the incomplete monitoring and modeling data 

available at the time of designations, for areas designated unclassifiable, we would expect states 

to include in these plans demonstrations ofexpeditious attainment and maintenance ofthe S02 

NAAQS. EPA is developing separate guidance on developing SIP revisions for the S02 standard 

and we intend to seek public review and comment on that guidance document. 

Identifying an area that is in violation orthe S02 NAAQS. Section 107(d){1) ofthe CAA 

defines an area as "nonattainn:tent" ifit is violating the NAAQS or if it is contributing to a 

violation in a nearby area. Thus, the first step in making designations is to identify through 

monitoring or appropriate modeling areas violating the NAAQS. In assessing whether 

monitoring data indicate a violation, EPA intends to use the most recent three consecutive years 

ofquality-assured, certified air quality data in the EPA Air Quality System (AQS), I using data 

from Federal Reference Method (FRM) and Federal Equivalent Method (FEM) monitors that are 

sited and operated in accordance with 40 CFR Parts 50 and 58. Procedures for using monitored 

air quality data to detennine whether a violation has occurred are given in 40 CFR Part 50 

Appendix T, as revised in conjunction with the final rule tor the 2010 S02 NAAQS. We expect 

that in providing their recommendations to EPA, states and tribes would review available S02 

monitoring data from 2008 through 2010. Prior to EPA issuing letters to states and tribes 

concem.ing any intended modifications to their recommendations, data from 2011 may become 

available. Ifthis is the case, EPA intends to also consider 2011 S02 air quality monitoring data 

in formulating any intended modifications to state and tribal recommendations. 

Air quality monitoring data affected by exceptional events may be excluded from use in 

identifying a violation ifthey meet the criteria for exclusion, as speci11ed in the final rule 

1 This information is available on EPA's website at www.epa.gov/ttn/alrs/alrsaqs/. 

3 
'Treatment of Data Influenced by Exceptional Events" (72 FR 13560; March 22, 2007) codified 

in 40 CFR Parts 50 and 51. In section VILB ofthe S02 NAAQS final rule preamble, we 

discussed schedules for states and tribes to flag data influenced by exceptional events and submit 

related documentation specificalIy for SOl data collected from 2008 through 2010 used in the 

initial designations process. These schedules are contained in Table 1 of 40 CFR 50.14 and 

require initial data flagging by October 1,2010 and detailed documentation submittal. by June 1. 

2011. This should assure that any exceptional events claim asserted by a state or tribe can be 

fully considered by EPA before final designations. 

States and tribes may also choose to use available air quality modeling results to indicate 

a violation ofthe N AAQS. Attachment 3 provides further guidance on the appropriate refined 

dispersion modeling analysis that could be used to support designation recommendations. Such 

modeling could include using the AERMOD dispersion model, \\ith allowable source emissions 

and emissions limitation credit for stacks no higher than good engineering practice. As noted 

above (and in the preamble to the final 802 primary NAAQS rulemaking), we recognize that it is 

not realistic to expect states or tribes to complete this type ofmodeting for all significant sources 

ofS02 in the time available for providing designation recommendations. Where the time and 

resources to conduct refined dispersion modeling are limited, we believe it is reasonable to focus 

first on the most significant sources of S02 emissions, and on those sources that are most likely 

to contribute to a violation. We recognize that this approach means that all areas where S02 

NAAQS violations may be occurring might not be identitied in the initial round ofarea 

designations. States are expected to address any such areas in the course of developing the SIPs 

due by June 3, 2013. 

Identifying attainment areas. EPA may initially designate an area as_attainment if it is 

clear that it meets the S02 NAAQS. EPA does not believe it would be appropriate to do so 

without appropriate refined dispersion modeling and, where avaiJable, air quality monitoring 

data indicating no violations ofthe NAAQS. In the absence ofinformation clearly 

demonstrating a designation of "attainment" or "nonattainment," EPA intends to designate the 

area as "unclassifiable." 

Determining nonattainment area boundaries. As a pollutant that arises from direct 

emissions, S02 concentrations are highest relatively close to the source(s) and much lower at 

greater distances due to dispersion. Thus, S02 concentration patterns resemble those ofother 

directly emitted pollutants like lead and differ from those of photochemically-formed 

(secondary) pollutants such as ozone. Accordingly, consistent with our approach under other 

NAAQS, we expect to consider the county line as the starting point for determining S02 

nonattainment areas. As discussed further in Attachment 2, EPA intends to consider several 

factors when determining the final nonattainment boundaries. We believe it is appropriate to 

evaluate each potential nonattainment area on a case-by-case basis, and to recognize that area4 
specific analyses conducted by states, tribes and/or EPA may support a boundary with either a 

larger or smaller area than the county boundary, 

A nonattainment area should contain the area violating the NAAQS (e.g., the area around 

a violating monitor), as well as any adjacent areas (e.g., counties or portions thereof) that contain 

emissions sources contributing to the violation. (See CAA section 107(d)(1)(A)(i». 

Consequently, we recommend that states and tribes base their boundary recommendations on an 

evaluation of five factors: 1) air quality data; 2) emissions-related data; 3) meteorology; 4) 

geography/topography and 5) jurisdictional boundaries, as well as other available data. 

Dispersion modeling, as discussed in Attachment 3, can be a helpful tool in this evaluation 

because it allows the model user to simultaneously assess multiple factors. States and tribes 

may identify and evaluate other relevant factors or circumstances specific to a particular area. 

While EPA generally believes that in the absence of other relevant information it is 

appropriate to use county boundaries to define nonattainment area';, we recognize that the fivefactor analysis and other infomlation may support designating only a portion of a county as 

"nonattainment." For example, a topographical teature may divide a county into two separate 

air basins, or contributing sources may be clustered in only a portion of a county. For defining 

partial county boundaries, EPA recommends the use of well·deJined jurisdictional lines such as 

township borders, immovable landmarks such as major roadways or other permanent and readily 

identifiable boundaries. 

Determining attainment area boundaries. In areas without a violating monitor, refined 

dispersion modeling could be used to help determine that an area with S02 sources is in 

attainment for the 1-hour S02 NAAQS. An attainment area boundary cannot contain any area 

that exceeds the NAAQS or any area containing sources that are causing or contributing to a 

violating area. (See CAA section 107(d)(1)(A)(i). County boundaries may be appropriate for 

defining attainment areas in the absence ofother information that would help define a more 

specific boundary around the modeled source(s). 

While we believe this memorandum provides helpful guidance on how boundaries would 

be determined for S02 designations, the guidance contained herein is not binding on states, tribes 

the public or EPA. The final basis for detemlining nonattainment area boundaries will be 

addressed in EPA's action to initially designate areas under the 2010 S02 standard. When EPA 

promulgates designations, those determinations will be final and binding on states, tribes, the 

public and EPA. 

Attachment 1 is a timeline ofkey dates in the designations process tor the revised 2010 

S02 NAAQS. Attachment 2 identifies the primary five factors that EPA plans to consider in 

evaluating and making decisions on nonattainment area boundaries. Attachment 3 is the 

modeling guidance that states and tribes should use to support designation recommendations, 

5 
including appropriate area boundaries. 

Staff members at EPA's Office of Air Quality }llanning and Standards are available for 

ass.istance and consultation throughout the designations process. General questions on this 

guidance may be directed to Valerie Broadwell (919) 541-3310 or Doug Solomon (919) 541­

4132. Modeling-related questions may be directed to James Thurman (919) 541-2703. 

Attachments: 3 

cc: 	 Scott Mathias, OAQPS 

Lydia Wegman, OAQPS 

Richard Wayland, OAQPS 

Greg Green, OAQPS 

Margo Oge, OTAQ 

Kevin McLean, OGe 

Sara Schneeberg, OGe 

6 

ATTACHMENT 1 


TIMELINE FOR 2010 Primary S02 NAAQS DESI(;NATION -PROCESS 

Milestone Date* 

EPA promulgates S02 NAAQS June 3, 2010 

States and tribes flag exceptional event-influenced 

S02 monitoring data from 2008-2009 October 1,2010 

States and tribes flag exceptional event-influenced 

S02 monitoring data from 2010; provide detailed 

documentation to support a1l2008-2010 claims 

No later than June 1,2011 

States and tribes submit recommendations for area 

designations to EPA No later than June 3, 2011 

EPA notifies states and tribes concerning any 

intended modifications to their recommendations 

(120.day letters) 

ola February 3, 2012 (no later than 120 

days prior to final designations) 

EPA publishes public notice of state and tribal 

recommendations and EPA's intended modifications 

and initiates 30-day public comment period 

ola February 20, 2012 

End of 30-day public comment period ola March 20,2012 

States and tribes submit additional information to 

demonstrate why an EPA modification is 

inappropriate 

ola April 3,2012 

EPA promulgates final S02 area designations No later than June 3, 2012 

'" ola = on or about 

Note: This schedule assumes EPA has sufficient information to promulgate designations within 

2 years. In the event EPA determines that insufficient information is available to do so, the 

Clean Air Act allows EPA to extend the designation process, but no later than June 3, 2013. 
ATTACHMENT 2 

. Determining Designations and Appropriate Area Boundaries 

for the l·hour, 75 ppb SOl NAAQS 

Nonattainment -.~-~ Attainment Unclassifiable (all other areas) 

An area' where monitoring 

data Q.t an appropriate 

modeling analysis indicate a 

violation. 

An area that has no monitored violations 

and which has an appropriate model ing 

analysis, if needed, and any other 

relevant infonnation demonstrating no 

violations. 

An area that has no monitored 

violations and lacks an appropriate 

modeling analysis, ifneeded, or other 

appropriate infonnation sufficient to 

support an alternate designation. 

Attainment area boundaries. Areas designated as "attainment" should be supported by 

inlunnation clearly demonstrating that there are no violations oCthe S02 NAAQS inside the area 

boundary. This could consist of appropriate air quality dispersion modeling and, where 

available. air quality monitoring data. As provided in Attachment 3, appropriate modeling would 

include using the AERMOD dispersion model, with allowable source emissions and emissions 

limitation credit for stacks no higher than good engineering practice. County boundaries may be 

appropriate for defining attainment areas in the absence of other infonnation that would help 

define a more specific boundary around the modeled source(s). In the absence of information 

clearly demonstrating a designation of"attainment" or "nonattainment" EPA intends to 

designate tbe area as ··unclassifiable." 

Nonattainment area boundarie~. EPA intends to lJse the county as tbe analytical starting 

point Jur assessing the appropriate geographic boundaries of a S02 nonattainment area. As a 

framework for area-specific analyses to support final boundary determinations, we intend to 

evaluate the five factors listed below, as well as other relevant available information. The 

purpose ofevaluating these factors is to determine the appropriate boundaries encompassing the 

area meeting the CAA's definition of "nonattainment area" i.e., an area violating the S02 

standard and any nearby areas contributing to tbe violating area. The modeling guidance in 

Attachment 3 discusses how modeling could be used to address several ofthese factors 

simultaneously. When considered as a whole, results may support nonattainment boundaries 

that are either larger or smaller than the analytical starting point. 

L 	 Air quality data. We intend to review 802 air quality monitoring data, including the design 

value calculated for each monitor in the area, for the most recent 3-year period. Areas where 

monitoring data indicate a violation ofthe I-hour, 75 ppb primary S02 standard will be 

designated as "nonattainment." Source-oriented modeling,may also be used to assess air 

quality in a particular location. Attachment 3 provides further guidance on using refined 

dispersion modeling for this type of assessment 

2. 	 Emissions-related data (location ofsources and potential contribution to ambient S02 

concentrations). We intcndto examine allowable emissions 0[S02 from sources located in 
and around the violating area. Significant emissions levels in a nearby area indicate the 

potentia] for the area to contribute to observed or modeled violations of the NAAQS. We 

intend to review data from the latest National Emissions Inventory or other relevant sources 

ofthe data, such as state inventories or inventories from other federal sources. We would 

also consider any additional information we receive on federally-enforceable emissions 

controls that are not reflected in recent inventories but which will require compliance before 

final designations are issued. 

3. 	 Meteorology (weather/transport patterns) .. We intend to evaluate meteorological data to 

help determine how weather conditions, including wind speed and direction, affect the plume 

ofsources contributing to ambient S~ concentrations. Where feasible, we would consider 

results from source-oriented dispersion modeling. 

4. 	 Geograpby/topography (mountain ranges or other air basin boundaries). We intend to 

examine the physical features of the land that might affect the distribution of S02 over an 

area. Mountains or other physical features may affect the distribution of emissions, and may 

help define boundaries. 

5. 	 Jurisdictional boundaries (e.g., counties, air districts, pre-existing nonattainment areas, 

reservations, metropolitan planning organizations). Once the geographic area associated with 

the area violating the S02 standard and the nearby area contributing to violations are 

determined, we intend to consider existing jurisdictional boundaries for the purposes of 

providing a clearly defined legal boundary for carrying out the air quality planning and 

enforcement functions for the nonattainment area. If an existing jurisdictional boundary is 

used to help define the nonattainment area, it should encompass all ofthe area that has been 

identitied as meeting the nonattainment definition. Where existing jurisdictional boundaries 

are not adequate to describe the nonattainment area, other clearly defined and permanent 

landmarks or geographic coordinates may be used. 

EPA plans to consider these tactors. along with any other relevant information, in 

determining whether to make modifications to the boundary recommendations made by states 

and tribes. The factors listed above, while generaLly comprehensive, are not intended to be 

exhaustive. States and tribes may submit additional information they believe is relevant for EPA 

to consider. Any information provided to support a boundary recommendation for a 

non attainment area should show that: 1) violations are not occurring in nearby portions that are 

excluded from the recommended nonattainment area; and 2) the excluded portions do not contain 

emission sources that contribute to the monitored or modeled violation. 

2 

ATTACHMENT 3 


Modeling Guidance for SOl NAAQS Designations 


1. Purpose 

On June 2, 2010, Administrator Jackson signed a final ruJemaking notice that revised the 

primary S02 NAAQS (75 FR 35520, published on June 22. 2010) after review of the existing 

two primary SOi standards, promulgated on April 30, 1971 (36 FR 8187).1 EPA established the 

revised primary S02 standard at 75 parts per billion (ppb) which is attained when the 3-year 

average of the 99th percentile of I-hour daily maximum concentrations does not exceed 75 ppb, 

In the final rule preamble, EPA outlined an expected analytic approach to determining 

compJiance with the new NAAQS that would include the use of both modeling and monitoring. 

EPA believes this analytic approach to determining compliance with the new I-hour NAAQS 

would be the generally more technically appropriate and accurate means of assessing peak 1­

hour SOl concentrations, and would be consistent with historic (past and more recent) 

implementation practice of using models to determine compliance with the SOl NAAQS. 

While this guidance explains the use of modeling for NAAQS designations, it does not 

preclude the fact that monitoring data may be more technically appropriate than modeling in 

some cases. In cases where there is complete air quality data from FRM or FEM S02 monitors, 

that data would be considered by EPA in designating areas as attainment or nonattainment. (See 

75 FR at 35570). The guidance presented here is for cases where modeling is used in support of 

the designations process. 

Dispersion modeling could be used in these initial designations to a limited degree (as 

could monitoring) but wouLd likely be used to a larger extent subsequently as the basis for redesignation of nonattainment and unclassifiable areas to attainment. As the preamble to the rule 

promulgating the new I-hour S02 NAAQS noted, EPA does not think it realistic or appropriate 

to expect states to complete modeling for all significant sources ofS02 and assess the results in 

time for the designation recommendations the Act requires be submitted by June 2011. (Sec 75 

FR at 35570-71). Therefore, we do not generally expect states to provide modeling information 

along with their initial designation recommendations. lIowever, EPA does intend to consider, as 

appropriate. available monitoring data and modeling information submitted by states or tribes in 

support of their recommendations. 

This guidance explains the expected application of dispersion models to support the 

designations process regarding: 

I EPA publicly disseminated a copy of the signed notice on June 3,2010, and therefore treats June 2, 2010, as 

the date ofthe rule's promulgation, for purposes of the deadlines in eM section 1 07(d). 

1 
1. 	 the use of modeling to infonn the nonattainment boundaries for areas with violating 

ambient air quality monitors ifthe presumptive county boundaries are not used (either to 

expand the boundaries outside the county or shrink the boundary within the county); and 

2. 	 The use of modeling in areas without a violating monitor as evidence of attainment of the 

NAAQS (showing no violations or contributions to violations of the standard). 

This guidance is consistent with EPA's Guideline on Air Quality Mode!s, or Appendix W to 40 

CFR Part 51, and other relevant modeling guidance issued to support regulatory programs. 

When the need for interpretation of this guidance arises, the user should consult with the 

appropriate Regional Modeling Contact2

, 

Also as indicated in the preamble ofthe I-hour 802 NAAQ8 final nile, we intend to issue 

additional guidance describing the development of an approvable 11 O(a)(1) implementation 

pJans for areas designated "unc1assifiable" that will include technical direction on how to 

conduct refined dispersion modeling to demonstrate future NAAQS attainment. 

2. Guidance on Air Quality Models 

Much of this guidance is based on EPA's Guideline on Air Quality Models, also 

published as Appendix W of40 CPR Part 51. Appendix W is the primary source of infonnation 

on the regulatory application of air quality models for State Implementation Plan (SIP) revisions 

for existing sources and for New Source Review (NSR) and Prevention ofSigni ficant 

Deterioration (PSD) programs. Air quality modelinf in support of this designations process 

would need to employ air quality dispersion models that properly address the source-oriented 

nature ofSO::! and, thus, should rely upon the principles and techniques in Appendix W. 

Appendix W was originally published in Apri1 1978 and was incorporated by reference in 

the regulations for the Prevention of Significant Deterioration of Air Quality, Title 40, Code of 

Federal Regulations (CFR) sections 51.166 and 52.2] in June 1978 (43 FR 26382-26388). The 

purpose ofAppendix W guidelines is to promote consistency in the use of modeling within the 

air quality management process. These guidelines are periodically revised to ensure that new 

model developments or expanded regulatory requirements are incorporated. 

Clarifications and interpretations ofmodeling procedures become official EPA guidance 

through several courses ofaction: 1) the procedures are published as regulations or guidelines; 2) 

2 List of Regional Modeling Contacts by EPA Regional Office is available from SCRAM website at: 

3 Dispersion modeling uses mathematical formulations to characterize the atmospheric processes that 

disperse a pollutant emitted by a source. Based on emissions and meteorological inputs, a dispersion model 

can be used to predict concentrations at selected downwind receptor locations. 

2 
the procedures are formally transmitted as guidance 10 Regional Office managers; 3) the 

procedures are formally transmitted as guidance to Regional Modeling Contacts as a result of a 

Regional consensus on technical issues; or 4) the procedures are a result of decisions by the 

EPA's Model Clearinghouse that effectively establish national precedent. Formally located in 

the Air Quality Modeling Group (AQMG) ofEPA's Office of Air Quality Planning and 

Standards (OAQPS), the Model Clearinghouse is the single EPA focal point for the review of 

criteria pollutant modeling techniques for specific regulatory applications. Model Clearinghouse 

and related Clarification memoranda involving decisions with respect to interpretation of 

modeling guidance are available at the Support Center for Regulatory Atmospheric Modeling 

(SCRAM) website.4 

Recently issued EPA guidance of relevance for consideration in modeling for designations 

includes: 

• 	 "Applicability of Appendix W Modeling Guidance for the 1-hour S02 NMQS" August 

23, 201O-confirming that Appendix W guidance is applicable for NSR/PSD permit 

modeling for the new S02 NAAQS. 

• 	 "Additional Clarification Regarding Application of Appendix W Modeling Guidance for 

the I-hour N02 National Ambient Air Quality Standard" March 1, 2011- provides 

additional guidance regarding N02 permit modeling and also relevant to S02. 

The foJ lowing sections will provide reference to the relevant sections of Appendix Wand 

other existing guidance with summaries as necessary. Please refer to those original guidance 

documents for full discussion and consult with the appropriate EPA Regional Modeling Contact 

ifquestions arise about interpretation on modeling techniques and procedures. 

3. 	Model selection 

Preferred air quality models for use in regulatory applications are addressed in Appendix 

A of EPA's GUIDELINE ON AIR QUALITY MODELS. Ifa model is to be used for a 

particular application, the user should folJow the guidance on the preferred model for that 

application. These models may be used without an area specific formal demonstration of 

applicability as long as they arc used as indicated in each model summary of Appendix A. 

Further recommendations for the application ofthese models to specific source problems are 

found in subsequent sections of Appendix W. In 2005, the American Meteorological 

Society/Environmental Protection Agency Regulatory Model (AERMOD) was promulgated as 

EPA's preferred near-field dispersion modeling for a wide range of regulatory applications in all 

types ofterrain based on extensive developmental and perfonnance evaluation. 

4 The Support Center for Regulatory Atmospheric Modeling (SCRAM) website is available at: 

httn;Lb1'\:Y'N,!.:fL'W4QY/Ulli.gId.ml· 

3 
For area designations under the l·hour S02 primary NAAQS, AERMOD should be used 

unless use of an alternative model can be justified (Section 3.2, Appendix W), such as the 

Buoyant Line and Point Source Dispersion Model (BLP). As outlined in the August 23, 2010 

clarification memo "Applicability ofAppendix W Modeling Guidance for the I-hour S02 

National Ambient Air Quality Standard", AERMOD is the preferred model for single source 

modeling to address the I-hour S02 NAAQS as part ofthe NSR/PSD permit programs. 

AERMOD is appropriate to inform this designations process because S02 

concentrations result from direct emissions from combustion sources so that concentrations are 

highest relatively close to sources and are much lower at greater distances due to dispersion. 

Given the source-oriented nature ofthis pollutant (See, e.g., 75 FR at 35570), dispersion models 

are the most appropriate air quality modeling tools to predict the near-field concentrations ofthis 

pollutant. 

The AERMOD modeling system includes several components. The regulatory 

components are: 

• 	 AERMOD: the dispersion model (U.S. EPA, 2004a) 

• 	 AERMAP: the terrain processor for AERMOD (U.S. EPA, 2004b) 

• 	 AERMET: the meteorological data processor for AERMOD (U.S. EPA, 2004c) 

• 	 BPIPPRIME: the building input processor (U.S. EPA, 2004d) 

and non-regulatory components are: 

• 	 AERSURFACE: the surface characteristics processor for AERMET (U.S. EPA, 2008) 

• 	 AERSCREEN: a recently released screening version of AERMOD (U.S. EPA, 2011 b) 

Before running AERMOD, the user should become familiar with the user's guides associated 

with the modeling components listed above and the AERMOD Implementation Guide (AlG) 

(U.S. EPA, 2009). The AIG lists several recommendations for applications of AERMOD which 

would be applicable for designations modeling. 

4. Modeling domain 

Selection of the modeling domain is important in terms of how many sources to explicitly 

model and what kind ofreceptor network to create. Two questions may arise in model domain 

selection: 

1. 	 Where to center the modeling domain?, and 

2. 	 How large should the modeling domain be? (i.e., in terms ofthe number ofsources to 

model and size ofthe receptor network in order to account for the areas ofimpact). 

4 
If the modeling is being pcrformed to inform the nonattainmcnt boundary around a violating 

monitor, the domain should be centered on the violating monitor. If the modeling is being done 

to show compliance with the NAAQS in the absence of a violating monitor, the domain should 

be centered on the dominant source in an area, that is, the source or sources expected to 

contribute the most to S02 air quality levels. In both cases, the domain should then extend to 

include nearby sources that are thought to cause or contribute to a potential NAAQS violation, as 

explained further below in Section 4.1. 

The determination of sources to include in modeling is a multi-step process. If modeling 

is being performed for a violating monitor, the first basic step would be to gather information 

and analyze the emission sources within 50 km of the monitor, which is the nominal distance at 

which EPA considers most steady-state Gaussian plume models are applicable. In some cases 

where large S02 sources are scattered outside of the 50 km radius, it may be necessary to extend 

the modeling domain beyond 50 km or conduct mUltiple AERMOD modeling exercises with the 

overall region broken down to several AERMOD runs covering different areas of the potential 

nonattainment area. For these situations, consultation with the appropriate EPA Regional 

Modeling Contact is recommended. 

4.1 	Determining sources to model 

As stated above, the determination ofsources to explicitly model is a multi-step process: 

1. 	 The spatial distribution of all sources within 50 km ofthe violating monitor or dominant 

source should be analyzed and initially assumed to be included in refined dispersion 

modeling. For the purposes ofdesignations it is reasonable to initially focus on the most 

significant sources of S02 emissions, e.g., sources emitting greater than 100 tons per 

year. Please note, however, that sources less than 100 tons can be potential contributors 

to a NAAQS violation, especially sources with short stacks andior located in complex 

terrain (Le., where receptor elevation is above stack height). 

2. 	 Sources should be examined and attempts made to determine if any sources can be 

accounted for without explicitly modeling them, i.e., use of monitored background 

concentrations. Accounting for such sources through the use of a background monitor 

will depend upon how well that monitor reflects impacts from those sources. 

3. 	 Sources found not to be representative by monitored background should also be 

examined through the use ofscreening models to see if they should or should not be 

included in the refined modeling. We recommend the use of EPA's new screening model 

AERSCREEN (US. EPA, 2011b) and following recommendations based onpre-existing 

screening guidance (U.S. EPA, 1992). For small isolated sources, screening may be 

useful on a source by source basis. However, for a cluster of small sources, their 

cumulative impact should also be assessed. Individual sources may not be significant by 

themselves, but together they could cause a NAAQS violation or significantly contribute 

to a NAAQS violation. Although AERSCREEN does not output a design value 

5 
conce,ntration based on the 99th percentile form of the I-hour S02 standard, it do~s output 

the overall maximum I-hour concentration which could be used as a conservative 

,estimate for comparison with the NAAQS and EPA's suggested interim significant 

impact level (SIL) for the I-hour S02 NAAQS of3 ppb5

• If the maximum I-hour 

concentration output from AERSCREEN violates the NAAQS. it does not mean that the 

source is in nonattainment, but that the source should be evaluated using refined 

dispersion modeling (See Step 3 below for more details). 

Figure 1 shows a hypothetical monitor with circles of 50 Ian and 10 km radii centered 

over it. Based on this figure, an example application of these three steps is described below. 

Step 1: Figure I shows facility emissions ranging from less than one ton to over 100 tons per 

year within 50 km of the violating monitor. Most ofthe smaller facilities (less than tcn tons) are 

located north ofthe violating monitor. There are two 100+ ton emitters near the monitor and two 

100+ ton emitters west-southwest of the monitor. At this point, it could be initially assumed that 

all faciHties should be included in refined modeling. 

Step 2: Detennine whether any source or sources can be accounted for by a representative 

background monitor. In Figure 1) there are two other monitors in the area, one north and one 

south of the violating monitor. The northernmost monitor may be representative of the facilities 

north (white and yellow dots) of the violating monitor and the southern monitor may be 

representative of the sources southeast (white and blue dots) ofthe violating monitor. 

Background concentrations should be calculated following the guidance in Section 7 below. 

Step 3: Screening modeling may be used to determine additional sources or combinations of 

sources to be excluded from refined modeling, especially smaller sources whose impacts may be 

largely dependent on their stack parameters (height, exit velocity. etc.). AERSCREEN could be 

used to eliminate such sources through screening modeling. AERSCREEN does not output an 

S02 design value but does output the overall maximum I-hour concentration for an individual 

stack. If a facility contains more than one emission point or stack, each stack should be 

processed in AERSCREEN and the maximum I-hour concentrations can be added together to 

represent impacts from the whole facility after running AERSCREEN. While AERSCREEN can 

be used with the surface characteristics of the source being screened, given the documented 

sensitivity of AERMOD to surface characteristics (Brode et aI., 2008), it may be useful to also 

model the source in AERSCREEN using the surface characteristics of the meteorological site 

being used in the refined modeling as well. to ensure that the source is below de minimis impact 

levels with either set of surface characteristics. 

5 The 3 ppb interim SIL for new 1-hour S02 NAAQS was provided by EPA for states to consider using for PSD 

program in the August 23, 2010 memorandum uGuidance Concerning the Implementation of the 1-hour S02 

NAAQS for the Prevention of Significant Deterioration ProgramU 

6 
FIGURE 1. HYPOTHETICAL EXAMPLE OF VIOLATING MONITOR (STAR) WITH EMISSIONS 

(CIRCLES) WITHIN 50 KM (LARGE CIRCLE) AND 10 KM (INNER CIRCLE). NOTE: OTHER 

MONITORS ARE SHOWN BY PLUS SIGN AND ASTERISKS, WHILE SHADED CONTOURS 

REPRESENT TERRAIN. 

When analyzing AERSCREEN output, the following general criteria could be followed: 

• 	 If the facility's maximum I-hour concentration exceeds 75 ppb, then the source should be 

included in refined dispersion modeling. 

• 	 If the tacility's maximum I-hour concentration is below 75 ppb but above the suggested 

interim I-hour significant impact level of3 ppb or the state's 1-hour SIL, it should be 

included in the refined modeling. 

• 	 If the facility's maximum I-hour concentration is below the suggested interim I-hour 

significant impact level or the state's I-hour SIL. that source may not have to be 

7 
included in refined modeling. However, the facility should not be excluded on the sole 

basis ofbeing below the SIL without first looking at surrounding sources and their 

maximum I-hour concentrations. The case may arise when there are several small 

sources that singularly are below the SIL but their cumulative impact may lead to 

concentrations that contribute to violations ofthe NAAQS. 

In summary for the example in Figure 1, the smaller sources below I ton of emissions to 

the north ofthe monitor may be best represented with the use of background monitor 

concentrations. Other sources between 1 and 10 tons that are not represented by background 

monitors could be excluded based on screening results, depending on their stack parameters and 

terrain. The smaller sources (less than I ton) within 10 km ofthe monitor location may also 

screen out. The 100+ ton sources near the edge of the 50 km domain should be included in 

refined modeling. The largest emitters very close to the sources should be included in refined 

modeling as they are likely contributing to potential NAAQS violations and are not reflected in 

background monitors. 

This is just one example of how to detennine the modeling domain and sources to model. 

In some cases, an analysis out to 50 km may not be needed. Please consult with the appropriate 

EPA Regional Office modeler ifthere is uncertainty in deciding which sources to explicitly 

model, which sources to represent based on background monitoring, andlor which to exclude 

from refined model jng using screening modeling. 

4.2 Receptor grid 

The model receptor grid is unique to the particular situation and depends on the size of 

the modeling domain, the number ofmodeled sources, and complexity ofthe terrain. Receptors 

should be placed in areas that are considered ambient air (i.e., where the public generally has 

access) and placed out to a distance such that areas of violadon can be detected from the model 

output to help determine the size of non attainment areas. Receptor placement should be of 

sufficient density to provide resolution needed to detect significant gradients in the 

concentrations with receptors placed closer together near the source to detect local gradients and 

placed farther apart away from the source. In addition, the user should place receptors at key 

locations such as around facility fence lines (which define the ambient air boundary for a 

particular source) or monitor locations (tor comparison to monitored concentrations for model 

evaluation purposes). The receptor network should cover the modeling domain. An example 

receptor grid for a single source is shown in Figure 2a with an example grid with multiple 

sources shown in Figure 2b. In Figure 2a, receptors are located every 50 m within one kilometer 

ofthe source and then every 100 m from one to two kilometers. From two to 10 km, the receptor 

spacing is 250 m and every 500 m outside of 1 0 km ofthe source. The modeling domain is 

centered on an isolated facility and extends out to 10 km in the east-west and north-south 

direction. Figure 2b shows an example grid for a multi-source area. Two sources are modeled 

with a fine grid ofreceptors J km (50 m spacing) around each source embedded within a lOx I 0 

8 
km grid (250 m spacing). The lOx 1 0 km grid is then embedded within a 20x20 km grid with 

coarser spacing (500 m). 

If modeling indicates elevated levels ofS02 (ncar the standard) near the edge of the 

receptor grid, consideration of expanding the grid or conducting an additional modeling run 

centered on the area of concern should be investigated. As noted above, terrain complexity 

should also be considered when setting up the receptor grid. If complex terrain is included in the 

model calculations, AERMOD requires that receptor elevations be included in the model inputs. 

In those cases, the AERMAP terrain processor (U.S. EPA, 2004b) should be used to generate the 

receptor elevations and hill heights. The latest version of AERMAP (09040) can process either 

Digitized Elevation Model (OEM) or National Elevation Data (NED) data files. The AIG 

recommends the use ofNED data since it is more up to date than OEM data, which is no longer 

updated (Section 4.3 ofthe AlG). 

5. Source inputs 

This section provides guidance on source characterization to develop appropriate inputs 

for dispersion modeling with the AERMOD modeling system. Section 5.] provides guidance on 

use of allowable vs. actual emission levels, Section 5.2 covers guidance on Good Engineering 

Practice (GEP) stack heights, Section 5.3 provides details on source configuration and source 

types, Section 5,4 provides details on urban/rural determination of the sources, and Section 5.5 

provides general guidance on source grouping, which may be important for design value 

calculations. 

5.1 Allowable VB. Actual emissions 

Consistent with past S02 modeling guidance (Section 4.5.2 orD.S. EPA (1994) and 

regulatory modeling for other programs (Appendix W, Section 8.1), dispersion modeling for the 

purposes ofdesignations should be based on the use of maximum allowable emissions or 

federally enforceable permit limits. Also consistent with past and current guidance, in the 

absence of allowable emissions or federally enforceable permit limits, potential to emit 

emissions (Le., design capacity) should be used. Because ofthe short-term nature ofthe new 

S02 NAAQS, the maximum short term or hourly emission rate should be input into AERMOD 

for each modeled hour. As stated in the August 23, 20 I 0 memo, 

"Since short~terrn S02 standards ($ 24 hours) have been in existence for decades, existing 

S02 emission inventories used to support modeling for compliance with the 3~hour and 

24-hour S02 standards should serve as a useful starting point, and may be adequate in 

many cases for use in assessing compliance with the new I-hour S02 standard since 

issues identified in Table 8~2 of Appendix W related to short-term vs. long-term emission 

estimates may have already been addressed." 

9 
a 


X~n(l!rrl) 

b 


·20 •••• , • .. ~ ... "" ....... ~~~, I+ •• ~i •• .,. .. ·r.·.·,., 

·20 ·15 .10 ..s 0 5 10 15 20 

X-dnldlon film) 

FIGURE 2, EXAMPLE RECEPTOR GRIDS WITH (A) A GRID CENTERED ON AN ISOLATED 

SOURCE WITH FENCELINE RECEPTORS SHOWN IN BLUE AND THE EMISSION POINTS 

SHOWN IN BLACK. AND (B) A GRID WITH MULTIPLE SOURCES, 

10 
The existing S02 inventories used for permitting or SIP demonstrati.ons should contain 

the necessary emissions information for designations-related modeling. If short-term emissions 

are not readily available, they may be calculated using the methodology shown in Table 8-2 of 

Appendix W. For an example calculation ofshort term emissions, see the June 28, 20 I 0 

memorandum "Applicability of Appendix W Modeling Guidance for the 1-hour N02 National 

Ambient Air Quality Standard." Although the example is for N02, the calculation methodology 

would be the same for S02. 

Regarding the use of allowable emissions and modeling of intermittent emissions 

sources, from such sources as emergency generators and startup/shutdown emissions~ the 

inclusion of such emissions for the purpose of modeling for S02 designations should follow the 

recommendations in the March 1, 2011 memo"Additional Clarification Regarding Application 

ofAppendix W Modeling Guidance for the 1-hour NO:! National Ambient Air Quality 

Standard." As stated in this memo, EPA believes the most appropriate data to use fbr 

compliance demonstrations for the I-hour N02 NAAQS are those based on emissions scenarios 

that are continuous enough or frequent enough to contribute significantly to the annual 

distribution of maximum daily I-hour concentrations. Although the referenced guidance in this 

memo is for N02 permit modeling, the common I hour averaging time and form of both the N02 

and S02 standards makes this modeling guidance applicable to the I-hour S02 NAAQS and, 

thus, applicable to S02 modeling in support of designations. For more details, refer to the N02 

memo. If any questions arise regarding preparation of emissions inputs for dispersions modeling 

including intermittent emissions from sources, then users should consult the appropriate EPA 

Regional Modeling Contact. 

5.2 Good Engineering Practice «~EP) stack height 

Consistent with previous S02 modeling guidance (U.S. EPA, 1994) and Section 6.2.2 of 

Appendix W, [or stacks with heights that are within the limits ofGood Engineering Practice 

(GEP), actual heights should be used in modeling. Under EPA's regulations at 40 CFR 51.100, 

GEP height, Hg, is determined to be the greater of: 

• 	 65 m, measured from the ground-level elevation at the base of the stack; 

• 	 For stacks in existence on January 12, 1979, and for which the owner or operator had 

obtained all applicable permits or approvals required under 40 CFR Parts 51 and 52 

Hg=2.5H 

provided the owner or operator produces evidence that this equation was actually relied 

on in designing the stack or establishing an emission limitation to ensure protection 

against downwash; 

11 
For all other stacks, 

Hg=H + l.SL, 

where H is the height of the nearby structure(s) measured from the ground-level elevation 

at the base of the stack and L is the lesser dimension of height or projected width of 

nearby structure(s), or 

• 	 the height demonstrated by a fluid model or a field study approved by EPA or the State/local 

agency which ensures that the emissions from a stack do not result in excessive 

concentrations of any air pollutant as a result of atmospheric downwash, wakes, eddy etTccts 

created by the source itself, nearby structures or nearby terrain features. 

For more details about GEP, see the Guideline for Determination of Good Engineering Practice 

Stack Height Technical Support Document (U .S. EPA, 1985). 

Ifstack heights exceed GEP, then OEP heights should be used with the individual stack's 

other parameters (temperature, diameter, exit velocity). For stacks modeled with actual heights 

below GEP, building downwash should be considered as this can impact concentrations near the 

source (Section 6.2.2b, Appendix W). If building downwash is being considered, the 

BPIPPRIME program (U.S. EPA, 2004d) should be used to input building parameters for 

AERMOD. More information about buildings and stacks is in Section 5.3. 

5.3 Source configurations and source types 

An accurate characterization of the modeled facilities is critical for refined dispersion 

modeling, including accurate stack parameters and physical plant layout. Accurate stack 

parameters should be determined for the emissions being modeled. Since modeling would be 

done with maximum allowable or potential emissions levels at each stack, the stack's parameters 

such as exit temperature, diameter, and exit velocity should reflect those emissions levels. 

Accurate locations (Le. latitude and longitude or Universal Transverse Mercator ([JTM) 

coordinates and datum)6 of the modeled emission sources are also important, as this can affect 

the impact of an emission source on receptors, determination ofstack base elevation. and relative 

location to any nearby building structures. Not only are accurate stack locations needed, but 

accurate information for any nearby buildings is important. This information would include 

location and orientation relative to stacks and building size parameters (height, and comer 

coordinates oftiers) as these parameters are input into BPIPPRIME to calculate building 

6 Latitudes and longitudes to four decimal places position a stack within 30 feet of its actual location and five 

decimal places place a stack within three feet orits actual location. Users should use the greatest precision 

available. 

12 
parameters for AERMOO. If stack locations and or building information are not accurate, 

downwash will not be accurately accounted for in AERMOO. 

Emission source type characterization within the modeling environment is also important. 

As stated in the AERMOD User's Guide (U.S. EPA, 2004a). emissions sources can be 

characterized as several different source types: POINT sources, capped stacks (POINTCAP). 

horizontal stacks (POINTHOR), VOLUME sources, OPENPIT sources, rectangular AREA 

sources, circular area sources (AREACIRC), and irregularly shaped area sources (AREAPOL Y). 

Note that POINTCAP and POINTHOR arc not part ofthe regulatory default option in AERMOD 

because the user must invoke the BETA option in the model options keyword MODELOPT 

while not including the "OF AULT'° modeling option for these options to work properly. While 

most sources can be characterized as POINT sources, some sources, such as fugitive releases or 

nonpoint sources (emissions from ports, airports, or smaller point sources with no accurate 

locations) may be best characterized as VOLUME or AREA type sources. If questions arise 

about proper source characterization or typing, users should consult the appropriate EPA 

Regional Modeling Contact. 

5.4 Urban/rural determination 

For any dispersion modeling exercise, the urban or rural detennination of a source is 

important in determining the boundary layer characteristics that affect the model's prediction of 

downwind concentrations. Figure 3 gives example maximum I-hour concentration profiles for a 

10 meter stack (Figure 3a) and a 100 m stack (Figure 3b) based on urban vs. rural designation. 

The urban popUlation used for the examples is 100,000. In Figure 3a, the urban concentration is 

much higher than the rural concentration for distances less than 750 m from the stack but then 

drops below the rural concentration beyond 750 m. For the taller stack in Figure 3b, the urban 

concentration is much higher than the rural concentration even as distances increase from the 

source. These profiles show that the urban or rural designation of a source can be quite 

important. 

In addition, for S02 modeling, the urban/rural detennination is important because 

AERMOD invokes a 4-hour halflife7 for urban S02 sources. This would only be done for urban 

sources when the POLLUTlD keyword in AERMOD is set to "802" and the MODEI"OPT 

keyword includes the OF AULT option. Rural sources within the same AERMOD run would not 

be affected. If the DFAULT option is not included with the MODELOPT keyword, the 4-hour 

half life would not be used and the user would specify the 4-hour half life using the HALFLlFE 

or DCA YCOEFF keywords in order to account for the chemical transformation. See Section 

3.2.6 of the AERMOD User's Guide (U.S. EPA, 2004a) for more details about these keywords. 

lethe user invokes the HALF LIFE or DCAYCOEEF option, then any rural sources included in 

., Over a 4-hour period, SOz concentrations decrease by half from the initial value. 

13 
the modeling would need to be run in separate AERMOD runs so that they are not subject to the 

4-hour half life. Note that ifthe DFAUl:T option is used. the rural sources would not need to be 

in a separate run from the urban sources. Determining whether a source is urban or rural can be 

done using the methodology outlined in Section 7.2.3 of Appendix Wand recommendations 

outlined in Sections 5.1 through 5.3 in the AlG (U.S. EPA, 2009). In summary, there are two 

methods of urban/rural classification described in Section 7.2.3 of Appendix W. 

The first method of urban determination is a land use method (Appendix W. Section 

7.2.3c). In the land use method, the user analyzes the land use within a 3 km radius ofthe source 

using the meteorological land use scheme described by Auer (1978). Using this methodology, a 

source is considered urban if the land use types, II (heavy industrial), 12 (light-moderate 

industrial), Cl (commercial), R2 (common residential), and R3 (compact residential) are 50% or 

more of the area within the 3 km radius circle. Otherwise, the source is considered a rural 

source. The second method uses population density and is described in Section 7.2.3d of 

Appendix W. As with the land use method, a circle of 3 km radius is used. If the popUlation 

density within the circle is greater than 750 peoplclkm2

, then the source is considered urban. 

Otherwise, the source is modeled as a rural source. Ofthe two methods, the land use method is 

considered more definitive (Section 7.2.3e, Appendix W). 

Caution should be exercised with either classification method. As stated in Section 5.1 of 

the AIG (U.S. EPA, 2009). when using the land use method, a source may be in an urban area 

but located close enough to a body ofwater or other non-urban land use category to result in an 

erroneous rural classification for the source. The AIG in Section 5.1 cautions users against using 

the land use scheme on a source by source basis, but advises considering the potential for urban 

heat island influences across the full modeling domain. When using the population density 

method, Section 7.2.3e of Appendix W states, "Population density should be used with caution 

and should not be applied to highly industrialized areas where the population density may be low 

and thus a rural classification would be indicated, but the area is sufficiently built-up so that the 

urban land use criteria would be satisfied ... " With eilher method, Section 7.2.3(1) of Appendix 

W recommends modeling all sources within an urban complex as urban, even ifsome sources 

within the complex would be considered rural using either the land use or population density 

method. 

Another consideration that may need attention by the user and is discussed in Section 5.1 

ofthe AIG relates to tall stacks located within or adjacent to small to moderate size urban areas. 

In such cases, the stack height or effective plume height for very buoyant sources may extend 

above the urban boundary layer height. The application ofthe urban option in AERMOD tor 

these types ofsources may artificially limit the plume height. The use ofthe urban option may 

not be appropriate for these sources, since the actual plume is likely to be transported over the 

urban boundary layer. Section 5.1 ofthe AIG gives details on detennining iCa tall stack should 

be modeled as urban or rural, based on comparing the stack or effective plume height to the 

urban boundary layer height. The 100 m stack illustrated in Figure 3b, may be such an example 

as the urban boundary layer height for this stack would be 189 m (based on a 

14 
10m 

1000,...-,,----1"---. ._-­

a 900~ I 

700 

j j , I J l ~ 

500 1000 15(1() :woo 2500 3000 3500 ~ 4500 5000 

OistllllCt'(III) 

100m 

b 

6 

2 

1 L ~ ! t .. .. ~ 

500 1000 1500 2000 2500 lOOO 3500 4000 4500 5000 

Distance(m) 

FIGURE 3. URBAN (REO) AND RURAL (BLUE) CONCENTRATION PROFILES FOR (A) 10 M 

BUOYANT STACK RELEASE, AND (B) 100 M BUOYANT STACK RELEASE. 

15 
population of 100,000) and equation 104 of the AERMOD fonnulation document (Cimorelli, ct 

al., 2004). This equation is: 

(1) 

where Ziuo is a reference height of 400 m corresponding to a reference population Po of 2,000,000 

people. 

Given that the stack is a buoyant release, the plume may extend above the urban 

boundary layer and may be best characterized as a rural source, even ifit were near an urban 

complex. Exclusion of these elevated sources from application ofthe urban option would need 

to be justified on a case-by-case basis in consultation with the appropriate EPA Regional 

Modeling Contact. 

AERMOD requires the input of urban population when utilizing the urban option. 

PopUlation can be entered to one or two significant digits (Le., an urban population of 1,674,365 

can be entered as 1,700,000). Users can enter multiple urban areas and populations using the 

URBANOPT keyword in the runstream file (U.S. EPA, 2004a). If multiple urban areas are 

entered, AERMOD requires that each urban source be associated with a particular urban area or 

AERMOD model calculations will abort. Urban populations can be dctennined by using a 

method described in Section 5.2 of the AIG (U.S. EPA, 2009), 

5.5 Source groups 

In AERMOD, individual emission sources' concentration results can be combined into 

groups using the SRCGROUP keyword (Section 3.3.11 of the AERMOD User's Guide (U.S, 

EPA,2004a). The user can automatical.ly calculate a total concentration (from all sources) using 

the SRCGROUP ALL keyword. For the purposes of designations and design value calculations, 

source group ALL should be used, especially if all sources in the modeling domain are modeled 

in one AERMOD run. Design values should be calculated from the total concentrations (all 

sources and background). For the purposes of designations modeling, individual source 

contributions outputs to the total concentration may not be necessary. However, if individual 

facility contributions are needed for deciding which facilities to include in the nonattainment or 

attainment area, source groups by facility should he used. To avoid any confusion, source 

groups that are used to calculate the design value concentrations or detennine source 

contributions to design values should be mutually exclusive (Le. an emission source should not 

be in two source groups), This would be especially important if the design value concentrations 

are calculated outside ofAERMOD by adding the individual groups together to calculate a total 

concentration (See Section 8.1 of this docwnent for examples). If individual source groups that 

are used in design value concentrations are not mutually exclusive, there would be double 

16 
counting of concentrations when calculating design values either in AERMOD or outside of 

AERMOD. 

6. Meteorological data 

Section 6 gives guidance on the selection of meteorological data for input into 

AERMOD. Much of the guidance from Section 8.3 ofAppendix W is applicable to designations 

modeling and is summarized here, In Section 6.2.1, the usc of a new tool, AERMINUTE (U.S. 

EPA, 2011a), is introduced. AERMINUTE is an AERMET pre-processor that calculates hourly 

averaged winds from ASOS (Automated Surface Observing System) l-minute winds. 

6.1 Surface characteristics and representativeness 

The selection of meteorological data that are input into a dispersion model should be 

considered carefully. The selection of data should be based on spatial and climatological 

(temporal) representativeness (Appendix W, Section 8.3). The representativeness ofthe data is 

based on: l) the proximity of the meteorological monitoring site to the area under consideration, 

2) the complexity ofterrain, 3) the exposure of the meteorological site, and 4) the period oftime 

during which data are collected. Sources ofmeteorological data are: National Weather Service 

(NWS) stations, site-specific or onsite data, and other sources such as universities, Federal 

Aviation Administration (FAA), military stations, and others. Appendix W addresses spatial 

representativeness issues in Sections 8.3.a and 8.3.c. 

Spatial representativeness ofthe meteorological data can be adversely affected by large 

distmlces between the source and receptors of interest and the complex topographic 

characteristics ofthe area (Appendix W, Section 8.3.a and 8.3.c). If the modeling domain is 

large enough such that conditions vary drastically across the domain then the selection of a 

single station to represent the domain should be carefully considered. Also, care should be taken 

when selecting a station ifthe area has complex terrain. While a source and meteorological 

station may be in close proximity, there may be complex terrain between them such that 

conditions at the meteorological station may not be representative of the source. An example 

would be a source located on the windward side of a mountain chain with a meteorological 

station a few kilometers away on the leeward side ofthe mountain. Spatial representativeness 

for off-site data should also be assessed by comparing the surface characteristics (albedo, Bowen 

ratio, and surface roughness) of the meteorological monitoring site and the analysis area. When 

processing meteorological data in AERMET (U.S. EPA, 2004c), the surface characteristics ofthe 

meteorological site should be used [Section 8.3.c ofAppendix Wand the AERSURFACE User's 

Guide (U.S. EPA 2008)]. Spatial representativeness should also be addressed tor each 

meteorological variable separately. For example, temperature data from a meteorological station 

several kilometers from the analysis area may be considered adequately representative, while it 

may be necessary to collect wind data near the plume height (Section 8.3.c of Appendix W). 

17 
Surface characteristics can be calculated in several ways. For details see Section 3.1.2 of 

the AIG (U.S. EPA,2009). EPA has developed a tool, AERSURFACE (U.S. EPA, 2008) to aid 

in the detennination ofsurface characteristics. The current version of AERSURF ACE uses 1992 

National Land Cover Data. Note that the usc ofAERSURF ACE is not a regulatory requirement 

but the methodology outlined in Section 3.1.2 of the AIG should be followed unless an 

alternative method can be justified. 

6.2 Meteorological inputs 

Appendix W states in Section 8.3.1.1 that the user should acquire enough meteorological 

data to ensure that worst-case conditions are adequately represented in the model results. 

Appendix W states that 5 years ofNWS meteorological data or at least one year of site-specific 

data should be used(Section 8.3.1.2, Appendix W) and should be adequately representative of the 

study area. Ifone or more years (including partial years) of site-specific data are available, those 

data are preferred. While the fonn ofthe S02 NAAQS contemplates obtaining three years of 

monitoring data, this does not preempt the use of 5 years of NWS data or at least one year of 

site-specific data in the modeling. The 5-year average based on the use of NWS data, or an 

average across one or more years of available site specific data, serves as an unbiased estimate of 

the 3-year average for purposes ofmodeling demonstrations of compliance with the NAAQ (See 

the August 23, 2010 Clarification Memorandum on "Applicability of Appendix W Modeling 

Guidance for the I-hour S02 National Ambient Air Quality Standard"). See the memorandum 

for more details on the use of 5 years ofNWS data or at least one year ofsite-specific data and 

applicability to the NAAQS. 

6.2.1 NWS data 

NWS data are available from the National Climatic Data Center (NCDC) in many 

fonnats, with the most common one in recent years being the Integrated Surface Hourly data 

(ISH). Most available formats can be processed by AERMET. As stated in Section 6.1, when 

using data from an NWS station alone or in conjunction with site-specific data, the data should 

be spatially and temporally representative of conditions at the modeled sources. 

A recently discovered issue with ASOS is that 5-second wind data that arc used to 

calculate the 2-minute average winds are truncated rather than rounded to whole knots. For 

example, a wind of 2.9 knots is reported as 2 knots, not 3 knots. To account for this truncation of 

NWS winds (either standard observation or AERMINUTE output), an adjustment of Y2 knot or 

0.26 mls is added to the winds in stage 3 AERMET processing. For more details refer to the 

AERMET User's Guide (U.S. EPA, 2004c) and/or the appropriate EPA Regional Modeling 

Contact. 

18 
6.2.1.1 AERMINUTE 

In AERMOD, concentrations are not calculated for variable wind (Le., missing wind 

direction) and calm conditions, resulting in zero concentrations for those hours. Since the S02 

NAAQS is a one hour standard, these light wind conditions may be the controlling 

meteorological circumstances in some cases because ofthe limited dilution that occurs under low 

wind speeds which can lead to higher concentrations. The excl.usion of a greater number of 

instances of near-calm conditions from the modeled concentration distribution may therefore 

lead to underestimation of daily maximum I-hour concentrations for calculation of the design 

value. 

To address the issues of calm and variable winds associated with the use of NWS 

meteorological data, EPA has developed a preprocessor to AERMET, called AERMINUTE 

(U.S. EPA, 2011 a) that can read 2-minute ASOS winds and calculate an hourly average. 

Beginning with year 2000 data, NCDC has made freely available, the I-minute winds, reported 

every minute from the ASOS network. The AERMINUTE program reads these 2-minute winds 

and calculates an hourly average wind. In AERMET (U.S. EPA, 2004c), these hourly averaged 

winds replace the standard observation time winds read from the archive of meteorological data. 

This results in a lower number of calms and missing winds and an increase in the number of 

hours used in averaging concentrations. For more details regarding the use ofNWS data in 

regulatory applications see Section 8.3.2 of Appendix Wand f'Or more infonnation about the 

processing ofNWS data in AERMET and AERMINUTE, see the AERMET (U.S. EPA, 2004c) 

and AERMINUTE User's guides (U.S. EPA, 2011a). ' 

6.2.2 Site-specific data 

The use of site-specific meteorological data is the best way to achieve spatial 

representativeness. AERMET can process a variety of fonnats and variables for site~specific 

data. The use ofsite-specific data for regulatory applications is discussed in detail in Section 

8.3.3 of Appendix W. Due to the range of data that can be collected onsite and the range of 

fonnats of data input to AERMET, the user should consult Appendix W, the AERMET User's 

Guide (U.S. EPA, 20040), and Meteorological Monitoring Guidance for Regulatory Modeling 

Applications (U.S. EPA, 2000). Also, when processing site-specific data for an urban 

application, Section 3.3 of the AERMOD Implementation Guide offers recommendations f'Or 

data processing. In summary, the guide recommends that site-specific turbulence measurements 

should not be used when applying AERMOD's urban option, in order to avoid doubJe counting 

the effects of enhanced turbulence due to the urban heat island. 

19 

6.2.3 Upper air data 

AERMET requires full upper air soundings to calculate the convective mixing height. 

For AERMOD applications in the U.S., the early morning sounding, usually the 1200 UTC 

(Universal Time Coordinate) sounding, is typically used for this purpose. Upper air soundings 

can be obtained from the Radiosonde Data of North America CD for the period 1946-1997. 

Upper air soundings for 1994 through the present are also available for free download from the 

Radiosonde Database Access website. Users should choose all levels or mandatory and 

significant pressure levels8 when selecting upper air data. Selecting mandatory levels only 

would not be adequate for input into AERMET as the use ofjust mandatory levels wouJd not 

provide an adequate characterization of the potential temperature profile. 

7. Background concentration 

The inclusion of ambient background concentrations to the model results is important in 

determining cumulative impacts. The modeled contribution to the cumulative analysis should 

follow the form of the standard and be calculated as described in Section 2.6.1.2 of the August 

23, 2010 clarification memo on "Applicability of Appendix W Modeling Guidance for the 1­

hour 802 National Ambient Air Quality Standard." This memo suggested a "first tier" approach 

to including a uniform monitored background contribution based on adding the overall highest 

hourly background S02 concentration from a representative monitor to the modeled design 

value. We recognize that this approach could be overly conservative in many cases and may also 

be prone to reflecting source-oriented impacts, increasing the potential for double-counting of 

modeled and monitored contributions. As discussed in EPA's March 1,2011 memo "Additional 

Clarification Regarding Application of Appendix W Modeling Guidance for the I-hour N02 

Ambient Air Quality Standard," we recommend a less conservative "first tier" approach for a 

uniform monitored background concentration based on the monitored design val ues for the latest 

3-year period, regardless of the years of meteorological data used in the modeling. Adjustments 

to this approach may be considered in consultation with the appropriate EPA Regional Modeling 

Contact with adequate justification and documentation of how the background concentration was 

calculated. 

Section 8.2.2 of Appendix W gives guidance on background concentrations for isolated 

single sources and is also applicable for multi-source areas. pne option is, as described in 

Section 8.2.2.b: 

8 By international convention, mandatory levels are in millibars: 1,000,850,700,500, 400, 300, 200, 150, 

100,50,30,20,10,75,3,2, and 1. Significant levels may vary depending on the meteorological conditions at 

the upper-air station 

20 
"Use air quality data in the vicinity of the source to determine the background 

concentration for the averaging times of concern. Determine the mean background 

concentration at each monitor by excluding concentrations when the source in question is 

impacting the monitor ... For shorter time periods, the meteorological conditions 

accompanying concentrations of concern should be identified. Concentrations tor 

meteorological conditions of concern, at monitors, not impacted by the source in 

question, should be averaged for separate averaging time to determine the average 

background value. Monitoring sites inside a 900 degree sector down~ind of the source 

may be used to determine the area of impact." 

When no monitors are located in the vicinity of the sources being modeled a "regional site" (i.e., 

one that is located away from the area of interest but is impacted by similar natural and distant 

man-made sources) may be used to determine background (Section 8.2.2.c, Appendix W), In 

multi-source areas, background includes two components, nearby sources and other sources 

(Section 8.2.3 of Appendix W). Nearby sources are those sources that arc expected to cause a 

significant concentration gradient in the vicinity of the source or sources under consideration, 

and should be explicitly modeled. Identification of nearby sources calls for professional 

judgment and consuJtation with the appropriate EPA Regional Modeling Contact. For other 

sources, such as natural sources. minor sources and distant major sources, the methodology of 

Section 8.2.2 should be used. 

EPA's March 1,2011 memo "Additional Clarification Regarding Application of 

Appendix W Modeling Guidance for the I-hour N02 Ambient Air Quality Standard," describes 

an appropriate methodology of calculating temporally varying background monitored 

concentrations by hour of day and season (excluding periods when the source in question is 

expected to impact the monitored concentration). The methodology for N02 is to use the 98th 

percentile concentration for each hour of the day by season and average across three years. This 

same methodology is applicable to S02 designations modeling based on use of the 99th percentile 

by hour of day and season for background concentration excluding periods when the dominant 

source(s) are influencing the monitored concentration (Le., 99th percentile, or 4th highest, 

concentrations for hour 1 for January or winter, 99tb percentile concentrations tor hour 2 for 

January or winter, etc.). Recent updates included in AERMOD allow for the inclusion of 

temporally varying background concentrations in the design value calculation in combination 

with modeling results. 

An illustrative example is shown in Figure 4. Shown arc the NAAQS standard 

concentration, the monitor's 3-year average design value, and 3-year averages of the 99th 

percentile concentrations by season and hour of day. To calculate the 99th percentile 

concentration for a season and hour of day combination, the second highest concentration for 

that combination should be selected. Also shown are 3-year averages of the 99th percentile 

concentration by hour of day (across all seasons), and the average concentration by hour of day 

21 

across the three years

9

• In this example, the winter background concentrations show a distinct 

diurnal variability, with less for each ofthe other seasons. 

20 

1 "v,."",i.~~--L-.....l-....j 

5 6 7 6 9 1011121314151617181920212223 

Hour of day 

FIGURE 4. S02 MONITORED CONCENTRATIONS FOR VARIOUS AVERAGING TIMES. 

It should be also noted here that the conventions regarding reporting time differ between 

ambient air quality monitoring, where the observation time is based on the hour-beginning 

convention, and meteorological monitoring where the observation is based on the hour-ending 

time. Thus, ambient monitoring data reported for hour 00 should be paired with meteorological 

data for hour 01, etc. This is important when incorporating time-varying background 

9 Modelers should use the lSI-highest value for more detailed pairings, such as month by hour-of-day or 

season by hour-of·day and day-of-week 

22 
concentrations in the AERMOD calculations, which allow for temporally varying background 

concentrations. 

8. Determining design value mctrics 

Designations modeling will provide predictions of S02 design values at each receptor that 

includes contributions from all modeled sources and backgrowld. Based on the form ofthe 1­

hour S02 NAAQS. the design value should be calculated as the average ofthe 99th percentile of 

the annual distribution of daily maximum I-hour concentrations averaged across the modeled 

years. 

8.1 Design value calculation methodology 

Whether design values are calculated within AERMOD or outside of AERMOD, to calculate 

a design value to compare against the standard, the following steps should be rollowed: 

1. 	 At each receptor, for each hour ofthe modeled period, calculate a total concentration 

across all sources including background concentrations if applicable. This can be done in 

AERMOD using SRCGROUP ALL or by adding individual source groups outside of 

AERMOD, using hourly POSTFILEs. Ifthe user is totaling the concentrations outside of 

AERMOD, the source groups need to be mutually exclusive, Le. no one source should be 

in mUltiple source groups. 

2. 	 From the total concentrations calculated in step), obtain the I-hour maximum 


concentration at each receptor for each modeled day. 


3. 	 From the output of step 2, for each year modeled, calculate the 99th percentile (4UI 

highest) daily maximum I-hour concentration at each receptor. If modeling 5 years of 

meteorological data, this results in five 99th percentile concentmtions at each receptor. 

4. 	 Average the 99th percentile (or 4th highest) concentrations across the modeled years to 

obtain a design value at each receptor. 

5. 	 Modeled source contributions to a NAAQS violation can be determined by analyzing the 

hourly concentrations from the individual source groups corresponding to the same hour 

as the 4th daily maximum 1-hour concentration from each year. (See 15 FR at 35540). 

For example, a receptor has a 5-year average design value of200.8 mg/m3 (or 

approximately 71 ppb) and AERMOD was modeled for the period January 1, 2005 

through December 31, 2009 for four source groups. From the AERMOD output, the user 

can determine the date ofthe 4th highest daily maximum I-hour concentrations that arc 

used to calculate the 5-year average design value. Table 1 shows the 4th highest daily 

maximum I-hour concentrations for each year and associated dates that are used in the 

design value calculation. 

23 
TABLE 1. 4TH HIGHEST DAILY MAXIMUM 1~HOUR CONCENTRATIONS (I.IG/M3

) FOR 2005-2009. 

Date Concentration ~.

(YYMMDDHH) 

05080101 200.1 


06073105 
 201.5 

07080403 207.1 


08072705 
 197~ 1 .,,­

09080104 198.1 

5-YEARAVG. 200.8 

If output by source group is available, the user can extract each source group's 

concentration at each of the hours listed in Table I. Table 2 shows example source contributions 

for each hour shown in Table 1 and indicates that Source 1 is the main contributor to the design 

value for all hours. 

TABLE 2. SOURCE CONTRIBUTIONS TO 4TH HIGHEST DAILY MAXIMUM 1~HOUR. 

CONCENTRATIONS (I.IG/M) AND 5·YEAR AVERAGE DESIGN VALUES. 

i;; Date TOTAL SOURCE 1 SOURCE 2 SOURCE 3 SOURCE 4 ' 

MMDDHH) I 

05080101 200.1 155.1 25.1 1.5 18.4

06073105 201.5 157.4 26.2 0.5 17.4

07080403 207.1 161.5 20.5 2.1 23.0 .­

~072705 197.1 159.2 23.1 1.7 13.1~-----j 

09080104 198.1 15§~ ! 20 -~ 

5-YEARAVG. 200.8 157.7 23.5 1.6 1[d 18.0

8.2 Running AERMOD and implications for design value calculations 

Recent enhancements to AERMOD include options to aid in the calculation of design 

values for comparison with the S02 NAAQS. These enhancements include: 

• 	 The output ofdaily maximum I-hour concentrations by receptor for each day in the modeled 

period for a specified source group. This is the MAXDAIL Y output option in AERMOD. 

• 	 The output, for each rank specified on the RECTABLE output keyword, of daily maximum 

I-hour concentrations by receptor for each year for a specified source group. This is the 

MXDYBYYR output option. 

• 	 The MAXDCONT option, which shows the contribution of each source group to the high 

ranked values for a specified target source group, paired in time and space. The user can 

specify a range of ranks to analyze, or specify an upper bound rank. i.e. 4th highest, and a 

lower threshold value, such as the NAAQS for the target source group. The model will 

24 
process each rank within the range specified, but will stop after the 1irst rank (in descending 

order of concentration) that is below the threshold, specified by the user. A warning message 

will be generated if the threshold is not reached within the range of ranks analyzed (based on 

the range ofranks specified on the RECTABLE keyword). This option may be needed to aid 

in determining which sources to include in a nonattainment area. 

Ideally, all explicitly modeled sources, receptors, and background should be modeled in 

one AERMOD run for all modeled years. In this case, the use of the one of the above output 

options can be used in AERMOD to calculate design values for comparison to the NAAQS and 

detennine the area's attainment status and/or infonn attainmentlnonattainment boundaries. The 

use of these options in AERMOD allows AERMOD to internally calculate concentration metrics 

that can be used to calculate design values and therefore lessen the need for large output files, i.e. 

hourly POSTFILES. 

However, there may be situations where a single AERMOD run with all explicitly 

modeled sources is not preferred. These situations often arise due to runtime or storage space 

considerations during the AERMOD modeling. Sometimes separate AERMOD runs are done 

for each facility or group of tacilities, or by year, or the receptor network is divided into separate 

sub-networks. In some types of these situations, the MAXDAILY, MXDYBYYR, or 

MAXDCONT output option may not be an option for design value calculations, especially if all 

sources are not included in a single run. Ifthe user wishes to utilize one ofthe three output 

options, then care should be taken in developing the model inputs to ensure accurate design value 

calculations. 

Situations that would effectively preclude the use ofthe MAXDAIL Y, MXDYBYYR, 

and MAXDCONT option to calculate meaningful AERMOD design value calculations include 

the following examples: 

• 	 Separate AERMOD nms tor each source or groups of sources. 

o 	 Designations modeling includes 10 facilities for five years of NWS data and each 

facility is modeled for five years in a separate AERMOD run, resulting in 10 

separate AERMOD runs. . 

• 	 Separate AERMOD runs for each source and each modeled year. 

o 	 10 facilities are modeled for 5 years ofNWS data. Each facility is modeled 

separately for each year, resulting in fifty individual AERMOD runs. 

In the two situations listed above, the MAXDAIL Y, MXDYBYYR, or, MAXDCONT option 

would not be useful as the different AERMOD runs do not include a total concentration with 

contributions from all tacilities. In these situations the use of hourly POSTFILES, which can be 

quite large, and external post-processing would be needed to calculate design values. 

25 
Situations that may use the MAXDAlL Y, MXDYBYYR, or, MAXDCONT option but 

may necessitate some external post-processing afterwards to calculate a design value include: 

• 	 The receptor network is divided into sections and an AERMOD run, with all sources and 

years, is made for each network. 

o 	 A receptor network of 20,000 receptors is divided into four 5,000 receptor subnetworks. Ten facilities are modeled with five years ofNWS data in one 

AERMOD run for each receptor network, resulting in four AERMOD runs. After 

the AERMOD runs are complete, the MAXDAIL Y, MXDYBYYR, or, 

MAXDCONT results for each network can be re-combined into the larger 

network. 

• 	 All sources and receptors are modeled in an AERMOD run for each year. 

• 	 Ten facilities are modeled with five years ofNWS data. All facilities are modeled with 

all receptors for each year individually, resulting in five AERMOD runs. MAXDAILY, 

MXDYBYYR, or, MAXDCONT output can be used and post-processed to generate the 

necessary design value concentrations. The receptor network is divided and each year is 

modeled separately for each sub-network with all sources. 

Ten facilities are modeled with five years of NWS data for 20,000 receptors. The 

receptor network is divided into four 5,000 receptor networks. For each subnetwork, all tcn facilities are modeled for each year separately, resulting in twenty 

AERMOD runs. MAXDAIL Y, MXDYBYYR, or, MAXDCONT output can be 

used and post-processed to generate the necessary design value concentrations. 

9. 	Use of modeling results to inform nonattainmentJattainment boundaries 

Dispersion modeling is a tool that could be used to examine the spatial extent of potential 

violations ofthe l·hour S02 NAAQS. Thus, in accordance with this guidance. refined 

dispersion modeling could be used to in1brm boundary determinations in support ofthe S02 

designations process, i.e. 

1. 	 For an area that contains a violating monitor, modeling could be used to inform decisions 

on the appropriate nonattainment boundary in conjunction with other factors listed in 

Attachment 2. 

2. 	 For an area without a violating monitor, modeling could be used as evidence of an area's 

attainment status and also to infonn decisions on the appropriate (attainment or 

nonattainment) boundary. 

The shape and size ofthe nonattainment or attainment area is recommended by the state and 

either adopted or modified by EPA. For initial designations, it is expected that states will focus 

on areas with violating monitors. If a county contains a violating monitor, that county would be 

26 
considered in nonattainment. If there are no violating monitors and no dispersion modeling 

results to show attainment or nonattaimnent, that county would general1y be considered 

unclassifiable. 

9.1 Nonattainment area boundaries 

For nonattainment areas (those with a violating monitor). modeling could be used to 

refine the nonattainment area boundaries from the presumptive county boundaries in conjunction 

with other factors such as those listed in Attachment 2. This could include reducing the 

nonattainment area from the presumptive county to a smaner area or expanding the boundary 

beyond the county if sources outside the county contribute to a NAAQS violation in the county. 

A nonattainment area boundary should contain the area that exceeds the NAAQS and include 

sources that may cause or contribute to a NAAQS exceedance. Figure 4 shows a hypothetical 

example of modeling of an area that exceeds the NAAQS (either through monitoring or 

modeling). In each panel of Figure 5, the black dot represents the emission source. In Figure 5a, 

the contours in orange and red are design values that exceed the NAAQS. Figures 5b-5d show 

different approaches to establishing the nonattainment boundary so that the orange and red 

contours arc within the boundary. Tn Figure 5b, the hypothetical nonattainment boundary is a 

circle, centered on the area shown as violating the NAAQS, while Figure 5c shows the 

hypothetical nonattainment boundary as a rectangle. Finally, Figure 5d shows a hypothetical 

nonattainment boundary as an irregular polygon in shape, perhaps based on jurisdictional 

boundaries or other landmarks such as roads. 

Figure 6 illustrates a hypothetical example for a multi-source situation that is ill 

nonattainment. In the example, there are five sources (denoted by blue dots) in a modeling 

domain that covers four counties (A, B, C, and D). The modeling domain is centered on the 

violating monitor (star). The orange contour represents concentrations above the NAAQS. As in 

the single source example shown in Figure 5, the nonattainmcnt area could be circular, 

rectahgular. or irregularly shaped using jurisdictional boundaries. In this example, the 

hypothetical nonattainment boundary would be defined by the northern portion ofCounty A and 

the southern portion of COWlty C. Since multiple sources are involved, the hypothetical 

nonattainment boundary should be extended to cover those sources that cause or contribute to a 

NAAQS violation. In this hypothetical example. Sources 2 and 5 are the largest contributing 

sources to the potential NAAQS violation so the nonattainment boundaries would include those 

two sources. 

27 

c 

a b 

d 

FIGURE 5. HYPOTHETICAL EXAMPLE OF A MODELED NAAQS VIOLATION (RED AND 

ORANGE CONTOURS) AND POSSIBLE NONATTAINMENT AREA BOUNDARIES DEFINED 

BY (B) CIRCLE, (C) RECTANGLE, AND (D) AN IRREGULAR POLYGON. 

28 
a b 

c d 

FIGURE 6. HYPOTHETICAL EXAMPLE OF A MULTI-SOURCE AREA WITH MODELED 

NAAQS VIOLATIONS (ORANGE CONTOUR) AND POSSIBLE NONATTAINMENT AREA 

BOUNDARIES DEFINED BY (8) CIRCLE. (C) RECTANGLE. AND (D) AN IRREGULAR 

POLYGON. 

9.2 Attainment area boundaries 

In areas without a vioJating monitor, modeling couJd be used to help determine that an 

area with S02 emitting sources is in attainment for the J·hour S02 NAAQS. An attainment area 

boundary could not contain any area that exceeds the NAAQS or any area containing sources 

that are causing or contributing to a violating area. When considering attainment area 

boundaries, there will be no predicted area of violation from dispersion modeling so that other 

factors would need to be considered ifthe boundary is not detemlined by using the county 

presumptive boundary. Figure 7 iUustrates a group ofsources where a monitored design value 

does not exceed the NAAQS and modeling also does not show any concentration levels in excess 

ofthe NAAQS. In this case, the state could recommend that county A be considered attainment, 

since the monitor and modeling do not show violations of the NAAQS. Also, ifthere are other 

29 
sources in the remaining three counties (Le., B, C. or D) and their modeled concentration levels 

do not show violations of the NAAQS, then these counties could also be recommended as part of 

the attainment area. 

D 

B 

A 

- -

FIGURE 7. HYPOTHETICAL EXAMPLE FOR AN AREA WITH A MONITOR (STAR) THAT 

DOES NOT VIOLATE THE NAAOS AND MODELING RESULTS FOR SOURCES (BLUE DOTS) 

THAT DO NOT SHOW A VIOLATION OF THE NAAOS. 

10. Documentation 

It is expected that the state would submit a modeling and analysis protocol that details the 

methodology and model inputs before commencement of the modeling exercise. This 

information should support the states' recommended designations, and provide a basis for EPA's 

evaluation ofthe recommendations. The protocol should include the following: 

30 
• 	 Characterization of the nonattainment problem or characterization ofthe modeled area in 

absence of a violating monitor, 

• 	 An emissions analysis around the violating monitor or area under consideration for 

designations in absence of a violating monitor. and 

• 	 Methodology for preparing air quality and meteorology inputs including choice of 

meteorological data and representativeness of the data. 

Additionally, the documentation should include: 

• 	 Summary and analysis ofmodeling results, and 

• 	 Provision of modeling data inputs and outputs in electronic form. 

A meeting with the appropriate EPA Regional Modeling Contact and other technical and 

planning staff to discuss the modeling and analysis protocol is recommended before submitting 

the protocol and beginning any refined modeling. 

11. 	Summary 

In summary, we emphasize the following key points of this modeling guidance: 

• 	 AERMOD is EPA's preferred near-field dispersion model for regulatory applications and 

is applicable for S02 designations modeling consistent with EPA's Guideline onA;r 

Quality Models, also published as Appendix W of40 CFR Part 51. 

• 	 Sources should be modeled with maximum allowable 1 ~hour or shorHerm emission rates 

in the designations modeling based on continuous operations at the source. 

• 	 Modeling should be done with five years of representative NWS meteorological data or 

at least one year ofsite specific meteorology. 

• 	 Background concentrations can be included as: 

o 	 "First tier" approach based on monitored design values added to modeled design 

values; or 

o 	 Temporally varying based on the 99th percentile monitored concentrations by hour 

of day and season added to modeled design values. 

• 	 Dispersion modeling results could be used to inform the nonattainmcnt or attainment 

areas in conjunction with other designations factors. 

• 	 States should submit a modeling and analysis protocol that details the methodology and 

model inputs before commencement of the modeling exercise. This information should 

support the states' recommended designations, and provide a basis for EPA's evaluation 

of the recommendations.· 

31 
• 	 At any time during the designations process when there are questions regarding modeling 

or interpretation ofthis guidance, the appropriate EPA Regional Modeling Contact 

should be consulted. 

12. References 

Auer, Jr., A.H., 1978: Correlation of Land Use and Cover with Meteorological Anomalies. 

Journal ofApplied Meteorology, 17(5),636·643. 

Brode, R., K. Wesson, 1. Thurman. and C. Tillerson, 2008: AERMOD Sensitivity to the Choice 

of Surface Characteristics, Paper 811, Air And Waste Management Association Annual 

Conference. 

Cimorelli, A. 1., S. G. Perry, A. Venkatram, J. C. Weil, R.J. Paine, R. B. Wilson, R. F. Lee, W. 

D. Peters, R. W. Brode, and 1. O. Paumier, 2004: AERMOD: Description of Model 

Formulation, EPA-454/R-03-004. U.S. Environmental Protection Agency, Research 

Triangle Park, NC. 

U.S. EPA, 1985: Guideline for Determination of Good Engineering Practice Stack Height 

(Technical Support Document for the Stack Height Regulations), Revised. EPA-450/4­

80-023R. U.S. Environmental Protection Agency, Research Triangle Park, NC 27711. 

U.S. EPA, 1992: Screening Procedures for Estimating the Air Quality Impact of Stationary 

Sources. EPA-454/R-92-019. U.S. Environmental Protection Agency, Research Triangle 

Park, NC 27711. 

U.S. EPA, 1994: 	S02 Guideline Document. EPA-452/R-95·008. U.S. Environmental Protection 

Agency, Research Triangle Park, NC 27711. 

U.S. EPA, 2000: Meteorological Monitoring Guidance for Regulatory Modeling Applications. 

EPA-454/R-99-005. U.S. Environmental Protection Agency, Research Triangle Park, NC 

2771 L 

U.S. EPA, 2004a: User's Guide for the AMS/EPA Regulatory Model 	 AERMOD. EPA-454/B03-001. U.S. Environmental Protection Agency, Research Triangle Park, NC 27711. 

U.S. EPA, 2004b: User's Guide for the AERMOD Terrain Preprocessor(AERMAP). EPA454/8-03-003. U.S. Environmental Protection Agency, Research Triangle Park, North 


Carolina 27711. 


U.S. EPA, 2004c: 	User's Guide for the AERMOD Meteorological Preprocessor (AERMET). 

EPA-454/B-03-002. U.S. Environmental Protection Agency, Research Triangle Park, 

NC 27711. 

32 
U.S. EPA, 2004d: User's Guide to the Building Profile Input Program. EPA-454/R·93-038. U.S. 

Environmental Protection Agency, Research Triangle Park, North Carolina 27711. 

U.S. EPA, 2005. Guideline (m Air Quality Models. 40 CPR Part 51 Appendix W. 

U.S. EPA, 2008: AERSURFACE User's Guide. EPA-4S4/B-08-00L U.S. Environmental 

Protection Agency, Research Triangle Park, North Carolina 27711. 

U.s. EPA, 2009: AERMOD Implementation Guide. U.s. Environmental Protection Agency, 

Research Triangle Park, North Carolina 2771 t. 

U.S EPA, 2011a: AERMfNUTE User's Guide. U.S. Environmental Protection Agency, 

Research Triangle Park, North Carolina 27711. 

U.S EPA, 20l1b: AERSCREEN User's Guide. EPA-454-/B-II-001. U.S. Environmental 

Protection Agency, Research Triangle Park, North Carolina 27711. 

33