1 

# Guidance on the use of models for assessing the impacts of emissions from single sources on the secondarily formed pollutants ozone and PM2.52 

### EPA-454/P-15-001 July 2015

Guidance on the use of models for assessing the imp acts of emissions from single sources on

the secondarily formed pollutants ozone and PM2.5

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Analysis Division Air Quality Modeling Group Research Triangle Park, NC3



## Executive Summary

The purpose of this document is to provide guidance on how to assess the air quality impact on ozone and secondary particulate matter from individual so urces (either new sources or modifications to existing sources) as part of the New Source Review (NSR), Prevention of Significant Deterioration (PSD ), or other programs. Sources are required to estimate both the impacts of primarily emitted and secondarily formed pollutants. AERMOD, which is a s teady-state gaussian plume dispersion model, is EPA’s preferred model for estimating project source impacts for primarily emitted pollutants, includin g primarily emitted PM2.5 (U.S. Environmental Protect ion Agency, 2005). This guidance outlines procedures for estimating O 3 or secondarily formed PM2.5 impacts from project s ources for the purposes of permit review programs.

To date, the EPA has issued some guidance to assist sources needing to demonstrate compliance with the PM2.5 NAAQS and PSD increments, including consi deration of the secondarily formed components
of PM2.5. In Guidance for PM2.5 Permit Modeling (U.S. Environmental Protection Agency, 2014a), the EPA identified three different approaches for asses sing the secondary PM2.5 impacts: a qualitative assessment, a hybrid qualitative/quantitative asses sment that utilizes existing technical work, and a full quantitative photochemical grid modeling exercise. Previously for PM2.5 (and currently for ozone), the appropriate analytical technique for assessing the air quality impact of project source emissions on secondarily formed pollutants was determined on a c ase-by-case basis in consultation with the permitting authority.

The degree of complexity required to assess potenti al secondary pollutant impacts from single sources varies depending upon the nature of the source, its emissions, and the background environment. A twotiered approach for addressing single-source impact s on ozone and secondary PM2.5 has been proposed by EPA (Preamble, Appendix W NPRM, 2015) to provide permit applicants flexibility for these assessments. The first tier involves use of appropr iate and technically credible relationships between emissions and impacts developed from existing infor mation that is deemed sufficient for evaluating a source’s impacts. The second tier involves more sop histicated case-specific chemical transport modelin g (e.g. with an Eulerian grid or Lagrangian puff phot ochemical model). The appropriate tier for a given permit application should be selected in consultati on with the appropriate permitting authority. This document is intended to provide more detail for app licants seeking to estimate single source impacts o n secondary pollutants for purposes of comparison to a SIL or level of the NAAQS under the first (Sectio ns 5.3.2.b and 5.4.2.b) and second (Sections 5.3.2.c a nd 5.4.2.c) tiers outlined in Appendix W.

The first tier screening-level approaches for estim ating single source secondary impacts described in the 2015 revision to Appendix W are intended to reduce burden on sources that can rely on existing information to characterize their impacts. Addition al information is provided here about the types of analysis and options that could satisfy the require ments of a first tier (Sections 5.3.2.b and 5.4.2.b ) assessment under Appendix W. For first tier assessm ents, it is generally expected that applicants woul d use existing empirical relationships between precur sors and secondary impacts based on modeling systems appropriate for this purpose as detailed in this guidance. It is also possible screening approaches based on full science chemical transport modeling systems (e.g. reduced form models) could provide information to satisfy the first tier in so me situations. The use of pre-existing credible tec hnical information or a screening model for the purposes o f estimating single source secondary impacts will b e considered on a case-by-case basis and should be do ne in consultation with the appropriate permitting authority.4

Examples of existing relevant technical information include air quality modeling for sources with simi lar or larger emissions in similar atmospheric environm ents for appropriate time periods that are conduciv e to the formation of O 3 or secondary PM2.5. EPA has extensively reviewed e xisting published technical reports and peer-reviewed literature that provide s ingle source impact estimates for O 3 and secondary PM2.5 (U.S. Environmental Protection Agency, 2015). However, it is important to note that published research studies were not designed specifically for the purposes of estimating single source secondary impacts for regulatory review. Therefore these stud ies may not have applied models for relevant time periods or post-processed results in a way consiste nt with methods preferred for this purpose.

For second tier assessments (Sections 5.3.2.c and 5 .4.2.c) when necessary, guidance is provided on the air quality models, inputs, run time options, recep tor placement, and application approach for the purposes of estimating the impacts on ozone and sec ondarily formed PM2.5 from single project sources. Within the second tier described in Appendix W, app licants are provided flexibility in terms of the complexity of model application for comparison to b oth the SIL and NAAQS. The sub-tiers of the Appendix W second tier allow for simpler approaches to be compared conservatively to the SIL and NAAQS and more sophisticated approaches could be ap plied to provide a more representative impact
for a source.

Estimating single source impacts can be done using a Lagrangian modeling system that includes O 3 and PM2.5 chemistry or photochemical grid models. In th e simplest case, a model simulation containing the project source emitting at post-construction condit ions is compared to a baseline simulation where the source is operating at pre-construction conditions or not included if the project source is new construction (See Figure 1). More details about the se scenarios are provided in section 4.7.

Figure 1. Simplified representation of modeling sin gle source secondary impacts using Lagrangian puff or photochemical grid models. This does not represent the process when a source emits both primary PM2.5 and PM2.5 precursor emissions (see section 6. 1 for this case).



## Baseline Conditions Scenario (1) Project Source Scenario (2) Project Source

Contribution Estimate (2-1)

• Model simulation with

baseline conditions and the
project source operating at preconstruction conditions (or not

in the simulation if a new source) • Model simulation with

baseline conditions and the
appropriate project source emissions adjustments • Estimated by difference

between the simulation with

baseline conditions and the
appropriate project source adjustments (2) and model

simulation with baseline conditions only (1)5

Once project source contributions have been estimat ed as detailed through procedures outlined in this guidance document those impacts are compared to the appropriate significant impact level (SIL) and the level of the appropriate NAAQS if a cumulative asse ssment is necessary. A simplified schematic of this process and some illustrative examples of the flexi bility afforded with each sub-tier of the significa nt impact analysis and cumulative impact analysis are shown in Figure 2.

Figure 2. Simplified schematic of the “second tier” process for assessing secondary pollutant impacts from source emissions with a significant impact ana lysis and cumulative impact analysis (if needed). T his does not represent the process when a source emits both primary PM2.5 and PM2.5 precursor emissions (see section 6.1 for this case).

Project Source
Contribution Estimate Estimated by difference between the simulation with baseline conditions with the appropriate project source adjustments and model simulation wit h baseline conditions only. See sections 5.3, 5.4, and 5.5 for NAAQS specific estimation app roaches.

Significant Impact Analysis Project source contribution estimate compared to NA AQS appropriate Significant Impact Level

(SIL). Sections 6.2.1, 6.3.1, and 6.4.1 provide mor e details about NAAQS specific impact comparison to the SIL.

Significant Impact Analysis Level 1 The modeled highest impact over all receptors shoul d be compared to the SIL. Model options include Lagrangian or photochemical transport model

.

Significant Impact Analysis Level 2 A more refined approach than level 1. This may incl ude the tool used for impact estimation (photochemical grid rather than Lagrangian model), configuration options for such tool (e.g. more refined grid resolution), or inclusion of addi tional representative episodes. After consultation with the permitting authority, a value less than the maximum impact could be used for comparison to the SIL.

Cumulative Impact Analysis Project source contribution estimate compared to NA AQS appropriate Significant Impact Level

(SIL) and also combined with an estimate of “backgr ound” for comparison to the level of the appropriate NAAQS. Sections 6.2.2, 6.3.2, and 6.4.2 provide more details about NAAQS specific cumulative impact assessments.

Cumulative Impact Analysis Level 1 The highest contribution from the project source ov er all receptors should be added to the highest monitored design value in the same area. Mo del options include Lagrangian or photochemical transport model.

Cumulative Impact Analysis Level 2 A more refined approach than level 1. This may incl ude the tool used for impact estimation, configuration options for such tool, or inclusion o f additional representative episodes. Here, the highest contribution from the project source on high modeled days at each receptor should be added to the monitored design value at that same receptor or an approved interpolated field of monitored design values and compared to th e level of the NAAQS. After consultation with the permitting authority, a value less than th e maximum impact could be used for addition to background estimates and comparison to the NAAQS.6

The schematic shown in Figure 2 is relevant for O 3 impacts and sources that do not emit primary PM2.5 emissions. For project sources that emit both prima ry PM2.5 and PM2.5 precursors an alternative construct is provided. For those situations, the me thods and approaches described here for estimating single source secondary PM2.5 impacts are used as a n input to AERMOD as an addition to the “BACKGROUND” concentration input variable and estab lished procedures are followed for the application of AERMOD for permit source application s as described in Appendix W. This approach takes advantage of existing well known procedures for AER MOD application and community expertise with the AERMOD modeling system. It is not expected that all situations would necessitate rigorous chemical transport modeling to provide AERMOD with an estima te of secondary PM2.5 from the project source. The selection of project-specific secondary PM2.5 i mpacts should be done in consultation with the appropriate permitting authority and be consistent with EPA guidance.

This document is consistent with the recommendation s for air quality modeling in the “Guideline on Air Quality Models” (Appendix W to 40 CFR Part 51), her eafter referred to as Appendix W (U.S. Environmental Protection Agency, 2005). Hereafter, references to “Appendix W” refer to both the proposed 2015 revisions and existing form. Informat ion presented here is intended to expand upon the principles set forth in Appendix W for estimating s ingle source impacts for permit review purposes.7



## Table of Contents

1 Background ......................................

................................................... .................................................. 9

2 Modeling systems for estimating secondary impacts

.................................................. ........................ 9

2.1 Lagrangian modeling systems ...................

................................................... ............................... 10

2.2 Eulerian photochemical grid models ............

................................................... ........................... 11

2.3 Elements of a model protocol ..................

................................................... ................................ 12

3 Relevant existing information or “First Tier” ass essment of single source impacts on O 3 and secondary PM2.5 ...................................

................................................... .................................................. 13

4 Refined or “Second Tier” assessment of single sou rce impacts on O 3 and secondary PM2.5 ........... 14

4.1 Model inputs ..................................

................................................... .......................................... 14

4.1.1 Project source emissions.....................

................................................... ............................. 14

4.1.2 Nearby source emissions .....................

................................................... ............................ 14

4.1.3 Meteorology inputs...........................

................................................... ............................... 14

4.2 Episode selection .............................

................................................... ........................................ 15

4.3 Receptor placement and domain extent ..........

................................................... ....................... 16

4.4 Vertical domain resolution ....................

................................................... .................................. 16

4.5 Horizontal domain resolution ..................

................................................... ................................ 17

4.6 Use of photochemical grid models for single sou rce impact assessments ............................ .... 17

4.7 Use of lagrangian models for single source impa cts ............................................... ................... 18

4.8 Model evaluation ..............................

................................................... ....................................... 19

4.9 Project-specific modeling .....................

................................................... .................................... 20

5 Appropriate processing of modeled estimates & bac kground ........................................... ................ 21

5.1 Operational definition of particulate matter ..

................................................... ......................... 21

5.2 “Absolute” and “Relative” modeling approaches .

................................................... ................... 21

5.3 Estimating the O 3 impact from a project source .....................

................................................... 21

5.4 Estimating the annual PM2.5 impact from a proje ct source ......................................... ............. 22

5.5 Estimating the daily PM2.5 impact from a projec t source .......................................... ............... 22

5.6 Background concentrations .....................

................................................... ................................ 22

6 Regulatory assessment: PSD ......................

................................................... ...................................... 23

6.1 Sources emitting both primarily emitted PM2.5 a nd PM2.5 precursors ............................... ..... 23

6.2 Assessments of 8-hr Ozone impacts .............

................................................... ........................... 238

6.2.1 Assessments of 8-hr Ozone impacts – significa nt impact analysis ................................ ..... 24

6.2.2 Assessments of 8-hr Ozone impacts – cumulativ e impact analysis ................................. ... 24

6.3 Assessment of sources only emitting PM2.5 precu rsors: annual PM2.5 ............................... ..... 25

6.3.1 Assessments of annual average PM2.5 impacts – significant impact analysis ................... 25

6.3.2 Assessments of annual average PM2.5 impacts – cumulative impact analysis .................. 25

6.4 Assessment of sources only emitting PM2.5 precu rsors: daily PM2.5 ................................ ....... 26

6.4.1 Assessments of daily average PM2.5 impacts – significant impact analysis ...................... 26

6.4.2 Assessments of daily average PM2.5 impacts – cumulative impact analysis ..................... 26

7 Regulatory assessment: nonattainment NSR ........

................................................... .......................... 27

7.1 Assessments of 8-hr ozone impacts .............

................................................... ............................ 27

7.2 Assessments of PM2.5 impacts ..................

................................................... .............................. 28

8 Regulatory assessment: Economic Development Zones

.................................................. .................. 28

9 References ......................................

................................................... ................................................. 2 99



## 1 Background

Sources with proposed modifications or new sources may be required to estimate the air quality impacts of these emissions as part of the New Source Review (NSR), Prevention of Significant Deterioration (PSD), or other programs. Sources are required to e stimate both the impacts of primarily emitted pollutants and secondarily formed pollutants. Stead y-state Gaussian plume dispersion models such as AERMOD are used to estimate the impacts of chemical ly inert (primarily emitted) compounds (U.S. Environmental Protection Agency, 2005).

To date, the EPA has issued some guidance to assist sources needing to demonstrate compliance with the PM2.5 NAAQS and PSD increments, including consi deration of the secondarily formed components
of PM2.5. In Guidance for PM2.5 Permit Modeling (U.S. Environmental Protection Agency, 2014a), the EPA identified three different approaches for asses sing secondary PM2.5 impacts: a qualitative assessment, a hybrid qualitative/quantitative asses sment utilizing existing technical work, and a full quantitative photochemical grid modeling exercise. Previously for PM2.5 (and currently for ozone), the appropriate analytical technique for assessing the air quality impact of project source emissions on secondarily formed pollutants was determined on a c ase-by-case basis in consultation with the permitting authority.

For assessing secondary pollutant impacts from sing le sources, the degree of complexity required to assess potential impacts varies depending upon the nature of the source, its emissions, and the background environment. A two-tiered approach for a ddressing single-source impacts on ozone and secondary PM2.5 has been proposed by EPA (preamble for 2015 Appendix W NPRM) to provide the user community flexibility in estimating these impacts. The first tier involves use of technically credible and appropriate relationships between emissions and imp acts developed from previous modeling that is deemed sufficient for evaluating a source’s impacts . The second tier involves application of more sophisticated case-specific photochemical modeling analyses, which is the focus of this document. The appropriate tier for a given permit application sho uld be selected in consultation with the appropriat e permitting authority and be consistent with EPA gui dance. The EPA’s expectation is that the first tie r should be appropriate for most permit applicants; t he second tier may only be necessary in special situations. Also, to further assist permit applica nts, the EPA is considering undertaking a rulemakin g to provide screening tools for this purpose.

This document describes the air quality models, inp uts, run time options, receptor placement, and application approach for the purposes of estimating the impacts on ozone and secondarily formed PM2.5 from single project sources. This document is consistent with the recommendations for air quality modeling in the “Guideline on Air Quality M odels” (Appendix W to 40 CFR Part 51), hereafter referred to as Appendix W (U.S. Environmental Prote ction Agency, 2005). These recommendations are considered relevant for both the 2015 proposed revi sions to Appendix W and existing form.



## 2 Modeling systems for estimating secondary impacts

Quantifying secondary pollutant formation requires simulating chemical reactions and thermodynamic gas-particle partitioning in a realistic chemical a nd physical environment. Chemical transport models treat atmospheric chemical and physical processes s uch as deposition and transport. There are two types of chemical transport models which are differ entiated based on a fixed frame of reference10

(Eulerian grid based) or a frame of reference that moves with parcels of air between the source and receptor point (Lagrangian) (McMurry et al., 2004).

A variety of Lagrangian and Eulerian modeling syste ms exist that could potentially be used to estimate single source impacts on secondarily formed polluti on such as ozone and PM2.5. These modeling systems represent varying levels of complexity in t he treatment of plume chemistry and the chemical and physical environment in which the plume exists. It is important that any Lagrangian or Eulerian modeling system be appropriately applied for assess ing the impacts of single sources on secondarily formed pollutants such as ozone and PM2.5 for the p urposes of permit review. This means that existing guidance for dispersion models and photochemical mo dels developed for other purposes may not be totally applicable for this type of assessment. Sou nd science and appropriate purpose are the fundamental basis of the approaches described for a ssessing single source impacts on secondarily formed pollutants.

This section describes tools that are best suited f or the purpose of estimating single source secondar y pollutant impacts. For a variety of regulatory prog rams secondary pollutant impacts such as O 3 and PM2.5 need to be assessed near the emitting source and sometimes long-range transport to key downwind receptors. It is important that modeling s ystems used for these assessments be fit for this purpose and have been evaluated for skill in replic ating meteorology and atmospheric chemical and physical processes that result in secondary polluta nt formation and deposition.

A candidate model for use in estimating single sour ce impacts on secondarily formed pollutants such as ozone and PM2.5 for the purposes of permit review p rograms should meet the general criteria for an “alternative model” outlined in 40 CFR part 51, App endix W, section 3.2 (U.S. Environmental Protection Agency, 2005). The acceptability of a particular mo del and approach for that model application is an E PA Regional Office responsibility that should include consultation with EPA’s Model Clearinghouse, if appropriate.



### 2.1 Lagrangian modeling systems

Lagrangian modeling systems that have been used to assess single source impacts in North America include CALPUFF, HYSPLIT, FLEXPART, SCIPUFF, and SC ICHEM. Some Lagrangian models treat in-plume gas and particulate chemistry. These models require time and space varying oxidant concentrations, and in the case of PM2.5 also neutralizing agents such as ammonia, as important secondary impacts happen when plume edges start to interact with the surroun ding chemical environment (Baker and Kelly, 2014; ENVIRON, 2012). These oxidant and neutralizing agen ts are not routinely measured, but can be generated with a three dimensional photochemical tr ansport model and subsequently input to a Lagrangian modeling system.

The Second-order Closure Integrated PUFF model with chemistry (SCICHEM) is an extension of the Second-order Closure Integrated PUFF model (SCIPUFF ) and simulates in-plume chemistry and subsequent transport and dispersion using second or der closure to solve turbulent diffusion equations using spatially and temporally variant meteorologic al input (Sykes et al., 1998). SCICHEM is a non-ste ady state puff dispersion model treating both O 3 and PM2.5 formation and their fate in the atmosphe re (Chowdhury et al., 2010). CALPUFF is a multi-specie non-steady state puff dispersion model that treats pollutant emissions, transport, represents some che mical processes, and deposition using temporally and spatially variant meteorological inputs (Scire et al., 2000). The CALPUFF system estimates primary and secondary PM2.5 but O 3 is input to the model and not estimated (Scire et al., 2000).11



### 2.2 Eulerian photochemical grid models

Photochemical grid models are three-dimensional gri d-based models that treat chemical and physical processes in each grid cell and use Eulerian diffus ion and transport processes to move chemical specie s to other grid cells (McMurry et al., 2004). Photoch emical models are advantageous by providing a spatially and temporally dynamic realistic chemical and physical environment for plume growth and chemical transformation (Baker and Kelly, 2014; Zhou et al., 2012). Publically available and documented Eulerian photochemical grid models such as the Comp rehensive Air Quality Model with Extensions (CAMx) (ENVIRON, 2014) and the Community Multiscale Air Quality (CMAQ) (Byun and Schere, 2006) model treat emissions, chemical transformation, tra nsport, and deposition using time and space variant meteorology. These modeling systems include primari ly emitted species and secondarily formed pollutants such as ozone and PM2.5 (Chen et al., 20 14; Civerolo et al., 2010; Russell, 2008; Tesche et al., 2006). These models have been used extensively to s upport State Implementation Plans and to explore relationships between inputs and air quality impact s in the United States and beyond (Cai et al., 2011 ; Civerolo et al., 2010; Hogrefe et al., 2011).

Even though single source emissions are averaged in to a grid volume, photochemical transport models have been shown to adequately capture single source impacts when compared with downwind in-plume measurements (Baker and Kelly, 2014; Zhou et al., 20 12). Where set up appropriately for the purposes of assessing the contribution of single sources to primary and secondarily formed pollutants, photochemical grid models could be used with a vari ety of approaches to estimate these impacts. These approaches generally fall into the category of sour ce sensitivity (how air quality changes due to chan ges in emissions) and source apportionment (the contrib ution of a specific source emissions to a receptor under existing ambient conditions).

The simplest source sensitivity approach (brute-for ce change to emissions) would be to simulate two sets of conditions, one with all emissions and one with a new source or a source of interest modified to reflect changes in operation (Cohan and Napelenok, 2011). The difference between these simulations provides an estimate of the air quality change rela ted to the change in emissions from the project source. Another source sensitivity approach to diff erentiate the impacts of single sources on changes in model predicted air quality is the decoupled direct method (DDM), which tracks the sensitivity of an emissions source through all chemical and physical processes in the modeling system (Dunker et al., 2002). Sensitivity coefficients relating source emi ssions to air quality are estimated during the mode l simulation and output at the resolution of the host model.

Some photochemical models have been instrumented wi th source apportionment, which tracks emissions from specific sources through chemical tr ansformation, transport, and deposition processes to estimate a contribution to predicted air quality at downwind receptors (Kwok et al., 2015; Kwok et al., 2013). Source apportionment has been used to differ entiate the contribution from single sources on model predicted ozone and PM2.5 (Baker and Foley, 2 011; Baker and Kelly, 2014). DDM has also been
used to estimate O 3 and PM2.5 impacts from specific sources (Baker and Kelly, 2014; Bergin et al., 2008; Cohan et al., 2005; Cohan et al., 2006; Kelly et al ., 2015) as well as the simpler brute-force sensiti vity approach (Baker and Kelly, 2014; Bergin et al., 200 8; Kelly et al., 2015; Zhou et al., 2012). Limited comparison of single source impacts between models (Baker et al., 2013) and approaches to differentiate single source impacts (Baker and Kell y, 2014; Cohan et al., 2006; Kelly et al., 2015) sh ow generally similar downwind spatial gradients and im pacts.12



### 2.3 Elements of a model protocol

A model protocol is intended to communicate the sco pe of the analysis. This document generally includes the types of analysis performed, the speci fic steps taken in each type of analysis, the ratio nale for the choice of modeling system, names of organiz ations participating in preparing and implementing the protocol, and a complete list of model configur ation options. The protocol should detail and formalize the procedures for conducting all phases of the modeling study, such as describing the background and objectives for the study, creating a schedule and organizational structure for the stud y, developing the input data, conducting model perform ance evaluations, interpreting modeling results, describing procedures for using the model to demons trate whether regulatory levels are met, and producing documentation to be submitted for review and approval. Protocols should include the following elements at a minimum.

1. Overview of Modeling/Analysis Project

• Participating organizations

• Schedule for completion of the project

• Description of the conceptual model for the project source/receptor area

• Identify how modeling and other analyses will be ar chived and documented

• Identify specific deliverables to the review author ity

2. Model and Modeling Inputs

• Rationale for the selection of air quality, meteoro logical, and emissions models

• Modeling domain specifications

• Horizontal resolution, vertical resolution and vert ical structure

• Episode selection and rationale for episode selecti on

• Description of meteorological model setup

• Description of emissions inputs

• Specification of initial and boundary conditions

• Methods used to quality assure emissions, meteorolo gical, and other model inputs

3. Model Performance Evaluation

• Identify relevant ambient data near the project sou rce and key receptors; provide relevant performance near the project source and key recepto r locations

• List evaluation procedures

• Identify possible diagnostic testing that could be used to improve model performance

4. Model Outputs

• Describe the process for extracting project source impacts including temporal aggregation and in the case of PM2.5 chemical species aggregation13



## 3 Relevant existing information or “First Tier” ass essment of single source impacts on O 3 

## and secondary PM2.5

This section is intended to provide more detail for applicants seeking to estimate single source impac ts on secondary pollutants for purposes of comparison to a SIL or level of the NAAQS under the first tier outlined in Appendix W (Sections 5.3.2.b and 5.4.2. b). More refined approaches that would fall under
the second tier are described in the sections subse quent to this chapter.

Under the first tier, existing technical informatio n is used in combination with other supportive information and analysis for the purposes of estima ting secondary impacts from a particular source. Th e existing technical information should provide a cre dible and representative estimate of the secondary impacts from the project source. In these situation s, a more refined approach for estimating secondary pollutant impacts from project sources may not be n ecessary where agreement is reached with the permitting authority.

EPA has been compiling and reviewing screening mode ls, screening approaches, and reduced form models that are based on technically credible tools (e.g. photochemical grid models) that relate sourc e precursor emissions to secondary impacts. A review of existing approaches detailed in peer reviewed journal articles and non-peer reviewed forms (e.g. technical reports, conference presentations) indica tes a very limited number of screening approaches have been developed and fewer still have been fully documented and tested for robust application (U.S. Environmental Protection Agency, 2015). One example of a reduced form model is the development of a tool for the New South Wales (NSW) Greater Metropolitan Region in Australia (Yarwood et al., 2 011). High O 3 impact days are modeled using a photochemical grid model with the higher order Deco upled Direct Method (HDDM) (Dunker et al., 2002) to calculate sensitivity coefficients for O 3 to additional NO X and VOC emissions from new hypothetical sources. The resulting O 3 sensitivity coefficients then allow O 3 impacts to be estimated for other NO X and/or VOC sources within the same metropolitan are a. The relevancy and applicability of a given screening technique should be discussed with the pe rmitting authority for a determination about whether that approach would fulfill or partially fu lfill a first tier assessment.

A demonstration tool could include the use of exist ing credible photochemical model impacts for
sources deemed to be similar in terms of emission r ates, release parameters, and background environment. A review has been done examining publi shed relationships between single source precursor emissions and downwind O 3 and secondary PM2.5 impacts (U.S. Environmental Pr otection Agency, 2015). Secondary impacts typically increase as precursor emissions increase. Single source secondary impacts are not always highest at the fac ility fence-line, but are usually highest in proxim ity
to the source and tend to decrease as distance from the source increases (U.S. Environmental Protectio n Agency, 2015). Empirical relationships based on exi sting technical work may be relevant where the modeling system used conforms to those for estimati ng single source secondary impacts in Appendix W and described in this guidance for alternative mode ls. The project source must generate a modeling protocol and describe how the existing modeling con forms to the O 3 or PM2.5 that is conceptually thought to form in that particular area. Where the existing technical information is based on chemical and physical conditions less similar to the project source and key receptors, a more conservative estimate of impacts using demonstration tools may b e adequate.14

An example of using existing empirical relationship s would be a hypothetical source with an additional 600 tpy of SO 2 emissions resulting from new construction at a fac ility in the Atlanta metropolitan area. Empirical relationships between single sources of S O 2 emissions in the Atlanta area and downwind impacts have been published (U.S. Environmental Pro tection Agency, 2015). However, the published impacts are the result of 100 and 300 tpy emissions in that area. Impacts could be extrapolated by increasing the downwind PM2.5 sulfate ion impacts f rom the published 300 tpy hypothetical source by a factor of 2 to estimate the post-construction impac ts of source seeking a permit. If those impacts are well below the PM2.5 SIL, then no further technical analysis may be necessary. If a source was locatin g in an area where existing information does not exis t, that source could present the most conservative estimate of impacts from sources previously modeled in areas with generally similar meteorology and air quality. However, in this case additional conse rvatism may need to be introduced to the previously estimated downwind impacts given the additional inc ongruity between the existing information and
actual conditions.

In all cases, additional information is needed from the project source with the existing information t o corroborate the appropriateness and relevancy of th e existing information for the anticipated conditio ns at the project source and key receptors.


## 4 Refined or “Second Tier” assessment of single sou rce impacts

on O 3 

## and secondary PM2.5

4.1 Model inputs

4.1.1 Project source emissions

Compliance with PSD should be demonstrated using em issions input data for the project source consistent with Appendix W (U.S. Environmental Prot ection Agency, 2005). Appendix W states that project sources should be “modeled using the design capacity (100 percent load).” Emissions inputs for the project source should be consistent with Tables 8.1 and 8.2 in Appendix W, meaning project source
emissions should be the maximum allowable emissions or federally enforceable permit level limits (U.S. Environmental Protection Agency, 2005).



### 4.1.2 Nearby source emissions

A realistic characterization of chemistry surroundi ng the project source is important for estimating secondary impacts. Therefore, unlike the project so urce that is modeled at maximum allowable emissions, other sources in proximity should be mod eled or characterized with a typical emission profi le and stack characteristics for the purposes of estim ating single source impacts on secondary pollutant
formation.



### 4.1.3 Meteorology inputs

The importance of meteorology coupled with the spat ial heterogeneity of chemical reactants in a project area necessitate meteorological inputs to t he air quality model that capture differences in15

meteorology (i.e. temperature and relative humidity ) over the entire spatial extent of the project are a both horizontally and vertically. Prognostic meteor ological model output should be used to support air quality modeling of secondary impacts of PM and ozo ne. Candidate prognostic meteorological models should be considered state of the science by the ai r quality modeling community, be routinely used as input for regulatory air quality modeling applicati ons, be peer-reviewed, fully documented, freely available on the internet, and actively supported b y the model developer. Currently, one of the more widely used prognostic meteorological models in the United States is the Weather Research and Forecasting (WRF) model (Skamarock et al., 2008) av ailable from the National Center for Atmospheric Research (http://www.wrf-model.org/index.php).

The prognostic meteorological model application sho uld be configured to match the grid projection and size of the air quality model domain used to assess the single source impacts on secondary pollutants. Prognostic meteorological model applications should include the entire troposphere with the finest vertical resolution in the planetary boundary layer to appropriately capture the dynamic processes related to vertical mixing. Prognostic meteorologic al model output should be translated for input to t he selected air quality model by making any needed adj ustments to match grid structure. None of the prognostic model output variables should be re-diag nosed or changed before input to the air quality model. It is important to maintain the integrity of the meteorological field to minimize dynamic inconsistencies between the air quality and meteoro logical models.

Where project source site-specific meteorology is a vailable, the project sponsors are encouraged to incorporate that data into the prognostic meteorolo gical model simulation. This can be done through inclusion with other observation data as the input analysis field and through observation nudging duri ng the model simulation.



### 4.2 Episode selection

Meteorology is an important factor in the formation of many secondarily formed pollutants, both directly (i.e. ammonium nitrate formation under coo l, humid conditions) and indirectly (i.e. warm temperatures and sunlight increase photochemistry a nd the availability of oxidants). Since secondary pollutant impacts are being estimated, the year(s) of meteorology selected for use in the assessment i s important. A time period with generally conducive m eteorology to the formation of secondary PM2.5 and/or ozone is necessary. This means that time per iods with elevated PM2.5 and/or ozone at the source and receptors must be used in the analysis.

At a minimum, modeling systems applied for the purp oses of characterizing secondary annual PM2.5 should be applied with at least one year of meteoro logical inputs that vary in time and space since so me components of PM2.5 are highest in the different se asons. An entire year should be modeled to capture different formation regimes and to capture the vari ety of wind flows at the sources and receptors bein g analyzed. It may not always be necessary that the p eriod used for estimating secondary impacts match a period used to estimate impacts of primarily emitte d PM2.5 when those impacts are estimated with a dispersion model such as AERMOD.

When daily PM2.5 impacts from single project source s are being modeled, it is preferential to model those impacts over at least one entire time period that has been shown to be generally conducive to
elevated PM2.5 formation. Since PM2.5 formation var ies in a given area, multiple elevated PM2.5 episodes would be appropriate for modeling the impa cts of a single source on ambient PM2.516

concentrations to capture the variety of wind flows and formation regimes in a given area. Where multiple episodes simulations are necessary for a s ingle source assessment, it is not necessary they b e consecutive.

When ozone impacts from single project sources are being modeled, it is preferential to model those impacts over at least one entire ozone season that has been shown to be generally conducive to
elevated ozone formation. Since ozone formation var ies in a given area, multiple ozone seasons or multiple well characterized ozone episodes would be appropriate for modeling the impacts of single source on ambient ozone concentrations to capture t he variety of wind flows and ozone formation regimes in a given area. Where multiple ozone episo de/season simulations are necessary for a single source assessment, it is not necessary they be cons ecutive.



### 4.3 Receptor placement and domain extent

Receptors are locations in the project area where a n air quality model estimates pollutant concentrations. A receptor network design should em phasize resolution and location rather than match a minimum number of receptors. Receptors should be placed at all locations where high concentrations may occur, not just where high concentrations may b e anticipated prior to the analysis. Receptor spacing near the source should be sufficient to cap ture expected concentration gradients around the
locations of maximum modeled concentrations. Where grid models are applied, the receptor location is the center of the surface layer grid cell.

For primarily emitted PM, the peak impacts are more likely to be near the emissions source. Secondaril y formed pollutants including PM and ozone may have m aximum impacts near the source or further downwind depending on meteorology, stack release ch aracteristics, and availability of important chemical reactants. Receptors should be placed in a ll directions surrounding a project source to captu re meteorological and chemical variability.

Receptor placement should extend from the fence-lin e of the project source out to a sufficient distanc e from the project source to account for the impacts of downwind chemical transformations and changing availability of important chemical species that may enhance secondary pollutant formation. Receptors should be placed to capture maximum concentrations of secondary impacts which may extend out to 50 km (U.S. Environmental Protection Agency, 2015) fro m the project source (Appendix W). Receptor placement for the purposes of estimating air qualit y impacts at downwind Class I areas for air quality related values should follow guidance developed by Federal land managers (U.S. Department of the Interior, 2010).



### 4.4 Vertical domain resolution

The best approach to representing the vertical atmo sphere in an air quality model is to match the vertical layer structure of the input prognostic me teorological model. However, it may not always be necessary in the air quality model to use the full vertical extent applied in the prognostic meteorolo gical model and resource considerations may make vertical layer collapsing necessary at times. When vertical layer collapsing is employed, it is important to ma tch most closely with the prognostic meteorological model the layers closest to the surface to best res olve the diurnal and seasonal variability in the mi xing height. Consultation with the permitting authority is recommended for instances when modeling the17

entire troposphere may not be necessary and when ve rtical layers are not matched one to one between the air quality and meteorological models.



### 4.5 Horizontal domain resolution

Photochemical grid based models have been applied f or long periods using domains covered by grid cells ranging in size from <1 to 15 square km (Couz o et al., 2012; Hogrefe et al., 2011; Jin et al., 2 010; Rodriguez et al., 2011; Stroud et al., 2011). Lagra ngian models have been applied using similar horizo ntal grid spacings (Dresser and Huizer, 2011; Levy et al ., 2002). Horizontal grid spacing is important to appropriately represent the heterogeneity in pollut ant concentrations between a source and receptor. This concentration gradient varies depending on a v ariety of factors including chemistry, available reactants, size of the particle, and terrain featur es among other influencing conditions.

Single source impact assessments for urban areas, w here the source and receptors are in the same urban area, should be conducted at grid resolutions between ~1 km up to ~12 km. Photochemical grid model application up to 12 km has been shown to cap ture similar changes in air quality due to changes in emissions from a specific source on secondary po llutants in an urban area estimated with finer grid resolution (Cohan et al., 2006). In instances where sources may be modeled at coarser resolution or at resolutions finer than 1 km consultation with the p ermitting authority is appropriate.

Single source impact assessments at regional scales , where the source and receptors are hundreds of km apart should be conducted at grid resolutions no la rger than ~12-15 km. Where resources are an important consideration, options such as 2-way nest ing may be useful to reduce computation runtime. In these situations, the source and receptors would be included in 2-way nests using finer grid resolution. In regional scale assessments, using to o fine grid spacing may not be appropriate as chemi cal and meteorological data may be insufficient leading to unrealistic results.

If a project source is modeled using a horizontal g rid resolution finer than what is typically applied for such purpose, the project source should also be mod eled using a horizontal grid spacing typical of contemporary applications for similar purpose and t he contribution estimates using the coarser model domain should be considered along with the finer do main impacts.



### 4.6 Use of photochemical grid models for single sou rce impact assessments

Where set up appropriately for the purposes of asse ssing the contribution of single sources to secondarily formed pollutants, photochemical grid m odels could be used with a variety of approaches to estimate these impacts. The simplest approach would be to simulate 2 sets of conditions, one with all
emissions and one with the source of interest modif ied from the original “baseline” simulation (Cohan et al., 2005). The difference between these simulation s provides an estimate of the air quality change du e to the adjusted emissions.

Source apportionment has been implemented in modeli ng systems such as CMAQ and CAMx in the past (ENVIRON, 2014; Kwok et al., 2015; Kwok et al., 201 3; Wang et al., 2009). CAMx currently includes multiple approaches to estimating ozone source cont ribution (ENVIRON, 2014). The standard OSAT approach apportions contribution based on estimated NO X /VOC sensitivity while an alternative approach (APCA) diverts ozone contribution to the a nthropogenic source when ozone is formed from a combination of anthropogenic and biogenic sources ( most typically anthropogenic NO X and biogenic18

VOC). For the purposes of estimating project source impacts for permit review, the APCA approach is preferred.

In some instances where the source and key receptor s are in very close proximity, the source and receptor may be located in the same photochemical g rid model cell. Since physical and chemical processes represent a volume average, this may not represent the gradients of pollution possible between the source and receptor when they are locat ed in such proximity. The preferred approach to better representing the spatial gradient in source- receptor relationships when they are in close proximity would be to use smaller sized grid cells. Grid resolution would be defined such that the sou rce and receptor are no longer in the same grid cell. I deally, there would also be several grid cells betw een the source and receptor to best resolve near-source pollution gradients.

In these situations of close proximity between the source and receptor, a photochemical model instrumented with sub-grid plume treatment and samp ling could potentially represent these relationships. Sub-grid plume treatment extensions in photochemical models typically solve for in-plum e chemistry and use a set of physical and chemical cr iteria for determination of when puff mass is merge d back into the host model grid. A notable limitation of sub-grid plume treatments is that these implementations do not have more refined informatio n related to meteorology or terrain than the host grid cell. In addition to tracking puffs at sub-gri d scale, the host modeling systems must be able to track and output surface layer sub-grid puff concentratio ns, “sub-grid plume sampling”, to best represent receptor concentrations that are in close proximity to the source (Baker et al., 2014). Another import ant reason sub-grid plume sampling is necessary is that inherently in this type of system (sub-grid plume treatment in a photochemical grid model) some of th e source’s impacts on air quality are resolved in puffs at the sub-grid scale and some has been resol ved in the 3-dimensional grid space. Just extractin g sub-grid plume information or just 3-dimensional mo del output would miss some of the source’s contribution to air quality meaning accounting for both is necessary either with sub-grid sampling or options that integrate puffs within a grid cell wit h grid cell concentrations. Sub-grid plume treatmen ts in photochemical grid models do not track source impac ts separately from other sources in the model simulation. When sub-grid treatment is applied for a project source under permit review, either source apportionment or source sensitivity is necessary to track the grid resolved source contribution in addition to sub-grid plume treatment to fully captu re source contribution.



### 4.7 Use of lagrangian models for single source impa cts

Given the complex nature of chemical reactions and spatial and temporal variability in chemical reactants it is of critical importance that when se condary impacts are estimated from single sources t hat they exist in a dynamic and realistic chemical and physical environment. Lagrangian models may provide adequate representation of in-plume gas, aqueous, a nd aerosol chemistry, but without realistic concentrations of oxidants and reacting pollutants the impacts from single sources may not be appropriately characterized. Many important oxidant s are not routinely measured. Variability from the surface vertically through the troposphere is also critically important given that many sources will h ave plumes that do not solely exist at the surface. The use of ambient measurements is unlikely to provide the spatial (at the surface and vertically) and tem poral variability in oxidants and reactants in an a rea. This data need typically necessitates the use of ph otochemical model concentration estimates to be used as input to a Lagrangian model.19

Due to the existence of overlapping puffs in many L agrangian puff models, multiple puffs can occupy th e same location at a given time. These overlapping p uffs interact with background concentrations independently. Under certain conditions, this model ing approach can lead to artifacts associated with double-counting background concentrations. For ins tance, (Karamchandani et al., 2008) found that
under certain conditions the concentration of nitra te in particles can greatly exceed the theoretical maximum value based on the availability of gas-phas e ammonia (NH 3 ) for ammonium nitrate formation. Since each overlapping puff has access to the entir e background amount of NH 3 , nitrate in each puff will condense according to that amount. Under condition s where NH 3 is the limiting species for ammonium nitrate formation, each overlapping puff can indepe ndently deplete the gas-phase NH 3 concentration and cause over-prediction of particle nitrate when puffs overlap.

In an attempt to counteract the nitrate errors just mentioned, a post-processing step known as the Ammonia Limiting Method (ALM) is sometimes applied (Escoffier-Czaja and Scire, 2002). This method repartitions total nitrate between nitric acid and particle nitrate with the total amount of NH 3 at a given receptor. The approach is not necessary in 3D photo chemical grid model simulations because Eulerian grid models do not allow for overlap of different a ir parcels. Use of the ALM approach is especially problematic in long-range transport applications be cause the deposition velocities of nitric acid and fineparticle nitrate differ greatly, and so the extent of transport of the pollutants depends on whether t hey exist in the gas or particle phase. The ALM post-pr ocessing step does not account for the differences in transport of nitric acid and particle nitrate due t o their different atmospheric lifetimes, and so ALM does not correct for the flaws in the approach to modeli ng overlapping puffs and likely introduces new bias es to the air quality model estimates.

Errors similar to those just described for nitrate could potentially occur in gas-phase chemistry calculations in situations where overlapping puffs are interacting with background concentrations of oxidants that are in limited supply. All chemical r eactions should happen dynamically and continually at run-time during model application when assessing th e impacts of single sources on secondary pollutants. Post-processing changes to chemical pha se or other similar techniques that occur after the model simulation has completed are not appropriate for assessing project source impacts on secondary pollutants.



### 4.8 Model evaluation

There are multiple components to model evaluation f or the purposes of assessing single source secondary pollutant impacts for permit review progr ams. According to Appendix W (Section 3.2.2.b), an
alternative model should be evaluated from both a t heoretical and a performance perspective before it is selected for use. Comparing modeling estimates a gainst regional tracer experiments and against near

source in-plume measurements are examples of evalua tions to satisfy the theoretical fit for use evaluation requirements and are typically only done when a modeling system has notably changed from previous testing or has never been evaluated for th is purpose. The tracer experiments are useful for assessing whether a modeling system correctly captu res long-range source-receptor relationships. Nearfield plume transects are useful for evaluating the model system’s skill in capturing primary and secondarily formed pollutant concentrations.

Also, it is necessary to determine whether the inpu ts to the modeling system for a specific scenario a re adequate (Appendix W Section 3.2.2.e). This type of evaluation usually consists of operationally comparing model predictions with observation data t hat coincides with the episode being modeling for20

a permit review assessment. One of the most importa nt questions in an evaluation concerns whether the prognostic or diagnostic meteorological fields are adequate for their intended use in supporting a variety of air quality modeling exercises.

It is important that any potential approaches for m odel performance for the purposes of single source
assessments for PSD and NSR use a model evaluation approach that is universally applicable to any single source modeling system, which includes both photochemical grid and Lagrangian modeling systems. Regardless of the modeling system used to estimate secondary impacts of ozone and/or PM2.5, model estimates should be compared to observ ation data to generate confidence that the modeling system is representative of the local and regional air quality. For ozone related projects, m odel estimates of ozone should be compared with observat ions in both time and space. For PM2.5, model estimates of speciated PM2.5 components (such as su lfate ion, nitrate ion, etc) should be matched in time and space with observation data in the model d omain. Model performance metrics comparing observations and predictions are often used to summ arize model performance. These metrics include mean bias, mean error, fractional bias, fractional error, and correlation coefficient (Simon et al., 2 012). There are no specific levels of any model performan ce metric that indicate “acceptable” model performance. Model performance metrics should be co mpared with model applications of similar geographic areas and time of year to assess how wel l the model performs (Simon et al., 2012).



### 4.9 Project-specific modeling

The different types of model simulations that are n eeded for different types of permit review
assessments are described in this section. The nece ssary modeling scenarios depend on the purpose of the modeling and the type of model tool used for th e assessment. A photochemical model used for estimating impacts for a PSD permit review would ty pically require both a baseline and project source scenario but a Lagrangian modeling system may only require a project source scenario. The credit source scenario is only needed where emissions offs ets are being compared to project source impacts.

Baseline conditions scenario . This scenario includes all sources in an area ope rating under typical (actual) conditions during the selected modeling pe riod. Where impacts of a new project source will be estimated then the new source should not have any e missions in this simulation. Where the impacts of a project source operating modification will be estim ated then the project source should be modeled using conditions representing pre-construction. Thi s step may not be necessary where modeling the impacts of a new source using a Lagrangian modeling system because those modeling systems typically only output source impacts.

Project source scenario . This scenario is the same as the baseline scenari o except it includes either 1) a new project source or 2) a modified project source as part of the simulation. Where project source impacts are estimated using photochemical model sou rce attribution techniques such as DDM or source apportionment this step may be necessary and the ba seline conditions scenario would not be necessary.

Credit source scenario . This scenario is only needed for situations where a new or modified source is seeking some type of emissions offset. This scenari o is the same as the baseline scenario except the facility or facilities identified for emissions cre dit offsets are modeled with appropriate changes to operations reflective of the target emission offset s (only the targeted offset emissions are adjusted in this scenario not the entire facilities). The locat ion of the facilities from which offsets are desire d should21

be modeled at their actual locations (or last opera ting location) unless directed otherwise after consultation with the permitting authority.



## 5 Appropriate processing of modeled estimates & bac kground

5.1 Operational definition of particulate matter

An important consideration when using any modeling system for the purposes of assessing single source impacts on total PM2.5 is the operational definitio n of PM2.5. Since PM2.5 is the sum of all particula te matter species with aerodynamic diameters less than 2.5 microns, it is important to understand how the modeling system used defines the size of PM2.5. Som e modeling systems use a size sectional approach and others use a modal approach to approximate the size distribution of PM2.5. A straightforward and conservative way to estimate secondary PM2.5 in mod al models (e.g. CMAQ) is to sum the secondary components of the fine particle modes (the Aitken a nd accumulation, i.e., “ i ” and “ j ”). The fine modes largely contain particle mass in the PM2.5 size ran ge that includes particles with aerodynamic diamete rs less than 2.5 microns. This approach produces an es timate consistent with modeling systems that use a sectional representation of particle size distribut ions (e.g. CAMx) but internally assume all secondar y PM is in the PM2.5 size range.



### 5.2 “Absolute” and “Relative” modeling approaches

For the purposes of single source impact assessment s for permit review programs, the absolute modeled concentrations are compared to significance thresholds. Photochemical models used for the purposes of projecting future year design values fo r ozone and PM2.5 attainment demonstrations estimate relative response factors at key monitors with the change in model response on the highest modeled days in the baseline period. One reason for using relative response factors is to minimize uncertainty in the different components of the emis sion inventory. Since project source emissions are well characterized and known, the use of the absolu te contribution estimate by a photochemical grid model is appropriate in single source permit applic ations. Additionally, it is necessary to estimate p roject source impacts throughout the area impacted by a so urce not just at locations where monitors exist.



### 5.3 Estimating the O 3 

### impact from a project source

The first step for estimating 8-hr O 3 impacts from a project source is to estimate the m aximum daily 8-hr

O 3 (MDA8) at each receptor for each modeled simulatio n day of the baseline scenario. This step may not be necessary when using a single source Lagrangian model.

Second, calculate the MDA8 at each receptor for eac h modeled simulation day of the project scenario using the same hours used to estimate MDA8 in the b aseline scenario. Estimate the difference between the project scenario MDA8 and baseline scenario MDA 8 for each receptor and model simulation day. This difference is the contribution from the projec t source. When a Lagrangian single source simulatio n has been completed, the absolute air quality impact s from the project scenario represent the project source impacts.22

If a credit scenario was modeled, calculate the MDA 8 at each receptor for each modeled simulation day of the credit scenario using the same hours used to estimate MDA8 in the baseline scenario. Estimate
the difference between the credit scenario MDA8 and baseline scenario MDA8 for each receptor and model simulation day. This difference is the impact from the credit source(s).



### 5.4 Estimating the annual PM2.5 impact from a projec t source

The first step for estimating annual PM2.5 impacts from a project source is to estimate the annual average PM2.5 at each receptor for the baseline sce nario. This step may not be necessary when using a single source Lagrangian model.

Second, calculate the annual average PM2.5 at each receptor for the project scenario. Estimate the difference between the project scenario annual aver age PM2.5 and baseline scenario annual average PM2.5 for each receptor. This difference is the con tribution from the project source. When a Lagrangia n single source simulation has been completed, the ab solute air quality impacts from this project scenar io represent the project source impacts.

If a credit scenario was modeled, calculate the ann ual average PM2.5 at each receptor for the credit
scenario. Estimate the difference between the credi t scenario annual average PM2.5 and baseline scenario annual average PM2.5 for each receptor. Th is difference is the impact from the credit source( s).



### 5.5 Estimating the daily PM2.5 impact from a project source

The first step for estimating daily PM2.5 impacts f rom a project source is to estimate the daily 24-ho ur average PM2.5 at each receptor for each modeled sim ulation day for the baseline scenario. This step may not be necessary when using a single source Lag rangian model.

Second, calculate the daily average PM2.5 at each r eceptor for each modeled simulation day for the project scenario. Estimate the difference between t he project scenario daily average PM2.5 and baselin e scenario daily average PM2.5 for each receptor and model simulation day. This difference is the contribution from the project source. When a Lagran gian single source simulation has been completed, the absolute air quality impacts from this project scenario represent the project source impacts.

If a credit scenario was modeled, calculate the dai ly average PM2.5 at each receptor for each modeled day for the credit scenario. Estimate the differenc e between the credit scenario daily average PM2.5 a nd baseline scenario daily average PM2.5 for each rece ptor and model simulation day. This difference is t he impact from the credit source(s).



### 5.6 Background concentrations

Appendix W (section 8.2.1) states background concen trations are essential for determining source impacts. Concentrations are spatially and temporall y variable throughout a project area due in part to differences in meteorology, terrain, landuse, and e missions. For a cumulative assessment (multi-source areas), Appendix W states that two components of ba ckground should be determined and include contributions from nearby sources and contributions from other sources. There is no single prescribed approach for characterizing the background concentr ation that must be added to the project source23

contribution for comparison to the level of the app ropriate NAAQS. An appropriate methodology for characterizing background concentrations must be ch osen in consultation with the permitting authority.

Background concentrations could be based on monitor ed concentrations in the project area or combined observed/modeled estimates at monitored lo cations in the project area. Given the greater potential of secondary pollution to form downwind o f a project source compared to primarily emitted PM, monitored values are an appropriate representat ion of “background” and “nearby” sources. A variety of approaches have been used to combine mod el surfaces with observation data, these techniques are generally referred to as “fused surf aces” (Fann et al., 2013). Any air quality modelin g that includes future emissions reductions from a pr oposed rule or hypothetical emissions reductions that are not associated with Federally enforceable State Implementation Plan (SIP) commitments should not be used to represent “background” or fused with observation data to represent “background”. This situation could occur when a projected future year used for a NAAQS nonattainment demonstration has past (e.g. a 2009 simulation projected from 2002) a nd may be thought to better reflect current air quality conditions.


## 6 Regulatory assessment: PSD

A simplified schematic of this process and the flex ibility afforded each sub-tier of the significant i mpact analysis and cumulative impact analysis are shown i n Figure 2. The schematic shown in Figure 2 is
relevant for O 3 impacts and sources that do not emit primary PM2.5 emissions. For project sources that emit both primary PM2.5 and PM2.5 precursors an alt ernative construct is provided. For these types of PM2.5 assessments, the project source impacts may b e estimated using different models; one for secondary and another for primary impacts. In this situation primary PM2.5 emissions would be modeled using AERMOD and the secondary impacts woul d be estimated with a more complex modeling system that includes chemistry. The approach for es timating single source impacts described in this section are intended to be relevant for PSD permit assessments. However, these approaches may be relevant for other programs and purposes.



### 6.1 Sources emitting both primarily emitted PM2.5 an d PM2.5 precursors

The analytical technique for estimating daily or an nual average secondarily formed PM2.5 impact could be from an approved reduced form (screening) approa ch or a refined approach. The secondary contribution impact could be input to AERMOD as an addition to the "BACKGROUND" concentration. Consequently, the impact compared to the SIL would include the AERMOD modeled primary impact and the estimate of secondary impact. In this approach of using AERMOD plus the “BACKGROUND” component including an estimate of secondary PM2.5 contribution, the AERMOD output should be used according to procedures outlined in Appendix W.



### 6.2 Assessments of 8-hr Ozone impacts

The modeled daily 8-hr maximum ozone impact, for th is case representing the change in emissions from the project source should be calculated for each re ceptor and day of the simulation as described in Section 5.3. A tiered approach for comparison of pr oject source impacts to the Significant Impact Leve l 1

1 Although there is currently no SIL for ozone, one of the screening tools suggested earlier would be t o establish an ozone SIL. The EPA is considering undertaking a rul emaking to do this.24

(note: currently there is no ozone SIL) and for a C umulative Impact Assessment follows. The cumulative impact modeled ozone contribution should include th e change in emissions from the project source combined with the appropriate “background” 8-hr ozo ne value that represents ozone impacts from all sources. This combined ozone impact should be compa red to the level of the 8-hr ozone NAAQS.



### 6.2.1 Assessments of 8-hr Ozone impacts – significa nt impact analysis

8-hr Ozone Significant Impact Analysis - First tier :

The modeled highest daily 8-hr maximum ozone impact over all receptors should be compared to the ozone SIL. If the highest daily 8-hr maximum ozone contribution is greater than the level of the SIL t hen a second tier assessment is necessary. The analytic al technique for estimating the ozone impact could be an approved Lagrangian or photochemical model ba sed approach.

8-hr Ozone Significant Impact Analysis - Second tie r:

The second tier differs from the first tier in that the analytical technique for estimating ozone impa ct must be estimated with a refined approach. The refi ned approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclus ion of additional representative episodes. After consultat ion with the permitting authority, a value less tha n the maximum impact may be used for comparison to th e SIL.



### 6.2.2 Assessments of 8-hr Ozone impacts – cumulativ e impact analysis

8-hr Ozone Cumulative Impact Analysis - First tier:

The highest daily 8-hr maximum ozone contribution f rom the project source over all modeled days and all receptors should be added to the highest monito red design value in the same area. If this value is below the level of the NAAQS or the source impact i s below the SIL then this test has been met. If thi s value is greater than the level of the NAAQS and th e project source contribution is greater than the S IL then a second tier assessment is necessary. The ana lytical technique for estimating the ozone impact could be an approved Lagrangian or photochemical mo del based approach.

8-hr Ozone Cumulative Impact Analysis - Second tier :

Identify each receptor on each model day that is gr eater or equal to the value representing a “high modeled day” for the baseline scenario only. High m odeled days include days at each receptor where modeled 8-hr daily maximum ozone exceeds 60 ppb. If less than 5 days are greater than 60 ppb then the test is not valid for that receptor (U.S. Environme ntal Protection Agency, 2014b). If the receptor whe re there are less than 5 high modeled days is consider ed likely to have large impacts from the project source, additional episode days may be needed to ad equately represent the project source impacts at that particular receptor.

The highest daily 8-hr maximum ozone contribution f rom the project source on high modeled days (or all modeled days if a single source Lagrangian mode l is applied) at each receptor should be added to t he monitored design value at that same receptor or an approved interpolated field of monitored design values and compared to the level of the NAAQS. If t his value is below the level of the NAAQS or the25

source impact is below the SIL then this test has b een met. The refined approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclusion of additional representative episodes. Af ter consultation with the permitting authority, a v alue less than the maximum impact may be used for additi on to background estimates and comparison to the NAAQS.



### 6.3 Assessment of sources only emitting PM2.5 precu rsors: annual PM2.5

The modeled annual average PM2.5 impact, for this c ase representing the change in emissions from the project source, should be calculated for each recep tor. A tiered approach for comparison of the projec t source impacts to the Significant Impact Level and a Cumulative Impact Assessment follows. The cumulative impact modeled PM2.5 contribution should include the change in emissions from the project source in addition to the rest of the facility and all other “nearby” emissions sources. This combined annual PM2.5 impact should be compared to the level of the annual average PM2.5 NAAQS.



### 6.3.1 Assessments of annual average PM2.5 impacts – significant impact analysis

Annual Average PM2.5 Significant Impact Analysis - First tier secondary impacts only:

The highest annual average PM2.5 impact over all re ceptors should be compared to the annual PM2.5 SIL. If the highest annual average secondarily form ed PM2.5 impact is greater than the level of the SI L then a second tier assessment is necessary. The ana lytical technique for estimating the annual secondarily formed PM2.5 impact could be from an ap proved Lagrangian or photochemical model based approach.

Annual Average PM2.5 Significant Impact Analysis - Second tier secondary impacts only:

The second tier differs from the first tier in that the analytical technique for estimating the second arily formed PM2.5 impact must be estimated with a refine d approach. The refined approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclusion of additional representat ive years. After consultation with the permitting authority, a value less than the maximum impact may be used for comparison to the SIL.



### 6.3.2 Assessments of annual average PM2.5 impacts – cumulative impact analysis

Annual Average PM2.5 Cumulative Impact Analysis - F irst tier secondary impacts only:

The highest annual average PM2.5 impact over all re ceptors should be added to the highest monitored design value in the same area. If this value is bel ow the level of the NAAQS or the project source
contribution is below the SIL then this test has be en met. If this value is greater than the level of the NAAQS and the project source contribution is greate r than the SIL then a second tier assessment is necessary. The analytical technique for estimating annual average secondary PM2.5 impact could be an approved Lagrangian or photochemical model based ap proach.

Annual Average PM2.5 Cumulative Impact Analysis - S econd tier secondary impacts only:26

The annual average PM2.5 impact at each receptor sh ould be added to a monitored design value representing the receptor location. This means the monitored design value should be paired in space but not necessarily in time with receptors. If this value is below the level of the NAAQS or the proje ct source contribution is below the SIL then this test has been met. The analytical technique for estimat ing the secondarily formed PM2.5 impact must be estimat ed with a refined approach. The refined approach may include the tool used for estimating impacts, c onfiguration options for such tool (e.g. more refin ed grid resolution), or inclusion of additional repres entative years. After consultation with the permitt ing authority, a value less than the maximum impact may be used for comparison to the SIL.



### 6.4 Assessment of sources only emitting PM2.5 precu rsors: daily PM2.5

The modeled daily average PM2.5 impact, for this ca se representing the change in emissions from the project source, should be calculated for each recep tor. A tiered approach for comparison of the projec t source impacts to the Significant Impact Level and a Cumulative Impact Assessment follows. The cumulative impact modeled PM2.5 contribution should include the change in emissions from the project source in addition to the rest of the facility and all other “nearby” emissions sources. This combined daily PM2.5 impact should be compared to the level of the daily average PM2.5 NAAQS.



### 6.4.1 Assessments of daily average PM2.5 impacts – significant impact analysis

Daily Average PM2.5 Significant Impact Analysis - F irst tier secondary impacts only:

The highest daily average PM2.5 impact over all rec eptors should be compared to the daily PM2.5 SIL. I f the highest daily average secondarily formed PM2.5 impact is greater than the level of the SIL then th e second tier assessment is necessary. The analytical technique for estimating the daily secondarily formed PM2.5 impact could be from an approved Lagra ngian or photochemical model based approach.

Daily Average PM2.5 Significant Impact Analysis - S econd tier secondary impacts only:

The second tier differs from the first tier in that the analytical technique for estimating the second arily formed PM2.5 impact must be estimated with a refine d approach. The refined approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclusion of additional representat ive years. After consultation with the permitting authority, a value less than the maximum impact may be used for comparison to the SIL.



### 6.4.2 Assessments of daily average PM2.5 impacts – cumulative impact analysis

Daily Average PM2.5 Cumulative Impact Analysis - Fi rst tier secondary impacts only:

The daily average PM2.5 impact over all receptors s hould be added to the highest monitored design
value in the same area. If this value is below the level of the NAAQS or the project source contributi on is
below than the SIL then this test has been met. If this value is greater than the level of the NAAQS a nd the project source contribution is greater than the SIL then a second tier assessment is necessary. Th e analytical technique for estimating daily average s econdary PM2.5 impact could be approved Lagrangian or photochemical model based approach.

Daily Average PM2.5 Cumulative Impact Analysis - Se cond tier secondary impacts only:27

Identify each receptor on each model day that is gr eater or equal to the value representing a “high modeled day” for the baseline scenario only. High m odeled days include the top 10% of modeled total PM2.5 in each quarter of the simulation. (U.S. Envi ronmental Protection Agency, 2014b).

The highest daily average PM2.5 contribution from t he project source on high modeled days (or all modeled days if a single source Lagrangian model is applied) at each receptor should be added to the monitored design value at that same receptor or an approved interpolated field of monitored design values and compared to the level of the NAAQS. The monitored design value should be paired in space but not necessarily in time with receptors. If this value is below the level of the NAAQS or the proje ct source contribution is below than the SIL then this test has been met. The analytical technique for estimating the secondarily formed PM2.5 impact must be estimated with a refined approach. The refined approach may include the tool used for esti mating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclusion o f additional representative years. After consultati on with the permitting authority, a value less than th e maximum impact may be used for comparison to the

SIL.


## 7 Regulatory assessment: nonattainment NSR

The approach for estimating single source impacts d escribed in this section are intended to be relevan t for nonattainment NSR permit assessments related to O 3 and PM2.5 precursor emissions trading. However, these approaches may be relevant for other programs and purposes.

7.1 

### Assessments of 8-hr ozone impacts

The modeled daily 8-hr maximum ozone impact, for th is case representing the change in emissions from the project source should be calculated for each re ceptor and day of the simulation as described in Section 5.3. Also, the modeled daily 8-hr maximum o zone impact should be similarly calculated from the credit source for each receptor and day of the simu lation as described in Section 5.3.

8-hr Ozone Precursor Emissions Offset Trading Analy sis - First tier:

The modeled daily 8-hr maximum ozone project source and credit source impacts should be paired in time (by episode day) for each receptor along with baseline modeled estimates (e.g. no project source or credit source modification). The analytical tech nique for estimating the ozone impact could be an approved Lagrangian or photochemical model based ap proach. Applicants should consult with the appropriate permitting authority to determine the m ost appropriate approach for interpreting modeled results for the purposes of establishing an emissio ns trade.

8-hr Ozone Precursor Emissions Offset Trading Analy sis - Second tier:

The second tier differs from the first tier in that the analytical technique for estimating ozone impa cts must be estimated with a refined approach. The refi ned approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclus ion of additional representative episodes. After consultat ion with the permitting authority, an alternative trade ratio may be established compared to the firs t tier analysis.28



### 7.2 Assessments of PM2.5 impacts

For project sources that emit both primary PM2.5 an d PM2.5, the project source impacts may be estimated using different models; one for secondary and another for primary impacts. In this situation primary PM2.5 emissions would be modeled using AERM OD and the secondary impacts would be estimated with a more complex modeling system that includes chemistry and accounted for in the AERMOD simulation. Where only secondary impacts fro m PM2.5 precursors are included in the assessment an appropriate chemical transport model could be used without a primary component
estimated with AERMOD.

Annual average PM2.5 Precursor Emissions Offset Tra ding Analysis - First tier:

The modeled annual average PM2.5 project source and credit source impacts should be estimated as described in Section 5.4 and paired for each recept or along with baseline modeled estimates (e.g. no project source or credit source modification). The analytical technique for estimating the PM2.5 impac t could be an approved Lagrangian or photochemical mo del based approach. Applicants should consult with the appropriate permitting authority to determ ine the most appropriate approach for interpreting modeled results for the purposes of establishing an emissions trade.

24-hr PM2.5 Precursor Emissions Offset Trading Anal ysis - First tier:

The modeled daily 24-hr average PM2.5 project sourc e and credit source impacts should be estimated as described in Section 5.5 and paired in time (by episode day) for each receptor along with baseline modeled estimates (e.g. no project source or credit source modification). The analytical technique for estimating the PM2.5 impact could be an approved La grangian or photochemical model based approach. Applicants should consult with the approp riate permitting authority to determine the most appropriate approach for interpreting modeled resul ts for the purposes of establishing an emissions
trade.

Annual and 24-hr PM2.5 Precursor Emissions Offset T rading Analysis - Second tier:

The second tier differs from the first tier in that the analytical technique for estimating PM2.5 impa cts must be estimated with a refined approach. The refi ned approach may include the tool used for estimating impacts, configuration options for such tool (e.g. more refined grid resolution), or inclus ion of additional representative episodes. After consultat ion with the permitting authority, an alternative trade ratio may be established compared to the firs t tier analysis.


## 8 Regulatory assessment: Economic Development Zones

The approach for estimating single source impacts d escribed in this section are intended to be relevan t for the purposes of air quality assessments intende d to support the establishment of an Economic Development Zone (EDZ). These designations may be g iven to parts of areas designated as nonattainment for a NAAQS to allow for industrial grow th in those areas without the administrative requirements of acquiring nonattainment NSR permits up to a certain limit of precursor emissions. Section 173(a)(1)(B) of the Clean Air Act authorize s EPA to identify, in consultation with the Secreta ry of Housing and Urban Development, zones within non-att ainment areas which should be targeted for economic development. A new or modified major stati onary source located in an EDZ is relieved of the29

New Source Review requirements to obtain offsets if the emissions from the new or modified stationary source do not exceed the emissions growth allowance that is identified for that EDZ in the State Implementation Plan for that nonattainment area.

Since an EDZ is essentially an “a priori” air qualit y credit for some part of a nonattainment area, ref ined modeling done to support an EDZ demonstration should generally follow the approach outlined for a nonattainment NSR credit demonstration in chapter 7 of this guidance. Choices made for these hypothetical sources should be done in consultation with the permitting authority. The approach described here for assessing air quality impacts fr om potential future emissions in a proposed EDZ constitutes one aspect of a multi-component analysi s for this purpose.



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