Technical Guidance for Demonstration of InterPrecursor Trading (IPT) for Ozone in the 

Nonattainment New Source Review Program

EPA-454/R-18-004

May 2018

Technical Guidance for Demonstration of Inter-Precursor Trading (IPT) for Ozone in the 

Nonattainment New Source Review Program

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Research Triangle Park, NC
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Table of Contents

1 Background ........................................................................................................................................... 2

2 O3 formation in the atmosphere........................................................................................................... 2

3 Modeling systems for estimating single source O3 impacts................................................................. 3

4 Model application considerations for estimating O3 IPT ratio.............................................................. 4

4.1 Model platform..................................................................................................................................... 4

4.2 Episode selection .................................................................................................................................. 4

4.3 Model domain and receptor placement............................................................................................... 5

4.4 Project and credit source emissions..................................................................................................... 5

4.5 Model evaluation.................................................................................................................................. 5

5 Approach for establishing a case-specific O3 IPT ratio.......................................................................... 6

6 General guidance for developing a case-specific IPT ratio for O3 precursors....................................... 6

7 Area Specific O3 IPT ratios..................................................................................................................... 8

8 References ............................................................................................................................................ 9

APPENDIX A. Illustrative example of a hypothetical project and credit source O3 interprecursor trading 

scenario (example 1)................................................................................................................................... 12

APPENDIX B. Illustrative example of a hypothetical project and credit source O3 interprecursor trading 

scenario (example 2)................................................................................................................................... 20

APPENDIX C. Illustrative example of a hypothetical project and credit source O3 interprecursor trading 

scenario (example 3)................................................................................................................................... 30
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1 Background

The EPA’s implementing regulations at 40 CFR 51.165 and part 51 Appendix S allow air agencies to 

establish inter-precursor trading (IPT) provisions for ozone (O3) as part of their Nonattainment New 

Source Review (NNSR) programs. See 40 CFR 51.165(a)(11)(i) and part 51 Appendix S section IV.G.5(i). O3

IPT provisions allow any new or modified major stationary source, locating in an O3 nonattainment area 

to satisfy the NNSR emissions offset requirements for O3 with emissions reductions of volatile organic 

compounds (VOC) or nitrogen oxides (NOX) interchangeably, subject to all statutory and regulatory 

offset requirements. This guidance and the supporting documents are not final agency actions and do 

not create any binding requirements on permitting authorities, permit applicants, the EPA, or the public. 

Further, this guidance applies only to IPT for the NNSR1 program

The CAA recognizes that emissions of both VOC and NOX contribute to ground-level O3 and, as such, are 

considered precursors for O3. In turn, the EPA’s NNSR regulations identify both NOX and VOC as 

precursors for O3, and generally apply the control requirements for O3 to both precursors in O3

nonattainment areas. See 40 CFR 51.165(a)(xxxvii)(c)(1). However, emissions of NOX and VOC are not 

considered interchangeable for all aspects of O3 control. For example, in certain situations for purposes

of meeting the CAA’s reasonable further progress requirements, the NNSR requirements for O3 in the 

CAA expressly require reductions in VOC emissions. Nevertheless, in NNSR permitting situations, with an 

appropriate technical demonstration, it is possible to define the relationship between emissions of VOC 

and NOX to establish ratios for using NOX decreases to offset VOC increases, or vice versa, that result in 

an equivalent or greater air quality benefit for O3 in a particular O3 nonattainment area. 

This document provides technical guidance that can be used by both air agencies and permit applicants 

to estimate facility-specific impacts on O3 for purposes of O3 IPT by comparing the equivalency of NOX

and VOC precursor emission impacts on ground-level O3. The air quality models and approaches for 

estimating single source O3 impacts are consistent with those described in the most recent update to 

the Guideline on Air Quality Models (U.S. Environmental Protection Agency, 2017). Further, this 

document does not specifically provide guidance for inter-basin precursor trading, but may provide 

useful information for developing such a demonstration. Inter-basin precursor trading demonstrations 

will be reviewed on a case-by-case basis by the reviewing authority and be done in consultation with the 

appropriate Regional office. 

2 O3 formation in the atmosphere

Air pollutants formed through chemical reactions in the atmosphere are referenced as secondary 

pollutants. While some very small amount of ambient O3 may result from the release of O3 emissions 

from certain sources, ground-level O3 is predominantly a secondary pollutant formed through 

photochemical reactions driven by emissions of NOX and VOC. O3 formation is a complicated nonlinear 

process that typically requires favorable meteorological conditions in addition to VOC and NOX emissions 

(Seinfeld and Pandis, 2012). Clear skies (abundant levels of solar radiation) and stagnant air masses (low 

wind speeds) increase O3 formation potential (Seinfeld and Pandis, 2012). 

 1 It does not address guidance and policy for other programs such as general conformity, CAA § 110(l), 

Economic Incentive Program (non NNSR IPT related), Motor Vehicle Emissions Budget (MVEB for conformity, 

Reasonable Further Progress (RFP), Aggregate Commitments and Contingency Measures.
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O3 formation may be limited by either NOX or VOC emissions depending on the meteorological 

conditions and the relative mix of these pollutants. When changes in ground-level O3 concentrations are 

impacted by changes in NOX emissions, the O3 formation regime is termed “NOX limited”. Alternatively, 

the O3 formation regime is termed “VOC limited” when ambient O3 formation is sensitive to changes in 

ambient VOC. The VOC-limited regime is sometimes referred to as “radical-limited” or “oxidant-limited” 

because reactions involving VOCs produce peroxy radicals that can lead to O3 formation by converting 

NO to NO2 in the presence of sunlight. In a NOX-limited regime, O3 decreases with decreasing NOX and 

has very little response to changes in VOC. The NOx-limited formation regime is more common in rural 

areas of the U.S. and many urban centers tend to be VOC-limited (Seinfeld and Pandis, 2012). O3

formation regimes vary across most areas due to the different mix of NOX and VOC sources and also in 

time, meaning the precursors limiting O3 formation can vary from day to day or even hour to hour in a 

given area. 

3 Modeling systems for estimating single source O3 impacts

Quantifying secondary pollutant formation requires simulating chemical reactions in a realistic chemical

and physical environment. Chemical transport models (CTMs) treat atmospheric chemical and physical

processes such as chemistry, deposition, and transport. Eulerian photochemical models are threedimensional grid-based models that treat chemical and physical processes in each grid cell and use

Eulerian diffusion and transport processes to move chemical species to other grid cells (McMurry et al.,

2004). Photochemical models can provide a spatially and temporally dynamic and realistic chemical and

physical environment for plume growth and chemical transformation (Baker and Kelly, 2014; Zhou et al.,

2012). Publicly available and documented photochemical grid models such as the Comprehensive Air

Quality Model with Extensions (CAMx) (Ramboll ENVIRON, 2016) and the Community Multiscale Air

Quality (CMAQ) (Byun and Schere, 2006) model treat emissions, chemical transformation, transport, and

deposition using time and space variant meteorology.

When using a photochemical grid model, specific source impacts can be isolated through the use of

either source sensitivity or source apportionment approaches. The simplest source sensitivity approach

(i.e., brute-force change to emissions) would be to simulate two sets of conditions, one with all existing

emissions and one with the addition of a new source or a source of interest modified to reflect changes

in operation (Cohan and Napelenok, 2011). The difference between these model simulations provides

an estimate of the air quality change related to the change in emissions from the new or modified

source. Another source sensitivity approach to differentiate the impacts of single sources on changes in

model predicted air quality is the Decoupled Direct Method (DDM), which internally tracks the

sensitivity of the emissions from a source through all chemical and physical processes within the

modeling system (Dunker et al., 2002). Sensitivity coefficients relating source emissions to air quality

levels are estimated during the model simulation and output at the grid resolution of the host model.

Some photochemical models have been instrumented with source apportionment capability, which

enables the tracking of emissions from specific sources through chemical transformation, transport, and

deposition processes to estimate a particular source’s impact on predicted air quality levels (Kwok et al.,

2015; Kwok et al., 2013). Source apportionment has been used to differentiate the impact from single

sources on model predicted O3 levels (Baker and Foley, 2011; Baker and Kelly, 2014; Baker et al., 2015).

DDM has also been used to estimate O3 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

sensitivity approach (Baker and Kelly, 2014; Bergin et al., 2008; Kelly et al., 2015; Zhou et al., 2012).
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Limited comparison of single source impacts between models and approaches to differentiate single

source impacts (Baker and Kelly, 2014; Cohan et al., 2006; Kelly et al., 2015) has shown generally similar

downwind spatial gradients and impacts.

4 Model application considerations for estimating O3 IPT ratio

A modeling protocol is intended to communicate the scope of the analysis and generally includes (1) the

types of analysis performed, (2) the specific steps taken in each type of analysis, (3) the rationale for the

choice of modeling system and episode(s), (4) names of organizations participating in preparing and

implementing the protocol, and (5) a complete list of model configuration options. For any IPT

demonstration, EPA recommends permit applicants first consult with the appropriate air agency and the

appropriate EPA Regional Office to develop a modeling protocol, and then conduct modeling consistent

with the protocol. Elements of a modeling protocol for these purposes are outlined in “Guidance on the

use of models for assessing the impacts of emissions from single sources on the secondarily formed

pollutants O3 and PM2.5” (U.S. Environmental Protection Agency, 2016b).

4.1 Model platform

The most recently submitted O3 attainment demonstration modeling platform considered appropriate

for the purposes of interprecursor trading demonstrations by the reviewing authority would be the best

platform for a modeling demonstrtaion. This could include the last approved SIP demonstration, a more

recent submission (even if not yet approved), or modeling not used to support a SIP demonstration but

considered representative of the current air quality in the area and of sufficient quality that is

comparable to a model platform supporting a SIP demonstration. This approach of using the most

recent SIP demonstration modeling will help support consistency and comparability between multiple

demonstrations since the same modeling platform could be used by multiple applicants. Where multiple

modeling platforms are available for a particular area, the platform that is considered to be the most

reflective of the current atmosphere in that area would best account for growth in the area and the

changing mix of sources. For instance, if an area has a SIP modeling platform with a baseline year or

2011 and projected future year of 2018 and the current year is 2018 then the projected future year may

better represent air quality in that area. For areas that do not have an existing area attainment

demonstration modeling platform, a modeling platform that represents the current air quality and

conforms to the specifications outlined for attainment demonstration modeling could be acceptable.

The specifications for area attainment demonstration model platforms (e.g., horizontal grid spacing,

vertical resolution, non-project source emission treatment, etc.) are detailed in the “Draft Modeling

Guidance for Demonstrating Attainment of Air Quality Goals for O3, PM2.5, and Regional Haze” (U.S.

Environmental Protection Agency, 2014).

4.2 Episode selection

Meteorology is an important factor in the formation of many secondarily formed pollutants, both 

directly (e.g., ammonium nitrate formation under cool, humid conditions) and indirectly (e.g., warm 

temperatures and sunlight increase photochemistry and the availability of oxidants). A time period with 

meteorology generally conducive to the formation of O3 is necessary. This means that time periods with 

elevated ambient O3 at the source and receptors would be most relevant for an IPT demonstration. 

Since O3 formation varies, even within a given area, an O3 season or multiple well characterized O3

episodes would be appropriate for modeling single source O3 impacts to capture the variety of wind 
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flows and O3 formation regimes in a given area. Where multiple O3 episode/season simulations are 

necessary for a single source assessment, it is not necessary they be consecutive. Multiple O3 episodes 

may be necessary when a single O3 episode does not have O3 levels above the level of the NAAQS or if 

the single episode does not capture all of the typical O3 formation regimes that are known in a particular 

area (U.S. Environmental Protection Agency, 2014, 2016b). Using modeled days much lower than the 

NAAQS may not be totally relevant for nonattainment related demonstrations such as interprecursor 

trading as the O3 formation regime may be very different at those levels and not representative of how 

the atmosphere might change at higher O3 levels.

4.3 Model domain and receptor placement

Model domains include locations considered “ambient air,” which may be located throughout the entire

nonattainment area for the IPT demonstration. Typically, the domain for an IPT demonstration will be

consistent with an existing O3 demonstration modeling platform. Receptor placement generally would

include area just beyond beyond property owned or controlled by the project source and evenly placed

throughout the nonattainment area. When a grid-based model is used to assess O3 impacts, all grid cells

intersecting the nonattainment area would be included in the IPT analysis to ensure the demonstration

reflects impacts in the entire area.

4.4 Project and credit source emissions

Project source annual emissions reflecting the amount of Emission Reduction Credits (ERCs) would be

most appropriate for the purposes to generating offsets under the CFR 51.165. In the uncommon

situations where the project source would be emitting the vast majority of its actual emissions on a few

days in a year an alternative emission rate may be used after consultation with the reviewing authority.

Credit sources that are part of the baseline model platform scenario can be modeled based on postconstruction conditions, and reflect the decrease in emissions sought for credit. If a credit source is not

part of the baseline model platform scenario then the credit source can be modeled based on preshutdown conditions, which would be an increase in emissions from the baseline scenario.

4.5 Model evaluation

It is important to use a model evaluation approach that is universally applicable to any single source

modeling system. Modeled O3 estimates are typically compared to observation data to generate

confidence that the modeling system is representative of local and regional air quality. For O3 related

projects, model estimates of O3 are be compared with observations in both time and space (Simon et al.,

2012; U.S. Environmental Protection Agency, 2014). Model performance metrics comparing

observations and predictions are often used to summarize model performance. These metrics include,

but are not limited to, mean bias, mean error, normalized mean bias, normalized mean error, and

correlation coefficient (Simon et al., 2012). There are no specific levels of any model performance metric

that indicate “acceptable” model performance. Model performance metrics are most useful when

compared with other model applications of similar geographic areas and time of year to assess how well

the model performs (Simon et al., 2012). Model performance for chemical transport models in the

context of single source impact assessments for well characterized project sources is intended to

provide confidence in the chemical environment of the source and does not provide specific information

about the amount or directionality of possible error in modeled source impacts.
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5 Approach for establishing a case-specific O3 IPT ratio

Since O3 formation can vary spatially and temporally, an IPT ratio tailored to the proposed facility’s 

circumstances (involving the project and credit source(s) at known locations) will best reflect the 

conditions in that area. In these situations, applicants conduct modeling of the proposed source’s postconstruction conditions compared with the credit source(s) used for the emissions offset. This type of 

facility-specific air quality modeling is similar to a Tier 2 demonstration and procedures for using models 

for this purpose are outlined in “Guidance on the Use of Models for Assessing the Impacts of Emissions 

from Single Sources on the Secondarily Formed Pollutants O3 and PM2.5” (U.S. Environmental Protection 

Agency, 2016b). 

EPA recommends that methods used to model project and credit source impacts be consistent with 

guidance provided in “Guidance on the Use of Models for Assessing the Impacts of Emissions from Single 

Sources on the Secondarily Formed Pollutants: O3 and PM2.5” (U.S. Environmental Protection Agency, 

2016b). Since the reactivity of specific VOCs make some more important for O3 production, VOC 

emissions get speciated to match the VOC emissions expected to be released from the proposed source. 

The credit sources would be modeled such that operating conditions and locations reflect the credit 

sources before controls or retirement unless otherwise directed after consultation with the reviewing 

authority. It would not be appropriate to model the credit source emissions and stack release at the 

same location as the project source unless the project and credit sources are actually co-located in the 

post-construction scenario. 

If the location and stack release characteristics of the credit emissions are not known, then a 

conservative approach must be taken in the technical demonstration to ensure protection of the air 

quality in the area. Conservative assumptions include stack parameters (e.g., low stack height), VOC 

speciation (e.g., VOC modeled as not highly reactive), and the “credit source” location, which could be 

considered by modeling the credit source at multiple locations in the area. The most conservative 

estimate from each of these modeled “credit sources” would represent a value most protective of an 

area when developing an IPT with the project source. 

In situations where mobile source emissions may be allowed as credits, EPA believes the best technical 

approach would be to model those emissions using the location and emissions release characteristics of 

the specific project from which the credits originated. For instance, if a project was put into place to 

change roadways to significantly reduce emissions then that particular road segment would be the 

source of emissions.

6 General guidance for developing a case-specific IPT ratio for O3

precursors

The general approach for developing an IPT demonstration is similar to that outlined for area-specific

interpollutant trading for precursors of PM2.5 (Fox, 2007; McCarthy, 2011). Illustrative examples using 

hypothetical sources are provided in the Appendix. Model simulations include impacts from both the 

project and credit sources are estimated. These impacts could be estimated in separate simulations or in 

a single simulation using source apportionment or other instrumented technique (e.g., higher-order 

DDM) that allows for differentiating source impacts. Here, the approach is described using the simplest 

approach where three separate scenarios would be modeled.
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1) A baseline scenario where project source is operating at pre-construction conditions and credit 

source(s) reflect actual conditions (e.g., not operating or operating at pre-construction 

conditions);

2) A project source scenario, which is the same as the baseline scenario except the project source 

is operating at post-construction conditions; and

3) A credit source scenario, which is the same as the baseline scenario except the credit source(s) 

is operating at post-construction conditions if included in the baseline scenario or operating at 

pre-closure conditions if not included in the baseline scenario. 

Hereafter, scenario 1 will be referred to as the “baseline scenario”, scenario 2 will be referred to as the 

“project source scenario” and scenario 3 will be referred to as the “credit source scenario”. 

In order to establish that the proposed increase in emissions is comparable to the reductions from the 

credit source(s) for an O3 IPT ratio, the modeled results of the project source scenario and the credit 

source scenario would be compared in grid cells or receptors within the nonattainment area using

NAAQS relevant averaging times (e.g. daily maximum 8-hr average) where the model is predicting 

elevated O3 (U.S. Environmental Protection Agency, 2016b). The general steps for estimating project and 

credit source sensitivities over an area follow. 

First, estimate the modeled maximum daily 8-hr O3 (MDA8) at each receptor for each simulation day of 

each of the baseline, project source, and credit source scenarios.

Second, estimate project source impacts by subtracting the project source scenario MDA8 values for 

each receptor and modeled day from the corresponding baseline scenario MDA8 values. If the credit 

source was not part of the baseline scenario, then estimate the credit source impacts by subtracting the 

credit source scenario MDA8 values for each receptor and modeled day from the corresponding 

baseline scenario MDA8 values. If the credit source was in the baseline scenario and was modeled with 

emission reductions matching the credit emissions amount, then subtract the baseline scenario MDA8 

values from the credit source scenario MDA8 values at each receptor and modeled day.

Third, match the MDA8 values estimated by the baseline (step 1) and project source (step 2). Next, 

match baseline (step 1) and credit source scenarios (step 2) for each receptor and model simulation day. 

Fourth, remove receptor-day pairings where either the project source or credit source impacts are 

negative (i.e., a disbenefit to air quality). Situations in which the increased emissions from the project or 

credit source result in a negative contribution are not included in the calculation of an O3 IPT ratio. Next, 

remove receptor-day pairings where source contribution is < 1 ppt. Additionally, receptor-day pairings 

where the baseline modeled MDA8 is less than a specific value may be removed where appropriate and 

technically justified (e.g. 65 ppb or other episode-specific/appropriate value to emphasize impacts on 

days where the model predicts relatively elevated O3 levels). A lower threshold may be necessary in 

some situations where there are few modeled days in the area at that level which means a slightly lower 

threshold may be needed to develop a robust respresentation of impacts. If modeled O3 levels are low 

throughout the episode then that episode is not appropriate for this type of demonstration. Selecting

modeled receptor-days with elevated O3 is important for NNSR demonstrations since the relationship 

between the project and credit source is most relevant for O3 levels closer to the level of the NAAQS. 

Using modeled days where levels are half or lower than the NAAQS for instance may not be relevant 
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because the O3 formation regime may be very different at those levels and not representative of how 

the atmosphere might change at higher O3 levels.

Fifth, for each modeled day, sum the project source contributions over all receptors (grid cells) meeting 

the criteria in step 4 of this process. Then sum the credit source contributions over all receptors (grid 

cells) meeting the criteria in step 4 of this process. Since emissions sensitivity will vary spatially, it would 

not be fully protective of the air quality in a given area to only consider impacts at monitor locations.

Sixth, sum the daily impacts over all days in the episode or modeling period for both the project and 

credit sources. The ratio of the episode or modeling period summed impacts represents the relative

impacts of the project and credit sources on O3 in that particular area. It is unlikely that the impacts will 

be exactly the same (i.e., a 1-to-1 relationship) so this ratio provides information about how much 

additional (or less) credit emissions may be needed to offset the change in project source emissions. 

Before selecting a specific O3 IPT value, conduct quality assurance of the resulting ratio and evaluate the

appropriateness given the nature of O3 precursor emissions sources and chemical formation in the area 

of interest. This evaluation will likely require area-specific emissions inventory information and observed 

ambient data for O3 and O3 precursors. One way to provide confidence in the modeled impacts would be 

to qualitatively determine whether the impacts conform to the conceptual understanding of the NOX

and/or VOC limited formation across the area. This means that in an area that is NOX limited the 

introduction of VOC emissions would not lead to as much O3 formation as the introduction of new NOX

emissions and vice versa in VOC limited areas. Another option for quality assurance may be comparison 

with other single source modeling done for that area or similar areas to support Tier 1 PSD 

demonstration tools (U.S. Environmental Protection Agency, 2016a). 

A narrative that shows that the increased emissions sought by the applicant for the project source will 

not adversely impact a particular population in the area either through indirect chemical reactions 

forming O3 disproportionally in that area or that increased exposure to the precursor itself or toxic 

components (e.g., formaldehyde) will not lead to adverse health effects in the area is an important 

element of an IPT demonstration. For example, a hypothetical situation where a new refinery or paint 

coating facility in an urban core area seeking NOX credits to offset increased VOC emissions. This result 

may not cause violations of the O3 NAAQS, but may result in increased exposure to air toxics in the 

urban core area.

If there are questions about applying these steps, air agencies can contact their Regional Office for 

further technical consultation.

7 Area Specific O3 IPT ratios

The previous section (Section 6 above) provided guidance on developing case-specific IPT ratios for O3

precursors. This section provides an approach for generating area-specific, i.e., “default” O3 IPT ratios, 

which involves an analysis of the existing technically credible O3 attainment demonstration (or similar 

quality) modeling data, emission inventory data, and ambient monitor data to determine whether an 

area or sub-sections in an area could be characterized as either NOX or VOC limited for O3 formation. 

Ambient data would typically include co-located NOX and VOC measurements to determine the 

relationship between these O3 precursors for an area. In addition to considering ambient and modeling 

data, emissions information is considered useful when determining whether an area’s O3 formation is 
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NOX or VOC limited. This determination may be easier for smaller metropolitan areas that do not have 

large NOX emissions sources (e.g. industrial point sources, transportation, etc.) and that do have large 

regional VOC sources (e.g., biogenic VOC) or large highly reactive VOC sources. 

This section provides information about how NOX and VOC single-source impacts on downwind O3 could 

be used to estimate an IPT ratio protective for a given area. Depending on the size of the nonattainment 

area, the prescribed area within which offsets need to be obtained may be smaller than the total 

nonattainment area, i.e., a defined sub-area, in order for emissions precursors to have a similar impact 

on O3. However, even if there is some variation in impacts within an entire nonattainment area, the 

ratio would be developed to be conservative enough to address any IPT used anywhere in the area as an 

alternative to generating sub-area ratios. 

Since emissions sensitivities typically vary across an area, an area-specific O3 IPT ratio would be most 

protective for an area when based on refined modeling that follows the approach outlined for a NNSR 

credit demonstration in this guidance. However, rather than modeling a specific post-construction 

scenario for existing project source facilities, the approach for this purpose involves modeling multiple 

hypothetical sources with varying emission rates and stack release characteristics typical of sources in 

the area or region. These sources would need to be located in different parts of the area to account for 

differences in sensitivities that may be possible when considering air quality impacts of sources located 

in different parts of the area. The overall approach for hypothetical source impact assessment would be 

generally similar to that provided for a tier 1 demonstration tool such as MERPs (U.S. Environmental 

Protection Agency, 2016a). Choices made for the number, placement, and type (emission levels and 

stack release characteristics) of hypothetical sources are important and EPA recommends selection be 

done in consultation with the permitting authority. Multiple hypothetical sources would be modeled in a 

particular area and the impacts from each would be compared then the most conservative ratio selected 

as the default ratio for that area. 

8 References

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primary and secondarily formed PM2.5. Atmospheric Environment 45, 3758-3767.

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sensitivity and apportionment approaches. Atmospheric Environment 96, 266-274.

Baker, K.R., Kotchenruther, R.A., Hudman, R.C., 2015. Estimating ozone and secondary PM 2.5 impacts 

from hypothetical single source emissions in the central and eastern United States. Atmospheric 

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offsets. Memorandum to EPA docket # EPA-HQ-OAR-2003-0062 

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Kwok, R., Napelenok, S., Baker, K., 2013. Implementation and evaluation of PM2.5 source contribution 

analysis in a photochemical model. Atmospheric Environment 80, 398-407.

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performance statistics published between 2006 and 2012. Atmospheric Environment 61, 124-139.
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Air Quality Goals for Ozone, PM2.5, and Regional Haze. 

https://www3.epa.gov/ttn/scram/guidance/guide/Draft_O3-PM-RH_Modeling_Guidance-2014.pdf.

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precursors (MERPs) as a tier 1 demonstration tool for permit related programs.

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12

APPENDIX A. Illustrative example of a hypothetical project and credit 

source O3 interprecursor trading scenario (example 1)

The following example is intended only to provide an illustrative example of how model results for 

specific sources could be used in the framework provided in this guidance document toward estimating 

equivalency in terms of O3 formation to inform an IPT ratio. 

Multiple hypothetical sources were modeled for a high O3 period in the northeast U.S. during July 2011. 

This hypothetical example considers source 4 the project source and source 2 the credit source (see 

Figure 1 left panel). The project source is seeking to offset 500 tpy of NOX emissions with 500 tpy of VOC 

emissions from the credit source. MDA8 O3 impacts from both the project and credit source were 

estimated for each day of the July 2011 episode using the CMAQ model applied with 4 km sized grid 

cells and 35 layers to resolve the vertical atmosphere from the surface to the tropopause. The extent of 

the 4 km model domain and area of interest for this hypothetical demonstration are shown in Figure 1

(right panel).

Figure 1. Hypothetical sources used in this analysis (4 and 2). The model domain and hypothetical 

area of interest (shown in orange) in the right panel.
13

Daily absolute impacts for the project source are shown in Figure 2 and credit source in Figure 3.

Figure 2. MDA8 O3 impacts for source 4 (project source) for 500 tpy of NOX.
14
15

Figure 3. MDA8 O3 impacts for source 2 (credit source) 500 tpy of VOC.
16
17

Figure 4 shows the ratio of MDA8 O3 project to credit source impacts where multiple conditions are 

satisfied. First, only impacts greater than 1 ppt are shown; second, only impacts are shown where the 

baseline bulk model O3 prediction was greater than 60 ppb; third, only impacts are shown where the 

grid cell intersects the area of interest (shown in Figure 1 as the orange colored cells). 

Figure 4. Ratio of project source to credit source impacts where multiple conditions are satisfied.
18

Daily metrics relating MDA8 project and credit source impacts are shown in Table 1. These impacts are 

based on episode days and grid cells meeting multiple criteria. First, only impacts greater than 1 ppt are 

shown; second, only impacts are shown where the baseline bulk model O3 prediction was greater than 

60 ppb; third, only impacts are shown where the grid cell intersects the area of interest (shown in Figure 

1 as the orange colored cells). For each day, the ratio is provided of the sum of project source impacts 

divided by the sum of credit source impacts over all cells meeting the criteria detailed above. The 

number of cells meeting the criteria is also provided along with that value being expressed as the 

percentage of all cells in the area of interest (the total number of cells examined for this analysis). The 

number of cells used in the analysis varies due to varying O3 production in the area of interest from day 

to day during this period of time. At the bottom of Table 1, the ratio represents the ratio of episode total 

impacts and is not the average of the daily ratios. 
19

Table 1. Project and credit source daily impacts, number of cells used, and the percentage of cells used 

in the area of interest. 

Episode Day

Sum of 

Project 

Source 

MDA8 O3 

Impacts 

(ppb)

Sum of 

Credit 

Source 

MDA8 O3 

Impacts 

(ppb)

Ratio of 

project to 

credit source 

impacts

Number of 

cells used for 

project 

source 

impact sum

Project 

source 

impacted 

cells divided 

by total cells 

in area of 

interest x 

100

Number of 

cells used 

for credit 

source 

impact sum

Credit source 

impacted 

cells divided 

by total cells 

in area of 

interest x 100

1 0 1.35 0 1 0.1 88 8.7

2 0 1.23 0 0 0 57 5.6

3 0.51 0.37 1.4 26 2.6 33 3.2

4 0 3.19 0 1 0.1 64 6.3

5 0.53 2.8 0.2 50 4.9 93 9.2

6 0.19 0.13 1.5 21 2.1 20 2

7 1.72 0.15 11.5 39 3.8 28 2.8

8 0.12 1.22 0.1 46 4.5 190 18.7

9 0.12 1.09 0.1 14 1.4 61 6

10 3.44 0.77 4.5 310 30.5 196 19.3

11 0.48 0.18 2.7 20 2 28 2.8

12 0.25 0.07 3.6 6 0.6 5 0.5

13 0 0.19 0 0 0 9 0.9

14 0.05 0.34 0.1 12 1.2 21 2.1

15 0 0.26 0 0 0 31 3.1

16 0.43 0.07 6.1 21 2.1 21 2.1

17 0.09 0 Inf 2 0.2 0 0

18 0.16 0.06 2.7 16 1.6 16 1.6

19 3.55 10.09 0.4 119 11.7 241 23.7

20 2.53 3.14 0.8 828 81.5 401 39.5

21 0.34 0.21 1.6 21 2.1 30 3

22 1.33 0.06 22.2 26 2.6 19 1.9

23 1.04 0.07 14.9 33 3.2 26 2.6

24 6.18 2.61 2.4 249 24.5 225 22.1

25 2 1.06 1.9 757 74.5 178 17.5

26 0.66 1.29 0.5 16 1.6 105 10.3

27 0 1.39 0 0 0 93 9.2

28 0.16 1.66 0.1 64 6.3 90 8.9

29 0.52 0.32 1.6 30 3 27 2.7

Sum 26.4 35.37 0.746
20

APPENDIX B. Illustrative example of a hypothetical project and credit 

source O3 interprecursor trading scenario (example 2)

The following example is intended only to provide an illustrative example of how model results for 

specific sources could be used in the framework provided in this guidance document toward estimating 

equivalency in terms of O3 formation to inform an IPT ratio. 

Multiple hypothetical sources were modeled for a high O3 period in the northeast U.S. during July 2011. 

This hypothetical example considers source 9 the project source and source 1 the credit source (see 

Figure 1 left panel). The project source is seeking to offset 500 tpy of NOX emissions with 500 tpy of VOC 

emissions from the credit source. MDA8 O3 impacts from both the project and credit source were 

estimated for each day of the July 2011 episode using the CMAQ model applied with 4 km sized grid 

cells and 35 layers resolved the vertical atmosphere from the surface to the tropopause. The extent of 

the 4 km model domain and area of interest for this hypothetical demonstration are shown in Figure 1

(right panel).

Figure 1. Hypothetical sources used in this analysis (9 and 1) the model domain and hypothetical area 

of interest shown in orange). 

Daily absolute impacts for the project source are shown in Figure 2 and credit source in Figure 3. Source 

impacts are only shown where modeled bulk MDA8 O3 was greater than 60 ppb. 
21

Figure 2. MDA8 O3 impacts for source 9 (project source) for 500 tpy of NOX.
22
23

Figure 3. MDA8 O3 impacts for source 1 (credit source) 500 tpy of VOC. Note scales are different 

between Figure 2 and Figure 3.
24

Figure 4 shows the ratio of the differences in impacts between sources. In Figure 4, the modeled impacts 

were not subset based on any particular criteria. 
25

Figure 4. Ratio of project source to credit source MDA8 O3 impacts.
26

Figure 5 shows the ratio of MDA8 O3 project to credit source impacts where multiple conditions are 

satisfied. First, only impacts greater than 1 ppt are shown; second, only impacts are shown where the 

baseline bulk model O3 prediction was greater than 60 ppb; third, only impacts are shown where the 

grid cell intersects the area of interest (shown in Figure 1 as the orange colored cells).
27

Figure 5. Ratio of project source to credit source impacts where multiple conditions are satisfied.
28

Daily metrics relating MDA8 project and credit source impacts are shown in Table 1. These impacts are 

based on episode days and grid cells meeting multiple criteria. First, only impacts greater than 1 ppt are 

shown; second, only impacts are shown where the baseline bulk model O3 prediction was greater than 

60 ppb; third, only impacts are shown where the grid cell intersects the area of interest (shown in Figure 

1 as the orange colored cells). For each day, the ratio is provided of the sum of project source impacts 

divided by the sum of credit source impacts over all cells meeting the criteria detailed above. The 

number of cells meeting the criteria is also provided along with that value being expressed as the 

percentage of all cells in the area of interest (the total number of cells examined for this analysis). The 

number of cells used in the analysis varies due to varying O3 production in the area of interest from day 

to day during this period of time. At the bottom of Table 1, the ratio represents the ratio of episode total 

impacts and is not the average of the daily ratios. 
29

Table 1. Project and credit source daily impacts, number of cells used, and the percentage of cells used 

in the area of interest. 

Episode Day

Sum of Project 

Source MDA8 

O3 impacts 

(ppb)

Sum of Credit 

Source MDA8 

O3 impacts 

(ppb)

Ratio of 

project to 

credit source 

impacts

Number of 

cells used for 

project source 

impact sum

Project source 

impacted cells 

divided by 

total cells in 

area of 

interest

Number of 

cells used for 

credit source 

impact sum

Credit source 

impacted cells 

divided by 

total cells in 

area of 

interest

1 1.5 2.86 0.5 111 10.9 101 9.9

2 17.07 1.83 9.3 213 21 74 7.3

3 3.19 0.4 8 140 13.8 37 3.6

4 25.89 5 5.2 247 24.3 120 11.8

5 8.06 2.97 2.7 209 20.6 123 12.1

6 0.45 0.2 2.2 53 5.2 37 3.6

7 4.02 0.54 7.4 197 19.4 59 5.8

8 7.57 1.47 5.1 341 33.6 223 21.9

9 2.42 1.14 2.1 54 5.3 60 5.9

10 16.4 0.69 23.8 297 29.2 194 19.1

11 2.04 0.18 11.3 97 9.5 25 2.5

12 5.55 0.22 25.2 71 7 27 2.7

13 0.74 0.13 5.7 48 4.7 16 1.6

14 1.06 0.32 3.3 21 2.1 21 2.1

15 3.87 0.32 12.1 95 9.4 35 3.4

16 4.94 0.73 6.8 322 31.7 72 7.1

17 3.58 0.01 358 89 8.8 5 0.5

18 2.22 0.09 24.7 106 10.4 22 2.2

19 7.63 8.8 0.9 196 19.3 231 22.7

20 25.15 3.89 6.5 879 86.5 322 31.7

21 2.05 0.25 8.2 80 7.9 29 2.9

22 5.02 0.71 7.1 132 13 66 6.5

23 9.58 0.31 30.9 199 19.6 65 6.4

24 18.42 1.6 11.5 339 33.4 160 15.7

25 9.73 1.03 9.4 940 92.5 148 14.6

26 6.93 1.22 5.7 166 16.3 128 12.6

27 2.81 2.17 1.3 109 10.7 93 9.2

28 3.15 2.72 1.2 188 18.5 137 13.5

29 4.74 0.31 15.3 156 15.4 31 3.1

Sum 205.78 42.11 4.9
30

APPENDIX C. Illustrative example of a hypothetical project and credit 

source O3 interprecursor trading scenario (example 3)

The following example is intended only to provide an illustrative example of how model results for 

specific sources could be used in the framework provided in this guidance document toward estimating 

equivalency in terms of O3 formation to inform an IPT ratio. 

A hypothetical source was modeled for a short July 1-10, 2013, time-period in the Chicago/Lake 

Michigan area. For this example, MDA8 O3 impacts from both the project and credit source (co-located) 

were estimated for each day of the July 1-10, 2013, time-period using the CMAQ model applied with 4 

km sized grid cells and 35 layers resolved the vertical atmosphere from the surface to the tropopause. 

The extent of the 4 km model domain and area of interest for this hypothetical demonstration is shown 

in Figure 1 (right panel).

Figure 1. Hypothetical source location, model domain, and hypothetical area of interest (orange).

This hypothetical example considers the project source and the credit source to be co-located. The 

project source is seeking to offset 500 tpy of NOx emissions with 500 tpy of VOC emissions from the 

credit source. Daily absolute O3 impacts from the project source are shown in Figure 2 and daily 

absolute O3 impacts from the credit source are shown in Figure 3. Spatial plots subset with criteria 

related to baseline model predicted O3 show source impacts where modeled bulk MDA8 O3 was greater 

than 30 ppb. A value of 30 ppb was selected for this hypothetical example because this period of time 

did not include many days with elevated O3. In a real-world situation, O3 episodes would be selected 

such that the time period in that area experienced elevated O3 levels. Multiple model predicted MDA O3 

thresholds were used as part of this example to illustrate how the relationship between source impacts 

can vary at different O3 levels and those impacts are shown in Table 2 of this Appendix section. The level 

of 30 ppb should not be used in actual demonstrations. 
31

Figure 2. MDA8 O3 impacts from the project source emitting 500 tpy of NOx. Note scales are different 

between Figure 2 and Figure 3.
32

Figure 3. MDA8 O3 impacts from the credit source emitting 500 tpy of VOC. Note scales are different 

between Figure 2 and Figure 3.

Figure 4 shows the ratio of MDA8 project source O3 impacts to credit source O3 impacts where multiple 

conditions are satisfied. First, only impacts greater than 1 ppt are shown; second, only impacts are 

shown where the baseline bulk model O3 prediction was greater than 30 ppb; third, only impacts are 

shown where the grid cell intersects the area of interest (shown in Figure 1 as the orange colored cells). 
33

Figure 4. Ratio of project source to credit source O3 impacts where multiple conditions are satisfied.

Daily metrics relating MDA8 project and credit source O3 impacts are shown in Table 1. These impacts 

are based on episode days and grid cells meeting multiple criteria. First, only impacts greater than 1 ppt 

are shown; second, only impacts are shown where the baseline bulk model O3 prediction was greater 

than 30 ppb; third, only impacts are shown where the grid cell intersects the area of interest (shown in 

Figure 1 as the orange colored cells). For each day, the ratio is provided of the sum of project source O3

impacts divided by the sum of credit source O3 impacts over all cells meeting the criteria detailed above. 

The number of cells meeting the criteria is also provided along with that value being expressed as the 

percentage of all cells in the area of interest (the total number of cells examined for this analysis). The 

number of cells used in the analysis varies due to varying O3 production in the area of interest from day 

to day during this period of time. At the bottom of Table 1, the ratio represents the ratio of episode total 

impacts and is not the average of the daily ratios. Table 2 presents an illustrative sensitivity analysis of 

the ratio of sums of O3 impacts at various baseline bulk model O3 cutoffs. 
34

Table 1. Ozone impacts from the hypothetical project source and credit source and ratio analysis

Episode 

Day

Sum of 

Project 

Source 

MDA8 O3 

Impacts 

(ppb)

Sum of 

Credit 

Source 

MDA8 O3 

Impacts 

(ppb)

Ratio of 

project to 

credit 

source O3 

impacts

Number 

of cells 

used for 

project 

source 

impact 

sum

Project 

source 

impacted 

cells divided 

by total cells 

in area of 

interest x 

100 

Number 

of cells 

used for 

credit 

source 

impact 

sum

Credit source 

impacted 

cells divided 

by total cells 

in area of 

interest x 100

1 0.02 0.02 1 4 0.5 4 0.5

2 0.12 0.03 4 7 0.9 3 0.4

3 1.47 4.94 0.3 161 19.7 340 41.7

4 20.92 1.92 10.9 255 31.2 237 29

5 17.95 4.43 4.1 422 51.7 357 43.8

6 22.05 4.69 4.7 171 21 317 38.8

7 25.16 1.7 14.8 197 24.1 181 22.2

8 9.82 0.61 16.1 173 21.2 156 19.1

9 15.61 1.98 7.9 218 26.7 240 29.4

10 0.09 0.01 9 13 1.6 4 0.5

sum 113.21 20.33

ratio of 

sums 

5.57

Table 2. Sensitivity analysis of the ratio of summed ozone impacts to changes in the baseline bulk model 

O3 cutoff. 

baseline bulk model O3 cutoff (ppb) ratio of sums

0 5.57

10 5.57

20 5.57

30 5.57

40 5.64

45 5.17

50 2.20

60 0.43
United States

Environmental Protection

Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Research Triangle Park, NC

Publication No. EPA-454/R-18-004

May, 2018