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PM2 5 Wildland Fire Exceptional Events Tiering
Document


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EPA-457/R-24-001
April 2024

PM2.5 Wildland Fire Exceptional Events Tiering Document

U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Policy Division
Research Triangle Park, NC


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Contents

1.	Purpose of the Document	2

2.	Tiered Approach for Determining the Level of Evidence Likely to be Necessary in
Wildland Fire-related PM2.5 Exceptional Events Demonstrations	5

3.	Overview of the EPA's Methodology to Identify Tiers	6

4.	Conceptual Model of an Event	10

5.	Clear Causal Relationship between the Specific Event and the Monitored
Concentration	11

5.1	Overview and Exceptional Events Rule Provisions	11

5.2	Comparison of Candidate Event Data to Tiering Thresholds	12

5.3	The Key Factor and Suggested Evidence to Include in Tier 1 Analyses	14

5.4	The Key Factor and Suggested Evidence to Include in Tier 2 Analyses	16

5.5	Tier 3 Analyses to Support the Clear Causal Relationship	18

5.6	Summary of Evidence Under Three Supporting Analysis Tiers that Could be Used to
Meet the Exceptional Events Rule Elements	19


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1. Purpose of the Document

This document supplements the EPA's September 2016 document titled, Guidance on the
Preparation of Exceptional Events Demonstrations for Wildfire Events that May Influence Ozone
Concentrations and focuses on preparing and reviewing exceptional events demonstrations
associated with wildfire and prescribed fire events for both the 24-hour and annual fine
particulate matter (PM2.5) standards. This document is relevant for events that may be associated
with initial area designations for the 2024 revised annual PM2.5 National Ambient Air Quality
Standards (NAAQS) and other actions of regulatory significance.

The EPA is providing this information to assist air agencies in preparing exceptional events
demonstrations for wildland fire influences on PM2.5 concentrations that meet the requirements
of Clean Air Act (CAA) section 319(b) and the Exceptional Events Rule. Where there are
differences between the information in this document and statute or regulatory requirements, the
statute and regulations take precedence. The EPA's decision regarding a submitted exceptional
events demonstration does not constitute final Agency action until the demonstration and the
EPA's decision are included in notice-and-comment rulemaking for the associated regulatory
action relying on the exclusion of the event data.

The EPA has previously released the following exceptional events implementation resources
related to fire-related events:

•	Guidance on the Preparation of Exceptional Events Demonstrations for Wildfire
Events that May Influence Ozone Concentrations (2016 Wildfire Guidance)1 -
outlines and clarifies EPA's expectations specifically for wildfire ozone
demonstrations

•	Exceptional Events Guidance: Prescribed Fire on Wildland that May Influence
Ozone and Particulate Matter Concentrations (Prescribed Fire Guidance)2 - outlines
EPA's expectations for prescribed fire demonstrations

•	Exceptional Event Demonstration for an Exceedance of the 2012 Annual PM2.5
NAAQS at Grass Valley, California on April 20, 2021, Due to Smoke From a
Prescribed Fire31 - an example demonstration for a prescribed fire on wildland

1	The EPA's September 2016 Wildfire Guidance (EPA-457/B-16-001) is available at https://www.epa.gov/air-
quality-analysis/final-guidance-preparation-exceptional-events-demonstrations-wildfire-events.

2	The EPA's August 2019 Prescribed Fire Guidance is available at https://www.epa.gov/sites/default/files/2019-
08/documents/ee prescribedJireyinal_guidance_-_august_2019.pdf.

3	Exceptional Event Demonstration for an Exceedance of the 2012 Annual PM2.5 NAAQS at Grass Valley,
California on April 20, 2021, Due to Smoke From a Prescribed Fire is available at https://www.epa.gov/air-quality-
analysis/exceptional-events-documents-particulate-matter-nevada-county-ca

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•	Wildfire Resource Document - outlines potential analyses that may be useful to
include in a wildfire demonstration4

•	Updated Frequently Asked Questions document5 - contains several fire-related
exceptional events questions and answers

This document supplements the 2016 Wildfire Guidance and further outlines the EPA's
expectations for the "narrative conceptual model" and "clear causal relationship" criteria for fire-
related events, including wildfires and prescribed fires on wildland, that cause monitored PM2.5
exceedances or violations. This document also identifies three analytical "tiers" and associated
levels of evidence appropriate to show the clear causal relationship criterion within an air
agency's fire-related PM2.5 exceptional events demonstration. While this document focuses on
PM2.5, the principles outlined in this document may also be appropriate to extend to
demonstrations of PM10 exceedances or violations caused by wildland fire events. Air agencies
should consult with their EPA Regional offices to determine whether and how to apply the
principles in this document to a specific PM10 wildland fire exceptional events demonstration.

The technical analyses described in this document to address the clear causal relationship
criterion are generally appropriate for exceptional events demonstrations for both wildfires and
prescribed fires on wildland. Other criteria, including the "natural event/human activity unlikely
to recur" and "not reasonably controllable or preventable" elements, require different approaches
for prescribed fires versus wildfires. This document does not address those criteria. Agencies
should consult either the 2016 Wildfire Guidance or Prescribed Fire Guidance previously
referenced for further information on how these criteria can be met for their specific event type.

One of the EPA's goals in developing this document is to establish clear expectations to enable
air agencies to better manage resources as they prepare the documentation required under the
Exceptional Events Rule and to avoid the preparation and submission of extraneous information.
Submitters should prepare and submit the appropriate level of supporting documentation, which
will vary on a case-by-case basis depending on the nature and severity of the event, as
appropriate under a weight of evidence approach. This document identifies important analyses
and language to include within an exceptional events demonstration and promotes a common
understanding of these elements between the submitting air agency and the reviewing EPA
Regional office. As a result, this document is expected to improve the EPA's efficiency in
reviewing demonstrations prepared consistent with the guidance. While this document contains
example analyses that air agencies may use in their demonstrations, air agencies can also prepare
analyses or present documentation not listed or explained in this guidance, provided the
information is well-documented, appropriately applied, technically sound, and supports the
weight of evidence showing for the Exceptional Events Rule regulatory criteria.

4	The EPA's Wildfire Resource Document, updated in August 2023, is available at

https://www.epa.gov/system/files/documents/2023-09/Wildfire%20Resource%20Document_Final_Revised.pdf.

5	The EPA's Updated Exceptional Events Rule Frequently Asked Questions document is available at
https://www.epa.gov/air-quality-analysis/updated-exceptional-events-rule-faqs.

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The EPA acknowledges the complexity and intricacies of regional conditions prevalent across
the country. The EPA is committed to continuing to provide clarification and assistance to air
agencies as the Exceptional Events Rule is implemented and through communications between
the EPA Regional offices and the air agencies to ensure that these regional conditions are
adequately and appropriately addressed. The EPA had a nonregulatory docket6 open from
January 11, 2024, to March 8, 2024, to solicit feedback on this tiering method and tool prior to
finalizing this memorandum. As we continue to improve exceptional events program
implementation, we intend to post new information, updates to the current tools, and new tools as
they become available on the EPA's exceptional events website at: https://www.epa.gov/air-
quality-analysis/treatment-air-quality-monitoring-data-influenced-exceptional-events.

For more detailed information on the initial notification process, regulatory significance, and
EPA's review, please see the 2016 Wildfire Guidance. During the initial notification process, the
EPA and the air agency will work together to identify the appropriate tier (Tier 1, 2, or 3) for the
event demonstration. Air agencies can use the Tiering Screening Tool, which is based on the
tiering methodology in Section 3 of this document, to assist in identifying the tier but, ultimately,
the EPA will decide the appropriate tier. An exceptional event must have regulatory significance,
as defined by the Exceptional Events Rule, for the EPA to consider the demonstration. The EPA
expects air agencies to include information and analyses sufficient to demonstrate the
significance of specific event data for a specific regulatorily significant action. Because this
document focuses only on the conceptual model and clear causal requirements for PM2.5 and
wildland fire-related events, Table 1 identifies the six elements that an air agency must include in
an approvable PM2.5 related exceptional events demonstration and identifies the location of that
information in this document and/or other relevant documents.

Table 1. Summary of Demonstration Elements

Element

Location of Relevant Information

1. A narrative conceptual model that describes the event(s)
causing the exceedance or violation and a discussion of how
emissions from the event(s) led to the exceedance or
violation at the affected monitor(s)

Section 4 of this document, as well as the
2016 Wildfire Guidance or Prescribed Fire
Guidance as appropriate and the Wildfire
Resource Document

2. A demonstration that the event affected air quality in such
a way that there exists a clear causal relationship between the
specific event and the monitored exceedance or violation.

Section 5 of this document

3. Analyses comparing the claimed event-influenced
concentration(s) to concentrations at the same monitoring
site at other times.

Section 5 of this document

4. A demonstration that the event was both not reasonably
controllable and not reasonably preventable.

Section 4 in the 2016 Wildfire Guidance
document or Section A.5 of the Prescribed
Fire Guidance (depending on the type of
wildland fire)

5. A demonstration that the event was caused by human

Section 5 in the 2016 Wildfire Guidance

6 The nonregulatory docket, EPA-HQ-OAR-2023-0586, is available at: https://www.regulations.gov/docket/EPA-
HQ-OAR-2023-0586.

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activity that is unlikely to recur at a particular location or
was a natural event.

document or Section A.4 of the Prescribed
Fire Guidance (depending on the type of
wildland fire)

6. Documentation that the submitting air agency followed
the public comment process.

Section 6 in the 2016 Wildfire Guidance

2. Tiered Approach for Determining the Level of Evidence Likely to be
Necessary in Wildland Fire-related PM2.5 Exceptional Events
Demonstrations

Each demonstration submitted by an air agency under the Exceptional Events Rule must meet
certain minimum criteria, as defined in the CAA and the EPA's implementing regulations. The
EPA expects that the documentation and analyses that air agencies include in their
demonstrations will vary consistent with the event characteristics, the relationship to the monitor
where the exceedance or violation occurred, and the complexity of the airshed, among other
considerations. The EPA reviews exceptional events demonstrations on a case-by-case basis
using a weight of evidence approach considering the specifics of the individual event.

This document outlines a tiered approach for addressing the clear causal relationship element
within a wildland fire PM2.5 demonstration, recognizing that some causal relationships may be
clearer and, therefore, require relatively fewer pieces of evidence to satisfy the rule requirements.

•	Tier 1 clear causal analyses are intended for wildland fire events that cause
unambiguous PM2.5 impacts well above historical 24-hour concentrations, thus
requiring less evidence to establish a clear causal relationship.7

•	Tier 2 clear causal analyses are likely appropriate when the impacts of the wildland
fire on PM2.5 concentrations are less distinguishable from historical 24-hour
concentrations, and require more evidence, than Tier 1 analyses.

•	Tier 3 clear causal analyses should be used for events in which the relationship
between the wildland fire and PM2.5 24-hour concentrations are more complicated
than a Tier 2 analysis, when 24-hour PM2.5 concentrations are near or within the
range of historical concentrations, and thus require more evidence to establish the
clear causal relationship than Tier 2 or Tier 1.

Figure 1 in Section 5 outlines the process for determining an appropriate tier for a given event.
Section 3 explains the methodology by which the EPA developed the thresholds for the tiering
analysis. Tier 1 analyses are described in Section 5.3, Tier 2 analyses are described in Section
5.4, and Tier 3 analyses are described in Section 5.5.

7 As described in Section 3, while the tiering structure described in this document applies to both the 24-hour and
annual PM2 5 standards, the tiering thresholds were developed using monitored concentrations relative to the 24-hour
NAAQS.

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Regarding the process for developing demonstrations, Figure 1 on page 6 in the 2016 Wildfire
Guidance shows a flowchart summarizing the overall process for preparing, submitting, and
reviewing wildfire ozone (O3) demonstrations, which includes the Initial Notification process
and recommended review timelines. The same process applies when preparing, reviewing, and
submitting wildland fire PM2.5 demonstrations.

Various analyses could be useful for wildland fire events that influence PM2.5 concentrations to
help support the demonstration of the clear causal relationship. Some products may be more
suitable for situations where the fire is nearby to potentially impacted monitor(s) and might not
be as appropriate for demonstrations where the transport distances are much greater. Additional
guidance and details on the types of analyses useful for exceptional events demonstrations can be
found on the exceptional events website, including the Wildfire Resource Document, 2016
Wildfire Guidance and the Updated Frequently Asked Questions document. The tiering structure
and analyses described in this document apply only to exceptional events influencing PM2.5
concentrations. The tiering structure and supporting analyses for ozone events are outlined in the
2016 Wildfire Guidance. Agencies intending to develop ozone demonstrations should follow that
guidance and discuss with their EPA Regional office when determining what evidence is
necessary for a particular demonstration.

Section 3 of this document provides a technical explanation of EPA's approach and methodology
for establishing the tiers and the basis for the Tiering Screening Tool. Section 4 of this document
discusses the conceptional model portion of an exceptional events demonstration with
information relevant to PM2.5 and wildland fire-related events. Section 5 describes how an air
agency can use the tier level approach to determine the evidence needed to establish a clear
causal relationship in a wildland fire PM2.5 exceptional events demonstration.

3. Overview of the EPA's Methodology to Identify Tiers

In developing the tiering approach described in this document, the EPA focused on a
methodology that would provide a quantifiable metric for each tier in a manner that could be
replicated nationally. As previously indicated, the EPA used monitored concentrations relative to
the 24-hour NAAQS to establish the tiering thresholds, which can apply to both the 24-hour and
the annual PM2.5 standards. Generally, events are relatively short in duration, and, in some cases,
a single event (particularly a Tier 1 event) could lead to an exceedance or violation of both the
24-hour and the annual PM2.5 standards. Additionally, the combined effects of multiple discrete
events (especially Tier 2 and Tier 3 events), individually of inherently short duration, could lead
to an exceedance or violation of the annual standard. The EPA expects that the developed tiering
approach is appropriate for either scenario.

The tier thresholds are based on the lesser value of either (a) the most recent 5-year month-
specific 98th percentile for 24-hour PM2.5 data, or (b) the minimum annual 98th percentile for 24-
hour PM2.5 data for the most recent 5-year period. In calculating both (a) and (b), all data with

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any "Request Exclusion" (R) or fire-related "Informational Only" (I) qualifiers are excluded.
More specifically, if any monitor at the site has an R or fire-related I qualifier for the day or any
hour of the day, then the daily combined site data record is excluded from the tier threshold
calculation. Tier threshold calculations are computed at the site level, using the combined site
data record in accordance with section 3.0(d) of 40 CFR Part 50 Appendix N (Interpretation of
the National Ambient Air Quality Standards for PM2.5).8 Throughout the document the most
recent 5-year period is defined as the most recent 5-year period with Air Quality System (AQS)
certified data. Annual data certifications are required to be submitted by May 1 of the following
year. Once data certification is complete after May 1, the 5-year period will shift forward one
year to include the most recent complete year of certified data. The 98th percentiles for the tiering
threshold are calculated with the same methodology as the 24-hour PM2.5 design values.9 Tier 1
demonstrations are appropriate for 24-hour PM2.5 greater than or equal to 1.5 times the threshold
determined, Tier 2 demonstrations are appropriate for 24-hour PM2.5 greater than or equal to the
threshold but less than 1.5 times the threshold, and Tier 3 demonstrations are appropriate for 24-
hour PM2.5 less than the threshold.

Table 2. PM2.5 Exceptional Events Demonstration Tiers and Thresholds.

Tier

Measured Concentration of Event Day vs Tiering
Threshold*

Tier 1

Measured value is greater than or equal to 1.5 times the
tiering threshold

Tier 2

Measured value is greater than or equal to the tiering
threshold and less than 1.5 times the tiering threshold

Tier 3

Measured value is less than the tiering threshold

* The tiering threshold is defined as the lesser value with all "Request Exclusion" (R) and fire-related
"Informational Only" (I) qualifiers excluded of either (a) the most recent 5-year month-specific 98th percentile for
24-hour PM2 5 data, or (b) the minimum annual 98th percentile for 24-hour PM2 5 data for the most recent 5-year
period.

To determine whether a relationship exists between approved demonstrations and the 98th
percentile tiering thresholds methodology, the EPA compiled and assessed numerous concurred-
on 24-hour PM2.5 exceptional events demonstrations due to wildland fire smoke to compare to
the proposed tiers. The EPA evaluated events from EPA Regions 5, 8, 9, and 10 in this
analysis.10 The EPA also included in the comparison, the results from three well-documented
case studies focused on the eastern and western United States that, as of the date of this
document, have not yet been submitted as exceptional events or concurred on by the EPA, but
that the EPA independently determined would most likely be Tier 1 events. The eastern wildland

8	40 CFR 50 Appendix N(3.0)(d).

9	The 98th percentile is calculated based on the directions in the Procedures and Equations for the 24-hour PM2 5
NAAQS located at in Appendix N of 40 CFR Part 50(4.0)(4.5)(a).

10	Specifically, the EPA assessed events from the states of California, Maryland, Pennsylvania, Ohio, Oregon, Idaho,
Utah, and Montana. A summary of these data and the related analyses are included in the Excel spreadsheet, "Test
Tiering Data and Sites" in Docket No. EPA-HQ-OAR-2023-0586.

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fire smoke case focused on the Canadian wildland fires in 2023 and the western wildland fire
smoke case focused on the Camp Fire in 2018 and the August Complex in 2020, both in
California.

The EPA chose to base the PM2.5 tiering threshold on a 98th percentile statistic, since this statistic
is already in use in PM2.5 NAAQS calculations and represents a site-specific high PM2.5 value
near the top of the distribution of ambient PM2.5 data.

To determine a 98th percentile that is most representative of a time period without smoke
impacting air quality, the EPA calculated the 98th percentile in two ways and used the lesser of
the two for comparison to the measured value. The first method was to calculate the 98th
percentile for a specific month over a 5-year period. This approach recognizes that many
monitoring sites have periods of seasonally high and low PM2.5, and that the event concentration
should be evaluated against other seasonally appropriate data. The second method was to
calculate the 98th percentile for each year in the 5-year period and take the lowest year of the
five. To ensure that the percentiles were better representative of smoke free air, the EPA
excluded all data with any "Request Exclusion" (R) or fire-related "Informational Only" (I)
qualifiers.11 More specifically, if any monitor at the site has an R or fire-related I qualifier for the
day or any hour of the day, then the daily combined site data record is excluded from the tier
threshold calculation. Tier threshold calculations are computed at the site level, using the
combined site data record in accordance with section 3.0(d) of 40 CFR Part 50 Appendix N
(Interpretation of the National Ambient Air Quality Standards for PM2.5).

The EPA finalized the tiers by first evaluating the ratio of the tiering threshold to the measured
values for PM2.5 concurred on events and the three case studies focused on the eastern and
western United States. The EPA then evaluated whether each event would be a Tier 1, 2, or 3
demonstration based on the criteria discussed previously. The PM2.5 exceptional events
demonstration tiers identified in Table 2 are the result of these analyses. For the 169 concurred
on exceptional events monitor days evaluated against the calculated tier, most (129 monitor days,
76%) of the measured concentrations fell within the expected tier in Table 2. For the majority of
the remainder of concurred on exceptional events (38 monitor days, 22%), the calculated tier was
greater than the expected tier, and thus the calculated tier was conservative. Instances of the

11 "Qualifier" is the common terminology for a data qualifier code in AQS. Within AQS, air agencies can use two
types of data qualifier codes: Informational Only qualifiers ("I") or Request Exclusion qualifiers ("R"). The EPA
uses the following qualifier codes to describe fires: "IF" - Fire - Canadian (Informational Only); "IG" - Fire -
Mexico/Central America (Informational Only); "IH" - Fireworks (Informational Only); "IM" - Prescribed Fire
(Informational Only); "IP" - Structural Fire (Informational Only); "IT" - Wildfire - US (Informational Only); "RF"
- Fire - Canadian (Request Exclusion); "RG" - Fire - Mexico/Central America (Request Exclusion); "RM" -
Prescribed Fire (Request Exclusion); "RP" - Structural Fire (Request Exclusion); and "RT" - Wildfire - US
(Request Exclusion). The EPA also has the qualifier codes "IF/RF" - Fire - Canadian ("IF/RF"), and "IG/RG" -
Fire - Mexico/Central America ("IG/RG"), because these qualifiers indicate the jurisdictional origin of the fire (i.e.,
outside of the submitting state/outside of the United States). Please note that when developing this tiering approach,
the EPA did not exclude all qualified data, only those identified as wildfires.

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calculated tier being greater than expected tier can occur if historical wildland fire impacted days
were not flagged in the AQS system, and the EPA expected this to be the case with some of the
monitor days evaluated. In only two cases of the 169 concurred on exceptional events, was the
expected tier greater than that calculated; thus, the EPA found this to be a well-reasoned method
for determining the tiering.

The EPA tested various tier thresholds for PM2.5 wildland fire exceptional events
demonstrations. The analysis described explains how the EPA arrived at the conclusion that it is
reasonable to use a tiering threshold based on the lesser of (a) the two 98th percentiles, the 5-year
month specific 98th percentile, or (b) the minimum annual 5-year 98th percentiles. This tiering
approach to PM2.5 wildland fire exceptional events demonstrations assists agencies with
determining the amount of evidence necessary to demonstrate a clear causal relationship between
wildland fire smoke and the exceedance or violation.

Additional Information on EPA's Literature Review

Fires, including both wildland fires and prescribed fires, are estimated to account for more than
43 percent of the nation's primary emissions of PM2.5.12In recent years, the frequency and
magnitude of wildland fires have increased.13 Fires can impact PM2.5 concentrations by emitting
direct PM2.5 along with hundreds of gaseous compounds. The gaseous compounds include
nitrogen oxides (NOx), carbon monoxide (CO), methane (CH4), and hundreds of volatile organic
compounds (VOCs), including many oxygenated VOCs (OVOCs).14 This chemical complexity
makes wildland fire smoke very different from typical industrial pollution. A key challenge for
understanding fire impacts on air quality is the large variability from fire to fire in both the
quantity and composition of emissions. Emissions can vary as a function of the amount and type
of fuel, meteorology, and burning conditions. These variations give rise to large uncertainties in
the emissions from individual fires. Once emitted, wildland fire smoke undergoes chemical
transformations in the atmosphere, which alter the mix of compounds and generate secondary
pollutants, such as ozone and secondary organic aerosol. Fire emissions can affect both nearby
and distant geographic areas beyond the actual location of the wildland fires. Most smoke in the
United States is associated with wildland fires in the United States, but fires outside the country
can also impact air quality in the United States. In 2017, high PM2.5 in the Pacific Northwest was

12 U.S. EPA (2021b). 2017 National Emissions Inventory: January 2021 Updated Release, Technical Support
Document. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Research
Triangle Park, NC. U.S. EPA. February 2021. Available at https.V/www.epa.gov/sites/production/files/2021-
02/documents/nei2017_tsdJiillJan2021.pdf

13U.S. EPA (2019). Integrated Science Assessment (ISA) for Particulate Matter (Final Report). U.S. Environmental
Protection Agency, Office of Research and Development, National Center for Environmental Assessment.
Washington, DC. U.S. EPA. EPA/600/R-19/188. December 2019. Available at

https://www.epa.gov/naaqs/particulate-matter-pm-standards-integrated-science-assessments-current-review.
14 Jaffe, D., O'Neill, S., Larkin, N., Holder, A., Peterson, D., Halofsky, J., Rappold, A., 2020. Wildfire and
prescribed burning impacts on air quality in the United States. Journal of the Air & Waste Management Association
70, 583-615.

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associated with large fires in British Columbia, Canada. These same fires were associated with
smoke transport to Europe and strong thunderstorm-pyrocumulonimbus activity, which injected
smoke into the stratosphere. Large fires in Quebec, Canada have affected air quality in the
northeast United States, and smoke from fires from Mexico and Central America have reached
Texas.

4. Conceptual Model of an Event

The Exceptional Events Rule requires that demonstrations include a narrative conceptual model
describing the event.15 To be meaningful and clearly interpreted, air agencies should tie all
supporting technical analyses to this simple narrative describing how emissions from a specific
fire (or group of fires) caused PM2.5 exceedances or violations at a particular location and how
these event-related emissions and resulting exceedances or violations differ from typical high
PM2.5 episodes in the area resulting from other natural and anthropogenic sources of emissions.
This narrative description of the cause of the exceedance and the supporting data and technical
analyses will provide a consistent framework by which the EPA can evaluate the evidence in a
submitted exceptional events demonstration. Because this narrative should appear at or near the
beginning of a demonstration, it will help readers and the reviewing EPA Regional office
understand the event formation and the event's influence on monitored pollutant concentrations
before the reader reaches the portion of the demonstration that contains the technical evidence to
support the requested data exclusion. The EPA expects that much of the information the air
agency discussed with or submitted to the EPA during the Initial Notification process would also
be useful in the narrative conceptual model section of a demonstration. The narrative conceptual
model should describe the principal features of the interaction of the event and how direct PM2.5
from the event was transported to the monitor(s) that measured the exceedance or violation.

The EPA expects that, in most cases, the conceptual model of the event will be a brief narrative
of the specific facts leading up to, and directly relevant to, the exceedance or violation date(s).
For example, it can be a description of what is known about the specific fire (or group of fires)
whose emissions impacted the monitor, the meteorological conditions leading to emissions being
transported from the fire to the monitor, the monitored value, and the typical levels of PM2.5
impacting the monitor in non-event conditions. Extensive presentations comparing patterns not
directly linked to the specific event (e.g., drought conditions, climate analyses) are not typically
needed. As discussed in the 2016 Wildfire Guidance, the conceptual model must also discuss the
regulatory significance of the event.

15 40 CFR 50.14(c)(3)(iv)(A).

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5. Clear Causal Relationship between the Specific Event and the
Monitored Concentration

5.1 Overview and Exceptional Events Rule Provisions

The Exceptional Events Rule requires that demonstrations address the technical element that "the
event affected air quality in such a way that there exists a clear causal relationship between the
specific event and the monitored exceedance or violation"16 supported, in part, by the
comparison to historical concentrations and other analyses. Air agencies must support the clear
causal relationship with a comparison of the PM2.5 data requested for exclusion with historical
concentrations at the air quality monitor.17 In addition to providing this information on the
historical context for the event-influenced data, air agencies must further support the clear causal
relationship criterion by demonstrating that the fire's emissions were transported to the monitor,
and that the emissions from the fire influenced the monitored concentrations.

The three analytical tiers described in this document, and summarized in Table 3, are intended to
assist air agencies in determining the appropriate analyses to include in an exceptional events
demonstration submission. Air agencies are encouraged to work with their reviewing EPA
Regional office to verify the appropriate tier and to identify sufficient information to support an
exceptional events demonstration.

Tier 1 analyses for the clear causal relationship are likely appropriate for wildland fire events
that cause extreme PM2.5 impacts resulting in 24-hour average concentrations well-above
historical concentrations, thus requiring fewer pieces of evidence. Tier 2 clear causal analyses
are appropriate when the impacts of the wildland fires on PM2.5 concentrations are less extreme
in comparison to historical 24-hour concentrations and require more evidence than Tier 1
analyses. Tier 3 clear causal analyses should be used for events in which 24-hour PM2.5
concentrations are near or within the range of historical concentrations, and thus require more
evidence of the clear causal relationship between the fire and the measured exceedance or
violation than Tiers 1 or 2. Figure 1 provides a simplified process diagram of the event
demonstration tiering process for PM2.5.

Section 5.3 discusses Tier 1 analyses; Section 5.4 discusses Tier 2 analyses and Section 5.5
discusses Tier 3 analyses.

16	40 CFR 50.14(c)(3)(iv)(B).

17	40 CFR 50.14(c)(3)(iv)(C).

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Table 3. Summary of Tiered Analyses.

Tier 1: Section 5.3

Tier 2: Section 5.4

Tier 3: Section 5.5

The event clearly influences
monitored PM2.5 exceedances or
violations when they occur in an area
that typically experiences lower PM2.5
concentrations. This tier is associated
with a PM2.5 concentration that is
clearly higher than non-event related
concentrations (greater than or equal
to 1,5x the tiering threshold) for the
historical month or annual period, as
appropriate.

The event's PM2.5
influences are higher than
most or all non-event
related concentrations
(between 1 to 1.5xthe
tiering threshold), and the
weight of evidence shows a
clear causal relationship.

The event does not
fall into the specific
scenarios that qualify
for Tier 1 or Tier 2,
but the clear causal
relationship criterion
can still be satisfied
by a weight of
evidence showing.

Figure 1. Process to Determine the Appropriate Tier for the Clear Causal Relationship Criterion

Determine the Tiering Threshold for the
Candidate Event Day

No

r

Is the event concentration greater than or equal
to 1.5x the tiering threshold?









Tier 2

Is the event concentration



Provide evidence that

greater than or equal to the

Yes

smoke:

tiering threshold and less



• was transported



than 1.5x the tiering



to the monitor



threshold?





and



No ^





• directly
affected the



Tier 3





monitor.



Prepare full Tier 3
demonstration.







Yes

1

Tier 1

Provide evidence
that smoke was
transported to the
monitor.

5.2 Comparison of Candidate Event Data to Tiering Thresholds

As discussed in more detail in Section 3 of this document, the determination of the appropriate
tiering level begins with an analysis of the measured PM2.5 air quality associated with the
candidate event in relation to historical concentrations. Air agencies should compare the

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concentration in question to the lesser value with all "Request Exclusion" (R) and fire-related
"Informational Only" (I) qualifiers excluded of either (a) the most recent 5-year month-specific
98th percentile for 24-hour PM2.5 data, or (b) the minimum annual 98th percentile for 24-hour
PM2.5 data for the most recent 5-year period.

As an initial screening, air agencies may generate an AMP480 report (also known as the Design
Value Report) from AQS, which includes all I qualifiers. If an event day's measured
concentration is above or equal to 1.5 times the tiering threshold calculated with only R
qualifiers excluded (as is the case with the AMP480), analyzing the data with I qualifiers would
not be necessary to determine if the candidate event demonstration is Tier 1. Please consult with
your EPA Regional office to ensure data are appropriately qualified in AQS.18

The EPA acknowledges that there may be unusual circumstances or anomalies in air agencies'
data that may affect tiering as proposed. For example, air agencies may not have removed other
instances of wildfire smoke impacts at the event site. Through discussions with the appropriate EPA
Regional office, the agency may be able to show through additional analysis that there is a more
appropriate tiering threshold for the event day than was determined by the default methodology.

Air agencies are encouraged to evaluate their data carefully and consult with their EPA Regional
office about any data anomalies on a case-by-case basis. The EPA also retains its authority and
discretion to evaluate data anomalies in submitted data and determine what tier is applicable for
a candidate event.

The following simplified example illustrates the tier level calculations. More thorough treatment
of the tiering threshold assessment is presented in sections 5.3 and 5.4.

18 "Qualifier" is the common terminology for a data qualifier code in AQS. Within AQS, air agencies can use two
types of data qualifier codes: Informational Only qualifiers ("I") or Request Exclusion qualifiers ("R"). Agencies
should use the "I" series qualifiers when identifying potential event-influenced data and the "R" series qualifiers to
identify data points for which the agency is requesting EPA's concurrence on an exceptional events exclusion. States
are required as part of the initial notification process to identify (or qualify with a data qualifier) event-associated air
quality data and create an initial event description in EPA's AQS. Attaching the "I" data qualifier is intended to
promote communication between air agencies and EPA Regional offices when air agencies begin to consider
developing an exceptional events demonstration. The "R" qualifier is added when the air agency submits a formal
request to the EPA to exclude data under the Exceptional Events Rule. "R" qualifiers are the only AQS qualifiers
that satisfy Exceptional Events Rule data qualifying as part of the required Initial Notification Process. The EPA can
act/concur only on data with "R" qualifiers.

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Simplified Example:

Candidate Event Day: July 20, 2023, 24-hr PM2.5 concentration = 72 |ig/m3

Tier Threshold (a): 98th percentile of all 24-hr PM2.5 concentrations from the month of

July in 2019-2023 = 54 |ig/m3

Tier Threshold (b): minimum annual 98th percentile 24-hr PM2.5 concentration from years

2019-2023 = {35, 29, 34, 32, 42} = 29 |ig/m3

Lesser Value of Tier Threshold (a) and (b) = 29 |ig/m3

Tier 1 Threshold: 1.5 x 29 |ig/m3 = 43.5 |ig/m3
Tier 2 Threshold: 1 x 29 |ig/m3 = 29 |ig/m3

In this simplified example, since the Candidate Event Day concentration of 72 |ig/m3 exceeds the
Tier 1 Threshold of 43.5 |ig/m3, the Candidate Event Day could involve a Tier 1 demonstration.

5.3 The Key Factor and Suggested Evidence to Include in Tier 1 Analyses

This section and Section 5.4 are intended to indicate whether a wildland fire-caused PM2.5 event
satisfies the key factors for either Tier 1 or Tier 2 clear causal analyses, then the additional
evidence described for each tier should be sufficient to support the clear causal relationship
criterion within an air agency's exceptional events demonstration for that particular event.

Key Factor for Tier 1 Analyses - Distinct high levels of monitored 24-hour PM2.5 concentrations
when compared to historical monthly or annual 24-hour levels ofPM2.5. The key factor that
delineates event-related monitored PM2.5 concentrations for Tier 1 analyses is the uniqueness of
the concentration when compared to the typical levels of PM2.5. For example, if an event-related
exceedance occurs during a time of year that typically has no exceedances, then that event-
related exceedance may be more clearly attributable to a fire than event-related concentrations
that occur during the same month or season as typical high PM2.5 concentrations. If the event-
related exceedance occurs during a time of year in which other exceedances have been measured,
the magnitude of the event-related exceedance should be clearly larger than any of the other
measured exceedances that are not attributable to other EPA concurred upon or otherwise
documented exceptional events. The EPA expects that Tier 1 analyses supporting the clear causal
relationship criterion may be appropriate for wildland fires that clearly influence monitored
PM2.5 exceedances or violations resulting in event concentrations that are clearly higher than
non-event related concentrations. Many "extreme" wildfire events may be suitable for Tier 1
analyses. In these situations, PM2.5 impacts should be accompanied by clear evidence that the
wildland fire's emissions were transported to the location of the monitor.

Criteria: The EPA has determined that event-related exceedances should be greater than or equal
to 1.5 times the tiering threshold as described for that candidate event day to be clearly
distinguishable from non-event related concentrations.

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An analysis like the one in Figure 219 should be provided to support the air agency's determination
of the tiering threshold of the event, appropriate to the specific option the agency used to determine
the tiering threshold. Agencies may choose to plot data with "R" qualified data excluded and/or
"R" and "I" qualified data excluded.

Simplified Example with Corresponding Figure for 2022 Wildfire Smoke Event affecting
Oakridge, OR.

Candidate Event Days: September 9-11; 17-21; 23-27; 30, 2022
Candidate PM2.5 Concentrations range from 58.9 ug/'m3 - 298.6 |ig/nr
Tier Threshold Calculation

a.	981h percentile of all 24-hr PM2.5 concentrations from the month of
September in 2018-2022 with all R and "informational only" (I) fire-
related qualified days excluded: = 233.4 |ig/m3.

b.	Minimum annual 98th percentile 24-hr PM2.5 concentration with all R and
"informational only" (I) fire-related qualified days excluded from years
2018-2022 = 26.2 jig/m3.

Lesser Value of (a) and (b) = 26.2 |ig/m3 (Tier 2 threshold) Tier 1 threshold = 1.5*26.2 =
39.3 jig/m3.

AQS Site ID 410392013

ft

500

400

2/4/2019	6/18/2020	10/31/2021	3/15/2023	7/27/2024

Date

Figure 2: Time series plot of PM2.5 daily combined site data for site 41-039-2013 (Oakridge,
OR) 2018-2023. The tier thresholds are based on 2018-2022, the most recent 5-year period of
certified data at the time of publication of this document. Tier 2 values are displayed as gold

19 This example figure was created on April 2,2024, from the PM2.5 Tiering Tool available at:

https:Jfymw.epa.gov/air-quaIitv-analvsis/pm25-tiering-tool-exceptional-events-anaIvsis

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dots. Tier 1 values are displayed as dark red dots. All candidate event-influenced days in this
example would qualify as Tier 1.

Evidence that the Event Emissions Were Transported to the Monitor(s)

In addition to the supporting analysis for the Tier 1 key factor described for a Tier 1 clear causal
relationship analysis, the air agency should also supply at least one piece of additional evidence
to support that the emissions from the fire were transported to the monitor location {i.e., the
latitude and longitude). For example, this evidence could include a trajectory analysis or satellite
imagery20 of the smoke plume. The trajectory analysis or combination of satellite and surface
measurements to show transport are described in more detail in Section 3.4.2 of the 2016
Wildfire Guidance document and its appendix. Additionally, more information on other
trajectory models is included in the Wildfire Resource Document.

5.4 The Key Factor and Suggested Evidence to Include in Tier 2 Analyses

If a wildland fire event influences PM2.5 concentrations, but this influence is not distinctly higher
than or equal to non-event related concentrations as defined as 1.5 times the tiering threshold,
then the event would not meet the Tier 1 key factor and the analyses for a Tier 1 event would not
be sufficient to show a clear causal relationship for the event. The air agency should then
determine whether Tier 2 analyses or Tier 3 analyses would be appropriate.

Key Factor for Tier 2 Analyses - High levels of monitored 24-hour PM2.5 concentrations, when
compared to historical monthly or annual 24-hour levels ofPM2.5. The EPA believes that it is
appropriate to use a similar approach to the analysis for Tier 1 to determine if a Tier 2 analysis
provides sufficient evidence to satisfy the clear causal relationship criterion for wildland fire
PM2.5 demonstrations. The EPA recommends a Tier 2 analysis when event-related exceedances
are greater than or equal to the tiering threshold but less than 1.5 times the tiering threshold, as
previously described. Applying this key factor recognizes that an air agency will likely need
more detailed information to establish a clear causal relationship between smoke transport from
the event to the monitored exceedance.

Evidence that the Event Emissions Affected the Monitor(s) and reached the Ground Level

In addition to the supporting analysis for the Tier 2 key factor, the air agency should provide
evidence showing the emissions from the wildland fire were transported to the monitor location
(i.e., the latitude and longitude). Air agencies can use, as a technical piece of evidence, either a
combination of trajectory analysis and surface measurements or satellite surface measurements to
show this transport. (These recommendations are the same as for Tier 1 demonstrations in Section
5.3 but are explained here again for completeness).

20 https://www.epa.gov/hesc/remote-sensing-information-gateway and
http://arset.gsfc.nasa.gov/airquality/applications/fires-and-smoke may be helpful resources.

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For the Tier 2 demonstration, the air agency should also supply at least two additional pieces of
evidence, one of which must be quantitative (see items 1-6 in the following list), to support a
weight of evidence conclusion that it was the emissions from the wildland fire, rather than other
sources, that affected the monitored PM2.5 concentration. Air agencies can use the following
example evidence to demonstrate the fire emissions were present at the altitude of the monitor(s).
This evidence could include, but is not limited to, the following:

1.	Evidence of changes in hourly temporal patterns of PM2.5 during the event, compared
to typical non-event data.

2.	Photographic or videographic evidence of ground-level smoke at or near the monitor

3.	Ground level measurements of corroborating pollutant concentrations [CO, PM
(hourly mass or speciation), VOCs, or altered pollutant ratios]

a.	Plots of co-located or nearby CO, PM2.5, PM10, or O3 and PM2.5 precursor
concentrations in the same airshed (or nonattainment/near nonattainment area)
that have increases, or differences, in typical behavior that indicate the wildland
fire's emissions influenced the monitor. Include an explanation of the plots.

b.	The timing and spatial distribution of NO, NO2, and O3, shown with data from
multiple monitoring sites. These pollutant concentrations may vary when
influenced by a wildland fire plume. Elevated levels that are widespread
throughout a region, or are upwind of the urban area, may be due to impact of a
fire plume. Peaks at locations and times different than those normally seen in an
anthropogenic O3 episode can indicate fire plume impact.

c.	Differences in CO:NOx and CO:PMio ratios: The ratio of CO and NOx emissions
depends on their source; for agricultural burning it is about 10-20, for wildfire and
prescribed wildland burning it is about 100,21 whereas for high-temperature fossil
fuel combustion sources it is more like 4.22 Thus, an unusually high CO:NOx ratio
is consistent with wildfire impact. Similarly, the CO:PMio emission ratio is 8-16
in wildfires, but 200-2000 for vehicles.23 However, changes in CO, and CO ratios,
might be difficult to discern in an area dominated by vehicular CO, as the fire
signal may be small in comparison.

d.	PM speciation data: PM2.5 emissions from fires often contain elevated levels of
organic carbon (OC), elemental carbon (EC), and are often enriched in water
soluble potassium (K).24 Levoglucosan, a biomass burning tracer molecule, can

21	Dennis, A., Fraser, M., Anderson, S., Allen, D., 2002. Air pollutant emissions associated with forest, grassland,
and agricultural burning in Texas. Atmospheric Environment, 36, 3779-3792.

22	Chin, M., Jacob, D.J., Munger, J.W., Parrish, D.D., Doddridge, B.G., 1994. Relationship of ozone and carbon
monoxide over North America. Journal of Geophysical Research, 99, 13565-14573.

23Phuleria, H., Fine, P., Zhu, Y., Sioutas, C., 2005. Air quality impacts of the October 2003 Southern California
wildfires, Journal of Geophysical Research-Atmospheres, 110.

24 Watson, J., Chow, J., Houck, J., 2001. PM2 5 chemical source profiles for vehicle exhaust, vegetative burning,
geological material, and coal burning in Northwestern Colorado during 1995. Chemosphere, 43, 1141-1151.

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serve as an indicator for wildfire smoke; PMio from wood smoke is 14 percent or
higher levoglucosan by mass.25 Co-located or nearby particle speciation data (OC,
EC, K, and/or levoglucosan) can be used to indicate fire impacts.

4.	Smoke models (e.g., High-Resolution Rapid Refresh, Rapid Refresh, FireWork,
BlueSky)

5.	Secondary (non-regulatory) data (e.g., special purpose, sensors, emergency, etc.
monitors)

6.	National Weather Service reports (e.g., Area Forecast Discussions)

7.	Local news reports

8.	Social media reports

While fires typically generate emissions of CO, NO, NO2, VOCs, PM10, and PM2.5,
anthropogenic sources, such as industrial and vehicular combustion, also emit these pollutants.
Therefore, the Tier 2 demonstration should distinguish the difference in the non-event pollutant
behavior (e.g., concentration, timing, ratios, and/or spatial patterns) from the behavior during the
event impact to more clearly show that the emissions from the wildland fire(s) affected the
monitor(s).

5.5 Tier 3 Analyses to Support the Clear Causal Relationship

Wildland fire-caused PM2.5 events not meeting the tiering threshold criteria for Tier 1 or Tier 2
analyses, or otherwise determined by the EPA to need only a Tier 1 or Tier 2 analysis, will be
considered by the EPA based on the Tier 3 level of analyses. Tier 3 is appropriate when the
relationship between the wildland fire and the PM2.5 exceedance/violation is more complicated
than the relationship in a Tier 2 analysis and thus would require more supporting documentation.
Tier 3 demonstrations are appropriate when the measured 24-hour PM2.5 concentration is less
than the tier threshold and there are not any other extenuating circumstances or data anomalies
that would point to a Tier 2 analysis being sufficient. These Tier 3 events include areas where
monitors are impacted by: multiple sources of emissions, including industrial sources; multiple
event types, including dust events, volcanic events, and cultural events like fireworks during
holidays or other events; and/or prescribed fires. Tier 3 may also be appropriate when an agency
believes long-range wildland fire smoke has impacted monitors that are thousands of miles away
from the fire source, and the PM2.5 concentration is closer to typical days of non-fire influenced
concentrations. Additionally, Tier 3 may be appropriate when the air agency has not identified a
specific wildland fire at surface areas along the long-range transport path and/or where

25 Jordan, T., Seen, A., Jacobsen, G., 2006. Levoglucosan as an atmospheric tracer for woodsmoke. Atmospheric
Environment, 40, 5316-5321. Kansas Department of Health and Environment, 2012. State of Kansas Exceptional
Events Demonstration April 6, 12, 13, and 29, 2011. Department of Health and Environment, Division of
Environment, Bureau of Air. November 27, 2012. http://www.epa.gov/sites/production/files/2015-
05/documents/kdheexeventsJinal_042011.pdf.

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concentrations along the path do not demonstrate transport. When addressing the Tier 3 clear
causal relationship criterion within the demonstration, in addition to the Tier 2 requirements, the
air agency might compile the following evidence to add to the demonstration, or other evidence
as appropriate for the event:

•	backward and forward trajectories from the wildland fire to the affected monitor

•	analysis of hourly PM, meteorological, or other available data

•	a vertical PM2.5 profile or model simulations

Together this information could satisfy the clear causal relationship criterion under a weight of
evidence approach. More complicated relationships between the wildland fires and influenced
PM2.5 concentrations may require additional detail to satisfy the clear causal relationship
element. The EPA does not expect an air agency to prepare all identified analyses but only those
that would be needed to establish a clear causal relationship under the weight of evidence
approach. As with all exceptional events demonstrations, the submitting air agency and the EPA
Regional office should discuss the appropriate level of evidence during the Initial Notification
process.

In addition to the evidence suggested for a Tier 1 or Tier 2 demonstration, an air agency should
provide evidence showing the emissions from the wildland fire were transported to the monitor
location. The Tier 3 clear causal relationship analyses could include multiple analyses from those
examples listed in Sections 5.3 and 5.4. Each additional piece of information that supports the
event's influence will strengthen the air agency's request for data exclusion under the
Exceptional Events Rule. Depending on evidence supplied in other sections of the demonstration,
an air agency may further support the clear causal relationship between the wildland fire and the
PM2.5 exceedance with the items listed in more detail:

1.	Buddy site comparisons26

2.	Emissions (maps, typical emissions)

3.	Multi-pollutant corroboration

4.	Ceilometer data

5.	Statistical Regression Modeling

6.	Photochemical modeling

5.6 Summary of Evidence Under Three Supporting Analysis Tiers that Could be Used to
Meet the Exceptional Events Rule Elements

Table 4 summarizes the technical information that air agencies can use to support the clear causal
relationship under each of the three analytical tiers for wildland fire-related exceptional events
demonstrations.

26 Compare concentrations at one site to nearby sites to look for anomalies.

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Table 4. Clear Causal Relationship Technical Demonstration Components Recommended for
Tier 1, Tier 2, and Tier 3 Demonstrations.

Tier 1 Analyses Should Include

Tier 2 Analyses Should Include

Tier 3 Analyses Should Include

The tiering threshold used for the event
day, which calculation methodology
was used, and comparison of the 24-
hour PM value to the tiering threshold.

The tiering threshold used for the event
day, which calculation methodology
was used, and comparison of the 24-
hour PM value to the tiering threshold.

The tiering threshold used for the
event day, which calculation
methodology was used, and
comparison of the 24-hour PM value
to the tiering threshold.

Comparison of the fire-influenced
exceedance with historical
concentrations, by providing two data
plots appropriate to the chosen tiering
threshold calculation methodology (R
qualified data removed, R and I qualified
data removed).

Comparison of the fire-influenced
exceedance with historical
concentrations, by providing two data
plots appropriate to the chosen tiering
threshold calculation methodology (R
qualified data removed, R and I qualified
data removed).

Comparison of the fire-influenced
exceedance with historical
concentrations, by providing two data
plots appropriate to the chosen tiering
threshold calculation methodology (R
qualified data removed, R and I
qualified data removed).

Evidence of transport of fire emissions
from fire to the monitor (one of these):

•	Trajectories linking fire with the
monitor (forward and backward),
considering height of trajectories,
or

•	Satellite evidence in combination
with surface measurements.

Evidence of transport of fire emissions
from fire to the monitor (one of these):

•	Trajectories linking fire with the
monitor (forward and backward),
considering height of trajectories,
or

•	Satellite evidence in combination
with surface measurements.

Evidence of transport of fire emissions
from fire to the monitor (one of these):

•	Trajectories linking fire with the
monitor (forward and backward),
considering height of
trajectories, or

•	Satellite evidence in combination
with surface measurements.



Two additional pieces of evidence
demonstrating that the fire emissions
affected the monitor, as identified for
Tier 2 analyses.

At least three additional pieces of
evidence demonstrating that the fire
emissions affected the monitor, which
could include the items in the next
box.





Additional evidence to add to the
weight of evidence demonstration, or
other evidence as appropriate for the
event, including:

•	Backward and forward
trajectories from the wildland
fire to the affected monitor,

•	Analysis of hourly PM,
meteorological, or other
available data, and

•	a vertical PM2 5 profile or model
simulations.

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United States Office of Air Quality Planning and Publication No. EPA-
Environmental Protection Standards 457/R-24-001
Agency Air Quality Policy Division April 2024
	Research Triangle Park, NC	

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