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2020 National Emissions Inventory Technical
Support Document: Nonpoint Overview


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EP A-454/R-23 -001 f
March 2023

2020 National Emissions Inventory Technical Support Document: Nonpoint Overview

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


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Contents

List of Tables	i

List of Figures	i

6	Nonpoint Overview	6-1

6.1	Nonpoint source approaches	6-1

6.2	Sources of data overview and selection hierarchies	6-1

6.2.1	Nonpoint Survey updates for the 2020 NEI	6-3

6.2.2	Wagon Wheel and Input Templates	6-4

6.2.3	SLT-submitted emissions	6-10

6.2.4	Data selection rules: cross-dataset tagging	6-16

6.3	Nonpoint PM augmentation	6-17

6.4	Nonpoint HAP Augmentation	6-18

6.5	EPA nonpoint data	6-18

6.6	Nonpoint Quality Assurance	6-21

6.6.1	The Iterative QA Report	6-22

6.6.2	Expected Pollutants List	6-24

6.6.3	Completeness Reports	6-24

6.6.4	EPA-estimated emissions QA	6-24

6.6.5	Input Template Review	6-24

6.6.6	Reviewing S/L/T data after the EIS submittal window has closed	6-24

6.6.7	Data Tagging Summary	6-25

6.6.8	Final Review of EPA-generated tool data	6-27

6.6.9	Final Nonpoint Selection review	6-27

List of Tables

Table 6-1: Data sources and selection hierarchy used for most nonpoint sources	6-1

Table 6-2: List of Wagon Wheel source categories; categories needing point inventory subtraction noted

	6-4

Table 6-3: S/L/T Input Templates submitted for the 2020 NEI	6-5

Table 6-4: Summary of Wagon Wheel tool updates in the 2020 NEI	6-8

Table 6-5: S/L/T nonpoint emission submittals for each category that EPA estimates	6-10

Table 6-6: EPA Nonpoint TSD Sections with indication of possible Point inventory subtraction	6-19

Table 6-7: Key Nonpoint QA issues, causes, and steps taken to address issues	6-21

Table 6-8: S/L Nonpoint Survey responses tagged with rationale provided	6-26

List of Figures

Figure 6-1: Example of nonpoint iterative QA report	6-23

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6 Nonpoint Overview

This section includes all sources that are in the nonpoint data category, including biogenics, and new for the
2020 NEI, all fires, including wildfires, prescribed burning, and agricultural field burning. These sources are
reported at the county level, though some sources such as shipping lanes and ports are more-finely resolved to
the county/shape identifier (ID) (polygon) level. Stationary sources that are inventoried at facilities and stacks
(coordinates) are discussed in the Point Section 3. This section discusses all sources in the Nonpoint inventory.
Some "nonroad" mobile sources such as trains and commercial marine vessels reside and are discussed here in
the nonpoint data category, not in the Nonroad Equipment Section 4.

6.1	Nonpoint source approaches

Nonpoint source data are provided by state, local, and tribal (S/L/T) agencies, and for certain sectors and/or
pollutants, they are supplemented with data from the EPA. This section describes the various sources of data
and the selection priority for each of the datasets to use for building the National Emissions Inventory (NEI)
when multiple data sources are available for the same emissions source. Section 2.2 provides more information
on the data selection process.

6.2	Sources of data overview and selection hierarchies

Table 6-1 describes the datasets comprising most of the nonpoint inventory, and the hierarchy for combining
these datasets in construction of the NEI. Rail line-specific data are provided in the stand-alone dataset
"2020EPA_Rail". While the bulk of these datasets are for stationary sources of emissions, some of these datasets
contain mobile sources so that emissions from ports, shipping lanes, rail lines, and in-flight aircraft (lead
emissions only) could be included as nonpoint sources. The following table includes the rationale for why each
dataset was assigned its position in the hierarchy. We excluded certain pollutants from stationary sources in the
2020 NEI: greenhouse gases for stationary sources and pollutants in the pollutant groups "dioxins/furans" and
"radionuclides"1. The EPA has not evaluated the completeness or accuracy of the S/L/T agency dioxin and furan
values nor radionuclides and does not have plans to supplement these reported emissions with other data
sources to compile a complete estimate for dioxin and furans nor radionuclides as part of the NEI.

Table 6-1: Data sources and selection hierarchy used for most nonpoint sources

Dataset name

Description and Rationale for the Order of the Selected Datasets

Order

Responsible Agency Data Set

S/L/T agency submitted data. These data are selected ahead of other
datasets. The only other situation where S/L/T agency emissions are
not used is where certain records are tagged in the Emissions
Inventory System (EIS) (at the specific source/pollutant level). This
occurs: 1) for hierarchy purposes to allow EPA nonpoint emissions to
be used ahead of S/L/T agency data where states asked for EPA data
to be used in place of their data and 2) where S/L/T agency data
were suspected outliers, unexpected pollutants for a given process,
or submitted for a source category not widely reported or significant.

1

1 Dioxins/furans include all pollutants with pollutant category name of: Dioxins/Furans as 2,3,7,8-TCDD TEQs, or
Dioxins/Furans as 2,3,7,8-TCDD TEQs - WH02005. Radionuclides have the pollutant category name of "radionuclides" The
specific compounds and codes are in the pollutant code tables in EIS.

6-1


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Dataset name

Description and Rationale for the Order of the Selected Datasets

Order

2020EPA_Cr_Aug

Hexavalent and trivalent chromium speciated from S/L/T agency
reported chromium. EIS augmentation function creates the dataset
by applying multiplication factors by SCC, facility, process or North
American Industry Classification System (NAICS) code to S/L/T
agency total chromium. See Section 2.2.2.

2

2020EPA_PMaug

PM components added to gap fill missing S/L/T agency data where
S/L/T agency have missing emissions across PM components. Uses
ratios of emission factors from the (new for 2020) EIS PM
Augmentation function for covered source classification codes
(SCCs). PM augmentation is discussed in Section 6.3.

3

2020SLT_H APAug_N P

HAP data computed from S/L/T agency criteria pollutant data using
ratios of HAP to CAP emission factors. The emission factors used to
create the ratios are the same emission factors as are used in
creating the EPA estimates (i.e., in the EPA nonpoint emission tools).
This dataset is below the S/L/T agency data so that the S/L/T agency
HAP data are used first. HAP augmentation is discussed in Section
6.4.

4

2020EPA_HAPAug-PMAug

This dataset was created in the same fashion as the
2020SLT_HAPAug_NP dataset above and is a supplement to it. This
dataset contains HAPs calculated by applying a ratio to PM25-PRI
emissions, for those instances where the S/L/T dataset did not
contain any PM25-PRI emissions, but the PM augmentation routine
was able to calculate a PM25-PRI value from some PM species that
was reported by the S/L/T.

5

2020EPA_NON POINT

All nonpoint EPA estimates are included in this dataset except those
listed elsewhere in this table. This dataset includes sources with and
without point source subtraction and outputs from most of the EPA
tools, including the "Wagon Wheel" with (if provided) SLT-submitted
Input Templates (see Section 6.2.2). This dataset also includes EPA-
estimated biogenic, wildland fires, and commercial marine vessel
emissions. Other sources in this dataset include agricultural fertilizer
application, most livestock waste, industrial and
commercial/institutional fuel combustion, residential wood
combustion, solvent utilization, oil and gas exploration and
production, open burning, agricultural field burning, road and
construction dust, and portable fuel containers.

6

2020EPA_HAPAugWWSLInput

This dataset was created in the same fashion as the
2020SLT_HAPAug_NP dataset above and is a supplement to HAPs
not generated in the 2020EPA_NONPOINT dataset via EIS HAP
Augmentation computations.

7

2020EPA_Rail

Blend of SLT-submitted and collaboratively generated diesel line and
diesel yard locomotive data (referred to as "rail" in this document)
emissions estimates. See Section 12.

8

2020EPA_Rail_HAPAug

This dataset was created in the same fashion as the
2020SLT_HAPAug_NP dataset above and is a supplement to HAPs
not generated in the 2020EPA_Rail dataset via EIS HAP
Augmentation computations.

9

2020EPA_Airports

2020 aircraft in-flight emissions (Lead only)

10

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The EPA developed all datasets listed above except for the "Responsible Agency Selection/' which contains only
S/L/T agency data. We used various methods and databases to compile the EPA generated datasets, which are
further described in subsequent subsections. The primary purpose of the EPA datasets is to add or "gap fill"
pollutants or sources not provided by S/L/T agencies, to resolve inconsistencies in S/L/T agency-reported
pollutant submissions for PM (Section 2.2.4) and to speciate S/L/T agency reported total chromium into
hexavalent and trivalent forms (Section 2.2.2). The hierarchy or "order" provided in Table 6-1 defines which data
are preferentially used when multiple datasets could provide emissions for the same pollutant and emissions
process. The dataset with the lowest order on the list is preferentially used over other datasets.

In addition to the order of the datasets, the hierarchy was also influenced by the EIS feature of data tagging
(Section 2.2.6). Any data that were tagged by EPA in any of the datasets were not used. S/L/T agency data were
tagged for three reasons: 1) S/L/Ts requested that their data not be used, 2) EPA found unexpected pollutants
for a source, and 3) sources were submitted that are not widely reported or significant (e.g., NH3 from human
perspiration and domestic animal waste). Due to continued improvements in the new nonpoint survey (next
section), there was very little need to tag EPA nonpoint data for 2020. If S/L/T agencies report zero emissions,
then backfilling with other datasets will not occur. There are two ways that S/L/T agencies can prevent
inappropriately backfilled emissions from being included in the NEI: 1) S/L/T agencies can submit zeros for any
pollutant they do not want filled in (the EPA data will otherwise fill in for all pollutants that are on the nonpoint
expected pollutant list), 2) S/L/T agencies can complete the nonpoint survey and specify "No..." to prevent any
EPA estimates from backfilling where S/L/Ts did not submit data, or 3) the EPA can add tags to backfill datasets
that prevent the tagged pollutants from being included in the NEI. The first option is most straightforward and
takes care of any possible augmentation from the numerous other datasets in the selection hierarchy. The
second option was developed as a quick tool for S/L/Ts to essentially prevent the need to "tag out" EPA data yet
achieve the same goal.

6.2.1 Nonpoint Survey updates for the 2020 NEI

The nonpoint survey, first developed for the 2014 NEI, streamlined for the 2017 NEI, underwent minimal
changes for the 2020 NEI. The purpose of the nonpoint survey is to increase the accuracy and transparency in
how the nonpoint inventory is built using EPA and S/L/T agency data. The nonpoint inventory includes all
nonpoint source categories that EPA generates estimates except for wildland fires, commercial marine vessels,
and rail line estimates.

Because each agency has their own universe of sources and inventory development approaches, each agency
reports nonpoint estimates a little differently. The nonpoint survey gathers information specifically for each SLT
regarding which source categories are covered by point, nonpoint, or both, and about where point source
reconciliation needs to be done to nonpoint activity.

For the 2020 NEI, the nonpoint survey was updated to include new source categories (e.g., agricultural silage),
new or revised SCCs (Dust from Hooves Tool), a checkbox for SLTs "Did Your Agency Provide an Input Template
for this Category?", and a tagging function for EPA inventory developers to change the Nonpoint Survey
response back to the default "Yes - Supplement my data with EPA estimates".

The nonpoint survey has an "Accept All Emissions Estimates" button on the home page for S/L/Ts that did not
submit emissions for any nonpoint sector. Note, acceptable S/L/T activity inputs (next section) provided to EPA
were absorbed into EPA tools and therefore became "EPA" estimates. For S/L/Ts that wanted to prevent some
EPA data from backfilling, there were options to edit the default responses for each SCC or accept EPA estimates
for entire sectors. The optional reasons to select "No" (and this was applied for each SCC that EPA generates

6-3


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estimates) are: 1) I do not have this Source, 2) This source is included in my Point Source contributions, 3) My
agency uses different SCCs, and 4) My inventory is complete; it does not need to be supplemented. An
additional option to select "Yes -Supplement Only for Missing Pollutants at my reported Counties or Tribe" is
provided to allow only missing (expected) pollutants to be added for locations where emissions were submitted
for at least one pollutant. More information on the nonpoint survey is available in Section 7.2.6 of the 2020 NEI
Plan. A detailed 2020 NEI nonpoint summary "2020NEI_Nonpoint_Survey_detail_25mar2023.xlsx" covering all
reporting agencies has been uploaded to the 2020 NEI Supplemental data FTP site.

6.2.2 Wagon Wheel and Input Templates

A central database, called the "Wagon Wheel", developed for the 2017 NEI, and updated for the 2020 NEI,
houses all inputs and calculates emissions for most nonpoint source categories. Prior to the 2017 NEI, EPA
shared different tools to S/L/Ts, many with the same inputs; this process was very inefficient and prone to
human error as many tools shared similar inputs and different versions of these tools were often used by S/L/Ts
vs the "final" versions ultimately regarded as "EPA" for the NEI. The Wagon Wheel links each activity input
tables to the appropriate sector/module such that refreshing one dataset ensures the next tool iteration
captures it for all appropriate sectors. The full list of nonpoint source categories/tools included in the Wagon
Wheel is provided in Table 6-2.

Table 6-2: List of Wagon Wheel source categories; categories needing point inventory subtraction noted

Wagon Wheel Source Category

Point Inventory
Subtraction?

Ability to Submit Control
Information?

Input Template
Required?

ICI Fuel Combustion

Yes

County/SCC/pollutant-level

Yes

Ag Dust (from hooves)



County/SCC-level



Ag Silage



County/SCC-level



Ag Tilling



County-level



Asphalt Paving



County/SCC-level



Aviation Gas Distribution Stage 1



County-level



Aviation Gas Distribution Stage 2



County-level



Commercial Cooking



County/SCC-level



Composting



County-level



Construction Dust: Non-Residential



County/SCC-level



Construction Dust: Residential



County/SCC-level



Construction Dust: Road



County/SCC-level



Cremation: Human and Animal



County/SCC-level



Landfills: working face (Hg-only)



County-level



Mining & Quarrying



County-level



Nonpoint Mercury (including human
cremation)



County/SCC-level



Open Burning: Land Clearing Debris



County/SCC-level



Open Burning: Municipal Solid Waste



County/SCC-level



Open Burning: Yard Waste



County/SCC-level



Publicly-Owned Treatment Works
(POTWs)

Yes

Co u nty/po 11 uta nt-level



Residential Charcoal Grilling



County-level



Residential Heating -Non-wood



County/SCC/pollutant-level



Residential Wood Combustion



County/SCC-level



Road Dust: Paved and Unpaved



County/SCC-level



6-4


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Wagon Wheel Source Category

Point Inventory
Subtraction?

Ability to Submit Control
Information?

Input Template
Required?

Solvents (to be renamed VCPs)

Yes

County/SCC-level



Stage 1 Gasoline Distribution

Yes

County/SCC-level



EPA strongly encouraged S/L/Ts to provide only inputs to the Wagon Wheel because, often late in the inventory
development cycle, EPA finds a need for a tool update (e.g., error, or new, improved information, and so if
S/L/Ts submitted emissions (rather than inputs) using an old version of the tool, then their submitted data could
be out of date or incorrect.

EPA provided blank input templates for all Wagon Wheel source categories. These blank templates included all
default activity data, and as these default activity data were updated, the input templates and the wagon wheel
were updated to incorporate it. S/L/Ts then provided their completed input templates back to EPA where their
updated data, after rudimentary quality assurance, were used to supersede the default data in the template and
ultimately the Wagon Wheel. In this process, all S/L/T-submitted input activity data became "EPA" data. Input
activity data also included information on controls and emission factors where provided.

With one key exception, S/L/Ts could opt out of submitting input templates as EPA methods did not need S/L/T
inputs to compute reasonable nonpoint estimates. EPA used S/L/T-submitted point emissions as default for
nonpoint reconciliation for solvents, stage 2 gasoline distribution, and publicly owned treatment works
(POTWs); and little to no overlap with the point inventory would be expected for most other nonpoint source
categories in the Wagon Wheel. However, for Industrial and Commercial/Institutional (ICI) nonpoint fuel
combustion, we relied on S/L/T-submitted throughput (fuel consumption) data, ideally from their Point
inventories. As discussed in Section 25, EPA provided four different options for submitting throughput for the ICI
tool. Only three state reporting agencies and two territories did not submit ICI emissions, an input template, or a
nonpoint survey indicating there were no nonpoint ICI emissions.

A complete list of all S/L/T-submitted wagon wheel input activity data is provided in Table 6-3. The input
templates that are needed for point inventory reconciliation are shaded.

Table 6-3: S/L/T Input Temp ates submitted for the 2020 NEI

S/L Agency

Central Database

ICI Fuel Combustion

POTWs

Solvents

Stage 1 Gas

Ag Tilling

Commercial Cooking

Landfills

Grilling

Road Dust

Residential Heating

Residential Wood
Combustion

Mining and
Quarrying

Compost

Asphalt Paving

Cremation

Animal Populations

Construction Dust
and Open Burning

County Business
Patterns

Alabama







































Alaska







































Maricopa Co, AZ



X



X

X





























Arizona



X



X











X



















Arkansas



X



































California







































Colorado







































Connecticut

X

X

X

X

X











X

















Delaware

X

X



X

























X





District of Columbia



X

X

X

X





























Florida



X



































Georgia



X



































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S/L Agency

Central Database

ICI Fuel Combustion

POTWs

Solvents

Stage 1 Gas

Ag Tilling

Commercial Cooking

Landfills

Grilling

Road Dust

Residential Heating

Residential Wood
Combustion

Mining and
Quarrying

Compost

Asphalt Paving

Cremation

Animal Populations

Construction Dust
and Open Burning

County Business
Patterns

Hawaii



X



































Idaho

































X





Illinois



X



































Indiana







































Iowa



X

X

X

X





X











X











Kansas



X

X

X

X

X



X



X



X

X

X

X

X





X

Jefferson Co, KY



X



































Kentucky







































Louisiana







































Maine



X

X

X































Maryland



X

X

X































Massachusetts

X

X

X

X

X











X





X











Michigan



X



X































Minnesota



X



X































Mississippi







































Missouri



X



































Montana







































Nebraska



X



































Clark Co, NV



































X



Nevada







































New Hampshire



X



X































New Jersey





X



X





























New Mexico



X



































New York



X



X































North Carolina



X

X

X

X









X













X

X



North Dakota







































Ohio



X

X

X

X





























Oklahoma



X



X































Oregon



X



X











X



X















Pennsylvania



X



X































Puerto Rico







































Rhode Island

X

X

X

X

X





























South Carolina



X



X







X









X













South Dakota







































Knox Co, TN



X





X

























X



Nashville, TN





X

X

X





















X







Shelby Co, TN



X



































Chattanooga, TN



X



































Tennessee



X



X































Texas







































Utah







X































Vermont



X







X



X



X

X

X



X

X





X



Virgin Islands







































Virginia



X



































Washington

X

X

X





X







X



X











X



6-6


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S/L Agency

Central Database

ICI Fuel Combustion

POTWs

Solvents

Stage 1 Gas

Ag Tilling

Commercial Cooking

Landfills

Grilling

Road Dust

Residential Heating

Residential Wood
Combustion

Mining and
Quarrying

Compost

Asphalt Paving

Cremation

Animal Populations

Construction Dust
and Open Burning

County Business
Patterns

West Virginia

X

X



X







X



X



















Wisconsin



X

X

X

X









X



















Wyoming







































A complete list of the specific S/L-submitted Input Templates for each EPA tool estimate category is provided in
the workbook "2020NEI_WW_SL_lnput_Template_Submittals.xlsx" on the 2020 Supplemental data FTP site.

6.2.2.1 Wagon Wheel updates for the 2020 NEl

For the 2020 NEI, we made several key changes to the Wagon Wheel, including how default and S/L Input
Template data were shared. High-level Wagon Wheel updates include:

•	As shown in Table 6-2, all sources now allow S/Ls to submit controls to be applied at the state and
county level by SCC and by pollutant for ICI fuel combustion, residential non-wood heating, and POTWs.

•	All VOC HAP computations have been removed from the Wagon Wheel; we instead rely on EIS HAP
Augmentation to compute all Wagon Wheel VOC HAPs. This serves two purposes, 1) reduces the size of
the Wagon Wheel output data, and more importantly, 2) ensures that a consistent set of VOC HAPs are
produced between Wagon Wheel data and S/L/T-submitted emissions -particularly when we update
emission factors for either VOC or VOC HAPs; having one centralized location (EIS) for VOC HAP
computations reduces a quality assurance issue of inconsistent HAPs being computed between EPA and
S/L/T emissions.

•	Input Template distribution to and from EPA was streamlined using a "NOMAD" (NOnpoint Method
Advisory) Committee SharePoint site available to S/L inventory developers, contractors, and EPA NEI
team members

•	Input Template structure was reformatted, and Wagon Wheel modified, to allow immediate upload by
S/Ls of their activity data to create Wagon Wheel outputs/draft estimates. This allowed S/Ls to
immediate develop and test the impacts of their local activity data changes to the latest version of the
Wagon Wheel tool.

•	Default point fuel consumption data for nonpoint ICI computation was developed based on the
relationship between S/L-submitted Point inventory carbon monoxide emissions and S/L-submitted
point fuel consumption data from ICI Input Templates. This was done at the sector/fuel-level and
analysis constrained which S/L-submitted input data were used, but the result was -for S/Ls that did not
submit nonpoint ICI emissions or Input Templates- a reduction in unavoidable double-count of nonpoint
ICI with the point ICI inventory for the 2020 NEI.

It is important to stress that the relative changes in emissions between NEI cycles are often more a result of
if/how S/Ls choose to submit activity data, accept EPA estimates, or submit direct emissions. A summary of
Wagon Wheel tool updates for each tool category between the 2017 NEI and the final version (7) used for the
2020 NEI are provided in Table 6-4.

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Table 6-4: Summary of Wagon Wheel tool updates in the 2020 NEI

Tool Category

Summary of Impactful Changes Between 2017 and 2020

Agricultural Silage

N/A; new category for 2020

Agricultural Tilling

No major changes overall; emissions are similar between years

Asphalt Paving

A new methodology was used to calculate asphalt paving emissions for the 2020 NEI.
The methodology included two new SCCs (for hot-mix and warm-mix asphalt), and
many states' emissions increased.

Aviation Gas

Emissions for most states are similar between years. States with larger differences are
due to fugitive valve emissions and fugitive pump emissions. Emissions for both of
these are calculated using a ratio of county to US LTOs. LTOs changed significantly
between 2017 and 2020 and drive changes in emissions. For example, in LA, TX, and
FL, the county to US LTO ratio increased between 2017 and 2020, valve and pump
emissions increased, and overall emissions increased. In CA, DC, and DE, county to US
LTO ratio decreased, so valve and pump emissions and overall emissions decreased.

Commercial
Cooking

Emissions increased for all states because of increases in restaurant counts. The
Hoovers database reported approximately 77% more restaurants nationally between
2017 and 2020. An analysis comparing County Business Patterns reported by the US
Census and the Hoovers database shows that 2017 restaurant counts were
underestimated by Hoovers.

Composting

No major changes overall; emissions are similar between years

Construction Dust

Emissions increases are mostly driven by an increase in nonresidential construction
emissions due to an increase in the value of private nonresidential construction
($347,666 to $471,450). This led to a 35% increase in acres disturbed by
nonresidential construction, which are the activity data behind nonresidential
construction emissions.

Cremation

Human deaths increased 29% nationally between 2017 and 2020 due to the COVID-19
pandemic, causing an increase in emissions across all states. Cremation rates also
increased overall.

Dust from Hooves

No major changes overall; emissions are similar between years

ICI

No major changes in underlying activity data without point source subtraction. When
considering point source data, there are some SCC-dependent changes in emissions.
For example, nonpoint coal consumption decreased, so coal emissions decreased. For
2017, there was no EPA default point source data, but EPA default point source data
is included for 2020. There is also a difference in both the quality and quantity of
point source fuel consumption templates submitted for the 2020 NEI compared to
those submitted for 2017. Default sulfur content for distillate fuel updated to 15ppm
based on ultra-low sulfur distillate.

Landfills

No major changes overall; emissions are similar between years

Mining and
Quarrying

Emissions in many states increased significantly because of increases in mineral,
metal, or coal production. Mineral production has a higher EF, so increases in mineral
production impact emissions increases the most.

Open Burning

Emissions are mostly similar between years, but some states saw larger increases in
emissions due to significant increases in land clearing debris emissions. Acres
distributed from nonresidential construction are used to calculate the amount of land
clearing debris, and this increased (see construction dust note).

Other Mercury

No major changes overall; emissions are similar between years

POTWs

No major changes overall; emissions are similar between years

Residential Grilling

No major changes overall; emissions are similar between years

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Tool Category

Summary of Impactful Changes Between 2017 and 2020

Residential Heating

No major changes overall; emissions are similar between years
Some states had significant changes in residential kerosene and distillate
consumption, according to the EIA SEDS data, that had larger impacts on emissions.
Default sulfur content for distillate fuel updated to 15ppm based on ultra-low sulfur
distillate.

Residential Wood
Combustion

Emissions from RWC were most affected by SEDS data. The 2020 SEDS data uses an
updated methodology: the national wood consumption from the Residential Energy
Consumption Survey (using updated 2015 data; the 2017 SEDS used 2009 RECS data)
is allocated to states using American Community Survey data on housing units and
heating degree days. Because of this, many southern states' emissions decreased,
which is consistent with decreases in wood consumption in SEDS. Many northern
states' emissions increased because of increases in wood consumption in SEDS.
In addition to updates to SEDS data, the 2020 NEI also uses higher PM2.5 emissions
factors from AP-42 for EPA-certified woodstoves (SCCs 2104008220, 2104008230,
2104008320, 2104008330). Wood density values updated based on USDA tree species
data. Removed SEDS adjustment when S/Ls submitted a burn rate or appliance
fraction template.

Road Dust

There are no major trends nationally, but some significant differences for specific
states. Road dust emissions are impacted by both paved VMT and unpaved VMT. For
example, in FL, both paved and unpaved VMT decreased causing emissions to
decrease. In MO, paved VMT decreased, but unpaved VMT increased, causing an
overall increase in emissions. In TX, the length of paved roads decreased, so the
calculated EF decreased causing emissions to decrease.

Updated meteorological adjustment factors overall also led to higher emissions for
some states. Meteorological adjustment factors account for roads being wet when it
rains, containing residual moisture, and leading to lower dust emissions. The
meteorological adjustment factors are updated in each inventory cycle based on
modeling conducted by EPA. The factors calculated for 2020 generally show that
roads contain less residual moisture than the 2017 factors and therefore dust
emissions are higher.

Solvents

The most impactful change to the Solvents tool was the updated emissions factors.
Total solvents emissions decreased for many states. There were both increases and
decreases in the solvent emission factors for 2020 compared to 2017, but some large
sectors, such as graphic arts and certain consumer solvents had large decreases in
their emission factors. The net result was large decreases in total solvents emissions
in many states.

The states whose total solvents VOC emissions decreased the most were KY (25.6%
decrease), Rl (26.2%), IL (27%), OH (37%), and UT (69.9%).

The states whose total solvents VOC emissions increased were MD (1% increase), CA
(1.4%), PR (5%), NY (5.2%), VI (6.1%), WA (6.6%), MT (10.7%), DE (12.4%), SD (22.7%),
NE (23.8%), DC (24.6%), ID (27%), and ND (68.7%).

Stage 1 Gas

Stage 1 Gasoline Distribution emissions decreased for most states. The US product
supplied of finished motor gasoline (also reported by SEDS), decreased between 2017
and 2020, and this data is used for many of the SCCs included in this tool. For some
states, emissions increased significantly, driven by increases in service station
unloading and breathing and emptying emissions. The activity for both SCCs is total
gasoline consumption, which increased in these states between 2017 and 2020 due to
the new distribution method.

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A complete list of activity data used in the 2020 NEI, including the sources of all data and Wagon Wheel release
dates, is provided in the workbook "NEI 2020 Activity Data Tracker_updated27mar2023.xlsx" on the 2020
Supplemental data FTP site.

6.2.3 SLT-submitted emissions

A complete list of S/L/T agencies that submitted 2020 nonpoint emissions for source categories that EPA also
estimates are provided in Table 6-5. It is important to note that this does not provide a single indication on
whether some/all S/L/T data or some EPA data are included in the 2020 nonpoint NEI selection for these
agencies and categories. Factors that could result S/L/T data not being in the NEI, or EPA data appearing in the
NEI for these agencies/categories include:

•	Completeness of S/L/T data: complete geographic and expected pollutant coverage

•	Outlier values resulting in tagging out of S/L/T data

•	Nonpoint Survey responses set to (Yes) allow EPA data to supplement any missing S/L/T data

•	Decision to use only EPA data for a particular source category (e.g., Biogenics)

Table 6-5: S/L/T nonpoint emission submittals for each category t

lat EPA estimates



TSD

State





EPA Estimate Category

Section

Agencies

Local Agencies

Tribal Agencies









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce





CA, GA,



Tribe, Shoshone-Bannock

Fires - Agricultural Field



ID, NJ,



Tribes of the Fort Hall

Burning

7

WA



Reservation of Idaho

Fires - Prescribed Fires

7

GA, WA





Fires - Wildfires

7

GA, WA













Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock







Maricopa County Air Quality

Tribes of the Fort Hall

Biogenics - Vegetation and Soil

8

CA

Department

Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock

Agriculture - Fertilizer





Maricopa County Air Quality

Tribes of the Fort Hall

Application

9

DE

Department

Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock





CA, DE,

Maricopa County Air Quality

Tribes of the Fort Hall

Agriculture - Livestock Waste

10

ID, UT

Department

Reservation of Idaho

Mobile - Commercial Marine









Vessels

11

CA, NH













Coeur d'Alene Tribe, Kootenai





AK, CA,



Tribe of Idaho, Nez Perce





CT, NC,

Maricopa County Air Quality

Tribe, Shoshone-Bannock





TX, VA,

Department, Washoe County

Tribes of the Fort Hall

Mobile - Locomotives

12

WA

Health District

Reservation of Idaho

6-10


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TSD

State





EPA Estimate Category

Section

Agencies

Local Agencies

Tribal Agencies





AK, CA,









CO, NJ,









OH, OK,





Industrial Processes - Oil & Gas



TX, UT,





Production

13

WV, WY



Southern Ute Indian Tribe









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock





CA, DE,

Maricopa County Air Quality

Tribes of the Fort Hall

Portable Fuel Containers

14

ID, NJ

Department

Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock

Non-combustion Mercury:







Tribes of the Fort Hall

Dental Amalgam

15

MN



Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock

Non-combustion Mercury:







Tribes of the Fort Hall

Fluorescent Lamp Recycling

15

MN



Reservation of Idaho

Non-combustion Mercury:









Laboratory Activities

15

MN













Coeur d'Alene Tribe, Nez









Perce Tribe, Shoshone-

Non-combustion Mercury:







Bannock Tribes of the Fort

Switches + Relays

15





Hall Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock

Non-combustion Mercury:







Tribes of the Fort Hall

Thermostats + Thermometers

15





Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce





CA, DE,



Tribe, Shoshone-Bannock





ID, NH,

Maricopa County Air Quality

Tribes of the Fort Hall

Dust: Ag Tilling

16

UT

Department

Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock





CA, DE,

Maricopa County Air Quality

Tribes of the Fort Hall

Dust: Animal Hooves

16

ID

Department

Reservation of Idaho









Coeur d'Alene Tribe, Kootenai









Tribe of Idaho, Nez Perce









Tribe, Shoshone-Bannock









Tribes of the Fort Hall

Agricultural Silage

17

CA



Reservation of Idaho







Knox County Department of

Coeur d'Alene Tribe, Nez





AK, CA,

Air Quality Management,

Perce Tribe, Shoshone-





CT, NJ,

Maricopa County Air Quality

Bannock Tribes of the Fort

Bulk Gasoline Terminals

18

TX, UT

Department

Hall Reservation of Idaho

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EPA Estimate Category

TSD
Section

State
Agencies

Local Agencies

Tribal Agencies

Gas Stations: Aviation Gasoline

18

DE, NJ,
UT

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Gas Stations: Stage 1 Gasoline
Distribution

18

AK, CA,
DE, NH,
NJ, UT,
VA

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho,
Southern Ute Indian Tribe

Storage + Transport: Stage 1
Gasoline Distribution

18

AK, CA,
DE, MA,
NH, NJ,
UT, VA

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Commercial Cooking

19

CA, ID,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Construction Dust: Residential

20

CA, DC,
DE, ID,
NH, NJ,
UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Construction Dust: Heavy

21

CA, DC,
DE, ID,
NJ, UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Dust - Construction Dust

22

AK, CA,
DC, DE,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Dust - Paved Road Dust

23

CA, DE,
ID, NH,
TX

Washoe County Health
District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Dust - Unpaved Road Dust

24

AK, CA,
NH, TX,
UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

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EPA Estimate Category

TSD
Section

State
Agencies

Local Agencies

Tribal Agencies

Fuel Comb -

Comm/lnstitutional - Biomass

25

1D, TX,
UT

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb -

Comm/lnstitutional - Coal

25

CA, ID,
NJ



Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb -

Comm/lnstitutional - Natural
Gas

25

AK, CA,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb -

Comm/lnstitutional - Oil

25

AK, CA,
ID, NJ,
PR, TX,
UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb -

Comm/lnstitutional - Other

25

AK, CA,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb - Industrial Boilers,
ICEs - Biomass

25

1D, TX,
UT

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb - Industrial Boilers,
ICEs - Coal

25

AK, ID,
NJ



Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb - Industrial Boilers,
ICEs - Natural Gas

25

AK, CA,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

6-13


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EPA Estimate Category

TSD
Section

State
Agencies

Local Agencies

Tribal Agencies

Fuel Comb - Industrial Boilers,
ICEs-Oil

25

AK, CA,
ID, NJ,
PR, TX,
UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb - Industrial Boilers,
ICEs - Other

25

AK, CA,
ID, NJ,
PR, TX,
UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho,
Southern Ute Indian Tribe

Fuel Comb - Residential -
Natural Gas

26

CA, ID,
NJ, TX,
UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho,
Southern Ute Indian Tribe

Fuel Comb - Residential - Oil

26

AK, CA,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Fuel Comb - Residential - Other

26

AK, CA,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho,
Southern Ute Indian Tribe

Residential Wood Combustion

27

AK, CA,
ID, MN,
TX, WA

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho,
Southern Ute Indian Tribe

Industrial Processes - Mining

28

AK, CA,
ID, NJ,
Rl, TX,
UT

Clark County Department of
Air Quality and
Environmental Management,
Knox County Department of
Air Quality Management,
Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

6-14


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EPA Estimate Category

TSD
Section

State
Agencies

Local Agencies

Tribal Agencies

Cremation: Human and Animal

29

ID, Rl

Knox County Department of
Air Quality Management,
Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Residential Charcoal Grilling

30

ID, TX

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvents: Asphalt Paving

31

CA, DE,
ID, MA,
NH, NJ,
TX, VA

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Consumer &
Commercial Solvent Use

32

AK, CA,
DE, ID,
MN, NH,
NJ, TX,
UT, VA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Degreasing

32

AK, CA,
DE, ID,
NJ, TX,
VA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Dry Cleaning

32

CA, ID,
NJ, TX

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Graphic Arts

32

CA, ID,
NJ, TX,
VA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Industrial Surface
Coating & Solvent Use

32

AK, CA,
DE, ID,
MA, MN,
NJ, TX,
VA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Solvent - Non-Industrial
Surface Coating

32

CA, DE,
ID, NJ,
TX, VA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

6-15


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EPA Estimate Category

TSD
Section

State
Agencies

Local Agencies

Tribal Agencies

Composting

33

CA, NC,
UT

Maricopa County Air Quality
Department

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Open Burning: Land Clearing
Debris

34

DE, GA,
ID, NJ,
WA

Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Open Burning: Household
Waste

35

AK, CA,
DE, ID,
MN, NC,
NJ, TX,
UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Open Burning: Yard Waste

36

CA, DE,
ID, NJ,
TX, UT

Maricopa County Air Quality
Department, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Northern Cheyenne
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

Publicly-owned Treatment
Works

37

CA, ID,
TX, UT

Knox County Department of
Air Quality Management,
Maricopa County Air Quality
Department, Memphis and
Shelby County Health
Department - Pollution
Control, Washoe County
Health District

Coeur d'Alene Tribe, Kootenai
Tribe of Idaho, Nez Perce
Tribe, Shoshone-Bannock
Tribes of the Fort Hall
Reservation of Idaho

6.2.4 Data selection rules: cross-dataset tagging

We compiled the 2020 nonpoint inventory using much of the same EIS automated data selection rules first
implemented for the 2017 NEI: Nonpoint Survey Rule, Pollutant Grouping Rule, and the Option Group/Option
Set Rule. In addition, the PM speciation rule has since been automated to run as part of the NEI selection, rather
than a separate EIS processing step (and input/output data). When applied, these rules greatly minimized the
need to "tag" out data that would otherwise be needed to prevent double counting of emissions across
pollutant groups, SCCs, and from different data submittal sources.

6.2.4.1 Nonpoint Survey rule

The 2020 nonpoint survey responses were directly applied to the nonpoint selection in the EIS. All S/L/Ts that
completed the nonpoint surveys (green status button on the home screen for the nonpoint survey), had their
responses directly applied in the NEI selection. For each "EPA Tool Estimate Category", nonpoint survey
responses were applied if the "Category Complete?" column was saved and submitted as "Yes". By default, all
nonpoint survey responses were defaulted to "Yes -Supplement my data with EPA estimates. This simply means
that if S/L/T data was not submitted, and EPA data exists (for that process/pollutant), then EPA data will be
selected for the NEI with a caveat to the 2 rules discussed in the next two sections. S/L/Ts were strongly
encouraged to leave the SCCs as default (yes) if they were submitting nonpoint inputs, because S/L/T inputs

6-16


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were absorbed into EPA tools and became "EPA" data; as discussed in Section 6.2.1, we updated the Nonpoint
Survey in 2020 to include a checkbox for each tool category "Did Your Agency Provide an Input Template for this
Category?" to help with quality assurance, particularly for tool categories that are limited to a single SCC.

A detailed 2020 NEI nonpoint summary "2020NEI_Nonpoint_Survey_detail_25mar2023.xlsx" covering all
reporting agencies has been uploaded to the 2020 NEI Supporting Data and Summaries site.

6.2.4.2	Pollutant grouping rule

In previous NEI cycles, we tagged out data to prevent double counting of pollutants across datasets that overlap
one another. Starting with the 2017 NEI and continued for the 2020 NEI, a software solution that occurs during
the blending process was developed so that overlapping pollutants would be excluded from the selection.
Business rules were developed to select data with overlapping pollutants across datasets, to allow different
datasets included in a selection to be blended together in a way that avoids double counting due to overlapping
pollutants. Because there are several HAPs that belong to pollutant groups or represent a pollutant group
themselves, these rules are needed to prevent both a group and individual pollutant in that group from being
used for the same process or facility. The implementation of these rules is automated in the EIS. These rules are
applied at the process level (location and SCC) for nonpoint sources and prevents lower-hierarchy dataset
pollutants/pollutant groups from possible double-counts. For example, if an S/L/T reports "Xylenes (Mixed
Isomers), then any EPA (lower hierarchy) -generated individual (or mixed) isomers will not make it into the NEI.
Rules for the following pollutant groups were applied: xylenes, cresols, polychlorinated biphenyls (PCBs), glycol
ethers, chromium, nickel, and PAHs. A complete discussion of the cross dataset tagging proposed rules, applied
to the 2020 NEI nonpoint inventory selection are available in Appendix 5 of the 2017 NEI Plan. One change to
these "Proposed" rules that we implemented for the 2017 and 2020 NEI is that we allow individual xylene
isomers to be reported with Xylenes (mixed isomers) within the same dataset.

6.2.4.3	Option Group/Option Set rule

We applied the EIS Option Group/Option Set (OGOS) feature for the first time in the 2017 nonpoint NEI and
continued with the same application for the 2020 NEI. In the Source Classification Code table, we can define
SCCs that have a hierarchical nature. That is, there may be a "general" group, as well as more specific SCCs
within the same group. These relationships are defined by the "Option Group / Option Set" (OGOS) fields in the
SCC table. When EPA and SLT datasets are placed in an NEI selection, there is the potential for double counting
of data sources (emissions) across these data sources. For example, the EPA may report emissions to a "general"
SCC while SLTs report data to detailed SCCs. Without OGOS evaluation, both sets of data would be included in
the NEI selection. The current OGOS rules employed in the Selection assumes that if a SLT submits data, they are
summitting data for the entire group and no additional data sets are to be used to "back-fill" any SCCs within the
same option set. The desired function is for the selection to back-fill any SCCs within the same option set. Refer
to "Appendix 6 - Option Group Option Set Enhancement EIS Requirements.pdf" on the 2017 National Emissions
Inventory Documentation website for a comprehensive discussion on the OGOS business rules implemented in
EIS for the 2020 nonpoint NEI. A complete list of OGOS assignments can be obtained by downloading the
complete SCC table (Bulk Download Options) from the SCC search site, and filtering on columns where Option
Group is populated.

6.3 Nonpoint PM augmentation

Section 2.2.4 provides an overview of PM augmentation in the 2020 NEI and explains that we integrated all PM
Augmentation directly into EIS for the 2020 NEI. EIS QA procedures eliminated much of the functionality needs

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from the PM Augmentation Tool that was used in prior NEIs. For the nonpoint data category, the results from
EIS PM Augmentation serve to merely supplement PM components (PM-CON, PM25-FIL, and PM10-PRI) where
expected and where SLTs did not submit. PM Augmentation will zero out any computed PM component less
than zero that could result from arithmetic operation of SLT and PM augmented species; for example, computed
PM-CON computed from SLT-submitted PM10-PRI minus PM10-FIL exceeding SLT-submitted PM25-PRI (which
would result in computed PM25-FIL being less than zero). Analysis of PM augmentation output revealed a
couple suspect SLT-submitted PM component emissions and these were tagged out where necessary. In cases
like this example, it is likely that the SLT erroneously submitted PM25-FIL as PM25-PRI.

6.4	Nonpoint HAP Augmentation

For nonpoint sources, we derived HAP augmentation ratios from the emission factors used to develop the EPA
nonpoint source estimates. Most EPA nonpoint HAP emission estimates are computed in EPA nonpoint database
"tools" (e.g., previously discussed wagon wheel, oil and gas tool). However, for the 2020 NEI, we removed HAP
VOCs from the wagon wheel tool to reduce the resources required to package and process the wagon wheel
data, and ensure that both SLT and EPA data would utilize EIS HAP Augmentation factors for computing VOC
HAPs, streamlining quality assurance if/when emission factors for VOC or VOC HAPs changed.

EPA also generates HAPs with CAPs in stand-alone databases such as that used for agricultural burning and
livestock waste. Because we used the same emission factors for these augmentation ratios, the ratios of HAP to
CAPs for augmented S/L/T agency data are the same as the HAP to CAP ratios for the EPA-only data. For access
by non-EIS users, the zip file called "HAPAugmentation_Nonpoint_28jan2023", on the 2020 NEI Supplemental
data FTP site, provides the emission ratios that the EPA used for augmenting nonpoint data. The nonpoint HAP
augmentation factors were updated as compared to what was used for the 2017 NEI, particularly for the
solvents, asphalt paving, and oil and gas sector. The EPA staff responsible for the nonpoint sectors use their
discretion for how to augment HAP emissions and work with the S/L/T agencies to reflect as complete and
accurate set of pollutants as possible for the many source types. In general, if a S/L/T agency submitted a partial
list of the HAPs that would be augmented for a given category, then we allowed the missing HAPs to be gap-
filled with the HAP augmentation data. These missing HAPs are determined by comparing the Expected
Pollutant List for Nonpoint SCCs with those that S/L/T agencies submitted. However, this approach has a risk of
potentially violating VOC mass balance, whereby the sum of the VOC HAPs exceeds the VOC total. Thus, special
cases occur when such problems are identified. In the limited cases where this occurred, we applied the
business rules defined in Section 3.4.2 in the 2020 NEI Plan to tag out S/L/T data causing this violation; in this
case, S/L/T-submitted HAP-VOCs were replaced with HAP augmentation (generally based on S/L/T-submitted
VOC) -based HAP-VOC estimates.

6.5	EPA nonpoint data

For the 2020 NEI, the EPA developed emission estimates for many nonpoint sectors in collaboration with a
consortium of inventory developers from various state agencies regional planning organizations called the
NOnpoint Method Advisory (NOMAD) Committee. Initiated for the 2014 NEI cycle, the broad NOMAD
committee meets approximately monthly to discuss the overall progress on the various sectors for which tools
and/or estimates are being developed or refined. During the 2020 NEI development process, NOMAD
collaboration meetings focused on overall wagon wheel and associated input template development schedules,
and a deeper dive into specific source categories that were undergoing methodology or significant activity data
changes, such as solvents, agricultural silage, residential wood combustion, agricultural NH3 livestock and

6-18


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fertilizer application, and industrial and commercial/institutional fuel combustion. Separate oil and gas
subcommittee meetings also tracked the development of the oil and gas production and exploration tools.

These meetings covered methodologies, emission factors, and SCCs, allowing the EPA to prepare the "default"
emission estimates/methodologies and/or input template formats for S/L/T agencies using the group's final
approaches. With the 2020 NEl, we continue to prioritize gathering of S/L/T input activity data, rather than
emission submittals, which makes for a more transparent quality assurance process as we have readily available
tracking of the inputs as well as resulting outputs (emissions). With S/L/Ts using the wagon wheel or submitting
inputs, we can ensure that the methodology used to estimate the final emissions for all Wagon Wheel sectors is
consistent.

During the 2020 NEI inventory development cycle, S/L/T agencies, using the nonpoint survey (Section 6.2.1),
could accept the NOMAD/EPA estimates to supplement/fulfill their nonpoint emissions reporting requirements.
The EPA encouraged S/L/T agencies that did not use the EPA's estimates or tools to improve upon these
"default" methodologies and submit input data directly.

Table 6-6 lists all EPA-developed emission estimates, technical support documentation (TSD) section number,
and an indication of whether the Wagon Wheel (WW) or Oil and Gas Production and Exploration (OG) tools
(vl.3) are available on the 2020 NEI Supplemental Nonpoint data FTP site. Table 6-6 also flags EPA estimation
categories where reconciliation with the Point inventory is recommended; that is, nonpoint estimates utilize
activity data encompassing the entire source category (point and nonpoint total), and the tools and/or point
emissions or activity data are needed from user inputs to compute the nonpoint data category component. All
EPA methodologies are discussed in the remaining nonpoint sectors that follow; however, some tables (primarily
emission factors) were too large to include in this TSD, and for WW source categories, we direct the reader to
the "Wagon Wheel Emission Factor Compendium" on the 2020 NEI Supporting Data and Summaries site, for
more information on emission factors. The SCCs associated with the EPA nonpoint data categories are provided
in each of these sections and can also be found on the EPA SCC Search website.

Table 6-6: EPA Nonpoint TSD Sections with indication of possible Point inventory subtraction



EPA

Point



TSD

EPA Estimate Category/Sector

Tool

Recon.?

TSD Section Name

Section

Fires - Agricultural Field Burning



N

Fires-Wild, Prescribed, and Field Burning

7

Fires - Prescribed Fires



N

Fires-Wild, Prescribed, and Field Burning

7

Fires - Wildfires



N

Fires-Wild, Prescribed, and Field Burning

7

Biogenics - Vegetation and Soil



N

Biogenics - Vegetation and Soil

8

Agriculture - Fertilizer Application



N

Agriculture - Fertilizer Application

9

Agriculture - Livestock Waste



N

Agriculture - Livestock Waste

10

Mobile - Commercial Marine Vessels



N

Commercial Marine Vessels

11

Mobile - Locomotives



N

Locomotives

12

Industrial Processes - Oil & Gas









Production

OG

Y

Oil and Gas Exploration and Production

13

Portable Fuel Containers



N

Portable Fuel Containers

14

Non-combustion Mercury: Dental









Amalgam

WW

N

Nonpoint Non-Combustion Mercury

15

Non-combustion Mercury: Fluorescent









Lamp Recycling

WW

N

Nonpoint Non-Combustion Mercury

15

Non-combustion Mercury: Laboratory









Activities

WW

N

Nonpoint Non-Combustion Mercury

15

Non-combustion Mercury: Switches +









Relays

WW

N

Nonpoint Non-Combustion Mercury

15

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EPA Estimate Category/Sector

EPA
Tool

Point
Recon.?

TSD Section Name

TSD
Section

Non-combustion Mercury: Thermostats +
Thermometers

WW

N

Nonpoint Non-Combustion Mercury

15

Dust: Ag Tilling

WW

N

Agriculture - Crops and Livestock Dust

16

Dust: Animal Hooves

WW

N

Agriculture - Crops and Livestock Dust

16

Agricultural Silage

WW

N

Agricultural Silage

17

Bulk Gasoline Terminals

WW

Y

Nonpoint Gasoline Distribution

18

Gas Stations: Aviation Gasoline

WW

Y

Nonpoint Gasoline Distribution

18

Gas Stations: Stage 1 Gasoline
Distribution

WW

Y

Nonpoint Gasoline Distribution

18

Storage + Transport: Stage 1 Gasoline
Distribution

WW

Y

Nonpoint Gasoline Distribution

18

Commercial Cooking

WW

N

Commercial Cooking

19

Construction Dust: Residential

WW

N

Dust - Construction -Residential

20

Construction Dust: Heavy

WW

N

Dust - Construction -Non-Residential

21

Dust - Construction Dust

WW

N

Dust - Construction -Road

22

Dust - Paved Road Dust

WW

N

Dust -Paved Roads

23

Dust - Unpaved Road Dust

WW

N

Dust-Unpaved Roads

24

Fuel Comb - Comm/lnstitutional - Biomass

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Comm/lnstitutional - Coal

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Comm/lnstitutional - Natural
Gas

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Comm/lnstitutional - Oil

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Comm/lnstitutional - Other

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Industrial Boilers, ICEs -
Biomass

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Industrial Boilers, ICEs - Coal

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Industrial Boilers, ICEs -
Natural Gas

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Industrial Boilers, ICEs - Oil

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Industrial Boilers, ICEs - Other

WW

Y

Fuel Combustion -Nonpoint Industrial and
Commercial/Institutional Boilers and ICEs

25

Fuel Comb - Residential - Natural Gas

WW

N

Fuel Combustion - Residential Heating -Natural Gas,
Oil, and Other

26

Fuel Comb - Residential - Oil

WW

N

Fuel Combustion - Residential Heating -Natural Gas,
Oil, and Other

26

Fuel Comb - Residential - Other

WW

N

Fuel Combustion - Residential Heating -Natural Gas,
Oil, and Other

26

Residential Wood Combustion

WW

N

Fuel Combustion - Residential Wood

27

Industrial Processes - Mining

WW

N

Industrial Processes -Mining and Quarrying

28

Cremation: Human and Animal

WW

N

Miscellaneous Non-Industrial NEC: Cremation -
Human and Animal

29

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EPA Estimate Category/Sector

EPA
Tool

Point
Recon.?

TSD Section Name

TSD
Section

Residential Charcoal Grilling

WW

N

Miscellaneous Non-Industrial NEC: Residential
Charcoal Grilling

30

Solvents: Asphalt Paving

WW

N

Solvents - Consumer and Commercial: Asphalt Paving

31

Solvent - Consumer & Commercial Solvent
Use

WW

Y

Solvents: All other Solvents

32

Solvent - Degreasing

WW

Y

Solvents: All other Solvents

32

Solvent - Dry Cleaning

WW

Y

Solvents: All other Solvents

32

Solvent - Graphic Arts

WW

Y

Solvents: All other Solvents

32

Solvent - Industrial Surface Coating &
Solvent Use

WW

Y

Solvents: All other Solvents

32

Solvent - Non-Industrial Surface Coating

WW

Y

Solvents: All other Solvents

32

Composting

WW

N

Waste Disposal: Composting

33

Open Burning: Land Clearing Debris

WW

N

Waste Disposal: Open Burning - Land Clearing Debris

34

Open Burning: Household Waste

WW

N

Waste Disposal: Open Burning - Residential
Household Waste

35

Open Burning: Yard Waste

WW

N

Waste Disposal: Open Burning - Yard Waste

36

Publicly-Owned Treatment Works

WW

Y

Waste Disposal: Nonpoint Publicly-Owned
Treatment Works

37

6.6 Nonpoint Quality Assurance

New for the 2020 NEI was the formation of a dedicated quality assurance (QA) team, which primarily focused on
the nonpoint data category. This team focused on six key aspects of QA for nonpoint data submissions listed in
Table 6-7.

Table 6-7: Key Nonpoint QA issues, causes, and steps taken to address issues

Type of QA Issue

Causes

Steps taken by QA Team to Address

Impossible Sums:

•	HAPVOC > VOC

•	PM PRI * PM-CON + PM-
FIL

•	PM10 < PM2.5

Emission factors are inconsistent with
each other.

Incomplete suite of HAPs is provided,
and when incongruent datasets (EPA
and SLT) are added, they add up to
more than VOC.

HAP aug itself is generating impossible
sums (some oil/gas profiles slightly
violate this QA check).

•	Checked HAP augmentation to ensure
impossible sums were not generated.

•	Ran iterative QA report on SLT
submissions during the window
opening to find these errors. Reported
back to SLTs.

•	Ran a script on the final selection to
check these sums.

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Type of QA Issue

Causes

Steps taken by QA Team to Address

Unexpected Pollutants or
Missing Pollutants

•	Not on expected
pollutants list and EPA will
backfill with tool

•	Not on expected
pollutants list and EPA
can augment HAPs

•	Not on EPA and EPA will
not backfill

•	In EPA but not in SLT

SLT submitted to wrong SCC, or
applied an incorrect emission factor,
or has additional information that EPA
lacks

•	Created an expected pollutants list for
comparison

•	Ran the iterative QA report on SLT
submissions during the window
opening to find these errors and report
back to SLTs.

•	Ran a script on the final selection to
check for unexpected or missing
pollutants.

Missing Data:

•	Missing county

•	Missing SCC

SLT inadvertently left out data

•	Ran an iterative report and provided
feedback to SLTs when counties or
SCCs appeared to be missing

•	Ran a script on the final selection to
check for missing data

Outliers:

•	Too high

•	Too low

SLT gives data that is outside of
acceptable QA limits.

EPA estimates are outside of
acceptable QA limits.

Possibly wrong data units of measure?

• Created rankings on a state SCC
pollutant basis and compared. Also
looked at magnitudes, mainly looking
at large orders of magnitudes of
difference.

Zeroes

Zeroes clog up our Emissions
inventory system, and should
only be included if the
Nonpoint Survey doesn't
cover the SCC

While zeroes are not always a
problem, sometimes their submittal
changes the way our option
group/option set selection process
works, so these should be submitted
with caution. See Section 6.2.4.3.

• Reviewed the option group/option set
to see if zeroes blocked out data from
coming in, inadvertently

Using Old Data

SLT submits data using old WW or
2017 default data.

• Checked the "emissions comment"
field for references to old tools or data.

The following subsections discuss how these QA checks were analyzed and identified issues were resolved prior
to finalizing the final nonpoint selection for the 2020 NEI.

6.6.1 The Iterative QA Report

New for 2020 inventory cycle was the Iterative QA report. The QA team performed this iterative QA while the
S/L/T EIS Production window was open (July 2021 through March 2022). The chief objective of the nonpoint
iterative QA report was to notify S/L/Ts in a timely fashion, to provide feedback concerns as soon as possible to
the S/L/T submitter's recent memory. This automated code was run every Monday morning during the
Production submittal window being open. Using R markdown. we created an iterative feedback report that was
emailed to each S/L/T agency that submitted the prior week via the NEI Help@epa.gov, and this opened up a
dialogue with each S/L/T agency. An example of the first page of an iterative QA report is provided in Figure 6-1.

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Figure 6-1: Example of nonpoint iterative QA report

EIS Nonpoint Submission Summary Report

We realise the window is still open, but in the new paradigm of automated QA here at SPA, we're providing timely feedback on
your submission. You still have until March 2022 to submit! - EPA NEI Nonpoint QA Team
Report generated on: December 02,2021
Nonpoint QA Summary for 

EIS submission date(s): 2021-11-05,2021-10-20.2021-11-22. 2021-11-01,2021-10-22. 2021-11-19, 2021-11-02
Submission included: 24 sectors, 102 SCCs
Submission Summary

The following summary contains information on the most relevant and argent QA findings for the 24- sectors included in your
recent submission^]. We appreciate your tijme in reviewing these findings and helping us build a complete and accurate emissions
inventory.

You will receive a new summary report with any additional submissions throughout the submittal window. Once the submittal
window closes, additional QAwill be done on all submissions to determine completeness based on your Agency's nonpointsurvey
answers,

Please remember to include all pollutants, not just revised pollutants, if submitting corrected xml hies.

Nonpoint Survey Status: 0%

This information reflects the percent completed of Agency's most current nonpoint survey submission located in the EIS Gateway.
Please visit the Gateway to complete the survey.

Critical QA Checks

The following categories, shown in Red Text, indicate ivhat ive found that may prevent your submission from making it
into the NEI as you intended. You should immediately review and correct, as necessary. When a QA check returns no
findings, the check is shown in green text, meaning your data submission looks good.

Missing Criteria Pollutants

Complete Omission: You seem to be missing same important pollutant data. We compared your submission to our expected
pollutants ligj^aud noted 4 criteria air pollutants [CAPs) missing from your submissions, This flag means that no values were
submitted by you for this pollutant process combination for any county. If you submitted a "No" on your N P Survey, EPA cannot
backfill these pollutants and your inventory could be incomplete. If you selected 'Yes" on the NP Survey, and no changes are made
to your submission, EPA will backfill these missing pollutants on your behalf. To view the omitted pollutants, filter on "Complete
Omission CAP" in the	column.

Partial Omission: None

Action Required; EPA has determined that these pollutants are expected from these proEatras^w4 may override your answer.
Please make sure to answer "Yes" on the NP survey, o? submit the emissions yourself. You can review your survey answers in the
provided table by checking the $^^KX£yAP^V£^column, If you have a reason to believe the expected pollutant list is in error,
please contact the NEI Team.

Additional QA Checks
Unexpected Criteria Pollutants

You have submitted pollutants inconsistent with our expectations. EPA may or may not include these pollutants in the NEI. Please
consider providing supporting documentation. These can be identified in the file by filtering on "Unexpected CAP" in the
BgVKWJbi column.

If there is reason these pollutants should be included, submit documentation supporting the reason they should
be included to EPA.

Unexpected Hazardous Pollutants

You have submitted HAPs inconsistent with our expectations, EPA may or may not include these pollutants in the NEI. Please
consider providing supporting documentation. These can be identified in the file by filtering on "Unexpected HAP" in the
col umn.

If there is reason these pollutants should be included, submit documentation supporting the reason they should
he included to EPA.

Missing Hazardous Pollutants

Your list of HAPs is incomplete when compared to our expectations. EPA may tag out incomplete HAP submissions and. when
available, use EPA tool estimates in the NEI. These can be identified an the file by filtering on "Complete Omission HAP" in the

BJWefcffcscolumn.

Update your submission to include all HAPs. or provide documentation on why they should or shoald not be
included in die NEI. Alternatively, you may do nothing and EPA tool estimates will be used in the NEI when available.

Zero Emissions

It is not necessary to submit zero emissions for an entire SCC and EPA asks that you refrain from doing this as it creates extraneous
records in EIS storage, Submitting the nonpoint survey will cover sectors that you do not wish to be backfilled, or that are covered
in the point data category of the NET. Ifvou have any tnsestions or- this, nlease contact the VFI "e--:-..	

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6.6.2	Expected Pollutants List

To determine whether S/L/T submissions were correct, EPA needed to create an accurate expected pollutants
list, or EPL. The NEI Team put together a list of EPA SCCs and EPA non-estimated SCCs that are often submitted
by SLTs, and the corresponding pollutants that EPA expects to be emitted from each process. The purpose of the
list is twofold: first, to guide the SLTs in providing their submissions for the NEI, and second, to cull out any
pollutants that do not belong in the NEI. The expected pollutants list helps everyone to understand what each
SCC is supposed to represent, as far as the suite of pollutants, and ultimately leads to a more consistent and
cohesive NEI.

This nonpoint EPL "NonPointSCCs_ExpectedPollutantsList_2020NEI.xlsx" is available on the 2020 NEI
Supplemental Nonpoint data FTP site. Note that this EPL includes pollutants that EPA does not have the
emission factors or methodology to estimate itself. If the "EPA Tool" field is populated, it means there is an
existing EPA tool for this SCC, and the EPEA tool name is given.

6.6.3	Completeness Reports

We issued Completeness Reports after the EIS S/L/T Production submittal window for the nonpoint data
category was closed in March 2022. A preview was sent to the S/L/Ts ahead of time, with time for them to
correct mistakes and incomplete submissions. In early May 2022 we sent a final report to Air Directors on EPA
letterhead. It included a comparison of submission completeness when compared to other State and Local
agencies in their region. We do not include example of the report as several S/Ls engaged with EPA after the
reports were sent to resolve QA issues prior to finalizing the 2020 nonpoint NEI selection.

6.6.4	EPA-estimated emissions QA

EPA requires all data inventory developers, including contractors, to be responsible for reviewing any emissions
data they provide, as well as keeping track of and reviewing the Input Templates that they upload into the
Wagon Wheel.

Upon providing EPA-generated estimates, each contractor provided a spreadsheet of QA checks they performed
on the data, as well as keeping a tally of and reviewing the Input Templates that they're uploaded into the
Wagon Wheel. We provide a QA Contractor Checklist "QA checklist for contractors.docx", available on the 2020
NEI Supplemental Nonpoint data FTP site that outlines all of the QA a contractor must perform when providing
emissions data to EPA via a tool.

6.6.5	Input Template Review

Input template review is the responsibility of the contractor and was performed on a rolling basis (i.e., as they
were submitted to the NOMAD SharePoint site). While Input Templates weren't incorporated formally until
after the submission window closed, getting back to the S/Ls in a timely fashion ensured that mistakes were
caught early in the process.

6.6.6	Reviewing S/L/T data after the EIS submittal window has closed

After the EIS nonpoint data category submittal window closed, we checked the S/L/T-submitted emissions data
for four main categories.

1. Completeness

a. Tag out unexpected pollutants. We've already given them a heads up during the window
opening with the iterative QA reports.

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b. Tag out incomplete HAPs. We also tagged out process records if CAPS were incomplete; for
example, missing NH3 from agricultural livestock waste.

2.	Old data/methods

a. The Wagon Wheel emissions comment field includes the version of the tool; we tagged out data
for sources where old tools used noted and activity data had known updates in the latest
version of the tool. We also reviewed and tagged out data significantly different from EPA
estimates or previous S/L/T submittals where the comment field indicated "engineering
judgement" and no other supporting documentation was provided.

3.	Check Nonpoint Survey Responses

a.	If a S/L chose "No -do not supplement" but their submittal had missing CAPs. There should not
be missing CAPs, and this would have also been caught as incomplete on Completeness Reports.

b.	Any tagged out S/L emissions data required a "YES" on their Nonpoint Survey; sometimes we
had to tag out a S/L Nonpoint Survey response (from "No") to ensure the NEI would capture EPA
estimates when S/L data were tagged out.

c.	We asked states to update the Nonpoint Survey answer themselves if not time-limited;
otherwise, EPA tagged out their survey responses in these cases.

4.	Percent change from previous NEIs

a.	This does not work for new or changed SCCs, or for some county changes (e.g., changed state-
county Alaska FIPS in 2020, and upcoming changes for Connecticut in 2023)

b.	Evaluated the minimum, maximum, and mean values from the last 3 NEIs (2011, 2014, 2017) -
compared to the 2020 submitted value. We looked more deeply at 2020 values outside the
min/max/20% from mean

c.	Graphed 2017 vs 2020 for the values that got flagged.

Each NEI Nonpoint "sector lead" reviewed QA team findings and reported back for team discussion on follow up
and reconciliation.

6.6.7 Data Tagging Summary
6.6.7.1 S/L/T emissions tagging

We tagged out 2020 SLT nonpoint emissions for various reasons, including but not limited to the following
observations:

•	Submittal of VOC HAPs that in sum, exceed submitted VOC

•	VOC HAPs submitted with no corresponding VOC, or HAP metals submitted with no corresponding PM
(exception for non-combustion mercury sources)

•	Apparent submittal of filterable PM as primary PM component.

•	Apparent unit of measure issue when comparing to EPA values, or ratio of HAP to associated CAP and
EIS HAP Augmentation multiplication factors; for example, benzene being < 0.01% of evaporative VOC

•	Double count with point inventory submittal; for example, identical emissions submitted for point and
nonpoint railyards

•	SLT request with or without EPA solicitation of an identified QA issue

•	Unexpected pollutants such as metals in Commercial cooking, VOC in road dust, mercury in composting,
etc.

•	Apparent submittal of values identical to EPA draft estimates that had later been updated

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•	Solvent HAPs appeared to be based on old HAP Augmentation profiles

•	GHGs submitted for stationary nonpoint sources

•	Contradiction with option group assignments. When an agency submits zero emissions, very small
emissions, or incomplete emissions for an option set "A" source (e.g., 2104008300: Woodstove:
freestanding, general) and more significant emissions for more-specific option set "B" sources (e.g.,
21040083xx: certified catalytic freestanding woodstoves, uncertified fireplace inserts, etc...) the EIS
Option Group/Option Set rule will only select the "A" SCC, leaving (more) significant SLT-submitted
emissions for the option "B" SCCs. In cases like these, we tagged out the lesser/incomplete "A" SCC to
allow SLT "B" emissions to make it into the NEI.

•	SCCs that should be retired but haven't (they will before the 2023 NEI). For example, spillage SCCs for
portable fuel containers that are covered by the MOVES model.

•	SCCs that are sparsely reported and not typically expected for use in modeling. For example, motor
vehicle and structure fires, swimming pools, human perspiration, domestic animal waste.

In most cases not involving mass balance (e.g., VOC HAPs > VOC), unexpected pollutants, or obvious errors, we
collaborated with SLTs on the observed issue and a recommended course of action. In most cases, SLTs agreed
with these recommendations and tags were created. A complete list of all tags applied to the 2020 SLT nonpoint
emissions submittals is available in the workbook "2020NEI_SLT_Nonpoint_emissions_Tags_25mar2023.xlsx" on

the 2020 NEI Supporting Data and Summaries site.

6.6.7.2 S/L Input Template review and Nonpoint Survey tagging

We compared SLT Input Template activity data submittals with EPA default activity and reached out to agencies
where we saw significant outliers. In most cases, SLTs were able to resolve the conflict and provide either
updated activity data or removed their template to accept EPA default data.

In addition to tagging of emissions, we also tagged Nonpoint Survey responses -reverting the Nonpoint Survey to
"Yes -Supplement my data with EPA data"- for select source categories at several S/Ls. The reasons for tagging
these Nonpoint Survey sources are provided in Table 6-8 but they often correspond to identified issues with SLT-
submitted emissions. In cases where SLTs submitted emissions, they often selected "No" in the Nonpoint
Survey, so we sometimes needed to also tag out the Nonpoint Survey to allow EPA estimates to supplement
their now nonexistent (tagged out) emissions.

There were also several scenarios where a S/L agency submitted an Input Template, but then selected "No" in
the Nonpoint Survey (nor submitted emissions). S/L Input template activity data submittals are loaded into the
EPA Wagon Wheel tool, and the estimates generated are therefore considered "EPA". This was the primary
reason for updating the Nonpoint Survey to include a checkbox for SLTs to indicate whether they submitted an
Input Template for the category. Regardless of that check box status, if we discovered an S/L input template and
a Nonpoint Survey response of "No', we reconciled this inconsistency in QA by tagging out the Nonpoint Survey
response to allow the S/L activity data-based estimates to make it into the NEI.

Table 6-8: S/L Nonpoint Survey responses tagged with rationale provided

Agency

EPA Tool Estimate Category

Reason for Tagging

Alaska Department of
Environmental Conservation

ICI Fuel Combustion - C/l LPG

Missing significant CAPs: VOC and NH3

Alaska Department of
Environmental Conservation

Road Dust Tool: unpaved roads

Outlier values

Alaska Department of
Environmental Conservation

Solvent Tool: Industrial Surface
Coating, Degreasing, Non-

Outlier values

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Agency

EPA Tool Estimate Category

Reason for Tagging



Industrial Consumer &





Commercial



California Air Resources Board

Ag Burning Estimates: all SCCs

NH3 missing

California Air Resources Board

Ag Fertilizer Tool

NH3 missing





Using BEIS for entire country, only 2

California Air Resources Board

Biogenics Estimates

agencies submitted direct emissions

California Air Resources Board

Composting Tool

NH3 missing

California Air Resources Board

ICI Fuel Combustion - all SCCs

NH3 missing



Livestock Waste Estimates: all

NH3 missing

California Air Resources Board

SCCs



California Air Resources Board

POTW Tool

NH3 missing



Residential Non-Wood

NH3 missing

California Air Resources Board

Combustion Tool: all SCCs





Residential Wood Combustion

NH3 missing

California Air Resources Board

Tool: all SCCs



Idaho Department of

Commercial Cooking Tool: deep

Outlier VOC value

Environmental Quality

fat frying



Idaho Department of

Livestock Waste Estimates: all

Agreed to use EPA estimates

Environmental Quality

SCCs



Maricopa County Air Quality



Using BEIS for entire country, only 2

Department

Biogenics Estimates

agencies submitted direct emissions

Maricopa County Air Quality

Commercial Cooking Tool:

Outlier PM value

Department

clamshell griddle frying



Memphis and Shelby County



No emissions submitted

Health Department - Pollution





Control

Solvent Tool: Lighter fluid



West Virginia Division of Air

Road Dust Tool: both unpaved

Outlier values

Quality

and paved



6.6.8	Final Review of EPA-generated tool data

1.	Completeness - confirm everything made it into EIS

a.	Review contractor QA checklists

b.	Compare to expected list of EPA Tool SCCs (pulled from Nonpoint Survey and tools into the
Expected Pollutants List)

c.	Compare tool pollutant outputs to Expected Pollutants List (run through iterative QA)

d.	Inform contractor of any missing SCCs or pollutants

2.	Check input template submission compared to Nonpoint Survey "Y/N" checkbox

a.	Review from Contractor QA Checklist

b.	Nonpoint Survey detailed report comparison to list of input templates

6.6.9	Final Nonpoint Selection review

A final review of the nonpoint data category includes:

1. Confirming tagged out data did not make it into the NEI selection

a.	Confirmed "Exclude tagged values" set to "yes" in EIS selection

b.	Run EIS tagging report to confirm all submitted tagged records are included

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Pollutant Completeness

a.	Check against Expected Pollutants List

b.	Find explanation for causes of any missing data

c.	Have rationale for any remaining "unexpected" pollutants
SCC/Sector Completeness

a.	Not every county should have a value for every SCC/Sector, but ensure there is an explanation

b.	Compare to previous (2017) NEI, look for:

i.	Whether S/L/T submitted in past vs current NEI: is it SLT vs SLT, EPA vs SLT for example

ii.	County or SCC changes since last NEI
Non-EPA SCCs in NEI

a.	What SCCs are S/L/Ts reporting that are not in EPA tools/estimates? We tagged some of these
out if they were not reported anywhere else (e.g., human perspiration, motor vehicle fires) to
avoid some inconsistencies across states.

b.	Is there any potential overlap with SCCs not included in the Option Group/Option Set
assignments (possible double-counting issue)?

c.	Does OGOS unintentionally drop S/L/T emissions? This happened in draft versions of the
selection as noted in "Contradiction with option group assignments" in Section 6.6.7.1.

Accuracy

a.	Final magnitude check comparing relative rankings at sector and state level to previous NEI. Did
the relative ranking change significantly for a given state/sector?

b.	Review where there are zero emissions for entire agency/SCC
HAPs

a.	Compare to expected pollutants list

b.	Ensure backfilled via augmentation

c.	Check HAP-VOC vs VOC and correct/tag if necessary.

Ensure all data exclusion rules properly reflected

a.	Nonpoint Survey: SLT data supersedes EPA data where appropriate

b.	Pollutant Groupings: each county/SCC should only have one group level between different
datasets

c.	OGOS: review selection SCCs to confirm correct application
PM speciation mass balance: sum of PM species equals PM2.5

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United States	Office of Air Quality Planning and Standards	Publication No. EPA-454/R-23-001f

Environmental Protection	Air Quality Assessment Division	March 2023

Agency	Research Triangle Park, NC


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