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2019 National Emissions Inventory Technical
Support Document: Point Data Category
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EP A-454/R-22-001
February 2022
2019 National Emissions Inventory Technical Support Document: Point Data Category
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Emissions Inventory and Analysis Group
Research Triangle Park, NC
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Contents
List of Tables ii
Acronyms and Chemical Notations iii
1 Introduction 1-1
1.1 What data are included in the 2019 NEI Point Data Category release? 1-1
1.2 What is included in this documentation? 1-2
1.3 Where can I obtain the 2019 NEI data? 1-2
1.3.1 Emission Inventory System Gateway 1-2
1.3.2 NEI main webpage 1-3
1.3.3 Modeling files 1-3
1.4 Why is the NEI created? 1-3
1.5 How is the NEI created? 1-4
1.6 Who are the target audiences for the NEI? 1-5
1.7 What are appropriate uses of the NEI and what are the caveats about the data? 1-6
2 2019 NEI contents overview 2-1
2.1 What are EIS sectors? 2-1
2.2 How is the NEI constructed? 2-3
2.2.1 Toxics Release Inventory data 2-4
2.2.2 Chromium speciation 2-4
2.2.3 HAP augmentation 2-6
2.2.4 PM augmentation 2-7
2.2.5 Other EPA datasets 2-7
2.2.6 Data Tagging 2-7
2.2.7 Inventory Selection 2-8
2.3 How did the 2017 NEI compare to past inventories? 2-8
2.3.1 Differences in approaches 2-9
2.4 How well are tribal data and regions represented in the 2019 NEI? 2-9
2.5 References for 2017 inventory contents overview 2-10
3 Point sources 3-11
3.1 Point source approach: 2019 3-11
3.1.1 QA review of S/L/T data 3-11
3.1.2 Sources of EPA data and selection hierarchy 3-12
3.1.3 Particulate matter augmentation 3-14
3.1.4 Chromium speciation 3-15
3.1.5 Use of the 2019 Toxics Release Inventory 3-15
3.1.6 HAP augmentation based on emission factor ratios 3-20
3.1.7 Cross-dataset tagging rules for overlapping pollutants 3-21
3.2 Airports: aircraft-related emissions 3-21
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3.3 Rail yard-related emissions 3-21
3.4 EGUs 3-21
3.5 Landfills 3-23
3.6 PM species 3-23
3.7 References for point sources 3-23
List of Tables
Table 1-1: Point source reporting thresholds (potential to emit) for CAPs in the AERR 1-5
Table 1-2: Examples of major current uses of the NEI 1-6
Table 2-1: EIS sectors/source categories with EIS data category emissions reflected 2-1
Table 2-2: Valid chromium pollutant codes 2-4
Table 2-6: Tribal participation in the 2019 NEI 2-9
Table 2-7: Facilities on Tribal lands with 2017 NEI emissions from EPA only 2-10
Table 3-1: Data sets and selection hierarchy used for 2019 NEI September 2021 release point source data
category 3-13
Table 3-2: Mapping of TRI pollutant codes to EIS pollutant codes 3-16
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Acronyms and Chemical Notations
AERR Air Emissions Reporting Rule
APU Auxiliary power unit
BEIS Biogenics Emissions Inventory System
CI Category 1 (commercial marine vessels)
C2 Category 2 (commercial marine vessels)
C3 Category 3 (commercial marine vessels)
CAMD Clean Air Markets Division (of EPA Office of Air and Radiation)
CAP Criteria Air Pollutant
CBM Coal bed methane
CDL Cropland Data Layer
CEC North American Commission for Environmental Cooperation
CEM Continuous Emissions Monitoring
CENRAP Central Regional Air Planning Association
CERR Consolidated Emissions Reporting Rule
CFR Code of Federal Regulations
CH4 Methane
CMU Carnegie Mellon University
CMV Commercial marine vessels
CNG Compressed natural gas
CO Carbon monoxide
C02 Carbon dioxide
CSV Comma Separated Variable
dNBR Differenced normalized burned ratio
E10 10% ethanol gasoline
EDMS Emissions and Dispersion Modeling System
EF emission factor
EGU Electric Generating Utility
EIS Emission Inventory System
EAF Electric arc furnace
EF Emission factor
El Emissions Inventory
EIA Energy Information Administration
EMFAC Emission FACtor (model) - for California
EPA Environmental Protection Agency
ERG Eastern Research Group
ERTAC Eastern Regional Technical Advisory Committee
FAA Federal Aviation Administration
FACTS Forest Service Activity Tracking System
FCCS Fuel Characteristic Classification System
FETS Fire Emissions Tracking System
FWS United States Fish and Wildlife Service
FRS Facility Registry System
GHG Greenhouse gas
GIS Geographic information systems
GPA Geographic phase-in area
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GSE Ground support equipment
HAP Hazardous Air Pollutant
HCI Hydrogen chloride (hydrochloric acid)
Hg Mercury
HMS Hazard Mapping System
ICR Information collection request
l/M Inspection and maintenance
IPM Integrated Planning Model
KMZ Keyhole Markup Language, zipped (used for displaying data in Google Earth
LRTAP Long-range Transboundary Air Pollution
LTO Landing and takeoff
LPG Liquified Petroleum Gas
MARAMA Mid-Atlantic Regional Air Management Association
MATS Mercury and Air Toxics Standards
MCIP Meteorology-Chemistry Interface Processor
MMT Manure management train
MOBILE6 Mobile Source Emission Factor Model, version 6
MODIS Moderate Resolution Imaging Spectroradiometer
MOVES Motor Vehicle Emissions Simulator
MW Megawatts
MWC Municipal waste combustors
NAA Nonattainment area
NAAQS National Ambient Air Quality Standards
NAICS North American Industry Classification System
NARAP North American Regional Action Plan
NASF National Association of State Foresters
NASS USDA National Agriculture Statistical Service
NATA National Air Toxics Assessment
NCD National County Database
NEEDS National Electric Energy Data System (database)
NEI National Emissions Inventory
NESCAUM Northeast States for Coordinated Air Use Management
NFEI National Fire Emissions Inventory
NG Natural gas
NH3 Ammonia
NMIM National Mobile Inventory Model
NO Nitrous oxide
N02 Nitrogen dioxide
NOAA National Oceanic and Atmospheric Administration
NOx Nitrogen oxides
03 Ozone
OAQPS Office of Air Quality Standards and Planning (of EPA)
OEI Office of Environmental Information (of EPA)
ORIS Office of Regulatory Information Systems
OTAQ Office of Transportation and Air Quality (of EPA)
PADD Petroleum Administration for Defense Districts
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PAH Polycyclic aromatic hydrocarbons
Pb Lead
PCB Polychlorinated biphenyl
PM Particulate matter
PM25-CON Condensable PM2.5
PM25-FIL Filterable PM2.5
PM25-PRI Primary PM2.55 (condensable plus filterable)
PM2.5 Particulate matter 2.5 microns or less in diameter
PM10 Particular matter 10 microns or less in diameter
PM10-FIL Filterable PM10
PM10-PRI Primary PM10
POM Polycyclic organic matter
POTW Publicly Owned Treatment Works
PSC Program system code (in EIS)
RFG Reformulated gasoline
RPD Rate per distance
RPP Rate per profile
RPV Rate per vehicle
RVP Reid Vapor Pressure
Rx Prescribed (fire)
SCC Source classification code
SEDS State Energy Data System
SFvl SMARTFIRE version 1
SFv2 SMARTFIRE version 2
S/L/T State, local, and tribal (agencies)
SMARTFIRE Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation
SMOKE Sparse Matrix Operator Kernel Emissions
S02 Sulfur dioxide
S04 Sulfate
TAF Terminal Area Forecasts
TEISS Tribal Emissions Inventory Software Solution
TRI Toxics Release Inventory
UNEP United Nations Environment Programme
USDA United States Department of Agriculture
VMT Vehicle miles traveled
VOC Volatile organic compounds
USFS United States Forest Service
WebFIRE Factor Information Retrieval System
WFU Wildland fire use
WLF Wildland fire
WRAP Western Regional Air Partnership
WRF Weather Resea rch and Forecasting Model
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1 Introduction
The Environmental Protection Agency (EPA) has released the 2019 National Emissions Inventory (NEI) for the
Point data category. This is not a comprehensive public release of the triennial NEI; the most-recent being the
2017 NEI, is available on the web at the 2017 NEI Data page. As such, this document will discuss only the point
emissions inventory for the 2019 NEI, which represents point source emissions for the year 2019. For the
remainder of this document "2019 NEI" is used to represent the 2019 Point data category of the NEI. Multiple
versions of the 2019 NEI point inventory were prepared. The 2019 NEI point data were first developed into an
inventory during the summer of 2021. This preliminary version was used to facilitate a review of toxics
emissions by state, local, and tribal (S/L/T) data submitters that occurred during August and September of 2021.
In September 2021 some updates were made particularly to installed control devices and this version was used
for analyses related to ozone precursors. In December 2021, updates from the S/L/T toxics review were
incorporated into the inventory and the resulting version was used for air quality modeling that included both
criteria and toxic emissions. This document focuses on the September 2021 and December 2021 versions.
Where methodological approaches between the September and December versions differ, those are described.
1.1 What data are included in the 2019 NEI Point Data Category release?
The NEI is a national compilation of air emission estimates of criteria air pollutants (CAPs), the precursors of
CAPs, and hazardous air pollutants (HAPs). The hazardous air pollutants that are included in the NEI are based
on Section 112(b) of the Clean Air Act. State, local and tribal air agencies submit emission estimates to EPA and
the Agency adds information from EPA emissions programs, such as the emission trading program, Toxics
Release Inventory (TRI), and data collected during rule development or compliance testing.
The triennial NEI also includes estimates of emissions from stationary sources (large and small industries,
commercial, institutional and consumer), mobile sources, fires and biogenic emissions. The 2019 NEI only
includes the point data category emissions, primarily stationary sources (large and small industries, commercial,
institutional), as well as emissions from aircraft (not including in-flight lead emissions) and many rail yards. EPA
uses the NEI in rule development, non-attainment area designations, and as an input to various reports and
assessments. This document discusses the Point inventory component of the NEI. The NEI program develops
datasets, blends data from these multiple sources, and performs data processing steps that further enhance,
quality assure, and augment the compiled data.
The emissions data in the NEI are compiled at different levels of granularity, depending on the data category. For
point sources (source at a known latitude and longitude), emissions are inventoried at a process-level within a
facility. The point data are collected from S/L/T air agencies and the EPA emissions programs including the TRI,
the Acid Rain Program, and Maximum Achievable Control Technology (MACT) standards development.
While not provided for the 2019 NEI, nonpoint sources (typically smaller, yet pervasive sources) and mobile
sources (both onroad and nonroad), emissions are given as county totals. For wildfires and prescribed burning,
the data are compiled as day-specific, coordinate-specific (similar to point) events in the "event" portion of the
inventory, and these emission estimates are further stratified into smoldering and flaming components.
The pollutants included in the NEI are the pollutants associated with the National Ambient Air Quality Standards
(NAAQS), known as CAPs, as well as HAPs associated with EPA's Air Toxics Program. The CAPs have ambient
concentration limits or are precursors for pollutants with such limits from the NAAQS program. These pollutants
include lead (Pb), carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), sulfur
dioxide (SQ2), particulate matter 10 microns or less (PM10), particulate matter 2.5 microns or less (PM2.5), and
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ammonia (NH3), which is technically not a CAP, but an important PM precursor. The HAP pollutants include the
187 remaining HAP pollutants (methyl ethyl ketone was removed) from the original 188 listed in Section 112(b)
of the 1990 Clean Air Act Amendments1 as well as a newly listed HAP 1-Bromopropane. There are many
different types of HAPs. For example, some are acid gases such as hydrochloric acid (HCI); others are heavy
metals such as mercury (Hg), nickel and cadmium; and others are organic compounds such as benzene,
formaldehyde, and acetaldehyde. Greenhouse gases (GHGs) are included in the NEI for point sources where they
have been reported.
1.2 What is included in this documentation?
This technical support document (TSD) provides a reference for the 2019 NEI. The primary purpose of this
document is to explain the sources of information included in the inventory. This includes showing the sources
of data and types of sources that are used for each data category, and then providing more information about
the EPA-created components of the data. After the introductory material included in this section, Section 2
provides an overview of the contents of the inventory. Section 3 provides an overview of how the point source
inventory was developed.
Estimates of emissions in the year 2019 for sources other than point sources were developed by EPA as part of
the 2019 emissions modeling platform but are not considered part of the NEI. For emissions data other than
point sources, the modeling platform emissions development methodologies for 2019 do not rely on data
submitted by state, local, and tribal agencies for the specific year like the NEI. Instead, estimates for some data
categories are based on adjustments to the most recent triennial NEI data, while others are based on data sets
with national coverage similar to those used to develop the triennial NEIs. Once completed, these data and the
documentation for the development of data for the 2019 modeling platform will be available from the 2019
Emissions Modeling Platform website.
1.3 Where can I obtain the 2019 NEI data?
NEI data are available in several different ways listed below. Data are available to the reporting agencies and
EPA staff via the Emission Inventory System (EIS).
1.3.1 Emission Inventory System Gateway
The EIS Gateway is available to all EPA staff, EIS data submitters (i.e., the S/L/T air agency staff), Regional
Planning Organization staff that support state, local and tribal agencies, and contractors working for the EPA on
emissions related work. The EIS reports functions can be used to obtain raw input datasets and create summary
files from these datasets as well as older versions of the NEI such as 2017, 2014, 2011, and 2008. The September
version of the 2019 NEI dataset in EIS is called "2019NEI_V1", while the December version of 2019 NEI dataset in
the EIS is called "2019NEI_V2". Note that if you run facility-, unit- or process-level reports in the EIS, you will get
the 2019 NEI emissions data, but the facility inventory is dynamic in the EIS and will reflect more current
information. The file that EIS creates for preparation of emissions for air quality modeling is called a "flat file",
which is a comma-separated tabular file of emissions that for point sources also includes locations and stack
parameters. The information in the flat file is based on the facility inventory information available at the time
the flat file is generated. Thus, facility information in the flat file from September will not be the same as facility
information in the flat file from December if facility inventory changes have occurred in the intervening time.
See Section 1.3.3 for more information on the modeling flat files.
1 The original of HAPs is available on the EPA Technology Transfer Network - Air Toxics Web Site.
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1.3.2 NEI main webpage
The 2019 NEI point inventory is not released on the NEI main web page but is released with the 2019 emissions
modeling platform. The 2017 NEI Data web page includes the most recent publicly-available version of the
triennial 2017 NEI along with the 2017 NEI plan and schedules and all publicly-available supporting materials by
inventory data category (e.g., point, nonpoint, nonroad mobile, onroad mobile, events) and an associated TSD.
Two types of point data summaries are available on the 2017 NEI Data page, facility summaries and process-
level summaries. The source classification codes (SCC) data files section of the webpage provides the process
level summaries for all data categories. These detailed CSV files (provided in zip files) contain emissions at the
process level. Due to their size, they are broken out into EPA regions. Facility-level by pollutant summaries are
also available. These CSV files must be "linked" (as opposed to imported) to open them with Microsoft® Access®.
County and tribe-level summaries for events are also provided.
The 2017 NEI Data page also includes a query tool that allows for summaries by EIS Sector (see Section 2.1) or
the more traditional Tier 1 summary level (for CAPs only) used in the EPATrends Report. Summaries from the
2017 NEI Data site include national-, state-, and county-level emissions for CAPs, HAPs and GHGs. You can
choose which states, EIS Sectors, Tiers, and pollutants to include in custom-generated reports to download
Comma Separated Value (CSV) files to import into Microsoft® Excel®, Access®, or other spreadsheet or database
tools. Biogenic emissions and tribal data (but not tribal onroad emissions) are also available from this tool. Tribal
summaries are also posted under the "Additional Summary Data" section of this page.
Documentation for the 2017 NEI is available from the 2017 NEI data page which includes links to the 2017 NEI
TSD and supporting materials. This page is a working page, meaning that content is updated as new products are
developed. Emissions data used in the 2019 emissions modeling platform rely on many of the methods used to
develop the 2017 NEI as described in the 2017 NEI TSD.
1.3.3 Modeling files
The modeling files, provided on the Air Emissions Modeling website, are provided in formats that can be read by
the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. These files are also CSV formats that
can be read by other systems, such as databases. The modeling files provide the process-level emissions
apportioned to release points (with one pollutant per line), and the release parameters for the release points.
Release parameters include stack height, stack exit diameter, exit temperature, exit velocity and flow rate. The
EPA may make changes to the NEI modeling files prior to their use. The 2019 modeling platform is based on the
2019 NEI point inventory along with emissions that represent 2019 for many other sources and for some sources
2017 NEI data are used directly. The development of the 2019 emissions modeling platform is discussed in the
TSD for the 2019 Emissions Modeling Platform, which will be posted on the 2019 Emissions Modeling Platform
web page once available.
The SMOKE flat files for the September and December versions of the point inventory are available on the air
emissions modeling FTP site for 2019.
1.4 Why is the NEI created?
The NEI is created to provide the EPA, federal, state, local and tribal decision makers, and the national and
international public the best and most complete estimates of CAP and HAP emissions. While the EPA is not
directly obligated to create the NEI, the Clean Air Act authorizes the EPA Administrator to implement data
collection efforts needed to properly administer the NAAQS program. Therefore, the Office of Air Quality
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Planning and Standards (OAQPS) maintains the NEI program in support of the NAAQS. Furthermore, the Clean
Air Act requires States to submit emissions to the EPA as part of their State Implementation Plans (SIPs) that
describe how they will attain the NAAQS. The NEI is used as a starting point for many SIP inventory development
efforts and for states to obtain emissions from other states needed for their modeled attainment
demonstrations. The NEI is the basis for many types of air quality modeling studies.
While the NAAQS program is the basis on which the EPA collects CAP emissions from the S/L/T air agencies, it
does not require collection of HAP emissions. For this reason, the HAP reporting requirements are voluntary.
Nevertheless, the HAP emissions are an essential part of the NEI program. These emissions estimates allow EPA
to assess progress in meeting HAP reduction goals described in the Clean Air Act amendments of 1990. These
reductions seek to reduce the negative impacts to people of HAP emissions in the environment, and the NEI
allows the EPA to assess how much emissions have been reduced since 1990.
1.5 How is the NEI created?
The Air Emissions Reporting Rule (AERR) is the regulation that requires state and local agencies to submit CAP
emissions, and the Emissions Inventory System is the data system used to collect, QA, and compile those
submittals as well as EPA augmentation data. Most S/L/T air agencies also provide voluntary submissions of HAP
emissions. The 2008 NEI was the first inventory compiled using the AERR, rather than its predecessor, the
Consolidated Emissions Reporting Rule (CERR). The 2017 NEI was the fourth AERR-based inventory, and
improvements in the 2017 NEI process reflect lessons learned by the S/L/T air agencies and EPA from the prior
NEI efforts. The AERR requires agencies to report all sources of emissions, except fires and biogenic sources.
Reporting of open fire sources, such as wildfires, is encouraged, but not required. Sources are divided into large
groups called "data categories": stationary sources are "point" or "nonpoint" (county totals) and mobile sources
are either onroad (cars and trucks driven on roads) or nonroad (locomotives, aircraft, marine, off-road vehicles
and nonroad equipment such as lawn and garden equipment).
The AERR has emissions thresholds above which States must report stationary emissions as "point" sources,
with the remainder of the stationary emissions reported as "nonpoint" sources.
The AERR changed the way these reporting thresholds work, as compared to the CERR, by changing these
thresholds to "potential to emit" thresholds rather than actual emissions thresholds. In both the CERR and the
AERR, the emissions that are reported are actual emissions, despite that the criteria for which sources to report
is now based on potential emissions. The AERR requires emissions reporting for "Type A" point sources every
year, with additional requirements every third year in the form of lower point source emissions thresholds. 2017
is one of these third-year (aka "triennial") inventories, while the reporting thresholds for 2019 are higher in this
interim year.
Table 1-1 provides the potential-to-emit reporting thresholds that applied for the 2017 and 2019 NEI cycles.
"Type B" is the terminology in the rule that represents the lower emissions thresholds required for point sources
in the triennial years. The reporting thresholds are sources with potential to emit of 100 tons/year or more for
most criteria pollutants, with the exceptions of CO (1000 tons/year), and, updated starting with the 2014
inventory, Pb (0.5 tons/year, actual). As shown in the table, special requirements apply to nonattainment area
(NAA) sources, where even lower thresholds apply. The relevant ozone (03), CO, and PM10 nonattainment
areas that applied during the year that the S/L/T agencies submitted their data for the 2017 NEI are available on
the Nonattainment Areas for Criteria Pollutants (Green Book) web site.
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Table 1-1: Point source reporting thresholds (potential to emit) for CAPs in the AERR
Pollutant
Type A sources
(every year)
Type B Sources
(triennial)
Triennial Thresholds1 within
Nonattainment Areas
(1) so2
>2500
>100
>100
(2) VOC
>250
>100
03(moderate) > 100
03 (serious) > 50
03 (severe) > 25
03 (extreme) > 10
(3) NOx
>2500
>100
>100
(4) CO
>2500
>1000
03 (all areas) > 100
CO (all areas) > 100
(5)Lead
>0.5 (actual)
>0.5 (actual)
(6) Primary PMio
>250
>100
PMio(moderate) >100
PMio(serious) >70
(7) Primary PM2.s
>250
>100
>100
(8) NH3
>250
>100
>100
thresholds for point source determination shown in tons per year of potential to emit as
defined in 40 CFR part 70, with the exception of lead.
Based on the AERR requirements, S/L/T air agencies submit emissions or model inputs of point, nonpoint,
onroad mobile, nonroad mobile, and fire emissions sources. With the exception of California, reporting agencies
were required to submit model inputs for onroad and nonroad mobile sources instead of emissions. For the
2017 NEI, all these emissions and inputs were required to be submitted to the EPA per the AERR by December
31, 2018 (with an extension given through January 15, 2019). For the 2019 NEI submissions for point sources
were required by December 31, 2020 (with an extension given through January 15, 2021). Once the initial
reporting NEI period closed, the EPA provided feedback on data quality such as suspected outliers and missing
data by comparing to previously established emissions ranges and past inventories. In addition, the EPA
augmented the S/L/T data using various sources of data and augmentation procedures. This documentation
provides a detailed account of EPA's quality assurance and augmentation methods.
1,6 Who are the target audiences for the NEI?
The comprehensive nature of the NEI allows for many uses and, therefore, its target audiences include EPA staff
and policy makers, the U.S. public, other federal and S/L/T decision makers, and other countries. Table 1-2
below lists the major current and planned uses of the NEI. These uses include those by the EPA in support of the
NAAQS, Air Toxics, and other programs as well as uses by other federal and regional agencies and for
international needs. In addition to this list, the NEI is used to respond to Congressional inquiries, provide data
that supports university research, and helps environmental groups and other interested parties to understand
sources of air pollution.
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Table 1-2: Examples of major current uses of the NEI
Audience
Purposes
U.S. Public
Learn about sources of air emissions
EPA - NAAQS
Regulatory Impact Analyses - benefits estimates using air quality modeling
NAAQS Implementations, including State Implementation Plans (SIPs)
Monitoring Rules
Final NAAQS designations
NAAQS Policy Assessments
Integrated Science Assessments
Transport Rule air quality modeling (e.g., Cross-State Air Pollution Rule)
EPA-Air toxics
Air toxics analyses
Mercury and Air Toxics Standard - mercury risk assessment and Regulatory Impact Assessment
National Monitoring Programs Annual Report
Toxicity Weighted emission trends for the Government Performance and Reporting Act (GPRA)
Residual Risk and Technology Review - starting point for inventory development
EPA-other
NEI Reports - analysis of emissions inventory data
Report on the Environment
Air Emissions website for providing graphical access to CAP emissions for state maps and Google
Earth views of facility total emissions
Support of regulatory development for mobile sources
Long term time series modeling analyses for deposition and other purposes (e.g., EQUATES)
Department of Transportation, national transportation sector summaries of CAPs
Black Carbon Report to Congress
Other federal or
regional agencies
Modeling in support of Regional Haze SIPs, the Centers for Disease Control and Prevention (CDC)
national environment public health tracking indicators, and other air quality issues
International
United Nations Environment Programme (UNEP) - global and North American Assessments
The Organization for Economic Co-operation and Development (OECD) - environmental data and
indicators report
UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP) - emission reporting
requirements, air quality modeling, and science assessments
Community Emissions Data System (CEDS) - science network for earth system, climate, and
atmospheric modeling
Commission for Environmental Cooperation (CEC) - North American emissions inventory
improvement and reduction policies
U.S. and Canada Air Quality Reports
Arctic Contaminants Action Program (ACAP) - national environmental and emission reduction
strategy for the Arctic Region
Other outside
parties
Researchers and graduate students
1.7 What are appropriate uses of the NEI and what are the caveats about the data?
As shown in the preceding section, the NEI provides a readily-available comprehensive inventory of both CAP
and HAP emissions to meet a variety of user needs. Although the accuracy of individual emissions estimates will
vary from facility-to-facility or county-to-county, the NEI largely meets the needs of these users in the aggregate
Some NEI users may wish to evaluate and revise the emission estimates for specific pollutants from specific
source types for either the entire U.S. or for smaller geographical areas to meet their needs. Regulatory uses of
the NEI by the EPA, such as for interstate transport, always include a public review and comment period.
One of the primary goals of the NEI is to provide the best assessment of current emissions levels using the data,
tools and methods currently available. For significant emissions sectors of key pollutants, the available data,
tools and methods typically evolve over time in response to identified deficiencies and the need to understand
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the costs and benefits of proposed emissions reductions. As these method improvements have been made,
there have not been consistent efforts to revise previous NEI year estimates to use the same methods as the
current year. Therefore, care must be taken when reviewing different NEI year publications as a time series with
the goal of determining the trend or difference in emissions from year to year. An example of such a method
change in the 2008 NEI v3 and 2011 NEI is the use of the Motor Vehicle Emissions Simulator (MOVES) model for
the onroad data category. Previous NEI years had used the Mobile Source Emission Factor Model, version 6
(MOBILE6) and earlier versions of the MOBILE model for this data category. The 2011 NEI (2011v2) also used an
older version of MOVES (2014) than the 2017 NEI (MOVES2014b). MOVES also calculates nonroad equipment
emissions, including VOCs and toxics. Emissions based on the latest version of MOVES lead to slightly more
nonroad NOx emissions in some locations as compared to previous inventories.
Other significant emissions sectors were improved in the 2017 NEI and therefore trends are also impacted by
inconsistent methods. Examples include paved and unpaved road PM emissions, ammonia fertilizer and animal
waste emissions, oil and gas production, residential wood combustion, solvents, industrial and
commercial/institutional fuel combustion and commercial marine vessel emissions.
Users should take caution in using the emissions data for filterable and condensable components of particulate
matter (PM10-FIL, PM2.5-FIL and PM-CON), which is not complete and should not be used at any aggregated
level. These data are provided for users who wish to better understand the components of the primary PM
species, where they are available, in the disaggregated, process-specific emissions reports. Where not reported
by S/L/T agencies, the EPA augments these components (see Section 2.2.4). However, not all sources are
covered by this routine, and in mobile source and fire models, only the primary particulate species are
estimated. Thus, users interested in PM emissions should use the primary species of particulate matter (PM10-
PRI and PM25-PRI), described in this document simply as PM10 and PM2.5.
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2 2019 NEI contents overview
2.1 What are EIS sectors?
First used for the 2008 NEI, EIS Sectors continue to be used for the 2019 NEI data. The sectors were developed
to better group emissions for both CAP and HAP summary purposes. The sectors are based simply on grouping
the emissions by the emissions process as indicated by the SCC to an EIS sector. In building this list, we gave
consideration not only to the types of emissions sources our data users most frequently ask for, but also to the
need to have a relatively concise list in which all sectors have a significant amount of emissions of at least one
pollutant. The SCC-EIS Sector cross-walk used for the summaries provided in this document is available for
download from the Source Classification Codes (SCCs) website. No changes were made to the SCC-mapping or
sectors used for the 2019 NEI except where SCCs were retired, or new SCCs were added.
Some of the sectors include the nomenclature "NEC," which stands for "not elsewhere classified." This simply
means that those emissions processes were not appropriate to include in another EIS sector and their emissions
were too small individually to include as its own EIS sector.
Since the 2008 NEI, the inventory has been reported and compiled in EIS using five major data categories: point,
nonpoint, onroad, nonroad and events. The event category is used to compile day-specific data from prescribed
burning and wildfires. While events could be other intermittent releases such as chemical spills and structure
fires, prescribed burning and wildfires have been a focus of the NEI creation effort and are the only emission
sources contained in the event data category.
Table 2-1 shows the EIS sectors or source category component of the EIS sector in the left most column. EIS data
categories -Point, Nonpoint, Onroad, Nonroad, and Events-that have emissions in these sectors/source
categories are also reflected. While this document only discusses the 2019 Point NEI, the other data categories
are provided as a reference.
As Table 2-1 illustrates, many EIS sectors include emissions from more than one EIS data category because the
EIS sectors are compiled based on the type of emissions sources rather than the data category. Note that the
emissions summary sector "Mobile - Aircraft" is reported partly to the point and partly to the nonpoint data
categories and "Mobile - Commercial Marine Vessels" and "Mobile - Locomotives" are reported to the nonpoint
data category. We include biogenics emissions, "Biogenics - Vegetation and Soil," in the nonpoint data category
in the EIS; however, we document biogenics in its own Section (8). NEI users who aggregate emissions by EIS
data category rather than EIS sector should be aware that these changes will give differences from historical
summaries of "nonpoint" and "nonroad" data unless care is taken to assign those emissions to the historical
grouping.
Table 2-1: EIS sectors/source categories with EIS data category emissions reflected
Component
EIS Sector or EIS Sector: Source Category Name
Point
Nonpoint
Onroad
Nonroad
Event
Agriculture - Crops & Livestock Dust
0
Agriculture - Fertilizer Application
0
Agriculture - Livestock Waste
0
0
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Component
EIS Sector or EIS Sector: Source Category Name
Point
Nonpoint
Onroad
Nonroad
Event
Biogenics - Vegetation and Soil
0
Bulk Gasoline Terminals
0
0
Commercial Cooking
0
Dust - Construction Dust
0
0
Dust - Paved Road Dust
0
Dust - Unpaved Road Dust
0
Fires - Agricultural Field Burning
0
Fires - Prescribed Burning
0
Fires - Wildfires
0
Fuel Comb - Comm/lnstitutional - Biomass
0
0
Fuel Comb - Comm/lnstitutional - Coal
0
0
Fuel Comb - Comm/lnstitutional - Natural Gas
0
0
Fuel Comb - Comm/lnstitutional - Oil
0
0
Fuel Comb - Comm/lnstitutional - Other
0
0
Fuel Comb - Electric Generation - Biomass
0
Fuel Comb - Electric Generation - Coal
0
Fuel Comb - Electric Generation - Natural Gas
0
Fuel Comb - Electric Generation - Oil
0
Fuel Comb - Electric Generation - Other
0
Fuel Comb - Industrial Boilers, ICEs - Biomass
0
0
Fuel Comb - Industrial Boilers, ICEs - Coal
0
0
Fuel Comb - Industrial Boilers, ICEs - Natural Gas
0
0
Fuel Comb - Industrial Boilers, ICEs - Oil
0
0
Fuel Comb - Industrial Boilers, ICEs - Other
0
0
Fuel Comb - Residential - Natural Gas
0
Fuel Comb - Residential - Oil
0
Fuel Comb - Residential - Other
0
Fuel Comb - Residential - Wood
0
Gas Stations
0
0
0
Industrial Processes - Cement Manufacturing
0
Industrial Processes - Chemical Manufacturing
0
0
Industrial Processes - Ferrous Metals
0
Industrial Processes - Mining
0
0
Industrial Processes - NEC
0
0
Industrial Processes - Non-ferrous Metals
0
0
Industrial Processes - Oil & Gas Production
0
0
Industrial Processes - Petroleum Refineries
0
0
Industrial Processes - Pulp & Paper
0
Industrial Processes - Storage and Transfer
0
0
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Component
EIS Sector or EIS Sector: Source Category Name
Point
Nonpoint
Onroad
Nonroad
Event
Miscellaneous Non-Industrial NEC: Residential Charcoal Grilling
0
Miscellaneous Non-Industrial NEC: Portable Gas Cans
0
Miscellaneous Non-Industrial NEC: Nonpoint Hg
0
Miscellaneous Non-Industrial NEC (All other)
0
0
Mobile - Aircraft
0
Mobile - Commercial Marine Vessels
0
Mobile - Locomotives
0
0
Mobile - NonRoad Equipment - Diesel
0
0
Mobile - NonRoad Equipment - Gasoline
0
0
Mobile - NonRoad Equipment - Other
0
0
Mobile - Onroad - Diesel Heavy Duty Vehicles
0
Mobile - Onroad - Diesel Light Duty Vehicles
0
Mobile - Onroad - Gasoline Heavy Duty Vehicles
0
Mobile - Onroad - Gasoline Light Duty Vehicles
0
Solvent - Consumer & Commercial Solvent Use: Agricultural Pesticides
0
Solvent - Consumer & Commercial Solvent Use: Asphalt Paving
0
Solvent - Consumer & Commercial Solvent Use: All Other Solvents
0
Solvent - Degreasing
0
0
Solvent - Dry Cleaning
0
0
Solvent - Graphic Arts
0
0
Solvent - Industrial Surface Coating & Solvent Use
0
0
Solvent - Non-Industrial Surface Coating
0
Waste Disposal: Open Burning
0
Waste Disposal: Nonpoint POTWs
0
Waste Disposal: Human Cremation
0
Waste Disposal: Nonpoint Hg
0
Waste Disposal (all remaining sources)
0
0
2.2 How is the NEI constructed?
Data in the NEI come from a variety of sources. The emissions are predominantly from S/L/T agencies for both
CAP and HAP emissions. In addition, the EPA quality assures and augments the data provided by states to assist
with data completeness, particularly with the HAP emissions since the S/L/T HAP reporting is voluntary.
The NEI is built by data category for point, nonpoint, nonroad mobile, onroad mobile and events. Each data
category contains emissions from various reporters in multiple datasets which are blended to create the final
NEI "selection" for that data category. Each data category selection includes S/L/T data and numerous other
datasets that are discussed in more detail in each of the following sections in this document. In general, S/L/T
data take precedence in the selection hierarchy, which means that it supersedes any other data that may exist
for a specific county/tribe/facility/process/pollutant. In other words, the selection hierarchy is built such that
the preferred source of data, usually S/L/T, is chosen when multiple sources of data are available. There are
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exceptions, to this general rule, which arise based on quality assurance checks and feedback from S/L/Ts that we
will discuss in later sections.
The EPA uses augmentation and additional EPA datasets to create the most complete inventory for
stakeholders, for use in such applications as NATA, air quality modeling, national rule assessments, international
reporting, and other reports and public inquiries. Augmentation to S/L/T data, in addition to EPA datasets, fill in
gaps for sources and/or pollutants often not reported by S/L/T agencies. The basic types of augmentation are
discussed in the following sections.
2.2.1 Toxics Release Inventory data
The EPA used air emissions data from the 2019 Toxics Release Inventory (TRI) to supplement point source HAP
and NH3 emissions provided to EPA by S/L/T agencies. All TRI emissions values that could reasonably be
matched to an EIS facility with some certainty and with limited risk of double-counting nonpoint emissions were
loaded into the EIS for viewing and comparison if desired, but only those pollutants that were not reported
anywhere at the EIS facility by the S/L/T agency were included in the 2019 NEI.
The TRI is an EPA database containing data on disposal or other releases including air emissions of over 650 toxic
chemicals from approximately 21,000 facilities. One of TRI's primary purposes is to inform communities about
toxic chemical releases to the environment. Data are submitted annually by U.S. facilities that meet TRI
reporting criteria. Section 3 provides more information on how TRI data was used to supplement the point
inventory.
2.2.2 Chromium speciation
The reporting cycle included 5 valid pollutant codes for chromium, as shown in Table 2-2.
Table 2-2: Valid chromium pollutant codes
Pollutant Code
Description
Pollutant Category Name
Speciated?
1333820
Chromium Trioxide
Chromium Compounds
yes
16065831
Chromium III
Chromium Compounds
yes
18540299
Chromium (VI)
Chromium Compounds
yes
7440473
Chromium
Chromium Compounds
no
7738945
Chromic Acid (VI)
Chromium Compounds
yes
In the above table, all pollutants but "chromium" are considered speciated, and so for clarity, chromium
(pollutant 7440473) is referred to as "total chromium" in the remainder of this section. Total chromium could
contain a mixture of chromium with different valence states. Since one key inventory use is for risk assessment,
and since the valence states of chromium have very different risks, speciated chromium pollutants are the most
useful pollutants for the NEI. Therefore, the EPA speciates S/L/T-reported and TRI-based total chromium into
hexavalent chromium and non-hexavalent chromium. Hexavalent chromium, or Chromium (VI), is considered
high risk and other valence states are not. Most of the non-hexavalent chromium is trivalent chromium
(Chromium III); therefore, the EPA characterized all non-hexavalent chromium as trivalent chromium. The 2019
NEI does not contain any total chromium, only the speciated pollutants shown in Table 2-2.
This section describes the procedure we used for speciating chromium emissions from total chromium that was
reported by S/L/T agencies.
We used the EIS augmentation feature to speciate S/L/T agency reported total chromium. For point sources, the
EIS uses the following priority order for applying the factors:
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1) By Process ID
2) By Facility ID
3) By County
4) By State
5) By Emissions Type (for NP only)
6) By SCC
7) By Regulatory Code
8) By NAICS
9) A Default value if none of the others apply
If a particular emissions source of total chromium is not covered by the speciation factors specified by any of the
first 8 attributes, a default value of 34 percent hexavalent chromium, 66 percent trivalent chromium is applied.
For the chromium augmentation, only the "By Facility ID" (2), "By SCC" (6), and "By Default" (9) were used on
S/L/T-reported total chromium values. For TRI dataset chromium, the "By NAICS" (8) option was primarily used,
although a small number of "By Facility" (2) occurrences were used rather than NAICS. The EIS generates and
stores an EPA dataset containing the resultant hexavalent and trivalent chromium species. For all other data
categories (e.g., nonpoint, onroad and nonroad), chromium speciation is performed at the SCC level.
This procedure generated hexavalent chromium (Chromium (VI)) and trivalent chromium (Chromium III), and it
had no impact on S/L/T agency data that were provided as one of the speciated forms of chromium. The sum of
the EPA-computed species (hexavalent and trivalent chromium) equals the mass of the total chromium (i.e.,
pollutant 7440473) submitted by the S/L/T agencies.
The EPA then used this dataset in the 2019 NEI selection by adding it to the data category-specific selection
hierarchy and by excluding the S/L/T agency unspeciated chromium from the selection through a pollutant
exception to the hierarchy.
Most of the speciation factors used in the 2019 NEI are SCC-based and are based on data that have been used by
the EPA for projects that estimate risks. Some factors are updated with every inventory cycle. New data may be
developed by OAQPS during rule development or toxics review. The speciation factors can be accessed in the EIS
through the reference data link "Augmentation Profile Information." A chromium speciation "profile" is a set of
output multiplication factors for a type of emissions source. The profile data for chromium are stored in the
same tables as the HAP augmentation factors described in Section 2.2.3. The speciation factors are a specific
case of HAP augmentation whereby the "output pollutants" are always hexavalent chromium and trivalent
chromium, and the "input pollutant" is always chromium. There are 3 main tables and a summary table. The
summary table excludes the metadata and comments regarding the derivation of the factors and assignment to
SCCs; to learn more of the derivation of the factor or assignment of "profile" to a source, the main tables (not
summary table) should be consulted.
The three main tables are:
• Augmentation Profile Names and Input Pollutants - general information about the profile and source of
the profile names and factors.
• Augmentation Multiplication Factors - provides the output pollutants and multiplication factors
associated with a given Augmentation Profile and input pollutant.
• Augmentation Assignments - provides the assignment of the profile to the data source (the list of 9
items above).
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The summary table is the Augmentation Multiplication Factors and Assignments, a composite table that
provides a view of all the combinations of output pollutants and assignment information associated with a given
profile.
For non-EIS users, the data from the main tables were downloaded and provided as described in Section 3
(3.1.4-S/L/T chromium speciation, 3.1.6 -TRI chromium speciation and 3.1.6, HAP augmentation).
2.2.3 HAP augmentation
The EPA supplements missing HAPs in S/L/T agency-reported data. HAP emissions are calculated by multiplying
appropriate surrogate CAP emissions by a ratio of HAP to CAP emission factors. For the 2019 NEI, we augmented
HAPs for the point and nonpoint data categories. Generally, for point sources, the CAP-to-HAP ratios were
computed using uncontrolled emission factors from the WebFIRE database (which contains primarily AP-42
emissions factors). For nonpoint sources, the ratios were computed from the EPA-generated nonpoint data,
which contain both CAPs and HAPs where applicable.
HAP augmentation is performed on each emissions source (i.e., specific facility and process for point sources,
county and process level for nonpoint sources) using the same EIS augmentation feature as described in
chromium speciation. However, unlike chromium speciation, there is no default augmentation factor so that not
every process that has S/L/T CAP data will end up with augmented HAP data.
HAP augmentation input pollutants are S/L/T-submitted VOC, PM10-PRI, PM25-PRI, S02, and PM10-FIL. The
resulting output can be a single output pollutant or a full suite of output pollutants. Not every source that has a
CAP undergoes HAP augmentation (i.e., livestock NH3 and fugitive dust PM25-PRI). The sum of the HAP
augmentation factors does not need to equal 1 (100%); however, we try to ensure, for example, that the sum of
HAP-VOC factors is less than 1 for mass balance. HAP augmentation factors are grouped into profiles that
contain unique output pollutant factors related to a type of source. Assigning these profiles to the individual
sources depends on the source attributes, commonly the SCC.
There are business rules specific to each data category discussed in the point section (3.1.6) of this TSD and
nonpoint (Section 4.1.6) in the 2017 NEI TSD. The ultimate goal is to prevent double-counting of HAP emissions
between S/L/T data and the EPA HAP augmentation output, and to prevent, where possible, adding HAP
emissions to S/L/T-submitted processes that are not desired. NEI developers use their judgment on how to apply
HAP augmentation to the resulting NEI selection.
Caveats
HAP augmentation does have limitations; HAP and CAP emission factors from WebFIRE do not necessarily use
the same test methods. In some situations, the VOC emission factor is less than the sum of the VOC HAP
emission factors. In those situations, we normalize the HAP ratios so as not to create more VOC HAPs than VOC.
We are also aware that there are many similar SCCs that do not always share the same set of emission
factors/output pollutants. We do not apply ratios based on emission factors from similar SCCs other than for
mercury from combustion SCCs. We would prefer to get HAPs reported from reporting agencies or get the data
from other sources (compliance data from rule), but such data are not always available.
Because many of the AP-42 factors are 20+ years old, many incremental edits to these factors have been made
over time. We have removed some factors based on results of NATA reviews. For example, we discovered
ethylene dichloride was being augmented for SCCs related to gasoline distribution. This pollutant was associated
with leaded gasoline which is no longer used. Therefore, we removed it from our HAP augmentation between
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2011 NEI v2 and 2014. We also received specific facility and process augmentation factors resulting from the
NATA reviews. More discussion of the underlying data used is discussed in Section 3.1.6.
For point sources, HAPs augmentation data are not used when S/L/T air agency data exists at any process at the
facility for the same pollutant. That means that if a S/L/T reports a particular HAP at some processes but misses
others, then those other processes will not be augmented with that HAP.
2.2.4 PM augmentation
Particulate matter (PM) emissions species in the NEI are primary PM10 (called PM10-PRI in the EIS and NEI) and
primary PM2.5 (PM25-PRI), filterable PM10 and filterable PM2.5 (PM10-FIL and PM25-FIL) and condensable PM
(PM-CON). The EPA needed to augment the S/L/T agency PM components for the point and nonpoint
inventories to ensure completeness of the PM components in the final NEI and to ensure that S/L/T agency data
did not contain inconsistencies. An example of an inconsistency is if the S/L/T agency submitted a primary PM2.5
value that was greater than a primary PM10 value for the same process. Commonly, the augmentation added
condensable PM or PM filterable (PM10-FIL and/or PM25-FIL) where none was provided, or primary PM2.5
where only primary PM2.5 was provided.
In general, emissions for PM species missing from S/L/T agency inventories were calculated by applying factors
to the PM emissions data supplied by the S/L/T agencies. These conversion factors were first used in the 1999
NEI's "PM Calculator" as described in an NEI conference paper [ref 1], The resulting methodology allows the EPA
to derive missing PM10-FIL or PM25-FIL emissions from incomplete S/L/T agency submissions based on the SCC
and PM controls that describe the emissions process. In cases where condensable emissions are not reported,
conversion factors are applied to S/L/T agency reported PM species or species derived from the PM Calculator
databases. The PM Calculator has undergone several edits since 1999; now called the "PM Augmentation Tool,"
this Microsoft ® Access ® database is no longer made available because it should not be run for any purpose
other than gap-filling the final NEI selection.
The PM Augmentation Tool is used only for point and nonpoint sources, and the output from the tool is heavily-
screened prior to use in the NEI. This screening is done to prevent trivial overwriting of S/L/T data from PM
Augmentation Tool calculations, particularly for primary PM submittals by S/L/Ts. More details on the caveats to
using the PM Augmentation Tool are discussed in Section 3.1.3 of this TSD for point sources and Section 4.1.5 in
the 2017 NEI TSD for nonpoint sources.
2.2.5 Other EPA datasets
In addition to TRI, chromium speciation, HAP and PM augmentation, the EPA generates other data to produce a
complete inventory. As discussed in Section 3.6, EIS generates the following speciated PM2.5 emissions for
sources with primary PM2.5 emissions: elemental (also referred to as "black") carbon (EC), organic carbon (OC),
nitrate (N03), sulfate (S04), and the remainder of PM25-PRI (PMFINE). In addition, a copy of PM25-PRI and
PM10-PRI from mobile source diesel engines, relabled as DIESEL-PM25 and DIESEL-PM10, respectively, are also
generated. Examples of other EPA data for point sources, discussed in Section 3, include EPA landfills, electric
generating units (EGUs), and aircraft.
2.2.6 Data Tagging
S/L/T agency data generally are used first when creating the NEI selection. When S/L/T data are used, then the
NEI would not use other data (primarily EPA data from stand-alone datasets or HAP, PM or TRI augmentation)
that also may exist for the same process/pollutant. Thus, in most cases the S/L/T agency data are used;
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however, for several reasons, sometimes we need to exclude, or "tag out" S/L/T agency data. Examples of these
"S/L/T tags" are when S/L/T agency staff alert the EPA to exclude their data (because of a mistake or outdated
value), or when EPA staff find problems with submitted data. Another example is when S/L/T emissions data are
significantly less than TRI and are presumed to be incomplete, which can happen for S/L/T that use automated
gap-filling procedures for facilities that do not voluntarily provide HAP emissions. These automated procedures
gap-fill only for processes that have emission factors and miss processes/pollutants that may have been
reported to TRI using other means besides published emission factors.
In previous NEI years data tagging had also been used to avoid double-counting emissions by using emissions
from more than one dataset because the two datasets were at different levels of granularity and thus not able
to be integrated to the full process level of detail required by the standard selection hierarchy software. The
primary example of this is the TRI dataset, which provides facility-total emissions rather than individual process-
level emissions. Because the TRI emissions must be stored to a single emission process that is not the same as
that used by the S/L/T agency, the standard hierarchy selection software would use both. Thus, tagging was
used to "block" any TRI values where the S/L/T had reported the same pollutant at any process(es) within the
same facility. Starting with the 2017 NEI, a series of additional rules were added to the selection hierarchy to
avoid such tagging. Point source datasets are now identified as being either Process-level, Unit-level, or Facility-
level granularity, and the selection software now uses those identifications to avoid double-counting, avoiding
the need for those types of tags.
2.2.7 Inventory Selection
Once all S/L/T and EPA data are quality assured in the EIS, and all augmentation and data tagging are complete,
then we use the EIS to create a data category-specific inventory selection. To do this, each EIS dataset is
assigned a priority ranking prior to running the selection with EIS. The EIS then performs the selection at the
most detailed inventory resolution level for each data category. For point sources, this is the process and
pollutant level. For nonpoint sources, it is the process (SCC)/shape ID (i.e., ports) and pollutant level. For onroad
and nonroad sources, it is process/pollutant, and for events it is day/location/process and pollutant. At these
resolutions, the inventory selection process uses data based on highest priority and excludes data where it has
been tagged. The EPA then quality assures this final blended inventory to ensure expected processes/pollutants
are included or excluded. The EIS uses the inventory selection to also create the SMOKE Flat Files, EIS reports
and data that appear on the NEI website.
2.3 How did the 2017 NEI compare to past inventories?
Many similarities exist between the 2017 NEI approaches and past NEI approaches, notably that the data are
largely compiled from data submitted by S/L/T agencies for CAPs, and that the HAP emissions are augmented by
the EPA to differing degrees depending on geographical jurisdiction because they are a voluntary contribution
from the partner agencies. In 2017, S/L/T participation was somewhat more comprehensive than in 2014,
though both were good. The NEI program continues with the 2017 NEI to work towards a complete compilation
of the nation's CAPs and HAPs. The EPA provided feedback to S/L/T agencies during the compilation of the data
on critical issues (such as potential outliers, missing SCCs, missing Hg data and coke oven data) as has been done
in the past, collected responses from S/L/T agencies to these issues, and improved the inventory for the release
based on S/L/T agency feedback. In addition to these similarities, there are some important differences in how
the 2017 NEI has been created and the resulting emissions, which are described in the following two
subsections.
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2.3.1 Differences in approaches
With any new inventory cycle, changes to approaches are made to improve the process of creating the inventory
and the methods for estimating emissions. The key changes for the 2017 cycle are highlighted here.
To improve the process, we learned from the prior three triennial inventories (for 2008, 2011, and 2014)
compiled with the EIS. We made changes to pollutant, SCC, and NAICS codes, refined quality assurance checks
and features that were used to assist in quality assurance and streamlined the Nonpoint Survey (introduced for
the 2014 NEI) to assist with S/L/T and EPA data reconciliation for the nonpoint data. The update to the nonpoint
survey helped S/L/Ts and EPA avoid double counting and ensure a complete inventory between the different
sources of data.
In addition to process changes, we improved emissions estimation methods for all data categories. We
summarize the differences in approaches in the following sections.
2.3.1.1 Point data category
For point sources, the only change was our use of EPA-developed HAP emission estimates for the EGUs covered
by the Mercury and Air Toxics Standards (MATS) review, rather than the S/L/T reported values. HAP
augmentation improvements are described in Section 3.1.6. More information on point source improvements is
available in Section 3.
2.4 How well are tribal data and regions represented in the 2019 NEI?
Two tribes submitted data to the EIS for 2019 NEI, Southern Ute Indian Tribe and Ute Mountain Tribe of the Ute
Mountain Reservation. In addition, as shown in Table 2-3, data for an additional 6 tribes were carried forward
from the 2017 NEI. In this table, a "CAP, HAP" designation indicates that both criteria and hazardous air
pollutants were submitted by the tribe; "GHG" indicates greenhouse gases were submitted. CAP indicates that
only criteria pollutants were submitted. Facilities on tribal land were augmented using TRI, HAPs, PM, and the
2017 NEI in the same manner as facilities under the state and local jurisdictions, as explained in Section 3.1,
therefore, Tribal Nations in Table 2-3 with just a CAP flag will also have some HAP emissions in most cases. Eight
additional tribal agencies, shown in Table 2-4, which did not submit any data, are represented in the point data
category of the 2019 NEI due to the emissions added by the EPA. The emissions for these facilities are from the
EPA gap fill datasets for airports, EGUs, and TRI data.
Table 2-3: Tribal participation in the 2019 NEI
Tribal Agency
Pollutants
Assiniboine and SiouxTribes of the Fort Peck Indian Reservation
CAP, HAP
Coeur d'Alene Tribe
CAP, HAP
Fort Mojave Indian Tribe of Arizona, California & Nevada
CAP, GHG
Nez Perce Tribe
CAP, HAP
Northern Cheyenne Tribe
CAP
Salt River Pima Maricopa Indian Community (SRPMIC) EPNR
CAP, HAP,
GHG
Shoshone-Bannock Tribes of the Fort Hall Reservation of Idaho
CAP, HAP
Southern Ute Indian Tribe
CAP, HAP,
GHG
Ute Mountain Tribe of the Ute Mountain Reservation
CAP, HAP
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Tribal Agency
Pollutants
Yakama Nation Reservation
CAP, HAP,
GHG
Table 2-4: Facilities on Tribal lands with 2017 NEI emissions from EPA only
Tribal Agency
EPA data used
Assiniboine and Sioux Tribes of the Fort Peck Indian Reservation, Montana
Airports
Fond du Lac Band of Lake Superior Chippewa
Airports
Gila River Indian Community
TRI
Navajo Nation
EGUs
Omaha Tribe of Nebraska
Airports
Southern Ute Indian Tribe
Airports
Tohono O-Odham Nation Reservation
TRI
Ute Indian Tribe of the Uintah & Ouray Reservation, Utah
EGUs
References for 2017 inventory contents overview
Strait, R.; MacKenzie, D.; and Huntley, R., 2003. PM Augmentation Procedures for the 1999 Point and
Area Source NEI. 12th International Emission Inventory Conference - "Emission Inventories - Applying
New Technologies", San Diego, April 29 - May 1, 2003.
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3 Point sources
This section provides a description of sources that are in the point data category. Point sources are included in
the inventory as individual facilities, usually at specific latitude/longitude coordinates, rather than as county or
tribal aggregates. These facilities include large energy and industrial sites, such as electric generating utilities
(EGUs), mines and quarries, cement plants, refineries, large gas compressor stations, and facilities that
manufacture pulp and paper, automobiles, machinery, chemicals, fertilizers, pharmaceuticals, glass, food
products, and other products. Additionally, smaller points sources are included voluntarily by S/L/T agencies,
and can include small facilities such as crematoria, dry cleaners, and even gas stations. These smaller sources
may appear in one state but not another due to the voluntary nature of providing smaller sources. There are
also some portable sources in the point source data category, such as hot mix asphalt facilities, which relocate
frequently as a road construction project progress. The point source data category also includes emissions from
the landing and take-off portions of aircraft operations, the ground support equipment at airports, and
locomotive emissions within railyards. Within a point source facility, emissions are estimated and reported for
individual emission units and processes. Those emissions are associated with any number of stack and fugitive
release points that each have parameters needed for atmospheric modeling exercises.
The approach used to build the 2019 National Emissions Inventory (NEI) for all point sources is discussed in
Section 3.1 through Section 3.6.
3,1 Point source approach; 2019
The general approach to building the NEI point source inventory is to use state/local/tribal (S/L/T)-submitted
emissions, locations, and release point parameters wherever possible. Missing emissions values are gap-filled
with EPA data reflecting 2019 activities where available. Because S/L/Ts are not required to submit all point
sources for 2019, the 2017 NEI is used to gap fill as a last resort where it appears that a facility is still operating
but was just not reported by the S/L/T for 2019 because it is below the reporting thresholds for the non-triennial
NEI years. Quality assurance reviews of the emission values, locations, and release point modeling parameters
are done by the EPA on the most significant emission sources and where data does not pass quality assurance
checks.
3.1.1 QA review of S/L/T data
State/local/tribal agency submittals for the 2019 NEI point sources were accepted through January 15, 2021. We
then compared facility-level pollutant sums as reported by S/L/Ts for 2016 thru 2019 to flag cases where the
2019 values had changed significantly from the earlier years or were missing or were new for 2019 and had
significant and unexpected emissions. The comparison table also showed the 2019 emission values from the
2019 Toxics Release Inventory (TRI), the 2019 S02 and NOx and mercury values as reported to EPA's Clean Air
Markets Division, and the 2019 Greenhouse Gas Reporting Program values. The set of facilities and pollutants
with significant (plus or minus 50 percent from an earlier year) changes was then filtered to only include those
where the absolute mass value of the difference was greater than a pollutant-specific threshold amount. When
a facility-pollutant combination was new in 2019 or didn't appear in the 2019 S/L/T reports, we included those
facilities and pollutants only when some reported year's emissions exceeded the pollutant-specific thresholds
because the percent differences were undefined. The resulting set of 826 facility-pollutant sums were reviewed
to see where we could explain the changes or had some corroborating evidence such as similar changes in TRI,
GHG, or CAMD CEM reports. We removed over half of the flags via this review and provided the final set of 403
facility-pollutant to S/L/T agencies for their review on March 12, 2021.
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State/local/tribal edits to address any emissions values were accepted in the Emissions Inventory System (EIS)
until June 30, 2021. The S/L/T agencies did not change all of the highlighted values. Where the comparisons
were exceptionally suspect, the EPA contacted the agencies by phone or by email if no edits had been made to
obtain confirmation of the reported values. For a small number of cases, neither confirmation nor edits were
obtained, and the value was tagged to be excluded from selection for the NEI. In some but not all of these
instances, a value from TRI or the CAMD data sets was available as a replacement.
Similar to previous NEI years, we quality assured the latitude-longitude coordinates at both the site level and the
release point level. In previous NEI cycles, we had reviewed, verified, and locked (in EIS) approximately 10,000
site-level coordinates of the most significant emitting facilities. For the 2019 NEI coordinate review, we
compared all site coordinate pairs to the county boundaries for the FIPS county codes reported for those
facilities. We then identified all facilities that met both of the following criteria: (1) more than 20 tons total
criteria pollutant emissions or more than 10 pounds total hazardous air pollutants (HAPs) for 2019, (2) the
coordinates caused the location of the facility to be more than a half mile outside of its indicated county. For
these facilities, we reviewed the location using Google Earth, edited the location as needed in EIS, and locked
the location in EIS.
In addition, we compared the release point coordinates of all release points with any 2019 emissions to their
site level coordinates, whether protected or not. In cases where we found a difference of more than 0.003
degrees in either latitude plus longitude, we reviewed the release point coordinates in Google Earth and either
confirmed that the release point appeared to be on the facility's footprint or we removed the release point's
coordinates, which will allow the modeling files to inherit the site coordinates. Site coordinates were edited and
locked as needed as part of this release point coordinate review. A new critical QA check was also implemented
in EIS, beginning with the 2018 NEI point source submittals, to disallow the reporting of facility and release point
coordinates that differ by more than a facility-specific amount for either latitude or longitude. The tolerance
amount was set at 0.003 for most facilities, but that tolerance was increased for facilities where the above
review had confirmed that the individual release point coordinates were valid. Some smaller footprint facilities
that had to be reviewed due to apparent violations also had the tolerance set lower as part of the above review.
Site coordinates as seen in the TRI and GHG Reporting programs were compared to the coordinates in EIS for
matched facilities. Because of similar reviews and the release point comparison work described above, almost
all discrepancies for facilities with any significant emissions had already been reviewed and locked in previous
NEI cycles. A handful of additional facilities were edited and locked in EIS from this review for the 2019 NEI.
An additional round of S/L/T agency review of 2019 HAP emissions from point sources was conducted beginning
July 31, 2021 and ending September 30, 2021. After reviewing all emissions changes, release point location
changes, and release point parameter changes submitted by S/L/T agencies, we created in EIS a facility dataset
containing release point location and release point location changes and a 2019 point dataset consisting of all
accepted HAP emissions changes (EIS dataset 2019EPA_ADTU_SLT). These datasets were applied to the first
version of the 2019 NEI to create a second version of the 2019 NEI in December 2021.
3.1.2 Sources of EPA data and selection hierarchy
Table 3-1 lists the datasets that we used to compile the 2019 NEI point inventory and the hierarchy used to
choose which data value to use for the NEI when multiple data sets are available for the same emissions source.
The EPA developed all datasets other than those containing S/L/T agency data. 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 particulate matter (PM) and to speciate S/L/T agency reported
total chromium into hexavalent and trivalent forms.
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The hierarchy or "order" provided in the tables below defines which data are to be used for situations where
multiple datasets provide emissions for the same pollutant and emissions process. The dataset with the lowest
order number on the list is preferentially used over other datasets. The table includes the rationale for why each
dataset was assigned its position in the hierarchy. In addition to the order of the datasets, the selection also
considers whether individual data values have been tagged. Any data that were tagged by the EPA in any of the
datasets were not used. State/local/tribal agency data were tagged only if they were deemed to be likely
outliers and were not addressed during the S/L/T agency data reviews. As in earlier NEI years, the 2019 point
source selection also excludes dioxins, furans and radionuclides. 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 and accurate estimate for these
pollutants as part of the NEI. The 2019 NEI point source inventory does include greenhouse gas emissions.
Facility total values for four GHGs (CO2, CH4, N20, and SF6) were copied from the U.S. Greenhouse Gas
Inventory Report website and matched to EIS facilities.
The 2019 NEI December 2021 version (EIS dataset 2019NEI_V2) is similar to the September 2021 selection (EIS
dataset 2019NEI_V1) shown in Table 3-1 except for the introduction of S/L/T edits resulting from an S/L/T air
toxics review effort; these S/L/T air toxics edits (EIS dataset 2019EPA_ATDU_SLT) supersede HAP emission
estimates and release point characteristics from the September 2021 selection shown here. Note that we
recommend the December 2021 version be used for analyses that require accurate estimates of air toxics.
Table 3-1: Data sets and selection hierarchy used for 2019 NEI September 2021 release point source data
category
Dataset name
Description and Rationale for the Order of the Selected Datasets
Order
2019EPA_GHG
Facility-level emissions for four specific GHGs from the USEPA's Greenhouse
Gas Reporting Program
1
2019EPA_PM-Aug
PM components added to gap fill missing S/L/T agency data or make
corrections where S/L/T agency have inconsistent emissions across PM
components. Uses ratios of emission factors from the PM Augmentation
Tool for covered source classification codes (SCCs). For SCCs without
emission factors in the tool, checks/corrects discrepancies or missing PM
species using basic relationships such as ensuring that primary PM is
greater than or equal to filterable PM (see Section 3.1.3).
2
Responsible Agency Data
Set
S/L/T agency submitted data through June 2021. These data are selected
ahead of lower hierarchy datasets except where individual values in the
S/L/T agency emissions were suspected outliers that were not addressed
during the draft review and therefore tagged by the EPA.
3
2019EPA_CrAug
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 3.1.4.
4
2019EPA_TRI
TRI data for the year 2019 (see Section 3.1.5). These data are selected for a
facility only when the S/L/T agency data do not include emissions for a
given pollutant at any process for that facility.
5
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Dataset name
Description and Rationale for the Order of the Selected Datasets
Order
2019EPA_TRIcr
TRI data reported as total chromium for the year 2019 speciated into the
chromium III and chromium VI valence amounts, usually by use of a NAICs-
based speciation profile, but possibly by use of a facility-specific profile.
6
2019EPA_HAPAug
HAP data computed from S/L/T agency criteria pollutant data using
HAP/CAP EF ratios based on the EPA Factor Information Retrieval System
(WebFIRE) database as described in Section 3.1.6. These data are selected
below the TRI data because the TRI data are expected to be better.
7
2019EPA_HAPAug-
PMAug
This dataset was created in the same fashion as the 2019EPA_HAPAug
dataset above and is a supplement to it. This dataset contains HAPs
calculated by applying a ratio to PM10-FIL emissions, for those instances
where the S/L/T dataset did not contain any PM10-FIL emissions, but the
PM augmentation routine was able to calculate a PM10-FIL value from
some PM species that was reported by the S/L/T. Note that older draft
versions of the EIS dataset 2019NEI_draft did not include this step.
8
2019EPA_EGU
CAP and HAP emission unit level emissions from either the annual sum of
CAMD hourly CEM data for S02, NOx or Hg or from emission factors used in
previous NEI year inventories from AP-42 and other sources multiplied by
2019 CAMD heat input data.
9
2017NEI_NOV2020_PT
The 2017 NEI selection, used here to gapfill any non-reported facilities and
pollutants that are still marked as "Operating" and for which no 2019
emission estimates are available from any of the higher-ranked datasets.
10
3.1.3 Particulate matter augmentation
Particulate matter emissions components2 in the NEI are primary PM10 (called PM10-PRI in the EIS and NEI) and
primary PM2.5 (PM25-PRI), filterable PM10 (PM10-FIL) and filterable PM2.5 (PM25-FIL) and condensable PM
(PM-CON, which is all within the PM2.5 portion on PM, i.e., PM25-PRI = PM25-FIL + PM-CON). The EPA needed
to augment the S/L/T agency PM components to ensure completeness of the PM components in the final NEI
and to ensure that S/L/T agency data did not contain inconsistencies. An example of an inconsistency is if the
S/L/T agency submitted a primary PM2.5 value that was greater than a primary PM10 value for the same
process. Commonly, the augmentation added condensable PM or PM filterable (PM10-FIL and/or PM25-FIL)
where no value was provided, or primary PM2.5 where only primary PM10 was provided. Additional information
on the procedure is provided in the 2008 NEI PM augmentation documentation [ref 1],
In general, emissions for PM species missing from S/L/T agency inventories were calculated by applying factors
to the PM emissions data supplied by the S/L/T agencies. These conversion factors were first used in the 1999
NEI's "PM Calculator" as described in an NEI conference paper [ref 2], The resulting methodology allows the EPA
to derive missing PM10-FIL or PM25-FIL emissions from incomplete S/L/T agency submissions based on the SCC
and PM controls that describe the emissions process. In cases where condensable emissions are not reported,
conversion factors developed are applied to S/L/T agency reported PM species or species derived from the PM
Calculator databases.
2 We use the term "components" here rather than "species" to avoid confusion with the PM2.5 "species" that are used for
air quality modeling (e.g., organic carbon, elemental carbon, sulfate, nitrate, and other PM).
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3.1.4 Chromium speciation
An overview of chromium speciation, as it impacts both the point and nonpoint data category, is discussed in
Section 2.2.2.
The EIS generates and stores an EPA dataset containing the resultant hexavalent and trivalent chromium
species. The EPA then used this dataset in the 2019 NEI selection by adding it to the selection hierarchy shown in
Table 3-1, excluding the S/L/T agency total chromium from the selection through a pollutant exception to the
hierarchy. This EIS feature does not speciate chromium from any of the EPA datasets because the EPA data
contains only speciated chromium.
For the 2019 NEI, the EPA named this dataset "2019EPA_CrAug." Most of the speciation factors used in the 2019
NEI are SCC-based and are the same as were used for the 2008, 2011, 2014 and 2017 NEIs. There are some
facility-specific factors resulting from reviews of previous year (e.g., 2014 and 2011) National Air Toxics
Assessment (NATA) data. Facility-specific factors were also provided for several facilities by the state of Indiana.
The factors "SLT_based_chromium_speciation.zip", based on data that have long been used by the EPA for
NATA and other risk projects, are available on the 2017 Supplemental data FTP site.
3.1.5 Use of the 2019 Toxics Release Inventory
The EPA used air emissions data from the 2019 TRI to supplement point source HAP and ammonia emissions
provided to the EPA by S/L/T agencies. The resulting augmentation dataset is labeled as "2019EPA_TRI" in the
Table 3-1 selection hierarchy shown above. For 2019, all TRI emissions values that could reasonably be matched
to an EIS facility were loaded into the EIS for viewing and comparison if desired, but only those pollutants that
were not reported anywhere at the EIS facility by the S/L/T agency were included in the 2019 NEI. The March 10,
2021 version of these data was used.
The basis of the 2019EPA_TRI dataset is the US EPA's 2019 Toxics Release Inventory (TRI) Program. The TRI is an
EPA database containing data on disposal or other releases including air emissions of over 650 toxic chemicals
from approximately 21,000 facilities. One of TRI's primary purposes is to inform communities about toxic
chemical releases to the environment. Data are submitted annually by U.S. facilities that meet TRI reporting
criteria.
The approach used for the 2019 NEI was similar to the one used for the 2017 NEI. The TRI emissions were
included in the EIS (and the NEI) as facility-total stack and facility-total fugitive emissions processes, which
matches the aggregation detail of the TRI database. The 2019 NEI used the same software procedures as were
introduced for the 2017 NEI inventory for how we avoid double-counting of TRI and other data sources
(primarily the S/L/T data). Rather than tagging each individual TRI facility-based value for wherever the S/L/T
had reported that pollutant at any process(es) within the same facility, the enhanced EIS selection software does
not use values from a "Facility" level dataset if a more preferred dataset (the S/L/T datasets) has the pollutant at
that facility. In addition to this "facility-based rule" in the selection software, we also used the "pollutant family
rule", also introduced for the 2017 NEI, which prevents pollutants defined as belonging to the same overlapping
family of pollutants from being selected for use if a higher preference dataset has already provided a pollutant
value for that family. This procedure had also been accomplished using tagging in previous NEI years.
The following steps describe in more detail the development of the 2019EPA_TRI dataset.
1. Update the TRI_ID to EISJD facility-level crosswalk
For the 2019 NEI, the same crosswalk list of TRI IDs that was used for the 2018 NEI was used as a starting
point. A limited review of the 2019 TRI facilities was conducted to identify new facilities with significant
3-15
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emissions that had not been previously matched to an EIS facility. A total of approximately 20 additional
TRI facilities were added to the crosswalk for 2019.
Map TRI pollutant codes to valid EIS pollutant codes and sum where necessary
Table 3-2 provides the pollutant mapping from TRI pollutants to EIS pollutants. Many of the 650 TRI
pollutants do not have any EIS counterpart, and so are not shown in Table 3-2. In addition, several EIS
pollutants may be reported to TRI as either of two TRI pollutants. For example, both Pb and Pb
compounds may be reported to TRI, and similarly for several other metal and metal compound TRI
pollutants. Table 3-2 shows where such pairs of TRI pollutants both correspond to the same EIS
pollutant. In such cases, we summed the two TRI pollutants together as part of the step of assigning the
TRI emissions to valid EIS pollutant codes. For the 2019 NEI, a total of 198 TRI pollutant codes were
mapped to 186 unique EIS pollutant codes. Similar to prior year NEIs, we did not use TRI emissions
reported for TRI pollutants: "Certain Glycol Ethers," "Dioxin and Dioxin-like Compounds,"
Dichlorobenzene (mixed isomers)," and "Toluene di-isocyanate (mixed isomers)," because they do not
represent the same scope as the EIS pollutants: "Glycol ethers," "Dioxins/Furans as 2,3,7,8-TCDD TEQs,"
"1,4-Dichlorobenzene," and "2,4-Di-isocyanate," respectively. We maintained TRI stack and fugitive
emissions separately during the summation step and maintained that separation through the storage of
the TRI emissions in the EIS.
Table 3-2: Mapping of TRI pollutant codes to EIS pollutant codes
TRI CAS
TRI Pollutant Name
EIS Pollutant
Code
EIS Pollutant Name
106945
1-BROMOPROPANE
106945
1-BROMOPROPANE
79345
1,1,2,2-TETRACHLOROETHANE
79345
1,1,2,2-TETRACH LOROETH ANE
79005
1,1,2-TRICHLOROETHANE
79005
1,1,2-TRICHLOROETHANE
57147
1,1-DIMETHYL HYDRAZINE
57147
1,1-DIMETHYL HYDRAZINE
120821
1,2,4-TRICHLOROBENZENE
120821
1,2,4-TRICHLOROBENZENE
96128
l,2-DIBROMO-3-CHLOROPROPANE
96128
l,2-DIBR0M0-3-CHL0R0PR0PANE
57147
1,1-DIMETHYL HYDRAZINE
57147
1,1-Dimethyl Hydrazine
106887
1,2-BUTYLENE OXIDE
106887
1,2-EPOXYBUTANE
75558
PROPYLENEIMINE
75558
1,2-PROPYLENIMINE
106990
1,3-BUTADIENE
106990
1,3-BUTADIENE
542756
1,3-DICHLOROPROPYLENE
542756
1,3-DICHLOROPROPENE
1120714
PROPANE SULTONE
1120714
1,3-PROPANESULTONE
106467
1,4-DICHLOROBENZENE
106467
1,4-DICHLOROBENZENE
25321226
DICHLOROBENZENE (MIXED ISOMERS)
NA- pollutant not used
95954
2,4,5-TRICHLOROPHENOL
95954
2,4,5-TRICHLOROPHENOL
88062
2,4,6-TRICHLOROPHENOL
88062
2,4,6-TRICHLOROPHENOL
94757
2,4-DICHLOROPHENOXY ACETIC ACID
94757
2,4-DICHLOROPHENOXY ACETIC ACID
51285
2,4-DINITROPHENOL
51285
2,4-DINITROPHENOL
121142
2,4-DINITROTOLUENE
121142
2,4-DINITROTOLUENE
53963
2-ACETYLAMINOFLUORENE
53963
2-ACETYLAMINOFLUORENE
79469
2-NITROPROPANE
79469
2-NITROPROPANE
91941
3,3'-DICHLOROBENZI DINE
91941
3,3'- DICHLOROBENZI DINE
119904
3,3'-DIMETH0XYBENZIDINE
119904
3,3'- DIMETHOXYBENZIDINE
119937
3,3'-DIMETHYLBENZIDINE
119937
3,3'-DIMETHYLBENZIDINE
101144
4,4'-METHYLENEBIS(2-CHL0R0ANILINE)
101144
4,4'-METHYLENEBIS(2-CHL0RANILINE)
101779
4,4'-METHYLEN EDI ANILINE
101779
4,4'-METHYLENEDIANILINE
534521
4,6-DINITR0-0-CRES0L
534521
4,6-DINITR0-0-CRES0L
92671
4-AMINOBIPHENYL
92671
4-AMINOBIPHENYL
60117
4-DIMETHYLAMINOAZOBENZENE
60117
4-DIMETHYLAMINOAZOBENZENE
100027
4-NITROPHENOL
100027
4-NITROPHENOL
75070
ACETALDEHYDE
75070
ACETALDEHYDE
60355
ACETAMIDE
60355
ACETAMIDE
75058
ACETONITRILE
75058
ACETONITRILE
98862
ACETOPHENONE
98862
ACETOPHENONE
107028
ACROLEIN
107028
ACROLEIN
79061
ACRYLAMIDE
79061
ACRYLAMIDE
3-16
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TRI CAS
TRI Pollutant Name
EIS Pollutant
Code
EIS Pollutant Name
79107
ACRYLIC ACID
79107
ACRYLIC ACID
107131
ACRYLONITRILE
107131
ACRYLONITRILE
107051
ALLYL CHLORIDE
107051
ALLYL CHLORIDE
7664417
AMMONIA
NH3
AMMONIA
62533
ANILINE
62533
ANILINE
7440360
ANTIMONY
7440360
ANTIMONY
N010
ANTIMONY COMPOUNDS
7440360
ANTIMONY
7440382
ARSENIC
7440382
ARSENIC
N020
ARSENIC COMPOUNDS
7440382
ARSENIC
1332214
ASBESTOS (FRIABLE)
1332214
ASBESTOS
71432
BENZENE
71432
BENZENE
92875
BENZIDINE
92875
BENZIDINE
98077
BENZOIC TRICHLORIDE
98077
BENZOTRICHLORIDE
100447
BENZYL CHLORIDE
100447
BENZYL CHLORIDE
7440417
BERYLLIUM
7440417
BERYLLIUM
N050
BERYLLIUM COMPOUNDS
7440417
BERYLLIUM
92524
BIPHENYL
92524
BIPHENYL
117817
DI(2-ETHYLHEXYL) PHTHALATE
117817
BIS(2-ETHYLHEXYL)PHTHALATE
542881
BIS(CHLOROMETHYL) ETHER
542881
BIS(CHLOROMETHYL)ETHER
75252
BROMOFORM
75252
BROMOFORM
7440439
CADMIUM
7440439
CADMIUM
N078
CADMIUM COMPOUNDS
7440439
CADMIUM
156627
CALCIUM CYANAMIDE
156627
CALCIUM CYANAMIDE
133062
CAPTAN
133062
CAPTAN
63252
CARBARYL
63252
CARBARYL
75150
CARBON DISULFIDE
75150
CARBON DISULFIDE
56235
CARBON TETRACHLORIDE
56235
CARBON TETRACHLORIDE
463581
CARBONYL SULFIDE
463581
CARBONYL SULFIDE
120809
CATECHOL
120809
CATECHOL
57749
CHLORDANE
57749
CHLORDANE
7782505
CHLORINE
7782505
CHLORINE
79118
CHLOROACETIC ACID
79118
CHLOROACETIC ACID
108907
CHLOROBENZENE
108907
CHLOROBENZENE
510156
CHLOROBENZILATE
510156
Chlorobenzilate
67663
CHLOROFORM
67663
CHLOROFORM
107302
CHLOROMETHYL METHYL ETHER
107302
CHLOROMETHYL METHYL ETHER
126998
CHLOROPRENE
126998
CHLOROPRENE
7440473
CHROMIUM
7440473
CHROMIUM
N090
CHROMIUM COMPOUNDS (EXCEPT CHROMITE
ORE MINED IN THE TRANSVAAL REGION)
7440473
CHROMIUM
7440484
COBALT
7440484
COBALT
N096
COBALT COMPOUNDS
7440484
COBALT
1319773
CRESOL (MIXED ISOMERS)
1319773
CRESOL/CRESYLIC ACID (MIXED ISOMERS)
108394
M-CRESOL
108394
M-CRESOL
95487
O-CRESOL
95487
O-CRESOL
106445
P-CRESOL
106445
P-CRESOL
98828
CUMENE
98828
CUMENE
N106
CYANIDE COMPOUNDS
57125
CYANIDE
74908
HYDROGEN CYANIDE
57125
CYANIDE
132649
DIBENZOFURAN
132649
DIBENZOFURAN
84742
Dl BUTYL PHTHALATE
84742
DIBUTYL PHTHALATE
111444
BIS(2-CHLOROETHYL) ETHER
111444
DICHLOROETHYL ETHER
62737
DICHLORVOS
62737
DICHLORVOS
111422
DIETHANOLAMINE
111422
DIETHANOLAMINE
64675
DIETHYL SULFATE
64675
DIETHYL SULFATE
131113
DIMETHYL PHTHALATE
131113
DIMETHYL PHTHALATE
77781
DIMETHYL SULFATE
77781
DIMETHYL SULFATE
79447
DIMETHYLCARBAMYL CHLORIDE
79447
DIMETHYLCARBAMOYL CHLORIDE
N120
DIISOCYANATES
NA- pollutant not used
26471625
TOLUENE DIISOCYANATE (MIXED ISOMERS)
NA- pollutant not used
584849
TOLUENE-2,4-DIISOCYANATE
584849
2,4-TOLUENE DIISOCYANATE
N150
DIOXIN AND DIOXIN-LIKE COMPOUNDS
NA- pollutant not used
106898
EPICHLOROHYDRIN
106898
EPICHLOROHYDRIN
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TRI CAS
TRI Pollutant Name
EIS Pollutant
Code
EIS Pollutant Name
140885
ETHYL ACRYLATE
140885
ETHYL ACRYLATE
51796
URETHANE
51796
ETHYL CARBAMATE
75003
CHLOROETHANE
75003
ETHYL CHLORIDE
100414
ETHYLBENZENE
100414
ETHYL BENZENE
106934
1,2-DIBROMOETHANE
106934
ETHYLENE DIBROMIDE
107062
1,2-DICHLOROETHANE
107062
ETHYLENE DICHLORIDE
107211
ETHYLENE GLYCOL
107211
ETHYLENE GLYCOL
151564
ETHYLENEIMINE
151564
ETHYLENEIMINE
75218
ETHYLENE OXIDE
75218
ETHYLENE OXIDE
96457
ETHYLENE THIOUREA
96457
ETHYLENE THIOUREA
75343
ETHYLIDENE DICHLORIDE
75343
ETHYLIDENE DICHLORIDE
50000
FORMALDEHYDE
50000
FORMALDEHYDE
N230
CERTAIN GLYCOL ETHERS
171
N/A Pollutant not used
76448
HEPTACHLOR
76448
HEPTACHLOR
118741
HEXACHLOROBENZENE
118741
HEXACHLOROBENZENE
87683
HEXACHLORO-l,3-BUTADIENE
87683
HEXACHLOROBUTADIENE
77474
HEXACHLOROCYCLOPENTADIENE
77474
HEXACHLOROCYCLOPENTADIENE
67721
HEXACHLOROETHANE
67721
HEXACHLOROETHANE
110543
N-HEXANE
110543
HEXANE
302012
HYDRAZINE
302012
HYDRAZINE
7647010
HYDROCHLORIC ACID (1995 AND AFTER "ACID
AEROSOLS" ONLY)
7647010
HYDROCHLORIC ACID
7664393
HYDROGEN FLUORIDE
7664393
HYDROGEN FLUORIDE
123319
HYDROQUINONE
123319
HYDROQUINONE
7439921
LEAD
7439921
LEAD
N420
LEAD COMPOUNDS
7439921
LEAD
58899
LINDANE
58899
1,2,3,4,5,6-HEXACHLOROCYCLOHEXANE
108316
MALEIC ANHYDRIDE
108316
MALEIC ANHYDRIDE
7439965
MANGANESE
7439965
MANGANESE
N450
MANGANESE COMPOUNDS
7439965
MANGANESE
7439976
MERCURY
7439976
MERCURY
N458
MERCURY COMPOUNDS
7439976
MERCURY
67561
METHANOL
67561
METHANOL
72435
METHOXYCHLOR
72435
METHOXYCHLOR
74839
BROMOMETHANE
74839
METHYL BROMIDE
74873
CHLOROMETHANE
74873
METHYL CHLORIDE
71556
1,1,1-TRICHLOROETHANE
71556
METHYL CHLOROFORM
74884
METHYL IODIDE
74884
METHYL IODIDE
108101
METHYL ISOBUTYL KETONE
108101
METHYL ISOBUTYL KETONE
624839
METHYL ISOCYANATE
624839
METHYL ISOCYANATE
80626
METHYL METHACRYLATE
80626
METHYL METHACRYLATE
1634044
METHYL TERT-BUTYL ETHER
1634044
METHYLTERT-BUTYL ETHER
75092
DICHLOROMETHANE
75092
METHYLENE CHLORIDE
60344
METHYL HYDRAZINE
60344
METHYLHYDRAZINE
121697
N,N-DIMETHYLANILINE
121697
N,N-DIMETHYLANILINE
68122
N,N-DIMETHYLFORM AMIDE
68122
N,N-DIMETHYLFORMAMIDE
91203
NAPHTHALENE
91203
NAPHTHALENE
7440020
NICKEL
7440020
NICKEL
N495
NICKEL COMPOUNDS
7440020
NICKEL
98953
NITROBENZENE
98953
NITROBENZENE
684935
N-NITROSO-N-METHYLUREA
684935
N-NITROSO-N-METHYLUREA
90040
O-ANISIDINE
90040
O-ANISIDINE
95534
O-TOLUIDINE
95534
O-TOLUIDINE
123911
1,4-DIOXANE
123911
P-DIOXANE
56382
PARATHION
56382
PARATHION
82688
QUINTOZENE
82688
PENTACHLORONITROBENZENE
87865
PENTACHLOROPHENOL
87865
PENTACHLOROPHENOL
108952
PHENOL
108952
PHENOL
75445
PHOSGENE
75445
PHOSGENE
7803512
PHOSPHINE
7803512
PHOSPHINE
7723140
PHOSPHORUS (YELLOW OR WHITE)
7723140
PHOSPHORUS
85449
PHTHALIC ANHYDRIDE
85449
PHTHALIC ANHYDRIDE
1336363
POLYCHLORINATED BIPHENYLS
1336363
POLYCHLORINATED BIPHENYLS
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TRI CAS
TRI Pollutant Name
EIS Pollutant
Code
EIS Pollutant Name
120127
ANTHRACENE
120127
ANTHRACENE
191242
BENZO(G,H,l)PERYLENE
191242
BENZO[G,H,l,]PERYLENE
85018
PHENANTHRENE
85018
PHENANTHRENE
N590
POLYCYCLIC AROMATIC COMPOUNDS
130498292
PAH, TOTAL
106503
P-PHENYLENEDIAMINE
106503
P-PHENYLENEDIAMINE
123386
PROPIONALDEHYDE
123386
PROPIONALDEHYDE
114261
PROPOXUR
114261
PROPOXUR
78875
1,2-DICHLOROPROPANE
78875
PROPYLENE DICHLORIDE
75569
PROPYLENE OXIDE
75569
PROPYLENE OXIDE
91225
QUIN0UNE
91225
QUIN0UNE
106514
QUINONE
106514
QUINONE
7782492
SELENIUM
7782492
SELENIUM
N725
SELENIUM COMPOUNDS
7782492
SELENIUM
100425
STYRENE
100425
STYRENE
96093
STYRENE OXIDE
96093
STYRENE OXIDE
127184
TETRACHLOROETHYLENE
127184
TETRACHLOROETHYLENE
7550450
TITANIUM TETRACHLORIDE
7550450
TITANIUM TETRACHLORIDE
108883
TOLUENE
108883
TOLUENE
95807
2,4-DIAMINOTOLUENE
95807
TOLUENE-2,4-DI AMINE
8001352
TOXAPHENE
8001352
TOXAPHENE
79016
TRICHLOROETHYLENE
79016
TRICHLOROETHYLENE
121448
TRIETHYLAMINE
121448
TRIETHYLAMINE
1582098
TRIFLURALIN
1582098
TRIFLURALIN
108054
VINYL ACETATE
108054
VINYL ACETATE
75014
VINYL CHLORIDE
75014
VINYL CHLORIDE
75354
VINYLIDENE CHLORIDE
75354
VINYLIDENE CHLORIDE
108383
M-XYLENE
108383
M-XYLENE
95476
O-XYLENE
95476
O-XYLENE
106423
P-XYLENE
106423
P-XYLENE
1330207
XYLENE (MIXED ISOMERS)
1330207
XYLENES (MIXED ISOMERS)
3. Split TRI total chromium emissions into hexavalent and trivalent emissions
The TRI allows facilities to report either "Chromium" or "Chromium compounds/' but not the hexavalent
or trivalent chromium species that are needed for the NEI (see Section 3.1.4). Because the only
characterization available for the TRI facilities or their emissions is the facilities' NAICS codes, we created
a NAICS-based set of fractions to split the TRI-reported total chromium emissions into the hexavalent
and trivalent chromium species. A table of Standard Industrial Classification (SlC)-based chromium split
fractions was available from earlier year NEI usage of TRI databases, which had been compiled by SIC
rather than NAICS. The earlier SIC-based fractions were used wherever they could be re-assigned to a
closely matching NAICS description.
Unfortunately, not all SIC-based fractions could be assigned this way, so we computed NAICS-based split
fractions for any NAICS codes in the 2017 TRI data that did not already have an SIC-to-NAICS assigned
split fraction. These factors were used for the remaining TRI-reported chromium. To calculate the NAICS-
based factors, we summed by NAICS the total amounts of chromium III and chromium VI for the entire
U.S. in the 2014 draft NEI data. These 2014 NEI S/L/T emissions were either reported directly by the
S/L/T agencies as chromium III and chromium VI, or they had been split from S/L/T agency-reported
total chromium by the EPA using the procedures described in Section 3.1.4. Those procedures largely
rely on either SCC-based or Regulatory code-based split factors. The derived NAICS split factors,
therefore, represent a weighted average of the SCC and Regulatory code-based split factors, weighted
according to the mass of each chromium valence in the 2014 NEI for that NAICS.
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After all TRI facilities with chromium had been assigned a NAICS-based split factor, the factors were
applied separately to both the TRI stack and fugitive total chromium emissions. This resulted in
speciated chromium emissions for each facility's stack and fugitive emissions that were included in the
EIS as part of the 2019EPA_TRI dataset.
Similar to S/L/T chromium speciation data, the TRI chromium speciation data includes some facility-
specific values resulting from 2011 and/or 2014 NATA reviews or provided by S/L/T for use in the 2017
NEI. The TRI-chromium speciation data "TRI_based_chromium_speciation.zip" is available on the 2017
Supplemental data FTP site.
4. Write the 2019 TRI emissions to EIS Process IDs with stack and fugitive release points
The total facility stack and total facility fugitive emissions values from the above steps were written to a
set of EIS process IDs created to reflect those facility total type emissions. In most cases, the EIS process
IDs for a given facility already existed in EIS as a result of an earlier NEI.
5. Revise SCCs on the EIS Processes used for the TRI emissions
The 2002 and 2005 NEIs had assigned all the TRI emissions to a default process code SCC of 39999999,
which caused a large amount of HAP emissions to be summed to a misleading "miscellaneous" sector.
The 2008 NEI approach reduced this problem somewhat because it apportioned all TRI emissions to the
multiple processes and SCCs that were used by the S/L/T agencies to report their emissions, but this
apportioning created other distortions. The 2011 NEI, and all NEIs since, reverted back to loading the TRI
emissions as the single process stack and fugitive values as reported by facilities to the TRI, but we
revised the SCCs on those single processes to something other than the default 39999999 wherever
possible. The purpose of this is to allow the TRI emissions to map to a more appropriate EIS sector.
3.1.6 HAP augmentation based on emission factor ratios
The 2019EPA_HAP-augmentation dataset was used for gap filling missing HAPs in the S/L/T agency-reported
data. We calculated HAP emissions by multiplying the appropriate surrogate CAP emissions (provided by S/L/T
agencies) by an emissions ratio of HAP to CAP EFs. For point sources, these EF ratios were largely the same as
were used in the 2008 NEI v3, though additional quality assurance resulted in some changes. The ratios were
computed using the EFs from WebFIRE and are based solely on the SCC code. The computation of these point
HAP to CAP ratios is described in detail in the 2008 NEI documentation. Section 3.1.5.
For pollutants other than Hg, we computed ratios for only the SCCs in WebFIRE that met specific criteria: 1) the
CAP and HAP WebFIRE EFs were both based on uncontrolled emissions and, 2) the units of the EF had to be the
same or be able to be converted to the same units. In addition, for Hg, we added ratios for point SCCs that were
not in WebFIRE for both PM10-FIL (the CAP surrogate for Hg) and Hg by using Hg or PM10-FIL factors for similar
SCCs and computing the resulting ratio. That process is described (and supporting data files provided) in the
2008 NEI documentation (Section 3.1.5.2), since these additional Hg augmentation factors were used in the
2008 NEI v3 as well.
A HAP augmentation feature was built into the EIS for the 2011 cycle, and the HAP EF ratios are available to the
EIS users through the reference data link "Augmentation Profile Information." The same tables provide both the
HAP augmentation factors and chromium speciation factors and were discussed in Section 2.2.2.
Since the initial set of HAP augmentation factors, factors and/or SCC-assignments were added including facility-
specific HAP augmentation factors resulting from past NATA reviews. New for the 2017 NEI were facility-specific
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coke oven to S02 ratios used to compute coke oven emissions for specific facilities with operating coke ovens
that were missing coke oven emissions. We have been also using test-based emission factor ratios in place of
WebFIRE-based ratios where data are sufficient to do so. Users interested in the few test-based factors that do
not have access to EIS can download the full set of HAP augmentation factors from the 201? Supplemental data
FTP site ("HAPaugmentation.zip") and peruse the metadata information (data source and factor comments) to
extract them.
3.1.7 Cross-dataset tagging rules for overlapping pollutants
Several HAPs can be reported as individual chemicals or chemicals that reflect a group which can overlap with
individual chemicals, e.g., o-Xylene and Xylenes (mixed isomers). In previous NEI cycles, we tagged out data to
prevent double counting of pollutants across datasets that overlap one another. For the 2017 NEI, a software
solution that occurs during the blending process was developed so that overlapping pollutants would be
excluded from the selection. The business rules were documented as part of the 2017 NEI plan (see Appendix 5).
One change to these "Proposed" rules that we implemented for the 2017 NEI is that we allow individual xylene
isomers to be reported with Xylenes (mixed isomers) within the same dataset. The cross-data business rules
remain unchanged in that they do not allow any individual isomer from one dataset to be used in a selection
when the mixed isomers pollutant appears in a higher ranked dataset, and vice-versa.
3.2 Airports: aircraft-related emissions
For the 2019 NEI Point data category we relied on the last dataset in the selection hierarchy
("2017NEI_NOV2020_PT") to gap fill the aircraft-related emissions. The 2019 aircraft-related emissions are
therefore the same as the 2017 NEI aircraft emissions. See Section 3.2 in the 2017 NEI TSD for a description of
how those emissions were developed.
3.3 Rail yard-related emissions
For the 2019 NEI Point data category we relied on the last dataset in the selection hierarchy
("2017NEI_NOV2020_PT") to gap fill the rail yard-related emissions. The 2019 rail yard-related emissions are
therefore the same as the 2017NEI rail yard emissions. See Section 3.3 in the 2017 NEI TSD for a description of
how those emissions were developed.
3.4 EGUs
The EPA developed a single combined dataset of emission estimates for EGUs to be used to fill gaps for
pollutants and emission units not reported by S/L/T agencies. For the 2019EPA_EGU dataset, the emissions were
estimated at the unit level, because that is the level at which the CAMD heat input activity data and the MATS-
based emissions factors (EFs) and the CAMD CEMS data are available. The 2019EPA_EGU dataset was developed
from three separate estimation sources. The three sources were the 2010 MATS rule development testing
program EFs for 15 HAPs; annual sums of S02 and NOx emissions based on the hourly CEMS emissions reported
to the EPA's CAMD database; and heat-input based EFs that were built from AP-42 EFs and fuel heat and sulfur
contents as part of the 2008 NEI development effort. We used the 2019 annual throughputs in BTUs from the
CAMD database with the two EF sets to derive annual emissions for 2019.
As shown above in Table 3-1, the selection hierarchy was set such that S/L/T-submitted data was used ahead of
the values in the 2019EPA_EGU dataset. In the 2011 NEI, the EPA EGU estimated emissions that were derived
from the MATS testing program were used ahead of the S/L/T values, unless the S/L/T submittal indicated that
the value was from either a CEM or a recent stack test. For the 2019 NEI, we used the S/L/T-reported values
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wherever they were reported (unless they were tagged out as an outlier), including where a MATS-based value
existed in the 2019EPA EGU dataset. In addition, we made the MATS emission factors available to S/L/T agencies
far in advance of the data being submitted so that facilities and/or S/L/T agencies could choose to use that
information to compute emissions if it was most applicable.
We assumed that all heat input came from the primary fuel, and the EFs used reflected only that primary fuel.
This introduces a small amount of uncertainty as many EGU units use a small amount of alternative fuels. The
resultant unit-level estimates had to be loaded into EIS at the process-level to meet the EIS requirement that
emissions can only be associated with the most detailed level. To do this for the EGU sectors, we needed to
bridge the unit level (i.e., the boiler or gas turbine unit as a whole) to the process level (i.e., the individual fuels
burned within the units). So, the EPA emissions were assigned to a single process for the primary fuel that was
used by the responsible S/L/T agency for reporting the largest portion of their emissions. A part of the selection
software includes a "unit-based" rule that prevents the need to tag out EPA emissions estimates for EGUs that
do not align at exactly the same process ID that the S/L/T may have used. This approach prevented double
counting of a portion of the S/L/T-reported emissions in cases where the S/L/T agency may have reported a
unit's emissions using two different coal processes and a small oil process, for example.
The matching of the 2019EPA_EGU dataset to the responsible agency facility, unit and process IDs was done
largely by using the ORIS plant and CAMD boiler IDs as found in the CAMD heat input activity dataset and linking
these to the same two IDs as had been stored in EIS. We also compared the facility names and counties for
agreement between the S/L/T-reported values and those in CAMD, and we revised the matches wherever
discrepancies were noted. As a final confirmation that the correct emissions unit and a reasonable process ID in
EIS had been matched to the EPA data, the magnitudes of the S02 and NOx emissions for all preliminary
matches were compared between the S/L/T agency-reported datasets and the EPA dataset. We identified and
resolved several discrepancies from this emissions comparison.
Alternative facility and unit IDs needed for matching with other databases
The 2019 NEI data contains two sets of alternate unit identifiers related to the ORIS plant and CAMD boiler IDs
(as found in the CAMD heat input activity dataset) for export to the Sparse Matrix Operator Kernel Emissions
(SMOKE) modeling file. The first set is stored in EIS with a Program System Code (PSC) of "EPACAMD." The
alternate unit IDs are stored as a concatenation of the ORIS Plant ID and CAMD boiler ID with "CAMDUNIT"
between the two IDs. These IDs are exported to the SMOKE file in the fields named ORIS_FACILITY_CODE and
ORIS_BOILER_ID. These two fields are used by the SMOKE processing software to replace the annual NEI
emissions values with the appropriate hourly CEM values at model run time. The second set of alternate unit IDs
are stored in EIS with a PSC of "EPAIPM" and are exported to the SMOKE file as a field named "IPM_YN." The
SMOKE software that prepares emissions data for air quality modeling uses this field to determine if the unit is
one that will have future year projections provided by the integrated planning model (IPM). The storage format
of these alternate EPAIPM unit IDs, in both EIS and in the exported SMOKE file, replicates the IDs as found in the
National Electric Energy Data System (NEEDS) database used as input to the IPM model. The NEEDS IDs are a
concatenation of the ORIS plant ID and the CAMD boiler ID, with either a "_B_" or a "_G_" between the two IDs,
indicating "Boiler" or "Generator." The ORIS Plant IDs and CAMD boiler IDs as stored in the CAMD Business
System (CAMDBS) dataset and in the NEEDS database are almost always the same, but there are occasional
differences in the numbering used for the same unit. The EPACAMD alternate unit IDs available in EIS are
believed to be a complete set of all those that can safely be used for the purpose of substituting hourly CEM
values without double-counting during SMOKE processing. The EPAIPM alternate unit IDs in the 2019 NEI are
not a complete listing of all the NEEDS/IPM units, although most of the larger emitters do have an EPAIPM
alternate unit ID. The NEEDS database includes a much larger set of smaller, non-CEM units.
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3.5 Landfills
For the 2019 NEI Point data category we relied on the last dataset in the selection hierarchy
("2017NEI_NOV2020_PT") to gap fill the landfill emissions. The 2019 landfill emissions are therefore the same
as the 2017NEI landfill emissions. See Section 3.5 in the 2017 NEI TSD for a description of how those emissions
were developed.
3.6 PM species
For the 2019 NEI PT inventory, the five species (EC, OC, S04, N03, and other) of PM2.5-PRI and diesel PM (which
are estimated for diesel mobile engines such as locomotives and diesel-fueled ground support equipment) were
developed and included using a new part of the selection software. A separate dataset for these species is
therefore not included in the hierarchy. These species were generated using the same multiplication ratios as
in the 2017 NEI using the PM speciation ratios as found on the Air Emissions Modeling website.
3.7 References for point sources
1. Dorn, J, 2012. Memorandum: 2011 NEI Version 2 - PM Augmentation approach. Memorandum to Roy
Huntley, US EPA. (PM augmt 2011 NEIv2 feb2012.pdf, accessible in the file "2008nei_references.zip" on
the 2008v3 NEI FTP site.
2. Strait et al. (2003). Strait, R.; MacKenzie, D.; and Huntley, R., 2003. PM Augmentation Procedures for the
1999 Point and Area Source NEI. 12th International Emission Inventory Conference - "Emission
Inventories - Applying New Technologies", San Diego, April 29 - May 1, 2003.
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United States Office of Air Quality Planning and Standards Publication No. EPA-454/R-22-001
Environmental Protection Air Quality Assessment Division February 2022
Agency Research Triangle Park, NC
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