United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-454/R-00-018
October 2000
Air
& EPA
USER'S GUIDE FOR THE EMISSIONS MODELING
SYSTEM FOR HAZARDOUS AIR POLLUTANTS
(EMS-HAP, VERSION 1.1)
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EPA-454/R-00-018
n!
\
USER'S GUIDE FOR THE
EMISSIONS MODELING SYSTEM
FOR HAZARDOUS AIR POLLUTANTS
(EMS-HAP, VERSION 1.1)
\)
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air Quality Planning and Standards
Emissions, Monitoring and Analysis Division
Research Triangle Park, North Carolina 27711
October 2000
> **»•
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DISCLAIMER
The information in this document has been reviewed in accordance with the U.S. EPA
administrative review policies and approved for publication. Mention of trade names or
commercial products does not constitute endorsement or recommendation for their use.
The following trademarks appear in this document:
UNIX is a registered trademark of AT&T Bell Laboratories.
SAS® is a registered trademark of SAS Institute.
SUN is a registered trademark of Sun Microsystems, Inc.
ACKNOWLEDGMENTS
Madeleine Strum (EPA) served as the primary technical editor and developer of this document.
Contributors to the technical content include Joe Touma (NOAA) and code developers: Bill
Battye, Diane Linderman (EC/R), John Langstaff (EPA, formerly with EC/R) and Richard
Mason (Dyntel). Tom Murawski, (The Murawski Group) assisted with document organization.
Patricia McGhee (Dyntel) assisted with formatting and editing.
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TABLE OF CONTENTS
CHAPTER 1 INTRODUCTION 1-1
1.1 What is EMS-HAP? 1-1
• 1.2 What are the main features of EMS-HAP? 1-2
1.3 How do I use this Guide? 1-4
CHAPTER 2 AIRCRAFT EMISSIONS PROCESSING
THE AIRCRAFT EMISSIONS PROCESSING PROGRAM (AirportProc) 2-1
2.1 What is the function of AirportProc? 2-1
2.1.1 Allocates county-level aircraft emissions to specific airports 2-3
2.1.2 Prepares allocated emissions for the point source processing programs 2-3
2.1.3 Appends unallocated emissions back to the mobile source inventory 2-4
2.2 How do I run AirportProc? 2-4
2.2.1 Prepare your mobile source inventory for input into AirportProc 2-4
2.2.2 Prepare your point source inventory for input into AirportProc 2-5
2.2.3 Determine whether you need to modify the ancillary input files for AirportProc 2-7
2.2.4 Prepare your batch file 2-7
2.2.5 Execute AirportProc 2-9
2.3 How do I know my run of AirportProc was successful? 2-9
2.3.1 Check your SAS® log file 2-9
2.3.2 Check your SAS® list file 2-9
2.3.3 Check other output files from AirportProc 2-9
CHAPTER 3 POINT SOURCE PROCESSING
THE DATA QUALITY ASSURANCE PROGRAM (PtDataProc) 3-1
3.1 What is the function of PtDataProc? 3-1
3.1.1 Quality assures point source location data 3-3
3.1.2 Quality assures stack parameters- defaults them where needed and for all
allocated aircraft emissions 3-9
3.1.3 Removes inventory variables and records not necessary for further processing
(inventory windowing) 3-10
3.2 How do I run PtDataProc? 3-11
3.2.1 Prepare your point source inventory for input into PtDataProc 3-11
3.2.2 Determine whether you need to modify the ancillary input files for PtDataProc 3-13
3.2.3 Prepare your batch file 3-14
3.2.4 Execute PtDataProc 3-17
3.3 How do I know my run of PtDataProc was successful? 3-17
3.3.1 Check your SAS® log file 3-17
3.3.2 Check your SAS® list file 3-18
3.3.3 Check other output files from PtDataProc 3-18
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TABLE OF CONTENTS
(continued)
CHAPTER 4 POINT SOURCE PROCESSING
THE ASPEN-SPECIFIC PROGRAM (PtAspenProc) 4-1
4.1 What is the function of PtAspenProc? 4-1
4.1.1 Selects pollutants, groups and/or partitions pollutants, and determines
their characteristics 4-3
4.1.2 Assigns urban/rural dispersion parameters 4-3
4.1.3 Assigns vent type and building parameters 4-4
4.2 How do I run PtAspenProc? ' 4-4
4.2.1 Prepare your point source inventory for input into PtAspenProc 4-4
4.2.2 Determine whether you need to modify the ancillary input files for PtAspenProc4-6
4.2.3 Modify the HAP table input files 4-7
4.2.4 Prepare your batch file 4-13
4.2.5 Execute PtAspenProc 4-14
4.3 How do I know my run of PtAspenProc was successful? 4-14
4.3.1 Check your SAS® log file 4-14
4.3.2 Check your SAS* list file 4-14
4.3.3 Check other output files from PtAspenProc 4-15
CHAPTER 5 POINT SOURCE PROCESSING
THE TEMPORAL ALLOCATION PROGRAM (PtTemporal) 5-1
5.1 What is the function of PtTemporal? 5-1
5.1.1 Assigns an hourly temporal profile to each emission record 5-3
5.1.2 Uses the hourly profiles to produce eight 3-hour emission rates for each record 5-3
5.2 How do I run PtTemporal? 5-4
5.2.1 Prepare your point source inventory for input into PtTemporal 5-4
5.2.2 Determine whether you need to modify the ancillary input files for PtTemporal 5-6
5.2.3 Modify the temporal allocation factor file (taffjiourly) 5-6
5.2.4 Modify the cross reference files used to link inventory records to the temporal
allocation factor file (scc2ams, sic2ams, and mact2scc) 5-7
5.2.5 Prepare your batch file 5-7
5.2.6 Execute PtTemporal 5-8
5.3 How do I know my run of PtTemporal was successful? 5-9
5.3.1 Check your SAS* log file 5-9
5.3.2 Check your SAS® list file 5-9
5.3.3 Check other output files from PtTemporal 5-9
11
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TABLE OF CONTENTS
(continued)
CHAPTER 6 POINT SOURCE PROCESSING
THE GROWTH AND CONTROL PROGRAM (PtGrowCntl) 6-1
6.1 What is the function of PtGrowCntl? 6-1
6.1.1 Assigns and applies growth factors to project emissions due to growth 6-3
6.1.2 Assigns and applies emission reduction information to emissions 6-3
6.2 How do I run PtGrowCntl? 6-8
6.2.1 Prepare your point source inventory for input into PtGrowCntl 6-8
6.2.2 Determine whether you need to modify the ancillary input files for PtGrowCntl6-10
6.2.3 Modify the growth factor input file (gfXX_YY.ssd01) 6-10
6.2.4 Modify the SCC to SIC cross-reference input file (ptscc2sic.txt) 6-11
6.2.5 Develop the emission reduction information files (MACT_gen.txt,
MACT_spec.txt, and SITE_spec.txt) 6-11
6.2.6 Prepare your batch file 6-12
6.2.7 Execute PtGrowCntl 6-15
6.3 How do I know my run of PtGrowCntl was successful? 6-15
6.3.1 Check your SAS® log file 6-15
6.3.2 Check your SAS® list file 6-15
6.3.3 Check other output files from PtGrowCntl 6-15
CHAPTER 7 POINT SOURCE PROCESSING
THE ASPEN FINAL FORMAT PROGRAM (PtFinalFormat) 7-1
7.1 What is the function of PtFinalFormat? 7-1
7.1.1 Assigns ASPEN source groups used in the ASPEN model output 7-3
7.1.2 Creates ASPEN input files, a column formatted text file and a SAS® file 7-4
7.2 How do I run PtFinalFormat? 7-5
7.2.1 Prepare your point source inventory for input into PtFinalFormat 7-5
7.2.2 Determine whether you need to modify the ancillary input files for
PtFinalFormat 7-7
7.2.3 Modify the ASPEN source group assignment files (mact_grp.txt, scc6_grp.txt,
and sic_grp.txt) 7-7
7.2.4 Prepare your batch file 7-8
7.2.5 Execute PtFinalFormat 7-10
7.3 How do I know my run of PtFinalFormat was successful? 7-10
7.3.1 Check your SAS® log file 7-10
7.3.2 Check your SAS® list file 7-10
7.3.3 Check other output files from PtFinalFormat 7-11
111
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TABLE OF CONTENTS
(continued)
CHAPTER 8 AREA SOURCE PROCESSING
THE AREA SOURCE AMPROC PREPARATION PROGRAM (AreaPrep) 8-1
8.1 What is the function of AreaPrep? ' " 8-1
8.1.1 Assigns a spatial surrogate for each area source category for subsequent spatial
allocation of county-level emissions to census tracts 8-3
8.1.2 Assigns a code to each source category for matching to temporal profiles .... 8-5
8.1.3 Creates inventory variables required by AMProc 8-5
8.2 How do I run AreaPrep? 8-5
8.2.1 Prepare your area source inventory for input into AreaPrep 8-5
8.2.2 Determine whether you need to modify the ancillary input files for AreaPrep .. 8-6
8.2.3 Modify the files that assign codes and spatial surrogates based on
MACT, SIC, SCC, and AMS codes 8-7
8.2.4 Prepare your batch file 8-8
8.2.5 Execute AreaPrep 8-9
8.3 How do I know my run of AreaPrep was successful? 8-9
8.3.1 Check your SAS® log file 8-9
8.3.2 Check your SAS® list file 8-9
8.3.3 Check other output files from AreaPrep 8-10
CHAPTER 9 MOBILE SOURCE PROCESSING
THE MOBILE SOURCE AMPROC PREPARATION PROGRAM (MobilePrep) 9-1
9.1 What is the function of MobilePrep? 9-1
9.1.1 Splits the mobile source inventory into onroad and nonroad inventories 9-3
9.1.2 Creates inventory variables required by AMProc 9-3
9.2 How do I run MobilePrep? 9-3
9.2.1 Prepare your mobile source inventory for input into MobilePrep 9-3
9.2.2 Determine whether you need to modify the ancillary input files for MobilePrep 9-4
9.2.3 Prepare your batch file 9-4
9.2.4 Execute MobilePrep 9-5
9.3 How do I know my run of MobilePrep was successful? 9-5
9.3.1 Check your SAS® log file 9-5
9.3.2 Check your SAS® list file 9-5
9.3.3 Check other output files from MobilePrep 9-6
IV
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TABLE OF CONTENTS
(continued)
CHAPTER 10 AREA AND MOBILE SOURCE PROCESSING
THE AREA AND MOBILE SOURCE PROCESSING PROGRAM (AMProc) 10-1
10.1 What is the function of AMProc? 10-1
10.1.1 Selects pollutants, groups and/or partitions pollutants, and assigns
their characteristics 10-3
10.1.2 Spatially allocates county-level emissions 10-3
10.1.3 Temporally allocates emissions 10-6
10.1.4 Determines ASPEN-specific modeling parameters 10-8
10.1.5 Assigns ASPEN source groups used in the ASPEN model output 10-8
10.1.6 Projects emissions to a future year 10-9
10.1.7 Creates ASPEN input files, column formatted text and SAS* files 10-13
10.2 How do I run AMProc? 10-14
10.2.1 Prepare your area and mobile source emission inventory files for
input into AMProc 10-14
10.2.2 Determine whether you need to modify the ancillary input files for AMProc 10-15
10.2.3 Modify the HAP table input file 10-17
10.2.4 Modify the file that assigns area and mobile source categories to
source groups 10-17
10.2.5 Modify the file that assigns spatial surrogates to mobile source
categories 10-18
10.2.6 Modify the temporal allocation factor file 10-18
10.2.7 Modify the growth factors and emission reduction information files 10-18
10.2.8 Prepare your batch file 10-19
10.2.9 Execute AMProc 10-21
10.3 How do I know my run of AMProc was successful? 10-21
10.3.1 Check your SAS® log file 10-21
10.3.2 Check your SAS® list file 10-21
10.3.3 Check other output files 10-24
REFERENCES R-l
APPENDIX A EMS-HAP Ancillary File Formats A-l
APPENDDC B EMS-HAP Sample Batch Files B-l
APPENDIX C 1996 NTI Point Source Preprocessor C-l
APPENDIX D Preparation of ASPEN-input Files for the 1996 Base Year Using EMS-HAP D-1
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LIST OF TABLES
Table 2-1. Variables Assigned to Point Source Aircraft Emissions 2-4
Table 2-2. Required Variables in AirportProc Input Mobile Source Inventory SAS* File ... 2-5
Table 2-3. Variables Required in AirportProc Input Point Source Inventory SAS® File 2-6 .
Table 2-4. Keywords in the AirportProc Batch File 2-8
Table 3-1. Assignment of LLPROB Diagnostic Flag Variable 3-4
Table 3-2. Resolutions in Discrepancy Between Alternate and Inventory FIPS 3-7
Table 3-3. Assignment of Diagnostic Flag Variables LFLAG and FIPFLAG 3-8
Table 3-4. Assignment of Stack Parameter Defaulting Diagnostic Flag Variables 3-10
Table 3-5. Variables Required for PtDataProc Input Point Source Inventory SAS® File ... 3-12
Table 3-6. Required Ancillary Input Files for PtDataProc 3-13
Table 3-7. Keywords for Selecting PtDataProc Functions 3-14
Table 3-8. Keywords in the PtDataProc Batch File 3-15
Table 3-9. Additional QA Files Created by PtDataProc 3-19
Table 4-1. Assignment of Vent Type Variable 4-4
Table 4-2. Variables in the PtAspenProc Input Point Source Inventory SAS® File 4-5
Table 4-3. Required Ancillary Input Files for PtAspenProc 4-6
Table 4-4. Structure of the HAP Table 4-8
Table 4-5. Sample Entries in a HAP Table 4-9
Table 4-6. Directions for Partitioning or Grouping of Inventory Species 4-11
Table 4-7. Using FACTOR Variable to Adjustment Emissions 4-12
Table 4-8. Keywords in the PtAspenProc Batch File 4-13
Table 5-1. Variables in the PtTemporal Input Point Source Inventory SAS® File 5-4
Table 5-2. Required Ancillary Input Files for PtTemporal 5-6
Table 5-3. Keywords in the PtTemporal Batch File 5-8
Table 6-1. Summary of Equations used to Calculate Projected Emissions 6-7
Table 6-2. Variables in the PtGrowCntl Input Point Source Inventory SAS* File 6-8
Table 6-3. Required Ancillary Input Files for PtGrowCntl 6-10
Table 6-4. Keywords for Selecting PtGrowCntl Functions 6-13
Table 6-5. Keywords in the PtGrowCntl Batch File 6-14
Table 7-1. Assignment of ASPEN Source Groups 7-3
Table 7-2. Variables in the PtFinalFormat Input Point Source Inventory SAS® File 7-5
Table 7-3. Required Ancillary Input Files for PtFinalFormat 7-7
Table 7-4. Keywords for Selecting PtFinalFormat Functions 7-8
Table 7-5. Keywords in the PtFinalFormat Batch File 7-9
Table 7-6. FinalFormat Output ASCII File Variables 7-12
VI
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LIST OF TABLES
(continued)
Table 8-1. Surrogates for Spatially Allocating Emissions from Counties to Census Tracts .. 8-4
Table 8-2. Variables Required in the AreaPrep Input Area Source Inventory SAS® File 8-6
Table 8-3. Ancillary Input Files for AreaPrep 8-7
Table 8-4. Keywords in AreaPrep Batch File 8-8
Table 9-1. Variables Required in the MobilePrep Input Mobile Source Inventory SAS® File 9-4
Table 9-2. Keywords in the MobilePrep Batch File 9-4
Table 10-1. Variables in the AMProc Input Area Source Inventory SAS® File 10-14
Table 10-2. Variables in the AMProc Input Mobile Source Inventory SAS* File 10-15
Table 10-3. Ancillary Files for the Area and Mobile Source Processor 10-16
Table 10-4. Keywords in the AMProc Batch File 10-19
Table 10-5. Format of AMProc ASCII Data File 10-25
Table 10-6. AMProc Core SAS® Output File Variables 10-26
Table 10-7. AMProc Extended SAS® Output File Variables .' 10-27
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LIST OF FIGURES
Figure 1-1. Overview of EMS-HAP Processing 1-3
Figure 2-1. AirportProc Flow Chart 2-2
Figure 3-1. PtDataProc Flow Chart 3-2
Figure 4-1. PtAspenProc Flow Chart 4-2
Figure 5-1. PtTemporal Flow Chart 5-2
Figure 6-1. PtGrowCntl Flow Chart 6-2
Figure 7-1. PtFinalFormat Flow Chart 7-2
Figure 8-1. AreaPrep Flow Chart 8-2
Figure 9-1. MobilePrep Flow Chart 9-2
Figure 10-1. Overview of Area and Mobile Source Emissions Processing (AMProc) 10-2
Figure 10-2. Area and Mobile Source Spatial Emissions Processing Flow Chart 10-5
Figure 10-3. Area and Mobile Source Temporal Emissions Processing Flow Chart 10-7
Figure 10-4. Area and Mobile Source Growth and Control Projection Flow Chart 10-10
via
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DEFINITION OF ACRONYMS
AIRS EPA's Aerometric Information Retrieval System
AMS AIRS Area and Mobile System source category code for area and mobile sources
of emissions
ASPEN Assessment System for Population Exposure Nationwide
CAS Chemical Abstract Service
EMS-HAP The Emission Modeling System for Hazardous Air Pollutants
EMS95 The Emissions Modeling System, 1995
EPA United States Environmental Protection Agency
HAP Hazardous Air Pollutant, as defined by Section 112 of the Clean Air Act
MACT Maximum Available Control Technology standards for HAP, established under
Section 112 of the Clean Air Act
NTI EPA's National Toxics Inventory
OAQPS EPA's Office of Air Quality Planning and Standards
ORD EPA's Office of Research and Development
OT AQ EP A's Office of Transportation and Air Quality
SAROAD Air pollution chemical species classification system used in EPA's initial data
base for "Storage and Retrieval of Aerometric Data"
SIC Standard Industrial Classification code used for Federal economic statistics
SCC AIRS Source Classification Code used for point sources of emissions
SAP Spatial Allocation Factor
TAP Temporal Allocation Factor
IX
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CHAPTER 1
Introduction
1.1 What is EMS-HAP?
The Emissions Modeling System for Hazardous Air Pollutants (EMS-HAP) is a series of
computer programs that process emission inventory data for subsequent air quality modeling.
EMS-HAP accomplishes two goals.
1. It processes an emission inventory, such as the 1996 National Toxics Inventory, for use in
the Assessment System for Population Exposure Nationwide (ASPEN) dispersion
model.1
2. It allows you to estimate future-year emissions data for use in the ASPEN dispersion
model.
To accomplish the first goal, EMS-HAP:
• quality assures point source inventory location and stack parameter data and defaults
missing or erroneous data where possible,
• groups and/or partitions individual pollutant species (e.g., groups lead oxide, lead nitrate
into a lead group; partitions lead chromate into lead and chromium groups),
• facilitates the selection of pollutants and pollutant groups for modeling,
• spatially allocates county-level area and mobile source emissions to the census tract level
using spatial surrogates such as population,
• allocates county-level aircraft emissions to airport locations,
• temporally allocates annual emission rates to annually averaged (i.e., same rate for every
day of the year) 3-hour emission rates based on the type of source, and,
• produces emission files formatted for direct input into the ASPEN model.
To accomplish the second goal, EMS-HAP projects base-year emissions to a future year,
accounting for growth and emission reductions resulting from emission reduction scenarios such
as the implementation of the Maximum Achievable Control Technology (MACT) standards.
The U.S. Environmental Protection Agency's Office of Air Quality Planning and Standards
(EPA/OAQPS), referred to hereafter as "we," developed EMS-HAP to facilitate multiple runs of
ASPEN and to analyze emission reduction scenarios. ASPEN can be used to estimate annual
average ambient air quality concentrations of multiple pollutants emitted from a large number of
sources at a large scale (i.e., nationwide) as part of a national air toxics assessment.1
Although we tailored EMS-HAP to process the 1996 National Toxics Inventory (NTI), you can
1-1
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use it for any emission inventory following the instructions in this guide. The 1996 NTI is the
first comprehensive model-ready national inventory of toxics, containing facility-specific
estimates of hazardous air pollutants (HAPs).2
While other emission models, such as EMS-953 and EPS 2.0,4 are available, they do not address .
the details of the 1996 NTI nor the input requirements of the ASPEN model.
1.2 What are the main features of EMS-HAP?
EMS-HAP is written in the SAS* programming language and is designed to run on any UNIX®
workstation. EMS-HAP can process three types of emission data: point source data where
emission sources are associated with specific geographic coordinates, area source data where
emission sources are reported at the county level, and mobile source data where emission sources
are also reported at the county level. EMS-HAP requires all emission inventory input data to be
SAS® formatted.
EMS-HAP consists of five point source programs, two area source programs, two mobile source
programs and one aircraft emissions program:
Point Source Programs
1. PtDataProc - The Data Quality Assurance Program, discussed in Chapter 3
2. PtAspenProc - The ASPEN-Specific Program, discussed hi Chapter 4
3. PtTemporal - The Temporal Allocation Program, discussed in Chapter 5
4. PtGrowCntl - The Growth and Control Program, discussed in Chapter 6
5. PtFinalFormat - The ASPEN Final Format Program, discussed in Chapter 7
Area Source Programs
1. AreaPrep - The Area Source AMProc Preparation Program, discussed in Chapter 8
2. AMProc - The Area and Mobile Source Processor, discussed in Chapter 10
Mobile Source Programs
1. MobilePrep - The Mobile Source AMProc Preparation Program, discussed hi Chapter 9
2. AMProc - The Area and Mobile Source Processor, discussed in Chapter 10
Aircraft Program
1. AirportProc - The Aircraft Emissions Processing Program, discussed in Chapter 2
Note that AMProc is used for both area and mobile source emissions processing.
Figure 1-1 provides a general overview of EMS-HAP processing. As you can see, the program
PtGrowCntl is optional, used only when you want to project the point source inventory to a
future year.
1-2.
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r
Point Source Emissions
File
I
Mobile Source Emissions
File
Area Source Emissions
File
PtTemporal
OR
PtGrowCntl
PtFinalFormat
AMProc (includes
optional projection
module)
AMProc (includes
optional projection
module)
Figure 1-1. Overview of EMS-HAP Processing
1-3
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In addition to the SAS® code for the different programs, EMS-HAP includes ancillary input files
in either SAS® or ASCII text format. An ancillary file is any data file you input to the program
other than your emission inventory. The SAS® ancillary files are those that you are not expected
to change when running EMS-HAP. For example, one SAS* ancillary file contains the radius of
each census tract. The text ancillary files are those that you may choose to change in order to
tailor the emission processing to your specific needs. As an example, the HAP table file (ASCII
text format) allows you to select the particular hazardous air pollutants (HAPs) to model. You
can model all of the HAPs in your inventory or any subset of HAPs by modifying this file.
1.3 How do I use this guide?
This guide describes the programs that comprise EMS-HAP, and gives instructions on how to
use them to create ASPEN emission input files for base year or projected year inventories of your
choice. This manual is not specific to any one input inventory. For example, you are not limited
to using the 1996 NTI to run EMS-HAP. You need only make sure your input inventory meets
the requirements described within each program.
We present the programs in the order you may choose to use them. Chapter 2 describes the
AirportProc program. Chapters 3 through 7 describe the point source processing programs.
Chapters 8 through 10 describe the programs for area and mobile source processing. Each
chapter describes the function of the program, how to run the program, all required ancillary
input files and emission inventory data requirements, and how to evaluate the output to
determine if the data were processed successfully. In this guide, all ancillary SAS® data files are
named without their extension, since SAS® data file extension names vary with system and
engine type. All programs are also named without their extension.
Appendix A presents the file formats of the ancillary input files. Appendix B contains sample
batch files for running the EMS-HAP programs. Appendix C discusses preparation of the point
source component of the 1996 NTI for input into EMS-HAP. Appendix D presents the
methodologies used to prepare emission input files for the ASPEN model for a national air toxics
assessment. Appendix D also discusses how we developed the key ancillary input files, such as
the spatial allocation factor files, provided with EMS-HAP. The ancillary files provided with
EMS-HAP are those we used to produce the 1996 ASPEN modeling inventory.
A separate user's guide is available for the ASPEN model.1 Users familiar with ASPEN model
input requirements will have a better understanding of EMS-HAP.
1-4
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CHAPTER 2
Aircraft Emissions Processing
The Aircraft Emissions Processing Program
(AirportProc)
AirportProc is the first program you run in EMS-HAP (see Figure 1-1). This program produces:
(1) a county-level mobile source file, and (2) a point source file containing aircraft emissions.
The mobile source file is an input to the mobile source processing programs (Chapters 9 and 10).
The point source file is an input to the point source processing programs (Chapters 3 through 7).
2.1 What is the function of AirportProc?
The Aircraft Emissions Processing Program (AirportProc) provides you with a means to model
aircraft emissions in ASPEN as point sources located at airports instead of spatially allocated
mobile sources. We built this capability because airport location data was readily available, and
we felt that modeling these emissions at airport locations as opposed to spatially allocating them
to census tracts would result in better ambient concentration estimates from the ASPEN model.
AirportProc performs the functions listed below:
• Allocates county-level aircraft emissions to specific airports
• Prepares allocated emissions for the point source processing programs
• Appends unallocated emissions back to the mobile source inventory
Figure 2-1 shows a flowchart of AirportProc. The following sections describe the above bullets.
2-1
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Batch File Containing Keywords
e.g. File Names and Locations,
Program Options
j Mobile Source Emissions File r
Reads Keywords
Reads Mobile Source Inventory and
Extracts Airport Emission Records
Allocates County-Level Airport Emissions
to Specific Locations within County
Appends Unallocated Airport Emission
Records to Mobile Source Inventory
File or Creates Separate File
(depending on program option)
Creates Variables Required for
Processing Airport Emissions as Point
Source Emissions through EMS-HAP
Point Source Inventory File
Appends Allocated Airport Emission
Records to Point Source Inventory File or
Creates Separate File (depending on
program option)
Figure 2-1. AirportProc Flowchart
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2.1.1 Allocates county-level aircraft emissions to specific airports
AirportProc first extracts aircraft emissions records from the mobile source inventory.
AirportProc currently extracts only those records that have the first six digits of the Area/Mobile
Source (AMS) code equal to either 227500 (airports, commercial) or 27.7505 (general aviation).
If your inventory's aircraft emissions have other AMS codes, you'll need to modify those codes
so that their first six digits are either 227500 or 227505 before you run AirportProc.
AirportProc then matches each aircraft emission record in the mobile source inventory to one or
more specific airports that are in the same county. To do this, AirportProc uses an ancillary
airport allocation SAS* file, apt_allc (see Section 2.2.3), containing data on airport locations and
allocation factors. AirportProc matches aircraft emissions to airport locations only based on the
county and not on the AMS code. Any different aircraft AMS codes within the same county will
thus be allocated to exactly the same airports. If a county has both commercial and
noncommercial airports, then emissions are only allocated to the commercial airports (even if the
AMS code begins with 227505). This is because commercial airports are assumed to have
general aviation as well as commercial activity. If multiple commercial airports are located in
the county, then emissions are divided among the commercial airports based on the relative
activity at the different airports in the county. If a county has multiple noncommercial airports,
then emissions are divided equally among the noncommercial airports.
2.1.2 Prepares allocated emissions for the point source processing programs
AirportProc creates the variables required by EMS-HAP to process the aircraft emission records
as point sources. Table 2-1 shows the list of variables AirportProc assigns along with the source
of the data or the value assigned. AirportProc also creates the MACTCODE, SIC, ZIP_CODE,
UTM_Z, CNTL_EFF and the stack parameter variables (described in Table 2-3) and sets their
values to missing. The point source processing programs require these variables to be present in
the input inventory SAS* data set.
The missing stack parameters for aircraft emissions will be defaulted by either SCC code, which,
in this case is the aircraft emissions AMS code, or by global defaults when you run the first point
source processing program, PtDataProc (Chapter 3). You choose which stack parameter default
technique to use (see Section 3.1.2). EMS-HAP assigns stack parameters to aircraft emissions
because the ASPEN model requires stack parameters for all point source emission records. Note
that assigning stack parameters to aircraft emissions is not inconsistent with ASPEN's treatment
of other mobile sources as pseudopoint sources (see ASPEN User's Guide1). Also, in
PtAspenProc (Chapter 4), aircraft emissions will be assigned a vent type of non-stacked, which
tells the ASPEN model not to perform plume rise calculations for these emissions.
After creating the necessary variables for allocated aircraft records, AirportProc then either
appends the records to the rest of the point source inventory or creates a separate file containing
the records. Having them in a separate file enables you to run aircraft point sources through the
point source programs separately from the non-aircraft point sources. You select the option to
use by specifying a value for keyword ADD2PT in the batch file (see Section 2.2.4, Table 2-4).
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Table 2-1. Variables Assigned to Point Source Aircraft Emissions
Variable
Name
Data Description
(units or values are in parentheses)
Source of Data or Value Assigned
ACT_ID code identifying a unique airport activity (same as
unique airport site)
COOR_ID code identifying a unique set of geographic
coordinates for the airport
EMIS pollutant emissions value (tons/year)
EMRELPID code identifying a unique combination of airport site
and airport AMS
EMRELPTY physical configuration code of release point
FIPS 5-digit FIPS code (state and county combined)
POLLCODE unique pollutant code
SCC EPA source category code identifying the process
SITE_ID code identifying a unique airport site
SRCJTYPE description of the emission source
X longitude (decimal degrees)
XYJTYPE type of coordinate system used (LAT/LON or UTM)
Y latitude (decimal degrees)
concatenation of' AP,' FIPS variable,
and number assigned consecutively to
each airport within county
same as ACT ID
mobile source inventory EMIS variable
concatenation of ACT_ID and mobile
source inventory AMS variable
'AP'
concatenation of mobile source
STATE and COUNTY variables
mobile source inventory CAS variable
mobile source inventory AMS variable
same as ACT_ID
'nonroad'
airport allocation file LON variable
'LATLON'
airport allocation file LAT variable
2.1.3 Appends unallocated emissions back to the mobile source inventory
If your inventory contains county-level aircraft emissions (i.e. AMS code equal to either 227500
or 227505) for a county that has no airports in the ancillary airport allocation file, you cannot
model these emissions as point sources. AirportProc identifies these records and then either
appends them back into the mobile source inventory, or puts them in a separate file. You select
which option you want by specifying a value for keyword ADD2MB in the batch file (see
Section 2.2.4, Table 2-4).
2.2 How do I run AirportProc?
2.2.1 Prepare your mobile source inventory for input into AirportProc
Your mobile source inventory must meet the following requirements:
It must be in SAS® file format.
To complete all mobile source programs in EMS-HAP, your data must contain, at
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a minimum, the variables listed in Table 2-2, with units and values as provided.
AirportProc retains any additional variables present for all records except aircraft
emissions, i.e., AMS codes beginning with 227500 or 227505.
• All data records should be uniquely identifiable by using the combination of the
state FIPS code (STATE), county FIPS code (COUNTY), AMS code (AMS), and
pollutant code (CAS).
• It shouldn't contain Alaska and Hawaii emission records because EMS-HAP
ancillary files currently don't cover these areas.
Table 2-2. Required Variables in AirportProc Input Mobile Source Inventory SAS® File
Variable Name
AMS
CAS
CAT_NAME
COUNTY
EMIS
POL_NAME
STATE
UNITS
Data Description
(Required units or values are in parentheses)
AMS 10-digit category code
unique pollutant code
mobile source emissions category name
county 3-digit FIPS code
emissions (tons/year)
pollutant name
state 2-digit FIPS code
emission units (tons/year)
Type*
A10
A10
A50
A3
N
A50
A2
A12
* Ax = character string of length x, N = numeric
2.2.2 Prepare your point source inventory for input into AirportProc
You need to prepare your point source inventory for input to AirportProc only if you choose to
append the allocated aircraft emissions to it; see keyword ADD2PT in Table 2-4 of Section 2.2.4.
If you don't choose to append the aircraft emissions to your point source inventory, you can skip
to Section 2.2.3.
Your point source inventory must meet the following requirements:
• It must be in SAS® file format.
• To complete all point source programs, your data must contain the variables in
Table 2-3 with units and values as provided. Additional variables can be present,
and will be included in the output inventory of AirportProc.
• All data records must be uniquely identifiable by using the combination of the
activity ID (ACT_ED), pollutant code (POLLCODE), and emission release point
ID (EMRELPID).
• All stack parameters within a group of records identified by the FIPS code (FIPS),
activity ID (ACT_E>), and emission release point ID (EMRELPID) must be the
same.
• It shouldn't contain Alaska and Hawaii emission records because EMS-HAP
ancillary files currently don't cover these areas.
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Table 2-3. Variables, Required in AirportProc Input Point Source Inventory SAS® File
Variable
Name
ACT_ID
CNTLJEFF"
COORJD
EMIS
EMRELPID
EMRELPTY
FIPS
MACTCODE
POLLCODE
sec
SIC
SITEJD
SRC_TYPE
STACKDIA
STACKHT
STACKVEL
STKTEMP
UTM_Z
X
XY_TYPE
Y
ZIP CODE
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process at a unique site
baseline control efficiency, expressed as a percentage
code identifying a unique set of geographic coordinates
pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01=fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck, 05=vertical
with rain cap, 06=downward-facing vent)
5-digit FIPS code (state and county combined)
process or site-level MACT code
unique pollutant code
EPA source category code identifying the process
Standard Industrial Classification (SIC) code for the site
code identifying a unique site
description of the emission source at the site ('nonroad' for aircraft emissions)
If you choose to define ASPEN source groups by this variable as explained in
7. 1 . 1 , or run PtGrowCntl (Chapter 6) then it must have the value of 'major' or
'area' for non-aircraft emissions.
diameter of stack (meters)
height of stack (meters)
velocity of exhaust gas stream (meters per second)
temperature of exhaust gas stream (Kelvin)
universal transverse mercator (UTM) zone
longitude (decimal degrees or degrees, minutes, seconds with no separating
characters) or UTM easting (meters or kilometers)
type of coordinate system used (LAT/LON or UTM)
latitude (decimal degrees or degrees, minutes, seconds with no separating
characters) or UTM northing (meters or kilometers)-
zip code of site
Type*
A25
N
A20
N
A50
A4
N
A7
A10
A10
A4
A20
A15
N
N
N
N
N
N
A7
N
A12
* Ax = character string of length x, N = numeric
" required only if you run the optional Growth and Control Program (Chapter 6)
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2.2.3 Determine whether you need to modify the ancillary input files for AirportProc
An ancillary file is any data file you input to the program other than your emission inventory.
AirportProc uses only one ancillary input file, apt_allc. This SAS* data file contains information
on each airport contained within a county, including its latitude and longitude and an allocation
factor. For commercial airports, the allocation factor is based on the relative activity of the
airport within the county. For noncommercial airports, the allocation factor equals 1 divided by
the number of noncommercial airports in the county. You don't need to modify this file unless
you obtain additional information concerning airport locations or relative airport activity. Figure
1 of Appendix A shows the format for this file, and Section D.4 (Appendix D) discusses how we
developed it.
2.2.4 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for AirportProc is shown in Figure 1 of
Appendix B.
Specify your keywords
Table 2-4 describes the keywords required in the batch file for AirportProc. Use keywords to
locate and name all input and output files. Use the keyword ADD2PT to select whether to
append the allocated aircraft emissions records to the input point source file. Use the keyword
ADD2MB to select whether to append the unallocated records to the output mobile source
inventory file.
You must include all directory names, file names, and variable values even if they are related to a
function that you do not select to perform. For example, if you set ADD2PT to 0, you still need
to assign a value to the keyword POINT. The value provided in this circumstance does not need
to represent an actual file; it is merely a place holder for the keyword.
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Table 2-4. Keywords in the AirportProc Batch file
Keyword
Description of Value
Inventory File Directories
POINT Point source inventory SAS* file directory
MOBILE Mobile source inventory SAS* file .directory -
Input Inventory Files
INPOINT Input point source inventory SAS* file name
INMOBIL Input mobile source inventory SAS* file name
Ancillary Files (Prefix of file name provided with EMS-HAP in parentheses)
REFDIR Reference file directory
AIRALLC Airport allocation SAS* file name (apt_allc)
Program Options
ADD2PT l=append the allocated aircraft emissions records to the input point source inventory
file (filename will be the value of the keyword OUTPOINT)
0=create an output file containing only the allocated aircraft emissions (filename
will be the value of the keyword OUTPOINT)
ADD2MB l=append the unallocated aircraft emissions records to the output mobile source
inventory file (filename will be the value of the keyword OUTMOBIL)
0=create an output file containing only the unallocated aircraft emissions (filename
will be the value of the keyword OUTMOBIL)
Output Inventory Files
OUTPOINT Output point source inventory SAS* file name
OUTMOBIL Output mobile source inventory SAS* file name
Prepare the execute statement
The last line in the batch file runs the AirportProc program. In the sample batch file provided in
Figure 1 of Appendix B, you will see a line preceding the run line that creates a copy of the
AirportProc code with a unique name. It is this version of the program that is then executed in
the last line. If you do this, the log and list files created by this run can be identified by this
unique name. If you don't do this and run the program under a general name, every run of
AirportProc will create a log and list file that will replace any existing files of the same name.
You may find that you need to assign a special area on your hard disk to use as work space when
running AirportProc. In the sample batch file, a work directory is defined on the last line
following the execution of AirportProc. For example, the command
'sas AirportProc_032800.sas -work /data/workl5/dyl/' assigns a work directory called
"/data/work 15/dyl". The directory you reference must be created prior to running the program.
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2.2.5 Execute A irportProc
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x AirportProc.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'AirportProc.bat'.
2.3 How do I know my run of AirportProc was successful?
2.3.7 Check your S AS® log file
Review the output log file to check for errors or other flags indicating incorrect processing. To
do this, search the log file for occurrences of the strings "error", "warning", "not found", and
"uninitialized". These can indicate problems with input files or other errors.
You can also look at the number of records in the input mobile and point source inventory files
and compare it to the number of records in the output mobile and point source inventory files.
You should be able to account for the number of records in each file according the manner in
which you chose to execute AirportProc (i.e., values assigned to ADD2PT and ADD2MB).
23.2 Check your S AS® list file
The list file created when AirportProc is executed contains information to assist in quality
assurance. The information in this file is listed below:
• First 100 allocated airport sites
• Pollutant-level and state-level emissions totals and record counts of allocated
aircraft emissions
• Emissions total and record count of output point source inventory file
• County-level and AMS code-level emissions totals and record counts of
unallocated aircraft emissions
• Emissions total and record count of output mobile source inventory file
2.3.3 Check other output files front AirportProc
You should check for the existence of both the output point and mobile source inventory files,
named by keywords OUTPOINT and OUTMOBIL, respectively. These files will serve as the
inputs to the next point (PtDataProc, Chapter 3) and mobile (MobilePrep, Chapter 9) source
processing programs you run. No other files are created by AirportProc.
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CHAPTER 3
Point Source Processing
The Data Quality Assurance Program (PtDataProc)
PtDataProc is the first program used in EMS-HAP for the processing of a point source inventory,
unless you ran the Aircraft Emissions Processing Program, AirportProc (see Figure 1-1) using a
point source inventory input file. The output point source emission inventory from PtDataProc is
used as the input to PtAspenProc.
3.1 What is the function of PtDataProc?
The Data Quality Assurance Program (PtDataProc) prepares the point source emission inventory
for modeling by assuring that each record contains valid latitude and longitude coordinates and
reasonable stack parameters. You control which of the three functions listed below are
performed in any given execution of PtDataProc (Table 3-7 in Section 3.2.3 details how to do
this).
• Quality assures point source location data
• Quality assures stack parameters- defaults them where needed and for all allocated
aircraft emissions
• Removes inventory variables and records not necessary for further processing
(inventory windowing)
Figure 3-1 shows a flowchart of PtDataProc. The following sections describe the above bullets.
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Batch File Containing Keywords
e.g. File Names and Locations,
Program Options
Point Source Inventory File
Zip Code File
County File
State File
County Polygon File
County Map File
County Data File
Random Tract List File
Tract Information File
SCC-based Default Stack [_
Parameter File i
SIC-based Default Stack
Parameter File
Variable List File
Records with Zero
Emissions
Records with Missing
Coordinate "
Output Point Source
Inventory File
Reads Keywords
PtDataProc: MACRO LOCATE
Reads point source inventory file. Determines
location in latitude and longitude coordinates.
Attempts to determine default location for
records without sufficient location information.
Determines state and county FIPS from
coordinates and attempts to resolve any
discrepancies between inventory FIPS and
coordinate-based FIPS.
J
Records without Location Data
-'"-
Recoras with Unresolved FIPS
PtDataProc: MACRO STACK
Defaults missing or out-of-range stack
parameters using SCC-based, SIC-based, or
global defaults, depending on program options
PtDataProc: MACRO SETVAR
Removes all variables not essential for further
EMS-HAP processing except any variables
specified within the variable list file (varlist.txt)
PtDataProc: MACRO WINDDATA
Removes all records with zero emissions values
and all records with missing latitude and
longitude coordinates
Figure 3-1. PtDataProc Flowchart
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3.1.1 Quality assures point source location data
PtDataProc calculates latitude and longitude coordinates in decimal degrees. For sites without
valid location information, PtDataProc assigns default locations if possible; sites are dropped
from the emission inventory when PtDataProc is unable to assign a default location. PtDataProc
considers location information invalid if it is missing, out of range, or if there is an inconsistency
between the state and county FIPS code and the geographic coordinates.
PtDataProc invokes two SAS® programs (known as "include" programs) to carry out specific
steps involved in this quality assurance function: 1) validFIP checks the validity of the FIPS code
in the emission inventory; 2) Iatlon2fip computes FIPS codes based on the inventory geographic
coordinates. You need to specify these names and the locations of these programs in your batch
file (see keywords VALIDFIP and FINDFIPS in the "Program Files" section of Table 3-8).
The following sections detail how PtDataProc quality assures the point source inventory location
data, and the diagnostics it produces.
Calculation of latitude and longitude coordinates
Some records in the point source inventory may have their geographical coordinates expressed in
the latitude longitude coordinate system (XY_TYPE='LATLON') and other records may have
the Universal Transverse Mercator (UTM) coordinate system (XY_TYPE='UTM'). PtDataProc
calculates latitude and longitude in decimal degrees based on the value of the XY_TYPE variable
and the values of the X, Y, and UTM_Z variables. The X and Y values for UTM coordinates can
be expressed in meters or kilometers, and the values for latitude and longitude coordinates can be
expressed in decimal degrees or in degrees-minutes-seconds format (excluding decimal point or
any other separating characters).
PtDataProc performs limited quality assurance checks on the values of the location data
(variables X, Y and UTM_Z). Depending on the evaluation of the location data, action is taken
to handle the data in a specific way or to correct the data. To assist you in identifying how the
data was evaluated, PtDataProc sets the value of the diagnostic flag variable LLPROB
accordingly. Table 3-1 presents the location data evaluation, what action is taken, if any, and
what value is assigned to the LLPROB variable. You can use the value of LLPROB to see if
problems exist in your inventory. Section 3.1.3 explains how you can reduce the number of
variables in your inventory through the windowing function, but still retain LLPROB, and any
other variables that are not essential for EMS-HAP processing.
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Table 3-1. Assignment of LLPROB Diagnostic Flag Variable
Location Data Evaluation
Correction Made to Location Data
Value Assigned to
LLPROB variable
X or Y is missing or zero, or, XYJTYPE = None; defaulting will be attempted
'UTM' and UTM_Z value is missing or zero
LAT and LON, as calculated from X, Y and
XY_TYPE variables are outside of an area
including the contiguous U.S., Puerto Rico,
and U.S. Virgin Islands.
UTM_Z is not missing or not zero;
XY_TYPE is not equal to 'UTM' or
'LATLON'
XY_TYPE='UTM' or location data is
assumed to represent UTM coordinates and
X value is greater than Y value
XY_TYPE='UTM' or location data is
assumed to represent UTM coordinates, and
Y value is greater than 10,000 and,
therefore, it must be measured in meters
Location data is to assumed represent
UTM coordinates
X and Y values are exchanged
X and Y values are used as they are
and are not converted from kilometers
to meters
UTM_Z is missing or zero; XY_TYPE is not Location data is assumed to represent
equal to 'UTM' or 'LATLON' lat/lon coordinates
XY_TYPE='LATLON' or location data is
assumed to represent lat/lon coordinates, and
X or Y value is less than zero
XY_TYPE='LATLON' or location data is
assumed to represent lat/lon coordinates, and
Y value is greater than the X value
Change sign of X or Y value
X and Y values are exchanged
XY_TYPE='LATLON' or location data is X and Y values are used as they are
assumed to represent lat/lon coordinates, and and are not converted from degrees,
X and Y values are not in degrees, minutes, minutes, seconds notation to decimal
seconds notation degrees
missing
None; defaulting will be attempted bad_loc
UTM
flipxy
meters
LATLON
negative
flipll
decimal
Defaulting of missing or out-of-range coordinates
If the location data provided on a record is incomplete or out-of-range (LLPROB='missing' or
LLPROB='bad_loc'), PtDataProc defaults the latitude and longitude based on the zip code or, if
no zip code is provided, on the state and county FIPS code of the facility. PtDataProc considers
the location out-of-range if the calculated latitude and longitude are outside of an area including
the contiguous U.S., Puerto Rico, and U.S. Virgin Islands. The default location based on the zip
code is the centroid latitude and longitude of the zip code area. If the record being defaulted to
the zip code centroid doesn't have a valid FIPS, PtDataProc changes it to the FIPS represented
by the zip code location. (Note that this will occur as long as the inventory state FIPS, if valid, is
not inconsistent with the state FIPS determined by the zip code.)
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The default location based on the state and county FTPS code is the centroid latitude and
longitude of a census tract within the county. PtDataProc selects the census tract from a list (or
array) of census tracts contained in the trctarry ancillary file. This file provides a random
ordering of the census tracts within each county. For each unique location within a county that
needs a default value, PtDataProc runs through the census tract list in the order of the tractarry
file, assigning a tract centroid location from the list. For example, if five locations need to be
defaulted in a particular county, the first location will be defaulted to the first tract centroid that's
within the county from the list. The second location will be defaulted to the second tract centroid
on the list for that county, and so on. If there are more coordinates that need defaulting than
tracts in that county, PtDataProc will go back to the beginning of the census tract list for that
county (following the same order) until all locations have been defaulted. The census tract
defaulting methodology ensures that if there are multiple point source locations that need to be
defaulted within the same county, they are assigned to as many different tract centroids within
the county as possible.
PtDataProc records which basis was used to default a location by setting the value of the
diagnostic flag variable LFLAG to either 'zipcode' or 'county'. When defaulting by zip code, if
PtDataProc changes the inventory FIPS to the zip code FIPS, it also sets the value of the
diagnostic flag variable FIPFLAG to 'assigned'. Note that this occurs only if PtDataProc
determines that the inventory FIPS code is invalid. You can use the values of these diagnostic
flag variables to check which point sources were defaulted, and the method PtDataProc used.
Section 3.1.3 explains how you can reduce the number of variables in your inventory through the
windowing function, but still retain LFLAG and FIPFLAG, and any other variables that are not
essential for EMS-HAP processing.
As stated earlier, the default location based on the state and county FIPS code is the centroid of a
census tract within the county. Census tracts with radius less than equal to 0.5 km are excluded
from the list of census tracts contained in the trctarry ancillary file. That is, no locations are
defaulted to tracts with radius less than or equal to 0.5 km. We chose 0.5 km to prevent the
ASPEN model from calculating excessively high concentrations for these small census tracts
(resulting from ASPEN's spatial averaging approach) which are not likely to be real values.
Also note that if you run EMS-HAP multiple times using different inventories (e.g., if you
remove certain facilities or subset different pollutants to run) the PtDataProc census tract
defaulting technique may result in different census tract locations for the same facilities you
defaulted in a previous run.
If the state or county FIPS is invalid, and PtDataProc can't determine a default location by the
zip code, the record is written to both a text file (nolocate.txt) and a SAS® data set (nolocate) and
is dropped from further processing (i.e., the record will not be modeled in ASPEN).
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Resolution of discrepancies between coordinates and FIPS location data
For some sources, there may be a discrepancy in the location information due to errors in the
inventory. For example, the latitude and longitude may indicate that the source is located in New
York, but the FIPS indicates Michigan. PtDataProc addresses this situation by:
1. Calculating a latitude/longitude coordinate-based FIPS, referred to hereafter as the
"alternate FIPS," for each unique set of geographic coordinates in the inventory.
2. Determining whether the alternate FIPS matches the inventory FIPS
3. Resolving the discrepancy when the alternate FIPS does not match the inventory FIPS
PtDataProc resolves discrepancies between coordinates and FIPS location data using three
approaches:
1. Distance Criterion: PtDataProc computes the distance between the geographical
coordinates and the centroid of the county based on the inventory FIPS. If this distance is
less than 5.4 times the county radius, PtDataProc then presumes that the geographical
coordinates can possibly be within the county and thus takes no action. We chose the value
of 5.4 as a potential worst case. For Monroe County Florida (the county that comprises the
Florida Keys) the distance between the farthest point in the county and its centroid is
approximately 5.4 times the county radius. This large value will ensure that PtDataProc will
not move coordinates that could potentially be within the county represented by the inventory
FIPS.
2. Zip Code Check: If the distance criterion in step 1 is not met, then PtDataProc uses
inventory zip code information if available, to resolve the discrepancy. If the FIPS based on
the zip code (zip code FIPS) matches the alternate FIPS, then PtDataProc changes the
inventory FIPS to the alternate FIPS. If the zip code FIPS matches the inventory FIPS, then
PtDataProc changes the geographical coordinates to the centroid of the zip code area.
3. FIPS validations: If steps 1 and 2 do not resolve the problem, then PtDataProc conducts a
series of additional checks. Depending on the validity of the inventory and alternate FIPS,
PtDataProc will do one of the following: change the inventory FEPS, change the
geographical coordinates, or drop the emissions record from further consideration. Table 3-2
contains the details.
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Table 3-2. Resolutions in Discrepancy Between Alternate and Inventory FIPS
Resolution
Occurs when the Distance Criterion and Zip Code
check do not Resolve the Discrepancy, AND when....
Default geographical coordinates to
the county-level default, i.e., the
centroid of a selected tract in the
county represented by the inventory
FIPS
Default inventory FIPS to the
alternate FIPS
The inventory contains a valid state/county FIPS.
Drop emission record from further
processing (this record will not be
modeled in ASPEN)
1. The county inventory FIPS is invalid and the alternate FIPS
is in the same state as the inventory FIPS, or
2. The state inventory FIPS is invalid and the alternate FIPS is
in the same state as represented by the postal code (1st two
digits of the ACTJD), or
3. The state inventory FIPS is invalid and the record doesn't
have a valid postal code (e.g., the 1" two digits of the ACT_ID
="ES")
1. The county inventory FIPS is invalid and the alternate FIPS
is not in the same state as the inventory FIPS, or
2. The state inventory FIPS is invalid and the alternate FIPS is
not in the same state as represented by the postal code (lsl two
digits of the ACTJD), or
3. Both the inventory FIPS and alternate FIPS are invalid
Records dropped from the inventory because the discrepancy could not be resolved are written to
both a text file (nomodel.txt) and a SAS® data set (nomodel).
PtDataProc uses the same diagnostic flag variables for location discrepancies as are used when
missing locations are defaulted. These variables are LFLAG and FIPFLAG. PtDataProc assigns
their values based on the action taken to resolve the discrepancy. Table 3-3 presents all possible
values assigned to these variables and their circumstances. Note that every combination of
LFLAG and FIPFLAG is unique to a particular situation. For example, if LFLAG='county' and
FIPFLAG='noch_ss' then the problem is a location discrepancy. PtDataProc resolved it by
defaulting the geographic coordinates based on the state and county FIPS (i.e., using the census
tract routine described above). The inventory FIPS, which represented the same state as the
geographic coordinates, was not changed.
You can use these diagnostic flag variables to check the problems that may exist in your
inventory, and how PtDataProc handled them. Section 3.1.3 explains how you can reduce the
number of variables in your inventory through the windowing function, but still retain LFLAG
and FIPFLAG, and any other variables that are not essential for EMS-HAP processing.
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Table 3-3. Assignment of Diagnostic Flag Variables LFLAG and FIPFLAG
Location Data Evaluation Values Assigned to Flag Variables
Geographic coordinates defaulted based on county (i.e., census
tract routine) due to invalid coordinates (LLPROB has value of
'missing' or 'bad_loc')
LFLAG = 'county' AND
FIPFLAG is not assigned a value
Geographic coordinates defaulted by zip code due to invalid
coordinates (LLPROB has value of 'missing' or 'bad_loc')
and the inventory FIPS and zip code FIPS agree
LFLAG = 'zipcode' AND
FIPFLAG is not assigned a value
Geographic coordinates defaulted by zip code due to invalid
coordinates (LLPROB has value of 'missing' or 'bad_loc') and
inventory FIPS is reassigned to the zip code FIPS. Note: this
happens when the inventory FIPS is invalid and either (1) the
state inventory FIPS is the same as the state zip code FIPS or
(2) the postal code from the address represents the same state as
the state zip code FIPS.
LFLAG = 'zipcode' AND
FIPFLAG = 'assigned'
Geographic coordinates defaulted based on county to resolve
disagreement between inventory FIPS and alternate FIPS
(LLPROB does not have value of 'missing' or 'bad_loc')
LFLAG = 'county' AND
FIPFLAG = 'noch_ss', when inventory FIPS
and alternate FIPS represent the same state;
FIPFLAG = 'noch_ds', when inventory FIPS
and alternate FIPS represent different states
Geographic coordinates defaulted by zip code to- resolve
disagreement between inventory FIPS and alternate FIPS
(LLPROB variable does not have value of 'missing' or
'bad_loc')
LFLAG = 'zipcode' AND
FIPFLAG = 'noch_ss', when inventory FIPS
and alternate FIPS represent the same state;
FIPFLAG ='noch_ds', when inventory FIPS
and alternate FIPS represent different states
Inventory FIPS disagrees with alternate FIPS, but the distance
criterion is met so no change is made to either FIPS or lat/lon.
(This would likely occur when point source is near a state or
county border.)
LFLAG is not assigned a value AND
FIPFLAG = 'noch_ss', when inventory FIPS
and alternate FIPS represent the same state;
FIPFLAG = 'noch_ds', when inventory FIPS
and alternate FIPS represent different states
Inventory FIPS disagrees with alternate FIPS, and is reassigned
to the zip code FIPS
LFLAG is not assigned a value AND
FIPFLAG = 'ZIP_ss', when inventory FIPS
and alternate FIPS represent the same state;
FIPFLAG = 'ZIP_ds', when inventory FIPS
and alternate FIPS represent different states
Inventory FIPS disagrees with alternate FIPS, and is reassigned
to the alternate FIPS
LFLAG is not assigned a value AND
FIPFLAG = 'reloc_ss', when inventory FIPS
and alternate FIPS represent the same state;
FIPFLAG = 'reloc_ds', when inventory FIPS
and alternate FIPS represent different states
Discrepancy between Inventory FIPS and alternate FIPS cannot
be resolved
LFLAG is not assigned a value AND
FIPFLAG = 'no model'
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3.1.2 Quality assures stack parameters- defaults them where needed and for all allocated
aircraft emissions
PtDataProc checks each record for valid stack parameters and provides defaults to missing or
erroneous data. PtDataProc determines if a non-missing stack parameter should be defaulted by
comparing it to the minium and maximum range values you provide for each parameter.
Because AirportProc (Chapter 2) sets the stack parameters for allocated aircraft emissions to
missing, PtDataProc will default stack parameters for these emission records. PtDataProc
defaults missing aircraft emission stack parameters the same way it defaults all other missing
stack parameters as described below.
Stack parameter values that fall outside of the range or are missing can be defaulted in several
ways. You can have PtDataProc assign default stack parameters using the 8-digit AIRS Source
Classification Code (SCC)-based and/or 4-digit Standard Industrial Classification (SlC)-based
defaults. You choose which defaulting technique PtDataProc uses and supply information on the
valid parameter ranges and global defaults to be used through the key words you enter in the
batch file (see Tables 3-7 and 3-8 in Section 3.2.3). If you choose either SCC-based or SIC-
based defaults, PtDataProc uses ancillary SCC or SIC default files. If you choose both SCC-
based and SIC-based defaults, and an inventory record can be matched to values in both the SCC
and SIC default files, the program will use the SCC-based default over the SIC-based one.
Some stack parameters may not be addressed by either of these methods (e.g., if an inventory
record has no SCC nor SIC) or, you may choose not to use these options. In these cases,
PtDataProc uses the following "global" defaulting routine: (1) If the stack parameters are
missing, PtDataProc will default them to the global stack parameters you choose, (2) If the stack
parameters are outside of the valid range you provide, PtDataProc will use either the minimum or
maximum range value as the default. The one exception to this global defaulting routine is for
horizontal stacks or fugitives (EMRELPTY = '03' or '01'). If the stack parameters are missing or
zero for these, PtDataProc uses the following defaults: stack height of 5 meters, stack diameter of
1 meter, stack temperature of 295 K and stack velocity of 0.5 meters/second.
Diagnostic flag variables, set for each stack parameter (HTFLAG, DIAFLAG, VELFLAG, and
TEMPFLAG), explain why and how each stack parameter was assigned a default value; these are
summarized in Table 3-4. Section 3.1.3 explains how you can reduce the number of variables in
your inventory through the windowing function, but still retain these diagnostic variables, and
any other variables that are not essential for EMS-HAP processing.
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Table 3-4. Assignment of Stack Parameter Defaulting Diagnostic Flag Variables
Default Evaluation of Invalid Stack
Method Parameter
Default Value Value Assigned to Diagnostic Flag
Assigned Variables Htflag, Diaflag, Velflag,
and Tempflag
sec
Parameter is not missing, but is outside
of valid parameter range
Parameter is missing
SIC
Parameter is not missing, but is outside
of valid parameter range
Parameter is missing
Neither SCC nor SIC
Parameter is missing
Parameter is not missing, but is less
than the minimum range value
Parameter is not missing, but is greater
than the maximum range value
SCC based
default
SCC based
default
SIC based
default
SIC based
default
Global default
Minimum
range value
Maximum
range value
Concatenation of the value of
DEFFLAG variable* included in SCC
default file and 'out'
Concatenation of the value of
DEFFLAG variable* included in SCC
default file and 'miss'
Concatenation of the value of
DEFFLAG variable* included in SIC
default file and 'out'
Concatenation of the value of
DEFFLAG variable* included in SIC
default file and 'miss'
'default'
'rangelow'
'rangehi'
* the DEFFLAG variable indicates the method used to obtain the default value. It is described in more detail
Figures 10 and 11 of Appendix A
3.1.3 Removes inventory variables and records not necessary for further processing
(inventory windowing)
Because point source inventories can be very large, it is useful for further processing of the data
through EMS-HAP to reduce the size of the inventory file as much as possible. The PtDataProc
program allows you to do this in two ways: (1) by removing nonessential variables from your
inventory and (2) by removing nonessential records from your inventory.
Removal of Nonessential Variables
You can choose to have PtDataProc remove all variables except for those required for further
processing within EMS-HAP. To do this, set the value of the DOSETVAR keyword to 1 in your
batch file (see Table 3-7 in Section 3.2.3). You also have the option of providing PtDataProc
with a list of additional variables (e.g., LLPROB, LFLAG, FIPFLAG) to be retained. To do this,
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set the DOSETVAR and USELIST keywords in your batch file to 1, and provide a list of
nonessential variables in an ancillary text file (see the varlist.txt file in Table 3-6).
Removal of Nonessential Records
You can choose to have PtDataProc remove all records that have no latitude/longitude data or
that have zero emissions. To do this, set the value of the DOWINDOW keyword in your batch
file to 1. Note that if you choose to have PtDataProc perform the location data quality assurance
function, windowing the inventory to remove records without latitude and longitude data would
not be necessary, because these records would have already been removed. You would still,
however, need to perform the windowing function if you want to remove records with zero
emissions.
3.2 How do I run PtDataProc?
3.2.1 Prepare your point source inventory for input into PtDataProc
Your point source inventory must meet the following requirements:
• It must be in SAS® file format.
• To complete all point source programs, your data must contain the variables in Table 3-5
with units and values as provided. Additional variables can be present, and will be
included in the output SAS® file. However, you can choose to create an output file with
only those variables needed in subsequent EMS-HAP processing programs by choosing
the windowing function which was discussed in Section 3.1.3.
• All data records must be uniquely identifiable by using the combination of the activity ID
(ACT_ID), pollutant code (POLLCODE), and emission release point ID (EMRELPID).
• All stack parameters within a group of records identified by the FIPS code (FIPS),
activity ID (ACT_ID), and emission release point ID (EMRELPID) must be the same.
• It shouldn't contain Alaska and Hawaii emission records because EMS-HAP ancillary
files currently don't cover these areas.
Your inventory will meet all requirements if it is the output of the AirportProc program. See
Appendix C for a description of the preprocessing programs we developed to create a point
source inventory for input into PtDataProc from the 1996 NTI modeling files.
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Table 3-5. Variables Required for PtDataProc Input Point Source Inventory SAS® File
(Variables used by PtDataProc are in bold; Other variables listed are used by subsequent point source processing programs)
Variable Name
ACT_ID
CNTL_EFFa
COORJD
EMIS
EMRELPID
EMRELPTY
FIPS
MACTCODE
POLLCODE
sec"
SIC
SITEJD
SRCJTYPE
STACKDIA
STACKHT
STACKVEL
STKTEMP
UTM_Z
X
XY_TYPE
Y
ZIP CODE
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process at a unique site
baseline control efficiency, expressed as a percentage
code identifying a unique set of geographic coordinates
pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01=fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck, 05=vertical
with rain cap, 06=downward-facing vent, AP=aircraft)
5-digit FIPS code (state and county combined)
process or site-level MACT code
unique pollutant code
EPA source category code identifying the process
Standard Industrial Classification (SIC) code for the site
code identifying a unique site
description of the emission source at the site ('nonroad' for aircraft emissions)
If you choose to define ASPEN source groups by this variable as explained in
7.1.1, or run PtGrowCntl (Chapter 6) then it must have the value of 'major' or
'area' for non-aircraft emissions.
diameter of stack (meters)
height of stack (meters)
velocity of exhaust gas stream (meters per second)
temperature of exhaust gas stream (Kelvin)
universal transverse mercator (UTM) zone
longitude (decimal degrees or degrees, minutes, seconds with no separating
characters) or UTM easting (meters or kilometers)
type of coordinate system used (LAT/LON or UTM)
latitude (decimal degrees or degrees, minutes, seconds with no separating
characters) or UTM northing (meters or kilometers)
zip code of site
Type*
A25
N
A20
N
A50
A4
A5
A7
A10
A10
A4
A20
A15
N
N
N
N
N
N
A7
N
A12
* Ax = character string of length x, N = numeric
' required only if you use the optional growth and control program (Chapter 6)
* used by PtDataProc only if you choose to use SCC-based defaults for missing/out-of-range stack parameters
c used by PtDataProc only if you choose to use SIC-based defaults for missing/out-of-range stack parameters
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5.2.2 Determine whether you need to modify the ancillary input files for PtDataProc
An ancillary file is any data file you input to the program other than your emission inventory.
Table 3-6 lists the ancillary input files for PtDataProc. Of the eleven different ancillary files
required to run PtDataProc, there are only three files that you may need to modify. The other
ancillary files contain standard reference data.
If you choose to have the program default the stack parameters by SCC or by SIC, you may want
to modify the def_scc.txt or def_sic.txt files, respectively (file formats are provided in Appendix
A, Figures 10 and 11). If you choose to have the program remove non-essential variables from
your inventory, you may want to modify the varlist.txt file in order to retain additional non-
essential variables of your choosing (see Appendix A, Figure 12 for file format).
Table 3-6. Required Ancillary Input Files for PtDataProc
Name of File
Provided with
EMS-HAP
zipcodes
cty_cntr
st cntr
counties
bound6
cntyctr2
trctarry
tractinf
def scc.txt
Purpose
Assigns default location coordinates by zip code
Determines validity of state and county FIPS
Determines state FIPS from postal code
Determines state and county FIPS from geographic
coordinates
Determines state and county FIPS from geographic
coordinates
Determines state and county FIPS from geographic
coordinates
Assigns random census tract by county for purpose of
assigning default location coordinates
Provides census tract centroid coordinates for default
location coordinates
Assigns default stack parameters by SCC if you choose
Need to Modify?
No
No
No
No
No
No
No
No
If you choose to
Format
SAS*
SAS*
SAS*
SAS*
SAS*
SAS*
SAS*
SAS*
text
def sic.txt
this option
Assigns default stack parameters by SIC if you choose
this option
default stack
parameters by SCC
If you choose to
default stack
parameters by SIC
text
varlist.txt
Provide list of non-essential variables to be retained in
inventory if you choose this option
If you choose to
retain additional
variables on the
inventory
text
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3.2.3 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for PtDataProc is shown in Figure 2 of
Appendix B.
Specify your keywords
Table 3-7 shows you how to specify keywords to select which functions you want PtDataProc to
perform. For example, if you've already calculated your latitude and longitudes in decimal
degrees and quality assured them, you may choose not to use this function. For this situation, set
the keyword "DOLOCATE" to zero.
Table 3-7. Keywords for Selecting PtDataProc Functions
PtDataProc Function
Keyword (values provided
cause function to be perfomed)
Quality assurance of location data
Quality assurance of stack parameters and defaulting of aircraft emission
stack parameters
Use SCC based defaults; use global defaults or range defaults if
parameters are still missing or out-of-range after SCC default process
Use SIC based defaults; use global defaults or range defaults if
parameters are still missing or out-of-range after SIC default process
Use both SIC and SCC based defaults; use global defaults or range
defaults if parameters are still missing or out-of-range (Note: when
single record can be defaulted by both SIC and SCC-based defaults,
PtDataProc will use the SCC default)
Use only global defaults (range defaults if parameters are out of range)
Window Inventory to reduce variable list
Specify additional variables to retain on output inventory file
Don't retain any non-essential variables on output inventory file
Window Inventory to exclude zero emissions and unlocated records
DOLOCATE = 1
DOSTACK=1
SCCDEFLT = 1; SICDEFLT = 0
SCCDEFLT = 0; SICDEFLT = 1
SCCDEFLT = 1; SICDEFLT = 1
SICDEFLT = 0; SCCDEFLT = 0
DOSETVAR = 1
USELIST = 1
USELIST = 0
DOWTNDOW=1
Table 3-8 describes all of the keywords required in the batch file. PtDataProc is the only EMS-
HAP program that uses "include" programs within the actual program. You specify the name of
these programs in the batch file (in the "Program Files" section). You must put the three
ancillary files used by 'Iatlon2fip.inc' in the directory named by keyword MAP_DIR, and they
must have the same names as the files we supplied to you (bound6, counties and cntyctr2). Note
the sections called "Valid Stack Parameter Ranges" and "Global Stack Parameters." You supply
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the values for stack parameter ranges used to determine if a stack parameter is valid. PtDataProc
will use the upper or lower bounds of the range as a "range default" if parameters are not
defaulted using SCC and/or SIC based defaults. You also supply values for global default stack
parameters for missing stack parameters not defaulted by the other methods.
Table 3-8. Keywords in the PtDataProc Batch File
Keyword
Description pf Value
Input Inventory Files
INJDATA Input SAS* file directory
INSAS Input inventory SAS* file name
Program Files (Prefix of file name provided with EMS-HAP in parentheses)
INC_DIR Include program directory
VALIDFIP Include program file name to determine validity of county FIPS code (validFIP)
FINDFIPS Include program file name to determine county FIPS based on latitude and
longitude (Iatlon2fip)
Ancillary Files (Prefix of file name provided with EMS-HAP in parentheses)
REFFILE Ancillary SAS* file directory
REFTEXT Ancillary text file directory
MAP_DIR Ancillary mapping file directory. This directory must contain the SAS* files
named bound6, counties and cntyctr2, which are used by the include program
Iatlon2fip
ZIP Zip code to FIPS and lat/lon cross-reference text file prefix (zipcodes)
CNTYCENT County FIPS to county centroid location SAS* file prefix (cty_cntr)
STCENT State FIPS to postal code cross-reference SAS* file prefix (st_cntr)
TRACTS County FIPS to random list of tracts correspondence SAS* file prefix (trctarry)
TRCTINFO Census tracts to state and county FIPS code, tract centroid, and tract radius
correspondence SAS* file prefix (tractinf)
SCCDEFLT SCC to default stack parameters correspondence text file prefix (def_scc)
SICDEFLT SIC to default stack parameters correspondence text file prefix (def_sic)
VARLIST Prefix of file containing list of additional variables to be retained in inventory
output file (varlist)
Program Options (see also Table 3-7)
DOLOCATE 1= quality assure location data; 0 = don't quality assure them
DOSTACK 1= quality assure stack parameters; 0 = don't quality assure them.
DOSCCDEF 1= assign default stack parameters by SCC; 0= don't assign them by SCC
DOSICDEF l=assign default stack parameters by SIC; 0 =don't assign them by SIC
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Keyword
Table 3-8. Keywords in the PtDataProc Batch File (continued)
Description of Value
DOSETVAR
USELIST
DOWINDOW
EMISVAR
DLOWHT
DHIHT
DLOWDIA
DHIDIA
DLOWVEL
DHIVEL
DLOWTEMP
DHITEMP
DFLTHT
DFLTDIA
DFLTVEL
DFLTTEMP
EMISVAR
OUTDATA
OUTTEXT
OUTSAS
FINAL
NOLOCATE
ZEROEMIS
l=retain only those non-essential variables from inventory specified by the user,
based on the value of USELIST and VARLIST
0=retain all variables
1= use ancillary file (keyword VARLIST) to provide additional non-essential
variables to retain in inventory
0=don't retain any non-essential variables from the inventory
l^remove all records with zero emissions values or records without latitude and
longitude values
0= don't remove records with zero emissions or without latitude and longitude
values (note that values without latitude and longitude values will still be removed
if you perform the data quality assurance of location data function)
Emissions variable used
Valid Stack Parameter Ranges
Minimum range value for valid stack height (in meters)
Maximum range value for valid stack height (in meters)
Minimum range value for valid stack diameter (in meters)
Maximum range value for valid stack diameter (in meters)
Minimum range value for valid stack velocity (in meters/second)
Maximum range value for valid stack velocity (in meters/second)
Minimum range value for valid stack temperature (in Kelvin)
Maximum range value for valid stack temperature (in Kelvin)
Global Default Stack Parameters
Default stack height (in meters)
Default stack diameter (in meters)
Default stack exit gas velocity (in meters/second)
Default stack exit gas temperature (in Kelvin)
Additional Input Data
Variable name containing the emissions data you want processed
Output files
Output SAS* file directory
Output directory for text file of records without latitude/longitude data
Output inventory SAS* file name (contains all variables and records)
Output inventory SAS* file name after windowing
Output data SAS* file name containing records without coordinates
Output data SAS* file name containing records with zero emissions values
You must include all directory names, file names, and variable values even if they are related to a
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function that you do not select to perform. For example, if you set DOSTACK to 0, you still
need to assign a value to the keywords for the SIC and SCC based default files and the global
default stack parameters in your batch file. The values provided in this circumstance do not need
to represent actual file names; they are merely place holder values for the keywords.
Prepare the execute statement
The last line in the batch file runs the PtDataProc program. In the sample batch file provided in
Figure 2 of Appendix B, you will see a line preceding the run line that creates a copy of the
PtDataProc code having a unique name. It is this version of the program that is then executed in
the last line. If you do this, the log and list files created by this run can be identified by this
unique name. If you don't do this and run the program under a general name, every run of
PtDataProc will create a log and a list file that replace any existing files of the same name.
You may find that you need to define a special area on your hard disk to use as work space when
running PtDataProc. In the sample batch file, a work directory is defined on the last line
following the execution of PtDataProc. The directory you reference here must be created prior to
running the program. For example, the statement:
'sas ptdataproc_061600.sas -work /data/work 15/dyl/'assigns a work directory called
"/data/work 15/dyl".
3.2.4 Execute PtDataProc
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x PtDataProc.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'PtDataProc.bat'.
3.3 How do I know my run of PtDataProc was successful?
3.3.1 Check your SAS® log file
Review the output log file to check for errors or other flags indicating incorrect processing. To
do this, search the log file for occurrences of the strings "error", "warning", "not found", and
"uninitialized". These can indicate problems with input files or other errors.
You can also look at the number of records in the input inventory file and compare it to the
number of records in the output inventory file. The number of records shouldn't change unless
PtDataProc removed records during the quality assurance of the location data or during the
windowing of the inventory. If so, you can determine the number of records written to the
PtDataProc output files containing the records which have been dropped from the inventory (files
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"nolocate" and "nomodel") and the SAS® file containing the records with zero emissions (file
named by keyword ZEROEMIS).
3.3.2 Check your SAS® list file
The list file contains the following information:
• First 100 sites requiring location defaulting due to missing or invalid location data
• First 100 sites dropped from the inventory because a default location could not be
determined; emissions total from all records dropped from inventory
• First 100 sites dropped from the inventory because the disagreement between the location
and FIPS of the facility could not be resolved; emissions total from all records dropped
from inventory
• Pollutant-level and state-level emissions totals and record counts after all location
defaulting is complete
• First 100 sites with out-of-range stack parameters; emissions total from all records with
out-of-range stack parameters
• Pollutant-level and state-level emissions totals and record counts after defaulting of stack
parameters
3.3.3 Check other output files from PtDataProc
You should check for the existence of the output inventory file named by keyword FINAL if you
chose to window the inventory, or by keyword OUTSAS if you didn't. While either of these two
files can serve as the input to PtAspenProc, you will likely want to use the file you reduced
through the window function (named by keyword FINAL) to minimize the disk space use.
PtDataProc also creates SAS® and ASCII formatted output files containing more information on
how the location and stack parameters were defaulted or dropped from the inventory. Table 3-9
describes these files.
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Table 3-9. Additional QA Files Created by PtDataProc
PtDataProc
Function
QA output files File Contents
Quality assurance of location data
dfltloc
nolocate.txt and
nolocate
nomodel.txt and
nomodel
all records where location was defaulted
because of missing or invalid location data
all records dropped from inventory because a
default location could not be determined
all records dropped from inventory because
discrepancy between location and state and
county FIPS could not be resolved
Quality assurance of stack parameters
stkcheck all records where stack parameters are outside a
normally anticipated range of values you
supply in the "Valid Stack Parameter Ranges"
section of Table 3-8
Window inventory to exclude nonzero emissions and unlocated sites
file name assigned all records dropped from the inventory where
through keyword emission values are zero
ZEROEMIS
file name assigned all records dropped from inventory because
through keyword either latitude and/or longitude are missing
NOLOCATE (Note: if you chose to quality assure the
location data, then this file should be empty)
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CHAPTER 4
Point Source Processing
The ASPEN-Specific Program (PtAspenProc)
PtAspenProc is executed after PtDataProc. The resulting point source emission inventory is then
used as input to PtTemporal (see Figure 1-1).
4.1 What is the function of PtAspenProc?
The ASPEN-Specific Processing Program (PtAspenProc) prepares pollutant-specific information
for the ASPEN model and determines ASPEN modeling parameters. PtAspenProc performs the
functions listed below:
• Selects pollutants, groups and/or partitions pollutants, and determines their characteristics
• Assigns urban/rural dispersion parameters
f
• Assigns vent type and building parameters
Figure 4-1 shows a flowchart of PtAspenProc. The following sections describe the above
bullets.
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Batch File Containing
Keywords e.g. File Names
and Locations
Reads Keywords
Point Source Inventory File
HAP Table File
PtAspenProc: MACRO SELHAPS
Reads point source inventory and HAP table
files. Selects, partitions, and groups pollutants
according to contents of HAP table file.
County Flag File
Tract Information File
PtAspenProc: MACRO TRCTFLAG
Reads County Flag File and Tract Information
File. Assigns urban/rural dispersion flag based
on either county or tract designation.
PtAspenProc: MACRO DEFAULT
Assigns vent type and building parameter
variables.
Figure 4-1. PtAspenProc Flowchart
4-2
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4.1.1 Selects pollutants, groups and/or partitions pollutants, and determines their
characteristics
PtAspenProc reads the point source inventory and selects, partitions, and groups pollutants to be
modeled by ASPEN. It also assigns pollutant characteristics that tell ASPEN how to treat
reactive decay and deposition. You control these processes through your entries in an ancillary
file that we refer to as the "HAP table." PtAspenProc uses two HAP table files. One is used for
the allocated aircraft emissions which you obtained by running AirportProc. The other is for all
other (i.e., non-aircraft) point sources. PtAspenProc uses the source type variable (SRCJTYPE)
to distinguish between aircraft point sources and all other point sources. All allocated aircraft
emissions have SRCJTYPE = "nonroad". PtAspenProc's utilization of two different HAP tables
gives you the flexibility to assign different pollutant characteristics (e.g., different particulate size
classes for the particulate pollutants) to the pollutants from aircraft emissions.
PtAspenProc uses the HAP table to:
• Subset the inventory to include only those pollutants you've chosen to model
• Assign a reactivity class to each gaseous pollutant and a particulate size class to each
particulate pollutant (through the variable REACT)
• Group multiple species into a single pollutant category
• Partition pollutants into multiple pollutant categories with different reactivity or
particulate size classes (e.g., apportion lead chromate to lead compounds, fine particulate;
lead compounds, coarse particulate; chromium compounds, fine particulate and
chromium compounds, coarse particulate)
• Apply potency factors, molecular weight, or other adjustment factors (FACTOR variable)
to the emissions of different species in a pollutant category
• Assign the resulting pollutant or pollutant category to be modeled in ASPEN a unique
HAP code (variable NTI_HAP) used for inventory projections in PtGrowCntl, a unique
pollutant group code (variable S AROAD) used for ASPEN modeling and a description of
the group (variable SAROADDC)
Section 4.2.3 contains instructions on how to modify a HAP table to meet your needs.
Appendix A, Tables 1-4 contain printouts of the HAP tables supplied with EMS-HAP.
Appendix D, Sections D.5 and D.6 discuss the development of these HAP tables.
4.1.2 Assigns urban/rural dispersion parameters
The ASPEN model uses different dispersion coefficients and deposition rates for urban and rural
sources. Thus, each emission source must be identified as being located in either an urban or a
rural census tract. PtAspenProc supplies this information through the assignment of the
urban/rural flag (UFLAG) where a value of 1 indicates an urban tract, and a value of 2 indicates a
rural tract. In many cases, all of the tracts within a county are either all urban or all rural, and the
assignment of the urban/rural flag is made by matching the state and county FIPS code to county
data in an ancillary file called ctyflag which contains urban/rural flags for uniform (i.e., either all
urban or all rural) counties. In cases where the tracts within a county are not uniformly urban or
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rural, PtAspenProc assigns the urban/rural flag by determining the specific tract in which the
facility is located, and matching it to tract-level urban/rural data contained in an ancillary file
called tractinf. The ancillary files supplied with EMS-HAP use the same urban/rural
designations used in the EPA's Cumulative Exposure Project (CEP).5 The CEP based the
designation on residential population density data for 1990 (urban if greater than 750
people/km2), except for a few very small tracts. You can change these designations by changing
ctyflag and tractinf. They are described briefly in Section 4.2.2 (Table 4-3), and their formats are
provided in Figures 14 and 9, respectively of Appendix A.
4.1.3 Assigns vent type and building parameters
PtAspenProc assigns the vent type parameter and several building parameters required by the
ASPEN model. The value of the vent type variable (IVENT) is assigned based on the stack type
specified by the emission release point type variable (EMRELPTY) according to the scheme
summarized in Table 4-1. An IVENT value of 0 (zero) represents a stacked vent and the ASPEN
model performs plume rise calculations for these stacks. When the IVENT value is 1,
representing a non-stacked vent, ASPEN does not perform plume rise calculations.
Table 4-1. Assignment of Vent Type Variable
Stack Type
vertical, goose neck, vertical with rain cap, downward-facing vent
horizontal
fugitive
aircraft emissions
Value of
EMRELPTY
2,4,5,6
3
1
AP
Assigned
Value of
IVENT
0
1
1
1
The building parameters required by the ASPEN model are a building code (IBLDG), building
width (BLDW), and building height (BLDH). For horizontal stacks, PtAspenProc sets the
building code to "1" and both building dimension variables to 5 meters. For all other stacks, the
building code is set to "0" and both dimension variables are set to 0 meters.
4.2 How do I run PtAspenProc?
4.2.1 Prepare your point source inventory for input into PtAspenProc
The point source inventory you use for input into PtAspenProc can come from a variety of
sources, but you will likely use the output inventory created by PtDataProc (see Chapter 3). If
your inventory has allocated aircraft emissions (from running AirportProc) you will have had to
run PtDataProc in order to default the missing aircraft emission stack parameters. If your input
to PtAspenProc is the result of processing through PtDataProc, the inventory will meet all
requirements. This inventory will contain at least the variables listed in Table 4-2. It may
contain additional variables such as the diagnostic flag variables (LFLAG, FIPFLAG, etc.)
4-4
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created by PtDataProc depending on the options you chose for the windowing function in
PtDataProc(see3.1.3).
Table 4-2. Variables in the PtAspenProc Input Point Source Inventory SAS® File
Variables used by PtAspenProc are in bold;
other variables listed are used by previously run or subsequent point source processing programs
Variable Name
ACTJD
CNTL_EFFa
COOR_ID
EMIS
EMRELPID
EMRELPTY
FIPS
LAT
LON
MACTCODE
POLLCODE
sec
SIC
SITE ID
SRC_TYPE
STACKDIA
STACKHT
STACKVEL
STKTEMP
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process at a unique site
baseline control efficiency, expressed as a percentage
code identifying a unique set of geographic coordinates
pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01 =fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck,
05=vertical with rain cap, 06=downward-facing vent, AP=aircraft)
5-digit FIPS code (state and county combined)
latitude (in decimal degrees)
longitude (in negative decimal degrees)
process or site-level MACT code
unique pollutant code
EPA source category code identifying the process
Standard Industrial Classification (SIC) code for the site
code identifying a unique site
description of the emission source at the site ('nonroad' for aircraft
emissions). If you choose to define ASPEN source groups by this variable as
explained in 7. 1 . 1 , or run PtGrowCntl (Chapter 6) then it must have the value
of 'major' or 'area' for non-aircraft emissions.
diameter of stack (meters)
height of stack (meters)
velocity of exhaust gas stream (meters per second)
temperature of exhaust gas stream (Kelvin)
Type*
A25
N
A20
N
A50
A4
A5
N
N
A7
A10
A10
A4
A20
A15
N
N
N
N
* Ax = character string of length x, N = numeric
required only by the optional Growth and Qontrol Program (Chapter 6)
4-5
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4.2.2 Determine whether you need to modify the ancillary input files for PtAspenProc
An ancillary file is any data file you input to the program other than your emission inventory.
Table 4-3 lists the ancillary input files for PtAspenProc. The ones you'll likely need to modify
are the HAP table files. Four different HAP table files are provided with EMS-HAP. These files
were developed for use with different emission data sources (point and area, onroad mobile, and
nonroad mobile) and for different pollutant types (directly emitted HAPs, and HAP precursors
that lead to secondary HAP formation). In Appendix D, Section D.5 details how we developed
the HAP table files for directly emitted HAPs, and Section D.6 details how we developed the
HAP table for the precursors. All of these files contain the same type of information in the same
format. You will probably want to modify these HAP table files in order to select and group the
pollutants for your modeling needs. A description of the function and format of a HAP table file
is presented in the next section. Complete listings of the individual HAP table files provided
with EMS-HAP can be found in Appendix A (Tables 1-4).
Table 4-3. Required Ancillary Input Files for PtAspenProc
Name
Purpose
Need to Modify
Format
HAP table Selects pollutants to be modeled, assigns
for non- reactivity and particulate size classes,
aircraft groups pollutants, adjusts emissions for non-
point aircraft point source emission records
sources
HAP table Selects pollutants to be modeled, assigns
for aircraft reactivity and particulate size classes,
sources groups pollutants, adjusts emissions
for allocated aircraft emission records
tractinf Provides census tract centroid location and
radius and urban/rural dispersion flag for
assigning dispersion flag to a site at the
tract-level
ctyflag Assigns urban/rural dispersion flag based on
county FIPS for counties with uniform
census tracts
If you choose to change Text
selection or characteristics
of pollutants from those in
files provided with EMS-
HAP
If you choose to change Text
selection or characteristics
of pollutants from those in
files provided with EMS-
HAP
If you choose to update the SAS*
tract-level urban/rural
dispersion designations
If you've updated the tract- SAS*
level urban/rural dispersion
designations
4-6
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4.2.3 Modify the HAP table input files
We've supplied you with four HAP Table files.
1) point_area HAP table (haptabl_point_area.txt)
2) onroad mobile HAP table (haptabl_onroad.txt)
3) nonroad mobile HAP table (haptabl_nonroad.txt)
4) precursor HAP table (haptabl_precursor.txt), which applies to precursors from point, area,
onroad and nonroad sources.
Precursors are pollutants that cause HAPs to form secondarily in the atmosphere. They may or
may not be HAPs themselves. More information about processing HAP precursors can be found
in Appendix D, Section D.6.
PtAspenProc uses two HAP table files in a single run. One is for aircraft emission sources which
were allocated to specific locations by the AirportProc program, and one is for non-aircraft point
sources. Before you run PtAspenProc you'll need to select the appropriate HAP tables and
modify them to fit your modeling needs and your inventory. If you are running the direct
emissions of HAPs, then select the point_area HAP table for non-aircraft emissions and nonroad
HAP table for aircraft emissions. Select the precursor HAP table for both non-aircraft point
sources and aircraft point sources if you are processing precursors to HAPs; Figure 3 of
Appendix B provides example batch files with these HAP table selections.
You may not need to modify any of the HAP table files provided with EMS-HAP. The most
likely reason to modify one of these files would be to select different pollutants or to assign
particulate size classes differently. In addition, you must change the file if it does not include all
species contained in your inventory. Do this by adding records for these species to a HAP table
file. Otherwise, EMS-HAP won't process these pollutants and it won't pass them to the ASPEN
model.
The remainder of this section describes the HAP table file. It describes how EMS-HAP uses the
information contained in the HAP table, and gives you the background you need to make
decisions on modifying the HAP tables for use with your inventory.
Key Features of the HAP table
With the HAP table, you can select which pollutants to retain from your emission inventory.
You can also group pollutants together (e.g., group lead oxide and lead chromate into lead
compounds) or partition pollutants (e.g., partition lead chromate into lead compounds and
chromium compounds). Depending on your inventory, you may need to modify the emission
values to account for such things as reactivity differences between two pollutants in the same
group or expressing the mass of metal-containing HAPs as the mass of the metal (which you may
want to do if you are combining emissions from several different metal-containing HAPs).
PtAspenProc makes these adjustments to the emissions by applying a weighting factor also
included in the HAP table file. Last, ASPEN modeling requires that every pollutant or pollutant
4-7
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group be assigned a unique code and a corresponding reactivity class for the SAROAD code.
PtAspenProc assigns these based on the information in the HAP table file.
Table 4-4 shows the format of the HAP tables that PtAspenProc uses for HAP-specific
processing. All variables except for POLLDESC and SAROADDC are required to have values
for the pollutants you choose to model. However, values of those variables would be useful for
interpreting information in the SAS® list file (see Section 4.3.2). PtAspenProc does not default
any information not present in your HAP table. Table 4-5 gives sample entries which illustrate
the key HAP-specific modeling features of EMS-HAP.
Table 4-4. Structure of the HAP Table
Variable name used
in PtAspenProc
Description
Type* Column Length Range
POLLDESC
SAROADDC
POLLCODE
Individual chemical name,
prior to aggregation
Name of the aggregated
SAROAD code
Code identifying individual
C
C
C
1
47
100
45
50
10
REACT
KEEP
SAROAD
FACTOR
NTI HAP
chemical in inventory (typically
a Chemical Abstracts System
[CAS] No.)
Reactivity or Particle Size Class N 113
Flag determining whether C 121
chemical will be modeled
Code defining a single chemical C 128
or group of chemicals for
modeling. Can be an historic
SAROAD code, or arbitrarily
assigned.
Emission adjustment factor N 135
Code identifying HAP on the C 144
Clean Air Act HAP list. Used
only in projection program
PtGrowCntl (Chapter 6)
1-9
YorN
1-188
* Type C=character, N=numeric
4-8
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Table 4-5. Sample Entries in a HAP Table
Inventory species name
Dioxins, total, w/o individ. isomers reported
1,2,3,7,8-Pentachlorodibenzo-p-dioxin
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1,2,3,7,8,9-Hexachlorodibenio-p-dioxin
l,2,3,4,6,7,8-Heptachlorodibenzo-p-/dioxin
Octachlorodibenzo-p-dioxin
Dioxins, total, w/o individ. isomers reported
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1,2,3,7,8 -Pentachlorodibenzo-p-dioxin
1,2,3,7,8,9-Hexachlorodibenzo-p-dioxin
1,2,3 ,4,6,7,8-Heptachlorodibenzo-p-/dioxin
Octachlorodibenzo-p-dioxin
Lead & Compounds
Lead carbonate
Lead titanate
Lead sulfate
Lead oxide
Lead nitrate
Lead & Compounds
Lead carbonate
Lead titanate
Lead sulfate
Lead oxide
Lead nitrate
Hydrogen Cyanide
HAP category name
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, upper bound
Dioxins/Furans as TEQ, lower bound
Dioxins/Furans as TEQ, lower bound
Dioxins/Furans as TEQ, lower bound
Dioxins/Furans as TEQ, lower bound
Dioxins/Furans as TEQ, lower bound
Dioxins/Furans as TEQ, lower bound
Lead compounds, fine particulate
Lead compounds, fine particulate
Lead compounds, fine particulate
Lead compounds, fine particulate
Lead compounds, fine particulate
Lead compounds, fine particulate
Lead compounds, coarse particulate
Lead compounds, coarse particulate
Lead compounds, coarse particulate
Lead compounds, coarse particulate
Lead compounds, coarse particulate
Lead compounds, coarse particulate
Cyanide Compounds, gas
NTI
species
code
610
40321764
1746016
19408743
35822469
3268879
610
1746016
40321764
19408743
35822469
3268879
195
598630
12060003
7446142
1309600
10099748
195
598630
12060003
7446142
1309600
10099748
74908
React-
ivity
class
2
2
2
2
2
2
3
3
3
3
3
3
1
Keep
7
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
SAROAD
code
80245
80245
80245
80245
80245
80245
80245
80412
80412
80412
80412
80412
80193
80193
80193
80193
80193
80193
80393
80393
80393
80393
80393
80393
80145
Factor to
adjust to
emission
value
(TEF or
other)
1.000
0.500
1.000
0.100
0.010
0.001
0.000
1.000
0.500
0.100
0.010
0.001
0.740
0.574
0.506
0.506
0.687
0.463
0.260
0.202
0.178
0.178
0.241
0.163
0.963
NTI
HAP
No.
903
903
903
903
903
903
903
903
903
903
903
903
122
122
122
122
122
122
122
122
122
122
122
122
82
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Selecting the pollutants you want to model
Set the KEEP variable to "Y" for each pollutant that you want to model, and "N" for each
pollutant you don't want to model. EMS-HAP uses this variable to determine which records to
keep for further processing. EMS-HAP will keep records for the pollutants in the HAP table
with KEEP equal to "Y" and drop records for pollutants with KEEP equal to "N."
Assigning reactivity and paniculate size classes to the pollutants
Make sure your HAP table has an assignment of the reactivity variable for every pollutant you
want to model. If you have additional information on how HAPs partition between fine and
coarse particulate size classes or between gas and particulate matter, you may want change how
they are partitioned in the HAP tables provided. To do this, you need to also read about
combining and partitioning inventory species into groups presented in the next section.
EMS-HAP uses the REACT variable to provide ASPEN information on the amount of decay or
deposition to use for each pollutant. As emissions disperse downwind, most organic HAPs are
gradually converted to other compounds. Particulate HAPs gradually settle and deposit as they
disperse downwind from an emission source. The REACT variable in Table 4-4, specifies the
reactivity class, or in the case of particulate HAPs, the particulate size class. EMS-HAP uses
these classes to establish and provide decay rate information for the ASPEN input files, as
discussed in Chapter 7, Section 7.1.2.
ASPEN uses up to seven reactivity classes to quantify degradation of gaseous organic pollutants,
and two classes to distinguish between fine and coarse particulate pollutants. These classes are:
• non-reactive or very low reactivity (REACT=1)
• low reactivity (REACT=9)
• medium low reactivity (REACT=4)
• medium reactivity (REACT=5)
• medium high reactivity (REACT= 6)
• high reactivity (REACT=8)
• very high reactivity (REACT=7)
• fine: particles with aerodynamic diameter less than 2.5 /urn- (REACT=2)
• coarse: particles with aerodynamic diameter beween 2.5 and 10 //m- (REACT=3)
This classification system and the associated decay coefficients were developed for the
Cumulative Exposure Project (CEP).6 The decay coefficients are located in the ancillary file
called indecay.txt. This file is used with PtFinalFormat (Chapter 7, see 7.2.2) and AMProc
(Chapter 10, see 10.2.2). Appendix A, Figure 26, contains sample file contents for indecay.txt.
4-10
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Combining/partitioning inventory species into groups
To group or partition inventory species, follow the directions in Table 4-6 below. If you are
partitioning HAPs, you must also adjust the FACTOR variable as discussed in the following
section.
Table 4-6. Directions for Partitioning or Grouping of Inventory Species
If you want to
Then
For Example
Partition a pollutant
into more than one
category.
Group multiple
inventory species to
the same HAP
category.
Partition a pollutant
into different particle
size classes, while at
the same time
grouping it together
with other pollutants
in a HAP category.
Use multiple records (in the HAP table)
with the same POLLCODE value and
different SAROAD values. You need a
separate record for each HAP category to
which the pollutant is assigned. Also see
Table 4-7 for information on how to
adjust the FACTOR variable.
Use multiple records (in the HAP table)
with the same SAROAD value, and
different POLLCODE values.
Use two records for each pollutant. Both
records have the same POLLCODE but
different SAROAD codes. One record
has a SAROAD representing the fine
particulate group, and one record has a
SAROAD representing the coarse
particulate group.
Table 4-5 shows "Lead &
Compounds" partitioned to
"Lead Compounds, coarse" and
"Lead Compounds, fine"
categories.
Table 4-5 shows that both
"Dioxins, total, w/o individ.
isomers reported"and
" 1,2,3,7,8-Pentachlorodibenzo-p-
dioxin" are assigned to the
"Dioxins/Furans as TEQ, upper
bound" HAP group.
Table 4-5 shows how to group
six lead inventory entries into
"Lead Compounds" and in turn
divide them into fine (REACT
=2) and coarse (REACT =3)
particulates. Note that 12 records
are needed in the HAP table, two
for each of the 6 species.
Adjusting emissions
Use the FACTOR variable to make adjustments to emissions as shown in Table 4-7. If you are
not adjusting emissions, you must set the FACTOR variable to 1. A missing FACTOR variable
will drop emissions for that pollutant from your inventory.
4-11
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Table 4-7. Using FACTOR Variable to Adjustment Emissions
Use FACTOR to
For Example.—
Apportion a pollutant's emissions
into more than one category
Adjust the emissions of a metal or
cyanide compound to account for
only the metal or cyanide portion of
the compound
Adjust the emissions of a metal or
cyanide compound to account for
only the metal or cyanide portion of
the compound and apportion the
emissions into more than one
category
Adjust the emissions of a dioxin
congener to 2,3,7,8-
tetrachlorodibenzodioxin toxic
equivalents (TEQs) using a toxics
equivalency factor (TEF)
Apply two different TEFs for those
dioxin/furans that can not be
converted to TEQ to produce both
upper and lower bound estimates for
dioxin/furans
If "Lead & Compounds" contained 26% coarse particulate and 74%
fine particulate, the factors (hereafter referred to as "split factors") to
apportion emissions into coarse and fine particulate classes would be
0.26 and 0.74, respectively
To quantify how much cyanide gas emissions come from Hydrogen
Cyanide (CHN), use a factor (hereafter referred to as "metal
reduction factor") equal to the ratio of the molecular weight (MW) of
total cyanide moles in CHN to the molecular weight of CHN. The
MW of cyanide moles is 26.0177, and the MW of CHN is 27.0256.
The factor for CHN is therefore 26.0177/27.0256= 0.9627.
Combine the coarse fine split factor and metal reduction factor by
multiplying them together. For Lead Carbonate (COSPb), the metal
reduction factor is the MW of lead (207.9) divided by the MW of
COSPb (267.2092), which is 0.7754. Given a 26/74 coarse/fine
split, the factor used in the HAP table for processing lead carbonate
for the coarse lead category is 0.7754*0.26= 0.202, and the factor for
the fine lead category is 0.7754*0.74 = 0.574
1,2,3,7,8-Pentachlorodibenzo-p-dioxin has a TEF of 0.5, thus use a
factor of 0.5 to adjust this species to TEQ.
Assign a TEF of 1.0 to "Dioxins, total, w/o individ. isomers reported"
to reflect an upper end estimate of TEQ. Assign it a TEF of 0.0 to
reflect a lower bound estimate of TEQ
The emissions for a HAP category is the sum of the adjusted emission for each species in the
category. The following hypothetical example illustrates how PtAspenProc groups and partitions
inventory species. Refer to Table 4-5 for the factors used in this example. A given stack emits
lead oxide, lead carbonate, and lead sulfate emissions. PtAspenProc calculates the emissions (E)
of lead compounds fine particulate (SAROAD= 80193) from that stack as:
F =0 fi87*F 4- 0 S74*F
Head compounds, fine particulate ".uo / J^ Lead oxide w.J/t i-
Lead carbonate"1" "•506 C, leadsuifate
The emissions of lead compounds coarse particulate (SAROAD=80393) are calculated as:
Head compounds, coarse particulate = 0.241 E Leadoxide + 0.202 E Lead cartxmate"1" O.l/O E, )ead sulfate
4-12
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4.2.4 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for PtAspenProc is shown in Figure 3 of
Appendix B.
Specify your keywords
Table 4-8 describes the keywords required in the batch file. Use keywords to locate and name all
input and output files.
Table 4-8. Keywords in the PtAspenProc Batch File
Keyword
Description of Value
Input Inventory Files
Input SAS* file directory
Input inventory SAS* file name
Ancillary or Reference Files (Prefix of file name provided with EMS-HAP)
Reference SAS* file directory
Reference text file directory
HAP table file prefix; used for non-aircraft point source emissions
(haptabl_point_area or haptabl_precursor)
HAP table file prefix; used for aircraft point source emissions (haptabl_nonroad
or haptabl_precursor)
County FIPS to urban/rural flag correspondence SAS® file for counties with a
uniform flag for all tracts within the county (cryflag)
Census tract information SAS* file containing data necessary to assign an
urban/rural flag (tractinf)
Additional Input Data
Variable name containing the emission data values
Output files
Output SAS* file directory
Output inventory SAS* file name
IN_DATA
INSAS
REFSAS
REFTEXT
PTHAPS
MOBHAPS
CTYFLAG
TRCTINF
EMISVAR
OUTDATA
OUTSAS
Prepare the execute statement
The last line in the batch file runs the PtAspenProc program. In the sample batch file provided in
Appendix B, you will see a line proceeding the run line that creates a copy of the PtAspenProc
code having a unique name. It is this version of the program that is then executed in the last line.
If you do this, the log and list files created by this run can be identified by this unique name. If
you don't do this and run the program under a general name, every run of PtAspenProc will
4-13
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create a log and a list file that will replace any existing files of the same name.
You may find that you need to assign a special area on your hard disk to use as work space when
running PtAspenProc. In the sample batch file, a work directory is defined on the last line
following the execution of PtAspenProc. For example, the command
'sas PtAspenProc_01 ISOO.sas -work /data/workl5/dyl/' assigns a work directory called
"/data/workl5/dyl". The directory you reference must be created prior to running the program.
4.2.5 Execute PtAspenProc
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x PtAspenProc.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'PtAspenProc.bat'.
4.3 How do I know my run of PtAspenProc was successful?
4.3.1 Check your SAS® log file
You need to review the output log file to check for errors or other flags indicating incorrect
processing. This review should include searching the log files for occurrences of the strings
"error", "warning", "not found", and "uninitialized". These can indicate problems with input
files or other errors.
Depending on how you selected, partitioned, and grouped pollutants, the number of records in
the output inventory file will be different from the number of records in the input inventory file.
After the application of the HAP table files, the number of records in the output inventory file
should not change when the urban/rural dispersion flag, vent type, and building parameters are
added.
4.3.2 Check your SAS9 list file
The list.file contains the following information:
• List of records (if any) from the inventory with pollutant codes not included in the HAP
tables
• List of pollutants codes retained for ASPEN modeling based on the HAP tables,
including the SAROAD assignment and FACTOR variable
• List of pollutant codes not retained for ASPEN modeling based on the HAP tables,
including any SAROAD assignment
• Comparison of pollutant code-level emission totals of aircraft and non-aircraft emissions
retained for modeling, not retained for modeling, and in the input inventory files
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• Pollutant code-level and SAROAD-level emission totals for emissions retained for
ASPEN modeling after application of weighting factor
• SAROAD-level emission totals after selection of pollutants, application of weighting
factor, and accumulation by SAROAD code
• SAROAD-level emission totals for output inventory from PtAspenProc
You should check to be sure that all pollutants of interest are included in your HAP tables by
reviewing the first lists of records describe above. Any records with pollutant codes not found in
the HAP tables are removed from the inventory. Based on these lists, you may need to revise
your HAP table files and rerun PtAspenProc.
It is important to check the accuracy of the pollutant selection, the application of weighting
factors, and the accumulation of emissions to the SAROAD code groups. The tables comparing
the emission totals between the pollutants retained for modeling and those not retained to the
input emission inventory is particularly useful for this purpose. It is also important to compare
the pollutant-level emission totals before and after the application of the weighting factors.
4.3.3 Check other output files from PtAspenProc
You should check for the existence of the output inventory file named by keyword OUTS AS.
This file will be the inventory input to PtTemporal.
4-15
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CHAPTER 5
Point Source Processing
The Temporal Allocation Program (PtTemporal)
PtTemporal is typically run after PtAspenProc (see Figure 1-1). You can input the resulting
inventory from PtTemporal into the PtGrowCntl program to project your inventory to a future
date, or the PtFinalFormat program to write out the emission input files for the ASPEN model.
5.1 What is the function of PtTemporal?
The PtTemporal program prepares the inventory for the ASPEN model by temporally allocating
annual point source emissions. Temporal allocation is the process of estimating emissions at
smaller temporal scales than the scales of the input emission inventory. The ASPEN model
requires emissions for eight 3-hour periods within an annually-averaged day; this uniform
allocation of annual emissions to days during the year results in each day of the year containing
the same emissions. This program produces these eight emission estimates for the point source
inventory. PtTemporal performs the following functions:
• Assigns an hourly temporal profile to each emission record
• Uses the hourly profiles to produce eight 3-hour emission rates
Figure 5-1 shows a flowchart of PtTemporal. The following sections describe the above bullets.
5-1
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Batch File Containing
Keywords e.g. File Names
and Locations
• Reads Keywords
Temporal Allocation Factor
(TAF) File
PtTemporal: MACRO READTAF
Reads temporal allocation factor file containing
24 1-hour factors. Calculates eight 3-hour
factors and renormalizes the 3-hour factors.
Point Source Inventory File
SCC to SCC/AMS Cross
Reference File
SIC to SCC/AMS Cross
Reference File
MACT Category to SCC
Cross Reference File
PtTemporal: MACRO MERGETAF
Reads point source inventory file. Assigns
TAFs by matching SCC on inventory to
SCC/AMS assigned to each profile of TAFs.
Uses cross reference files to match other
source/process information (SIC or MACT
category) on inventory to profile SCC/AMS.
Figure 5-1. PtTemporal Flowchart
5-2
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5.1.1 Assigns an hourly temporal profile to each emission record
EMS-HAP assigns temporal profiles from an ancillary temporal allocation factor (TAP) file.
This file contains temporal profiles based on 8-digit AIRS Source Classification Codes (SCC) or
10-digit Area and Mobile System (AMS) codes. Each profile consists of 24 temporal allocation
factors (TAFs) that can allocate annual emissions to each hour of an average day. Details on
how we developed this file are presented in Appendix D, Section D.7. PtTemporal attempts to
match each record in the emission inventory to a temporal profile in the TAP file based on either
the SCC code, the Standard Industrial Classification (SIC) code, or the Maximum Achievable
Control Technology (MACT) code. If the emission record contains an 8-digit SCC code,
PtTemporal first attempts to match the record directly to a temporal profile. For those records
without an SCC code or with a code for which no profile is provided, PtTemporal checks for
other information that can be linked to an SCC or AMS code in the TAF file. By using several
cross-reference files, PtTemporal attempts to link to temporal profiles using the following
information on the inventory records in the order given: partial SCC code, SIC code, or MACT
code. For records that still cannot be assigned a temporal profile, PtTemporal tries to match the
first 6 digits of the SCC with the first 6 digits of the SCC codes in the TAF file. If none of this
information links to a temporal profile, then the emissions are assigned uniform temporal
allocation factors that evenly distribute the emissions over the eight 3-hour periods.
5.7.2 Uses the hourly profiles to produce eight 3-hour emission rates for each record
Because ASPEN requires emissions for eight 3-hour periods of an average day, PtTemporal uses
the 24 hourly TAFs to produce emission rates for the 3-hour periods. Although the initial 24
hourly TAFs are assumed to be normalized to conserve mass, PtTemporal checks the
normalization of the 3-hour TAFs for each profile. PtTemporal then applies the TAFs and, as
required by ASPEN, converts the annual emission rate to grams/second.
The example shows the calculation for the 3-hour period from midnight to 3 am.
E0.3 = Em x (HF, + HF2 + HF3) x CF, x CF2 x CF, x CF4 x CF5 (eq. 5-1)
where:
E0_3 = emission rate during the midnight to 3 a.m. time period for an average day (grams/second)
Eain = annual emissions (tons/year)
HFn = temporal allocation factor for hour "n" (fraction of daily emissions occurring in hour "n" -
dimensionless)
CF, = conversion factor (1 year / 365 days)
CF2 = conversion factor (1 day / 24 hours)
CF3 = conversion factor (1 hour / 3600 seconds)
CF4 = conversion factor (2000 Ibs /1 ton)
CF5 = conversion factor (453.592 grams /I Ib)
5-3
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5.2 How do I run PtTemporal?
5.2.1 Prepare your point source inventory for input into PtTemporal
The point source inventory you use for input into PtTemporal must be the output of PtAspenProc
if you intend to create ASPEN-input files. If you don't intend to create ASPEN-input files, you
could use the output from PtDataProc as the-input into PtTemporal. The inventory produced by
either PtDataProc or PtAspenProc will meet all requirements. The inventory produced by
PtAspenProc will contain at least the variables listed in Table 5-1. It may contain additional
variables such as the diagnostic flag variables (LFLAG, FIPFLAG, etc.) created by PtDataProc
depending on the options you chose for the windowing function in PtDataProc (see 3.1.3).
Table 5-1. Variables in the PtTemporal Input Point Source Inventory SAS* File
Variables used by PtTemporal are in bold;
other variables listed are used by previously run or subsequent point source processing programs
Variable Name
ACTJD
BLDH
BLDW
CNTL_EFFa
COORJD
EMIS
EMRELPID
EMRELPTY
FIPS
IBLDG
IVENT
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process at a unique site
ASPEN building height (in meters) (5 for horizontal stacks, 0 for all
other stacks); assigned in PtAspenProc (see Section 4.1 .3)
ASPEN building width (in meters) (5 for horizontal stacks, 0 for all other
stacks); assigned in PtAspenProc (see Section 4.1.3)
baseline control efficiency, expressed as a percentage
code identifying a unique set of geographic coordinates
pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01=fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck,
05=vertical with rain cap, 06=downward-facing vent, AP=aircraft)
5 -digit FIPS code (state and county combined)
ASPEN building code (1 for horizontal stacks, 0 for all other stacks)
assigned in PtAspenProc (see Section 4.1.3)
ASPEN vent type (0 for stacked sources, 1 for non-stacked sources)
assigned in PtAspenProc (see Section 4.1.3)
Type*
A25
N
N .
N
A20
N
A50
A4
A5
Al
Al
5-4
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Table 5-1. Variables in the PtTemporal Input Point Source Inventory SAS® File
(Continued)
Variable Name
LAT
LON
MACTCODE
NTI_HAP
POLLCODE
REACT
SAROAD
SAROADDC
sec
SIC
SITE_ID
SRCJTYPE
STACKDIA
STACKHT
STACKVEL
STKTEMP
UFLAG
Data Description
(Required units or values are in parentheses)
latitude (in decimal degrees)
longitude (in negative decimal degrees)
process or site-level MACT code
code identifying HAP on the Clean Air Act HAP list; assigned in
PtAspenProc (see Section 4.1.1)
unique pollutant code
pollutant reactivity class (1-9); assigned in PtAspenProc (see Section
4.1.1)
unique pollutant-group code; assigned in PtAspenProc (see Section 4.1.1)
descriptive name for the SAROAD; assigned in PtAspenProc (see
Section 4. 1.1)
EPA source category code identifying the process
Standard Industrial Classification (SIC) code for the site
code identifying a unique site
description of the emission source at the site ('nonroad' for aircraft
emissions) If you choose to define ASPEN source groups by this variable
as explained in 7.1.1, or run PtGrowCntl (Chapter 6) then it must have the
value of 'major' or 'area' for non aircraft emissions.
diameter of stack (meters)
height of stack (meters)
velocity of exhaust gas stream (meters per second)
temperature of exhaust gas stream (Kelvin)
urban/rural dispersion flag (1 for urban, 2 for rural); assigned in
PtAspenProc (see Section 4.1.2)
Type*
N
N
A7
.A3
A10
N
A10
A50
A10
A4
A20
A15
N
N
N
N
N
*Ax = character string of length x, N = numeric
required only if you run the optional Growth and Control Program (Chapter 6)
5-5
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5.2.2 Determine whether you need to modify the ancillary input files for PtTemporal
An ancillary file is any data file you input to the program other than your emission inventory.
Table 5-2 lists the ancillary input files required for PtTemporal and when you may need to
modify them.
Table 5-2. Required Ancillary Input Files for PtTemporal
Name of File
Provided with
EMS-HAP
Purpose
Need to Modify?
Format
taff_hourly.txt Provides temporal profiles containing
24 hourly temporal allocation factors
(TAFs) by SCC and/or AMS codes
scc2ams.txt Provides cross reference between
SCC on inventory to SCC and/or
AMS in order to assign temporal
profile
sic2ams.txt
Provides cross reference between SIC
on inventory to SCC and/or AMS in
order to assign temporal profile
mact2scc.txt Provides cross reference between
MACT code on inventory to SCC in
order to assign temporal profile
When additional source Text
specific temporal factors
become available
When inventory contains Text
records with partial SCC
codes, or SCC codes that are
not in the cross-reference
file or TAF file
When inventory contains Text
records with the source
category identified by SIC
codes that are not in the
cross-reference file
When inventory contains Text
records with the source
category identified by
MACT category codes that
are not in the cross-
reference file
5.2.3 Modify the temporal allocation factor file (taff_hourly)
The primary ancillary input file for PtTemporal is the temporal allocation factor (TAF) file
(taff_hourly). This is a common file used for point, area, and mobile source emission processing
within EMS-HAP. This file provides 24 hourly allocation factors that are applied to emissions
sources based on 8-digit SCC or 10-digit AMS codes. Local time zones are used. The TAFs
should be normalized and, therefore, sum to 1 to conserve mass. Details on the development of
this file are presented in Appendix D, Section D.7, and Figure 15 of Appendix A contains the file
format. You can modify the allocation factors for existing profiles or add new profiles.
5-6
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5.2.4 Modify the cross-reference files used to link inventory records to the temporal
allocation factor file (scc2ams, sic2ams, and mact2scc)
PtTemporal uses three cross-reference files for cases where there the SCC is missing or the value
contained on the emission inventory record can't be linked directly to the SCC and/or AMS on
the TAP file. These cross-reference files provided with EMS-HAP were developed to
accommodate the types of source category information included in the 1996 NTI. For instance,
the 1996 NTI does not include SCC for every emission record or sometimes uses a shortened
1-digit, 3-digit or 6-digit SCC. Therefore, one cross-reference file (scc2ams.txt) links generic
1-digit, 3-digit, and 6-digit SCCs to the 8-digit SCC and 10-digit AMS codes used in the
temporal profile file. Another file links SIC codes to SCC and AMS codes (sic2ams.txt), and is
used in cases where no SCC is included on the emission record, but an SIC is included. A third
file links MACT codes to SCC and AMS codes (mact2scc.txt), and is used for cases where no
SCC code is present on the emission record, but a MACT code is available. The formats for
these three files are provided in Figures 16,17 and 18 of Appendix A. Details on how we
developed these files are presented in Appendix D, Section D.9.
You would expect to modify any of these files depending on the source category information
included in your emission inventory. You might consider modifying these files after executing
PtTemporal if you find that a large number of records with some form of source category
information cannot be matched to a temporal profile and, therefore, are being assigned a uniform
profile. You can determine which records are being assigned a uniform profile by looking at the
log and list files and a special SAS® file, named "notaf," created when you run PtTemporal (see
Section 5.3.3 for more details).
5.2.5 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for PtTemporal is shown in Figure 4 of
Appendix B.
Specify your keywords
Table 5-3 describes the keywords required in the batch file. Use keywords to locate and name all
input and output files.
5-7
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Table 5-3. Keywords in the PtTemporal Batch File
Keyword Description of Value
Input Inventory Files
IN_DATA Input SAS* file directory
INSAS Input inventory SAS® file name
Ancillary Files (Prefix of file name provided with EMS-HAP in parentheses)
REFFILE Ancillary text file directory
TAF Temporal profile text file (taffjiourly)
SCCLINK SCC to AMS cross-refererice text file (scc2ams)
SICLINK SIC to SCC or AMS code cross-reference text file (sic2ams)
MACTLINK MACT category code to SCC or AMS code cross-reference text file (mact2scc)
Additional Input Data
EMISVAR Variable name containing the values to be temporally allocated
Output files
OUTDATA Output SAS* file directory
OUTSAS Output inventory SAS® file name
Prepare the execute statement
The last line in the batch file runs the PtTemporal program. In the sample batch file provided in
Appendix B, you will see a line preceding the run line that creates a copy of the PtTemporal code
having a unique name. It is this version of the program that is then executed in the last line. If
you do this, the log and list files created by this run can be identified by this unique name. If
you don't do this and run the program under a general name, every run of PtTemporal will create
a log and list file that will replace any existing files of the same name.
You may find that you need to assign a special area on your hard disk to use as work space when
running PtTemporal. In the sample batch file, a work directory is defined on the last line
following the execution of PtTemporal. For example, the command
'sas PtTemporal_062000.sas -work /data/workl5/dyl/' assigns a work directory called
"/data/work 15/dyl". The directory you reference must be created prior to running the program.
5.2.6 Execute PtTemporal
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x PtTemporal.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'PtTemporal.bat'.
5-8
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5.3 How Do I Know My Run of PtTemporal Was Successful?
5.3.1 Check your SASt* log file
You should review the output log file to check for errors or other flags indicating incorrect
processing. This review should include searching the log files for occurrences of the strings
"error", "warning", "not found", and "uninitialized". These can indicate problems with input
files or other errors.
You can look at the number of records in the input inventory file and compare it to the number of
records in the output inventory file. The number of records should be the same in these two
files.
5.3.2 Check your SASf* list file
The list file created when PtTemporal is executed contains information to assist in quality
assurance. The information is this file is listed below:
• List of records from the temporal allocation factor (TAF) file where the sum of
the allocation factors before normalization is less than 0.9 or greater than 1.1
• Annual emission totals of the temporally allocated emissions and the unmatched
(uniformly allocated by default) emissions by SAROAD code
5.3.3 Check other output files from PtTemporal
You should check for the existence of the output inventory file named by keyword OUTS AS.
This file will serve as the input to the next point source processing program you choose to run.
PtTemporal also creates a SAS® output file named notaf. This file contains information on the
emission records not assigned a specific temporal profile. For these records, emissions were
uniformly allocated to each of the eight 3-hour time periods. You can reduce the number of
records appearing in this file in several ways. You can modify the TAF file (taffjiourly) by
adding SCC codes and corresponding temporal allocation factors. You can modify one of the
cross-reference files hi order to link an AMS or SCC code in the TAF file with the source or
process information is contained on the emission records (i.e., SCC, SIC, or MACT). See
Section 5.2.4 for a description of the cross-reference files (scc2ams.txt, sic2ams.txt, or
mact2scc.txt).
5-9
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CHAPTER 6
Point Source Processing
The Growth and Control Program (PtGrowCntl)
PtGrowCntl is executed after PtTemporal (see Figure 1-1). The output inventory is then used as
the input to PtFinalFormat.
Note that this program is expected to undergo developmental changes, and we will provide
updated documentation when the revised version is released. PtGrowCntl's control methodology
is currently tailored to emission standards identified by the MACT code in the inventory or to
facility specific information you provide. We refer to these emission standards as Maximum
Achievable Control Technology (MACT) standards although they also include standards under
Section 129 of the Clean Air Act. The current growth methodology relies solely on SIC-specific
growth factors.
6.1 What is the function of PtGrowCntl?
The Growth and Control Program (PtGrowCntl) computes future emissions as a result of
emission reduction strategy scenarios (currently MACT standards only) and projected economic
growth. You control which of the two functions listed below are performed in any given
execution of PtGrowCntl (Table 6-4 in Section 6.2.6 details how to do this).
• Assigns and applies growth factors to project emissions due to growth
• Assigns and applies emission reduction information to emissions
Figure 6-1 shows a flowchart of PtGrowCntl. The following sections describe the above bullets.
6-1
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Batch File Containing
Keywords e.g. File Names
and Locations, Program
Options
General MACT Reduction
Control Information File
Specific Process/Pollutant
MACT Reduction Control
Information File
Specific Process/Pollutant
Facility Reduction Control
Information File
Reads Keywords
Point Source Inventory File
SCC to SIC Cross-
Reference File
Growth Factor File
' '
t
PtGrowCntl: MACRO GROW
Ti J " 4. * A .C1 T» J Orf"*/"1! A
Keaus point source inventory tile. Keaas oL-U to
SIC cross-reference file. Assigns missing SIC
codes in inventory from cross-reference file.
T3 A it. f * C\ A _it_
Keaus growtn tactor Hie. Assigns growtn
factors by SIC and state FIPS.
PtGrowCntl: MACRO APPLCNTL
Reads general MACT reduction control
information file and assigns control information
to emission records by MACT category. Reads
specific process/pollutant MACT reduction
control information file and assigns control
information to emission records by MACT
category and pollutant and/or process codes.
Reads process/pollutant facility reduction
control information files and assigns control
information to emission records by process and
pollutant codes. Calculates projected emissions.
Figure 6-1. PtGrowCntl Flowchart
6-2
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6.1.1 Assigns and applies growth factors to project emissions due to growth
PtGrowCntl assigns a growth factor to each emission record based on each record's state FIPS
and the first two digits of the SIC code (PtGrowCntl does currently allow growth factors to be
specified for one three-digit SIC code: '371'). You can choose to have PtGrowCntl assign SIC
codes to those records in the inventory with missing values for SIC based on the inventory SCC
codes (see keyword DOSCC in Table 6-4 in Section 6.2.6). PtGrowCntl uses an ancillary SCC
to SIC cross-reference file (see Section 6.2.4) for this function.
PtGrowCntl uses growth factors, indexed by the state FIPS code and SIC, from an ancillary
growth factor file (see Section 6.2.3). The growth factor file is specific to both the base year and
future year. Each execution of PtGrowCntl results in an inventory file containing emissions
projected to that one future year. PtGrowCntl computes grown 3-hour emission rates from the
base year 3-hour emission rates for each record by multiplying the base year 3-hour emission
rates by the assigned growth factor, as follows.
Grown emissions = (Base year baseline emissions) x (Growth factor).
The same growth factor is applied to all eight 3-hour emission rates. Note that any record will be
assigned the default growth factor of one when there is no SIC code or when no match is found
in the growth factor input file. In these cases, or, if you choose not to grow the emissions, the
grown emissions will be unchanged from the base year emissions.
6.1.2 Assigns and applies emission reduction information to emissions
PtGrowCntl can assign emission reduction information several different ways; you choose the
method by specifying keywords in the batch file (see Table 6-4 in Section 6.2.6). You supply the
emission reduction information through ancillary files. You can supply information on a
MACT-category level (e.g., for wood furniture manufacturing), and/or on a facility level (e.g.,
for the ABC company). The emission reduction information includes not only control
efficiencies, but also information that tells PtGrowCntl whether and how to apply them to the
inventory emission records.
In the next sections we discuss the emission reduction information, provide details on how
PtGrowCtnl assigns it to the inventory records and present PtGrowCntl's computation of
controlled emissions.
6-3
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Emission Reduction Information
The emission reduction information you supply in the ancillary files consists of:
1. Two control efficiencies for the reduction strategy. One efficiency represents the
emission reduction to be applied to existing sources; the other represents the emission
reduction to be applied to new sources. PtGrowCntl gives you the flexibility to apply
different efficiencies for new versus existing facilities because air pollution regulations
often require a higher emission control efficiency for new facilities than for existing
facilities. PtGrowCntl assumes that all new point sources are located at existing point
sources. This would occur, for example, if an existing source rebuilt or constructed an
additional operation to the extent that it (or part of it) would be considered a new source.
2. The percentage of emissions at existing sources that will come from new sources.
PtGrowCntl uses this information to apportion the emissions into new source versus
existing source emissions for each inventory record. A value of 100% would mean that
in the future year, the entire MACT category (or specific facility) rebuilt to the extent that
the efficiency for new sources would apply. A value of 50% would signify half of the
emissions was due to new sources at the existing facilities and the other half was from the
existing part.
3. An application control flag. PtGrowCntl uses this to determine whether or not to apply
the control efficiencies. This enables you to keep the emission reduction information
you've put in an ancillary file, but not use it for a particular run of EMS-HAP.
The MACT-category level emission reduction information also includes:
4. A source control flag. This determines to which source type (major4 versus both areab
and major) the control efficiencies would apply. For example, if a particular MACT
standard affects only major sources, then you'd set the source control flag to "M" and the
efficiencies would only be applied to inventory records with a source type of "major".
5. The compliance year for the standard. PtGrowCntl uses this information along with the
projection year to determine whether or not the standard will affect the emissions. For
example, if you are projecting to 2002, and the compliance year of the standard is 2003,
then PtGrowCntl will not apply the reduction for that standard to the inventory.
6. The MACT bin. If the compliance year is not known, PtGrowCntl will use the MACT
bin, which indicates the number of years between 1990 and planned the promulgation
date of the MACT standard (2, 4, 7, or 10 years).
6-4
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Assignment of Emission Reduction Information
PtGrowCntl provides you with three ways to assign reduction information to the point source
inventory through the use of three ancillary files, MACT_gen.txt, MACT_spec.txt and
SITE_spec.txt (also discussed in Section 6.2.5). You can choose any combination of the
following assignment methods:
• General MACT category information based on MACT code alone. You can specify
general MACT reduction information through the MACT_gen.txt ancillary file. General
reduction information applies to an entire MACT category or MACT process (if the
process has a unique MACT code), but not to a particular facility or pollutant emitted by
the process. In addition, processes that don't have a unique MACT code, but are part of a
MACT standard (e.g., equipment cleaning process in wood furniture manufacturing),
can't be assigned emission reduction information through the MACT_gen file.
• Specific MACT category information based on MACT code and HAP and/or SCC. You
can specify process and/or pollutant specific MACT reduction information through the
MACT_spec.txt ancillary file. This file allows you to assign different reduction
information for different processes within a MACT category or for different HAPs that a
MACT standard will affect. For each MACT code, you can provide reduction
information by the following criteria: (1) 6-digit or 8-digit SCC codes alone, (2) 6-digit or
8-digit SCC codes along with the NTI_HAP variable, or (3) the NTI_HAP variable alone.
Note that you will need to use the specific information in conjunction with the general
information. This is because the MACT_spec file does not contain the required
compliance year or MACT bin information (but the MACT_gen file does). In addition,
you will likely not have process or pollutant/specific control efficiencies for every MACT
standard.
• Facility-level Reduction information based on the facility's activity ID (ACT_ID
variable and HAP. You can specify process and pollutant specific.facility-level reduction
information through the SITE_spec.txt ancillary file. This allows you to assign different
reduction information for different processes at a specific facility or for different HAPs
emitted by those processes at that facility. You can provide reduction information by
unique ACT_IDs or you can combine the ACTJDs with NTI_HAPs.
If you choose to specify information by all of these methods, and an individual inventory record
can be matched to the information in more than one ancillary file, the following hierarchy
applies: the process and/or pollutant specific MACT reduction information will supercede
information assigned by the MACT code alone. Reduction information assigned at the facility-
level will supercede any of the MACT category-based reduction information.
6-5
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Application of Emission Reduction Efficiencies
Based on the emission reduction information assigned to each inventory record, PtGrowCntl
determines whether to apply the new and/or existing control efficiencies to the grown and
temporally allocated emissions.
When MACT category-based emission reduction information is assigned to an inventory record
(i.e., no facility-specific reduction information exists for that inventory record), PtGrowCntl
applies a control efficiency to the emissions when the following criteria are met:
• The application control flag (MACT_APP) is equal to 1.
• The inventory source type variable (SRC_TYPE) is 'major' and the source control flag
(MACT_SRC) is 'M' or the inventory source type variable has any value and the source
control flag is 'B' (this value indicates that the reduction efficiency is applied to all
source types).
• The projection year is greater than the compliance year or, if the compliance year is not
provided, the projection year is greater than the MACT bin plus 1995.
If facility-based emission reduction information is assigned to an inventory record, PtGrowCntl
applies this reduction information to the emissions when the application control flag
(SITE_APP) is equal to 1.
PtGrowCntl computes projected emissions separately for the existing part and the new part of
emission records in the inventory, and then sums the values to determine the final projected
emissions. PtGrowCntl uses information on the percentage of grown emissions being emitted
from new part of sources that you supplied in the ancillary files (variable MACTRATE or
SITERATE, depending on whether MACT-based or facility-based information is being used,
respectively). As discussed earlier in the section, this percentage allows PtGrowCntl to
apportion the grown emissions to existing sources (e.g., 1-MACTRATE/100) to which the
control efficiency for existing sources is applied and new sources (e.g., MACTRATE/100) to
which the control efficiency for new sources is applied.
PtGrowCntl uses the baseline control efficiency (CNTL_EFF variable) included in the inventory
to account for any existing controls reflected in the emission inventory rates. Note that values
for the CNTL_EFF variable may or may not be missing in the inventory, but the inventory input
file must contain this variable for PtGrowCntl to execute successfully. If CNTLJ3FF is less than
the control efficiency in the ancillary file (variables MACTEXIS and MACT_NEW or
SITEEXIS and SITE_NEW), PtGrowCntl removes the baseline control prior to applying the
strategy control efficiency to the grown emissions. If the baseline control efficiency is greater
than the strategy control efficiency, we assume that the emission reduction in the ancillary file
will not affect the facility. Therefore, PtGrowCntl doesn't apply that control efficiency.
Table 6-1 shows the calculations for existing and new source projected emissions.
6-6
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Table 6-1. Summary of Equations used to Calculate Projected Emissions
Example calculations for MACT-based reductions;
substitute SITERATE, SITEEXIS, and SITE_NEW for facility-based reductions
Existing Sources
Strategy control efficiency > baseline control efficiency (Eq. 6-1)
Projected EmissionsE = Grown Emissions x (l-MACTRATE/100) x fl -MACTEXIS/lOO)
(1 - CNTL_EFF/100)
Baseline control efficiency > strategy control efficiency (Eq. 6-2)
Projected EmissionsE = Grown Emissions x (l-MACTRATE/100)
New Sources
Strategy control efficiency > baseline control efficiency (Eq. 6-3)
Projected Emissions,, = Grown Emissions x (MACTRATE/100) x (1 - MACT NEW/100)
(1 - CNTL_EFF/100)
Baseline control efficiency > strategy control efficiency (Eq. 6-4)
Projected EmissionsN = Grown Emissions x (MACTRATE/100)
Where:
Projected EmissionsE = grown and controlled emissions from existing sources
Projected EmissionsN = grown and controlled emissions from new sources
Grown Emissions = (Base year baseline emissions) x (Growth factor) [see Section 6.1.1]
MACTRATE = MACT-based percentage of grown emissions attributed to new sources
(SITERATE = facility-based percentage)
MACTEXIS = MACT-based control efficiency for existing sources
(SITEEXIS = facility-based control efficiency for existing sources)
MACT_NEW = MACT-based control efficiency for new sources
(SITE_NEW is the facility-based control efficiency for new sources)
CNTL_EFF = inventory baseline control efficiency
If no reductions are applied to the temporally allocated grown emissions, then the final projected
emissions are equal to the grown emissions.
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6.2 How do I run PtGrowCntl?
6.2.1 Prepare your point source inventory for input into PtGrowCntl
The point source inventory you use for input into PtGrowCntl must be the output of PtTemporal
(Chapter 5). Further, you must have run PtAspenProc (Chapter 4) prior to PtTemporal. This
inventory will contain at least the variables listed in Table 6-2. It may contain additional
variables such as the diagnostic flag variables (LFLAG, FIPFLAG, etc.) created by PtDataProc
depending on the options you chose for the windowing function in PtDataProc (see
Section 3.1.3).
Table 6-2. Variables in the PtGrowCntl Input Point Source Inventory SAS® File
Variables used by PtGrowCntl are in bold;
other variables listed are used by previously run or subsequent point source processing programs
Variable Name
ACT_ID
BLDH
BLDW
CNTL_EFF
COORJD
EMIS
EMRELPID
EMRELPTY
FIPS
IBLDG
IVENT
LAT
LON
MACTCODE
NTI_HAP
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process
ASPEN building height (in meters) (5 for horizontal stacks, 0 for all other
stacks); assigned hi PtAspenProc (see Section 4.1.3)
ASPEN building width (in meters) (5 for horizontal stacks, 0 for all other
stacks); assigned in PtAspenProc (see Section 4.1.3)
baseline control efficiency, expressed as a percentage
code identifying a unique set of geographic coordinates
pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01=fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck, 05=vertical
with rain cap, 06=downward-facing vent, AP=aircraft)
5-digit FIPS code (state and county combined)
ASPEN building code (1 for horizontal stacks, 0 for all other stacks) assigned in
PtAspenProc (see Section 4. 1 .3)
ASPEN vent type (0 for stacked sources, 1 for non-stacked sources) assigned in
PtAspenProc (see Section 4.1.3)
latitude (in decimal degrees)
longitude (in negative decimal degrees)
process or site-level MACT code
code identifying HAP on the Clean Air Act HAP list; assigned in PtAspenProc
(see Section 4. 1.1)
Type*
A25
N
N
N
A20
N
A50
A4
A5
Al
Al
N
N
A7
A3
6-8
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Table 6-2. Variables in the PtGrowCntl Input Point Source Inventory SAS® File
(continued)
Variable Name
POLLCODE
REACT
SAROAD
SAROADDC
sec
SCC_AMS
SIC
SITEJD
SRC_TYPE
STACKDIA
STACKHT
STACKVEL
STKTEMP
TAFATE1-
TAFATE8
TEMIS1-
TEMIS8
UFLAG
Data Description
(Required units or values are in parentheses)
unique pollutant code
pollutant reactivity class (1-9)
unique pollutant-group code; assigned in PtAspenProc (See section 4.1.1)
descriptive name for the SAROAD; assigned in PtAspenProc (see Section 4.1.1)
EPA source category code identifying the process
SCC or AMS code from the temporal allocation factor file identifying the
temporal profile used; assigned in PtTemporal
Standard Industrial Classification (SIC) code for the site
code identifying a unique site
description of the emission source at the site ('nonroad' for aircraft emissions)
If you choose to define ASPEN source groups by this variable as explained in
7.1.1, or run PtGrowCntl (Chapter 6) then it must have the value of 'major' or
'area' for non-aircraft emissions.
diameter of stack (meters)
height of stack (meters)
velocity of exhaust gas stream (meters per second)
temperature of exhaust gas stream (Kelvin)
temporal factors for the eight 3-hour periods of an average day; assigned in
PtTemporal
temporally allocated emissions for the eight 3 -hour periods of an average day
(grams/sec); calculated in PtTemporal
urban/rural dispersion flag (1 for urban, 2 for rural); assigned in PtAspenProc
(see Section 4. 1.2)
Type*
A10
N
A10
A50
A10
A10
A4
A20
A15
N
N
N
N
'N
N
N
*Ax = character string of length x, I = integer, N = numeric
6-9
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6.2.2 Determine whether you need to modify the ancillary input files for PtGrowCntl
An ancillary file is any data file you input to the program other than your emission inventory.
Table 6-3 lists the ancillary input files required for PtGrowCntl and when you may need to
modify them.
Table 6-3. Required Ancillary Input Files for PtGrowCntl
Name of File Provided Purpose
with EMS-HAP
Need to Modify
Format
gfXX_YY
(where XX specifies the
projection year and YY
specifies the base year)
ptscc2sic
MACT_gen*
MACT_spec*
SITE_spec*
Provides the assignment of year
specific growth factors by state and
SIC code.
Provides cross reference between
SCC codes and SIC codes for purpose
of assigning growth factors by state
and SIC code.
Provides emission reduction strategy
information by MACT category
Provides emission reduction strategy
information by MACT category and
SCC and/or HAP identification code
Provides emission reduction
information by the facility-specific
activity identification code and HAP
identification code
When growth factors are SAS*
needed for a different
projection year or base
year
When additional or Text
different SCC to SIC
cross-references are
needed to assign growth
factors
Develop by obtaining Text
MACT-based reduction
information
Develop by obtaining Text
MACT-based reduction
information
Develop if you have Text
facility specific emission
reduction information for
a future year
* These files are not currently being provided as part of EMS-HAP.
6.2.3 Modify the growth factor input file (gfXX_YY)
The growth factor file provides factors that are used to project the growth in emissions from the
base year of the emission inventory to a future year that is of interest in your control strategy
analysis. Each growth factor file consists of a series of records, with each record providing the
growth factor to be used for a particular industrial category (SIC) within a particular state. Thus,
each record includes a state FIPS code, an SIC code, and a growth factor that is applicable to that
state/SIC combination. Note that only the first two digits of the SIC code are used along with the
state FIPS to assign growth factors to the inventory records (PtGrowCntl does currently allow
growth factors to be specified for the three-digit SIC code '371'). The format for this file is
provided in Figure 19 of Appendix A.
Because you may want to use EMS-HAP to analyze a series of future years, you may have
6-10
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occasion to create a number of different growth factor files, with each separate version
addressing a different projection year. Only one version of the growth factor file can be used in a
particular run of EMS-HAP.
6.2.4 Modify the SCC to SIC cross-reference input file (ptscc2sic.txt)
PtGrowCntl uses the SCC to SIC cross-reference file for cases where there is no SIC contained
on the emission inventory record. This file consists of unique 8-digit SCC codes and the
corresponding 4-digit SIC code. Although many SCC codes can be assigned to the same SIC
code, only one SIC code can be assigned to a given SCC code. Note that only the first two digits
of the SIC code are used along with the state FIPS to assign growth factors to the inventory
records (PtGrowCntl does currently allow growth factors to be specified for the three-digit SIC
code '371'). The format for this file is provided in Figure 20 of Appendix A.
You would expect to modify this file depending on the SIC information included in your
emission inventory. Note that any records without an SIC code will be assigned the default
growth factor of one and, therefore, the grown emissions will be unchanged from the base year
emissions.
6.2.5 Develop the emission reduction information files (MACT_gen.txt, MACT_spec.txt,
and SITE_spec.txt)
These files are not currently being provided as part of EMS-HAP and, therefore, if you want to
apply emission reductions to your inventory, you will need to develop these files. These files
provide the reduction information needed to calculate the controlled emissions for the specified
projection year. This information was presented in Section 6.1.2.
In the general MACT control file (MACT_gen.txt), you provide the list of MACT categories that
will be addressed in your control strategy analysis. For each category, you provide the emission
reduction information described in Section 6.1.2 by MACT code. The format for the general
MACT control file is provided in Figure 2 la of Appendix A.
If you have control efficiencies for specific HAPs or specific processes within a MACT category,
use the specific MACT control file (MACT_spec.txt). In this file, you assign the reduction
information by MACT code and by either a process code alone, a HAP identification code
(NTI_HAP variable) alone, or by a process code and NTI_HAP together. The process code can
be in the form of a 6-digit SCC code or 8-digit SCC code. The format for the specific MACT
control file is provided in Figure 21b of Appendix A.
6-11
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In cases where an emission inventory record is affected by more than one record in the specific
MACT control file, the following order of precedence is followed in PtGrowCntl:
8-digit SCC and HAP code
6-digit SCC and HAP code
6-digit SCC alone
8-digit SCC alone
HAP code
For instance, a reduction information record that specifies an 8-digit SCC and NTI_HAP will
supercede a record that specifies a 6-digit SCC and NTI_HAP, and so on.
If you have control efficiencies for specific HAPs or specific processes within a specific point
source facility, you can use the specific facility control file (SITE_spec.txt). In this file, you can
assign the reduction information by either the facility-specific activity identification code
(ACTJD variable) alone or by the ACTJD and NTI_HAP variables together. The format for
the specific facility control file is provided in Figure 22 of Appendix A.
In cases where an emission inventory record is affected by more than one record in the specific
facility control file, the reduction information record that specifies the ACT_ID and NTI_HAP
will supercede a record that specifies ACT_ED alone. In addition, the specific facility control
information will supercede any of the MACT-based control information.
6.2.6 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for PtGrowCntl is shown in Figure 5 of
Appendix B.
Specify your keywords
Table 6-4 shows you how to specify keywords to select which functions you want PtGrowCntl to
perform. For example, if you want to factor in economic growth into your projection emissions,
set the DOGROW keyword to 1.
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Table 6-4. Keywords for Selecting PtGrowCntl Functions
PtGrowCntl Function
Keyword (values provided cause function to be
performed)
Assign and apply growth factors
Assign missing SICs by SCC to SIC cross-reference file
Assign and apply reduction information
Use general MACT reduction information only
Use process and/or pollutant specific MACT reduction
information only - this combination should only be
used if you are providing an input inventory file that
was already run through PtGrowCntl using general
MACT reduction information
Use facility-level reduction information only
Use general and process and/or pollutant specific
MACT reduction information
Use general MACT and facility-level reduction
information
Use process and/or pollutant specific MACT and
process and facility-level reduction information - this
combination should only be used if you are providing
an input inventory file that was already run through
PtGrowCntl using general MACT reduction
information
Use all reduction information
DOGROW = 1
DOSCC = 1
DOCNTL=1
GENCNTL = 1; PROCHEM = 0; SITECHEM = 0
GENCNTL = 0; PROCHEM = 1; SITECHEM = 0
GENCNTL = 0; PROCHEM = 0; SITECHEM = 1
GENCNTL = 1; PROCHEM = 1; SITECHEM = 0
GENCNTL = 1; PROCHEM = 0; SITECHEM = 1
GENCNTL = 0; PROCHEM = 1; SITECHEM = 1
GENCNTL = 1; PROCHEM = 1; SITECHEM = 1
Table 6-5 describes all of the keywords required in the batch file. You must include all
directory names, file names, and variable values even if they are related to a function that you do
not select to perform. For example, if you set DOGROW to 0, you still need to assign a value to
the keyword GF and SCC2SIC. The values provided in this circumstance do not need to
represent actual file names; they are merely a place holder for the keywords.
6-13
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Table 6-5. Keywords in the PtGrowCntl Batch File
Keyword
Description of Value
Input Inventor}' Files
IN_DATA The input SAS* file directory
INSAS Input inventory SAS* file name
Ancillary Files (Prefix of file name provided with EMS-HAP in parentheses)
REFSAS The reference SAS* file directory
REFTEXT The reference text file directory
SCC2SIC SCC to SIC cross-reference text file (ptscclsic)
GF Growth factors to SIC and state FIPS cross-reference SAS* file (gfXX_YY, where XX
specifies the projection year and YY specifies the base year)
MACTGEN General MACT-based emission reduction information text file prefix (MACT_gen)
MACTSPEC Specific MACT-based emission reduction information text file prefix (MACT_spec)
SITESPEC Specific facility-based emission reduction information text file prefix (SITE_spec)
Program Options (See also Table 6-4)
DOGROW l=project emissions as a result of economic growth; 0=don't grow emissions
DOSCC l=use SCC to SIC cross-reference file to assign SIC where missing in inventory; 0=don't
assign SIC where missing
DOCNTL l=project emissions as a result of emission reduction strategies; 0=don't apply emission
reduction strategies
GENCNTL l=Use general MACT emission reduction information; 0= don't use general MACT
information
PROCCHEM l=Use process and/or pollutant specific MACT emission reduction information; 0=don't use
process and/or pollutant specific MACT emission reduction information
SITECHEM l=Use facility emission reduction information; 0=don't use facility emission reduction
information
Additional Input Data
GROWYR Year to which emissions are to be grown
Output files
OUTDATA The output SAS* file directory
OUTSAS Output inventory SAS* file name
Prepare the execute statement
The last line in the batch file runs the PtGrowCntl program. In the sample batch file provided in
Figure 5 of Appendix B, you will see a line proceeding the run line that creates a copy of the
PtGrowCntl code having a unique name. It is this version of the program that is then executed in
the last line. If you do this, the log and list files created by this run can be identified by this
unique name. If you don't do this and run the program under a general name, every run of
PtGrowCntl will create a log and list file that will replace any existing files of the same name.
You may find that you need to define a special area on your hard disk to use as work space when
6-14
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running PtGrowCntl. In the sample batch file, a work directory is defined on the last line
following the execution of PtGrowCntl. The directory you reference here must be created prior
to running the program.. For example, the statement:
'sas PtGrowCntl_062000.sas -work /data/work 15/dyl/' assigns a work directory called
"/data/worklS/dyl".
6.2.7 Execute PtGrowCntl
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system.. For example,
'chmod u+x PtGrowCntl.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'PtGrowCntl.bat'.
6.3 How Do I Know My Run of PtGrowCntl Was Successful?
6.3.1 Check your SAS® log file
Review the output log file to check for errors or other flags indicating incorrect processing. To
do this, search the log file for occurrences of the strings "error", "warning", "not found", and
"uninitialized". These can indicate problems with input files or other errors.
You can look at the number of records in the input inventory file and compare it to the number of
records in the output inventory file. The number of records should be the same in these two
files.
6.3.2 Check your SAS® list file
The list file created when PtGrowCntl is executed contains information to assist in quality
assurance. The information is this file is listed below:
• Summary of inventory records assigned growth factors
• Summary of inventory records assigned general MACT reduction information
• Summary of inventory records assigned process and/or pollutant specific MACT
reduction information
• Summary of inventory records assigned facility-level reduction information; if MACT-
based reduction information is present, the summary includes MACT code, SCC, and
MACT-based reduction information.
6.3.3 Check other output files from PtGrowCntl
You should check for the existence of the output inventory file named by keyword OUTSAS.
This file will serve as the input to PtFinalFormat, the last point source processing program you
run.
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CHAPTER 7
Point Source Processing
The ASPEN Final Format Program (PtFinalFormat)
PtFinalFormat is the final point, source processing program you run (see Figure 1-1). You can
run PtFinalFormat after PtTemporal, to create base year emission input files, or after
PtGrowCntl, to create future year emission input files.
7.1 What is the function of PtFinalFormat?
The ASPEN Final Format Processing Program (PtFinalFormat) creates the emission input files
for the ASPEN model. PtFinalFormat performs the functions listed below.
• Assigns ASPEN source groups used in the ASPEN model output
• Creates ASPEN input files, a column formatted text file and a SAS® file
You control whether to have PtFinalFormat write out the ASPEN input and column formatted
text files in your execution of PtFinalFormat. Table 7-4 in Section 7.2.4 details how to do this.
Figure 7-1 shows a flowchart of PtFinalFormat. The following sections describe the above
bullets.
7-1
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Batch File Containing
Keywords e.g. File Names
and Locations, Program
Options
Point Source Inventory File
Source Group by MACT
Category File
Source Group by SCC File
Source Group by SIC File
Reactivity Class Decay Rate
File
Reads Keywords
PtFinalFormat: MACRO GROUPSET
Reads point source inventory file. Depending
on program options, reads source group by
MACT category file, source group by SCC file,
and/or source group by SIC file. Assigns
source group as instructed by program options.
PtFinalFormat: MACRO FORMAT
Reads reactivity class decay rate file. Creates
ASPEN input emission files for each reactivity
class.
PtFinalFormat: MACRO ASCII2
Creates ASCII text version of data written to
ASPEN input emission files.
Figure 7-1. PtFinalFormat Flowchart
7-2
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7.1.1 Assigns ASPEN source groups used in the ASPEN model output
The ASPEN model computes concentrations by source groups which can be used to analyze the
relative impacts of different types of emissions sources. ASPEN can use up to 10 source groups.
PtFinaLFormat can assign ASPEN source groups several different ways. You choose the method
based on the keywords you specify in your batch file (see Table 7-4 in Section 7.2.4).
PtFinalFormat can use the source type variable (SRCJTYPE), the MACT category code variable
(MACTCODE), the 6-digit SCC and/or the SIC. Table 7-1 shows how PtFinalFormat assigns
the source group by SRCJTYPE.
Table 7-1. Assignment of ASPEN Source Groups
Value of Description . Source Group
SRCJTYPE Assignment
Variable
major major source of HAPs based on definition in 0
Section 112 of Clean Air Acta
area area source of HAPs based on definition in 1
Section 112 of Clean Air Actb
nonroad nonroad mobile source emissions (these are the 3
allocated aircraft emissions)
" "...any stationary source or group of stationary sources located within a contiguous area and under common
control that emits or has the potential to emit considering controls, in the aggregate, 10 tons per year or more of any
hazardous pollutant or 25 tons per year or more of any combination of hazardous air pollutants..."
b "...any stationary source of hazardous air pollutants that is not a major source... shall not include motor vehicles or
nonroad vehicles subject to regulation under title II.."
In point source processing, the only nonroad sources you would have in your point source
inventory are allocated airport emissions obtained from running AirportProc (see Chapter 2).
If you choose to assign the source group by the MACT category, the 6-digit SCC and/or the SIC,
PtFinalFormat uses the appropriate ancillary file (mact_grp, SCC_grp and/or SIC_grp) based on
your assignment method. These files contain the group assignment value (which can be 0
through 9) by code. See Section 7.2.3 for instructions on how to modify these files if you
choose to assign your groups this way. If you choose to assign the source group by more than
one method, PtFinalFormat uses a set hierarchy. The MACT category assignment would replace
a source type assignment. An SCC or SIC assignment would replace either a source type or
MACT category assignment. 'The assignment of groups by both SCC and SIC have an
associated ranking that control when the SIC assignment replaces the SCC assignment. If, for
any record in your inventory, no source group assignment is made by the above methods, a
default source group is assigned. You specify the value for this default in your batch file
(Section 7.2.4, see keyword DFLTGRP in Table 7-5).
7-3
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7.1.2 Creates ASPEN input files, a column formatted text file and a S'AS®file
PtFinalFormat can create three different types output files:
1. The ASPEN input files
2. A column formatted ASCII text file
3. A SAS* output file.
You control whether or not to create the ASPEN input and column formatted text file in your
execution of PtFinalFormat, based on the keywords you specify in your batch file (see Table 7-4
in Section 7.2.4). PtFinalFormat automatically creates the SAS® output file.
ASPEN Input Files
The ASPEN model requires emission data in the form of one ASCII text file for each of the
possible nine reactivity class. PtFinalFormat creates all nine files in the appropriate format.
Each text file consists of a header and body. The elements of the header are:
1.. A run identifier: You supply this in the batch file (keyword RUNID in Table 7-5)
2. Wet and dry deposition codes: PtFinalFormat sets these to t) for particulates and 1 for
gaseous species. These values tell ASPEN whether to invoke the deposition algorithm for
particulates (ASPEN does not perform deposition for gases).
3. Decay coefficients associated with the reactivity class: PtFinalFormat determines these from
the ancillary file indecay.txt based on the value of the REACT variable (discussed in detail in
Chapter 4, Section 4.2.3). This file contains a set of coefficients for each of the nine
reactivity classes.
The file body contains source information such as latitude and longitude, source characteristics
such as stack height, building width, and vent type, and the emissions for each of eight 3-hour
periods for each pollutant (of the appropriate reactivity class) emitted from the stack.
PtFinalFormat names the nine ASPEN input files in the form "OUTCODE.rREACT.inp" where
OUTCODE is the file identifier keyword you provide in the batch file, and REACT is the
reactivity class (a number 1-9). An example file name is "Pt96.US.D121599.rl.inp" where
OUTCODE is "P196.US.D121599" and REACT is "1".
Column Formatted ASCII File
PtFinalFormat can create a single column formatted ASCII text file containing data written to the
ASPEN input emissions files. This file can provide easy access to the data for quality assurance
purposes. You specify the prefix name of this file in your batch file (keyword ASCII in Table 7-
5); the suffix is "txt". Table 7-6 in Section 7.3.3 shows the format of this file.
7-4
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SASt* Output File
PtFinalFormat automatically creates an output SAS® inventory file. This file contains the same
data as in the input SAS® inventory file except that the source group variable (GROUP) has been
added. You specify the name of this file in your batch file (keyword OUTS AS in Table 7-5).
7.2 How do I run PtFinalFormat?
7.2.1 Prepare your point source inventory for input into PtFinalFormat
The point source inventory you use for input into PtFinalFormat can be the output from either
PtTemporal (see Chapter 5) or PtGrowControl (see Chapter 6). In either case, if you've followed
the run stream of Figure 1-1, the inventory will meet all requirements. This file will contain at
least the variables shown in Table 7-2. It may contain additional variables such as the diagnostic
flag variables (LFLAG, FIPFLAG, etc.) created by PtDataProc depending on the options you
chose for the windowing function in PtDataProc (see Section 3.1.3).
Table 7-2. Variables in the PtFinalFormat Input Point Source Inventory SAS® File
Variable Name
ACTJD
BASEMIS1-
BASEMIS8b
BINb
BLDH
BLOW
CNTL_EFFa
COMPLYRb
COORJD
EMIS
EMRELPID
EMRELPTY
FIPS
Data Description
(Required units or values are in parentheses)
code identifying a unique activity within a process at a unique site
temporally allocated baseline emissions for the eight 3-hour periods of an average
day (grams/sec); assigned in PtGrowCntl
number of years between 1990 and planned the promulgation date of the MACT
standard (2,4,7, or 10 years); assigned in PtGrowCntl (see Section 6.1.2)
ASPEN building height (in meters) (5 for horizontal stacks, 0 for all other
stacks); assigned in PtAspenProc (see Section 4. 1 .3)
ASPEN building width (in meters) (5 for horizontal stacks, 0 for all other stacks);
assigned in PtAspenProc (see Section 4.1.3)
baseline control efficiency, expressed as a percentage
compliance year of MACT standard; assigned in PtGrowCntl (see Section 6.1.2)
code identifying a unique set of geographic coordinates
baseline pollutant emissions value (tons/year)
code identifying a unique emission point within an activity
physical configuration code of release point
(01=fugitive; 02=vertical stack; 03=horizontal stack, 04=goose neck, 05=vertical
with rain cap," 06=downward-facing vent, AP=aircraft)
5-digit FIPS code (state and county combined)
Type*
A25
N
A2
N
N
N
A4
A20
N
A50
A4
A5
7-5
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Table 7-2. Variables in the PtFinalFormat Input Point Source Inventory SAS® File
(continued)
Variable Name
GFb
IBLDG
IVENT
LAT
LON
MACT_APPb
MACTCODE
MACTEXISb
MACT_NEWb
MACTRATEb
MACT_SRCb
NTI_HAP
POLLCODE
REACT
SAROAD
SAROADDC
sec
SCC_AMS
SETSIC"
Data Description
(Required units or values are in parentheses)
Growth factor; assigned in PtGrowCntl (see Section 6.1.1)
ASPEN building code (1 for horizontal stacks, 0 for all other stacks) assigned in
PtAspenProc (see Section 4.1.3)
ASPEN vent type (0 for stacked sources, 1 for non-stacked sources) assigned in
PtAspenProc (see Section 4.1 -.3)
latitude (in decimal degrees)
longitude (in negative decimal degrees)
flag indicating whether or not the MACT-based controls should be applied (0 to
not apply, 1 to apply control); assigned in PtGrowCntl (see Section 6.1.2)
process or site-level MACT code
MACT-based control information: Control efficiency for existing sources;
assigned in PtGrowCntl (see Section 6.1.2)
MACT-based control information: Control efficiency for new sources; assigned
in PtGrowCntl (see Section .6. 1.2)
MACT-based control information: Percentage of grown emissions attributed to
new sources; assigned in PtGrowCntl (see Section 6.1.2)
flag indicating to which source types the MACT-based controls should be applied
(M for major sources only, B for all source types); assigned in PtGrowCntl (see
Section 6. 1.2)
code identifying HAP on the Clean Air Act HAP list; assigned in PtAspenProc
(see Section 4. 1.1)
unique pollutant code
pollutant reactivity class (1-9)
unique pollutant-group code; assigned in PtAspenProc (see Section 4.1.1)
descriptive name for the SAROAD; assigned in PtAspenProc (see Section 4.1.1)
EPA source category code identifying the process
SCC or AMS code from the temporal allocation factor file identifying the
temporal profile used; assigned in PtTemporal
SIC assigned by cross-reference to SCC for use in' assigning growth factors;
assigned in PtGrowCntl (see Section 6.1.1)
Type*
N
Al
Al
N
N
Al
A7
N
N
N
Al
A3
A10
N
A10
A50
A10
A10
A4
7-6
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Table 7-2. Variables in the PtFinalFormat Input Point Source Inventory SAS® File
(continued)
Variable Name
Data Description
(Required units or values are in parentheses)
Type*
SIC Standard Industrial Classification (SIC) code for the site A4
SITE_APPb flag indicating whether or not the facility-based controls should be applied (0 to Al
not apply, 1 to apply control); assigned in PtGrowCntl (see Section 6.1.2)
SITEEXISb Facility-based control information: Control efficiency for existing sources; N
assigned in PtGrowCntl (See Section 6.1.2)
SITE_ID code identifying a unique site A20
SITE_NEWb Facility-based control information: Control efficiency for new sources; assigned N
in PtGrowCntl (see Section 6.1.2)
SITERATEb Facility-based control information: Percentage of grown emissions attributed to N
new sources; assigned in PtGrowCntl (see Section 6.1.2)
SITE_SRCb flag indicating to which source types the facility-based controls should be applied Al
(M for major sources only, B for all source types); assigned in PtGrowCntl (see
Section 6.1.2)
SRC_TYPE description of the emission source at the site ('nonroad' for aircraft emissions) If A15
you choose to define ASPEN source groups by this variable as explained in 7.1.1,
or run PtGrowCntl (Chapter 6) then it must have the value of 'major' or 'area' for
non aircraft emissions.
STACKDIA diameter of stack (meters) . N
STACKHT height of stack (meters) N
STACKVEL velocity of exhaust gas stream (meters per second) N
STKTEMP temperature of exhaust gas stream (Kelvin) N
TAFATE1 - temporal factors for the eight 3-hour periods of an average day; assigned in N
TAFATE8 PtTemporal
TEMIS1 - temporally allocated emissions for the eight 3-hour periods of an average day N
TEMIS8 (grams/sec); calculated in PtTemporal, unless emissions projections were done in
which case, values represent temporally allocated projected emissions calculated
in PtGrowCntl
UFLAG urban/rural dispersion flag (1 for urban, 2 for rural); assigned in PtAspenProc (see N
Section 4.1.2)
* Ax = character string of length x, I = integer, N = numeric
' required only if you run the optional Growth and Control Program (Chapter 6)
b variable present only if you run the optional Growth and Control Program (Chapter 6)
7-7
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7.2.2 Determine whether you need to modify the ancillary input files for PtFinalFonnat
An ancillary file is any data file you input to the program other than your emission inventory.
Table 7-3 lists the ancillary input files required for PtFinalFonnat and when you may need to
modify them.
Table 7-3. Required Ancillary Input Files for PtFinalFormat
Name of File
Provided with
EMS-HAP
Purpose
Need to Modify?
Format
mact_grp.txt Provides the assignment of ASPEN
source groups by MACT code.
scc6_grp.txt Provides the assignment of ASPEN
source groups by 6-digit SCC and a
rank code used to determine if the
source group can be replaced by a SIC-
based source group
sic_grp.txt Provides the assignment of ASPEN
source groups by SIC and a rank code
used to determine if the source group
can replace a SCC-based source group
indecay.txt Provides decay coefficients for 6
stability classes for the eight 3-hour
time periods for up to 9 reactivity
classes
If you want to make Text
different source group
assignments by MACT code
If you want to make Text
different source group
assignments by SCC code
If you want to make Text
different source group
assignments by SIC code
No Text
7.2.3 Modify the ASPEN source group assignment files (mactjgrp.txt, scc6_grp.txt, and
sic_grp.txt)
The ASPEN model output presents data for each pollutant by census tract and by source group.
The source group assignment you make in PtFinalFonnat will determine how ASPEN will group
the concentration estimates. You can control this assignment based on the source type using the
SRC_TYPE variable (as was discussed in 7.1.1) and/or by using any one of the three ASPEN
source group assignment files. The specific formats for these files are presented in Appendix A,
Figures 23-25. The mact_grp.txt is a simple text file that has a MACT code followed by a source
group code (number between 0 and 9, inclusive). To modify it, put the same group code next to
each MACT code that you want in the same group. If you choose to use this file in combination
with either of the other two files, it is important to remember that a MACT code-based
assignment will automatically replace a source type-based assignment and will automatically be
replaced by either an SCC-based or SIC-based assignment.
7-8
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If you want to use both SCC-based assignments and SIC-based assignments, you can control
whether or not the SIC-based assignment replaces the SCC-based assignment by setting the rank
field in each file. These files contain the SCC or SIC code followed by the source group,
followed by the rank. If an inventory record contains both SCC and SIC codes, the SCC
assignment is made first. If an assignment can also be made by SIC, the SIC-based assignment
will only replace the SCC-based assignment if the SIC rank is lower than the SCC rank (e.g. an
SIC rank of 1 and a SCC rank of 3 will result in the SCC-based assignment to be replaced by the
SIC-based assignment of the source group).
7.2.4 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for PtFinalFormat is shown in Figure 6 of
Appendix B.
Specify your keywords
Table 7-4 shows you how to specify keywords to select PtFinalFormat functions.
Table 7-4. Keywords for Selecting PtFinalFormat Functions
PtFinalFormat Function Keyword (values provided cause function to be
performed)
Assign ASPEN source groups
by source type DOSOURCE = 1
by MACT code DOMACT = 1
by SCC DOSCC = 1
by SIC DOSIC = 1
Create ASPEN input files DOWRITE = 1
Create single text-formatted file DOASCII = 1
Table 7-5 describes all of the keywords required in the batch file. In addition to supplying all
input and output file names and directories and program options, you must also supply additional
input data (see "Additional Input Data" section in Table 7-5). You must supply a value for
keyword ITYPE, which tells ASPEN whether your sources are point or pseudopoint sources.
Always set ITYPE to 0 (which signifies point source).
7-9
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Table 7-5. Keywords in the PtFinalFormat Batch File
Keyword
Description of Value
Input Inventory Files
IN_DATA Input SAS* file directory
INSAS Input inventory SAS* file name
Ancillary Files (Prefix of file name provided with EMS-HAP in parentheses)
REFFILES Ancillary file directory
MACTGRP MACT code to source group correspondence text file prefix (mact_grp)
SCCGRP SCC code to source group correspondence text file prefix (scc6_grp)
SICGRP SIC code to source group correspondence text file prefix (sic_grp)
DECAY Reactivity class decay coefficients for 6 stability classes for eight 3-hour time periods
(indecay)
Program Options (see also Table 7-4)
DOSOURCE 1= assign source group by source type; 0=don't assign by source type
DOMACT l=assign source group by MACT category code; 0=don't assign by MACT
DOSCC l=assign source group by SCC code; 0=don't assign by SCC
DOSIC l=assign source group by SIC code; 0=don't assign by SIC
DOWRITE l=create ASPEN input emission files; 0=don't create ASPEN input files
DOASCII l=create column-formatted ASCII text output file; 0=don't create column-formatted ASCII
text output file
Additional Input Data
DFLTGRP Default source group (must be an integer between 0 and 9, inclusive)
OUTCODE File identifier included in name of ASPEN input emission files (limit of 10 characters is
recommended. Additional characters will be truncated from the file header, not the file
name)
ITYPE ASPEN Source type (0 for point sources)
RUNID Run identifier included in ASPEN input emission file header (limit of 25 characters is
recommended. Additional characters will be truncated)
Output files
OUTDATA Output SAS* file directory
OUTSAS Output inventory SAS* file name
OUTFILES Output ASPEN emission files directory
ASCIIFILE Output ASCII text file directory
ASCII Column-formatted ASCII text file name
You must include all directory names, file names and variable values even if they are related to a
function that you do not select to perform. For example, if you set DOMACT to "0", you still
need to assign a value to keyword MACTGRP in your batch file. The value provided in this
circumstance does not need to represent an actual file name; it is merely a place holder value for
the keyword.
7-10
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Prepare the execute statement
The last line in the batch file runs the PtFinalFormat program. In the sample batch file provided
in Appendix B, you will see a line preceding the run line that creates a copy of the PtFinalFormat
code with a unique name. It is this version of the program that is then executed in the last line.
If you do this, the log and list files created by this run can be identified by this unique name. If
you don't do this and run the program under a general name, every run of PtFinalFormat will
create a log and list file that will replace any existing files of the same name.
You may find that you need to assign a special area on your hard disk to use as work space when
running PtFinalFormat. In the sample batch file, a work directory is defined on the last line
following the execution of PtFinalFormat. For example, the command
'sas PtFinalFormat_062000.sas -work/data/work 15/dyI/' assigns a WOfk directory Called
"/data/work 15/dyl". The directory you reference must be created prior to running the program.
7.2.5 Execute PtFinalFormat
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x PtFinalFormat.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute
the batch file by typing the file name on the command line, for example, 'PtFinalFormat.bat'.
7.3 How Do I Know My Run of PtFinalFormat Was Successful?
7.3.1 Check your SAS? log file
You need to review the output log file to check for errors or other flags indicating incorrect
processing. This review should include searching the log files for occurrences of the strings
"error", "warning", "not found", and "uninitialized". These can indicate problems with input
files or other errors.
You can look at the number of records in the input inventory file and compare it to the number of
records in the output SAS® inventory file. The number of records should be the same in these
two files.
7.3.2 Check your SAS?* list file
This program does not create a list file.
7-11
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7.3.3 Check other output files from PtFinalFormat
PtFinalFormat can create several different output files. It automatically creates an output S AS®
inventory file, named by keyword OUTSAS. This file contains the same data as in the input
SAS® inventory file except that the source group variable has been added. If you set the
DOWRITE keyword to "1", PtFinalFormat will create nine ASPEN input emissions files, one for
each possible reactivity class. You should check that all nine files were created and that
emission data are included only in those files representing reactivities classes for which you
know your inventory has emission data. You may also want to check the header of the files for
the decay rate information. If you set the DO ASCII flag to "1", PtFinalFormat will create a
single column formatted ASCII file which can be helpful in checking the quality of the ASPEN
input emission data. Table 7-6 provides the variables in this file.
7-12
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Table 7-6. FinalFormat Output ASCII File Variables
Variables and Data Description Type*
(Units or values are in parentheses)
FIPS: 5-digit FIPS code; state and county combined A5
PLANTJD: ASPEN plant ID (first 10 characters of EMS-HAP ACTJD) A10
LON: point source longitude (negative decimal degrees) 10.5
LAT: point source latitude (decimal degrees) 8.5
ITYPE: ASPEN source type, 0 for point, 3 for pseudopoint (0) Al
UFLAG: urban/rural dispersion flag (1 for urban, 2 for rural) 1.
STACKID: ASPEN Stack ID (derived from EMS-HAP EMRELPID) A5
STACKHT: height of stack (meters) 6.1
STACKDIA: diameter of stack (meters) 6.2
STACKVEL: velocity of exhaust gas stream (meters per second) 6.1
STKTEMP: temperature of exhaust gas stream (Kelvin) 6.1
SAROAD: unique pollutant-group code A5
GROUP: ASPEN source group (integer between 0 and 9, inclusive) Al
TEMISA1: Emissions rate (grams/second) for the first 3-hour time period E10.
TEMISA2: Emissions rate, time period 2 E10.
TEMISA3: Emissions rate, time period 3 E10.
TEMISA4: Emissions rate, time period 4 E10.
TEMISA5: Emissions rate, time period 5 E10.
TEMISA6: Emissions rate, time period 6 E10.
TEMISA7: Emissions rate, time period 7 E10.
TEMISA8: Emissions rate, time period 8 E10.
SITEJD: Identifies a unique site A20
ACT_ID: Identifies unique activity within a process A25
* Ax = character string of length x, x.y = numeric format with y places right of decimal, Ex. = exponential
7-13
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CHAPTER 8
Area Source Processing
The Area Source AMProc Preparation Program
(AreaPrep)
AreaPrep is the first program used in EMS-HAP for the processing of an area source inventory
(see Figure 1-1). The output inventory from this program is fed into the Area and Mobile Source
Processor (AMProc).
8.1 What is the Function of AreaPrep?
The Area Source AMProc Preparation Program (AreaPrep) is used to prepare an area source
emission inventory for the Area and Mobile Source Processor (AMProc). AreaPrep performs the
following functions:
• Assigns a spatial surrogate for each area source category for subsequent spatial
allocation of county-level emissions to census tracts
• Assigns a code to each source category for matching to temporal profiles
• Creates inventory variables required by AMProc
Figure 8-1 shows a flowchart of AreaPrep. The following sections describe the above bullets.
8-1
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Batch File Containing
Keywords e.g. Filenames and
Locations
Area Source Inventory File
Cross-Reference /
Spatial Surrogate Files
SIC-to-AMS
SCC-to-AMS
MACT-to-AMS
AMS Surrogates
Temporal Allocation
Factor File
Reads Keywords
i
Reads emissions
Prints emissions tracking summary
Verifies that emissions units are all tons/year
Converts format of source category codes to
standard AMS/SCC codes.
Prints frequencies of pollutants and source
categories. Prints emissions totals by source
category, by pollutant, and by state.
Merges spatial surrogate codes into the
emissions file using MACT, SIC, SCC, AMS
precedence. Prints list of spatial surrogates
which will be needed.
Checks for source categories with no temporal
allocation factors
Prints emissions tracking summary
1
Prints emissions summaries
I
; Output Area Source Inventory Filelfofs'AMProc j
Figure 8-1. AreaPrep Flow Chart
8-2
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8.1.1 Assigns a spatial surrogate for each area source category for subsequent spatial
allocation of county-level emissions to census tracts
AreaPrep assigns spatial surrogates to be used for spatial allocation in AMProc. Emission
processors use surrogates for spatial allocation of county-level emissions based on the premise
that the geographic distribution of particular surrogates is similar to the geographic distributions
of emissions from particular source categories.
Emission processors usually assign spatial surrogates to source categories extracted from the 10-
digit AMS code. Because we designed EMS-HAP based on the 1996 NTI, it can assign spatial
surrogates to area source categories using a variety of codes that may be in the area source
inventory. These are: the MACT code, the SIC code, the SCC code or the AMS code. In
addition, shortened AMS codes (4- or 7-digit) and SCC codes (3- or 6-digit) can be used for
general categories of emissions; you may assign surrogates based on these. We designed EMS-
HAP to use these other codes in addition to AMS for two reasons. First, in the 1996 NTI, the 10-
digit AMS code is missing for some area source categories; in these cases the categories will
have a non-missing MACT, SIC or SCC code. Second, these codes (MACT, SIC, SCC) tend to
be more defined than the AMS code that is in the 1996 NTI, and are therefore more useful for
assigning spatial surrogates. When a specific area source category contains multiple codes,
AreaPrep uses the following hierarchy to select the spatial surrogate: MACT code, SIC code,
SCC code, and AMS code. We determined that this hierarchy provided the best match of area
source category to available spatial surrogate for the 1996 NTI, because of the level of detail
provided in that inventory by the different classification codes. The MACT category code
provides the most detail, followed by the SIC, SCC, and AMS codes. Note that even though
AreaPrep was designed based on the 1996 NTI, it is sufficiently general to assign surrogates for
any emission inventory. For example, AreaPrep will assign surrogates to your area source
inventory based solely on AMS code, if the data for all of the other codes are missing.
AreaPrep makes surrogate assignments through the use of ancillary files (see Section 8.2.3 for
directions on how you would modify these files). Each record provides the spatial surrogate that
should be used for the applicable code. If AreaPrep can't assign a spatial surrogate to a source
category (because either the source category has no codes or the codes it has are not contained in
your ancillary files) then AreaPrep prints out a warning in your output SAS® list file and assigns
this category to population (spatial surrogate code 20).
The actual implementation of the spatial surrogates to allocate county-level emissions to the
census tracts (as required by ASPEN) is performed in AMProc (see Section 10.1.2 in Chapter
10). Table 8-1 gives a description of available spatial surrogates in the EMS-HAP ancillary files
and their corresponding spatial surrogate code. Information on how we developed the spatial
allocation factors for these surrogates is provided in Appendix D (D.10).
8-3
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Table 8-1. Surrogates for Spatially Allocating Emissions from Counties to Census Tracts
Code Surrogate
Definition
Origin of data
1 Residential land
2 Commercial land
3 Industrial land
4 Utility land
6 Sum of commercial land
and industrial land
7 Farm land
8 Orchard land
9 Confined feeding
10 Farm land & confined
feeding
12 Rangeland
13 Forest land
14 Rangeland & forest land
15 Water
17 Mining & quarry land
18 Inverse population
density
19 Inverse population
density
20 Population
21 Railway miles
22 Roadway miles
24 50% Population & 50%
roadway miles
25 25% Population & 75%
roadway miles
26 Tract area
27 Urban - inverse
population density (18)
Rural - farmland
28 Urban - population
Rural - tract area
29 Sum of farmland and
orchard land
USGS land use categories: Residential, plus one-third of mixed urban mid-70's to 80's
and built-up land plus one-third of other urban and built-up land
USGS land use categories: Commercial and services, plus one-half of mid-70's to 80's
industrial and commercial complexes, plus one-third of mixed urban and
built-up land plus one-third of other urban and built-up land
USGS land use categories: industrial, plus one-half of industrial and mid-70's to 80's
commercial complexes, plus one-third of mixed urban and built-up land,
plus one-third of other urban and built-up land
USGS land use category: "transportation, communications, and utilities" mid-70's to 80's
Sum of commercial land and industrial land, as defined above mid-70's to 80's
USGS land use category: "cropland and pasture" mid-70's to 80's
USGS land use category: "orchards, groves, vineyards, nurseries, and mid-70's to 80's
ornamental horticultural areas"
USGS land use category "confined feeding" mid-70's to 80's
USGS land use categories "cropland and pasture" plus "confined feeding" mid-70's to 80's
USGS land use categories: "herbaceous rangeland" plus "scrub and mid-70's to 80's
brush" plus "mixed rangeland"
USGS land use categories: "deciduous forest" plus "evergreen forest" mid-70's to 80's
plus "mixed forest land"
Sum of rangeland and forest land, as defined above mid-70's to 80's
US Census category: water area 1990
USGS land use category: "strip mines, quarries, and gravel pits" mid-70's to 80's
Inverse (reciprocal) of: census tract population (20-defined below) 1990
divided by censuslract area. Tracts with zero population assigned spatial
factors of zero.
Inverse (reciprocal) of: census tract population (20 -defined below) 1990
divided by census tract land area. Tracts with zero population assigned
tract population of one.
U.S. Census category: 1990 residential population 1990
Total railway miles, as reported in TIGER/Line 1993
Total miles of all roadway types in each census tract, as reported in 1993
TIGER/Line
Surrogate based equally on population and on roadway miles 1990-93
Surrogate based on population and roadway miles, weighted by 25% and 1990-93
75% respectively
The area of census tracts (includes land and water) 1990
inverse population density (18) for urban counties; 1990,
farmland for rural counties mid-70's to 80's
Population (20) for urban counties, tract area (26) for rural counties 1990
Sum of farmland and orchard land, as defined above mid-70's to 80's
8-4
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8.1.2 Assigns a code to each source category for matching to temporal profiles
As with spatial surrogate assignments, EMS-HAP uses the various codes (MACT, SIC, SCC and
AMS) that may be present in the inventory to match inventory records with temporal profiles.
To do this, AreaPrep assigns an additional code to each inventory record. We refer to this code
in this documentation as the AMS_SCC code (although AMProc names it the AMS code)
because it can be either a 10-digit AMS code or an 8-digit SCC code. The next area source
processing program you run, the Area and Mobile Source Processor (AMProc) uses this code to
match each record to an appropriate temporal profile. AreaPrep assigns this code the same way it
assigns a spatial surrogate (i.e., using either the existing MACT code, SIC, SCC or AMS in the
inventory along with the ancillary files discussed in Section 8.2.3.) The AMS_SCC can
overwrite the AMS code in the inventory. This will happen if the inventory record has values for
both the AMS and another code (MACT, SIC or SCC) due to the fact that the inventory AMS is
at the bottom of the hierarchy for this assignment. If a record has only a value for the inventory
AMS, and no other code, then the assigned AMS_SCC will equal the inventory AMS. If a
particular source category has no codes, or the codes it has are not contained in your ancillary
files, then AreaPrep assigns the code a value of1111111. The Area and Mobile Source Processor
(AMProc) will eventually assign these source categories a uniform temporal profile.
AreaPrep also reads in the temporal allocation factor (TAP) ancillary input file, and gives you
diagnostic information (See 8.3.2) regarding how the profiles in the TAP file match to the
assigned AMS_SCC codes. The TAF file used here is the same as the one used for point source
temporal allocation and is discussed in detail in Chapter 5. If there are source categories with no
temporal allocation factor assignments, AreaPrep provides a warning that these categories will be
assigned a uniform temporal profile.
8.1.3 Creates inventory variables required by AMProc
AreaPrep creates the 5-character STCOUNTY variable by concatenating the 2-digit STATE and
the 3-digit COUNTY variables. It also creates the POLLCODE variable and sets its value equal
to the CAS variable. The area source inventory you input to AMProc (see Table 10-1) requires
these variables.
8.2 How do I run AreaPrep?
8.2.1 Prepare your area source inventory for input into AreaPrep
Your area source inventory must meet the following requirements:
It must be in SAS® file format.
• It must contain, at a minimum, the variables listed in Table 8-2, with units and values as
provided. Additional variables will not be present in the output inventory file.
• All data records should be uniquely identifiable by using the combination of the state
ID (STATE), county ID (COUNTY), source category name (CAT_NAME), and
pollutant code (CAS).
8-5
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• It shouldn't contain Alaska and Hawaii emission records because EMS-HAP ancillary
files currently don't cover these areas.
Table 8-2. Variables Required in the AreaPrep Input Area Source Inventory SAS® File
Variable Name
AMS
CAS
CAT_NAME
COUNTY
EMIS
MACT
POL_NAME
sec
SIC
STATE
UNITS
Data Description
AMS code
unique pollutant code
area source emissions category name
county 3-digit FIPS code
emissions (tons/year)
MACT code
pollutant name
EPA source category code (SCC) identifying the
process
Standard Industrial Classification (SIC) code
state 2-digit FIPS code
emission units (tons/year)
Type*
A10
A10
A90
A3
N
A4
A50
A8
A4
A2
A6
*Ax = character string of length x, N = numeric
8.2.2 Determine whether you need to modify the ancillary input files for AreaPrep
An ancillary file is any data file you input to the program other than your emission inventory.
Table 8-3 lists the ancillary input files for AreaPrep. You may need to modify all of these files to
tailor them to your emission inventory (for example, if your inventory has a value for SIC not
contained in the sic2ams.txt file, or if you choose to use different spatial surrogate assignments
from those we provided) since they were developed based on the 1996 NTI. How to do this is
explained in the next section.
8-6
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Table 8-3. Ancillary Input Files for AreaPrep
File Name
Provided with
EMS-HAP
Purpose
Need to Modify?
Format
surrxref.txt Assigns each AMS code in the
emission inventory to a particular
spatial surrogate category
mact2ams.txt Assigns spatial surrogates and
AMS_SCC codes for temporal
allocation by MACT code
scc2ams.txt Assigns spatial surrogates and
AMS_SCC codes for temporal
allocation by SCC code
sic2ams.txt Assigns spatial surrogates and
AMS_SCC codes for temporal
allocation by SIC code
taff_hourly.txt Provides temporal profiles
containing 24 hourly temporal
allocation factors (TAFs) by
AMS and/or SCC (i.e.,
AMS_SCC) codes. These will be
applied in AMProc (Chapter 10)
If you choose to change the spatial surrogate text
assignments or have AMS codes in your
inventory not included in this file
If you choose to change the spatial surrogate text
or AMS_SCC assignments or have MACT
codes in your inventory not included in this
file
If you choose to change the spatial surrogate text
or AMS_SCC assignments or have SCC
codes in your inventory not included in this
file
If you choose to change the spatial surrogate text
or AMS_SCC assignments or have SIC codes
in your inventory not included in this file
If you choose to add or change the temporal text
allocation factors for a particular source
category
8.2.3 Modify the files that assign codes and spatial surrogates based on MACT, SIC, SCC,
and AMS codes
Figures 16, 17,27, and 28 in Appendix A give the structure and sample file contents of the
following respective spatial surrogate and AMS_SCC assignment files: scc2ams.txt, sic2ams.txt,
surrxref.txt, and mact2ams.txt. You can edit these text files to change the spatial surrogate
assignment or AMS_SCC assignment for a particular area source category or add a record for a
source category that is in your inventory, but not represented in these files. Table 8-1 gives a
description of available spatial surrogates and their corresponding spatial surrogate code.
Information on how we developed the spatial allocation factors for these surrogates is provided
in Appendix D(D. 10).
When you add or change an AMS_SCC code assignment in mact2ams.txt, sic2ams.txt or
scc2ams.txt files, you should look at the codes (and a description of the codes) in the temporal
allocation factor (TAP) file (see Appendix A, Figure 15). You want to make sure the codes you
change or add to the assignment files are present in the TAF file. Otherwise the AMS_SCC you
add will not match to a temporal profile.
8-7
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You don't need to change or add spatial surrogate and AMS_SCC assignments in all three
ancillary assignment files if a source category in your inventory is only represented by one of the
files. For example, if you have a source category in your inventory called "Consumer Products
Usage" and it is represented only by AMS code 2460000000 (i.e., all other codes are blank), you
only need to change the surrxref.txt file. Also, as discussed in Section 8.1.3, AreaPrep uses the
MACT code file first, followed by the SIC, SCC and AMS. So, if your category has all four
codes, make sure you modify the mact2ams.txt file first.
8.2.4 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for AreaPrep is shown in Figure 7 of
Appendix B.
Specify your keywords
Table 8-4 lists the keywords required in the batch file. Use keywords to provide a run identifier
and to locate and name all input and output files.
Table 8-4. Keywords in the AreaPrep Batch File
Keyword
RUNID
INPFILES
AREADATA
OUTFILES
OUTDATA
REFFILES
SIC2AMS
SCC2AMS
MACT2AMS
SURRXREF
TAFFILE
Description (prefix of file name provided with EMS-HAP in parentheses)
Run identification for titles
Input emission file directory
Input inventory SAS* file name
Output files directory
Output inventory SAS* file name
Ancillary files directory
Spatial surrogate assignments and codes for matching to temporal profiles by
SIC text file prefix (sic2ams)
Spatial surrogate assignments and codes for matching to temporal profiles by
SCC text file prefix (scc2ams)
Spatial surrogate assignments and codes for matching to temporal profiles by
MACT text file prefix (mact2ams)
Spatial surrogate assignments by AMS text file prefix (surrxref)
Temporal profile text file prefix (taff_hourly)
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Prepare the execute statement
The last line in the batch file runs the AreaPrep program. In the sample batch file provided in
Appendix B, you will see a line preceding the run line that creates a copy of the AreaPrep code
having a unique name. It is this version of the program that is then executed in the last line. If
you do this, the log and list files created by this run can be identified by this unique name. If you
don't do this and run the program under a general name, every run of AreaPrep will create a log
and list file that will replace any existing files of the same name.
You may find that you need to assign a special area on your hard disk to use as work space when
running AreaPrep. In the sample batch file, a work directory is defined on the last line following
the execution of AreaPrep. For example, the command
'sas AreaPrep_060900.sas -work /data/home/mls/' assigns a work directory called "/data/home/mls".
The directory you reference must be created prior to running the program.
8.2.5 Execute AreaPrep
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x AreaPrep.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'AreaPrep.bat'.
8.3 How Do I Know My Run of AreaPrep Was Successful?
8.3.1 Check your SAS? log file
You need to review the output log file to check for errors or other flags indicating incorrect
processing. This review should include searching the log files for occurrences of the strings
"error", "warning", "not found", and "uninitialized". These can indicate problems with input
files or other errors.
8.3.2 Check your SASt* list file
The list file contains the following information:
• Emissions totals and record counts, by pollutant, for the input emission inventory
• List of source category names
• Frequencies of lengths of codes
• The numbers of present and missing AMS, SCC, SIC, and MACT source category
codes and names
• Frequencies of AMS, SCC, SIC, and MACT source category codes and names
• SCC Codes in emissions file not in SCC link file
8-9
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• Warning message if a problem was encountered when matching source category codes
• Warning message if there were source categories with no spatial surrogate assignments
• List of the spatial surrogates which will be used in AMProc
• Warning message if there were source categories with no temporal allocation factor
assignments, with a note that these categories will be assigned a uniform temporal
profile in AMProc
• Summaries of Emissions With Missing SCC's
All AMS, SCC, SIC, and MACT code combinations, with assigned AMS_SCC codes
and spatial surrogates. Five tables: sorted by category name, AMS, SIC, SCC, and
MACT codes
• Contents of the data set written put for subsequent input to AMProc, and the first six
records in the file
• Output area source emissions totals for each pollutant
• Output file source category frequencies
• State-level emissions totals and record counts
One of the most important summaries in the list file is the one entitled "All Code Combinations,
With Matched AMS_SCC Code and Spatial Surrogates." This summary shows the spatial
surrogates and AMS_SCC code assignments. If you want to modify these assignments, you will
need to change the mact2ams.txt, scc2ams.txt, sic2ams.txt, and surrxref.txt files as discussed
above and rerun AreaPrep.
8.3.3 Check other output files from AreaPrep
You should check for the existence of the output inventory file named by keyword OUTDATA.
This file (or this file divided up into smaller files, depending on how large it is and how much
memory your computer has)-will serve as the input to the Area and Mobile Source Processor
(AMProc).
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CHAPTER 9
Mobile Source Processing
The Mobile Source AMProc Preparation Program
(MobilePrep)
The Mobile Source AMProc Preparation Program (MobilePrep) is run after the airport
processing program, AirportProc (see Figure 1-1). The output from MobilePrep is fed into the
Area and Mobile Source Processor (AMProc).
9.1 What is the function of MobilePrep?
The Mobile Source AMProc Preparation Program (MobilePrep) is used to prepare mobile source
emissions for input to the Area and Mobile Source Processor (AMProc). MobilePrep performs
the following functions:
• Splits the mobile source inventory into onroad and nonroad inventories
• Creates inventory variables required by AMProc
Unlike AreaPrep (discussed in Chapter 8), MobilePrep does not assign spatial surrogates or
AMS_SCC codes. AMProc performs these functions for mobile sources. This is because, in the
1996 NTI, the mobile source emission inventory contains only one coding system, the AMS
code. Thus, temporal allocation factors and spatial surrogates are selected using this code alone.
Figure 9-1 shows a flowchart of MobilePrep. The following sections describe the above bullets.
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Batch File Containing
Keywords e.g. Filenames
and Locations
; Mobile Source Emissions File !-
Reads Keywords
Reads emissions
Prints emissions tracking summary
Verifies that emissions units are all tons/year
Prints frequencies of pollutants and source
categories. Prints emissions totals by source
category, by pollutant, and by state.
Prints emissions tracking summary
Separates emissions into onroad and nonroad
components
Prints emissions summaries
; Output Mobile
Figure 9-1. MobilePrep Flow Chart
9-2
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9.1.1 Splits the mobile source inventory into onroad and nonroad inventories
MobilePrep splits the mobile source inventory into onroad and nonroad inventories based on the
inventory AMS code. If the first 3 characters of the AMS code are 220 or 223, then the emission
records are written into the onroad file (last two characters of the file name are "on"); records
having all other AMS codes are written to the nonroad emissions file (last two characters are
"of).
MobilePrep creates separate onroad and nonroad emission inventories to allow these inventories
to be processed separately in AMProc. You will likely want to process these inventories
separately through AMProc because it is the only way to assign different pollutant characteristics
such as coarse/fine particulate matter splits for onroad and nonroad sources. Many metals, for
example, have different coarse/fine particulate matter splits for onroad and nonroad sources. To
use different splits, you need to specify a different HAP table when you run AMProc. You do
this by running AMProc twice, each time using a different HAP table. The HAP table is one of
the ancillary files for AMProc, and is discussed in greater detail in Chapters 4 (Section 4.2.3), 10
(Section 10.1.1) and Appendix D (Sections D.5 and D.6).
9.1.2 Creates inventory variables required by AMProc
MobilePrep creates the 5-character STCOUNTY variable by concatenating the 2-digit State ID
and the 3-digit County ID. It also creates the POLLCODE variable and sets its value equal to the
CAS variable. These variables are required in the inventory you input to AMProc (see Table 10-
2).
9.2 How do I run MobilePrep?
9.2.7 Prepare your mobile source inventory for input into MobilePrep
Your mobile source inventory must meet the following requirements:
• It must be in SAS® file format.
• It must contain, at a minimum, the variables listed in Table 9-1, with units and values as
provided. (Additional variables can be present, but will not be present in the output
inventory file.)
• All data records should be uniquely identifiable by using the combination of the state ID
(ST_FIPS), county ID (CTY_FIPS), AMS source category code (AMS), and pollutant
code (CAS).
• It shouldn't contain Alaska and Hawaii emission records because EMS-HAP ancillary
files currently don't cover these areas.
9-3
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Table 9-1. Variables Required in the MobilePrep
Input Mobile Source Inventory SAS® File
Variable Name
AMS
CAS
CAT_NAME
COUNTY
EMIS
POL_NAME
STATE
UNITS
Data Description
AMS 10-digit category code
unique pollutant code number
mobile source emissions category name
county 3-digit FIPS code
emissions (tons/year)
pollutant name
state 2-digit FIPS
emission units (tons/year)
Type*
A10
A10
A50
A3
N
A50
A2
A12
*Ax = character string of length x, N = numeric
9.2.2 Determine whether you need to modify the ancillary input flies for MobilePrep
An ancillary file is any data file you input to the program other than your emission inventory.
There are no ancillary input files for MobilePrep.
9.2.3 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for MobilePrep is shown in Figure 8 of
Appendix B.
Specify your keywords
Table 9-2 lists the keywords required in the batch file. Use keywords to provide a run identifier
and to locate and name all input and output files.
Table 9-2. Keywords in the MobilePrep Batch File
Keyword
Description
TITLE
INPFILES
INEMIS
OUTFILES
OUTEMIS
WORKDIR
Run identification for titles
Input emission file directory
Input emissions file name prefix
Output files directory
Output file name prefix (must be no more than 6 characters
if you're using SAS* version 6)
Temporary directory for large work file
9-4
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Prepare the execute statement
The last line in the batch file runs the MobilePrep program. In the sample batch file provided in
Appendix B, you will see a line preceding the run line that creates a copy of the MobilePrep code
having a unique name. It is this version of the program that is then executed in the last line. If
you do this, the log and list files created by this run can be identified by this unique name. If you
don't do this and run the program under a general name, every run of MobilePrep will create a
log and list file that will replace any existing files of the same name.
You may find that you need to define a special area on your hard disk to use as work space when
running MobilePrep. A directory for work space is defined in the batch file by the keyword
WORKDIR. The directory you specify in your batch file must be created prior to running the
program.
9.2.4 Execute MobilePrep
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x MobilePrep.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'MobilePrep.bat'.
9.3 How do I know my run of MobilePrep was successful?
9.3.1 Check your SASt* log file
You need to review the output log file for MobilePrep to check for errors or other flags
indicating incorrect processing. This review should include searching the log files for
occurrences of the strings "error", "warning", "not found", and "uninitialized". These can
indicate problems with input files or other errors.
9.3.2 Check your SASf list file
The list file contains the following information:
The options that you specified
Contents of input emissions file
Emissions totals and record counts, by pollutant, for the input emission inventory
List of source category names
List of states in the inventory
Table of emission units (there should be only tons/year listed)
Emissions totals for each source category and pollutant for all mobile sources
Contents of the onroad and nonroad data sets written out for subsequent input to AMProc
9-5
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• Output emissions totals for each pollutant for all mobile, onroad, and nonroad sources
You should review the list file to verify that the emissions, pollutants, and source categories are
correct. You should also make sure the emission units are "tons/year."
9.3.3 Check other output files from MobilePrep
You should check for the existence of the onroad, nonroad and combined nonroad and onroad
output inventory files. MobilePrep names the combined file what you entered as your name for
the keyword "OUTFILE." It names the onroad and nonroad files with the name you used for
keyword "OUTFILE" concatenated with an "on," for onroad and an "of for nonroad. These
files (or these files divided up into smaller files, depending on how large they are and how much
memory your computer has) will serve as the input to the Area and Mobile Source Processor.
9-6
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CHAPTER 10
Area and Mobile Source Processing
The Area and Mobile Source Processor (AMProc)
AMProc is the final program you run for processing area or mobile sources (see Figure 1-1).
You must run AMProc separately for area sources and mobile sources. You will likely need to
run AMProc separately for nonroad mobile sources and onroad mobile sources, as discussed in
Section 9.1.1. AMProc uses the output of AreaPrep for area sources. It uses the output of
MobilePrep for nonroad or onroad mobile sources. If you are running onroad and nonroad
together, AMProc uses the combined onroad and nonroad inventory output from MobilePrep.
10.1 What is the Function of AMProc?
The Area and Mobile Sources Processor (AMProc) is the core of EMS-HAP's processing of area
and mobile source emissions. It performs the functions listed below.
• Selects pollutants, groups and/or partitions pollutants, and assigns their
characteristics
• Spatially allocates county-level emissions
• Temporally allocates emissions
• Determines ASPEN-specific modeling parameters
• Projects emissions to a future year
Assigns ASPEN source groups
• Creates ASPEN input files, column formatted text and SAS® files
You control whether or not to have AMProc project emissions to a future year in your execution
of the program; Section 10.1.6 details how to do this.
Figure 10-1 gives an overview of the Area and Mobile Sources Processor. The following
sections describe the above bullets.
10-1
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Batch File Containing Keywords
e.g. File Names and Locations, i > Reads Keywords
Program Options
i
Emission Inventory File | ' H Reads and Summarize Emissions
HAP Table ; „ Pollutant Processing
(selection, grouping, and partitioning)
ASPEN Source Group File | ^j Assignment of ASPEN Source Groups
i
AMS-to-Spatial Surrogate
pjlg , Spatial Allocation of County Emissions to
Census Tracts
Spatial Allocation Factors I—
Temporal Allocation i ^ Temporal Allocation of Annual Emissions to
Factors 3-Hour Periods
; Growth & Control Files | H Growth and Control OR
iis SiiffinanSliT; f* 1 Produces Emissions Summaries
! : :ASPEN EmissionsMes ; << 1 Writes ASPEN Emissions Files
Figure 10-1. Overview of Area and Mobile Source Emissions Processing (AMProc)
10-2
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10.1.1 Selects pollutants, groups and/or partitions pollutants, and assigns their
characteristics
One of the first functions the Area and Mobile Source Processor performs is the selection,
partitioning and grouping of pollutants to be modeled by ASPEN and the assignment of their
characteristics. This same function is performed for point source processing with the
PtAspenProc program (see Chapter 4). As with point source processing, you control these
processes through your entries in an ancillary input file we refer to as the "HAP table" file.
Unlike point sources, AMProc uses only one HAP table. Thus, if you want to specify a different
HAP table for onroad sources than nonroad sources you will need to run AMProc twice, once
with the onroad HAP table and once with the nonroad HAP table.
AMProc uses the HAP table to:
• Subset the inventory to include only those pollutants you've chosen to model
• Assign a reactivity class to each gaseous pollutant and a particulate size class to each
paniculate pollutant (through the variable REACT)
• Group multiple species into a single pollutant category
• Partition pollutants into multiple pollutant categories with different reactivity or
particulate size classes (e.g., apportion lead chromate to lead compounds, fine
particulate; lead compounds, coarse particulate; chromium compounds, fine particulate
and chromium compounds, coarse particulate)
• Apply potency factors, molecular weight, or other adjustment factors (FACTOR
variable) to the emissions of different species in a pollutant category
• Assign the resulting pollutant or pollutant category to be modeled in ASPEN a unique
HAP code (variable NTI_HAP) used for inventory projections (if you choose this
function), a unique pollutant group code (variable SAROAD) used for ASPEN
modeling and a description of the group (variable SAROADDC)
Because this function is the same for point sources as it is for area and mobile sources, we refer
you back to Chapter 4 for details about the HAP table. Section 4.2.3 contains instructions on
how to modify it to meet your needs. Appendix A (Tables 1-4) contains printouts of all HAP
tables supplied with EMS-HAP. Appendix D (D.5-D.6) describes how we developed these HAP
tables.
10.1.2 Spatially allocates county-level emissions
Emission inventories generally provide area and mobile source emissions at the county level.
EMS-HAP spatially allocates county-level emissions to the census tracts within each county.
AMProc uses "spatial allocation factors" to apportion county-level emissions to census tracts.
These spatial allocation factors are derived from data on the geographic distribution of various
"spatial surrogates" that are believed to have geographic variations similar to those of emissions
from various source categories.
Figure 10-2 presents a flow chart of the spatial allocation process in EMS-HAP for area and
10-3
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mobile sources. The first step is to assign the appropriate spatial surrogate to each source
category. For area sources, this is done in AreaPrep; the process is explained in detail in Section
8.1.1. For mobile sources, AMProc assigns the spatial surrogates using the AMS code and the
AMS-based surrogate assignment ancillary file, surrxref.txt (see Section 10.2.5).
The next step is to apply spatial allocation factors (SAFs) to the county-level emissions in the
inventory to compute tract-level emissions. AMProc obtains the SAFs from ancillary SAF files.
Each set of SAFs (the set consists of one SAF per tract) conies from an ancillary SAF file
corresponding to a particular spatial surrogate. For example, SAF20 corresponds to population,
since the surrogate code for population is "20." AMProc uses the spatial surrogate assignments
discussed above to link each county-level emission record to the appropriate SAF file. AMProc
then applies the factors to the county-level emissions. This results in tract-level emission
estimates, for that county, for each area or mobile source category. AMProc uses the following
equation to compute tract level emissions for each source category, j, in a county:
-'-'tract, county, j ~ •'-'county, j ^county, tract, j \^4- iv-l)
where
Etract, county, j ~ census tract emissions from source category j in a county
Ecounty j = emissions from category j in the county that contains the census
tract
, tract, j ~ tne spatial allocation factor for the tract in the county that
corresponds to the spatial surrogate assigned to source category j.
(The spatial allocation factors for all of the tracts in a given county
will sum to 1.0 for any given spatial surrogate.)
A discussion of the development of the ancillary SAF files supplied with EMS-HAP is provided
in Appendix D (Section D.10).
10-4
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Mobile Source Emission Inventory File
(Output From MobilePrep)
Onroad, Nonroad or Both
Area Source Emission Inventory File
AMS Surrogates
Spatial
Allocation
Factor File
AMProc: MACRO MERGESAF
Merges spatial surrogate codes into
emissions file. Merges spatial
allocation factors into emissions
file.
Cross-Reference /
Spatial Surrogate Files
SIC-to-AMS
SCC-to-AMS
MACT-to-AMS
AMS Surrogates
AreaPrep
Merges spatial surrogate codes
into emissions file using MACT,
SIC, SCC, AMS precedence.
AMProc: MACRO APPLYSAF
Applies spatial allocation factors to emissions,
checks that all emission records are matched and
produces summary of non-matched emissions.
Drops records with zero emissions.
AMProc: MACRO APPLYSAF
Applies spatial allocation factors to emissions,
checks that all emission records are matched and
produces summary of non-matched emissions.
Drops records with zero emissions.
?-: • •- "ja'Spatiallylftldcated'Emissionsv
Spatially Allocated Emissions4
Figure 10-2. Area and Mobile Source Spatial Emissions Processing Flow Chart
10-5
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10.1.3 Temporally allocates emissions
Temporal allocation of emissions is the process of estimating emissions at a finer temporal
resolution than that of the emission inventory. The ASPEN model requires emission rates for
eight 3-hour periods within an average day of the year (i.e., no seasonal, monthly or day-of-week
variations in emissions are accounted for). AMProc produces these eight estimates for area and
mobile source categories using temporal profiles for each source category. These temporal
profiles are in an ancillary file we refer to as the temporal allocation factor (TAP) file.
Note that temporal allocation of point sources is done in PtTemporal (see Chapter 5). The
temporal allocation methodology in AMProc is the same as PtTemporal except for the hierarchy
of codes used to assign the TAFs to sources. AMProc uses the AMS code to assign TAFs. For
area sources, this code was assigned in AreaPrep (see Section 8.1.2) based on the following
hierarchy: MACT code, SIC code, SCC code and inventory AMS code. For point sources,
PtTemporal assigns TAFs using a different hierarchy: the SCC, SIC and the MACTCODE.
AMProc produces a list any categories that do not match to temporal profiles in the ancillary
TAP file. As in PtTemporal, these categories are assigned a uniform profile.
Figure 10-3 shows a flow chart of the temporal allocation process in EMS-HAP for area and
mobile sources.
10-6
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Spatially Alocated
Emissions Inventory File
Temporal Allocation
Factor File
AMProc: MACRO READTAF
Reads temporal allocation factors (TAFs) and converts
hourly TAFs to 3-hour TAFs. Normalizes TAFs if
necessary.
AMProc: MACRO APPLYTAF
Merges the temporal allocation factors into the emissions
file by source category and applies them. Checks that all
emissions records are matched and produces a summary
of non-matched emissions.
Figure 10-3. Area and Mobile Source Temporal Allocation Flow Chart
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10.1.4 Determines ASPEN-specific modeling parameters
Urban/Rural Dispersion Parameters
The ASPEN model uses different dispersion parameters and deposition rates for urban and rural
sources; therefore, each tract must be identified as -being either urban or rural. AMProc supplies
this information through the assignment of the urban/rural flag where a value of 1 indicates an
urban tract, and a value of 2 indicates a rural tract.
AMProc reads the urban/rural flags at the tract level from the spatial allocation factor (SAF)
files. These files are ancillary input files to the program (see 10.2.2, Table 10-3) and also serve
to provide the spatial allocation factors for allocating county-level emissions to the census tracts,
as was discussed in Section 10.1.2. The SAF files supplied with EMS-HAP use the same
urban/rural designations used in the EPA's Cumulative Exposure Project (CEP).6 The CEP
based the designation on residential population density data from 1990 (urban if greater than 750
people/km2), except for a few very small tracts. Each SAF file contains the same urban/rural
flag designations. To change these designations you need to change them in all SAF files. The
format of the SAF files is provided in Figure 29 of Appendix A.
Vent Type Parameter IVENT
An IVENT value of 0 (zero) represents a stacked vent. The ASPEN model performs plume rise
calculations for these stacks. An IVENT value of 1 represents a non-stacked vent. The ASPEN
does not perform plume rise calculations for this case. IVENT is set to 1 for all area and mobile
sources because stacks are not being processed.
10.1.5 Assigns ASPEN source groups used in the ASPEN model output
The ASPEN model computes concentrations for up to 10 source groups which can be used to
analyze the relative impacts of different types of emission sources. AMProc assigns groups
using an ancillary source group assignment file, am_grp.txt (see Section 10.2.4). This file links
the source category name variable (CAT_NAME) and the county-level urban/rural designation to
a group number (between zero and nine, inclusive.) Use of the county-level urban/rural
designation allows you to distinguish between sources located in urban counties from sources
located in rural counties. Note that the county-level urban/rural designation is different from the
tract-level urban/rural dispersion parameter described in 10.1.4. The county-level urban/rural
designations come from the ancillary file popflag96.txt.
10-8
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10.1.6 Projects emissions to a future year
AMProc can project the area and mobile source emissions inventories to a future year, reflecting
the impacts of growth and emission reduction scenarios. We expect you will use this primarily
for area sources, since mobile source projections usually involve running a mobile source
emissions model rather than multiplying base year emissions by a series of factors (which is
basically what this program does.) Nonetheless, if you develop a set of growth and emission
reduction factors to use, this program can be used for mobile sources.
You can choose to project your emissions along with the other functions in AMProc, or you can
supply an inventory that is already temporally and spatially allocated and project emissions for
that inventory. Emission reduction information can be assigned to the emission records either by
the source category, reflecting a user-defined reduction scenario, or by the MACT code,
reflecting the reductions to be achieved by Maximum Achievable Control Technology (MACT)
standards and standards under Section 129 of the Clean Air Act,
The "Program Options" section of Table 10-4 shows how to set the keywords in your batch file
to select your options for projecting emissions.
The projection methodology for area and mobile sources in AMProc is very similar to that for
point sources in PtGrowCntl. The major difference is that AMProc allows you to provide user-
defined emission reduction scenarios (which could include MACT and other strategies you
choose). PtGrowCntl currently only allows you to provide category-based reductions based on
the MACT code variable or facility-specific emission reduction information.
Figure 10-4 shows a flowchart for the area and mobile sources growth and control processing.
Note that this module of AMProc is expected to undergo developmental changes. We will
provide updated documentation when the revised version is released.
10-9
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Temporally Allocated
Emissions
Source Category to SIC
Cross-Reference File
Source Category to
Category Code and
Emission Bin File
Growth Factor File
Merge Growth Factor File with cross-reference
files to create a growth factor file by category
code and FTPS. Merge this file with Temporally
Allocated Emissions by category code and FIPS
Source Category Emission
Reduction Information
File
General MACT
Emissions Reduction
Information File
Pollutant-specific MACT
Emissions Reduction
Information File
User-defined Reduction
Scenario based on
source category
OR
MACT Reduction
Scenario based on
MACTCODE
Combine source category
reduction information with the
emissions inventory
Combine MACT category
reduction information with
emissions inventory
Calculate Grown & Controlled Emissions
1
I • =i Prbj ecte^JEmissiqns f
Figure 10-4. Area and Mobile Source Growth and Control Projection Flow Chart
10-10
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Projections due to Economic Growth
AMProc assigns growth factors to each emissions record based on the state FIPS and the SIC
code (similar to PtGrowCntl). AMProc uses an ancillary file containing a cross-reference
between source category names and SIC codes to supply SIC codes where they are missing in the
inventory (see Section 10.2.7). The growth factor is specific to both the base year and future
year and is supplied to the program through an ancillary growth factor SAS® file (see Section
6.2.3). AMProc computes future 3-hour emission rates for each record by multiplying the base
year 3-hour emission rates by the assigned growth factor, as follows.
Grown emissions = (Base year baseline emissions) x (Growth factor)
Each execution of AMProc results in an inventory file containing emissions projected to that one
future year. Note that any record will be assigned the default growth factor of one when there is
no assigned SIC code or when no match is found in the growth factor input file by state FIPS and
SIC. In these cases, or, if you choose not to grow the emissions, the grown emissions will be
unchanged from the base year emissions.
Projections due to User-Defined Emission Reduction Scenarios
AMProc can account for the impacts of user-defined emission reduction strategies. You can
supply emission reduction information for each individual area or mobile source category in the
emission inventory using the area_cntl.txt ancillary file (see Section 10.2.7). The emission
reduction information in this file includes: (1) two control efficiencies for the reduction strategy
(one for new sources and one for existing sources), (2) the percentage of emissions at existing
sources that will come from new sources, and (3) an application control flag. These variables
and their use in AMProc are the same as in the point source growth and control methodology in
PtGrowCntl. See Section 6.1.2 of Chapter 6 for more details.
After the emission reduction information has been assigned to the emission records, the existing
and new source projected emissions are calculated and are summed to determine the projected
emissions for each inventory record. The calculations are:
Total Projected Emissions = Projected Emissionsexisting + Projected Emissions new (eq. 10-2)
Projected Emissions,,,^ = Grown Emissions x(l-NewRate/l00) •x.(\-'Efna[nagl 100) (eq. 10-3)
Projected Emissions new = Grown Emissions x (NewRate/100) xO-EffT^/100) (eq. 10-4)
where
EffT = emission reduction strategy efficiency
NewRate = Percentage of emissions attributed to new sources
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Projections due to MACT Emission Reduction Scenarios
As an alternative to applying user-defined reductions based on source category, you can have
AMProc apply MACT emission reductions based on the inventory MACT code. AMProc
assigns this MACT category-based reduction information to the emission records using the same
two ancillary files, MACT_gen and MACT_spec, as are used in PtGrowCntl (Chapter 6). The
use of these files and the emission reduction information they contain are described in more
detail in Section 6.1.2.
In summary, you can specify general MACT reduction information through the MACT_gen
ancillary file. General reduction information applies to an entire MACT category or MACT
process (if the process has a unique MACT code), but not to a particular pollutant emitted by the
process. You can assign pollutant-specific MACT reduction information through the
MACT_spec ancillary file.
Note that because the MACT_spec file is also used to project point source emissions, this file
may also include MACT reduction information identified by SCC. AMProc will not use any
records including SCC information in the MACT_spec file for the projection. Thus, if you want
to assign pollutant-specific information to the entire MACT category, make sure you include a
record in the MACT_spec file in which the SCC fields are blank.
For an individual inventory record, the assignment of process and pollutant-specific MACT
reduction information will supercede information assigned by the MACT code alone.
AMProc applies the new and/or existing MACT control efficiencies to the grown and temporally
allocated emissions when the following criteria are met:
The application control flag (MACT_APP) is equal to 1.
• The source control flag is 'B' (this value indicates that the control efficiency is
applied to all source types).
• The projection year is greater than the compliance year or, if the compliance year is
not provided, the projection year is greater than the MACT bin plus 1995.
See equations 10-2,10-3 and 10-4 above for AMProc's calculation of the projected emissions.
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10.1.7 Creates ASPEN input files, column formatted text and SAS® files
AMProc creates three different types of output files:
1. The ASPEN input files
2. A column formatted ASCII text file
3. SAS® output files - a core file and an extended file.
You control whether or not to create the extended SAS® file in your execution of AMProc, as
discussed below.
ASPEN Input Files
The ASPEN model requires emission data in the form of one ASCII text file for each of the
possible nine reactivity classes. Each file contains data for all pollutants having the same
reactivity class. AMProc creates all nine files in the appropriate format. Each file consists of a
header and body. The elements of the header are: .
1. A run identifier: You supply this in the batch file (keyword RUNID in Table 10-4)
2. Wet and dry deposition codes: AMProc sets these to 0 for particulates and 1 for gaseous
species. These values tell ASPEN whether to invoke the deposition algorithm for
particulates (ASPEN does not perform deposition for gases).
3. Decay coefficients associated with the reactivity class: AMProc determines these from the
ancillary file indecay.txt based on the value of the REACT variable (discussed in detail in
Chapter 4, Section 4.2.3). This file contains a set of coefficients for each of the nine
reactivity classes.
The file body contains source information such as census tract latitude and longitude, source
group, and the emissions for each of eight 3-hour periods for each pollutant (of the appropriate
reactivity class) emitted from the stack.
Using the run identifier keywords in the batch file, AMProc names the ASPEN input files in the
form "EMISTYPE.USRLABEL.dRUNDATE.rREACT.inp". An example file name is
"MV.Base96.3.d020499.r9.inp", where "Base96" is the keyword USRLABEL, "MV" (note that
it would be "AR" for area sources) is the keyword EMISTYPE, "3" is the emissions group
variable, "9" the REACT variable, and "d020499" is the keyword RUNDATE.
Column Formatted ASCII Files
AMProc creates a single column formatted ASCII text file containing data written to the ASPEN
input emissions files. This file can provide easy access to the data for quality assurance
purposes. You specify the prefix name of this file in your batch file (keywords EMISTYPE and
USRLABEL); the suffix is "dat". Table 10-5 in Section 10.3.3 shows the format of this file.
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SAS® output files
There are two SAS®-formatted files written out by AMProc. One is the core output file,
reflecting what is written to the ASPEN emissions files, and the other is the extended output file,
which retains the source category information for each source, and is therefore much larger. You
can specify that AMProc not produce the extended file in your execution of AMProc by setting
the keyword SAVEFILE in your batch file (see Table 10-4 in Section 10.2.8) to 0 (zero). Tables
10-5 and 10-6 in Section 10.3.3 show the formats of the core and extended output files.
The name of the extended output file is the first 7 characters of the value assigned to the
concatenation of the keywords EMISTYPE and USRLABEL with the suffix "##", where "##" is
an engine-specific suffix. For example, if "EMISTYPE" is "MV" (mobile), "USRLABEL" is
"Bas96", then the extended SAS®-formatted output file prefix would be "MVBas96". The file
name of the core output file is the same as the extended file except that it is preceded by the letter
"c", e.g., "cMVBas96".
10.2 How do I run AMProc?
10.2.1 Prepare your area and mobile source emission inventory files for input into
AMProc
Area Source Inventory Requirements
The area source inventory you use for input into AMProc must be the output inventory SAS® file
from AreaPrep. This file will contain the variables listed in Table 10-1.
Table 10-1. Variables in the AMProc Input Area Source Inventory SAS® File
(Variables used by AMProc are in bold; Other variables listed were either created or used by AreaPrep)
Variable Name Data Description Type*
AMS AMS 10-digit category code or SCC 8-digit category code; assigned in AreaPrep A10
(see 8.1.2)
CAS unique pollutant code A10
CAT_NAME emissions category name A90
EMIS emissions (tons/year) N
MACT MACT code A4
MATCH information on how AreaPrep assigned spatial surrogates and AMS codes; A4
assigned in AreaPrep
POL_NAME pollutant name A50
POLLCODE pollutant code (same value as CAS); assigned in AreaPrep A10
SCC SCC code A8
SIC SIC code A4
SPATSURR the assigned spatial surrogate from AreaPrep N
STCOUNTY 5-dieit FIPS code (state and county combined) AS
*Ax = character string of length x, N = numeric
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Onroad and Nonroad Mobile Source Inventory Requirements
The mobile source inventory you use for input into AMProc must be an output inventory SASS
file from MobilePrep. It can be either the onroad inventory, the nonroad inventory or the
combined onroad and nonroad inventory. These files will contain the variables listed in Table
10-2.
Table 10-2. Variables in the AMProc Input Mobile Source Inventory SAS® File
(Variables used by AMProc are in bold; Other variables listed were either created or used by MobilePrep)
Variable Name
AMS
CAS
CATJVAME
COUNTY
EMIS
POLLCODE
POL_NAME
STATEN
STCOUNTY
Data Description
AMS 10-digit category code or SCC 8-digit category
code
unique pollutant code
emissions category name
county 3-digit FIPS code
emissions (tons/year)
unique pollutant code (same value as CAS)
pollutant name
2-digit State abbreviation
5 -digit FIPS code (state and county combined")
Text*
A10
A15
A50
A3
N
A15
A50
A2
A5
*Ax = character string of length x, N = numeric
Splitting Your Input Emissions Files into Smaller Files
You may need to split the input emission inventory file into smaller files and run each of these
through AMProc separately. Do this after running AreaPrep (for area sources) and MobilePrep
(for mobile sources). File splitting will be necessary if you run out of disk space while running
AMProc. You may not need to do this if your inventory contains a limited number of pollutants
and/or source categories. The number of inventory subsets will be determined by the number of
pollutants, source categories and counties that are being processed, and the amount of available
free disk space.
10.2.2 Determine whether you need to modify the ancillary input files for AMProc
An ancillary file is any data file you input to the program other than your emission inventory.
Table 10-3 lists the ancillary input files needed to run AMProc. In the following sections we
discuss the content of most of these files and when you need to modify them. Appendix A
contains the file formats of all of these files; see the table of contents in Appendix A for the list
of ancillary files associated with AMProc.
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Table 10-3. Ancillary Files for the Area and Mobile Source Processor
Keyword, File
Description or File
Name
Purpose
Need to Modify?
For-
mat
indecay
HAP Table
SAF#, where # is a
number between 1-
29 (inclusive)
taff_hourly.txt
surrxref.txt
am_grp.txt
popflg96.txt
gfXX_YY
(where XX specifies
projection year; YY
specifies base year)
area sic.txt
area_cntl.txt*
MACT_gen*
MACT_spec*
Provides decay coefficients for 6
stability classes for the eight 3-hour
time periods for the 9 reactivity
classes
Selects pollutants to be modeled,
assigns classes, groups pollutants,
adjusts emissions
Contain spatial allocation factors for
the spatial surrogates available in
EMS-HAP, also contain urban/rural
dispersion flags for each tract
Provides temporal profiles containing
24 hourly temporal allocation factors
(TAFs) by SCC and/or AMS codes
Contains AMS to spatial allocation
surrogate cross-references
Provides ASPEN source group
assignments by source category
Contains county-level urban/rural
designations
Provides the assignment of year
specific growth factors by state and
SIC code.
Provides cross-reference between
source categories and SIC codes for
purpose of assigning growth factors
by state and SIC code.
Provides emission reduction strategy
information by area source category
Provides emission reduction strategy
information by MACT category
Provides emission reduction
information by MACT category and
HAP identification code
No Text
If you want to change selection or Text
characteristics of pollutants from files
provided with EMS-HAP
If you want to use updated spatial SAS®
surrogate information or new
surrogates; if you want to change the
tract-level urban/rural dispersion
designations
If you want to use different source Text
category specific temporal factors
If you want to use different surrogates Text
or have additional categories in your
area/mobile inventories
If you want to make different source Text
group assignments or have additional
categories in your area/mobile
inventories
If you are specifying different source Text
group assignments for urban vs. rural
counties and want to use different
county-level urban/rural designations
If you are growing your inventory and SAS*
you need growth factors for a
different projection year or base year
When additional or different SCC to Text
SIC cross-references are needed to
assign growth factors
Develop if you want to use category- Text
based emission reduction strategies
Develop by obtaining MACT-based Text
reduction information
Develop by obtaining MACT-based Text
reduction information
1 These files are not currently being provided as part of EMS-HAP.
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10.2.3 Modify the HAP table input file
We've supplied you with four HAP Table files.
1) point_area HAP table (haptabl_point_area.txt)
2) onroad mobile HAP table (haptabl_onroad.txt)
3) nonroad mobile HAP table (haptabl_pffroad.txt)
4) precursor HAP table (haptabl_precursor.txt), which applies to precursors from point, area,
onroad and nonroad sources.
Precursors are pollutants that cause HAPs to form secondarily in the atmosphere. They may or
may not be HAPs themselves. More information about processing HAP precursors can be found
in Appendix D, Section D.6.
AMProc uses a single HAP table with each run for processing your inventory. Before you run
AMProc you'll need to select the appropriate HAP table and modify it to fit your modeling needs
and your inventory. Select the onroad HAP table for onroad HAP emissions, the nonroad HAP
table for nonroad HAP emissions and the point_area HAP table for area HAP emissions. You
can use either onroad or nonroad for diesel particulate matter unless you change the coarse fine
particulate matter allocation factors from those in the current HAP tables, and you change them
such that they differ between onroad and nonroad emission types. Select the precursor HAP
table if you are processing area or mobile source precursors.
See Section 4.2.3 for a detailed description of the format of the HAP Table files and how to
modify them.
10.2.4 Modify the file that assigns area and mobile source categories to source groups
You can modify the emission groups ancillary input file, am_grp.txt, to specify different ASPEN
source groups for different area or mobile source categories by county urban/rural designation.
For example, if you want to determine the contribution of onroad mobile sources in urban areas
to your ASPEN results, then assign a unique source group number (between zero and 9,
inclusive) in the emission groups ancillary input file to every onroad mobile source category in
the urban column, and make sure that no other category (area, point, nonroad mobile, rural
onroad mobile) uses this number.
The format ofam_grp.txt is shown in Appendix A, Figure 30. The CAT_NAME variable on
this file is used to identify unique source categories. This file must contain one record for each
category in the emission inventory. For each source category, this file specifies an emissions
group for urban and for rural sources. It also assigns a unique category code for each source
category for use in AMProc's growth and control module (see 10.2.7). The use of the category
code makes the growth and control program run more efficiently.
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10.2.5 Modify the file that assigns spatial surrogates to mobile source categories
The most important option in spatial allocation is,the selection of the appropriate spatial
allocation surrogates. AMProc assigns surrogates to mobile sources using the ancillary input
file surrxref.txt. This file provides a spatial surrogate assignment for each unique AMS code.
This file is also used to assign surrogates for area sources (in conjunction with other spatial
surrogate assignment files) in AreaPrep (see Section 8.2.3).
You can assign different surrogates to source categories or add new source categories (by AMS
code) to this file and assign surrogates to those. Table 8-3 gives a list of available spatial
surrogates for EMS-HAP. Appendix A, Figure 27, gives the format of this file.
10.2.6 Modify the temporal allocation factor file
The temporal allocation factor file is a common file used for point, area and mobile sources. It
provides hourly allocation factors that are applied to emissions sources based on 8-digit AIRS
Source Classification Codes (SCC) or 10-digit Area and Mobile System (AMS) codes. The file
is used to allocate emissions for each source into average diurnal profiles that are representative
of a typical day. You can change temporal allocation factors for source categories in this file and
you can add profiles for additional source categories. Appendix A, Figure 15, gives the format
of this file.
10.2.7 Modify the growth factors and emission reduction information files
The growth and control algorithm can use the following input files, depending on the type of
reduction scenario you want to apply:
• am_grp.txt file - cross-reference file from category name to category code
• area_sic.txt - cross-reference file from area or mobile source category to SIC
GFXX_YY - growth factor file to grow from year XX to year YY
• area_cntl.txt - user-defined emission reduction information file
MACT_gen.txt - general MACT emission reduction information file
• MACT_spec.txt - pollutant specific MACT emission reduction information file
The am_grp.txt file (also discussed in 10.2.4) is used to cross-reference a category name from the
area_sic and area_cntl to a category code. Note that AMProc also uses am_grp.txt to assign a
category code to each category name in the inventory. AMProc uses the category code (rather
than the category name) in the growth and control module to allow the module to run more
efficiently. You need to make sure that the category names in the am_grp.txt file exactly match
the names in your emissions inventory and in the area_sic and area_cntl files.
Figure 33 of Appendix A, provides the file format and sample file contents ofarea_sic.txt. This
file assigns a 2- or 3-digit SIC code for each emission source category. The SIC code is used to
access appropriate growth factors from the growth factor file.
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The growth factor file is specific to the emission inventory base year, and the year of the
projection inventory. This file is described in Section 6.2.3 and the format is provided in
Figure 19 of Appendix A.
Figure 32 of Appendix A, provides the file format of the area_cntl.txt file. Each record contains
two efficiency parameters: emission reduction efficiency for existing sources and emission
reduction efficiency for new sources. In addition, a percentage of the emissions attributable to
new sources is also included.
The MACT_gen.txt and MACT_spec.txt files are described in Section 6.2.5 and the formats are
provided in Figures 21a and 21b of Appendix A.
10.2.8 Prepare your batch file
The batch file serves two purposes: (1) allows you to pass "keywords" such as file names and
locations, program options, and run identifiers to the program, and (2) sets up the execute
statement for the program. A sample batch file for AMProc is shown in Figure 9 of Appendix B.
' Specify your keywords
Table 10-4 describes all of the keywords required in the batch file. Use them to locate and name
all input and output files and supply run identification information. Use them also to select
program options, such as selecting the growth and control function (keyword GROWCNTL) and
choosing which output files to create (keyword SAVEFILE). Further, you can run the program
for a single HAP or State and get diagnostic information on a particular census tract. Note that
the keywords cannot have blanks in their values, so if you don't want to run the program for a
single HAP, you still need to provide a value for the pollutant code. The value provided in this
circumstance does not need to represent an actual pollutant code; it is merely a place holder value
for the keyword.
Table 10-4. Keywords in the AMProc Batch File
Keyword Description of Value
Run identifiers
RUNID Run identification (at most 60 characters)
EMISLABL Emissions category description (for titles only, at most 60 characters)
RUNDATE Date, to help identify files (e.g., 011999)
EMISTYPE Emissions file type (AR for area, MV for mobile)
USRLABEL User-specified label used as prefix for output files (1 to 5 characters)
Input Inventory Files
INPEMISS Input emissions files directory
EMISFILE Input county-level emissions file prefix (SAS*)
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Table 10-4. Keywords in the AMProc Batch File (continued)
Keyword
Description of Value
Ancillary Input files (Prefix of file name provided with EMS-HAP in parentheses)
INPFILES The ancillary files directory
SAFFILE Spatial allocation factor SAS* files prefix (safe#, where # is a 1 or 2-digit number)
TAFFILE Temporal profile text file prefix (taff_hourly)
INDECAY Reactivity class decay coefficients for 6 stability classes for eight 3-hour time periods
(indecay)
HAPTABLE HAP table file prefix (haptabl_point_area, haptabl_onroad, haptabl_offroad, or
haptabljprecursor)
SURRXREF Spatial surrogate assignments by AMS text file prefix (surrxref)
EMISBINS ASPEN emission source groups assignment text file prefix (am_grp)
CNTYUR County urban/rural cross-reference file (popflg96)
MACTGEN General MACT-based emission reduction information text file prefix (MACT_gen)
MACTSPEC Specific MACT-based emission reduction information text file prefix (MACT_spec)
SRCCNTL Source category-based emission reduction information text file prefix (area_cntl)
Program Options
SAVEFILE l=save large SAS*-formatted file with all emissions information on a source category level
basis for each census tract 0=don't save this large SAS* file
GROWCNTL 1= perform growth and control calculations; 0= don't perform growth and control
calculations; 2=run growth and control only, using an existing temporally and spatially
allocated emissions file
DOGROW 1 =project emissions as a result of economic growth; 0=don't grow emissions
CNTLFLAG 1= assigns and applies user-defined reduction control information; 2= assigns and applies
MACT reduction information; 0= doesn't apply any reduction information to emissions
PROCCHEM 1= Use pollutant-specific MACT reduction information; 0= don't use pollutant-specific
MACT reduction information
REBIN l=Reassign emission groups during growth and control processing; 0=don't reassign them
Subsetting controls
LSUBSETP 1 = process only one pollutant; 0=don't process only one pollutant
SUBSET? The pollutant code to be subset to
LSUBSETG 1= process only one state; 0=don't process only one state
SUBSETG State 2-character postal code abbreviation of the state to be subset to
Diagnostics flags
LCPTIMES l=print component CPU times; 0=don't print component CPU times
LDBG 1 =printout of diagnostic information; 0=don't
LONECELL 1 =printout diagnostics for a selected single cell (tract); 0=don't
ONECELL The selected single cell
Output files
OUTFILES The output file directory
WORK2 Directory for large temporary work files
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Prepare the execute statement
The last line in the batch file runs the AMProc program. In the sample batch file provided in
Appendix B, you will see a line preceding the run line that creates a copy of the AMProc code
having a unique name. It is this version of the program that is then executed in the last line. If
you do this, the log and list files created by this run can be identified by this unique name. If you
don't do this and run the program under a general name, every run of AMProc will create a log
and list file that will replace any existing files of the same name.
You may find that you need to define a special area on your hard disk to use as work space when
running AMProc. In the sample batch file, a directory for work space is defined by the keyword
WORK2. The directory you reference here must be created prior to running the program.
10.2.9 Execute AMProc
There are two ways to execute the batch file. One way is to type 'source' and then the batch file
name. Alternatively, first set the permission on the file to 'execute.' You do this by using the
UNIX CHMOD command and adding the execute permission to yourself, as the owner of the
file, to anyone in your user group, and/or to anyone on the system. For example,
'chmod u+x AMProc.bat' gives you permission to execute the batch file. Refer to your UNIX
manual for setting other permissions. After you have set the file permission, you can execute the
batch file by typing the file name on the command line, for example, 'AMProc.bat'.
10.3 How Do I Know My Run of AMProc Was Successful?
10.3.1 Check your SAS? log file
You should review the output log file to check for errors or other flags indicating incorrect
processing. This review should include searching the log files for occurrences of the strings
"error", "warning", "not found", and "uninitialized". These can indicate problems with input
files or other errors.
10.3.2 Check your SASf* list file
The list file contains the following information:
• The options that you specified
• Contents of input emissions file
• Emissions totals and record counts, by pollutant, for the input emission inventory
• Summary of Input Emission Rates by Pollutant
• Summary of Input Emission Rates by State
• HAP table pollutant code list
• Warning message if there are pollutants in emissions file not matched to HAP table.
Lists the pollutant codes in emissions inventory not matched to HAP table file.
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Warning message if records with no reactivity code were encountered when merging
reactivity codes with emissions. Prints the first 10 records and a summary of
emissions by pollutant.
Pollutant sums by pollutant before and after collapsing to SAROAD codes
Warning message if there are counties in the emissions file which do not have a match
in the county urban/rural codes file
Warning message if there are emissions categories not matched to source groups.
Lists the unmatched categories.
Table of assignment of spatial surrogates to source categories
Surrogate-level summary of emissions
Warning message if records with no matching surrogate code were encountered when
merging spatial surrogate codes with emissions. These are assigned to population.
Lists the AMS codes which did not match to spatial surrogates. Prints the first few
non-matched records. Prints summaries of non-matched emissions by pollutant and by
source category.
Summary of emissions by pollutant after spatial surrogate matching
Spatial surrogates frequency table
Warning message if records with no matching spatial factors were encountered when
matching spatial surrogates with emissions. Lists the first few records with no factors.
Summarizes emissions without factors by pollutant, by county, by source category,
and by surrogate.
Summary of emission rates by pollutant after spatial allocation
Summary of temporal profiles used
Summary of emission rates by pollutant after temporal factor merge
Warning message if records with no matching TAFs were encountered when merging
temporal allocation factors with emissions. Lists the AMS codes which did not match
to temporal factors. Prints the first few non-matched records. Prints summaries of
non-matched emissions by pollutant and by source category.
Summary of emission rates by pollutant after collapsing source categories to source
groups
Summary of temporally allocated emissions by pollutant
Run times for processing components
Pollutant sums by source category group
Emissions summaries by reactivity class
Contents of the core SAS* output emission data set
Contents of the extended SAS* output emission data set
Table of emissions totals by pollutant, with reactivity class, record counts, and the
average emissions for a tract
Summary of emissions by state
Frequencies of emissions sources by reactivity class
• Emissions totals by reactivity class
• Growth and control warning messages and summaries
At succeeding steps in the processing, emissions are summed and printed in the processing
output files. You should review these after completion of program execution, looking for
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changes in emissions, which then would need to be explained. These are the processing points
where emissions sums are reported:
• After reading the emissions, before any processing
• Before collapsing from CAS pollutants to SAROAD pollutant groups
• After collapsing from CAS pollutants to SAROAD pollutant groups
• After match/merge of spatial surrogates with emissions
• After spatial allocation of emissions
• After temporal allocations of emissions
• When writing out the ASPEN emissions files
You should also check the number of records in the several datasets that are created and modified
during the course of processing, to make sure they are reasonable. The number of records after
conversion from inventory pollutant codes to SAROAD codes can change for three reasons: 1)
some pollutants are dropped here, 2) some pollutants are split into two pollutants, and 3) after the
pollutants have been assigned to SAROAD code groups, the emissions are summed to the
SAROAD level. The increase in the number of records after spatial allocation results from the
distribution of all county-level emissions to the census tracts within those counties. The number
of records decreases when the emissions file is collapsed to the source group level. More
detailed information about the number of records in intermediate files can be found in the
processing log file.
Temporal allocation factors are matched to emission records according to source categories. If a
source category is present in the emissions file but absent in the temporal allocation factor file,
the emission record cannot be matched and is assigned a uniform (constant) profile. In this case
a warning message is printed to the AMProc list file along with a summary of how many
emission records were not matched, and a summary by source category of the non-matched
emissions. Inspection of this information shows which emissions categories need to be added to
the temporal allocation factor file, and the importance of each in terms of the amount of
emissions in the categories.
In AMProc, spatial surrogates are matched to mobile source emission records according to
source category AMS codes. If a source category is present in the emissions file but absent in
the spatial surrogate file, the emission record cannot be matched and is assigned the default
surrogate, population. In this case a warning message is printed to the AMProc output file along
with a summary of how many emission records were not matched, and a summary by source
category of the non-matched emissions. Inspection of this information allows you to see which
emissions categories need to be added to the spatial surrogate file, and the importance of each of
these in terms of the amount of emissions in the categories.
The spatial allocation factors are matched to emissions records according to spatial surrogates. If
these do not match properly, AMProc prints a warning message, summaries and other
information. The most common cause of non-matches is counties or census tracts missing from
one or more spatial allocation factor files.
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The HAP table file is matched to emission records according to the inventory pollutant code. If a
pollutant is present in the emissions file but absent in the HAP table, the emission record cannot
be matched. In this case a warning message is printed to the AMProc output file along with a
summary of how many emission records were not matched, and a summary by pollutant of the
non-matched emissions. Inspection of this information allows you to see which pollutants need
to be added to the HAP table.
The ASPEN emissions source groups assignment file is matched to emission records according
to source category and county urban/rural designation. If a source category is present in the
emissions file but absent in the ASPEN source groups file, the emission record cannot be
matched. In this case a warning message is printed to the AMProc output file along with a
summary of how many emission records were not matched, and a summary by source category
of the non-matched emissions. Inspection of this information allows you to see which source
categories need to be added to the ASPEN source groups file.
The county data file is matched to emission records according to FIPS state and county codes. If
a county is present in the emissions file but absent in the county data file, the emission record
cannot be matched. In this case a warning message is printed to the AMProc output file along
with a summary of how many emission records were not matched, and a summary by county of
the non-matched emissions. Inspection of this information allows you to see which counties
need to be added to the county data file.
10.3.3 Check other output flies
You should check for the existence of the ASPEN-input files. You should check that all nine
files were created and that emission data are included only in those files representing reactivities
classes for which you know your inventory has emission data. You may also want to check the
header of the files for the decay rate information.
You should check for the existence of the column formatted ASCII file and the core SAS® file.
Tables 10-5 and 10-6 show the format of each of these files. If you chose to create the extended
SAS® file (i.e., the keyword SAVEFILE=1), then you should check for its existence as well.
Table 10-7 shows the format of the extended file.
10-24
-------
Table 10-5. Format of AMProc ASCII Data File
(Values in order listed)
Description Type*
5-digit FIPS code; state and county combined A5
Census tract centroid location longitude (negative decimal degrees) 10.5
Census tract centroid location latitude (decimal degrees) 10.5
ASPEN Source type (0=points, 3=pseudo-points) Al
Urban/rural dispersion flag (1 for urban, 2 for rural) 1 -0
ASPEN Stack ID (same as State/County FIPS code) A5
constant = 999. 6-°
constant = 999. 6-°
constant = 999. • 6-°
constant = 999. 6-°
Unique pollutant group code (SAROAD code) A5
ASPEN source group (integer between 0 and 9, inclusive) Al
Emissions rate (grams/second) for the first 3-hour time period** E10.
Emissions rate, (grams/second) time period 2 ** E10.
Emissions rate, (grams/second) time period 3 ** E10.
Emissions rate, (grams/second) time period 4 ** E10.
Emissions rate, (grams/second) time period 5 ** E10.
Emissions rate, (grams/second) time period 6 ** E10.
Emissions rate, (grams/second) time period 7 ** E10.
Emissions rate, (grams/second) time period 8 ** E10.
Tract ID A6
Vent/stack flag Al
Building wake effects flag Al
Baseline annual emissions rate (tons/year) E12.5
Baseline annual emissions rate (grams/second) E12.5
* Ax = character string of length x, x.y = numeric format with y places right of decimal, Ex. = exponential
** Emission values represent projected emissions when you choose to perform EMS-HAP's emission projection capabilities
10-25
-------
Table 10-6. AMProc Core SAS® Output File Variables
Variable Name
CELL
EMIS
EMISBIN
EMISJTPY
IBLDG
IVENT
LAT
LON
NOSC
NOWD
NOWS
POLLCODE
REACT
SRCETYPE .
STACKID
STCOUNTY
TEMIS1
TEMIS2
TEMIS3
TEMIS4
TEMIS5
TEMIS6
TEMIS7
TEMIS8
TRACTR
UFLAG
WBANID
Description
State and county FIPS codes concatenated with the 6-digit tract ID
Baseline annual emissions rale (grams/second)
ASPEN source group (integer between 0 and 9, inclusive)
Baseline annual emissions rate (tons/year)
Building wake effects flag
Vent/stack flag
Census tract centroid location latitude (decimal degrees)
Census tract centroid location longitude (negative decimal degrees)
Excluded stability classes
Excluded wind directions
Excluded wind speeds
Unique pollutant-group code (SAROAD)
Reactivity class (integer between 1 and 9, inclusive)
Source type (0=points, 3=pseudo-points)
State/county FIPS code
State/county FIPS code
Emissions rate (grams/second) for the first 3-hour time period **
Emissions rate, (grams/second) time period 2 **
Emissions rate, (grams/second) time period 3 **
Emissions rate, (grams/second) time period 4 **
Emissions rate, (grams/second) time period 5 **
Emissions rate, (grams/second) time period 6 **
Emissions rate, (grams/second) time period 7 **
Emissions rate, (grams/second) time period 8 **
Tract ID
Urban/rural dispersion flag (l=urban, 2=rural)
Meteorological station ID
* Ax = character string of length x, x.y = numeric format with y places right of decimal, Ex. = exponential
** Emission values represent projected emissions when you choose to perform EMS-HAP's emission projection
Type*
All
N
N
N
Al
Al
N
N
A6
A6
A6
N
N
Al
All
A5
N
N
N
N
N
N
N
N
A6
Al
A5
capabilities
10-26
-------
Table 10-7. AMProc Extended SAS® Output File Variables
Variable Name
AMS
AVETAF
BASEMIS1**
BASEMIS2**
BASEMIS3**
BASEMIS4**
BASEMIS5**
BASEMIS6**
BASEMIS7**
BASEMIS8**
CATCODE
CELL
EMIS
EMISBIN
EXISTEFF**
GF**
LAT
LON
MACT
NEW_EFF**
NEWRATE**
NTI_HAP
POLLCODE
REACT
SICX**
STCOUNTY
SURR
Description
AMS source category code
Factor used to normalize temporal allocation factors
Baseline emissions rate (tons/year), time period 1
Baseline emissions rate (tons/year), time period 2
Baseline emissions rate (tons/year), time period 3
Baseline emissions rate (tons/year), time period 4
Baseline emissions rate (tons/year), time period 5
Baseline emissions rate (tons/year), time period 6
Baseline emissions rate (tons/year), time period 7
Baseline emissions rate (tons/year), time period 8
Source category code specified in the source group cross-reference file
State and county FTPS codes concatenated with the 6-digit tract ID
Baseline annual emissions rate (tons/year)
ASPEN source group
Control efficiency for existing sources
Growth factor
Census tract centroid location latitude (decimal degrees)
Census tract centroid location longitude (negative decimal degrees)
MACT code
Control efficiency for new sources
Percentage of grown emissions attributed to new sources
Code identifying HAP on the Clean Air Act HAP list
Unique pollutant-group code (SAROAD)
Reactivity class
4-digit SIC code
State/county FIPS code
Spatial allocation surrogate code
Type*
A10
N
N
N
N
N
N
N
N
N
A4
All
N
N
N
N
N
N
A4
N
N
A4
N
N
A4
A5
N
10-27
-------
Table 10-7. AMProc Extended SAS® Output File Variables (continued)
Variable Name
TF3HR1
TF3HR2
TF3HR3
TF3HR4
TF3HR5
TF3HR6
TF3HR7
TF3HR8
TEMIS1
TEMIS2
TEMIS3
TEMIS4
TEMIS5
TEMIS6
TEMIS7
TEMIS8
UFLAG
Description
Temporal allocation factor for the first 3-hour time period (dimensionless)
Temporal factor, time period 2
Temporal factor, time period 3
Temporal factor, time period 4
Temporal factor, time period 5
Temporal factor, time period 6
Temporal factor, time period 7
Temporal factor, time period 8
Emissions rate (tons/year) for the first 3-hour time period; represents
projected emissions when emission projections are done
Emissions rate (tons/year), time period 2; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 3; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 4; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 5; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 6; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 7; represents projected emissions
when emission projections are done
Emissions rate (tons/year), time period 8; represents projected emissions
when emission projections are done
Urban/rural dispersion flag (l=urban, 2=rural)
Type*
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Al
* Ax = character string of length x, N = numeric
** Variables included only when emission projections are done
10-28
-------
REFERENCES
1. User's Guide: Assessment System for Population Exposure Nationwide (ASPEN,
Version 1.1) Model. EPA-454-R-00-017, U.S. Environmental Protection Agency,
Research Triangle Park, NC. March 2000.
2. Driver, L.; Pope, A.; Billings, R.; Wilson, D. "The 1996 National Toxics Inventory and
Its Role in Evaluating the EPA's Progress in Reducing Hazardous Air Pollutants in
Ambient Air", Presented at the 92nd Annual Meeting of the Air & Waste Management
Association, St. Louis, Missouri, June 1999; paper 91-501.
3. Emigh, R.A.; Wilkinson, J.G. The Emissions Modeling System (EMS-95) User's Guide;
Alpine Geophysics, Inc., Boulder CO, 1995.
4. Causley, M.C.; Fieber, J.L.; Jiminez, M.; Gardner, L. User's Guide for the Urban Airshed
Model, Volume IV: User's Manual for the Emissions Preprocessor System, U.S.
Environmental Protection Agency, Research Triangle Park, NC, 1990; EPA-450/4-90-
007D.
5. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96-33r2,
Prepared for the U.S. Environmental Protection Agency, Office of Policy, Planning, and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 5-3 to
5-4.
6. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96-33r2,
Prepared for the U.S. Environmental Protection Agency, Office of Policy, Planning, and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 5-9 to
5-11.
R-l
-------
Appendix A: EMS-HAP Ancillary File Formats
-------
TABLE OF CONTENTS
Program Name List of Figures Corresponding to All Ancillary Files Needed Page #
AirportProc Figure 1. Airport Location and Allocation File (apt_allc) A-l
PtDataProc . Figure 2. Zip Code File (zipcodes) A-2
FigureS. County File (cty_cntr) A-3
Figure 4. State File (st_cntr) A-4
Figure 5. Counties File (counties) A-5
Figure 6. Boundary File (bound6) A-6
Figure 7. County Mapping File (cntyctr2) A-7
Figures. Tract Array File (trctarry) A-8
Figure 9. Tract Information File, including location of centroid A-9
and urban/rural flag (tractinf)
Figure 10. SCC-Based Default Stack Parameter File A-10
(def_scc.txt)
Figure 11. SIC-Based Default Stack Parameters File A-11
(def_sic.txt)
Figure 12. Additional Variables File (varlist.txt) A-12
PtAspenProc Figure 13. HAP Table File (haptabl_XXX.txt) A-13
Table 1. HAP Table File Used to Process 1996 NTI Point and A-14
Area Source Emissions Data (haptabl_point_area.txt)
Table 2. HAP Table File Used to Process Precursors from 1996 A-27
NTI and 1996 speciated NET Point, Area and Mobile Source
Emissions Data (haptabl_precursor.txt)
Table 3. HAP Table File Used to Process 1996 NTI Onroad A-29
Mobile Source Emissions Data (haptabl_onroad.txt)
Table 4. HAP Table File Used to Process 1996 NTI Nonroad A-30
Mobile Source Emissions Data (haptabl_nonroad.txt)
Figure 14. County-level Urban/Rural Flag File (ctyflag) A-31
Figure 9. Tract Information File, including location of centroid A-9
and urban/rural flag (tractinf)
A-i
-------
TABLE OF CONTENTS
(continued)
Program Name List of Figures Corresponding to All Ancillary Files Needed Page #
PtTemporal
PtGrowCntl
PtFinalFormat
AreaPrep
Figure 15. Temporal Allocation Factor File (taff_hourly.txt) A-32
Figure 16. SCC to AMS Cross-Reference File (scc2ams.txt) A-33
Figure 17. SIC to SCC or AMS Cross-Reference File A-34
(sic2ams.txt)
Figure 18. MACT Category to SCC or AMS Cross-Reference A-35
File (mact2scc.txt)
Figure 19. Growth Factor File to Grow from Year XX to Year A-36
YY (GFXX_YY)
Figure 20. SCC to SIC Cross-Reference File (ptscc2sic.txt) A-37
Figure 2la. General MACT Reduction Information File A-38
(MACT_gen.txt)
Figure 2 Ib. Specific MACT Reduction Information File A-39
(MACT_spec.txt)
Figure 22. Specific Facility Reduction Information File A-40
(SITE_spec.txt)
Figure 23. ASPEN Source Group Assignment by MACT A-41
Category File (MACT_grp.txt)
Figure 24. ASPEN Source Group Assignment by SCC Code A-42
File (SCC6_grp.txt)
Figure 25. ASPEN Source Group Assignment by SIC Code File A-43
(SIC_grp.txt)
Figure 26. Decay Rate File (indecay.txt) A-44
Figure 27. Spatial Surrogate Assignment File (surrxref.txt) A-45
Figure 16. SCC to AMS Cross-Reference File (scc2ams.txt) A-33
Figure 17. SIC to SCC or AMS Cross-Reference File A-34
(sic2ams.txt)
Figure 28. MACT Category to AMS or SCC Code Cross- A-46
Reference File (mact2ams.txt)
A-ii
-------
TABLE OF CONTENTS
(continued)
Program Name List of Figures Corresponding to All Ancillary Files Needed Page #
Figure 15. Temporal Allocation Factor File (taff_hourly.txt) A-32
MobilePrep There are no ancillary files for MobilePrep
AMProc Figure 26. Decay Rate File (indecay.txt) A-44
Figure 13. HAP Table File (haptabl__XXX.txt) A-13
Figure 15. Temporal Allocation Factor File (taff_hourly.txt) A-32
Figure 27. Spatial Surrogate Assignment File (surrxref.txt) A-45
Figure 29. Spatial Allocation Factor File (SAFn) A-47
Figure 30. Area and Mobile Source Group and Category Code A-48
Assignment File (am_grp.txt)
Figure 31. County-level Urban/Rural Designations File A-49
(popflg96.txt)
Figure 19. Growth Factor File to Grow from Year XX to Year A-36
YY (GFXX_YY)
Figure 2la. General MACT Reduction Information File A-38
(MACT_gen.txt)
Figure 2Ib. Specific MACT Reduction Information File A-39
(MACT_spec.txt)
Figure 32. Area and Mobile Source Reduction Information File A-50
(area_cntl.txt)
Figure 33. Area Emission Source Category to SIC Cross- A-51
Reference File (area_sic.txt)
A-iii
-------
File Name: aptjallc
File Type: SAS*
Variables and Structure
Name
ST FIPS
Cty_FIPS
Locid
Lat
Lon
Alloc
Arpt_nam
City
County
State
Activity
Fraction
Air_carr
Arpt_use
Type*
A2
A3
A4
N
N
N
A25
A6
Al
A2
N
N
A6
A2
Description
State FIPS code
County FIPS code
Latitude of the airport
Longitude of the airport
Allocation factor for activity within a specific airport. Sums to 1 .0 for
all of the airports In a particular county.
Airport name
Postal abbreviation
Airport activity, not used
Test variable, not used
Carrier code
Airport use, not used
* Ax=character string of length x, N=numeric
Sample records
01 001 1A9 32
Prattville
01 003 4R4 30.
Fairhope
01 005 EUF 31.
Eufaula
01 007 OA8 32,
Centreville
01 009 20A 33,
Oneonta
.43877500 86,
Autauga
.46211250 87
Baldwin
.95131917 85.
Barbour
,93679056 87.
Bibb
,97231972 86.
Blount
.51044778 1.0000 Autauga County
AL 0.08 1.0000 PU
.87801972 1.0000 Fairhope Muni
AL 3.00 0.9259 PU
.12892500 1.0000 Weedon Field
AL 3.00 0.9740 PU
08888306 1.0000 Bibb County
AL 0.08 1.0000. PU
37942722 1.0000 Robbins Field
AL 0.08 1.0000 PU
Figure 1. Airport Location and Allocation File (apt_allc)
A-l
-------
File Name: zipcodes
File Type: SAS*
Variables and Structure
Name
CntLon
CntLat
FIPS
Zip_Code
Type*
N
N
A5
A5
Description
Longitude of the zip code centroid (negative for West)
Latitude of the zip code centroid
State and county FIPS codes.
Zip Code
* Ax=character string of length x, N=numeric
Sample records
-156.767
-147.933
-156.977
-153.122
-149.675
-152.441
-130.561
-161.996
-150.557
-120.059
-120.503
-119.270
-123.612
-120.745
-121.188
-121.025
-119.927
-120.300
-123.313
-121.793
-122.725
-121.703
-123.209
-119.573
-119.829
-122.390
-122.813
-123.787
-123.620
-120.373
-120.297
-123.697
-123.253
-119.621
60.3045
66.3257
57.5460
60.2933
62.4791
68.9926
55.3437
62.5095
59.9493
39.0849
40.7815
37.5986
39.4520
41.5977
39.8527
35.7180
34 .9444
39.4885
41.6818
41.4740
40.0801
40.1609
40.3513
37.9598
38.5142
39.5797
39.3149
41.5751
41.2205
38.8950
38.6574
40.8768
•40.9764
37.6995
00001
00002
00003
00004
00006
00007
00008
00010
00011
00013
00019
00020
00022
00025
00028
00031
00032
00033
00034
00035
00037
00038
00039
00040
00044
00047
00048
00049
00050
00051
00052
00054
00055
00058
00000
00000
00000
00000
00000
00000
00000
00000
00000
06061
06035
06039
06045
06049
06063
06079
06083
06091
06093
06093
06103
06103
06105
06109
06003
06021
06033
06015
06023
06017
06017
06023
06105
06043
Figure 2. Zip Code File (zipcodes)
A-2
-------
File Name: cty_cntr
File Type: SAS*
Variables and Structure
Name Type*
FTPS A5
Cyname A25
AvgLat N
AvgLon N
Stname A20
Area mi2 N
Rad_mi N
Description
State and county FIPS codes
County Name
Latitude of the county centroid
Longitude of the county centroid
(negative for West)
State Name
Area of County (square miles)
Radius of County (miles)
*Ax=character string of length x, N=numeric
Sample records
01001 Autauga
01003 Baldwin
01005 Barbour
01007 Bibb
01009 Blount
01011 Bullock
01013 Butler
01015 Calhoun
01017 Chambers
01019 Cherokee
01021 Chilton
01023 Choctaw
01025 Clarke
01027 Clay
01029 Cleburne
01031 Coffee
01033 Colbert
01035 Conecuh
01037 Coosa *
01039 Covington
01041 Crenshaw
01043 Cullman
01045 Dale
01047 Dallas
01049 DeKalb
01051 Elmore
01053 Escambia
01055 Etowah
32.4967 -86.5162
30.6183 -87.7776
31.8521 -85.2971
33.0190 -87.0847
33.9834 -86.5568
32.0948 -85.7230
31.7685 -86.6697
33.7048 -85.8266
32.8743 -85.2889
34.1673 -85.6360
32.8601 -86.6811
31.9981 -88.2686
31.6937 -87.8321
33.2497 -85.8423
33.6396 -85.5005
31.3612 -85.9429
34.7323 -87.7110
31.4348 -86.9805
32.9756 -86.1582
31.2736 -86.3953
31.7370 -86.2985
34.1542 -86.8498
31.4013 -85.6303
32.3727 -87.0579
34.4634 -85.7886
32.5648 -86.2204
31.0848 -87.2756
34.0185 -86.0205
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
Alabama
597
1589
884
625
643
625
779
611
596
553
695
909
1230
605
561
680
589
854
657
1038
611
738
561
975
778
622
951
542
14
22
IV.
14
14
14
16
14
14
13
15
17
20
14
13
15
14
16
14
18
14
15
13
18
16
14
17
13
Figure 3. County File (cty_cntr)
A-3
-------
Name
StFips
State
Type*
A2
A2
Description
State FIPS (code)
State Name (2-letter abbreviation)
* Ax'=character string of length x, N=numeric
File Name: st_cntr
File Type: SASX
Variables and Structure
Sample records
01
04
05
06
08
09
10
11
12
13
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
44
45
46
47
48
AL
AZ
AR
CA
CO
CT
DE
DC
PL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
Figure 4. State File (st_cntr)
A-4
-------
File Name: counties
File Type: SAS*
Variables and Structure
Name
County
State
Segment
Density
X
Y
*Ax=charactei
Sample records
1 1
1 1
1 1
1 l
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
l 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
Type* Description
N County FIPS code
N State FIPS code
N County Segment Number
N Density for lower resolution map
N Unprojected longitude in radians
N Unprojected latitude in radians
string of length x, N=numeric
1 6 1.51449
1 3 1.51343
1 3 1.51344
1 6 1.51239
1 6 1.51191
1 0 1.50819
1 6 1.50818
1 6 1.50818
1 0 1.50816
1 6 1.50846
1 6 1.50858
1 6 1.50871
1 6 1.50882
1 6 1.50892
1 3 1.50902
1 6 1.50902
1 6 1.50903
1 6 1.50905
1 6 1.50906
1 6 1.50916
1 6 1.50925
1 6 1.50933
1 6 1.50945
1 6 1.50955
1 6 1.50957
1 6 1.50955
1 6 1.50956
1 0 1.50966
1 6 1.50970
1 6 1.50977
0.57006
0.57004
0.57081
0.57081
0.57082
0.57084
0.56884
0.56879
0.56566
0.56550
0.56549
0.56547
0.56550
0.56559
0.56557
0.56545
0.56533
0.56522
0.56510
0.56503
0.56492
0.56485
0.56490
0.56486
0.56475
0.56464
0.56453
0.56451
0.56450
0.56449
Figure 5. Counties File (counties)
A-5
-------
File Name:
File Type: SA
Variables and
Sample record
1.51703
1.53639
1., 49658
1. ,52579
I.'si780
1.50097
bound6
3*
Structure
Name
Xmax
Xmin
Ymax
Ymin
Segct
StCt
BegSeg
EndSeg
BegSt
EndSt
County
State
Segment
Type*
N
N
N
N
N
N
N
N
N
N
N
N
N
Description
Maximum x-value
Minimum x-value
Maximum y- value
Minmum y-value
Seg,ment count
Start count
Beginning segment
Ending segment
Beginning state
Ending state
County FIPS code
State FIPS code
County Segment Number
*Ax=character string of length x, N=numeric
s
1.50816 0.57084 0.56387 164 164 1 164 1
1.52492 0.54660 0.52746 429 592 165 593 • 1
1.48441 0.56109 0.55183 186 777 594 779 1
1.51627 0.58025 0.57299 44 820 780 823 1
1.50627 0.59795 0.58931 202 1021 824 1025 1
1.49068 0.56380 0.55641 87 1107 1026 1112 1
111
311
5 ' 1 1
711
911
11 1 1
Figure 6. Boundary File (bound6)
A-6
-------
File Name: cntyctr2
File Type: SAS*
Variables and Structure
Name
FIPST
FIPCNTY
State
Lon
Lat
County
TrueCnty
Type*
A5
A5
A2
N
N
A25
A25
*Ax=character string of length x,
Sample records
1 1
1 3
1 5
1 7
1 9
1 11
1 13
1 15
1 17
1 19
1 21
1 23
1 25
1 27
1 29
1 31
1 33
1 35
1 37
1 39
1 41
1 43
1 45
1 47
1 49
1 51
1 53
1 55
AL
AL
AL
AL
AL
AL
AL '
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Description
State FIPS codes.
County FIPS code
State (2-letter abbreviation)
Longitude of the county centroid (negative for West)
Latitude of the county centroid
County Name
True County Name
N=numeric
86.6642 32.5245
87.7021 30.7599
85.4021 31.8822
87.1486 33.0384
86.6334 34.0127
85.7047 32.0816
86.6773 31.7440
85.8380 33.7621
85.3594 32.9185
85.6211 34.2320
86.6969 32.8655
88.2019 32.0040
87.8198 31.5915
85.9075 33.2946
85.5963 33.7168
85.9928 31.4006
87.7832 34.7294
87.0479 31.4721
86.2590 32.9292
86.4441 31.2610
86.3228 31.7458
86.7850 34.0858
85.6035 31.4077
87.1441 32.3880 '
85.8158 34.5299
86.1442 32.5897
87.1521 31.1279
86.0353 34.0211
AUTAUGA
BALDWIN
HARBOUR
BIBB
BLOUNT
BULLOCK
BUTLER
CALHOUN
CHAMBERS
CHEROKEE
CHILTON
CHOCTAW
CLARKE
CLAY
CLEBURNE
COFFEE
COLBERT
CONECUH
COOSA
COVINGTON
CRENSHAW
CULLMAN
DALE
DALLAS
DEKALB
ELMORE
ESCAMBIA
ETOWAH
AUTAUGA
BALDWIN
BARBOUR
BIBB
BLOUNT
BULLOCK
BUTLER
CALHOUN
CHAMBERS
CHEROKEE
CHILTON
CHOCTAW
CLARKE
CLAY
CLEBURNE
COFFEE
COLBERT
CONECUH
COOSA
COVINGTON
CRENSHAW
CULLMAN
DALE
DALLAS
DE KALB
ELMORE
ESCAMBIA
ETOWAH
Figure 7. County Mapping File (cntyctr2)
A-7
-------
File Name: trctarry
File Type: SAS*
Variables and Structure
Name
FIPS
Tl ... T1652
N
*Ax=character
Type*
A5
A6
N
string of length x,
Description
State and county FIPS codes.
Random
array of tract numbers
missing or = 1653
N=numeric
Sample records (including variables Tl through TIO only)
01001 20300
01003 10902
01005 950700
01007 951300
01009 50400
01011 952300
01013 952800
01015 2500
01017 954100
01019 955800
01021 60402
01023 956700
01025 958000
01027 959200
01029 959500
01031 10400
01033 20400
01035 960200
01037 961000
01039 961600
01041 963600
21000
10400
950600
951600
50300
952400
953300
1700
954600
955900
60700
956800
957900
959000
959600
10800
21000
960300
961200
962700
963400
20100
11100
950500
951400
50600
952200
953100
2600
954200
955700
60500
957000
957500
958900
959700
11000
20100
960700
961100
962600
963700
20700
11202
950300
951500
50500
952100
953200
1000
953800
956100
60102
956900
957800
959100
959800
11100
20700
960600
962100
963800
20400
10600
950400
50200
952700
1600
954300
956000
60200
957600
10600
20500
960400
962500
963900
21100 20800
11300 10300
950100 950200
50102 50101
953400 952900
1800 2100
954700 954000
60101 60300
957700
10700 10300
20600 20800
960500
961900 962800
963500
20200 20900 20600
11600 10703 11401
950800 950900
50700
953500 953000
1900 1300 200
953700 954400 953900
60600 60401
10900 10200 11300
20900 20200 20300
962900 961700 962400
Figure 8. Tract Array File (trctarry)
A-8
-------
File Name: tractinf
File Type: SAS*
Variables and Structure
Name Type*
FIPS A5
Tract A6
TrLon N
TrLat N
TrRad N
Uflag N
Description
State and County
FIPS code
Tract Identification Number
Longitude of the
tract centroid
Latitude of the tract centroid
Radius of the tract
Urban/Rural flag
Values: 1 (urban), 2 (rural).
* Ax=character string of length x, N=numeric.
Sample records
01001 20100 -86.486433
01001 20200 -86.472171
01001 20300 -86.45861
01001 20400 -86.443581
01001 20500 -86.427195
01001 20600 -86.476381
01001 20700 -86.450539
01001 20800 -86.499096
01001 20900 -86.510556
01001 21000 -86.749412
01001 21100 -86.703688
01003 10100 -87.777357
01003 10200 -87.679484
01003 10300 -87.829813
01003 10400 -87.6968
01003 10500 -87.777433
01003 10600 -87.774911
01003 10701 -87.895933
01003 10702 -87.894121
01003 10703 -87.838217
01003 10800 -87.900319
01003 10901 -87.680218
01003 10902 -87.726362
01003 11000 -87.707953
01003 11100 -87.84749
01003 11201 -87.894621
01003 11202 -87.904921
01003 11300 -87.880924
01003 11401 -87.759805
01005 950100 -85.170708
01005 950200 -85.450932
32.474244
32.471439
32.474265
32.467688
32.449808
32.44054
32.448456
32.521553
32.639226
32.610292
32.466033
31.067326
30.954101
30.822099
30.759083
30.89022
30.861673
30.674223
30.640161
30.629101
30.594581
30.588978
30.549474
30.49058
30.502787
30.533266
30.512735
30.437874
30.390277
31.977997
31.887413
1.77
1.03
1.31
1.43
2.33
1.64
2.71
10.07
9.66
11.12
12.51
17.93
8.39
10.81
15.37
2.39
2.41
7.20
4.27
6.67
5.03
10.32
5.95
6.46
5.05
2.18
4.82
7.94
11.08
12.79
12.85
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Figure 9. Tract Information File, including location of centroid and urban/rural flag
(tractinf)
A-9
-------
File Name: def_scc.txt
File Type: ASCII Text
Variables and Structure
Name
sec
AvgHt
AvgDiam
AvgVel
AvgTemp
defflag
Type*
C
N
N
N
N
C
Column
1
12
27
42
57
74
Length
10
14
14
14
16
6
Decimals
10
10
10
10
Description
Source Category Code
Default Stack Height (in meters)
Default Stack Diameter (in meters)
Default Stack Exit Gas Velocity (in meters/second)
Default Stack Exit Gas Temperature (in Kelvin)
Default data flag that provides the source of the
default data (in the sample file, SCCNTI refers to
defaults used in generating the 1 996 NTI, and
SCCGEN was based on averages computed from
1996 NTI data).
*C = character, N = numeric.
Sample of File Contents
01020060 26.2006604013 0.8778257557 17.9984759970 308.1833333333 SCCgen
10000199 12.3992887986 0.7680975362 16.9987299975 547.1833333333 SCCgen
10100101 91.4063474750 4.5719527517 23.4699289010 421.6769452153 SCCgen
10100201 252.3749047498 6.5532131064 28.9560579121 433.3333333333 SCCNTI
10100202 137.1602743205 5.1816103632 23.1648463297 413.8888888889 SCCNTI
10100203 137.4650749302 4.4958089916 28.0416560833 427.2222222222 SCCNTI
10100204 67.0561341123 2.7523495047 11.5824231648 436.1111111111 SCCNTI
10100205 77.8547842810 3.8948728183 30.0310461192 461.0396825397 SCCgen
Figure 10. SCO-Based Default Stack Parameter File (def_scc.txt)
A-10
-------
File Name: def_sic.txt
File Type: ASCII Text
Variables and Structure
Name
SIC
AvgHt
AvgDiam
AvgVel
AvgTemp
defflag
Type*
C
N
N
N
N
C
Column
1
10
25
40
55
72
Length
5
14
14
14
16
6
Decimals
10
10
10
10
Description
State and County FIPS code
Default Stack Height (in meters)
Default Stack Diameter (in meters)
Default Stack Exit Gas Velocity (meters/second)
Default Stack Exit Gas Temperature (in Kelvin)
Default data flag that provides the source of the
default data (in the sample file, SICNTI refers to
defaults used in generating the 1996 NTI, and
SICGEN was based on averages computed from
1996 NTI data).
*C = character, N = numeric.
Sample of File Contents
0782 20.0297543452 0.9579447730 8.0619761240 476.1904761905 SICgen
0851 7.3152146304 0.8534417069 12.0640081280 450.0000000000 SICgen
0913 3.6576073152 4.1148082296 0.7040894082 316.6666666667 SICgen
0971 9.3016737758 0.4620269241 143.7890525781 870.1157407407 SICgen
1009 3.0480060960 0.2011684023 3.9989839980 295.5555555556 SICgen
1011 38.4018288037 2.4384048768 17.9984759970 360.1833333333 SICNTI
1021 18.3024786832 0.8445422628 13.3421590655 307.9009249972 SICgen
1031 21.0312420625 0.5577851156 46.9392938786 294.4444444444 SICgen
Figure 11. SJC-Based Default Stack Parameters File (def.slc.txt)
A-ll
-------
File Name: varlist.txt
File Type: ASCII Text
Variables and Structure
Name
Var
Keep
Type*
C
C
Column
1
16
Length
8
1
Description
Name of variable to be retained in inventory
Keep flag ('Y' to retain variable)
*C=character, N=numeric
Sample of File Contents
ADDRTYPE
AIRBASIN
AIRSPLID
AIRSPTID
AMS_CODE
AQCR
CITY
' COUNTRY
CTRLSTAT
CTY_FIPS
DB_NO
DESCRIPT
DIAM_FLG
D_HORIZ
D_UNITS
D_VERT
EMISTYPE
EPA_REG
FED2DESC
FED_ID
FED_ID2
FENCEDIS
FIPFLAG
FLOWRATE
FLOW_FLG
HT_FLG
IDDF_FLG
LLPROB
MACTFLAG
METHCODE
NTI_CODE
N_STACKS
PLUME_HT
SEGMT_ID
SEQ_NO
SITENAME
N
N
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
Figure 12. Additional Variables File (varlist.txt)
A-12
-------
File Name: haptabl_XXX.txt
File Type: ASCII Text
Variables and Structure
Name
POLLDESC
SAROADDC
POLLCODE
REACT
KEEP
SAROAD
FACTOR
NTI_HAP
Type*
C
C
C
N
C
C
N
C
Column
1
47
100
113
121
128
135
144
Length
45
50
10
1
1
5
7
3
Decimals
4
Description
Individual chemical name,
prior to aggregation
Name of the aggregated SAROAD code
Code identifying individual chemical in inventory
(typically a Chemical Abstracts System [CAS] No.)
Reactivity or Particle Size Class
Flag determining whether chemical will be modeled
Defines a single chemical or group of chemicals for
modeling. Can be an historic SAROAD code, or
arbitrarily assigned.
Emission adjustment factor
Code identifying HAP on the Clean Air Act HAP
list. Describes HAP code used only in growth and
control program
*C = character, N = numeric.
Sample of File Contents
POLLDESC
(Dichloromethyl) benzene
Pyrene
16-PAH
Benzofluoranthenes
Phenanthrene
Benzo [g , h, i , J perylene
Benzo [b+k] fluoranthene
Indeno (1 , 2 , 3 - c , d] pyrene
Benzo [b] fluoranthene
Benzo [k) fluoranthene
Chrysene
Benzo [a] pyrene
Dibenzo [a , h] anthracene
Benz [a] anthracene
HAPDESC
(Dichloromethyl) benzene - nonHAP
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
16-PAH,
fine
fine
fine
fine
fine
fine
fine
fine
fine
fine
fine
fine
fine
PM
PM
PM
PM
PM
PM
PM
PM
PM
PM
PM
PM
PM
POLLCODE
98873
129000
40
56832736
85018
191242
102
193395
205992
207089
218019
50328
53703
56553
React
2
2
2
2
2
2
2
2
2
2
2
2
2
Keep
N
N
N
N
N
N
N
N
N
N
N
N
N
N
SaroadFactor
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
NTI
165
165
165
165
165
165
165
165
165
165
165
165
165
Figure 13. HAP Table File (haptabl_XXX.txt)
A-13
-------
Table 1. HAP Table File Used to Process 1996 NTI Point and Area Source Emissions Data
POLLDESC
(Dichloromethyl) benzene
Pyrene
16-PAH
Benzofluoranthenes
Phenanthrene
Benzo[g,h,i,]perylene
Benzo[b+k]fluoranthene
Indeno[1,2,3-c,d]pyrene
Benzo[b]fluoranthene
Benzo [k]fluoranthene
Chrysene
Benzo[a]pyrene
Dibenzo[a,h]anthracene
Benz[a]anthracene
1-Phenanthrene
Acenaphthalene
Acenaphthene
Acenaphthylene
Anthracene
jFluoranthene
Fluorene
Naphthalene
2,6-Dimethyl-4-heptanone
4-Vinylcyclohexene
Benzo(b+k)fluoranthene
Indeno[1,2,3-c,d]pyrene
Benzo[b]fluoranthene
Benzo[k]fluoranthene
Chrysene
Benzo[a]pyrene
Dibenzo[a,h]anthracene
Benz [a]anthracene
7-PAH
Benzofluoranthenes
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
2 -Acetylaminofluorene
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
4 -Aminobiphenyl
Aniline
o-Anisidine
ANTIMONY TRICHLORIDE
HAPDESC
(Dichloromethyl) benzene - nonHAP
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
16-PAH, fine PM
2,6-Dimethyl-4-heptanone - nonHAP
4-Vinylcyclohexene - nonHAP
7-PAH, fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
7 - PAH,
7-PAH,
7-PAH,
7-PAH,
7-PAH,
7-PAH,
7-PAH,
7-PAH,
7-PAH,
Acetaldehyde
Acetamide
Acetonitrile
Acetophenone
Acetylaminofluorene, 2- , fine PM
Acrolein
Acrylamide
Acrylic acid
Acrylonitrile
Allyl chloride
Aminobiphenyl, 4 -
Aniline
Anisidine, o-
Antimony Compounds, coarse PM
POLLCODE
98873
129000
40
56832736
85018
191242
102
193395
205992
207089
218019
50328
53703
56553
283
78
83329
208968
120127
206440
86737
91203
108838
100403
102
193395
205992
207089
218019
50328
53703
56553
75
56832736
75070
60355
75058
98862
53963
107028
79061
79107
107131
107051
92671
62533
90040
10025919
React Keep
2
2
2
2
2
2
2
2
•2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
5
7
1
1
2
5 •
7
5
1
5
8
7
3
N
N
N
N
N
N
N
N
N
N
N
N
N
N'
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
Y
N
N
Y
N
N
N
N
N
SaroadFactor
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80232
80233
80233
80233
80233
80233
80233
80233
80233
80233
80233
43503
80101
70016
80103
53963
43505
80105
43407
43704
80108
92671
45701
80110
80311
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1,
1.
1
1.
1,
1.
1.
1.
0.
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
. 0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
,0000
.0000
.0000
.0000
.0000
.0000
.0000
,0000
,2402
NTI
165
165
165
165
165
165
165
165
165
165
165
165
165
16S
165
165
165
165
165
165
165
IfiS
165
165
165
165
165
165
165
165
165
37
38
39
40
23
41
42
43
44
45
33
46
149
47
A-14
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Antimony trioxide
Antimony Oxide
ANTIMONY TRISULFIDE
Antimony Pentafluoride
Antimony
Antimony & Compounds
Ant imony
ANTIMONY
Antimony
Ant imony
ANTIMONY
Antimony
Antimony
Antimony
Se Compounds
TRICHLORIDE
trioxide
Oxide
TRISULFIDE
Pentafluoride
& Compounds
Antimony & Compounds
ARSENIC PENTOXIDE
ARSENIC ACID
Arsenic Trioxide
Arsenic compounds (inorganic)
Arsenic
Arsine
Arsenic & Compounds (inorganic
Arsenic & Compounds (inorganic
ARSENIC PENTOXIDE
ARSENIC ACID
Arsenic Trioxide
Arsenic compounds (inorganic)
Arsenic
Arsine
Arsenic & Compounds (inorganic
Arsenic & Compounds (inorganic
Asbestos
Asbestos
Benzaldehyde
Benzene
Benzidine
Benzoic acid
Benzotrichloride
Benzoyl chloride
Benzyl chloride
Beryllium & Compounds
Beryllium Oxide
BERYLLIUM SULFATE
Beryllium
BERYLLIUM FLUORIDE
Beryllium & Compounds
Beryllium & Compounds
Beryllium Oxide
including
including
including
including
Antimony Compounds
Antimony Compounds
Antimony Compounds
Ant imony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Antimony Compounds
Arsenic Cmpds.
Arsenic Cmpds.
Arsenic Cmpds.
Arsenic Cmpds.
Arsenic Cmpds.
Arsenic Cmpds.
arsinArsenic Cmpds.
arsinArsenic Cmpds.
Arsenic Compou
Arsenic Compounds
Arsenic Compounds
Arsenic Compounds
Arsenic Compounds
Arsenic Compounds
arsinArsenic Compounds
arsinArsenic Compounds
Asbestos, coarse PM
Asbestos, fine
Benzaldehyde -
Benzene (inclu
Benzidine, gas
Benzoic acid -
Benzotrichloride
Benzoyl chloridi
Benzyl chloride
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
Beryllium Compounds
nds, coarse PM
nds, coarse PM
nds, coarse PM
nds , coarse PM
nds, coarse PM
.nds, coarse PM
.nds , coarse PM
nds, coarse PM
nds, fine PM
nds , f ine PM
.nds, fine PM
.nds, fine PM
.nds, fine PM
nds, fine PM
.nds, fine PM
.nds, fine PM
.nds, fine PM
(inorganic, incl. arsine) , coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
(inorganic, incl. arsine), coarse PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ids (inorganic, incl. arsine), fine PM
ie PM
PM
nonHAP
ling benzene from gasoline)
nonHAP
le
le - nonHAP
mnds, coarse PM
mnds , coarse PM
mnds , coarse PM
mnds, coarse PM
mnds, coarse PM
mnds, coarse PM
mnds, fine PM
mnds, fine PM
1309644
1327339
1345046
619
7440360
92
ANTCMPS
1
10025919
1309644
1327339
1345046
619
7440360
92
ANTCMPS
1
1303282
1327522
1327533
601
7440382
7784421
93
2
1303282
1327522
1327533
601
7440382
7784421
93
2
1332214
1332214
100527
71432
92875
65850
98077
98884
100447
109
1304569
13510491
7440417
7787497
3
109
1304569
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
3
2
1
7
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y-
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
Y
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
80311
80311
80311
80311
80311
80311
80311
80311
80111
80111
80111
80111
80111
80111
80111
80111
80111
80312
80312
80312
80312
80312
80312
80312
80312
80112
80112
80112
80112
80112
80112
80112
80112
45201
80115
80116
45810
80318
80318
80318
80318
80318
80318
80118
80118
0.3759
0.3570
0.3226
0.2528
0.4500
0.4500
0.4500
0.4500
0.2935
0.4594
0.4363
0.3942
0.3089
0.5500
0.5500
0.5500
0.5500
0.2673
0.2164
0.3105
0.4100
0.4100
0.3941
0.4100
0.4100
0.3846
0.3114
0.4469
0.5900
0.5900
0.5671
0.5900
0.5900
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
0.3200
0.1153
0.0275
0.3200
0.0613
0.3200
0.6600
0.2450
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
49
49
50
51
52
53
54
54
54
54
54
54
54
54
A-15
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
BERYLLIUM SULFATE
Beryllium
BERYLLIUM FLUORIDE
Beryllium S. Compounds
Biphenyl
Bis(2-ethylhexyl)phthalate
Bis(chloromethyl)ether
Bisphenol A
Brotnof orm
1,3-Butadiene
CADMIUM CHLORIDE
CADMIUM SULFATE
CADMIUM NITRATE
Cadmium & Compounds
Cadmium Oxide
CADMIUM SULFIDE
Cadmium
CADMIUM IODIDE
Cadmium & Compounds
CADMIUM CHLORIDE
CADMIUM SULFATE
CADMIUM NITRATE
Cadmium & Compounds
Cadmium Oxide
CADMIUM SULFIDE
Cadmium
CADMIUM IODIDE
Cadmium & Compounds
Calcium Cyanamide
Captan
Carbaryl
Carbon disulfide
Carbon tetrachloride
Carbonyl sulfide
Catechol
Chloramben
Chlordane
Chlorine
Chloroacetic acid
2-Chloroacetophenone
Chlorobenzene
Chlorobenzilate
Chloroform
Chloromethyl methyl ether
Chloroprene
Chlorotoluene
Calcium chromate
SODIUM CHROMATE(VI)
CHROMIUM CHLORIDE
Chromic Sulfate
Beryllium Compounds, fine PM
Beryllium Compounds, fine PM
Beryllium Compounds, fine PM
Beryllium Compounds, fine PM
Biphenyl
Bis(2-ethylhexyl)phthalate (DEHP), gas
Bis(chloromethyl) ether
Bisphenol A - nonHAP
Bromoform
Butadiene, 1,3-
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, coarse PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Cadmium Compounds, fine PM
Calcium Cyanamide
Captan, gas
Carbaryl, gas
Carbon disulfide
Carbon tetrachloride
Carbonyl sulfide
Catechol
Chloramben
Chlordane, gas
Chlorine
Chloroacetic acid
Chloroacetophenone, 2-
Chlorobenzene
Chlorobenzilate, fine PM
Chloroform
Chloromethyl methyl ether
Chloroprene
Chlorotoluene - nonHAP
Chromium Compounds, fine PM
Chromium Compounds, coarse PM
Chromium Compounds, coarse PM
Chromium Compounds, coarse PM
13510491
7440417
7787497
3
92524
117817
542881
80057
75252
106990
10108642
10124364
10325947
125
1306190
1306236
7440439
7790809
4
10108642
10124364
10325947
125
1306190
1306236
7440439
7790809
4
156627
133062
63252
75150
56235
463581
120809
133904
57749
7782505
79118
532274
108907
510156
67663
107302
126998
25168052
13765190
10034829
10060125
10101538
2
2
2
2
9
1
1
1
7
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
7
5
1
1
1
5
1
1
1
1
1
2
1
1
6
2
3
3
3
Y
Y
Y
Y
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
Y
N
N
N
Y
Y
Y
Y
80118
80118
80118
80118
45226
45470
80121
80122
43218
80324
80324
80324
80324
80324
80324
80324
80324
80324
80124
80124
80124
80124
80124
80124
80124
80124
80124
80127
80128
43934
43804
43933
80132
80134
80135
80136
45801
43803
80139
43862
80141
80341
80341
80341
0.0583
0.6800
0.1304
0.6800
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
0.1471
0.1294
0.1141
0.2400
0.2101
0.1867
0.2400
0.0737
0.2400
0.4660
0.4098
0.3613
0.7600
0.6652
0.5912
0.7600
0.2332
0.7600
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
0.2366
0.0931
0.0952
0.0496
54
54
54
54
56
57
58
59
10
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
61
62
63
64
65
66
67
68
69
70
71
24
178
73
74
75
76
77
77
77
77
A-16
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Barium chromate
Sodium dichromate
POTAS ZNC CHROM HYDR
CHROMIC ACID*OBSOLET
CHROMIUM DIOXIDE
CHROMIUM ZINC OXIDE
ZINC CHROMATES
CHROMIUM HYDROXIDE
Chromic Oxide
Chromium trioxide
Zinc Chromate
CHROMIC ACID
Chromium & Compounds
LITHIUM CHROMATE
CHROMYL CHLORIDE
Chromium III
LEAD CHROMATE OXIDE
Chromium +6
ZINC CHROMITE
Chromium
Chromic Acid
Lead chromate
CHROMIC ACID,(H2CR04
POTASSIUM DICHROMATE
CHROMYL FLUORIDE'
POTASSIUM CHROMATE
Strontium chromate
AMMONIUM DICHROMATE
Calcium chromate
Chromium & Compounds
SODIUM CHROMATE(VI)
CHROMIUM CHLORIDE
Chromic Sulfate
Barium chromate
Sodium dichromate
POTAS ZNC CHROM HYDR
CHROMIC ACID*OBSOLET
CHROMIUM DIOXIDE
CHROMIUM ZINC OXIDE
ZINC CHROMATES
CHROMIUM HYDROXIDE
Chromic Oxide
Chromium trioxide
Zinc Chromate
CHROMIC ACID
Chromium & Compounds
LITHIUM CHROMATE
CHROMYL CHLORIDE
Chromium III
LEAD CHROMATE OXIDE
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Chromium
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds,
Compounds ,
Compounds ,
Compounds,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
Compounds ,
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
coarse PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
10294403
10588019
11103869
11115745
12018018
12018198
1308130
1308141
1308389
1333820
13530659
13530682
136
14307358
14977618
16065831
18454121
18540299
50922297
7440473
7738945
7758976
7775113
7778509
7788967
7789006
7789062
7789095
13765190
5
10034829
10060125
10101538
10294403
10588019
11103869
11115745
12018018
12018198
1308130
1308141
1308389
1333820
13530659
13530682
136
14307358
14977618
16065831
18454121
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80341
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
.80141
0.0595
0.1151
0.0632
0.1278
0.1795
0.1292
0.0831
0.1464
0.1984
0.1508
0.0831
0.1278
0.2900
0.1161
0.0974
0.2900
0.0276
0.2900
0.0813
0.2900
0.1278
0.0467
0.1278
0.1025
0.1236
0.0776
0.0741
0.1197
0.0966
0.2900
0.2279
0.2331
0.1213
0.1458
0.2819
0.1548
0.3128
0.4395
0.3164
0.2036
0.3583
0.4858
0.3692
0.2036
0.3128
0.7100
0.2842
0.2383
0.7100
0.0676
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
122
77
77
77
77
122
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
77
122
A-17
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Chromium +6
ZINC CHROMITE
Chromium
Chromic Acid
Lead chromate
CHROMIC ACID,(H2CR04
POTASSIUM DICHROMATE
CHROMYL FLUORIDE
POTASSIUM CHROMATE
Strontium chromate
AMMONIUM DICHROMATE
Chromium & Compounds
COBALT SULFATE
COBALT OXIDE
COBALT OXIDE-C03O4
COBALT SULFIDE
COBALT ALUMINATE
Cobalt & Compounds
COBALT CARBONATE 1:1
COBALT NAPHTHA
Cobalt Hydrocarbonyl
Cobalt
Cobalt & Compounds
COBALT SULFATE
COBALT OXIDE
COBALT OXIDE-C0304
COBALT SULFIDE
COBALT ALUMINATE
Cobalt & Compounds
COBALT CARBONATE 1:1
COBALT NAPHTHA
Cobalt Hydrocarbonyl
Cobalt
Cobalt & Compounds
Coke Oven Emissions
Cresols (includes o,
o-Cresol
p-Cresol
m-Cresol
Cresol
Cumene
SODIUM CYANIDE
Potassium Cyanide
SILVER CYANIDE
ZINC CYANIDE C2N2ZH
POTASSIUM FERROCYANI
BENZYL CYANIDE
POTASS NICKEL CYANID
GOLD CYANIDE
COPPER CYANIDE
ra, & p)/Cresylic Acids
Chromium Compounds, fine PM 18540299 2 Y
Chromium Compounds, fine PM 50922297 2 Y
Chromium Compounds, fine PM 7440473 2 Y
Chromium Compounds, fine PM 7738945 2 Y
Chromium Compounds, fine PM 775897S 2 Y
Chromium Compounds, fine PM 7775113 2 Y
Chromium Compounds, fine PM 7778509 2 Y
Chromium Compounds, fine PM 7788967 2 Y
Chromium Compounds, fine PM 7789006 2 Y
Chromium Compounds, fine PM 7789062 2 Y
Chromium Compounds, fine PM 7789095 2 Y
Chromium Compounds, fine PM 5 2 Y
Cobalt Compounds, coarse PM 10124433 3 N
Cobalt Compounds, coarse PM 1307966 3 N
Cobalt Compounds, coarse PM 1308061 3 N
Cobalt Compounds, coarse PM 1317426 3 N
Cobalt Compounds, coarse PM 1345160 3 N
Cobalt Compounds, coarse PM 139 3 N
Cobalt Compounds, coarse PM 513791 3 N
Cobalt Compounds, coarse PM 61789513 3 N
Cobalt Compounds, coarse PM 16842038 3 N
Cobalt Compounds, coarse PM 7440484 3 N
Cobalt Compounds, coarse PM 6 3 N
Cobalt Compounds, fine PM 10124433 2 N
Cobalt Compounds, fine PM 1307966 2 N
Cobalt Compounds, fine PM 1308061 2 N
Cobalt Compounds, fine PM 1317426 2 N
Cobalt Compounds, fine PM 1345160 2 N
Cobalt Compounds, fine PM 139 2 N
Cobalt Compounds, fine PM 513791 2 N
Cobalt Compounds, fine PM 61789513 2 N
Cobalt Compounds, fine PM 16842038 2 N
Cobalt Compounds, fine PM 7440484 2 N
Cobalt Compounds, fine PM 6 2 N
Coke Oven Emissions, fine PM 140 2 Y
Cresol/Cresylic acid (mixed isomers), fine PM 331 2 N
Cresol/Cresylic acid (mixed isomers), fine PM 95487 2 N
Cresol/Cresylic acid (mixed isomers), gas 106445 2 , N
Cresol/Cresylic acid (mixed isomers), gas 108394 2 N
Cresol/Cresylic acid (mixed isomers), gas ' 1319773 2 N
Cumene 98828 9 N
Cyanide Compounds, coarse PM . 143339 3 N
Cyanide Compounds, coarse PM 151508 3 N '
Cyanide Compounds, coarse PM 506649 3 N
Cyanide Compounds, coarse PM 557211 3 N
Cyanide Compounds, fine PM 13943583 2 N
Cyanide Compounds, fine PM 140294 2 N
Cyanide Compounds, fine PM 14220178 2 N
Cyanide Compounds, fine PM 37187647 2 N
Cyanide Compounds, fine PM 544923 2 N
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80141
80342
80342
80342
80342
80342
80342
80342
80342
80342
80342
80342
80142
80142
80142
80142
80142
80142
80142
80142
80142
80142
80142
80411
45605
45605
45605
45605
45605
45210
80143
80143
80143
80143
80144
80144
80144
80144
80144
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
.7100
.1990
.7100
.3128
.1142
.3128
.2510
.3026
.1901
.1813
.2929
.7100
.0760
.1573
.1468
.1295
.0666
.2000
.0991
.0290
.0689
.2000
.2000
.3042
.6292
.5874
.5182
.2666
.8000
.3964
.1158
.2782
.8000
.8000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.5309
.3996
.1943
.4432
.4238
.2221
.4019
.1167
.2905
77
77
77
77
122
77
77
77
77
77
77
77
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
79
80
80
80
80
80
81
82
82
82
82
82
82
82
82
82
A-18
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
GOLD POTASSIUM CYANI
Cyanide
Cyanide & Compounds
Hydrogen Cyanide
2 -Methyl-Propanenit rile
Cyanide & Compounds
2,4-Dichlorophenoxy acetic acid
DDE (1,l-dichloro-2,2-bis(p-chlorophenyl)
Dibenzofuran
1,2-Dibromo-3-chloropropane
Dibutyl phthalate
1,4-Dichlorobenzene
3,3'-Dichlorobenzidene
Dichloroethyl ether
1,3-Dichloropropene
Dichlorvos
Diesel PM
Diesel PM
Diethanolamine
Diethyl sulfate
3,3'-Dimethoxybenzidine
4-Dimethylaminoazobenzene
Dimethylcarbamoyl chloride
N,N-Dimethylformamide
1,1-Dimethyl hydrazine
Dimethyl phthalate
Dimethyl Sulfate
3,3'-Dimethylbenzidine
4,6-Dinitro-o-cresol
2,4-Dinitrophenol
2,4-Dinitrotoluene
p-Dioxane
Dioxins
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1,2,3,7,8,9-hexachlorodibenzo-p-dioxin
Pentachlorodibenzo-p-dioxin
Pentachlorodibenzofuran
Octachlorodibenzo-p-dioxin
1,2,3,4,6,7,8-heptachlorodibenzo-p-/dioxin
Oct achlorodibenzofuran
1,2,3,4,7,8-hexachlorodibenzo-p-dioxin
1,2,3,7,8-pentachlorodibenzo-p-dioxin
2,3,7,8-Tetrachlorodibenzofuran
1,2,3,4,7,8,9-heptachlorodibenzofuran
2,3,4,7,8-pentachlorodibenzofuran
1,2,3,7,8-pentachlorodibenzofuran
1,2,3,6,7,8-hexachlorodibenzofuran
1,2,3,6,7,8-hexachlorodibenzo-p-dioxin
2,3,7,8-TCDD TEQ
2,3,4,6,7,8-hexachlorodibenzofuran
Cyanide Compounds,
Cyanide Compounds,
Cyanide Compounds,
Cyanide Compounds,
fine PM
fine PM
gas
gas
Cyanide Compounds, gas
Cyanide Compounds, gas
D, 2,4- (including salts and esters), gas
ethyDDE
Dibenzofuran, gas
Dibromo-3-chloropropane, 1,2-
Dibutylphthalate, gas
Dichlorobenzene,p 1,4-
Dichlorobenzidene, 3,3'- , gas
Dichloroethyl ether (Bis[2-chloroethyl]ether)
Dichloropropene, 1,3-
Dichlorvos
Diesel, coarse PM
Diesel, fine PM
Diethanolamine
Diethyl sulfate
Dimethoxybenzidine, 3,3'-, gas '
Dimethyl aminoazobenzene, 4- , fine PM
Dimethyl carbamoyl chloride
Dimethyl formamide
Dimethyl hydrazine, 1,1-
Dimethyl phthalate
Dimethyl sulfate
Dimethylbenzidine, 3,3'- , fine PM
Dinitro-o-cresol, 4,6- , gas
Dinitrophenol, 2,4- , gas
Dinitrotoluene, 2,4-
Dioxane, 1, 4
Dioxins/Furans as 2,3,7,8TCCD TEQ,
Dioxins/Furans as 2,3,7,8TCCD TEQ,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
Lower Bound,
8TCCD TEQ, Lower Bound,
8TCCD TEQ, Lower Bound,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
8TCCD TEQ,
Dioxins/Furans as 2,3,7,8TCCD TEQ, Lower Bound,
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
554074
57125
144
74908
78820
7
94757
72559
132649
96128
84742
106467
91941
111444
542756
62737
80400
80400
111422
64675
119904
60117
79447
68122
57147
131113
77781
119937
534521
51285
121142
123911
155
1746016
19408743
36088229
30402154
3268879
35822469
39001020
39227286
40321764
51207319
55673897
57117314
57117416
57117449
57653857
600
60851345
2
2
1
1
1
1
1
2
1
. 1
1
1
1
5
4
4
3
2
7
1
7
2
0
7
7
1
1
2
1
5
1
5
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
Y
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
80144
80144
80145
80145
80145
80145
80146
80247
92672
45452
45807
80150
80151
80152
80153
80401
80400
80154
80156
8^157
92673
92674
43450
80159
45451
80161
92675
80162
80163
80164
80165
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
0.1806
1.0000
1.0000
0.9627
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
0.0000
1.0000
0.1000
0.0500
0.0495
0.0010
0.0100
0.0010
0.1000
0.5000
0.1000
0.0100
0.5000
0.0500
0.1000
0.1000
1.0000
0.1000
82
82
82
82
82
82
19
83
902
6
86
13
26
87
11
88
89
90
27
34
93
142
3
91
92
28
32
20
21
108
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
A-19
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Dibenzofurans (chlorinated) {PCDFs}
Dioxins, total, w/o Individ, isomers reported
1,2,3,4,6,7,8-heptachlorodibenzofuran
1,2,3,4,7,8-hexachlorodibenzofuran
1,2,3,7,8,9-hexachlorodibenzofuran
Dioxins/Furans as TEQ
Hexachlorodibenzo-p-dioxin
Polychlorinated dibenzo-p-dioxin, total
Polychlorinated dibenzofurans, total
Total tetrachlorodibenzo-p-dioxin
Dioxins
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1,2,3,7,8,9-hexachlorodibenzo-p-dioxin
Pentachlorodibenzo-p-dioxin
Pentachlorodibenzofuran
Octachlorodibenzo-p-dioxin
1,2,3,4,6,7,8-heptachlorodibenzo-p-/dioxin
Octachlorodibenzofuran
1,2,3,4,7,8-hexachlorodibenzo-p-dioxin
1,2,3,7,8-pentachlorodibenzo-p-dioxin
2,3,7,8-Tetrachlorodibenzofuran
1,2,3,4,7,8, 9 -heptachlorodibenzof uran
2,3,4,7,8-pentachlorodibenzofuran
1,2,3,7,8-pentachlorodibenzofuran
1,2,3,6,7,8-hexachlorodibenzofuran
1,2,3,6,7,8-hexachlorodibenzo-p-dioxin
2,3,7,8-TCDD TEQ
2,3,4,6,7,8-hexachlorodibenzofuran
Dibenzofurans (chlorinated) {PCDFs}
Dioxins, total, w/o individ. isomers reported
1,2,3,4,6,7,8-heptachlorodibenzofuran
1,2,3,4,7,8-hexachlorodibenzofuran
1,2,3,7,8,9-hexachlorodibenzofuran
Dioxins/Furans as TEQ
Hexachlorodibenzo-p-dioxin
Polychlorinated dibenzo-p-dioxin, total
Polychlorinated dibenzofurans, total
Total tetrachlorodibenzo-p-dioxin
1,2-Diphenylhydrazine
l-Chloro-2,3-Epoxypropane
1,2-Epoxybutane
Ethyl Chloride
Ethyl Acrylate
Ethyl carbamate chloride
Ethyl Benzene
Ethylene Dibromide
Ethylene Dichloride
Ethylene Glycol
Ethylene Oxide
Ethylene thiourea
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3.
Dioxins/Furans as 2,3,
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3.
Dioxins/Furans as 2,3,
Dioxins/Furans as 2,3,
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3,
8TCCD TEQ, Lower Bound,
8TCCD TEQ, Lower Bound,
8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Lower Bound,
7.8TCCD TEQ, Lower Bound,
7.8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Lower Bound,
7,8TCCD TEQ, Upper Bound,
7,8TCCD TEQ, Upper Bound,
7.8TCCD TEQ, Upper Bound,
7,8TCCD TEQ, Upper Bound,
7,8TCCD TEQ, Upper Bound,
Dioxins/Furans as 2,3,7,8TCCD TEQ, Upper Bound
Dioxins/Furans as 2,3,7,8TCCD TEQ, Upper Bound
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
8TCCD TEQ, Upper Bound,
Dioxins/Furans as 2,3,7
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,
Dioxins/Furans as 2,3,7,8TCCD TEQ, Upper Bound
Dioxins/Furans as 2,3,7,8TCCD TEQ, Upper Bound
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Diphenylhydrazine
7.8TCCD TEQ, Upper Bound,
7.8TCCD TEQ, Upper Bound,
7,8TCCD TEQ, Upper Bound,
7.8TCCD TEQ, Upper Bound,
1,2-
Epichlorohydrin (l-Chloro-2,3-epoxypropane)
Epoxybutane, 1,2-
Ethyl Chloride (Chloroethane),
Ethyl acrylate
Ethyl carbamate (Urethane)
Ethylbenzene
Ethylene dibromide (Dibromoethane)
Ethylene dichloride (1, 2-Dichloroethane)
Ethylene glycol
Ethylene oxide
Ethylene thiourea
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
Fine
609
610
67562394
70648269
72918219
701
34465468
623
624
41903575
155
1746016
19408743
36088229
30402154
3268879
35822469
39001020
39227286
40321764
51207319
55673897
57117314
57117416
57117449
576538S7
600
60851345
609
610
67562394
70648269
72918219
701
34465468
623
624
41903575
122667
106898
106887
75003
140885
51796
100414
106934
107062
107211
75218
96457
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y.
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
Y
Y
Y
N
Y
N
80412
80412
80412
80412
80412
80412
80412
80412
80412
80412
80245
80245
80245
80245
80245
80245
80245
80245
80245'
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
80245
92676
43863
80167
43812
43438
80170
45203
43837
43815
43370
43601
80177
0.
0.
0.
0.
0.
1.
0.
0.
0.
0.
1.
1.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
1 .
0.
0.
1.
0.
0.
0.
1.
0.
1.
0.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
0000
0000
0100
1000
1000
0000
0000
0000
0000
0000
0000
0000
1000
0500
0495
0010
0100
0010
1000
5000
1000
0100
5000
0500
1000
1000
0000
1000
5000
0000
0100
1000
1000
0000
1000
0000
1000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
903
7
94
8
97
95
96
98
99
100
101
102
103
A-20
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Ethyleneimine
Ethylidene Dichloride
Fine Mineral Fibers
Glasswool (man-made fibers)
Formaldehyde
Furfuryl alcohol
Gasoline
Ethylene Glycol Methyl Ether
Ethylene Glycol Methyl Ether
Ethylene Glycol Monomethyl Ether Acetate
1,2-Dimethoxyethane
Cellosolve Solvent
Cellosolve Acetate
Butyl Cellosolve
Diethylene Glycol Monomethyl Ether
Diethylene glycol monoethyl ether
Diethylene glycol dimethyl ether
2-Butoxyethyl Acetate
Carbitol Acetate
2-(Hexyloxy)Ethanol
Diethylene Glycol Monobutyl Ether
Methoxytriglycol
Triethylene glycol dimethyl ether
Ethoxytriglycol
N-Hexyl Carbitol
Phenyl Cellosolve
Butyl Carbitol Acetate
Triglycol Monobutyl Ether
Glycol ethers
Propyl Cellosolve
Propylene Glycol Monomethyl Ether
Propylene Glycol Methyl Ether Acetate
Isopropyl Glycol
3-Ethoxy-l-Propanol
Diethylene Glycol
Triethylene Glycol
1-Ethoxy-2 -Propanol
Dipropylene Glycol Monomethyl Ether
Diethylene Glycol Di(3-Aminopropyl) Ether
1,1-Dimethoxyethane
Propylene Glycol T-Butyl Ether
Nonyl Phenyl Polyethylene Glycol Ether
Glycols, Polyethylene,
Glycols, Polyethylene,
Heptachlor
Hexachlorobenzene
Hexachlorobutadiene
ethers
ethers
ethers
ethers
ethers
ethers
ethers
ethers
ethers
ethe'rs
ethers
ethers
ethers
Glycol ethers
Glycol ethers
Glycol ethers
Mono(l,1,3,3-TetramethyGlycol ethers
Polypropylene MonobutylGlycol ethers
Heptachlor, gas
Hexachlorobenzene
Hexachlorobutadiene
Ethyleneimine (Aziridine)
Ethylidene dichloride (1,1-Dichloroethane)
Fine mineral fibers, coarse PM
Fine mineral fibers, coarse PM
Formaldehyde
Furfuryl alcohol - nonHAP
Gasoline - nonHAP
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
Glycol ethers, gas
gas
gas
gas
gas
gas
gas
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
non HAP
Glycol ethers,
Glycol ethers,
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Glycol
Hexachlorocyc1opent adiene
Hexachloroethane
Hexamethylene diisocyanate
Hexachlorocyclopentadiene
Hexachloroethane
Hexamethylene-l,6-diisocyanate,
gas
151564
75343
383
613
50000
98000
8006619
100805
109864
110496
110714
110805
111159
111762
111773
111900
111966
112072
112152
112254
112345
112356
112492
112505
112594
122996
124174
143226
171
2807309
107982
108656
109591
111353
111466
112276
1569024
34590948
4246519
534156
621
9016459
9036195
9038953
76448
118741
87683
77474
67721
822060
7
1
3
3
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
1
1
1
1
1
N
N
N
N
y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N1
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
N
N
80175
43813
43502
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
43367
80182
80183
80184
80185
80186
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
104
105
106
106
107
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
108
109
110
111
112
113
114
A-21
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Hexamethylphosphoramide
Hexane
Hydrazine
Hydrazine monohydrate
Hydrochloric acid
Hydrogen fluoride
Hydroquinone
Isobutyraldehyde
Isodecanol
Isophorone
Isophorone diisocyanate
Isovaleraldehyde
Lead Arsenite
LEAD NITRATE
LEAD TITANATE
LEAD TITANATE ZIRCON
LEAD OXIDE
LEAD TETROXIDE P 304
Lead Oxide
LEAD MONO OXIDE
LEAD FLUOROBORATE
,LEAD CHROMATE OXIDE
Lead & Compounds
LEAD CARBONATE
Lead compounds (inorganic)
Lead Oxide
Lead
LEAD SULFATE
Lead chromate
LEAD ARSENATE
LEAD NEODECANOATE
Lead acetate
Lead compounds (other than inorganic)
LEAD NAPHTHENATE
LEAD STEARATE
Tetraethyl Lead
Alkylated lead
Lead Arsenite
LEAD NITRATE
LEAD TITANATE
LEAD TITANATE ZIRCON
LEAD OXIDE
LEAD TETROXIDE P 304
Lead Oxide
LEAD MONO OXIDE
LEAD FLUOROBORATE
LEAD CHROMATE OXIDE
Lead & Compounds
LEAD NEODECANOATE
Lead acetate
Hexamethylphosphoramide
Hexane
Hydrazine
Hydrazine monohydrate - nonHAP
Hydrochloric acid (Hydrogen chloride), fine PM
Hydrogen fluoride (Hydrofluoric acid), fine PM
Hydroquinone
Isobutyraldehyde - nonHAP
Isodecanol - nonHAP
Isophorone
Isophorone diisocyanate - nonHAP
Isovaleraldehyde - nonHAP
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, coarse PM
Lead Compounds, fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
fine PM
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
Lead Compounds,
680319
110543
302012
7803578
7647010
7664393
123319
78842
25339177
78591
4098719
590863
10031137
10099748
12060003
12626812
1309600
1314416
1317368
13173681
13814965
18454121
195
598630
602
620
7439921
7446142
7758976
7784409
27253287
301042
603
61790145
7428480
78002
88
10031137
10099748
12060003
12626812
1309600
1314416
1317368
13173681
13814965
18454121
195
27253287
301042
0
9
7
2
2
5
7
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
2
2
2
N
Y
Y
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
43231
80188
80189
80190
80191
80192
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80393
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
0.1385
0.1627
0.1777
0.1777
0.2252
0.2357
0.2414
0.2414
0.1415
0.1972
0.2600
0.2016
0.2600
0.2414
0.2600
0.1776
0.1667
0.1552
0.0980
0.1656
0.2600
0.0970
0.0696
0.1666
0.2600
0.3941
0.4629
0.5059
0.5059
0.6410
0.6710
0.6869
0.6869
0.4026
0.5612
0.7400
0.2789
0.4714
115
116
117
118
119
120
121
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
122
A-22
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
LEAD CARBONATE
Lead compounds (inorganic)
Lead compounds (other than inorganic)
LEAD NAPHTHENATE
Lead Oxide
LEAD STEARATE
Lead
LEAD SULFATE
Lead chromate
LEAD ARSENATE
Tetraethyl Lead
Alkylated lead
1,2,3,4,5,6-Hexachlorocyclyhexane
Maleic Anhydride
MANGANESE NITRATE
Manganese Dioxide
Manganese Tetroxide
MANGANESE NAPTHENATE
Manganese & Compounds
Manganese
MANGANESE TALLATE
Manganese sulfate
Manganese & Compounds
MANGANESE NITRATE
Manganese Dioxide
Manganese Tetroxide
MANGANESE NAPTHENATE
Manganese & Compounds
Manganese
MANGANESE TALLATE
Manganese sulfate
Manganese & Compounds
Mercuric chloride
Mercury & Compounds
MERCURY (ORGANIC)
MERCURY ACETATO PHEN
Mercury
Mercury t Compounds
Methacrylic acid
Methanol
Methly Methly Isobutyl Carbinol
Methoxychlor
Methyl acrylate
Methyl bromide
Methyl chloride
Methyl Chloroform
Methyl ethyl ketone
MethyIhydraz ine
Methyl iodide
Methyl isobutyl ketone
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lead Compounds, fine PM
Lindane (all isomers), gas
Maleic anhydride
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, coarse PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Manganese Compounds, fine PM
Mercury Compounds, fine PM
Mercury Compounds, gas
Mercury Compounds, gas
Mercury Compounds, gas
Mercury Compounds, gas
Mercury Compounds, gas
Methacrylic acid - nonHAP
Methanol
Methly Isobutyl Carbinol - nonHAP
Methoxychlor, gas
Methyl acrylate - nonHAP
Methyl bromide (Bromomethane)
Methyl chloride (Chloromethane)
Methyl chloroform (1,1,1-Trichloroethane)
Methyl ethyl ketone (2-Butanone)
Methyl hydrazine
Methyl iodide (lodomethane)
Methyl isobutyl ketone (Hexone)
598630
602
603
61790145
620
7428480
7439921
7446142
7758976
7784409
78002
88
58899
108316
10377669
1313139
1317357
1336932
198
7439965
8030704
7785877
11
10377669
1313139
1317357
1336932
198
7439965
8030704
7785877
11
7487947
199
22967926
62384
7439976
12
79414
67561
108112
72435
96333
74839
74873
71556
78933
60344
74884
108101
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
N
N
N
N
N
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80193
80194
43603
80396
80396
80396
80396
80396
80396
80396
80396
80396
80196
80196
80196
80196
80196
80196
80196
80196
80196
80197
80405
80405
80405
80405
80405
43301
80199
80200
43801
43814
43552
P0205
80206
43560
0.5738
0.7400
0.7400
0.2762
0.6869
0.1981
0.7400
0.5056
0.4744
0.4417
0.4741
0.7400
1.0000
1.0000
0.1013
0.2085
0.2377
0.0450
0.3300
0.3300
0.3300
0.1201
0.3300
0.2057
0.4234
0.4826
0.0913
0.6700
0.6700
0.6700
0.2437
0.6700
0.7388
1.0000
1.0000
0.5957
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
122
122
122
122
122
122
122
122
122
122
122
122
4
125
126
126
126
126
126
126
126
126
126
126
126
126
126
126
126
126
126
126
127
127
127
127
127
127
128
129
130
131
132
133
140
134
135
A-23
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
Methyl isocyanate
Methyl methacrylate
Methyl tert-butyl ether
Methylene chloride
4,4'-Methylenebis(2-chloraniline)
4,4'-Methylenedianiline
4,4'-Methylenediphenyl diisocyanate
N,N-Dimethylaniline
N-Nitroso-N-methylurea
N-Nitrosodimethylamine
N-Nitrosomorpholine
Naphthalene
Naphthalene
NICKEL SULFATE.6H2O
Nickel subsulfide
NICKEL HYDROXIDE
NICKEL CARBIDE
NICKEL NITRATE
Nickel oxide
NICKEL(lll) OXIDE
NICKEL BROMIDE NIBR2
>Nickel carbonyl
NICKEL SULFAMATE
Nickel & Compounds
Nickel acetate
NICKEL DIACETATE TET
Nickel
NICKEL CHLORIDE
NICKEL SULFATE
Nickel & Compounds
NICKEL SULFATE.6H2O
Nickel subsulfide
NICKEL HYDROXIDE
NICKEL CARBIDE
NICKEL NITRATE
Nickel oxide
NICKEL(111) OXIDE
NICKEL BROMIDE NIBR2
NICKEL SULFAMATE
Nickel & Compounds
Nickel acetate
NICKEL DIACETATE TET
Nickel
NICKEL CHLORIDE
NICKEL SULFATE
Nickel carbonyl
Nickel & Compounds
Nitrobenzene
4-Nitrobiphenyl
4-Nitrophenol
Methyl isocyanate 624839 5 N
Methyl methacrylate 80626 7 N
Methyl tert butyl ether 1634044 1 Y
Methylene chloride (Dichloromethane) 75092 9 Y
Methylenebis(2-chloroaniline), 4,4'- , gas 101144 7 N
Methylenedianiline, 4,4'- , gas 101779 5 N
Methylenediphenyl diisocyanate, 4,4'- (MDI), gas 101688 5 N
N,N-Diethyl aniline (N,N-Dimethylaniline) 121697 8 N
N-Nitroso-N-methylurea 684935 N
N-Nitrosodimethylamine 627S9 0 N
N-Nitr03omorpholine 59892 0 N
Naphthalene, fine PM 91203 2 N
Naphthalene, gas 91203 5 N
Nickel Compounds, coarse PM 10101970 3 Y
Nickel Compounds, coarse PM 12035722 3 Y
Nickel Compounds, coarse PM 12054487 3 Y
Nickel Compounds, coarse PM 12710360 3 Y
Nickel Compounds, coarse PM 13138459 3 Y
Nickel Compounds, coarse PM 1313991 3 Y
Nickel Compounds, coarse PM 1314063 3 Y
Nickel Compounds, coarse PM 13462889 3 Y
Nickel Compounds, coarse PM 13463393 3 Y
Nickel Compounds, coarse PM 13770893 3 Y
Nickel Compounds, coarse PM 226 3 Y
Nickel Compounds, coarse PM 373024 3 Y
Nickel Compounds, coarse PM 6018899 3 Y
Nickel Compounds, coarse PM 7440020 3 Y
Nickel Compounds, coarse PM 7718549 3 Y
Nickel Compounds, coarse PM 7786814 3 Y
Nickel Compounds, coarse PM 14 3 Y
Nickel Compounds, fine PM 10101970 2 Y
Nickel Compounds, fine PM 12035722 2 Y
Nickel Compounds,, fine PM 12054487 2 Y
Nickel Compounds, fine PM 12710360 2 Y
Nickel Compounds, fine PM 13138459 2 Y
Nickel Compounds, fine PM 1313991 2 Y
Nickel Compounds, fine PM 1314063 2 Y
Nickel Compounds, fine PM 13462889 2 Y
Nickel Compounds, fine PM 13770893 2 Y
Nickel Compounds, fine PM ' 226 2 Y
Nickel Compounds, fine PM 373024 2 Y
Nickel Compounds, fine PM • 6018899 2 Y
Nickel Compounds, fine PM 7440020 2 Y'
Nickel Compounds, fine PM 7718549 2 Y
Nickel Compounds, fine PM 7786814 2 Y
Nickel Compounds, fine PM 13463393 2 Y
Nickel Compounds, fine PM 14 2 Y
Nitrobenzene 98953 4 N
Nitrobiphenyl, 4- 92933 N
Nitrophenol, 4- 100027 4 N
80208
43441
43376
43802
80211
46111
45730
80155
80221
80222
46702
46701
80316
80316
80316
80316
80316
80316
80316
80316
80316
80316
80316
80316
80316
8'0316
80316
80316
80316
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
80216
45702
80218
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.5000
.5000
.0916
.1002
.2597
.1280
.1317
.3223
.2911
.1102
.1410
.0959
.4100
.1362
.0967
.4100
.1857
.1556
.4100
.1318
.1442
.3736
.1841
.1896
.4637
.4189
.1585
.1381
.5900
.1959
.1392
.5900
.2673
.2238
.2029
.5900
.0000
.0000
.0000
135
137
138
139
29
30
31
141
143
144
145
165
165
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
147
148
35
36
A-24
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
2-Nitropropane
Anthracene
D ibenzo[a,i J pyrene
D [a, h) pyrene
D [a, e] pyrene
Benzo[e]pyrene
Perylene
B[j]fluoranthen
Acenaphthylene
D[a,j]acridine
1-Phenanthrene
5-Methylchrysene
3-Methylcholanthrene
7,12-Dimethylbenz[a]anthracene
Acenaphthalene
Acenaphthene
1-methylnaphthalene
2-Methylnaphthalene
Benzo[b+k]fluoranthene
Benzo [g,h, i, Jperylene
Indeno[1,2,3 -c,d]pyrene
Benzo[b]fluoranthene
Benzo[k]fluoranthene
Chrysene
PAH, total
Polycyclic Organic Matter
Benzo[a]pyrene
Dibenzo[a,h]anthracene
Benz[a]anthracene
16-PAH
Fluoranthene
Fluorene
Phenanthrene
Pyrene
Benzofluoranthenes
2-Chloronaphthalene
Paraffin
Parathion
Pentachloronitrobenzene
Pentachlorophenol
Phenol
p-Pheny1enediamine
Phosgene
Phosphine
Phosphorus
Phosphorus Oxychloride
Triphenyl phosphite
PHOSPHOROUS ACID
Triphenyl phosphate
Phosphorous nitride
Nitropropane, 2-
POM, total (including total PAH)
POM, total (including total PAH)
(including total PAH)
(including total PAH)
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
POM, total
Paraffin -
Parathion,
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total
PAH)
(including total PAH)
(including total PAH)
(including total PAH)
(including total PAH)
nonHAP
gas
Pentachloronitrobenzene (Quintobenzene),
Pentachlorophenol, gas
Phenol
Phenylenediamine, p-
Phosgene
Phosphine
Phosphorus
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
gas
79469
120127
189559
189640
192654
192972
198550
205823
208968
224420
283
3697243
56495
57976
78
83329
90120
91576
102
191242
193395
205992
207089
218019
234
246
50328
53703
56553
40
206440
86737
85018
129000
56832736
91587
8002742
56382
82688
87865
108952
106503
75445
7803512
7723140
10025873
101020
10294561
115866
12136913
4
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
.2
2
2
2
7
1
1
5
7
9
2
2
2
2
2
2
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
80219
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80230
80223
80224
80225
45300
80227
80228
80229
80229
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
I'.OOOO
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
1.0000
25
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
165
156
157
158
72
154
160
161
162
A-25
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
PHOSPHOROUS SALT
PHOSPHORUS TRIOXIDE
Phosphorus Pentoxide
Phosphorus Pentasulfide
PHOSPHOROTHIOIC ACID
Phosphoric Acid
Phosphorus Trichloride
Zinc Phosphate
Triorthocresyl phosphate
PHOSPHORIC ACID.RX P
Phosphorus Compounds
Phthalic anhydride
Polychlorinated biphenyls
1,3-Propanesultone
beta-Propiolactone
Propionaldehyde
Propoxur
Propylene Dichloride
Propylene oxide
1,2-Propylenimine
Quinoline
'Quinone
Iodine-131
Radionuclides (including radon)
Radionuclides
Radon and its decay products
SELENIUM OXIDE
Selenium & Compounds
SELENIUM OXIDE SEO2
Selenium sulfide
Selenium Disulfide
Selenium
Selenium & Compounds
SELENIUM OXIDE
Selenium & Compounds
SELENIUM OXIDE SE02
Selenium sulfide
Selenium Disulfide
Selenium
Selenium & Compounds
Styrene
Styrene oxide
Tert-dodecyl mercaptan
1,1,2,2-Tetrachloroethane
Tetrachloroethylene
Tetrahydrofuran
Titanium tetrachloride
Toluene
Toluene-2,4-diamine
2,4-Toluene diisocyanate
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phosphorus Compounds, non HAP
Phthalic anhydride
Polychlorinated biphenyls (Aroclors), fine PM
Propanesultone,1,3-
Propiolactone, beta-
Propionaldehyde
Propoxur (Baygon), gas
Propylene dichloride (1, 2-Dichloropropane)
Propylene oxide
Propylenimine (2-Methylaziridine), 1,2-
Quinoline
Quinone
Radionuclides (including radon), gas
Radionuclides (including radon), gas
Radionuclides (including radon), gas
Radionuclides (including radon), gas
Selenium Compounds,
Selenium Compounds,
Selenium Compounds,
Selenium Compounds,
(including radon),
(including radon),
(including radon),
(including radon),
coarse PM
coarse PM
coarse PM
coarse PM
Selenium Compounds, coarse PM
Selenium Compounds, coarse PM
Selenium Compounds, coarse PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Selenium Compounds, fine PM
Styrene
Styrene oxide
Tert-dodecyl mercaptan - nonHAP
Tetrachloroethane, 1,1,2,2-
Tetrachloroethylene (Perchloroethylene)
Tetrahydrofuran, non HAP
Titanium tetrachloride
Toluene
Toluene diamine-2,4
Toluene diisocyanate, 2,4-
13011546
1314245
1314563
1314803
2921882
7664382
7719122
7779900
78308
92203026
398
85449
1336363
1120714
57578
123386
114261
78875
75569
75558
91225
106514
24267569
400
605
606
12640890
253
7446084
7446346
7488564
7782492
17
12640890
253
7446084
7446346
7488564
7782492
17
100425
96093
25103586
79345
127184
109999
7550450
108883
95807
584849
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
Y
N
Y
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
Y
Y
N
N
Y
N
N
1.0000
1.0000
1.0000
1.0000
.0000
.0000
.0000
,0000
.0000
.0000
1.0000
45601
80231
43504
80235
43838
43602
80238
80239
80240
80241
80241
80241
80241
80343
80343
80343
80343
80343
80343
80343
80242
80242
80242
80242
80242
80242
80242
45220
80244
80246
43817
80248
45202
80250
45731
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
. 0000
.0712
.1000
.0712
.0711
.0552
.1000
.1000
.6404
.9000
.6404
.6403
.4966
.9000
.9000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
.0000
163
1S4
12
55
166
167
168
169
9
170
171
172
172
172
172
173
173
173
173
173
173
173
173
173
173
173
173
173
173
174
175
1
176
177
108
179
22
A-26
-------
Table 1. Point and Area HAP Table File: Used to Process the 1996 NTI Point and Area Source Emissions Data (continued)
o-Toluidine
Toxaphene
1,2,4-Trichlorobenzene
1,1,2-Trichloroethane
Trichloroethylene
2,4,5-Trichlorophenol
2,4,6-Trichlorophenol
Triethylamine
Trifluralin
2,2,4-Trimethylpentane
Tris(2-chloroethyl)phosphate
Vinyl acetate
Vinyl bromide
Vinyl chloride
Vinylidene chloride
Vinylidene chloride
p-Xylene
m-Xylene
Xylenes (mixture of o,
o-Xylene
m, and p isomers)
Toluidine, o-
Toxaphene (chlorinated camphene), fine PM
Trichlorobenzene, 1,2,4-
Trichloroethane, 1,1,2-
Trichloroethylene
Trichlorophenol, 2,4,5-
Trichlorophenol, 2,4,6-
Triethylamine
Trifluralin, gas
Trimethylpentane, 2,2,4-
Tris(2-chloroethyl)phosphate - nonHAP
Unknovm-Silver - non HAP
Unknown-invalid CAS #
Vinyl acetate
Vinyl bromide
Vinyl chloride
Vinylidene chloride (1,1-Dichloroethylene)
Vinylidene chloride (1,1-Dichloroethylene), Inert
Xylenes (mixed isomers)
Xylenes (mixed isomers)
Xylenes (mixed isomers)
Xylenes (mixed isomers)
95534
8001352
120821
79005
79016
95954
88062
121448
1582098
540841
115968
7440224
78133
108054
593602
75014
75354
75354
106423
108383
1330207
95476
7
2
1
9
9
1
1
1
7
1
5
9
1
4
1
5
5
5
5
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
Y
N
N
Y
Y
Y
Y
80252
45830
43820
43824
80256
80257
43250
43453
80260
43860
80262
80307
45102
45102
45102
45102
1.0000
1.0000
1.0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
0000
1.0000
151
180
5
2
181
17
18
182
183
15
184
185
186
187
187
188
188
188
188
A-27
-------
Table 2. Precursor HAP Table File: Used to Process Point, Area and Mobile Precursor Inventory (HAP and nonHAP VOCs combined)
POLLDESC
Propene
Butene, 2-
Pentene, 2-
Hexene, 2-
Heptene, 2-
Octene, 2-
Nonene, 2-
Butene,2-, 2 -methyl
Pentene,
Pentene,
Ethanol
Propene
Butene,
Pentene,
Hexene,
Heptene,
Octene,
Nonene,
2-,
2-,
3-methyl
4 -methyl
2-
2-
2-
2-
2-
2-
Butene,2-, 2-methyl
Pentene, 2-, 3-methyl
»Pentene, 2-, 4-methyl
Ethanol
Butadiene, 1,3-
Toluene
Toluene
•Ethene
Propene
Butene, 1-
Pentene, 1-
Hexene, 1-
Heptene, 1-
Octene, 1-
Nonene, 1-
Decene, 1-
Propene, 2-methyl (Isobutene)
Butene, 1-, 2-methyl
Butadiene, 1,3-
Butene, 1-, 3-methyl
Pentene, 1-, 3-methyl
Butene, 1-, 2,3-dimethyl
Isoprene
Butene, 1-,
Pentene, 1-,
Pentene, 1-,
Pentene, 1-,
Acetaldehyde
MTBE
Methanol
2-ethyl
2-methyl
4-methyl
2,4,4-trimethyl
HAPDESC
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-inert surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acetaldehyde precursors-reactive surrogate
Acrolein precusor - inert surrogate
Cresol Precursors - inert surrogate
Cresol Precursors - reactive surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
Formaldehyde precursors-inert surrogate
POLLCODE
P33
P10
P19
P13
P12
P18
P17
P16
P23
P26
P28
P33
P10
P19
P13
P12
P18
P17
P16
P23
P26
P28
106990
108883
108883
P29
P33
P01
P07
P04
P03
P06
P05
P02
P30
P14
106990
P21
P22
P08
P32
Pll
PIS
P25
P09
75070
1634044
67561
React Keep Saroad Factor
1
1
1
1
1
1
1
1
1
1
1
7
7
7
7
7
7
7
7
7
7
7
1
1
4
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
80301
80301
80301
80301
80301
80301
80301
80301
80301
80301
80301
80100
80100
80100
80100
80100
80100
80100
80100
80100
80100
80100
80302
80306
80506
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
80303
0.5250
1.5800
0.6300
0.5200
0.4500
0.3900
0.6300
0.9450
0.7800
0.5200
0.0480
0.5250
1.5800
0.6300
0.5200
0.4500
0.3900
0.6300
0.9450
0.7800
0.5200
0.0480
1.0000
0.2880
0.2880
0.5136
0.7100
0.5400
0.4300
0.3600
0.3100
0.2700
0.2400
0.2100
0.8640
0.6880
1.1200
0.4300
0.3600
0.5760
0.8844
0.5760
0.5760
0.3600
0.4320
0.3400
0.0143
0.0282
NTI
A-28
-------
Table 2. HAP Table File Used to Process 1996 NET Point and Area Source Speciated VOC Emissions Data (continued)
Ethene
Propene
Butene,
Pentene,
Hexene,
Heptene,
Octene,
Nonene,
Decene,
Propene,
Butene,
1-
1-
1-
1-
1-
1-
1-
2-methyl (Isobutene)
1-, 2-methyl
Butadiene, 1,3-
Butene, 1-, 3-methyl
Pentene, 1-, 3-methyl
Butene, .1-, 2,3-dimethyl
Isoprene
Butene, 1-,
Pentene, 1-,
Pentene, 1-,
Pentene, 1-,
Acetaldehyde
MTBE
Methanol
Butene, 1-, 2-methyl
Butane
Isopentane
Pentane, 3-methyl
Butene, 1-, 2-methyl
Butane
Isopentane
Pentane, 3-methyl
Methylene Chloride
Tetrachloroethylene
Trichloroethylene
Vinylidene Chloride
Vinylidene Chloride
Methylene Chloride
Tetrachloroethylene
Trichloroethylene
Butene, 1-
Pentene, 2-
Hexene, 3-
Butene, 1-
Pentene, 2-
Hexene, 3-'
2-ethyl
2-methyl
4-methyl
2,4,4-trimethyl
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
Formaldehyde precursors-reactive surrogate
MEK precursors-inert surrogate
MEK precursors-inert surrogate
MEK precursors-inert surrogate
MEK precursors-inert surrogate
MEK precursors-reactive surrogate
MEK precursors-reactive surrogate
MEK precursors-reactive surrogate
MEK precursors-reactive surrogate
Phosgene precursors - inert surrogate
inert surrogate
inert surrogate
inert surrogate
reactive 4 surrogate
reactive 9 surrogate
reactive 9 surrogate
. , reactive 9 surrogate
Propionaldehyde precursors-inert surrogate
Propionaldehyde precursors-inert surrogate
Propionaldehyde precursors-inert surrogate
Propionaldehyde precursors-reactive surrogate
Propionaldehyde precursors-reactive surrogate
Propionaldehyde precursors-reactive surrogate
Phosgene precursors
Phosgene precursors
Phosgene precursors
Phosgene precursors
Phosgene precursors
Phosgene precursors
Phosgene precursors
P29
P33
P01
P07
P04
P03
P06
P05
P02
P30
P14
106990
P21
P22
P08
P32
Pll
P15
P25
P09
75070
1634044
67561
P14
P27
P31
P24
P14
P27
P31
P24
75092
127184
79016
75354
75354
75092
127184
79016
P01
PI 9
P20
P01
P19
P20
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
1
1
1
1
7
7
7
7
1
1
1
1
4
9
9
9
1
1
1
7
7
7
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y
Y
80180
80180
80180
80180
8U180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80180
80304
80304
80304
80304
80204
80204
80204
80204
80350
80350
80350
80350
80550
80450
80450
80450
80305
80305
80305
80234
80234
80234
0.5136
0.7100
0.5400
0.4300
0.3600
0.3100
0.2700
0.2400
0.2100
0.8640
0.6880
1.1200
0.4300
0.3600
0.5760
0.8844
0.5760
0.5760
0.3600
0.4320
0.3400
0.0143
0.0282
0.8600
0.0309
0.0249
0.0213
0.8600
0.0309
0.0249
0.0213
1.1600
0.2816
0.2988
0.7446
0.7446
1.1600
0.2816
0.2988
0.5200
0.8300
1.3800
0.5200
0.8300
1.3800
A-29
-------
Table 3. Onroad Mobile HAP Table File: Used to Process 1996 NTI Onroad Mobile Source Emissions Data
POLLDESC
16-PAH
7-PAH
Acetaldehyde
Acrolein
Arsenic & Compounds
Arsenic & Compounds
Benzene
1,3-Butadiene
Chromium & Compounds
Chromium & Compounds
Diesel PM, coarse
Diesel PM, fine
Diesel PM
Diesel PM
Dioxins/Furans as TEQ
Dioxins/Furans as TEQ
Ethyl Benzene
Forma1denyde
Hexane
'Lead & Compounds
Lead & Compounds
Manganese & Compounds
Manganese & Compounds
Mercury & Compounds
Methyl tert-butyl ether
Nickel & Compounds
Nickel & Compounds
16-PAH
Propionaldehyde
Styrene
Toluene
Xylenes (mixture of o, m.
(inorganic including
(inorganic including
and p isomers)
HAPDESC
16-PAH, fine PM
7-PAH, fine PM
Acetaldehyde
Acrolein
arsinArsenic Cmpds. (inorganic, incl. arsine), coarse PM
arsinArsenic Compounds (inorganic, incl. arsine), fine PM
Benzene (including benzene from gasoline)
Butadiene, 1,3-
Chromium Compounds, coarse PM
Chromium Compounds, fine PM
Diesel, coarse PM
Diesel, fine PM
Diesel, coarse PM
Diesel, fine PM
Dioxins/Furans as 2,3
Dioxins/Furans as 2,3
Ethylbenzene
Formaldehyde
Hexane
Lead Compounds, coarse PM
Lead Compounds, fine PM
Manganese Compounds, coarse PM
Manganese Compounds, fine PM
Mercury Compounts, fine PM
Methyl tert butyl ether
Nickel Compounds, coarse PM
Nickel Compounds, fine PM
POM, total (including total PAH)
Propionaldehyde
Styrene
Toluene
Xylenes (mixed isomers)
7,8TCCD TEQ, Lower Bound, Fine
7.8TCCD TEQ, Upper Bound, Fine
POLLCODE
40
75
75070
107028
93
93
71432
106990
136
136
dpmcoarse
dpmfine
80400
80400
701
701
100414
50000
110543
195
195
198
198
199
1634044
226
226
40
123386
100425
108883
1330207
React Keep
2
2
5
5
3
2
1
7
3
2
3
2
3
2
2
2
4
5
9
3
2
3
2
2
1
3
2
2
5
7
4
5
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
SaroadFactor
80232
80233
43503
43505
80312
80112
45201
43218
80341
80141
80401
80400
80401
80400
80412
80245
45203
43502
43231
80393
80193
80396
80196
80197
43376
80316
80216
80230
43504
45220
45202
45102
1
1
1
1
0
0
1
1
0
0
1
1
0
0
1
1
1
1
1
0
0
0
0
1
1
0
0
1
1
1
1
1
.0000
.0000
.0000
.0000
.1000
.9000
.0000
.0000
.1400
.8600
.0000
.0000
.0800
.9200
.0000
.0000
.0000
.0000
.0000
.2400
.7600
.3600
.6400
.0000
.0000
.1700
.8300
.0000
.0000
.0000
.0000
.0000
NTI
165
165
37
41
48
48
50
10
77
77
903
903
98
107
116
122
122
126
126
127
138
147
147
165
166
174
108
188
A-30
-------
Table 4. Nonroad Mobile HAP Table File: Used to Process 1996 NTI Nonroad Mobile Source Emissions Data
POLLDESC
16-PAH
7-PAH
Acetaldehyde
Acrolein
Arsenic & Compounds (inorganic including
Arsenic & Compounds (inorganic including
Benzene
Beryllium & Compounds
Beryllium & Compounds
1,3-Butadiene
Cadmium & Compounds
Cadmium & Compounds
Chromium & Compounds
Chromium & Compounds
Diesel PM, coarse
Diesel PM, fine
Diesel PM
Diesel PM
Ethyl Benzene
Formaldehyde
Hexane
Lead & Compounds
Lead & Compounds
Manganese & Compounds
Manganese & Compounds
Mercury & Compounds
Methyl tert-butyl ether
Nickel & Compounds
Nickel & Compounds
16-PAH
Propionaldehyde
Selenium & Compounds
Selenium & Compounds
Styrene
Toluene
Xylenes (mixture of o, m, and p isomers)
HAPDESC
16-PAH, fine PM
7-PAH, fine PM
Acetaldehyde
Acrolein
arsinArsenic Cmpds. (inorganic, incl. arsine), coarse PM
arsinArsenic Compounds (inorganic, incl. arsine), fine PM
Benzene (including benzene from gasoline)
Beryllium Compounds, coarse PM
Beryllium Compounds, fine PM
Butadiene, 1,3-
Cadmium Compounds, coarse PM
Cadmium Compounds, fine PM
Chromium Compounds, coarse PM
Chromium Compounds, fine PM
Diesel, coarse PM
Diesel, fine PM
Diesel, coarse PM
Diesel, fine PM
Ethylbenzene
Formaldehyde
Hexane
Lead Compounds, coarse PM
Lead Compounds, fine PM
Manganese Compounds, coarse PM
Manganese Compounds, fine PM
Mercury Compounts, fine PM
Methyl tert butyl ether
Nickel Compounds, coarse PM
Nickel Compounds, fine PM
POM, total (including total PAH)
Propionaldehyde
Selenium Compounds, coarse PM
Selenium Compounds, fine PM
Styrene
Toluene
Xylenes (mixed isomers)
POLLCODE
40
75
75070
107028
93
93
71432
109
109
106990
125
125
136
136
dpmcoarse
dpmf ine
80400
80400
100414
50000
110543
195
195
198
198
199
1634044
226
226
40
123386
253
253
100425
108883
1330207
React Keep
2
2
5
5
3
2
1
3
2
7
3
2
3
2
3
2
3
. 2
4
5
9
3
2
3
2
2
1
3
2
2
5
3
2
7
4
5
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
N
Y
Y
Y
SaroadFactor
80232
80233
43503
43505
80312
80112
45201
80318
80118
43218
80324
80124
80341
80141
80401
80400
80401
80400
45203
43502
43231
80393
80193
80396
80196
80197
43376
80316
80216
80230
43504
80343
80242
45220
45202
45102
1.
1.
1.
1.
0.
0.
1.
0.
0.
1,
0,
0,
0.
0.
1.
1,
0.
0.
1 (
1.
1.
0,
0.
0.
0,
1.
1.
0.
0.
1.
1,
0,
0.
1.
1,
1.
.0000
.0000
,0000
.0000
.1700
8300
.0000
,6100
.3900
.0000
,6200
.3800
.2000
.8000
.0000
,0000
.0800
,9200
,0000
.0000
.0000
.1200
.8800
.2100
.7900
.0000
.0000
.5100
.4900
.0000
.0000
.1100
.8900
.0000
.0000
.0000
NTI
165
165
37
41
48
48
50
54
54
10
60
60
77
77
98
107
116
122
122
126
126
127
138
147
147
165
166
173
173
174
108
188
A-31
-------
File Name: ctyflag
File Type: SAS*
Variables and Structure
Name
FIPS
Uflag
Type*
A5
N
Description
State and county FIPS codes.
Urban or rural flag, 1 indicates the entire county is urban, 2
county is rural, 9 - the county is mixed urban and rural
- the entire
* Ax=character string of length x, N=numeric
Sample of File Contents
01001 2
01003 2
01005 2
01007 2
01009 2
01011 2
01013 2
01015 9
01017 2
01019 2
01021 2
01023 2
01025 2
01027 2
01029 2
01031 2
01033 9
01035 2
01037 2
01039 2
01041 2
01043 2
01045 2
01047 9
01049 2
01051 2
01053 2
01055 9
01057 2
01059 2
01061 2
01063 2
01065 2
01067 2
Figure 14. County-level Urban/Rural Flag File (ctyflag)
A-32
-------
File Name: taff_hourly.txt
File Type: ASCII Text
Variables and Structure
Name
SCC_AMS
Hour 1 thru
Hour_24
Desc_l
Desc_2
Desc_3
Desc_4
Type*
C
N
C
C
C
C
Column
1
13,21,29,
etc.
205
259
313
383
Length
10
8 each
54
54
70
70
Dec-
imals
5
Description
SCC code or AMS code, SCC codes are preceded by
2 blank spaces at the beginning of the line. AMS
codes begin in space 1.
Hourly emission allocation factors. The factors sum
to 1.0
Level 1 description of the SCC or AMS
(corresponding to the 1 -digit SCC)
Level 2 description (corresponding to the 3 -digit
SCC)
Level 3 description (corresponding to the 6-digit
SCC)
Level 4 description (corresponding to the 8-digit
SCC)
*C=character, N=numeric
Sample record from the SCC-based section of the file
10100101 0.03262 0.03126 0.03053 0.03042 0.03103 0.03269 0.03624 0.04057
0.04375 0.04559 0.04626 0.04650 0.04611 0.04563 0.04479 0.04462 0.04542 0.04622
0.04611 0.04628 0.04560 0.04280 0.03862 0.03420 External Combustion Boilers
Electric Generation
Anthracite Coal
Pulverized Coal
Sample records from the AMS-based section of the file
2201001000 0.01702 0.01258 0.01028 0.00922 0.01019 0.01632 0.03711 0.05684
0.05215 0.04945 0.04945 0.05665 0.05896 0.05877 0.06112 0.06741 0.07361 0.07018
0.05767 0.04766 0.03827 0.03438 0.02886 0.02301
Mobile Sources
Highway Vehicles - Gasoline
Light Duty Gasoline Vehicles (LDGV)
Total: All Road Types
2201060000 0.01702 0.01258 0.01028 0.00922 0.01019 0.01632 0.03711 0.05684
0.05215 0.04945 0.04945 0.05665 0.05896 0.05877 0.06112 0.06741 0.07361 0.07018
0.05767 0.04766 0.03827 0.03438 0.02886 0.02301
Mobile Sources
Highway Vehicles - Gasoline
Light Duty Gasoline Trucks 1 & 2 (LDGT) ___^_
Figure 15. Temporal Allocation Factor File (taff_hourly.txt)
A-33
-------
File Name: scc2ants.txt
File Type: ASCII
Text
Variables and Structure
Name
sec
SCC_AMS
Spatial
Cat_name
Type*
C
C
C
C
Column
1
11
2
70
Length
8
10
24
28
Description
SCC code
SCC code or AMS code, SCC codes are preceded by 2
blank spaces at the beginning of the line. AMS codes begin
in space 11.
Spatial surrogate code; required for area and mobile source
processing
SCC category name, required for area and mobile source
processing
*C=character, N=numeric
Sample of File Contents
SCC_code(8) ,xx,SCC_AMS
101015 10101502
301 2301010000
302 2302000000
302002 2302000000
302004 30200420
302007 30200771
302009 30200903
302010 30201004
302015 30201501
302016 30201601
302019 30201999
302030 30203001
302040 30204001
303 2303000000
303001 30300101
303005 30400204
303023 30302301
304 30301542
304003 30400330
304004 30400401
304007 30301501
30402200 30402201
305008 30500812
305014 30501404
305016 30501601
305050 30505001
307 2307000000
307007 30700715
307008 30700899
307030 30703099
(10) , xx, Spatial (2) ,xx,Cat_name (70)
19 Geothermal Power
3 Industrial Inorganic Chemical Manufacturing
3 Miscellaneous Foods and Kindred Products
2 Roasted Coffee
7 Food and Agricultural Products: Cotton Ginning
3 Rice Milling
3 Malt Beverages
3 Distilled and Blended Liquors Production
7 Raw
Cane Sugar
3 Beet Sugar
3 Edible Fats
and Oils, nee
3 Dairy Products
3 Cereal Breakfast Foods
3 Misc. Primary Metal Products Manufacturing
3 Primary Aluminum Production
3 Copper Foundries
3 Taconite Iron Ore Processing
3 Iron and Steel Forging
3 Gray and Ductile Iron Foundries
3 .Secondary Lead Smelting
3 Iron and Steel Foundries: Steel Foundries
3 Metal Heat Treating Manufacturing
3 Ceramic Wall and Floor Tile Manufacturing
3 Pressed & Blown Glass & Glassware Manufacturing
3 Lime Manufacturing
3 Asphalt Concrete Manufacturing
3 Plywood/Particle Board Manufacturing
3 Softwood Veneer and Plywood
3 Sawmills and Planing Mills, general
3 Wood Products, Nee - -
Figure 16. SCC to AMS Cross-Reference File (scc2ams.txt)
A-34
-------
File Name: sic2ams.txt
File Type: ASCII Text
Variables and Structure
Name
SIC
SCC_AMS
Spatial
Cat name
Type*
C
c
C
c
Column
1
7
20
24
Length
4
10
2
70
Description
SIC code
SCC code or AMS code, SCC codes are preceded by 2 blank
spaces at the beginning of the line. AMS codes begin in
space 7.
*C=character, N=numeric
Sample of File Contents
SIC_code(4),xx,SCC_
1311 2310000000
1446 2325000000
2011 2302000000
2013 2302000000
2015 2302000000
2016 2302000000
2020 30203001
2022 2302000000
2023 2302000000
2033 2302000000
2034 2302000000
2035 2302000000
2037 2302000000
2038 2302000000
2041 2302000000
2043 30204001
2044 30200771
2045 2302050000
2046 2302000000
2047 2302000000
2048 2805001000
2061 30201501
2062 30201501
2063 30201601
2066 2302000000
2077 2302000000
2079 30201999
2082 30200903
2083 30200708
2085 30201004
2086 2302000000
2087 2302000000
AMS(10),xxx,Spatial(2),xx,Cat_name(70)
19 Crude Petroleum and Natural Gas
3 Industrial Sand
3 Meat Packing Plants
3 Sausages And Other Prepared Meats
3 Poultry Slaughtering and Processing
3 Poultry Dressing Plants
3 Dairy Products
3 Cheese, Natural and Processed
3 Condensed and Evaporated milk
3 Canned Fruits and Vegetables
3 Dehydrated Fruits, Vegetables, and Soups
3 Pickles, Sauces, And Salad Dressings
3 Frozen fruits, Fruit Juices and Vegetables
3 Frozen Specialties, nee
3 Flour and Other Grain Mill Products
3 Cereal Breakfast Foods
3 Rice Milling
3 Prepared Flour Mixes And Doughs
3 Wet Corn Milling
3 Dog and Cat Food
3 Prepared Feeds Manufacturing
3 Raw Cane Sugar
3 Cane Sugar Refining
3 Beet Sugar
3 Chocolate And Cocoa Products
3 Animal And Marine Fats And Oils
3 Edible Fats and Oils, nee
3 Malt Beverages
3 Malt
3 Distilled and Blended Liquors Production
3 Bottled and Canned Soft Drinks
3 Flavoring Extracts and Syrups Production
Figure 17. SIC to SCC or AMS Cross-Reference File (sic2ams.txt)
A-35
-------
File Name: mact2ams.txt
File Type: ASCII Text
Variables and Structure
Name
MACTCAT
MACTdesc
sec
SCCdesc
SCC_AMS
Type*
C
C
C
C
C
Column
1
7
80
90
174
Length
4
70
8
80
10
Decimals
Description
MACT category code
MACT category description
SCC code
SCC description
SCC code or AMS code, SCC codes are preceded by 2 blank spaces at the
beginning of the line. AMS codes begin in space 174
*C=character, N=numeric
Sample of File Contents
Note: Column placements have been adjusted to accommodate page width.
0101
0101
0101
0101
0101
0101
0101
0101
0101
0101
0101
03,01
0101
0101
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Engine
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Test
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
Facilities
204001
204003
204004
204800
20400110
20400112
20400199
20400301
20400302
20400303
20400304
20400305
20400399
20400401
Aircraft Engine Testing
Turbine
Reciprocating Engine
Equipment Leaks
Jet A Fuel
JP-4 Fuel
Other Not Classified
Natural Gas
Diesel/Kerosene
Distillate Oil •
Landfill Gas
Kerosene/Naphtha
Other Not Classified
Gasoline
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
20400110
Figure 18. MACT Category to SCC or AMS Cross-Reference File (mact2scc.txt)
A-36
-------
File Name: GFXX_YY
File Type: SAS*
Variables and File Structure
Name
FIPSST
SIC
GF
Type*
C
C
N
Column
1
4
8
Length
2
3
12
Dec-
imals
10
Description
FIPS State code
SIC code, generally 2 digits left justified, but sometimes 3
digits
Growth factor
*C = character, N = numeric.
Sample of File Contents
01 1 1.0407186414
01 2 1.0407186414
01 7 1.1072844918
01 8 1.1072844918
01 9 1.1072844918
01 10 1.0163934426
01 11 1.0639196439
01 12 1.0639196439
01 13 0.9796269023
01 14 1.0416666667
01 15 1.0276939178
01 16 1.0276939178
01 17 1.0276939178
01 20 1.0349711707
01 21 0.9397590361
01 22 1.0611094805
01 23 1.0359140418
01 24 1.0156041474
01 25 1.0904799371
01 26 1.052496047
01 27 1.0256709452
01 28 1.0169783677
01 29 1.0499432463
01 30 1.0453389362
01 31 1.0666666667
01 32 1.0227272727
01 33 1.0345286506
01 34 1.0378504673
01 35 1.1381616302
01 36 1.1174489726
01 37 1.0761151758
01 38 1.0319715808
01 39 1.0442739079
01 40 1.06587473
Figure 19. Growth Factor File to Grow from Year XX to Year YY (GFXX_YY)
A-37
-------
File Name: ptscc2sic.txt
File Type: ASCII Text
Variables and File Structure
Name
SCC Name
SCC
SIC
SIC Name
Type*
C
C
C
C
Column
1
41
50
55
Length
40
8
4
35
Description
Source Category Code (SCC) name (for descriptive purposes; not
read by PtGrowCntl)
SCC
Standard Industrial Code (SIC)
SIC name (for descriptive purposes; not read by PtGrowCntl)
*C = character, N = numeric.
Sample of File Contents
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
External
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Comb
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
Boilers
-Utilities-Coal 10100201 4911
-Utilities-Coal 10100202 4911
-Utilities-Coal 10100203 4911
-Utilities-Coal 10100204 4911
-Utilities-Coal 10100212 4911
•Utilities-Coal 10100222 4911
-Utilities-Coal 10100223 4911
-Utilities-Coal 10100224 4911
-Utilities-Coal 10100226 4911
-Utilities-Coal 10100301 4911
-Utilities-Coal 10100302 4911
-Utilities-Coal 10100303 4911
•Utilities-Coal 10100306 4911
-Utilities-Oil 10100401 4911
-Utilities-Oil 10100404 4911
-Utilities-Oil 10100501 4911
-Utilities-Gas 10100601 4911
-Utilities-Gas 10100604 4911
•Industrial-Coal 10200104 2271
•Industrial-Coal 10200201 1094
-Industrial-Coal 10200202 1011
•Industrial-Coal 10200203 2046
-Industrial-Coal 10200204 1011
-Industrial-Coal 10200205 1429
•Industrial-Bit Coal0200210 2047
•Industrial-Coal 10200212 2046
-Industrial-Coal 10200217 2075
•Industrial-Coal 10200219 2111
-Industrial-Coal 10200221 2063
-Industrial-Coal 10200222 2062
-Industrial-Coal 10200224 2063
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Svcs-Electric
Woven Carpets and Rugs
Uranium/Radium Ores
Iron Ores
Wet Corn Milling
Iron Ores
Crushed/Broken Stone,NEC
Pet Food
Wet Corn Milling
Soybean Oil Mills
Cigarettes
Beet Sugar
Cane Sugar Refining
Beet Sugar
Figure 20. SCC to SIC Cross-Reference File (ptscc2sic.txt)
A-38
-------
File Name: MACT_gen.txt
File Type: ASCII Text
Variables and File Structure
Name
MACTcode
MACTexis
MACT_new
MACTrate
Bin
Flag
Complyr
MACT_app
MACT_src
MACT name
Type*
C
N
N
N
C
C
C
C
C
C
Column
1
6
13
20
27
30
32
37
39
41
Length
4
6
6
6
2
1
4
1
1
39
Dec-
imals
2
2
2
Description
MACT category code, right justified
Control efficiency to be applied to existing emission sources
Control efficiency to be applied to new, modified, or
reconstructed emission sources
Percentage of future emission attributed to new sources
MACT standard bin, this can have four possible values: 2, 4,
7, or 10.
Not currently used.
Can'take a value of A, B, C or D
A - categories where the compliance date precedes the base
year of analysis
B - categories for which specific efficiencies have been
compiled
C - categories for which no specific efficiencies are
available.
D - categories which are expected to be dropped from the
MACT list.
Expected deadline for affected emission sources to comply
with standards; used with the bin to determine if MACT
controls are applied
Application control flag: set to 1 if controls are to be
applied, set to 0 if control are not to be applied
Source control flag: set to M to apply controls only to major
point sources, set to B to apply controls to all point sources
MACT category name (for descriptive purposes, not read by
PtGrowCntl)
*C = character, N = numeric.
No sample file is currently provided as apart of EMS-HAP
Figure 21 a. General MACT Reduction Information File (MACT_gen.txt)
A-39
-------
File Name: MACT_spec.txt
File Type: ASCII Text
Variables and File Structure
Name
MACTcode
NTI_HAP
SAROAD
SCC8
SCC6
EffXspec
EffNspec
SnewRate .
SApp_Eff
SApp_Src
PollName
ProcName
MACTname
Type*
C
C
C
C
C
N
N
N
C
C
C
C
C
Column
1
6
10
17
26
34
41
48
55
57
52
82
141
Length
4
3
5
8
6
6
6
6
1
1
30
33
90
Dec-
imals
2
2
2
Description
MACT category code
HAP identification code
Not currently used: Pollutant code assigned by
PtAspenProc
8-digit SCC
6-digit SCC
Control efficiency to be applied to existing emission
sources
Control efficiency to be applied to new, modified, or
reconstructed emission sources
Percentage of future emissions attributed to new sources
Application control flag: set to 1 if controls are to be
applied, set to 0 not to apply controls
Source control flag: set to M to apply controls only to
major point sources, set to B to apply controls to all
sources
Pollutant name (for descriptive purposes, not read by
PtGrowCntl)
Process name (for descriptive purposes, not read by
PtGrowCntl)
MACT category name (for descriptive purposes, not read
by PtGrowCntl)
*C = character, N = numeric.
No sample file is currently provided as a part of EMS-HAP
Figure 21 b. Specific MACT Reduction Information File (MACT_spec.txt)
A-40
-------
File Name: SITE_spec.txt
File Type: ASCII Text
Variables and File Structure
Name
ACTJD
NTI_HAP
SAROAD
EffXspec
EffNspec
SNewRate
SApp_Eff
PollName
Type*
C
C
C
N
N
N
C
C
Column
1
27
31
37
44
51
58
62
Length
25
3
. 5
6
6
6
1
40
Dec-
imals
2
2
2
Description
Facility-level activity identification code
HAP identification code
Not currently used: Pollutant code assigned by PtAspenProc
Control efficiency to be applied to existing emission sources
Control efficiency to be applied to new, modified, or
reconstructed emission sources
Percentage of future emissions attributed to new sources
Application control flag: set to 1 if controls are to be
applied, set to 0 not to apply controls
Pollutant name (for descriptive purposes, not read by
PtGrowCntl)
*C = character, N = numeric.
No sample file is currently provided as apart of EMS-HAP
Figure 22. Specific Facility Reduction Information File ( SITE_spec.txt)
A-41
-------
File Name: MACT_grp.txt
File Type: ASCII Text
Variables and File Structure:
Name
MACTcode
MACT_grp
Type*
C
C
Column
1
6
Length
4
3
Description .
MACT category code
ASPEN source group
*C=character, N=numeric
Sample of File Contents
0101
0102
0103
0104
0105
0106
0201
0202
0203
0204
0205
0206
0207
0301
0302
0303
0304
0305
0306
0307
0308
0309
0310
0401
0402
0403
0404
0405
0406
0407
0408
0409
0410
0411
0412
0501
0502
6
6
6
6
6
6
4
5
4
4
2
7
6
6
1
6
4
6
7
7
6
6
4
6
6
6
6
6
6
6
6
5
4
6
4
4
5
Figure 23. ASPEN Source Group Assignment by MACT Category File (MACT_grp.txt)
A-42
-------
File Name: SCC6_grp.txt
File Type: ASCII Text
Variables and File Structure:
Name
sec
ADD_grp
SCCrank
Type*
C
C
C
Column
1
8
12
Length
6
3
' 2
Description
6-digit SCC code
ASPEN source group
Hierarchy rank of ASPEN source group assignment
*C=character, N=numeric
Sample of File Contents
301001
301003
301005
301006
301007
301008
301009
301010
301014
301015
301018
301019
301020
301021
301023
301024
301025
301026
301027
301030
301031
301032
301033
301034
301035
301040
301050
301060
301070
301091
301099
301100
301120
301121
301125
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Figure 24. ASPEN Source Group Assignment by SCC Code File (SCC6_grp.txt)
A-43
-------
File Name: SIC_grp.txt
File Type: ASCII Text
Variables and File Structure
Name
SIC
ADD_grp
SCCrank
Type*
C
C
C
Column
1
6
10
Length
4
3
2
Description
SIC code
ASPEN source group
Hierarchy rank of ASPEN source group assignment
*C=character, N=numeric
Sample of File Contents
2011
2013
2015
2020
2021
2022
2023
2024
2026
2032
2033
2034
2035
2037
2038
2041
2043
2044
2045
2046
2047
2048
2051
2052
2062
2063
2064
2066
2067
2074
2075
2076
2077
2079
2080
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Figure 25. ASPEN Source Group Assignment by SIC Code File (SIC_grp.txt)
A-44
-------
File Name: indecay.txt
File Type: ASCII Text
Variables and Structure
Name
Reactivity class
Time block
Decay
coefficients
Type*
C
C
N
Colum
n
1
3
5
Length/ format
1
1
6 nos. at 10E3
Description
Ranges from 1 to 9
Ranges from 1 to 8
Coefficients for stability classes A
through F.
*C=character, N=numeric
Sample File Content
i i
1 2
1 3
-1 4
1 5
1 6
1 7
1 8
4 1
4 2
4 3
4 4
4 5
4 6
4 7
4 8
5 1
5 2
5 3
5 4
5 5
5 6
5 7
5 8
6 1
6 2
6 3
6 4
6 5
6 6
6 7
6 8
7 1
7 2
7 3
7 4
7 5
7 6
7 7
7 8
8 1
8 2
8 3
8 4
8 5
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
9.870E-07
9.870E-07
1.180E-05
7.890E-05
6.710E-05
2.370E-05
1.970E-06
9.870E-07
2.470E-06
2.470E-06
.960E-05
.970E-04
.680E-04
.920E-05
.930E-06
2.470E-06
4.930E-06
.930E-06
.920E-05
.950E-04
.350E-04
.180E-04
9.870E-06
4.930E-06
.010E-04
.210E-05
.OOOE-05
.930E-04
.040E-04
1.790E-04
3.950E-05
5.010E-04
1.230E-05
1.230E-05
1.480E-04
9.870E-04
8.390E-04
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
9.870E-07
9.870E-07
7.890E-06
5.920E-05
5.130E-05
1.780E-05
1.970E-06
9.870E-07
2.470E-06
2.470E-06
1.970E-05
1.480E-04
1.280E-04
4.440E-05
4.930E-06
2.470E-06
4.930E-06
4.930E-06
3.950E-05
2.960E-04
2.570E-04
8.880E-05
9.870E-06
4.930E-06
5.010E-04
3.210E-05
6.040E-05
4.450E-04
3.860E-04
1.340E-04
3.950E-05
5.010E-04
1.230E-05
1.230E-05
9.870E-05
7.400E-04
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
9.870E-07
9.870E-07
3.950E-06
3.950E-05
3.550E-05
1.180E-05
1.970E-06
9.870E-07
.470E-06
.470E-06
9.870E-06
9.870E-05
8.880E-05
2.960E-05
4.930E-06
2.470E-06
4.930E-06
4.930E-06
1.970E-05
1.970E-04
1.780E-04
5.920E-05
9.870E-06
4.930E-06
.010E-04
.210E-05
.080E-05
.970E-04
.670E-04
9.OOOE-05
3.950E-05
5.010E-04
1.230E-05
1.230E-05
4.930E-05
.930E-04
6.410E-04 4.440E-04
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
0.OOOE+00 0
.870E-07 9
,870E-07 9
,970E-06 9
,970E-05 9
.970E-05 9
7.890E-06 9
9.870E-07 9
9.870E-07 9
2.470E-06 2
2.470E-06 2
4.930E-06 2
4.930E-05 2
4.930E-05 2
1.970E-05 2
2.470E-06 2
2.470E-06 2
4.930E-06 4
4.930E-06 4
9.870E-06 4
9.870E-05 4
9.870E-05 4
3.950E-05 4
4.930E-06 4
4.930E-06 4
5.010E-04
3.210E-05 5
1.600E-05 5
1.490E-04 8
1.490E-04 8
5.990E-05 8
,210E-05 5
,010E-04 5
.230E-05 1
.230E-05 1
.470E-05 1
2.470E-04 1
2.470E-04 1
5.
OOOE+00
OOOE+00
OOOE+00
OOOE+00
OOOE+00
OOOE+00
OOOE+00
OOOE+00
870E-07
870E-07
870E-07
870E-07
870E-07
870E-07
870E-07
870E-07
470E-06
470E-06
470E-06
470E-06
470E-06
470E-06
470E-06
470E-06
930E-06
930E-06
930E-06
930E-06
930E-06
930E-06
930E-06
930E-06
010E-04
010E-04
010E-04
140E-06
140E-06
140E-06
010E-0-J
010E-04
230E-05
230E-05
230E-05
230E-C5
230E-05
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
0.OOOE+00
9.870E-07
9.870E-07
9.870E-07
9.870E-07
9.870E-07
9.870E-07
9.870E-07
9.870E-07
2.470E-06
2.470E-06
2.470E-06
2.470E-06
2.470E-06
2.470E-06
2.470E-06
2.470E-06
4.930E-06
4.930E-06
4.930E-06
4.930E-06
4.930E-06
4.930E-06
4.930E-06
4.930E-06
5.010E-04
5.010E-04
5.010E-04
8.140E-06
8.140E-06
8.140E-06
5.010E-04
5.010E-04
1.230E-05
1.230E-05
1.230E-05
1.230E-05
1.230E-05
Figure 26. Decay Rate File (indecay.txt)
A-45
-------
File Name: surrxref.txt
File Type: ASCII Text
Variables and Structure
Name
AMS
Ssur
Desc
Type*
C
C
C
Column
1
12
34
Length
10
2
200
Description
AMS code
Numeric code representing the spatial surrogate that should be used
(from the available entries in Table 4-3,
Description of the AMS category
*C=character, N=numeric
Sample record from the SCC-based section of the file
Stationary Source Fuel Combust
2101000000 4
Electric Utility
2101001000 4
Electric Utility
210100200.0 4
Electric Utility
2101003000 4
Electric Utility
2101004000 4
Electric Utility
2101004001 4
Distillate Oil
2101005000 4
Electric Utility
2101006000 4
Electric Utility
2101006001 4
Natural Gas
2101006002 4
Natural Gas
Anthracite Coal
Bituminous/Subbituminous Coal
Lignite Coal
Distillate Oil
All Boiler Types
Residual Oil
Natural Gas
All Boiler Types
All I.C. Engine Types
Figure 27. Spatial Surrogate Assignment File (surrxref.txt)
A-46
-------
File Name: mact2ams.txt
File Type: ASCII Text
Variables and File Structure
Name Type* Column
MACT C 1
AMS C 7
Surr C 19
Descript C. 28
*C = character, N = numeric.
Sample of File Contents
0105 20100101 6
0106 2100000000 3
0406 2305000000 3
0501 2310000000 19
0601 2501060050 2
1609 2461000000 6
1636 2305000000 3
1802 2601000000 19
Length Decimals Description
4 MACT category code
10 AMS code or point source SIC code that gives the best fit
to temporal allocation data
2 Spatial surrogate for spatial allocation
50 Category description
Stationary 1C Engines
Stationary Turbines
Refractories Manufacturing
Oil & Nat. Gas Production
Gas Dispensing, Gasoline Distribution Stage I
Commercial Sterilization
Friction Products
Municipal Waste Combustors
Figure 28. MACT Category to AMS or SCC Code Cross-Reference File (fna~ct2ams.txt)
A-47
-------
File Names: SAFn (where n
File Type: SAS*
= 1-22)
Variables and Structure
Name
Cell
StCounty
UHag_l
LandLon
LandLat
Ntract
SAFn
(where n= 1, 2
*Ax=character
, etc.)
Type
*
All
A5
Al
N
N
N
N
string of length x,
Description
State (2-digit) and county (3-digit) FIPS codes, followed by the 6-digit
Census tract code, with leading zeros where appropriate
State and county FIPS code
Urban/rural flag. Urban = 1, Rural = 2. Assignments of urban and rural
codes were made using 1990 Census data.
Longitude of the tract centroid (not used)
Latitude of the tract centroid (not used)
Number of tracts in the county
Spatial allocation factor, defined as the fraction of county level activity that
is assigned to each tract. This variable totals to 1 for each county.
N=numeric
Sample record from the SCC-based section of the file
01001020100
01001020200
01001020300
01001020400
01001020500
01001020600
01001020700
01001020800
01001020900
01001021000
01001021100
01003010100
01003010200
01003010300
01003010400
01003010500
01003010600
01003010701
01003010702
01003010703
01003010800
01003010901
01003010902
01003011000
01003011100
oiooi
01001
01001
01001
01001
01001
01001
01001
01001
01001
01001
01003
01003
01003
01003
01003
01003
01003
01003
01003
01003
01003
01003
01003
01003
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2'
2
2
2
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
-87.
4864 32.4742 11 0.108108108108
4722 32.4714 11 0.175675675676
4586 32.4743 11 0.105405405405
4436 32.4677 11 0.213513513514
4272 32.4498 11 0.0351351351351
4764 32.4405 11 0.186486486486
4505 32.4485 11 0.0459459459459
4991 32.5216 11 0.0297297297297
5106 32.6392 11 0.0297297297297
7494 32.6103 11 0.0108108108108
7037 32.466 11 0.0594594594595
7774 31.0673 21 0.0083005679336
6795 30.9541 21 0.0096111839231
8298 30.8221 21 0.039755351682
6968 30.7591 21 0
7774 30.8902 21 0.0878112712975
7749 30.8617 21 0.0550458715596
8959 30.6742 21 0.000873743993
8941 30.6402 21 0.0777632153779
8382 30.6291 21 0.0419397116645
9003 30.5946 21 0.0174748798602
6802 30.589 21 0 .-0048055919616
7264 30.5495 21 0.047619047619
708 30.4906 21 0.0091743119266
8475 30.5028 21 0.0275229357798
Figure 29. Spatial Allocation Factor File (SAFn)
A-48
-------
File Name: am_grp.txt
File Type: ASCII Text
Variables and File Structure
Name Type* Co
SrceCatName C
SrceCatCode C
BinJJ C
Bin_R C
*C = character, N = numeric
Sample of File Contents
lumn Length Decimals Description
1 90 Category description
91 4 Source category identification code
96 1 Bin to be used for urban sources
98 1 Bin to be used for rural sources
Acrylic Fiber s/Modacrylic Fiber Production 9001 1 1
Adhesives and Sealants 9002 1 l
Aerospace Industries
9003 1 1
Agricultural Chemicals and Pesticides 9004 1 1
Agricultural Production 9005 1 1
Air and Gas Compressors 9006 1 1
Air and Water Resource and Solid Waste Management 9007 1 1
Alkalies And Chlorine 9008 1 1
Aluminum Die-Castings 9009 1 1
Aluminum Extruded Products 9010 1 1
Aluminum Foundries
9011 1 1
Aluminum Foundries (Castings) 9012 1 1
Aluminum Rolling and
Drawing, nee 9013 1 1
Aluminum Sheet, Plate, and Foil manufacturing 9014 1 1
Amino and Phenolic Resins Production 9015 1 1
Ammunition, Except for Small Arms 9016 1 1
Analytical Instruments 9017 1 1
Animal And Marine Fats And Oils 9018 1 1
Animal Cremation
9019 1 1
Apparel and Accessories, nee 9020 1 1
Architectural Metal
Work 9021 1 1
Asbestos Products Manufacturing 9022 1 1
Asphalt Concrete Manufacturing 9023 1 1
Asphalt Paving: Cutback Asphalt 9024 1 1
Asphalt Paving: Cutback and Emulsified 9025 1 1
Figure 30. Area and Mobile Source Group and Category Code Assignment File (am_grp.txt)
A-49
-------
File Name: popflg96.txt
File Type: ASCII Text
Variables and Structure
Name
STCTY
CNTYNAME
POPFLG96
STABBR
Type*
C
C
C
C
Column
4 '
13
56
65
Length
5
42
2
2
Description
State/county FIPS code
County name
Urban/Rural flag
2-character state abbreviation
*C=character
Sample of File Contents
STCTY CNTYNAME
02068 Denali Borough
02232 Skagway-Hoonah-Angoon Census Area
02282 Yakutat Borough
01007 Bibb
01011 Bullock
01013 Butler
01019 Cherokee
01021 Chilton
01023 Choctaw
01025 Clarke
01027 Clay
01029 Cleburne
01035 Conecuh
01037 Coosa
01039 Covington
01041 Crenshaw
01043 Cullman
01049 DeKalb
01053 Escambia
01057 Fayette
01059 Franklin
01061 Geneva
POPFLG96 STABBR
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
R
AK
AK
AK
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Figure 31. County-level Urban/Rural Designations File (popflg96.txt)
A-50
-------
File Name: area_cntl.txt
File Type: ASCII Text
Variables and File Structure
Name
SrceCatName
ExistEff
New_Eff
NewRate
App_Eff
Type*
C
N
N
N
C
Column
1
98
105
112
120
Length
90
6
6
6
1
Decimals
2
2
2
Description
Category description
Control efficiency to be applied to existing emission sources
Control efficiency to be applied to new, modified, or
reconstructed emission sources
Percentage of future emissions attributed to new sources
Application control flag: set to 1 if controls are to be applied,
set to 0 not to apply controls
*C = character, N = numeric.
No sample file is currently provided as apart of EMS-HAP
Figure 32. Area and Mobile Source Reduction Information File (area_Chtl.txt)
A-51
-------
File Name: area_sic.txt
File Type: ASCII Text
Variables and File Structure
Name
SrceCatName
SIC
SICdesc
Type*
C
C
C
Column
1
91
96*
Length
90
4
50
Decimals
Description
Category description
SIC code
SIC description
*C = character, N = numeric.
Sample of File Contents (first two rows are headers)
* Area category and sic file:
* Category description c(90), sic c(4), Ix, SIC description c(50)
Acrylic Fibers/Modacrylic Fiber Production
Aerospace Industries
Agricultural Production
Agricultural Field Burning: Open, Propane, Stack Burning
Amino and Phenolic Resins Production
Asphalt Concrete Manufacturing
Asphalt Paving: Cutback Asphalt
Asphalt Paving: Cutback and Emulsified
Asphalt Roofing Manufacturing
Autobody Refinishing Paint Application
Aviation Gas Distribution
28
37
Organic fibers, noncellulosic
Aircraft
01 Agricultural production - crops
01 Agricultural production - crops
28 Plastics materials and resins
29 Asphalt paving mixtures and blocks
16 Highway and street construction
16 Highway and street construction
29 Asphalt felts and coatings
75 Auto repair shops
45 Air transportation
Figure 33. Area Emission Source Category to SIC Cross-Reference File (area_sic.txt)
A-52
-------
APPENDIX B: EMS-HAP Sample Batch Files
-------
Table Of Contents
Program Name
List of Figures Corresponding to Sample Batch Files
Page#
AirportProc
PtDataProc
PtAspenProc
PtTemporal
PtGrowCntl
PtFinalFormat
AreaPrep
MobilePrep
AMProc
Figure 1. Sample of AirportProc Batch File
Figure 2. Sample of PtDataProc Batch File
Figure 3. Sample of PtAspenProc Batch File
Figure 4. Sample of PtTemporal Batch File
Figure 5. Sample of PtGrowCntl Batch File
Figure 6. Sample of PtFinalFormat Batch File
Figure 7. Sample of AreaPrep Batch File
FigureS. Sample of MobilePrep Batch File
Figure 9. Sample of AMProc Batch File
B-l
B-2
B-5
B-6
B-7
B-9
B-ll
B-12
B-13
B-ii
-------
# AirportProc program of EMSHAP
# For this run, we do not concatenate the point source data set with the allocated aircraft emissions
# Define all directories
# path for the point source data set
setenv POINT /data/work!4/ecr/EMSHAP/areamobile/newmobile/
# path for the mobile source data set
setenv MOBILE /data/work 14/ecr/EMSHAP/areamobile/newmobile/
# path for reference data sets
setenv REFDIR /data/work 14/ecr/EMSHAP/reffiles/
# Define all input files
# Point source inventory
setenv INPOINT AAAAA
# Mobile source inventory
setenv INMOBIL mv030900
# Airport allocation reference file
setenv AIRALLC apt_allc
# Define output files
# Point source inventory
setenv OUTPOINT pt0328ap
# Mobile source inventory
setenv OUTMOBIL mv0328ap
# Set add2pt to 1 in order to add allocated airport emission records to the point source inventory.
# set it to 0 to create output file containing only airport emissions.
setenv ADD2PT 0
# Set add2mb to 1 in order to add unallocated airport emission records to the mobile source inventory
# without the allocated airport emission records.
# Set it to 0 to create output file containing only unallocated airport emissions.
setenv ADD2MB 1
cp -p /data/workl4/ecr/EMSHAP/point/Programs/AirportProc.sas AirportProc_032800.sas
sas AirportProc_032800.sas -work/data/worklS/dyl/
Figure 1. Sample of AirportProc Batch File
B-l
-------
# Point Source Processing: The Data Quality Assurance Program (PtDataProc)
# Defaults locations and stack parameters; windows file
# Provide directory paths:
# path for the SAS output data set'
setenv IN_DATA /data/work!4/ecr/EMSHAP/point/nata4-point/
# path for the SAS output data set
setenv OUTDATA /data/work 14/ecr/EMSHAP/point/nata4-poinf
# path for reference SAS data sets
setenv REFFILE /data/work!4/ecr/EMSHAP/reffiles/
# path for reference text files
setenv REFTEXT /data/work 14/ecr/EMSHAP/reffiles/
# path for included program to determine the FIPS from lat/lon
setenv INC_DIR /data/workl4/ecr/EMSHAP/point/Programs/
# path for map files used by the program to determine the FIPS from lat/lon
# this directory must contain three data sets named bound6 and counties and cntyctr2
setenv MAP_DIR /data/workl4/ecr/EMSHAP/reffiles/
# path for output text file of records without latitude/longitude data
setenv OUTTEXT /data/work 14/ecr/EMSHAP/point/nata4-point/
# Provide input and output SAS data set names
# input SAS data set name
setenv INSAS preprocc
# output SAS data set name
setenv OUTSAS dataset
# output SAS data set name created from Windowing portion of the data processing
setenv FINAL dataproc
# Select the procedures to be included in data processing
# Set value to 1 for yes and 0 for no
# Provide name of necessary reference files and other information
# Default invalid or missing locations: set value of DoLocate to 1 for yes and 0 for no
setenv DOLOCATE 1
Figure 2. Sample of PtDataProc Batch File
B-2
-------
# If defaulting locations, provide the name of the include file used to determine
# if the FIPS code on the inventory is valid or not
setenv VALIDFIP validFIP
# Also provide names of the text files containing the
# county centroids by zip code, county FIPS, and state FIPS and postal abbr.
setenv ZIP zipcodes
setenv CNTYCENT cty_cntr
setenv STCENT st_cntr
# Also provide name of include program used to determine missing FIPS from lat/lon
# This program requires three files, bound6, counties, and cntyctr2, located in the MAP_DIR directory
setenv FINDFIPS latlonlfip
# Also provide name of SAS dataset containing the random array of tracts, with radius
# greater than 0.5 miles, for each county to be used to assign default locations
setenv TRACTS trctarry
# Also provide name of SAS dataset containing tract information,
# specifically the location of the tract centroid
setenv TRCTINFO tractinf
# Default stack parameters: set value of DoStack to 1 for yes and 0 for no
setenv DOSTACK 1
# To default stack parameters by SCC: set value of DoSCC to 1 for yes and 0 for no
setenv DOSCCDEF 1
# If defaulting stack parameters by SCC, provide the name of the SCC correspondence file
setenv SCCDEFLT def sec
# To default stack parameters by SIC: set value of DoSIC to 1 for yes and 0 for no
setenv DOSICDEF 1
# If defaulting stack parameters by SIC, provide the name of SIC correspondence file
setenv SICDEFLT def_sic
# If defaulting stack parameters, provide valid ranges and global defaults for each parameter
# Stack Height range
setenv DLOWHT 0.003
setenv DHIHT 381
Figure 2. Sample of PtDataProc Batch File (Continued)
B-3
-------
# Stack Velocity range
setenv DLOWVEL 0.003
setenv DHIVEL 198
# Stack Temperature Range
setenv DLOWTEMP 273
setenv DHITEMP 1505
# Stack Diameter Range
setenv DLOWDIA 0.0762
setenv DHIDIA 15.24
# Set global defaults
setenv DFLTHT 10
setenv DFLTVEL 1
setenv DFLTTEMP 295
setenv DFLTDIA 1
# Window inventory data set by selecting variables and removing records with zero emissions
# To select variables: set value of DoSetVar to 1 for yes and 0 for no
setenv DOSETVAR 1
# To select variables in addition to the required variables: set value of
# UseList to 1 for yes and 0 for no and provide the name of the file
setenv USELIST 1
setenv VARLIST varlist2
# To window by zero emissions and valid locations: set value of DoWindow to 1 for
# yes and 0 for no
setenv DOWINDOW 1
# If windowing inventory, provide names of data sets to store the records with zero
# emissions and the records without lat/lon values. Also provide the name of the
# emissions variable to be used
setenv NOLOCATE nolatlon
setenv ZEROEMIS zeroemis
setenv EMISVAR emis
cp -p /data/work!4/ecr/EMSHAP/point/Programs/ptdataproc.sas ptdataproc_061600.sas
sas ptdataproc_061600.sas -work /data/workl5/dyl/
Figure 2. Sample of PtDataProc Batch File (Continued)
B-4
-------
# Point Source Processing - The ASPEN Specific Program (PtAspenProc)
# Provide directory paths:
# path for the SAS input data set
setenv IN_DATA /data/work 14/ecr/EMSHAP/point/nata4-point/
# path for the SAS output data set
setenv OUTDATA /data/work 14/ecr/EMSHAP/point/nata4-point/
# path for the reference SAS data sets
setenv REFSAS /data/work 14/ecr/EMSHAP/reffiles/
# path for the reference text files
setenv REFTEXT /data/work 14/ecr/EMSHAP/reffiles/
# Provide input and output SAS data set names
# input SAS data set name
setenv INSAS dataproc
# output SAS data set name
setenv OUTSAS PtAspen
# Provide name of the HAP TABLE text files
# These files contain the correspondance between the pollutant code used in the inventory
# and SAROAD code, the NTI HAP code, pollutant descriptions, keep flag and factor variable
# File for nonroad emissions (that is, the airports that are being processed as point sources)
setenv MOBHAPS haptabl_nonroad
# File for point emissions (all point sources other than airports)
setenv PTHAPS haptabl_point_area
# name of the SAS data set containing the urban/rural flags by county (value is 1 or 0 if
# all tracts within the county are the same and value is 9 for non-uniform counties)
setenv CTYFLAG cryflag
# name of the SAS data set containing the census tract information, including
# urban/rural flags, state and county FTP codes, tract location, and tract radius
setenv TRCTINF tractinf
# Provide the values for additional variables used in the program
# Choose the variable in the input data set containing the emissions value
# to be used to window the inventory to only those records with non-zero emission values
setenv EMISVAR emis
cp -p PtAspenProc.sas PtAspenProc_011300.sas
sas PtAspenProc_011300.sas -work /data/workl5/dyl/
Figure 3. Sample of PtAspenProc Batch File
B-5
-------
# Point Source Processing - The Temporal Allocation Progam (PtTemporal)
# Provide directory paths:
# path for the SAS input data set
setenv IN_DATA /data/work 14/ecr/EMSHAP/point/nata4-point/
# path for the SAS output data set
setenv OUTDATA /data/work 14/ecr/EMSHAP/point/nata4-point/
# path for the reference text files
setenv REFFILE /data/work 14/ecr/EMSHAP/reffiles/
# Provide input and output SAS data set names
# input SAS data set name
setenv INSAS PtAspen
# output SAS* data set name
setenv OUTSAS Temporal
# Provide name of Temporal Allocation File (TAP)
setenv TAF taffjiourly
# Provide name of the SCC_AMS correspondance texts:
# name of SCC to SCC_AMS correspondance file
setenv SCCLINK scc2ams
# name of SIC to SCC_AMS correspondance file
setenv SICLINK sic2ams
# name of MACT category code to SCC_AMS correspondance file
setenv MACTLINK mact2scc
# Provide the variable in the input data set containing the emissions value
setenv EMISVAR emis
cp -p /data/workl4/ecr/EMSHAP/Point/Programs/PtTemporal.sas PtTemporal_062000.sas
sas PtTemporal_062000.sas -work /data/workl5/dyl/
Figure 4. Sample of PtTemporal Batch File
B-6
-------
#Point Source Processing - The Growth and Control Program (PtGrowCntl)
#Provide directory paths:
# path for the SAS input datasets
setenv IN_DATA /data/work 14/ecr/EMSHAP/point/JanPoint/
# path for the SAS output datasets
setenv OUTDATA /data/work 14/ecr/EMSHAP/point/JanPoint/
# path for the SAS reference datasets
setenv REFSAS /data/work 14/ecr/EMSHAP/reffiles/
# path for the reference text files
setenv REFTEXT /data/work!4/ecr/EMSHAP/reffiles/
^Provide input and output SAS data set names:
# input SAS data set name
setenv INSAS pttemporal
# input SAS* data set name
setenv OUTSAS ptgrow
#Select functions of the program you want performed on the input file.
# Set value to 1 for yes (or true) and 0 for no (or false)
#Add growth factors: set value of DoGrow to 1 for yes (or true) and 0 for no (or false)
setenv DOGROW 1
# Assign missing SIC codes using' the SCC to SIC correspondence file
# set value of DoSCC to 1 for yes (or true) and 0 for no (or false)
setenv DOSCC 1
# If assigning missing SIC codes, provide the name of the text SCC to SIC correspondence file
setenv SCC2SIC ptscclsic
# If adding growth factors, provide name of SAS data set containing annual growth factors for one year
setenv GF gf07_96
#Add control efficiencies and calculate projected and controlled emissions:
# set value of DoCntl to 1 for yes (or true) and 0 for no (or false)
setenv DOCNTL 1
# Use general MACT reduction control information:
# set value of GenCntl to 1 for yes (or true) and 0 for no (or false)
# then provide the names of the general reduction control information text file
Figure 5. Sample of PtGrowCntl Batch File
B-7
-------
setenv GENCNTL 1
setenv MACTGEN MACT_gen
# Use process and/or pollutant specific MACT reduction control information:
# set value of ProcChem to 1 for yes (or true) and 0 for no (or false)
# then provide the name of the specific MACT control information text file
setenv PROCCHEM 1
setenv MACTSPEC MACT_spec
# Use process and/or pollutant specific facility-level reduction control information:
# set value of SiteChem to 1 for yes (or true) and 0 for no (or false)
# then provide the name of the facility-level control information text file
setenv SITECHEM 1
setenv SITESPEC SITE_spec
^Specify the growth year corresponding to the growth factors used to project the emissions
setenv GROWYR 2007
cp -p ptgrowcntl.sas ptgrowcntl_011300.sas
sas ptgrowncntl_011300.sas -work/data/worklS/dyl/
Figure 5. Sample of PtGrowCntl Batch File (Continued)
B-8
-------
# Point Source Processing - The ASPEN Final Format Program (PtFinalFormat)
# Assigns source groups for ASPEN
# Produces ASPEN-formatted text files
# Provide directory paths:
# path for the SAS input dataset
setenv IN_DATA /data/work 14/ecr/EMSHAP/point/nata4-point/ .
# path for the SAS output dataset
setenv OUTDATA /data/work 14/ecr/EMSHAP/point/nata4-point/
# path for the reference text files
setenv REFFILES /data/work!4/ecr/EMSHAP/reffiles/
# path for the output files for input into ASPEN
setenv OUTFILES /data/workl4/ecr/EMSHAP/ASPENemis/nata4-point/
# path for the single ASCII output file
setenv ASCIIFILE /data/work 14/ecr/EMSHAP/ASPENemis/nata4-point/
# Provide input and output SAS data set names
# input SAS data set name
setenv INSAS temporal
# output SAS* dataset name
setenv OUTSAS pt062000
# Select the procedure to be used to assign source groups
# Assign source groups by source type (major or area): set value of DoSource to 1 for yes
# (or true) and 0 for no (or false)
setenv DOSOURCE 1
# Assign source groups by MACT categories: set value of DoMACT to 1 for yes
# (or true) and 0 for no (or false)
setenv DOMACT 0
# If using MACT categories, provide name of the text file containing the group assignments
setenv MACTGRP MACT_grp
# Assign source groups by SCCs: set value of DoSCC to 1 for yes (or true)
# and 0 for no (or false)
setenv DOSCC 0
# If using SCCs, provide the name of the text file containing the group assignments
setenv SCCGRP SCC6_grp
Figure 6. Sample of PtFinalFormat Batch File
B-9
-------
# Assign source groups by SIC: set value of DoSIC to 1 for yes (or true) and
# 0 for no (or false)
setenv DOSIC 0
# If using SICs, provide the name of the text file containing the group assignments
setenv SICGRP SIC_grp
# Provide a default group assignment (value between 0 and 9) for those source
# not assignment by your selected procedure
setenv DFLTGRP 1
# Select the creation of ASPEN-formatted text files
# Set value of Do Write to 1 for yes (or true) and 0 for no (or false)
setenv DOWRITE 1
# Provide the file name of the text file containing the decay rates for each reactivity class, extention must be .txt
setenv DECAY indecay
# Provide a file identifier to be included in the name of the ASPEN-formatted text files
# and the ASPEN file header
# A limit of 10 characters is recommended.
# Additional characters will be truncated from the file header, not the file name
setenv OUTCODE PT.ptl96.US.D062000
# Specify the source type, set value of Itype to 0 for point sources and 3 for pseudo point sources
setenv ITYPE 0
# Provide an identifying run name to be included in the ASPEN file header
# A limit of 25 characters is recommended.
# Additional characters will be truncated from the file header
setenv RUNID '06/20 run of 06/00 NTT
# Select the creation of the single ASCII-formatted file
# Set value of DoASCII to 1 for yes (or true) and 0 for no (or false)
setenv DOASCII 1
# Provide the file name of the output ASCII file
setenv ASCII PT.ptl96.US.D062000
cp -p /data/workl4/ecr/EMSHAP/point/Programs/PtFinalFormat.sas PtFinalFormat_062000.sas
sas PtFinalFormat_062000.sas -work /data/worklS/dyl/
Figure 6. Sample of PtFinalFormat Batch File (Continued)
B-10
-------
# The Area Source AMProc Preparation Program (AreaPrep)
# Run Title
setenv RUNID ' 1996 NTI Area Source Inventory June 2000'
# SAS input file containing area source inventory
setenv AREADATA areadata
# SAS output file containing processed area source inventory
setenv OUTDATA areaprep
# Input file directory
setenv INPFILES /data/work 14/ecr/EMSHAP/areamobile/nata4-area/
# Ancillary files directory
setenv REFFILES /data/work!4/ecr/EMSHAP/reffiles/
# Output file directory
setenv OUTFILES /data/work 14/ecr/EMSHAP/areamobile/nata4-area/
# Name of Temporal Allocation Factor File
setenv TAFFILE taffjiourly
# Name of Spatial Surrogate reference file
setenv SURRXREF surrxref
# Name of SIC to AMS cross-reference file
setenv SIC2AMS sic2ams
# Name of SCC to AMS cross-reference file
setenv SCC2AMS scc2ams
# Name of MACT to AMS cross-reference file
setenv MACT2AMS mact2ams
cp -p /data/workl4/ecr/EMSHAP/areamobiIe/programs/AreaPrep.sas AreaPrep_060900.sas
sas AreaPrep_060900.sas -work /data/home/mis
Figure 7. Sample of AreaPrep Batch File
B-ll
-------
# The Mobile Source AMProc Preparation Program (MobilePrep)
# Run identification for titles
setenv TITLE ' 1996 NTI Mobile Inventory March 2000 version'
# Input files directory
setenv INPFILES /data/work 14/ecr/EMSHAP/areamobile/newmobile/
# Input emissions file name prefix
setenv INEMIS mv0309ap
# Output files directory
setenv OUTFILES /data/work 14/ecr/EMSHAP/areamobile/newmobile/
# Output emissions file name prefix (limited to 6 characters if using SAS version 6)
setenv OUTEMIS mv0309
# Temporary work directory
setenv WORKDIR /data/workl5
cp -p /data/EMSHAP/areamobile/programs/MobilePrep.sas MobilePrep030900.sas
sas MobilePrep030900.sas
Figure 8. Sample of MobilePrep Batch File
B-12
-------
# The Area and Mobile Source Processor (AMProc)
# This is for running file 1 of the onroad mobile source inventory
# Run identification for titles
setenv RUNID 'AMProc- 1996 NTI onroad*!* mobile source processing (5/09/00)'
# Description of emissions file
setenv EMISLABL '1996 NATA ONRoad* 1 * Mobile Source Emissions (May 2000)'
# Date this run is performed
setenv RUNDATE 050900
# Emissions type (AR or MV)
setenv EMISTYPE MV
# Label for output files (limited to 6 characters if using SAS version 6)
setenv USRLABEL onntl
# Reference files directory
setenv INPFILES /data/work 14/ecr/EMSHAP/reffiles
# Input files directory
setenv INPEMISS /data/work 14/ecr/EMSHAP/areamobile/nata4-mob/
# Output files directory
setenv OUTFILES /data/EMSHAP/ASPENemis/nata4-mob/
# Input emissions file name prefix
setenv EMISFILE MVonnel
# SAP file name prefix
setenv SAFFILE SAFc
# TAP file name prefix
setenv TAFFILE taffjiourly
# Decay rates file name prefix
setenv INDECAY indecay
# Pollutant xref file name prefix
setenv HAPTABLE haptabl_onroad
# Spatial surrogate xref file name prefix
setenv SURRXREF surrxref
# Name of file that contains the ASPEN source group assignments
setenv EMISBINS am_grp.txt
Figure 9. Sample of AMProc Batch File
B-13
-------
# County urban/rural flag xref file name prefix
setenv CNTYUR popflg96
# Select The growth and control option (1= perform growth and control calculations; 0= don't perform growth #
and control calculations; 2=run growth and control only, using an existing temporally and spatially allocated #
emissions file)
setenv GROWCNTL 0
# If doing Growth and Control set the option to re-apply source group definitions (l=yes, 0=no)
setenv REBIN 0
# Select which reduction information files to use (1= assigns and applies user-defined reduction control
# information; 2= assigns and applies MACT reduction information; 0= applies no reduction control
# information)
setenv CNTLFAG 1
# Name of file containing general reduction information by source category
setenv SRCCNTL area_cntl
# Select if pollutant-specific MACT reduction control information file will be used (1= Use pollutant-specific
# MACT reduction information; 0= don't use)
setenv PROCCHEM 0
# Name of file containing general reduction information by MACT
setenv MACTGEN MACT_gen
#Name of file containing specific (pollutant specific) information by MACT
setenv MACTSPEC MACT_spec
# SaveFile = 1 to save large SAS emissions file
setenv SAVEFILE 1
# Lsubsetp = 1 to subset to a pollutant
setenv LSUBSETP 0
# The pollutant code for subsetting to
setenv SUBSETP 98
# Lsubsetg = 1 to subset to a state
setenv LSUBSETG 0
# The 2-character state abbreviation for subsetting to
setenv SUBSETG US
# Lcptime = 1 to print out module run tunes
setenv LCPTIMES 1
# Ldbg = 1 to turn on debugging prints
setenv LDBG 0
Figure 9. Sample of AMProc Batch File (Continued)
B-14
-------
Appendix C: 1996 NTI Point Source Preprocessor
-------
Table of Contents
C.I Description of Point Sources Preprocessor C-l
C.2 Emissions Inventory Input Files C-l
C.3 Output files Produced to Assist Quality Assurance C-2
C.4 Output Files Used in EMS-HAP Processing C-2
C-i
-------
C.I Description of Point Sources Preprocessor
The Point Sources Preprocessor provided with EMS-HAP is designed primarily to read the
modeler's version of the 1996 National Toxics Inventory (NTI), and produce a file suitable for
processing through the first point source processing program (PtDataProc) of EMS-HAP. The
preprocessor draws data from a number of NTI input files for point sources. Fields in the various.
NTI point source files are linked in accordance with the instructions in NTI documentation.
For convenience, the Point Sources Preprocessor is divided into two SAS® programs: PreprocA
and PreprocB. PreprocA preforms two functions in addition to reading various NTI point source
files and linking them together. Where the emissions for a stack are reported in more than one
type, a single value for the stack is selected according to the following hierarchy: (1) actual
annual (most preferred type), (2) actual hourly, (3) average, (4) average daily, (5) potential, (5)
maximum annual, (6) maximum, (7) maximum allowable, (8) maximum hourly, (9) unknown
(least preferred type). In addition, the emissions values are converted to tons/year based on the
unit in which the emission values were reported in the NTI point source files. Furthermore,
PreProcA reassigns the source type variable, SRCJTYPE, if the inventory SRC_TYPE is
'unknown '. The source type is reassigned to 'major' when the total emissions of any single
pollutant from a facility (based on the Site_ID) is greater than 10 tons/year or if the total
emissions of all pollutants from the facility is greater than 25 tons/year. For all other facilities,
the source type is reassigned to 'area'.
PreprocB also performs several functions in addition to reading various NTI point source files
and linking them together. Stack parameters are converted from English units, as reported in the
NTI, to metric units. In addition, all emission records for sites located in Alaska and Hawaii are
removed.
C.2 Emissions Inventory Input Files
The EMS-HAP Point Sources Preprocessor reads the following files from the NTI:
• activities.csv
• emissions.csv
• emission_processes.csv
• emission_units.csv
• sites.csv
• addresses.csv
• control_strategies.csv
• aggregate_controls.csv
• paths.csv
• emission_release_points.csv
• geographic_locations.csv
• geographic_coordinates.csv
The format of these files is detailed in the NTI documentation.
c-i - -
-------
C.3 Output files Produced to Assist Quality Assurance
There are two ways you can monitor the quality of the data and the functioning of the Point
Source Preprocessor. First, you can monitor the point source emissions, either by pollutant code
or overall inventory total, and the number of records contained within the inventory. Three
S AS® data sets are produced (EmisSum and ProcASum by PreprocA, and ProcBSum by
PreprocB) that contain emission totals and record counts by pollutant code. In addition, these
sums are printed to the list file produced when the programs are run. The EmisSum data set is
produced immediately after the emissions data are read, emission records are selected by type,
and emission values are converted to tons/year. The ProcASum and ProcBSum data sets are
produced at the end of the PreprocA and PreprocB programs, respectively. The only changes
you should observe in the emission totals or the record counts occur in the PreprocB program,
because of the removal of emission records from Alaska and Hawaii. Both emission totals and
record counts for Alaska and Hawaii emissions are provided in the PreprocB list file.
You can also evaluate the processing of data through PreprocA and PreprocB by monitoring the
reading of the NTI data files and the linking of these files together. This information is provided
in the list file produced when the program is run. When an error occurs in reading vital data
from the data file, the data are printed to the list file. When data are merged with the emissions
data, unmatched data records are also printed to the list file. Any unmatched emissions records
are of particular importance.
C.4 Output Files Used in EMS-HAP Processing
The output file produced by the Point Source Preprocessor is a SAS® data set containing the data
variables listed in Table C-l. This table includes the variable format and whether or not the data
variable is mandatory for processing through the programs of EMS-HAP.
In addition to the required variable listed above, each record within the output data from the
Point Source Preprocessor must be uniquely identified by the combination of the activity ID
(ACTJD), pollutant code (POLLCODE), and emission release point ID (EMRELPID). In
addition, all stack parameters within a group of records identified by the FIPS code (FIPS),
activity ID (ACT_ID), and emission release point ID (EMRELPID) must have the same stack
parameters.
C-2
-------
Table C-1. Description of Variables Contained in the Point Source Preprocessor Output
File using the 1996 NTI
Variable
Name
ACTJD
ADDRTYPE
AIRBASIN
AIRSPLID
AIRSPTID
AMS_CODE
AQCR
CITY
CNTLSTRT
CNTL_EFF
COORJD
COUNTRY
CTRLSTAT
CTY_FIPS
DB_NO
DESCRIPT
DIAM_FLG
D_HORIZ
D_UNITS
D_VERT
EMIS
EMISTYPE
Data Description
unique identifier assigned in activities.csv file
code for type of address provided
name of state-designated air basin
AIRS ID for facility
AIRS point ID
source category AMS code
air quality control region of source
name of nearest city
unque identifier assigned in
control_strategies.csv file
total capture control efficiency
unique identifier assigned in
geographic_coordinates.csv file
FIPS country code
control status indicator code
3 -digit FIPS county code
Dun & Bradstreet number of facility
text description of emission release point
indicates if default stack diameter assigned
nonstack horizontal dimension
units used for nonstack dimensions
nonstack vertical dimension
pollutant emissions value (tons/year)
code based on qualifier for emission estimate
Length
25
2
40
8
6
5
8.
32
25
8
20
5
14
3
12
40
20
8.
50
8.
E10
2
Format
Character
Character
Character
Character
Character
Character
Numeric
Character
Character
Numeric
Character
Character
Character
Character
Character
Character
Character
Numeric
Character
Numeric
Numeric
Character
Required
yes
no
no
no
no
no
no
no
no
yes
yes
no
no
no
no
no
no
no
no
no
yes
no
C-3
-------
Table C-l. Description of Variables Contained in the Point Source Preprocessor Output
File using the 1996 NTI (continued)
Variable
Name
EMRELPID
EMRELPTY
END
EPA_REG
FACILITY
FED2DESC
FEDJD
FEDJD2
FENCEDIS
FIPS
FLOWRATE
FLOW_FLG
GEOJD
HT_FLG
IDDF_FLG
MACTCODE
MACTFLAG
METHCODE
NTI_CODE
N_STACKS
PLUME_HT
Data Description
unique identifier from paths. csv file
physical configuration code of release point
ending time for inventory year
EPA region in which source is located
facility ID assigned to a group site Ids
representing the same facility
coding system used to develop FED_ID2 value
AIRS stack ID
ID corresponding to FED2DESC variable
distance to nearest fenceline (feet)
5-digit FIPS code (state and county combined)
stack gas flow rate (standard cubic feet per
second)
indicates if default flow rate assigned
unique identifier assigned in
geographic_locations.csv file
indicates if default stack height assigned
indicates if default value assigned within
emission release point information file
MACT code based on process or site
indicates if MACT code is SCC-based default
emission estimation method code
[not currently used in NTI]
number of stacks for each process, unit, or site
calculated plume height of exhaust stream from
stack (feet)
Length
50
4
8
2
20
30
5
16
8.
5.
12.
20
20
20
20
7
12
5
10
8.
8.
Format
Character
Character
Character
Character
Character
Character
Character
Character
Numeric
Numeric
Numeric
Character
Character
Character
Character
Character
Character
Character
Character
Numeric
Numeric
Required
yes
yes
no
no
no
no
no
no
no
yes
no
no
no
no
no
yes
no
no
no
no
no
C-4
-------
Table C-l. Description of Variables Contained in the Point Source Preprocessor Output
File using the 1996 NTI (continued)
Variable
Name
Data Description
Length Format Required
POLLCODE unique NTI pollutant code number
PROC_ID unique identifier from emission_processes.esv
file
SCC EPA source category code
SEGMTJD AIRS segment ID
SEQ_NO order number of a sequence of coordinate
points
SIC source category SIC code
SITENAME facility name
SITERULE name of a control regulation or rule
SITE_ID unique identifier from sites.csv file
SITE_LOC geographic location code assigned in sites.csv
file
SRC_TYPE source category to which the emission source
belongs
STACKDIA diameter of stack (meters)
STACKHT height of stack (meters)
STACKVEL velocity of exhaust gas stream (meters per
second)
STACKJD state or local stack ID
START Beginning time for inventory year
STCK_LOC geographic location code assigned in
emission_release_point.csv file
STKTEMP temperature of exhaust gas stream (Kelvin)
STLOCUID emission unit ID used at state or local level
STLOC_ID process ID used at state or local level
10 Character yes
25 Character no
10 Character yes
3 Character no
2 Character no
4 Character yes
65 Character no
200 Character no
20 Character yes
20 Character no
15 Character yes
8. Numeric yes
8. Numeric yes
8. Numeric yes
20 Character no
8 Character no
20 Character no
10. Numeric yes
35 Character no
37 Character no
C-5
-------
Table C-l. Description of Variables Contained in the Point Source Preprocessor Output
File using the 1996 NTI (continued)
Variable
Name
ST_FIPS
TEMP_FLG
THRUMETH
THRUPUT
TRANSJD
UNITS
UNITTEXT
UNITTYPE
UNITJD
UNIT_LOC
UTM_Z
VEL_FLG
X
XY_TYPE
Y
ZIP_CODE
Data Description
2-digit FIPS state code
indicates if default stack temperature assigned
code for method of estimation of throughput
numeric value of process activity
unique identifier assigned in transmittals.csv
file
dimensional units of pollutant emissions
full-text specification dimensional units
code for emission unit type
unique identifier assigned in emission units.csv
file
geographic location code assigned in units.csv
file
universal transverse mercator (UTM) zone
indicates if default stack velocity assigned
longitude or UTM easting
type of coordinate system used (LAT/LON or
UTM)
latitude or UTM northing
zip code of source
Length
2
20
5
8.
15
12
40
3
25
20
3.
20
10.
7
10.
12
Format
Character
Character
Character
Numeric
Character
Character
Character
Character
Character
Character
Numeric
Character
Numeric
Character
Numeric
Character
Required
no
no
no
no
no
no
no
no
no
no
yes
no
yes
yes
yes
yes
C-6
-------
APPENDIX D
Preparation of ASPEN-input Files for the 1996 Base
Year Using EMS-HAP
-------
Table of Contents
APPENDIX D PREPARATION OF ASPEN-INPUT FILES FOR THE 1996 BASE YEAR
USING EMS-HAP D-l
D. 1 How We Prepared the Emission Inventories for Input Into EMS-HAP D-2
D.I.I We used the 1996 NTI D-2
D.I.2 We used the 1996 NET inventory, speciated for particular VOCs D-3
D. 1.3 We used a rulemaking inventory and the 1996 NET inventory for diesel PM . D-6
D.2 How We Ran EMS-HAP D-7
D.2.1 We ran it for the direct emissions of HAPs and diesel PM D-7
D.2.2 We ran it for the HAP precursors D-8
D.3 The Ancillary Files We Used D-9
D.4 How We Developed the Airport Allocation Ancillary File (apt_allc) D-l3
D.4.1 We assembled airport location data D-13
D.4.2 We developed airport allocation factors D-13
D.5 How We Selected HAPs. Grouped/Partitioned Them, and Determined Their
Characteristics (HAP Table for HAPs) :...' D-14
D.5.1 We assigned reactivity and particulate size classes D-14
D.5.2 We grouped HAP species belonging to HAP compound classes D-l6
D.6 How We Selected the HAP Precursors. Grouped/Partitioned Them, and Determined
Their Characteristics (HAP Table for Precursors) D-22
- D.7 How We Developed the Temporal Allocation Factors File (taff_hourly.txt) D-24
D.8 How We Assigned Spatial Surrogates for Area and Mobile Source Categories . . D-33
D.9 How We Developed the Surrogate Assignment / Temporal Allocation Cross-Reference
Files (scc2ams.txt, sic2ams.txt, andmact2scc.txt) D-42
D.10 How We Developed the Spatial Allocation Factors for the Spatial Surrogates ... D-43
D. 11 Program Options and Parameters D-52
D. 11.1 AirportProc program options D-52
D.I 1.2 PtDataProc program options and parameters D-52
D. 11.3 PtFinalFormat program options and parameters D-54
D. 11.4 AMProc program options D-55
D. 12 Pollutants in the ASPEN-Input Files for the 1996 Base Year EMS-HAP Run . . . D-55
D-ii
-------
List of Tables
Table D-l. Non-HAP VOC Species Used for Modeling Secondary HAP Formation D-4
Table D-2. Source of Speciation Data for Mobile Source Categories D-5
Table D-3. Summary Speciation Protocol for Non-HAP Precursor Species D-6
Table D-4. Ancillary Files Used in EMS-HAP for the 1996 Base Year Run D-10
Table D-5. Average Particulate Size Class Allocation Factors D-l5
Table D-6. Gas and Particulate Allocations for Mercury Compounds D-l5
Table D-7. 7-PAH and 16-PAH Subgroups, and Additional Individual POM Compounds
with Available Health Data D-18
Table D-8. Grouping Scheme for Total POM D-19
Table D-9. Species, Groups and Subgroups of Dioxins Reported in the 1996 NTI D-21
Table D-10. Scaling Factors for HAP Precursors D-23
Table D-l 1. Additions to the ORD Temporal Profile Database D-27
Table D-12. Temporal Allocation of Some Area Source Categories in EMS-HAP D-28
Table D-13. Temporal Allocation of Mobile Source Categories in EMS-HAP D-29
Table D-14. Spatial Allocation of Some Area Source Categories in EMS-HAP as compared
to Other Emission Models D-34
Table D-l 5. Surrogates Used for Spatial Allocation of the 1996 NTI Area Source
Inventory D-35
Table D-16. Surrogates Used for Spatial Allocation of the 1996 Diesel PM Inventory D-39
Table D-17. Spatial Allocation of Mobile Source Categories in EMS-HAP as Compared
to Other Emission Models D-40
Table D-18. Spatial Allocation Factors Developed for EMS-HAP D-44
Table D-19. Surrogate Data Available for Puerto Rico and the Virgin Islands D-47
Table D-20. Methodology for Puerto Rico/Virgin Islands Spatial Allocation Factors .... D-47
Table D-21. Program Options Used to Execute AirportProc D-52
Table D-22. Program Options and Parameters Used for PtDataProc D-53
Table D-23. Program Options and Parameters Used for PtFinalFormat D-54
Table D-24. Program Options Used to Execute AMProc D-55
Table D-25. List of Pollutants in ASPEN-ready input files * D-56
D-iii
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List of Figures
Figure D-l. Composite Temporal Emission Profile for On-road Motor Vehicles D-31
Figure D-2. Temporal Profiles for Diesel Highway Vehicles and Non-road Engines D-32
Figure D-3, Nationwide Tract-level Emission Densities Using Three Different Treatments
of SAF19 D-50
Figure D-4. The Effect of the Three Different Treatments of S AF19 on State-level Mean
Concentrations Estimates D-51
D-iv
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Appendix D
Preparation of ASPEN-input Files for the 1996 Base
Year Using EMS-HAP
This appendix describes how we processed-inventories containing 1996 emission data through
EMS-HAP to create the ASPEN-input files for a national scale air toxics assessment.
We created ASPEN-input files for the direct emissions of hazardous air pollutants (HAPs), direct
emissions of diesel particulate matter (PM), and pollutants that will react in the atmosphere to
produce HAPs.
The 1990 Clean Air Act (Section 112) lists a number of HAPs and provides a process to add and
delete pollutants from the list. There are currently 188 HAPs.1 The pollutants that will produce
HAPs are referred to as HAP precursors and the transformation as secondary HAP formation.
The HAP precursors are volatile organic compounds (VOC's) which may or may not be HAPs
themselves. We refer to those VOC's which are not HAPs as "non-HAP" VOC's.
Section D.I discusses the emission inventories we used, and how we prepared them for EMS-
HAP. Section D.2 describes the run stream for the EMS-HAP programs we ran. Sections D.3
through D.10 presents the ancillary input files we used, and discusses how we created the key
ones for EMS-HAP (e.g., the spatial and temporal allocation factor files.) Section D.I 1 presents
the program options we selected. Section D. 12 lists the pollutants in the ASPEN-input files
resulting from our run of EMS-HAP.
D-l
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D.I How We Prepared the Emission Inventories for Input Into EMS-HAP
We prepared two point, two area and three mobile source inventories for input into EMS-HAP,
as shown below.
Directly emitted HAPs
HAP precursors
Diesel PM
Point
Source
Inventor
y
X
X
Area
Source
Inventor
y
X
X
Mobile
Source
Inventor
y
X
X
X
The emission data for directly emitted HAPs were obtained from the February 2000 (mobile),
June 2000 (point") and August 2000 (area) versions of the 1996 National Toxics Inventory
(NTI).2 HAP precursor emission data were obtained from two separate sources: (1) non-HAP
VOC's came from Version 3 of 1996 National Emissions Trends (NET)3 inventory, speciated for
specific organic compounds; (2) data for HAPs that are precursors to other HAPs came from the
1996 NTI (same versions as specified above). The diesel PM data came from two sources: (1)
data for the continental U.S. were from inventories developed as part of the rulemaking for
Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control
Requirements; (2) data for Puerto Rico and Virgin Islands were derived from Version 3 of the
NET's mobile source particulate matter (PM-10) inventory.
The next subsections provide more details on the sources of data we used and how we prepared
the data for EMS-HAP.
D. 1.1 We used the 1996 NTI
The emission data for directly emitted HAPs were obtained from the 1996 National Toxics
Inventory (NTI).2 We received point, area and mobile source files at different times throughout
the year 2000, but the data we used are consistent with the August 2000 version of the 1996 NTI
with a very few exceptions to the point source data."
We received the 1996 NTI point source inventory modeler's version as 14 text files linked
together through a variety of identification codes which serve as primary and secondary keys.
We also received cross-reference files defining these codes. The 1996 NTI contains data from
°A small number of revisions to NTI point source estimates were made manually for purposes of ASPEN modeling
without creating a corresponding version of the NTI itself, based on state requested revisions after June 2000.
These revisions consisted of less than 20 facility deletions to the point source inventory.
D-2
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the 50 States, the District of Columbia, Puerto Rico and the Virgin Islands. We developed two
preprocessing programs to read these files and link them together according to the instructions in
the NTI documentation. These preprocessing programs are described in Appendix C. The point
source inventory file produced by executing our preprocessing programs met all of the data
criteria required by EMS-HAP.
We received the 1996 NTI area and mobile source inventory modeler's versions as flat text files
(i.e., they didn't need to be linked). We received the area source inventory as a single file
containing data from the 50 States, the District of Columbia, Puerto Rico and the Virgin Islands.
We received the mobile source inventory as 53 files, one for each State, the District of Columbia,
Puerto Rico and the Virgin Islands. We developed preprocessing programs to read these area
and mobile source text files and produce SAS* files that met the criteria required by EMS-HAP.
The 1996 NTI point, area and mobile source documentation is in six volumes4:
• Documentation for the 1996 Base Year National Toxics Inventory for Point Sources
• Documentation for the 1996 Base Year National Toxics Inventory for Aircraft Sources
• Documentation for the 1996 Base Year National Toxics Inventory for Area Sources
• Documentation for the 1996 Base Year National Toxics Inventory for Commercial
Marine Vessel and Locomotive Mobile Sources
• Documentation for the 1996 Base Year National Toxics Inventory for Nonroad Vehicle
and Equipment Mobile Sources
• Documentation for the 1996 Base Year National Toxics Inventory for Onroad Sources
These can be accessed on the EPA web site at http://www.epa.gov/ttn/chief/ei_guide.html#toxic.
D.I.2 We used the 1996 NET inventory, speciated for particular VOCs
We received point, area and mobile source emission data for 33 non-HAP VOC species resulting
from a speciation of the Version 3 1996 NET inventory. Table D-l provides a list of these and
also shows which HAPs they form through secondary transformation. We received this data for
the continental U.S. and the District of Columbia. The NET inventory does not contain data for
Puerto Rico nor the Virgin Islands. Emissions for these territories were derived via extrapolation
of emissions estimates from surrogate U.S. locations. This was the same approach as was used
for the area and mobile source components of the 1996 NTI. No speciated point source VOC's
were obtained for Puerto Rico and the Virgin Islands.
D-3
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Table D-l. Non-HAP VOC Species Used for Modeling Secondary HAP Formation
HAP Formed from VOC Species
formaldehyde acetaldehyde propionaldehyde MEK
ethene X
propene X X
1-butene X X
1-pentene X
1-hexene X
1-heptene X
1-octene X
1-nonene X
1-decene X
isobutene (2methylpropene) X
2-methyl- 1-butene X X
3-methyl-1-butene X
3-methyl-1-pentene X
2,3-dimethyl-l-butene X
isoprene X
2-ethyl- 1-butene X
2-methyl-1-pentene X
4-methyl- 1-pentene X
2,4,4-trimethyl-l-pentene X
2-butene X
2-pentene X X
2-hexene X
2-heptene X
2-octene X
2-nonene X
2-methyl-2-butene X
3-methyl-2-pentene X
4-methyl-2-pentene X
ethanol X
3-hexene X
butane X
isopentane X
3-methvlt)entane X
D-4
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Except for a few mobile source categories, the VOC data were speciated using the SPECIATE
database. Based on the 1990 inventory used for the Cumulative Exposure Project (CEP), most of
the anthropogenic precursors come from mobile sources. Therefore, most of the efforts in this
study to speciate anthropogenic emissions were for mobile sources. We asked staff from the
Office of Transportation and Air Quality (OTAQ), formerly called the Office of Mobile Sources
(OMS), for speciation data applicable to 1996 mobile source emissions. OTAQ staff indicated
that there was a paucity of speciation data applicable to most 1996 mobile source emissions.
They provided recommendations and/or data to use for speciating the various types of mobile
sources. Table D-2 summarizes their recommendations.5
Table D-2. Source of Speciation Data for Mobile Source Categories
Mobile Source Category
Light Duty Gasoline Vehicles (LDGV)
Light Duty Gasoline Trucks (LDGT)
Heavy Duty Gasoline Vehicles
(HDGV)
Motorcycles (MC)
Light Duty Diesel Vehicles (LDDV)
Light Duty Diesel Trucks (LDDT)
Heavy Duty Diesel Vehicles (HDDV)
All Off-highway Vehicle: Gasoline,
2-Stroke
All Off-highway Vehicle: Gasoline,
4-Stroke
All Off-highway Vehicle: Diesel
All Aircraft Types and Operations
Marine Vessels, Commercial
Railroads-Diesel
AMS code
A2201001
A2201060
A2201070
A2201080
A2230001
A2230060
A2230070
A2260000
A2265000
A2270000
A2275000
A2280000
A2285002
Speciation Profile to Obtain those non-HAP VOC
species that are precursors to HAP formation
EXHAUST PROFILE BASED ON SPECIATE 1313
NONEXHAUST PROFILE BASED ON SPECIATE 1305
Speciate exhaust and nonexhaust emissions separately by
appling the above profiles directly to each of these rather than
summing exhaust and nonexhaust emissions and applying a
composite profile.
Use HDDV profile
Use HDDV profile
Create HDDV profile from emission data collected from the
California Air Resources Board diesel exhaust toxicity test
program.6 Data supplied by Rich Cook, OTAQ, 9/29/99.
Instructions:
Develop a composite profile from the hot and cold start
fractions by weighting cold start 1/7 and hot start 6/7.
Create 2-srroke gasoline profile from unpublished test data on
two types of two stroke engines from Peter Gabele, EPA
Office of Research and Development, supplied by Rich
Cook, OTAQ, 9/29/99
Create 4-stroke gasoline profiles from emission data collected
by EPA's Office of Research and Development on four stroke
lawn mower engines.7 Data supplied by Rich Cook, OTAQ
9/29/99.
Use HDDV profile
Use SPECIATE profile for commercial aircraft
Use HDDV profile
Use HDDV profile
D-5
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In some cases, the speciation data available in the SPECIATE database were not consistent with
the species needed to model secondary HAP formation. We developed a protocol presented in
Table D-3, to address these situations.
Table D-3. Summary Speciation Protocol for Non-HAP Precursor Species
If the speciation
information
Then
For example
Specifically lists the desired Use that value
precursor
Contains the cis or trans isomers
of the same compound listed
Contains a group that is limited
in scope and that has one or
more precursors desired
Contains a broad group that can
represent several precursors
desired, but also a large number
of chemicals that are not
precursors
Use those values
Divide the value for the group by
number of precursors in Table D-l
that are in the group, less the
number of precursors that are
already in the profile. Use the
result for all precursors that belong
in the group other than those that
are already listed in the profile.
Do not use that value
Use the value for 1-pentene
Use the values for "cis-2-pentene and
"trans-2-pentene" for 2-pentene (sum
the cis and trans isomers)
If the profile contains a group called
"C-5 ene" and has no specific "C-5
enes" from Table D-l, then divide the
"C-5 ene by five and use the resulting
value for: 1-pentene, 2-pentene, 2-
methyl-2-butene, 2-methyl-1 -butene,
and 3-methyl-l-butene.
Do not use "C5H10"
In order to prepare the speciated VOC emission data for processing through EMS-HAP, we
developed and ran several preprocessing programs. These programs read the VOC data, create
all the necessary variables, and ensure that the data meet the criteria required by EMS-HAP.
D.I.3 We used a rulemaking inventory and the 1996 NET inventory for diesel PM
The diesel PM emissions data for the continental United States were derived from 1996 base-
year inventories developed as part of the rulemaking on Heavy-Duty Engine and Vehicle
Standards and Highway Diesel Fuel Sulfur Control Requirements (June 2, 2000; 65 FR 35430).
These inventories are based on Federal Highway estimates of vehicle operation, estimates of the
distribution of fuel type and weight classes of vehicles from the EPA Office of Transportation
and Air Quality (OTAQ), and adjusted MOBILESb emission factors to simulate projected results
from MOBILE6. The nonroad emissions, with the exception of aircraft, commercial marine, and
locomotive emissions, were from OTAQ's June 2000 draft NONROAD model.8
Note that we did not use the final 1996 base-year inventory developed for the rulemaking. In
addition to including only the exhaust (no brake and tire wear) component of the emissions, the
inventory we used did not include OTAQ's latest information on adjustments to account for on-
D-6
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highway emissions modifications. Further, both the onroad and nonroad diesel PM inventories
we used reflect changes in methods and data sources since the release of versions we used for the
1996 NET and 1996 NTI. Time did not allow for estimates of other HAP from diesel vehicles
and equipment to be revised accordingly, but an exploratory analysis indicated that the effect on
estimates of other HAP would not have been large.
We received the diesel PM data as two text files (one for onroad and one for nonroad), each
containing of estimates diesel-fine PM (PM-2.5) and diesel-coarse PM (PM-2.5 to PM-10) by
county and by source category.
The 1996 NET PM-10 data were used to estimate mobile source diesel PM emissions for Puerto
Rico and Virgin Islands. As discussed earlier, the NET does not contain data for these territories.
Thus, similar to the non-HAP precursors, diesel PM emissions were derived via extrapolation of
emissions estimates from surrogate U.S. locations. We concatenated the U.S. data with the
territorial data prior to running EMS-HAP. Because we received only diesel PM-10 estimates
for Puerto Rico and the Virgin Islands, we used EMS-HAP to partition them into coarse and fine
diesel PM (See D.5.1).
Note that the diesel PM inventories included estimates from only mobile sources. In addition,
the diesel PM data for onroad vehicles for the continental U.S. and District of Columbia were
restricted to their exhaust PM; NET estimates of PM from diesel vehicles include all PM
attributable to the vehicles including brake and tire wear (but not road dust). Therefore, the
PR/VI estimates included brake and tire wear.
D.2 How We Ran EMS-HAP
Section D.12 contains a list of the pollutants we modeled in EMS-HAP. The list includes the
direct emissions of HAPs and diesel PM, and emissions of pollutants that are precursors to
HAPs. Section D.2.1 describes the EMS-HAP run stream for the direct emissions of HAPs and
diesel PM. Section D.2.2 describes it for the precursors.
D.2.1 We ran it for the direct emissions of HAPs and diesel PM
We used EMS-HAP to model direct emissions of pollutants on the list of 33 HAPs in the Urban
Air Toxics Strategy.9 We also modeled additional HAPs (not on the list) requested by EPA's
Office of Transportation and Air Quality (OTAQ), and diesel PM. Note that diesel PM is not a
listed HAP.
Aircraft Emissions Processing
We processed the 1996 NTI mobile source inventory through a preprocessing program to read in
the mobile source emission data and format them as required by AirportProc. We then processed
the mobile source emissions through the AirportProc program. We did not process any point
source emissions through the AirportProc program since we chose not to append the aircraft
point sources to the non-aircraft point sources. We ran the point source output file from
D-7 * '
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AirportProc (i.e., the point source aircraft inventory) through the point source processing
programs in the following order: PtDataProc, PtAspenProc, PtTemporal, and PtFinalFormat.
Because aircraft emissions do not contain diesel PM, we did not process this inventory through
AirportProc nor the subsequent point source programs.
Point Source Processing
We processed the 1996 NTI point source inventory through two preprocessing programs
(discussed in Appendix C) to read in the point source emission data and format it as required by
PtDataProc. We then processed the point source emissions through the point source processing
programs in the following order: PtDataProc, PtAspenProc, PtTemporal, and PtFinalFormat.
We did not have diesel PM emissions from point sources.
Mobile Source Processing
We processed the mobile source output file from AirportProc through MobilePrep. We then
separately processed the nonroad and onroad mobile source data through AMProc. Separate
processing was necessary because the coarse-fine particulate matter splits for some of the metals
in these two inventories are different, and therefore we had to use two different HAP tables (see
Section D.5), Due of the size of the onroad mobile file, we split it into three parts and ran each
part separately through AMProc.
We processed the diesel PM emissions inventory separately from the HAPs. We first processed
this inventory through a preprocessing program (to prepare it for MobilePrep). We ran
MobilePrep and then processed the total (onroad and nonroad together) mobile source output
inventory through AMProc. We were able to process onroad and nonroad together because the
same HAP table file (see Section D.5) applies to both onroad and nonroad diesel PM.
Area Source Processing
We processed the 1996 NTI area source inventory through a preprocessing program to read in the
area source emission data and format it as required by AreaPrep. Due to the size of the area
source file, we split it into two parts and then ran each part separately through AMProc.
D.2.2 We ran it for the HAP precursors
The EPA's Cumulative Exposure Project (CEP)'10 which selected the year 1990 as its focus,
identified thirteen HAPs for which secondary formation may account for a significant portion of
ambient concentrations. Of these HAPs, we modeled formaldehyde, acetaldehyde,
propionaldehyde, and acrolein. The precursors to formaldehyde include both HAPs and non-
HAP VOC's.
We used EMS-HAP to process data from two separate emission inventories in order to prepare
D-8
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ASPEN input files for the HAP precursors. For the non-HAP VOC's, we used data from the
1996 NET inventory, speciated for the particular VOC's we needed (as discussed previously in
Section D.I.2). For the precursors which are HAPs, we used the 1996 NTI. Table D-25, which
lists all of the pollutants we modeled in EMS-HAP, also contains entries for the precursors we
modeled. Note that because 1,3 butadiene, which was modeled as a directly emitted HAP, is the
only precursor for acrolein, Table D-25 does not have a separate entry for "acrolein, precursor." .
Aircraft Emissions Processing
We merged the mobile NTI emissions with the speciated mobile NET emissions in a pre-
processor and ran that through AirportProc. We then fed the output precursor aircraft emissions
inventory to the point source processing programs in the following order: PtDataProc,
PtAspenProc, PtTemporal, and PtFinalFormat. We used the precursor HAP table (see D.6) in
PtAspenProc.
Point Source Emissions Processing
We ran the speciated NET point source inventory through a preprocessing program and then ran
it through PtDataProc and PtAspenProc, using the precursor HAP table file (see D.6). We ran
the 1996 NTI through PtDataProc and PtAspenProc, also using the precursor HAP table file. We
then merged the output of the two separate runs of PtAspenProc and ran the resulting precursor
inventory through PtTemporal, and PtFinalFormat.
Mobile Source Processing
We processed the precursor output (containing both NET and NTI data) from AirportProc
through MobilePrep. We processed the nonroad and onroad mobile precursor data together
through AMProc. We were able to process onroad and nonroad together because both used the
same HAP table file (the precursor HAP table).
Area Source Processing
We merged those area NTI emissions which are HAP precursors with the speciated area NET
emissions and ran the resulting precursor inventory through AreaPrep. We then ran the output
through AMProc.
D.3 The Ancillary Files We Used
Each EMS-HAP program (except for MobilePrep) requires a variety of ancillary input files. The
ancillary files we used to prepare 1996 base year ASPEN input files are provided as a part of
EMS-HAP. Table D-4 lists the ancillary input files for each program we ran. Some of the
ancillary files used for area and mobile source processing are the same as those used for point
source processing. File formats, descriptions, and sample data for each of these files are
provided in Appendix A. This appendix (see Tables 1-4) also lists the contents of all of the
HAP table files in their entirety.
D-9 - -
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Table D-4. Ancillary Files Used in EMS-HAP for the 1996 Base Year Run
EMS-HAP Batch File
Program Keyword
File Name
(SAS files are shown
without their
extension)
Data Source and Appendix D section
which provides more information
Aircraft Emissions Processing
AirportProc
AIRALLC
apt_allc
Point Source Processing
PtDataProc and its "include" programs validFIP and Iatlon2fip
ZIP zipcodes
CNTYCENT cty_cntr
STCENT
N/A*
N/A*
N/A*
TRACTS
st_cnrr
counties
bound6
cntyctr2
trctarry
TRCTINFO
SCCDEFLT
SICDEFLT
VARLIST
tractinf
def scc.txt
def sic.txt
varlist.txt
based on data complied by Gregory Rigamer
and Associates" and the FAA12 See D.4
developed from a SAS* map data set
developed from a geographic information
systems (GIS) database
developed from a SAS* map data set
SAS* map data set
developed from a SAS* map data set
developed from a GIS database
developed by creating random arrays of the
tracts within each county from tractinf file
urban/rural designations based on 1990
designations made in the CEP13; tract radius
and centroid data based on 1990 Census data
developed from averaging stack parameter data
for each SCC from June 2000 version of the
1996 point source NTI
developed from averaging stack parameter data
for each SIC from June 2000 version of the
1996 point source NTI
based on our preference
D-10
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Table D-4. Ancillary Files Used in EMS-HAP for the 1996 Base Year Run (continued)
EMS-HAP
Program
Batch File
Keyword
File Name
Data Source and Appendix D section
which provides more information
Point Source Processing.... continued
PtAspenProc
PtTemporal
PtFinalFormat
MOBHAPS
PTHAPS
CTYFLAG
TRCTINF
TAP
SCCLINK
SICLINK
MACTLINK
DECAY
haptabl_nonroad.txt (direct
emissions)
haptabl_precusor.txt
(precursor emissions)
haptabl_point_area.txt
(direct emissions)
haptabl_precusor.txt
(precursor emissions)
ctyflag
tractinf
taff_hourly.txt
scc2ams.txt
sic2ams.txt
mact2scc.txt
indecay.txt
reactivity and paniculate size class
information based on the analytical
framework developed in the CEP14 See D.5
and D.6
reactivity and particulate size class
information based on the analytical
framework developed in the CEP14 See D.5
and D.6
developed from trctinf file
same file as TRCTINFO under PtDataProc
Primarily from temporal allocation database
maintained by EPA's Office of Research
and Development (ORD) See D.7
based on EPA's FIRE database15 See D.8
and D.9
based on SIC definitions published by the
Office of Management and Budget16 See
D.8 and D.9
based on MACT category definitions17 See
D.8 and D.9
derived from the CEP14
D-ll
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Table D-4. Ancillary Files Used in EMS-HAP for the 1996 Base Year Run (continued)
EMS-HAP
Program
Batch File
Keyword
File Name
Data Source and Appendix D section
which provides more information
Area Source Processing
AreaPrep
TAFFILE
SCC2AMS
SIC2AMS
taff_hourly.txt
scc2ams.txt
sic2ams.txt
MACT2AMS mact2scc.txt
SURRXREF surrxref.txt
Area and Mobile Source Processing
AMProc
SAFFILE safl.safZ,...
TAFFILE
SURRXREF
HAPTABLE
EMISBINS
taff_hourly.txt
surrxref.txt
haptabl_point_area.txt
(direct emissions, area),
haptabl_onroad.txt (direct
emissions, onroad),
haptabl_nonroad.txt (direct
emissions, nonroad),
haptabl_precursor.txt
(precursor emissions)
am_grp.txt
CNTYUR
DECAY
popflg96.txt
indecay.txt
same as TAF in PtTemporal
same as SCCLINK in PtTemporal
same as SICLINK in PtTemporal
same as MACTLINK in PtTemporal
developed using CEP, EMS-95 and OTAQ
recommendations, see D.8
spatial allocation factors primarily from the
CEP. Tract-level urban/rural dispersion
parameters from the CEP. Urban/rural
county designations from 1990 and 1996
census data18 See D. 10
same as TAF under PtTemporal
same as SURRXREF under AMProc
same as MOBHAPS and PTHAPS under
PtAspenProc
based on our selection: we grouped all 'area
and other sources'** into group 1, all
nonroad mobile (including aircraft,
commercial marine and locomotives) into
group 3 and all onroad mobile into group 2.
based on 1990 and 1996 Census data18
same as DECAY under PtFinalFormat
* not applicable because PtDataProc requires the filenames given for these ancillary files
** 'area and other' includes both area sources based on Clean Air Act definition. 'Other' stationary sources are sources that
may be more appropriately addressed by other programs rather than through regulations developed under certain air toxics
provisions (sections 112 or 129) in the Clean Air Act. Examples of other stationary sources include wildfires and prescribed
burning whose emissions are being addressed through the burning policy agreed to by EPA and USDA.
D-12
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D.4 How We Developed the Airport Allocaiton Ancillary File (apt_allc)
The 1996 NTI and most other emissions inventories include emissions from airport takeoffs and
landings as county-level totals in the mobile source inventory. EMS-HAP uses an airport
allocation file (apt_allc) to apportion the county-level emissions to specific airport locations.
This file provides detailed location data (latitude and longitude) for all known airports in the
U.S., Puerto Rico and the Virgin Islands, as well as allocation factors for situations where more
than one airport is located in a particular county.
D.4.1 We assembled airport location data
We used data compiled by Gregory Rigamer and Associates to provide latitudes and longitudes
for about 18,000 airports in the U.S., Puerto Rico and the Virgin Islands." This database
includes both commercial and noncommercial airports. We made a few changes to this database
to correct errors we discovered when we initially ran the location quality assurance routine in
PtDataProc. The changes are listed below:
1. We changed the latitude and longitude of the Four Season's Airport in Reading, New York to
be consistent with the range of coordinates in Shuler county (the original coordinates were not
within Shuler county). The coordinates were changed from 42.40617750 latitude/ -77.96083611
longitude to 42.300278 latitude/ -76.876667 longitude.
2. We changed the county FIPS code of the Dahlgren Naval Surface Warfare Center from 199
(York County) to 099 (King George County) to be consistent with the locational coordinates.
D.4.2 We developed airport allocation factors
In developing allocation factors, we relied primarily on an FAA emplanement data set, which
provides information on the number of passengers carried in 1996 at approximately 2000
commercial airports in the U.S., Puerto Rico and the Virgin Islands.12
We developed an allocation factor to address situations where there are multiple airports in a
given county (since the inventory contains emission data at the county level). Where multiple
commercial airports were located in the same county, we assumed that the fraction of emissions
attributable to each airport in the county is the same as the fraction of passengers served by that
airport:
Passengers served by airport A
Allocation factor for airport A =
Total passengers served in the county
D-13
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We did not identify a source of activity data for noncommercial airports. In cases where
commercial and noncommercial airports were located in the same county, we assumed that all of
the emissions emanated from the commercial airports. We assumed this because commercial
airports tend to have both general aviation and commercial activity. For counties which contain
no commercial airports and multiple noncommercial airports, we divided any emissions equally
among the noncommercial airports.
We merged the location and emplanement databases using the common airport designation code.
D.5 How We Selected HAPs. Grouped/Partitioned Them, and Determined Their
Characteristics (HAP Table for HAPs)
For modeling the direct emissions of HAPs, we used three separate versions of the HAP table
pertaining to: (1) point and area sources, (2) onroad mobile sources, and (3) nonroad mobile
sources. Appendix A contains a complete listing of each of these files (Tables 1, 3 and 4). These
versions of the HAP table differ in two ways: 1) the apportionment of metal HAPs among the
fine and coarse particulate size classes, and 2) the apportionment of mercury among fine
particulate and non-reactive gas classes.
D.5.1 We assigned reactivity and particulate size classes
Reactivity and particulate size class information for each pollutant are assigned through the same
variable (REACT). The versions of the HAP tables supplied in Appendix A contain the REACT
variable and SAROAD codes for those HAPs selected for modeling and for a substantial number
of other pollutants reported in the 1996 NTI but not selected. The treatment of HAP reactivity in
EMS-HAP is based on the analytical framework developed in EPA's CEP.15 The reactivity and
particulate size class definitions and most assignments of chemical species to reactivity classes
were also taken from the CEP project. Those assignments that were not taken from the CEP
were because (1) the pollutant was not addressed in the CEP, (2) we had different degrees of
inventory information for determining coarse/fine particulate size class allocation, or (3) we
received recommendations from the EPA's Emission Measurement Center.19
Tables D-5 and D-6 show how we assigned particulate size class allocation factors to metal
compound classes. Except for diesel PM and mercury compounds, we computed allocation
factors for the metal compound classes based on averages from the CEP's 1990 emission
inventory.20 Diesel PM emissions splits were only used for Puerto Rico and Virgin Islands since
we received the data already speciated into coarse and fine diesel for the continental U.S. The
diesel PM splits in the onroad and nonroad HAP tables were based on recommendations from
EPA's Office of Transportation Air Quality (OTAQ).21'22
D-14
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Table D-5. Average Particulate Size Class Allocation Factors
Onroad
Antimony
Arsenic
Beryllium
Cadmium
Chromium
Cobalt
Lead
Manganese
Nickel
Selenium
Diesel PM
(Puerto Rico
and Virgin
Islands only)
coarse %
31
10
14
19
24
36
17
0
8
fine %
69
90
86
81
76
64
83
100
92
Nonroad
coarse %
63
17
61
62
20
10
12
21
51
11
8
fine %
37
83
39
38
80
90
88
79
49
89
92
Point and Area
coarse %
45
41
32
24
29
20
26
33
41
10
fine %
55
59
68
76
71
80
74
67
59
90
Table D-6. Gas and Particulate Allocations for Mercury Compounds
Reported as...
Onroad Nonroad Point and
Area
coarse % fine % gas % coarse % fine % gas % coarse % fine % gas %
Mercury &
Compounds
Mercuric
Chloride
Other Mercury
Species
(including
"elemental"
mercury)
0 100 0 0 100 0 0 0
0 100
0 0
•
100
0
100
As seen in Table D-6, we allocated mercury compound emissions to gaseous (reactivity class 1)
and fine particulate classes (reactivity class 2). Elemental mercury emissions were assigned to
the gaseous mercury group, because elemental mercury deposits relatively slowly, and mercuric
D-15
-------
chloride emissions were assigned to the fine particulate group, because this species deposits at a
moderate rate.23 All mercury emissions from mobile sources were assigned to paniculate
mercury group, since the EPA's OTAQ indicated that the factors used to estimate these
emissions originated from particulate measurements. All other species of mercury in the point
and area inventories, including the broad compound class 'mercury & compounds,' were
assigned to the gaseous group.
Based on recommendations from EPA's Emission Measurement Center19:
• All dioxins were assigned to the fine particulate class (reactivity class 2).
• All species grouped into 7-PAH or total POM were assigned to the fine particulate class
(class 2).
• Cyanide compounds were assigned to fine (class 2), coarse (class 3) and gaseous (class
1) groups in HAP table, depending on the particular cyanide species reported in the
inventory.
• Naphthalene was split 50/50 among fine and reactivity class 1, although when assigned
to total POM, it was modeled as all fine particulate.
D.5.2 We grouped HAP species belonging to HAP compound classes
The 1996 NTI contains approximately 400 different individual species representing the 188
HAPs. Many of the species (e.g., lead oxide) belong to compound classes. Grouping of these
species is necessary for many reasons. One reason is that the species belonging to HAP groups
may not be geographically consistent. For example, individual lead oxide emissions may have
been reported in some counties, whereas other counties aggregated their lead oxide emissions
into a group called "lead & compounds." Grouping allows for pollutants with similar
characteristics to be modeled together for purposes of efficiency. Proper grouping is essential for
assuring that the most accurate deposition and decay characteristics are assigned to HAPs
provided in the emission inventory.
The following subsections describe how we grouped pollutants in the 1996 NTI.
HAPs listed with their isomers
All HAPs that are listed in Section 112 of the Clean Air Act as both individual species and
compound classes including their isomers (e.g., xylenes, cresols) were modeled as a group that
included all individual isomers. For example, we aggregated emissions of o-xylene, p-xylene,
and m-xylene into the "xylene, including all isomers" group.
Grouping of Metal HAPs
With the exception of mercury compounds (discussed later), each metal HAP class was prepared
and modeled as two HAP groups: a fine particulate group of the metal HAP class (e.g.,
chromium compounds, fine particulate) and a coarse particulate group of the metal HAP class
(e.g., chromium compounds, coarse particulate). Because the inventory did not contain
•j •
D-16
-------
information on the participate size class of the metal species, we used the particulate size class
allocation factors shown in Table D-5, which were discussed earlier in Section D.5.1. Note that
these allocation factors are specific to the type of source (e.g., nonroad, onroad, and point and
area). Fine and coarse HAP groups account for differences in deposition characteristics between
fine and coarse particulate HAPs. However, they do not necessarily account for the differences
in toxicological characteristics among individual species in the metal group. Such differences
generally could not be accounted for due to the lack of speciated data for a great number of
sources. Because metals consisted of a fine and a coarse particulate group, the resulting modeled
concentrations were summed subsequent to ASPEN modeling to provide a single concentration
for each metal group.
We also applied a mass reduction factor, computed as the mass ratio of the moles of the metal in
the chemical compound to the entire chemical compound. We applied this factor to each specific
metal compound reported to adjust the mass emissions to the metal portion of the compound.
Such an adjustment is desirable in allowing comparison of the modeled concentrations to
monitored concentrations, because monitors generally measure only the metal portion of metal
compounds. In addition, the health data are often associated only with the absorbed mass of the
metal. For metals reported as diverse groups or compound classes, such as "alkylated lead," it
was assumed that the reported mass of the pollutant included only the metal portion; therefore, a
factor of 1.0 was used.
The compound class "mercury compounds" was also prepared and modeled as two different
HAP groups, and summed up to a single ambient mercury concentration after ASPEN modeling.
However, unlike the other metal compound classes grouped into fine and coarse particulate
groups, the two different HAP groups were gaseous mercury and fine particulate mercury, with
the splits described in Section D.5.1 (Table D-6).
Grouping ofPolycyclic Organic Matter (POM)
The grouping of POM provided a challenge due to the general lack of speciated data, the large
number of POM congeners and groups of congeners reported, and the uncertainty in the
definitions used. For example, the reported groups include 7-PAH, 16-PAH, "PAH, total" and
"total POM". The well-defined subgroups 7-PAH and 16-PAH, as shown in the first two
columns of Table D-7, have been used by EPA in the CAA 112(c)(6) emission inventory.24 The
groups "PAH, total" and "total POM" are less defined.
D-17
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Table D-7. 7-PAH and 16-PAH Subgroups,
and Additional Individual POM Compounds with Available Health Data
7-PAH
Benz(a)anthracene
Benzo(a)pyrene
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Chrysene .
Dibenz(a, h)anthracene
Indeno( 1 ,2,3-cd)pyrene
16-PAH
Benz(a)anthracene
Benzo(a)pyrene
Benzo(b)fluoranthene
Benzo(k)fluoranthene
Chrysene
Dibenz(a, h)anthracene
Indeno( 1 ,2,3-cd)pyrene
Acenaphthene
Acenaphthylene
Anthracene
Benzo(ghi)perylene
Fluoranthene
Fluorene
Naphthalene
Phenanthrene
Pyrene
POM Compounds (in addition
to 7 and 16-PAH) for which we
have cancer assessments
Carbazole
Dibenz[a,h]acridine
Dibenz[aj]acridine
7H-Dibenzo[c,g]carbazole
Dibenzo[a,e]pyrene
Dibenzo[a,i]pyrene
Dibenzofa,l]pyrene
7,1 2-Dimethylbenz[a]anthracene
1,6-Dinitropyrene
1,8-Dinitropyrene
3-Methylcholanthrene
5-Methylchrysene
5-Nitroacenaphthene
6-Nitrochrysene
2-Nitrofluorene
2-Nitrofluorene
1-Nitropyrene
4-Nitropyrene
D-18
-------
For processing the 1996 NTI, we chose to group POM species in two ways: (1) as 7-PAH, and
(2) as total POM. Modeling POM using these two groups allows us to bound the health risks for
POM. Table D-8 shows the HAP species reported in the inventory that were grouped as total
POM. As shown in the second column of this table, we excluded 7-PAH. This is because all 16-
PAH estimates already included the 7-PAH. If it had been included, it would have been double-
counted. We also excluded the dioxin/chlorinated furan species and subgroups because these
were grouped under the dioxins pollutant grouping (discussed later). Furthermore, we excluded
the individual species that are listed separately as HAPs other than naphthalene. Although they
structurally fit within the POM jgroup, they are generally not reported or assessed as POM. This
is because they are typically emitted separately rather than as part of POM mixtures and have
health benchmarks that are distinct from POM mixture components.
Table D-8. Grouping Scheme for Total POM
Included in the Total POM group
Excluded from the total POM group
16-PAH
Individual POM species (e.g., benzo-a-
pyrene, 1-methylnaphthalene, chrysene)
Naphthalene
"PAH, total"
Total POM
4 7-PAH
4 Individual POM species that are listed
separately as HAP (e.g., 2-
acetylaminofluorene) other than
naphthalene
4 Dioxin/ chlorinated furan species and
subgroups (e.g., pentachlorodibenzofuran)
Note that if the same stack contained emission estimates from more than one item in the first
column of the above table, then emissions from these items were summed together. For
example, if the same stack contained a "PAH, total" "POM," and naphthalene emissions, all
three were summed together.
The limitations resulting from the POM grouping scheme can be qualified based on the
assumptions made. For 7-PAH, the assumption was that if only "PAH, total" or "POM" were
reported from the stack, none of those groups contained any species that are part of 7-PAH. Thus
modeled 7-PAH concentrations may underestimate the actual concentrations/exposure estimates
in those cases where species in the 7-PAH group were included in the reported group. For total
POM, the modeling could overestimate the ambient concentration exposure estimates where all
species of POM are not mutually exclusive.
D-19
-------
Grouping of dioxins and chlorinatedfurans
Dioxin and chlorinated furan congeners (typically denoted by the single term "dioxin" or
"dioxins") are included in the CAA HAP list as 2,3,7,8 TCDD, and as part of the group "POM,"
but tend to be reported as dioxins. Individual congeners can have greatly varying toxicities. To
address this, an additional pollutant group that reflects the toxic equivalent quantity (TEQ) of the
individual species of dioxins and chlorinated furans is often used.25 This group is called 2,3,7,8-
TCDD TEQ. For risk characterization purposes, the ideal way to group the dioxins and
chlorinated furans would be to use this 2,3,7,8-TCDD TEQ convention.
We used the FACTOR variable in the HAP table to convert individual species of dioxins and
chlorinated furans into 2,3,7,8-TCDD TEQ. We set this variable to the appropriate toxic
equivalency factor (TEF) to the emissions of the individual species. We used the I-TEFs from
the early 90's because these are the factors built into the 1996 NTI for estimating TEQ. EMS-
HAP multiplies the emissions by the TEF, thereby converting them to 2,3,7,8-TCDD TEQ.
Difficulties arise in handling those pollutant subgroups that cannot be directly converted to TEQ
because the amount of the individual species they contain is not known. Table D-9 shows the
specific subgroups in the NTI that cannot be directly converted into 2,3,7,8-TCDD TEQ. To
address the uncertainty resulting from the unspeciated reporting of dioxin and chlorinated furan
HAP groups in the inventory, we chose to create two separate pollutant groups to model dioxins.
One group reflects an upper bound estimate of TEQ, and the second reflects a lower bound
estimate. Where specific congeners in the NTI were known, we used the appropriate TEF, and
included the congener in both the upper and lower bound TEQ group. Where specific congener
identities were not known we used the maximum value of the TEF for the mixture for the upper
bound group, and zero for the lower bound group.
D-20
-------
Table D-9. Species, Groups and Subgroups of Dioxins Reported in the 1996 NTI
Could be converted to TEQ (or is already TEQ)
Could not be converted to TEQ
2,3,7,8-Tetrachlorodibenzo-p-dioxin
1,2,3,7,8,9-hexachlorodibenzo-p-dioxin
Pentachlorodibenzo-p-dioxin (estimates by EPA's
Emission Measurement Center that 1,2,3,7,8-
Pentachlorodibenzo dioxin constitutes ~ 10% of
total Pentachlorodibenzo dioxins26)
Pentachlorodibenzofuran (estimates by EPA's
Emission Measurement Center that
1,2,3,7,8-pentachlorodibenzofuran constitutes -9%
of total Pentachlorodibenzo furans and that
2,3,4,7,8-pentachlorodibenzofuran constitutes ~9%
of total Pentachlorodibenzo furans26)
Octachlorodibenzo-p-dioxin
Octachlorodibenzo furan
1,2,3,4,7,8-hexachlorodibenzo-p-dioxin
1,2,3,7,8-Pentachlorodibenzo-p-dioxin
2,3,7,8-Tetrachlorodibenzo furan
1,2,3,4,7,8,9-heptachlorodibenzofuran
2,3,4,7,8-pentachlorodibenzo furan
1,2,3,7,8-pentachlorodibenzo furan
1,2,3,6,7,8-hexachlorodibenzo furan
1,2,3,6,7,8-hexachlorodibenzo-p-dioxin
2,3,7,8-TCDD TEQ
2,3,4,6,7,8-hexachlorodibenzo furan
1,2,3,4,6,7,8-heptachlorodibenzofuran
1,2,3,4,7,8-hexachlorodibenzo furan
1,2,3,7,8,9-hexachlorodibenzo furan
Dioxins/Furans as TEQ
• Dioxins
• 1,2,3,4,6,7,8-heptachlorodibenzo-p-dio
xin
• Dibenzofurans (chlorinated) {PCDFs}
• Dioxins, total, w/o individual, isomers
reported
• Hexachlorodibenzo-p-dioxin
• Polychlorinated dibenzo-p-dioxin, total
• Polychlorinated dibenzofurans, total
D-21
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D.6 How We Selected the HAP Precursors, Grouped/Partitioned Them, and Determined
Their Characteristics (HAP Table for Precursors)
The CEP identified HAPs for which secondary formation may account for a significant portion
of ambient concentrations. We've prepared the HAP table for ASPEN modeling of the
secondary formation of formaldehyde, acetaldehyde, propionaldehyde, acrolein, methyl ethyl
ketone, phosgene and cresol. Table D-10 shows the precursors for these HAPs. Appendix A,
Table 2, shows a complete listing of the precursor HAP table we used for preparing the ASPEN
input files for the 1996 national assessment. You will see (by looking at the KEEP variable) that
we modeled formaldehyde, acetaldehyde, propionaldehyde, and acrolein in this assessment.
The treatment of secondary HAP formation in EMS-HAP is based on the analytical framework
developed in EPA's CEP.27 The approach makes use of pollutant decay calculations performed
in ASPEN. Each precursor species is modeled in ASPEN with and without reactive decay. The
difference between the precursor concentrations modeled with no decay and with reactive decay
reflects the amount of the precursor species converted to secondary pollutants and other products,
such as carbon dioxide. Because any given pollutant may transform into a number of other
species, some of which are HAPs and some of which are not, a molar yield factor is applied to
the difference to account for the typical HAP yield when a molecule of precursor degrades.
Because of the proportional relationship between emissions and modeled concentrations, the
molar yield factor, adjusted by a molecular weight factor to convert from moles to mass, can be
applied to precursor mass emissions in EMS-HAP.
We can also apply a reaction rate factor to adjust the reactivities of species which are precursors
to the same HAP to the same reactivity class. This allows us to group a large number of species
that are precursors to the same HAP into a single precursor group. We developed the precursor
HAP table to perform this grouping process for all precursors except for phosgene and acrolein,
since they do not have a large number of precursors. Note that in Table D-10 the reaction rate
factor for these species is 1.
Table D-10 shows the molar yield factor, the molecular weight adjustment factor and the reaction
rate factor for each species. The molar yields and reaction rates were those used in the CEP.27
The overall scaling factor (the three factors multiplied together) is the FACTOR variable in the
precursor HAP table.
D-22
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Table D-10. Scaling Factors for HAP Precursors
HAP
Formaldehyde
Acetaldehyde
Propionaldehyde
Methyl ethyl ketone
Acrolein
Cresol
Phosgene
Precursors
Ethene
Propene
1-butene
1 -pentene
1-hexene
1-heptene
1-octene
1-nonene
1-decene
Isobutene (or 2-methylpropene)
2-methyl- 1-butene
1,3-butadiene
3-methyl- 1 -butene
3-methyl- 1 -pentene
2,3-dimethyl-l -butene
Isoprene
2-ethyl- 1-butene
2-methyl- 1 -pentene
4-methyl-l -pentene
2,4,4-trimethyl- 1 -pentene
Acetaldehyde
Methyl-t-butyl ether
Methanol
Propene
2-butene
2-pentene
2-hexene
2-heptene
2-octene
2-nonene
2-methyl-2-butene
3-methyl-2-pentene
4-methyl-2-pentene
Ethanol
1-butene
2-pentene
3-hexene
2-methyl- 1-butene
Butane
Isopentane
3-methylpentane
1 ,3-butadiene
Toluene
Methylene chloride
Trichloroethylene
Tetrachloroethylene
Vinvlidene chloride
Reaction
Molar rate
yield factor
.6 I
„
0.67 :
1
1
3.3
.6
.6
.6
.6
.6
1 1
1 1.6
1 0.5
0.42 0.1
1 0.03
1 0.5
2
1
1
1
1
1
1 .5
1.5
1
0.05
0.5
1
2 1
1 1
0.03
0.03
0.03
1
1
1
1
1
1
Molecular
weight
factor
1.07
0.71
0.54-
0.43
0.36
0.31
0.27
0.24
0.21
0.54
0.43
0.56
0.43
' 0.36
0.36
0.44
0.36
0.36
0.36
0.27
0.68
0.34
0.94
1.05
0.79
0.63
0.52
0.45
0.39
0.63
0.63
0.52
0.52
0.96
1.04
0.83
0.69
0.86
1.03
0.83
0.71
1.04
1.20
1.16
0.83
0.64
1.02
Overall
scaling
factor
0.51
0.71
0.54
0.43
0.36
0.31
0.27
0.24
0.21
0.86
0.69
1.11
0.43
0.36
0.57
0.89
0.57
0.57
0.36
0.43
0.34
0.01
0.03
0.52
1.57
0.63
0.52
0.45
0.39
0.63
0.94
0.79
0.52
0.05
0.52
0.83
1.38
0.86
0.03
0.03
0.02
1.04
1.20
1.16
0.83
0.64
1.02
D-23
-------
The structure of the precursor HAP table used in processing both point and area precursor
inventories is the same as the point and area HAP table discussed in Section D.5 and in Section
4.2.3. A full listing of the precursor HAP table is provided in Appendix A, Table 2. The
precursor HAP table includes two sets of records for each precursor to be modeled. One set
reflects the reactivity class that is appropriate to the precursor, and the other reflects the reactivity
class of 1 (non-reactive or inert). The only exception to this is the precursor for acrolein, which
is 1,3 butadiene. Because 1,3 butadiene is already in the HAP tables for the direct emissions of
HAPs, the precursor HAP table contains only non-reactive 1,3 butadiene.
Note that the reactive and non-reactive precursor species have separate SAROAD codes. For
example, for formaldehyde precursor there is a set of records for formaldehyde precursor reactive
(reactivity class 6, SAROAD=80180), and a set for formaldehyde precursor, inert (reactivity
class 1, SAROAD=80303). The number of records in the set depends on how many specific
VOCs or HAPs having the same reactivity class are involved in the formation of the HAP. For
formaldehyde precursor, for example, there are twenty-two species. As stated earlier, the
FACTOR variable for each species was set to the overall scaling factor in Table D-10.
Where one pollutant is a precursor of two HAPs, as in the case of 1-butene (which is a precursor
of formaldehyde and propionaldehyde), four records are needed in HAP table, two for each HAP
that the precursor produces.
D.7 How We Developed the Temporal Allocation Factors File (taff_hourly.txt)
EMS-HAP uses the same ancillary input file, taff_hourly.txt, to temporally allocate point, area
and mobile sources. This file contains temporal allocation factors (TAFs) that provide the hourly
variation of emissions in an annually-averaged day based on the source category. Local time
zones are used. For each source category, there are 24 TAFs; each TAF represents an activity
level for each hour in the day. These activities sum to 1. In developing the temporal profiles for
EMS-HAP, we reviewed available temporal allocation data developed under previous modeling
efforts. These included:
• A temporal allocation database maintained by EPA's Office of Research and
Development (ORD). This database was originally developed for regional
emission modeling studies under the National Acid Precipitation Assessment
Program (NAPAP),28 and was updated to improve allocation factors for point
sources in 1995.29
• Temporal allocation profiles used in EMS-95 for regional and local ozone
modeling.30
D-24
-------
• Temporal allocation profiles used in the emission processing system (EPS) for the
Urban Airshed Model (UAM) of ozone.31 These factors were also used in the
CEP.
We used the database developed by ORD as a starting point, because it is the most complete
database and its development is documented in an EPA report.28
We made some changes and additions to the data as follows:
1. The ORD temporal database actually contains hourly temporal allocation factors for specific
seasons and day-of-week classes (weekday, Saturday, and Sunday). In the EMS-HAP TAP
file, we consolidated the seasonal and day-of-week information to produce a set of factors
that reflect hourly emissions activity on an annual average. To do this, we averaged the
hourly activity factors for different days and seasons, weighted by weekly and seasonal
activity patterns. Equation D-l was used:
HFn = 13 x £..M [(WHFn/i x WDF, x 5) + (SaHF^ x SaDF,) + (SuHFn/i x SuDF()] x SFS
where (eq. D-l)
HFn = average fraction of daily emissions occurring in hour "n"
subscript i ranges from 1 to 4, denoting the season
WHFn/i = fraction of daily emissions in hour "n" on weekdays in season "i"
WDFj = fraction of emissions in season "i" occurring on a typical weekday
SaHFn/i = fraction of daily emissions in hour "n" on Saturdays in season "i"
SaDF, = fraction of emissions in season "i" occurring on a typical Saturday
SuHFn/, = fraction of daily emissions in hour "n" on Sundays in season "i"
SuDFj = fraction of emissions in season "i" occurring on a typical Sunday
SF, = fraction of annual emissions occurring in season "i"
5 = 5 weekdays per week
13= 13 weeks per average season
D-25
-------
2. For highway gasoline vehicles, the NTI emissions inventory provides aggregated emissions
estimates for the entire category, while the ORD database treats different road classes separately.
In order to handle the aggregated highway vehicle category in the NTI, we developed a
composite temporal profile by taking the average of three separate ORD profiles for rural, urban,
and interstate roadways. The following equation was used:
HFn/compos,,c = (HFn/imerstate + HFn/urban + HF./nml)/3 (eq. D-2)
where
n= hour of the day
HFn = fraction of daily emissions occurring in hour n
3. Light duty diesel vehicles were not specifically addressed in the ORD temporal database. We
assumed that they have a similar profile to heavy-duty diesels. (A second option would have
been to use the gasoline vehicle profile. However, the diesel and gasoline profiles were
believed to be fundamentally different because of increased evaporative emissions from
gasoline vehicles in the afternoon.)
4. EPA's Office of Transportation and Air Quality (OTAQ) provided new information that we
used to develop a new temporal profile for commercial aircraft landings and takeoffs.32
5. For source categories in the emissions inventories processed which are not in the ORD
database, but were in the speciated NET inventory, we assigned profiles from similar
categories. Table D-l 1 shows the new profiles we assigned. Note that we chose not to assign
a profile for Industrial Equipment, Other Oil Field Equipment. As a result, AMProc
assigned this source category a uniform temporal profile (the default).
All highway and nonroad profiles were reviewed with OTAQ prior to the selection of temporal
profiles for EMS-HAP. A few of the area and all of the mobile source profiles selected for
EMS-HAP are summarized in Tables D-l2 and D-l3 respectively. Figure D-l shows the ORD
temporal profiles for the three separate roadway classes, and the composite profile developed for
gasoline highway vehicles in EMS-HAP. Figure D-2 shows temporal profiles used in EMS-HAP
for diesel highway vehicles and nonroad vehicles.
D-26
-------
Table D-ll. Additions to the ORD Temporal Profile Database
New
AMS code
2260004016
2260004021
2260004026
2260004031
2260004071
2265003070
2265004011
2265004016
2265004026
2265004031
2265004041
2265004046
2265004051
2265004056
2265004066
2265004071
2265004076
2265005060
2265010010
2270003070
2270004036
2270004041
2270004046
2270004056
2270004066
•' 2270004071
1 2270005060
2270010010
Description
2-stroke, Lawn and Garden Equipment, Rotary Tillers < 6 HP (Commercial)
2-stroke, Lawn and Garden Equipment, Chain Saws < 6 HP (Commercial)
2-stroke, Lawn and Garden Equipment,Trimmers/Edgers/Brush Cutters (Commercial)
2-stroke, Lawn and Garden Equipment, Leafblowers/Vacuums (Commercial)
2-stroke, Lawn and Garden Equipment, Turf Equipment (Commercial)
4-stroke, industrial equipment, (AC/Refrigerator)
4-stroke, lawn & garden equipment, Lawn Mowers (Commercial)
4-stroke, lawn & garden equipment, Rotary Tillers < 6 HP (Commercial)
4-stroke, lawn & garden equipment, Trimmers/Edgers/Brush Cutters (Commercial)
4-stroke, lawn & garden equipment Leafblowers/Vacuums (Commercial)
4-stroke, lawn & garden equipment, Rear Engine Riding Mowers (Commercial)
4-stroke, lawn & garden equipment, Front Mowers (Commercial)
4-stroke, lawn & garden equipment, Shredders < 6 HP (Commercial)
4-stroke, lawn & garden equipment, Lawn and Garden Tractors (Commercial)
4-stroke, lawn & garden equipment, Chippers/Stump Grinders (Commercial)
4-stroke, lawn & garden equipment, Turf Equipment (Commercial)
4-stroke, lawn & garden equipment, Other Lawn and Garden Equipment (Commercial)
4-Stroke, Farm Equipment (Irrigation Sets)
4-stroke, industrial equipment, other oil field equipment
industrial equipment (AC/Refrigeration)
lawn & garden equipment, Snowblowers (Commercial)
lawn & garden equipment, Rear Engine Riding Mowers (Commercial)
lawn & garden equipment, Front Mowers (Commercial)
lawn & garden equipment, Lawn and Garden Tractors (Commercial)
lawn & garden equipment, Chippers/Stump Grinders (Commercial)
lawn & garden equipment, Turf Equipment (Commercial)
Agricultural equipment (Other Agricultural Equipment)
Industrial Equipment, Other Oil Field Equipment
Existing
AMS w/ TAP
2260004015
2260004020
2260004025
2260004030
2260004070
2265003060
2265004010
2265004015
2265004025
2265004030
2265004040
2265004045
2265004050
2265004055
2265004065
2265004070
2265004075
2265005050
Existing
Description
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Terminal Tractors)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Comme'cial)
(Hydro-power Units)
No data on this AMS code added to database
2270003060
2270004035
2270004040
2270004045
2270004055
2270004065
2270004070
2270005055
(Terminal Tractors)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Commercial)
(Irrigation Sets)
No data on this AMS code added to database
D-27
-------
Table D-12. Temporal Allocation of Some Area Source Categories in EMS-HAP
NTI Area Source Category
Instl/Comm. Heating: Distillate Oil
Instl/Comm. Heating: Residual Oil
Instl/Comm. Heating: Natural Gas
Residential Heating: Anthracite Coal
Residential Heat.: Bituminous/Lignite
Residential Heating: Distillate Oil
Residential Heating: Natural Gas
Res, Heat.: Wood/Wood Residue
Surface Coatings: Architectural
Autobody Refinishing Painting
Surface Coatings: Traffic Markings
Industrial Maintenance Coatings
Dry Cleaning (Petroleum Solvent)
Asphalt Paving: Cutback Asphalt
Pesticide Application
Consumer Products Usage
Aviation Gas Distribution: Stage I&II
Gasoline Distribution Stage II
Open Burning: Scrap Tires
Landfills, all types
Structure Fires
Hospital Sterilizers
Human Cremation
Animal Cremation
Foo'd & Agricultural: Cotton Ginning
AMS code
21-03-004
21-03-005
21-03-006
21-04-001
21-04-002
21-04-004
21-04-006
21-04-008
24-01-001
24-01-005
24-01-008
24-01-100
24-20-000
24-61-021
24-61-000
24-60-000
25-61-000
25-01-060-100
28-30-000
26-20-000
28-10-030
28-50-000-100
na
na
na
EMS-95 Hourly Profile
Code
25
25
25
25
25
25
25
25
25
25
24
na
25
24
24
25
na
na
na
Brief description
8-hour day, with
ramped beginning
and end
see above
see above
see above
see above
see above
see above
see above
see above
see above
uniform 24-hour
na
see above
uniform 24-hour
uniform 24-hour
see above
na
na
na
CEP Hourly Profile
Code
37
33
12
12
12
16
16
12
40
16
24
na
54
54
24
na
na
na
na
Brief description
very low 3-6a,
moderate 6-9a and
6-9p, peak 9a-6p
bimodal -
morning/evening
flat 6a to 6p
see above
see above
low 6-9a, high 9a-
midnight
see above
see above
3a-6p, peak 6a-
noon
see above
uniform 24-hour
na
6a-midnight, peak
9a-9p
see above
uniform 24-hour
na
na
na
na
NAPAP Temporal
Profile
~2.5%/hr 1 lpm-7am,
5.5%/hr 7am-4pm,
4.4%/hr4-llpm
Roughly sinusoidal,
peaking at ~6.3%/hr at
6am, lowest at ~2%/hr at
5pm
flat 6a-8p, 0 at night
flat 7a-4p, 0 at night
uniform 24 hours
-6.9%/hr 7am-6pm,
~1.9%/hr at night
flat 7a-6p, 0 at night
same as industrial
maintenance coatings
uniform 24-hour
na
flat 5a-8p, 0 at night
uniform 24-hour
uniform 24-hour
uniform 24-hour
na
na
na
EMS-HAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
NAPAP
16 hour day
NAPAP
NAPAP
NAPAP
NAPAP
8 hour day
8 hour day
8 hour day
na - not available
D-28
-------
Table D-13. Temporal Allocation of Mobile Source Categories in EMS-HAP
NTI Mobile
Source
Category
Subcategories,
where
applicable*
Light Duty Gasoline Vehicles
(LDGV)
Light Duty Gasoline Trucks
(LDGT)
Heavy Duty Gasoline Vehicles
(HDGV)
Motorcycles (MC>
Light Duty Diesel Vehicles
(LDDV)
Light Duty Diesel Trucks
(LDDT)
Heavy Duty Diesel Vehicles
(HDDV)
All
Off-highway
Vehicle:
Gasoline,
2-Stroke
.1
4
All
Recreational
Construction
Industrial
Lawn & garden
Farm equipment
Light
commercial
Logging
Airport service
AMS code
A2201001
A2201060
A2201070
A2201080
A2230001
A2230060
A2230070
A2260000
A2260001
A2260002
A2260003
A2260004
A2260005
A2260006
A2260007
A2260008
EMS-95 Hourly Profile
Code
not
appl.
25
Description
VMT and emission
factor both undergo
allocation, with the
combined result
reflected in the final
emission file
8-hour day, with
ramped start and end
CEP Hourly Profile
Code
not
appl.
Description
Exhaust and evaporative
are allocated separately
See detailed list below
37
61
62
63
64
24
63
24
very low 3-6am, moderate
6-9am & 6-9pm, peak
9am-6pm
24 hours, higher activity
6-9am & 6-9pm, highest
6am-6pm
Similar to profile 61, less
pronounced peak
Highest 9am-6pm, less 6-
9pm
Highest 9am-9pm, less 6-
9am, very little 9pm-
midnight
Uniform 24 hours
Highest 9am-6pm, less 6-
9pm
Uniform 24 hours
NAPAP Temporal Allocation
File
Composite of evaporative and
exhaust (varies depending on
road-type)
not addressed
not addressed
Near uniform 6am-6pm, with
break at noon, low at night
Ramps up 6-9am, uniform from
9-am-6pm
EMS-HAP
Average of the NAPAP
composite profiles for various
road-types
NAPAP HDDV profile
same as above
same as above
NAPAP profile
D-29
-------
Table D-13. Temporal Allocation of Mobile Source Categories in EMS-HAP (continued)
NTI Mobile
Source
Category
All
Off-highway
Vehicle:
Gasoline,
4-Stroke
All
Off-highway
Vehicle:
Diesel
Subcategories,
where
applicable1*
Same as for
2-stroke engines
Same as for
2-stroke engines
All Aircraft Types and
Operations
Marine Vessels, Commercial
Railroads-Diesel
AMS code
A2265000
A2270000
A2275000
A2280
A2285002
EMS-95 Hourly Profile
Code
25
25
25
24
20
Description
See above
See above
See above
Uniform 24 hours
Uniform 3am- 1 1pm
CEP Hourly Profile
Code
Description
Same as for 2-stroke engines
Same as for 2-stroke engines
24
not
appl.
65
Uniform 24 hours
CEP included pleasure
craft, only
Similar to profile 62, less
pronounced peak
NAPAP Temporal Allocation
File
Same as for 2-stroke engines
High activity 6am-6pm, low
activity 6pm-midnight
Varies depending on aircraft
type, commercial is uniformly
high 6am-midnight with very low
activity midnight-6am
Varies depending on fuel, diesel
is uniformly high 6am-6pm,
dropping to 1/3 that level from
6pm-6am
Roughly the same as diesel ships
EMS-HAP
Same as above
NAPAP profile
Newly derived profile based on
take-off and landing data on
major airports
NAPAP diesel profile
NAPAP profile
"For some of the NTI emission categories,
the subcategories are listed individually.
the temporal allocation factors used in EMS-95 and the CEP varied among different subcategories. Where this occurs,
D-30
-------
0.08
0.07
0.06
0.05
o 0.04
re
0.03
0.02
0.01
0
0
o
A °
r A^
A
.'A
/
£ 9
G ,'" A
° ' -O_ ^ . £>'
'i~'-^'-" J ' •-'-
, , I . i 1 i | 1
A A"'
A, "A "* o
,-'o o o
V
Composite
A Rural
A Urban
0 Interstate
, . 1 i . i
A
,* n 'f 4
ft 0
D
'i
\
\
4
A
9 12 15
Hour of the day
18
21
24
Figure D-1. Composite temporal emission profile for on-road motor vehicles
D-31
-------
Diesel highway vehicles
Hour of the day
Commercial Aircraft
9 12 15
Hour of the day
18
21
24
Off-
0.1
0.09
& 0.08
> 0.07
8 0.06
o 0.05
§ 0.04
o 0.03
i 0.02
0.01
0
Highway Vehicles and Equipment
^AA-AAAA-AA
I /' ' '1
1 J 1
I / »
IA
J — Diesel
/I -A- Gasoline
*
^
I
I
I
. . * , J. f. Jf . . 1 . . | , . 1 . , , A ,Al».A, A
9 3 6 9 12 15
Hour of the day
18 21 24
Railroads and marine vessels
0.07
0.02
9 12 15
Hour of the day
Figure D-2. Temporal profiles for diesel highway vehicles and non-road engines
D-32
-------
D.8 How We Assigned Spatial Surrogates for Area and Mobile Source Categories
This section discusses how we selected spatial surrogates. We selected from the list of available
surrogates presented in 8.1.1 and again in Table D-17. We discuss the availability of surrogate
data in D.10. This section discusses our selections within the available choices.
As discussed in Chapters 8 and 10, EMS-HAP uses four files for spatial surrogate assignment.
In addition to the three cross-reference files, scc2ams.txt, sic2ams.txt and mact2scc.txt, EMS-
HAP uses a file named surrxref.text, which links AMS codes to surrogate assignments. For
mobile sources, this is the only file used to assign surrogates. For area sources, surrxref.txt is
used only when a surrogate was not already assigned by MACT, SIC, or SCC codes. (AMS is at
the bottom of the assignment hierarchy for area sources.)
To select spatial surrogates for the various emission categories in the area source component of
the 1996 NTI, we drew on spatial surrogate assignments used in previous modeling efforts. In
particular, we reviewed the assignments used in the CEP and in the EMS-95 emission modeling
system. The assignments used in CEP are generally the same as those used in the Emission
Processing System (EPS) for the Urban Airshed Model (UAM-V). EMS-95 is also used with
UAM-V, and has been used extensively in regional ozone modeling. We also examined the
development of the area source estimates in the 1996 NTI. Where they included county-level
estimates allocated from national and state level estimates, we examined the methodology used
to allocate to the county level. In addition, we drew upon our own judgement.
For mobile source emissions categories, we obtained recommendations on spatial allocation from
EPA's Office of Transportation and Air Quality (OTAQ).
Table D-14 compares the spatial surrogates used in EMS-HAP, the CEP, and EMS-95 for some
of the area source categories in the NTI. Table D-15 shows the surrogates we chose for all of the
area sources in the 1996 NTI, and the code by which they were matched to surrogates. Table D-
16 shows the surrogates we chose for the sources in the 1996 diesel PM inventory. Table D-17
compares spatial surrogates used in EMS-HAP, the CEP, and EMS-95 for onroad and nonroad
mobile source categories in the 1996 NTI.
D-33
-------
Table D-14. Spatial Allocation of Some Area Source Categories in EMS-HAP as Compared to Other Emission Models
NTI Area Source Category
Institutional/Commercial Heating: Distillate Oil Combustion
Institutional/Commercial Heating:: Residual Oil Combustion
Institutional/Commercial Heating:: Natural Gas Combustion
Residential Heating: Anthracite Coal
Residential Heating: Bituminous and Lignite Coal
Residential Heating: Distillate Oil
Residential Heating: Natural Gas
Residential Heating: Wood/Wood Residue
Surface Coatings: Architectural
Surface Coatings: Traffic Markings
Industrial Maintenance Coatings
Dry Cleaning (Petroleum Solvent)
Asphalt Paving: Cutback Asphalt
Consumer Products Usage
Aviation Gasoline Distribution: Stage I & II
Gasoline Distribution Stage II
Open Burning: Scrap Tires
Landfills, all types
Structure Fires
Hospital Sterilizers
Human Cremation
Animal Cremation
Food and Agricultural Products: Cotton Ginning
AMS code
21-03-004
21-03-005
21-03-006
21-04-001
21-04-002
21-04-004
21-04-006
21-04-008
24-01-001
24-01-008
24-01-100
24-20-000
24-61-021
24-60-000
25-61-000
25-01-060
28-30-000
26-20-000
28-10-030
28-50-000
na
na
na
EMS-95 Spatial Profile
Code
8
8
8
4
4
4
4
8
8
8
8
8
8
8
8
na
5
5
4
8
na
na
na
Description
Population
Population
Population
Housing
Housing
Housing
Housing
Population
Population
Population
Population
Population
Population
Population
Population
na
Inverse housing
Inverse housing or
Population
Housing
Population
na
na
na
CEP Spatial Profile
Code
2
2
2
20
20
20
20
20
20
3
3
3
22
20
22
na
19
19
20
na
na
na
na
Description
Commercial land
Commercial land
Commercial land
Population
Population
Population
Population
Population
Population
Industrial land
Industrial land
Industrial land
All roadways
Population
Roadway miles
na
Inverse population
density
Inverse population
density
Population
na
na
na
na
EMS-HAP
Code
2
2
2
20
20
20
20
20
20
22
3
20
22
20
20
20
19
19
20
2
2
19
7
Commercial land
Commercial land
Commercial land
Population
Population
Population
Population
Population
Population
Roadway miles
Industrial land
Population
Roadway miles
Population
Population
Population
Inverse population
density
inverse population
density
Population
Commercial land
Commercial land
Inverse population
density
Tarmland
na = not available
D-34
-------
Table D-15. Surrogates Used for Spatial Allocation of the 1996 NTI Area Source Inventory
Surrogate
name (and
code)
Population (20)
Residential land
(1)
Inverse
population
density (18)
Inverse
population
density (19)
Roadway miles
(22)
Farm land (7)
Farmland plus
orchard land (29)
Forest land (13)
Utility land (4)
Commercial land
plus industrial
land (6)
Commercial land
(2)
•1
t
Definition
U.S. Census category: 1990 residential population
USGS land use categories: Residential, plus one-
third of mixed urban and built-up land plus one-
third of other urban and built-up land
Inverse of: census tract population (category 20)
divided by census tract area. Tracts with zero
population assigned a SAP of zero.
Inverse of: census tract population (category 20)
divided by census tract area. Tracts with zero
population assigned tract population of one.
Total miles of all roadway types in each census
tract, as reported in TIGER/Line
USOS land use category: cropland and pasture
USGS land use categories: cropland and pasture,
plus orchards, groves, vineyards, nurseries, and
ornamental horticultural areas
USGS land use categories: deciduous forest plus
evergreen forest plus mixed forest land
USGS land use category: transportation,
communications, and utilities
Sum of commercial land and industrial land, as
defined below
•USGS land use categories: Commercial and
services, plus one-half of industrial and
commercial complexes, plus one-third of mixed
urban and built-up land plus one-third of other
urban and built-up land
Emissions inventory categories
Business Services (SIC), Consumer Products Usage (AMS), Fuel Use (AMS), Grocery Stores (SIC), Investors (SIC), Lamp
Breakage (AMS), Paper Hanging (SIC), Perchloroethylene Dry Cleaning (AMS), Residential Heating (AMS), Structure Fires
(AMS), Surface Coatings: Architectural (AMS), Swimming Pools (AMS), Water Supply (SIC)
Residential Open Burning (AMS)
Construction (AMS)
Air and Water Resource and Solid Waste Mgmt. (SIC), Correctional Institutions (SIC), Crude Petroleum and Natural Gas
(SIC), Geothermal Power (SCC), Hazardous TSDF (SCC), Hazardous Waste Incineration (SCC), Institutional/Commercial
Heating: POTW Gas (AMS), Landfills (excluding Gas Flares) (AMS), Medical Waste Incineration (SCC), Municipal
Landfills (AMS), Municipal Waste Combustors (MACT), Oil and Natural Gas Production (MACT), Open Burning: Scrap
Tires (AMS), Publicly Owned Treatment Works (POTWs) (AMS), Refuse Systems (SIC), Sewerage Systems (AMS), Space
Research and Technology (SIC), Treatment, Storage, Disposal Facilities (AMS),
Asphalt Paving: Cutback and Emulsified (AMS), Motor Vehicle Fires (AMS), Surface Coatings: Traffic Markings (AMS)
Food and Agricultural Products: Cotton Gin (SCC)
Agricultural Field Burning: Open, propane, (AMS), Agricultural Production (AMS), Paved Road Dust (AMS), Pesticide
Application (AMS), Soil Dust (AMS), Unpaved Road Dust (AMS)
Open Burning: Forest and Wildfires (AMS), Open Burning: Prescribed Burnings (AMS)
Aviation Gas Distribution (AMS)
Bankbooks and Looseleaf Binders (SIC), Book Printing (SIC), Bookbinding And Related Work (SIC), Cold Cleaning (Misc.)
(AMS), Commercial Printing (SIC), Commercial Sterilization Facilities (MACT), Graphic Arts (AMS), Halogenated Solvent
Cleaners (SCC), Jewelers' Materials & Lapidary Work (SIC), Non-halogenated solvent cleaning (AMS), Paint Stripping
Operations (SCC), Platemaking Services (SIC), Printing/Publishing (Surface Coating) (SCC), Roasted Coffee (SIC),
Stationary Internal Combustion Engines - D (MACT) .
Animal Cremation (SCC), Autobody Refinishing Paint Application (AMS), Commercial Physical Research (SIC),
Commercial: Asphalt Roofing (AMS), Dental Equipmient and Supplies (SIC), Dental Preparation and Use (SCC), Dry
Cleaning (Petroleum Solvent) (SCC), Engineering Services (SIC), Gas Dispensing (MACT), Gasoline Distribution Stage I
(MACT), Gasoline Distribution Stage II (AMS), Gasoline Trucks in Transit (SIC), General Laboratory Activities (SCC),
Hospital Sterilizers (AMS), Human Cremation (SCC), Institutional/Commercial Heating (AMS), National Security (SIC),
Noncommercial Research Organizations (SIC), Top & Body Repair & Paint Shops (SIC)
D-35
-------
Table D-15. Surrogates Used for Spatial Allocation of the 1996 NTI Area Source Inventory (continued)
Surrogate name
(and code)
Definition
Emissions inventory categories
Industrial land (3)
USGS land use categories: industrial, plus
one-half of industrial and commercial
complexes, plus one-third of mixed urban and
built-up land, plus one-third of other urban
and built-up land
Adhesives and Sealants (SIC), Aerospace Industries (AMS), Agricultural Chemicals and Pesticides (SIC), Air and Gas
Compressors (SIC), Alkalies And Chlorine (SIC), Aluminum (SIC), Analytical Instruments (SIC), Animal And Marine Fats
And Oils (SIC), Apparel and Accessories (SIC), Appliances & Heat Equipment Coating (SIC), Architectural Metal Work
(SIC), Asbestos Products Mfg. (SIC), Asphalt Concrete Mfg. (SCC), Asphalt Roofing Mfg. (SCC), Automatic Vending
Machines (SIC), Automotive and Apparel Trimmings (SIC), Automotive stampings (SIC), Ball and Roller Bearings Mfg.
(SIC), Beet Sugar (SIC), Biological Products (SIC), Blowers and Fans (SIC), Boat Building and Repairing (SIC), Boat
Mfg. (SCC), Bolts, Nuts, Rivets and Washers (SIC), Bottled and Canned Soft Drinks (SIC), Brass, Bronze, Copper, Copper
Base Alloy (SIC), Brick and Structural Clay Tile (SIC), Brooms and Brushes (SIC), Building Paper and Building Board
Mills (SIC), Burial Caskets (SIC), Cane Sugar Refining (SIC), Canned Fruits and Vegetables (SIC), Carbon Black (SIC),
Carbon and Graphite Products (SIC), Carburetors, Pistons, Rings and Valves Mfg. (SIC), Cathode Ray Television Picture
Tubes Mfg. (SIC), Cement, Hydraulic (SIC), Ceramic Wall and Floor Tile Mfg. (SIC), Cereal Breakfast Foods (SIC),
Cheese, Natural and Processed (SIC), Chemical Preparations (SIC), Chemicals and Allied Products (SIC), Chocolate And
Cocoa Products (SIC), Chromium Metal Plating (AMS), Cigarettes (SIC), Clay Refractories (not subject to Refracto (SIC),
Cold Finishing of Steel Shapes (SIC), Commercial Laundry Equipment (SIC), Commercial Lighting Fixtures (SIC),
Communications Equipment (SIC), Concrete, Gypsum, And Plaster Products (SIC), Condensed and Evaporated milk (SIC),
Construction Machinery Mfg. (SIC), Conveyors and Conveying Equipment Mfg. (SIC), Copper Foundries (SIC), Copper
Rolling and Drawing (SIC), Cultured Marble Mfg. (AMS), Custom Compound Purchased Resins (SIC), Cutlery (SIC), Cut
Stone and Stone Products (SIC), Cutlery (SIC), Cyclic Crude and Intermediate Production (SIC), Dehydrated Fruits,
Vegetables, and Soups (SIC), Diagnostic Substances (SIC), Distilled and Blended Liquors Production (SIC), Drapery
Hardware and Blinds and Shades (SIC), Edible Fats and Oils (SIC), Electric Lamps (SIC), Electrical Equipment and
Supplies (SIC), Electrical Housewares and Fans (SIC), Electrical Industrial Apparatus (SIC), Cyanide Chemicals
Production (AMS), Dehydrated Fruits, Vegetables, and Soups (SIC), Diagnostic Substances (SIC), Distilled and Blended
Liquors Production (SIC), Dog and Cat Food (SIC), Drapery Hardware and Blinds and Shades (SIC), Drum and Barrel
Reclamation (AMS), Edible Fats and Oils (SIC), Electric Lamps (SIC), Electromedical Equipment Mfg. (SIC),
Electrometalturgical Products Mfg. (SIC), Electronic & Other Electric Equipment (SIC), Elevators and Moving Stairways
(SIC), Engine Electric Equipment (SIC), Environmental Controls Mfg. (SIC), Explosives & Blasting Agents (SIC),
Extraction Solvent (AMS), Fabricated Metal Products Mfg. (SIC), Fabricated Pipe and Fittings (SIC), Fabricated Plate
Work (Boiler Shops) (SIC), Fabricated Rubber Products (SIC), Fabricated Textile Products (SIC), Farm Machinery and
Equipment Mfg. (SIC), Fasteners, Buttons, Needles, and Pins (SIC), Fertilizers, Mixing only (SIC), Fiber Cans, Drums, and
Similar Products (SIC), Flat Glass (SIC), Flavoring Extracts and Syrups Production (SIC), Flexible Polyurethane Foam
Fabrication (AMS). Flour and Other Grain Mill Products (SIC). Fluid Meters and Counting Devices (SIC).
D-36
-------
Table D-15. Surrogates Used for Spatial Allocation of the 1996 NTI Area Source Inventory (continued)
Surrogate name
(and code)
Definition
Emissions Inventory categories
Industrial land (3)
USGS land use categories: industrial, plus
one-half of industrial and commercial
complexes, plus one-third of mixed urban and
built-up land, plus one-third of other urban
and built-up land
Fluid Power Pumps and Motors (SIC), Fluorescent Lamp Recycling (SCC), Food Preparations Production (SIC), Food
Products Machinery Mfg. (SIC), Footwear Cut Stock (SIC), Friction Products (MACT), Frozen Specialties (SIC), Frozen
fruits, Fruit Juices and Vegetables (SIC), Fumed Silica Production (SCC), Furniture and Fixtures Mfg. (SIC), Gaskets,
Packing and Sealing Devices Mfg. (SIC), General Industrial Machinery Mfg. (SIC), Glass Containers (SIC), Gray and
Ductile Iron Foundries (SIC), Gum and Wood Chemical Mfg. (SIC), Gypsum Products (SIC), Hand and Edge Tools Mfg.
(SIC), Hard Chromium Electroplating (AMS), Hardware Mfg. (SIC), Hardwood (SIC), Hats, Caps, And Millinery (SIC),
Heating Equipment, Except Electric (SIC), Hoists, Cranes, and Monorails (SIC), Hose and Belting and Gaskets and
Packing (SIC), Household Equipment (SIC), Household Furniture (SIC), Hydrochloric Acid Production (AMS), Hydrogen
Fluoride Production (AMS), Industrial Boilers (AMS), Industrial Gases Mfg. (SIC), Industrial Inorganic Chemicals (SIC),
Industrial Machinery (SIC), Industrial Organic Chemicals Mfg. (SIC), Industrial Sand (SIC), Inorganic Pigments Mfg.
(SIC), Instruments to Measure Electricity (SIC), Internal Combustion Engine Mfg. (SIC), Iron and Stee' (SIC), Lawn and
Garden Equipment (SIC), Lead Pencils, Art Goods Mfg. (SIC), Leather Tanning and Finishing (not subject (SIC), Lighting
Equipment (SIC), Lime Mfg. (SIC), Lubricating Oils and Greases (SIC), Macaroni And Spaghetti (SIC), Machine Tools,
Metal Forming Types (SIC), Magnetic and Optical Recording Media Mfg. (SIC), Malleable Iron Foundries (SIC), Malt
Beverages (SIC), Mfg. Industries Mfg. (SIC), Marine Cargo Handling (SIC), Marking Devices (SIC), Measuring and
Controlling Devices (SIC), Meat Packing Plants (SIC), Mechanical Rubber Goods Mfg. (SIC), Medical, Dental, and
Hospital Equipment, S (SIC), Medicinals and Botanicals Mfg. (SIC), Men's Footwear, Except Athletic (SIC), Men's and
Boys' Shirts (SIC), Metal Barrels, Drums, and Pails Mfg. (SIC), Metal Doors, Sash, and Trim (SIC), Metal Forgings and
Stampings (SIC), Metal Heat Treating Mfg. (SIC), Metal Household Furniture (SIC), Metal Sanitary Ware Mfg. (SIC),
Metal Stampings Mfg. (SIC), Metal Valves (SIC), Metal cans (3411) (SIC), Metal Cans (Surface Coating) (AMS), Metal
coating and allied services (3479) (SIC), Metalworking Machinery (SIC), Millwork (SIC), Mineral Wool (SIC), Mineral
Wool Mfg. (SCC), Minerals, Ground or Treated Production (SIC), Mining Machinery Mfg. (SIC), Misc. Fabricated Metal
Products (SIC), Misc. Foods and Kindred Products (SIC), Misc. Mfg. (3990) (SIC), Misc. Mfg. Coating (SIC), Misc. Metal
Work (SIC), Misc. Organic Chemical Processes (AMS), Misc. Plastics Products (SIC), Misc. Primary Metal Products
(SIC), Mobile Homes (SIC), Motor and Generators Mfg. (SIC), Natural Gas Transmissions and Storage (AMS),
Nitrogenous Fertilizers (SIC), Nonclay Refractories (SIC), Noncurrent-Carrying Wiring Devices (SIC), Nonferrous Metals
(SIC) Nonmetallic Mineral Products Mfg. (SIC), Office Furniture, Except Wood (SIC), Oil and Gas Field Machinery Mfg.
(SIC), Oil and Gas Support (SCC), On-Site Waste Incineration (AMS), Ophthalmic Goods (SIC), Optical Instruments and
Lenses (SIC), Ordnance and Accessories Mfg. (SIC), Organic Fibers, Non-cellulosic (SIC), Paints, Coatings, and
Adhcsivcs (SIC), Paper Coating (AMS), Paper Industries Machinery (SIC), Paper Mills (SIC), Paper and Other Webs
(Surface Coating) (AMS), Partitions and Fixtures, Except Wood (SIC), Pens and Mechanical Pencils (SIC), Petroleum
Refining (SIC), Pharmaceutical Preparations Manufacturing (SIC), Pharmaceuticals Production (AMS), Phosphatic
Fertilizers (SIC), Photographic Equipment and Supplies Manufa (SIC), Pickles, Sauces, And Salad Dressings (SIC), Plastic
Parts and Products (Surface Coatin (AMS), Plastics Products (SIC), Plumbing Fixture Finings and Trim (SIC),
Plywood/Particle Board Manufacturing (SCC), Polishes and Sanitation Goods Manufacturin (SIC), Polysulfide Rubber
Production (AMS), Polyvinyl Chloride and Copolymers (SCC), Porcelain Electrical Supplies (SIC), Pottery Products, nee
(SIC), Poultry Slaughtering and Processing (SIC), Power Driven Handtools (SIC), Power Transmission Equipment (SIC),
Pre-recorded Records and Tapes (SIC), Prefabricated Metal Buildings (SIC), Prefabricated Wood Buildings and
Component (SIC), Prepared Feeds Manufacturing (SIC), Prepared Flour Mixes And Doughs (SIC), Pressed and Blown
Glass and Glassware (SIC), Primary Aluminum Production (SCC), Primary Batteries (SIC), Primary Metal Products
Manufacturing (SIC), Primary Nonferrous Metals Production (SIC), Printing Ink (SIC), Printing, Coating, and Dyeing of
Fabrics (SCC), Printing Trades Machinery Manufacturing (SIC), Process Control Instruments (SIC), Products of Purchased
Glass (SIC),
D-37
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Table D-15. Surrogates Used for Spatial Allocation of the 1996 NTI Area Source Inventory (continued)
Surrogate name
(and code)
Definition
Emissions inventory categories
Industrial land (3)
USGS land use categories: industrial, plus
one-half of industrial and commercial
complexes, plus one-third of mixed urban and
built-up land, plus one-third of other urban
and built-up land
Public Building and Related Furniture (SIC), Pulp mills (2611) (SIC), Pumps and Pumping Equipment Manufacturing
(SIC), Radio and Television Communications Equip. (SIC), Railroad Equipment Manufacturing (SIC),Raw Cane Sugar
(SIC), Reconstituted Wood Products (SIC), Refractories Manufacturing (MACT), Refrigeration and Heating Equipment
(SIC), Reinforced Plastic Composites Production (AMS), Relays and Industrial Controls (SIC), Residential lighting fixtures
(SIC), Rice Milling (SIC), Rolling Mill Machinery (SIC), Rubber and Plastic Footwear (SIC), Rubber and Plastic Hose and
Belting (SIC),Sanitary Food Containers (SIC), Sausages And Other Prepared Meats (SIC), Saw Blades and Handsaws
(SIC), Sawmills and Planing Mills, general (SIC), Scales and Balances, excluding Laboratory (SIC), Screw Machine
Products Mfg. (SIC), Search and Navigation Equipment (SIC), Secondary Lead Smelting (SCC), Secondary Nonferrous
Metals Production (SIC), Semiconductors and Related Devices (SIC), Service Industry Machinery (SIC), Sheet Metal
Work (SIC), Ship Building And Repairing (SIC), Silverware and Plated Ware (SIC), Small Arms (SIC), Small Arms
Ammunition (SIC), Soaps, Cleaners, and Toilet Goods (SIC), Softwood Drying Kilns (AMS), Softwood Veneer and
Plywood (SIC), Soil and Groundwater Remediation (AMS), Special Dies, Tools, Jigs and Fixtures (SIC), Special Industry
Machinery Mfg. (SIC), Speed Changers, Drives, and Gears (SIC), Spills, Dumping, MSW Handling (AMS), Stationary
Turbines (MACT), Steel Pickling HC1 Process (AMS), Steel Pipe and Tubes Mfg. (SIC), Steel Springs, Except Wire (SIC),
Steel Wire and Related Products Mfg. (SIC), Storage Batteries Mfg. (SIC), Structural Wood Members (SIC), Surface
Active Agents Mfg. (SIC), Surface Coatings: Industrial Maintenance (AMS), Surgical Appliances and Supplies (SIC),
Switchgear and Switchboard Apparatus (SIC), Synthetic Rubber Mfg. (SIC), Taconitc Iron Ore Processing (SCC), Tank
Transit (AMS), Tanks and Tank Components Mfg. (SIC), Telephone and Telegraph Apparatus (SIC), Textile Machinery
(SIC), Textile Products (AMS), Tire Cord and Fabric (SIC), Tires and Inner Tubes (SIC), Toilet Preparations Mfg. (SIC),
Toys and Sporting Goods (SIC), Transformers, Except Electronic (SIC), Travel Trailers and Campers Mfg. (SIC), Turbines
And Turbine Generator Sets (SIC), Typewriters Computer Storage Devices (SIC), Unsupported Plastics (SIC), Upholstered
I louschold Furniture (SIC), Valves And Pipe Fittings (SIC), Vitreous China Table & Kitchcnwarc (SIC), Vitreous
Plumbing Fixtures (SIC), Waste Disposal: Open Burning (AMS), Welding Apparatus (SIC), Wet Corn Milling (SIC), Wire
Springs (SIC), Women's Footwear, Except Athletic (SIC), Women's, Misses', and Juniors' Suits, Skir (SIC), Wood
Preserving (SIC). Wood Products (S1C1. Woodworking Machinery (SIC). X-ray Apparatus And Tubes (SIC)
D-38
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Table D-16. Surrogates Used for Spatial Allocation of the 1996 Diesel PM Inventory
Surrogate name (and code)
Industrial land (3)
Commercial land plus industrial
land (6)
Forest land (13)
Water (15)
Mining and quarry land (17)
Inverse population density (18)
Railway miles (21)
Roadway miles (22)
25% Population & 75%
roadway miles (25)
Tract area (26)
Urban - Inverse population
density
Rural - farmland (27)
Sum of farmland and orchard
land (29)
Definition
USGS land use categories: industrial, plus one-half of industrial and
commercial complexes, plus one-third of mixed urban and built-up
land, plus one-third of other urban and built-up land
Sum of commercial land and industrial land, as defined below
USGS land use categories: deciduous forest plus evergreen forest
plus mixed forest land
US Census category: water area
USGS land use categories: strip mines, quarries, and gravel pits
Inverse of: census tract population (category 20) divided by census
tract area. Tracts with zero population assigned a SAP of zero.
Total railway miles, as reported in TIGER/Line
Total miles of all roadway types in each census tract, as reported in
TIGER/Line
Surrogate based on population fraction and roadway mile fractions,
respectively weighted by 25% and 75%, for each of four roadway
types
The area of census tracts (including land and water)
Inverse population density (18) for urban counties; farmland (7) for
rural counties
Sum of farmland and orchard land, as defined above
Diesel PM inventory source categories
Industrial Equipment
Lawn and Garden Equipment, Commercial Equipment
Logging Equipment
Commercial Marine Vessels, Pleasure Craft
Underground Mining Equipment
Construction and Mining Equipment, Airport Ground Support Equipment
Railroads, Railway Maintenance
HDDV Rural Total: Interstate, Other Principal Arterial, Minor Arterial, Major
Collector, Minor Collector, Local; HDDV Urban Total: Interstate, Other Freeways
and Expressways, Other Principal Arterial, Minor Arterial, Collector, Local
LDDT & LDDV Rural Total: Interstate, Other Principal Arterial, Minor Arterial,
Major Collector, Minor Collector, Local; LDDT & LDDV Urban Total: Interstate,
Other Freeways and Expressways, Other Principal Arterial, Minor Arterial, Collector,
Local
Recreational Equipment
All Off-highway Diesel
Agricultural Equipment
D-39
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Table D-17. Spatial Allocation of Mobile Source Categories in EMS-HAP as Compared to Other Emission Models
NTI Mobile
Source Category
Subcategories,
where applicable1"
Light Duty Gasoline Vehicles (LDGV)
Light Duty Gasoline Trucks (LDGT)
Heavy Duty Gasoline Vehicles (HDGV)
Motorcycles (MC)
Light Duty Diesel Vehicles (LDDV)
Light Duty Diesel Trucks (LDDT)
Heavy Duty Diesel Vehicles (HDDV)
Nonroad: Gasoline,
2-stroke
All
Recreational
Construction
Industrial
Lawn & garden
Light commercial
Logging
Airport service
AMS code
A2201001
A2201060
A2201070
A2201080
A2230001
A2230060
A2230070
A2260000
A2260001
A2260002
A2260003
A2260004
A2260006
A2260007
A2260008
EMS-95 Spatial Profile
Code
not
appl.
8
L8
8
8
4
8
6
2
Description
Roadway links
(vehicle-miles-
traveled)
Population
Population
Population
Population
Housing
Population
1 /Population
Airports
CEP Spatial Profile
Code
30
19
19
18
3
1
2
13
19
Description
'/z Roadway miles + !/2 Population
Inverse population density
Inverse population density
Inverse population density
Industrial land
Residential land
Commercial land
Forest land
Inverse population density
EMS-HAP
(3/4) Roadway miles + (1/4)
Population
(3/4) Roadway miles + (1/4)
Population
(3/4) Roadway miles + (1/4)
Population
(3/4) Roadway miles + (1/4)
Population
(3/4) Roadway miles + (1/4)
Population
(3/4) Roadway miles + (1/4)
Population
Roadway miles
census tract area
D-40
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Table D-17. Spatial Allocation of Mobile Source Categories in EMS-HAP as Compared to Other Emission Models (continued)
NTI Mobile
Source Category
All Off-highway
Vehicle: Gasoline,
4-Stroke
All Off-highway
Vehicle: Diesel
Subcategories,
where applicable"
All
Recreational
Construction
Industrial
Lawn & garden
Farm equipment
Light commercial
Logging
Airport service
All
Recreational
Construction
Industrial
Lawn & garden
Farm equipment
Light commercial
Logging
Airport service
All Aircraft Types and Operations
Marine Vessels, Commercial
Railroads-Diesel
AMS code
A2265000
A2265001
A2265002
A2265003
A2265004
A2265005
A2265006
A2265007
A2265008
A2270000
A2270001
A2270002
A2270003
A2270004
A2270005
A2270006
A2270007
A2270008
A2275000
A2280000
A2285002
EMS-95 Spatial Profile
Code
8
8
8
8
4
8
8
6
2
8
8
8
8
4
8
8
6
2
2
9
10
Description
Population
Population
Population
Population
Housing
Population
Population
1 /Population
Airports
Population
Population
Population
Population
Housing
Population
Population
1 /Population
Airports
Airports
Ports
Railroads
CEP Spatial Profile
Code
19
19
18
3
1
7
2
13
19
19
19
18
3
1
7
2
13
19
18
15
21
Description
Inverse population density
Inverse population density
Inverse population density
Industrial land
Residential land
Crop land
Commercial land
Forest land
Inverse population density
Inverse population density
Inverse population density
Inverse population density
Industrial land
Residential land
Crop land
Commercial land
Forest land
Inverse population density
Inverse population density
Water
Railway miles
EMS-HAP
lural Counties: tract area
Jrban Counties: population
Rural Counties: farmland, as
used in CEP
Urban Counties: Inverse
population density
treat as point sources, locatec
at major airports in each
county
Water
Railway miles
Tor some of the NTI emission categories, the spatial
allocation surrogates used in EMS-95 and the CEP
varied among different subcategories. Where this
oqcurs, the subcategories are listed individually.
D-41
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D.9 How We Developed the Surrogate Assignment/ Temporal Allocation Cross-Reference
Files (scc2ams.txt, sic2ams.txt, and mact2scc.txt)
EMS-HAP uses the above-mentioned cross-reference files for assigning spatial surrogates to area
sources and for assigning temporal profiles to both point and area sources. They are not used for
mobile source categories because these categories are indexed only by AMS codes which can be
linked directly to spatial surrogate and temporal profile data. EMS-HAP uses these cross-
reference files to assign temporal profiles for point source records when they don't have a
standard 8-digit SCC, but rather have an alternative code such as a shortened SCC, SIC or
MACT (see 5.1.1 for details). They are also used to assign temporal profiles (see 8.1.3) and
spatial surrogates (see 8.1.2) for area sources when emissions are indexed by MACT, SIC or
SCC codes.
The cross-reference file named scc2ams.txt links generic 1-digit, 3-digit, and 6-digit SCCs to the
8-digit SCC and 10-digit AMS codes used in the TAP file. It also contains a spatial surrogate
assignment which is used to assign surrogates for area sources not having a MACT or SIC code
(SCC follows the MACT and SIC codes in the hierarchy of spatial surrogate assignments). To
produce this file, we reviewed the definition of the shortened SCC, as given in EPA's Factor
Information Retrieval (FIRE) data base.15 For area sources, we also reviewed the definition of
the emission category in documentation for the 1996 NTI. We then selected the most appropriate
8-digit SCC to represent the category using SCC definitions from FIRE. We also used the SCC
definitions to select the most appropriate spatial surrogate to represent the category (see D.8).
The cross-reference file named sic2ams.txt links SIC codes to SCC and AMS codes
(sic2ams.txt). It also contains a spatial surrogate assignment which is used to assign surrogates
for area sources with an SIC code but not having a MACT code (SIC follows the MACT code in
the hierarchy of spatial surrogate assignments). To produce this file, we drew on detailed SIC
definitions published by the Office of Management and Budget.16 We also used the SIC
definition to select the most appropriate spatial surrogate to represent the category (See D.8).
The cross-reference named mact2scc.txt links MACT codes to SCC and AMS codes
(mact2scc.txt). It also contains a spatial surrogate assignment which is used to assign surrogates
for area sources having this code. We produced this file by reviewing MACT category
definitions from the EPA source category listing document. The MACT category definitions17
were compared with SCC and AMS category definitions from FIRE. We also used the MACT
category definition to select the most appropriate spatial allocation surrogate (see D.8).
D-42
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D.10 How We Developed the Spatial Allocation Factors
The spatial allocation factors (SAFs) in EMS-HAP for allocating county level emissions to the
census tract were primarily obtained from the developers of the CEP. They computed SAFs
from tract-level land use and population data. We denote land use and population as "spatial
surrogates." We assume that the spatial distribution of county-level emissions categories within
a county's census tracts is proportional to the spatial distribution of these land use and population
surrogates within the county's pensus tracts. The developers of the CEP used population data
from the 1990 U.S. census (see www.census.gov),33 roadway data from the 1990 Topologically
Integrated Geographic Encoding and Referencing (TIGER®/Line) files34 and land use data
compiled by the United States Geological Survey between the middle of the 1970's through the
middle of the 1980's.35 They calculated SAFs from this data using the following equation:
SAFcounty,,j = Ai. j / Acounty, j (eq. D-3)
where
S AFcounty j J = the spatial allocation factor for surrogate j and census tract i within
a county. (For any spatial surrogate, the values for all of the tracts
in a given county will add to 1.0.)
A; j = land use, population, or other activity data for surrogate j in tract i
Acounty j = total land use, population, or other activity data for surrogate j in
the county that contains tract i
Table D-18 shows the surrogates and corresponding sets of SAFs we developed for EMS-HAP.
Note that we did not use all of the surrogates listed in the table for preparing the 1996 ASPEN-
input files. We did not use SAFS, SAF9, SAP 12, SAF14, SAP 17 or SAF24. The assignment of
surrogates to area and mobile source categories in the 1996 NTI is discussed in Section D.8.
As you can see, most of the SAFs developed for EMS-HAP came directly from the CEP. We
did, however, make some changes to their SAFs. These changes are discussed below the table.
D-43
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Table D-18. Spatial Allocation Factors Developed for EMS-HAP
Code
for set
ofSAFs
SAF1
SAF2
SAF3
SAF4
SAF6
SAF7
SAF8
SAF9
SAF10
SAF12
SAF13
SAP 14
SAF15
SAF17
SAF18
SAF19
Surrogate
Residential
land
Commercial
land
Industrial
land
Utility land
Sum of
commercial
land and
industrial
land
Farm land
Orchard land
Confined
feeding
Farm land &
confined
feeding
Rangeland
Forest land
Rangeland &
forest land
Water
Mining &
quarry land
Inverse
population
density
Inverse
population
density
Definition
USGS land use categories: Residential, plus one-third of
mixed urban and built-up land plus one-third of other
urban and built-up land
USGS land use categories: Commercial and services, plus
one-half of industrial and commercial complexes, plus
one-third of mixed urban and built-up land plus one-third
of other urban and built-up land
USGS land use categories: industrial, plus one-half of
industrial and commercial complexes, plus one-third of
mixed urban and built-up land, plus one-third of other
urban and built-up land
USGS land use category: "transportation, communications,
and utilities"
Sum of commercial land and industrial land, as defined
above
USGS land use category: "cropland and pasture"
USGS land use category: "orchards, groves, vineyards,
nurseries, and ornamental horticultural areas"
USGS land use category "confined feeding"
USGS land use categories "cropland and pasture" plus
"confined feeding"
USGS land use categories: "herbaceous rangeland" plus
"scrub and brush" plus "mixed rangeland"
USGS land use categories: "deciduous forest" plus
"evergreen forest" plus "mixed forest land"
Sum of rangeland and forest land, as defined above
US Census category: water area
USGS land use category: "strip mines, quarries, and gravel
pits"
Inverse of: census tract population (defined above) divided
by census tract area. Tracts with zero population assigned
spatial factors of zero.
Inverse of: census tract population (as defined above)
divided by census tract land area. Tracts with zero
population assigned tract population of one.
Origin of
Data
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
mid-70's
to 80's
1990
mid-70's
to 80's
1990
1990
How we developed the
set of SAFs
from CEP1'"
from CEP1-"
from CEP"'"
from CEP'"
land use data from
developers of CEP*'b,
SAP computed from
equation D-3
from CEP''"
from CEP'-"
from CEP"-"
from CEP'-"
from CEP1 "
from CEP1-"
from CEP''"
from CEP1'"
from CEP1'"
from CEP1'"
population and land
area data from CEPb,
SAF computed from D-
3 (see item 5, below)
D-44
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Table D-18. Spatial Allocation Factors Developed for EMS-HAP (continued)
Code Surrogate
for set
ofSAFs
Definition
Origin of How we developed the
Data setofSAFs
SAF20 Population
SAF21 Railway
miles
U.S. Census category: 1990 residential population
Total railway
miles, as reported in TIGER/Line
1990 fromCEP1-"
1993 fromCEP1-"
SAF22 Roadway
miles
SAF24 50%
Population &
50% roadway
miles
SAF25 25%
Population &
75% roadway
miles
Total miles of all roadway types in each census tract, as
reported in TIGER/Line
Surrogate based equally on population fraction and on
roadway mile fractions for each of four roadway types
Surrogate based on population fraction and roadway mile
fractions, respectively weighted by 25% and 75%, for each
of four roadway types
SAF26 Tract area The area of census tracts (including land and water)
1993 fromCEP1-"
1990-93 0.5*SAF20 +
0.5*SAF22
1990-93 0.25*SAF20 +
0.75*SAF22
1990 tract areas computed
from CEP tract radiib
data SAF computed
from D-3
Inverse population density (18) for urban' counties;
farmland (7) for rural' counties
SAF27 Urban -
Inverse
population
density
Rural -
farmland
SAF28 Urban - Population (20) for urban' counties; tract area for (26)
population rural' counties
Rural - tract
area
SAF29 Sum of Sum of farmland and orchard land, as defined above
farmland and
orchard land
1990, SAF 18 from CEP,
mid-70's SAF 7 from CEP,
toSO's , .
urban/rural county
designations from 1990
and 1996 census data
1990 SAF 20 from CEP,
SAF 26 from CEP,
urban/rural county
designations from 1990
and 1996 census data
mid-70's land use data from
to 80's developers of CEP1 b,
SAF computed from
equation D-3
1 except that we made changes to SAFs in Halifax and South Boston, Virginia counties, see item 4, below
" except for census tracts in the Virgin Islands and Puerto Rico (these areas were not modeled in the CEP) see item 3
below
' county-level urban rural designation.was made using 1990 and 1996 census tract data18
The following list discusses the additional surrogates (and resulting SAFs) we added and the
changes we made to the those SAFs used in the CEP.
1. We added spatial allocation factors based on a tract area spatial surrogate (S AF26).
D-45
-------
We computed the tract area for each census tract based on the tract radius. These radii were
originally computed from tract area values supplied by the developers of the CEP. We used
equation D-3, using tract area as the activity.
We developed the tract area SAFs to implement the recommendations of the EPA's Office of
Transportation and Air Quality(OTAQ)36'37 They suggested (as shown in Table D-16) we use
this surrogate for allocating the mobile source category of nonroad gasoline, 2-stroke engines and
nonroad gasoline 4-stroke engines (rural counties only).
2. We added "composite" spatial allocation factors which use more than type of land use or
population data.
SAF6, SAP 10, SAF24, SAF25, SAF27 and SAF28 combine more than one type of data. Of
these SAFs, we developed SAF6, SAF24, SAF25, SAF27 and SAF28. SAF6, for example,
combines commercial and industrial land data. SAF27 uses inverse population density data for
urban counties and farmland for rural counties. We used 1990 and 1996 census data to establish
the county-level urban/rural designation.18
We developed the SAFs for the composite surrogates because we felt that the composite
surrogates provided a better approach for allocating some of our area and mobile source
categories, and the data was readily available. For example, we felt that halogenated solvents
were used at both industrial and commercial facilities. To develop a set of industrial and
commercial land SAFs (SAF6) we added industrial and commercial land data for each tract, and
used equation D-3. The EPA's OTAQ recommended two composite surrogates (see SAF27 and
SAF28) that use different types of data depending on whether the tract is an urban or rural
county.36'37 They recommended (as shown in Table D-16) SAF27 for nonroad diesel engines and
SAF28 for nonroad gasoline 4-stroke engines.
3. We added Puerto Rico and Virgin Islands spatial allocation factors since these areas were not
modeled in the CEP.
We developed Puerto Rico and Virgin Islands land use and population data by processing
geographic information system (GIS) coverages obtained from the Region 2 web site at
www.epa.gov/region2/gis/atlas. Table D-19 lists the data we obtained from the website. We
used equation D-3 for developing SAFs from the land use and population data.
Some land use categories we used for the continental U.S. (forest land, for example) were not
available for these islands. Therefore, we derived spatial allocation factors from the most
closely-matched available data. Table D-20 shows the SAFs we used in this situation.
D-46
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Table D-19. Surrogate Data Available for Puerto Rico and the Virgin Islands
Puerto Rico
Population
Roadway miles
Tract area
Commercial land
Farmland
Industrial land
Residential land
Railroad miles
Water
Virgin Islands
Population
Roadway miles
Tract area
Table D-20. Methodology for Puerto Rico/Virgin Islands Spatial Allocation Factors
When the continental U.S.
used (surrogate code in
parenthesis)
Puerto Rico used
Virgin Island used...
residential land (1)
commercial land (2)
industrial land (3)
utility land (4)
commercial and industrial land
(6)
farm land (7)
water (15)
urban counties: inverse
population density
rural counties: farmland (27)
farm land and orchard land
(29)
residential land
commercial land
industrial land
inverse population density
commercial and industrial
land
farm land
water
urban counties: inverse
population density
rural counties: farmland
farmland
population
population
population
inverse population density
population
tract area
population
urban counties: inverse
population density
rural counties: tract area
tract area
In addition, For Puerto Rico and the Virgin Islands surrogates 18 and 19 used tract area (based on
D-47
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the radius of the tract) rather than land area in the calculation of inverse population density. The
difference between the two is that land area does not include water area.
4. In 1993. the census no longer treated South Boston as a county, and therefore we had to make
adjustments to the CEP SAFs
The single tract formerly in South Boston City, Virginia was, in 1996, considered part of Halifax
county, Virginia. Because South Boston was no longer a county, there were no area source or
mobile source emission estimates for it from the 1996 NTI or NET inventories. In order to make
sure that EMS-HAP allocated Halifax county emissions to the South Boston tract we needed to
change the SAFs supplied to us by the CEP. The change was to associate the South Boston tract
with Halifax county. Note that this recalculation only affected Halifax county and South Boston
SAFs.
5. We changed the way zero population tracts were treated using the inverse population density
surrogate 19
As seen in Table D-18, there are two inverse population density surrogates (SAF18 and SAF19)
in EMS-HAP. They differ in how they treat zero population tracts. There are nearly 10,000 zero
population census tracts, and they vary in size. (In fact, about 300 of these have zero tract areas).
We changed the treatment of zero population tracts only for the SAFs associated with surrogate
19. We refer to these SAFs as "SAF19." In the former SAF19 used for the CEP, zero population
tracts were given the maximum inverse population density of all tracts in the county. Note that
this value was assigned to these zero population tracts regardless of their size.
We changed the use of the maximum inverse population density for zero population tracts
because we noticed that in some areas, particularly in Denver County, Colorado, there are a
large number of zero population tracts. Denver County, for example, has 30 out of a total of 182
tracts. The use of former SAF19 results in high SAF values for these tracts, which in turn
produces high emission densities for these tracts. These tracts were also located near one another
so that even though the ASPEN model does not account for the impact of these emissions for the
resident tract38, the small tracts nearby were affected.
We chose to recompute the inverse population density using a population of one person for zero
population tracts rather than assign them the maximum inverse population density. We refer to
this treatment as "new SAF19." We tested the effect of new SAF19 by choosing a particular
pollutant in which emissions are dominated by a single source category. The pollutant is diesel
PM, and the category is nonroad diesel engines. We modeled this pollutant through EMS-HAP
and ASPEN (using a draft diesel PM inventory based on the 1996 NET). We also tested a
variation of new SAF 19 which we call "tract area SAF 19." For this tract area SAF 19 we used
the tract area of each tract rather than the land area of each tract to calculate inverse population
density. Note that the developers of the CEP used land area for former SAF 19. The difference
in the two areas is that water area is not included in land area, but it is included in tract area. We
tested tract area SAF 19 for two reasons. First was to show the effect of changes in 19 on
modeling results. Second was that we actually used this tract area SAF 19 for allocating those
D-48
-------
categories matched to surrogate 19 for Puerto Rico and Virgin Islands (see item 3 in this section).
For the purposes of the test we allocated county-level diesel PM emissions from nonroad diesel
engines to the three different treatments (former, new, tract area) of SAP 19. Note that this
category normally uses 27 (see Table D-16); we used 19 only for the test. We kept all other
mobile source categories allocated as in Table D-16.
Figure D-3 shows the differences in tract-level emission densities (emissions per tract area)
resulting from the two approaches. Note that the tracts with zero tract area are not included in
this figure because the emission density is infinite for these tracts. As seen in the figure, the new
SAF19 resulted in substantially lower emission densities for a large number of tracts.
We also ran the ASPEN model to see the effect on ambient concentrations. We looked at the
State mean, because this statistic is sensitive to outliers. Figure D-4 shows the results. In
Colorado, the mean concentration was reduced using new SAF19, which alleviates the concerns
mentioned earlier raised from the former SAP 19.
D-49
-------
10'
Former SAF19
— NewSAF19
Tract Area SAF19
Emission Density [g's~'knf
Figure D-3. Nationwide Tract-level Emission Densities
Using Three Different Treatments of SAF19.
D-50
-------
Diesel Nonroad: SAP 19 w/ Tract Area
BBI Diesel Nonroad: SAP 19 New
I 1 Diesel Nonroad: SAP 19 Old
Diesel Onroad
0.5 -
PL «Z flR Cfl CO CT BE DC FL Cfi ID IL IN Ifl KS KY Lft ME MD Mfl MI MN MS MO MT NE NV NH NJ NM NY NC NI OH OK OR Pfl RI SC SD TN TX UT VT Vfl Hfl HV HI MY PR VI USft
1 Figure D-4. The Effect of the Three Different Treatments of S AF19 on State-level Mean Concentrations Estimates
D-51
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D.ll Program Options and Parameters
This section presents the options used to run EMS-HAP for the base year 1996 run. Several of
the EMS-HAP programs contain options for determining which specific functions to run and
choices of how to run them. In addition, the data quality assurance program, PtDataProc
requires you to enter parameters for the default stack parameter assignments. This section
summarizes the options and parameters we selected for the 1996 base year ASPEN input files.
We only present programs we ran that have options.
D.ll.l AirportProcprogram options
Aircraft emissions were extracted from the mobile source inventory and stored in a file separate
from the point source inventory as indicated by the setting of the program options given in Table
D-21. The allocated aircraft emissions inventory was then processed through the remaining
EMS-HAP programs independent of the rest of the point source inventory.
Table D-21. Program Options Used to Execute AirportProc
Keyword Description Value
ADD2PT 1 =append records to ouput point source inventory file and 0
0=create an output file containing only allocated aircraft emission records
ADD2MB l=append records to output mobile source inventory file and 1
0=create an output file containing only unallocated aircraft emission
records
D.I 1.2 PtDataProc program options and parameters
Location Data Quality Assurance
When the 1996 NTI and the 1996 NET speciated point source inventories were processed
through PtDataProc, point source locations were converted to latitude and longitude in decimal
degrees and all location quality checks and defaulting procedures were performed.
Quality Assurance of Stack Parameters
Missing or out-of-range stack parameters were defaulted using SCC and SIC defaults. We
defined the out-of-range boundaries for each parameter as shown in Table D-22. Any out-of-
range stack parameters that could not be defaulted by SCC or SIC defaults (i.e., if there was no
SCC or SIC code on the record, or the code did not match those in the SCC/SIC default files)
were defaulted to the range maximum or minimum value, depending on the value of the stack
parameter. For example, a stack height greater than 381 meters was defaulted to 381 meters.
D-52
-------
Any missing stack parameters that could not be defaulted by SCC or SIC were defaulted to the
global default values in Table D-22. Because we did not use SCC-based defaults for aircraft
emissions, these were defaulted using the global defaults.
Table D-22. Program Options and Parameters Used for PtDataProc
Keyword
Description
Value
DOLOCATE
DOSTACK
SCCDEFLT
SICDEFLT
DOSETVAR
USELIST
DOWINDOW
DLOWHT
DHIHT
DLOWDIA
DHIDIA
DLOWVEL
DHIVEL
DLOWTEMP
DHITTEMP
DFLTHT
DELTVEL
DFLTTEMP
DEFLTDIA
1= quality assure location data; 0 = don't quality assure them
1= quality assure stack parameters; 0 = don't quality assure them.
SCC to default stack parameters correspondence text file prefix (def_scc.txt)
SIC to default stack parameters correspondence text file prefix (def_sic.txt)
l=retain only those non-essential variables from inventory specified by the
user, based on the value of USELIST and VARLIST
0=retain all variables
1= use ancillary file (keyword VARLIST) to provide additional non-essential
variables to retain in inventory
0=don't retain any non-essential variables from the inventory
l=remove all records with zero emissions values or records without latitude
and longitude values
0= don't remove records with zero emissions or without latitude and
longitude values (note that values without latitude and longitude values will
still be removed if you perform the data quality assurance of location data
function)
Minimum range value for valid stack height (in meters)
Maximum range value for valid stack height (in meters)
Minimum range value for valid stack diameter (in meters)
Maximum range value for valid stack diameter (in meters)
Minimum range value for valid stack velocity (in meters/second)
Maximum range value for valid stack velocity (in meters/second)
Minimum range value for valid stack temperatures (in Kelvin)
Maximum range value for valid stack temperatures (in Kelvin)
Default stack height (in meters)
Default stack exit gas velocity (in meters/second)
Default stack exit gas temperature (in Kelvin)
Default stack diameter (in meters)
0.003
381
0.0762
15.24
0.003
198
273
1505
10
1
295
1
D-53
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D.11.3 PtFinalFormat program options and parameters
When the 1996 NTI and the 1996 NET speciated point source inventories were processed
through PtFinalFormat, ASPEN source groups were assigned by the source type only (See Table
7-1). Assignments were not made by MACT category, 6-digit SCC, or SIC. The default ASPEN
source group was group 1, although no records contained a missing source type and, therefore,
the default ASPEN source group was not used. The ASPEN source type designation (ITYPE)
was set to 0. The ASPEN input emission files were created and the data were also written to an
ASCII text file. Table D-23 summarizes the program options and parameters we specified in the
PtFinalFormat batch file.
Table D-23. Program Options and Parameters Used for PtFinalFormat
Keyword
DOSOURCE
DOMACT
DOSCC
DOSIC
DO WRITE
DOASCII
DFLTGRP
ITYPE
Description
1= assign source group by source type
l=assign source group by MACT category code
l=assign source group by SCC code
l=assign source group by SIC code
l=create ASPEN input emission files
l=create single ASCII text output file
Default source group (0 through 9)
Source type (0 for point sources and 3 for pseudo point sources)
Value
1
0
0
0
1
1
1
0
D-54
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D.11.4 AMProcprogram options
When the 1996 NTI and the 1996 NET speciated area and mobile source inventories were
processed through AMProc, the program options in Table D-24 were specified.
Table D-24. Program Options Used to Execute AMProc
Keyword
Description
Value
SAVEFILE
GROWCNTL
REBIN
LSUBSETP
SUBSETP
LSUBSETG
SUBSETG
LCPTIMES
LDBG
LONECELL
ONECELL
l=save large SAS*-formatted file with all emissions 1
information on a source category level basis for each
1= perform growth and control calculations; 0= don't 0
perform growth and control calculations; 2=run
growth and control only, using an existing temporally
l=Reassign emission groups during growth and 0
control processing; 0=don't reassign them
1= process only one pollutant; 0=don't process only 0
one pollutant
The NTI pollutant code to be subset to
1= process only one state; 0=don't process only one 0
State 2-character postal code abbreviation of the state US
to be subset to
l=print component CPU times; 0=don't print 1
component CPU times
l=printout of diagnostic information; 0=don't 0
1 =printout diagnostics for a selected single cell 0
The selected single cell
D.12 Pollutants in the ASPEN-Input Files for the 1996 Base Year EMS-HAP Run
Using the methodology discussed in D.I through D.I 1, we created point, area and mobile source
ASPEN emission files containing the pollutants listed in Table D-25 below. Pollutants in the
same reactivity class within the same point, area or mobile source run were written to the same
ASPEN emission file. For example, nonroad mobile source direct HAP emissions for all fine
metals (e.g., arsenic compounds, fine; beryllium compounds, fine; cadmium compounds, fine;
etc.) are contained in the file MV.omat.US.D050900.r2.inp, which represents reactivity class 2.
D-55
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Table D-25. List of Pollutants in ASPEN-ready input files
Pollutant
acetaldehyde
acetaldehyde, precursor
acetaldehyde precursor, inert
acrolein
acrvlonifrile
arsenic compounds, fine
arsenic compounds, coarse
benzene
beryllium compounds, fine
beryllium compounds, coarse
1,3 butadiene
1 ,3 butadiene, inert
cadmium compounds, fine
cadmium compounds, coarse
carbon tetrachloride
chloroform
chromium compounds, fine
chromium compounds, coarse
col^e oven emissions
1 ,3Michloropropene
SAROAD
in
EMS-HAP
43503
80100
80301
43505
43704
80112
80312
45201
80118
80318
43218
80302
80124
80324
43804
43803
80141
80341
80411
80152
Pollutant
diesel PM, fine {for mobile sources only}
diesel PM, coarse {for mobile sources only}
dioxins/chlorinated furans, lower bound
dioxins/chlorinated furans, upper bound
ethvl benzene
ethylene dibromide
ethylene dichloride
ethylene oxide
formaldehyde
formaldehyde, precursor
formaldehyde, precursor, inert
hexachlorobenzene
hexane
hydrazine
lead compounds, fine
lead compounds, coarse
manganese compounds, fine
manganese compounds, coarse
mercury compounds, fine
mercury compounds, gas
SAROAD
in
EMS-HAP
80400
80401
80412
80245
45203
43837
43815
43601
43502
80180
80303
80183
43231
80188
80193
80393
80196
80396
80197
80405
Pollutant
methyl tert-butyl ether
methylene chloride
nickel compounds, fine
nickel compounds, coarse
polvchlorinated biohenvls
polycylic organic matter
7-PAH
propionaldehyde
propionaldehyde, precursor
propionaldehyde, precursor, inert
propylene dichloride
quinoline
styrene
1 , 1 ,2,2-terrachloroethane
tetrachloroethylene (perc.)
toluene
trichloroethylene
vinyl chloride
xylenes
SAROAD
in
EMS-HAP
43376
43802
80216
80316
80231
80230
80233
43504
80234
80305
43838
80239
45220
80246
43817
45202
43824
43860
45102
D-56
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REFERENCES FOR APPENDIX D
1. U.S. Environmental Protection Agency. Unified Air Toxics Website: The Pollutants.
http://www.epa.gov/ttn/uatw/pollsour.html
2. Driver, L.; Pope, A.; Billings, R.; Wilson, D. "The 1996 National Toxics Inventory and
Its Role in Evaluating the EPA's Progress in Reducing Hazardous Air Pollutants in
Ambient Air", Presented at the 92nd Annual Meeting of the Air & Waste Management
Association, St. Louis, Missouri, 1999; paper 91-501.
3. "National Air Pollutant Emission Trends Procedures Document, 1900-1996," EPA-
454/R-98-008, U.S. Environmental Protection Agency. May 1998.
4. U.S. Environmental Protection Agency. Emission Inventory Guidance.
http://www.epa.gov/ttn.chief/ei guide.html#toxic
5, Electronic Mail. From Rich Cook, U.S. Environmental Protection Agency, Office of
Transportaion and Air Quality to Madeleine Strum, U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, September 30, 1999.
6. College of Engineering - Center for Environmental Research and Technology, University
ofCalifonia. 1998. Evaluation of Factor that Affect Diesel Exhaust Toxicity. Submitted
to California Air Resources Board, Contract No. 94-312.
7. Gabele, P. 1997. Exhaust Emissions from Four-Stroke Lawn Mower Engines. J. Air&
Waste. Manage. Assoc. 47:945-952.
8. U.S. Environmental Protection Agency. Nonroad Vehicle & Emission Modeling.
http://www.epa.gov/otaq/nonrdmdl.htm
9. U.S. Environmental Protection Agency. Integrated Urban Air Toxics Strategy PO Data
System, http://www.epa. gov/ttn/uatw/urban/urbanpg.html
10. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96-33r2,
Prepared for the U.S. Environmental Protection Agency, Office of Policy, Planning, and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, p. 2-8.
11. FAA 5010 Database, g.c.r. and associates, http://www.gcrl.com/.
12. Statistical Handbook of Aviation, 1996. Federal Aviation Administration, U.S.
Department of Transportation, Washington, DC.
-------
13. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96/33r2,
Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 5-3 to
5-4.
14. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96/33r2,
Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 3-12,
. 5-9 to 5-10.
15. Factor Information Retrieval (FIRE) data system (version 6.22). U.S. Environmental
Protection Agency, Research Triangle Park, NC. October 1999.
http://www.epa.gov/tmchiel/fire.htm.
16. Standard Industrial Classification Manual. Executive Office of the President, Office of
Management and Budget, Washington, DC. 1987.
17. "Initial List of Categories of Sources Under Section 112(c)(l) of the Clean Air Act
Amendments of 1990." Federal Register. 57:(137). Pp. 31576-31592.
18. Electronic Mail. From Laurel Driver, U.S. Environmental Protection Agency, Office of
Air Quality Planning and Standards (OAQPS) to Madeleine Strum (OAQPS), August 13,
1999.
19. Personal Communication with Robin Segall and Rima Dishakjian, both from the U.S.
Environmental Protection Agency's Emissions Measurement Center, July-August, 1999.
20. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96/33r2,
Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 4-11.
21. Electronic Mail. From Joseph Somers, U.S. Environmental Protection Agency, Office of
Mobile Sources (OMS) to Chad Bailey (QMS), Pamela Brodowicz (OMS), Rich Cook
(QMS), Betsy McCabe (OMS) and Madeleine Strum (OAQPS), August 12,1999.
22. EPA-AA-AQAB-94-2 Draft Users Guides to PART5: A Program for Calculating Particle
Emissions from Motor Vehicles, February 1995. Table 4, page 66.
23. EPA-452/R-97-005 Mercury Study Report to Congress, Volume III: Fate and Transport
of Mercury in the Environment, December 1997, p. ES-5.
-------
24. 1990 Emissions Inventory of Section 112(c)(6) pollutants; polycylic organic matter
(POM) 2,3,7,8-Tetrachlorodibenzo-p-dioxin, 2,3,7,8-Tetrachlorodibenzo furan,
polychlorinated biphenyl compounds (PCB's), mercury, and alkylated lead, Final Report;
U.S. Environmental Protection Agency, Research Triangle Park, N.C., 1998.
25. Ven den Berg, M.; Bimbaum, L.; Bosveld, A.; et.al. "Toxicity Equivalence Factors
(TEFs) for PCBs, PCDDs, PCDFs for Humans and Wildlife", Environ. Health Persp.
1998, 106(12), 775-792.
26. Electronic Mail. From Robin Segall, U.S. Environmental Protection Agency, OAQPS Air
to Madeleine Strum (OAQPS), September 1,1999.
27. Rosenbaum, A.S.; Ligocki, M.P.; Wei, Y.H. "Modeling Cumulative Outdoor
Concentrations of Hazardous Air Pollutants, Volume 1: Text"; SYSAPP-99-96/33r2,
Prepared for U.S. Environmental Protection Agency, Office of Policy, Planning and
Evaluation, by Systems Applications International, Inc., San Rafael, CA. 1998, pp. 4-11.
28. Fratt, D.B.; Mudgett, D.F.; Walters, R.A. The 1985 NAPAP Emissions Inventory:
Development of Temporal Allocation Factors. EPA-600/7-89-01 Od, U.S. Environmental
Protection Agency, Research Triangle Park, NC. April 1990.
29. Moody, T.; Winkler, J.D.; Wilson, T.; Kirsteter, S. The Devlopment and Improvement of
Temporal Allocation Factor Files. EPA-600/R-95-004. U.S. Environmental Protection
Agency, Research Triangle Park, NC. January 1995.
30. Janssen, Mark. EMS-95 User's Guide. Lake Michigan Air Directors (LADCo).
(http://www.ladco.org/emis.guide/ems95.html). August 1998.
31. Causley, M.C.; Fieber, J.L.; Jiminez, M.; Gardner, L. User's Guide for the Urban Airshed
Model, Volume IV: User's Manual for the Emissions Preprocessor System, U.S.
Environmental Protection Agency, Research Triangle Park, NC, 1990; EPA-450/4-90-
007D.
32. Federal Aviation Administration APO Data System, http://www.apo.data.faa.gov
(accessed June 7, 1999).
33. United States Census Bureau Home Page, http://www.census.gov (accessed February
1999).
34. United States Census Bureau, http://www.census.gov/geo/www/tiger/t92top.html
(accessed February 1999).
3 5. Land Use and Land Cover Digital Date From 1:250,000- and 1:100,000-Scale Maps,
Data Users Guide 4. U.S. Department of the Interior, U.S. Geological Survey, Reston,
VA, 1990.
-------
36. Email from Chad Bailey, U.S. U.S. Environmental Protection Agency, Office of
Transportaion and Air Quality (OTAQ) to Rich Cook (OTAQ) and Pamela Brodowicz
(OTAQ), June 8, 1999.
37. Email from Chad Bailey, U.S. Environmental Protection Agency, Office of Transportaion
and Air Quality (OTAQ) to Madeleine Strum, U.S. Environmental Protection Agency,
Office of Air Quality Planning and Standards, July 21, 1999.
38. User's Guide: Assessment System for Population Exposure Nationwide (ASPEN,
Version 1.1) Model. EPA-454-R-00-017, U.S. Environmental Protection Agency,
Research Triangle Park, NC. March 2000.
-------
TECHNICAL REPORT DATA
(Please read Instructions on reverse before completing)
1. REPORT NO.
EPA-454/R-00-018
4 TITLE AND SUBTITLE
USER'S GUIDE FOR THE EMI£
HAZARDOUS AIR POLLUTANTS
2.
JSIONS MODELING SYSTEM FOR
(EMS -HAP, Version 1.1)
7. AUTHOR(S)
9. PERFORMING ORGANIZATION NAME AND ADDRESS
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Prc
Office of Air Quality
Emissions, Monitoring
Research Triangle Park
tection Agency
Planning and Standards
& Analysis Division
, NC 27711
3. RECIPIENT'S ACCESSION NO.
5. REPORT DATE
October 2000
6. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT
NO.
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
EPA Contract No.
68D98006
13. TYPE OF REPORT AND PERIOD COVERED
Final Report
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
EPA Work Assignment Manager: Madeleine L. Strum
16. ABSTRACT
This user's guide provides documentation for the Emissions Modeling System for
Hazardous Air Pollutants (EMS-HAP, Version 1.1), also referred to as EMS-HAP. ' It
describes the EMS-HAP program functions and ancillary files, and it provides the user
instructions for running the model. In addition, Appendix D discusses how the EMS-HAP
ancillary files were developed, and how EMS-HAP was run to process the 1996 National
Toxics Inventory for a national air toxics assessment. The Emissions Modeling System
for Hazardous Air Pollutants is an emissions processor for the Assessment System for
Population Exposure Nationwide (ASPEN, Version 1.1) model. It performs the steps
needed to process an emission inventory for input into ASPEN, Version 1.1. These steps
include: spatial allocation of area and mobile source emissions from the county level
to the census tract level, and temporal allocation of annual emission rates to annually
averaged (i.e. same rate for every day of the year) 3-hour emission rates. In
addition, EMS-HAP can project future emissions, by adjusting point, area and mobile
emission data to account for growth and emission reductions resulting from emission
reduction scenarios such as the implementation of the Maximum Achievable Control
Technology (MACT) standards. ^
KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
Air Pollution
Emission Models
Emission Processing
Hazardous Air Pollutants
National Toxics Inventory
National Air Toxics Assessment
Air Toxics
18. DISTRIBUTION STATEMENT
Release Unlimited
b. IDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (Report)
Unclassified
20. SECURITY CLASS IPage)
Unclassified
c. COSATI Field/Group
21. NO. OF PAGES
3%G
22. PRICE
IPX Form 2220-1 (Rev. 4-77)
PREVIOUS EDITION, Ifi OBSOLETE.
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