VOLUME III: CHAPTER 1
INTRODUCTION TO AREA SOURCE
EMISSION INVENTORY
DEVELOPMENT
Revised Final
January 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
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DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
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ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee of
the Emission Inventory Improvement Program and for Charles Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency. Members of the Area
Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
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CONTENTS
Section Page
1 Introduction 1.1-1
1.1 Overview of Volume 1.1-2
1.2 Definition of Area Sources 1.1-3
2 Inventory Planning 1.2-1
2.1 Defining the Scope 1.2-3
2.2 The QA Program 1.2-7
2.3 Emission Estimation Methods 1.2-9
2.4 Documentation 1.2-10
2.5 Data Collection/Management 1.2-11
3 Emission Estimation Approaches 1.3-1
3.1 Extrapolating from a Sample or other Database 1.3-3
3.2 Material Balance Method 1.3-5
3.3 Mathematical Models 1.3-6
3.4 Emission Factors 1.3-6
3.4.1 Emission Factor Accuracy 1.3-8
3.4.2 Emission Factor References 1.3-8
3.4.3 Updating Emission Factors 1.3-11
3.4.4 Emission Factor Calculations 1.3-11
4 Adjustments to Emission Estimates 1.4-1
4.1 Accounting for Point Source Emissions 1.4-1
4.2 Control, Rule Effectiveness and Rule Penetration 1.4-5
4.2.1 Control Efficiency 1.4-5
4.2.2 Rule Effectiveness 1.4-5
4.2.3 Rule Penetration 1.4-6
4.2.4 Example Showing Application of CE, RP, and RE 1.4-6
4.2.5 Temporal Adjustments 1.4-8
4.2.6 Seasonal Activity 1.4-9
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CONTENTS (CONTINUED)
Section Page
4.2.7 Activity Days per Week 1.4-10
4.2.8 Calculations for Temporal Adjustments 1.4-10
4.3 Spatial Allocation 1.4-16
4.4 Applying Growth Factors for Projections 1.4-21
5 Data Collection and Management 1.5-1
5.1 Data Collection and Storage 1.5-1
5.1.1 Data Resources 1.5-1
5.1.2 Data Handling 1.5-2
5.1.3 Data Storage 1.5-6
5.1.4 Necessary Data Elements 1.5-7
5.1.5 Special Issues 1.5-7
5.1.6 National Emissions Inventory (NEI) Input 1.5-8
5.2 Surveys 1.5-8
6 Inventory Quality and Uncertainty 1.6-1
6.1 QA/QC Procedures for Area Source Inventories 1.6-1
6.2 QA/QC for Inventory Calculations 1.6-6
6.3 Uncertainty in Area Source Inventories 1.6-7
6.4 Variability 1.6-10
6.5 Parameter Uncertainty 1.6-10
6.6 Model Uncertainty 1.6-11
7 References 1.7-1
VI EIIP Volume III
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FIGURES AND TABLES
Communication and Information Sharing During Inventory Preparation .
Example Decision Tree for Choosing an Estimation Methodology
Page
. 1.2-2
. 1.3-4
Figures
1.2-1
1.3-1
1.6-1 Internal Source Category Consistency and Accuracy Quality Control
Checks 1.6-2
Tables Page
1.2-1 Potential Area Sources of Ozone Precursor Emissions 1.2-5
1.3-1 Emission Estimation Models Useful for Area Sources 1.3-7
1.4-1 Source Categories that may have Area and Point Source Contributions .... 1.4-2
1.4-2 Examples of Area VOC Source Categories Requiring Special
Consideration when Calculating Emissions 1.4-8
1.4-3 Area Source Seasonal Activity Factors and Days per Week for the Peak
Ozone and CO Seasons 1.4-11
1.5-1 Activity Data Example Sources for Ozone Inventory 1.5-3
1.6-1 Sources of Uncertainty in Area Source Emission Estimates 1.6-8
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ABBREVIATIONS AND ACRONYMS
ABBREVIATIONS
ACT Alternative Control Techniques
AFS AIRS Facility Subsystem
AIRS Aerometric Information Retrieval System
AMS AIRS Area and Mobile Subsystem
BE A Bureau of Economic Analysis
BID background information document
CAAA Clean Air Act Amendments of 1990
CAS Chemical Abstract Services
CD-ROM compact disc read-only memory
CE control efficiency
CHIEF Clearinghouse for Inventories and Emission Factors
CO carbon monoxide
CO2 carbon dioxide
CTC Control Technology Center
CTG Control Techniques Guidelines
DOT Department of Transportation
DQOs Data Quality Objectives
EFIG Emission Factor and Inventory Group
EIA Energy Information Administration
EIIP Emission Inventory Improvement Program
EIQA emission inventory quality assurance
EPA U.S. Environmental Protection Agency
FIRE Factor Information Retrieval System
FTP file transfer protocol
GIS Geographical Information System
GPO Government Printing Office
HAPs hazardous air pollutants
ID identification
L&E Locating and Estimating
LAEEM Landfill Air Emissions Estimation Model
MACT maximum achievable control technology
MPO metropolitan planning organization
MSA metropolitan statistical area
NAPAP National Acid Precipitation and Assessment Program
NOX nitrogen oxides
NPDES National Pollutant Discharge Elimination System
OAQPS Office of Air Quality Planning and Standards
Vlll
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ABBREVIATIONS AND ACRONYMS
(CONTINUED)
ORD Office of Research and Development
PM paniculate matter
POTW publicly owned treatment works
PSD Prevention of Significant Deterioration
QA quality assurance
QC quality control
RE rule effectiveness
ROP rate of progress
RP rule penetration
SAP seasonal activity factor
SAMS SIP air pollutant inventory management system
SARA Superfund Amendments and Reauthorization Act
SCC source classification code
SIC standard industrial classification
SEVIS Surface Impoundment Modeling System
SIP State Implementation Plan
SSCD Stationary Source Compliance Division, now Office of Enforcement and
Compliance Assurance (OECA)
TRIS Toxic Release Inventory System
TSD Technical Support Documents
TSDF treatment, storage, and disposal facility
U.S. United States
USD A U.S. Department of Agriculture
VMT vehicle miles traveled
VOCs volatile organic compounds
XATEF Crosswalk/Air Toxic Emission Factor Database
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use ofEIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
Emissions from area sources are an important component of regional air pollution inventories.
With the passage of the Clean Air Act Amendments (CAAA) in November 1990, the need for
specific and standardized procedures for the preparation of area source inventories has
increased. Over the years, the United States (U.S.) Environmental Protection Agency (EPA)
Office of Air Quality Planning and Standards (OAQPS) has established several standard
procedures for the preparation of State Implementation Plan (SIP) emission inventories. The
Emission Inventory Improvement Program's (EIIP's) Area Sources Committee has sought to
update and expand the EPA guidance through the development of this guidance document. The
objectives of Volume in, Area Sources, are to:
• Establish standard procedures for the preparation of area source emission
inventories;
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CHAPTER 1 - INTRODUCTION 7/37/07
• Present preferred and alternative methods for estimating emissions from selected
area source categories; and
• Describe new and innovative emission estimation methods in addition to methods
that have been commonly used.
1.1 OVERVIEW OF VOLUME
This chapter describes the process of planning and developing an area source inventory.
Fundamental emission estimation approaches for area sources as well as data management,
quality assurance, and documentation requirements are described. Subsequent chapters present
preferred and alternative methods for specific area source categories, and include new and
innovative estimation methods whenever they are available. Methods chapters in this volume
describe and recommend procedures for estimating emissions from an area source category.
Each methodology chapter is divided into eight sections.
In this chapter:
• Section 1 outlines the contents of this chapter and defines the area source
category.
• Section 2 describes the planning process involved in developing an inventory.
• Section 3 provides an overview of available emission estimation approaches.
Section 4 provides details on how to make adjustments to the emission estimates,
and
Section 5 discusses data management.
• Section 6 discusses the quality and uncertainty associated with each method.
• Section 7 is the reference section.
In addition, technical abstracts providing limitated amounts of information are available for
downloading from the EIIP Website www.epa.gov/ttn/chief/eiip. When it was recognized that
inventory preparers needed assistance with a particular source category, yet limited information
existed, that information was compiled into a brief technical document describing the category
and how to estimate emissions. These documents are called abstracts.
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7/37/07 CHAPTER 1 - INTRODUCTION
1.2 DEFINITION OF AREA SOURCES
An area source may be defined as a collection of similar emission units within a geographic
area. Commonly, area sources have been defined at the county level, and most area source
methods are designed to estimate area source emissions at the county level. However, any
specified area (e.g., city, town, or census division) could be used to define an area source.
User-defined areas such as grid cells or polygons could also be used.
Area sources collectively represent individual sources that are small and numerous, and that
have not been inventoried as specific point, mobile, or biogenic sources. Individual sources are
typically grouped with other like sources into area source categories. These source categories
are grouped in such a way that they can be estimated collectively using one methodology. For
example, gasoline stations and dry cleaning establishments are often treated as area sources.
The main reason not to treat them as point sources is that the effort required to gather data and
estimate emissions for each individual facility is great although emissions per facility are
generally small. For these sources, the distinction between point and area is usually defined by a
cutoff point typically based on annual emissions. SIP ozone inventories, for example, define
volatile organic compound (VOC) point sources as individual facilities emitting more than
10 tons of VOCs per year. Emissions from smaller facilities are treated as an area-source group.
True area-wide sources, such as pesticide use and commercial/consumer product use, are
examples of this source type. The boundaries of the individual activities associated with these
sources are often hard to determine or are, at best, arbitrary. Even within a point source facility,
some activities occur that are more easily treated as area source emissions. Some emissions
associated with surface coating operations such as equipment cleaning, for example, can be
more practically estimated using area source methods even though other surface coating
emissions may be reported as part of the point source inventory.
The main distinction between point and area sources is the methodology used to estimate
emissions. Point sources are inventoried individually, and area sources are inventoried
collectively. While all stationary sources could be treated as either point sources or area
sources, for practical reasons some cutoff is usually set to distinguish between them. The end
use of the inventory, the desired accuracy of the emissions, and the resources available for
inventory development all affect where that cutoff is set. Volume in of this EIIP series provides
guidance for area source emissions estimation methods for many common area source processes.
The term "process" is used here to name an operation or activity that produces emissions. Area
sources include the following broad groups of processes:
• Commercial and consumer organic solvent usage (surface coating, dry cleaning,
degreasing, graphic arts, rubber and plastics);
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CHAPTER 1 - INTRODUCTION 7/37/07
• Stationary fuel combustion (heating, including waste oil combustion);
• Material storage and distribution;
• Waste treatment and disposal;
• Miscellaneous industrial manufacturing operations;
• Comfort and industrial cooling towers;
• Miscellaneous sources (agricultural/forest burning, structure fires, mining or
construction, for example);
• Gasoline service stations; and
• Hospital and laboratory sterilizers.
Each of these broad groups of processes contain a number of more specific groups that share
similar emission processes and emission estimation methods.
Although mobile and biogenic sources could be inventoried as area sources, specialized methods
have been developed for these categories. These methods are described in EIIP Volumes IV and
V, respectively.
Finally, in this volume of EIIP documents, ozone precursors and the criteria pollutant particulate
matter (PM) are emphasized. Where it was possible, emission factors or speciation profiles for
other criteria pollutants, hazardous air pollutants (HAPs), and greenhouse gases were included.
However, the lack of information for other pollutants in these methodologies should not be
construed to mean that a source does not emit those pollutants.
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INVENTORY PLANNING
Thorough planning at the beginning of the inventory development process is essential for the
efficient development of sound emissions inventories. An essential part of the area source
inventory planning process is to coordinate complementary point, mobile, and biogenic
inventory activities to ensure that overall inventory requirements are met. The overall role of
planning is discussed in some detail in Volume I of this series {Introduction to Area Source
Emission Inventory Development, July 1997); the role of planning in the quality assurance (QA)
program is described in Volume VI (Chapter 2). This section concentrates on issues relevant to
area source inventories.
Figure 1.2-1 provides an overview of inventory planning and information flow at a typical
agency. Note that the area source inventory group has more interactions with other groups than
any other inventory group. Therefore, it is essential that the area source inventory team:
• Identify other departments or agencies that need to be contacted for inventory
information;
• Define the role that the departments or agencies will have, and communicate their
role clearly before work begins;
• Ensure that the other departments or agencies are aware of procedural and
documentation requirements before work begins; and
• Identify points of contact in each department.
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CHAPTER 1 - INTRODUCTION
1/31/01
Federal, State, Local Agency
Determine scope
and objectives
of inventory
Set data
quality objectives
Prepare inventory
work/QA plan
Prepare
inventory
External Organizations
Inventory planning & development
Requests for Information
Information supplied
FIGURE 1.2-1. COMMUNICATION AND INFORMATION SHARING
DURING INVENTORY PREPARATION
1.2-2
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The flow chart emphasizes the importance of good communication both among members of the
inventory staff as well as between different agencies and individuals. Careful planning will
facilitate good communication. The activities associated with the planning process can be
classified into five general groups:
• Defining the scope of the inventory including the pollutants, geographic
boundaries, sources, and end uses;
• Planning the quality assurance and control activities and documenting them in a
QA plan;
• Choosing the appropriate methods for calculating emissions and identifying the
data needed;
• Identifying the appropriate types and comprehensiveness of the documentation
and preparing an inventory work plan; and
• Developing a plan for collecting and managing the data.
Many of these activities are performed by personnel outside of the area source inventory group
or are provided by others at the beginning of inventory development. Specific area source
inventory concerns within each of these groups are described in the remainder of this section.
2.1 DEFINING THE SCOPE
The overall inventory planning process should result in defining the end uses for the data, the
data quality objectives (DQOs) for the pollutants of interest, the geographic area to be
inventoried, and the appropriate spatial and temporal resolutions of the data. The next steps in
defining the area source inventory scope are to identify source categories to be inventoried and
to ensure that the area source inventory will completely cover sources that are not being
inventoried as point, mobile, and biogenic sources. Then the sources that will be included in the
inventory should be prioritized to facilitate efficient allocation of resources.
To determine which area sources to include:
• Compile a comprehensive and exhaustive list of sources from guidance
documents, other inventories, business directories, EPA guidance, and any other
information on emissions activities in the inventory area;
• Prioritize the list based on the expected magnitude of emissions or some other
measure of importance;
• Review the list carefully and eliminate any sources that are not relevant or are
insignificant sources in the inventory region; and
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CHAPTER 1 - INTRODUC TION 1/31/01
• Define and develop a good understanding of the process and industries that make
up the source.
Table 1.2-1 gives an example list of potential area source categories for a state's ozone precursor
inventory. Early in the process, the inventory preparers should eliminate any sources that are not
found within the inventory area. For example, volcanoes and geysers are rarely of concern in
most states. However, it is not always possible to determine the applicability of a source
without some research. The initial list should, therefore, be as comprehensive as possible so that
no source is overlooked.
Sources should be prioritized based on their importance in the inventory. The agency's
resources should be allocated preferentially to the sources that are most important for meeting
the inventory objectives. The sources can be prioritized by checking previous or other agencies'
inventories to identify the largest-emitting area sources. Alternatively, the end-users may
specify the sources that are most important to them. High-priority sources will include those
that are:
• Known or inferred significant contributors;
• Regulated sources;
• Sources under consideration for future regulation;
• Sources of specific, targeted pollutants (e.g., photochemically reactive VOCs);
and
• Sources most likely to impact human health.
If the source list is prioritized on the basis of the largest area-source emitters, information from a
previous inventory may be used. An example of a prioritized list is shown in Example 1.2-1.
2.2 THE QA PROGRAM
Before any area source emission calculations take place, data collection, data handling, emission
reporting, and documentation procedures should be carefully planned. Volume VI of this series
provides detailed discussions on general QA issues for planning and documentation of
inventories. This section will focus on the planning issues, including QA planning, that
specifically pertain to area source inventories.
An essential component of planning is the development of a QA plan that specifies all QA and
quality control (QC) procedures to be followed in preparing the inventory. Early in the planning
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CHAPTER 1 - INTRODUCTION
TABLE 1.2-1
POTENTIAL AREA SOURCES (BY EPA TRENDS TIER 1 CODE)
OF OZONE PRECURSOR EMISSIONS
Category (Tier 1 Code)
PM
voc
NOX
CO
HAPs
NH3
Fuel Combustion - Electric Utility (01)
Internal Combustion
/
/
/
/
/
Fuel Combustion - Industrial (02)
Coal
Gas
Internal Combustion
Oil
Other
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Fuel Combustion - Other (03)
Commercial/Institutional Coal
Commercial/Institutional Gas
Commercial/Institutional Oil
Residential Wood
Residential Other
Miscellaneous Fuel Combustion except
Residential
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Chemical and Allied Products Manufacturing (04)
Inorganic Chemicals
Organic Chemicals
Pharmaceuticals
Polymers and Resins
/
/
/
/
/
/
/
/
Metal Processing (05)
Ferrous Metals
Nonferrous Metals
Metals Processing NEC
/
/
/
/
/
/
/
/
/
/
/
Petroleum and Related Industries (06)
Asphalt Manufacturing
Oil and Gas Production
Petroleum Refineries and Related Industries
/
/
/
/
/
/
/
/
/
/
/
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CHAPTER 1 - INTRODUCTION
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TABLE 1.2-1
(CONTINUED)
Category (Tier 1 Code)
PM
voc
NOX
CO
HAPs
NH3
Other Industrial Processes (07)
Agricultural, Food, and Kindred Products
Machinery Products
Mineral Products
Rubber and Miscellaneous Plastic Products
Wood, Pulp and Paper, and Publishing Products
Construction
Miscellaneous Industrial Processes
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Solvent Utilization (08)
Degreasing
Dry Cleaning
Graphic Arts
Nonindustrial
Other Industrial
Surface Coating
Solvent Utilization NEC
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Storage and Transport (09)
Bulk Terminals and Plants
Organic Chemical Storage
Petroleum and Petroleum Product Storage
Petroleum and Petroleum Product Transport
Service Stations: Breathing and Emptying
Service Stations: Stage I
Service Stations: Stage II
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Waste Disposal and Recycling (10)
Incineration
Industrial Waste Water
Landfills
Open Burning
POTWs
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
1.2-6
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CHAPTER 1 - INTRODUCTION
TABLE 1.2-1
(CONTINUED)
Category (Tier 1 Code)
TSDFs
Other
PM
voc
/
/
NOX
/
CO
/
HAPs
/
/
NH3
Natural Sources (13)
Biogenic
Geogenic, Wind Erosion
/
/
/
/
/
/
Miscellaneous (14)
Agriculture and Forestry
Other Combustion (Structure Fires, Forest Fires,
Slash Burning, Prescribed Burning, Managed
Burning)
Catastrophic/ Accidental Releases
Health Services
Agricultural Crops (Tillage)
Paved Roads
Unpaved Roads
Other Fugitive Dust (e.g., Mining and Quarrying)
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
References: EPA. 1999. Emissions Inventory Guidance for Implementation of Ozone and Paniculate Matter
National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina.
EPA. 2000. National Air Pollutant Emission Trends, 1900-1998. U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina.
PM
VOC
NOX
CO
HAP
NH3
Paniculate matter
Volatile organic compounds
Nitrogen oxides
Carbon monoxide
Hazardous air pollutant
Ammonia
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CHAPTER 1 - INTRODUC TION 1/31/01
Example 1.2-1
Based on summaries of data submitted for the CAAA-mandated 1990 SIP VOC
inventories, the following area sources reported in the Aerometric Information
Retrieval System (AIRS) Area and Mobile Subsystem (AMS) are responsible
for 90 percent of the VOCs from area sources:
• Architectural surface coating
• Gasoline service stations
• Consumer solvents
• Degreasing
• Auto refinishing
• Commercial pesticide application
• Industrial surface coating
• Graphic arts
• Dry cleaning
• Traffic marking
• Residential fuel use
* Open burning
• Managed burning and forest wildfires
Many of the above categories have subcategories that contribute to the total.
process, the area source inventory developers may be asked to specify estimation methods or QC
procedures that will ensure that the inventory meets its DQOs. The agency should also include a
discussion in the QA plan that addresses how QC checks will be used for the different emissions
estimation methods. The inventory documentation should also clearly describe the QA and QC
procedures, checks, and results. QA activities for a particular emissions estimation method may
include a detailed review of the data sources, documentation of procedures, and the development
of specific QC checks, such as verifying emissions calculations. Examples of QC checks can be
found in Chapter 3 of EIIP Quality Assurance Procedures (Volume VI) and in Section 6 of this
chapter.
The best possible emissions estimation method to use for a particular source can vary depending
on the source category and local conditions. Within each source category, several estimation
methods and emission factors may be available. The agency should identify in the inventory
work plan the procedures it will use to ensure that the methods and emission factors used are the
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best choice considering the DQOs, the constraints on the inventory, and the priority of the
source. The agency should identify the requirements for each method, including time frame,
funds, data, and the availability of experienced personnel available for inventory preparation.
In planning the QA/QC program for area sources, the following elements should be considered:
• Ensure that double counting does not occur;
• Determine if temporal adjustment to emissions were done appropriately;
• Determine how the peak seasons for the inventory pollutants were defined; and
• Determine how emissions will be projected and the projection period, including
end year and intermediate years for projection inventories.
Double counting is an especially important issue for area sources. It is caused by overlaps
between inventoried area source categories, or overlaps between area source and point source
categories. For example, emissions from large dry cleaners (major point sources) are included in
an inventory. Emissions from small dry cleaners (below some specified cutoff) have been
treated as an area source using a top-down estimation approach. The area source inventory must
be adjusted downward by subtracting the major source contributions to avoid double counting.
Double counting leads to inaccuracies in the final inventory and should be avoided.
The inventory work plan needs to identify and eliminate potential double counting of emissions
with the following steps:
• Identify categories that have a point source component. The area source activity
must be adjusted to account for point source activity in order to avoid double
counting emissions; and
• Identify potential overlap among area source categories and document how to
avoid it.
The QA plan should include procedures to ensure that these specified steps were done correctly.
2.3 EMISSION ESTIMATION METHODS
Emission estimation methods should be determined for each source during the planning phase.
The choice of methods will be based on a number of factors, including agency resources, source
category priority, and the information needs of the inventory. The preferred methods specified
in this volume will yield a higher-quality estimate of emissions and should be used when a
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source is ranked as a high priority or when a specific local characteristic would skew the results
obtained from an alternative method. In contrast, alternative methods usually will yield lower-
quality estimates of emissions and are best used for source categories that are not highly
prioritized.
For each area source category, the rationale for the method used should be stated in the work
plan. This can be as simple as stating that the preferred method is from EIIP Area Source
Preferred and Alternative Methods guidance. More explanation is warranted if the method used
deviates from the preferred method. If alternative emission factors or activity data are available,
the reason for using the factors or data chosen should be stated in the work plan. Similarly, any
assumptions used in developing the activity data or emission factors should also be clearly
stated.
Area sources subject to regulatory controls should be identified in the inventory planning
process so that the appropriate control information will be collected. Control information may
include the portion of the category affected by the regulation (rule penetration), the type of
control, the amount of emissions that are controlled (control efficiency), and the estimated
effectiveness of the control (rule effectiveness). Controls are discussed further in Section 4 of
this chapter.
2.4 DOCUMENTATION
Documentation is an integral part of an emissions inventory, and is of critical importance for
QA/QC activities. All inventory documentation should fulfill some basic requirement. The
guiding principle is reproducibility. It should be possible for anyone reading the document to
reproduce the results. Complete and well-organized documentation will result in a more reliable
and technically defensible inventory. Internal review of the written documentation of an
inventory's data sources and procedures by an agency's QA and technical personnel will uncover
errors in assumptions, calculations, or methods.
More information on the role of QA/QC review of inventory documentation can be found in
Quality Assurance Procedures (Volume VI) of this series. General guidance on documentation
is given in Volume I. Area source inventories rely on more diverse types of data sources than
any other type of inventory. It is very important that all sources be thoroughly documented,
including databases or information from other agencies.
Reporting requirements for inventory data are usually specified by the agency or regulation
requiring the inventory. In general, the data used to develop the input variables should be
supplied if at all possible. For example, where employment in several standard industrial
classification (SIC) Codes is summed to produce the activity parameter, the original
employment data by SIC Code should be shown in an appendix unless prohibited by the size of
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7/37/07 CHAPTER 1 - INTRODUCTION
the data set or confidentiality issues. Alternatively, if the data were derived from a published
data set, the source should be referenced (supplying page and table numbers, if necessary). All
conversion factors used should be explicitly stated.
If models are used in any part of the calculations, the input data used for the model should be
provided. Any statistical analyses should also be clearly documented; the complete data set used
and the output from the statistical analysis should be provided. Similarly, survey results should
be provided in as much detail as possible along with, at a minimum, the survey questionnaire,
the number of facilities surveyed, the percentage responding, and some descriptive statistics of
the results.
Sufficient information should be given to document the completeness of the area source
inventory. Categories excluded should be specified, and the reasons for their exclusion stated.
Some explanation of the process used to identify source categories also must be provided.
In addition to text explaining the process used to develop the inventory, sample calculations
should be provided. This is particularly important for complicated calculations or if several
steps were required to develop the estimates.
Referencing of all data sources and assumptions is part of reproducibility. The sources of all
data, methods, and assumptions should be fully documented. If the source is a person at a
government agency, trade group, or other organization, that person's name, affiliation, and the
date of the contact should be documented, at a minimum. Reports and other documents should
be referenced by author (if known), year, title of document, publishing agency, and location.
Documents published by most government agencies usually have an identifying number that
should be included.
2.5 DATA COLLECTION/MANAGEMENT
To some extent, overall data management decisions are made by personnel who specialize in
data consolidation and transfer, and the final repository of the area source data may not be under
the control of the area source team. However, collection and management of data that will
ultimately become part of the area source inventory are usually under the control of the area
sources staff. Consider the following in planning data collection and management for an area
source inventory:
• Determine the role of existing inventory data and ensure that any previously
omitted data and sources have been identified;
• Select data collection methods that are most appropriate to the estimation
methods; and
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CHAPTER 1 - INTRODUC TION 1/31/01
• Review overall inventory data management system requirements to ensure
compatibility.
An important planning consideration is whether and to what extent information contained in
existing emissions inventories can be used. Existing inventories should be examined to
determine whether the appropriate emission sources have been included and if the emissions
data represent current conditions. Existing inventories serve as a starting point for developing
lists of sources. They also should provide extensive data and support information, such as
documentation of procedures and data ranges for identifying outlier values. Simple sensitivity
analyses of existing inventories can be used to prioritize categories and identify key data needs
(see Section 6, Sensitivity Analysis, in Chapter 3 of Volume VI of the EIIP series).
The data for a new inventory may or may not be available from a previous inventory in the
correct level of detail depending upon the objectives and degree of success of prior inventory
efforts. Even though some data are not required in the basic inventory, an agency may find it
expedient to collect additional information as part of a routine update of the inventory. If the
agency anticipates the need for special data (for use in a photochemical model, for instance) it is
more efficient to collect that data at the same time as the required data for the basic inventory.
Any needs or restrictions of the data management system should be identified in the planning
phase and compared to the form of the information produced by the various emission estimation
methods. The data management system will be used to store inventory information and to
transfer the information to other users, such as photochemical modelers, so the further uses of
this information should be considered. Issues of particular concern for area sources are
mismatches in source identification codes, units, or levels of detail, and incompatibility between
the data management system's data input formats and the format of the data generated by the
area source estimation method. An example of the latter is when emissions are estimated using
a computer model, but the data management system uses an emission factor and activity data.
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EMISSION ESTIMATION APPROACHES
Emissions from area sources are nearly always estimated using some type of calculation
procedure. Direct measurement of area source emissions is hardly ever practical because of
technical and cost considerations. This section describes the methods that are commonly used to
estimate area source emissions. There are four basic approaches for developing an area source
emission estimate:
• Extrapolation from a sample set of the sources (surveys, permit files, or other
databases);
• Material balance method
• Mathematical models; and
• Emission factors applied to activity levels. Detailed descriptions of emission
estimation methods and example calculations for specific area sources are
included in the following chapters of this volume.
As described in the previous section, an emission estimation approach should be chosen during
the inventory planning phase and depends on inventory objectives, available resources
(including availability of quality data needed), source category priority, intended use of the
inventory, and the available methods for a source. Information needed for choosing emission
estimation approaches is:
• The source's ranking in the prioritization scheme (see Section 2.1);
• The schedule for completing the inventory and the resources available;
• The level of detail needed (based on current or future regulations, knowledge
about local differences, modeling and data storage needs, etc.); and
• Descriptions of the source categories and the methods that can be used to estimate
emissions from them.
A list of decisions for choosing among area source methodologies is shown in Example 1.3-1.
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CHAPTER 1 - INTRODUC TION 1/31/01
Example 1.3-1
• Identify the priority sources for the inventory area;
• Assign resources based on prioritization of the sources;
• Investigate possible emission estimation methods for area sources;
Reject methods that obviously cannot be used (e.g., using a
mathematical model or permit information for architectural surface
coating).
• Compare the needs of the inventory with the information that the available
methods produce;
The method calculates the pollutant at the required level of detail in
terms of speciation, and temporal or spatial allocation; and
The method results reflect economic or regional differences that
would affect emissions, (e.g., if the inventory area is mostly high-
density housing with a lower than average per capita architectural
coating use).
• Consider subcategorizing sources and using different methods for the
subcategories;
Subcategorization of a source may allow more detailed estimation of
the most significant portion of a source, and may be the most
efficient way to achieve inventory goals of more accurate emission
estimates, more detailed inventory information, or other quality goals
that improve the estimate.
• If available methods vary in the amount of resources that they require, rank
them according to the amount of resources that they need. Determine if the
increase in needed resources is justified by an increase in accuracy or detail.
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3.1 EXTRAPOLATING FROM A SAMPLE OR OTHER DATABASE
For many area sources, the EIIP preferred approach is to extrapolate from a sample set of data
for the industry/activity to the entire population. This often requires a survey of a statistically
valid sample set, but sometimes existing data sets can be used as a starting point. An agency
may have files or databases that can be accessed for use in emissions inventory development.
Permits are typically required for construction, startup, and modifications of an emission source.
Permit applications generally include enough information about a potential source to describe
the nature of the source and to estimate the magnitude of emissions that will result from its
operations. Some permits also include source test data. These files are often used for point
sources but may include information that is useful for area source estimation as well.
Permits for emissions of pollutants not included in a particular inventory can also be useful.
Permits for emissions of air toxics may be useful to identify or characterize sources of VOCs,
for example. Rules unrelated to air emissions may be useful if they require facilities to report
information that could be used in the inventory. Title V permits, solid waste permits, and
National Pollutant Discharge Elimination System (NPDES) permits could be useful sources of
information. A category may be subdivided to use information where available and use another
approach for the remaining sources.
If an agency has previously estimated emissions based on a survey of the industry, those data can
sometimes be used to estimate emissions for the newer inventory. This may be as simple as
applying a growth factor to the emissions, or it may require further adjustments to account for
other changes in the industry. If possible, a survey of a representative cross-section of the
sources should be used to update information. For example, more sources may be controlled
than were previously, new types of controls may be in use, or processes may have changed.
For some source categories, an industry-wide survey may be warranted. If the category
represents a significant proportion of emissions, has the potential for further controls, or is
poorly characterized by other methods, the agency should consider surveying the population of
sources. If this includes a very large number of facilities, a statistically valid sampling method
can be used. Figure 1.3-1 illustrates the decision-making process that might be followed to
arrive at this method.
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3 I
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spend on this?
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of total?
Use emission
factor
Done
Do you have
data* that
can be used to
develop
an adequate
estimate?
Use emission
factor
Done
Do you have
sufficient resources
to conduct a
survey (at least for
a representative
sample)?
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'Data includes:
• surveys from previous years
• permit or fee inventory data
• industry-wide surveys
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3.2 MATERIAL BALANCE METHOD
An agency can, in some cases, use a material balance technique to develop emission factors or
total emissions for an inventory period. For some sources, a material balance is the only
practical method of estimating VOC emissions; it also can be the most accurate, especially when
the balance covers the entire inventory period, and the nonair losses are small or easily
quantified. Source testing of low-level, intermittent, or fugitive VOC exhaust streams can be
difficult, costly, and highly variable in many instances. Emissions from these and other solvent
evaporation sources are most commonly determined by the use of material balances.
Use of material balances involves the examination of a process to determine whether emissions
can be estimated solely upon knowledge of operating parameters, material compositions, and
total material usage. The simplest material balance assumes that all solvent used in a process
will evaporate to become air emissions somewhere at the facility. For instance, for many
surface coating operations, it can be assumed that all of the solvent in the coating evaporates to
the atmosphere during the application and drying processes. In such cases, emissions equal the
amount of solvent contained in the surface coating plus any added thinners and cleanup solvents.
Material balances are greatly simplified and very accurate in cases where all of the consumed
solvent is emitted to the atmosphere. But many situations exist where a portion of the
evaporated solvent is captured and routed to a control device such as an afterburner (incinerator)
or condenser. In these cases, the captured portion must be measured or estimated by other
means and the disposition of any recovered material must be accounted for. As a second
example, in degreasing operations, emissions will not equal solvent consumption if waste
solvent is removed from the unit for recycling or incineration. A third example is where some
fraction of the diluent (which is used to liquify cutback asphalt, for example) is believed to be
retained in the substrate (pavement) rather than evaporated after application. In these examples,
a method of accounting for the nonemitted solvent is required to avoid an overestimation of
emissions.
Material balances cannot be accurately employed at a reasonable cost for some evaporation
processes because the amount of material lost is too small to be determined accurately. As an
example, applying material balances to petroleum product storage tanks is not generally feasible
because the losses are too small relative to the uncertainty of any metering devices. In these
cases, using emission factors or equations from EPA's Compilation of Air Pollution Emission
Factors, Volume I: Stationary Point and Area Sources, commonly referred to as AP-42 (EPA,
1995), is recommended.
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3.3 MATHEMATICAL MODELS
A model may be used to estimate emissions when emissions are not directly related to any one
parameter. A model may be a simple equation, but is typically in the form of a computer
program. This facilitates the processing of a large number of equations and interactions. Data
requirements for models vary, depending on the model. Mathematical models used for
predicting area source emissions attempt to reproduce the "real world" behavior of processes
that generate emissions. A model will incorporate mathematical relationships derived from
experimental data and/or some statistical or advanced computational intelligence technique.
Models that have been thoroughly tested and validated should be capable of estimating area
source emissions to a high level of accuracy. However, when using any model, please
remember that the accuracy of the results will depend on the accuracy of the data entered into
the model and the suitability of the model to the particular emissions source.
Some examples of available emissions models are shown in Table 1.3-1. All of these and other
emission estimation models are available through the Clearinghouse for Inventories and
Emission Factors (CHIEF) website. A detailed summary of these models may also be found in
Volume II, Point Sources, of the EIIP series. See Section 3.4.2 of this chapter for more
information about CHIEF.
3.4 EMISSION FACTORS
One of the most useful tools available for estimating emissions from area sources is the emission
factor. An emission factor is an estimate of the quantity of pollutant released to the atmosphere
as a result of some activity such as combustion or industrial production, divided by the level of
that activity. In most cases, emission factors are expressed simply as a single number, with the
underlying assumption that a linear relationship exists between emissions and the specified
activity level over the probable range of application. Thus, emission factors may be thought of
as simple forms of emission models where there is a direct relationship between emissions and a
single parameter.
An emission factor relates a quantity of an air pollutant to a process parameter, or a surrogate
parameter, so that if the parameter is known, an estimate of emissions can be made. For
example, an emission factor in the form of pounds of VOCs per ton of solvent used in a process
can be used to estimate VOC emissions from a source if the weight of the solvent used is known
or can be determined. In this case, the emission factor and activity are parameters for direct
estimation of emissions from a source. However, area sources sometimes are not easily
estimated by a direct measure of throughput. In that case, an emission factor that is based on a
surrogate measure for activity level such as population or employment in an industry will need
to be devised.
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TABLE 1.3-1
EMISSION ESTIMATION MODELS USEFUL FOR AREA SOURCES
03
Model Name
CHEMDAT8
WATERS
Landfill Air Emissions Estimation
Model (LAEEM)
TANKS, version 2.0
MECHANICAL
WIND
Description/Features
• Estimates VOC emissions from TSDF processes.
• Lotus 1-2-3® spreadsheet.
• Default input parameters provided to demonstrate
calculations.
• Estimates emissions from wastewater treatment
systems.
• Menu-driven computer program.
• Estimates HAP, VOC, methane, and CO2 emissions
from a landfill.
• Computer model.
• Site-specific data can be entered; defaults
(conservative) provided.
• Estimates organic chemical emissions from storage
tanks.
• Variety of tank types included.
• User enters site-specific data; defaults provided.
• Computer model.
• Estimates fugitive PM emissions from roads,
materials handling, agricultural billing, and
construction/demolition.
• Estimates PM emissions from wind erosion.
Contact/Reference
Elaine Manning, EPA Emissions
Standards Division,
(919) 541-5499
Elaine Manning, EPA Emissions
Standards Division,
(919) 541-5499
Susan Thorneloe-Howard, EPA Air
Pollution Prevention and Control
Division, (919) 541-2709
Info CHIEF (MD-14)
United States Environmental
Protection Agency
Research Triangle Park, NC
27711,
Control of Open Fugitive Dust
Sources, EPA-450/3 88-008
Control of Open Fugitive Dust
Sources, EPA-450/3 88-008
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3.4.1 EMISSION FACTOR ACCURACY
Because emission factors are typically averages obtained from data with wide ranges and
varying degrees of accuracy, emissions calculated this way for a given source are likely to differ
from that source's actual emissions. Because they are averages, factors will indicate higher than
actual emissions for some sources and lower than actual emissions for others. Only specific
source measurement can determine the actual pollutant contribution from a source under
conditions existing at the time of the test. For the most accurate emissions estimate, it is
recommended that source-specific data be obtained whenever possible. This is rarely possible
for area sources that represent a collection of sources in an area that are usually individually
small. In an area source inventory, emission factors are appropriately used to estimate the
collective emissions of a number of small individual sources that would be difficult or
impossible to estimate using other methods. If factors are used to predict emissions from new or
proposed sources, an agency should review the latest literature and technology to determine
whether such sources would likely exhibit emissions characteristics different from those of
typical existing sources.
When the information used to develop an emission factor is based on national data, such as a
wide range of source tests or national consumption estimates, the inventory preparer should be
particularly careful with potential local variations. Emissions calculated using national emission
factors may vary considerably from actual values at a specific source or within a specific
geographic area. National emission factors should be used either when no locally derived factor
exists, the local mix of individual sources in the category is similar to the national average, or
the source is a low priority in the inventory.
A locally derived emission factor is preferred when either a national-level emission factor does
not account for local variations or the category is a high priority in the area. These emission
factors are developed either thorough local surveys or measurements, are based on local
consumption for solvent categories, or are adapted from emission information in permits or
another inventory. Typically, the information gathering necessary for developing a local
emission factor can be significant, but the benefits are that the emissions for the source will be
well characterized, and the emission factor or the information used to develop it can be used in
subsequent inventories.
3.4.2 EMISSION FACTOR REFERENCES
The following emission references may also be sources for other information needed for
emission calculations, like VOC speciation, source controls, rule effectiveness and rule
penetration, and fuel loading. Other databases and documents that contain emission factors for
use in inventories are listed in the individual source methodology chapters.
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Factor Information Retrieval (FIRE) System
The EPA's FIRE System is a consolidation of emissions estimation data (factors) for criteria and
HAPs that currently includes the information contained in the EPA databases such as
Crosswalk/Air Toxic Emission Factor (XATEF), the Air Emissions Species Database
SPECIATE, and the AIRS Facility Subsystem (AFS), as well as emission factors from EPA
documents such asAP-42 and the EPA's Locating and Estimating (L&E) series of emission
factor documents. These databases and documents are the basic sources of emission factors that
have been used in the preparation of inventories, as well as economic analyses, permit
preparation for Prevention of Significant Deterioration (PSD) and New Source Review
applications, and other federal, state, and local agency assessments of air pollution sources.
Additional emission factors for FIRE have been collected from the literature, material balance
calculations, and source tests. Each emission factor in FIRE includes information about the
pollutant (Chemical Abstract Services [CAS] numbers and chemical synonyms) and about the
source (SIC Codes and descriptions, and source classification codes [SCCs] and descriptions).
Each emission factor includes comments about how it was developed in terms of the calculation
methods and/or source conditions, as well as the references where the data were obtained. The
emission factor also includes a data quality rating.
The FIRE database is divided into two main sections. One section contains all the emissions
data as described above, as well as any additional data that are collected by the EPA. This
section is called the "Repository Subsystem." The other section will contains only a single
emission factor that is recommended for each source/pollutant combination. This section is
called the "Distribution Subsystem" and is provided to users for loading onto their own
computers or local area network.
The FIRE database has been designed to be very user friendly. Data can be searched in many
different ways and can be downloaded to print or data files, or can be printed in a report format
that is designed by the user. The FIRE database can be downloaded from the EPA's CHIEF
electronic system (see below). FIRE is also available in a compact disc read-only
memory (CD-ROM) form from Air CHIEF (see below).
CHIEF
CHIEF is maintained by the Emission Factors and Inventory Group (EFIG) of EPA's Emissions,
Monitoring and Analysis Division in Research Triangle Park, North Carolina. As a
clearinghouse, CHIEF is the repository of the most up-to-date information on inventories and
emission estimation data, such as emission factors. The original method of relaying this
information to the public was through a newsletter. Currently, CHIEF maintains a site on the
Internet, http://www.epa.gov/ttn/chief
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CHIEF contains all of the AP-42 stationary source volume and draft revisions, the SPECIATE
database, and the L&E series of documents, all of which can be used as sources of emission
factors. CHIEF also contains the models mentioned in this section, the MOBILESa model, and
the AFS database.
Fax CHIEF
Fax CHIEF provides emission calculation information through fax.
Air CHIEF
Air CHIEF is designed to combine parts of the emission estimation information from CHIEF
into CD-ROM. Currently, Air CHIEF includes some data from FIRE, the SPECIATE database,
emission factors from AP-42, and the L&E documents. Copies of the Air CHIEF CD-ROM and
the user's manual are available from the Emission Factor and Inventory Group,
U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711
AP-42
AP-42 compiles source descriptions, process descriptions, emission factors, and control
information for processes resulting in emissions from combustion, waste disposal, solvent
evaporation, industry and manufacturing, agricultural operations, and miscellaneous sources.
AP-42 is a primary reference for the information needed to estimate emissions.
EPA's Emission Factor Inventory Group recently released a major update and expansion of
factors m AP-42, including a more detailed breakout of VOCs and other organic emissions by
compound or compound class, PM, and additional factors for greenhouse gases where data are
available. It is expected that this more detailed breakout of VOCs and other pollutants will
better meet the needs of inventory compilers for generating speciated VOC, HAP, PM and
greenhouse gas emission inventories.
A paper copy of the entire AP-42 can be ordered from the Government Printing Office (GPO),
Box 371954, Pittsburgh, Pennsylvania 15250-7954, Stock No. 055-000-00500-1, $56.00 total.
Telephone orders can be made to (202) 512-1800, and orders by via facsimile to (202)
512-2250. AP-42 can also be found on Air CHIEF. Sections of the AP-42 can be downloaded
from the CHIEF and by using Fax CHIEF. EPA's EFIG develops and maintains the AP-42
series.
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3.4.3 UPDATING EMISSION FACTORS
An updated emission factor may be needed when the rate of emissions from a source has
changed relative to the activity. For instance, if industrial solvent use per employee has been
reduced through the 1980s because of the substitution of water-based products, then an older
employee-based emission factor will not reflect that change. The keys to developing an updated
emission factor are:
• Identify the nature of the change;
• Estimate the amount of change in emissions;
• Apportion the emission factor to reflect the change, and
• Document the reasoning behind the change, the assumptions, and
calculations used.
In the case of the altered solvent use Equation 1.3-1:
New emission factor Current amount of solvent used in the process
Old emission factor Old amount of solvent used in the process
3.4.4 EMISSION FACTOR CALCULATIONS
(1.31)
Part of the appeal of the emission factor method is its simplicity. To calculate emissions, the
activity and emission factor are multiplied. Corrections for rule effectiveness, rule penetration,
and control efficiency, and seasonal adjustments or point source emissions still need to be
applied. The calculation for emissions is shown in Equation 1.3-2:
. . Uncontrolled
Activity
Emissions = . * Emission (1-3-2)
Level
Factor
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ADJUSTMENTS TO EMISSION
ESTIMATES
In the previous section, emission estimation methods were discussed. This section presents
general procedures for refining area source emissions estimates to account for point sources,
emission controls, pollutant speciation, spatial and temporal allocation of emissions, and general
information about projection of emissions estimates. In the simplest case of emissions
estimation, area source emissions are estimated using Equation 1.3-2. In other cases, an
emissions model may be used, which incorporates calculation procedures to account for some or
all of the factors noted above.
Adjustments are needed to make emissions estimates reflect the local conditions that differ in
some way from the average conditions on which an emission factor is based or for which an
estimation model is designed. Adjustments may compensate for regional meteorologic
differences or seasonal activity differences, or they may be used to weight the allocation of
emissions to subdivisions of an area such as counties in a region or grid cells in a modeling
domain. Emission estimates will sometimes need to be corrected to reflect emission controls or
to show the effect of projected growth.
For maximum flexibility, it is desirable to perform these adjustments in separate, independent
steps. This facilitates the ability to calculate emissions for different scenarios (e.g., different
levels of control, different species profiles). Keeping each step separate allows one factor to be
easily changed while all others are held constant. Inventory documentation also benefits from
clear, discrete calculations using factors that are each well defined.
4.1 ACCOUNTING FOR POINT SOURCE EMISSIONS
When a point source inventory and an area source inventory estimate emissions from the same
process, there is the possibility that emissions could be double counted. For example, emissions
from large dry cleaning establishments may be included in the point source inventory.
Emissions from small dry cleaners (below some specified cutoff) may be treated as an area
source. The area source inventory must be adjusted to avoid double counting.
Certain area sources such as consumer solvent use and architectural surface coating do not
require any point source adjustments, but many other source categories should at
least be examined for possible double counting. Examples of area sources that may share
processes with point sources are shown in Table 1.4-1.
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TABLE 1.4-1
SOURCE CATEGORIES THAT MAY HAVE AREA AND POINT SOURCE CONTRIBUTIONS3
Process
Category Examples
AMS Source
Category Codes
Fuel Combustion
Electric Utilities
Industrial Fuel Combustion
21-01-
21-02-
Industrial Processes
Chemicals and Allied Products
Metals Production
Rubber and Plastics
Oil and Gas Production
Mineral Processes, Mining and
Quarrying
Construction/Demolition
Machinery
Petroleum Refining
23-01-
23-03-
23-04-
23-08-
23-10-
23-25-
23-11-
23-12-
23-06
Solvent Utilization
Graphic Arts
Surface Coating
Dry Cleaning
Degreasing
24-25-
24-01-
24-20-
24-15-
1.4-2
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CHAPTER 1 - INTRODUCTION
TABLE 1.4-1
(CONTINUED)
Process
Category Examples
AMS Source
Category Codes
Storage and Transport
Petroleum and Petroleum Product
Storage and Transport
Organic Chemical Storage and
Transport
Inorganic Chemical Storage and
Transport
Rail and Tank Car Cleaning
25-01-
25-05-
25-10-
25-15-
25-10-
25-15-
25-**-***-900
Waste Disposal, Treatment and Recovery
Commercial and Industrial
Incineration
Industrial and Municipal Open
Burning
Wastewater Treatment
TSDFs
Scrap and Waste Materials
Landfills
26-01-
26-10-
26-30-
26-40-
26-50-
26-20-
Miscellaneous Sources
Cooling Towers
Health Services
Firefighting Training
Engine Testing
28-20-
28-50-
28-10-035-
28-10-040-
Common examples based on AIRS source codes are listed. Any category could include point sources.
Coordination between point and area source inventory developers is required to ensure that all sources are
properly accounted for.
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If the potential for double counting exists, the area source emission estimate must be adjusted.
This is best done by subtracting the point source activity from the total activity as shown in
Equation 1.4-1:
Area Source Activity = Total Activity of Source Category - Sum of Point Source Activity (1.4-1)
From Equation 1.4-1, area source activity represents whatever activity is not accounted for as
point source activity. Area source activity is estimated by subtracting out the point source
activity total.
Where area source emissions are calculated using employment data, the employment at the point
sources should be subtracted from the inventory region employment to give the area source
employment. If the exact employment at the point sources is unknown, it can be approximated
using County Business Patterns* Details of this procedure are provided in the relevant area
source category sections of this volume.
If the resulting area source activity is less than zero, the point source data should be reviewed for
errors and any errors found should be corrected. If area source activity is still less than zero,
then the area source activity is assumed to be equal to zero. The geographic area for which this
adjustment is done may have an effect on the results. Subtracting state totals is less likely to
produce negative results than subtracting at the county level, for example, especially if data were
collected at the state level. Often, the county-level data used for each source has been allocated
to counties using a surrogate. Thus, the county-level data are less reliable.
Sometimes the activities used to calculate point and area source emissions for the same category
are not similar. Emissions from area sources are often estimated using surrogate activity factors,
such as population, while for the comparable point sources direct measurement or direct activity
applied to several emission factors may be used. The area source emission factor may also be
combined with activity data in order to estimate total uncontrolled emissions (for point as well
as area sources). This results in emissions estimates for total uncontrolled emissions (developed
using the area source emission factor) plus the emissions calculated for the point sources using
point source methods. In these cases, total and point source uncontrolled emissions can be used
to estimate the contribution of uncontrolled area sources as Equation 1.4-2 shows:
UAEA =
A
Total
Uncontrolled
Emissions
Uncontrolled
Point Source
Emissions
(1.4-2)
a See the most recent publication, which can be obtained from the U.S. Bureau of Census,
Department of Commerce, Washington, D.C.
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where:
UAEA = uncontrolled area emissions of pollutant A
Please note that this equation takes into account the difference in the level of control between
area and point sources. When activity levels are adjusted for their point source components
before area source emissions are calculated, it is unnecessary to subtract out point source
controls.
4.2 CONTROL, RULE EFFECTIVENESS, AND RULE PENETRATION
Inventories performed before 1987 assumed that regulatory programs would be implemented
with full effectiveness, achieving all required or intended emissions reductions and maintaining
the reduction level over time. However, experience has shown regulatory programs to be less
than 100 percent effective for most source categories in most areas of the country.
Control efficiency (CE), rule effectiveness (RE), and rule penetration (RP) are applied to an area
source emission estimate if regulations are in place that affect any of the individual sources
within a source category. CE, RE, and RP are used to estimate the effect of controls being
applied in an imperfect world. Sources that are completely uncontrolled do not have CE, RE, or
RP applied.
4.2.1 CONTROL EFFICIENCY
CE is the emission reduction efficiency, and is a percentage value representing the amount of a
source category's emissions that are controlled by a control device, process change, or
reformulation. For area sources in particular, controls can vary widely. CE values for area
sources represent the weighted average control for the category.
4.2.2 RULE EFFECTIVENESS
RE is an adjustment to the CE to account for failures and uncertainties that affect the actual
performance of the control. For example, control equipment performance may be adversely
affected by age of the equipment, lack of maintenance, or improper use. A default value of 0.80
for RE is recommended by EPA if information cannot be acquired to substantiate the true value
of RE.
Although RE reflects the assumption that regulations are rarely 100 percent effective, when
controls are irreversible process changes or reformulations, RE can be set to 100 percent.
RE can be developed for area sources in the following ways:
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• Assume an 80 percent default value for all sources;
• Perform a survey (with EPA approval for SIP inventories) to determine a source-
specific RE value; or
• Use a Stationary Source Compliance Division (SSCD) (now Office of
Enforcement and Compliance) Protocol Study specific to a category and
geographic area, and in accordance with SSCD procedures to calculate RE.
Alternative methods of developing RE values should be approved by the statutory authority
guiding or dictating the inventory requirement.
4.2.3 RULE PENETRATION
RP is the percentage of the area source category that is covered by the applicable regulation or is
expected to be complying to the regulation. The RP value can be based on a percentage of the
source that is regulated, a cutoff level, or regulation of an activity. Both RE and RP are applied
to entire source categories when calculating area source emission estimates.
RP is a measure of the extent to which a regulation covers a source category. For example,
regulations on gasoline underground tank filling may apply only to stations
above a specified size cutoff, or the regulation may apply to facilities built after a certain date.
Rule penetration is calculated by Equation 1.4-3:
Uncontrolled Emissions
n , n . .• Covered by Regulation 1AA Cl 4-3")
Rule Penetration = * 100 v1-^ J)
Total Uncontrolled Emissions
For example, if a rule only affects sources built since 1987 and 20 percent of the facilities have
been built since that time, then RP is equal to 0.2. Default values are not feasible for RP
because it is highly category- and location-dependent.
4.2.4 EXAMPLE SHOWING APPLICATION OF CE, RP, AND RE
Area source controls are less common than point source controls except in a few large urban
areas. Area sources that are most likely to be controlled are:
• Industrial surface coating;
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• Gasoline marketing (Stage I);
* Cutback asphalt use;
• Surface cleaning;
• Autobody refinishing;
• Automobile refueling (Stage II);
• Architectural surface coating;
• Open burning; and
• Printing processes.
If an area source is controlled, emissions are calculated by Equation 1.4-4:
CAEA = (EFA)(Q) [(1 - (CE)(RP)(RE)] (1.4-4)
where:
CAEA = Controlled area source emissions of pollutant A
EFA = Uncontrolled emission factor for pollutant A
Q = Category activity
CE = % Control efficiency/100
RP = % Rule penetration/100
RE = % Rule effectiveness/100
Alternatively, in the case where only uncontrolled area source emissions are known, such as
those where the point source correction has been made, Equation 1.4-5 can be used to calculate
controlled area source emissions:
CAEA = (UAEA) [(1 - (CE)(RP)(RE)] (1.4-5)
where:
UAEA = Uncontrolled area estimate of pollutant A
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The values for RE and RP need to be known to perform these calculations.
In practice, Equations 1.4-4 and 1.4-5 are difficult to apply in some situations. CE is not always
clear-cut and must sometimes be calculated. Table 1.4-2 lists example sources where special
consideration is required when calculating area source VOC emissions because of difficulty
determining CE and, in some cases, RP, as well. CE, RE, and RP for these source categories are
discussed in their respective methodology chapters. Where CE, RE, and RP for a source
category require special consideration, this is also discussed in its respective methodology
chapter.
TABLE 1.4-2
EXAMPLES OF AREA VOC SOURCES REQUIRING SPECIAL
CONSIDERATION WHEN CALCULATING EMISSIONS
Special Calculation Issue
VOC content control device by regulation
Activity is banned
Controls reduce consumption, not emission rate
Emission factor based on control device emissions
Example Sources
Architectural Surface Coating
Industrial Surface Coating
Autobody Refmishing
Commercial/Consumer Solvent Use
Emulsified Asphalt Paving
Cutback Asphalt Paving
Open Burning
Degreasing (Surface Cleaning)
Gasoline Stage I Marketing
(Submerged Balance Fill Method)
Automobile Refueling (Stage II)
Landfill Flares
4.2.5 TEMPORAL ADJUSTMENTS
Temporal adjustments are made because of seasonal differences in the rate of emissions or
activity, or to apportion emissions to a particular season, day or hour. The need to make these
adjustments will be based on the needs for the particular inventory. A SIP ozone inventory, for
instance, will need to have emissions either calculated for just one typical ozone season day, or
have emissions corrected for the season, and apportioned for the typical ozone season day.
The best method to get the most accurate emission estimates for an inventory day or period is to
directly collect the emission information or the activity data for that particular time period.
1.4-8
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Because area source inventories rarely have sufficient resources to do this detailed level of data
collection, the preferred method for temporal adjustment is the one that produces the most
accurate activity or adjustment factors for a source category reflecting the inventory time period
and locality. If a survey is being used to collect emission or activity data, then the questionnaire
can also be used to gather information about working hours and production for the inventory
time period. Other less direct sources of information, such as state or national business and
labor statistics, or Department of Energy statistics, may also be used, but may not reflect local
variations. If no information is available that is recent or representative of local conditions, then
national average adjustment factors can be used. These approaches are discussed further in the
following section.
4.2.6 SEASONAL ACTIVITY
Source activity for many categories fluctuates on a seasonal basis. Because emissions are
generally a direct function of source activity, seasonal changes in activity levels should be
examined. For all categories, seasonal variations in activity must be considered if seasonal or
daily emissions are to be estimated. A VOC inventory covers an ozone season typically defined
as the months of June, July, and August. A carbon monoxide (CO) season will be the coldest
months of the year, December, January and February. The months covered by an ozone or CO
season may vary by region. Emission factors for some categories may also be dependent on
seasonal variables. The type of information needed to calculate emissions depends on the source
category and the desired temporal resolution of the emissions estimates.
Some operations, such as architectural surface coating, might be more active in the warmer
months in some inventory regions because of the warmer weather, and may be more active
because there are more hours of daylight for the activity. In some cases, a activity may take
place only during the warmer months. On the other hand, some sources, because of summer
vacation shutdowns or decreased demand for the product, may be less active during the ozone
season. Such sources (e.g., residential heating), may exhibit greater activity in colder months
and, thus, emissions are greater for a typical CO season. However, many sources, particularly
industrial facilities, will show no strong seasonal change in activity and little adjustment will
need to be made to estimate the seasonal emissions component.
An important seasonal variable is temperature. Sources such as petroleum product handling and
storage operations, breathing losses from fixed-roof tanks, and loading of rail tank cars, tank
trucks, and marine vessels are significantly influenced by temperature changes. Empirical
formulas and reference tables can be found mAP-42 to calculate these losses, and the TANKS
model can be used to estimate emissions from fixed-roof storage tanks under varying
temperatures.
There are several other source categories with emissions that are affected by variations in
temperature for which temperature-dependent equations are not currently available. EPA is
currently investigating methods for use in future inventories to estimate these emissions that will
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reflect the effects of both temperature and vapor pressure. For more information, contact the
EPA Emission Factor and Inventory Group at (919) 541-4676.
4.2.7 ACTIVITY DAYS PER WEEK
If daily emissions are to be calculated, the activity days per week must be identified so they can
be used in the emission equation. For most industrial sources, the number of days per week is
five. For many consumer or commercial activities, six or seven days are generally used.
Table 1.4-3 shows the activity days per week for some common area source categories.
4.2.8 CALCULATIONS FOR TEMPORAL ADJUSTMENTS
Seasonal or percent period throughput, discussed above, is required to calculate daily or seasonal
emissions. Of course, the best situation is to obtain activity data that are specific for the season
of interest.
The best way to calculate daily or seasonal emission estimates is to obtain activity data that are
specific for the season of interest. However, if this is not possible, an estimate of seasonal
activity can be calculated using an adjustment factor applied to the annual activity. In cases
where a surrogate activity factor is used to calculate emission estimates, an adjustment factor is
applied to the calculated annual emission estimates. Factors for making seasonal adjustments
may be expressed as fractions, percentages, or ratios. Thus, an adjustment factor is typically
expressed as:
• A fraction: seasonal activity factor (SAP) representing the amount of annual
activity or emissions within a period (such as 4/12 = 0.33);
• A percentage: percent period throughput, the percent value of the SAP for a
period (such as 0.33 * 100 = 33); or
• A ratio: seasonal adjustment factor, the ratio of seasonal activity or emissions to
average period activity or emissions (such as 0.33/0.25 = 1.33).
For example, if a VOC source category has one third more emissions during the 3-month ozone
season than the rest of the year, the SAP would be 0.33, the percent period throughput would be
33 percent, and the seasonal adjustment factor would be 1.33. If annual estimated emissions are
2,000 tons of VOCs, the calculation for the ozone season using a SAP (0.33) would be as shown
in Equation 1.4-6:
= 0.33 * 2,000 tons VOCs (1-4-6)
666 tons VOCs
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TABLE 1.4-3
AREA SOURCE SEASONAL ACTIVITY FACTORS AND
DAYS PER WEEK FOR THE PEAK OZONE AND CO SEASONS
Area
Source
Seasonal Activity Factors
Ozone
CO
Activity
Days Per
Week
Gasoline Service Stations
Tank Trucks in Transit
Tank Truck Unloading
(Stage I)
Vehicle Fueling (Stage II)
Storage Tank Breathing
Losses
Seasonal variations in throughput vary
from region to region. Use average
temperature for a summer day where
appropriate.
6
6
7
7
Solvent Usage
Degreasing
Dry Cleaning
Surface Coatings
Architectural
Auto Refinishing
Other Small Industrial
Graphic Arts
Cutback Asphalt
Pesticides
Commercial/Consumer
0.25
0.25
0.33
0.25
0.25
0.25
6
5
7
5
5
5
Refer to local regulations and practices
0.33
0.25
6
7
Waste Management Practices
POTWs
0.35
7
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TABLE 1.4-3
(CONTINUED)
Area
Source
Hazardous Waste TSDFs
Municipal Landfills
Seasonal Activity Factors
Ozone
0.30
0.25
CO
Activity
Days Per
Week
7
7
Stationary Source Fossil Fuel Use
Residential
Commercial/Institutional
Industrial
0.08
0.15
0.25
0.43
0.35
0.25
7
6
6
Solid Waste Disposal
On-site Incineration
Open Burning
Structural Fires
Field/Slash/Prescribed Burning
Wildfires
0.25
Refer to local
regulations and
practices
0.20
Refer to local
regulations
Refer to local fire
conditions
0.25
Refer to local
regulations and
practices
0.33
0.10
0.05
7
7
7
7
7
1.4-12
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where:
AEvOCO = Area emissions of VOCs for ozone season
The calculation using a percent period throughput factor would be quite similar as shown in
Equation 1.4-7:
AEvoco = 33/100* 2,000 tons VOCs (1-4-7)
666 tons VOCs
However, the calculation using the seasonal adjustment factor must take the number of months
into account, as shown in Equation 1.4-8:
AEyoco = 1.33 * (3/12 * 2,000 tons VOCs) (1-4-8)
666 tons VOCs
Further adjustments to the emission estimate would be made to calculate a daily emission
estimate. To determine daily emission estimates from facilities with uniform annual production
or throughput, the Equation 1.4-9 can be used:
„ . . . . Emissions
Typical Annual
J\-, • • per year
Emissions = *-—^- (1 4.9)
per day Operating Operating j
\ days/week ) \ weeks/year }
For sources that require a seasonal adjustment, seasonal daily emission estimates can be
calculated as in Equation 1.4-10:
„ . , c , Emissions
Typical Seasonal
J^-c • • per season
Emissions = —— . F : r- (1.4-10)
per day I Operating I Operating j
^ days/week } \ weeks/season }
An example calculation of a peak ozone season daily emission estimate where the peak ozone
season is the 3 months of summer, is shown in Equation 1.4-11:
Example: Annual Emissions = 1.3 tons of VOCs
SAP = 0.28 (28 percent)
Peak Ozone Season = 0.25 (25 percent or 3 months)
Operating Schedule = 6 days per week, 52 weeks per year
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2,000 Ib \ ( 0.28
Typical Ozone I I I ton II 0.25 / n4_i
Season Daily = A year > V '-± '— = 9.3 Ib VOCs per day U'4
Emissions (^ days/week) (52 weeks/year)
Table 1.4-3 shows default SAP values for some area source categories.
In some cases the season affects the calculation of emission factors, rather than, or in addition
to, activity factors. The volatility of VOCs depends partly on temperature so that the
temperature relationship must be included in emission factor calculation.
It is important to bear in mind that although temperature enters into many different calculations,
the temperature used may vary depending on the source category. For gasoline distribution
emission factors, the temperature of the product—not the ambient temperature-is the input
variable. However, as an example, the evaporative losses from automobile gas tanks (usually
included in the mobile sources) may use temperatures closer to ambient. Therefore, although
some coordination of seasonal variables is needed, the values used may not necessarily be the
same for all area sources in the inventory region.
If an agency wishes to develop its own SAP, it must establish the peak period (in number of
months) for its area, choose the inventory year for its investigation, identify the sources within
the source category under consideration, and develop an approach for collecting seasonal
activity information for these sources. Approaches include questionnaires, researching more
recent SAFs, or researching trade groups, or labor or economic statistics.
A questionnaire for collecting SAP information should request data for the inventory year,
including annual process activity data, peak period activity data, and, if possible, the emission
factor or estimate. The agency can then develop its own seasonal activity factor for the source
category for any inventory season using the following equation:
SAP =
Peak Period Activity
Annual Activity
Months of Inventory Season
Months of Peak Activity
(1.4-12)
This SAP can then be applied to annual activity information to estimate seasonal emissions, just
as AP-42 emissions factors are applied to estimate annual emissions. The SAP can be converted
to the percent period throughput (PPT) by multiplying by 100.
A study to improve and augment existing temporal allocation factors using data from more
current data sources has been completed by EPA's Office of Research and Development (EPA,
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1994). This study developed new temporal allocation factors and amended previous allocation
factors for a significant number of point source categories to better represent the intended source
categories. Information was gathered from the literature, state and local regulatory air pollution
agencies, and other government and private organizations. In many cases, source test data were
used to develop the new or improved temporal allocation factors files. When the point source
process and the area source category are well matched, point source factors would be suitable to
use for an area source emission inventory.
The report (EPA, 1994) describes all of the available data in detail. A temporal allocation factor
file, based on the results of the study, is available from the Emissions Characterization and
Prevention Branch, Research Triangle Park, North Carolina (phone: (919) 541-4593). Temporal
allocation factors for seasonal, weekday/Saturday/ Sunday and hourly periods are recorded for
most AIRS AFS SCCs and AIRS AMS area source category codes.
These data may be used as default factors for temporal allocation when no local data are
available. For the most part, the area source factors represent temporal allocation factors that
were derived for the 1985 National Acid Precipation and Assessment Program (NAPAP)
national emissions inventory.
Labor and economic statistics can also be used to develop default temporal allocation factors.
The statistics are published on varying temporal resolutions: seasonally, monthly, and weekly.
Data may be supplemented by industry surveys for further temporal resolution to an hourly
basis. The basic assumption is that operating or economic statistics are surrogate indicators of
industrial processes releasing pollutants. For example, the number of hours worked by
employees or the industry's production rate are assumed to be directly related to that industry's
potential emissions during that time frame.
The following data sources may provide sufficient information to support development of
temporal allocation factors:
• Business and labor statistics data;
• Department of Energy data pertaining to production/consumption from various
energy industries;
• State source test reports;
• State stationary source operating schedule data;
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• Waste-to-energy data;a
• Business Statistics?
• Employment and Earnings;" and
• Commodity Research Bureau Year Book.A
4.3 SPATIAL ALLOCATION
Spatial allocation factors can be applied to the activity levels used to calculate emission
estimates, or the emission estimates themselves. An instance when activity may need to be
allocated to a smaller geographic area would be when state-level gasoline sales need to be
apportioned to the county level. Spatial allocation of emissions estimates is done when the
emissions need to be assigned to a more specific and smaller area. This may need to be done
when using the information from a base year SIP inventory for an air quality model that needs
gridded emissions data, or when activity data apply to a larger area than that needed for the
inventory. The techniques for allocating activity and emissions are typically the same for a
particular source category and emissions estimation method.
Area source inventories are often prepared for state or county geographical extents. In some
cases, it may be desirable to allocate these emissions to smaller individual geographic areas,
either subsections of a county or grid cells for use in a model. The amount of effort required to
implement this resolution will vary depending on the type of source. Emissions that have been
estimated by an individual facility may be reported to within a fraction of a kilometer in the
existing inventory; hence, assigning emissions from these sources to the appropriate grid cell is
simple.
By contrast, spatial resolution of more diffuse area source emissions requires substantially more
effort. Two basic methods can be used to apportion area source emissions to grid cells. The
most accurate (and resource-intensive) approach is to obtain area source activity level data
directly for each grid cell. This information is possible to collect when the activity data are of a
a Found in the annual Resource Recovery Yearbook, Directory and Guide., Governmental
Advisory Associates, Inc., New York, New York.
b Obtained from the Bureau of Economic Analysis, U.S. Department of Commerce,
Washington, D.C.
c Obtained from the Bureau of Labor Statistics, U.S. Department of Labor, Washington,
D.C.
d Obtained from the Commodity Research Bureau, Chicago, Illinois.
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type that can be directly assigned to a specific geographic area. Examples of these types of
activity data would be population when detailed census data are available, or land use that can
also be assigned to grid cells. This approach is the preferred approach, when it can be used.
The alternative (and more commonly employed) approach is to apportion the county-level
emissions from the existing annual inventory to grid cells using representative apportioning
factors for each source type.
This latter approach requires:
• Identification of a spatial surrogate indicator of emission levels or activity such as
population, census tract data, or type of land use for each grid cell that is
appropriate for the source category;
A surrogate apportioning factor takes the place of the actual activity level,
but is assumed to be a reasonable indicator of the actual activity level.
• Creation of apportioning factors based on the distribution of these spatial
surrogates; and
* Application of these factors to the county-level emissions.
These steps will yield estimates of emissions from that source category by grid cell. The process
can also be applied to state or regional activity or emissions to yield activity or emissions at the
county or subcounty level. The major assumption underlying this method is that emissions from
each area source behave spatially in the same manner as the spatial surrogate indicator. In
developing spatial apportioning factors, the agency should emphasize the determination of
accurate factors for the more significant sources. The purpose of the inventory and the
capabilities of the agency may also need to be considered when choosing an apportioning
method. For most large urban areas, local planning agencies can provide the agency with
detailed land use or population data, or in some cases employment statistics at the subcounty
level; these data can be used to spatially apportion most of the area source emissions in the
inventory.
A Geographical Information System (GIS) can be a useful tool in handling spatially distributed
data. A GIS uses sophisticated computer technology to store, retrieve, analyze, update, and
display spatially arranged data (maps). This type of system can locate each point source, define
the boundaries around each area source, and map road networks. Map coverages are available in
digital formats from transportation departments, tax offices, planning/zoning offices, and
emergency response agencies. Information stored in a GIS can be the most direct method of
spatially allocating activity data and may allow the use of more detailed surrogates that would be
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too labor-intensive to use without a GIS. In most cases, using a GIS with good quality map
coverages and well-chosen surrogates will be the preferred spatial allocation method.
Further information about the potential applications of the GIS technologies in emissions
inventory preparation can be obtained from the Air Quality Modeling Group of the EPA Office
of Air Quality Planning and Standards (OAQPS) and the EPA Office of Research and
Development (ORD), both in Research Triangle Park, North Carolina; local colleges or
universities with geography, civil engineering, or natural sciences departments; state and local
land/resource management agencies or environmental protection agencies; and private
organizations that provide mapping services.
Commonly used spatial surrogate indicators include land use parameters, employment in various
industrial and commercial sectors, population, and dwelling units. Different surrogate indicators
may be used to apportion emissions for the various area source categories depending on which
of the available indicators best describes the spatial distribution of the emissions. EPA guidance
and good engineering judgment should be used to select appropriate indicators for apportioning
area source emission totals. Local authorities should be contacted to verify the applicability of
the source category/spatial surrogate indicator pairings for a particular inventory region.
The table in Example 1.4-1 lists example spatial allocation surrogate indicators for area source
categories as utilized in various urban areas. These indicators could be used to spatially
apportion emissions from these source types in the absence of more detailed or locally specific
data; however, the agency should make a special effort to choose spatial surrogate indicators for
the various source categories that accurately reflect the distribution of activity for those sources
in the inventory region. Other references that contain useful information for developing spatial
resolution for some specific source categories are:
• Census of Business Selected Services Area Statistics (for county-level gasoline
handling source categories);a and
• Sales of Fuel Oil and Kerosene (for state-level commercial and institutional fuel
combustion).b
Other resources, which will be addressed in detail below, include land use patterns (from maps
and/or computerized databases) and Census Bureau demographic statistics by traffic zone or
census tract. Planning, land use, and transportation models are already in use in many regions, a
and can provide the agency with much of the data necessary to allocate emissions. Local
agencies and metropolitan planning organizations should always be contacted during the
a Obtained from the U. S. Department of Commerce, Bureau of the Census, Washington,
D.C.
b Obtained from Mineral Industry Surveys, Bureau of Mines, Washington, D.C.
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Example 1.4-1
EXAMPLE SPATIAL ALLOCATION SURROGATE INDICATORS FOR SELECTED
AREA SOURCE CATEGORIES
Emissions Category
Residential fuel combustion
Commercial/institutional fuel combustion
Industrial fuel combustion
Gasoline marketed
Unpaved roads
Unpaved airstrips
Forest wildfires
Managed burning-prescribed
Agricultural operations
Structural fires
Degreasing
Dry cleaning
Graphic arts/printing
Rubber and plastic manufacturing
Architectural coating
Auto body repair
Motor vehicle manufacturing
Paper coating
Fabricated metals
Machinery manufacturing
Surrogate Indicators
Housing
Urban land use
Urban land use
Population, VMT
County area, land use
County area, airport location
Composite forest
Composite forest
Agricultural land use
Housing
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
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Example 1.4-1
(CONTINUED)
Emissions Category
Furniture manufacturing
Flat wood products
Other transportation equipment manufacturing
Electrical equipment manufacturing
Ship building and repair
Miscellaneous industrial manufacturing
Miscellaneous solvent use
Publicly owned treatment works (POTWs)
Cutback asphalt paving operation
Fugitive emissions from synthetic organic chemical
manufacturing
Bulk terminal and bulk plants
Fugitive emissions from petroleum refinery operations
Process emissions from bakeries
Process emissions from pharmaceutical
manufacturing
Process emissions from synthetic fibers
manufacturing
Crude oil and natural gas production fields
Hazardous waste treatment, storage, and disposal facilities
(TSDFs)
Surrogate Indicators
Population, employment
Population, employment
Population, employment
Population, employment
Water proximity, employment
Population, employment
Population, employment
Population, employment
Population, VMT
County area, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, employment
Population, land use
1.4-20
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7/37/07 CHAPTER 1 - INTRODUCTION
inventory planning process to determine what planning models are being utilized and how the
data available from these models can be used in the emissions inventory effort. Trying to
independently develop all the necessary information that should be available from local planning
boards requires much redundant effort on the part of the agency. Additionally, any subsequent
conclusions drawn from the inventory might likely be challenged if there is inconsistency with
other information available to the public.
4.4 APPLYING GROWTH FACTORS FOR PROJECTIONS
General projection issues for inventories are discussed in Volume I of this series.
Area source projections can be made using local studies or surveys or through surrogate growth
indicators, such as Bureau of Economic Analysis (BEA) data, to approximate the rise or fall in
indicators activity. The most commonly used surrogate growth indicators are those parameters
typically projected by the local metropolitan planning organization (MPO) such as population,
housing, land use, and employment. Regardless of the growth indicator employed, the
calculation is the same: the ratio of the value of the growth indicator in the projection year to its
value in the base year is multiplied by the area source activity level in the base year to yield the
projection year activity level.
The EIIP Projections Committee has developed a series of guidance documents containing
information on options for forecasting future emissions. You can refer to these documents at
http://www.epa.gov/ttn/chief/eiip/project.htm.
If activity is not used in emission calculations, which would be the case if base year emissions
were measured directly, or material balance methods or mathematical models are used, then a
growth factor reflecting the change from the base year to the projection year can be calculated.
The purpose of developing a projection inventory is to either determine the emissions reductions
that will be needed to attain air quality standards or to project future compliance. In general,
projection year emissions are based on base year allowable emissions, but in certain
circumstances, it may be appropriate to use base year actual emissions. For CAAA 15 percent
Rate of Progress (ROP) Plans, actual emissions can be used for source categories that are
currently subject to a regulation and for which the state does not anticipate subjecting the source
to additional regulation, or for source categories that are currently unregulated and are not
expected to be subject to future regulations.
Actual emissions are based on a source's actual operating hours, production rates, and control
equipment for processes at the source. Allowable emissions are based on the expected future
operating rates or throughput and maximum emissions limits. Maximum emission limits may
be process-based emissions factors, capture and/or control device efficiencies, or emission rate
limits. Emission factor limits and capture and/or control device efficiency limits should take
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CHAPTER 1 - INTRODUCTION
1/31/01
Example 1.4-2
EXAMPLE GROWTH INDICATORS FOR PROJECTING EMISSIONS
FOR AREA SOURCES
Source
Gasoline marketing
Dry cleaning
Degreasing (Cold cleaning)
Architectural refinishing
Automobile refinishing
Small industrial surface coating
Graphic arts
Asphalt use: Paving
Asphalt use: Roofing
Pesticide applications
Commercial/Consumer solvent use
POTWs
Hazardous waste TSDFs
Municipal solid waste landfills
Growth Indicators
Projected gasoline consumption
Population: retail service
employment
Industrial employment
Population or residential
dwelling units
Industrial employment
Industrial employment
Population
Consult industry
Industrial employment;
construction employment
Historical trends in agricultural
operations
Population
Site-specific information
State planning forecasts
State Waste Disposal Plan
Information Sources
MOBILE fuel
consumption model
Solvent suppliers; trade
associations
Trade associations
Local MPO
BEA
BEA
State planning agencies;
local MPO
Consult state DOT and
industry
Local industry
representatives
State department of
agriculture; local MPO
Local MPO; state planning
agencies
State planning
agencies
State planning
agencies: local MPO
Local MPO; state planning
agencies
1.4-22
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CHAPTER 1 - INTRODUCTION
Example 1.4-2
Source
Commercial/Industrial fuel
combustion
Industrial fuel combustion
Construction equipment
On-site incineration
Fires: Managed burning
agricultural field burning, frost
control (Orchard heaters)
Forest wildfires
Structural fires
(CONTINUED)
Growth Indicators
Commercial/Institutional
employment; population
Industrial employment (SIC
Code 10-14, 50-51); or
industrial land use
Industry growth (SIC
Code 16)
Based on information
gathered from local regulatory
agencies
Areas where these activities
occur
Historical average
Population
Information Sources
Local MPO; land use
projections
Local MPO; land use
projections; state planning
agencies
Local MPO
Local agencies; state
planning agencies; local
MPO
U.S. Forest Service, state
agricultural extension office
Local, state, and federal
forest management officials
Local MPO; state planning
agencies
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CHAPTER 1 - INTRODUC TION 1/31/01
precedence over emission rate limits when they are available. In determining the maximum
emissions limit, existing regulations must be considered in addition to future planned
regulations.
A major difference between making area source projections for the basic, county-wide inventory
and for a detailed, photochemical inventory is that, in the latter, emission estimates must be
resolved at the grid-cell level. This adds a dimension of complexity to the projection effort,
since changing growth patterns may require that different apportioning factors be determined for
the projection years. Fortunately, in most large urban areas where photochemical models are
employed, the local MPO will be able to provide land use maps, as well as detailed zonal
projections of employment, population, etc., for future years. Hence, these projections can be
used directly, as described above, to determine changes in spatial emission patterns.
If the surrogate indicators used for apportioning certain area source emissions are not projected
at a subcounty level, engineering judgment must be used to decide whether spatial distributions
of various activities will change enough to warrant the effort of identifying new patterns.
Changes may be warranted in rapidly growing areas for the more important area source emitters.
For regions where little growth is expected, and especially for minor area sources, the same
apportioning factors can be used in baseline and projection inventories.
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DATA COLLECTION AND
MANAGEMENT
Data management comprises data collection, data storage, and updates to the database, as well as
the planning and QA/QC of the process. The collection and storage of data, particularly as it
applies to area sources, is addressed in this section. The development and implementation of
surveys as a data collection method merit particular attention in this section. Inventory QA/QC
is addressed in Volume VI of this series, Quality Assurance Procedures, and in Volume I of this
series, Introduction to the EIIP.
5.1 DATA COLLECTION AND STORAGE
5.1.1 DATA RESOURCES
Area source inventory data can come from a number of diverse sources. Surveys and agency
pollution files are methods typically used for point sources that may also be useful in collecting
data for area source emissions, activity, and control data. Other commonly used area source data
resources are U.S. Census Bureau documents such as County Business Patterns, Census of
Agriculture, Census of Manufactures, and Current Industrial Reports; documents and reports
from other federal agencies such as the Energy Information Administration (EIA); locally
collected activity information, trade contacts, journals, and databases; and data compilations
such as the Frost & Sullivan Industrial Solvents report or the Chemical Marketing Reporter.
Accessing these types of market research reports is discussed below. Sources for inventory
procedural guidance include AP-42 and guidance manuals such as this one. Data sources for
source category characterization include EPA reports such as Background Information
Documents (BIDs), Control Technique Guidelines (CTG) documents, Locating and Estimating
(L&E) documents, emission model manuals, Technical Support Documents (TSDs), Alternative
Control Techniques (ACT) documents, and AP-42.
Market research reports are one source for information on the past sales of, and future trends in
the use of, different products. Occasionally, these reports can be found in a business school
library or large university library, but because they can be quite expensive, not many libraries
collect them. On-line bibliographic utilities such as Knight Ridder's DIALOG, offer databases
containing the full text of market research reports. These databases include Freedonia Market
Research, BCC Market Research, and Frost & Sullivan Industrial Solvents.
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CHAPTER 1 - INTRODUC TION 1/31/01
Some state libraries offer on-line literature search services, and should be able to locate the
information needed. If not, information brokers who do literature searches for a fee will be able
to help. These services can be found in the telephone directory under the headings "Information
Brokers," "Information Processing and Retrieval Systems & Services," or "Information Search
and Retrieval."
Rather than purchasing an entire report, the librarian or information broker can retrieve the
information needed, usually at a fraction of the cost of the whole report. On-line computer
charges for the databases listed above run about $60.00 per hour plus $16.00 per item typed or
printed out (as of July 1995).
Because charges are usually based on time spent on-line plus the per-item cost, it helps to be as
precise as possible in explaining information needs to the librarian or information specialist.
Some background on the context of the request (i.e., how the information is to be used) can be
very useful and cost-effective.
5.1.2 DATA HANDLING
Typically, the data used for area source emissions estimates are retrieved from a variety of
sources. Data collection methods for area sources vary much more than those for point sources.
Specific data collection methods and data sources are provided for a number of area source
categories later in this volume. Often, data availability (or unavailability) determines the
method that must be used to estimate emissions.
If the area source inventory is being prepared by more than one person, coordination is needed to
assure consistency of activity data and to avoid duplicating effort. A table showing the area
source category, estimation procedure, activity data needed, and activity data source should be
prepared. Table 1.5-1 gives an example for a hypothetical ozone inventory. Note that
categories may use common activity data; for example, emissions for three source categories can
be calculated using population data. Where alternative sources of information exist, the
preferred source of information should be identified and used consistently throughout the
inventory.
All data collected, regardless of the source, should be documented and logged into a central file.
In particular, information gathered over the telephone needs to be well documented in writing,
including the date of the call and the names of the participants. These procedures are covered in
more detail in the Volume I of this series. It is very important to begin data collection as soon as
possible because obtaining data is not always straightforward. If the data are not already
published, contacting the right person and then eliciting the information in the required format
can take weeks or even months.
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TABLE 1.5-1
ACTIVITY DATA EXAMPLE SOURCES FOR AN OZONE INVENTORY
03
Area Source Category
Commercial/Consumer Solvent Use
Architectural Surface Coating
Gasoline Distribution
Industrial Surface Coating
Surface Cleaning Operations
Dry Cleaning Operations
Automobile Refinishing
Graphic Arts Facilities
Asphalt Paving
Traffic Paints
Agricultural Pesticides Application
Commercial Bakeries
Estimation Procedure
Per capita
Survey
Gasoline consumption
Per employee
Per employee
per employee
Per capita
Per employee
Consumption
Consumption
Application rate, acres of
crops
Per capita
Activity Data
Population
Gallons of paint
Gallons of gasoline
Employment by SIC
Employment by SIC
Employment by SIC
Population
Employment by SIC
Barrels of asphalt
Gallons of paint
Crop type by acre, types
of pesticides
Population
Source of Activity Data
U.S. Census data
Paint manufacturers
State Department of
Transportation (DOT), State
Energy Office
State Labor Department
State Labor Department
State Labor Department
U.S. Census data
U.S. Census data
State DOT, paving contractors
State DOT
State Agriculture Office, U.S.
Department of Agriculture
(USDA)
U.S. Census data
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TABLE 1.5-1
(CONTINUED)
i
Area Source Category
Structure Fires
Municipal Landfills
Residential Fuel Combustion
Industrial Fuel Combustion
Commercial/Institutional Fuel
Combustion
Petroleum Vessel Loading/Unloading
Aircraft Refueling
Wastewater Treatment
Hospital Sterilizers
Forest Fires
Breweries
Estimation Procedure
Per fire
Statistical models
Fuel use
Fuel use
Fuel use
Petroleum products
loaded/unloaded
Aviation fuel consumption
Surface impoundment modeling
system (SIMS)
Per hospital bed
Acres burned
State beer production
Activity Data
Number of fires
Tons of refuse,
landfill age
Amount of fuel
used
Amount of fuel
used
Amount of fuel used
Gallons of fuel
Gallons of fuel
Gallons of
wastewater and
portions of
industrial
wastewater
Hospital beds
Acres burned
Barrels of beer
Source of Activity Data
Fire marshall
State Solid Waste
Management Agency
State Energy Office,
Energy Information
Administration (EIA)
State Energy Office, EIA
State Energy Office, EIA
Port Authority, Waterborne
Commerce
State Energy Office, airports
Publicly owned treatment
works (POTW) operators
State Health Department
State Forester
State Commerce Office, trade
groups
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TABLE 1.5-1
(CONTINUED)
03
^i
C3
Area Source Category
Barge, Tank Car, Railcar,
Drum Cleaning
Medical Waste Incinerators
Asphalt Roofing Kettles
Orchard Heaters
Distilleries
Agricultural/Slash Burning
Wineries
TSDFs
Superfund Sites
Open Burning
Estimation Procedure
Survey
Survey
Per square paper
Fuel consumption
Distilled spirits production
Acres burned
Wine production
Survey
Survey
Survey
Activity Data
Vessels cleaned,
material cleaned
out of vessels
Waste incinerated
Material throughput
Amount of fuel used
Barrels of spirits
Acres burned
Barrels of wine
Material type,
material throughput,
treatment type
Material type,
material throughput,
treatment type
Occurrence of
burning
Source of Activity Data
Trade groups, drum-
cleaning facilities
State Health Department
Trade groups
Extension agents,
agricultural schools
State Commerce Office,
trade groups
Extension agents,
agricultural schools
State Commerce Office,
trade groups
State Environmental
Office
State Environmental
Office
State Environmental
Office
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CHAPTER 1 - INTRODUCTION 7/37/07
In addition to those staff members usually responsible for compilation and maintenance of
emission inventories, the agency should enlist the services of: (1) a computer programmer or
systems analyst to plan the storage and manipulation of the large amounts of emission data
needed, (2) an urban or regional planner to analyze land use data from local planning agencies,
and (3) a chemist familiar with the various classes of chemicals that will need to be speciated
into the individual components.
5.1.3 DATASTORAGE
Computerized data handling is preferable to paper files for large areas with diverse sources.
Computerized data handling becomes significantly more cost-effective as the database, the
variety of tabular summaries, or the number of iterative tasks increase. In these cases, the
computerized inventory requires less overall time involvement and has the added advantage of
forcing organization, consistency, and accuracy.
Some activities that can be performed efficiently and rapidly by computer include:
• Printing mailing lists and labels;
• Maintaining status reports and logs;
• Calculating and summarizing emissions;
• Performing error checks and other audit functions;
• Storing source, emissions, and other data;
• Sorting and selectively accessing data; and
• Generating output reports.
Phone logs, paper copies of notes, references, and other noncomputerized data should be stored
in a project file that allows access by the inventory staff and safety from loss. The inventory
staff should be issued notebooks that are used exclusively for the inventory preparation. These
notebooks can become a useful history of the inventory process.
Additional data management concerns are discussed in the following sections.
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5.1.4 NECESSARY DATA ELEMENTS
The data elements needed for a source category will be determined by the emission estimation
method and the information requirements of the inventory. The inventory preparer should check
the EPA website (http://www.epa.gov/ttn/chief/) for the latest information (codes) available to
characterize emission estimates from the source category. A complete list of Source
Classification Codes (SCC) can be retrieved at http://www.epa.gov/ttn/chief/codes/.
Available codes and process definitions influence and help guide the preparation of emission
estimates for a category. Data transfer formats should be taken into account when an inventory
preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use
in regional and national scale analyses.
5.1.5 SPECIAL ISSUES
For modeling inventories that are more detailed in terms of speciation and spatial or temporal
allocation, additional data may need to be collected for assigning emissions to grid cells, for
determining temporal distributions, or for selecting the appropriate speciation factors to be
assigned to the compound classes. Ideally, emissions data (including speciation
information) would be available for each source for each hour of any day selected. In practice,
however, this degree of detail is neither necessary nor practical for all sources because of the
inordinate amount of effort required to procure such data and because for many sources and
applications inclusion of these data would have little effect on the end use of the data.
As a general rule, the maximum degree of source category resolution from the annual inventory
should be maintained in the modeling inventory. For example, if separate emissions estimates
have been prepared for dry cleaners using perchloroethylene and dry cleaners using petroleum-
based solvents, this distinction should be maintained in the modeling inventory because it will
permit more accurate speciation of the emissions associated with these sources.
Some area source categories may be treated as point sources in a modeling inventory; other
source categories may be represented in both the point and area source inventories depending on
the emissions cutoff level used to make this distinction. The agency should be aware of all such
distinctions for the existing inventory and may need to institute certain changes to ensure that
the modeling inventory meets its objectives.
Projection inventories also require collection of data beyond that needed for a base-year
inventory. The primary difference is the need for growth factors and indicators, which are
applied to the base-year emissions, as discussed in Section 4.4 of this chapter.
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CHAPTER 1 - INTRODUC TION 1/31/01
5.1.6 NATIONAL EMISSIONS INVENTORY (NEI) INPUT
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data
elements necessary to complete the data set for use in regional or national air quality and human
exposure modeling. The inventory preparer should review the area source portion of the
acceptable file format(s) to understand the necessary data elements. The EPA describes its use
and processing of the data for purposes of completing the national inventory, in its Data
Incorporation Plan, also located at http://www.epa.gov/ttn/chief/net/.
5.2 SURVEYS
For some area source categories, a survey of a representative sample of facilities within the
source category may be necessary. Although it is beyond the scope of this document to
thoroughly address survey and sample design, guidance on conducting area source surveys is
provided in Chapter 24 of this volume, "Conducting Surveys for Area Source Inventories."
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INVENTORY QUALITY AND
UNCERTAINTY
The EIIP QA guidance stresses the importance of distinguishing between data quality and
uncertainty. Area source emissions estimates tend to be more uncertain than point sources;
given this, the data quality can (and should) be high. Inventory data quality is specified in the
data quality objectives (DQOs), and is attained by following a prescribed set of QC and QA
activities. The details of developing DQOs and QA plans, and QA/QC methods are covered in
Volume VI of this series.
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
6.1 QA/QC DATA VERIFICATION PROCEDURES FOR AREA SOURCE
INVENTORIES
In this section, some QA/QC issues particularly relevant to area sources are discussed. In
general, QA/QC procedures for an area source inventory involves (1) data verification to ensure
that the information being used is complete, accurate, and current and produces reasonable
estimates; (2) checks of data entry to minimize transcription errors when data are entered into an
electronic format, and (3) calculation checks to verify that arithmetic errors were not made.
Data verification involves the use of QA procedures at critical stages in the inventory
development to ensure that completeness, consistency, double counting, and reasonableness
evaluations are conducted. The procedures usually are facilitated by using checklists (see
Figure 1.6-1). The QA procedures also should be described in the inventory report. Data
validation procedures can be implemented manually or electronically. The QA Plan should state
how and when these will be used during the inventory process.
Completeness Checks
Completeness checks are designed to ensure that all emission sources have been represented in
the inventory. Manual completeness checks may include comparing the agency's list of area
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CHAPTER 1 - INTRODUCTION 7/37/07
Inventory Identification Assessed By
Date
Provide the information requested along with the corresponding resource document [ref] or data. After
completing the checklist, indicate the actions to be taken, deadline for completion, and date the actions
are completed.
SOURCE CATEGORY:
Defined before data collection? [ref] Yes No
Were definitions adhered to during data collection? Yes No
Inclusive of all listed pollutants? [ref] Yes No
POINT SOURCE CUTOFFS:
Identified during data collection? [ref] Yes No
Documented and reported to people involved in area source inventory? Yes No
Report
ID
Date
SURVEY RESULTS:
Was the response rate determined? Yes No
rate
Was the percentage of missing information per returned survey
estimated? Yes No
percent
EMISSIONS CALCULATIONS VERIFICATIONS:
Were nonreactive VOC emissions excluded from each source category
emissions estimates? [ref] Yes No
EPA recommended estimation methodology used? Yes No
FIGURE 1.6-1. INTERNAL SOURCE CATEGORY CONSISTENCY AND
ACCURACY CONTROL CHECKS
1.6-2 EllP Volume III
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7/37/07 CHAPTER 1 - INTRODUCTION
Emissions calculations checked? Yes No
checked by date
Are equations explicitly shown? [ref] Yes No
REASONABLENESS CHECKS:
Were magnitudes of calculated emissions compared with other source
categories? Identify second source reference or reference location of
data in file, [ref] Yes No
Were magnitudes compared with national/state ranks of source
categories? Yes No
compared by date
Were other inventories and/or national averages compared to AIRS? List
other inventories or reference data in master file. Yes No
Were findings reported and documented?
Yes No
SOURCE DATA:
Were area source activity data reliability verified using available data
sources? Yes No
verified by date
Are emissions factor sources documented? Yes No
where
Are local emission factors within national range? [ref] Yes No
Were facilities whose emissions and activity levels are known compared
against generic emission factors to check emission factor
reasonableness? Yes No
compared by date project file no.
Are assumptions documented for scaling-up source category emissions
and seasonal adjustment factor corrections? [ref] Yes No
Were point sources subtracted from area source emissions estimates?
[ref] Yes No
Are point source corrections to area source emission estimates
documented in the category calculations? [ref] Yes No
Use the worksheet on page 3 of 3 to record the actions to be taken in response to any problems found.
Set a deadline for the completion of the action and indicate when the actions are implemented.
FIGURE 1.6-1. (CONTINUED)
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CHAPTER 1 - INTRODUCTION
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INTERNAL SOURCE CATEGORY CONSISTENCY
AND ACCURACY QUALITY CONTROL CHECKS (Continued)
Actions To Be Taken
Deadline
Completion Date
FIGURE 1.6-1. (CONTINUED)
1.6-4
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sources with the area source categories shown in Section 2 of this chapter, or comparing with
independent listings (local business directories) of facilities by source category to ensure that all
the significant types of sources in the metropolitan statistical area (MSA) are included.
Consistency Checks
Consistency checks for data should also be implemented by the agency. Figure 1.6-1 is an
example inventory consistency and accuracy checklist. These example consistency checks for a
VOC inventory are designed to ensure that: (1) the same geographic area was used for all source
categories; (2) only reactive VOCs were counted in the inventory; (3) potential double counting
of point and area source categories was taken into consideration; and (4) the use of emission
factors, units of measurement, year(s) of data and information, and apportioning and distribution
techniques were consistent. The agency's plan to implement these checks should be included in
the QA Plan.
Double Counting
An important data verification step is to ensure that double counting of emissions does not occur
in the inventory. Double counting can occur because of overlaps between point and area source
inventories, and overlaps in area source groups. Inventory preparers should compare their lists
of point and area emission sources to see if any emission sources have been inventoried under
both point and area inventory tasks. If the emissions from a process at a facility are included in
both the point and area inventories, then the area source inventory should be adjusted downward
to exclude the emissions calculated for this facility's process in the point source inventory.
Overlaps in area source calculations can be minimized by careful definition of the emission
sources covered by each grouping, and an understanding of the processes that take place at a
source. For example, a category whose emissions are estimated using material balance may
account for 100 percent of the solvent used by a facility. However, some of the solvent may
actually be disposed of in wastewater and as solid waste in a landfill. Emissions estimated from
the wastewater and landfill categories, then, would include a double counting of the emissions
from these solvents.
Further discussion of the correction for double counting can be found in Section 4, Adjustments
to Emission Estimates, of this chapter.
Reasonableness
The data obtained or calculated for the inventory also should be checked for reasonableness.
Reasonableness checks-which should not be confused with consistency checks—are needed to
ensure individual data element values and emission estimates fall within reasonable or
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acceptable ranges. The primary method to check for reasonableness is the comparison of the
data collected with that from similar inventories or inventories from previous years.
The following questions should be considered by agency staff members, peer reviewers, and QA
personnel to ensure that all data provided are reasonable:
• Were the data representative of the region being inventoried?
• Is the information up to date? If not, can reliable adjustment factors be found?
• Are data from an appropriate time frame used (e.g., annual, or CO and ozone
seasons)?
• Are the collection techniques documented?
Data Entry Errors
Once the data are in the inventory format, individual data elements should be checked for data
entry errors. Error checks can be random checks of a small percentage of the entries, with a
higher percentage of checks being made if errors are found. All entries should be subject to
error checks. Errors to check for will include missing entries, typographical errors, and
misassignment of codes.
6.2 QA/QC FOR INVENTORY CALCULATIONS
Calculations should be done with computerized spreadsheets as much as possible to reduce
errors. If handwritten calculations are necessary, they should be performed on worksheets or in
project notebooks. Calculations should be peer reviewed for accuracy and checked to ensure
that all emission and activity factors are used correctly. The agency should identify in the QA
Plan (see Section 2, Inventory Planning) how the following QC steps will be ensured and who
will perform the QA audits:
• Equations are accurately used and are consistent within each method or
procedure; if not consistent, a justification is provided;
• Assumptions and engineering judgments used in the calculations are documented
and reviewed;
• Correct units are used and unit conversions are accurate;
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• Calculations are reviewed for data entry problems, such as transposition of digits
and entering of incorrect numbers into calculators or computers;
• Procedures used to record calculations are consistent; and
• Misinterpretation of either the emission factors or their use is not done.
Random selection and duplication of calculations should be an integral part of the QC
evaluations. The number or percentage of calculations that should be checked depend on the
difficulty and importance of the source and the DQOs. If significant errors are found, the
number of checks should be increased. In addition, the process used to derive the calculations
should be checked. The frequency of these checks will depend on staff experience, staff size,
inventory size, etc.
Another QA audit procedure for calculations is to check that all assumptions and engineering
judgments used in the calculations are recorded in the project notebooks. The notebooks should
contain all of the calculations used to develop the inventory and should contain the references
for the data sources. The auditor should be able to perform QC checks on the calculations solely
from the information recorded. If the data are calculated using computers, a hard copy of the
program or algorithms used for all calculations and input files should be maintained in the
project files.
The use of a computerized system for calculations can facilitate the QA process by assisting in
inventory submittal tracking, edit checking, and data and calculation review. Chapter 3,
Section 5, of EIIP Volume VI, describes some automated checks and audit tools that can be
built-in to spreadsheets or database programs. CHIEF should be checked periodically for new
QA information or software.
6.3 UNCERTAINTY IN AREA SOURCE INVENTORIES
Area source emissions are generally held to be highly uncertain and less accurate than point
source emission estimates. While both criticisms are somewhat warranted, they are probably
overstated in many cases. The first step towards reducing the uncertainty associated with area
source emissions is to understand the causes of variability and inaccuracies in area source
emission estimates. As this discussion indicates, although some uncertainty is unavoidable in
area sources inventories, it can be minimized.
To better understand the sources of uncertainty in area source emissions, it is necessary to
identify uncertainties associated with specific aspects of the estimation methods. Basically,
three general forms of uncertainty are potentially applicable: variability, parameter uncertainty,
and model uncertainty. Table 1.6-1 summarizes the discussion and provides examples of each
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oo
TABLE 1.6-1
i
SOURCES OF UNCERTAINTY IN AREA SOURCE EMISSION ESTIMATES
Source of Uncertainty
Variability
Parameter Uncertainty
Measurement errors
Sampling error
[n
Examples
Fluctuation in VOC emissions for pesticide use caused by
environmental conditions.
Daily/weekly variations in activity (dry cleaner,
commercial fuel combustion, individual surface coating,
etc.).
Seasonal variability in activity (residential fuel
combustion).
Process or activities included in the category are not
uniform (e.g., product formulations vary).
Ways to Minimize
Quantify variability if
possible.
Make sure averaging time of
emission factor and activity
are appropriate for temporal
scale of inventory.
If possible, subdivide
category to create more
uniform subcategories.
Incorrect response on a survey form.
Misclassification of data (e.g., facility in SIC Code group
that does not accurately define activities).
Inadequate sample size.
Underlying data not normally distributed.
QA audits of survey data.
Ensure adequate sample size
by increasing response rate or
increasing distribution of
survey.
Consider distribution of data
in sample design and
statistical analysis.
§
c
o
^J
i
c"
(B
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rn
"
CD
TABLE 1.6-1
(CONTINUED)
03
^i
C3
Source of Uncertainty
Examples
Ways to Minimize
Systematic error
Inherent bias in a survey (for example, if only largest
facilities are surveyed and they do not reflect activities at
smaller facilities).
Incorrect assumption (such as assuming 100% compliance
with rules and ignoring rule effectiveness).
External review of methods
and assumptions by a
qualified expert on the
industry.
Make sure that characteristics
of source population are
understood and accounted for
in methods.
Model Uncertainty
Surrogate variables
Use of population or number of employees as surrogate
for emission activities that do not correlate to those
surrogates.
Use surveys of local sources
instead.
Develop emission factors
based on statistically
correlated surrogate.
Exclusion of variables/model
oversimplification
Potentially a problem for area source estimates based on
emission factors or models.
Validate model for specific
use if possible (i.e., use model
to predict a known value).
Avoid use of oversimplified
methods if at all possible.
i
I
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CHAPTER 1 - INTRODUC TION 1/31/01
type of uncertainty. More information on uncertainty can be found in EUP Volume VI, Chapter
4, Evaluating the Uncertainty of Emission Estimates.
6.4 VARIABILITY
Uncertainty is often equated with variability, which is the natural fluctuation in the value of a
variable. These are nonrandom fluctuations although they may appear random if the causal
mechanisms are unknown. Emissions due to the application of pesticides, for example, are
highly variable. They are affected by the volatility of the solvents in the pesticide,
meteorological conditions, the amount of vegetation sprayed, and the effect of biological
organisms (some of which metabolize the pesticide). Pesticide use and other area sources that
are affected by biological or other environmental processes are extreme examples of variable
sources. However, most sources show some sort of temporal variation because of variability in
activity patterns. For example, residential fuel consumption is higher in the winter than in the
summer. Commercial or industrial activity may be greater on weekdays than on weekends.
Preferred area source methods should minimize uncertainty due to variability whenever
possible. For most sources, the main source variability is in the temporal fluctuations in activity,
and is usually greatest on a daily or weekly basis (e.g., weekday versus weekend activity rates).
Some sources vary significantly between years, particularly if they are driven by extreme events
(spills, for example).
Good area source inventories will minimize the uncertainty due to temporal variability by
assuring that factors and activity data match the scale of the inventory. If factors or activity have
to be scaled up or down, adjustments must be made that account for temporal variability.
Similarly, any other adjustments to the calculation to account for variability should be made.
6.5 PARAMETER UNCERTAINTY
Parameter uncertainty is caused by three types of errors: measurement errors, sampling errors,
and systematic errors (nonrandom errors). Measurement errors occur because of the imprecision
of the instrument or method used to measure the parameters of interest. Where emissions are
measured directly, the measurement error of a particular method is usually known; EPA
typically uses the concept of relative accuracy to describe the performance of a measurement
method (or device) with respect to a EPA Reference Method. A more common measurement
error for area sources occurs from misclassification. For example, area source categories are
frequently identified by SIC Code group, and the number of employees or facilities in a
particular SIC group are used as the activity data. However, some SIC groups encompass a wide
variety of industrial processes and activities, not all of which are emissions sources. For
example, the number of office workers at one plant may cause emission estimates to be too high
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7/37/07 CHAPTER 1 - INTRODUCTION
if the emissions are estimated using a per employee factor. This can be a problem even when a
survey is used if the sample design does not account for subpopulations adequately. In addition,
facilities are sometimes listed under an incorrect SIC Code or more than one SIC Code may
apply. Any of these errors results in misclassification of data and adds to uncertainty about the
emissions estimates.
Sampling error is an important factor when one or more of the parameters (i.e., activity, factors,
or emissions) are to be estimated from a sample of the population. Although most people
recognize the importance of an adequate sample size, obtaining an adequate sample size is often
not feasible. Furthermore, sample data are usually used to estimate a mean value from which
the population total is extrapolated. This approach assumes that the underlying data are
normally distributed—an assumption that is often violated. Again, sampling error can be
minimized if proper statistical approaches are used, quality assurance procedures are followed,
and sample sizes are adequate and properly obtained.
Systematic (or nonrandom) errors are the most problematic sources of parameter uncertainty
because they are the most difficult to detect and reduce. They occur primarily because of an
inherent flaw in the data-gathering process or in the assumptions used to estimate emissions. A
common way that this happens is if the population to be sampled is not well-defined, and a
sample (thought to be random) is actually nonrandom. This is a fairly common problem for
certain types of industries. Take, for example, a local survey of solvent use by autobody
refmishing shops. One approach would be to develop a list of facilities from business
registrations, or other state/local business listings. However, this industry has a very large
number of "backyard" operations that are not identified in these official lists. Therefore, any
sample that did not recognize this fact would have systematic sampling errors. A solution in this
case is to identify retailers or suppliers for the industry.
6.6 MODEL UNCERTAINTY
This type of uncertainty applies to nearly all area sources. A model is a simplified
representation of reality. The simplest type of model uses activity multiplied by an emission
factor to estimate emissions. More complex computer models such as the Landfill Air
Emissions Estimation Model (LAEEM) and the Surface Impoundment Modeling System
(SIMS) are also used to estimate emissions. Model uncertainty stems from the use of surrogate
variables, exclusion of variables, and oversimplification of processes.
The use of surrogate variables is common in area source methods where population or the
number of employees are used as surrogates for emission activities. The uncertainty in using
these surrogates is especially high when emissions for a small region (i.e., county or smaller
area) are estimated using a national average factor. Local variations in activity are not
necessarily accounted for by using population or employment as an activity, and emissions. A
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common example is found in large cities that have the corporate headquarters for an industry.
The number of employees may be high, but all of the manufacturing may be occurring in other
areas.
Per capita emission factors are often an oversimplification of emission processes. An example
would be an emission factor developed from national solvent use figures and material balance.
If this type of factor is used, recognize that issues like a correspondence between emissions and
population or disposal of the product may not have been addressed.
This discussion of uncertainty in area source emissions is by no means exhaustive. More details
are provided in the specific area source chapters. EHP has encouraged the reduction in
uncertainty by recommending methods better than per capita or per employee factors wherever
possible. Unfortunately, this is not always practical. It is important that inventory preparers
recognize the sources of uncertainty, quantify it, and reduce it as much as is practical.
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REFERENCES
EPA. 2000. National Air Pollutant Emission Trends, 1900-1998. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North
Carolina.
EPA. 1999. Emissions Inventory Guidance for Implementation of Ozone and Particulate Matter
National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina.
EPA. 1995. Compilation of Air Pollution Emission Factors, Volume I: Stationary Point and
Area Sources, Fifth Edition, AP-42 (GPO 055-000-00500-1). U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina. January.
EPA. 1994. The Development and Improvement of Temporal Allocation Factor Files. Air and
Energy Engineering Research Laboratory, Office of Research and Development, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
EPA. 1993. Guidance for Growth Factors, Projections, and Control Strategies for the
15-PercentRate-of-Progress Plans. U.S. Environmental Protection Agency,
EPA-452/R-93-002. Research Triangle Park, North Carolina. March.
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VOLUME III: CHAPTER 2
RESIDENTIAL WOOD COMBUSTION
Revised Final
January 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
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DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Radian Corporation and revised by Eastern Research Group, Inc.
for the Area Sources Committee of the Emission Inventory Improvement Program and for
Charles Mann of the Air Pollution Prevention and Control Division, U.S. Environmental
Protection Agency. Members of the Area Sources Committee contributing to the preparation of
this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
ill
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IV El IP Volume IV
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CONTENTS
Section Page
1 Introduction 2.1-1
2 Source Category Description 2.2-1
2.1 Emission Sources 2.2-1
2.1.1 Fireplace Types 2.2-1
2.1.2 Woodstove Types 2.2-2
2.2 Factors Influencing Emissions 2.2-4
2.2.1 Process Operating Factors 2.2-4
2.2.2 Regulatory Issues 2.2-4
3 Overview of Available Methods 2.3-1
3.1 Emission Estimative Methodologies 2.3-1
3.2 Available Methodologies 2.3-1
3.3 Data Needs 2.3-1
3.3.1 Data Elements 2.3-1
3.3.2 Application of Controls 2.3-2
3.3.3 Spatial Allocation 2.3-3
3.3.4 Temporal Resolution 2.3-4
3.3.5 Projecting Emissions 2.3-5
4 Preferred Method for Estimating Emissions 2.4-1
4.1 Survey Planning 2.4-1
4.2 Survey Preparation 2.4-2
4.3 Survey Distribution 2.4-2
4.4 Survey Compilation and Scaling 2.4-2
4.4.1 Emission Estimation 2.4-4
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CONTENTS (CONTINUED)
Section Page
5 Alternative Method for Estimating Emissions 2.5-1
5.1 Emission Factors 2.5-2
5.2 Special Emission Calculation Issues 2.5-3
6 Quality Assurance/Quality Control 2.6-1
6.1 Emission Estimate Quality Indicators 2.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 2.6-1
6.1.2 Sources of Uncertainty 2.6-3
7 Data Coding Procedures 2.7-1
7.1 Necessary Data Elements 2.7-1
8 References 2.8-1
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TABLES
Page
2.4-1. Criteria Pollutant Emission Factors for Residential Wood Combustion 2.4-5
2.4-2. HAP Emission Factors for Residential Wood Combustion 2.4-6
2.4-3. Polycyclic Aromatic Hydrocarbon (PAH) Emission Factors
for Residential Wood Combustion 2.4-7
2.4-4. Factors To Convert Wood Volume (cubic feet) to Weight (pounds)
(EPA, 1995) 2.4-8
2.6-1. Preferred Method DARS Scores: Local Survey of a Sample of Residences 2.6-2
2.6-2. Alternative Method DARS Scores: National Emission Factors and
Apportioned Census Bureau Activity 2.6-2
2.7-1. Area and Mobile Source Category Codes for Residential Wood Combustion 2.7-2
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Vlll EIIP Volume IV
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
This chapter describes the procedures and recommended approaches for estimating emissions
from residential wood combustion. Section 2 of this chapter contains a general description of the
residential wood combustion category, and an overview of available control techniques.
Section 3 of this chapter provides an overview of available emission estimation methods.
Section 4 presents the preferred emission estimation method for residential wood combustion,
while Section 5 presents alternative emission estimation techniques. Quality assurance/quality
control are discussed in Section 6. Data coding procedures are discussed in Section 7, and
Section 8 is the reference section.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
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SOURCE CATEGORY DESCRIPTION
The area source category of residential wood combustion is defined as wood burning that takes
place primarily in woodstoves and fireplaces. Residential wood burning occurs either as a
necessary source of heat or for aesthetics. In the 1980's, woodstoves became more popular and
fireplaces became standard equipment in houses, townhouses, and some resorts. Residential
wood combustion could be a significant contributor of pollution in many areas of the country,
particularly in Colorado and states in New England and the Pacific Northwest. Pollutants
emitted from residential wood combustion include particulate matter (PM), volatile organic
compounds (VOC), hazardous air pollutants (HAPs), nitrogen oxides (NOX) and carbon
monoxide (CO).
2.1 EMISSION SOURCES
The following descriptions of wood-burning devices are derived from Compilation of Air
Pollutants Emission Factors, AP-42 (EPA, 1995a). More information about these sources can be
found in the primary references and background documents for the AP-42 sections pertaining to
wood combustion, Chapter 1, Sections 9 and 10.
2.1.1 FIREPLACE TYPES
Fireplaces can be divided into 2 broad categories: (1) masonry (generally brick and/or stone,
assembled on site, and integral to a structure) and (2) factory-built (usually metal, installed on
site as a package with appropriate duct work).
Masonry fireplaces typically have large fixed openings to the fire bed and have dampers above
the combustion area in the chimney to limit room air and heat losses when the fireplace is not
being used. Some masonry fireplaces are designed or retrofitted with doors and louvers to reduce
the intake of combustion air during use.
Factory-built fireplaces are commonly equipped with louvers and glass doors to reduce the intake
of combustion air, and some are surrounded by ducts through which floor level air is drawn by
natural or forced convection, heated, and returned to the room. Many varieties of factory-built
fireplaces are now available on the market. One general class is the freestanding fireplace, the
most common of which consists of an inverted sheet metal funnel and stovepipe directly above
the fire bed. Another class is the "zero clearance" fireplace, an iron or heavy gauge steel firebox
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
lined inside with firebrick and surrounded by multiple steel walls with spaces for air circulation.
Some zero clearance fireplaces can be inserted into existing masonry fireplace openings, and thus
are sometimes called "inserts." Some of these units are equipped with close fitting doors and
have operating and combustion characteristics similar to woodstoves.
Masonry fireplaces usually heat a room by radiation, with a significant fraction of the combustion
heat lost in the exhaust gases and through fireplace walls. Moreover, some of the radiant heat
entering the room goes toward warming the outside air that is pulled into the residence to make
up for that drawn up the chimney. The net effect is that masonry fireplaces are usually inefficient
heating devices. Indeed, in cases where combustion is poor, where the outside air is cold, or
where the fire is allowed to smolder (thus drawing outside air into a residence without producing
appreciable radiant heat energy), a net heat loss may occur in a residence using a fireplace.
Fireplace heating efficiency may be improved by a number of measures that either reduce the
excess air rate or transfer back into the residence some of the heat that would normally be lost in
the exhaust gases or through fireplace walls. As noted above, such measures are commonly
incorporated into factory-built units. As a result, the energy efficiencies of factory-built
fireplaces are slightly higher than those of masonry fireplaces.
Fireplace emissions are highly variable and are a function of many wood characteristics and
operating practices. In general, conditions which promote a fast burn rate and a higher flame
intensity enhance secondary combustion and thereby lower emissions. Conversely, higher
emissions will result from a slow burn rate and a lower flame intensity. Such generalizations
apply particularly to the earlier stages of the burning cycle, when significant quantities of
combustible volatile matter are being driven out of the wood. Later in the burning cycle, when
all volatile matter has been driven out of the wood, the charcoal that remains burns with
relatively few emissions.
2.1.2 WOODSTOVE TYPES
Woodstoves are commonly used in residences as space heaters. They are used both as the
primary source of residential heat and to supplement conventional heating systems.
There are five different woodstove categories:
• The conventional woodstove;
* The catalytic woodstove;
• The noncatalytic woodstove;
• The pellet stove; and
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1/31/01 CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
• The masonry heater.
Among these categories, there are many variations in device design and operation characteristics.
The conventional woodstove category comprises all woodstoves without catalytic combustors
that are not included in the other noncatalytic categories (i.e., noncatalytic and pellet).
Conventional stoves do not have any emission reduction technology or design features and, in
most cases, were manufactured before 1988. Stoves of many different airflow designs may be in
this category, such as updraft, downdraft, crossdraft, and S-flow.
Catalytic woodstoves are equipped with a ceramic or metal honeycomb device, called a
combustor or converter, that is coated with noble metals such as platinum and palladium. The
catalyst material reduces the ignition temperature of the unburned VOCs and CO in the exhaust
gases, thus augmenting their ignition and combustion at normal stove operating temperatures. As
these components burn, the temperature inside the catalyst increases to a point at which the
ignition of the gases is essentially self-sustaining.
Noncatalytic woodstoves do not employ catalysts but do have emission reducing technology or
features. Typical noncatalytic design includes baffles and secondary combustion zones.
Pellet woodstoves are fueled with pellets of sawdust, wood products, and other biomass materials
pressed into manageable shapes and sizes. These stoves have active air flow systems and unique
grate design to accommodate this type of fuel. Some pellet stove models are subject to the 1988
New Source Performance Standards (NSPS), while others are exempt due to a high air-to-fuel
ratio (i.e., greater than 35-to-l).
Masonry heaters are large, enclosed chambers made of masonry products or a combination of
masonry products and ceramic materials. These devices are exempt from the 1988 NSPS due to
their weight (i.e., greater than 800 kg). Masonry heaters are gaining in popularity as a cleaner
burning and heat efficient form of primary and supplemental heat, relative to other types of
woodstoves. In a masonry heater, a complete charge of wood is burned in a relatively short
period of time. The heat released is stored in the large thermal mass of masonry materials. This
"stored" heat is then slowly released to the surrounding area for many hours after the fire has
burned out.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
2.2 FACTORS INFLUENCING EMISSIONS
2.2.1 PROCESS OPERATING FACTORS
Fireplace and woodstove emissions are highly variable and are a function of many wood
characteristics and operating practices. In general, conditions which promote a fast burn rate and
a higher flame intensity enhance secondary combustion and thereby lower emissions. Secondary
combustion is especially important in wood burning because of the high volatile matter content
of wood, typically 80 percent by dry weight. Conversely, higher emissions will result from a
slow burn rate and a lower flame intensity. Such generalizations apply particularly to the earlier
stages of the burning cycle, when significant quantities of combustible volatile matter are being
driven out of the wood. Later in the burning cycle, when all volatile matter has been driven out
of the wood, the charcoal that remains burns with relatively few emissions (EPA, 1996).
2.2.2 REGULATORY ISSUES
The Clean Air Act Amendments of 1990 (CAAA) required that all areas in the country achieve
the National Ambient Air Quality Standard (NAAQS) for PM10 by December 31, 1994. The
EPA published technical guidance for reasonably available control measures (RACM) and best
available control measures (BACM) for control of paniculate matter (PM) from woodstoves to
achieve this goal of reducing PM10 emissions. Those areas that do not achieve PM10 attainment
by December 31, 1994, must apply BACM and develop a plan to meet the NAAQS by December
31, 2001. The only exceptions are those areas that were reclassified as serious after 1990; these
areas must attain the NAAQS for PM10 no later than the end of the tenth calendar year after the
area's designation as nonattainment. The BACM requirements include combinations of the
following control measures: the use of new technology woodstoves, improvements in wood
burning performance (e.g., control of wood moisture content, weatherization of homes), the use
of "no burn" days, public awareness and education programs, replacement or installation of gas-
burning equipment in fireplaces, and total banning of burning. The use of these BACM will
reduce VOC, HAPs, and CO along with PM, for measures that produce more complete
combustion of wood; for measures that reduce the occurrence of combustion, NOX will also be
reduced.
Considerations for projecting emissions from residential wood combustion should include the
potential applicability of RACM and/or BACM to the inventory region. Projection of emissions
should also address the potential for an increase in new homes in the inventory region, since
fireplaces are standard in many new homes. The future use of woodstoves is a more complicated
issue that is affected by weather patterns, electricity prices, increased public awareness,
environmental concerns, and socioeconomic factors.
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATIVE METHODOLOGIES
Selection of the appropriate estimation method depends on the relative significance of emissions
from this source in the inventory area and the data quality objectives (DQOs) of the inventory
plan. Refer to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for
discussions of inventory categories and DQOs. This section discusses the methods available for
calculating emission estimates from residential wood combustion and identifies the preferred
emission estimation method. A discussion of the data elements needed for each method is also
provided.
3.2 AVAILABLE METHODOLOGIES
The preferred and alternative methods to estimate activity factors for residential wood
combustion are as follows:
• Preferred Method: Residential Wood Survey
• Alternative Method: Census Bureau and Energy Information Administration
(EIA) Data Method
If an inventory is being prepared only for warm weather months—when wood burning is at a
minimum, if not nonexistent—the Preferred Method described below would not be a good use of
resources. In this case, the alternative method should be used.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements required to estimate emissions from residential wood combustion depend
partly on the method used and the level of detail required in the inventory.
The data elements needed to calculate emissions for this category when using the survey method
are:
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• Wood burned, in tons;
• Fireplace or woodstove type;
• Information needed for scaling up the inventory information (any or a
combination of the following):
distribution of rural/urban population in inventory area
landuse
economic distribution
age of residences
• Information on state and local regulations; and
• Degree heating days for inventory area.
The survey should also request information on seasonal variability.
The data elements needed to calculate emissions by the Census data method are:
• Distribution of rural/urban population in inventory area or Census data on
households heating with wood;
• Wood burning equipment type, if possible;
• Information on state and local regulations; and
• Degree heating days for inventory area.
3.3.2 APPLICATION OF CONTROLS
Controls for this category may be:
• Use of new technology woodstoves;
• Improvements in wood burning performance;
• Use of "no burn" periods;
• Public awareness and education programs;
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1/31/01 CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
• Replacement or installation of gas-burning equipment in fireplaces; and
• Total banning of burning.
An evaluation of applicable state or local regulations will give an indication of the adjustments
that should be made to emission estimates calculated by the Census data method. If the survey
method is used, the state and local regulations affecting this source category should be reviewed
during the inventory planning stage, and the survey should be prepared so that information about
new technology, lower-emitting woodstoves can be collected.
Since the use of lower-emitting woodstoves represents an irreversible process change, rule
effectiveness (RE) usually can be assumed to be 100 percent for those households with the new
woodstoves. However, it is unlikely that rule penetration will be 100 percent within an area.
Factors that will affect rule penetration will include:
• Residences with woodstoves installed before the regulations came into effect;
• The ease in which consumers can purchase and install woodstoves that do not
conform to the current regulations; and
• The consumer's understanding and willingness to purchase and use the lower-
emitting woodstoves.
Control efficiency is reflected in the lower emission factors of the new technology woodstoves.
However, from field tests it is apparent that control efficiencies of the new, low emission stoves
drop after only a few years of use if preventative maintenance is not performed (EPA, 1994b).
3.3.3 SPATIAL ALLOCATION
Spatial allocation may be needed during the inventory preparation to allocate:
• State or regional activity to local level; and
• County-level emission estimates to a modeling grid cell.
Spatial allocation issues for the Census data method are included in the description of the
alternative method in Section 5. Information that is typically used for spatial allocation can also
be used to develop surrogate factors for scaling up the information gathered by the survey
method. Scaling up survey information is discussed in Section 4.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
3.3.4 TEMPORAL RESOLUTION
Seasonal Apportioning
Residential wood combustion is strongly dependant on the season temperature. If the preferred
method is used, the survey should attempt to collect information about wood burned during only
the inventory months. The alternative to survey information is allocation using heating degree
days.
The method for allocating residential wood burning using heating degree days is as follows:
• Obtain the number of heating degree days for the inventory season and for the
entire year.
A heating degree day is a measure of the amount of heating necessary for a
particular day. One heating degree day is registered for each degree below
65° F that the day's average temperature is.
This information can be obtained from state climatological offices,
airport meteorology stations, or National Oceanographic and
Atmospheric Administration (NOAA) climate data1.
0 i T- i * i T- i ( Number of Heating
Seasonal fuel Annual fuel ^ ^ 0
„ „ Degree Days in Season
Consumption = Consumption •
Space Heating) For Space Heating Total Heating
^ Degree Days Annually
(2.3-1)
For example, if the heating degree days for an entire year in an inventory area are 2430, and
the heating degree days for the inventory period (90 days) are 1800, then the apportioning
factor for the inventory area is:
n _. 1800 inventory period heating degree days
0.74 = — — (2 3-2)
2430 annual heating degree days
A seasonal activity factor of 0.43 can be used for the 3 month winter wood-burning season, if
other approaches are not possible (EPA, 1991).
1 See the most recent publication, which can be obtained from the National Climatic Data
Center, Asheville, NC; refer to http://www.ncdc.noaa.gov/.
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1/31/01 CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
Daily Resolution
Residential wood combustion is assumed to occur seven days a week during the heating
season.
3.3.5 PROJECTING EMISSIONS
Residential wood combustion is unlike many other area source categories in that population
growth and development may not necessarily be reflected in growth for this source category.
Projections of wood combustion activity should be based on the same factors used to spatially
allocate activity. The EIIP Projections Committee has developed a series of guidance
documents containing information on options for forecasting future emissions. You can refer
to these documents at http://www.epa.gov/ttn/chief/eiip/project.htm.
If the survey method is used to collect activity data for this category, and the data can be
broken down to types of woodstoves in use, then controls will be reflected in the emission
factors used. Rule effectiveness must be considered to account for failures and uncertainties
that may affect the actual performance of the control. Some woodstove designs may not need
any consideration of RE. However, some designs such as woodstoves equipped with catalytic
converters may degrade over time if preventive maintenance is not performed.
If detailed information about the types of woodstoves used, especially lower-emitting
woodstoves, has not been collected, then projecting emissions is more complex. Estimates of
the amount of wood being burned in lower-emitting woodstoves in comparison to the total
amount of wood being burned are used to develop a value for rule penetration. Rule
penetration, control efficiency and rule effectiveness are discussed in more depth in Chapter 1,
Introduction to Area Source Emission Inventory Development.
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
The preferred method for calculating emission estimates from residential wood combustion is
a survey of residences in the inventory area. The main steps in developing an emission
estimate through a survey are: (1) survey planning, (2) survey preparation, (3) survey
distribution, (4) survey compilation and scaling, and (5) emission estimation. These steps will
be discussed below.
4.1 SURVEY PLANNING
Planning a survey for this source category will include many of the same survey
considerations discussed in Chapter 1, Introduction to Area Source Emission Inventory
Development under Surveys, in Section 6. (The reader is also encouraged to review Chapter
24 for more information in conducting an area source survey). However, some source-specific
issues apply. An example of a multi-state survey of resident wood fuel use can be found in
Residential Fuelwood Consumption and Production in the Plains States, 1994 (USD A,
1996). A survey of residences will need to be a representative sample of all of the residences
in the inventory area so that information gathered on residential combustion can be scaled up
(refer to the EJIP QA volume for more information on scaling up surveys). Issues that should
be determined at this stage are:
• The necessary sample size;
• The number of surveys that will need to be sent in order to achieve the sample
size;
• The demographic factors that will be used to scale up the survey results to the
entire survey area, including how to collect that information; and
• The level of detail needed, for instance:
Is the inventory for an average day, an average week, or the entire
season, thus requiring activity data for one of those time periods?
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
Should the inventory include information about the use of controls or
other factors that would require data on the different types of
woodstoves being used?
Details about how to conduct a residential wood burning survey may be obtained by
contacting the state and local air pollution agencies in the areas of high wood burning in the
United States (e.g., Seattle, Washington; Portland, Oregon; Denver, Colorado; or Montana).
4.2 SURVEY PREPARATION
Survey questions should be tailored to suit the inventory region and the needs of the inventory.
General points that should be included in a survey sent to a representative sample of
residences are:
• An explanation of why the survey is necessary, and how more information is
beneficial to the public;
• Questions that request the information needed to scale up the inventory (this
should be simple, a zip code may suffice); and
• An attachment that describes the different woodstove types.
Example questions for a residential wood survey are shown in Example 4-1.
4.3 SURVEY DISTRIBUTION
Survey distribution will be determined by the budget for this category. Surveys can be
distributed by a mailing, or the information can be collected through a telephone survey.
Initial contacts and followup contacts may also be undertaken as part of the survey. Survey
distribution issues are discussed in Chapter 1, Introduction to Area Source Emission Inventory
Development under Surveys, in Section 6 and in Chapter 24, Conducting Surveys for Area
Source Inventories.
4.4 SURVEY COMPILATION AND SCALING
Survey compilation and scaling is discussed in theEIIP QA volume of this series.
Scaling up the survey may be done using the following types of information:
• Distribution of rural/urban population in inventory area;
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1/31/01 CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
• Landuse;
• Household economic distribution; and
• Age of residences.
Example 4-1
• Do you have a fireplace or woodstove? (If not, please return the survey
without answering any more questions)
• What type of wood-burning equipment do you have? (See descriptions of
woodstove types at the end of this survey)
Fireplace
Conventional woodstove
Noncatalytic woodstove
Catalytic woodstove
Pellet stove
Masonry heater
Woodstove, do not know what type
• How often do you burn wood in a winter week?
times per week all week
• How much wood do you burn in an average winter week?
cords* (example: 1/4 cord)
• How often do you burn wood in the rest of the year, per week?
*Note: One cord is equal to a stack of wood 4x4x8 feet. One full-size pickup truck
load is about one-half of a cord.
Planning prior to the survey should include an investigation of the best surrogate for scaling
the survey information. Then, the survey can request the necessary information.
In addition to the QA/QC issues common to all survey efforts, checks should be put into place
for the woodstove types entered and the amount of wood used. These entries will probably be
the most likely to be in error. The conversion from wood used in cords to wood used in tons,
which is dependant on wood species, could also be a source of error.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
4.4.1 EMISSION ESTIMATION
After data from the surveys have been compiled and scaled up to the inventory area, the
resulting activity data, in the form of wood burned in tons for each equipment type, should
then be applied to emission factors provided in Tables 2.4-1 through 2.4-3. Residential
woodstoves are classified as Phase I, Phase n and Pre-Phase I. Phase n stoves are those
certified to meet the July 1, 1990, EPA standards; Phase I stoves meet only the July 1, 1988,
EPA standards; and Pre-Phase I stoves do not meet any of the EPA standards but in most
cases do necessarily meet the Oregon 1986 certification standards. AP-42 contains PM10 and
CO emission factors for catalytic and noncatalytic woodstoves in each of these classifications,
but only emission factors for Phase JJ are presented here. Information on how the AP-42
emission factors were developed can be found in the AP-42 woodstoves section. Factors from
the latest edition AP-42 should be used for emission estimates. At the time of this writing, no
factors for PM2 5 are available. Jf PM25 emission estimates are required for an inventory, it can
be assumed that all of the PM10 is PM2 5 (EPA, 1997). Emissions estimated using this
assumption should not be perceived to be of the same level of quality as the factors found in
AP-42, and if new AP-42 factors became available, they should supersede emission factors
that are presented here.
Table 2.4-4 gives density conversion factors for hardwoods and softwoods by typical forest
type within a region. These generalized factors represent a weighted average density of the
three most common (in terms of volume) softwood or hardwood species within the forest type.
Forest types are identified by the primary tree species or tree species groups, but will include
other tree species that are typically found in that biome. Local or state forestry service
personnel should be able to identify an typical forest type for an area. Although densities for
softwoods are provided, it is most likely that wood used for fuel will be hardwoods.
One cord of wood can be assumed to be about 79 cubic feet of solid wood (no air spaces).
AP-42 Appendix A also contains more general conversion factors. The more detailed factors
in Table 2.4-4 are preferred.
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1/31/01
CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
TABLE 2.4-1
CRITERIA POLLUTANT EMISSION FACTORS FOR
RESIDENTIAL WOOD COMBUSTION (LB/TON)S
Process Description
Residential Total Woodstoves and Fireplaces'5
Residential Fireplaces0
Residential Woodstoves - Catalytic Phase II
Residential Woodstoves - Noncatalytic Phase II
Residential Woodstoves - Conventional
Residential Woodstoves - Pellet/Certified11
Residential Woodstoves - Pellet/Exempt6
Masonry Heatersf
Criteria Pollutant
Emission Factors
PM10
34.6
34.6
16.2
14.6
30.6
4.2
8.8
5.6
NO,
2.6
2.6
2.0
2.8
13.8
CO
252.6
252.6
107.0
140.8
230.8
39.4
52.2
149.0
voc
229.0
229.0
15.0
12.0
53.0
so,
0.4
0.4
0.4
0.4
0.4
0.4
a Source: EPA, 1995a.
b These emission factors are for fireplaces and should be used when information separating wood burning
equipment types is not available.
0 Exempt from the 1988 New Source Performance Standards for woodstoves because of air: fuel ratio > 15:1
and/or minimum burn rate > 5 kg/hr.
d Certified pursuant to the 1988 New Source Performance Standards for woodstoves.
e Exempt from the 1988 New Source Performance Standards for woodstoves because of air: fuel ratio >3 5:1.
f Exempt from the 1988 New Source Performance Standards for woodstoves because of weight > 800 kg.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
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TABLE 2.4-2
HAP EMISSION FACTORS FOR
RESIDENTIAL WOOD COMBUSTION (LB/TON)a
HAP
Benzene
Cadmium
Chromium
Manganese
Methyl Ethyl Ketone
Nickel
Phenol
Toluene
O-Xylene
Woodstove Type
Conventional
1.94E-00
2.2E-05
<1.0E-06
1.7E-04
2.9E-01
1.4E-05
7.3E-01
2.0E-01
Noncatalytic
2.0E-05
<1.0E-06
1.4E-04
2.0E-05
<1.0E-03
Catalytic
1.46E-00
4.6E-05
<1.0E-06
2.2E-04
6.0E-02
2.2E-06
5.2E-01
1.9E-01
Source: EPA, 1995a
2.4-6
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1/31/01
CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
TABLE 2.4-3
POLYCYCLIC AROMATIC HYDROCARBON (PAH) EMISSION FACTORS FOR
RESIDENTIAL WOOD COMBUSTION (LB/TON)A
Pollutant
PAH
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a)Anthracene
Benzo(b)Fluoranthene
Benzo(g,h,i)Fluoranthene
Benzo(k)Fluoranthene
Benzo(g,h,i)Perylene
Benzo(a)Pyrene
Benzo(e)Pyrene
Biphenyl
Chrysene
Dibenzo(a,h)Anthracene
7, 12-Dimethylbenz(a)Anthracene
Fluoranthene
Fluorene
Indeno(l ,2,3,cd)Pyrene
9-Methylanthracene
12-Methylbenz(a)Anthracene
3 -Methylchlolanthrene
1 -Methylphenanthrene
Naphthalene
Nitronaphthalene
Perylene
Phenanthrene
Phenanthrol
Phenol
Pyrene
PAH Total
Stove Type
Conventional
0.010
0.212
0.014
0.020
0.006
0.002
0.004
0.004
0.012
0.012
0.000
0.020
0.024
0.000
0.288
0.078
0.024
0.730
Noncatalvtic
0.010
0.032
0.009
< 0.001
0.004
0.028
< 0.001
0.020
0.006
0.002
0.022
0.010
0.004
0.004
0.008
0.014
0.020
0.004
0.002
< 0.001
0.030
0.144
0.000
0.002
0.118
0.000
< 0.001
0.008
0.500
Catalvtic
0.006
0.068
0.008
0.024
0.004
0.006
0.002
0.002
0.004
0.004
0.010
0.002
0.012
0.014
0.004
0.186
0.048
0.010
0.414
Exemot Pellet"
2.60 E-05
7.52 E-05
5.48 E-05
3.32 E-05
4.84 E-05
2.38 E-04
a Source: EPA, 1995a
b Only the woodstoves exempt from the 1988 New Source Performance Standards for woodstoves because of
air fuel ratio > 35:1.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
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TABLE 2.4-4
FACTORS TO CONVERT WOOD VOLUME (CUBIC FEET) TO
WEIGHT (POUNDS)*
Region
Southeast and
South Central
Northeast and
Mid Atlantic
North Central and
Central
Rocky Mountain and
Pacific Coast
Forest Type
Pines
Oak-Hickory
Oak-Pine
Bottomland Hardwoods
Pines
Spruce-Fir
Oak-Hickory
Maple-Beech-Birch
Bottomland Hardwoods
Pines
Spruce-Fir
Oak-Hickory
Maple-Beech
Aspen-Birch
Bottomland Hardwoods
Douglas Fir
Ponderosa Pine
Fir-Spruce
Hemlock-Sitka Spruce
Lodgepole Pine
Larch
Redwoods
Hardwoods
Density Conversion Factors
Softwood
31.8
33.4
32.6
28.7
23.6
23.0
23.3
24.0
28.7
26.3
21.9
26.0
23.2
23.1
28.7
29.5
26.0
21.8
27.1
26.4
31.7
26.0
26.5
Hardwood
39.9
39.9
39.9
36.2
33.8
32.8
39.7
37.4
36.2
33.1
30.0
39.4
35.9
29.0
36.2
23.7
23.7
23.7
27.0
23.7
27.0
36.2
24.0
Source: EPA, 1995b.
2.4-8
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ALTERNATIVE METHOD FOR
ESTIMATING EMISSIONS
The alternative method to estimate activity factors for residential wood combustion uses
information on residential wood data compiled by state or federal agencies, and apportioned
using data from the U.S. Census Bureau and the U.S. Energy Information Administration.
The emission factors used for the preferred method are also used for the alternative method.
The preferred source of information on residential wood burning is the state energy office, or
state forest service. Available information may be estimates of wood burned for residential
heating at the state, regional or county level. Inventory personnel should try to collect the
most detailed and area-specific information possible.
If the state energy office does not have information on residential wood burning, other sources
of information for area-wide wood use, or per household wood use should be identified.
USDA Forest Service regional experiment stations may compile information that may be
useful. One such document is a special study prepared by the North Central Forest
Experiment Station in St. Paul, Minnesota (USDA, 1996). This study compiled residential
wood use statistics for Kansas, Nebraska, North Dakota, and South Dakota, including average
per household fuelwood consumption.
Other information resources are documents compiled by the U.S. Department of Energy
(DOE), Energy Information Administration (EIA). Statistics for wood fuel use can be found
in the EIA's Residential Energy Consumption Survey: Household Energy Consumption and
Expenditures1, published triennially, and state wood use data can be found in the State Energy
Data Report, which is published annually by the EIA.
1 See the publication for the year closest to the inventory year, which can be obtained from
the U.S. DOE, EIA, Washington, DC. The EIA maintains a Web site at:
http://www.eia.doe.gov/index.html.
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
The wood burned at the state level is apportioned to the county level using U.S. Census1 data
on households that use wood as a primary fuel. The equation is:
County c. . „, , TT County Wood-Burning Households
«r j TT = State Wood Use * n ^.\\
Wood Use State Wood-Burning Households v ' '
State level wood use (in cords) is available in the EIA' s State Energy Data Report. State and
county statistics on wood-burning households are available from the U.S. Census Bureau.
Cords of wood are converted to pounds of wood using factors in Table 2.4-4 orAP-42
Appendix A. Example 5-1 shows this process for one county.
If desired, determine the type of wood burning equipment in the inventory region by
performing a survey to apportion the wood used in fireplaces and woodstoves, by type.2 In
some areas with homogeneous housing (by age and economic level), a survey of a
representative number of households can be performed and scaled-up to the inventory area.
Information on the use of new technology woodstoves can be obtained from the state
environmental agency, woodstove vendors in the area, and the Hearth Products Association.3
5.1 EMISSION FACTORS
The preferred emission factors for estimating emissions from residential wood combustion are
shown in Tables 2.4-1 through 2.4-3. Emission factors for the relevant criteria pollutants are
shown in Table 2.4-1; emission factors for the relevant HAPs are shown in Tables 2.4-2 and
2.4-3. When information about the different woodstove types is not available, use the
emission factors for conventional woodstoves. If no distinction has been made between
fireplaces and woodstoves, use the emission factors for fireplaces.
1 See the publication for the year closest to the inventory year, which can be obtained from
the U.S. Commerce Department, Census Bureau. The Census Bureau also maintains a Web Site
which allows for interactive queries of Census data: http://venus.census.gov/cdrom/lookup. The
Census Summary Tape File 3 (STF3 A) contains this information.
2 Conventional, catalytic, noncatalytic (new technology), masonry, or pellet fired.
3 Located in Washington, DC, the Heart Products Association maintains a web at
http://www.heartassoc.org/.
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1/31/01 CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
Example 5-1:
For a 1993 inventory, the wood used in State A is obtained from the EIA's State Energy
Data Report for that year. The wood used for residential energy is listed in Table 18,
Residential Energy Consumption Estimates, under the classification of Biofuels, and is
622 thousand cords. U.S. Census data on house heating fuel is available for the year 1990,
and that data will be used to apportion the state wood use data to the county level. There
are 80,047 households using wood as a primary fuel at the state level, and 1242
households using wood as a primary fuel at the county level. To apportion the state level
wood usage:
County ,»~ nnn , 1,242
«r A TT = 622,000 cords * —
Wood Use go 047
= 9,651 cords
To calculate the wood weight from the number of cords, one cord is estimated to be about
79 ft3 solid wood (air spaces are removed). State A is a southeastern state, so the specific
gravity of the wood is estimated to be 0.639 for a southeastern hardwood, and the specific
gravity is multiplied by the weight of a cubic foot of water (62.4 Ibs). The calculation is:
u+ , cords * 79 ft3 * 0.639 * 62.4 Ib
Weight
= 30,400,789 Ib
= 15,200 tons
5.2 SPECIAL EMISSION CALCULATION ISSUES
To calculate wood use for a season day from annual wood use, the wood used for heating
should be separated from wood used for other year-round purposes and apportioned to the
season according to the number of days where space heating is needed. The method is as
follows:
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
If wood is used for appreciable amounts of water heating and cooking as well as space heating
in an inventory area, a survey should be performed to apportion wood use between space
heating and the other uses. The use of wood for cooking and water heating is negligible in
most regions.
The use of wood for space heating can be apportioned from the annual amount of wood
burned to that burned for a season-day by one of the methods listed in Section 3 under
Temporal Re solution. These methods are, in order of preference:
• Survey of residences;
• Heating degree days allocation; and
• Seasonal activity factor.
Section 3 discusses the heating degree day and seasonal activity factor methods.
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QUALITY ASSURANCE/QUALITY
CONTROL
During the inventory planning process, the agency should define the data quality objectives for
the inventory, and set data quality goals for the emission estimates developed for this source
category. Quality assurance and quality control methods may vary based on the data quality
objectives for the inventory. The Quality Assurance Source Document of this series of
volumes discusses methods to be used to ensure the development of a quality inventory.
Quality assurance for area source inventories is also discussed in Chapter 1 of this volume,
Introduction to Area Source Emission Inventory Development.
When using the preferred survey method, the survey method, sample design, and data
handling should be planned and documented in the Quality Assurance Plan. Special care
should be taken when compiling surveys for this source to ensure that equipment types are
properly assigned, that wood use units are correct, and conversions of wood use are correct.
When using the alternative method, data handling for all activity and emission factor data
should be planned and documented in the Quality Assurance Plan.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The preferred method will produce the most accurate and detailed estimate of emissions;
however, surveys can be an expensive undertaking. Furthermore, the success of the survey
depends heavily on the rate and completeness of the responses. The level of effort required
for the Census data method is considerably lower, but the potential accuracy and detail in
regard to the equipment type in use will be lower.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be
found in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following
discussion uses the DARS rating system as a way to compare the estimation approaches
presented in this chapter and analyze their strengths and weaknesses. The DARS scores for
each method are summarized in Tables 2.6-1 and 2.6-2. All scores assume that good QA/QC
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
1/31/01
measures are performed and no deviations from good inventory practice have been made. If
these assumptions are not met, new DARS scores should be developed according to the
guidance provided in the QA Source Document.
TABLE 2.6-1
PREFERRED METHOD DARS SCORES: LOCAL SURVEY OF A SAMPLE OF RESIDENCES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
5
7
9
9
0.75
Activity
7.5
7
8
8
0.76
Emissions
0.375
0.49
0.72
0.72
0.58
Comments: Temporal scores will go down for the factors as time increases (i.e., the further you get from survey
date).
TABLE 2.6-2
ALTERNATIVE METHOD DARS SCORES: NATIONAL EMISSION FACTORS AND
APPORTIONED CENSUS BUREAU ACTIVITY
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
5
5
9
9
0.7
Activity
6
6
3-6
7.5
0.23-0.64
Emissions
0.3
0.3
0.27-0.54
0.68
0.16-0.46
2.6-2
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Both of the methods presented in this chapter use the same emission factors, so the DARS
scores for the emission factor attributes are the same, except for the source specificity
category. The Census data activity method will not provide information about the types of
woodstoves in use in an area. If a limited survey is performed to provide that level of detail,
then source specificity will be equivalent to that for the preferred method. The key difference
between the two methods is the collection of the activity data, and in particular, assigning
activity to the correct location.
6.1.2 SOURCES OF UNCERTAINTY
Another way to assess the emission estimates is to look at the associated uncertainty. For
estimates derived from survey data, the uncertainty can be quantified (see the QA Source
Document, Chapter 4). Statistics needed to quantify the uncertainty for emissions derived by
the Census data activity method are incomplete.
The uncertainty for emission estimates derived from the survey method is affected by several
variables. These variables are:
• The sample size;
• Whether the surrogate used for scaling up the survey data is appropriate for the
source category activity;
• Accurate description of the woodstove type;
• Accurate estimation and unit conversion for the wood burned; and
• Unquantifiable degradation of the control efficiency of lower emission
woodstoves, especially catalytic woodstoves (EPA, 1994b).
Uncertainty of emission estimates developed by using the Census data method depend on the
level of detail that the inventory preparer goes to in collecting activity information. The
activity can be viewed as a combination of information, all of which could be more or less
reliable. This method requires:
• An estimate of wood use in the state or region;
• Information that can be used to apportion the wood use to the inventory area,
and to the individual counties within the inventory area;
• The choice of collecting woodstove type information in the inventory area; and
EIIP Volume IV 2.6-3
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION 1/31/01
• The choice of using survey, heating degree days or a seasonal activity factor for
seasonal apportioning of the emission estimates.
Thus, decisions regarding the source and quality of the state or regional wood use data, and the
spatial and temporal apportioning will determine the uncertainty of the resulting emission
estimates.
2.6-4 EIIP Volume IV
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from residential wood
combustion. A complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 2.7-1 lists the applicable SCCs for residential
wood combustion.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation.
Consistent categorization and coding will result in greater continuity between emission
inventories for use in regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data
elements necessary to complete the data set for use in regional or national air quality and
human exposure modeling. The inventory preparer should review the area source portion of
the acceptable file format(s) to understand the necessary data elements. The EPA describes its
use and processing of the data for purposes of completing the national inventory, in its Data
Incorporation Plan, also located at http://www.epa.gov/ttn/chief/net/.
EIIP Volume IV 2.7-1
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CHAPTER 2 - RESIDENTIAL WOOD COMBUSTION
1/31/01
TABLE 2.7-1
AREA AND MOBILE SOURCE CATEGORY
CODES FOR RESIDENTIAL WOOD COMBUSTION
Process Description
Residential Wood Combustion - Total: Wood Stoves and Fireplaces
Residential Wood Combustion - Fireplaces
Residential Wood Combustion - Woodstoves: General
Residential Wood Combustion - Catalytic Woodstoves: General
Residential Wood Combustion - Non-Catalytic Woodstoves: General
Residential Wood Combustion - Non-Catalytic Woodstoves: Conventional
Residential Wood Combustion - Non-Catalytic Woodstoves: Low Emitting
Residential Wood Combustion - Non-Catalytic Woodstoves: Pellet Fired
Source Category Code
21-04-008-000
21-04-008-001
21-04-008-010
21-04-008-030
21-04-008-050
21-04-008-051
21-04-008-052
21-04-008-053
2.7-2
El IP Volume IV
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8
REFERENCES
EIA. 1997. Residential Energy Consumption Survey (REC): Household Energy Consumption
and Expenditures, Supplement: Regional. U. S. Department of Energy, Energy Information
Administration, Washington, DC. Published every three years. Last year published at the date
of this document: 1997.
EPA. 1997. National Air Pollutant Emission Trends Procedures Document for 1900 - 1996.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards. Research
Triangle Park, N.C.
EPA. 1996. Compilation of Air Pollutant Emission Factors—Volume I: Stationary Point and
Area Sources. Fifth Edition Supplement, AP-42. U. S. Environmental Protection Agency, Office
of Air Quality Planning and Standards. (GPO 055-000-00251-7). Research Triangle Park, North
Carolina, http://www.epa.gov/ttn/chief/ap42/ap42supp.html.
EPA. 1995b. State's Workbook, Methodologies for Estimating Greenhouse Gas Emissions.
U.S. Environmental Protection Agency, Office of Policy, Planning and Evaluation. Washington,
D.C.
EPA. 1994a. AIRS Database. U. S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1994b. Jaasma, D.R., C.H. Stern and M. Champion. Field Performance of Woodburning
Stoves in CrestedButte during the 1991-92 Heating Season. U.S. Environmental Protection
Agency, EPA-600/R-94-061 (NTIS PB 94-161270). Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Vol.1. EPA-450/4-91-016, May 1991.
EPA. 1989. Guidance Document for Residential Wood Combustion Emission Control
Measures. U. S. Environmental Protection Agency, EPA-450/2-89-015. Research Triangle
Park, North Carolina.
USDA. 1996. Residential FuelwoodConsumption and Production in the Plains States, 1994.
USDA Forest Service, North Central Forest Experiment Station. Resource Bulletin NC-173.
St. Paul, Minnesota.
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2.8-2 El IP Volume IV
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VOLUME III: CHAPTERS
ARCHITECTURAL SURFACE
COATING
November 1995
Prepared by:
Radian Corporation
Post Office Box 13000
Research Triangle Park, North Carolina
27709
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Lucy Adams and Donna Lee Jones of Radian Corporation for
the Area Sources Committee of the Emission Inventory Improvement Program and for
Charles Mann of the Air Pollution Prevention and Control Division, U.S. Environmental
Protection Agency. Members of the Area Sources Committee contributing to the preparation
of this document are:
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Dennis Goodenow, California Air Resources Board
Kwame Agyei, Puget Sound Air Pollution Control Agency
Mike Fishburn, Texas Natural Resource Conservation Commission
Larry Jones, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Gwen Judson, Wisconsin Department of Natural Resource
Jo Crumbaker, Maricopa County Air Pollution Control
Linda Murchison, California Air Resources Board
Sally Otterson, Washington Department of Ecology
Lee Tooly, Emission Factor and Inventory Control, U.S. Environmental Protecton Agency
Chris Mulcahy, Connecticut Department of Environmental Protection
Jim Wilkinson, Maryland Department of the Environment
George Leney, Allegheny County Health Department
-------
CONTENT
Section Page
1 Introduction 1-1
2 Source Category Description 2-1
Emission Sources 2-2
Factors Influencing Emissions 2-2
Process Operating Factors 2-2
Control Techniques 2-2
3 Overview of Available Methods 3-1
Emission Estimation Methodologies 3-1
Available Methodologies 3-1
Volatile Organic Compounds 3-1
Hazardous Air Pollutants 3-2
Data Needs 3-2
Data Elements 3-2
Application of Controls 3-3
Spatial Allocation 3-4
Temporal Resolution 3-4
Projecting Emissions 3-5
4 Preferred Methods for Estimating Emissions 4-1
Survey Planning 4-1
Survey Preparation 4-2
Survey Distribution 4-8
Survey Compilation and Scaling 4-8
Emission Estimation 4-8
5 Alternative Methods for Estimating Emissions 5-1
iv Volume III
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CONTENT
Section Page
6 Quality Assurance/Quality Control 6-1
Emission Estimate Quality Indicators 6-1
Data Attribute Rating System (DARS) Scores 6-1
Sources of Uncertainty 6-4
7 Data Coding Procedures 7-1
Process and Control Codes 7-1
8 References 8-1
Volume III v
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FIGURES AND TABLES
Figure Page
4-1 Survey Request Form for Architectural Surface Coating Suppliers and Manufacturert-4
4-2 Example Architectural Coating Types 4-7
Table Page
2-1 State VOC Limits (Grams VOC/Liter Coating, Less Water) 2-4
4-1 Architectural Surface Coating Request Form 4-5
5-1 Quality and Value of Shipments of Paint and Allied Product 5-3
5-2 Emission Factors for Architectural Surface Coatings (EPA, 1993a) 5-7
5-3 VOC Species Profile for Water-Based Architectural Surface Coating
(CARB, 1991) 5-7
5-4 VOC Species Profile for Solvent-Based Architectural
Surface Coating (CARB, 1991) 5-9
6-1 Preferred Method DARS Scores: Survey of Coating Use
by Types in the Inventory Region 6-2
6-2 Alternative Method DARS Scores: National Factors Applied to
National Per Capita Usage 6-3
6-3 Alternative Method DARS Scores: Regulatory Limits Applied to
National Per Capita Usage 6-3
7-1 AIRS AMS Codes for Architectural Surface Coating 7-2
7-2 Airs Control Device Codes 7-3
vi Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from architectural surface coating. Section 2 of this chapter contains a general description of
the architectural surface coating category, and an overview of available control technologies.
Section 3 of this chapter provides an overview of available emission estimation methods.
Section 4 presents the preferred emission estimation method for architectural surface coatings,
while Section 5 presents alternative emission estimation techniques. Quality assurance and
control procedures are described in Section 6. Coding procedures used for data input and
storage are discussed in Section 7, and Section 8 is the reference section.
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1-2 Volume III
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SOURCE CATEGORY DESCRIPTION
Architectural surface coating operations (SIC 17) consist of applying a thin layer of coating
such as paint, paint primer, varnish, or lacquer to architectural surfaces, and the use of
solvents as thinners and for cleanup. Architectural surface coatings protect the substrates to
which they are applied from corrosion, abrasion, decay, ultraviolet light damage, and/or the
penetration of water. Some architectural coatings also increase the aesthetic value of a
structure by changing the color or texture of its surface. Architectural coatings are also
important in construction of structures. Examples of the latter are concrete form release
compounds, which prevent concrete from sticking to forms, and concrete curing compounds,
which allow concrete to cure properly (Brandau, 1990). It should be noted that this category
does not include auto refmishing, traffic marking, surface coating during manufacturing,
industrial maintenance coatings, special purpose coatings, or paints used in graphic arts
applications.
A wide range of coatings are used to cover both the interior and exterior surfaces of
architectural structures. The majority of architectural surface coatings are applied by
homeowners and painting/surface coating contractors to domestic, industrial, institutional, and
governmental structures throughout a geographic area. Because the emissions from this
source category are likely to be scattered throughout the inventory region, it is recommended
that this source category usually be treated as an area source. However, emissions from this
category may also be estimated as one of many processes occurring at a point source, for the
purposes of permitting and emission trade offs.
Because the coated architectural surface dries or cures in the ambient air, the use of exterior
architectural coatings may be limited to periods when local climatic conditions facilitate
acceptable coating curing. Although interior coating applications are less influenced by
outdoor conditions, complete curing of these coatings also can be hampered by cool, moist
weather (i.e., when evaporation rates are reduced).
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
EMISSION SOURCES
Volatile organic compounds (VOCs) that are used as solvents in the coatings are emitted
during application of the coating and as the coating dries.a The amount of coating used and
the VOC content of the coating are the factors that primarily determine emissions
from architectural surface coating operations. Secondary sources of VOC emissions are from
the solvents used to clean the architectural coating application equipment and VOC released
as reaction byproducts while the coating drys and hardens. VOC emitted from this chemical
reaction is determined by the resins used in a particular coating. The VOC emitted from any
of these sources could include HAP (EPA, 1993a).
Emission factors and area source estimation methods have been developed for VOC and HAP
emissions but not for PM emissions. If all architectural surface coatings are applied using
brushes and rollers, then it is reasonable not to consider PM emissions. However, many
commercial paints use spray guns; if a significant amount of the paint is applied in this
manner (particularly to exterior surfaces), then inventories of PM may need to address
emissions from this source category. Point source methods and factors can be used to
estimate PM emissions from architectural surface coatings.
FACTORS INFLUENCING EMISSIONS
PROCESS OPERATING FACTORS
Structural maintenance practices indirectly influence VOC emissions by controlling the total
coating consumption on a long-term basis. Regular inspection and maintenance programs can
be used to reduce the need for entire surface recoating (Brandau, 1990).
CONTROL TECHNIQUES
Since the use of organic solvents in architectural surface coatings is the primary source of
emissions, control techniques for this source category involve either product substitution or
product reformulation. These alternate formulations include low-solvent-content coatings,
waterborne coatings, and powder coatings. In certain situations, recycling of unused coatings
may also be considered a form of control.
a There are many solvents that may be used in architectural surface coating operations.
Some compounds may be considered nonreactive and should not be counted in an
ozone (VOC) inventory, but would need to be quantified for air modeling, or HAP
inventory.
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
Coating types may be considered to be solvent based or water based, depending on whether
the principle flow controller is an organic solvent or is water. Solvent based coatings are
defined by the U.S. EPA as coatings that only contain organic solvents, with water, if it is
present at all, only present in trace quantities. Water based coatings have more than 5 weight
percent water as their volatile fraction. Another way of looking at the distinction between the
two types of coatings is that solvent based coatings have resins dissolved in organic solvents
and water based coatings have resin systems suspended in water as liquid emulsions of solid
dispersion (EPA, 1993a).
The EPA is using regulatory negotiation to prepare a national rulemaking for controlling VOC
emissions from architectural and industrial coatings. Currently, no federal EPA regulations
are in place to limit VOC content or VOC emissions from architectural surface coatings.
However, since Occupational Safety and Health Administration (OSHA) regulations limit
worker exposure to solvents, OSHA rules can indirectly affect the VOC content of coatings
and the solvents used in them. The OSHA exposure limits vary with compound toxicity and
as a result, manufacturers must consider the composition of coatings during product
development to minimize the exposure hazards (EPA, 1993a).
Five states—Arizona (AZ), California (CA), New Jersey (NJ), New York (NY), and Texas
(TX)—have coating regulations that affect architectural surface coatings; Maryland has a draft
rule. The various state regulatory limits are summarized in Table 2-1. For a coating to be in
compliance with most state regulations, the VOC content when applied must be below the
specified VOC limit, regardless of whether any thinning followed, or whether the
manufacturer's recommended thinning rate was exceeded (EPA, 1993a).
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11/08/95
TABLE 2-1
STATE VOC LIMITS (GRAMS VOC/LITER COATING, LESS WATER)3
Coating Categories
All other architectural coatings
Bond breakers
Concrete-curing compounds
Enamel undercoaters
Flat architectural coatings
Form-release compounds
General primers, sealers, and
undercoaters
Lacquers
Magnesite cement coatings
Mastic texture coatings
Nonflat architectural coatings
Opaque stains
Pretreatment wash primer
Quick-dry enamels
Quick dry primers, sealers, and
undercoaters
Roof coatings
Sanding sealers
Semitransparent stains
Shellac (clear)
Shellac (pigmented)
Specialty flat products
AZb
(07/13/91)c
350
350
350
680
350
400
300
350
400
CA-CARBd
(09/01/92)c
350
350
250
350
680
600
300
350
780
300
550
350
730
550
NJ6
(08/08/90)c
250
600
350
250
350
680
200
380
350
500
300
550
730
550
NYr
(07/01/89)c
600
350
350
680
200
350
500
300
550
730
550
TXg
(01/01/91)c
2-4
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11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
TABLE 2-1 (CONTINUED)
Coating Categories
Specialty primers, sealers, and
undercoaters
Varnishes
Waterproof mastic coating
Waterproof sealers
Wood preservatives (all)
Wood preservatives (opaque)
Wood preservatives
(semitransparent and clear)
Wood preservatives (below
ground)
Alkyd varnishes
Epoxy paints
Exterior alkyd paints
Exterior stains
Interior alkyd paints
Interior stains
Nitrocellulose-based lacquers
Nonflat and flat latex paints
Urethane coatings
AZb
(07/13/91)c
350
350
300
400
350
CA-CARBd
(09/01/92)c
350
400
350
350
600
NJe
(08/08/90)c
450
300
600
550
NYr
(07/01/89)c
450
300
600
550
TXg
(01/01/91)c
540
540
480
720
420
840
670
260
540
aBlanks indicate that no definition and/or limit exists for that category.
bArizona Regulation III—Control of Air Contaminants, Rule 335-Architectural
Coatings, Section 300—Standards. Applies only to Maricopa County.
"Effective date.
dARB-CAPCOA Suggested Control Measures for Architectural Coatings; a model
rule that applies to the whole state.
eNew Jersey Administrative Code Title 7, Chapter 27, Subchapter 23—Volatile
Organic Substances in Consumer Products, Section 7:27-23:3 Architectural
Coatings. Applies to the whole state.
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
TABLE 2-1 (CONTINUED)
'New York Title 6, Chapter III—Air Resources, Part 205, Section 205.4,
Prohibitions and Requirements. Applies only to the New York City Metropolitan
Area.
BTexas resin categories listed at the end of the table. Texas Air Control Board,
Regulation V (31 TAC Chapter 115)—Control of Air Pollution from Volatile
Organic Compounds, Section 115.191. Applies to the following counties:
Brazoria, Chambers, Collin, Dallas, Denton, El Paso, Fort Bend, Galveston,
Hardin, Harris, Jefferson, Liberty, Montgomery, Orange, Tarrant, and Waller.
2-6 Volume III
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OVERVIEW OF AVAILABLE METHODS
EMISSION ESTIMATION METHODOLOGIES
There are several methodologies available for calculating emissions from architectural surface
coatings. The method used is dependent upon the degree of accuracy required in the
estimate, available data, and available resources. Since architectural surface coatings can be
the largest single area source in an area source ozone inventory, this category warrants the
time and effort needed to calculate emission estimates for it.
This section discusses the methods available for calculating emission estimates from
architectural surface coatings and identifies the preferred calculation method. A discussion of
the data elements needed for each method is also provided.
AVAILABLE METHODOLOGIES
VOLATILE ORGANIC COMPOUNDS
Most VOC released into the air by architectural surface coating use are from the evaporation
of the VOC contained in the coating, coating thinners, and thinners used for cleanup.
Determining the amount of the VOC in coatings and thinners should provide a good estimate
of the VOC emitted by this source category. There are two approaches to estimating the
amount of VOC emitted from this source category:
• Surveying architectural surface coating use in the inventory area; and
• Using one of two population-based estimation methods:
National average per-gallon emission factors applied to national per
capita usage rates, or;
Regulatory state or local per-gallon emission limits applied to national
per capita usage rates.
The survey method is the preferred approach for emission estimation. It will most accurately
reflect the actual use and content of coatings in the inventory area, and thus also reflect any
controls applied. The survey method can also be used to determine separately the amount of
paint that is recycled or sent to a landfill. The level of detail provided by this method allows
Volume III 3-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
for control strategies to be more accurately modeled.
If off-site disposal is part of an emission reduction program, or is a potentially significant
factor in estimated emissions, a survey directed at a subset of the disposal facilities could be
used to estimate the emission reduction from the unused coating.
The alternate approaches—population-based estimates—do not provide the same level of
detail in terms of the specific amounts and types of paints used in the inventory area as the
survey method does. Calculating a per capita usage for the inventory year and applying to it
national emission factors will not take into account variability between regions, but will take
into account the variability of usage at the national level from year to year. This method is
best used if controls are limited or nonexistent and no further controls are anticipated for the
source category. The population-based method using local emission limits will create an
emission factor that will probably be very conservative. This method is acceptable if the
source category is judged to be less important, or if resources and time are not sufficient to
allow use of the survey method.
HAZARDOUS AIR POLLUTANTS
HAP emissions from this source can be estimated using two methods:
• Surveying architectural surface coating use in the inventory area; or
• Applying speciation profiles to the VOC emission estimate, obtained by using
either the preferred or alternative methods for VOC.
The survey method is the preferred method, because it will provide that most accurate
information or coating usage and content. The effect of VOC controls on HAP emissions
should also be apparent when using this method.
Speciation profiles can be used as an alternate approach when a detailed survey is not
practical. Although specific profiles will be provided in Section 5, updated or local speciation
profiles should be used when available.
DATA NEEDS
DATA ELEMENTS
The data elements used to calculate emission estimates for the architectural coatings category
will depend on the methodology used for data collection. The data elements that are
necessary for an emission calculation and should be requested in a survey of paint distributors
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
include:
• Product type;
• Product amount distributed by type (gallon);
• Product density (Ib/gallon);
• VOC content of product or, solvent content by type and VOC percentage of
solvents (weight percent); and
• HAP content of product or solvent by type (weight percent) for all HAP in
product.
A survey respondent may have information on the VOC content, but not the solvent content
or VOC fraction of the various solvents in a paint type. Fewer data elements will be needed
in this case, and the emission calculation, presented in Section 4, will be simplified.
A separate survey of recycling facilities should determine the type and amount of architectural
coatings collected and recycled. Product types should match those used by the manufactures
or distributors surveyed.
If an emission factor method is used, the following data elements are needed: local and
national population, local or national coating usage, and a VOC emission factor and
speciation profiles. To develop a local or updated emission factor, usage and emission factors
for the individual coating types at the national or state level, or for a representative subsection
of the inventory area need to be collected. National, state or sample subsection population
will also be needed to complete the calculation.
APPLICATION OF CONTROLS
Since most controls will affect the content of the coating itself, a survey of coating usage and
VOC content or an emission factor developed from recent data will reflect controls that are in
place. Because a reformulation or substitution represents an irreversible process change, and
thus, a reduction in emissions from a coating type, rule effectiveness can be assumed to be
100 percent for that coating type.
Rule penetration will be based on the percent of sources within the category that are affected
by the rule.
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
SPATIAL ALLOCATION
Spatial allocation may be needed in two possible cases during the preparation of an inventory:
(1) allocation of state or regional activity to a county level, and (2) allocation of county level
emission estimates to a modeling grid cell. In each case, a surrogate for activity should be
found that can approximate spatial variation for this category.
Architectural surface coatings are almost always used in and on buildings where people live
or work. Therefore, building square footage is the preferred method for spatial allocation in
both cases. Tax assessor's offices typically have this information, and, if it has been
compiled into a computerized database or geographical information system (GIS), it should be
reasonably accessible for use in an inventory. This method should be particularly worthwhile
for allocating emissions to a modeling grid cell.
A less detailed alternative spatial apportioning method uses land use data from county
planning departments, or population distributions, available from the Census Bureau. Using
population to allocate estimated emissions or activity by county or within a grid cell is fairly
straight forward, and is discussed in this volume's, Chapter 1, Introduction to Area Source
Emission Inventory Development. Land use data can be used to generalize building size and
type.
TEMPORAL RESOLUTION
Seasonal Apportioning
Architectural surface coating use is influenced by the seasons, since spreading and drying
characteristics for many paints are dependant on the temperature. Temperatures below 50°F
are not suitable for painting, and limit activity. The seasonal factor for ozone season activity
is 1.3 or 33% of annual activity (EPA, 1991). Bureau of the Census reports on paint and
allied products'1 can be used to calculate an alternative seasonal apportioning factor for a
particular year. The second and third quarter usage figures cover the months of April through
September. The first and fourth quarters are periods of low coating usage in most areas.
Based on 1993 and 1992 Census data, the seasonal factor for ozone season architectural
coating activity is 1.12, or 28 percent of annual activity for a 3-month period.
a Bureau of the Census, Manufacturing and Construction Division, Report
MA28F—Paint and Allied Products, available on the Census Bureau Bulletin Board,
(301) 457-2310.
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
Daily Resolution
Coating use may take place 7 days a week during the active season.
PROJECTING EMISSIONS
A discussion about developing growth factors and projecting emission estimates can be found
in Section 4 of this volume's Chapter 1, Introduction to Area Source Emission Inventory
Development. Projected emission estimates may need to be calculated differently in the three
following cases:
Case 1) No controls and no change in emission factor;
Case 2) Controls are reflected in the emission factor; and
Case 3) Controls are expressed as a control efficiency factor, the emission factor
stays the same.
Each case uses a different projection equation. If there are no controls and no changes in the
emission factor, projected emissions are calculated using the following equation:
EMISPY = ORATEBY * EMF * GF (3-1)
where:
EMISpy = Projection year emissions
ORATEBY = Base year activity rate
EMF = Emission factor
GF = Growth factor
For Case 2, where controls are reflected in the emission factor, the equation would be:
EMISPY = ORATEBY * EMFpY * GF (3-2)
where:
EMFpY = Projection year emission factor
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When controls are expressed as an emission limit or a percent reduction, reductions are
calculated using a control efficiency factor, which is Case 3. See Section 4 of this chapter for
an example of how to develop and apply a control efficiency factor in a base year emission
estimation equation. Projected emission estimates for Case 3 are calculated using the
following equation:
ENDS
PY
ORATEDV * EMF
"BY
CE
'PY
100
RE
PY
100
RP
PY
100
* GF (3.3)
where:
CE
RE
RP
'PY
'PY
PY
Projection year control efficiency
Projection year rule effectiveness
Projection year rule penetration
Tools for the development and use of growth factors are discussed in Chapter 1 of this
volume. Forecasts of real estate sales, available from local planning boards, can also be used
to estimate future growth in architectural surface coating.
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
The preferred method for calculating emission estimates from architectural surface coating is
a survey of coating manufacturers in the region, or distributors in the area. This section
provides an outline for preparing and using an architectural surface coating survey, and
calculating emission estimates from the information collected.
Survey methods are theoretically the most accurate approach for estimating emissions, but
also are the most expensive. Advantages to using this method are that regional or area
specific information about the amount and type of coatings used will be collected. Coatings
surveyed will more precisely reflect the regulations for VOC that are in place in the inventory
area. Emissions of HAPs can be calculated based on the specific types of coatings in use in
the area. The level of detail that is possible to collect with a survey is not available when
using the alternative methods.
The cost and labor effort is highest for the first time that a regional or local survey is
performed. Subsequent updates to the survey may be done using fewer samples at much less
cost. In the years following the baseline survey, updates on sales may be all that is needed.
Periodically, changes in formulations, methods of application, and the percentages of different
types of coatings used may be updated.
A specific discussion of surveys for area sources is provided in Volume I of the EIIP series
and in Chapter 1 of this volume. An approach for a survey of suppliers or manufacturers of
architectural coatings uses five steps: (1) survey planning, (2) survey preparation, (3) survey
distribution, (4) survey compilation and scaling, and (5) emission estimation. These steps will
be discussed below.
SURVEY PLANNING
During the planning phase for the survey, the following issues should be addressed:
• Identify survey data quality objectives (DQOs), information needed, and how
the DQOs will be realistically reached.
• Identify the survey recipients, either suppliers or manufacturers, and the data
needs, depending on either choice.
Volume III 4-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
If suppliers are chosen as the recipients, a subset of all area suppliers
may be surveyed, but, the inventory DQOs should be taken into account
when determining the sample size. Identify a scaling surrogate for
scaling up the survey results (e.g., building square footage, number of
burning units, or population).
If manufacturers are chosen as recipients, the resulting information will
probably cover a larger region than the inventory area. The information
collected will need to be scaled to the inventory area. Information
about distribution patterns may need to be collected from the
manufacturers in the survey.
• Decide whether to prescreen recipients.
• Coordinate with other inventory areas, if necessary.
• Identify data handling needs specific to this survey.
• Identify and begin to implement survey QA/QC.
The survey package should include a cover letter explaining the program, the survey form, a
list of definitions, a map defining the study area(s), and a postage-paid envelope.
Either architectural coating suppliers or manufacturers can be surveyed for the information
needed for this category. Suppliers can be identified through the telephone Yellow Pages.
Additional disposal information may be collected as part of a waste disposal or recycling
category. The portion of emissions that correspond to recycled or discarded architectural
surface coatings from the disposal or recycling category should be subtracted from the
emission estimate for architectural surface coating. This is necessary to avoid double
counting.
SURVEY PREPARATION
In the planning phase, the information that the survey will collect should have been identified.
In this step, the survey should be put into its final form.
At a minimum, the survey should request the number of gallons of architectural surface
coating distributed in the inventory area or the inventory county, listed by coating type and
carrier (solvent or water), and the average VOC content of each coating. Alternatively,
national averages of VOC for each coating type can be multiplied by the number of gallons
of the coating type to estimate emissions. National averages of VOC content for types of
coatings have been prepared by the National Paint and Coatings Association (EPA, 1993a). A
more detailed survey will request:
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
• Product type;
• Product amount distributed by type (gallon);
• Product density (Ib/gallon);
• Solvent content of each product type (weight percent);
• VOC content of product by type or of solvent by type (weight percent); and
• HAP content of product by type or of solvent by type (weight %) for all HAP
in product.
The advantages of the more detailed approach are an inventory that is more specific to the
locality, and information that can be more readily projected to inventories for subsequent
years.
Instructions for the survey form are provided on the survey cover page, shown in Figure 4-1.
As shown in Table 4-1, respondents must first estimate the annual amount of coatings and
solvent used in coatings, less waste disposed of offsite. This information is then combined
with the coating and solvent density to yield the pounds of product used in a given year.
HAP weight-percent information is then derived from the material safety data sheets (MSDSs)
provided with each coating.
Using this method for a HAP inventory would require HAP information collection. A
representative sample of the HAP contents for each product type, applied to a more complete
inventory of surface coating types and usage, will simplify data collection.
Since most coatings are not transported great distances from where they are manufactured, it
is possible to characterize architectural surface coating use in an area by surveying regional
manufacturers. These manufacturers can be identified through resources like the Paint Red
Book (Commercial Channels, Inc., 1985), and the Rauch Guide (Rauch Associates, Inc.,
1984), which are both commercial directories of the paint industry and should be available in
university and technical libraries. A survey of manufacturers should include all manufacturers
in a multi-state region surrounding the study area, as well as the major nationwide
manufacturers. Before undertaking a regional manufacturers' survey, a state or local agency
should consider coordinating the survey with neighboring states or localities, since repeated
information requests from multiple agencies may be ignored. A regional manufacturer's
survey may provide the most complete picture of coating use in an area.
Volume III 4-3
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
Name of Manufacturer/Distributer:
Street Address:
City:
Contact Person/Phone Number:
1. On the attached table, list the amount of each individual product manufactured
or distributed in 1994. Products include coatings and solvent manufactured to
be used in preparing coatings for use.
2. Enter the amount of any coating disposed of offsite and not used in 1994. If
only total amount of liquid disposed of offsite is known, allocate the total
between the different products.
3. Subtract the amount of waste or unsold coatings from the amount purchased to
yield the amount of each product used in gallons.
4. From the Material Safety Data Sheet (MSDS) for each product, enter the
product density in pounds per gallon (Ib/gal). If the MSDS only indicates the
specific gravity, calculate the density by multiplying the specific gravity by
8.34 Ib/gal (the density of water).
5. Multiply the gallons of product used by the density to yield the pounds of each
product used.
6. From the Material Safety Data Sheet for each product, enter the hazardous air
pollutant (HAP) or VOC weight percent listed.
7. Multiply the pounds of product used by the HAP/VOC weight percent to yield
pounds of each HAP/VOC emitted.
FIGURE 4-1. SURVEY REQUEST FORM FOR ARCHITECTURAL SURFACE COATING
SUPPLIERS AND MANUFACTURERS
4-4 Volume III
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I
5"
CD
TABLE 4-1
ARCHITECTURAL SURFACE COATING REQUEST FORM
Ul
Coating Type a
Amount Sold
(gallon)
Amount Disposed
of Offsite"
(gallon)
Product Density
(Ib/gallon)
Amount Used
Ob)
o
o
I
o
1
i~
03
2
o
m
o
§
-------
TABLE 4-1 (CONTINUED)
o
Coating Type3
Amount Sold
Ob)
HAP Weight %
HAP Emitted (lb)
aSee Figure 4-2 for list of example architectural coating types.
bColunm not applicable to survey of manufacturers.
o
1
i~
03
I
O
m
o
§
"
CD
Ul
-------
11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
Anti-graffiti
Below ground wood preservatives
Bituminous coatings
Bond breakers
Clear wood preservatives
Concrete curing compounds
Dry fog coatings
Fire retardant/resistive coatings
Form release compounds
High performance architectural coatings
Lacquers
Magnesite cement coatings
Texture coatings
Opaque stains
Opaque wood preservatives
Pretreatment wash primers
Primers
Quick dry enamels
Quick dry primers, sealers, undercoat
Sanding sealers
Sealers
Semi-transparent stains
Semi-transparent wood preservatives
Shellacs
Swimming pool coatings
Undercoaters
Varnishes
Waterproofing sealers
Waterproofing sealers with pigment
Interior flats
Exterior flats
Interior non-flats
Exterior non-flats
FIGURE 4-2. EXAMPLE ARCHITECTURAL COATING TYPES
Volume III
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
SURVEY DISTRIBUTION
Survey distribution will be determined by the budget for this source category. Surveys can be
distributed by a mailing, or the information can be collected through a telephone survey.
Initial contacts and follow up contacts may also be undertaken as part of the survey, in order
to answer any questions. Survey distribution issues are discussed in Chapter 1 of this
volume.
SURVEY COMPILATION AND SCALING
Survey compilation and scaling issues are discussed in Volume I of this series. A survey of
surface coating manufacturers or distributors will result in information that includes many
types of paints and multiple pollutants, so compilation of this information will require
planning for data transfer and data management. Efficient transfer to the data handling
system will benefit from inventory planner's consideration of the transfer step during the
design of the survey.
Quality control checks should be in place during this phase of the work (see Volume VI for
QA/QC methods). Incoming surveys should be checked for errors such as potential unit
conversion errors or misidentification of products or chemicals. Survey information should be
checked for reasonableness. Compiled survey information should also be subject to similar
checks. Survey recipients may need to be recontacted in order to correct any errors.
Depending on the recipients of the survey, results may need to be either scaled up for all
counties in the inventory area or scaled down to the inventory area. In either case, a scaling
factor should have been identified in the planning phase, and any necessary requests for
information from the survey respondents included in the survey form.
EMISSION ESTIMATION
Emission estimation calculations involve the calculation of emissions of individual pollutants,
and then the application of any necessary spatial or temporal adjustments. Because the
application of architectural surface coating is generally defined as an area source, there should
not be a need to subtract point source emission estimates from the total. However, there may
be cases when emission estimates from this category may be estimated as one of many
processes occurring at a point source for the purposes of permitting and emission tradeoffs.
These emissions must be identified and then subtracted from the area source estimates.
The equation below can be used to estimate the total amount of pollutant (P) emitted in the
inventory area from architectural surface coating operations.
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
ASEp = £ £ TACcs • SCC;S • FP;S (4-1)
c=l s=l
where:
ASEp = Total emissions of pollutant (P) from architectural surface
coating operations, for all coatings (C) with all solvents (S)
TACSC = Total architectural surface coating consumed in the inventory area for
each coating (c) with each solvent (s) containing pollutant (P)
SCCjS = Amount of solvent (s) in each coating (c)
Fp s = Fraction of pollutant (P) in each solvent (s)
Spatial allocation to individual counties or other inventory area units can be done using the
methods described in Section 3. The methods that are available, in order of preference, are to
use building square footage, land use data or population to allocate coating use.
Temporal allocation may be necessary if the inventory requires seasonal or daily emission
estimates, and is discussed in Section 3 of this chapter.
Volume III 4-9
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING
11/08/95
Example 4-1:
Formaldehyde is reported in various weight percents for some formulations of primers, varnishes
and waterproofing sealers. Reported weight percents for these coating types, and the amount
delivered to the inventory area, in pounds, are presented below.
Formaldehyde Content by Weight Percent
Coating
Type
Primers
Varnishes
Waterproofing Sealers
Weight
%
1.60
17.50
0.55
7.50
0.55
0.65
0.55
Amount
Distributed
(Ib)
304.50
47.85
52.20
5.22
845.50
1330.00
8.96
Emissions are calculated for varnishes:
Formaldehyde
Emissions from =
Varnishes
[ 842.5 Ib * 0.55% ] + [ 1330 Ib * 0.65% ]
4.65 + 8.645
13.295 Ib Formaldehyde
Emissions are calculated for waterproofing and primers in the same manner, and all emission
estimates are summed for the final estimate.
4-10
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
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Volume III 4-11
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
The alternative method for calculating emissions from architectural surface coating is to use
population-based usage and emission factors. This section provides an outline for developing
a per capita usage factor, and for using that usage factor and an emission factor to calculate a
VOC emission estimate. Because the application of architectural surface coating is defined as
an area source, there is no need to subtract point source emissions from the total, and all
emissions estimated for this source are area source emissions. The procedure is as follows:
• Determine the per capita usage factor by dividing the national total
architectural surface coating quantities" for solvent and water based coatings by
the U.S. population for that year.b Example 5-1 shows how to sum gallons of
water and solvent based paints for the year 1993.
• Determine the VOC emission factors for solvent- and water-based coatings.
Emission factors based on weighted averages from a 1990 survey study are
listed at the end of this section (EPA, 1993a). These emission factors are
based on the weighted average VOC emission at maximum thinning. State or
local emission limits also can be used to calculate an emission factor. If
sufficient information is available, a more recent emission factor can be
calculated. That information includes the amount used and percent VOC
content of each of the architectural surface coatings.
When state or local emission limits are used to develop an emission
factor, and those limits are a range of values for different types of
coatings, a weighted average, based on real or estimated consumption of
each coating type will need to be calculated.
a Total national coating usage is compiled by the Bureau of the Census, Report
MA28F—Paint and Allied Products, available on the Census Bureau Bulletin Board,
(301)457-2310.
b U.S. Census Bureau, Department of Commerce, Washington, DC.
Volume III 5-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
Example 5-1:
Table 5-1 shows a portion of Table 2 from the U.S. Bureau of Census MA28F - Paint and Allied
Products. This section of the table summarizes the market information available on architectural
coatings for the years of 1993 and 1992. In the table, types of paints are identified as being either
solvent or water based paints, except for the two types listed as Architectural Lacquers and
Architectural Coatings N.S.K. These latter types of paints can be assumed to be entirely solvent
based coatings. The calculation to obtain the number of gallons of solvent based paints totals the
gallons for Exterior Solvent Type, Interior Solvent Type, Architectural Lacquers and Architectural
Coatings N.S.K:
Solvent
Based = 70,109 + 56,442 + 5,793 + 13,957
Paints
146,301 thousand gallons of paints
The calculation to obtain the number of gallons of water based paints totals the gallons for Exterior
Water Type and Interior Water Type:
Water
Based = 154,777 + 297,729
Paints
452,506 thousand gallons of paints
The per capita usage factor is calculated by dividing the total usage of solvent based paints by the
U.S. population, and the total usage of water based paint by the U.S. population.
Per Capita Solvent
Based Usage Factor = Gallons of Solvent Based Paints/Population
146,301,000/248,709,873
0.59 gallons per person
For water based paints:
Per Capita Water
Based Usage Factor = Gallons of Water Based Paints/Population
452,506,000/248,709,873
1.82 gallons per person
5-2 Volume III
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7 7/05/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING
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Volume III
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7 7/05/95 CHAPTER 3 - ARCHITECTURAL SURFACE COATING
The following is a description of how emission factors for different coatings may be
developed:
• Multiply the VOC content percentage times the amount used for each of the
types of architectural surface coatings to produce an emission estimate for each
of the types of coatings.
• Separately sum the VOC emission estimates for the solvent based coating
types, and the water based coating types. Separately sum the amounts used of
the solvent and the water based coatings.
• Divide the two VOC emission estimates by the total amounts of either solvent
based or water based coating used. The result, in the form of emissions per
gallon, is the emission factor for either solvent or water based coatings (see
Example 5-2).
Example 5-2:
The equation to develop an emission factor for water-based architectural surface coatings is:
efr * SC
c:
=1
scc
c=l
where:
EFW = Emission factor for all water based surface coatings
efc = Emission factor for each coating (c) in Ib/gal
SCC = Amount of coating (c) used in gal
For solvent based paints, the equation to calculate emissions is:
VOC Emissions Solvent Solvent VOC
From Solvent Based = Population * Usage * Emission
Coatings Factor Factor
Volume III 5-5
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
For water based paints, the equation to calculate emissions is:
VOC Emissions Water Based Water Based
from Water Based = Population * Usage * VOC Emission
Coatings Factor Factor
Add the two emission estimates to get the total VOC emissions from the
category.
When an emission factor is being calculated using regulatory limits, it is
possible that the limits are expressed as a range rather than a single value. In
that case, the upper bound of the limit should be used to calculate the emission
factor. This is in keeping with the very conservative approach that this
methodology represents.
Use the speciation profiles at the end of this section to calculate HAP
emissions from architectural surface coatings.
Multiply the percentage of the individual HAP for either solvent- or
water-based paints with the amount of VOC calculated for that type of
coating (see Example 5-3).
Example 5-3:
Benzene Emissions VOC Emission
from Water Based = Estimate for * 0.003
Coatings Water Based Coatings
Table 5-2 lists the emission factors for architectural surface coatings. Tables 5-3 and 5-4 list
the VOC species profiles for water- and solvent-based architectural surface coating species,
respectively.
5-6 Volume III
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11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
TABLE 5-2
EMISSION FACTORS FOR ARCHITECTURAL SURFACE COATINGS (EPA, 1993A)
Coating Type
Water-based coatings
Solvent-based coatings
VOC Content
Ob/gal)
0.74
3.87
TABLE 5-3
VOC SPECIES PROFILE FOR WATER-BASED ARCHITECTURAL SURFACE COATING
(CARB, 1991)
Species
Benzene3
n-Butyl alcohol
2-(2-Butoxyethoxy)-ethanol
2-Butyltetrahydrofuran
1-Chlorobutane
3-(Chloromethyl)-heptane
n-Decane
Dibutyl ether
Dichloromethanea (methylene chloride)
Ethyl chloride"
2 -Ethyl- 1 -hexanol
1 -Ethoxy-2-propanol
Ethylene glycoF
1-Heptanol
Weight Fraction
0.0030
0.2000
0.0070
0.0010
0.0220
0.0060
0.0020
0.0020
0.0550
0.0060
0.0100
0.0140
0.0050
0.0070
Volume III
5-7
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING
11/08/95
TABLE 5-3
(CONTINUED)
Species
Hexylene glycol
Isoamyl isobutyrate
Methyl chloride
Methyl isobutyrate
Propylcyclohexanone
Substituted C7 ester (C12)
Substituted C9 ester (C12)
n-Undecane
Undecane isomers
Weight Fraction
0.0140
0.0030
0.0050
0.0010
.0100
.2690
.2850
.0010
.0100
"Hazardous air pollutant listed in Clean Air Act Amendments of 1990.
Volume III
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11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
TABLE 5-4
VOC SPECIES PROFILE FOR SOLVENT-BASED ARCHITECTURAL
SURFACE COATING (CARB, 1991)
Species
Acetone
n-Butyl acetate
n-Butyl alcohol
Cyclohexane
Dimethyl formamidea
2-Ethoxyethyl acetate
Ethyl alcohol
Ethylbenzenea
Ethylene glycola
n-Hexane
Isobutyl acetate
Isobutyl alcohol
Isobutyl isobutyrate
Isomers of xylenea
Isopropyl alcohol
Methyl alcohol
Methyl ethyl ketonea
Methyl isobutyl ketonea
Methyl n-butyl ketone
Propylene glycol
Toluene
Weight Fraction
0.0320
0.0250
0.0160
0.2070
0.0050
0.0130
0.0060
0.0430
0.0060
0.2070
0.0150
0.0060
0.0610
0.0260
0.1640
0.0390
0.0560
0.0060
0.0070
0.0080
0.0520
hazardous air pollutant listed in Clean Air Act Amendments of 1990.
Volume III
5-9
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5-10 Volume III
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QUALITY ASSURANCE/QUALITY
CONTROL
When using the preferred method, the survey planning, sample design, and data handling
should be planned and documented in the inventory QA/QC plan. Refer to the discussion of
survey planning and survey QA/QC in Chapter 1 of the volume.
Data handling for the survey data and for data collected for the alternate methods should also
be planned and documented in the inventory QA/QC plan and do not involve any category-
specific issues. Please consult the EIIP volume on inventory QA/QC for more information.
EMISSION ESTIMATE QUALITY INDICATORS
The preferred method gives higher quality estimates than either of the alternative methods,
but requires significantly more effort. The level of effort required to calculate emissions
using either of the alternative methods ranges from 8-40 hours. Conducting a survey requires
between 100 to 800 hours depending on the size of inventory region and the desired level of
detail of the survey. However, the resultant increase in the quality may justify this
expenditure of resources, especially if this category is believed to be a significant contributor
to emissions. Emissions from architectural surface coatings are typically among the top ten
area sources of VOCs and HAPs in urban areas.
DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 6-1, 6-2, and 6-3. A range of
scores is given for the preferred method because the scores are dependent on the
representativeness, sample size, and other survey characteristics. All scores assume that good
QA/QC measures are performed and that no significant deviations from the prescribed
methods have been made. If these assumptions are not met, new DARS scores should be
developed according to the guidance (Beck, et. al., 1994).
The preferred method gives higher DARS scores than either of the alternative methods. The
two alternative methods have composite scores in the 0.3-0.4 range while the preferred
method scores vary from 0.64 to 0.96. Furthermore, the scores on all attributes are higher
compared to the alternatives. The alternative methods have similar composite scores, but the
composite measurement and source specificity attribute scores are quite different.
Volume III 6-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING
11/08/95
TABLE 6-1
PREFERRED METHOD DARS SCORES: SURVEY OF COATING USE
BY TYPES IN THE INVENTORY REGION
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.7-0.9
1.0
0.8-1.0
0.7-1.0
0.80-0.98
Activity
0.7-0.9
1.0
0.8-1.0
0.7-1.0
0.80-
0.98
Emissions
0.64-0.81
1.0
0.64-1.0
0.49-1.0
0.69-0.95
Comment
Sample size and
representativeness of
sample determine score.
Assumes that survey is
specific to source
category and inventory
region.
A 1.0 is appropriate if
survey is region
specific; lower value
given if factor or
activity extrapolated
from a larger or smaller
region.
High value applies if
sample uses data from
inventory target year;
lower value if sample
data are from a
different year.
6-2
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11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
TABLE 6-2
ALTERNATIVE METHOD DARS SCORES: NATIONAL FACTORS APPLIED TO
NATIONAL PER CAPITA USAGE
Attribute
Measurement
Source specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.8*
0.7
0.5
0.7"
0.68
Activity
0.7
0.5
0.5
0.7"
0.6
Emissions
0.56
0.35
0.25
0.49
0.41
TABLE 6-3
ALTERNATIVE METHOD DARS SCORES: REGULATORY LIMITS APPLIED TO
NATIONAL PER CAPITA USAGE
Attribute
Measurement
Source specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.1*
0.6
0.8
0.7"
0.55
Activity
0.7
0.5
0.5
0.7"
0.6
Emissions
0.07
0.3
0.4
0.49
0.32
Score assumes total VOC factor is used; if this is speciated to get
HAPs, score should be lowered.
'Assumes factor/activity data year different than inventory year but not by much.
Volume III
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
SOURCES OF UNCERTAINTY
The uncertainty of the emission estimates can be quantified if the preferred method is used
(See QA Source Document, Chapter 4). However, the statistics needed to quantify the
uncertainty of either alternative method are incomplete. The variability of paint use per
capita is not well defined. Per capita usage may be lower than the national average in urban
areas of high-density housing, in milder climates, or where wooden buildings are not
common. For example, a survey of paint use in the New York City area resulted in per
capita consumption 25 percent lower than the national average (Leone, et al., 1987),
presumably due to the predominance of high-density housing in the city. Paint use may be
higher in corrosive environments (such as near salt water) or in areas where wooden
structures predominate.
The solvent content of paint is also variable. The VOC contents shown in Table 5-2 are
weighted means for the two general categories shown. The unweighted mean and standard
deviation for water-based coatings is 2.22 ±1.9 Ib/gal; for solvent-based coatings, the
unweighted mean and standard deviation is 4.0 ±1.07 Ib/gal. The weighted means account for
the proportions of primers, sealers, lacquers, and so forth used nationally, and if these
proportions do not vary regionally, the national factor will be representative of local
conditions. Therefore, the preferred method should be used wherever local conditions suggest
that either the total quantity of paint used or the type of paints used are very different from
the average.
The use of regulatory emission limits is likely to be biased because solvent content can be
lower than the limit. The true emissions are likely to be lower than the limit. However,
because the national factor is an average, it may either overestimate or underestimate
emissions in a given area.
6-4 Volume III
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DATA CODING PROCEDURES
This section describes the codes available to characterize architectural surface coating
emission estimates. Consistent categorization and coding will result in greater uniformity
between inventories. Inventory planning for data collection calculations and inventory
presentation should take the data formats presented in this section into account. Available
codes and process definitions may impose constraints or requirements on the preparation of
emission estimates for this category.
PROCESS AND CONTROL CODES
The source category process codes for architectural surface coating operations are shown in
Table 7-1. These codes are derived from the EPA's Aerometric Information Retrieval System
(AIRS) AMS source category codes (EPA, 1994). The control codes for use with AMS are
shown in Table 7-2. The "099" control code can be used for miscellaneous control devices
that do not have a unique identification code. The "999" code can be used for a combination
of control devices where only the overall control efficiency is known.
Typically, the source category code for "total all solvent types, architectural surface coating"
will be used. Low solvent or water-borne coatings will be the control method, so either
control device code 101 or 103 will be used.
Volume III 7-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING
11/08/95
TABLE 7-1
AIRS AMS CODES FOR ARCHITECTURAL SURFACE COATING
Process Description
Total: All Solvent Types
Solvent — General
Acetone
Butyl Acetate
Butyl Alcohols: All Types
n-Butyl Alcohol
Isobutyl Alcohol
Diethylene Glycol Monobutyl Ether
Diethylene Glycol Monoethyl Ether
Diethylene Glycol Monomethyl Ether
Ethyl Acetate
Ethylene Glycol Monoethyl Ether (2-Ethoxyethanol)
Ethylene Glycol Monomethyl Ether (2-Methoxyethanol)
Ethylene Glycol Monobutyl Ether (2-Butoxyethanol)
Glycol Ether: All Types3
Isopropanol
Methyl Ethyl Ketone3
Methyl Isobutyl Ketone3
Special Naphthas
Xylenes3
AMS Code
24-01-001-000
24-01-001-999
24-01-001-030
24-01-001-055
24-01-001-060
24-01-001-065
24-01-001-070
24-01-001-125
24-01-001-130
24-01-001-135
24-01-001-170
24-01-001-200
24-01-001-210
24-01-001-215
24-01-001-235
24-01-001-250
24-01-001-275
24-01-001-285
24-01-001-370
N/Ab
"Hazardous Air Pollutant listed in the Clean Air Act Amendments of 1990.
'TST/A = No AMS source code assigned.
7-2
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11/08/95
CHAPTER 3 - ARCHITECTURAL SURFACE COATING
TABLE 7-2
AIRS CONTROL DEVICE CODES
Control Device
Process Modification
Process Modification
Process Modification
— Low Solvent Coatings
— Powder Coatings
— Water-Borne Coatings
Miscellaneous Control Device
Combination Control
Efficiency
Code
101
102
103
099
999
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
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7-4 Volume III
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8
REFERENCES
Beck, L., Rebecca Peer, Luis Bravo, and Ying Yan. 1994. A Data Attribute System.
U.S. Environmental Protection Agency, Air and Engineering Research Laboratory, Research
Triangle Park, North Carolina.
Brandau, A., 1990. Introduction to Coatings Technology; Federation Series on Coating
Technology. Federation of Societies for Coating Technology, Blue Bell, Pennsylvania.
California Air Resources Board (CARB). 1991. Identification of Volatile Organic Compound
Species Profile (August 1991 version). Emission Inventory Branch, Technical Support
Division. Sacramento, California.
Communication Channels, Inc., 1985 Paint Red Book, Atlanta, Georgia.
EPA. 1994. AIRS Database. U. S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, Research Triangle Park, North Carolina. 1994.
EPA. 1993a. Information provided in the regulation negotiation proceedings in support of a
VOC regulation for architectural and industrial maintenance coatings. Docket No. II-E-36.
VOC Emissions from Architectural and Industrial Maintenance Coatings.
EPA. 1993b. Guidance for Growth Factors, Projections and Control Strategies for the 15
Percent Rate-of-Progress Plans. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, EPA-452/R-93-002. Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide
and Precursors of Ozone, Vol. I. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, EPA-450/4-91-016. Research Triangle Park, North Carolina.
Leon, R.M., E.W. Davis, and A.D. Jones. 1987. Updating Nontraditional VOC Source
Inventories. Prepared for New York State Department of Environmental Conservation,
Bureau of Abatement Planning.
Rauch Associates, Inc. 1984. The Rauch Guide to the U.S. Paint Industry (Data for 1983,
1984 and Projections to 1989), Bridgewater, New Jersey.
Volume III 8-1
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CHAPTER 3 - ARCHITECTURAL SURFACE COATING 11/08/95
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8-2 Volume III
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VOLUME III: CHAPTER 4
DRY CLEANING
Final Report
May 1996
Prepared by:
Radian Corporation
Post Office Box 13000
Research Triangle Park, North Carolina 27709
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Lucy Adams of Radian Corporation for the Area Sources
Committee, Emission Inventory Improvement Program and for Charles O. Mann of the Air
Pollution Prevention and Control Division, U.S. Environmental Protection Agency (EPA).
Members of the Area Sources Committee contributing to the preparation of this document are:
Kwame Agyei, Puget Sound Air Pollution Control Agency
Gwen Judson, WI Department of Natural Resources, Bureau of Air Management
Angie Shatus, Office of Air Quality Planning and Standards, Information Transfer and Program Integration
Division
Other contributors have been:
Tahir R. Khan, Chemical Emission Management Services, Mississauga, Ontario
Jens Laas, WI Department of Natural Resources, Bureau of Air Management
Phyllis Strong, MN Pollution Control Agency, Air Quality Division
Tamera Thompson, VA Environmental Quality Department, Air Toxics Section
Chun Yi Wu, MN Pollution Control Agency, Air Quality Division
EIIP Volume III in
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CHAPTER 4-DRY CLEANING 5/17/96
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iv EIIP Volume III
-------
CONTENTS
Section Page
1 Introduction 4.1-1
2 Source Category Description 4.2-1
2.1 Emission Sources 4.2-2
2.2 Factors Influencing Emissions 4.2-2
2.3 Control Techniques 4.2-3
3 Overview of Available Methods 4.3-1
3.1 Emission Estimation Methodologies 4.3-1
3.1.1 Volatile Organic Compounds and Hazardous Air Pollutants .... 4.3-1
3.1.2 Available Methodologies 4.3-1
3.2 Data Needs 4.3-4
3.2.1 Data Elements 4.3-4
3.2.2 Adjustments to Emission Estimates 4.3-4
3.3 Projecting Emissions 4.3-10
4 Preferred Methods for Estimating Emissions 4.4-1
4.1 Survey Planning 4.4-1
4.2 Per Dry Cleaning Unit Emission Factor Method (Coin-op Dry
Cleaners) 4.4-4
4.3 Per Plant Consumption Factor Method (Commercial Dry Cleaners and
Industrial Launderers) 4.4-5
5 Alternative Methods for Estimating Emissions 4.5-1
5.1 Methods for Coin-op Dry Cleaners (SIC 7215) 4.5-1
5.1.1 Alternative One 4.5-1
5.1.2 Alternative Two 4.5-1
EIIP Volume III V
-------
CONTENTS (CONTINUED)
Section Page
5.2 Methods for Commercial and Industrial Dry Cleaners (SIC 7216 and
7218) 4.5-3
5.2.1 Alternative One 4.5-3
5.2.2 Alternative Two 4.5-3
6 Quality Assurance/Quality Control 4.6-1
6.1 Emission Estimate Quality Indicators 4.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 4.6-1
6.1.2 Sources of Uncertainty 4.6-6
7 Data Coding Procedures 4.7-1
7.1 Process and Control Codes 4.7-1
8 References 4.8-1
vi Volume IV
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FIGURES AND TABLES
Figure Page
4.4-1 Sample Survey Cover Sheet 4.4-2
4.4-2 Sample Survey Form 4.4-3
Table Page
4.2-1 NESHAP Requirements for Dry Cleaning Sources of
PERC (58 FR 49354) 4.2-5
4.3-1 Preferred and Alternate Methods for Estimating Emissions
from Dry Cleaning Facilities 4.3-3
4.3-2 Data Elements Needed for Each Method 4.3-5
4.3-3 Data Needs for Emission Estimate Adjustments 4.3-6
4.5-1 National Per Employee Emission Factors for Dry Cleaning Operations 4.5-2
4.6-1 Preferred Method DARS Scores: Survey SIC 7215, 7216 and 7218:
Develop a Local per Unit or Per Facility Emission Factory 4.6-2
4.6-2 Alternative Method 1 for SIC 7215 (Coin-op): Using a
Local Commercial (SIC 7216) per Dry Cleaning Unit
Emission Factor 4.6-2
4.6-3 Alternative Method 1 for SIC 7216 and 7218 (Commercial
and Industrial Cleaners): Survey to Develop a Local per
Employee Factor 4.6-3
4.6-4 Alternative Method 2 for SIC 7215 and 7216 (Coin-op and Commercial Cleaners):
Using a National per Employee Factor 4.6-3
4.6-5 Alternative Method 3 for SIC 7215 Cleaners:
Using a National per Facility Factor 4.6-4
EIIP Volume III vii
-------
FIGURES AND TABLES (CONTINUED)
Table Page
4.6-6 Composite Emissions DARS Scores: Summary for all Industries,
all Methods 4.6-4
4.7-1 AIRS AMS Codes for the Dry Cleaning Category 4.7-2
4.7-2 AIRS Control Device Codes 4.7-2
viii Volume IV
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from dry cleaning. Section 2 of this chapter contains a general description of the dry cleaning
category and an overview of available control technologies. Section 3 of this chapter
provides an overview of available emission estimation methods. Section 4 presents the
preferred method for emission estimation for dry cleaning, and Section 5 presents the
alternative emission estimation techniques. Quality assurance issues and emission estimate
quality indicators for the methods presented in this chapter are discussed in Section 6. Data
coding procedures are discussed in Section 7, and Section 8 is the reference section.
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CHAPTER 4-DRY CLEANING 5/17/96
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4.1-2 Volume IV
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SOURCE CATEGORY DESCRIPTION
The dry cleaning industry is a service industry for the cleaning of garments, draperies, leather
goods, and other fabric items. Dry cleaning operations do not use water that can swell textile
fibers but typically use either synthetic halogenated or petroleum distillate organic solvents for
cleaning purposes. Use of solvents rather than water prevents wrinkles and shrinkage of
fabrics. The dry cleaning industry is the most significant emission source of
perchloroethylene (PERC) in the United States.
The two major types of dry cleaning operations are coin-operated (coin-op) (Standard
Industrial Classification [SIC] Code 7215) and commercial (SIC 7216). Industrial launderers
(SIC 7218) are usually associated with soap and detergent cleaning, but also use large-
capacity dry cleaning units. Coin-operated dry cleaning units are self-service machines that
are usually found in laundromats. Commercial dry cleaners are independent small businesses
that offer dry cleaning services to the public. Some commercial dry cleaning businesses
provide numerous drop-off/pick-up outlet stores that are serviced by a single dry cleaning
plant, and thus some sites identified as dry cleaners may not be emissions sources. Industrial
launderers who use dry cleaning solvents are usually part of a business operation that
generates soiled fabrics, where it is convenient or cost-effective to perform dry cleaning on
site. Industrial launderers can also be large businesses that provide uniform and other rental
services to business, industrial, and institutional customers.
The primary synthetic halogenated dry cleaning solvent is PERC; small quantities of
1,1,1-trichloroethane (TCA) and trichlorofluoroethane (CFC-113) are used in specialty
cleaning operations. The petroleum solvents most used in dry cleaning are a mixture of
paraffins and aromatic hydrocarbons. Stoddard solvent (mineral spirits) is the primary
petroleum solvent used in dry cleaning. PERC is used for its aggressive solvent properties,
whereas CFC-113 is well suited for cleaning delicate clothing. TCA is a more aggressive
solvent than PERC, but may damage some clothing and must be used in stainless steel dry
cleaning machines.
Dry cleaning facilities may be point or area sources. Most coin-op and commercial dry
cleaners are expected to be area sources. Commercial dry cleaners are responsible for the
greatest amount of emissions. Industrial launderers that do dry cleaning are expected to be
point sources except for a few facilities. Point source emissions must be subtracted from total
emissions to produce an estimate of dry cleaning area source emissions.
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CHAPTER 4-DRY CLEANING 5/17/96
2.1 EMISSION SOURCES
Volatile organic solvents that are used as cleaning solvents are emitted during the dry
cleaning process. The petroleum solvents most commonly used in dry cleaning are Stoddard
solvent (mineral spirits) and 140-F (EPA, 1985). The synthetic solvents that are used in dry
cleaning, PERC, TCA, and CFC-113, are not considered photochemically reactive and should
not be included in an ozone (volatile organic compound [VOC]) inventory; PERC and TCA,
however, are hazardous air pollutants (HAPs) that should be included in an air toxic
inventory. TCA and CFC-113 are ozone-depleting substances (ODSs), and CFC-113 may be
listed in some state regulations as a toxic air pollutant.
It is estimated that 82 percent of all dry cleaning facilities use PERC, 15 percent use
petroleum solvents, 3 percent use CFC-113, and less than 1 percent use TCA (EPA, 1991a).
However, based on a study of national solvent use, 57 percent of all dry cleaning solvents are
petroleum solvents (primarily mineral spirits), 39 percent of the solvents are PERC, and 3 and
1 percent are TCA and CFC-113, respectively, with a minor amount of unspecified solvents
(Frost & Sullivan, 1990). Small dry cleaning facilities, such as coin-operated sites use PERC
exclusively, and larger facilities, such as commercial facilities use petroleum solvents,
resulting in this disparity.
2.2 FACTORS INFLUENCING EMISSIONS
Emissions from dry cleaning operations are influenced by the type of dry cleaning machines
used. Dry cleaning machines are either dry-to-dry or transfer machines. In the dry-to-dry
process, both washing and drying takes place in one machine. Dry-to-dry machines are either
vented during the drying cycle or are ventless, where emissions occur only during loading and
unloading operations. With transfer machines, the material is washed in one machine and
manually transferred to another machine to dry. Emissions occur during the transfer as well
as from the washer and dryer vents. Facilities using petroleum solvents have typically used
transfer machines. Transfer units are an older technology; all the demand for new equipment
in the dry cleaning industry is for dry-to-dry machines. Some petroleum solvent dry-to-dry
machines are now being produced in the United States and Europe, and may become more
significant in the industry in the future.
Most facilities using PERC use dry-to-dry machines. CFC-113 is used exclusively in dry-to-
dry systems. Because petroleum solvents are flammable and may form explosive mixtures,
their use has been limited to transfer machines where the solvent concentration in vapors do
not build up to high levels. However, commercial petroleum solvent dry-to-dry machines are
now being manufactured. National Fire Protection Association codes may limit the locations,
such as shopping centers, that petroleum solvents can be used.
4.2-2 Volume IV
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5/17/96 CHAPTER 4 - DRY CLEANING
In facilities that use PERC, solvents recovered during the dry cleaning process are usually
filtered and distilled for recycling back to the process. Emissions occur from the equipment,
such as filters, muck cookers, oil cookers, and other stills, that is used to filter and distill the
dirty solvent. Filters may be reusable or the cartridge type that is drained, air dried, and
discarded. With petroleum solvents, the residue (muck) is drained of excess solvent, air
dried, and discarded. Because of the low cost of petroleum solvents, recycling is not
emphasized at dry cleaning facilities using these solvents.
Industrial launderers usually have efficient recycling and recapture procedures. Most
industrial and commercial cleaners use off-site solvent recycling businesses for solvent waste
recovery and disposal services, whereas few coin-op dry cleaners utilize these services.
Solvent use is dependent upon the amount of material cleaned. Transfer machines can have a
much larger capacity than dry-to-dry units, and therefore involve the use of more solvents. In
general, industrial dry cleaning machines are larger than both commercial and coin-op
machines, with commercial units larger than coin-op units. Coin-op units usually have a
capacity of 8 to 25 pounds of clothes per load, with one or two machines per facility. The
average capacity of commercial dry cleaning units is 35 pounds, with a range of 15 to 97
pounds per load. Most of these units are dry-to-dry. The average capacity of industrial dry
cleaners is 140 pounds per load for dry-to-dry units and 250 pounds per load for transfer
units. Most of the industrial units are transfer units, although their use is being phased out as
new dry-to-dry units are purchased to replace the older transfer units.
2.3 CONTROL TECHNIQUES
Control strategies for dry cleaners include the use of add-on controls such as refrigerated
condensers and carbon adsorbers to capture and reduce emissions from dry cleaning machine
air vents. Emission control is also achieved through changes in operational practices to
reduce fugitive emissions. Examples of changes in operational methods include prompt
detection and repair of leaky valves, hose connections, and gaskets; storage of solvents and
wastewater in tightly sealed containers; and minimization of the time the door of the dry
cleaning machine is open.
The Occupational Safety and Health Administration requires that all equipment that uses
PERC be enclosed to meet the permissible exposure level for PERC in the workplace. Under
the National Emission Standards for Hazardous Air Pollutants (NESHAP) program, the EPA
has passed regulations that require the control of emissions for dry cleaning units using
PERC. The NESHAP requirements, shown in Table 4.2-1, include the use of refrigerated
condensers, leak detection and seal inspection programs, and monitoring and reporting
requirements. Coin-op dry cleaning units are exempt from all but the initial reporting
NESHAP requirements. Dry cleaning with petroleum solvents will be regulated under
El IP Volume III 4.2-3
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to
TABLE 4.2-1
o
NESHAP REQUIREMENTS FOR DRY CLEANING SOURCES OF PERC (58 FR 49354)
Source Size/
Machines
PERC
Consumption
Limits (gal/yr)
Process Vent Controls
Existing
New
Fugitive Controls
Existing
New
Small Area Source
Dry-to-Dry
Transfer
Combination
Less than:
140
200
140
None
RC
LDR/SC
LDR/SC and NNT
Large Area Source
Dry-to-Dry
Transfer
Combination
Between:
140 -2,100
200 - 1,800
140 - 1,800
RC or CAa
RC
LDR/SC
LDR/SC and NNT
Major Source
Dry-to-Dry
Transfer
Combination
More than:
2,100
1,800
1,800
RC or CAa
RC/CA
LDR/SC
Room enclosure
LDR/SC
Room enclosure
O
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-<
O
i~
i
1
A carbon adsorber can be used if already in place.
CA = Carbon absorber.
LDR/SC = Leak detection and repair, and storage of PERC in sealed containers.
NNT = No new transfer units.
RC = Refrigerated condenser (or equivalent).
RC/CA = Refrigerated condenser followed by carbon adsorber.
Ul
CD
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5/17/96 CHAPTER 4 - DRY CLEANING
NESHAP in 2000.
Many states also regulate emissions from dry cleaners. Inventory planning for this source
category should include inquiries to the local air pollution control authorities about applicable
regulations.
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4.2-6 Volume IV
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
There are several methodologies available for calculating emissions from dry cleaning. The
method used is dependent upon the degree of accuracy required in the estimate, available
data, and available resources. Since dry cleaning has been one of the top ten largest area
sources in area source ozone inventories, this category warrants time and effort in the
calculation of emission estimates for it.
This section discusses the methods available for calculating emission estimates from dry
cleaning and identifies the preferred method of calculation. A discussion of the data elements
needed for each method is provided.
3.1.1 VOLATILE ORGANIC COMPOUNDS AND HAZARDOUS AIR POLLUTANTS
The VOCs emitted from dry cleaning operations are from the solvents used to clean in the
dry cleaning process. These VOCs may be emitted from dry cleaning machines during
operation of the units or during solvent reclamation processes. There are several approaches
to estimating the amount of VOCs emitted from this category, depending on the information
sought and the data available.
• Number of facilities or dry cleaning units:
Local per facility emission factors (using survey or permit information);
Emission factors based on type of machine;
National average per facility emission factors;
• Number of employees:
Local per employee emission factors (using survey or permit
information);
National average per employee emission factors;
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CHAPTER 4-DRY CLEANING 5/17/96
• Per capita: National average per capita emission factor.
Use caution when applying emission factors that are more than 3 years old, since emission
factors can quickly become obsolete due to compliance efforts by the industry.
HAP emissions from this source are determined by the same approaches discussed for VOC
emissions, in conjunction with a survey or estimate of the proportion of each solvent type
used in the dry cleaning facilities in the inventory area. The emissions of each HAP are
assumed to be proportional to the amount of each HAP used as solvent.
The preferred approach depends on the type of dry cleaning facilities for which emissions are
being estimated. Table 4.3-1 summarizes these options.
3.1.2 AVAILABLE METHODOLOGIES
Coin-op
Please note that coin-op dry cleaners use PERC. For a VOC inventory, coin-op dry cleaners
may not need to be inventoried. Also, all dry cleaners using PERC have been required under
the dry cleaning NESHAP to report to their EPA Regional Office a description of each dry
cleaning machine and the amount of PERC used. For a facility designated as a "small area
source" (see Table 4.2-1), only PERC used in 1994 needs to be reported (58 FR 49354).
Individual states may have more stringent rules requiring more detailed information.
For coin-op dry cleaners, development and use of a local per facility emission factor is the
preferred method. Data collected under the dry cleaning NESHAP can be used if it reflects
current local conditions. If a local per facility emission factor cannot be developed for
coin-op dry cleaners, a locally developed per dry cleaning unit emission factor for commercial
dry cleaners can be used as the first alternative method. If this approach is not practical, then
the national per employee emission factor for dry cleaning is recommended. County
employment data are the best source of the total number of employees. The third alternative
method is a survey of the number of dry cleaning units in the inventory area, used with the
corresponding appropriate emission factors. The effectiveness of any of these methods will
depend on how well the activity and emission factors used or developed reflect all of the
local conditions.
Commercial and Industrial Dry Cleaners
For commercial dry cleaners and industrial launderers, development of a per facility solvent
consumption factor is the preferred approach. For this method, the number of facilities in the
area must be obtained. NESHAP requirements promulgated in 1993 (58 FR 49354) require
4.3-2 Volume IV
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rn
I
CD
Ul
TABLE 4.3-1
PREFERRED AND ALTERNATE METHODS FOR ESTIMATING
EMISSIONS FROM DRY CLEANING FACILITIES
Methods
Preferred Method
Alternative Method 1
Alternative Method 2
Alternative Method 3
Coin-op (SIC 7215)
Survey a subset of facilities for
the amount of solvent used, using
data collected under the dry
cleaning NESHAP, if it reflects
current local conditions.
Develop a per facility emission
factor, based on either total
solvent use by facility or solvent
used by dry cleaning unit.
Use the per dry cleaning unit
emission factor developed for
commercial laundries (see next
column).
Use the national average per
employee emission factor.
Use the national average per
facility emission factor.
Commercial (SIC 7216)
Survey a subset of facilities for
the amount of solvent used, using
data collected under the dry
cleaning NESHAP. Develop a per
facility emission factor, based on
either total solvent use by facility
or solvent used by dry cleaning
unit.
Survey a subset of facilities for
the amount of solvent used and
the number of employees. Develop
a per employee emission factor.
Use the national average per
employee emission factor.
None
Industrial Laundries (SIC
7218)
Survey a subset of facilities for
the amount of solvent used,
using data collected under the
dry cleaning NESHAP. Develop
a per facility emission factor,
based on either total solvent use
by facility or solvent used by dry
cleaning unit.
Survey a subset of facilities for
the amount of solvent used and
the number of employees.
Develop a per employee
emission factor.
None"
None
O
There is no national average per employee emission factor for industrial laundries.
O
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CHAPTER 4-DRY CLEANING 5/17/96
reporting of this information by commercial and industrial PERC dry cleaning facilities on an
annual basis to the EPA Regional Office. The amount of solvent sent to off-site recycling
should also be determined to estimate emissions. The first alternative method to estimate
emissions for these categories is to use locally developed per employee emission factors.
National emission factors can be used if local factors cannot be developed. A survey of the
number of dry cleaning units can be used as another alternative method, as discussed above
for coin-op dry cleaners. Industrial dry cleaners often use large dry cleaning units that may
emit more than 10 tons/yr per unit. Inventory preparers should be careful that these industrial
facilities and larger commercial facilities are treated as point sources.
All Cleaners
To determine the total emissions from dry cleaning in an inventory area, emissions from each
of the types of dry cleaning are summed. All procedures discussed above must account for
point source emissions.
3.2 DATA NEEDS
3.2.1 DATA ELEMENTS
The data elements needed to calculate emission estimates for dry cleaning sources will depend
on the methodology used for data collection. The data elements that are needed for each
emission estimation technique are presented in Table 4.3-2.
Some of the data elements in Table 4.3-2 are listed as "optional." Inventory preparers will
need to consider current and future needs for the current and possibly other inventories. If
the preferred methods are used, the extra work of collecting additional information will be
small in comparison to repeating the survey effort later.
The number of employees and plants can be determined from local employment offices. The
consumption data can be obtained from a limited survey of representative facilities.
3.2.2 ADJUSTMENTS TO EMISSION ESTIMATES
Data needs for adjustments to emission estimates are presented in Table 4.3-3. Any of these
adjustments may be necessary, depending on the type of inventory being prepared. For
instance, projections or temporal resolution may not be necessary for an annual inventory.
Point Source Corrections
The dry cleaning source category can include point and area sources. Because methods
presented in this chapter may be used to estimate emissions from the entire source category,
4.3-4 Volume IV
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rn
I
CD
Ul
TABLE 4.3-2
DATA ELEMENTS NEEDED FOR EACH METHOD
Data Element
Local Per
Employee
Emission
Factor
(from a
survey)3
Local Per
Facility or
Per Unit
Emission
Factor
(from a
survey)3
National
Average
Emission
Factors
Local Per
Employee
Emission
Factor for
Commercial
and
Industrial
Dry Cleaners
Survey Information:
Types of solvents used
Amount of solvent used (purchased - shipped off-site)
Amount of solvent shipped off-site
Number of employees for each surveyed facility site
Number of employees for inventory area for the SIC
Number of dry cleaning units for a facility
Type of dry cleaning units for a facility
Control types and efficiencies for each equipment type
Number of facilities in an inventory area for the SIC
X
X
Optional15
X
X
Optional
Optional
Optional
Optional
X
X
Optional15
X
X
X
X
Optional
X
Emission Factor Methods:
Local per employee factor
Number of employees or facilities for inventory area for the SIC
National average per employee or per facility factor
X
X
X
X
O
O
;o
-<
o
l~
i
I
a If information collected under the NESHAP requirements is available, it should be the preferred and most accurate data source. If
this is not available, survey a subset of facilities. See Volumes I and VI of this series and Chapter 1 of this volume for more
information about surveys.
b Collection of this information is optional, but it is needed for the most accurate results.
-------
TABLE 4.3-3
DATA NEEDS FOR EMISSION ESTIMATE ADJUSTMENTS
o
I
CD
Data Element
Local Per
Employee
Emission
Factor
(from a
survey)
Local Per
Facility or
Per Unit
Emission
Factor
(from a
survey)
National
Average
Emission
Factors
Local Per
Employee
Emission
Factor for
Commercial
and Industrial
Dry Cleaners
Point Source Corrections:
Point source emissions
Point source employment for inventory area for the SIC
Alternate
Preferred
Preferred
Alternate
Preferred
Alternate
Preferred
Application of Controls:
Control efficiency (CE)
Rule effectiveness (RE)
Rule penetration (RP)
X
X
X
X
X
X
X
X
X
X
X
X
Spatial Allocation:
Employment
Number of facilities
Population of inventory area
Preferred
Alternate 1
Alternate 2
Preferred
Alternate 1
Preferred
Alternate 1
Alternate 2
Preferred
Alternate 1
Alternate 2
Temporal Resolution:
Seasonal throughput
Operating days per week
Operating hours per day for representative facilities
X
X
Optional
X
X
Optional
X
X
Optional
X
X
Optional
O
;o
-<
o
l~
i
1
Ul
-------
rn
I
CD
Ul
TABLE 4.3-3
(CONTINUED)
Data Element
Local Per
Employee
Emission
Factor
(from a
survey)
Local Per
Facility or
Per Unit
Emission
Factor
(from a
survey)
National
Average
Emission
Factors
Local Per
Employee
Emission Factor
for Commercial
and Industrial
Dry Cleaners
Projection:
Projection year precontrol emission factors
Projection year CE
Projection year RE
Projection year RP
Projection year growth factor
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
o
O
;o
-<
o
l~
i
I
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CHAPTER 4-DRY CLEANING 5/17/96
the total emission estimate should be corrected for the amount contributed by the point
sources.
There are two ways to correct for point source contributions, and the choice of approach
depends on the method used to estimate emissions and the data available. The two methods
are either to correct the activity level, such as the number of employees used with an
employee-based emission factor, or to subtract the point source emissions from the total
calculated emissions. If the inventoried point source emissions are greater than the total
estimated emissions, set the area source emissions to zero.
Table 4.3-3 lists the two point source correction methods and shows which is preferred and
which is an alternative for each emission estimation method. The procedure for correcting the
activity level, such as employment, is shown below.
The general equation to correct activity for point sources is:
Total Employees
at Area Sources
Total Employees
in Dry Cleaning
Total Employees
at Point Sources
(4.3-1)
This information may be available from the point source inventory. Be sure to count
employment by SIC Code. Match employees of point source commercial facilities (SIC Code
7216) to total commercial employment, and point source coin-op facilities (SIC Code 7215)
with total coin-op employment.
If the number of employees at point sources is not known, an alternative method can be used
to estimate this value, as follows:
• Use data from the state labor department or County Business Patterns* to
determine the total number of employees reported for SIC 7215 for each dry
cleaning facility in each county in the inventory region.
• Use the region's point source files to obtain the number of point sources in the
inventory region; if this is not available, then:
Use an inventory that lists dry cleaning facilities and their total
emissions and determine the number of facilities above the emission
a See the most recent publication, which can be obtained from the U.S. Bureau of Census,
Department of Commerce, Washington, DC.
4.3-8 Volume IV
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5/17/96 CHAPTER 4 - DRY CLEANING
cutoff for point sources. This is dictated by the type of inventory; for
ozone (VOC) State Implementation Plan (SIP) 1990 base year
inventories, the cutoff was 10 tons of VOC per year.
In the County Business Patterns, the number of employees can be determined
from information presented as the number of facilities with a total number of
employees in a specified range. The total number of employees for all the
facilities listed in each range can be estimated by the midpoint of the indicated
size range. The following example illustrates this technique:
Example 4.5-1:
If an inventory for the region contains five dry cleaning point sources, and the top
five dry cleaning facilities by total employment in the County Business Patterns for
dry cleaning in the region are distributed as follows: three facilities in the 100 to
149 employees per facility size range and two facilities in the 50 to 99 employee per
facility size range, then the total number of employees for point sources can be
calculated using the midpoint of the employee size ranges, as in the equation below:
Total Fmnlovees \ (10° + 149) (50 + ") 1
i°ral Employees = 3 +2 = 3(124.5) + 2(74.5) = 523
at Point Sources ' - ' v ' ^ '
Assume that point sources correspond to the facilities with the highest number of
employees. Start with the facilities with the largest number of employees and sum
the number of employees at the largest facilities for as many facilities as there are
point sources of dry cleaning in the county for the desired SIC.
Application of Controls
Since the level of control required by regulation is usually determined by factors of individual
facility size, type of solvent, and/or machine type, it will be difficult to determine the exact
reduction in emissions with controls unless a survey is performed and information on the type
of machine is gathered. Information on the age of the units, type and amount of solvent used,
and current controls in place may also be needed to estimate the level of control in place.
See the section below on projecting emissions to see the calculation for the application of
controls.
Spatial Allocation
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CHAPTER 4-DRY CLEANING 5/17/96
The spatial allocation of dry cleaning emissions by county can be performed using local
population data. If a detailed survey is performed to estimate emissions, the spatial allocation
of emissions can be performed according to facility location, as with the point source
inventory, or with local employment data. If urban versus rural population is known, urban
population should be used to allocate dry cleaning emissions. Urban and rural population
information can be found in Population and Housing Unit Counts* from the U.S. Census
Bureau.
Temporal Resolution
Seasonal Apportioning. Dry cleaning emissions do not demonstrate differences in activity
from season to season (EPA, 199la). The seasonal activity factor that should be used for this
category is 1.0; activity takes place 52 weeks in the year.
Daily Resolution. Commercial and industrial dry cleaning businesses are open 5 to 6 days
a week. Commercial cleaners are usually open 12 hours a day (starting from 6 or 7 a.m.) but
may only actually do cleaning from 6 to 11 a.m. Industrial dry cleaners may run two shifts,
i.e., 16 hours a day. Coin-op cleaners are open 6 to 7 days a week and may operate
anywhere from 12 to 24 hours a day (Agyei, 1994; EPA, 1991b). The preferred method for
daily resolution is to collect representative information from industrial, commercial, and
coin-op facilities. The alternative method is to assume that activity takes place during a
5-day week (EPA, 199la).
3.3 PROJECTING EMISSIONS
The number of employees or facilities can be adjusted to project future emissions, assuming
that there is no change in the basic processes or chemicals that are used. These data may be
obtained from information on projected revenue growth in the industry and correlation of
revenue to number of employees or facilities.
The equation for projecting emissions in this case is:
b See the most recent publication, which can be obtained from the U.S. Bureau of Census,
Department of Commerce, Washington, DC.
4.3-10 Volume IV
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CHAPTER 4 - DRY CLEANING
EMISPY = ORATEBYO * EMFpYpc *
1 -
100
* GF
(4.3-2)
where:
EMISpY
ORATE
EMF
BY,O
PY,pc
CE
RP
RE
GF
TY
PY
,PY
Projection year emissions
Base year operating rate for each production unit
Projection year precontrol emissions factor (mass of pollutant/
production unit)
Projection year control efficiency (percent)
Projection year rule penetration (RP) (percent)
Projection year rule effectiveness (RE) (percent)
Growth factor (dimensionless)
The precontrol emission factor (EMFPYpc) reflects the mass of pollutant per production unit
emitted before control (EPA, 1993). Chapter 1 of this volume, Introduction to Area Source
Emission Inventory Development, discusses inventory projections in more detail.
EIIP Volume III
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4.3-12 Volume IV
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
The preferred method to estimate emissions for coin-op dry cleaners is the development of
local per facility or per dry cleaning unit emission factors. For commercial dry cleaners and
industrial launderers, a per facility emission factor method is the preferred approach. Unless
permit information with actual emission values is available, developing local emission factors
requires a survey of a subset of dry cleaning facilities. Please refer to Volume I of this
series, Chapter 5, Inventory Development, Chapter 1 of this volume, and Volume VI of this
series, Quality Assurance, for more detailed information about using surveys.
4.1 SURVEY PLANNING
A sample survey cover sheet and form is included in Figures 4.4-1 and 4.4-2. Recommended
data elements to be requested on the forms are:
• Solvent types used;
• Amounts of each type of solvent purchased for inventory year;
• Listing of equipment types at the facility;
• Controls in place at the facility;
• Operating days per week, hours per day;
• Facility employment; and
• Estimated amount of solvent sent for off-site disposal or recycling.
The remainder of this section describes the preferred method of estimating emissions from all
types of dry cleaning sources. Note that total emission estimates for dry cleaners must be
adjusted for point sources to estimate area source emissions.
4.2 PER DRY CLEANING UNIT EMISSION FACTOR METHOD
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CHAPTER 4 - DRY CLEANING
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Name of Facility:_
Street Address:
City/State:_
Contact Person:
Telephone Number:
Please check the appropriate box describing your operation.
1. Solvent Used
PERC (Perchloroethylene)
Petroleum (Stoddard Solvent)
Other Petroleum Solvents
CFC-113 (Trichlorofluoroethane)
TCA (1,1,1-Trichloroethane)
Other
Amount Purchased
Annually (gallons)
FIGURE 4.4-1. SAMPLE SURVEY COVER SHEET
4.4-2
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For each machine at
Machine Type
your facility, please
Load
Capacity
(pounds of
garments)
provide the following information:
Estimated
Solvent Use Per
Load (gallons
of solvent) Controls in Place
For your entire facility, please estimate the amount of solvent sent for off-site disposal or
recycling:
Solvent Type Estimated (gallons/year)
PERC (Perchloroethylene)
Petroleum Solvents:
TCA (1,1,1-Trichloroethane)
CFC-113 (Trichlorofluoroethane)
Other (please specify):
For your facility, please estimate the average days per week and hours per day that
dry cleaning equipment is operating:
days per week hours per day
Please list the number of employees at this facility:
employees
FIGURE 4.4-2. SAMPLE SURVEY FORM
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CHAPTER 4-DRY CLEANING 5/17/96
The following list identifies the steps involved in developing a local per unit emission factor.
• Identify facilities that would be suitable survey recipients, noting those that are
point sources. Facilities can be identified from the local employment office or
tax office records; because many of these facilities are small, they do not
usually belong to dry cleaning associations. However, as more rules come into
place affecting the dry cleaning industry, local information should be easier to
collect.
• Conduct a survey of the total number of dry cleaning units and solvent
consumed for a representative sample of facilities and develop a per unit
emission factor for coin-op dry cleaners. Emission factors that can include the
type of dry cleaning machine as well as the method of control will produce a
more accurate estimate of emissions, and provide a good basis for projections.
• Determine the total number of coin-op dry cleaning facilities in the inventory
region in SIC 7215 from data acquired by state or local labor departments, or
County Business Patterns. If county figures are not available for 4-digit SICs,
state data (which are given in both 2-digit and 4-digit levels) can be used to
break county 2-digit levels into 4-digits.
• Scale up the number of dry cleaning units reported in the survey for all of the
coin-op facilities in the area.
• Correct for point source facilities by subtracting the number of units at the
point source facility sites for this SIC from the estimated total number of area
source dry cleaning units.
• Multiply the per unit emission factor obtained by the procedures described
above by the estimated number of dry cleaning units in area source facilities of
SIC 7215 to obtain an estimate of emissions at dry cleaning area sources.
4.4-4 Volume IV
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5/17/96 CHAPTER 4 - DRY CLEANING
4.3 PER PLANT CONSUMPTION FACTOR METHOD (COMMERCIAL
DRY CLEANERS AND INDUSTRIAL LAUNDERERS)
• Determine the number of facilities in the SIC from local employment offices or
dry cleaning trade association.
• Determine average solvent consumption per facility through a survey of a
representative number of facilities in the SIC.
• Total solvent consumption is estimated by multiplying the number of facilities
times the average solvent consumed per facility.
• For commercial dry cleaners, total emissions are estimated by reducing the total
estimated solvent consumption by the average percent of solvent sent off-site
for recycling. This amount can either be collected by the survey of facilities,
or be obtained from local waste processing and solvent recovery companies
that can be identified from the Yellow Pages. A typical plant produces
approximately one 55-pound bucket of solvent-laden wastes every 2 months.
• For industrial launderers, total emissions are estimated as a percentage of
solvent purchased that cannot be accounted for in its off-site disposal or
recycling manifests. If this information is not available, it can be assumed to
be 5 percent (Agyei, 1994).
• To obtain area source emissions for commercial or industrial dry cleaners,
subtract point source emissions from the total emissions estimated above.
As a gauge of the information returned by the surveys, average annual consumption for
commercial dry cleaning facilities with dry-to-dry units is approximately 40 gallons PERC per
facility (±10 percent). Fewer facilities use transfer machines, since these units are being
phased out. For transfer machines, the annual PERC consumption rate can be assumed to be
in the range of 80 gallons per facility (±10 percent) for facilities with controls, up to
200 gallons per facility for facilities without controls (Agyei, 1994). Please keep in mind that
any projections from this information should reflect this change in equipment type.
In 1993, NESHAP regulations were put into place that require reporting from commercial and
industrial PERC dry cleaners (58 FR 49354). Reports include information about the dry
cleaning machines used at a facility, and the PERC consumption at that facility. The EPA
has distributed this information to their ten Regional Offices. Inventory preparers should
contact the Air Toxics Coordinator in the Air Division of their Regional Office for more
information.
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4.4-6 Volume IV
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
The alternative methods for estimating dry cleaning emissions are described below, by
industry type.
5.1 METHODS FOR COIN-OP DRY CLEANERS (SIC 7215)
The three alternative methods are, in order of preference:
• Use the per dry cleaning unit factor developed as the first alternate method for
commercial dry cleaners (SIC 7216).
• Use the national per employee emission factor.
• Use the national per facility emission factor.
5.1.1 ALTERNATIVE ONE
The first alternative, using the per unit factor that has been developed for commercial dry
cleaners, is described in Section 4.2 of this chapter for the commercial dry cleaning category.
5.1.2 ALTERNATIVE Two
The steps needed to use the second alternative method are as follows:
• Subtract the number of employees at dry cleaning point sources using
information acquired from the point source inventory, or use the method for
point source correction described in Section 3.2.2 of this chapter. Be sure to
match only those employees working at coin-op facilities.
• Multiply the per employee emission factor, either the local commercial per
employee factor, or the national per employee factor (listed in Table 4.5-1), by
the number of employees in area sources of SIC 7215 to obtain an estimate of
emissions at dry cleaning area sources.
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CHAPTER 4 - DRY CLEANING
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TABLE 4.5-1
NATIONAL PER EMPLOYEE EMISSION FACTORS FOR
DRY CLEANING OPERATIONS FROM (EPA, 1991 A)
Subcategory
All solvents (total)
Halogenated Solvents
(total PERC, TCA and
CFC 113)
Coin Operated
Commercial/Industrial
Mineral Spirits &
Other Unspecified
Solvents
Reactive
VOC
(Ib/year/employee)
l,800a
1,800
Applicable
SIC
7216
7216
Total
Organics
(Ib/year/employee)
2,300b
980C
52C
1,200C
1,800
Applicable
SIC
7215, 7216
7215 &
7216
7215
7216
7216
a Emission factor excludes emissions of PERC, TCA, and CFC 113, and represents only emissions of mineral
spirits and other solvents. Thus, this factor is not applicable for coin-operated facilities (SIC 7215) that use
exclusively PERC.
b Total organics are the sum of the PERC, TCA, CFC 113, mineral spirits, and unspecified other solvents.
0 These emission factors would not be used in a VOC inventory, but could be used for an inventory of HAPs.
Readers are encouraged to review the source document for more information about these factors (EPA,
1991a).
5.1.3 ALTERNATIVE THREE
The third alternative method is the use of a national average per facility emission factor of
0.8 tons/facility-year (EPA, 1988). Please note that this number is based on the following
assumptions:
• The average coin-op facility has two dry cleaning units; and
• Each unit emits 0.4 tons of PERC per year.
The total number of coin-op facilities can be determined using the same method as the one
described in Section 4 for the coin-op preferred method. Point source facilities should be
subtracted from this total amount of facilities to determine the number of area source
facilities. This number is applied to the emission factor to calculate the emission estimate.
4.5-2
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5/17/96 CHAPTER 4 - DRY CLEANING
5.2 METHODS FOR COMMERCIAL AND INDUSTRIAL DRY CLEANERS
(SIC 7216 AND 7218)
For commercial dry cleaners and industrial launderers, the alternative methods are the same
for the two industry types, except that the national per employee factor should not be used to
estimate emissions from industrial launderers. The two alternative methods are, in order of
preference:
• Use a local per employee emission factor developed by surveying a subset of
facilities.
• Use a national per employee emission factor (only for commercial dry
cleaners).
5.2.1 ALTERNATIVE ONE
The first alternative method, developing a local per employee emission factor, involves
sending out a survey to a subset of commercial or industrial laundry facilities in the area.
Note that per employee emissions will be significantly different between commercial and
industrial laundries, and separate factors for the two should be developed. Survey forms
should request solvent use, employment numbers, operating days and hours, equipment types
and solvent use, off-site waste disposal, and controls. Emission factors that can incorporate
the type of dry cleaning machine as well as the method of control will produce a more
accurate estimate of emissions. Be certain that point source emissions are not included in the
estimate of area source emissions estimates. See the point source correction discussion in
Section 3.2.2.
5.2.2 ALTERNATIVE Two
The steps needed to use the second alternative method for commercial dry cleaners, using a
national per employee emission factor (listed in Table 4.5-1), are similar to the steps required
in the first alternative method for commercial dry cleaners and industrial launderers. These
steps are:
• Subtract the number of employees at dry cleaning point sources using
information acquired from the point source inventory, or using the method
described in Section 3.2.2, for point source corrections. Be sure to match only
those employees working at commercial facilities to the commercial dry
cleaning employment and industrial laundries to industrial laundry employment.
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CHAPTER 4-DRY CLEANING 5/17/96
Multiply the per employee emission factor, either the local per employee factor,
or the national per employee factor, by the number of employees in area
sources of SIC 7216 to obtain an estimate of emissions at dry cleaning area
sources for commercial dry cleaners.
Multiply the local per employee emission factor by the number of employees in
area sources of SIC 7218 to obtain an estimate of emissions at dry cleaning
area sources for industrial launderers.
4.5-4 Volume IV
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QUALITY ASSURANCE/QUALITY
CONTROL
When using the preferred method, or alternative survey methods, the survey planning, sample
design, and data handling should be undertaken according to the inventory work plan and
Quality Assurance/Quality Control (QA/QC) plans. Refer to the discussion of survey
planning, QA/QC, and the Data Attribute Rating System (BARS) in Volume I of this series
and in the QA volume of this series. No category-specific issues need to be considered.
Data handling for the survey data and for data collected for the other methods should also be
undertaken according to the inventory QA/QC plan. Since facilities may use different
acronyms or trade names for solvents, and may use different measurement units in describing
their operations, care should be taken in the review and collation of the information gathered
from the surveys. No other category-specific issues need to be addressed.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The preferred method and the alternative survey methods give higher quality estimates than
the alternative national emission factor method, but require significantly more effort. The
level of effort required to calculate emissions using any of the national emission factor
methods ranges from 8-40 hours. Conducting a survey requires between 100 to 800 hours
depending on the size of inventory region and the desired level of detail of the survey.
However, the resultant increase in the quality may justify this expenditure of resources,
especially if this category is believed to be a significant contributor to emissions. Emissions
from dry cleaning operations, when calculated using national emission factors, are typically
among the top ten area sources of VOCs and HAPs in urban areas.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARs scores for each method are summarized in Tables 4.6-1 through 4.6-6. A range of
scores is given for several of the survey methods because the scores are dependent on the
representativeness, sample size, and other survey characteristics.
For example, in Table 4.6-1 the score for the activity data will be at the lower end of the
ranges shown if the sample size is small or does not adequately sample facilities of
different sizes because the variability in emissions between facilities can be high. Source
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CHAPTER 4 - DRY CLEANING
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TABLE 4.6-1
PREFERRED METHOD DARS SCORES: SURVEY SIC 7215, 7216,
AND 7218: DEVELOP A LOCAL PER UNIT OR
PER FACILITY EMISSION FACTOR
Attribute
Measurement
Source Specificity
Pollutant
Spatial
Temporal
Composite Scores
Scores
Factor
0.7 - 0.9
1.0
0.6 - 1.0
0.8 - 1.0
0.7 - 1.0
0.76 - 0.98
Activity
0.4 - 0.7
1.0
1.0
0.8 - 1.0
0.7 - 1.0
0.78 - 0.94
Emissions
0.28 - 0.54
1.0
0.6 - 1.0
0.64 - 1.0
0.49 - 1.0
0.60 - 0.92
TABLE 4.6-2
ALTERNATIVE METHOD 1 FOR SIC 7215 (COIN-OP): USING A LOCAL
COMMERCIAL (SIC 7216) PER DRY CLEANING UNIT EMISSION FACTOR
Attribute
Measurement
Source Specificity
Pollutant
Spatial
Temporal
Composite Scores
Scores
Factor
0.7 - 0.9a
0.5
1.0
0.8
0.8
0.76 - 0.8
Activity
0.5
0.8
1.0
0.9
0.7
0.78
Emissions
0.35 - 0.45
0.40
1.0
0.72
0.56
0.60 - 0.62
aAssumes a factor developed by the preferred method.
4.6-2
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CHAPTER 4 - DRY CLEANING
TABLE 4.6-3
ALTERNATIVE METHOD 1 FOR SIC 7216 AND 7218 (COMMERCIAL AND
INDUSTRIAL CLEANERS): SURVEY TO DEVELOP A LOCAL PER EMPLOYEE
FACTOR
Attribute
Measurement
Source Specificity
Pollutant
Spatial
Temporal
Composite Scores
Scores
Factor
0.7 - 0.9
0.9
0.6 - 1.0
0.8
0.7 - 1.0
0.74 - 0.92
Activity
0.3 - 0.5
0.8
1.0
0.8
0.7 - 1.0
0.72 - 0.82
Emissions
0.21 - 0.45
0.72
0.6 - 1.0
0.64
0.49 - 1.0
0.53 - 0.75
TABLE 4.6-4
ALTERNATIVE METHOD 2 FOR SIC 7215 AND 7216 (COIN-OP AND COMMERCIAL
CLEANERS): USING A NATIONAL PER EMPLOYEE FACTOR
Attribute
Measurement
Source Specificity
Pollutant
Spatial
Temporal
Composite Scores
Scores
Factor
0.4
0.5
1.0a
0.4
0.7b
0.6
Activity
0.4
0.9
1.0
0.9
0.7b
0.78
Emissions
0.16
0.45
1.0
0.36
0.49
0.47
a Lower for speciated emissions.
b Assumes factor/activity data year is different than inventory year, but not by much.
EIIP Volume III
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CHAPTER 4 - DRY CLEANING
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TABLE 4.6-5
ALTERNATIVE METHOD 3 FOR SIC 7215 CLEANERS:
USING A NATIONAL PER FACILITY FACTOR
Attribute
Measurement
Source Specificity
Pollutant
Spatial
Temporal
Composite Scores
Scores
Factor
0.3
0.4
0.6 - 1.0
0.3
0.6
0.44 - 0.52
Activity
0.3
0.9
1.0
0.9
0.7
0.76
Emissions
0.09
0.16
0.6 - 1.0
0.27
0.42
0.33 - 0.40
TABLE 4.6-6
COMPOSITE EMISSIONS DARS SCORES:
SUMMARY FOR ALL INDUSTRIES, ALL METHODS
Method
Preferred Method
Alternate Method 1
Alternate Method 2
Alternate Method 3
Coin-op (SIC 7215)
0.60 - 0.92
0.60 - 0.62
0.47
0.33 - 0.40
Commercial (SIC 7216)
0.60 - 0.92
0.53 - 0.75
0.47
-
Industrial (SIC 7218)
0.60 - 0.92
0.53 - 0.75
-
-
4.6-4
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specificity is set to 1.0 assuming that the specific inventory region is surveyed; if the survey
region is different, then this score should be lowered.
In the summary tables, scores may be presented as a range for a particular method because of
variability in the survey sample size, the region covered, or the applicability of the emission
factor to individual sources. For each attribute, issues that would influence scores would be:
• Measurement—sample size and representativeness of the sample determine the
score. The score will also be affected by the correlation between emissions
and the choice of a surrogate activity.
• Source Specificity—is based on whether the emission factor and activity factor,
particularly a surrogate activity factor, are specific to the source being
inventoried or is based on a subset, superset, or category that has been judged
similar.
• Pollutant—a high score is given if the emission factor is developed specifically
for the intended pollutant, and a lower score if less specific methods, such as
speciation profiles are used.
• Spatial-a high score is given if the method was developed for the inventory
region. A lower score is given if the emission factor or activity factor is
extrapolated from a larger or smaller region.
• Temporal—scores will vary based on how specific the emission factor or
activity factory is to the inventory year.
All scores assume that good QA/QC measures are performed and that no significant
deviations from the prescribed methods have been made. If these assumptions are not met,
new DARS scores should be developed according to the guidance [refer to Source Document
(Beck et al., 1994)].
The preferred method gives higher DARS scores than any of the alternative methods. The
alternative methods have composite scores ranging between 0.33 and 0.75, while the scores
for the preferred method vary from 0.6 to 0.92. Furthermore, the scores on all attributes for
the preferred method are higher compared to the alternatives. The highest possible scores for
alternative methods are for well-run surveys of solvent used per employee or amount of
clothes cleaned. The lowest score is for a national average per facility emission factor for
coin-op dry cleaners. The measurement and spatial attribute scores have the greatest
variations amongst the different types of attributes. National level emission factors, because
they represent top-down methods and will not reflect spatial variations, are the methods most
strongly affected by the measurement and spatial attributes.
OF UNCERTAINTY
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CHAPTER 4-DRY CLEANING 5/17/96
The uncertainty of the emission estimates can be quantified if any of the survey methods is
used. [See QA Source Document, Chapter 4]. However, the statistics needed to quantify the
uncertainty of the national emission factor methods and the national solvent use method are
incomplete. Factors that affect the uncertainty for these methods are:
• Regional variability of activity;
• Spatial variability of locations of facilities;
• The number of employees that actually are involved with operations; and
• The amount of true activity that takes place relative to that implied by a
surrogate activity.
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DATA CODING PROCEDURES
This section describes the codes available to characterize dry cleaning emission estimates.
Consistent categorization and coding will result in greater uniformity between inventories.
7.1 PROCESS AND CONTROL CODES
The process codes for dry cleaning operations are shown in Table 4.7-1. These codes are
compatible with the Aerometric Information Retrieval System (AIRS) Area and Mobile
Source (AMS) source category codes (EPA, 1994). The control codes for use with AMS are
shown in Table 4.7-2. Federal, state, and local regulations can be used as guides to estimate
the type of control used and the level of efficiency that can be achieved. Be careful to apply
only the regulations that specifically include area sources. If the regulation is applicable only
to point sources, it should not be assumed that similar controls exist at area sources without a
survey. The "099" control code can be used for miscellaneous control devices that do not
have a unique identification code. The "999" code can be used for a combination of control
devices where only the overall control efficiency is known.
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TABLE 4.7-1
AIRS AMS CODES FOR THE DRY CLEANING CATEGORY
Category Description
Commercial/Industrial Cleaners
(SIC 7216 and SIC 7218)
Coin-Operated Cleaners (SIC 7215)
All Processes
Process Description
Perchl oroethy 1 ene
Special Naphthas
Solvent - Other
Total: All Solvent Types
Perchl oroethy 1 ene
Special Naphthas
Solvent - Other
Total: All Solvent Types
Perchl oroethy 1 ene
Special Naphthas
Total: All Solvent Types
AMS Code
24-20-010-055
24-20-010-370
24-20-010-999
24-20-010-000
24-20-020-055
24-20-020-370
24-20-020-999
24-20-020-000
24-20-000-055
24-20-000-370
24-20-000-000
TABLE 4.7-2
AIRS CONTROL DEVICE CODES
Control Device
Carbon Adsorption
Refrigeration System
Miscellaneous Control Device
Combined Control Efficiency
Code
048
073
099
999
4.7-2
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8
REFERENCES
Agyei, K., Puget Sound Air Pollution Control Agency, with L. Adams, Radian Corporation.
November 10, 1994. Dry Cleaning Emission Estimation Methodologies.
Beck, L.L., R.L. Peer, L.A. Bravo, Y. Yan. 1993. A Data Attribute Rating System.
Presented at the EPA/AWMA Specialty Conference on Emission Inventory: Applications and
Improvement, Raleigh, North Carolina.
EPA. 1994. AIRS Database. Office of Air Quality Planning and Standards,
U.S. Environmental Protection Agency. Research Triangle Park, North Carolina. 1994.
EPA. 1993. Guidance for Growth Factors, Projections, and Control Strategies for the
15 Percent Rate-of-Progress Plans. Office of Air Quality Planning and Standards,
U.S. Environmental Protection Agency, 452/R-93-002. Research Triangle Park,
North Carolina.
EPA. May 199 la. Procedures for the Preparation of Emission Inventories for Carbon
Monoxide and Precursors of Ozone, Vol. I: General Guidance for Stationary Sources. Office
of Air Quality Planning and Standards Office of Air and Radiation, U.S. Environmental
Protection Agency, EPA-450/4-91-016. Research Triangle Park, North Carolina.
EPA. November 1991b. Dry Cleaning Facilities—Background Information for Proposed
Standards. Office of Air Quality Planning and Standards, U.S. Environmental Protection
Agency, EPA 450/3-91-020a (NTIS PB92-126762). Research Triangle Park, North Carolina.
EPA. September 1988. Control of Volatile Organic Emissions from Perchloroethylene Dry
Cleaning Systems. U.S. Environmental Protection Agency, 230-09-88/039. Research Triangle
Park, North Carolina.
EPA. September 1985 - 1995. Compilation of Air Pollutant Emission Factors, Volume I:
Stationary Point and Area Sources. Fourth Edition and Supplements A-F, AP-42
(GPO 055-000-00251-7). U.S. Environmental Protection Agency. Research Triangle Park,
New York.
Frost & Sullivan, Inc. 1990. Industrial Solvents - Winter 1989. New York, New York.
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EIIP Volume III 4.8-1
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VOLUME III: CHAPTERS
CONSUMER AND
COMMERCIAL SOLVENT USE
Final Report
August 1996
Prepared by:
Eastern Research Group
Post Office Box 2010
Morrisville, North Carolina 27560
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
CONTENTS
Section Page
1 Introduction 5.1-1
2 Source Category Description 5.2-1
2.1 Emission Sources 5.2-2
2.1.1 Personal Care Products 5.2-3
2.1.2 Household Products 5.2-5
2.1.3 Automotive Aftermarket Products 5.2-5
2.1.4 Adhesives and Sealants 5.2-7
2.1.5 FIFRA-regulated Products 5.2-7
2.1.6 Coatings and Related Products 5.2-7
2.1.7 Miscellaneous Products 5.2-8
2.2 Factors Influencing Emissions 5.2-8
2.2.1 Process Operating Factors 5.2-8
2.2.2 Control Techniques 5.2-8
3 Overview of Available Methods 5.3-1
3.1 Emission Estimation Methodologies 5.3-1
3.2 Available Methodologies 5.3-1
3.2.1 Volatile Organic Compounds 5.3-1
3.2.2 Hazardous Air Pollutants 5.3-2
3.3 Data Needs 5.3-2
3.3.1 Data Elements 5.3-2
3.3.2 Application of Controls 5.3-3
3.3.3 Spatial Allocation 5.3-3
3.3.4 Temporal Resolution 5.3-4
3.3.5 Projecting Emissions 5.3-4
4 Preferred Methods for Estimating Emissions 5.4-1
4.1 Application of Controls 5.4-2
4.2 Other Adjustments 5.4-7
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CONTENTS
Section Page
5 Alternative Methods for Estimating Emissions 5.5-1
5.1 Procedure 5.5-1
5.2 Data Elements 5.5-1
6 Quality Assurance/Quality Control (QA/QC) 5.6-1
6.1 Emission Estimate Quality Indicators 5.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 5.6-1
6.1.2 Sources of Uncertainty 5.6-3
7 Data Coding Procedures 5.7-1
7.1 Process Codes 5.7-1
8 References 5.8-1
Appendix A: Results of the EPA's Consumer Product Survey
Appendix B: EPA Consumer/Commercial Products Survey
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TABLES
Tables Page
5.2-1 Consumer Product Groups and Categories 5.2-4
5.2-2 Automotive Consumer Product Categories 5.2-6
5.2-3 Product Subcategories Listed for Development of Federal Regulations
by 1997 5.2-10
5.2-4 Existing and Proposed State Regulations for Consumer and
Commercial Products 5.2-11
5.4-1 Per Capita Consumer and Commercial Solvent VOC Emission
Factors and Contents 5.4-3
5.4-2 Per Capita Consumer and Commercial Solvent HAP Emission Factors 5.4-4
5.6-1 Preferred Method BARS Scores: National Per Capita
Emission Factors with Adjustments for Regulations 5.6-2
5.6-2 Alternative Method BARS Scores: Local Survey of
Bistributors/Retailers 5.6-2
5.7-1 AIRS AMS Codes for Consumer and Commercial Products 5.7-2
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vi Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from consumer and commercial solvent use. Section 2 of this chapter contains a general
description of the consumer and commercial solvents category and an overview of available
control technologies. Section 3 of this chapter provides an overview of available emission
estimation methods. Section 4 presents the preferred emission estimation methods for
consumer and commercial solvents, and Section 5 presents alternative emission estimation
techniques. Quality assurance and quality control procedures are described in Section 6.
Data coding procedures are discussed in Section 7, and Section 8 is the reference section.
Appendix A presents a compilation of the U.S. Environmental Protection Agency's (EPA's)
1992 consumer product survey, as presented in Table 5-1 of the March 1995 Report to
Congress (EPA-453/R-94-066-A). This information was used to develop the volatile organic
compound (VOC) emission factors presented in this chapter. Information derived from the
survey was also used to develop hazardous air pollutant (HAP) emission factors for consumer
and commercial solvent use. Appendix B presents the survey form developed by the EPA to
obtain information on these products.
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SOURCE CATEGORY DESCRIPTION
Products containing solvents are used in a variety of industrial, commercial, and domestic
applications. Solvent compounds are used as cleaning agents, as intermediate compounds in
the application of another product, or as a component in the formulation of many products.
Section 183(e) of the 1990 Clean Air Act Amendments required the EPA to prepare a Report
to Congress to assess the impact of VOC emissions from the use of consumer and
commercial products. As explained in the EPA's Report to Congress Study of Volatile
Organic Compound Emissions from Consumer and Commercial Products (EPA, 1995), the
1990 Clean Air Act's statutory definition of consumer and commercial products is much
broader than just traditional personal care and household cleaning products. It includes all
VOC-emitting products used in the home, by businesses and institutions, and in industrial
manufacturing operations. Therefore, this broad definition of products includes surface
coatings, metal cleaning solvents, graphic arts inks, industrial adhesives, and asphalt paving
materials.
In the Report to Congress, the terminology is clarified by defining "consumer products" as
those products used around the home, office, institution, or similar settings. The commercial
and institutional use of these products is included under "consumer products." This
definition is consistent with the EPA's definition of "commercial/consumer solvent use"
discussed in the procedures document (EPA, 1991). The other solvent-containing products
included in the broad statutory definition of consumer and commercial products are covered
in individual inventory source categories, particularly under stationary source solvent
evaporation source categories such as graphic arts, dry cleaning, surface cleaning, and asphalt
paving. Industrial solvent applications should also be accounted for as point sources, or
included in industrial area source solvent categories.
This chapter discusses only nonindustrial solvents that are used in commercial or consumer
applications. The solvent-containing products in this category include personal care products,
household products, automotive aftermarket products, adhesives and sealants, pesticides,
some coatings, and other commercial and consumer products that may emit VOCs. The
product subcategories will be discussed in more detail below. The information and emissions
data presented in this section remain consistent with previous area source emission inventory
definitions of consumer products, while at the same time allowing the inventory agency to be
consistent with regulatory and compliance requirements, provided all terminology is clearly
defined. Products not included in this category are products used as non-aerosol traffic
markings, architectural and industrial maintenance coatings, autobody refinishing coatings,
and products used in industrial processes.
2.1 EMISSION SOURCES
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Volatile organic compounds are ingredients of consumer and commercial products that serve
as propellants, aid in product drying (through evaporation), act as co-solvents and cleaning
agents, and are emitted during product use. Typically these VOC sources are large in
number, highly dispersed, and individually emit relatively small amounts of VOC. It is
important to note here that not all organic compounds contained in consumer and commercial
products are considered reactive VOCs by the EPA due to their negligible photochemical
reactivity. Care must be taken to identify the individual VOC species in consumer and
commercial products and exclude nonreactive compounds in a State Implementation Plan
(SIP) emissions inventory or similar inventory. The VOC emission factors presented in this
chapter have been adjusted to remove compounds such as acetone listed as nonreactive by
the EPA as of April 1996.
Solvents contained in consumer and commercial products are primarily released during
product use. Residual amounts of solvent may also remain in discarded product packaging,
enter the municipal solid waste stream, and be disposed of in landfills. Solvents from these
products may also enter the wastewater treatment system through use and disposal. The
assumption in previous SIP inventories has been that all VOCs in consumer and commercial
products will volatilize to the air. However, recent studies prepared by the EPA have
identified several substances that are known to be biodegradable in wastewater, which allows
for more accurate assessments of the fate of these compounds when they are ingredients of
products that are used with water (detergents, soaps, etc.). The EPA concluded, however,
that there was not enough information available on the fate of VOCs in consumer products in
landfills to make any adjustments for VOC-release mechanisms at this time. Therefore, as
noted in Appendix A, the VOC emission factors presented in this chapter have been adjusted
to account for biodegradation of VOCs that enter the wastewater stream, but not those that
enter a landfill. Detailed information on the fate of solvents in consumer and commercial
products in landfills and wastewater treatment systems is presented in two EPA Reports to
Congress (EPA, 1994a, 1994b).
The EPA is in the process of developing regulations for this source category. Seven major
consumer and commercial product groups and their respective categories have been
established by the EPA. These are:
• Personal care products;
• Household products;
• Automotive aftermarket products;
• Adhesives and sealants;
• Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA)-regulated
products;
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• Coatings and related products; and
• Miscellaneous products.
Table 5.2-1 provides the categories assigned to these major product groups. These product
categories are also categories of household hazardous waste and are discussed in more detail
below.
2.1.1 PERSONAL CARE PRODUCTS
Personal care products, as shown in Table 5.2-1, include hair care products, deodorants and
antiperspirants, perfumes and colognes, and nail care products. According to surveys of the
industry, ethanol and isopropanol are the primary solvents used in the formulation of these
products (Frost & Sullivan, Inc., 1989).
As shown in Appendix A, hair care products alone consist of over 20 different subcategories
of product types. Most hair care products are regulated by the Food and Drug
Administration (FDA) as cosmetics. Hair care product types differ by the function they
perform. Frequency of use depends on the product's function and determines the quantity of
the product type consumed annually. Virtually every hair care product contains some
amount of VOCs; the amount of VOC can range from 0 to 100 percent of total formulation.
Several factors affect the amount of VOC emitted by hair care products, primarily market
share and VOC content. These factors are influenced by product type, product form, and
variation in consumer use.
The product market for deodorants and antiperspirants offers a variety of high- to low-VOC
content products. The ingredients in deodorants and antiperspirants are classified as active or
nonactive (inert), depending on the function they perform. The active ingredients in most
deodorants on the market are Triclosan®, zinc phenolsulfonate, or Hyamine®. Aluminum
salts are the active ingredient in most antiperspirants. Unlike active ingredients, nonactive
ingredients vary greatly from product to product. Like hair care products, virtually all
underarm products contain VOCs that are generally nonactive ingredients. Aerosol
propellants account for the largest VOC weight percentage of an ingredient in underarm
products. Deodorant aerosols contain
TABLE 5.2-1
CONSUMER PRODUCT GROUPS AND CATEGORIES
Personal Care Products
Adhesives and Sealants
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Hair Care Products8
Deodorants and Antiperspirants
Fragrance Products
Powders
Nail Care Products
Facial and Body Treatments
Oral Care Products
Health Use Products
Miscellaneous Personal Care Products
Household Products
Hard Surface Cleaners
Laundry Products
Fabric and Carpet Care Products
Dishwashing Products
Waxes and Polishes
Air Fresheners
Shoe and Leather Care Products
Miscellaneous Household Products
Automotive Aftermarket Products
Detailing Products
Maintenance and Repair Products
Consumer Adhesives
Sealants
FIFRA-Regulated Products'3
Insecticides
Fungicides and Nematicides
Herbicides
Antimicrobial Agents
Other FIFRA-Regulated Products
Coatings and Related Products
Aerosol Spray Paints
Coating-Related Products
Miscellaneous Products (not otherwise covered)
Arts and Crafts Supplies
Nonpesticidal Veterinary and Pet Products
Pressurized Food Products
Office Supplies
a Consists of over 20 different subcategories of product types. Most products are regulated by the Food and
Drug Administration as cosmetics.
b Federal Insectide, Fungicide, and Rodenticide Act.
5.2-4
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95 percent VOCs by weight, 30 percent propellant and 65 percent solvent. Antiperspirant
aerosols contain an average of 75 percent VOCs by weight. The most commonly used
propellants are n-butane, isobutane, and propane.
2.1.2 HOUSEHOLD PRODUCTS
Household products primarily consist of cleaning products for hard surfaces, clothing, carpet,
and dishes, and waxes and polishes. Other products include air fresheners and charcoal
lighter fluids.
Each subcategory of cleaning products is made up of a variety of product types and
formulations. Cleaning products are categorized based on their cleaning function. The
frequency of use and quantity of a product used depends on the product's cleaning function
and the amount of product required to meet that function. Like the other products discussed
here, cleaning products can contain from 0 to 100 percent VOCs. The amount of VOCs
emitted primarily depends on the VOC content of the product and the amount of product
used. The VOC content of a product formulation depends on the product type and form, as
well as the VOC function requirements. The VOCs in a product may be an essential
component of the cleaning function, or serve to maintain interactions among other
ingredients.
Product types differ by their function to mask or remove odors from the air. Air fresheners
(room deodorizers) are designed principally to treat indoor environments. Most products are
air fresheners that mask odors with a pleasant scent. Other products are marketed to remove
the odors through chemical reactions. The VOC content of air fresheners ranges from 3.5 to
100 percent, depending on the form of the product. Aerosol and liquid sprays typically
contain ethanol and isopropanol as solvents. Aerosols also contain propane, butane, and
isobutane as propellants. Gels and powders have a relatively low VOC content.
2.1.3 AUTOMOTIVE AFTERMARKET PRODUCTS
The EPA has divided automotive consumer products into two major categories: (1) detailing
products, and (2) maintenance and repair products. Table 5.2-2 delineates the subcategories
of products in these two groups. It is often difficult to distinguish the automotive
aftermarket product subcategories because product category descriptions and designations
may overlap. It can also be difficult to distinguish between formulations for distinct product
types and different formulations for products intended for the same use. In some cases,
varying formulations may be due to the product form. There are a large number of
individual VOCs in these products, including HAPs.
TABLE 5.2-2
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AUTOMOTIVE CONSUMER PRODUCT SUBCATEGORIES
Product Type
Detailing Products
Body cleaning compounds
Bug and tar removers
Car washing products
Fiberglass polish
Glass or plexiglass/plastic window
cleaner/treatment
Metal polish/chrome cleaner
Polishes
Rubber/vinyl/leather protectants/dressing (and
vinyl top cleaners/waxes)
Rustproofing/treatment compounds (exterior)
Soaps
Tire coating/paints
Upholstery cleaners/interior cleaners
Waxes
Wheel/tire/mat cleaners
Maintenance and Repair Products
Antifreeze/coolant
Belt dressings
Engine cleaners/degreasers/parts cleaners
Engine starting fluids
Fuel system antifreeze
Lubricants
Motor flush/crankcase cleaner
Transmission sealer/conditioner/additive/leak-stop
Tire cement/sealant/inflators
Windshield deicer
Windshield washer fluid
Detailing products are used for cosmetic purposes for cleaning, polishing, and waxing. This
category does not include products used for restoring or repainting operations, but does include
windshield washer fluids. VOCs contained in detailing products are emitted during their use or
over time after application.
Maintenance and repair products include engine and parts cleaners, carburetor/fuel injection
cleaners, lubricants, antifreeze, radiator cleaners, and brake fluids, among others. VOC
emissions from the use of these products occur during application, removal (for replacement),
leakage, and from disposal of unused portions.
Automotive "touch-up" paints, sanding primers, engine enamels and other aerosol coatings
that would not be included in the autobody refmishing area source category are in the
coatings group of the consumer and commercial solvent use area source category.
5.2-6
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2.1.4 ADHESIVES AND SEALANTS
Adhesives are formulated organic polymer compounds that adhere to, or form a bond
between, one or more substrates. They are commonly referred to as cements, glues, and
pastes. Adhesives can be classified as water-based, solvent-based, hot melts, or radiation
curable. Sealants and caulking compounds are organic polymers used to fill or seal gaps
between surfaces. The primary solvents used in formulating adhesives and sealants are
aliphatic hydrocarbons and ketones.
2.1.5 FIFRA-REGULATED PRODUCTS
Pesticides defined by FIFRA include substances or mixtures that are used to prevent, destroy,
repel, or mitigate pests, as well as substances used as plant regulators, defoliators, and
desiccants. The pesticide industry can be divided into consumer and agricultural categories.
Agricultural products are applied to crops to prevent the growth of weeds and insect
infestations.
Consumer pesticides are used in the home and garden, as well as in commercial and
governmental applications. Disinfectants and antimicrobial products are included.
Household uses include pet care products, disinfectants, and insecticides. All consumer and
commercial pesticide products contain VOCs. Aerosol and liquid sprays contain VOCs as
solvents, usually ethanol and isopropanol. Aerosol propellants are primarily propane, butane,
and isobutane. Products such as baits, powders, and granules have relatively low VOC
content due to their solid form. Pesticide products can be grouped according to their target
pest, but should also be grouped according to their form (solid, liquid, or aerosol) when
considering control measures.
The FIFRA emission factors presented in this chapter are for consumer and commercial
product use. Emission estimation methods for FIFRA-regulated products are also discussed
in detail in Chapter 9, Pesticide Applications, of this volume. Care should be taken to avoid
double counting emissions calculated with Chapter 9 methods and those presented in this
chapter. Depending on the methods used, it may not be practical to use the FIFRA data in
Appendix A (Consumer Product Survey).
2.1.6 COATINGS AND RELATED PRODUCTS
Aerosol spray paints and related products such as paint removers make up this consumer and
commercial solvent product group. Other forms of coatings (besides aerosols) are not
included in this group, but are included under architectural or industrial coatings, or autobody
refinishing. Aerosol spray paints contain VOCs that function as both solvents and
propellants. The most commonly used propellants in aerosol paints are propane, butane, and
isobutane. Synthetic propellants such as chloroflurocarbons are no longer used in significant
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amounts as propellants nor are they regulated as VOCs.
Paint removers are classified as either application removers or immersion removers. Paint
removers typically contain methylene chloride (a nonreactive VOC) as the principal
ingredient. Other solvents such as methanol, ethanol, and isopropanol are also used to
enhance the action of the paint remover. Methylene chloride (53 percent) and methanol (41
percent) account for the majority of paint-removing solvents consumed (Frost & Sullivan,
Inc., 1990).
2.1.7 MISCELLANEOUS PRODUCTS
Miscellaneous consumer products not covered in the other product groups include arts and
crafts supplies, nonpesticidal veterinary and pet products, and pressurized food products.
These products are not significant contributors to VOC emissions relative to the other source
categories.
2.2 FACTORS INFLUENCING EMISSIONS
2.2.1 PROCESS OPERATING FACTORS
Consumer purchasing practices directly influence VOC emissions by controlling total product
consumption on a long-term basis. In any evaluation of emissions and potential control
strategies, consumer acceptability and product safety must be considered. The method used
to dispose of unused products also affects overall VOC emissions from consumer and
commercial products.
2.2.2 CONTROL TECHNIQUES
Potential control strategies for VOC emissions from consumer and commercial products
typically involve:
• A change in the application method (repackaging);
• Product substitution;
Product reformulation; and
Directions for use, storage, and disposal.
Requiring a change in the application method generally means that liquid and aerosol
products are replaced with solid products. As discussed above, products in solid form
typically have lower VOC content because solvent is not required to aid in drying and
5.2-8 Volume III
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8/02/96 CHAPTER 5 - SOLVENT USE
propellants are not needed.
Product substitution is a control measure that consists of replacing an existing product with a
substitute product that acheives the desired goal, but results in reduced VOC emissions (EPA,
1995).
The EPA also acknowledges the innovative product concept, which involves the use of
higher VOC-containing products that result in reduced VOC emissions over time or per
application. For example, the use of some types of products results in less frequent
reapplications, or less of the product is needed, thereby reducing overall VOC emissions.
Product reformulation typically consists of developing low-VOC products by modifying the
chemical composition. Reformulation may involve substitution of VOCs with less
photochemically reactive compounds while maintaining the product's integrity (SAIC, 1987;
EPA, 1995). An example of a compound used to replace VOCs in consumer and
commercial products is the use of carbon dioxide as a propellant.
Providing consumers with directions for the proper use, storage, and disposal of products can
also result in reduced emissions. Product labeling and consumer education are typically
used.
In a March 23, 1995, Federal Register (FR) notice, the EPA identified 24 consumer product
subcategories scheduled for development of federal regulations (60 FR 15264). These
subcategories are shown in Table 5.2-3. The EPA notes in the Federal Register notice that
these products are currently regulated in one state or more. As individual products and
categories are further assessed, the EPA reserves the right to remove categories from or add
categories to the list.
Seven states—California, Connecticut, Massachusetts, New Jersey, New York, Rhode Island,
and Texas—have or are proposing regulations that affect consumer and commercial product
VOC emissions. Table 5.2-4 summarizes the existing and proposed state regulations for
consumer and commercial products that limit the percentage of VOCs the products can
contain. The regulations listed in Table 5.2-4 may not be all inclusive and are subject to
change.
El IP Volume III 5.2-9
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CHAPTER 5 - SOLVENT USE
8/02/96
TABLE 5.2-3
PRODUCT SUBCATEGORIES LISTED FOR DEVELOPMENT OF
FEDERAL REGULATIONS BY 1997
Aerosol Cooking Sprays
Aerosol Underarm Antiperspirants and Deodorants
Air Fresheners
Auto Windshield Washer Fluids
Bathroom and Tile Cleaners
Carburetor and Choke Cleaners
Charcoal Lighter Materials
Dusting Aids
Engine Degreasers
Fabric Protectants
Floor Waxes and Polishes
Furniture Maintenance Products
General Purpose Cleaners
Glass Cleaners
Hair Sprays
Hair Mousses
Hair Styling Gels
Household Adhesives
Nonagricultural Insecticides
Laundry Prewash Treatments
Laundry Starch Products
Nail Polish Removers
Oven Cleaners
Shaving Creams
5.2-10
Volume III
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rn
TABLE 5.2-4
Co
I
CD
to
EXISTING AND PROPOSED STATE REGULATIONS FOR CONSUMER
AND COMMERCIAL PRODUCTS (AS OF 12/94)
Product Subcategory
Aerosol Cooking Sprays
Air Freshener
Single-phase
Double-phase
Liquids/Pump Sprays
Solids/Gels
Dual Purpose Air Freshener/
Disinfectant Aerosol
Automotive Windshield
Washer Fluids
Cold Climate Areas
All Other Areas
Bathroom and Tile Cleaners
Aerosols
All Other Forms
Charcoal Lighter Material
Carburetor/Choke Cleaners
Percent VOCs by Weight
California"
Phase
I
18
70
30
18
3
35
10
7
5
75
Phase
II
30
60
Proposed
Connecticut'
Phase
r
70
30
18
Phase
II"
30
Mass"
70
30
18
3
Proposed
New Jersey'
Phase
Is
18
70
30
18
3
35
10
75
Phase
IP
30
New York1
Phase
F
70
30
18
3
Phase
IIk
30
Proposed
Rhode
Island1
70
30
18
3
60
7
5
Texas1"'"
18
70
30
18
3
23.5
7
5
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TABLE 5.2-4
(CONTINUED)
Product Subcategory
Disinfectants
Dusting Aids
Aerosol
All Other Forms
Engine Degreasers
Fabric Protectants
Floor Polishes/Waxes
Products for Flexible
Flooring Materials
Products for Nonresilient
Flooring
Wood Floor Wax
Furniture Maintenance
Products
Aerosols
All Other Forms
(except solid or paste)
General Purpose Cleaners
Glass Cleaners
Aerosols
Percent VOCs by Weight
California"
Phase
I
60
35
1
75
75
7
10
90
25
7
10
12
Phase
II
30
25
50
60
Proposed
Connecticut'
Phase
r
75
10
Phase
II"
50
Mass"
75
7
10
90
25
7
10
12
Proposed
New Jersey'
Phase
I8
35
7
75
75
7
10
90
25
10
12
Phase
II"
25
50
New York1
Phase
F
10
Phase
IIk
Proposed
Rhode
Island1
60
75
7
10
90
25
7
10
12
Texas1"'"
35
7
75
75
7
10
90
25
10
12
O
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-------
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to
TABLE 5.2-4
(CONTINUED)
Product Subcategory
All Other Forms
Hair Mousses
Hair Sprays
Hair Styling Gels
Household Adhesives
Aerosols
Construction and Panel
Contact
General Purpose
Insecticides
Crawling Bug
Flea and Tick
Flying Bug
Foggers
Percent VOCs by Weight
California'
Phase
I
8
16
80
6
75
40
80
10
40
25
35
45
Phase
II
6
55
25
20
Proposed
Connecticut*
Phase
Ic
80
40
25
35
45
Phase
II"
55
20
Mass"
8
16
80
6
40
25
35
45
Proposed
New Jersey'
Phase
le
8
80
75
40
80
10
40
25
35
45
Phase
II"
6
55
25
20
New York1
Phase
F
80
Phase
II"
55
Proposed
Rhode
Island1
8
16
80
6
40
20
30
40
Texas111'11
6
16
80
6
75
40
80
10
40
25
35
45
O
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m
-------
CHAPTER 5 - SOLVENT USE
8/02/96
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u^
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oo
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Nail Polish Removers
Oven Cleaners
oo
oo
oo
oo
Aerosols/Pump Sprays
„
-
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Shaving Creams
S
Underarm Antiperspirall
£,
O
0
0
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(N
O
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&
0
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b
0
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5.2-14
Volume III
-------
rn
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TABLE 5.2-4
(CONTINUED)
Product Subcategory
Underarm Deodorant
Aerosol
Nonaerosol
Percent VOCs by Weight
California'
Phase
I
20/20"
0/0"
Phase
II
0/10"
0/0"
Proposed
Connecticut'
Phase
r
20
Phase
II"
Mass"
20"
Proposed
New Jersey'
Phase
Is
60"
0"
Phase
II"
0"
0"
New York1
Phase
P
20/20"
0/0"
Phase
II"
0/10"
0/0"
Proposed
Rhode
Island1
0/10"
0/0"
Texas1"'"
20"
0"
California Code of Regulations, Title 17 - Public Health, Division 3 - Air Resources, Chapter 1 - Air Resources Board, Subchapter 8.5 -
Consumer Products; adopted January 28, 1991; amended September 19, 1991; December 7, 1992.
"Sprays Under Pressure," Spray Technology & Marketing, 4:18. October 1994.
Effective 1/1/96 (if adopted).
Effective 1/1/98 (if adopted).
"Sprays Under Pressure/Regulatory Affairs," Spray Technology and Marketing, 5:23. January 1995.
"Regulatory: Sprays Under Pressure," Spray Technology and Marketing, 5:14. February 1995.
Expected to become effective in December 1995.
Effective at some yet undetermined date.
Regulatory Affairs/Aerosols Under Pressure," Spray Technology and Marketing, 1:10. December 1991.
Effective 1/1/94.
Effective 1/1/96 for air fresheners and hair sprays and 1/1/97 for deodorants and antiperspirants.
"Sprays Under Pressure," Spray Technology and Marketing, 4:10. January 1994.
"Sprays Under Pressure/Regulatory," Spray Technology and Marketing, 4:39. September 1994.
Effective 1/1/95 for everything but nail polish removers and 1/1/96 for nail polish removers.
In response to a petition from a manufacturer, Texas is in the process of deleting Aerosol Insect Repellents from the Table of Standards
(65%).
HVOC/MVOC limits (MVOC = organic compounds with vapor pressure greater than 2 mm of Hg at 20°C).
Limit is for HVOCs (organic compounds with vapor pressure greater than 20 mm of Hg at 20°C).
o
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CHAPTER 5 - SOLVENT USE 8/02/96
This page is intentionally left blank.
5.2-16 Volume III
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8/02/96 CHAPTER 5 - SOLVENT USE
OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
Two methodologies are available for calculating emissions from consumer and commercial
solvent use. The method used depends upon the degree of accuracy required in the estimate,
available data, and available resources.
This section discusses the methods available for calculating emissions estimates from
consumer and commercial products and identifies the preferred calculation method. A
discussion of the data elements needed for each method is also provided.
3.2 AVAILABLE METHODOLOGIES
3.2.1 VOLATILE ORGANIC COMPOUNDS
As discussed previously, most VOCs released into the air from the use of consumer and
commercial products are from the evaporation of the solvent contained in the product or
from the propellant. Determining the amount of VOCs in the products, making adustments
for the biogradation of VOCs in wastewater, and determining the volume of products sold (or
used) should provide a good estimate of the VOCs emitted by this source category. There
are two approaches for estimating the amount of VOCs emitted from this source category:
• National average per capita emission factors adjusted for state or local
emission limits; or
• Surveying consumer and commercial product use or sales in the inventory
area.
The population-based method is preferred for emission estimation. This method can be used
to estimate VOC emissions from consumer and commercial products in the inventory area,
and can be adjusted to reflect applicable controls (see discussion in Section 4.1).
While surveying consumer and commercial product use may be a more accurate method for
El IP Volume III 5.2-1
-------
emission estimation, it will be very expensive if done correctly. Most consumer and
commercial solvent use cannot be easily identified by questionnaires, surveys, or other
inventory procedures yielding local emission estimates because of variations in product
formulations and wholesale/retail distribution. Product surveys of distributors and retailers
may still be useful in determining local trends in product use, however. It may also be
useful to conduct surveys of product use by the general public. The survey results can be
used to make adjustments to the population-based emission estimates if it is determined that
they are needed.
3.2.2 HAZARDOUS AIR POLLUTANTS
HAP emissions from this source can also be estimated using two methods:
• Using national average per capita emission factors (population-based method);
or
• Developing speciation profiles based on the information provided in this
chapter and applying them to the VOC emission estimate developed using the
alternative method.
The population-based method is the preferred method, with adjustments for state and local
regulations on this industry.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements used to calculate emission estimates for the consumer and commercial
products category depend on the methodology used to estimate emissions. The data elements
that are necessary for using the national average per capita VOC or HAP emission factors
are:
• Population in the inventory area;
• Per capita emission factors (shown in Section 4 and in Appendix A); and
• Information on state and local regulations.
If the survey method is used to estimate emissions or to make local adjustments to the
estimates made using the national average per capita emission factors, the data elements
necessary in a survey include:
5.3-2 Volume III
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8/02/96 CHAPTER 5 - SOLVENT USE
• Product type;
• Product amount distributed or used by type (weight or volume); and
• Product density, if distributors or retailers are surveyed rather than consumers.
The survey may also request information on seasonal variability and other factors that may
affect product use.
3.3.2 APPLICATION OF CONTROLS
Because most controls will affect the content of the products themselves (requiring
reformulation or a change in the application method) or require product substitution, an
evaluation of applicable state or local regulations will give an indication of the adjustments
that should be made to the emission estimates derived using the population-based method.
Since a reformulation or substitution represents an irreversible process change, and thus a
reduction in emissions from a product category, rule effectiveness can be assumed to be 100
percent for that product type.
Rule penetration will be based on the percentage of sources within the category that are
affected by the rule and consumer purchasing practices. Factors that will affect rule
penetration include: (1) sales of older products that may be grandfathered in the regulation
because they were manufactured or distributed before the regulation was enacted, (2) the ease
with which consumers can purchase unregulated products, and (3) the desire on the part of
consumers to purchase unregulated products.
A discussion of how controls affect emission estimates when emissions are calculated using
emission factors is in Section 4. This section also provides examples of calculations for
controlled emissions.
3.3.3 SPATIAL ALLOCATION
Spatial allocation may be needed during the preparation of an inventory to allocate:
(1) state or regional activity to a county level, and (2) county-level emission estimates to a
modeling grid cell. In each case, a surrogate for activity should be found that can
approximate spatial variation for this category.
The preferred method, per capita emission factors, uses activity which is available at the
county level. The alternative method, a survey, can also use population as a scaling method.
However, it should be assumed that usage is constant over the inventory area for consumer
and commercial products. If estimated emissions from consumer and commercial products
El IP Volume III 5.3-3
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CHAPTER 5 - SOLVENT USE 8/02/96
are to be allocated on a refined level within the study area, residential population,
households, or number of commercial establishments should be used with the allocation
depending on the category.
3.3.4 TEMPORAL RESOLUTION
Seasonal Apportioning
For the most part, consumer and commercial product use is not influenced by the seasons.
An exception is pesticides, which are discussed in this chapter as well as in Chapter 9 of this
volume. In colder climates and seasons, windshield washer fluids typically have higher VOC
content, which would mean that the emission factor for windshield washer fluids for that
time period will be higher. There should not be a significant difference in the use between
different seasons.
Daily Resolution
The use of consumer and commercial products is generally assumed to occur 7 days a week
throughout the year. Thus, the annual emissions estimate is divided by 365 in order to
calculate a daily emission estimate.
3.3.5 PROJECTING EMISSIONS
Projected emission estimates may need to be calculated differently in the three following
cases:
Case 1: No controls and no change in the emission factor;
Case 2: Controls are reflected in the emission factor; and
Case 3: Controls are expressed as a control efficiency factor and the emission
factor stays the same.
5.3-4 Volume III
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8/02/96
CHAPTER 5 - SOLVENT USE
Each case uses a different projection equation (EPA, 1993). If there are no controls and no
changes in the emission factor, projected emissions are calculated using the following
equation:
EMISDV = ORATEnv * EMF * GF
r I D I
(5.3-1)
where:
EMISpY
ORATEBY
EMF
GF
Projection year emissions
Base year activity rate
Emission factor
Growth factor
For Case 2, where controls are reflected in the emission factor, the equation would be:
EMISpY = ORATEBY * EMFPY *
200 - RPp
100
* GF
(5.3-2)
where:
EMF
RP
PY
PY
Projection year emission factor
Projection year rule penetration (%
When controls are expressed as an emission limit or a percent reduction, reductions are
calculated using a control efficiency factor, as in Case 3. See Section 4 of this chapter for
an example of how to develop and apply a control efficiency factor in a base year emission
estimation equation. Projected emission estimates for Case 3 are calculated using the
following equation:
where:
CE
RE
PY
PY
= ORATEBY * EMF
1-
100
100
100
Projection year control efficiency
Projection year rule effectiveness (%
* GF
(5.3-3)
A discussion about developing growth factors and projecting emission estimates can be found
El IP Volume III 5.3-5
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CHAPTER 5 - SOLVENT USE 8/02/96
in Section 4 of this volume's Chapter 1, Introduction to Area Source Emission Inventory
Development.
5.3-6 Volume III
-------
PREFERRED METHODS FOR
ESTIMATING EMISSIONS
The preferred method for calculating emissions from consumer and commercial products uses
the nationally based per capita emission factors for the product categories of interest. This
section provides an outline for using these emission factors and makes recommendations on
how to make adjustments to the estimated emissions based on applicable regulations.
Because the use of consumer and commercial products is defined as an area source, there is
no need to subtract point source emissions from the total. All of the emissions estimated for
this source are area source emissions. The procedure recommended for estimating emissions
is as follows:
• Identify applicable state and local regulations;
• Create a database or spreadsheet with per capita emission factors for the
source categories of interest (making sure they can be matched to regulated
categories);
• Obtain population data for the base year of interest and allocate it to
geographic areas as needed (including consideration of areas affected by
regulations);
• Multiply per capita emission factors by population to obtain overall emissions
estimates; and
• Adjust estimated emissions for applicable regulations as needed.
An example calculation (5.4-1) is shown on the following page.
Table 5.4-1 and Appendix A present the per capita VOC emission factors recommended for
estimating emissions from consumer and commercial solvents (EPA, 1995). These emission
factors were developed by the EPA in conjunction with product manufacturers and trade
associations. Information on product sales and baseline VOC content were gathered by the
EPA for base year 1990 through an extensive survey of manufacturers and distributors.
Table 5.4-2 presents the per capita HAP emission factors.
El IP Volume III 5.4-1
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CHAPTER 5 - SOLVENT USE 8/02/96
Example 5.4-1
The equation to estimate VOC emissions from personal care products is:
Population * Per Capita Emission Factor = Emissions
If the population of the area is 1 million persons, the VOC emissions from personal
care products are:
1,000,000 persons * 2.32 Ib VOCs/person/yr = 2,320,000 Ib VOC/yr
= 1,160 tons VOCs/yr
The VOC and HAP emission factors developed from the survey results were adjusted for
estimated market coverage of respondents based on a review of the survey data by
manufacturing and trade association members. As discussed in Section 2, some of the VOCs
in products that come in contact with water during use may not be emitted to the air, and
thus should be excluded from an emissions inventory. The percent VOCs emitted (as
opposed to biodegraded in wastewater) was therefore used to further adjust the per capita
emission factors. These adjustments were also developed based on the trade association
members, review of the survey data. The adjustments take into consideration the likelihood
of VOC-containing products entering the wastewater stream at significant levels (because
they are detergents, soaps, shampoos, etc.) and the fate of individual VOC compounds in the
water (likelihood of biodegradation).
4.1 APPLICATION OF CONTROLS
If there are applicable state or local regulations, estimated emissions must be adjusted. The
existing and proposed regulations limit the VOC content of products. The information
presented in Appendix A can be used to calculate the baseline VOC content (by weight) of
the products surveyed. These values can be calculated by dividing the adjusted VOC content
(tons) by the adjusted product sales (tons) shown in Appendix A.
As an example (5.4-2), the average VOC content for finishing hair sprays is 90 percent. The
California Phase I regulation limits the VOC content of hair sprays to 80 percent by weight.
In this example, product usage of the regulated hairspray is assumed to be the same as
product usage of the unregulated hairspray. If information on consumer practices is available
that indicates product usage would change, adjustments would be needed to account for
additional (or lower) VOC reductions. Note that this example assumes that RE and RP are
both 100 percent. Section 3.3.2 discusses some factors that should be considered about these
assumptions.
5.4-2 Volume III
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8/02/96
CHAPTER 5 - SOLVENT USE
TABLE 5.4-1
PER CAPITA CONSUMER AND COMMERCIAL SOLVENT VOC
EMISSION FACTORS^
Product Category
Personal Care Products
Household Products
Automotive Aftermarket Products
Adhesives and Sealants
FIFRA-Regulated Products'1
Coatings and Related Products
Miscellaneous Products
Total for All Consumer and Commercial Products
Per Capita Emission
Factor
(Ib VOC/person)c
2.32
0.79
1.36
0.57
1.78
0.95
0.07
7.84
a Source: Adapted from EPA, 1995.
b Emission factors are based on usage and population data for 1990.
0 Compounds listed as nonreactive by the EPA as of April 1996 have been excluded. Significant changes to earlier
definitions are the removal of acetone from the list of reactive VOCs.
d Care should be taken to avoid double counting in applying this VOC emission factor if the alternative estimation
method given in Chapter 9 of this volume for consumer and commercial pesticide use is used.
EIIP Volume III
5.4-3
-------
TABLE 5.4-2
o
PER CAPITA CONSUMER AND COMMERCIAL SOLVENT HAP EMISSION FACTORS (LB/YR/PERSON)"
Pollutant
Acetamide
Acetophenone
Acrylic acid
Benzene
Carbon tetrachloride
Chlorobenzene
Chloroform
Dibenzofurans
1 ,4-Dichlorobenzene
1 ,2-Dichloroethane
1,3-Dichloropropene
Dimethyl formamide
1,4-Dioxane
Ethyl benzene
Ethylene oxide
Formaldehyde
Personal
Care
Products
1.38E-07
4.62E-06
2.71E-05
Household
Products
4.79E-02
3.52E-08
2.56E-06
6.74E-06
Automotive
Aftermarket
Products
4.72E-06
3.60E-05
2.78E-08
7.51E-05
Adhesives
& Sealants
3.94E-09
8.07E-06
2.29E-07
1.09E-05
1.36E-05
2.51E-05
FIFRA-
Regulated
Products'1
7.16E-02
3.52E-02
1.60E-01
1.30E-03
1.51E-02
3.81E-04
Coatings
& Related
Products
8.53E-06
4.10E-10
1.51E-05
9.55E-04
6.86E-04
8.55E-04
Misc.
7.43E-06
Overall Emission
Factor
(Ib HAP/yr/person)
1.38E-07
8.53E-06
3.94E-09
4.72E-06
4.10E-10
7.16E-02
9.91E-04
8.07E-06
3.52E-02
4.65E-06
1.60E-01
3.49E-05
1.09E-05
2.07E-03
1.51E-02
1.26E-03
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CHAPTER 5 - SOLVENT USE
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E//P Volume III
5.4-5
-------
fj\
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TABLE 5.4-2
(CONTINUED)
Pollutant
Triethylamine
Vinyl acetate
Xylenes
Personal
Care
Products
Household
Products
3.28E-03
Automotive
Aftermarket
Products
1.20E-02
Adhesives
& Sealants
4.94E-08
9.76E-03
FIFRA-
Regulated
Products'1
3.13E-04
1.37E-01
Coatings
& Related
Products
5.26E-04
4.05E-02
Misc. (Not
Covered)
4.31E-04
Overall Emission
Factor
(Ib HAP/yr/person)
8.39E-04
4.94E-08
2.03E-01
a Factors are from the Consumer Products Database (adjusting for content emitted and market coverage). Some HAP emission
factors may not be shown here because they were not considered reportable VOCs. Additional HAPs may be emitted from
consumer and commercial products.
b Before using these factors, refer to the discussion in Section 2 of this chapter.
O
Ul
i
03
O
§
§
m
"
CD
Co
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8/02/96 CHAPTER 5 - SOLVENT USE
Example 5.4-2
To estimate VOC emissions from finishing hair sprays affected by the California
Phase I regulation, CE must first be calculated.
Uncontrolled Emissions * [ 1- (CE)*(RE)*(RP)] = Controlled Emissions
CE is calculated as:
(Uncontrolled VOC content - Controlled VOC content)/Uncontrolled VOC = Control
Efficiency
(90 - 80.0)/90 =0.11
The uncontrolled emissions from finishing hair sprays are calculated from the
information in Appendix A using the per capita VOC emission factor of
1.3 Ibs/person.
The controlled emissions from finishing hair sprays in a city with a population of 1
million persons will be:
Uncontrolled Emissions * [ 1- (CE)*(RE)*(RP)] = Controlled Emissions
650 tons VOC * [ 1 - (0.11*1.00*1.00)] = 578.5 tons VOC
4.2 OTHER ADJUSTMENTS
Finally, adjustments may be made to the estimated emissions from consumer and commercial
products based on local survey data. If a survey is conducted for a product category and the
results are sufficient to provide an indication of local product usage (i.e., delineate types of
products that are not used or sold in the inventory area, provide information on a different
formulation), some products can be excluded from the emissions inventory, or adjustments
can be made to the per capita emission factors.
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5.4-8 Volume III
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
The alternative method for calculating VOC emissions from consumer and commercial
solvent use is to conduct a survey of product usage or sales, and combine the information
obtained with the VOC and HAP content of the products. This section provides an outline
for preparing and using a consumer and commercial products survey if distributors and
retailers or consumers are surveyed, and calculating emissions from the information
collected. As discussed previously, the survey method is not recommended for this source
category unless the agency has reason to believe that local product usage differs greatly from
national average usage, and the agency has adequate resources to survey this diverse and
widespread source category. Please refer to Chapter 1 of this volume; Volume I of this
series, Chapter 5, Inventory Development; and Volume VI of this series, Quality Assurance
Procedures, for more detailed information about using surveys.
5.1 PROCEDURE
The survey procedure is as follows:
• Perform a survey of distributors and retailers or consumers of consumer and
commercial products use in the inventory region;
• Obtain data on the amounts of products sold or used in the inventory region;
and
• Estimate the total amount of VOCs (or HAPs) emitted in the inventory region
from consumer and commercial products.
5.2 DATA ELEMENTS
A survey should request the following information:
• Product type;
• Product amount distributed by type (weight or volume); and
• Product density, if manufacturers and distributors are surveyed, and product
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CHAPTER 5 - SOLVENT USE 8/02/96
amount is recorded in volume units.
The Consumer and Commercial Products Survey sent out by the EPA to manufacturers and
distributors is shown in Appendix B (EPA, 1995). Instructions for the survey form are
provided on the survey cover page. Respondents must estimate the annual amount of
products sold. This information is then combined with the product density to yield the
pounds of product used in a given year. A smaller survey of local usage would use a
simplified version of this questionnaire, limiting questions to a smaller group of products and
to just usage amounts. The survey package should include a cover letter explaining the
program, the survey form, a list of definitions, a map of the study area, and a postage-paid
return envelope.
Returned information from the questionnaires should be compiled and stored using
procedures defined in the inventory quality assurance plan. Because the survey
recommended as an alternative method for this source category collects information about
local usage, emissions are calculated by multiplying the usage amounts by the product VOC
content (calculated by dividing the adjusted VOC content by the adjusted product sales) and
VOC emitted percents developed from the EPA 1995 report and listed in Appendix A.
Product usage amounts collected in volume units will need to be converted to weight units
using the product density information collected from manufacturers or distributors.
To estimate HAP emissions from consumer and commercial products using the local usage
data, use the per capita emission factors in Table 5.4-2 and the VOC per capita emission
factors in Table 5.4-1 to develop weight percent factors for the HAP of interest. The weight
percent factors are developed based on a ratio of individual HAPs to product VOC content.
This method assumes that only product usage has changed (based on the survey results), not
the HAP/VOC content ratio. An example calculation is shown below.
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8/02/96 CHAPTER 5 - SOLVENT USE
Example 5.5-1
The estimate glycol ethers emitted from personal care products (all types), the
weight percent of glycol ethers emitted per pound of VOC is calculated by:
glycol ethers
weight percent = [(0.0000152 lb/yr/person)/(2.32 lb/yr/person)] * 100
= 0.0006551
The weight percent factor is applied to the local VOC emission estimate:
glycol ethers
emissions = (0.0006551/100) * VOC emissions
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5.5-4 Volume III
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QUALITY ASSURANCE/QUALITY
CONTROL (QA/QC)
When using the preferred method, data handling for all activity and emission factor data
collected should be planned and documented in the Quality Assurance Plan. When using the
alternative survey method, the survey planning, sample design, and data handling should be
planned and documented in the Quality Assurance Plan. Refer to the discussion of survey
planning and survey QA/QC in Chapter 1 of this volume, and the QA volume (VI) of the
EIIP series.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The role of emission estimate quality indicators in the inventory planning and development
process is discussed in the QA volume of the EIIP series. This volume also provides
information about the Data Attribute Rating System (BARS).
The preferred method gives high-quality estimates with relatively little effort. The level of
effort required to calculate VOC emissions from consumer and commercial solvent use can
range from 8 to 40 hours, depending on the level of detail needed within each product
category, and whether or not there are applicable regulations that must be considered. It is
impossible to estimate the resources needed if a survey is undertaken for all or some of the
product categories to evaluate local use patterns. In fact, it is not recommended that a
survey be undertaken for this source category unless the agency has reason to believe
adjustments in the activity data (and product formulations if distributors and retailers are
surveyed) are justified.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 5.6-1 and 5.6-2. All scores
assume that satisfactory QA/QC measures are performed and no significant deviations from
good inventory practice have been made. If these assumptions are not met, new DARS
scores should be developed according to the guidance provided in the QA volume.
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CHAPTER 5 - SOLVENT USE
8/02/96
TABLE 5.6-1
PREFERRED METHOD DARS SCORES: NATIONAL PER CAPITA EMISSION FACTORS
WITH ADJUSTMENTS FOR REGULATIONS
Attribute
Measurement
Source specificity
Spatial
Temporal3
Composite scores
Scores
Emission Factor
3
9
6
9
0.675
Activity Factor
4
3
9
10
0.65
Emissions
0.12
0.27
0.54
0.90
0.457
Temporal scores will go down for the factors as time increases (i.e., the more time elapsed from survey date).
TABLE 5.6-2
ALTERNATIVE METHOD DARS SCORES: LOCAL SURVEY OF
DISTRIBUTORS/RETAILERS
Attribute
Measurement
Source specificity
Spatial
Temporal15
Composite scores
Scores"
Emission Factor
3
10
10
10
0.825
Activity Factor
6
7
10
10
0.825
Emissions
0.18
0.70
1.0
1.0
0.72
a Assumes that the survey is well designed and carried out. Flaws or limitations in the survey coverage will
lower the scores.
b Assumes this survey is for year of inventory.
5.6-2
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8/02/96 CHAPTER 5 - SOLVENT USE
6.1.2 SOURCES OF UNCERTAINTY
The statistics needed to quantify the uncertainty of the preferred method are incomplete. The
variability of consumer and commercial product use is not well
defined. Per capita usage may be lower or higher than the national average in different parts
of the country and in different seasons.The product formulations are also variable. The VOC
and HAP contents are national averages adjusted only for estimated market coverage of the
manufacturer/distributor survey respondents and do not reflect local variations in product
formulation. The uncertainty of the emission estimates can be quantified if the alternative
method is used, as discussed in the QA volume.
The greatest source of variability pertinent to emissions is the regional variation in product
usage. Climate, lifestyle, and behavioral factors will affect the amounts and types of
products used in a locality. Furthermore, demographics (i.e., proportion of population in
different age groups) need to be considered. Preteen children are not likely to use many of
these products. Other age, gender, and ethnic differences will affect the type and amount of
product used. Because the emission factor is based on the national population, local
variations from national demographics patterns contribute to emission estimate uncertainty.
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5.6-4 Volume III
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DATA CODING PROCEDURES
This section describes the codes available to characterize consumer and commercial solvent
emission estimates. Consistent categorization and coding will result in greater uniformity
between inventories. Inventory planning for data collection calculations and inventory
presentation should take the data formats presented in this section into account. Available
codes and process definitions may impose constraints or requirements on the preparation of
emission estimates for this category.
7.1 PROCESS CODES
The source category process codes for consumer and commercial products are shown in
Table 5.7-1. These codes are derived from the EPA's Aerometric Information Retrieval
System (AIRS) Area and Mobile Source (AMS) category codes (EPA, 1994c). There are no
appropriate control codes for use with AMS for this source category.
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CHAPTER 5 - SOLVENT USE
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TABLE 5.7-1
AIRS AMS CODES FOR CONSUMER AND COMMERCIAL PRODUCTS
Process Description
AMS Code
Miscellaneous Nonindustrial: All Classes
All processes
Total: All solvent types
Acetone
Butyl acetate
Butyl alcohols: All types
n-Butyl alcohol
Isobutyl alcohol
Ethanol
Ethyl acetate
Ethylbenzene
Isopropanol
Methanol
Methyl isobutyl ketone
Monochl orob enzene
o-Dichlorobenzene
p-Dichlorobenzene
Perchl oroethy 1 ene
Propylene glycol
Special naphthas
Tri chl oroethy 1 ene
Solvents: NEC3
24-60-000
24-60-000-000
24-60-000-030
24-60-000-055
24-60-000-060
24-60-000-065
24-60-000-070
24-60-000-165
24-60-000-170
24-60-000-185
24-60-000-250
24-60-000-260
24-60-000-285
24-60-000-300
24-60-000-330
24-60-000-340
24-60-000-345
24-60-000-350
24-60-000-370
24-60-000-385
24-60-000-999
5.7-2
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CHAPTER 5 - SOLVENT USE
TABLE 5.7-1
(CONTINUED)
Process Description
AMS Code
Miscellaneous Nonindustrial: Commercial
All Processes
Total: All solvent types
Adhesives and Sealants
Total: All solvent types
Pesticide Application: All Processes
Total: All solvent types
Solvents: NEC
24-61-000
24-61-000-000
24-61-200
24-61-200-000
24-61-800
24-61-800-000
24-61-800-999
Miscellaneous Nonindustrial: Consumer
All Products/Processes
Total: All solvent types
Acetone
Butyl acetate
Butyl alcohols: All types
n-Butyl alcohol
Isobutyl alcohol
Ethanol
Ethyl acetate
Ethylbenzene
Isopropanol
Methanol
Methyl isobutyl ketone
24-65-000
24-65-000-000
24-65-000-030
24-65-000-055
24-65-000-060
24-65-000-065
24-65-000-070
24-65-000-165
24-65-000-170
24-65-000-185
24-65-000-250
24-65-000-260
24-65-000-285
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5.7-3
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CHAPTER 5 - SOLVENT USE
8/02/96
TABLE 5.7-1
(CONTINUED)
Process Description
Monochl orob enzene
o-Dichlorobenzene
p-Dichlorobenzene
Perchl oroethy 1 ene
Propylene glycol
Special naphthas
Tri chl oroethy 1 ene
Solvents: NEC
Personal Care Products
Total: All solvent types
Household Products
Total: All solvent types
Automotive Aftermarket Products
Total: All solvent types
Adhesives and Sealants
Total: All solvent types
Pesticide Application
Total: All solvent types
Miscellaneous Products: NEC
Total: All solvent types
AMS Code
24-65-000-300
24-65-000-330
24-65-000-340
24-65-000-345
24-65-000-350
24-65-000-370
24-65-000-385
24-65-000-999
24-65-100
24-65-100-000
24-65-200
24-65-200-000
24-65-400
24-65-400-000
24-65-600
24-65-600-000
24-65-800
24-65-800-000
24-65-900
24-65-900-000
Source: EPA, 1994c.
5.7-4
Volume III
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8
REFERENCES
Consumer and Commercial Products: Schedule for Regulation. 60 FR 15264,
March 23, 1995.
EPA. 1995. Study of Volatile Organic Compound Emissions from Consumer and
Commercial Products. Report to Congress. U.S. Environmental Protection Agency, Office
of Air Quality Planning and Standards, EPA-453/R-94-066-A. Research Triangle Park, North
Carolina.
EPA. 1994a. Fate of Consumer Product VOC in Landfills. Report to Congress. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-453/R-94-066-C. Research Triangle Park, North Carolina.
EPA. 1994b. Fate of Consumer Product VOC in Wastewater. Report to Congress. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-453/R-94-006-D. Research Triangle Park, North Carolina.
EPA. 1994c. AIRS Database. Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina.
EPA. 1993. Guidance for Growth Factors, Projections and Control Strategies for the
15 Percent Rate-of-Progress Plans. EPA-452/R-93-002. Office of Air Quality Planning
and Standards, Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide
and Precursors of Ozone. Volume I: General Guidance for Stationary Sources.
EPA-450/4-91-016. Office of Air Quality Planning and Standards, Research Triangle Park,
North Carolina.
Frost & Sullivan, Inc. 1990. Industrial Solvents - Winter 1989. New York, New York.
Systems Applications International Corporation (SAIC), 1987. Control Techniques for
Reducing Emissions of Photochemically Reactive Organic Compounds from Consumer and
Commercial Products. U. S. Environmental Protection Agency, Region 2, New York, New
York.
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8/02/96 CHAPTER 5 - SOLVENT USE
APPENDIX A
RESULTS OF THE EPA's
CONSUMER PRODUCT SURVEY
(VOC)
[Adapted from Table 5-1 of EPA, 1995]
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Final 8/02/96 CHAPTER 5 - SOLVENT USE
APPENDIX A
Notes on Results of the Consumer Products Survey
1. Reportable volatile organic compounds (RVOCs) are a subset of VOCs (EPA's definition
of VOC can be found in 57 FR 3941, February 3, 1992). RVOCs are those VOCs that
have a vapor pressure greater than 0.1 mm Hg at 20 °C or which, if the vapor pressure is
unknown, contain 12 or less carbon atoms. Those VOCs that exist as solids at 20°C and
readily sublime or become vapors at the temperature at which they are used are also
RVOCs.
2. Information on product sales reported, and RVOC content were obtained directly from the
survey responses.
3. Estimated market coverage information was obtained from Chemical Specialties
Manufacturers Association (CSMA), Cosmetics, Toiletries, and Fragrance Association
(CTFA), and Soap and Detergent Association (SDA).
4. Adjusted RVOC content was obtained by dividing RVOC content reported by estimated
market coverage.
5. Percent RVOC content emitted is based on information submitted by CSMA, CTFA, and
SDA. This factor accounts for biodegradation or other fates (other than being emitted to
the air) of consumer product RVOCs that enter the wastewater stream.
6. RVOC emitted in U.S. was obtained by multiplying Adjusted RVOC content by percent
RVOC content emitted and reflects actual RVOC emissions to the air.
7. Emissions per person were obtained by dividing RVOC emitted in U.S. by the U.S.
population (284 million).
8. Before using the pesticide data, refer to the discussion in Section 2 of this chapter.
The remainder of this Appendix is a table of emission factors, and is attached to this document
as a spreadsheet, namedEIIPRES. WK1. (Note: Worksheet has been converted to a pdf file. ALI
6/24/97)
EIIP Volume III 5.1-1
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Product Category Description
Estimated Market
RVOC Content Reported Coverage
(tons per year) (percent)
Adjusted Product Sales
(tons)
RVOC Content
Adjusted RVOC Content Emitted
(tons per year) (percent)
RVOC Emitted in U.S.
(tons per year)
Per Capita Emissions
(Ib/yr/person)
PERSONAL CARE PRODUCTS
Hair Care Products
Bleaches and lightners
Brilliantines
Conditioners
Conditioning sprays
Curl activators
Curl revitalizers
Dyes - Permanent
Dyes - Semipermanent
Dyes - Temporary
Finishing hair sprays
Finishing spritzes
Grooming creams
Mousses
Permanent wave treatments
Pomades
Rinses
Setting lotions
Shampoos
Spray shines
Straighteners
Styling gels
Styling sprays
Styling spritzes
Thickeners
Tonics
Other hair care products
All Hair Care Products
Deodorants and Antiperspirants
Underarm deodorants and antiperspirants
Underarm antiperpirants
Foot deodorant sprays
Feminine hygiene deodorants
Other deodorants and antiperspirant products
All Deodorants and Antiperspirants
Fragrance Products
Colognes
Perfumes
Toilet waters
After shave treatments
Body fragrance sprays
Bath oils, beads and capsules
Other fragrance products
All Fragrance Products
Powders
Baby powders
Body powders
101.97
0.18
843.35
12.62
2.33
172.02
1 ,455.34
72.25
739.12
152,229.77
6,115.34
4.17
2,312.69
251 .36
3.78
9.21
237.34
1,895.11
469.51
0.00
603.24
3,637.18
7,101.12
0.06
367.56
48.91
178,685.53
95
95
95
95
95
95
95
95
95
94
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
3,090.13
5.83
130,813.90
1 ,398.02
1 ,220.80
833.59
15,662.70
3,327.25
6,649.97
179,512.87
7,422.48
1 ,408.68
19,471.63
52,933.83
1 ,945.92
975.96
1 ,357.55
291,199.33
917.98
5.48
12,647.41
6,322.15
9,469.20
29.82
1 ,455.58
2,723.76
752,801 .82
107.34
0.19
887.74
13.29
2.46
181.07
1,531.93
76.06
778.02
161,946.56
6,437.20
4.39
2,434.41
264.59
3.98
9.69
249.83
1 ,994.85
494.22
0.00
634.99
3,828.61
7,474.86
0.06
386.90
51.49
189,794.74
10
100
5
100
100
100
10
10
10
100
100
100
100
10
100
5
100
5
100
10
100
100
100
100
100
100
10.73
0.19
44.39
13.29
2.46
181.07
153.19
7.61
77.80
161,946.56
6,437.20
4.39
2,434.41
26.46
3.98
0.48
249.83
99.74
494.22
0.00
634.99
3,828.61
7,474.86
0.06
386.90
51.49
184,564.91
8.66E-05
1 .53E-06
3.58E-04
1 .07E-04
1 .98E-05
1 .46E-03
1 .24E-03
6.13E-05
6.27E-04
1.31E+00
5.19E-02
3.54E-05
1 .96E-02
2.13E-04
3.21 E-05
3.91 E-06
2.01 E-03
8.04E-04
3.99E-03
2.86E-09
5.12E-03
3.09E-02
6.03E-02
5.13E-07
3.12E-03
4.15E-04
1 .49E+00
8,961.29
21,817.84
167.74
32.31
81.91
31,061.10
100
100
95
95
95
24,363.66
37,755.10
184.94
69.72
363.20
62,736.62
8,961.29
21,817.84
176.57
34.01
86.22
31 ,075.94
100
100
100
100
100
8,961.29
21,817.84
176.57
34.01
86.22
31 ,075.94
7.23E-02
1 .76E-01
1 .42E-03
2.74E-04
6.95E-04
2.51 E-01
8,460.98
152.50
807.21
5,988.03
1 ,562.69
156.36
753.20
17,880.98
95
95
95
95
95
95
95
10,755.10
183.02
949.20
11,177.61
1,818.60
10,156.94
3,770.56
38,811.03
8,906.29
160.53
849.70
6,303.19
1 ,644.94
164.59
792.84
18,822.08
100
100
100
100
100
5
100
8,906.29
160.53
849.70
6,303.19
1 ,644.94
8.23
792.84
18,665.72
7.18E-02
1 .29E-03
6.85E-03
5.08E-02
1 .33E-02
6.64E-05
6.39E-03
1.51 E-01
10.15
19.45
95
95
92,141.87
3,598.28
10.69
20.47
100
100
10.69
20.47
8.62E-05
1.65E-04
-------
Foot powders
Other powder products
Nail Care Products
Polishes
Base coats, undercoats
Polish removers
Nail extenders
Cuticle softeners
Manicure preparations
Other nail care products
All Powders
All Nail Care Products
Facial and Body Treatments
Astringents
Creams, scrubs, cleaners
Rouges and blushes
Makeup bases, foundations and fixatives
Lipsticks
Moisturizers
Skin lighteners
Facial masques
Mascara
Eyeliner
Eye shadow
Eye makeup remover
Eyebrow pencil
Hand and body lotions
Skin protectants
Depilatories
Self-tanning preparations
Suntan oils and lotions
Sunscreens
Other facial and body makeup and treatments
All Facial and Body Treatments
Oral Care Products
Mouthwashes
Breath fresheners
Toothpastes, gels and powders
Plaque removal solutions
Fluoride rinses
Dental care products
Other oral care products
All Oral Care Products
Health Use Products (External Only)
Over-the-counter (OTC) drugs (external only)
Prescription Pharmaceuticals (external only)
Other health use products
All Health Use Products (External Only)
2,497.19
847.84
3,374.64
95
95
4,448.12
2,515.23
102,703.50
2,628.63
892.47
3,552.25
100
100
2,628.63
892.47
3,552.25
2.12E-02
7.20E-03
2.86E-02
1 ,448.30
417.25
1,804.10
0.00
0.37
0.19
819.77
4,489.98
95
95
95
95
95
95
95
2,780.68
580.68
8,072.25
11.52
109.91
55.36
1,133.93
12,744.33
1 ,524.53
439.21
1 ,899.05
0.00
0.39
0.20
862.91
4,726.29
100
100
100
100
10
100
100
1 ,524.53
439.21
1 ,899.05
0.00
0.04
0.20
862.91
4,725.94
1 .23E-02
3.54E-03
1 .53E-02
O.OOE+00
3.11E-07
1 .61 E-06
6.96E-03
3.81 E-02
5,442.72
311.29
10.28
128.29
3.00
152.72
17.24
8.77
175.05
11.58
6.55
8.31
0.51
361.31
136.40
6.56
30.42
52.60
132.82
248.79
7,245.20
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
95
15,563.60
24,919.04
1 ,203.92
4,181.73
952.80
14,399.23
268.63
1 ,554.50
954.41
135.51
420.08
509.67
57.52
57,966.63
12,325.90
1 ,566.48
885.02
1,579.12
4,343.37
3,097.84
146,885.00
5,729.18
327.68
10.82
135.04
3.15
160.75
18.14
9.23
184.27
12.19
6.89
8.74
0.53
380.32
143.58
6.91
32.03
55.36
139.81
261 .89
7,626.52
100
10
100
100
100
100
100
100
100
100
100
100
100
100
100
10
100
100
100
100
5,729.18
32.77
10.82
135.04
3.15
160.75
18.14
9.23
184.27
12.19
6.89
8.74
0.53
380.32
143.58
0.69
32.03
55.36
139.81
261 .89
7,325.39
4.62E-02
2.64E-04
8.72E-05
1 .09E-03
2.54E-05
1 .30E-03
1 .46E-04
7.44E-05
1 .49E-03
9.83E-05
5.56E-05
7.05E-05
4.31 E-06
3.07E-03
1.16E-03
5.57E-06
2.58E-04
4.46E-04
1.13E-03
2.11E-03
5.91 E-02
23,932.53
386.42
1,083.21
2,111.43
562.81
33.34
24.91
28,134.66
77
95
95
95
95
95
95
159,846.68
619.34
89,532.10
32,925.46
9,203.84
3,868.67
1 ,084.85
297,080.94
31,081.21
406.76
1,140.23
2,222.55
592.43
35.10
26.22
35,504.50
5
5
5
5
5
5
5
1 ,554.06
20.34
57.01
111.13
29.62
1.75
1.31
1 ,775.22
1 .25E-02
1 .64E-04
4.60E-04
8.96E-04
2.39E-04
1 .42E-05
1 .06E-05
1 .43E-02
3,877.13
438.58
1 ,539.26
5,854.98
95
95
95
43,373.96
2,523.03
10,484.45
56,381.44
4,081.19
461 .67
1 ,620.27
6,163.13
100
100
100
4,081.19
461 .67
1 ,620.27
6,163.13
3.29E-02
3.72E-03
1 .31 E-02
4.97E-02
Miscellaneous Personal Care Products
-------
Hand cleaners and soaps
Rubbing alcohol
Shaving creams, gels, and soaps
Other miscellaneous personal care products
All Miscellaneous Personal Care Products
ALL PERSONAL CARE PRODUCTS
HOUSEHOLD PRODUCTS
13,594.20
23,027.28
1 ,857.50
3,979.46
42,458.44
319,185.49
72
95
97
95
636,887.19
37,084.21
47,990.06
119,394.84
841 ,356.30
2,311,500.98
18,880.83
24,239.24
1,914.95
4,188.91
49,223.93
346,489.38
5
100
5
100
944.04
24,239.24
95.75
4,188.91
29,467.94
287,316.45
7.61 E-03
1 .95E-01
7.72E-04
3.38E-02
2.38E-01
2.32E+00
Hard Surface Cleaners
General purpose cleaners
Glass cleaners
Oven cleaners
Tub, tile, and sink cleaners
Mildew removers
Toilet bowl cleaners
Hard surface rust stain removers
Metal cleansers
Soap scouring pads
Other hard surface cleaners
Laundry Products
Detergents
Soaps
Presoaks
Prewash spot and stain removers
Bleaches
Whiteners/brighteners
Bluing
Fabric softeners
Water softeners and conditioners
Starches, sizings, and fabric finishes
Other laundry products
All Hard Surface Cleaners
All Laundry Products
Fabric and Carpet Care Products
Carpet cleaners
Carpet deodorizers and fresheners
Upholstery cleaners
Spot removers
Fabric stain repellants
Water repellants
Fabric dyes
Antistatic sprays
Dry cleaning fluids
Other fabric, carpet, and upholstery care products
All Fabric and Carpet Care Products
Dishwashing Products
Dish detergents (manual)
Dish detergents (machine)
Rinse aids
Film and spot removers
27,741 .06
14,604.73
1 ,806.96
2,634.83
291 .00
606.46
1.17
1 ,525.42
93.24
6,145.07
55,449.94
90
95
95
95
100
100
100
100
100
100
529,617.81
217,180.86
28,607.45
57,011.15
18,805.17
55,364.27
3,336.53
20,302.87
12,233.37
226,340.20
1,168,799.68
30,823.39
15,373.40
1 ,902.06
2,773.50
291 .00
606.46
1.17
1 ,525.42
93.24
6,145.07
59,534.72
5
100
100
50
100
5
100
100
100
5
1,541.17
15,373.40
1 ,902.06
1 ,386.75
291 .00
30.32
1.17
1 ,525.42
93.24
307.25
22,451.79
1 .24E-02
1 .24E-01
1 .53E-02
1.12E-02
2.35E-03
2.45E-04
9.42E-06
1 .23E-02
7.52E-04
2.48E-03
1.81E-01
41,476.16
1.81
18.67
3,795.64
714.10
15.63
0.16
6,279.65
14.67
4,423.94
1 ,463.84
58,204.28
81
73
73
73
58
73
73
75
73
73
73
2,826,470.93
28,130.75
4,470.05
86,965.05
1 ,395,927.74
22,231.11
220.17
581 ,862.56
54,326.31
127,141.62
31,284.10
5,159,030.39
51,205.14
2.47
25.58
5,199.50
1,231.20
21.41
0.22
8,372.87
20.10
6,060.20
2,005.26
74,143.96
1
1
1
25
1
1
1
1
1
100
1
512.05
0.02
0.26
1 ,299.88
12.31
0.21
0.00
83.73
0.20
6,060.20
20.05
7,988.92
4.13E-03
1 .99E-07
2.06E-06
1 .05E-02
9.93E-05
1 .73E-06
1 .78E-08
6.75E-04
1 .62E-06
4.89E-02
1 .62E-04
6.44E-02
1 ,820.25
245.26
208.27
996.28
1 ,043.52
10.91
0.01
22.24
1 ,629.65
172.15
6,148.55
100
100
100
100
95
50
100
50
100
100
42842.87
21457.70
2064.63
5102.85
5142.87
409.56
33.14
212.60
1689.68
2998.74
81 ,954.64
1 ,820.25
245.26
208.27
996.28
1 ,098.45
21.82
0.01
44.47
1 ,629.65
172.15
6,236.63
50
100
100
100
100
100
5
100
100
100
910.13
245.26
208.27
996.28
1 ,098.45
21.82
0.00
44.47
1 ,629.65
172.15
5,326.49
7.34E-03
1 .98E-03
1 .68E-03
8.03E-03
8.86E-03
1 .76E-04
2.66E-09
3.59E-04
1 .31 E-02
1 .39E-03
4.30E-02
23,198.00
3,377.83
99.98
1.05
78
79
73
73
637,692.42
384,802.25
8,978.14
494.50
29,741 .02
4,275.74
136.96
1.43
1,487.05
85.51
1.37
0.01
1.20E-02
6.90E-04
1.10E-05
1.16E-07
-------
Other dishwashing products
Waxes and Polishes
Furniture waxes and polishes
Floor waxes and polishes
Dusting aids
Other household waxes and polishes
Air Fresheners
Room air fresheners
Toilet deodorant blocks
Other air fresheners
All Dishwashing Products
All Waxes and Polishes
All Air Fresheners
Shoe and Leather Care Products
Leather preservative treatments
Shoe polishes
Other shoe and leather care products
All Shoe and Leather Care Products
Miscellaneous Household Products
Lubricants
Drain openers
Charcoal lighters
Wck lamp fuels
Plant leaf cleaners and waxes
Driveway cleaners
Other miscellaneous household products
All Miscellaneous Household Products
ALL HOUSEHOLD PRODUCTS
AUTOMOTIVE AFTERMARKET PRODUCTS
Detailing Products
Waxes, polishes and finish sealers
Vinyl and leather cleaners
Upholstery fabric cleaners
Tire cleaners
Wheel cleaners
Bug and tar removers
Chrome cleaners and polishes
Rubber and vinyl protectants
Other automotive detailing products
All Detailing Products
Maintenance and Repair Products
Engine degreasers
Carburetor and choke cleaners
Brake cleaners
Brake anti-squeal compounds
Tire sealants and inflators
Belt dressings
13.59
26,690.45
3,856.47
6,275.82
720.58
1,271.03
12,123.90
25,647.83
6,648.37
2,064.23
34,360.44
101.84
43.50
85.58
230.92
1,735.72
385.20
35,653.66
5,962.97
6.24
2.94
5,122.62
48,869.35
242,077.83
4,107.63
157.76
262.89
385.13
145.25
857.68
103.15
1,101.17
1,606.04
8,726.70
6,551.91
10,858.42
3,750.73
14.52
3,293.63
46.09
73
95
95
90
90
95
75
90
100
50
75
50
100
90
90
100
90
90
95
95
95
90
90
95
95
95
90
98
95
95
95
100
100
2,452.49
1,034,419.80
31 ,909.86
163,125.16
4,030.50
21 ,546.06
220,61 1 .58
120,722.48
9,661.94
10,915.68
141,300.10
286.63
486.82
313.47
1 ,086.92
13,000.28
18,277.87
95,932.98
8,573.40
52.57
239.70
23,665.43
159,742.23
7,966,945.34
16,793.88
1 ,224.34
2,849.90
5,653.91
3,003.06
1,397.16
555.86
3,001.27
18,717.36
53,196.74
17,875.50
13,372.35
16,020.42
295.56
10,955.59
336.56
18.62
34,173.77
4,059.44
6,606.13
800.64
1,412.25
12,878.47
26,997.72
8,864.49
2,293.59
38,155.80
101.84
87.00
114.11
302.95
3,471.44
385.20
39,615.18
6,625.52
6.24
3.27
5,691.80
55,798.64
281 ,224.94
4,323.83
166.07
276.73
427.92
161.39
902.82
108.57
1,159.12
1 ,784.49
9,310.94
6,685.62
1 1 ,429.92
3,948.13
15.28
3,293.63
46.09
100
100
100
100
100
50
100
100
100
100
100
1
10
10
100
100
100
100
100
100
100
100
100
100
100
100
25
50
100
100
100
100
0.19
1,574.14
4,059.44
6,606.13
800.64
1,412.25
12,878.47
26,997.72
4,432.25
2,293.59
33,723.56
101.84
87.00
114.11
302.95
3,471.44
3.85
3,961.52
662.55
6.24
3.27
5,691.80
13,800.67
98,046.98
4,323.83
166.07
276.73
427.92
161.39
902.82
108.57
1,159.12
1,784.49
9,310.94
1,671.40
5,714.96
3,948.13
15.28
3,293.63
46.09
1.50E-06
1.27E-02
3.27E-02
5.33E-02
6.46E-03
1.14E-02
1.04E-01
2.18E-01
3.57E-02
1.85E-02
2.72E-01
8.21 E-04
7.02E-04
9.20E-04
2.44E-03
2.80E-02
3.11E-05
3.19E-02
5.34E-03
5.04E-05
2.64E-05
4.59E-02
1.11E-01
7.91 E-01
3.49E-02
1.34E-03
2.23E-03
3.45E-03
1.30E-03
7.28E-03
8.76E-04
9.35E-03
1.44E-02
7.51 E-02
1.35E-02
4.61 E-02
3.18E-02
1.23E-04
2.66E-02
3.72E-04
-------
Engine starting fluids
Lubricants (other than engine oil)
Antifreezes
Brake fluids
Body repair products (other than coatings)
Windshield deicers
Windshield washer fluids
Other automotive maintenance and repair products
All Maintenance and Repair Products
ALL AUTOMOTIVE AFTERMARKET PRODUCTS
ADHESIVES AND SEALANTS
Consumer Adhesives
Household glues and pastes
Arts and crafts adhesives
Carpet and tile adhesives
Wallpaper adhesives
Woodworking glues
Plastic pipe cements and primers
Thread locking compounds
Specialty automotive adhesives
Construction adhesives
Other adhesives
All Consumer Adhesives
Sealants
Spackling compounds
Caulking compounds
Window glazing compounds
Pipe thread sealants
Plumber's putties
Painter's putties
Wood fillers
Insulating and sealing foams
Driveway patching compounds
Cold process roof cements
Other sealants
All Sealants
ALL ADHESIVES AND SEALANTS
4,099.05
17,371.06
2,843.42
2,553.71
312.54
2,030.61
45,476.18
36,736.64
135,938.50
144,665.20
90
100
90
90
90
100
60
90
5,102.64
70,324.77
241,697.15
30,036.85
12,412.39
3,943.82
214,854.52
65,403.43
702,631 .55
755,828.29
4,554.50
17,371.06
3,159.36
2,837.45
347.26
2,030.61
75,793.64
40,818.49
172,331.04
181,641.98
50
100
100
100
100
100
100
100
2,277.25
17,371.06
3,159.36
2,837.45
347.26
2,030.61
75,793.64
40,818.49
159,324.62
168,635.56
1 .84E-02
1 .40E-01
2.55E-02
2.29E-02
2.80E-03
1 .64E-02
6.11E-01
3.29E-01
1 .28E+00
1 .36E+00
276.23
479.60
5,152.04
22.96
570.64
4,114.23
6.36
1 ,662.34
26,048.42
16,958.14
55,290.96
90
90
90
90
90
90
90
90
90
90
13,680.39
3,088.70
80,383.57
2,336.56
24,160.91
6,551.56
2,769.59
57,844.11
154,405.11
113,610.19
458,830.69
306.92
532.89
5,724.49
25.51
634.05
4,571.37
7.06
1 ,847.05
28,942.69
18,842.37
61 ,434.40
100
100
100
100
100
100
100
100
100
100
306.92
532.89
5,724.49
25.51
634.05
4,571.37
7.06
1 ,847.05
28,942.69
18,842.37
61 ,434.40
2.48E-03
4.30E-03
4.62E-02
2.06E-04
5.11E-03
3.69E-02
5.70E-05
1 .49E-02
2.33E-01
1 .52E-01
4.95E-01
76.15
3,119.17
446.62
16.34
0.00
0.03
356.11
8.03
173.47
1 ,086.57
2,825.91
8,108.40
63,399.36
90
90
90
90
90
90
90
90
90
90
90
22,834.94
84,098.71
18,082.99
1,375.18
492.09
1.98
2,661.23
5,751.61
3,453.59
4,036.37
57,176.98
199,965.67
658,796.36
84.61
3,465.74
496.24
18.16
0.00
0.03
395.67
8.93
192.75
1 ,207.30
3,139.90
9,009.33
70,443.73
100
100
100
100
100
100
100
100
100
100
100
84.61
3,465.74
496.24
18.16
0.00
0.03
395.67
8.93
192.75
1 ,207.30
3,139.90
9,009.33
70,443.73
6.82E-04
2.79E-02
4.00E-03
1 .46E-04
O.OOE+00
2.39E-07
3.19E-03
7.20E-05
1 .55E-03
9.74E-03
2.53E-02
7.27E-02
5.68E-01
FIFRA-REGULATED PRODUCTS
Insecticides
Lawn and garden insecticides
Space insecticides and room foggers
Flying insect sprays
Residual insecticides
Hornet and wasp sprays
Flea and tick soaps, sprays, and dips
Other insecticides
All Insecticides
6,627.42
4,120.99
5,908.45
16,417.44
1,319.84
3,070.47
16,127.67
53,592.29
75
95
95
95
95
95
90
77,260.81
24,508.89
16,758.28
46,263.01
4,615.46
1 1 ,900.53
104,977.41
286,284.39
8,836.56
4,337.89
6,219.42
17,281.52
1,389.31
3,232.07
17,919.64
59,216.41
100
100
100
100
100
100
100
8,836.56
4,337.89
6,219.42
17,281.52
1,389.31
3,232.07
17,919.64
59,216.41
7.13E-02
3.50E-02
5.02E-02
1 .39E-01
1.12E-02
2.61 E-02
1 .45E-01
4.78E-01
Fungicides and Nematicides
-------
Lawn and garden treatments
Wood preservatives
Mold and mildew retardants
Other fungicides and nematicides
All Fungicides and Nematicides
Herbicides
Aquatic herbicides
Swimming pool algicides
Terrestrial herbicides, defoliants, desiccants
Other herbicides
All Herbicides
Antimicrobial Agents
Sanitizers
Disinfectants
Sterilants
Other antimicrobial agents
All Antimicrobial Agents
Other FIFRA-Regulated Products
Insect repellants
Domestic cat and dog repellants
Rodent poisons and baits
Other miscellaneous FIFRA-controlled products
All Other FIFRA-Regulated Products
ALL FIFRA-REGULATED PRODUCTS
COATINGS AND RELATED PRODUCTS (Except Architectural and
Aerosol Spray Paints
Nonflat enamels
Flat enamels
Nonflat lacquers
Flat lacquers
Metallic pigmented coatings
Clear coatings
Ground/traffic marking coatings
Exact match automotive paints
Vinyl/fabric coatings
Glass coatings
Automotive sanding primers
Rust-inhibitive primers
Spatter finishes
Wood stains
Engine enamels
High temperature coatings
Other aerosol spray paints and coatings
All Aerosol Spray Paints
Coating-Related Products
Paint thinners
Paint removers
Brush cleaners and reconditioners
221 .24
15,562.75
22.97
23,538.86
39,345.83
2.44
336.38
43,195.79
20,195.67
63,730.28
1 ,757.65
29,094.86
2,494.15
353.44
33,700.10
7,951.05
169.30
12.42
29,677.70
37,810.47
228,178.97
Industrial Maintenance
27,520.66
5,884.67
5,172.12
999.29
4,163.64
2,650.33
3,153.50
905.52
144.26
13.30
1 ,703.57
2,865.97
525.52
221.34
2,046.38
1 ,475.44
3,181.10
62,626.62
14,061.00
4,499.78
331 .73
90
100
100
90
90
90
100
100
100
99
90
100
99
100
100
100
Coatings)
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
90
90
90
221 .24
15,562.75
22.97
23,538.86
39,345.83
90
100
100
90
4,259.13
93,048.64
439.81
71 ,774.82
169,522.40
245.83
15,562.75
22.97
26,154.29
41 ,985.84
100
100
100
100
245.83
15,562.75
22.97
26,154.29
41 ,985.84
1 .98E-03
1 .26E-01
1 .85E-04
2.11E-01
3.39E-01
2.44
336.38
43,195.79
20,195.67
63,730.28
90
90
100
100
15,348.99
10,390.77
328,635.53
86,289.05
440,664.34
2.71
373.76
43,195.79
20,195.67
63,767.92
5
5
100
100
0.14
18.69
43,195.79
20,195.67
63,410.28
1 .09E-06
1 .51 E-04
3.48E-01
1 .63E-01
5.11E-01
1 ,757.65
29,094.86
2,494.15
353.44
33,700.10
100
99
90
100
65,584.93
367,780.51
15,108.13
8,875.93
457,349.50
1 ,757.65
29,388.75
2,771.27
353.44
34,271.11
50
50
75
75
878.83
14,694.37
2,078.46
265.08
17,916.74
7.09E-03
1.19E-01
1 .68E-02
2.14E-03
1 .44E-01
7,951.05
169.30
12.42
29,677.70
37,810.47
228,178.97
99
100
100
100
10,286.23
1,323.19
3,148.36
43,053.89
57,811.67
1,411,632.30
8,031 .36
169.30
12.42
29,677.70
37,890.79
237,132.07
100
100
100
100
8,031.36
169.30
12.42
29,677.70
37,890.79
220,420.05
6.48E-02
1 .37E-03
1 .OOE-04
2.39E-01
3.06E-01
1 .78E+00
27,520.66
5,884.67
5,172.12
999.29
4,163.64
2,650.33
3,153.50
905.52
144.26
13.30
1 ,703.57
2,865.97
525.52
221.34
2,046.38
1 ,475.44
3,181.10
62,626.62
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
54,693.77
15,432.01
9,918.92
2,091.84
6,039.44
4,250.81
5,348.38
1 ,955.83
255.07
680.53
3,586.64
5,074.98
1,013.80
1 ,659.26
3,618.87
2,273.24
13,446.85
131,340.24
27,520.66
5,884.67
5,172.12
999.29
4,163.64
2,650.33
3,153.50
905.52
144.26
13.30
1 ,703.57
2,865.97
525.52
221 .34
2,046.38
1 ,475.44
3,181.10
62,626.62
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
27,520.66
5,884.67
5,172.12
999.29
4,163.64
2,650.33
3,153.50
905.52
144.26
13.30
1 ,703.57
2,865.97
525.52
221 .34
2,046.38
1 ,475.44
3,181.10
62,626.62
2.22E-01
4.75E-02
4.17E-02
8.06E-03
3.36E-02
2.14E-02
2.54E-02
7.30E-03
1.16E-03
1 .07E-04
1 .37E-02
2.31 E-02
4.24E-03
1 .79E-03
1 .65E-02
1.19E-02
2.57E-02
5.05E-01
15,659.00
15,928.21
482.29
15,659.00
4,999.76
368.59
100
100
100
15,623.00
4,999.76
368.59
1.26E-01
4.03E-02
2.97E-03
-------
Solvents 28,407.76 90
Other coatings related products 3,081.06 90
All Coating-Related Products 50,381.34
ALL COATINGS AND RELATED PRODUCTS 113,007.96
MISCELLANEOUS PRODUCTS (Not Otherwise Covered)
Arts and Crafts Supplies
Artists paints, pigments and thinners 577.28 90
Fixative sprays 29.74 90
Specialty cleaning products 642.84 90
Ceramic finishing products 19.48 90
Other arts and crafts supplies 501.55 90
All Arts and Crafts Supplies 1,770.89
Animal drugs (external only) 176.51 100
Livestock and pet grooming products 126.30 100
Cat litters 262.50 60
Other non-pesticidal veterinary and pet products 72.05 100
All Non-Pesticidal Veterinary and Pet Products 637.36
Pressurized Food Products
Pan sprays 2,583.89 95
Whipped dessert toppings 107.85 90
Other pressurized food products 0.04 90
All Pressurized Food Products 2,691.77
Office Supplies
Pens 16.58 25
Ink 1.93 25
Permanent markers 14.21 25
Dry erasable markers 0.01 25
Highlighters 2.48 25
Correction fluids 0.01 25
Inked ribbons (for typewriters, printers, etc.) 0.00 25
Other office supplies 702.18 25
All Office Supplies 737.39
ALL MISCELLANEOUS PRODUCTS 5,837.41
All Surveyed Categories 1,116,352.23
46,338.53
24,563.35
102,971.38
234,311.62
1,129.61
158.68
1,313.02
436.37
2,454.20
5,491.88
15,398.93
1 ,620.76
319,601.89
5,809.78
342,431 .36
9,902.98
7,596.50
1 57.76
17,657.24
23,725.04
128.78
2,412.22
305.76
1,910.13
0.03
1 ,226.75
5,703.84
35,412.55
400,993.03
13,740,007.92
31,564.18
3,423.40
56,014.94
118,641.55
641 .42
33.05
714.27
21.64
557.27
1 ,967.65
176.51
126.30
437.50
72.05
812.36
2,719.88
119.83
0.04
2,839.75
66.32
7.73
56.84
0.04
9.90
0.03
0.00
2,808.72
2,949.58
8,569.34
1,244,143.00
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
641.42
33.05
714.27
21.64
557.27
1,967.65
176.51
126.30
437.50
72.05
812.36
2,719.88
119.83
0.04
2,839.75
66.32
7.73
56.84
0.04
9.90
0.03
0.00
2,808.72
2,949.58
8,569.34
972,037.67
5.17E-03
2.67E-04
5.76E-03
1.75E-04
4.49E-03
1.59E-02
1.42E-03
1.02E-03
3.53E-03
5.81 E-04
6.55E-03
2.19E-02
9.66E-04
3.29E-07
2.29E-02
5.35E-04
6.23E-05
4.58E-04
3.04E-07
7.98E-05
2.42E-07
O.OOE+00
2.27E-02
2.38E-02
6.91 E-02
7.84E+00
-------
8/02/96 CHAPTER 5 - SOLVENT USE
APPENDIX B
EPA CONSUMER/COMMERCIAL PRODUCTS SURVEY
El IP Volume III 5.A-1
-------
CHAPTER 5 - SOLVENT USE 8/02/96
THIS PAGE IS INTENTIONALLY LEFT BLANK.
Volume III
-------
U.S. ENVIRONMENTAL PROTECTION AGENCY
CONSUMER AND COMMERCIAL PRODUCTS SURVEY
EPA CONSUMER/COMMERCIAL PRODUCTS SURVEY
P.O. Box 14847
RESEARCH TRIANGLE PARK, NC 27709-4847
(919) 493-6263
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GENERAL INSTRUCTIONS FOR THE CONSUMER AND COMMERCIAL
PRODUCTS VOC SURVEY FORM
THE CONSUMER AND COMMERCIAL PRODUCTS VOC SURVEY FORM
(SURVEY FORM) is COMPOSED OF TWO SHEETS; A COMPANY SHEET AND A TWO-
PAGE PRODUCT SHEET. EACH COMPANY RECEIVING THIS FORM NEEDS TO
COMPLETE AND RETURN A COMPANY SHEET. THE PRODUCT SHEET (OR THE
COMPUTER DATABASE EQUIVALENT) NEEDS TO BE COMPLETED BY ALL COMPANIES
THAT PRODUCE OR MARKET A PRODUCT LISTED IN ATTACHMENT A AND THAT ARE
NOT EXEMPT, AS DESCRIBED BELOW. THE FOLLOWING STEPS SHOULD BE
FOLLOWED BEFORE COMPLETING EITHER THE COMPANY SHEET OR PRODUCT
SHEET:
1) DETERMINE IF ANY OF THE PRODUCT CATEGORIES LISTED IN
ATTACHMENT A INCLUDE PRODUCTS DISTRIBUTED OR SOLD BY THE
COMPANY.
2) DETERMINE IF ANY OF THE PRODUCTS IDENTIFIED IN ITEM 1 ABOVE
ARE SOLD UNDER THE COMPANY'S LABEL (SEE EXEMPTIONS FROM
SUBMITTING PRODUCT SHEETS BELOW).
3) GATHER FORMULATION DATA (LIST OF INGREDIENTS), DISTRIBUTION
DATA, 1990 SALES DATA, AND OTHER INFORMATION REQUIRED FOR
COMPLETING THE PRODUCT SHEET FOR EACH PRODUCT MEETING THE
ABOVE REQUIREMENTS. TREAT EACH PRODUCT FORM (AEROSOL,
LIQUID, ETC.) AS A SEPARATE PRODUCT.
GROUPING OF PRODUCTS. PRODUCTS MAY BE GROUPED AND
REPORTED ON ONE PRODUCT SHEET IF ALL OF THE FOLLOWING
CONDITIONS ARE MET!
A) ALL PRODUCTS IN THE GROUP ARE IN THE SAME
PRODUCT CATEGORY (I.E., HAVE THE SAME PRODUCT
-------
CATEGORY CODE IN ITEM 2 ON THE PRODUCT SHEET).
B) ALL PRODUCTS HAVE THE SAME PRODUCT FORM (ITEM 3
ON THE PRODUCT SHEET).
c) EACH PRODUCT IN THE GROUP HAS A TOTAL
REPORTABLE VOLATILE ORGANIC COMPOUND (RVOC)
CONTENT THAT DOES NOT DIFFER BY MORE THAN 5%
FROM ANY OTHER PRODUCTS IN THE GROUP. SEE
ATTACHMENT B FOR A DESCRIPTION OF RVOC AND THE
INSTRUCTIONS FOR COMPLETING PRODUCT SHEETS,
ITEM 9 ON PAGE 11 FOR FURTHER CLARIFICATION.
IF PRODUCTS ARE BEING GROUPED, THE NET PRODUCT WEIGHT SOLD
IN 1990 (ITEM 8) SHOULD BE A SUM OF THE TOTAL WEIGHT FOR ALL
PRODUCTS IN THE GROUP. THE TOTAL RVOC (ITEM 9) AND ENTRIES
FOR INDIVIDUAL RVOC'S (ITEM 11 A) SHOULD BE BASED ON AVERAGES
OF ALL PRODUCTS INCLUDED IN THE GROUP.
4) DETERMINE WHICH INGREDIENTS FIT THE DESCRIPTION OF AN RVOC
AS OUTLINED IN ATTACHMENT B.
5) FILL OUT THE COMPANY SHEET APPROPRIATELY, USING THE
INSTRUCTIONS PROVIDED.
6) FILL OUT THE PRODUCT SHEETS USING EITHER OPTION A OR B.
A) AN OPTION FOR THE TRANSFER OF INFORMATION BY
ELECTRONIC MEDIA (COMPUTER DISKS) IS AVAILABLE FOR
PRODUCT SHEETS, AND is HIGHLY ENCOURAGED. THIS is A
MENU-DRIVEN, PC-BASED PROGRAM THAT WILL OPERATE
INDEPENDENTLY. HELP SCREENS EXPLAINING EACH ITEM IN THE
COMPUTERIZED SURVEY FORM ARE AVAILABLE WITH ONE
KEYSTROKE. REQUIREMENTS TO RUN THE PROGRAM INCLUDE! A
-------
FLOPPY DISK DRIVE (5.25 OR 3.5 INCH, DOUBLE SIDED, DOUBLE
DENSITY); 640 KILOBYTES OR MORE OF RAM; AND DOS 3.0 OR
HIGHER. A COPY OF THE PROGRAM FILES ARE PROVIDED ON
THE ENCLOSED 5.25 INCH DISKETTE. ARRANGEMENTS CAN BE
MADE TO ACQUIRE THE PROGRAM ON A 3.5 INCH DISKETTE BY
CALLING (919) 493-6263. IF YOU HAVE QUESTIONS REGARDING
THE PROGRAM, PLEASE CALL (919) 493-6263.
B) IF YOU PREFER TO SEND HARD COPY INFORMATION FOR
PRODUCT SHEETS, PLEASE FOLLOW THE INSTRUCTIONS
PROVIDED. BE SURE TO COPY THE BLANK FORM (2 PAGES) AND
COMPLETE A SEPARATE COPY FOR EACH PRODUCT OR GROUP
OF PRODUCTS.
EXEMPTIONS FROM SUBMITTING PRODUCT SHEETS
1) IF A COMPANY PRODUCES A PRODUCT THAT DOES NOT FALL INTO ONE
OF THE CATEGORIES LISTED IN ATTACHMENT A, THEY ARE EXEMPT
FROM SUBMITTING A PRODUCT SHEET FOR THAT PRODUCT. IF THE
PRODUCT FALLS WITHIN ONE OF THE CATEGORIES ON THE LIST IN
ATTACHMENT A, A PRODUCT SHEET MUST BE SUBMITTED FOR THAT
PRODUCT REGARDLESS OF RVOC CONTENT.
2) ONLY THOSE COMPANIES LISTED ON THE PRODUCT LABEL ARE
REQUIRED TO SUBMIT PRODUCT SHEETS. IF MORE THAN ONE
COMPANY IS IDENTIFIED ON THE PRODUCT LABEL, THE COMPANY THAT
THE PRODUCT WAS MANUFACTURED FOR OR DISTRIBUTED BY IS
REQUIRED TO SUBMIT A PRODUCT SHEET.
3) ALL COMPANIES NOT REQUIRED TO SUBMIT PRODUCT SHEETS ARE
STILL REQUIRED TO COMPLETE AND SUBMIT A COMPANY SHEET.
-------
INSTRUCTIONS FOR USING THE COMPUTERIZED SURVEY FORM
THE COMPUTERIZED SURVEY FORM IS DESIGNED TO WORK ON IBM-COMPATIBLE PERSONAL COMPUTERS USING DOS
VERSION 3.0 OR HIGHER. VERSIONS FOR OTHER OPERATING PLATFORMS (MACINTOSH, VAX, ETC.) ARE NOT AVAILABLE. THE
COMPUTERIZED FORM CONSISTS OF THREE DATABASE FILES (PRODUCT.DBF, RVOC.DBF AND ALT.DBF) AND AN EXECUTABLE
FILE (SURVEY.EXE) DESIGNED TO REQUEST INFORMATION IN A FORMAT THAT RESEMBLES THE HARD COPY FORM. SUPPORT
DATABASE FILES FOR PROVIDING CATEGORY CODE CHOICES (CATCODES.DBF) AND HELP SCREENS (SURVHELP.DBF) ARE ALSO
PROVIDED. HELP SCREENS ARE AVAILABLE BY PRESSING THE KEY IN MOST INSTANCES. IF A "HELP" SCREEN IS NOT
AVAILABLE, INSTRUCTIONS PROVIDED FOR THE HARD-COPY SURVEY FORM ALSO APPLY TO THE COMPUTERIZED FORM AND SHOULD
HELP TO PROVIDE GUIDANCE.
IT IS HIGHLY RECOMMENDED THAT THE PROGRAM AND DATABASE FILES BE COPIED TO A HARD-DRIVE IN A SEPARATE
SUBDIRECTORY. THE INSTALL BATCH FILE ON THE ENCLOSED DISK WILL DO THIS JOB FOR YOU. FOLLOW THE INSTRUCTIONS GIVEN
BELOW FOR INSTALLING SOFTWARE ON A HARD DRIVE. IF YOU PLAN ON ENTERING DATA USING A FLOPPY DRIVE, PLEASE COPY ALL
FILES ON THE DISK PROVIDED TO ANOTHER DISK (PREFERABLY HIGH-DENSITY, 1.2 OR 1.44 MEGABYTES) AND KEEP THE ORIGINAL
DISK SEPARATE.
THE SOFTWARE WAS DESIGNED TO ALLOW SURVEY RESPONDENTS TO ENTER THE SURVEY INFORMATION INTO APPROPRIATE
DATABASE FORMATS FROM A KEYBOARD. IF MOST OF THE INFORMATION BEING REQUESTED IS ALREADY IN A DATABASE FORMAT, IT
MAY BE ADVANTAGEOUS TO APPEND THAT INFORMATION INTO THE SURVEY DATABASES BEFORE PERFORMING ANY KEYBOARD ENTRY.
IF TRANSFER OF INFORMATION IN THIS MANNER IS POSSIBLE FOR YOUR ORGANIZATION, PLEASE CALL (919) 493-6263 AND REQUEST
A COPY OF THE DATABASE STRUCTURES AND FIELD DEFINITIONS. ANY QUESTIONS REGARDING THIS PROCEDURE CAN ALSO BE
ADDRESSED BY CALLING THE NUMBER LISTED ABOVE.
ALTHOUGH THE COMPUTERIZED SURVEY FORM is DESIGNED TO REPLACE THE NEED FOR SUBMITTING PRODUCT SHEETS, A
SIGNED COMPANY SHEET NEEDS TO BE SUBMITTED IN HARD COPY FORM. IF SEPARATE DIVISIONS WITHIN A COMPANY ARE
SUBMITTING INDIVIDUALLY, EACH DIVISION MUST ALSO SUBMIT SEPARATE COMPANY SHEETS.
INSTALLING SOFTWARE ON A HARD DRIVE
1. PLACE THE DISK PROVIDED INTO AN APPROPRIATE FLOPPY DRIVE. ENTER THE LETTER OF THAT DISK PLUS A COLON (:) AT
THE DOS PROMPT (E.G., A:), AND FOLLOW BY PRESSING THE KEY. THIS MAKES THAT DRIVE THE CURRENT
DRIVE.
2. TYPE INSTALL, LEAVE A SPACE, THEN TYPE THE LETTER OF THE HARD-DRIVE (OR HIGH-DENSITY FLOPPY) TO WHICH YOU
WANT THE PROGRAM COPIED (E.G., INSTALL C:), FOLLOWED BY PRESSING THE KEY. IF YOU DO NOT
DESIGNATE A DRIVE AFTER YOU TYPE INSTALL, THE FILES WILL AUTOMATICALLY BE COPIED TO THE C DRIVE.
3. THE PROGRAM CAN BE INVOKED BY TYPING CD\SURVEY FOLLOWED BY PRESSING , THEN TYPING SURVEY
FOLLOWED BY THE KEY.
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USING THE SURVEY SOFTWARE (FOR TECHNICAL ASSISTANCE, CALL (919) 493-6263)
STARTING SURVEY
BEFORE THE SURVEY SOFTWARE CAN BE INVOKED, THE PROPER DRIVE AND DIRECTORY MUST BE MADE CURRENT USING
DOS. IF THE INSTALL BATCH FILE WAS USED, THE DIRECTORY is CALLED SURVEY. THE DEFAULT DRIVE is C: UNLESS
OTHERWISE INDICATED DURING INSTALLATION. FIRST MAKE THE APPROPRIATE DRIVE CURRENT BY TYPING THE DRIVE LETTER, PLUS A
COLON(:) AT THE DOS PROMPT (E.G., C:), THEN PRESS THE KEY. NEXT, MAKE THE SURVEY DIRECTORY CURRENT BY
TYPING CD\SURVEY AND PRESSING THE KEY.
START THE PROGRAM BY TYPING SURVEY FOLLOWED BY THE KEY. IF THE PROGRAM DOES NOT OPERATE,
CALL THE TECHNICAL ASSISTANCE NUMBER LISTED ABOVE. OTHERWISE, A SCREEN ASKING FOR THE APPROPRIATE DIRECTORY FOR
DATABASE FILES WILL APPEAR. SIMPLY PRESS THE KEY TO ACCEPT THE DEFAULT. IF YOUR ORGANIZATION HAS MANY
DIVISIONS, EACH WITH A LARGE NUMBER OF PRODUCTS THAT WILL BE INCLUDED IN THE SURVEY, IF MAY BE ADVANTAGEOUS TO COPY
A SEPARATE VERSION OF THE EMPTY DATABASES TO A DIFFERENT SUBDIRECTORY FOR EACH DIVISION BEFORE DATA ENTRY. IF YOU
HAVE QUESTIONS REGARDING HOW THIS CAN BE DONE, CALL THE NUMBER LISTED ABOVE.
ENTERING DATA INTO THE COMPUTERIZED FORM
THERE ARE TWO SCREENS OF INFORMATION REQUESTS ASSOCIATED WITH THE COMPUTERIZED SURVEY FORM. THESE
SCREENS ARE ROUGHLY EQUIVALENT TO THE TWO-PAGE PRODUCT FORM INCLUDED IN THE HARD COPY OF THE SURVEY FORM.
MOST OF THE INSTRUCTIONS FOR COMPLETING PRODUCT SHEETS ALSO APPLY TO THE COMPUTERIZED FORM. ADDITIONAL HELP
INFORMATION IS ALSO AVAILABLE THROUGH HELP SCREENS IN THE SOFTWARE BY PRESSING THE KEY. PLEASE ALSO NOTE
THAT INSTRUCTIONS ARE GIVEN AT THE BOTTOM OF THE SCREEN. THESE INSTRUCTIONS WILL CHANGE BASED ON THE INFORMATION
BEING REQUESTED.
OTHER UTILITIES ARE AVAILABLE THROUGH OTHER "F" KEYS: SEARCH, DELETE, PRINT, AND THE
CONTROL KEY (DESIGNATED A) PLUS PAGE UP (PGUP) OR PAGE DOWN (PGDN) TO GO TO THE TOP OF THE FILE OR THE
BOTTOM OF THE FILE . PLEASE NOTE THAT THE AVAILABILITY OF THESE FUNCTIONS DURING VARIOUS POINTS IN THE
PROGRAM EXECUTION WILL BE SUSPENDED AND THAT THE INSTRUCTIONS AT THE BOTTOM OF THE SCREEN WILL REFLECT THIS
STATUS. EACH OF THESE FUNCTIONS is DESCRIBED IN GREATER DETAIL BELOW.
MANY OF THE DATA ELEMENTS REQUESTED IN THE SURVEY FORM ARE REQUIRED. IF A REQUIRED ELEMENT is LEFT BLANK,
THE PROGRAM CONTINUOUSLY LOOPS BACK UNTIL A VALID ENTRY IS MADE.
ITEM 1. THE INFORMATION ENTERED IN ITEM 1 (COMPANY NAME AND DIVISION NAME) FOR THE FIRST RECORD WILL ALSO
BE ENTERED IN EACH SUBSEQUENT NEW RECORD, UNTIL CHANGED THROUGH THE KEYBOARD. ALL SUBSEQUENT RECORDS WILL THEN
HAVE THE "NEW" ITEM 1 INFORMATION ADDED AUTOMATICALLY.
ITEM 2. A SERIES OF THREE MENUS ARE AVAILABLE TO ASSIST YOU IN ENTERING THE CATEGORY CODES. THESE ARE
INVOKED BY PRESSING WITH THE ITEM 3 INFORMATION LEFT BLANK. THESE MENUS ARE SIMILAR IN STRUCTURE TO
ATTACHMENT A OF THE SURVEY FORM. To CHANGE AN ENTRY IN ITEM 3, USE THE KEY TO BLANK OUT THE FIELD AND
PRESS TO INVOKE THE MENUS. AN INVALID ENTRY WILL ALSO INVOKE THE MENUS.
ITEM 4. THE PRODUCT NAME is A REQUIRED PIECE OF INFORMATION. PLEASE CONSULT THE INSTRUCTIONS FOR
COMPLETING PRODUCT SHEETS FOR A DISCUSSION OF GROUPING PRODUCTS.
ITEM 8. THE AMOUNT OF PRODUCT SOLD IN 1990 is ALSO A REQUIRED PIECE OF INFORMATION. THE PROGRAM WILL NOT
CONTINUE TO THE NEXT SCREEN UNLESS THIS INFORMATION IS FILLED OUT.
ITEM 11. THE DEFAULT ASSUMPTION is THAT YOU WILL BE PROVIDING PRODUCT RVOC INFORMATION. THE SCREEN WILL
-------
ACCOMMODATE RVOC INFORMATION BASED ON ENTRIES TO ITEM 9 AND ITEM 10 FOR UP TO 20 RVOC INGREDIENTS. UPON FIRST
ENTERING THE SECOND SCREEN (PAGE 2) OF THE COMPUTERIZED FORM FOR A NEW RECORD, YOU WILL BE ASKED WHETHER OR NOT
YOU HAVE PRODUCT FORMULATION INFORMATION. IF YOU ANSWER EL, YOU WILL NOT BE ASKED AGAIN UNLESS YOU ENTER A
ZERO FOR ITEMS 9 AND 10. IF YOU ANSWER o, YOU WILL BE ASKED TO VERIFY YOUR ANSWER EVERY TIME YOU ENTER PAGE 2
FOR THAT RECORD. BASED ON YOUR ANSWER TO THAT FIRST INQUIRY, YOU WILL EITHER BE ASKED TO PROVIDE RVOC INGREDIENT
INFORMATION, OR THE NAME AND ADDRESS OF SOMEONE WHO DOES HAVE THAT INFORMATION.
PLEASE CONSULT THE INSTRUCTIONS FOR COMPLETING PRODUCT SHEETS FOR ADDITIONAL GUIDANCE.
DESCRIPTIONS OF FUNCTIONS
SEARCH
THE SEARCH UTILITY ALLOWS YOU TO QUICKLY GO TO A RECORD MEETING THE GIVEN CRITERIA. THE CRITERIA CHOICES
ARE RECORD NUMBER, PRODUCT NAME, OR CATEGORY CODE. FOR THE FIRST TWO CRITERIA, ONLY ONE RECORD WILL APPLY.
FOR CATEGORY CODE, IT IS POSSIBLE FOR MANY RECORDS (PRODUCTS OR GROUPS OF PRODUCTS) TO HAVE THE SAME CATEGORY
CODE. THE CATEGORY CODE SEARCH WILL ONLY LOCATE THE FIRST RECORD MEETING THE CRITERIA.
DELETE
DELETE WILL MARK THE CURRENT RECORD FOR DELETION. THE DELETION STATUS WILL THEN BE DISPLAYED AT THE TOP
RIGHT CORNER OF THE SCREEN. DELETE CAN BE TOGGLED OFF BY PRESSING THE KEY AGAIN. RECORDS ARE NOT
PERMANENTLY DELETED UNTIL THE PROGRAM IS EXITED BY PRESSING THE KEY.
PRINT
THE PRINT FUNCTION ALLOWS EITHER A HARD COPY OR DISK FILE IN ASCII FORMAT TO BE PRODUCED FROM INFORMATION
IN THE DATABASES. THE PURPOSE OF SUCH A UTILITY IS TO ALLOW FOR BETTER QUALITY CONTROL OF DATA ENTRIES.
TECHNICAL ASSISTANCE
IF YOU HAVE ANY REMAINING QUESTIONS OR NEED ADDITIONAL GUIDANCE, PLEASE CALL THE FOLLOWING NUMBER AND
DESCRIBE YOUR NEED:
(919)493-6263
INSTRUCTIONS FOR COMPLETING COMPANY SHEET
ALL COMPANIES RECEIVING THIS INFORMATION COLLECTION REQUEST MUST RESPOND BY SUBMITTING A COMPLETED COMPANY
SHEET, EVEN IF NO COVERED PRODUCTS ARE MANUFACTURED OR SOLD. (SEE EXEMPTIONS FROM SUBMITTING PRODUCT SHEETS
GENERAL INSTRUCTIONS). ONE COMPANY SHEET CAN BE SUBMITTED FOR AN ENTIRE COMPANY, UNLESS THE COMPANY HAS
DELEGATED RESPONSIBILITY FOR SUBMITTING THE PRODUCT SHEETS TO SEPARATE DIVISIONS. IN THIS CASE, PLEASE SUBMIT A
COMPANY SHEET FOR EACH DIVISION SUBMITTING PRODUCT SHEETS, INDICATING BOTH COMPANY AND DIVISION NAMES ON EACH
-------
SHEET.
1. COMPANY NAME. ENTER THE COMPANY NAME, OR COMPANY AND DIVISION NAMES.
2. PERSON TO CONTACT. ENTER THE NAME OF THE PERSON TO BE CONTACTED BY EPA IF CLARIFICATIONS ARE NEEDED.
3. ADDRESS. ENTER THE MAILING ADDRESS OF THE PERSON TO CONTACT.
4. PHONE. ENTER THE PHONE NUMBER OF THE PERSON TO CONTACT.
5. TYPE OF BUSINESS. PLACE AN "X" IN ONE OR MORE OF THE BOXES TO INDICATE THE PRIMARY ASPECTS OF THE BUSINESS
CONDUCTED BY THE COMPANY OR DIVISION. THIS INFORMATION WILL BE USED TO ASSIST EPA IN DETERMINING COVERAGE OF
PRODUCT CATEGORIES IN THE SURVEY. MARKING A PARTICULAR BOX DOES NOT DETERMINE IF YOUR COMPANY IS THE
COMPANY RESPONSIBLE FOR REPORTING ON A PARTICULAR PRODUCT. THE COMPANY RESPONSIBLE FOR REPORTING IS THE
COMPANY WHICH IS IDENTIFIED ON THE PRODUCT LABEL.
MANUFACTURER MEANS A COMPANY THAT MANUFACTURES PRODUCTS WITH ITS COMPANY OR DIVISION
NAME ON THE LABEL PER FTC, EPA, CPSC, OSHA, OR FDA LABELING REQUIREMENTS. THE COMPANY
THAT OWNS THE PRODUCT LABEL AND INITIATES MANUFACTURE IS CONSIDERED TO BE THE
MANUFACTURER, EVEN IF SOME OR ALL OF THE FORMULATION AND PACKAGING OF THAT PRODUCT
OCCURS AT A CONTRACT PACKAGER SITE.
RETAILER MEANS A COMPANY THAT SELLS PRODUCTS TO INDIVIDUAL CONSUMERS OR HOUSEHOLDS.
RETAILER ALSO INCLUDES RETAIL OUTLETS AND COMPANIES WHO SELL DIRECTLY TO THE CONSUMER
THROUGH SALES REPRESENTATIVES OR THROUGH MAIL-ORDER.
DISTRIBUTOR MEANS A COMPANY THAT SELLS PRODUCTS TO RETAIL BUSINESSES OR TO INSTITUTIONAL
OR INDUSTRIAL CUSTOMERS.
PRIVATE LABEL CONTRACT PACKAGER MEANS A COMPANY THAT MANUFACTURES PRODUCTS BASED ON
ITS OWN FORMULATION BUT PLACES ANOTHER COMPANY'S NAME ON THE PRODUCT LABEL.
CUSTOM CONTRACT PACKAGER MEANS A COMPANY THAT MANUFACTURES PRODUCTS BASED ON
FORMULATION SPECIFICATION OF ANOTHER COMPANY AND PLACES THE OTHER COMPANY'S NAME ON THE
PRODUCT LABEL PER FTC, EPA, CPSC, OSHA, OR FDA LABELING REQUIREMENTS.
6. INDICATE NUMBER OF PRODUCT SHEETS ATTACHED. ENTER THE NUMBER OF PRODUCT SHEETS ATTACHED FOR THE
COMPANY OR DIVISION. INDICATE IF THE COMPANY IS EXEMPT FROM SUBMITTING PRODUCT SHEETS DUE TO EITHER OF THE
TWO CONDITIONS LISTED. NOTE THAT THE COMPANY SHEET MUST STILL BE SUBMITTED, EVEN IF ONE OF THE TWO CONDITIONS
APPLY. (IF SENDING COMPUTERIZED DATABASE INFORMATION, PLEASE INDICATE THE NUMBER OF PRODUCTS IN THE DATABASE.)
7. CERTIFICATION. PLEASE HAVE THE COMPANY OR DIVISION OFFICER WHO is RESPONSIBLE FOR ENVIRONMENTAL COMPLIANCE
OR GOVERNMENT AFFAIRS CERTIFY THE ACCURACY OF THE COMPLETED COMPANY SHEET AND PRODUCT SHEET.
-------
COMPANY SHEET
1. COMPANY NAME:
DIVISION NAME:
2. PERSON TO CONTACT:
3. ADDRESS:
4. PHONE:
5. TYPE OF BUSINESS (MARK WITH "X" FOR ALL THAT APPLY):
MANUFACTURER —I RETAILER —I DISTRIBUTOR —I PRIVATE LABEL —I CUSTOM CONTRACT
CONTRACT PACKAGER PACKAGER
6. INDICATE NUMBER OF PRODUCT SHEETS ATTACHED:
OR ZERO PRODUCT SHEETS ARE ATTACHED BECAUSE:
THIS COMPANY DOES NOT MANUFACTURE, DISTRIBUTE, OR SELL ANY OF THE REPORTABLE PRODUCTS
LISTED IN ATTACHMENT A.
THIS COMPANY DOES MANUFACTURE, DISTRIBUTE, OR SELL SOME OF THE REPORTABLE PRODUCTS
LISTED IN ATTACHMENT A, BUT THIS COMPANY is NOT THE PARTY RESPONSIBLE TO REPORT BECAUSE
IT IS NOT NAMED ON THE PRODUCT LABEL.
7. CERTIFICATION. THE COMPANY OR DIVISION OFFICER WHO is RESPONSIBLE FOR ENVIRONMENTAL COMPLIANCE OR
GOVERNMENT AFFAIRS MUST SIGN THE CERTIFICATION STATEMENT BELOW:
"I HEREBY CERTIFY THAT, TO THE BEST OF MY KNOWLEDGE AND BELIEF, ALL INFORMATION ENTERED ON
THIS COMPANY SHEET AND ANY ATTACHED PRODUCT SHEETS is COMPLETE AND ACCURATE."
NAME SIGNATURE
TITLE DATE SIGNED
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INSTRUCTIONS FOR COMPLETING PRODUCT SHEET(S)
A PRODUCT SHEET MUST BE SUBMITTED FOR EACH DIFFERENT PRODUCT OR GROUP OF PRODUCTS FOR WHICH YOUR COMPANY OR DIVISION
IS RESPONSIBLE. (AS DISCUSSED IN THE GENERAL INSTRUCTIONS SECTION OF THIS MAILING, AN ALTERNATIVE, ELECTRONIC FORMAT IS
AVAILABLE AND IS HIGHLY ENCOURAGED.) THE COMPANY RESPONSIBLE FOR REPORTING IS THE COMPANY WHICH IS IDENTIFIED ON THE
PRODUCT LABEL. PLEASE COPY THE BLANK PRODUCT SHEET FORM PROVIDED AS NECESSARY, AND NUMBER EACH IN THE SPACE AT THE
TOP OF THE FORM. DUE TO THE NEED FOR ACCURATE INGREDIENT DATA (ITEM 11 A), YOU MUST SUBMIT SEPARATE PRODUCT SHEETS FOR
DIFFERENT PACKAGE FORMS OF THE SAME TRADE NAME (AEROSOL VERSUS SPRAY PUMP, OR LIQUID VERSUS GEL, SEE ITEM 3), BUT IT MAY
NOT BE NECESSARY TO SUBMIT SEPARATE PRODUCT SHEETS FOR DIFFERENT FLAVORS, SCENTS, COLORS, OR SIZES OF PRODUCTS HAVING
ESSENTIALLY THE SAME FORMULATION DATA. SEE INSTRUCTIONS FOR ITEM 3 BELOW.
GROUPING OF PRODUCTS. PRODUCTS MAY BE GROUPED AND REPORTED ON ONE PRODUCT SHEET IF ALL OF THE FOLLOWING CONDITIONS
ARE MET:
A) ALL PRODUCTS IN THE GROUP ARE IN THE SAME PRODUCT CATEGORY (/.£., HAVE THE SAME PRODUCT CATEGORY CODE IN
ITEM 2 ON THE PRODUCT SHEET).
B) ALL PRODUCTS HAVE THE SAME PRODUCT FORM (ITEM 3 ON THE PRODUCT SHEET).
c) EACH PRODUCT IN THE GROUP HAS A TOTAL REPORTABLE VOLATILE ORGANIC COMPOUND (RVOC) CONTENT THAT DOES NOT
DIFFER BY MORE THAN 5% FROM ANY OTHER PRODUCTS IN THE GROUP. SEE ATTACHMENT B FOR A DESCRIPTION OF RVOC
AND THE INSTRUCTIONS FOR COMPLETING PRODUCT SHEETS, ITEM 9 ON PAGE 11 FOR FURTHER CLARIFICATION.
IF PRODUCTS ARE BEING GROUPED, THE NET PRODUCT WEIGHT SOLD IN 1990 (ITEM 8) SHOULD BE A SUM OF THE TOTAL WEIGHT FOR ALL
PRODUCTS IN THE GROUP. THE TOTAL RVOC (ITEM 9) AND ENTRIES FOR INDIVIDUAL RVOC'S (ITEM 11 A) SHOULD BE BASED ON AVERAGES
OF ALL PRODUCTS INCLUDED IN THE GROUP.
1. COMPANY NAME. ENTER YOUR COMPANY, OR COMPANY AND DIVISION NAME(S) AS RECORDED ON YOUR COMPANY SHEET.
2. PRODUCT CATEGORY. ENTER THE CODE FOR THE CATEGORY WHICH BEST DESCRIBES THE PRODUCT (OR GROUP OF PRODUCTS)
FROM THOSE LISTED IN ATTACHMENT A. YOU MAY HAVE TO LOOK UNDER MORE THAN ONE MAJOR CATEGORY TO FIND THE
APPROPRIATE DESCRIPTOR. PRODUCTS WHICH MAY BE USED IN MORE THAN ONE AREA (E.G., UPHOLSTERY SHAMPOO WHICH MIGHT
BE USED IN EITHER THE HOME OR CAR) WILL BE LISTED IN THE MORE GENERAL CATEGORY (IN THIS CASE, HOME CARE). IF A
PRODUCT IS FORMULATED FOR A SPECIALIZED USE (E.G., AUTOMOTIVE GLASS CLEANER VERSUS REGULAR GLASS CLEANER), IT
SHOULD BE LISTED IN THE MORE SPECIFIC CATEGORY. IF YOU CANNOT LOCATE AN EXACT MATCH, USE THE MOST SUITABLE
CATEGORY NAME ON THE LIST, AND GIVE A BRIEF DESCRIPTION OF THE PRODUCT AND ITS USE.
3. PRODUCT FORM. PLACE AN "X" IN ONE OF THE BOXES TO INDICATE THE FORM IN WHICH THE PRODUCT is DISPENSED OR APPLIED.
BECAUSE THE FORMULATION INFORMATION (ITEM 11 A) FOR A PRODUCT LINE is LIKELY TO VARY BY PRODUCT FORM, YOU SHOULD
NOT MARK MORE THAN ONE BOX FOR THIS ITEM. PLEASE SUBMIT SEPARATE PRODUCT SHEETS FOR DIFFERENT FORMS OF THE SAME
PRODUCT LINE.
/AEROSOL DISPENSERS USE A LIQUIFIED OR COMPRESSED GAS PROPELLANT TO DELIVER THE PRODUCT, IN THE FORM
OF A SPRAY, MIST, STREAM, FOAM, OR GEL.
PUMP SPRAY DISPENSERS USE A MANUAL PUMP TO DELIVER THE PRODUCT IN THE FORM OF A SPRAY.
LIQUID PRODUCTS ARE POURED OR SQUEEZED OUT OF THE CONTAINER AND DO NOT FIT THE DESCRIPTION OF AN
AEROSOL, PUMP SPRAY PRODUCT, SOLID OR GEL.
SOLID PRODUCTS DO NOT DEFORM WITH USE, EXCEPT BY EVAPORATION (E.G., MOTH REPELLENTS) OR SURFACE
WEAR (E.G., BAR SOAPS). THIS INCLUDES SOLID BLOCKS, GRANULES, OR POWDERS.
GEL OR PASTE PRODUCTS WILL NOT POUR, BUT WILL SPREAD OR DEFORM EASILY.
IF NONE OF THESE CATEGORIES APPLY, MARK OTHER AND GIVE A DESCRIPTION, E.G., "MATERIAL
IMPREGNATED IN A CLOTH."
4. FULL PRODUCT OR PRODUCT GROUP NAME. ENTER THE PRODUCT NAME AS IT APPEARS ON THE PRODUCT LABEL. PLEASE ENSURE
THAT EACH PRODUCT SHEET SUBMITTED HAS A UNIQUE PRODUCT NAME. IF PRODUCTS ARE BEING GROUPED, USE AN APPROPRIATE,
UNIQUE, DESCRIPTIVE NAME FOR THE PRODUCT GROUP. SEE ITEM 5 BELOW.
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5. IF THE DATA ON THIS PRODUCT SHEET REPRESENT MORE THAN A SINGLE STOCK-KEEPING UNIT (SKU), ENTER THE NUMBER OF
SKU'S REPRESENTED. PRODUCTS FOR WHICH TOTAL REPORTABLE VOLATILE ORGANIC COMPOUND (RVOC) CONTENTS DO NOT
DIFFER BY MORE THAN 5 PERCENT OF THE TOTAL PRODUCT WEIGHT MAY BE GROUPED TOGETHER FOR REPORTING PURPOSES ON
ONE PRODUCT SHEET (SEE DISCUSSION ABOVE REGARDING GROUPING OF PRODUCTS). FOR EXAMPLE, SCENTED AND UNSCENTED
VARIETIES OF A PRODUCT FOR WHICH THE TOTAL RVOC CONTENTS DO NOT DIFFER BY MORE THAN 5 PERCENT OF THE TOTAL
PRODUCT WEIGHT MAY BE COMBINED AND REPORTED ON ONE PRODUCT SHEET (PRODUCT A, WITH 45% TOTAL RVOC, CAN BE
INCLUDED IN A LISTING OF THE UNSCENTED PRODUCT, WITH 41% TOTAL RVOC).
6. MAJOR CUSTOMER TYPE. PLACE AN "X" IN ONE OR MORE OF THE BOXES TO INDICATE USERS OF THE PRODUCT.
HOUSEHOLD CONSUMERS USE THE PRODUCT THEMSELVES IN THE HOME OR IN OTHER PERSONAL AREAS, SUCH AS
AUTOMOBILES OR BOATS.
COMMERCIAL/INSTITUTIONAL CONSUMERS USE THE PRODUCT IN A COMMERCIAL BUSINESS OR INSTITUTIONAL
SETTING. THIS INCLUDES COMMERCIAL BUSINESSES PERFORMING SERVICES IN PRIVATE HOMES (E.G., CARPET
CLEANERS, PEST CONTROL, ETC.).
INDUSTRIAL CONSUMERS USE THE PRODUCT AT AN INDUSTRIAL SITE, SPECIFICALLY IN ASSOCIATION WITH A
MANUFACTURING PROCESS (E.G., MOLD RELEASE USED IN PLASTIC FORMS).
7. PRODUCT SIZE. MARK ANY SIZES REPRESENTING 25 PERCENT OR MORE OF YOUR NET SALES. IF THE PRODUCT is SOLD BY VOLUME,
USE THE FIRST ROW OF BOXES. IF THE PRODUCT IS SOLD BY WEIGHT, USE THE SECOND ROW OF BOXES.
8. NET PRODUCT WEIGHT SOLD IN THE U.S. FOR 1990 (POUNDS). ENTER THE ANNUAL U.S. SALES OF THE PRODUCT OR PRODUCTS
IN UNITS OF POUNDS OF NET FINAL PRODUCT. INCLUDE ALL "CONSUMABLE" ELEMENTS OF THE PRODUCT, SUCH AS ACTIVE
INGREDIENTS, PROPELLANTS, DILUENTS, ADDITIVES, OR FILLERS ADDED BY A CONTRACT FILLER. DO NOT INCLUDE THE WEIGHT OF
STRUCTURAL ELEMENTS, CONTAINERS OR PACKAGING. ANY CONTINUOUS 12 MONTH PERIOD MAY BE USED, AS LONG AS THE
MAJORITY OF THE PERIOD IS WITHIN THE CALENDAR YEAR 1990.
COMPLETING THE NEXT THREE ITEMS (9, 10 AND 11A) WILL REQUIRE INFORMATION ON THE SPECIFIC CHEMICAL FORMULATION OF THE
PRODUCT. IF YOUR COMPANY DOES NOT HAVE ACCESS TO SUCH INFORMATION AND CANNOT OBTAIN IT, WHICH MIGHT BE TRUE IF A PRIVATE
LABEL CONTRACT PACKAGER MAKES THE PRODUCT UNDER CONTRACT WITH YOUR COMPANY, PLEASE SKIP TO ITEM 11B. YOUR COMPANY
IS STILL RESPONSIBLE FOR COMPLETING ALL OTHER ITEMS ON THE PRODUCT SHEET, INCLUDING THE SALES VOLUME (ITEM 8).
9. TOTAL NET WEIGHT % REPORTABLE VOC. ENTER THE TOTAL WEIGHT PERCENT OF THE NET FINAL PRODUCT WHICH is REPORTABLE
VOC. PROPELLANTS OR OTHER MATERIALS ADDED BY A CONTRACT FILLER SHOULD BE CONSIDERED PART OF THE NET FINAL
PRODUCT. THE DEFINITION OF "REPORTABLE VOC" (RVOC) IS PROVIDED IN ATTACHMENT B. RVOC DOES NOT INCLUDE ALL
VOC'S DEFINED BY EPA FOR REGULATORY PURPOSES. THE DEFINITION GIVEN IN THIS SURVEY FORM SHOULD NOT BE CONSTRUED
AS REDEFINING EPA'S DEFINITION OF VOC. (ADDITIONAL INFORMATION IS REQUESTED UNDER ITEM 11 REGARDING METHYLENE
CHLORIDE AND 1,1,1-TRICHLOROETHANE, BUT THESE SHOULD NOT BE INCLUDED IN THE TOTAL REPORTED HERE.) IF SEVERAL
PRODUCTS ARE GROUPED, USE AN AVERAGE WEIGHT PERCENT FOR EACH INGREDIENT FROM ALL PRODUCTS IN THE GROUP.
10. TOTAL NUMBER OF REPORTABLE INGREDIENTS. ENTER THE NUMBER OF REPORTABLE VOC INGREDIENTS CONTAINED IN THE
PRODUCT. COMPLEX MIXTURES SUCH AS FRAGRANCES AND PETROLEUM DISTILLATES CAN BE CONSIDERED A SINGLE INGREDIENT
IF THEY ARE PURCHASED BY YOUR COMPANY AS A MIXTURE. IF PRODUCTS ARE BEING GROUPED, LIST THE TOTAL NUMBER OF
INDIVIDUAL INGREDIENTS WITHIN THAT GROUP. FOR EXAMPLE, IF ACETONE IS LISTED AS AN INGREDIENT IN ALL FIVE PRODUCTS IN
A GROUP, IT SHOULD BE COUNTED ONLY ONCE AS AN INGREDIENT COMPOUND. IF ETHANOL IS FOUND IN TWO PRODUCTS AND
METHANOL IN THE OTHER THREE, EACH SHOULD BE COUNTED ONCE AS AN INGREDIENT COMPOUND FOR THAT GROUP.
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11 A. LIST THE LARGEST REPORTABLE VOC (RVOC) INGREDIENTS AND THEIR WEIGHT PERCENTS FOR ALL RVOC THAT ARE 5% OR MORE
OF THE PRODUCT WEIGHT. THE PURPOSE OF THIS ITEM IS TO IDENTIFY THE INDIVIDUAL INGREDIENTS WHICH COMPRISE THE BULK
OF THE TOTAL RVOC. RVOC INGREDIENTS SHOULD BE DENOTED BY CHEMICAL ABSTRACTS SERVICE (CAS) REGISTRY NUMBER
AND SIMPLE CHEMICAL NAMES WHEN AVAILABLE. THE WEIGHT PERCENTS ARE TO BE REPORTED TO THE NEAREST 0.1%. IF THE
INGREDIENT IS A COMPLEX MIXTURE OR PROPRIETARY INGREDIENT PROVIDED BY ANOTHER SUPPLIER, REPORT THE TRADE NAME AND
SUPPLIER IN THE SPACE PROVIDED FOR RVOC NAME, AND THE PERCENT WEIGHT OF THE INGREDIENT UNDER WEIGHT %. DO NOT
REPORT INDIVIDUAL COMPONENTS OF INGREDIENTS WHICH ARE FRAGRANCE MATERIALS. A CAS NUMBER IS NOT REQUIRED FOR
COMPLEX MIXTURES NOR PROPRIETARY INGREDIENTS PROVIDED BY THIRD PARTY SUPPLIERS. COMPOUNDS WITH WEIGHT PERCENTS
LESS THAN 5% CAN BE REPORTED TOGETHER AS "ALL OTHER REPORTABLE VOC" IN THE LAST LINE OF THE TABLE. CONFIRM THAT
THE SUM OF ALL OF THE INDIVIDUAL RVOC INGREDIENTS LISTED PLUS THE "ALL OTHER REPORTABLE VOC" EQUALS THE PERCENT
REPORTED IN ITEM 10.
IF PRODUCTS ARE BEING GROUPED, USE AVERAGES FOR EACH RVOC THAT IS REPRESENTED AT LEASE ONCE IN THE PRODUCT
GROUP. FOR EXAMPLE:
THERE ARE FIVE PRODUCTS IN A GROUP AND TWO CONTAIN ETHANOL AT 8% AND 10%, WHILE THE OTHER THREE
CONTAIN METHANOLAT 10%, 11%, AND 12%. THE AVERAGE RVOC PERCENT WEIGHTS FOR THIS GROUP WOULD
BE 3.6% ETHANOL (18^-5) AND 6.5% METHANOL (33 -r- 5).
ADDITIONAL INFORMATION REGARDING THE PERCENT OF THE PRODUCT COMPOSED OF METHYLENE CHLORIDE AND/OR 1,1,1-
TRICHLOROETHANE IS REQUESTED SEPARATELY, EVEN THOUGH THESE ITEMS ARE NOT RVOC. THESE COMPOUNDS SHOULD NOT
BE ADDED TO THE RVOC TOTAL.
11B. ENTER NAME AND ADDRESS OF COMPANY WITH FORMULATION INFORMATION IF YOU DO NOT HAVE THE DATA TO COMPLETE ITEM
11 A. IF YOUR COMPANY IS IDENTIFIED ON THE PRODUCT LABEL PER FTC, EPA, CPSC, OSHA, OR FDA LABELING REQUIREMENTS
BUT DOES NOT HAVE ACCESS TO THE SPECIFIC CHEMICAL FORMULATION INFORMATION, ENTER THE NAME AND ADDRESS OF THE
COMPANY THAT CAN PROVIDE THAT INFORMATION FOR EACH PRODUCT LISTED. INDICATE A CONTACT PERSON AND ANY OTHER
INFORMATION (SUCH AS CONTRACT NUMBERS OR PRODUCT CODES) WHICH THE EPA MAY NEED TO OBTAIN ITEM 11A INFORMATION
FROM THAT COMPANY. THIS REQUIREMENT DOES NOT APPLY TO INGREDIENTS WHICH ARE FRAGRANCE MATERIALS.
12. INDICATE WHICH ITEMS CONTAIN CONFIDENTIAL BUSINESS INFORMATION. MARK ANY OF THE ITEMS WHICH YOUR COMPANY
CONSIDERS CONFIDENTIAL BUSINESS INFORMATION (CBI). PLEASE DO NOT CLAIM CBI UNLESS THE INFORMATION IS TRULY
CONFIDENTIAL. PLEASE REFER TO ENCLOSURE 3 AND ENCLOSURE 5 OF THE ACCOMPANYING COVER LETTER. MARKING "SALES"
INDICATES THAT THE AMOUNT OF PRODUCT SOLD IN 1990 SHOULD BE CONSIDERED CONFIDENTIAL. MARKING "TOTAL RVOC %"
INDICATES THAT THE TOTAL AMOUNT OF RVOC CONTAINED IN THE PRODUCT IS CONFIDENTIAL. MARKING "INGREDIENTS" INDICATES
THAT SOME OF THE NAMED COMPOUNDS IN ITEM 11A ARE CONFIDENTIAL. MARKING "INGREDIENT WEIGHT PERCENTS" INDICATES
THAT WHILE THE COMPOUNDS MAY BE COMMON KNOWLEDGE, THE AMOUNTS OF EACH RVOC ARE CONFIDENTIAL.
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PRODUCT SHEET #
PAGE 1 OF 2
1. COMPANY NAME : _
DIVISION NAME :
2. PRODUCT CATEGORY CODE (SEE ATTACHMENT A):
DESCRIPTION (FROM ATTACHMENT A AND/OR ADDITIONAL DESCRIPTIONS):
3. PRODUCT FORM : —I AEROSOL —I SPRAY PUMP —I LIQUID —I GEL —I SOLID
OTHER
4. FULL PRODUCT OR PRODUCT GROUP NAME :
5. IF THE DATA ON THIS PRODUCT SHEET REPRESENT MORE THAN A SINGLE STOCK KEEPING UNIT (SKU), ENTER THE NUMBER OF SKU'S
REPRESENTED (SEE INSTRUCTIONS ON GROUPING PRODUCTS):
6. MAJOR CUSTOMER TYPE : —I HOUSEHOLD —I COMM/INST —I INDUSTRIAL
7. PRODUCT SIZE -BY VOLUME :
OR
-BY WEIGHT :
0 TO 32 FL.OZ. —I >32 FL.OZ. TO 5 GAL.
>5 TO 55 GAL.
0 TO 1 LB.
1 TO 5 LB.
>55 GAL.
5 TO 20 LB.
>20 LB.
8. NET PRODUCT WEIGHT SOLD IN THE U.S. FOR 1990 (POUNDS) :
9. TOTAL REPORTABLE VOC (WEIGHT % OF NET PRODUCTS):
DO NOT INCLUDE METHYLENE CHLORIDE OR 1,1,1-TRICHLOROETHANE IN THIS TOTAL.
IF FORMULATION INFORMATION IS NOT AVAILABLE TO YOUR COMPANY, GO TO ITEM 11B.
10. TOTAL NUMBER OF REPORTABLE VOC INGREDIENT COMPOUNDS :
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PRODUCT SHEET #
PAGE 2 OF 2
11 A. LIST THE LARGEST REPORTABLE VOC INGREDIENT COMPOUNDS AND THEIR WEIGHT %'S FOR ALL REPORTABLE VOC THAT ARE 5%
OR MORE OF THE TOTAL NET PRODUCT WEIGHT. USE THE CRITERIA LISTED IN ATTACHMENT B TO DETERMINE IF THE COMPOUND IS
AN RVOC. PLEASE LIST THESE COMPOUNDS IN ORDER OF HIGHEST TO LOWEST WEIGHT PERCENT, IF POSSIBLE. Do NOT REPORT
INDIVIDUAL COMPONENTS OF INGREDIENTS WHICH ARE FRAGRANCE MATERIALS.
REPORTABLE VOC INGREDIENT COMPOUNDS
NAME
CAS NO.
WEIGHT % IN FINAL
PRODUCT
1.
2.
3.
4.
5.
6.
7.
8.
ALL OTHER REPORTABLE VOC
TOTAL REPORTABLE VOC %
(SHOULD MATCH ITEM 9)
ADDITIONAL INFORMATION is REQUESTED SEPARATELY FOR TWO OTHER COMPOUNDS: METHYLENE CHLORIDE AND 1,1,1-TRICHLOROETHANE. Do NOT INCLUDE THESE
COMPOUNDS IN TOTAL RVOC.
METHYLENE CHLORIDE
1,1,1 -TRICHLOROETHANE
75-09-2
71-55-6
11 B. ENTER NAME AND ADDRESS OF COMPANY WITH FORMULATION INFORMATION IF YOU DO NOT HAVE THE DATA TO COMPLETE ITEM 11 A.
THIS REQUIREMENT DOES NOT APPLY TO INGREDIENTS WHICH ARE FRAGRANCE MATERIALS.
12. INDICATE WHICH ITEMS CONTAIN CONFIDENTIAL BUSINESS INFORMATION
SALES
TOTAL RVOC
INGREDIENTS
INGREDIENT Wt. %s
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ATTACHMENT B
DEFINITION OF A REPORTABLE VOLATILE ORGANIC COMPOUND (RVOC)
THIS DEFINITION OF A REPORTABLE VOLATILE ORGANIC COMPOUND (RVOC) SHOULD BE USED IN CONJUNCTION WITH THE DECISION TREE
ON THE FOLLOWING PAGE TO DETERMINE IF AN INGREDIENT COMPOUND IS AN RVOC. RVOC IS A SUBSET OF ERA'S DEFINITION OF VOC.
THIS IS NOT TO BE CONSTRUED AS A MODIFICATION OF THE EPA DEFINITION FOR VOC. ONLY INGREDIENT COMPOUNDS FROM PRODUCTS
LISTED IN ATTACHMENT A NEED TO BE CONSIDERED. IF A COMPOUND is FOUND TO NOT BE AN RVOC, NO OTHER CONSIDERATIONS ARE
NEEDED FOR THAT COMPOUND.
1) ANY INGREDIENT COMPOUND FOR PRODUCTS LISTED IN ATTACHMENT A SHOULD BE CONSIDERED A POSSIBLE RVOC IF IT IS
AN ORGANIC COMPOUND (CONTAINS AT LEAST ONE CARBON).
2) THE FOLLOWING COMPOUNDS ARE EXCEPTIONS, AND SHOULD NOT BE CONSIDERED AS RVOC:
A) THE COMPOUNDS [CAS NUMBER IN BRACKETS]:
METHANE
ETHANE
CARBON MONOXIDE
CARBON DIOXIDE
CARBONIC ACID SALTS
METALLIC CARBIDES OR CARBONATES
AMMONIUM CARBONATE
1,1,1-TRICHLOROETHANE
METHYLENE CHLORIDE
TRICHLOROFLUOROMETHANE (CFC-11)
DlCHLORODIFLUOROMETHANE (CFC-12)
CHLORODIFLUOROMETHANE (HCFC-22)
TRIFLUOROMETHANE (HFC-23)
TRICHLOROTRIFLUOROETHANE (CFC-113)
DlCHLOROTETRAFLUOROETHANE (CFC-114)
CHLOROPENTAFLUOROETHANE (CFC-115)
DlCHLOROTRIFLUOROETHANE (HCFC-123)
TETRAFLUOROETHANE (HFC-134A)
DlCHLOROFLUOROETHANE (HCFC-141 B)
CHLORODIFLUOROETHANE (HCFC-142s)
2-CHLORO-1,1,1,2-TETRAFLUOROETHANE (HCFC-124)
PENTAFLUOROETHANE (HFC-125)
1,1,2,2-TETRAFLUOROETHANE(HFC-134)
1,1,1-TRIFLUOROETHANE (HFC-143A)
1,1-DlFLUOROETHANE (HFC-152A)
[74-82-8]
[74-84-0]
[630-08-0]
[124-38-9]
[VARIOUS]
[VARIOUS]
[506-87-6]
[71-55-6]
[75-09-2]
[75-69-4]
[75-71-8]
[75-45-6]
[75-46-7]
[76-13-1]
[1320-37-2]
[76-15-3]
[306-83-2]
[75-68-3]
AND
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B) PERFLUOROCARBON COMPOUNDS IN THE FOLLOWING CLASSES:
(1) CYCLIC, BRANCHED, OR LINEAR, COMPLETELY FLUORINATED ALKANES
(2) CYCLIC, BRANCHED, OR LINEAR, COMPLETELY FLUORINATED
ETHERS WITH NO UNSATURATIONS
(3) CYCLIC, BRANCHED, OR LINEAR, COMPLETELY FLUORINATED
TERTIARY AMINES WITH NO UNSATURATIONS
(4) SULFUR-CONTAINING PERFLUOROCARBONS WITH NO
UNSATURATIONS AND WITH SULFUR BONDS ONLY TO CARBON
AND FLUORINE.
3) THE INGREDIENT COMPOUND IS AN RVOC IF IT IS A SOLID AT ROOM TEMPERATURE (20°C) AND READILY SUBLIMES
(BECOMES A GAS). EXAMPLES INCLUDE PARA-DICHLOROBENZENE, NAPHTHALENE, AND CAMPHOR. ALL OTHER SOLIDS
ARE EXEMPT AND ARE NOT RVOC'S UNLESS THE INGREDIENT COMPOUND BECOMES A VAPOR AT A TEMPERATURE AT
WHICH IT IS USED (SUCH AS COMPONENTS OF HOT GLUES, PLUG-IN AIR FRESHENERS, ETC.).
4) THE INGREDIENT COMPOUND IS AN RVOC IF IT IS AN ORGANIC GAS OR LIQUID WITH A VAPOR PRESSURE ABOVE 0.1 MM
HG AT 20°C.
5) IF THE VAPOR PRESSURE FOR THE INGREDIENT COMPOUND IS UNKNOWN AND IT CONTAINS LESS THAN OR EQUAL TO
12 CARBONS, IT IS AN RVOC.
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ATTACHMENT A
CONSUMER AND COMMERCIAL PRODUCTS SURVEY CATEGORIES
PERSONAL CARE PRODUCTS
HAIR CARE PRODUCTS
1101 BLEACHES AND LIGHTENERS
1102 BRILLIANTINES
1103 CONDITIONERS
1104 CONDITIONING SPRAYS
1105 CURL ACTIVATORS
1106 CURL REVITALIZERS
1107 DYES - PERMANENT
1108 DYES - SEMIPERMANENT
1109 DYES - TEMPORARY
1110 FINISHING HAIR SPRAYS
1111 FINISHING SPRITZES
1112 GROOMING CREAMS
1113 GROWTH PRODUCTS
1114 MOUSSES
1115 PERMANENT WAVE TREATMENTS
1116 POMADES
1117 PROTECTIVE SPRAYS
1118 RINSES
1119 SETTING LOTIONS
1120 SHAMPOOS
1121 SPRAY SHINES
1122 STRAIGHTENERS
1123 STYLING GELS
1124 STYLING SPRAYS
1125 STYLING SPRITZES
1126 THICKENERS
1127 TONICS
1199 OTHER HAIR CARE PRODUCTS
DEODORANTS AND ANTIPERSPIRANTS
1201 UNDERARM DEODORANTS
1202 UNDERARM ANTIPERSPIRANTS
1203 FOOT DEODORANTS
1204 FEMININE HYGIENE DEODORANTS
1299 OTHER DEODORANT AND ANTIPERSPIRANT PRODUCTS
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FRAGRANCE PRODUCTS
1301 COLOGNES
1302 PERFUMES
1303 TOILET WATERS
1304 AFTER SHAVE TREATMENTS
1305 BODY FRAGRANCE SPRAYS
1306 BATH OILS, BEADS, AND CAPSULES
1399 OTHER FRAGRANCE PRODUCTS
POWDERS
1401 BABY POWDERS
1402 BODY POWDERS
1403 FOOT POWDERS
1499 OTHER POWDER PRODUCTS
NAIL CARE PRODUCTS
1501 POLISHES
1502 BASE COATS, UNDERCOATS
1503 POLISH REMOVERS
1504 NAIL EXTENDERS
1505 CUTICLE SOFTENERS
1506 MANICURE PREPARATIONS
1599 OTHER NAIL CARE PRODUCTS
FACIAL AND BODY MAKEUP AND TREATMENTS
1601 ASTRINGENTS
1602 CREAMS, SCRUBS, CLEANERS
1603 ROUGES AND BLUSHES
1604 MAKEUP BASES, FOUNDATIONS, AND FIXATIVES
1605 LIPSTICKS
1606 MOISTURIZERS
1607 SKIN LIGHTENERS
1608 FACIAL MASQUES
1609 LEG AND BODY PAINTS
1610 MASCARA
1611 EYELINER
1612 EYE SHADOW
1613 EYE MAKEUP REMOVER
1614 EYEBROW PENCIL
1615 HAND AND BODY LOTIONS
1616 SKIN PROTECTANTS
1617 DEPILATORIES
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1618 SELF-TANNING PREPARATIONS
1619 SUNTAN OILS AND LOTIONS
1620 SUNSCREENS
1699 OTHER FACIAL AND BODY MAKEUP AND TREATMENTS
ORAL CARE PRODUCTS
1701 MOUTHWASHES
1702 BREATH FRESHENERS
1703 TOOTHPASTES, GELS, AND POWDERS
1704 PLAQUE REMOVAL SOLUTIONS
1705 FLUORIDE RINSES
1706 DENTURE CARE PRODUCTS
1799 OTHER ORAL CARE PRODUCTS
HEALTH USE PRODUCTS
1801 OVER-THE-COUNTER (OTC) DRUGS (EXTERNAL ONLY)
1802 PRESCRIPTION PHARMACEUTICALS (EXTERNAL ONLY)
1899 OTHER HEALTH USE PRODUCTS
MISCELLANEOUS PERSONAL CARE PRODUCTS
1901 HAND CLEANERS AND SOAPS
1902 RUBBING ALCOHOL
1903 SHAVING CREAMS, GELS, AND SOAPS
1999 OTHER MISCELLANEOUS PERSONAL CARE PRODUCTS
HOUSEHOLD PRODUCTS (INCLUDING INSTITUTIONAL USES)
HARD SURFACE CLEANERS
2101 GENERAL PURPOSE CLEANERS
2102 GLASS CLEANERS
2103 OVEN CLEANERS
2104 TUB, TILE, AND SINK CLEANERS
2105 MILDEW REMOVERS
2106 TOILET BOWL CLEANERS
2107 HARD SURFACE RUST STAIN REMOVERS
2108 METAL CLEANERS
2109 SOAP SCOURING PADS
2199 OTHER HARD SURFACE CLEANERS
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LAUNDRY PRODUCTS
2201 DETERGENTS
2202 SOAPS
2203 PRESOAKS
2204 PREWASH SPOT AND STAIN REMOVERS
2205 BLEACHES
2206 WHITENERS/BRIGHTENERS
2207 BLUING
2208 FABRIC SOFTENERS
2209 WATER SOFTENERS AND CONDITIONERS
2210 STARCHES, SIZINGS, AND FABRIC FINISHES
2299 OTHER LAUNDRY PRODUCTS
FABRIC. CARPET. AND UPHOLSTERY CARE PRODUCTS
2301 CARPET CLEANERS
2302 CARPET DEODORIZERS AND FRESHENERS
2303 UPHOLSTERY CLEANERS
2304 SPOT REMOVERS
2305 FABRIC STAIN REPELLENTS
2306 WATER REPELLENTS
2307 FABRIC DYES
2308 ANTISTATIC SPRAYS
2309 DRY CLEANING FLUIDS
2399 OTHER FABRIC, CARPET, AND UPHOLSTERY CARE PRODUCTS
DISHWASHING PRODUCTS
2401 DISH DETERGENTS (MANUAL)
2402 DISH DETERGENTS (MACHINE)
2403 RINSE AIDS
2404 FILM AND SPOT REMOVERS
2499 OTHER DISHWASHING PRODUCTS
WAXES AND POLISHES
2501 FURNITURE WAXES AND POLISHES
2502 FLOOR WAXES AND POLISHES
2503 DUSTING AIDS
2599 OTHER HOUSEHOLD WAXES AND POLISHES
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AIR FRESHENERS
2601 ROOM AIR FRESHENERS
2602 TOILET DEODORANT BLOCKS
2699 OTHER AIR FRESHENERS
SHOE AND LEATHER CARE PRODUCTS
2701 LEATHER PRESERVATIVE TREATMENTS
2702 LEATHER DYES
2703 SHOE POLISHES
2799 OTHER SHOE AND LEATHER CARE PRODUCTS
MISCELLANEOUS HOUSEHOLD PRODUCTS
2801 LUBRICANTS
2802 DRAIN OPENERS
2803 CHARCOAL LIGHTERS
2804 WICK LAMP FUELS
2805 PLANT LEAF CLEANERS AND WAXES
2806 DRIVEWAY CLEANERS
2899 OTHER MISCELLANEOUS HOUSEHOLD PRODUCTS
AUTOMOTIVE AFTERMARKET PRODUCTS
DETAILING PRODUCTS
3101 WAXES, POLISHES, AND FINISH SEALERS
3102 VINYL AND LEATHER CLEANERS
3103 UPHOLSTERY FABRIC CLEANERS
3104 TIRE CLEANERS
3105 WHEEL CLEANERS
3106 BUG AND TAR REMOVERS
3107 CHROME CLEANERS AND POLISHES
3108 RUBBER AND VINYL PROTECTANTS
3199 OTHER AUTOMOTIVE DETAILING PRODUCTS
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MAINTENANCE AND REPAIR PRODUCTS
3201 ENGINE DEGREASERS
3202 CARBURETOR AND CHOKE CLEANERS
3203 BRAKE CLEANERS
3204 BRAKE ANTI-SQUEAL COMPOUNDS
3205 TIRE SEALANTS AND INFLATORS
3206 BELT DRESSINGS
3207 ENGINE STARTING FLUIDS
3208 LUBRICANTS (OTHER THAN ENGINE OIL)
3209 ANTIFREEZES
3210 BRAKE FLUIDS
3211 BODY REPAIR PRODUCTS (OTHER THAN COATINGS)
3212 WINDSHIELD DEICERS
3213 WINDSHIELD WASHER FLUIDS
3299 OTHER AUTOMOTIVE MAINTENANCE AND REPAIR PRODUCTS
ADHESIVES AND SEALANTS
ADHESIVES
4101
4102
4103
4104
4105
4106
4107
4108
4109
4199
SEALANTS
4201
4202
4203
4204
4205
4206
4207
4208
4209
4210
4299
HOUSEHOLD GLUES AND PASTES
ARTS AND CRAFTS ADHESIVES
CARPET AND TILE ADHESIVES
WALLPAPER ADHESIVES
WOODWORKING GLUES
PLASTIC PIPE CEMENTS AND PRIMERS
THREAD LOCKING COMPOUNDS
SPECIALTY AUTOMOTIVE ADHESIVES
CONSTRUCTION ADHESIVES
OTHER ADHESIVES
SPACKLING COMPOUNDS
CAULKING COMPOUNDS
WINDOW GLAZING COMPOUNDS
PIPE THREAD SEALANTS
PLUMBER'S PUTTIES
PAINTER'S PUTTIES
WOOD FILLERS
INSULATING AND SEALING FOAMS
DRIVEWAY PATCHING COMPOUNDS
COLD PROCESS ROOF CEMENTS
OTHER SEALANTS
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FIFRA-REGISTERED PRODUCTS
INSECTICIDES
5101 LAWN AND GARDEN INSECTICIDES
5102 SPACE INSECTICIDES AND ROOM FOGGERS
5103 FLYING INSECT SPRAYS
5104 RESIDUAL INSECTICIDES
5105 HORNET AND WASP SPRAYS
5106 FLEA AND TICK SOAPS, SPRAYS, AND DIPS
5199 OTHER INSECTICIDES
FUNGICIDES AND NEMATICIDES
5201 LAWN AND GARDEN TREATMENTS
5202 WOOD PRESERVATIVES
5203 MOLD AND MILDEW RETARDANTS
5299 OTHER FUNGICIDES AND NEMATICIDES
HERBICIDES
5301 AQUATIC HERBICIDES
5302 SWIMMING POOL ALGICIDES
5303 TERRESTRIAL HERBICIDES, DEFOLIANTS, DESICCANTS
5399 OTHER HERBICIDES
ANTIMICROBIAL AGENTS
5401 SANITIZERS
5402 DISINFECTANTS
5403 STERILANTS
5499 OTHER ANTIMICROBIAL AGENTS
MISCELLANEOUS FIFRA-CONTROLLED PRODUCTS
5501 INSECT REPELLENTS
5502 DOMESTIC CAT AND DOG REPELLENTS
5503 RODENT POISONS AND BAITS
5504 REPTILIAN AND AMPHIBIAN CONTROL AGENTS
5599 OTHER MISCELLANEOUS FIFRA-CONTROLLED PRODUCTS
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COATINGS AND RELATED PRODUCTS
AEROSOL SPRAY PAINTS AND COATINGS
6101 NONFLAT ENAMELS
6102 FLAT ENAMELS
6103 NONFLAT LACQUERS
6104 FLAT LACQUERS
6105 METALLIC PIGMENTED COATINGS
6106 CLEAR COATINGS
6107 GROUND/TRAFFIC MARKING COATINGS
6108 EXACT MATCH AUTOMOTIVE PAINTS
6109 VINYL/FABRIC COATINGS
6110 GLASS COATINGS
6111 AUTOMOTIVE SANDING PRIMERS
6112 RUST-INHIBITIVE PRIMERS
6113 SPATTER FINISHES
6114 WOOD STAINS
6115 ENGINE ENAMELS
6116 HIGH TEMPERATURE COATINGS
6199 OTHER AEROSOL SPRAY PAINTS AND COATINGS
RELATED PRODUCTS
6201 PAINT THINNERS
6202 PAINT REMOVERS
6203 BRUSH CLEANERS AND RECONDITIONERS
6204 SOLVENTS
6299 OTHER RELATED PRODUCTS
MISCELLANEOUS PRODUCTS (NOT OTHERWISE COVERED)
ARTS AND CRAFTS SUPPLIES
7101 ARTISTS PAINTS, PIGMENTS, AND THINNERS
7102 FIXATIVE SPRAYS
7103 SPECIALTY CLEANING PRODUCTS
7104 CERAMIC FINISHING PRODUCTS
7199 OTHER ARTS AND CRAFTS SUPPLIES
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NON-PESTICIDAL VETERINARY AND PET PRODUCTS
7201 ANIMAL DRUGS (EXTERNAL ONLY)
7202 LIVESTOCK AND PET GROOMING PRODUCTS
7203 CAT LITTERS
7299 OTHER NON-PESTICIDAL VETERINARY AND PET PRODUCTS
PRESSURIZED FOOD PRODUCTS
7301 CHEESE SPREADS
7302 PAN SPRAYS
7303 WHIPPED DESSERT TOPPINGS
7399 OTHER PRESSURIZED FOOD PRODUCTS
OFFICE SUPPLIES
7401 PENS
7402 INK
7403 PERMANENT MARKERS
7404 DRY ERASABLE MARKERS
7405 HIGHLIGHTERS
7406 CORRECTION FLUIDS
7407 LIQUID TONERS (FOR COPIERS, FAX MACHINES, PRINTERS, ETC.)
7408 INKED RIBBONS (FOR TYPEWRITERS, PRINTERS, ETC.)
7499 OTHER OFFICE SUPPLIES
-------
VOLUME III: CHAPTERS
SOLVENT CLEANING
September 1997
Prepared by:
Eastern Research Group
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee,
Emission Inventory Improvement Program and for Charles O. Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency (EPA). Members of the
Area Sources Committee contributing to the preparation of this document are:
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Carolyn Lozo, California Air Resources Board
Kwame Agyei, Puget Sound Air Pollution Control Agency
Mike Fishbum, Texas Natural Resource Conservation Commission
Gwen Judson, Wisconsin Department of Natural Resource
Charles Masser, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Linda Murchison, California Air Resources Board
Sally Otterson, Washington Department of Ecology
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Jim Wilkinson, Maryland Department of the Environment
Other contributors have been:
Dennis Goodenow, California Air Resources Board
Ron Ryan, EPA/EFIG
Stephen M. Roe, E.H. Pechan and Associates
Tahir R. Khan, Chemical Emission Management Services, Mississauga, Ontario
EIIP Volume III ill
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CONTENTS
Section Page
1 Introduction 6.1-1
2 Source Category Description 6.2-1
2.1 Solvent Cleaning Activities 6.2-1
2.1.1 Batch Cold Cleaning Machines 6.2-1
2.1.2 Batch Vapor Cleaning Machines 6.2-3
2.1.3 In-line Cleaning Machines 6.2-4
2.1.4 Cleanup Solvent Use 6.2-5
2.2 Emission Sources 6.2-6
2.2.1 Cleaning Machines 6.2-6
2.2.2 Cleanup Solvents 6.2-7
2.3 Factors Influencing Emissions 6.2-7
2.4 Control Techniques 6.2-8
2.4.1 Cleaning Machines 6.2-8
2.4.2 Cleanup Solvents 6.2-11
2.5 Regulatory Status 6.2-12
2.5.1 Solvent Cleaning Machines 6.2-12
2.5.2 Cleanup Solvents 6.2-13
2.5.3 Summary 6.2-13
3 Overview of Available Methods 6.3-1
3.1 Emission Estimation Methodologies 6.3-1
3.1.1 Solvent Emissions 6.3-1
3.1.2 Surveys 6.3-3
3.1.3 Facility-specific Data 6.3-4
3.1.4 Emission Factors 6.3-4
3.1.5 Speciated Emissions (VOCs, HAPs) 6.3-5
IV EIIP Volume III
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CONTENTS
Section Page
3.2 Data Needs 6.3-7
3.2.1 Data Elements 6.3-7
3.2.2 Application of Controls 6.3-8
3.2.3 Spatial Allocation 6.3-8
3.2.4 Temporal Resolution 6.3-9
3.2.5 Projecting Emissions 6.3-9
4 Preferred Methods for Estimating Emissions 6.4-1
4.1 Emission Estimation Methodologies 6.4-1
4.2 Facility-specific Data 6.4-1
4.3 Surveys 6.4-2
4.3.1 Cold Cleaners 6.4-2
4.3.2 Cleanup 6.4-4
4.3.3 Survey Compilation and Calculations 6.4-4
5 Alternative Methods for Estimating Emissions 6.5-1
5.1 Solvent Cleaning Equipment 6.5-1
5.1.1 Facility-specific Data 6.5-1
5.1.2 Emission Factors 6.5-1
5.2 Solvent Cleanup Activities 6.5-4
6 Quality Assurance/Quality Control 6.6-1
6.1 Emission Estimate Quality Indicators 6.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 6.6-1
6.1.2 Sources of Uncertainty 6.6-1
7 Data Coding Procedures 6.7-1
7.1 Process and Control Codes 6.7-1
8 References 6.8-1
Appendix A - Example Survey for Solvent Cleanup Activities
EIIP Volume III V
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FIGURES AND TABLES
Figure Page
6.4-1 Example Survey for Cold Cleaning Full Service Suppliers 6.4-3
Table Page
6.2-1 State Regulations 6.2-14
6.2-2 Cleanup Solvent Regulations by State 6.2-16
6.3-1 Summary of Available Estimation Methods for Solvent Cleaning
Activities 6.3-2
6.3-2 Commonly Used Cleanup Solvents 6.3-6
6.4-1 Solvent Cleaning Activities by Industry 6.4-5
6.5-1 1994 Safety-Kleen Emissions Data for Cold Cleaners 6.5-3
6.5-2 Per Capita and Per Employee Solvent Cleaning Emission Factors 6.5-4
6.5-3 Estimates of the Amount of VOC Cleaning Solvent Used by Industry 6.5-6
6.5-4 Nationwide VOC Solvent Usage and Emission Estimates for
Selected Industries 6.5-8
6.6-1 Facility-specific Equipment Solvent Cleaning: Preferred for
Halogenated Cleaners, Alternative 1 for Non-Halogenated
Cold Cleaning and Solvent Cleanup 6.6-3
6.6-2 Survey of Solvent Cleaning Uses (Equipment or Solvent) in the Inventory
Region: Preferred for Non-Halogenated Cleaners and Solvent
Cleanup, Alternative 1 for Non-Halogenated Cold Cleaners 6.6-4
6.6-3 Cold Cleaning Unit Emission Factor: Alternative 2 for Cold Cleaners 6.6-5
6.6-4 Solvent Cleanup Emission Factors: Alternative 2 for Solvent Cleanup 6.6-5
6.6-5 National Factors Applied to Local Activity Data (Number of Employees):
Alternative 2 for All Cleaning Types 6.6-6
vi Volume IV
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FIGURES AND TABLES (CONTINUED)
Table Page
6.6-6 National Factors Applied to Local Activity Data (Population):
Alternative 2 for All Cleaning Types 6.6-7
6.7-1 AIRS AMS Codes for Solvent Cleaning Machines by Industry 6.7-2
6.7-2 AIRS Control Device Codes 6.7-4
EIIP Volume III Vll
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Vlll EIIP Volume III
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1
INTRODUCTION
Solvent cleaning operations are an integral part of many industries and involve the use of solvents
or solvent vapor to remove water-insoluble contaminants such as grease, oils, waxes, carbon
deposits, fluxes, and tars from metal, plastic, glass, and other surfaces. Solvent cleaning is
usually performed prior to painting, plating, inspection, repair, assembly, heat treating, and
machining (EPA, 1991; EPA, 1993a).
Section 2 of this chapter contains general descriptions of the solvent cleaning source category, a
listing of emission sources commonly associated with solvent cleaning operations, and an
overview of the available control technologies for various solvent cleaning operations. Section 3
of this chapter provides an overview of available emission estimation methods. Section 4
presents the preferred emission estimation methods for solvent cleaning operations, and Section 5
presents alternative emission estimation techniques. Quality assurance (QA) and quality control
(QC) procedures are described in Section 6 and data coding procedures are discussed in Section
7. Section 8 lists references. Refer to Chapter 1, Introduction to Area Source Emission
Inventory Development, for general concepts and technical approaches.
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6.1-2 EIIP Volume III
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SOURCE CATEGORY DESCRIPTION
There are two basic types of cleaning machines: batch and in-line cleaning machines (also called
continuous cleaning machines). Both of these equipment types are designed to use solvent to
clean parts. The solvent is either used to clean in its nonvapor liquid form (at a temperature
below the boiling point, referred to as cold cleaning), or heated to a temperature above its
boiling point (referred to as vapor cleaning). Other solvent cleaning operations involve the use of
solvent in wipe-cleaning and equipment cleanup.
Solvents used in cleaning machines include 1,1,1-trichloroethane (TCA), trichloroethylene
(TCE), methylene chloride, perchloroethylene (PERC), carbon tetrachloride, chloroform,
chlorofluorocarbons (CFCs), petroleum distillates (e.g., Stoddard solvent, mineral spirits,
naphthas), and alcohols. Solvents used in cleanup include acetone, alcohols, butyl acetate,
cyclohexanone, ethyl acetate, ethylbenzene, ethylene glycol, methyl ethyl ketone, methyl isobutyl
ketone, naphthas, toluene, and xylene. Acetone, CFCs, methylene chloride, PERC, and TCA are
specifically exempted from the EPA's definition of reactive volatile organic compounds (VOCs)
due to their low photochemical reactivity. TCA, carbon tetrachloride, and CFCs such as CFC-11
and CFC-13 will not be produced after January 1, 1996 as part of the Montreal Protocol to
reduce stratospheric ozone depletion. Higher molecular weight organics (i.e. naphthas) usually
have lower vapor pressures and thus lower emissions and less impact on ozone levels. Water-
based cleaners may also be substituted for organic solvents to eliminate any ozone impacts.
2.1 SOLVENT CLEANING ACTIVITIES
2.1.1 BATCH COLD CLEANING MACHINES
Batch cold cleaning machines use solvent in the liquid phase to clean and remove foreign material
such as oils and grease from the surface of materials. These machines are batch loaded, and
cleaning operations include spraying, flushing, solvent or parts agitation, wipe cleaning, brushing,
and immersion. Both halogenated and nonhalogenated solvents are used in batch cold cleaning
machines. Carburetor cleaners use halogenated solvents and Stoddard solvent. The predominant
solvent used for all other batch cleaning machines are nonhalogenated solvents.
Nonhalogenated solvents used in cold cleaning machines include aliphatic petroleum distillates
(e.g., mineral spirits, Stoddard solvent, petroleum naphthas), alcohols, ketones, glycol ethers and
others. In some carburetor cleaners, a mixture containing halogenated solvents, such as
methylene chloride and nonhalogenated solvents, is used. The total halogenated and
nonhalogenated solvents used in cold cleaning machines in the past has been estimated as
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
430,000 tons, based on several year's data (EPA, 1991). However, halogenated solvent use in
cold cleaning machines has been estimated as 65,000 tons for the year of 1991 (EPA, 1993a).
Cold cleaners are usually individually small emission sources and, because they are widely
scattered and frequently used, they are most easily treated as area sources. If they are collocated
at a major source, they may be included in the point source inventory and those emissions will
need to be subtracted from the area source estimate.
Ninety percent of Stoddard solvent batch cold cleaning machines use a remote reservoir and 10
percent use immersion; however, many cold cleaning machines are a combination of both types
(EPA, 1991; EPA, 1994a). Remote reservoir cleaning machines pump solvent through a sink-
like work area. The solvent drains back into an enclosed container through a small drain while
the contaminated parts (called workload) are being cleaned. Fewer vapors are emitted from the
solvent in the enclosed container during nonuse compared to immersion cleaners. In immersion
cold cleaning machines, the workload is simply immersed in the liquid solvent (EPA, 1994a).
Solvent may also be sprayed on the parts to enhance cleaning. Combination remote
reservoir/immersion cleaning machines resemble a remote reservoir machine in that solvent is
pumped to a sink-like work area. However, the machine's work area contains a shelf that can be
removed; once the shelf is removed, the workload can be cleaned by immersion (EPA, 1994a).
Machines that can be either a remote reservoir or an immersion cleaning machine are considered
to be immersion cleaning machines by the Environmental Protection Agency (EPA) (Federal
Register, 1994).
Approximately one million cold cleaning machines were estimated to be in operation in the
United States in 1994 (EPA, 1994a). Approximately 50 percent of batch cold cleaning machines
are used in automotive repair shops (Standard Industrial Classification [SIC] Code 753). This
includes top, body, and upholstery repair and paint shops (SIC Code 7532), automotive exhaust
system repair shops (SIC Code 7533), tire retreading and repair shops (SIC Code 7534),
automotive glass replacement shops (SIC Code 7536), automotive transmission repair shops
(SIC Code 7537), general automotive repair shops (SIC Code 7538), and automotive repair
shops not elsewhere classified (SIC Code 7539). Automotive repair shops generally use smaller
cold cleaning machines with a solvent/air interface less than or equal to 0.4 m2. Larger
immersion batch cold cleaning machines are used in manufacturing processes as well as
automotive rebuilding and repair, and machining industries (EPA, 1991; EPA, 1994a).
2.1.2 BATCH VAPOR CLEANING MACHINES
Batch vapor cleaning machines represent the largest source of halogenated solvent (e.g., TCA,
TCE, methylene chloride, PERC, carbon tetrachloride, and chloroform) emissions. The most
common type of batch vapor cleaning machine is the Open Top Vapor Cleaner (OTVC). The
OTVC is a tank designed to generate and contain solvent vapor. The tank is equipped with a
heating system that uses steam, electricity, hot water, or a heat pump to boil the liquid solvent.
As the solvent boils, dense solvent vapors rise and displace the air in the tank. Coolant is
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
circulated in condensing coils on the top of the tank to create a controlled vapor zone within the
tank. Condensing solvent vapors dissolve the contaminants on the surface of the workload and
flush both the dissolved and undissolved contaminants from the workload. When the
temperature of the workload equals the temperature of the vapor, no further cleaning will occur
by this mechanism (because solvent will no longer condense on the part). The vapor cleaning
phase may be supplemented, or even replaced, by the immersion of the workload into the hot
liquid solvent. Several operational variations are possible. The cleaning cycle can be modified
from a basic vapor cleaning cycle to improve cleaning efficiency. One OTVC operational
variation is the immersion-vapor-spray cycle where the workload is first immersed in the warm or
boiling solvent for precleaning. The workload is then cleaned in the vapor section and sprayed
with the solvent. Organic impurities (e.g., grease and oil) do not contaminate the vapor because
of their higher boiling points. Because the solvent remains clean, it can be used for longer
periods of time compared to cold cleaning.
Non-OTVC batch vapor cleaning machines are a hybrid of the OTVC and in-line machines. They
tend to be larger, with an enclosed design with conveyorized systems for moving large parts and
parts baskets. Non-OTVC batch cleaning machines include the cross-rod, the vibra, the Ferris
wheel, and the carousel cleaners. All of these cleaning machines tend to have multiple loads
within the machine simultaneously. The cross-rod degreaser contains rods with suspended parts
baskets and is fully enclosed with the exception of one opening. Through this opening, parts
enter and exit the machine. Since parts tend to be loaded semicontinuously and typically
manually, the machine is classified as a batch unit. In the vibra cleaning machine, the soiled parts
are fed in a batch into a pan and flooded with boiling solvent at the bottom of the machine. The
machine includes a vibrating spiral elevator that lifts the parts through the increasing cleaner
solvent baths (either vapor or liquid). This unit can clean large volumes of small parts. The
Ferris wheel machine is so named because it is typically characterized by four baskets rotating in
a vertical plane. The cleaner would typically have four stages; at any one time, one parts basket
is in each stage. One stage is for loading and unloading of parts and is located at the only
opening in the machine. The other three stages are various cleaning stages including spray,
solvent bath, and/or vapor cleaning. The carousel cleaning machine is similar to the Ferris wheel
machine except that parts move through a horizontal plane.
In 1991, 16,400 batch vapor cleaning machines using halogenated solvents were estimated to be
in operation in the United States, and it is estimated that those machines used approximately
104,500 tons of methylene chloride, PERC, TCE, TCA, and l,l,l-trichloro-2,2,2-trifluoroethane
(CFC-113) (EPA, 1993a). Stoddard solvent is not used in batch vapor cleaning machines due to
its flammability. Thus, only machines using TCE would need to be considered for a VOC
inventory.
An estimated 10,000 to 13,500 small vapor cleaning machines could potentially be small sources
for hazardous air pollutants (HAPs) that would need to be inventoried as area sources unless they
are collocated and counted as part of a major source. Assuming no emissions control, it is
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
estimated that half of the large vapor cleaning machines (those with an average 16 ft2 working
area) emit less than 10 tons per year of a HAP, and could also be counted as area sources (EPA,
1993a).
The largest amounts of halogenated solvent used for cleaning are in the manufacture of furniture
and fixtures (SIC Code 25), fabricated metal manufacturing (SIC Code 34), electric and
electronic equipment (SIC Code 36), transportation equipment (SIC Code 37), and
miscellaneous manufacturing industries (SIC Code 39). Other industries that use halogenated
solvents for cleaning include food and kindred products (SIC Code 20), primary metals (SIC
Code 33), nonelectric machinery (SIC Code 35), and instruments and clocks (SIC Code 38).
Nonmanufacturing industries such as railroad, bus, aircraft, and truck maintenance facilities,
automotive and electric tool repair shops, automobile dealers, service stations, and miscellaneous
repair services (SIC Codes 40, 41, 42, 45, 49, 55, 75, and 76, respectively) also use halogenated
solvents for solvent cleaning (EPA, 1993a).
2.1.3 IN-LINE CLEANING MACHINES
In-line cleaners are usually inventoried as point sources (EPA, 1991). In-line cleaning machines
employ automated loading on a continuous basis. These machines are often custom made for
large-scale operations and can work in a vapor or nonvapor mode. However, the vapor mode is
most commonly used. A continuous or multiple-batch loading system greatly reduces or even
eliminates the manual parts handling associated with batch cleaning. The cross-rod batch
cleaning machine can also be designed to operate continuously with no manual loading. The
same cleaning techniques are used for in-line cleaning as for batch cleaning but on a larger scale.
In-line cleaning machines are enclosed to prevent solvent losses; however, entry and exit
openings cannot be sealed (EPA, 1993a). The four types of in-line cleaning machines are:
monorail, belt, strip, and printed circuit board processing equipment (e.g., photoresist strippers,
flux cleaners, and developers). The monorail vapor cleaning machine is used when the workload
to be cleaned is being transported between manufacturing operations on a monorail conveyor
(EPA, 1993a). A belt cleaning machine conveys the workload through a long and narrow boiling
chamber where the workload is cleaned by condensing vapor or immersion. The strip cleaning
machine is similar to the belt cleaner except the strip is the material being cleaned. Printed circuit
boards are cleaned with photoresist strippers and circuit board cleaning machines (EPA, 1993a).
The five most common halogenated solvents used in in-line solvent cleaning operations are
methylene chloride, PERC, TCE, TCA, and CFC-113 (EPA, 1993a). PERC, TCE, and TCA are
commonly used because they are not flammable and their vapors are much heavier than air (EPA,
1991). In 1991, an estimated 39,000 tons of halogenated solvents were used by vapor in-line
solvent cleaning machines (EPA, 1993a). Approximately 2,500 to 4,000 in-line cleaners
employing halogenated solvents were estimated to be in operation in 1991 (EPA, 1991).
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
In-line solvent cleaning machines are used by a broad spectrum of industries but are most often
found in plants where there is a constant stream of parts to be cleaned, such as printed circuit
boards for the electronic and electrical components industry (EPA, 1991; EPA, 1993a).
2.1.4 CLEANUP SOLVENT USE (EPA, 1994s)
Cleanup solvents are used to clean external surfaces, such as products, parts and equipment,
floors, tables, and walls, and internal surfaces or containers, such as tanks and supply lines.
Cleaning processes may include wiping using mops, brushes, and rags, spraying, flushing the
interiors of equipment, purging spray equipment, or dipping small parts in vessels of solvents.
These processes are used to clean products as part of the manufacturing process, such as before
painting, cleaning of process equipment, and cleaning before maintenance.
Wiping is perhaps the most common cleaning activity because the contaminant is quickly
removed. Wipe cleaning is easily performed anywhere in the plant and is a frequent part of
maintenance activities (e.g., cleaning machinery, floors). Surfaces can be cleaned while in place
without disassembly. Wipe cleaning is an integral part of many production processes including
automotive manufacturing, truck and bus manufacturing, and automotive parts and accessories
manufacturing; in the manufacture of adhesives, packaging, plastics, furniture, fiberglass boats,
electrical equipment, magnetic tape, and photographic chemicals; and rotogravure printing and
autobody refmishing as well as offset lithographic printing.
Frequently used industrial cleaning solvents include acetone, butyl acetate, cyclohexanone,
ethanol, ethyl acetate, ethylbenzene, ethylene glycol, isopropyl alcohol, methanol, methyl ethyl
ketone, methyl isobutyl ketone, naphtha, PERC, toluene, and xylene. Estimated annual cleaning
solvent usage ranges from 270,000 to 1,400,000 tons per year; however, this estimate is for the
industries listed above. Nationwide use of cleaning solvents has not been quantified and is
expected to be much higher.
2.2 EMISSION SOURCES
2.2.1 CLEANING MACHINES
Batch and in-line solvent cleaning machines are characterized by three operating modes that have
characteristic emission mechanisms. The operating modes are idling, working, and downtime.
Cold cleaners do not have an idling mode. Fugitive emissions also occur as a result of leaks,
filling/draining losses, wastewater losses, start-up/shutdown losses, distillation losses, and solvent
decomposition losses.
Idling emissions occur when the cleaning machine is turned on and ready to operate, but is not
actively processing parts. Air and solvent interface losses consist of solvent vapor diffusion (or
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
evaporation from liquid solvent in cold cleaning machines) and solvent convection caused by a
warm freeboard (freeboard is the distance between the top of the tank and the solvent/air
interface). Diffusion occurs because solvent molecules move from areas of higher concentration
in the vapor zone to areas of lower concentration in the air. Idling diffusion is the greatest when
air flow is introduced across the solvent/air interface from room drafts. Drafts can also sweep
solvent-laden air from the freeboard area into the ambient air. Convection occurs from the tank
walls being heated from the heated liquid solvent and vapor. Emissions occur as a result of the
convective flow up along the freeboard that carries solvent vapor out of the cleaning machine. If
freeboards are kept at ambient temperatures, emissions will be minimized. Emission rate variance
can be explained by the varying primary condensing temperatures; however, emission rates are
lowest when the primary condenser temperature of the cleaning machine is the lowest. Typical
idling losses are 0.03 Ib/ft2/hr (EPA, 1993a).
Working emissions occur when the cleaning machine is turned on and operating and include
idling emissions with additional emissions from the introduction of parts being cleaned, the
cleaning process (e.g., spraying), the evaporation of solvent from the part as the workload is
pulled out of the cleaning machine, and solvent carry out. Working emissions from cold cleaners
include solvent carryout and cleaning process losses. The typical emission rate for working
emissions is 0.40 Ib/ft2/hr. Emission rate variability is caused by varying operational parameters
(EPA, 1993 a).
Downtime emissions occur when the heat to the sump (cleaning machine tank) is turned off and
the cleaning machine is not operating. Downtime emission mechanisms include evaporation of
solvent from the liquid solvent surface and subsequent diffusion into the air. Downtime emission
rates are estimated to be 0.30 Ib/ft2/hr (EPA, 1993a).
2.2.2 CLEANUP SOLVENTS
Emission sources from the use of cleanup solvents occur due to solvent evaporation. Typical
sources of evaporation are emissions from storage and handling of fresh and spent solvents,
solvent evaporation from the cleaned surfaces, evaporation as the solvent is splashed or sprayed,
fugitive emissions from flushing or spray systems, and evaporation from solvent-soaked rags or
cleaning tools. All solvent not recycled or sent to waste disposal is eventually emitted into the
atmosphere (EPA, 1994b).
2.3 FACTORS INFLUENCING EMISSIONS
Process operating factors largely influence emissions from cleaning machines and wipe cleaning.
These are:
• Leaks from manufacturing defects or equipment use;
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• Manual filling and draining of cleaning machines, especially with open buckets and
drums;
• Water/solvent separators;
• Start-up operations that cause solvent-laden air to be dispersed into the ambient
air when a new solvent vapor layer is being established;
• Shutdown operations that create emissions from evaporation of hot solvent;
• Emissions from distillation/sludge disposal that occur when spent solvent is
regenerated on-site:
• Excessive pooling/entraining of solvents on improperly oriented or drained parts;
• Solvent decomposition;
• Turbulence from high conveyor belt speeds and from manual removal of parts;
• Exhaust systems used without a carbon adsorber;
• Careless or improper use of cleaning tools (e.g., rags, brushes) or parts during and
after cleaning;
• Splashing and spilling of the solvent;
• Lack of a cover over solvent;
• Drying of parts in areas vented directly to the atmosphere; and
• Using adsorbent or porous items such as ropes and bags for handling solvent-
soaked items (EPA, 1993a, 1994b).
Emissions from cold cleaning machines may also be influenced by physical and chemical
properties of the solvent in the machine. These chemical factors include volatility, viscosity,
boiling points, and surface tension.
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2.4 CONTROL TECHNIQUES
2.4.1 CLEANING MACHINES
Techniques used to control emissions from solvent cleaning machines include both machine
design controls as well as improved operating procedures. Control technologies are based on the
size, design, application, and operation of the machines. Many of these control techniques are
required on all sizes of halogenated cleaners by the National Emission Standards for Hazardous
Air Pollutants: Halogenated Solvent Cleaning. Design features that control solvent emissions
from batch cold cleaning machines include:
• Increased freeboard ratio;
• Covers;
• Internal drainage rack; and
• Visible fill line.
Emissions from carburetor cold cleaning machines are well controlled because the cleaning
solutions contain water, which forms a layer above the solvent mixture in the tank. This water
layer significantly reduces the evaporation of methylene chloride into
the air (EPA, 1994a).
Design features that decrease emissions from batch vapor and in-line cleaning machines include
the following:
• Covers to eliminate drafts, control vapor/air interface emissions, and reduce
diffusion losses;
• Freeboard refrigeration devices that use a second set of cooling coils cool the air
directly above the vapor zone forming a cool air blanket and decreasing
diffusional losses;
• Hot vapor recycle or superheated vapor designs to create a zone of superheated
solvent vapor within the vapor layer. Cleaned parts are passed through the
superheated zone so the liquid solvent is evaporated prior to the part being
withdrawn from the batch or in-line cleaner. This method is expected to be used
mostly with chlorofluorinated solvents;
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• Increased freeboard height to decrease turbulence caused by room drafts and
increase the diffusion column;
• Vacuum chamber cleaning machines, a new type of batch cleaning machine that
decreases emissions by cleaning items in a sealed decompression chamber.
Emission concentrations of less than 50 parts per million (ppm) per cleaning cycle
have been reported (EPA, 1993a);
• In-line cleaning machines that can be designed with a U-turn to decrease entrance
and exit opening emissions by reducing drafts within the in-line cleaning machines.
Hanging flags over these openings will also reduce drafts;
• Freeboard refrigeration devices, which are similar to those used in batch cleaning
machines, to decrease emissions;
• A drying tunnel, which is an added enclosure that extends the exit area for drying
purposes, to reduce carryout emissions because evaporated solvent will sink back
into the vapor zone instead of the atmosphere;
• Rotating baskets to prevent the trapping of liquid solvent in parts and, therefore,
also reduce carryout emissions; and
• The use of carbon adsorption when a lip exhaust system is used to reduce solvent
concentration around the top perimeter of the cleaner. This is done by capturing
solvent vapors from peripheral exhaust ducts and ducting to an activated carbon
bed before the vent stream is exhausted to the atmosphere. The bed is desorbed
and the recovered solvent can be reused in the cleaning machine. This option may
increase solvent usage and waste if the solvent is not removed (EPA, 1994a).
Work practice modifications to decrease emissions from batch, in-line, and cold cleaning
machines include the following:
• Decreasing the speed at which parts are moved in and out of openings in a solvent
cleaning machine;
• Reducing room drafts;
• Limiting the horizontal area of the load to be cleaned to 50 percent or less of the
batch cleaning machine solvent/air interface area;
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• Spraying within the vapor zone at a downward angle helps control excess
emissions;
• Turning on the primary condenser before heating the solvent will reduce solvent
emissions at start-up;
• Allowing the cooling system to stay on after the heater is shut off will reduce
shutdown emissions;
• Using covers and freeboard refrigeration devices during downtime;
• Pumping the solvent into an airtight storage container during downtime;
• Detecting and repairing routine leaks on a regular schedule;
• Employing submerged pipe filling to decrease solvent transfer losses;
• Not bypassing carbon adsorbers during the desorption cycle; and
• Replacing the carbon bed often to prevent solvent breakthrough (EPA, 1993a).
Many of these work practices have been proposed in the New Source Performance Standards for
cold cleaning machines.
In addition, alternative cleaning solvents are being developed that may be substituted for
halogenated or nonhalogenated solvents in some cases. Alternative cleaning solvents are
generally grouped into the following categories: (1) hydrochlorofluorocarbons (HCFCs);
(2) aqueous; (3) semiaqueous; and (4) organic solvents. HCFCs are used to replace CFCs and
TCA; however, the use of these HCFCs are temporary because their production will be banned
by the Montreal Protocols. Aqueous cleaners can be substituted for solvents, because they use
water as the primary solvent with alkaline salts, surfactants, and other additives. Aqueous
cleaners can effectively clean inorganic or polar soils, oils, greases, and films. Semiaqueous
cleaners can be substituted for halogenated solvents. These solutions combine terpenes or
hydrocarbons with surfactants along with additives such as corrosion inhibitors. These cleaners
can effectively remove heavy grease, tar, waxes, hard-to-remove soil, and polar and nonpolar
contaminants. Organic solvent cleaners use no water and include oxygenated hydrocarbon
formulations, aliphatic hydrocarbons, esters, glycol ethers, alcohols, aromatics, and ketones.
These solvent alternatives should be identified and included in a VOC inventory.
Alternative cleaning technologies currently being developed include ice particle cleaning, plasma
cleaning, and cleaning with high-pressure gases, supercritical fluids, and ultraviolet ozone (EPA,
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1993a). The Solvent Alternatives Guide (SAGE), a software system distributed by EPA, can
provide recommendations for solvent replacements in cleaning operations.a
2.4.2 CLEANUP SOLVENTS
Emission reduction techniques for solvent cleaning activities include substituting a less volatile
solvent, reducing usage rates, and better management of the spent solvent and the wipes, rags,
other cleaning tools. Improved work practices are particularly important in minimizing
evaporative emissions.
2.5 REGULATORY STATUS
Based on the high usage and emissions of these cleaners throughout industry as well as the large
number of cleaners, the EPA determined that there is a great potential for exposure to HAPs
used as solvents in solvent cleaning machines. In addition, the EPA has determined that these
compounds present a threat of adverse effects to human health or the environment.
Control technique guidelines for solvent cleaning were established in 1977 for the control of
VOCs from solvent cleaning machines. These recommended requirements were adopted by 33
states. In 1980, a New Source Performance Standard (NSPS) was proposed for the solvent
cleaning industry. An Alternative Control Techniques (ACT) document for halogenated solvent
cleaning machines was published in 1989 after substantial review by industry. In 1994, a
National Emission Standard for Hazardous Air Pollutants (NESHAP) was promulgated to
regulate HAP emissions from halogenated solvent cleaning machines. The most recent
information about the regulatory status of solvent cleaning processes can be found on the EPA
Technology Transfer Network (TTN). See Chapter 1 of this volume for more information about
the EPA TTN.
2.5.1 SOLVENT CLEANING MACHINES
The halogenated solvent cleaning NESHAP promulgated in December 1994 (59 FR 61801,
December 2, 1994) established standards for both area and major sources of solvent cleaners
using HAP solvent. The NESHAP requires batch vapor solvent cleaning machines and in-line
solvent cleaning machines to meet emission standards reflecting the application of the maximum
achievable control technology (MACT). Area source batch cold cleaning machines are required
SAGE can be downloaded from the Control Technology Center (CTC) portion of the
EPA Technology Transfer Network (TTN) web site. For Internet access to the
EPA TTN, use: http://www.epa.gov/ttn/chief/.
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to achieve generally available control technology (GACT). The rule regulates the emissions of
the following halogenated solvents: methylene chloride, PERC, TCE, TCA, carbon
tetrachloride, and chloroform.
The proposed NSPS for cold cleaning operations requires sources to control emissions to the
level achievable by the best demonstrated technology (BDT) (FederalRegister, 1994). The
proposed BDT is a combination of equipment and work practice standards that allow for the best
emission control and enforceability. The BDT for large cold cleaning machines (>1.8 m2)
includes requirements for covers, drain racks, increased drain time, a visible fill line, a freeboard
ratio (the relationship of freeboard height divided by the interior width of the cleaning machine)
of at least 0.5, solvent pump pressure design limits, work practice labels, and reporting and
recordkeeping of solvent usage and disposition.
Twenty-six state agencies currently regulate in-line batch cold, batch vapor, and solvent cleaning
machines. These states are listed in Table 6.2-1. All 26 states require the use of control
equipment (e.g., covers, increased freeboard ratio) and specify work practices such as leak
detection and repair programs.
Consumption of TCA, CFC, and carbon tetrachloride is expected to decline rapidly in solvent
cleaning operations because of their scheduled phaseout as a result of the 1987 Montreal
Protocol on Substances that Deplete the Ozone Layer, Title VI of the 1990 Clean Air Act
Amendments (CAAA), and an Executive Order (58 FR 65018, December 10, 1993). Production
of these solvents is scheduled to cease in 1996.
However, their use will extend into the future. As a result of the Montreal Protocol and the 1994
solvent cleaning NESHAP, it is expected that 27 percent of the 1994 population of cleaning
machines will be replaced with new machines. The industry has been shifting from halogenated
solvents to nonhalogenated solvents, including aqueous and semi aqueous solvents.
2.5.2 CLEANUP SOLVENTS
Cleanup solvents have not been addressed by federal regulations in the Clean Air Act; however
the Alternative Control Techniques Document - Industrial Cleaning Solvents (EPA, 1994b) has
been developed to assist state and local agencies reducing VOC emissions.
Sixteen states currently regulate VOC emissions from cleanup solvents. In addition, regulations
at the city and county level have been developed to control VOCs. Approximately 46 percent of
these regulations have only recordkeeping requirements. Eleven agencies regulate control
equipment, and 14 agencies regulate work practices. Only five agencies limit VOC emissions,
and eight agencies regulate the type of solvents used. A summary of state, county, and city
regulations is shown in Table 6.2-2.
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2.5.3 SUMMARY
At this time, two federal rules apply to the solvent cleaning source category, the NESHAP
promulgated in 1994 for halogenated solvent cleaning and CAAA Title VI, which resulted from
the Montreal Protocol on Substances that Deplete the Ozone Layer. The NESHAP requires that
all machines (batch vapor, in-line, and batch cold cleaning machines) using halogenated solvents
either demonstrate that each machine emits less than a defined limit, or demonstrate compliance
through tracking of consumption. All affected facilities must submit an initial notification report
at a minimum.
TABLE 6.2-1
STATE REGULATIONS
State
Alabama
California Bay Area
California South Coast
Colorado
Delaware
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana
Michigan
Missouri
New York
Citation
Code of Alabama 22-28-14, 22-22A5, 6, 8
Regulation 8, Rule 16
Regulation IX Section 1 122
Colorado Code of Regulations Section 5
Dept. of Natural Resources; Regulation 24 Section 33
F.A.C. Rule 62-296.5 11
391-3-l-.02(w)-(2)(ff)
Title 35 Subtitle B Chapter I Section 215-182, 183, 184
326 IAC 8-3-1
KSA 65-3005, 3010
401 KAR 59:185
LAC 33: III Chapter 21, Subchapter C
Rule 336.1612, 1614, 1708, 1710
10 CRS 10
Title 6, Chapter 111, Subchapter A, Part 226
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North Carolina
Ohio
Oregon
Pennsylvania
South Carolina
Tennessee
Title ISA, Chapter 2, Subchapter2D
Title 3 745, Chapter 21
Chapter 340, Division 22-1 80, 182,
186
Title 25, Chapter 129.63
Chapter 6 1-62
TCA1200-3-18-.31
TABLE 6.2-1
(CONTINUED)
State
Texas
Utah
Virginia
Washington
West Virginia
Wisconsin
Citation
19 TexReg 3703, 30 TAC Chapter 115, Subchapter E,
Sections 115.412-115.419a
R307-1-4.9.4
VR 120-04-2403,
Title 173, Chapter
2404
173-490-40
4521-30
Natural Resources
423.03
Texas regulations are available on-line in hypertext mark-up language (HTML), PDF, or text versions on the World
Wide Web at http://www.tnrcc.state.us.
The processes regulated through the NESHAP use solvents that are mostly non-VOCs. The
exceptions are TCE and chloroform. The Montreal Protocol and associated CAAA Title VI
rules further reduce the likelihood of emissions of solvents that are being phased out after 1997.
Both the NESHAP and Title VT rules simplify tracking and information collection for these
processes and the chemicals used in them. It is important to note that the processes regulated
under the NESHAP may be limited in importance as VOC emitters, but would be important
processes to investigate for a HAP inventory.
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The cold cleaner NSPS planned to be promulgated in 1997 will affect cold cleaners with a
surface area greater than 1.8 m2 (19 ft2), which is a small proportion of cold cleaners that use
nonhalogenated solvents. Recordkeeping or reporting requirements have not yet been defined.
Cold cleaner processes must be evaluated for emissions to be included in VOC and HAP
inventories. No federal rules exist for the use of cleanup solvents. If solvent cleaning machines
covered by the NESHAP are inventoried as part of the point source inventory, then cleanup
solvent use and cold cleaners will be the only processes that need to be inventoried for a VOC
area source inventory.
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TABLE 6.2-2
CLEANUP SOLVENT REGULATIONS BY STATE
m
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State
Alabama, Jefferson County
Alabama, Huntsville
Arizona, State
Arkansas, State
California, State
California South Coast
California Bay Area
California, Ventura County
Colorado, State
Colorado, Denver City /County
Florida, Jacksonville
Control
Equipment
X
X
X
X
Work
Practice
X
X
X
X
X
X
Recordkeeping
X
X
X
X
X
X
X
X
Emission
Limits
X
Solvent
Type
Restrictions
X
X
X
Source Category
Regulated
Surface coating
operations
Surface coating
operations
Coating, ink, and adhesive
applications
Surface coating
operations
Surface coating
operations; aerospace
assembly
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TABLE 6.2-2
(CONTINUED)
1
State
Georgia, State
Indiana, State
Indiana, Evansville
Iowa, State
Iowa, Polk County
Kansas, State
Kentucky, State
Louisiana, State
Maryland, Baltimore
Michigan, Wayne County
Minnesota, State
Missouri, State
Nevada, Washoe County
North Carolina, Buncombe
County
Control
Equipment
X
X
X
X
Work
Practice
X
X
X
X
Recordkeeping
X
X
X
X
X
X
X
X
X
X
X
Emission
Limits
X
Solvent
Type
Restrictions
X
X
X
Source Category
Regulated
Lithographic printing,
metal parts cleaning
Paint manufacturing
Lithographic, rotogravure
and flexographic printing
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(CONTINUED)
1
State
Washington, Puget Sound
Wisconsin, State
Control
Equipment
X
Work
Practice
X
Recordkeeping
X
X
Emission
Limits
X
Solvent
Type
Restrictions
Source Category
Regulated
a Not all counties in Texas are affected. See footnote to Table 6.2-1 of this chapter for more information about Texas regulations.
b Recordkeeping is required for open-top vapor cleaning, convey orized cleaning, and lithographic printing.
0 Emission limits apply to open-top vapor cleaning only.
d Solvent type restrictions apply to lithographic printing only.
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
A number of methods are available for estimating emissions from solvent cleaning activities. The
choice of method depends on the desired degree of accuracy for the estimate while taking into
account the availability of data and resources. This section presents and ranks each of the
available methods. The first part of this section describes the general methods for estimating
emissions. The second part provides ways to determine the species-specific emission estimates.
Section 4 of this chapter describes the preferred method, and Section 5 covers the alternative
methods for estimating solvent cleaning activity emissions.
Emissions from solvent cleaning machines can also be considered to be point sources; therefore,
the estimation process for the source category must take this into account to prevent double-
counting of emissions. Additionally, emissions from solvent cleanup may be included as a part of
an industry- or process-specific emission estimate. The inventory preparer will need to evaluate
how these other sources are inventoried to ensure that double-counting is avoided. Sources of
solvent cleaning emissions that will not be addressed through the use of facility-specific data
include smaller cold cleaners (less than 1.8 m2 or 19 ft2) that are exempt from the NSPS, cleanup
solvent uses for permitted facilities that need not report all sources of the pollutant, and
nonpermitted facilities.
3.1.1 SOLVENT EMISSIONS
There are four general approaches available for estimating solvent emissions from solvent
cleaning:
• Surveys of:
Users
Suppliers who provide both equipment and solvent ("full service"
suppliers), for example, as a part of a service contract (cold cleaners
primarily)
Solvent suppliers
Equipment suppliers
• Facility-specific data;
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• Emission factors:
Population-based (per capita)
Employee-based (per employee)
Equipment-based (per unit in use); and
• Apportionment of national/regional/local area solvent uses ("top down"
approach).
Emissions from solvent cleaning activities occur as a result of solvent evaporation.
Consequently, annual emissions can be estimated based on the amount of solvent used per year.
Where the solvent is recycled, reclaimed, or disposed of off-site, the annual usage must be
adjusted for this amount. Also, if emissions are being captured by an air emissions control
device, this amount must be subtracted from the annual usage.
Table 6.3-1 summarizes and ranks the emission estimation methods for each of the categories of
solvent cleaning.
TABLE 6.3-1
SUMMARY OF AVAILABLE ESTIMATION METHODS
FOR SOLVENT CLEANING ACTIVITIES
Category
• Halogenated solvent
cleaning equipment
• Cold cleaning
equipment
• Solvents used for
cleanup
Methods
Surveys
Alternative 1
Preferreda
Preferred
Facility-specific
Data
Preferred
Alternative 1
Alternative 1
Emission Factors
Alternative 2
Alternative 2
Alternative 2
The final NSPS may require facility-specific data for larger cold cleaners. These data would become the preferred
method. A survey would still be needed for the smaller cold cleaners.
6.3-2
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3.1.2 SURVEYS
Survey methods can usually provide the most locality-specific information, and a higher quality
emission estimate. From a practical standpoint, the method is the most expensive, and it is often
difficult to identify facilities to participate in the survey and to assure that the group is a
representative subset of the entire population. The success of surveys depends heavily on the
rate and completeness of the responses, and many small facilities who use solvents for cleaning
do not have the resources to participate fully. An example of a large-scale survey for solvent
cleaning emissions can be found in Roe, et. al., 1995.
Of the four possible survey populations for this source category, data from the user is
theoretically more complete. Not only will the responses supply the kinds of solvent uses, the
associated types and quantities of solvents, and the level of emission control, but the detailed
information allows for better control strategy development. Furthermore, facilities that have
been identified as point sources can be more easily subtracted from the area source inventory so
that the inventory preparer can avoid double counting. Because of the wide variety of solvents
used for cleaning, surveying the user is the only practical approach for vapor cleaning machines.
Even then, the practical difficulties of surveying so many users of solvent cleaning equipment
limit the utility of this approach. Industries that may use solvent cleaning processes can be
identified through their SIC Codes in permit files, Chamber of Commerce listings, or local
property tax listings for solvent cleaning equipment. See Sections 2.1.1, 2.1.2, and 2.1.3 of this
chapter for SIC Codes of businesses that may use solvent cleaning.
Surveying the full services supplier (company supplying equipment, solvent, and/or service)
instead of the user is primarily feasible for cold cleaners. Surveys of suppliers who provide just
equipment or just solvent for cleaning machines are not generally recommended. These groups
are too removed from the use of the solvents and many assumptions must be made that introduce
a higher degree of inaccuracy in the emission estimates. More detail could be obtained by
surveying a subset of users for emissions from specific processes, then using information from
suppliers and recyclers to scale up emissions to the entire inventory area.
For solvent cleanup activities, a survey of solvent suppliers is one of the few options available
unless facility-specific data include these uses. Even though the solvent supplier may provide
usage data for the different solvents, the inventory preparer must still determine what other uses
the solvents might have and estimate how much is actually used for cleaning. As in the case for
cold cleaners, a survey of a small subset of users could be used to determine the type and
amounts of solvents used for cleaning, and emissions could be scaled up with a surrogate such as
amounts of solvents distributed or recyled.
3.1.3 FACILITY-SPECIFIC DATA
The use of facility-specific data that may already be in house at the state or local agency has some
clear advantages. With reporting requirements under the halogenated solvent cleaning NESHAP
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soon to take effect, all users of halogenated solvent cleaning equipment will be required to submit
an initial notification to state agencies. As a part of the notification, users also are to provide
annual solvent consumption and control practices information. Emissions can be estimated from
this information. A requirement for initial notification has also been proposed under the cold
cleaners NSPS, thus information for this part of the solvent cleaning category may soon be
available as well. Facility permit files such as those required by Title V are also a possible source
of information.
Solvent cleaning activities that either are not or are unlikely to be subject to the standards include
small cold cleaners and solvent cleanup. For some facilities, estimates may be available if the
facility has had to report these sources as a part of a permit application. These data would need
to be available for a majority of the facilities to be inventoried, or at least for a representative
number of the facilities where the number and type of facilities are known, and the data should be
reasonably current.
Facility-specific data are often already incorporated into point source inventories. The goal in an
area source inventory is to account for emissions that have not be included in the point source
inventory, but information being compiled is less detailed. In some cases, it may be possible to
define some assumptions about industries that allow for less data collection and compilation.
The first step in area source inventory preparation is to determine how much of the source
category emissions have been included in the point source inventory.
3.1.4 EMISSION FACTORS
Emission factors are an alternative estimation method to surveys and facility-specific data. Some
emission factors may need to be used in conjunction with surveys where a survey would be used
to determine activity (e.g., number of cold cleaners in use). Several emission factors are available
for VOCs from solvent cleaning machines. There are three types:
• Per capita;
• Per employee; and
• Per equipment unit in use.
Of these, per unit-in-use emission factors would be the most accurate, followed by per employee
emission factors. Per capita emission factors would be the least accurate because solvent
cleaning is not necessarily related to population.
For solvent cleanup emissions, solvent use and emission estimates presented in the EPA
document Alternative Control Techniques - Industrial Cleaning Solvents (industrial solvent
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cleaning ACT) are based on emission factors (EPA, 1994b). However, the emission factors are
not presented in that document.
To apportion national/regional/local area solvent uses, a "top-down" approach has the benefit of
providing a conservative estimate of emissions but runs the risk of overestimating the
contribution of solvent use for cleanup. All of the solvents used in cleaning have other
applications; therefore, care must be taken to subtract these other uses from the total if a
reasonable estimate of emissions attributable to solvent cleaning is to be determined. Identifying
these other uses and the associated solvent consumption can be difficult. Consequently, the
resulting emission estimate may be inaccurate. This method is not recommended as an inventory
method, and is perhaps best used as an order-of-magnitude reality check on estimates derived
using one of the recommended methods.
3.1.5 SPECIATED EMISSIONS (VOCs, HAPs)
Cold cleaners can be divided into two groups: carburetor cleaners and other cold cleaners.
Carburetor cleaners may use halogenated cleaners such as methylene chloride, and
nonhalogenated solvents. As a result, carburetor cleaners that use halogenated solvents are
subject to NESHAP reporting requirements. Other types of cold cleaning equipment use
nonhalogenated solvents and are not subject to NESHAP reporting. For batch vapor and in-line
degreasers, TCE is the only common solvent that is a VOC. In general, cold cleaner solvents are
not EPA-listed HAPs. For the batch and in-line degreasers, all the common solvents except
CFC-113 are EPA-listed HAPs.
Solvents frequently used in cleanup tend to be used both as pure solvents and as mixtures. The
solvents identified as commonly used in the industrial solvent cleaning ACT are listed in Table
6.3-2. Also shown is whether the solvent is classified as a reactive VOC for inventory purposes,
and/or a HAP. Please note that acetone and perchloroethylene are not listed as reactive VOCs.
For purposes of future inventory development, it is important to note that production of
CFC-113 and TCA, which are regulated under Title VI of the Clean Air Act Amendments, will
cease in 1996. Inventory preparers should also be aware that air toxics regulations may cause the
types of solvents used for cleaning to change further. Some companies have begun moving away
from the more toxic solvents as a part of corporate objectives to be more environmentally
conscientious.
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TABLE 6.3-2
COMMONLY USED CLEANUP SOLVENTS'*
Solvent
Acetone
Alcohols'1
Butyl Acetate
Cyclohexanone
Ethanol
Ethyl Acetate
Ethylbenzene
Ethylene Glycol
Isopropyl Alcohol
Methanol
Methyl Ethyl Ketone
Naphthaf
P er chl or oethy 1 ene
Toluene
Xylene
Volatile Organic Compound15
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Hazardous Air Pollutant0
No
e
No
No
No
Yes
Yes
Yes
No
Yes
Yes
g
Yes
Yes
Yes
EPA, 1994b,p. 3-15.
These are reactive VOCs.
The HAPs are subject to regulation under Section 112 of the 1990 Clean Air Act Amendments.
Total nonspecified production of Cu or lower unmixed alcohols.
This class may include the use of methanol, phenol and cresols, which are HAPs.
This solvent includes naphthas, petroleum naphtha, VM&P naphtha, mineral spirits, Stoddard solvent, naphthols,
and naphthanols.
Naphthas may include HAPs but generally only in trace amounts.
6.3-6
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
Speciated emission factors are not generally available. When a survey or facility-specific data
from reporting and permits are used for the inventory, VOC and HAP contents of the solvents
used can be obtained along with the rest of the inventory data. This is the preferred method of
speciating emissions for this source category. For vapor cleaning equipment, the solvent is
usually a single compound. The second alternative method for cold cleaners recommends using
cleaning unit solvent information from suppliers to develop a VOC emission factor. This solvent
information also can be used to estimate HAP emissions.
3.2 DATA NEEDS
3.2.1 DATA ELEMENTS
The data needed to estimate emissions depend on the estimation method selected. Minimum
elements for a survey on solvent cleaning machines would include:
• The type of solvent cleaning machine(s) used; and
• For each solvent cleaning machine:
The type of solvent(s) used;
Solvent composition and characteristics (supplying a material safety data
sheet will suffice);
How much solvent is used per year, on average (annual purchases can
serve as a surrogate);
How much of the solvent used is recycled off-site and not returned to the
site;
How much of the solvent used is disposed of off-site (i.e., is not recycled);
The types of emission controls in use; and
Work practices that may affect emissions.
For a cleanup solvents survey, information requested should include:
• The types of solvents used;
• A general description of the use for each solvent;
• The annual amount of each solvent used; and
• Any recycling, reclamation, and off-site disposal amount for the reporting year.
Facility-specific information will include initial reports submitted under the halogenated solvent
cleaning NESHAP that contain solvent usage and emission control information. For larger cold
EIIP Volume III 6.3-7
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
cleaners, similar reports may be required under the cold cleaners NSPS as well. For smaller cold
cleaners and solvent cleanup, data would only have been provided to the state as a part of
another requirement, such as a part of the facility's operating permit required under Title V. To
use this information, facilities likely to do solvent cleaning must be identified, then the facility
files must be located and the relevant data extracted.
If an emission factor approach is to be used, the relevant activity data must be collected.
Adjustments may be necessary if the activity data do not exactly match the area to be inventoried.
Additionally, if speciated emissions are desired, solvent composition information is needed that
can be applied to the VOC emission factor. Further adjustments may also be needed depending
on the use of controls.
3.2.2 APPLICATION OF CONTROLS
In determining emissions, the inventory preparer should take any existing emission controls into
account. The importance of the emission controls on the estimate depends on how the estimate
is derived. If, for example, solvent use is the basis for the estimate, the only control technique
that will affect emissions is one where the solvent evaporative losses are captured but not
recovered and returned to the process. As another example, if the estimate is based on the rate
of evaporation from the exposed surface of the cold cleaner, then controls that prevent
evaporation must be considered.
Some controls will be established by regulatory requirements; therefore, the inventory preparer
can assume some percentage of the industry is applying the required controls and can adjust the
emission estimate accordingly. For example, by 1997 the halogenated solvent cleaning NESHAP
will impact all solvent cleaning machines using halogenated solvents. Similarly, once the cold
cleaners NSPS has been promulgated, larger cold cleaners will be subject to requirements that
reduce emissions. These issues are discussed in Chapter 1 of this volume, Introduction to Area
Source Emission Inventory Development., in the section on Control, Rule Effectiveness, and Rule
Penetration.
3.2.3 SPATIAL ALLOCATION
Spatial allocation may be needed in two cases during inventory preparation: (1) allocation of
state or regional activity to a county level, and (2) allocation of county- level emission estimates
to a modeling grid cell. Facility-specific data may be used if they are available and
comprehensive. However, more often a surrogate for activity must be used to approximate
spatial allocation for solvent cleaning activities. One readily available surrogate is employment
data by SIC Code published by the U.S. Department of Commerce, Bureau of the Census in
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CHAPTER 6 - SOLVENT CLEANING
County Business Patterns* This is preferred over population data because employment is
expected to be better correlated to solvent cleaning than population. SIC codes for industries
that use solvent cleaning are listed with the cleaning type descriptions in Section 2.1 of this
chapter.
3.2.4 TEMPORAL RESOLUTION
For most solvent cleaning activities, seasonal variability is not expected. Daily variations may
apply for some of the industries. Some industries operate seven days per week, others only five
days. Some industries are likely to operate two or three shifts per day, others may only have one.
Information on the operating schedule may be available from existing files at the agency doing
the inventory. Alternatively, State Implementation Plan (SIP) Inventory Guidance material
provides a default value of uniform activity throughout the year, six days per week (EPA, 1991).
3.2.5 PROJECTING EMISSIONS
In many instances, the inventory will be used as the baseline from which future emissions are
estimated. Projecting emissions is discussed in Chapter 1 of this volume. The most common way
to project emissions is to apply a growth factor to the baseline estimate. If surveys are used to
collect data, another option is to request the forecasting information from the recipient.
The following should be used when emissions are calculated by methods other than use of an
emission factor (EPA, 1993b):
EMISPY = EMISBYO *
1
CE
^J— 'pv
100
BY
100
^
100
, RElBY
100
. RPPY)
100 j
. RPRY]
100 j
* GF
where:
EMIS
'PY
EMIS
BYi0
Projection year emissions for an ozone season, typical weekday
(mass of pollutant/day)
Base year ozone season actual emissions (mass of pollutant/day)
Projection year control efficiency (percent)
See the publication for the inventory year, which can be obtained from the U.S. Bureau of
the Census, Department of Commerce, Washington, D.C.
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CHAPTER 6 - SOLVENT CLEANING
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CE
RE
RE
RP
RP
GF
'BY
'PY
'BY
PY
BY
Base year control efficiency (percent)
Projection year rule effectiveness (percent)
Base year rule effectiveness (percent)
Projection year rule penetration (percent)
Base year rule penetration (percent)
Growth factor (dimensionless)
The following equation should be applied when emissions are calculated using an emission factor
and control efficiencies are used to reflect current or future control strategies (EPA, 1993b):
EMISPY = ORATEBYO * EMFpYpc *
CE
PY
RE
PY
100
100
RP
PY
100
* GF
where:
EMIS
'PY
EMF
PY, pc
CE
RE
'PY
'PY
RPpY
GF
Projection year emissions for an ozone season, typical weekday
(mass of pollutant/day)
Base year operating rate (activity level): ozone season, daily
(production units/day)
Projection year pre-control emission factor (mass of
pollutant/production unit)
Projection year control efficiency (percent)
Projection year rule effectiveness (percent)
Projection year rule penetration (percent)
Growth factor (dimensionless)
6.3-10
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
4.1 EMISSION ESTIMATION METHODOLOGIES
The preferred method for estimating emissions from solvent cleaning operations varies with the
type of solvent cleaning activity. For halogenated solvent cleaning machines, use of the facility-
specific data submitted under the halogenated solvent cleaning NESHAP is the preferred method.
For cold cleaners until the NSPS is promulgated, the preferred method is to conduct a survey of
suppliers. For solvent cleanup, the preferred method is to conduct a survey of a subset of users.
4.2 FACILITY-SPECIFIC DATA
Facility-specific data already collected by the agency can be a good source of emissions
information. First, the inventory preparer must identify:
• Facilities reporting under the halogenated solvent cleaning NESHAP; and/or
• Facilities permitted as VOC and/or HAP sources.
The initial report required by the halogenated solvent cleaning NESHAP must include an
estimate of annual halogenated HAP solvent consumption for each solvent cleaning machine.
These reports are due to EPA by August 29, 1995 (59 FR 61814, December 2, 1994). These
numbers may or may not include amounts sent off-site for recycling, reclamation, or disposal, and
the emissions calculated may overestimate emissions. To address this potential problem, the
inventory preparer may be able to identify cases where no adjustment appears to have been made
by comparing all the reports by cleaning machine type and looking for outliers. A follow-up with
the facility can be used to determine whether all necessary adjustments have been made.
Many of the solvent cleaning machine reports received to comply with the NESHAP will be large
individual emitters or part of an operation that emits large amounts of VOCs or HAPs. The
facilities that will be reported as point sources should be identified to avoid double counting, but
data from these reports do not need to be compiled as part of the area source inventory.
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
4.3 SURVEYS
An example of a survey of solvent cleaning operations and the survey's results can be found in
Roe et al. (1995). Specific discussion of surveys for area sources is provided in Chapter 1 of this
volume. However, the general approach for surveys is as follows:
• Identify the industries most likely to have solvent cleaning operations and the
facilities to be surveyed within each of these industries. Use the data quality
objectives of the inventory to determine the size of the survey subset.
Manufacturing directories, or local or state property tax records may be useful for
identifying businesses with certain types of equipment.
• Decide whether to prescreen survey recipients. Prescreening can be helpful to
identify survey recipients when a subset of facilities are to be surveyed, and to
define scaling factors for scaling up the results of the survey. Conduct
prescreening;
• Develop and distribute a survey;
• Design a database if the number of responses is expected to be large;
• Collect surveys, follow up with respondents if there are any questions, and
transfer information to the database; and
• Compile the data and develop the emission estimate(s).
4.3.1 COLD CLEANERS
For cold cleaners, a survey of the equipment suppliers who also provide service for the facility
("full service" suppliers) is the preferred method. These suppliers are limited in number and
maintain accurate records on solvent usage because this is the basis upon which the facility is
billed. A potential drawback to this method is that some suppliers may be reluctant to report the
information needed for an emission estimate. In addition, some cold cleaning activity can
overlooked if not all of the suppliers are included in the survey or if some facilities in the
inventory area service their own equipment. An example survey is provided in Figure 6.4-1. The
survey may be designed to identify some of the cold cleaners that may be overlooked (see Part III
of Figure 6.4-1). Point source emissions from cold cleaners will need to be totaled and then
subtracted from the area source estimate.
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FIGURE 6.4-1. EXAMPLE SURVEY FOR COLD CLEANING FULL SERVICES SUPPLIERS
SURVEY NO:
DATE:
PAGE: 1 of
PARTI
Company Name:.
Address:
Contact Name, Title:.
Contact Phone No:
Region for which information is provided:..
PART II
For equipment that you service, please provide the following:
Model
Number
Equipment Description "
No. of Services
in year
Solvent Type
Annual
Amt. of Solvent
Delivered
"(gal)
Annual
Amt. of Solvent
Returned
(gal)
a Attach equipment information.
b Attach material safety data sheets.
PART III
For equipment that you sold sincevear* but do not service, please provide the following:
Model
Number
Equipment Description
Solvent Type0
Description of Client's
Business"
Typical Annual Solvent
Usage per Unit (gal)e
a Select a time period based on the datedness of the existing equipment population datab Attach equipment information.
0 Attach material safely data sheets.d If known. e Provide a range if necessary.
1
O
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
4.3.2 CLEANUP
The preferred method for estimating emissions from solvent cleanup is to conduct surveys of key
industries using solvents in this manner. To identify and survey all industries that use solvent for
cleanup would be impractical. A recent EPA publication, Alternative Control Techniques
Document - Industrial Cleaning Solvents (EPA, 1994b),identifies 15 industries using solvents for
cleanup and surveyed 6 of these for specific solvent cleanup information. The 15 industries and
their solvent uses are shown in Table 6.4-1. Given resource constraints, state and local agencies
should focus on these first. Some industries may not be located in the areas to be inventoried;
however, the agency may want to include others in their area that they have reason to believe
may have significant solvent cleanup emissions. The agency may also want to limit the survey to
facilities that are area sources. Otherwise, emissions calculated from the survey data will need to
be corrected for point source emissions.
An example survey for solvent cleaning activities used by the EPA is provided in Appendix A.
Questions were developed to collect the data based on a material balance around a unit operation
system (UOS) at the facility. The UOS provides a framework for describing and understanding
the cleaning activities. Based on the survey results, nine such UOSs appear to represent most
solvent cleanup activities. These are spray gun cleaning, spray booth cleaning, large
manufactured parts cleaning, small manufactured parts cleaning, equipment cleaning, floor
cleaning, line cleaning, tank cleaning, and parts cleaning (each column in Table 6.4-1 represents a
UOS). General descriptions of these UOSs are provided as an attachment to the survey; more
detailed descriptions with diagrams are provided in the Industrial Cleaning Solvents ACT (EPA,
1994b).
Although the Industrial Cleaning Solvents ACT specifically excluded metal parts cleaning using
vapor and cold cleaning equipment [this is addressed in another report: Control of Volatile
Organic Emissions from Solvent Metal Cleaning (EPA-450/2-77-022)], a survey using the
UOSs may collect this information as well. To avoid double-counting between cleanup
operations and solvent cleaning machine use of solvents, these results must be compared to
estimates derived from solvent cleaning equipment. The solvent cleaning equipment emissions
will need to be subtracted from the total.
4.3.3 SURVEY COMPILATION AND CALCULATIONS
From the survey data collected, emissions can be calculated for a given facility as the difference
between annual solvent use and the amount of solvent that is sent off-site for recycling,
reclamation, or is otherwise captured such as in an emission control device. The assumption is
that any solvent that is not accounted for through recycling, reclamation, or captured by a control
device like carbon adsorption, evaporates.
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TABLE 6.4-1
SOLVENT CLEANUP ACTIVITIES BY INDUSTRY3
1
Industry
Automotive-Manufacturing
(SIC Code 3711)
Automotive-Parts/Access.
(SIC Code 3714)
Automotive-Trucks and Buses
(SIC Code 3713)
Automotive-Stamping
(SIC Code 3465)
Electrical Equipment
Furniture
Magnetic Tape
Packaging
Photographic Supplies
(chemicals)
Spray
Gun
X
X
X
X
X
X
Spray
Booth
X
Equip.
X
X
X
X
X
X
X
Floor
X
X
X
X
Line
X
X
Tank
X
X
X
Parts
X
X
X
X
X
X
X
X
Large
Mfd
Components
X
X
X
Small
Mfd
Components
X
X
X
X
o
5
-o
al
O)
CO
O
i—
I
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P
1
I
Adapted from EPA, 1994b, Table 3-6, p. 3-19. No data were provided for adhesives, autobody refinishing, fiber-reinforced plastic (FRP)
boats, offset lithographic printing, plastics, or rotogravure printing.
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CHAPTER 6 - SOLVENT CLEANING
9/16/97
Emissions are calculated from survey data by the following equation:
Annual
emissions
Annual
= solvent -
use
Annual amount
of solvent
recycled
off-site
Annual amount
of solvent
reclaimed
off-site
Annual amount
of solvent sent
off-site for disposa
Where only a subset of the population of facilities provided data, the estimated emissions will
need to be scaled up. This is discussed in Chapter 1 of this volume; however, for this source
category, scaling can be done using the total number of facilities, the total number of employees,
or the total number of units in use. The choice of which to use will depend on which best
represents the population of interest, and how accurate and readily available the chosen scaling
factor may be.
6.4-6
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
To estimate emissions from halogenated solvent cleaning equipment, the alternatives to the
preferred method are to conduct a survey and to use emission factors. For cold cleaners and
solvent cleanup, the alternatives are to use facility-specific data and emission factors. Surveys
were described in Section 4 and are covered in detail in Chapter 1 of this volume. Additional
information concerning facility-specific data and use of emission factors is provided below.
5.1 SOLVENT CLEANING EQUIPMENT
5.1.1 FACILITY-SPECIFIC DATA
Use of facility-specific data is the first alternative method for estimating emissions from cold
cleaners and for the use of solvents for cleanup. This method is usable only if facility-specific
information is available for a reasonable subset of cold cleaners and operations where cleanup
solvents are used. The subset will need to include a cross-section of the industries, processes,
and solvents present in the inventory area, or there will need to be a way to estimate emissions
from occurrences that have not been included in the subset. Facility-specific information will be
available for facilities that are permitted as VOC and/or FLAP sources as well as facilities that are
reporting under the NSPS requirements once the cold cleaner NSPS is promulgated.
Sources of solvent cleaning emissions that will not be addressed through the use of facility-
specific data include smaller cold cleaners (less than 1.8 m2 or 19 ft2) that are exempt from the
NSPS, cleanup solvent uses for permitted facilities that need not report all sources of the
pollutant, and nonpermitted facilities. As a result, these will need to be addressed separately.
This step may have already been completed during the point source inventory development
process; therefore, preparing the point and area source inventories for this source category
should be coordinated to minimize duplication of effort. The remaining uncounted emissions can
then be estimated by either scaling up the existing data or by using one of the other alternative
methods.
5.1.2 EMISSION FACTORS
Emission factors are another alternative to surveys for estimating emissions from solvent cleaning
equipment, and these are available in EPA publications. Recent data on cold cleaners collected
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
by the EPA as a part of NSPS development for cold cleaners are reproduced in Table 6.5-1
(EPA, 1994c). Submitted by Safety-Kleen, these data represent model-specific emission
estimates for several of their cold cleaner models. Table 6.5-1 provides typical annual solvent
loss estimates for five cold cleaner models, and for five service intervals. Service intervals for
these machines vary based on how often customers need the solvent in their cold cleaners
replaced. A longer service interval indicates a lower level of use of the cold cleaner and results in
lower emissions, which are reflected in the lower solvent loss numbers. Although manufacturer
models will vary, the broad range is probably representative of the industry. Furthermore,
Safety-Kleen holds a significant share of the market so these data will be accurate for a high
percentage of the cold cleaners in use.
Two emission factors from Procedures for the Preparation of Emission Inventories for Carbon
Monoxide and Precursors of Ozone: Volume I: General Guidance for Stationary Sources
(EPA, 1991) may be used to estimate emissions from solvent cleaning. Based on how the
category is described, this does not include cleanup solvent uses. The basis for the emission
factors is 1989 industrial solvent consumption and (1) 1989 U.S. population (245.7 million) and
(2) industrial employment in SIC Codes 25, 33-39, 417, 423, 551, 552, 554-556, and 753. Per
capita and per employee emission factors are presented in Table 6.5-2.
State and local agencies may want to update the emission factors using the same or similar
references used in the EPA Procedures document and recalculating the emission factors to reflect
more recent usage, and to reflect the delisting of acetone and PERC as reactive VOCs. The
solvent usage data in EPA' ^Procedures report were taken from Industrial Solvents - Winter
1989 (Frost and Sullivan, Inc., New York, NY, 1990), Chemical Economics Handbook (SRI
International, Menlo Park, CA, 1991), Chemical Marketing Reporter (Schnell Publishing
Company, Inc., New York, NY, 1991) and Chemical Products Synopsis (Mannsville Chemical
Products Corporation, Asbury Park, NJ, 1991). Population data are collected by the U.S.
Department of Commerce, Bureau of the Census, and published in Statistical Abstracts of the
United States (year). The employment data are available from Employment and Wages Annual
Averages (year), published by the U.S. Department of Labor, Bureau of Labor Statistics. Such
data may also be found in County Business Pattern^, published annually by the Bureau of the
a See the publication for the inventory year, which can be obtained from the U.S. Bureau of
the Census, Department of Commerce, Washington, D.C.
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.5-1
1994 SAFETY-KLEEN EMISSIONS DATA FOR COLD CLEANERS3
Service Interval
(weeks)
4
5
6
7
8
Typical Annual Solvent Loss (gallons)15'0
by Safety-Kleen Model Numberd
14
19
16
13
11
10
16
33
26
22
19
17
30
51
41
34
30
26
34
64
52
44
38
34
44
81
66
55
48
43
a EPA, 1994c. Safety-Kleen caveat: emissions may not reflect true losses of a particular customer's equipment.
Emissions include losses during machine use, carry-off on parts, and carry-off in small cups for remote cleaning.
b Based on SK-105 Solvent: 85% mineral spirits, 12% C8 and aromatics, 1% xylene, 0.5% each toluene and
ethylbenzene, 0-1% chlorinated solvents (TCA, PERC).
0 To obtain the weight of solvent loss, multiply number of gallons by 6.5 pounds per gallon.
d From the reference, descriptions of the models are as follows:
Model 16: 9-gallon parts cleaner
Model 30: 17-gallon parts cleaner
Census. Local planning departments may also have population and employment data that are
specific to the area of interest.
Because EPA emission factors are based on national consumption and may not accurately reflect
local consumption, state and local agencies may consider using local
solvent usage data where these are available (a top-down approach). In some cases, local solvent
usage data may be available but the total includes more uses than just solvent cleaning. These
additional uses must be identified and quantified, then subtracted from the total. Because such
information is typically limited and the level of effort is significant, the cost of using this approach
outweighs the benefit (accuracy) of the resulting estimate.
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.5-2
PER CAPITA AND PER EMPLOYEE SOLVENT CLEANING EMISSION FACTORS
(EPA, 1991)
Subcategory
Solvent Cleaning
(total)
SIC Codes
25, 33-39, 417,
423, 551, 552,
554-556, 753
Per Capita Factor
(Ib/yr/person)
VOCs
4.3
Organics
7.2
Per Employee Factor
(Ib/yr/employee)
VOCs
87
Organics
144
Cold Cleaning
Automobile Repair
Manufacturing
417,423, 551,
552, 554-556,
753
25, 33-39
2.5
1.1
2.5
1.1
270
24
270
24
Vapor and In-Line Cleaning
Electronics and
Electrical
Other
36
25, 33-39, 417,
423, 551, 552,
554-556, 753
0.21
0.49
1.1
25
29
9.8
150
49
5.2 SOLVENT CLEANUP ACTIVITIES
Alternative methods for estimating solvent cleanup emissions are the facility-specific method
described in Section 5.1.1 and emission factors developed from information collected for the
Industrial Cleaning Solvents ACT, which will be described here (EPA, 1994b).
The Industrial Cleaning Solvents ACT provides estimates of solvent amounts used at the national
level for cleanup for 15 industries (Table 6.5-3). These estimates were drawn from references
that were prepared as early as 1979 and as recently as 1993. For 9 of the 15 industries, the ACT
provides estimates of national VOC emissions from cleanup
6.5-4
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
processes (Table 6.5-4). These estimates are based on usage-per-employee and emissions-per-
employee factors from studies at a small number of test facilities.
There are limitations to using this study for inventory preparation that should be kept in mind.
Although these industries are not the only industries that use the solvent cleanup process, they
are thought to be most significant sources. The study had to use assumptions based on studies of
only a few facilities for each industry. The study was limited to 15 solvents (see Table 6.3-2),
but there may be others that could also be used as cleaners. Using a material balance method to
develop an emission factor for this process will result in a very conservative estimate for
emissions. Some of the solvent can be expected to be collected and reclaimed off-site or
disposed of in some other manner. Even with these limitations, these estimates provide industry-
specific estimates of a subcategory of solvent cleaning that is otherwise difficult to characterize
and may have previously not been included in emission estimates.
Please note that in order to avoid double-counting within the area source inventory, inventory
preparers should note when other area source categories include solvent cleanup. In particular,
area source emission estimating methods for the printing, packaging, and furniture (as a surface
coating process) industries and the autobody refmishing industry may include solvent cleanup
emissions.
Emission factors for the nine industries listed in Table 6.5-4 can be developed by dividing the
national emissions number by either national employment for that industry or by national
population.
The national numbers presented in Tables 6.5-3 and 6.5-4 may be used to estimate local
emissions for the 15 industries by developing a national per employee or per capita emission
factor. A per employee factor should more accurately reflect emissions, but
the per capita emission factor will be easier to calculate. A per employee emission factor is
calculated from any of the national emission estimates by the following steps:
• Determine the national-level number of employees in the industry. Employment
information at the national level can be found in the Census Bureau report,
Statistics for Industry Groups and Industries.*
a See the publication for the year matching the year of the usage estimate, which can be
obtained from the U.S. Bureau of the Census, Department of Commerce, Washington,
D.C.
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TABLE 6.5-3
ESTIMATES OF THE AMOUNT OF VOC CLEANING SOLVENT USED BY INDUSTRY, x 103 TONS/YRa
m
T5
Industry (SIC Code)
Automotive-Manufacturing
(3711)
Automotive-Trucks and
Buses (37 13)
Automotive-Parts/Access.
(3714)
Automotive- Stamping
(3465)
Adhesives
Packaging0
Plastics
Furniture0
Rotogravure Printing0
FRP Boats4
Autobody Refinishing
Electrical Equipment
Magnetic Tape
Reference Year
1990
89-410
73-330
19-88
7.8-35
1988
b
14-62
8.3d
5.5
1979
46-210
28-130
16-72
e
1988
26-120
1993
72
16
7.7
1.0
30
230
5.6
11
Low
72
16
7.7
1.0
46
30
28
19
14
8.3
7.8
5.6
5.5
High
410
16
7.7
1.0
330
30
130
230
62
8.3
120
5.6
11
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TABLE 6.5-3
(CONTINUED)
Industry
Offset Lithographic Printing
Total
Reference Year
1990
1988
1.1 -6.6e
1979
1988
1993
Low
1.1
270
High
6.6
1,400
Adapted from EPA, 1994b, pp. 3-11.
This range may represent usage in more than the 3711 SIC Code subcategory.
Please note that for these industries, cleaning solvent use may be estimated as part of another area source category. Preparation of emission
inventories for these categories should be coordinated.
FRP = fiber-reinforced plastic.
Estimate based on a usage equals emissions assumption.
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TABLE 6.5-4
NATIONWIDE VOC SOLVENT USAGE AND EMISSION ESTIMATES FOR SELECTED INDUSTRIES, TONS/YRa
(EPA,1994e)
Industry
Equipment
Cleaning
Floor
Cleaning
Large
Manufd.
Component
Cleaning
Line
Cleaning
Parts
Cleaning
Small
Manufd.
Component
Cleaning
Spray
Booth
Cleaning
Spray
Gun
Cleaning
Tank
Cleaning
Total
Automotive - Manufacturing
Solvent
Usage
Emissions
220
220
570
570
8,400
7,700
14,000
130
129
130
180
180
17,000
15,000
28,000
9,500
3,100
110
72,000
34,000
Automotive - Trucks and Buses
Solvent
Usage
Emissions
6,900
6,900
8,800
8,800
16,000
16,000
Automotive - Parts/Accessories
Solvent
Usage
Emissions
15
15
7,600
2,100
130
55
7,700
2,200
Automotive - Stamping
Solvent
Usage
Emissions
Electrical Eq
Solvent
Usage
Emissions
1,000
320
13
13
1,000
330
uipment
500
450
77
77
1,900
520
290
220
2,800
1,100
5,600
2,400
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TABLE 6.5-4
(CONTINUED)
Usage and emission values are from a 1990 report.
Estimates based on nationwide extrapolation of usage-per-employee factors from surveyed plants (using total plant employment).
Totals are different due to rounding.
Industry
Furniture
Solvent Usage
Emissions
Equipment
Cleaning
7,300
5,600
Floor
Cleaning
Large
Manufd.
Component
Cleaning
900
840
Line
Cleaning
39,000
3,800
Parts
Cleaning
1,800
540
Small
Manufd.
Component
Cleaning
130
72
Spray
Booth
Cleaning
Spray
Gun
Cleaning
180,000
36,000
Tank
Cleaning
Total
230,000
47,000
Magnetic Tape
Solvent Usage
Emissions
670
230
330
6.6
2,400
440
7,700
430
11,000
1,100
Packaging
Solvent Usage
Emissions
1,300
960
5,900
2,500
23,000
3,500
30,000
7,000
Photographic Supplies
Solvent Usage
Emissions
Total Usage0
Total Emissions0
4,400
110
14,000
7,600
3.1
3.1
6,600
3,200
16,200
15,400
53,000
3,900
130
1.3
38,000
7,600
610
490
17,000
15,000
5.3
5.3
220,000
55,000
36,000
360
47,000
900
41,000
480
410,000
109,000
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
• Divide the usage estimate by the national-level employment. The resulting
number is a per employee emission estimate for that industry for that year.
• Determine the employment in the industry for the inventory area and the inventory
year. Using local employment data or employment data from the U.S. Census
Bureau report, County Business Patterns.
• Local employment multiplied by the per employee emission factor calculates the
emission estimate for the industry.
A per capita emission factor is calculated by dividing the usage value by the national population
for the year of the data.
6.5-10 EIIP Volume III
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QUALITY ASSURANCE/
QUALITY CONTROL (QA/QC)
Prior to inventory preparation during the planning process, the agency must delineate the data
quality objectives for the inventory. As a part of these objectives, the agency may elect to
establish specific goals for individual categories. Depending on the data quality objectives, the
QA and QC methods to be applied will vary. Quality Assurance Procedures., Volume VI of this
series of reference volumes, is dedicated to the discussion of methods to be used to ensure the
development of a quality inventory. QA for area source inventories is discussed in Chapter 1 of
this volume.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The preferred method will produce the most accurate estimate of emissions; however, surveys
can be an expensive undertaking. Furthermore, the success of the survey depends heavily on the
rate and completeness of the responses. The accuracy of facility-specific data and the top-down
approach vary depending on the availability of information. Both can be resource-intensive too.
Emission factors are the easiest method but may be relatively inaccurate.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
One way to evaluate the estimates calculated using each of the alternatives is to calculate the
DARS scores for each. The DARS methodology is presented in the Quality Assurance
Procedures volume. The resulting scores for estimates based on facility-specific data for
halogenated solvent cleaning equipment, surveys of cleaning solvent equipment uses, and uses of
emission factors are presented in Tables 6.6-1 through 6.6-5. All scores assume that good
QA/QC measures have been performed and that no significant deviations from the prescribed
methods have been made. If these assumptions are not met, new DARS scores should be
developed according to the guidance in the Quality Assurance Procedures volume.
6.1.2 SOURCES OF UNCERTAINTY
Another way to assess the emission estimate is to look at the associated uncertainty. For
estimates derived from survey data, the uncertainty can be quantified. Similarly, the uncertainty
can be determined for the facility-specific data if the basis for the emission estimate is provided
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
(see Quality Assurance Procedures, Volume VI, Chapter 4). Statistics needed to quantify the
uncertainty for the emission factor and top-down approaches are incomplete.
For a per capita emission factor, the uncertainty of the resulting emission estimate depends on
how closely related solvent cleaning activities are to population and how well the emission factor
represents the area to be inventoried. Although it is reasonable to expect more commercial and
industrial activity near centers of population, a statistical correlation has not been attempted;
therefore, the association between population and solvent cleaning activity is weak. A per
employee emission factor assumes that solvent cleaning is related to employment in specific
industries identified as conducting solvent cleaning activities. Again, the estimate depends on
how well the emission factor represents local practices. Emissions based on a per unit emission
factor would intuitively seem to produce a more accurate estimate than those derived from the
other types of emission factors but uncertainty is introduced in determining the total number and
types of units in use. There is also variability in emissions that depend on the unit type and
operating practices that may not be accommodated in the emission factor. A choice of emission
factor based on the uncertainty would require an assessment of the basis for each.
Determining sources of uncertainty associated with an estimate derived using the top-down
approach begins with the solvent usage data. Each step taken to apportion the total solvent
usage to solvent cleaning in the inventory area introduces additional sources of uncertainty.
Even if care is taken in the apportionment of solvent usage, the resulting estimate may not truly
represent emissions, for example, where local recycling or add-on controls have not been taken
into account.
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.6-1
FACILITY-SPECIFIC EQUIPMENT SOLVENT CLEANING: PREFERRED FOR HALOGENATED
CLEANERS, ALTERNATIVE 1 FOR NONHALOGENATED
COLD CLEANING AND SOLVENT CLEANUP
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores"
Factor
0.7
1.0
1.0
1.0
0.93
Activity
0.9
1.0
1.0
0.7- 1.0
0.9-0.98
Emissions
0.63
1.0
1.0
0.7- 1.0
0.83 -0.9
This is essentially a point source methodology. Temporal activity depends on whether an annual, daily, or other time
period is needed (The score for when solvent consumption annual emissions are used to calculate daily emissions is
0.7).
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.6-2
SURVEY OF SOLVENT CLEANING USES (EQUIPMENT OR SOLVENT) IN THE
INVENTORY REGION: PREFERRED FOR NONHALOGENATED CLEANERS AND
SOLVENT CLEANUP, ALTERNATIVE 1 FOR HALOGENATED COLD CLEANERS
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scoresa
Factor
0.7
0.8
0.8
1.0
0.83
Activity
0.7
0.7 - 0.9b
0.9
0.9- 1.0b
0.8-0.88
Emissions
0.49
0.56-0.72
0.72
0.9- 1.0
0.67 - 0.72
a Scores for activity will depend on how good and thorough the survey is. These scores assume that less than 100
percent of the population is sampled; therefore, the estimate is scaled up by the ratio of the number surveyed to the
number in the population.
b Activity score ranges depend on the accuracy of the surrogate used to scale the survey subset to the entire inventory
area.
6.6-4
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.6-3
COLD CLEANING UNIT EMISSION FACTOR: ALTERNATIVE 2 FOR COLD CLEANERS
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.3 -0.4
0.7
0.7
0.8
0.63 -0.65
Activity
0.6-0.7
0.7
0.7
0.7
0.68-0.7
Emissions
0.18-0.28
0.49
0.49
0.56
0.43 - 0.46
TABLE 6.6-4
SOLVENT CLEANUP EMISSION FACTORS: ALTERNATIVE 2 FOR SOLVENT CLEANUP
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.3 -0.5
0.6
0.7
0.5
0.53 -0.58
Activity
0.9
0.5
0.8
0.6
0.7
Emissions
0.27 - 0.45
0.3
0.56
0.3
0.36-0.41
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.6-5
NATIONAL FACTORS APPLIED TO LOCAL ACTIVITY DATA (NUMBER OF EMPLOYEES):
ALTERNATIVE 2 FOR ALL CLEANING TYPES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores3
Factor
0.3
0.5-0.6
0.5
0.5-0.8
0.45-0.55
Activity
0.9
0.5-0.6
0.8
0.6
0.7-0.73
Emissions
0.27
0.25-0.36
0.40
0.3 -0.48
0.31 -0.40
Notes:
Factor measurement: does not include all losses.
Source specificity: cleanup solvent use may not be included.
Spatial: national taken to the county level.
Temporal: annual taken to the daily level, 1989 to inventory year.
Activity: assumes some estimation/scaling from national or state data was used. Also, assumes some variability in
employment with the year and from year to year.
6.6-6
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.6-6
NATIONAL FACTORS APPLIED TO LOCAL ACTIVITY DATA (POPULATION):
ALTERNATIVE 2 FOR ALL CLEANING TYPES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores3
Factor
0.3
0.5-0.6
0.5
0.5-0.8
0.45-0.55
Activity
0.9
0.3
0.8
0.6
0.65
Emissions
0.27
0.15-0.18
0.4
0.3 -0.48
0.28-0.36
Notes:
Factor measurement: does not include all losses.
Source specificity: cleanup solvent use may not be included.
Spatial: national taken to the county level.
Temporal: annual taken to the daily level, 1989 to inventory year.
Activity: assumes some estimation/scaling from national or state data was used. Also, assumes some variability in
employment with the year and from year to year.
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
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6.6-8 EIIP Volume III
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DATA CODING PROCEDURES
This section describes the codes available to characterize solvent cleaning emission estimates.
Consistent categorization and coding will result in greater uniformity between inventories.
Inventory planning for data collection calculations and inventory presentation should take the
data formats presented in this section into account. Available codes and process definitions may
impose constraints or requirements on the preparation of emission estimates for this category.
7.1 PROCESS AND CONTROL CODES
The source category process codes for solvent cleaning operations are shown in Table 6.7-1.
These codes are derived from the EPA's Aerometric Information Retrieval System (AIRS) Area
and Mobile Source (AMS) source category codes (EPA, 1994d). Codes have not been assigned
for all the individual solvents in this source category or for all of the industries where solvent
cleaning may take place.
The control codes for use with AMS are shown in Table 6.7-2. The "099" control code can be
used for miscellaneous control devices that do not have a unique identification code. The "999"
code can be used for a combination of control devices where only the overall control efficiency is
known. Federal, state, and local regulations can be used as guides to estimate the type of control
used and the level of efficiency that can be achieved. Be careful to apply only the regulations that
specifically include area sources. If a regulation is applicable only to point sources, it should not
be assumed that similar controls exist at area sources without a survey. The equations used to
apply control efficiency, rule penetration, and rule effectiveness for area sources are discussed in
Chapter 1 of this volume.
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.7-1
AIRS AMS CODES FOR SOLVENT CLEANING MACHINES BY INDUSTRY
SIC Code
25
33
33
34
35
36
37
38
39
40-45
55
75
76
25
33
33
34
35
36
37
38
39
40-45
Industry
All Industries
Furniture and Fixtures
Primary Metal
Secondary Metal
Fabricated Metal Products
Industrial Machinery & Equipment
Electronic & Other Electronics
Transportation Equipment
Instruments & Related Products
Miscellaneous Manufacturing
Transportation Maintenance Facilities
Automotive Dealers
Auto Repair Services
Miscellaneous Repair Services
All Industries
Furniture and Fixtures
Primary Metal
Secondary Metal
Fabricated Metal Products
Industrial Machinery & Equipment
Electronic & Other Electronics
Transportation Equipment
Instruments & Related Products
Miscellaneous Manufacturing
Transportation Maintenance Facilities
Process Description
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
All processes
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
Open top degreasing
AMS Code'
24-15-000-x
24-15-005-x
24-15-010-x
24-15-015-x
24-15-020-x
24-15-025-x
24-15-030-x
24-15-035-x
24-15-040-x
24-15-045-x
24-15-050-x
24-15-055-x
24-15-060-x
24-15-065-x
24-15-100-x
24-15-105-x
24-15-110-x
24-15-115-x
24-15-120-x
24-15-125-x
24-15-130-x
24-15-135-x
24-15-140-x
24-15-145-x
24-15-150-x
6.7-2
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.7-1
(CONTINUED)
SIC Code
55
75
76
25
33
33
34
35
36
37
38
39
40-45
55
75
76
25
33
33
34
35
36
Industry
Automotive Dealers
Auto Repair Services
Miscellaneous Repair Services
All Industries
Furniture and Fixtures
Primary Metal
Secondary Metal
Fabricated Metal Products
Industrial Machinery & Equipment
Electronic & Other Electronics
Transportation Equipment
Instruments & Related Products
Miscellaneous Manufacturing
Transportation Maintenance Facilities
Automotive Dealers
Auto Repair Services
Miscellaneous Repair Services
All Industries
Furniture and Fixtures
Primary Metal
Secondary Metal
Fabricated Metal Products
Industrial Machinery & Equipment
Electronic & Other Electronics
Process Description
Open top degreasing
Open top degreasing
Open top degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Convey orized degreasing
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
AMS Code3
24-15-155-x
24-15-160-x
24-15-165-x
24-15-200-x
24-15-205-x
24-15-210-x
24-15-215-x
24-15-220-x
24-15-225-x
24-15-230-x
24-15-235-x
24-15-240-x
24-15-245-x
24-15-250-x
24-15-255-x
24-15-260-x
24-15-265-x
24-15-300-x
24-15-305-x
24-15-310-x
24-15-315-x
24-15-320-x
24-15-325-x
24-15-330-x
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.7-1
(CONTINUED)
SIC Code
37
38
39
40-45
55
75
76
Industry
Transportation Equipment
Instruments & Related Products
Miscellaneous Manufacturing
Transportation Maintenance Facilities
Automotive Dealers
Auto Repair Services
Miscellaneous Repair Services
Process Description
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
Cold cleaning
AMS Code3
24-15-335-x
24-15-340-x
24-15-345-x
24-15-350-x
24-15-355-x
24-15-360-x
24-15-365-x
x = solvent type:
000 = total: all solvent types
300 = monochlorobenzene
350 = perchloroethylene
370 = special naphthas
385 = trichloroethylene
999 = solvents: not elsewhere classified (NEC)
TABLE 6.7-2
AIRS CONTROL DEVICE CODES
Control Device
Vapor Recovery System
Activated Carbon Adsorption
Process Enclosed
Miscellaneous Control Device
Combination Control Device
Code
047
048
054
099
999
6.7-4
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8
REFERENCES
EPA. 1994a. Cold Cleaning Machine Operations New Source Performance Standards.
Background Information Basis and Purpose Document. U.S. Environmental Protection Agency,
Office of Air Quality Planning and Standards, EPA-453/D-94-067. Research Triangle Park,
North Carolina. August.
EPA. 1994b. Alternative Control Techniques Document - Industrial Cleaning Solvents.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Emission
Standards Division, EPA-453/R-94-015. Research Triangle Park, North Carolina. February.
EPA. 1994c. Emission Losses from Safety-Kleen Parts Cleaner Models: 14, 16, 30, 34 and
44. Docket No. A-94-08, Item No. II-D-5. Information provided by Safety-Kleen during
information gathering for Standards of Performance for New Stationary Sources, Cold Cleaning
Machine Operations.
EPA. 1994d. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1993 a. National Emission Standards for Hazardous Air Pollutants: Halogenated
Solvent Cleaning - Background Information Document for the Proposed Rule. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-453/R-93-054. Research Triangle Park, North Carolina. November.
EPA. 1993b. Guidance for Growth Factors, Projections and Control Strategies for the
15 Percent Rate-of-Progress Plans. U.S. Environmental Protection Agency, Office of Quality
Planning and Standards, EPA-453/R-93-002. Research Triangle Park, North Carolina. March.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone. Volume I: General Guidance for Stationary Sources. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-450/4-91-016. Research Triangle Park, North Carolina. May.
Federal Register. September 9, 1994. Standards of Performance for New Stationary Sources
Cold Cleaning Machine Operations. 40 CFR Part 60. Office of the Federal Register,
Washington, D.C. Volume 59, page 46602.
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
Roe, S.M., P. Costello, L. Jones, C. DiSogra, and R. Grant. 1995. Improved VOC Emission
Estimates for Solvent Cleaning and Degreasing in California. In: The Emission Inventory:
Programs and Progress. Proceedings of a Specialty Conference, VIP-56, Air Waste
Management Association, Pittsburgh, Pennsylvania.
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
APPENDIX A
EXAMPLE SURVEY FOR SOLVENT
CLEANUP ACTIVITIES
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
REQUESTED INFORMATION FROM MANUFACTURERS
The information received in response to this information request will be used to develop a control
technique guideline (CTG) document for industrial cleanup solvent operations. The document is
intended for State and local agencies to use as a guide in estimating emissions of volatile organic
compounds (VOCs) from the use of cleanup solvents and in developing regulations to reduce
such emissions. For the purposes of this document, cleanup solvent operations are defined as
those which remove adhesives, inks, uncured coatings, and contaminants such as dirt, soil, oil,
and grease from parts, products, tools, machinery, process vessel interiors, piping, equipment,
and general work areas. The definition of a VOC is provided, for your information, on the last
page of this enclosure.
The intent of this information request is to quantify the amount of solvent evaporated (resulting
in VOC emissions) that results from cleaning operations. The specific techniques employed may
include wiping, dipping (immersing), spraying, or flushing. Specialized items of equipment which
may be used include ultrasonic cleaners, spray gun washers, and parts washers. A broad range of
solvent cleaning operations is being considered in the "source category" for this CTG.
Intermittent swabbing of oil drips on a floor with a sol vent-soaked rag and large-scale solvent
flushing of process lines and batch reactors would both be considered cleanup solvent operations.
Vapor degreasers, conveyorized degreasers, and batch-loaded cold cleaners, used for solvent
metal cleaning, are excluded from consideration in the current study because a CTG already
exists for these specific cleaning operations. Perchloroethylene dry cleaning is also excluded
because a CTG exists for it as well.
Please feel free to report any information which you consider to be relevant to the development
of this document that is not specifically addressed in the information request. If you are unable
to respond to an item as stated or would like clarification of some question, please
contact .
Please return the completed information request to:
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CHAPTER 6 - SOLVENT CLEANING 9/16/97
This request should be completed for each plant using cleanup solvents. If multiple plants exist,
reproduce and complete the forms for each plant and identify each plant by a number (e.g., Plant
Nos. 1, 2, 3).
Name of company:
Name of plant: _
SIC Code for this plant:
Response completed by:
Title:
Plant address: Physical (No. and Street):
City
State Zip
Plant mailing address (No. and Street or Post Office Box):
City State Zip
PI ant telephone No.: ( )
Mailing address of respondent (if different from above):
Telephone No. of respondent (if different from above):
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9/76/97 CHAPTER 6 - SOLVENT CLEANING
I. Plant/Process Information
A. Provide a general description of the product(s) manufactured and the process(es) used to
produce them. (Or attach brochures, handouts, or other prepared material that includes this
information)
B. How many production lines?
How many are currently operating?
C. Plant layout
1. Provide a simplified flowchart of product flow through the plant.
2. Provide a floor plan highlighting those areas where cleanup solvents are used,
handled, and stored.
D. How many working days per year?
E. What are the hours of operation
(hr/d , hr/wk , hr/yr
F. What is the typical duration of a run?
G. What is the number of employees for 1990:
1. For the site?
2. That occasionally use cleanup solvents in the normal course of their work?
3. Whose primary j ob function is the use of cleanup solvent?
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H. What is the production rate?
1. Maximum hourly?
2. Maximum yearly?
3. Average hourly?
4. Average yearly?
II. Description of all Processes Requiring Use of Cleanup Solvents
In Table 6.A-1 (attached), indicate all process steps in your plant that require the use of
cleanup solvents. For the purpose of this document, cleanup solvent operations are defined
as those which remove adhesives, inks, uncured coatings, and contaminants such as dirt,
soil, oil, and grease from parts, products, tools, machinery, process vessel interiors, piping,
equipment and general work areas. Please identify the particular type of cleaning operation
- wiping, dipping, spraying, or flushing - that is used in each process step. If these words
for type of cleaning "operation" do not accurately describe the way the cleanup solvent is
used, please use (and define) your own terminology. The type of solvent used (brand name
and/or chemical composition or formulation) and the frequency of use should also be
included in Table 6.A-1.
For each solvent listed in Table 6.A-1, please provide a copy of the manufacturer's Material
Safety Data Sheet (MSDS). If the MSDS does not have a detailed breakdown of
composition, which will enable the VOC content to be calculated, then please provide the
composition, by chemical name (and CAS number, if available). For in-house solvent
blends, please provide the composition of the resulting mixture, or the "recipe" used to
generate the mixture.
Note: Section C of this information request asks that a copy of Table 6.A-2A be completed
for each process step listed in Table 6.A-1. To simplify the completion of Section C, if a
particular process step involves more than one cleanup operation, e.g., dipping a part to
remove the majority of contaminants and then wiping the excess solvent from the part,
choose the operation which constitutes the majority of the process. Furthermore, if you
cannot determine if a particular operation involves wiping, dipping, spraying, or flushing,
please describe the operation as thoroughly as possible and complete the table in Section C
that most closely resembles the operation.
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III. Detailed Description of Cleanup Solvent Operations
Attached are four tables labeled Tables 6.A-2A through 6.A-2D; each is titled with a
specific cleanup operation, such as "wiping" (Table 6.A-2A). For each of the process steps
listed in Table 6.A-1, please fill out the appropriate Table 6.A-2A for the cleanup operation
associated with that step. If your plant has more than one process step employing a
cleanup operation (i.e., wiping), then multiple copies of the appropriate table should be
made and completed individually for each process step.
IV. Total Cleanup Solvent Consumption
Please complete Table 6.A-3 for all of the cleanup solvents used in your plant. If VOC
emissions from cleanup operations is included in your State or local air permit, please
answer the following questions:
A. Total VOC emissions permitted, tons/yr:
B. Cleanup VOC emissions permitted, tons/yr:
C. Actual total VOC emissions, tons/yr:
D. Actual cleanup VOC emissions, tons/yr:
V. Solvent Recovery
A. Is any solvent used in your plant (process and/or cleanup) recovered, reclaimed, or
recycled?
In house or by an outside firm?
1. If in house, describe process (e.g., distillation).
2. If by an outside firm, give name and address, and pickup and delivery interval (e.g.,
weekly, bimonthly).
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B. If not currently practiced, are there any plans to institute recovery/recycle programs? (for
example, to reduce the cost of solvent disposal.) Why or why not?
C. Are the cleanup solvent wastes segregated from other solvent wastes?
D. Are waste cleanup solvents that are used in different process steps or different cleanup
operations segregated, even though they are the same material? (e.g., are spent
"manufacturing" cleanup solvents segregated from spent "maintenance" cleanup solvents?)
Why and how is this done?
Are other wastes from equipment cleanup (e.g., caustic wash water) segregated from
solvent wastes?
E. Can the waste r.lparmp solvent from one operation be used for another cleaning operation?
Is this technique practiced at your plant?
How is it done?
F. Can the number of different cleaning agents be reduced to simplify the waste solvent
mixtures, thereby enabling reuse or recycling? Why or why not?
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VI. Recordkeeping Requirements
A. Describe the recordkeeping practices for cleanup solvents at your facility:
B. What is the frequency with which measurements are made and recorded?
C. Are the recordkeeping practices based on corporate, site, or regulatory requirements?
D. Provide copies of recordkeeping forms and material balance worksheets. Include
forms/worksheets relating to solvent recovery.
E. Evaluate and briefly discuss the feasibility and additional manpower requirements
associated with recording the following information on an hourly basis:
1. Surface area cleaned.
2. The aggregate total amount of cleanup solvent used (gallons).
3. Name and total amount of each individual cleanup solvent used (gallons).
F. Evaluate the feasibility of and additional recordkeeping burden associated with recording
the same information on a daily and monthly basis.
VII. Reduced VOC Cleaners
A. Are you aware of substitute cleaners not containing VOCs, or that are very low in VOCs,
that will meet your needs? If so please identify the alternatives and the solvents and uses
for which they could be substituted.
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B. Will the use of these alternative cleaners pose any operating problems such as requiring
modification of your process operation, additional cleaning steps/ time, or reduced
effectiveness/quality? Please explain.
C. Will the use of alternatives affect the cost of your clean-up operations? If yes, by
how much and on what is that estimate based?
D. Do you have a program in place at your plant to reduce VOC emissions from cleanup
solvent operations? If so, please describe.
VIII.Hazardous Air Pollutants
The 189 HAPs defined by the 1990 CAAA are listed in Enclosure . For each solvent
listed in Table 6.A-1 that contains one or more HAPs please answer the following
questions:
A. If you were required to eliminate the use of HAPs from your clean-up operations, are you
aware of substitute solvents not containing HAPs that would meet your needs?
If so please identify the alternative solvents.
B. Will the use of these alternative solvents pose any operating problems such as requiring
modification of your process operation, additional cleaning steps/ time, or reduced
effectiveness/quality?
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C. Will the use of alternatives affect the cost of your clean-up operations?
If yes, by how much, and or what is that estimate based?
IX. Definitions
Volatile Organic Compounds (VOO
[NOTE: This definition may subsequently change. The Code of Federal Regulations (40 CFR
51.100[s]) will provide the current legal definition.] Any compound of carbon, excluding carbon
monoxide, carbon dioxide, carbonic acid, metallic carbides or carbonates, and ammonium
carbonate, which participates in atmospheric photochemical reactions.
1. This includes any such organic compound other than the following, which have been
determined to have negligible photochemical reactivity: methane; ethane; methylene
chloride (dichloromethane); 1,1,1-trichloroethane (methyl chloroform); 1,1,1-trichloro-
2,2,2-trifluoroethane (CFC-113); trichlorofluoromethane (CFC-11);
dichlorodifluoromethane (CFC-12); chlorodifluoromethane (CFC-22); trifluoromethane
(FC-23); 1,2-dichloro 1,1,2,2-tetrafluoroethane (CFC-114); chloropentafluorethane
(CFC-115); 1,1,1-trifluoro 2,2-dichloroethane (HCFC-123); 1,1,1,2-tetrafluoroethane
(HFC-134a); 1,1-dichloro 1-fluoroethane (HCFC-141b); 1-chloro 1,1-difluoroethane
(HCFC-142b); 2-chloro 1,1,1,2-tetrafluoroethane (HCFC-124); pentafluoroethane
(HFC-125); 1,1,2,2-tetrafluoroethane (HFC-134); 1,1,1-trifluoroethane (HFC-143a);
1,1-difluoroethane (HFC-152a); and perfluorocarbon compounds which fall into these
classes:
(a) Cyclic, branched, or linear, completely fluorinated alkanes;
(b) Cyclic, branched, or linear, completely with fluorinated ethers with no
unsaturations;
(c) Cyclic, branched, or linear, completely fluorinated tertiary amines with no
unsaturations; and
(d) Sulfur containing perfluorocarbons with no unsaturations and with sulfur bonds
only to carbon and fluorine.
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2. For purposes of determining compliance with emission limits, VOC will be measured by
the test methods in the approved State implementation plan (SIP) or 40 CFR Part 60,
Appendix A, as applicable. Where such a method also measures compounds with
negligible photochemical reactivity, these negligibility-reactive compounds may be
deducted from the reported VOC if the amount of such compounds is accurately
quantified, and such exclusion is approved by the enforcement authority.
3. As a precondition to excluding these compounds as VOC or at any time thereafter, the
enforcement authority may require an owner or operator to provide monitoring or testing
methods and results demonstrating, to the satisfaction of the enforcement authority, the
amount of negligibly-reactive compounds in the source's emissions.
4. For the purposes of Federal enforcement for a specific source, the EPA shall use the test
method specified in the applicable EPA-approved SIP, in a permit issued pursuant to a
program approved or promulgated under Title V of the Act, or under 40 CFR Part 51,
Subpart I or Appendix S, or under 40 CFR Parts 52 or 60. The EPA shall not be bound
by any State determination as to appropriate methods for testing or monitoring
negligibly-reactive compounds if such determination is not reflected in any of the above
provisions.
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-1
GENERAL INFORMATION OF CLEANUP OPERATIONS
Process
No.
Example 1
Example 2
Example 3
Example 4
Cleanup
Description
Blanket wash
Press cleaning
Spill mopping
Gun wash
Surface Being
Cleaned
Press roll
Machine
Floor
Spray gun
Cleanup
Operationa
Wiping
Wiping
Wiping
Flushing
Solvent
Used"
SK 105
SK 105
SK 105
Lacquer
thinner
Frequency of
Operation
Once/shift
Continuous
When spills occur;
estimated three
times/shift
Once per hour
a Use terminology corresponding to Tables 6.A-2A, 6. A-2B, 6.A-2C, or 6.A-2D (wiping,
dipping, spraying, or flushing) or other, more precise terms, with definition appended.
b Provide copy of MSDS plus other documentation (if required) to establish VOC content of
each solvent listed in this table.
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TABLE 6.A-2A
WIPING OPERATION QUESTIONNAIRE
Question
Process step (taken from Table 6.A-1)
Description of part or machine being cleaned
How much labor time is spent in this cleaning
operation?
Cleanup solvent used/Brand Name/Identification
No.
Is the cleanup solvent diluted with water before
use?
If so, what is the ratio of solvent to water?
How much of the concentrated cleanup solvent is
used:
For this operation?
Per shift?
How much of the spent solvent is collected?
How much of the solvent evaporates during this
wiping operation?
Describe the contaminant or soil that is being
removed.
Response and Comments
To what degree do the following factors affect your selection of the cleanup solvent used in
this cleaning operation?
A - Primary consideration
B - Secondary consideration
C - Not important
If your answer is "A" or "B", please elaborate.
Physical and chemical properties of
contaminant to be removed
ABC
6.A-12
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-2A
(CONTINUED)
Question
Physical and chemical properties of the
substrate on which the contaminant is
deposited
The degree of cleaning efficiency required
The size, shape, and complexity of parts or
objects to be cleaned
The volume or number of parts or obj ects to be
cleaned per unit of time
The substrate preparation required
Solvent costs
Worker exposure concerns
Fire code or insurance protection requirements
Recycle and recovery options
Regulatory requirements
Ventilation requirements
Waste disposal (including wastewater
treatment)
Availability of factory floor space
Other special considerations
Does this cleanup activity have particular
requirements that either require or preclude the
use of any specific types(s) of cleanup solvent(s)?
If so, specify.
What material is used to wipe the solvent on the
substrate (e.g., rag, brush, sponge, paper towel,
etc.)?
How is the solvent applied to the wiping
material?
Response and Comments
A
A
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
B
B
B
B
B
B
B
B
B
B
C
C
C
C
C
C
C
C
C
C
C
C
C
C
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TABLE 6.A-2A
(CONTINUED)
Question
Response and Comments
If rags are used:
What is the size of the rags?
How many rags are used per week?
Are they reusable?
How are the used rags handled for cleaning or
disposal (i.e., hand wrung, stored wet in closed
drum, left to air dry, sent out for laundering,
washed on the premises, etc.)?
Is the spent or dirty solvent collected from
this operation reused, recycled, or
disposed? If so, how much?
Explain how a dirty solvent is handled.
Are any steps taken in this wiping operation to
minimize the release of organic vapors into the
workplace (e.g.. bv working in a hood")? If so.
describe.
Are any steps taken to minimize the release of
organic vapors into the atmosphere (e.g., is there
an emission control device on hood exhaust)? If
so, describe.
A - Primary consideration, B - Secondary consideration, C - Not important.
6.A-14
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-2B
DIPPING OPERATION QUESTIONNAIRE
Question
Process step number (taken from Table 6.A-1)
Description of part or machine being cleaned
How much labor time is spent in this operation?
Cleanup solvent used/Brand Name/Identification
No.
Is the cleanup solvent diluted with water before
use?
If so, what is the ratio of solvent to water?
How much of the concentrated cleanup solvent is
used:
For this operation?
Per shift?
How much of the spent solvent is collected?
How much of the solvent evaporates during this
dipping operation?
Describe the contaminant or soil that is being
removed.
Response and Comments
To what degree do the following factors affect your selection of the cleanup solvent used in
this cleaning operation?
A - Primary consideration
B - Secondary consideration
C - Not important
If your answer is "A" or "B", please elaborate.
Physical and chemical properties of contaminant to
be removed
ABC
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TABLE 6.A-2B
(CONTINUED)
Question
Physical and chemical properties of the substrate on
which the contaminant is deposited
The degree of cleaning efficiency required
The size, shape, and complexity of parts or objects
to be cleaned
The volume or number of parts or objects to be
cleaned per unit of time
The substrate preparation required
Solvent costs
Worker exposure concerns
Fire code or insurance protection requirements
Recycle and recovery options
Regulatory requirements
Ventilation requirements
Waste disposal (including wastewater treatment)
Availability of factory floor space
Other special considerations
Does this cleanup activity have particular
requirements that either require or preclude the use
of any specific types(s) of cleanup solvent(s)? If so,
specify.
Describe the type of equipment used (dip tank,
vessel, etc.) to apply the solvent to the substrate
(how are parts added/removed, etc.).
Are capture/control devices for VOC emissions
(hoods, etc.) In place and operating during dipping
operations? If so, explain.
Response and Comments
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
6.A-16
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-2B
(CONTINUED)
Question
Is the spent or dirty solvent collected from this
operation reused, recycled, or disposed of? If so,
how much?
Explain how a dirty solvent is handled.
Response and Comments
A - Primary consideration, B - Secondary consideration, C - Not important.
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TABLE 6.A-2C
SPRAYING OPERATION QUESTIONNAIRE
Question
Process step number (taken from Table 6.A-1)
Description of part or machine being cleaned
How much labor time is spent in this operation?
Cleanup solvent used/brand name/identification No.
Is the cleanup solvent diluted with water before use?
If so, what is the ratio of solvent to water?
How much of the concentrated cleanup solvent is
used:
For this operation?
Per shift?
How much of the spent solvent is collected?
How much of the solvent evaporates during this
spraying operation?
Describe the contaminant or soil that is being
removed.
Response and Comments
To what degree do the following factors affect your selection of the cleanup solvent used in
this cleaning operation?
A - Primary consideration
B - Secondary consideration
C - Not important
If your answer is "A" or "B", please elaborate.
Physical and chemical properties of contaminant to be
removed
Physical and chemical properties of the substrate on
which the contaminant is deposited
The degree of cleaning efficiency required
ABC
ABC
ABC
6.A-18
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-2C
(CONTINUED)
Question
The size, shape, and complexity of parts or objects to be
cleaned
The volume or number of parts or objects to be cleaned per
unit of time
The substrate preparation required
Solvent costs
Worker exposure concerns
Fire code or insurance protection requirements
Recycle and recovery options
Regulatory requirements
Ventilation requirements
Waste disposal (including wastewater treatment)
Availability of factory floor space
Other special considerations
Does this cleanup activity have particular requirements that
either require or preclude the use of any specific types(s) of
cleanup solvent(s)? If so, specify.
Describe the type of spray equipment used to apply the
solvent to the substrate.
Are solvents applied in-place, or is the part/machine taken
to a designated station?
Are capture/control devices for VOC emissions (hoods,
etc.) in place and operating during this spraying operation?
If so, explain.
Is any spent or dirty solvent collected from this operation
reused, recycled or disposed of? If so, how much?
Explain how a dirty solvent is handled.
Response and Comments
A
A
A
A
A
A
A
A
A
A
A
A
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
A - Primary consideration, B - Secondary consideration, C - Not important.
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TABLE 6.A-2D
FLUSHING OPERATION QUESTIONNAIRE
Question
Process step number (taken from Table 6.A-1)
Description of part or machine being cleaned
How much labor time is spent in this operation?
Cleanup solvent used/brand name/identification No.
Is the cleanup solvent diluted with water before
use?
If so, what is the ratio of solvent to water?
How much of the concentrated cleanup solvent is
used:
For this operation?
Per shift?
How much of the spent solvent is collected?
How much of the solvent evaporates during this
flushing operation?
Describe the contaminant or soil that is being
removed.
Response and comments
To what degree do the following factors affect your selection of the cleanup solvent used in
this cleaning operation:
A - Primary consideration
B - Secondary consideration
C - Not important
If your answer is "A" or "B", please elaborate.
Physical and chemical properties of contaminant to
be removed
ABC
6.A-20
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-2D
(CONTINUED)
Question
Physical and chemical properties of the substrate on
which the contaminant is deposited
The degree of cleaning efficiency required
The size, shape, and complexity of parts or objects
to be cleaned
The volume or number of parts or objects to be
cleaned per unit of time
The substrate preparation required
Solvent costs
Worker exposure concerns
Fire code or insurance protection requirements
Recycle and recovery options
Regulatory requirements
Ventilation requirements
Waste disposal (including wastewater treatment)
Availability of factory floor space
Other special considerations
Does this cleanup activity have particular
requirements that either require or preclude the use
of any specific types(s) of cleanup solvent(s)? If so,
specify.
Describe the type of equipment used in the flushing
operation (i.e., is there a drain, how is the operation
done, etc.).
Response and Comments
A
A
A
A
A
A
A
A
A
A
A
A
A
A
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
B C
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CHAPTER 6 - SOLVENT CLEANING
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TABLE 6.A-2D
(CONTINUED)
Question
Does the drain direct the waste to a sludge reservoir
or a water treatment system?
Does any of your solvent enter the local municipal
waste treatment system? If so, how much?
Are capture/control devices for voc emissions in
place and operating during flushing operations? If
so, explain.
Is the spent or dirty solvent collected from flushing
reused, recycled, or disposed of? If so, how much?
Explain how dirty solvent from flushing is handled.
Response and Comments
A - Primary consideration, B - Secondary consideration, C - Not important.
6.A-22
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CHAPTER 6 - SOLVENT CLEANING
TABLE 6.A-3
PLANT CONSUMPTION OF CLEANUP SOLVENT
Solvent3
Source (supplier)
Amount
purchased per
year
Amount of used
solvent
recovered as
liquid waste
Amount of
cleanup solvent
that is contained
in solid waste or
product shipped
Net loss of
cleanup solvent
by evaporation1"
a Use the same identification for each solvent in this table that was used in Table 6.A-1.
b If any of this evaporated solvent is subsequently treated by an emission control device, please explain.
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6.A-24 EIIP Volume III
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VOLUME III: CHAPTER 7
GRAPHIC ARTS
Final Report
November 1996
Prepared by:
Eastern Research Group, Inc.
Post Office Box 2010
Morrisville, North Carolina 27560-2010
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
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ACKNOWLEDGEMENT
This document was prepared by Donna Jones of Radian Corporation and Lucy Adams of
Eastern Research Group, Inc., for the Area Sources Committee of the Emission Inventory
Improvement Program and for Charles Mann of the Air Pollution Prevention and Control
Division, U.S. Environmental Protection Agency. Members of the Area Sources Committee
contributing to the preparation of this document are:
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Chris Nguyen, California Air Resources Board
Kwame Agyei, Puget Sound Air Pollution Control Agency
Mike Fishburn, Texas Natural Resource Conservation Commission
Larry Jones, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Gwen Judson, Wisconsin Department of Natural Resource
Jo Crumbaker, Maricopa County Air Pollution Control
Linda Murchison, California Air Resources Board
Sally Otterson, Washington Department of Ecology
Lee Tooly, Emission Factor and Inventory Control, U.S. Environmental Protection Agency
Chris Mulcahy, Connecticut Department of Environmental Protection
Jim Wilkinson, Maryland Department of the Environment
George Leney, Allegheny County Health Department
Other reviewers of this document are:
Demian P. Ellis, U.S. Environmental Protection Agency, Region 2
Raymond K. Forde, U.S. Environmental Protection Agency, Region 2
EIIP Volume III in
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CONTENTS
Section Page
1 Introduction 7.1-1
2 Source Category Description 7.2-1
2.1 (Roto)gravure Printing 7.2-3
2.2 Flexograpic Printing 7.2-7
2.3 Offset Lithographic Printing 7.2-8
2.4 Letterpress Printing 7.2-9
2.5 Screen Printing 7.2-9
2.6 Plateless Printing 7.2-10
2.7 Point Source Considerations 7.2-10
2.8 Emission Sources 7.2-12
2.9 Factors Influencing Emissions 7.2-12
2.9.1 Process Operating Factors 7.2-12
2.9.2 Control Techniques 7.2-15
3 Overview of Available Methods 7.3-1
3.1 Emission Estimation Methodologies 7.3-1
3.2 Available Methodologies 7.3-1
3.2.1 Volatile Organic Compounds 7.3-1
3.2.2 Hazardous Air Pollutants 7.3-2
3.3 Data Needs 7.3-2
3.3.1 Data Elements 7.3-2
3.3.2 Double Counting Considerations 7.3-4
3.3.3 Application of Controls 7.3-4
3.3.4 Spatial Allocation 7.3-4
3.3.5 Temporal Resolution 7.3-5
3.3.6 Projecting Emissions 7.3-5
iv Volume III
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CONTENTS (CONTINUED)
Section Page
4 Preferred Methods for Estimating Emissions 7.4-1
4.1 Planning 7.4-1
4.2 Distribution 7.4-2
4.3 Survey Compilation and Scaling 7.4-2
5 Alternative Methods for Estimating Emissions 7.5-1
5.1 Ink Sales Emission Factor Method 7.5-1
5.2 Per Capita Emission Factor Method 7.5-9
6 Quality Assurance/Quality Control 7.6-1
6.1 Emission Estimate Quality Indicators 7.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 7.6-1
6.1.2 Sources of Uncertainty 7.6-2
7 Data Coding Procedures 7.7-1
7.1 Process and Control Codes 7.7-1
8 References 7.8-1
EIIP Volume III V
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TABLES
Table Page
7.2-1 Product Printed by Each Graphics Arts Technology 7.2-2
7.2-2 SIC Codes that May Include Graphic Arts Operations
(EPA, 1995b) 7.2-4
7.2-3 Distribution of Products and Ink Sales by Printing Type 7.2-6
7.2-4 Estimated Small Business Distribution of Printing Facilities 7.2-11
7.2-5 National Regulations for the Graphic Arts Industry 7.2-18
7.5-1 AFS Source Classification Codes for Graphic Arts 7.5-3
7.5-2 Component VOC Emission Factors for Graphic Arts Operations 7.5-8
7.6-1 Facility Survey Method DARS Scores 7.6-3
7.6-2 Ink Sales Emission Factor Method DARS Scores 7.6-3
7.6-3 Per Capita Method DARS Scores 7.6-4
7.7-1 AIRS AMS Codes for the Graphic Arts 7.7-2
7.7-2 AIRS Control Device Codes 7.7-2
vi Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from graphic arts. Section 2 of this chapter contains a general description of the graphic arts
category and an overview of available emission control technologies. Section 3 of this
chapter provides an overview of available emission estimation methods. Section 4 presents
the preferred emission estimation method for the graphic arts industry, and Section 5 presents
alternative emission estimation techniques. Quality assurance/quality control (QA/QC) issues
are discussed in Section 6. Data coding procedures are discussed in Section 7, and Section 8
is the reference section.
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7.1-2 Volume III
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SOURCE CATEGORY DESCRIPTION
The graphic arts industry can be divided by technology into six different printing segments:
rotogravure, flexographic, offset lithographic, letterpress, screen, and plateless (xerographic,
electrostatic, magnetic, thermal, ink-jet, etc.). The technology (i.e., the type of press
equipment) dictates the types of inks and coatings that can be used and defines to a large
extent the emissions and the control techniques that are applicable (Environmental Protection
Agency [EPA], 1995a).
The printing industry can also be divided by the type of substrate that is used. Among the
flexible substrates, paper, foil, and films are used. Paper can be further classified in many
ways, including coated versus uncoated. Films include polyethylene and a number of other
polymers. Rigid substrates include cardboard, vinyl, and metal cans. A given substrate may
be printed upon using different technologies depending on factors such as the end use, quality
requirements, quantity, cost, and environmental considerations (EPA, 1995a). Textiles are
specifically excluded from the graphic arts operations source category.
A third way to segment the printing industry is by the type of product or end use. In general,
the end use falls into the broad categories of publications, packaging, or products. Publication
printing includes newspapers, magazines, books, and advertising. Packaging includes paper,
plastic and foil bags, wrappers, cardboard cartons, and metal cans. Products include wall and
floor covering, greeting cards, and paper towels. Various technologies can be used to print
specific items within the broad categories (EPA, 1995a). Table 7.2-1 shows the six major
types of printing and the types of products printed by each (EPA, 1995b).
Graphic arts operations are performed on printing presses that are made up of one or more
"units." Each unit can print only one color. The substrate in graphic arts operations is either
continuous and called a "web," or individual pieces of substrate called "sheets." The pattern
that is printed on the substrate is called the "image."
The graphics arts industry includes operations classified by Standard Industrial Classification
(SIC) Codes 2752 (Commercial Printing-Lithography), 2754 (Commercial Printing-Gravure),
and 2759 (Commercial Printing Not Elsewhere Classified [n.e.c.], which includes letterpress,
flexographic, screen, and other commercial printing). Other four-digit codes under major SIC
Code 27 cover printing-related industries such as
TABLE 7.2-1
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Final 11/18/96
PRODUCTS PRINTED BY EACH GRAPHICS ARTS TECHNOLOGY3
Technology
Rotogravure
Flexography
Offset Lithography
Letterpress
Screen
Plateless
Products
Packaging, advertising, greeting cards, art
books, catalogues, and directories
Packaging, advertising newspapers, books,
magazines, financial and legal document
directories
Magazines, catalogues and directories,
newspapers, books, stationary, financial and
legal documents, advertising, journals,
packaging, metal cans
Magazines, catalogues and directories,
newspapers, books, stationary, financial and
legal documents, advertising, journals,
packaging, metal cans
Signs, electronics, wallpaper, greeting cards,
ceramics, decals, banners, plastic bottles
Images printed on paper by laser printers,
xerographic copiers, fax machines, and ink jets
Source: EPA, 1995a and 1995b.
7.2-2
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publishing, book printing, and other printing-related service trades. Because graphic arts
operations include not only those whose primary business involves printing, potentially any
entities classified under the major SIC Code 27 may perform graphic arts operations.
The SIC Codes 26 (Paper and Allied Products), 30 (Rubber and Miscellaneous Plastic
Products), 32 (Stone, Clay, and Glass Products), 34 (Fabricated Metal Products),
39 (Miscellaneous Manufacturing Industries), and 86 (Membership Organizations) may also
include graphic arts operations. Some of these operations may be inventoried as part of the
industrial surface coating source category. Inventory preparers should take care to avoid
double counting between these two source categories within an area source inventory. Also,
the point source and area source inventory definitions of graphic arts and industrial surface
coating should match. This is particularly important when subtracting point source emissions
from total estimated emissions in order to get area source emissions. Table 7.2-2 lists the
SIC Codes that are likely to have graphic arts operations.
The following six sections discuss the six types of graphic arts operations grouped by printing
technology. The importance of the type of printing on a national level, in regard to total
emissions, is likely to be a reflection of the product market share and ink sales data presented
in Table 7.2-3. The importance of each type of printing on a regional and local level may
differ from these national trends.
2.1 (ROTO)GRAVURE PRINTING
Gravure is a printing process in which an image is etched or engraved below the surface of a
plate or cylinder. Nearly all gravure printing is done by rotogravure. On the gravure plate or
cylinder (roto), the printing image consists of millions of minute cells. Gravure printing
requires very fluid inks that flow from the cells to the substrate at high press speeds.
Solventborne or waterborne ink systems can be used in gravure printing but these ink systems
are not interchangeable. Both the printing cylinders and the drying systems are specific to the
solvent system in use. Rotogravure printing is usually performed on a web (EPA, 1995b).
Rotogravure printing can be divided into publication and product/packaging segments.
Publication gravure presses in the United States use Solventborne (toluene/xylene-based) ink
systems exclusively. Because of the expense and complexity of rotogravure cylinder
engraving, it is particularly suited to long-run printing jobs. Packaging/product gravure inks
include nitrocellulose and water-based inks (EPA, 1995b).
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TABLE 7.2-2
SIC CODES THAT MAY INCLUDE GRAPHIC ARTS OPERATIONS3
(EPA, 1995s)
SIC Code
2652
2653
2655
2656
2657
2671
2672
2673
2674
2676
2677
2678
2679
27 Ix
272x
2731
2732
274x
2752
2754
2759
2761
2771
3081
Industry Description
Set up paperboard boxes
Corrugated and solid fiber boxes
Fiber cans, drums, and similar products
Sanitary food containers
Folding paperboard boxes
Paper coated and laminated, packaging
Paper coated and laminated, n.e.c.
Bags: plastics, laminated, and coated
Bags: uncoated paper and multiwall
Sanitary paper products
Envelopes
Stationary products
Converted paper products, wall coverings, gift wrap, n.e.c.
Newspapers
Periodicals
Book publishing
Book printing
Miscellaneous publishing
Commercial printing, lithographic
Commercial printing, gravure
Commercial printing, n.e.c.
Manifold business forms
Greeting cards
Unsupported plastics, film and sheet
7.2-4
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CHAPTER 7 - GRAPHIC ARTS
TABLE 7.2-2
(CONTINUED)
SIC Code
3083
3085
3089
3221
3411
3412
3466
3996
86xx
Industry Description
Laminated plastics, plate and sheet
Plastic bottles
Plastics, n.e.c.
Glass containers
Metal cans
Metal barrels, drums, and pails
Crowns and closures
Floor coverings
Membership organizations
n.e.c. = not elsewhere classified.
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TABLE 7.2-3
DISTRIBUTION OF PRODUCTS AND INK SALES BY PRINTING TYPE
Type of Printing
Rotogravure
Flexography
Offset Lithography
Letterpress
Screen
Plateless
Estimated
Number of
Facilities3
427
1,587
54,000
21,000
21,000
unknown
Estimated
Percentage
of Product
Market Share3
18
18
47
8
3
3
Percentage of
Ink Solvent Use"
22
16
35
8
part of remaining
19 percent
a Source: EPA, 1995a.
b Compiled from: Darnay, 1990; Renson, 1991; and National Association of Printing Ink Manufacturers, 1988.
7.2-6
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Gravure ink solvents include alcohols, aliphatic naphtha, aromatic hydrocarbons, esters, glycol
ethers, ketones, and nitroparaffins. Gravure water-based inks are in regular production use at
some facilities to reduce volatile organic compound (VOC) emissions from the press (EPA,
1993a).
In rotogravure printing, the web is printed on one side at a time and must be dried after the
application of each color. Thus, for four-color, two-sided publication printing, eightpasses
through the press are employed, each including a pass over a steam drum or through a hot-air
dryer at temperatures from ambient up to 120°C (250°F) to remove nearly all of the solvent
(EPA, 1993a).
In addition to inks, other materials including adhesives, primers, coatings, and varnishes may
be applied with rotogravure cylinders. These materials dry by evaporation as the substrate
passes through hot air dryers. Cleaning solutions containing solvents are also used in the
rotogravure printing process (EPA, 1995a).
2.2 FLEXOGRAPIC PRINTING
In flexographic printing, the image area is raised from the surface of a plate (like a
typewriter) with a rubber (flexible) image carrier. Alcohol-based inks are generally used.
The process is usually webfed and used for medium or long multicolor runs on a variety of
substrates, including heavy paper, fiberboard, and metal and plastic foil. Almost all milk
cartons and multiwall bags, and half of all flexible packaging are printed by this process
(EPA, 1993a).
Steam-set inks, employed in the "water flexo" or "steam-set flexo" process, are low-
viscosity inks of a paste consistency that are gelled by water or steam. Steam-set inks are
used for paper bag printing and produce no significant emissions (EPA, 1993a).
Solvent-based inks are used primarily in publication printing and contain about 75 percent (by
volume) organic solvent. The solvent, which must be rubber compatible, may be alcohol or
alcohol mixed with an aliphatic hydrocarbon or ester. Typical solvents also include
nonaromatic glycols, ketones, and ethers. The inks dry by solvent absorption into the web
and by evaporation, usually in high-velocity steam drums or hot-air dryers, at temperatures
below 120°C (250°F). Most of the solventborne flexographic inks contain few or no
hazardous air pollutants (HAPs). As in rotogravure publishing, the web is printed on only
one side at a time. The web passes over chill rolls after drying; no emissions occur from
chilling (EPA, 1993a).
When flexography is used to print corrugated board and most paperboard, water-based inks
can be used; however, fast-drying inks are required for plastic films and packaging papers so
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the web can be rewound or processed into the final product at the end of the press.
Flexography is becoming popular for printing pressure-sensitive labels, a process in which the
ink must dry quickly without penetration. Use of inks that dry by exposure to ultraviolet
radiation (producing no emissions) have been used in label printing with much success (EPA,
1995b).
Additional converting operations, which are often done at the flexographic press stations or
in-line with the presses, such as film blowing, laminating, coating, adhesive application, and
cutting, may result in additional emissions. Cleaning operations also use solvents that
contribute to emissions (EPA, 1995b).
2.3 OFFSET LITHOGRAPHIC PRINTING
Lithographic printing is characterized by a planographic printing process (i.e., the image and
nonimage areas are on the same plane). The image area is ink-wettable and water- repellent,
and the nonimage area is chemically repellent to ink and hydrophilic. The inks used in
lithography are either heatset or nonheatset. In offset printing, the graphic image is applied
from an ink-covered print plate to a rubber-covered "blanket" cylinder and then transferred
onto the substrate, hence the name "offset" lithography (EPA, 1993a). The substrate in offset
lithography can be either a web or sheet. A web substrate can be used with either heatset or
nonheatset inks; sheets are used with nonheatset inks only. Some offset presses print on both
sides of the paper at the same time (called "perfecting"); others print on one side only or two
sides sequentially (EPA, 1994a).
An aqueous solution of isopropyl alcohol is commonly used to dampen the nonimage area on
the plate and is called the "fountain" or "dampening" solution. The fountain solution in offset
lithographic printing has traditionally contained about 15 percent alcohol; at times as high as
30 percent alcohol could be used. Because of environmental pressures, the use of isopropyl
alcohol (a VOC) is decreasing. Fountain solutions that contain lower VOCs and/or alcohol
substitutes are now in use. The newspaper industry segment of offset lithographic printing
predominantly uses alcohol substitutes. Some facilities may use both alcohol and alcohol
substitutes; in this case, the alcohol is generally much lower than 15 percent in the fountain
solution (EPA, 1994a).
Offset lithographers also use cleaning solutions to clean the press and parts. These cleaning
solutions have traditionally been high-solvent-containing (90 to 100 percent) solutions. Some
lower- or no-solvent cleaners are becoming available, in which the solvent content is 0 to 30
percent (EPA, 1994a).
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2.4 LETTERPRESS PRINTING
Letterpress printing is the oldest form of movable type printing. Letterpress printing uses a
relief printing plate (as does flexography) and viscous inks similar to lithographic inks.
Various types of letterpress plates are available. These plates differ from flexographic plates
in that they have a rigid backing (metal or plastic) and are not "flexible." Both sheetfed and
web presses are in use. Web letterpress equipment uses heatset and nonheatset inks.
Letterpress printing uses no fountain solutions; the cleaning solvents are similar to those used
in lithography. Traditionally, letterpress printing dominated periodical and newspaper
publishing; however, the majority of newspapers have converted to nonheatset web offset
printing (EPA, 1995a).
Letterpress printing uses a paper web that is printed on both sides, one side at a time, and
uses heatset inks, usually of about 40 percent (by volume) solvent. The web is dried after
each color is applied. Heatset letterpress ink is similar to heatset lithographic ink. These inks
contain resins dissolved in aliphatic hydrocarbons and are dried in hot-air ovens. The inks
can be entirely HAP free (EPA, 1993a).
"Moisture set" inks used in some packaging applications contain trimethylene glycol (a HAP).
"Water washable" letterpress inks are sometimes used for printing paper and corrugated
boxes. These inks contain glycol-based solvents that may contain HAPs (EPA, 1995a).
2.5 SCREEN PRINTING
Screen printing involves forcing ink through a stencil in which the image areas are porous.
The screens are generally made of silk, nylon or metal mesh. Screen printing is used for
signs, displays, electronics, wallpaper, greeting cards, ceramics, decals, banners, and textiles.
Nearly half of the screen printing plants in the United States print on textiles. Ink systems
used in screen printing include ultraviolet cure, waterborne, solventborne, and plastisol, with
plastisol (polyvinyl chloride) being mainly used in textile printing. Solvent-based ink systems
contain aliphatic, aromatic, and oxygenated organic solvents (EPA, 1995a).
Both sheetfed and web presses are used in screen printing. Depending on the substrate
printed, the substrate can be dried after each printing station or, for absorbent substrates, after
all colors are printed. Solvent- and waterborne inks are dried in hot-air or infrared drying
ovens. Dryer gases are partially recycled and partially vented (EPA, 1995a).
2.6 PLATELESS PRINTING
This technology is a relatively new process used primarily for short runs on paper substrates.
Plateless printing processes include electronic (e.g., laser printers), electrostatic (e.g.,
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xerographic copiers), magnetic, thermal (e.g., facsimile machines) and ink jet printing.
Plateless printing processes are estimated to account for only 3 percent (by value) of printed
products. Electrostatic toners and ink jet printer inks may contain HAPs; however the
quantities emitted at any location are small (EPA, 1995a).
2.7 POINT SOURCE CONSIDERATIONS
Although 80 percent of graphic arts facilities are estimated to have fewer than 20 employees
and less than 10 tons per year (tpy) VOC emissions (Ulconovic, 1991), there are likely to be
some point sources and/or point source emissions for this source category in most inventory
areas. Forty percent of VOC emissions from graphic arts operations are estimated to be from
plants in the 10- to 100-tpy range.
This indicates that the interface between point and area sources, as well as the attainment
status of the region, will be especially important for inventories of this source category. A
typical scenario is to find a few large graphic arts operations and numerous small graphic arts
operations with an equal potential for a significant amount of emissions from both size
groups.
Table 7.2-4 presents the available information about the estimated percentage of facilities that
are area sources among the various printing processes. These estimates substantiate the
assumption that there are a significant number of area source facilities among all types of
printing.
Also, many of these small graphic arts operations may be located at facilities whose
predominant operation is not printing. This fact is reflected in the SIC Codes for graphic arts
operations (Table 7.2-2) that are outside of major SIC Code 27 (Printing and Publishing).
According to Title V permit requirements, if a source qualifies as a major source for one
HAP, the facility needs to inventory all HAP sources, regardless of their size. Therefore, data
may exist for some small printing operations if they are located in facilities large enough to
qualify for Title V permitting. These sources will also be included in a point source
inventory.
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CHAPTER 7 - GRAPHIC ARTS
TABLE 7.2-4
ESTIMATED SMALL BUSINESS DISTRIBUTION OF PRINTING FACILITIES
Type of Printing
Rotogravure
Flexography
Offset Lithography
Letterpress
Screen
Plateless
Estimated
Number of
Facilities'1
427
1,587
54,000
21,000
21,000
Unknown
Estimated
Percentage of
Small Businesses
0 for publication; 48 percent of
packaging/product printing
are small businesses (<500 employees)13
Out of 600 responses to an EPA survey
of flexographic printing, 98 percent were
considered small businesses (<500
employees/1
Manyc
Unknown
Manyd
Manyd
a EPA, 1995a.
b EPA, 1995b.
c EPA, 1994a.
d Assumed.
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2.8 EMISSION SOURCES
The predominant emissions from graphic arts printing are VOCs contained in the printing
inks, fountain solutions, and cleaning solutions. Many of these VOCs are also likely to be
HAPs. To a lesser extent, VOCs and HAPs are emitted from binding and laminating
operations (EPA, 1995a).
Printing inks vary widely in composition, but all consist of three major components:
pigments, which produce the desired colors and are composed of finely divided organic and
inorganic materials; binders, the solid components that lock the pigments to the substrate and
are composed of organic resins and polymers or, in some inks, oils and rosins; and solvents,
which dissolve or disperse the pigments and binders and are usually composed of organic
compounds. The binder and solvent make up the "vehicle" part of the ink (EPA, 1993a).
In "heatset" printing processes, the solvent evaporates from the ink into the atmosphere during
a drying step. In nonheatset processes, minimal VOCs or HAPs are emitted from inks,
although emissions still result from fountain solution (offset lithographic printing only) and
cleaning solution use. Ultraviolet inks may be used in graphic arts operations; in this case,
there will be no emissions from inks (EPA, 1994a).
Emissions from proofing presses, cleaning operations, ink storage tanks, and ink mixing
operations are relatively minor compared to the emissions during the printing process, but
they do contribute to overall emissions (EPA, 1995a).
2.9 FACTORS INFLUENCING EMISSIONS
2.9.1 PROCESS OPERATING FACTORS
The type of printing and/or ink (offset heatset, offset nonheatset, gravure, flexographic, etc.) is
the most important process operating factor for estimating emissions from graphic arts
operations. For similar processes, the next most important process operating factor affecting
emissions is the production volume (i.e., amount of material printed [area times length]). The
amount of ink used per unit of substrate (i.e., the relative amount of inked versus noninked
areas), which is determined by the type of product (newspaper, cereal box, greeting card,
etc.), is another important factor. All things being equal, the production volume will be the
determining factor in the relative magnitude of emissions. The type of substrate has little
effect on the quantity of emissions.
Since printing is not a high-profit-margin production activity, it is in the interest of the printer
to minimize the use of raw materials and time needed for each product. Therefore, it would
appear that emissions minimization would be an auxiliary goal of the printer to minimize the
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use of raw materials. A factor that supersedes these goals, however, is customer satisfaction.
It is because of the customer's perception of the final product that this source category retains
the descriptor of an "art." Consequently, the printer may alter process variables that increase
chemical use and, thus, possibly emissions, to achieve an end result that meets the customer's
scrutiny. Chemical use may also be increased in the interest of shorter production time and
less product waste to increase the profit margin.
One example of this trend in graphic arts operations is in offset lithographic printing, where
the use of alcohol, one of the more expensive raw materials, may be used at a higher rate if it
appears to be the only way to print a product that pleases the customer. This was shown in
the case of a press operator who was found to purchase his own alcohol—at his own expense--
to ensure high quality of a printing job when alcohol purchases had been eliminated by the
plant management for environmental reasons (EPA, 1994a).
The following process variables relate to specific types of printing or operations common to
all types:
Rotogravure
In publication rotogravure printing, the inks contain from 55 to 95 percent (by volume)
low-boiling-point solvent (average is 75 percent by volume) with low viscosities (EPA,
1993a). It is important that the ink or other coating dry quickly between each color;
therefore, the ink vehicle must be evaporated between stations (EPA, 1995b). Organic
solvents (such as toluene, xylene, and ethylbenzene, which are HAPs) and alcohol are mainly
used as the volatile portion of the ink, but water-based inks are becoming more popular
because of their lower cost and less potential for air pollution. However, a single press is not
compatible for use with both systems because water-based inks require more equipment
drying capacity and a different cell design.
Although some rotogravure inks contain solvents, additional solvents may be mixed into the
ink as well to obtain the desired viscosity. Publication gravure plants recover a large portion
of spent solvents from their ink, some of which is reused and some excess that is sold back to
the ink suppliers. Some virgin solvent, which has the same composition as the solvent in the
inks, is purchased for replenishment purposes, and a small amount is used for cleaning the
presses (EPA, 1995a).
Flexography
The ink used in flexography is of low viscosity because the ink must be fluid to print
properly. Most flexographic printing (including all flexographic newspaper and corrugated
carton printing) is done with waterborne inks, but alcohol or other low-viscosity, volatile
liquids are also used as the ink base. Solvents used must be compatible with the rubber or
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polymeric plates; thus, aromatic solvents are not used. Some of the components of solvent-
based flexographic ink include ethyl, methyl, n-propyl, and isopropyl alcohols; glycol ethers;
ethylene glycol; aliphatic hydrocarbons; acetates; and esters. Most of the solventborne
flexographic inks contain little or no HAPs (EPA, 1995b).
When flexography is used to print corrugated board and most paperboard, water-based inks
can be used; however, fast-drying inks are required for plastic films and packaging papers so
the web can be rewound or processed into the final product at the end of the press. When
printing pressure-sensitive labels, the ink must dry quickly without penetration (EPA, 1995b).
Offset Lithography
The solvents (high-boiling-temperature petroleum oils >400°F) in heatset inks are driven off
in a hot air or direct-flame dryer (400-500°F) to set the ink. Nonheatset inks dry by
adsorption or oxidation and are not released from the substrate under normal conditions.
Approximately 20 to 40 percent of the solvent remains in the substrate with heatset inks; 95
to 100 percent remains in the substrate with nonheatset inks (EPA, 1993a).
Emissions from the fountain solution will depend on whether alcohol or nonalcohol additives
are used. The concentration of VOCs in the fountain solution can vary from facility to
facility, and from job to job within any one facility (EPA, 1994a).
Solvents used for press cleanup are usually kerosene-type high-boiling-point hydrocarbons,
sometimes mixed with detergents (EPA, 1995a). These materials can contain up to
100 percent VOCs but are generally free of HAPs. Low-VOC cleaning solutions are also in
use where the VOC content is less than 70 percent, and often less than 30 percent VOCs
(EPA, 1994a).
Letterpress
Only web presses using solventborne inks are sources of emissions in this industry.
Letterpress newspaper and sheetfed printing use oxidative drying inks and are not a source of
emissions. Cleaning solutions are used with all letterpress operations (EPA, 1993a).
Screen Printing
Ink systems used in screen printing include ultraviolet cure, waterborne, solventborne, and
plastisol, with plastisol (polyvinyl chloride) being mainly used in textile printing.
Solvent-based ink systems contain aliphatic, aromatic, and oxygenated organic solvents (EPA,
1995a).
In-Process Fuel
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Fuels such as oil or natural gas are used to operate the dryers used in heatset offset
lithography, heatset letterpress, gravure, and alcohol-based flexography. In some cases,
recovered solvent may be used as supplemental fuel in the dryer. A boiler may be used to
generate steam for steam-/water-based flexography and to regenerate the activated carbon
beds used as control devices. The combustion byproducts include particulate matter (PM),
particulate matter with diameters less than 10 jig (PM10), sulfur oxides (SOX), nitrogen oxides
(NOX), VOCs, and carbon dioxide (CO). Recovered solvent may be burned in the dryer
(EPA, 1994a).
Storage Tanks
Graphic arts operations may use storage tanks to store inks, solvents, and fuels (oil).
2.9.2 CONTROL TECHNIQUES
Afterburners, both thermal and catalytic, can be used to control VOC emissions from the
heatset web offset lithography, rotogravure printing, and flexography. Activated carbon
adsorption can be used to control VOC emissions from rotogravure printing and flexography
(EPA, 1995a). Condenser filters with and without activated carbon can be used to control
VOC emissions from heatset offset lithography (EPA, 1994a). The condensers alone can
achieve 90 percent control, while activated carbon increases the control to 95 percent. Total
enclosure, with venting of collected VOCs to a control device, is used with rotogravure
printing. Pebble-bed incinerators that combine the functions of a heat exchanger and a
combustion device also can be used to control VOCs in the graphic arts industry (EPA,
1995a).
Refrigeration of the dampening solution is a process change that can achieve approximately
40 percent reduction of the alcohol emissions (which are VOCs) from offset lithographic
printing operations. The use of alcohol substitutes in the dampening solution of offset
lithographic printing operations can reduce or eliminate the use of alcohol (EPA, 1994a).
The use of lower-VOC-containing or lower-vapor-pressure cleaning solutions can reduce VOC
and HAP emissions from cleaning operations in all types of printing. Storing cleaning rags in
closed containers can control some of the fugitive emissions from cleaning (EPA, 1994a). In
screen printing, low-VOC- and/or HAP-emitting screen printing cleaning products are
available for the removal/reclamation of the stencil from the screen. Process modifications to
lower VOC/HAP emissions in screen reclamation are also being used, such as the Screen
Printing Association International (SPAI) Workshop Process, high-pressure water blaster, and
automatic screen washing system.
In 1978, a control technique guidelines (CTG) document (EPA, 1994a) was published for the
control of VOCs from rotogravure and flexographic printing operations (EPA, 1978). New
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Source Performance Standards (NSPS) for VOC emissions from publication rotogravure
printing were proposed in the Federal Register (FR) October 28, 1980 (45 FR 71538), and
promulgated November 8, 1982 (47 FR 50644). NSPS for VOC emissions from rotogravure
printing and coating of flexible vinyl were promulgated June 29, 1984 (49 FR 26885). In
1993, a draft CTG document was published for the control of VOC emissions from offset
lithographic printing. The draft CTG document was presented as an "Alternative Control
Techniques" (ACT) document and announced in June 1994, with modifications, as a result of
public comments submitted to EPA in response to the draft CTG (EPA, 1994a).
The following is a chronology of VOC regulations for the graphic arts industry:
• 1978: A CTG document was published for the control of VOCs from
rotogravure and flexographic printing operations (EPA, 1978).
• 1982: NSPS for VOC emissions from publication rotogravure were proposed
October 28, 1980 (45 FR 71538) and promulgated November 8, 1982 (47 FR
50644).
• 1984: NSPS for VOC emissions from rotogravure printing and coating of
flexible vinyl were promulgated June 29, 1984 (49 FR 26885).
• 1994: A draft CTG document was published for the control of VOC emissions
from offset lithographic printing in November 1993. The draft CTG was
reclassified as an ACT document and announced in June 1994. The ACT
information included revisions made in response to public comments to the
1993 draft CTG document (EPA, 1994a).
Although none of these above regulatory efforts were specifically directed towards HAPs,
many HAPs of concern in the printing industry are VOCs and, therefore, the same control
devices used to limit VOC emissions are also applicable to control of HAPs. A National
Emission Standard for Hazardous Air Pollutant (NESHAP) for the printing and publishing
industry was proposed in March 1995 (60 FR 13664; 40 CFR Part 63); the background
information document for the NESHAP is available (EPA, 1995a).
Table 7.2-5 summaries the national regulations that affect the graphic arts industry. Note that
in most cases there is no size cutoff for applicability of the regulation. State regulations may
also be in effect that are more stringent than federal regulations. The size cutoffs of these
regulations should be noted when preparing an area source inventory; in many cases the state
may make the federal rule more stringent by eliminating the size cutoff or facility age
exemption that will bring all sources under the regulation or extend the regulations statewide
that are primarily targeted for nonattainment areas.
7.2-16 Volume III
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TABLE 7.2-5
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NATIONAL REGULATIONS FOR THE GRAPHIC ARTS INDUSTRY
Type of
Printing
Rotogravure
Type of
Regulation
CTG (1978)1
NSPS (1982)"
NESHAP
(proposed 1995)
Applicability
Packaging facilities in
nonattainment areas
Publication facilities
in nonattainment areas
Packaging and
publication facilities
in nonattainment areas
Publication facilities
Publication facilities
that are major sources0
Product and packaging
facilities that are
major sources0
Regulated
Pollutant
VOCs
VOCs
VOCs
VOCs
HAPs
HAPs
Control Requirement
70-80% capture
90% destruction
65% overall control
75-85% capture
90% removal
75% overall control
Inks with 25% or less solvent
Ink with 60% nonvolatile
component
84% overall control
92% overall control
95% overall control
<0.2 kg emitted per kg ink solids
<0.04 kg emitted per kg ink solids
for presses with a common solvent
recovery system
Control Method(s)
Incineration
Carbon adsorption
Material substitution
Material substitution
Solvent recovery
systems or
waterborne inks
0>
O
CD
O
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I
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I
CD
TABLE 7.2-5
(CONTINUED)
Type of
Printing
Offset
Lithography
Type of
Regulation
ACT (1994)4e
Applicability
Heatset web facilities
that emit >15 Ib per day
total emissions
Nonheatset web facilities
that emit >15 Ib per day
total emissions
Nonheatset sheet
facilities that emit
>15 Ib per day total
emissions
Newspaper facilities that
emit >15 Ib per day total
emissions
Cleaning solution at any
facilities that emit
>15 Ib per day total
emissions
Regulated
Pollutant
VOCs
VOCs
VOCs
VOCs
VOCs
Control Requirement
95% control of ink emissions
Fountain solution VOCs < 1.6% (weight)
Fountain solution VOCs < 3% (weight)
Fountain solution VOCs < 5% (weight)
Fountain solution VOCs < 5% (weight)
Fountain solution VOCs < 5% (weight)
Fountain solution VOCs < 8.5% (weight)
Cleaning solution VOCs < 5% (weight)
Fountain solution VOCs < 5% (weight)
VOCs < 30% (weight)
Vapor pressure < \0 mm Hg at 20°C
Control Method(s)
Refrigeration
Alcohol substitutes
Alcohol substitutes
Refrigeration
Alcohol substitutes
Alcohol substitutes
a EPA, 1978.
b EPA, 1980.
0 Emit over 10 tpy of any one HAP or over 25 tpy total of two or more HAPs.
d EPA, 1994a.
e Recommended for nonattainment areas.
0}
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
A number of methodologies are available for estimating emissions from the graphic arts
industry. The method used is dependent upon the degree of accuracy required in the estimate,
the available data, and the available resources.
This section discusses the methods available for estimating emissions from area sources in the
graphic arts industry and identifies the preferred method. A discussion of the data elements
needed for each method is also provided. All methods must take into account point source
facilities of graphic arts operations and their emissions.
3.2 AVAILABLE METHODOLOGIES
3.2.1 VOLATILE ORGANIC COMPOUNDS
The VOCs released into the air by graphic arts operations are from the evaporation of the
VOCs contained in the raw materials such as inks, fountain solution (offset lithographic
printing only), and cleaning solutions used in the printing processes. There are three
approaches to estimating the amount of VOCs emitted from this source category:
• Facility Survey Method;
• Ink Sales Emission Factor Method; and
• Per Capita Emission Factor Method.
The Facility Survey Method, the preferred method, and Ink Sales Emission Factor Method,
the first alternative method, take into account the variations in VOC emissions between each
printing type and in the type of emission controls for each type. With the Facility Survey
Method, the amount of VOCs recycled can also be addressed. However, for offset
lithographic printing processes, the Facility Survey Method requires incorporating assumptions
about the amount of VOCs in the inks that are retained in the substrate and not released
during printing. The emissions estimate for offset lithographic printing facilities will not be a
simple mass balance calculation (because some ink solvent VOCs are retained in the
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
substrate). Therefore, an emissions estimate from facility surveys for offset lithography will
be more uncertain than for other than printing processes where all the solvent used is emitted.
The Per Capita Emission Factor Method assumes a correlation between population size and
graphic arts emissions, which is probably a very weak assumption. Emissions estimated using
the Per Capita Emission Factor Method will not reflect variability between regions and,
depending on the emission factor used, may not reflect the distribution of the different types
of printing within the region and the controls that are being used.
3.2.2 HAZARDOUS AIR POLLUTANTS
HAP emissions from graphic arts operations can be estimated using two methods:
• Facility Survey Method; or
• Applying speciation profiles to the VOC emission estimate obtained using the
Ink Sales Emission Factor or Per Capita Emission Factor Methods.
The Facility Survey Method is the preferred method because it provides the most accurate
information on material usage and HAP content. The effect of VOC controls on HAP
emissions can also be obtained when using this method.
Speciation profiles can be used with either the Facility Survey or Ink Sales Emission Factor
Methods as alternative approaches when a detailed survey is not practical. The least desirable
method is the use of speciation profiles with the Per Capita Emission Factor Method.
The speciation profiles will need to be updated frequently as a result of changes in product
use that are now occurring to meet new regulations (Titles I, III, and V of the Clean Air Act
Amendments) and/or as better quality profiles are available. Local speciation profiles may
also be available.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements used to calculate emission estimates for the graphic arts operations will
depend on the methodology used for emission estimation. The following data elements are
necessary for emissions calculations and should be obtained for each method.
For the Facility Survey Method (from each facility sampled):
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• Type of printing (rotogravure, flexography, etc.);
• Primary business;
• Number of employees, and number of employees involved in printing
operations;
• Amount of VOC-containing raw materials by type;
• VOC content of each product type (weight percent);
• Percentage of VOCs contained in the material that is emitted during graphic
arts operations that is estimated or obtained from source test measurements;
• HAP content of product or solvent by type (weight percent) for all HAPs in the
product and estimated amount of HAPs emitted during printing operations;
• Controls used at facility, control efficiency; and
• Amount of VOCs or HAPs recycled.
For the first alternative method, the Ink Sales Emission Factor Method:
• Ink sales for the state, or data from the U.S. Census Bureau;
• Uncontrolled point source emissions for graphic arts operations; and
• Controls in use in the inventory region.
For the second alternative method, the Per Capita Emission Factor Method:
• Population of the inventory area; and
• Per capita emission factor from a national database or local survey.
3.3.2 DOUBLE COUNTING CONSIDERATIONS
Double counting can occur for this source category either because emission sources are
counted as both graphic arts and as industrial surface coating area sources, or because point
source emissions are not properly subtracted from estimates of total emissions. In either case,
a clear definition of what processes and industries are included in the graphic arts and
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
industrial surface coating source categories should be made before data collection for either
source category begins. In particular, industries with SIC codes that are not in the printing
and publishing SIC of 27 should be examined for overlap between the two source categories.
3.3.3 APPLICATION OF CONTROLS
Add-on controls may be used to control ink emissions in the graphic arts industry. Material
substitution may also be used to control emissions from all aspects of printing that include the
use of water-based inks, reduced alcohol and/or alcohol substitutes in fountain solution, and
the use of lower-VOC or low-vapor-pressure cleaning solutions. Rule effectiveness (RE) may
be less than 100 percent for add-on controls; RE for material substitution can be assumed to
be 100 percent.
Rule penetration will depend on the cutoff size or exemptions for the applicable regulations
and can be calculated based on the percentage of sources within the category that are affected
by the rule. Because a large number of small sources contribute to total emissions for
graphic arts operations, many of the regulations will apply to area sources as well as point
sources. In some cases, a lower size cutoff that does not correspond with point versus area
distinctions may be specified by the regulation.
3.3.4 SPATIAL ALLOCATION
Spatial allocation may be needed in two possible cases: (1) allocation of state or regional
activity to a county level, and (2) allocation of county level emission estimates to a modeling
grid cell. In each case, a surrogate for activity should be found that can approximate spatial
variation for this category, if specific locations cannot be identified. The preferred method of
spatial allocation is to use the facility location collected with other survey information under
the preferred method.
Most printing operations occur in or near urban areas to be close to the customers, labor
force, or transportation centers. Some national companies locate their large printing plants in
suburban or rural areas where land is less expensive. Spatial apportioning can be performed
with land use data obtained from county planning departments or population distributions
available from the U.S. Census Bureau. Using population to allocate estimated emissions or
activity by county or within a grid cell is fairly straightforward and is discussed in Chapter 1,
Introduction to Area Source Emission Inventory Development. Land use data can be used to
generalize building type (i.e., commercial versus residential).
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Alternatively, printing facility distributions can be used from County Business Patterns3 (U.S.
Bureau of the Census, Department of Commerce) or the local "Yellow Pages" to allocate
some segments of the category, such as lithographers. However, these indicators may not be
useful for in-house or captive printing operations. The importance of these smaller sources to
the total area source inventory will determine the usefulness of the data.
3.3.5 TEMPORAL RESOLUTION
Seasonal Apportioning
There are no dramatic seasonal fluctuations in production in the graphic arts industry;
therefore, it can be assumed that emissions are distributed uniformly throughout the year. To
determine seasonal emissions, the fraction of the year that corresponds to the season of
interest can be multiplied times annual emissions to obtain seasonal emissions.
Daily Resolution
Based on a review of the National Acid Precipitation Assessment Program (NAPAP) data
(EPA, 1990), 75 percent of emissions activity occurs on weekdays, 20 percent on Saturdays,
and 5 percent on Sunday. For allocation on a hourly basis, 65 percent of activity occurs
between 9 a.m. and 6 p.m., with the remaining 35 percent occurring between 7 p.m. and 12
a.m.
3.3.6 PROJECTING EMISSIONS
The following equation should be applied when the base year emissions are calculated by the
emission factor method and the emission factor takes into account the control level for the
projection year (EPA, 1993b):
a See the most recent publication, which can be obtained from the U.S. Bureau of the
Census, Department of Commerce, Washington, D.C.
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CHAPTER 7 - GRAPHIC ARTS
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EMISPY = ORATEBY * EMFPY
1 -
CE
PY
RP
PY
100
100
100
*GF
(7.3-1)
where:
EMISpY
ORATE
EMF
BY
PY
CE
RE
RP
GF
'PY
'PY
PY
Projection year emissions: ozone season typical weekday (mass of
pollutant/day);
Base year operating rate (activity level);
Projection year (postcontrol) emission factor (mass of pollutant/
production unit);
Projection year control efficiency (percent);
Projection year rule effectiveness (percent);
Projection year rule penetration (percent); and
Growth factor (dimensionless).
Current control projection emissions in this case are calculated if the projection year emission
factor and RE values represent current regulatory or permit conditions and/or actual conditions
when appropriate.
Tools for the development and use of growth factors are discussed in Chapter 1 of this volume.
Forecasts of ink or paper sales from the data sources discussed in Section 5 of this chapter can
also be used to estimate future growth in the graphic arts.
7.3-6
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
The preferred method for calculating emissions from graphic arts is the Facility Survey Method.
In this method, graphic arts facilities in the inventory area will need to identified. Although
initially this is a labor-intensive approach, the results can be used to develop an emission factor
specific to the inventory region. Subsequent inventories can use this factor with updated activity
data to estimate emissions. If it is not possible to inventory all of the graphic arts facilities in
the area, then a representative sample of these graphic arts facilities can be surveyed, and the
results can then be scaled up for all facilities in the area. Please refer to Volume I of this series,
Chapter 5, Inventory Development, Chapter 1 of this volume; and Volume VI of this series,
Quality Assurance Procedures, for more detailed information about using surveys.
4.1 PLANNING
Identify facilities that would be suitable survey recipients, noting those that are point sources.
Facilities engaged in graphic arts may be listed as part of a state or local permitting program.
Look for facilities that may have graphic arts facilities as part of another, more significant
operation. Title V or other operating permits may include information from such facilities.
Facilities can also be identified from the local employment office, professional organizations,
and entries in local tax records for printing equipment.
Prepare a survey form or forms that collect the information needed for the inventory. At a
minimum, the survey should request:
• Name, location, and contact person of the operation;
• Primary activity and type of graphic arts process(es) used at the facility;
• Amount of inks, fountain solution, and cleaning solution used at the facility. If
the amount is expressed in gallons, the density of the materials will be needed as
well, in order to calculate emissions in weight units such as pounds or kilograms;
• The VOC or the HAP content of each material, in pounds, or as a weight
percentage;
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
• The amount of material that is recovered and recycled, but not reused within the
facility; and
• Control equipment and control efficiency.
During the planning phase, a scaling method should be identified and the survey form should
request the information needed to scale up the data collected, such as total employment or
production workers. If the survey results are to be converted into an area-specific emission
factor, the surrogate activity will also need to be collected. Possible surrogate factors would be
per unit, per facility, or per employee factors. If practical, use production workers rather than
the total number of employees.
4.2 DISTRIBUTION
Survey distribution will be determined by the budget for the category. Surveys can be
distributed by mailing, with initial and follow-up telephone calls. Initial calls may be useful to
identify the portion of the survey set that does not have graphic arts processes occurring on their
premises. These facilities are an important part of the sample because when the survey is scaled
up, if that portion of facilities were to have emissions assigned to them, the emission estimates
would be too high. Survey distribution issues are discussed in Chapter 1, Introduction to Area
Source Emission Inventory Development, under Surveys, in Section 6.
4.3 SURVEY COMPILATION AND SCALING
Use the survey results to either develop an emission factor or an areawide emission estimate. If
material amounts were reported in gallons, then the gallons need to be converted to weight units:
Amount used
in pounds
Amount of
material (gal)
x
Density factor
(lb/gal)
(7.4-1)
Note that the amount of VOCs emitted during printing (volatile fraction) is not always
equivalent to the measured or estimated VOC content of the raw material (especially for offset
lithographic printing), since all the VOCs contained in the raw material may not be emitted
during printing. The data used in the alternative Ink Sales Emission Factor Method to determine
the VOC emissions by amount of ink used should be used with the Facility Survey Method if
the volatile fraction specific to the process is not available. Refer to the Ink Sales Emission
Factor Method description and emission factors in Section 5 of this chapter. For example,
although nonheatset lithographic inks may contain some VOCs, only 2 percent of the VOCs are
emitted during printing.
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CHAPTER 7 - GRAPHIC ARTS
Use the equation below to estimate uncontrolled total emissions for each pollutant (P) emitted,
from each type of graphic arts operation (i). Point source emissions should calculated using the
same equation and subtracted from the total emissions calculated using Equation 7.4-2.
Total
Uncontrolled Emissions p
from
Graphic Arts
= £
Amount
Raw Material
[ Used
( Volatile ^
1 Fraction
( Amount^!
~ I^RecycledJ
(7.4-2)
An area source emission factor can be developed by calculating the area source emissions and
dividing the area source emissions by the area source activity rate:
Graphic Arts
Emission
Factorpi
/ \
Total
Uncontrolled
Emissionspi
-
/ \
Uncontrolled
Point Source
Emissionspi
Area Source
-f- Activity
Rat^
(7.4-3)
When the emission factor is used, control efficiency (CE), rule penetration (RP), and rule
effectiveness (RE) need to be included as part of the emissions calculation. Please refer to
Section 4.2 in Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development for more information about developing these factors.
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
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7.4-4 Volume III
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
The alternative methods for calculating emissions from the graphic arts source category are the
Ink Sales Emission Factor Method and the Per Capita Emission Factor Method. This section
provides an outline for estimating emissions from either ink sales or population data. The
procedures follow below.
5.1 INK SALES EMISSION FACTOR METHOD
In the Ink Sales Emission Factor Method, total uncontrolled emissions from all graphic arts
operations sources are estimated using national or state ink sales data. This method's advantages
are:
• Inks are common to all printers and not used by any other source except printers;
• The VOC content of the inks is fairly consistent and can be estimated on the
average; and
• The printing processes are technically consistent within each printing type (i.e.,
emissions per unit of ink will be approximately the same from one facility to
another) for ink with the same VOC content used in the same type of printing
process.
If the amount of printing ink that is recycled is expected to be significant in the inventory area,
the emission estimate needs to be adjusted accordingly. Use information collected from the
point source inventory to determine the rate of recycling at graphic arts facilities.
Uncontrolled point source emissions for each printing type are subtracted from the total
uncontrolled emissions calculated using this method to obtain uncontrolled area source
emissions. If the uncontrolled point source emissions from graphic arts operations are not
available or cannot be estimated, then the Facility Survey Method or the other alternative method
should be used.
The total area source emissions from graphic arts operations are estimated from the sum of
emissions estimated for each of the six types of printing. If local information on ink sales is
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CHAPTER 7 - GRAPHIC ARTS
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available, it should be used for this method. If local information is not available, the following
approach should be used to estimate ink sales in the inventory area:
First, obtain apportioned ink sales by the following steps:
• Obtain the amount of inks produced, in pounds, in the United States for the
inventory year, from the Census Bureau's Census of Manufactures, Industry Series
for SIC Code 289, Miscellaneous Chemical Products.a
• Apportion the nationwide ink amount produced for the inventory year to the state
level by the ratio between state and national employment in printing and
publishing (SIC Code 27). The Census Bureau's report, Statistics for Industry
Groups and Industries, can provide this information.a The equation to use is:
(7.5-1)
Total Ink
Sales for =
State
Total Ink
Sales for
US
Printing
Employment
in State
Printing
Employment
in US
Next, correct the apportioned ink sales amount for point sources in the state. To do this,
identify point sources (from the point source inventory) that have graphic arts processes at their
facilities. The Aerometric Information Retrieval System (AIRS) Facility Subsystem (AFS)
Source Classification Codes (SCCs) in Table 7.5-1 can be used to identify the applicable graphic
arts emissions from the point source inventory. For these facilities, the following additional
information should be collected:
• Facility location (county or inventory area);
• Amount of ink used by the facility (amount purchased minus amount recycled);
• SIC Code for the facility's primary operation; and
See the most recent publication, which can be obtained from the U.S. Bureau of the
Census, Department of Commerce, Washington, D.C.
7.5-2
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11/18/96
CHAPTER 7 - GRAPHIC ARTS
TABLE 7.5-1
AFS SOURCE CLASSIFICATION CODES FOR GRAPHIC ARTS
Point Source
Description
Offset Lithography -
All Processes
Heatset Offset
Lithography
Nonheatset Offset
Lithography
Letterpress - All
Processes
Process Description
Dampening Solution
with Isopropyl Alcohol
Dampening Solution
with Alcohol Substitute
Cleaning Solution -
High Solvent Content
Cleaning Solution -
Water-Based
Heatset Lithographic
Inks
Heatset Lithographic
Inks
Heatset Lithographic
Inks
Heatset Ink Mixing
Heatset Solvent
Storage
Nonheatset
Lithographic Inks
Nonheatset
Lithographic Inks
Nonheatset
Lithographic Inks
Letterpress Cleaning
Solution
sec
4-05-004-13
4-05-004-15
4-05-004-16
4-05-004-17
4-05-004-11
4-05-004-12
4-05-004-01
4-05-004-21
4-05-004-22
4-05-004-31
4-05-004-32
4-05-004-33
4-05-002-15
Units
Tons Alcohol Used
Tons Substitute Used
Tons Pure Solvent
Used
Tons Used
Tons Solvent in Ink
Gallons Ink
Tons Ink
Tons Solvent in Ink
Tons Solvent Stored
Tons Ink
Tons Solvent in Ink
Gallons Ink
Tons Solvent
Consumed
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CHAPTER 7 - GRAPHIC ARTS
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TABLE 7.5-1
(CONTINUED)
Point Source
Description
Heatset Letterpress
Gravure Printing
Flexographic
Alcohol-Based Inks
Process Description
Heatset Letterpress Ink
Heatset Letterpress Ink
Heatset Letterpress Ink
Ink Mixing
Storage
Gravure Ink
Gravure Ink
Gravure Ink - High
Solvent Content
Gravure Ink -
Water-Based
Ink Mixing
Solvent Storage
Gravure Cleanup
Solvent
Flexographic Ink Use -
Alcohol-Based
Flexographic Ink Use -
Alcohol-Based
Flexographic Ink Use -
Alcohol-Based
sec
4-05-002-01
4-05-002-11
4-05-002-12
4-05-006-01
4-05-007-01
4-05-005-01
4-05-005-11
4-05-005-13
4-05-005-12
4-05-006-01
4-05-007-01
4-05-005-14
4-05-003-01
4-05-003-11
4-05-003-13
Units
Tons Ink
Tons Solvent in Ink
Gallons Ink
Tons Solvent in Ink
Tons Solvent Stored
Tons Ink
Tons Solvent in Ink
Gallons Ink
Gallons Ink
Tons Solvent In Ink
Tons Solvent Stored
Tons Solvent
Consumed
Tons Ink
Tons Solvent in Ink
Gallons Ink
7.5-4
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CHAPTER 7 - GRAPHIC ARTS
TABLE 7.5-1
(CONTINUED)
Point Source
Description
Flexographic
Alcohol-Based Inks
(Continued)
Flexographic Steam/
Water-Based Ink
Miscellaneous
Process Description
Flexographic Ink Use -
Alcohol-Based
Flexographic-Alcohol
Cleanup
Ink Mixing
Solvent Storage
Flexographic Ink Use -
Steam/Water-Based
Flexographic Ink Use -
Steam/Water-Based
Flexographic Ink Use -
Steam/
Water-Based
Steam/Water-Based Ink
Mixing
Steam/Water-Based Ink
Storage
Cleaning Rags
sec
4-05-003-12
4-05-003-14
4-05-003-01
4-05-007-01
4-05-003-15
4-05-003-16
4-05-003-17
4-05-003-18
4-05-003-19
4-05-008-01
Units
Gallons Ink
Tons Solvent
Consumed
Tons Solvent in Ink
Tons Solvent Stored
Tons Ink
Tons Solvent in Ink
Tons Solvent Stored
Tons Solvent Stored
Tons Solvent Stored
Tons Solvent Used
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CHAPTER 7 - GRAPHIC ARTS
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• Facility's employment, if the SIC Code is 27, and if it is available.
Subtract the amount of ink (do not include fountain solutions or cleaning solutions) used by all
point source facilities in the state from the total amount of ink allocated to the state:
• Determine the number of employees at printing and publishing point source
facilities (SIC Code 27) in the state and subtract those employees from the state
total. The remaining employee numbers will be used to apportion the area source
ink sales numbers.
• If the numbers of employees at the printing and publishing point source facilities
is not available from the facilities' permits, point source inventory information, or
local employment data, then the employment can be derived from the U.S Bureau
of the Census report, County Business Patterns.
When employment in County Business Patterns is presented as a number of
facilities that have employment within a range of values, the total number of
employees for all the facilities listed in each range can be estimated using the
midpoint of the indicated size range. See Example 7.5-1 for more details.
The remaining amount of ink can be assumed to be responsible for area source emissions. This
ink should be apportioned from the state level to the inventory area, using the non-point-source
employment in facilities with SIC Codes of 27.
Apportion the statewide ink sales data for each type of printing to the inventory region by the
ratio of the printing employment in the inventory region for each printing type (t) to the state
printing employment, as follows:
Total Ink
Sales for
Inventory Region
Total Ink
Sales for
State
Printing
Employment
in Inventory
Region
Printing
Employment
in State
(7.5-2)
Apportion the inventory region ink sales to each type of printing, using the
estimated percentage product market share of ink sales for each type of printing in
Table 7.2-3.
7.5-6
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CHAPTER 7 - GRAPHIC ARTS
Example 7.5-1:
If an inventory for the region contains five graphic arts point sources, and the top five
graphic arts facilities, by total employment, in the County Business Patterns for the
region are distributed as follows: three facilities in the 100 to 149 employees per
facility size range and two facilities in the 50 to 99 employee per facility size range,
then the total number of employees for point sources can be calculated using the
midpoint of the employee size ranges, as in the equation below:
Total Employees =
at Point Sources
(100 + 149)
+2
(50 + 99)
= 3(124.5) + 2(74.5) = 523
Assume that point sources correspond to the facilities with the highest number of
employees. Start with the facilities with the largest number of employees and sum the
number of employees at the largest facilities for as many facilities as there are point
source graphic arts facilities in the county for the desired SIC.
Uncontrolled emission factors for ink, fountain solution, and cleaning solution, in
terms of pounds of VOCs emitted per pound of ink used, are in Table 7.5-2. The
equation to calculate uncontrolled emissions for a single printing type (t) is:
(7.5-3)
Uncontrolled
VOC Emissions
Area Source
Inkt Sales
in the
Inventory Region
| Ink Emission]
^ Factort JH
/ \
Fountain
Solution
Emission
, Factort/
+
f Y
Cleaning
Solution
Emission
V Factor, J_
See Table 7.2-5 in this chapter for a summary of national rules for the graphic arts industry.
Other types of controls and control efficiencies will vary from area to area and more stringent
controls may be required, which will need to be identified from local rules or, if necessary,
through a survey of a small cross section of area source graphic arts facilities. Please refer to
Section 4.2 in Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development for more information about developing these factors. Alternatively, no controls
could be applied to the area source emission estimates, which will result in the most
conservative estimate.
EIIP Volume III
7.5-7
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CHAPTER 7 - GRAPHIC ARTS
11/18/96
TABLE 7.5-2
COMPONENT VOC EMISSION FACTORS FOR GRAPHIC ARTS OPERATIONS
Type of Printing
Rotogravure
Flexography
Offset Lithography
Heatset
Nonheatset Web
Nonheatset Sheet
Newspaper
Letterpress
Screen
Planographic
Component Emission Factors
(Pounds of VOC Emitted per Pound of Ink Used)
Ink
0.70a
0.60a
Fountain Solution
NAb
NA
Cleaning Solution
0.03a
0.04a
0.32C
0.02C
0.02C
0.02C
0.24d
f
f
0.90C
0.53C
1.25C
0.07C
NA
NA
NA
0.03C
0.03C
1.10C
0.07C
e
f
f
a Bay Area SIP (engineering judgement).
b NA = not applicable.
c EPA, 1994a.
d EPA, 1993a.
6 Unknown at this time; use the emission factor for newspaper offset lithography if no other information is
available.
.p
Unknown at this time. The Facility Survey Method should be used for these sources until information is
available if they are expected to be significant area source emissions.
7.5-8
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Final 11/18/96
CHAPTER 7 - GRAPHIC ARTS
Calculate controlled area source emissions for each printing type (t) for the
inventory region with the following equation:
Controlled
Area Source =
Emissions,
Area Source
Inkt Sales
in the Inventory Region
Fountain Solution
Ink Emission
Factor
Emission Factort ) x
Cleaning Solution!
Emission Factor x
1 -
1 -
CE, RE,
RP,
100 100 100,
CEFS ^ REFS
"Too" ~Too~
100
1 -
'CECS x RECS x RPCJ
v 100 100 100 J
(7.5-4)
where:
(CEIFSCS)
Control efficiency (percent) for each material used: ink (I), fountain
solution (FS), and cleaning solution (CS);
(REIFSCS) = Rule effectiveness (percent); and
(RPIFSCS) = Rule penetration (percent).
• Calculate the total area source controlled VOC emissions from graphic arts
operations in the inventory region by summing the controlled VOC emissions for
each type of printing (t):
Total Controlled
Area Source
VOC Emissions in
Inventory Region
Total Controlled
VOC Emissionst in the
Inventory Region
(7.5-5)
5.2 PER CAPITA EMISSION FACTOR METHOD
EIIP Volume III
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CHAPTER 7 - GRAPHIC ARTS
Final 11/18/96
This method calculates graphic arts emissions from the inventory area population. The
correlation between population and graphic arts activity is not strong and emissions calculated
using this method will not reflect local variability in activity, controls, or types of printing
taking place.
• Obtain the population of the inventory region from federal, state, or local census
data for the current inventory year and the most recent year for which emission
estimates derived from survey data are available.
• Estimate the total VOC emissions from graphic arts facilities with less than 100
tons per year VOC emissions, as in the equation below:
Total Uncontrolled
Emissions from
Graphic Arts
Facilities with
<100 tpy Emissions
(tons)
Population of
Inventory
Region
0.00065
(tons VOC per capita)
(7.5-6)
Note: The factor 0.00065 tons VOC per capita is equivalent to 1.3 pounds per
person per year (EPA, 1991). This factor was derived for facilities with
emissions that are less than 10 tpy, and is independent of the number of
facilities with emissions greater than 100 tpy in the inventory area.
Subtract the emissions from point sources in the inventory region (as defined by
the region) with emissions less than 100 tons per year using data from the point
source inventory as in the equation below:
Total Uncontrolled
Emissions from
Graphic Arts
Area Sources
Total Uncontrolled
Emissions from
Graphic Arts
Facilities with
<100 tpy Emissions
Total Uncontrolled
Emissions from
Graphic Arts
Point Sources with
<100 tpy Emissions
(7.5-7)
If information about CE, RE, and RP is available, then the following equation
should be used:
7.5-10
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Final 11/18/96
CHAPTER 7 - GRAPHIC ARTS
Total Controlled
Emissions from =
Area Sources
Total Uncontrolled
Emissions from
Graphic Arts
Area Sources
r fCEx REx RP^l (7.5-8)
L U00 10° 10°J J
If control information is not available, then the more conservative uncontrolled
estimate should be used.
EIIP Volume III
7.5-11
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
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7.5-12 Volume III
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QUALITY ASSURANCE/
QUALITY CONTROL (QA/QC)
Data handling for all of the methods do not involve any category-specific issues; refer to the
discussion of data handling QA/QC in Volume VI for more information. When using the
Facility Survey Method, the survey planning, sample design, and data handling should be
planned and documented in the inventory QA/QC plan. Refer to the discussion of survey
planning and survey QA/QC in Chapter 1 of this volume.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The preferred method gives higher quality estimates than the alternative methods, but requires
significantly more effort. The level of effort for the Facility Survey Method requires from 100
to 800 hours depending on the size of the inventory region, the number of graphic arts
operation facilities, and the level of detail in the survey. The level of effort for the Ink Sales
Emission Factor Method requires between 100 and 200 hours depending on the size of the
inventory region, the number of graphic arts operation facilities, and the ease in obtaining the
appropriate ink sales data. The level of effort required to calculate emissions using the Per
Capita Emission Factor Method ranges from 8 to 40 hours.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 7.6-1, 7.6-2, and 7.6-3. A range
of scores is given for the preferred and first alternative method because the implementation of
these methods can vary. All scores assume that good QA/QC measures are performed and that
no significant deviations from the prescribed methods have been made. If these assumptions
are not met, new DARS scores should be developed according to the guidance in Appendix F
of EIIP Volume VI, Quality Assurance Procedures.
The preferred method gives a higher DARS score than the alternative methods, with the
Facility Survey Method scoring higher than the Ink Sales Emission Factor Method that in turn
scored higher than the Per Capita Emission Factor Method. The alternative methods have
scores of 0.5 and 0.31, and the preferred method has a score ranging from 0.56 to 0.76. The
relatively high score for the Ink Sales Method assumes that ink sales data are available. This
method will have a lower score if the data cannot be obtained directly, and national data must
be apportioned.
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
6.1.2 SOURCES OF UNCERTAINTY
Some of the uncertainty of the emissions estimates based on the Facility Survey Method can be
quantified using standard statistical methods. A relative and qualitative assessment can be
made for other methods. The Facility Survey Method will be the least uncertain, since (in
theory) the local mix of process types and sizes will be accounted for. Emissions from printing
types in which most of the ink evaporates from the substrate can be estimated by mass balance
with a high degree of certainty. The uncertainty in the emissions estimate is highest for
material when an estimate of the amount of VOCs retained in the substrate is needed and is
comparable in magnitude to that emitted (for heatset offset lithographic printing only).
However, the scaling of the survey results will need to be planned with care. The surrogate(s)
should reflect the printing activity for each facility including the nonpublishing and printing
industries that use graphic arts processes.
The Ink Sales Emission Factor Method's advantage is that the ink sales data and the
information used for the apportioning method are readily available and inexpensive. However,
the use of surrogate apportioning factors to apportion the national ink usage to the inventory
area and national percentages to allocate ink usage to the different types of printing introduces
uncertainty. Because the estimated emissions of each type of material used in printing is not
expected to vary widely from facility to facility, and because the type of printing is usually
known with a high degree of certainty, the emission factors used in the Ink Sales Emission
Factor Method will have the same certainty as that used in the Facility Survey Method.
The Per Capita Emission Factor Method will have the highest degree of uncertainty, since a
true relationship between population and printing has not been established. Since the per capita
emission factor was developed from national data, as the spatial scale is reduced from the
national level, the uncertainty of the emissions estimated is greatly increased. Also, because of
variation in emissions among the types of printing, population data will likely not reflect the
local distribution of printing type, and consequently, emissions.
7.6-2 Volume III
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Final 11/18/96
CHAPTER 7 - GRAPHIC ARTS
TABLE 7.6-1
FACILITY SURVEY METHOD DARS SCORES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5
0.8 - 0.9
0.9
0.8 - 1.0
0.83 - 0.90
Activity
0.8 - 0.9
0.5 - 0.8
0.9 - 1.0
0.8 - 1.0
0.75 - 0.85
Emissions
0.4 - 0.45
0.4 - 0.72
0.81 - 0.90
0.64 - 1.0
0.56 - 0.76
TABLE 7.6-2
INK SALES EMISSION FACTOR METHOD DARS SCORES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.4 - 0.5
0.8 - 0.9
0.7 - 0.6
0.7 - 0.6
0.65
Activity
0.6
0.8 - 0.9
0.7 - 0.6
0.9
0.75
Emissions
0.24 - 0.30
0.64 - 0.81
0.49 - 0.36
0.63 - 0.54
0.5 - 0.49
EIIP Volume III
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CHAPTER 7 - GRAPHIC ARTS
Final 11/18/96
TABLE 7.6-3
PER CAPITA METHOD DARS SCORES
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.4
0.5
0.3
0.5
0.43
Activity
0.8
0.4
1.0
1.0
0.75
Emissions
0.32
0.2
0.27
0.45
0.31
7.6-4
Volume III
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DATA CODING PROCEDURES
This section describes the codes available to characterize the graphic arts emission estimates.
Consistent categorization and coding will result in greater uniformity between inventories.
Inventory planning for data collection calculations and inventory presentation should take the
data formats presented in this section into account. Available codes and process definitions
may impose constraints or requirements on the preparation of emission estimates for this
category.
7.1 PROCESS AND CONTROL CODES
The source category process codes for the graphic arts operations are shown in Table 7.7-1.
These codes are derived from the EPA's AIRS Area and Mobile Source (AMS) source
category codes (EPA, 1994b).
The control device codes shown in Table 7.7-2 may be used in AMS to record the level of
control used for this source in the inventory region. Federal, state, and local regulations can be
used as guides to estimate the type of control used and the level of efficiency that can be
achieved. Be careful to apply only the regulations that specifically include area sources. If a
regulation is applicable only to point sources, it should not be assumed that similar controls
exist at area sources without a survey. The equations that utilize the control efficiency to
calculate area source emissions for the inventory region are discussed in Chapter 1 of this
volume.
Other control devices may be used in the graphic arts industry. The "099" code can be used
for miscellaneous control devices that do not have a unique control device identification code.
The "999" code can be used for a combination of control devices where only the overall
control efficiency is known.
EIIP Volume III 1.1-I
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CHAPTER 7 - GRAPHIC ARTS
Final 11/18/96
TABLE 7.7-1
AIRS AMS CODES FOR THE GRAPHIC ARTS
Category Description
Graphics Arts: All Processes
Process Description
Total: All Solvent Types
AMS Code
24-25-000-000
Units
Tons VOCs Emitted
TABLE 7.7-2
AIRS CONTROL DEVICE CODES
Control Device
Code
Catalytic Afterburner
Catalytic Afterburner with Heat Exchanger
Direct Flame Afterburner
Direct Flame Afterburner with Heat Exchanger
Activated Carbon Adsorption
Vapor Recovery System
Process Change
Process Enclosed
Miscellaneous Control Device
Combined Control Devices
019
020
021
022
048
047
046
054
099
999
7.7-2
Volume III
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8
REFERENCES
Darnay, AJ. (Editor). 1990. Manufacturing USA, A Ward's Business Directory (First Edition).
Gale Research, Inc., Detroit, Michigan.
EPA. 1995a. National Emission Standards for Hazardous Air Pollutants: Printing and
Publishing Industry-Background for Proposed Standards. U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, EPA-453/R-95-002a. Research Triangle
Park, North Carolina.
EPA. 1995b. Economic Impact Analysis for the Printing and Publishing NESHAP.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-452/D-95-001. Research Triangle Park, North Carolina.
EPA. 1994a. Alternative Control Techniques Document: Offset Lithographic Printing.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-453/R-94-054. Research Triangle Park, North Carolina.
EPA. 1994b. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1993a. Compilation of Air Pollution Emission Factors, Volume I: Stationary Point and
Area Sources, Fourth Edition and Supplements A-F, AP-42 (September 1985 through
September 1991), GPO 055-000-00251-7. U.S. Environmental Protection Agency, Office of
Air Quality Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1993b. Guidance on the Relationship Between the 15 Percent Rate of Progress Plans
and Other Provisions of the Clean Air Act. U.S. Environmental Protection Agency,
EPA-452/R-93-007 (NTIS PB93-200525). Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emissions Inventories for Carbon Monoxide
and Precursors of Ozone, Volume 1: General Guidance for Stationary Sources.
U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-450/4-91-016 (NTIS PB92-112168). Research Triangle Park, North Carolina.
EIIP Volume III 7.8-1
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CHAPTER 7 - GRAPHIC ARTS Final 11/18/96
EPA. 1990. The 1985 NAPAP Emission Inventory: Development of Temporal Allocation
Factors. U.S. Environmental Protection Agency, EPA-600/7-89-010d. Research Triangle Park,
North Carolina.
EPA. 1980. Publication Rotogravure Printing - Background Information for Proposed
Standards. U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, EPA-450/3-80-03la. Research Triangle Park, North Carolina.
EPA. 1978. Control of Volatile Organic Compound Emissions from Existing Stationary
Sources-Volume VIII: Graphic Arts-Rotogravure andFlexography. U.S. Environmental
Agency, Office of Air Quality Planning and Standards, EPA-450/2-78-033. Washington, D.C.
Renson, James, National Association of Printing Ink Manufacturers. September 10, 1991.
Printing Inks and Solvent Use. Letter and attachments to George Viconovic, E.H. Pechan &
Associates.
Ulconovic, George, E.H. Pechan & Associates, Durham, North Carolina, with Gary Jones,
Graphic Arts Technical Foundation, Pittsburgh, Pennsylvania. July 22, 1991.
National Association of Printing Ink Manufacturers. 1988. The Printing Ink Handbook (Fifth
Edition). Product and Technical Committees, Harrison, New York.
7.8-2 Volume III
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VOLUME III: CHAPTERS
INDUSTRIAL SURFACE COATING
September 1997
Prepared by:
TRC Environmental Corporation
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by TRC Environmental Corporation for the Area Sources
Committee of the Emission Inventory Improvement Program and for Charles Mann of the Air
Pollution Prevention and Control Division, U.S. Environmental Protection Agency. Members of
the Area Sources Committee contributing to the preparation of this document are:
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Carolyn Lozo, California Air Resources Board
Kwame Agyei, Puget Sound Air Pollution Control Agency
Mike Fishburn, Texas Natural Resource Conservation Commission
Gwen Judson, Wisconsin Department of Natural Resource
Charles Masser, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Linda Murchison, California Air Resources Board
Sally Otterson, Washington Department of Ecology
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Jim Wilkinson, Maryland Department of the Environment
-------
CONTENTS
Section Page
1 Introduction 8.1-1
2 Source Category Description 8.2-1
2.1 Category Description 8.2-1
2.2 Process Description and Emission Sources 8.2-2
2.3 Factors Influencing Emissions 8.2-2
2.4 Control Techniques 8.2-8
3 Overview of Available Methods 8.3-1
3.1 Emission Estimation Methodologies 8.3-1
3.1.1 Available Methodologies 8.3-1
3.1.2 DataNeeds 8.3-2
3.2 Projecting Emissions 8.3-5
4 Preferred Method for Estimating Emissions 8.4-1
5 Alternative Methods for Estimating Emissions 8.5-1
5.1 Alternative Method 1 - Default Per Employee Factors 8.5-1
5.2 Alternative Method 2 - Per Capita Emission Factor 8.5-3
6 Quality Assurance/Quality Control (QA/QC) 8.6-1
6.1 Emission Estimate Quality Indicators 8.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 8.6-1
6.1.2 Sources of Uncertainty 8.6-3
7 Data Coding Procedures 8.7-1
7.1 Process and Control Codes 8.7-1
8 References 8.8-1
iv EIIP Volume III
-------
TABLES
Page
.2-1 Principal Industrial Surface Coating SIC 8.2-3
.2-2 1992 Manufacturing Industry Surface Coating Consumption 8.2-6
.2-3 Other Industries That May Consume Surface Coatings 8.2-7
.3-1 Preferred and Alternative Methods for Estimating Emissions from
Small Industrial Surface Coating Operations 8.3-2
.3-2 Data Elements Needed for Each Method 8.3-3
.5-1 National Default Per Employee Emission Factors (EPA, 1991) 8.5-2
.5-2 National Default Per Capita VOC Emission Factors 8.5-4
.6-1 Preferred Method DARS Scores: Area-Specific per Employee Factor 8.6-4
.6-2 Alternative Method 1 DARS Scores: National Default per Employee Factor 8.6-4
.6-3 Alternative Method 2 DARS Scores: National Default per Capita Factor 8.6-5
.7-1 AMS Codes for the Industrial Surface Coating Category 8.7-2
.7-2 AIRS Control Device Codes 8.7-3
EIIP Volume III
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vi EIIP Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from small industrial surface coating operations. Section 2 of this chapter contains a general
description of the small industrial surface coating category and an overview of available control
technologies. Section 3 provides an overview of available emission estimation methods.
Section 4 presents the preferred method for estimating emission from small industrial surface
coating, and Section 5 presents the alternative emission estimation techniques. Quality assurance
issues and emission estimate quality indicators for the methods presented in this chapter are
discussed in Section 6. Data coding procedures are discussed in Section 7. Section 8 contains
references used for this chapter.
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
This page is intentionally left blank.
8.1-2 El IP Volume III
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SOURCE CATEGORY DESCRIPTION
2.1 CATEGORY DESCRIPTION
Surface coating operations involve applying a thin layer of coating (e.g., paint, lacquer, enamel,
varnish, etc.) to an object for decorative or protective purposes. The surface coating products
include either a water-based or solvent-based liquid carrier that generally evaporates in the drying
or curing process. In 1989, approximately 3.8 billion pounds of organic solvents, roughly one-
third of all solvents purchased that year, were used in surface coating operations. These solvents
were used both as carriers for coatings and to clean up coating equipment (EPA, 1991).
The use of surface coatings by manufacturing industries and other sectors of the economy is
pervasive. Applications include: (1) coatings that are applied during the manufacture of a wide
variety of products by Original Equipment Manufacturers (OEMs) including furniture, cans,
automobiles, other transportation equipment, machinery, appliances, metal coils, flat wood, wire,
and other miscellaneous products, (2) architectural coatings, and (3) special purpose coatings
used for applications such as maintenance operations at industrial and other facilities, auto
refmishing, traffic paints, marine finishes, and aerosol sprays. For area source purposes, the
small industrial surface coating category includes OEM applications, some marine coatings, and
maintenance coatings not accounted for by point sources. This category does not include
architectural surface coatings, traffic markings, automobile refmishing, or aerosols. These
categories are covered in other EIIP area source chapters. Architectural coatings are covered in
Chapter 3; graphic arts in Chapter 7; auto refmishing in Chapter 13; traffic markings in Chapter
14; and aerosols in Chapter 5, which covers consumer and commercial solvent use.
Ideally, all industrial surface coating facilities would be inventoried as point sources. Preferred
and alternative methods for estimating point source emissions from industrial surface coating
operations are given in EIIP Volume II, Chapter 7. That chapter also includes more detailed
discussion of surface coatings technology and controls, as well as process descriptions for
industries having significant point source emissions. As a practical matter, it is not usually
possible to account for all industrial surface coating facilities as point sources. Although the
majority of industrial surface coating emissions may be inventoried as point sources, remaining
emissions of volatile organic compounds (VOCs) and hazardous air pollutants (HAPs) from
industrial surface coating operations must be accounted for as area sources. Since the use of
surface coatings by manufacturing industries is so widespread, it is extremely difficult to identify
all of the industries in which coating materials are consumed. This makes the job of compiling a
truly complete and accurate area source inventory for this category a difficult one. The following
EIIP Volume III 8.2-1
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
tables list Standard Industrial Classification (SIC) codes that are likely to be associated with
industrial surface coating operations. Table 8.2-1 lists the SIC codes for which national level
data are available to estimate the quantities of coatings consumed. The largest of these industries
are shown in Table 8.2-2, which lists those industries accounting for 90 percent of reported OEM
coating consumption on a dollar value basis for 1992. Finally, Table 8.2-3 lists other
manufacturing SICs known to consume surface coatings, but for which no reliable national data
are available to estimate the volume used. All of the SICs listed in Tables 8.2-1 and 8.2-3 may
be thought of as possible industries to be considered for inclusion in an area source industrial
surface coating inventory. However, there is no assurance that this list is totally inclusive, nor
can it be stated that these SICs always represent categories that include area source industrial
surface coating operations.
2.2 PROCESS DESCRIPTION AND EMISSION SOURCES
Surface coating is the process by which paints, inks, varnishes, adhesives, or other decorative or
functional coatings are applied to a substrate (e.g., paper, metal, plastic) for decoration and/or
protection. This can be accomplished by brushing, rolling, spraying, dipping, flow coating,
electrocoating, or specialized combinations or variations of these methods. The process by
which the coating is applied is determined in part by the product's intended end use, the substrate
to which the coating is applied, and the composition of the coating itself.
After the coating has been applied, it is cured or dried either by conventional curing or radiation
curing processes. Conventional curing is accomplished through the use of thermal ovens. The
heat from these ovens causes the solvents and/or water trapped in the coating to be driven off into
the atmosphere. Coatings can also be cured using radiation. The two types of radiation curing
processes currently in use are ultraviolet (UV) curing and electron beam (EB) curing.
Emissions result from the evaporation of the paint solvent and any additional solvent used to thin
the coating. Emissions also result from the use of solvents in cleaning the surface prior to
coating and in cleaning coating equipment after use.
2.3 FACTORS INFLUENCING EMISSIONS
VOC emissions from small industrial surface coating operations are influenced by several
factors. Emissions from surface preparation and coating applications are a function of the VOC
content of the product used. Emissions are also a function of the coating process used, including
the transfer efficiency of the spray equipment. Transfer efficiency is the percentage of coating
solids sprayed that actually adhere to the surface being coated. Emissions from cleaning
operations are dependent on the type of cleanup and housekeeping practices used.
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9/26/97
CHAPTER 8 - INDUSTRIAL SURFACE COATING
TABLE 8.2-1
PRINCIPAL INDUSTRIAL SURFACE COATING SIC
SIC Code
2451
2452
2493
2499
2511
2512
2514
2517
2519
2521
2522
2531
2541
2542
2599
3411
3412
3441
3443
3444
3446
3448
3449
3465
3466
3469
3471
3479
3523
3524
SIC Description
Mobile Homes
Prefabricated Wood Buildings and Components
Reconstituted Wood Products
Wood Products, Not Elsewhere Classified
Wood Household Furniture, Except Upholstered
Wood Household Furniture, Upholstered
Metal Household Furniture
Wood Television, Radio, Phonograph, and Sewing Machine Cabinets
Household Furniture, Not Elsewhere Classified
Wood Office Furniture
Office Furniture, Except Wood
Public Building and Related Furniture
Wood Office and Store Fixtures, Partitions, Shelving, and Lockers
Office and Store Fixtures, Partitions, Shelving, and Lockers, Except Wood
Furniture and Fixtures, Not Elsewhere Classified
Metal Cans
Metal Shipping Barrels, Drums, Kegs, and Pails
Fabricated Structural Metal
Fabricated Plate Work (Boiler Shops)
Sheet Metal Work
Architectural and Ornamental Metal Work
Prefabricated Metal Buildings and Components
Miscellaneous Structural Metal Work
Automotive Stampings
Crowns and Closures
Metal Stampings, Not Elsewhere Classified
Electroplating, Plating, Polishing, Anodizing, and Coloring
Coating, Engraving, and Allied Services, Not Elsewhere Classified
Farm Machinery and Equipment
Lawn and Garden Tractors and Home Lawn and Garden Equipment
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9/26/97
TABLE 8.2-1
(CONTINUED)
SIC Code
3531
3532
3536
3561
3563
3581
3585
3586
3593
3594
3612
3613
3621
3631
3632
3633
3634
3635
3639
3711
3713
3714
3715
3716
3721
3724
3728
3731
3732
SIC Description
Construction Machinery and Equipment
Mining Machinery and Equipment, Except Oil and Gas Field Machinery and
Equipment
Overhead Traveling Cranes, Hoists, and Monorail Systems
Pumps and Pumping Equipment
Air and Gas Compressors
Automatic Vending Machines
Air Conditioning and Warm Air Heating Equipment
Measuring and Dispensing Pumps
Fluid Power Cylinders and Actuators
Fluid Power Pumps and Motors
Power, Distribution, and Specialty Transformers
Switchgear and Switchboard Apparatus
Motors and Generators
Household Cooking Equipment
Household Refrigerators and Home and Farm Freezers
Household Laundry Equipment
Electric Housewares and Fans
Household Vacuum Cleaners
Household Appliances, Not Elsewhere Classified
Motor Vehicles and Passenger Car Bodies
Truck and Bus Bodies
Motor Vehicle Parts and Accessories
Truck Trailers
Motor Homes
Aircraft
Aircraft Engines and Parts
Aircraft Parts and Auxiliary Equipment, Not Elsewhere Classified
Ship Building and Repairing
Boat Building and Repairing
8.2-4
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TABLE 8.2-1
(CONTINUED)
SIC Code
3792
3799
3931
3949
3951
3952
3953
3993
3995
SIC Description
Travel Trailers and Campers
Transportation Equipment, Not Elsewhere Classified
Musical Instruments
Sporting and Athletic Goods, Not Elsewhere Classified
Pens, Mechanical Pencils, and Parts
Lead Pencils, Crayons, and Artists' Materials
Marking Devices
Signs and Advertising Specialties
Burial Caskets
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TABLE 8.2-2
1992 MANUFACTURING INDUSTRY SURFACE COATING CONSUMPTION£
SIC Code
371
341
347
289
344
251
363
254
373
346
352
249
252
Description
Motor Vehicles and Equipment
Metal Cans and Shipping Containers
Metal Services, Not Elsewhere Classified
Misc. Chemical Products (Printing Ink)b
Fabricated Structural Metal Products
Household Furniture
Household Appliances
Partitions and Fixtures
Ship and Boat Building and Repairing
Metal Forgings and Stampings
Farm and Garden Machinery
Miscellaneous Wood Products
Office Furniture
Cost of Coatings Consumed
(Million $)
1770.1
328.2
321.7
318.2
218.1
173.3
142.3
87.7
87.7
86.9
85.6
82.8
802
a Information has been compiled from: 1992 Census of Manufactures, Geographic Area Series, U.S. Department of
Commerce, Bureau of the Census, Washington, DC.
b Represents coating materials consumed for printing ink manufacture. Therefore, this SIC should not be included
for inventory purposes as an industrial surface coating end use category.
8.2-6
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CHAPTER 8 - INDUSTRIAL SURFACE COATING
TABLE 8.2-3
OTHER INDUSTRIES THAT MAY CONSUME SURFACE COATINGS
SIC Code
2436
262
263
265
3069
308
331
3433
3494
3452
364
366
367
3812
382
384
3861
3942
3944
SIC Description
Softwood Veneer and Plywood
Paper Mills
Paperboard Mills
Paperboard Containers and Boxes
Fabricated Rubber Products, Not Elsewhere Classified
Miscellaneous Plastic Products, Not Elsewhere Classified
Blast Furnace and Basic Steel Products
Heating Equipment, Except Electric
Valves and Pipe Fittings, Not Elsewhere Classified
Bolts, Nuts, Rivets, and Washers
Electric Lighting and Wiring Equipment
Communications Equipment
Electronic Components and Accessories
Search and Navigation Equipment
Measuring and Controlling Devices
Medical Instruments and Supplies
Photographic Equipment and Supplies
Dolls and Stuffed Toys
Games, Toys, and Children's Vehicles
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
2.4 CONTROL TECHNIQUES
The main approaches for reducing VOC emissions from small industrial surface coating
operations are (1) use of lower-VOC coatings, (2) use of enclosed cleaning devices, and (3)
increased transfer efficiency. Other housekeeping activities can also be used to reduce emissions
from small industrial surface coating operations. These activities include using tight-fitting
containers, reducing spills, mixing paint to need, providing operator training, maintaining rigid
control of inventory, using proper cleanup methods, etc.
Regulations designed to reduce VOC emissions have led to the development of high-solids and
powder coatings, as well as increased use of water-based coatings. Although water-based
coatings include some organic solvents, water makes up the main carrier component (generally at
least 80 percent) in these formulations.
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
There are several methodologies available for calculating emissions from small industrial surface
coating operations. The selection of a method to use depends on the degree of accuracy required
in the estimate, the available data, and the available resources. This section discusses the
methods available for estimating emissions from small industrial surface coating operations and
identifies the preferred method for this category.
3.1.1 AVAILABLE METHODOLOGIES
Volatile Organic Compounds
Methods available for estimating emissions from small industrial surface coating operations
include the following: (1) using SIC-specific, inventory area-specific per employee emission
factors; (2) using national default per employee emission factors; and (3) using per capita
emission factors. These methods are summarized in Table 8.3-1. Because of the potentially
large number of small industrial surface coating operations within an inventory area and the
difficulty in identifying candidate industries to be surveyed, conducting surveys to collect
activity, product use, and product-specific VOC content data to develop product-specific,
site-specific detailed emissions estimates is generally not recommended. A survey methodology
is likely to be too resource intensive for both the facilities surveyed and the inventorying agency.
The preferred method for estimating emissions from small industrial surface coating operations
involves developing and applying SIC-specific, inventory area-specific per employee emission
factors based on reported point source emissions. Other methods for estimating emissions from
this category include using national default per employee and per capita emission factors.
Procedures for the Preparation of Emission Inventories for Carbon Monoxide and Precursors of
Ozone, Volume 1 (EPA, 1991) andAP-42 (EPA, 1995) contain per employee and per capita
emission factors for this category.
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TABLE 8.3-1
PREFERRED AND ALTERNATIVE METHODS FOR ESTIMATING
EMISSIONS FROM SMALL INDUSTRIAL SURFACE COATING OPERATIONS
Methods
Preferred Method -
SIC-Specific, Area-Specific Per Employee
Factor
Alternative Method 1 -
National Default Per Employee Factor
Alternative Method 2 -
Per Capita Factor
Description
• Divide total reported point source emissions (by SIC) for
inventory area by total point source employment (by SIC)
for inventory area to develop SIC-specific, inventory area-
specific per employee emissions factor.
• Subtract total point source employment from total
employment within the SIC to develop total area source
SIC employment.
• Multiply area source employment by SIC-specific,
inventory area-specific employee factor.
Use national default per employee emission factors and
number of employees in SIC to estimate emissions.
Use per capita emission factor and population in inventory
area to estimate emissions.
Hazardous Air Pollutants
HAP emissions from this source are determined by the same methods discussed above for VOC
emissions. Again, conducting a survey to gather specific HAP information may be too resource-
intensive for the inventorying agency to undertake. Using the preferred method described above
assumes that the coatings and HAP contents used in small facilities are similar to those used and
reported by large facilities. The agency may want to verify this assumption with local industry
experts.
3.1.2 DATA NEEDS
Data Elements
The data elements needed to calculate emission estimates for small industrial surface coating
operations depend on the methodology used for data collection. Each methodology requires
some measure of activity (or surrogate for activity) and an emission factor. The data elements
needed for each emission estimation technique are presented in Table 8.3-2.
8-1 o
. J-Z
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CHAPTER 8 - INDUSTRIAL SURFACE COATING
TABLE 8.3-2
DATA ELEMENTS NEEDED FOR EACH METHOD
Data Element
Point source emissions by SIC
Point source employment by SIC
Total employment by SIC
Population (inventory area)
SIC-specific, area-specific per employee
emission factor
National default per employee emission
factor
Per capita emission factor
Preferred
Method8
X
X
X
X
Alternate
Method lb
X
X
X
Alternate
Method 2C
X
X
a Preferred method is the SIC-specific, area-specific per employee factor method.
b Alternative Method 1 is the national default per employee factor method.
c Alternative Method 2 is the per capita factor method.
Adjustments to Emissions Estimates
Adjustments applied to annual emissions estimates include point source corrections, applications
of controls, spatial allocation, and temporal resolution. The type of adjustment is dependent on
the type of inventory required. The data needs for point source emission estimate adjustments
are dependent in part on the methodology used. Data needs for the adjustments listed below are
as follows:
• Point source corrections require point source emissions or point source
employment data for inventory area for the specific SIC;
• Application of controls requires information about control efficiency, rule
effectiveness; and rule penetration;
• Spatial allocation requires employment, population, facility location, zoning, or
business districts location data;
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• Temporal resolution requires data for seasonal throughput, operating days per
week, and operating hours per day.
Point Source Corrections
If the Preferred Method is used to estimate area source emissions from this category, the point
source correction is performed as part of the method itself. If Alternative Method 1 is used, the
point source corrections can be performed by one of the following: (1) subtract point source
emissions from calculated total emissions, or (2) subtract point source employment in the
specific SIC from total employment in that SIC and calculate area source emissions using the
remaining employment in the SIC. If Alternative Method 2 is used, the point source corrections
can only be performed by subtracting point source emissions from calculated total emissions.
Application of Controls
Section 3.8 of Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Volume I (EPA, 1991) provides guidance for determining and applying rule
effectiveness (RE) for a source category. In addition, the EPA document Procedures for
Estimating and Applying Rule Effectiveness in Post-1987 Base Year Emission Inventories for
Ozone and Carbon Monoxide State Implementation Plans (EPA, 1989) provides more detailed
information on RE.
Sections 4.1.1 and 5.4 of $\Q Procedures for the Preparation of Emission Inventories for Carbon
Monoxide and Precursors of Ozone, Volume I (EPA, 1991) describe how to account for
emissions reductions expected to result from applying a regulation. If a regulation exists for a
surface coating operation SIC represented in the inventory areas and the inventorying agency
uses a "top down" approach to estimate emissions from this category, the agency should
incorporate an estimate of rule penetration.
If an area source is controlled (e.g., VOC content of surface coating products controlled by
regulation), the following general equations can be used to calculate emissions:
CAEA = (UAEA)[1 - (CE)(RP)(RE)] (8.3-1)
or
CAEA = (EFA)(Q)[1 - (CE)(RP)(RE)] (8.3-2)
where:
CAEA = controlled area source emissions of pollutant A
UAEA = uncontrolled area source emissions of pollutant A
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CE = control efficiency/100
RP = rule penetration/100
RE = rule effectiveness/100
EFA = emission factor for pollutant A
Q = activity factor for category
Spatial Allocation
If the emissions estimates are developed using a per employee factor, the spatial allocation of
emissions can be performed according to facility location (if known) as with the point source
inventory, or with local employment data. The agency should be aware that since location of
surface coating operations does not necessarily mirror location of population within a county,
using population to spatially allocate emissions might be misleading. The inventorying agency
will need to evaluate options for allocating county emissions, such as zoning information, actual
location data identified from surveys, industry publications, etc.
Temporal Resolution
Seasonal Apportioning. Small industrial surface coating emissions do not demonstrate
differences in activity from season to season (EPA, 1991). The agency may want to evaluate
point source data to determine actual seasonal activity within the inventory area. Area source
emissions can be seasonally allocated using the most frequently occurring or average seasonal
throughput values found in the point source inventory for the specific SIC.
Daily Resolution. Small industrial surface coating facilities typically operate five days per week
(EPA, 1991). This value may be used if local survey data or point source records on daily
resolution are not available.
3.2 PROJECTING EMISSIONS
The type of surrogate used to project emissions is dependent on the methodology used to develop
the initial emissions estimate. In "growing" the emissions estimate, the inventorying agency
should use the same activity parameter as was used to develop the initial estimate. For example,
if a per employee factor was used to develop the initial estimate, growth in employment should
be used to develop the projected emissions estimate. The agency should use SIC-specific growth
information, rather than general business growth projections, if available.
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The general equation for developing the projected emissions is:
CE RP RE
V_/J—/TJ-y _I-XJ_ n\T -*-* * /P
EMISPY = ORATEBYO * EMFpYpc * [1 - (-JlX-X-)] * GF (8.3-3)
where:
EMIS
PY
ORATEBYO
EMF
PY,pc
RE
GF
,PY
projection year emissions: ozone season typical weekday
(mass of pollutant/day)
base year operating rate: ozone season daily activity level
projection year precontrol emissions factor (mass of
pollutant/production unit)
projection year control efficiency (percent)
projection year rule penetration (percent)
projection year rule efficiency (percent)
growth factor (dimensionless)
The precontrol emission factor (EMFPYpc) reflects the mass of VOCs per production unit emitted
before control (EPA, 1993).
8.3-6
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
The preferred method for estimating emissions from small industrial surface coating operations
uses employment as the activity factor and an inventory area-specific, SIC-specific per employee
emission factor. This method essentially scales up point source surface coating emissions by the
ratio of total employment to point source employment. This method is most appropriate when
most surface coating emissions have been accounted for as point sources. Implicit assumptions
are that emissions per employee for area sources are the same as for point sources and that
emissions from SICs for which there are no point sources are insignificant. The following
procedures should be followed.
(1) Develop an SIC-specific, inventory area-specific per employee emission factor. The total
reported point source emissions for all of the surface coating classification codes (SCCs)
reported within an SIC are divided by the point source employment for the SIC. This
method may not be practical if emissions, SCCs and SIC codes for each facility are not all
available.
• Point source surface coating emissions are reported under the 402***** SCC.
Table 7.2-1 of EIIP Volume II, Chapter 7 gives a full list of applicable point
source surface coating SIC codes.
• Emissions by SCC can be obtained from state emissions databases or the
Aerometric Information Retrieval System (AIRS) Facility Subsystem (AFS).
AIRS AFS allows reporting of SIC codes for facilities, but they are not required.
State databases may be a more complete source of information for this procedure.
Database queries should request a list of facilities' emissions that are reported for
SCC 402*****, and those facilities' SIC codes. Facilities may list themselves as
being in more than one SIC code. Inventory preparers will have to use some
judgement to decide which SIC code is the most appropriate match, both for the
per employee emission factor, and the point source correction.
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
• County employment information can be obtained from state or local records, such
as state or local commerce departments, or County Business Patterns1 County
Business Patterns lists employment by SIC code.
PSESIC
SlC-specific, area-specific, per Employee Emission Factor = (84-1)
PSEmpSIC
where:
PSESIC = total point source SIC emissions for coating SCCs
PSEmpSIC = total point source SIC employment
A variation of the above procedure would be to develop the area-specific, SIC-specific per
employee emission factors based on a selected sample of the point source facilities, instead of
basing emission factors on all point sources. A suggested approach is to plot a distribution of
emissions per employee values for all point sources. Those sources that have values that may be
considered "outliers" (extremely high or low compared to other sources) could be excluded from
the sample. The justification for the exclusion is that if a large enough sample of point sources
exists, and this sample contains sources with excessively large or small emissions per employee
factors, these may not be representative of the typically small sources being inventoried as area
sources. In theory, this approach might produce more representative emission factors for area
sources. By deliberately excluding some point sources from the sample, however, the sample
becomes biased. It is a matter of engineering judgement as to whether this bias would cause less
inventory error than basing area source emission factors on a sample of all point sources.
Excluding some individual point sources from the sample for those SICs for which there are only
a very small number of point sources is generally not a good idea, since the sample is too small to
establish a representative average value for emissions per employee.
(2) Subtract total point source employment from total employment for each SIC to calculate
total area source employment. (Point source employment may be available from state
inventory or permit files, or from industrial directories or commercially available
databases. Alternatively, point source employment may be estimated from County
Business Patterns data using the procedure described later in this section.)
ASEmpSIC = TEmpSIC - PSEmpSIC (8.4-2)
1 County Business Patterns, U.S. Department of Commerce, Bureau of the Census,
Washington, DC. Annual publication.
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where:
TEmpSIC = total SIC employment
PSEmpSIC = total point source SIC employment
ASEmpSIC = area source SIC employment
(3) Multiply area source employment by per employee emission factor developed in Step 1.
ASESIC = ASEmpSIC * per Employee Emission Factor (8.4-3)
where:
ASEmpSIC = area source SIC employment
ASESIC = area source SIC emissions
(4) Sum area source surface coating emissions.
ASEsurf = £ * ASESICx (8.4-4)
where:
ASEsurf = total small industrial surface coating emissions
ASESICt = area source SIC emissions for SIC x
The following procedures can be used to determine total point source employment if these data
are not available from the point source or permit files.
Using County Business Patterns:
(1) Assume that the point source facilities are the facilities reported in County Business
Patterns as having at least x employees. The term x may vary by SIC and location, and
can be appropriately selected for each SIC.
(2) Determine the number of point sources reporting from the AFS or state/local records.
(3) County Business Patterns reports the number of facilities by employment class size.
These classes are represented by a range (e.g., 20 to 49 employees, 50 to 99 employees,
100 to 249 employees, etc.). Total numbers of employees are given for all facilities in the
SIC, except where the information does not meet Bureau of the Census requirements to
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
prevent disclosure of data for individual facilities. In these instances, assume that the
facility is at the midpoint of the range, if you cannot estimate the number of employees
from the available data.
(4) Using the County Business Patterns size-class distribution and number of point sources
reporting, sum the number of employees, starting with the largest size class and working
down until all reporting point sources have been considered.
(5) Area source SIC employment is then estimated by subtracting estimated point source SIC
employment from total SIC employment as given in County Business Patterns.
Example 8.4-1 presents through atypical calculation.
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CHAPTER 8 - INDUSTRIAL SURFACE COATING
Example 8.4-1
County X reports 12 point source facilities in SIC yyyy. For County X, the total employment
from County Business Patterns for SIC yyyy is 3,281 and the distribution of facilities by size
class is:
Size Class
1,000 or more
500 to 999
250 to 499
100 to 249
50 to 99
20 to 49
10 to 19
5 to 9
1 to 4
Total
No. of
Facilities
0
1
0
5
6
2
1
0
0
No. of
Employees
not available
964
871
not available
not available
Point source employment =
3,281
750 (one facility in size class 500 to 999,
using 750 as the midpoint) + 964 (five
facilities in size class 100 to 249, with total
employment of 964) + 450 (6 facilities in size
class 50 to 99, using midpoint of 75)
2,164
Area source employment is then calculated:
Area Source Employment for SICyyyy in County X = 3,281 - 2,164 = 1,117
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
5.1 ALTERNATIVE METHOD 1 - DEFAULT PER EMPLOYEE FACTORS
Alternative Method 1 uses the national default per employee emission factors given in the
Procedures (EPA, 1991). These emission factors are presented in Table 8.5-1. Emissions are
estimated by either of the following procedures:
(1) Determine point source SIC employment as outlined in the preferred method. Subtract
point source SIC employment from total SIC employment to determine area source SIC
employment. Multiply area source SIC employment by the appropriate default emission
factor from Table 8.5-1.
(2) Multiply total SIC employment by the appropriate default emission factor from Table 8.5-
1. Subtract total point source surface coating emissions for the SIC from total emissions.
The result is the area source emissions for the SIC. If the result is negative for an SIC, set
the area source emissions equal to zero. If many negative results occur, use of
procedure 1 may be a better approach.
Note that these two methods may provide slightly different results because the default emission
factor may not accurately represent conditions in the inventory area.
The inventorying agency will need to evaluate which procedure is more representative of activity
in the inventory area. Information on temporal allocation and seasonal adjustment factors can be
found in Chapter 1 of this volume, or the Procedures, (EPA, 1991).
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TABLE 8.5-1
NATIONAL DEFAULT PER EMPLOYEE EMISSION FACTORS (EPA, 1991)
Category
Furniture and Fixtures
Metal Containers
Automobiles (new)
Machinery and
Equipment
Appliances
Other Transportation
Equipment
Sheet, Strip, and Coil
Factory Finished Wood
Electrical Insulation
Other Product Coatings
High-Performance
Maintenance Coatings
Marine Coatings
Other Special Purpose
Coatings
SIC Code
25
341
3711
35
363
37, except 37 11 and 373
3479
2426-9, 243-245, 2493,
2499
3357,3612
NAa
NA
373
NA
Per Employee VOC
Emission Factor
(Ib/yr)
944
6,029
794
77
463
35
2,877
131
290
NA
NA
308
NA
Per Employee Coating
Usage Factor
(gal/yr)
175
1,218
131
17
181
14
474
40
114
NA
NA
47
NA
1 NA = not available, use per capita emission factors from Table 8.5-2.
8.5-2
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Example 8.5-1
Assume that point source employment for the SIC is 200, total employment for the SIC is
250, default emission factor is 80 Ib/employee, and total surface coating SCC point source
emissions for the SIC are 15,000 Ib.
Using procedure 1 above, area source emissions would be calculated as follows:
250 employees - 200 employees = 50 employees
(50 employees) (80 Ib/employee) = 4,000 Ib
Using procedure 2 above, area source emissions would be calculated as follows:
(250 employees) (80 Ib/employee) = 20,000 Ib
20,000 Ib - 15,000 Ib = 5,000 Ib
5.2 ALTERNATIVE METHOD 2 - PER CAPITA EMISSION FACTOR
In this alternative method, population in the inventory area is used with SIC-specific default per
capita VOC emission factors to estimate emissions by SIC:
where:
EaSIC = SIC emissions for area a
POPa = population in area a
EFSIC = per capita SIC VOC emission factor
Population data may be obtained from state or local records or from national databases and
publications maintained by the U.S. Department of Commerce, Bureau of the Census. The
recommended per capita VOC emission factors are shown in Table 8.5-2. As with other
emissions estimation methodologies, point source emissions for this category should be
subtracted from the total emissions generated using this methodology. Information on temporal
allocation and seasonal adjustment factors can be found in Chapter 1 of this volume, or the
Procedures (EPA, 1991).
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TABLE 8.5-2
NATIONAL DEFAULT PER CAPITA VOC EMISSION FACTORS
Category
Furniture and Fixtures
Metal Containers
Automobiles (new)
Machinery and
Equipment
Appliances
Other Transportation
Equipment
Sheet, Strip, and Coil
Factory Finished Wood
Electrical Insulation
Other Product Coatings
High-Performance
Maintenance Coatings
Marine Coatings
Other Special Purpose
Coatings
SIC Codes
25
341
3711
35
363
37, except 37 11, 373
3479
2426-9, 243-245, 2493,
2499
3357,3612
NAa
NA
373
NA
Per Capita
VOC Emission Factor
(Ib/yr)
2.0
1.3
1.1
0.7
0.2
0.2
0.5
0.3
0.1
0.6
0.8
0.2
0.8
Per Capita
Coating Usage Factor
(gal/yr)
0.37
0.26
0.18
0.15
0.10
0.08
0.08
0.08
0.06
0.23
0.13
0.04
0.18
1 NA = not available.
8.5-4
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QUALITY ASSURANCE/
QUALITY CONTROL (QA/QC)
When using any of the methods for estimating emissions from industrial surface coating, data
compilation should be planned and documented in the inventory QA/QC plan. When using the
preferred method, all assumptions made about facilities that are excluded from the emission
factor calculations, and the use of emission factors developed from facilities in one specific SIC
being used for a less specific SIC group must be documented and justified. If permit data for
facilities in a particular SIC are not available, employment for that SIC should be checked before
it is assumed that emissions from the SIC do not need to be calculated. Refer to the discussion of
survey planning and survey QA/QC in Chapter 1 of this volume if the preferred method is used.
Data handling for data collected for all of the methods should be planned and documented in the
inventory QA/QC plan and does not involve any category-specific issues. Please consult EIIP
Volume VI on inventory QA/QC for more information.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The preferred method results in higher quality estimates than either of the alternative methods,
but it requires significantly more effort. The level of effort required to calculate emission
estimates using either of the two national default emission factors is estimated to be between 8
and 40 hours. The preferred method will require two to three times as much time. Inventory
preparers will need to decide if the use of the preferred method in their areas will result in
enough of an increase in quality to justify the use of this more detailed method. Inventory
planners may wish to review the number of employees in industrial surface coating-related SICs
and the information available through point source reporting for the inventory area to determine
if the preferred method can be used. Planners should also investigate potential differences in
coating formulations between area source and point source operations.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 8.6-1, 8.6-2, and 8.6-3. A range of
scores is given for the preferred method to reflect variability in the results of the technique. All
scores assume that good QA/QC measures are performed and that no significant deviations from
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the prescribed methods have been made. If these assumptions are not correct, new DARS scores
should be developed according to the guidance provided in Appendix F of EIIP Volume VI.
The preferred method results in higher DARS scores than either of the alternative methods. The
preferred method's DARS scores are between 0.42 and 0.51 and the alternative method DARS
scores range between 0.27 and 0.34. The preferred method scores higher on the emission
factor-related attributes than the alternative methods. The preferred and first alternative methods
use the same activity factor, and thus have the same activity attribute scores. The second
alternative method, which uses population as an activity surrogate, has a lower activity source
specificity score because there may be a low correlation between population and industrial
surface coating activity.
The preferred method compiles existing information from local permits to develop an area source
emission factor. This method depends on several assumptions concerning point and area
industrial surface coating sources being true:
• That most surface coating emissions have been accounted for as point sources;
• That emissions for area sources are the same as those for point sources (i.e.,
processes and materials are similar, emissions per employee are similar, and
controls in permitted facilities are similar to those in nonpermitted facilities); and
• That emissions are insignificant from SICs for which there are no permit data.
Ranges in the scoring for the emission factor depend on several issues. The measurement of the
emission factor, based on permit data, will vary depending on the original data collection effort's
data quality objectives and the methods used to measure emissions. Potential measurement
methods can be plant-specific material balance, continuous emission monitoring, source
sampling, or AP-42 emission factors.
The score for the source specificity attribute addresses the application of a few point source
facilities' emission rates to all of the area sources. Source specificity scores depend on whether
the assumptions listed above are true. The source specificity score will be reduced considerably
if data collected for one SIC are used for a more general SIC grouping that includes that SIC.
The greatest advantage that this method has over the alternatives is that it should address spatial
and temporal variability that is problematic for the alternative methods.
Emission factors for the alternative methods are scored lower than the preferred methods because
they use national-level emission factors based on 1989 solvent usage for all industrial surface
coatings. Such factors do not take into account controls in place, changes in processes and
materials since 1989, or differences in climate that may result in different formulations of
coatings from region to region. Emissions calculated using these factors need to be corrected for
8.6-2 EIIP Volume III
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9/26/97 CHAPTER 8 - INDUSTRIAL SURFACE COATING
point source emissions in the inventory area. When using the population-based emission factor,
spatial attributes are scored lower because the single factor does not reflect any variation in
different types of industry in the inventory area.
6.1.2 SOURCES OF UNCERTAINTY
The statistics needed to quantify the uncertainty of the preferred and alternative methods are
incomplete. Because of the number of different processes used in this source category and the
use of surface coatings in so many different industries, it is a very difficult emission source to
characterize, and area source methods will necessarily carry a heavy load of uncertainty.
Factors that influence the uncertainty for the preferred method depend on variations between
large and small operations. Processes, materials, controls, and the number of employees actually
engaged in surface coating may be quite different depending on the size of the operation. Also,
assuming that area source emissions will be unimportant if there are no permitted facilities could
result in a major underestimation for the SIC. Checking the employment for that SIC will reduce
the uncertainty of that assumption.
Factors that influence the uncertainty for the two alternative methods are:
• The proportion of coating solvent emitted, as opposed to that assumed from the
top-down national material balance estimate;
• Changes in the solvent usage since 1989, when the emission factor was prepared
(see the discussion in Section 6.1.1 about changes since 1989);
• Regional variability in the types of coatings used depending on climate-based
drying or curing times; and
• The number of employees that are actually involved in the surface coating
operation at a facility, as opposed to other operations.
For the per capita factor method (Alternative Method Two) only, one additional factor influences
uncertainty: the regional distribution of industries that do surface coating.
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CHAPTER 8 - INDUSTRIAL SURFACE COATING
9/26/97
TABLE 8.6-1
PREFERRED METHOD DARS SCORES: AREA-SPECIFIC PER EMPLOYEE FACTOR
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.3 -0.5
0.3 -0.6
0.7-0.7
0.8-0.8
0.53 -0.65
Activity
0.9
0.5
0.9
0.8
0.78
Composite
0.27 - 0.45
0.15-0.3
0.63 - 0.63
0.64 - 0.64
0.42-0.51
TABLE 8.6-2
ALTERNATIVE METHOD 1 DARS SCORES: NATIONAL DEFAULT PER
EMPLOYEE FACTOR
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.3
0.5
0.5
0.5
0.45
Activity
0.9
0.5
0.9
0.8
0.78
Composite
0.27
0.25
0.45
0.4
0.34
8.6-4
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9/26/97
CHAPTER 8 - INDUSTRIAL SURFACE COATING
TABLE 8.6-3
ALTERNATIVE METHOD 2 DARS SCORES: NATIONAL DEFAULT PER CAPITA FACTOR
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.3
0.5
0.3
0.5
0.40
Activity
0.9
0.3
0.9
0.8
0.73
Composite
0.27
0.15
0.27
0.4
0.27
EIIP Volume III
8.6-5
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CHAPTER 8 - INDUSTRIAL SURFACE COATING 9/26/97
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8.6-6 El IP Volume III
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DATA CODING PROCEDURES
This section presents the codes available to characterize small industrial surface coating emission
estimates. Consistent categorization and coding will result in greater uniformity among
inventories.
7.1 PROCESS AND CONTROL CODES
The process codes for the industrial surface coating category are shown in Table 8.7-1. These
codes are compatible with the AIRS Area and Mobile Source Subsystem (AMS) source category
codes (EPA, 1994). The control codes for use with AMS are shown in Table 8.7-2. Federal,
state, and local regulations can be used as guides to estimate the type of control used and the
level of efficiency that can be achieved. Be careful to apply only the regulations that specifically
include area sources. If a regulation is applicable only to point sources, it should not be assumed
that similar controls exist at area sources. A survey should be conducted to determine if similar
controls exist at area sources. The "099" control code can be used for miscellaneous control
devices that do not have a unique identification code. The "999" code can be used for a
combination of control devices where only the overall control efficiency is known.
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CHAPTER 8 - INDUSTRIAL SURFACE COATING
9/26/97
TABLE 8.7-1
AMS CODES FOR THE INDUSTRIAL SURFACE COATING CATEGORY
Category
Factory Finished Wood
(SIC 2426-2429, 243-
245, 2492, and 2499)
Wood Furniture
(SIC 2511, 2571, 2521,
and 2541)
Metal Furniture
(SIC 2514, 2522)
Metal Cans (SIC 341)
Miscellaneous Finished
Metals (SIC 34, not
mcludrng341 and 3498)
Machinery and
Equipment (SIC 35)
Large Appliances
(SIC 363)
Electronic and Other
Electrical (SIC 36, not
including 363)
Motor Vehicles
(SIC 3711, 3713, 3715)
Marine (SIC 373)
Railroad (SIC 3743)
Miscellaneous
Manufacturing
Industrial Maintenance
Coatings
Other Special Purpose
Coatings
Process Description
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
Total: All Solvent Types
AMS Code
24-01-015-000
24-01-020-000
24-01-025-000
24-01-040-000
24-01-050-000
24-01-055-000
24-01-060-000
24-01-065-000
24-01-070-000
24-01-080-000
24-01-085-000
24-01-090-000
24-01-100-000
24-01-200-000
Units
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Number of Employees
Population of Area
Population of Area
Population of Area
8.7-2
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9/26/97
CHAPTER 8 - INDUSTRIAL SURFACE COATING
TABLE 8.7-2
AIRS CONTROL DEVICE CODES
Control Device
Wet Scrubber - High Efficiency
Wet Scrubber - Medium Efficiency
Wet Scrubber - Low Efficiency
Mist Eliminators - High Velocity
Mist Eliminators - Low Velocity
Catalytic Afterburners
Catalytic Afterburners with Heat Exchangers
Direct Flame Afterburners
Direct Flame Afterburners with Heat Exchangers
Flares
Activated Carbon Adsorption
Packed-Gas Absorption Column
Tray-Type Gas Absorption Column
Impingement Plate Scrubber
Mat or Panel Filter
Dust Suppression by Water Sprays
Refrigerated Condenser
Barometric Condenser
Process Modification - Water-based Coatings
Process Modification - Low-Solvent Coatings
Process Modification - Powder Coatings
Miscellaneous Control Device
Combined Control Efficiency
Code
001
002
003
014
015
019
020
021
022
023
048
050
051
055
058
061
073
074
101
102
103
099
999
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8
REFERENCES
EPA. 1995. Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and
Area Sources., Fifth Edition, AP-42. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, Research Triangle Park, NC.
EPA. 1994. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, Research Triangle Park, NC.
EPA. 1993. Guidance for Growth Factors, Projections, and Control Strategies for the 15
Percent Rate-of-Progress Plans. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, EPA-452/R-93-002. Research Triangle Park, NC.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone. Volume 1: General Guidance for Stationary Sources. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards,
EPA-450/4-91-016, (NTIS PB92-112168). Research Triangle Park, North Carolina.
EPA. 1989. Procedures for Estimating and Applying Rule Effectiveness in Post-1987 Base Year
Emission Inventories for Ozone and Carbon Monoxide State Implementation Plans. U. S.
Environmental Protection Agency, Research Triangle Park, NC.
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8.8-2 EIIP Volume III
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VOLUME III: CHAPTER 9
PESTICIDES - AGRICULTURAL AND
NONAGRICULTURAL
Revised Final
June 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by TRC Environmental Corporation and revised by Eastern
Research Group, Inc. for the Area Sources Committee, Emission Inventory Improvement
Program and for Charles O. Mann of the Air Pollution Prevention and Control Division, U.S.
Environmental Protection Agency (EPA). Members of the Area Sources Committee contributing
to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
EIIP Volume III ill
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CONTENTS
Section Page
1 Introduction 9.1-1
2 Source Category Description 9.2-1
2.1 Emissions Sources 9.2-2
2.2.1 Factors Influencing Emissions 9.2-3
3 Overview of Available Methods 9.3-1
3.1 Emission Estimation Methods 9.3-1
3.2 Available Methods 9.3-1
3.2.1 Volatile Organic Compounds 9.3-1
3.2.2 Hazardous Air Pollutants 9.3-3
3.2.3 National Solvent Use Apportioned to Counties 9.3-3
3.3 Data Needs 9.3-3
3.3.1 Data Elements 9.3-3
3.4 Spatial Allocation 9.3-6
3.5 Temporal Resolution 9.3-7
3.5.1 Seasonal Apportioning 9.3-7
3.5.2 Daily Resolution 9.3-7
3.6 Projecting Emissions 9.3-7
4 Preferred Method for Estimating Emissions 9.4-1
4.1 Agricultural Applications 9.4-1
4.2 Nonagricultural Applications 9.4-23
4.2.1 Municipal 9.4-23
4.2.2 Commercial 9.4-26
4.2.3 Consumer 9.4-27
IV EIIP Volume III
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CONTENTS (CONTINUED)
Section Page
5 Alternative Methods for Estimating Emissions 9.5-1
5.1 Agricultural Applications 9.5-1
5.1.1 Pesticide-Specific Volatile Component of Pesticide Applied 9.5-1
5.1.2 Default Volatile Organic Component of Pesticide Applied 9.5-4
5.1.3 Volatility/Biodegradability Method 9.5-5
5.2 Nonagricultural Applications 9.5-9
5.3 Method for All Users: Top-Down Solvent Use Method 9.5-11
6 Quality Assurance/Quality Control 9.6-1
6.1 Emission Estimate Quality Indicators 9.6-1
6.1.2 Data Attribute Rating System (DARS) Scores 9.6-2
6.1.3 Sources of Uncertainty 9.6-7
7 Data Coding Procedures 9.7-1
7.1 Necessary Data Elements 9.7-1
8 References 9.8-1
EIIP Volume III V
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FIGURES AND TABLES
Figure Page
9.5-1 Flowchart of Emissions Estimation Method for Semi-Volatile Pesticides 9.5-7
Table Page
9.2-1 Municipal Usage of Pesticides 9.2-2
9.2-2 Summary of Formulations, Equipment, and Application Strategies 9.2-4
9.3-1 Preferred and Alternate Methods for Estimating Emissions from
Pesticide Applications 9.3-2
9.3-2 Data Elements Needed for each Method 9.3-4
9.4-1 Trade Names for Selected Active Ingredients 9.4-3
9.4-2 Vapor Pressures of Selected Active Ingredients 9.4-18
9.4-3 Average VOC Content of Pesticide Inert Ingredient Portion, by
Formulation Type 9.4-21
9.4-4 Uncontrolled Emission Factors for Pesticide Active Ingredients
(Metric And English Units) 9.4-22
9.5-1 Semi-Volatile Pesticides 9.5-6
9.6-1 Preferred: Agricultural Pesticide Use 9.6-3
9.6-2 Preferred: Municipal and Commercial Pesticide Use 9.6-3
9.6-3 Alternative 1: Agricultural Pesticide Use 9.6-4
9.6-4 Alternative 2: Agricultural Pesticide Use 9.6-4
9.6-5 Alternative 3: Agricultural Pesticide Use 9.6-5
9.6-6 Preferred: Consumer Pesticide Use 9.6-5
vi EIIP Volume III
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FIGURES AND TABLES (CONTINUED)
Section Page
9.6-7 Alternative 1: Municipal, Commercial, and Consumer Pesticide Use 9.6-6
9.7-1 Area and Mobile Source Category Codes for Agricultural and Nonagricultural
Pesticide Applications 9.7-2
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CHAPTER 9 - PESTICIDES -AGRICULTURAL 6/18/01
AND NONAGRICULTURAL
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Vlll EIIP Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of available
resources and skills; and different levels of needs for accuracy and reliability of their estimates.
More information about the EIIP program can be found in Volume 1 of the EIIP series,
Introduction and Use of EIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
This chapter describes the procedures and recommended approaches for estimating emissions
from pesticide applications. Section 2 of this chapter contains a general description of the
pesticide applications category. Section 3 of this chapter provides an overview of available
emission estimation methods. Section 4 presents the preferred emission estimation method for
pesticide applications, while Section 5 presents alternative emission estimation techniques.
Quality assurance/quality control are discussed in Section 6. Data coding procedures are
discussed in Section 7, and Section 8 is the reference section.
EIIP Volume III 9.1-1
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CHAPTER 9 - PESTICIDES -AGRICULTURAL 6/18/01
AND NONAGRICULTURAL
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9.1-2 EllP Volume III
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SOURCE CATEGORY DESCRIPTION
Pesticides are substances used to control nuisance weeds (herbicides), insects (insecticides),
fungi (fungicides), and rodents (rodenticides). Pesticides can be broken down into three
chemical categories: synthetics, nonsynthetics (petroleum products), and inorganics.
Formulations of pesticides are made through the combination of the pest-killing material
referred to as the active ingredient, and various solvents (which act as carriers for the pest-killing
material) referred to as the inert ingredient. Both types of ingredients contain volatile organic
compounds (VOC) that can potentially be emitted to the air either during application or as a
result of evaporation. Pesticide applications can be broken down into two user categories:
agricultural and nonagricultural (which includes municipal, commercial, and consumer). The
criteria pollutant of concern from the application of pesticides is VOC.
Pesticides are used mainly for agricultural applications. Agricultural pesticides are a
cost-effective means of controlling weed, insects, and other threats to the quality and yield of
food production. Application rates for a particular pesticide may vary from crop to crop and
region to region. Application of pesticides can be from the ground or from the air and pesticides
can be applied as sprays, dusts, pellets, fogs, or through other dispersion techniques.
Nonagricultural applications are a smaller part of the inventory and include municipal,
commercial, and consumer applications. Municipal applications cover state and possibly public
institutions such as schools and hospitals, and public recreational areas. Municipal applications
can include mosquito control and weed suppression by government agencies, pesticide
application at parks, highway department use, utilities maintenance, and pesticide application at
railroad right-of-ways. Commercial applications include applications to public and private golf
courses and homeowner/business property (yards, dwellings, and buildings) by a commercial
exterminator/lawn care service. Consumer applications include homeowner-applied insecticides
(e.g., flea and tick sprays, wasp and hornet sprays, lawn and garden insecticides), fungicides and
nematicides (e.g., wood preservatives, and mold and mildew retardants), and herbicides
(e.g., defoliant herbicides, swimming pool algicides, and aquatic herbicides). As with
agricultural applications of pesticides, nonagricultural applications can be from the ground or
from the air and pesticides can be applied as sprays, dusts, pellets, fogs, or through other
dispersion techniques. Table 9.2-1 provides a summary of municipal usage of pesticides and the
suggested organizations to contact for information on usage.
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.2-1
MUNICIPAL USAGE OF PESTICIDES
Type of Use
Publicly -Maintained Golf Courses
Public Parks
Public Institutions (grounds and gardens)
Mosquito/Other Pest Control
Utility Right of Ways
Roadways
Suggested Organizations to Contact
Public Parks Department
Public Parks Department
Public Parks Departments,
Institution's Maintenance Departments
Public Health Department
Utility Companies
State and Local Highway Departments
2.1 EMISSIONS SOURCES
Approximately 68 to 75 percent of pesticides used in the United States are applied to agricultural
lands, both cropland and pasture (Baker and Wilkinson, 1990), (Aspelin et. a/., 1991). Of the
remaining 25 to 32 percent, 7 to 8 percent are used privately for home and garden pests, and the
remaining 18 to 24 percent are used for industrial, commercial, and government purposes.
A wide variety of solvents are used in pesticide formulations. In 1987, according to the
Freedonia solvent marketing study, the United States consumed approximately 1,090 million
pounds of pesticide formulations. This study estimated that these formulations contained about
570 million pounds of active ingredients and about 520 million pounds of solvents (Freedonia
Group, 1989). Both the active ingredient and the solvent emit VOC either during and/or after
application.
9.2-2
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6/75/07 CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
2.2.1 FACTORS INFLUENCING EMISSIONS
To use pesticides effectively, the most appropriate pesticide formulation, equipment, and
application and treatment strategy must be determined. Table 9.2-2 summarizes the different
formulations, equipment, and application strategies available. Each of these factors will
influence the amount of VOC emitted by the pesticide application being investigated. Limited
information is available on the effects of each of these factors on VOC emissions. However, it
can be reasoned that solid formulations such as powders, dusts, and pellets will have lower VOC
emissions than solutions, concentrates, and aerosols. In addition, pesticides that are applied by
equipment that increases the surface area to which the pesticide is applied, such as compressed
air sprayers and mist blowers, will have higher VOC emissions per unit of time than small hand
dusters and sprayers. Finally, application strategies that increase the area over which the
pesticide is applied, such as a broadcast application, will have higher VOC emissions than a
strategy that applies the pesticide to a specific part of the plant to be treated, such as in a directed
application. Currently there are no federal or state regulations limiting air emissions from
pesticide applications.
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.2-2
SUMMARY OF FORMULATIONS, EQUIPMENT, AND APPLICATION STRATEGIES
Formulations
Equipment
Emulsifiable Concentrate
Solution
Flowable
Wettable Powder
Dry Flowable
Soluble Powder
Ultra Low Volume Concentrate
Low Concentrate Solution
Aerosol
Invert Emulsion
Dust
Bait
Granule
Pellets
Micro Encapsulation
Water-soluble Packets
Impregnates
Hand Dusters
Rotary-type Hand Dusters
Knapsack Dusters
Power Dusters
Compressed Air Sprayers
Power Sprayers
Hand Sprayers
Knapsack Sprayers
Mist Blowers
Applications/Treatments
Band
Basal
Broadcast
Directed
Sequential
Serial
Spot
9.2-4
EIIP Volume III
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODS
There are several methods available for calculating emissions from pesticide applications. The
method chosen is dependent on the type of application (agricultural or nonagricultural), available
data, available resources, and the degree of accuracy required for the estimate. Also, selection of
the appropriate estimation method depends on the relative significance of emissions from this
source in the inventory area and the data quality objectives (DQOs) of the inventory plan. Refer
to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for discussions of
inventory categories and DQOs.
This section discusses the methods available for calculating emission estimates from agricultural
and nonagricultural pesticide applications and identifies the preferred method of calculation for
each category. A discussion of the data elements needed for each method is provided.
3.2 AVAILABLE METHODS
3.2.1 VOLATILE ORGANIC COMPOUNDS
The VOC emitted from agricultural and nonagricultural pesticide applications are from the inert
ingredients (i.e., solvent carriers) and the volatile organic constituents of the active ingredients.
These VOC are emitted during application and evaporate over time. There are several methods
for estimating VOC emissions from both agricultural and nonagricultural application, depending
on the data available and the information sought. Table 9.3-1 summarizes these methods. The
preferred methods are discussed in Section 4 and alternative methods are discussed in Section 5.
Agricultural Pesticide Applications
Each method (with the exception of the per capita emission factor) requires information on the
total area to which the pesticide is applied, the amount of active and inert ingredients in the
pesticide, and the application rate. There are several approaches to estimating the amount of
VOC emitted from this category, depending on the data available.
EIIP Volume III 9.3-1
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VO
1>J
to
TABLE 9.3-1
PREFERRED AND ALTERNATIVE METHODS FOR ESTIMATING EMISSIONS FROM PESTICIDE APPLICATIONS
O
rn
c"
CD
Methods
Preferred Method
Alternative Method 1
Alternative Method 2
Alternative Method 3
(Volatility/
Biodegradability)
Alternative Method 4
(Top-Down Solvent
Use)
Agricultural
Gather data from State Agricultural
Departments to calculate emissions
based on the pesticide applied, the
formulation of the pesticide, and the
total acres to which the pesticide is
applied. The emission factors in this
method are based on the vapor
pressures of the active ingredients in
the pesticides.
Gather data from State Agricultural
Departments to calculate emissions
based on the pesticide applied, the
formulation of the pesticide, and the
total acres to which the pesticide is
applied. This method requires data on
the VOC content of the active and inert
ingredients in the pesticide.
Gather data from State Agricultural
Departments to calculate emissions
based on the pesticide applied, the
formulation of the pesticide, and the
total acres to which the pesticide is
applied. This method uses a default for
the amount of VOC present in the
active ingredient to calculate the total
emissions. Use this method if no
pesticide-specific data are available.
This method calculates emissions by
taking into consideration the volatility
and biodegradability of the pesticide.
This method can only be used for semi-
volatile pesticides and requires detailed
information on the formulation of the
pesticide. This is the preferred method
if this level of information is available
from a State Agricultural Department.
Emissions are calculated by month.
Apportion national solvents
consumption for this source category to
counties.
Nonagricultural
Municipal
Survey State and local government
agencies, highway departments, utility
companies, and parks offices to gather
information on the total acres and the
amount of pesticide applied to those
acres. The more information on the
pesticide that can be found, the more
accurate the emission estimate.
Use a national per capita emission
factor. Calculation is for all
nonagricultural pesticide applications.
Commercial
Survey commercial pesticide
application companies to
determine the pesticides used,
the formulation of those
pesticides, and the amount
applied.
Use a national per capita
emission factor. Calculation
is for all nonagricultural
pesticide applications.
Consumer
Use data from
EPA's
Consumer
Products
Survey.
o
0)
o
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6/75/07 CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
Nonagricultural Pesticide Applications
For nonagricultural pesticide applications, the methods require information on the total area to
which the pesticide is applied, the amount of active and inert ingredients in the pesticide, and
the application rate. If no information is available, total nonagri cultural emissions can be
calculated based on a per capita emission factor. The method used to calculate emissions
depends on the type of nonagri cultural application method being used (i.e., municipal,
commercial, or consumer).
3.2.2 HAZARDOUS AIR POLLUTANTS
Hazardous air pollutant (HAP) emissions from this source are determined by the methods
discussed above for VOC emissions. The emissions of each HAP are assumed to be
proportional to the amount of HAP used in the pesticide formulation for which the emissions are
being calculated.
3.2.3 NATIONAL SOLVENT USE APPORTIONED TO COUNTIES
An alternative method is a material balance top-down approach, starting with total national
solvent consumption and apportioning it to counties. This method utilizes national annual
solvents consumption for this source category, surrogates for spatial allocation to counties, a
method to show growth (if national numbers not for inventory year), knowledge of regulations1
and recycling and waste management policies.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements needed to calculate emission estimates for pesticide applications depend on
the methodology used for data collection and on the methodology used to estimate emissions.
The data elements needed for each emission estimation technique are presented in Table 9.3-2.
1 State any assumptions made to include national/state/local regulations and the exact
regulation applied. Clarify any issues related to regulation and control assumptions.
The final emissions estimates are highly dependent on these assumptions, therefore
they must be stated explicitly in all documentation.
EllP Volume III 9.3-3
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vo
o
TABLE 9.3-2
DATA ELEMENTS NEEDED FOR EACH METHOD
[n
Total acres
AgriculturaT
Preferred
X
ALT1
X
ALT 2
X
ALTS
X
ALT4d
Nonagriculturalb
Munici
Preferred
X
palc
ALT1
Commercial0
Preferred
ALT 1
Pesticide formulation
Fraction active ingredient
Fraction inert ingredient
Fraction VOC in active
ingredient
Fraction VOC in inert ingredient
Vapor pressure of active
ingredient
Amount of pesticide applied per
acre
Average temperature in month of
application
Relative humidity during month
of application
Water evaporation rate
Vapor pressure of water at
average temperature
Area population
National solvents consumption
for this source category
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
o
rn
r- 0)
O
I
(B
I
-------
[n
c"
CD
TABLE 9.3-2
(CONTINUED)
1
Surrogate data for spatial
allocation to counties
Growth indicators to adjust
activity (if national numbers not
for inventory year)
Impact of regulations3 on
emissions
Recycling and waste management
Solvent content factor
Agricultural2
Preferred
ALT1
ALT 2
ALTS
ALT4d
X
X
X
X
X
Nonagriculturalb
Munici
Preferred
palc
ALT1
Commercial0
Preferred
ALT 1
aALT 1 for agricultural applications is the pesticide-specific volatile component of pesticide applied method.
ALT 2 for agricultural applications is the default volatile component of pesticide applied method.
ALT 3 for agricultural applications is the California Air Resources Board method.
bConsumer pesticide applications should use EPA's 1992 Consumer Products Survey to estimate emissions.
°ALT 1 for municipal applications is the use of national per capita emission factors.
ALT 1 for commercial applications is the use of national per capita emission factors.
dALT 4 for agricultural applications is the national top-down solvent use method.
I
CO
O
o o
;o ;o
o o
VO
r- r-
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CHAPTER 9 - PESTICIDES -AGRICULTURAL 6/18/01
AND NONAGRICULTURAL
Adjustments to Emission Estimates
Adjustments to an emission estimate for pesticide applications may be necessary depending on
the type of inventory being prepared. For an annual inventory, adjustments would be made to
spatially allocate the emissions to the appropriate counties and any corrections for applicable
regulations. Therefore, data will be needed on where the pesticide was used and the appropriate
values for rule effectiveness and rule penetration, assuming regulations apply to pesticide
applications in the study area. A seasonal inventory will require seasonal corrections as outlined
in Section 5.8 of Volume I of Procedures for the Preparation of Emission Inventories for
Carbon Monoxide and Precursors of Ozone (EPA-450/4-91-016, May 1991), herein referred to
as the Procedures document. The correction assumes application through a nine month growing
season, six days per week (EPA, 1991). No additional data are required to seasonally adjust an
inventory (the default value of 1.3 can be used) unless the pesticide application is not equivalent
to the assumptions in the Procedures document. Projecting emissions for pesticides requires
data on the anticipated changes in the number of acres to which pesticides are being applied in
the area of concern.
Information on seasonal activity of the agricultural pesticide usage can also be obtained from
agricultural extension offices. Such information may include data on the standard schedules for
pesticide and herbicide application and the type of crops grown during the inventory season.
Application of Controls
Historically, control of emissions from pesticide applications have been limited. The use of
solid formulations, low volume spray equipment, and direct applications have the potential for
reducing the amount of VOC emitted. No states have regulated air emissions from pesticide
applications through the controls mentioned, however, these types of regulations are being
developed. When considering the effect of these potential rules, both rule effectiveness and rule
penetration should be applied to the emission estimate.
3.4 SPATIAL ALLOCATION
The spatial allocation of agricultural pesticide application emissions can be performed by using
agricultural data from the State Agricultural Departments. To spatially allocate municipal
applications, data should be obtained by surveying various state and local agencies and utility
companies that are responsible for applying the pesticide to determine in which county the
pesticide was applied. For commercial applications, a survey should be used to pinpoint the
county in which the pesticide was used. Finally, for consumer applications, spatial allocation
can be accomplished by using local population data.
9.3-6 EllP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
3.5 TEMPORAL RESOLUTION
3.5.1 SEASONAL APPORTIONING
Emissions from all types of pesticide applications vary from season to season in most areas of
the United States. Seasonal throughput or months of application information should be
collected so that a seasonal adjustment can be calculated. Section 5.8 of the Procedures
document contains information and instructions on the methods for calculating a seasonal
adjustment factor.
3.5.2 DAILY RESOLUTION
Most agricultural pesticide applications occur either five or six days per week. Municipal and
commercial applications also occur five or six days per week. Consumer pesticide applications
can take place throughout the entire seven day week. Most pesticide applications, both
agricultural and nonagricultural, occur during daylight hours.
3.6 PROJECTING EMISSIONS
Projecting emissions from agricultural and nonagricultural pesticide applications requires
information on anticipated changes in the number of acres to which pesticides are applied.
However, if no information is available, the inventorying agency can assume no changes to the
number of acres treated.
EIIP Volume III
9.3-7
-------
PREFERRED METHOD FOR
ESTIMATING EMISSIONS
4.1 AGRICULTURAL APPLICATIONS
The preferred method for estimating emissions from agricultural applications of pesticides uses
the vapor pressure of the active ingredient to determine the appropriate emission factor, the
amount of pesticide applied to an area, and the percent of the active ingredient in the pesticide
applied. This method takes into consideration the method by which the pesticide is applied, the
type of formulation, and the fact that volatilization is essentially complete within 30 days of
application (EPA, 1996).
This method cannot be used for aerial applications. A major factor in losses by aerial
application is drift, and neither equations nor experimental data are currently available to permit
predictions of these losses or the development of emission factors.
The following procedures should be applied for non-aerial applications:
(1) Contact State Agricultural Departments to collect data on:
• The pesticides applied;
• The amount of pesticide applied by county/nonattainment area;
• Method of application;
• The active ingredient(s) in the pesticide applied;
• The vapor pressure of the active ingredient(s);
• The type of formulation;
• The percentage of inert ingredients in the pesticide applied; and
• The percentage of VOC in the inert ingredients.
EllP Volume III 9.4-1
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CHAPTER 9 - PESTICIDES -AGRICULTURAL 6/18/01
AND NONAGRICULTURAL
Data on the formulations can be found in publications such as the Farm Chemicals
Handbook2 or from the National Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC (USDA, 1992). If specific data can not be obtained from
the state, Tables 9.4-1 through 9.4-4 provide active ingredients for many pesticides,
vapor pressures for typical active ingredients, and average VOC content for the inert
portion by formulation type.
(2) Calculate the emissions from the active ingredient of the pesticide applied.
E! = RxAxPAxEF (9.4-1)
where:
Ej = emissions from the active ingredient
R = pounds of pesticide applied per year per harvested acre
A = total harvested acres
PA = fraction active ingredient in the pesticide applied
EF = emission factor from Table 9.4-4 based on vapor pressure of active
ingredient
3) Calculate emissions from the inert ingredients in the pesticide applied.
E2 = R x A x PI x PVI (9.4-2)
where:
E2 = emissions from inert ingredients
R = pounds of pesticide applied per year per harvested acre
A = total harvested acres
PI = fraction inert ingredient in the pesticide applied
PVI = fraction VOC in the formulation from Table 9.4-3
2 The Farm Chemicals Handbook is published annually by Meister Publishing Company,
Willoughby, OH.
9.4-2 El IP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1
TRADE NAMES FOR SELECTED ACTIVE INGREDIENTS3
Trade Nameb
Active Ingredienf
Insecticides
AC 8911
Acephate-met
Alkron®
Aileron®
Aphamite®
Bay 17147
Bay 19639
Bay 70143
Bay 71628
Benzoepin
Beosit®
Brodan®
BugMaster®
BW-21-Z
Carbamine®
Carfene®
Cekubaryl®
Cekudifol®
Cekuthoate®
CGA-15324
Chlorpyrifos 99%
Chlorthiepin®
Phorate
Methamidophos
Ethyl Parathion
Ethyl Parathion
Ethyl Parathion
Azinphos-methyl
Disulfoton
Carbofuran
Methamidophos
Endosulfan
Endosulfan
Chlorpyrifos
Carbaryl
Permethryn
Carbaryl
Azinphos-methyl
Carbaryl
Dicofol
Dimethoate
Profenofos
Chlorpyrifos
Endosulfan
EIIP Volume III
9.4-3
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Comite®
Corothion®
Crisulfan®
Crunch®
Curacron
Curaterr®
Cyclodan®
Cygon 400®
D1221
Daphene®
Dazzel®
Denapon®
Devicarb®
Devigon®
Devisulphan®
Devithion®
Diagran®
Dianon®
Diaterr-Fos®
Diazajet®
Diazatol®
Diazide®
Di carbarn®
Dicomite®
Active Ingredient0
Propargite
Ethyl Parathion
Endosulfan
Carbaryl
Profenofos
Carbofuran
Endosulfan
Dimethoate
Carbofuran
Dimethoate
Diazinon
Carbaryl
Carbaryl
Dimethoate
Endosulfan
Methyl Parathion
Diazinon
Diazinon
Diazinon
Diazinon
Diazinon
Diazinon
Carbaryl
Dicofol
9.4-4
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Dimethogen®
Dimet®
Dizinon®
DPX 1410
Dyzol®
E-605
Ectiban®
Endocide®
Endosol®
ENT 27226
ENT27164
Eradex®
Ethoprop
Ethoprophos
Ethylthiodemeton
Etilon®
Fezudin
FMC-5462
FMC-33297
Fonofos
Force®
Fosfamid
Furacarb®
G-24480
Active Ingredient0
Dimethoate
Dimethoate
Diazinon
Oxamyl
Diazinon
Ethyl Parathion
Permethryn
Endosulfan
Endosulfan
Propargite
Carbofuran
Chlorpyrifos
Ethoprop
Ethoprop
Disulfoton
Ethyl Parathion
Diazinon
Endosulfan
Permethryn
Dyfonate
Tefluthrin
Dimethoate
Carbofuran
Diazinon
EIIP Volume III
9.4-5
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Active Ingredient0
Gardentox®
Gearphos®
Golden Leaf Tobacco Spray18
Hexavin®
Hoe 2671
Indothrin®
Insectophene®
Insyst-D®
Karbaspray®
Kayazinon®
Kayazol®
Kryocide®
Lannate® LV
Larvin®
Metafos
Metaphos®
Methomex®
Methyl
Metiltriazotion
Nipsan®
Niran®
Nivral®
NRDC 143
Ortho 124120
Diazinon
Methyl Parathion
Endosulfan
Carbaryl
Endosulfan
Permethryn
Endosulfan
Disulfoton
Carbaryl
Diazinon
Diazinon
Cryolite
Methomyl
Thiodicarb
Methyl Parathion
Methyl Parathion
Methomyl
Methyl Parathion
Azinphos-methyl
Diazinon
Ethyl Parathion
Thiodicarb
Permethryn
Acephate
9.4-6
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Orthophos®
Panthion®
Paramar®
Paraphos®
Parathene®
Parathion
Parathion
Parawet®
Partron M®
Penncap-M®
Phoskil®
Piridane®
Polycron®
PP557
Pramex®
Prokil®
PT265®
Qamlin®
Rampart®
Rhodiatox®
S276
SD 8530
Septene®
Sevin 5 Pellets®
Active Ingredient0
Ethyl Parathion
Ethyl Parathion
Ethyl Parathion
Ethyl Parathion
Ethyl Parathion
Methyl Parathion
Ethyl Parathion
Ethyl Parathion
Methyl Parathion
Methyl Parathion
Ethyl Parathion
Chlorpyrifos
Profenofos
Permethryn
Permethryn
Cryolite
Diazinon
Permethryn
Phorate
Ethyl Parathion
Disulfoton
Trimethacarb
Carbaryl
Carbaryl
EIIP Volume III
9.4-7
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Soprathion®
Spectracide®
SRA5172
Stathion®
Tekwaisa®
Temik®
Tercyl®
Thimul®
Thiodan
Thiofor®
Thiophos
Tricarnam®
Trimetion®
UC51762
UC 27867
Uniroyal DO 14
Yaltox®
None listed
None listed
Herbicides
A-4D
AC 92553
Acclaim
Acme MCPA Amine 4®
Active Ingredient0
Ethyl Parathion
Diazinon
Methamidophos
Ethyl Parathion
Methyl Parathion
Aldicarb
Carbaryl
Endosulfan
Endosulfan
Endosulfan
Ethyl Parathion
Carbaryl
Dimethoate
Thiodicarb
Trimethacarb
Propargite
Carbofuran
Dicrotophos
Terbufos
2,4-D
Pendimethalin
Fenoxaprop-ethyl
MCPA
9.4-8
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Aljaden®
Amiben®
Amilon®-WP
Amine®
Aqua-Kleen®
Arrhenal®
Arsinyl®
Assure®
Avadex® BW
Banlene Plus®
Banvel®
Barrage®
Basagran
Bay 30130
Bay DIG 1468
Bay 94337
Benefex®
Benfluralin
Bentazon
Bethrodine
BH® MCPA
Bioxone®
Blazer®
Bolero®
Active Ingredient0
Sethoxydim
Chloramben
Chloramben
MCPA
2,4-D
DSMA
DSMA
Quizalofop-ethyl
Triallate
MCPA
Dicamba
2,4-D
Bentazon
Propanil
Metribuzin
Metribuzin
Benefm
Benefm
Bentazon
Benefm
MCPA
Methazole
Aciflurofen
Thiobencarb
EIIP Volume III
9.4-9
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Border-Master®
Brominex®
C-2059
Cekuiron®
Cekuquat®
Cekusima®
CGA-24705
Checkmate®
Chloroxone®
Classic®
Clomazone
Command®
CP50144
Crisuron®
Croprider®
Dacthal®
Dailon®
Depon®
Dextrone®
Di-Tac®
Diater®
DMA
DM A- 100®
DPA
Active Ingredient0
MCPA
Bromoxynil
Fluometuron
Diuron
Paraquat
Simazine
Metolachlor
Sethoxydim
2,4-D
Chlorimuron-ethyl
Clomazone
Clomazone
Alachlor
Diuron
2,4-D
DCPA
Diuron
Fenoxaprop-ethyl
Paraquat
DSMA
Diuron
DSMA
DSMA
Propanil
9.4-10
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Active Ingredienf
DPX-Y6202
EL-110
EL-161
Emulsamine®
T^ ®
Esgram
Excel®
EXP-3864
Expand®
Far-Go®
Farmco Diuron®
Farmco Atrazine Gesaprim®
Fervinal®
Ferxone®
Furore®
Fusilade 2000
G-30027
G-34161
G-34162
Gamit®
Genate Plus®
Glyphosate Isopropylamine Salt
Goldquat® 276
Grasidim®
Herb All®
Quizalofop-ethyl
Benefm
Ethalfluralin
2,4-D
Paraquat
Fenoxaprop-ethyl
Quizalofop-ethyl
Sethoxydim
Triallate
Diuron
Atrazine
Sethoxydim
2,4-D
Fenoxaprop-ethyl
Fluazifop-p-butyl
Atrazine
Prometryn
Ametryn
Clomazone
Butylate
Glyphosate
Paraquat
Sethoxydim
MSMA
EIIP Volume III
9.4-11
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Active Ingredient0
Herbaxon®
Herbixol®
Higalcoton®
Hoe 002810
Hoe-023408
Hoe-Grass®
Hoelon®
Illoxan®
Kilsem®
Lasso®
Lazo®
Legumex Extra®
Lexone® 4L
Lexone® DF®
Linorox®
LS 801213
M.T.F®
Magister®
Mephanac®
Merge 823®
Methar® 30
Mezopur®
Monosodium methane arsenate
Nabu®
Paraquat
Diuron
Fluometuron
Linuron
Diclofop-methyl
Diclofop-methyl
Diclofop-methyl
Diclofop-methyl
MCPA
Alachlor
Alachlor
MCPA
Metribuzin
Metribuzin
Linuron
Aciflurofen
Trifluralin
Clomazone
MCPA
MSMA
DSMA
Methazole
MSMA
Sethoxydim
9.4-12
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Option®
Oxydiazol
Paxilon®
Pillarquat®
Pillarxone®
Pillarzo®
Pilot®
Plantgard®
Pledge®
PP005
Primatol Q®
Probe
Prop-Job®
Propachlor
Prowl®
Rattler®
RH-6201
Rodeo®
Roundup®
S 10145
Sarclex®
Saturno®
Saturn®
Scepter®
Active Ingredient0
Fenoxaprop-ethyl
Methazole
Methazole
Paraquat
Paraquat
Alachlor
Quizalofop-ethyl
2,4-D
Bentazon
Fluazifop-p-butyl
Prometryn
Methazole
Propanil
Propachlor
Pendimethalin
Glyphosate
Aciflurofen
Glyphosate
Glyphosate
Propanil
Linuron
Thiobencarb
Thiobencarb
Imazaquin
EIIP Volume III
9.4-13
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
SD 15418
Sencor® 4
Sencor® DF
Shamrox®
Sodar®
Sonalan®
Squadron®
Squadron®
Strel®
Surpass®
Targa®
Target MSMA®
Telok®
Tigrex®
Total®
Toxer®
Trans-Vert®
Tri-4®
Tri-Scept®
Tributon®
Trifluralina 600®
Trinatox D®
Tritex-Extra®
Tunic®
Active Ingredient0
Cyanazine
Metribuzin
Metribuzin
MCPA
DSMA
Ethalfluralin
Imazaquin
Pendimethalin
Propanil
Vernolate
Quizalofop-ethyl
MSMA
Norflurazon
Diuron
Paraquat
Paraquat
MSMA
Trifluralin
Imazaquin
2,4-D
Trifluralin
Ametryn
Sethoxydim
Methazole
9.4-14
EIIP Volume III
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Unidron®
VCS 438
Vegiben®
Vernam 10G
Vernam 7E
Vonduron®
Weed-Rhap®
Weed-B-Gon®
Weedatul®
Weedtrine-n®
Whip®
WL 19805
Zeaphos®
Zelan®
None listed
None listed
None listed
None listed
Other Active Ingredients
A7 Vapam®
Aquacide®
Avicol®
Carbarn (MAP)
Clortocaf Ramato®
Active Ingredient0
Diuron
Methazole
Chloramben
Vernolate
Vernolate
Diuron
MCPA
2,4-D
2,4-D
2,4-D
Fenoxaprop-ethyl
Cyanazine
Atrazine
MCPA
EPIC
Fomesafen
Molinate
Tridiphane
Metam Sodium
Diquat
PCNB
Metam Sodium
Chlorothalonil
EIIP Volume III
9.4-15
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Clortosip®
Cotton Aide HC®
De-Green®
DBF®
Deiquat
Dextrone®
E-Z-OffD®
Earthcide®
Exotherm Termil®
Folex®
Folosan®
Fos-Fall A®
Karbation®
Kobutol®
Kobu®
Kypman® 80
M-Diphar®
Mancozin®
Maneba®
Manebe
Manzate® 200
Manzeb
Manzin®
Maposol®
Active Ingredient0
Chlorothalonil
Cacodylic
Tribufos
Tribufos
Diquat
Diquat
Tribufos
PCNB
Chlorothalonil
Tribufos
PCNB
Tribufos
Metam Sodium
PCNB
PCNB
Maneb
Maneb
Mancozeb
Maneb
Maneb
Mancozeb
Mancozeb
Mancozeb
Metam Sodium
9.4-16
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6/18/01
CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-1 (CONTINUED)
Trade Nameb
Active Ingredienf
Metam for the Acid
Moncide®
Montar®
Nemispor®
Pentagen®
Quintozene
Rad-E-Cate® 25
Region
Riozeb®
RTU® PCNB
Sectagon® II
SMDC
Soil-Prep®
Sopranebe®
Superman® Maneb F
Terrazan®
Tersan 1991®
TriPCNB®
Tubothane®
Weedtrine-D®
Ziman-Dithane®
None listed
None listed
None listed
Metam Sodium
Cacodylic
Cacodylic
Mancozeb
PCNB
PCNB
Cacodylic
Diquat
Mancozeb
PCNB
Metam Sodium
Metam Sodium
Metam Sodium
Maneb
Maneb
PCNB
Benomyl
PCNB
Maneb
Diquat
Mancozeb
Dimethipin
Ethephon
Thiadiazuron
a From Farm Chemicals Handbook. See the USD A publication on Agricultural Chemical Usage (USD A, 1992)
for selected pesticides used on major field crops.
b From Farm Chemicals Handbook.
0 Common names. See Farm Chemicals Handbook for chemical names.
EIIP Volume III
9.4-17
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TABLE 9.4-2
VAPOR PRESSURES OF SELECTED ACTIVE INGREDIENTS3
Active Ingredient
Vapor Pressure
(mmHgat20to25°C)
1,3 -Di chl oropropene
2,4-D acid
Acephate
Alachlor
Aldicarb
Aldoxycarb
Amitraz
Amitrole (aminotriazole)
Atrazine
Azinphos-methyl
Benefm (benfluralin)
Benomyl
Bifenox
Bromacil acid
Bromoxynil butyrate ester
Butylate
Captan
Carbaryl
Carbofuran
Chlorobenzilate
Chloroneb
Chloropicrin
Chlorothalonil
Chlorpyrifos
Clomazone (dimethazone)
Cyanazine
Cyromazine
29
8.Ox 1Q-6
1.7x ID'6
1.4x 1Q-5
3.Ox 1Q-5
9x 1Q-5
2.6 x ID'6
4.4 x ID'7
2.9 x ID'7
2.0 x ID'7
6.6 x 1Q-5
<1.0x ID'10
2.4 x ID'6
3.1x ID'7
l.Ox 1C'4
1.3x 1C'2
8.Ox 1Q-8
1.2 x ID'6
6.0 x ID'7
6.8 x 1Q-6
3.Ox 1C'3
18
l.Ox 10'3 (estimated)
1.7 x 1Q-5
1.4x 1C'4
1.6x 1C'9
3.4 x 1C'9
9.4-18
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AND NONAGRICULTURAL
TABLE 9.4-2 (CONTINUED)
Active Ingredient
Vapor Pressure
(mmHgat20to25°C)
DCNA (dicloran)
DCPA (chlorthal-dimethyl; Dacthal®)
Diazinon
Dichlobenil
Dicofol
Dicrotofos
Dimethoate
Dinocap
Disulfoton
Diuron
Endosulfan
EPIC
Ethalfluralin
Ethion
Ethoprop (ethoprophos)
Fenamiphos
Fenthion
Fluometuron
Fonofos
Isofenphos
Lindane
Linuron
Malathion
Methamidophos
Methazole
Methiocarb (mercaptodimethur)
Methomyl
1.3x ID'6
2.5 x 1Q-6
6.0 x 1Q-5
l.Ox 1C'3
4.0 x ID'7
1.6x 1C'4
2.5 x 1Q-5
4.0 x ID'8
1.5 x 1C'4
6.9 x It)'8
1.7x ID'7
3.4 x It)'2
8.8x 1Q-5
2.4 x 1Q-6
3.8x 1C'4
l.Ox 1Q-6
2.8 x ID'6
9.4 x ID'7
3.4 x 1C'4
3.Ox 1Q-6
3.3x 1Q-5
1.7 x 1Q-5
8.Ox ID'6
8.Ox 1C'4
l.Ox ID'6
1.2x 1C'4
5.Ox ID'5
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
TABLE 9.4-2 (CONTINUED)
Active Ingredient
Vapor Pressure
(mmHgat20to25°C)
Methyl parathion
Metolachlor
Metribuzin
Mevinphos
Molinate
Naled
Norflurazon
Oxamyl
Oxyfluorfen
Parathion (ethyl parathion)
PCNB
Pendimethalin
Permethrin
Phorate
Phosmet
Profenofos
Prometon
Prometryn
Propachlor
Propanil
Propargite
Propazine
Propoxur
Siduron
Simazine
Tebuthiuron
Terbacil
Terbufos
1.5 x 1Q-5
3.1x 1Q-5
< l.Ox 1Q-5
1.3x 1C'4
5.6x 1C'3
2.0 x 1C'4
2.0 x 1Q-8
2.3 x 1C'4
2.0 x ID'7
5.Ox ID'6
l.lx 1C'4
9.4 x ID'6
1.3 x It)'8
6.4 x 1C'4
4.9 x ID'7
9.0 x ID'7
7.7 x 1Q-6
1.2x ID'6
2.3 x 1C'4
4.0 x 1Q-5
3.Ox 1C'3
1.3x ID'7
9.7 x 10'6
4.0 x 1C'9
2.2 x 1Q-8
2.0 x ID'6
3.1x ID'7
3.2 x 1C'4
9.4-20
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CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
TABLE 9.4-2 (CONTINUED)
Active Ingredient
Thiobencarb
Thiodicarb
Toxaphene
Triallate
Tribufos
Trichlorfon
Trifluralin
Triforine
Vapor Pressure
(mmHgat20to25°C)
2.2 x 1Q-5
l.Ox ID'7
4.0 x ID'6
l.lx 1C'4
1.6x ID'6
2.0 x 1Q-6
l.lx 1C'4
2.0 x ID'7
From Wauchope, et al, 1992. Vapor pressures of other pesticide active ingredients can also be found there.
TABLE 9.4-3
AVERAGE VOC CONTENT OF PESTICIDE INERT INGREDIENT
PORTION, BY FORMULATION TYPE*
Formulation Type
Average VOC Content Of Inert Portion
5 (wt. %)
Oils
Solution/liquid (ready to use)
Emulsifiable concentrate
Aqueous concentrate
Gel, paste, cream
Pressurized gas
Flowable (aqueous) concentrate
Mi croencapsul ated
Pressurized liquid/sprays/foggers
Soluble powder
Impregnated material
Pellet/tablet/cake/briquette
66
20
56
21
40
29
21
23
39
12
38
27
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6/18/01
TABLE 9.4-3 (CONTINUED)
Formulation Type
Wettable powder
Dust/powder
Dry flowable
Granule/flake
Suspension
Paint/coatings
Average VOC Content Of Inert Portion
(wt. %)
25
21
28
25
15
64
Written communication from California Environmental Protection Agency, Department of Pesticide Regulation,
Sacramento, CA, to D. Safriet, U.S. Environmental Protection Agency, Research Triangle Park, NC.
December 6, 1993.
TABLE 9.4-4
UNCONTROLLED EMISSION FACTORS FOR
PESTICIDE ACTIVE INGREDIENTS3
(METRIC AND ENGLISH UNITS)
EMISSION FACTOR RATING: E
Vapor Pressure Range
(mmHgat20°to25°C)b
Emission Factor0
kg/Mg
Ib/ton
Surface application
(SCC 24-61-800-001)
lxlO-4to IxlO'6
>1 x 10-4
Soil incorporation
(SCC 24-61-800-002)
<1 x 10-6
lxlO-4to IxlO'6
>1 x 10-4
350
580
2.7
21
52
700
1,160
5.4
42
104
a Factors are functions of application method and vapor pressure. SCC = Source Classification Code.
b See Wauchope et al, 1992 for vapor pressures of specific active ingredients.
c Based on Jury, etal, 1983a, Jury, etal, 1983b, Jury, etal, 1984a, Jury, etal, 1984b, and Midwest
Research Institute, 1994. Expressed as equivalent weight of active ingredients volatilized/unit weight
of active ingredients applied.
9.4-22
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CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
(4) Calculate the total emissions
where:
E = E + E
(9.4-3)
E = total emissions from pesticide applied during the 30 day period
Ej = emissions from active ingredient
E2 = emissions from inert ingredients
The 30-day period was chosen because (1) most pesticides volatilize within 30 days of
application and (2) there are very few data available on pesticide volatilization based on field
application studies with sampling times greater than 30 days.
Example 9.4-1
Ibs/year
Farmco Atrazine Gesaprim® is surface applied to the soil
surrounding corn at an annual rate of 3.5 Ibs/year/acre. There are
15,000 acres of corn in the area.
From Table 9.4-1, Gesaprim®'s active ingredient is atrazine, with a
vapor pressure (from Table 9.4-2) of 2.9 x 10"7 mm Hg at 20° to
25 °C. The pesticide is an emulsifiable concentrate that is 52
percent active ingredient and 48 percent inert ingredient. From
Table 9.4-4, the emission factor is 700 Ib/ton and from Table 9.4-3,
the VOC content of the inert portion of emulsifiable concentrates is
56 percent.
E! = 3.5 Ibs/year/acre x 15,000 acres x 1 ton/2000 Ibs x 0.52 x 700 Ib/ton = 9,555
E, = 3.5 Ibs x 15,000 acres x 0.48x0.56= 14,112 Ibs/year
4.2 NONAGRICULTURAL APPLICATIONS
4.2.1 MUNICIPAL
The preferred method for estimating emissions from municipal applications of pesticides
involves using a survey to collect data on the pesticide use and total acreage. The following
procedures should be followed:
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AND NONAGRICULTURAL
(1) Survey state and local government agencies, state and local highway departments, local
utility companies, and state and local park offices to determine:
• The amount of pesticides applied per acre;
• Total acres (parks, right-of-ways, etc.);
• The pesticides applied to those acres;
• The percent active and inert ingredients in the pesticides applied;
• The VOC content of the active and inert ingredients; and
* Times of year in which the pesticide was applied.
(2) Calculate a pesticide-specific VOC content for each pesticide that is applied in the study
area.
PVP = (PA x PVA) + (PI x PVI) (9.4-4)
where:
PVP = pounds VOC per pound of pesticide applied
PA = fraction active ingredient in the pesticide applied
PVA = fraction VOC in the active ingredient of the pesticide applied
PI = fraction inert ingredient in the pesticide applied
PVI = fraction VOC in the inert ingredient of the pesticide applied
(3) Using the pesticide-specific VOC content developed with equation 9.4-4, calculate the
total emissions.
Total emissions = PVP x R x A x ER (9.4-5)
where:
PVP = pounds VOC per pound of pesticide applied
R = pounds of pesticide applied per year per acre
A = total acres
ER = evaporation rate (typically 0.9) (Wiens, 1977)
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The seasonal adjustment factor should be calculated based on the information in Section 5.8 of
the Procedures document.
Example 9.4-2 Assume County X has 1,000 acres of park land and 300 acres of
other municipal land. Pesticide A is applied to 1,100 acres
(900 acres of park land plus 200 acres of municipal land), and is
47 percent active ingredient (90 percent VOC) and 53 percent inert
ingredient (60 percent VOC). Pesticide A is applied at 1.5 Ibs per
acre per year. Using Equations 9.4-4 and 9.4-5, emissions for
County X are calculated as follows:
PVP = (0.47 x 0.90) + (0.53 x 0.60) = 0.741 Ibs VOC per Ib Pesticide A
Total emissions = 0.741 Ib VOC/lb Pesticide A x 1.5 Ibs Pesticide A/acre/yr x
1,100 acres x 0.9
Total emissions = 1,100 Ib VOC/yr = 0.55 tons VOC/yr
The Procedures document assumes that the inert ingredient (solvent carrier) in the pesticide is
1.45 times the active ingredient (the amount of which can be found for most pesticides).
Therefore, 2.45 times the active ingredient has the potential to be emitted as a VOC. The
method in the Procedures document also assumes that 2 to 5 pounds of pesticide are applied per
year per acre (average of 3.5 pounds of pesticide per year per acre). This range was derived
from national pesticide use data, and can be used as a default or a check for the specific
application rate, if necessary. Therefore, where the survey does not provide enough detail, the
defaults of 2.45 pounds of VOC per pound of active ingredient and an average of 3.5 pounds of
pesticide per year per acre can be used. However, at a minimum, the survey must provide
information on the amount of active ingredients in the pesticides applied. Equation 9.4-6 shows
the calculation used in this approach.
Total emissions = R x PA x PVP x A x ER (9.4-6)
where:
R = pounds of pesticide applied per year per acre (in this approach, R = 3.5
pounds of pesticide per year, per acre)
PA = fraction active ingredient in the pesticide
PVP = pounds VOC per pound of active ingredient (in the approach, PVP =
2.45 pounds of VOC per pound of active ingredient)
A = total acres
ER = evaporation rate (typically 0.9) (Wiens, 1977)
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CHAPTER 9 - PESTICIDES -AGRICULTURAL
AND NONAGRICULTURAL
6/18/01
Example 9.4-3
Total emissions =
Again, assume County X has 1,100 acres of park and municipal
land. However, while the survey did not provide any information
on the application rate, it did indicate that 41 percent of the
pesticide is active ingredient. Using default assumptions (2.45
pounds VOC per pound active ingredient and 3.5 pounds pesticide
applied per year per acre), the calculation of total emissions is as
follows:
3.5 Ib pesticide/yr/acre x 0.41 Ibs active ingredient/lb pesticide x
2.45 Ib VOC/lb active ingredient x 1,100 acres x 0.9
Total emissions = 3,481 Ib VOC/yr = 1.74 tons VOC/yr
4.2.2 COMMERCIAL
The preferred method for estimating emissions from commercial applications of pesticides is to
conduct a survey to gather information on each commercial pesticide application company. The
following procedure should be used:
(1)
(2)
Survey commercial pesticide application companies (exterminators and lawn care
services) to determine the pesticides used, the formulation of the pesticides (indicating
the active and inert ingredients), and the total amount applied in a given period.
Calculate total emissions based on the information gathered in Step (1).
Total emissions = R x PA x PVA x ER
(9.4-7)
where:
R = pounds of pesticide applied per year
PA = fraction active ingredient in the pesticide applied
PVA = fraction VOC in the active ingredient or 2.45 pounds VOC per pound of
active ingredient
ER = evaporation rate (typically 0.9) (Wiens, 1977)
If R is given in gallons, it will be necessary to convert to pounds by multiplying by the density
of the pesticide. The density of the pesticide should be available from the manufacturer.
9.4-26
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Example 9.4-4 An area surveys commercial pesticide application companies and
determines that 1,500 gallons of pesticide X are used to eliminate
fleas and ticks and 10,000 pounds of pesticide Y are used for lawn
weed control. Pesticide X is 50 percent active ingredient. Pesticide
Y is 45 percent active ingredient. Pesticide X has a density of
7.2 pounds per gallon. Using the Equation 9.4-7, total emissions are
calculated as follows:
Total emissions of X = 1,500 gal/yr x 7.2 Ibs/gal x 0.5 Ibs active ingredient/lb
pesticide x 2.45 Ibs VOC/lb active ingredient x 0.9
Total emissions of X = 11,907 Ibs VOC/yr = 5.95 tons VOC/yr
Total emissions of Y = 10,000 Ibs/yr x 0.45 Ibs active ingredient/lb pesticide x 2.45
Ibs VOC/lb active ingredient x 0.9
Total emissions of Y = 9,923 Ibs VOC/yr = 4.96 tons VOC/yr
Total emissions for area = 11,907 Ibs VOC/yr + 9,923 Ibs VOC/yr = 21,830 Ibs
VOC/yr = 10.9 tons VOC/yr
4.2.3 CONSUMER
Limited information is available on consumer use of pesticides. In 1992, EPA conducted a
consumer/commercial products survey to determine the number of products, the sales of those
products, and the VOC content of the products. From these data, EPA calculated estimates of
emissions for specific product categories in pounds per 10,000 people and in tons for
nonattainment areas. Chapter 5 of this volume titled Consumer and Commercial Solvent Use
includes per capita emission factors for pesticide application. However, these per capita factors
are based on a wide range of uses including consumer, municipal, and commercial. Multiplying
the emission factor by the population yields total pesticides applied. Subtracting municipal and
commercial use (using any of the methods described in this chapter) yields estimates of
consumer usage.
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This page is intentionally left blank.
9.4-28 EIIP Volume III
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ALTERNATE METHODS FOR
ESTIMATING EMISSIONS
5.1 AGRICULTURAL APPLICATIONS
5.1.1 PESTICIDE-SPECIFIC VOLATILE COMPONENT OF PESTICIDE APPLIED
This alternative method for estimating emissions from agricultural applications of pesticides
uses a pesticide-specific volatile component of the pesticide, total acreage, and application rate.
The following procedures should be followed:
(1) Collect data on:
• The total harvested acreage by crop in the study area;
• The pesticides used for each crop;
• The time of year when the pesticide is typically applied to the crop. If the
application time is not during the inventory season, it may not be necessary to
estimate emissions for that pesticide;
• The application rate of each pesticide for each crop; and
• The percent active and inert ingredients and the VOC contents of each ingredient
for each pesticide used.
Some states may gather this information periodically, mainly on an annual basis. In addition,
many states publish an annual handbook which contains suggested pesticides for a particular
crop and suggested application rates. When this information is not already compiled, it can be
collected from other sources. Acreage by crop data can be found in the following sources:
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CHAPTER 9 - PESTICIDES -AGRICULTURAL 6/18/01
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• The Department of Commerce Bureau of Census publication Census of
Agriculture2 includes county level harvested acres by crop and other data that can
be helpful in estimating emissions. However, the Census of Agriculture is
published at 5 year intervals for years ending in "2" and "7" and may not be
available for the inventory year. Inventory preparers will need to decide whether
the data in this publication is suitable for their inventory area.
• The United States Department of Agriculture (USD A) National Agricultural
Statistics Service (NASS)3 maintains county statistics on production for major
crops and farm acreage.
* State agricultural departments and state commerce departments may also compile
the acreage of major crops in each county.
Although detailed information about the type of pesticide used, the time of application and the
pesticide-specific application rate for each county's crops may not be available, reasonable
estimates can be made based on local recommended practices. It is best to identify crops that
have either high rates of pesticide use or are the most significant crops in the area, so that
inventory personnel can focus their efforts on crops that are the most significant sources of
emissions in their area. Local agricultural extension agents can discuss the typical pesticide
treatment, application time, and application rate. Agricultural chemical suppliers can discuss
the recommended practices for the major crops in an area. State universities with agricultural
schools also can be contacted for recommended pesticide usage practices. When several
counties in an inventory area have similar crops, only one contact may be necessary to collect
data on all of the crops and pesticides.
Agricultural extension agents, agricultural chemical suppliers, and agricultural university
experts may also be sources of information about total VOC content of the pesticides used in the
area.
(2) Calculate the pesticide-specific VOC content of the pesticide applied.
PVP = (PA x PVA) + (PI x PVI) (9.5-1)
2 The Census of Agriculture is published every 5 years by the U.S. Department of
Commerce, Bureau of Census, Washington, D.C. Information about the Census can also be found
on the Bureau of Census Website at: http://www.census.gov/.
3 At the time of this writing, NASS maintains a World Wide Web site at:
http://www.usda.gov.nass/. Links are available to state offices. NASS can also be contacted
through the NASS Information Hotline at: 1-800-727-9540.
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where:
PVP = pounds VOC per pound of pesticide applied
PA = fraction active ingredient in the pesticide applied
PVA = fraction VOC in the active ingredient in the pesticide applied
PI = fraction inert ingredient in the pesticide applied
PVI = fraction VOC in the inert ingredient in the pesticide applied
(3) Using the pesticide-specific VOC content developed in Step (2), calculate the total
emissions.
Total emissions = PVP x R x A x ER (9.5-2)
where:
PVP = pounds VOC per pound of pesticide applied
R = pounds of pesticide applied per year per harvested acre
A = total harvested acres
ER = evaporation rate (typically 0.9) (Wiens, 1977)
This procedure would be followed for each pesticide and each crop for which it is used.
Example 9. 5-1 Pesticide A is applied to corn at an annual rate of 3.8 Ibs/year/acre.
There are 2,100 acres of corn in the area. Pesticide A is 47 percent
active ingredient (90 percent VOC) and 53 percent inert ingredient
(60 percent VOC).
Using the above equations, total emissions from Pesticide A applied
to corn in this area are calculated as follows:
PVP = (0.47 x 0.90) + (0.53 x 0.60) = 0.741 Ibs VOC/lb Pesticide A applied
Total emissions = 0.741 Ibs VOC/lb Pesticide A x 3.8 Ibs Pesticide A/yr/acre x
2,100 acres x 0.9
Total emissions = 5,322 Ibs VOC/yr = 2.7 tons VOC/yr
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5.1.2 DEFAULT VOLATILE ORGANIC COMPONENT OF PESTICIDE APPLIED
Another alternative method for estimating emissions is to use a default for the VOC content of
the pesticide. This method also requires the use of total acreage and application rate. The
following procedures should be followed:
(1) Contact State Agricultural Departments to collect data on:
• The total harvested acreage by crop in the county/nonattainment area;
• The pesticides used for each crop;
• The application rate of each pesticide for each crop; and
• The percent active ingredient for each pesticide used.
(2) Calculate the total emissions using the information gathered in Step (1). The Procedures
document assumes that the inert ingredient (solvent carrier) in the pesticide is 1.45 times
the active ingredient (the amount of which can be found for most pesticides)
(EPA, 1991). Therefore, 2.45 times the active ingredient has the potential to be emitted
as a VOC. The following equation is the same as the equation for the preferred method;
however, a default VOC content of 2.45 pounds VOC per pound active ingredient is
assumed in place of the pesticide-specific VOC content (PVP).
Total emissions = A x R x I x ER x 2.45 pounds VOC/pound active ingredient (9.5-3)
where:
A = total harvested acres
R = pounds of pesticide applied per year per harvested acre
I = pounds of active ingredient per pound of pesticide
ER = evaporation rate (typically 0.9) (Wiens, 1977)
Again, this procedure would be followed for each pesticide and each crop for which it is used.
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AND NONAGRICULTURAL
Example 9.5-2 Assume an area has 800,000 acres of corn and 2.9 Ibs of pesticide
are applied per year per harvested acre. The pesticide contains
0.8 Ibs of active ingredient (AI) per Ib of pesticide (P).
Using the equation above, total emissions are calculated as follows:
Total emissions = 800,000 acres x 2.9 Ibs P/acre x 0.8 Ibs AMb P x 2.45 Ibs
VOC/lb AI x 0.9
Total emissions = 4,092,480 Ibs VOC/yr = 2,046 tons VOC/yr
The method in the Procedures document assumes that 2 to 5 Ibs of pesticide are applied per year
per harvested acre (average of 3.5 Ibs of pesticide per year per harvested acre). This range was
derived from national pesticide use data, and can be used as a default or a check for the specific
application rate, if necessary.
5.1.3 VOLATILITY/BlODEGRADABILITY METHOD
The final alternative method for calculating emissions takes into consideration the volatility and
the biodegradability of the pesticide (CARB, 1991). The data that are used in the methodology
are available through the California Department of Food and Agriculture's Pesticide Use Report.
The methodology classifies pesticides into the following four categories:
• Very low volatility pesticides;
• High volatility pesticides;
• Semi-volatile pesticides that are highly absorbed; and
• Semi-volatile pesticides that are highly biodegradable.
Table 9.5-1 provides a list of highly absorbed and highly biodegradable semi-volatile pesticides.
For those pesticides with very low volatility (vapor pressure less than 10"7 mm Hg), the pesticide
is assumed not to volatilize and therefore has no emissions associated with its application
(Li, 1981). For those pesticides that are highly volatile (vapor pressure greater than 0.3 mm
Hg), the amount of pesticide that is applied is assumed to equal the total emissions from that
pesticide because it will completely evaporate within a month of the application (Seiber, et a/.,
1983).
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6/18/01
TABLE 9.5-1
SEMI-VOLATILE PESTICIDES'*
Highly Adsorbed Pesticides'3
Azinphosmethyl
Chlordane
Chloroxuron
Dichlobenil
Fenac
Fluchloralin
Heptachlor
Nitralin
Picloram
Tebuthiuron
Highly Biodegradable Pesticides0
Alachlor
Amitrole
Ammonium Ethyl
Carbamoylphosphonate
Barb an
Bentazon
Bromoxynil Octanoate
Dalapon
Eptam
IPC (Propham)
Monocrotophos
Propanil
2-4-D
a Data in this table has been drawn from Matsumura and Murti, 1982; Wangern, 1983; Verschueren, 1983; Weed
Science Society of America, 1979; and Worthing, 1979.
b Pesticides that persist for one year or more and are not considered to undergo biological degradation.
0 Pesticides that undergo complete biodegradation within 30 days and are not considered subject to sequestration.
Assume loss due to biodegradation will be 30 percent per month.
Special calculation procedures were developed for the semi-volatile pesticides. Figure 9.5-1 is a
flow chart of the process. Due to pesticide applications being reported in acres as well as other
units (such as gallons), equations exist for each type of application units (this does not affect the
process as outlined in Figure 9.5-1).
For acreage applications, emissions during application = Al - A2
(9.5-4)
9.5-6
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CHAPTER 9 - PESTICIDES - AGRICULTURAL
AND NONAGRICULTURAL
LOSS
EMISSIONS
Pesticides
applied
(Ai)
Loss by
sequestration
Emissions
during
application
(Ai-A2)
Pesticide
deposited
(A2)
Loss by
degradation
during a month
Pesticides
deposited
at start of month
Pesticide available
for evaporation
during month
(A4)
Emissions by
evaporation
during month
(Ax)
Pesticide remaining
at end of month
(A4-Ax)
FIGURE 9.5-1
FLOWCHART OF EMISSIONS ESTIMATION METHOD FOR SEMI-VOLATILE PESTICIDES
EIIP Volume III
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where:
Aj = total pesticide applied per acre
A2 = total pesticide deposited per acre
To calculate A2, use the following equation:
A2 =A! x (1 - [4.625 x (log P; + 7) x (0.0024 x T2) x 0.01] (9.5-5)
where:
P; = vapor pressure of pesticide i (mm Hg at 20°C)
T = average temperature in the month of application (°C)
It is assumed that 2 percent of the amount of pesticide deposited is lost by sequestration and that
an additional 4 percent of the remaining amount of pesticide (after sequestration) is lost by
biodegradation. Therefore, the calculation of those losses is as follows:
A3 = (1 - 0.02) x A2 (9.5-6)
where:
A3 = remaining pesticide per acre after sequestration
A2 = total pesticide deposited per acre
A4 = (1 - 0.04) x A3 (9.5-7)
where:
A4 = remaining pesticide per acre after loss by biodegradation
A3 = remaining pesticide per acre after sequestration
In order to calculate the emissions on a monthly basis, the maximum monthly evaporation rate
must be calculated. The Hartley Equation is used to calculate the maximum monthly
evaporation rate as follows (Hartley, 1969):
Ep = [EA/(1-RH)] x [(P; x M;a5)/(Pw x Mw°-5) (9.5-8)
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where:
Ep = the maximum evaporation rate of compound i in Ibs/acre during the
month p (Ep is calculated for each month)
EA = adjusted water evaporation rate in Ibs/acre
RH = average relative humidity during the month p (in percent)
P; = vapor pressure of compound i at cited temperature (mm Hg)
M; = molecular weight of compound i
Pw = vapor pressure of water at cited temperature (mm Hg)
Mw = molecular weight of water
EA is equal to 0.73 x E, 0.40 x E, and 0.70 x E for applications to vegetated land, soil surfaces,
and water surfaces, respectively. E is equal to the inches of water evaporated times
226,600 pounds per inch of water on one acre.
The monthly emissions from the deposited pesticide are calculated by the following equation:
k x t = 2.303 x log[A4/(A4 - Ax)] (9.5-9)
where:
k = rate constant
t = time in days
A4 = remaining pesticide after loss by biodegradation in Ibs per acre
Ax = pounds of pesticide evaporated per acre in any month for time t
This is an iterative process starting with t=l and solving for k. The calculation of monthly
emissions would continue by calculating the losses and following the steps outlined above until
Ax is less than 0.1 pounds per acre or 12 months have passed since the application. The
calculation is best illustrated with an example (see Example 9.5-3).
5.2 NONAGRICULTURAL APPLICATIONS
The alternative method for estimating emissions is through the use of national per capita
emission factors for nonagricultural pesticide uses provided in Chapter 5 of this volume, titled
"Consumer and Commercial Solvent Use."
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Example 9.5-3 Assume that an area applies mineral oil as an insecticide to nectarines. The vapor
pressure of mineral oil is 7.4 x 10"6 mm Hg, and its molecular weight is 327. Assume
that 182 pounds of the insecticide are applied in February on 23 acres of nectarines.
The average temperature in February is 10.28°C, with a relative humidity of
75 percent and a water evaporation rate of 2.46 inches. The vapor pressure of water
is 17.535 mm Hg, and its molecular weight is 18.
Emissions during application
A2 = 182/23 x (1 - [(4.625) x (log 7.4F6 + 7) x (0.0024) x (10.282) x (0.01)]) (9.5-5)
A2 = 7.74 Ibs/acre deposited
A! - A2 = 182/23 -178/23 = 0.17 Ibs/acre emitted during application (9.5-4)
Loss by sequestration
A3 = (1 - 0.02)(7.74) = 7.6 Ibs/acre deposited after sequestration (9.5-6)
Loss by biodegradation
A4 = (1 - 0.04)(7.6) = 7.3 Ibs remaining after loss by biodegradation (9.5-7)
Maximum evaporation rate
Ep = [(0.73 x 2.46 x 226,600)7(1-0.75)] x [(7.4 x 10'6 x 327° 5)/(17.535 x 18°5)] (9.5-8)
Ep = 2.93 Ibs/acre
Monthly emissions
solve for k at t = 1 day
A4 = 7.3 Ibs/acre
Ax = 2.93 lbs/acre/30 days = 0.0976667
k x 1 = 2.303 log [7.37(7.3 - 0.0976667)] (9.5-9)
k = 0.0134717
then solve for Ax
0.0134717 x 30 = 2.303 log [7.37(7.3 - AJ]
7.37(7.3 - AJ = antilog (0.1754889)
Ax = 2.426 Ibs/acre during the month
Therefore the total emissions in February are:
Total emissions = (Al - A2) + Ax x acres
Total emissions = 4 + 2.426 x 23 = 59.8 Ibs
To determine whether to continue the calculation of monthly emissions, determine the remaining
pesticide that is available for the next month as follows:
A4 - Ax = 7.3 - 2.426 = 4.874 Ibs/acre, which is greater than 0.1 Ibs/acre, therefore the calculation is
continued for the month of March following the same procedure as outlined above.
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5.3 METHOD FOR ALL USERS: TOP-DOWN SOLVENT USE METHOD
Another alternative type of methodology involves the estimation of national solvents
consumption, spatial allocation of consumption to counties, and application of local control
regulations. Estimation of national consumption is based on a material balance approach, since
this is the best way of ensuring that the inventory covers all solvents emissions. A detailed
description and application of this method with emission calculations can be found in (reference
project report). The steps required for this method are:
• Estimate solvents consumption for this source category at the national level.
These data can be obtained from solvents industries studies (reference project
report).
Apply growth indicator, if national solvent consumption data from
industry studies are not available for the target inventory year:
*• Use national solvent consumption projections for the target
inventory year from industry studies, or extrapolate between past
and future years that span the target inventory year, using data
obtained from the same national solvent consumption data from
industry studies.
» Use BEA estimates of future employment and Census projections
of population to project solvent use from national solvent
consumption data from industry studies for previous years.
• Estimate county-level solvents consumption (S) from national data in the same
proportions as employment for this source category. The following equation is
used to allocate national consumption to counties:
Scty= Snat * Fnat, cty (9.5.10)
where:
Scty = County solvent consumption
Snat = National solvent consumption
Fnat cty = Spatial allocation factor for the county: the ratio of employment in
the county to nationwide employment
Note: Employment data at a county level are available in the County Business Patterns database (U.S. DOC).
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• Incorporate the effects of national, state, and local regulations1 into spatial
allocation to counties. On the state/local level, stricter controls in some
states/counties than in others has the effect of moving some of the solvent
emission from the more highly controlled counties/states into other
counties/states. (Reference project report).
Estimate the extent of recycling and waste management practices in the
source category.
• Subtract out point source solvent use, using the method described in
Section 3.2.2. Point sources should be accounted for, and subtracted out from,
the solvent consumption that is allocated to the county level. Point source
solvent consumption for the category may be determined from the emission
factor(s) used or from other underlying consumption data if available.
Otherwise, the point source activity (solvent consumption) may be assumed
equal to point source (uncontrolled) emissions, and that proportion subtracted
from the total county solvent consumption.
• The emission factor used in converting solvents to VOC2 emissions is complete
conversion of consumption to emission (2000 Ibs solvent/ton VOC) adjusted for
controls/regulations,1 recycling and waste management, and processes that
consume solvents with no emissions. For activity data in terms of
product/coating consumption, emission factors account for the amount of solvent
in the product/coating by including a solvent content factor.
1 State any assumptions made to include national/state/local regulations and the exact
regulation applied. Clarify any issues related to regulation and control assumptions. The
final emissions estimates are highly dependent on these assumptions, therefore they must
be stated explicitly in all documentation.
2 The solvents consumption information is identified by solvent chemical and type of
source. Some of the solvents chemicals are HAPs, and one could follow a similar
process as the above method (which estimates VOC not individual chemicals to obtain
estimates for some HAPs.
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QUALITY ASSURANCE/
QUALITY CONTROL
Data collection and handling for this source category should be planned and documented in the
Quality Assurance Plan. When using survey methods, the survey planning and data handling
should also be documented. Refer to the discussion of survey planning and survey QA/QC in
Chapter 1, Introduction to Area Source Emission Inventory Development., of this volume, and
Volume VI, Quality Assurance Procedures, of the Emission Inventory Improvement Program
(EIIP) series. Potential pitfalls when developing emission estimates by using a survey for this
category are data gaps due to surveys not returned; unanswered or misunderstood survey
questions; inappropriate assumptions used to compensate for missing information or scaling up
the survey sample; errors in compiling the returned survey information; and calculation errors,
which can include unit conversion errors, and data handling errors.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
For agricultural pesticide emission estimates, the third alternative method gives higher Data
Attribute Rating System (DARS) scores, but requires more effort than the other methods. The
preferred method for agricultural pesticide gives the next highest DARS scores.
The lowest potential DARS score assigned to any of the methods is assigned to the preferred
method for consumer pesticide use. The method recommends using the pesticide use portion of
the emission factor from Chapter 5 of this volume, Consumer and Commercial Solvent Use, for
consumer pesticide use. However, this factor has been developed for consumer and commercial
(which includes municipal) users and must be corrected by subtracting the estimated municipal
and commercial emissions in order to estimate consumer pesticide use only. The alternative
method for municipal, commercial, and consumer pesticide use recommends using the
unadjusted pesticide use emission factor from Chapter 5 of this volume to estimate emissions
for all of these users. It is more suitable in this case, and has a higher DARS score. Another
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advantage of using this alternative method is that it is a straightforward and economical
approach.
6.1.2 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 9.6-1 through 9.6-7. A range of
scores is provided for the methods because the implementation of these methods can vary. The
higher scores assume that reliable data were collected specifically for the inventory area and
time period, and few, if any, assumptions or generalizations have been made in the data
gathered. All scores assume that satisfactory QA/QC measures are performed and no significant
deviations from good inventory practices have been made. If these assumptions are not met,
new DARS scores should be developed according to the guidance provided in Appendix F of
EIIP Volume VI.
The preferred method for agricultural pesticide use is to collect detailed data on pesticide usage
and type, and estimate emissions based on the pesticide formulation vapor pressure and
application method. DARS scoring for this method is shown in Table 9.6-1. The preferred
method for municipal and commercial pesticide use and the first alternative method for
agricultural pesticide use collect information on the amount of active and inert ingredients and
assume a standard emission rate. DARS scores for these sources are shown in Tables 9.6-2 and
9.6-3. The second alternative method for agricultural pesticide use is similar to the first
alternative method, but uses a default proportion of active to inert ingredients. DARS scores for
the second alternative method for agricultural pesticides are shown in Table 9.6-4. In each of
these methods, the approach is similar, but the method of calculating emissions becomes more
generalized and consequently, DARS scores for the emission factor become lower. The third
alternative method for agricultural pesticide use collects detailed data on pesticide usage and
type, and estimates emissions based on the pesticide formulation vapor pressure, local
temperatures, and reductions from sequestration and biodegradation. The DARS scores for this
method are shown in Table 9.6-5.
The preferred method for consumer pesticide use calculates emissions from the per capita
pesticide usage factor provided in Chapter 5 of this volume for all municipal, commercial, and
consumer pesticide use, and then subtracts the estimated emissions from commercial and
municipal users collected by survey. Because the preferred method for municipal and
commercial pesticide use is based on local survey data, it will provide an estimate that reflects
local usage. If these emission estimates are significantly different from the national average
(which is inherent in the pesticide usage factor in Chapter 5), then using the surveyed estimates
for municipal and commercial pesticide use to adjust the consumer estimate will skew the
estimate for consumer pesticide use in a manner that is opposite from the most likely local
consumption level.
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TABLE 9.6-1
PREFERRED: AGRICULTURAL PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.5-0.5
0.6-0.8
0.7-0.8
0.5-0.8
0.58-0.73
Activity
0.3-0.9
0.4-0.9
0.7- 1
0.7-0.9
0.53-0.93
Emissions
0.15-0.45
0.24 - 0.72
0.49-0.8
0.35-0.72
0.31 -0.67
TABLE 9.6-2
PREFERRED: MUNICIPAL AND COMMERCIAL PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3-0.4
0.5-0.7
0.6-0.7
0.5-0.5
0.48-0.58
Activity
0.3-0.6
0.3-0.6
0.6-0.9
0.7-0.9
0.48-0.75
Emissions
0.09 - 0.24
0.15-0.42
0.36-0.63
0.35-0.45
0.24 - 0.44
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TABLE 9.6-3
ALTERNATIVE 1: AGRICULTURAL PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3 -0.4
0.5-0.7
0.6-0.6
0.5-0.5
0.48-0.55
Activity
0.3-0.6
0.3-0.6
0.6-0.9
0.7-0.9
0.48-0.75
Emissions
0.09 - 0.24
0.15-0.42
0.36-0.54
0.35-0.45
0.24-0.41
TABLE 9.6-4
ALTERNATIVE 2: AGRICULTURAL PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3
0.5
0.6
0.5
0.48
Activity
0.3-0.6
0.5-0.7
0.6-0.9
0.7-0.9
0.53-0.78
Emissions
0.09-0.18
0.25-0.35
0.36-0.54
0.35-0.45
0.26-0.38
9.6-4
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TABLE 9.6-5
ALTERNATIVE 3: AGRICULTURAL PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.5-0.5
0.7-0.8
0.7-0.8
0.8-0.8
0.68-0.73
Activity
0.3-0.9
0.7-0.9
0.7- 1
0.7-0.9
0.6-0.93
Emissions
0.15-0.45
0.49 - 0.72
0.49-0.8
0.56-0.72
0.42 - 0.67
TABLE 9.6-6
PREFERRED: CONSUMER PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3
0.5
0.5
0.6
0.48
Activity
0.6
0.5
0.5
0.9
0.63
Emissions
0.18
0.25
0.25
0.54
0.31
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TABLE 9.6-7
ALTERNATIVE 1: MUNICIPAL, COMMERCIAL, AND CONSUMER PESTICIDE USE
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3
0.7
0.6
0.6
0.55
Activity
0.6
0.5
0.9
0.9
0.73
Emissions
0.18
0.35
0.54
0.54
0.40
The unadjusted per capita emission factor is also recommended as the first alternative method
for municipal, commercial and consumer pesticide use. A discussion of QA/QC for the per
capita method can be found in Chapter 5 of this volume, but the BARS scores for the use of the
per capita pesticide factor have been compiled for the preferred consumer method and the first
alternative municipal, commercial, and consumer method, and are shown in Tables 9.6-6 and
9.6-7.
Scores for these methods are presented as ranges to allow for variability in data collection and
the use of assumptions. The upper range of scores can be used as long as survey responses are
complete and few assumptions have been made. However, assumptions about the pesticides
used in an area, the volatility of a pesticide, or the proportion of volatile organic compounds
(VOC) to the amount of active ingredients will result in lower scores. Temporal congruity
DARS scores may need to be lowered if emissions are estimated for a longer or shorter time
period than the inventory time period, and the estimates are apportioned to the inventory time
period without adjustment for variations in usage or temperature. When using these methods,
inventory preparers are cautioned to consider the feasibility of the methods and the detail
necessary to develop an estimate that merits the higher score.
DARS scoring attributes were originally developed for rating emission factor-based methods
(EIIP Volume VI, Appendix F). When applying DARS scores to methods that use more than
emission and activity factors in the calculation, it is useful to review which DARS attribute
covers which part of the emission estimation method. For the methods described in this chapter,
the DARS attributes reflect the following qualities:
9.6-6
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• Measurement — The quality and reliability of the data used as variables in the
emission estimation equation. For this source category, this attribute is used to
show how well the method (material balance) takes all the potential variables
affecting emission rates into account;
• Source Specificity — The specificity of the equation to the actual emission
process, the choices of variables used or not used in the emission estimation
equation, or the use of surrogate variables in the equation;
• Spatial Congruity — The variability in emissions that may be introduced by local
climate, terrain, or other environmental factors, and the scaling of data used in
the emission estimation equations for the inventory area; and
• Temporal Congruity — The specificity of the method and the data used in the
method to the temporal scale of the inventory.
6.1.3 SOURCES OF UNCERTAINTY
Another way to evaluate the emission estimates is to examine the associated uncertainty. For
estimates derived from survey data, the uncertainty can be quantified (see Chapter 4 of
Volume VI of the EIIP series). Statistics needed to quantify the uncertainty of emissions
derived by the per capita emission factor method are incomplete. Please refer to Chapter 5 of
this volume, Consumer and Commercial Solvent Use., for further discussion of the uncertainties
associated with the use of these emission factors.
There are a number of sources of uncertainty in estimating emissions from this source category.
Emissions from pesticide use depend on variables such as the amounts and types of pesticides
used, application method, the timing of the application relative to the inventory period, and
meteorology. Data collection alone for this number of variables is likely to be a source of
uncertainty. The preferred method for consumer pesticide use, which adjusts a national average
per capita emission factor with the estimated emissions from municipal and commercial use
surveys, is affected by the associated uncertainty of both the emission factor and the surveys of
commercial and municipal pesticide usage.
The preferred emission estimation methods for agricultural, municipal, and commercial
pesticide emissions, and the third alternative method for agricultural pesticide emissions are
based on the actual amount and types of pesticides used, and include more of the potential
variables in their respective emission estimation equations. These methods can be viewed as
being the least uncertain of the methods presented here. The remaining alternative methods
have increasingly uncertain results as more and more assumptions are made.
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from agricultural and
non-agricultural pesticides. A complete list of Source Classification Codes (SCC) can be
retrieved at http://www.epa.gov/ttn/chief/codes/. Table 9.7-1 lists the applicable SCCs for
agricultural and non-agricultural pesticides.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use
in regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data
elements necessary to complete the data set for use in regional or national air quality and human
exposure modeling. The inventory preparer should review the area source portion of the
acceptable file format(s) to understand the necessary data elements. The EPA describes its use
and processing of the data for purposes of completing the national inventory, in its Data
Incorporation Plan, also located at http://www.epa.gov/ttn/chief/net/.
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TABLE 9.7-1
AREA AND MOBILE SOURCE CATEGORY CODES
FOR AGRICULTURAL AND NONAGRICULTURAL
PESTICIDES APPLICATIONS
Process Description
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Pesticide Application
Herbicides - Corn
Herbicides - Apples
Herbicides - Grapes
Herbicides - Potatoes
Herbicides - Soybeans
Herbicides - Hay and Grain
Herbicides - Misc. Agricultural Use
Other Pesticides - Corn
Other Pesticides - Apples
Other Pesticides - Grapes
Other Pesticides - Potatoes
Other Pesticides - Soybeans
Other Pesticides - Hay and Grain
Other Pesticides - Misc. Agricultural Use
Nonagri cultural Use
Source Category Code
24-61-850-001
24-61-850-002
24-61-850-003
24-61-850-004
24-61-850-005
24-61-850-006
24-61-850-009
24-61-850-051
24-61-850-052
24-61-850-053
24-61-850-054
24-61-850-055
24-61-850-056
24-61-850-099
24-61-870-999
9.7-2
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8
REFERENCES
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C ARB. 1991. Methods for Assessing Area Source Emissions in California. California Air
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Li, Ming-Yu. 1981. Recommendations for the Future Use of the Pesticide Use Report Data to
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Wauchope, R.D., et al. 1992. The SCS/ARS/CES Pesticide Properties Database for
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Weed Science Society of America. 1979. Herbicide Handbook.
Wiens, F.J., Reactive Organic Gas Emissions from Pesticide Use in California. California Air
Resources Board, Report No. PD-777-002. Sacramento, California.
Worthing, C.R. Editor. 1979. The Pesticide Manual. British Crop Protection Council.
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USDA. 1992. Agricultural Chemical Usage: 1991 Field Crops Summary. U.S. Department of
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Verschueren, K. 1983. Handbook of 'Environmental Data on Organic Chemicals. Van
Nastrand Reinhold Company. New Jersey.
8-2 EIIP Volume III
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VOLUME III: CHAPTER 11
GASOLINE MARKETING (STAGE I AND
STAGE II)
Revised Final
January 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared for the Area Sources Committee of the Emission Inventory
Improvement Program and for Charles Mann of the Air Pollution Prevention and Control
Division, U.S. Environmental Protection Agency. Members of the Area Sources Committee
contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
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IV EIIP Volume III
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CONTENTS
Section Page
1 Introduction 11.1-1
2 Source Category Description 11.2-1
2.1 Category Description 11.2-1
2.2 Process Description and Emission Sources 11.2-1
2.3 Factors Influencing Emissions 11.2-3
2.4 Control Techniques 11.2-3
3 Overview of Available Methods 11.3-1
3.1 Emission Estimation Methodologies 11.3-1
3.2 Available Methodologies 11.3-1
3.1.1 Emission Factors 11.3-2
3.1.2 Activity Levels 11.3-3
3.1.3 Special Emission Calculation Issues 11.3-8
3.1.4 Methodology Summaries 11.3-8
3.3 Data Needs 11.3-8
3.3.1 Data Elements 11.3-8
3.3.2 Adjustments to Emissions Estimates 11.3-11
3.3.3 Point Source Corrections 11.3-11
3.3.4 Application of Controls 11.3-11
3.3.5 Spatial Allocation 11.3-12
3.3.6 Temporal Resolution 11.3-12
3.4 Projecting Emissions 11.3-13
4 Preferred Methods for Estimating Emissions 11.4-1
4.1. Gasoline Trucks in Transit 11.4-1
4.2 Fuel Delivery to Outlets 11.4-2
4.3 Vehicle Refueling 11.4-2
4.4 Storage Tank Breathing 11.4-3
5 Alternative Methods for Estimating Emissions 11.5-1
5.1 Alternative Method 1 11.5-1
5.1.1 Gasoline Trucks in Transit 11.5-1
5.1.2 Fuel Delivery to Outlets 11.5-2
5.1.3 Vehicle Refueling 11.5-2
5.1.4 Storage Tank Breathing 11.5-3
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CONTENTS (CONTINUED)
Section Page
5.2. Alternative Method 2 11.5-3
5.2.1 Gasoline Trucks in Transit 11.5-3
5.2.2 Fuel Delivery to Outlets 11.5-3
5.2.3 Vehicle Refueling 11.5-4
5.2.4 Storage Tank Breathing 11.5-4
6 Quality Assurance/Quality Control 11.6-1
6.1 Emission Estimate Quality Indicators 11.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 11.6-1
6.1.2 Sources of Uncertainty 11.6-8
7 Data Coding Procedures 11.7-1
7.1 Necessary Data Elements 11.7-1
8 References 11.8-1
VI EIIP Volume III
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FIGURES AND TABLES
Figure Page
11.2-1 Gasoline Marketing Operations and Emission Sources 11.2-2
Table Page
11.3-1 VOC Emission Factors for Gasoline Marketing Activities 11.3-2
11.3-2 HAP Percent of VOC Emissions 11.3-2
11.3-3 Preferred and Alternate Methods for Estimating Emissions from Gasoline
Distribution Subcategories 11.3-5
11.3-4 Data Elements Needed for Each Method 11.3-10
11.3-5 Daily and Hourly Allocation of Gasoline Distribution System
Emissions 11.3-13
11.6-1 Preferred Method DARS Scores: Tank Trucks in Transit; Local Gasoline
Sales, Adjustment Factor from Highway Weigh Station Data 11.6-2
11.6-2 Alternative Method 1 DARS Scores: Tank Trucks in Transit; Local Gasoline
Sales, Default Adjustment Factor 11.6-2
11.6-3 Alternative Method 2 DARS Scores: Tank Trucks in Transit; Scaled
State-Level Gasoline Sales, Default Adjustment Factor 11.6-3
11.6-4 Preferred Method DARS Scores: Fuel Delivery to Outlets; Local Gasoline
Sales, Filling Method from Survey 11.6-3
11.6-5 Alternative Method 1 DARS Scores: Fuel Delivery to Outlets; Scaled
State-Level Gasoline Sales, Filling Method from Survey 11.6-4
11.6-6 Alternative Method 2 DARS Scores: Fuel Delivery to Outlets; Scaled
State-Level Gasoline Sales, Filling Method from Trade Groups 11.6-4
11.6-7 Preferred Method DARS Scores: Vehicle Refueling; Local Gasoline Sales,
Filling Method from Regulators 11.6-5
EIIP Volume III vii
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FIGURES AND TABLES (CONTINUED)
Table Page
11.6-8 Alternative Method 1 BARS Scores: Vehicle Refueling; Scaled State-Level
Gasoline Sales, Filling Method from Survey 11.6-5
11.6-9 Alternative Method 2 DARS Scores: Vehicle Refueling; Gasoline Use from
VMT, Filling Method from Survey 11.6-6
11.6-10 Preferred Method DARS Scores: Storage Tank Breathing; Local Gasoline
Sales 11.6-6
11.6-11 Alternative Method 1 DARS Scores: Storage Tank Breathing; Scaled
State- Level Gasoline Sales 11.6-11
11.7-1 Area and Mobile Source Category Codes For Gasoline Marketing 11.7-2
Vlll EIIP Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
This chapter describes the procedures and recommended approaches for estimating emissions
from gasoline tank trucks in transit and at retail gasoline marketing outlets. Section 2 of this
chapter contains a general description of the gasoline distribution industry category and an
overview of available control technologies. Section 3 provides an overview of available
emission estimation methods. Section 4 presents the preferred method for estimating emissions,
and Section 5 presents the alternative emission estimation techniques. Quality assurance issues
and emission estimate quality indicators for the methods presented in this chapter are discussed
in Section 6. Data coding procedures are discussed in Section 7. Section 8 contains references
used for this chapter.
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SOURCE CATEGORY DESCRIPTION
2.1 CATEGORY DESCRIPTION
Motor gasoline is produced by domestic petroleum refineries or in some cases imported to the
United States, and then transported through a distribution network to customers. The distribution
network is a complex system that includes many wholesale and retail outlets. The network
includes a variety of storage and transfer facilities. Gasoline may be transported by tanker ships
and barges, through pipelines, or by rail tank cars or tank trucks. This chapter covers most of
those sections of the distribution network where evaporative emissions are usually considered to
be area sources. Stage I and Stage n emissions (occurring during the transfer of gasoline from
tank trucks to storage tanks at service stations, and subsequent transfer to the vehicle gasoline
tank, respectively) are covered, as well as emissions from delivery trucks in transit, gasoline
station storage tanks, and spillage. Additional information about this category can be found in
AP-42 (Section 4.4) (EPA, 1995), and the AIRS Area and Mobile Source Category Codes
(EPA, 2000).
Figure 11.2-1 shows a typical path by which gasoline may be transported from producer to
consumer. This path includes operations that are not addressed in this chapter. Marine vessel
loading and unloading operations are covered in Chapter 12. Bulk terminals and gasoline bulk
plants, which are intermediate distribution points between refineries and outlets, are usually
inventoried as point sources. Loading and unloading of railroad tank cars and pipeline
transmission losses could be significant area source categories in some areas, but have not been
included in this chapter.
2.2 PROCESS DESCRIPTION AND EMISSION SOURCES
The area sources of evaporative VOC emissions from the distribution of gasoline that are
covered in this chapter include the following:
• Trucks in transit: evaporation of gasoline vapor (1) from loaded tank trucks
during transportation of gasoline from the bulk plant/terminal to the service
station or other dispensing outlet, and (2) from empty tank trucks returning from
service stations to bulk plant/terminals.
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Refinery
Gasoline
Pipeline
Imported
Gasoline
Tank Truck
Tank Car
! = Emissions Sources
Tanker/Barge
Figure 11.2-1
Gasoline Marketing Operations and Emission Sources
11.2-2
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• Stage I: displacement of gasoline vapors from the storage tanks during the
transfer of gasoline from tank trucks to storage tanks at the service station
• Stage II: displacement of gasoline vapors from vehicle gasoline tanks during
vehicle refueling. This category also may include spillage of gasoline (and
subsequent evaporation) during either delivery activity above. This loss includes
prefill and postfill nozzle drip and spitback and overflow from the filler pipe of
the vehicle's fuel tank during filling.
• Storage tank working losses: evaporation of gasoline vapors from the storage
tank and from the lines going to the pumps during transfer of gasoline.
Service stations (Standard Industrial Classification code 5541) traditionally have been the
primary retail distributors for gasoline. Gasoline can be purchased from other types of
businesses, such as auto repair garages, parking garages, and convenience stores. Gasoline may
also be distributed to vehicles through various nonretail outlets, such as government motor pools
and other vehicle fleet servicing operations. Gasoline is stored in underground and aboveground
storage tanks at service stations and other dispensing facilities. Evaporative emissions occur
during tank filling and vehicle refueling.
2.3 FACTORS INFLUENCING EMISSIONS
VOC emissions from gasoline marketing activities are influenced by several factors. Fuel
volatility (measured as Reid vapor pressure, or RVP) affects the evaporation rate of gasoline.
The technology for loading tank trucks and tanks (splash loading, submerged loading, vapor
balance, etc.) affects the release of displacement emissions. Tank characteristics (color and
design) affect working losses from aboveground storage tanks.
2.4 CONTROL TECHNIQUES
Emissions from underground tank filling operations at service stations (Stage I emissions) can be
reduced by the use of a vapor balance system, which consists of a hose that returns gasoline
vapors displaced from the underground tanks during filling back to the tank truck, as well as
measures to ensure tightness of the truck. The control efficiency of the balance system can range
from 93 to 100 percent (EPA, 1995). Emissions from vehicle refueling (Stage II emissions) also
can be reduced by a vapor balance system. During refueling, the vapors displaced from the
vehicle fuel tanks are returned to the underground tanks through the use of a special nozzle
(EPA, 1995). Stage I controls have been implemented in some areas, both attainment and
nonattainment. Stage n controls are currently not widely implemented, but are required in some
ozone nonattainment areas as defined by the 1990 Clean Air Act (CAA) (EPA, 1991).
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
The following activities of the gasoline distribution industry are generally area sources of air
pollution: (1) gasoline trucks in transit; (2) fuel delivery to outlets (Stage I); (3) vehicle refueling
(Stage n); and (4) storage tank breathing. The emissions estimation methodologies for the
subcategories of gasoline distribution identified in Section 2 have a common, simple form:
Emissions = Emission Factor x Activity Level (11.3-1)
The methodologies for adjusting the emission factors and activity levels vary somewhat among
the subcategories. Accordingly, methodologies for developing emission factors and activity
levels are presented separately for each subcategory.
3.2 AVAILABLE METHODOLOGIES
Selection of the appropriate estimation method depends on the relative significance of emissions
from this source in the inventory area and the data quality objectives (DQOs) of the inventory
plan. Refer to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for
discussions of inventory categories and DQOs.
Methods for estimating emissions from the gasoline marketing system generally involve
employing an emission factor (provided by EPA or generated with EPA's MOBILE model)
relating emissions to the volume of gasoline distributed. Gasoline distribution within the study
area may be determined by area-specific tax records or survey data. Unfortunately, gasoline sales
tax data are not always available at the county or city level, and performing a valid survey may
not be feasible due to resource limitations. Alternately, state-level gasoline sales may be
allocated to the study area based on economic data (dollars of total sales, available in U.S.
Bureau of the Census publications).
Emission factors for gasoline trucks in transit, fuel delivery to outlets, and storage tank breathing
are all provided by EPA. No methodologies have been identified to replace the use of these
emission factors. Emission factors for vehicle refueling should be developed through the use of
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EPA's MOBILE model. This software uses local data (e.g., temperature, fuel volatility) to
generate a custom VOC emission factor.
In selecting preferred methodologies identified for gasoline marketing subcategories, preference
has been given to methodologies that maximize use of survey data or other data collected or
reported at the county or city level.
3.1.1 EMISSION FACTORS
Gasoline Trucks in Transit
EPA has published emission factors for gasoline tank trucks in transit. The emission factors are
included in Table 11.3-1.
TABLE 11.3-1
VOC EMISSION FACTORS FOR GASOLINE MARKETING ACTIVITIES*
Emission Source
Gasoline Tank Trucks in Transit
Vapor-filled Tank Trucks'3
Gas-filled Tank Trucks0
Filling Underground Tank (Stage I)
Submerged Filling
Splash Filling
Balanced Submerged Filling
Underground Tank Breathing and Emptyingd
mg/Liter
Throughput
6.5
0.5
880
1,380
40
120
lb/1000 gal
Throughput
0.055
0.005
7.3
11.5
0.3
1.0
a Source: AP-42 Tables 5.2-5, 5.2-7.
b Midpoint of typical range provided in AP-42. Under extreme conditions, the upper end of
the range is 0.37 lb/1000 gal (44.0 mg/L).
c Midpoint of typical range provided in AP-42. Under extreme conditions, the upper end of
the range is 0.08 lb/1000 gal (9.0 mg/L).
d Includes any vapor less between tank and gas pump.
11.3-2
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Emission factors can be supplemented by using the HAP speciation profiles provided in the NTI
area source category, Gasoline Distribution Stage n. The NTI documentation provides profiles
that can be applied to the VOC estimates for baseline, reformulated, and winter-oxygenated
gasolines. The reformulated and winter-oxygenated gasolines are then subdivided depending on
the additive contents, which include methyl tertiary butyl ether (MTBE) or ethanol. Table 11.3-2
displays the HAP speciation profiles that should be applied to the VOC emissions.
TABLE 11.3-2
HAP PERCENT OF VOC EMISSIONS
HAP
2,2,4-Trimethylpentane
Benzene
Ethylbenzene
Hexane
MTBE
POM as 16-PAH
Toluene
Xylene
Gasoline Type
Baseline
0.8
0.9
0.1
1.6
0
0.05
1.3
0.5
Reformulated
w/ MTBE
0.7
0.4
0.1
1.4
8.7
0.05
1.1
0.4
w/ Ethanol
0.7
0.4
0.1
1.4
0
0.05
1.1
0.4
Winter-Oxygenated
w/ MTBE
0.7
0.7
0.1
1.4
11.9
0.05
1.1
0.4
w/ Ethanol
0.7
0.7
0.1
1.4
0
0.05
1.1
0.4
Source: EPA, 1999
Fuel Delivery to Outlets
EPA has published emission factors for filling underground storage tanks (Stage I). The
emission factors are included in Table 11.3-1.
Vehicle Refueling
EPA recommends that the MOBILE model be used to generate refueling (Stage II) emission
factors for highway vehicle emission inventories (EPA, 1992b). The model, designed to support
the evaluation of air pollution from gasoline- and diesel-fueled vehicles, generates emission
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factors for tailpipe emissions and refueling activities. A detailed discussion of using this model
is available from EPA (EPA, 1994).
The MOBILE model allows the user to select whether refueling emission factors are presented in
grams per gallon (g/gal) of dispensed fuel or in grams per mile (g/mi). The preferred approach is
to use the g/gal refueling emission factor that reflects any applicable Stage II controls, then
multiply the emission factor by total gasoline sales (TGD). Using the g/gal emission factor will
capture refueling emissions from gasoline purchased in the study area but consumed outside the
study area. Conversely, the g/mi emission factor will assign to the study area emissions for
vehicles refueled outside the study area but driven within the study area. It should be noted that
MOBILE makes use of improved predictive equations to calculate refueling emission factors,
including sensitivity to temperature and Reid vapor pressure (RVP), and these have not yet been
incorporated into published AP-42 factors for refueling. Additionally, the user may provide
information on local Stage II emission controls to develop an emission factor for controlled
emissions.
Refueling emissions have two mechanisms of introducing emissions to the environment: (1)
vapor displacement from the vehicle fuel tank during refilling; and (2) gasoline spillage during
refueling. The MOBILE user may request either a single emission factor that combines the two
mechanisms or separate emission factors for displacement and spillage. Because both
mechanisms should be taken into account when estimating refueling emissions, the preferred
approach is to request the combined emission factor.
Storage Tank Breathing
EPA has published emission factors for storage tank breathing. The emission factors are
included in Table 11.3-1.
3.1.2 ACTIVITY LEVELS
All of the preferred methodologies discussed in this document use total gasoline distribution as
activity levels. The most useful source of existing data for estimating total gasoline distributed
(TGD) in the inventory area is any existing collection of highway fuel sales data. The preferred
approach to estimating TGD is to use these data. If available, these data should be collected,
assessed, and processed to ensure that only highway vehicle gasoline dispensed in the area of
concern is included in the total to be used as TGD. According to a recent EPA study, only
10 states actually collect and publish this type of data: Alabama, Arizona, Florida, Hawaii,
Mississippi, Nevada, New Mexico, New York, Washington and, Wyoming. Most of the states
with significant nonattainment problems are absent from this list. In addition, the reliability of
these statistics as measures of gasoline distributed at the county level is unknown; significant
errors in allocation may occur if statistics are based on locations of distributors and not all of this
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fuel supply remains in the area of concern, or if substantial quantities of fuel come from
distributors outside the area.
Where adequate data are not routinely collected, the only other alternatives for developing
county-level data are (1) to collect sales tax data from the state taxing agency, if these data are
available at sufficient disaggregation, or (2) to generate original data by collecting gasoline sales
data from fuel distributors and retailers. State taxing agencies typically cannot provide the level
of geographic detail necessary for inventory application; fuel taxes are usually collected from
distributors rather than retailers, and these data are often considered proprietary information.
Any tax-based estimates should be cross-checked with data from associations of service station
owners, distributors, and other local sources. The large number of retailers and ongoing changes
in retailer locations and ownership can make an original survey costly and difficult, although a
small area might find this a reasonable approach. Scaling survey results to account for outlets
not surveyed and/or nonresponders is also problematic; however, this could be accomplished
using employment data for SIC Code 5541 or data on the total numbers of outlets in the area.
One advantage of this approach is that information on the amount of gasoline distributed under
different types of emission control scenarios can be directly estimated.
Another alternative for estimating gasoline consumption is to use data from various national
publications. The Federal Highway Administration (FHWA) annually publishes Highway
Statistics, which contains gasoline consumption data for each state.1 Countywide estimates can
be made by apportioning these statewide totals by the percentage of state gasoline station sales
occurring within each county. Countywide service station gasoline sales data (dollars of sales,
not gasoline volume) are available from the Bureau of the Census's Census of Retail Trade2
(Note: Data in the Census of Retail Trade are usually too old to use directly in estimating
countywide sales; however, they are useful in allocating other data to the county level.) Other
apportioning variables, such as registered vehicles or vehicle miles traveled (VMT), can be used
if the local agency feels that their use results in more accurate distributions of state totals to the
county level. Even if the agency uses local sales data in the area source inventory, this approach
should be used as a cross-check of the local consumption estimates. One distinct advantage of
using data in Highway Statistics is that sales are tabulated by month which facilitates a seasonal
adjustment of the gasoline station emission totals.
1 Highway Statistics. U.S. Department of Transportation. Federal Highway
Administration, Washington, D.C. (Annual publication. Check USDOT/FHWA Web site
for latest version, http://www.fhwa.dot.gov).
2 Census of Retail Trade: Geographic Area Series. Bureau of the Census, U.S. Department
of Commerce, Washington, D.C. (Available on hard copy by contracting the Census
Bureau at 1-800-541-8345 or see the Census Bureau Web site, http://www.census.gov.
Alternatively, check http://sasquatch.kerr.orst.edu/econ-stateis.html.
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Another method of estimating gasoline sales is to use VMT data available from the ongoing
transportation planning process. This alternative is not generally recommended for several
reasons. First, it requires local information on both the percentage of VMT attributable to diesel
versus gasoline fuel and the average miles-per-gallon fuel efficiency of the gasoline-powered
motor fleet. None of these data may be available locally, and using nationwide averages may
introduce errors in certain applications. Moreover, highway travel will not account for all
gasoline sold at various off-highway applications. For these reasons, fuel sales is the preferred
method for determining fuel use.
Note: Using state or local air pollution permit files for inventorying gasoline dispensing outlets
is not likely to be an effective alternative. Permit information is not usually collected because of
the large number of stations and because each station's emissions are much lower than traditional
point source cutoff levels. Registration systems are being attempted in some states where major
retail chains are required to compile and submit service station lists. Such a detailed approach is
not usually warranted when gasoline distribution data will yield adequate emissions estimates.
Gasoline Trucks in Transit
The activity level for estimating emissions from gasoline trucks in transit is fuel transported
through the study area. In order of preference, the available methods for estimating fuel
throughput include: (1) obtaining (if available) existing gasoline sales data for the study area;
and (2) apportioning state gasoline sales data to the study area level using surrogate allocation
variables such as gasoline sales, vehicle registration, or economic activity data.
Gasoline distributed in an inventory area may be transported once (from bulk terminals outside
the study area to retail outlets) or twice (distribution to gasoline bulk plants, then subsequent
distribution to retail outlets). Recent industry trends favor more direct delivery to outlets,
bypassing bulk plants.
The following equation can be used to develop an adjusted gasoline transportation activity factor
for trucks in transit to account for gasoline transported twice within the inventory region:
_. TGD + TGT
GTA = di T,-2\
TGD UA->A>
where:
GTA = Gasoline transportation adjustment factor
TGD = Total gasoline dispensed in the inventory region (1,000 gallons)
TGT = Amount of gasoline transported twice within the inventory region
(1,000 gallons)
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A default value of 1.25 for GTA can be used if the information needed to calculate GTA is not
available. This default value is based on an estimated overall historical national ratio of bulk
plant throughput to total gasoline consumption and should be used only as a last resort since it
will not reflect temporal or regional variations from this national historical average.
Depending on the location of nearby gasoline terminals and routes used to deliver product to
remote bulk plants or outlets, there may be some inventory areas with heavy tank truck traffic on
local interstates consisting of gasoline being transported through the area but not loaded or
unloaded locally. There are currently no adjustment factors for this specific type of activity.
However, it may be possible to obtain data on this type of traffic from weigh stations on
interstate highways and add this throughput to the estimate of TGD in the area to obtain an
upper-limit estimate for total emissions for trucks in transit including transport through the area
(assuming that the factors for full and empty trucks are appropriate in this case). Inventory
preparers may want to make a gross estimate of the contribution to overall emissions that these
trucks may make before investing significant resources in this effort. (Typical round-trip
emissions for each truck are probably less than 1 pound of VOCs.)
Total gasoline tank truck emissions (TTE) in the inventory region can be estimated with the
following equation:
„_ (TGD x LEF x GTA) + (TGD x UEF x GTA)
TTE = -^ '- i '- HI 3.3^
2000 ^i.^J
where:
TTE = Total gasoline emissions from tank trucks in transit (tons)
LEF = Loaded tank truck in-transit emission factor from Table 11.3-1 (pounds
per 1,000 gallons)
UEF = Unloaded tank truck in-transit emission factor from Table 11.3-1 (pounds
per 1,000 gallons)
Fuel Delivery to Outlets
In order to use the emission factors for fuel delivery to outlets included in Table 11.3-1, it may be
necessary to make estimates of the amounts of fuel delivered by each delivery technology
(submerged filling, splash filling, balanced submerged filling). The first step is to determine
what rules are in place for Stage I tank filling. If a rule requires a certain type of control or filling
method, then the inventory preparer need only determine a rule penetration factor. Otherwise,
estimates of or surrogates for the volumes of fuel delivered via each filling method are required.
Potential methodologies for making these estimates include:
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Method 1 - Obtain estimates of gasoline delivery volumes: Obtain data on throughput of area
gasoline outlets from state/local regulators or industry and trade groups (the national Petroleum
Marketing Association, located in Arlington, Virginia, or state/local associations of gasoline
dealers and repair shops). This is the preferred method.
Method 2 - Use estimated fractions of service stations using each filling method: Obtain the
number of gasoline outlets that use each of the three types of tank filling methods from state and
local regulators or industry and trade groups. Distribute gasoline delivery volumes according to
these results.
Method 3 - Survey of outlets by filling method: Perform a survey of all or a representative
sample of gasoline dispensing outlets in the inventory region to determine the type of tank filling
method. Distribute gasoline delivery volumes according to these results. A survey design must
ensure that the sample selected is representative. It is likely that smaller stations may use
different controls or filling methods than larger ones. A sample should be stratified to ensure
that all types of outlets are included. The survey needs to collect gasoline throughput data and
other data that may be used to scale survey results to study area totals. Potential surrogates may
be number of employees, number of pumps, or storage tank capacities.
The activity levels for each of the three fuel delivery technologies is then calculated as follows:
A; = Fi x TGD (11.3-4)
where:
A; = Adjusted activity rate for fill type I (1,000 gallons)
F; = Fraction of area total for fill type I (based on either throughput or number of
stations)
TGD = Total gasoline dispensed in the inventory region (1,000 gallons)
I = 1-3 representing the three filling methods
Vehicle Refueling
The activity factor for vehicle refueling can be either the total amount of gasoline distributed in
the area or vehicle miles of travel (VMT). The preferred approach is to use estimates of local
gasoline sales if these data are available.
• Obtain information on the amount of gasoline dispensed in the inventory region
(TGD) using the methods described previously in this section. Use the best
locally available estimate of TGD as the activity factor for vehicle refueling.
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• If no local sources of information are available for estimating TGD, the agency
may wish to use VMT as an alternative. Estimates of VMT should be obtained
from the local transportation or planning agency who is responsible for preparing
the highway vehicle emissions inventory. The disadvantage of using VMT is that
it is a measure of vehicle activity in the area not a measure of the fuel dispensed in
the inventory area. VMT produced by vehicles simply passing through the area,
that did not refuel in the inventory region would tend to overstate the vehicle
refueling activity level.
Storage Tank Breathing
The activity level for estimating emissions from storage tank breathing is total gallons delivered
(TGD) in the inventory area. The methodology for estimating TGD for vehicle refueling is also
recommended for this subcategory.
3.1.3 SPECIAL EMISSION CALCULATION ISSUES
Estimation of month-specific emissions from gasoline distribution can be based on activity
apportionment factors developed from monthly state fuel use statistics available in Highway
Statistics. Projections for fuel use can also be based on historic fuel use and vehicle miles
traveled data from Highway Statistics, historic records from the sources from which current year
area fuel usage was obtained, and/or area-specific VMT from Highway Performance Monitoring
System (HPMS) (from Federal Highway Administration, Washington, DC) or local
transportation agencies.
3.1.4 METHODOLOGY SUMMARIES
The methodologies proposed in this document are summarized in Table 11.3-3 below.
Preferred and alternate methodologies are presented for each of the subcategories.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements needed to calculate emission estimates for the gasoline distribution system
depend on the methodology used for data collection. Each methodology requires some measure
of activity (or surrogate for activity) and an emission factor. The data elements needed for each
emission estimation technique are presented in Table 11.3-4.
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TABLE 11.3-3
PREFERRED AND ALTERNATE METHODS FOR ESTIMATING EMISSIONS
FROM GASOLINE DISTRIBUTION SUBCATEGORIES
Sub-category
Gasoline
Trucks in
Transit
Fuel Delivery
to Outlets
Vehicle
Refuel-ing
Storage Tank
Breath-ing
Method
Preferred Method - Use
detail or survey data
Alternate Method 1 - Use
combination of default
and detailed data
Alternate Method 2 - Use
default GTA and
allocated fuel sales data
Preferred Method - Use
detail or survey data
Alternate Method 1 - Use
allocated fuel sales data,
survey filling data
Alternate Method 2 - Use
allocated fuel sales data,
local knowledge of filling
technology
Preferred Method - Use
MOBILE emission
factor and detail or
survey data
Alternate Method 1 - Use
MOBILE emission
factor, allocated fuel sales
Alternate Method 2 - Use
MOBILE emission
factor, vehicle miles
traveled (VMT) data
Preferred Method - Use
EPA emission factor and
detail or survey data
Alternate Method 1 - Use
EPA emission factor,
allocated fuel sales
Description
Emission Factors - from Table 3-1.
Activity Level - Obtain fuel sales from tax records or survey data.
Develop adjustment factor based on survey or highway-weigh
station data.
Emission Factor - from Table 3-1.
Activity Level - Same as preferred method, substituting default
GTA.
Emission Factor - from Table 3-1.
Activity Level - Same as preferred method, substituting default
GTA, allocate state fuel sales to study area based on gasoline
station sales.
Emission Factor - from Table 3-1.
Activity Level - Obtain fuel sales from tax records or survey data.
Use survey data to determine filling technologies.
Emission Factor - from Table 3-1.
Activity Level - Same as preferred method, using allocated fuel
sales estimates instead of actual data. Use survey data to determine
filling technologies' usage.
Emission Factor - from Table 3-1.
Activity Level - Same as preferred method, using allocated fuel
sales estimates instead of actual data. Use trade association or local
knowledge to determine filling technologies' usage.
Emission Factor - use MOBILE emission factor.
Activity Level - Obtain fuel sales from tax records or survey data.
Emission Factor - use MOBILE emission factor.
Activity Level - use allocated fuel sales estimates instead of actual
data.
Emission Factor - use MOBILE emission factor to get emission
factor in dimensions grams per mile traveled.
Activity Level - Get VMT data from highway planners.
Emission Factor - see Table 3-1.
Activity Level - Obtain fuel sales from tax records or survey data.
Emission Factor - see Table 3-1.
Activity Level - Use allocated fuel sales estimates instead of actual
data.
11.3-10
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TABLE 11.3-4
DATA ELEMENTS NEEDED FOR EACH METHOD
Subcategory
Gasoline Trucks in Transit
Fuel Delivery to Outlets
Vehicle Refueling
Tank Breathing
Data Element
County-level fuel sales
tax/survey data
Highway/weigh-station
data
State fuel sales
Gasoline station sales
County-level fuel sales
tax/survey data
Filling technology survey
data
Filling technology
summary from local/state
regulators or trade groups
State fuel sales
Gasoline station sales
MOBILE model inputs
(see Reference 8)
County-level fuel sales
tax/survey data
State fuel sales
Gasoline station sales
VMT data
County-level fuel sales
Tax/survey data
State fuel sales
Gasoline station sales
Preferred
Method
X
X
X
X
X
X
X
Alternate
Method 1
X
X
X
X
X
X
X
X
X
Alternate
Method 2
X
X
X
X
X
X
X
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3.3.2 ADJUSTMENTS TO EMISSIONS ESTIMATES
Adjustments applied to annual emissions estimates include point source corrections, applications
of controls, spatial allocation, and temporal resolution. The type of adjustment is dependent on
the type of inventory required. The data needs for point source emission estimate adjustments
are dependent in part on the methodology used. Data needs for the adjustments listed below are
as follows:
• Point source corrections
Application of controls
Spatial allocation
Temporal resolution
3.3.3 POINT SOURCE CORRECTIONS
point source emissions or point source employment
for inventory area for the specific SIC
control efficiency, rule effectiveness, rule
penetration
employment, population, facility location, zoning or
business districts location
seasonal throughput, operating days per week,
operating hours per day
If the preferred method is used to estimate area source emissions from this category, the point
source correction is performed as part of the method itself. If Alternate Method 1 is used, the
point source corrections can be performed by one of the following: (1) subtract point source
emissions from calculated total emissions, or (2) subtract point source employment in the
specific SIC from total employment in that SIC and calculate area source emissions using the
remaining employment in the SIC. If Alternate Method 2 is used, the point source corrections
are performed by subtracting point source emissions from calculated total emissions.
3.3.4 APPLICATION OF CONTROLS
Section 3.8 of Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Volume I, (EPA, 1991) provides guidance for determining and applying
rule effectiveness (RE) for a source category. In addition, the EPA document Procedures for
Estimating and Applying Rule Effectiveness in Post-198 7 Base Year Emission Inventories for
Ozone and Carbon Monoxide State Implementation Plans (EPA, 1989) provides more detailed
information on RE.
11.3-12
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Controlled area source emissions may be calculated with either of the following equations:
CAEA = (EFA)(Q)[1 - (CE)(RP)(RE)] (11.3.5)
or
CAEA = (UAEA)[1 - (CE)(RP)(RE)]
where: CAEA = controlled area source emissions of pollutant A
EFA = emission factor for pollutant A
Q = activity factor for category
CE = control efficiency/100
RP = rule penetration/100
RE = rule effectiveness/100
UAEA = uncontrolled area source emissions of pollutant A
3.3.5 SPATIAL ALLOCATION
If the emissions estimates are developed using a per employee factor, the spatial allocation of
emissions can be performed according to facility location (if known) as with the point source
inventory, or with local employment data. The agency should be aware that since location of
gasoline marketing does not necessarily mirror location of population within a county, using
population to spatially allocate emissions might be misleading. The inventorying agency will
need to evaluate options for allocating county emissions, such as zoning information, actual
location data identified from surveys, industry publications, etc.
3.3.6 TEMPORAL RESOLUTION
Seasonal Apportioning
Because emissions from these subcategories are generally directly proportional to fuel sales and
fuel sales have well-documented seasonal trends, annual gasoline distribution emissions should
be apportioned monthly based on fuel sales data. Fuel sales tax revenues are usually available
from state departments of revenue and should be used to allocate emissions.
Daily/Hourly Resolution
As with all issues, the inventory agency should use local data if available. If no data are
available, inventory agencies may use the Table 11.3-5 as default values:
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TABLE 11.3-5
DAILY AND HOURLY ALLOCATION OF
GASOLINE DISTRIBUTION SYSTEM EMISSIONS
Subcategory
Trucks in Transit
Fuel Delivery to Outlets
Vehicle Refueling
Storage Tank Breathing
Daily Allocation
(days per week)
6
6
7
7
Hourly Allocation
(hours per day)
24
24
24
24
3.4 PROJECTING EMISSIONS
The type of surrogate used to project emissions is dependent on the methodology used to develop
the initial emissions estimate. In "growing" the emissions estimate, the inventorying agency
should use the same activity parameter as was used to develop the initial estimate. For example,
if a per gallon factor was used to develop the initial estimate, growth in gasoline sales should be
used to develop the projected emissions estimate.
The EIIP Projections Committee has developed a series of guidance documents containing
information on options for forecasting future emissions. You can refer to these documents at
http://www.epa.gov/ttn/chief/eiip/project.htm.
11.3-14
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
The following procedures should be used for estimating emissions from the gasoline distribution
subcategories. See Section 3 for additional guidance for the application of these methods.
4.1 GASOLINE TRUCKS IN TRANSIT
(1) Consult state gasoline sales tax records or data collected through a survey of fuel
distributors and retailers to determine the gasoline consumption in the study area.
(2) Obtain highway weigh-station data to estimate the amount of fuel transported through the
area. Calculate GTA, the factor accounting for twice-transported fuel:
_. TGD + TGT
GTA = (114-1}
TGD ^ ;
where:
GTA = Gasoline transportation adjustment factor
TGD = Total gasoline dispensed in the inventory region (1,000 gallons)
TGT = Amount of gasoline transported twice within the inventory region
(1,000 gallons)
(3) Calculate emissions:
(TGD x LEF x GTA) + (TGD x UEF x GTA)
TTE = ^ '- ^ '- t\ i 4_2)
2000 \il •-**•)
where:
TTE = Total gasoline emissions from tank trucks in transit (tons)
LEF = Loaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
UEF = Unloaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
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4.2 FUEL DELIVERY TO OUTLETS
(1) Consult gasoline sales tax records or survey data to determine the gasoline consumption
in the study area.
(2) Use survey data to determine penetration of each filling technology.
(3) Multiply total fuel sales in the study area by the fraction of stations using each filling
technology to estimate the fuel dispensed by each technology.
(4) Use technology-specific emission factors to estimate emissions from submerged filling,
splash filling, and vapor-balanced submerged filling activities.
(5) Sum emissions from each technology to estimate total emissions.
4.3 VEHICLE REFUELING
(1) Consult gasoline sales tax records or survey data to determine the total amount of
gasoline dispensed in the study area.
(2) From the local control agency or survey data, determine the level of local Stage II
refueling controls.
(3) Run the MOBILE model to determine the emission rate on a mass per volume throughput
(grams per gallon, converted to pounds per gallon) basis. (In MOBILESb, this is
accomplished by setting HCFLAG = 3). Based on the results of step 2, determine
whether Stage II refueling controls need to be considered. If local stage II controls are in
place, enter the appropriate data in the MOBILE one-time data section per MOBILE
model requirements (EPA, 1994). (In MOBILESb, set RLFLAG = 1 if there are no local
Stage II controls, or set RLFLAG = 2 to calculate an emission factor that includes local
Stage n controls. Note that MOBILESb will factor in the effects of the national on-board
vapor recovery system requirements for either value of RLFLAG.) MOBILE6 is due for
release in 2000. The reader should check the OTAQ Website for updated information on
MOBILE6 (www.epa.gov/oms/m6.htm).
(4) Multiply the emission factor (Ib/gallon of fuel) times the estimated gasoline volume
(gallons of gasoline) to estimate emissions from vehicle refueling.
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4.4 STORAGE TANK BREATHING
(1) Consult gasoline sales tax records or survey data to determine the gasoline consumption
in the study area.
(2) Multiply gasoline sales (gallons) times the emission factor to estimate emissions from
storage tank breathing.
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
Frequently, local county-level sales tax data for gasoline sales or other local data needed to adjust
these values are not available. Also, the collection of local gasoline sales data through surveys of
distributors and retailers may be impractical or too expensive. Under these circumstances, use of
one of the following alternative methods is appropriate.
5.1 ALTERNATIVE METHOD 1
5.1.1 GASOLINE TRUCKS IN TRANSIT
This method is the same as the preferred method, except that a default factor is used to estimate
the adjustment factor for gasoline transported twice in the inventory area.
(1) Consult gasoline sales tax records or survey data to determine the gasoline consumption
in the study area.
(2) Use 1.25, a national default rate, as GTA (gasoline transportation adjustment factor).
(3) Calculate emissions:
(TGD x LEF x GTA) + (TGD x UEF x GTA)
TTE = ^ '- i '- (ii 5_n
2000 l ;
where:
TTE = Total gasoline emissions from tank trucks in transit (tons)
LEF = Loaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
UEF = Unloaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
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5.1.2 FUEL DELIVERY TO OUTLETS
This method apportions state-level data to counties instead of using local sales tax or survey data.
(1) Assume that gasoline consumption is proportional to gasoline station sales, reported in
the Bureau of the Census's Census of Retail Trade. Allocate state gasoline consumption
data from Highway Statistics to the study area according to the dollar sales figures
reported in the Census of Retail Trade.
(2) Use survey data to determine penetration of each filling technology.
(3) Multiply total fuel sales in the study area by the fraction of stations using each filling
technology to estimate the fuel dispensed by each technology.
(4) Use technology-specific emission factors to estimate emissions from submerged filling,
splash filling, and vapor-balanced submerged filling activities.
(5) Sum emissions from each technology to estimate total emissions.
5.1.3 VEHICLE REFUELING
(1) Allocate state gasoline consumption from Highway Statistics to the study area. Assume
that gasoline consumption is proportional to gasoline station sales, reported in the Bureau
of the Census's Census of Retail Trade.
(2) From the local control agency or survey data, determine the level of local Stage II
refueling controls.
(3) Run the MOBILE model to determine the emission rate on a mass per volume throughput
(grams per gallon, converted to pounds per gallon) basis. (In MOBILESb, this is
accomplished by setting HCFLAG = 3). Based on the results of Step 2, determine
whether Stage II refueling controls need to be considered. If local Stage n controls are in
place, enter the appropriate data in the MOBILE one-time data section per MOBILE
model requirements (EPA, 1994). (In MOBILESb, set RLFLAG = 1 if there are no local
Stage II controls, or set RLFLAG = 2 to calculate an emission factor that includes local
Stage n controls. Note that MOBILESb will factor in the effects of the national on-board
vapor recovery system requirements for either value of RLFLAG.) MOBILE6 is due for
release in 2000. The reader should check the OTAQ Website for updated information on
MOBILE6 (www.epa.gov/oms/m6.htm).
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(4) Multiply the emission factor (Ib/gallon of fuel) times the estimated gasoline volume
(gallons of gasoline) to estimate emissions from vehicle refueling.
5.1.4 STORAGE TANK BREATHING
(1) Allocate state gasoline consumption from Highway Statistics to the study area. Assume
that gasoline consumption is proportional to gasoline station sales, reported in the Bureau
of the Census's Census of Retail Trade.
(2) Multiply gasoline sales (gallons) times the Table 11.3-1 emission factor to estimate
emissions from storage tank breathing.
5.2 ALTERNATIVE METHOD 2
5.2.1 GASOLINE TRUCKS IN TRANSIT
(1) Allocate state gasoline consumption from Highway Statistics to the study area. Assume
that gasoline consumption is proportional to gasoline station sales, reported in the Bureau
of the Census's Census of Retail Trade.
(2) Use 1.25, a national default rate, as GTA.
(3) Calculate emissions:
(TGD x LEF x GTA) + (TGD x UEF x GTA)
= s
„_
TTE
2000
where:
TTE = Total gasoline emissions from tank trucks in transit (tons)
LEF = Loaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
UEF = Unloaded tank truck in-transit emission factor from Table 11.3-1
(pounds per 1,000 gallons)
5.2.2 FUEL DELIVERY TO OUTLETS
(1) Allocate state gasoline consumption from Highway Statistics to the study area. Assume
that gasoline consumption is proportional to gasoline station sales, reported in the Bureau
of the Census's Census of Retail Trade.
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(2) Use advice of local trade groups, industry representatives, or regulators to determine
penetration of each filling technology.
(3) Multiply total fuel sales in the study area by the fraction of stations using each filling
technology to estimate the fuel dispensed by each technology.
(4) Use technology-specific emission factors to estimate emissions from submerged filling,
splash filling, and vapor-balanced submerged filling activities.
(5) Sum emissions from each technology to estimate total emissions.
5.2.3 VEHICLE REFUELING
(1) Consult state or local transportation planners to obtain VMT data for the study area.
(2) From the local control agency or survey data, determine the level of local Stage II
refueling controls.
(3) Run the MOBILE model to determine the emission rate on a mass per vehicle-mile
(grams per vehicle mile traveled, converted to pounds per mile) basis. (In MOBILESb,
this is accomplished by setting HCFLAG = 2). Based on the results of Step 2, determine
whether Stage II refueling controls need to be considered. If local Stage n controls are in
place, enter the appropriate data in the MOBILE one-time data section per MOBILE
model requirements (EPA, 1994). (In MOBILESb, set RLFLAG = 1 if there are no local
Stage II controls, or set RLFLAG = 2 to calculate an emission factor that includes local
Stage n controls. Note that MOBILESb will factor in the effects of the national on-board
vapor recovery system requirements for either value of RLFLAG.)MOBILE6 is due for
release in 2000. The reader should check the OTAQ Website for updated information on
MOBILE6 (www.epa.gov/oms/m6.htm).
(4) Multiply the emission factor times the VMT estimates to estimate emissions from vehicle
refueling.
5.2.4 STORAGE TANK BREATHING
Only one alternate methodology is provided for this category.
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QUALITY ASSURANCE/
QUALITY CONTROL
Data collection and handling for the gasoline marketing source category should be planned and
documented in the Quality Assurance Plan. When using survey methods, the survey planning
and data handling should also be documented. Refer to the discussion of survey planning and
survey QA/QC in Chapter 1, Introduction to Area Source Emission Inventory Development, of
this volume, and the QA volume (VI) of the Emission Inventory Improvement Program (EIIP)
series. Potential pitfalls to avoid when developing emission estimates by using a survey for
this category are data gaps due to survey nonreturns or unidentified operations, unanswered or
misunderstood survey questions, inappropriate assumptions used to compensate for missing
information or scaling up the survey sample, and errors in compiling the returned survey
information. Potential errors that are common to many area source methods are calculation
errors, which can include unit conversion errors and data transfer errors.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
In this chapter, four subcategories of emission sources are discussed. Emission estimation for
all of the subcategories requires the amount of gasoline sold in the inventory area as the
activity level. The preferred methods call for detailed gasoline sales data that may not be
available at the county or study area level. While using the most accurate fuel distribution data
available is important, if the data are not immediately available, conducting a survey to
determine actual gasoline distribution data is difficult, expensive, and time consuming.
Allocating fuel distribution to the county level using gasoline station sales is estimated to
require from 20 to 30 hours of technical effort, while performing a survey would probably take
several months and possibly 1,000 to 2,000 hours of technical effort.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be
found in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following
discussion uses the DARS rating system as a way to compare the estimation approaches
presented in this chapter and analyze their strengths and weaknesses.
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The DARS scores for methods for tank trucks in transit are summarized in Tables 11.6-1
through 11.6-3; for fuel delivery to outlets, in Tables 11.6-4 through 11.6-6; for vehicle
refueling, in Tables 11.6-7 through 11.6-9; and for storage tank breathing, in Tables 11.6-10
and 11.6-11. A range of scores is provided for activity attributes when the recommended
method for activity data collection uses either local tax data or survey results scaled to the
inventory area. The higher scores are assigned to the local tax data because local tax data are
the most direct measure of local data for the inventory period. Survey data require a scaling
step, which introduces potential over- or underestimation. All scores assume that satisfactory
QA/QC measures are performed and no significant deviations from good inventory practice
have been made. If these assumptions are not met, new DARS scores should be developed
according to the guidance provided in the QA volume.
TABLE 11.6-1
PREFERRED METHOD DARS SCORES: TANK TRUCKS IN TRANSIT;
LOCAL GASOLINE SALES, ADJUSTMENT FACTOR
FROM HIGHWAY WEIGH-STATION DATA
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.6
0.7
0.5
0.63
Activity
0.6-0.9
0.4-0.5
0.7-1
0.7-0.8
0.60 - 0.80
Emissions
0.42 - 0.63
0.24 - 0.30
0.49 - 0.70
0.35 - 0.40
0.37-0.51
11.6-2
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TABLE 11.6-2
ALTERNATIVE METHOD 1 DARS SCORES: TANK TRUCKS IN TRANSIT;
LOCAL GASOLINE SALES, DEFAULT ADJUSTMENT FACTOR
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.6
0.7
0.5
0.63
Activity
0.6 - 0.9
0.7-0.9
0.5-0.8
0.5-0.6
0.59 - 0.79
Emissions
0.42 - 0.63
0.42 - 0.54
0.37-0.53
0.26-0.30
0.37-0.50
TABLE 11.6-3
ALTERNATIVE METHOD 2 DARS SCORES: TANK TRUCKS IN TRANSIT;
SCALED STATE-LEVEL GASOLINE SALES, DEFAULT ADJUSTMENT FACTOR
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.6
0.7
0.5
0.63
Activity
0.6
0.7
0.5
0.5
0.59
Emissions
0.42
0.42
0.37
0.26
0.37
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TABLE 11.6-4
PREFERRED METHOD DARS SCORES: FUEL DELIVERY TO OUTLETS;
LOCAL GASOLINE SALES, FILLING METHOD FROM SURVEY
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.7
0.7
0.5
0.65
Activity
0.4-0.5
0.4-0.5
0.7-1
0.7-0.8
0.54 - 0.70
Emissions
0.29 - 0.38
0.24 - 0.32
0.49 - 0.70
0.35 - 0.40
0.34-0.45
TABLE 11.6-5
ALTERNATIVE METHOD 1 DARS SCORES: FUEL DELIVERY TO OUTLETS;
SCALED STATE-LEVEL GASOLINE SALES, FILLING METHOD FROM SURVEY
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.7
0.7
0.5
0.65
Activity
0.4
0.4
0.6
0.7
0.52
Emissions
0.29
0.24
0.42
0.35
0.33
11.6-4
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CHAPTER 11 - GASOLINE MARKETING
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TABLE 11.6-6
ALTERNATIVE METHOD 2 DARS SCORES: FUEL DELIVERY TO OUTLETS;
SCALED STATE-LEVEL GASOLINE SALES, FILLING METHOD FROM TRADE GROUPS
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.7
0.7
0.5
0.65
Activity
0.4
0.4
0.6
0.7
0.54
Emissions
0.29
0.29
0.42
0.35
0.34
TABLE 11.6-7
PREFERRED METHOD DARS SCORES: VEHICLE REFUELING;
LOCAL GASOLINE SALES, FILLING METHOD FROM REGULATORS
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.8
0.8
1
0.9
0.88
Activity
0.4-0.7
0.6-0.8
0.7 - 1
0.7-0.8
0.60 - 0.83
Emissions
0.32 - 0.56
0.48 - 0.64
0.70- 1.00
0.63 - 0.72
0.53-0.73
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TABLE 11.6-8
ALTERNATIVE METHOD 1 DARS SCORES: VEHICLE REFUELING;
SCALED STATE-LEVEL GASOLINE SALES, FILLING METHOD FROM SURVEY
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.8
1
0.9
0.85
Activity
0.4
0.6
0.6
0.7
0.58
Emissions
0.28
0.48
0.60
0.63
0.50
TABLE 11.6-9
ALTERNATIVE METHOD 2 DARS SCORES: VEHICLE REFUELING;
GASOLINE USE FROM VMT, FILLING METHOD FROM SURVEY
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.8
1
0.9
0.85
Activity
0.4
0.4
0.7
0.7
0.55
Emissions
0.28
0.32
0.70
0.63
0.48
11.6-6
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CHAPTER 11 - GASOLINE MARKETING
(STAGE I AND STAGE II)
TABLE 11.6-10
PREFERRED METHOD DARS SCORES: STORAGE TANK BREATHING;
LOCAL GASOLINE SALES
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.7
0.7
0.5
0.65
Activity
0.6-0.9
0.7-0.9
0.7-1
0.7-0.8
0.68 - 0.90
Emissions
0.42 - 0.63
0.49 - 0.63
0.49 - 0.70
0.35 - 0.40
0.44 - 0.59
TABLE 11.6-11
ALTERNATIVE METHOD 1 DARS SCORES: STORAGE TANK BREATHING;
SCALED STATE-LEVEL GASOLINE SALES
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.7
0.7
0.7
0.5
0.65
Activity
0.6
0.7
0.6
0.7
0.65
Emissions
0.42
0.49
0.42
0.35
0.42
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CHAPTER 11 - GASOLINE MARKETING 1/31/01
(STAGE I AND STAGE II)
All of the emission calculation methods for tank trucks in transit, fuel delivery to outlets, and
storage tank breathing use emission factors from AP-42. Important points to consider when
scoring the emission factor component of these methods are that the factors are based on
studies published in 1982 and that local temperature variations and gasoline Reid vapor
pressure (RVP) are not factored into the emission calculation. The age of the emission data
means that any changes in gasoline formulation and improvements in vapor control technology
since 1982 will not be reflected in the emission factors. DARS scoring for all of the AP-42
emission factors are the same except for the tank trucks in-transit subcategory. The scores for
emission factor source specificity for tank trucks in transit are lower than for other
subcategories because the factors provided in this chapter are averages of ranges provided in
AP-42.
The emission factor recommended for the vehicle refueling subcategory was developed using
the MOBILE model, and is a factor that expresses refueling emissions as a function of fuel
RVP, temperature of dispensed fuel, and the difference in the temperature between the
dispensed fuel and the residual tank fuel. The effects of emission controls may also be
included in this factor. These more locally specific and up-to-date emission factors are scored
higher than the AP-42 factors.
The most significant difference between the preferred and the first and second alternative
methods for this source category is how the activity-level data are collected. The preferred
methods for activity data collection use either local gasoline sales data collected by a state or
local tax authority, or survey data obtained from gasoline retailers in the area. Using local
gasoline sales tax data results in the highest DARS scores for activity attributes. The other
preferred method for collecting activity data, a survey of gasoline retailers, will require a
scaling step. That scaling step could introduce the same level of variability to the estimate that
is introduced in Alternative Method 2, in which state-level gasoline sales are scaled down to
the inventory area. DARS scores assigned to the survey approach and the scaled state-level
data approach reflect this similarity.
A component of the DARS scoring for gasoline trucks in transit, fuel delivery to outlets, and
vehicle refueling is the apportioning of the activity. For trucks in transit, the amount of
gasoline sold in the area must be adjusted up to account for gasoline that is transported twice
within the inventory area and gasoline that is transported through, but not delivered in, the
area. The preferred approach for this adjustment, using weigh-station data, will not capture all
of the activity. Activity scores for the preferred method are reduced because of this adjustment
approach. The alternative approach is a national default factor, which reduces the spatial
congruity score because it will not reflect variability at the local level. The activity temporal
congruity score for tank trucks in transit is also lowered since the adjustment factor is based on
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a 1978 report on gasoline marketing (EPA, 1991) and does not reflect any recent changes in
transport practices. Adjustments for fuel delivery to outlets and vehicle refueling activities
must be made to define uncontrolled or controlled portions for the emission estimate. In each
case, the apportioning procedure reduces the rating of activity measurement and source
specificity from what they might have been if the activity level had been more directly
measured and assumptions about the application of controls were more specific to gasoline
sales. These adjustments may result in an over- or underestimation of emissions if the
assumptions are not valid in the inventory area.
6.1.2 SOURCES OF UNCERTAINTY
Another way to assess the emission estimates is to examine the associated uncertainty. For
activity estimates derived from survey data, the uncertainty can be quantified (see Chapter 4 of
Volume VI of the EIIP series). Statistics needed to quantify the uncertainty for other methods
of activity-level data collection are incomplete.
Sources of uncertainty in estimating emissions from gasoline marketing include the difficulty of
collecting information for adjustment and apportioning factors, and the use of assumptions
when using that information. Of particular concern is the assumption that activity data for fuel
delivery to outlets can be apportioned to different types of controls by a count of gasoline
stations with no consideration of the differences in throughput that may exist between a larger
and possibly controlled station and a smaller uncontrolled station.
The emission factors provided in AP-42 also carry a degree of uncertainty in that any single
emission factor for gasoline marketing processes will not necessarily reflect the local gasoline
formulation or temperatures, or the equipment and handling practices in the area for the
inventory time period. The emission factors calculated by the MOBILE model should reduce
the uncertainty for the vehicle refueling subcategory emission estimates.
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from gasoline marketing.
A complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 11.7-1 lists the applicable SCCs for gasoline
marketing.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use in
regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data elements
necessary to complete the data set for use in regional or national air quality and human exposure
modeling. The inventory preparer should review the area source portion of the acceptable file
format(s) to understand the necessary data elements. The EPA describes its use and processing
of the data for purposes of completing the national inventory, in its Data Incorporation Plan, also
located at http://www.epa.gov/ttn/chief/net/.
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TABLE 11.7-1
AREA AND MOBILE SOURCE CATEGORY CODES
FOR GASOLINE MARKETING
Process Description
Petroleum Product Transit: Truck - Gasoline
Petroleum Product: Underground Tank Filling-Submerged
Storage - Gasoline Service Stations: Underground Tank Filling-Splash
Storage - Gasoline Service Stations: Underground Tank Filling-Balanced Submerged
Storage - Gasoline Service Stations: Vehicle Fueling-Uncontrolled Displacement Loss
Storage - Gasoline Service Stations: Vehicle Fueling-Controlled Displacement Loss
Storage - Gasoline Service Stations: Vehicle Fueling-Spillage
Storage - Gasoline Service Stations: Underground Tank-Breathing and Emptying
Storage - Gasoline Service Stations: Total All Processes
Source Category
Codes
25-01-030-120
25-01-060-051
25-01-060-052
25-01-060-053
25-01-060-101
25-01-060-102
25-01-060-103
25-01-060-201
25-01-060-000
11.7-2
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8
REFERENCES
EPA, 2000. AIRS Area and Mobile Source Category Codes. U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards (OAQPS), Research Triangle Park, North
Carolina, (www.epa.gov/ttn/chief/scccodes.html)
EPA 1999. SPECIATE database, version 3.1. U.S. Environmental Protection Agency, Office of
Air Quality Planning and Standards (OAQPS), Research Triangle Park, North Carolina.
(http://www.epa.gov/ttn/chief/software.html#speciate)
EPA. 1995. Compilation of Air Pollution Emission Factors - Volume 1: Stationary Point and
Area Sources. Fifth Edition, Supplements A-F, AP-42. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina, (www.epa.gov/ttn/chief/ap42.html)
EPA. 1994. User's Guide to MOBILEXX(Current version covers MOBILESb; however,
MOBILE6 is due for release by early 2001). U.S. Environmental Protection Agency, Office of
Mobile Sources, Ann Arbor, Michigan.
EPA, 1992a. AIRS Area and Mobile Source Category Codes. U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards (OAQPS), Research Triangle Park, North
Carolina.
EPA. 1992b. Procedures for Emission Inventory Preparation-Volume IV: Mobile Sources.
EPA-450/4-81-026d (Revised). U.S. Environmental Protection Agency, Office of Mobile
Sources, Ann Arbor, Michigan and Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina. 1992.
EPA. 1991. Procedures for the Preparation of Emissions Inventories for Carbon Monoxide and
Precursors of Ozone. Volume 1: General Guidance for Stationary Sources. EPA-450/4-91-016.
(NTIS PB92-112168). U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, North Carolina.
EPA. 1989. Procedures for Estimating and Applying Rule Effectiveness in Post-1987 Base Year
Emission Inventories for Ozone and Carbon Monoxide State Implementation Plans. U. S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
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VOLUME III: CHAPTER 12
MARINE VESSEL LOADING,
BALLASTING, AND TRANSIT
Revised Final
January 2001
•vALAPCp.,
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared for the Area Sources Committee of the Emission Inventory
Improvement Program and for Charles Mann of the Air Pollution Prevention and Control
Division, U.S. Environmental Protection Agency. Members of the Area Sources Committee
contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Other reviewers contributing to this document are:
Allen Ellett, BP Oil Company
Rob Ferry, TGB Partnership
Tahir Khan, Chemical Emission Management Services
EIIP Volume III ill
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IV EIIP Volume III
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CONTENTS
Section Page
1 Introduction 12.1-1
2 Source Category Description 12.2-1
2.1 Category Description 12.2-1
2.2 Process Description and Emission Sources 12.2-1
2.2.1 Loading Losses (Ships/Ocean Vessels and Barges) 12.2-2
2.2.2 Ballasting Losses (Ship/Ocean Vessels) 12.2-2
2.2.3 Transit Losses (Ship/Ocean Vessels and Barges) 12.2-2
2.3 Factors Influencing Emissions 12.2-3
2.4 Control Techniques 12.2-3
3 Overview of Available Methods 12.3-1
3.1 Emission Estimation Methodologies 12.3-1
3.1.1 Volatile Organic Compounds 12.3-1
3.1.2 Hazardous Air Pollutants 12.3-1
3.2 Data Needs 12.3-1
3.2.1 Data Elements 12.3-1
3.2.2 Point Source Corrections 12.3-3
3.2.3 Application of Controls 12.3-3
3.2.4 Spatial Allocation 12.3-4
3.2.5 Temporal Resolution 12.3-4
3.3 Projecting Emissions 12.3-4
4 Preferred Methods for Estimating Emissions 12.4-1
4.1 Preferred Method 12.4-1
4.1.1 Determination of Amount of Petroleum Transported to or from the
Inventory Region 12.4-1
4.1.2 Identification of Emission Points 12.4-2
4.1.3 Classification of Petroleum Products by Fuel Type 12.4-3
4.1.4 Estimation of Transit Emissions 12.4-6
4.1.5 Correction for Point Source Emissions 12.4-6
EIIP Volume III V
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CONTENTS (CONTINUED)
Section Page
4.1.6 Estimation of Emissions from Petroleum Vessels 12.4-9
5 Alternative Methods for Estimating Emissions 12.5-1
6 Quality Assurance/Quality Control 12.6-1
6.1 Emission Estimate Quality Indicators 12.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 12.6-1
6.1.2 Sources of Uncertainty 12.6-2
7 Data Coding Procedures 12.7-1
7.1 Necesssary Data Elements 12.7-1
8 References 12.8-1
VI EIIP Volume III
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TABLES
Page
12.4-1 Emission Points For Petroleum Vessel Traffic Classifications 12.4-4
12.4-2 Product Type Classifications For Common Petroleum Vessel Commodities .. 12.4-5
12.4-3 Example Spreadsheet for Sabine-Neches Waterway, TX 12.4-7
12.4-4 Process/ Product Categories 12.4-8
12.4-5 Uncontrolled VOC Emission Factors For Petroleum Carrying Marine Vessels 12.4-10
12.6-1 Preferred Method: DARS Scores 12.6-2
12.7-1 Area and Mobile Source Category Codes for Marine Vessel Loading,
Ballasting, and Transit 12.7-2
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
This chapter describes the procedures and recommended approaches for estimating emissions
from marine vessel loading, ballasting, and transit. Section 2 of this chapter contains a general
description of marine vessel loading, ballasting, and transit and an overview of available control
technologies. Section 3 provides an overview of available emission estimation methods.
Section 4 presents the preferred method for estimating emissions from these processes, and
Section 5 of this series of documents usually presents alternative emission estimation techniques.
For this source category, no alternative methods are known to exist, and Section 5 presents a
brief discussion of this issue. Quality assurance issues and emission estimate quality indicators
for the methods presented in this chapter are discussed in Section 6. Data coding procedures are
discussed in Section 7. Section 8 is the reference section.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
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SOURCE CATEGORY DESCRIPTION
2.1 CATEGORY DESCRIPTION
Petroleum liquids are transported via ships and barges, and on-land transportation. The
procedures discussed below relate to evaporative VOC emissions from marine transport of
petroleum liquids. This category does not include exhaust emissions from fuel consumed by
vessels while in transit or in port. Additional information about petroleum vessels can be found
inAP-42 (EPA, 1995), AIRS Area and Mobile Source Category Codes (EPA, 1999), and
Methodologies for Estimating Air Emissions from Three Non-Traditional Source Categories
(EPA, 1993).
2.2 PROCESS DESCRIPTION AND EMISSION SOURCES
In general, "petroleum liquids" include both crude oil and any refined petroleum product.
Refined petroleum products conveyed to fuel marketing terminals and petrochemical industries
via ships and barges include gasoline, kerosene, distillate oil, residual oil, jet fuel, and other
petroleum-derived chemicals such as naphtha, mineral spirits, and asphalt.
For the purposes of this document, petroleum liquids are classified into groups which are
represented by crude oil, gasoline, jet naptha, distillate oil/kerosene, or residual oil. Evaporative
emissions from marine vessel operations result from three processes: loading, ballasting, and
transit. These processes are described in more detail below and in Methodologies for Estimating
Air Emissions from Three Non-Traditional Source Categories. Although there may be certain
ports where loading large marine tankers results in emissions greater than 100 tons per year (tpy)
at a given facility, Volatile Organic Compound (VOC) emissions in most ports do not exceed
100 tpy. Methods discussed in this chapter apply to area sources only. Emissions for point
source facilities, such as petroleum refineries, should be calculated using more detailed methods.
Petroleum vessel loading, ballasting and their associated emissions are typically concentrated in
urban coastal areas and ports on inland waterways. Transit emissions are based on the amount of
time that the vessel is in an area.
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2.2.1 LOADING LOSSES (SHIPS/OCEAN VESSELS AND BARGES)
Loading losses occur as organic vapors in "empty" cargo tanks are displaced to the atmosphere
by the liquid being loaded into the tanks. These vapors are a composite of vapors formed in three
ways:
• Vapors which are formed in the "empty" tank by evaporation of residual product
from previous loads;
• Vapors transferred to the tank from a vapor balance system that was used when
the previous load was being unloaded; and
* Vapors generated in the tank as the new product is being loaded.
Loading losses are usually the largest source of evaporative emissions from petroleum vessels
(EPA, 1996). This activity usually only occurs at refineries or at the terminal at the end of the
pipeline where the product is loaded for distribution. However, petroleum liquids shipped in
"super tankers" may be unloaded to barges or smaller ships in a harbor or bay to allow the larger
tanker to enter shallower ports. In this situation called "lightering operations", vessel loading
emissions occur along with ship transit and ballasting emissions. Barges (compartment depth
10 to 12 feet) exhibit higher emissions levels than ocean vessels which have greater compartment
depth (approximately 40 feet).
2.2.2 BALLASTING LOSSES (SHIP/OCEAN VESSELS)
Ballasting losses are associated with the unloading of petroleum liquids at marine terminals and
refinery loading docks from vessels which do not have segregated ballast tanks. It is common
practice to load several cargo tank compartments with sea water after the cargo has been
unloaded. This water, called "ballast," improves the stability of the empty tanker during the
subsequent voyage. Ballasting emissions occur as vapor-laden air in the empty cargo tank is
displaced to the atmosphere by ballast water being pumped into the tank. More often, the vessel
being ballasted will be equipped with segregated ballasting tanks are ballasting will not result in
emissions of VOC to the atmosphere. However, if the vessels being ballasted are not equipped
with segregated ballasting tanks, then ballasting may range between 15 to 40 percent of the
vessels' capacities (EPA, 1996).
2.2.3 TRANSIT LOSSES (SHIP/OCEAN VESSELS AND BARGES)
Transit losses are similar to breathing losses associated with petroleum storage. Transit loss is
the expulsion of vapor from a vessel compartment through vapor contraction and expansion,
which are the result of changes in temperature and barometric pressure. This loss may be
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accompanied by slight changes in the level of the liquid in the tank due to liquid expansion or
contraction due to the temperature change. Some ships are equipped with controls for these
losses.
2.3 FACTORS INFLUENCING EMISSIONS
VOC emissions from petroleum vessel loading, ballasting, and transit are influenced by several
factors. Emissions are a function of the physical and chemical characteristics of both previous
and new cargos. Emissions are also a function of the vessel size. Many U.S. harbors are too
shallow to receive large tankers. Instead, these tankers must remain outside the harbor area and
off-load their cargo to smaller vessels in a process known as lightering. Since most lightering
occurs more than 30 miles offshore, emissions from these operations are well dispersed before
they reach the land. Lightering operations that occur outside the inventory study area may not
need to be included in the inventory. Preparers of inventories should check with policymakers,
modelers, or other inventory clients to determine whether it is necessary to include offshore
lightering emissions. If lightering emissions do need to be included in an inventory, estimating
the potential emissions from loading or ballasting will reflect the same processes as those
discussed in Sections 2.2.1 and 2.2.2 of this chapter.
VOC emissions are also a function of the method of vessel loading. In splash loading, the fill
pipe dispensing the cargo is lowered only partway into the cargo tank, resulting in higher
turbulence during loading and subsequent high levels of vapor generation and loss. On the other
hand, in submerged loading, the fill pipe extends almost to the bottom of the cargo tank, thus
controlling liquid turbulence, and resulting in much lower vapor generation than encountered
during splash loading.
2.4 CONTROL TECHNIQUES
The U.S. Coast Guard administers regulations (33 CFR, Part 157) that apply to all vessels
exceeding 150 gross tons and are either documented under U.S. laws or are foreign vessels that
transfer cargoes at ports subject to the jurisdiction of the U.S., or otherwise enter or operate in the
navigable waters of the United States. The only exceptions are for foreign ships that are simply
passing through U.S. waters or are exempt by the Port and Tanker Safety Act, as amended. The
Coast Guard rule requires that all affected ships must have segregated ballast tanks, which should
eliminate emissions from ballasting for these ships. Vessels unaffected by the regulation should
be considered potential sources of ballasting emissions.
Many states require controls on vessel loading. State and local rules should be investigated
before collecting other data for this category. Cases exist where companies have agreed to install
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controls where none are required by Federal, state or local regulations. Inventory preparers
should identify these instances.
Emissions from vessel loading can be controlled through loading practice or through control
equipment. Submerged loading, in which the fill pipe opening is below the liquid surface level,
reduces liquid turbulence and resulting vapor generation (EPA, 1996). Emissions from splash
loading can also be reduced by restricting the loading rate until the fill pipe is submerged. This
practice reduces the liquid turbulence during the splash loading portion of the load cycle.1 When
vessel loading is part of a lightering operation, vapor balancing may be used to transfer the vapor
from the vessel being loaded to the vessel being unloaded. Emissions from vessel loading may
also be controlled at terminals through vapor balance systems or with vapor control systems,
such as carbon adsorption, refrigeration, or thermal destruction units.1
Controls for emissions from ballasting include using segregated non-contaminated ballast tanks,
or placing the ballast between hulls on double-hulled ships (33 CFR, Part 157).
Emissions during transit can be reduced through the use of an inert gas system that maintains an
inert gas atmosphere at a slight positive pressure in each tank to minimize emissions and reduce
the risk of explosions.1
The use of any of these controls within the inventory area should be investigated before
emissions are calculated.
1 Personal communication between Allen Ellet, Senior Environmental Consultant, BP Oil
Company, and L. Adams, Eastern Research Group Inc., February 1998.
12.2-4 EllP Volume III
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
This document does not present an alternative method of estimating emissions from marine
vessels carrying petroleum liquids. The preferred method can be used for any type of marine
vessel, traffic classification, crude oil or refined petroleum product type, and any area of the
United States served by marine vessels.
3.1.1 VOLATILE ORGANIC COMPOUNDS
The preferred method for estimating VOC emissions from marine vessel loading, ballasting, and
transit is based on estimates of amount and type of products transported to or from the inventory
area by waterways as well as the traffic classification (import, domestic, internal upbound, etc.).
Fuels and other petroleum liquids transported are classified into five major product types of
significantly different densities, vapor pressures, and physical compositions and the types of
losses (emission points) expected from a specific operation are determined based on the traffic
classification identified above. Inventory preparers with detailed information about the products
being handled in their inventory area can use AP-42 equations for estimation calculations, after
activity data has been collected. VOC emissions are estimated by multiplying the throughput by
the appropriate emission factors corresponding to the type of loss occurring in a specific traffic
classification.
3.1.2 HAZARDOUS AIR POLLUTANTS
Hazardous air pollutant (HAP) emissions from this source are assumed to be proportional to the
HAP vapor phase weight concentrations of the petroleum liquid for which the emissions are
being calculated.
3.2 DATA NEEDS
3.2.1 DATA ELEMENTS
Several data sources are available on the movement of crude oil and other petroleum products;
tonnage shipped and received; and capacities of refineries and bulk terminals at the national,
regional, Petroleum Administration for Defense (PAD) District, state and local levels.
EllP Volume III 12.3-1
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 7/37/07
The minimum data elements needed to calculate emission estimates for marine vessel loading,
ballasting, and transit are as follows:
• Petroleum liquids by traffic classification shipped1 by type and volume aggregated
by vessel type;
• Petroleum liquid by traffic classification received2 by type and volume aggregated
by vessel type;
• Petroleum liquid in transit through inventory area;
• Controls in place for all operations, and control effectiveness;
• Product type within each traffic classification;
• Information on transport situation (i.e., barge loading, ballasting, transit) inferred
from the traffic classification; and
• Fraction of transit time spent in inventory area.
Traffic classifications will depend on the data source used. Examples used in this document are
based on the publication Waterborne Commerce of the United States 3
As mentioned in Section 2 of this chapter, regulations administered by the U.S. Coast Guard
require that large marine vessels control organic vapors from ballasting through measures such as
segregated ballast tanks. As a result, ships affected by this rule do not need to be included in
1 Traffic classification shipped: Materials classified as shipments or outbound are moved from
the subject port to another location.
2 Traffic classification received: Materials classified as receipts or inbound are moved from
another location to the subject port.
3 The publication can be obtained from the U.S. Army Corps of Engineers, New Orleans District,
Waterborne Commerce Statistics Center, P.O. Box 61280, New Orleans, LA, 70161-1280.
Tel. 504-862-1400; Waterborne commerce statistics may also be obtained on the internet from
the Waterborne Commerce Statistics Center Wide World Web site at
http://www.bts.gov/ntda/acewcsc/
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
estimates of emissions from ballasting. Ballasting emissions from smaller vessels will need to be
investigated.
3.2.2 POINT SOURCE CORRECTIONS
Although there are certain ports where handling of crude oil and other petroleum products may
result in large emissions, annual VOC emissions at most ports would not exceed 100 tons. As a
result, emissions from marine vessel loading and other operations generally should be considered
area sources. Some areas may have petroleum refineries where vessel loading operations have
been accounted for as point sources. If so, the area source emissions estimating methodology
should be designed to not double-count any sources that have been inventoried as point sources.
3.2.3 APPLICATION OF CONTROLS
Control techniques for loading, ballasting and transit are discussed in Section 2.4 of this chapter.
Rules will vary by locale and the size of the terminal or vessel. Inventory preparers should
investigate the rules in place in the inventory area, and determine if those rules apply to the
smaller sources that make up an area source inventory. Air agencies, local port authorities, and
marine vessel operators should be contacted about rules that apply in the inventory area. In
addition to controls that are put in place because of rules, inventory preparers should identify
instances of controls that are not required, but still used.
Air pollution control regulations in Louisiana and Pennsylvania require that marine loading
facilities serving ships and/or barges loading crude oil, gasoline, or volatile organic compounds
be equipped with a vapor collection system designed to collect the organic compounds vapors
displaced from ships and/or barges during loading. The vapors are then processed by recovery
and/or destruction systems such that uncontrolled emissions are reduced by at least 90 percent by
weight. Pennsylvania air laws also require that by September 28, 1996, a minimum of 65 percent
of the total volume of receipt of crude oil and gasoline during a specified period be delivered to a
facility in vessels which do not ballast, such as barges, or in vessels which do not emit VOC
when ballasted, such as tankers using segregated ballast tanks.
Chapter 1 of this volume, the Introduction to Area Source Emission Inventory Development.,
provides general guidance for determining and applying rule effectiveness (RE) for a source
category. In addition, the EPA document Procedures for Estimating and Applying Rule
Effectiveness in Post-198 7 Base Year Emission Inventories for Ozone and Carbon Monoxide
State Implementation Plans provides more detailed information on RE (EPA, 1989).
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
3.2.4 SPATIAL ALLOCATION
The preferred method estimates emissions from loading, ballasting, and transit at the study region
level. Emissions from these operations are concentrated in coastal areas, areas surrounding the
Great Lakes, and areas adjacent to ports on inland waterways.
3.2.5 TEMPORAL RESOLUTION
Seasonal Apportioning
Some emissions from loading, ballasting, and transit of petroleum liquids from marine vessels
are expected to be spread evenly over time, while other emissions will exhibit seasonal
variations. Crude oil activities are relatively stable throughout the seasons. However, seasonal
variations are expected in gasoline shipments and in those areas where wintertime frozen waters
make ports inaccessible, such as the Great Lakes region.
Alternatively, temporal allocation of vessel loading, ballasting, and transit emissions can be
accomplished by (1) obtaining detailed monthly activity data for the port in question and
applying these data to the estimation equation, or (2) by apportionment factors based on use of
the various products. The second method would capitalize on data which should already exist
from area/mobile source inventory efforts (e.g., monthly or seasonal allocation of motor fuel;
consumption and/or vehicle miles traveled; home heating fuels; aircraft fuels, etc.).
VOC emissions from these marine vessel operations vary due to changes in temperature as well
as vapor pressure. Equations are available that account for such variations. However, this source
category generally accounts for a relatively small portion of the overall area inventory.
Daily Resolution
Vessel loading and unloading operations are assumed to occur on a daily basis, seven days a
week.
3.3 PROJECTING EMISSIONS
The EIIP Projections Committee has developed a series of guidance documents containing
information on options for forecasting future emissions. You can refer to these documents at
http://www.epa.gov/ttn/chief/eiip/project.htm.
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
Projecting emissions from petroleum vessel loading, ballasting, and transit requires information
on anticipated changes in demand for those products and prices, as well as changes in storage
capacity at ports and harbors. If no information is available, the inventorying agency can assume
no changes to the existing level of activities. Alternatively, historic activity at the ports in the
inventory area would be the best source of data for projecting future vessel activity.
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
This page is intentionally left blank.
12.3-6 EllP Volume III
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS
4.1 PREFERRED METHOD
The preferred method for estimating emissions from petroleum vessel loading, ballasting, and
transit is described below. This method has limitations because the data that are needed are often
not available. The method is intended to produce representative area source emissions estimates
without requiring the expenditure of an unreasonable amount of resources to fill information
gaps. However, it is recommended that, as a first step, inventory preparers identify controls that
are in use in the area, and determine if emissions are primarily inventoried as part of the point
source inventory. See Sections 2.4 and 3.2.3 of this chapter for more information about controls.
Because some controls may eliminate emissions from certain processes and vessels altogether,
data collection can be reduced to only those vessels and processes that are actually creating
emissions. The steps of the methodology are as follows:
4.1.1 DETERMINATION OF AMOUNT OF PETROLEUM LIQUIDS TRANSPORTED TO OR
FROM THE INVENTORY REGION
Determine the amount and type of petroleum liquids transported to or from the inventory region
by waterway. The publication Waterborne Commerce of the United States1 can be used to obtain
data on the movements of commodities and vessels at individual ports and harbors and on
individual waterways and canals of the United States. Both foreign and domestic commerce are
included. Other sources of potentially useful information are the Petroleum Supply Annual?
Petroleum Storage and Transportation (DOE, 1989), publications from the U.S. Maritime
1 The publication can be obtained from the U.S. Army Corps of Engineers, New Orleans District,
Waterborne Commerce Statistics Center, P.O. Box 61280, New Orleans, LA, 70161-1280.
Tel. 504-862-1400; Waterborne commerce statistics may also be obtained on the internet from
the Waterborne Commerce Statistics Center Wide World Web site at
http://www.bts.gov/ntda/acewcsc/
2 The Petroleum Supply Annual can be obtained from the Energy Information Administration
(EIA), Department of Energy, Washington, DC; refer to the EIA web site at
http://www.eia.doe.gov.
EllP Volume III 12.4-1
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
Administration (U.S. Maritime Administration, 1985), and the Petroleum Terminal
Encyclopedia^ Estimates of percentage of each fuel type carried by each type of vessel are
available from National or Regional Petroleum Administrations for Defense district, or the state.
The New Orleans District Data Request Office of the U.S. Army Corps of Engineers also handles
special requests (at a cost), for water commerce statistics such as port- and harbor-specific
information regarding shipping and receiving operations. Available data include the following:
• Crude oil and other petroleum products shipped and received at each harbor
aggregated by fuel and type of vessel (i.e., tankers versus barges);
• Refinery receipts of crude oil and petroleum products by type of vessel; and
• Refinery shipments of crude oil and petroleum products by type of vessel.
In some cases, only one shipping company ships specific products to and from certain locations.
If the Data Request Center were to reveal the tonnage for each product shipped, the Confidential
Business Information for that particular company may be compromised. In this situation the
Data Request Center prefers to submit the data as lump sum totals without specifying the tonnage
to each destination.
4.1.2 IDENTIFICATION OF EMISSION POINTS
Use Table 12.4-1 to identify the emission points for each traffic classification. Determine
emission points for all petroleum commodity types. Additional traffic classifications may exist.
Classifications listed here represent the most likely emission process assignments. Table 12.4-1
is based on the following assumptions:
• All traffic involves transit emissions;
• Loading (ship, vessel, barge) emissions only result from export, shipment,
and outbound traffic;
• Ballasting emissions only result from import and receipts traffic where the
return voyage requires balancing;
* Through traffic results only in transit emissions; and
3 A periodic report from Salsby/Wilson Press, Houston, Texas; also available at
http://www.opisnet.com/terminal.htm
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
• Barge loading emissions result only from exports and shipments traffic in
shallower waterways (e.g. internal, lakeside waterways). Inventory
preparers should investigate the use of barges and ships in their area.
The emission points presented in Table 12.4-1 are defined based on the traffic type definitions
presented in the U.S. Army Corps of Engineers' Waterborne Commerce of the United States.
Definitions of the traffic classifications can be found in that document. Loading operations
(ship/vessel loading and barge loading) occur when the commodity is moved from the subject
port to another port or location. Other traffic is assumed to be either traffic that has originated
from another port or location and represents an unloading operation, or through traffic that does
not stop at the port/waterway. One exception to this rule is intra-port or intra-waterway traffic
which is loaded and unloaded in the subject waterway.
Unloading operations do not result in emissions from the vessel itself. Unloading operations
only result in emissions counted as part of this source category if ballasting into non-segregated
cargo tanks occurs to the vessel being unloaded. Otherwise the emissions that result due to the
loading of the receiving tank or truck are counted as the source category covering emissions from
loading tanks or trucks. Unless the receiving vessel is another marine vessel, loading of the tank
or truck would not be considered marine loading and would not be part of this area source
category.
4.1.3 CLASSIFICATION OF PETROLEUM PRODUCTS BY FUEL TYPE
Classify the petroleum liquids transported in the inventory region into five fuel type
classifications using Table 12.4-2. If inventory data quality objectives require more detailed
emission estimates, the inventory preparer may want to use the equations for calculating
emissions from AP-42, Section 5.2, Transportation and Marketing of Petroleum Liquids, and
portions of AP-42, Section 7.1, Liquid Storage Tanks, including Table 7.1-2, Properties of
Selected Petroleum Liquids. The equations in AP-42 require considerably more data collection
than the data collection discussed in this chapter. The inventory preparer may want to consider
the costs and benefits of using the more detailed approach, and may want to use the AP-42
equations on a small subset of products that will most make the most significant improvement to
the overall estimate, and use the emission factors presented here for the remaining products.
EllP Volume III 12.4-3
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
1/31/01
TABLE 12.4-1
EMISSION POINTS FOR PETROLEUM VESSEL
TRAFFIC CLASSIFICATIONS
Traffic Classificationa
Foreign Imports
Foreign Exports
Foreign Intratransit Merchandise
Foreign Through Upbound
Foreign Through Downbound
Canadian Exports
Canadian Imports
Canadian Through Upbound
Canadian Through Downbound
Coastwise Receipts
Coastwise Shipments
Coastwise Through Upbound
Coastwise Through Downbound
Lakewise Receipts
Lakewise Shipments
Internal Receipts
Internal Shipments
Internal Inbound Upbound
Internal Inbound Downbound
Internal Outbound Upbound
Internal Outbound Downbound
Internal through Upbound
Internal through Downbound
Internal Intra- waterway Upbound
Internal Intra-waterway Downbound
Internal Intraport
Intra-territory Shipments
Intra-territorv Receipts
Ship/Ocean
Vessel Loading
X
xd
X
Barge
Loadingb'c
Xd
X
X
X
X
X
X
X
X
Ballasting0
X
xd
X
X
X
X
X
X
X
X
X
Transit
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
These classifications are used in the Waterborne Commerce of the United States, U.S. Army Corps of Engineers,
Waterborne Commerce Statistics Center, New Orleans, LA.
Barges may not be used at all ports by the indicated traffic classification.
Inventory preparers should research ballasting practices in their area to identify the traffic classifications where
d ballasting actually occursv
Inventory preparers should research the use of barges and ships in their area.
12.4-4
EIIP Volume III
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1/31/01
CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
TABLE 12.4-2
PRODUCT TYPE CLASSIFICATIONS FOR COMMON PETROLEUM
VESSEL COMMODITIES3
Petroleum Vessel Commodity
Crude petroleum
Gasoline
Kerosene
Distillate fuel oil
Residual fuel oil
Lube oil and greases
Petro. jelly and waxes
Naphtha and solvents
Asphalt, tar, and pitch
Petroleum coke
Liquid natural gas
Petroleum products not elsewhere classified
Product Type Classification
Crude oil
Gasoline
Distillate oil
Distillate oil
Residual oil
Distillate oil
Distillate oil
Jet naphtha
Residual oil
Residual oil
Gasoline
Jet naphtha
These classifications were determined by approximately matching the density, vapor pressure, and physical
composition of the commodities to the five product types. The product types match available AP-42 emission
factors.
EIIP Volume III
12.4-5
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
An example of how data from the Waterborne Commerce document can be compiled for one
large waterway is shown in Example 12.4-1.
Example 12.4-1:
Data from Example Area A, an area where large amounts of petroleum liquids are handled, is listed
in Appendix A as it is provided in the Waterborne Commerce of the United States. Shipments and
receipts of commodities are listed by product type and traffic classification. Definitions of traffic
classifications can be found in the Waterborne Commerce document. For an area source inventory,
the information needs to be compiled first by traffic classifications representing similar processes,
and then by product types that can be linked to existing emission factors. For this example, these
steps are accomplished using a spreadsheet. The first step, shown in Table 12.4-3, is to enter the
data into the spreadsheet so it can be sorted by traffic classification and product type.
Table 12.4-4 shows the data further combined into groups based on traffic classification and sorted
by product types that will match AP-42 emission factors. Table 12.4-1 can be used to match traffic
classifications and AP-42 processes, e.g. ship loading or barge loading. Note that based on local
information, only foreign and Canadian and coastwise receipt categories were subject to ballasting.
4.1.4 ESTIMATION OF TRANSIT EMISSIONS
For transit emissions, estimate the average time traffic is in the inventory area. Specific data may
be difficult to obtain. The best resource for this information may be the local port authorities.
4.1.5 CORRECTION FOR POINT SOURCE EMISSIONS
It is possible for some marine loading operations, such as those at large petroleum refineries
operating their own port, to be included in point source inventories. To make the
double-counting correction, the material throughputs from specific point source SCCs should be
totaled and subtracted from the total area source material transferred. Area source emissions
should then be estimated based on this corrected material transferred amount.
If the point source material throughputs are not available, the correction can be made at the
emissions level (subtract total emissions from specific point source SCCs from total area source
emissions). Emissions from vessel loading/unloading operations at facilities such as petroleum
refineries located in the inventory area should be deducted from the area source totals. Point
source SCCs may include 40600231 through 40600259. Additional point source SCCs may
exist, so the point source inventory should be carefully reviewed.
12.4-6 EllP Volume III
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1/31/01
CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
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EIIP Volume III
12.4-7
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to
4^
OO
TABLE 12.4-4
PROCESS/ PRODUCT CATEGORIES3
AP-42
Product
Type
Class
Crude
Distillate
Distillate
Distillate
Distillate
Gasoline
Gasoline
Jet
Naphtha
Jet
Naphtha
Residual
Residual
Residual
Product
Code
2100
2330
2350
2221
2410
2640
2211
2990
2429
2340
2430
2540
Commodity
Name
Crude Petroleum
Distillate Fuel Oil
Lube Oil & Grease
Kerosene
Petroleum Jellv and Waxes
Liquid Natural Gas
Gasoline
Petroleum Prod., NEC
Naphtha & Solvents
Residual Fuel Oil
Asphalt, Tar and Pitch
Petroleum
Coke
Ship loading
Foreign
&
Canadian
Exports
0
8
47
0
0
27
518
0
22
160
41
3,435
Coastwise
Shipments
4
239
314
0
0
0
1,633
7
0
85
0
0
Barge Loading
Internal
Outbound
575
1,398
356
131
0
55
940
226
373
1,947
23
64
Internal
Intra
33
72
3
0
0
4
192
15
216
205
0
4
Ballasting
Foreign &
Canadian
Imports
38,744
12
690
0
0
131
0
0
155
72
2
241
Coastwise
Receipts
72
83
256
0
0
0
21
0
27
59
0
0
Transit
Foreign
&
Canadian
Total
38,744
20
737
0
0
158
518
0
177
232
43
3,676
Coastwise
Total
75
322
570
0
0
0
1,654
7
27
144
19
0
Internal
Total
5,654
4,494
1,112
290
56
552
5,294
624
2,119
5,613
1,075
776
I
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1 All commodity amounts in one thousand tons
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7/37/07
CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
4.1.6 ESTIMATION OF EMISSIONS FROM PETROLEUM VESSELS
Use the estimates of petroleum liquids, grouped by traffic classification and sorted by product
types, and the emission factors in Table 12.4-5 to estimate total VOC emissions from petroleum
vessels for each of the five types of petroleum liquids (p) at each emission point. It should be
noted that these factors are for dispensed product at 60°F and can be adjusted for significantly
different conditions using original derivation methods in AP-42. It should also be noted that
some emission factors may not apply to a particular port, e.g., barge loading or ballasting, may
not take place.
In Section 2.2.2 of this chapter, ballasting practices are discussed. If ballasting only occurs
using segregated ballast tanks, it is not necessary to estimate ballasting emissions. However, if
ballasting uses the empty cargo tank, emissions will occur, and must be calculated. Note that the
calculation for ballasting emissions in the equation includes a correction term of 0.30. This
correction term reflects the practice of loading a ship or barge at some fraction of capacity when
ballasting. Emission estimates will be improved if local information about typical percentages
can be located and used. The correction term presented here represents a conservative
assumption.
Apply any control efficiency to the appropriate terms in Equation 12.4-1, or Equation 12.4-2 can
be used to apply control efficiency.
PVp = [(SOEFp
where:
(BREFp x PPBp) + (BLEFpU x 0.30 x PPBLp) + (TREFp x PPTp)] * 2
* 2000
(12.4-1)
PVp =
SOEFp =
PPS p =
BREFp =
PP
Bp
BLEFp =
Total VOC emissions from petroleum vessel loading, ballasting, and
transit for each of the petroleum liquids (p) transported: crude oil,
gasoline, kerosene, distillate oil, and residual oil (tons)
Ship/ocean vessel loading emission factor (pounds VOC per 1,000 gallons
transferred)
Amount of petroleum liquid (p) loaded into ships and ocean vessels in the
inventory region (1,000 gallons)
Barge vessel loading emission factor (pounds VOC per 1,000 gallons
transferred)
Amount of petroleum liquid (p) loaded into barges in the inventory region
(1,000 gallons)
Ballasting emission factor (pounds VOC per 1,000 gallons water ballasted)
Amount of petroleum liquid (p) unloaded from vessels that are ballasted
(1,000 gallons)
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
1/31/01
TREFp =
PP
T,P
Vessel transit emission factor (pounds VOC per week per 1,000 gallons
transferred)
Amount of petroleum liquid (p) transported by marine vessels in the
inventory region (1,000 gallons)
TABLE 12.4-5
UNCONTROLLED VOC EMISSION FACTORS FOR PETROLEUM CARRYING MARINE
VESSELS (EPA, 1996)
Petroleum
Liquid
Crude Oil
Gasoline13
Jet Naphtha/
Other
Distillate
Oil/Kerosene
Residual Oil
Ship/Ocean Vessel
Loading (Pounds
VOC per 1,000
gallons Transferred)
0.61
1.8b
0.5
0.005
4x ID'5
Barge Loading
(Pounds VOC
per 1,000 gallons
Transferred)
1
3.4b
1.2
0.012
9x ID'5
Ballasting
(Pounds VOC per
1,000 gallons
Ballasted)3
l.lb
0.8b
NA
NA
NA
Transit (Pounds
VOC per week per
1,000 gallons
Transported)
1.3
2.7b
0.7
0.005
3 x ID'5
a It may not be necessary to estimate ballasting emissions. See Section 3, of this chapter, Data Elements for discussion.
b These are AP-42 "typical overall situation" factors; various additional factors related to specific types of service can be
found in AP-42. In addition, AP-42 equations could be used, if necessary, to calculate emission factors for specific
compounds, given values for true vapor pressures and average liquid molecular weights.
If controls exist, then control efficiency can be calculated:
PPC=PPTJ*(1-CE/100)
(12.4-2)
where:
CE
Controlled emissions (tons)
Uncontrolled emissions (tons)
Control efficiency (%)
12.4-10
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
Data obtained from sources such as the Waterborne Commerce of the United States are typically
provided in terms other than 1,000 gallons (Mgal) as is required in Equation 12.4-1 and must be
converted. Equation 12.4-3 can be used to convert units from 1,000 ton (Mtons) to Mgal.
PPV = (PPm/d) * 2,000 Ib/ton * Mgal/1,000 gallons * 1,000 tons/Mtons (12.4-3)
where:
PPV = Amount of petroleum liquid (Mgal)
PPm = Amount of petroleum liquid (Mtons)
d = Density of petroleum liquid; see Table 7.1-2 in AP-42 (Ib/gallon)
Example 12.4-2 illustrates the calculations used to estimate emissions from tons of fuel.
EllP Volume III 12.4-11
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
1/31/01
Example 12.4-2
The inventory area had an annual throughput of gasoline from vessel loading, barge
loading, and transit operations as indicated below:
Operation
Vessel loading
Barge loading
Ballasting
Transit
Throughput (1,000 tons)
2,178
1,191
152
8,176
Using the gasoline density factor found in AP-42, Table 7.1-2 (5.6 Ib/gal), and
Equation 12.4-3, the mass throughputs are converted to volumetric throughputs.
Vessels loading throughputs are converted by:
PPv = [2,178 Mtons/(5.6 Ib/gal)] * 2'°°0 lb *
Mgal 1,000 tons
ton 1,000 gal Mtons
The results of the calculation are shown below:
Conversion of Mass Throughputs to Volumetric Throughputs
Operation
Vessel loading
Barge loading
Ballasting
Transit
Equation 12.4-1
Parameter
pp
rrS,gas
PP
r±B,gas
PP
r±BL,gas
PPT.«
Throughput
(Mtons)
2,178
1,191
1,213
8,176
Throughput
(Mgal)
777,857
425,357
54,286
2,920,000
12.4-12
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
Example 12.4-2 (Continued^)
For vessel loading operations, 90 percent of the total throughput was loaded at terminals with a
control system of 95 percent efficiency. According to the local port authorities, transit time in
the inventory area is two days (2/7 of a week). Emissions for each emission point are
calculated using Equation 12.4-1 and the emission factors from Table 12.4-5. In this example,
emissions for each emission point are calculated separately and then totaled. Note that CE is
applied to vessel loading emissions, and transit emissions are apportioned to two days per
week by multiplying emissions by 2/7.
Vessel Loading emissions are calculated:
( 95 "l
PVgas= [1.8 Ib VOC/Mgal* 777,857 Mgal/yr) * (0.10 + (0.9 * 1-—^ ]-2,000 Ib/ton
= 102 tons/yr
Barge Loading emissions are calculated:
PVgas = [3.4 Ib VOC/Mgal * 425,357 Mgal/yr)]-2,000 Ib/ton
= 723 tons/yr
Ballasting emissions are calculated:
PVgas = [0.8 Ib VOC/Mgal * 54,286 Mgal/yr) * 0.30]-2,000 Ib/ton
= 7 tons/yr
Transit emissions are calculated:
PVgas = (2.7 Ib VOC/Mgal * 2,920,000 Mgal/yr * 2/7 wk)-2,000 Ib/ton
= 1,128 tons/yr
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
Example 12.4-2 (Continued)
Total VOC emissions are calculated as follows:
Total VOC = 102 tons/yr + 723 tons/yr + 7 tons/yr + 1,128 tons/yr
= 1,957 tons/yr
Contributions from the point source inventory are 82 tons/yr VOC. The total VOC emissions
in the area source inventory are:
1,957 tons/yr-82 tons/yr = 1,875 tons/yr
12.4-14 EllP Volume III
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
No alternative methods are known to exist, nor are any necessary since the preferred method and data
associated with it can be used for any type of vessel, any type of traffic, any type of fuel, and any area
of the United States serviced by petroleum vessels.
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
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12.5-2 EllP Volume III
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QUALITY ASSURANCE/
QUALITY CONTROL
Data collection and handling for the marine vessel loading, ballasting, and transit source category
should be planned and documented in the Quality Assurance Plan. In particular, material type
assignments and emission estimation calculations should be reviewed as part of the QA/QC
procedures. Refer to the discussion of inventory planning and QA/QC in Chapter 1, Introduction
to Area Source Emission Inventory Development, of this volume, and the QA volume (VI) of the
EIIP series.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
One method is provided in this chapter for estimating emissions from marine vessel loading,
ballasting, and transit. Data collection for this source category involves identifying the most
suitable data source from those listed in Section 4 of this chapter, and compiling the information.
Although data collection for this category can require a significant amount of effort, the quality
of the activity data is high, and the effort required may be justified by the importance of the
estimated emissions in areas where there is a significant amount of marine vessel loading,
ballasting, and transit.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
The DARS scores for the preferred method are summarized in Table 12.6-1. A range of scores is
provided to account for differences in the implementation of the method. Lower activity scores
are shown for activity data that are not drawn from records collected specifically for the
inventory area. This would be the case if specific product data are not available for the inventory
area and the tonnage of each product loaded or unloaded in the inventory area must be
apportioned from regional data. Higher DARS scores than those assigned in Table 12.6-1 could
EIIP Volume III 12.6-1
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
1/31/01
be assigned if the equations from AP-42 are used, rather than emission factors that have been
derived from the equations.
Lower emission factor scores reflect the necessary simplifications that must be made for an area
source method. The first simplification is the use of emission factors developed from the
equations provided in AP-42. Assumptions have been made concerning the fuel type vapor
pressure and the molecular weight of vapors, which are addressed in the source specificity score,
and average annual temperature, which is addressed in the spatial congruity score. The emission
factor measurement scores will vary depending on whether the product is actually the product
type for which the emission factor was developed, or a similar product that has been grouped into
that product classification (see Table 12.4-1). Variability in local practices affect the spatial
congruity score. Seasonal temperature differences and potential changes in equipment and filling
practices since the latest update of the emission equations and parameters in AP-42 affect the
temporal congruity score.
TABLE 12.6-1
PREFERRED METHOD: DARS SCORES
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.3 -0.5
0.7-0.9
0.5
0.5
0.5-0.6
Activity
0.9
0.7-0.9
0.7- 1.0
0.9- 1.0
0.80-0.95
Emissions
0.27-0.45
0.49-0.81
0.35-0.5
0.45-0.5
0.39-0.57
6.1.2 SOURCES OF UNCERTAINTY
There are several sources of uncertainty in estimating emissions from this source category.
When the method provided in this chapter is used, activity data are collected, the data may be
apportioned to reflect activity in the inventory area, and amounts of some materials are grouped
with similar material types into product classifications. Each of these steps will have some
associated uncertainty, and the uncertainty cannot be quantified.
12.6-2
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1/31/01 CHAPTER 6 - QUALITY ASSURANCE/QUALITY CONTROL
An additional source of uncertainty comes from using emission factors rather than equations that
use a number of parameters. In this case, the sensitivity of the equations to different parameters
could be quantified using typical sensitivity analysis techniques.
EllP Volume III 12.6-3
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
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12.6-4 EllP Volume III
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from marine vessel
loading, ballasting, and transit. A complete list of Source Classification Codes (SCC) can be
retrieved at http://www.epa.gov/ttn/chief/codes/. Table 12.7-1 lists the applicable SCCs for
marine vessel loading, ballasting, and transit.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use in
regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa. gov/ttn/chief/net/. The acceptable data transfer formats contain the data elements
necessary to complete the data set for use in regional or national air quality and human exposure
modeling. The inventory preparer should review the area source portion of the acceptable file
format(s) to understand the necessary data elements. The EPA describes its use and processing
of the data for purposes of completing the national inventory, in its Data Incorporation Plan, also
located at http://www.epa.gov/ttn/chief/net/.
EllP Volume III 12.7-1
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
1/31/01
TABLE 12.7-1
AREA AND MOBILE SOURCE CATEGORY CODES FOR MARINE VESSEL LOADING,
BALLASTING AND TRANSIT
Process Description
Gasoline: Ship Loading -Cleaned and Vapor Free Tanks
Gasoline: Ocean Barges Loading
Gasoline: Barge Loading - Cleaned and Vapor Free Tanks
Gasoline: Ship Loading - Ballasted Tank
Gasoline: Ocean Barges Loading - Ballasted Tank
Gasoline: Ship Loading -Uncleaned Tanks
Gasoline: Ocean Barge Loading - Uncleaned Tanks
Gasoline: Barge Loading - Uncleaned Tanks
Gasoline: Tanker Ship - Ballasted Tank Condition
Gasoline: Barge Loading - Average Tank Condition
Gasoline: Tanker Ship - Ballasting
Crude Oil: Loading Tankers
Jet Fuel: Loading Tankers
Kerosene: Loading Tankers
Distillate Oil: Loading Tankers
Crude Oil: Loading Barges
Jet Fuel: Loading Barges
Kerosene: Loading Barges
Distillate Oil: Loading Barges
Crude Oil: Tanker Ballasting
Tanker/Barge Cleaning
Gasoline: Barge Loading - Ballasted
Not Classified
Not Classified
Source Category Code
40-60-002-31
40-60-002-32
40-60-002-33
40-60-002-34
40-60-002-35
40-60-002-36
40-60-002-37
40-60-002-38
40-60-002-39
40-60-002-40
40-60-002-41
40-60-002-43
40-60-002-44
40-60-002-45
40-60-002-46
40-60-002-48
40-60-002-49
40-60-002-50
40-60-002-51
40-60-002-53
40-60-002-59
40-60-002-60
40-60-002-98
40-60-002-99
12.7-2
EIIP Volume III
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8
REFERENCES
EPA. 1995. Compilation of'Air Pollution Emission Factors -Volume 1: Stationary Point and
Area Sources. Fifth Edition, Supplements A-F, AP-42. U.S. Environmental Protection Agency,
Office of Air Quality Planning and Standards. (GPO 055-000-00251-7). Research Triangle
Park, North Carolina, (www.epa.gov/ttn/chief/ap42/)
EPA. 1993. Methodologies for Estimating Air Emissions from Three Non-Traditional Source
Categories: Oil Spills, Petroleum Vessel Loading and Unloading, and Cooling Towers. U.S.
Environmental Protection Agency, Office of Research and Development. EPA-600/R-93-063
(NTISPB93-181592). Washington, DC.
EPA. 1999. AIRS Point, Area, and Mobile Source Category Codes. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards. Research Triangle Park, North
Carolina, (www.epa.gov/ttn/chief/scccodes.html)
EPA. 1989. Procedures for Estimating and Applying Rule Effectiveness in Post-1987 Base Year
Emission Inventories for Ozone and Carbon Monoxide State Implementation Plans. U.S.
Environmental Protection Agency. Research Triangle Park, North Carolina.
DOE. 1989. Petroleum Storage and Transportation, Volume II: System Dynamics. Nation
Petroleum Council, U.S. Department of Energy. Washington, DC.
U.S. Maritime Administration. 1985. Domestic Waterborne Trade of the U.S. U.S. Maritime
Administration, Office of Domestic Shipping. Washington, DC.
EIIP Volume III 12.8-1
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CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT 1/31/01
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7/37/07 CHAPTER 12 - MARINE VESSEL LOADING, BALLASTING, AND TRANSIT
Appendix A
Example Waterborne Commerce Data
EIIP Volume III
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EXAMPLE AREA A
Section Included: Gulf of Mexico to turning basins at West Port Arthur, Beaumont, and Orange, TX, about 85.8 miles;
Adams Bayou Channel, about 1.6 miles; and Cow Bayou Channel, about 7 miles. Controlling Depth: Sabine Pass
Channel, TX, 40feet; Port Arthur, TX, 37 feet; Beaumont, TX, 39feet; extension to Bethlehem Steel Shipyard, 32feet;
Orange, TX, 27 feet except channel around Harbor Island, 20 feet; Adams Bayou Channel, 9 feet; and Cow
Bayou Channel, 8 feet. Project Depth: Sabine Pass Harbor, TX, 40 to 42 feet; Port Arthur, TX, 40feet; Beaumont.TX,
40feet exceptturning basin, 34feet, and extension to Bethlehem Steel Shipyard, SOfeet; Orange, TX, SOfeet
except channel around Harbor Island, 25 feet, Adams Bayou, 12 feet, and Cow Bayou, 13 feet, mean lowtide.
Comparative Statement of Traffic
(thousandtons)
Year
1986
1987
1988
1989
1990
Total
75,943
79,742
89,091
96,564
90,819
Year
1991
1992
1993
1994
1995
Total
84,213
88,348
95,191
99,675
103,254
FreightTraffic, 1995
(thousandtons)
Commodity Total
Total, all commodities 49,124
Total petroleum and petroleum products 44,305
Subtotal crude petroleum 38,744
2100 crude petroleum 38,744
Subtotal petroleum products 5,562
2211 gasoline 518
2330 distillatefueloil 21
2340 residualfueloil 232
2350 lubeoil&greases 737
2429 naphtha Ssolvents 177
2430 asphalt, tar & pitch 43
2540 petroleum coke 3,676
2640 liquid natural gas 158
Total chemicals and related products 757
Subtotalfertilizers 12
3190 fert. & mixes nee 12
Subtotalotherchemicalsand related products 745
3211 acyclic hydrocarbons 26
3212 benzene&toluene 44
3219 other hydrocarbons 104
3220 alcohols 103
3240 nitrogenfunc. comp 10
3260 organiccomp. nee 25
3275 inorg.elem., oxides, & halogen salts 0
3276 metallicsalts 430
3281 radioactive material 0
3282 pigments & paints 0
3285 perfumes and cleansers 0
3286 plastics 0
3291 pesticides 0
3297 chemical additives 1
3298 wood& resin chem. 0
Foreian
I m ports
40,724
39,886
38,583
38,583
1,303
12
72
690
155
2
241
131
33
33
22
4
3
3
0
0
0
0
Exports
8,178
4,203
4,203
518
8
160
47
22
41
3,380
27
724
12
12
712
4
44
100
100
10
22
430
0
0
0
0
1
0
Canadian
Imports Exports
167 55
161 55
1fi1
161
55
EE HE
EIIP Volume III
12.A-1
-------
Commodity Total
Total crude materials, inedibleexceptfuels 727
Subtotal forest products, wood and chips 231
4161 woodchips 224
4170 wood in the rough 0
4189 lumber 6
Subtotal pulpandwastepaper 62
4225 pulp & waste paper 62
Subtotal soil, sand, gravel, rockand stone 432
4322 limestone 30
4331 sand & gravel 402
Subtotal iron oreand scrap 2
4420 iron Ssteel scrap 2
Subtotal non-ferrous ores and scrap 0
4680 non-ferrous scrap 0
Subtotal other non-metal, min. 0
4900 non-metal, min. nee 0
Total primary manufactured goods 549
Subtotal paper products 22
5120 paper Spaperboard 21
5190 paper products nee 0
Subtotal lime, cementand glass 2
5290 misc. mineral prod. 2
Subtotal primary iron and steel products 313
5312 pigiron 2
5320 i&s primary forms 262
5330 i&s plates Ssheets 1
5360 i&s bars Sshapes 3
5370 i&s pipe &tube 1
5390 primary i&s nee 45
Subtotal primary non-ferrous metal products 2
5422 aluminum 1
5429 smelted prod, nee 0
5480 fab. metal products 1
Subtotal primary wood products 21 1
5540 primary wood prod. 211
Total food and farm products 2,778
Subtotal grain 1,733
6241 wheat 1,486
6344 corn 0
6442 rice 20
6447 sorghum grains 227
Subtotal oilseeds 513
6522 soybeans 513
6590 oilseeds nee 0
Subtotal vegetable products 15
6653 vegetable oils 1
6654 vegetables & prod. 14
Fo
Imports
441
6
0
6
432
30
402
2
2
0
0
333
0
0
0
0
0
304
1
256
1
0
45
1
1
0
27
27
30
ieign
Exports
286
224
224
0
62
62
0
0
211
21
21
0
1
1
4
0
3
1
1
0
0
1
183
183
2,748
1,733
1,486
0
20
227
513
513
0
15
1
14
Canadian
Imports I Exports
g
6
g
12.A-2
EIIP Volume III
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Commodity Total
Subtotal processed grain and animalfeed 507
6746 wheatflour 385
6747 grain mill products 95
6782 animalfeed, prep. 27
Subtotal other agricultural products 11
6858 fruitjuices 0
6871 coffee 3
6885 alcoholic beverages 0
6889 food products nee 8
6893 cotton 0
Total all manufactured equipment, machinery 8
and products
7110 Machinery (not elec) 3
7120 electrical machinery 3
7210 vehicles & parts 0
7220 air crafts parts 0
7230 ships & boats 1
7400 manufac. wood prod. 0
7500 textile products 0
7600 rubbers plastic pr. 0
7900 manufac. prod, nee 0
Total u n known or not elsewhere classified 0
9900 unknown ornec 0
Ton-miles (xlOOO) 123,373
Foreign & Canadian
Foreign
Imports I Exoorts
2'
2'
'
(
(
(
(
(
(
(
(
80,52-
Commodity Total
Total, all commodities 3,949
Total petroleum and petroleum products 2,818
Subtotal crude petroleum 75
2100 crude petroleum 75
Subtotal petroleum products 2,743
2211 gasoline 1,654
2330 distillate fuel oil 322
2340 residual fuel oil 144
2450 lubeoil&greases 570
2429 naphtha Ssolvents 27
2430 asphalt, tar & pitch 19
2990 petro. products nee 7
Total chemicals and related products 1,059
Subtotalotherchemicalsand related products 1,059
3212 benzene&toluene 31
3219 other hydrocarbons 105
3220 alcohols 113
7 480
385
95
j
3 7
D 0
3
0
1 7
0
I 6
1 2
D 2
D 0
0
1
}
D 0
D 0
D 0
)
~\
42,846
Canadian
Imports I Exports
0
0
Coastwise
Through
Receipts Shipment Upbound
576 3,346 27
518 2,828 19
72 4
72 4
446 2,278 19
21 1,633
83 239
oy oo
256 314
27
1 g
7
4 1,050 5
4 1,050 5
4 26
105
1 n
EIIP Volume III
12.A-3
-------
Commodity
3271 sulphur(liquid)
3274 sodium hydroxide
3276 metallicsalts
3297 chemical additives
3299 chem. products nee
Total crude materials, inedibleexceptfuels
Subtotal soil, sand, gravel, rockand stone
4338 soil &fill dirt
Subtotal iron ore and scrap
4420 iron Ssteel scrap
Subtotal sulphur, clay and salt
4782 clay refrac. mat.
Subtotal other non-metal, min.
4900 non-metal, min. nee
Total primary manufactured goods
Subtotal primary iron an steel products
5320 i&s primary forms
Subtotal primary non-ferrous metal products
5421 copper
5480 fab. metal products
Total all manufactured equipment, machinery and products
7110 machinery (not elec)
7400 manufac. wood prod.
Ton-miles(xlOOO)
Coastwise
Total
352
4
12
436
7
56
3
3
53
53
0
0
0
0
14
11
11
3
1
1
2
0
1
199,731
Coastwise
Receipts
0
53
53
53
1
1
1
0
0
28,002
Shipment
352
10
436
7
2
1
1
0
0
0
0
13
11
11
1
1
0
0
169,459
Through
Upbound
4
1
1
1
1
1
1
2,270
Internal
Commodity Total Inbound Outbound
Upbound Downbnd Upbound Downbnd
Total.all 50,181 5,879 1,529 1,226 7,880
Commodities
Total coal 107 1 1 48
1 100 Pnal linnitp ft 1
1900 rnal rnkp QQ 1 J.ft
Total Petroleum 27,660 2,935 860 994 5,096
and Petroleum
products
Subtotal crude 5,654 841 30 545
petroleum
2100 crude 5,654 841 30 545
petroleum
Through
Upbound Downbnd
14,797
5
5
7,360
852
852
17,425
51
7
44
9,673
3,353
3,353
Intra
Upbound
972
510
23
23
Downbnd
474
231
10
10
12.A-4
EIIP Volume III
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Commodity
Subtotal
petroleum
products
2211 gasoline
2221 kerosene
2330 distillatefuel
oil
2340 residual fuel oil
2350 lubeoilS
greases
2410 petro. jelly &
waxes
2429 naphthas
solvents
2430 asphalt, tar &
pitch
2540 petroleum
coke
2640 liquid natural
gas
2990 petro.
products nee
Total chemicals
and related
products
Subtotal
fertilizers
3110 nitrogenous
fert.
3120 phosphatic
fert.
3130 potassicfert.
3190 fert. & mixes
nee
Subtotal other
chemicals and
related products
3211 acylic
hydrocarbons
3212 benzenes
toluene
3219 other
hydrocarbons
3220 alcohols
3230 carboxylic
acids
3240 nitrogen func.
comp.
3260 organiccomp.
nee
3271 sulphur(liquid)
3272 sulphuricacid
3273 ammonia
3274 sodium
hydroxide
Total
22,006
5,294
290
4,494
5,613
1,112
56
2,119
1,075
776
552
624
16,101
741
506
135
4
96
15,360
1,084
1,369
4,669
2,559
381
813
602
82
231
1,016
970
Internal
Inbound
Outbound
Upbound Downbnd
2,094
581
492
483
23
384
11
8
58
54
1,439
1
1
1,437
QQR
196
96
119
97
109
C.J
48
-|Q
30
40
860
45
48
58
4
37
3
438
181
47
53
0
0
53
32
6
2
Upbound
964
162
130
107
290
137
4
1
64
67
161
161
7
122
1
Downbnd
4,551
778
1
1,291
1,657
219
369
22
55
159
2,367
0
2,366
5
485
417
564
57
280
3
45
186
29
Through
Upbound Downbnd
6,508
1,526
92
691
1,863
519
51
571
767
241
124
63
5,789
151
71
6
75
5,638
134
99
3,015
589
252
374
242
5
35
352
6,320
2,010
67
1,793
1,057
207
5
538
271
20
131
221
5,587
588
436
129
3
20
5,000
559
362
814
908
45
57
299
30
132
800
549
Intra
Upbound Downbnd
487 222
86 106
62 10
198 7
2 1
126 90
4
4
462 243
462 243
33 156
197
33 43
EIIP Volume III
12.A-5
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Commodity
3275 inorg.
elem., oxides,
Shalogen
salts
3276 metallicsalts
3297 chemical
additives
3298 wood &
resin chem.
3299 chem.
products nee
Total crude
materials, inedible
exceptfuels
Subtotal forest
products, wood
and chips
4110 rubbers
gums
4189 lumber
4190 forest
products nee
Subtotal
soil, sand, gravel,
rock and stone
4432 limestone
4323 gypsum
4327 phosphate
rock
4331 sand&
gravel
4335 waterway
improve, mat
4338 soil &fill dirt
Subtotal iron
ore and scrap
4410 iron ore
4420 iron& steel
scrap
Subtotal
marineshells
4515marineshells
Subtotal
non-ferrous ores
and scrap
4650 aluminum ore
4670 manganese
ore
4690 non-ferrous
ores nee
Subtotal
sulphur, clay
and salt
4782 clay&
refrac. mat.
Subtotal slag
4860 slag
Total
230
61
1,184
2
407
3,003
13
3
2
8
1,029
390
57
7
496
73
6
558
115
443
68
68
1,119
1,058
51
11
16
16
108
108
Internal
Inbound Outbound
Upbound Downbnd Upbound Downbnd
9 1
504
286 4 9 205
29 4 21 86
1,136 98 1 15
n
o
768 53 1
^nn ^">
AC.Q n 1
m n
363 5
67
295 5
43
A1
3
3
2004
2004
3
3
Through
Intra
Upbound Downbnd Upbound Downbnd
99
10
332
9
98
1,239
3
3
2
2
140
9
131
1,067
1,043
19
5
3
3
19Q
42
106 199 43
169
51 5
Q
2
205
^ft
57
7
35
R^
g
50
39
12
25
9^
49
14
29
R
7
7
105
105
12.A-6
EIIP Volume III
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Commodity
Subtotal other
non-metal, min.
4900 non-metal
min. nee
Total primary
manufactured
goods
Subtotal paper
products
5110 newsprint
5120 papers
paperboard
Subtotal lime,
cementand glass
5210 lime
5220 cements
concrete
Subtotal
primary iron and
steel
products
5312 pigiron
5315 ferroalloys
5320 iSs primary
forms
5330 iSsbarsS
sheets
5360 iSsbarsS
shapes
5370 iSs pipeS
tube
5390 primary iSs
nee
Subtotal
primary non-ferrous
metal products
5421 copper
5422 aluminum
5429 smelted prod.
nee
5480 fab. metal
products
Subtotal
primary wood
products
5540 primarywood
prod.
Total food and
farm products
Subtotal grain
6241 wheat
6344 corn
6442 rice
6445 oats
6447 sorghum
grains
Total
91
91
1,856
14
14
0
101
3
98
1,638
281
81
68
568
274
246
121
97
2
1
8
86
5
5
736
347
116
7
200
11
13
Internal
Inbound Outbound
Upbound Downbnd Upbound Downbnd
0212
0212
297 2 1 277
n
n
88 0 0 0
88 0 0 0
209 0 0 272
206
1
9^7
100
1 4
1 4
1 1
1 1
16 5 15 61
Through
Intra
Upbound Downbnd Upbound Downbnd
23
23
106
10
10
69
3
9
5
26
9
5
12
27
2
2
24
247
92
48
7
24
-IQ
63
63
1 173
14
1A
3
3
1 Q88
72
70
4ft
542
239
mo
64
.
K
56
4
A
392
955
68
17fi
1 1
EIIP Volume III
12.A-7
-------
Commodity
Subtotal
oilseeds
6522 soybeans
Subtotal
vegetable
products
6653 vegetable oils
6654 vegetables &
prod.
Subtotal
processed grain
andanimalfeed
6746 wheatflour
6838 animalfeed,
prep.
Subtotal other
agricultural
products
6835 fish, prepared
6838 tallow,
animal oils
6861 sugar
6865 molasses
6871 coffee
6885 alcoholic
beverages
6887 groceries
6888 water&ice
6889 food
products nee
Total all
manufactured
equipment,
machinery and
products
7110 machinery
(notelec)
7210 vehicles &
parts
7230 ships & boats
7300 ordnances
access.
7500 textile
products
7600 rubbers
plasticpr.
7900 manufac.
prod, nee
Total
16
16
9
3
6
28
5
24
337
3
8
204
28
1
11
0
76
7
172
120
0
0
5
6
16
25
Internal
Inbound Outbound
Upbound Downbnd Upbound Downbnd
11
11
4 13 3
1
4 -|Q -I
16 1 2 48
Q
16 1 2 48
o
26 2 3 59
25 2 3 57
n
1
2
Through
Intra
Upbound Downbnd Upbound Downbnd
5
5
6
g
5
•a
2
139
3
124
2
0
4
7
51
13
0
3
15
20
3
0
4
A
130
79
27
n
1 1
5
32
21
o
c
3
1
2
12.A-8
EIIP Volume III
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Commodity Total
and scrap nee
scrap nee
Ton-miles 3,033,660
Internal (x100)
Tons All Traffic (x (1000)
Ton-miles All Traffic (x 1000
Inbound
Upbound Downbnd
29 509
29 509
32,842
159,544
103,254
) 3,356,592
Internal
Outbound Through Intra
Upbound Downbnd Upbound Downbnd Upbound Downbnd
3 5 -1
139,905 1,456,126 6,713
25,880 1,194,804 17,674
EIIP Volume III
12.A-9
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VOLUME III: CHAPTER 13
AUTO BODY REFINISHING
Draft
BMP Area Sources Committee
January 200O
Prepared by:
Eastern Research Group, Inc
1 6OO Perimeter Park
Morrisville, North Carolina 2756O
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
This document was furnished to the Emission Inventory Improvement Program and the
U.S. Environmental Protection Agency by Eastern Research Group, Inc., Research Triangle Park,
North Carolina. This report is intended to be a working draft document and has not been reviewed by
the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, and has not
been approved for publication. The opinions, findings, and conclusions expressed are those of the
authors and not necessarily those of the U.S. Environmental Protection Agency. Mention of company
or product names is not to be considered an endorsement by the U.S. Environmental Protection
Agency.
-------
CONTENTS
Section Page
1 Introduction 13.1-1
2 Source Category Description 13.2-1
2.1 Category Description 13.2-1
2.2 Process Description and Emission Sources 13.2-2
2.3 Factors Influencing Emissions 13.2-3
2.4 Control Techniques 13.2-3
3 Overview of Available Methods 13.3-1
3.1 Emission Estimation Methodologies 13.3-1
3.2 Available Methodologies 13.3-1
3.2.1 Volatile Organic Compounds 13.3-1
3.2.2 Hazardous Air Pollutants 13.3-3
3.3 DataNeeds 13.3-3
3.3.1 DataElements 13.3-3
3.3.2 Adjustments to Emissions Estimates 13.3-3
3.3.3 Point Source Corrections 13.3-5
3.3.4 Application of Controls 13.3-5
3.3.5 Spatial Allocation 13.3-6
3.3.6 Temporal Resolution 13.3-6
3.4 Projecting Emissions 13.3-7
4 Preferred Methods for Estimating Emissions 13.4-1
4.1 National VOC Emission Estimate 13.4-1
4.2 Preferred Method 13.4-1
El IP Volume III iii
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CONTENTS (CONTINUED)
Section Page
5 Alternate Methods for Estimating Emissions 13.5-1
5.1 Alternate Method 1 - Apportion National Employment Data 13.5-1
5.2 Alternate Method 2 - Apportion National Population Data 13.5-1
6 Quality Assurance/Quality Control (QA/AC) 13.6-1
6.1 Emission Estimate Quality Indicators 13.6-1
6.2 Data Attribute Rating System (DARS) Scores 13.6-1
6.3 Sources of Uncertainty 13.6-2
7 Data Coding Procedures 13.7-1
7.1 Process and Control 13.7-1
8 References 13.8-1
IV El IP Volume III
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FIGURES AND TABLES
Figure Page
13.4-1 Example Survey Questions 13.4-5
Tables
13.2-1 Estimated VOC Emission Reductions for Automotive Refinishing
Coatings 13.2-5
13.3-1 Preferred and Alternate Methods for Estimating Emissions from
Auto Body Refinishing 13.3-2
13.3-2 Data Elements Needed for Each Method 13.3-4
13.4-1 National VOC Emissions By Body Shop Size 13.4-3
13.4-2 VOC Parameters of Conventional (Pre-regulation) Auto Body
Refinishing Products 13.4-4
13.6-1 Preferred Method: Auto Body Refinishing Survey of Very Large
Shops 13.6-3
13.6-2 Alternate Method 1: Apportion National Employment Data 13.6-3
13.6-3 Alternate Method 2: Apportion National Population Data 13.6-4
13.7-1 AMS Codes for Auto Body Refinishing Operations 13.7-2
13.7-2 AIRS Control Device Codes 13.7-3
El IP Volume III
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
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VI El IP Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions from
automobile (auto body) refmishing operations. Section 2 of this chapter contains a general description
of the auto body refinishing category and an overview of available control technologies. Section 3 of
this chapter provides an overview of available emission estimation methods. Section 4 presents the
preferred emission estimation methods for auto body refinishing, and Section 5 presents alternative
emission estimation techniques. Quality assurance and quality control procedures are described in
Section 6. Data coding procedures are discussed in Section 7, and Section 8 lists all references cited in
this chapter.
This ESP chapter is one of a series of chapters developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of available
resources and skills, and different levels of needs for accuracy and reliability of their estimates. More
information about the ESP program can be found in Volume 1 of the ESP series, Introduction and
Use ofEIIP Guidance for Emissions Inventory Development.1
Throughout this chapter and other ESP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the source
categories that are the largest emitters; most likely to be subject to regulations or are already subject to
regulations; or require special effort because of some policy reason. Prioritization is particularly
important for area source inventories, because in some cases, a source category that is difficult to
characterize may contribute very little to overall emissions and attempting to prepare a high quality
estimate for that source category may not be cost effective.
ESP chapters are written for the state and local air pollution agencies, with their input and review. ESP
is a response to the U.S. Environmental Protection Agency's (EPA's) understanding that state and local
agency personnel have more knowledge about their inventory area's activities, processes, emissions,
and availability of information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best fits
their overall needs and constraints.
1 EIIP volumes area available at: http://www.epa.gov/ttn/chief/eiip/.
EIIP Volume III 13.1-1
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
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13.1-2 El IP Volume III
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SOURCE CATEGORY DESCRIPTION
2.1 CATEGORY DESCRIPTION
Auto body refinishing is the repairing of worn or damaged automobiles, light trucks, and other vehicles,
and refers to any coating applications that occur subsequent to those at original equipment manufacturer
(OEM) assembly plants. (Coating of new cars is not included in this category.) The majority of these
operations occur at small body shops that repair and refinish automobiles. This category covers solvent
emissions from the refinishing of automobiles, including paint solvents, thinning solvents, and solvents
used for surface preparation and cleanup. According to data published in 1994, nationwide solvent
usage in automobile refinishing was estimated to be 37.5 million gallons per year (Kline and Company,
1995). Data published in 1998 estimate that about 64,000 auto body shops were operating in the
United States (Dun and Bradstreet, 1998). Facilities performing these operations are classified with the
Standard Industrial Classification (SIC) code 7532 (establishments primarily engaged in the repair of
automotive tops, bodies, and interiors, or automotive painting and refinishing). Two parts of SIC code
7532 are top and body repair shops., which are establishments primarily engaged in the repair of
automobile tops and bodies with or without painting, and refinishing and paint shops, which include
establishments primarily engaged in automobile painting and refinishing. Coatings applied at OEM
assembly plants are classified with SIC code 3711, and are not included here.
Most auto refinishing jobs are performed as part of collision repair and involve only a small portion of a
vehicle, such as a panel or a spot on a panel ("spot" repair). About 17 percent of refinishing jobs
involve the entire vehicle. For a typical shop, approximately 90 percent of the work consists of spot
and panel repairing, and the entire vehicle is completely refinished only about ten percent of the time.
Shops specializing in repainting entire automobiles are referred to as "production" shops.
Auto body refinishing shops may be area or point sources, but the majority of shops are considered
area sources of emissions. Point source emissions must be subtracted from total emissions to produce
an estimate of auto body refinishing area source emissions.
EIIP Volume III 13.2-1
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
2.2 PROCESS DESCRIPTION AND EMISSION SOURCES
Auto body refinishing operations consist of four steps: (1) vehicle preparation, (2) primer application,
(3) topcoat application, and (4) spray equipment cleaning. The products and equipment used in these
steps are usually bought from distributors, also known as jobbers. Prior to any painting, the surface is
prepared, i.e., washed thoroughly with water and detergent and allowed to dry. It is then cleaned with
a solvent (generally a blend of toluene, xylene, and other petroleum distillates) to remove any wax,
grease, and dirt to ensure proper adhesion of the primer and topcoats. Solvents typically used are 100
percent volatile, with the volatile organic compound (VOC) content ranging from 5.8 pounds VOC per
gallon to 6.5 pounds VOC per gallon (EPA, 1994a). A tack cloth is often used as a final step to
remove any remaining dirt or debris prior to the coating application.
Next, the surface is primed to provide corrosion resistance, fill surface imperfections, and provide a
bond for the topcoat. Primers fall into four general categories: prepcoat, primer-surfacers, primer-
sealers, and sealers. A prepcoat is a metal conditioner that etches the surface and prevents flash
rusting, which can occur from base metal exposure to the atmosphere. Prepcoats have good corrosion
resistance and adhesion properties, but have little or no filling capacity. Primer-surfacers provide the
best filling or "build" properties for deep scratches or dents, but some of these provide limited corrosion
protection. They are frequently used over prepcoats. The three types of primer-surfacers are
nitrocellulose lacquer, acrylic lacquer, and alkyd enamel. Primer-sealers combine the corrosion
resistance and adhesion properties of prepcoats with some of the scratch-filling capacity of primer-
surfacers. Primer-sealers also add a sealing property needed when an old finish is being repainted.
This type of primer is typically enamel-based. Sealers differ from primer-sealers in that they cannot be
used as a primer and must be sprayed over a prepcoat, a primer-surfacer, or an old finish. Sealers are
acrylic lacquer-based products.
The third step is topcoat application, which consists of a series of coats applied over the primer.
Topcoat determines the final color and appearance of the refinished area. For optional results, topcoats
(as well as other coating applications) are typically applied in a spray booth, which minimizes the
possibility of dirt adhering to the wet coating. Metallic finishes and some other finishes require a two-
stage topcoat system, consisting of a basecoat and a clearcoat. Since most repairs are spot and panel
repairs, the refinisher is concerned with matching the OEM color as closely as possible. Paint mixing
machines are typically provided by the shop's paint supplier. These machines are capable of mixing
coatings to manufacturer's specifications to allow for precise matching. As paints fade, it becomes
increasingly difficult for refinishers to match OEM paints to the faded paint. OEM paints manufactured
after 1991 typically have more durability and less fading, which makes matching paints easier, but older
paints are more likely to fade. In some cases, the paint may be so faded that it is impossible to match
colors. Topcoats can be divided into four categories: acrylic lacquer, alkyd enamel, acrylic enamel,
13.2-2 EIIP Volume III
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Draft January 2000 CHAPTER 13- AUTO BODY REFINISHING
and polyurethane. Based on 1994 data derived from the Chemical Economics Handbook (SRI
International, 1997), acrylic lacquers accounted for 20 percent of topcoats, acrylic and alkyd enamels
20 percent, and urethanes 60 percent.
The last step in auto body refinishing is spray equipment cleaning. Spray equipment can be cleaned
manually or with gun cleaning systems specially designed for this purpose. Shops that do not have
spray gun cleaning systems usually rinse the outside of the gun and cup, add solvent to the cup, and then
spray the solvent into the air or into a drum set aside for spent solvent (EPA, 1994a). The cleaning
solvent is recirculated until it is too contaminated to use. Waste solvents are then disposed of by
evaporation or incineration, or are reclaimed via distillation. The EIIP chapter on solvent cleaning
contains a thorough description of equipment cleaning operations.
The breakdown of solvent usage and emissions among the four steps is approximately 2 percent for
vehicle preparation, 20 percent for primer application, 70 percent for topcoats, and 8 percent for
equipment cleaning (EPA, 1994a).
2.3 FACTORS INFLUENCING EMISSIONS
VOC emissions from automobile refinishing are influenced by several factors. Emissions from surface
preparation and coating applications are a function of the VOC content of the product used. Emissions
are also a function of the transfer efficiency of the spray equipment. Transfer efficiency is the percent of
paint solids sprayed that actually adheres to the surface being painted.
Equipment with lower transfer efficiency would require more material to be sprayed, thus, increasing
VOC emissions. Emissions from cleaning operations are dependent on the type of cleanup and
housekeeping practices used.
2.4 CONTROL TECHNIQUES
There are three main approaches for reducing VOC emissions from auto body refinishing shops: (1)
use of lower-VOC coatings, (2) increased transfer efficiency, and (3) use of enclosed equipment
cleaning devices. Specific control strategies for auto body refinishing operations include the following:
for vehicle preparation - using reduced-VOC cleaners and using a second detergent for cleaning; for
primer application - improving transfer efficiency of spray guns (e.g., high-volume, low-pressure, or
HVLP, spray guns), and using lower-VOC primers, such as waterborne primers and urethane primers;
for topcoat application - improving transfer efficiency of spray guns (HVLP spray guns) and using
reduced-VOC coatings; and for equipment cleaning - using a solvent recovery system. By using a
cleanup solvent recovery system, facilities of any size can reduce VOC emissions by about 15 percent.
EIIP Volume III 13.2-3
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
Reductions of 30 to 45 percent can be achieved when HVLP spray guns are used in place of
conventional air-atomizing spray guns (EPA, 1988). In addition, shops can use add-on controls for
their spray booths such as thermal incineration, catalytic incineration, and carbon adsorption. A control
efficiency of 90 percent or more can be achieved with the use of add-on controls (EPA, 1991a).
Although the use of these add-on controls is technically feasible, cost has been the primary limiting
factor. One 1990 reference estimated the annual operating cost of an incinerator at $120,000 and of a
carbon adsorber at $40,000 (EPA, 1990). These costs are prohibitive to body shops, one-quarter of
which have annual sales less than $100,000 (Babcox Publications, 1993). In addition, since small
facilities may not have spray booths, the add-on control techniques are not applicable to their situation.
Other housekeeping activities can also be used to reduce emissions from auto body refmishing
operations. These activities include using tight fitting containers, reducing spills, mixing paint to need to
avoid waste paint disposal, providing operator training, and maintaining rigid control of inventory.
On September 11, 1998, national EPA regulations were promulgated to control VOC emissions from
the use of automobile refinishing coatings. The regulations set specific VOC content limits on seven
categories of automobile refinish coatings. The VOC limits are to be met by the manufacturers of
refinish coatings that are manufactured on or after January 11, 1999. Table 13.2-1 provides the
approximate emission reductions that can be achieved based on the VOC limits set forth in the
September 11, 1998, rulemaking.
A few states also have regulations in place that require VOC content limits on coatings as they are
applied in body shops. In these states, body shops are usually required to keep extensive records on
coating usage and VOC content. Maximum Achievable Control Technology (MACT) standards
applicable to hazardous air pollutant (HAP) emissions for existing and new facilities engaged in
automobile and light-duty truck refinishing operations are scheduled to be promulgated before
November 15, 2000.
13.2-4 EIIP Volume III
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Draft January 2000
CHAPTER 13- AUTO BODY REFINISHING
TABLE 13.2-1. ESTIMATED VOC EMISSION REDUCTIONS FOR AUTOMOTIVE
REFINISHING COATINGS
Coating Category
Pretreatment Wash Primer
Primer/Primer Surfacer
Primer Sealer
Single/2-Stage Topcoats
Topcoats of 3 or more stages
Multicolored Topcoats
Specialty Coatings
Overall
Regulation VOC Content
Limit (lb/gal)a
6.5
4.8
4.6
5.0
5.2
5.7
7.0
Approximate Percent
Reduction in Emissions b
0
55
75
40-70C
30
Not Available
0
37
a Federal Register, 1998.
b EPA, 1995.
0 The percent reduction ranges from about 70 percent for lacquers to approximately 40 percent for all other topcoats.
El IP Volume III
13.2-5
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
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13.2-6 EIIP Volume III
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
There are several methodologies available for calculating emissions from auto body refinishing. The
selection of a method to use depends on the degree of accuracy required in the estimate, the available
data, and the available resources. Estimating emissions accurately depends on accurately estimating the
amount and type of coating materials used. This section discusses the methods available for estimating
emissions from auto body refinishing and identifies the preferred method for this category.
3.2 AVAILABLE METHODOLOGIES
3.2.1 VOLATILE ORGANIC COMPOUNDS
Methods available for estimating emissions from auto body refinishing operations include conducting
surveys to collect activity (e.g., annual solvent and coatings usage), and apportioning a national estimate
to the local level by using a per employee or per capita emission factor. These methods are
summarized in Table 13.3-1.
Although theoretically it would be possible to conduct a survey to collect activity, product use, and
product-specific VOC content data to develop product-specific, site-specific detailed emissions
estimates, this approach is not practical due to resource and information availability at both the facility
and the inventorying agency levels, and to the variety of surface preparation, primers, coatings, and
cleaning products. For example, five companies (i.e., E.I. duPont de Nemours and Company, Inc.,
including Nason Automotive Finishes; PPG Industries; the Sherwin-Williams Company; BASF
Chemicals; and Akzo Coatings) account for about 95 percent of automobile refmish coating sales.
These five manufacturers also produce components such as catalysts, solvents (thinners or reducers),
and additives for use with their coatings. The remaining five percent of coatings are supplied by
approximately 12 smaller manufacturers. About two dozen other U.S. manufacturers produce lower-
cost coating components that are marketed for use with the coatings produced by the major
manufacturers (EPA, 1994a).
EllP Volume III 13.3-1
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CHAPTER 13-AUTO BODYREFINISHING
Draft January 2000
TABLE 13.3-1
PREFERRED AND ALTERNATE METHODS FOR ESTIMATING
EMISSIONS FROM AUTO BODY REFINISHING
Methods
Description
Preferred Method -
Apportion National Data
and Survey Very Large
Shops
Part I - Using information from Dun and Bradstreeta>b, apportion
the national estimate for each shop size category to the state or
county level by multiplying the national estimate by the ratio
local-to-national SIC code employment.
Part n - Survey shops with expected annual revenues greater
than $624,000 for annual coatings and solvent usage data.
Using the MSDS, calculate emissions for each facility and then
sum the emissions for the local level. This local estimate may
replace the estimate from Part I for very large shops.
Alternate Method 1 -
Apportion National Data
With Employment
Similar to the preferred method, except without the survey. If
Dun and Bradstreet data are not available, then County
Business Patterns0 can be used to apportion the national
estimate based on the ratio of local-to-national SIC code
employment.
Alternate Method 2 -
Apportion National Data
With Population
Similar to alternate method 1, except that population data from
the Bureau of Census is used instead of SIC code employment
for the ratio.
a Dun and Bradstreet data are available electronically on their Internet World Wide Web page at
http://www.dnb.com/. Note, there is a fee for accessing Dun and Bradstreet information.
b There are also alternate sources that provide auto body shop information. For example, American Business
Information (ABI) provides shop-specific information similar to Dun and Bradstreet; the difference is that ABI
only gives employment by size ranges for each shop instead of specific values (ABI/INFORM is a registered
trademark of Bell & Howell Information and Learning, Ann Arbor, MI).
c Annual County Business Patterns data are available electronically on the U.S. Census Internet World Wide Web
page at: http://www.census.gov/epcd/cbp/view/cbpview.html, and can be reached by phone at (301) 457-2580.
Individual manufacturers often market several lines of products, with each line containing a specific
series of surface preparation, primer, coating, cleaning, thinning, reducing, etc., products. Material
Safety Data Sheets (MSDS) are available from the manufacturers for each product in each line and
13.3-2
El IP Volume III
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Draft January 2000 CHAPTER 13- AUTO BODY REFINISHING
show the chemical species and percent (or range of percent) contribution of each species. These
MSDS can be used with information on amount of each specific product used from local surveys to
develop emission estimates. However, the level of effort required to complete a detailed survey to
collect the product-specific VOC content and use data may be a significant burden on the auto body
refinishing shop. Some coating suppliers may, however, have software programs that can assist shop
personnel in tracking this information. In addition, your agency may not have sufficient resources to
interpret, analyze, and compile these data.
Instead, surveys of the largest shops can be conducted to collect only general activity data (e.g., annual
usage of coatings and solvents). These survey data can then be used with MSDS to develop emission
estimates.
Another method for estimating emissions from auto body refinishing operations involves apportioning a
national estimate to the county level. The national estimate may be apportioned by using a ratio of
local-to-national SIC code employment, or population.
3.2.2 HAZARDOUS AIR POLLUTANTS
HAP emissions from this source are determined by the survey methods discussed above for VOC
emissions. Since the type(s) of HAPs present differ from product to product, developing a detailed
inventory may be very resource intensive. You may choose to forego some level of accuracy by
determining the most commonly used products in the inventory from the survey and assuming that the
HAP makeup of those products is representative of the product category in general. The emissions of
each HAP are assumed to be proportional to the amount of HAP in each product.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements needed to calculate emission estimates for auto body refinishing operations depend
on the methodology used for data collection. The data elements needed for each emission estimation
technique are presented in Table 13.3-2.
3.3.2 ADJUSTMENTS TO EMISSIONS ESTIMATES
Adjustments applied to annual emissions estimates include point source corrections, applications of
controls, spatial allocation, and temporal resolution. The type of adjustment is dependent on the type of
inventory required. The data needs for point source emission estimate adjustments
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CHAPTER 13-AUTO BODYREFINISHING
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TABLE 13.3-2
DATA ELEMENTS NEEDED FOR EACH METHOD
Data Element
Annual solvent and coatings usage for very large
shops
Material Safety Data Sheets (MSDS)
National and inventory area Dun and Bradstreet
employment data sorted by revenue for SIC
code 7532a
Annual Sales'3
National and inventory area County Business Pattern
employment data for SIC code 7532a
National and inventory area population from the U.S.
Bureau of the Census
Method
Preferred
X
X
X
xb
Altl
X
Alt 2
X
a SIC code 7532 (Top, body and upholstery repair shops and paint shops) includes establishments primarily
engaged in the repair of automobile tops, bodies, and interiors, or automotive painting and refmishing.
b This data element is used only for Part II of the Preferred Method. Revenue is then used to determine which
facilities will receive surveys.
are dependent in part on the methodology used. Data needs for the adjustments listed below are as
follows:
Point source corrections
Application of controls
point source emissions or point source employment for
inventory area for SIC code 7532
control efficiency; rule effectiveness; rule penetration
13.3-4
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• Spatial allocation employment; population; facility locale; rural/urban
population
Temporal resolution seasonal throughput; operating days per week;
operating hours per day
3.3.3 POINT SOURCE CORRECTIONS
The point source correction is performed by subtracting point source emissions for SIC code 7532
from the area source estimate.
Note however that employment in SIC code 7532 includes not only establishments primarily engaged in
automotive painting and refinishing, but also establishments involved in the repair of automotive interiors
(upholstery) and auto top (plastic and canvas) installation and repair.
3.3.4 APPLICATION OF CONTROLS
Section 3.8 of Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Volume I (EPA, 1991b) provides guidance for determining and applying rule
effectiveness (RE) for a source category. In addition, the EPA document Procedures for Estimating
and Applying Rule Effectiveness in Post-1987 Base Year Emission Inventories for Ozone and
Carbon Monoxide State Implementation Plans (June, 1989) provides more detailed information on
RE (EPA, 1989).
Sections 4.1.1 and 5.4 of the EPA procedures document (1991b) describe how to account for
emissions reductions expected to result from applying a regulation. If a regulation exists for auto body
refinishing in the inventory area and you use a "top down" approach to estimate emissions from this
category, you should incorporate an estimate of rule penetration.
If an area source is controlled (e.g., VOC content of surface coating products controlled by regulation),
the following general equations can be used to calculate emissions:
CAEA = (RA)CQ>[1 - (CE)(RP)(RE)] (13.3-1)
or
CAEA = (OAEA)[1 - (CE)(RF)(RE)] (13.3-2)
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
where:
CAEA = controlled area source emissions of pollutant A
RA = Ratio of local-to-national SIC code employment or population
Q = national estimate
CE = control efficiency/100
RP = rule penetration/100
RE = rule effectiveness/100
UAEA = uncontrolled area source emissions of pollutant A
3.3.5 SPATIAL ALLOCATION
If a survey, Dun and Bradstreet, or some other source is used to develop emission estimates for the
very large shops, then the spatial allocation of part of the emissions can be based on facility location, as
with the point source inventory, or with local employment data. If allocation is based on facility
location, you can use the address matching capability of a Geographical Information System to assign
map coordinates to shop locations. From these coordinates, shops can then be assigned to grid cells
for spatial allocations of emissions.
If you need to estimate emissions at the sub-county level, you should consider that the location of auto
body shops does not necessarily mirror the location of population within a county. You will need to
evaluate options for allocating county emissions, such as urban versus rural population (available from
U.S. Bureau of the Census publications), actual location data identified from surveys, etc.
3.3.6 TEMPORAL RESOLUTION
Seasonal Apportioning. In Procedures for the Preparation of Emission Inventories for
Carbon Monoxide and Precursors of Ozone, Volume I: General Guidance for Stationary
Sources, EPA (1991b) reports that auto body refinishing emissions do not seem to demonstrate
differences in activity from season to season. However, other references have indicated that since there
is a direct relationship between auto body refinishing activity and number of automobile accidents, if
there is a seasonal difference in accident occurrence, the same seasonal variation may be seen in auto
body refinishing activity. If time permits, you could review annual accident statistics to determine if any
seasonal variability exists for your inventory area. The National Safety Council annual publication,
Accident Facts provides this information.
Daily Resolution. From the EPA procedures document (199 Ib), auto body refinishing shops
typically operate five days per week. This figure may be used if local data on daily resolution are not
available.
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CHAPTER 13- AUTO BODY REFINISHING
3.4 PROJECTING EMISSIONS
The type of surrogate used to project emissions is dependent on the methodology used to develop the
initial emissions estimate. In "growing" the emissions estimate, you should use the same activity
parameter as was used to develop the initial estimate. For example, if a per capita factor was used to
develop the initial estimate, population growth should be used to develop the projected emissions
estimate. Any source survey conducted to gather information on auto body refinishing activity should
include questions on source growth and expected changes in factors that affect emissions (EPA,
1991b).
The equation for developing the projected emissions is:
G:
where:
EMIS
'PY
ORATEBYO =
EMF
PY,pe
RAT
PY,pc
RPpY
GF
projection year emissions: ozone season typical weekday (mass of
pollutant/day)
base year operating rate: ozone season daily activity level
emission factor (mass of pollutant per activity level)
ratio of local-to-national SIC code employment or population
projection year control efficiency (percent)
projection year rule effectiveness (percent)
projection year rule penetration (percent)
growth factor (dimensionless)
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PREFERRED METHODS FOR
ESTIMATING EMISSIONS _
The preferred method for estimating emissions from auto body refinishing operations involves
apportioning a national estimate to the local level for each shop size category, and surveying shops with
annual revenues in excess of $624,000 (i.e., very large size shops) for annual coatings and solvents
usage data. Emission estimates for the surveyed shops will replace those apportioned to very large
shops from the national estimate. Figure 13.4-1, at the end of this section, is an example survey
questionnaire for auto body refinishing facilities. The questionnaire should be modified to meet your
specific needs, but should contain sections for the following types of information: (1) identification,
including firm name, address, and contact, and type of facility, (2) number of employees, and (3)
annual coating and solvent usage based on user information.
4.1 NATIONAL VOC EMISSION ESTIMATE
A national VOC emission estimate of 79,429.39 tons per year has been developed using 1997 activity
and 1998 and 1999 emission rate information. Dun and Bradstreet sales and employment statistics for
auto body refinishing businesses were used to scale emission rates for equipment cleaning solvent use
from the Connecticut Department of Environmental Protection Bureau of Air Management (CT DEP,
1998); and to scale emission rates for coating applications from the Texas Natural Resources
Conservation Commission (TNRCC) (Smith and Dunn, 1999).
4.2 PREFERRED METHOD
Using the preferred method, the first step is to apportion the national estimate to the local level for each
shop size. This operation is shown by the following equation:
EAS = ^AS x (Pi "- Eg) (13.4-1)
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
where:
EAS = Local VOC emissions for shop size S (tons/year)
NBAS = National VOC emissions for shop size S (tons/year)
Ej = Number of employees for SIC code 7532 in area of interest
EN = Number of employees for SIC code 7532 in U.S.
National emissions by shop size are shown in Table 13.4-1.
The second step in estimating emissions is to determine if the survey responses for very large shops
adequately represent the local activity. You can compare the survey responses to Dun and Bradstreet
employee counts for SIC code 7532 to estimate the coverage of the survey. If you believe the survey
results are a more accurate reflection of the activity for very large shops, then the survey-derived
estimates should replace the estimates apportioned to very large shops from the national estimate.
Using the preferred method, the equation for estimating emissions for each specific auto body refinishing
product at each very large shop:
EA = PE x 4 x 12 x Cs "- 2.000 Ibc/ton (13.4-2)
where:
EA = VOC emissions (tons/year)
Px = Amount of product x used in quarts (from survey) per month
Cx = VOC content of product x in pounds per gallon (from MSDS)
The emission totals from all products and shops would then be summed to develop total emissions for
all very large shops.
Depending on the quality of the survey responses, you may need to modify the source of Cx, the VOC
content of product x. If you do not have the resources or the survey responses do not provide
sufficient data to evaluate each MSDS for each product to develop VOC content values, you may
calculate emissions using average or default values for product categories (e.g., pretreatment, precoat,
base coats, etc.). Table 13.4-2 provides data on VOC range (in pounds per gallon), and average
VOC content (in pounds per gallon) by product category.
Be sure to account for point source emissions by subtracting point source emissions from the total
emissions estimate developed through this preferred method.
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Draft January 2000
CHAPTER 13- AUTO BODY REFINISHING
TABLE 13.4-1
NATIONAL VOC EMISSIONS BY BODY SHOP SIZE
Body Shop
Size
Small
Medium
Large
Very Large
Average
Annual Revenue/
Shop
<$104,000
$104,000-364,000
$364,000 - 624,000
>$624,000
Total
National Annual
VOC Emissions
from Coating
Applications (tpy)a
6,401.49
22,426.94
4,166.96
6,733.55
39,728.94
National Annual
VOC Emissions
From Equipment
Cleaning (tpy)b
4,753.65
18,671.85
5,791.65
10,483.50
39,700.65
Total National
Annual VOC
Emissions (tpy)
11,155.14
41,098.79
9,958.61
17,217.05
79,429.59
a Estimate is for all shops this size in the U.S. based on data collected in 1999.
b Estimate is for all shops this size in the U.S. based on data collected in 1998.
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CHAPTER 13-AUTO BODYREFINISHING
Draft January 2000
TABLE 13.4-2
VOC PARAMETERS OF CONVENTIONAL (PRE-REGULATION) AUTO BODY
REFINISHING PRODUCTS (EPA, 1988; EPA1994a)
Category
Pretreatment
Primers
Prepcoat
Primer/Primer-Surf acer
Primer-Sealer
Coatings
Single Stage - Lacquer
Single Stage - Enamel
Basecoat
Acrylic Lacquer
Acrylic Enamel
Clearcoat
Acrylic Lacquer
Acrylic Enamel
Specialty Coatings
Surface Cleaners
Cleanup
VOC Range
(Ib/gal)
5.8-6.5
4.6-7.1
4.6-7.1
5.0-6.7
5.8-6.7
4.8-6.0
5.8-6.7
N/A
N/A
4.6-6.7
N/A
N/A
N/A
6.2-7.3
6.2-7.3
Average VOC
Content (Ib/gal)
6.3
5.8
5.7
6.3
6.3
5.6
6.2
6.3
5.3
5.2
6.4
5.6
7.0
6.75
6.75
N/A = Not available.
Assumes 0.25 pints of surface preparation products are used per job (EPA, 1994a).
13.4-4
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Draft January 2000 CHAPTER 13- AUTO BODY REFINISHING
Auto Refinishing Questionnaire
A. Identification
Firm Name:
Mailing Address:
City: State Zip.
Street Location:
Business Telephone Number: £_
Respondent's Name:
Respondent's Title:
2. Please indicate which type of operation is your primary function.
A. New and Used Car Dealership C. Auto Refinishing Shop
B. Used Car Dealership D. General Automotive Repair Shop
E. Other (specify)
3. Do you provide autobody refinishing services at this location?
01 .. .YES"* CONTINUE to B.I. 02 . . NO STOP. Thank you for your
time. Return the questionnaire in
the envelope provided.
4. How many total employees do you currently have working at this shop location?
Number of employees:
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
Figure 13.4-1. Example Survey Questions
B. Solvent and Coatings Usage
1. We need to know about the amount of volatile organic compound (VOC)-containing material your
shop is using. This is the most important question in this survey. Ask your distributor or
jobber to help you with any of this information.
We would like to obtain information about your paint and solvent usage during one month.
Specifically, we are interested in the quantity of surface preps, primers, surfacers/fillers, sealers,
topcoats (single and base/clear), thinners/reducers, hardeners, catalysts, newly purchased cleaning
solvent, and other solvent-based products used and their VOC content.
This information can be provided using Table 1. Please enter the time period for your
information on the line at the top of the table. The table is organized into columns that are
described below. An example is shown in the first few lines of the table; start your shop's
information in the next available space.
Column 1: Category. A definition of the general class of solvent-containing materials used in
your shop such as topcoats, surface preps, primers, surfacers, fillers, sealers, thinners, reducers,
hardeners, catalysts, and cleaners.
Column 2: Name and/or Specific Identifier. Identification of the specific products used in your
shop. At a minimum, we would like the manufacturer's name (e.g., DuPont, BASF, ICI
Autocolor, PPG Industries), the material ID or product number, and a brief description of the
product (color and/or paint type).
Column 3: Quarts Used The number of quarts ofthe material used duringthe month reported.
Column 4: How the Quarts Used Were Estimated How you calculated the number of quarts
of material. Examples include: "summarizing customer invoices," "monthly material inventory," and
"best guess."
Column 5: VOC Content. This information can be found on the label for each material.
Alternatively, we can determine this information if you provide the product manufacturer's name
and ID/product number.
C. Control Equipment
Various equipment is available to control VOC emissions in work areas (i.e., carbon filters,
incinerators). Does this body shop use any of this equipment? If so, please describe the
equipment.
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Draft January 2000 CHAPTER 13- AUTO BODY REFINISHING
Figure 13.4-1. Example Survey Questions (Continued)
EIIP Volume III 13.4-7
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m
T5
I
CD
TABLE 1. Information for the Time Period
^
era'
H
i
~&.
rtT
C
o
c
re
=
o
P4-
a'
c
LIST YOUR SHOP'S INFORMATION IN THE SPACES BELOW
Column 1
Category
Surface Preps
Primers/sealers
Surface/fillers
Topcoats
Hardeners/catalysts
Newly- purchased
cleaning solvents
Column 2
Name and/or Specific Identifier
Column 3
Quarts Used
Column 4
How the Quarts
Used Were
Estimated
Column 5
VOC Content
(pounds/gallon)
I
I
o
§
Co
C
3
DO
O
NOTE: DON'T FORGET TO PUT THE MONTH AND YEAR FOR THIS INFORMATION
rn
~
co
a:
-------
ALTERNATE METHODS FOR
ESTIMATING EMISSIONS _
5.1 ALTERNATE METHOD 1 -APPORTION NATIONAL EMPLOYMENT
DATA
This method is identical to the preferred method except that survey data are not included in the
development of the estimate. Equation 13.4-1 is applicable for this method, with the following
modification: if only County Business Patterns data are available (i.e., Dun and Bradstreet data are not
available), then instead of calculating emission estimates for each shop size, a single estimate for all shop
sizes will result from Equation 13.4-1. County Business Patterns data do not contain revenue data, so
emissions cannot be determined for each "revenue-based" shop size category. Dun and Bradstreet
data is the preferred source for developing emissions using this method; however, limited resources on
the part of the inventorying agency may prevent it from being used.
5.2 ALTERNATE METHOD 2 - APPORTION NATIONAL POPULATION DATA
This method is similar to the alternate method 1 except that instead of using employment data to allocate
a national emissions estimate, population data from the Bureau of Census are used:
EA = UEA x (Pj i- PK) (13.5-1)
where:
EA = Local VOC emissions
NEA = National VOC emissions
Pj = Population of the area of interest
PN = U.S. population
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QUALITY ASSURANCE/
QUALITY CONTROL (QA/AC)
Data collection and handling for the auto body refmishing source category should be planned and
documented in the Quality Assurance Plan. When using survey methods, the survey planning and data
handling should also be documented. Refer to the discussion of survey planning and survey QA/QC in
Chapter 1, Introduction to Area Source Emission Inventory Development, of this volume, and
Volume VI, Quality Assurance Procedures, of the Emission Inventory Improvement Program (EIIP)
series. Potential pitfalls to avoid when developing emission estimates by using a survey for this category
are data gaps due to surveys not returned, unanswered or misunderstood survey questions,
inappropriate assumptions used to compensate for missing information or scaling up the survey sample,
errors in compiling the relumed survey information, and calculation errors which can include unit
conversion errors, and data handling errors.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
In this chapter, one preferred and two alternate methods are presented. In the preferred method,
activity level is the amount of product used by large shops, and is being collected by a survey.
Alternate Methods 1 and 2 recommend scaling the national VOC emissions estimate to the local level
using either employment or population.
6.2 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 13.6-1 through 13.6-3. A range of
scores is provided for the method that uses surveys because the implementation of this method can
vary. The higher scores assume that reliable data were collected specifically for the inventory area, the
inventory time period, and the full range of very large auto body refinishing operations and few, if any,
assumptions or generalizations have been made in using the data gathered. All scores assume that
satisfactory QA/QC measures are performed and no significant deviations from good inventory practice
have been made. If these assumptions are not met, new DARS scores should be developed according
to the guidance provided in the QA volume.
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
The survey of products used for the inventory area and time period by large shops, the preferred
method, has the highest potential BARS scores (Table 13.6-1). This method also requires the most
effort, because this category includes many facilities, which can be difficult to include in a survey even
when limited to only very large shops. Ranges in the scores for this method are based on the
completeness of the survey used for this category. Spatial and temporal scores are highest when local
product usage data are collected because the national emissions do not take into account the effects of
local rules or work practices. Temporal scores can be improved if new emissions data are developed
from the most recent data available when the inventory is undertaken. The auto body refinishing
industry is changing rapidly, and new paint formulations mean that emission estimates for the industry
should go down. The industry has also enjoyed technological advances in high efficiency equipment like
HVLP guns, whose improved efficiency has reduced paint use emissions.
Tables 13.6-2 and 13.6-3 provide DARS scores for the two alternate methods. The level of effort
required for each method goes down as the DARS score for the method becomes smaller. For this
category, activity surrogates such as employment and population are not necessarily very specific to
activity in the category, which may be influenced more by population density, climate, and economic
factors. Given the uncertainty associated with this industry overall, however, they can be used unless
more refined estimates are needed.
6.3 SOURCES OF UNCERTAINTY
Another way to evaluate the emission estimates is to examine the associated uncertainty. For estimates
derived from survey data, the uncertainty can be quantified (see Chapter 4 of Volume VI of the EIIP
series). Statistics needed to quantify the uncertainty of emissions derived by emission factor methods
are incomplete.
Sources of uncertainty in estimating emissions from this source category include the difficulty of
collecting information that truly represents auto body refinishing operations, variability in the types and
amounts of products used, and the rapidly changing level of emissions from the industry. Emissions will
decrease as higher VOC products can no longer be manufactured because of the federal rule that
applies to the VOC content of coating manufactured on or after January 11, 1999. When using a
national average, state- or local-level rules, product formulations, or frequency of repairs may increase
the uncertainty of the emission estimate.
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CHAPTER 13- AUTO BODY REFINISHING
TABLE 13.6-1
PREFERRED METHOD: AUTO BODY REFINISHING SURVEY OF VERY LARGE SHOPS
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.5
0.7-0.8
0.6
0.7
0.63 -0.65
Activity
0.6-0.8
0.7
0.6 - 07
0.7-0.8
0.65-0.75
Emissions
0.30-0.40
0.49-0.56
0.36-0.42
0.49-0.56
0.41 -0.49
TABLE 13.6-2
ALTERNATE METHOD 1: APPORTION NATIONAL EMPLOYMENT DATA
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.5
0.7
0.6
0.7
0.63
Activity
0.7
0.6
0.6
0.7
0.65
Emissions
0.35
0.42
0.36
0.49
0.41
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Draft January 2000
TABLE 13.6-3
ALTERNATE METHOD 2: APPORTION NATIONAL POPULATION DATA
Attribute
Measurement
Source Specificity
Spatial Congruity
Temporal Congruity
Composite Scores
Scores
Factor
0.5
0.7
0.6
0.7
0.63
Activity
0.6
0.3
0.5
0.7
0.53
Emissions
0.30
0.21
0.30
0.49
0.33
13.6-4
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DATA CODING PROCEDURES
This section describes the codes available to characterize auto body refinishing emission estimates.
Consistent categorization and coding will result in greater uniformity among inventories.
7.1 PROCESS AND CONTROL CODES
The process codes for auto body refinishing operations are shown in Table 13.7-1. These codes are
compatible with the AIRS AMS source category codes (EPA, 1994b). The control codes for use with
AMS are shown in Table 13.7-2. Federal, State, and local regulations can be used as guides to
estimate the type of control used and the level of efficiency that can be achieved. Be careful to apply
only the regulations that specifically includes area sources. If the regulation is applicable only to point
sources, it should not be assumed that similar controls exist at area sources without a survey. The
"099" control code can be used for miscellaneous control devices that do not have a unique
identification code. The "999" code can be used for a combination of control devices where only the
overall control efficiency is known.
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CHAPTER 13 -AUTO BODY REFINISHING
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TABLE 1 3.7-1
AMS CODES FOR AUTO BODY REFINISHING OPERATIONS
Category Description
Process Description
Auto Body Refinishing: SIC Code 7532
All Solvent Types
Acetone
Butyl Acetate
Butyl Alcohols: All Types
n-Butyl Alcohol
Isobutyl Alcohol
Diethylene Glycol Monobutyl Ether
Diethylene Glycol Monoethyl Ether
Diethylene Glycol Monomethyl Ether
Ethyl Acetate
Ethylene Glycol Monoethyl Ether
(2-Ethoxyethanol)
Ethylene Glycol Monomethyl Ether
(2-Methoxyethanol)
Ethylene Glycol Monobutyl Ether
(2-Butoxyethanol)
Glycol Ethers: All Types
Isopropanol
Methyl Ethyl Ketone
Methyl Isobutyl Ketone
Special Naphthas
Solvents: NEC
AMS Code
24-01-005
24-01-005-000
24-01-005-030
24-01-005-055
24-01-005-060
24-01-005-065
24-01-005-070
24-01-005-125
24-01-005-130
24-01-005-135
24-01-005-170
24-01-005-200
24-01-005-210
24-01-005-215
24-01-005-235
24-01-005-250
24-01-005-275
24-01-005-285
24-01-005-370
24-01-005-999
Units
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
Tons Consumed
13.7-2
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CHAPTER 13- AUTO BODY REFINISHING
TABLE 1 3.7-2
AIRS CONTROL DEVICE CODES
Control Device
Catalytic Afterburner
Catalytic Afterburner with Heat Exchanger
Direct Flame Afterburner
Direct Flame Afterburner with Heat Exchanger
Carbon Adsorption
Miscellaneous Control Device
Combined Control Efficiency
Code
019
020
021
022
048
099
999
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8
REFERENCES
Babcox Publications. 1993. 1993 Annual Industry Profile.
Collision Repair Industry. 1991. Repair in the 90's. Insight 1:5.
Connecticut Department of Environmental Protection (CT DEP). 1998. Auto Body Refinishers
Emission Factor. Letter and attached memorandum from Carmine DiBattista, Connecticut
Department of Environmental Protection to Michael Kenyon, United States Environmental Protection
Agency, Region 1.
Department of Commerce. Annual Publication County Business Patterns. U.S. Department of
Commerce, Bureau of the Census, Washington, DC.
Dun and Bradstreet. 1998. The Dun andBradstreet Businesses Database. Dun and Bradstreet,
Inc., New York, New York.
EPA. 1995. Volatile Organic Compound Emissions from Automobile Refinishing - Background
Information for Proposed Standards - Draft. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, EPA-453/D-95-005a. Research Triangle Park, North Carolina.
EPA. 1994a. Alternative Control Techniques Document: Automobile Refinishing. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards, EPA-453/R-94-031,
Research Triangle Park, North Carolina.
EPA. 1994b. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, North Carolina.
EPA. 1993. Guidance for Growth Factors, Projections, and Control Strategies for the
15 Percent Rate-of-Pr ogress Plans. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, EPA-452/R-93-002. Research Triangle Park, North Carolina.
EllP Volume III 13.8-1
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CHAPTER 13 -AUTO BODY REFINISHING Draft January 2000
EPA. 1991 a. Compilation of Air Pollutant Emission Factors - Volume I: Stationary Point and
Area Sources. Fifth Edition and Supplements, AP-42. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina. September 1991. Internet:
http://www.epa.gov/ttn/chief/ap42pdf/c4s02_l.pdf. January 4, 2000.
EPA. 1991b. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Volume I: General Guidance for Stationary Sources. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, EPA-450/4-91-016. Research
Triangle Park, North Carolina.
EPA. 1990. OAQPS Control Cost Manual. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, EPA-450/3-90-006. Research Triangle Park, North Carolina.
EPA. 1989. Procedures for Estimating and Applying Rule Effectiveness in Post-1987 Base Year
Emission Inventories for Ozone and Carbon Monoxide State Implementation Plans. U. S.
Environmental Protection Agency, Research Triangle Park, North Carolina.
EPA. 1988. Reduction of Volatile Organic Compound Emissions from Automobile Refinishing.
U.S. Environmental Protection Agency, Control Technology Center, EPA-450/3-88-009. Research
Triangle Park, North Carolina.
Federal Register. September 11, 1998. National Volatile Organic Compound Emission Standards
for Automobile Refinish Coatings. Office of the Federal Register, Washington, D.C. Volume 63, Page
48806.
Kline and Company. 1995. Paint and Coatings "2000": Review and Forecast. Prepared for the
National Paint and Coatings Association, Fairfield, New Jersey.
National Safety Council, Chicago, IL. Annual Publication. Accident Facts. Annual publication.
Tel: (708) 285-1121, 1121 Spring Lake Drive, Itasca, Illinois 60143.
Smith, K. and K. Dunn. 1999. VOC Emissions from Autobody Shops. Draft report prepared for the
Texas Natural Resources Conservation Commission.
SRI International. 1997. Chemical Economics Handbook. Menlo Park, California.
13.8-2 EHPVolumelll
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VOLUME III: CHAPTER 14
TRAFFIC MARKINGS
Final
May 1997
Prepared by:
Eastern Research Group
Post Office Box 2010
Morrisville, North Carolina 27560-2010
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Lucy Adams of Eastern Research Group, Inc. for the Area
Sources Committee of the Emission Inventory Improvement Program and for Charles Mann of
the Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency.
Members of the Area Sources Committee contributing to the preparation of this document are:
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Carolyn Lozo, California Air Resources Board
Kwame Agyei, Puget Sound Air Pollution Control Agency
Mike Fishbum, Texas Natural Resource Conservation Commission
Gwen Judson, Wisconsin Department of Natural Resource
George Leney, Allegheny County Health Department
Charles Masser, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Linda Murchison, California Air Resources Board
Sally Otterson, Washington Department of Ecology
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Jim Wilkinson, Maryland Department of the Environment
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CONTENTS
Section Page
1 Introduction 14.1-1
2 Source Category Description 14.2-1
2.1 Emission Sources 14.2-1
2.2 Factors Influencing Emissions 14.2-2
2.2.1 Process Operating Factors 14.2-2
2.2.2 Control Techniques 14.2-2
3 Overview of Available Methods 14.3-1
3.1 Emission Estimation Methodologies 14.3-1
3.2 Available Methodologies 14.3-1
3.2.1 Volatile Organic Compounds 14.3-1
3.2.2 Hazardous Air Pollutants 14.3-2
3.3 Data Needs 14.3-2
3.3.1 Data Elements 14.3-2
3.3.2 Application of Controls 14.3-3
3.3.3 Spatial Allocation 14.3-3
3.3.4 Temporal Resolution 14.3-4
3.3.5 Projecting Emissions 14.3-4
4 Preferred Method for Estimating Emissions 14.4-1
4.1 Survey Planning 14.4-2
4.2 Survey Preparation 14.4-3
4.3 Survey Distribution 14.4-5
4.4 Survey Compilation and Scaling 14.4-5
4.5 Emission Estimation 14.4-8
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CONTENTS (CONTINUED)
Section Page
5 Alternative Methods for Estimating Emissions 14.5-1
5.1 Volatile Organic Compounds 14.5-1
5.1.1 Alternative One: National Traffic Paint Sales andNPCA
Emission Factor 14.5-1
5.1.2 Alternative Method Two: Lane Miles Emission Factor 14.5-2
5.1.3 Alternative Method Three: Per Capita Emission Factor 14.5-6
5.2 Hazardous Air Pollutants 14.5-6
6 Quality Assurance/Quality Control 14.6-1
6.1 Emission Estimate Quality Indicators 14.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 14.6-1
6.1.2 Sources of Uncertainty 14.6-2
7 Data Coding Procedures 14.7-1
7.1 Process and Control Codes 14.7-1
8 References 14.8-1
iv Volume III
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FIGURES AND TABLES
Figure Page
14.4-1 Survey Request Form for Traffic Markings State and County Highway
Departments 14.4-6
Table Page
14.2-1 Comparison of Estimated VOC Emissions 14.2-3
14.2-2 Advantages and Disadvantages of Alternative Traffic Marking Materials 14.2-4
14.4-1 Emission Factors for Traffic Markings 14.4-4
14.4-2 Traffic Markings Data Request Form 14.4-7
14.4-3 HAP Species Profiles for Traffic Markings 14.4-12
14.5-1 Quality and Value of Shipments of Paint and Allied Products:
1994 and 1993 14.5-3
14.5-2 Lane Mile VOC Emission Factors 14.5-5
14.6-1 Preferred Method DARS Scores: Survey of State and County Highway
Departments Coating Use in the Inventory Region 14.6-3
14.6-2 Alternative Method 1 DARS Scores: Activity Apportioned from the Inventory
Year National Level Applied to NPCA 1991 Emission Factors 14.6-3
14.6-3 Alternative Method 2 DARS Scores: Lane Miles Applied to 1988 CTC Emission
Factors 14.6-4
14.6-4 Alternative Method 3 DARS Scores: Activity Apportioned by Population
and Applied to NPCA 1991 Emission Factors 14.6-4
14.7-1 AIRS AMS Codes for Traffic Markings 14.7-2
14.7-2 AIRS Control Device Codes 14.7-3
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VI Volume III
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1
INTRODUCTION
This chapter describes the procedures and recommended approaches for estimating emissions
from traffic markings. Section 2 of this chapter contains a general description of the traffic
marking category and an overview of available control technologies. Section 3 of this chapter
provides an overview of available emission estimation methods. Section 4 presents the preferred
emission estimation method for traffic markings, and Section 5 presents alternative emission
estimation techniques. Quality assurance and control (QA/QC) procedures are described in
Section 6. Coding procedures used for data input and storage are discussed in Section 7, and
Section 8 is the reference section.
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14.1-2 Volume III
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SOURCE CATEGORY DESCRIPTION
Traffic marking operations consist of marking of highway center lines, edge stripes, and
directional markings and painting on other paved and nonpaved surfaces, such as markings in
parking lots. Materials used for traffic markings include solvent-based paints, water-based
paints, thermoplastics, preformed tapes, field-reacted materials, and permanent markers.
Solvent-based formulations of alkyd resins or chlorinated rubber resins are the most commonly
used traffic paints. This chapter focuses on applications of traffic paints that emit a significant
quantity of volatile organic compounds (VOCs). The use of traffic paints is entirely an area
source.
Traffic paints are applied by maintenance crews or by contractors during new road construction,
resurfacing, and other maintenance operations. The method of application is usually a spray.
The paints are subjected to harsher conditions than most other paints and must withstand wear
from tires, rain, sun, and other environmental factors for a considerable period of time.
Solvent- and water-based paints have roughly the same durability, with both beginning to
deteriorate about a year after their application. Both solvent- and water-based paints must be
applied in dry conditions and at temperatures above 40°F. If applied properly, water-based paint
is considered to be of better quality than solvent-based paint; however, application of water-
based paint is more susceptible to weather constraints such as humidity. Plastic-based paints
(i.e., thermoplastics, preformed tapes, and field-reacted systems) are more durable than either
solvent- or water-based paints.
2.1 EMISSION SOURCES
VOC emissions result from the evaporation of organic solvents during and shortly after the
application of the marking paint. Of the painting materials commonly used for traffic marking,
three types emit VOCs in appreciable amounts:
• Nonaerosol traffic paint, water- and solvent-based: Solvent-based paints include
aliphatic hydrocarbons, toluene, xylene, ketones, and chlorinated hydrocarbons.
Water-based paints contain some organic solvent components, usually emulsions
of glycols and alcohols; however, the VOC emissions are considerably lower than
those from solvent-based paints.
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• Aerosol marking paint, water- and solvent-based: These paints are used to apply
stripes or markings to outdoor surfaces, such as streets, golf courses, athletic
fields, or construction sites. Markings can be either temporary or permanent.
Chapter 5, of this volume, Consumer and Commercial Solvent Use, page A-9,
includes an emission factor of 0.0254 Ib/person for the use of these products.
Total annual emissions in the U.S. for this subcategory are estimated as
3,154 tons of reactive VOC per year. Emissions from these paints are not
included in this chapter.
• Preformed tapes applied with adhesive primer: Emissions from traffic marking
adhesives are included as part of Chapter 5, Consumer and Commercial Solvent
Use, on page A-7, under the subcategory of "other adhesives." Emissions from
these adhesives are not included in this chapter.
VOC emissions are negligible from application of some alternative paints including
thermoplastics, preformed tapes with no adhesive primer, and two-component, field-reacted
systems. In addition to the painting material used, VOCs from solvents utilized in cleaning the
striping equipment should be quantified in the category.
2.2 FACTORS INFLUENCING EMISSIONS
2.2.1 PROCESS OPERATING FACTORS
Emissions from traffic marking vary depending on the marking material used and the frequency
of application. Table 14.2-1 compares estimated annual VOC emissions for the different marking
types. These emission factors account for traffic marking applications that take place either more
frequently or less frequently than once a year, since a more durable marking material will
effectively emit less because it needs to be applied less frequently. Climate conditions and paint
durability, coupled with factors such as pavement type, traffic density, and position of the
marking, will influence the frequency of application.
2.2.2 CONTROL TECHNIQUES
Because the use of organic solvents in traffic markings is the primary source of emissions, control
techniques for this source category involve either product substitution or product reformulation.
Alternative formulations include low-solvent-content coatings, water-based coatings, and plastic-
based coatings. Because the performance requirements for different marking situations differ,
and because these materials have different physical and chemical properties and a wide range of
costs, different materials are advantageous for specific application situations. Table 14.2-2 lists
the advantages and disadvantages of various traffic marking materials.
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CHAPTER 14 - TRAFFIC MARKINGS
TABLE 14.2-1
COMPARISON OF ESTIMATED VOC EMISSIONS (EPA, 1988)
Marking Materials
Solvent-based (non-aerosol)
Water-based (non-aerosol)
Thermoplastic
Field-reacted
Polyester
Epoxy
Preformed Tapes
Without adhesive primer
With adhesive primer
Permanent Markers
Estimated VOC
Emissions (Ib/lane mile-yr)a
69b
13C
___d
___d
0.25
0
58e
0
a Mile refers to one 4-inch-wide solid stripe that is 1 mile long.
b Solvent-based paints typically consist of a resin, pigment, and various additives, all suspended
in an organic solvent. The average VOC content for solvent-based paints listed in this
reference is 3.15 Ib/gal.
c Water-based paints typically consist of latex emulsions which also include some organic
solvent. The average VOC content for water-based paints listed in this reference is 0.76
Ib/gal.
d Negligible.
e Adhesive primers for tapes are included in Chapter 5, Consumer and Commercial Solvent
Use.
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05/17/97
TABLE 14.2-2
ADVANTAGES AND DISADVANTAGES OF
ALTERNATIVE TRAFFIC MARKING MATERIALS (EPA, 1988)
Marking Material
Advantages
Disadvantages
Solvent-based Paints
Low initial cost
Good dry-night visibility
Short drying times available
Good equipment availability
Well-established technology
No pavement-type limitations
High VOC emissions
Short life
Poor wet-night visibility
Water-based Paints
Low VOC emissions
Low initial cost
Good dry-night visibility
Easy to adapt from solvent-based formulations
Easy cleanup
No pavement-type limitations
Poor wet-night visibility
Short life
Weather restrictions for application
Thermoplastics
Negligible VOC emissions
Long life
Good night visibility (wet & dry)
100 percent solids
High initial cost
High application temperature
Reduced durability on Portland cement
More difficult application than for
paint
Preformed Tapes
No VOC emissions if adhesive primer is not used
Long life
Little or no application equipment needed
Excellent material safety
100 percent solids
High VOC emissions if primer is used
Very high initial cost
Variable night visibility
Field-reacted Systems
Negligible VOC emissions
Long life
Moderate initial cost
Essentially 100 percent solids
Good night visibility
Polyester type adheres poorly to
Portland cement
Special application equipment needed
Permanent Markers
Negligible VOC emissions
Long life
Excellent night visibility (wet & dry)
High initial cost
Poor durability in snowplow areas
14.2-4
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
Several methodologies are available for calculating emissions from traffic markings. The method
used is dependent upon the degree of accuracy required in the estimate, available data, and
available resources.
This section presents the methods available for calculating emission estimates from traffic
markings and identifies the preferred calculation method. The data elements needed for each
method are also discussed.
3.2 AVAILABLE METHODOLOGIES
3.2.1 VOLATILE ORGANIC COMPOUNDS
The VOCs released into the air by traffic marking application are from the evaporation of the
VOCs contained in the coating. Determining the amount of the VOCs in coatings should provide
a good estimate of the VOC emitted by this source category. There are four approaches to
estimating the amount of VOC emitted from this source category:
Preferred Method: Survey of traffic marking use in the inventory area;
Alternative Method 1: Emissions based on Manufacturing Census data on paint
production, Federal Highway Administration data, and the national average per gallon
emission factor;
Alternative Method 2: Lane miles emission factor; and
Alternative Method 3: Per capita usage and the national average per gallon emission
factor.
The preferred method is the best approach for emissions estimation because it will most
accurately reflect the actual use, seasonal application, and content of traffic coatings in the
inventory area and, if requested in the survey, will include cleanup solvent estimates. If required
by the inventory, the level of detail provided by this method allows for greater accuracy in VOC
as well as hazardous air pollutant (HAP) emissions estimation and control strategy modeling.
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The alternative approaches do not provide the same level of detail as does the survey method in
terms of the specific amounts and types of paints used in the inventory area. This means that
information on the use of water- versus solvent-based coatings, or the amount and type of
cleanup solvents used is not available when the alternative methods are used. Alternative
Method 3 in particular does not take into account variability among regions, but will take into
account the variability of usage at the national level from year to year. The alternative methods
are best used if controls are limited or nonexistent and no further controls are anticipated for the
source category.
3.2.2 HAZARDOUS AIR POLLUTANTS
HAP emissions for this category can be estimated using two methods:
• Surveying traffic marking use in the inventory area; or
• Applying speciation profiles to the VOC emissions estimate, obtained by using
either the preferred or alternative methods for VOCs.
The survey method is the preferred method, because it will provide the most accurate information
on coating usage and HAP content of the coatings used. The effect of VOC controls on HAP
emissions will also be apparent when using this method.
Speciation profiles can be used as an alternate approach when conducting a detailed survey is not
practical. Although specific profiles will be provided in Section 5, updated or local speciation
profiles should be used when available.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements used to calculate emission estimates for this category will depend on the
methodology used for data collection. The data elements necessary for an emission calculation
that should be requested in a survey of state and county highway departments include:
• Product type;
• Product amount distributed by type (gallon) for the inventory period;
• Product density (pounds per gallon);
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05/17/97 CHAPTER 14 - TRAFFIC MARKINGS
• VOC and HAP content of each product, or solvent content by type, and VOC
percentage of solvents (weight percent) for each product;
• Information on the amount and type of cleanup solvent; and
• Information on disposal of unused products.
If an emission factor method is used, the following data elements are needed depending on the
chosen method: national or local coating usage, statistics for highway maintenance spending,
national and local population, number of lane miles in the inventory area, and a VOC emission
factor and HAP speciation profiles (both provided in Section 5). Emission factors may be
developed at the national or state level or representative sample subsection, then apportioned to
the inventory level.
3.3.2 APPLICATION OF CONTROLS
Because the use of controls will affect the VOC or HAP content of the coating itself, a survey of
coating usage and VOC or HAP content, or development of an emission factor from recent usage
data, will reflect controls that are in place. Because a reformulation or substitution represents an
irreversible process change and, thus, a reduction in emissions, rule effectiveness can be assumed
to be 100 percent for that coating type.
Rule penetration will be based on the weighted percentage of coatings within the inventory area
that are affected by the rule.
3.3.3 SPATIAL ALLOCATION
Spatial allocation is used in two cases in the preparation of an area source inventory: (1) to
allocate emissions or activity to the county level and (2) to allocate county-level emission
estimates or activity to a modeling grid cell. Allocation of emissions or activity to the county
level is addressed in the discussion of each preferred or alternative method.
Allocation of emission estimates or activity to a modeling grid cell level can be done using one of
three potential spatial surrogates, shown below in order of preference:
1. Use detailed information about the number of lane miles within each grid cell, or a
group of grid cells. This information may be available from inventory personnel
involved in estimating mobile source emissions or from county or state
departments of transportation.
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CHAPTER 14 - TRAFFIC MARKINGS 05/17/97
2. Use other land use data, if land use can be generalized to estimate the number of
lane miles. This information is usually available through county planning
departments.
3. Use population data, available from the U.S. Census Bureau.
3.3.4 TEMPORAL RESOLUTION
Seasonal Apportioning
Traffic marking use is influenced by the seasons, since spreading and drying characteristics for
many paints are dependent on temperature. Solvent-based traffic paints are usually applied only
when the temperature of the road surface is 50°F or higher. Best results from water-based paints
are achieved when they are applied when air temperature is 50°F or higher and there is low
humidity. The preferred method for seasonal apportioning is to survey state or local highway
departments. Because it can be assumed that seasonal usage is similar among all users in the
area, the survey sample can be small. If a survey is not practical, the seasonal activity factor for
the ozone season is 1.3 or 33 percent of annual activity (EPA, 1991). See Chapter 1 of this
volume, Introduction to Area Source Emission Inventory Development for more information
about using seasonal activity factors and seasonal apportioning.
Daily Resolution
Traffic marking application typically takes place 5 days a week during the active season.
3.3.5 PROJECTING EMISSIONS
A discussion about developing growth factors and projecting emission estimates can be found in
Section 4 of Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development. Projecting emissions for this source category will take two variables into account,
the change in activity (e.g., road miles painted, or gallons of paint used) and the change in the
formulations of paints and other marking materials used, which will determine the emission factor
that is used. Projected emission estimates may need to be calculated differently in the two
following cases:
Case 1: There are no controls and thus there is no change in the emission factor;
and
Case 2: There are controls in place for traffic markings, and emission reductions
are reflected in the emission factor.
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CHAPTER 14 - TRAFFIC MARKINGS
Each case uses a different projection equation. If there are no controls and no changes in the
emission factor, projected emissions are calculated using the following equation:
EMISPY = ORATEBY * EMF * GF
(14.3-1)
where:
EMIS
pY
EMF
GF
Projection year emissions
Base year activity rate
Emission factor
Growth factor
For Case 2, where controls are reflected in the emission factor, the equation would be:
EMISpY = ORATEBY * EMFpy *
200 - RPpY)
100
*GF
(14.3-2)
where:
EMF
PY
Projection year emission factor
Projection year rule penetration (%
Tools for the development and use of growth factors are discussed in Chapter 1 of this volume.
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14.3-6 Volume III
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
The preferred method for calculating emission estimates from traffic markings is to conduct a
survey of marking use by state and county highway departments, and city road maintenance
departments. The highway and road maintenance departments are responsible for the
predominant part of traffic coatings applied. Records should be accessible and information
should be sufficiently detailed to calculate VOC and HAP emissions. This section provides an
outline for preparing and using a traffic markings survey, and calculating emission estimates from
the information collected.
Survey planners are asked to refer to Section 2.1 of this chapter, Emission Sources, before
developing any survey. There are three types of traffic markings that have appreciable emissions,
traffic paints, aerosol traffic markings, and traffic tapes that use an adhesive primer. Of those
three, the traffic aerosols and traffic tape adhesives are discussed in Chapter 5 of this document,
Consumer and Commercial Solvent Use. A survey of traffic markings may include the use of
traffic tapes and possibly the use of aerosols, but if the survey results for those products are used,
then estimated emissions for the aerosol and adhesive subcategories of the consumer products
source category will need to be reduced to avoid double counting of emissions. However,
information about the proportion of adhesives or aerosol products that can be attributed to traffic
marking uses is not available.
Drawbacks to the survey method are that not all highway and maintenance departments may
keep records of coating usage. If highway and maintenance departments do not keep these
records, then using this method is not practical. Also, a survey of highway and maintenance
departments will not include markings used for parking lots by private contractors unless the
contractors are also surveyed. However, it is unlikely that a survey of contractors would be as
reliable as that of government highway departments for a number of reasons. First, the response
rate will likely be lower; second, they may not keep as complete or as detailed records; and third,
a contractor will do work over county or state boundaries and may not be able to estimate
coating use for just the inventory area. However, a national-level survey of traffic coating end
users shows that government highway departments are using 95 percent of the traffic coatings in
the United States (EPA, 1993).
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The final drawback to this method is that a well-planned, well-run survey requires more time,
effort and expense than a top-down approach. Inventory preparers must judge whether the costs
of this approach are outweighed by the benefit of having an estimate that is more specific to the
inventory area and time period.
Costs and labor efforts are highest for the first time that a regional or local survey of traffic
marking use is performed. Subsequent updates to the survey may be done using fewer samples at
much less cost. In the years following the baseline survey, updates on coating usage may be all
that is needed. Periodically, information on changes in formulations, methods of application, and
the percentages of different types of coatings used will be needed to accurately estimate
emissions.
Surveys for area sources are specifically discussed in Volume I of the Emission Inventory
Improvement Program (EIIP) series and in Chapter 1 of this volume. A survey of state and
county highway departments will consist of: (1) survey planning, (2) survey preparation,
(3) survey distribution, (4) survey compilation and scaling, and (5) emission estimation.
Discussion of these steps follows.
4.1 SURVEY PLANNING
During the planning phase, the following issues should be addressed:
• Survey data quality objectives (DQOs) should be identified, and how the DQOs
will be realistically reached specified.
• The survey recipients and data needs must be identified.
Information from the state and county levels may cover an area larger or
smaller than the inventory area. Should scaling be needed for survey
results, identify an available scaling surrogate (e.g., number of lane miles,
population).
In some cases, highway departments in several counties will arrange to
purchase paint and will contract with a private contractor to have the
painting done. During survey planning, this sort of situation should be
identified, an allocation approach will need to be defined, and data should
be collected for it.
When counties in the inventory area include extensive state or national
parks, military bases, or very large commercial properties which arrange
for their own traffic marking, the maintenance offices for these areas may
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need to be surveyed. However, these areas may not need to be surveyed if
the facility already reports traffic marking activities as part of a point
source inventory, or the amount of traffic marking at the facility is
proportionally small in comparison to the activity in the rest of the county.
If the usage of different types of coatings and solvents is known to be
consistent from county to county, a standard profile of product types can
be developed and the survey need only collect the total amount of coatings
and solvents used per county.
• Data handling needs specific to this survey must be identified.
• Survey QA/QC methods must be delineated and implemented.
The survey package should include a cover letter explaining the program, the survey form, a list
of definitions and a postage-paid return envelope. Both state and county highway departments
may need to be surveyed in order to collect information needed for the traffic markings category.
Additional disposal information may be collected as part of a waste disposal or recycling
category. The portion of emissions that correspond to recycled or discarded traffic coating
materials from the disposal or recycling category should be subtracted from the emission estimate
for traffic marking. This is necessary to avoid double counting.
4.2 SURVEY PREPARATION
A survey may be planned to collect either a detailed amount of data or only the minimum amount
needed for to estimate emissions. The minimum amount of information needed to calculate an
emission estimate is the number of gallons of solvent-based and water-based traffic paints used in
the inventory area or inventory county. The national averages of VOCs for solvent-based and
water-based traffic coatings can be multiplied by the number of gallons of each coating type to
estimate emissions. National averages of VOC content for types of coatings have been prepared
by the National Paint and Coatings Association (NPCA) (EPA, 1993) shown in Table 14.4-1.
A more detailed survey will request:
• Product type, including thinning and cleanup solvents;
• Product amount used by type (gallon);
• Product density (pound per gallon);
• Estimates of the proportion of products used during the inventory season; and
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• VOC or solvent content of each product type (pounds per gallon or weight
percent) for a VOC inventory, or, for a HAP inventory, HAP or solvent content
of each product type (pounds per gallon or weight percent).
Survey preparers should clearly define the time period that the survey information is being
collected for. A request for annual data, for instance, should specify the range of months to
avoid confusion between fiscal and calendar years. It is preferable to collect data specific to the
inventory period, but for periods less than 12 months, usage will probably have to be apportioned
by the inventory preparer.
If the survey results need to be scaled to a different spatial scale, or are expected to be adjusted
for future inventories, factors that may be useful to adjust the survey information may also be
collected. For example, the road miles or lane miles within the county that the department is
responsible for could be requested from that department. Road miles or lane miles may also be
available from mobile emissions inventory preparers. Then, a county-specific emission factor
based on the number of road miles or lane miles can be developed and used in future inventories.
TABLE 14.4-1
EMISSION FACTORS FOR TRAFFIC MARKINGS (EPA, 1993)a
Coating Type
Water-based coatings
Solvent-based coatings
National average, water- and solvent-based
VOC Content
(Ib/gal)
0.72
3.64
3.36
Data are based on a 1991 survey.
The advantages of the more detailed approach are that the inventory developed is more specific
to the locality, and the information collected can be more readily projected to inventories for
subsequent years.
Instructions for using the survey form are provided on the survey cover page, shown in
Figure 14.4-1. As shown in Table 14.4-2, respondents must first estimate the annual amount of
coatings as the amount stocked and VOC weight percent or pounds per gallon used in coatings,
less waste disposed of off-site or unused. For HAP inventories, material safety data sheets
(MSDS) for each product should be requested. This information can be combined with the
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05/17/97 CHAPTER 14 - TRAFFIC MARKINGS
coating and solvent density to yield the pounds of product used in a given year. HAP weight-
percent information can be derived from the MSDS provided with each coating.
An alternative survey-based method for a HAP inventory would use a representative sample of
the HAP contents for each product type, applied to a more complete inventory of traffic marking
types and usage.
4.3 SURVEY DISTRIBUTION
This method requires contact with every transportation department that uses traffic coatings in
the inventory area. Surveys can be distributed by mail, or the information can be collected
through a telephone survey. Initial contacts and follow-up contacts may also be undertaken as
part of the survey to answer any questions. Survey distribution issues are discussed in Chapter 1
of this volume.
4.4 SURVEY COMPILATION AND SCALING
Survey compilation and scaling issues are discussed in Volume I of this series. Completed
surveys will result in information that includes many types of coatings and multiple pollutants, so
compilation of this information will require planning for data transfer and data management.
Efficient transfer to the data handling system will benefit from inventory planner's consideration
of the data transfer step during the design of the survey.
QC checks should be performed during this phase of the work (see Volume VI for QA/QC
methods). Incoming surveys should be checked for errors such as potential unit conversion
errors or misidentification of products or chemicals. Survey information should be checked for
reasonableness. Compiled survey information should also be subject to similar checks. Survey
recipients may need to be recontacted in order to correct any errors.
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CHAPTER 14 - TRAFFIC MARKINGS 05/17/97
Name of Highway Department:
Street Address:
City:
Contact Person/Phone Number:
The purpose of this survey is to collect information about the amounts of traffic
paints used so that estimates of air pollution from the traffic paints can be made.
Please enter the following information on the attached form.
1. List the product types stocked in year . Product types should
include all traffic coatings and any solvents used for thinning or cleanup in
association with them.
2. Provide the weight percent of VOCs for each product or, if it is available,
provide the amount of VOCs, as pounds per gallon of product. Please
clearly mark the entry as a percent (%) or pounds per gallon (Ib/gal).
3. If the entry in Column B is weight percent, provide the specific gravity of
the product.
4. Provide the amount, in gallons, of each product stocked.
5. Subtract from the products listed under Column A any coating or solvent
that was disposed of off-site (Column E), lost as waste (spills, etc.) in
Column F, or portions that were unused (Column G). If only the total
amounts of these losses are known, split the total between the different
products.
6. Attach copies of the Material Safety Data Sheets (MSDSs) for all of the
products listed (for HAP inventories).
FIGURE 14.4-1. SURVEY REQUEST FORM FOR TRAFFIC MARKINGS
STATE AND COUNTY HIGHWAY DEPARTMENTS
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TABLE 14.4-2
TRAFFIC MARKINGS DATA REQUEST FORM3
A
Product Type
B
Product VOC
Weight Percent or
Pounds/Gallon
C
Specific
Gravity of
Product"
D
Amount
Stocked
in year
E
Amount
Disposed of
Off-site
F
Amount Lost
as Waste
G
Amount
Unused
Amount Used = D
- (E + F + G)
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a Volume of product expressed gallons unless otherwise noted.
b The specific gravity of the product is needed only if VOC content of the product is in weight percent.
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CHAPTER 14 - TRAFFIC MARKINGS 05/17/97
Depending on the recipients to the survey, results may need to be either scaled up for all counties
in the inventory area or scaled down to the inventory area. In either case, a scaling factor should
have been identified in the planning phase, and any necessary requests for information from the
survey respondents included on the survey form. Refer to Sections 3.3.3 Spatial Allocation, and
3.3.4 Temporal Resolution for more information about allocation and scaling factors for this
source category.
4.5 EMISSION ESTIMATION
Emission estimation calculations involve determining emissions of the pollutant(s) of interest, and
then the application of any necessary spatial or temporal adjustments. Because the application of
traffic markings is defined as an area source, there should not be a need to subtract point source
emission estimates from the total. Emission estimate calculations from the information collected
by survey require the following steps:
If pounds of VOC per gallon are not available, then emissions are calculated as follows:
• Multiply the specific gravity of the product by 8.34 Ib/gal, the density of water, to
get the product density.
• "4 (144-,)
Multiply the gallons of product used by the density to yield the pounds of each
product used.
Pounds of _ Gallons Product C\AA
Product ~ of Product * Density (14.4-
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For a VOC inventory, multiply the VOC weight percent by the pounds of product
for each coating or cleaning solvent. For a HAP inventory, identify the HAP
components from the coating MSDS and multiply the weight percent of each
HAP by the pounds of product for the coating or cleaning solvent.
Pollutant
p0uutant
Emissions = fr. , . * ,T7 • ,, 0/ (144-3)
,,,, of Product Weight % \i^.^ J)
Emissions for each product type should be calculated separately.
If pounds of VOCs per gallon for each product type is available, then VOCs are calculated as:
VOC Amount of VOCs per
Emissions = Product * Gallon (14 4-4)
(Ib) (gal) (gal)
Emissions for each product type should be calculated separately.
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Example 4-1
In this example, information on the pounds of VOCs per gallon of each type of coating
used in one county has been collected. The data collected and calculation for the total
amount of VOCs emitted for the county is shown below:
Example traffic coating usage for one county:
• 10,000 gallons yellow traffic paint; solvent-based, 3.21 Ib VOCs/gal
• 1,560 gallons white traffic paint; solvent-based, 3.26 Ib VOCs/gal
• 6,324 gallons yellow traffic paint; water-based, 0.54 Ib VOCs/gal
• 7,610 gallons white traffic paint; water-based, 0.69 Ib VOCs/gal
The calculation will be:
VOC Emissions
from = [(10,000 gal * 3.21 Ib/gal) + (1.560 gal * 3.26 Ib/gal) +
Traffic Coatings (6,324 gal * 0.54 Ib/gal) + (7,610 gal * 0.69 Ib/gal)]
= 45,852 Ib VOC
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Example 4-2
In this example, the HAP emissions from one paint type are calculated from the HAP
volume percent for that paint type and the HAP density. Representative HAP volume
percents and densities are shown in Table 14.4-3.
Emissions for carbon tetrachloride from traffic paint used in an area would be calculated:
Carbon tetrachloride emissions = 10,000 gal * 0.009 % * 12.19 (Ib/gal)
= 10.97 Ib
Emissions from each HAP from each type of paint are calculated as they are above, then
summed to get the total for all paint types.
Spatial allocation of emissions to individual counties or other inventory area units can be done by
proportioning emissions with a surrogate factor. Potential surrogate factors, in order of
preference, are lane mile data, land use data, or population.
Temporal allocation may be necessary if the inventory requires seasonal or daily emission
estimates, and is discussed in Section 3 of this chapter.
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05/17/97
TABLE 14.4-3
HAP SPECIES PROFILES FOR TRAFFIC MARKINGS
(EPA, 1993)a
HAP
Carbon tetrachloride
Cumene
Ethylbenzene
Ethylene glycol
Glycol ethers
Methyl ethyl ketone
Methyl isobutyl ketone
Methyl methacrylate
Naphthalene
Propylene oxide
Styrene
Toluene
Xylenes (mixed isomers)
Volume Percent
(%)
0.009
0.002
0.009
0.086
0.040
1.514
0.002
0.044
0.002
0.115
0.277
6.914
0.499
Density
(Ib/gal)
12.19
7.19
7.24
9.31
7.01
6.89
6.71
7.84
9.55
6.93
7.55
7.23
7.18
a Data based on a 1991 survey.
b These volume percent factors are based on the amounts of each HAP component in a sales-
weighted average traffic paint.
14.4-12
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
This section provides an outline for developing and using emission factors as alternative methods
for calculating emissions from traffic markings. Procedures for using the three alternative
methods described in Section 3 are provided in the following discussion.
5.1 VOLATILE ORGANIC COMPOUNDS
5.1.1 ALTERNATIVE ONE: NATIONAL TRAFFIC PAINT SALES AND NPCA EMISSION
FACTOR
This method uses NPCA per gallon emission factors multiplied by traffic paint usage values that
are specific to the inventory year, but are apportioned from the national level to the county level
in two steps. The national to state apportioning step proportions the amount of traffic paint by
the dollars spent on roads and highways in the inventory state. This information is available in
Federal Highway Administration reports, and is well suited as a surrogate for apportioning. The
apportioning approach of using dollars spent will reflect differences between states in the number
of lane miles in each state that the states have to maintain, differences in the types of roads in
each state, and variations between states in the levels of maintenance for roads. The federal
report does not provide this information for individual counties, so apportioning from the state to
the county level requires another surrogate. Paved lane miles or population are used in this
method because they are easily available, but other surrogates, such as state-generated,
per-county highway maintenance spending, or vehicle registration numbers can be used to
calculate a per-county estimate of traffic paint used.
The advantage to this method is that most of the information needed for the calculations should
be relatively simple to collect and manage. The disadvantage is that the estimate will not include
cleanup emissions (although thinning is included in the NPCA emission factor), and the usage
numbers will not be as specific as those from the survey method.
The steps needed to use the first alternative method are as follows:
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• Determine the amount of U.S. traffic paint usage for the inventory year. Use data
from the U.S. Census Bureau, Report MA28F-Paint and Allied Products.
a Table 14.5-1 is an example report.
• Apportion the national traffic paint usage to the state level based on spending for
highway maintenance. The Federal Highway Administration publishes Highway
Statistics annually.13 Table HF-2, Total Disbursements for Highways, All Units of
Governments, in the Highway Statistics publication will have the necessary
information.
• Apportion the state estimate of traffic paint usage to the county level using either
the proportion of the number of county paved lane miles to the number of state
paved lane miles, or by the proportion of county to state population. Using paved
lane miles as a surrogate is the preferred approach.
• If information is available on the proportion of solvent- versus water-based
coatings for the state or county, those proportions can be used to develop a local
emission factor from the NPCA solvent- and water-based coating factors in Table
14.4-1. Otherwise, the national average emission factor for both types of coatings
from the NPCA survey should be used. The equation for calculating emissions is:
_ _ . . NPCA Emission County Traffic / n . _ n x
VOC Emissions = Factor (lb/gal) * Paint T]sage (gal) (14-5-1)
Example 5-1 shows the calculation for a typical county.
5.1.2 ALTERNATIVE METHOD Two: LANE MILES EMISSION FACTOR
This method uses an emission factor for lane miles of road painted paired with local data. The
emission factors are from a 1988 Control Technology Center (CTC) report (EPA, 1988).
Emission factors for solvent- and water-based traffic paints, and for lane
a Total national coating usage is compiled by the Bureau of the Census, Report MA28F-
Paint and Allied Products, available from the U.S. Census Bureau, Department of
Commerce, Washington, D.C.
b Federal Highway Administration, U.S. Department of Transportation, Washington, D.C.
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TABLE 14.5-1
QUALITY AND VALUE OF SHIPMENTS OF PAINT AND ALLIED PRODUCTS: 1 994 AND 1 993
(QUANTITY IN THOUSANDS OF GALLONS; VALUE IN THOUSANDS OF DOLLARS)3
Product
Code
2851
28513 11
Product Description
Paint and allied products b
Traffic marking paints (all types, shelf goods anc
highway department
1994
Quantity
1,103,693
33,898
1994
Value
14,140,288
202,810
1993
Quantity
1,228,531
29,515
1994
Value
13,538,654
174,154
Source: U.S. Bureau of the Census Report MA28F-Paint and Allied Products.
Represents total shipments for those establishments producing paint and allied products that have 20 or more
employees. These establishments represent approximately 95 percent of the total value of shipments for Standard
Industrial Classification (SIC) industry 2851, paint, varnishes, lacquers, enamels, and allied products based on
relationships observed in the 1992 Census of Manufactures preliminary report.
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Example 5-1:
U.S. traffic paint sales totaled 29,515,000 gallons in 1993 (see Table 14.5-1).
According to the Federal Highway Administration's annualHighway Statistics report,
Table HF-2, total disbursements on roads and highways was $62,351,345,000, and
State A spent $1,115,435,000. Gallons of traffic paint are apportioned from the
national level to state level by:
State A Traffic = [$1,115,435,000/$62,351,345,000] * 29,515,000 gallons
Paint Usage
= 528,009 gallons
The amount of traffic paint is apportioned from the state to the county level using
population for County B and State A (77,055 and 6,386,600 people, respectively):
County B Traffic = [77,055/6,386,600] * 528,009 gallons
Paint Usage
= 6,370 gallons
In this case, no information is available about the proportions of solvent- versus water-
based paints used in the inventory area, so the national average emission factor
provided in Table 14.4-1 should be used. VOC emissions are calculated for County B
by:
County B VOC
Emissions from = 6,370 gallons paint * 3.36 Ib/gal
Traffic Paints
= 21,4031bVOCs
= 10.7 tons VOCs
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CHAPTER 14 - TRAFFIC MARKINGS
miles painted or total lane miles are shown in Table 14.5-2. If the number of lane miles that were
actually painted in the inventory year are available, a more specific estimatecan be made using the
factor for emissions per lane miles painted, in units of pounds per mile. If only the total lane
miles in the inventory area are available, then emission estimates can be estimated using the factor
for typical annual emissions, in units of pounds per mile and year. Lane miles painted data may
be available from state and county highway departments. Total lane miles data should be
available from state and county highway departments, or from air agency mobile inventory
preparers.
The emission factors for solvent-based paints should be used if there is no information about
whether solvent- or water-based paints are used. This will result in the most conservative
estimate. However, the preferred approach is to gather information about the proportions of
solvent-based versus water-based paint if at all possible. State or local rules may determine the
type of paint or other marking type that can be used within an area, or a small telephone survey
of a subset of highway departments may be used to define the proportions of paint type.
The equation used to calculate emissions using these emission factors is:
Inventory Area
Emissions from =
Traffic Paints
Emission Factor Traffic Lane
(Ib/lane mile) Miles Painted
(14.5-2)
If the lane mile data are available, this method has the advantage of being easy to use. However,
the method does not take into account any region-specific use of lower-emitting coatings, such as
water-based coatings or thermoplastic tapes. Using the typical annual emissions factor with total
lane miles also will not reflect area-specific repainting schedules.
TABLE 14.5-2
LANE MILE VOC EMISSION FACTORS (EPA, 1988)
Traffic Paint
Type
Solvent-based
Water-based
Typical Expected
Life (years)
0.75
1.0
VOC Emissions
Per Lane Mile
Painted (Ib/mile)
52
13
Typical Annual
VOC Emissions
(lb/mile-year)a
69
13
Mile refers to one 4-inch-wide stripe that is 1 mile long.
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5.1.3 ALTERNATIVE METHOD THREE: PER CAPITA EMISSION FACTOR
This method is a simplified version of Alternative Method One. A national average usage factor
of gallons per person is developed from U.S. Census data for the inventory year. The per capita
usage factor is multiplied by the NPCA per-gallon emission factor to calculate emissions. The
steps needed for this method are:
• Collect the necessary data: National traffic paint sales data, in gallons, from
U.S. Census Report MA28F-Paint and Allied Products, national population and
inventory area population figures for the inventory year, and the NPCA per-gallon
emission factor.
• Develop a national average per capita usage factor:
National National Traffic M , , T t
Per Capita _ p. TJ , National Inventory m S ^
Usage " paint Usage / Year Population (14.5-3)
/ i; x (gallons) F
(gal/person) vo
• Multiply the usage factor, the NPCA per gallon emission factor, and the inventory
area population to get the inventory area emission estimate:
itory Area National Per Capita NPCA Emission T
sions from = Usage Factor * Factor * p ^(14.5-4)
Fie Paints (gal/person) (lb/gal)
Popma*
The advantage of this method is that all of the information needed is easily obtained and the
calculations are simple. If this source category is a low priority in the inventory and no controls
are planned, this could be an appropriate method. However, limitations to this method are:
population is not the most accurate surrogate for traffic coatings because it does not take into
account the region-specific use of lower-emitting coatings, and the activity will not reflect
whether an area has a higher or lower level of maintenance.
5.2 HAZARDOUS AIR POLLUTANTS
HAP emissions are calculated by multiplying the county traffic paint usage amount by the HAP
volume percent (Table 14.4-3). The equation for this calculation is:
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w/™ T-, • • County Traffic HAP Volume HAP /1 . c c,
VOC Emissions „ . i TT * 0/ * „ (14 5-5)
Paint Usage % Density V1^--1 ->)
See Example 14.5-1 for an example calculation.
If Alternative Method Two is used, assume that 16 gallons of traffic paint of either type are used
for every lane mile counted (EPA, 1988).
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14.5-8 Volume III
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QUALITY ASSURANCE/QUALITY
CONTROL
When using the preferred method, the survey planning, sample design, and data handling should
be planned and documented in the inventory QA/QC plan. Refer to the discussion of survey
planning and survey QA/QC in Chapter 1 of this volume.
Data handling for the survey data and for data collected for the alternate methods should also be
planned and documented in the inventory QA/QC plan and do not involve any category-specific
issues. Please consult EIIP Volume VI on inventory QA/QC for more information.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
Surveys are theoretically the most accurate approach for estimating emissions, but also are the
most expensive. Advantages to using surveys are that region- or area-specific information about
the amount and type of traffic markings used will be collected. Markings surveyed will more
precisely reflect the regulations for VOCs that are in place in the inventory area. Emissions of
HAPs can be calculated based on the specific types of coatings in use in the area. The level of
detail that is possible to collect with a survey is not available when using the alternative methods.
The preferred method gives higher quality estimates than any of the alternative methods, but
requires significantly more effort. The level of effort required to calculate emissions using either
of the alternative methods ranges from 8 to 40 hours. Conducting a survey of state, county, and
city highway departments requires between 60 to 150 hours depending on the size of inventory
region and the desired level of detail of the survey. However, the resultant increase in the quality
may justify this expenditure of resources, especially if this category is believed to be a significant
contributor to emissions or is subject to regulations. Emissions from traffic markings are
typically among the top 15 area sources of VOCs and HAPs in urban areas.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for each method are summarized in Tables 14.6-1, 14.6-2, 14.6-3, and 14.6-4.
A range of scores is given for the preferred method and first alternative method to reflect
variability in survey techniques. A range of scores for spatial congruity is also given for the
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CHAPTER 14 - TRAFFIC MARKINGS 05/17/97
second alternative method to account for the use of either the more specific lane miles painted
activity or less specific total miles painted. In the case of the first alternative method, use of
more specific apportioning surrogates and more specific information about the types of paint
used in the area will improve the scores. All scores assume that good QA/QC measures are
performed and that no significant deviations from the prescribed methods have been made. If
these assumptions are not met, new BARS scores should be developed according to the guidance
provided in Appendix F of EIIP Volume VI.
The preferred method gives higher BARS scores than any of the alternative methods. The
alternative method BARS scores range between 0.51 and 0.33, and the preferred
method's BARS scores are between 0.85 and 0.73. The preferred method scores higher on all
attributes than the alternative methods.
Among the alternative methods, lane miles and an emission factor use the most locally specific
surrogate activity factor and consequently has the higher activity composite score for the
alternative methods.
6.1.2 SOURCES OF UNCERTAINTY
The uncertainty of the emission estimates developed through the preferred method can be
quantified (see QA Procedures, Volume VI, Chapter 4). However, the statistics needed to
quantify the uncertainty of the alternative methods are incomplete. Activity for the alternative
methods is based on the use of surrogates: highway maintenance spending and population for the
first alternative method, lane miles for the second alternative method, and population for the third
alternative method. Actual paint use is expected to vary in relation to these surrogates, but is not
defined.
The emission factors that are used in the alternative methods are also expected to vary by region.
Factors that cause regional variation are climate, traffic density, and driving patterns all of which
result in variations in wear, maintenance schedules, rules affecting the materials used for traffic
markings, and lack of information about unused paints or the use of cleanup solvent use.
Identifying the types of paints or other marking materials used in the inventory region so that a
more specific factor can be developed will reduce variability, as will the development of locally
specific activity factors.
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CHAPTER 14 - TRAFFIC MARKINGS
TABLE 14.6-1
PREFERRED METHOD DARS SCORES: SURVEY OF STATE AND COUNTY HIGHWAY
DEPARTMENTS COATING USE IN THE INVENTORY REGION
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5-0.63
0.9- 1.0
1.0
0.9
0.83 -0.88
Activity
0.8- 1.0
0.9- 1.0
0.9- 1.0
0.9
0.88-0.98
Emissions
0.40 - 0.60
0.81 - 1.0
0.90- 1.0
0.81
0.73 -0.85
a Score assumes emissions are calculated using mass balance calculation of VOC content. If a
VOC emission factor used or speciated to get HAPs, the score should be lowered.
TABLE 14.6-2
ALTERNATIVE METHOD 1 DARS SCORES: ACTIVITY APPORTIONED FROM THE
INVENTORY YEAR NATIONAL LEVEL APPLIED TO NPCA 1991 EMISSION FACTORS
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5a
0.8
0.5-0.7
0.7
0.60-0.65
Activity
0.6
0.5-0.7
0.8
0.9
0.70-0.75
Emissions
0.30
0.40-0.56
0.40-0.56
0.63
0.43 -0.51
a Score assumes total VOC factor is used; if this is speciated to get HAPs, score should be
lowered.
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TABLE 14.6-3
ALTERNATIVE METHOD 2 DARS SCORES: LANE MILES APPLIED TO
1988 CTC EMISSION FACTORS
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5a
0.6
0.5-0.7
0.5
0.52
Activity
0.6
0.6
0.9
0.9
0.75
Emissions
0.30
0.36
0.45-0.63
0.45
0.39-0.44
a Score assumes total VOC factor is used; if this is speciated to get HAPs, score should be
lowered.
TABLE 14.6-4
ALTERNATIVE METHOD 3 DARS SCORES: ACTIVITY APPORTIONED BY POPULATION
AND APPLIED TO NPCA1991 EMISSION FACTORS
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5a
0.8
0.5
0.7
0.6
Activity
0.6
0.3
0.3
0.9
0.53
Emissions
0.30
0.24
0.15
0.63
0.33
a Score assumes total VOC factor is used; if this is speciated to get HAPs, score should be
lowered.
14.6-4
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DATA CODING PROCEDURES
This section describes the codes available to characterize traffic marking emission estimates.
Consistent categorization and coding will result in greater uniformity between inventories.
Inventory planning for data collection calculations and inventory presentation should take the
data formats presented in this section into account. Available codes and process definitions may
impose constraints or requirements on the preparation of emission estimates for this category.
7.1 PROCESS AND CONTROL CODES
The source category process codes for traffic marking operations are shown in Table 14.7-1.
These codes are derived from the EPA's Aerometric Information Retrieval System (AIRS) Area
and Mobile Source (AMS) source category codes (EPA, 1994). The control codes for use with
AMS are shown in Table 14.7-2. The "099" control code can be used for miscellaneous control
devices that do not have a unique identification code. The "999" code can be used for a
combination of control devices where only the overall control efficiency is known.
Typically, the source category code for "total: all solvent types, traffic markings" will be used.
Low-solvent or water-based coatings will be the control method, so either control device code
101 or 103 will be used.
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TABLE 14.7-1
AIRS AMS CODES FOR TRAFFIC MARKINGS
Process Description
Total: All Solvent Types
Acetone
Butyl Acetate
Butyl Alcohols: All Types
n-Butyl Alcohol
Isobutyl Alcohol
Diethylene Glycol Monobutyl Ether
Diethylene Glycol Monoethyl Ether
Diethylene Glycol Monomethyl Ether
Ethyl Acetate
Ethylene Glycol Monoethyl Ether (2-Ethoxyethanol)
Ethylene Glycol Monomethyl Ether (2-Methoxyethanol)
Ethylene Glycol Monobutyl Ether (2-Butoxyethanol)
Glycol Ether: All Types
Isopropanol
Methyl Ethyl Ketone
Methyl Isobutyl Ketone
Special Naphthas
Solvent — General
Xylenes
AMS Code
24-01-008-000
24-01-008-030
24-01-008-055
24-01-008-060
24-01-008-065
24-01-008-070
24-01-008-125
24-01-008-130
24-01-008-135
24-01-008-170
24-01-008-200
24-01-008-210
24-01-008-215
24-01-008-235
24-01-008-250
24-01-008-275
24-01-008-285
24-01-008-370
24-01-008-999
N/Aa
N/A = No AMS source code assigned.
14.7-2
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CHAPTER 14 - TRAFFIC MARKINGS
TABLE 14.7-2
AIRS CONTROL DEVICE CODES
Control Device
Process Modification — Low-Solvent Coatings
Process Modification — Powder Coatings
Process Modification — Water-Borne Coatings
Miscellaneous Control Device
Combination Control Efficiency
Code
101
102
103
099
999
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14.7-4 Volume III
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8
REFERENCES
EPA. 1994. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1993. VOC Emissions from Architectural and Industrial Maintenance Coatings. Docket
No. II-E-36. Information provided in the regulation negotiation proceedings in support of a
VOC regulation for architectural and industrial maintenance coatings.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Vol.1: General Guidance for Stationary Sources. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, EPA-450/4-91-016. Research
Triangle Park, North Carolina.
EPA. 1988. Reduction of Volatile Organic Compound Emissions from the Application of
Traffic Markings. U.S. Environmental Protection Agency, Control Technology Center,
EPA-450/3-88/007. Research Triangle Park, North Carolina.
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14.8-2 Volume III
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VOLUME III: CHAPTER 15
LANDFILLS
Revised Final
January 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee of
the Emission Inventory Improvement Program and for Charles Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency. Members of the Area
Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Other contributors are:
Tahir R. Khan, Chemical Emission Management Services
Ron Meyers, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mary Ann Warner, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency
Volume III ill
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IV Volume III
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CONTENTS
Section Page
1 Introduction 15.1-1
2 Source Category Description 15.2-1
2.1 Emission Sources 15.2-1
2.2 Factors Influencing Emissions 15.2-2
2.2.1 Process Operating Factors 15.2-2
2.2.2 Regulatory Issues 15.2-3
3 Overview of Available Methods 15.3-1
3.1 Emission Estimation Methodologies 15.3-1
3.2 Available Methodologies 15.3-1
3.3 DataNeeds 15.3-5
3.3.1 Data Elements 15.3-5
3.3.2 Application of Controls 15.3-5
3.3.3 Spatial Allocation 15.3-7
3.3.4 Temporal Resolution 15.3-7
3.3.5 Projecting Emissions 15.3-7
4 Preferred Method for Estimating Emissions 15.4-1
4.1 Data Collection 15.4-1
4.2 Landfill Gas Emission Calculation (EPA, 1995) 15.4-2
4.3 VOC and Hazardous Air Pollutant Emission Calculation 15.4-3
Volume III V
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CONTENTS (CONTINUED)
Section Page
5 Alternative Methods for Estimating Emissions 15.5-1
5.1 Alternative One: Guidelines for Using Assumptions with Landfill Data .. 15.5-1
5.2 Alternative Two: Regression Model 15.5-3
5.3 Alternative Three: Population-based Waste Generation Factor 15.5-5
6 Quality Assurance/Quality Control 15.6-1
6.1 Emission Estimate Quality Indicators 15.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 15.6-2
6.1.2 Sources of Uncertainty 15.6-5
7 Data Coding Procedures 15.7-1
7.1 Necessary Data Elements 15.7-1
8 References 15.8-1
Appendix A
VI Volume III
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TABLES
Page
15.2-1 Applicability of the NSPS and EG to MSW Landfills 15.2-5
15.4-1 Uncontrolled Landfill Gas Constituents 15.4-5
15.6-1 Preferred Method DARS Scores: Survey of All Landfills in the Inventory
Region 15.6-2
15.6-2 Alternative Method 1 DARS Scores: Survey Using Assumptions 15.6-3
15.6-3 Alternative Method 2 DARS Scores: Regression Model 15.6-3
15.6-4 Alternative Method 3 DARS Scores: Population-based Waste Factor .... 15.6-4
15.6-5 Composite DARS Scores: Summary for All Methods 15.6-4
15.7-1 Area and Mobile Source Category Codes for Municipal Solid Waste
Landfills 15.7-2
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Vlll Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
Landfills are significant sources of methane (CH4) and carbon dioxide (CO2). In addition to
CH4 and CO2 small amounts of nonmethane organic compounds (NMOCs) are produced.
NMOCs include reactive volative organic compounds (VOCs) and hazardous air pollutants
(HAPs). Unlike other area sources that may be small sources individually but numerous within
the inventory area, only a few landfills may be found within a multi-county area. However, each
landfill may emit significant amounts of pollutants. Landfills differ from sources typically
categorized as point or major sources in that pollutants are emitted over the area of the landfill,
not at a specific point or points. For these reasons, landfills have been treated as area sources in
the past. Recently, air operating permits have been required for landfills, so that inventory
preparers have begun to address them as point sources. The preferred method described in this
chapter is very close to a point source inventory method, and, if site-specific test data are
available, those data may be used to develop emissions estimates.
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This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
This chapter describes the procedures and recommended approaches for estimating emissions
from landfills. Section 2 of this chapter contains a general description of the landfills category,
and an overview of available control techniques. Section 3 of this chapter provides an overview
of available emission estimation methods. Section 4 presents the preferred emission estimation
method for landfills, and Section 5 presents alternative emission estimation techniques. Quality
assurance/quality control (QA/QC) are discussed in Section 6. Data coding procedures are
discussed in Section 7, and Section 8 is the reference section.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
15.1-2 Volume III
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SOURCE CATEGORY DESCRIPTION
The following description of landfills and discussion of landfill emission sources have been
drawn from theAP-42 section on landfills and the U.S. Environmental Protection Agency's
(EPA's) Office of Policy Planning and Evaluation's (OPPE) report on anthropogenic methane
emissions for 1990 (EPA, 1998a; EPA, 1994a).
A municipal solid waste (MSW) landfill unit is a discrete area of land or an excavation that
receives household waste and that is not a land application unit, surface impoundment, injection
well, or waste pile. An MSW landfill unit may also receive other types of wastes, such as
commercial solid waste, nonhazardous sludge, and industrial solid waste (EPA, 1998a).
Landfills that accept hazardous waste should be classified as treatment, storage, and disposal
facilities (TSDFs). Open dumps should not be categorized as landfills, because the waste types
are variable and are not necessarily MSW. Also, the waste is not compacted and covered as
waste is in a sanitary landfill, so the anaerobic decomposition process that is the source of the
landfill gas may not take place. The emission estimation methods presented in this chapter are
not suitable for TSDFs or open dumps.
2.1 EMISSION SOURCES
Methane and CO2 are the primary constituents of landfill gas, and are produced during anaerobic
decomposition of cellulose and proteins in the landfilled waste. Anaerobic decompostion takes
place in the absence of oxygen. Although particulate emissions are generated by landfill
operations, only landfill gas emissions are addressed in this chapter. In addition to CH4 and
CO2, NMOCs are produced as a small fraction of the landfill gas emissions. NMOCs include
hazardous air pollutants and reactive VOCs. The decomposition is a complex process and
requires certain environmental conditions. Environmental factors that affect the decomposition
include moisture content of the waste, nutrient concentration, the presence and distribution of
microorganisms, the particle size of the waste, water flux, pH, and temperature. Because of the
complex set of conditions that must occur before landfill gas is generated, waste may be in place
for a year or more before anaerobic decomposition begins and landfill gas is generated. Refuse
in a landfill may produce landfill gas for 20 to 30 years. Uncontrolled dumps, where waste is
exposed to air, result in aerobic decomposition (EPA, 1994a). Aerobic decomposition results
mainly in CO2 and water.
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2.2 FACTORS INFLUENCING EMISSIONS
2.2.1 PROCESS OPERATING FACTORS
The number of landfills in the United States is declining, yet the amount of waste generated is
increasing. Surveys of U.S. landfills have shown a steady decline in the estimated number of
landfills taking MSW with 6,034 landfills in 1986, 3,558 landfills in 1994 and 2,216 in 1999
(EPA, 1988; Steuteville, 2000). In 1986, the average landfill capacity, based on survey data,
was 2.65 million cubic yards, but the median landfill capacity of the same survey data set was
0.39 million cubic yards, showing that it is the less numerous larger landfills that handle most of
the waste. A decreasing proportion of the total waste is being sent to U.S. landfills as well. In
1989, an estimated 80 percent of MSW was landfilled, and in 1994, 67 percent was sent to
landfills, with recycling and incineration being the alternative form of treatment as reported in
the April 1995 issue ofBioCycle (Steuteville, 1995).
Because of stricter regulations affecting landfills, many of the smaller landfills have closed, and
the larger, more technologically advanced landfills remain. Nearly one-third of MSW landfills
were estimated to be privately owned in 1996, and the remainder were owned by federal, state,
county, or other government entities. In the same year, an estimated 91 percent of the MSW
landfills have permits, usually from the state (EPA, 1988).
Description (EPA, 1998a)
Landfill design and operation normally uses one or a combination of three fill methods. These
are the area, trench, and ramp methods, all of which use a three-step process consisting of
spreading the waste, compacting the waste, and covering the waste with soil. The trench and
ramp methods are not commonly used, and are not the preferred methods when liners and
leachate collection systems are used.
The area fill method entails placing waste on the ground surface or landfill liner, spreading it in
a layer, and compacting it with heavy equipment. Successive layers are added until a depth of
3 to 4 meters (m) [10 to 12 feet (ft)] is reached. A daily soil cover is spread on the top and sides
of the compacted waste. The soil cover can come from other parts of the landfill or be imported
from outside the landfill. The trench method entails excavating daily trenches designed to
receive a day's worth of waste. Successive parallel trenches are excavated and filled, with the
soil from the excavation being used for cover material and wind breaks. The ramp method is
typically employed on sloping land, where waste is spread and compacted in a manner similar to
the area method; however, the cover material is generally obtained from the front of the working
face of the filling operation.
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The basic landfill unit is common to all landfilling methods, and is usually designed to accept a
day's waste, after which it is closed, compacted, and covered with soil at the day's end.
Generally, the height of a landfill unit is less than 2.4 m (8 ft), and the working face of the unit
can extend to the facility boundaries. Waste densities generally range from 1,100 to
1,400 pounds per cubic yard after the waste has been compacted, and range from 1,700 to
1,900 pounds per cubic yard after waste degradation and settling. If site-specific data are not
available, a density of 1,160 pounds per cubic yard is recommended.
Modern landfill design often incorporates liners constructed of soil such as recompacted clay,
synthetics such as high-density polyethylene, or both to provide an impermeable barrier to
leachate (water that has passed through the landfill) and gas migration from the landfill. Soil
liners can reduce permeability to between 7 to 10 centimeters (cm) per second, and synthetic
liners to between 10 to 13 cm per second.
Bioreactors within landfills are an emerging technology. Anaerobic bioreactors increase the rate
of methane generation, which can then be collected and used for energy recovery, whereas
aerobic bioreactors foster aerobic instead of anaerobic decomposition, reducing methane
generation. These are not widely used to present. The emission estimation procedures
recommended in this chapter do not reflect landfills that are being operated as a bioreactor under
enhanced conditions where leachate is added.
Control Techniques
Landfill emissions are collected through either active or passive collection systems. Disposal or
treatment of the collected gases can be accomplished by the combustion or purification of the
landfill gas. Landfill gas collection and treatment methods and efficiencies are discussed in
more detail in Section 3 of this chapter.
2.2.2 REGULATORY ISSUES
Air quality standards and regulations that affect municipal solid waste landfill facility operations
are New Source Performance Standards (NSPS), and Emissions Guidelines. The Standards of
Performance for New Municipal Solid Waste Landfills, 40 Code of Federal Regulations (CFR)
part 60, Subpart WWW are federal regulations affecting air emissions for new landfills or
landfills that began construction, modification, or reconstruction on or after May 30, 1991. The
Emission Guidelines required States to develop State plans to regulate existing landfills that
began construction before May 30, 1991 and that have accepted waste since November 8, 1987,
or have capacity to accept additional waste.
The Emission Guidelines are contained in 40 CFR part 60 Subpart Cc. As of December 1999,
existing landfills throughout the U.S. were covered by either approved State plans that
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CHAPTER 15 - LANDFILLS 1/31/01
implement and enforce the Emission Guidelines, or by the Federal plan in 40 CFR part 62,
Subpart GGG (see 40 CFR part 62 for a list of approved State plans).
In late 2000, EPA expects to propose national emission standards for hazardous air pollutants
from landfills. The proposed rule contains the same requirements as the Emission Guidelines
and NSPS. The collection and control requirements of the Emission Guidelines and NSPS are
the best control technology available for hazardous air pollutant emissions from landfills. Under
the proposed rule, in addition to the requirements in the Emission Guidelines and NSPS,
landfills that have installed controls would be subject to additional recordkeeping and reporting
requirements, such as documentation of startup, shutdown, and malfunction reports.
The NSPS and the State and Federal plans that implement the Emission Guidelines require
owners or operators of new and existing landfills to file a design capacity report. Landfills equal
to or larger than 2.5 million megagrams (Mg) and 2.5 million cubic meters (m3) must provide
periodic estimates of annual NMOCs, either through calculation using standard assumed values
or based on on-site measurements (Table 15.2-1). One exception to the annual reporting
requirement is that if the landfill has an estimated NMOC emission rate of less than 50 Mg/yr
for the next five years, the owner or operator may elect to submit an estimate of the NMOC
emission rate for the next five years rather than an annual report.
New and existing landfills that have estimated annual emissions of NMOCs greater than the
50 Mg threshold must reduce emissions under either the NSPS (for new landfills) or the
applicable State and Federal Plan for existing landfills. The EPA's final rule provides a tier
system under which the landfill owner or operator can determine if controls are required. The
tier system allows owners and operators to conduct testing for more site-specific values to prove
that emissions are below the 50 Mg/yr emission threshold. If landfill emissions exceed
50 Mg/yr, emissions must be reduced by installing gas collection systems and routing the gas to
a suitable energy recovery system or combustion device that is capable of reducing NMOC
emissions by 98 weight-percent or to 20 parts per million by volume dry (ppmvd) as hexane.
The collection system must be operated so that the methane concentration is less than 500 parts
per million (ppm) above background at the surface of the landfill (EPA, 1999). Monitoring of
surface concentration and other collection system and control device operating parameters is
also required.
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CHAPTER 15 - LANDFILLS
TABLE 15.2-1
APPLICABILITY OF THE NSPS AND EG TO MSW LANDFILLS (EPA, 1999)
Landfill Maximum
Design Capacity
Constructed, Reconstructed,
Modified, or Began
Accepting MSW on or after
5/30/91
Constructed, Reconstructed,
or Modified before 5/30/91.
Accepted Waste after 11/8/87
or Has Additional Capacity
<2.5 million Mg
or
2.5 million m3
Must report design capacity.
No further requirements.
Must report design capacity.
No further requirements.
>2.5 million Mg
and
2.5 million m3
Must comply with the
requirements of the NSPS.
Must comply with the
requirements of the EG.
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OVERVIEW OF AVAILABLE METHODS
3.1 EMISSION ESTIMATION METHODOLOGIES
The recommended method for calculating emission estimates from landfills is to use the
equation in the section addressing landfills in AP-42 (EPA, 1998a). The Landfill Gas Emissions
Model (LandGEM) uses the AP-42 equation and eases the calculation burden for estimating
emissions for individual landfills (EPA, 1998b). However, several methods are available for
collecting the data needed to use the emission estimation calculation for landfills. Determining
the best method to use depends upon the degree of accuracy required in the estimate, the
available data, and the available inventory resources. Refer to EIIP Volume VI, Quality
Assurance Procedures., Sections 2.1 and 2.4.
Selection of the appropriate estimation method depends on the relative significance of emissions
from this source in the inventory area and the data quality objectives (DQOs) of the inventory
plan. Refer to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for
discussions of inventory categories and DQOs.
This section discusses the methods available for collecting landfill data and identifies the
preferred data collection method. A discussion of the data elements needed for each method is
provided. The preferred and first two alternative methods also take into account control
technologies.
3.2 AVAILABLE METHODOLOGIES
The methods are as follows:
• Preferred Method: Required reporting;
• Alternative Method One: Guidelines for using assumptions with landfill data;
• Alternative Method Two: Regression model; and
• Alternative Method Three: Population-based waste generation factor.
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Before choosing any of these methods, inventory preparers should investigate how many
landfills are in the inventory area. Some counties send all of their waste to landfills in other
counties or even other states. If there are no landfills that have accepted waste in the past
25 years in a county, then it may not be necessary to estimate emissions from this source
category for that county. Before investing resources in collecting detailed information about
landfills that closed before 1987, setting a cutoff level for landfill size and age could be
worthwhile. Because of RCRA rules and the Emission Guidelines, States should have lists of
landfills that accepted waste since 1987.
Preferred Method
Emission estimates for all landfill emission methods are calculated using either the LandGEM or
the equations from theAP-42 section on landfills. The AP-42 landfills section was updated in
November 1998. Check the EPA Technology Transfer Network (TTN) Web for the most
current version of theAP-42 section when preparing landfill emission estimates for an
inventory. The EPA updates AP-42 as new information becomes available. The LandGEM is a
personal computer-based model that uses the same equation as that in AP-42, but provides the
advantages of an automated calculation and utilities. Appendix A of this chapter contains an
overview of the LandGEM, with example model runs for the program. The LandGEM and the
landfill section of AP-42 can be accessed from the EPA's Web site.1 Please refer to Chapter 1 of
this volume, Introduction to Area Source Emission Inventory Development, for more
information about accessing the TTN Web site.
Total landfill gas, methane, carbon dioxide, and NMOC concentration can be calculated using
the equations in AP-42 and LandGEM. The AP-42 section and the LandGEM use three
equations to calculate (1) methane generation rate; (2) NMOCs or other pollutants expressed as
cubic meters per year, and (3) convert the volume estimate of each pollutant to a mass estimate
(kilograms per year). Reactive VOCs and air toxics can be calculated using default
concentration values that are also provided. Reductions in emissions resulting from the use of
controls can be calculated from control efficiency factors listed in the AP-42 section. The
emissions calculations for landfill gas require several steps and a combination of site-specific
information and default values. The following site-specific information is required:
• The design capacity of the landfill;
• The years the landfill has been in operation;
• Controls in place in the landfill (if available); and
1 For Internet access to the EPA TTN Web, use http://www.epa.gov/ttn.
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• Whether the landfill has been used for disposal of hazardous waste (codisposal)
In addition, the following default values are available in LandGEM and AP-42:
• The methane generation rate (k);
• The potential methane generation capacity (Lo);
• The concentration of NMOCs found in the landfill gas;
• The concentration of toxic air pollutants found in the landfill gas (if air toxic
pollutants are to be calculated); and
• The concentration of reactive VOCs found in the landfill gas.
The AP-42 section and the LandGEM provide default factors for the parameters k, L0, and
NMOC concentration that are needed to calculate total landfill gas, methane, carbon dioxide,
and NMOC concentration. In all cases, landfill-specific values are preferred over the use of
default values.
The LandGEM provides two sets of default values for k, L0, and NMOCs. One set is based on
the requirements of the NSPS and Emission Guidelines. This set of default values produces
conservative emission estimates and should be used to determine whether the landfill is subject
to the control requirements of the NSPS and Emission Guidelines. The other set of default
values is the same as those in AP-42 and produces more representative emission values that can
be used to produce typical emission estimates in the absence of site-specific test data. The
default values presently in the model may be revised in future updates of the model based on
new information collected by the EPA. Unlike the AP-42 equation, the LandGEM allows the
user to enter annual waste acceptance amounts into the emission model. Reductions from
controls are not included in the LandGEM. The model also provides utilities for estimating
values for k and landfill waste in place. Calculations are performed automatically after the
necessary information has been collected and entered (EPA, 1998b).
Alternative Method One: Guidelines for Using Assumptions with Landfill Data
The first alternative method is a set of guidelines for making the best possible estimates of the
values needed to calculate emissions from landfills when actual values are not directly available.
Possible sources of information are given in the discussion of the method. This method
supplements the approach of the preferred method, in case detailed information for every landfill
in an inventory area cannot be located or budget constraints limit the level of effort for the
source category.
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Alternative Method Two: Regression Model
The second alternative method uses a regression model to develop waste-in-place factors for
landfills in a large inventory area or modeling domain from a subset of area landfills. This
method requires a survey of a subset of landfills in the inventory area. The survey covers all of
the landfills in counties that can be deemed typical for the larger area. The information collected
should include waste-in-place and age of the landfill, or reliable local estimates of those factors.
A factor is developed that can be used to estimate the waste in place and landfill age for the
remaining counties using a surrogate for activity such as population or population density.
This method should provide more specific emission estimates than Alternative Method One in
most cases but, unlike Alternative Method One, still requires a considerable amount of data
collection. This method can be used when the inventory area is large (greater than 10 counties),
time and budget constraints are such that collection of specific data for the preferred method is
not practical, yet there is still a need for region-specific information. This method is not suitable
for smaller areas, where the sample size may not be adequate for good results.
The agency should have the resources to collect complete information from several counties in
the inventory area or region. Personnel should be available that can interpret the statistics to
judge the validity of the regression model results and set a statistically valid sample size for the
survey. Although survey planning and interpretation of results require statistical training, data
collection and preparation for the model require only inventory and spreadsheet skills. Most
spreadsheet packages provide regression analysis tools. Regression analysis provides a
mathematical model that relates two or more sets of variables to one another. In this case, the
surrogate factor(s), such as population density, property values, or education level, for the survey
counties are related to the amount of waste in place in landfills in those counties.
Alternative Method Three: Population-based Waste Generation Factor
This method uses a population-based waste generation factor and population by county to
estimate the waste-in-place value that is used in the AP-42 equation. The advantage of this
method is that it requires no specialized information and can be completed with very little effort.
Disadvantages are that solid waste disposal methods other than landfills, waste reduction
programs, or transport of the waste to other areas will not be taken into account. Controls in
place in individual landfills also will not be taken into account.
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3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements used to calculate emission estimates for landfills will depend on the
methodology used for the estimation and the level of detail required in the inventory. For all
methods, the minimum information for using the AP-42 equation or LandGEM is waste in place
and the open and close dates for the landfills in the area. The alternative methods can use
assumptions about the opening and closure dates. Knowledge of state and local regulations and
average annual rainfall also are needed.
The data elements required for the preferred method are listed in Section 3.2 under the
discussion of the AP-42 landfill section and the LandGEM.
The first alternative method can use the same data elements as those listed for the preferred
method, but does not require the same detailed information. When the detailed information is
not available, other information is collected to substitute. Acreage of the landfills and local
practices for landfill depth can be substituted for waste-in-place. Assumptions are used for open
and close dates, when actual dates are not available.
The data elements needed to calculate emissions for this category when using Alternative
Method Two, the regression model, are:
• The estimated number of landfills in the entire inventory area;
• Information about each landfill in the selected survey counties (see the data
elements needed for the preferred and the first alternative method); and
• Surrogate activity information for all of the inventory counties.
3.3.2 APPLICATION OF CONTROLS
Larger and newer landfills are very likely to have landfill gas collection systems in place to
control air emissions. The discussion of landfill gas collection systems in the AP-42 landfill
section should be consulted for information about landfill gas controls. In that section, average
control efficiencies for landfill gas constituents and emission rates for secondary compounds are
given for typical landfill gas control devices.
Emissions from landfills are typically controlled by installing a gas collection system and
destroying the collected gas through the use of internal combustion engines, flares, or turbines.
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Gas collection systems are not 100 percent efficient in collecting landfill gas, so emissions of
CH4 and NMOCs at a landfill with a gas recovery system still occur. To estimate controlled
emissions of CH4, NMOCs, and other constituents in landfill gas, the collection efficiency of the
system must first be estimated. Reported collection efficiencies typically range from 60 to
85 percent, with an assumed average of 75 percent. If site-specific collection efficiencies are
available, they should be used instead of the 75 percent average.
Controlled emission estimates also need to take into account the efficiency of the control device.
Control efficiencies for CH4 and NMOCs with different control devices are presented in the AP-
42 section. Emissions from control devices, also available in AP-42, need to be added to the
uncollected emissions to estimate total controlled emissions. Equation 15.3-2 shows how to
estimate total controlled emissions of pollutant P from a specific landfill:
Controlled
Landfill = P
Emissions
1 -
Percent
Collection
Efficiency
100
Percent
Collection
Efficiency
100
1 -
Percent
Control
Efficiency
100
(15.3-2)
Example 3-1 shows how emissions for a landfill with controls are calculated.
Example 3-1:
VOC emissions from Landfill A are estimated to be 3,197 cubic meters per year.
Average collection efficiency of the landfill gas recovery system is not known at
Landfill A, so a 75-percent collection efficiency rate is assumed. The collected
landfill gas is controlled by a flare, which has a control efficiency for NMOCs of
83.16 percent.
Controlled = 3,197 m3 * [1-0.75] + 3,197 m3 * [0.75] * [1-0.8316]
NMOC
Emissions
= 799.25m3+ 3,197m3* 0.1263
= 799.25m3+ 403.78m3
= 1,203 m3
15.3-6
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When emissions have been calculated using the alternative methods, less specific information
will be available about controls. However, if information is available, it should be used.
Emission factors and procedures for estimating secondary compounds (CO2, CO, NOX, SO2, and
HC1) from landfill gas combustion control devices are also included inAP-42.
Point Source Corrections
Some landfills in the inventory area may be counted as point sources in the point source
inventory. Area source estimates for landfills should be corrected for these emissions. There
are two ways to correct for the point source contribution depending on the area source
estimation method used.
The first approach is to remove the point source landfills from the area source emission
calculations. This approach can be used if emissions are being calculated from specific
information, as in the preferred and first alternative methods. If the second or third alternative
methods are used, estimated emissions from the point source landfills can be subtracted from the
inventory area total estimate.
3.3.3 SPATIAL ALLOCATION
Spatial allocation may be needed during inventory preparation to allocate the emission estimates
calculated using Alternative Methods Two or Three to smaller areas, such as modeling grid
cells, or to allocate the surrogate activity factor(s) used in Alternative Method Three to a smaller
area. The preferred method and the first alternative method do not require any spatial allocation
because these methods collect data for individual landfills, and emissions are assigned according
to the landfills' locations.
3.3.4 TEMPORAL RESOLUTION
Seasonal Apportioning/Daily Resolution
Emissions from this source category are expected to remain constant from season to season, and
they are not expected to vary on a day-to-day basis. The seasonal activity factor that should be
used for this source category is 1.0.
3.3.5 PROJECTING EMISSIONS
Unlike typical sources, landfill emissions increase each year as more waste is added to the
landfill. Landfill emissions peak shortly after the landfill closes, then gradually decrease over
time. For projecting future emissions, projected variables such as time since initial waste
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placement, amount of waste in place, and average waste acceptance rate for the particular year of
interest should be used, rather than using the current values.
Emissions projections for landfill emissions need to take into account changes in emissions due
to any increase or decrease in waste generation, the age of the waste in place, and any potential
changes in landfill controls. Factors that may affect the amount of waste in place in landfills in
the inventory area are changes in waste generation or how the waste is handled: incineration,
recycling, or transport in or out of the inventory area. Emissions may change because of added
controls. The preferred approach to defining these changes is to collect information from
planning departments and solid waste departments about projected changes in the amount of
waste in place for the projection year, the status of landfill openings or closures, and future
controls.
An alternative method is to use population to scale current emission estimates to the projection
year, but the effects of factors like recycling programs or additional controls at landfills will not
be included.
The EIIP Projections Committee has developed a series of guidance documents containing
information on options for forecasting future emissions. You can refer to these documents at
http://www.epa.gov/ttn/chief/eiip/project.htm. Tools for the development and use of growth
factors are discussed in Chapter 1 of this volume, Introduction to Area Source Emission
Inventory Development.
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
The preferred method for this source category uses information that has been compiled as part of
a permit or reporting requirement such as for NSPS or RCRA. State and local solid waste
management agencies and the federal EPA Office of Solid Waste can be contacted for RCRA
information. State and local air agencies or EPA Regional Offices will also have information
from air permits, the NSPS, or the State or Federal plan implementing the Emission Guidelines.
In fact, as part of their State plans, states were required to develop inventories and emission
estimates for existing landfills that commenced construction before May 30, 1991 and accepted
waste since November 8, 1987. In many cases, the information will already be compiled into a
spreadsheet or database. The equations in Section 2.4, Landfills, of AP-42 or the LandGEM are
used to calculate emissions.
The Standards of Performance for New Municipal Solid Waste Landfills (NSPS), 40 CFR 60,
Subpart WWW, and the Emission Guidelines for Control of Existing Municipal Solid Waste
Landfills (EG), 40 CFR 60, Subpart Cc, are briefly summarized in Section 2.2.2 of this chapter.
The significance of these rules for inventory preparers is that owners or operators of any new or
existing MSW landfill (as defined by the NSPS and the EG) need to report design capacity, and
if the landfill has a design capacity at or above 2.5 million Mg and 2.5 million m3, then periodic
estimates of NMOC emissions must be reported. New and existing landfills that have estimated
annual emissions of NMOCs greater than the 50 Mg limit must either reduce emissions through
collection and control, or must conduct testing to prove that emissions are below the emission
threshold. Landfill operators may use sampling and gas flow testing to determine more specific
values for NMOC concentration and k when estimating emissions (EPA, 1995).
4.1 DATA COLLECTION
Permits can be used to collect the information needed to calculate landfill emissions. The
information needed is discussed in Section 3.2, but at a minimum, landfill opening and closure
year and the current amount of waste-in-place is necessary for the calculation.
Additional information that can be used, if it is available, is the amount of waste brought in
annually, landfill-specific information for calculating k and L0, and measured concentration
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values for CH4, CO2, NMOCs, and other pollutants in the landfill gas. If the amount of waste is
reported as a volume measurement, the following conversion factors can be used (EPA, 1995):
• 1,100 to 1,400 pounds per cubic yard of compacted waste;
• 1,700 to 1,900 pounds per cubic yard of waste after degradation and settling; and
* 1,160 pounds per cubic yard of waste (if unknown if waste was compacted).
In some cases, emission estimates from permits can be used, but only if those estimates have
been calculated using landfill-specific data for k or the AP-42 defaults. If emissions have been
calculated using the more conservative k and L0 values required under the NSPS and Emission
Guidelines, then emission estimates should be recalculated using AP-42 default values for k and
L0. The AP-42 default for L0 should be used.
4.2 LANDFILL GAS EMISSION CALCULATION (EPA, 1995)
The emission estimation equation used to calculate landfill gas emissions is a theoretical first-
order kinetic model of methane production developed by the EPA (EPA, 1991). This is the
equation used in AP-42 and in the LandGEM. The equation is as follows:
QcH4 =L0R(e-kc-e-kt) (15.4-1)
where:
QcH4 = Methane generation rate at time t, m3/yr;
L0 = Methane generation potential, m3 CH4/Mg refuse;
R = Average annual refuse acceptance rate during active life, Mg/yr;
e = Base log, unitless;
k = Methane generation rate constant, yr"1;
= Time since landfill closure, years (c = 0 for active landfills); and
= Time since the initial refuse placement, years.
The average annual refuse acceptance rate (R) is calculated by dividing the current amount of fill
by the number of years that the landfill has been accepting waste. If the landfill has a measured
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value for k, then that value should be used; otherwise, the value recommended in AP-42 should
be used. Estimation of the methane generation constant, k, is a function of a variety of factors,
including moisture, pH, and temperature, other environmental factors, and landfill operating
conditions. Specific CH4 generation constants (k) can be computed by use of the EPA Method
2E. L0 is generally treated as a function of the moisture and organic content of the refuse, and
the AP-42 default value should be used.
If the computer model LandGEM is used, the measured values of k, L0, and NMOC
concentration are preferred. Site-specific NMOC concentration can be measured using EPA
Method 25C and the sampling procedures described in the NSPS. Otherwise, use the
recommended values from AP-42 for k, L0, and NMOC concentration. Note that AP-42
provides separate default k values for arid areas (less than 25 inches of rain per year) and non-
acid areas.
4.3 VOC AND HAZARDOUS AIR POLLUTANT EMISSION CALCULATION
When gas generation reaches steady state conditions, landfill gas consists of approximately
40 percent by volume CO2, 55 percent CH4, 5 percent N2 and trace amounts of NMOC s when
gas generation reaches steady state conditions. Therefore, the estimate derived for CH4
generation using the method above can also be used to represent CO2 generation. Addition of
the CH4 and CO2 emissions will yield an estimate of total landfill gas emissions. If site-specific
information is available to suggest that the CH4 content of landfill gas is not 55 percent, then the
site-specific information should be used, and the CO2 emission estimate should be adjusted
accordingly. LandGEM uses 50% of CH4 and 50% CO2 as the default landfill gas composition,
however, these defaults can be overridden.
Emissions of pollutants other than CO2 and CH4 from landfills result from either their being
contained in the landfilled waste or from their creation from biological processes and chemical
reactions within the landfill cell. There is a wide range of values for various VOC species and
air toxics in landfill emissions. For inventory purposes, it is preferable that site-specific
information about landfill gas constituents be used to calculate VOC and air toxic emissions.
The emissions of reactive VOCs and toxic air pollutants must be calculated individually from
the estimated emissions of total landfill gas. When using the LandGEM, enter any site-specific
concentrations available for that landfill and run the model. Emissions for individual VOCs
from the model results can be summed to get total VOC emissions. If the AP-42 equations are
used, use the most recent list of landfill gas constituents from AP-42 and calculate emission
estimates for each of those constituents that are defined as reactive VOCs using the equations in
the AP-42 landfill section. The AP-42 section for landfills has default concentrations for 43
landfill gas constituents, of which 30 are currently defined as reactive VOCs and 24 are listed as
hazardous air pollutants (HAPs). These landfill gas constituents are listed in Table 15.4-1.
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AP-42 also contains equations and procedures for calculating controlled emissions of CH4,
NMOC, and speciated organics. It also contains procedures for calculating secondary emissions
from landfills gas combustor devices (NOx, CO, CO2, SO2, HC1).
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TABLE 15.4-1
UNCONTROLLED LANDFILL GAS CONSTITUENTS
Compound
1,1,1-Trichloroethane (methyl chloroform)
1 , 1 ,2,2-Tetrachloroethane
1,1-Dichloroethane (ethylidene di chloride)
1,1-Dichloroethane (vinylidene chloride)
1,2-Dichloroethane (ethyl ene dichoride)
1,2-Dichloropropane (propylene di chloride)
2-Propanol (isopropyl alcohol)
Acetone
Acrylonitrile
Bromodichloromethane
Butane
Carbon disulfide
Carbon monoxide0
Carbon tetrachloride
Carbonyl sulfide
Chlorobenzene
Chlorodifluoromethane
Chloroethane (ethyl chloride)
Chloroform
Chloromethane
voca
N
Y
Y
Y
N
Y
Y
N
Y
Y
Y
Y
N
Y
Y
Y
N
Y
Y
Y
Hazardous Air
Pollutant"
(HAP)
Y
Y
Y
Y
Y
Y
N
N
Y
N
Y
Y
N
Y
Y
Y
N
Y
Y
N
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TABLE 15.4-1
(CONTINUED)
Compound
Di chl orob enzened
Dichlorodifluoromethane
Di chl orofluorom ethane
Dichloromethane (methylene chloride)
Dimethyl sulfide (methyl sulfide)
Ethane
Ethanol
Ethyl mercaptan (ethanethiol)
Ethylbenzene
Ethylene dibromide
Fluor otri chl or om ethane
Hexane
Hydrogen sulfide
Mercury6
Methyl ethyl ketone
Methyl isobutyl ketone
Methyl mercaptan
Pentane
Perchl oroethyl ene (tetrachl oroethyl ene)
Propane
voca
Y
N
N
N
Y
N
Y
Y
Y
Y
N
Y
N
N
Y
Y
Y
Y
N
Y
Hazardous Air
Pollutant"
(HAP)
Y
N
N
Y
N
N
N
N
Y
Y
N
Y
N
Y
Y
Y
N
N
Y
N
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TABLE 15.4-1
(CONTINUED)
Compound
Tri chl oroethyl ene (tri chl oroethene)
t- 1 , 2-Di chl oroethene
Vinyl chloride
Xylenes
voca
Y
Y
Y
Y
Hazardous Air
Pollutant"
(HAP)
N
N
Y
Y
NOTE: This is not an all-inclusive list of potential LFG constituents, only those for which test data were available
at multiple sites (EPA 1995).
a Reactive VOC.
b Hazardous Air Pollutants listed in Title III of the 1990 Clean Air Amendments.
0 Carbon monoxide is not a typical constituent of LFG, but does exist in instances involving landfill
(underground) combustion. Of 18 sites where CO was measured, only 2 showed detectable levels of CO.
d Source tests did not indicate whether this compound was the para-or ortho- isomer. The para- isomer is a
Title Ill-listed HAP.
e No data were available to speciate total Hg into the elemental and organic forms.
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
The alternative methods to estimate the data used in the landfill equation are as follows:
• Alternative Method One: Guidelines for using assumptions with landfill data;
• Alternative Method Two: Regression model; and
• Alternative Method Three: Population-based waste generation factor.
All of the methods use the AP-42 landfill emissions equation or LandGEM to calculate
emissions. Refer to AP-42 and Sections 3 and 4 of this chapter for information about using the
equation or the model.
5.1 ALTERNATIVE ONE: GUIDELINES FOR USING ASSUMPTIONS
WITH LANDFILL DATA
This method is a set of decision-making rules to follow for data collection of landfill
waste-in-place and landfill opening and closure dates used in the AP-42 equation or the
LandGEM, and assumptions to use when local data are not available. This method should be
used when the agency's budget does not allow the extensive data collection that is needed for the
preferred method, or the data for all of the landfills in the inventory area are not available. If the
inventory area is made up of many counties (>10), then the second alternative method may be a
better approach. Although the first method is very similar to the approach used in the preferred
method, a distinction is being made between the two because the use of assumptions and
generalizations in the alternative method increases the uncertainty of the emission estimates.
The first step to take for this method is to identify the landfills in the inventory area. Use solid
waste agency data (county, state, or EPA Regional Office) or data from air permitting groups,
local planning departments, or local or state tax records. Information about closed landfills may
be available from long-term employees at state, county, or local health or sanitation departments.
Second, identify landfills in the inventory area that are listed in the point source inventory.
These point sources will not need to be addressed in the area source inventory. Use the
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preferred method for as many landfills as possible that remain. The landfills that have been
addressed at this point will probably be active, the largest, and also most likely to have controls.
The final remaining landfills may make only a minor contribution to the source category
emissions. Therefore, the agency preparing the inventory should decide if these smaller landfills
are significant enough to warrant the effort needed to produce emission estimates from them.
The effort expended for these remaining landfills may be minimized if the proportion of
emissions is small.
The third step is to collect information about the acreage of the remaining landfills. Land use
information from planning boards and information from tax records is best. If the acreage that is
filled at the time of the inventory year is available, it will be preferable to total acreage, which
may be only partly used.
If information is available about the depth of the individual landfills and landfill opening and
closure dates are available, then it should be collected as well. Some states and counties have
rules about landfill construction that define appropriate depths. State and county solid waste
experts should be able to define a reasonable depth for area landfills. Health and sanitation
departments may also have information about older landfills. Employees of long standing in
these departments may provide particularly useful information.
Fourth, develop waste-in-place estimates using the following:
• Estimate the capacity for each landfill:
Estimated T ,,,,, Estimated
Landfill
Capacity = . * Landfill
f\r i \ Acreage „ ,,
(Volume) & Depth
The LandGEM's utilities can be used to perform this calculation as well. A
utility for estimating refuse in place from landfill dimensions is available in the
Windows™ version of the program.
• If calculating volume is not practical from available data, determining weight and
converting this to volume can be done using the following from AP-42:
1,100 to 1,400 lb/yd3 for compacted waste;
1,700 to 1,900 lb/yd3 for waste that has undergone degradation and
settling; or
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Use 1,160 lb/yd3 if it is unknown whether the waste has degraded, or been
compacted.
For example:
Estimated Estimated
Capacity = Capacity * 1,160 lb/yd3
(Weight) (Volume)
Another method of estimating the waste-in-place, which is needed for the emissions equation, is
by using an estimate of the percentage filled. Alternatively, fill can be estimated by
proportioning the estimated capacity by the years that the landfill has accepted or is expected to
accept waste.
If opening and closure dates are known, then closed landfills can be assumed to have filled their
capacity. Waste in place for landfills that are still accepting waste can be estimated by dividing
the capacity by the number of years the landfill is accepting waste (closing year - opening
year +1). Multiply the annual acceptance rate by the number of years that the landfill has been
open.
If opening and closure dates for the landfills are not available, assume that the landfill is still
accepting waste, and opened 25 years before the inventory year. This is a conservative
assumption, and will assign most of the emissions to the inventory year. If only the closing date
is known, assume that the landfill accepted waste for 10 years. This is also a conservative
assumption.
Use the AP-42 defaults for L0 and k in the equation. Calculate VOC or HAP emissions using the
default concentrations and equations in AP-42.
This alternative method should allow inventory preparers the opportunity to prepare fairly
reliable estimates for the largest landfills in the inventory area and more uncertain, but
conservative estimates for the smaller landfills.
5.2 ALTERNATIVE Two: REGRESSION MODEL
This method uses information gathered about a sample of the landfills in an inventory area to
develop a regression model that can be used to estimate the waste in place for all of the landfills
in the inventory region. Regression is used to analyze how a dependant variable is affected by
the values of one or more independent variables. The dependant variable in this case is landfill
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waste in place, and the independent variables are the surrogate factors that will be used to
calculate waste in place estimates for other counties within the inventory area.
This method can be used as an alternative to the more detailed data collection of the preferred
method when the number of counties in the inventory area is large (>10). If there are fewer than
10 counties or other geographic units in the inventory area, then this method is not suitable and
the first alternative method should be used. This approach uses regression analysis to relate
surrogate factors to landfill attributes. Because this method uses a survey of an inventory area
subset, and the regression output includes statistical indicators of the model validity, personnel
working on this method should have enough training in statistics to ensure that the results of the
survey and the model are valid.
The steps taken to develop a regression model are as follows:
• Define the scope of the landfill population in the inventory area. Identify counties
or other geographical units that can be efficiently surveyed and that, when
combined, represent a reasonable cross section of a statistically valid size. More
data points (landfills) will result in a more reliable model.
* Develop a survey approach. A mail out with written forms may be designed, a
telephone survey, or a combination of the two approaches may be used. See the
discussion of surveys in Chapter 1, Introduction to Area Source Emission
Inventory Development, and in Volume I of this series.
• Define what information can be reasonably requested. The information needed
can be used to develop an emissions estimate, such as the amount of waste in
place (or information that allows an estimate of waste in place) and the opening
and closure dates, and information that can be used to develop a surrogate, such
as population, population density, rural/urban population mix, property values,
and land use. The information for the emission estimation will be collected from
the landfill operators or the government agency that oversees landfills for that
area. The surrogate information can come from U.S. Bureau of the Census data
sources, tax records, and county planners. Review the first alternative method for
options when incomplete data are available.
• Distribute the survey and compile the results. If information about waste in place
could not be directly collected, then use the methods discussed in the first
alternative method to estimate waste in place for the surveyed landfills.
• Use the waste-in-place numbers and the surrogate values to develop a regression
model of the relationship between those variables. Develop a regression model of
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the relationship between the landfill age and the surrogate factors as well.
Spreadsheet programs such as Lotus® 1-2-3, Quattro® Pro and Microsoft® Excel
provide regression analysis as a function.
The results of the regression analysis should be reviewed for validity.
• Collect the surrogate information from the unsurveyed counties and apply the
regression model factors.
• Use the AP-42 equation or LandGEM to calculate emissions using the estimated
waste in place and the estimated landfill age for each county.
5.3 ALTERNATIVE THREE: POPULATION-BASED WASTE
GENERATION FACTOR
This method should be used only if there are no other means with which to calculate landfill
emissions. Emissions are based on total waste in place, so waste generation must be calculated
for years previous to the inventory year. Although landfills can generate emissions for many
years, the greatest emissions can be assumed to be emitted from waste 25 years old or less. The
steps for calculating waste in place are:
• Collect population figures for the inventory year and the 24 years previous for a
total of 25 years of population data.
• Multiply the waste generation factor of 0.69 tons/person/year times the population
for each year (EPA, 1996c).
* Multiply tons by 0.9072 to get megagrams (tonnes).
• Use the annual waste estimates in the LandGEM, or calculate the average annual
waste estimates and use that value in the AP-42 equation.
Because this method uses no landfill-specific information, control factors cannot be applied to
these estimated emissions.
The per capita waste generation factor supplied here is from the U.S. EPA Office of Solid Waste
and Emergency Response annual publication, Characterization of Municipal Solid Waste in the
United States: 1995 Update, and represents the estimated average generation of all types of
MSW in 1994. Waste types include yard trimmings, paper, glass, metals and plastics which may
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be composted or recycled in some areas.2 The major uncertainty of this method is that it does
not account for the amount of waste shipped into or out of a county.
2 The EPA Office of Solid Waste maintains a World Wide Web page at:
http://www.epa.gov/epaoswer/osw/index.htm, can be reached by telephone through the RCRA
hotline at 1-800-424-9346 or 1-800-553-7672, and by mail at: RCRA Information Center, U.S.
EPA, 401 M Street, SW (5305W), Washington, DC 20460.
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QUALITY ASSURANCE/QUALITY
CONTROL
During the inventory planning process, the agency should define the data quality objectives for
the inventory and set data quality goals for the emission estimates developed for this source
category. QA and QC methods may vary based on the data quality objectives for the inventory.
The Quality Assurance Procedures Volume (Volume VI) of the EIIP series discusses methods to
be used to ensure the development of a quality inventory. QA for area source inventories is also
discussed in Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development.
When using the preferred method, the survey planning, sample design, and data handling should
be planned and documented in the inventory QA/QC plan. Refer to the discussion of survey
planning and survey QA/QC in Chapter 1 of this volume, and Volume VI of the EIIP series.
Data handling for the data collected using all of the methods should also be planned and
documented in the inventory QA/QC plan. Other than the conversion of the waste-in-place
estimates from volume to weight units, data handling does not involve any category-specific
issues. However, the first and second alternative methods require decision making and
assumptions in order to develop emission estimates. All of these decisions and assumptions
should be clearly documented, supported in writing, and reviewed as the estimates are
developed. Please consult the Emission Inventory Improvement Program (EIIP) volume on
inventory QA/QC for more information about data handling and documentation.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
Surveys are theoretically the most accurate approach for estimating emissions, but also are the
most expensive. The advantage to using a survey is that specific information about the landfills
in an area are collected in terms of the landfill fill and age, controls in place are more accurately
reflected with actual data, and the local practices in waste disposal are reflected. The level of
detail that is possible to collect with a survey is not available when using the alternative
methods.
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However, to following the preferred method does not necessarily require a survey. Information
that is current and reliable may be available to state and local agencies for some landfills
(especially larger landfills) from permits and reports required under RCRA, the NSPS, or the
State or Federal plan that implements the Emission Guidelines.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
The DARS scores for each method are presented in Tables 15.6-1 through 15.6-4. Table 15.6-5
is a summary of all of the methods' composite scores. A range of scores is given for the first and
second alternative method to reflect variability in survey techniques and the validity of the
assumptions that have been made in the course of data gathering. More information about
DARS scoring can be found in Appendix F of EIIP Volume VI.
TABLE 15.6-1
PREFERRED METHOD DARS SCORES:
USING INFORMATION COMPILED AS PART OF A PERMIT
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5
0.5
0.3
0.8
0.53
Activity
0.8
1.0
1.0
1.0
0.95
Emissions
0.4
0.5
0.3
0.8
0.5
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TABLE 15.6-2
ALTERNATIVE METHOD 1 DARS SCORES:
GUIDELINES FOR USING ASSUMPTIONS WITH LANDFILL DATA
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5
0.5
0.3
0.8
0.53
Activity
0.3 -0.6
0.7-0.9
1.0
0.8- 1.0
0.7-0.88
Emissions
0.15-0.30
0.35-0.45
0.3
0.64-0.8
0.36-0.46
TABLE 15.6-3
ALTERNATIVE METHOD 2 DARS SCORES: REGRESSION MODEL
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5
0.5
0.3
0.8
0.53
Activity
0.5-0.6
0.7
0.7-0.9
0.9
0.7-0.78
Emissions
0.25-0.30
0.35
0.21 -0.27
0.72
0.38-0.41
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TABLE 15.6-4
ALTERNATIVE METHOD 3 DARS SCORES: POPULATION-BASED WASTE FACTOR
Attribute
Measurement
Source Specificity
Spatial
Temporal
Composite Scores
Scores
Factor
0.5
0.5
0.3
0.8
0.53
Activity
0.6
0.1
0.3
0.5
0.38
Emissions
0.30
0.05
0.09
0.40
0.21
TABLE 15.6-5
COMPOSITE DARS SCORES: SUMMARY FOR ALL METHODS
Method
Preferred Method
Alternative Method 1
Alternative Method 2
Alternative Method 3
Scores
Factor
0.53
0.53
0.53
0.53
Activity
0.95
0.7-0.88
0.7-0.78
0.38
Emissions
0.5
0.36-0.46
0.38-0.41
0.21
All of the DARS scores for the factor ratings are the same. This is because all of the methods
use the same emission estimation method, the AP-42 equation for landfill gas emissions. The
difference between the methods is in the data collection for the variables used in the AP-42
equation: waste in place, landfill opening and closure dates, k, L0, and the concentration of
NMOC in the landfill gas. The data collection methods are scored as activity ratings.
Scores for all methods are limited by the fact that emissions from this source category depend on
a number of variables that cannot be adequately modeled in a single, fairly simple equation. The
most significant limitation to the emission equation is that without detailed understanding of the
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types of wastes being landfilled (expressed as the generation potential, L0) and the impact of
climate on landfills (expressed as the methane generation constant, k), local variables are not
reflected in the calculation. It is difficult to generalize landfill emissions from region to region
because local waste management will determine how much of the waste is recycled and what
types of wastes are landfilled, and local rules will determine landfill construction and the use of
controls.
Activity data, if it is understood to be the waste in place, landfill age, and control information,
can be collected with a satisfactory amount of detail. The preferred method collects data for
each landfill for the time period of the inventory. All scores assume that adequate QA/QC
measures are performed and that no significant deviations from the prescribed methods have
been made. If these assumptions are not met, new BARS scores should be developed according
to the guidance in Appendix F of the EIIP QA Procedures volume.
DARS scores vary for Alternative Method One depending on how many of the landfills must
have assumptions made about their capacity or age, and how significant their emissions are
compared to those for which the detailed information is available. The scores for Alternative
Method Two will vary based on how many counties the survey portion of the study can cover,
and how closely the surveyed counties represent the estimated counties. Alternative Method
Three has the lowest scores of all of the methods because using a per capita estimate of waste
generation as a surrogate for waste in place will not reflect the local variables of waste reduction
and recycling, incineration, or shipping the waste out of or into the area. Also, population can
be a poor surrogate because it will not include waste generated by people that live outside of the
area but work in the area. This method also will not include the effect of controls.
6.1.2 SOURCES OF UNCERTAINTY
Estimates generated using any of these methods are relatively uncertain. A variety of chemical,
biological, and physical factors affect the rate of landfill emissions. The only reliable way to
determine emissions is by direct, continuous measurement. Source testing can provide a
snapshot of emissions at a given time period, but landfill emissions can fluctuate over time.
Therefore, source testing results are not always a reliable estimator of average or future
emissions without a large number of repeated samples. Even with repeated testing, it is still
necessary to predict future emissions using AP-42 equations and the site-specific measured
methane generation rate constant (k), and NMOC or and HAP concentrations. This is because
mass emission rates from landfills change from year to year as additional waste is added, and as
the initial waste gets older.
The preferred method gives higher-quality estimates than any of the alternative methods but
requires more effort. The level of effort required to calculate emissions using the preferred
method will vary depending on the availability of information from permitting agencies and the
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form in which it can be retrieved. Readers are reminded that the goal of the inventory is to
locate and estimate the largest share of landfill emissions possible within the budget for this
source category. Small landfills that closed before 1987 (for Emission Guidelines and RCRA
States should have a list of landfills that accepted waste since 1987) may require more time and
effort than their proportionate contribution to the source category emissions total. It is possible
to estimate a range of error that results from not including those landfills in the inventory.
Landfill emissions depend on a complex combination of variables and, even with the most
accurate data for waste in place and the landfill age, emissions cannot be characterized as
accurately as those for other source categories may be.
The first alternative method is similar to the preferred method, but uses assumptions that
introduce uncertainty to the estimates. This uncertainty cannot be quantified. Statistics
describing the error and the uncertainty of the activity for the second alternative method are
calculated with the regression model. This second method will require a similar amount of
effort to collect and compile the survey information from the selected counties as that needed for
the preferred method, but the remaining portion of the inventory area requires much less effort.
The uncertainty of the emission estimates and the activity information developed through the
preferred and second alternative methods may be quantified (see QA Procedures volume,
Chapter 4). However, the statistics needed to quantify the uncertainty of the first and third
alternative methods are incomplete. Activity for the third alternative method is based on the use
of population as a surrogate, which does not take into account local waste management practices
or possible controls being used in the inventory area.
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from landfills. A
complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 15.7-1 lists the applicable SCCs for landfills.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use
in regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data
elements necessary to complete the data set for use in regional or national air quality and human
exposure modeling. The inventory preparer should review the area source portion of the
acceptable file format(s) to understand the necessary data elements. The EPA describes its use
and processing of the data for purposes of completing the national inventory, in its Data
Incorporation Plan, also located at http://www.epa.gov/ttn/chief/net/.
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TABLE 15.7-1
AREA AND MOBILE SOURCE CATEGORY CODES FOR
MUNICIPAL SOLID WASTE LANDFILLS
Process Description
Landfills: All Categories
Landfills: Industrial
Landfills: Commercial/Institutional
Landfills: Municipal
Source Category Code
26-20-000-000
26-20-010-000
26-20-020-000
26-20-030-000
15.7-2
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REFERENCES
Federal Register. May 30, 1991. Standards of Performance for New Stationary Sources and
Guidelines for Control of Existing sources: Municipal Solid Waste Landfills; Proposed Rule,
Guideline, and Notice of Public Hearing. 40 CFR Parts 51, 52, and 60. Vol. 56, No. 104. p.
24468.
EPA. 1999. Municipal Solid Waste Landfills, Volume 1: Summary of the Requirements for the
New Source Performance Standards and Emission Guidelines for Municipal Solid Waste
Landfills. U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, EPA-453/R-96-004. Research Triangle Park, North Carolina.
EPA. 1996a. Characterization of Municipal Solid Waste in the United States: 1995 Update.
U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, EPA-
530/R-96-001. Washington, D.C.
EPA. 1998a. Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and
Area Sources, Fifth Edition, AP-42. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1998b. Landfill Gas Emission Model (LandGEM), Users Manual, Version 2.01.
U.S. Environmental Protection Agency, Control Technology Center, EPA-600/R-98-054.
Research Triangle Park, North Carolina.
EPA. 1995. Air Emissions from Municipal Solid Waste Landfills - Background Information for
Final Standards and Guidelines. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards, EPA-453/R-94-021. Research Triangle Park, North Carolina.
EPA. 1994a. International Anthropogenic Methane Emissions: Estimates for 1990. U.S.
Environmental Protection Agency, Office of Policy Planning and Standards,
EPA-230/R-93-010. Washington, D.C.
EPA. 1994b. AIRSDatabase. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1991. LandGEMDatabase. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards. Research Triangle Park, North Carolina.
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EPA. 1988. National Survey of Solid Waste (Municipal) Landfill Facilities.
U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response,
EPA-530/SW-88-034. Washington, D.C.
Steuteville, R. 1995. The State of Garbage in America. BioCycle. April: 54-63.
Steuteville, R. 2000. The State of Garbage in America. BioCycle. April: 32-39.
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APPENDIX A
Landfill Gas
Emissions Model
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APPENDIX A
This appendix is organized into the following sections:
15.A-1 Abstract
15.A-2 Introduction
15.A-3 System Utilities
15.A-4 Examples: Steps for Running a Study Using the Model
15.A-5 Potential Operational Errors
Attachments
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15.A-1 ABSTRACT
This document is an abridged user's guide for a computer model, the Landfill Gas Emissions
Model (LandGEM), for estimating air pollutant emissions from municipal solid waste (MSW)
landfills. The model was developed by the Control Technology Center. This manual provides
step-by-step guidance for using this model. The Landfill Gas Emissions Model can be used to
estimate emission rates for methane, carbon dioxide, nonmethane organic compounds, and
individual air pollutants from landfills for emission inventories. The program can also be used
by landfill owners and operators to determine if a landfill is subject to the control requirements
of the federal New Source Performance Standard (NSPS) for new MSW landfills (40 CFR 60
subpart WWW) or the Emission Guidelines for existing MSW landfills (40 CFR 60 Subpart
Cc).
The model is based on a first order decay equation. The model can be run using site-specific
data for the parameters needed to estimate emissions or, if no site-specific data are available,
using default values. There are two sets of default values. One set is based on the requirements
of the NSPS and Emission Guidelines. This set of default values produces conservative
emission estimates and can be used to determine whether the landfill is subject to the control
requirements of the NSPS and Emission Guidelines. The other set of default values is based on
emission factors in the U.S. Environmental Protection Agency's (EPA's) Compilation of Air
Pollutant Emission Factors, AP-42 (EPA, 1998a). This set of default values produces more
representative emission values and can be used to produce typical emission estimates to be used
in emission inventories. The default values presently in the model are the parameter values
recommended by the NSPS and AP-42 as of September 1997. However, these parameter values
may be revised in future updates of the model based on new information collected by the EPA.
15.A-2 INTRODUCTION
The Landfill Gas Emissions Model (LandGEM) provides an automated estimation tool for
quantifying air emissions from municipal solid waste (MSW) landfills. This document provides
an introduction to the model and step-by-step instructions for using it. The model was
developed by the Control Technology Center (CTC) of the U.S. Environmental Protection
Agency and can be obtained by downloading from the TTN Web (http://www.epa.gov/ttn/catc/).
A glossary of terms is available as Attachment 15.A-1.
Air emissions from landfills come from landfill gas, generated by the decomposition of refuse in
the landfill. Landfill gas is assumed by this model to be roughly half methane and half carbon
dioxide, with additional, relatively low concentrations of other air pollutants. The following
information is needed to estimate emissions from a landfill:
• The design capacity of the landfill,
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• The amount of refuse in place in the landfill, or the annual refuse acceptance rate
for the landfill,
• The methane generation rate (k),
• The potential methane generation capacity (L0),
• The concentration of total nonmethane organic compounds (NMOC) and
speciated NMOC found in the landfill gas,
• The years the landfill has been in operation, and
• Whether the landfill has been used for disposal of hazardous waste (codisposal).
Default values are available for k, L0, NMOC concentration, and toxic air pollutant
concentrations.
The estimation method used by the model is a simple first-order decay equation. Because the
data available for landfills, such as data on the quantity, age, and composition of the refuse in
the landfill are limited, using a more sophisticated calculation method was not justified. The
Landfill Gas Emissions Model estimates emissions of methane, carbon dioxide, nonmethane
organic compounds, and selected air pollutants. A list of the air pollutants for which the model
will calculate emissions is included as Attachment 15.A-2.
Information on the assumptions used in the model can be found in the background information
document (NTIS-PB91-197061) written to support the Standards of Performance for New
Stationary Sources (40 CFR 60 Subpart WWW) and Emission Guidelines for Control of
Existing Sources (40 CFR 60 Subpart Cc) and in the public docket (Docket A-88-09).
The Landfill Gas Emissions Model can be used with site-specific data for all the information
needed to generate emission estimates, or it can be used with two different sets of default values.
One set of default values (the CAA defaults) is for estimating emissions to determine the
applicability of the Clean Air Act (CAA) regulations for MSW landfill emissions, specifically
the New Source Performance Standards (NSPS) for new MSW landfills and the Emission
Guidelines for existing MSW landfills. The CAA default values in the model provide emission
estimates that would reflect the expected maximum emissions and generally would be used only
for determining the applicability of the regulations to a landfill. To estimate emissions for an air
emissions inventory in the absence of site-specific data, a second set of default values (the
AP-42 defaults) is provided in the model. The AP-42 default values in the model are based on
emission factors from the U.S. Environmental Protection Agency's Compilation of Emission
Factors, AP-42 (EPA, 1998a). The AP-42 default values provide emission estimates that should
reflect typical landfill emissions and are the values suggested for use in developing estimates for
state inventories.
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15.A-3 SYSTEM UTILITIES
The landfill model is designed as a tool to estimate landfill emissions. To aid in estimation, the
landfill model has been equipped with Help screens to describe and explain features of the
model and its functions. In addition, the model has been equipped with utility functions to assist
the user. Like Help screens, the utilities for this program are available when any of the model
windows (i.e., the Operating Parameters window or a Report window) is being used. There are
three utilities: a Unit Conversion utility, a Refuse Estimator utility, and an Autocalc function.
These utility functions are described in the succeeding sections.
15.A-3.1 The Unit Conversion Utility
This program uses metric units (such as megagrams of refuse) rather than English units (such as
tons of refuse), because metric units are used by the federal government and for the CAA
regulations for MSW landfills. However, users of the model who prefer to use English units can
use the conversion utility to convert English units to metric units, or vice versa.
To use the Unit Conversion utility:
1. Choose Unit Conversions from the Utilities menu.
2. Type the units to be converted in the "To convert from" text box. The units should be in a
format specified by the program. This format is explained in the Help for the Unit
Conversion utility. Select [Help], then choose Unit Formulas in the topics list on the main
Help screen. For example, use the symbol A to indicate an exponent, * to indicate
multiplication, and / to indicate division. The following are several examples of units in
formats that will be accepted by the system: kg/mA3; 1.25 kg/m/s; 1.25 kg(m*s)A2.
3. Type the units to convert to in the "to" text box.
4. Select [Convert] and the units will be converted. If the units you typed in were units only,
with no value, the result of conversion will be a factor by which to multiply the value. If the
units you typed in were accompanied by a value (e.g., 35,000 tons) the result will be a
converted value (e.g., 31,751 Mg).
5. [Update] will update the units conversion database by adding new units or editing units
already included in the conversion database. See below.
6. To exit the Unit Conversion utility, select [Cancel] or double click on the close button in the
upper right corner of the Utility window.
You can add new units and delete or edit existing unit conversion factors in the Unit Conversion
utility with the Unit Database Maintenance facility.
To update the Unit Conversion Utility:
1. Choose Unit Conversions from the Utilities menu.
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2. In the Unit Conversions screen, select [Update]. A Unit Database Maintenance dialog box
will come up.
3. Type the unit to add to the unit conversion database in the "Unit" text box.
4. Specify whether the unit is case dependent. Metric units, for example, are generally case
dependent; mg and Mg are different units. English units are generally not case dependent;
ton and Ton are the same unit.
5. Select [Locate] to locate a unit in the database, to be sure the unit is not already there.
6. Type the conversion factor for the unit in the "Factor" text box.
7. Type the metric unit into which the English unit will be converted in the "Base Unit" text
box. The base units should be base units in the metric system, if possible (that is, you
would use g rather than Mg as a base unit). The base units of the metric system are listed in
Help. To access, select [Help]. Choose Search Method in the topics list on the main Help
screen and "base quantity" highlighted in the Help text. A list of the metric base units and
abbreviations for them will appear.
8. Select [Add] or [Delete] to add a unit to or delete it from the conversion database.
9. Updating the conversion database is explained in the Help for the Unit Conversion Utility.
To access help for updating the conversion database, select Help. Choose Adding Units or
Database Maintenance from the topics list on the main Help screen.
15.A-3.2 The Refuse Estimator Utility
This program requires refuse in place or refuse acceptance rates, and calculates emissions using
refuse in place. The Refuse Estimator utility allows a user to estimate emissions using this
program even if no refuse in place data are available other than the dimensions of the landfill.
To use the refuse estimator:
1. Select Refuse Estimator from the Utilities menu.
2. In the Refuse Estimator dialog box, select the Landfill Size (Acres) text box. If you do not
have the size of the landfill in acres, use the Unit Conversion utility to convert to acres.
3. Enter the acreage of the landfill.
4. Select the Landfill Depth (Feet) text box. Enter the depth of the landfill in feet. Use the
Unit Conversion utility if necessary to convert the depth to feet.
5. Select [Estimate]. The estimator will estimate the refuse in place in Mg and the value will
appear in the Estimated Refuse in Place (Mg) text box.
6. Select [OK] to exit the Refuse Estimator.
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15.A-3.3 The Autocalc Function
The Autocalc function is located under the Edit menu. This function can be used to assist the
user in calculating either waste acceptance rates or refuse in place for the years of operation of
the model. The Autocalc function is easy to use and allows the user either to enter an average
acceptance rate for a period of operation or to linearly interpolate refuse data between two years
(e.g., year 1 and year 10 of a given period of uniform or linearly increasing or decreasing waste
acceptance). Examples of how to use the Autocalc function are available in Attachment 15.A-3.
The user should take caution: The Autocalc function does not recognize the landfill capacity as
the upper limit which the refuse in place cannot exceed. It is possible to use the Autocalc
function to calculate values for the acceptance rates or the refuse in place that cause the final
values for the accumulated refuse to exceed the landfill capacity. If accumulated refuse exceeds
the landfill capacity, the data must be erased or adjusted before a report can be generated.
15.A-4 EXAMPLES: STEPS FOR RUNNING A STUDY USING THE MODEL
This section outlines a step-by-step example of how to operate the emission estimation model
for a standard case. Section 4.1 of this document describe the basic operation of the model. The
methodology for modifying the parameters to run specific scenarios are described in section 4.3.
The following steps need to be followed to run a model:
• Open or Create a New Landfill Study,
Select Model Parameters for Calculating Emissions,
• Define the Operating Parameters of the Landfill,
• Adapt the Model for a Specific Scenario,
Generate a Report, and
Save the Landfill Study.
The following Model Parameters are needed to estimate emissions from a landfill:
The methane generation rate (k),
The potential methane generation capacity (L0),
The estimated percentage composition of methane and carbon dioxide in the
landfill gas (the default value is a 50/50 split),
The concentration of nonmethane organic compounds (NMOC) and speciated
NMOC found in the landfill gas,
The concentrations of toxic air pollutants found in the landfill gas, and
Whether the landfill has been used for disposal of hazardous waste (codisposal).
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The following Operating Parameters are needed to estimate emissions from a landfill:
The years the landfill has been in operation (including the Closure Year),
• The design capacity of the landfill, and
The amount of refuse in place in the landfill, or the annual refuse acceptance rate
for the landfill.
The following data entry pattern is recommended when entering operating parameters into the
computer model:
Select the Year Opened;
• Select the final year for which information is available (Current Year);
Make any changes to the Closure Year that are needed;
• Enter the Landfill Capacity; and
Enter the Acceptance Rate or Refuse In Place data.
With the exception of the requirement that the landfill capacity must be entered before any waste
data, this recommended order of entry is not required.
15.A-4.1 An Example User Session
This section describes a step-by-step procedure for estimating landfill emissions using the
model, which can be operated in Windows 3.1, Window 3.11, or Windows 95. The data
provided below are for a generic landfill and a generic study.
Landfill Scenario Model Parameter Data:
Methane Generation Rate (k): AP-42 default
Methane Generation Potential (L0): AP-42 default
Percentage Composition of CO2 and CH4: 50%/50%
Concentration of NMOC: AP-42 default
Selected Air Pollutant: add EthylMercaptan
(MW = 62.13; concentration = 0.86)
Landfill Type: Codisposal
Landfill Scenario Operating Parameter Data:
Year Opened: 1975
Current Year: 1995
Landfill Design Capacity: 3,000,000 Mg
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Refuse in Place in 1980: 330,500 tons
Annual Refuse Acceptance Rate: 109,890 ton/yr from 1980 to 1994
Autocalc: (Refuse in place from 1975 to 1979)
Closure Year: 2001
Steps
I. Open or Create a New Landfill Study
1. Launch the program (either by double-clicking on the program icon or selecting
landwin.exe from the Program Manager).
2. The Landfill Gas Emissions Model will open with an abbreviated set of menus.
From the File menu, select [New] or [Open] to run a landfill study. A landfill
study window (the Operating Parameters window) will open. A new landfill
study is assigned the default name landfill. 000. This name will be replaced by a
user-supplied name when the landfill study is saved and named.
II. Select Model Parameters for Calculating Emissions
A. Methane Generation Rate (k) and Methane Generation Potential (L0)
1. To set the default values for k, L0, and NMOC concentration used to calculate
emissions, select the Defaults menu.
2. To set the system for estimating emissions for emission inventories for municipal
solid waste landfills, select AP-42.
B. Percentage Composition of CO2 and CH4
1. From the Parameters menu, select Air Pollutants. An Air Pollutant Compound
Parameters dialog box will appear.
2 Methane and carbon dioxide are assumed to make up 50 percent each of the
landfill gas. Leave these percentages as they are.
C. Concentration of NMOC
1. From the Parameters menu, select Air Pollutants. An Air Pollutant Compound
Parameters dialog box will appear.
2. Because the AP-42 defaults were selected from the Defaults menu (see step A.2.)
the NMOC concentration has already been set as the AP-42 default; the other
options (i.e., CAA defaults and User Specific defaults) are dimmed and cannot be
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selected. Only when the User Specific option is selected from the Defaults menu
can the value for the NMOC concentration be changed.
D. Concentrations of Toxic Air Pollutants
1. A total of 47 air pollutants expected to be emitted from landfills is included in the
program. Air pollutants that are designated as HAP and/or VOC are indicated as
so in parentheses. Additional air pollutants can be added or inappropriate ones
can be deleted. To edit the list of toxic air pollutants for which emissions will be
estimated, select Air Pollutants from the Parameters menu. In the Air Pollutant
Compound Parameters dialog box that opens, select [Edit Air Pollutants]. A
Selected Air Pollutants dialog box will open.
2. To add an additional entry for Ethyl Mercaptan, type over the existing data that
appear for a pollutant in the box. Start by selecting the name of the chemical in
the text box. Delete this information and type in Ethyl Mercaptan.
3. Select the molecular weight text box. Delete the information in the box and type
in 62.13.
4. Select the Concentration, Codisposal, text box. Delete the information in the box
and type in 0.86. Repeat this step for the concentration, no codisposal, text box.
5. Choose [Append] to add the record for Ethyl Mercaptan.
6. Select [OK] to accept these data and to add Ethyl Mercaptan to the list of air
pollutants for which emissions will be estimated. In the Air Pollutants Parameters
dialog box, select [OK] to accept the set values for pollutant concentrations.
E. Landfill Type
1. Select Parameters from the Main Menu.
2. Select Landfill type.
3. Select Codisposal. This option should be used when the landfill has been used to
dispose of hazardous waste.
III. Define the Operating Parameters of the Landfill
A. Enter Year Opened and Design Capacity
1. Select the Year Opened text box in the data entry box. The year opened defaults
to 10 years before the current year (determined from the computer's clock).
2. Delete the default Year Opened. Enter 1975.
3. Delete the default Current Year. Enter 1995.
4. Select the Capacity text box and type in 3.OE+06 for 3,000,000 Mg refuse
capacity. Press Enter to accept this value.
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B. Enter Refuse In Place for the First Year of Accepting Refuse
1. Because the refuse in place in 1980 and annual refuse acceptance rate values for
this landfill are recorded in tons and the program calls for megagrams, the units of
measure need to be converted.
l(a). From the Main Menu, select Utilities.
l(b). Select Unit Conversions to bring up the dialog box for the unit conversion
utility.
l(c). Select the "To convert from" text box. Type in the refuse in place value,
including the units: 330,500 tons.
l(d). Select the "to" text box. Type in the units to which you want to convert:
Mg.
l(e). Select [Convert].
l(f). The box with the result (the "multiply quantity in source unit by" text box)
will give the value of the refuse in place in Mg. This value rounds to
300,000 Mg. Record this value to use later.
l(g). To convert the annual acceptance rate to Mg, select the "To convert from"
text box. Delete the value in it and type in 109,890 tons.
1 (h). Select the "to" box and type in Mg.
1(1). Select [Convert]. The annual acceptance rate in Mg rounds to 100,000
Mg. Record this value to use later.
l(j). To exit the unit conversion utility, Select [Cancel] or double-click on the
close box in the upper right corner of the conversion utility dialog box.
2. In the Operating Parameters table, select the year 1980. The cells in the
Acceptance Rate/Refuse in Place column for 1980 will be highlighted by a bold
box around them.
3. Select the button in the data entry box for Refuse in Place.
4. Select the Waste Value text box.
5. Type in 3.0E+05 (300,000) for the refuse in place in 1980. Press Enter to accept
the value. The program will enter 3.0E+04 as the refuse in place for all following
years up to the current year until you enter specific values for specific years. The
table represents refuse in place, which is cumulative.
6. Highlight the Refuse in Place cells from 1975 through 1980. Choose the Autocalc
function from the Edit menu. By using the Autocalc function, you will assume
that waste has been received at a uniform rate of 60,000 Mg/yr since the landfill
opened. You will see this change reflected in the refuse acceptance rates from
1975 through 1979.
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C. Enter Refuse Acceptance Rates for Following Years
1. Enter a refuse acceptance rate for 1980 of 100,000 Mg. Do this by selecting the
Acceptance Rate (Mg) cell in the row for 1980. This selection will select the
Acceptance Rate (Mg/yr) check box on the toolbar. Highlight the entry in the
Waste Value box on the toolbar and type 100,000. Press Enter to accept this
value. [Note: Refuse in place values in this model are calculated at the beginning
of the year. That is, the refuse in place for a landfill is a total of the previous
year's refuse in place and the previous year's refuse acceptance rate. By entering a
value of 100,000 Mg received in 1980, you will not have altered the Refuse in
Place value for that year (i.e., the value will remain 300,000 Mg). However, the
Refuse in Place value for 1981 will be changed to 400,000 Mg.]
2. The refuse acceptance rate remains constant from 1980 through 1994. Using the
Autocalc function will help to speed the data entry rather than repeating step 1 for
each year from 1980 to 1994. To do this, repeat step C. 1 for the year 1994 (i.e.,
enter a refuse acceptance rate for 1994 of 100,000 Mg). Highlight the refuse
acceptance rate cells from 1980 through 1994. Then select the Autocalc function
from the Edit menu. This action will change the refuse acceptance rates for these
years from their default values to 100,000 Mg/yr. Consequently, the refuse in
place values will increase by 100,000 Mg each year from 1981 through 1995. The
refuse in place in 1995 should total 1,800,000 Mg.
D. Closure Year
1. To set the closure year of the landfill, select the Closure Year item from the
Parameters menu.
2. Click on the check box User Specified to permit entry of a certain closure year.
3. Type in 2001. Select [OK]. [Note: When a report is generated the program will
calculate, based on this selection, the difference (1,200,000 Mg) between the
landfill design capacity (3,000,000 Mg) and the refuse in place (1,800,000 Mg) for
the last year for which information has been entered (i.e., 1995). The program
will divide this value by the number of years (6) between the current year (1995)
and the closure year (2001). When a report is generated, the quotient (200,000
Mg/yr) will be entered as the acceptance rates for the years in which no data have
been entered.]
IV. Adapt the Model for a Specific Scenario
Models can be adapted to specific scenarios to account for non-biodegradable waste or areas
of the landfill for which the emissions are collected and controlled. For this study it was
assumed that none of the waste in the landfill is non-biodegradable and that none of the
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emissions from the landfill are collected and controlled. These topics are discussed in more
detail in section 4.3.
V. Generating a Report, Saving a Study, and Exiting the Program
A. Generate a Textual Report of Emissions
1. To see the emissions generated based on the operating parameters, program
defaults, and pollutant concentrations selected, select Reports from the Main
Menu. To generate a textual report of emissions, select Text. A dialog box titled
Select an Emitted Substance will appear.
2. Select EthylMercaptan as the pollutant to report. Select [OK] to generate the
emission report for all the years the landfill is open, plus 200 years past closure.
A report will appear in the landfill study window.
3. To print the report, select Print from the File menu. A Print dialog box will come
up, with a list of variable printers.
4. Select a printer. Select [Print].
(A copy of the text report is included as Attachment 15.A-4).
B. Generate a Graphical Report of Emissions
1. To generate a graphical report of emissions, select Graphics from the
Reports menu.
2. Select Ethyl Mercaptan. Select [OK].
3. Select Print from the File menu. Select [Print].
(A copy of the graphical report is included as Attachment 15.A-5.)
C. Save the Landfill Study
1. To save the landfill study and assign a filename, select Save As from the
File menu. A dialog box for Save As Landfill Study will appear, with a
list of the landfill study files, if there are any (landfill study files are
assigned a .PRM file extension), in the working directory for the program.
The landfill study will be filed in the working directory of the program
unless you specify another directory.
2. Select the File Name text box. Type test. The program will add the .PRM
extension to the filename. This study will be saved in the working
directory for the program as test.PRM. Select [OK].
D. Exit the Program
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Select Exit from the File menu.
15.A-4.2 Adapting the Model for a Specific Scenario
Whenever possible, actual landfill data should be used to run the emissions estimation model.
However, sometimes landfill data may be incomplete or unavailable, or a landfill owner or
operator may wish to estimate the emissions for a landfill that has not yet opened. In such cases,
the model can be used to forecast landfill emissions.
15.A-4.2.1 Forecasting Landfill Emissions
When forecasting emissions, it is best to use any actual data that are available. Even if a
complete set of data is not available, any partial data sets should be put into the model. In cases
where data are not available, the model can be used to give reasonable estimates of the landfill
waste to forecast emissions.
Using the model to forecast emissions is similar to calculating past waste acceptance rates and
refuse in place. The same general methodology described in the previous sections is used: select
the model parameters, identify the length of operation of the landfill, enter the refuse in place or
the acceptance rates of refuse, and run a report.
The principal difference between modeling emissions for existing landfill wastes and forecasting
emissions for future landfill wastes is that, instead of actual data, estimates are needed for the
length of operation, landfill capacity, and landfill waste when forecasting emissions. The
following paragraphs describe the modified approach to use when forecasting emissions.
Length of Operation: Specifying the length of operation of the landfill can be more
complicated when forecasting emissions. If precise years of operation (e.g., 1950, 1990,
1991) are known, they can be entered for the time variables (e.g., Year Opened, the
Current Year, and the Closure Year), and the model functions normally. However, when
precise dates are not known, the length of operation of the landfill can be specified with
generic year numbers, such as 0001 (Year Opened), 0015 (Current Year), and 0016
(Closure Year).
Begin entering the length of time in which the landfill operates by entering a value for the
Year Opened. Then choose a value for the Current Year that allows you to input refuse
data for as many years past opening as you desire. The current year is the last year for
which you will be able to input refuse data into the model. If the landfill will be open
and accepting waste after the current year, then the user can choose a value for the
Closure Year, or the computer model will automatically calculate it. However, if the
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current year is the year in which the landfill will reach its capacity, the user should either
allow the computer to automatically calculate the closure year or specify a closure year
value that is one year in the future of the current year.
Landfill Capacity: The model algorithms and validation procedures require that a design
capacity be entered prior to entering yearly refuse data. That is, even for a landfill not yet
in operation, the total landfill capacity must be specified before any other information
about the refuse in the landfill can be entered. If necessary, the user may use the Refuse
Estimator to determine the landfill capacity from estimated landfill dimensions.
Landfill Waste: For each year of operation, the amount of landfill refuse must either be
entered as a refuse in place or an acceptance rate. If data are available for either refuse
parameter, they should be entered into the model. For years in which no such data are
available, estimates must be provided. The Autocalc Function can assist the user in
entering estimates for years in between those in which refuse acceptance rate or the
amount of refuse in place is known.
15.A-4.2.2 Compensating for Non-biodegradable Debris, Areas with Emission Controls,
and Areas Outside the Radius of Influence of Emission Controls
In certain cases, there are sections of a landfill that contain largely non-biodegradable debris
(e.g., concrete, rocks, asphalt or other demolition debris) and do not produce emissions that other
landfill refuse does. If records are available documenting such a quantity of waste and the
regulatory agency is in agreement with this judgement, this amount of waste can be subtracted
from the accumulated waste and the landfill capacity.
Similarly, when an area of the landfill is operated with a gas collection system and emission
controls, this area of the landfill and the subsequent landfill waste will not release emissions at
the same rate as an uncontrolled area of the landfill. In the case of a landfill with such emission
controls, the user must estimate the quantity of the waste for which gas is collected and
controlled. The controlled and uncontrolled portions of the landfill can then be modeled
separately. Application of controls are discussed in Section 3.3.2 of this chapter.
15.A-5 POTENTIAL OPERATIONAL ERRORS
Some inputs can cause problems in the operation of the program. The following sections
describe how to avoid them.
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15.A-5.1 The Autocalc Function
The Autocalc function is located under the Edit menu and assists the user in calculating waste
acceptance rates or refuse in place for the years of operation of the model. The Autocalc
function will not recognize the landfill capacity as the upper limit for the accumulated refuse.
When this occurs, calculated values for accumulated refuse will exceed the landfill capacity.
The user should compare the amount of accumulated refuse as calculated by the Autocalc
function to the landfill capacity value prior to entering the data into the model to be certain that
the refuse in place does not exceed the landfill capacity. If the calculated accumulated refuse
amounts do exceed landfill capacity, then the user should adjust the acceptance rate data in the
Autocalc function to reduce the calculated accumulated refuse amount. Please note that the
program will continue to run if the entered value for landfill capacity has been exceeded.
15.A-5.2 The Closure Year
The Closure Year function is located under the Parameters menu and allows the user either to
calculate the closure year automatically or to specify an actual closure date for the landfill. In
either case, the closure year is the year in which the landfill waste accumulated reaches the
capacity of the landfill. The default option is for the model to calculate the closure year
automatically. The following is a brief description of the two options and an explanation of how
the closure variable choice affects operation of the model.
System Calculated Closure Year: The computer model will project the closure based on the last
non-zero acceptance rate and the capacity of the landfill. The model will project waste
acceptance at the last non-zero acceptance rate until the year in which the accumulated refuse in
place reaches the landfill capacity. This year becomes the closure year.
User-specified Closure Year: If the user does not know the refuse acceptance rates for the final
years of the landfill's operation, the user may specify the closure year for the landfill and allow
the computer to calculate the acceptance rates until closure. The model will calculate the
acceptance rates for the final years of operation by dividing the remaining capacity of the landfill
by the number of years between the current year and the user-specified closure year.
The user must take caution when specifying the closure year because of the model's method of
calculation. If a closure year is chosen that is the same as the current year, the model's
calculation routine will not be able to estimate emissions correctly. To avoid this problem, the
user should always specify a closure year that is at least one year beyond the current year even if
the current year is the year in which the refuse in place reaches the capacity of the landfill (i.e., a
case in which the current year is, by definition, the closure year). If the current year is the
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closure year, we recommend allowing the model to automatically calculate the closure year (i.e.,
use the default System Calculated Closure Year).
15.A-5.3 Cut, Copy, and Paste
The Cut, Copy, and Paste commands, which function similarly as in other Windows software
programs, are designed to be implemented in the following way: highlight the contents of the
origin cell (i.e., drag the cursor across the cell with the primary mouse button depressed); select
the Cut or Copy command; highlight the contents of the destination cell; and then select the
Paste command.
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CHAPTER 15 - LANDFILLS
ATTACHMENT 15.A-1
GLOSSARY OF TERMS
Term
Definition
Codisposal
Disposal of hazardous waste as well as other kinds
of waste in a landfill.
Landfill Capacity
The total amount of refuse that can be disposed of in
the landfill.
Landfill Gas
Landfill gas is a product of biodegradation of refuse
in landfills and consists of primarily methane and
carbon dioxide, with trace amounts of NMOC and
air pollutants.
Methane Generation Rate Constant (k)
k is a constant that determines the rate of landfill gas
generation. The first-order decomposition model
assumes that k values before and after peak landfill
gas generation are the same, k is a function of
moisture content in the landfill refuse, availability of
nutrients for methanogens, pH, and temperature.
Nonmethane Organic Compounds (NMOC)
NMOC are specified in this program as the fraction
of landfill gas containing nonmethane organic
compounds, expressed as hexane. NMOC include
air pollutants and volatile organic compounds.
NMOC concentration can be measured using
guidance provided by the proposed EPA
Method 25C.
Potential Methane Generation Capacity (L0)
L0 is a constant that represents the potential capacity
of a landfill to generate methane (a primary
constituent of landfill gas). L0 depends on the
amount of cellulose in the refuse.
Air Pollutants
Compounds found in landfill gas or emitted with
landfill gas, some of which are listed as air
pollutants under section 112 of the Clean Air Act. A
total of 47 air pollutants emitted from landfills are
included in the model.
Closure Year
The year in which the landfill ceases, or is expected
to cease, accepting waste.
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ATTACHMENT 15.A-2. POLLUTANTS INCLUDED IN THE LANDFILL
GAS EMISSIONS MODEL
Concentration (ppmv)
Chemical
1,1,1-Trichloroethane (HAP)
1, 1,2,2-Tetrachloroethane (HAP/VOC)
1,1,2-Trichloroethane (HAP/VOC)
1,1-Dichloroethane (HAP/VOC)
1,1-Dichloroethene (HAP/VOC)
1,2-Dichloroethane (HAP/VOC)
1,2-Dichloropropane (HAP/VOC)
2-Propanol (VOC)
Acetone
Acrylonitrile (HAP/VOC)
Benzene (HAP/VOC)
Bromodichloromethane (VOC)
Butane (VOC)
Carbon Disulfide (HAP/VOC)
Carbon Monoxide
Carbon Tetrachloride (HAP/VOC)
Carbonyl Sulfide (HAP/VOC)
Chlorobenzene (HAP/VOC)
Chlorodifluoromethane (VOC)
Chloroethane (HAP/VOC)
Chloroform (HAP/VOC)
Chloromethane (HAP/VOC)
Dichlorobenzene (VOC/HAP for 1,4 isomer)
Dichlorodifluoromethane (VOC)
Dichlorofluoromethane (VOC)
Dichloromethane (HAP)
Dimethyl Sulfide (VOC)
Ethane
Ethanol (VOC)
Ethylbenzene (HAP/VOC)
Ethyl Mercaptan (VOC)
Ethylene Dibromide (HAP/VOC)
Fluorotrichloromethane (VOC)
Hexane (HAP/VOC)
Hydrogen Sulfide
Mercury (HAP)
Methyl Ethyl Ketone (HAP/VOC)
Methyl Isobutyl Ketone (HAP/VOC)
Methyl Mercaptan (VOC)
Pentane (VOC)
Perchloroethylene (HAP/VOC)
Propane (VOC)
Toluene (HAP/VOC)
Trichloroethene (HAP/VOC)
t- 1 ,2-Dichloroethene
Vinyl Chloride (HAP/VOC)
Xylene (HAP/VOC)
Molecular Weight
133.41
167.85
133.41
98.96
96.94
98.96
112.99
60.11
58.08
53.06
78.12
163.83
58.12
76.14
28.01
153.84
60.07
112.56
86.47
64.52
119.38
50.49
147
120.91
102.92
84.93
62.13
30.07
46.08
106.17
62.13
187.88
137.37
86.18
34.08
200.61
72.11
100.16
48.11
72.15
165.83
44.1
92.14
131.38
96.94
62.5
106.17
Codisposal
0.48
1.11
0.1
2.35
0.2
0.41
0.18
50.1
7.01
6.33
11.1
3.13
5.03
0.58
141
0.004
0.49
0.25
1.3
1.25
0.024
1.21
0.21
15.7
2.62
14.3
7.82
889
27.2
4.61
1.25
0.001
0.76
6.57
35.5
0.000253
7.09
1.87
2.49
3.29
3.73
11.1
165
2.82
2.84
7.34
12.1
No Codisposal
0.48
1.11
0.1
2.35
0.2
0.41
0.18
50.1
7.01
6.33
1.91
3.13
5.03
0.58
141
0.004
0.49
0.25
1.3
1.25
0.024
1.21
0.21
15.7
2.62
14.3
7.82
889
27.2
4.61
1.25
0.001
0.76
6.57
35.5
0.000253
7.09
1.87
2.49
3.29
3.73
11.1
39.3
2.82
2.84
7.34
12.1
Note: Technical support information for the above pollutant data is located in the Compilation ofAir Pollutant Emission Factors, AP-42,
Volume 1: Stationary Point and Area Sources (EPA, 1998a) which can be obtained from the TTN website
(http://www.epa.gov/ttn/chief/ap42back.html) or from the National Technical Information Service.
15.A-20
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ATTACHMENT 15.A-3
EXAMPLES OF THE AUTOCALC FUNCTION
Example 1: Using the Autocalc Function When Only Partial Data Are Available
If refuse information is available for only certain years of landfill operation and assumptions can
be made about acceptance rates in the years for which there is no information, the Autocalc
function can be useful to estimate and enter acceptance rate data. In this example, the user will
have two periods of acceptance rates for which the Autocalc function will be used: one in which
the user will assume that the acceptance rate increases linearly over time and one in which the
acceptance rate is constant for a number of years. In this example, the landfill will open in 1971,
and the current year will be 1986.
To input an increasing refuse acceptance rate, an acceptance rate must be entered for the
beginning and ending points. Assume that the landfill capacity is 2,000,000 Mg, the refuse
acceptance rate in the first year (1971) is 10,000 Mg/yr, and the refuse acceptance rate in the
tenth year (1980) is 100,000 Mg/yr. To use the Autocalc function to interpolate between the two
rates, select the waste acceptance rate for the year 1971. Click and drag the mouse until all the
cells from years 1971 through 1980 are highlighted. Then, from the Edit menu, select the
Autocalc function. The computer model will linearly interpolate the acceptance rate for the
years between 1971 and 1980. In this case, the rate increases from 10,000 Mg/yr to
100,000 Mg/yr in 10,000 Mg/yr increments.
To enter a constant refuse acceptance rate, the same value for the acceptance rate must be
entered for the beginning and end points of the period throughout which refuse is received at a
uniform rate. In this case, assume that the acceptance rate remains constant at 100,000 Mg/yr
from 1980 through 1985. Start by entering 100,000 Mg/yr in the acceptance rate cell for the year
1985. (A value of 100,000 Mg/yr should have already been entered for 1980 based on the
directions in the previous paragraph). Then highlight all the cells from years 1980 through 1985.
From the Edit menu choose the Autocalc function. The computer model will enter the
acceptance rate of 100,000 Mg/yr for each year between 1980 and 1985. Note that, in both
cases, entering acceptance rate values with the Autocalc function caused the estimates for the
refuse in place to change accordingly.
Example 2: Using the Autocalc Function With No Data for Early Periods of Operation
This example will begin with a new study. Assume that a landfill with a of capacity
5,000,000 Mg opens in the year 1971 and the current year is 1980. For the last two years (i.e.,
1979 and 1980) the amount of refuse in place has been recorded. In 1979 the refuse in place
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totaled 2,000,000 Mg, and in 1980 it was 2,350,000 Mg. However, there are no records to
indicate what the refuse in place was for 1971 through 1978.
The Autocalc function can be used to estimate the refuse in place for the years between 1971 (the
year the landfill opened) and 1978. The refuse in place in 1971 must be zero because 1971 is the
year the landfill opened. Assuming that refuse acceptance rates were constant between 1971 to
1978, the Autocalc function can be used to linearly interpolate backwards to produce estimates
of the refuse between 1971 and 1978. As in the previous example, begin by selecting the cell
with the earlier date (i.e., move the active cell to the refuse in place for 1971). Click and drag
the mouse until all the cells between 1971 and 1979 are highlighted. Then choose the Autocalc
function from the Edit menu. The values in both the refuse acceptance rate and refuse in place
column will be calculated. The refuse acceptance rate for years 1971 through 1978 will be
250,000 Mg/yr, and the refuse acceptance rate for 1979 will be 350,000 Mg/yr. The refuse in
place estimates will be adjusted accordingly from 1971 (0 Mg in place) to 1979 (2,000,000 Mg
in place).
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CHAPTER 15 - LANDFILLS
ATTACHMENT 15.A-4
A COPY OF THE TEXT REPORT FROM THE EXAMPLE STUDY IN SECTION 4.1
Source: C:\LANDFILL\TEST.PRM
Model Parameters
Lo: 100.00 mA3 / Mg
k : 0.0400 1/yr
NMOC : 2420.00 ppmv
Methane : 50.0000 % volume
Carbon Dioxide : 50.0000 % volume
Air Pollutant : Ethyl Mercaptan
Molecular Wt = 62.13 Concentration = 0.860000 ppmV
Landfill Parameters
Landfill type : Co-Disposal
Year Opened : 1975 Current Year : 1995 Closure Year: 2001
Capacity : 3000000 Mg
Average Acceptance Rate Required from
Current Year to Closure Year : 200000.00 Mg/year
Model Results
Ethyl Mercaptan Emission Rate
Year Refuse In Place (Mg) (Mg/yr) (Cubic m/yr)
1976 6.000E+04 1.067E-03 4.128E-01
1977 1.200E+05 2.092E-03 8.094E-01
1978 1.800E+05 3.076E-03 1.190E+00
1979 2.400E+05 4.022E-03 1.557E+00
1980 3.000E+05 4.932E-03 1.908E+00
1981 4.000E+05 6.516E-03 2.522E+00
1982 5.000E+05 8.038E-03 3.111E+00
1983 6.000E+05 9.501E-03 3.677E+00
1984 7.000E+05 1.091E-02 4.221E+00
1985 8.000E+05 1.226E-02 4.743E+00
1986 9.000E+05 1.355E-02 5.245E+00
1987 l.OOOE+06 1.480E-02 5.727E+00
1988 1.100E+06 1.600E-02 6.191E+00
1989 1.200E+06 1.715E-02 6.636E+00
1990 1.300E+06 1.825E-02 7.064E+00
1991 1.400E+06 1.932E-02 7.475E+00
1992 1.500E+06 2.034E-02 7.870E+00
1993 1.600E+06 2.132E-02 8.249E+00
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1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
1.
1.
2.
2.
2.
2.
2.
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.
3.
3.
3.
3.
3.
700E+06
800E+06
OOOE+06
200E+06
400E+06
600E+06
800E+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
OOOE+06
2
2
2
2
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
9
.226E-02
.316E-02
.581E-02
.836E-02
.080E-02
.315E-02
.540E-02
.757E-02
.610E-02
.468E-02
.332E-02
.202E-02
.076E-02
.955E-02
.840E-02
.728E-02
.621E-02
.518E-02
.420E-02
.325E-02
.234E-02
.146E-02
.062E-02
.981E-02
.903E-02
.829E-02
.757E-02
.688E-02
.622E-02
.558E-02
.497E-02
.439E-02
.382E-02
.328E-02
.276E-02
.226E-02
.178E-02
.132E-02
.087E-02
.045E-02
.004E-02
.643E-03
8.
8.
9.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
1.
9.
9.
8.
8.
8.
7.
7.
7.
7.
6.
6.
6.
6.
5.
5.
5.
5.
4.
4.
4.
4.
4.
4.
3.
3.
614E+00
964E+00
989E+00
097E+01
192E+01
283E+01
370E+01
454E+01
397E+01
342E+01
290E+01
239E+01
190E+01
144E+01
099E+01
056E+01
014E+01
746E+00
364E+00
997E+00
644E+00
305E+00
979E+00
666E+00
366E+00
077E+00
799E+00
533E+00
277E+00
031E+00
794E+00
567E+00
349E+00
139E+00
937E+00
744E+00
558E+00
379E+00
207E+00
042E+00
884E+00
732E+00
15.A-24
Volume III
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1/31/01
CHAPTER 15 - LANDFILLS
2036
2037
2038
2039
3.000E+06
3. OOOE + 06
3.000E+06
3.OOOE + 06
9.265E-03
8.902E-03
8.553E-03
8.217E-03
3.585E+00
3.445E+00
3.310E+00
3.180E+00
2198
2199
2200
3. OOOE + 06
3.OOOE + 06
3.OOOE + 06
1.421E-05
1.365E-05
1.312E-05
5.499E-03
5.284E-03
5.076E-03
Volume III
15.A-25
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CHAPTER 15 - LANDFILLS
1/31/01
ATTACHMENT 15.A-5 A COPY OF THE GRAPHICAL REPORT FROM THE EXAMPLE
STUDY IN SECTION 4.1
Projected Ethyl Mercaptan Emissions
v r 1
CO
CO
etc?
Year
15.A-26
Volume III
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VOLUME III: CHAPTER 16
OPEN BURNING
Revised Final
January 2001
ALAPCp
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee of
the Emission Inventory Improvement Program and for Charles Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency. Members of the Area
Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Also contributing to the preparation of this document is Tahir Khan of Chemical Emission Management Services of
Ontario, Canada
EIIP Volume III 111
-------
CONTENTS
Section Page
1 Introduction 16.1-1
2 Source Category Description 16.2-1
2.1 Open Burning Subcategories 16.2-1
2.2 Factors Influencing Emissions 16.2-2
2.2.1 Process Factors 16.2-2
2.2.2 Other Factors 16.2-3
2.2.3 Control Techniques 16.2-4
3 Overview of Available Methods 16.3-1
3.1 Planning 16.3-2
3.1.1 Municipal Solid Waste (MSW) Burning 16.3-2
3.1.2 Land Clearing Waste Burning 16.3-2
3.1.3 Yard Waste Burning 16.3-3
3.2 Available Methods and Data Requirements 16.3-3
3.2.1 Municipal Solid Waste Burning 16.3-4
3.2.2 Land Clearing Waste Burning 16.3-4
3.2.3 Yard Waste Burning 16.3-7
3.3 Adjustments for Controls 16.3-7
3.4 Spatial Allocation 16.3-7
3.5 Temporal Resolution 16.3-9
3.5.1 Seasonal Apportioning 16.3-9
3.5.2 Daily Resolution 16.3-9
3.6 Other Factors Influencing Emissions Estimates 16.3-9
3.7 Projecting Emissions 16.3-9
IV EIIP Volume III
-------
CONTENTS (CONTINUED)
Section Page
4 Preferred Method for Estimating Emissions 16.4-1
4.1 Preferred Methods 16.4-2
4.1.1 Municipal Solid Waste Burning 16.4-2
4.1.2 Land Clearing Debris 16.4-7
4.1.3 Yard Wastes 16.4-17
5 Alternative Methods For Estimating Emissions 16.5-1
5.1 Municipal Solid Waste Burning 16.5-1
5.1.1 First Alternative Method 16.5-1
5.1.2 Second Alternative Method 16.5-4
5.2 Land Clearing Waste Burning 16.5-6
5.2.1 First Alternative Method 16.5-6
5.2.2 Second Alternative Method 16.5-7
5.3 Yard Waste Burning 16.5-8
5.3.1 First Alternative Method 16.5-8
5.3.2 Second Alternative Method 16.5-8
5.3.3 Third Alternative Method 16.5-9
6 Quality Assurance/Quality Control 16.6-1
6.1 Emission Estimate Quality Indicators 16.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 16.6-2
6.2 Sources of Uncertainty 16.6-2
7 Data Coding Procedures 16.7-1
7.1 Necessary Data Elements 16.7-1
8 References 16.8-1
Appendix A Prescribed Burning Fuel Categories (Peterson and Ward, 1993) to be Used for
Land Clearing Waste Burning
EIIP Volume III V
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TABLES
Tables Page
16.3-1 Summary of Available Methods for Municipal Solid Waste Burning 16.3-5
16.3-2 Summary of Available Methods for Land Clearing Waste Burning 16.3-6
16.3-3 Summary of Available Methods for Yard Waste Burning 16.3-8
16.4-1 Emission Factors for Open Burning of Municipal Refuse (EPA, 1997
and EPA, 1995a) 16.4-3
16.4-2 Land Clearing Burning Criteria Pollutant Emission Factors 16.4-10
16.4-3 Land Clearing Burning HAP Emission Factors (EPA, 1996b) 16.4-12
16.4-4 HAP Emission Functions to be Used for Land Clearing Burning 16.4-13
16.4-5 Factors to Convert Wood Volume (Cubic Feet) to Weight (Pounds)
(EPA, 1995) 16.4-16
16.4-6 Fuel Loading Factors — for Land Clearing Debris 16.4-17
16.4-7 Yard Waste Burning Emission Factors (EPA, 1995a) 16.4-20
16.5-1 Generation of Municipal Solid Waste, by Material 1994 (EPA, 1996a) . . . 16.5-3
16.5-2 Generation of Household Waste, by Material (EPA, 1997) 16.5-5
16.6-1 MSW Burning Preferred Method: Local Estimate 16.6-3
16.6-2 MSW Burning Alternative Method 1: Estimated Total Minus Landfilled
Amount 16.6-4
16.6-3 MSW Burning Alternative Method 2: Scaling of Data from a
Similar Area 16.6-4
VI EIIP Volume III
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TABLES (CONTINUED)
Tables Page
16.6-4 Land Clearing Waste Burning Preferred Method: Local Activity and Fuel
Loading Data 16.6-5
16.6-5 Land Clearing Waste Burning Alternative Method 1: Estimate from
Total Land Cleared and Amount of Material disposed of by Other Means . 16.6-5
16.6-6 Land Clearing Waste Burning Alternative Method 2: Extrapolate Data
from a Similar Area 16.6-6
16.6-7 Yard Waste Burning Preferred Method: Local Data 16.6-6
16.6-8 Yard Waste BurningAlternative Method 1: Small-Scale Survey from
Permits and Violations 16.6-7
16.6-9 Yard Waste Burning Alternative Method 2: Extrapolate from a
Similar Area 16.6-7
16.6-10 Yard Waste Burning Alternative Method 3: Estimated Local Yard
Waste Minus Landfilled or Composted Yard Waste 16.6-8
16.7-1 Area and Mobile Source Category Codes for Open Burning 16.7-2
EIIP Volume III Vll
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Vlll EIIP Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
This chapter describes the procedures and recommended approaches for estimating emissions
from open burning of residential municipal solid waste, land clearing debris, and yard wastes.
Section 2 of this chapter contains descriptions of open burning subcategories, their associated
pollutants, and restrictions to their occurrence. Section 3 of this chapter provides an overview of
available emission estimation methods. Section 4 presents the preferred emission estimation
methods for each of the open burning subcategories, and Section 5 presents alternative emission
estimation techniques. Quality assurance and quality control procedures are described in
Section 6. Data coding procedures are discussed in Section 7, and Section 8 lists all references
cited in this chapter.
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CHAPTER 16 - OPEN BURNING 1/31/01
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16.1-2 El IP Volume III
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SOURCE CATEGORY DESCRIPTION
Open burning is the purposeful burning of materials in outdoor areas such as forests and yards.
The types of open burning included in this chapter are fires that: (1) result from anthropogenic
activities; and, (2) are intentionally set in order to dispose of non-hazardous wastes by burning.
This category excludes burning in dedicated combustion devices and buildings, and fires that are
accidental, such as forest wildfires or structure fires. Open burning subcategories included in
this chapter are open burning of residential municipal (household) solid wastes (MSW), land
clearing wastes, and yard wastes. In many cases, however, the approaches for preparing
emission estimates for some of the accidental fires may be very similar to the approaches
presented here for intentional fires.
2.1 OPEN BURNING SUBCATEGORIES
A description of each of the anthropogenic open burning subcategories is provided in the
following text:
• Residential Municipal Solid Wastes (MSW). Residential MSW is the
nonhazardous refuse produced by households. MSW includes paper, plastics,
metals, wood, glass, rubber, leather, textiles, and food wastes. Open burning of
MSW at municipal landfills was prohibited by federal law in 1979 (40 CFR 257),
therefore, burning of residential MSW is practiced only by private individuals.
Most municipalities and some states have laws that prohibit on-site burning of
residential MSW. Open burning of residential MSW is a concern mostly in rural
areas, where burning is seen as an easier or cheaper alternative to landfilling.
• Land Clearing Wastes. The clearing of land for the construction of new
buildings and highways often results in debris consisting of trees, shrubs, and
brush. This debris may be burned in place but it is usually collected in piles for
burning. The burning of land clearing wastes may be practiced by private
individuals, corporations, and government agencies (e.g., highway construction
department). There are no federal laws restricting the open burning of land
clearing wastes, although state or local laws may exist.
• Yard Wastes. Yard waste burning is the open burning of materials such as grass
clippings, leaves, and trimmings from trees and shrubs. Yard waste burning
EIIP Volume III 16.2-1
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CHAPTER 16 - OPEN BURNING 1/31/01
takes place where the waste is generated (i.e., residences, parks, institutions such
as universities or hospitals, office complexes or other areas where grounds
maintenance generates this type of waste) or waste disposal sites where wastes
have been collected. Although there are no federal regulations restricting the
open burning of yard wastes, many municipalities prohibit or restrict the burning
of yard wastes, and promote composting as an alternative.
Previous efforts to estimate emissions from open burning, such as the 1990 base year State
Implementation Plan (SIP) inventories for ozone precursors, estimated emissions for the
subcategories described in the document Procedures for the Preparation of Emission
Inventories for Carbon Monoxide and Precursors of Ozone (EPA, 1991). The open burning
subcategories described in that document are forest fires, slash/prescribed burning, agricultural
burning, structure fires, rural residential MSW burning, rural commercial/institutional MSW
burning, and industrial MSW burning. This chapter does not include agricultural burning
prescribed burning, forest fires, structure fires, rural commercial/institutional or industrial
MSW. Forest fires and structure fires are outside of this chapter's scope, because these fires are
not intentionally set. Emission estimation methods can be found in Chapter 18, Accidential
Fires, of this volume. Unless there is evidence of open burning of MSW by
commercial/institutional or industrial generators within the inventory area, that source does not
need to be included in an inventory.
Open burning practices have changed considerably since the factors in the Procedures document
were prepared, and the reader should keep in mind that they will likely continue to change. For
example, landfilling and recycling policies will affect burning practices. Materials that were
previously burned may be landfilled or recycled, resulting in a decrease in open burning
emissions. On the other hand, if a landfill closes, raises fees, or no longer accepts certain types
of wastes that are combustible, residents may choose to dispose of the material by burning,
legally or illegally, resulting in an increase in open burning emissions.
2.2 FACTORS INFLUENCING EMISSIONS
2.2.1 PROCESS FACTORS
Emissions from open burning depend mainly on the type of waste, type of fire, and fuel loading
(the weight of the material to the measured volume of the material or the area burned).
Residential MSW may include paper, plastics, and other man-made products. Wastes from land
clearing and yard debris consist almost entirely of naturally occurring vegetative materials.
Emission factors presented in this chapter will reflect the difference in the materials burned for
each type of burning. In some cases, different emission factors will be provided for many
16.2-2 EIIP Volume III
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1/31/01 CHAPTER 16 - OPEN BURNING
different types of fuels for the same type of fire. For example, land clearing emission factors are
provided for different vegetation types and burning configurations.
In the case of land clearing burning, the combustion process is important because the different
phases of combustion greatly affect the amount of emissions produced. The phases of the
combustion process include preheating, flaming and smoldering. Preheating is the first stage,
where water and highly volatile hydrocarbons are volatilized. Flaming combustion is the rapid
oxidation of the fuel cellulose, lignin, and volatile hydrocarbons, usually consuming fine fuels
and surface fuels. As less oxygen is available either from the fuel or from the atmosphere,
flaming combustion is harder to maintain and smoldering occurs. Emissions occur at all phases,
but individual pollutants are emitted in different proportions during different phases and
emissions are related to the rate of fuel combustion (Peterson and Ward, 1993).
AP-42 Section 13.1, Table 13.1-3 (EPA, 1995a) presents emission factors for the flaming and
smoldering phases of combustion of forest materials, and a more general factor for the entire
fire. The emission factors labeled "fire" for a material type should be used for area source
inventories.
The configuration of the burned material will also affect emissions. Land clearing wastes may
be piled, collected in windrows (material heaped or collected in rows), or spread out at the time
of burning. Land clearing waste burning emission factors are available for different fuel
configurations, and these should be used when fuel configuration information is available.
When fuel configuration information is not available, recommendations for appropriate emission
factors are provided in Sections 4 and 5 in the descriptions of specific methods.
Open burning emissions are also affected by combustion efficiency. Combustion efficiency is
the proportion of the waste that is actually burned out of the total amount of waste that is
subjected to burning. In a more detailed approach to estimating emissions, it may be appropriate
to estimate combustion efficiency. Although combustion efficiency is not discussed in the
method descriptions in this section, the inventory preparer may decide that it should be included
in emissions calculations.
A fuel loading factor is the final component of an emissions calculation for land clearing
burning. Fuel loading factors are provided for these burning types in the descriptions of the
preferred and alternative methods.
2.2.2 OTHER FACTORS
Weather affects open burning practices. During extremely dry periods, most regions prohibit
any type of open burning, even though it is allowed during normal weather periods. An
inventory of open burning emissions for a dry period should result in lower than normal
EIIP Volume III 16.2-3
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CHAPTER 16 - OPEN BURNING 1/31/01
emission levels. Weather-related catastrophes may cause an increase in open burning emissions.
For example, a region may temporarily suspend restrictions on burning of land clearing debris
after a hurricane has occurred and a lot of trees have been downed.
2.2.3 CONTROL TECHNIQUES
The most effective control technique for open burning emissions is to ban open burning and
require disposal of the wastes by other methods. Composting of land clearing or yard wastes,
increasing household waste pickups in an area, or improving recycling rates will reduce burning
of these wastes. Another means of disposal is by combustion or incineration in a dedicated
furnace or incinerator with emissions control devices. Although incineration also results in
emissions, they are generally much lower per unit of mass than emissions from open burning.
Air curtain incinerators may be used to control emissions from open burning. An air curtain
incinerator consists of a burn pit and a device that blows air across and into the pit. The
effectiveness of these devices in controlling emissions, compared to burning the wastes in a pit
without the blower, has been questioned, but they do decrease the amount of time required to
burn the waste.
16.2-4 EIIP Volume III
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OVERVIEW OF AVAILABLE METHODS
Emissions from open burning are estimated by multiplying activity data and emission factors.
Emission factors for open burning categories are available from a number of sources. The
primary source is AP-42, but other EPA documents and documents produced by the USD A
Forest Service are good information resources. Emission factors are provided in the preferred
methods section of this chapter for each source category, but inventory preparers can use
emission factors from other sources if the factors better characterize local conditions.
Activity data used with an emission factor should be specific to the inventory area. One of the
particular difficulties with this source category is the frequent lack of activity information. This
category requires a number of variables for the emission equation, and some of those variables
may not be well defined or available. Inventory preparers will need to be prepared to make
well-educated assumptions in some cases. Preferred and alternative methods in this chapter
differ mainly in how activity data are collected, and how detailed and area-specific those data
are.
Selection of the appropriate estimation method depends on the relative significance of emissions
from this source in the inventory area and the data quality objectives (DQOs) of the inventory
plan. Refer to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for
discussions of inventory categories and DQOs.
Each method has advantages and disadvantages in terms of the expense and labor required by
the method and the resulting quality of the emission estimate. The inventory preparer must
select a method based on the desired accuracy of the emissions inventory and the resources
available to develop the inventory.
There are many factors to consider when deciding which open burning subcategories to
inventory in a particular area. The selection of the subcategories depends on the data quality
objectives (DQOs) of the inventory, the burning practices that take place in the inventory area,
the temporal scale of the inventory, and the pollutants of interest. Some types of open burning
may simply not be practiced in an area (e.g., prescribed burning of forests in a strictly urban
area), or there may be regulations that prohibit or discourage its use. If an inventory is for a
specific season or period of the year, it may be that some types of open burning do not occur
during that period, although they occur during other seasons of the year. When an inventory is
to be pollutant specific, the inventory preparer should determine if any of the open burning
subcategories are sources of emissions of that pollutant. If so, the preparer must decide if the
EIIP Volume III 16.3-1
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CHAPTER 16 - OPEN BURNING 1/31/01
emissions are likely to be significant enough, relative to other sources of that pollutant in the
inventory area, to warrant inclusion in the emissions inventory.
3.1 PLANNING
As noted above, open burning may not be practiced or may not be a source of significant
emissions in all inventory areas. During the planning stage of the inventory, the open burning
subcategories discussed in this chapter should be investigated before they are included in the
inventory or methods are chosen to estimate emissions from them. If a type of open burning
takes place during the time period of interest for the inventory and if the potential emissions
could provide a detectable addition to the total area source emissions, the subcategory should be
included in the inventory, and an appropriate estimation method chosen based on the potential
level of emissions, inventory budgets, and schedules. However, if a type of open burning is
rarely, if ever, practiced in the inventory area, or all or most of the activity occurs outside of the
inventory period, then there is no need to estimate emissions from this category. Also, before an
estimation method can be chosen, inventory personnel should have researched and made certain
that the source of activity information recommended for the estimation method is available and
is at a sufficient level to satisfy the DQOs of the inventory. The following paragraphs list the
agencies and organizations that can be contacted for the preliminary data collection step.
3.1.1 MUNICIPAL SOLID WASTE (MSW) BURNING
County sanitation, health, and fire departments are most likely to monitor open burning of
household wastes. One of these departments or local or state air agencies should be able to
indicate whether this type of open burning occurs frequently in the inventory area. In most
cases, this activity is not legal or requires a permit.
Factors most likely to increase activity for this subcategory are the lack of garbage pickup, high
costs for pickup or disposal, or drop off points that are difficult to reach. Inventory planners
should consider these factors when deciding if the subcategory is important to include in their
inventory, and if it may become more or less important in the future. If yard waste burning
emissions are also being estimated, information about yard waste pickup and composting
programs should be collected at the same time as information about MSW.
3.1.2 LAND CLEARING WASTE BURNING
Permits for the burning of land clearing wastes may be issued by local or state air agencies, local
fire departments, or local health departments. Other sources of information concerning land
clearing activity would be landfill personnel, state departments of transportation (DOT) when a
significant proportion of the clearing is for roads, and local planning departments. The number
16.3-2 El IP Volume III
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1/31/01 CHAPTER 16 - OPEN BURNING
of burning permits issued should provide an indicator of the scale of the activity in this source
subcategory. These same agencies should also know if there are restrictions on burning at
certain times of the year, or if there were restrictions during the specific inventory period. For
instance, burning for this subcategory and others such as yard wastes can be banned during
droughts. On the other hand, catastrophic events such as tornadoes, floods or hurricanes may
result in burning of debris even though such burning is ordinarily banned. These agencies
should also be aware of alternative disposal methods such as landfilling or composting that are
practiced in their area.
Data collection for the land clearing waste subcategory and the prescribed burning subcategory
should be coordinated, because these two burning types will sometimes be reported together.
These burning types will also rely on similar fuel loading data and will use the same emission
factors.
3.1.3 YARD WASTE BURNING
State and local regulations and programs that provide pickup for leaves and other yard debris, or
encourage composting of the material should be identified. Rules prohibiting or limiting open
burning of yard wastes and the organization that enforces those rules should be identified. In
1996, 23 states had rules banning yard wastes from landfills (EPA, 1996b). Solid waste
agencies should be contacted about rules currently in place for an inventory area. Composting
programs are meant to reduce the burden on landfills and are typically run by local departments
in charge of solid waste. These departments may also track reductions in burning and non-
compliance with non-burning rules.
Inventory planners should also define the potential scope of the activity during the inventory
time period and in the inventory area. Factors that may increase yard waste burning activity are
high costs for pick up or tipping at local landfills, or not having a local landfill that will accept
the waste. Some areas may limit burning to leaves and grass clippings only, or prohibit burning
during certain times of the year, such as the summer months, or during droughts. Yard waste
burning may take place primarily in the rural areas outside of the inventory area, or may take
place during a different season than the inventory time period. Estimating emissions from this
subcategory may not be necessary if there is little evidence of activity during the inventory time
period and area.
Information gathering about the collection or composting of yard wastes should be coordinated
with the information collection for MSW.
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3.2 AVAILABLE METHODS AND DATA REQUIREMENTS
The following sections outline the preferred and alternative methods for this source category.
Sections 4 and 5 of this chapter provide detailed descriptions of the methods.
3.2.1 MUNICIPAL SOLID WASTE BURNING
Table 16.3-1 presents the preferred and alternative methods for estimating emissions from open
burning of municipal solid wastes. Emission factors from the most recent AP-42 section on
open burning, Chapter 2, Section 5, and an EPA document titled, Evaluation of Emissions from
the Open Burning Of Household Waste in Barrels., (EPA, 1997), are used in all of the methods
for this burning type. Methods for estimating residential burning of MSW vary in the way that
activity data are collected. The preferred method requires a local estimate of the amount of
waste burned. The first alternative method takes into account that it may be more convenient to
estimate the fraction of waste generated that is not burned than it is to estimate the fraction of
waste that is burned. The method provides an approach for estimating the amount of waste open
burned in an area, using either locally-generated estimates of the total amount of MSW
generated, or a national average per capita waste generation. The amount of waste known to be
disposed of through landfilling, composting, incineration or other disposal methods is subtracted
from this total, and the remainder is assumed to be open burned. The second alternative method
uses emissions data from another area (similar area or an area that contains the inventory area)
or tons of waste burned in another area extrapolated to the inventory area.
3.2.2 LAND CLEARING WASTE BURNING
The preferred and alternative methods for estimating emissions from the open burning of land
clearing wastes are shown in Table 16.3-2. Emission calculations for all methods are based on
determining the fuel type in order to estimate the fuel loading, and the emission factor. Data
collection issues, assumptions and factors for fuel loading are provided in Section 4 of this
chapter. The preferred method develops activity data through permit data for land debris
burning. Estimates of the average tons of fuel burned in the permitted burns will need to be
collected from state or local experts. The preferred method uses information that is specifically
collected for the inventory area. The first alternative method estimates activity data by
estimating the acres of land cleared, estimating the waste generated by the land clearing, and
subtracting the waste that is known to be disposed of through other means, such as landfilling or
composting. The second alternative method extrapolates emissions or the amount of waste
burned from a similar area. Scaling the emissions or activity can be done by comparing rules
between the two areas, and either population growth or building activity.
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5
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TABLE 16.3-1
SUMMARY OF AVAILABLE METHODS FOR
MUNICIPAL SOLID WASTE BURNING
METHOD DESCRIPTION
PREFERRED
Collect a local estimate of MSW open burned.
Calculation:
Amount of waste burned in inventory area * Emission factor
ALTERNATIVE 1
Collect a local estimate of the total amount of MSW generated in
the inventory area (or estimate using the national per capita waste
generation rate) and the amount of MSW that is disposed of by
other means (landfilling, incineration).
Calculation:
(Amount of waste generated in inventory area - Amount of waste
disposed of by other means in inventory area) * Emission factor
ALTERNATIVE 2
Obtain data (emissions or amount of waste burned) from an area
that is similar to the inventory area, extrapolate the data to the
inventory area based on the ratio of the rural population of the
inventory area to the rural population of the similar area, and
multiply by an emission factor.
Calculation:
(Rural population of inventory area/Rural population of similar
area) * Emissions from similar area
ACTIVITY DATA REQUIRED
- Tons of waste burned in inventory area
Tons of waste generated in inventory area
Tons of waste disposed of by other means
(other than open burning) in inventory
area
Emissions data from similar area (or tons
of waste burned and emission factors)
Ratio of rural population of similar area to
inventory area
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TABLE 16.3-2
SUMMARY OF AVAILABLE METHODS FOR LAND CLEARING WASTE BURNING
C
METHOD DESCRIPTION
PREFERRED
Collect local activity and fuel loading data.
Calculation:
Permits for land clearing waste burns in inventory area * Fuel
loading factor for each burn * Emission factor
ALTERNATIVE 1
Collect the total number of acres cleared and a local fuel
loading factor, subtract the amount of debris that is disposed
of by means other than burning.
Calculation:
[(Acres of land cleared * Fuel loading factor) -Amount of
debris disposed of by other means] * Emission factor
ALTERNATIVE 2
Obtain data (emissions or amount of waste burned) from an
area that is similar to the inventory area, extrapolate the data
to the inventory area based on a scaling surrogate.
ACTIVITY DATA REQUIRED
Permits for land clearing burns
Fuel loading factor (ton/burn)
Fuel type (for determining fuel loading and
emission factor)
Acres of land cleared in inventory area
Fuel loading factor (ton/acre)
Debris disposed of by other means in
inventory area (tons)
Activity or emissions from a similar area
The scaling surrogate is a ratio between the
similar area and the inventory area based on
population growth, acres cleared, or
building permits
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3.2.3 YARD WASTE BURNING
The preferred and alternative methods for estimating emissions from open burning of yard
wastes are presented in Table 16.3-3. The preferred approach is to identify and use
locality-specific data, if it is available. This approach, however, may not be an option, and three
alternatives are also available. The first alternative is to survey a subset of the inventory area,
and scale that estimate up to the larger inventory area. The second alternative is to use
information from a similar area and extrapolate the data to the inventory area. Suitable
information would be collected using the methods described under the preferred or first
alternative methods. The third alternative is to develop a local generation rate that can be scaled
to the inventory area, corrected by estimates of the material that is landfilled or composted.
3.3 ADJUSTMENTS FOR CONTROLS
Air curtain incinerators are the only devices currently used to control emissions from open
burning. In an air curtain incinerator, a rotating mass ("curtain") of high velocity, high
temperature air is circulated across an open chamber or pit in which burning occurs. The
continued air flow over-oxygenates the fire and increases turbulence, resulting in more complete
combustion. The effectiveness of air curtain incinerators in reducing emissions has not been
fully established. Available factors for burning with air curtain incinerators are provided in
Section 4.
Other controls on open burning emissions are regulations that prohibit or restrict open burning,
and recycling practices in the inventory area. These controls are reflected in lower activities.
3.4 SPATIAL ALLOCATION
Spatial allocation of the activity data may be necessary in some cases. Spatial allocation is the
assignment of an activity level or emission estimate to a smaller or larger geographic area than
the area for which it was prepared. Allocation requires the identification of a surrogate indicator
that can be used for extrapolation or scaling. In addition to scaling or extrapolating emissions or
activity from one area to another, emissions or activity may need to be allocated within the
inventory area. When a method uses a spatial surrogate, preferred and alternative surrogates are
described as part of the method. Some spatial allocation surrogates would be land use in the
area, distribution of rural population, and building permit activity.
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3.5 TEMPORAL RESOLUTION
Open burning emissions can be seasonal or influenced by weather conditions. Land clearing
waste and yard waste burning may occur only during certain times of the year, and may not take
place during the season of interest for a particular inventory. For that reason, it has been
emphasized in this chapter that the preparer must investigate the seasonal aspect of the activity
before collecting other emission calculation data for these burning types. All of the burning
types covered in this chapter may be limited or banned because of seasonal drought or wind
conditions. These conditions should also be investigated before committing resources to
inventory data collection.
3.5.1 SEASONAL APPORTIONING
The preferred method for allocating open burning emissions is to use local season-specific
activity data. An alternative is to collect estimates of seasonal activity percentages from local
experts.
3.5.2 DAILY RESOLUTION
Open burning can be expected to take place seven days a week.
3.6 OTHER FACTORS INFLUENCING EMISSIONS ESTIMATES
Natural disasters may affect open burning practices and the resulting emissions. Natural
disasters such as hurricanes, tornadoes, or floods may generate wastes, and open burning rules
may be suspended to dispose of those wastes. These special conditions should be identified as
part of the planning process for an inventory.
3.7 PROJECTING EMISSIONS
A discussion about developing growth factors and projecting emission estimates can be found in
Section 4 of Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development. Projecting emissions for this source category usually will take into account only
changes in burning activity because rules for reducing emissions are most likely to reduce
activity. Burning of land clearing wastes may be affected by controls if air curtain incineration
is used. Emission factors specific to this device should be used to calculate emissions in this
case.
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Activity and emissions can vary substantially from year to year for open burning types. Sources
of variation will depend on the burning type, but some factors apply to all burning types:
• Change in population, either in total or as a population shift from urban to rural
areas;
• Changes in cost or location of landfills or other methods of waste disposal; and
• Implementation of new laws that affect types of open burning.
Yard waste composting programs may reduce burning for this waste type.
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
Because the data collection for this source category can be difficult, the preferred methods
presented here are in the form of a set of guidelines for identifying data sources and using
assumptions in order to develop reasonable estimates. There is no universal data source that can
be used for every inventory to estimate emissions for this source category. When lists of
potential data sources are given as part of a method, one or more of these data sources may need
to be contacted.
AP-42 is the primary source of emission factors for all of the types of burning covered here.
Additional emission factors are presented in Ward, et al. (1989), and two EPA Control
Technology Center reports, EPA (1996) and EPA (1997). There are only limited factors in these
references for burning of land clearing wastes, but factors developed for prescribed burning can
be used for the land clearing subcategory.
Drawbacks to using the preferred methods are that the activity information can be difficult to
collect; the process may be expensive in terms of time and effort; and the resulting information
may still be based on estimates of activity, rather than measured amounts of materials burned.
However, previous estimates of this category were often based on dated waste generation rates,
and emission estimates for the category may not have reflected current burning practices.
Collecting local, period-specific data and applying reasonable assumptions should provide a
much better estimate of the scale and importance of the category relative to the inventory area's
air pollution problems.
As with all area source inventory categories, documentation should be maintained for data
collected, assumptions, information contacts, and calculations. Because this source category
does require making assumptions in order to develop activity levels, the basis for all
assumptions should be well documented.
Costs and labor efforts are highest the first time that the preferred methods are used. Subsequent
updates to the inventory may be done using a local activity adjustment factor, if a suitable
scaling surrogate can be identified. Also, subsequent inventories should take advantage of the
data handling and quality assurance/quality control (QA/QC) routines that were put into place
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the first time the method was used. See discussions of surveys for area sources in Volume I of
the EIIP series and in Chapter 1 of this volume for more information.
4.1 PREFERRED METHODS
4.1.1 MUNICIPAL SOLID WASTE BURNING
The preferred method for estimating emissions from burning MSW is to collect estimates of
open burning of MSW, in weight units, from state or local experts, or a survey of a subset of the
inventory area. The subset should be representative of the activity throughout the entire
inventory area. For the preferred method, the information is collected specifically for the
inventory area and the inventory time period. See the discussion of the alternative methods if
this level of information is not available.
If activity data are available for a subset of the inventory area, then information will need to be
identified that can be used to scale the activity to the entire inventory area. Section 3.1.2 of this
chapter discusses factors that influence activity for this source category, such as a lack of
garbage pickup services, high costs for pickup or disposal, or drop off points that are difficult to
reach. The alternative scaling factor is rural population.
Emission Factors
Emission factors for open burning MSW come from two sources, AP-42 (EPA, 1995a) and an
EPA document Evaluation of Emissions from the Open Burning Of Household Waste in Barrels,
(EPA, 1997).J The recommended emission factors are listed in Table 16.4-1, and the source of
each factor is indicated in the table. AP-42 factors are based on a 1967 study of emissions from
two test burns of MSW (Gerstle and Kemnitz, 1967). No detail is provided about the make up
of the MSW in that article. The emission factors are expressed in units of the emission rate for
the entire refuse weight.
The more recent EPA factors are also based on two test burns, out of four done for the study.
Differences between the two test burns are described in the next paragraph. The proportions of
waste types are provided in the report. These emission factors are expressed in units of the
emission rate for only the fuel that actually burned.
1 Evaluation of Emissions from the Open Burning of Household Waste in Barrels, is
available from the Clean Air Technology Center (CATC), on the EPA TTN Website, at:
http//www.epa.gov/ttncatcl/products.html#aptecrpts.
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CHAPTER 16 - OPEN BURNING
TABLE 16.4-1
EMISSION FACTORS FOR OPEN BURNING OF MUNICIPAL REFUSE
(EPA, 1997 AND EPA, 1995a)
Pollutant
Sulfur Oxides
Carbon Monoxide
Methane
Nitrogen Oxide
VOCsa
PM10
PM2.5
Chlorobenzenes
Benzene
Acetone
Styrene
Phenol
Dichlorobenzenes
Tri chl orob enzenes
Tetrachlorobenzenes
Pentachlorobenzene
Hexachl orob enzene
Total Polycyclic Aromatic
Hydrocarbons (PAHs)b
Emissions
(Ib/ton entire
refuse weight)
1.0
85
13
6
Emissions
(Ib/ton actually
burned)
8.556
38
34.8
0.0008484
2.48
1.88
1.48
0.28
0.00032
0.00022
0.000148
0.000106
0.000044
0.132
Emission Factor
Source
AP-42 (EPA, 1995a)
AP-42 (EPA, 1995a)
AP-42 (EPA, 1995a)
AP-42 (EPA, 1995a)
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
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CHAPTER 16 - OPEN BURNING
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TABLE 16.4-1
(CONTINUED)
Pollutant
Acenaphthylene
Naphthalene
Phenanthrene
Total Polychlorinated
dibenzo-p-dioxins (PCDD)
Total Polychlorinated
dibenzo furans (PCDF)
Total Polychlorinated
biphenyls (PCB)
Hydrogen chloride (HC1)
Hydrogen cyanide (HCN)
Emissions
(Ib/ton entire
refuse weight)
Emissions
(Ib/ton actually
burned)
0.022
0.036
0.0146
0.000076
0.0000122
0.00572
0.568
0.936
Emission Factor
Source
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
EPA, 1997
a The component VOCs measured for this factor include acetone, which is not considered a reactive VOC for
ozone inventories (40 CFR 51.100). Reactive VOC can be calculated by subtracting the separate acetone
emission factor in this table from the listed VOC factor. The other component VOCs measured are: 1,3-
butadiene, 2-butanone, benzene, chloromethane (methyl chloride), ethyl benzene, naphthalene, styrene, and
toluene. More detail about measurements of VOC is available in the source document.
b Total PAH includes emissions from acenaphthene, acenaphthylene, anthracene, benzo(a)anthracene,
benzo(a)pyrene, benzo(b)fluoranthene, benzo(ghi)perylene, benzo(k)fluoranthene, chrysene,
dibenzo(ah)anthracene, fluoranthene, fluorene, indeno(123cd)pyrene, naphthalene, phenanthrene, pyrene.
Individual emission factors for acenaphthylene, naphthalene, and phenanthrene were provided in the source
document and are listed in this table.
The mix of household wastes burned in the 1997 EPA study was based on a survey done by the
New York State Department of Environmental Conservation's Division of Solid Waste and is
based on waste stream characterizations for New York State. Sample waste mixes were
prepared for the study for an "avid recycler," who removed the paper from the mix, and a
16.4-4
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1/31/01 CHAPTER 16 - OPEN BURNING
"non- recycler," which included all household wastes. Both samples included noncombustables.
Emission factors for test burns using the non-recycler's waste are those recommended here.
Test burns of the non-recycler's waste resulted in about 50 percent of the total waste burned.
The non-recycler's waste included about 20 percent noncombustables, such as glass or metal.
The reader should note important differences in how the emission factors from the two
documents can be used. The AP-42 factors should be applied to the estimated total waste
subjected to burning. However, the factors from the 1997 EPA document should be applied to
the estimated amount of waste that actually burns. This means that when using factors from the
1997 EPA document, the amount of waste that actually burned must be estimated based on the
estimate of the amount of waste subjected to burning. The proportions of waste actually burned
to total waste from the 1997 EPA document, discussed above, are recommended.
Example 16.4-1 shows how the emission factors may be used, and what assumptions have to be
made.
Example 16.4-1
Estimating emissions from open burning of household waste in County A:
Survey results
A survey has been completed of 1,000 households in a rural portion of County A in the inventory
area. The survey area covered only locations where no public or private garbage pickup services are
available, determined through telephone conversations with County A's Planning Department. An
average household size is 2.5 people determined from U.S. Census Bureau statistics. Average waste
generation for a household is 6.75 Ibs per day, and 1.38 Ibs of the waste is noncombustible material.
Thus, combustable waste per household is 5.37 Ib/day. Sixty-seven of the 1,000 households use
burn barrels to dispose of combustable household waste.
Survey scaling
U.S. Census Bureau data lists 17,502 households in the rural portion of County A, and 2,636 of the
households are in areas where public or private garbage pickup services are available. This study
assumes that only the remainder, 14,866 households, are likely to open burn their waste. Of that
number, 6.7 percent (from the survey) are expected to actually burn their household waste
(996 households).
Emissions calculations for CO and PM
Both of the following waste calculations assume that households that open burn generate the
average amount of household waste, noncombustable material is not put in the burn barrels, and that
all of the combustable was subjected to burning and not recycled.
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Example 16.4-1 (continued)
The emissions calculation using ar\AP-42 factor uses total combustable waste. Total combustable waste
for County A:
Total Waste = 996 * 5.37 Ib/day
Burned (Ib/day)
5349 Ib/day
2.68 ton/day
CO emissions = 85 Ib CO/ton total waste burned * 2.68 ton/day
227.8 Ib CO/day
The emissions calculation using a factor from EPA (1997) uses waste actually burned. Fifty percent of
the waste subjected to burning, burned in tests reported in Evaluation of Emissions from the Open
Burning Of Household Waste in Barrels, (EPA, 1997). Twenty percent of that was noncombustable.
In County A, 50 percent of the total household waste generated by household is:
Waste Actually = 6.75 Ib/day * 50%
Burned (Ib/day)
= 3.38 Ib/day
The waste actually burned for County A is:
Waste Actually = 996 * 3.38 Ib/day
Burned (Ib/day)
= 3366 Ib/day
= 1.68 ton/day
Emissions calculation using factors from EPA (1997):
PM25 emissions = 34.8 Ib PM25/ton waste actually burned * 1.68 ton/day
= 58.5 Ib PM25/day
Activity Level Data Collection
Potential information sources for MSW open burning activity are:
• State solid waste agencies — these agencies track waste types, generation of
wastes and their treatment and disposal.
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• Local or state air quality agencies - these agencies should have information about
the rules in place concerning open burning, and they may track violations of the
rules, and generate estimates of the activity.
• Local health sanitation departments — these departments manage waste pickup
and disposal, and may have estimates of the amount of household waste (MSW)
burned, or estimates of the entire amount generated.
• Local fire and public safety departments — these departments may track reports of
violations of open burning rules. Reports may include burning of MSW, yard
wastes and land clearing wastes.
4.1.2 LAND CLEARING DEBRIS
Land clearing debris burning and prescribed burning are similar processes and burn similar fuels.
However, only land clearing debris burning is covered in this chapter. In some cases, the
distinction between the two subcategories will be the source of the activity data and the purpose
of the burning. Some inventories may combine these two subcategories. Care should be taken
not to double count activity between land clearing debris burning and prescribed burning.
Land clearing debris is typically piled and then burned, but can also be applied to material
collected in windrows, or to broadcast debris (material left undisturbed before burning) over an
area. The term slash is used for the debris that is left after logging or clearing.
The preferred method for estimating emissions from burning land clearing debris is to collect
permit data for land debris burning from the permitting agency. Estimates of the average tons of
fuel burned in the permitted burns of land clearing debris (the fuel loading per burn) will need to
be collected from state or local experts. In some cases, the permit may contain enough
information to estimate an average or typical amount of fuel burned. However, this method may
need to be supplemented with information such as the number of acres cleared for a sample of
permits, which would be collected from planning departments or building permits. This method
uses information specifically collected for the inventory area.
The amount of land clearing wastes burned can vary from year to year, usually depending on
local building and development, and by how much of the material cleared is either sold or
disposed of in some other manner. Other factors that may increase activity levels are natural
events such as tornadoes or insect infestations that create fallen wood that needs to be disposed
of.
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Activity Level Data Collection
Potential information sources for land clearing debris burning activity are:
• Local or state air quality agencies - These agencies should have information
about the rules in place concerning debris burning. They may be responsible for
permits and may track violations of the rules, and generate estimates of the
activity.
• Federal, state and local forest service and agricultural extension agents — Some
land clearing may result from the harvest of commercial timber, or removal of
stands of timber that have become diseased. The remaining material may be
disposed of by burning. See comments about sources of information about fuel
loading.
• Local planning departments — These departments track building permits and
development of land that will result in clearing, and register changes in land use.
• State or local transportation departments — These departments can estimate the
amount of clearing that took place for building new roads. If clearing did take
place, the transportation department may also have records that can be used to
estimate how much of the clearing debris was landfilled, composted, or burned.
• State solid waste agencies — These agencies may track or estimate land clearing
debris generation, and may maintain records about what happens to the debris.
These agencies are most likely to enforce rules about illegal dumping of wastes,
and may have estimates of the amount of waste illegally dumped that is from land
clearing.
• Local health and sanitation departments — These departments may have estimates
of the amount of land clearing debris generated, or estimates of the amount
burned. In some cases, these departments may be responsible for some of the
debris burning. These agencies should also be contacted about land clearing
debris that is landfilled or composted.
• Local fire and public safety departments — These departments may track reports of
violations of burning rules. Reports may include burning of MSW, yard wastes
and land clearing wastes, with no clear distinction between types.
Many areas require that permits be obtained before burning land clearing debris. Although the
permits may not include any estimates of the amount of waste burned, local experts may provide
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some estimates of typical size piles, or the amount of land cleared for each pile of debris. If
permit information is not available, if not all burning requires a permit, or if the information
needed for fuel loading is not available, this method cannot be used.
Emission Factors
At the time of this writing, there are no emission factors available that have been developed
specifically for land clearing debris burning. The emission factors for prescribed burning from
the most recent AP-42 section on Wildfires and Prescribed Burning, Chapter 13, Section 1, the
factors for unspecified forest residues in Table 2.5-2 of the AP-42 Open Burning section
(Chapter 2, Section 5), factors developed by Ward, et al. (1989) for logging slash, factors from
the EPA CTC study (EPA, 1996) or emission functions from Peterson and Ward (1993) are
recommended. Inventory preparers will have to decide which of these factors best suit the
activity data that has been collected for the inventory area, and the local fuel types. The AP-42
section on prescribed burning and Ward, et al. (1989) include factors for two phases of the burn,
termed the flame and the smolder. The flame stage is the initial fire, involving the smaller sized
and dryer fuels. The smolder phase occurs after the initial flame, and consumes larger sized fuels
and fuels that were initially not dry. Using these emission factors would imply a level of detail
rarely possible in area source emission estimates. Therefore, other factors provided for "fire"
burns that represent the average emission rate for the flame and smolder phases should be used
for area source inventory calculations. Assume that the emission factor for non-methane TOC is
entirely VOC.
A bench-scale study of emissions from typical land clearing debris materials has been done by
the US EPA Control Technology Center (CTC) (EPA, 1996b), which reports emissions of CO,
NO, total hydrocarbons (THC), PM2 5, PM10, and some HAPs. Emission factors for CO, CO2,
methane, non-methane hydrocarbons (NMHC), total PM, PM2 5, PM10, and NO from AP-42,
Ward, et al. (1989) and the CTC report are compiled in Table 16.4-2. Emission factors have
been converted to pounds per ton of fuel for this table. Emission factors from AP-42 are more
general and should be used in most cases. However, the Ward et al. (1989) factors and EPA
(1996b) factors can be used if the fuel configurations and material burned descriptions match that
being burned in the inventory area.
Emission factors and emission functions are also available for some HAPs. Factors from the
EPA (1996b) report are presented in Table 16.4-3, and emission functions from Peterson and
Ward (1989) are presented in Table 16.4-4. The EPA (1996b) factors are for piled debris
burning. The Peterson and Ward (1993) emission functions were developed to estimate
emissions for air toxics from prescribed burning emission factors for carbon monoxide (EFCO),
methane (EFCH4), or total particulates (EFPM). In this way, if one of these pollutants' emission
factors varies because of different fuel classifications or combustion phases, pollutants estimated
using the functions in Table 16.4-4 will also reflect that difference.
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TABLE 16.4-2
i
LAND CLEARING BURNING CRITERIA POLLUTANT EMISSION FACTORS
C
I
ct
EF
Source
Ward, et al
1989
AP-42,13.1
AP-42,13.1
AP-42, 13.1
AP-42, 13.1
AP-42, 2.5
Ward, et al
1989
EPA 1996b
Fuel
Configuration
Piled
Piled
Piled
Broadcast
Broadcast
Broadcast
unspecified
Broadcast
Broadcast
Broadcast
Broadcast
underburn
Broadcast
Test burn1
Test burn1
Test burn1
Test burn1
Material Burned
Coniferous Slash
Woody Debris
Logging Slash
Logging Slash
Hardwood
Logging Slash Conifer -
Short Needle
Logging slash Conifer -
Long Needle
Forest Residues
Douglas-Fir Hemlock
Slash
Hardwood Slash
Long-Needle Pine Slash
Mixed Conifer Slash
Juniper
Land Clearing Debris
(TN)
Land Clearing Debris
(TN)
Land Clearing Debris
(FL)
Land Clearing Debris
(FL)
Pollutants, Ib/ton
CO
153.20
185.40
74.00
224.00
350.00
254.00
140.00
312.40
256.20
178.40
201.40
163.00
46.00
32.00
38.00
30.00
CO2
3,271.20
3,143.40
3,082.40
3,072.20
3,201.80
3,165.40
3,231.00
Methane
11.40
21.72
3.60
12.20
11.20
11.40
5.60
11.00
13.20
8.20
12.80
12.00
NMHC
8.00
15.20
12.80
7.00
8.40
18.00
7.20
10.80
6.40
9.80
10.40
32.00
12.00
18.00
8.00
Total
PM
20.40
36.40
12.00
36.00
34.00
40.00
16.00
29.60
37.40
39.60
29.00
28.30
PM25
10.80
23.40
8.00
22.00
24.00
26.00
21.80
22.40
22.00
18.80
18.70
28.26
20.08
3.50
9.12
PM10
8.00
24.00
26.00
26.00
20.40
33.62
20.50
15.50
9.32
NO
0.74
0.10
0.06
0.18
01
O
I
CD
S
Co
-------
5
I
TABLE 16.4-2
(CONTINUED)
EF
Source
EPA 1996b
Fuel
Configuration
Test burn with
blower1
Test burn with
blower1
Material Burned
Land Clearing Debris
(TN)
Land Clearing Debris
(TN)
Pollutants, Ib/ton
CO
24.00
22.00
CO2
Methane
NMHC
14.00
12.00
Total
PM
PM,,
24.14
PM,n
24.46
NO
0.50
Sources: Ward, et al. (1989); EPA (1995a); EPA (1996b)
1 Factors from this source were derived from individual laboratory test burns. Test debris was collected in Tennessee (TN) and Florida (FL). Two
reported test burns were undertaken using blowers to simulate air curtain incinerators. These are marked on the table as ' Test burn with blower'.
See the reference document for further description of the study.
Co
i
01
o
I
CD
I
§
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CHAPTER 16 - OPEN BURNING
1/31/01
TABLE 16.4-3
LAND CLEARING BURNING HAP EMISSION FACTORS (EPA, 1996b)
Compound
(Ib/ton)
2-butanone(methyl ethyl ketone)
Ethyl benzene
Styrene
Cumene
Phenol
Dibenzofuran
Material Source and Fuel Configuration
No Blower
TN
0.084
0.074
0.152
0.038
0.075
0.010
TN
0.072
0.058
0.140
0.007
0.167
0.004
FL
0.080
0.042
0.080
0.004
0.130
0.008
FL
0.032
0.018
0.034
Nd
0.088
0.005
With Blower
TN
0.060
0.054
0.118
Nd
0.024
0.003
TN
0.038
0.070
0.172
0.036
0.190
0.009
a Factors from this source were derived from individual laboratory test burns. Test debris was collected in
Tennessee (TN) and Florida (FL). Two reported test burns were undertaken using blowers to simulate air curtain
incinerators. These are marked on the table as 'with blower'. See the reference document for further description
of the study.
b Nd - not detected.
Fuel Types
Fuel types described here are the same as those that would be burned in prescribed burning, so
descriptions of fuel types developed for prescribed burning can be used for land clearing burning
as well. Land clearing waste will typically not include live fuels. Fuel types are made up of
varying quantities of the following materials (Peterson and Ward, 1993):
• Woody fuels — include branches, logs, stumps and limbs.
• Duff — matted layers of partially decomposed organic matter and high organic
content soils such as humus or peat.
• Litter - Fallen leaves and needles, twigs, bark, cones, and small branches that
have not decayed to the extent of loosing their identity.
16.4-12
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CHAPTER 16 - OPEN BURNING
TABLE 16.4-4
HAP EMISSION FUNCTIONS To BE USED FOR LAND CLEARING BURNING
(PETERSON AND WARD, 1993)
Pollutant
Formaldehyde (HCHO)
Acetaldehyde (C2H4O)
Acrolein (C3H4O)
1,3-Butadine (C4H6)
Benzene (C6H6)
Toluene (C6H5CH3)
o-Xylenes
m,p-Xylene
n-Hexane (C6H14)
Polynuclear Organic Material (POM)
Methyl Chloride (CH3C1)
Carbonyl sulfide (COS)
Emission Factor Function (lb/ton)a
(0.0137*EFCO)-0.0358
0.315*EFHCHO
(0.0029*EFCO)+0.1398
0.00213*EFCO
0.00592*EFCO
0.00588*EFCO
0.00089*EFCO
0.00161 *EFCO
0.00017*EFCO
0.000345*EFPM
8.8toll.4b
0.267
a EFCO - carbon monoxide emission factor (Ib/ton)
EFHCHO - formaldehyde emission factor as calculated with formaldehyde function (Ib/ton)
EFPM - paniculate matter emission factor (Total PM) (Ib/ton)
b Flaming factor is presented
Example fuel models are listed in Appendix A. In a detailed study of emissions from burning
land clearing waste, emissions from varying quantities of each of the materials listed above
would be considered as part of the total emissions. However, fuel type groupings that are useable
for area source calculations are much more generalized, such as those listed in Table 16.4-2.
Fuel Loading
Fuel loading estimates are necessary in order to use the emission factors, which are based on the
weight of the material burned. Specifically, the debris that is burned will be a function of the
total biomass on the area, minus any wood or other material logged or harvested, amount of
wood that may be collected as fuelwood, and the amount of wood or other material that is
landfilled, composted or allowed to decay. For an area source inventory, generalized estimates
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can be made for fuel loading, although if specific information is easily available, it is preferred.
The most conservative estimate will assume that all material is burned. However, in areas where
there is usable timber, where rules restrict burning, or other disposal methods exist, information
about logging, landfilling, composting or firewood use should be collected.
The preferred approach for estimating fuel loading for land clearing debris is to use estimates
made specifically for the burns that have taken place. If a state forestry service requires a smoke
management report for land clearing debris, or has good compliance in a voluntary program, then
that data can be collected and used. If tonnages or volumes of land clearing debris are not
reported, then alternatives can be local estimates of the species types and debris amounts that
would be typical for the area. Regional estimates for fuel loading can also be used. The U.S.
Forest Service compiles forest resource data about forest area, volume, removals, residues and
timber product outputs, by region/subregion, ownership class, and species group which could be
useful in defining fuel loading for land clearing activity.2 Forest Service Technical Reports may
include enough information to develop a regional estimate of the amount of debris that typically
remains after logging or clearing.
State forestry agencies may compile similar data, and may be able to estimate the amount of
material cut for lumber or fuelwood and the amount burned. Landfill operators should have
records of the amount of land clearing debris that has been brought in to the landfill. In the
absence of reliable estimates, assume that all of the debris in an area that is cleared is burned.
However, this latter approach will overestimate emissions.
Other potential resources for fuel loading information are state forestry departments in other
states. Data collected in a neighboring state for prescribed burning estimates may have enough
similarity to the target state's forest types and disposal practices to be useable for an inventory.
Another alternative for estimating fuel loading is to use a procedure drawn from the
Intergovernmental Panel of Climate Change (TPCC, 1994). This procedure can be used when the
land cleared is logged before clearing and all useable timber on the cleared land is removed
before burning the remainder. The amount of timber that is harvested for commercial use may be
available through forest service statistics or state economic reports. Estimates of typical timber
yields for an area may also be available from state forest service experts or U.S. Forest Service
reports. The procedure uses a factor applied to the amount of logged wood to account for the
2 An example publication is Forest Statistics of the United States, 1992, Metric Units.,
(USDA, 1994) which has forest area statistics by state, and per hectare estimates of logging
residues by subregion and wood type (hardwood or softwood). These publications are produced
by regional forest experiment stations, and more recent publications may be available on the
regional stations' Web sites through the Internet.
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1/31/01 CHAPTER 16 - OPEN BURNING
unharvested portion (limbs, small trees, etc.) of the total biomass that was cleared. This factor is
called an expansion ratio, since it expands the measured amount of wood that is removed as logs
to calculate the amount of material that remains.
The expansion will take two steps. Because commercial timber may be measured by volume, the
first step is to convert the volume of harvested wood to weight units, using the values provided in
Table 16.4-5. The table gives density conversion factors for hardwoods and softwoods by typical
forest type within a region. The generalized factors represent a weighted average density of the
three most common (in terms of volume) softwood or hardwood species within the forest type.
Forest types are identified by the primary tree species or tree species groups, but will include
other tree species that are typically found in that biome. Local or state forestry service personnel
should be able to identify a typical forest type for an area. AP-42 Appendix A also contains more
general conversion factors. The more detailed factors in Table 16.4-5 are preferred.
The second step is to expand the amount of commercial timber harvested to represent the amount
that was left behind. Default ratios for expanding harvested timber amounts to unharvested
biomass are (IPCC, 1994):
• Undisturbed forests 1.75
• Logged forests 1.90
• Unproductive forests 2.00
Undisturbed forests are, or are close to being, in a natural, undisturbed state. These forests would
not commonly be cleared. Logged forests are those that have been logged or cleared previously,
and are regrowing, but not fully regrown (a forest may take one hundred years or more to return
to the state of an undisturbed forest). Unproductive forests have been overused or poorly
managed and may have reduced amounts of usable timber. When the forest type is unknown, the
more conservative expansion ratio for unproductive forests should be used as a default.
The calculation is:
Commercially Wood Type
Unharvested = Harvested ^ Density * Expansion Ratio (16 4-3)
biomass 3 /1U/A3\ '
Timber(ft ) (Ib/ft )
This amount can be assumed to be entirely burned, or can be corrected for the amount which is
estimated to be disposed of in other ways: landfilled, composted, or used as fuelwood. The
remainder is assumed to be open burned.
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TABLE 16.4-5
FACTORS TO CONVERT WOOD VOLUME (CUBIC FEET) TO
WEIGHT (POUNDS) (EPA, 1995)
Region
Southeast and
South Central
Northeast and
Mid Atlantic
North Central and
Central
Rocky Mountain and
Pacific Coast
Forest Type
Pines
Oak-Hickory
Oak-Pine
Bottomland Hardwoods
Pines
Spruce-Fir
Oak-Hickory
Maple-Beech-Birch
Bottomland Hardwoods
Pines
Spruce-Fir
Oak-Hickory
Maple-Beech
Aspen-Birch
Bottomland Hardwoods
Douglas Fir
Ponderosa Pine
Fir-Spruce
Hemlock-Sitka Spruce
Lodgepole Pine
Larch
Redwoods
Hardwoods
Density Conversion Factors
Softwood
31.8
33.4
32.6
28.7
23.6
23.0
23.3
24.0
28.7
26.3
21.9
26.0
23.2
23.1
28.7
29.5
26.0
21.8
27.1
26.4
31.7
26.0
26.5
Hardwood
39.9
39.9
39.9
36.2
33.8
32.8
39.7
37.4
36.2
33.1
30.0
39.4
35.9
29.0
36.2
23.7
23.7
23.7
27.0
23.7
27.0
36.2
24.0
16.4-16
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CHAPTER 16 - OPEN BURNING
If only the number of acres cleared is known, then Table 16.4-6 provides a default fuel loading
value from AP-42 for forest residues after harvest, from IPCC (1994) for grasslands, and
example fuel loading values from Ward et al. (1989). The example values for fuel loading were
developed from tests in the Pacific North West for mostly hardwood, mostly long-needle pine,
or mixed conifer forest types.
Emissions Calculations
Emissions calculations for emissions from burning land clearing debris use the following
general equation:
Emissions = Area Burned (acres) * Fuel Loading (tons/acre) * Emission Factor
TABLE 16.4-6
FUEL LOADING FACTORS -- FOR LAND CLEARING DEBRIS
Source
AP-42
Ward, etal., 1989
IPCC, 1994
Debris Type
Unspecified forest residues
Hardwood slash
Long-needle pine slash
Mixed conifer slash
Grasslands
Fuel Loading
(ton/acre)
70
66
21
54
4.5
(Mg/hectare)
157
149
46
121
10
In some cases, estimates of the tons of material burned will be substituted for the acres burned
and fuel loading factors.
4.1.3 YARD WASTES
Yard wastes include grass clippings, leaves, and tree and brush trimmings from residential,
institutional, and commercial sources. Planning and data collection for this source subcategory
should include research on local and state rules about open burning of these materials, the
disposal of yard wastes in landfills, and composting programs that may be in place for the
inventory area. Some localities prohibit open burning of yard wastes, and in that case,
emissions from this source subcategory may be negligible. On the other hand, localities may
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CHAPTER 16 - OPEN BURNING 1/31/01
collect yard wastes and dispose of the waste by burning. Estimating emissions in that case
would require an estimate of the yard waste collected by the locality, conversion of volume
measurements to weight, assumptions about the predominant materials in the waste, and
emission factors for the materials.
The preferred approach for this burning type is to collect locality-specific activity information
from a local expert. Sanitation and health departments, local recycling and composting
programs, and fire and public safety officials may track local generation or incidences of
burning and have estimates of the proportions of the yard waste that landfilled, composted and
burned.
In most cases, yard waste amounts will be estimated in units of volume, rather than weight.
This unit conversion can be problematic, because densities of grass clippings, leaves, or tree and
brush clippings can vary from tens of pounds to hundreds of pounds per cubic yard, depending
on the material, compaction and moisture content. The preferred approach for converting
volumes to weight is to derive a local estimate for yard wastes in the area. Local refuse haulers
that collect materials for composting programs may keep track of weights of incoming loads and
the volumes of the trucks. For example, if the volume capacity and tare weight (empty weight)
of a truck are known, and gross weights (filled weight) of several loads have been recorded, then
the weight to volume ratio can be calculated:
(16.4-5)
Ratio = (Gross-TareWolume
Where:
Ratio = Weight to volume ratio (yd3/tons)
Gross = Average filled truck weight (tons)
Tare = Empty weight of truck (tons)
Volume = Volume of truck (yd3)
There are major uncertainties in this approach, since the types of materials are unknown and it is
unknown whether the truck is full or not. However, the material in the truck has most likely
been compacted, and the resulting weight estimate can be taken as a conservative upper limit for
yard waste density. As a comparison, MSW weighs between 1,100 and 1,400 Ib/cu yd when
compacted, and 100 and 200 Ib/cu yd when uncompacted (NSWMA, 1985).
Emission factors for leaf burning (unspecified), weeds, and forest residues inAP-42
Tables 2.5-5 and 2.5-6 in Section 2.5 Open Burning, can be used to calculate emission estimates
and are shown in Table 16.4-10. The EPA Office of Solid Waste and Emergency Response
estimates that as a "ballpark" composition of yard waste, average composition by weight is
50 percent grass, 25 percent brush, and 25 percent leaves (EPA, 1996). These proportions will
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CHAPTER 16 - OPEN BURNING
vary according to season, region and climate, and it may be that only one type of yard waste is
burned, such as leaves in the fall. Alternatively, the conservative assumption of using the higher
emission factor between the two sets of factors can be made.
Emissions Calculations
A general emission calculation for yard waste burning is:
Emissions =
Yard % Weeds
Waste * Grass * Emission
(tons) Composition Factor
Forest
Residue
(tons) Composition E™ssion
v ' v Factor
Yard
Waste
Brush
Yard % Leaf
Waste * Leaf * Emission
(tons) Composition Factor
(16.5-2)
Yard waste is the total estimated amount of yard waste burned. If they are available, the
proportions of grass, brush or leaves can be used to subdivide that total to be applied to the
weed, forest residue or leaf emission factors, respectively. If the waste type proportions are not
known, the equation becomes:
Emissions =
Yard
Waste
(Tons)
Emission Factor
Where the emission factor used is the highest for the pollutant shown on Table 16.4-7.
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CHAPTER 16 - OPEN BURNING
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TABLE 16.4-7
YARD WASTE BURNING EMISSION FACTORS (EPA, 1995a)a
Yard Waste
Type
Leaf Species
Unspecified
Forest Residues,
Unspecified
Weeds,
Unspecified
Particulateb
Ib/ton
38
17
15
Carbon
Monoxide
Ib/ton
112
140
85
TOCC
Methane
Ib/ton
12
5.7
3
Nonmethane
Ib/ton
28
19
9
Emission factors in this table have been given a rating of D in AP-42.
b The majority of paniculate is submicrometer in size.
Average TOC emissions are reported for leaf burning are 29% methane, 1 1% other saturates, 33% olefins, 27%
other (aromatics, acetylene, oxygenates). For forest residues and weeds, average TOC values are 22% methane,
7.5% other saturates, 17% defines, 15% acetylene, 38.5% unidentified. Unidentified TOC are expected to
include aldehydes, ketones, aromatics, and cycloparaffins.
16.4-20
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
Alternative methods require less effort and less cost than the preferred methods, but may result
in less detail or estimates that are less specific to the area. The choice of a preferred over an
alternative method will be determined by the DQOs and budget of the inventory. For this source
category in particular, the significance of this source to total area emissions should be
considered when choosing methods.
During the planning stage of the inventory, research should be done to identify data sources,
rules affecting the source category, or other factors that might influence emissions from the
source category. See Section 16.4.1, Planning, for more specific issues.
5.1 MUNICIPAL SOLID WASTE BURNING
5.1.1 FIRST ALTERNATIVE METHOD
The first alternative method for estimating emissions from burning MSW is to collect estimates
of total MSW generation in the inventory area from local experts, and subtract the amount of
MSW that is disposed of by methods other than open burning. The remaining amount of waste
is assumed to be burned. In this case, the waste generation information and the disposal
information are specific to the inventory area.
Sources of information for total MSW generation or estimates of the landfilling, incineration or
recycling activity in the area would be many of the same information sources listed in Section 4
of this document for MSW open burning: state solid waste agencies, local sanitation agencies,
and local health departments. Other sources could be civil engineering departments in
universities, local or state planning departments, or environmental public interest groups.
If no estimates of local activity are available, then estimates will need to be generated. The
information needed is:
• Estimated total MSW generated in the inventory area;
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CHAPTER 16 - OPEN BURNING 1/31/01
• Estimated amount of the MSW that is landfilled, either in the inventory area or
outside of the area; and
• Estimated amount incinerated, composted, recycled, or otherwise disposed of.
Typical densities of MSW are:
Loose refuse: 100 to 200 Ib/cu yd (NSWMA, 1985)
Compacted waste: 1,100 to 1,400 Ib/cu yd (EPA, 1995a)
The general equation for estimating the MSW burned is:
MSW Total
Open = MSW
Burned Generated
MSW Total / A,re«r TV A f \
/-v A^cmr I A^cmr T jr-ii j MSW DlSDOSed OI I ,n , ,. _x
Open = MSW - MSW Landfilled + TT . ^, FA, ., , (165-2)
R,1,H r,^^ V Usm§ Other Methods } ^ >
Other methods of disposal for MSW will be any incineration, composting, or recycling that
takes place in the area. Some MSW will also be disposed of by open dumping. Activity for
open dumping will be difficult to estimate because it is typically illegal, but state solid waste
agencies may be able to provide estimates. Local estimates for total MSW generated are
preferred, but calculating estimates based on population-based generation rates are suitable for
this source category. The recommended population-based waste generation rate is 3.77 Ib MSW
generated per person per day, or 0.69 tons MSW generated per person per year (EPA, 1996a).
These generation rates are from the Office of Solid Waste's (OSW) annual report on the
characterization of MSW in the US and are for 1994.1 Waste make up, by material type, is
listed in Table 16.5-1. Total MSW reported in the OSW annual report is the MSW that enters
the waste stream to be landfilled, incinerated, recycled or composted where the composted
material is collected then treated. The estimate includes wastes from households, commercial
establishments, and other sources. It does not include the portion that may be open burned or
disposed of by other means. Thus, it can be assumed that the per capita MSW generation
estimate is an underestimate of the total that is generated in the US. However, within a
particular area, the national average per capita generation rate could be either an over- or an
1 The EPA Office of Solid Waste and Emergency Response maintains an Internet home page
at: http://www.epa.gov/epaoswer/osw/, and can be reached by telephone through the RCRA hotline
at 1-800-424-9346 or 1-800-553-7672, or by mail atRCRA Information Center, U.S. EPA, 401 M
Street, SW (5305W), Washington, D.C. 20460.
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CHAPTER 16 - OPEN BURNING
TABLE 16.5-1
GENERATION OF MUNICIPAL SOLID WASTE, BY MATERIAL 1994
(EPA, 1996a)
Materials
Paper and paperboard
Glass
Metals
Plastics
Rubber and leather
Textiles
Wood
Other
Food Trimmings
Yard trimmings
Miscellaneous inorganic wastes
Total MSW Generated
MSW Generated minus Yard trimmings
Ib/person/day
1.71
0.28
0.33
0.42
0.13
0.14
0.31
0.08
0.30
0.64
0.07
4.41
3.77
under-estimation. Yard waste should be reported separately, and is discussed in Section 16.5.5
of this chapter.
Estimates of the amount of MSW that is landfilled, and MSW that is disposed of using other
methods may have already been collected for the landfill source category emissions estimate
described in Chapter 15 of this document. Public health departments, local sanitation
departments and individual active landfills may need to be contacted for this information.
Activity data for this source category differs from the landfill source category in that landfill
activity data includes waste generated before and during the inventory year, and this source
category only requires information about the inventory year. Another correction to the landfill
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CHAPTER 16 - OPEN BURNING 1/31/01
source category activity data may be to remove the estimated amounts of wastes other than
MSW. These wastes would be land clearing debris and yard wastes, or industrial wastes, if such
wastes are accepted at the landfill.
Emission Factors
The emission factors discussed in Section 4 of this document for municipal waste are
recommended. These factors are listed in Table 16.4-4.
5.1.2 SECOND ALTERNATIVE METHOD
The second alternative method for estimating emissions from municipal solid waste burning
uses either the activity data collected or the emission estimates that were calculated for another,
similar area. The original data should have been collected using the preferred method, but can
be data from a different year than that of the current inventory, so long as the similarity between
areas is maintained. The data are scaled to the inventory area using a surrogate factor. If
activity data are used, the preferred method emission factors are employed to calculate emission
estimates.
An alternative to collecting activity from a similar inventory area is to use the per household
waste generation factor reported in the EPA report, Evaluation of Emissions from the Open
Burning Of Household Waste in Barrels, (EPA, 1997). This report is discussed in Section 4.1.2
of this chapter. The waste generation factor used in this report was based on a survey done by
the NY State Department of Environmental Conservation's Division of Solid Waste.
Table 16.5-2 lists the material types and amounts generated by the surveyed average household
of four people. This area is effected by a bottle bill, where beverage containers can be returned
for a deposit. This per household waste generation rate is in contrast to the waste generation
estimates presented in Table 16.5-1, which is based on the waste total generated by households,
commercial establishments and other sources.
The best match between two areas would be for areas that have the same demographic and
waste handling situations. During the preparation of emission estimates for the original area,
the significant matching factors for activity should have been identified. These factors may
include: deposits on glass, plastic and aluminum beverage containers; the presence of a rural,
less dense population; lack of refuse haulers; the distance between residences and the landfill;
the cost of hauling; and the population's income. If such factors can be identified, they can be
used to match inventory areas. Many cities and counties maintain demographic information and
information about services that could be useful. The U.S. Census Bureau also reports rural
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CHAPTER 16 - OPEN BURNING
TABLE 16.5-2
GENERATION OF HOUSEHOLD WASTE, BY MATERIAL (EPA, 1997)
Materials
Paper and paperboard
Glass/Ceramics
Metals
Plastics
Textiles/Leather
Wood
Food Waste
Total Waste Generated
Ib/household/day
6.7
1.1
1.1
0.8
0.4
0.1
0.6
10.8
population numbers for many counties.2 The extent of detailed information collected will
depend on the DQO of the inventory, the importance of the source category, and resources
available.
Rural population is the primary factor for matching inventory areas, and can also be used to
scale the emissions or the activity from the original area to the inventory area. Example 16.5-2
shows a typical scaling calculation:
2 U.S. Census Bureau data are available on CD-ROMs, paper reports, and can be viewed on
the Internet on: http://venus.census.gov/cdrom/lookup. Summary files under the Census Summary
Tape File 3 (STF3) listing on the Internet site will include population, households, household
income, education level and other population and housing statistics by county and by census tract.
The Summary Tape File 1A CD-ROM will have the same data, as will the Census printed reports,
Summary Population and Housing Characteristics, CPH-1 for county-level data, and Population and
Housing Characteristics for Census Tracts and Block Numbering Areas, CPH-3.
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Example 16.5-2
County A has a total population of 38,759, of which 33,951 people are considered rural
residents, from U. S. Census data. Using the first alternative method, it has been estimated that
593 tons of MSW is burned in County A. County B has a total population of 1 8 1 ,83 5, of which
27,078 people are rural residents.
The scaling equation is:
IVKAAA - County B Rural Populaion County A
"
Emissions " County A Rural Population M§W Burned
County B „„ „_„ „ , „ ., . 593 tons
MSW = 2?'°78 Rural Residents
Burned 33'951 Rural Residents Burned
= 473 tons MSW Burned
Emission Factors
The emission factors discussed in Section 4 of this document for municipal waste are
recommended. These factors are listed in Table 16.4-4.
5.2 LAND CLEARING WASTE BURNING
Methods for this burning type all use the emission factors discussed in Section 4, and vary only
in the specificity of the activity data and fuel loading factors used to the inventory area. The
information sources for activity and fuel loading that are listed in Section 4 for this type of
burning can be used for the alternative methods listed below.
5.2.1 FIRST ALTERNATIVE METHOD
The first alternative method is to estimate the amount of debris burned by collecting estimates of
debris generated by the land cleared in the inventory area during the inventory time period, and
subtracting the amount of debris that is disposed of by other methods.
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Activity data is developed for this method in three steps:
• Estimate the amount of land cleared in the inventory area during the inventory
time period;
• Estimate the amount of debris generated for a typical acre of cleared land and
multiply by the acres of land cleared; and
• Estimate the amount of debris that is not burned — either landfilled, composted,
or if possible estimates of debris that is illegally dumped, and then subtract from
the estimated total amount of debris generated.
See the listing of information sources under land clearing activity level data collection in
Section 4 of this chapter. Planning departments and DOTs should be contacted for information
about the amount of land cleared, and if possible, whether the debris was burned and if the land
was logged first, which would reduce the amount of debris. Forest service offices can be
contacted for information about the type of plant cover that would be burned in a particular area.
State solid waste agencies or environmental agencies may be able to provide estimates of how
much land clearing debris is illegally landfilled. State solid waste, landfill operators, and local
sanitation agencies should have estimates of the amounts of land clearing debris that were
accepted at local landfills during the inventory period. The cost of hauling this type of debris
over great distances would be prohibitive. Debris generated far from a landfill is probably not
sent to a landfill.
Refer to the land clearing portion of Chapter 4 for more information about information sources
and choosing fuel loading and emission factors.
5.2.2 SECOND ALTERNATIVE METHOD
The second alternative method for estimating emissions from burning land clearing waste uses
either the activity data collected or the emission estimates that were calculated for another,
similar area. Review the discussion of fuel types and fuel loadings for land clearing debris
burning in Section 4.2.3. The original data can be collected using either the preferred or the
first alternative methods. The data can also be from a different time period than that of the
inventory, so long as the similarity between areas is maintained. The data is scaled to the
inventory area using a surrogate factor. If activity data is used, the preferred method emission
factors are used to calculate emissions.
Areas should be matched by comparing disposal rules, disposal methods, and costs for disposing
of land clearing waste, and land cover types. Land covers should share enough common
qualities so that the fuel loading is similar. Areas can also be compared by looking at land use
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patterns. Clearing that is done for roads and commercial development will clear more per acre
of the land than that done for residential development.
Two types of scaling factors can be used for this source subcategory. If most of the land
clearing is for residential building, population growth can be used. If land clearing has been
done for roads, commercial development and residential building, the acres cleared should be
used to scale activity from the original area to the inventory area. Alternatively, the number of
residential and commercial building permits may be used to scale activity between the two
areas.
Emission estimates are calculated using the same equations and emission factors as the preferred
method.
5.3 YARD WASTE BURNING
Alternative methods for this type of burning differ from the preferred approach in that they use
less specific activity information and require more assumptions. Please review the discussion of
the types of material burned, conversion factors for, and other factors that affect data collection
and calculations under the discussion of the preferred method.
5.3.1 FIRST ALTERNATIVE METHOD
The first alternative method uses records of permits and violations of rules prohibiting yard
waste burning. If records are maintained of permits and violations, then an estimate of yard
waste burning from the permits and reported violations may be possible. Assumptions
necessary to transform reports of violations into an estimate of activity are estimates of the
typical volume and material for piles of yard waste, and scaling surrogates in order to scale
reports of burning from one small portion of the inventory area to the rest of the inventory area.
5.3.2 SECOND ALTERNATIVE METHOD
The second alternative method for estimating emissions from burning yard waste uses either the
activity data collected or the emission estimates that were calculated for another, similar area.
Review the discussion of yard waste activity and limits on activity in Section 4.2.5. The data is
scaled to the inventory area using a surrogate factor. If activity data is used, the preferred
method emission factors are employed in the emission estimation calculations.
The area used as a data source should be matched to the inventory area using similarities in
rules, waste disposal practices (such as composting programs and yard waste pickup programs)
and population density. Activity or emission estimates should be scaled using population.
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5.3.3 THIRD ALTERNATIVE METHOD
The third alternative method uses a local per acre waste generation rate, multiplied by
residential land use, and corrected with the amounts of yard waste that are estimated to be
landfilled or composted for the inventory area. Like the first alternative method discussed
above, this method relies on sampling a small portion of activity, and scaling it up for the entire
inventory area. The local generation rate is an estimate of what a typical maintained acre
produces in grass, trimmings, and leaves during either a year or during the inventory period.
Detailed information is unlikely, and gross assumptions will have to be made. Only one contact
should be necessary in order to develop a generation rate. Potential contacts are:
• Sanitation or health department personnel in areas where yard wastes are
collected separately from other wastes.
• The grounds maintenance crews of a landscaped park, or an institution with
grounds that may be similar to residential lots can be contacted for estimates of
the waste generated over a typical time period.
Volumes or weight amounts of the wastes collected for a known area can be averaged to a
typical acre. See Section 4.2.4 for more information about converting volume measures of yard
waste to weight measures. The per acre yard waste generation rate is applied to the amount of
the inventory area that is defined as residential, commercial and institutional land use. Local
planning departments or tax offices should be able to provide land use information.
The total yard waste generated for the inventory area is corrected by subtracting the amount of
waste that is collected and disposed of, or composted in the area. These estimates may be
available from health or sanitation departments, landfill operators, waste collection departments,
or local recycling and composting programs. It should be assumed that a certain amount of yard
waste is composted on-site where it was generated. Local recycling and composting programs
may be able to supply estimates of on-site composting. The remaining waste is assumed to be
burned.
There are considerable uncertainties in the scaling and correction steps of this approach.
The assumption necessary to use the per acre yard waste generation rate to the inventory area
will be an assumption of typical lot size.
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QUALITY ASSURANCE/QUALITY
CONTROL
Data collection and data handling for this source category should be planned and documented in
the Quality Assurance Plan. Quality assurance (QA) and quality control (QC) methods may vary
based on the data quality objectives for the inventory.
When using survey methods and other detailed methods that require data collection from
permits, or reports of violations, then the survey method, sample design, data collection, and
data handling steps should be documented in the Quality Assurance Plan. Refer to the
discussion of survey planning and survey QA/QC in Chapter 1, Introduction to Area Source
Emission Inventory Development, of this volume, and Volume VI, Quality Assurance
Procedures, of the Emission Inventory Improvement Program (EIIP) series. When using other
methods, data handling for activity, fuel loading factors, and emission factors should be planned
and documented in the Quality Assurance Plan. For all methods, the basis for choosing fuel
loading factors, and emission factors should be documented. Methods that use surrogate scaling
factors should also include an explanation of why those factors were chosen.
Potential pitfalls when preparing estimates for this source category are the potential overlap and
double counting of the open burning subcategories, use of the wrong fuel loading factor, the
choice of inappropriate scaling factors, or unit conversion errors.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
There are not large variations in the Data Attribute Rating System (DARS) scores between
preferred and alternative methods for most of the open burning source categories discussed in
this chapter. Emissions for all of the open burning source categories are estimated using
activity, fuel loading, and emission factors, and values for these parameters vary widely for very
similar circumstances; this means that for most of these source categories, estimates based on
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careful and detailed collection of data for these three parameters may still be far from the actual
emissions.
Emission factor scores provided here reflect emission rate variations dependent on differences
in the materials burned, burning types (smoldering vs. flaming), and whether the factors are
averages of direct measurements or ratios. Activity factor scores reflect variability in the
amount of available fuel that actually burned, fuel loading, and spatial and temporal variability
introduced when data from one area is scaled or extrapolated to the inventory area.
The effort required in collecting high quality activity information for these open burning source
categories and the inherent difficulty in obtaining good quality emission estimates, even when
detailed information has been collected, should be considered when planning the inventory and
choosing an estimation method.
6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for emission estimation methods for municipal solid waste burning are shown
in Tables 16.6-1 through 16.6-3; for land clearing waste burning, in Tables 16.6-4 through
16.6-6; and for yard waste burning Table 16.6-7 through 16.6-10. A range of scores is given
for many of the methods to account for the applicability of the available emission factors to the
materials that are actually being burned in the inventory area, the specificity of fuel loading
factors used, and different approaches for collection and scaling of activity data for a particular
method. DARS scores for these methods and for these source categories can be improved if the
uncontrolled variables that affect emissions can be limited.
6.2 SOURCES OF UNCERTAINTY
There are many sources of uncertainty in estimating emissions from open burning source
categories. Historically, emissions from this source category have been difficult to estimate
because of the lack of cost-efficient data collection methods and the large number of variables
that affect emissions. Methods presented here provide some more streamlined approaches, but
at a cost of less area-specific estimates. The data quality objectives for a particular inventory
and the priority of the open burning source category in the inventory should be used as a guide
when choosing inventory methods.
Although the methods presented here generally use only emission factors, fuel loading factors,
and activity factors, many other parameters operate when burning actually takes place. Details
for these other parameters, which include fuel moisture, type of combustion, and the amount of
fuel that is actually burned, are not available at the level required in an area source inventory.
The variance that may exist between burning that takes place in the inventory area and the
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burning measured to develop emission factors or fuel loadings cannot be defined without a
detailed study outside of the usual scope of an area source inventory.
In many cases, methods presented in this chapter recommend that data collected by survey or
other detailed methods such as permits or burning violation reports should be done for only a
subset of the inventory area or should be collected for another similar area. These data will need
to be scaled to the entire inventory area using a scaling surrogate. In all cases, scaling data from
another area will add uncertainty to the estimate of activity. If burning practices are well
matched from the data source area to the inventory area, this uncertainty is reduced; but if
burning practices are not similar, choosing an appropriate surrogate factor becomes more
important. In the case of the yard waste burning methods that use scaling, the inventory preparer
is expected to identify an appropriate scaling surrogate. Selecting the best scaling surrogate will
depend on the reasons that people burn and the material that they burn. Examples of appropriate
scaling surrogates for this subcategory of open burning are the number of rural residences,
residential lot size, or household income.
TABLE 16.6-1
MSW BURNING
PREFERRED METHOD: LOCAL ESTIMATE
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.7
0.5
0.55
Activity
0.4-0.6
0.7
0.7-0.9
0.7
0.63 - 0.73
Emissions
0.16-0.24
0.42
0.49 - 0.63
0.35
0.36-0.41
Emission factors are from AP-42 with a factor rating of D.
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TABLE 16.6-2
MSW BURNING
ALTERNATIVE METHOD 1: ESTIMATED TOTAL MINUS LANDFILLED AMOUNT
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.7
0.5
0.55
Activity
0.4
0.6
0.7
0.7
0.6
Emissions
0.16
0.36
0.49
0.35
0.34
a Emission factors are from AP-42 with a factor rating of D.
TABLE 16.6-3
MSW BURNING
ALTERNATIVE METHOD 2: SCALING OF DATA FROM A SIMILAR AREA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.7
0.5
0.55
Activity
0.4
0.5-0.6
0.6
0.7
0.55-0.58
Emissions
0.16
0.3-0.36
0.42
0.35-0.35
0.31 -0.32
Emission factors are from AP-42 with a factor rating of D.
16.6-4
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TABLE 16.6-4
LAND CLEARING WASTE BURNING
PREFERRED METHOD: LOCAL ACTIVITY AND FUEL LOADING DATA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4-0.7
0.5-0.8
0.7
0.8
0.6-0.75
Activity
0.7
0.7-0.9
0.9
0.6-0.8b
0.73 -0.83
Emissions
0.28 - 0.49
0.35-0.72
0.63
0.48 - 0.64
0.44 - 0.62
a Score depends on the factor used. Refer to source material for emission factors Current AP-42 factors get the
lower score.
b Fuel loading may vary by season, it is unlikely that it will be taken into account for these estimates. The higher
score is for data specific to the inventory time period, the lower score is given if data has been collected for a
different season, or for an entire year, when seasonal emissions must then be apportioned.
TABLE 16.6-5
LAND CLEARING WASTE BURNING
ALTERNATIVE METHOD 1: ESTIMATE FROM TOTAL LAND CLEARED AND
AMOUNT OF MATERIAL DISPOSED OF BY OTHER MEANS
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4-0.7
0.5-0.8
0.70
0.80
0.6-0.75
Activity
0.30
0.60
0.70
0.6-0.8b
0.55-0.6
Emissions
0.12-0.21
0.3-0.48
0.49
0.48 - 0.64
0.35-0.46
a Score depends on the factor used. Refer to source material for emission factors Current AP-42 factors get the
lower score.
b Fuel loading may vary by season, it is unlikely that it will be taken into account for these estimates. The higher
score is for data specific to the inventory time period, the lower score is given if data has been collected for a
different season, or for an entire year, when seasonal emissions must then be apportioned.
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TABLE 16.6-6
LAND CLEARING WASTE BURNING
ALTERNATIVE METHOD 2: EXTRAPOLATE DATA FROM A SIMILAR AREA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4-0.7
0.5-0.8
0.7
0.8
0.6-0.75
Activity
0.3 - 0.7b
0.6-0.9
0.5-0.7
0.6-0.8C
0.5-0.78
Emissions
0.12-0.49
0.30-0.72
0.35-0.49
0.48 - 0.64
0.31 -0.59
Score depends on the factor used. Refer to source material for emission factors Current AP-42 factors get the
lower score.
Activity score depends on the method used to collect data in the similar area (see scoring for preferred and
alternative one methods).
Fuel loading may vary by season, it is unlikely that it will be taken into account for these estimates. The higher
score is for data specific to the inventory time period, the lower score is given if data has been collected for a
different season, or for an entire year, when seasonal emissions must then be apportioned.
TABLE 16.6-7
YARD WASTE BURNING
PREFERRED METHOD: LOCAL DATA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.5
0.8
0.58
Activity
0.4-0.6
0.5-0.7
0.7-0.9
0.7
0.58-0.73
Emissions
0.16-0.24
0.3-0.42
0.35-0.45
0.56
0.34-0.42
Emission factors are from AP-42 with a factor rating of D.
16.6-6
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TABLE 16.6-8
YARD WASTE BURNING
ALTERNATIVE METHOD 1: SMALL-SCALE SURVEY FROM PERMITS AND VIOLATIONS
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.5
0.8
0.58
Activity
0.5
0.5-0.7
0.5-0.7
0.8
0.58-0.68
Emissions
0.2
0.3-0.42
0.25-0.35
0.64
0.35-0.4
Emission factors are from AP-42 with a factor rating of D.
TABLE 16.6-9
YARD WASTE BURNING
ALTERNATIVE METHOD 2: EXTRAPOLATE FROM A SIMILAR AREA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.5
0.8
0.58
Activity
0.4
0.5
0.5-0.6
0.7
0.53-0.55
Emissions
0.16
0.3
0.25-0.3
0.56
0.32-0.33
Emission factors are from AP-42 with a factor rating of D.
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TABLE 16.6-10
YARD WASTE BURNING
ALTERNATIVE METHOD 3: ESTIMATED LOCAL YARD WASTE MINUS LANDFILLED OR
COMPOSTED YARD WASTE
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor3
0.4
0.6
0.5
0.8
0.58
Activity
0.4
0.5-0.7
0.5-0.7
0.5
0.48-0.58
Emissions
0.16
0.3-0.42
0.25-0.35
0.4
0.28-0.33
Emission factors are from AP-42 with a factor rating of D.
16.6-8
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from open burning. A
complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 16.7-1 lists the applicable SCCs for open burning.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use in
regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data elements
necessary to complete the data set for use in regional or national air quality and human exposure
modeling. The inventory preparer should review the area source portion of the acceptable file
format(s) to understand the necessary data elements. The EPA describes its use and processing
of the data for purposes of completing the national inventory, in its Data Incorporation Plan, also
located at http ://www.epa. gov/ttn/chief/net/.
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TABLE 16.7-1
AREA AND MOBILE SOURCE CATEGORY CODES FOR OPEN BURNING
Process Description
Open Burning - All Categories
Open Burning - Industrial
Open Burning - Commercial/Institutional
Open Burning - Residential
Open Burning - Other Combustion: Managed
Burning — Slash
Source Category Code
26-10-000-000
26-10-010-000
26-10-020-000
26-10-030-000
28-10-005-000
16.7-2
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8
REFERENCES
EPA. 1997. Evaluation of Emissions from the Open Burning Of Household Waste in Barrels.
EPA-600/R-97-134a. U.S. Enivironmental Protection Agency, Control Technologies Center.
Research Triangle Park, North Carolina.
EPA. 1996a. Characterization of Municipal Solid Waste in the United States: 1995 Update.
U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response.
EPA 530-R-96-001; PB96-152 160.
EPA. 1996b. Evaluation of Emissions from the Open Burning of Land-Clearing Debris.
EPA-600/R-96-128. U.S. Environmental Protection Agency, Control Technology Center.
Research Triangle Park, North Carolina.
EPA. 1995a. Compilation of Air Pollution Emission Factors, Volume I: Stationary Point and
Area Sources, Fifth Edition, AP-42 (GPO 055-000-00500-1). U.S. Environmental Protection
Agency. Research Triangle Park, North Carolina.
EPA. 1994. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, NC.
EPA. 1992. Prescribed Burning Background Document and Technical Information Document
for Prescribed Burning Best Available Control Measures. EPA-450/2-92-003. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards. Research
Triangle Park, NC.
EPA. 1991. Procedures for the Preparation of Emissions Inventories for Carbon Monoxide and
Precursors of Ozone. Volume 1: General Guidance for Stationary Sources. EPA-450/4-91-016.
(NTIS PB92-112168). U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, North Carolina.
Gerstle, R. W. and D. A. Kemnitz. 1967. Atmospheric Emissions from Open Burning. Journal
of the Air Pollution Control Association. 17(5):324-327.
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IPCC. 1994. IPCC Guidelines for National Greenhouse Gas Inventories^ volumes: Vol. 1,
Reporting Instructions; Vol. 2, Workbook; Vol. 3, Reference Manual. Intergovernmental Panel
on Climate Change, Organization for Economic Co-Operation and Development. Paris, France.
National Solid Waste Management Association. 1985. Basic Data: Solid Waste Amounts,
Composition and Management Systems. Technical Bulletin No. 85-6.
Peterson, J. and D. Ward, 1993. An Inventory of Paniculate Matter and Air Toxic Emissions
from Prescribed Fires in the United States for 1989. IAG#DW12934736-01-0-1989. Final
Report, USDA Forest Service, Pacific Northwest Research Station, Fire and Environmental
Research Applications, Seattle, WA.
USDA. 1994. Forest Statistics of the United States, 1992 Metric Units, General Technical
Report, NC-168. Forest Science. U.S. Department of Agriculture, North Central Forest
Experiment Station, St. Paul Minnesota.
Ward, D.E., C.C. Hardy, D.V. Sandberg, and T.E. Reinhardt. 1989. Mitigation of Prescribed
Fire Atmospheric Pollution Through Increased Utilization of Hardwoods, Piled Residues, and
Long-Needled Conifers. Final Report, USDA Forest Service, Pacific Northwest Research Station,
Fire and Air Resource Management Project.
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APPENDIX A
PRESCRIBED BURNING
FUEL CATEGORIES
(PETERSON AND WARD, 1993)
TO BE USED FOR
LAND CLEARING WASTE BURNING
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Emission rates from prescribed burning vary depending on the fuels burned. One system for
categorizing the materials burned is the National Fire Danger Rating System, which uses 20 fuel
models to organize fuels according to their response to weather and influence on fire behavior.
Definitions of fuel components and the 20 fuel models are listed below.
FUEL COMPONENTS
1. Fine fuels less than 1 inch in diameter consisting of grasses, needles, and/or small twigs.
2. Small fuels 1 to 3 inches in diameter consisting of small branches and/or brush stems.
3. Large fuels greater than 3 inches in diameter consisting of large branches and/or logging
debris.
4. Live woody fuels from live, brush plants such as chaparral, palmetto-galberry, and juniper.
5. Litter and duff from the organic layers above the mineral soil. The litter retains its original
form, in contrast to duff which, by definition, is partially or fully decayed organic residue.
EXAMPLE FUEL MODELS
Brief descriptions of the NFDRS fuel models follow:
• Fuel Model A: Western grasslands vegetated by annual grasses and forbs. Brush
or trees may be present, but are very sparse, occupying less than one-third of the
area. Examples include cheatgrass and medusahead, open pinyon-juniper,
sagebrush-grass, and desert shrub.
• Fuel Model B: Mature, dense field of brush 6 feet or more in height are
represented by this fuel model. This model is for California mixed chaparral,
generally 30 years or older.
• Fuel Model C: Open pine stands typify Model C fuels. Perennial grasses and
forbs are the primary ground fuel, but there is enough needle litter and
branchwood present to contribute significantly to the fuel loading. Some brush
and shrubs may be present, but they are of little consequence. Examples are open
longleaf, slash, ponderosa, Jeffrey, and sugar pine stands.
• Fuel Model D: This fuel model is specifically for the palmetto-galberry
understory-pine overstory association of the southeast coastal plains.
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Fuel Model E: This model is for hardwood and mixed hardwood-conifer types
after leaf fall. The primary fuel is hardwood leaf litter.
Fuel Model F: Mature closed chamise and oak brush fields of Arizona, Utah, and
Colorado are represented by Fuel Model F. It also applies to young, closed stands
and to mature, open stands of California mixed chaparral.
Fuel Model G: Fuel Model G is used for dense conifer stands where there is a
heavy accumulation of litter and downed woody material. Such stands are
typically overmature and may also be suffering insect, disease, wind, or ice
damage—natural events that create a very heavy buildup of dead material on the
forest floor. Types meant to be represented by Fuel Model G are hemlock-Sitka
spruce, coast Douglas fir, and windthrown or bug-killed stands of lodgepole pine
and spruce.
Fuel Model H: The short-needed conifers (white pines, spruces, larches, and firs)
are represented by Fuel Model H. In contrast to Model G fuels, Fuel Model H
describes a healthy stand with sparse undergrowth and a thin layer of ground fuels.
Fuel Model I: Fuel Model I was designed for clearcut conifer slash where the total
loading of materials less than 6 inches in diameter exceeds 25 tons/acre.
Fuel Model J: This is for clearcuts and heavily thinned conifer stands where the
total loading of materials less than 6 inches in diameter is less than 25 tons per
acre.
Fuel Model K: Slash fuels from light thinnings and partial cuts in conifer stands
are represented by Fuel Model K. Typically the slash is scattered about under an
open overstory. This model applies to hardwood slash and to southern pine
clearcuts where the loading of all fuel is less than 15 tons/acre.
Fuel Model L: This fuel model is meant to represent western grasslands
vegetated by perennial grasses. The principal species are coarser and the loadings
heavier than those in Model A fuels.
Fuel Model N: This model was constructed specifically for the sawgrass prairies
of south Florida. It may be useful in other marsh situations where the fuel is
coarse and reedlike.
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Fuel Model O: Model O applies to dense, brushlike fuels of the southeast. The
high pocosins of the Virginia and North and South Carolina coasts are the ideal of
Fuel Model O.
Fuel Model P: Closed, thrifty stands of long needled southern pines are
characteristic of P fuels.
Fuel Model Q: Upland Alaskan black spruce is represented by Fuel Model Q.
This fuel model may also be useful for jack pine stands in the Lake States.
Fuel Model R: This model represents the hardwood areas after the canopies leaf
out in the spring.
Fuel Model S: Alaskan or alpine tundra on relatively well-drained sites is
represented by Model S. Grass and low shrubs are often present, but the principal
fuel is a deep layer of lichens and moss.
Fuel Model T: The sagebrush-grass types of the Great Basin and intermountain
west are characteristics of T fuels. This model might also be used for immature
scrub oak and desert shrub associations in the west, and the scrub oak-wire grass
in the southeast.
Fuel Model U: Closed stands of western long-needled pines are covered by this
model. Fuel Model U should be used for ponderosa, Jeffrey, sugar, and red pine
stands of the Lake States.
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16. A-6 EIIP Volume III
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VOLUME III: CHAPTER 17
ASPHALT PAVING
Revised Final
January 2001
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
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Volume III 11
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DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
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ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee of
the Emission Inventory Improvement Program and for Charles Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency. Members of the Area
Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
IV Volume III
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CONTENTS
Section Page
1 Introduction 17.1-1
2 Source Category Description 17.2-1
2.1 Process Description 17.2-1
2.1.1 Asphalt Mixtures 17.2-1
2.2 Emission Sources 17.2-3
2.2.1 Asphalt Mixtures 17.2-3
2.3 Factors Influencing Emissions 17.2-5
2.3.1 Process Operating Factors 17.2-5
2.3.2 Control Techniques 17.2-5
3 Overview of Available Methods 17.3-1
3.1 Estimation Methods 17.3-1
3.2 Available Methodologies 17.3-1
3.2.1 Volatile Organic Compounds 17.3-2
3.2.2 Hazardous Air Pollutants 17.3-4
3.3 Data Needs 17.3-4
3.3.1 Data Elements 17.3-4
3.3.2 Application of Controls 17.3-5
3.3.3 Spatial Allocation 17.3-5
3.3.4 Temporal Resolution 17.3-6
3.3.5 Projecting Emissions 17.3-8
4 Preferred Method for Estimating Emissions 17.4-1
4.1 Survey Planning 17.4-2
4.2 Survey Preparation 17.4-3
4.3 Survey Distribution 17.4-4
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CONTENTS (CONTINUED)
Section Page
4.4 Survey Compilation and Scaling 17.4-4
4.5 Emission Estimation 17.4-8
4.5.1 Volatile Organic Compounds 17.4-8
4.5.2 Hazardous Air Pollutants 17.4-9
5 Alternative Methods for Estimating Emissions 17.5-1
5.1 Volatile Organic Compounds 17.5-1
5.1.1 Alternative Method 1: Limited Survey of Selected DOTs 17.5-1
5.1.2 Alternative Method 2: State Usage Data, Minimum Data
Collection From DOTs 17.5-5
5.1.3 Alternative Method 3: Volume Usage Emission Factors 17.5-6
5.2 Hazardous Air Pollutants 17.5-9
6 Quality Assurance/Quality Control 17.6-1
6.1 Emission Estimate Quality Indicators 17.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 17.6-2
6.2 Sources of Uncertainty 17.6-2
7 Data Coding Procedures 17.7-1
7.1 Necessary Data Elements 17.7-1
8 References 17.8-1
vi Volume III
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FIGURES AND TABLES
Figure Page
17.4-1 Survey Request Form for Asphalt Cement Use - Instructions 17.4-5
17.4-2 Cutback Asphalt Data Request Form 17.4-6
17.4-3 Emulsified Asphalt Data Request Form 17.4-7
17.5-1 Simplified Data Request Form 17.5-2
17.5-2 Example Telephone Survey Form 17.5-7
Table
17.5-1 Evaporative VOC Emissions From Cutback Asphalts as a Function of
Diluent Content and Cutback Asphalt Type 17.5-3
17.5-2 Asphalt Paving Emission Factors 17.5-8
17.5-3 HAP Speciation Profiles for Asphalt Paving: Cutback Asphalt 17.5-8
17.6-1 DARS Scores for Asphalt Paving Preferred Method:
Comprehensive Survey 17.6-3
17.6-2 DARS Scores for Asphalt Paving Alternative Method 1:
Simplified Survey 17.6-3
17.6-3 DARS Scores for Asphalt Paving Alternative Method 2:
State-Level Usage Data 17.6-3
17.6-4 DARS Scores for Asphalt Paving Alternative Method 3:
Emission Factors 17.6-4
17.7-1 Area and Mobile Source Category Codes for Asphalt Paving 17.7-2
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Vlll Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
This chapter describes the procedures and recommended approaches for estimating emissions
from asphalt paving. Section 2 of this chapter contains a general description of the asphalt
paving category, the emission sources, and an overview of available control technologies.
Section 3 of this chapter provides an overview of available emission estimation methods.
Section 4 presents the preferred emission estimation method for asphalt paving, and Section 5
presents alternative emission estimation techniques. Quality assurance and quality control
(QA/QC) procedures are described in Section 6. Coding procedures used for data input and
storage are discussed in Section 7, and Section 8 is the reference section.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
This source category does not include emissions from asphalt plants, or emissions from other
related products such as roofing asphalts and sealers. It also does not include emissions that may
occur during the road preparation prior to paving.
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SOURCE CATEGORY DESCRIPTION
2.1 PROCESS DESCRIPTION
Asphalt paving is used to pave, seal, and repair surfaces such as roads, parking lots, drives,
walkways, and airport runways. Asphalt concrete used in paving is a mixture of asphalt cement,
which is a binder, and an aggregate. Asphalt cement is the semi-solid residual material left from
petroleum refining after the lighter and more volatile fractions have been distilled out. Hot-mix
asphalt is a mixture of heated asphalt cement and aggregate. Asphalt cutbacks are asphalt
cements thinned with petroleum distillates (diluents). Asphalt emulsions are mixtures of asphalt
cement with water and emulsifiers. Aggregates used in asphalt cements are typically
rock gravel or recycled asphalt pavement, but can also be byproducts from metal ore refining
processes. Aggregate may constitute up to 95 percent by weight of the total mixture.1 Mixture
characteristics for asphalt concrete are determined by the amount and grade of asphalt cement
used, the addition of solvent- or soap-based liquefying agents, and the relative amount and types
of aggregate used.
Recycled asphalt pavement (RAP) is being used more frequently, partly as a means to reduce
solid waste. One source estimates that 90 percent of asphalt processed is RAP.1 To reuse the
asphalt, the RAP is typically pulverized; sorted; mixed with recycling agents such as lime or
calcium chloride, or additional aggregate; then applied. The five methods of recycling are: cold
planing, hot recycling, hot in-place recycling, cold in-place recycling, and full depth reclamation.
All except hot recycling occur at the location where paving is to be done, although material
removed during cold planing may be processed at an asphalt plant.
2.1.1 ASPHALT CONCRETE
Asphalt concrete is grouped into three general categories: hot-mix, cutback, and emulsified.
Each is discussed below. Emissions from the application of hot-mix, cutback and emulsified
asphalt are discussed in Section 2.2.
1 Personal communication between Gary Fore, of the National Asphalt Pavement
Association and L. Adams, Eastern Research Group, Inc., February 1997.
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Hot-Mix Asphalt
Hot-mix asphalt is the most commonly used paving asphalt for surfaces of 2 to 6 inches thick.
Hot-mix asphalt is prepared at a hot-mix asphalt plant by heating asphalt cement before adding
the aggregate. To maintain a liquid mixture, these plants must be near to the paving site. In
some cases, mobile facilities are used. An estimated 22 million tons of hot-mix asphalt cement
concrete were sold in 1994 (Moulthrop, et al. 1997).
Cutback Asphalt
Cutback asphalt is used in tack and seal operations, in priming roadbeds for hot-mix application,
and for paving operations for pavements up to several inches thick. In preparing cutback asphalt,
asphalt cement is blended or "cut back" with a diluent, typically from 25 to 45 percent by volume
of petroleum distillates, depending on the desired viscosity. Cutback asphalt is prepared at an
asphalt plant. There are three types of cutback asphalt cement:
• Rapid Cure (RC) which uses gasoline or naphthas as diluents;
• Medium Cure (MC) which uses kerosene as a diluent; and
• Slow Cure (SC) which uses low volatility fuel solvents as diluents.
An estimated 0.75 million tons of cutback asphalt were sold in 1994 (Moulthrop, et al. 1997).
This represents about three percent of sales of all asphalt cement types.
A number of states recognize the emission potential from the use of cutback asphalts and have
established regulations limiting the amounts used and the time of year when they are used. The
inventory preparer should determine whether such regulations are in place for the area to be
inventoried before beginning data collection.
Emulsified Asphalt
Emulsified asphalt is used in most of the same applications as cutback asphalts but is a lower-
emitting, energy saving, and safer alternative to the cutback asphalts (Moulthrop, et al. 1997).
Instead of blending asphalt cement with petroleum distillates, emulsified asphalts use a blend of
asphalt cement, water and an emulsifying agent, such as soap. Such blends typically contain
one-third water, two-thirds asphalt cement and minor amounts of an emulsifier.2 Some
2 Telephone conversation between R. Benson of the Asphalt Institute and S. K. Buchanan,
Eastern Research Group, Inc., September 1997.
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emulsified asphalts may contain up to 12 percent organic solvents by volume (California
SCAQMD Rule 1108.1).1 Emulsification is done at an asphalt plant. Emulsified asphalts cure
by two methods: water evaporation and, in the case of cationic and anionic emulsions, ionic
bonding. For purposes of this document, the three types of concern are determined by the
proportions of the emulsifier and water in the blend:2
Rapid Set (RS);
Medium Set (MS); and
Slow Set (SS).
Approximately 1.76 million tons of emulsified asphalt were used in 1994 (Moulthrop, et al.
1997). This represents about seven percent of overall use of all asphalt types that year.
2.2 EMISSION SOURCES
Emissions from asphalt paving operations occur when asphalt mixtures are applied and as they
cure. The pollutants emitted depend on the diluents used and may include volatile organic
compounds (VOCs) and hazardous air pollutants (HAPs). Emission estimation methods are
available for calculating VOC emissions. To estimate HAP emissions, inventory preparers will
need to develop their own HAP content profiles from local data.
2.2.1 ASPHALT MIXTURES
Emissions from the application of the different asphalt mixtures are discussed below.
Hot-Mix Asphalt
For hot-mix asphalt, the organic components have high molecular weights and low vapor
pressures. Therefore, hot-mix asphalt use produces minimal emissions of VOCs and HAPs.
Estimates for national hot-mix asphalt paving emissions are about one order of magnitude lower
than national estimates of cutback asphalt paving. More information about hot-mix asphalt
paving emissions can be found in the EPA publication, Final Report - Evaluation of Emissions
1 Telephone conversation between R. Ryan of the U.S. Environmental Protection Agency
and L. Adams, Eastern Research Group, Inc., February 1997.
2 Additional information on emulsions may be obtained from the Asphalt Emulsion
Manufacturers Association, phone: (410) 267-0023
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from Paving Asphalts (EPA, 1994a). Because emissions from hot-mix asphalt are low,
estimation methods will not be included in this chapter.
Cutback Asphalt
For cutback asphalt, emissions are due to the use of diluents that contain VOCs and, in some
cases, HAPs. Cutback asphalt has the highest diluent content of the three asphalt categories and,
as a result, emits the highest levels of VOCs per ton used. Estimating emissions from the use of
cutback asphalt should be given a high priority in this source category. The two major variables
affecting both the quantity of VOCs and HAPs emitted and the time over which emissions occur
are the type and the quantity of organic solvent used as a diluent. As the rapid cure cutback
asphalt has the highest diluent content, use of this type of cutback asphalt produces the highest
emissions; evaporative losses are estimated at 95 percent by weight of diluent. Medium cure
evaporative losses are estimated at 70 percent by weight of diluent, and slow cure at 25 percent
by weight of diluent (EPA, 1996).
Emulsified Asphalt
In general, emulsified asphalts have a lower emission potential than cutback asphalts as they
contain less or no diluents. However, some may contain up to 12 percent by volume solvents
(California SCAQMD Rule 1108.1).5 Therefore, the inventory preparer should consider
evaluating the diluent content and composition of emulsified asphalts used in the inventory area,
before deciding whether to collect data to estimate emissions. Because cutback asphalt use is
regulated by a number of states to reduce VOC emissions, use of emulsified asphalts has gained
popularity. Thus, although emulsified asphalt diluent contents are typically lower than the
cutback asphalt, the amount used may be twice that of the cutbacks. If the emulsified asphalts in
use contain any VOC or HAP diluents, they may be worth including in the inventory.
Recycled Asphalt Pavement
Emissions from the use of recycled asphalt pavement (RAP) are expected to be no higher than
from hot-mix use. Heat is used to soften the asphalt coating the aggregate, thus no additional
source of VOCs or HAPs is introduced.6
5 Telephone conversation between R. Ryan of the U.S. Environmental Protection Agency
and L. Adams, Eastern Research Group, Inc., February 1997.
6 Telephone conversation between R. Benson of the Asphalt Institute and S. K. Buchanan,
Eastern Research Group, Inc., September 1997.
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2.3 FACTORS INFLUENCING EMISSIONS
2.3.1 PROCESS OPERATING FACTORS
Emissions from asphalt paving depend on the type of asphalt used (hot-mix, cutback, or
emulsified). Emissions are also a function of the VOC/HAP content. Because emissions result
from diluent evaporation, factors such as temperature will affect the rate of evaporation.
Hot-mix asphalt results in the lowest emissions per ton used, followed by emulsified asphalts.
Cutback asphalts result in the highest emissions.
2.3.2 CONTROL TECHNIQUES
The primary control option for emissions from asphalt paving is to reduce the amount of any
VOC/HAP-containing diluent in the asphalt. However, in some situations, asphalt with a lower
diluent content may not meet the performance requirements of the paving job and a higher
emitting asphalt must be used. Some reductions are also realized where the slower cure asphalts
are used. An estimated 95 percent of the diluent in rapid cure cutback asphalt evaporates,
whereas only 25 percent of diluent evaporates from the slow cure cutback asphalts (EPA, 1996).
States have also either prohibited the use of diluent-containing asphalts or established seasonal
schedules for the higher VOC asphalt cements such that these are not used during the peak ozone
formation season.
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OVERVIEW OF AVAILABLE METHODS
3.1 ESTIMATION METHODS
Two methods are available for estimating emissions from asphalt paving operations:
• Estimates based on surveys of the state and local Departments of Transportation
(DOTs) and paving companies; and
• Estimates using emission factors.
Selection of the appropriate estimation method depends on the relative significance of emissions
from this source in the inventory area and the data quality objectives (DQOs) of the inventory
plan. Refer to EIIP Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for
discussions of inventory categories and DQOs.
Before selecting an estimation method, the inventory preparer should research state and local
rules for asphalt paving operations in the inventory area. Many state and local air agencies limit
or ban the use of cutback asphalts, particularly during the ozone season. If this is the case for the
area to be inventoried and the timeframe of interest for the inventory is the ozone season, then
the priorities for inventorying asphalt paving operations will change and the estimation method
chosen may differ.
3.2 AVAILABLE METHODOLOGIES
Methods for estimating emissions for this source category differ primarily in the amount of data
to be collected and the manner in which the data are collected. Surveys are used in the preferred
method and the first and second alternative methods. Collecting more locally-specific
information will provide more accurate estimates. Surveys are a more intensive data collection
effort than gathering activity data to use with emission factors. With surveys, information on the
specific HAPs can be requested and the speciated emissions calculated from the outset.
Emission factors are only available for VOC estimates; therefore, speciation can be done only
after the VOC emissions are estimated using diluent composition information.
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3.2.1 VOLATILE ORGANIC COMPOUNDS
VOC emissions depend on the amount of VOCs in the diluent used in asphalt (term used
genetically to include cutback and emulsified asphalts). For the purposes of the chapter, diluents
are assumed to contain 100 percent VOCs. Thus, the amount of each asphalt type and the diluent
content must also be determined. Regardless of the estimation method used, assumptions about
the amount of VOC that evaporates must be made. Approximations for the amount of diluent
that evaporates from cutback asphalt are provided in AP-42:
• Rapid cure: 95 percent by weight of the diluent evaporates;
• Medium cure: 70 percent by weight of the diluent evaporates; and
• Slow cure: 25 percent by weight of the diluent evaporates.
Note that evaporation to these levels occurs over a period of about four months. Evaporation
curves are provided in AP-42. About 75 percent by weight of diluent evaporates in the first day
following application of rapid cure cutback asphalts, whereas, it takes about one week for
50 percent by weight of the diluent to evaporate from medium cure cutback asphalts.
Such estimates of evaporation are not available for emulsified asphalts. In the absence of this
information, the inventory preparer may elect to apply the estimates for the cutback asphalt
evaporation rates or may conservatively assume all the diluent evaporates.
A majority of asphalt paving work is done by the state and local DOTs, either by their own staff
or by contractors. Thus information on practices is generally centralized and should be available
to the state agency preparing the inventory. In addition, private companies may also pave such
surfaces as private roads and parking lots with asphalt materials. They may also pave under
contract to other governmental agencies like the military, the Bureau of Land Management,
forest service, or entities such as tribal governments. Information on this asphalt use is more
difficult to collect. Before undertaking a data gathering effort for these private paving
operations, the inventory preparer should assess the potential for these private activities to be a
significant emission source. One way would be to determine how much construction and private
road maintenance and repair is occurring in the inventory area, perhaps through the cognizant
construction permitting agency or a trade association for developers. Another way to assess
activity might be to contact a few private paving companies to develop an understanding of how
their asphalt uses compare to those by the DOTs. If the activity level is low, the inventory
preparer may opt to exclude the private paving operations from the inventory. Because the
emissions contribution from private paving operations is often much less than from DOT paving
activities, methods to estimate emissions from private paving operations have not been
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specifically addressed. These methods would be the same as for paving activities done for or by
the state and local DOTs.
For emissions from asphalt paving, the ranking of the estimation methods is as follows:
1. Preferred Method: Comprehensive survey of all state and local DOTs for data on
asphalts;
2. Alternative Method 1: Survey representative state and local DOTs, shorten the
survey by making assumptions about asphalt specific gravity, use AP-42 cutback
asphalt emission factors;
3. Alternative Method 2: Survey representative state and local DOTs, shorten the
survey further by making assumptions about asphalt specific gravity and
collecting usage data from other resources (e.g., trade associations), use AP-42
cutback asphalt emission factors; and
4. Alternative Method 3: A per capita or usage emission factor from EPA guidance
for preparing carbon monoxide and ozone inventories (EPA, 1991), collect
activity data (census data or usage data from trade associations or DOTs).
With the exception of Alternative Method 3, all require assumptions about evaporation of the
diluent. As mentioned earlier, AP-42 is one source for information.
The Preferred Method results in the most accurate estimate because data are collected on actual
paving practices. Alternative Method 1 is less accurate as it relies on EPA emission factors
rather than actual data. The estimate is improved by the use of activity data that are specific to
the inventory area. Alternative Method 2 is less accurate than the Preferred Method and
Alternative Method 1 because the usage data are not specific to the inventory area. Published
state data needs to be allocated to the local inventory level. Alternative Method 3 is the least
accurate, even though local per capita or usage data would be used. The emission factors are
based on the assumption that the diluent content is 35 percent solvent (special petroleum
naphthas), which is the midpoint of the range of contents according to AP-42, and that
five percent of diluent remains in the pavement, which is the evaporation rate for rapid cure
cutback asphalts. Thus, the resulting emissions may be overestimated.
To date, emission factors have not been developed by industry. However, if these are available at
the time the inventory is prepared, the inventory preparer should determine if these would be an
improvement over the EPA emission factors before using them. To assess this, the methods used
by industry and for AP-42 for deriving the emission factors need to be compared and a
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determination made of which is more accurate, based on a technical evaluation. Also, how well
the underlying data represent paving practices in the inventory area should be considered.
3.2.2 HAZARDOUS AIR POLLUTANTS
Surveys can be used to collect HAP data from state and local DOTs. In general, this will involve
requesting material safety data sheets (MSDSs) or manufacturer technical data sheets (TDSs) for
each of the asphalt types the state and local DOTs apply to identify diluent composition.
Resulting estimates are HAP-specific. Emission factors for HAPs are not available; therefore,
the inventory preparer must again rely on MSDSs and TDSs. The VOC emission estimates can
then be adjusted to determine speciated emissions. Although local data on the HAP content of
diluents used in the inventory area are preferred, a secondary source for speciation information
may be other state agencies.
3.3 DATA NEEDS
3.3.1 DATA ELEMENTS
The data elements used to calculate emission estimates for this category will depend on the
methodology used for data collection. The data elements necessary for an emission calculation
that should be requested in a comprehensive survey of state and local DOTs, the preferred
method, include:
• types of cutback asphalts (rapid, medium, slow cure);
• types of emulsified asphalts (rapid, medium, slow set);
• amount of each asphalt type used for the inventory year, before aggregate is
added;
• diluent content of each type;
• HAP content by weight for each diluent (for HAP inventories only); and
• seasonal practices for each asphalt type (for ozone inventories).
Also needed for the estimation are the specific gravities (density) of the diluted asphalt and the
diluents, where VOC and HAP contents are reported in percents by volume. Default values for
the density of cutback asphalt diluents are provided mAP-42 (0.7kg/L for rapid cure, 0.8kg/L for
medium cure, and 0.9kg/L for slow cure). According to the Asphalt Institute, emulsified asphalt
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densities are similar to that of water (1.0 kg/L; the AP-42 default is 1.1 kg/L). Emulsified
asphalts with diluents have densities somewhat higher or lower than that of water, depending on
the types and amounts of solvents.1 Solvent densities are available from MSDSs and other
standard chemistry references.
Fewer elements are needed if emission factors are to be used. It is still preferable to collect the
data from the state and local DOTs, but some may be available from other sources. For example,
local paving companies may be able to supply the typical diluent contents and trade associations
may be able to provide data on state usage that can be apportioned to the local inventory area.
Additionally, an estimate based on surveying representative DOTs may be sufficiently accurate
for inventory purposes.
3.3.2 APPLICATION OF CONTROLS
The most effective way to control emissions from asphalt paving is to reduce the VOC and HAP
contents in the asphalts. Because the asphalt types have different characteristics and meet
specific paving needs, use of the low VOC/HAP asphalts is not always feasible. As the data
collected will represent the actual VOC and HAP contents for asphalts in use, no additional
adjustment for controls will be needed.
Another control strategy to reduce ozone formation is to prohibit or limit the use of the
VOC-containing asphalts during the ozone season, as some states have done. Any adjustments to
incorporate state regulatory requirements will need to be made as a part of the temporal
allocation of emissions.
3.3.3 SPATIAL ALLOCATION
Spatial allocation is used in two cases in the preparation of an area source inventory: (1) to
allocate emissions or activity to the county level, and (2) to allocate county-level emission
estimates or activity to a modeling grid cell. For all but one method, the resulting estimate will
be at the county level because county level data are used in the estimate. To allocate emissions
or activity from the state level to the county level for Alternative Method 2, a number of
parameters may be used to determine county level activity. These include highway spending data
published by the Federal Highway Administration, population data published by the U.S. Census
Bureau, data on miles paved or lane miles from the state DOT, and data on vehicle miles traveled
(VMT) from the mobile source emissions group at the agency.
1 Telephone conversation between R. Benson of the Asphalt Institute and S. K. Buchanan,
Eastern Research Group, Inc., September 1997.
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Allocation of the emission estimates or activity to a modeling grid can be done using one of four
potential spatial surrogates, shown below in order of preference:
1. Detailed information about the miles of highway paved or the vehicle miles
traveled (VMT) within each grid cell, or a group of grid cells. This will typically
be done by the inventory personnel involved in estimating mobile source
emissions.
2. Highway spending data.
3. Lane miles.
4. Population data.
3.3.4 TEMPORAL RESOLUTION
Because asphalt paving activities depend somewhat on the weather, the level of activity over the
course of the year will vary from state to state. State and local regulations may also limit
activities during the ozone season. For the best information to temporally allocate emissions, the
inventory preparer should talk with the state DOT to establish any seasonal patterns. Daily
allocation of emissions for asphalt paving operations differ from other source categories in that
emissions occur over a period of time after the paving is done (EPA, 1996). Therefore, a seven
day week should be used to allocate daily emissions from this source category. However, if the
number of days worked per week are being used to estimate the relative amount of asphalt used
during a time period, then information about actual work schedules will need to be collected.
Application of asphalt paving materials will generally occur 5 days per week during typical
business hours; however, some large projects and maintenance operations may involve overtime.
Activity is dependant of the weather; more activity will take place during warmer and dryer
months. Refer to Chapter 1 of this volume for more information about temporal resolution.
Example 17.3-1 shows a typical calculation of daily emissions during the ozone season from
annual emissions.
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CHAPTER 17 - ASPHAL T PA VING
Example 17.3.1
Cutback asphalt use in County A is banned by state regulation. Weather conditions limit
the use of emulsified asphalt to the warmer months, from May through September, which
is about 21 weeks. Paving work is done 5 days a week during the months of May and
September (8 weeks) and 6 days a week from June through August (13 weeks). Asphalt
use is expected to be proportionate to the number of days worked. Evaporation of the
asphalt diluents are assumed to take place over a period of time after paving. Emissions
are expected to occur over 7 days a week.
Because cutback asphalt use is banned, emissions for cutback asphalt are not included in
County A's ozone season inventory. Daily emissions from emulsified asphalt paving are
calculated from annual emissions by following these steps:
1) Calculate the ozone season emissions from the proportion of days worked:
Number of Days
Asphalt is Applied = (8 weeks * 5 days/week) + (13 weeks * 6 days/week)
= 40 + 78
= 118 days asphalt is applied
Activity Percentage
During Ozone = (78 days/118 days) * 100
Season
= 66%
Ozone Season
Emissions
= Annual Emissions * 66%
2) Calculate daily emissions from ozone season emissions:
Daily
Emissions
Ozone Season
= Emissions/(7 days/week) (13 weeks/year)
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3.3.5 PROJECTING EMISSIONS
A discussion about developing growth factors and projecting emission estimates can be found in
Section 4 of Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development. Projecting emissions for this source category will require that two variables be
taken into account, the change in paving activity and any change in emission controls. Paving
activity may be projected using the same factors used to project changes in local lane miles,
VMT, or highway spending.
The EIIP Projections Committee has developed a series of guidance documents containing
information on options for forecasting future emissions. You can refer to these documents at
http://www.epa.gov/ttn/chief/eiip/project.htm.
17.3-8 Volume III
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
The preferred method for estimating emissions from asphalt paving is to conduct a
comprehensive survey of asphalt use by state and local departments of transportation (DOTs).
These highway and road maintenance departments are responsible for much of the total asphalt
paving activity. Furthermore, records should be accessible and information should be
sufficiently detailed to calculate VOC and HAP emissions. This section provides an outline for
preparing and using an asphalt paving survey and calculating emission estimates from the
information collected.
Use of the survey method depends on DOTs keeping records of asphalt usage. If DOTs do not
keep these records, this method is not practical. Also, a survey of DOTs will not include private
asphalt paving activities done by private contractors unless the contractors are also surveyed.
However, it is unlikely that a survey of contractors would be as reliable as that of DOTs for a
number of reasons. First, the response rate will likely be lower; second, they may not keep as
complete or as detailed records; and third, a contractor will do work over county or state
boundaries and may not be able to estimate asphalt use for just the inventory area.
Another drawback to this method is that a well-planned, well-implemented survey requires more
resources than other methods. Inventory preparers must judge whether the costs of this approach
are outweighed by the benefit of having an estimate that is more accurate and specific to the
inventory area and time period. Costs and labor efforts are highest the first time that a regional
or local survey is performed. Subsequent updates to the survey may be done using fewer surveys
at a much lower cost. In the years following the baseline survey, updates on asphalt usage may
be all that are needed. Periodically, information on changes in the percentages of different types
of asphalt used and the VOC/HAP content will be needed to accurately estimate emissions.
Surveys for area sources are specifically discussed in Volume I of the Emission Inventory
Improvement Program (EIIP) series and in Chapter 1 of this volume. A survey of state and
county DOTs will consist of: (1) survey planning, (2) survey preparation, (3) survey distribution,
(4) survey compilation and scaling, and (5) emission estimation. Discussion of these steps
follows.
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4.1 SURVEY PLANNING
During the planning phase, the following issues should be addressed:
• Survey data quality objectives (DQOs) should be identified, and procedures for
realistically reaching these objectives specified.
• The survey recipients and data needs must be identified.
- For counties where paving responsibilities are shared to a significant degree
by others (e.g., private developers, military installations, state or National
Parks), the survey may need to be sent to others besides local DOTs.
Where private contractors are used by DOTs, the DOTs may not maintain all
the records. Inventory preparers should consider having the DOTs take
responsibility for having their contractors complete the survey. However, in
the interest of time or due to resource constraints, the inventory preparer may
need to survey contractors directly.
- The use of diluents in emulsified asphalts should be preliminarily assessed. If
this is rare or only limited to certain counties or times of the year, then the
survey may be able to be shortened.
Where the characteristics of the types of asphalts used (i.e., percent diluent
and types of solvents) are similar across the state or for a region within the
state, a representative profile can be developed and applied to the others. This
would greatly reduce the survey effort.
The assumptions for diluent evaporation and asphalt densities should be
determined.
Paving projects may cross county boundaries, thus usage data must be
allocated to each county. Alternatively, the inventory area may include only
parts of some counties, thus only some of its paving activities need be
included. The basis for apportioning these activities is best determined by the
cognizant county agencies; however, some surrogates like the ratio of miles
paved or population may suffice. A choice of surrogate should be made
before the survey design is complete so that the data can be collected.
• Data handling needs specific to this survey must be identified.
• Survey QA/QC methods must be delineated and implemented.
The survey package should include a cover letter explaining the program, the survey form, a list
of definitions and a postage-paid return envelope. Both state and local DOTs may need to be
surveyed to collect necessary information.
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4.2 SURVEY PREPARATION
A survey may be either comprehensive or collect the minimum amount needed to estimate
emissions. The more detailed survey necessary for the preferred method would request:
• the types of cutback asphalts used (rapid, medium and slow cure);
• the types of emulsified asphalts used (rapid, medium and slow set);
• the amounts of each type of asphalt used in the inventory year;
• the diluent content of each type of asphalt; and
• seasonal usage patterns (for an ozone inventory).
Additional elements to consider requesting include:
• HAP content for each diluent (for HAP inventories only);
• specific gravities for each asphalt type (only if diluent or HAP contents are in
per cents by volume); and
• Factors to use for spatial or temporal allocation.
For a HAP inventory, the diluent composition would also be needed (types and percents of each
solvent) to determine the HAP content of the diluents. This may be available from material
safety data sheets (MSDSs) and manufacturer technical data sheets (TDSs) so the survey
respondent should send the relevant MSDSs and TDSs.
Where volume percents are provided, the inventory preparer will also need specific gravities for
the diluents or HAPs. These can be determined from standard chemistry references.
Survey preparers should clearly define the time period for which the survey information is being
collected. A request for annual data, for instance, should specify the range of months to avoid
confusion between fiscal and calendar years. It is preferable to collect data specific to the
inventory period, but for periods less than 12 months, usage will probably have to be apportioned
by the inventory preparer.
If the survey results need to be adjusted to a different spatial scale for future inventories, factors
that may be used to adjust the survey information may also be collected. For example, the miles
paved within the county for which the department is responsible could be requested from that
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department. Alternatively, VMT as a surrogate may be available from mobile emissions
inventory preparers.
The advantages of the more detailed approach are that the inventory developed is specific to the
locality, and the information collected can be more readily projected to inventories for
subsequent years.
Instructions for using the example survey form are provided on the survey cover page, shown in
Figure 17.4-1. Example data request forms are presented in Figures 17.4-2 and 17.4-3. For HAP
inventories, MSDSs for each asphalt type should be requested. The HAP weight-percent
information on the MSDSs is then used to determine HAP-specific emissions. An alternative
survey-based method for a HAP inventory would use a representative sample of the HAP
contents for each asphalt type, applied to a more complete VOC inventory of asphalt types and
usages.
4.3 SURVEY DISTRIBUTION
The preferred method requires the inventory preparer to contact every DOT in the inventory area.
Surveys are best distributed by mail, with an initial call to ensure receipt and to answer any
questions, and a follow-up call when the inventory preparer has any questions. Survey
distribution issues are discussed in Chapter 1 of this volume.
4.4 SURVEY COMPILATION AND SCALING
Survey compilation and scaling issues are discussed in Volume I of this series. Completed
surveys will result in information for many asphalt types and, in the case of HAP inventories,
multiple pollutants, so accurate and efficient data compilation will require planning for data
transfer and data management.
QC checks should be performed during this phase of the work (see Volume VI for QA/QC
methods). Incoming surveys should be checked for errors such as potential unit conversion
errors or omissions. Survey information should be checked for reasonableness. Survey
recipients may need to be contacted to clarify responses or to correct any errors. Once compiled,
survey information should also be subject to similar checks to ensure complete and accurate data
entry, prior to analysis. Preliminary sorting of the data by county to compare responses can be
used to identify outliers.
Depending on who responds to the survey, results may need to be either scaled up to account for
all counties in the inventory area, or scaled down to the inventory area where some counties need
only be partially included. In either case, a scaling factor should have been identified in the
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Department of Transportation for: county
Street Address:
City:
Contact Person/Phone Number:
The purpose of this survey is to collect information about the amounts and types
of asphalts used for paving so that estimates of air pollution from paving
operations can be made. Please enter the following information on the attached
forms.
1. List the asphalt types used in calendar year . Note that Table 17.4-
1 is for cutback asphalt; Table 17.4-2 is for emulsified asphalts.
Information about hot-mix asphalt is not needed.
2. Provide the cure or set rate for each asphalt type (include units of measure).
3 .* Provide the amount, in tons, of each asphalt type used.
4.* Provide the specific gravity for each asphalt type.
5.* Provide the volume percent of diluents in each asphalt type.
6. List the months during the year that each asphalt type is used (for
ozone inventories).
1. Attach copies of the material safety data sheets and manufacturer
technical data sheets for all of the asphalt types listed (for HAP
inventories).
For the asphalt mixed with aggregate (less the aggregate) and is not "as applied" during actual
paving operations.
FIGURE 17.4-1. SURVEY REQUEST FORM FOR ASPHALT CEMENT USE - INSTRUCTIONS
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1
Identification
# or Name
2
Cure Rate3
3
Amount Used,
Tons
4
Specific Gravity
5
Diluent Content,
Volume %
6
Amount Used in
Each Calendar
Month
o
s!
1
2
s
Rapid, medium, slow
FIGURE 17.4-2. CUTBACK ASPHALT DATA REQUEST FORM
c"
CD
03
-------
I
c"
1
Identification
# or Name
2
Set Rate3
3
Amount Used,
Tons
4
Specific Gravity
5
Diluent Content,
Volume %
6
Amount Used
in Each
Calendar
Month
03
O
a Rapid, medium, slow
FIGURE 17.4-3. EMULSIFIED ASPHALT DATA REQUEST FORM
1
2
s
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planning phase, and any necessary requests for information from the survey respondents included
on the survey form. Refer to Sections 3.3.3 Spatial Allocation and 3.3.4 Temporal Resolution for
more information about allocation and scaling factors for this source category.
4.5 EMISSION ESTIMATION
4.5.1 VOLATILE ORGANIC COMPOUNDS
Emission estimate calculations involve determining emissions of the pollutant(s) of interest, then
the application of any necessary spatial or temporal adjustments. Because asphalt paving is
defined as an area source, there should be no need to subtract the contribution from point sources
from the total. Emission estimate calculations from the information collected by survey require
the following steps. The diluent content may be assumed to be 100 percent VOCs.
When the weight of cutback (or emulsified) asphalt used and the volume percent of diluent are
provided:
Volume of Weight of ^ Density of
Cutback Used ~ Cutback Used ' Cutback
Volume of Volume of Volume % Diluent
Diluent Used " Cutback Used * in the Cutback (17.4-2)
Weight of Volume of Density of m A
Diluent Used ~ Diluent Used * Diluent (i/-4'-
Mass = Weight of ^ Weight % of Diluent
Emissions Diluent Used Evaporated ^ ' " '
If the weight percent of diluent is provided, Equation 17.4-5 is used instead of Equations 17.4-1,
17.4-2, and 17.4-3 to determine the weight of diluent used. Equation 17.4-4 is still used as the
last step to calculate mass emissions.
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Weight of = Weight of ^ Weight % of
Diluent Used Cutback Used Diluent in the Cutback ^ ' '
Diluent evaporation rates depend on the type of asphalt used and were discussed earlier. The
best information to use is product-specific; however, this kind of information is not expected to
be available. In the absence of product-specific data, AP-42 provides some guidance for
cutback asphalts. Note that the diluent densities assumed may differ from those in the inventory
area and this will be a source of error.
• Rapid cure cutback asphalts: 95% by weight of diluent evaporates;
• Medium cure cutback asphalts: 75% by weight of diluent evaporates; and
• Slow cure cutback asphalts: 25% by weight of diluent evaporates.
For emulsified asphalts, a conservative estimate can be derived by assuming all the diluent
evaporates. Alternatively, values similar to those from AP-42 for the cutback asphalts might be
used.
To convert specific gravity to density for use in Equations 17.4-1 and 17.4-3:
Density = Specific 8.34 Ib
(Ib/gal) = Gravity * gal (17.4-6)
or
Density Specific 1 kg
(kg/L) Gravity
4.5.2 HAZARDOUS AIR POLLUTANTS
To determine HAP emissions, first estimate the VOC emissions from Equations 17.4-1 through
17.4-4, then multiply by the ratio of the HAP of interest to the total VOC emitted (the weight
fraction).
Mass Emissions _ VOC Mass Weight Fraction f\7 A s
for Each HAP ~ Emissions * of Each HAP (1/.4-S
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Where:
Weight Fraction Weight of Each HAP
of Each HAP Weight of VOC Emitted
(17.4-9)
Example 17.4-1 illustrates how both VOC and HAP emissions are estimated.
Example 17.4-1
Data provided by one county for use in this example are summarized in the table:
Asphalt Type
Medium cure
cutback asphalt
Rapid set
emulsified asphalt
Amount Used (tons)
250
190
Density (Ib/gal)
7.8
8.5
Diluent Content (vol%)
28
7
The MSDSs state the diluent in the medium cure cutback asphalt was naphtha and the
diluent in the rapid set emulsified asphalt was xylene. Additional data used in the
calculations are:
* density of naphtha = 7.5 Ib/gal
• density of xylene = 7.2 Ib/gal
• evaporation of diluent from the medium cure cutback asphalt = 75% by weight
(from AP-42)
• evaporation of diluent from the rapid set emulsified asphalt = 95% by weight
(assumed same as for rapid cure cutback asphalt, in AP-42)
17.4-10
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Example 17.4-1 (Continued)
Combining Equations 17.4-1 through 17.4-4, emissions from the medium cure cutback
asphalt use:
Weight of
Cutback Used * ' . Density of Weight % Diluent Unit
= * Diluent m* „., , * ° , , *^
Density of Cutback Cutback Dlluent Evaporated Conversion
250 tons Q 2g ^ 7.5 Ibs ^ Q ?5 2,000 Ibs
7.8 Ibs/gal gal ton
= 100,961 Ibs naphtha
Similarly, emissions from the rapid set emulsified asphalt use:
Weight of Vol 0/
Emulsified Used „., °. Density of Weight % Diluent Unit
= * Dlluent m *„.,,* ° , , *^
Density of Emulsified Emulsified Dlluent Evaporated Conversion
190 tons ft -„ 7.2 Ibs ft ne 2,000 Ibs
= * 0.07 * * 0.95 * —
8.5 Ibs/gal gal ton
= 21,405 Ibs xylene
Total VOC emissions are the sum of the emissions for each type of asphalt used:
Total VOC
Emissions for the = 100,961 Ibs naphtha + 21,405 Ibs xylene
One County
= 122,366 Ibs
Total HAP emissions in this example are the same as total VOC emissions,
122,366 pounds. Speciated HAP emissions are calculated as the sum of each HAP emitted
from each type of asphalt used. As each asphalt type contained a single, different HAP,
the speciated HAP emissions from each asphalt type are the same as the VOC calculated
for each asphalt type, 100,961 Ibs naphtha and 21,405 Ibs xylene.
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This page is intentionally left blank.
17.4-12 Volume III
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
This section provides alternatives to the comprehensive survey approach that is the preferred
method. Alternative Methods 1 and 2 require some information collection from state and local
DOTs, but some of the information needed is collected from other sources. Alternative
Method 3 requires the least amount of data collection, however, the resultant emission estimate is
the least accurate.
5.1 VOLATILE ORGANIC COMPOUNDS
5.1.1 ALTERNATIVE METHOD 1: LIMITED SURVEY OF SELECTED DOTs
Alternative Method 1 is a simplified version of the preferred method. Instead of sending surveys
to all DOTs, a representative set are selected for surveying. Additionally, assumptions about
specific gravities are made by the inventory preparer which reduces the information requested in
the survey. The example survey form shown in Figure 17.5-1 differs from Figures 17.4-1 and
17.4-2 only in that specific gravity is no longer requested. For cutback asphalts, densities are
assumed to be the same as those used in developing the AP-42 emission factors in Table 17.5-1,
thus AP-42 emission factors can be used to estimate emissions. For emulsified asphalts, the
density is assumed to be the same as that of water.1
Once the data have been compiled, estimates of use by the rest of the counties must be
calculated. To do this, the inventory preparer will apply a ratio of activities for the counties,
determined during the survey planning phase. Some possible ratios are miles of highway (state
transportation data), VMT (mobile emission inventory preparers), government highway spending
(U.S. Office of Highway Information Management), and population (U.S. census data).
1 Telephone conversation between R. Benson of the Asphalt Institute and S. K. Buchanan,
Eastern Research Group, Inc., September 1997.
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1
Asphalt Type3 b
2
Cure or Set
Ratec
3
Amount Used,
Tons
5
Diluent Content,
Volume %
6
Months of the
Year Used
a Numbers in each column match the instructions provided in Section 4.4. Item 4, Specific
Gravity, is not needed for this alternative.
b Cutback Asphalt = CA
Emulsified Asphalt = EA
c Rapid , medium , slow
FIGURE 17.5-1. SIMPLIFIED DATA REQUEST FORM"
17.5-2
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CHAPTER 17 - ASPHAL T PA VING
Cutback Asphalt
To estimate emissions from cutback asphalt paving, the data collected on the cure type and
diluent content are used to determine the weight percent of cutback asphalt evaporated from
Table 17.5-1.
TABLE 17.5-1
EVAPORATIVE VOC EMISSIONS FROM CUTBACK ASPHALTS
As A FUNCTION OF DILUENT CONTENT AND CUTBACK ASPHALT TYPE*
Type of Cutback13
Rapid cure (RC)
Medium cure (MC)
Slow cure (SO
Percent, by Volume, of Diluent In Cutback0
25%
17
14
5
35%
24
20
8
45%
32
26
10
a These numbers represent the percent, by weight, of cutback asphalt evaporated. AP-42 Emission
Factor Rating: C
b Typical densities assumed for diluents used in RC, MC, and SC cutback asphalts are 0.7, 0.8, and 0.9
kg/liter, respectively.
0 Diluent contents typically range between 25 - 45%, by volume. Emissions may be linearly interpolated
for any given type of cutback asphalt between these values.
The weight percent is then multiplied by the weight of cutback asphalt used, also determined
from the surveys, to estimate emissions.
Mass Emissions =
Weight of
Cutback
Used
Weight % of
Cutback
that Evaporates
(17.5-1)
Emulsified Asphalt
As discussed earlier, data on diluent evaporation are not available for emulsified asphalt. As a
conservative estimate, the inventory preparer can choose to assume all the diluent evaporates.
Alternatively, some adjustment can be made based on the set rate; data in AP-42 suggests that the
slower the cure, the lower the evaporative emissions. The AP-42 emission factors in
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Table 17.5-1 do not apply, thus emissions must be calculated using Equations 17.4-1 through
17.4-4 in Section 4.5.
Combining these equations, emissions from emulsified asphalts are calculated as:
Mass
Emissions
Weight of ~ .+ ~
^ , -r- . Density of
Emulsified ^ , .~ ,
A , ,. - Emulsified
Asphalt ,,
Used Asphalt
Volume % of
Diluent in the
Emulsified
Asphalt
Density of
Diluent
Weight % of
Diluent
Evaporated
(17.5-2)
The equation is further simplified by assuming that emulsified asphalt is the same density as
water, regardless of the diluent content.2 The density parameters cancel and emissions are
calculated as:
Mass
Emissions
Weight of
Emulsified
Asphalt
Used
Volume % of
Diluent in the
Emulsified
Asphalt
Weight % of
Diluent
Evaporated
(17.5-3)
When all the diluent is assumed to evaporate, the value in Equation 17.5-3 for percent diluent
that evaporates is 100. When less than complete evaporation is assumed, the value of the percent
diluent represents the adjustment.
An example is provided to illustrate use of Alternative Method 1.
]
]
example 17.5-1:
Data provided by one county for use in this example are summarized in the table:
Asohalt Tvoe
Medium cure cutback
asphalt
Rapid set emulsified
asohalt
Amount Used (tons)
250
50
Diluent Content (vo\%)
28
7
2 Telephone conversation between R. Benson of the Asphalt Institute and S. K. Buchanan,
Eastern Research Group, Inc., September 1997.
17.5-4
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Example 17.5-1 (Continued)
Interpolating from Table 17.5-2, about 16 percent of the weight of the cutback asphalt would
evaporate from a medium cure cutback asphalt with 28 percent by volume of diluent.
Mass Emissions, OCA . 2,000 Ibs „ ,,
^ ,u , A , ,' = 250 tons * — * 0.16
Cutback Asphalt ton
= 80,000 Ibs
To determine emissions from the use of emulsified asphalt, densities for the diluent and the
emulsified asphalt are needed. Assuming the density for emulsified asphalt including diluent
is the same as for water, 8.34 Ibs/gal, and assuming 100% of the diluent evaporates:
Mass Emissions, CA , 2,000 Ibs _0/ 1AAO/
„ , -r- , * , V = 50 tons * — * 7% * 100%
Emulsified Asphalt tons
= 7,000 Ibs
Total VOC emissions are the sum of the emissions for each type of asphalt used:
Total VOC Emissions OA AAA ,, „ AAA ,,
f ^u /^ ^ >. = 80,000 Ibs + 7,000 Ibs
for the One County
= 87,000 Ibs
5.1.2 ALTERNATIVE METHOD 2: STATE USAGE DATA, MINIMUM DATA COLLECTION
FROM DOTs
Alternative Method 2 involves the use of state asphalt usage data from other sources like the
Asphalt Institute, rather than requesting this from DOTs, as is done with the preferred method
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and Alternative Method 1.3 First the state level data must be apportioned to the county level. As
discussed earlier, the basis for this should be determined in the planning phase. Like
extrapolating representative county data to counties for which data have not been collected as
done in Alternative Method 1, some options to use as a basis for this allocation include miles of
highway, VMT, government highway spending budgets, and population.
State usage data from the Asphalt Institute may not distinguish between the cutback and
emulsified asphalt types. The information needed to proportion the total into emulsified and
cutback categories can be collected from state and local DOTs. As with Alternative Method 1, a
representative group of DOTs should be identified, then information on practices and usage can
be collected by telephone. The goal is to (1) determine the percents of each asphalt type that are
used, (2) their typical diluent contents, and (3) when the types are used (for ozone inventories).
An example telephone survey is shown in Figure 17.5-2.
Once the usage by county has been assigned and the data on asphalt types are available, the
equations under Alternative Method 1 can be used to estimate emissions (Equations 17.5-1 and
17.5-3).
5.1.3 ALTERNATIVE METHOD 3: VOLUME USAGE EMISSION FACTORS
The least preferred alternative, Alternative Method 3, is to use volume-based emission factors
applied to total asphalt usage data (Table 17.5-2).
These emission factors were prepared for EPA's 1991 guidance for preparing CO and ozone
inventories (EPA, 1991) and are discussed in that document. Data on asphalt use must be
requested from county DOTs, or state usage data from sources like the Asphalt Institute can be
apportioned to the county level as described for Alternative Method 2.
Per capita factors based on national average asphalt use are not recommended for this source
category, because population is not a reliable indicator of local activity when scaling down from
a national level, and usage can vary from year to year, making a factor developed from one year's
data inappropriate for another year. A per capita factor developed from state specific data may
be an inexpensive way to estimate emissions when the source category is not a high priority.
3 The Asphalt Institute can be contacted by telephone: (606) 288-4960, or through their
internet web page: http://www.asphaltinstitute.org.
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CHAPTER 17 - ASPHAL T PA VING
Asphalt Type
Cutback Asphalt
Emulsified Asphalt
Cure/Set Rate
rapid
rapid
medium
medium
slow
slow
rapid
rapid
medium
medium
slow
slow
Estimated %
of Total Usage
Approximate
Diluent Content
Months of the
Year Useda
a Only needed for ozone inventories.
FIGURE 17.5-2. EXAMPLE TELEPHONE SURVEY FORM
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CHAPTER 17 - ASPHAL T PA VING 7/37/07
TABLE 17.5-2
ASPHALT PAVING EMISSION FACTORS
Asphalt Type
Cutback asphalt
Emulsified asphalt
Volume-based"
(Ib VOC/Barrel Asphalt)
88
9.2
a Assuming that the density of asphalt is similar to that of water, 8.34 Ibs/gal, one barrel (42 gal) of asphalt weighs
350 Ibs.
Asphalt Paving
The EIIP Asphalt Paving chapter was compared to the NTI source category, Asphalt Paving:
Cutback Asphalt. The EIIP chapter states that no generic emission factors for HAPs were
available. We can supplement the EIIP asphalt paving chapter by using the speciation profiles
used in the NTI for cutback asphalt. The speciation profile used in the NTI is shown in
Table 17.5-3.
TABLE 17.5-3
HAP SPECIATION PROFILES FOR ASPHALT PAVING: CUTBACK ASPHALT
HAP
Ethylbenzene
Toluene
Xvlene (mixed isomers")
Percent Weight of VOC
2.3
6.4
12.2
Once the data have been collected, emissions are estimated as follows:
A, T- • • Volume Usage Volume Used
Mass Emissions = _ . . _ ° * _, . ,, . , ... ,«-<-,,.
Emission Factor (Barrels of Asphalt) (17.5-4)
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5.2 HAZARDOUS AIR POLLUTANTS
The simplest way to collect the necessary composition information to determine HAP emissions,
is for the inventory preparer to request material safety data sheets (MSDSs) or manufacturer
technical data sheets (TDSs) from the DOTs receiving the survey. The weight percent of each
HAP is taken from the MSDS or TDS, then is multiplied by the weight of VOC emissions
estimated by any of the alternative methods to determine the speciated emissions
(see Equations 17.4-8 and 17.4-9). Alternatively, the inventory preparer may solicit HAP
information from local vendors or a few representative DOTs to establish typical compositions
for the asphalt types used in the inventory area. Again, this information is applied to the VOC
estimate to determine the speciated HAP emissions.
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QUALITY ASSURANCE/QUALITY
CONTROL
Data collection and data handling for all estimation methods for this source category should be
planned and documented in the Quality Assurance Plan. Quality assurance (QA) and quality
control (QC) methods may vary based on the data quality objectives for the inventory.
When using survey based estimation methods, the QA Plan should address the survey method
and sample design, in addition to data collection, and data handling steps. Refer to the
discussion of survey planning and survey QA/QC in Chapter 1, Introduction to Area Source
Emission Inventory Development., of this volume, and Volume VI, Quality Assurance
Procedures., of the Emission Inventory Improvement Program (EIIP) series. When using other
methods, data collection, data handling, apportioning of activity data to the inventory area and by
asphalt type (for the second alternative method) should be laid out in the QA Plan.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
The highest quality results will come from collecting the most detailed, locality- and
time-specific data possible. The preferred approach, if there is good survey coverage, should
yield such high quality data. When there are too many asphalt users in the inventory area to
survey completely, or when not all of the survey forms are returned, the first alternative method
can still provide information about asphalt types, diluent contents, and usage that can be used to
develop a high quality area source emission estimate. However, the work involved in collecting
the required information through surveys is significantly higher than the work required for the
second and third alternative methods. The greater amount of work involved in the preferred and
first alternative methods is rewarded in estimates that are more specific to the inventory area and
time period. Because asphalt types used and amounts of asphalt used can vary substantially by
locale and time period, this more detailed information could be useful, especially where rules
have been put in place since the previous inventory period, or new rules are being considered.
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
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6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The DARS scores for asphalt paving emission estimate methods are shown in Tables 17.6-1
through 17.6-4. The preferred method should provide very good results, so long as most of the
asphalt use is included in the survey. The first alternative method, a simplified survey, will also
provide good results, but will be less specific because of the scaling of the sample data and the
use of average emission factors in some of the equations. Both of these two methods reflect use
of specific types of asphalt during the inventory period. Scoring for these two methods scores the
asphalt type and diluent content information collection under the emission factor attribute, and
scores the usage of each type of asphalt as the activity factor.
The second and third alternative methods, in contrast, are less representative of the inventory area
and time period. The second alternative method provides results that reflect state asphalt type
usage, but not necessarily local asphalt type usage. The proportions of the asphalt types and the
diluent type and content are used to determine the emission factor. Scores for the emission factor
attributes are lower than those for the survey methods since this method uses a less specific
approach for identifying asphalt types. The third alternative method uses emission factors that
were developed through a 1989 top-down, material balance approach. The emission factor
attribute scores for this method reflect the overestimation that is introduced by taking this more
general approach.
6.2 SOURCES OF UNCERTAINTY
Actual emissions from this source category are affected by variables such as diluent contents of
asphalts, climate, road types, and repair frequencies. Emission estimates are affected by the
collection of information about the types and amounts of asphalt, diluent contents, scaling factors
and the use of average or default diluent contents and densities. Because of these variables,
local, inventory time specific data is the best way to reduce uncertainty in emission estimates.
It is important, however, to look at the uncertainty of estimates for asphalt paving in the context
of emissions from all area sources. For example, in an area where cutback asphalt use is banned
during the inventory season, emissions from emulsified asphalt may be so low that a high degree
of uncertainty in the estimate may not significantly impact the overall quality of the inventory.
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CHAPTER 17 - ASPHAL T PA VING
TABLE 17.6-1
DARS SCORES FOR ASPHALT PAVING
PREFERRED METHOD: COMPREHENSIVE SURVEY
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Factor
0.8
0.9
0.9
1
0.90
Activity
0.9
0.9
0.9
0.9
0.90
Emissions
0.72
0.81
0.81
0.90
0.81
TABLE 17.6-2
DARS SCORES FOR ASPHALT PAVING
ALTERNATIVE METHOD 1: SIMPLIFIED SURVEY
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Factor
0.7
0.8
0.8
1
0.83
Activity
0.8
0.9
0.8
0.9
0.85
Emissions
0.56
0.72
0.64
0.90
0.71
TABLE 17.6-3
DARS SCORES FOR ASPHALT PAVING
ALTERNATIVE METHOD 2: STATE-LEVEL USAGE DATA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Factor
0.4
0.6 - 0.7
0.6
0.8
0.60 - 0.63
Activity
0.7
0.8
0.7
0.8
0.75
Emissions
0.28
0.48 - 0.56
0.42
0.64
0.46- 0.48
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TABLE 17.6-4
DARS SCORES FOR ASPHALT PAVING
ALTERNATIVE METHOD 3: EMISSION FACTORS
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Factor
0.3
0.5
0.5
0.5
0.45
Activity
1
0.5
1
1
0.88
Emissions
0.30
0.25
0.50
0.50
0.39
17.6-4
Volume III
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from asphalt paving. A
complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 17.7-1 lists the applicable SCCs for asphalt paving.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use in
regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data elements
necessary to complete the data set for use in regional or national air quality and human exposure
modeling. The inventory preparer should review the area source portion of the acceptable file
format(s) to understand the necessary data elements. The EPA describes its use and processing
of the data for purposes of completing the national inventory, in its Data Incorporation Plan, also
located at http ://www.epa. gov/ttn/chief/net/.
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TABLE 17.7-1
AREA AND MOBILE SOURCE CATEGORY CODES FOR ASPHALT PAVING
Process Description
Cutback Asphalt - Total: All Solvent Types
Cutback Asphalt - Special Naphthas
Cutback Asphalt - Solvents: NEC3
Emulsified Asphalt - Total: All Solvent Types
Emulsified Asphalt - Special Naphthas
Emulsified Asphalt - Solvents: NEC
Source Category Code
24-61-021-000
24-61-021-370
24-61-021-999
24-61-022-000
24-61-022-370
24-61-022-999
' NEC = Not elsewhere classified.
17.7-2
Volume III
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8
REFERENCES
EPA. 1995. Compilation of Air Pollution Emission Factors - Volume I: Stationary Point and
Area Sources, Fifth Edition and Supplements, AP-42. U.S. Environmental Protection Agency,
Office of Air Quality Planning and Standards. (GPO-055-000-00251-7). Research Triangle
Park, North Carolina.
EPA. 1994a. Final Report - Evaluation of Emissions from Paving Asphalts. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, EPA-600/R-94-135. Research
Triangle Park, North Carolina
EPA. 1994b. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1993. Guidance for Growth Factors, Projections, and Control Strategies for the
15 Percent Rate-of-Progress Plans. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, EPA-453/R-93-002. Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Vol.1: General Guidance for Stationary Sources. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, EPA-450/4-91-016. Research
Triangle Park, North Carolina.
Moulthrop, J.S., R.G. Hicks, W.R. Ballou. Emulsion: The Future of Pavement Maintenance?
Emulsified Asphalt seeks its niche in the paving industry. The Asphalt Contractor. February
1997. p. 49.
State of California South Coast Air Quality Management District Rule 1108.1. Emulsified
Asphalt. Adopted August 3, 1979, am ended December 4, 1981, November 4, 1983. Paragraph
(b) Requirements.
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17.8-2 Volume III
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VOLUME III: CHAPTER 18
STRUCTURE FIRES
Revised Final
January 2001
ALAPCp
Prepared by:
Eastern Research Group, Inc.
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc. for the Area Sources Committee of
the Emission Inventory Improvement Program and for Charles Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency. Members of the Area
Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Ray Bishop, Oklahoma Department of Environmental Quality
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Also contributing to this document was Joy Bell of Maricopa County, AZ, Environmental Services Department.
EIIP Volume III
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IV EIIP Volume III
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CONTENTS
Section Page
1 Introduction 18.1-1
2 Source Category Description 18.2-1
2.1 Process Description 18.2-1
2.2 Factors Influencing Emissions 18.2-1
3 Overview of Available Methods 18.3-1
3.1 Planning 18.3-1
3.2 Available Methods and Data Requirements 18.3-2
3.3 Adjustments 18.3-3
3.3.1 Application of Controls 18.3-3
3.3.2 Spatial Allocation 18.3-3
3.3.3 Temporal Resolution 18.3-3
3.3.4 Other Factors Influencing Emission Estimates 18.3-4
3.3.5 Projecting Emissions 18.3-5
4 Preferred Method for Estimating Emissions 18.4-1
4.1 Structure Fires 18.4-1
4.1.1 Activity Level Data Collection 18.4-1
4.1.2 Fuel Loading 18.4-2
5 Alternative Methods for Estimating Emissions 18.5-1
5.1 First Alternative Method 18.5-1
5.2 Second Alternative Method 18.5-2
EIIP Volume III V
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CONTENTS (CONTINUED)
Section Page
6 Quality Assurance/Quality Control 18.6-1
6.1 Emission Estimate Quality Indicators 18.6-1
6.1.1 Data Attribute Rating System (DARS) Scores 18.6-2
6.1.2 Sources of Uncertainty 18.6-3
7 Data Coding Procedures 18.7-1
7.1 Necessary Data Elements 18.7-1
8 References 18.8-1
VI EIIP Volume III
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TABLES
Tables Page
18.3-1 Summary of Available Methods for Structure Fires 18.3-2
18.3-2 Occurrence of Residential and Non-residential Structure Fires in 1994,
by Month 18.3-5
18.4-1 Emission Factors for Structure Fires 18.4-5
18.6-1 Structure Fires Preferred Method: Local Data 18.6-2
18.6-2 Structure Fires Preferred Alternative Method 1: Scaled Local Activity ... 18.6-3
18.6-3 Structure Fires Alternative Method 2: Per Capita Activity 18.6-3
18.7-1 Area and Mobile Source Category Codes for Structure Fires 18.7-2
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Vlll EIIP Volume III
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1
INTRODUCTION
This chapter is one of a series of documents developed to provide cost-effective, reliable and
consistent approaches to estimating emissions for area source inventories. Multiple methods are
provided in the chapters to accommodate needs of state agencies with different levels of
available resources and skills; and different levels of needs for accuracy and reliability of their
estimates. More information about the EIIP program can be found in Volume 1 of the EIIP
series, Introduction and Use of EIIP Guidance for Emissions Inventory Development.
Throughout this chapter and other EIIP area source methods chapters, we stress that area source
categories should be prioritized by the inventory planners so that resources can be spent on the
source categories that are the largest emitters, most likely to be subject to regulations or are
already subject to regulations, or require special effort because of some policy reason.
Prioritization is particularly important for area source inventories, because in some cases, a
difficult to characterize source category may contribute very little to overall emissions and
attempting a high quality estimate for that source category may not be cost effective.
EIIP chapters are written for the state and local air pollution agencies, with their input and
review. EIIP is a response to EPA's understanding that state and local agency personnel have
more knowledge about their inventory area's activities, processes, emissions, and availability of
information; and require flexible inventory methods to best use their sometimes limited
resources. These EIIP area source chapters are written as a set of options presented to inventory
professionals capable of using their own experience and judgement to apply the method that best
fits their overall needs and constraints.
This chapter describes the procedures and recommended approaches for estimating emissions
from structure fires. Section 2 of this chapter contains a description of this category. Section 3
of this chapter provides an overview of available emission estimation methods. Section 4
presents the preferred emission estimation methods for structure fires, and Section 5 presents
alternative emission estimation techniques. Quality assurance and quality control procedures are
described in Section 6. Data coding procedures are discussed in Section 7, and Section 8 lists all
references cited in this chapter.
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18.1-2 El IP Volume III
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SOURCE CATEGORY DESCRIPTION
Accidental structure fires result from unintentional actions, arson, or natural events. Structure
fires covered in this chapter are accidental fires that occur in residential and commercial
structures. Accidental industrial fires are not included in this chapter because detailed emission
estimates are required that depend on the materials burned in each fire. Discussions about this
source can be found in two EPA documents (EPA, 1991 and EPA, 1993). A method for
estimating emissions from firefighters' practice fires is not defined in this chapter, but if it is
necessary to estimate fires from this source, the emission factors and the approach used in this
chapter to determining fuel loading may be useful.
Prescribed fires, agricultural fires, and other forms of open burning are discussed in Chapters 16,
19, and 20 of this volume. Fires covered in these chapters are those that occur because of
intentional actions (excluding arson) and are used to reduce or remove waste materials.
2.1 PROCESS DESCRIPTION
Structure fires covered in this chapter are only those affecting residential or commercial
structures. Accidental fires in yards, of vehicles and telephone poles are not included in this
chapter. Emissions from these types of fires are assumed to be very small.
Structural materials such as insulation and wood, and the contents of structures such as
furniture, carpets, clothing, paper and plastics, can burn in a structure fire. Not all of the
contents and structural materials burn in a fire, rather, the fire burns a portion of the contents and
structural material in the rooms where the fire originates and spreads. The average total material
burned (fuel loading) in a residential fire is estimated to be 1.15 tons (CARB, 1994). The
emission estimation methods discussed here are not valid for industrial fires where chemicals or
industrial materials are burned. Emission estimates for industrial fires should be based on the
type of industrial chemicals burned in each fire.
2.2 FACTORS INFLUENCING EMISSIONS
Emissions from structure fires depend on the structure type, physical properties of combustible
materials, and amount of material combusted. Residential and commercial structures will tend
to have differences in mixtures and quantities of combustible materials that will cause
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CHAPTER 18 - STRUCTURE FIRES Draft 1/31/01
differences in structural fire emissions. The portion of the structure and contents that are burned
is a function of the extent of the fire as well as the available fuel loading.
Process control mechanisms do not exist for accidental structure fires. Programs that improve
public awareness may reduce the number of accidental structure fires. However, the correlation
between such programs and reductions in structure fires is difficult to determine. Fire codes also
serve to reduce emissions from structure fires by requiring reductions in available fuel,
installation of sprinkler systems, and warning systems that improve emergency response time.
18.2-2 EIIP Volume III
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OVERVIEW OF AVAILABLE METHODS
Calculations for estimating emissions for structure fires use an equation based on emission
factors, fuel loading, and activity data. Area source methods can not address all of the
complexity involved in this source category. This section provides an overview of inventory
planning issues for the structure fire source category, outlines the preferred and alternative
methods, and discusses temporal adjustments and emission projection issues.
One of the particular difficulties in estimating emissions from the structure fire source category
is the lack of activity data, in terms of the number of incidents and the quantity of material
burned. When parameters have poorly defined or unavailable information, inventory preparers
will need to make well-educated assumptions.
Preferred and alternative methods in this chapter differ mainly in the level of detail and
area-specificity of the collected fuel loading and activity data. Each method has advantages and
disadvantages in terms of the expense and labor required for the method and the resulting quality
of the emission estimate. The inventory preparer must select a method based on the desired
accuracy of the emissions inventory, the resources available to develop the inventory, and the
potential for the source to contribute to the emissions inventory.
3.1 PLANNING
The first step in planning for structure fire estimation is to determine if enough fires took place
in the inventory area during the inventory time period to warrant including this source category
in the inventory. Refer to the second alternative method for ways to estimate the scale of
potential emissions from this source.
If it is determined that this source category should be included in the inventory, then the next
step is to choose an emission estimation method. This choice is based on the inventory data
quality objectives (DQOs), the estimated scale of the emissions relative to other area sources,
and availability of the information needed to make the calculations. The available information
and the amount of time and resources needed to collect it should be balanced with the priorities
and DQOs of the inventory to select the appropriate method for the inventory. Refer to EIIP
Volume VI, Quality Assurance Procedures, Sections 2.1 and 2.4 for discussions of inventory
categories and DQOs. Detailed information about this source category should be available from
local fire marshals and public safety departments, or state agencies that oversee public safety.
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Draft 1/31/01
National summary statistics on structure fires are available from the United States Fire
Administration and the National Fire Protection Agency (NFPA).1'2
3.2 AVAILABLE METHODS AND DATA REQUIREMENTS
The preferred and alternative methods for estimating emissions from structure fires are
summarized in Table 8.3-1. Emission factors are available to estimate particulate matter (PM),
total organics (TOG), methane (CH4), sulfur oxides (SOX), carbon monoxide (CO), hydrogen
cyanide, formaldehyde, acrolein, and nitrogen oxides (NOX) (Butler, 1972; EPA, 1995). To use
these emission factors, the total tons of material burned must be obtained from the activity and
the fuel loading. Calculation parameters to determine the quantity of material burned are
provided with the description of each estimation method.
TABLE 18.3-1
SUMMARY OF AVAILABLE METHODS FOR STRUCTURAL FIRES
Method Description
PREFERRED
Collect data for the number of residential and
non-residential structural fires. Use the fuel loading and
emission factors provided.
Calculation:
Number of fires * Fuel Loading Factor * Emission Factor
ALTERNATIVE 1
Collect data on the number of fires for a representative
portion of the inventory area and scale to the entire
inventory area based on population. Use the fuel loading
and emission factors provided.
ALTERNATIVE 2
Use the fires per capita factor provided with the method,
fuel loading and emission factors provided.
Activity Data
- Number of fires occurring within inventory area
- Number of fires for superset or subset area
- Inventory area and subset area population
- Inventory area population
The United States Fire Administration can be contacted at: 16825 South Seton Ave.,
Emmitsburg, MD 21727, phone: (301) 447-1000, or on the Internet:
http://www.usfa.fema.gov/
The National Fire Protection Agency can be contacted at: 1 Batterymarch Park,
Quincy, MA, 02269, phone: (617) 770-3000, or on the Internet: http://www.nfpa.org/
18.3-2
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The preferred method uses activity data collected for the entire inventory area. The first
alternative method uses activity data for either a subarea or a similar area that is scaled or
apportioned to the entire inventory area. A similar area is one that has the same population
density and housing characteristics. The second alternative is based on default per capita
activity.
3.3 ADJUSTMENTS
3.3.1 APPLICATION OF CONTROLS
No controls are available for this sources. The number of structure fires may be reduced as a
result of public awareness programs. The activity may reflect the impact of such programs.
3.3.2 SPATIAL ALLOCATION
Spatial allocation of the activity data is necessary for the alternative estimation methods. In
those cases, the data must be extrapolated or scaled to the inventory area using a spatial
surrogate. In addition to scaling or extrapolating emissions or activity from one area to another,
emissions or activity may need to be allocated within the inventory area. The recommended
spatial allocation surrogate for structure fires is population.
3.3.3 TEMPORAL RESOLUTION
Seasonal Resolution
Structure fires vary seasonally. Structural fires may increase during cold weather for some
inventory areas due to careless open burning, Christmas lights, or space heater or fireplace use.
For this reason, it is emphasized that the inventory preparer should investigate the time of
occurrence for these fires relative to the time period of the inventory during the inventory
planning stage.
The preferred method for apportioning structural emissions by season is to use local season-
specific activity data. The preferred emission estimation method is detailed enough to collect
season-specific data. In this case, information is collected on an incident-by-incident basis, and
emissions are either calculated for each incident or can be apportioned according to locally
specific activity levels.
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Alternative apportioning methods for structure fires are, in order of preference:
* Collect data from another area, either a subset, superset, a similar area, or from a
year other than that of the inventory for the inventory area. Using this approach
should include an effort to match the surrogate area or year to the inventory area
and year in terms of the factors that influence the frequency and severity of
accidental fires;
• Use estimates of activity from a local expert, such as the fire marshal or public
safety office; or
• Use the seasonal distribution reported in the National Fire Data Center's report,
Fire in the United States3 An example for 1994 of the monthly distribution of
residential and nonresidential structure fires is provided in Table 18.3-2. Please
note that this distribution represents national averages, and the distribution of
occurrences within a particular inventory area may differ. Non-residential fires
for this report are classified as industrial and commercial properties, institutions,
educational establishments, mobile properties, and properties that are vacant or
under construction.
Daily Resolution
Structure fires can be expected to take place seven days a week. Structure fire occurrences are
consistent through the week.3 The preferred and alternate methods discussed above for attaining
seasonal resolution apply for daily resolution as well.
3.3.4 OTHER FACTORS INFLUENCING EMISSION ESTIMATES
Natural disasters may affect structure fire activity and the resulting emissions. Natural disasters
such as hurricanes, tornadoes, ice storms or floods may cause electricity outages which
increases the use of fire in residences and increase the risk of structure fires. If the per capita
activity factor is used to develop the inventory, expert opinion may be required to estimate the
impact of natural disasters on structural fire activity.
3 Fire in the United States 1985 -1994, Ninth Edition, FA- 173/July 1997, or a similar
and more recent publication can be ordered from: United States Fire Administration,
Federal Emergency Management Agency, Publications Center, Room N310, 16825
South Seton Avenue, Emmitsburg, MD 21727, or ordered through the Web site:
http://www.usfa.fema.gov/
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TABLE 18.3-2
OCCURRENCE OF RESIDENTIAL AND NON-RESIDENTIAL STRUCTURE FIRES IN 1994,
BY MONTH"
Month
January
February
March
April
May
June
July
August
September
October
November
December
Total
Residential Structure Fires
%
12.6
9.8
9.1
8.2
7.4
7.5
7.4
6.9
6.6
7.5
8.0
9.0
100
Non-Residential Structure Fires
%
9.0
7.8
9.0
9.3
8.6
8.9
8.5
7.8
7.4
8.1
7.8
7.7
99.9
a Source: FEMA, 1997.
3.3.5 PROJECTING EMISSIONS
A discussion about developing growth factors and projecting emission estimates can be found in
Section 4 of Chapter 1 of this volume, Introduction to Area Source Emission Inventory
Development.
Projecting emissions for structure fires usually will take into account only changes in activity
levels. Sources of variation in structural fires include:
• Changes in population, either in total population or population shift in residential
housing types; and
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Changes in fire codes, building codes, or inspection policies that reduce the risk
of fires.
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PREFERRED METHOD FOR
ESTIMATING EMISSIONS
Emissions from structure fires are determined by the incidence of fires and the amount and the
type of material burned. The preferred method presented here is a set of guidelines for
identifying the parameters that need to be collected, where the information can be located, and
the assumptions that can be used in order to develop reasonable estimates. There is no universal
data source that can be used for every inventory to estimate emissions for this source category.
When lists of potential data sources are given as part of a method, one or more of these data
sources may need to be contacted.
As with all area source inventory categories, documentation should be maintained for data
collected, assumptions, information contacts, and calculations. Because preparation of an
inventory for this source category requires making assumptions in order to develop activity
levels, the basis for all assumptions must be well documented.
For structure fires, costs and labor efforts are highest the first time that the preferred method is
used. Subsequent updates to the inventory can be done using a local activity adjustment factor,
if a suitable scaling surrogate can be identified. Subsequent inventories should take advantage
of the data handling and quality assurance/quality control (QA/QC) routines put into place the
first time the method was used. See discussions of surveys for area sources in Volume 1 of the
EIIP series and in Chapter 1 of this volume for more information.
4.1 STRUCTURE FIRES
The preferred method for estimating emissions from structure fires should be used if more
detailed emission estimates are needed for planning, or the source category is a high priority. If
the information needed for this method can be easily compiled, then it may be worthwhile to
develop locality-specific activity surrogate factors and fuel loadings.
4.1.1 ACTIVITY LEVEL DATA COLLECTION
The preferred method for structural fires uses the statistics for the total number of fires in an
inventory area. Structure fire statistics by month are preferred for seasonal inventories such as
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ozone or CO inventories. If the default fuel loading factor is being used, then data on the
structure types that are involved in the fires need not be collected.
Potential information sources for locality-specific structure fires activity data are local or state
fire marshals or local or state fire and public safety departments. Reporting and availability of
information about structure fires will vary by locality. These contacts may also be able to
provide estimates of material loss for the inventory area, either as a portion of the structure or as
tons burned per fire.
When collecting information about occurrences of structure fires, be certain that the definition of
a structure fire counted by the fire marshal is actual fires and not the number of emergency calls.
Also, clarify the size of the fires if possible. Structure fires can be very small, such as electrical
wiring or cooking fires, or they can be large, consuming the entire structure. Most reported fires
will be small. Additionally, if fires that take place on residential property, such as garage fires,
are classified separately from other residential fires, then statistics for garage fires should be
obtained and included in the activity used to estimate emissions. Descriptions of the statistics
will also assist in determining if the majority of fires within the inventory area are accounted for
by the fire marshal.
4.1.2 FUEL LOADING
Fuel loading estimates are necessary to convert the activity (number of fires) to units compatible
with the emission factors, which are based on the weight of material burned. The material
burned will be a function of the total material available and the duration of the fire. The total
combustible material depends on the intended use of the structure. Structures can be broadly
classified as residential and non-residential, which includes commercial and institutional
structures. Residential structures can be further classified as single family and multi-family
dwellings. The state or local fire marshal may be able to provide estimates of material loss for
the inventory area, either as a portion of the structure or tons burned per fire. However, losses
are usually reported in terms of the dollar value lost.
The most conservative fuel loading estimate will assume that all the combustible material is
burned. However, this is not likely for most structural fires. Locality-specific fuel loading
factors for different structure types would improve the emission estimate, but a fuel loading
factor of 1.15 tons per fire using a method developed by California Air Resources Board
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(CARB) is an acceptable default value for all types of structures.4 The CARB approach to
developing a local fuel loading factor could be used for other inventory areas.
The fuel loading factor is based on an estimate of combustible structural content for a typical
residence, and an estimate of the average loss per fire. Combustible structural content is the sum
of the combustible structural materials and the building contents. Fuel loading is a percentage of
the total combustible structural content. Fuel loading is calculated:
Combustible Structural Materials = (Structural Mass + Contents) * Loss Percentage (18.4-1)
Combustible structural mass is calculated by multiplying an estimate of combustible material
per square foot in the building structure by the average residence's square footage:
Combustible Structural Materials (tons) =
Combustible Square Footage
Structural Mass * per Residence
Ib/sq ft sq ft
- 2000 Ib/ton (18.4-2)
CARB's estimate for combustible structural mass is 16.3 pounds per square foot. Assuming an
average residence size is 1350 square feet, combustible structural materials would be:
Combustible Structural Materials = (16.3 Ib/sq ft * 1350 sq ft) - 2000 Ib/ton
=11 tons
(18.4-3)
Average residence size can vary from region to region. Inventory preparers are encouraged to
identify a local average residence size. The U.S. Census Bureau5 reports that the national
median residence size in 1995 was 1732 square feet.
Combustible building contents are calculated by multiplying an estimate of contents per square
foot in the building structure by the average residence's interior floor space:
4 This method is derived from the CARB Emission Inventory Procedural Manual, Vol. Ill:
Methods for Assessing Area Source Emissions, developed by the California Environmental
Protection Agency: Air Resources Board. The latest version of the manual is available on
the internet at: http://www.arb.ca.gov/emisinv/areasrc/areameth.htm
5 The U.S. Census Bureau maintains an Internet Web site at: http://www.census.gov/
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Combustible Building Contents (tons) =
Combustible Floor Space
Building Contents * per Residence
Ib/sq ft sq ft
- 2000 Ib/ton (18.4-4)
CARB's estimate for combustible building contents is 7.91 pounds per square foot. Assuming
an average floor space per residence is 1200 square feet, combustible building contents would
be:
Combustible Building Contents = (7.91 Ib/sq ft * 1200 sq ft) - 2000 Ib/ton
= 4.7 tons
(18.4-5)
CARB estimates that the average loss per fire is 7.3 percent of the combustible structural
content. The average loss is based on monetary losses reported by FEMA and the average value
of residences reported by the California Association of Realtors. The loss rate is applied to the
estimated total combustible structural content to obtain a fuel loading per fire:
Fuel
Loading =
tons/fire
Combustible
Combustible
Structural Materials + Building Contents
tons
tons
Loss
* Rate
(18.4-6)
= (11 tons + 4.7 tons) * 0.073
= 1.15 tons/fire
The percent loss was estimated based on monetary losses. Fire marshalls typically report losses
as dollar loss statistics. There are, however, several weaknesses in using the dollar loss to
estimate the percentage of material combusted. First, material may be damaged by smoke or
sprinkler systems and counted as loss even though it is not combusted. Second, the value of
contents or structures is not directly proportional to the mass. Finally, the percent monetary loss
is the average loss divided by the average dollar value of structures. Since these two values do
not come from the same data source, there can be discrepancies in how they are determined.
Despite these weaknesses in representing material combusted, percent dollar losses may be the
most practical way to represent the percentage of material burned in a fire.
Emission Factors
Emission factors for structural fires are presented in Table 18.4-1. The emission factors given
are assumed to apply to all structure types.
18.4-4
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CHAPTER 18 - STRUCTURE FIRES
TABLE 18.4-1
EMISSION FACTORS FOR STRUCTURE FIRES
Pollutant
PM
TOG
Hydrogen cyanide
Formaldehyde
Acrolein
Hydrochloric acid
voc
NOX
CO
Factor (Ib/ton burned)
10.8
13.9
35.49
1.02
4.41
15.11
11
1.4
60
Reference
CARS, 1994a
CARS, 1994a
EPA, 2000
EPA, 2000
EPA, 2000
EPA, 2000
EPA, 1991
EPA, 1991
EPA, 1991
See footnote 4 in the text for more information about this document.
Emission Calculations
Emissions from structure fires are determined by multiplying the number of reported structure
fires by the fuel loading per fire and the emission factors from Table 18.4-1:
Emissions = Emission factor * Activity * Fuel loading
(18.4-7)
where:
Emissions
Emission factor
Activity
Fuel loading
Emissions for a given pollutant (Ib emitted)
Emission factor for a certain pollutant (Ib emitted/ton
burned)
Number of fires within the inventory area (fires)
Fuel loading per fire (ton burned/fire)
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If emissions are being calculated for an inventory season, and local season-specific activity is
not available, emissions can be apportioned using any of the three alternative apportioning
approaches from Section 3.3.3 of this chapter. Example 18.4-1 shows a typical calculation for
one county in an inventory area.
Example 18.4-1:
County A has had 115 structure fires reported for the inventory year. Information about the
structure types and the extent of the material burned in each fire was not collected, so the
default fuel loading of 1.15 tons per fire was used. The PM emissions for structure fires in
County A are:
Emissions = 10.8 Ib/ton * 115 fires/year * 1.15 tons/fire
= 1,428 Ibs/year
= 0.71 tons/year
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ALTERNATIVE METHODS FOR
ESTIMATING EMISSIONS
Alternative methods require less effort and less cost, but may result in estimates that are less
detailed and/or less locality-specific. The choice of a preferred over an alternative method will
be determined by the DQOs and budget for the inventory. For this source category in particular,
the significance of sources to the total area emissions should be considered when choosing
methods.
During the planning stage of the inventory, research should be done to identify data sources and
other factors that might influence emissions from the source category. See Section 3.1 of this
chapter for specific issues.
5.1 FIRST ALTERNATIVE METHOD
The first alternative method for estimating emissions from structural fires uses the same
emission factors and same default fuel loading described in the preferred method for this
category. The first alternative method relies on activity data from a larger inventory area that is
apportioned to the inventory area, or on activity data from a subarea that is scaled to the
inventory area. Activity information may be available from state or local fire marshals and
public safety departments, neighboring inventory areas, or from a subset of the inventory area.
When activity data is available for the whole state, or an area larger than the inventory area, then
the number of fires for the state will need to be apportioned to the county level. Population can
be used to apportion the number of fires. The equation to apportion the number of fires is:
Fires in county = Fires in state * county population/state population (18.5-1)
If activity data is scaled from a subarea or similar area, population is also used for scaling.
When information is collected for a small area and scaled to the inventory area, the number of
fires that occurred in that subarea can be collected from the few fire departments that serve that
subarea. The area that is used as a source of activity data should be similar to the entire
inventory area. According to statistics in the report, Fire in the United States: 1985 - 1994
(FEMA, 1997), cooking and heating are the leading causes of residential structure fires. As a
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result, heating types may have some influence on fire incidences, and structure fire activity from
an area that has distinctly different residential heating types than the inventory area may not be a
good match. The U.S. Bureau of Census can provide data on population and heating types.6
The scaling equation for structure fire activity from a subarea to a county in the inventory area
is:
Fires in county = Fires in subarea * county population/subarea population (18.5-2)
After activity data is scaled or apportioned to the inventory area, the default fuel loading factor,
emission factors, and emission calculations are the same as those described for the preferred
method.
Use any of the three alternative seasonal apportioning methods listed in Section 3.3.3 of this
chapter.
5.2 SECOND ALTERNATIVE METHOD
The second alternative method for estimating emissions from structural fires uses the same
emission factors and the same fuel loading that is described in the preferred method. However,
for this method, the activity is obtained by multiplying a national average factor of fires per
capita by the inventory area population. The number of fires per capita is based on an estimated
602,500 total fires reported for 1994 (FEMA, 1997) and a U.S. population of 260.4 million
(1994 U.S. population)7, averaging 2.3 fires per 1,000 people. If more recent data on total fires
becomes available, then those data can be used to calculate a more recent per capita activity
factor. Inventory area population is multiplied by the per capita factor to get the estimated
number of structure fires in the area.
After the inventory area activity level is determined, emission calculations are the same as those
described for the prescribed method, using the default fuel loading of 1.15 tons per fire and the
emission factors in Table 18.4-1. Example 18.5-1 shows typical calculations.
6 Census data is available through the U. S. Bureau of Census, Commerce Department,
Washington, DC, or through the Web site: http://www.census.gov.
7 U.S. Bureau of Census Web site: http://www.census.gov.
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Example 18.5-1:
County B's population is 0.5 million people. The structure fire activity is determined to be:
Activity = population * fires/population
= 0.5 million people * 2.3 fires/ 1,000 persons
1,150 fires
PM emissions can then be calculated as:
Emissions = emission factor * activity * fuel loading
= 10.8 Ib/ton * 1,150 fires/year * 1.15 tons/fire
14,283 Ibs/year
Use any of the three alternative seasonal apportioning methods listed in Section 3.3.3 of this
chapter.
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QUALITY ASSURANCE/QUALITY
CONTROL
Data collection and handling for the structure fire source category should be planned and
documented in the Quality Assurance Plan. Assumptions used and decisions made concerning
data sources should be documented. Refer to the Quality Assurance Quality Control (QA/QC)
section of Chapter 1, Introduction to Area Source Emission Inventory Development, of this
volume, and the QA volume (VI) of the Emission Inventory Improvement Program (EIIP) series.
Potential pitfalls when developing emissions estimates:
• Incomplete or inaccurate reports of the number of fires;
• Reporting that covers a geographic area that is either larger or smaller than that
for the inventory; and
• Inaccurate estimates of the material burned for each fire.
Potential errors common to many area source methods are calculation errors, including unit
conversion errors and data transfer errors.
6.1 EMISSION ESTIMATE QUALITY INDICATORS
In this chapter, three estimation methods are presented. The preferred method uses local data on
fire incidences collected for the entire inventory area, fuel loading factors developed from local
data or default factors from CARB, and a set of emission factors compiled from multiple
sources (see Table 18.4-1). The first alternative method uses local data on fire incidences
collected for a subset of the inventory area, the CARB default fuel loading factors, and the same
set of emission factors as the preferred method. The second alternative method uses the national
average factor of fires per capita to develop the activity, the CARB default fuel loading factor,
and the emission factors used for the preferred and first alternative methods. Using the most
accurate activity data, in the form of fire incidences and fuel loading, is the way to develop the
best emission estimates. However, inventory planners should consider the costs of data
collection versus the benefit of a more accurate estimate for a very small emissions source.
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6.1.1 DATA ATTRIBUTE RATING SYSTEM (DARS) SCORES
The Data Attribute Rating System (DARS) has been developed as a tool to rate emission
inventories. A description of the system and the EIIP recommendations for its use can be found
in Appendix F of EIIP Volume VI, Quality Assurance Procedures. The following discussion
uses the DARS rating system as a way to compare the estimation approaches presented in this
chapter and analyze their strengths and weaknesses.
The DARS scores for the three estimation methods are summarized in Tables 18.6-1 through
18.6-3. Variation between scores depends on the activity data used. All scores assume that
good QA/QC measures were performed and that no significant deviations from the prescribed
methods were made.
TABLE 18.6-1
STRUCTURE FIRES
PREFERRED METHOD: LOCAL DATA
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor
0.5
0.7
0.7
0.7
0.65
Activity
0.6
0.4
0.7
0.9
0.65
Emissions
0.3
0.28
0.49
0.63
0.43
18.6-2
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TABLE 18.6-2
STRUCTURE FIRES
ALTERNATIVE METHOD 1: SCALED LOCAL ACTIVITY
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor
0.5
0.7
0.7
0.7
0.65
Activity
0.5
0.4
0.6
0.9
0.6
Emissions
0.25
0.28
0.42
0.63
0.4
TABLE 18.6-3
STRUCTURE FIRES
ALTERNATIVE METHOD 2: PER CAPITA ACTIVITY
Attribute
Measurement
Source specificity
Spatial congruity
Temporal congruity
Composite
Scores
Factor
0.5
0.7
0.7
0.7
0.65
Activity
0.4
0.3
0.5
0.8
0.5
Emissions
0.2
0.21
0.35
0.56
0.33
6.1.2 SOURCES OF UNCERTAINTY
Another way to assess the emission methods is to examine the associated uncertainty. For the
preferred and first alternative methods, activity data is derived from local data, and can be
treated as survey data. Uncertainty for survey data can be quantified (see Chapter 4 of
Volume VI of the EIIP series). The uncertainty for the second alternative method, using fires
per 1,000 people, can be calculated by referring to the supporting documentation for the national
fire estimates (FEMA, 1997). This uncertainty will only pertain to the national estimate.
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Additional uncertainty will be introduced by scaling the activity estimate to an inventory area,
where average conditions of fire incidence may not exist.
A source of uncertainty for all of the methods is the fuel loading factor. No two fires will burn
the same amount of material, and material types and structure sizes vary from region to region in
the United States, as well as within a single county. The default fuel loading factor provided
here is an average of a highly variable factor, and should be understood to represent a practical
way to estimate area-wide emissions.
Emission factors also contribute to overall uncertainty. Emission rates of any pollutant for this
source category will be highly variable, given that the process is uncontrolled combustion of
mixed materials, and is not well constrained. This uncertainty cannot be quantified.
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DATA CODING PROCEDURES
The inventory preparer should check the EPA website (http://www.epa.gov/ttn/chief/) for the
latest information (codes) available to characterize emission estimates from structure fires. A
complete list of Source Classification Codes (SCC) can be retrieved at
http://www.epa.gov/ttn/chief/codes/. Table 18.7-1 lists the applicable SCCs for structure fires.
Available codes and process definitions influence and help guide the preparation of emission
estimates for this category. Data transfer formats should be taken into account when an
inventory preparer plans for data collection, calculation, and inventory presentation. Consistent
categorization and coding will result in greater continuity between emission inventories for use
in regional and national scale analyses.
7.1 NECESSARY DATA ELEMENTS
If the category emissions data will be transferred to EPA for incorporation into the national
criteria and toxics air pollutant inventory, specific data transfer formats are acceptable. The
acceptable data transfer format(s) are described and available for download at
http://www.epa.gov/ttn/chief/net/. The acceptable data transfer formats contain the data
elements necessary to complete the data set for use in regional or national air quality and human
exposure modeling. The inventory preparer should review the area source portion of the
acceptable file format(s) to understand the necessary data elements. The EPA describes its use
and processing of the data for purposes of completing the national inventory, in its Data
Incorporation Plan, also located at http://www.epa.gov/ttn/chief/net/.
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TABLE 18.7-1
AREA AND MOBILE SOURCE CATEGORY CODES FOR STRUCTURE FIRES
Process Description
Structure Fires - total
Source Category Code
28-10-030-000
18.7-2
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s
REFERENCES
CARB. 1994. Emission Inventory Procedural Manual, Vol. Ill: Methods for Assessing Area
Source Emissions. California Environmental Protection Agency: Air Resources Board.
EPA. 2000. National Toxics Inventory. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards. Research Triangle Park, N.C.
EPA. 1998. National Air Pollutant Emission Trends, Procedures Document, 1900 - 1996.
EPA-454/R-98-008. U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards. Research Triangle Park, N.C.
EPA, 1995. Development of Area Source Hazardous Air Pollutant Inventories, Volume 1: Air
Toxic Emission Inventories for the Chicago Area. U. S. Environmental Protection Agency,
Office of Air Quality Planning and Standards. Research Triangle Park, North Carolina.
EPA. 1994. AIRS Database. U.S. Environmental Protection Agency, Office of Air Quality
Planning and Standards. Research Triangle Park, NC.
EPA, 1993. Identification and Characterization of Five Non-Traditional Source Categories:
Catastrophic/Accidental Releases, Vehicle Repair Facilities, Recycling, Pesticide Application
and Agricultural Operations. EPA-600/R-93-045. U.S. Environmental Protection Agency, Air
and Energy Engineering Research Laboratory. Research Triangle Park, North Carolina.
EPA. 1991. Procedures for the Preparation of Emission Inventories for Carbon Monoxide and
Precursors of Ozone, Vol. I. EPA-450/4-91-016. U. S. Environmental Protection Agency,
Office of Air Quality Planning and Standards. Research Triangle Park, North Carolina.
FEMA. 1997. Fire in the United States: 1985-1994, Ninth Edition (FA-173/July 1997). Federal
Emergency Management Agency, United States Fire Administration, National Fire Data Center.
Emmitsburg, MD.
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VOLUME III: CHAPTER 24
CONDUCTING SURVEYS FOR AREA
SOURCE INVENTORIES
Final Report
December 2000
Prepared by:
Eastern Research Group
Prepared for:
Area Sources Committee
Emission Inventory Improvement Program
-------
DISCLAIMER
As the Environmental Protection Agency has indicated in Emission Inventory Improvement
Program (EIIP) documents, the choice of methods to be used to estimate emissions depends on
how the estimates will be used and the degree of accuracy required. Methods using site-specific
data are preferred over other methods. These documents are non-binding guidance and not rules.
EPA, the States, and others retain the discretion to employ or to require other approaches that
meet the requirements of the applicable statutory or regulatory requirements in individual
circumstances.
-------
ACKNOWLEDGEMENT
This document was prepared by Eastern Research Group, Inc., for the Area Sources Committee
of the Emission Inventory Improvement Program and for Charles O. Mann of the Air Pollution
Prevention and Control Division, U.S. Environmental Protection Agency (EPA). Members of
the Area Sources Committee contributing to the preparation of this document are:
Kristin Abraham, West Virginia Department of Environmental Protection
Kwame Agyei, Puget Sound Air Pollution Control Agency
Dan Brisko, New York State Department of Environmental Conservation
Orlando Cabrera-Rivera, Wisconsin Department of Natural Resources
Andy Delao, California Air Resources Board
Laurel Driver, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
Mark Eastburn, Delaware Department of Natural Resources
Charles Mann, Air Pollution Prevention and Control Division, U.S. Environmental Protection Agency
Sally Otterson, Washington Department of Ecology
Kenneth Santlal, Massachusetts Department of Environmental Protection
Walter Simms, Maryland Department of the Environment
Jack Sipple, Delaware Department of Natural Resources and Environmental Control
Karla Smith-Hardison, Texas Natural Resources Conservation Commission
Angel Thompson, South Carolina Department of Health and Environmental Control
Lee Tooly, Emission Factor and Inventory Group, U.S. Environmental Protection Agency
ill
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CONTENTS
Section Page
1 Introduction 24.1-1
1.1 What Is a Survey? 24.1-1
1.2 How Can This Chapter Help Me? 24.1-1
1.3 How Is This Chapter Organized? 24.1-1
1.4 Where Can I Go For Additional Information? 24.1-3
2 How Do I Determine if a Survey Is Necessary? 24.2-1
2.1 Assess Your Data Needs 24.2-1
2.2 Evaluate the Relative Importance of the Category to Your Total
Emissions Inventory Program 24.2-2
2.3 Evaluate the Data Quality Objectives for the Inventory 24.2-3
2.4 Assess Data Availability 24.2-4
2.5 Evaluate Resource Availability 24.2-5
2.6 Consider the Administrative Clearances 24.2-7
2.7 Consider If It Is Possible to Coordinate the Information Collection
Activity with Other Inventory Efforts 24.2-7
3 What Is the Most Important Aspect of Conducting a Survey? 24.3-1
4 What Survey Techniques are Available? 24.4-1
4.1 Mail Surveys 24.4-1
4.2 E-Mail Surveys 24.4-2
4.3 Web Page Surveys 24.4-3
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CONTENTS (CONTINUED)
Section Page
4.4 In-Person and Telephone Interviews 24.4-4
5 How Do I Determine How Many Surveys to Send - and To Whom? 24.5-1
5.1 What Are the Advantages of Sampling from the Entire Population? 24.5-1
5.2 How Do I Identify the Population? 24.5-1
5.3 How Do I Determine the Sample Size? 24.5-4
5.4 How Do I Select the Sample? 24.5-6
6 What Should I Consider When Preparing the Questionnaire Form? 24.6-1
6.1 What Are the Most Important Aspects of Preparing the Questionnaire
Form? 24.6-1
6.2 Where Do I Start? 24.6-1
6.3 What Should I Consider for the Survey Format? 24.6-2
6.3.1 Keep the Survey Brief 24.6-2
6.3.2 Design the Questionnaire to Fit the Medium 24.6-2
6.3.3 Consider All of the Survey "Users" 24.6-2
6.3.4 Miscellaneous Tips 24.6-3
6.4 What is Most Important for the Questions? 24.6-3
6.4.1 Open-end and Closed-end Questions 24.6-3
6.4.2 "Don't Know" or "Not Applicable" 24.6-4
6.4.3 Miscellaneous Tips 24.6-4
6.5 Instructions 24.6-5
6.6 Pilot Testing 24.6-5
7 What Should I Consider When Preparing the Cover Letter? 24.7-1
7.1 Who Should Send the Letter? 24.7-1
7.2 Who Should Receive the Letter? 24.7-1
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CONTENTS (CONTINUED)
Section Page
7.3 What Should Be Included in the Letter? 24.7-2
8 What is Really Involved in the Mail Out and Tracking Steps? 24.8-1
8.1 Preparation of the Mailing List 24.8-1
8.2 Prescreening 24.8-2
8.3 Preparation and Mailing 24.8-2
8.4 Tracking and Follow-up 24.8-3
9 I Got Responses - Now, What Do I Do With All of That Data? 24.9-1
10 References 24.10-1
VI EIIP Volume III
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FIGURES AND TABLES
Figure Page
24.1-1 Steps in the Surveying Process 24.1-2
Table Page
24.2-1 BARS Scores for Architectural Surface Coating Emissions Estimated by Two
Different Methods 24.2-4
24.5-1 Factors Impacting Sample Size 24.5-5
24.5-2 Types of Survey Sampling Methods 24.5-8
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1
INTRODUCTION
1.1 WHAT Is A SURVEY?
A survey is a method of gathering information from a number of individuals (a "sample") in
order to learn something about the larger population from which the sample has been drawn.
Surveys can be conducted using different tools and may have variety of purposes, but all surveys
have two characteristics in common:
• Information is collected from only a sample of the population; and
• Information is collected by means of standardized questions so that every
individual surveyed responds to exactly the same question(s).
The steps involved in the survey process are presented in Figure 24.1-1. Inventory preparers
often use survey questionnaires to gather point source emissions inventory data. Emission
inventories for area sources are usually not compiled using the same methods as emission
inventories for point sources. The level of effort required to collect data and estimate emissions
from the large number of individual facilities or activities would be very high, especially with
respect to the relatively low levels of pollutants emitted by each. To estimate emissions from
area sources, the individual facilities or activities are grouped with like facilities or activities
into broad source categories so that emissions can be collectively estimated using one
methodology. A survey approach can be used to gather information needed to calculate area
source emission estimates or used to develop region-specific emission factors for the
development of emission estimates.
1.2 How CAN THIS CHAPTER HELP ME?
This chapter is intended to help state and local air pollution control agency personnel determine
if a survey is needed as part of their area source emissions inventory development effort, and if
so, will assist them in planning and implementing each of the steps in the survey process.
1.3 How Is THIS CHAPTER ORGANIZED?
This chapter consists of 10 sections and presents information you can use to:
• Determine if you need to conduct a survey (see Section 2);
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Steps in the Surveying Process
1. Define the purpose. Be specific!
2. Determine if a survey is needed.
3. Define the population.
4. Develop the survey plan.
5. Develop survey questions.
6. Develop introduction and instructions.
7. Pretest instrument.
8. Edit and revise questionnaire.
9. Obtain approvals as required.
10. Di stribute the survey.
11. Follow-up as required.
12. Quality control/data reduction.
13. Analyze the data.
14. Compile the results.
Figure 24.1-1. Steps in the Surveying Process
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• Prepare a written plan for your survey effort (see Section 3);
• Choose the appropriate type of survey for your project (see Section 4);
• Select an appropriate sample for your survey (see Section 5);
• Identify the appropriate contacts (see Section 5);
• Design an effective survey document (see Section 6 and 7);
• Distribute and track the survey (see Section 8);
• Compile the data; and
• Conduct quality control/quality assurance (QA\QC) throughout the survey
process.
1.4 WHERE CAN I Go FOR ADDITIONAL INFORMATION?
While this document attempts to compile the information necessary to plan and conduct a
survey, you may wish to refer to more in-depth references for additional information on some
aspect the of the survey process. Section 10 of this chapter presents complete citations for all of
the references used to prepare this document. In addition, you can find valuable information in:
Babbie, E. (1990). Survey Research Methods. Belmont, CA: Wadsworth, Inc.
Braverman, M.T. & Slater, J.K. (Eds) (1996). Advances In Survey Research. New Directions
for Evaluation, 70. San Francisco, CA: Jossey-Bass.
Dillman, D. (2000). Mail and Internet Surveys: The Tailored Design Method. New York: John
Wiley & Sons.
Fink, A. (1998). How to Design Surveys. The Survey Kit No. 5. Thousand Oak, CA: Sage.
Fink, A. & Kosecoff, J. (1998). How to Conduct Surveys: A Step-by-Step Guide. Thousand
Oaks, CA: Sage.
Fowler, FJ. (1993). Survey Research Methods. Sage Applied Social Research Methods Series
Volume 1. Thousand Oaks, CA: Sage.
Kalton, G. (1983). Introduction to Survey Sampling. Sage Series on Quantitative Applications
in the Social Sciences, Volume 35. Thousand Oaks, CA: Sage.
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Litwin, M.S. (1995). How to Measure Survey Reliability and Validity. The Survey Kit No. 7.
Thousand Oaks, CA: Sage.
Oppenheim, A.N. (1992). Questionnaire Design, Interview ing and Attitude Measurement. New
York: Pinter Publishers.
Patton, M.L. (1998). Questionnaire Research. Los Angeles, CA: Pryczak Publishing.
Rea, L.M. & Parker, R.A. (1997). Designing and Conducting Survey Research: A
Comprehensive Guide. San Francisco, CA: Jossey-Bass.
Smith, M.L. & Glass, G.V. (1987). Research and Evaluation in Education and the Social
Sciences. Englewood Cliffs, NJ: Prentice-Hall.
Sudman, S. & Bradburn, N.M. (1982). Asking Questions: A Practical Guide to Questionnaire
Design. San Francisco, CA: Jossey-Bass.
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How Do I DETERMINE IF A SURVEY
Is NECESSARY?
In general, you should remember that any survey requires an extensive level of effort. The
decision to undertake a survey should be made only after you have considered all other
possibilities.
Surveys can be useful tools for collecting information from a large population—they can
provide data to make calculations or information on which to base decisions. Although surveys
can be expensive, difficult, or time-consuming, there are times when a survey is the most
appropriate tool to use to gather data. To determine if a survey is required as part of the data
collection effort for an area source emissions inventory for a specific category, you should:
• Assess your data needs;
• Evaluate the relative importance of the category to total emissions inventory;
• Evaluate your data quality objectives;
• Assess data availability;
• Evaluate resource availability;
* Consider the administrative clearances needed under federal or state rules to
conduct a survey of the private sector; and
• Consider if it is possible to coordinate the information collection activity with
other inventory efforts.
Each of these criteria is discussed in the following sections.
2.1 ASSESS YOUR DATA NEEDS
In order to determine if you must conduct a survey to collect the data needed for your area
source emission inventory effort, you must first develop a specific definition of what data are
required. The more specific you can make your definitions, the easier it will be to collect the
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appropriate data. The objectives of a survey can usually be phrased in the form of a question,
such as:
• Which control devices do autobody refinishers use?
• How much solvent do dry cleaning facilities purchase on an annual basis?
• How much wood do households burn per week in the winter?
Surveys may be used to collect qualitative information for the source category, but should be
designed to produce quantitative results—that is, results that can be expressed numerically and
can be used in rigorous data analysis.
For area source inventory purposes, keep in mind that the data collected from the sample will be
scaled up for the entire inventory region. Even if not specifically stated in the inventory
preparation plan, you will need to identify and collect reasonable surrogate data.
2.2 EVALUATE THE RELATIVE IMPORTANCE OF THE CATEGORY TO
YOUR TOTAL EMISSIONS INVENTORY PROGRAM
You should use existing inventory data and your knowledge of federal, state, and local
regulations to determine the importance of an individual emissions inventory project within the
scheme of the overall responsibilities of your agency.
Questions to ask include:
• Does the source category emit a large percentage of the pollutant(s) of interest?
Is the category a significant source of volatile organic compounds, hazardous air
pollutants (HAPs) nitrogen oxides, sulfur dioxide, carbon monoxide, particulate
matter, or ammonia?
• Is an accurate inventory of the pollutants of interest of particular importance to
your agency (e.g., PM-2.5, ozone precursors, specific HAPs)?
• What is the end use of the inventory? An inventory with significant regulatory
implications such as a residual risk study for HAP sources may require a survey
component for data collection, while an inventory for source characterization
may not.
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Inventory efforts identified as high priority should be afforded sufficient resources to ensure that
complete and accurate data are compiled. For many area sources, this data collection effort may
require a survey.
2.3 EVALUATE THE DATA QUALITY OBJECTIVES FOR THE INVENTORY
The first step in planning any inventory is to define the purpose and intended end use of the
inventory. This information is used to determine the data quality objectives (DQOs) and the
quality control/quality assurance (QA/QC) requirements for the inventory. DQOs are qualitative
and quantitative statements of the uncertainty that a decision maker is willing to accept in the
estimates and/or decisions made with inventory data. For a more complete discussion of DQOs,
refer to EIIP Volume VI, Chapter 2 (Documentation).
Preparation of a written DQO statement should be part of the initial planning stages of the
inventory process. The DQO statement should address:
• Accuracy (or uncertainty) of emission estimates;
• Completeness;
• Representativeness; and
• Comparability,
For inventory efforts with strict DQOs, it may be necessary to conduct a survey in order to
ensure that appropriate data are collected.
You can use the Data Attribute Rating System (DARS) to evaluate the merits of one emission
estimation method relative to another. DARS defines certain classifying attributes that are
believed to influence the accuracy, appropriateness, and reliability of an emission factor or
activity, and assigns a numerical score to each of these components that are combined to arrive
at an overall confidence rating—an uncertainty estimate—for the inventory. You can develop
DARS scores for several potential estimation methods and use this information when planning
your inventory. For example, the DARS scores for two alternative methods to estimate
emissions from the architectural surface coatings area source category are shown in
Table 24.2-2. One method is based on a survey of paint distributors, the second uses a national
per capita factor. The more resource-intensive survey method results in a much higher overall
DARS score. You can use this information when considering questions such as:
• How much better can an inventory get if a survey is used compared to other
methods?
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Draft 12/19/00
TABLE 24.2-1
DARS SCORES (UNITLESS) FOR ARCHITECTURAL SURFACE COATING
EMISSIONS ESTIMATED BY Two DIFFERENT METHODS
Attribute
Factor
Activity
Emissions
Local Survey
Measurement/Method
Source Specifity
Spatial
Temporal
Composite
0.7
1.0
1.0
1.0
0.925
0.9
1.0
1.0
1.0
0.975
0.63
1.00
1.00
1.00
0.908
National Per Capita Factor
Measurement/Method
Source Specifity
Spatial
Temporal
Composite
0.3
1.0
0.3
0.7
0.575
0.4
0.3
0.3
1.0
0.500
0.12
0.30
0.09
0.70
0.30
• Does this amount of improvement justify the additional cost?
You will need to balance the inventory quality objectives and the available resources in order to
formulate a workable strategy for your inventory. Refer to EIIP Volume VI (Chapter 4 and
Appendix F) for detailed discussions of DARS.
2.4 ASSESS DATA AVAILABILITY
Before taking on any data collection effort, survey or non-survey, you should always check to
see if the data have already been compiled. Each of the chapters in this volume suggest
references of information for the respective area source categories. In general, you should also
check for relevant data in:
24.2-4
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• Permit files or compliance files;
* Case studies and site visit reports;
• U.S. Department of Commerce publications including County Business Patterns,
Census of Population, Census of Manufacturers, Census of Agriculture, County
and City Data Book, Current Industrial Reports, Annual Housing Survey, and
Census of Retail Trade;
• U.S. Department of Energy publications such as State Energy Data Reports,
Natural Gas Annual, and Petroleum Marketing Annual;
• State Departments of Transportation and State Energy Offices (for information
on gasoline consumption and paving activities);
• State Departments of Labor (for employment data by SIC [Standard Industrial
Classification] code);
• Local industrial directories (these are often organized by SIC code and provide
employment data);
• Trade and professional association publications;
• Regional planning commission publications;
• Agency-sponsored surveys;
• National and state directories of manufacturers; and
• Data compiled by private research and development companies such as the
Directory of Chemical Producers compiled by SRI International.
2.5 EVALUATE RESOURCE AVAILABILITY
As with any task, the resources required to conduct a survey will be determined by the scope of
the project. You will need to evaluate your agency's ability to commit the appropriate
resources—both personnel and money—to ensure that the survey is designed and conducted
properly. Taking shortcuts can invalidate the results. The cost of a survey is a function of the
completeness and specificity of the questionnaire, the size of the target audience, and the
thoroughness of the QA/QC follow-up activities (Radian, 1996).
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The survey process consists of a series of steps including planning, sample design, sample
selection, contact identification, questionnaire preparation, pre-testing, mail-out, response
tracking, follow-up activities, data collection, data reduction, data processing, data extrapolation,
and QA/QC at each step. Each of these steps may require experience not readily available in an
emissions inventory agency. You may need to factor in the cost of additional personnel or
"learning curve" inefficiencies. Examples of resources required to conduct a survey include
(Ferber, et al., 1994):
• Managerial staff time for planning the study and supervision through the various
stages;
• Labor and material costs for design and pretest of the questionnaires;
• Computer hardware and software for data management;
• Telephone charges;
• Postage (surveys are often sent via registered mail);
* Reproduction and printing costs;
• Labor and materials cost for mail-out including compilation of up-to-date mailing
lists, production of labels and cover letters, stuffing envelopes;
• Labor cost for programming e-mail or Internet surveys; and
* Labor costs for tracking responses, including data logging and follow-up with
non-respondents.
You should recognize that allowing ample resources for quality checks at each step of the survey
process is critical to a well-designed and well-conducted survey project. Be sure to include the
cost of a rigorous QA/QC program when developing a project budget.
You must also consider the amount of time available to prepare the inventory. It may take
several months to conduct a survey and analyze the data. If an emissions estimate must be
prepared in 3 months and the survey process requires 6 months, you will need to use a non-
survey method, even if a survey would result in a more accurate estimate of emissions.
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2.6 CONSIDER THE ADMINISTRATIVE CLEARANCES
Before deciding to conduct a survey, you must identify any regulations that relate to the conduct
a survey of the private sector. Specifically:
• Federal - Under the Paperwork Reduction Act, any Federal Government entity
must obtain an approval from the Office of Management and Budget (OMB) to
collect substantially similar information from ten or more respondents in any
12 month period. If EPA decides to collect information, it must prepare an
Information Collection Request and submit it for OMB approval.
• Typically, the Director of the air quality regulatory agency has the authority to
request information. However, you should identify the procedures that apply to
your agency prior to planning and mailing the survey.
2.7 CONSIDER IF IT Is POSSIBLE TO COORDINATE THE INFORMATION
COLLECTION ACTIVITY WITH OTHER INVENTORY EFFORTS
Because survey efforts are time-consuming and expensive, you should consider the possibility of
coordinating your data collection efforts with other activities being conducted by your agency.
Surveys are frequently conducted by permitting groups. If another survey is being planned that
will include an appropriate population to collect the information that you require for your
emissions inventory estimate, it may be most efficient to work cooperatively to collect the
required information.
Two points must be carefully considered when making the decision to combine data collection
efforts:
• You must make certain that the surveyed population represents a sample that is
appropriate for all of the data collection efforts. Both the sample size and sample
representativeness must be evaluated for each the data collection efforts.
• You must design the survey with extreme care. Unless response to the survey is
mandatory, you will need to carefully balance the effort to collect information for
more than one project with the need to keep the survey short and simple. If the
questionnaire becomes too long or too confusing, recipients may not be willing to
complete and return the form.
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WHAT Is THE MOST IMPORTANT
ASPECT OF CONDUCTING A
SURVEY?
Simply put, the key to a successful survey effort is good planning.
Careful and thorough planning of survey procedures will greatly facilitate the process and can
prevent the need for costly revisions to the survey while in progress or emissions estimates that
are generated from the survey data. Before the inventory process begins, your agency should
prepare an inventory preparation plan to identify the required staffing levels and resource
allocations. The inventory preparation plan will also specify the methods and procedures to be
used by each member of the inventory team to collect, handle, review, and report emissions data.
Refer to the Handbook for Criteria Pollutant Inventory Development: A Beginner's Guide for
Point and Area Sources (EPA, 1999b) for additional information on inventory preparation plans.
While careful planning and survey design take time and may add front-end costs to the inventory
effort, you should keep in mind that good planning actually reduces overall costs by preventing:
• Time wasted by the repeated need to make short-term decisions on what to do
next;
• Duplication of data collection efforts;
• Time wasted collecting and analyzing irrelevant data; and
• Unplanned data analysis in the hope of finding relevant information in an
incomplete data set (GAO, 1991).
As part of the inventory preparation plan, as a stand-alone document, or as a series of
documents, you should prepare a written plan that covers every phase of the survey
process. The written plan should clearly identify the goals, methods, and resources required for
each step in the survey process. The written plan should:
• Define the data quality objectives;
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• Define the data to be collected;
• Determine appropriate sample size;
• Identify the sample selection technique;
* Identify the survey technique;
• Outline techniques for design, pilot test, and revision of the survey;
• Identify the mail out and tracking techniques;
• Identify the data entry procedures;
• Identify the statistical methods to be used in the data analysis; and
• Identify the QA/QC procedures to be conducted during all phases of the survey
process.
These survey procedures are discussed in the following sections.
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WHAT SURVEY TECHNIQUES ARE
AVAILABLE?
There are a variety of methods that can be used to collect survey data:
• Mail surveys;
• Electronic (E-mail or website) questionnaires;
• In-person interviews; and
• Telephone interviews.
The advantages and disadvantages of each method are described in the following sections. The
information below was summarized from several documents (Fink and Kosecoff, 1998; Creative
Research Systems, 2000; and Parker, 1999).
4.1 MAIL SURVEYS
Mail surveys, also referred to as "paper questionnaires", are documents mailed to the sample
population that include a cover letter, instructions, and a form for the recipient to complete and
return.
Advantages of the mail survey include:
• Mail surveys are one of the least expensive survey techniques. Unlike interview
techniques, you will not need a team of trained interviewers;
• Mail survey forms can contain graphics. Use of diagrams, photographs, and
tables is not possible with telephone interviews and may be limited with e-mail
survey forms;
• Unlike interview techniques, mail surveys allow the survey recipients to respond
when it is convenient for them. Mail surveys are considered less intrusive than
telephone or personal interviews;
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• This method gives survey recipients time to consider and research responses
increasing the accuracy and completeness of the responses; and
• There is no possibility for interviewer bias to influence the respondents.
Disadvantages of the mail survey include:
* Mail surveys require more time than other survey techniques. You may need to
wait for several weeks after mailing the questionnaires before you can assess your
response rate. It may take several more weeks to follow-up with
non-respondents;
• It may be difficult to obtain up-to-date and accurate mailing lists;
* Respondents may misinterpret or omit questions; and
• Mail surveys require motivated or interested respondents. Without legal
requirements or incentives, respondents may choose to ignore a survey form.
4.2 E-MAIL SURVEYS
E-mail surveys are documents electronically distributed to the sample population. These
messages include an introduction (similar to the cover letter of a paper survey), instructions, and
a form for the recipient to complete and return via e-mail. More people have e-mail than have
full Internet access, making e-mail a better choice than web page surveys for some populations.
Advantages of the e-mail survey include:
• E-mail surveys are one of the least expensive survey techniques. Because there
are not fees for mailing or costs for interviewers time, it does not cost more to
collect large samples;
• E-mail surveys can be fast. You can send the survey and receive responses in a
period of days;
• The novelty element and convenience of an e-mail survey might stimulate higher
levels of response than an ordinary paper survey;
• With many systems, you can attach picture and sound files; and
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• Like paper surveys, e-mail surveys allow recipients to respond at their
convenience and to carefully consider their responses.
Disadvantages of the e-mail survey include:
• It may be difficult or expensive to obtain up-to-date and accurate e-mail address
lists;
• The sample population is limited to those with e-mail access. You will need to
either acknowledge this when you identify the sample or be willing to distribute
paper surveys to those who do not have e-mail access;
• It can be difficult to track e-mail responses. It is not unusual for recipients to
forward the survey to multiple associates—or to respond more than once. It is
important that the size and the representativeness of the sample that the responses
be carefully monitored;
• Many people dislike unsolicited e-mail even more than unsolicited regular mail;
and
• Respondents may misinterpret or omit questions.
4.3 WEB PAGE SURVEYS
Surveys can be posted on Internet web pages. The web pages include an introduction (similar to
the cover letter of a paper survey), instructions, and a form for the recipient to complete and
submit.
Advantages of web page surveys include:
• Web page surveys can be extremely fast and reach a large population;
• Like e-mail surveys, it does not cost more to collect large samples;
• These surveys can be designed to be interactive. The programs can be designed
to provide respondents with explanations of terms or complex questions. Web
page questionnaires can use complex question skipping logic and
randomizations;
• The forms can be designed so that only "legal" answers are accepted, reducing
the resources required for QA/QC and follow-up;
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• Data in the submitted responses can be automatically entered into programs for
analysis; and
• Web page questionnaires can use colors, fonts, and formatting options not
available with an e-mail surveys.
Disadvantages of web page surveys include:
• The sample population is limited to those with Internet access. You will need to
either acknowledge this when you identify the sample or be willing to distribute
paper surveys to those who do not have Internet access;
• Depending on your software, you may have no control over who replies. This
issue can be addressed by posting the survey on a page that can only be addressed
directly (there are no links to it) or by restricting access by requiring a password;
and
• Constructing an Internet web page may require a software engineer or
programmer.
4.4 IN-PERSON AND TELEPHONE INTERVIEWS
In-person and telephone interviews are conducted by trained individuals who collect information
from individuals using a written script and prepared data forms.
Advantages of in-person and telephone interviews include:
• The interviewer can explore answers given by respondents or provide additional
information to ensure that the respondent understands each of the questions;
• The interviewer can prompt the respondent to prevent incomplete or
inappropriate responses;
Disadvantages of in-person and telephone interviews include:
• Conducting interviews is resource intensive. You will need to find up-to-date
phone numbers, schedule the interviews, ensure that all of the interviewers are
well trained, and supervise dispersed personnel performing a complex task; and
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This type of survey has the greatest possibility that the interviewer can influence
(bias) the results.
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How Do I DETERMINE How MANY
SURVEYS TO SEND - AND To WHOM?
5.1 WHAT ARE THE ADVANTAGES OF SAMPLING FROM THE ENTIRE
POPULATION?
A complete enumeration (or census) of the entire population may not be practical and is almost
never economical. Collecting data from a properly identified sample of the population requires
fewer resources than a census. You can use inferential statistics to determine a population's
characteristics by directly observing only a portion (or sample) of the population.
Additionally, a sample may be more accurate than a census. A poorly designed and/or poorly
conducted census can provide less reliable information than a carefully obtained sample.
Keep in mind that two things are absolutely necessary, however, to ensure a high level of
confidence that the sample represents the population:
• A sufficiently large sample; and
• An unbiased sample.
5.2 How Do I IDENTIFY THE POPULATION?
As a starting point, you need to be familiar with the following terms (Fridah, 1998):
• Population - a group of individual persons, objects, or items from which samples
are taken for measurement. For example, a "population" from an area source
inventory might be all dry cleaners.
• Sample - a finite part of a statistical population whose properties are studied to
gain information about the whole. For example, a "sample" for an area source
inventory might be 10 percent of the dry cleaners in the non-attainment counties
within a given state.
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• Sampling - the act, process, or technique of selecting a suitable sample, or a
representative part of a population for the purpose of determining parameters or
characteristics of the whole population
The first step in the survey process is to define the relevant population (Ferber et al., 1994).
This is particularly important for area source inventory efforts. Unlike surveys conducted for
point source inventories, the best recipient may not be at the point of emissions. For example,
an area source survey on solvent use could be sent to manufacturers, distributors, retailers,
users—or a combination of these groups. You will need to identify the appropriate
facilities/subcategories or point in production/use within the surveyed source category to serve
as the population.
To identify the appropriate population, you should carefully evaluate:
* The data requirements for the survey effort; and
• The practical considerations of surveys of the different potential populations. In
the solvent use example, it might be most practical to survey the manufacturers or
the distributors.
In order to identify the relevant population, you will need to compile a list of the names, address,
and general process category of each facility in the inventory area that could be included in the
survey. This list could be based on information resources including:
• Existing Inventories. A recent or recently updated, well-documented, existing
air emissions inventory is a good starting point. However, many existing
inventories may focus on pollutants other than those needed in the inventory
being prepared. Thus, certain sources that emit only one type of pollutant may
not be well represented.
• Other Inventories. In addition to emissions inventories, other environmental
inventories may be useful in identifying plants in various Standard Industrial
Classification (SIC) Codes. Information in the Toxic Release Inventory System
(TRIS), gathered annually under the "Community Right-to-Know" Law of the
Superfund Amendments and Reauthorization Act (SARA Title HI), and facility
inventories developed under Title V may be useful. The TRIS database gives
plant locations and SIC Codes, as well as quantitative information on emissions
of specific toxic chemicals including many solvents. Title V permits may
provide specific information about area source processes taking place at a
facility.
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In addition, listings of water pollution sources and hazardous waste generators are maintained by
state water pollution and hazardous waste agencies. These may be used to identify potential
sources in various SIC codes.
• Air Pollution Control Agency Files. Compliance, enforcement, permit
application, or other air pollution control agency files may provide valuable
information on the location and types of sources in the area of concern. These
files can also be used later to cross-check certain information supplied on
questionnaires.
• Other Government Agency Files. Files maintained by labor departments
and tax departments frequently aid in the preparation of the mailing list. Such
files will include various state industrial directories in which companies are listed
alphabetically by SIC code and county. The information available in these files
will vary from state to state. Thus, it is advisable to contact the appropriate
personnel with these agencies to become familiar with which listings are
available.
• Other Local Information Sources. The following local information sources
can be consulted, where available:
Local industrial directories—A local industrial development authority
may provide a current list of the sources that operate in the inventory area.
These are often organized by SIC code and provide employment data.
Yellow Pages—The local telephone directory will have names, addresses,
and telephone numbers of many industrial/commercial facilities that may
be emissions sources. However, telephone directory areas often do not
correspond to county or community boundaries.
Manufacturers and suppliers—Firms that make or supply equipment and
materials such as solvents, storage tanks, gasoline pumps, incinerators, or
emissions control equipment maybe used to identify industries emitting
VOCs, HAPs, CO, and nitrogen oxides.
• National Publications. The national publications listed below can be used
when available. However, the information in them may be older and less
accurate than local primary references.
Dun & Bradstreet, Million Dollar Directory and Middle Market Directory
compile lists of companies by SIC code and county (refer to
http://www.dnb.com);
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Dun & Bradstreet, Industrial Directory;
National Business Lists—Companies are listed by SIC Code and county
with information on financial strength and number of employees; and
Trade and professional society publications—Names and addresses of
members are listed along with their type of business.
5.3 How Do I DETERMINE THE SAMPLE SIZE?
The sample size is dependent on:
• The data quality objectives established for the accuracy of the results of the
survey project;
• Available resources;
• The nature of the analyses to be performed; and
• The degree of heterogeneity of the population.
Ideally, the sample size chosen for a survey should be based on how reliable the final estimates
must be. In practice, a trade-off is usually made between the ideal sample size and the expected
cost of the survey. You can get a general idea of the sample size needed for your survey project
from the checklist in Table 24.5-1.
Risk, as it relates to sample size determination, is specified by two interrelated factors:
• The confidence level; and
• The precision (or reliability) range.
To minimize risk, you should have a high confidence (say 95 percent) that the true value you
seek (the actual value in the population) lies somewhere within a small interval (say + or
- 5 percent) around your sample value (your precision). The desired degree of precision and
confidence level are established as part of the data quality objectives.
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TABLE 24.5-1
FACTORS IMPACTING SAMPLE SIZE
The calculations or decisions
to be made based on the
survey data have important or
costly consequences
The data quality objectives
for level of confidence are
high
The data quality objectives
for level of confidence are
low - only a rough estimate is
required
The population to be sampled
is relatively heterogeneous
(high level of variance)
The population to be sampled
is relatively homogeneous
(little variance)
Project costs increase
dramatically with sample size
Project costs and time
required vary only slightly
with increases in sample size
Financial and staffing
resources are limited
Time allowed for project
completion is limited
Large sample
/
/
/
/
Small Sample
/
/
/
/
/
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Basic statistics books present the formulas that you can use to determine sample size.
On-line calculators are available to determine sample size, for example:
• http://www.au.af.mil/au/hq/selc/samplsiz.htm
• http://www.surveysystem.com/sscalc.htm
Also, you should adjust the computed sample size (n) by dividing by the expected response rate.
For instance, if you determined that the appropriate sample size for your survey effort was 125
and you expect a 75 percent response rate, you should make your sample size equal 125/0.75 or
166.
If more sources are identified on the mailing list than can be realistically handled with available
resources, your agency should review the mailing list to reduce the number of facilities to be
sent questionnaires.
One way to reduce the size of the mailout is to develop an initial estimate of emissions by
facility. If the number of employees in a company is known, then an estimate of the emissions
potential can be made using available per-employee emission factors. This will provide a rough
estimate of the emissions potential of each facility, which can then be used to select a sample of
facilities that represent a range of emissions to receive the questionnaire. Any bias that this
selection process introduces to the returned surveys should be considered when scaling up the
survey results. Another way to reduce the size of the mailout is to contact the intended
recipients of the survey by telephone before mailing the survey. These brief contacts with plant
managers or other appropriate employees will indicate whether the pollutant-emitting process
takes place at the facility (or if the facility is even operating), and reduce the number of surveys
that are sent out unnecessarily.
5.4 How Do I SELECT THE SAMPLE?
Just as important as the size of the sample is the determination of the appropriate sampling
method. Random sampling always produces the smallest possible sampling error—the size of
the sampling error in a random sample is affected only by random chance. Because a random
sample contains the least amount of sampling error, it is referred to as an unbiased sample. Note
that this does not mean that the sample contains no error, but rather the minimum possible
amount of error.
Sampling techniques range from simple random selection of the population units to highly
complex samples involving multiple stages or levels of selection with stratification and/or
clustering of the units into various groupings. Whether simple or complex, a properly designed
sample always has two distinguishing characteristics:
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• All the units in the target population have a known, nonzero chance of being
included in the sample; and
• The sample design is described in sufficient detail to permit reasonably accurate
calculation of sampling errors.
These features make it scientifically valid to draw inferences from the sample results about the
entire population which the sample represents (Ferber et al., 1994).
The sampling method will be determined by the objectives of the survey effort. Table 24.5-2
lists some of the common sample selection techniques. The two most useful random sampling
techniques are simple random and stratified random sampling methods.
Stratified random sampling is often conducted for area source survey projects (Radian, 1996).
For example, most urban areas with a diversified economy contain numerous, small
manufacturing facilities that may use solvents in coating, degreasing, or wipe cleaning
operations. These facilities could include wood products manufacture and coating, plastics
coating, miscellaneous metal parts manufacture and coating. The large number of operations
and the differences in raw materials and production characteristics require that you develop a
survey approach to accurately collect information that can be statistically extrapolated to the
entire population of non-point source facilities. You could use a stratified random survey to
solve this problem:
• The first stratum might be to use source category codes such as the Area and
Mobile Source (AMS) Codes and the Source Classification Codes (SCC) to
group facilities manufacturing similar materials.
• A second stratum might be to use number of employees to distinguish between
larger and smaller facilities to account for different rates of material usage.
Stratified random sampling requires a detailed knowledge of the distribution of attributes or
characteristics of interest within the population to determine the homogeneous groups that
compose the population. A stratified random sample is superior to a simple random sample
because the population is divided into smaller homogeneous groups before sampling, resulting
in less variation the samples. This enables you to reach the desired degree of accuracy with a
smaller sample size. But, if you cannot accurately identify the homogeneous groups, you are
better off using the simple random sample because improper stratification can lead to serious
error.
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TABLE 24.5-2
TYPES OF SURVEY SAMPLING METHODS
I
rn
I
CD
Method
Haphazard sampling
Judgement sampling
Simple random sampling
Stratified random sampling
Description
"Any sampling location will do"
Take samples at convenient locations or times.
lead to biased estimates.
Can
Subjective selection by an individual. Select
samples that appear to be "representative" of
average conditions. Can lead to biased estimates.
Accuracy is difficult to measure.
Each population unit has an equal chance of being
selected for measurement. Selection of one unit
does not influence selection of other units.
The best way to choose a simple random sample is
to use a random number table or a computer-
generated series of random numbers. As the first
step, you assign each member of the population a
unique number. The members of the population
chosen for the sample will those whose numbers are
identical to the ones on the random number list in
succession until the desired sample size is reached.
Divide target population into non-overlapping parts.
If one group is proportionally larger than another,
its sample size should also be proportionally larger.
As appropriate, different sampling techniques can
be used in each of the different groups.
Conditions When the Sampling Design is Useful
A very homogeneous population over time and space is
essential if unbiased estimates of population parameters
are needed. This method of selection is not recommended
due to difficulty in verifying this assumption.
The target population should be clearly defined,
homogeneous, and completely assessable so that sample
selection bias is not a problem. Conversely, specific
samples are selected for their unique value and interest
rather than for making interferences to a wider population.
The simplest random sampling design. Other designs
below will frequently give more accurate estimates if the
population contains trends or patterns of emission rates.
Useful when a heterogeneous population can be broken
down into parts that are internally homogeneous. For
example, solvent usage might be stratified according to the
end product produced.
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(B
TABLE 24.5-2
(CONTINUED)
O
=t
I
to
l/i
Method
Multi-stage sampling
Cluster sampling
Systematic sampling
Double sampling
Description
Divide target population into primary units. Select
a set of primary units using simple random
sampling. Randomly subsample each of the
selected primary units. Example: collect soil
samples (primary units) at random, then select one
or more aliquots at random from each subsample.
Clusters of individual units chosen at random. All
units in chosen clusters are measured.
Samples are selected at intervals, locations, or times
according to a predetermined spatial or temporal
pattern. For example, assign each member of the
population a unique number, choose a random
number as a starting point and then survey every nth
member. This is a non-random sampling method!
Regardless of how much you mix the population
before selecting a starting point, the fact remains
that once that point is chosen, further selection of
members for the sample is non-random (no
independence).
If data using one measurement technique has a
strong linear relationship to data obtained with less
expense or effort using another measurement
technique, more samples can be taken using the less
expensive method. The linear relationship between
the two techniques is then applied to estimate the
mean for the more expensive method.
Conditions When the Sampling Design is Useful
Needed when measurements are made on subsamples of
the field sample. This technique has limited applicability
to emissions inventory development.
Useful when population units cluster together (schools of
fish, clumps of plants, etc.) and every unit in each
randomly selected cluster can be measured. This
technique has limited applicability to emission inventory
development.
Usually the method of choice when estimating trends or
patterns of emissions over space. Also useful for
estimating the mean when trends and patterns are not
present or they are known a priori or when strictly random
methods are impractical.
Useful when there is a strong linear relationship between
the variable of interest and a less expensive or more easily
measured variable.
O
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1/1
I
o
TABLE 24.5-2
(CONTINUED)
I
Method
Description
Conditions When the Sampling Design is Useful
Search sampling
Used to geographically locate pollution sources or
to find "hot spots" of elevated contamination.
Useful when historical information, site knowledge, or
prior samples indicate where the object of the search may
be found. This technique has limited applicability to
emissions inventory development. This approach,
however, could be used to develop information that would
describe the spatial characteristics of emissions in
relationship to a specific parameter (for example, lawn and
garden equipment use versus household income).
Source: Gilbert, 1987
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WHAT SHOULD I CONSIDER WHEN
PREPARING THE QUESTIONNAIRE
FORM?
You will need to develop a questionnaire specifically tailored for each source category you
survey. While this may require significant resources, it will allow you to use industry-specific
terminology and ask only relevant questions thus reducing confusion and increasing accuracy.
6.1 WHAT ARE THE MOST IMPORTANT ASPECTS OF PREPARING THE
QUESTIONNAIRE FORM?
Many factors are critical to designing a survey form that will result in a high response rate and
usable data. The most important points to keep in mind are:
• Make certain that you ask the right questions;
• Design the questionnaire for the person who will be asked to fill it out; and
• Be as brief as possible.
The goal is to design a survey that will provide you with accurate information that meets your
data needs. Chapters 2, 3, 4, 13, 14, and 17 of this volume all contain example survey forms.
6.2 WHERE Do I START?
As the first step in designing a survey, you must set the survey boundaries so that you can write
the correct questions. You need to have a specific definition of all of the information that the
survey is being developed to collect. This should be included in the inventory preparation plan.
Construct a list of potential questions and use the following criteria to determine which
questions should be included in the final survey:
• Does the question pertain to a stated survey goal? If a question is not necessary,
do not include it.
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• Place your questions into three groups: need to know, useful to know, and nice to
know. Discard the last group.
For area source inventory purposes, keep in mind that the data collected from the sample will be
scaled up for the entire inventory region. Even if not specifically stated in the inventory
preparation plan, you will need to identify and collect reasonable surrogate data.
6.3 WHAT SHOULD I CONSIDER FOR THE SURVEY FORMAT?
6.3.1 KEEP THE SURVEY BRIEF
Keep the survey as short and simple as possible—this is very important to both the response
rate and the accuracy of the responses. You should invest the resources to make the survey as
understandable, simple, and quick as possible for the recipient. Remember, they are doing you a
favor and you want to maintain a good agency-industry working relationship.
Carefully consider the physical size and format of the document. Again, keep the form as short
as possible. If you need only a few specific data items, consider a pre-printed, postage-paid
postcard.
While brevity is important, you should not design a survey that looks crowded or confusing.
Techniques for wise use of space on a page include:
• Using columns in the page layout;
• Using different fonts and bold text for emphasis;
• Defining sections and emphasizing key items using lines, boxes, or shading; and
• Printing double-sided pages.
6.3.2 DESIGN THE QUESTIONNAIRE TO FIT THE MEDIUM
You need to design the questionnaire to fit the medium. Each survey type (paper, e-mail, web
site, or interview) has advantages and limitations. For example, only some survey formats allow
you to incorporate graphics. Review the descriptions of each survey type presented in Section 4
of this chapter. Use the survey medium to its fullest potential.
6.3.3 CONSIDER ALL OF THE SURVEY "USERS"
You want to make the survey attractive and easy for the recipient to complete. However, there
are other people who will be working with the survey, and if you keep them in mind while
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designing the forms, you can save time and money. Once the survey is completed and returned,
it will go through several processes:
Log-in;
• QA/QC to check for completeness and reasonableness of responses; and
• Data entry.
Design the survey so that each of these processes can be conducted quickly and accurately
(Creative Research Systems, 2000):
• For questions requiring text answers, you should allow sufficient space for
handwritten answers. Lines should be about one half inch apart.
• Try to keep the answers in a straight line, either horizontal or vertical. Studies
show that the best place for answers is the right hand edge of the page.
6.3.4 MISCELLANEOUS TIPS
Other techniques that can improve response rate or the accuracy of the responses for your survey
include:
• Leave a space at the end of the questionnaire entitled "Other Comments". A
respondent might include a remark about an issue you had not even considered.
• Include the return address on each page of the survey. It is not unusual for return
envelopes and forms to get separated.
6.4 WHAT is MOST IMPORTANT FOR THE QUESTIONS?
You need to make sure that all of the questions are simple and well-worded. Keep in mind that
the way you phrase a question can change the answers you get.
6.4.1 OPEN-END AND CLOSED-END QUESTIONS
An open-end question is one that the recipients answer in their own words. In many area source
inventory surveys, you will be requesting that the recipient provide "fill in the blank"
information. When you write open-end questions:
• Be specific;
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• Clearly indicate the relevant time period for the requested data; and
• Clearly indicate the units of measure for the response.
A closed-end question lists the possible answers from which the respondents choose the
response appropriate for their facilities. When you write closed-end questions:
• Provide references or lists so that recipients use appropriate chemical trade
names, synonyms, Chemical Abstract Service (CAS) numbers, etc.;
• Make certain that you include all of the possible responses;
• Include a blank space for "Other" responses (just in case!); and
• Clearly indicate the relevant time period for the requested data.
6.4.2 "DON'T KNOW" OR "Noi APPLICABLE"
Include instructions for items that recipients do not want to, or cannot, answer. Allow a "Don't
Know" or "Not Applicable" response to all questions, except to those in which you are certain
that all respondents will have a clear answer.
While this may seem like an invitation for incomplete survey forms, it actually makes the
QA/QC review of the returned surveys much simpler. Without "Don't Know" or "Not
Applicable" as response choices, the respondent may simply skip the question. This requires
either follow-up by the inventory staffer a decision by the QA/QC and data analysis groups on
how to enter and analyze the data.
6.4.3 MISCELLANEOUS TIPS
Other techniques that can improve response rate or the accuracy of the responses for your survey
include:
• Use industry-appropriate terminology.
• Define all acronyms the first time you use them.
• Each question should be self-explanatory or accompanied by clear directions.
• Make certain that each question addresses only one issue. Ask separate questions
rather than try to collect multiple data points with one question.
• Clearly identify the time period (months, year) you need data for.
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• Consider asking for the raw data. That way you'll know how values were
calculated and will be able to perform QA/QC checks.
6.5 INSTRUCTIONS
Prepare a set of procedures and instructions to accompany the survey. The instructions should
clearly and completely (yet briefly):
• Explain, in general terms, how to fill out the questionnaire;
• Provide specific directions for how to complete each type of question;
• Tell the recipient the date the survey should be returned to the agency; and
• Provide names and contact information for agency personnel who can provide
technical assistance with survey issues.
6.6 PILOT TESTING
The purpose of pilot testing is to see how well your cover letter motivates your respondents and
how clear your instructions, questions, and answers are. You should always have the survey
reviewed by peer reviewers within your agency (experts) and a focus group from the appropriate
industry. Pilot testing takes time and may be expensive, but it is best to identify areas for
improvement before the survey is distributed. Once the survey has been sent out, changing the
directions, questions, or potential responses is no longer an option.
After explaining the purpose of the pilot test, let the peer reviewers read and answer the
questions without interruption. When they are through, ask them to critique the cover letter,
instructions, and each of the questions and answers. Rigorous pilot testing:
• Reveals whether people understand the directions;
• Reveals whether people can answer each of the questions;
• Helps you confirm that you are using the appropriate industry-specific
terminology;
* Tells you how long it takes to complete the survey;
Use the reviewers' recommendations and comments to finalize your survey document.
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WHAT SHOULD I CONSIDER WHEN
PREPARING THE COVER LETTER?
The cover letter is key to a successful survey effort. If the cover letter does not command
attention, the attached questionnaire might be not be considered a priority and it may be filed
away or discarded.
Start with an introduction or welcome message. In the case of mail questionnaires, this message
can be in a cover letter or on the questionnaire form itself. If you are sending e-mails that ask
people to take a web page survey, put your main introduction or welcome message in the e-mail.
State who you are and why you want the information in the survey. A good introduction or
welcome message will encourage people to complete your questionnaire.
7.1 WHO SHOULD SEND THE LETTER?
Whenever possible, survey forms should be sent by the state or local air pollution control
agency. Most of the surveys conducted to collect information required to compile an area source
inventory are voluntary—recipients are not legally required to respond. Recipients are more
likely to respond to a survey from a state agency than to a request from a contractor.
If you send the survey cover letters on state or local air pollution control agency letterhead and
have them signed by a government official, you may have a positive influence on the response
rate.
7.2 WHO SHOULD RECEIVE THE LETTER?
There are two possible strategies for the distribution of survey forms: approaching the facilities
directly, or dealing with trade associations and requesting that they collect the information from
their members.
If you choose to send surveys directly to facilities, your effort will be more successful if you
have specific contact names. If it is not feasible or economical to compile contact information,
determine an appropriate job title and clearly mark the outer envelope (e.g., "Attention: Plant
Manager") to direct the survey to the proper supervisory personnel.
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A trade association that supports the inventory effort can be a valuable ally in a data collection
effort. These groups are used to working with government agencies and may have access to
contact information that is not publicly available. Facilities may be more comfortable sharing
information with a trade group than sending it to a government agency. However, keep in mind
that if you adopt this strategy, you may lose control over the techniques used to choose the
sample from the population. If the size and composition of the sample are critical to the survey
study design, this strategy may not be appropriate.
7.3 WHAT SHOULD BE INCLUDED IN THE LETTER?
The cover letter should be as short and direct as possible. A strong statement about any existing
and applicable regulations which require the recipient to respond is your most powerful tool for
maximizing return rate. If response to your survey is not a legal requirement, you should
include a statement explaining the potential benefit of the survey effort to individual facilities
and the industry as a whole. Explain why the survey is important to your agency and your state.
Another important item to include in the cover letter is the response due date. To improve the
return rate, you should present the final due date in the cover letter so that it will not be
overlooked by the recipients who do not read the instructions. Provide a reasonable amount of
time for recipients to complete the survey—but not so much that they set it aside to do it later
and then forget it.
You should clearly state that all Confidential Business Information (CBI) will be handled
appropriately. In addition, you should provide names and contact information for agency
personnel who can provide technical assistance with survey issues.
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8
WHAT is REALLY INVOLVED IN THE
MAIL OUT AND TRACKING STEPS?
The process of mailing and tracking the survey includes:
• Preparing the mailing list;
• Pre-screening;
• Assembling survey packets;
• Mailing the survey packets;
• Tracking responses; and
• Following-up with non-respondents and incomplete responses.
8.1 PREPARATION OF THE MAILING LIST
The first step in the survey distribution process is to compile a mailing list that tabulates the
name and address of each facility to be surveyed. Assign each facility a unique identification
code. Whenever possible, identify a specific individual at each facility. You should have
collected most of this information while conducting research to identify the relevant population.
Refer to Section 5.2 of this chapter for a list of potential data sources.
Invest the time and effort to ensure that the appropriate facility and contact information has been
identified. Check and double check addresses—it will save you lots of time in the long run if
you don't have to deal with lots of returned survey packages.
You can greatly increase the efficiency and accuracy of the survey process if you use a database
or spreadsheet program to construct your mailing list. A well-designed database can be used to
generate mailing forms, create identification labels for each form, track survey returns, and
format data for analysis and reporting. This type of tool will enable you to enter facility-specific
information only once, rather than repeating data entry at several steps of the survey process.
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8.2 PRESCREENING
You can improve the response rate by contacting the survey recipients before you send out the
survey forms. Prescreening can be used to:
• Collect information (does the process of interest occur at the facility?) to help
limit the number of surveys that are sent to inappropriate facilities;
• Confirm mailing addresses and ensure that appropriate contacts have been
identified; and
• Inform the recipients about the upcoming survey project and foster support for
the effort.
8.3 PREPARATION AND MAILING
The survey package will include the envelope; cover letter; survey form; and a pre-addressed,
postage-paid return envelope.
To expedite tracking and data processing procedures, print duplicate mailing labels and place
one on the outer envelope and the second one on the survey form. This will ensure that the
proper identification code is on the returned survey. Mailing labels should contain the following
information:
• SIC code (if applicable);
• Unique identification number;
• Contact name (or appropriate job title if a specific contact has not been
identified);
• Contact title;
• Facility name;
• Street address;
City;
• County;
• State; and
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• Zip code.
If you were not able to identify specific contact information for a facility, determine an
appropriate job title and clearly mark the outer envelope (e.g., "Attention: Plant Manager") to
direct the survey to the proper supervisory personnel.
Your agency will need to carefully consider whether to send the surveys via first class or
registered mail. With registered mail, the sending agency is informed when a questionnaire is
received. Registered mail is more expensive and labor-intensive, but it does positively impact
the response rate—simply because the recipient knows that the agency knows that the survey
was delivered. Whether to spend money on registered mail depends on the importance of high
response rate of success of the survey project. As an alternative, you might consider using
registered mail for the largest or "most important" sources.
8.4 TRACKING AND FOLLOW-UP
Responses can begin arriving within a few days after mailing. The majority of the early returns
will be from companies that are not sources of the emissions being studied and questionnaires
returned by the postal service as undeliverable.
The following records must be kept for every survey form that you send:
• Facility information—all of the information included on the mailing label;
• Date mailed;
• Date returned;
• Whether follow-up is required; and
• Status of follow-up effort.
Follow-up will be required if the survey is returned by the postal service; the facility receives the
survey but does not respond; or if the response is inadequate.
For all surveys "Returned to Sender", you will need to conduct research to find up-to-date
information and re-send as appropriate. Log in corrected addresses, contact information, date
mailed, and date returned for all surveys re-sent.
Approximately 2 weeks before the survey response deadline, you should begin to contact the
facilities that have not responded. If the number of non-respondents is small, you can collect the
information through telephone contacts or plant visits. If a facility refuses to complete the
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survey, your agency might take legal action (if appropriate) to force a response; or you will need
to follow the data handling procedures for non-responses outlined in the QA/QC plan.
Returned surveys will be checked by the QA/QC staff to ensure that the information on each
form is complete and reasonable. If the data are determined to be inadequate, your agency will
need to re-contact the surveyed facility. Telephone calls or plant visits are the most efficient
means to collect the complete or revised information. Direct contact will provide your agency
with the opportunity to clarify any misunderstood questions and assist the facilities to complete
the survey form.
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I GOT RESPONSES - Now, WHAT Do
I Do WITH ALL OF THAT DATA?
As survey responses are received, they are logged in and put through an initial data check to
determine if responses are complete and the data are reasonable. The QA/QC procedures and
criteria for this check should be presented in the inventory preparation plan. As described in
Section 4 of this chapter, you will need to follow-up with facilities that do not respond or that
submitted inadequate data.
Following the initial QA/QC check and any required follow-up, your data entry team can input
the information into the appropriate data files. Consider designing look-up tables or pull-down
menus in the data entry programs to define and fill in permissible entries—this is particularly
helpful when the data entry involves lots of chemical names.
Your QA/QC staff will then review the entered data as required by the QA/QC procedures and
criteria to verify the accuracy of the data entry. You can also use automated computerized
checks to:
• Ensure against entering inappropriate data in a field—for example characters
where numbers are expected;
• Conduct range checks to confirm that values are within a specified minimum and
maximum for a specific variable; and
• Highlight outliers or suspect data.
Refer to Volume VI of the EIIP series, Quality Assurance Procedures., for additional
information on QA/QC of data entry and analysis.
You will need to address any outliers identified in the data set by using apply programming
solutions, statistical techniques, or your knowledge of the sources and processes. These
procedures should be defined in the inventory preparation plan.
A properly designed area source survey will collect the necessary data and include a mechanism
for "scaling up" the survey results. By the nature of area sources, it may not be possible to
survey the entire population of a source category. The method extrapolating from a sample to
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the population will depend on the type of source that is covered by the survey effort. Refer to
the source-specific chapters in this volume for additional information.
A suggested method on how to scale up your survey results can best be illustrated using an
industrial source category example. You conduct a survey of facilities reporting under SIC
code 2711, Newspapers. In the county of interest, a publicly available business database shows
150 facilities in this SCC code. You randomly select 25 facilities and mail surveys:
• 5 do not respond; and
• 20 respond.
2 are listed under wrong SIC codes;
14 are listed under correct SIC codes, and complete the survey; and
4 are listed under correct SIC code, but do not complete the survey
adequately.
So, out of the 150 facilities in this SCC code:
• You know nothing about 20% (the non-respondent facilities);
• You know something about the respondent 80%:
8% report under the wrong SIC code;
56% you can develop emission estimates for; and
16% you can NOT develop emission estimates for.
Thus, your sample data can be extrapolated to 72% (108 facilities) of the total population
reporting under that SIC code. Emission estimates can also be extrapolated to the unknown
20% by assuming that 8% of these facilities report under the wrong SIC code, and 92%
(27 additional facilities) report under the correct SIC code.
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10
REFERENCES
Creative Research Systems. 2000. The Survey System Tutorial: Survey Design.
http://www.surveysystem.com/sdesign.htm
EIIP. 1997. Evaluating the Uncertainty of Emission Estimates. In: EJIP Volume VI, Quality
Assurance Procedures. U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, EPA-454/R-97-004f. Research Triangle Park, North Carolina.
EPA. 1999a. Emissions Inventory Guidance for Implementation of Ozone and P articulate
Matter National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards, EPA-454/R-
99-006. Research Triangle Park, North Carolina.
EPA. 1999b. Handbook for Criteria Pollutant Inventory Development: A Beginner's Guide for
Point and Area Sources. U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, EPA-454/R-99-037. Research Triangle Park, North Carolina.
Ferber, R., P. Sheatsley, A. Turner, and J. Waksberg. 1994. What Is A Survey? Subcommittee
of the Section on Survey Research Methods. American Statistical Association Washington,
D.C. http://asio.jde.aca.mmu.ac.uk/resdesgn/survey3.htm
Fink, A. and J. Kosecoff. 1998. How To Conduct Surveys: A Step-By-Step Guide. Sage
Publications, Thousand Oaks, CA.
Fridah, M.W. 1998. Sampling In Research. Cornell University.
http://trochim.human.cornell.edu/tutorial/Mugo/TUTORIAL.HTM
GAO, 1991. Designing Evaluations. U.S. General Accounting Office, Program Evaluation and
Methodology Division, GAO/PEMD-10.1.4.
Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring. VanNostrand
Reinhold Company, New York.
Parker, R. 1999. Survey Research: Sampling and Design (Part of a course in Planning
Analysis). http://darkwing.uoregon.edu/~rgp/PPPM613/classl 1 .htm
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Radian International, LLC. 1996. Mexico Emissions Inventory Program Manuals. Volume IE:
Basic Emission Estimating Techniques. Prepared for the Western Governors' Association and
the Binational Advisory Committee. Radian International, LLC., Sacremento, CA.
U.S. Air Force. 1996. Air University Sampling and Surveying Handbook. United States Air
Force, Air University. Maxwell AFB, AL 36112-6335.
http://www.au.af.mil/au/hq/selc/smplntro.htm
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