INTRODUCTION TO AREA SOURCE

EMISSION INVENTORY

DEVELOPMENT





 	



   

 

  



 
	 
 
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.
EIIP Volume III

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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EIIP Volume III v

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
vi EIIP Volume III

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
EIIP Volume III vii

FIGURES AND TABLES

Figures Page

1.2-1 Communication and Information Sharing During Inventory Preparation . . . 1.2-2

1.3-1 Example Decision Tree for Choosing an Estimation Methodology ....... 1.3-4

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
viii EIIP Volume III

ABBREVIATIONS AND ACRONYMS 

ABBREVIATIONS

ACT Alternative Control Techniques

AFS AIRS Facility Subsystem

AIRS Aerometric Information Retrieval System

AMS AIRS Area and Mobile Subsystem

BEA 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
EIIP Volume III ix

ABBREVIATIONS AND ACRONYMS

(CONTINUED)

ORD Office of Research and Development

PM particulate 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

SAF seasonal activity factor

SAMS SIP air pollutant inventory management system

SARA Superfund Amendments and Reauthorization Act

SCC source classification code

SIC standard industrial classification

SIMS 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

USDA 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 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.

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 III, Area Sources, are to: 

 Establish standard procedures for the preparation of area source emission

inventories; 
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1.1-2 EIIP Volume III

 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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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 III 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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1.1-4 EIIP Volume III

 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.
EIIP Volume III 1.2-1

2

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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FIGURE 1.2-1. COMMUNICATION AND INFORMATION SHARING 

 DURING INVENTORY PREPARATION
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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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1.2-4 EIIP Volume III

 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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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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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  
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TABLE 1.2-1

(CONTINUED)

Category (Tier 1 Code) PM VOC NOx CO HAPs NH3

TSDFs  

Other  

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 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. 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 = Particulate matter

VOC = Volatile organic compounds

NOx = Nitrogen oxides

CO = Carbon monoxide

HAP = Hazardous air pollutant

NH3 = Ammonia
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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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EIIP Volume III 1.2-9

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 lowerquality 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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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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 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. 
EIIP Volume III 1.3-1

3

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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1.3-2 EIIP Volume III

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 highdensity 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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FIGURE 1.3-1. EXAMPLE DECISION TREE FOR CHOOSING AN 

ESTIMATION METHODOLOGY
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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.
1

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EIIP Volume III 1.3-7 TABLE 1.3-1 EMISSION ESTIMATION MODELS USEFUL FOR AREA SOURCES Model Name Description/Features Contact/Reference CHEMDAT8  Estimates VOC emissions from TSDF processes.  Lotus 1-2-3® spreadsheet.  Default input parameters provided to demonstrate calculations. Elaine Manning, EPA Emissions Standards Division, (919) 541-5499 WATER8  Estimates emissions from wastewater treatment systems.  Menu-driven computer program. Elaine Manning, EPA Emissions Standards Division, (919) 541-5499 Landfill Air Emissions Estimation Model (LAEEM)  Estimates HAP, VOC, methane, and CO2 emissions from a landfill.  Computer model.  Site-specific data can be entered; defaults (conservative) provided. Susan Thorneloe-Howard, EPA Air Pollution Prevention and Control Division, (919) 541-2709 TANKS, version 2.0  Estimates organic chemical emissions from storage tanks.  Variety of tank types included.  User enters site-specific data; defaults provided.  Computer model. Info CHIEF (MD-14) United States Environmental Protection Agency Research Triangle Park, NC 27711, MECHANICAL  Estimates fugitive PM emissions from roads, materials handling, agricultural billing, and construction/demolition. Control of Open Fugitive Dust Sources, EPA-450/388-008 WIND  Estimates PM emissions from wind erosion. Control of Open Fugitive Dust Sources, EPA-450/388-008
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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 as AP-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 MOBILE5a 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 in 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: 

(1.31)

New emission factor

Old emission factor

Current amount of solvent used in the p rocess

O ld am ount of solvent used in the p rocess =

3.4.4 EMISSION FACTOR CALCULATIONS

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:

Emissions = (1.3-2)

Activity

Level * 

Uncontrolled

Emission

Factor
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4

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 CONTRIBUTIONSa

Process Category Examples

AMS Source

Category Codes

Fuel Combustion

Electric Utilities 21-01-

Industrial Fuel Combustion 21-02-

Industrial Processes

Chemicals and Allied Products 23-01-

Metals Production 23-03-

23-04-

Rubber and Plastics 23-08-

Oil and Gas Production 23-10-

Mineral Processes, Mining and

Quarrying

23-25-

Construction/Demolition 23-11-

Machinery 23-12-

Petroleum Refining 23-06

Solvent Utilization

Graphic Arts 24-25-

Surface Coating 24-01-

Dry Cleaning 24-20-

Degreasing 24-15-
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TABLE 1.4-1

(CONTINUED)

Process Category Examples AMS Source

Category Codes

Storage and Transport

Petroleum and Petroleum Product

Storage and Transport

25-01-

25-05-

Organic Chemical Storage and

Transport

25-10-

25-15-

Inorganic Chemical Storage and 

Transport

25-10-

25-15-

Rail and Tank Car Cleaning 25-**-***-900

Waste Disposal, Treatment and Recovery

Commercial and Industrial

Incineration

26-01-

Industrial and Municipal Open

Burning

26-10-

Wastewater Treatment 26-30-

TSDFs 26-40-

Scrap and Waste Materials 26-50-

Landfills 26-20-

Miscellaneous Sources

Cooling Towers 28-20-

Health Services 28-50-

Firefighting Training 28-10-035-

Engine Testing 28-10-040-

a 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.
CHAPTER 1 - INTRODUCTION 1/31/01

 a See the most recent publication, which can be obtained from the U.S. Bureau of Census,

Department of Commerce, Washington, D.C.

1.4-4 EIIP Volume III

UAEA 

Total

Uncontrolled

Emissions



Uncontrolled

Point Source

Emissions

(1.4-2)

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.

a

 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:
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-5

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:
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-6 EIIP Volume III

Rule Penetration 

Uncontrolled Emissions

Covered by Regulation

Total Uncontrolled Emissions

100 (1.4-3)

 Assume an 80 percent default value for all sources;

 Perform a survey (with EPA approval for SIP inventories) to determine a sourcespecific 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:

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;
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-7

CAEA  (EFA)(Q) [(1  (CE)(RP)(RE)] (1.4-4)

CAEA  (UAEA) [(1  (CE)(RP)(RE)] (1.4-5)

 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:

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:

where:

UAEA = Uncontrolled area estimate of pollutant A
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-8 EIIP Volume III

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 Example Sources

VOC content control device by regulation Architectural Surface Coating

Industrial Surface Coating 

Autobody Refinishing

Commercial/Consumer Solvent Use

Emulsified Asphalt Paving

Activity is banned Cutback Asphalt Paving

Open Burning

Controls reduce consumption, not emission rate Degreasing (Surface Cleaning)

Emission factor based on control device emissions 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. 
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-9

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 in AP-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
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-10 EIIP Volume III

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 (SAF) 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 SAF 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 SAF 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 SAF (0.33) would be as shown

in Equation 1.4-6:

AEVOC,O = 0.33 * 2,000 tons VOCs (1.4-6)

= 666 tons VOCs
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-11

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 Activity

Days Per

Ozone CO Week

Gasoline Service Stations

Tank Trucks in Transit Seasonal variations in throughput vary

from region to region. Use average

temperature for a summer day where

appropriate.

6

Tank Truck Unloading 

(Stage I)

6

Vehicle Fueling (Stage II) 7

Storage Tank Breathing

Losses

7

Solvent Usage

Degreasing 0.25 6

Dry Cleaning 0.25 5

Surface Coatings

 Architectural 0.33 7

 Auto Refinishing 0.25 5

 Other Small Industrial 0.25 5

Graphic Arts 0.25 5

Cutback Asphalt Refer to local regulations and practices

Pesticides 0.33 6

Commercial/Consumer 0.25 7

Waste Management Practices

POTWs 0.35 7
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-12 EIIP Volume III

TABLE 1.4-3

(CONTINUED)

Area

Source

Seasonal Activity Factors Activity

Days Per Ozone CO Week

 Hazardous Waste TSDFs 0.30 7

 Municipal Landfills 0.25 7

Stationary Source Fossil Fuel Use

 Residential 0.08 0.43 7

 Commercial/Institutional 0.15 0.35 6

 Industrial 0.25 0.25 6

Solid Waste Disposal

 On-site Incineration 0.25 0.25 7

 Open Burning Refer to local

regulations and

practices

Refer to local

regulations and

practices

7

Structural Fires 0.20 0.33 7

Field/Slash/Prescribed Burning Refer to local

regulations

0.10 7

Wildfires Refer to local fire

conditions

0.05 7
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-13

Typical Seasonal

Emissions

per day



Emissions

per season

Operating

days/week

Operating

weeks/season

(1.4-10)

where:

AEVOC,O = 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:

AEVOC,O = 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:

AEVOC,O = 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:

Typical Annual

Emissions

per day



Emissions

per year

Operating

days/week

Operating

weeks/year

(1.4-9)

For sources that require a seasonal adjustment, seasonal daily emission estimates can be

calculated as in Equation 1.4-10:

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

SAF = 0.28 (28 percent)

Peak Ozone Season = 0.25 (25 percent or 3 months)

Operating Schedule = 6 days per week, 52 weeks per year
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-14 EIIP Volume III

Typical Ozone

Season Daily

Emissions



1.3 tons

year

2,000 lb

ton

0.28

0.25

(6 days/week) (52 weeks/year)  9.3 lb VOCs per day (1.4-11)

SAF  Peak Period Activity

Annual Activity

Months of Inventory Season

Months of Peak Activity (1.4-12)

Table 1.4-3 shows default SAF 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 SAF, 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 SAF 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:

This SAF 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 SAF 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,
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-15

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;
CHAPTER 1 - INTRODUCTION 1/31/01

 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.

1.4-16 EIIP Volume III

 Waste-to-energy data;a

 Business Statistics;

b

 Employment and Earnings;

c

 and

 Commodity Research Bureau Year Book.

d

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
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-17

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
CHAPTER 1 - INTRODUCTION 1/31/01

 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.

1.4-18 EIIP Volume III

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 
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-19

 Example 1.4-1

EXAMPLE SPATIAL ALLOCATION SURROGATE INDICATORS FOR SELECTED 

AREA SOURCE CATEGORIES

Emissions Category Surrogate Indicators

Residential fuel combustion Housing

Commercial/institutional fuel combustion Urban land use

Industrial fuel combustion Urban land use

Gasoline marketed Population, VMT

Unpaved roads County area, land use

Unpaved airstrips County area, airport location

Forest wildfires Composite forest

Managed burning--prescribed Composite forest

Agricultural operations Agricultural land use

Structural fires Housing

Degreasing Population, employment

Dry cleaning Population, employment

Graphic arts/printing Population, employment

Rubber and plastic manufacturing Population, employment

Architectural coating Population, employment

Auto body repair Population, employment

Motor vehicle manufacturing Population, employment

Paper coating Population, employment

Fabricated metals Population, employment

Machinery manufacturing Population, employment
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-20 EIIP Volume III

 Example 1.4-1

(CONTINUED)

Emissions Category Surrogate Indicators

Furniture manufacturing Population, employment

Flat wood products Population, employment

Other transportation equipment manufacturing Population, employment

Electrical equipment manufacturing Population, employment

Ship building and repair Water proximity, employment

Miscellaneous industrial manufacturing Population, employment

Miscellaneous solvent use Population, employment

Publicly owned treatment works (POTWs) Population, employment

Cutback asphalt paving operation Population, VMT

Fugitive emissions from synthetic organic chemical 

manufacturing 

County area, employment

Bulk terminal and bulk plants Population, employment

Fugitive emissions from petroleum refinery operations Population, employment

Process emissions from bakeries Population, employment

Process emissions from pharmaceutical 

manufacturing

Population, employment

Process emissions from synthetic fibers 

manufacturing

Population, employment

Crude oil and natural gas production fields Population, employment

Hazardous waste treatment, storage, and disposal facilities

(TSDFs)

Population, land use
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-21

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
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-22 EIIP Volume III

 Example 1.4-2

EXAMPLE GROWTH INDICATORS FOR PROJECTING EMISSIONS

FOR AREA SOURCES

Source Growth Indicators Information Sources

Gasoline marketing Projected gasoline consumption MOBILE fuel

consumption model

Dry cleaning Population: retail service

employment

Solvent suppliers; trade

associations

Degreasing (Cold cleaning) Industrial employment Trade associations

Architectural refinishing Population or residential

dwelling units

Local MPO

Automobile refinishing Industrial employment BEA

Small industrial surface coating Industrial employment BEA

Graphic arts Population State planning agencies;

local MPO

Asphalt use: Paving Consult industry Consult state DOT and

industry

Asphalt use: Roofing Industrial employment;

construction employment

Local industry

representatives

Pesticide applications Historical trends in agricultural

operations

State department of

agriculture; local MPO

Commercial/Consumer solvent use Population Local MPO; state planning

agencies

POTWs Site-specific information State planning

agencies

Hazardous waste TSDFs State planning forecasts State planning

agencies: local MPO

Municipal solid waste landfills State Waste Disposal Plan Local MPO; state planning

agencies
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.4-23

 Example 1.4-2

(CONTINUED)

Source Growth Indicators Information Sources

Commercial/Industrial fuel

combustion

Commercial/Institutional

employment; population

Local MPO; land use

projections

Industrial fuel combustion Industrial employment (SIC

Code 10-14, 50-51); or

industrial land use

Local MPO; land use

projections; state planning

agencies

Construction equipment Industry growth (SIC 

Code 16)

Local MPO

On-site incineration Based on information

gathered from local regulatory

agencies

Local agencies; state

planning agencies; local

MPO

Fires: Managed burning

agricultural field burning, frost

control (Orchard heaters)

Areas where these activities

occur

U.S. Forest Service, state

agricultural extension office

Forest wildfires Historical average Local, state, and federal

forest management officials

Structural fires Population Local MPO; state planning

agencies
CHAPTER 1 - INTRODUCTION 1/31/01

1.4-24 EIIP Volume III

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.
EIIP Volume III 1.5-1

5

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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1.5-2 EIIP Volume III

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. 
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.5-3

TABLE 1.5-1

ACTIVITY 

DATA 

EXAMPLE 

SOURCES FOR AN 

OZONE NVENTORY I

Area Source Category Estimation Procedure Activity Data Source of Activity Data

Commercial/Consumer Solvent Use Per capita Population U.S. Census dataArchitectural Surface Coating Survey Gallons of paint Paint manufacturersGasoline Distribution Gasoline consumption Gallons of gasoline State Department of

Transportation (DOT), StateEnergy Office

Industrial Surface Coating Per employee Employment by SIC State Labor DepartmentSurface Cleaning Operations Per employee Employment by SIC State Labor DepartmentDry Cleaning Operations per employee Employment by SIC State Labor DepartmentAutomobile Refinishing Per capita Population U.S. Census dataGraphic Arts Facilities Per employee Employment by SIC U.S. Census dataAsphalt Paving Consumption Barrels of asphalt State DOT, paving contractorsTraffic Paints Consumption Gallons of paint State DOTAgricultural Pesticides Application Application rate, acres of

crops

Crop type by acre, typesof pesticides

State Agriculture Office, U.S.Department of Agriculture(USDA)

Commercial Bakeries Per capita Population U.S. Census data
CHAPTER 1 - INTRODUCTION 1/31/01

1.5-4 EIIP Volume III

TABLE 1.5-1

(CONTINUED)

Area Source Category Estimation Procedure Activity Data Source of Activity Data

Structure Fires Per fire Number of fires Fire marshallMunicipal Landfills Statistical models Tons of refuse,

landfill age

State Solid Waste Management Agency

Residential Fuel Combustion Fuel use Amount of fuel

used

State Energy Office, Energy Information Administration (EIA)

Industrial Fuel Combustion Fuel use Amount of fuel

used

State Energy Office, EIA

Commercial/Institutional FuelCombustion

Fuel use Amount of fuel used State Energy Office, EIA

Petroleum Vessel Loading/Unloading Petroleum products

loaded/unloaded

Gallons of fuel Port Authority, Waterborne

Commerce

Aircraft Refueling Aviation fuel consumption Gallons of fuel State Energy Office, airportsWastewater Treatment Surface impoundment modeling 

system (SIMS)

Gallons of wastewater andportions of industrial wastewater

Publicly owned treatmentworks (POTW) operators

Hospital Sterilizers Per hospital bed Hospital beds State Health DepartmentForest Fires Acres burned Acres burned State ForesterBreweries State beer production Barrels of beer State Commerce Office, trade

groups
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.5-5

TABLE 1.5-1

(CONTINUED)

Area Source Category Estimation Procedure Activity Data Source of Activity Data

Barge, Tank Car, Railcar,Drum Cleaning

Survey Vessels cleaned,

material cleanedout of vessels

Trade groups, drumcleaning facilities

Medical Waste Incinerators Survey Waste incinerated State Health DepartmentAsphalt Roofing Kettles Per square paper Material throughput Trade groupsOrchard Heaters Fuel consumption Amount of fuel used Extension agents, 

agricultural schools

Distilleries Distilled spirits production Barrels of spirits State Commerce Office,

trade groups 

Agricultural/Slash Burning Acres burned Acres burned Extension agents,

agricultural schools

Wineries Wine production Barrels of wine State Commerce Office,

trade groups

TSDFs Survey Material type,

material throughput, treatment type

State EnvironmentalOffice

Superfund Sites Survey Material type,

material throughput, treatment type

State EnvironmentalOffice

Open Burning Survey Occurrence of 

burning

State EnvironmentalOffice
CHAPTER 1 - INTRODUCTION 1/31/01

1.5-6 EIIP Volume III

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 DATA STORAGE

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.
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.5-7

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 petroleumbased 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.
CHAPTER 1 - INTRODUCTION 1/31/01

1.5-8 EIIP Volume III

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.” 
EIIP Volume III 1.6-1

6

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 
CHAPTER 1 - INTRODUCTION 1/31/01

1.6-2 EIIP Volume III

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
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.6-3

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)
CHAPTER 1 - INTRODUCTION 1/31/01

1.6-4 EIIP Volume III

INTERNAL SOURCE CATEGORY CONSISTENCY

AND ACCURACY QUALITY CONTROL CHECKS (Continued)

Actions To Be Taken Deadline Completion Date

FIGURE 1.6-1. (CONTINUED)
1/31/01 CHAPTER 1 - INTRODUCTION

EIIP Volume III 1.6-5

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
CHAPTER 1 - INTRODUCTION 1/31/01

1.6-6 EIIP Volume III

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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EIIP Volume III 1.6-7

 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 
CHAPTER 1 - INTRODUCTION 1/31/01

1.6-8 EIIP Volume III

TABLE 1.6-1

SOURCES OF 

UNCERTAINTY IN 

AREA 

SOURCE 

EMISSION 

ESTIMATES

Source of Uncertainty Examples Ways to Minimize

Variability  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). 

 Quantify variability if

possible.

 Make sure averaging time of

emission factor and activityare appropriate for temporalscale of inventory.

 If possible, subdivide

category to create moreuniform subcategories.

Parameter UncertaintyMeasurement errors  Incorrect response on a survey form.

 Misclassification of data (e.g., facility in SIC Code group

that does not accurately define activities).

 QA audits of survey data.

Sampling error  Inadequate sample size.

 Underlying data not normally distributed.

 Ensure adequate sample size

by increasing response rate orincreasing distribution ofsurvey.

 Consider distribution of data

in sample design andstatistical analysis.
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EIIP Volume III 1.6-9

TABLE 1.6-1

(CONTINUED)

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 atsmaller facilities).

 Incorrect assumption (such as assuming 100% compliance

with rules and ignoring rule effectiveness).

 External review of methods

and assumptions by aqualified expert on theindustry.

 Make sure that characteristics

of source population areunderstood and accounted forin methods.

Model UncertaintySurrogate variables  Use of population or number of employees as surrogate

for emission activities that do not correlate to thosesurrogates.

 Use surveys of local sources

instead.

 Develop emission factors

based on statisticallycorrelated surrogate.

Exclusion of variables/modeloversimplification

 Potentially a problem for area source estimates based on

emission factors or models.

 Validate model for specific

use if possible (i.e., use modelto predict a known value).

 Avoid use of oversimplified

methods if at all possible.
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type of uncertainty. More information on uncertainty can be found in EIIP 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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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

refinishing 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. EIIP 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-Percent Rate-of-Progress Plans. U.S. Environmental Protection Agency, 

EPA-452/R-93-002. Research Triangle Park, North Carolina. March.
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