EPA 560/5-85-004
JULY 1985
METHODS FOR ASSESSING EXPOSURE
TO CHEMICAL SUBSTANCES
Volume 4
Methods for Enumerating and Characterizing
Populations Exposed to Chemical Substances
by
Douglas A. Dlxon, Karen A. Hammerstrom, G1na L. Hendrlckson,
Patricia Jennings, Thompson Chambers, Amy Borensteln,
John Dorla, Thomas Faha
EPA Contract No, 68-01-6271
Project Officer
Michael A. Callahan
Exposure Evaluation Division
Office of Toxic Substances
Washington, DC 20460
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF PESTICIDES AND TOXIC SUBSTANCES
WASHINGTON, DC 20460
II
, IL
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DISCLAIMER
This document has been reviewed and approved for publication by the
Office of Toxic Substances, Office of Pesticides and Toxic Substances,
U.S. Environmental Protection Agency. The use of trade names or
commercial products does not constitute Agency endorsement or
recommendation for use.
111
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FOREWORD
This document 1s one of a series of volumes, developed for the U.S.
Environmental Protection Agency (EPA), Office of Toxic Substances (OTS),
that provides methods and Information useful for assessing exposure to
chemical substances. The methods described 1n these volumes have been
Identified by EPA-OTS as having utility 1n exposure assessments on
existing and new chemicals 1n the OTS program. These methods are not
necessarily the only methods used by OTS, because the state-of-the-art 1n
exposure assessment 1s changing rapidly, as 1s the availability of
methods and tools. There 1s no single correct approach to performing an
exposure assessment, and the methods 1n these volumes are accordingly
discussed only as options to be considered, rather than as rigid
procedures.
Perhaps more Important than the optional methods presented 1n these
volumes 1s the general Information catalogued. These documents contain a
great deal of non-chem1cal-spedf1c data which can be used for many types
of exposure assessments. This Information 1s presented along with the
methods 1n Individual volumes and appendices. As a set, these volumes
should be thought of as a catalog of Information useful 1n exposure
assessment, and not as a "how-to" cookbook on the subject.
The definition, background, and discussion of planning exposure
assessments are discussed 1n the Introductory volume of the series
(Volume 1). Each subsequent volume addresses only one general exposure
setting. Consult Volume 1 for guidance on the proper use and
Interrelations of the various volumes and on the planning and Integration
of an entire assessment.
The titles of the nine basic volumes are as follows:
Volume 1 Methods for Assessing Exposure to Chemical Substances
(EPA 560/5-85-001)
Volume 2 Methods for Assessing Exposure to Chemical Substances 1n the
Ambient Environment (EPA 560/5-85-002)
Volume 3 Methods for Assessing Exposure from Disposal of Chemical
Substances (EPA 560/5-85-003)
Volume 4 Methods for Enumerating and Characterizing Populations
Exposed to Chemical Substances (EPA 560/5-85-004)
Volume 5 Methods for Assessing Exposure to Chemical Substances 1n
Drinking Water (EPA 560/5-85-005)
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Volume 6 Methods for Assessing Occupational Exposure to Chemical
Substances (EPA 560/5-85-006)
Volume 7 Methods for Assessing Consumer Exposure to Chemical
Substances (EPA 560/5-85-007)
Volume 8 Methods for Assessing Environmental Pathways of Food
Contamination (EPA 560/5-85-008)
Volume 9 Methods for Assessing Exposure to Chemical Substances
Resulting from Transportation-Related Spills
(EPA 560/5-85-009)
Because exposure assessment 1s a rapidly developing field, Its
methods and analytical tools are quite dynamic. EPA-OTS Intends to Issue
periodic supplements for Volumes 2 through 9 to describe significant
Improvements and updates for the existing Information, as well as adding
short monographs to the series on specific areas of Interest. The first
four of these monographs are as follows:
Volume 10 Methods for Estimating Uncertainties 1n Exposure Assessments
(EPA 560/5-85-014)
Volume 11 Methods for Estimating the Migration of Chemical Substances
from Solid Matrices (EPA 560/5-85-015)
Volume 12 Methods for Estimating the Concentration of Chemical
Substances 1n Indoor A1r (EPA 560/5-85-016)
Volume 13 Methods for Estimating Retention of Liquids on Hands
(EPA 560/5-85-017)
Michael A. Callahan, Chief
Exposure Assessment Branch
Exposure Evaluation Division (TS-798)
Office of Toxic Substances
v1
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ACKNOWLEDGEMENTS
This report was prepared by Versar Inc. of Springfield, Virginia, for
the EPA Office of Toxic Substances, Exposure Evaluation Division,
Exposure Assessment Branch (EAB) under EPA Contract No. 68-01-6271 (Task
9). The EPA-EAB Task Manager was Karen A. Hammerstrom, the EPA Program
Manager was Michael Callahan; their support and guidance 1s gratefully
acknowledged. Acknowledgement 1s also given to Elizabeth Bryan and Loren
Hall of EPA-EED, who also took part 1n this task.
A number of Versar personnel have contributed to this task over the
three-year period of performance as shown below:
Program Management - Gayaneh Contos
Task Management - Douglas D1xon
Technical Support - Glna Hendrlckson
Patricia Jennings
Thompson Chambers
Amy Borensteln
John Dorla
Thomas Faha
Steve Mitchell
Michael Neely
Editing - Juliet Crumrlne
Secretarial/Clerical - Shirley Harrison
Lucy Gentry
Donna Barnard
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TABLE OF CONTENTS
Page No.
FOREWORD v
ACKNOWLEDGEMENTS v11
TABLE OF CONTENTS 1x
LIST OF TABLES x11
LIST OF FIGURES xv
LIST OF METHODS xv11
1. INTRODUCTION 1
1.1 Purpose and Scope 1
1.2 Report Organization 1
1.3 Framework of Methods 2
2. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT
ENVIRONMENT 5
2.1 Introduction 5
2.2 Identification of Exposed Populations 5
2.3 Methods for the Enumeration of Exposed Populations 9
2.3.1 Census of Population 9
2.3.2 Enumeration of Populations Exposed via Inhalation 35
2.3.3 Enumeration of Populations Exposed via Dermal
Contact 56
2.3.4 Enumeration of Non-Human Populations 59
2.4 Characterization of Exposed Populations 61
2.4.1 Populations Exposed via Inhalation 61
2.4.2 Population Exposed via Dermal Contact 63
2.5 References 66
3. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE
OCCUPATIONAL ENVIRONMENT .... 69
3.1 Introduction 69
3.2 Identification of Exposed Populations 69
3.3 Methods for the Enumeration of Exposed Populations . . 72
IX
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TABLE OF CONTENTS (Continued)
Page No.
3.3.1 Enumeration of Populations Identified by SIC
Code 73
3.3.2 Enumeration of Populations Defined by
Occupation and Industry 77
3.3.3 Enumeration of Site-Specific Populations .... 79
3.4 Characterization of Occupatlonally Exposed Populations.. 82
3.5 References 87
4. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE
INGESTION OF FOOD 89
4.1 Introduction 89
4.2 Identification of Exposed Populations 89
4.3 Methods for the Enumeration of Exposed Populations. . . 91
4.3.1 Enumeration of Populations Exposed as a Result
of Agricultural Practices 93
4.3.2 Enumeration of the Populations Exposed as a
Result of Processing and Packaging 94
4.3.3 Enumeration of Populations Exposed as a Result
of Releases from Other Sources ... 98
4.3.4 Enumeration of Exposed Populations by the Use of
Monitoring Data 106
4.4 Characterization of the Exposed Population Ill
4.5 References 115
5. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE USE OF
CONSUMER PRODUCTS 117
5.1 Introduction 117
5.2 Identification of Exposed Populations 117
5.3 Methods for the Enumeration of Exposed Populations . . . 120
5.3.1 Enumeration of Exposed Populations via Simmons
Market Research Bureau Reports 120
5.3.2 Enumeration of Exposed Populations via Production
and Sales Data 138
5.3.3 Enumeration of Exposed Populations via Chemical-
Specific Information 138
5.3.4 Enumeration of Consumers Performing Amateur or
Hobbyist Activities 141
5.4 Characterization of Exposed Populations 142
5.5 References 146
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TABLE OF CONTENTS (Continued)
Page No.
6. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION
OF DRINKING WATER 147
6.1 Introduction 147
6.2 Identification of Exposed Populations 149
6.3 Methods for the Enumeration of Exposed Populations . . . 149
6.3.1 Enumeration of Populations 1n Specific
Geographic Areas 151
6.3.2 Enumeration of Populations Exposed via
Treatment Methods 160
6.3.3 Enumeration of Exposed Populations by Type of
Distribution System 163
6.3.4 Enumeration by Use of Monitoring Data 165
6.4 Characterization of Exposed Populations 168
6.5 References 169
APPENDIX A: APPLICATION OF METHODS TO EXAMPLE PROBLEMS 171
Introduction 173
A-l. Populations Exposed to Chemical Substances
1n the Ambient Environment 174
A-2. Populations Exposed to Chemical Substances
1n the Occupational Environment 200
A-3. Populations Exposed to Chemical Substances
via the Ingestlon of Food 208
A-4. Populations Exposed to Chemical Substances
via the Use of Consumer Products 214
A-5. Populations Exposed to Chemical Substances
via the Ingestlon of Drinking Water 225
APPENDIX B: EXAMPLES OF DATA BASES USED IN OCCUPATIONAL
POPULATIONS METHODS SECTION 233
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LIST OF TABLES
Page No.
Table 1 Population Subject Items Included 1n the 1980 Census . . 10
Table 2 Geographic Units of the Census of Population 12
Table 3 Information on 1980 Census Reports: Their
Geographical Breakdown, Characteristics, and
Expected Dates of Release 20
Table 4 Relationship of 1980 Summary Tape Files. Printed
Reports, and Microfiche 25
Table 5 Summary Tape File Geography (1980) 26
Table 6 Smallest Type of Area on 1980 Census Summary Tape
Files 27
Table 7 Census Outline Maps 28
Table 8 Population Densities for the Different Census Bureau
Area Classifications and Regions 47
Table 9 Average U.S. Population Size for ATM-SECPOP
Concentration Sectors for General Point Sources Located
1n Urbanized, Metropolitan, and Nonmetropolltan Areas . . 48
Table 10 1980 Population Data for the U.S. and Regions by
Census Geography 51
Table 11 Sources of Information on Non-Human Populations .... 62
Table 12 Population of the United States by Age and Sex:
April 1, 1980 64
Table 13 Data Available 1n the 1977 Economic Censuses 76
Table 14 Employed Persons by Occupation and Sex, 1979 84
Table 15 Age and Sex Distribution of Employment by General
Occupation 86
Table 16 Ranking of Seafood Species by Percent of Individuals
Consuming and Projected 1980 Consuming Population . . . 103
xn
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LIST OF TABLES (Continued)
Page No.
Table 17 Percent of Households, U.S. Population, and Household
Size 1n Urban, Rural Non-Farm, and Rural Farm Areas with
107
Table 18
Table 19
Table 20
Table 21
Table 22
Table 23
Table 24
Table 25
Table 26
Table 27
Table 28
Table 29
Percent Gardening Households Growing, Freezing, Canning,
or Preserving Selected Home Grown Fruits and Vegetables,
1975-77
Simmons Market Research Bureau Product Categories and
Services Provided by Volume
Alphabetical Index of Products and Services Measured
1n the 1980 SMRB Study
Product Usage Categorization for SMRB "Heavy," "Medium,"
and "Light" Designations
Example of 1981 SMRB Data: Demographic Variables for
Usage of Rug Cleaners Purchased by Female Homemakers . .
Example of 1981 SMRB Data: Demographic Variables for
Types of Rug Cleaners Purchased by Female Homemakers . .
Example of 1981 SMRB Data: Demographic Variables for
Brands of Rug Cleaners Purchased by Female Homemakers .
Summary of the Number of Households that Can Be
Considered To Have at Least One Amateur or Hobbyist
With Respect to a Specific Activity
Federal Reporting Data System (FRDS) Description of 11
Standard Reports
Population Served by Drinking Water Treatment Processes
for the U.S
Distribution System Components and Potential
Contaminants
Populations Served by Drinking Water System Size and
Source Type
108
121
122
130
131
132
133
143
158
161
164
167
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LIST OF TABLES (Continued)
Page No.
Table 30
Table 31
Table 32
Table 33
Line Source Corridor Distances, Population Density and
Population Exposed 1n Problem 5
Characterization of Exposed Population for Line
Source Problem 5
Employment by SIC Code for Producers and Users of
Phosphate Fertilizers ,
Rug/Carpet Cleaning Products Market Survey Results . .
197
199
201
219
xiv
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LIST OF FIGURES
Page No.
Figure 1 Three-Stage Framework for Identifying, Enumerating,
and Characterizing Populations Exposed to Chemical
Substances 3
Figure 2 Three-Stage Framework for Enumerating and Characterizing
Populations Exposed to Chemical Substances 1n the
Ambient Environment 6
Figure 3 Geographic Regions and Divisions of the United States . 11
Figure 4 Geographic Organization of the Major Census Statistical
Categories 16
Figure 5 Breakdown of Census Geography 17
Figure 6 Census Geography for Metropolitan and Nonmetropolltan
Counties 18
Figure 7 Examples of Census Maps 30
Figure 8 Telephone Contacts for Bureau of the Census Data
Users 31
Figure 9 Wind Rose Sectors for ATM-SECPOP 37
Figure 10 Sample ATM-SECPOP Output for Concentration, Population,
and Population Exposure 39
Figure 11 Sample ATM-SECPOP Graphic Display: Bar Chart of
Population Exposure vs. Distance 40
Figure 12 Sample ATM-SECPOP Graphic Display: Line Plot of
Concentration vs. Distance 41
Figure 13 Sample ATM-SECPOP Graphic Display: Rose Diagram of
Population Exposed 42
Figure 14 Sample of ATM-SECPOP Mapping of ED/BGs Around a
Point Source 43
Figure 15 Schematic Representation of the Procedure to Enumerate
Populations Exposed to Chemical Substances Released
from a Line Source 54
xv
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LIST OF FIGURES (Continued)
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Three-stage Framework for Enumeration and
Characterization of Occupatlonally Exposed
Populations ,
Three-stage Framework for the Enumeration and
Characterization of Populations Exposed to Chemical
Substances via the Ingestlon of Food
Example Data Summary from National Food Consumption
Survey of 1977-78
Three-stage Framework for the Identification,
Enumeration, and Characterization of Populations
Exposed to Chemical Substances 1n Consumer Products
A Page from a Typical 1980 SMRB Marketing Report .
Three-stage Framework for Enumerating and
Characterizing Populations Exposed to Chemical
Substances via the Ingestlon of Drinking Water . .
Example Printout of the Model State Information
System - Public Water Supply Inventory for
Redmond City, Oregon
Page No.
70
90
112
118
134
148
157
XVI
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LIST OF METHODS
General Procedure for Identifying Populations Exposed
to Chemical Substances 1n the Ambient Environment . . .
Method 2-1
Method 2-2 Enumeration of Populations Exposed via Inhalation to
Atmospheric Concentrations of Chemical Substances
Released from Point Sources
Method 2-3 Enumeration of Populations Exposed via Inhalation to
Chemical Substances Released from Prototype Point
Sources
Method 2-4 Enumeration of Populations Exposed via Inhalation to
Atmospheric Concentrations of Chemical Substances
Released from Area Sources
Method 2-5 Enumeration of Populations Exposed via Inhalation to
Chemical Substances Released from Line Sources ....
Method 2-6 Enumeration of Populations Exposed via Dermal Contact .
Method 2-7 Characterization of Populations Exposed to Chemical
Substances via Inhalation of Ambient A1r
Method 3-1 General Procedure for Identifying Populations Exposed
1n the Workplace
Method 3-2 Enumeration of Populations Identified by SIC Code . . .
Method 3-3 Enumeration of Populations Identified by Occupation and
Industry
Method 3-4 Enumeration of Site-Specific Populations
Method 3-5 Characterization of Occupatlonally Exposed
Populations
Method 4-1 Generalized Procedure for Identifying Populations
Exposed to Chemical Substances via the Ingestlon of
Food
Method 4-2 Enumeration of Populations Exposed as a Result of
Agricultural Practices
Page No.
7
44
49
52
57
58
65
71
74
78
80
83
92
95
xvn
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LIST OF METHODS
Page No.
Method 4-3 Enumeration of Populations Exposed as a Result of
Packaging and Processing of Food 97
Method 4-4 Enumeration of Populations Exposed as a Result of
Packaging or Processing Procedures Used by a Specific
Company 99
Method 4-5 Enumeration of Populations Exposed as a Result of
Consuming Noncommercial Freshwater F1sh or Game from a
Geographically Defined Area of Contamination 101
Method 4-6 Enumeration of Populations Exposed as a Result of
Consuming Seafood from a Geographically Defined Area of
Contamination 105
Method 4-7 Enumeration of Populations Exposed to Chemical
Substances via the Consumption of Home Grown Fruits and
Vegetables 109
Method 4-8 Enumeration of Exposed Populations by the Use of
Monitoring Data 110
Method 4-9 Characterization of Populations Exposed to Chemical
Substances 1n Types of Food 113
Method 5-1 General Procedure for Identifying Populations Exposed
to Chemical Substances 1n Consumer Products 119
Method 5-2 Enumeration of Exposed Consumer Populations via the Use
of Simmons Market Research Bureau Reports 136
Method 5-3 Enumeration of Populations Exposed to Chemicals 1n
Consumer Products via the Use of Economic Data .... 139
Method 5-4 Characterization of Populations Exposed to Chemical
Substances 1n Consumer Products 145
Method 6-1 General Procedure for Identifying Populations Exposed
to Chemical Substances 1n Drinking Water 150
Method 6-2 Enumeration of Populations Exposed to Chemical
Substances 1n Surface Sources of Drinking Water Using
the REACH File 153
xvm
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LIST OF METHODS
Method 6-3
Method 6-4
Method 6-5
Method 6-6
Enumeration of Populations Exposed to Chemical
Substances 1n Surface Sources of Drinking Water Using
the FRDS Data Base
Enumeration of Populations Exposed to Chemical
Substances 1n Ground Sources of Drinking Water . . .
Enumeration of Populations Exposed to Chemical
Substances as a Result of Lack of Treatment Processes
Enumeration of Exposed Populations by the Use of
Monitoring Data
Page No.
155
159
162
166
xix
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1. INTRODUCTION
This volume 1s the fourth In a series of nine volumes presenting
methods for assessing exposures to chemical substances; the reports are
being developed for the U.S. Environmental Protection Agency (EPA),
Office of Toxic Substances (OTS). This volume presents methods and
supporting Information for enumerating and characterizing populations
exposed to chemical substances 1n each of the EPA-OTS defined exposure
categories. The purpose and scope of this report, the report
organization, and the methodological framework are discussed 1n the
following subsections.
1.1 Purpose and Scope
This document and the methods that 1t contains have been prepared to
aid 1n overcoming one of the major difficulties encountered 1n the
preparation of exposure assessments for Individual chemical substances:
the enumeration and characterization of specific populations exposed to
chemical substances. Each of the seven categories of an exposure
assessment has certain populations associated with 1t, and each
population has further subpopulatlons that vary with respect to the
concentrations to which they are exposed and the frequency and duration
of exposure. While 1t has often been possible to Identify exposed
populations from monitoring or release data, 1t has rarely been possible
to estimate sizes of specific subpopulatlons. The purpose of this
report, therefore, 1s to catalog pertinent Information, data bases, and
tools, and to provide a systematic approach or methods whereby the
population exposed to a given chemical substance 1n each of the exposure
categories can be enumerated and characterized according to age and sex
at any desired level of detail.
1.2 Report Organization
The data sources and methods to enumerate and characterize exposed
populations In each of the exposure categories are specific to that
exposure category. This report, therefore, Is divided Into separate
sections according to the category of exposed populations as follows:
• Section 2 - Populations Exposed to Chemical Substances 1n the
Ambient Environment
• Section 3 - Populations Exposed to Chemical Substances 1n the
Occupational Environment
• Section 4 - Populations Exposed to Chemical Substances via the
Ingestlon of Food
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t Section 5 - Populations Exposed to Chemical Substances via the Use
of Consumer Products
• Section 6 - Populations Exposed to Chemical Substances via the
Ingestlon of Drinking Water.
Exposures resulting from the disposal and transportation related spills
of chemical substances are subsets of exposures occurring In the ambient
environment. Populations exposed to chemical substances 1n these
categories are Identified either geographically or by occupation.
Section 2 of this report covers the geographic enumeration and
characterization of exposed populations, while Section 3 covers the
enumeration and characterization of occupatlonally exposed populations.
Finally, demonstrations of the methods contained 1n each section of this
report are presented as example population problems In the Appendix.
1.3 Framework of Methods
The framework for enumerating and characterizing exposed populations
1s the same for each of the sections and comprises three stages. These
stages are:
1. The Identification of the exposed population.
2. The enumeration of the exposed population.
3. The characterization of the exposed population according to age
and sex.
Figure 1 1s a flow diagram of the three-stage framework. The following
paragraphs briefly describe each stage; detailed Information Is provided
1n each of the sections of this report.
The first stage, the Identification of exposed populations, 1s a
function of the chemical and physical properties, sources of
environmental release (I.e., manufacturing, processing, distribution,
use, and disposal), and environmental transport and transformation of a
chemical substance. Identification and evaluation of these data will
Indicate the media (I.e., air, water, soil), exposure route (Inhalation,
Ingestlon, dermal absorption), exposure category or scenario (e.g.,
ambient, occupational, drinking water), and the activities that lead to
exposure or the microenvlronments where exposure occurs. Information on
Identifying exposed populations 1s contained 1n Volumes 2 through 9 of
this exposure assessment methods report series.. This report only
briefly describes the procedures for Identifying exposed populations.
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IDENTIFICATION OF EXPOSED POPULATIONS
• EVALUATE CHEMICAL/PHYSICAL PROPERTIES
• IDENTIFY SOURCES & RELEASES
• EVALUATE TRANSPORT AND TRANSFORMATION
• GATHER MONITORING DATA
TO
• IDENTIFY MEDIA AND EXPOSURE ROUTE
• IDENTIFY EXPOSURE SCENARIOS (i.e., AMBIENT
OCCUPATIONAL, CONSUMER, FOOD, DRINKING WATER !
• IDENTIFY MICROENVIRONMENTS AND ACTIVITIES
ENUMERATION OF EXPOSED POPULATIONS
DATA SOURCES AND METHODS TO ENUMERATE
POPULATIONS EXPOSED TO CHEMICAL
SUBSTANCES IN:
• THE AMBIENT ENVIRONMENT
• THE OCCUPATIONAL ENVIRONMENT
• FOOD
• DRINKING WATER
• CONSUMER PRODUCTS
III CHARACTERIZATION OF EXPOSED POPULATIONS
DATA SOURCES AND METHODS TO OBTAIN AGE AND/OR
SEX CHARACTERISTICS BY USING:
• GEOGRAPHIC OR ACTIVITY SPECFIC DATA
• GENERIC DATA
Figure 1. Three-stage Framework for Identifying,
Enumerating, and Characterizing Populations
Exposed to Chemical Substances
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The second stage Involves the use of various data sources,
computerized data bases, and generic Information to enumerate exposed
populations. In the appropriate exposure category sections of this
report, data sources are discussed, Including any limitations; the
responsible agencies or Individuals who must be contacted to obtain the
required Information are also listed. Methods utilizing the various data
sources are presented 1n a step-by-step fashion 1n each section so that
the Investigator or exposure assessment team can enumerate exposed
populations efficiently.
The final stage describes the data sources and procedures to be used
to characterize the exposed population. Characterization of the exposed
population Involves determining the numbers of Individuals 1n particular
age and sex classes. The age and sex of the exposed population affect
the physiological parameters that determine exposure (I.e., breathing
rate, body weight, skin surface area) and Identify sensitive
subpopulatlons (e.g., children, women of chlldbearlng age). Detailed
exposure assessments may require that populations be described by age and
sex distribution. The procedures presented for this stage 1n each of the
exposure category sections direct the Investigator or assessment team 1n
the use of geographic data, activity-specific data, or generic data on
age and sex distributions to characterize exposed populations.
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2. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT
ENVIRONMENT
2.1 Introduction
This section presents methods for enumerating and characterizing
populations exposed to chemical substances In the ambient environment.
The methods described are applicable to populations exposed as a result
of Industrial effluents, non-point or area sources, natural sources,
disposal related releases, consumer related releases, spills from
transportation or storage activities, and unknown sources.
Figure 2 1s a flow diagram of the three-stage framework for
enumerating populations exposed to chemical substances 1n the ambient
environment. Included 1n the diagram are some of the major data sources
used 1n the three stages.
The Identification of exposed populations 1s discussed only briefly
1n this section (Subsection 2.2); the ambient exposure assessment methods
report (Volume 2) describes the process 1n detail.
The enumeration of the exposed population principally relies on
population data collected by the Bureau of the Census, particularly the
decennial Census of Population. The most recently conducted Census, the
data publication form and document titles, and the use of census data 1n
exposure assessment population studies are discussed 1n detail 1n
Subsection 2.3.
The age and sex of the exposed population affect the physiological
parameters that determine exposure (e.g., breathing rate, skin surface
area) and Identify sensitive subpopulatlons (e.g., women of child-bearing
age, the elderly). Detailed exposure assessments may require that
populations be described by age and sex distribution. Subsection 2.4
discusses the data sources and procedures to characterize populations by
age and sex distribution.
2.2 Identification of Exposed Populations
Populations potentially exposed to a chemical substance 1n the
ambient environment are Identified through an evaluation of the
substance's sources, Its behavior 1n the environment, and applicable
monitoring data. Subpopulatlons may be further defined by their
participation 1n specific activities leading to exposure. Method 2-1
summarizes the steps Involved 1n Identifying populations exposed to
chemical substances 1n the ambient environment. Volume 2 of this series
describes the requisite data 1n detail.
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r
IDENTIFICATION OF EXPOSED POPULATION
DETERMINE EXPOSURE ROUTE VIA
CHEMICAL/PHYSICAL PROPERTIES AND
RELEASE CHARACTERISTICS OF SUBSTANCE
IDENTIFY HUMAN ACTIVITIES
LEADING TO EXPOSURE
(SWIMMING IN
CONTAMINATED WATER)
DETERMINE
GEOGRAPHIC RESOLUTION
Q
DETERMINE
GEOGRAPHIC RESOLUTION
ENUMERATE EXPOSED
POPULATION FOR
DEFINED CENSUS
GEOGRAPHY FROM
1910 CENSUS OF
POPULATION
m
I
DETERMINE POPULATION
FOR GEOGRAPHIC AREA
FROM 1910 CENSUS OF
POPULATION
ENUMERATE EXPOSED
POPULATION VIA
GENERIC ACTIVITY DATA
J
L
SITE SPECIFIC AGE/SEX
DISTRIBUTION FROM
1980 CENSUS OF POPULATION:
NUMBER OF INHABITANTS
NATIONAL AGE/SEX
DISTRIBUTION FROM
19(0 CENSUS OF POPULATION
I
•NOT CONSIDERED IN THIS METHOD
(SEE VOLUME 5 - METHODS FOR ASSESSING EXPOSURE TO CHEMICAL SUBSTANCES IN DRINKING WATER)
Figure 2. Three-stage Framework for Enumerating and Characterizing
Populations Exposed to Chemical Substances in the
Ambient Environment
6
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Method 2-1. General Procedure for Identifying Populations Exposed
to Chemical Substances in the Ambient Environment
Step 1 Identify the locations of chemical release into the environment;
define each release to the atmosphere as a point, area, or line
source. Using monitoring data and/or environmental fate information,
identify the geographic locales and media of concern (air, water,
land). Volume 2 of this series catalogs data bases, information
sources, and tools that will aid in this process.
Step 2 For each medium of interest, evaluate the significance of exposure
routes:
• Air - inhalation
• Water - dermal contact
• Land - dermal contact
Step 3 Identify exposed populations by listing significant pathways:
• Persons breathing ambient air contaminated by atmospheric
point, area, or line sources.
• Persons swimming in contaminated surface waters.
• Non-human populations of ecological or economic importance
residing in the locale and media of concern.
• Other populations not specifically addressed in this volume
(e.g., children swallowing or chewing objects or playing in
soil contaminated with fallout of particulates consisting of or
containing the chemical substance).
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Exposed populations are Initially Identified as those near sources of
the substance; modeling and monitoring provide the geographic definition
of "near" by defining the levels of exposure 1n the environment at a
given point or general location. Knowledge of a substance's physical and
chemical properties, emission characteristics, and environmental
transport and transformation helps to Identify the physical state of the
chemical and the media (e.g., air, water) Into which 1t 1s released and
to which 1t will partition. The physical state and media 1n turn
determine the potential exposure routes: Inhalation, 1ngest1on, and
dermal contact.
In order to enumerate exposed populations, Identification must be
refined beyond the determination of exposure route by considering the
geographic locations where the chemical 1s released and the activities 1n
the ambient environment that result 1n exposure. Inhalation exposures
may result from proximity to:
• Point sources - known locations of emissions Identifiable by
geographic coordinates (e.g., Industrial discharges, disposal
sites).
• Area sources - sources related to chemical use or Incidental
emission defined by broad geographic boundaries (e.g., urban areas
as a source of automotive exhaust).
• Line sources - sources of chemical emission, usually assumed to be
at a constant rate, that are mobile and move along a pathway or
line such as a road, rail, or river.
Since breathing 1s a constant activity, populations exposed via
Inhalation are defined only by the sources listed above.
Dermal exposure to a chemical substance may result from contact with
ambient air, water, or soil. Dermal exposure to airborne contaminants 1s
likely to be Insignificant 1n comparison to Inhalation exposure. The
most Important exposure pathways for the dermal route are probably
swimming 1n surface waters and contacting soil during work or play.
Only the most significant and common pathways of exposure are
considered 1n this report. There are numerous other exposure pathways 1n
the ambient environment that are not dealt with 1n this report (e.g.,
1ngest1on of contaminated soil by children). Identification of these
pathways and the exposed populations must be addressed within Individual
exposure assessments. The data bases, Information sources, and tools
discussed 1n this report win aid 1n this process.
-------
2.3 Methods for the Enumeration of Exposed Populations
This section discusses the data sources and recommended procedures
for enumerating populations exposed to chemical substances 1n the ambient
environment. Because populations exposed to chemical substances 1n the
ambient environment are defined geographically and since the Census of
Population 1s the major geographic population data base, the first
subsection (2.3.1) 1s devoted to Its discussion. The methods developed
for the enumeration of exposed populations are subsequently discussed
according to Inhalation exposure 1n Subsection 2.3.2 and dermal exposure
1n Subsection 2.3.3.
2.3.1 Census of Population
The U.S. Census, conducted once every decade, determines the size,
distribution, and demographic characteristics of the population. The
most recent Census was conducted 1n 1980 and 1s divided Into two
categories: (1) complete count data for the entire U.S. population
(short form) and (2) more detailed population, social, and economic
characteristics for 20 percent of the U.S. population (long form). The
data collected 1n each of these categories are listed In Table 1.
The data collected 1n the Census are organized according to
geographic areas 1n the U.S. as Illustrated 1n Figure 3 and within
geographic areas according to census-defined statistical areas and
government units as listed 1n Table 2. Figure 4 Illustrates the
geographic organization of the major census statistical areas (I.e.,
Standard Metropolitan Statistical Areas (SMSAs), urbanized areas, and
urban and rural areas). The detailed breakdown of census geography 1s
Illustrated 1n Figures 5 and 6. Population data, therefore, are
available within SMSAs to the level of the Block and 1n non-SMSAs to the
level of the Enumeration District (EO).
Census geography and the population data available for each
geographic category are extremely Important throughout this methodology.
In this section, and all sections of the methodology, census geography
will be used as consistently as possible. It should be noted that many
organizations report population data according to what appears to be
census geographic categories (e.g., "urban" population, "rural"
population). Upon further Investigation, however, sample design and data
presentation may not strictly follow the census definition of geographic
categories. When using population data not reported by the Bureau of the
census, therefore, the Investigator should carefully review the
geographic categories of data presentation for consistency with the
census classifications.
-------
Table 1. Population Subject Items Included in the 1980 Census
lOOt Items
Sample items
(201 sample or 1 out of 6 households)
• Household relationship
• Sex
• Race
• Age
• Marital status
• Spanish/Hispanic origin
or descent
• School enrollment
• Educational attainment
• State or foreign country of birth
• Citizenship and year of immigration
• Current language and English
proficiency
• Ancestry
• Place of residence five years ago
• Activity five years ago
• Veteran status and period of service
• Presence of disability or handicap
• Children ever born
• Marital history
• Employment status last week
• Place of work
• Travel time to work
• Means of transportation to work
• Number of persons in carpool
• Year last worked
• Industry
• Occupation
• Type of employment
• Number weeks worked in 1979
• Usual hours worked per week in 1979
• Number weeks looking for work in 1979
• Amount of inclome in 1979 by source
Source: Bureau of the Census 1979a.
10
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Table 2. Geographic Units of the Census of Population
Statistical areas
Government units
Regions: Regions are large, geographi-
cally contiguous groups of states (with
the exception of the region that
includes Alaska and Hawaii). There are
four regions: Northeast, North Central,
South, and West (see Figure 1).
Divisions: Divisions are groups of
states which are subdivisions of
regions. There are nine divisions: New
England, Middle Atlantic, South
Atlantic, East South Central, West South
Central, East North Central, West North
Central, Mountain, and Pacific (see
Figure 1).
Standard Metropolitan Statistical Areas
(SMSAs): An SMSA is an integrated
economic and social unit with a
recognized large population nucleus.
Generally, each SMSA consists of one or
more entire counties, or county equiva-
lents, that meet standards pertaining to
population and metropolitan character.
In New England, towns and cities, rather
than counties, are used as the basic
geographic units for defining SMSAs. In
Alaska, census divisions are used to
define SMSAs. Criteria used to
delineate the 267 SMSAs for which data
were tabulated for the 1972 Economic
Censuses specified that an SMSA include
at least (1) one city with 50,000
inhabitants, or more or (2) a city
having a population of at least 25,000
which, with the addition of the popula-
tion of contiguous places, incorporated
or unincorporated, has a population
density of at least 1,000 persons per
square mile. Together, they must
constitute, for general economic and
social purposes, a single community with
• The United States
• States: The 50 states are the major
political units of the United States.
The District of Columbia is treated as a
state-equi valent.
• Counties: Counties are the primary
political and administrative divisions
of the states.
Minor Civil Divisions (MCDs): These are
the primary political and administrative
subdivisions of counties; most
frequently known as townships, but in
some states include towns, precincts,
and magisterial districts.
Census County Divisions (CCDs). In 21
states, MCDs were found to be unsuitable
for presenting statistics due to area's
small population size, frequent boundary
changes, etc. CCDs are defined with
boundaries that seldom change and can be
easily located (e.g., roads, railroads,
power lines, and bridges).
Places: A concentration of population,
regardless of the existence of legally
prescribed units, powers, or functions.
In the 1970 Census, most places are
incorporated as cities, towns, villages,
or boroughs.
- Incorporated places: These are
political units incorporated as
cities, boroughs (excluding Alaska
and New York), villages, and towns
(excluding the New England States,
New York, and Wisconsin). Most
incorporated places are subdivisions
of the MCD or CCD in which they are
12
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Table 2. (continued)
Statistical areas
Government units
a combined population of at least
50,000, provided that the county or
counties in which the city and
contiguous places are located has a
total population of at least 75,000.
• Central cities (of an SMSA): The
largest city of an SHSA is always a
central city. One or two additional
cities may be added to the SMSA title
and identified as central cities if:
(1) the additional city or cities have a
population of one-third or more of that
of the largest city and a minimum
population of 25,000 or (2) the
additional city has at least 250,000
inhabitants.
• Standard Consolidated Statistical Areas
(SCSAs): Two or more contiguous SHSAs
which meet certain criteria of
population size, urban character, social
and economic integration, and contiguity
of urbanized areas. Examples are:
Detroit-Ann Arbor, HI, Seattle-Tacoma,
WA, San Francisco-Oakland-San Jose, CA.
• Urbanized Areas (UAs): Contain a
central city (or twin cities) meeting
the same criteria as an SMSA, plus the
surrounding closely settled incorporated
and unincorporated areas which meet
certain criteria of population size or
density. UAs differ from SHSAs chiefly
by excluding the rural portions of
counties that make up the SHSAs as well
as those places that are separated by
rural territory from the densely
populated fringe around the central city.
located, for example, a village
located within and legally part of a
township. However, almost 4,000
incorporated places cross HCD and/or
county lines, but no incorporated
places cross state lines since they
are chartered under the laws of a
state. There were over 18,500
incorporated places in 1970.
Unincorporated places. These are
densely settled population centers
without legally defined corporate
limits or any other corporate powers
or functions. In 1970, statistics
were tabulated for each
unincorporated place with 5,000
inhabitants or more if located inside
an urbanized area, or with 1,000
inhabitants or more if located
outside an urbanized area.
13
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Table 2. (continued)
Statistical areas Government units
Urban and Rural Areas: Urban population
comprises all persons living in
urbanized areas and in places of 2,500
inhabitants or more outside urbanized
areas. The population not classified as
urban constitutes the rural population.
This is divided into rural-farm (all
rural households living on farms) and
rural nonfarm (remaining rural
population).
Census Designated Place (CDP): for the
1980 Census, CDPs will be used to
describe densely settled population
centers without legally defined limits
or corporate powers. CDPs, like
unincorporated places in 1970, contain a
dense, city-type street pattern and
ideally should have an overall
population density of at least 1,000
persons per square mile. In addition, a
CDP should be a community that can be
identified locally by place name, having
developed over the years from a small
commercial area or market center, rather
than encompassing a residential land
subdivision, apartment development, or
general urban expansion area.
Census Tracts: Generally, small,
relatively permanent areas into which
metropolitan and certain other areas are
divided. An average tract contains
about 4,000 residents. All SHSAs are
completely tracted.
Enumeration Districts (EDs): Areas
within census tracts, HCDs, and CCDs
with an average of about 800 people or
250 housing units. EDs are generally
used when block groups are not defined
for an area. Together with Block
Groups, the ED/BG category covers the
entire U.S.
14
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Table 2. (continued)
Statistical areas Government units
• Block Groups (BGs): This area is a
combination of contiguous blocks having
an average population of about 1,100.
BGs are subdivisions of census tracts.
• Blocks: A census block is a
well-defined piece of land, bounded by
streets, roads, railroad tracks,
streams, or other features on the
ground. Blocks do not cross census
tract boundaries, but may cross other
boundaries such as city limits. Blocks
are the smallest areas for which census
data are tabulated.
Source: U.S. Bureau of the Census 1979b.
15
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= STANDARD METROPOLITAN STATISTICAL AREA (SMSA)
= URBANIZED AREA. CONSISTS OF CENTRAL CITY AND URBAN FRINGE
(MAY IN RARE CASES EXTEND OUTSIDE OF SMSA BOUNDARY).
OTHER URBAN AREAS
UNSHADED AREAS INSIDE OR OUTSIDE OF SMSA BOUNDARIES ARE
CONSIDERED RURAL.
Figure 4. Geographic Organization of the Major Census Statistical Categories
16
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SMSA / Metropolitan Counties
Block
Nonmetropolitan County
Minor
Civil
Division
"S
Incorporated
Place
Enumeration
District
SOURCE: BUREAU OF THE CENSUS 1980a.
Figure 6. Census Geography For Metropolitan and Nonmetropolitan Counties
18
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The data collected 1n the 1980 Census of Population are 1n the
process of being released by the Census Bureau. The data are available
both 1n printed documents and on computer tape. Table 3 lists the
printed documents that are or will be available 1n the near future from
the Census Bureau.
The Number of Inhabitants (Series PC80-1-A) and General Population
Characteristics (Series PC80-1-B) are the most useful reports for
obtaining population data down to the town or township level. Both
documents are available according to state, and each Includes a separate
U.S. summary document. Number of Inhabitants provides only population
counts (I.e., no age and sex or other demographic data). General
Population Characteristics provides population counts by sex and by age
and sex as well as the other demographic data listed 1n Table 3 to the
same geographic resolution as Number of Inhabitants.
Detailed counts and characteristics within Standard Metropolitan
Statistical Areas (SMSAs) are available 1n Census Tracts (Series PHC80-2)
and Block Statistics (PHC80-1). Census Tracts will be Issued with
accompanying maps (for tract Identification) and will contain detailed
characteristics of the population (e.g., age, sex, race, education).
Census Tracts 1s available by the photocopied page, and by mid-1983
1t will be available on microfiche by SMSA (which 1s less expensive) and
on computer tape. If further resolution or detail 1s required, Block
Statistics may be consulted. This has been Issued 1n microfiche only
with accompanying maps both 1n print and on microfiche. Block Statistics
provides population counts only; further Information on population
characteristics 1s not available on such a detailed level.
Detailed demographic Information collected In the 20 percent sample
Census (long form) 1s available 1n the series General Soda! and Economic
Characteristics (PC80-1C) and Detailed Population Characteristics
(PC80-1-D). General Social and Economic Characteristics provides
demographic data to the town or township level of detail according to
states. A U.S. summary report 1s also Included 1n the series. Detailed
Population Characteristics 1s available by state, U.S. summary, and
SMSA. These two reports provide considerable Information on the
population characteristics previously listed 1n Table 1.
All of the Information sources previously discussed contain results
from the 1980 Census; they are available 1n most reference libraries.
Specific population data that have been collected 1n 1980 and that have
not yet been released may be obtained by calling the Population Division
of the Bureau of the Census (202-763-5002 or 5020).
19
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Table 3. Information on 1980 Census Reports: Their Geographical
Breakdown, Characteristics, and Expected Dates of Release
Series
Name
Geographical
breakdown
Characteristics
Expected dates
of release
PC80-1-A
(complete
count data
- 100%)
Number of inhabitants
(U.S. Summary and by
state)
PC80-1-B
(complete
count data
- 100%)
General Population
Characteristics
(U.S. Sumnary and by
state)
United States
Regions
Divisions
States
SCSAs, SMSAs
Urbanized areas
Incorporated places
Counties
County subdivisions
United States
Regions
Divisions
States
SCSAs, SMSAs
Urbanized areas
Places & towns/town-
ships of 1,000 or
more
Counties
Rural portion of
counties
Population
counts
Available
Population
counts by sex
Available
United States
States
SCSAs, SMSAs
Urbanized areas
Places & towns/
townships of
10,000 to 50,000
Places & towns/
townships of
2,500 to 10,000
Counties
Age and sex,
household type &
relationship,
type of family,
and marital status
20
-------
Table 3. (continued)
Series
PC80-1-C
(sample
estimate
data - 20%)
Name
General Social and
Economic Characteristics
(U.S. Summary and by
state)
Geographical
breakdown
United States
Regions
Divisions
States
Characteristics
Population
counts
Expected dates
of release
Hid to late
1983
SCSAs, SMSAs
Urbanized areas
Place & towns/
townships of
50,000 or more
Places & towns/
townships of
2,500 to 10,000
counties
United States
States
Counties
United States
States
States
SHSAsd
Urbanized areasd
Places & towns/
townships of
50,000 or mored
Central cities''
Places & towns/
townships of
10,000 to 50,000d
Counties
21
Population counts
for non-rural and
rural farms.
Age & sex, fertility,
household relation-
ship, education,
family composition,
nativity and place of
birth, residence in
1975, journey to work,
disability status,
veteran status, labor
force status, class of
worker, industry and
occupation, income and
poverty status.
Age & sex, fertility,
household relation-
ship, education, family
composition, marital
status, nativity &
place of birth, resi-
dence in 1975, journey
to work, disability
status, type of group
quarters, veteran
status, labor force status,
class of worker, industry 4
occupation, income &
poverty status.
-------
Table 3. (continued)
Series
PC80-1-D
(sample
estimate
data - 201)
Name
Detailed Population
Characteristics
(U.S. Summary and by
state)
Geographical
breakdown
United States
States
SHSAs of 250,000
or more
Characteristics
Cross- tabul at i ons
of social &
economic charac-
teristics by
age, sex, etc.
Expected dates
of release
Hid to late
1983
PHC80-2
(sample
estimate
data - 20%)
Census Tractsb
(U.S. Summary and by
SHSA)
States
SHSAs of 250,000
or more6
SHSAs
Central cities
Counties
Places of 10,000
or more
Census tracts
SHSAC
Counties0
Places of 10,000
or morec
Census tractsc
Social and
economic
characteristics
Population counts
(number of people
in each tract by
SHSA & other
tracted areas)
Late
1983
(currently
available on a
photocopy
basis)
Age and sex, fertility,
household relationship,
education, family com-
position, marital status,
nativity, language usage
and ability to speak
English, residence in
1975, journey to work,
disability status, labor
force status, industry
and occupation, income
and poverty status.
Structural equipment,
financial and household
characteristics of
housing units.
22
-------
Table 3. (continued)
Series Name
Geographical
breakdown
Expected elates
Characteristics of release
PH80-1
(complete
count data
- 100%)
Block Statistics3
(microfiche only; maps
printed - U.S. Sumnary
and by SMSA)
States
SMSAs
Counties
County Subdivisions
Places
Tracts
Blocks
Population counts
Available
Note: Data for towns/townships are shown for 11 states only: Maine, New Hampshire, Vermont,
Massachusetts, Rhode Island, Connecticut, New York, New Jersey, Pennsylvania, Michigan, and
Wisconsin.
aReport contains 100% data; race and Spanish origin data, where presented, are provisional.
bReport contains both 100% and sample data.
C0ata are shown only for those groups having 400 or more persons in the specific geographic area.
dQata for American Indian, Eskimo, and Aleut and Asian and Pacific Islander are shown for the
specific geographic area having 1,000 or more persons of the population group.
eData are shown only for those groups having 25,000 or more persons in the specific geographic
area.
Source: Bureau of the Census, Customer Services Branch; Washington, D.C. (202-763-4100).
23
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Another source of census Information 1s the computerized Summary Tape
Files (STFs). There are five basic files. STFs 1 and 2 are derived from
the complete-count part of the Census and reflect respondents' answers to
questions on the short form. STFs 3, 4, and 5 contain estimates derived
from the sample part of the Census (20 percent sample) and cover the full
range of topics represented on the long form. Although the source of
Information 1s the same, the STFs are designed to provide much greater
geographic and subject detail (e.g., age, sex, education, marital status)
than 1s feasible or desirable 1n printed reports. The STFs are only on
magnetic computer tape, with the exception of STF 1A, which 1s also
available on microfiche. Each of the five STFs 1s divided Into Parts A,
B, and C. Table 4 Illustrates the relationships between the 1980 printed
reports and STFs 1 through 5. Table 5 Illustrates the geography of each
file and Its three parts. Table 6 lists the geographical resolution that
will appear on the 1980 STFs, as well as the tentative schedule of
release for these files.
Several other types of computer tape files are also available for
population data (Bureau of the Census 1982a). Of particular Importance
1s the Master Area Reference File (MARF). MARF contains numeric codes
and names of all geographic areas used 1n the 1980 Census. The file also
contains population and housing data for each area 1n the file. Donnelly
Marketing, Incorporated, a subsidiary of Control Data Corporation, has
acquired the file and added geographic coordinates (latitude-longitude)
to all ED/BGs 1n MARF. This permits computerized mapping of the
population data. This file along with the proprietary geographic
coordinate data was recently purchased by EPA-OTS and entered Into Its
Graphical Exposure Modeling System (GEMS). EPA-OTS can now access,
aggregate, and manipulate 1980 population data as well as display the
geographic distribution of the data 1n conjunction with ambient
concentration data predicted by fate models. Details on MARF and Its
application as well as GEMS and the computerized concentration prediction
models are discussed 1n the next subsection.
The STFs and other computer tape files such as MARF are considerably
more expensive than printed reports. One STF reel (approximately one
state) costs $140 compared to $5 for comparable printed reports.
Computer tape files, however, Increase the versatility of the population
data; users can manipulate, aggregate, or otherwise extensively process
census data.
Another source of population data that can be very useful,
partlculary 1n the study of specific geographic areas, 1s census maps.
Census outline maps allow the Investigator to determine the geographic
distribution of populations 1n specific areas of Interest. Maps that are
available for use with 1980 census data vary according to the resolution
needed (refer to Figure 5) and conform to the geographic units already
described 1n Table 2. The census outline maps available for use with
1980 census data are summarized 1n Table 7.
24
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Count:
Table 6. Smallest Type of Area on 1980 Census Summary Tape Files
File A
(state-by-state)
File B
(state-by-state)
File C
(national)
Tentative dates
of release
STF 1
BG/ED
Blocks/EO
County, place of
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Available
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Tract
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County, place of Available
10,000 or more
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STF 3
BG/ED
County, place of
10,000 or more
STF 3A is available
STF 3B has been
cancelled
STF 3C expected in
mid 1983
STF 4
STF 5
Tract
Place of 2,500
or more, MCD/CCD
SHSA, County of
50,000 or more,
place of 50,000
or more
County, place of
10,000 or more
Hid to late
1983
Late 1983
Source: Customer Services Division, Bureau of the Census (202-763-4100).
27
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28
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The metropolitan, tract outline, and county subdivision maps are the
key census maps for correlating 1980 census data to sites 1n urban or
rural areas. These map series are Issued separately or with specific
census publications. Examples of census outline maps for metropolitan
and non-metropolitan areas are presented 1n Figure 7.
Additionally, the Census Bureau Issues several series of statistical
maps and graphic summaries that display census data 1n map form. The map
series 1n this category Include the 6E-50, GE-70, and 6E-80 (Urban Atlas)
series. These maps, of varying sizes and scales, utilize color schemes
to Illustrate population and other social and economic census data.
All printed census matter 1s available for purchase through the
Government Printing Office (GPO); all series Issued on microfiche, maps,
computer tapes, and technical documentation are available directly from
the Customer Services Branch at the Bureau of the Census, Department of
Commerce, Washington, D.C. These series can be ordered by calling
(202) 763-4100 (Customer Services Branch).
The Bureau of the Census will also prepare, on a cost reimbursable
basis, special tabulations of data from the 1980 Census based on customer
specifications. Such tabulations can cover any specific geographic or
subject matter area as long as the requests do not violate
confidentiality restrictions. These types of reports are expensive and
may require considerable time to produce. Standard reports, tapes, and
microfiche should be used whenever possible.
A complete description of the documents and services available from
the Bureau of the Census 1s not within the scope of this volume. This
subsection has attempted to briefly describe the documents and data files
that would be of most use towards enumerating populations exposed to
chemical substances 1n the ambient environment. For more detailed
descriptions of the documents and data files previously discussed, or for
Information on other services available from the Bureau of the Census,
the Investigator should contact:
Data User Services Division
Bureau of the Census
Washington, DC 20233
(202) 763-4100
A detailed 11st of contacts for census data Information 1s provided 1n
Figure 8.
The population data discussed 1n this report reflect Information
collected 1n 1980, and, therefore, are not up-to-date. Population data
for large statistical reporting areas or categories (e.g., regions,
divisions, states, urban areas, SMSAs) will not have changed
29
-------
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-------
TELEPHONE CONTACTS
FOR DATA USERS
BUREAU OF THE CENSUS
U.S. Department of Commerce • Bureau of the Census • Washington, D.C. 20233 November 1981
No. 20
Director Bruce Chapman (301 )763-5190
Deputy Director Daniel B. Levine 763-5192
Associate Director for Administration James D. Lincoln 763-7980
Associate Director for Demographic Fields Meyer Zitter, Actg. 763-5167
Associate Director for Economic Fields Shirley Kallek 763-5274
Associate Director for Field Operations C. Louis Kincannon, Actg. 763-7247
Associate Director for Information Technology *• Bruce Ramsay 763-5180
Associate Director for Statistical Standards and Methodology... Barbara A. Bailar 763-2562
Assistant Director for Administration 0. Bryant Benton 763-2350
Assistant Director for Computer Services Howard Hamilton 763-2360
Assistant Director for Demographic Censuses Peter A. Bounpane 763-7670
Assistant Director for Economic and Agriculture Censuses Michael G. Farrell 763-7356
Assistant Director for International Programs Meyer Zitter 763-5167
Assistant Director for Processing C. Louis Kincannon 763-7247
Assistant Director for Statistical Research Roger H. Moore 763-3807
Congressional Liaison Pennie Harvison 763-5360
Data User Services Division Staff 899-7600
Public Information Office Staff 763-4040
DEMOGRAPHIC FIELDS
Center for Demographic Studies CDS James R. Wetzel, Chief 763-7720
Decennial Census Division DCD Peter Bounpane, Actg. Chief 763-7670
Demographic Surveys Division DSD Thomas C. Walsh, Chief 763-2777
Foreign Demographic Analysis Division FDA Samuel Baum, Actg. Chief 763-4010
Housing Division HOUS Arthur F. Young, Chief (301)763-2863
International Demographic Data Center IDDC Samuel Baum, Chief 763-2870
International Statistical Programs Center ISPC Robert 0. Bartram, Chief 763-2832
Population Division POP Roger A. Herriot, Chief 763-7646
Statistical Methods Division SMD Charles D. Jones, Chief 763-2672
Population and Housing Subjects
Age and Sex:
States (age only) POP Marianne Roberts 763-5072
United States POP Louisa Miller 763-5184
Aliens POP Jennifer Marks 763-5184
Annexation Population Counts POP Joel Miller 763-7955
Apportionment POP Robert Speaker 763-7955
Births and Birth Expectations; Fertility Statistics POP Martin O'Connell 763-5303
Census Tracts:
Boundary Information GEOO Alice Winterfeld 763-7291
Census Data POP Johanna Barten 763-5002/5020
Citizenship:
Foreign Born Persons, Country of Birth;
Foreign Stock Persons POP Elmore Seraile 763-7571
Commuting:
Means of Transportation; Place of Work POP Philip Fulton 763-3850
Congressional Districts:
Census Data POP Johanna Barten 763-5002/5020
Address Locations GEOG Ernie Swapshur 763-5437
Population Estimates POP Donald Starsinlc 763-5072
Consumer Expenditure Survey DSD Gail Hoff 763-2764
Consumer Purchases and Ownership of Durables POP Jack McNeil 763-5032
Crime Surveys:
Data Analysis and Publication CDS Adolfo Paez 763-1765
Victimization, General Information DSD Robert Tinari 763-1735
Current Population Survey DSD Gregory Russell 763-2773
(See detailed listing on page 2 for Population Estimates)
Decennial Census:
Content and Tabulations DCD Earl Knapp 763-1840
Count Complaints DCD Ann Liddle 763-3814
General DCD Rachel F. Brown 763-2748
Minority Statistics Program DCD Alfred Hawkins 763-5987
•••••^•^^•^••••••^•••••••MBH Figure 3 ^^mm^^m^^mmmmmm^mmmi^mmm^mmmmmm
31
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Population and Housing Subjects-Con.
Decennial Census—con.
Special Tabulations:
Population Data POP Paula Schneider 763-7962
Housing Data HOUS Bill Downs 763-2873
Disability POP Jack McNeil 763-5032
Education; School Enrollment and Social Stratification POP Paul Siegel 763-5050
Employment; Unemployment; Labor Force POP T. Palumbo/V. Valdlsera 763-2825
Farm Population POP Diana DeAre 763-7955
Health Surveys DSD Robert Mangold 763-5508
Households and Families:
Marriage and Divorce POP James Weed 763-7950
Projections POP Robert Grymes 763-7950
Size; Number; Social Characteristics POP Steve Rawlings 763-7950
Housing:
Annual Housing Survey HOUS Edward Montfort 763-2881
Components of Inventory Change Survey HOUS Elmo Beach • 763-1096
Contract Block Program HOUS Richard Knapp 763-2873
Housing Information, Decennial Census HOUS Bill Downs 763-2873
Housing Vacancy Data HOUS Stanley Rolark 763-2880
Market Absorption HOUS Charles Clark 763-2866
Residential Finance HOUS Peter Fronczek 763-2866
(See also Economic Subjects—Construction Statistics)
Income Statistics:
Current Surveys POP M. Henson/E. Welniak 763-5060
Decennial Statistics POP G. Patterson/R. Sanders 763-5060
Household POP Robert Cleveland 763-5060
Revenue Sharing POP Dan Burkhead 763-5060
Incorporated/Unincorporated Places POP Joel Miller 763-7955
Industry and Occupation Statistics
(See also Economic Fields) POP John Priebe/Paula Vines 763-5144
Institutional Population POP Arlene Saluter 763-7950
International Population POP Samuel Baura 763-2870
Language, Current; Mother Tongue POP Paul Siegel 763-5050
Longitudinal Surveys DSD George Gray 763-2764
Marital Status; Living Arrangements POP Arlene Saluter 763-7950
Metropolitan Areas (see SMSA's)
Migration POP Kristin Hansen 763-3850
Neighborhood Statistics DCD Joanne Eitzen 763-1818
Outlying Areas (Puerto Rico, etc.) POP Jennifer Marks 763-5184
Population:
General Information; Published Data from Censuses,
Surveys, Estimates, and Projections POP Johanna Barten 763-5020(TDY)/763-5002
Population Estimates Methodology:
Congressional Districts; SMSA's POP Donald Starsinic 763-5072
Counties; Federal-State Cooperative
Program for Local Population Estimates POP Fred Cavanaugh 763-7722
Estimates Research POP Richard Irwin 763-7883
Local Areas; Revenue Sharing POP Fred Cavanaugh 763-7722
States POP Marianne Roberts 763-5072
United States (National) POP Louisa Miller 763-5184
Population Projections Methodology:
National POP Gregory Spencer 763-5021
State POP Signe Wetrogan 763-5021
Poverty Statistics POP Arno Winard 763-5790
Current Surveys POP Carol Fendler 763-5790
Decennial Census/Poverty Areas POP Thomas Gelinne 763-5790
Prisoner Surveys:
National Prisoner Statistics DSD Chester A. Bowie 763-2380
Data Analysis and Publication CDS John Wallerstedt 763-7968
Race and Ethnic Statistics: POP Nampeo McKenney 763-7890
American Indian Population POP K. Crook/E. Paisano 763-5910/-7572
Asian Americans POP P. Berman/P. Johnson 763-2607
Black Population POP D. Johnson/T. King 763-7572
Ethnic Populations POP Elmore Seraile 763-7571
Race POP Patricia Berraan 763-2607
Spanish Population POP Edward Fernandez 763-5219
Religion POP Elmore Seraile 763-7571
Revenue Sharing (See Incone Statistics; Population:
General Information; Population Estimates
Methodology; Economic Fields—Governments)
Sampling Methods SMD Charles Jones 763-2672
Social Indicators CDS John Deshaies 763-2490
Social Stratification POP Paul Siegel 763-5050
Special Population Censuses DCD George Hum 763-5806
Special Surveys DSD Linda R. Murphy 763-2061
SMSA's:
Census and Estimates Data; Current Definitions POP Johanna Barten 763-5002/5020
Mew Criteria POP Richard Forstall 763-5591
Travel Surveys DSD Ron Dopkowski 763-1798
Urban/Rural Residence POP Diana DeAre 763-7955
Veteran Status POP Mark Littman 753-7962
Voting and Registration POP Jerry Jennings 763-ol79
Voting Rights POP Gilbert Felton 763-5313
Figure 8 (continued)i
32
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ECONOMIC FIELDS
Agriculture Division AGR Arnold Bol lenbacher, Chief (301)763-5230
Business Division BUS Vacant 763-7564
Construction Statistics Division CSD Leonora M. Gross, Chief 763-7163
Economic Census Staff ECS Michael G. Farrell, Chief 763-7356
Economic Surveys Division ESD W. Joel Richardson, Chief 763-7735
Foreign Trade Division FTD Emanuel A. Lipscomb, Chief 763-5342
Governments Division GOVS John Coleman, Chief 763-7366
Industry Division IND Roger H. Bugenhagen, Chief 763-5850
Economic Subjects
Agriculture:
Crop Statistics AGR Donald Jahnke 763-1939
Farm Economics AGR John Blackledge 763-5819
General Information AGR Arnold Bollenbacher 763-5170
Livestock Statistics AGR Thomas Monroe 763-1081
Puerto Rico, Guam, etc AGR Kenneth Norell 763-5914
Construction Statistics:
Census/Industries Surveys CSD Alan Blum 763-5435
Special Trades; Contractors; General Contractor
Built CSD Andrew Visnansky 763-7547
Construction Authorized by Building Permits
(C40 Series) and Residential Demolitions
(C45 Series) CSD David Fondelier 763-7244
Current Programs CSD William Mittendorf 763-7165
Expenditures on Residential Additions, Alterations,
Maintenance and Repairs, and Replacements
(C50 Series) CSD George Roff 763-5717
New Residential Construction:
Housing Starts (C20 Series) CSD Barry Rappaport 763-7842
Housing Completions (C22 Series) CSD Juliana Van Berkum 763-7843
In Selected SMSA' s (C21 Series) CSD Diana Farrelly 763-7842
Sales of New One-Family Homes (C25 Series) CSD Steve Berman 763-5731
"rice Index for New One Family Homes (C27 Series)... CSD Dorothy Walton 763-7314
Characteristics of New Housing (C25 Annual Report).. CSD Dale Jacobson 763-5732
Value of New Construction Put in Place (C30 Series) CSD Allan Meyer 763-5717
County Business Patterns ESD Stanley Hyman 763-7642
Employment/Unemployment Statistics POP T. Palumbo/V. Valdisera 763-2825
Energy Related Statistics DIRS Elmer S. Biles 763-7184
Enterprise Statistics ESD John Dodds. 763-7086
Foreign Trade Information FTD Juanita Noone 763-5140
Governments:
Criminal Justice Statistics GOVS Diana Cull 763-2842
Fastern States Government Sector GOVS G. Beaven/G.Speight 763-5017/-2890
Employment GOVS Alan Stevens 763-5086
Finance GOVS Vancil Kane 763-5847
Governmental Organization and Special Projects GOVS Muriel Miller 763-5308
Revenue Sharing (See also Demographic Fields) GOVS John Coleman 763-5272
Taxation GOVS John Behrens 763-2844
Wescern States Government Sector GOVS Ulvey Harris 763-5344
Industry and Commodities Classification ESD Walter Neece 763-1935
Manufactures:
Census/Annual Survey of Manufactures IND B. J. Fitzpatrick 763-1503
Durables '. IND Dale Gordon 763-7304
Nondurables IND Michael Zampogna 763-2510
Subject Reports (Concentration, Production
Index, Water, etc.) IND John Govoni 763-7665
Current Programs IND John Wikoff 763-7800
Durables IND Malcolm Burnhardt 763-2518
Environmental Surveys IND Wayne McCaughey 763-5616
Fuels/Electric Energy Consumed by Manufactures IND John 'McNamee 763-5938
Nondurables IND Elinor Champion 763-5911
Origin of Exports IND John Govoni 763-7666
Shipments, Inventories, and Orders IND Ruth Runyan 763-2502
Mineral Industries IND John McNamee 763-5938
Minority Businesses ESD Jerry McDonald 763-5182
Puerto Rico:
Censuses of Retail Trade, Wholesale Trade, and
Selected Service Industries BUS Alvin Barten 763-5282
Retail Trade:
Annual Retail Trade Report, Advance Monthly
Retail Sales, Monthly Retail Inventories Survey BUS Irving True 763-7S60
Census BUS Dennis Pike 763-7038
Monthlv Retail Trade Report: Accounts
Receivable; and Monthly Department Store Sales BUS Irving True 763-7660
Service Industries:
Census BUS Sid Marcus 763-7039
Current Selected Services Reports BUS Edward Gutbrod 763-7026
Transportation:
Commodity Transportation Survey; Truck
Inventory and Use; Domestic Movement
of Foreign Trade Data ESD Robert Torene 763-5430
Wholesale Trade:
Census BUS John Trimble 763-5281
Current Wholesale Sales and Inventories;
Green Coffee Survey; Canned Food Survev BUS Ronald Piencykoski 763-7007
Figure 8 (continued)'
33
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GEOGRAPHY AND STATISTICAL RESEARCH
Geography Division GEO Stanley Matchett, Chief
Statistical Research Division 3RD Roger H. Moore, Chief
Boundaries and Annexations GEO Brian Scott
Census Geography 1970/1980; Geographic Concepts GEO Staff
Computer Graphics and Computer Mapping GEO Frederick Broome
Congressional District Component Areas, Atlas GEO Kevin Shaw
Earth Resources Satellite Technology:
International GEO Robert Durland
United States GEO James Davis
GBF/DIME System GEO Staff
Area Measurement and Centers of Population GEO Roy Borgstede
Geographic Statistical Areas GEO Staff
Census Maps GEO Staff
Revenue Sharing Geography GEO Bob Bakondi
Survey Methodology Information System SRD Patricia Fuellhart
USER SERVICES
Administrative Services Division ASD Robert L. Kirkland, Chief
Data User Services Division DUSD Michael G. Garland, Chief
Field Division FLD Lawrence T. Love, Chief
Age Search - Access to Personal Census Records DUSD Christine Stewart
Bureau of the Census Catalog DUSD Ann King
Census Procedures, History of DUSD Frederick Bohme
Clearinghouse for Census Data Services DUSD John Kavallunas
College Curriculum Support Project DUSD Les Solomon
Computer Tapes DUSD Customer Services
Data User News (Monthly Newsletter) DUSD Neil Tlllman
Data User Training:
Registration DUSD Dorothy Chin
Seminars, Workshops, Conferences DUSD Deborah Barrett
Directory of Data Files DUSD Customer Services
Exhibits DUSD Douglas Moyer
Guides and Directories DUSD Gary Young
Library ASD Betty Baxtresser
Circulation ASD Jim Thome
Interlibrary Loan ASD Staff
Out of Print Publications ASD Maria Brown
Reference Service ASD Grace Waibel
Map Orders DUSD Customer Services
Microfilm/Microfiche DUSD Customer Services
Public Use Samples (Microdata) DUSD Paul Zeisset
Reapportionment/Redistricting DUSD Cathy Talbert
State Data Center Program DUSD Larry Carbaugh
Statistical Compendia DUSD Glenn King
Publication Orders (Subscriber Services) DUSD Customer Services
User Software (CENSPAC, ADMATCH, etc.) DUSD Larry Finnegan
(301)763-5636
763-3807
763-5437
763-5720
763-7442
763-5437
763-2034
763-5808
763-7315
763-7856
763-2364
763-7818
763-5437
763-7600
763-5400
899-7620
763-5000
899-7625
899-7672
899-7625
899-7732
899-7755
899-7600
899-7670
899-7645
899-7645
899-7600
899-7665
899-7670
763-5040
763-1175
763-1930
763-5511
763-5042
899-7600
899-7600
899-7618
899-7631
899-7732
899-7650
899-7600
899-7634
Regional Assistance
Census Bureau
Regional Offices
Atlanta, GA
Boston, MA
Charlotte, NC
Chicago, IL
Dallas, TX
Denver, CO
Detroit, MI
Kansas City, KS
Los Angeles, CA
New York, NY
Philadelphia, PA
Seattle, WA
Information
Services
Specialists
404/881-3312
617/223-0226
704/371-6144
312/353-0980
214/767-0625
303/234-5825
313/226-4675
816/374-4601
213/824-7291
212/264-4730
215/597-8313
206/442-1560
Census Bureau
Satellite Offices
Birmingham, AL
Cincinnati, OH
Columbia, SC
Houston, TX
Miami, FL
San Antonio, TX
San Francisco, CA
Washington, DC
Information
Services
Specialists
205/254-0040
513/684-2448
803/765-5435
713/226-5457
305/350-4064
512/229-6018
415/556-6372
301/763-5830
Listing of Telephone Contacts for Data Users compiled by Carolyn Grace, User Training Branch, Data User
Services Division, Bureau of the Census. Write for additional copies, or call 301/899-7645.
Figure 8 (continued)i
34
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significantly since the data were collected. Population estimates for
these areas are published each year 1n Statistical Abstract of the U.S.
(Bureau of the Census 1982b). Population data for detailed geographic
areas (e.g., census tracts, enumeration districts, block groups),
however, may have changed significantly since the data were collected.
The Bureau of the Census does keep records of major population shifts and
also has developed procedures and methodologies to estimate populations
for periods between the decennial Censuses. A description of the
procedures and methodologies 1s not within the scope of work of this
volume. Information on these subjects may, however, be obtained from the
Bureau of the Census at the above listed address.
2.3.2 Enumeration of Populations Exposed via Inhalation
As discussed 1n Subsection 2.2, populations exposed to chemical
substances 1n the ambient environment via the Inhalation route are
Identified on the basis of their geographic location with respect to the
atmospheric source of the chemical substances. Atmospheric sources
Include airborne releases resulting from Industrial processes, consumer
products, disposal, Incineration, transportation activities (e.g., spills
and vehicular exhausts), stationary combustion processes (e.g., home
heating), and airborne releases of unknown origin.
For the purposes of predicting ambient concentrations of the chemical
substance and for purposes of Identifying the population exposed, these
atmospheric sources are divided Into three categories: (1) point
sources, (2) area sources, and (3) line sources. The following
subsections present methods for enumerating the Identified population 1n
each of these three source categories. The methods have been developed
keeping 1n mind the atmospheric modeling tools available to EPA and the
major data bases that contain population Information (discussed 1n the
preceding section). The methods recommended have also been developed
after consideration of the strengths and weaknesses of previous
enumeration efforts or on-going efforts 1n other EPA offices. The
following discussions, therefore, also Include a review of any historical
methods considered relevant to the recommended procedures.
(1) Point Sources. This subsection presents a procedure for
enumerating populations exposed to atmospheric concentrations of chemical
substances released from point sources. This subsection also presents a
procedure to enumerate populations around point sources that are too
numerous to deal with Individually. These are called prototype point
sources or, as frequently cited 1n the literature, general point
sources. Both procedures Initially rely on the estimate of atmospheric
concentrations via a computer based atmospheric fate model. The
acquisition of the population data 1s, however, operationally different.
Enumeration of exposed populations around point sources requires
35
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site-specific population data. Enumeration of populations around
prototype point sources uses population density data for different Census
defined geographic statistical categories depending on where the sources
are located.
The recommended procedure for enumerating exposed populations around
point sources 1s to use an Integrated computer based fate model and
population data retrieval program known as ATM-SECPOP, developed by the
EPA Office of Toxic Substances, Exposure Evaluation Division (OTS-EED),
and General Software Corporation. ATM-SECPOP Integrates the output of a
concentration prediction model, a population distribution data base, and
graphic and mapping Information displays. The Integration affords a
rapid and efficient means of generating and presenting exposure-related
data resulting from the airborne release of chemical substances from
point sources.
ATM-SECPOP estimates concentrations of chemical substances and
enumerates the population exposed to these concentrations around point
sources that release the chemical to air. The program combines the
output of the Atmospheric Transport Model (ATM) (Patterson et al. 1982)
and population data contained 1n the proprietary 1980 Master Area
Reference File (MARF) (1980 Census Data) which 1s accessed via a
population distribution model called SECPOP.
ATM calculates pollutant concentrations around a point source by
combining data on the facility location, data on emission source
characteristics, physlochemlcal data on the chemical of Interest, and
stored data on localized meteorological conditions. Pollutant
concentrations are estimated for radial sectors around the point source
as delineated by axes running 1n the 16 compass directions and 10
concentric rings at 0.5, 1, 2, 3, 4, 5, 10, 15, 25, and 50 kilometers
from the source (Illustrated 1n Figure 9). Concentrations are,
therefore, calculated for a total of 160 sectors around the source. The
user also has the option to specify the ring distances to which
concentrations of the chemical substance will be calculated. Detailed
Information on the application and data Input requirements of ATM are
provided 1n Volume 2 of this series and 1n the GEMS Users Manual (GSC
1983).
MARF 1s a data file released by the Bureau of the Census, as
previously discussed 1n Subsection 2.3.1, to which Donnelly Marketing,
Incorporated has added the latitude-longitude coordinates of all ED/BGs
1n the U.S. The 1980 population and housing data 1n the file, therefore,
may be accessed for geographic exposure analysis. The file contains
records for states, counties, county subdivisions, places, census tracts,
enumeration districts (EDs) 1n unblocked areas, and block groups 1n
36
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50km
NW
WNW
WSW
SEGMENT
CONCENTRATION
BASED ON AVERAGE
OF 4 CONCENTRATIONS
WITHIN EACH SECTOR
NNW
NNE
NE
ENE
ESE
ONE RADIAL SECTOR
Figure 9. Wind Rose Sectors for ATM-SECPOP
37
-------
blocked areas. Each record shows the total population by five race
groups, population of Spanish origin, number of housing units, number of
households, and number of families.
OTS-EED has recently acquired MARF and entered It Into their
Graphical Exposure Modeling System (GEMS) (GSC 1983). The file has been
Integrated with ATM via the SECPOP program. The SECPOP program retrieves
the number of people or housing units within each radial sector defined
by ATM. The concentration and population data are combined to provide
tables on the estimated number of people exposed at various concentration
levels. Figure 10 1s a sample summary table of the output of an
ATM-SECPOP model run.
GEMS also has graphic display capabilities. These functions may be
used to Illustrate the relationship of variables such as the distribution
of exposure or concentration versus distance for any or all directions
around a facility. GEMS provides prompts to the user to help 1n
Identifying other variables, which may be graphically displayed. Graphic
displays may be 1n the form of bar charts and scatter plots as
Illustrated 1n Figures 11, and 12. The relative value of variables may
also be displayed 1n "Rose" diagrams as Illustrated 1n Figure 13. GEMS
also has mapping capabilities for use 1n displaying the geographic
distribution of ED/BGs around a facility as Illustrated 1n Figure 14. A
complete description of GEMS' capabilities 1s provided 1n the GEMS Users
Manual (GSC 1983). Because of the proprietary nature of the data
contained 1n MARF, ATM-SECPOP's use 1s restricted to personnel and
contractors of EPA-OTS. Special arrangements for outside parties to use
the data are, however, available. Inquiries should be directed to the
Chemical Fate Branch Modeling Team of EPA-OTS.
Method 2-2 summarizes the data requirements and steps necessary to
enumerate populations via the ATM-SECPOP program. A complete sample
computer run of ATM-SECPOP for the point source emission of
trlchloroethane 1s provided 1n Appendix A-l to this report.
The MARF data retrieved by SECPOP do not Include the distribution by
age and sex of the populations within the sectors, nor do they contain
the additional census data 1n the 20 percent census count such as
occupation, Income, travel time, and form of transportation. This
Information must currently be obtained from forthcoming Census Bureau
publications or STF 3 as discussed 1n Section 2.3.1 of this report.
Numerous private sources of population data are also available; marketing
companies can provide demographic data for particular geographic areas
for a fee.
Point sources may at times be too numerous to deal with
Individually. This must be determined on a case-by-case basis and may be
due to financial and manpower limitations or because the specific
38
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Method 2-2. Enumeration of Populations Exposed via Inhalation
to Atmospheric Concentrations of Chemical Substances
Released from Point Sources
Step 1 Identify the location of the point source(s). Locations can be
identified by latitude-longitude or by ZIP code. Latitude-longitude
of point source(s) is preferred for reasons of accuracy.
Step 2 The investigator has the option to obtain: (1) concentration and
exposed population data via ATM-SECPOP or (2) only population data
within radii and sectors around a point source via SECPOP. For
population data only, proceed to Step 3. To estimate the atmospheric
concentration of the chemical substance around the point source(s)
via ATM, it will be necessary to gather site-specific or generic
emission characteristics of the point source(s) and chemical
substance of interest. It will also be necessary to gather
information on the physiochemical properties of the chemical
substance. Volume 2 of this series discusses sources of information
on site-specific and generic emission characteristics, and
physiochemical properties of chemical substances required for ATM.
Step 3 Run ATM-SECPOP. The user must log on the GEMS system at 484-4540 or
4541 with an appropriate account number and password. GEMS is a
"user friendly" system and will prompt the user according to the
required data entries and available default values. Information on
GEMS or ATM-SECPOP may be obtained from the GEMS User's Manual (GSC
1983) or from the EPA-Chemical Fate Branch Modeling Team, Exposure
Evaluation Division, Office of Toxic Substances. Concentration
results can be plotted graphically against population data. The
investigator should consult graphic capabilities of GEMS.
To access population data only, the user, on the first operational
prompt, should enter GEODATA HANDLING (GH) operation, then either the
Census Data (CD) or Radii-5 (R) procedure to generate a data table or
map display, respectively. Follow prompts for entering
latitude-longitude (or ZIP code) and the band or distance from the
source for which population data are desired. The data resulting
from the Census Data procedure will be population count and number of
housing units in tabular form. If the user requires the data to be
plotted on a map (see Figure 14) and aggregated by distance and
direction, he should enter RADII 5 in place of code CD
Note: The EPA-OTS Chemical Fate Branch Modeling Team can also extract
population records by state and region from MARF for specific
exposure assessment efforts. Population data can then be retrieved
by the user according to counties (using FIPS code) and SMSAs. The
modeling team requires advance notice for this type of operation
because it is more complex then the two previously described
procedures.
44
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locations of the point sources are unknown. Preliminary exposure
assessments may also require only order-of-magn1tude estimates of
concentrations and exposed populations. In each of these cases, the
estimation of "atmospheric concentrations of a substance can be b'ased on
the development of a prototype point source. Generic emission
characteristics representative of the point sources of Interest are
gathered, and concentrations are modeled via ATM for one or a series of
locations to represent the range of possible ambient air concentrations
around the sources. Volume 2 of this series provides a detailed
discussion on the development of prototype point sources.
The enumeration of exposed populations also depends on the
development of a prototype. The population prototype 1n turn depends on
area and the estimated population density for each of the ATM-defined
radial sectors (see Figure 9). The product obtained by multiplying these
two pieces of data 1s an average population for the radial sector of
Interest. The populations within sectors are then aggregated for radial
sectors of equal atmospheric concentration.
Several levels of effort are possible 1n enumerating populations
around prototype point sources. The level of effort 1s determined by the
available locatlonal Information for the point sources of Interest. The
population prototype can be developed with the following population
density data:
1. Specific SMSA population densities.
2. Regional population densities.
3. National population density.
4. Regional or national population densities for Census defined
geographic statistical categories (I.e., urban, metropolitan,
and rural).
If the point sources of Interest can be located according to SMSAs,
the specific SMSA population density should be used to create the
prototype. SMSA population densities can be obtained from the U.S.
summary for Number of Inhabitants (Bureau of the Census 1983a) or General
Population Characteristics (Bureau of the Census 1983b). Statistical
Abstract of the U.S. (Bureau of the Census 1982b) also provides the land
area and yearly updates of the population for each of the SMSAs 1n the
U.S., from which up-to-date SMSA population densities can be calculated.
If the point sources of Interest can be located only according to
regions or 1f locatlonal data are completely lacking, regional or
45
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national population densities can be used to calculate the average
population 1n each of the ATM radial sectors. Population densities for
regions and the U.S. are listed 1n Table 8.
If the location of the point sources can be determined according to
the Census defined geographic statistical categories (e.g., urbanized,
metropolitan (SMSAs), or nonmetropolltan), the population densities for
each of these categories should be used to create a population
prototype. To Illustrate this approach, prototypes for sources located
1n urbanized, metropolitan, and nonmetropolltan areas have been created.
This was accomplished as previously mentioned by calculating the land
area of each radial sector defined by ATM and then multiplying the area
by the respective population density of the geographic category.
Population densities of 1,033 persons/km2 for urbanized*, 120
persons/km2 for metropolitan (SMSAs), and 8 persons/km2 for
non-metropolitan areas were used (Bureau of the Census 1981b). Results
of these calculations are presented 1n Table 9. It 1s Important to note
that when the population prototypes for urbanized and metropolitan areas
were calculated, the respective densities were only applied to the radial
sectors within radial rings that correspond to the average radius of
urbanized and metropolitan areas. The average rad11 of 8 km and 26 km
for urbanized and metropolitan areas 1n the U.S., respectively, were
calculated by dividing the total U.S. land area for each category by the
number of areas 1n the U.S. of each (Bureau of the Census 1981b). This
average area was assumed to equal the area of a circle 1n order to
back-calculate the radius.
The enumeration of populations exposed to chemical substances
released from prototype point sources known to be located In one of these
statistical categories 1s now possible by using the results presented 1n
Table 9. The population estimates for each radial sector should be
linked to the ATM-calculated concentration estimates for each sector (or
radial ring) of the prototype point source. Populations should then be
summed for all sectors of equal concentration to estimate the total
exposed population for each concentration. These results are then
multiplied by the number of sources to calculate the total population
exposure distribution 1n the U.S. Method 2-3 summarizes the basic
procedural steps for enumerating populations around prototype point
sources.
This procedure 1s an approach to enumerating populations exposed via
Inhalation to atmospheric concentrations of chemical substances released
from point sources too numerous to deal with Individually. Each exposure
assessment for a chemical substance should have an approach tailored to
the available Information for the point sources and chemical substance of
*Joel Miller, Populations Section, Bureau of the Census, personal
communication with Douglas D1xon, Versar Inc., April 1983.
46
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Table 8. Population Densities for the Different Census
Bureau Area Classifications and Regions
Density
Region/classification (persons/km2)
U.S. 251
Metropolitan 120^
Nonmetropoli tan 81
Northeast 1161
Metropolitan 29I1
Nonmetropol i tan 27]
North Central 301
Metropolitan 1301
Nonmetropoli tan 111
South 33}
Metropolitan 1021
Nonmetropoli tan 151
West 101
Metropolitan 76 ^
Nonmetropolitan 2^
Urban 8732
In Urbanized Areas 1.0332
Central Cities 1,3712
Urban Fringe 8402
Other Urban 49I2
Rural 72
^Bureau of Census, 1981a.
Preliminary unpublished data based on 1980 Census and updated census
geography from Joel Miller, Bureau of the Census, Population Section
(763-7955).
47
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Table 9. Average U.S. Population Size for ATM-SECPOP
Concentration Sectors for General Point
Sources Located in Urbanized, Metropolitan,
and Nonmetropoli tan Area
Radial sector population
Distance of boundary
arc from source, r (km)
0.5
1.0
2.0
3.0
4.0
5.0
10.0
15.0
25.0
50.0
Radial sector
land area (km^)
0.05
0.15
0.59
0.98
1.37
1.77
14.72
24.53
78.50
367.97
Urbanized
521
1551
609 1
1.0121
1.4151
1 .8281
8.7602
2.9403
9.4203
4.0674
Metropolitan
6
18
71
118
164
212
1,770
2,940
9,420
4.0674
Nonmetropol i tan
1
1
5
8
11
14
118
196
628
2,944
^Sector population calculated using the density of urbanized areas of 1,033 persons/km^.
^Sector population calculated using the density of urbanized areas of 1,033 persons/km2
to a radius of 8 km and the metropolitan density of 120 persons/km^ to the remaining area
within 10 km.
^Sector population calculated using the metropolitan density of 120 persons/km^.
^Sector population calculated using the metropolitan density of 120 persons/km^ to a
radius of 26 km and the nonmetropolitan density of 8 persons/km^ beyond 26 km.
48
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Method 2-3 Enumeration of Populations Exposed via Inhalation
to Chemical Substances Released from Prototype
Point Sources
Step 1 The materials balance or information on the production and use of a
chemical substance will identify the number of point sources to be
considered. The location of these sources should be further
identified according to cities, SMSAs, regions, counties, or a Census
defined geographic statistical category (e.g., urbanized,
metropolitan, or non-metropolitan). Volume 2 of this series provides
information on data bases, documents, and associations that may aid
in locating point sources.
Step 2 Using generic emission characteristics and site-specific
meteorological data stored in GEMS that is representative of
conditions around a typical facility, perform an ATM run (see Method
2-2). Volume 2 of this series also provides detailed information on
the development of prototype point sources. The GEMS Users Manual
(GSC 1983) describes meterological data stored to support ATM
simulations.
Step 3 Using population densities for the locations of the point sources
(e.g., SMSAs, regions) or the data in Table 9, calculate or record
the average population for each radial sector or within each radial
ring (radial sector population X16). The population in each radial
sector or ring should then be matched to the concentration or range
of concentrations predicted for each radial sector or ring around the
prototype point source. Populations should then be aggregated for
all radial sectors or rings of equal concentration.
Step 4 Multiply the Step 3 results by the total number of point sources in
the U.S. to enumerate the total exposed population at each
concentration or possible range of concentrations.
49
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Interest. The approach should also be developed according to the level
of detail required and should obviously be within the time, financial,
and manpower constraints of the effort.
(2) Area Sources. Area sources are sources of atmospheric release
of chemical substances so numerous that patterns of concentration can be
efficiently analyzed only as a group. Area sources may be either
stationary, such as home heating systems, or mobile, such as vehicles.
The usual approach to modeling area source emissions 1s to assume that
the emissions are uniformly distributed within a geographic area.
Emission rates per unit area (or per capita, household, or vehicle) are
estimated, and resulting concentrations for the geographic area are
calculated using an appropriate area source model or algorithm. Volume 2
of this series provides details on procedures and models for the
calculation of atmospheric concentrations resulting from area source
emissions.
Enumerating the exposed population for area sources Involves the
acquisition of census data for the geographic area of Interest. The most
straightforward procedure, therefore, 1s to define the area according to
census geography. Census geographic categories Include urban areas,
urbanized areas, Standard Metropolitan Statistical Areas (SMSAs), central
dtles, and rural areas; these categories were defined 1n Table 2.
Table 10 summarizes the 1980 population count data for the major census
geographic categories and for each of the four census regions 1n the
U.S. Detailed population data for census divisions or for states are
available 1n the summary documents for Number of Inhabitants and
Population Characteristics of the U.S. These documents provide precise
enumerations of populations based on decennial Censuses. Statistical
Abstracts of the U.S.. published yearly, also supplies population count
data for many of the census categories. The population data 1n this
document are based on the most recent Census and are updated yearly by
Census Bureau projections.
The major problem with the use of census data to estimate populations
around area sources 1s that no Information 1s available on the
differential levels of exposure to the populations residing 1n the
geographic areas. Systems Applications, Inc. (SAI 1980) has presented a
method of estimating differential exposures within geographic areas by
distributing national area source emissions among different size cities
(as determined by population) according to number of motor vehicles,
heating day requirements, and population density. For detailed
Information, the Investigator should consult the SAI document (SAI
1980). Unless finances and manpower are plentiful, the approach
discussed 1n the preceding paragraph 1s an efficient procedure for
enumerating populations exposed via Inhalation to chemical substances
released from area sources. Method 2-4 summarizes the required
procedural steps.
50
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Method 2-4. Enumeration of Populations Exposed via Inhalation
to Atmospheric Concentrations of Chemical Substances
Released from Area Sources
Step 1 Determine the demographic category and geographic location of the
area source from the production, use, and environmental release data
for the chemical substance. Demographic categories for which census
data are available include:
• Urban Areas
- urbanized areas
- other urban areas
• Standard Metropolitan Statistical Areas
- central cities
- outside central cities
• Nonmetropolitan Areas
• Rural Areas
The nature of the source determines which category should be
used to define the area. Urban areas or central cities may be
of concern with respect to vehicular exhaust or dry cleaning
solvents; rural locations may be area sources of pesticides
used in farms and gardens.
Step 2 Enumerate the population for demographic and geographic category of
interest from Table 10. If more detailed data are required (e.g.,
census division, state), retrieval of population data in MARF
according to specific areas is possible using the GEODATA HANDLING
(GH) operation and Census Data (CD) program of GEMS as previously
described in subsection (1) and Method 2-2. Population data are also
available in the the U.S. summary of Number of Inhabitants or General
Population Characteristics. Statistical Abstract of the U.S. will
also provide population data for many of the demographic categories
listed, based on updates from the 1980 census year.
52
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(3) Line Sources. This section presents a method for enumerating
populations exposed to chemical substances released from line sources.
As defined 1n Section 2.2, line sources are predominantly sources of
airborne release of chemical substances along transportation corridors,
such as highway and railroad lines. Other types of releases from line
sources also exist, such as the volatilization of chemical substances
from waterways and fugitive emissions or spills and leaks that occur
along pipelines used to transport chemical substances. These types of
releases are not specifically addressed 1n this section; however, the
general principle of the methodology presented 1s applicable to them.
The only existing method Identified for enumerating populations
exposed to chemical substances released from a line source was developed
for the U.S. Department of Commerce, Maritime Administration (ADL 1974).
The method was developed to calculate the safety hazards resulting from
different modes of transportation of hazardous substances. Basically,
the method requires data on the length of the line source (or
transportation corridor), the width of the area adjoining the line source
affected by the release of the chemical substance, and the population
densities along the line source. The total area affected by the chemical
substance 1s calculated by multiplying the length and width of the
affected area. Total area affected 1s then multiplied by population
densities to enumerate the exposed population.
The method developed for the Maritime Administration assumes that all
line sources of chemical release are straight lines that pass through
metropolitan areas, nonmetropolltan areas, or combinations of both.
Metropolitan areas are defined as those designated Standard Metropolitan
Statistical Areas (SMSA) by the Census Bureau. Nonmetropolltan areas are
defined as all areas outside SMSAs.
For a line source that begins and terminates 1n an SMSA, the
following procedure for calculating the length of the line which passes
through metropolitan and nonmetropolltan areas was developed:
The SMSA for each principal city along the origin-destination route
1s recorded 1n units of square miles according to census data. This area
1s then converted to a circular configuration with the principal city
located at Its center. If the line source (the vehicle or transportation
corridor) travels completely through an SMSA, then the hypothetical
diameter of each SMSA 1s assumed to be equivalent to the length of the
metropolitan population corridor exposed to the chemical substance of
Interest. If the line source originates or terminates 1n an SMSA, then
the length of the metropolitan population corridor 1s assumed to be equal
to the hypothetical radius of the SMSA. The length of the
nonmetropolltan population corridor, therefore, 1s equal to the total
distance between the beginning and end of the line source minus the
calculated length of the metropolitan population corridor. This
procedure for calculating metropolitan and nonmetropolltan population
corridor lengths 1s Illustrated 1n Figure 15.
53
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The width of the line source is defined according to an appropriate
algorithm or model using emissions characteristics of the pollutant and
meteorological conditions (wind speed, direction, and atmospheric
stability). The total metropolitan area exposed is calculated as the
product of the length and width of the metropolitan corridor. The same
procedure is followed for calculating the total nonmetropolitan area
exposed. The calculated areas are then multiplied by the average
metropolitan (SMSA) and nonmetropolitan (non-SMSA) population density,
respectively, to enumerate the total exposed population.
This procedure for enumerating populations exposed to chemical
substances released from a line source is believed to be a suitable
approach for the current needs of OTS-EED. One of the main data
requirements of the ADL approach is the length of the line source. These
data are generally provided on a chemical-specific basis in the exposure
assessment process.
Detailed information on methods to calculate the length of line
sources related to transportation spills is available in Volume 9 of this
series. Statistical Abstract of the U.S. (Bureau of the Census 1982b) is
also an excellent source on such generic data as metropolitan and
non-metropolitan highway mileage, inter-city bus lines, and railroad
mileage for the total U.S. and the individual states. For detailed
geographic resolution, the topographic maps published by the U.S.
Geological Survey are the recommended tool for obtaining the length of a
particular line source. Since most of these maps also include plots of
metropolitan and nonmetropolitan areas, it is also possible to rapidly
determine the length of the line in each category.
Calculation of the width of the line source corridor requires the use
of one of several line source simulation models. Line source simulation
models consider emission characteristics and meteorological conditions to
determine concentrations at various distances downwind of the source.
Currently, OTS-EED does not have any line source models integrated into
GEMS. The UNIVAC version of HIWAY is included in the EPA-OTS computer
file library and, therefore, is available to the OTS-Modeling Team.
Additional information on line source models is provided in Volume 2 of
this series.
The final data requirement for enumerating the exposed population 1s
the population density for the area of interest. Population densities
for all SMSAs are available in the Census summary document Number of
Inhabitants (PC-80-1-A). Population densities for cities with 100,000 or
more inhabitants are available in Statistical Abstracts of the U.S.
(Bureau of Census 1982b). Population densities for specific urban areas
with populations less than 100,000 (but greater than 2,500) are available
in the Census summary document General Population Characteristics
(PC-80-1-B).
55
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Finally, Table 8, previously presented, lists population densities for
the different Census Bureau classifications based on 1980 Census data.
The population densities obtained from the above listed documents or from
Table 8 are then multiplied by the area of the line source corridor to
enumerate the total population.
Method 2-5 summarizes the procedure for enumerating populations
exposed via Inhalation to chemical substances released from line
sources. A demonstration of the method on a theoretical line source
problem 1s presented 1n Appendix A-l (Problem 5).
2.3.3 Enumeration of Populations Exposed via Dermal Contact
Dermal exposure to chemical substances 1n the ambient environment may
occur through a number of pathways. One activity has been Identified as
having the greatest potential for significant exposure: swimming 1n
contaminated surface waters. Methods for estimating the size of the
population Involved 1n that activity are presented 1n Method 2-6.
Approximately 101.7 million persons swim 1n U.S. surface waters
(Bureau of the Census 1982b); this represents 45 percent of the U.S.
population. The technique for estimating the number of swimmers
contacting water contaminated by a particular substance depends on
whether the exposure source was Identified through monitoring data or
through examination of the chemical's release Information. Volume 2 of
this series discusses Identification of sources of chemicals released to
surface water.
Geographically defined areas of aquatic exposure, such as river
reaches downstream of an Industrial discharge, may be Identified by
examining release Information. The exposed population 1s therefore the
swimmers 1n those specified receiving waters. The most reliable method
for estimating the number of persons exposed to contaminants 1n surface
waters 1s to contact regional authorities, such as the state, city, or
county department of parks. These authorities can Identify affected
recreational areas and estimate the extent to which they are used.
Another approach to enumerating that population 1s to obtain a figure
for the total population for the region using the water body as a source
of recreation, then to multiply that total by 45 percent, the fraction of
persons who swim. There are limitations to this estimation technique;
determining the region that uses a recreational facility, such as a lake
or river, 1s difficult. Matching that region to a census-defined
geography for which population data are available may also present
problems. If necessary, the area may be broken Into block groups or
56
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Method 2-5. Enumeration of Populations Exposed via Inhalation
to Chemical Substances Released from Line Sources
Step 1 Calculate the length of the line source as illustrated in Figure 15.
Sources of information on the calculation of the length of the line
source include Volume 9 of this series Methods for Estimating
Exposure to Chemical Substances Resulting from Transportation Related
Hazardous Materials Spills and A Hodal Economic and Safety Analysis
of the Transportation of Hazardous Substances in Bulk (AOL 1974).
Generic data for line source lengths can be obtained from Statistical
Abstracts of the U.S. (Bureau of the Census 1982b) or from government
agencies and associations such as U.S. Department of Transportation -
Federal Highway Administration and Federal Railroad Administration;
the U.S. Interstate Cocrmerce Conmission; Bureau of the Census -
Transportation Surveys; Association of American Railroads,
Washington, D.C.; American Bus Association, Washington, D.C.; and
American Public Transit Association, Washington, O.C.
Step 2 Calculate the area affected by the released pollutant. This may be
accomplished by calculating the width of the exposed corridor using
an appropriate line source model. Data on the emissions
characteristics and meteorological conditions are required for most
of the available line source models. Exposed area is the product of
the length of the line source and the corridor width.
Step 3 Enumerate population by multiplying the population density of the
exposed area by the calculated area exposed (Step 2). Population
densities for specific census divisions, states, and urban areas
based on the 1980 Census are available in the Census Report General
Population Characteristics: U.S. Summary. Population densities for
SMSAs are available in the Census document Number of Inhabitants:
U.S. Summary. Table 8 lists generic population density data that
would also be valuable where detailed or specific data are not
required. If more resolution is required for urban areas, population
estimates can be refined by consulting maps of ED/BGs to determine
which ones fall into the affected area. Populations can be sunned
for these ED/BGs to provide a more accurate estimate than that given
by the product of area and average density.
57
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Method 2-6. Enumeration of Populations
Exposed via Dermal Contact
Determine the number of swimmers contacting contaminated ambient
surface waters.
Option 1 - (contamination identified by monitoring data or release
information) contact the local authorities to identify impacted
recreational areas. Inquire about the area's use to estimate the
number of affected persons.
Option 2 - (contamination identified by monitoring data). Multiply
the frequency of detection in percent by the total population of
swironers, 101.7 million persons. (This option yields a very crude
estimate of the exposed population. It assumes that the monitoring
data are from a nationwide survey of all potential swimming locations
or that they are from a sampling that is statistically representative
of all swimming locations.)
Option 3 - (contamination identified by release information).
Identify the water bodies of concern. Enumerate the total population
within a 50 mile radius or corridor, using data in General Population
Characteristics for census-defined geographies such as cities, towns,
counties, or SMSAs. Multiply the total population of the area by
45 percent, the fraction of persons who swim in surface waters.
Option 4 - (contamination identified by monitoring data). If
extensive nationwide monitoring data are available, they can be used
to identify the affected water bodies. The procedure to enumerate
the number of swimmers exposed to the chemical substance is the same
as in Option 3.
58
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enumeration districts, then reaggregated. It 1s reasonable to assume
that a body of water within 50 miles of a person (a one-hour drive) may
be used as a source of recreation. The Investigator might assume that
the population within that radius or corridor 1s potentially exposed.
The General Population Characteristics for the area should be consulted,
and the total population of counties, towns, SHSAs, etc., within the
radius or corridor should be totaled.
For contaminants Introduced by sources other than point discharges of
effluents, geographic definition of potential exposure may not be
possible. Monitoring data retrievals from STORET or similar data bases
can then be used to Indicate the prevalence of waterborne pollution for a
chemical substance. If enough data are available, an estimate of the
number of persons dermally exposed via swimming can be obtained by
multiplying the frequency of detection of the contaminant 1n surface
water (1n percent) by the participating population (101.7 million
persons).
These population enumeration techniques assume that persons will swim
1n contaminated waters as often as 1n noncontamlnated lakes and rivers.
Figures obtained by these methods may therefore be overestimates. That
assumption 1s not, however, unreasonable; low level contamination that
may cause human exposure 1s not always detectable.
2.3.4 Enumeration of Nonhuman Populations
Nonhuman populations are generally more difficult to quantify than
are human populations because less Information 1s available, and the data
that are available are often measured In units other than numbers of
organisms; populations may, for example, be expressed as herds or
blomass. The adequacy and sources of nonhuman population data vary
considerably, depending on the organism. As might be expected, most
research effort has been Invested In plant and animal species that have
economic significance.
In most cases, 1t is necessary to gather the data from diverse
sources to enumerate nonhuman populations. The major sources available
include journal articles and other publications, federal and state
agencies, and selected private agencies. A literature search, using
computerized data bases such as the following, is recommended:
A6RICOLA (National Agricultural Library, Beltsville, MD)
AGRICOLA 1s the cataloging and indexing data base of the National
Agriculture Library. It provides comprehensive coverage of worldwide
journal and monographic literature on agriculture and related
subjects.
59
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ASFA (NOAA/Cambr1dge Scientific Abstracts, Bethesda, MD)
The Aquatic Sciences and Fisheries Abstracts (ASFA) 1s a
comprehensive data base on life sciences of the seas and Inland
waters as well as related legal, political, and soda! topics. It
Includes Information on aquatic biology, oceanography, fisheries, and
water pollution.
BIOSIS PREVIEWS (Blosdences Information Service, Philadelphia, PA)
BIOSIS PREVIEWS provides comprehensive worldwide coverage of research
1n the life sciences. It contains citations from Biological
Abstracts and Biological Abstracts/RRM.
Life Sciences Collection (Cambridge Scientific Abstracts, Bethesda, MD)
Life Sciences Collection contains abstracts of worldwide journal
articles, books, conference proceedings, and report literature. The
Information Includes animal behavior, ecology, and entomology.
SSIE Current Research (Smithsonian Science Information Exchange,
Washington, D.C.)
SSIE Current Research contains reports of both government and
privately funded scientific research projects either currently 1n
progress or Initiated and completed during the most recent two years.
These and other data bases can be accessed through DIALOG Information
Retrieval Service (DIS 1982).
In addition to these data bases, a retrieval from the F1sh and
Wildlife Reference Service and a retrieval from the GEOECOLOGY Data Base
may be worthwhile. The reference service 1s operated by the U.S. F1sh
and Wildlife Service out of Denver, Colorado. Computerized literature
searches, covering the published and unpublished fish and wildlife
research reports resulting from federally funded programs, are conducted
for a fee of $30. The GEOECOLOGY Data Base (Olson et al. 1980),
maintained by the Oak Ridge National Laboratory, Oak Ridge, Tennessee, 1s
a compilation of computerized environmental data. The data base
Includes, at the county level of resolution, selected data on terrain and
soils, water resources, forestry, vegetation, agriculture, land use,
wildlife, and endangered species. The wildlife sector Includes
Information from the annual Breeding Bird Survey, data on federally
designated endangered and threatened species, and the geographic range of
various mammals. The Endangered Species File and Code Dictionary of the
GEOECOLOGY data base 1s currently available through the EPA-OTS computer
library (Files W09 and W10, respectively). Requests for Information or
retrievals for the other data Included 1n GEOECOLOGY should be directed
to:
60
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D1ck Olsen
GEOECOL06Y Project Team
Oak Ridge National Laboratory
PO Box X, Building 1505
Oak Ridge, TN 37830
(615) 574-7819
Estimates of exposed nonhuman population sizes may also be made, 1f
the resources permit, through contact with appropriate state and federal
agencies. The two that are of most use are the F1sh and Wildlife Service
and the U.S. Department of Agriculture's Forest Service. Both maintain
regional research offices which may provide published or unpublished
population data not available from other sources. Private agencies such
as those listed 1n Table 11 may also be contacted for population
Information. The National Wildlife Federation (1980) lists many private
organizations with specific wildlife concern which may also be used as
Information sources.
The Investigator should be aware that, for most species, the
population data, 1f any, are scant and are based on a handful of studies
1n specific locales. Extrapolating such data to large regions or to the
nation Involves considerable uncertainty because uneven spatial
distribution and temporal fluctuations are characteristic of many
nonhuman populations. Population density Is highly dependent on habitat
type, and the population density estimated 1n one local study may be
significantly higher or lower than the average population density for
larger areas (e.g., counties, states, regions).
2.4 Characterization of Exposed Populations
The average physiological parameters that determine exposure (e.g.,
breathing rate, body weight, and skin surface area) are age- and
sex-spedf1c. Subpopulatlons defined by age or sex, such as the elderly
or women of child-bearing age, may be especially susceptible to a
chemical substance. Characterization of exposed populations permits the
determination of exposure distributions and the enumeration of specific
high risk subpopulatlons. Methods for characterizing populations exposed
via Inhalation and dermal exposure 1n the ambient environment are
presented 1n the following subsections.
2.4.1 Populations Exposed via Inhalation
The level of geographic resolution necessary to an assessment of
atmospheric pollutants dictates the scheme by which characterization
proceeds. Populations near point sources for which ATM-SECPOP 1s used to
determine exposure may be characterized by the use of census data
61
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Table 11. Sources of Information on NonHuman Populations
National Wildlife Federation
1412 16th Street, NW
Washington, DC 20036
(202) 797-6800
National Audubon Society
950 Third Avenue
New York, NY 10022
(212) 832-3200
North American Wildlife Foundation
709 Wire Building
Washington, DC 20005
(202) 347-1775
Raptor Research Foundation, Inc.
c/o Richard R. Olendorff
Division of Resources
U.S. Bureau of Land Management
2800 Cottage Way
Sacramento, CA 95825
The Wildlife Society
Suite 611
7101 Wisconsin Avenue, NW
Washington, DC 20014
(301) 986-8700
62
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specific to the area. For prototype point sources, area sources, and
line sources, both site-specific and generic data on the age and sex
characteristics of the population may be applicable sources of
Information.
(1) Point Sources Enumerated by SECPOP. The SECPOP data base
enumerates the populations differentially exposed 1n segments around
point sources. Data for geographically-defined areas within the SECPOP
radius are available from the Bureau of the Census.
Populations enumerated by SECPOP can usually be characterized by
consulting the General Population Characteristics series for the area
within the model radius. The level of detail achievable through this
data source will be sufficient for all but the most 1n-depth exposure
analyses; Table 2 (Section 2.3.1) lists the census-defined areas for
which age and sex data are available from General Population
Characteristics.
Segments within the model radius can also be segregated Into census
tracts 1f more detail 1s required. Series PHC80-2, Census Tracts.
presents data by age and sex for populations defined by census tract.
(2) Point. Area, and Line Sources. The data sources discussed above
(General Population Characteristics and Census Tracts) can be used to
characterize populations around or within these pollutant sources.
Point, area, and line sources are, however, often too numerous to be
treated Individually. Table 12 presents the age and sex distribution of
the U.S. population as determined by the 1980 Census. These data may be
used to estimate the distribution of males and females of different ages
1n relatively large exposed populations; that distribution would be
expected to be similar to the national distribution. Method 2-7 1s a
guide to characterizing exposed populations.
2.4.2 Populations Exposed via Dermal Contact
Numerous activities 1n the ambient environment may lead to dermal
contact with chemical substances: aquatic recreation, gardening and other
contact with the soil, and contact with atmospheric pollutants deposited
on the skin surface. Of these, one 1s considered to be a potentially
significant source of exposure: swimming 1n contaminated surface waters.
As discussed 1n Section 2.3.4, a large proportion of the population
swims 1n lakes, rivers, and the ocean. It can be assumed that such a
large population constitutes a cross section of the U.S. populace and
that swimmers can be characterized by the data 1n Table 12. It 1s likely
that the actual swimming population 1s skewed somewhat toward the young,
and that the young swim more frequently, but data to substantiate that
premise are not available.
63
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Table 12. Population of the United States
by Age and Sex: April 1, 1980
Age and sex
1. Both sexes
All ages
Under 5
5-9
10-14
15-19
20-24
25-34
35-44
45-54
55-64
65-74
75-84
Over 85
Median age
2. Hale
All ages
Under 5
5-9
10-14
15-19
20-24
25-34
35-44
45-54
55-64
65-74
75-84
85 +
Median age
3. Females
All ages
Under 5
5-9
10-14
15-19
20-24
25-34
35-44
45-54
55-64
65-74
75-84
85 +
Median age
Population
226,504,825
16,344,407
16,697,134
18.240,919
21,161,667
21,312,557
37,075,629
25,631,247
22,797,367
21,699,765
15,577,586
7,726,826
2,239,721
30.0
110,032,295
8,360,135
8,537,903
9,315,055
10,751,544
10,660,063
18,378,764
12,567,786
11,007,985
10,150,459
6,755,199
2,865,974
681,428
28.8
116,472,530
7,984,272
8,159,231
8,925,864
10,410,123
10,652,494
18,696,865
13,063,461
11,789,382
11,549,306
8,822,387
4,860,852
1,558,293
31.3
Percent
100.00
7.22
7.37
8.05
9.34
9.41
16.37
11.32
10.65
9.58
6.88
3.41
.99
100.00
7.59
7.76
8.46
9.77
9.69
16.70
11.42
10.00
9.22
6.14
2.60
0.62
100.00
6.85
7.00
7.66
8.94
9.15
16.05
11.22
10.12
9.92
7.57
4.17
1.34
Source: Personal communication between Mrs. McCoy of the Population
Division, Bureau of the Census, and Amy Borenstein, Versar, Inc.,
July 1982.
64
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Method 2-7. Characterization of Populations Exposed to Chemical
Substances via Inhalation of Ambient Air
For populations near point sources (as enumerated by SECPOP), line
sources, or area sources, choose the option providing the desired
level of detail. The method of enumeration and the financial and
manpower resources allotted will dictate the choice of options.
Option 1 - The most detailed characterization is obtained by
determining census tracts within the defined radius, area, or
corridor and using the age-sex distributions for each (in Census
Tracts) to describe the population.
Option 2 - General Population Characteristics for the area (SHSA,
county, town, etc.) provides the age and sex characterization for the
enumerated population.
Option 3 - The generic data in Table 12, describing the U.S.
population as a whole, may be used to characterize populations around
point, general point, area, or line sources.
65
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2.5
References
AOL. 1974. Arthur D. Little, Inc. A modal economic and safety analysis
of the transportation of hazardous substances 1n bulk. Washington, DC:
U.S. Department of Commerce, Maritime Administration.
Bureau of the Census. 1979a. 1980 Census of population and housing,
August 1979. Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1979b. Census geography. Data access
descriptions, No. 33. Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1980a. Census '80. Introduction to products and
services. Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1980b. Data user news, Volume 15, No. 8, August
1980. Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1980c. Factflnder. No. 8. February 1980.
Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1981a. Factflnder. No. 22. September 1981.
Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1981b. 1980 Census update, Issue No. 18, April
1981. Washington, DC: U.S. Department of Commerce.
Bureau of the Census. 1982a. Directory of data files. Machine readable
data available from the Bureau of the Census. Washington, D.C: U.S.
Department of Commerce, Subscriber Services Section (Publications).
Bureau of the Census. 1982b. Statistical abstract of the United
States: 1982 (103rd edition). Washington, DC: U.S. Department of
Commerce, U.S. Government Printing Office.
Bureau of the Census. 1983a. 1980 Census of population. Number of
Inhabitants. U.S. Summary. ( PC80-1-A) Washington, DC: U.S. Department
of Commerce. U.S. Government Printing Office.
Bureau of the Census. 1983b. 1980 Census of population. General
population characteristics. U.S. Summary. (PC80-1-B). Washington, DC:
U.S. Department of Commerce. U.S. Government Printing Office.
DIS 1982. DIALOG Information Services, Inc. DIALOG Information
retrieval service data base catalog. Palo Alto, CA.
66
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GSC. 1983. General Software Corporation. Graphical exposure modeling
system (GEMS) user's guide. Draft final report. Washington, DC: U.S.
Environmental Protection Agency, Office of Toxic Substances. EPA
Contract No. 68-01-6618.
National Wildlife Federation. 1980. Conservation Directory. 1980.
25th anniversary edition. The National Wildlife Federation. Washington,
DC.
Olson RJ, Emerson CJ, Nungesser MK. 1980. GEOECOLOGY: a county level
environmental data base for the conterminous United States. Oak Ridge,
TN: Oak Ridge National Laboratory. ORNL/TM-7351.
Patterson MR, Sworskl TJ, SJoreen AL, Browman MG, Coutant CC, Hetrlcka
DM, Murphy BD, Rarldon RJ. 1982. User's manual for UTM-TOX, a unified
transport model. Draft report. Oak Ridge, TN: Oak Ridge National
Laboratory. ORNL-TM-8182. IEG-AD-89-F-1-3999-0.
SAI. 1980. Systems Applications, Inc. Human exposure to atmospheric
concentrations of selected chemicals. Research Triangle Park, NC: U.S.
Environmental Protection Agency, Office of A1r Quality Planning and
Standards. EPA Contract No. 68-02-3066.
67
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3. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE OCCUPATIONAL
ENVIRONMENT
3.1 Introduction
This section presents methods for enumerating and characterizing
occupatlonally exposed populations. The methods described apply to
workers 1n Industry, trade, and commercial establishments. The data
provide various levels of detail that enable the user to produce both
preliminary and 1n-depth assessments.
Figure 16 1s a flow diagram of the three-stage method framework.
Included 1n the diagram are some of the major data sources used.
The Identification of the exposed population 1s discussed only
briefly 1n this section (Subsection 3.2); the occupational exposure
assessment methods report (Volume 6) describe the process 1n detail.
The enumeration of the exposed population relies on the direct
utilization and combination of numerous data bases. This Information 1s
largely the result of efforts by the federal government to monitor
employment; as such, the data may not be 1n a format directly applicable
to exposure assessments. Subsection 3.3 addresses the limitations of the
data and how they can be used for occupational population studies.
The age and sex of a worker affect physiological parameters that
determine exposure (e.g., breathing rate, skin surface area). Detailed
exposure assessments may require that populations be described by age and
sex distributions; Subsection 3.4 discusses methods of characterizing
workers by age and sex.
Examples of the use of the methods 1n this section of the report are
presented 1n Appendix A-2.
3.2 Identification of Exposed Populations
Methods for Identifying occupatlonally-exposed populations are
summarized herein; Volume 6 of this series provides details on these
methods. Specific job titles and 4-d1g1t Standard Industrial
Classification (SIC) designations are the most common forms by which
employment 1s listed. Identification should be keyed to this fact when
possible. Method 3-1 summarizes the general approach to population
Identification.
69
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r
IDENTIFICATION OF EXPOSED POPULATIONS
I
INDUSTRY OR
PRODUCT
EXPOSURE
~i
INDUSTRY AND
OCCUPATION
EXPOSURE
SIC CODE
I
n
SITE-
SPECIFIC
EXPOSURE
JOB TITLE
ENUMERATION
VIA ECONOMIC
CENSUSES OR
BLS* DATA
JOB LOCATION
ENUMERATION
VIA 1-0 MATRIX*
OR BUREAU OF
THE CENSUS
DATA
r
i
ENUMERATION VIA
DIRECT CONTACT,
INDUSTRIAL
DIRECTORIES,
EIS*, OR OSHA
~i
CHARACTERIZATION OF EXPOSED POPULATION
CENSUS DATA
FOR GENERAL
INDUSTRIES,
AND OCCUPATIONS,
AGE AND SEX
SPECIFIC
DATA FROM
INDUSTRIAL
DIRECTORIES.
SEX ONLY
*BLS = BUREAU OF LABOR STATISTICS
*l-0 MATRIX = INDUSTRY-OCCUPATION MATRIX
*EIS = ECONOMIC INFORMATION SYSTEMS, INC.
Figure 16. Three-stage Framework for Enumeration and Characterization
of Occupationally Exposed Populations
70
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Method 3-1. General Procedure for Identifying
Populations Exposed in the Workplace
Step 1 Determine which industries and types of establishments produce,
process, use, and sell the chemical substance of concern. Locate
major production and use facilities. Identify the applicable SIC
codes for all industries and establishments (see Volume 6 of this
series).
Step 2 Consult the production, use, and release information and available
monitoring data to identify points of chemical release and possible
exposure pathways and exposure routes. Identify activities leading
to exposure (see Volume 6).
Step 3 For each industry and activity identified in Steps 1 and 2, list the
workers potentially exposed by occupation or job title. Use the
Industry-Occupation (1-0) matrix as a guide in listing.
71
-------
Employees potentially exposed via Inhalation, 1ngest1on, and dermal
contact may be Identified by examining workplace monitoring data or by
considering the workers' process equipment and Job activities.
Monitoring data are usually available only for a relatively small
number of existing chemicals. New chemicals must be Investigated by
studying the premanufacturlng notice (PMN) submlttal and supplementing
that Information with knowledge of the process. Analysis of monitoring
data and production, use, and release Information may Identify:
• Workers exposed 1n a particular Industry, Identifiable by SIC code.
• Persons employed In a specific occupation In an Industry.
• Workers exposed by their presence at an Industrial site.
• Persons performing certain activities or processes not directly
classifiable by occupation (e.g., cleaning, sampling, waste
disposal).
These groups are enumerated by methods specific to each. The following
section discusses the methods by which exposed populations can be
enumerated. Most of the methods rely upon direct use of data bases
maintained to monitor employment levels. As mentioned previously, the
data may not match the Identified populations; adaptation of the
Information 1s discussed.
3.3 Methods for the Enumeration of Exposed Populations
This section presents the recommended procedures and data sources for
the enumeration of occupationally-exposed populations. The methods may
often be used 1n combination with each other to achieve the best estimate
of workers exposed to chemical substances, though common sense must be
used to avoid double-counting subpopulatlons. The method or methods to
be used are often dictated by the Identification scheme.
This section 1s divided Into three subsections, based on the
categories for Identifying the exposed populations. Subsection 3.3.1
discusses data bases and methods based on the Standard Industrial
Classification (SIC) codes. Populations Identified by occupation and
Industry are discussed 1n Subsection 3.3.2, and Subsection 3.3.3 deals
with site-specific worker populations.
72
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Some of the methods discussed 1n this section provide better
estimates than others. The greater the level of detail available, the
better the estimate of the exposed population; thus, the methods based on
specific occupation by Industry or activity data are generally better
than the SIC-based method. The limitations of each type of data are
discussed 1n each section. Examples of the data available for many of
the methods are Included as Appendix B to this report. Appendix A-2
presents examples of applying the methods 1n this section.
3.3.1 Enumeration of Populations Identified by SIC Code
The method for enumerating workers Identified by SIC code
(Method 3-2) 1s straightforward and relies on the use of two types of
Information: (1) the Bureau of Labor Statistics1 Employment and Earnings
(U.S. Department of Labor 1981a) and (2) the Economic Census and related
reports.
All SIC-based data have one major limitation. An establishment may
be Involved 1n activities classifiable under numerous 4-d1g1t SIC codes,
but all data are reported under one SIC designation (the "major activity"
1n which the company 1s Involved). This provision simplifies a company's
reporting requirements but produces data that may be gross underestimates
or gross overestimates when used for exposure assessments. There 1s no
way to account for such discrepancies 1n occupational population studies.
Another limitation has varying effects on the reported data. Some
Industries count only paid employees; establishments staffed by unpaid
family members or owner-proprietors will therefore be uncounted or
undercounted.
A problem with all SIC-based data Is the lack of completeness. The
11st of 4-d1g1t SIC codes runs nearly 80 pages of print, but data are
reported for only a fraction of the established 4-d1g1t codes. Some
publications are limited by choice, I.e., only specific codes are
reported. More often the limitation 1s related to the need to preserve
confidentiality of responses when few data are reported for an Industry.
(1) Employment and Earnings. The U.S. Department of Labor's Bureau
of Labor Statistics (BLS) publishes Employment and Earnings monthly. The
data therein are thus the most recent available; the employment figures
1n each publication are for the previous month.
The major limitation 1n the monthly BLS data 1s the lack of
completeness. Only a fraction of the 4-d1g1t SIC codes 1n manufacturing
Industries 1s represented, and nonmanfacturlng Industries (such as trade,
construction, and services) are present at the 3-d1g1t level of
resolution at best. Use of data based on the 2- or 3-d1g1t level may
result 1n overestlmatlon of occupational populations, because the broad
categories may Include Industries 1n which no exposure occurs.
73
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Method 3-2. Enumeration of Populations Identified by SIC Code
Step 1 Determine which source(s) list populations for the SIC codes for
which data must be obtained. For nationwide chemical assessments,
consult (in order of preference):
- Employment and Earnings (most recent data)
- The Economic Censuses (fairly complete and readily available)
- Other information such as County Business Patterns and the Annual
Survey of Manufactures
- When enumerating populations in specific geographic areas,
consult County Business Patterns (published last in 1981) or the
Geographic Series of the Economic Censuses (accessible in hard
copy or through GEMS).
Step 2 Choose the data most representative of the workers actually
exposed. In manufacturing industries, for example, "production
workers" is generally a better category for estimating exposures
during the process than is total employment for a SIC listing (which
includes office workers who may not be exposed).
Step 3 Qualify all data by addressing questions of limitations:
- Does the SIC code represent the exposed population? If not, are
data overestimates or underestimates?
- Are data based only on paid employees and therefore possibly
underestimates?
74
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The BIS establishment data are number of jobs, not number of
workers. If a person holds two jobs, he may be reported twice 1n
Employment and Earnings. This, however, 1s rarely a limitation to the
data as they are used 1n exposure assessments; only workers with both
jobs classified under the same SIC code would be double counted 1n the
exposed population for an occupation.
(2) Economic Censuses.
five-year cycles:
Eight Economic Censuses are conducted 1n
1.
2.
3.
4.
5.
6.
7.
8.
Census
Census
Census
Census
Census
Census
Census
Census
of Service Industries
of Wholesale Trade
of Retail Trade
of Manufactures
of Mineral Industries
of Construction Industries
of Transportation
of Agriculture
Years ending 1n 2 and 7
- Years ending 1n 8 and 3
All of the censuses contain Information on employment, listed by SIC
code. More Information on the censuses 1s available from the Research
Triangle Insltute (RTI 1982) and U.S. Department of Commerce (USOC 1979);
detailed Information on the compilation techniques 1s presented 1n the
Census publications associated with each Economic Census. The data
available 1n the first six economic censuses are summarized 1n Table 13.
The Census of Transportation's only employment data are listings of
truckers "for hire" and "not for hire" (RTI 1982).
Data related to the Economic Censuses Include County Business
Patterns and the Annual Survey of Manufactures. The County Business
Patterns, last compiled 1n 1977, provide county-by-county and national
summary statistics by SIC code for the full range of 2-, 3-, and 4-d1g1t
classifications. The reporting requirements and resulting data are
similar to those of the Economic Censuses. The Annual Survey of
Manufactures 1s a yearly update of the Census of Manufactures.
Despite their limitations, SIC-based data have proved useful In
exposure assessments. This 1s especially true for widely used chemicals,
such as formaldehyde 1n textile resins. Data from the Census of
Manufactures provided useful estimates of textile mill workers exposed to
formaldehyde, and the Censuses of Retail Trade and Wholesale Trade were
used to enumerate persons exposed as a result of selling formaldehyde-
treated cloth and apparel (Versar 1982).
All SIC-based employment data are government-generated and are
therefore available to the public. All publications listed In this
75
-------
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76
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section can be obtained through the Government Printing Office, and many
are available In major D.C. area libraries. The Modeling Team of the
Exposure Evaluation Division's Chemical Fate Branch has begun
Incorporating the Economic Censuses Into the Graphical Exposure Modeling
System (GEMS). GEMS users can extract data for 3- or 4-d1g1t SIC codes
from the Geographic Series of the Censuses of Manufactures, Retail Trade,
Wholesale Trade, and Service Industries. Total employment, number of
establishments, and (where applicable) production workers can be obtained
as national totals or by states, counties, SMSAs, or cities. These data
can be statistically analyzed and displayed by GEMS 1n tabular form or 1n
a variety of graphical presentations (e.g., bar graphs and scatterplots).
3.3.2 Enumeration of Populations Defined by Occupation and Industry
Occupatlonally exposed populations will often be Identified by job
title, e.g., by occupation and Industry. The most detailed employment
Information available, the Industry-Occupation (1-0) matrix (U.S.
Department of Labor 1981b), 1s presented 1n this format. The Bureau of
the Census also presents data 1n that style, though at a much more
aggregated level reflecting less detail than the 1-0 matrix. A third
source of this form of occupational data 1s contact with professional
organizations and trade associations. The use of these data 1s
summarized as Method 3-3. Each type of Information 1s discussed below.
(1) The Industry-Occupation (1-0) Matrix. The 1-0 matrix 1s a
compilation of data collected regularly from the Bureau of Labor
Statistics (BLS), state employment agencies, and the Employment and
Training Administration of the Department of Labor. The matrix 1s
collated for data 1n three-year cycles (RTI 1982). The data are actually
presented as two matrices encompassing 1,615 occupations 1n 378
Industries. One matrix lists Industries by occupation; the printed
output of this matrix 1s about 2,500 pages. The more useful listing of
occupations by Industry 1s 5,000 pages long. Both are available on
computer tape from BLS; they can be obtained as paper hardcopy and on
microfiche from the National Technical Information Service (NTIS). An
example of the 1-0 matrix output 1s contained 1n Appendix B-l.
Personnel at the Bureau of Labor Statistics Indicate that the
publicly-available 1-0 matrix may be somewhat reduced 1n scope from Its
Initial conception.* The effect of those changes on the usefulness of
the data cannot be projected at this time.
*Personal communication with G. Schweer, Versar, and E. Abramson, BLS,
Division of Occupational Outlook, May 1982.
77
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Method 3-3. Enumeration of Populations Identified by Occupation and
Industry
Option 1 Consult the 1-0 matrix directory, and enumerate populations
listed therein. Employment is read directly off the matrix; no
adjustment or extrapolation is necessary.
Option 2 For very specific or unusual occupations, identify the
applicable trade or professional organizations. Contact the
organization and ask whether data on the number of member's is
representative of total employment in that field.
Option 3 In the absence of all other data, estimate the population by
consulting Occupation by Industry. If possible, state
qualitatively whether the 1970 data provide overestimates or
underestimates (more likely).
-------
(2) Bureau of the Census data. The decennial Census collects
detailed employment Information from one 1n six respondents for
publication as the Occupation by Industry series report (Bureau of the
Census 1972). The biggest limitation to the use of the data 1s that they
were last published 1n 1972, as a result of the 1970 Census. Budget
limitations may preclude the publication of Occupation by Industry for
the 1980 Census. Data collected 1n 1980 have not yet been programmed;
publication or availability of tapes prior to 1984 1s unlikely.t Any
data derived from the 1970 Census must be used with caution.
(3) Contact with professional organizations and trade associations.
Often the most precise and up-to-date employment figures can be obtained
by contacting the organization representing a trade or profession.
The following references are useful 1n locating the relevant organization;
• Gale's Encyclopedia of Associations (Gale Research 1980)
• O.C. area telephone directories
The association staffer should be Informed of the reason for the request,
so that he or she can provide the most applicable estimate. Data
limitations to be aware of Include the possibility that retired or
Inactive members no longer Involved 1n the occupation are still listed,
or that the membership lists are simply out-of-date.
3.3.3 Enumeration of Site-Specific Populations
Exposure assessments requiring enumeration of workers at specific
production facilities may be undertaken by using Method 3-4. This method
relies on four sources of Information:
1. Economic data (such as the Economic Information System - EIS -
computerized data and printed reports)
2. The State Industrial Directories (State Industrial Directories
Corp. 1979)
3. Direct contact with producers
4. State and federal OSHA Inspection data.
tPersonal communication between G. Hendrlckson, Versar, and P. Vines,
Bureau of the Census, December 1982.
79
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Method 3-4. Enumeration of Site-Specific Populations
Option 1 (Direct Enumeration)
Step 1 Determine total employment at plant.
Option 1: Retrieve data from EIS. The Line-of-Business reports,
available for major manufacturers, list the locations
and total employment for facilities.
Option 2: Consult the State Industrial Directory. Facilities are
listed by city in each state's volume.
Option 3: Directly contact the manufacturer.
Step 2 Estimate the proportion of total employees involved in production of
the chemical in question.
Option 2 (Extrapolation of Sample Data)
Step 1 Retrieve OSHA inspection data for the chemical substance.
Inspections will list the number of workers affected at each plant
site.
Step 2 Calculate the average number of workers exposed per plant for each
type of facility (production, processing, etc.).
Step 3 Multiply the average per plant by the total number of plants
nationwide to enumerate the total occupational population.
Note: The limitations to the use of Option 2 are described in Section
3-3.3.
30
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The method can use any or all of the sources above, but H 1s best
applied to enumerating a limited number of populations; direct
enumeration of this type may be expensive and time-consuming. While the
data from these sources are reliable, 1t 1s often difficult to ascertain
what proportion of workers 1n a large plant are Involved 1n the
production of the chemical substance of Interest. Extrapolation of data
from a few plants to obtain national employment estimates 1s possible.
There are limitations to the use of sample data. Unless Inspections are
(1) representative of Industry-wide conditions and (2) complete (I.e.,
all exposed workers 1n each plant were Identified), data from
extrapolation may be Inaccurate. An additional problem 1s that the
majority of Inspections are several years old, and few OSHA Inspections
are now done each year.
The Economic Information System (EIS) 1s a comprehensive computer
data base listing a company's facilities and the number of employees at
each site. The data are, however, expensive to retrieve ($90 per hour
online); the usefulness of the EIS 1s therefore restricted. Data can be
obtained through the Control Data Corporation's Economic Business
Information System (EBIS) or by phone or mall contact:
Economic Information Systems, Inc.
310 Madison Avenue
New York, N.Y. 10017
(212) 697-6080
The State Industrial Directories Corporation publishes a
state-by-state listing of Industrial facilities, arranged by city. The
Directory 1s published annually and 1s available 1n major libraries. The
level of detail reported varies by state; some states record total
employment, while some distinguish between office and production workers
and characterize the workers by sex. The data recorded 1n the Directory
may, however, be Incomplete since all Information 1s supplied to the
Corporation voluntarily (State Industrial Directories Corp. 1979).
States and smaller government units may also publish their own
directories 1n an effort to attract business. State Departments of
Commerce and local Chambers of Commerce are good sources of Information.
Contacting a producer directly, either by mall or telephone, often
produces the most recent and detailed data on workers.
As mentioned previously, one production facility may process any
number of chemicals. Knowledge of the total employment at that plant
provides only an upper limit for estimating the exposed worker
population. Assuming that production techniques for different chemicals
are equally labor Intensive, the following may provide an
order-of-magn1tude estimate of the number of workers Involved 1n the
production of one chemical:
81
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.
PVt -Et
where
PVa = the production volume of the chemical being assessed
PVt = total production at the facility
Ea = employees producing the chemical being assessed (the exposed
population), and
Et = total plant employment.
3 . 4 Characterization of Occupational^ Exposed Populations
Method 3-5 summarizes the characterization of occupational ly exposed
populations. Physiological differences between workers of both sexes and
various ages may affect chemical exposure or the resultant risk. The
most recent data on the distribution of the work force between men and
women are presented 1n Table 14; the relevant "percent of total
employment" figures can be applied to the enumerated population.
Table 15 presents the age and sex distributions for major
occupational groups. These data are based on the 1970 Census, however,
and they should be used with caution. Economic and social evolution of
the past decade has produced changes that are readily apparent to one who
compares Tables 14 and 15. Women once accounted for less than 17 percent
of the managers and administrators; 1n 1979, over 30 percent of that
group were women.
The State Industrial Directory series discussed 1n Section 3.3.3 may
also provide the number of male and female workers at specific locations,
but those data are only collected for a few states.
82
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Method 3-5. Characterization of Occupational!;/ Exposed Populations
Step 1 Determine whether age and sex characterization or sex
characterization is required.
Step 2 Characterize the population. Apply percent distributions to the
enumerated population.
Option 1: (Age and Sex.) Consult Table 15 for data on general
occupations. Be cognizant that data are 12 years old.
Option 2: (Sex only.) Consult Table 14 for 1979 data on
general and specific occupations.
Option 3: (Sex only.) Consult data derived from site-specific
sources (see Section 3.3.3).
83
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Table 14. Employed Persons by Occupation and Sex, 1979
Occupation
Professional and technical workers
Medical and other health
Teachers except college
Other
Managers and administrators, non-farm
Salaried
Self-employed, retail trade
Other self-employed
Sales workers
Retail trade
Other
Clerical workers
Stenographers, typists, secretaries
Other
Craft workers
Carpenters
Construction craftsworkers
Mechanics and repairers
Metal craftsworkers
Blue collar supervisors
All other
Operatives, except transport
Durable goods manufacture
Nondurable goods manufacture
Other industries
Transport equipment operators
Drivers, motor vehicles
Al 1 others
Non-farm laborers
Construction
Manufacturing
Other industries
Percent of total
Male
46.0
25.2
20.6
64.5
68.1
67.5
62.1
78.6
45.9
31.5
65.1
17.3
1.4
22.9
92.6
100.0
98.9
98.2
95.1
85.7
80.0
51.7
57.6
36.4
55.5
91.0
90.1
96.4
87.0
95.3
81.8
86.4
employment
Femal e
54.0
74.8
79.4
35.5
31.9
32.5
37.9
21.4
54.1
68.5
34.9
82.7
98.6
77.1
7.4
-
1.1
1.8
4.9
14.3
20.0
48.3
42.4
63.6
44.5
9.0
8.9
3.6
13.0
4.7
18.2
13.6
84
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Table 14. (continued)
Occupation
Percent of total employment
Male
Female
Private household workers
Service workers, except private household
Food service
Protective service
All other
Farmers and farm managers
Farm laborers and supervisors
Paid
Unpaid family
1.1
36.5
29.8
85.7
32.7
86.1
73.3
78.8
33.6
98.9
63.5
70.2
14.3
67.3
13.9
26.7
21.2
66.7
Source: Adapted from BLS (1980).
85
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3.5 References
BLS. 1980. Bureau of Labor Statistics. Handbook of labor statistics.
Washington DC: U.S. Department of Labor. BLS Bulletin 2070.
Bureau of the Census. 1972. Occupation by Industry: 1970 Census of
population. Washington, DC: U.S. Department of Commerce, Social and
Economic Statistics Administration.
Gale Research Corp. 1980. Encyclopedia of Associations. Michigan:
Gale Research Corporation.
RTI. 1982. Research Triangle Institute. Identification, analysis, and
procurement of data bases for assessing exposed populations. Phase I
report. Identification of data bases. Draft. Washington, DC: U.S.
Environmental Protection Agency, Office of Toxic Substances. Contract
No. 68-01-5848.
State Industrial Directories Corp. 1979. State Industrial Directory.
New York, NY: State Industrial Directories Corp.
USDC. 1979. U.S. Department of Commerce. Mini-guide to the 1977
economic censuses. Washington, DC: Bureau of the Census.
U.S. Department of Labor. 1981a. Employment and earnings. October
1981. (Monthly Reports). Washington, DC: Bureau of Labor Statistics.
U.S. Department of Labor. 1981b. The national Industry-occupation
employment matrix, 1970, 1978, and projected 1990. Volumes I and II.
Washington, DC: Bureau of Labor Statistics. Bulletin No. 2086.
Versar. 1982. Exposure assessment for formaldehyde. Draft Report.
Washington, DC: U.S. Environmental Protection Agency, Office of Toxic
Substances. Contract No. 68-01-6271.
87
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4. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF
FOOD
4.1 Introduction
This section presents methods for enumerating and characterizing
populations exposed to chemical substances via the 1ngest1on of food.
The methods described are applicable to food Hems or categories of foods
that contain chemical substances as a result of (1) agricultural
practices (e.g., use of pesticides, fertilizers), (2) processing (e.g.,
packaging, canning), (3) contaminants that can be traced to point, area,
and line sources, and (4) contaminants of unknown origin detected via
monitoring data.
The methods that follow rely 1n many cases on simplifying assumptions
In order to enumerate the exposed populations; foods and food products
have geographical distributions and processing patterns that fluctuate
depending on seasonal demand and availability. Enumeration of the total
consuming population for a specific food 1s a relatively straightforward
process. The exposed population 1s, however, some fraction of the
consuming population; that fraction 1s a function of the source of the
chemical substance. The methods presented 1n this section can be used to
estimate the range of the exposed population.
Figure 17 1s a flow diagram of the three-stage framework for
enumerating and characterizing populations exposed to chemical substances
via the 1ngest1on of food. Each stage 1s composed of several methods
depending on the source of the exposure or how the exposed population 1s
Identified 1n the exposure assessment. Subsection 4.2 briefly describes
the procedures for Identifying the exposed population. The enumeration
of the exposed population 1s the second stage and 1s discussed 1n
Subsection 4.3. Subsection 4.3 1s organized according to the source of
the chemical substance as Illustrated 1n Figure 17. The third stage,
characterization of the exposed population by age and sex distribution,
1s the subject of Subsection 4.4. This stage would only be used 1f It
were determined that a chemical substance had a specific effect on a
particular age or sex group or that a particular group was more highly
exposed.
Examples of the use of the methods 1n this section of the report are
presented 1n Appendix A-3.
4.2 Identification of Exposed Populations
Exposed populations can be Identified either through knowledge of the
sources of chemical contamination or by examination of monitoring data.
89
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The former 1s a "materials balance" approach and comprises three types of
sources Identifiable by an examination of a substance's use and release
Information:
1. Sources that result from agricultural practices (e.g., pesticide
application, fertilization, growth hormones).
2. Sources related to processing and packaging procedures (e.g.,
contaminants Introduced during canning, contaminants 1n food
preservatives, leaching of contaminants from packing).
3. Other Identifiable sources (e.g., ocean dumping, Industrial
effluents, contamination of animal feed during Industrial
processing).
Monitoring data may Identify food Items with contamination of unknown
origin. The "Market Basket Surveys" of the Food and Drug Administration
(OHEW 1975) are examples of monitoring data surveys that may Identify
contaminated food Items, the consumers of which are the exposed
population.
Comprehensive population Identification must consider all three
source types as well as available monitoring data. This Identification
will be conducted on a chemical-specific basis 1n the exposure assessment
process. The general procedure for Identification 1s presented 1n Method
4-1.
4.3 Methods for the Enumeration of Exposed Populations
Enumeration of the population eating a particular food Item 1s
straightforward; however, only a fraction of that population may consume
contaminated food. Information on the geographic distribution of food
Items following harvest and packaging or processing 1s not available.
Consequently, enumeration of the actual exposed population Is not
possible. Estimation of the population range 1n which the actual exposed
population exists, however, 1s possible. The upper limit of the
population range 1s equal to the total population that consumes a food
Item. The lower limit of the population range, based on the assumption
that the consuming population 1s directly proportional to the quantity of
the food Item contaminated, can be estimated by multiplying the upper
limit of the range by the percentage of the food Item contaminated (e.g.,
the percentage of the food Item grown 1n a particular geographic area,
raised by a particular agricultural practice, processed or packaged by a
particular procedure). The data bases and Information sources that
provide data and the methods to calculate the exposed population range
are discussed 1n the following subsections according to the categories
for Identifying the exposed populations.
91
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Method 4-1. Generalized Procedure for Identifying Populations Exposed to
Chemical Substances via the Ingestion of Food
Step 1 Obtain all available monitoring data for the substance being
assessed. Monitoring data for food items provide positive
identification of exposure; the population that consumes the
food item is an exposed population.
Step 2 Examine the uses of the substance being assessed. If it is
used in an agricultural practice, the food items on which it is
used may be contaminated. If it is used in a food processing
procedure or in a packaging material, the food items processed
or in contact may also be contaminated; the population that
consumes the potentially contaminated food item is an exposed
population.
Step 3 Examine the sources of the substance in the ambient
environment. Knowledge of these sources, coupled with
knowledge of the fate and transport of the substance in the
environment, leads to the identification of the potentially
contaminated food item; the population that consumes the food
item is an exposed population.
92
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4.3.1 Enumeration of Populations Exposed as a Result of Agricultural
Practices
Enumeration of the population exposed to a chemical substance as the
result of consuming a food Item contaminated from an agricultural
practice requires two steps. The Investigator must first ascertain the
size of the population that consumes the food Hem. This 1s the upper
limit of the range of the exposed population. The percent of the total
quantity of the food Hem that 1s produced via a specific agricultural
practice must then be determined. This percentage multiplied by the
number for the total consuming population yields an estimate of the lower
limit of the range of the exposed population.
Values for the percent of the U.S. population that consumes a
specific food Hem are available for some food Hems from the U.S.
Department of Agriculture (USOA) Food Consumption Surveys. USDA Food
Consumption Surveys are conducted approximately every 10 years. The most
recent survey was 1n 1977-78, but the complete data reports for the
1977-78 survey have not yet been released. Therefore, the Investigator
must use data collected 1n the 1965-66 survey. Food Consumption of
Households In the U.S.. Seasons and Year 1965-66 (USDA 1972) presents
data on food consumption by households 1n the 48 conterminous states for
the period from April 1965 to March 1966. The percent of 15,112
households using selected food Hems for a seven-day period prior to the
Interview 1s presented.
The food Hems for which data are available represent a wide range of
major food groups. The households surveyed were scientifically selected
to represent a self-weighting sample of housekeeping households 1n each
of four census regions during each of the four seasons. Excluded from
the survey were those households In which no member ate as many as 10
meals from the household food supply during the seven days preceding the
Interview. Food Consumption of Households 1n the United States. Seasons
and Year 1977-78. the most updated version of the 1972 USDA report, 1s
expected to become available 1n mid 1983. Food Consumption of Households
1n the U.S.. Spring 1977 (USDA 1982) presents preliminary data on food
consumption of households 1n the 48 conterminous states during the period
from April to June of 1977. Like the 1965-66 survey, this one presents
the percent of 15,000 households using food Hems for a period of seven
days prior to the survey. Unlike the survey of 1965-66 (USDA 1972), the
survey of 1977-78 (USDA 1982) Included households regardless of the
number of meals eaten away from home.
93
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Information used to obtain values for the percent of a food Item
produced via a specific agricultural practice or 1n a specific geographic
area 1s available for select food Items from two data sources. The 1978
Census of Agriculture. U.S. Summary (Bureau of the Census 1982a)
presents statistics for the leading states and counties for select
agricultural products based on data obtained from the Census of
Agriculture. More detailed Information was obtained for farms with sales
of $2,500 or more than for farms with less gross sales. Statistics on
value of agricultural products sold, number of acres harvested, and
quantity harvested are Included.
Agricultural Statistics 1978 (USOA 1978) also presents data for
production and value of select agricultural products and utilization
(e.g., fresh, frozen, canned, dried) of quantities sold. Some statistics
for states are Included. If the quantity of a food Item harvested from a
specific geographic region 1s desired and 1s not Included 1n either of
these two sources, the Information, 1f available, can be obtained by
contacting the Statistical Reporting Service-Crop Reporting Board of the
United States Department of Agriculture ((202) 447-4020).
The basic steps for enumerating populations exposed to chemical
substances via the 1ngest1on of food contaminated by some form of
agricultural practice 1s presented 1n Method 4-2. The approach can be
used for virtually any situation.
4.3.2 Enumeration of the Populations Exposed as a Result of Processing
and Packaging
The procedures for enumerating the population exposed to a chemical
substance as a result of consuming a food contaminated during processing
and packaging are similar to the procedure discussed 1n Section 4.3.1.
If a food 1s contaminated during a processing procedure (e.g., canning,
freezing, drying), the Investigator must determine the percent of the
U.S. population that consumes the processed food Item. This percentage
1s multiplied by the total 1980 U.S. population to determine the
consuming population. If the chemical substance contaminating the
processed food 1s generic to all methods for producing the processed food
Hem, then the exposed population Is equal to the consuming population.
If, however, the chemical substance Is specific to only certain methods,
then the consuming population 1s the upper limit of the range of the
exposed population. To determine the lower limit of the range of the
exposed population, the Investigator must determine the fraction of the
food that undergoes the specific processing method; this fraction Is
multiplied by the consuming populations.
94
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Method 4-2. Enumeration of Populations Exposed as a Result of
Agricultural Practices
Step 1 Determine the percentage of households that consume a specific
food item by consulting Food Consumption of Households in the
U.S.. Spring 1977 (USDA 1982). Statistical evaluation of
seasonal data by USDA (1972) indicates that household food
consumption at home in the spring is more representative of
average consumption during the year than is consumption in the
simmer, fall, or winter. Food Consumption of Households in the
U.S.. Seasons and Year 1977-78. the best information source,
will be published in mid 1983.
Step 2 Multiply the percentage determined in Step 1 by the total U.S.
resident population in 1980 of 226,500,000 (Bureau of the
Census 1982b) to calculate the consuming population or the
upper range of the exposed population.
Step 3 Define the contaminated area by county, and determine the
percentage of the total quantity of the food item harvested
from the geographic area subjected to the agricultural practice
by consulting the 1978 Census of Agriculture (Bureau of the
Census 1982a) and Agricultural Statistics (USDA 1978). If the
information needed is not in this report, contact the USDA,
Statistical Reporting Service - Crop Reporting Board
((202) 449-4020).
Step 4 Multiply the fraction derived in Step 3 by the value calculated
for the consuming population in Step 2. The resulting value is
the estimated lower limit of the exposed population.
95
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The technique for enumerating the population exposed to a chemical
substance 1n food as a result of packaging 1s the same as that discussed
for exposure from processing. The consuming population (I.e., the upper
limit of the exposed population) 1s estimated first. The Investigator
determines what fraction of the food undergoes a specific packaging
procedure and then multiplies that fraction by the population estimated
to consume the food Item to estimate the lower limit of the range. The
following paragraphs discuss the sources of Information for the data
needed to perform these calculations.
The report Food Consumption of Households 1n the United States.
Spring 1977-78 (USDA 1982) should be used to obtain values for the
percentage of the U.S. population that consumes select food Items. This
data source has been discussed 1n detail 1n the previous subsection.
This report also Includes data on processed food consumption for select
food Items (e.g., canned peas, frozen peas, powdered milk).
There 1s no comprehensive source of data reporting the percentage of
specific methods and chemicals for processing or packaging materials for
specific foods and beverages (e.g., the percentage of meats processed
with or without nitrites; the percent of frozen broccoli packaged In
cardboard vs. that packaged 1n plastic film). This Information may be
available from the trade association corresponding most closely to the
food Item or packaging procedure 1n question. For a comprehensive
listing of trade associations, consult the most recent Issue of the
"Encyclopedia of Associations" published by Gale Research, Inc. The
procedural steps to enumerate populations exposed to a chemical substance
via the 1ngest1on of food contaminated by processing and packaging are
presented 1n Method 4-3.
In some Instances, the contamination from processing or packaging of
a specific food Hem may result from procedures used by a specific
company. The number of people that consume a specific brand of food or
beverage can be estimated for select foods and beverages from the Simmons
Media Studies Volumes on Food and Food Marketing. Alcoholic Beverages.
and Carbonated Soft Drinks and Pet Food (SMRB 1977). EPA-OTS 1s 1n the
process of acquiring the latest Simmons Market Research Bureau (SMRB)
reports. Volumes for 1976-77 are available 1n the Washington, D.C. area
at the George Mason University Library.
The SMRB studies are designed to make 1t possible for advertisers and
agencies to assess the relative values of media 1n terms of marketing
potential for over 500 product and service categories and 3,000
Individual brands. The studies present demographic and lifestyle
characteristics, media habits, and product use, based on data collected
from one of the largest annual national consumer probability samples
taken. Respondents are selected to represent the conterminous U.S.
population 18 years of age and older. It should be noted that, for most
food Items listed, the number of users 1s based on the total U.S.
96
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Method 4-3. Enumeration of Populations Exposed as a Result of
Packaging and Processing of Food
Step 1 Determine the percentage of users of the food from Food
Consumption of Households in the U.S. Spring 1977 (USDA 1982).
This report contains values for both processed and unprocessed
foods.
Step 2 Multiply the percentage (i.e., fraction) obtained in Step 1 by
the U.S. population in 1980 of 226,500,000 (Bureau of the Census
1982b) to estimate the consuming population. This is the upper
limit of the exposed population. If the chemical substance is
generic to all methods for producing the processed food, then
the exposed population is equal to the total consuming
population.
Step 3 If a chemical substance is introduced to a food item (1) via a
specific method for processing or (2) from a packaging procedure
or material, investigators must determine what portion of total
production for that food item is affected. These data may be
difficult to obtain. Food Consumption on Households in the U.S.
Spring 1977 (USDA 1977) provides data on the percentage of users
of food items prepared by such processes as canning, drying, and
freezing. Trade associations that are related to the food item
may have this information. Processing and packaging
associations (e.g., National Food Processors Association,
Washington, D.C.) may also have this information. For a
comprehensive listing of trade associations, consult the most
recent issue of the "Encyclopedia of Associations" published by
Gale Research Corp.
Step 4 Multiply the total consuming population estimated in Step 2 by
the percentage determined in Step 3 to estimate the lower limit
of the range of the exposed population. If no information on
the percentage of the food item packaged or processed by the
method causing contamination is obtained in Step 3, the upper
limit estimated in Step 2 should be used; however, it should be
clearly labeled as a possible overestimate.
97
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population of female homemakers (the buyers of the food) and not the
total U.S. population 18 years of age and older. The data, however, can
be used to approximate household use. Section 5 of this volume,
Populations Exposed to Chemical Substances via the Use of Consumer
Products, provides greater detail on the use of SMRB data.
To enumerate the population exposed as a result of consuming food
contaminated by processing or packaging procedures used by a specific
company, the general approach described 1n Method 4-4 should be used. In
some cases, data will be reported only for the female homemaker. To
extrapolate for the total consuming population, Investigators should
(1) refer to SMRB data (which provide the number of persons 1n the
buyer's household) or (2) use a generic multiplication factor of 2.73
persons per household (Bureau of the Census 1982c).
4.3.3 Enumeration of Populations Exposed as a Result of Releases
from Other Sources
This category Includes all forms of food contamination that are not
the result of either an agricultural practice or a processing and
packaging procedure. This section concentrates principally, however, on
chemical substances Introduced as a result of accidents (e.g.,
Introduction of PBB to cattle feed 1n Michigan) and from point source
airborne or waterborne effluents (fish contaminated from Industrial
discharges, airborne partlculates deposited on fruits and vegetables).
The source of the chemical substance need not be Identified. The methods
1n this section also apply to foods from geographically defined areas of
contamination which have been Identified from monitoring data. This
special case 1s discussed 1n Subsection 4.3.4.
The procedure for enumerating the population exposed to a chemical
substance as the result of consuming a food Item contaminated from such
sources 1s similar to the procedures previously discussed. The
Investigator must first determine the percent of the U.S. population that
consumes the food Hem. This percentage 1s applied to the total 1980
U.S. population to determine the total consuming population. Next, the
percent of the total quantity of the food Item 1n the U.S. from the
geographic area affected by the source of contamination must be
ascertained. The product of the total consuming population and the
percent of the food Item affected by the source provides an estimate of
the lower limit of the exposed population.
Four basic food groups may be affected by these sources of
contamination: agricultural products, freshwater fish and game, seafood,
and home grown foods. The method used to enumerate the exposed
population 1s different for each of these basic food groups.
(1) Agricultural products. To enumerate the U.S. population exposed
to a chemical substance as a result of consuming a contaminated
agricultural product, the Investigator should use the method for
enumerating the population exposed as a result of agricultural practices
98
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Method 4-4. Enumeration of Populations Exposed as a Result of Packaging
or Processing Procedures Used by a Specific Company
Step 1 Identify the affected brand of food, and obtain use data from
the Simrons Market Research Bureau reports (SMRB 1977). Users
may be reported as total adults or female homemakers.
Step 2 Estimate the total consuming population for the food brand.
Option 1 - The average number of persons per household is 2.73.
Assuming that there is one food shopper per
household, multiply the total number of buyers by
2.73 to calculate the exposed population.
Option 2 - Sinmons data are aggregated by the number of persons
in a user's household. (This is fully discussed in
Section 5.3.1 of this report.) The calculation is
performed as follows:
1 person household = number of buyers x 1 = A
2 person household = number of buyers x 2 = B
3-4 person household = number of buyers x 4 = C
5 or more person household = number of buyers x 6 = D
A+B+C+D= total exposed population (estimated
conservatively).
99
-------
(see Method 4-2, described 1n Section 4.3.1). Instead of determining the
percent of the total quantity of the food Hem harvested from the
geographic area subjected to the agricultural practice (Step 3),
determine the percent of the food from the geographic area that has been
contaminated.
(2) Noncommercial fish and game. To enumerate the U.S. population
exposed to a chemical substance as a result of consuming contaminated
freshwater fish or game, the Investigator can use Information from the
fish and game commission of the state 1n which the contaminated area 1s
located. The sample population for these surveys comprises hunters and
fishermen who have purchased licenses from the state conducting the
surveys. Based on Information from the few states contacted, most states
conduct surveys of this nature about every five years. An example of the
type of survey Information that may be pertinent 1s the summary of
applicable categories of results Included 1n the 1975 Fishing Survey
conducted by the State of West Virginia (West Virginia DNR 1979). These
categories Include:
1. Estimated number of fishermen and days fished by type of fishing.
2. Estimated number of fishermen and days fished by district (WVA
ONR) fished and type of fishing.
3. Estimated number of fishermen and days fished by river system
and major river.
4. Estimated number of fishermen and days fished 1n lakes and
Impoundments.
To enumerate the population exposed to a chemical substance as a
result of consuming noncommercial freshwater fish or game contaminated,
from an Identified source, the Investigator should use Method 4-5. The
estimated exposed population obtained 1n Step 1 of this method
underestimates the actual exposed population because 1t represents the
number of licensed hunters or fishermen 1n a defined geographic area and
does not Include all the consumers of the fish or game (such as friends
and family members). If 1t 1s assumed that each license represents a
household, the exposed population can be estimated, as presented In
Step 2, by multiplying the number of licenses by 2.73, the average number
of persons per household (Bureau of the Census 1982c).
(3) Commercial fish and shellfish. To enumerate the population
exposed as a result of consuming seafood contaminated by releases from an
Identified source, one must determine the percent of the U.S. population
that consumes the food Item. The percent of the total quantity of the
food Item from the geographic area affected by the source of
contamination must also be ascertained.
100
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Method 4-5. Enumeration of Populations Exposed as a Result of
Consuming Noncommercial Freshwater Fish or Game
from a Geographically Defined Area of Contamination
Step 1 Obtain the number of licensed fishermen or hunters reported to
fish or hunt in the geographically-defined area of contamination
by contacting the state fish or game commission. The best
source of this information is usually the most recent fish and
game survey conducted by the state fish and game commission.
Step 2 Estimate the upper limit of the actual exposed population by
assuming that each licensed fisherman or hunter represents a
consuming household. Since there are 2.73 persons in the
average household (Bureau of the Census 1982c), a rough estimate
of the actual exposed population can be calculated by
multiplying 2.73 by the number of licensed hunters or fishermen
obtained from Step 1.
101
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Values for the percent and projected number of Individuals 1n 1980
who consume the 45 most commonly eaten species of seafood are available
1n the Report to the National Marine Fisheries Service on Seafood
Consumption Patterns by NPO Research Inc. (NPD 1977). Table 16
summarizes the statistics on seafood consumption compiled by NPO (1977).
The quantity of the food Hem from the geographic area affected by
the source of contamination can be obtained from a computerized data base
maintained by the National Oceanic and Atmospheric Administration (NOAA)
for all states except Maryland. The NOAA data base Includes catch
records by NOAA area or by county for oysters, flnflsh, and crabs. Catch
records for clams are available only for descriptive areas such as "Mouth
of the Patuxent River." Catch records for clams, oysters, and flnflsh
are available 1n the form of dally records for the years 1975 through
1981. Catch records for crabs are available only for 1981. For
Information on retrieving data from the NOAA computerized data base,
contact Oaryl Chrlstensen of the National Marine Fisheries Service at
(201) 872-0200. For retrieval of data on seafood catches for the
Chesapeake Bay, contact M1ke Burch of the Statistics Division of the
Maryland Department of Natural Resources at (301) 269-3784. There 1s no
charge to government agencies for either of these services.
For Information on the total quantity of seafood species caught In
the United States, the statistics on commercial fishery landings
published 1n Fisheries of the United States. 1980 by the National Marine
Fisheries Service of NOAA (NOAA 1981) can be used.
The general approach for enumerating the population exposed to a
chemical substance as a result of consuming seafood contaminated by
releases from an Identified source 1s presented 1n Method 4-6.
Table 16 Includes a few freshwater fish species. Method 4-6,
however, cannot be used to enumerate the population exposed as a result
of consuming these fish species. To obtain such Information,
Investigators must ascertain the quantity of freshwater fish caught
annually from the geographically defined area of contamination. Although
the quantity of select seafood Hems caught from a geographically defined
area of contamination can be obtained from computerized NOAA data, no
similar data base for freshwater fish was found.
(4) Home grown fruits and vegetables. In 1977, 1t was estimated
that 44 percent of U.S. households (32 million households) had home
gardens (USEPA 1980). Furthermore, 80 percent of these 32 million
households had gardens every year, and 40 percent of these 32 million
households had had gardens for 11 years or more. The consumption of home
grown foods, therefore, may be a significant route of exposure, both
short- and long-term, 1f the garden 1s located near a point source of
contamination, such as a smelter.
102
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Table 16. Ranking of Seafood Species by Percent of Individuals Consuming and
Projected 1980 Consuming Population
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Species
Total sample
Total seafood
Tuna, light
Shrimp
Flounders
Ocean Perch
Salmon
Clams
Cod
Pollock
Haddock
Herring
Oysters
Crab, other than King
Trout (Freshwater)
Catfish (Freshwater)
Bass
Lobster, Northern
Hackeral , Other than Jack
Halibut
Scallops
Whitefish
Snapper
Hake
Pike
Lobster, Spiny
Smelt
Perch (Freshwater)
Bluegills
Bluefish
Crappie
Trout (Marine)
Bon i to
Crab, King
Mullet
Number of
users
25,947
25,165
16,817
5,808
3,327
2,519
2,454
2,242
1,492
1,466
1,441
1,251
1,239
1,168
970
876
826
675
616
574
526
492
490
392
390
350
328
268
265
236
228
220
148
130
97
Percent Projected number of
of sample total 1980 population
size (X 1,000)
100.0
94.0
64.8
22.4
12.8
9.7
9.5
8.6
5.6
5.6
5.6
4.8
4.8
4.5
3.7
3.4
3.2
2.6
2.4
2.2
2.0
1.9
1.9
1.5
1.5
1.3
1.3
1.0
1.0
0.9
0.9
0.8
0.6
0.5
0.4
226,000
204,000
146,000
50,600
28,900
21,900
21 ,500
19,400
12,700
12,700
12,700
10,800
10,800
10,200
8,360
7,680
7,230
5,880
5,420
4,970
4,520
4,290
4,290
3,390
3,390
2,940
2,940
2,260
2,260
2,030
2,030
1,810
1,360
1,130
904
103
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Table 16. (Continued)
Rank
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
Species
Spot
Croaker
Anchovies
Rockfish
Catfish (Marine)
Groupers
Carp
Buffalofish
Sunfish
Drums
Scup
Other Shellfish
Aba lone
Squid and Octopi
Swordfish
Butterfish
Shad
Dolphin
Tuna, white
Mackeral , Jack
Snook
Tilefish
Blue Crab
Pompano
Kingfish
Sablefish
Sharks
Number of
users
91
76
75
75
70
68
64
60
60
58
55
54
48
45
41
39
39
34
22
13
13
11
11
10
8
7
3
Percent
of sample
size
0.4
0.3
0.3
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.1
0.1
0.1
0.
0.
0.
0.
0.
0.1
0.1
Projected number of
total 1980 population
(X 1,000)
904
678
678
678
678
678
452
452
452
452
452
452
452
452
452
452
452
226
226
226
226
226
226
226
226
226
226
Source: NPD 1977, NOAA 1978.
104
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Method 4-6. Enumeration of Populations Exposed as a Result of
Consuming Seafood from a Geographically Defined Area of
Contamination
Step 1 Determine the number of users of the seafood by consulting the
information in Table 15 on projected number of individuals in
1980 who consumed the seafood item of concern.
Step 2 Determine the percentage of the total quantity of the item
caught for sale in the U.S. which is from the geographically
defined area of the source of contamination. This can be
accomplished by computing the quantity of the seafood caught
annually from the geographically defined area of contamination
based on computerized NOAA data. Next, the total quantity of
the seafood species caught in the United States annually must be
obtained from commercial fishery landings published in Fisheries
of the United States. 1980 (NOAA 1981). The fraction of the
total quantity of the seafood species caught for sale in the
U.S. which is from the geographically defined area of the source
of contamination can be computed by the following formula:
quantity of the seafood item caught from the
geographically defined area of contamination
total quantity of the seafood item caught in
the United States
Step 3 Multiply the fraction computed in Step 2 by the value determined for
the consuming population determined in Step 1.
105
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Table 17 presents data for the year 1977 on the percent of urban,
rural non-farm, and rural farm households with gardens as well as the
percent of the U.S. population for each category. These geographic
categories are consistent with the census geography of the Bureau of the
Census. Table 18 presents data on the percentage of total households
growing, freezing, canning, or preserving selected home grown fruits and
vegetables. The data presented 1n these two tables can be used to
enumerate local populations exposed to a chemical substance via the
consumption of Inadvertently contaminated home grown fruits and
vegetables. Method 4-7 presents that procedure.
4.3.4 Enumeration of Exposed Populations by the Use of Monitoring Data
The source of contamination of a food Hem will frequently be
unknown. The fact that contamination exists, however, can be positively
confirmed through monitoring data collected. Market Basket Surveys such
as those conducted by the Food and Drug Administration (DHEW 1975)
exemplify how food contamination can be detected. The consumers of the
food Hem 1n which the substance has been detected are the exposed
population.
Monitoring data can be used to predict the number of people consuming
foods containing a chemical substance. The method extrapolates data on
the frequency of detection of the substance. The accuracy achieved by
this tool depends on the form, representativeness, and sample size of the
data. The procedure for enumerating population by use of monitoring data
1s presented 1n Method 4-8.
The assumptions Inherent 1n this very gross estimation Include the
assumption that the data are Independent of the source of the
contamination or that the data represent the total food supply from all
geographic areas. Obviously, these assumptions limit the usefulness of
the method; H should only be used 1n the absence of more refined data.
The use of monitoring data to estimate the exposed population Is
limited 1n all cases by two assumptions. The sample size must be large
enough that the frequency of detection approximates the frequency of
occurrence, and Individuals who consume food containing the chemical at
levels below the detection limit are not Included 1n the exposed
population. Exposure below the detection limit may, however, be
significant for certain chemicals.
106
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Table 17. Percent of Households, U.S. Population, and Household Size
in Urban, Rural Non-Farm, and Rural Farm Areas with Home
Fruit and Vegetable Garden in 1977
Urbanization
Urban
Rural non-farm
Rural farm
Percent households
with garden
43
41
84
Household
size (number
of persons)
3.17
3.44
3.86
Percent of total
U.S. population
32
9
3
Source: USEPA (1980).
107
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Table 18. Percent Gardening Households Growing, Freezing, Canning,
or Preserving Selected Home Grown Fruits and Vegetables,
1975-77
Item
Grown
1975 1976
1977
Frozen
1975 1976
1977
Canned or Preserved
1975 1976 1977
Vegetables
Tomatoes 95 97 91 26 29 26 65 66 58
Beans (green, wax, lima, etc.) 71 69 70 54 49 55 42 35 38
Cucumbers 62 61 59 4*2 29 23 29
Peppers 61 60 60 28 28 32 10 11 7
Radishes 59 54 50 * * * * * *
Green onions (scallions) 58 54 50 2*4 1 * *
Lettuce 56 55 51 1 * * * * *
Onions 52 54 48 3** 4**
Carrots 50 46 46 15 12 16 898
Corn 50 44 49 41 36 39 15 9 11
Squash 45 41 41 21 19 22 843
Beets 40 42 38 779 29 29 24
Peas 40 36 38 27 26 31 747
Turnips 26 25 22 764 112
Potatoes 10 37 39 * * * * * 3
Cabbage 7 37 40 * * 10 * 2 8
Fruits
Strawberries 22 21 22 16 13 14 943
Apples 20 17 20 11 8 13 15 7 10
Melons 13 15 17 3 * * 1 * *
Peaches 13 10 12 757 10 5 7
Pears 10 7 8 3 * * 10 * 1
Rasberries, blackberries,
blueberries, etc. 6 10 16 5 7 12 345
*Either not mentioned or mentioned by less than 1 percent of the gardening households surveyed.
Source: USEPA (1980).
108
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Method 4-7. Enumeration of Populations Exposed to
Chemical Substances via the Consumption of
Home Grown Fruits and Vegetables
Step 1 Identify the geographic area contaminated from the source of the
chemical substance (e.g., industrial point source, area source).
Step 2 Determine the number of households in the geographic area from
General Population Characteristics. Series PC80-1-B (Bureau of
the Census 1982b).
Step 3 Multiply the number of households obtained in Step 2 by the
percent of households with home fruit and vegetable gardens for
the type of urbanization from Table 16. This is the number of
households with fruit and vegetable gardens in the area
contaminated, the inhabitants of which are the potentially
exposed population.
Step 4 Enumerate the exposed population by multiplying the number of
households from Step 3 by the household size for the degree of
urbanization also available in Table 16.
Step 5 Steps 3 and 4 determined the number of households and
individuals that have fruit and vegetable gardens, not the
households that grow a specific type of food. If the chemical
substance is absorbed by a specific food item, the data in
Table 17 can be used. For example, if a pollutant is absorbed
specifically by lettuce, the number of households for each
population category estimated in Step 3 must be multiplied by 51
percent, the percentage of gardening households that grow
lettuce according to the latest available data. These results
should then be multiplied by household size (Table 16) to
enumerate the exposed population.
109
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Method 4-8. Enumeration of Exposed Populations by the Use of
Monitoring Data
Step 1 Identify the food items contaminated as a result of the
monitoring survey results.
Step 2 Enumerate the total consuming population for each of the food
items identified. The enumeration procedures of Methods 4-2,
4-5, 4-6, or 4-7 should be used to estimate the consuming
population. This is the upper limit of the range of the exposed
population (i.e., all consumers of the food item eat some
contaminated food).
Step 3 Calculate the frequency of detection from the monitoring data;
if detected in 10 of 100 samples, the detection frequency is 10
percent.
Step 4 Multiply the detection frequency by the total consuming
population as enumerated in Step 2 to estimate the exposed
population. This is the lower limit of the range of the exposed
population (i.e., the exposed population consumed only
contaminated food).
110
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4.4 Characterization of the Exposed Population
This subsection describes the data sources and procedures for
characterizing the exposed population with respect to age and sex. In
most exposure assessments, age and sex characterization will not be
necessary. If, however, the chemical substance of Interest has special
effects on particular age classes such as children or the elderly,
further characterization of the enumerated population 1s Indicated. If a
chemical substance 1s determined to be teratogenlc, enumeration of women
of child bearing age may be required. Age and sex also Influence the
average rate of food Intake and the types of food consumed. Construction
of a plausible worst-case exposure scenario for contaminated food may,
for Instance, focus on males 19 to 22 years of age; they have the highest
average dally food Intake rate (USDA 1980).
The simplest and most rapid method of characterizing a large
population 1s to assume that the age and sex distributions approach those
of the total U.S. population. This approach can be used only for very
large, generally-defined populations. For example, the population
consuming the typical "American Diet" or those who consume groups of
major food categories approximate the national distribution. The age and
sex distribution by percentage of the total U.S. population has been
presented 1n Table 12 of Section 2.4 of this report (Characterization of
Populations Exposed to Chemical Substances 1n the Ambient Environment).
The characterization of populations exposed to chemical substances
through the consumption of particular food Items, however, often requires
a much more accurate approach; the defined food preferences vary greatly
according to particular age and sex, and even by sex within age classes.
There are two data sources for characterizing populations exposed to
chemical substances via food consumption: USOA's food consumption
surveys for Individuals and the Simmons Market Research Bureau reports.
The USDA data are applicable to populations eating various types of food,
while SMRB marketing Information 1s useful for characterizing consumers
of specific brands of foods.
The Individual food consumption surveys conducted by USDA were
designed to be representative of the U.S. population. As a result, the
age and sex distribution of the sampled population closely approximates
that of the U.S. as a whole. Data on usage are reported for various age
and sex groups, as Illustrated 1n Figure 18, as percentages of the total
sample within that group. Percents reported under the column heading for
the food of Interest can be applied directly to the total U.S. population
for that age/sex classification to characterize the exposed population.
Method 4-9 presents the steps to be performed for this type of
characterization.
111
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TABLE 1.2b.—MILK, MILK PRODUCTS; EGGS; LEGUMES, NUTS, SEEDS
Individuals using1 in a day,2 spring 1977
46 States, all urbanizations, all incomes
Sex and age
(years)
Individuals
: M,i
Total : Total
Kilk, mi Ik products
Ik, milk drinks :
: Fluid : Yogurt :
: nuilk : :
Cream, :
milk : Cheese
desserts :
Eggs
Legumes,
nuts,
seeds
Males and females:
Under 1
1-2
3.5
6-8
Kales:
9-H
12-14
15-18
19-22
23-34
35.50
51-64
65-74
75 and over
Females:
9-11
12-14
15-18
19-22
23-34
35.50
51-64
65-74
All individuals...
3 78
••264
437
469
216
313
400
287
770
784
634
295
127
241
309
402
337
949
942
792
377
197
59,620
92.2
93.4
91.7
93.4
92.9
90.2
85.9
81.6
73.8
75.8
77.8
81.3
80.7
92.5
88.6
85.4
78.1
74.3
73.0
73.9
80.3
84.2
80.7
92.2
90.9
87.8
90.5
90.7
86.3
77.3
74.3
58.3
57.6
61.8
71.2
67.9
88.8
80.9
74.7
65.1
58.6
55.2
58.2
68.4
73.1
68.8
60.9
90.5
85.6
88.5
87.9
81.1
75.7
69.7
53.6
56.5
60.9
70.4
66.3
86.8
76.2
69.2
62.3
54.5
52.6
56.0
67.3
71.4
65.9
0
.6
.3
1.2
.5
.4
.7
1.3
2.9
.8
1.1
.3
0
0
.3
2.0
1.9
3.4
2.8
2.5
2.7
2.0
1.7
6.5
19.3
21.8
25.0
24.3
23.0
27.9
16.4
21.9
24.1
26.2
2S.1
25.8
25.6
22.7
24.2
18.3
18.8
21.4
21.1
26.9
28.4
22.8
3.6
21.7
21.0
19.7
16. 1
14.5
20.7
26.0
28.3
27.0
25.9
24.8
25.2
16.8
22.8
24.9
26.9
28.5
28.0
26.8
25.6
24.5
24.7
10.0
33.3
33.6
24.3
26.4
28.8
30.4
3C.1
33.7
39.8
40.1
47.7
51.5
19.7
23.4
25.5
27.2
31.3
28.0
33.2
32.9
32.2
31.9
14.5
22.8
30.7
29.4
28.0
27.5
20.9
17.7
19.7
22.5
20.5
15.2
20.3
30.6
21.0
18.0
14.3
18.2
17.4
17.1
11.7
9.6
20.2
1 User is an individual reporting a specified food item.
2 Based on 24-hour dietary recall of day preceding interview.
3 Excludes 36 breast-fed infants.
5Excludes 4 breast-fed infants.
Excludes 40 breast-fed infants.
Source: USDA (1980).
Figure 18. Example Data Summary from National Food Consumption Survey of 1977-78
112
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Method 4-9. Characterization of Populations Exposed to Chemical
Substances in Types of Food
Step 1 Locate the food item usage data in the USDA (1972, 1980) food
consumption surveys for individuals in one day. The more recent
(1980) data should be used whenever possible.
Step 2 Apply the "percent using" value for each age/sex category to the
corresponding total population in that category (from Table 13).
Step 3 Compare "percent using" for the total sample as reported in the
one-day survey to the "percent using" reported in the USOA
(1982) one-week household consumption survey. This comparison
will provide a qualitative indicator of the one-day survey's
accuracy. If the data values are significantly different (i.e.,
the individual consumption data in USOA (1972, 1980)
underestimates the consuming population), the total consuming
population should be estimated using household data (USDA 1982)
as presented in Step 1 of Method 4-2. The percentage of the
total consuming population that is in the age or sex group of
interest should be determined from the individual survey data
(USOA 1972, 1980). This is calculated by aggregating the
consumers for each age or sex class and dividing by the total
consuming population of the individual sample. This percentage
should then be applied to the total consuming population
determined from the household data to characterize the exposed
population (See Appendix A-3, problem 7).
113
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Though the sample population 1s representative of the age and sex
distribution of the U.S. population, a limitation Inherent In the one-day
survey biases the data. Consumption during one day may not be
representative of normal eating patterns; this generally results 1n an
underestimate of the number of consumers of specific foods. The one-day
survey 1s, however, the only source of consumption data that presents the
Information by age and sex. Method 4-9 provides an approach to determine
the accuracy of the Individual consumption data and a procedure that can
be used to eliminate the error.
Age and sex distributions of populations that consume specific brand
names of food can be derived from the Simmons Market Research Bureau
Reports. The most recent version of this report 1s available 1n
EPA-OTS. Reports for the years 1977 through 1978 are available In the
Washington, D.C., area at the George Mason University Library. SMRB
reports present demographic data for most major brand name food Items.
Section 5 of this report discusses the use of SMRB data to
characterize populations using consumer Hems; that discussion 1s equally
relevant to food consumption. In essence, SMRB presents Information on
the frequency that sample households Include children within certain age
groups. The ages of the adults 1n the household are similarly reported
as frequencies. A general age distribution can thus be compiled easily
for any item; the proportion of males and females can be assumed.
114
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4.5
References
Bureau of the Census. 1982a. 1978 Census of Agriculture. Volume 1.
United States - State and County Data. Washington, DC: U.S. Department
of Commerce.
Bureau of the Census. 1982b. 1980 Census of population. General
population characteristics, U.S. Summary. Washington, DC: U.S.
Department of Commerce. U.S. Government Printing Office.
Bureau of the Census. 1982c. Statistical abstract of the United
States. National data book and guide to sources. Washington, D.C.:
U.S. Department of Commerce.
DHEW. 1975. Department of Health, Education and Welfare. Compliance
program evaluation. FY 1874 heavy metals 1n foods survey. Washington,
DC: Bureau of Foods.
NOAA. 1978. National Oceanic and Atmospheric Administration. Report on
the chance of U.S. seafood consumers exceeding the current acceptable
dally Intake for mercury and recommended regulatory controls.
Washington, DC: U.S. Department of Commerce, National Marine Fisheries
Service, Seafood Quality and Inspection Division.
NOAA. 1981. National Oceanic and Atmospheric Administration. Fisheries
of the United States, 1980. Washington, DC: U.S. Department of
Commerce, National Marine Fisheries Service.
NPD. 1977. NPD Research. Report to National Marine Fisheries Service
on seafood consumption patterns. Washington, D.C.
SMRB. 1977. Simmons Market Research Bureau Inc. 1976/1977 Selective
markets and media reaching them. New York, NY: Simmons Media Studies.
USDA. 1972. U.S. Department of Agriculture. Food consumption of
households 1n the U.S., seasons and year 1965-66. Washington, DC:
Agricultural Research Service.
USDA. 1978. U.S. Department of Agriculture. Agricultural Statistics
1978. Washington, DC: United States Government Printing Office.
USDA. 1980. U.S. Department of Agriculture. Food and nutrient Intakes
of Individuals 1n 1 day 1n the United States, Spring 1977. Nationwide
food consumption survey 1977-78. Preliminary report No. 2. Washington,
DC: Science and Education Administration.
115
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USDA. 1982. U.S. Department of Agriculture. Food consumptions:
households 1n the United States, Spring 1977. Nationwide food
consumption survey 1977-78, report no. H-l. Washington, DC: Consumer
Nutrition Center, Human Nutrition Information Service.
USEPA. 1980. U.S. Environmental Protection Agency. Dietary consumption
distributions of selected food groups for the U.S. population.
Washington, DC: Office of Pesticides and Toxic Substances, Office of
Testing and Evaluation. EPA 560/11-80-012.
West Virginia DNR. 1979. West Virginia Department of Natural
Resources. 1975 Fishing Survey. Division of Wildlife Resources.
116
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5. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE USE OF CONSUMER
PRODUCTS
5.1 Introduction
This section presents methods for enumerating and characterizing
populations exposed to chemical substances via the use of consumer
products. The methods described are applicable to new and existing
substances 1n consumer products. Figure 19 1s a flow diagram of the
three-stage method framework. Included 1n the diagram are some of the
major data sources used.
The Identification of the exposed population 1s discussed only
briefly 1n this report (Subsection 5.2). The process 1s straightforward
and relies primarily on materials balance Information and data generated
by the consumer exposure assessment methods report (Volume 7).
Enumeration of exposed populations may Involve one or more steps and
a variety of data sources. Subsections within Section 5.3 describe the
sources of data applicable to enumeration of consumers and methods for
utilizing and refining available data.
The age and sex of the exposed consumers affect the physiological
parameters (I.e., breathing rate, skin surface area) that determine
exposure; they also Identify sensitive subpopulatlons (e.g., women of
child-bearing age). Detailed exposure assessments may require that
populations be described by age and sex distribution. Subsection 5.4
discusses methods of characterizing exposed consumer populations.
Examples of the use of the methods 1n this section are presented 1n
Appendix A-4 of this report.
5.2 Identification of Exposed Populations
The Identification of populations exposed to chemical substances via
the use of consumer products (Method 5-1) necessitates a listing of all
products containing the chemical 1n question. The Information needed to
compile such a 11st Is derived from the materials balance for existing
chemicals, from Information submitted by Premanufacturing Notice (PMN)
petitioners, and through literature searches.
Exposure assessments for most existing chemicals Include a materials
balance delineating the uses for that chemical, as well as the amount
going to each use. A PMN submittal provides the corresponding
Information for new chemicals. PMNs are, however, usually Incomplete;
use Information 1s often general, and not all the potential uses of a new
chemical will be considered. Volume 7 of this series (methods for
assessing consumer exposure to chemical substances) presents methods to
predict uses for new chemicals.
117
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Method 5-1. General Procedure for Identifying
Populations Exposed to Chemical Substances
in Consumer Products
Step 1 Compile a comprehensive list of the consumer products known to
or thought to contain the chemical substance by consulting the
materials balance or PMN submittal.
Step 2 Determine whether all or a portion of the consumer product class
contains the chemical; if possible, identify by brand name to
expedite enumeration.
Step 3 Identify products obviously intended for use by males or females
or specific age groups.
Step 4 Evaluate each product (using the guidelines in Volume 7 of this
series) to determine whether passive exposure is of concern.
Consumer product use patterns will identify the passively
exposed population (i.e., family or household members).
119
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Many types of consumer products are of varied formulation, and only a
fraction of the product class (perhaps Identifiable by brand name) may
contain the chemical substance. This fact should be established during
the population Identification phase. For example, formaldehyde 1s used
1n some shampoos as a preservative; 1n order to define and enumerate the
population exposed to formaldehyde 1n shampoo, one must determine what
fraction or brands of the product class (shampoo) contain the chemical
(formaldehyde). Methods for that purpose are presented 1n Subsection 5.3.
Some products may cause exposure not only to the user (active
exposure) but also to others 1n the vicinity (passive exposure).
Volume 7 presents some guidelines for Identifying products that may cause
passive exposure. Generally, passive exposure to consumers results from
the use of household or personal care products; the passively exposed
population 1s the household of which the user 1s a member. Subsequent
sections address the concept of enumerating those passively exposed 1n
households.
5.3 Methods for the Enumeration of Exposed Populations
The effort required to enumerate consumers exposed to a particular
product depends on two factors: (1) the availability of data specific to
that product and (2) whether both active and passive exposure to the
substance are Involved. The following subsections guide the assessor 1n
obtaining the available data and present methods for their use.
5.3.1. Enumeration of Exposed Populations via Simmons Market Research
Bureau Reports
Simmons Market Research Bureau (SMRB) 1s a market research
corporation that collects Information on the buying habits of the
population through questionnaires administered to a nationwide panel of
consumers. The Simmons studies, "Selective Markets and the Media
Reaching Them" (SMRB 1982), are designed to serve retailers, advertising
agencies, and the media by providing up-to-date, comprehensive
Information on current and potential sales markets of consumer products.
SMRB data applicable to enumerating exposed consumer populations are
contained 1n 29 volumes organized by product category. Table 19 lists
the 29 product categories. These volumes contain Information on market
share, the number of buyers, and buyer demographics for over 500 consumer
products. Table 20 1s an alphabetical Index of Individual products and
services Investigated by SMRB.
120
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Table 19. Simmons Market Research Bureau Product
Categories and Services Provided by Volume
Volume Number
Volume Title
P-l
P-2
P-4
P-5
P-6
P-7
P-8
P-9
P-10
P-ll
P-12
P-13
P-14
P-15
P-16
P-17
P-18
P-19
P-20
P-21
P-22
P-23
P-24
P-25
P-26
P-27
P-28
P-29
P-30
Automobiles
Cycles, Trucks, Vans & Tires
Automotive Products & Services
Travel
Banking Investments, Memberships &
Public Activities
Insurance & Credit Cards
Books, Records, Tapes, Stereo & TV
Appliances, Sewing & Garden Care
Home Furnishings & Home Improvements
Sports & Leisure
Restaurants, Stores & Grocery
Shopping
At Home Shopping, Yellow Pages,
Florists & Telegrams
Jewelry, Wristwatches, Luggage &
Men's Apparel
Women's Apparel
Tobacco Products & Photography
Distilled Spirits & Mixes
Malt Beverages & Wine
Coffee, Tea, Soft Drinks, Juices &
Bottled Water
Dairy Products, Spreads, Cookies &
Desserts
Cereals, Rice, Pasta, Pizza, Fruits
& Vegetables
Soup, Meat, Fish, Condiments &
Dressings
Chewing Gum, Candy & Snacks
Soap, Laundry & Paper Products &
Kitchen Wraps
Household Cleaners, Room
Deodorizers & Pet Foods
Health Care Products & Remedies
Oral Hygiene Products, Skin Care &
Deodorants
Hair Care & Shaving Products
Women's Beauty Aids, Cosmetics &
Personal Products
Games & Toys, Children's & Babies'
Apparel & Specialty Products
Relative Volume of Consumption
Source: SMRB 1982.
121
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Table 20.
Alphabetical Index of Products and Services Measured
in the 1982 SMRB Study
Aches, Muscle, Head or Back
Active Participation in Sports
Activities, Public
Adhesive Bandages
Adult Education Courses
After Shave Lotion & Cologne
Ailments
Air Conditioner, Room
Air Conditioning, Central
Air Filters
Air Freshener Sprays & Room Deodorizers
Airlines
Alarm, Burglar
Alarm, Smoke/Fire Detector
Ale
Allergies
Allergy & Cold Remedies
Aluminum Foil
American/Pasteurized Processed Cheese
Ammunition, Factory Loaded
Amplifier/Receiver/Tuner, Stereo
Annual Mileage Driven
Anti-Freeze
Anti-Perspirants & Deodorants
Aperitif & Specialty Wines
Apparel/Men's, Women's & Children's
Archery
Arthritis or Rheumatism
Asthma Relief Remedies
Athlete's Foot
Athlete's Foot Remedies
Attendance at Sports Events
Auto Insurance
Auto Loan
Automatic Dishwasher
Automatic Dishwashing Detergent
Automatic Drip Coffee Maker
Automatic Garage Door Opener
Automatic Washing Machine
Automobiles
Auto Racing or Rallying
B
Baby Foods
Baby Formula, Liquid
Baby Lotion S- Bsby Oil
Baby Nursers
Babv Oil & Baby Lotion
Baby Powaer
Babv Shampoo
Backache
BacKpacking/Csmomg Equipment
Backpacking or Hiking
Baggage or Luggage
Bags, Garbage & Trasn Can Line's. Plastic
Bags. Sandwich or Food. Plastic
Baked Beans
Bandages Adhesive
Banking & Investments
Barbecue & Seasoning Sauces, Bottled
Bath Oil & Other Bath Additives
Bathroom Cleaners (Household Cleaners)
Bathroom Plumbing Fixtures
Batteries, Car
Battery or Electric Shaver
Bedroom Furniture
Beds
Beer
Bench/Table Circular Saw
Bicycle
Bicycling
Biscuits or Treats, Dog
Blankets, Electric
Blankets, Other (Not Electric)
Blank Tape Cartridge, Cassette, Reel
Bleach
Blended or Rye Whiskey
Blender, Electric
Blouse/Shirt, Women's
Blusher
Boats
Boating
Body & Hand Cream, Lotion or Oil
Bonds
Bonnet-Type Hair Dryer
Book Clubs
Books
Boots, Hiking or Climbing
Boots, Leather
Boots, Ski
Bottled Natural Spring or Mineral Water
Bouillon Cubes & Dry Soup Mix
Bourbon Whiskey
Bowling
Bowling Ball
Bowling Shoes
Brake Lining Pads
Brandy & Cognac
Brassiere
Bread
Breakfast Cereals
Breakfast Drinks, Powdered Fruit Flavored
Breath Fresheners
Built in Automatic Dishwasher
Burglar Alarm
Bus Companies. Domestic
Business Club Membership
Business Purchase Decisions
Bus-Tvpe Motor Home
Butter
Buving Style
Cabinets, Kitchen
Caoies. Telegrams & Wires
Cake Mixes. Drv
Cakes, Pies & Pastries. Frozen
Calculator
Cameras
Camper, Tent (Folding)
Camper or Travel Trailer, Towable
Camper, Truck Mounted
Camping/Backpacking Equipment
Camping Trips, Overnight
Camping Vehicles
Canadian Whisky
Candy Bars & Packages, Regular Size
Candy, Fun, Miniature & Snack Size
Candygram
Candy, Hard Roll
Canned Cat Food
Canned Dog Food
Canned or Jarred Fruits
Canned Ham
Canned Macaroni & Spaghetti Products
Canned Soup
Canned Tea
Canned Tuna
Canned Vegetables, or Jarred
Canning Jars & Lids
Canoe
Canvas Shoes
Car Batteries
Car Leasing
Carpeting
Carpet Squares
Car Polish & Wax
Car Rental
Cars
Cartridges, Blank Tape
Cartridges, Pre-Recorded Tape
Casseroles & Entrees (Frozen Main Courses)
Cassette Deck
Cassette, Video Recorder/Player
Cassettes, Blank Tape
Cassettes, Pre-Recorded Tape
Casual/Leisure Suit
Cat Food
Cat Ownership
Catsup
CB Base Unit
CB Mobile Radio
Ceiling, Floor or Wall Insulation
Ceiling Tile. Residential
Central Air Conditioning
Cents-Off Coupons
Cereals
Certificates of Deposit/Savings Certificates
Cham Saw
Champagne. Cold Duck & Sparkling Wines
Check Guarantee Caro
Checking Account
Checks. Travelers
Cheese
Chewing Gum
Chewing Tooacco
Children s Clothing
Children s Fever Reducers a Pain Relievers
Children s Shoes
122
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'Children's Vitamins
China, Fine
Chips, Corn & Tortilla, & Snacks
Chips, Potato
Christmas Club
Church Board Membership
Cigarette Rolling Paper
Cigarettes
Ciganllos & Little or Small Cigars
Cigars
Circular Saw
Citizens Band Base Unit
Citizens Band Mobile Radio
Civic Club Membership
Cleaners, Dram
Cleaners, Household (Including
Bathroom/Kitchen)
Cleaners, Oven
Cleaners, Rug
Cleaners, Toilet Bowl
Cleaners, Window
Cleansing Creams & Lotions
Cleansing Wipes, Pre-Moistened, For Babies
Climbing or Hiking Boots
Cloth Coat, Women's
Cloth Diapers
Clothes Dryer
Clothing, Men's
Clothing, Women's
Clothing, Children's
Club, Book
Club, Civic
Club, Country
Club, Health
Club, Record & Tape
Club, Religious
Club, Tape
Club, Veterans
Coats, Men's
Coats, Women's
Cocktail Mixes, Prepared
Cocktail Parties
Coffee
Coffee Maker
Cognac & Brandy
Com Collecting
Coins, Gold
Coins, Silver
Cola Drinks
Cold Cuts
Cold Duck. Champagne & Sparkling Wines
Cold & Allergy Remedies
Colds
College or School Board Membership
Cologne & After Shave Lotion
Cologne & Pertume
Coloring Products. Hair
Comb, Hair-Stvling, Electric
Comrorters/ Quilts
Common Stock
Comoact or Console Stereo
Compactor. Trash. Electric
Compact Pick-Up Truck
Complete Dinners. Frozen (TV Dinners!
Comolete Packagea Preparea Disnes
i Dinner Mixes
Comouter Home
Console or Compact Stereo
Constipation
Contact Lenses
Convection Oven
Convenience Stores & Supermarkets
Cooker, Pressure
Cookies (Ready-to-Eat)
Cooking for Fun
Cooking or Salad Oil
Cooking Spray, Non-Stick
Cookware Set, Metal
Cordials & Liqueurs
Corn & Tortilla Chips & Snacks
Costume jewelry
Cottage Cheese
Cotton Swabs
Cough Drops
Coughs
Cough Syrup
Countries Visited—Foreign Travel
Country Club Membership
Coupons, Cents-Off
Courses For Adult Education
Crackers
Cream, Lotion or Oil, Hand & Body
Cream, Shave
Cream Substitutes, Non-Dairy
Credit Cards
Crystal Ware
Cross Country Snow Skiing
Cubes, Bouillon, & Dry Soup Mix
Cups, Disposable
Curler Set, Hair, Electric
Curtains/Draperies
Decaffeinated Instant or Freeze-Dned Coffee
Deck. Cassette
Deck. Eight Track (Record & Play)
Dental Insurance
Dentures
Deodorants & Anti-Perspirants
Deodorizers, Room, & Air Freshener Sprays
Department Stores & Discount Stores
Depilatories
Desk Top Calculator
Dessert Pies, Cakes & Pastries, Frozen
Desserts, Flavored Gelatin
Dessert Wines, Port & Sherry
Detector. Smoke/Fire
Detergent, Dishwashing
Detergents & Soaps. Laundry
Dial Face Wnstwatch
Diamond Ring
Diapers
Diarrhea
Diesel Fuel & Gasoline
Diet Control
Diet or Low Calorie Carbonated Sort Dnnks
Digital Face Wnstwatch
Dining Room Furniture
Dinner Mixes. Complete PacKageci, & Dishes
Dinner Parties
Dinners. Frozen Complete (TV Dinners'
Dinnerware
Discount Stores & Deoartment Stores
Dishwasner ^tomatic
Dishwasher Detergent. Automatic
Dishwashing Liquid
Disposable Cups
Disposable Diapers
Disposable Lighters
Disposable Razors
Disposal, Garbage
Dog Biscuits or Treats
Dog Food
Dog Ownership
Domestic Beer, Light/Low Calorie
Domestic Beer, Regular
Domestic Travel
Domestic Wine
Door Opener, Garage
Doors, Storm, or Windows
Door-to-Door Sales
Douches & Suppositories, Feminine Hygiene
Dough Products, Refrigerated
Downhill Snow Skiing
Draft Beer
Dram Cleaners
Draperies/Curtains
Drawing, Painting, Sculpting
Dresses or Suits, Children's
Dresses, Women's
Dressing, Salad
Dress or Regular Shirt, Men's
Drill, Electric
Drink Mixers, Prepared, Without Liquor
Drinks, Breakfast, Powdered Fruit-Flavored
Drinks, Fruit, & Juices
Drinks, Mixed, Prepared With Liquor
Drinks, Soft
Drinks, Soft. Powdered
Drip Coffee Maker, Automatic
Drive-In & Fast Food Restaurants
Driver's License
Driving
Driving, Type of Vehicle Driven
Dry Cake Mixes
Dry Cat Food
Dry Dog Food
Dryer, Clothes
Dryer, Hair
Dry Mix Salad Dressing
Dry Soup Mix & "Bouillon Cubes
Dungarees or leans. Children's
E
Eczema
Education Courses for Adults
Eight Track Deck (Record & Play)
Electric & Battery Shaver
Electric Blankets
Electric Blender
Electric Chain Saw
Electric Circular Saw
Electric Clothes Dryer
Electnc Coffee Maker
Electric Drill
Electnc Food Processor
Electric Fry Pan
Electric Grill
Electnc Hair Curler Set
Electnc Hair Drver
Electnc Hair-Styling Como
Electnc Jig/Saore Saw
Electric luicer
123
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Electric Mixer
Electric Power Mower
Electric Range or Stove
Electric Refrigerator
Electric Sander
Electric or Battery Shaver
Electric Steam Cooker
Electric Toothbrush
Electric Trash Compacter
Electric Typewriter, Portable
Encyclopedia
Entrees & Casseroles (Frozen Main Courses)
Exterior House Paint & Stains
Eyeglasses
Eye Liner
Eye Shadow
Fabric Softeners
Face Powder
Facial Moisturizers & Cleansing Creams
Facial Tissues
Factory Loaded Ammunition
Family Restaurants & Steak Houses
Farm Ownership
Fast Food & Drive-In Restaurants
Feminine Hygiene Douches & Suppositories
Fertilizers
Fever
Fever Reducers. Children's, & Pain Relievers
Film
Film Processing
Rlter or Purifier, Water
Filters, Air
Filters, Oil
Fire/Smoke Detector
Fishing
Fishing Reel
Fishing Rod
Fixtures, Lighting
Fixtures, Plumbing, Bathroom
Flatware
Flavored Gelatin Desserts
Flavored Snack, Saltine & Graham Crackers
Flea & Tick Care Products For Dogs & Cats
Floor, Ceiling or Wall Insulation
Flooring, Sheet Vinyl
Floor Polish & Wax
Floor Tile
Florists
Flowers bv Wire
Flower & Vegetable Seeds
Fluorescent Lighting
Flying Private Plane
Foil. Aluminum
Folding Tent Camper. Towable
Food or Sandwich Bags, Plastic
Food Processor, Electric
Food Stores, Gourmet & Health
Foreign Travel
Formula. Liquid Baby
Foundation Makeup
Frankfurters & Wieners
Fraternal Oraer Membership
Freeze-Dned or Instant Corree
Freezer Home
Fresneners. Air & Room Deoaoniers
Fresheners. Sreatr
Fresh Fruits
Fresh Water Fishing
Fresh Water Fishing Reel
Fresh Water Fishing Rod
Frozen Complete Dinners (TV Dinners)
Frozen Dessert Pies, Cakes & Pastries
Frozen Mam Courses (Casseroles & Entrees)
Frozen Orange Juice
Frozen Pizzas
Frozen Potato Products
Frozen Vegetables
Frozen Yogurt
Fruit-Flavored Breakfast Drinks, Powdered
Fruit juices & Drinks
Fruits, Canned or Jarred
Fruits, Fresh
Fry Pan, Electric
Fun, Miniature & Snack Size Candy Bars &
Packages
Furnace
Furnishings, Household
Furniture
Furniture Polish
Games & Toys
Games, Video
Garage Door Opener, Automatic
Garbage Bags & Trash Can Liners, Plastic
Garbage Disposal
Gardening
Garden Tiller
Garden Tractor
Gas Cham Saw
Gas Clothes Dryer
Gas Grill
Gasoline & Diesel Fuel
Gasoline Additives
Gas Power Mower
Gas Range or Stove
Gelatin Desserts, Flavored
Gel or Cream, Shaving
Gems & Jewelry
Gifts by Wire
Gin
Girdle
Gloss, Lip & Lipstick
Gold/Gold Coins
Gold Jewelry
Golf
Golf Balls
Golf Clubs
Golf Courses
Golf Shoes
Gourmet Food Stores
Government, Local, Belong To
Grill, Electric
Grill, Gas
Grocery Shopping, Weekly Expenditure
Groin Irritation
Ground Coffee
Gum
Gun For Target Shooting
H
Hair Coloring Products
Hair Conditioners
Hair Curler Set. Electric
Hair Dryer
Hair Rinse, Creme
Hair Sprays
Hair-Styling Comb, Electric
Hair Tonic or Dressing
Ham, Canned
Hand Ball
Hand & Body Cream, Lotion or Oil
Hand-Held Hair Dryer, Electric
Hand-Held or Pocket Calculator, Electric
Hand Tool Outfit
Hard Cover Books
Hard Roll Candy
Hayfever
Headache Remedies & Pain Relievers
Headaches
Head Phones, Stereo
Health Club Membership
Health Food Stores
Health, Hospital or Medical Insurance
Heater/Stove, Wood Burning
Heater, Water
Heating, Solar
Heating Unit, Separate Room
Heat Pumps
Heavyweight Jacket
Hemorrhoids
Hiking or Backpacking
Hiking or Climbing Boots, Men's
Home Entertaining
Home Freezer
Home Improvements
Home, Mobile, Towable
Home, Motor, Bus-Type & Mini
Home Owners or Personal Property Insurance
Home, Vacation/Weekend
Horseback Riding
Hose or Stockings, Women's
Hospital Board Membership
Hospital, Medical or Health insurance
Hotels & Motels
Hot Lather Machine
Hot Tub Systems
Hot Water Heater
Household Cleaners
Household Furnishings
House Paint
Humidifier, Room, Portable
Hunting
Hunting Rifle
I
Ice Cream. Ice Milk & Sherbert
Ice Tea Mix, Instant
Ice Skating
illnesses
Imported Beer
Imported Dinner/Table Wines
Imorovements. Home
Inboard/Outboard Power Boat
In-Bowl Toilet Bowl Cleaners
Indigestion Aids i Lpset Stomach Remedies
Indigestion or Upset Stomach
Individual Retirement iIRA) or Keogh Plan
Inaoor Gardening i Plants
Indoor Lighting Fixtures
Inooor-Outdoor Caroeting
imlatabie Boat
124
-------
Insecticides
Instant Iced Tea Mix
Instant or Freeze-Dned Coffee
Instant Potatoes, Packaged
Instant Tea
Insulation for Ceiling, Floor or Wall
Insurance, Auto
Insurance, Dental
Insurance, Health, Hospital or Medical
Insurance, Home Owners or Personal Property
Insurance, Life
Insurance, Loss of Income
Insurance, Personal Liability
Insurance, Travel
Insurance, Vision Care
In-Tank Toilet Bowl Cleaners
Interior Wall Paint
Investment Property
Investments & Banking
Irish Whiskey
I
Jacket, Heavyweight
lacket, Lightweight
lacket, Sport
Jams & Jellies
Jarred or Canned Fruits
Jarred or Canned Vegetables
Jars, Canning & Lids
Jeans
Jellies & lams
Jewelry, Costume
Jewelry & Gems
Jewelry, Cold
Jig/Sabre Saw
Jogging or Running
Jogging or Running Shoes
Juice, Orange, Frozen
Juice, Orange, In Bottles, Cans or Cartons
Juicer, Electric
luices & Drinks, Fruit (Not Orange)
Juices, Tomato & Vegetable
Keogh Plan or Individual Retirement Plan (IRA)
Ketchup (Catsup)
Kitchen Cabinets
Kitchen Cleaners (Household Cleaners)
Kitchen Wrap. Plastic-Type
Knee High Hose
Lather Machine, Hot
Laundrv Detergents & Soaps
Laundrv Pre-Soaks & Pre-Cleaners
Laundrv Washloads
Lawn Mower
Lawn; Porch Furniture
Lawn Seed
Laxatives
Leasing. Car
Leather Shoes
Leisure Activities
Leisure/Casual Suit
Lenses. Contact
Liaoilitv Insurance Personai
Lias. Canning, i lars
Lire Insurance
Lighted Make-Up Mirror
Lighters, Disposable
Lighting Fixtures
Lighting, Fluorescent
Light/Low Calorie Domestic Beer
Lightweight Jacket, Men's
Lightweight Summer Suit
Liner, Eye
Liners. Trash Can, & Garbage Bags, Plastic
Lipstick & Lip Gloss
Liqueurs & Cordials
Liquid Baby Formula
Liquid Prepared Salad Dressing
Liquor, Malt
Living Room Furniture
Loan, Auto
Loan, Personal
Local Government, Belong To
Loss of Income Insurance
Lotion, After Shave & Cologne
Lotion & Oil. Baby
Lotion, Shave, Pre-Electric
Low Calorie or Diet Carbonated Soft Drinks
Lozenges, Throat, Medicated
Luggage or Baggage
M
Macaroni & Spaghetti Products, Canned
Mailgram
Mail Order
Main Courses, Frozen (Casseroles & Entrees)
Make-Up, Foundation
Make-Up Mirror, Lighted
Malt Liquor
Margarine
Mascara
Mattresses
Mayonnaise & Mayonnaise-Type Salad
Dressing
Medical, Hospital or Health Insurance
Medicated Skin Care Products
Medicated Throat Lozenges
Membership. Business Club
Membership, Church Board
Membership. Civic Club
Membership. Country Club
Membership, Fraternal Order
Membership, Health Club
Membership. Hospital Board
Membership, Religious Club
Membership, Regional Development
Committee
Membership, School or College Board
Membership, Union
Membersmp, Veterans Club
Menstrual or Period Pain
Metal Cookware Set
Microwave Oven
Mileage Driven in Last Year
Milk
Mineral & Spring Water, Bottled
Mimbikes or Mmicycies
Mirror. Make-Up. Lighted
Mixed Drinks Preoared With Liquor
Mixer Slectrc
Mixers Drink. Preoareo Witnout Liquor
Mixes. Cake. Dn.
Mixes, Dinner, Complete Packaged, & Dishes
Mixes, Iced Tea, Instant
Mixes, Prepared Cocktail
Mixes, Salad Dressing, Dry
Mixes. Soup, Dry, & Bouillon Cubes
Mobile Home, Towable
Moist Cat Food
Moist Dog Food
Moisturizers & Cleansing Creams & Lotions,
Facial
Money by Wire
Mopeds
Mortgage
Motels & Hotels
Motion Sickness
Motorcycles
Motorcycling
Motor Home, Bus-Type & Mini
Motor Oil
Motor Oil Additives
Motor, Outboard
Motorscooters
Mouthwash
Movie Cameras
Movie Projector
Movies, Attendance
Mower
Mufflers
Muscle Aches
Mustard
Mutual Funds
N
Nail Polish
Napkins & Pads, Sanitary
Nasal Sprays
Natural Cheese
Needlework
Nervous Tension
Non-Dairy Cream Substitutes
Non-Decaffeinated Instant or Freeze-Dned
Coffee
Notions & Sewing Materials
Nursers, Baby
Oil Additives (Motor Oil Additives)
Oil & Lotion. Baby
Oil, Bath, & Other Bath Additives
Oil Filters
Oil, Motor
Oil. Salad or Cooking
Opener, Garage Door, Automatic
Orange Juice. Frozen
Orange Juice in Bottles, Cans or Cartons
Organ
Outboard/Inboard Power Boat
Outboard Motor
Outdoor Gardening
Outdoor-Indoor Carpeting
Outdoor Lighting Fixtures
Outerwear, Children s
Oven Cleaners
Oven. Microwave & Convection
Oven. Self/Continuous Cleaning
Overcoat-Topcoat
Ownership or Cats
Ownership ot Dogs
125
-------
Packaged Dry Cat Food
Packaged Dry Dog Food
Packaged Instant Potatoes
Packaged Moist Cat Food
Packaged Moist Dog Food
Packaged Prepared Dishes & Dinner Mixes,
Complete
Paddle Ball
Pads, Scouring
Pain Relievers, Children's, & Fever Reducers
Pain Relievers & Headache Remedies
Pain Relieving Rubs & Liquids
Paint, Exterior House & Stains
Painting, Drawing, Sculpting
Paint, Interior Wall
Pancake & Table Syrup
Paneling, Wall
Pan, Fry, Electric
Pants Suit, Women's
Panty Hose
Paperback Books
Paper, Cigarette Rolling
Paper Cups, Disposable
Paper, Toilet
Paper Towels
Paper. Wall
Parties, Cocktail
Parties, Dinner
Parties, Other (Not Cocktail or Dinner)
Party/Pop/Sangria Wines
Passports
Pastries, Cakes & Pies, Frozen Dessert
Pasteurized Processed/American Cheese
Patterns, Sewing
Peanut Butter
Perfume & Cologne
Period or Menstrual Pain
Personal Liability Insurance
Personal Loan From Bank
Personal Loan From Finance Company
Personal Property or Home Owners Insurance
Pewter Flatware
Piano
Pick-Up Trucks
Pies, Cakes & Pastries, Frozen Dessert
Pillowcases
Pipe Tobacco
Pizzas, Frozen
Plants & Indoor Gardening
Plastic Garbage Bags & Trash Can Liners
Plastic Sandwich or Food Bags
Plastic-Type Kitchen Wrap
Platform Tennis
Player/Recorder, Video Cassette
Plumbing Fixtures, Bathroom
Pocket or Hand-Held Electronic Calculator
Poison Ivy, Oak or Sumac
Polish & Wax. Car
Polish & Wax. Floor
Polish, Furniture
Polish. Naii
Political Classification
Pool Swimming
Porcn/Lawn Furniture
Pork Sausages
Portable Circular Saw Electric
Portable Disnwasner Automatic
Portable ]ig/Saw, Electric
Portable Room Humidifier
Portable Typewriter, Electric
Port, Sherry & Dessert Wines
Potato Chips
Potatoes, Frozen
Potatoes, Packaged Instant
Powder, Baby
Powdered Fruit Flavored Breakfast Drinks
Powdered Soft Drinks
Powder, Face
Powder, Scouring
Power Boat
Power Boating
Power Mower
Power Yard Trimmer
Pre-Geaners & Pre-Soaks, Laundry
Preferred Stock
Pre-Moistened Cleansing Wipes for Babies
Pre-Soaks & Pre-Cleaners, Laundry
Prepared Cocktail Mixes Without Liquor
Prepared Dishes & Dinner Mixes, Complete
Packaged
Prepared Mixed Drinks With Liquor
Prepared Salad Dressing, Liquid
Pre-Recorded Cassette Tape
Pre-Recorded Tape Cartridges
Pre-Recorded Tape Reel
Pressure Cooker
Pretzels
Processor, Food, Electric
Projector, Movie
Projector, Slide
Property, Investment
Property, Retirement
Psoriasis
Psychographics
Public Activities
Pumps, Heat
Purchase of Liquor or Wine By Case
Purifier or Filter, Water
Quilts/Comforters
Racquet Ball
Racquet, Tennis
Radial/Arm Ssw, Stationary
Radio. CB. Base Unit
Radio, CB, Mobile Unit
Radio Sports, Frequency of Listening
Raincoat or All Weather Coat
Range or Stove
Razor Blades
Razors, Disposable
Ready Made Draperies/Curtains
Real Estate
Receiver/Tuner/Amplifier, Stereo
Recliner
Recorder/Plaver. Video Cassette
Records
Record & Tape Clubs
Records & Tapes: Types Bought
Rectal or Vaginal Itcning
Reel. Fishing
Reel, Taoe. Blank
Reei. Taoe. Pre-Recoraea
Reel-To-Reel^ Tape Player/Recorder
Refrigerator
Regional Development Committee
Regular Candy Bars & Packages
Regular Carbonated Soft Drinks
Regular Domestic Beer
Regular or Dress Shirt, Men's
Regular Tea
Religious Club Membership
Remedies, Allergy & Cold
Remedies, Asthma
Remedies, Athlete's Foot
Remedies, Children's
Remedies, Headache & Pain Relievers
Remedies, Indigestion & Upset Stomach
Removers, Spot
Rental, Car
Residential Ceiling Tile
Restaurants, Family, & Steak Houses
Restaurants, Fast Food & Drive-In
Retirement Property
Rheumatism or Arthritis
Rice
Riding, Horseback
Rifle For Hunting
Ring, Diamond
Rinse, Hair, Creme
Roll Candy, Hard
Roller Skating
Rolling Paper, Cigarette
Roofing
Room Air Conditioners, Separate
Room Deodorizers & Air Freshener Sprays
Room Heating Unit, Separate
Room Humidifier, Portable
Row boat
Rubs & Liquids, Pain Relieving
Rug Cleaners
Rugs
Rum
Run-Down, Tired Feeling
Running, Distance
Running or Jogging
Running or Jogging Shoes
Rustproof!ng (Cars)
Rye or Blended Whiskey
Sabre/Jig Saw
Safe Deposit Box
Sailing
Salad Dressing
Salad Oil or Cooking Oil
Salted Crackers & Flavored Snack Crackers
Salt Water Fishing
Salt Water Fishing Reel
Salt Water Fishing Rod
Sander, Electnc
Sandwich or Food Bags. Plastic
Sangria/Pop/Party Wines
Sanitary Napkins & Pads
Sauces. Bottled Barbecue & Seasoning
Sauce. Spagnetti
Sausages. Pork
Savings Account
Savings Certificates/Certificates ot Deposit
Saw Arm/Radial. Stationary
Saw. Chain
126
-------
Saw, Circular
Saw, Jig/Sabre
School or College Board Membership
Scotch Whisky
Scouring Pads
Scouring Powder
Sculpting, Painting, Drawing
Seasoning & Barbecue Sauces, Bottled
Second Mortgage
Securities
Seeds
Self-Concept
Separate Electric Clothes Dryer
Separate Gas Clothes Dryer
Separate Home Freezer
Separate Microwave Oven
Separate Room Air Conditioer
Separate Room Heating Unit
Sewing
Sewing Machine
Sewing Materials & Notions
Shampoo
Shampoo, Baby
Shave Lotion (After-Shave) & Cologne
Shave Lotion, Pre-Electnc
Shavers, Disposable
Shavers, Electric or Battery
Shaving
Shaving Cream or Gel
Sheets
Sheet Vinyl Flooring
Sherbet, Ice Cream & Ice Milk
Sherry, Port & Dessert Wines
Shirt/Blouse, Women's
Shirt, Regular or Dress, Men's
Shirt, Sport, Men's
Shock Absorbers
Shoes, Bowling
Shoes, Canvas
Shoes, Children's
Shoes, Golf
Shoes, Jogging or Running
Shoes, Leather
Shoes, Tennis
Shopping, Grocery, Weekly Expenditure
Shopping, Supermarket & Food
Shotgun For Hunting
Silver Flatware
Silver/Silver Coins
Sinus Congestion
Sinus Headache
Skating, Ice
Skating, Roller
Ski Boots
Ski Clothes
Skiing, Cross Country Snow
Skiing, Downhill Snow
Skiing, Water
Skin Care Products. Medicated
Skin Diving or Snorkelmg
Skirt
Skis, Snow
Skis. Water
SlacKs
Sleeplessness
Sleeowear Children s
Shoe Projector
Suo
Smoke/Fire Detector
Snack Crackers, Flavored & Salted Crackers
Snacks, Corn & Tortilla, & Chips
Sneakers
Snorkelmg or Skin Diving
Snow Blower
Snowmobile
Snow Skiing, Cross Country
Snow Skiing, Downhill
Snow Skis
Snuff
Soaps & Detergents for Fine Fabrics
Soaps & Detergents for Regular Laundry
Soap, Toilet
Socks
Sofa Bed
Soft Drinks, Carbonated
Soft Drinks, Powdered
Softeners, Fabric
Solar Heating
Sore Throats
Soup, Canned
Soup, Dry Mix, & Bouillon Cubes
Spaghetti & Macaroni Products, Canned
Spaghetti Sauce
Sparkling Wines, Champagne & Cold Duck
Spark Plugs
Speaker, Stereo
Specialty & Aperitif Wines
Sporting Goods
Sport Jacket (Suit Type)
Sports Events Attendance
Sport Shirt, Men's
Sports & Leisure
Sports, Radio Listening
Sports, TV Watching
Sport/Utility Vehicles
Spot Removers
Sprays, Air Fresheners & Room Deodorizers
Spray, Non-Stick Cooking
Spread Cheese
Spring & Mineral Water, Bottled
Squash
Stainless Steel Flatware
Stain & Paint, Exterior House
Stamp Collecting
Stationary Bench/Table Circular Saw
Stationary Jig/Sabre Saw
Stationary Radial/Arm Saw
Steak Houses & Family Restaurants
Steam Cooker, Electric
Stereo, Compact or Console
Stereo Head Phones
Stereo Receiver/Tuner/Amplifier (All In One)
Stereo Speaker
Sterling Silver Flatware
Stern Dnve Boat
Still Cameras
Stockings or Hose
Stocks
Stomach Remedies & Indigestion Aids
Stores, Convemance. & Supermarkets
Stores. Deoartment & Discount
Stores. Health Fooa
Storm Doors or Windows
Stove/Heater. Wood Burning
Stove or Range. Electric
Stove or Ranee. Gas
Sugar, Brown & Granulated White
Suit, Leisure or Casual
Suit, Lightweight or Summer
Suit, Pants, Women's
Suits or Dresses, Children's
Suit, Swimming
Suit, Warm-Up
Suit, Winter or All-Year
Suit, Women's
Sunglasses
Sunscreen & Suntan Products
Suppositories & Douches, Feminine Hygiene
Swabs, Cotton
Sweater
Swimming
Swimming Pool
Swim Suit
Syrup, Pancake & Table
Table/Bench Circular Saw, Stationary
Tampons
Tape Cartridges, Blank
Tape Cartridges, Pre-Recorded
Tape Cassette, Blank
Tape Cassette, Pre-Recorded
Tape Player/Recorder, Reel-To-Reel
Tape & Record Clubs
Tape Reel, Blank
Tape Reef, Pre-Recorded
Tapes & Records: Types Bought
Target Gun
Target Shooting
Tea, Canned
Tea, Instant
Tea Mix, Iced, Instant
Tea, Regular
Telegrams & Wires
Telephones
Television Sets
Tennis
Tennis Balls
Tennis Clothing
Tennis Courts
Tennis. Platform
Tennis Racquet
Tennis Shoes
Tension. Nervous
Tent Camper, Towable Folding
Tequila
Theme Parks
Throat Lozenges, Medicated
Tick & Flea Care Products for Dogs & Cats
Tile. Ceiling, Residential
Tile, Floor
Tiller, Garden
Tired, Run-Down Feeling
Tires. Car, Truck & Van
Tissues, Facial
Tobacco, Chewing
Tobacco. Pipe
Toilet Bowl Cleaners
Toilet Pacer
Toilet Soao
Tomato & Vegetable luices
Tonic. Hair, or Hair Dressing
Tool Outtit Hand
Tootnacne
127
-------
Toothbrush, Electric
Toothpaste
Topping, Whipped
Tortilla & Corn Chips & Snacks
Tour Package
Towable Folding Tent Camper
Towable Mobile Home
Towable Travel or Camp Trailer
Towels
Towels, Paper
Toys & Games
Tractor, Garden
Tractor-Type/Riding Lawn Mower
Trailer, Towable Travel or Camper
Transmission Services
Trash Can Liners & Garbage Bags, Plastic
Trash Compactor, Electric
Travel Agent
Travel, Domestic
Travelers Checks
Travel, Foreign
Travel Insurance
Travel or Camper Trailer, Towable
Travel, Weekly
Treasury Notes
Treats. Dog, or Biscuits
Trips, Camping
Trips, Domestic Travel
Trips. Foreign Travel
Truck Driving, Reasons For
Truck Mounted Camper
Trucks
Trust Agreement With Bank
T-Shirt, Women's
Tuna, Canned
Tuner/Amplifier/Receiver, Stereo
Tupperwear
Turntable
TV Dinners (Frozen Complete Dinners)
TV Sets
TV Special Programs, Frequency of Watching
TV Sports, Frequency of Watching
Typewriter, Electric Portable
Underwear, Children's
Union Membership
Upset Stomach or Indigestion
Upset Stomach Remedies & Indigestion Aids
Utility/Sport Vehicle
Vacation/Weekend Home
Vaginal or Rectal Itching
Vans
Vegetable & Flower Seeds
Vegetables, Canned or Jarred
Vegetables. Frozen (Excluding Potatoes)
Vegetable & Tomato luices
Vehicle, Camping
Vehicle. Soort/Utihtv
Vermouth
Veterans Club Membership
Video Cassette Recorder/Plave'
Video Game
Vmvl F'oonng. Sheet
Vision Care Insurance
Vitamins for Children
Vitamin Tablets, Capsules & Liquids
Vodka
Voting
W
Wall, Floor or Ceiling Insulation
Wall Paint, Interior
Wall Paneling
Wall Paper
Wall-To-Wall Carpeting or Room Sized Rugs
Warm-Up Suit
Washing Machine, Automatic
Washloads of Laundry
Water Filter or Purifier
Water Heater
Water, Mineral & Spring, Bottled
Water Skiing
Water Skis
Wax & Polish, Car
Wax & Polish, Floor
Weekend /Vacation Home
Weekly Expenditure on Groceries
Weekly Travel
Whipped Topping
Whiskey, Bourbon
Whiskey, Irish
Whiskey, Rye or Blended
Whiskey, Canadian
Whiskey, Scotch
Wieners & Frankfurters
Window Cleaners
Windows, Storm, or Door
Wmes, Aperitif & Specialty
Wines, Dessert, Port & Sherry
Wines, Domestic Dinner/Table
Wmes, Imported Dinner/Table
Wines. Pop/Party/Sangria
Wines, Sparkling, Champagne & Cold Duck
Wipes, Cleansing, Pre-Moistened, For Babies
Wires & Telegrams
Wood Burning Stove/Heater
Woodworking
Wrap, Kitchen, Plastic-Type
Wnstwatch, Digital Face
Wristwatch, Dial Face
Yard Trimmer
Yellow Pages
Yogurt
Yogurt, Frozen
Source: Reprinted from SMRB 1982,
128
-------
The Information provided for each product In each volume 1s divided
Into three sections: usage, types, and brands. In each section,
demographic Information on the buyer of the product 1s presented: age,
race, employment, education, place of residence (I.e., metropolitan
central dty, metropolitan suburban, and non-metropolitan), Income, and
household occupant characteristics. Usage of products by Individuals and
households 1s subdivided Into "heavy," "medium," or "light." Table 21
lists an example of a hypothetical product usage calculation as performed
by SMRB. The "heavy," "medium," and "light" designations are not
absolute. They are based on the relative frequency of use of each
product; the designations therefore vary from product to product. The
usage rates are defined by SMRB for each product, and a table such as
Table 21 1s generated for each SMRB product. This Information Is
particularly valuable for enumerating populations that may have high,
medium, or low exposure to chemical substances via the use of consumer
products when the same usage rates for product consumption are used to
predict exposure levels. Table 22 1s a sample table of SMRB usage data
for rug cleaners. SMRB also presents the same demographic data according
to product types (e.g., a rug cleaner may be marketed as a liquid, an
aerosol, or a powder). Table 23 1s a sample table of SMRB data for
different types of rug cleaners purchased by female homemakers. Finally,
SMRB also presents demographic data for specific name brands of
products. Table 24 1s a sample table of SMRB data for different name
brand rug cleaners purchased by female homemakers.
SMRB presents data according to the characteristics of the buyer
only. For example, for many consumer products the principal purchaser
(as determined by the SMRB national consumer panel) may be the "female
homemaker."* SMRB therefore only presents data for that product for the
female homemaker. Six population groups are assumed to represent
principal purchasers: adults, males, females, professional/managerial,
female homemakers, and mothers. Furthermore, SMRB only reports data for
populations 18 years of age and older. The Implications of these factors
cannot always be quantified.
Users of a product can be enumerated as the total number of users, or
they can be disaggregated by brand or type of product. Figure 20
Illustrates the SMRB presentation of data on usage of toothpaste by
females. The first number 1n Column A under "all users" Indicates that
75,174,000 females use toothpaste; this represents 92.7 percent of all
* The term "female homemaker" Is defined by SMRB as adult women who
assume responsibility for the maintenance of a household. The term
Includes working women and women living alone as well as 1n families, and
represents over 90 percent of adult women. It should be recognized that
products bought and used by female homemakers are often purchased and
used by males maintaining households. SMRB does not adjust for this
limitation; resultant population data may therefore be somewhat
underestimated.
129
-------
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130
-------
Table 22. Example of 1982 SMKB Data: Demographic
Variables for Usage of Rug Cleaners Purchased
by Female Homemakers
TOTt^ FEMALE HOMEMAKERS
It - !«
25 - 34
3b - 44
45 - 54
55 - C4
Ei OR OLDER
15 - 34
IE - 49
25 - 54
35 - 4S
50 OR OLDER
GRADUATED COLLEGE
ATTENDED COLLEGE
GRADUATED HIGH SCHOOL
DID NOT GRADUATE HIGH SCHOOL
EMPLOYED
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
PROFESSIONAL /MANAGER
CLERICAL /SALES
CRAFTSMEN 'FOREMEN
OTHER EMPLOYED
SINGLE
MARRIED
DIVORCE 0/SEPARATED/H1 DOMED
PARENT:
NHITE
BLACK
OTHER
NORTHEAST-CENSUS
NORTH CENTRAL
SOUTH
NEST
NDRTHEAST-MKTG
EAST CENTRAL
NEST CENTRAL
SOUTH
PACIFIC
COUNTY SIZE A
COUNT> sin e
COUNT* sm r
COUNTS SUE D
METRO CENTRAL CITY
METRO SUBURBAN
NON METRC
TOP 5 ADI 'S
TOP 10 ADI 'S
TOP 20 AD! 'S
HSHU INC S40.000 OR MORE
$30 000 OR MORE
S25 000 OR MORE
$20 000 - $24.999
$15 000 - SIS. 999
$10 000 - J14.999
UNDER $10 000
HOUSEHOLD OF 1 PERSON
2 PEOPLE
3 OR 4 PEOPLE
5 OR MORE PEOPLE
NO CHILE IN HSHLD
CH1LDIREN) UNDER 2 VRS
2 - 5 YEARS
6-11 YEARS
12 - I1 YEARS
RESIDENCE OMNED
VALUE $50 000 OR MORE
VALUE UNDER $50 000
TOTAL
U S
•000
77506
9335
18029
134T7
11E32
11283
13811
27364
46197
43078
18833
31310
9890
T223E
32853
22527
37446
29717
7729
40060
10614
14780
824
11229
8267
50768
18471
31500
67876
8235
1395
1E922
20200
26132
14252
17524
11814
1347S
22E75
11814
31229
23352
12137
10789
23359
34657
19491
17725
25079
35085
8818
18653
25911
9349
8862
13844
19541
11694
25454
ZB521
11637
43986
565 1
12521
15766
16144
55460
28563
268S7
A
•000
36879
37SO
8934
7073
5753
5E79
5689
12685
22535
21760
9850
14345
5021
5798
16-190
9571
18217
1414E
4071
18662
5355
6964
• 429
5468
3220
25994
7666
16214
32560
3573
• 746
7815
10219
12341
6505
7849
ES52
E542
10727
5210
14084
11373
6335
5087
9906
17101
9t72
7990
11418
16056
4450
9421
13098
4E43
4580
8572
7985
4657
11362
14790
6070
19806
270E
6469
8603
83EE
28352
14704
13648
ALL USERS
BCD
;. ACROSS
DONN X 1NDX
100 0
10.2
24 2
19.2
15.6
15 4
15 4
34 4
61 1
59 0
26 7
38 9
13 E
15 7
44 7
26 C
45 4
38 4
11 0
SO 6
14 5
18 9
1.2
14 8
8 7
70 5
20 8
44 0
88 3
9 7
2.0
21.2
27 7
33.5
17 6
21 3
17.8
17 7
29 1
14 1
31 2
30 8
17 2
13 t
26 9
46 4
26 8
21 7
31 0
43 5
12 1
25.5
35 5
12.6
12 4
17 8
21 7
12 6
30.8
40 1
16 5
53 7
7.3
17 5
23 3
22 7
76 9
39 9
37.0
47 6 100
40 2 84
49 6 104
52 7 111
49 104
50 106
41 87
46 97
48 103
50 106
52 3 110
45 8 96
50 8 107
4? 4 100
50 2 105
42 5 89
4f C 102
47 6 100
52 7 111
46 E 98
50 5 IDE
47 1 99
52 1 109
48 7 102
39 0 82
51.2 108
41.5 87
51 5 108
48 0 101
43 4 91
53.5 112
46. -2 97
50 E 106
47.2 99
45.6 96
44.8 94
55 5 117
48 5 102
46 9 99
44 1 93
45 1 95
4t 7 102
s: 2 no
47 1 99
42 4 89
49 3 104
50 E IDE
45 1 95
45 5 96
45 E 9E
50 5 106
50 5 106
50. S 10E
49 7 104
51 7 109
47 5 100
40.9 86
39 2 82
44. E 94
51.9 109
52.2 110
45 0 95
47 9 101
51 7 109
54 E 116
51 8 109
51 1 107
51 5 108
50 7 107
HEAVY USERS
A B C D
t ACROSS
'000 DONN •„ INDX
13063
1417
3293
2276
2222
1867
1988
4710
7966
7791
3266
509E
1451
1878
5E49
4084
E30E
5002
1304
E756
IEEE
2342
..1(6
1133
1171
8935
2956
5773
10982
1780
• •301
2960
3252
4897
1955
2928
2-331
18E2
4306
1635
5024
3958
2249
1832
3556
5690
3814
3040
4394
5947
1340
2733
4094
15S2
1543
2304
3561
1722
4102
4822
2418
6936
1022
2532
3074
3017
S424
4632
4792
100 0
10 8
25 2
17 4
17.0
14.3
15.2
36 1
61.0
59. E
24 9
39 0
11 1
14 4
43 2
31 3
46 3
38.3
10 0
51 7
12 8
17 9
1 3
16.3
9 0
68 4
22 6
44 2
84 1
13 6
2.3
22 7
24 9
37 5
15 0
22 4
17 8
14.3
33 0
12 5
38 5
30 3
r :
14 0
27 2
43 E
29 2
23 3
33 E
45.5
10 3
20 9
31 3
12 0
11.8
17.6
27.3
13 2
31 4
3E 9
18.5
53 1
7.8
19 4
23.5
23 1
72 1
35.5
36 7
IE. 9 100
15 2 90
18 3 108
17.0 101
19.1 113
16.5 98
14.4 85
17 2 102
17 2 102
18 1 107
17 3 103
16 3 97
14 7 87
15 3 91
17.2 102
18 1 108
16 8 100
16 8 100
16 9 100
16 9 100
15 7 93
15 8 94
20 1 120
19 0 113
14.2 84
17.6 104
16 0 95
IB 3 109
IE. 2 96
21.6 128
21 6 128
17 5 104
16 1 96
IS 7 111
13 7 81
1C 7 99
19,7 117
13 8 82
18 8 112
13 8 82
16 1 95
16 9 101
It. 5 110
17 0 101
16 2 90
16 4 97
19 6 11E
17 2 102
17 5 104
17 0 101
15 2 90
14.7 87
15 8 94
16 7 99
17 4 103
16 6 99
18.2 108
14.5 86
16 1 96
16.9 100
20 8 123
15.8 94
18 1 107
20 2 120
19.5 116
18 7 111
17 0 101
16 2 96
17.8 IDE
MEDIUM USERS
A 6 C D
S ACROSS
•000 DONN 2 INDX
10034
898
2362
1945
1492
1729
1608
3260
5972
5799
2712
4062
1209
1788
4617
2420
4818
3638
1180
521E
1448
1863
• •174
1333
947
8981
2106
4400
8830
1007
• •197
2196
3147
2904
1787
2084
2034
2056
2512
1349
3540
3014
1887
1593
2819
4174
3040
2110
2996
4114
1190
2614
3503
1340
1191
1822
2179
1302
2816
4378
1538
5306
723
1697
2451
2200
7775
3769
4006
100.0
8 9
23 5
19 4
14 9
17.2
16 0
32 5
59.5
57 8
27.0
40.5
12.0
17.8
4E 0
24 1
4E 0
3E 3
11 8
52 0
14 4
18 6
1.7
13 3
9 4
69 6
21 0
43 9
88 0
10 0
2.0
21.9
31 4
28 9
17.8
20 8
20 3
20 5
25.0
13.4
35.3
30 0
is e
15 9
28 1
41 E
30.3
21.0
29 S
41 0
11 9
26 1
34 9
13 4
11.9
18.2
21 7
13 0
28 1
43.6
15.3
52.9
7 2
IE S
24 4
21.9
77.5
37 6
39 9
12 9 100
9.6 74
13 1 101
14 5 112
12 8 99
15 3 118
11 6 90
11 9 92
12 9 100
13 5 104
14 4 111
13 0 100
12 2 94
14 6 113
14 1 109
10 7 83
12 9 39
12 2 95
15.3 118
13 0 101
13 6 105
12 6 97
21.1 163
11 9 92
11 5 88
13 8 106
11 4 88
14 0 108
13 0 100
12 2 94
14 1 109
13.0 100
15.6 120
11 1 86
12 5 97
11 9 92
17 2 133
15 3 118
11.0 85
114 88
11 3 88
12.9 100
16 5 120
14 8 114
12 1 93
12 0 93
15 E 120
11 S 92
11.9 92
11 7 91
13.5 104
14 0 108
13 5 104
14 3 111
13 4 104
13 2 102
11.2 86
10 9 85
11 1 85
15 4 119
13 2 102
12.1 93
12 8 99
13. E 105
15.5 120
13.6 105
14 0 108
13.2 102
14 9 115
LIGHT USERS
A B C D
X ACROSS
'000 DONN 5 INDX
13783
1435
3279
2853
2040
2084
2093
4714
8596
8171
3882
5187
2361
2131
6224
3067
7093
5507
1586
(690
2242
2760
• •89
2002
1101
10079
2603
6041
12748
78E
••249
2(60
3820
4540
27(4
2837
2188
2(24
3908
222E
S520
4401
2199
1(63
3529
723E
301S
2840
402 f
5996
1920
4074
5502
1742
1846
2447
2246
1(34
4445
5590
2114
75(4
9(1
2240
3079
3150
11154
(303
4851
100 0
10.4
23 8
20.7
14.8
15 1
15.5
34.2
(2 4
59.3
28.2
37.6
17 1
15 5
45.2
22 3
51 5
40.0
11 6
48.5
16.3
20.0
0.6
14 5
8 0
73.1
18.9
43.8
92.5
5.7
1.8
19.3
27.7
32.9
20 1
20.6
15.9
19.0
28 4
IE. 2
40.0
31.9
1E C
12 1
25 E
52.5
21 9
20.6
29 2
43.5
13 9
29 6
39 9
12.6
13.4
17.8
IB. 3
11.9
32.2
40 6
15.3
54.9
7.0
16.3
23.3
22.9
SO. 9
45 7
35.2
17 8 100
15 4 86
18.2 102
21.3 120
17 5 99
18.5 104
15 2 85
17.2 97
18.6 105
19 0 107
20.6 116
IE 6 93
23.9 134
17 4 9E
18.9 107
13.6 77
16 9 107
18 5 104
20.5 115
16 7 94
21 1 119
18 7 105
1C 8 61
17 8 100
13.3 75
19 9 112
14 1 79
19.2 lOt
18.8 106
9.5 54
17 8 100
15 7 88
18.9 106
17 4 98
19.4 109
16.2 91
18.5 104
19.5 109
17 1 96
18 8 106
17 7 99
It 8 106
IE 1 102
15 4 87
15 1 85
20.9 117
15.5 87
16.0 90
IE 1 90
17 1 96
21 8 122
21 8 123
21.2 119
18 E 105
20 8 117
17 7 99
11.5 (5
13 7 77
17.5 98
19.6 110
18 2 102
17.2 97
17.0 96
17.9 101
19.5 110
19 5 110
20.1 113
22 1 124
18 0 101
Source: SMRB 1982.
131
-------
Table 23. Example of 1982 SMRB Data: Demographic
Variables for Types of Rug Cleaners Purchased
by Female Homemakers
LIQUID
TOTAL A E C D
US '. ACROSS
'000 '000 CONN S 1NDX
AEROSOL
(BCD
•. ACROSS
'000 DONN •- 1NDK
PONDER'GRANULES
A B C 0
X ACROSS
'000 DONK J INOX
A B C D
'. ACROSS
'000 DONN -. INOt
TOTAL FEMALE HOMEMAKERS
IB - 24
25 - 34
35 - 44
45 - 54
55 - 64
65 OR OLDER
1B - 34
18 - 49
25 - 54
35 - 43
50 OR OLDER
GRADUATED COLLEGE
ATTENDED COLLEGE
GRADUATED HIGH SCHOOL
DID NOT GRADUATE HIGH SCHOOL
EMPLOYED
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
PROFESSIONAL 'MANAGER
CLERICAL/SALES
CRAFTSMEN'FOREMEN
OTHER EMPLOYED
SINGLE
MARRIED
DIVORCED/SEPARATED/NIDOMED
PARENTS
HHITE
BLACK
OTHER
NORTHEAST-CENSUS
NORTH CENTRAL
SOUTH
NEST
NORTHEAST-HKTG
EAST CENTRAL
NEST CENTRAL
SOUTH
PACIFIC
COUNTY SIZE A
COUNTY SIZE B
COUNTY SIZE C
COUNTY S!Zf D
METRO CENTRAL CITY
METRO SUBURBAN
NOM f-tm
TOP 5 ADI 'S
TOP 10 ADI'S
TOP 20 ADI'S
HSHLD INC $40 000 OR MORE
$30 000 OR MORE
$25 000 OR MORE
$20 000 - S24 999
115.000 - $19 999
$10 000 - $14 999
UNDER $10.000
HOUSEHOLD OF 1 PERSON
2 PEOPLE
3 OR 4 PEOPLE
5 OR MORE PEOPLE
NO CHILD IN HSHLD
CHILDIREN1 UNDER 2 YRS
2 - 5 YEARS
6 - 11 YEARS
12 - 17 YEARS
RESIDENCE ONNED
VALUE $50 000 OR MORE
VALUE UNDER $50.000
77506 1893S 100 0 24 4 100 13862 100 0 17 9 100 6044 100 0 78 100
9335
18029
13417
11632
M283
13811
27364
16197
43078
18833
31310
9890
12236
32853
22527
37446
2S717
7729
40060
10614
14780
824
112J9
8267
50768
18471
31500
67876
8235
1395
16922
20200
26132
14252
17524
11814
13479
22875
11814
31229
23352
1?13T
ID'89
233S9
34657
19491
17725
25079
35085
8818
1BES3
25911
9349
8862
13844
19541
11894
25454
28521
11637
43986
5651
12521
15766
16144
S5460
28563
26897
1706
4515
4241
2903
2903
2673
6221
11914
11658
SS94
7025
2535
2955
8311
5139
9264
7254
2010
9676
2665
3542
••222
2836
1370
13940
3629
9208
16S84
1890
••465
4035
5505
6098
3302
3718
3853
3326
5486
2557
6495
5970
3645
2830
4717
872C
S496
3820
5347
7556
2487
5129
6963
2357
2571
3115
3933
1856
5550
8036
3497
9224
1421
3542
5149
4940
15154
7777
7378
9 0
23 8
22 4
15.3
15 3
14 1
32 8
62 9
61 6
30 1
37 1
13 4
15 6
43 9
27 1
48 9
38 3
10 6
51 1
14 1
18 7
1 2
15 0
7.2
73 6
19 2
48.6
87 6
10 0
2 5
21 3
29 1
32.2
17 4
19 6
20 3
17 6
29 0
13. S
34 3
31 5
19 :
14 9
24 9
46 1
29 0
20 2
2£ 2
39 9
13 1
27 1
36 8
12 4
13 6
16 4
20 8
9 8
29 3
42 4
18 5
48 7
7 5
18 7
27 2
26 1
80 0
41 1
39 0
18 3
25 0
31 6
25 0
25 7
1!i 4
22 7
35 B
27 1
30 2
22 4
35 6
24 2
25 3
22 8
24 7
24 4
26 0
24 2
25 1
24 0
26 9
25 3
16 6
27 5
19 6
29 2
.24 4
23 0
33 3
33 8
27.3
23.3
23 2
21 2
32 6
24 7
24 0
21 6
2C 8
K 6
30 0
26 2
20 2
25 2
2£ 2
21 6
21 3
21 5
28 2
37 5
26 9
25.3
29 0
22.5
20 1
15 6
21 e
28 2
30 1
21.0
25.1
28 3
32 7
30 6
27 3
27 2
27 t
75
102
129
102
105
79
93
106
111
124
92
105
99
104
93
101
100
106
99
103
98
110
103
66
112
80
130
100
94
136
98
112
95
95
87
133
101
98
89
85
105
123
107
83
103
115
88
87
88
115
113
110
103
119
92
82
64
19
115
123
86
103
116
134
125
112
111
112
1746
3855
2351
2231
213E
1543
5601
9058
8437
3458
4803
2008
2719
6521
2613
7069
5431
1638
6792
3169
3903
••125
1872
1504
9881
2477
5946
13547
1128
••186
3054
3744
4337
2727
3129
2259
2410
3731
2333
5905
4283
2065
1609
4027
6531
3313
3327
4854
B725
1849
3747
5491
1964
1563
2542
2302
1566
439}
5878
2026
7685
1153
2634
3155
3542
10322
5721
4602
12 t
27 8
17 0
16 1
15 4
11 1
40 4
65 3
60 9
24 9
34 6
14 5
19 6
4' 0
IS 9
51 0
35 2
11 8
49 0
15.6
20 9
C 9
13 5
10 8
71 3
17 9
42 9
90 5
8 1
1 3
22 0
37 0
31 3
19 7
22 6
16.3
17 4
26 9
16 8
42 6
30.9
K S
11 6
29 1
47 0
23 9
23 3
35 0
48 5
13 3
37 0
39 6
14 3
It 3
18.3
16 6
11.3
31 7
42 4
14 6
55 4
8.3
19 0
22 8
18 3
74 5
41 3
33.2
18 7
21 4
17 5
IS 2
18 9
11 2
20 5
19 6
19 6
16 i
15 3
20 3
22 2
19 t
11 6
It 9
IE 3
21 2
17 0
20 4
19 6
15 2
16 7
ie 2
19 5
13 4
U 9
18 5
13 7
13 3
18 0
18 5
16 6
19 1
17 9
19 1
17 9
16 3
19 7
18 9
18 3
17 0
14 9
17 2
18 8
17 C
18 2
19 4
19 2
21 0
20 1
21.2
21 0
17.6
18 4
11 8
13.2
17.3
20.6
17 4
17.5
20 4
21 0
20 0
15 7
18 6
20 0
17.1
105
120
98
107
106
62
114
110
110
103
86
114
124
111
65
IOC
102
118
95
114
110
85
93
102
109
75
106
103
77
75
101
104
93
107
100
107
100
91
110
106
103
95
83
96
105
95
102
108
107
117
112
118
117
99
103
66
74
96
115
97
98
114
118
112
88
104
112
96
813
1442
976
842
888
1083
2255
3598
3260
1343
2446
772
911
3718
1642
3178
2346
832
2866
707
1119
• •45
1306
657
3927
1460
2427
5106
713
"225
11(4
1481
2465
935
1276
923
963
2138
746
2398
1322
893
832
1916
2610
1519
1316
1829
2717
• 470
1232
1869
685
790
1023
1677
958
1862
2331
893
3448
• 3t7
S90
1193
1412
4313
2066
2248
13 E
23 9
16 1
13 9
14 7
17.9
37 3
59 5
53.9
22.2
40 5
12 8
15 1
45 0
37 2
52. C
36 8
13 8
47 4
11 7
18 5
0 7
31 E
10 9
65.0
34 2
40 2
84 5
11 8 '
3 7
19 3
24.5
40.8
15 5
21 1
15 3
15.9
35 4
12.3
39.7
31.8
14. t
13.8
31 7
43 3
25 1
21 8
30.3
45.0
7 8
20 4
30 9
11.3
13 1
16.9
37 7
15 9
30.8
38. i
14.8
57.0
6 1
14 7
19.7
23 4
71 4
34 2
37.3
8 7 112
8 0 103
7 3 93
7 2 93
7 9 101
7 8 101
8 2 106
7 8 100
7 6 97
7 1 91
7 8 100
7.8 100
7 4 95
8 3 106
7 3 93
8.5 10S
7 9 101
10 8 138
7 3 92
6 7 85
7 6 97
5 5 70
11 6 146
7 9 10J
7 7 99
7 9 101
7 ' St
7 5 96
8 7 111
16 1 307
6 9 88
7 3 94
9 4 121
6 6 84
7.3 93
7.8 100
7 1 92
9.3 120
6.3 81
7 7 98
8.2 106
7 4 94
7 7 99
8.2 105
7.5 97
7 8 100
7.4 95
7 3 94
7 7 99
5.3 68
6 6 85
7.2 92
7 3 94
8.9 114
7.4 95
8 6 110
8 1 103
7.3 94
8.2 105
7.7 it
7.8 101
6.5 83
7.1 91
7.6 97
8 7 112
7.8 100
7.2 93
8 4 107
Source: SMRB 1982.
132
-------
Table 24. Example of 1982 SMKB Data: Demographic
Variables for Brands of Rug Cleaners Purchased
by Female Homemakers
TOTAL FEMALE HOMEMAKERS
18 - 24
25 - 34
35 - 44
45 - 54
55 - E4
65 OR OLDER
It - 34
18 - 49
25 - 54
35 - 49
50 OR OLDER
GRADUATED COLLEGE
ATTENDED COLLEGE
GRADUATED HIGH SCHOOL
DID NOT GRADUATE HIGH SCHOOL
EMPLOYED
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
PROFESSIONAL /MANAGER
CLERICAL 'SALES
CRAFTSMEN 'FOREMEN
OTHER EMPLOYED
SINGLE
MARRIED
DIVORCED/SEPARATED/NIDOHED
PARENTS
HHITE
BLACK
OTHER
NORTHEAST-CENSUS
NORTH CENTRAL
SOUTH
NEST
NORTHEAST -MKTG
EAST CENTRAL
NEST CENTRAL
SOUTH
PACIFIC
COUNTY SIZE A
COUNTY SIZE B
COUNTY SIZE C
COUNTY SIZE (
METRO CENTRAL CITY
METRO SUBURBAN
NON METRC
TOP 5 ADI'S
TOP 10 ADI'S
TOP 20 ADI'S
HSHLO INC S40.000 OR MORE
J30.000 OR MORE
J25.000 OR MORE
$20.000 - S24.999
SIS OOO - S19.999
$10 000 - $14,999
UNDER $10.0OO
HOUSEHOLD OF 1 PERSON
J PEOPLE
3 OR 4 PEOPLE
5 OR MORE PEOPLE
NO CHILD IN HSHLD
CH1LD(REN> UNDER 2 VRS
2 - 5 YEARS
6-11 YEARS
12 - 17 YEARS
RESIDENCE OHNEO
VALUE $50.000 OR MORE
VALUE UNDER ISO. 000
TOTAL
U S.
'000
77506
9335
18029
13417
11632
11283
13811
273(4
4S197
4307 S
18833
31310
9890
12236
32B53
22527
37446
29717
7729
40060
10(14
14710
824
11229
82(7
50768
18471
31500
(7876
8235
1395
1(922
20200
2(132
14252
17524
11814
13479
22B75
11814
31229
23352
12137
10789
23359
34657
19491
17725
2S079
35085
8818
18653
2S911
9349
88(2
13844
19541
11894
25454
28521
11(37
439S6
56S1
12521
15766
16144
55460
285(3
2(897
BLUE LUSTRE
A B C D
I ACROSS
'000 OOHN I 1NOX
7924 100.0
799
1(38
1(22
13(3
1347
1155
2436
4823
4(23
2387
3101
910
1207
3(14
2194
3998
3073
924
3926
973
1(10
••201
1213
(30
5549
1745
3519
7125
(77
••122
13(4
2656
2853
1051
1252
2054
1390
2569
• (59
2168
2593
1(14
1548
1800
32(9
2855
1017
1700
2(21
960
2110
2746
8(8
1124
1330
1855
9(0
2231
3411
1322
4153
•519
1108
19(5
2230
(568
2893
3(75
10 1
20 7
20 5
17.2
17.0
14. (
30.7
(0.9
St. 3
30 1
39.1
11.5
15.2
45. (
27.7
50.5
38.8
11 7
49 S
12 3
20 3
2 S
15 3
8 0
70 0
22 0
44 4
89.9
8 5
1.5
17.2
33.5
36 0
13.3
15.8
25.9
17.5
32.4
8.3
27 4
32 7
20 4
19 5
22 7
41 3
3E.O
12.8
21.5
33 1
12 1
26 (
34 7
11.0
14 2
1C 8
23 4
12 1
28.2
43.0
K.7
52 4
C.5
14 0
24 8
28 1
82.9
36 5
46 4
10 2 100
e.( 84
9 1 89
12 1 118
11 7 115
11 9 117
8.4 82
8 9 87
10 4 102
10 7 105
12 7 124
9.9 97
9.2 90
9.9 96
It 0 108
9.7 95
10 7 104
10 3 101
12 0 117
9 8 96
9.2 90
10.9 107
24 4 239
10 t 106
7.6 75
10.9 107
9.4 92
11 2 109
10 5 103
8.2 80
87 ((
t 1 79
13 1 129
10 9 107
7 t 72
7 1 70
17 4 170
10.3 101
11.2 110
b 6 55
6 9 (E
11 1 109
13 3 130
14 3 140
7 7 76
9 4 92
14 6 143
5.7 56
6 8 66
7 5 73
10 9 106
11.3 111
10 ( 104
9 3 91
12 7 124
9.6 94
9 5 93
8.1 79
e.8 >6
12.0 117
11.4 111
9 4 92
9.2 90
8.8 87
12 5 122
13 8 135
11 8 116
10 1 99
13 7 134
GLAMORENE
SPRAY 'N VAC
A B C D
X ACROSS
•000 DOWN X INDX
3872 100.0
• •301
890
(30
(74
70S
(72
1190
2155
2194
9(5
171(
(31
594
1728
920
1913
1523
• 389
1959
• (04
743
• •53
•512
•392
2(23
857
1323
3S27
•331
• •14
945
1038
1256
• (33
985
551
(23
1156
• 557
1(37
11(1
•(29
445
995
1890
987
1118
1472
1942
•4EO
1086
1(49
• 418
•354
(61
791
532
1300
1402
•(38
2386
••2(0
•(27
839
(46
3000
1544
1457
7.8
23 0
If. 3
17 4
18 2
17 4
30.7
55 7
56.7
24 9
44.3
16.3
15.3
44. (
23.8
49 4
39.3
10 0
SO (
15 (
19.2
1.4
13.2
10 1
(7.7
22 1
34 2
91.1
8.5
0 4
24 4
2( 8
32 4
16.3
25 4
14.2
IE 1
29.9
14 4
42.3
30 0
16.2
11.5
25 7
48.8
25 5
28 9
38 0
50.2
11 9
28 0
42 (
10 8
9 1
17 1
20.4
13 7
33. f
36.2
16.5
(1 (
(.7
1C. 2
21 7
1C 7
77 5
39 9
37 C
5.0 100
.2 (5
9 89
7 94
.8 IK
.3 125
.9 97
.3 87
4.7 93
S.I 102
S.I 103
S S 110
( 4 128
4.9 97
S 3 105
4 1 82
S 1 102
5.1 103
S 0 101
4.9 98
S 7 114
S 0 101
(.4 129
4.6 91
4 7 95
S.2 103
4 ( 93
4.2 84
5.2 104
4.0 80
1.0 20
56 112
S 1 103
4.8 96
4 4 89
5.6 113
4 7 93
4 C 93
5 1 101
4.7 94
5.2 105
S.O 100
5.2 104
4 1 83
4 3 85
5.S 109
5 1 101
6 3 126
5.9 117
5.5 111
5.2 104
5 8 117
(.4 127
4.S 89
4 0 80
4.8 9E
4.0 81
4.5 90
5 1 102
4 9 98
5 S 110
5.4 109
4 ( 92
5 0 100
5 3 107
4 0 80
S 4 108
5 4 108
5.4 lOt
JOHNSON'S GLORY
A B C C
t ACROSS
'000 DONN 1 INDX
4766 100.0
802
1303
(19
(02
590
fSO
2105
3268
2724
11(3
149S
Sfl
636
2148
1419
2(40
2014
•626
2126
S(5
1373
• •16
(87
744
3190
833
2137
3932
784
••SO
841
13(5
2004
556
814
928
795
1831
•398
1534
17(3
• (17
855
1527
1929
1310
(27
not
18(7
•440
1071
1S29
(74
• 438
827
1299
(74
14(4
1932
(97
2503
• 376
923
1252
9(1
3189
1396
1793
1C. 8
27.3
17.2
12 C
12 4
13. (
44.2
(86
57.2
24 4
31 4
11.8
13 4
45 1
29 8
55 4
42.3
13 1
44. C
11 9
28 8
0 3
14 4
15 6
((.9
17.5
44.8
82 5
16 4
1 0
17 6
28 6
42.0
11 7
17 1
19 5
1C 7
38 4
t 4
32 2
37 0
12 S
17.9
32 0
40 5
2" S
13 2
23.2
39 2
9 2
22 5
32 1
14 1
9.2
17 4
27 3
14 1
30 7
40 5
14. C
52. S
7.9
19 4
26 3
20.2
(6 9
29 3
37. B
6 1 100
t E 140
7 2 111
6 1 99
5 2 84
5.2 85
4 7 77
7 7 125
7 1 115
(.3 103
( 2 100
4 8 78
5 7 92
5.2 85
(.5 106
( 3 102
7 1 115
6 8 110
B 1 132
5.3 86
5 3 87
9 3 151
1 9 32
E 1 99
9 0 146
6.3 102
4 5 73
6 8 110
5 8 94
9 5 155
3.6 58
5 0 81
(.t 110
7,7 125
3 9 63
4 E 76
7 9 128
5 9 96
t.O 130
3 4 55
4.9 tO
7.5 123
5 1 83
7.9 12t
8 5 106
5 6 91
6 7 109
3 5 51
4 4 72
5 3 87
5 0 81
5.7 93
5 9 96
7 2 117
4 9 80
6 0 97
C 6 108
5 7 92
S t 94
6.8 110
E 0 97
5 7 93
C.C lOt
7 4 120
7 9 129
C 0 97
5 t 94
4 9 79
( 7 lOt
A
•ooo
MOOL1TE
BCD
•„ ACROSS
DONN • INDX
9154 100 0
10E1
?313
1116
144t
1520
1E95
3374
5191
4877
1817
39E3
12t7
1715
3861
2290
4085
3124
961
50(8
1280
1E16
• •Cl
1126
933
6171
2049
3415
8404
(34
• •11C
1768
2160
3349
1876
1707
1326
1427
3034
1(60
3682
2991
147S
1104
2933
4101
2119
1t71
2706
3995
1208
2099
2903
1242
1042
1818
2149
1CE8
3221
2999
12(7
5(50
(92
1409
1686
1545
6973
3766
3207
11 (
25 3
12 2
15 t
16. C
18 5
36 9
56 7
53 3
19 8
43 3
14 1
18 7
42 2
25 0
44 (
34 1
10. s
55 4
14 0
17 7
0 7
ii 3
10 2
E7 4
22 4
37 3
91.8
C.9
1.3
19 3
23 6
36. E
20.5
18.6
14,6
15 C
33 1
18 1
39 1
32 7
16 1
1! 1
32.0
44 t
23 1
20 4
29. e
43 (
13 2
22 9
31 7
13. (
11.4
19 9
23.5
16 2
35 2
32 t
13 8
(1.7
7 (
15 4
1t 4
16 9
76.2
41 1
35 0
11 B 100
11 4 96
12 t 109
t 3 70
12 4 105
13.5 114
12.3 104
12.3 104
11.2 95
11.3 9E
9 ( 82
12 7 107
13 0 110
14 0 119
11.8 100
10 2 86
10 9 92
10 5 89
12 4 105
12 7 107
12 1 102
10 9 93
7.8 E6
10 0 85
11 3 9E
12.2 103
11 1 94
10 8 92
12 4 105
7 7 65
8.3 70
10 4 88
10 7 91
12 8 109
13 2 111
9.7 82
11.2 95
10. E 90
13 3 112
14 1 119
11.5 97
12 t 101
12.2 103
10.2 87
12 6 106
11.8 100
10 9 92
10 6 (9
10 8 91
11.4 96
13 7 116
11 3 95
11.2 95
13.3 112
11.8 100
13 1 111
11 0 93
14.0 119
12 7 107
10 5 89
10.9 92
12.8 109
12.2 104
11.3 95
10 7 91
9 ( 81
12 6 106
13 2 112
11 9 101
Source: SMRB 1982.
-------
TOOTHPASTE: USAGE
(FEMALES)
TOTAL FEMALES
FEMALE HOMEMAKERS
EMPLOYED MOTHERS
18 - 24
25-34
35-44
46-54
55-64
65 OR OLDER
18-34
18 - 49
35 - 49
GRADUATED
ATTEM3ED COLLEGE
GRADUATED HIGH SCHOOL
DID NOT GRADUATE HIGH SCHOOL
EMPLOYED
EMPLOYED FULL-TIME
EMPLOYED PART-TIME
NOT EMPLOYED
PROFESSIONALAMNAGER
CLERICAL/SALES
CRAFTSMEN/FOREMEN
OTHER EMPLOYED
SINGLE
MARRIED
DIVORCED/SEPARATED/WIDOMED
PARENTS
WHITE
BLACK
OTHER
NORTHEAST-CENSUS
NORTH CENTRAL
SOUTH
WEST
NORTHEAST-+KTG.
EAST CENTRAL
WEST CENTRAL
SOUTH
PACIFIC
COUNTY SIZE A
COUNTY SIZE B
COUNTY SIZE C
COUNTY SIZE D
METRO CENTRAL CITY
METRO SUBURBAN
NON METRO
HSHLD INC $36,000 OR 'MORE
$25.000 OR MORE
$20.000 - $24.999
$15.000 - $19,999
$10,000 - $14,999
$ 5,000 - $ 9,999
UNDER $5.000
HSHLD OF 1 OR 2 PEOPLE
3 OR 4 PEOPLE
5 OR MORE PEOPLE
NO CHILD IN HSHLD
CHILD(REN) UNDER 2 YRS
2-5 YEARS
6-11 YEARS
12 - 17 YEARS
RESIDENCE OWNED
VALUE: $40.000 OR MORE
VALUE: UNDER $40.000
ALL USERS
A B C D
X ACROSS
'000 DOWN % INDX
HEAVY USERS
A B C D
X ACROSS
'000 DONN X INK
MEDIUM USERS
A B C D
X ACROSS
'000 DOWN X INDX
38575 rtOO.O
35798
751741100,0
687551 St.S
164581 21.3
21663 ItOO.O
18966 I 87.6
3791 I 17.5
81073
74434
16753
26.7 100
25,5 95
22.6 85
14334
17619
12488
11996
10991
13745
140841 18.7
172081 22.9
121021 16.1
111671
9679)
10935!
4814 I 22.2
4994 123.1
7007
9125
6696
5877
4881
4989
.1 25
2.2 24.0 90
.0 22.\ 83
98.2 106/1
97.5 1
96.2 1
31853
50029
18176
31292| 41.6
487791 64.9
17487| 23.3
145.3 30.81115
66.5 28.8\108
21.2 25.3 \95 j
9131
12426
33454
26062
12.1 28.7
17.0 29.6
41.0 26.5
30.0 24.9
38362
29473
8888
42711
10136
7551
2564
11527
9410
15875
720
12358
9135
15383
685,
117S71
129111
46601
15662
3137W 41.7
13227
49579
18266
31932
LIGHT USERS
A B C D
% ACROSS
'000 DOWN X INDX
47.6 100
92.8 48.1 101
25.3 58.2 122
48.9 103
52.1 109
53.6 113
49.0 103
44.4
36.3
93
76
50.6 106
51.3 108
52.4 110
53.3 112
14936t100.0
139911 93.7
29211 19.6
I
22621 15.1
30891 20.7
22901 15.3
22311
21581
18.4 100
16.8 102
17.4 95
86
96
14.9
14.4
19.5
29061
5352| 35.*
8709| f
3358 <
15.8
17.6
18.3 100
18.6 101
19.6 107
21.1 115
The percent of all heavy users who are age
35.44. Percents in this column add to 100%
vertically.
This is an index based on the percent in
column C. The 25.0% of women age 35-44
who are heavy users is 7% lower than the
26.7% of total women who are heavy users.
This yields an index of 93 (25.0%- 26.7%).
The percent of all women age 35-44 who are
heavy users of toothpaste. These percents
project to each individual demographic
break.
The pro]ected number of people in
thousands. This reflects 3,117,000 women
age 35-44 who are heavy users of
toothpaste.
These illustrative data were taken from
1982 SMRB Marketing Report. The headings
reflect adult female users of toothpaste
grouped by total, heavy, medium and light
users.
Users of individual brands are reported
the same manner as heavy, medium and light
users of the product category.
Figure 20. A Page From a Typical 1982 SMRB Marketing Report
Source: SMRB 1982.
134
-------
females over 18 (Column C). To enumerate all users of toothpaste, one
would consult the corresponding table for adults. That total would
indicate the number of persons over 18 using toothpaste. The
Investigator must use judgment on a case-by-case basis to decide whether
"adults" accurately represent the user population. In the case of
toothpaste and similar hygiene products, census totals for persons
between the ages of 1 and 17 should be added to the adult total derived
from SMRB.
Examination of Tables 23 and 24 Indicates the ease by which users of
different brands or types of products can be enumerated. In most cases,
the totals under Column A or the percentages 1n Column C are directly
applicable to enumeration. Distinctions among adult users of different
ages are easily made, if such distinction 1s required. Subsection 5.4.1
further discusses age and sex characterization of consumers using these
data.
The SMRB data are clearly Intended to describe the market variability
of existing products. Consequently, the data are generally more
applicable to existing chemicals and product formulations currently on
the market than to new chemical substances. The SMRB data may, however,
prove useful to assessments of PMN substances when the new chemical Is
Intended for use as a substitute for an existing chemical. If use
Information Included 1n a PMN submlttal 1s sufficiently detailed, the
SMRB data can be used to predict the number of exposed consumers.
Method 5-2 summarizes the use of SMRB data for any chemical or product.
Examples of the use of SMRB data are presented 1n Appendix A-4. That
discussion provides clear methods for estimating the number of product
users or the actively exposed population. Those who may be exposed to
chemical residuals by their proximity to consumer products are passively
exposed and are more difficult to enumerate accurately. Simmons'
demographic data for households can be used toward this end, as
Illustrated In Method 5-2 and Appendix A-4.
The data set used to enumerate a product's users (by usage, type, or
brand) also presents the frequency distribution of household size. For
example, Table 22 indicates that 36,879,000 women use rug cleaners
(Column A, all users, total female homemakers). Near the bottom of the
page, still under Column A, are the numbers of households having 1, 2, 3
or 4, or 5 or more persons; these households also total approximately
36,879,000. To approximate the number of persons living in the
36,879,000 households, apply the frequency distribution and household
size. Ranges can be used to accurately estimate the exposed population;
use of the high end of the ranges generates a conservative estimate of
exposed persons.
135
-------
Method 5-2. Enumeration of Exposed Consumer Populations via
the Use of Simmons Market Research Bureau Reports
Step 1 From the list of consumer products known to or thought to
contain a chemical substance under investigation, identify those
for which SMRB collects use data (Table 20). If SMRB does
collect data, identify the appropriate product category
volume(s) from Table 19.
Step 2 Identify applicable tables for enumeration as follows;
• If chemical substance is found in all types of products and
brand names, the usage tables should be used.
• If chemical substance is found in only certain product types
(e.g., aerosols versus liquids), the type tables should be
used.
• If chemical substance is found in only certain brand names,
the table on individual brand products should be used.
Step 3 Enumerate the actively exposed population as follows;
• If the exposed population is all adults and the data are
available as such in SMRB, the column for all users (Column
A) should be used. If the data are only available as adult
males and adult females, the data in column A in each table
should be added for the total exposed population. The
investigator should decide whether children of less than 18
years of age are also actively exposed. If so, the age
bracket should be determined and the total population in the
U.S. for the age bracket should be obtained from Table 12
(Section 2.4). The adult percentage of users (Column C)
should then be applied to the total number of children in the
specified age bracket. The resulting population estimate
should then be added to the total adult population for
complete population enumeration.
• If only one member of the household is actively exposed, then
the data for all users as listed for the product buyers
(e.g., female homemakers) should be used to enumerate the
exposed population.
• If the entire household is actively exposed but the SMRB data
are only available for the type of buyer, the procedures to
enumerate the exposed population are the same as the
procedures to enumerate the passively exposed population
described in Step 5.
136
-------
Method 5-2. (continued)
Step 4 To enumerate the exposed population according to heavy, medium,
or light exposure, the same procedures previously discussed are
applicable; however, rather than using the column of data for
all users, the columns of data for heavy, medium, and light
users should be used. This should be done only when exposure
levels are derived from the SMRB use patterns.
Step 5 To enumerate the passively exposed population, two approaches
are possible. The second approach will provide a more accurate
estimate. Both approaches assume that the actively exposed
population will also be passively exposed.
Option 1 - Enumerate the actively exposed population as
described in Step 3. Multiply this population by 2.73, which is
the average number of members per household in the U.S.
Option 2 - Using SMRB collected demographics on the buyer's
household size, multiply the household size by the number of
buyers and then add the results to estimate the total passively
exposed population. For example, to generate a conservative
estimate:
1 person household = Number Buyers x 1 = A
2 person household = Number Buyers x 2 = B
3 or 4 person household = Number Buyers x 4 = C
5 or more person household = Number Buyers x 6 = D
A + B + C + D = total passively exposed population
137
-------
5.3.2 Enumeration of Exposed Populations via Production and Sales Data
Users of consumer products can be enumerated by applying a number of
assumptions and estimation techniques to economic data such as chemical
production volume, Census of Manufactures output, and retail sales
Information. To enumerate the users of a consumer product, the
Investigator must estimate the number of units of a product bought by
consumers, then apply data on usage patterns to determine the average
number of consumers. The result of this calculation will be an estimate,
but a fairly valid one; the components of the calculation are reliably
predicted. An example of the method (Method 5-3) 1s presented 1n
Appendix A-4.
The parameters specific to this calculation are the number of units
of the product manufactured or sold annually and the annual usage
patterns. The first, the number of units, can be derived 1n the manner
described 1n problem 2 1n Appendix A-4 (by assuming an average mass per
unit) or by consulting published data. The Census of Manufactures
(Bureau of the Census 1980) lists production of very specific products
(by seven digit SIC code) 1n units such as pounds, kilograms, cases,
etc. The assessor must assume that production equals sales to
consumers. Other data bases containing this type of Information and
specific Information on retail sales are listed 1n the consumer exposure
assessment methods report (Volume 7). Use patterns can be either
estimated on a product-specific basis or derived from the use Information
provided by SMRB data, as detailed 1n the previous Subsection (5.3.1).
It should be noted that this method of population estimation assumes
that users are brand-loyal; I.e., for any product, a consumer either
always or never uses a brand with the chemical. The result of this
assumption Is that some consumer populations may be underestimated; some
Individual exposures may likewise be overestimated. The calculated
Individual exposure resulting from the use of the product will be higher
than 1f the consumer used various brands or formulations, some of which
contained the chemical substance and some of which did not. The
Information needed to resolve this problem 1s not available at this time.
5.3.3 Enumeration of Exposed Populations via Chemical-Specific
Information
Populations exposed to chemical substances 1n consumer products can
be enumerated through the use of various sources of chemical-specific
Information. The approach 1s not as methodical as that applied to the
use of market research data or economic (production and sales) data;
rather, 1t entails researching Information sources each time a chemical
1s assessed. The various types of Information resources and the
advantages and limitations of each are discussed below.
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Method 5-3. Enumeration of Populations Exposed to Chemicals in
Consumer Products Via the Use of Economic Data
Step 1 Determine the number of units of the product sold or produced
annually.
Option 1 - consult the Census of Manufactures (Bureau of the
Census 1980) to obtain production in unit quantities.
Option 2 - estimate the number of units produced by dividing the
amount of the chemical destined for that use by the formulation
percent and the total mass of product per unit.
Option 3 - consult Volume 7 for alternative sources of data
(sales information, computerized data).
Step 2 Determine use patterns for the product. The SMRB presentation
of heavy-medium-light use, discussed in Section 5.3.1, provides
data for most products. Heavy use may, for example, be defined
as 5 or more cans per week; medium use, 3 or 4 cans, and light
use, 2 or fewer cans per week.
Step 3 Calculate the exposed population by dividing the production
volume in units (from Step 1) by the units used per person per
year (from Step 2).
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(1) Direct contact with associations. Associations are able to
provide many types of consumer-related Information. Many associations
are headquartered 1n the Washington, D.C., area and can be found 1n the
telephone directory. The most comprehensive 11st of associations,
however, 1s 1n the Encyclopedia of Associations (Gale Research 1980).
Although associations can often provide the most accurate and precise
estimates of consumer populations, acquiring the data may be time
consuming and may therefore limit the usefulness of this method to
detailed assessments.
When an association 1s consulted for population estimates, the
contact should be Informed of the reason for the request so that he can
provide the best possible data. The representativeness of the data
should be questioned; for example, a hobbyist association may be able to
provide a membership number and also be able to say that the membership
represents 75 percent of the total hobbyists.
Although there are some limitations to this approach, 1t has been
used successfully 1n exposure assessments for many existing chemicals.
When sufficient time and use Information 1s available, PMN substances can
be Investigated 1n the same manner. Care must be taken to avoid
disclosure of confidential business Information (CBI) provided by PMN
submitters.
(2) Government agencies. The Environmental Protection Agency (EPA),
the Consumer Product Safety Commission (CPSC), and the Bureau of the
Census can provide pertinent consumer Information. The Information 1s
available through direct contact with experts 1n the agencies and the
reports they publish.
CPSC has collected a great deal of Information on recognized hazards
such as asbestos. Information provided by CPSC may aid exposure
assessments of consumer products containing existing chemicals and new
substances Intended as substitutes for recognized hazards. The CPSC,
however, limits Its data collection efforts largely to substances that
have proved harmful. Unless a new chemical 1s similar 1n properties and
1s analogous 1n use to an existing chemical, CPSC's data are of little
aid 1n Investigating new chemicals.
The many publications of the Bureau of the Census may contain useful
Information. For example, those exposed to formaldehyde by residing in
mobile homes were quantified (Versar 1982) by consulting the Annual
Housing Survey (Bureau of the Census 1981). The Statistical Abstract of
the United States (Bureau of the Census 1982) may also provide
activity-related data that are useful in enumerating consumer populations
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Studies of existing chemicals are often conducted by more than one
EPA Office and by many contractors. An exposure assessment of such a
substance will benefit from a review of the published literature
(available through the National Technical Information Service). The
authors or sponsors of these reports may provide additional data 1f
contacted directly.
Some consumer products are so widely used that one can safely assume
the entire population of the U.S. may be exposed. For Instance, all
persons contact plastics and fabrics; common additives to them may cause
nationwide exposure. The most recent data available from the Bureau of
the Census should be used to enumerate the exposed population.
Currently, a total of 226.5 million persons are reported to reside 1n the
U.S. (Bureau of the Census 1982).
5.3.4 Enumeration of Consumers Performing Amateur or Hobbyist
Activities
Consumers may be exposed to chemical substances 1n products designed
mainly for use by professionals. Persons who do their own automobile
maintenance and repair, house painting, lawn care, carpentry and
remodeling, or photographic film development may be exposed to a chemical
substance In a product that might be overlooked 1n a consumer exposure
assessment. Enumeration of the exposed population may be keyed to the
number of people engaged In these activities when other enumeration
procedures, as previously discussed, are not possible. This method of
enumeration, however, overestimates the exposed population because 1t
assumes that all people who engage 1n a particular activity use the
product or products containing the chemical substance.
All of the estimates assume that there 1s one amateur per household.
The estimates presented below and summarized In Table 25 rely on the
Bureau of Census (1982) estimate of 77,330,000 households In the U.S. and
the following additional data.
(1) Automobile work. The U.S. Department of Energy (1980) estimates
that 85 percent (65,700,000) of all households have at least one motor
vehicle and that 55 percent of those households change their own oil.
Thus, 36,100,000 households are estimated to have at least one person who
changes his own oil.
(2) Painting. SMRB (1978) reports that 17.5 percent of U.S.
households purchased exterior paint and 25.7 percent purchased Interior
paint during a one-year period. If 1t 1s assumed that the persons
purchasing paint Intended to use 1t themselves (rather than providing It
to a hired professional painter), the potentially exposed population can
be estimated. If only one member of each household uses paint, then
13,533,000 persons are actively exposed to exterior paint and 19,874,000
are exposed to Interior paint. The members of each household would
experience passive exposure to paint components, probably only 1n
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Interior paint. With an average of 2.78 persons per household, the
passively exposed population 1s 55,250,000 persons.
(3) Lawn and garden care. The number of people who mow their own
lawn provides a fair estimate of people who use fertilizers, pesticides,
and other lawn and garden products. SMRB (1978) estimates that 37
percent of households own a lawn mower. Assuming that one person from
each household Is responsible for lawn care, an estimate of 28,612,000
people tend their own lawns.
(4) Carpentry. A rough estimate of the number of people who engage
1n carpentry can be made based on ownership of electric saws. Anyone
seriously Involved 1n carpentry and, therefore, potentially exposed to
chemical substances 1n carpentry related products, would own this tool.
SMRB (1978) estimates that 23 percent of all households own an electric
saw. Therefore, at least 17,786,000 households Include amateur
carpenters.
(5) Remodeling. The number of people potentially exposed to
chemical substances as a result of household remodeling activities can
also be estimated from SMRB data. SMRB (1978) estimates that 1,132,000
basements, 2,313,000 kitchens, 2,572,000 bathrooms, and 3,898,000 other
rooms were remodeled 1n 1976-77 by a household member. Based on the
number of households 1n 1977 as estimated by SMRB, 74,019,000, the
following percentages are derived; 1.5 percent of households had
basements remodeled, 3.1 percent of households had kitchens remodeled,
3.5 percent of households had bathrooms remodeled, and 5.3 percent of
households had other rooms (e.g., living rooms, bedrooms) remodeled by a
household member. Assuming these data are representative of current
remodeling activities, the percentages can be applied to the current
number of U.S. households to calculate populations. The results are
presented in Table 25.
(6) Photography. An estimated two to three million people develop
their own film (Wolfram Report 1979). This would be 2.6 to 3.9 percent
of the U.S. households, assuming that there is only one photographer per
household.
5.4 Characterization of Exposed Populations
Exposed populations are often characterized by age and sex, since
physiological parameters affecting exposure or risk are often age- or
sex-dependent. Characterization of consumer populations is especially
important, since many products are designed for or used by specific
subpopulations.
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Table 25. Summary of the Number of Households That Can Be Considered
To Have at Least One Amateur or Hobbyist with Respect
to a Specific Activity.
Activity Number of households^ Percent of all
households
Crankcase oil and filter change
Lawn and garden maintenance
Painting (exterior of house)
Painting (interior of house)
Carpentry
Remodel i ng
Basement
Kitchen
Bathroom
Other
36,100,000
28,612,000
13,533,000
19,874,000
17,786,000
1,160,000
2,397,000
2,707,000
4,098,000
47
37
17.5
25.7
23
1.5
3.1
3.5
5.3
Photography 2,500,000
on 77,330,000 households in the U.S. (Bureau of the Census 1982).
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As was discussed In Subsection 5.3.1, the SMR8 data are presented by
detailed demographic characteristics. The populations reported as
buyers/users of each product, assumed to be the actively exposed
populations, are defined by sex and then stratified by age (see
Tables 22 to 24). The characteristics of adults actively exposed to
consumer products are therefore readily available. Less easily
characterized are persons under the age of 18 and passively exposed
populations. The SMRB data report only the relative frequency of the
presence of children 1n the age groups of 0 to 2, 2 to 5, 6 to 11, and 12
to 17 years of age In the households with active users.
The only data available for characterizing the consumer population
under 18 by age and sex are the national distributions presented 1n
Section 2.4 of this volume (Table 12). Should such a characterization of
the population be necessary, the assessor must assume that the affected
group can be described by those data or a discrete subset thereof (I.e.,
males or females or some defined age group).
As described 1n Subsection 5.3.1, persons passively exposed 1n a
user's household can be enumerated by use of the relative frequency of
household sizes. However, no characteristics of the household members
are available; generic data must be used to characterize that
population. If 1t 1s assumed that the total population of persons living
1n households with users of the product represent a cross-section of the
total U.S. population, the data (Table 12) 1n Section 2.4 of this volume
can be used to describe the age and sex characteristics of the group.
Method 5-4 summarizes the steps to be performed In the
characterization of populations exposed to chemical substances 1n
consumer products.
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Method 5-4. Characterization of Populations Exposed to Chemical
Substances in Consumer Products
Step 1 If the consumer population was enumerated by the use of SMRB
data, use the demographic characteristics reported for
buyers/users to characterize the actively exposed population
by age and sex.
Populations enumerated by other methods can also be
characterized by consulting the SMRB report for the
product(s) most similar to that being assessed.
Step 2 Consult Section 2.4 (Table 12) of this volume to derive
generic age and sex characterization for:
- Consumer populations under the age of 18
- Passively exposed household members
- The entire population of the U.S.
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5.5 References
Bureau of the Census. 1980. 1977 Census of manufactures. Washington,
DC: U.S. Department of Commerce.
Bureau of the Census. 1981. Annual housing survey. Washington, DC:
U.S. Department of Commerce.
Bureau of the Census. 1982. Statistical abstract of the United States,
1982-83. 103rd edition. Washington, DC: U.S. Department of Commerce.
Gale Research Corp. 1980. Encyclopedia of associations. Michigan:
Gale Research Company.
SMRB. 1978. Simmons Market Research Bureau. Simmons studies of
selective markets and the media reaching them. Volume 29. Home
furnishings, remodeling and upkeep. New York, NY.
SMRB. 1981. Simmons Market Research Bureau. Simmons studies of
selective markets and the media reaching them. New York, NY.
SMRB. 1982. Simmons Market Research Bureau. Simmons study of selective
markets and the media reaching them. New York, NY.
U.S. Department of Energy. 1980. Analysis of potential used oil
recovery from Individuals. Final report. Washington, DC: U.S.
Department of Energy, DOE/BC/10053-21.
Versar. 1982. Exposure assessment for formaldehyde. Draft report.
Washington, DC: U.S. Environmental Protection Agency, Office of Toxic
Substances.
Wolfram Report. 1979. Wolfram report on the photographic Industry.
Modern Photography, New York, NY.
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6. POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF
DRINKING WATER
6.1 Introduction
This section presents methods for the enumeration and
characterization of populations exposed to chemical substances via the
Ingestlon of drinking water. The methods described are applicable to
publicly and privately supplied drinking water that may contain chemical
substances as a result of (1) Industrial, commercial, and household
effluents to surface and ground water, (2) runoff or seepage from waste
disposal sites, (3) non-point source runoff or seepage from agricultural
and nonagrlcultural land uses, (4) drinking water treatment processes,
(5) drinking water distribution systems, and (6) pollution of unknown
origin. The methods are based on exposure as a result of the voluntary
Ingestlon of drinking water; as such, the methods do not consider
Involuntary Ingestlon (e.g., swallowing of water during swimming) or
dermal and Inhalation exposure to chemical substances 1n drinking water.
Figure 21 1s a flow diagram of the three-stage method framework for
enumerating and characterizing populations exposed to chemical substances
via the Ingestlon of drinking water. The following paragraphs briefly
describe each of the stages; detailed Information 1s provided 1n
subsequent sections.
The first stage, Identification of exposed populations, is
accomplished by examining the sources of the chemical substance.
Detailed Information on procedures to complete a drinking water exposure
assessment, which Include identification of the exposed population, 1s
included 1n Volume 5 of this series, in "Methods for Assessing Exposure
to Chemical Substances In Drinking Water." Subsection 6.2, therefore,
only briefly describes the procedures for identifying the exposed
population.
Enumeration of the exposed population is discussed in Subsection 6.3.
This stage Involves the use of various computerized data bases that
contain information on drinking water such as the sources of the raw
water supply, intake locations, treatment methods, and populations
served. Enumeration also involves the use of generic data on populations
served when detailed geographic, resolution is not required or when the
financial or manpower constraints of the exposure assessment effort do
not permit the development of detailed information.
The final subsection (6.4) describes the procedures for
characterizing the enumerated population according to age and sex. Data
sources are presented which will provide age and sex characteristics of
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populations where geographic detail 1s required or generic age and sex
characteristics for situations where specific detail 1s not required.
Examples of the use of the methods 1n this section are presented 1n
Appendix A-5 of this report.
6.2 Identification of Exposed Populations
Exposed populations can be Identified either through knowledge of the
sources of chemical contamination or by examination of monitoring data.
The former 1s a "materials balance" approach and comprises three types of
sources:
1. Sources that can be geographically defined (e.g., Industrial
effluents and non-point sources of water pollution).
2. Sources related to the treatment processes used 1n production of
potable water (e.g., use of chemicals as coagulant aids).
3. Sources within the distribution system (e.g., dissolution of
solvents from glued pipe joints).
Monitoring data may identify water sources with contamination of known or
unknown origin.
Comprehensive identification must consider all three source types as
well as available monitoring data. Identification may be keyed to the
geographic location of the water supply, treatment methods, distribu-
tion system type, or any combination of the three. The procedure for
identification is presented as Method 6-1.
It is readily apparent that only Step 1 of Method 6-1 provides
positive identification of exposed populations; the materials balance
approach outlined in Steps 2 and 3 identifies those that are potentially
exposed. The drinking water exposure assessment methods report
(Volume 5) presents detailed methods for Identifying exposed populations.
The populations Identified in this stage must subsequently be
enumerated. The following subsection discusses the methods for
enumerating populations defined by the three types of sources and
identified through monitoring data.
6.3 Methods for the Enumeration of Exposed Populations
This section discusses the recommended procedures and data sources
for enumerating populations exposed to chemical substances via the
Ingestion of drinking water. The section is divided into four
subsections based on the categories for Identifying the exposed
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Method 6-1. General Procedure for Identifying Populations
Exposed to Chemical Substances in Drinking Water
Step 1 Obtain all available monitoring data for the substance being
assessed. Monitoring data for finished water provides positive
identification of an exposure source; however, it may not
identify what the source is. The population served by the
utility surveyed is an exposed population.
Step 2 Examine the environmental releases of the substance in the
ambient environment. Knowledge of these releases, coupled with
knowledge of the environmental fate of the substance in the
aquatic environment, leads to identification of contaminated
aquifers and surface waters. The persons drinking these waters
are potentially exposed.
Step 3 Examine the uses of the substance. If it is used in the
drinking water treatment or distribution systems, the
populations served by those systems may be exposed.
(NOTE: Detailed information on identifying sources of chemical
contamination and exposed populations is provided in Volume 5 of this
exposure assessment methods report series.)
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populations. Subsection 6.3.1 presents the procedures and data sources
for enumerating exposed populations that are geographically defined by
the sources of the chemical substance of Interest; the procedures 1n
Subsection 6.3.2 enumerate populations exposed to chemical substances as
a result of drinking water treatment processes; the procedures 1n
Subsection 6.3.3 enumerate populations exposed to chemical substances
from the materials (e.g., pipes) used to distribute drinking water; and
the procedures 1n Subsection 6.3.4 enumerate populations exposed to
chemical substances that have been Identified from water quality data
collected during drinking water monitoring. The Investigator's choice of
an appropriate method should be based on how the exposed population has
been Identified.
6.3.1 Enumeration of Populations 1n Specific Geographic Areas
This section presents methods for enumerating populations 1n specific
geographic areas where sources of the chemical substance of Interest are
located. These sources may Include Industrial, commercial, or household
effluents, Publicly Owned Treatment Works (POTWs), waste disposal sites
(e.g., landfills, wastewater lagoons), and transportation related
spills. The Individual volumes of this series discuss the data sources
and procedures for Identifying the sources of a chemical substance.
Methods to link geographically-defined point sources with nearby drinking
water Intakes are discussed in the drinking water exposure assessment
methods report (Volume 5). Identification of the sources of the chemical
substance in turn permits the identification of the affected raw drinking
water supplies. Identification of the raw water supplies, therefore, is
the first step required. The type of raw water supply used, either
surface water or ground water, determines the data bases that should be
used 1n the population enumeration effort.
(1) Surface water. The principal data source for identifying both
public and private drinking water utility companies that use surface
water as their raw water supply is the Water Supply Data Base (WSDB).
WSOB is a computerized data base maintained by the EPA Monitoring and
Data Support Division, Water Quality Analysis Branch. It contains
information on the location of surface water utilities; the locations of
the utilities' treatment plants, intakes, and sources of raw water; the
populations served; and the average and maximum daily production. A
complete description of WSDB is available in Water Supply Data Base:
Inventory of Surface Water Supplies and Addendum on a Groundwater Data
Base Structure (Versar 1981).
The most useful application of WSDB is the integration of its data
with data on sources and concentrations of chemical substances contained
1n other data files maintained by EPA-MDSD, such as the Industrial
Facility Discharge (IFD) File and the STORET Water Quality Data Base.
The data in each of these files can be accessed via another data base
known as the REACH File. A complete description of the REACH File is not
within the scope of this report; essentially, however, the REACH File is
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a data source for Information on surface water, rivers, streams, lakes
and reservoir segments that are coded within the U.S. Geological Survey's
Hydrologlc Unit Cataloging System. The drinking water intake locations
1n WSDB, the Industrial discharge locations 1n IFD, and the locations of
water quality monitoring stations 1n STORE! are similarly coded with a
REACH number. The REACH number, therefore, hydrologlcally links these
files together. EPA-MDSD has developed several software packages to
access the data contained in the various files via the use of the REACH
number. Population data contained in WSDB may be obtained in this
Integrated approach. Method 6-2 lists the procedural steps of the
integrated approach to obtaining Information on sources, affected surface
water supplies, and populations served. The drinking water exposure
assessment methods report (Volume 5) provides a much more detailed
description of WSDB and the other hydrologlcally linked data bases.
(Note: Requests for data base retrieval should be directed to Mr. Phil
Taylor, USEPA, Monitoring and Data Support Division, Water Quality
Analysis Branch.)
The Investigator will now have identified sources, raw water
supplies, drinking water utilities, and populations served in one
integrated process. EPA-MDSD is further expanding the usefulness of the
integrated approach by assigning river mile indexes to all discharge
points in IFD and intake points in WSDB. This will facilitate
determination of the distances between these points. Distance
calculations can then be used to model 1n-stream water quality dilution
and the resultant concentration at drinking water supply intake points.
Details on retrieval methods, keywords, and other integrated approaches
are available in General Information on IFD. Drinking Water Supplies.
Stream Gages. Reach, and Fishkill Files and Retrieval Procedures for
Hydroloqically Linked Data Files (USEPA I981a).
The enumeration of populations exposed to chemical substances via
surface water supplies contaminated by other sources (e.g., runoff from
waste disposal sites, non-point sources) is also straightforward. The
recommended approach 1s presented as Option 2 in Method 6-2.
The investigator should be aware of two limitations in WSDB, and they
should be noted 1n the exposure assessment report. First, the intake
location coordinates for drinking water utilities that serve populations
less than 25,000 are only approximate locations (generally within +.10
minutes of latitude and longitude). Location coordinates for utilities
serving more than 25,000 people are extremely accurate because they were
developed from USGS 7.5-m1nute topographic, maps. The second limitation
1s that the population data were collected between 1965 and 1975 and may
not reflect current populations. If the data set of identified utilities
1s limited, the investigator should contact the drinking water utility
supervisor and directly request up-to-date data on populations served by
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Method 6-2. Enumeration of Populations Exposed to Chemical
Substances in Surface Sources of Drinking Water Using
the REACH File
Option #1 - To be used for surface sources contaminated by industrial and
POTW effluents. For detailed information on the following steps, see
Volume 5 of this methods series or USEPA (1981a).
Step 1 Identify cipplicable SIC codes for the chemical substance of
interest >3e Volume 2, Methods for Assessing Exposure to
Chemical r :'jstances in the Ambient Environment).
Step 2 Request retrieval of IFO data for facilities within SIC category
(requests should be directed to Mr. Phil Taylor, USEPA,
Monitoring and Data Support Division, Water Quality Analysis
Branch, Washington, DC).
Step 3 Identify receiving water bodies by REACH number and USGS
cataloging unit. (Note: The REACH number actually consists of
11 digits and includes the 8-digit USGS cataloging unit and the
3-digit EPA segment number. The segment number is frequently
referred to as the REACH number. Retrievals limited to the
entire 11-digit REACH number will identify water supply intakes
and industrial discharges only on that particular segment. If a
retrieval is made according to the USGS cataloging unit only, it
will identify all points of interest in the USGS surface water
drainage basin.)
Step 4 Request a hydrologic tree retrieval (HYDRO) from EPA-MDSD for
each REACH number or cataloging unit identified. Include a
request for populations served in the data tabulation. HYDRO
will list in a tree diagram industrial discharge pipes, water
supply monitoring stations, and water supply intake points
according to hydrologic order. "Hydrologic ordering" provides
stations on the most downstream reach first, and proceeds
upstream, reach by reach.
Option #2 - To be used for surface sources contaminated by non-industrial
effluents (e.g., chemical spills, non-point sources, waste disposal site
runoff).
Step 1 Identify contaminated raw water supplies by USGS Hydrologic
Units (8-digit number) using USGS State Hydrologic Unit
Maps. Segment numbers, if desired, can be obtained from
Mr. Robert Horn, EPA-MDSD, Monitoring Branch.
Step 2 Request WSDB retrievals from EPA-MDSD according to USGS
hydrologic units. Include population served and intake
name and location as parameters in data tabulation
request. Check WSDB retrieval to determine whether listed
utilities are withdrawing water directly from or downstream
of the water body of concern.
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the utilities' distribution system. (Note: Drinking water utilities
will frequently perform a residential meter count rather than an actual
head count of residential customers. If data are provided 1n this
format, the Investigator can assume 2.73 persons/meter based on Census
data for the number of persons per household (Bureau of Census 1982a) to
enumerate the total population.)
The WSDB 1s recommended as the primary data source for enumerating
populations exposed to chemical substances via the ingestion of surface
supplied drinking water. This 1s principally due to the Inclusion of the
REACH number 1n the data base structure. That number facilitates an
Integrated process of Identifying sources (I.e., industrial and POTW
dischargers) of chemical substances and enumerating exposed populations
as previously described. There 1s another data base, however, that
includes surface water populations served and intake locations. This
data base, maintained by the EPA Office of Drinking Water, is known as
the Federal Reporting Data System (FRDS). FRDS, discussed 1n the
subsequent section on ground water, can be used as a source of
Information supplementary to that contained in WSDB. It can also be used
to check the accuracy of the WSDB-listed population data. FRDS
population data are updated annually by each primary agency (i.e., state
or EPA region). As such, the population data is more accurate than the
data stored in the WSDB. Cross-referencing of the two data bases is
straightforward because WSDB listings include the FRDS utility number in
the data structure. FRDS geographic restricted retrievals can be made by
state, county (i.e., according to FIPS code), SMSA and USGS hydrologic
units. FRDS, however, does not include EPA developed stream segment
numbers for intake locations; therefore, integrated data retrievals with
other STORET and EPA-MDSD-maintained data files are not possible. The
recommended method for obtaining and using FRDS data is presented in
Method 6-3.
(2) Ground water. The principal data source for identifying either
public or private drinking water utilities that use ground water is the
previously mentioned Federal Reporting Data System (FRDS).
FRDS 1s an information management system used by both EPA
headquarters and regional personnel to monitor program performance in
each state. It contains Inventory data as well as the compliance status
of each public water supply. Separate data bases are maintained for each
*A.W. Marks, EPA-Office of Drinking Water, Washington, DC: personal
communication with M. Callahan, EPA-Office of Toxic Substances;
memorandum dated August 2, 1983.
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Method 6-3. Enumeration of Populations Exposed to
Chemical Substances in Surface Sources
of Drinking Water Using the FRDS Data Base
Step 1 Request PROS retrieval according to geographic area of interest
(e.g., by state and/or county according to FIPS code, by SMSA
according to SMSA code, or according to USGS cataloging unit).
Note: FRDS retrieval requests should be directed to:
Mr. Avrum Marks
Manager Computer Systems Staff
EPA Office of Drinking Water
Washington, DC 20460
Step 2 Scan retrieval for utilities listed that obtain raw water
supplies from the water bodies of interest.
Step 3 Check for utilities that purchase finished drinking water from
another utility. Under "source type," these utilities will be
listed with the letter P. When totaling populations served, the
investigator should not count population data for these
utilities since these are already contained in the population
served data for the utility that is processing the raw water.
This avoids "double counting" the exposed population.
Step 4 Total the data on population served to enmumerate the total
population exposed to the chemical substance of interest.
155
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fiscal year after 1978 as well as the current year. FRDS became
operational during January of 1979. As of April 15, 1980, Information
from all 57 states and territories, as well as Information on Indian
reservations within four EPA regions, had been received and processed.
Four types of data are collected by FRDS, based on regulatory
reporting requirements (Marks 1980):
1. Inventory. This Includes public water supply (PWS) capacity,
source Information, monitoring requirements, and facility name
and address. Figure 22 1s a sample report containing the types
of Information available for each PWS. However, since many of
the data elements are not required for federal reporting, all of
this Information may not be available for each PWS.
2. Violation. This Includes data pertaining to noncompHance with
EPA or state standards by a specific water supply.
3. Variance and exemption. This Includes data pertaining to
authorized exceptions to the standards which are granted to a
specific water supply.
4. Enforcement action. This includes information pertaining to
actions taken against a public water supply.
In addition, summary statistics for each state are generated and
maintained within the FRDS data base. The data types of greatest
relevance are the inventory Information and the summary statistics.
Besides the ad hoc capabilities of the system, 11 standard reports have
been generated. These are summarized in Table 26. The most useful are
marked with an asterisk; they include reports listing data on populations
served (number of meters), source location, treatment types (where
available), and percentage breakdowns of data for individual states.
The procedure for enumerating populations exposed via ground water is
to define the area of concern as determined by the sources of the
chemical substance of interest (e.g., landfill leachate to ground water
in a specific county or state). This step will be completed as part of
the overall exposure assessment process. Detailed Information on
procedures for completing this step are presented in the drinking water
exposure assessment methods report (Volume 5). The procedure is
summarized in steps in Method 6-4.
The output of the procedure will be a list of all facilities in the
geographic region selected (which may or may not be tapping the aquifer
of interest), together with the population served and treatments used by
each facility. The degree to which this information is complete depends
on the thoroughness of the Input from the particular state.
156
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Table 26. Federal Reporting Data System (PROS)
Description of 11 Standard Reports
Report Title Description
*1. Public Water Systems - Comprehensive Lists all PWSs meeting the selection parameters, one
Listing per page, showing all FVIS inventory data.
*2. Public Water Systems - Production Details production, capacities, meters, and services
and Capacity Data data for each PWS meeting the user's selection
criteria.
*3. Public Water Systems - Service Area Lists service area location and characteristics and
and Source Data water source information, including treatments, for
each PWS satisfying the user's selection criteria.
4. Public Water Systems - State Dis- Details all state discretionary data and variances
cretionary Data and exemptions for each PWS satisfying the user's
selection criteria.
*5. Number and Percentage of Facilities Shows this information by population category and by
and Populations Served by Type of state.
Water Supply Source
6. Enforcement Actions Summary by Shows number of enforcement actions occurring by state,
Population population category, and type.
7. Enforcement Actions Summary by Type Shows number of enforcement actions occurring by state,
and Source type of action, and type of water source.
8. Violations Summary by Population Shows number of violations occurring by state, popula-
tion category, and type.
9. Violations Sunmary by Type and Shows number of violations occurring by state, contam-
Source inant, type of violation, and type of water source.
10. Variances and Exemptions Summary by Shows number of variances and exemptions by state,
Population population category, and type.
11. Variances and Exemptions Sunmary by Shows number of variances and exemptions by state,
Type and Source contaminant, type, and type of water source.
* Indicates report useful for population enumeration effort.
Source: Harks 1980. As updated via personal communication by A.W. Marks, EPA-Office of Drinking
Water, to M. Callahan, EPA-Office of Toxic Substances; memorandum dated August 2, 1983.
158
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Method 6-4. Enumeration of Populations Exposed to Chemical Substances
in Ground Sources of Drinking Water
Step 1 Request a FRDS retrieval for the subject county and all
surrounding counties: or by SHSA. This should be a
"Comprehensive Listing" of all PWS using ground water in the
subject counties or SMSA. Since the specific aquifer used as
the source is almost never identified, it will have to be
assumed that all local ground water facilities are potentially
tapping the subject aquifer. The FRDS printout will supply data
on populations served and treatment types used. When
populations are totaled, the population data included in utility
listings that purchase finished water (Code P under source type)
should not be included. This avoids counting populations twice.
Step 2 FRDS does not include private wells. If necessary, this number
can be deduced by conducting both surface water and ground water
retrievals for the subject area, and subtracting population
figures from the total population of the region (available from
the Bureau of the Census (1982b)).
159
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Although the WSDB 1s not, at this time, a useful data source for
enumerating populations exposed via ground water, EPA-MOSD plans to
expand the WSDB ground water coverage. The WSDB structure has been
recently expanded to facilitate the storing of ground water utility
Information (Versar 1981). Included 1n the ground water utility
Information 1s the capability for recording the name and USGS-developed
code for the aquifer from which the water 1s obtained. Presently, only
the data for the 100 largest cities 1n the U.S., as Identified by USGS 1n
1962 (Durfor and Becker 1964), have been added to WSDB. These data were
updated 1n a telephone survey 1n 1981 (Versar 1981) before being added to
the data base. The updating of WSDB with data on all ground water
utilities 1n the U.S. 1s tentatively planned by EPA-MDSD pending
determination of future funding priorities.
6.3.2 Enumeration of Populations Exposed via Treatment Methods
The screening of a chemical substance's sources may Identify a
drinking water treatment process, or lack thereof, that could result 1n
human exposure. For example, the addition of a polyelectrolyte (e.g.,
polyacrylamide) to coagulate suspended sediments 1n raw water may add a
residual contaminant (e.g., acrylamide monomer) to the finished drinking
water. Similarly, the absence of activated carbon filtration treatment
of raw water contaminated with organic chemicals may result in the
production of finished drinking water containing organic chemicals.
Exposed populations may, therefore, occasionally be identified by a
treatment process or combination of processes. The primary data source
for the enumeration of populations exposed via treatment processes 1s the
FRDS Data Base discussed in Subsection 6.3.1(2).
FRDS contains figures for the number of people served for each listed
public water supply system; in many cases treatment methods are also
listed. Treatment information is not required by EPA but is often
supplied by states. The population served by treatment type, therefore,
is slightly inaccurate. It will, however, provide an estimate of the
order of magnitude of the population size.*
The EPA Office of Drinking Water, which maintains FRDS, has put
together several summary reports that relate populations, locations, and
water source (ground vs. surface) with treatment processes (Marks 1980).
These reports are listed in Table 26, Subsection 6.3.1(2). These reports
are valuable as quick reference documents to enumerate populations when
general geographic area information is required. For purposes of
convenience, Table 27 summarizes the number of facilities and populations
served by treatment processes for the entire U.S., based on 1980 data.
When data for a specific geographic area are required, the investigator
should request FRDS retrievals from the Computer Systems Staff, EPA
Office of Drinking Water, as described in Method 6-5. Completion of
these steps will result in the enumeration of the exposed population.
*K. Karin Wang, EPA-Office of Drinking Water, Washington, DC: personal
communication with D. Dixon, Versar Inc., July 27, 1982.
160
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Table 27. Population Served by Drinking Water Treatment
Processes for the U.S.
Treatment
method
Corrosion control
Softening
Taste and odor
Iron removal
Ammoniation
Fluori elation
Disinfection
Untreated
Aeration
Prechlorination
Coagulation
Sedimentation
Filtration
Number of
facilities1
3,334
2,540
2,941
4,275
1,071
7,150
20,663
33.7812
4,154
4,791
4,615
5,020
6,265
Population served
(x 1,000)
68,636
39,582
97,728
54,773
18,242
115,392
171,666
20,530
64,952
76,952
117,309
114,800
117,066
Source: FRDS Data Retrieval FY 1980
^ facility is defined as a system serving >25 persons
^Primarily ground water systems
161
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Method 6-5. Enumeration of Populations Exposed to Chemical
Substances as a Result of Lack of Treatment Processes
Step 1 Identify the treatment process or processes of interest (e.g.,
coagulation, chlorination, fluoridation).
Step 2 Identify the source(s) of raw water (i.e., surface, ground, or
both).
Step 3 Identify the geographic area of interest (e.g., state, county,
SMSA, USGS cataloging unit).
Step 4 Request FRDS retrieval from EPA Office of Drinking Water
according to the above-identified parameters. Include a listing
of the population served in data retrieval request. Exclude
utilities that purchase finished or raw drinking water ("P"
code) to avoid counting populations twice.
NOTE: Reporting of treatment techniques is not required of states by
EPA. The sizes of the populations covered by various treatment methods
are generally under-reported. FRDS, therefore, provides only an
order-of-magnitude estimate of the size of the exposed population.
162
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6.3.3 Enumeration of Exposed Populations by Type of Distribution System
The distribution system may be a source of exposure to chemical
substances. Distribution system components and potential contaminants
are listed 1n Table 28.
It would be Ideal to enumerate the populations served by each type of
distribution system and component. This approach 1s not feasible for two
major reasons:
• While 1t Is simple to enumerate the customers served by any
distribution system, 1t 1s nearly Impossible to determine the
components of any system. Many types of pipe are used 1n each
system, and there 1s often no record of the type of piping,
• Neither historical nor current data on sales and use of pipe and
other components 1n drinking water distribution systems are
available.
Some qualitative generalizations about the relative uses of various pipes
are possible. The generalizations are based on the applicability of
different pipes 1n different situations.
Plastic pipe (usually polyvlnyl chloride (PVC)) dominates the market
1n rural water systems. PVC pipe has long been accepted for drinking
water supply, which 1s the main water use 1n rural areas. In urban
areas, fire protection Is a major concern, and the high pressures at
which water Is piped 1n cities do not allow the use of PVC. It has been
estimated that 11.2 million rural Americans were drinking water from PVC
pipes in 1979*. The number of urban users 1s unknown but 1s thought to
be small. The relative proportion of Americans drinking water from
PVC pipe is expected to increase, since PVC 1s used mainly 1n new
construction areas.
In urban areas, the market for water pipe is very competitive. It
appears to be fairly evenly split among concrete, ductile iron, asbestos-
cement, and steel pipe in the 16-to 24-1nch size range, and Iron and
copper for smaller pipe.''" It should be noted that the smaller pipe
(less than 16 inches in diameter) accounts for 90 percent of the linear
footage of pipe laid.*
*B111 Nesbitt, President, Uni-Bell Plastic Pipe Assn., personal
communication with Gina Hendrlckson, Versar, Inc., April 1982.
'''John Capita, American Water Works Assn., personal communication with
Gina Hendrickson, Versar, Inc., April 1982.
WHlett, Concrete Pressure Pipe Assn., Personal communication
with Gina Hendrickson, Versar, Inc., April 1982.
163
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Table 28. Distribution System Components
and Potential Contaminants
Component
Potential contaminant
Metal pipe (copper,
iron, steel)
Pipe joint glue
Asbestos-cement pipe
Lined pipe and
plastic pipe
Metals; microbial
products
Organic solvents
Asbestos fibers
Plastic monomers,
polycyclic aromatic
hydrocarbons
164
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A very rough estimate of the urban populations served by different
types of pipe can be obtained from the preceding Information. In
reality, the population exposed via each type may range from less than 25
percent to 100 percent of the urban population, since no two types of
pipe are Incompatible and 1t 1s likely that more than one type 1s used 1n
a single system.
6.3.4 Enumeration by Use of Monitoring Data
Monitoring data can be used to predict the number of persons drinking
water containing a chemical substance. The method extrapolates data on
the frequency of detection of the substance. The level of detail
achieved by this tool depends on the form, representativeness, and sample
size of the data. In Its simplest form, the enumeration proceeds as
shown 1n Method 6-6. The assumptions Inherent 1n this very gross
estimation Include the assumption that the data are Independent of the
water source (surface or ground water). It must also be assumed that the
data represent systems of all sizes, so that the frequency can be applied
to the total population. Obviously, these assumptions limit the
usefulness of the method; 1t should only be used 1n the absence of more
refined data.
The Investigator can Improve this technique by breaking out the total
population Into groups defined by drinking water source or system size.
Table 29 lists the populations served by systems of different sizes and
source types. If the monitoring data Indicate the source or system size,
that Information should be used since the following two considerations
can greatly affect water quality:
• The fate of pollutants 1n surface and ground waters differ.
While a chemical may volatilize from surface water, 1t may
persist 1n an aquifer. B1odegradat1on may proceed at a slower
rate In ground water because of lack of oxygen. More
partitioning to soils and sediments may occur 1n groundwater
because there is larger surface area available for absorption.
• Pollution (such as vehicle-generated heavy metal contamination)
may be anthropocentric and consequently related to system size.
Treatment techniques also vary by size of the system; generally,
less sophisticated treatment is used 1n systems serving small
populations.
If a pollutant's frequency of detection can be defined by either
system size or source, the frequency can be applied to that subpopulatlon
to derive an accurate estimate of the exposed population. Examples of
this method are demonstrated in Appendix A-5.
The use of monitoring data to estimate the exposed population 1s
limited in all cases by two assumptions. The sample size must be large
165
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Method 6-6. Enumeration of Exposed Populations by the Use of
Monitoring Data
Step 1 Calculate the frequency of detection from the monitoring data;
if detected in 10 of 100 samples, the detection frequency is 10
percent.
Step 2 Multiply the detection frequency by the total population of the
U.S. (226.5 million).
166
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-------
enough that the frequency of detection approximates the frequency of
occurrence. The detection limit 1s the lower limit for estimating the
exposed population via this method. Exposure below the detection limit
may, however, be significant for certain chemicals.
6.4 Characterization of Exposed Populations
This subsection describes the data sources and procedures for
characterizing the exposed population with respect to age and sex. In
most exposure assessments, age and sex characterization will not be
necessary. However, drinking water Intake rates are a function of the
Individual's age and sex; characterization may be necessary to obtain a
precise exposure distribution. If the chemical substance of Interest has
special effects on particular age classes such as children or the
elderly, further characterization of the enumerated population 1s also
Indicated. If, for example, a chemical substance is determined to be
teratogenlc, enumeration of women of child-bearing age may be required.
The simplest and most rapid method of characterizing a large
population is to assume that the age and sex distributions approach those
of the total U.S. population. Table 12 of Section 2.4 of this report
depicts the age and sex distributions by percent for the total U.S.
population. These percentages should be applied to the population
enumerated via the data sources discussed in the previous section 1n
order to characterize the population exposed via drinking water.
Characterization within specific geographic, areas, such as states,
townships, and cities, is also straightforward and involves the use of
census publications. General Population Characteristics, PC80-1-B Series
(Bureau of the Census 1982b) provides the age and sex population data for
most defined geographic areas. These data will frequently be provided as
total population by age and sex and not as percentages in each age class
or sex. The data, therefore, must be converted to a percentage basis.
The calculated percentages are then applied to the population enumerated
via one of the data sources discussed in the previous section.
168
-------
6.5 References
Bureau of the Census. 1982a. Statistical abstract of the United
States: 1982 (103rd edition). Washington, DC: U.S. Department of
Commerce, U.S. Government Printing Office.
Bureau of the Census. 1982b. 1980 Census of population. U.S. summary.
General population characteristics. PC80-1-B Series. Washington, DC:
U.S. Department of Commerce.
Durfor CN, Becker E. 1964. Public water supplies of the 100 largest
cities in the United States, 1962. Geological Survey Water-Supply Paper
1812. Washington, DC: U.S. Geological Survey.
Marks AW. 1980. EPA's computer systems for drinking water. Washington
DC: U.S. Environmental Protection Agency, Office of Drinking Water.
USEPA. 1981a. U.S. Environmental Protection Agency. General
information on IFD, drinking water supplies, stream gages, reach, and
fishkill files and retrieval procedures for hydrologically linked data
files. Washington, DC: Water Quality Analysis Branch, Monitoring and
Data Support Division.
USEPA. 1981b. U.S. Environmental Protection Agency. Memorandum from
B. Coniglio, ODW, to 1SPC Solvents Work Group No. 2. Washington, DC:
U.S. Environmental Protection Agency.
Versar Inc. 1981. Water supply data base. Inventory of surface water
supplies and addendum on a ground water data base structure. Washington,
DC: U.S. Environmental Protection Agency, Monitoring and Data Support
Division.
169
-------
Introduction
The population enumeration methods report 1s a compilation of data,
Information resources, and methods. This appendix to the report 1s
designed to Illustrate some of the approaches recommended 1n the methods
already discussed. A perusal of these examples will demonstrate that the
methods are not necessarily steps that must be explicitly followed; the
Investigator must be flexible and creative when choosing among available
methods and options.
This appendix 1s arranged as follows:
A-l: Populations Exposed to Chemical Substances 1n the
Ambient Environment
A-2: Populations Exposed to Chemical Substances 1n the
Occupational Environment
A-3: Populations Exposed to Chemical Substances via the
Ingestlon of Food
A-4: Populations Exposed to Chemical Substances via the
Use of Consumer Products
A-5: Populations Exposed to Chemical Substances via the
Ingestlon of Drinking Water
In some cases the examples are hypothetical; other problems are based on
actual problems encountered during the assessment of exposure to chemical
substances.
The methods and data used In the compilation of this appendix are
detailed In the text of the methods report. Whenever data limitations
became apparent 1n the course of problem-solving, however, those
limitations are discussed in the examples.
173
-------
APPENDIX A-l
POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE AMBIENT ENVIRONMENT
Problem 1: Attached 1s a sample computer run of ATM-SECPOP. The model
was used to estimate air concentrations of trlchloroethane as a result of
process emissions from a point source located 1n Texas. The purpose of
the printout 1s to exemplify procedures used to perform ATM-SECPOP
simulation.
174
-------
Enter an operation? AUTOHELP
Operations include*.
FILE MANAGEMENT
GRAPHICS
ENPART
#UTMTOX (U)
* Not yet implemented
Enter 3 model n ; >J ATM
The title o" the run can be UP tc< eights chisr
-------
AL PQ. PLACE SOMEWHERE^ LA I/LONG USED — 10/1'A'79#*
Enter the titlf of this runt Site A? 1»1»1 - Trichloroethane
The user should enter PhFAULT. (In future- vejsions of the sy<>teirif
users wiJ.i 'UP .*bJe to supply aitorn-st IVBS to the default valuer)*
Entering DEFAULT causes the following values to be ust-d by ATM!
Number of cont-entratJon points in each
of the sixteen wind directions! 40
Number of rJnSst 10
Ring distances (km)! 0,5» 1? 2? 7> 4»
5? 1.0, 13» 2ti» 50
Number of concentration points Her rin^I 4
Enter the default status! DEFAULT
The name of the point source csn be UP to twenty-four c-hsrsctevs
lon^. This information must be supplied by the uvier At present.
Enter the nsrne of the point source; Site A
Type LAT/LONG or ZIFCODE to indicate thft kind of source location
identifier yttu will use. Thn source location identifier is LAT/LONG
if the user knows thp rffosraphic coordinates of tht> sJte» or ZIPCOBE
if onJy the ,.iprode j.s known. Itf both di'& evsiliiblei' the u^nr should
use LAI/LONG. Henerslly? more accurate results wi'U bw obtained if
tiie correct LAT-'LONij is used.
Press Rh.TUf>'N to continue;
177
-------
Enter the source location identifier? LAT/LON6
The latitude i& entered in decrees* minutes* ,ind seconds»
Each of the components of the latitude should us separated frotii
the others by one space.
Example: N 34 32 10
This information must be supplied b>.< the user »t present.
Enter latitude in degrees* minutes* end second I N 28 59 10
The longitude is entered in degrees* irunutfs* and seconds.
Each of the components of th«? longitude should be separated from
the others by one spacet
Example: U 7 A ^i4 32
Thin information must he supp]je>"i bv; the user at present.
Enter longitude in degrees* minutes* an
-------
INDEX STATION NAME LAT / LOH PER TON OF SlABJl. 11Y !HC. f
NUMBER dt?£l nun -ies mm RECORD CLASSES
0065 GALVESTON/BCHQLES TX N 29 16 / U 9", 'J2 1956-1960 6 61,5
1410 HOUSTON/ELL fNH) UN IX i
-------
Enter the vent radiur. for PROCESS emissions in (m)J ,026
The vent 3ss temperature defines the disch»rSe temperature in
decrees Kelvin of th* emissions through 3 vent. This information
must be supplied by the- user at present,
Enter the PROCESS vent fiss t&mp in degrees (K)! 311
The ejection velocity defines the discharge ejection velocity
of the emission-; in meters per second (m/s). This infonsation
must be supplied bn the user at present,
Enter the ejection velorily for PROCESS emissions jn (m/s)» 1,524
The emission rete define* the source strength of tht? einitsi ons
in arsms per second (rf/s). This information must be supplied by
the user si present.
Enter the PROCESS emission r,;te in (^/s)J 2,755
The name of the pollutant may be UP to ten characters long.
It should he selected so thrH it identifies the chemical uninueJ.y,
Example I F'hN 81-XXX
This information inu-;t be supplied by the user at present.
Enter the name of the pollutant! l»lfl-TCE
Press RETURN to continue!
180
-------
The rollutant state- idt-ntifiei is GAS if the poJluts-nt is
aa^eou-ij or PftKTtCIE if the F-oLlut^nt is 3 ^articulate . This
information must be supplied by tlif user at present*
Enter the pollutant -^tate* GAS
The molecular weight of the 3as must be supplned bH tht> u?.-t-:r
at
Enter the molecular weight. 133.4
atmospheric: half life of the pollutant is entered in sec-
onds. This information muvt be supplied by the u%er at present.
Please use the format shown in the example?;? where *L* precedes
the exponent in powers uf ten.
Examples: 1.557E8
Enter the half life in (*>, 1.577E8
Control commands;
BACK will return the user to the previous prompt.
CLEAR will return the user to the Operation prompt,
EXIT will return the user to VAX/VMS.
HELP will di-ipi.3'4 the appropriate HELP message.
GO will besin proressj n<3 of the user's fully
AUTOHELP i' 11 cause the HELP messed to be
Pref,f RETURN to roiitinue".
181
-------
Site A? 1»1»1 - Trichlornethane
PASUUILL STABILITIES NOT U8ED--ST ABIl.niES FOUND IN SUBROUTINE SIGMA
BRIGGS DISPERSION VAUJhS
NUMBER UF WIND SPEEDS- 6
NUMBER Of WIND UIRECTIONS- 16
NUMBER OF STABILIT1ES^- 6
STABILITIFS USED--- 1. 2 3 4 5 6
SIGMAX(M) FOR EACH STABILITY 3N THE TAF-LE
STABILITY SIGMAX
1 3200,
2 1600.
3 800,
4 500,
5 200,
6 100,
Press RETURN tc continue',
183
-------
DISTANCED) 01- THE 40 CONCENTRATION POINTS ]M FACH Uh THh 1* UIN)i D
ID
NO,
1
5
9
13
17
21
25
29
33
37
DiSIANUK
1250,
2250,
3-! 50,
6250,
11 ?.':, 0,
17500,
31250,
III NO.
o
6
JO
14
18
22
26
30
34
38
10
250,
1500,
2500,
3500,
4500,
7500.
12500.
20000,
37500.
MU,
3
7
11
15
19
23
27
31
35
39
D r. STANCE:
375,
875.
1750.
3750.
47:jO,
8750,
1.3/50,
22500,
43750,
[Li
N)i D
NO,
4
S
12
1.6
20
24
28
32
36
4-v
i.Hf-CT.HlNh
DISTANCE
500,
1000,
2000,
>000,
4000,
50oo,
10000,
1.5000,
25000,
50000,
LATITUDE AND LONGITUDE OF POINT SOURCES
NAHfc LATITUDE LONG) fLDJE
DKGKEt.S MINUTES SfCONDS DEGREFS H/NUTHS SECONDS
Site A 28, 59, 10, 95, 24, 45.
'r&S'-, RETURN to con t inuf-
184
-------
EMISSION TYPE HEIGHT(M) PHAPPA(M) UKAPPA(M) AT(K) ST(K) RftlKH) VEL(H/S)
PROCESS 15,24 0,08 3,56 295,0 311,0 0,026 1,524
WIND SPEEDS(M/S) FOR PROCESS EMISSION HEIGHT AS A FUNC-TION OH EACH STABI1 MY
GRASS COVER 1,0
AFTERNOON MIXING
NOCTURNAL MIXING
UIMO SPKED CLASS
#
STABILITY 1
STABILITY 2
STABILITY 3
STABILITY 4
STABILITY ':,
STABILITY 6
* CENTRAL WIND
HFIGHTS
-------
Site Ai l>lil - Tnchloroethsne
POLLUTANT i 1.1.1-TCE SOURCE i Site A EMISS'UN TYPE > PROCESS
REPORTED lAMILAk UALUtS WITHIN INDIVIDUAL SECTOR StliMtNTS ! ANNUAL AVlrkAiit CONCENTRATION (UG/M3)
POPULATION (PhRSOHS)
* POPULATION EXPOSUKE (UG/YR)
I POPULATION EXPOSURE = ANNUAL AVERAGE CONCENTRATION * POPULATION * ANNUAL HKhAiHINC- RATE(22M3/DAY * ,545 UAYS/YR)
DISTANCES (KM) I 0.0- 0.5 0.5- t.O 1.0- 2.0 ,7.0- 3.0 3.0- 4.0 4,0- 5.0 5.0-10.0 10.0-15.0 1S.O-215.0 25.0-bO.O
SECTOR MID-ANGLE
N 0.0 1.380E+01 6.077E+00 2.386E+00 9.40JE-01 5.048E-01 3.181E-01 1.4S9K-01 5..56.5E-02 2.532t-02 1.005E-02
00000 1075 1939 0 11663 1838
O.OOOEtOO 0.000?tOO O.OOOE+00 O.OOOt+00 O.OOOt+00 2,744tt04 2.J/2E + 06 O.OOOF+00 2.371t+04 1.483t+05
NNE 22.5 5.046E+00 2..580E+00 9.900E-01 3.938E-01 2.101E-01 1..U6E-01 5.9/3F-02 2.159E-02 1.012E-02 3.979E-03
0000 1S74 1061 2654 0 0 11570
O.OOOE + 00 O.OOOE+00 O.OOOE+00 O.OOOE+00 2.65"jF+OA 1.121Et<>6 1.2/3E+06 O.OOOE+00 O.OOOE+00 3.697E+05
HE 4h.O J.45.8R+00 J.221E4-00 1.103E+00 4.444t-01 2.307E-01 1.406t-01 6.086F.-02 2.0J3F-02 9.1/8E-03 J.448t-03
0 0 0 0 605 0 0 0 16 242
O.OOOE+00 O.OOOttOO O.OOOE+00 O.OOOttOO 1.1V>1F.+06 O.OOOttOO O.OOOE+00 O.OOOfctOO 1.179E + 05 6.699Et03
ENE 67.5 1.465E+00 9.800E-01 5.049E-01 2.0?9E-01 1.042E-01 6.V86E-02 2.6/4E-02 8.654E-03 3.828f-0.i 1.407E-03
0000000 1024 143 401
O.OOOE+00 O.OOOttOO O.OOOEtOO O.OOOttOO O.OOOE+00 O.OOOftOO O.OOOEtOO 7.114tt04 4.JV6E+03 4.332Et03
E 90.0 2.289F.+00 1.148E+00 5.38SE-01 2.147E-01 1.115E-01 6.801E-02 2.951E-02 9.V11E.-03 4.494E-0.? 1.702E-03
000000 214 000
O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOF+00 O.OOOE+00 5.070E+04 O.OOOEtOO O.OOOt+00 O.OOOEtOO
ESE 11?.5 ?.283E+00 1.0S6E+00 4.747E-01 1.8V8t-01 9.V70E-02 6.149t-02 2.719E-02 9.4.W-03 4.328E-03 1.4J7E-03
0 0 0 0 79B 924 3082 523 0 0
O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOftOO 6.388Et05 4,543t+05 6.729Et05 4.002f+04 O.OOOEtOO O.OOOEtOO
SE 135.0 3.279E+00 1.578t.tOO 6.708E-01 2.685E-01 1.433t-01 8.VA6E-02 4.0S9F-02 1.4S9E-02 6.805E-03 2.6i'OE-03
0 0 0 224 0 358 6821 000
O.OOOE+00 O.OOOttOO O.OOOE+00 4.830Ft05 O.OOOE+00 2.577ftOS 2.223E+06 O.OOOE+00 O.OOOE+00 O.OOOttOO
SSE 157,5 2.60/E+OO 1.061E+00 4.002E-01 1.587E-01 8.640E-02 5.S15E-02 2.579E-02 9./61E-03 4.633E-03 1.805E-03
0000000000
O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOF.+OO O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOE+00 O.OOOE+00
S 180.0 3.067E+00 3.152£tOO 1.219E+00 4.81U-01 2.584E-01 1.6UU-01 7.491E-02 2.763E-02 1.291E-02 4.934E-03
0000000000
O.OOOE+00 O.OOOttOO O.OOOE + 00 O.OOOttOO O.OOOE + 00 O.OOOttOO O.OOOEtOO O.OOOt + 00 O.OOOF. + OO O.OOOE + 00
SSW 202.5 5.4B8E+00 2.178E+00 8.282E-01 3.280E-01 1.777E-01 l.li>9E-01 5.247E-02 1.96&E-02 9.235E-0.5 3.L35E-03
0000000000
O.OOOE+00 O.OOOE+00 0.00<>E+00 O.OOOF+00 O.OOOEtOO O.OOOF+00 O.OOOEtOO O.OOOE+00 O.OOOE+00 O.OOOEtOO
SU 2J-J.O ^.A04E + 00 2.9SAt + 00 1.18AE + 00 4.i88f-01 2.M2E-01 1.381t-01 7 .2 J"9E-02 2.640t-02 1.229E-02 4.700E-03
0 0 0 0 0 0 530 0 0 439
O.OOOEtOO O.OOOt + 00 O.OOOE + 00 O.OOOP-+00 O.OOOE + 00 0,000(-+00 3.0'AEt05 O.OOOttOO O.OOOE + 00 1.4'57t + 04
WSW 247.5 4.554E+00 2.031E+00 7.959F-OI 3.1A5t-01 1.709E-01 1.0H3F-01 S.001E-0? 1.8S1E-02 8.644F-03 3.2H1E-03
0 0 0 0 0 4! 1 857 ^0 306 6°2
O.OOOE + 00 O.OOOEtOO O.OOOEtOO 0.0<>OFtOO O.OOOE + 00 ~,i. ^j 7"-jt+.)5 3.44"2i£t6"5 0.0<)OttOO"j i"l?"4Et04' 1 .~823t t04"
U 270.0 8.407EtOO 3.*80E + 00 1,48/EtoO 5.S88F-01 j.HlE-01 l.96Vt-01 S.Vj.^E-02 3 .;i!Vt-0.? 1.4y'JK-o;' 5.646E-03
000 558 000 1413 489 4043
O.OOOE+00 O.OOOE+00 O.OOOE+00 2.638E+04 O.OOOF+00 O.OOOE+00 O.OOOEtOC j.t>A4F+05 8.257E+04 1.833E+05
UNU 292,5 1.036E + 01 4.505E + 00 1.681E + 00 4.612t-01 3.58SE-01 l'.:>82E-ol 1.063E-01 3.V38E-02 I.H83E-0? 7.342E-03
00000000 35?i 6936
O.OOOE + 00 O.OOOt + 00 O.OOOK-tOO 0.0o0f+»0 O.OOOttOO 0.000^00 j.OOOttOO O.i-V0t+O0 5.5:'9E + 05 4.089tt05
NW 315.0 1.263E1-01 5,419fc+00 ?.07bF + GO 3.1SJE-Q1 4.422F-Ot 2.H')4L.-.-; i.?*8f-o; .i.J'J"E-0; ; ./'tt-Or 8.87'E-03
000030 l;°-> 3 171 4'iO
O.OOOEtOO O.OOOhtOO O.OOOEtOC O.OOOf-^^0 0.0')0t +'jO 'j.ooOH-oo 1.6o4tru6 D. C')0f-00 3.1.4E + 04 3.53Att05
k-NU 337,5 *.i;9E + OC 3.308ttOO 1.410Ei'J0 f,b4c.t-01 3.01?fc-01 l.J'.?L.-"l '-1 .n".'F-02 3.J ---"2 l.s tr: -i.fj;t-f)J 1 ,.':! Ot-05 2.1-'f-r35
p>-es5 RETJSN to continue!
187
-------
50.0 KM RADIUS POPULATION EXPOSt-D AND EXPOSURE OF l,l»l-TCt
RESULTING FROM PROCESS MISSIONS AT Site A
CUMULATIVE * CUMULATIVE
CONCENTRATION LEVEL POPULATION EXPOSED POPULATION EXPOSURE
CUC/H3) (PERSONS) (UG/YR)
1.X80E+01 0 O.OQOh.100
3.000EI01 0 O.OOOh+OO
5.000E+00 0 O.QOOE+00
2.500E + 00 0 0,00(>F.K>0
l.OOOE-f-00 0 O.OOOEfOO
5.000E-01 553 2.638E+06
2.500E-01 1857 5.867E-F06
l.OOOE-01 11422 1.874F.-I-G7
5.000E-02 26944 2.883E+07
2.500E-0? 51794 2
l.OOOE-02 :iB975 J
5.000E-03 80909 3.718EI07
2.500E-03 93995 .5.760EI07
1.407E-03 94396
* CUMULATIVE POPULATION EXPOSURE WAS ARRIVED AT BY ACCUMULATING
POPULATION EXPOSURES ASSOCIATE!" W11H INHIVIDUAL StCTUR SFliMENTS,
Press RETURN to continue:
188
-------
Operations include: FILL MANAGhMt.NT (F'H)
GRAPHICS (G)
MODELING (M>
STATISTICS (S)
TABULAR OUTPUT (TO)
ESTIMATION (E>
Enter an operation} EXIT
Type BACK if you want to save temporary dstasets}
189
-------
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192
-------
NOTE:
Problem 2:
Solution:
The following problem and solution 1s presented to
demonstrate a possible approach for enumerating populations
around point sources that are too numerous to deal with
Individually. Approaches, however, will have to be
developed on a case-by-case basis for exposure assessments
depending upon the availability of locatlonal Information
and within the time and manpower constraints of the effort.
A chemical substance 1s known to be released from 100 point
sources located 1n metropolitan areas throughout the United
States. Using generic release characteristics, the
following range of atmospheric concentrations has been
estimated, via ATM, for radial rings within a 10 kilometer
radius of the prototype source:
Radial Distance (km)
Concentration (ug/m3)
1
0.0
0.5
0
2.0
3.0
4.0
5.0
0.5
1.0
2.0
3.0
4.0
5.0
10.0
1.4 x 10° -
2.0 x 10-"1 -
4.6 x 10~2 -
1 .5 x 10~2 -
7.3 x 10-3 -
4.4 x 10-3 -
1 .9 x 10~3 -
7.0 x 10°
1.2 x 10°
2.4 x 10-"1
6.9 x 10~2
3.3 x TO'2
2.0 x 10~2
8.7 x 10~3
Estimate the population exposed at each concentration.
Since no other information on the location of the 100
sources is available, 1t 1s assumed they are located in
metropolitan areas (SMSAs). To estimate the size of the
population within each ring, the average population density
of metropolitan areas in the U.S., 120 persons/km2
(Table 8), was multiplied by the areas of each ring.
Following are the results:
Radial Distance (km)
0.0 -
0.5 -
0.5
3.0
4.0
5.0 - 10.0
Prototype Ring Population
96
288
1136
1888
2624
3392
28,320
193
-------
Since there are 100 sources nationwide and the prototype 1s
assumed to be representative of all sources, the exposed
population 1n each ring times 100 1s equal to the total
exposed population at each concentration range as follows:
Radial Distance (km) Concentration Range (ug/m3) Exposed Population
9,600
28,800
113,600
188,800
262,400
339,200
2,832,000
1 X 1s released as a result of
vehicular emissions. Enumerate the population 1n the San Antonio
SMSA that 1s exposed to different concentrations of chemical X given
the following Information: modeling of area source concentrations
using meteorological factors characteristic of the San Antonio area
determines that the atmospheric concentration of chemical X 1n urban
areas 1s Y mg/m3 and Z mg/m3 1n rural areas.
Solution: This problem was solved via application of Method 2-4 as follows:
The Bureau of Census publication, Number of Inhabitants
(PC 80-1-A45), for 1980 provides the following data for the San
Antonio SMSA. (Bureau of Census 1983a, Table 12, p. 52):
0
0
1
2
3
4
5
Probl
.0
.5
.0
.0
.0
.0
.0
em
- 0
- 1
- 2
- 3
- 4
- 5
- 10
3:
.5
.0
.0
.0
.0
.0
.0
Area
1.
2.
4.
1 .
7.
4.
1.
Source (
4
0
6
5
3
4
9
X
X
X
X
X
X
X
Site
10°
10-1
10-2
10-2
10-3
io-3
io-3
- 7
- 1
- 2
- 6
- 3
- 2
- 8
.0
.2
.4
.9
.3
.0
.7
X
X
X
X
X
X
X
10°
100
10-1
10-2
10-2
10-2
io-3
Specific) - Chem
Problem 4:
urban portion
rural portion:
population 985,149
population 86,805
Therefore, populations are exposed to different concentrations of
chemical X as follows:
y mg/m3 = 985,149
z mg/m3 = 86,805
Prototype Area Source - Chemical X 1s released as a result
of the combustion of fossil fuels 1n home and Industrial
heating systems. The atmospheric concentration 1s directly
related to population density and geographic location.
Enumerate the population exposed to the different
concentrations of chemical X according to the following
modeling results;
194
-------
Northeast
South
North Central
West
Concentration (mg/m3)
Urbanized Area Urban Area Rural Area
100
20
80
50
60
10
40
40
20
1
10
5
Solution: This problem was solved via application of Method 2-4 as
follows:
Table 10 of the methods report provides 1980 population data
for the U.S. based on census geographic regions. Data for
the regions of Interest are as follows:
Population (x IP3)
Urbanized Other Urban Rural
Northeast
South
North Central
West
35,520
39,639
32,822
31,130
3,484
10,743
8,644
5,083
10,232
24,967
17,388
6,953
These various population figures are readily matched up with
the corresponding concentrations to yield the following
results:
Concentration
100
80
60
50
40
20
10
5
1
Population (x 1Q3)
35,520
32,822
3,484
31,130
13,727
49,871
28,131
6,953
24,967
(8,644 + 5,083)
(39,639 + 10,232)
(10,743 + 17,388)
195
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Problem 5: Line Source Example - Chemical X 1s Imported to Baltimore,
MO, and 1s distributed by railroad tank car to manufacturing
sites 1n Richmond, VA; Pittsburgh, PA; Louisville, KY; and
Newark, NJ. Leakage of chemical X along the transportation
corridors results 1n an Inhalation exposure to residents 1n
the vicinity. Modeling of atmospheric concentrations based
on the emission of X estimates the concentration to be z
mg/m3 within 0.5 mile of the rail lines. Enumerate the
population exposed. Characterize the population by age and
sex.
Solution: This problem was solved via application of Method 2-5 as
follows:
Road atlases were consulted to determine distances between
cities and the Identity of central cities of SMSAs located
on or very near straight lines drawn from Baltimore to each
terminal dty. Population density of each SMSA was
calculated from 1980 data 1n the Bureau of Census
publication, Number of Inhabitants (Individual states).
This reference provided total populations for each SMSA as
well as the area (square miles) of each Individual county.
County areas were summed within an SMSA to determine total
SMSA area. The number of people per square mile was then
calculated. This Information will be obtained much faster
following publication of the U.S. Summary for Number of
Inhabitants (mid 1983). The U.S. summary will 11st each
SMSA along with population, land area, and population
density.
Table 30 summarizes data and results for each route. Note
that the Baltimore to Newark route presented problems that
could not be solved by conventional use of the methodology.
There are six SMSAs along the Baltimore-Newark corridor,
Including the end points. Each of these SMSAs borders
directly on the next with no nonmetropolltan territory 1n
between. Because of this, and because the subject SMSAs
have odd shapes, the sum of all rad11 along the route
calculated according to the previously discussed methods
exceeds the actual distance between the terminal cities.
Therefore, actual distances across SMSAs (straight lines
through the central cities) were determined from road maps.
The remaining three routes were analyzed by the conventional
methods.
196
-------
Table 30. Line Source Corridor Distances, Population Density, and
Population Exposed in Problem 5
SMSA Distance a Densityb Number of persons (x 103)
(miles) (persons/m±2)
Baltimore to Newark (total distance 168 mi.)
Baltimore 34
Wilmington 40
Philadelphia 46
Trenton 1 1
New Brunswick 15
Newark 22
Baltimore to Pittsburgh (total
Baltimore 27
Hagerstown 24
Pi ttsburgh 31
non-SMSA
Baltimore to
Hagerstown 25
Hagerstown to
Pittsburgh 111
Baltimore to Louisville (total
Baltimore 27
Louisville 21
non-SHSA
Baltimore to
Louisville 550
968
479
1336
1357
1886
1954
distance 218
968
248
741
38
69
distance 598
968
646
38
1
32.9
19.2
61.5
14.9
28.3
43.0
mi .)
26.1
6.0
23.0
1.0
7.7
mi .)
26.1
13.6
20.9
Baltimore to Richmond (total distance 144 mi.)
Baltimore 19°
Washington, D.C. 49
Richmond 26
non-SHSA
Washington, D.C
to Richmond 50
TOTAL Population Exposed
968
1090
296
38
18.4
53.4
7.7
1.9
405.6 x 103
aDistance in miles is equivalent to areas in square miles
because width of corridor is 1 mile.
^Source: Number of Inhabitants.
cAdjusted to reflect fact that Baltimore and Washington, D.C., SHSAs
are adjacent (compare treatment of Balitmore-Newark route in text).
197
-------
Except for the Baltimore-Newark route, each SMSA 1s
considered to be a circle. In Table 30, "distance" 1s
equivalent to the radius of this circle 1n the case of a
terminal SMSA, and equivalent to the diameter 1n the case of
an Intermediate SMSA. Radius or diameter was calculated
from the area of the SMSA by the familiar formula,
A = irr^. Nonmetropolltan mileage was calculated as the
difference between total length of route and the sum of all
SMSA rad11. The density of population 1n nonmetropolltan
areas 1s taken for the appropriate region from Table 8 of
the text.
The calculated total exposed population of 405.6 x 103 was
characterized by age and sex. Proportions of each age and
sex group were calculated from data 1n Table 12 of the
text. Results are summarized 1n Table 31.
193
-------
Table
31. Characterization of Exposed Population for Line Source Problem 5
Age Group
5
5 -
10 -
15 -
20 -
25 -
35 -
45 -
55 -
65 -
75 -
85+
9
14
19
24
34
44
54
64
74
84
Hale population (x 103)
15.0
15.3
16.7
19.3
19.1
32.9
22.5
19.7
18.2
12.1
5.1
1.2
Female population (x 10^)
14.2
14.6
16.0
18.6
19.1
33.5
23.4
21.1
20.7
15.8
8.7
2.8
(Numbers may not add to total due to rounding)
199
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APPENDIX A-2
POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES IN THE OCCUPATIONAL ENVIRONMENT
Problem 1: Substance Y 1s a mineral contaminant of phosphate rock used
1n the preparation of fertilizers. How many persons are
occupatlonally exposed to Y as a result of production,
sales, and use of phosphate rocks and fertilizers?
Solution: This problem was solved via application of Method 3-1 and
3-2 as follows:
Step 1 - List of Establishments (from SIC manual)
• SIC 0711 - Soil Preparation Services (use)
• SIC 1475 - Phosphate Rock Mining (production)
• SIC 2874 - Phosphatlc Fertilizers (production)
• SIC 5191 - Farm Supplies/Wholesale Distribution
(Phosphate Rock - ground) (sales)
• SIC 5261 - Retail Nurseries, Lawn and Garden
Supply Stores (fertilizers) (sales)
Step 2 - Determine Sources
(Economic Censuses)
Step 3 - Choose Data
(see Table 32)
Step 4 - Sum and qualification of data
1)
2)
3)
4)
5).
8,
5,
10,
35,
578
900
TOO
772
36.360
96,710 total exposed
SIC 0711 - 1s the only 4-d1g1t code in the 071 class;
populations reported for 071 and 0711 are equivalent.
However, handling phosphatlc fertilizers would only
account for part of the activity described for this
service industry.
200
-------
Table 32. Employment by SIC Code for Producers
and Users of Phosphate Fertilizers
SIC Found
Number of employees
Census cited
071
1475
2874
5191
526
8,578 (paid employees) 1978 Agriculture
5,900 (year average for 1977 Mineral Industries
production, development,
and exploration workers
for all types of operations)
10,100 (production workers) 1977 Manufactures
35,772 (paid employees) 1977 Wholesale Trade
36,360 (paid employees) 1977 Retail Trade
201
-------
2. SIC 1475 - the number reported would be representative of
those actually exposed.
3. SIC 2874 - the number reported would again be
representative of works actually exposed.
4. SIC 5191 - the number reported reflects a certain over-
estimation of those employees actually exposed to products
containing contaminated phosphate rocks.
5. SIC 526 - similar to 0711, 5261 1s the only 4-d1g1t code
1n the 526 class; nonetheless, the reported number of
paid employees 1s a gross overestimate of those actually
exposed. (Exposure would be limited to accidental
release of fertilizer from Its packaging.)
Problem 2: Chemical Z 1s a reagent used 1n typing blood. (Typing 1s
done 1n laboratories and 1s a common lab experiment 1n high
school biology classes.) How many persons are exposed to
chemical Z? Characterize that population by age and sex.
Solution: This problem was solved via application of Method 3-3 as
follows:
Assumptions -(1) High school biology students are exposed 1n
the classroom as Is the teacher.
The exposed population will Include:
• Medical/clinical technicians running tests.
• Biology teachers using this curriculum.
• Biology students of the appropriate grade.
Option, 2 - Contact associations/appropriate representative
organi zations.
• National Association of Biology Teachers, Inc.
Reston, Virginia 471-1134
Dr. Moyer: This test 1s done very Infrequently because
of resulting social problems 1t has posed
with students and their families. Where 1t 1s
done, this test 1s part of the 10th grade biology
curriculum.
202
-------
• National Science Teachers Association
Washington, D.C. 328-5800
D1na Weiss: From the U.S. Registry of Junior and Senior
High School Science and Math Teaching
Personnel: most current estimate of biology
teachers for grades 9 through 12 1s 34,412 (at
least 75% of national total).
• National Center of Educational Statistics
(U.S. Department of Education), Washington, O.C. 436-7900
- Survey of national student enrollment for 1972 - 1973
school year 1n public schools, Biology I (10th grade)
Indicates 2,049,000 students.
- Statistics show that 1n 1972 the ratio of public to
private high school students (grades 9-12) was about 10
to 1 (13,913,000/1,300,000).
- Statistics also show that since 1976, high school student
enrollment 1n general has declined. 1982 survey results
of public and private high school total enrollment shows
about one million fewer students.
Option 3 - Occupation by Industry, 1970
• Health Technologists and Technicians employed at
hospitals and with other health services.
Male Female
16 to 24 = 12,911 + 2,050 16 to 24 = 42,824 t 12,379
25 to 44 = 25,545 * 7,169 25 to 44 = 55,150 + 23,195
45 to 64 = 7,917 + 4,720 45 to 64 = 22,616 * 8,937
65 + = 365 + 404 65 + = 1,413 + 694
Data Summation
(1) • 10th grade biology students best fit Into the 15 to 19
year age category. From 1980 Census data (Table 12), the
ratio of 15 to 19 year old men to women = 10.751.544 = 1.03,
10,410,123
or 0.508:0.492.
203
-------
• In the 1972 - 1973 school year there were 2,049,000 Biology I
students 1n public high school; and an estimated 204,900 Biology
I students 1n private high school; totaling 2,253,900 Biology I
students 1n 1972 - 1973. If general enrollment has decreased by
about 10% since 1972, the current total would equal 2,028,510
high school students.
• Male: 16 to 24 = 1,030,483 Female: 16 to 24 = 998,027.
(11) • 34,412 currently registered high school biology teachers who
could teach using the blood type test.
• Age and sex characterization for this special subpopulatlon
1s derived from the generic percentages of total employed
in the "Professional, Technical, and Kindred" occupation
classes (text Table 15):
Male Female
16 to 24 = 7.2% 16 to 24 = 7.5%
25 to 44 = 33.5% 25 to 44 = 18.3%
45 to 64 = 16.9% 45 to 64 = 12.7%
65 + = 2.0% 65 + =1.4%
-60% -40%
The total percent ratio of male to female biology teachers (60
to 40) from the professional, technical, and kindred breakdown
supplied by the 1970 occupational census (Table 15), agrees with
the estimate of male to female biology teachers supplied by the
National Science Teachers Association's registry.
(111) • Data for Health Technologist and Technicians employed 1n 1970
have been reported; the distribution is assumed to remain the
same.
(iv) Age Class Male Female
• 16-24 1.047.922 1.055.811
Students (1,030,483) (998,027)
Teachers ( 2,478) ( 2,581)
Technicians & ( 14,961) ( 55,203)
technologists
204
-------
• 25-44 44.242
Teachers (11,528)
Technicians & (32,714)
technologists
• 45-64 18.453
Teachers ( 5,816)
Technicians & (12,637)
technologists
• 65* 1.457
Teachers ( 688)
Technicians & ( 769)
technologists
84.642
( 6,297)
(78,345)
35.923
( 4,370)
(31,553)
2.589
( 482)
(2.107)
1,112,074
TOTAL = 2,291,339
1,178,965
Problem 3: Eight million Ibs/yr of hexamethylenetetramlne are produced at
Chemical Synthesizers, Sioux Falls, South Dakota. They convert
1 million Ibs/yr of that compound to another derivative for
sale. How many persons are exposed to the derivative? How
many production workers are Involved? Characterize by age
and sex.
Solution: This problem was solved via application of Methods 3-4 and 3-5
as follows:
Step 1 - Option 2 - Direct enumeration using 1981 South Dakota State
Industrial Directory (SIC 2899, Chemical Preparations)
Employment statistics
Office: male = 25 female
Plant: male = 80 female
Step 2 - (From text, subsection 3.3.3)
= 25
= 46 (Total Plant = 126)
PVt Et
1 x 1p6ibs/yr
8 x 10&lbs/yr
126 workers
16 - Eaworkers
205
-------
Using Method 3-5, characterize the population
Option 1 - (See Table 15 of text)
• Ages and sexes are derived from the generic percentages of
total employed (16) 1n the "Operatives, Except Transport"
occupation class:
Male
16 - 24 (13.8%)
25 - 44 (26.1%)
45 - 64 (20.4%)
65+ ( 1.4%)
2
4
3
J.
10
Female
16 - 24 ( 6.2%) = 1
25 - 44 (16.1%) = 2
45 - 64 (15.0%) = 2
65+ ( 1.1%) = 0
Option 2 - State Industrial Directory Indicates that there
are 80 men and 46 women employed at the plant. The
male:female ratio of 80:46, or 1.74 men for each woman, may
be used to derive the population characterization by sex. Of
the 16 employees exposed, 10 are men and 6 are women. The
age distribution above still applies.
Problem 4: Chemical W, a volatile organic compound, 1s used 1n the
formulation of specialty plastic products. Approximately
200 plants nationwide use chemical W. Because of Its high
volatility, production workers and non-production workers
are exposed to chemical W vapor. OSHA Inspection of 5
plants detected chemical W 1n all areas with the highest
concentrations occurring 1n the production areas, particularly
around melt pot and mold pouring points. Following are the
site Inspection data for the five plants:
Plant 1 2 3 4 5
Plant Consumption of W (Ibs/yr) 100 10,000
Total number employees 15 70
Production employees 5 20
-Melters and Molders 2 6
50
9
4
2
1,500
40
10
6
500
125
50
4
Estimate the total number of (1) non-production employees,
(2) production employees, and (3) melters and molders exposed
to chemical W nationwide. What are the shortcomings 1n using
the site Inspection data?
206
-------
Solution: This problem was solved via application of Method 3-4 as
follows:
Option 2 - Extrapolation from sample data.
Step 1 - (Given)
2_ - • Average number of non-production workers: 34
• Average number of production workers: 18
• Average number of melters and molders: 4
- (x200 plants)
• Non-production workers = 6,800
• Production workers = 3,600
• Melters and Molders 800
11,200 National Total
Comments: Using actual field data that 1s relevant to the
circumstances being assessed 1s of course the most
defensible approach. However, It Is difficult to qualify
the representativeness of the sample group, I.e., are these
plant data representative of all the plants 1n the field,
and 1s this a large enough sample group?
207
-------
APPENDIX A-3
POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA THE INGESTION OF FOOD
Problem 1: Lettuce harvested for sale from the State of California has
been treated with a chemical substance to reduce the
susceptibility to attack by an Insect Indigenous to this
geographic area. Enumerate the population 1n the United
States that may be exposed to this chemical substance as a
result of consuming lettuce harvested for sale from
California.
Solution: This problem was solved by the application of Method 4-2 as
follows:
- Determine the percentage of users of lettuce. The best
available source of Information regarding the percentage of
users of lettuce 1s the 1977-78 household food consumption
survey (USDA 1982). This value 1s reported to be 69.7
percent of the households surveyed.
Step 2 - Calculate the consuming population or the upper range of the
exposed population: Assuming that the household survey 1s
representative of the consumption patterns of the total U.S.
population, the percentage determined 1n Step 1 1s
multiplied by the total U.S. population 1n 1980 of 226.5
million.
.697 x 226.5 million = 157.9 million
Step 3 - Determine the percentage of the U.S. total lettuce harvested
from California. According to the 1974 Census of
Agriculture (Bureau of the Census 1978), this value 1s 72.3
percent.
Step 4 - Calculate the lower limit of the exposed population.
Multiply the percentage obtained 1n Step 3 by the value
calculated for the consuming population from Step 2:
208
-------
.723 x 157.9 million = 114.2 million
The actual exposed population, therefore, 1s probably
between 114.2 million and 157.9 million people.
Problem 2: Irish potatoes harvested for sale from Penobscot County,
Maine, have been treated with a chemical substance to reduce
their susceptibility to blight. Enumerate the population of
the United States that may be exposed to this chemical
substance as a result of consuming potatoes harvested for
sale from Penobscot County, Maine.
Solution: This problem was also solved via the application of Method
4-2 as follows:
Step 1 - Determine the percentage of users of Irish potatoes. The
best available sources of Information regarding the
percentage of users of Irish (white) potatoes 1s the 1977-78
household consumption survey (USDA 1982). This value 1s
reported to be 72.8 percent of the households surveyed.
Step 2 - Calculate the consuming population or upper range of the
exposed population. The percentage obtained 1n Step 1 1s
multiplied by the total U.S. population In 1980 of 226.5
million.
.728 x 226.5 million = 164.9 million
Step 3 - Determine the percentage of the U.S. total represented by
Irish potatoes harvested for sale from Penobscot County.
Maine. According to the 1978 Census of Agriculture (Bureau
of the Census 1982a), the quantity of Irish potatoes
harvested for sale 1n the United States 1n 1978 (the most
recent year for which data are available) 1s 314,929,746
hundredweight; the quantity harvested for sale 1n Penobscot
County, Maine, 1s 1,122,414 hundredweight. The percent of
the U.S. total of Irish potatoes harvested for sale 1n
Penobscot County, Maine 1s:
1.122.414 x 100 = .36 percent
314,929,746
209
-------
Step 4 - Calculate the lower range of the exposed population.
Multiply the percentage obtained 1n Step 3 by the value
calculated for the consuming population from Step 2:
.0036 x 164.9 million = 593,600
The population exposed to the chemical substance, therefore,
1s between 593,600 people and 164.9 million people.
Problem 3: Yogurt produced 1n the United States 1s often packaged 1n
plastic containers possibly containing a residual monomer
that may leach from the packaging material Into the food.
Enumerate the U.S. population possibly exposed to this
residual monomer as a result of consuming yogurt.
Solution: This problem was solved by the application of Method 4-3 as
follows:
Step 1 - Determine the percentage of users of yogurt. The best
available source of Information regarding the percentage of
users of yogurt 1s Food Consumption: Households 1n the
United States. Spring 1977. (USDA 1982). This value 1s
reported to be 12.5 percent of the households surveyed.
Calculate the consuming population. The percentage
determined 1n Step 1 1s multiplied by the total U.S.
resident population 1n 1980 of 226.5 million:
.125 x 226.5 million = 28.3 million
The estimate of 28.3 million persons 1s the upper limit of
the range of the potentially exposed population. To
determine the lower limit of the exposed population, the
percentage of yogurt packaged 1n plastic containers would
have to be known. This Information may be obtained by
contacting the trade association that most closely
represents packers of foods or dairy products.
210
-------
Problem 4: A brand name beer 1s manufactured from spring water known to
be contaminated with a chemical substance. Enumerate the
U.S. population exposed to this chemical substance as a
result of drinking this brand of beer.
Solution:
Step 1
This problem was solved via the application of Method 4-4 as
follows:
Determine the number of users of the brand of beer. The
number of users of this beer 1s reported by Simmons Market
Research Bureau, Inc. (1977) to be 10,735,000 adults.
Step 2 - Calculate the exposed population. No adjustment Is
necessary 1f one assumes that only adults consume beer,
since Simmons' data are representative of U.S. residents
over the age of 18.
Problem 5: A certain brand of margarine 1s reported to be contaminated
by a solvent used 1n cleaning process equipment. Enumerate
the total population exposed to the solvent as a result of
eating this brand of margarine.
Solution: This problem was also solved via the application of Method
4-4. It 1s based on the use of SMRB data which are
currently not available. Data values are assumed according
to the SMRB data format 1n order to demonstrate the method.
SMRB data will be available to personnel of EPA-OTS and
their contractors 1n the near future.
Step 1 - Determine the number of buyers. Simmons may report that
18,000,000 female homemakers buy this brand of margarine.
Calculate the exposed population. The sizes of the
18,000,000 households may be distributed as follows:
1 person household
2 person household
3-4 person household
5 or more person household
18,000,000
(total buyers)
2,000,000 x 1
3,000,000 x 2
8,000,000 x 4
5.000.000 x 6
70,000,000
(total consumers)
2,000,000
6,000,000
32,000,000
30.000.000
211
-------
Simmons' usage tables (as discussed 1n Section 5.0 of this
report) present data on household size.
Problem 6: The Kanawha River 1n West Virginia has been contaminated by
a chemical substance from an Industrial effluent. Enumerate
the population exposed as a result of consuming fish caught
on a noncommercial basis.
Solution: This problem was solved via application of Method 4-5 as
follows:
According to the 1975 West Virginia Fishing Survey, the
number of fishermen fishing on the Kanawha River 1n 1975,
the most recent year for which statistics are available, 1s
9,400. Assuming each fisherman catches and consumes fish,
this number represents a lower limit for the actual exposed
population. If one assumes that each fisherman represents a
consuming household and that there are 2.78 persons per
household (Bureau of the Census 1982b), then a rough
approximation of the upper limit for the exposed population
1s 2.78 x 9,400 = 26,132.
Problem 7: A chemical substance 1s detected 1n five percent of the
processed whole milk samples analyzed. Enumerate the
population potentially exposed to the chemical substance.
Solution:
This problem was solved via application of Method 4-8 as
follows:
The monitoring data Identify the contaminated food Item as
processed whole milk.
The total consuming population can be enumerated by the data
presented In Food Consumption: Households 1n the United
States. Spring 1977. (USDA 1982). According to the data for
household use 1n a week, 65.5 percent of the household
sampled bought fluid milk. The total consuming population
1s, therefore, .655 x 226.5 million = 148.4 million.
Step 3 - The frequency of detection 1s 0.05.
212
-------
Step 4 - The lower limit of exposed population 1s
* 0.05 x 148.4 million
= 7.4 million
The population exposed to the chemical substance 1s between
7.4 million and 148.4 million people.
Problem 8: A contaminant 1n milk may result 1n significant risk to
children between the ages of 0 and 8 years old. Estimate the
exposed population for this age group.
Solution: This problem was solved via application of Method 4-2 and
Method 4-9 as follows:
Step 1- According to USOA Household Consumption Survey of 1977-78
(USDA 1982), 65.5 percent of the households surveyed consume
milk. The total milk consuming populations 1s approximated
as:
0.655 x 226.5 million . 148.4 million
Step 2- According to the USOA Individual Food Consumption Survey of
1977-78 (USDA 1980) (see Figure 18 of text) 16.98 percent of
the milk-consuming population 1s 8 years old or less. This
was calculated by aggregating the consumers of milk for each
age class less than 8 years of age and dividing by the total
milk consuming population of the sample:
Number of consumers of fluid milk 8 years old or less
= (78 x 0.609) * (264 x 0.905) + (437 x 0.856) t (469 x 0.885)
= 1,076
Number of consumers of fluid milk = 9,620 x 0.659 = 6,340
Percentage of consumers who are 8 years old or less
= 1.076 x 100 = 16.97 percent
6,340
The estimated milk consuming population 8 years old or less
1s:
0.1697 x 148.4 million = 25.2 million
213
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APPENDIX A-4
POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA USE OF CONSUMER PRODUCTS
Problem 1: Chemical X 1s a solvent used 1n all aerosol rug cleaners
currently marketed.
- How many persons are actively exposed?
- How many persons are exposed at heavy, medium, and light
usage levels?
- How many persons are passively exposed?
- Characterize each population above by age and sex
distribution.
Solution: This problem was solved via application of Method 5-2 using
1982 SMRB data and Method 5-4 as follows:
Step 1 - Rug cleaners.
Step 2 - SMRB Type tables used (aerosol).
Step 3 - Population actively exposed.
• Due to the Inherent bias of the data base, we assume that
only female homemakers are actively exposed (data for male
counterparts are not available, though men do purchase and
use rug cleaners to some extent).
• It 1s further assumed that use of this product 1s not
restricted to any age group, I.e., that any female
homemaker physically capable of applying the product
does. Purchase = use = active exposure.
13,862,000 total female homemakers purchase aerosol rug
cleaners, of which:
214
-------
1,746,000 are 18 - 24 years of age, (12.6%);
3,855,000 are 25 - 34 years of age, (27.8%);
2,351,000 are 35 - 44 years of age, (17.0%);
2,232,000 are 45 - 54 years of age, (16.1%);
2,136,000 are 55 - 64 years of age, (15.4%); and
1,543,000 are 65+ years of age, (11.1%).
Since SMRB data are not provided for heavy, medium, and
light (H, M, L) users of aerosol rug cleaners, the ratio of
H:M:L users of all rug cleaner types 1s applied. This 1s
derived from the appropriate SMRB data table for rug
cleaners (1982 data).
(1) 36,879,000 total female homemakers use all types of rug
cleaners of which:
13,063,000 are at heavy levels;
10,034,000 are at medium levels; and
13,783,000 are at light levels.
(11) H:M:L =
0.35:0.27:0.37 = 1.00
(111) Applied to the 13,862,000 total aerosol users:
4,852,000 are at heavy levels;
3,743,000 are at medium levels; and
5,129,000 are at light levels.
Population passively exposed.
Option 2
(1) Of the 13,862,000 total aerosol rug cleaner users:
1,566,000 live In single person households;
4,392,000 live 1n 2 person households;
5,878,000 live 1n 3-4 person households; and
2,026,000 live 1n 5 or more person households.
(11) 1,566,000 x 1
4,392,000 x 2
5,878,000 x 4
2.026.000 x 6
1,566,000
8,784,000
23,512,000
12.156,000
Total passively
exposed population = 46,018,000
(men and women)
215
-------
(111) Method 5-4, using generic 1980 resident population
characteristic data (text Table 12).
Ratio of males to females = 0.49:0.51,
applied to total population passively exposed =
22,548,820 males, of which:
1,711,455 are under 5 years of age (7.59%);
1,749,788 are 5 - 9 years of age (7.76%);
1,907,630 are 10 - 14 years of age (8.46%);
2,203,020 are 15 - 19 years of age (9.77%);
2,184,981 are 20 - 24 years of age (9.69%);
3,765,653 are 25 - 34 years of age (16.70%);
2,575,075 are 35 - 44 years of age (11.42%);
2,254,882 are 45 - 54 years of age (10.00%);
2,079,001 are 55 - 64 years of age (9.22%);
1,384,498 are 65 - 74 years of age (6.14%);
586,269 are 75 - 84 years of age (2.60%); and
139,803 are 85+ years of age (0.62%).
And 23,469,180 females, of which:
1,607,639 are under 5 years of age (6.85%);
1,642,843 are 5 - 9 years of age (7.00%);
1,797,739 are 10 - 14 years of age (7.66%);
2,098,145 are 15 - 19 years of age (8.94%);
2,147,430 are 20 - 24 years of age (9.15%);
3,766,803 are 25 - 34 years of age (16.05%);
2,633,242 are 35 - 44 years of age (11.22%);
2,375,081 are 45 - 54 years of age (10.12%);
2,328,143 are 55 - 64 years of age (9.92%);
1,776,617 are 65 - 74 years of age (7.57%);
978,665 are 75 - 84 years of age (4.17%); and
314,487 are 85+ years of age (1.34%).
Problem 2: A manufacturer submits a PMN for a new type of solvent to be
used 1n rug cleaners. He plans to produce and market 500,000
kg/year.
- How many persons will be exposed, both actively and
passively?
- Characterize the active and passive population by age and
sex.
216
-------
Solution: The solution of Problem 2 employs a variation of
Method 5-3. The steps outlined below do not exactly match
those presented 1n the method because the multitude of
assumptions that must be made and the lack of available
data. As was stated 1n the Introduction to this Appendix,
the method's primary function 1s to provide a framework for
population enumeration and Introduce the tools that can be
used. The solution of this problem Illustrates the
creativity and flexibility that must be applied when
utilizing the methods provided.
Actively Exposed Populations
• Gosselln's (1976) Clinical Toxicology of Commercial
Products* was used to evaluate "solvents" as formulation
components of these products. Because the term "solvent"
can be ambiguous 1f not clearly described, 1t was assumed
that the solvent subject of the PMN must (a) not be
water; (b) be present 1n formulation 1n a significant
proportion; and (c) be a volatile distillate used
primarily as a support matrix that would evaporated very
quickly Immediately following application. Analysis of
the Information found 1n Gosselln et al. (1976) produced
the following results:
Two types of "solvent" containing cleaners used predominantly for
rugs and carpets were Identified as:
(1) soap-solvent combination cleaners, that were
- liquid
- 15-45 (30%) solvent content
- 45 - 95% water content
- 0.7 - 5% ammonia content
- 0-2% solids (soaps, borax, etc.)
*Gossel1n RE, Hodge MC, Smith RP, Gleason MM. 1976. Chemical toxicology
of commercial products. 4th edition. Baltimore, MO: The Williams and
W1lk1ns Company.
217
-------
(2) absorbent type cleaners, that were
- aerosol
- 25% solvent content, primarily light petroleum
distillate
- 75% solids (as sorbants and propellant)
• Given: Solvent product = 500,000 kg/yr.
Use: solvent 1n aerosol and liquid rug cleaners
Percent
solvent
(avq)
Aerosol 25%
liquid 30%
powder
wt/un1t
cleaner (kg)1
0.609
1.340
0.5435
$/kqT
5.02
3.82
6.33
#purchasers/yr2
13,862,000
18,939,000
6,044,000
"From Table 33
2From SHRB (text, Table 23)
36% of the purchasers purchase aerosols
49% purchase liquids
16% purchase powders
• There are two alternative assumptions which could be made to
facilitate estimating the breakdown of the 500,000 kg
between aerosol and liquid:
(1) Consumers use equal amounts by weight of each type.
Therefore, 36% of the kg of rug cleaner produced 1s In aerosol
form, 49% 1s liquid (and 16% 1s powder).
(2) Consumers use equal amounts by unit of each type. Therefore,
36% of the units produced are aerosol, 49% are liquid (and 16% are
powder).
ASSUMPTION NO. 1: kg aerosol/person = kg liquid/person.
Step 1 - Determine how much of the 500,000 kg of chemical goes Into
aerosols and how much goes Into liquids.
For every 36 kg of aerosol rug cleaner purchased, 49 kg of
liquid are purchased. The aerosol contains 25% by weight of
the chemical solvent 1n question, and the liquid contains
30%.
218
-------
Table 33. Rug/Carpet Cleaning Products Market
Survey Results
Name
Aerosol Products:
Scotchgard Carpet Cleaner
Wool He Rug Cleaner
Glamorene Spray 'n Vac
Glory Rug Cleaner
(Johnson Wax)
Lestoil Rug Cleaner
(Noxell)
Carpet Magic Rug Shampoo
Bissell Foam Rug Cleaner
Average
Reported
weight2
(kilograms)
(ounces)
(24)
(24)
(19)
(19)
(24)
0.524
0.624
0.680
0.680
0.538
0.538
0.680
0.609
Averaged
retail price^
(dollars)
3.19
3.19
2.89
2.85
2.89
2.49
3.75
Retail price
per kilogram
(dollars)
6.09
5.11
4.25
4.19
5.37
4.63
5.51
5.02
Liquid Products: (fluid ounces)
Scotchgard Carpet Cleaner
Glamorene Rug Cleaner
Carpet Magic "steam"
Cleaning (solution)
Carpet Magic Rug Shampoo
(concentrate)
Bissell Wall to Wall
Rug Shampoo
Trewax Up and Out Rug
Shampoo
Average
Powder Products:
Bissell Powder Carpet
Cleaner
Airwick Plush Dry Cleaner
Average
(32)
(32)
(65.5)
(64.5)
(32)
(46)
(ounces)
(16)
0.946
0.946
1.937
1.907
0.946
1.360
1.340
0.453
0.454
0.5435
4.29
2.89
6.29
5.89
4.39
5.89
2.89
2.85
4.53
3.05
3.25
3.09
4.64
4.33
3.82
6.38
6.28
6.33
1 Performed by Versar, November 1982.
Conversion of fluid ounces to grams assumed density of water,
using the formula:
1 gram x 1000 cc
Ice 1 liter
2.957xlQ-2 liters = 29.57 g
1 fluid oz.
oz.
^Products appearing in several establishments with different prices
display an average of those prices.
219
-------
Thus:
% Total available solvent used In aerosol =
36 kg aerosol x 0.25 kg solvent
kg aerosol x 100%
36 kg aerosol x 0.25 kg solvent + 49 kg liquid x 0.30 kg solvent
kg aerosol kg liquid
= 38%
% Total available solvent used 1n liquid =
49 kg liquid x 0.30 kg solvent
kg liquid x 100%
49 kg liquid x 0.30 kg solvent + 36 kg aerosol x 0.25 kg solvent
kg liquid kg aerosol
= 62%
Thus,
190,000 kg solvent (500,000 x 38%) will be used 1n aerosols, and
310,000 kg solvent (500,000 x 62%) will be used In liquids.
Step 2 - Determine the kilograms of both aerosol and liquid products
which could be produced from available solvent.
kg aerosol product = 190.000 kg = 760,000 kg (42%)
0.25
kg liquid product = 310.000 kg -- 1,033,333 kg (58%)
0.30
This is what would be expected because 1f 36 kg of aerosol
are purchased for every 49 kg of liquid, proportionally, 42%
of the purchases would be aerosol and 58% would be liquid.
Step__3 - Determine number of persons actively exposed. Since
products are purchased on a unit basis, the kg are converted
to units:
760.000 kg = 1,248,000 units of aerosol
0.609 kg/unit
220
-------
1.033.333 kg = 771,000 units of liquid
1.34 kg/unit
If kg aerosol/person = kg liquid/person, then two aerosol
units would be used per one liquid unit (2 x 0.609 kg/unit
~ 1.34 kg/unit). The following conclusions can be drawn:
Possible consumption
scenarios (per year) Number actively
liquid aerosol exposed
(Case 1) 1 unit 2 units 1,395,000 (771,000 + 1.248.000)
2
(Case 2) 2 units 4 units 624,000 (1/2 x 1,248,000)
(Case 3) 3 units 6 units 465,000 (771.000 +1.248.000)
3 6
ASSUMPTION NO. 2: Units of aerosol/person = units liquid/person
Step 1 - Determine how much of the 500,000 kg goes Into aerosols and
how much goes Into liquids. 36 units of aerosol are
produced for every 49 units of liquid. Thus:
% Total available solvent used 1n aerosol =
36 units aerosol x 0.25 kg solvent x 0.609 kg aerosol
kg aerosol unit aerosol x 100%
36 units aerosol x 0.25 kg solvent x 0.609 kg aerosol +
kg aerosol unit aerosol
(49 units liquid x 0.30 kg solvent x 1.34 kg liquid)
kg liquid unit liquid
= 22%
% Total available solvent used 1n
liquid =
49 units liquid x 0.30 kg solvent x 1.34 kg liquid
kg liquid unit liquid x 100%
49 units liquid x 0.30 kg solvent x 1.34 kg liquid +•
kg liquid unit liquid
36 units aerosol x 0.25 kg solvent x 0.609 kg aerosol
kg aerosol unit aerosol
= 78%
221
-------
Thus,
110,000 kg solvent (500,000 x 22%) will be used 1n aerosols,
and
390,000 kg solvent (500,000 x 78%) will be used 1n liquids.
Step 2 - Determine the number of units which can be produced.
units aerosol product = 110.000 kg = 722,000 units (43%)
(25%)(0.609 kg/unit)
units liquid product = 390.000 kg = 970,000 units (57%)
(30%)(1.34 kg/unit)
As with Step 2 of assumption one, approximately 43% and 57%
would be what was expected.
Step 3 - Determine the number of persons actively exposed.
If units of aerosol/person = units of liquid/person, then
one aerosol unit would be used per one liquid unit. The
following conclusions can be drawn:
Possible consumption
scenarios (per year) Number actively
liquid aerosol exposed
(Case 1) 1 1 1,692,000 (722,000 + 970,000)
(Case 2) 2 2 846,000 (1/2 x 1,692,000)
(Case 3) 3 3 564,000 (1/3 x 1,692,000)
o Without more Information on actual personal consumption
patterns of these products, neither assumption one nor
assumption two provide "more accurate" exposure numbers.
So, for the purpose of the continuation of this analysis, a
"worst case" value will be adopted to represent exposure for
this problem (assumption two, case one = 1,692,000).
Passively Exposed Populations
The enumeration of the population passively exposed to the
solvent-containing rug cleaning products 1s based on the
actively exposed population and follows the methods outlined
1n Step 5 of Method 5-2. with some modification.
222
-------
Assume that the same percentage of household sizes
Identified for all rug cleaner users applies to the
population enumerated for rug cleaner users. (Actively
exposed to the PMN solvent).
From SMRB data; text Table 22.
Household of:
Percentage:
1 person
12.6%
2 people
30.8%
3-4 people
40.1%
(11)
(1)
1 person household
2 person household
3-4 person household
5 + person household
1,692,000 x 0.126 x 1
1,692,000 x 0.308 x 2
1,692,000 x 0.401 x 4
1,692,000 x 0.165 x 6
Total passively exposed population
5+ people
16.5%
= 213,000
= 1,042,000
= 2,714,000
= 1.675.000
= 5,644,000
Characterization of actively and passively exposed
populations.
The actively exposed population (100% female) 1s
characterized for age distribution using the SMRB data
base. (Text Table 22). These data Indicate:
Years of age
18-24
25-34
35-44
45-54
55-64
654-
Percent of total
10%
24%
19%
16%
15%
15%
These percentages applied to the 1,692,000 females actively
exposed results 1n the following:
169,200 are 18-24
406,080 are 25-34
321,480 are 35-44
270,720 are 45-54
253,800 are 55-64
253,800 are 65 or older
223
-------
(11) Characterization of the passively exposed population (males
and females) relies entirely on generic U.S. Census data
(text Table 12). Ratio of males to females = 0.49:0.51.
Applied to the total population passively exposed
(5,644,000), 2,766,000 are male of which:
210,000 are under 5 years of age (7.59%);
215,000 are 5 - 9 years of age (7.76%);
234,000 are 10 - 14 years of age (8.46%);
270,000 are 15 - 19 years of age (9.77%);
268,000 are 20 - 24 years of age (9.69%);
462,000 are 25 - 34 years of age (16.70%);
316,000 are 35 - 44 years of age (11.42%);
277,000 are 45 - 54 years of age (10.00%);
255,000 are 55 - 64 years of age (9.22%);
170,000 are 65 - 74 years of age (6.14%);
71,900 are 75 - 84 years of age (2.60%); and
17.100 are 85+ years of age (0.62%).
And, 2,878,000 are female of which:
197,000 are under 5 years of age (6.85%);
201,000 are 5 - 9 years of age (7.00%);
220,000 are 10 - 14 years of age (7.66%);
257,000 are 15 - 19 years of age (8.94%);
285,000 are 20 - 24 years of age (9.15%);
462,000 are 25 - 34 years of age (16.05%);
323,000 are 35 - 44 years of age (11.22%);
291,000 are 45 - 54 years of age (10.12%);
285,000 are 55 - 64 years of age (9.92%);
218,000 are 65 - 74 years of age (7.57%);
120,000 are 75 - 84 years of age (4.17%); and
38,600 are 85+ years of age (1.34%).
224
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APPENDIX A-5
POPULATIONS EXPOSED TO CHEMICAL SUBSTANCES VIA INGESTION OF DRINKING WATER
Problem 1: Point Source Surface Hater - Chemical Q 1s discharged from a
plant located In Lambertvllle, NJ (40022'00" - 74°56'10") to
the Delaware River. Surface water monitoring has detected
Chemical Q downstream of the plant as far as Wilmington,
DE. Enumerate the population potentially exposed to
Chemical Q because their drinking water 1s obtained from the
Delaware River. Chemical Q 1s teratogenlc. How many women
of child-bearing age are potentially exposed?
Solution: This problem was solved via application of Method 6-2 as
follows:
Step 1 - Not applicable
Step 2 - Not applicable
Step 3 - The first step towards solution of this problem was the
Identification of the USGS cataloging units of concern
between Lambertvllle, NJ and Wilmington, DE. Cataloging
units were obtained from USGS Hydrologlc Unit Maps for the
states of New Jersey, Pennsylvania, and Delaware. The
cataloging units are:
02-04-02-05
02-04-02-04
02-04-02-03
02-04-02-02
02-04-02-01
02-04-01-05
The next step was the Identification of the downstream and
upstream Delaware River REACH numbers between which drinking
water Intakes are to be Identified. REACH numbers were
obtained from REACH maps on file at the EPA-Mon1tor1ng and
Data Support Division, Water Quality Analysis Branch. The
cataloging unit and REACH (segment) numbers to which the
eventual WSDB retrieval was limited are:
02-04-01-05-006. (Lambertvllle, NJ)
02-04-02-04-002. (Wilmington, DE)
- A hydrologlc tree retrieval was requested from the
EPA-Mon1tor1ng and Data Support Division. The retrieval
request was limited to drinking water utilities on the
Delaware River mainstem as stored in WSDB between the above
listed cataloging units. Figure 23 1s the output received.
Listed below are the utilities and the exposed population
(I.e., population served);
225
-------
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Facility
Philadelphia Water Oept.
Bristol Water Oept.
Lower Bucks Water Dept.
U.S. Steel Water Dept.
Morr1sv1lle Water Dept.
Lambertvllle Water Dept.
Trenton Water Dept.
Keystone Water Dept.
Total
Exposed Population
1,950,098
30,000
90,000
8,000
21,000
4,400
250,000
2.616
2,356,114
"Child-bearing age" 1s taken as 15 to 44 years of age. The
percentage of the U.S. population that 1s female and within
that age group was calculated from Table 12 of the text.
Results are as follows:
Age Group
15-19
20-24
25-34
35-44
Total
Percent of Total U.S. Population
4.60
4.70
8.25
5.77
23.32
2,356,114 x 0.2332 = 549,446
Therefore, 549,446 women of child-bearing age are
potentially exposed to Chemical Q.
Problem 2: Point Source Ground Water - A waste disposal site on the
outskirts of Miami, FL, leaches Chemical K to ground water.
Monitoring data has detected K 1n ground water 1n all
directions up to 50 miles from the site. Enumerate the
population potentially exposed to K via drinking water from
public and private ground water systems 1n this area.
Solution: The solution to this problem 1s based on a slight
modification of Method 6-4.
Step 1 - The first step was the Identification of the counties around
Miami affected by the ground water contamination. This was
accomplished by the use of a 1° x 2° topographic map of the
Miami area. The 50-mile radius of the waste disposal site
basically Includes all of Dade County, Florida.
227
-------
Step 2 - An FRDS retrieval restricted to drinking water utilities 1n
Dade County was requested from the computer system staff of
the EPA-Off1ce of Drinking Water. The FRDS retrieval
revealed a complex web of public, private, Industrial, and
business facilities which use ground water for drinking
purposes. A total of 472 systems were listed with the major
one being the Miami - Dade County Water and Sewer Authority
which serves 500,000 people. A sample of an FRDS printout
for this system Is presented 1n Figure 24. Only one surface
water utility serving 9,037 people, however, was listed. It
was felt, therefore, that a more accurate enumeration of the
exposed population would be obtained by obtaining the
current population of Dade County. This avoids counting any
populations twice and also Includes those people who have
private wells 1n their home. According to the Census
publication, Number of Inhabitants (1980), the total
population of Dade County, 1n which Miami 1s located, 1s
1,625,781. This 1s also the population potentially exposed
to the chemical substance. That population which consumes
surface supplied drinking water 1s Insignificant; 1t 1s also
highly probable that they consume ground supplied drinking
water at the place of work or other business concerns.
Problem 3: Treatment Method Example - An Industrial plant located 1n
Cincinnati, OH, discharges a non-toxic substance to the Ohio
River. This substance, however, reacts with flourlne to
produce a toxic chemical. The non-toxic substance has been
detected In the Ohio River 100 miles downstream of the
plant. Enumerate the population which consumes flourldated
drinking water obtained from the Ohio River and 1s
potentially exposed to the toxic chemical formed.
Solution: This problem was solved by using a combination of Method 6-2
(as 1n Problem 1) and a modification of the approach
discussed 1n Section 6.3.2 of the text.
Step 1 - The cataloging units and REACH numbers of the Inclusive
section of the Ohio River 100 miles downstream of Cincinnati
were Identified from USGS hydrologlc unit maps of Ohio and
Kentucky and REACH maps on file at the EPA-Mon1tor1ng and
Data Support Division. The upstream and downstream
cataloging units and REACH numbers are as follows:
05-14-02-06-001 (100 miles downstream)
05-09-02-01-001 (Cincinnati)
228
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Step 2- A hydrologlc tree retrieval restricted to water supplies on
the Ohio River between these river segments was requested
from the EPA-Mon1tor1ng and Data Support Division, Water
Quality Analysis Branch. The output 1s similar to Figure
23, previously presented. The purpose of this retrieval was
twofold (1) to Identify utilities and (2) to obtain the FRDS
number of the utilities Identified. The FRDS number would
then be used to retrieve treatment Information for those
facilities from the FRDS Data Base of the EPA-off1ce of
Drinking Water. The retrieval, however, revealed that only
three facilities withdraw drinking water from the Ohio River
within 100 miles downstream of Cincinnati. These are the
Newport Water Works, the Cincinnati Water Department, and
the Kenton County Water Works. Since so few facilities are
Involved, 1t was decided to call each Individually Instead
of conducting an additional retrieval. They were each
contacted; each Indicated that they do fluoridate their
water. Therefore, the population exposed to the toxic
reaction product 1s the total population served by the three
facilities. This was calculated from the retrieval data as
follows:
Newport Water Dept. 30,000
Cincinnati Water Dept. 850,000
Kenton Water Dept. 52.000
Total 930,000 persons potentially exposed
Problem 4: Monitoring Example - Chemical S 1s ubiquitous. As a result
of nationwide sampling of both finished surface and ground
obtained drinking water at over 100 plants, the following
detection frequency 1s observed.
Cumulative detection Cumulative detection
frequency 1n finished frequency 1n finished
Concentration surface water groundwater
<10 ug/1 10% 1%
< 5 ug/1 50% 25%
< 1 ug/1 95% 50%
Enumerate the population exposed to chemical S at the three
concentrations.
Solution: This problem was solved using a combination of the data 1n
Table 29 and Method 6-6.
230
-------
Step 1 - The first step was the calculation of the relative percent
of use of surface and ground water 1n the U.S. This was
accomplished as follows:
From Table 29:
Population consuming surface water = 124,480,000
Population consuming ground water = 87,404,000
It 1s assumed, since the data 1n Table 29 do not Include
systems of fewer than 25 people, that the difference
between the current U.S. population (226,504,000) and the
total of the above 1s the population which consumes water
from private wells (14,620,000). This population 1s
Included 1n that population which consumes ground water.
Therefore, the relative use of ground and surface water 1s
as follows:
Surface = 124.480.000
226,504,000
Ground = 87.404.000
= 0.55
14.620.000 = 0.45
226,504,000
Therefore, the populations exposed to different
concentrations of S are as follows:
Concentration
10
5
1
Detection frequency
Surface Ground
Fraction of U.S. Number of
population3 persons (xlQ6)b
.1
.5
.95
.01
.25
.50
0.060
0.388
0.748
13.6
87.9
169.4
a (surface frequency x 0.55) +• (ground frequency x 0.45)
b fraction x 226.5 million (1980 U.S. population)
Problem 5: Source Type. A pollutant Is detected 1n five percent of
surface water supplies and 50 percent of ground water
supplies. Enumerate the potentially exposed population.
Solution: This problem was solved via application of Method 6-6 and
the data 1n Table 29 of the text as follows:
231
-------
Frequency of detection 1n surface water = 0.05
Population served by surface water = 124,480,000
Frequency of detection 1n ground water = 0.50
Population served by ground water = 87,404,000
Population exposed = (0.05)(124,480,000) +(0.50)(87,404,000)
= 49,926,000 persons
Problem 6: System size. A pollutant 1s detected 1n 20 percent of
finished waters serving fewer than 10,000 persons, but 1n 70
percent of those serving over 10,000 persons. Enumerate the
potentially exposed population.
Solution: This problem was also solved via application of Method 6-6
and the data 1n Table 29 as follows:
Frequency of detection 1n "small" systems = 0.20
Population served by "small" systems = 44,182,000
Frequency of detection 1n "large" systems = 0.70
Population served by "large" systems
Population exposed = (0.20)(44,182,000)
= 126,228,000 persons
= 167,702,000
(0.70)(167,702,000)
232
-------
Appendix B. Examples of Data Bases Used in Occupational Population
Methods Section
(1) 1970 Census of Population; Occupation by Industry
• Sample of Tkble 1. Industry group of employed persons by
occupation, age, and sex: 1970.
(2) The National Industry - Occupation Employment Matrix, 1970,
1978, and Projected 1990. Volume I.
• Sample of Table 1. Percent distribution of industry
employment by occupation, 1970, 1978, and projected 1990.
(3) The National Industry - Occupation Employment Matrix, 1970,
1978, and Projected 1990. Volume II.
• Sample of Table 2. Percent distribution of occupational
employment by industry, 1970, 1978, and projected 1990.
• Sample of Table 3. National nonagricultural employment of
wage and salary workers by industry, 1970 and projected
1990.
• Sample of Table 4. Total national employment by industry,
1970, 1978, and projected 1990.
• Sample of Table 5. National 1978 employment, projected
1990 requirements, and average annual openings, 1978-90, by
occupation.
(4) Employment and Earnings. October 1981.
• Sample of Table B-2. Employees on nonagricultural payrolls
by industry.
(5) Example of 1977 Economic Census Reports - 1977 Census of
Manufactures: Industry Series. Industrial Organic Chemicals.
SIC 2861, 2865, and 2869.
• Samples of tables containing employment information.
(6) Procedures used to Develop the 1978, 1979, 1980 and
Projected 1990 OES Survey - Based Matrix
234
-------
UNITED STATES
IPARTMENT OF
OMMERCE
JBLICATION
PC(2)-7C
U S DEPARTMENT
OF COMMERCE
Social and Economic
tistics Administration
BUREAU OF
THE CENSUS
SUBJECT REPORTS
Occupation
by Industry
1Q7O
CEN$U$ OF
POPULATION
235
-------
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clerks, n e
gss i-Sef £ isgS-s gf5 : 1 II
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3
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OCCUPATION BY INDUSTRY
240
-------
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241
OCCUPATION BY INDUSTRY
-------
Employ
f,"?,.'• .f-vtf& '*,„ v««^.y-'*»,,, /Ur^aHM--*
|i,,,**... VaW . >- ^ ,.i^^^»Q*.,,l^Mi^4MW
m :i.
-------
Table 1. Percent distribution of. industry employment by occupation, 1970, 1978 and projected 1990
Total
all
industries
1970 1978 1990
Agncultre,
forestry,
fisheries
1970 1978 1990
Agriculture
197O - 1978 1990
Total all occupations
Professional and technical
tnqineers,technical
Aeronautical
Chemical
Civil
hiectrical
Industrial
Mechanical
Me talluryical
P e 111> 1 o u m
:,ali-,
U t liei t.MUJlm-e [ S
Llt«' and physical scientists
Aqilcultural
Atmospheric and space
Biological
Oiemir.ts
ueolog i , t s
Ph yslcis t s and astronomers
Natnematical specialist,;
Actuaries
Ha themat1Ciana
;>t a t1st icians
tngineeriny, -science technician-^
A>) I icu 11 UL a 1 , h lulgc 1 , exc uea j. t u
i-ht'iiucd 1 ti:chn icidii:.
bt itters
Electrical and electronic
Industrial en-jineeriny
Mechanical engineering
s ur ve yors
other engineer invj, j,c it'nce toc.i
rle'iiodl worKi-L s, exc t fcnnu: i an..
ChuopLdCtors
boat 1st-;
dietitians
0( ycholog i:. t L;
IIi n dn ami L i1 g i ond 1 j» i an IK* L -•
100.00 100.00 100.00
13.8B 15.09 IK.78
100.00 100.00 100.00
100.00 100.00 100.00
2. 13
3.21
1.20
1.38
1.99
2.75
1.UO
.08
.06
.21
.36
.20
.214
.02
.02
.Ob
. 1 /
. 2t>
.02
.01
.0^4
. It
.0 i
.0 i
.04
. J 1
.01
.03
1.01
.05
. 10
. i«4
.20
.03
.02
.Oli
. i 1
1. / /
.02
. 12
-OU
. 0»>
. 11)
. J 7
.0 1
.i 1
. 10
.0 )
.3b
. 17
.02
.02
.07
.OH
.20
.06
.03
.0 1
.01
.Ob
. Jb
, Z ^
. 1 1
.02
. 11)
. JH
. J-i
.'J 1
1.2 J
. Ob
.06
. 16
.32
. 20
. 21
. 02
.02
. Ot
. lr>
. 30
. 02
.01
.07
. 13
. 0 )
. 03
. 0^
.01
.01
. 02
1. 01
. 05
. 0')
. 31
.21
. 03
.02
. OH
. 2"4
2. 0 )
. 02
. 13
. 0"4
. 02
. 1"4
.140
. 01
1. 06
. \'l
. U 1
. T>«
. 2 i
. 04
.02
. 1 1
. in
. 23
. 00
. 03
.01
. Ob
. 00
. Mb
. 26
. 17
. 0 i
. 2rt
. 1 J
. 12
. 02
1.2
."44
.0 1
1 .28
.20
.04
-5S
.23
.06
.02
.12
.15
.25
.09
.03
.01
.05
.07
.50
.28
. 19
.0 J
. 12
. 1 b
. 1 !
.02
.06
.00
.00
.04
.00
.00
.01
.00
.00
.00
.01
. 12
.09
.00
.02
. 01
.00
.00
.00
.00
.00
.00
.16
.09
.00
.02
.00
.00
.00
.02
.02
. b b
.00
.00
.00
.00
.00
.00
.00
.01
.00
.54
.01
.00
.00
.00
.00
.01
.09
.07
.00
.00
.01
.01
.01
.00
.00
.00
.00
.00
.00
.00
.09
.00
.00
.06
.00
.00
. 01
.00
.00
.00
.02
.21
.15
.01
.05
.01
.00
.00
.00
.00
.00
.00
.28
. 16
.00
.03
.01
.00
.00
.03
.04
. 71
. 00
.00
.00
. 00
.00
.00
.00
.00
. 00
.70
.01
.00
.00
. 00
.00
. 01
. 13
. 10
.00
.00
.01
.02
.01
.01
.00
. 00
.01
. 01
. 00
. 00
. 12
.00
.00
.07
.00
.00
.02
.00
.00
.00
.02
.35
.25
.00
.08
.02
.00
.00
.00
.00
.00
.00
.41
.28
.00
. 04
.00
.00
.00
.03
.05
. 119
.00
.00
.00
. 00
.00
.00
.00
. 00
.00
.89
.02
. 00
. 00
. 00
.00
.01
. 19
. 16
.00
.00
.01
.02
.01
.01
.00
.00
.01
.0 1
.00
. 00
.02
.00
.00
.01
.00
.00
.00
.OU
.00
.00
.01
.09
.08
.00
.01
.00
.00
.00
.00
.00
.00
.00
.12
.09
.00
.01
.00
.00
.00
.01
.01
.b7
.00
.00
.00
.00
.00
.00
.00
.0 1
.00
.56
.01
.00
.00
.00
.00
.01
.07
.07
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
. JO
.02
.00
.00
.01
.00
.00
.00
.00
.00
.00
.01
.15
.13
.00
.02
.01
.00
.00
.00
.00
.00
.00
.21
. 17
.00
.02
.00
.00
.00
.01
.02
. /4
.00
.00
.00
.00
.00
.00
.00
.00
.00
. 73
.01
.00
.00
.00
.00
.01
. 10
. 10
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.04
.00
.00
.02
.00
.00
.00
.00
.00
.00
.02
.28
.22
.00
.05
.02
.00
.00
.00
.00
.00
.00
.14
. 28
. 00
.02
.00
.00
.00
.01
.01
.9 i
.00
.00
. 00
. 00
.00
.00
. 00
.00
.00
.93
.02
.00
. 00
.00
.00
.01
. 16
. 16
. 00
. 00
.00
.00
.00
. 00
.00
.00
.00
. 00
. 00
. 00
244
-------
1-iuK- 1. ivccrnt di;;ti ibutiim or nuJUstiy employment by occupation, 1970, 1978 and projected 1990
Crude
tl.lt UI ill IJilS
l')70 1971) 1990
Other crat ts , k indted womer:*
C lane, dec rick, hoist operator
Inspectors, other
btationary engineers
otntr crafts workers
opei .1 1 1 vos
opt1 1 tit i vet., e net pt tian sport
,itMM i ->X. 1 1 It d ii.f t a IH ot k l rivj
t' u i it.ii.e t eiidi. i , i.in*.- 1 1 L .->, pouter.*
u i i H' 1 i ii 'j ma i h i in* u pt • i .1 1 1 v«>.>
tie. i I *• i :. , irn- 1 ,1 i
j.ti I In - , in i 1 1 1 1 nj in,) i h t)\ t-L Jt In l p I t'i I : ) (- ii .ii.it ti upt'L i to; ..
«»• Idt- L •> d nd t 1 dint' cut L ui. .»
0 1 iu1 L operatives, c xc traui>poLt
A:,o«'mblt t s
Blasters
...ULveyoLii* hel pot-j
uut tint) operatives, other
Or L 11 f L o , eat t h
oar a.j t' wrkr,yas station d t ten
Me it cutter s,tutcfieLS,oxc ml j
Mint- opeLdtiveb,other
lixinq operatives
ui !*•! .s, 9 reader s,oxc au to.nobi let,
t'hotovjL d pa ic j. i oci:^ii workers
-j,i i I i»i ^ and dt t k it and;.
-.,i-y»-i ,
r1 u j 1 1.1 ft* t tin! i ,..toKt,t-x< nu- 1 , o t tit'l
M i.,t *• 1 laneoui, n-acli inu op*.'t a t vo ^
utiM't overall vebfe]tc t L aiu, j-ot t
r cariisj-joc t fquijircnt operative j
tioat opeiat oct
beiiVi-'Cy and toutt1 uorKer^>
FOLK lift,to« rrotoi ou'Lative^.
Hail vehicle cperatorb, utiier
nail roaa ttakt. opt, ra t ors
Haiiioad switch operatJt^
TdJticab drivetb, chautfears
l>e r v ice workers
L 1 caul mj iiGivice wurkeis
bldq intenoi c leaner t*, other
Janitors and ^e xtom*
Kood see v ice we t kers
Bar tendets
Cooks,exc private house tioldi.
us hwashers
Food counter, fountain workers
H ai teis
Other tood serv wkrs,exc privt
Healtn service workers
Health aides, except nursing
Nur^in^ aides and oraeilies
Practical nurses
ri/o
2.d3
1.79
.36
.57
.1 1
43.94
J7. 17
J. 35
.23
. 1 1
.01
.00
.00
2.97
33. U2
.00
.71
. 10
.05
4.08
.14
.00
27. 17
.02
1.13
.00
.1)0
. ijli
. 1 1
.00
.UO
.0 J
6.78
.00
. 04
. JO
1.08
. Jb
.01
.04
5.24
2.36
1 '_> M
. 14
1.40
.05
.01
.04
.00
.00
.00
. J1
Netdl
iiu n i ii'i
1 9 / H
2.47
1. 53
. 37
. 4b
. 11
39. b4
32. 24
3. HI
.24
. 11
. 01
. UO
. UO
i. 4'j
28.43
.00
.73
. 11
.06
3. 92
. 10
.00
21. 94
.02
1. 17
. 00
. 00
. U(>
. 211
. 00
.00
. 03
7. 40
. 00
. 04
. 3b
1. 00
. 08
. 01
. 04
5. 83
2. 22
1. 48
. 14
1. 34
. 05
. 01
. 03
. 00
. oo
. 00
. 01
1 99 0
2.32
1.79
.20
.24
.09
35-fa8
25.06
4.74
.20
.09
.02
.00
.00
4.42
20.32
.00
.82
. 16
.09
2.84
.07
.00
14.09
.03
1. 1 1
.00
.00
.04
.44
.00
.00
.01
10.63
.00
.05
.44
.70
.15
.0 1
.03
9.25
1.64
1.13
.09
1.05
.04
.01
.02
.00
.00
.00
.01
.05 .04 .08
.01 .01 .01
.03 .02 .05
.02 .01 .01
1'1/0
2.47
.48
.80
1.17
.02
52.51
4U.03
1.79
.00
.04
.00
.01)
.00
1.75
42.24
.03
1.2U
. 13
2.66
2.46
.00
.02
3U. 16
.04
1. 35
.00
.00
.07
.07
. 00
.01
.01
H.48
.00
.13
.37
3.45
.00
.00
.00
4.53
.99
.60
.08
.52
.01
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
Codl
mi n inq
1 '( 7 8
2.47
.41
.98
1.06
. 01
49.53
40.91
1.87
.00
.0?
.00
.00
.00
1.84
39.05
.03
1.27
. 16
2.85
2. 21
.00
.01
30.97
.05
1.39
.00
.00
.07
. 04
.00
. 01
.01
8.62
.00
. 12
.48
3.24
.00
.00
.00
4.77
.94
.56
.08
.48
.01
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
1990
2.31
.46
1.02
.81
.01
50.37
41.03
1.57
.00
.02
.00
.00
.00
1.5S
39.46
.02
1.06
.23
2.71
1.33
.00
.01
32.69
.07
1.25
.00
.00
.06
.01
.00
.01
.01
9. 34
.00
.11
.57
2.25
.00
.00
.00
6.42
.70
.36
.04
. Jl
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
6.46
.50
.48
5.11
.06
36.51
32.95
1.43
.00
.21
.00
.Ob
.01
1.15
31.52
.11
.25
.06
.07
5. 75
.05
.00
24.57
.0«
.35
.03
. 1 1
.0,'
.OH
.02
.01
.01
3.56
. 10
.18
.07
.29
.00
.01
.01
2.H7
1.24
.82
.12
.71
.28
.00
.20
.01
.03
.02
.03
.00
.00
.00
.00
5. 13
.48
.58
4.00
.07
34.39
30.65
1.54
.00
. 17
.00
.04
.01
1. 32
29. 1 1
. 15
.23
.Ob
.08
5.96
.03
.00
21.88
.04
.40
.03
. 1 1
.02
. 06
.01
.01
.01
3.75
.09
. 17
.09
.23
.00
.01
.04
3. 11
1. 17
.77
. 11
.66
.25
.00
.16
.01
.04
.01
.03
.00
.00
.00
.00
2.85
. 75
.60
1.43
.08
36.98
32.07
1.82
.00
. 1 1
. 00
.02
.00
1.68
30.25
.26
. 19
.06
.08
6.74
.02
.00
22.03
.04
.52
. 01
. IB
. OS
.OH
.00
.00
.00
4, 92
.07
. 17
. 10
.08
.00
.01
.04
4. 45
.95
.51
.05
.46
.29
.00
. 13
.01
.08
.02
.04
.00
.00
. 00
.00
245
-------
Jabl e 1. It'1 i, en* distribution oi i ndu-.try ^mpl o yment by occupation, 1y /U, 1 97« and pro JIM; ted
NOMITHM .ll 1 1C
in i ii t M'j .1 nd
• |n.ii i y i nrj
i/o r* /M 1S9U
Const i uc tn
14/0 1'>7H
other managers , of i icials , pro f
Mqrs, superintendents, Duiid
Olfice irdnayers, other
Other managers, ddnu
Sjl*?j wor kf*r s
Advertising a,S
Other sales « crkers
Clt-Tic.il *orker:j
Legal stcretanes
other secretaries
btenographers
1'y fists
ut t ice machine operator;*
bookkeepmq ard billing
Compute! dnJ Letipheral e .j u i p
Key punc h
Ot fiet cleiiceil WOL kei^
[' 1111 ntj r if L k t
Mookkeepi11 ;.
C i.,hi.fi:.
I 1 I 1 i < .1 i 1,\\ [M( V l-.Ot .,, 0 t lit- I
i.ulit't_t(ji.,, L l 1 J an it .K C'ju ft t
Countet t !<• i k • , *' xt t o tuer
Lxpedittrs,production uontloirs
K i i e c 1 e r k -s
Mdii handlers.exe [Ost otrice
Mi'iisen-j el s ana ot t ice Helpers
Pdyioll, t line keeping c U-t K.S
KI-M 1 estate a L pr tiisor i.
rt ecep t lonistb
-jiilppinq and receiving c 1 e t K »
btatibtical clerks
btocjt clerks and store Keeper*
Telephone operdtors
taeighers
Misc clerical workers
c r a 11 s and kindied w o t K f L .•>
Lori.? 11 uc 11 on ci at t s wo i ki*i >
Cdr penteis and .ippren t i cu.*
br ick, stonprrdions, appienticoj
bulldozei operdtois
Cernen t and cone re te
Electr;
Excavating,»
and
rrach
Floor layers, exc tile s
Plasterers and apprentice^
Plumr>ers,pipetittersraprentict;ii
Koofers dad ulatets
jtructutdl rretdl ciot t wor&eL^
Hie setteis
7. 81
7.19
.42
. 13
. 1b
. 0 1
.Ob
.01
.27
.00
.07
. 20
. 12
.38
. 1 1
. it,
. 30
27.31
11.09
. / 1
. 1 1
2. Ob
. 00
.96
t). i i
.00
. 2 1
. 00
. 00
. 1 3
.00
.00
.00
. 36
. 02
. 24
. 10
•}. 46
. 13
1. H3
. 06
. 0'.
. 01
. 06
. 44
. 15
. 17
. 06
. 06
. 01
. JO
. 00
.07
. 10
. 15
. 34
. 09
.99
. 33
28. 36
10. 6 /
.76
. 09
2.02
.00
. 99
6. 51
.00
. 19
.00
. 00
. 1 1
. 00
. 00
.00
.24
.01
.17
.06
5.15
. 15
1.64
. 11
.OK
.01
.0;
.45
.11
. 15
.06
.06
.01
,24
.00
.06
. 14
.16
.27
.10
.93
.37
31.09
11.94
.70
.05
2.69
.01
.90
7.38
.00
. 13
.00
.00
.06
.00
.00
.01
5.79 5.88
6. 15
1.93 1.84 1.99
.01 .01 .01
1.55 1.56 1.70
.07 .03 .01
.30 .25 .28
.13 .13 .12
.02 .01 .01
.03 .06 .06
.06 .04 .04
3.74
.03
1.35
. 16
.0'.
.01
.02
.0)
.86
.09
.06
.03
.02
.24
.04
. 12
.04
.08
. 14
.03
.03
.32
53.46
44.08
lb.32
3.23
1.08
1.29
4.24
4.82
.31
5.51
.19
.55
4.62
1.31
1.09
.51
3.91
.04
1. 32
. 14
. OS
. 01
.02
.04
1.06
. 10
.05
.03
.02
. 26
.04
. 11
. 04
.08
. 13
.02
.03
.33
53.82
44.03
15.67
3.05
1. 1 1
1.29
4.75
4. 13
.23
5. 30
.31
.43
4.50
1.89
.92
.45
4.03
.06
1.08
. 25
. 06
.0)
.03
.06
.95
. 16
.06
.03
.02
.27
.06
. 1 1
.05
. 10
. 19
.02
.05
.42
55.80
45. 11
15. 18
2.91
1.52
1.47
5.24
4.83
.20
5. 10
.30
.38
4.34
1.99
1.11
.55
15.88
.06
.23
.00
.01
15.57
.60
.00
.59
4.88
1.75
.01
1.58
.02
. 14
.07
.02
.01
.04
J.06
.02
1. 15
.01
.03
.01
.01
.01
.88
.09
.04
.02
.02
.21
.00
.14
.03
.03
.06
.03
.01
.28
52.28
47.90
36.20
3.82
. 37
1.32
.62
1.16
.10
1.42
.02
.32
1.01
.32
1.12
. 12
21.<35
.09
.24
.00
.01
21.52
.58
.00
.58
4.77
1.58
.01
1.45
.01
. 12
.07
.01
.03
.03
3.12
.02
1.05
.01
.04
.00
.01
.01
1.06
.10
.03
.02
.02
.22
.00
. 13
.03
.03
.05
.02
.01
.28
50.41
46.05
35.44
3.37
. 39
1.20
.64
1.05
.08
1.31
.04
.26
.90
.45
.81
. 12
12.93
. 13
.31
.00
.01
12.48
' .56
.00
.56
4. S3
1.60
.01
1.47
.00
. 1 3
.06
. 02
.02
.02
3. 17
.04
.91
.02
.05
. 00
. 02
. 01
. 99
. 15
.04
.03
.03
.23
.00
. 13
.04
.04
.08
.01
.01
.34
55. 3U
50. 12
35.9(1
3.7B
. 62
1.47
.91
1.72
.08
2. 13
.01
.42
1. 3!>
.57
. 91
. 19
blue col Id r
',upo r v L.JOI ~.
6. 05
6.04
2.72
2.78
2.60
2.31
2. 38
2.51
246
-------
..j-.'^m^^^.^mm^^M^.
:' '**?Vhinrrte'ir« ttSSrf;;m^
The National
I ndustry-Occupation
Employment Matrix,' x*\$* ' Itp
1970,1978, and. :::;., ;,:;i W'$:y>ijil
Projected 1990-•• ;':.., ' ;'-':'••"?t|'!':ilfl!f|
* ' '. : " .;L >,' i ,'s: far'1-V'i '!li
U.S. Dopartrneni of Labor,
Bureau of Labor Statistics '
Apiil 1U81 ,
Bulletin 2086 -
-. ;'F
i--45
-------
'JjDIt- 2. I'trcunt distribution ui occupa tiondl umtJloymeiit by industry, 1970, 1978 and projected 1990
Total
occupations
1970 1978 1990 1970 1978 1990 1970 1970 1990
Professnal
and
technical
Knq incers,
technical
I'otal ail industries
A 'jLicultu re, forestry, fisheno
Aiji iculturu
Ajiicultidl production
jt'L VI CUS, iJXCept hOLtlCUitUL*
Mo r t icul t ui itl sei vices
Forestry
Fisheries
Mining
Cod 1
(,i ude petroleuii and natural ga.i
Nonmut allic mining and 'juairying
coristLuction
lienora 1 building contractors
(ieneia 1 cont fact or:;, ex c building
jpc-c id 1 trade contractors
(1 a 1 1 u t a c t u c A n g
UiJi cel laneous wood products
K u i. ni tu LO a nd t ix t ui es
St one, clay, and glass pioducti.
(jidi.s and glass products
Cement , conct t tu, plaster
S ti net uiai clay pi o ducts
l'uttt;iy ami t elated pioduct.>
rtiscel laneous noninet a iic,otoue
i' L mid ly metal industries
n ids t t urnacws, steel work..*
nth PL piimaiy steel
CL uridi y aluminum
ut h« L pinndiy nonferrou;;
Fabricated me ta 1 pioducti*
•> utluty and other hardware
Fdbi icated structural metal
.:>cre w machine products
Metd 1 stamping
n L ^cel laneous tabncated m«ta 1
Clachiner y except electrical
trujinOi, and turbines
Far ni machinery and equipment
Construction mach ines
fl^talworking machinery
ot fice and accounting macmnes
hiec tr oriic computing ecjui pmen t
uthe machinei y,exc electrical
tlt-ct ical machinery
Hou.s hold appliances
Uddi , tv communications eguip
u the electiical machinery
Transportation equipment
Hotoi vehicles and eyuipment
Aitctatt and parts
Ship, boat building and repair
bdilioad equipment
Mobile dwellings
Cycles, misc transportation
100.00 100.00 100.00
100.00 100.00 100.00
100.00 100.00 100.00
bcientitic instr uments
optical, health serv supplier
Ptiuto eguipnifciit and supplier
batches and clock devices
Mi a eel id no ous maiiutdcturinj
Nonduidble y oudi>
•»„';,>
4.') 0
J.'JU
.i\
.^0
.00
.05
.BO
. 1 1
. Id
. JS
.It
b.SH
1.44
1.7«
2.71
J.1.V1
14. Jl
. J7
.la
. 14
.49
. 1b
.^t
-Ml
.^J
.2U
,U7
.05
. 17
l.tob
.70
. 4b
. 19
.2H
1. 7b
. 19
-»4
. 13
..29
.S9
2.31
. 14
. 1b
.37
.40
. 1 1
.23
I.OU
2.44
.23
.80
i..*o
2.42
1. J2
.84
.35
.06
. 10
.03
.57
.22
. 17
. 1 3
.04
. -jb
3.69
). 53
3. 01
. 2')
. 20
.08
.07
.93
. 10
.22
. 4d
.13
b. 26
1.55
1.b4
3.06
21.84
13. Ob
. Id
. 72
. 13
. 44
. 13
. 55
.73
.21
. 26
. 05
.05
. 16
1. 33
. 50
. 38
. 19
. 24
1. 64
. 19
.53
. 11
. 25
.54
2.45
. 14
. 15
.39
.36
.07
.28
1. 03
2. 17
. 19
.63
1. 35
2. 19
1. 04
.62
. 3u
.Ob
. 1 1
.04
. 59
. 20
.21
. 13
.03
. 49
2.69
2.57
2.09
.26
.21
.06
.05
.92
.09
.29
.43
.10
6.05
1.50
1.68
2.d5
20.71
12.76
. 15
.bU
.09
.40
. 14
.59
.62
.19
.22
.02
.03
. 13
1.18
.42
.37
.15
.22
1.63
.20
.60
.10
.25
.47
2.61
.12
.15
.40
.38
.05
.39
I.OU
2.19
.18
.57
1.43
2.08
1.00
.45
.27
.05
.23
.05
.59
.17
.23
.10
.03
.44
.69
.43
.Ob
. 33
.04
.24
.01
.61
.07
.02
.47
.04
1.76
.21
1.30
.24
16.98
11.53
.70
.11
.01
.07
.02
.10
.36
.10
. 11
.02
.02
.09
.74
.31
. 16
.1 1
. 15
.76
.07
.29
.04
.09
.24
2.27
. 13
.09
.29
.25
.14
.64
.71
3.05
.1 1
1.31
1.61
2.50
.58
1.58
.26
.03
.01
.0 1
.68
.31
. 15
.20
.01
.21
.79
.46
. 10
.31
.04
.30
.01
.75
.06
.03
.61
.03
1.40
. 18
.96
.25
14.35
9.61
.32
.11
.01
.07
.02
. 10
.31
.09
. 10
.01
.02
.08
.59
.22
.13
. 10
.12
.66
.07
.25
.03
.08
.21
2. 18
. 12
.08
.28
.22
.09
.74
.63
2.51
.09
.98
1.43
1.95
.56
1. 11
. 19
.03
.01
. 01
.67
.26
.20
. 19
.01
. 19
.76
.47
.15
.29
.03
.25
.03
.76
.06
.05
.61
.03
1.52
.20
1.03
.28
13.53
9.06
.25
.11
.01
.07
.03
.11
.23
.07
.07
.00
.01
.06
.52
. 18
. U
.08
. 11
.60
.07
.23
.03
.07
.18
2.38
.09
.08
.26
.22
.06
1.01
.62
2.42
.08
.98
1.35
1.61
.50
.83
. 18
.02
.04
.02
.63
.20
.20
.21
.00
. 16
. IB
.04
.0 1
.00
.00
.12
.0 '
1.73
.21
.11
1.20
.12
8.29
.96
6.24
1.08
54.26
45.82
3.48
.19
.01
.11
.05
.19
.90
.26
.27
.04
.05
.27
2.20
.87
.48
.37
.47
2.46
.26
.87
.16
.34
.82
8.31
.56
.35
1.15
.98
.42
1.75
3.08
13.23
.41
5.91
6.88
11.97
2.17
8. S3
1.03
.14
.03
.05
2.36
1.27
.41
.61
.05
.47
.27
.Ob
.05
.00
.00
.17
.02
2.40
.21
. 16
1.90
.12
7.08
.86
4.99
1.22
50.08
42. 16
1.78
. 19
.02
.12
.05
.20
.85
.25
.24
.02
.05
.27
2.01
.69
.44
.41
.45
2.44
.30
.82
.16
.33
.82
8.80
.59
.36
1.27
.98
.30
2.13
3.14
12.37
.39
4.99
b.98
10.53
2.40
7.02
.83
.15
.04
.07
2.48
1.23
.55
.65
.04
.46
.26
. OH
.07
.00
.00
. 14
.04
2.65
.25
.28
2.01
. 10
7.32
.87
5. 12
1.32
45.78
38.37
1.34
.21
.01
. 13
.06
. 19
.65
.20
.18
.01
.03
.20
1. 75
.54
.40
.38
.42
2. 19
.34
.61
. 14
. 33
.75
4.21
.46
.29
1. 17
.97
.21
3.08
2.99
11. 16
.35
».5S
6.24
9.07
2.20
5.70
.86
. 10
. 11
.08
2.15
.91
.51
.69
.03
.41
10.46
8. 71
5.4U
4. 74
U. 46
.4 j
7.91
7.40
248
-------
2. i'i'Li:eni ai.,t.L ibu 11^it ,jL jccutJdtioii.il employment by induotry , 1970, 19/d and projected
Aero-
IldUtlC.ll
engineers
VJ / 0 1 •) 7 B
1990
Chemical
eng meet
1970 1978
1990
Civil
«iny meet's
1970 1978
1990
1 uta 1 ail lud ustllos
Agriculture, tocestry,tish«Lieia
Agriculture
Agriculttal production
Horticultural servict:±>
Forestry
Mining
Metal
LOdl
Crude petroleum and natu ral gas
Nonmetallic mining and 'juarryiuo,
Lonsttuction
tit'jiut d 1 building contt actoi i»
(.enui a 1 emit i dc tut :.,e iu; buiIdiu j
iffc ia 1 11 i»dk- eoiitiactuiu
.Ida u tdC tu L ing
uui aLle good s
u i iltia nee
LUmuet and woud ptudut ti*
L u y -j 1 n g
jd win il 1 , pi aning drid in i 11 nut n
fl i .<: t'1 1 ei DC U u •> wood pLuduct.i
Kut in tu t e ana tixtui*'-.,
.> t one ,c Id y , and glass product:*
bla^^ and glass ptod uc tj
Cement,concrete,pidatec
btLUctuLdl clay products
Pottery and related products
fl iscelldneous nonmetdlic,stone
Primary metal industries
Jldst £ urndces,steel uoi K^
other primary steel
f i itndr y
Kabiicatc'd mo td1 prod u<: t i
Cat lei. y drid ot hi-t ha t d *a i.«.'
Jr'dtJLiCdteu structural metal
jcrew mdch intj products
Metdl stamping
M iijcel Idrieous f dbt led ted me td 1
Hdchinery except clectiicai
Mivjine;; dnd turbineb
fdim machinery and equipment
Construction cndchines
Metdlworking machinery
Oft ice doa accounting mdcninea
fc.lec t L on ic c ompu tiny e^ui ptnen t
Utner indchinery,*jxc electrical
tiectiicdl nidchiru-ry
Hou^eliula dp^lidnceo
nadic>, tv couunuru cdtiorij ejui^
ottieL elec tr iCdl mac tuner y
TL diispoi t at ion *»>jui pmeiit
flo tot vi'h ic lk;ij and rtj a ipmuiit
Aiicidtt and paiti^
jhip,bojt tuildinq and Lap an
UdilLOdd equipment
MotJile dwell inqs
Cycles,misc trdnsportation
Fcote^siondl,scientific in^tr^
Scientific instruments
Opticdljhealth serv supplier
Pnoto equiprr.tnt and supplier
«(dtchei. dnd clock device^
Miscelldneous tnanufacturinj
NonduLaule goods
lOU.OU 1UU.UO 100.OU
100.00 100.OU 100.00
100.UO 100.00 100.00
.00
. 00
.00
. 00
.00
.UO
.UO
.00
.00
.UO
.00
.00
.00
. 00
at>. 29
Ho
b
1
7 ;
/o
. 23
. 4 'j
. 00
.OU
. 00
. OU
.uu
.00
.00
. JO
. JO
.JO
. U J
.00
. JJ
.JO
. 00
. 11 J
. uu
. JU
. 00
. JO
.00
. JU
. J»
. 17
.00
. 00
.00
.00
. 0 3
. 17
. 12
. J J
. '> 1
. Ja
. 10
. 1 1
. la
. 11!
. J2
. uu
. J J
.60
. J4
. J4
. 01
.JO
. n
.00
.00
.00
.00
.00
.00
.00
. OU
.00
.00
.00
. 00
.00
. 00
B1.09
HI. Ob
4. It
. 00
. OU
. 00
. 00
. UO
. 00
.00
.00
. 00
. 00
. 00
.00
.00
.00
. 01)
. 00
. OU
. OU
. 00
.OU
. 00
.00
. 44
. 19
.00
.00
.00
. 00
.05
. 19
1. Ib
.OU
. Ul
. 3U
7M. 1 1
. 1 ;
/ J. ti2
. 2t)
. 02
. OU
-OJ
. 74
. bb
.07
. Ul
.00
. MJ
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
73.41
73.41
3.47
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.00
.uu
.uu
.uu
.00
.00
.00
.00
.29
.09
.00
.00
.00
.00
.05
.14
.b4
.OU
,'jb
.oa
6/.7M
. 12
b ;.4J
.21
.00
.UO
.00
.58
.50
.07
.00
.00
.bb
.00
.00
.00
.00
.oo
2.21
.12
.05
1.71
.32
1.95
.16
1.79
.OU
80.87
16.39
1.36
.06
.02
.00
.0 i"
.05
2.14
.43
.31
.29
.23
.87
2.05
.81
. iO
.31
. '> /
.«/
.07
.28
.01
. 13
.38
2.20
. 1 1
.00
.18
.06
.15
.52
1. 1o
3.4'j
.17
.81
2.47
2.32
.'j 1
1.6 1
. 13
.02
.00
.01
1.56
.21
.29
1.04
.01
.29
.00
.00
.00
.00
.00
2.92
. 12
.08
2.38
.3J
2.13
. 17
1.95
.00
76. 19
14. 19
.70
.04
.01
.00
.02
. 12
1.98
.42
.30
. 15
. 16
.93
1.93
.71
. 30
.311
. S )
. It!
. 10
.22
.01
. 13
.29
1. 99
.OU
.00
.20
.07
. 11
.54
.97
2. 48
. 1 1
.4H
1.88
2.0'j
. 'j7
1. )0
. 13
.02
.00
.01
1.79
.21
.42
1. 14
.00
.31
.00
.00
.00
.00
.00
2.20
.10
. 16
1.66
.26
1.74
. 19
1.55
.OU
75.59
10. 3S
.59
.03
.01
.00
.02
. 38
1.45
.36
.20
.01
.03
.83
1.80
.73
.32
. JO
. 44
.47
. 19
.06
.01
.11
.07
1.03
.00
.00
. 16
.06
.07
.37
.34
.74
.00
.29
.44
1.57
.44
. 89
.21
.00
.00
.00
1.92
. 16
.47
1.28
.00
.32
.78
.12
.09
.01
.66
.71
.07
.07
.U7
.09
U2.94
H.'I2
Jb.11*
^.H^
8.23
6. 1H
.i«
. 13
.02
.07
.04
.02
.65
.04
.51
.02
.01
.OU
.77
.49
.10
. 1 1
.{)')
.4(1
.02
.76
.00
.03
. 15
.58
.03
.03
.21
.01
.00
.03
.25
.45
.00
.21
.23
1.BO
. 20
1.32
.22
.03
.02
.00
. 14
.04
.02
.07
.00
.04
1.25
.21
.IB
.02
1.04
.92
.07
.09
.b7
.08
37.50
4.62
29. H3
J.04
6.28
4.55
.23
.13
.01
.08
.03
.02
.59
.04
.47
.02
.00
.05
.60
.36
.09
.09
.04
.70
.03
.63
.00
.02
.09
.39
.02
.03
.14
.01
.00
.02
.15
.25
.00
. 1 1
.13
1. 13
.21
.94
.14
.01
.01
.00
.14
.03
.02
.07
.00
.05
1. 15
. 27
.26
.01
.87
.97
.07
. 17
.66
.06
37.42
4.34
JO. 16
2.91
5. 13
3.52
. 15
. 19
.00
. 14
.05
.04
.54
.02
.42
.02
.00
.06
.60
.36
.13
.07
. 0)
.43
.04
.36
.00
.00
.01
. 11
.00
.04
.02
.01
.00
.00
.02
.09
.00
.07
.01
1.07
. 25
.66
. 13
.00
.00
.00
. 17
.02
.03
. 11
.00
.09
. u5
bu.47 62.00 65.24
2.09
1.72
f.61
249
-------
Table 2. Percent distribution of occupational employment ty industry, 19/0, 1978 and projected 1990
Sales
engineers
1970 1978 1990
Other
engineers
1970 1978 1990
Life and
physical
scientists
19/0 1978 1990
Jut .1 1
llidui.l I in:,
101).OU 1UU.OO 100.00
100.00 100.00 100.00
100.00 100.00 100.00
Agriculture, f or estry,fishenes
Ag r icult urc
Agncultral production
Services, except horticulture
Hoi t icultuldl service:,
Km <•.,!. L y
Pi slier les
Mining
Metal
COdl
Cruue petroleuir and natural gd.^
Nonmetallic mining and guarryiay
Construction
General building contractors
Generdl cont rac tors,exc building
special trade contractors
Hdnu tdc t ur ing
Durable goods
Or dridnce
Lumoer and wood products
Logy ing
Sd wmil 1, planing and trill worK
fliscellaneous wood products
Furniture and fixtures
St one ,cldy , and glass products
uldss and glass products
Cement, c on ciete, plaster
structural clay products
Pottery and related products
M i.scellaneou K nonnie tallc, stone
Primary metal industries
ill.u.t t ULiidCts t :,t ee 1 work,
Ot hei pi imdl y stfi'L
i'r iitiai y al um mum
ut ti*-i pi linai y nont»'l loU'i
Fabiicated metal products
Cutlery and ether hardware
FdbiiCdted structural metal
bcrew nachint products
Metal stamping
Mi seel Idneou E fdbricated metal
Machinery except electrical
engines and turbines
Farm machinery and eg,uipment
Construction machines
Hetalworking machinery
Office and accounting machines
hlectronic computing equipment
Other machinery, exc electrical
Electrical machinery
Household appliances
Badio,tv comir unica tions eguip
Other electrical machinery
Transportation equipment
Motor vehicles and equipment
Aircraft and parts
Ship, boat building and repair
Mailroad equipment
Mobile dwellings
cycles, misc transportation
Professional, scientific Instrs
Scientific instruments
Optical, health serv supplies
Photo equipment and supplies
Hatches and clock devices
Miscellaneous manufacturing
Nonduidble goods
.06
.06
.00
.02
.04
.00
.00
1.14
.02
.00
.98
. 13
3.98
.51
.47
2.99
45.02
39.73
. 15
.23
.01
.15
.07
.28
1.52
. 13
.52
. 19
.OB
.59
2. ;j
. 19
1.11
. 4'>
.(.II
'j.'jl
. 19
2. 54
. J5
.55
1.S8
14.05
.47
.19
1.U7
3.28
.10
.56
7.56
9.39
.26
1.60
7.52
2.06
1.11
1.25
.11
. 13
.04
.01
2.52
2.08
.30
.08
.05
.60
.06
. 06
.00
.02
. 04
.00
. 00
1.75
.02
.00
1.58
. 15
4. 45
.50
.45
3. 50
40. 10
35.04
.06
.27
.00
.22
.05
.28
1.47
.09
.53
. 17
. 10
.57
2. 42
. 37
1. 02
. 4U
.51)
4. 21
. 12
2.03
. 19
. 28
1.57
12.97
.23
. 19
1.80
2.95
.05
.50
7.22
8.22
. 16
.76
7.29
2.20
1. 04
.92
. 10
.07
.03
.01
2.32
1.92
.25
.08
.05
.57
.00
.00
.00
.00
.00
.00
.00
2.14
.02
.00
1.94
.18
4.79
.41
.28
4.09
36.67
30.89
.02
.49
.00
.49
.00
.40
1.46
.00
.58
.15
.17
.55
2.59
.35
1./S
. J9
.5')
1.8 J
.02
.88
.02
.02
.88
11.15
.00
.20
1.19
2.30
.00
.80
6.64
8.44
.00
.71
7.73
1.92
1.15
.66
.05
.00
.03
.01
1.93
1.66
.05
.10
.10
.61
.25
.14
.09
.02
.01
. 1 1
.00
.42
.04
.01
.31
.04
.40
.26
.22
.02
.02
. 13
.00
.54
.04
.02
.43
.04
5.28
5.05
. 5.77
41.95
5.30
.29
.02
.20
.06
.37
1.58
.57
.42
.04
.09
.44
1.07
.41
. t I
. 10
.21
J. 04
.15
1. 12
.15
.37
1.23
12.25
1.00
.69
2.01
1.29
.66
2.49
4.09
7.69
.31
3.15
4.21
4.45
1.08
2. J8
.58
.30
.06
.02
4.93
2.54
.93
1.33
.12
.94
7.52
37. 11
2.51
.27
.03
.18
.05
.34
1.36
.48
.36
.03
.08
.40
.86
.29
.27
. 12
. 17
3.04
.15
1.06
.15
.38
1.28
12.35
.99
.65
2.05
1.35
.45
2.75
4.08
6.99
.29
2.68
4.02
3.72
1.12
1.70
.45
.31
.07
.04
4.81
2.29
I. 13
1.28
.09
.82
. 39
.35
.30
.02
.02
.04
.00
.43
.04
.02
.32
.03
1.96 2.10 2.99
.18 .22 .29
1.42 1.43 2.11
.34 .44 .58
49.48 43.50 39.23
34.23
1.77
.22
.03
.13
.05
.30
.83
.29
.20
.01
.05
.26
.69
.19
.22
. IS
. 1 J
3.12
. 14
.86
.18
.49
1.43
12.73
.72
.50
1.60
1.68
.37
3.60
U.23
6.98
.35
2.87
3.74
2.92
1.00
1.02
.39
.23
.20
.07
3.99
1.66
1.00
1.26
.06
.63
2.03
1.55
.57
.57
.41
. 1 1
.14
8.11
1.12
.12
6.56
.29
.93
.02
.90
.00
41.50
14.57
1.02
.09
.00
.05
.04
.03
1.32
.31
.52
.12
.04
.31
3.82
1.HB
.67
.42
.11 1
.89
.06
.24
.07
.05
.46
1.40
.12
.05
.14
.17
.13
.36
.41
2.12
.04
.67
1.39
1.83
.38
1.12
.28
.02
.00
.00
1.66
.39
.11
.83
.02
.36
2.65
1.82
.86
.47
.49
.58
.23
8.32
.80
.14
7.13
.23
.77
.03
.73
.00
32.57
11.15
.49
.06
.00
.02
.03
.02
.96
.25
.36
.07
.03
.23
2.71
1.20
.49
. 10
.d'j
.75
.05
.21
.05
.04
.38
1.23
.11
.03
.13
.15
.07
.35
.35
1.74
.03
.52
1. 18
1.33
.35
.78
. 14
.02
.00
.00
1.57
.34
.48
.72
.01
.25
3.04
2. 34
1.25
.68
.41
. 16
. 33
9. 18
.79
.21
7.98
. 19
.90
.07
.83
.00
27.97
9.36
.48
. 04
.00
.00
.03
.02
.56
.20
.14
.02
.04
. 14
2. 16
.87
. 19
.Jf>
. 64
.68
.02
.21
.05
.05
.33
1. 30
. 10
.02
. 12
. 16
.05
.49
.32
1.52
.05
.51
.95
1.00
.33
.S2
.08
.03
.01
.01
1.42
.26
.43
.71
.00
. 12
6.38 4.99
26.93 21.42 18.61
250
-------
e 2. Pen IMI t dis t1 ibu t ion or occupational employment by industry. 1970, 1978 and projected 1990
Clerical
workers
19/0
1'J7U
1990
Stenogrphr,
typists,
secretaries
1970
197B
1990
Legal
secretaries
19/0
19/t)
1990
Totdl all industries
Agriculture,forestry,fisheries
Agriculture
igncultral production
Services,except horticulture
Horticultural services
Forestry
Fisheries
flining
Itetdl
COdl
Crude petroleum and natural yds
Noninetallic nlninq and quarrying
Corts tr uct ion
dfnt'ldl building cont l ,ic toi t
UtMK-rdi cunt I ac t ol s, <-xc building
bpc-cial trade contractors
Manufacturing
Durable goods
ordnance
Lumber and uocd products
Logging
.idmni.il, planing and mill nor*
Miscellaneous wood products
furniture and fixtures
Stone,clay,and glass products
Glass and glass products
Cement,concrete,plaster
btructural clay products
L'ottwty and related products
Miscellaneous nonmotal ic, stone
t'rimaiy metal industries
blast I urnacts, s t eel nor*-*
other pcimar> steel
Primary aluminum
other primary nonfeirous
fabricated metal products
cutlery and ether hardware
Fabricated structural metal
jciev machine products
Metal stamping
Miscellaneous fabricated inetal
flacninery except electrical
Engines and turbines
farm machinery and equipment
Construction machines
MetaIwockiny machinery
ottice and accounting machines
tlectionic ccmputing equipment
other machin«ry,exc eloctricj.1
tlectricai machinery
household appliances
Radio,tv communications equip
other electrical aachinery
transportation equipment
Motor vehicles and equipment
Aircraft arid parts
bhip.boat building and repair
Hailroad equipment
Mobile dwellings
cycles,roisc transportdtrun
Professional,scientific instc^
.icientitic instruments
optical,health serv supplies
Photo equipment and supplies
batches and clock devices
Miscellaneous manufacturing
[iGuducable goods
100.oo 100.00 100.00
100.00 100.00 100.00
100.00 100.00 100.00
.25
.22
.07
. 1 1
.03
.03
.00
.41
.03
.04
.27
.Ob
1.97
.40
.09
.87
17.it
10. 1 7
.33
.23
.01
. 1 5
.Ob
. 31
.46
. 12
. 17
.02
.02
. 1 1
. ^6
.44
.23
. 1 1
. Itt
1.20
. 15
.36
. 1 1
.16
.11
1.99
. 10
. 13
.31
.27
. M
.2.1
. til
1. 91)
. 15
. 73
1.06
1.70
.tj J
.7b
.21
.OH
.03
.02
.•)7
.2.1
. 1o
. 1 S
.0 J
. U2
.34
.29
. 13
. 11
.04
.04
.00
.51
.03
.05
.37
.05
2. OS
.41
.t, t
1.00
14.70
8.75
. 15
.20
.01
. 14
.05
. 28
. 39
. 10
. 14
.01
.02
. 1U
. 74
. )1
. 18
. 10
. 14
1.07
. 14
. 33
. oy
. 14
. 36
1.91
. 10
. 11
.32
. 24
. 07
. 2H
. 76
1. 67
. 12
. 56
.99
1. 35
.5b
. 50
. 15
.04
.04
.02
. 56
. 19
. 20
. 114
. 02
. 36
.25
.21
.08
.08
.03
.02
.01
.39
.02
.05
.27
.03
1.95
. IU
.67
.89
12.95
7.90
. 12
.17
.00
.12
.05
.30
.30
.08
.10
.00
.01
.08
.60
.24
.15
.07
.13
.96
.12
.31
.07
.12
.31
2.00
.08
.09
.31
.2S
.05
.39
.79
1.54
.10
.44
1.00
1.01
.47
.25
.13
.03
.08
.03
.54
.15
.21
. 15
.01
.33
.30
.23
.07
.10
.05
.06
.00
.53
.05
.02
.39
.06
2. J1
.51
.79
1.00
18.07
10.73
.42
.22
.00
.15
.06
.30
.50
. 14
.17
.03
.02
. 12
.83
.31
.19
. 12
.19
1.20
.15
.35
.10
. 16
.42
2.17
.09
.11
.28
.30
. 14
. t 1
.90
2.27
.16
.64
1.26
1.60
.50
.82
.16
.03
.04
.02
.70
.28
.20
. 18
.03
.47
.46
.37
. 19
.11
.06
.07
.01
.65
.04
.03
.52
.05
2. 30
.49
.69
1.11
15.28
9.16
. 18
.21
.01
.14
.05
.29
.45
.13
. 15
.02
.02
. 11
.64
.22
. 15
. 11
.15
1.08
. 13
. 34
.09
. 13
.37
2.02
.08
. 10
.28
.27
.09
. 33
.83
1.87
. 12
.61
1.13
1.27
.49
.55
. 12
.03
.04
.02
.69
.24
.24
. 17
.02
.42
.32
.25
.10
.09
.04
.05
.01
.48
.03
.04
.38
.03
2.08
.41
.69
.97
13.81
8.23
. 12
.19
.00
. 13
.05
.32
.38
.12
. 12
.01
.02
.09
.52
.19
. 13
.07
.12
.96
.09
.36
.07
. 11
.32
2.00
.06
.09
.26
.26
.06
.43
.81
1.61
.09
.45
1.06
.97
.39
.33
. 10
.02
.08
.02
.65
. 18
.24
.21
.01
.44
.01
.01
.01
.00
.00
.00
.00
.46
.02
.00
.U2
.00
.27
.Ob
.17
.03
2.47
1.33
.10
.01
.00
.01
.00
.01
.11
.04
.06
.00
.00
.00
. 14
.09
.02
.00
.02
.08
.01
.02
.00
.00
.04
.21
.00
.03
.05
.01
.01
.01
.OB
.34
.00
.16
.18
.27
.07
.18
.01
.00
.00
.00
.06
.00
.03
.03
.00
.00
.00
.00
.00
.00
.00
.00
.00
.43
.01
.00
.40
.00
.16
.04
.10
.01
1.14
.82
.03
.00
.00
.00
.00
.00
.07
.02
.03
.00
.00
.00
.07
.04
.01
.00
.01
.05
.00
.02
.00
.00
.02
. 14
.00
.03
.04
.00
.00
.01
.04
.24
.00
.09
.14
.14
.04
.07
.01
.00
.00
.00
.05
.00
.03
.01
.00
.00
.00
.00
.00
.00
.00
.00
.00
.39
.02
.01
.34
.00
.20
.05
. 14
.00
1.56
.98
.03
.00
.00
.00
.00
.00
.06
.02
.02
.00
.00
.00
.06
.03
.01
.00
. 01
.08
.01
.04
.00
.00
.03
. 18
.00
.04
.04
.00
.00
.05
. 04
.37
.00
. 11
.25
. 10
.03
.02
.03
.00
.00
.00
.08
. 00
.05
.02
.00
. 00
7. j;
7.
6. 12
5.58
1.09
.57
251
-------
Table 3. National nonagrlcultural employment of wage and salary workers by Industry 1970 and
projected 1990
(In thousands)
Industry
Total nonagrlcultural employment .
Mining
Metal mining . . . ...
Iron ores
Copper ores
Coal mining
Bituminous coal and lignite mining
Oil and gas extraction
Crude petroleum and natural gas fields
Oil and gas field services
Nonmetallic minerals, except fuels . .
Crushed and broken stone ... . .
Sand and gravel .
Contract construction
General building contractors . .
Heavy construction contractors
Highway and street construction
Heavy construction, nee
Special trade contractors
Plumbing, heating, air conditioning
Painting, paper hanging, decorating .
Electrical work
Masonry, stonework, and plastering
Roofing and sheet-metal work
Manufacturing
Durable goods . . ...
Ordnance and accessories . .
Ammunition, except for small arms
Complete guided missiles
Ammunition, except for small arms,
Lumber and wood products
Logging camps and logging contractc
nee .
rs
Sawmills and planing mills
Sawmills and planing mills, general
Millwork, plywood, and related products
Millwork
Veneer and plywood
Wooden containers
Wooden boxes, shook, and crates
Miscellaneous wood products . . .
Furniture and fixtures .
Household furniture .
Wood household furniture
Upholstered household furniture
Mattresses and bedsprings
Office furniture ... ....
Partitions and fixtures
Other furniture and fixtures .
Stone, clay, and glass products
Flat glass
Glass and glassware, pressed ur blown
Glass containers
Pressed and blown glass nee
1967 Standard
Industrial
Classification
code
10-14
10
101
102
11-12
12
13
131,2
138
14
142
144
15-17
15
16
161
162
17
171
172
173
174
176
19-39
19,24,25,32-39
19
192
1925
1929
24
241
242
2421
243
2431
2432
244
2441.2
2512
25
251
2511
2512
2515
252
254
253,9
32
321
322
3221
3229
1970
("0.616
622
939
259
367
1445
1389
2696
144 1
1255
114 1
403
368
3,345
1,003 1
705 2
3247
3805
1,6365
4046
1248
2963
2098
1137
19,369
11.198
242.1
1700
990
71 0
5725
71 9
2138
181 3
167 1
722
702
332
267
864
4599
3207
161.5
873
368
377
51 1
504
6385
243
1322
768
554
1990
107,978
1,038
1130
190
570
339.0
3354
4750
190.0
2850
111 0
384
35 9
4,925
1,428.6
972 8
3950
5778
2.5236
6287
147 1
4962
2479
1642
23,585.0
14,5020
153.0
103.0
86.0
170
691 0
640
1750
141 7
2839
121 7
1044
140
100
154.1
6760
4970
248.1
1548
435
566
698
526
7160
163
1558
886
672
252
-------
Table 3. Continued—National nonagricultural employment of wage and salary workers by industry, 1970 and
projected 1990
(In thousands)
Industry
Cement hydraulic
Structural clay products
Brick and structural clay ttle .
Pottery and related products . . -
Concrete gypsum and plaster products
Other stone and nometalhc mineral products .
Abrasive products ... . . ....
Primary metal industries
Blast furnace and basic steel products
Blast furnaces and steel mills . . .
Iron and steel foundries
Gray iron foundries .
Malleablo iron foundries
Stool foundries
Nonfurrous inttl.ils
Primary aluminum
Nonferrous rolling and drawing .. . .
Copper rolling and drawing .
Aluminum rolling and drawing
Nonferrous wire drawing and insulating
Nonterrous foundries
Aluminum castings ...
Other nonferrous castings . . .
Miscellaneous primary metal products
Iron and steel forgings
Fabricated metal products
Metal cans
Cutlery, hand tools, and hardware
Cutlery and hand tools, including saws
Hardware, nee
Plumbing and heating, except electric
Sanitary ware and plumbers br
-------
Table 4. Total national employment by Industry, 1970, 1978, and protected 1990
luilustry
Total all industries . .
Agriculture, forestry, and fisheries
Agriculture
Agricultural production
Services, except horticulture
Horticultural services
Forestry
Fisheries . .
Mining . . ....
Metal mining
Coal mining ..... . .
Crude petroleum and natural gas
Nonmetallic mining and quarrying
Construction
General building contractors
General contractors exc building ... . .
Special trade contractors
Manufacturing .
Durable goods
Ordnance
Lumber and wood products
Logging . . ... ....
Sawmill planing and mill work . .
Miscellaneous wood products . .
Furniture and fixtures
Stone, clay, and glass products ... ....
Glass and glass products
Cement, concrete, plaster . . .
Structural clay products . . . .
Pottery and related products
Miscellaneous norimetalhc stone
Primary metal industries ..
Blast furnaces steel works . ...
Other primary steel
Primary aluminum ..
Other primary nonferrous
Fabricated metal products
Cutlery and other hardware
Fabricated structural metal ...
Screw machine products .
Metal stamping . ...
Miscellaneous fabricated metal
Machinery except electrical
Engines and turbines . . .
Farm machinery and equipment
Construction machines
Metalworking machinery . ...
Office and accounting machines
Electronic computing equipment
Other machinery, except electrical
Electrical machinery
Household appliances
Radio. TV, communication equipment .
Other electrical machinery
I'lli/ Ktimil.ml
IllcJU'.llhll
Classification
code
01
07 except 0713.
073
073
08
09
10
11.12
13
14
15
16
17
19
24
241
242,243
244.9
25
32
321-3
324.7
325
326
328,9
3312, 3
3315-7. 332,3391
Part 3399
3334. pt 334, 3352,
3361. pt 3392.9
3331-3.9. pt 334.
3351,6.7, 3362,9,
pi 3392 and 9
342
344
345
346
341,3,7-9
351
352
353
354
357 exc 3
3573
355.6.8,9
363
365,6
361.2.4,7
19/0
78.627 7
3.561 1
3.463 4
3.1355
1705
1574
534
44.3
6340
937
1448
2792
1163
4,673 3
1,1380
1,401 9
2.133.4
19.6359
11.4107
2963
6205
1108
3883
121 4
4643
644 1
1852
221 8
591
439
134 1
1303.4
5560
3677
1564
2232
1.3874
151 6
431 4
104 8
232 3
4672
1,9785
1100
1286
293 3
3178
909
1879
8499
1.9196
1847
6303
1 . 1 04 5
iu/a
94,3726
3,484 7
3,3348
2,845 8
241 9
247 1
795
704
8848
946
2127
4533
1242
5,907 9
1,4664
1,552.3
2,889 2
20,61 1 6
12.3476
1723
6854
131 2
4227
131 5
5221
6976
2022
245 t
M 3
469
152 t
12552
4806
3666
1793
2287
1,547 7
1800
5023
1087
244 9
511 8
2,3164
132 5
1496
3708
3484
72 1
2680
975 1
2,056 4
1827
5985
1.275 2
199U
114,0003
3,067 9
2,934 0
2,384 8
3038
2454
71 1
628
1,0592
113.1
3398
491 0
1155
6.897 8
1,7179
1,9253
3,254.6
23,617 1
14,5500
1729
7399
1043
4659
169.7
6744
7104
221 6
260 1
31 9
423
1544
1345.5
4785
427 1
181 2
2587
1,8680
2276
692.8
1135
291 0
5432
2,9804
1428
179.7
466 7
4366
659
4508
1.2380
2.5005
2130
6572
1.630.3
254
-------
Table 4 Continued—Total national employment by Industry, 1970, 1978, and projected 1990
Transportation equipment
Motor vehicles and equipment
Aircraft and parts . ...
Ship, boat building and repair
Railroad equipment
Mobile dwellings
Cyclos, misc transportation
Professional scientific instruments
Scientific instruments
Optical, health serv supplies
Photo equipment and supplies
Watches and clock devices .
Miscellaneous manufacturing
Nondurable qoods
hood and kicdred produt tb
Meat products
Dairy products
Canning and preserving
Grammill products
Bakery products
Confectionery products
Beverages
Miscellaneous food preparation
Tobacco manufacturing
Textile mill products
Knitting mills
Dyeing, finishing textiles
Floor coverings
Yarn and fabric mills
Miscellaneous textile mills
Apparel and textile products
Apparel and accessories
Miscellaneous fabricated textiles
Paper and allied products .
Pulp, paper, paperboard mills
Paperboard containers, boxes .
Miscellaneous paper and pulp
Printing and publishing
Newspaper publishing, printing
Other printing, exc newspapers
Chemicals and allied products
Industrial chemicals
Plastics and synthetics . . .
Synthetic fibers
Drugs and medicines
Soaps and cosmetics
Paints and varnishes
Agricultural chemicals
Miscellaneous chemicals
Petroleum and coal products . .
Petroleum refining
Misc petroleum, coal products
Rubber and miscellaneous plastics
Rubber . . ...
Miscellaneous plastics .
Leather products
Leather tanning and finishing
Footwear except rubber .
All other leather products
Transportation, other public utilities
rlli/ '.Milliard
linlit'.tf ml
Classification
code
371
372
373
374
3791
375.3799
381,2
383,4.5
386
387
39
201
202
203
204,0713
205
207
208
206,9
21
225
226
22 /
221-4,8
229
231^8
239
261-3.6
265
264
271
272-9
281
282 exc 2823,4
2823.4
283
284
285
287
286,9
291
295,9
301-3,6
307
311
313,4
312,5-7,9
19/0
1,9071
8046
6659
2756
506
852
25 1
4539
177 3
1364
1089
31 3
4355
8,225 2
1 , 7M 2
344 2
2446
284 1
138 1
2736
827
2361
1807
81 7
9785
247 3
832
57 1
5159
749
1,3923
1,224 5
167 8
/07 4
291 6
226 1
1897
1,161 1
417 2
7439
1,031 3
3189
101 7
1086
143 1
124 8
684
550
110 7
190 1
1535
366
577 8
288 1
289 7
320 7
26 1
2255
69 1
5,025 8
..
19/B
2.066 4
981 6
5866
2828
622
1108
424
564 5
1963
2068
131 1
303
4638
8.264 0
1./07 7
3506
1867
300 1
1462
2327
775
2278
1861
673
8989
2357
787
61 4
453 1
700
1,3423
1,1468
1955
6962
265 1
212.9
218 2
1,2593
4595
7998
1,078 1
3256
962
1169
1854
1345
722
61 0
863
2084
1645
439
7478
2959
451 9
2582
225
171 7
640
5,7498
1990
2,371 5
1.1452
5132
3143
639
2690
659
6832
1960
2666
1843
363
5032
9,067 1
1,7359
3554
1373
3630
1566
2048
802
2344
2042
578
1,0549
3339
769
1034
4582
825
1,5570
1,3203
2367
7904
2557
2665
268 1
1,342 7
531 0
811 7
13332
3935
1089
1808
2207
1663
920
57 1
1139
1778
121 5
563
8027
339,1
4637
2147
137
132 1
690
6,332 1
255
-------
Table 5. National 1978 employment, projected 1990 requirements, and average annual openings, 1978-90, by occupation
Occupation
il all occupations
otessional and technical
Engineers, technical .
Aeronautical
Chemical
Civil
LlBCtricdl
Industrial
Mechanical
Metallurgical
Mining
Petroleum
Sales
Other engineers
Life and physical scientists
Agricultural .
Atmospheric and space
Biological .
Chemists
Geologists
Marine
Physicists and astronomers
Other lite and physical scientists
Mathematical specialists
Actuaries .
Mathematicians .
Statisticians .
Engineering and science technicians
Agricultural, biological, exc health
Chemical technicans
Drafters . ...
Electrical and electronic .
Industrial engineering . . .
Mathematical technicians
Mechanical engineering . .
Surveyors ....
Other engineering and science
technicians
Medical workers, exc technicians
Chiropractors
Dentists
Dietitians
Optometrihls
Pharmacists
Physicians and osteopaths
Podiatrists
Registered nurses
Therapists
Veterinarians
Other medical and health workers
Health technologists, technicians
Clinical lab technologists, tech
Dental hygiemsts
Health record technologists,
technicians
Radiologic technologists,
technicians
Therapy assistants ...
Other health technicians
I'J/b
employment
94,372 6
14,244 6
1,157 1
580
530
1550
3000
1850
1950
165
60
170
340
1376
2806
197
125
622
1225
31 0
52
249
26
42 4
90
104
230
967 1
44 7
882
2960
196 1
27 6
1 2
15 1
738
224 4
1 91S 1
180
1193
350
209
1350
3756
8 1
1,001 7
164 4
296
7 6
5102
217 9
350
156
1038
73
1306
1 'J1IO
employment
114,0003
16,8542
1.4180
700
636
1903
364 4
233 1
2322
21 3
95
234
320
1782
3498
260
140
790
151 3
438
63
264
30
54 3
11 9
11 3
31 1
1,241 0
555
1106
3930
2534
357
1 9
199
870
2840
2,688 5
21 1
1550
,500
263
1850
5040
124
1,4550
2300
398
98
6708
2650
650
200
1400
100
1708
I'uii mil
Uiuiiijti
1978-90
20.8
183
225
207
200
228
21 >,
260
19 1
29 1
583
376
-59
295
247
320
120
270
235
41 3
21 2
60
154
28 1
322
8.7
352
283
242
254
328
292
293
583
31 8
179
266
404
172
299
429
258
370
342
53 1
453
399
34 5
289
31 5
21 6
85 7
282
349
370
308
AvonKje a
Total
5,177.4
675.8
47.2
1 9
1 8
78
105
80
7.5
.8
.6
.8
.6
7.0
12.4
1.2
.4
2.9
5.2
1.9
2
4
1
2 3
.5
3
1.5
404
2.2
3.5
134
7.4
1.3
1
7
26
94
1405
1 5
55
3 1
1 6
126
168
9
85.0
11 4
1 8
7
30.6
106
43
1 2
66
.5
7 4
nnual openings 111
Employment
change
1,635.6
2175
21 7
1 0
9
29
54
40
3 1
4
3
5
-2
34
58
.5
1
1 4
24
1 1
1
1
0
1 0
2
1
7
228
9
1 9
8 1
48
7
1
4
1 1
50
644
3
30
1 3
5
42
107
4
378
55
9
2
134
39
25
4
3.0
2
34
/H 00
Replacement
needs'
3,541 8
4583
255
9
9
49
5 I
40
4.4
4
3
3
8
36
66
7
.3
1 5
28
8
1
3
1
1 3
3
2
.8
176
1 3
1 6
53
26
6
0
3
1 5
44
76 1
1 2
25
1 8
1 1
84
61
5
472
59
9
5
172
67
1 8
8
36
3
40
256
-------
Table 5. Continued—National 1978 employment, projected 1990 requirements, and average annual openings, 1978-90, by occupation
Occupation
Technicians, except health
Atrpl2 1
00
'88
'78
>26
78
)08
>96
!76
6 1
)6 1
188
)5 5
)4 5
>90
'94
7 5
32
30
43
66
87
65
1 3
69
43
8 1
52
7 5
0 1
5 7
4 5
65
5 1
4 4
4 1
30
9 1
50
92
54
53
50
83
63
38
87
32
85
4 7
25
66
64
89
93
08
Average annual openings 1978-90
Total
101
32
9
2
2
27
3
28
166
92
68
5
148
73
3
60
3
7
4
111 9
36
67
763
126
1 2
11 5
58 1
8
35
23
6
58
11 6
10 1
72
39
76
8
38
1909
587
65
6
14 1
5 1
3
2.5
2
2 1
358
7 7
35
168
34
70
209
66
5947
Employment
change
55
23
5
0
1
1 0
2
1 4
11 2
6 1
49
2
79
40
.2
32
2
4
1
-98
9
-69
188
3 7
-265
3
176
4
7
6
3
1 4
4 1
45
1 0
1 2
27
5
3
559
21 1
35
1
1 2
1 3
1
a
.0
1
94
1 1
1 5
4.4
7
29
63
1 4
1748
Replacement
needs'
46
9
4
2
1
1 7
1
1 4
54
3 1
1 9
3
69
33
1
28
1
.3
3
121 7
27
136
575
89
277
11 2
405
4
2.8
1 7
3
44
75
56
62
27
4.9
3
35
135.0
376
30
5
129
38
2
1 7
2
20
264
66
20
11 4
27
4 1
146
52
4199
257
-------
EMPLOYMENT AND EARNINGS
U S Department of Labor
Bureau of Labor Statistics
In this issue'
Establishment data
adjusted to new
benchmarks
June 1983
>**.
-------
ESTABLISHMENT DATA
EMPLOYMENT
B-2. Employees on nonagrlcultura! payrolls by Industry
1972
SIC
Co*
-
-
10
101
102
11. 12
12
13
131 2
138
14
142
144
147
_
15
152
153
154
16
161
162
17
171
172
173
175
176
-
24 25,
3239
20-23
2631
24
241
242
2421
2426
243
2431
2434
2435
2436
244
245
2451
249
26
251
2511
2512
2514
2515
252
253
254
259
Indultry
TOTAL
PRIVATE SECTOR
MINING
METAL MINING
Iron orei
Copper ores
COAL MINING
BITUMINOUS COAL AND LIGNITE MINING
OIL AND GAS EXTRACTION
liquids
Oil and gas f-eld services
NONMETALLIC MINERALS, EXCEPT FUELS
Crushed and broken stone
Sand and grave
Chemical and fertilizer minerals
CONSTRUCTION
GENERAL BUILDING CONTRACTORS
Residertia1 building construction
Operative builders
Nonresidenlial building construction
HEAVY CONSTRUCTION CONTRACTORS
Highway and street construction
Heavy construction except highway
SPECIAL TRADE CONTRACTORS
Plumbing hea'ng ai' conditioning
Painting, paper hanging decorating
Electricat work
Carpentering and flooring
Roofing and sheet metal work
MANUFACTURING
DURABLE GOODS
NONDURABLE GOODS
DURABLE GOODS
LUMBER AND WOOD PRODUCTS
Logging camps and 'ogg.ng contractors
Sawm'"! and planing mills
Sawmills and planing mills general
Hardwood dimension and floo-mg
Millwork p'ywood and sT'uctu-a! members
Millwork
Wood kitchen cabinets
Hardwood veneer and plywood
Softwood veneer and p'ywood
Wood containers
Wood buildings and mobile homes
Mobile homes
Miscellaneous wood products
FURNITURE AND FIXTURES
Household furniture
Wood household furniture
Upholstered household furniture
Metal household turn lure
Mattresses and bedspnngs
Office furniture
Public building and related furniture
Miscellaneous turn, lure and futures
»pr.
1982
69,938
73,7614
1, 197
87.6
18.3
29-8
25H.?
251.5
7414.0
273.1
K">0.9
1 10.4
35. 1
31.7
2U.3
3,600
965.5
1422.3
us. 14
I49H.8
805.lt
196.5
608.9
2,029.1
1469.2
1 17.2
398.9
293.6
96.5
1148.1
19,060
11,348
7,732
593.1
69.0
178. 1
1t9.0
25.3
171.9
61.6
141.7
22.5
33.9
38.9
61 .5
OS. 2
73.7
1135.1
272.8
122.5
82.6
27.6
26.0
514.0
21.9
57.6
26.8
B»T
1982
90, 107
714,228
1, 179
79.7
17.2
24.4
251. 1
2H7.6
731.3
276.0
U56. 3
113.6
37.3
32.6
714.1
3,998
1,007.6
U51.U
4P.6
507.6
859.0
2314.0
f 25.0
2, 131.3
20<4.5
201.8
628.8
279.6
349.2
101.6
33.9
29.2
20.5
3, 1453
891.H
1406.6
148. 5
1436.3
•"02. 1
157.8
5HII.3
1, P59.9
464.3
103.9
376.H
27H.7
100.0
129.8
18, 166
10, 59 C
7,57f
620.5
72.H
186.2
155.7
26.6
168.5
72.6
"42.2
21.9
37.5
37.5
63.7
116. 1
72.2
H31.3
271.0
120.2
85.2
29.0
27.8
53. 5
20.5
51. 9
31.14
Apr.
1983P
89,005
72,971
991
R1.2
8.14
19.9
202.6
199.9
619.2
278.2
3U1.0
108.3
37.3
31.9
20.3
3,6149
926. 2
H28.5
52.2
14145.5
757.3
191.5
565.8
1,965.6
H68. 0
112.3
376. 0
292.3
105.2
113. H
18,295
10,689
7,606
640.0
714.6
190.5
159.7
26.8
193.8
75. 2
143.8
21. B
38.1
3P.7
68.6
U9.9
73.6
139.6
276.0
122.5
87.1
29.11
26.3
53.8
20.6
57.3
31.9
Har
1983P
89,873
73,806
1,006
.
-
-
-
-
-
-
-
_
-
~
3,893
~
-
-
:
~
_
-
-
16,455
10,806
7,649
66H.2
-
:
-
-
1141.7
-
-
"
*•
Apr.
19P2
_
59,521
881
65.2
13.5
22.5
210.1
207.3
521.7
123.1
39P.3
83.6
27.9
-
~
2,691
711.3
295.7
21.5
391. 1
632.2
159.4
472.8
1,550.3
353.6
94.3
303.7
216.3
70.6
116.5
12, 9"1?
7,562
5, 4 17
464 .0
51 . 1
156. 1
131.2
21.5
138.5
47.8
32. 6
19.6
29.6
32.9
111. 2
34.5
f 1.2
344.0
224.6
105. 2
66. 1
22.3
20.9
41.7
16. 3
41.9
19.5
rn
flay
1982
.
59.989
863
58.6
13.0
17.6
206.7
203.6
511. 1
^26. 0
385. 1
86.8
30.1
-
~
3,088
751.9
323.0
24.7
404.2
686.2
196.0
490.?
1,649.4
360. 4
105.7
309.5
261.8
77. 1
121.6
12,968
7,539
5,429
494.4
55. 1
158.4
133.2
21.9
141. 5
49.9
33.4
19.6
29.0
32.9
45. 9
35.5
60.6
310.8
222. 1
104.0
66.7
20.9
20.9
11.5
1^.8
41.8
19.6
iductson worfc
Far.
1983
_
57,989
699
44.2
5.6
11.14
163.8
161. «
415.5
129.4
2*6.1
75.0
26.0
~
~
2, 566
636.4
277.6
24.9
333.9
537. P
122.3
415.5
1,391.3
329.5
82.6
280. 1
227.7
73.4
98.6
12,241
6,944
5,297
511.8
55.3
If 3.8
137.3
21.0
154.2
57.6
33.0
10.0
33.4
31.3
47.5
36.0
59.7
340.4
223.1
103.2
68. 1
24. n
20.9
40.7
15.0
40.3
21.3
VI1
Apr.
1983P
_
58,760
696
41.5
5.5
11.5
162.1
159.8
107.8
129.3
278.5
81.9
29.2
-
~
2,752
668.1
297.4
28. 1
342.6
592.6
154.8
437.8
1 ,490. 8
333. 1
90.5
280.2
243. 2
78.1
111.5
12,370
7,039
5,331
529.3
57.2
167.9
141.2
23.2
159.2
60.3
34.4
19.0
34.0
32.4
51.7
39.1
60.9
347.4
227.9
105.4
70.0
24.0
21.3
40.9
15. 0
42.0
21.6
Bay
1983P
_
59,568
711
_
-
~
-
-
-
-
-
-
~
~
2,984
-
-
-
_
:
-
-
~
12,541
7,163
5,381
552. 5
-
-
-
~
350. 0
-
-
-
260
-------
ESTABLISHMENT DATA
EMPLOYMENT
B-2. Employee* on nonagricutturat payroll* by Industry — Continued
[In thousand!|
1972
(1C
Cod.
32
321
322
3221
3229
323
324
325
326
327
3271
3272
3273
329
3291
3292
3296
33
331
3312
3317
332
3321
3322
3325
3334
3351
3353
3357
336
3361
34
341
341 1
342
3423,5
3429
343
3432
344
3441
3442
3443
3444
3446
345
3451
3452
346
3462
3465
3469
347
3471
3479
348
349
3494
3496
35
351
3511
3519
352
3523
353
3531
Induttry
STONE. CLAY, AND CLASS PRODUCTS
Flat glass
Glass and glassware, pressed or blown
Glass containers
Pressed and blown glass, nee
Products o) purchased glass
Cement, hydraulic
Structural clay products
Pottery and related products
Concrete, gypsum and plaster products
Concrete block and brick
Concrete products, nee
Read* mixed concrete
Misc nonmetallic mineral products
Abrasive products
Asbes-os products
Mmera' wool
PRIMARY METAL INDUSTRIES
Blast furnace and basic steel products
Blast furnaces and steei mills
Steel pipe and lubes
Iron and steel foundries
Malleable iron foundries
Steel foundries, nee
Copper roHing and d-awtng
A'u-n ij— shee' plate, arxj foil
Nonlerrous wee drawing and insulating
Nonferrous foundries
Aluminum foundries
FABRICATED METAL PRODUCTS
Metal cans and shipping containers
Metal cans
Cutlery hand tools and hardware
Hand and edge toots, and hand saws and blades
Hardware nee
Plumbing and heating, except electric
Plumbing f'tti igs and brass goods
Fabricated structural metal products
Fabi icaterj structural metal
Metal doois sash and trim
Fabricated plate work [boilei shops)
Sheet meta1 work
Arcnitectura meta1 work
Screw machine pioduc's bolts etc
Screw machine products
Metal forging* and stampings
Iron and steel forgmgs
Automotive stampings
Meta1 stampings nee
Pioting and polishing
Meta1 coa'.ig and allied services
Ordnance and acessones nee
Misc fabricated meta1 products
Valves and pipe fittings
M'ie fabricated wire products
MACHINERY EXCEPT ELECTRICAL
Engines and urbines
Turbines and turbine generate' sets
Interna1 combustion engines, nee
Farm ar't? garde" machinery
Farrr machinery and equipment
Construction and related machinery
Construction machinery
ipt.
1982
580. 1)
16.3
111.2
61.9
H9.3
HI. 2
27. 1
33.8
39.6
177.6
16.7
60.3
82.9
122.6
2H.U
13.5
27.0
981.5
128.8
3514.3
29-8
172-0
1 0 J - 8
12.9
U3.<4
58.9
30.5
193-1
27.5
31.0
82.1
82.9
1.8.7
1,«68.6
6U. 9
52.7
115.5
51.2
81.3
60.8
23. a
28.3
062.6
92.0
70.2
136.2
102. 1
28.1
9U. 5
1414.0
SC . 5
239.1
"41.9
8«.2
101.5
97.8
67. 1
30.7
611.6
26.8
239.0
98.0
50.8
2,379.8
1 19.1
143.3
76. 1
1149.14
129.8
380.9
121. 1
nay
1982
588. 5
16.1
110.6
62.5
18.3
11. 6
27.7
31.1
39.14
185.6
17.7
61.2
99.1
121.7
2U.1
13.1
27.0
952. 5
1413.3
310.1
29.6
161.9
97. 2
12.0
11.1
56.7
30.0
193.1
27.0
31.2
32.14
82.2
18.1
1,1456.9
65.3
53.0
112.3
148.14
90. P
60.0
23.1
27.U
U60. 2
91.2
72.1
131.0
101. 3
2^.8
92.9
U3. 6
19.?
218.5
140. 0
m.2
99.6
96.9
66. 3
30. 1
fi'.O
27. 0
236.0
95 . °
50.5
,351.9
117.6
142.8
714.8
150.2
131.U
3->2.8
120.5
*~**~
Bar.
1983
5141.9
16.9
102.6
57.1
US. 2
141.0
2<4.6
33.2
36.5
166.7
16.8
5H.7
77.9
110.3
21.3
12.6
25.1
820.8
332.6
273.6
21.9
137.5
88.2
10. «
29.0
18. 2
21.5
181.6
26.0
29.6
76.3
80.6
147.8
1,359.7
62.7
50.7
136.0
141.7
78.9
60. 1
23.1
27.6
1117.8
77.5
75.5
112. 6
= 6.2
27.3
81.1
39. 1
14 5 . 0
225.6
32.11
85.5
97.0
90.9
61.5
26. 1
65.0
26. 2
217.5
84.2
19.3
2, 011.3
130.0
39.1
60.9
130. 1
110.5
253.6
73. 6
»pr.
19B3P
559.9
u. a
102. i
56.8
15.9
11.7
25.5
31.7
3P.1
178.5
17.6
57.2
86.2
111.6
21. «
12.9
25.1
629.6
337.2
277.6
22.2
139.1
89 .7
10.3
29.5
18.6
21. 8
182.3
26. 0
30.0
76. 1
82.0
18. 8
1,367. 3
62. 6
50.6
136.7
11. 1
80.0
61.3
23.3
28.1
119.3
76.5
77.1
111.1
97.3
27.5
85.3
39.9
15. 1
226.3
32.7
85.6
97.9
92.2
65.3
26.9
65.1
28.7
218.2
91.2
19.8
2,013.7
98.9
38.6
60.3
130.2
112.0
253. 1
71.8
Bay
1983P
*r _
57 U. 3
-
-
-
-
-
_
-
-
-
-
-
-
-
-
-
~
64 1.7
-
-
-
-
_
-
_
_
_
-
-
-
-
-
1 ,376.5
-
-
-
:
-
-
_
-
-
-
-
-
-
-
-
-
-
-
-
_
_
-
-
_
-
-
-
2,065.8
-
-
-
-
-
-
"
Apr.
1962
138.0
12.5
92.7
51.2
3B.5
27.1
21.6
21.7
32.0
133.2
11.0
11.0
61.0
65.14
15.5
10.0
~
732.0
319.6
261.6
22.3
133.2
82. 7
9.6
33.0
12.8
22. 6
136.9
20.1
23.6
58. 1
65.7
30.1
1,061.7
51.7
15.2
107. tl
36.6
59.7
11. B
18.1
17.8
30P.1
65.0
19. S
~>9. 9
73.2
19.3
71.1
3U.7
36. U
167. P
31. B
70.7
T6.5
77.6
514.3
23.3
11.8
17. 8
171 .5
65.5
38.5
1,163.0
•>3.6
23. 1
50. 5
98. 1
83.5
213.2
71.9
Pi
Bay
1982
115.9
12.5
92.1
5". 6
37.6
27.6
21.9
25.2
32.0
111.0
12.0
15.2
69. i
81.7
15.1
v 9.9
~
70P.2
307.14
253.3
22. 1
121.6
76.9
R.P.
31.1
11.1
22. 1
13-M
20.0
23.«
56.2
61.9
39.0
1,051.5
51.9
15.1
101.7
3S.2
59.5
11.1
18. 1
17.0
307.0
6?. 8
?1.6
78.8
77.5
1P. 8
69.5
31.3
35.2
187.5
30.11
73.7
"»1.7
76.-'
5u. n
22.7
11. 1
17.7
168.1
63.5
38.0
1.»15.2
72.7
22.8
19.9
99.7
8f .0
237.1
71. 8
oductKm wofl
Bar.
1963
008.2
13.3
85. 1
50.3
35.1
27.1
19.1
21.6
28.8
121.0
11.1
39.5
59.7
77.3
13.6
9.2
~
606.8
717.8
205.1
15.1
103.0
69. 1
7.7
20.5
31.5
10.0
127.5
18.7
23.0
53.6
61.0
39.0
979.U
53.1
13.6
99. 1
32.5
?8.1
12.2
18.0
17. 1
277.0
53. 1
51. 0
65. 1
68. 1
1P.T
62.3
30.14
31.9
177. 0
23. e
72.5
T3.2
Vl.7
52.1
1°.6
12.2
1 8.7
151.2
C1.5
36.8
1,181. 1
SP.3
21.0
37.3
S3. 3
69.2
13F. 1
29.9
•rl1
Apr.
1983T
121.2
13.2
85. 9
U9.6
36.3
27.9
19.9
26.2
30.0
131. 8
11.8
11.7
67.1
78.3
13.7
9.5
"~
611.9
251.3
208.3
15.6
105.7
70.8
"'.I
21.0
31.8
1B.1
128.5
16.8
23.3
53.5
65.3
10.0
987. 1
52.9
13. 6
100.2
32.1
59.5
143. 1
16.0
18.6
278. 8
52.1
55.5
61.3
68. P
IP. 8
63.2
31.0
32. 2
178.1
21. 1
72. 5
71. 0
73.0
52.9
20.1
12.6
19.3
151. 9
51.7
37.3
1 , 185.0
57. 1
20.6
36.5
81.2
71. 2
133.9
29.6
Bay
1983P
138.7
-
-
-
-
-
-
-
-
-
-
-
-
*
-
-
~
627.6
-
-
-
-
-
-
_
_
_
-
-
-
-
-
997. 6
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
_
-
-
-
—
-
~
—
1,209. 1
-
-
-
-
-
-
261
-------
_MC77JJ?RF
Iv.uril Inly I'JHO
Industry Series
Industrial Organic
Chemicals
2861 Gum and Wood Chemicals
2865 Cyclic Crurlcsand Intermediates
2869 Industrial Oryamc Chomicnls, N.E.C.
.e
mo^c^
V\
263
U.S. Department of Commerce
Philip M. Klutznick, Secretary
Luther H. Hodges, Jr.,
Deputy Secretary
Courtenay M. Slater,
Chief Economist
BUREAU OF THE CENSUS
Vincent P. Barabba,
Director
-------
USERS' GUIDE IN LOCATING STATISTICS BY TABLE NUMBER
|F 01 explanation of tuims, see appendix A)
1
2
3
4
b
0
'
8
i)
111
1 1
12
13
14
15
Hi
i ;
18
11)
20
21
22
23
24
25
Item
Number ot in.inul.irlui nn| establishments
1 mployment and pdyioll
Number of employees . .
Pdyioll
Supplemental labor costs
Production workers
Production woikei houis
Production woikei wages
SI MI -merits, r ost of mate n alb, and vdlue ddded
Vdlue ol shipments (4-diyit)
Product class shipments (b digit)
Product Mlipmenls (7-digil)
Vlilue , idded by m.iiuifiK ture
Cost ot riuitei uils
Cost of fuels and electric energy
Materials consumed by kind
I n v e n t o 1 1 e s
End of y o u r
Stage of fabt iration
Capital expenciituies, assets, rental pdymcnts, iind purchased services
New capital expenditures
UM d plant and e(|Uipment expenditures
r,M,y, ,,sset,
1 Ji 'pi e( i.lt 101 1
Retirements ot buildings and machinery
f{i'nt,il payments
Pui chased services
Speuah/ation
Coverage
4-digit industry statistics
By
Operating geographic
Historical ratios area
la 2
Id 1b 2
1a 1b 2
1 a 1 b 2
1a 1b 2
1a 1b 2
la 1b 2
1a 1b 2
1a 1b 2
la
1a 2
la 1 b
1a
1a
Detdiled infonnation shown
264
-------
4 ilitjit nulustty
Summaiy By
dtic! employment
supplemental size
'3.1 4
3d 4
3d 4
'3b
'3a 4
'3d 4
3d 4
3d 4
3a 4
1 .id 4
3d
3a 4
3d
3d, ' 3b 4
1 3d ' 3h
'Jh
'3b
'3b
'3b
'3h
3d
3d
statistics Con
By
industry and Materials
pioduct class consumed
specialization by kind
b.i
5d
5a
5a
5a
5a
5d
Sd
bd
7a
Bd
5 digit product class and 7-digit |)roduct statistics
Pioduct
Industry class by Histoncal
ptoduct Product geographic product
analysis shipments area class
5b, 5c
5b, 5c 6d 61) 6c
6a
bb
bb
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
2b
265
-------
Table ia. Historical Statistics for the Industry: 1977 and Earlier Years
ruat1
197^ Census
1!)7fa ASM6 •
1075 ASM -
1U/4 ASM
1S1/J AbM
19/<> < unsus-
19, 1 ASM
19/0 ASM
t'H.J ASM
iaoa ASM
1'»t>/ Consub
1 (6b ASMb
19M AbM- -
19f)4 ASM - - •
19f/t Ounsus -
VJ77 Census- •
1976 ASM
1»;5 ASM
1974 ASM -
1973 ASM
1(. ASM
I'JfjS ASM -
lab4 ASM
1 96 J Consus
1977 Census -
197f> ASM-
19/5 ASM --
1974 ASM - -
19/3 ASM- -
1972 Census
19/1 ASM -
19'0 ASM
1909 ASM-
1 Sb« ASM -
19o.' ,onsus -
1 96b ASM
1965 ASM- - -
1yb*l ASM -
1963 Census -
Com-
panies2
(no)
All icjl.tlilihtimfnt:,
With 20
employ-
ees or
Total more
(no ) (no )
All »t|[i[)loy««B
Num- Payroll
ber (million
(1,000) dollars)
I'mctui linn woikiHH
Num- Wages
ber Hours (million
(1,000) (millions) dollars)
Valutt
added by Value ol
manulac- Cost of ship-
lure materials merits
(million (million (million
dollars) dollars) dollars)
Lxpendlturen and
••••(•
New GIOSB
capital value of
expend- fixed
itures assets
(million (million
dollars) dollars)
tnd-ol-
year
inven-
tories
(million
dollars)
Milloi
Spe-
cial-
ization
(per-
cent)
Cover-
age
(per-
cent)
INDUSTRY 2861, QUM AND WOOD CHEMICALS
100
(NA)
(NA)
(NA)
(NA)
118
INA)
(NA
(NA)
(NA)
1/2
(NA)
(NA)
(NA)
229
119 37
(NA) (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
13') 41
(NA) (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
184 42
(NA) (NA)
(NA) (NA)
(NA) (NA)
24b 53
48 540
47 472
46 426
51 44 S
55 466
59 476
52 408
63 379
•SB 360
'i 7 35 0
b9 335
50 31 5
Cfl 32 1
64 324
58 327
38 78 38 9
37 74 35 0
37 67 319
42 78 34 0
41 86 33 5
47 94 33 5
41 82 28 5
42 84 26 8
47 93 25 8
44 87 24 2
46 80 23 1
38 79 214
43 88 219
50 101 22 4
54 108 229
1850 2053 391 3
1472 2108 3648
1302 1964 3142
1995 2208 4033
181 1 1766 3S54
1554 1759 332.3
1430 1447 279.4
1163 1440 281 7
1023 1300 2285
11/2 1148 2333
1008 1153 2159
992 1096 2087
926 112.3 2062
1023 1169 222.0
1003 1146 2129
27 0 (NA)
320 1846
126 1621
100 I486
152 2106
1 1 1 203 1
105 1679
89 185 3
B3 1528
137 1476
206 1382
66 (NA
44 (NA
4.9 1181
56 1152
657
712
764
846
574
522
497
393
476
468
46.3
435
46.4
48.8
537
76
NA
NA
NA
NA
70
NA
NA
NA
NA
73
(NA)
NA
(NA)
74
67
NA)
NA
NA
NA!
75
78
(NA)
M
(NA)
77
INDUSTRY 2865, CYCLIC CRUDES AND INTERMEDIATES
135
(NA)
(NA)
(NA)
(NA)
123
(NA)
(NA)
(NA
(NA)
1 I'l
(NA
(NA)
(NA)
120
191 127
(NA) (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
1/4 118
(NA) (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
1// 10/
(NA) (NA)
(NA) (NA)
(NA) (NA)
141 84
35 7 631 5
278 4418
2^ 8 406 1
? ' 6 365 0
29 5 348 0
282 3182
300 3159
30 2 293 fi
30 9 289 8
30 1 285 1
i(M) 2')l I
2U ^ 240 4
2« I) 232 3
28 2 2113
27 7 201 9
23 4 46 6 369 8
179 35 8 282 6
179 364 2424
184 383 2226
190 394 2071
187 384 181 1
200 417 1953
199 413 1 76 7
208 4'IB 1792
20 •> 422 164 1
,'<> i 41 / tVB
21) 1 42 (1 1 50 1
199 416 141 9
187 385 1285
109 386 1248
22144 34536 56370
1 798 7 2 956 6 4 677 7
1 3538 24426 3819.2
1 4653 2 0783 34133
1 1403 1 2660 2426.4
9297 1 1103 20496
965 4 1 037 4 987.6
R55 1 960 3 804 0
040 7 97f> 3 7BB 9
7746 9386 7161
/295 8745 6B6 8
/41 7 8263 656 a
682 3 788 5 1 466 3
621 1 6883 1 2896
6053 634 1 1 2128
443 1 (NA)
443 6 3 345 4
432.0 3111.4
319.9 2 504 3
200.8 2 356 3
1668 21748
27B 6 2 237 B
2832 20108
1404 1 8054
88 3 1 695 2
136 1 1 6126
88 4 INA)
81 8 (NA)
103.5 1 116.4
106.8 1 0478
8444
706.8
6138
62SO
3761
3560
371 7
3177
304 1
2770
261 B
24 '3
2325
2080
211 0
68
76
NA)
NA
NA
NA|
73
(NA
NA
NA
JNA
67
(NA)
NA
NA
(NA;
66
66
NA
NA
NA
NA
INDUSTRY 2869, INDUSTRIAL ORGANIC CHEMICALS, N.E.C.
388
(NA
(NA)
(NA)
(NA)
349
(NA)
(NA)
(NA)
(NA
339
(NA)
(NA
(NA)
343
569 346
(NAI (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
514 295
(NAi (NA)
(NA) (NA)
(NA) (NA)
(NA) (NA)
488 ^68
(NA) (NA)
(NA (NA
(NA) (NA)
464 241
1123 2 1087
1093 8592
1049 6303
1025 4896
1028 3324
1024 2486
1002 1407
104 2 099 7
101 b 0210
yii 6 925 4
95 1 844 a
96 7 833 4
91 6 7680
87 1 7140
85 5 677 3
707 14^7 1 2165
687 1390 1 0590
648 1297 9042
656 1348 8473
6G 1 1355 7781
645 1299 7130
638 1291 6495
664 1359 6291
o', / 137 4 5974
b36 131 8 5454
6httu products invonlorieb betwuen lieginniny and end of yttar
1lJData m vaiuo of shipments column represent value of work done rather than value ol shipments Consequently, formula for computing value added by manufacture was modified to
exclude any chanyo in inventories between beginning and end of year
MANUFACTURES—INDUSTRY SERIES
266
INDUSTRIAL ORGANIC CHEMICALS
-------
Table 2.
Industry Statistics by Geographic Area: 1977 and 1972
Geographic area
INDUSTRY 2861, GUM AND
WOOD CHEMICALS
United States
W«-.t North (..Mitral Division
S.fiilh All.inli. [ tivi'.Kin
Wtn.l Vinjinm
Last South Conical Division
Kontucky -
West Soulh Central Division
Arkansas
lexab
P,(< itic Oiviwon
INDUSTRY 2865, CYCLIC
CRUDES AND
INTERMEDIATES
Now * nyland Division
Rh d I-" ft
Connecticut
Middle Atlantic Division
N|tW
Pennsylvania
Fast North Central Division
Ohio
Illinois - -
Siu.lh Mi.mlu, Division
rWny'.iH )
W«sl Virijiiiirt - - ...
Smith t arultna
fast South Cwniral Qiv-siun
Ktjntu- tt - - - -
Alabama -
WHM South Central Division
Louisiana -----
Toxas - - - -
Paultt Division
C.alilornia
INDUSTRY 2669,
INDUSTRIAL ORGANIC
CHEMICALS, N.E.C.
Unltod StatGB ----------
New Englano Division
New Hampshire
Massachusetts
Rhode Island
i.onnecticul -
Mindle Atlantic Division
New fork
flew Jftr^cy - - ...
Pennsylvania - -
Las! North Centra! Division
r.rio
India1 ia - - - - - -
Illinois
Michigan - - -
VWst TJorlh Oerural Division
Mii-O'in - -
19/7
E1
-
1 I
-
E3
E1
-
-
-
-
-
-
'-
All establishments
With 20
employ-
ees or
Total more
(no ) (no )
lit 37
1 1
1 i
it
9 ')
1 1
7 2
16 2
J 2
181 127
6 2
2 1
2 1
12 6
42 30
14 9
13 10
16 111
-1 j
) .''
7 •>
7 5
8 7
1 1
? 2
4 4
3 3
13 10
U ',
569 348
2 £
10 5
4 3
13 8
39 23
73 45
23 13
31 17
6 .1
28 11
20 13
I ! 6
3 L
li ?
All employees
Num- Payroll
ber2 (million
(1,000) dollars)
4 8 54 0
(.(. (D)
AA ID)
AA (1 n
II <(>)
(,( (U)
AA (D)
AA (D)
02 1 8
BB (D)
367 bJlt.
BB (D)
CC (D)
BB (D)
28 446
123 2377
16 238
FF (D)
:< h 4t> '!
0 / 7 ')
(,( (II)
(.(. (U)
FF (U)
EL (D)
Cr (D)
BU (D)
AA (D)
EE (D)
BB (D)
27 57 !>
Bil (U)
1123 2 1087
BB (D)
12 215
CC |D)
EE (D)
42 724
77 138 1
43 722
29 520
CC IO)
20 32 «'
76 141 B
l.L ID)
f f (D)
f t |D)
A/. (D|
Production workers
Wages
Number Hours (million
(1,000) (millions) dollars)
38 78 38 9
(II) (D) (I))
(I I) (D) (U)
|l>) 1)1 (D)
(11) 0 ill)
(0) D) |D)
(D) (D) (D)
(D) (D) (D)
01 03 14
(D) (D) (D)
23 4 48 6 388 8
(D) (D) (D)
(D) (D) (D
(D) (D) (D)
19 35 28 4
86 167 141 8
10 22 141
ID) (D) (D)
17 34 <"J I
0 4 (I I) 6 II
(D) (D) (D)
(D) (D) (D)
(D) (D) (D)
(D) (D) (D)
(D) (D) (D)
(D) (D| ID)
(D) (D) (D)
(D) ID) (D)
(D) (D) (D)
16 34 27 rj
ID) (D) (D|
707 1457 1 216.5
(D) D) (D)
0 ' 15 124
ID) (D) (D)
(D) (D) |D)
24 51 33 0
51 108 836
27 53 41 2
16 36 30 6
(D) |D) ID)
13 23 197
47 90 795
ID) |D) ID)
(D) (Dl ID)
(D) ID) ID)
ill) (D) (D)
Value
added by
manu- Cost (
facture materia
(million (millio
dollars) dollar
New
capital
ex-
it Value ot pend-
s shipments ilures
n (million (million
) dollars) dollars)
185.0 206 3 381 3 27 0
(D) (D) (D) (D)
(D) (D) (D) (D)
ty
D)
i li) ii)
D 0 0)
D D) D)
(0) (D) (D) (D)
(D) (D) (D) (D)
47 44 9,0 07
(D) (D) (D) (D)
22144 34838 68370 443.1
(D) (D) (D) (D)
(D) D) (D) D)
(D) D) (D) D)
1425 1000 2423 (D)
605 6 805 5 1 402 9 (D)
1108 1782 2886 (D)
(D) (D) ID) (D)
1i)64 26113 42.) 7 404
210 3D 6 58 U 20
ID) (D) (D) (D)
(D) (D) (D) (D)
(D) (D) (D| (D)
(D) (D) (D) D)
(D) (D) (D) D)
(D) (D) (D) (D)
(D) (D) (D) (D)
(D) (D) (D) (D)
(D) (D) (D) (D)
4405 7169 1 1434 582
(D) (D) ID) (D)
104757 139488 242328 31628
(D) (D) (D) (D)
484 759 1224 33
(D) (D) (D) (D)
(D) (D) (D) (D)
2251 2262 4456 (D)
5123 8108 1 3207 596
171 2 3702 5520 223
2759 3762 6342 504
(D) (D) (D) (D)
1771 1841 3548 304
401 9 348 9 736 7 917
(D) (D) (D) (D)
(D) (D) (D) (D)
(D) (D) (D) (D)
(D) (D) (D) (D)
1U72
Value
added by
All manu-
employ- tacture
ees2 (million
(1.000) dollars)
5.9 166.4
CC (D)
(NA) (NA)
AA H
tt U
EE D
AA (D)
(NA) (NA)
(NA) (NA!
AA (D)
28.2 929.7
BB (D)
CC (D1
AA (D)
26 491
63 2340
1 8 503
EE (D)
26 765
CC (U)
CC D)
CC D1
EE (D)
CC (D)
CC (D
(NA) (NA)
CC (D
cc (D;
AA (D)
EE (D)
AA (D)
102.4 4 988.0
AA (D)
AA (D)
CC (D)
ff (D)
61 1586
131 448 2
20 329
31 996
EE |D)
FE (D)
FF (D)
BB (D;
AA (D)
EF D)
(NA) (NA)
MANUFACTURES—INDUSTRY SERIES
267
INDUSTRIAL ORGANIC CHEMICALS
-------
Summary Statistics for the Industry: 1977
Muni
Primary product specialization ratio1
w rn 1 14 In «
With 20 to 99 employees - •
All employees, average lor year - - - -
Payroll lor yeai. all employees
Avuruyu lor yuar
March
May
August ...
November - ---.. - . . _
Hours
January Id March - - -
A), III Irj luiM'
it.l/ in ''< pli'tnlicf
i JUOfjt f I'' iJcct-'tnbor
W.KJlt-,
( u-,l ut iMdiuiuls utc - - - - - -
Mdt'-Tiais parts container*, ett, consumed - - -
Hosn.o, - -
1 LHiK nl'1'.UHU.-tl
i'uft h.iscd tjluclrit- t'norgy
( ,onlfdi I vvotk
V.ili.t '-1 sliii»i'.-Mh, incluiliin) M'Miln-
Vrtlu*1 ul M-balus - - -
V.tlu-i .nli Jo! hy rnanutai tuiu
M,»nut-i, tuM'f1, inv-riloriUS
h.-yinnin.) < I yi-m
f mi ,ln (! pit K|U< Is
W(,4 in pioi uss
Materials supplies, luoi, ut<, -
f m.shed products - - - - ...
Matermlb supplies, fuel, etc - --------
Capital expenditures for plant and equipment- •
New capital expenditures - - -
N..-W buildings and other structures
Ni'vv machinery and equipment
Usf,'u capital expenditure. r> - - - - -
Unit ol
mua
iiUCO
percent -
number
00 • • - - -
do
do
1,000 •
mil dol
1 01)0
do -
do -
do
do
do • -
do
do
Uo
mil dol
do
do
do --
do - -
do
do
du
do
tin
do
do
do
do - -
do
do • - - •
do
do - • -
do - • - -
do • - - -
ao
do -
do - - -
chtiinK ills
(SIC JUbl)
76
6/
ay
Ot
24
1 3
48
540
•J 11
36
39
39
3 7
7 y
1 8
?0
,'0
1 ')
3liU
20') 3
1796
1 6
IH 9
A 7
0 b
39 1 1
3 f
IH'jO
1, ll>
4(1 h
/ '1
?l) /
6& 7
404
1 6
238
347
?70
108
162
7 /
(.yUll 1 IllddS Itnd
inluimiidiiitus
(SIC 2866)
68
67
1 91
64
SB
69
357
631 5
2.1 4
J3 b
21 7
233
23 1
11 9
11 9
1 1 4
11 4
3698
3 4536
2 9250
1136
271 8
113 1
30 1
!> 63/0
12/2
2 2144
/II4 2
3'j() 9
l(l') /
2b7 7
844 4
391 7
155 8
2969
4486
443 1
526
3905
55
lllllu'.llllll OIUIIMI!
(.homii ills n «i i
(SIC 28b9)
69
84
569
223
164
182
1123
2 1087
70 7
607
702
71 5
71 1
359
365
')(• 7
366
1 2165
13 9488
11 405 5
4205
1 3939
4528
2760
24 232 8
496 1
10 476 7
2 591 5
1 2473
474 7
8694
2 942 7
1 4197
494 1
1 0289
3 1895
3 1826
4477
2 7149
269
( i- presents zero
iti'jn standards
(U) Withheld to avoid disclosing operations of individual companies (NA) Not available
) Noi applicable (Z) Loss than 50 thousand doiletr-j or hours, under 50 employees
nee Not elsewhere classified (S) Withheld because estimate did no
urits raiio ol primary product shipments to total produc
onts ratio ul primary products shipped by esiablishmen
nships art1 not meaningful because of predominance o
m purcunlaijt uxact porcontaiju withhold to avoid disc
shipmunis (pntnary and secondary, excluding miscellaneous receipts) for establishments classified in industry
s classified in industry fo total shipments of such products by all manufacturing establishments, wherever classified
miscellaneous rucoipls, particularly receipts for contract and commission work on materials owned by others
osing operations of individual companies
than
iilun of production ralln
iin>i!ij( i', I'luuniofit'b tjciwutfn tHtyin'itng mid und ol yoai
i.ii/i tot vaiuu of shipment!, reprasunl vafuu ol work donu ra their than
i.'i huiwuuit buginmny and und ol yuar
-out dtyii industry totals lor all items including establishment counts art) not equal to sum of b-digit subindustry figures due to difficulties in classifying a few establishments at submdustr
valuu ul stnpniuntii Conauquunlly formula for Lonipuliny value added by manutacluru wati moxlified to uxclucto any t hang
value of shipmunts C'Onsoquently formula for computing value added by manufacture was modified to exclude any Chang
MANUFACTURES—INDUSTRY SERIES
268
INDUSTRIAL ORGANIC CHEMICALS
-------
Table 4 Industry Statistics by Employment Size of Establishment: 1977
Industry and employment size class
INDUSTRY 2861, GUM AND WOOD CHEMICALS
i st dt)li*>hmi tills with an avtuaqo ot-
1 to •! ««iiploy,«js
'. lu 'Jumpluymr,
10 lu I'l fimploymis
.'() I-, -I'l finpluytius
M) lu 'i'i tmifiloyuus
100 lu 00 lo 999 employaos - - - - -
1 o';o lo 2 *HJ9 umplo/ous
^.Suu ompiOyoos or more - ...
t ov«f(i i by .KiminiMrativo record;,* - - -
E1
(H
1 4
t'l
M)
E9
E4
E4
EO
t4
t.4
F2
LO
All
estab-
lish-
ment
(no)
119
4 'I
H
4
0
0
2
I
';•!
191
22
17
25
34
24
29
23
11
6
35
569
I!/
56
50
83
81
80
46
30
22
4
130
All employees
Payroll
Number (million
(1.000) dollars)
4.8 54.0
I) 1 10
01 10
0 ! 2 ')
OS 4 /
I) I 62
(.1 21 (30 5)
(H) (D)
ID) «')
0 J .' 1)
35.7 831.5
<) (D)
02 03 15
23.4 46.6 389.8
(Z) W 03
01 02 11
02 04 27
07 15 100
11 23 149
26 53 36 9
47 98 75.4
50 97 77 2
(90) (175) (1514)
02 03 22
70.7 145.7 1 218.5
01 03 17
03 05 37
04 09 58
16 34 21 6
34 69 50 6
82 172 1267
106 22 8 1805
133 272 2368
(32 6) (66 7) (589 3)
(D) (D) (D)
03 06 50
Value
added New End-ol-
by Value of capital year
manu- Cost of ship- expend)- mven-
tacture materials ments lures tones
(million (million (million (million (million
dollars) dollars) dollars) dollars) dollars)
185.0 205.3 391.3 27.0 85.7
32 42 74 (78) 1 :i
41 63 104 (O) 13
6 3 123 100 11 8 .14
170 16 7 JJ3 11 B2
266 299 558 (175) 107
(1278) (1359) (2654) (O) (408)
(D) ("> (") ") (D
(0) (D) (D) (D) (D)
60 76 136 1 1 25
2 214.4 3 453.8 S 637.0 443.1 844.4
07 33 50 05 07
12 20 3 215 10 24
184 334 513 60 65
618 1592 2422 74 262
968 2135 3042 230 415
240 6 395 3 628 6 55 1 109 2
462 0 940 1 1 390 4 80 6 237 8
6504 9792 1 6325 112 1 1747
(6625) (7093) (13613) (1574) (2415)
105 194 298 27 4.5
10 475.7 13 946.8 24 232.8 3 162.6 2 942.7
136 217 357 26 45
259 386 640 45 63
460 689 1186 69 145
1806 2596 4406 683 471
4984 7527 1 241 3 989 1761
10233 15401 25392 1866 3627
1 652 5 2 730 9 4 368 7 732 4 467 1
18745 2 339 7 41787 265 8 4335
(51600) (61968) (112561) (17944) (14369)
(D) (D) (D) (Di ID
29 1 37 3 66 4 72 62
Rttpiu^entb zero (O) Withheld to avoid disclosing operationb of individual Lonipaniett Data for this item are included in (igurtti in parentheses above (NA) Not available nee Not
Lt.buwhuru Udibihwd |S) Withheld because estimate did not rueut publication standards (X) Not applicable (Z) Less than 50 thousand dollars or hours, under SO employees
'Payroll and ^aies data for small single-unit companies with up to 20 employees (cutoff varied by industry) ware obtained from administrative records of other government agencies rather
man Irom census report forms These data were then used in conjunct'on with industry averages to estimate the balance of items shown tor these small establishments This technique was also used
tor a small number of other establishments whose reports were not received at time data were tabulated The following symbols are shown where estimated data based on administrative records
data auouni for 10 percent or more of figures shown E1 —10 to 19 percent, E2--20 to 29 percent. E3—30 to 39 percent, E4—40 to 49 percent, E5—50 to 59 percent, E6—80 to 69 percent,
E7-/0 to 79 percent, E8—dO to 89 percent. E9—90 to 99 percent EO—100 percent
2Report forms were not mailed to small single-unit companies with up to 20 employees (cutoff varied by industry) Payroll and sales data for 197 7 were obtained from administrative records supplied
by other agencies of the Federal Government These data were then used
-------
Industry Statistics by Industry and Primary Product Class Specialization: 1977
Indus-
iry or
pro
ifurt
i-Oilc
2tibl
/lib 11
2B61S
2865
28651
26652
?8b5 i
..'U655
28b9
28(193
?W>')4
.-bi/l'j
2Bb9b
1her industrial organic > tmmicals, I. n i
1 •.Mblishmunts witli this pinilm t ( las-, finin,iry
[ Mdblishmonts with /5 pen ent spot alizalion or rnoru in class
Misi_elldnoous Brid use chemicals and chtjmi! al products.
except urea
libtabiishments with this product class primary
Establishments with 75 percent spec alization or more in class -
Miscellaneous cyclic and acyclic chemicals and chemical
products
t Mablishments wilh this product class primary - - - . -
t stablishments with 75 percent specialization or more in class -
All
establish-
ments
(numnm)
1 I'l
lub
9
7
46
36
1
-------
Procedures Used to Develop the 1978, 1979, 1980,
and Projected 1990 OES Survey-Based Matrices
Introduction
The Bureau of Labor Statistics converted the National
industry-occupational matrix from a Census base to an
Occupational Employment Statistics (OES) survey base in 1981.
This paper presents a brief overview of the general procedures
established to develop OES survey-based matrices and describes
the detailed steps used to develop the first National matrices
based on OES survey data.
In early 1982, a bulletin will be published presenting the 1973
and 1990 matrices. The 1980 and 1990 matrices are the basis of
the analytical statements on employment outlook and job openings
for the 1982-83 edition of the Occupational Outlook Handbook.
OVERVIEW
Because the OES surveys are conducted on a three-year cycle in
which each covered industry is only surveyed once in each cycle,
a matrix developed for any given reference year must be based on
survey data for three different years. Given this data
constraint, a matrix for any given year should most accurately
describe occupational employment by industry if it were based on
data that were at most one year from the reference year. For
example, OES survey data for 1978, 1979, and 1930 should provide
the most reliable data to construct a 1979 matrix based on OES
survey data.
The timing in which National OES survey data become available and
the established cycle for production of National occupational
projections and publication of the Occupational Outlook Handbook ,
however, have resulted in the development of procedures in which
matrices are developed for specific reference years prior to the
availability of the most reliable data that will become
available. Survey data are generally not available until late
December of the year following the survey reference year. For
example, 1980 OES survey data will not be available until
December 1981. Program commitments, however, required that data
for 1980 be presented in the Occupational Outlook Handbook that
was completed in mid-1981 and which will be published in 1982.
Because staffing patterns do not change significantly over a
three-year period> procedures were developed in which a
preliminary 1980 matrix uas developed using the survey data
available at the time the employment estimates presented in the
Handbook were developed.
The following is a general description of the system that has
been designed for developing OES survey-based matrices. Three
base year or current matrices will be produced for every
271
-------
OES Survey-Based Matrix Procedures-- 2
reference year. They are to be titled I, Preliminary; II,
Revised; and III, Final. The preliminary matrix will be based on
OES survey data for the three years prior to the reference year.
The revised matrix will be based on OES survey data for the
reference year and the two previous years. The final matrix will
be based on OES survey data for the reference year, the previous
year, and the year following the reference year. The 1979-1
matrix, therefore, is based on OES survey data for 1976, 1977,
and 1978. The 1979-11 matrix uses 1977, 1978, and 1979 survey
data. A 1979-III matrix will be constructed using 1978, 1979,
and 1980 data after the latter become available in December 1981.
To develop employment data for each reference year's matrix
(whether it is a I, II, or III), the staffing patterns from the
OES survey data are applied to actual annual average industry
employment totals from the Current Employment Survey—CES—
(ES-202 data for industries for which CES data are not available)
for the reference year. To develop a matrix that covers all
uorkers, the OES survey-based data are supplemented with data for
industries not covered by the OES surveys. Estimates of
occupational employment of self-employed persons and unpaid
family workers are also developed and added at the total all
industries level.
DETAILED DESCRIPTION OF PROCEDURES USED TO DEVELOP THE FIRST
CURRENT AND PROJECTED NATIONAL OES SURVEY-BASED MATRICES
The first National OES survey-based matrices uere developed
during 1980 and 1981. Matrices were developed for the years
1978, 1979, 1980, and projected 1990. Current or base year
matrices produced include a 1978-11, 1978-III, 1979-1, 1979-11,
and a 1980-1. For industries covered by the OES surveys, the
1978-11 and 1979-1 have the same staffing patterns and the
1978-III, 1979-11, and 1980-1 have the same staffing patterns.
Staffing patterns for the nonsurveyed sectors and the
occupational distribution of self-employed persons and unpaid
family workers are the same for the three matrices for each
reference year, whether a I, II, or III matrix/ because the
actual source data for the reference year ware available at the
time the matrix was developed.
Current Year Matrices C1978. 1979. and 1980)
Industry Controls
In all current years, industry controls for wage and salary
workers in the 378 industries in the National survey-based
matrices are annual averages. Most of the data are from
three-digit SIC industry estimates from CES series; data for
railroads, education, Federal government, State government, and
272
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OES Survey-Based Matrix Procedures-- 3
local government are on a two-digit SIC basis. Wage and salary
workers in all five of the current matrices discussed in this
paper use CES estimates benchmarked to ES-202 data in the spring
of 1981. These CES data will be published in August 1981 as
Supplement to Employment and Earnings Revised Establishment Data.
In some cases, detailed industries are disaggregated from CES
series that were combinations of two or more three-digit SIC
industries. In these cases. ES-202 data for 1978 were used to
disaggregate the 1978 CES data and ES-202 data for 1979 were used
to disaggregate the 1979 and 1980 CES data. When the 1980 ES-202
data become available, they will be used to disaggregate the 1980
CES data, where necessary, for the 1980-11 matrix. The ES-202
data for 1978 will be published in the fall of 1981 by the
National Technical Information Service (NTIS) and comparable data
for 1979 will be published by NTIS in early 1932.
In a few cases--agricu1ture, forestry, and fishing and private
households--industry employment controls were obtained from the
CPS . These data are published each year in the January issue of
Employment and Earnings following the reference year.
1978 Matr i ces
1978-11 Matrix. The 1978-11 matrix included data from
Occupational Employment Statistics (OES) surveys on wage and
salary worker staffing patterns in State government and local
government collected in 1975 (no later data were available);
transportation, communications, and public utilities industries
collected in 1975 and 1976; trade industries, Federal government,
hospitals, and railroads collected in 1976; manufacturing
industries collected in 1977; and nonmanufacturing industries
collected in 1978.
A combined data file of all the OES survey staffing patterns
within the scope of the 1978-11 matrix was produced and
benchmarked to the 1978 industry controls. This benchmarking
step was necessary for two reasons: (1) OES survey data
represent observations taken in the spring (second quarter) of
the survey'year, and (2) the combined OES survey file represents
observations in different years; benchmarking theoretically
unifies the data to a single year. Because of the differences
that can occur as a result of benchmarking to annual averages for
a single year, different values for any single
occup ation/industry cell are usually recorded in the matrix and
in the actual OES survey. Wage and salary worker staffing
patterns for the nonsurveyed industries--agricu1ture, forestry,
and fishing; education; and private households--which were
developed from the Census-based matrix and the CPS were also
inputed to this combined data file. Details of the development
of the estimates for the nonsurveyed ""Actors are given in a Irter
section of this paper.
273
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OES Survey-Based Matrix Procedures— 4
Data on employment for some detailed occupations in the OES
survey-based matrix are not collected in some OES surveys,
generally because employment is believed to be too small to
develop reliable survey estimates. Employment in such
occupations, however, is included in a broader category in the
OES survey, generally in a residual occupation such as "all other
professional uorkers." For many of these occupational cells, a
procedure was developed to disaggregate an employment estimate
from the appropriate OES survey data based on employment for a
similar occ upa t i on/i ndust r y cell in the Census-based matrix. \_/
For some occupations included in some OES surveys, however, no
procedure was believed to be adequate to disaggregate data for
industries in which the occupation was not included in the
survey. In such cases, available OES survey data were collapsed
into the appropriate residual category in the OES survey-based
matrix.
In some cases, two or more detailed survey occupations were
collapsed into a single occupation that had a Census-based matrix
equivalent. In these cases, sufficient information or knowledge
was lacking on which to make employment estimates for cells that
had not been surveyed and for which analysts felt there should be
employment. For other occupations, collapsing survey data to the
comparable Census-based matrix occupations enabled analysts to
dissaggreg ate employment estimates from the survey-based matrix
residuals. In this manner, detailed employment information for a
number of specialized kinds of compositors, collected only in the
printing industry, was suppressed to the broad title of
compositors, which was then disaggregated from the residual all
other crafts workers for the missing cells. £/
Once the wage and salary worker portion of the matrix had been
developed, the matrix was listed off in two forms: industry by
occupation and occupation by industry (transposed matrix). Staff
analysts examined the data to identify cells that were
inconsistent with their knowledge about an industry or an
occupation. The analysis concentrated on occupation/industry
cells for which employment estimates were developed by
disaggreg ation procedures.
For some occupations, analysts who reviewed the matrix believed
that employment did exist in industries that showed no employment
and recommended that employment be added for these matrix cells.
To implement these recommendations necessitated further
disaggregation of survey-based matrix residuals. Frequently,
more than one occupation had to be disaggregated from the same
residual to account for the recommendations. In these cases,
three policies were generally followed before the changes in the
matrix were made. (1) If the sum of the recommended changes did
not exceed the appropriate residual, the changes were accepted.
(2) If the sum of the recommended changes did exceed the
appropriate residual, the recommendations were prorated so that
each cell recommended for ~hange received a portion of the
274
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OES Survey-Based Matrix Procedures— 5
residual. (3) If the designated residual contained no
employment* updates were disallowed. One notable exception was
made to the latter procedure for data processing machine
mechanics. For this occupation, emoloyment estimates were
disaggregated, to the limits of the residuals, from all other
mechanics, all other engineering technicians, and all other'
technicians, because it was believed that these workers could
have been included in all three categories in the OES surveys.
A very detailed procedure was followed to review all update
recommendations received from the analytical staff.
Recommendations that were accepted were incorporated manually
into the matrix. Appropriate residuals were manually adjusted.
A total of 4,776 manual updates were made (including updates to
residuals). Most updates (about two-thirds) were less than 50
persons in size. .3_/
The final step in developing the current employment estimates was
to add the separately developed estimates of self-employed
persons and unpaid family workers to the updated matrix by
detailed occupation at the total all industries level. Details
of the methods used to develop these estimates are contained in a
later section of this paper.
19 78-III Matrix. This matrix and the 1979-11 have the same
staffing patterns. The detailed occupational employment values
are different only because of the different industry controls
used in the two years. A detailed explanation of the development
of the staffing patterns for the 1978-III matrix is given below
in the section discussing the 1979-11 matrix.
1979 Matr i ces
1979-1 Matrix. This matrix was developed by first replacing the
detailed wage and salary worker occupational employment data for
the nonsurveyed sectors with 1979 estimates and then applying the
1979 industry controls to those industries in the 1978-11 matrix
where wage and salary worker staffing patterns were based on OES
survey data. Detailed occupational employment estimates of
self-employed persons and unpaid family workers were prepared for
1979. Because the 1979-11 matrix was prepared immediately after
the 1979-1 matrix, the 1979-1 was not used for any substanative
an a 1ys i s .
1979-11 Matrix. This matrix, which has the same' staffing
patterns as the 1973-III matrix, includes data from OES surveys
of hospitals and railroads collected in 1976 (no later data were
available), manufacturing industries and Federal government
collected in 1977, nonmanufacturing industries collected in 1978,
and balance of nonman uf ac t u r i ng industries collected in 1979. _£/
Balance of nonmanufacturing was a new designation in 1979,
resulting from the combination of surveys, some of which had been
conducted in 1975 and others in 1976. Included are
275
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OES Survey-Based Matrix Procedures-- 6
transportation, communication, and public utilities; wholesale
and retail trade,' State government; and local government.
Although a survey of employment in educational services
establishments was conducted for the first time in 1979, summary
data were not available at the time that matrix production began.
Consequently, employment estimates for education were developed
at the National level from secondary sources, as explained in a
later section of this paper.
Estimates from the 1977 and 1978 OES surveys, along uith
estimates from the 1975 and 1976 OES surveys, had previously been
used to build the 1978-11 National survey-based matrix. The
simplest method of producing the 1979-11 matrix was to replace
the 1975 and 1976 data with 1979 data for the same industries,
leaving the 1977 and 1978 surveyed industry staffing patterns
intact. Twenty-four new occupations, 12 of which were in the
education survey, that were added for the 1979 round of surveys*
were collapsed back to the appropriate survey occupations that
appeared in the 1975 and 1976 rounds. In order to duplicate the
matrix parameter file, these collapses were done on an industry
by industry basis. The application of 1979 industry annual
averages from the CES benchmarked all sectors to 1979 employment.
Since the 1978-11 matrix that was used in this procedure had
already been updated, only the new 1979 estimates were reviewed
and updated. The basis for these updates to the new survey data
was the updates for the same cells' in the 1978-11 matrix.
Similar values' were used, to the limit of the appropriate
residuals. Manual calculations of the affected residuals were
incorporated also.
Employment estimates for 1979 for the nonsurveyed sectors of
agriculture, forestry, and fishing, education, and private
households were developed and added. Occupational employment
estimates for self-employed persons and unpaid family workers at
the all industries level (the same as in the 1979-1 matrix) were
added to the matrix.
The wage and salary worker portion of this 1979-11 matrix for OES
survey covered industries was benchmarked to 1978 annual average
industry controls from the CES to produce the 1973-III matrix.
Nonsurveyed sectors and s e 1 f -enp 1 oyed persons and unpaid family
workers for 1978 were added. The 1 9 7 8 - 1 1 1 matrix became the base
year for the 1990 projected matrix.
1 980 Matr i x
for the 1979-1
employment data
276
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QES Survey-Based Matrix Procedures-- 7
workers were used to benchmark the staffing patterns from the
1979-11 matrix to preliminary 1980 staffing patterns. Detailed
1980 occupational employment estimates of self-employed persons
and unpaid family workers* developed separately> were added.
Thus, the wage and salary worker staffing patterns in the 1 9 7 8 -111 ,
1979-11, and 1980-1 matrices are the same, having been based on
the same set of OES survey rounds.
Employment estimates from the 1980-1 matrix will be used in the
1982-83 edition of the Occupational Outlook Handbook .
Nonsurveyed Sectors
Occupational employment estimates within industry sectors not
covered by OES survey data—agriculture, forestry, and fishing;
education; and private households — were developed at the 2-digit
industry level and incorporated into the matrix estimating system
as data files, just as if they had been surveyed. S./ The primary
inputs in developing these estimates were the CPS and the 1978
National Census-based matrix.
Aor iculture. Staffing patterns for agriculture, forestry, and
fishing are based on patterns for private wage and salary workers
in the Census-based matrix and the CPS. Using the private wage
and salary worker patterns eliminated the double-counting of
Federal, State, and local government workers employed in these
industries, who were already counted in the detailed government
industries.
Data from the 1978 Census-based matrix industry, agricultural
production, was on a 1967 SIC basis. To use these data in the
OES survey-based matrix, which is on a 1972 SIC basis, the
Census-based matrix data was divided into the two detailed
survey-based matrix industries agricultural production, crops,
and agricultural production, livestock. This distribution was
made on a 70/30 basis, as a result of discussions held with
officials of the Department of Agriculture. All survey-based
matrices for the years 1973-1980 reflect this percentage
distribution. The staffing pattern in the 1978 Census-based
matrix industry, agricultural production, was used for both OES
survey-based matrix industries, except for an adjustment to the
total employment of athletes in the two survey-based matrix
industries to reflect the 80 percent of total athletes in
agriculture in the Census-based matrix who were assumed to be
horse trainers in the survey-based matrix industry, agricultural
production, livestock. An 80/20 adjustment also was made to the
control value from the Census-based matrix value for
veterinarians to reflect the greater proportion of these workers
who would be expected to be found in agricultural production,
livestock. After these adjustments, all other cells were forced
to the control totals from the CPS for farm workers and for total
wage and salary workers for all detailed agriculture, forestry,
and fish ng industries.
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OES Survey-Based Matrix Procedures-- 8
Educational Services. Occupational employment estimates in the
educational services sector were based on the 1978 Census-based
matrix staffing pattern for all wage and salary workers,
including
government
industry
employment
estimates
estimates
educat i on
private industry and Federal, State, and local
workers. jS/ Government workers were included in this
because of their significance to total education
and because of the need to generate employment
for education separate from the much larger employment
for the government sectors. In these matrices,
workers are not included in the estimates for State and
local government. A few further disaggregations of occupations
were made based on limited data from one State's OES survey in
1976. _7/ These occupations were refined using ratios from that
survey and included college teachers, graduate students, and
extension service specialists from college and university
teachers; librarians and audio-visual specialists from
librarians; three kinds of file clerks; four kinds of food
service workers; and a number of other detailed survey
occupations, a complete list of which is shown below.
Census-Based Matrix Occ.
Biological scientists
Eng . and sci . tech., nee
Therap i sts
Technicians, nee
Teachers, college & univ
Librarians
Sales workers
Computer operators
Bookkeepers
File clerks
Receptionists
Misc. clerical workers
Foremen, nee
Survey-Based Matrix Occ.
Biological scientists
Medical scientists
All other engineering techs.
Science technicians
Speech and hearing clinicians
Physi. cal therapists
All other therapists
technicians
assts., library
voc. ed. & train.
college
ass i stants
All other
Techn i cal
Teachers,
Teachers ,
Graduate
specialists
Extension service
Librarians
Audio-visual specialists
Sales clerks
Sales reps., agents
Computer operators
Peripheral equip, operators
Accounting clerks
Bookkeepers, hand
File clerks
Personnel clerks
Admissions evaluators
Receptionists
Switchbd. ops./receptionists
Mail clerks
General clerks, office
All other off. clerical wkrs.
Supervisors, nonworking
SBM Code
10040601
10040602
10081898
10081899
10101803
10101804
10101810
10141404
10141405
10202001
1 0202002
10202003
10202004
10242401
10242402
30001802
30001899
40040601
40040602
40060601
40060603
40062601
40062602
40061603
40064802
40064803
40063402
40066312
40066393
50040003
278
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OES Survey-Based Matrix Procedures-- 9
Supervisors, nonwkg., service 70200001
Craft workers, nee Ma int. repairers, gen. util. 50144821
All other skilled workers 50144899
Cooks Cooks, short order 70040802
Cooks» institutional 70040804
Waiters and waitresses Hosts and hostesses, rest. 70041601
Waiters and waitresses 70041602
Food service workers, nee Kitchen helpers 70041802
Fd. prep, wkrs., fast food 70041804
Pantry, sandwich prep, wk. 70041805
All other fd. service wkrs. 70041899
Misc. laborers Helpers, trades 80002833
All other unskilled wkrs. 80002899
Based on information available from the National Center for
Educational Statistics (NCES) and other secondary sources, five
cells were fixed in the 1978 matrices: Elementary school
teachers; technical assistants, library; janitors; secretaries;
and typists. All other cells in the educational services sector
uere forced to the 1978 industry control. The 1978 pattern was
used to developed the 1979 and 1980 estimates.
P r i y.a t.e Households. For each year's OES survey-based matrix, the
CPS annual average employment for each of the five detailed
private household worker occupations was used as a fixed cell.
The remaining occupations in the private household industry were
developed by forcing the re'mainder of the CPS annual average
industry employment into a distribution based on the private
household industry in the 1978 Census-based matrix.
Uith the addition of the nonsurveved sectors to the surveyed
sectors? total wage and salary worker matrices were produced, bv
occupation and industry.
Self-Employed Persons and Unpaid Family Workers
Estimates of occupational employment of self-employed persons and
unpaid family workers were developed only at the total all
industries level, rather than by detailed industry as in the
Census-based matrix, because the development of such data would
have produced very unreliable estimates. The general procedure
was to develop employment estimates of self-employed persons and
unpaid family workers for each detailed Census-based matrix
occupation and then distribute the employment to related OES
survey-based matrix occupations.
The 1978 Census-based matrix was the primary source of data used
to develop estimates of self-employed persons and unpaid family
workers. Data in the 197S Census-based matrix, however, were
modified for some occupations where the relationship of
self-employed persons and unpaid family workers to total
employment were out of line with trends over the 1971-78 period,
279
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OES Survey-Based Matrix Procedures —10
based on CPS data. To develop estimates for 1979 and 1930,
trends in the relationship of self-employed persons and unpaid
family workers to total employment over the 1971-80 period were
used to modify the 1978 ratios. These ratios uere applied to CPS
total employment for each occupation in these years to develop
estimates of self-employed persons and unpaid family workers.
The resulting data uere forced to agree with the CPS 1979 and
1980 annual average employment estimates for each class of
worker .
The employment totals for self-employed persons and unpaid family
workers in each Census-based matrix occupation were distributed
to OES survey-based matrix occupations. A list of QES
survey-based matrix occupations that were related to the 400
Census-based matrix occupations was developed. Analysts studied
these relationships and distributed the Census-based matrix
occupational control totals to OES survey-based matrix
occupations. Some occupations uere a one-for-one match. For
other occupations, however, a distribution was made based on
limited information. One of the following procedures was used by
individuals making the estimates for each occupation: (1) The
entire Census-based matrix employment of self-employed persons
and unpaid family workers was distributed to related OES
survey-based matrix occupations based on the distribution of wage
and salary workers in those ocupations in the OES survey-based
matrix; (2) The entire Census-based matrix employment for each
class of worker was distributed on a judgment basis to selected
OES survey-based matrix occupations to which it was related; (3)
The entire Census-based matrix employment of self-employed
persons and unpaid family workers was placed in an appropriate
OES survey-based matrix occupational residual; and (4) Any
combination of the above that made sense in terms of the
analyst's knowledge of the specific occupation(s) .
In using these procedures, the analysis was focused on the 1978
data and then similar procedures were used for 1979 and 1980 for
each occupation. In general, the most common procedure followed
was to distribute the control totals for seIf—emp1oyed persons
and unpaid family workers in the Census-based matrix by the
distribution of wage and salary workers in related OES
survey-based matrix occupations. Adjustments were made in cases
where this distribution did not make analytical sense. For
example, no estimate was made for self-employed judges or
self-employed claims takers for unemployment insurance benefits,
even if the Census-based matrix occupation where these workers
uere included had some self-employed persons.
Summa ry Tables
After employment estimates of self-employed persons and unpaid
family workers were developed, they were added to the wage and
salary worker employment estimates to produce total employment by
occupation at the total all industries level.
280
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3_t.- i c os M 9 9 G }
The 1993 cccupat;3nai projection-- were developed as part of the
Bureau's e c c ~, eric ard employment projections efforts* which
include projections of the la bo.- force, gross national product*
productivity,. industry output/ and industry employment. The
Bureau developed three alternative 1990 projections* each based
on different assumptions concerning such factors as labor force
growth, defense expenditures, u n ? T 2 I 7 y n e n t rate, ana productivity
trends. The assumptions and r c= 1 a r -.• d projections are published in
the August 1981 issue of the M c n t h 1 y __ L3_cj2JT_JL£J£_Ls.y. •
The basic procedure used to develop occupational projections was
to apply projected staffing patterns for each industry in the OES
survey-based matrix to projected wage and salary worker
employment in the related industry. Separate totals for
self-employed persons and UP. paid family workers were projected
for each occupation. These totals were added to the projected
wage and salary worker totals for the occupation tc develop the
total employment projection by occupation. Projections were
developed for each of the three alternative scenarios, but the
same staffing patterns of industries were used in each
alternative. The following detailed procedures were used to
develop the occupational projections.
Industry Controls
The Bureau's model produces projections for 156 industry groups.
These projections were disaggregated to the 373 industries
included in the OES survey-based matrix. In general, projections
of industry employment for all CES pjolished series developed
through regression analysis were used to c1 i s ago r agate employment
in the 156 sectors. Indust-y employ merr projections for the
unpublished CES series were developed by d i s agg r ega t i on of the
appropriate projected CES series on the basis of trends in ES-202
data.
Occupational Staffing Patterns
t
Surveyed Sectors . In projecting occupational staffing patterns
for industries in previous projection cycles, Decennial Census
data were extrapolated into the future based on decade to decade
changes. Considerable analysis a r, d review identified the factors
that caused changes in staffing patterns. The analysis resulted
in many changes to the mechoiicallv developed extrapolated
ratios. However, a review of the 19 "5 occupational projections,
done just prior to the development of the nost recent 1990
projections, indicated that the major cause cf errors in the
projections was incorrect projection cf occupational ratios. An
intensive effort was devoted to research on net hod? of projecting
OES survey-based matrix staffing patterns. .3 /
281
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OES Survey-Based Matrix Procedures —12
In general, the research tested the merits of a variety of
extrapolation techniques. In these tests, use of current
staffing patterns in the projected years generally produced
better results, on the average, than any extrapolation technique.
However, for large occupations that were not affected by any
problems related to changes in industry or occupational
definitions, the exponential extrapolation technique generally
outperformed the constant ratio method. Since the tests were
performed on data covering a short period of time and the
exponential method worked well for large occupations representing
a very significant proportion of employment, this technique was
used where possible. The research also indicated that ratios
developed through mechanical means must undergo intensive
analytical review.
The first step in developing the projected staffing patterns for
the OES survey-based matrix was to project trends in OES survey
data from the last two OES survey rounds for each industry.
Unfortunately, because of changes between survey rounds in
industry definitions (change from the 1967 SIC to the 1972 SIC),
occupational definitions, survey forms, and geographical
coverage, many difficulties were encountered in this process.
Periodically, the SIC system, used as the basis for OES survey
industry definitions, is changed. Such a change occurred between
the OES survey round providing data for the current 1978 and 1930
matrices and the OES survey round im-mediately preceeding that
affected several industries. As a result, trends could not be
developed because the data were not comparable. In these cases?
ratios were held constant at 1978 levels for the initial 1990
projected matrix. Trends were extrapolated only in industries in
which 95 percent or more of employment included in the 1972 SIC
industry definition was also included in the same industry in the
1967 SIC industry definition.
Between the last two survey rounds, definitions were changed for
several OES survey occupational categories. Some new occupations
were added in the last survey round. With only one observation,
trends could not be developed for these new occupations.
Additionally, the occupational category that probably 'ncluded
the occupation in the previous round could net be projected
because of inconsistent occupational content. Similar situations
resulted when occupations were dropped or combined with other
occupations in the OES survey.
Even though the OES survey has been conducted since 1971 as a
Federa 1-State cooperative program, all States do not participate
in the program and the number of States in each OES survey round
has varied. Beginning with the 1977 OES survey, the BIS surveyed
the nonparticipating States as a whole and National data became
available. J./ Because National data were not available for both
of the last two survey rounds in any industry, data from States
that participated in both of the last two OES surveys for each
282
-------
procedjres — 1 3
i n d ./ s t * y v s r e summed and used as s proxy f o - M a t i o r a 1 data. The
number o ->c States providing data used in developing trends to 1990
\.iss as "c ileus for Each survey "ourd: "9 7^ anc 1977
•? a n u •? 3 c ': u - "• n g , 27; 1975 ana 1973 nonrnanu facto-ing, 29: sr-6 1973
and ', 9 v 6 trader 19. The cl a v e '. o r n e n t of trends? therefore?
?x-~~,;r:ec .v.:. ~3 Stctes , - ? c •!!?;' h ? v ~ r>3^ .; ; ~-~ : •;•; -. r nt ^~.-:-^'. y? ^r-i' in
? s ~ - c > -'- : J o c c u r: f c i o ~ - i "• ~'-: c '-• r .-• • >- ? i e c '~ i c ~ r o u," r! s - t r i s
weakness w i i i o e e 1 i rr, < n s '~ e c' ; : -i c-1 t i o i r X rJ ^ : s "H ' i 1 ? e c ? m a a v ~ i j a c i z
for two o o i n r s in time b e q i r n i n g '-' ; t h the i 9 B 0 CHS s -j - v e y , a n c e D t
for- e d u c s t i o n and r a i .", r o c d s .
To overcome the problems ' d a n 'C i •?: s d a b o v % ccrce:rn:rc the
comparability of OES survey data in the last t v o QES survey
rounds; orly those occupations w ' ^ h consistent d e x r n i t i a r, s that
were found in industries with consistent SIC content were
projected through the a x p o r. e r, t i a .'. extr?oolst:- on technique to
1990. The projected trends in survey occupations were related" to
appropr:ate G E S survey-based matrix occupations. Adjustments
were made to these ceils and any other cells in the matrix by
analysts who reviewed t P e data f o f all industries. The analysis
was concentrated. however- on industries that erplcyed over
1CO.QCQ workers. Cells that y e r e not projected w e -- e held
constant in 1990 at the 1978 levels. An iteration procedure
forced the distribution patterns in e?ch i ^ d u s T: r y t c add to ICO
percent. These patterns became the initial 1990 projected
staf-;nq patterns,
T h = i n ' t < r 1 n ,- o j ~ c tea -; c x • • ~ i ~ r t o t • j r r : r ; a c :' • '1 ^ •; t r \ u. c s
e o p 1 " s d to projecced i r d ',' s t r y e m o \ o y r.. e --, r t or?1 :; T T r- i,- ace 3 n d
73 '. 3 r v workers r o develop r h 3 c ~ 3 ". ; rr- : n a r y '! ~; 9 C o c. cups •" r, 2 r ", 1
'o r o j e c t ' o "• ? . These projections v>' a f" - =' r ~ 1 y z c d ' r detail', o v e >•• 3
six m c n t h p e r i o o• b a ~ e d on studies o F o c o J p a t i c n s and industries
conducted d u r : n o preparation of t h ^. QjL£,iL2Si_l 'LQ ?•._!,_ 0 u 11 c_oj(
Handbook . " s c t ~ r s considered by e. n a 1 y r t s included changes i ">
product'on methods? technological changes affecting occupational
mix, changes in product mix of industries. changes in average
sine of establishments in industries- and other economic factors
In addit'cn, some occupations «ere projected independently o-F the
matrix based ~n the relationship cf the oc-upatio^ to more
c 1 : s e 1 y associated variables. For example; ar eject ions o -^
2 i =; n e r, ': a r y school teachers were based on estimates of the school
see population and puo:l-tascher ratios. Projections developed
in t h s ' m a " n s r were u 3 G a ; n t ^ e n s t - i x i n d a a j '; 3 t rr, 3 n t s in t h s
r " i. i C 3 - O " n ~ h Q " O C C U 0 ~ ~ O ", S U <3 •* e r. R O "3 V be" '" = C '.'-. ' ? S - \" -
D'.. ;• i n g t r e a r, -,, j y 3 i :; , •-f- ". a t " i n ;~ h i r - L' -.. . .-: s : " - i . '-; -• Ci " 3 t •.-< e £• r>
o c c w p d ;: i o n s "< t h e Census-based T ? t • ' ,; 5 r u .. •-. s •! ;: :• .-, . * v f_ y -based
mat~ix to o" t 3 " the benefit o ^ 3 1 o n c e • t::~s si^'&s, B ^ s e d on
ail t h e a n 5 '.;/ s e ?. d e s c '• i c e d s b o ,• e . c 'n = n c e s ^, CT - e ^ a a e > n the
re 3 s r> ^ ^ r c *,' h s r x h c ? c ^ T "^ i ^ c n ^ ". i 9
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OES Survey-Based Matrix Procedures —14
added to 100 percent. The resulting ratios were applied to total
projected employment of wage and salary workers in each industry
to develop the final occupational projections of wage and salary
workers.
Nonsurveved Sectors. The initial projected 1990 occupational
ratios for the agriculture, forestry, and fishing, education, and
private households industries were taken directly from the 1990
Census-based matrix developed by the Bureau for 1978-90. The
ratios were analysed based on CPS data that became available
after the Census-based matrix was developed, and a feu ratios
were adjusted. The occupational distribution in the Census-based
matrix was converted to the OES survey-based matrix distribution
in the same way described above for the current year matrices.
The projected ratios were applied to the 1990 industry
projections for the appropriate industries. The results were
reviewed in detail. Changes in the staffing patterns resulted
from this review were incorporated in the final matrix.
Sel.f-Emoloved Persons and Unpaid Family Workers. Based on an
analysis of the trends in the 1978-90 Census-based matrix and the
1971-80 CPS data on the ratio of self-employed persons and unpaid
family workers to total employment in each occupation, estimates
were developed of the percentage of each of these two classes of
workers to total employment in each Census-based matrix
occupation. These ratios were applied to projected 1990 total
employment for each Census-based matrix occupation. The summed
result was compared to the 1990 control totals for these two
classes of workers, which had been independently projected as
part of the Bureau's economic model. Minor adjustments forced
the ratios to 100 percent and the individual estimates to the
control totals.
Using the methods already indicated, the Census-based matrix
occupational estimates were disaggregated by Handbook analysts to
the full list of survey-based matrix occupations. These were
reviewed for consistency with information developed in the course
of other occupational research and appropriate changes were made.
Total Occupational Emo Iovment. To develop total employment
projections by occupation, projections of wage and salary workers
in the surveyed and nonsurveyed sectors was added to the
projected totals of self-employed persons and unpaid family
workers. Unlike previous projections of total National
employment, the totals in the OES survey-based matrix represent
the number of jobs by occupation, not the number of persons
employed by occupation. 1O/ These totals are different because
one person may have more than one jcb. The difference between
the number of jobs and the number of parsons employed in 1990 is
estimated at approximately 7 percent.
284
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)ES Survey-Based Matrix Procedures — I 5
F oo.t notes
J_/ For a more detailed explanation of these disaggregat: on
techniques, see "Development of the State OES Survey -Based
Matrix," OES Matrix/Projections Memo No, 12 , September 10, 1979,
Approximately 4 percent of total occupational employment was
developed through disaggregat ion of residuals.
2_/ A total of 1,836 detailed survey occupations uere used
directly, disaggregated, or collapsed to a final occupational
list (after manual updating) containing 1,615 detailed matrix
occupations. This same final occupational list was used for all
1978, 1979, and 1980 matrices. These numbers may change in
future matrices as tha number of OES survey occupations included
increases or decreases.
Z_/ A list of these updates was given to States engaged in
developing projections for the interim projections project to use
as a guide for updating State matrices. In this list, updates of
less that 50 persons were excluded to eliminate possible problems
in allocating small numbers among the various States. When these
smaller updates uere removed from the list, the number of updates
dropped to 1,543.
4./ Employment in hospitals was resurveyed in 1930. Employment in
railroads has not been surveyed sincE 1976; there are no
immediately plans to resurvey this industry.
.
.5 / Although an OES survey of employment in educational services
was conducted in 1979, National data from this survey are not
available because 10 States did not participate,- one cf which was
California. Furthermore, a combined estimates file of the 41
States that did participate in the OES education survey was not
available in time to use in these first National OES survey-based
matrices. Surrogate National estimates? based on data from the
41 States, uill be used in the 1930-11 rratrjx.
6/ See f tn . ' 5 .
7/ In 1976, Oklahoma became the first State to collect data on
employment in educational services. No other data on emoloyment
in education uere available at the tin-, a the matrices discussed in
this paper were developed.
8/ For s mere detailed explanation? see. "Projected Occupational
Staffing Patterns of Industries." B L 5 technical paper, April
1981.
_9/ Funds to do this uork uere provided to the Bureau by the
National Science Foundation.
285
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OES Survey-Based Matrix Procedures — 16
_!_C / Wage and salary workers in agriculture) private households,
and education uiere only counted once> even if they held more than
one job because the CPS was the source of data on employment in
these industries. Similarly, self-employed persons and unpaid
family uorkers are counted only once in their primary job.
286
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50272-101
REPORT DOCUMENTATION
PAGE
1. REPORT NO.
EPA 560/5-85-004
3. Recipient's Accession No.
4. Title and Subtitle
Methods for Assessing Exposure to Chemical Substances
Volume 4: Methods for Enumerating and Characterizing
Populations Exposed to Chemical Substances
5. Report Date
7/85
7. AuthoKs) Douqlas A. Dixon, Karen A. Hammerstrom, Gina L. Hendncksc
Amy Borenstein, John J. Doria, Thomas Faha. Patricia Jennings
. Performing Organization Rept. No.
9. Performing Organization Name and Address
Versar Inc.
6850 Versar Center
Springfield, Virginia 22151
10. Project/Task/Work Unit No.
Task 9
11. Contract(C) or Grant(G) No.
(o EPA 68-01-6271
(G)
12. Sponsoring Organization Name and Address
United States Environmental Protection Agency
Office of Toxic Substances
Exposure Evaluation Division
Washington, D.C. 20460 •
13. Type of Report & Period Covered
Final Report
14.
15. Supplementary Notes
EPA Project Officer was Michael A. Callahan
EPA Task Manager was Karen A. Hammerstrom
16. Abstract (Limit: 200 words)
This report, one of a series of reports concerning exposure assessment,
describes methods for estimating the sizes of populations potentially exposed to
chemical substances. Five categories of exposed populations are covered:
(1) populations exposed to chemicals in the ambient environment, (2) workers,
(3) populations exposed through ingestion of chemicals in food, (4) users of
consumer products, and (5) populations exposed through ingesting chemicals in
drinking water. The report contains general data on populations from governmental
agencies such as the U.S. Bureau of Census, U.S. Department of Labor, U.S. Department
of Agriculture, and EPA's Office of Drinking Water. It also contains step-by-step
methods for locating and using data to enumerate each subpopulation identified as
potentially exposed to toxic chemicals. Appendix A contains sample calculations
illustrating the methods presented in the text. Appendix B is OSHA's Industry-
Occupation (1-0) Matrix, described in Section 3 of the report.
17. Document Analysis a. Descriptors
b. Identifiers/Open-Ended Terms
Exposure Assessment Population Size
Toxic Substances/Population Characteristics
c. COSATI Field/Group
18. Availability Statement
Distribution Unlimited
19. Security Class (This Report)
Unclassified
20. Security Class (This Page)
Unclassified
21. No. of Pages
304
22. Price
(See ANSI-Z39.18)
See Instructions on Reverse
OPTIONAL FORM 272 (4-77)
(Formerly NTIS-35)
Department of Commerce
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