&EPA
United States
Environmental Protection
Agency -
Office of Air Quality
Planning and Standards
Research Triangle Park NC 2771 1
EPA-450/D-86-001
June 1986
Air
User's Manual
For The Human
Exposure Model
(HEM)
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USER'S MANUAL
FOR
THE HUMAN EXPOSURE MODEL (HEM)
Pollutant Assessment Branch
Office of Air Quality Planning and Standards
June 1986
**i Protection Agency
US Environmental Proteu
r,0 MlinoiS
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This report has been reviewed by the Strategies and Air Standards Division
of the Office of Air Quality Planning and Standards, EPA, and approved for
publication. Mention of trade names or commercial products is not intended
to constitute endorsement or recommendation for use. Copies of this report
are available through the Library Services Office (MD-35), U. S. Environmental
Protection Agency, Research Triangle Park, N.C. 27711, or from National
Technical Information Services, 5285 Port Royal Road, Springfield, Virginia
22161.
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TABLE OF CONTENTS
Title Page
Chapter 1 1-1
l-l.1 ' Introduction 1-1
1-2. When To Use SHED or SHEAR 1-2
1-3. Permanent Data Bases 1-2
1-4. Computer Access .1-9
1-5. Risk Estimates 1-11
Chapter 2 2-1
2-1. Introduction to SHED 2-1
2-2. Input Data ' 2-1
2-3. Dispersion Modeling 2-6
2-4. Assumptions 2-18
2-5. Using the SHED Model 2-20
2-6. Using Output from other Dispersion Models 2-37
2-7. Output from SHED 2-40
Chapter 3 3-1
3-1. Introduction to SHEAR 3-1
3-2. Input Data 3-2
3-3. Dispersion Modeling 3-5
3-4. Assumptions 3-10
3-5. Using the SHEAR Model 3-11
3-6. Using Output from other Dispersion Models 3-35
3-7. Output from SHEAR 3-37
References R-l
Appendix A A-l
Appendix 3 B-l
Appendix C C-l
Appendix 0 0-1
Appendix E E-l
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List of Figures
Figure Page
1-1. Locations of STAR Stations 1-7
2-1. Effects of Chemical Reactivity on Concentration
Distribution of Chloroprene 2-8
2-2. Effect of Building Wake on Concentration
Distribution of Chloroprene .2-10
2-3. Impacts of Release Height on Concentration
Distribution of Chloroprene .... 2-11
2-4. Pairing of BG/ED with Concentration Points
Within a 3.5 Km Radius 2-14
2-5. Log-linear Interpolation Scheme 2-16
2-6. Summary of SHED Data Entry Format 2-31
2-7. Typical SHED Data File 2-32
2-8. Summary of the Input Data ... 2-41
2-9. Individual Plant Concentration Grid 2-42
2-10. Map of Population Centroids and Population by 3rid .... 2-43
2.11. Map of Population Centroids and Population by Patch .... 2-44
2.12. Cummulative Summary 2-46
2-13. Overall Summary 2-47
3-1. !3Qual Card for SHEAR 3-14
3-2. Population Extraction Data for SMEAR 3-16
3-3. Exclusion Data for SHEAR 3-19
3-4. Chemical and STAR Data for SHEAR 3-20
3-5. Point Source and Prototype Data for SHEAR 3-23
3-6. Area Source Data for SHEAR 3-26
3-7. Summarization Data for SHEAR 3-28
ii
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3-8. Plot Data for SHEAR 3-31
3-9. Selection of Center for Listing of Concentrations .... 3-33
3-10. Point Source and Prototype Data for SHEAR ......... 3-34
3-11. Selection of ISC Output Files 3-36
111
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List of Tables
Table Page
1-1. The SHED and SHEAR Models 1-3
1-2. Conparison of SHED and SHEAR Results 1-4
iv
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Chapter 1
1-1. Introduction.
The Human Exposure Model (HEM) is a general model designed to estimate
the population exposed to air pollutants emitted from stationary sources and
the carcinogenic risk associated with this exposure. The HEM is comprised
i '
of (1) an atmospheric dispersion model, with included meteorological data,
(2) a population distribution based on Bureau of Census data and (3) .a
procedure for estimating risks due to the predicted exposure. The only
inputs needed to operate this model are source data, e.g., plant location,
height of the emission release point, the temperature of the off gases,
etc. Based on source data, the model estimates the magnitude and distribution
of ambient air concentrations of the pollutant in the vicinity of the
source. These concentration estimates are coupled with the population to
estimate public exposure to the pollutant. The HEM then predicts population
risks if a unit risk number determined from health data is input for the
pollutant.
Within HEM there are two basic models, the Systems Applications Human
Exposure and Dosage (SHED) model and the Systems Applications Human Exposure
And Risk (SHEAR) model. The SMED model was developed to access sources on
a nationwide source category basis, e.g., all primary copper smelters. It
is generally faster and more economical to run SHED than SHEAR for major
point sources (large producers and users). The SHEAR model was developed
from SHED to model hot spots, or smaller regions with more than one source.
In addition to modeling major point sources, SHEAR can also be used to nodel
prototype sources (model plants) and area sources. Since the applications
and actual data input of SHED and SHEAR vary, these aspects will be discussed
in separate chapters of this manual.
1-1
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1-2. When to Use SHED or SHEAR.
As explained above, SHED and SHEAR are two models within HEM which
differ slightly in their purpose and scope. Table 1-1 summarizes the
differences between the two models. This summary yields the following
conclusions of which model should be used in a particular analysis:
i *
1. Use SHED when addressing national exposure from one chemical.
2. Use SHEAR when addressing multiple chemicals from a source or
group of sources and the assumption is valid that risks to human
health can be approximated simply by adding together the risks
from each chemical studied.
3. Use SHEAR when the source is located near uninhabitable areas such
as large bodies of water and where the nearest population centroid
is close (less than 1.0 km) to the plant.
4. Use SHEAR to assess the impact of area or prototype sources in
small geographical areas.
These guidelines should assist in determining which model to use for a
particular analysis. To show the possible differences which could be
expected with SHEO and SHEAR, the same plant was modeled using SHEO and
SHEAR. The results are outlined in Table 1-2. For more detail on the
model differences please refer to Chapters 2 and 3.
Certain components of SHEO and SHEAR are similar, for example,
the meteorological and population data bases. The subsequent sections of
this chapter will address those features common to both models.
1-3. Permanent Data Bases
Four major types of data are essential for assessing exposures to
and dosages of atmospheric chemicals:
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TABLE 1-1. THE SHED AND SHEAR MODELS
AREA
EVALUATED
SHED
SHEAR
SCOPE
NATIONAL (MAJOR POINT SOURCES)
POLLUTANTS
NUMBER PEOPLE
EXPOSED
INDIVIDUAL
RISK
RESOURCES
SINGLE POLLUTANT RUNS ONLY
DOUBLE COUNTS IF SOURCES SITED
NEAR EACH OTHER
MORE REALISTIC ESTIMATE (GENERALLY
OVERESTIMATES SLIGHTLY)
INEXPENSIVE TO RUN
LIMITED GEOGRAPHICAL AREA ANALYSIS!
(MAJOR POINT, PROTOTYPICAL*, AND
AREA** SOURCES)
MULTIPLE POLLUTANTS
NUMBER OF PEOPLE EXPOSED HELD
CONSTANT
UNDERESTIMATE
MORE EXPENSIVE
* ASSIGNS MODEL PLANTS RANDOMLY TO BG/EO CENTROIOS
** EMISSIONS ASSIGNED TO POPULATION OR ASSUMED TO BE UNIFORMLY DISTRIBUTED
OVER AREA SPECIFIED
1-3
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TABLE 1-2. COMPARISON OF SHED AND SHEAR RESULTS
2 Plants Modeled in New York City (50 Km Radius)
MEASURES
i
Maximum Lifetime Risk
Annual Incidence
Total No. of People Exposed
No. of People Exposed to
Incremental Risk
>io-3
>10'4
>10-5
>io-8
>10-7
>10-8
Maximum Concentration
Model ed
Cost (1986)
SHED
2.4 x 10-3
1.0
27,400,000
1,285
32,270
927,000
13,700,000
27,000,000
27,400,000
8.0 x 10-1
(.2 Km, NE)
$ 6.63
SHEAR
5.9 x 10-*
1.0
13,700,000
0
43,900
1,380,000
9,460,000
13,500,000
13,700,000
8.0 x 10-1
(.2 Km, NE)
$ 61.50*
RATIO
SHED/SHEAR
4.1
1
2
* This is the cost of running the point source portion of SHEAR only.
To run point source, you roust first run a population routine called
XTRACT which would cost additional dollars. The exact amount depends
largely on the population density of the area modeled. Hew York City
is >$100.
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> Emissions inventories of chemicals
> Atmospheric reactivities of chemicals
> Meteorological data
> Population distribution data
ซ
The first two of the four types of data bases are data specific for
each chemical. These data must be input for each risk assessment for SHED
or SHEAR. These data bases are covered under each section entitled ".Input
Data" in the SHED and SHEAR chapters.
Meteorological data and population distributions do not vary with the
specific chemical but depend on geographic location. These are permanent
data bases in the program. The remainder of this section provides further
detail on these data bases. Systems Applications, Incorporated (March 1983
and May 1983) provide more detail on the creation of these data bases.
Health data are essential to derive copulation risks from population
exposure. However, these data are provided in the form of a unit risk
estimate, which is derived external to the exposure model. This health
data type will not be discussed in this manual.
Meteorological Data
The dispersion computations carried out by the HEM require data on
wind speed, wind direction, and the intensity of atmospheric turbulence.
The turbulence intensity is represented by the atmospheric stability class.
These data are provided by a permanent data base in the program known as
the Stability Array or STAR data set.
Acquisition and Processing of STAR Data
Martin and Tikvart (1968) developed the STAR program from routinely
collected meteorological data to generate frequencies and percentage
frequencies of wind direction by speed classes for each stability category.
1-5
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The specifications of stability categories depending on wind speed and sky
cover were set up by Pasquill (1961) and were modified by Turner (1964).
The program was adopted for use at the National Climatic Center (NCC),
where archived records of all national reporting weather stations are kept.
The most up-to-date version of the STAR data from all STAR stations in the
i
country was obtained on magnetic tape from NCC, and the matrices of STAR
frequencies used in the program were taken from these tapes.
The data sets on the NCC tapes were reprocessed into a format which
includes 16 wind directions, six wind speed classes, and seven stability
categories with categories A, B, C, and D^y in the daytime and categories
ฐnightซ Eป anfl' ^ 1n the nighttime. There are data sets for 312 stations in
this reprocessed STAR data file. Figure 1-1 shows the locations of these
STAR sites.
STAR Station Selection
By default, meteorological data recorded at the STAR station nearest to
the source are used in the dispersion modeling for SHED. The nearest station
is typically input for SHEAR, as well. (See Appendix A for location of the
nearest STAR station.) However, local meteorological trends and topographic
features may be more important factors in selecting a STAR station than is
the absolute distance between the source and the station. A STAR station
with climatological conditions most similar to those of the source of
emissions may not be the nearest station, so the STAR stations may be
manually selected to account for such situations.
Detailed STAR Selection Process
As stated previously, STAR stations can be manually selected such that
they are in similar local meteorological regimes and are influenced by
1-5
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t/1
c
o
(/I
c
o
1-7
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similar orographic (topography on the scale of mountain ranges) conditions
as the emission sources. Major features which should be considered include
the following:
> Surface thermal patterns, which can affect the local wind. For
example, the local sea-land breeze wind system is usually limited
to surface-based layers several hundred meters thick. Since this
region is the atmospheric layer into which chemicals are emitted,
consideration of these winds is important for chemical plants
located on ocean coasts or adjacent to large lakes. Another example
concerns foehn winds (winds flowing down mountains), the influence
of which should be considered for emissions sources located in
Montana (Chinook wind) and in Los Angeles County (the Santa Ana wind).
> Wind patterns may be obtained from the Climatic Atlas (U.S. Environ-
mental Data Service, 1968) and from maps of the U.S. Geological
Survey (1:500,000; 1:125,000).
> Topographical effects, such as that of mountain-valley wind. The
behavior of the wind in ridge-valley topography depends both on the
relationships between the wind direction and the solar azimuth, and
on the orientation of the ridge lines and valleys. These local
wind effects should be taken into consideration in the selection
process, especially for emissions sources located in the valleys of
the Cascades and coastal ranges (northwestern states) or the Appalachian
Mountains (eastern states).
> Urban effects, including wind, low disturbances by urban thermal or
frictional elements such as organized patterns of urban skyscrapers
(Chicago, New York City, Los Angeles metropolitan, etc.). Such
1-8
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features substantially influence airstream and, consequently, the
diffusion of air contaminants. If an emission source is located in
a small city, and if STAR stations in a large city and in a small
city are equidistant from the emission source, then preference should
tbe given to the STAR station in the small city.
Population Distribution Data Base
The HEM program uses the latitude and longitude from the input d.ata in
determining the population of the study area. The permanent data base is
comprised of the 1980 Census Data Base broken down by Block Group/Enumeration
District (8G/ED). Further information on this data base and the manner in
which it is accessed is covered in the following sections.
Population Data Processing
The population data base contains the population centroid coordinates
(latitude and longitude) and the 1980 population of each BG/ED in the
country (about 300,000 centroids in 50 states plus the District of Columbia)
as found in Master Area Reference File 2 (MARF2). In addition, the data
base contains large arrays of descriptive and summary population statistics.
vJhile these data may be a valuable adjunct in certain types of exposure
analyses, the size of the complete file interferes with efficient access to
the small subset of information needed for most exposure calculations. For
this reason, the permanent data base contains only the essential information
in a fonn that permits rapid access to the relevant study area.
1-4. Computer Access
The HEM program is currently run on the National Computer Center's
(NCC) UNIVAC computer system located at Research Triangle Park, N.C. The
computer may be easily accessed by terminals located at Research Triangle
1-9
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Park and at EPA's facilities in the NC Mutual Building in Durham, NC.
Terminals in the Mutual Building are presently located in Rooms 934, 624,
654, 653 and 646A.
Access can also be obtained via the EPA regional offices or through
any organization using the NCC system. To gain access to the computer,
i '
users must have an account to which the computer time will be charged and a
user ID. Within the Environmental Protection Agency, user IDs and accounts
are obtained through the ADP coordinator by contacting Pete Carter at (919)
541-3522. For information concerning interagency agreements contact Jim
Obenchain at (919) 541-2122. To set up a contract for the NCC UNI VAC
outside of EPA, contact Ms. Weaver of National Technical Information
Service (NTIS) at (703) 487-4805. Ms. Weaver can send the appropriate
forms which must be completed and returned. Ms. Weaver will also upon
receipt of the completed paperwork, contact EPA to obtain an account number
and user 10. To establish equipment compatability call TELE Communications
at (919) 541-4506, FTS 629-4506 or (300) 334-0741.
The HEM is frequently under revision to ensure that the best information
is incorporated. This manual will thus soon become outdated. Therefore,
before attempting to operate HEM, please contact Michael Dusetzina,
Brenda Riddle or George Ouggan of the Pollutant Assessment Branch, at (919)
541-5645 or FTS 629-5645. These personnel can alert you to changes in the
model and can help in deciding which version of the model may be most
appropriate for your application. Once one of these is contacted and you
have an account number and a compatible terminal, HEM may be run by following
the instruction detailed in sections 2-5 and 3-5.
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1-5. Risk Estimates
The HEM produces estimates of annual incidence and maximum individual
lifetime risk. These numbers, however, should not be construed as the
absolute health risks. HEM was designed to screen, 1) substances to be
regulated, 2) source cagtegories to be regulated and 3) alternative control
i *
techniques. To produce results inexpensively with limited data (as required
by screening techniques), HEM makes many simplifying assumptions. Since
these assumptions are common among HEM runs, the results can be compared.
Therefore, HEM results should be used only to compare within similar sub-
stances, scenarios, etc. for decision-making and not be presented as absolute
values of risk.
The assumptions required to estimate the health risk with HEM involve
both estimating the exposure to a substance and estimating the health
effects due to this exposure. These assumptions ar* outlined below.
Exposure Assessment
The HEM estimates concentrations of a substance in the ambient air at
specific points around a source. It is known, however, that pollutant
exposure occurs for exposures other than ambient air exposures (i.e., food,
water) and populations move through different microenvironments. This model
also employs a number of simplifying assumptions including:
1. It is assumed that most exposure occurs at population weighted
centers (centroids) of block group and enumeration districts (BG/EO) as the
locations of actual residences are not contained in available databases.
The model relies on information provided in a database developed by the
U.S. Census Bureau.
2. It is assumed that people reside at these centroids for their
entire lifetimes (assumed to be 70 years for calculating cancer risk).
1-11
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3. It is assumed that indoor concentrations are the same as outdoor
concentrations.
4. It is assumed that plants emit pollutants at the same emission
rate for 70 years.
5^ .It is assumed that the only source of exposure is the ambient air
and resuspension of pollutants via dust is not considered.
6. It is assumed that there is no population migration or growth.
7. The model does not provide for descriminating exposure situations
that may differ with age, sex, health status, or other situations.
8. The model is designed to model for flat terrain.
Table 1 presents the directional impact some of these assumptions may
have on the risk results. It is important to note that these estimates may
not be universally applicable to all pollutants and source categories.
Nevertheless, they should serve as a useful qualitative description of the
effect each assumption may have on the risk estimates.
There is also uncertainty associated with various specifications re-
quired for running the HEM as well as uncertainty associated with the
variables specified. These model specifications and variables include:
1. Given the variations in meteorology each year and with each location,
there is uncertainty as to the extent to which the meteorological station
used to model the site modeled is representative. This includes the selection
of urban or rural for stability.
2. There is uncertainty associated with the emission estimates and
the plant parameters used to characterize the emission source.
3. If the plant is not correctly located, there will be a problem in
the matching of population census data with concentrations, which alters
1-12
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TABLE 1. DIRECTIONAL IMPACT OF SIMPLIFYING ASSUMPTIONS ON RISK ESTIMATES
MODEL ASSUMPTION
MAXIMUM
INDIVIDUAL
RISK
AGGREGATE
RISK
COMMENT
Exposure at
centroids
Underestimates
Minimal
underestimate
SHEAR underestimates
risk close to the
plant due .to this
assumption
Exposure at
receptors
Overestimates
occasionally
Minimal
overestimate
SHED can overestimate
rfith this assumption
if no one lives at the
highest concentration
level
Indoor exposure
equals outdoor
Overestimates
Overestimates
This assumes no in-
door sources of the
pollutant
Immobile
population
Overestimates
No effect
Aggregate is un-
affected because
population leaving
are replaced at the
same rate
Mo individual
behavior
patterns
Underestimates
Underestimates
Individuals are at
higher risk due to
outdoor or closer
activities
Flat terrain
Underestimates
Underestimates
Unless the source
is higher than the
surrounding area,
the plume impacts
on rough terrain
1-13
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risk estimates.
Table 2 presents some of the specifications required by HEM and the
directional impact of selecting one specification rather than another.
Again, these impact estimates may not apply to all situations and sources
but may provide useful information for the general trend.
Unit Risk Value
The unit risk value constitutes all of the health risk information
input required by the HEM. The uncertainty involved with the unit risk
estimate depends on the amount, type and quality of data used in its
development. For instance, when only animal data is available, a statistical
upper bound is used to calculate the unit risk. When human data is available,
a maximum likelihood estimate is used to estimate the unit risk. Although
these are similar, the upper bound is often higher than the maximun likelihood
estimate by a factor of 2 or 3. There are several areas that contribute
to the uncertainty associated with the unit risk or cancer potency estimates
developed by the Carcinogen Assessment Group. These areas are divided in a
number of different ways but the following grouping is reasonable:
1. Extrapolation: Animal-to-man or route-to-route.
2. Absorption: When route-to-route extrapolation is employed it is
necessary to examine, if available, absorption estimates that have been
derived from controlled exposure studies using concentrations that are
reasonably similar to the ambient exposures.
3. Model Specifications: The consistency of model specifications
used in calculating the cancer unit risk estimates.
4. Pharmacokinetics: The consideration of oharmacokinetics especially
for studies requiring route-to-route extrapolation.
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TABLE 2. COMPARISON OF RISK ESTIMATES BASED ON VARIOUS HEM SPECIFICATIONS
MODEL ASSUMPTION
MAXIMUM
INDIVIDUAL
RISK
AGGREGATE
RISK
COMMENT
Urban vs rural
Higher estimates Lower estimates
Rural setting results
in more stable
meteorology and higher
distant concentrations.
Urban setting is less
stable but generally
produces .higher
maximum individual risk,
Stack height
(low vs high)
Higher estimates Somewhat higher
estimates
Taller stacks cause
greater dispersion
within the 50 km
area and hence lower
concentrations
Exit velocity
(low vs high)
Higher estimates Higher estimates
Higher velocities
cause more dispersion
and lower concentrations
Emissions
Proportional
Proportional
Concentrations and risk
are proportional to
emissions
Diameter
(smal1 vs large)
Location
Small city
Medium city
Large city
Higher estimates Higher estinates
Higher/lower
Higher/lower
Minimal
Higher/lower
Higher/lower
Minimal
Only affects the risk
occasionally
Location of sources
determines affected
SG/EDs. Large cities
are more likely to
have consistent popu-
lation density.
Location can have a
very large impact for
small and medium
cities.
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Chapter 2
2-1. Introduction to SHED
SHED is a model within HEM that is used primarily for major (specific)
point sources (usually producers or large users of specified chemicals) on
a nationwide basis. Each source in SHED must be specifically located by
longitude and latitude. For each source the release parameters must be
described, these include stack height, exit velocity, emission rate, etc.
SHED is relatively fast to run. After input of the data, the
program may take only ten minutes of computer time to run as many as one
hundred sources. This rapid processing causes SHED to be relatively
inexpensive to run.
2-2. Input Data
As discussed in Section 1-2, the meteorological data and population
data are part of the internal computer data base. The necessary input data
falls into four categories:
> Source Location
> Emissions Data
> Vent Parameter Data
> Atmospheric Reactivities of Chemicals
Source location, emissions data and vent parameter data are always
necessary to analyze sources. The atmospheric reactivities, however, are
only necessary when the chemical is extremely reactive. For example, the
atmosphere half-life should be specified for those chemicals *ith half-lives
of less than three or four hours. The following section provides additional
guidance on the information needed and possible sources of the information.
How to input the data into a file for use by the program is discussed in
Section 2-5.
2-1
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To link the computed exposures to the cancer risk of the population,
the unit risk estimate must also be included. Generally, these estimates
are obtained from the Carcinogen Assessment Group in a Health Assessment
Document (HAD) for the chemical. A unit risk estimate is the estimated
risk of cancer to an individual if that individual is exposed to one ug/m3
of the chemical for their entire lifetime. Hence it is expressed in units
of (jg/m3')'1. If the unit risk is unknown, HEM assumes a risk of 1.0. The
results then merely reflect the concentrations and the number of people
exposed to those concentrations without estimating the health risk from
that exposure. The "annual incidence" and "maximum individual risk" numbers
reported using a unit risk of one may simply be multiplied by the correct unit
risk number when it becomes availabale.
Source Location
The geographic location of the source must be identified in order to
run the SHED portion of HEM. Specific point source locations may be determined
generally from a variety of published sources. These include:
> Directory of Chemical Producers and Chemical Economics Handbook, published
by Stanford Research Institute.
> "Chemical Marketing Reporter."
> U.S. Government publications, such as the U.S. Tariff Commission's
Synthetic Organic Chemical Production and Sales."
> Reference guides, such as the "Kline Guide to the Chemical Industry."
> Other sources, such as trade associations, trade journals and periodicals,
and technical journals and periodicals.
> Existing EPA exposure and risk reports.
Once the general locations (company name, city and state) of the point
source are determined, geographic coordinates must be assigned. Geographic
coordinate information can also be determined from a variety of sources.
These include:
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> Personal communication with state air agencies and/or EPA regional
offices.
> Emissions inventory files (e.g., the National Emissions Data System (NEDS).
> United States Geological Survey Maps (U.S.G.S).
> Existing EPA exposure and risk reports.
In some instances, these sources will be able to provide geographic
coordinates in Universal Tranverse Mercator (UTMs) units. These may be
converted by use of a computer program on the UNI VAC system to geodetic
coordinates (latitude/longitude). To use this program, please refer to
Appendix 8.
Emissions Data
Emission factors can be developed to estimate the emissions from the
production, consumption, and incidental formation of the various chemicals
assessed. The emission factor is expressed as tie total kilograms of a
specific chemical lost to the atmosphere per kilogram of the chemical pro-
duced or used. Multiplication of the emission factor by the quantity of the
chemical produced or used at an individual site or in a specific geographic
region during a specific time period yields the estimated emissions of the
chemical, in kilograms, for that location.
The total emissions resulting from the production of a chemical or
chemical intermediate use of a specific chemical are a summation of process,
storage, and fugitive emissions losses:
> Process emissions are discrete losses that occur at process vents from
reactors, columns, and other types of plant equipment.
> Storage emissions include losses from the raw material feed, in-
process and final product storage tanks, as well as from loading and
handling losses.
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> Fugitive emissions are losses that result from plant equipment leaks,
visual openings, evaporation from waste products, and other non-discrete
sources.
If possible, emission factors should be determined for each of these
types of emissions. To develop specific chemical emission factors various
i '
methods are available. Each method produces its own level of reliability
of the resulting data. Below are listed some of these methods, in decreasing
order of reliability:
> Plant Site Visits: Data are collected by actual site visits or
from letters to producers. In certain instances this actual data
from a few producers may be useful for preparing model plant parameters
for a large number of producers.
> State Air Emission Inventory Questionaires (EIQs): The air EIOs for
most manufacturing sites are on file at various state air agencies
throughout the United States.
> Other Published Sources: A variety of published reports for different
chemicals and types of sources have been orepared by EPA and for EPA
by contractors. The most recent publications should be used.
> Engineering Estimates: Occasionally certain pollutants are produced
or used in a sinilar manner. In such cases, estimates from an unknown
process can be made by generalizing from a similar, previously defined
process. In other instances, an emission factor for an unknown
chemical intermediate use of a specific chemical can be calculated
based on a weighted average factor of all other known chemical
intermediate uses of the same chemical.
Once the emission factor is determined it must be multiplied by the plant's
consumption to determine the emission rate required for input to the HEM.
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Vent Parameter Data
Vent parameter data are necessary for dispersion modeling of the
chemical emissions. The vent parameter data in each of the chemical
summaries include the number of process and storage tank vents, vent height,
vent diameter, gas discharge temperature, gas emission velocity, fugitive
i *
discharge area, and building cross-sectional area. These data can be
obtained from the same four source levels discussed above, under emission
factors. Some data are supplied by producers during site visits, some data
are obtained from EIQs, and some from other published reports or text
books.
Atmospheric Reactivities of Chemicals
A variety of studies have reported the lifetime or atmospheric residence
time of many listed chemicals. Often, however, the basis for the decay
rates are not given and reconciliation between studies tends to be impossible.
In this instance, all available data and best engineering judgment should
be used.
Most chemical destruction of gaseous compounds in the atmosphere occurs
by one of the following three mechanises:
> Photolysis
> Reaction with free radicals (chiefly hydroxyl)
> Reaction with atmospheric oxidants (chiefly ozone)
The process of photolysis and reaction with hydroxyl radicals occur only during
daylight hours. Hydroxyl radicals have a short atmospheric residence time
and requirs a continuing photolytic source to maintain their concentrations.
Thus, if no source for the hydroxyl radical exists, no reaction will occur.
2-5
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The HEM is generally constrained to a study area in a 50 km radius of
the source. In most instances, the reactivity of a chemical is not sufficiently
high to cause significant removal before the material is dispersed to this
distance. Therefore, this input to the HEM can be left blank with the
model assuming no atmospheric decay. Some chemicals, however, do have high
t "
reactivity (e.g., formaldehyde) and should be analyzed for this behavior.
2-3. Dispersion Modeling
The previous section discussed the information necessary to run the
SHED model. This section explains how that data is used to give the
resulting exposure/dosage estimation.
The concentration patterns caused by major point source emissions
depend most strongly on four factors.
> Emission rate
> Source elevation above terrain (stack height); effective plume
elevation may, in turn, depend on meteorological factors
> Wind vectors (speed and direction)
> Dispersive effects (intensity of atmospheric turbulence)
The dispersion node! in SHED is a Gaussian model in the climatological form
of the EPA's Climatological Dispersion Model (COM) in that it uses the same
basic dispersion algorithm, is coded and used to estimate the annual average
ground-level concentrations resulting from emissions of major point sources.
Flat terrain is assumed.
The maximum radius generally considered in the exposure/dosage estimation
is set as 50 km for major point sources. Concentrations are estimated for
10 receptors--0.2, 0.5, 1.0, 2.0, 5.0, 10.0, 20.0, 30.0, 40.0, and 50.0 km
from the sourcealong each of the 16 wind directions. In some instances
2-6
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there may be more than one type of point source (each with its characteristic
release height, emissions rate, etc.) within a single plant. Fugitive
emissions (valve and flange leaks, etc.) that are random and indeterminate
but not negligible can be approximated by an area or volume approximation
at a reasonable level above the ground (l-10m). This is the height range
( '
typical of outdoor plumbing. Each emissions category is modeled individually,
and the total ground-level concentrations resulting from plant emissions
are then computed by summing the individual estimates.
The dispersion algorithm can also treat chemical formation and decay,
enhanced dispersion caused by building wake effects, and release or stack
height. These features are discussed in the following subsections.
Chemical Reactivity
The detailed approach adopted in estimating the effect of chemical
reactions on ambient concentrations is shown with chloroprene as an example.
Chloroprene is an organic compound that is decidedly photoreactive in the
atmosphere. Based on preliminary calculations conducted with the estimated
chloroprene atmospheric decay rate, approximately 90 percent of the chloroprene
emitted into the sunlit urban atmosphere would be removed within an hour
through reaction with hydroxyl radicals and ozone molecules. However, the
chemical decay rates are much lower in the nighttime or under overcast
conditions. Figure 2-1 displays a comparison between the resulting con-
centrations along a single wind direction with and without the chemical
decay computed for a chloroprene example. Because the atmospheric reactions
change atmospheric concentrations over time, the reactivity of a compound
has less impact on the concentrations near the emissions source than further
downwind. The difference in concentrations between the two curves of
2-7
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100.0
0)
I
&
s
o
REACTIVE (REFERENCE
0.1 0.2 0.5 1.0 2.0 5.0 10.0 20.0
Downwind Distance fron Source (km)
Source: Systems Applications, Incorporated computations using SAI
dispersion model and SAI reactivity estimates.
FIGURE 2-1 EFFECTS OF CHEMICAL REACTIVITY ON CONCENTRATION
DISTRIBUTION OF CHLOROPRENE
2-8
-------
Figure 2-1 at 200 meters from the source is about 3 percent (43.2/41.9 -
1); at 20 km from the source the difference is about 30 percent (0.070/
0.054 - 1).
Building Wake Effect
Pollutants emitted into the wake of a building are subject to an
i '
enhanced dispersion (e.g., the concentration is reduced very quickly by
the turbulence on the lee side of the building). If a dispersion analysis
ignored this effect, the occurrence of high concentrations would be over-
estimated.
The grou/id-level concentrations that result from different building
structure dimensions are depicted in Figure 2-2, where the major parameters
for estimating these concentrations are the same as those of the reference
case. Clearly, the building wake effect would have insignificant impacts
on ground-level concentrations at points further downwind from the source
than 1.0 km. However, sources with larger building effects would result
in larger ground-level concentrations near the sources. Additional analyses
that assess the precise impacts of building wake effect may be required to
determine the extent to which the example in Figure 2-2 is site-specific.
Release Height
The exact release height of a source can have a great effect on ground-
level concentrations. As Figure 2-3 shows, concentrations resulting from
ground-level emissions (H = 0) can be more than 10 times as great as those
resulting from emissions at a moderate height (H > 20 m). However, these
differences become insignificant further downwind (R > 5 km).
Figures 2-1, 2-2, and 2-3 indicate that groundlevel concentrations
decrease approximately log-log linearly with distance at receptors more
2-9
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100.0
0.1 0.2 0.5 1.0 2.0 5.0 10.0 20.0
Downwind Distance from Source (km)
Source: Systems Applications, Incorporated computations using
SAI dispersion model and SAI building wake algorithms,
FIGURE 2-2 EFFECT OF BUILDING WAKE ON CONCENTRATION
DISTRIBUTION OF CHLOROPRENE
2-10
-------
1000.0
20 m aฃ?ฃRENCt CASE)
0.1 0'.2 OJ ''llo 2'.0 S'.O ' 10.0 20.0
OUUnci from Sourct (ta)
Source: Systems Applications, Incorporated com-
putations using SAI dispersion model and
Briggs' plume rise formulas
FIGURE 2-3 IMPACTS OF RELEASE HEIGHT ON CONCENTRATION
DISTRIBUTION OF CHLOROPRENE
2-11
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than 2 km from the source. A plot of this log-log linear relationship
could be used to interpolate concentrations at specific locations within
the range of 2 to 50 km from the source.
Exposure and Dosage Estimation Scheme
The dispersion modeling approach is coded in a standard Fortran program.
The output of the program is a concentration array for 160 receptors around
the plant (10 receptors along each of the 16 wind directions). These are
the sum of concentration patterns resulting from all sources within a
plant. This subsection outlines the basic approach used in combining the
concentration pattern with the population distribution pattern around a
plant. Three terms are defined here that will be used frequently in the
following discussion. A polar grid point is one of the 160 receptors at
which concentrations are estimated by the dispersion modeling. A population
centroid is the population-weighted geographical center of a BG/ED for
which geodetic coordinates are known. A grid cell is defined as the area
bounded by two radial arcs and two wind directions.
Exposure is the product of the population and the concentration to
which that population is exposed. To form this product, both the concentration
and the population must be known at the same location or point. The SHED
model uses a two-level interpolation scheme to pair the concentrations with
populations prior to the compution of dosages and exposures. The two-level
approach is appropriate because the concentrations are defined on a radius-
azimuth (polar) grid pattern with non-uniform spacing. This means that at
small radii the grid cells are much smaller than BG/EDs while at larger radii
the grid cells are much larger than 8G/EDs. Interpolation techniques are most
appropriately applied by interpolating values of the factor defined on a
coarse network (larger) at the locations of the finer (smaller) network, thus
2-12
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maximizing the resolution and minimizing the uncertainties of interpolation.
As previously mentioned, the fine/course relationship between polar grid
cells and BG/EDs varies with radius. Hence, the two level approach allows
the BG/ED population to be interpolated to the grid point when the BG/EDs
are larger than the grid cells and allows the grid point concentration to
i *
be interpolated to the BG/ED centrofd when the reverse is true. The details
of this approach are outlined below. The numbers used assume the analysis
is to he completed for a 50 km radius. If the maximum radius changes, so
will the radii of the grid points.
For BG/ED centroids located between 0.2 km and 3.5 km from the source,
populations are apportioned among neighboring polar grid points. There are
64 (4 x 16) polar grid points within this range. Associated with each of
these grid points, at which the concentration is known, is a smaller polar
sector bounded by two concentric arcs and two radial lines. The boundary
concentric arcs are defined by radii of .10, .35, .75, 1.5, and 3.5 km and
the boundary radial lines are drawn right in the middle of two wind directions.
These boundary lines are represented by the dashed lines in Figure 2-4. Each
of the polar grid points are assigned to the nearest BG/ED centroid identified
from the census data set. The population at each centroid is then apportioned
among all polar grid points assigned to that centroid according to the area
of the polar sector associated with the grid point. For example, all of
the polar grid points (labeled b) nearest population centroid 3 would be
assigned a certain proportion of the people in B. The ratio between the
area of the polar sector and the area assigned to the population centroid
determine the proportionment. Thus, the population density is assumed to
be the same for all polar sectors assigned to a single centroid. Figure 2-4
shows that the grid points closer to the source are boxed in by much smaller
2-13
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Figure 2-4. Pairing of BG/ED with Concentration Within A 3.5 Km Radius
Population Centroid
Polar Grid Point
Polar Sector
A, B, C - Locations of BG/ED Centroids
a b c - Polar grid points to be allocated a portion of population
reported at centroids A, B, C, respectively.
-------
sectors than those further away. Hence, the b grid points closer to the
center will receive a smaller apportionment of the people from population
centroid 3 than those further away. Both concentration and population
counts are thus available for each polar grid point.
Log-log linear interpolation is used to estimate the concentration at
i *
each ED/BG population centroid located between 3.5 km and 50 km from the
source. Concentration estimates for 96 (6 x 16) grid points (receptors at
5.0, 10.0, 20.0, 30.0, 40.0 and 50.0 km from the source along each of the
sixteen directions) resulting from dispersion modeling are used here as
reference points for this interpolation. For each ED/BG centroid, four
reference points are located at the four corners of the polar sector in
which the centroid is located. These four reference points (labeled Cj, Cg,
03, and 64) would surround the centroid (Cx) as depicted in Figure 2-5. As
shown in Figures 2-1, 2-2, and 2-3, there is a linear relationship between
the logarithm of concentrations and the logarithm of distances for receptors
more than 2.0 kn away from the source. This relationship is used to estimate
the concentrations at points CAj and CA2 (see Figure 2-5). These estimates,
are then linearly interpolated with the polar angle to determine the con-
centration at the centroid (Cx). Using the two-level approach, concentrations
and populations are paired up for the 64 concentration grid points within
3.5 km of the source and for all 3G/ED centroids located between 3.5 km and
50 km fron the source.
The total dosage was then computed as follows:
11
Total Annual Dosage (ug/nr-person) = / ^ P^Ci
N
^M
i
2-15
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Figure 2-5
Log-linear Interpolation Scheme
\
|C3 \ CA2
1
C4
Given:
A -
R2 -
C\ -
C2 -
03 =
04 s
The angle in degrees subtended clockwise about the source from due south
to the BG/ED centroid;
The angle from due south to the radial line immediately counterclockwise
from A, or passing through A if there is an exact match;
The angle from the south to the radial line immediately clockwise of A]_
(A2 is 0 if it is due south);
The distance from the source to the BG/ED centroid;
The distance from the source to the largest circular arc of radius on
grid that is less than R;
The distance from the source to the smallest circular arc of radius on
grid that is greater than or equal to R;
The concentration value at (A^,
The concentration value at (A]_,
The concentration value at (Ag,
The concentration value at (A2ป Rฃ); then
exp (In GI + (In Ca - In GI) (In R - In
exp (In 03 ป (In C^ - In 3) (In R - In
+ (CA2 - CAi)(A - A!) / (A2 -
/ (In R2 - In
/ (In R2 - In
2-16
-------
where P^ = the population at point i, C^ = the annual average concentra-
tion at point i, and N = the total number of grid points and EO/BG cen-
troids with a specified combination of concentration and population
(representing the entire area within 50 km of the source).
The population exposed to each of a number of concentration levels,
Lj, was computed by:
N
m
Exposure to Lj (person) =
where
if Ci < Lj
if
The dosage of the fraction of the population that is exposed to concentra-
tions greater than or equal to each of a number of concentration levels,.
Lj, was computed by using the following summation:
Annua
l Dosage at Lj (ug/m3 -person) = \^ ฐiCiSi (Ci ,Lj)
Note that the annual dosage at the minimum concentration within 50 km of
the source will equal the total annual dosage.
2-17
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The concentration levels at which exposure Is to be estimated are
selected by an exponential function coded In the program.
2-4. Assumptions
In order for SHED to be simple, run quickly and require as little
input data as it does, certain assumptions must be made. This section
i '
outlines the necessary assumptions to provide the user with an understanding
of the limitations of the model and the need to consider such limitations
in the use of the output data.
Population Count Errors
The SHED model uses census data to the 8G/ED level. Although this is
the smallest defined population unit, it still places on average approximately
800 people at one point. In reality, some people will reside closer to the
plant and may be more highly exposed. For others, the modeled exposure
*ill be an overestimate of the actual exposure.
Another problem occurs when two plants are located within 50 km of one
another. The people who are exposed to both plants will be counted twice
in the summation of the exposed population. Although the number of people
will be an overestimate, the dosage (people times concentrations) is not
affected by the overlap of the study areas. Two people each exposed to a
concentration X from one of two plants is regarded as the same amount of
exposure as a single person exposed to a concentration of X from both.
Populations may be partially doublecounted if sources are close to each
other, but aggregate exposure is not.
The SHEO model may also mislocate people if a plant is located near a
large body of water. The manner in which SHED spreads the population to
the concentrations within the 3.5 km radius allows the program to assign
2-18
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people to areas which may be covered by bodies of water. One potential
problem may arise if the program determines a maximum concentration to which
people are exposed that is located over a lake or other body of water. In
this case, it could be argued that no one is actually exposed to this con-
centration. For those sources that appear to produce maximum concentrations,
i '
identification of the receptor location and consultation of topographical
maps to verify public exposure is recommended. If the maximum receptor is
located in an area where people would not reside, the next highest receptor
should be used or that plant should be modeled individually with a different
more specific model.
Concentration Pattern Errors
The concentration patterns used in the exposure computations are
obtained through atmospheric dispersion modeling based on known source
characteristics and weather patterns at nearby stations. Naturally, any
deviations in these estimates from the true pattern directly affect the
exposure results. Thus, if the nearest STAR station is 50 - 100 miles
away, the weather patterns may not be representative of the weather
patterns in the area around the source.
The program also assumes flat terrain. This is especially crucial
when dealing with sources in a valley/mountainous area because the STAR
station will not give adequate information to model the wind patterns
accurately.
In addition, the SHEO model uses a Gaussian dispersion model to determine
the concentrations around the source. This model is based on how gases will
act when dispersed from a stack. Thus, if the pollutant is fibrous or
particulate, such as asbestos, the assumption that the pollutant behaves
as a gas may misrepresent the actual dispersion pattern.
2-19
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The assumption Is also made that the annual average weather conditions
continually persist and that the source emits at the annual average amount.
At times, these averages may not be representative over shorter terms. It
also assumes that each recorded wind persists in a given direction long
enough to yield dispersion out to 50 Km.
i '
Commuting Pattern Errors
There are also time-dependent aspects of the exposure problem. The
exposure program uses a time-averaged concentration pattern for each source,
so that the time dimension is ignored in the computations. If the population
distribution were essentially constant over the averaging time period, the
resulting estimates would be true averages. However, population distributions
are constantly changing as people commute to work, go shopping, and take
longer trips. Particularly in urban industrial centers, the shifts in
populations and concentrations throughout the day may be highly correlated;
thus, the actual exposure may differ considerably from the value obtained
by matching time-averaged concentrations with population distributions
based on census addresses. Whether the exposure is over- or underestimated
depends on whether populations in the vicinity of a source are drained
(e.g., because people leave residences near the source for work in an urban
center) or are augmented (e.g., because of employment near the source).
2-5. Using the SHED Model
To use the model you must first obtain (1) a user 10, (2) an account
number and (3) a project 10. These may be obtained by following the
instructions in Section 1-3. You, the user, may then access and use the
HEM by the procedures described throughout this chapter.
2-20
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Logging On
Generally, when you approach a hard-wired terminal, the screen will be
blank but the terminal is on. To get the Sperry log on directions push the
button labeled transmit (or XMIT). The screen should now look like this:
****************************************************
! * *
* Welcome to the Sperry 110/82 System! *
* *
* "Tab" to the desired session and XMIT *
* *
* DEMAND for a DEMAND session *
* *
* MAPPER for a MAPPER session *
* *
****************************************************
The small rectangle in the upper left corner is the cursor. The cursor
may be moved by pressing any of the directional keys, the space bar, the
back space, tab forward or tab back. The easiest way to position the cursor
in this instance is to press TAB FWD as indicated by the directions. This
should place the cursor immediately following the first "DEMAND" on the
screen. Now press XMIT. If you are accessing the model through a moden,
you must establish communication with the UNI VAC computer. The commercial
phone number for the NCC is (919) 541-4642. Long distance users can use
TELENET to reduce phone charges. Please refer to Section 1-4 for the
appropriate contact personnel who can help with more specific instructions.
Once you are connected with the NCC, press XMIT. The screen will write the
options for access. Type UNI and hit XMIT.
After requesting the UNI VAC demand mode with either the hardwired
system or the modem connection, the screen should roll up and write
the following:
xxxxxxxxxxxxxx ENTER USER ID/PASSWORD:
If the soe (>) or prompt and cursor appear above the line, type
2-21
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@@INS 11 and XMIT. This should move the cursor below the line. The very
first time you log on to the terminal, you must type your user ID, a slash
(/), your user 10 again, a slash (/) and your password. The password is
your own invention but after the first log on remains the same until changed
(i.e., remember what you used). After the first log on, you simply type
your user 10, a slash (/) and your password. At any time, you may change
i '
your password when you log on. UNI VAC requires that you change your password
every 90 days. This is accomplished by typing your user ID, a slash .(/),
your old password, a slash (/), and your new password. Remember to hit XMIT,
enter or return in order to enter any line. The system should respond with:
* Destroy user-IO/password entry
* UNI VAC 110 Operating System
Enter Run ID or (CR) for default to USER ID
The Run 10 consists of 2-6 characters which are chosen from A-2 and
0-9 only. As a National Computer Center (NCC) user, the first two characters
of the Run 10 should be your MCC bin number. The last four characters
can be anything which will allow you to identify your run. The user's
initials are often chosen for this reason.
Always press XMIT enter or return after typing any line to be entered.
The computer will then ask a series of questions which you, the user,
answers. The example below shows the questions the computer will ask
(underlined here to distinguish from user response) and the user's response
to each question.
Enter Run 10 or (CR) for Default to USER ID
08 XY
Enter Account Number
69096FRZ
Enter Project-ID
ABCD
2-22
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Enter UID
SASDPHEP
After typing each response, the user must hit XMIT for the transmission
of the response. After entering the final response, the computer will type
out several lines of information. For example:
Run Number 46
Last Run at: 072784 140637
Date: 073084 Time: 103448
*** News Current as of 11:19:47 on 07/23/84 ****
When the computer stops typing information and the cursor stops beside
an soe (>) you are logged on to the computer and ready to begin.
* * *
NOTE: For all the instructions below, all information within
commands which are specific to your file or run will be
typed in small letters and contained in parentheses. For
example, @@CONS RC (run id) means type @@CONS RC 08PT if
08PT is the run id of the run you needed to check. Dp_
not type the paretheses.
* * *
Cataloging Files
The UNIVAC system works with two types of files; data files and program
files. Contrary to its title, the program file is used only for storage
and may be broken into elements to store several sets of data. The data
file has only one set of data and is available for use by the program.
In order to use the HEM, a program file must be cataloged to store
data and two data files must be cataloged in order to run the program
2-23
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(one more data file must be cataloged in order to run Decay rates for the
chemical). To catalog these files certain commands must be entered which
basically name the files. Many catalog options are available but the catalog
statements conventionally used to catalog the files for HEM are:
Program file: @CAT,P (FileName).,F33,NCC040
^*^._.
/ "N
1-12 Alphanumeric characters
Data files: ?CAT,P (Qualifier)*Gauss-in.,F33, NCC040
1-12 Alphanumeric characters ^
flCAT.P (Oualifier)*Gauss-out.,F33,NCC040
ASAME AS ABOVE
0CAT.P (Qualifier)*0ecay.,F33,NCC040
f
SAME AS ABOVE
Please type the above lines exactly as they appear except the "Filename"
and "Qualifier" should be your own invention. The Filename in Line(l) may be
any alphanumeric name with 1-12 characters. The Qualifier lines (2), (3)
and (4) may also be any alphanumeric name of 1-12 characters. The Qualifier
used in line (2) must, however, be exactly the same as the Qualifier in lines
(3) and (4).
Once this is accomplished, you have cataloged all the files you will
ever need to catalog to run HEM. As previously mentioned, the program file
cataloged by line (1) can store a larqe number of files under various element
names. To run the program you can empty the GAUSS-IN file and add the data
from the element. This must be done because data files (GAUSS-IN is a data
file) cannot be broken into elements. By emptying and reusing the
GAUSS-IN. file, however you only need one.
At this time, a discussion of file names is pertinent. A program file
name has three primary parts: the qualifier, file name, and element name.
2-24
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It looks like this:
Dualifier*Filename.Element
The cataloging instructions given above do not give the program file a qualifier.
Hence, the system assumes that the project 10 (which was used to log on) is
the qualifier. If a different project ID is used to log on, the old project ID
must be included as the qualifier when calling the file. Otherwise the
Filename.Element is sufficient to call the file.
Data files have only two primary parts because data files have no elements.
Data files look like this:
Qualifier*Filename.
In the case of HEM data files the file name is always GAUSS-IM, GAUSS-OUT
and DECAY. The qualifier is not the project 10 but whatever was assigned
when the files were cataloged.
Now that all necessary files have been cataloged, data can be entered
using the instructions below.
Entering Data
To enter data into a file a text editor must be used. Several text
editors are available but the most frequently used on the UNI VAC for HEM is
the Maryland Editor. PC users familiar with the PC editor and KERMIT or
XTALK can create a file in the proper format on the PC and send the file to
the UNI VAC. A text editor has various commands which allow data to be
input, changed, rearranged and/or deleted. A summary of often used commands
for the Maryland Editor is shown in Appendix C. At this point it is important
to read Appendix C and become sonewhat familiar with the commands listed.
A complete list of commands for the Maryland Editor nay be found in the "Text
Editor User's Guide" by Hagerty and Sibbald (1975).
To call the Maryland Editor, enter the command (?EOM, a space, the
file name which has been cataloged, a oeriod and an element name.
2-25
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For example:
@EDM Filename.Element (An element is any alphanumeric name
including "-" which has 1-12 characters)
The first time this file element is accessed, the element is created and
the editor automatically places you in input mode. The UNIVAC will respond
with:
F.DM 2981 MEM 02/28/86 16:34 I(0):F
INPUT
>
Please hit XMIT, enter or return as suggested in Appendix C to get to the
edit mode and use the commands listed there to input the data. When you
hit XMIT, or when you enter an element that has been created previously,
the UNIVAC responds with:
EDIT
*>
Once in the edit mode, the file is ready for entering data. The format in
which data must be entered for HEM is discussed in the following subsection.
Data Format
The HEM is designed such that the program reads numbers from certain
columns and rows of data. If the numbers are not in the proper position,
the computer will misread the data. This can cause unusual and incorrect
results or prevent the program from completing the run. Thus, this section
is very important to follow closely. To check to see if a line has been
entered correctly type P and XMIT. This should print the line. Next type
SC and XMIT. This will print a scale of numbers under the line to make
column counting easier.
Each line of data, referred to as a card, has a specific function and
format. The first card to be entered is entered once for each run and
contains the following information [Remember to type I and a space in order
to enter the data in the edit mode]:
2-26
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Columns 1-5 = Greater than or equal to the number of plants;
right justified (used as scratch space
allocation)
Columns 6 - 10 = Blank spaces
Column 11 = Indicator as to whether maps are to be produced
as part of the output, (Maps - Table of estimated
BG/EO and Population at centroid by 16 wind
directions and 10 distances), T = Yes, F = Mo
Column 12 = Indicator as to whether the exposure analysis
should be performed out to each ring distance
separately, T = Yes, F = No
Columns 13-23 = Unit risk number for lifetime risk
Next, one set of three cards is entered for each facility. They contain
the following information:
Card 1, Columns 1-80 = The name of the chemical being modeled.
Card 2, Columns 1-80 = The location of the facility given as the
facility name, city and state.
Card 3, Columns 1-6 = Latitude of the facility in degrees, minutes,
seconds. (Two digits each with no spaces
or symbols between, e.g., 414900).
Columns 7-13 = Longitude of the facility in degrees (must be
three digits), minutes, seconds, (e.g., 0784900).
Columns 14-18 = Star site identification number. This is the
location to be used as a source for meteorological
data by the model. It is optional and if a number
is not provided (the field is left blank) the
2-27
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program will automatically find the closest
source of meteorological data and use it (see
note below).
Columns 19-38 = Meteorological data values which may be left
blank if such meteorological data are not avail-
able. The program will automatically use
i '
standard values for these fields. (19-23 = ambient
temperature in degrees Kelvin, 24-28 = temperature
lapse rate to be used for 0 stability, 29-33 =
temperature lapse rate to be used for E stability^
34-38 = temperature lapse rate to be used for F
stability). (See note below)
* * *
NOTE: To make data entry easier, enter all columns of consecutive
data using I, space, and the data. If several blank spaces
are to be entered between the first group of data and the
next group, enter the first group hit XMIT and use the R,
column number command to enter the second group. For
example, to enter card 3 with samole data type:
I 4249000784900 (XMIT)
R,39 000001
This will enter 42ฐ49'00" for the latitude, 78ฐ49'00"
for the longitude, blanks for the star site and
meteorological data, urban setting and one source at
the facility.
* * *
Column 39 = Indicator as to whether the facility is located in
an urban or rural setting. 0 = urban; 1 = rural
2-28
-------
Columns 40-44 = Total number of sources to be modeled at this
facility (right justified). These columns must
be filled and must be accurate or the program
will not run.
Finally a set of cards, one card for each source at the facility identified
in columns 40 - 44 in card 3, is entered. These cards give the emission
characteristics of each source as follows:
Column 1 - Indicator as to emission type, P = process
vent,
S = storage vent, F = fugitive emissions,
H = stack.
Columns 2-13 = Emission rate in kg/year including decimal
point.
Columns 14-17 = Release height (Stack, vent or height of fugitive
release) in meters with decimal point.
Columns 13-21 = For P, S or H, this is the vertical building
(off vent or stack) cross-sectional area
(m^) perpendicular to the mean wind flow,
including decimal point. For F, this is
the area of release. This should be right
justified or contain a decimal point. (The
area should never exceed 2000 m^.)
Column 22 = Indicator as to vent type, 0 = vertical stack,
1 = non-vertical stack or vent.
Columns 23-25 = Inside stack or vent diameter in meters including
decimal point. (For fugitive leave blank)
2-29
-------
Columns 27-31 = Gas exit velocity from vent or stack in m/sec
including decimal point. (If this is unknown,
use at least 0.1 m/sec.)
Columns 32-35 = Gas exit temperature in degrees K including
decimal point. (If unknown, use 293-298 K.)
Figure 2-6 gives a good summary of all the above data. A xeroxed copy of that
figure and Appendix C (or this manual) should always be available while
adding data to a file.
You should now look at your file. The commands
T XMIT
0 9 XMIT
will allow you to see the first 9 lines of your file. Please compare this
to Figure 2-7, a typical program file. Using the delete, change and SC
commands correct your file so that it will contain the information you
want.
You should now exit the file. To do this type "Exit" while you are in
the edit mode. If you are running a chemical with no chemical reactivity,
you are finished entering data and may skip to "Running the Program." If
your chemical has chemical decay, you must follow additional instructions
below.
In order to run a program with chemical decay, a separate file must be
opened. A good suggestion to remember which decay file coincides with which
source file is to add -DK to the title of the source file to entitle the decay
file. So, to open the file (again using the Maryland editor), type:
0EDM File Name. Element-DK
Only one card is entered into this file which contains the following information
in the following format:
2-30
-------
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Figure 2-7. Typical SHED Data File
OOOO4 FF OO76
ASBESTOS
PLANT NAME NEW YORK CITY
4O43OOO74O10O O 1
F144. 1O.O1OO.11O.O.OOO9293
PLANT NAME RALEIGH, NC
334700O7839OO O I
Ffe . 8O 10 010O 110.O OOO9S93
ASBESTOS
PLANT NAME MONTPELIER, VT
44160O07S3'5OO O 1
F 1 SO 1 O O 10O 1 1 O O . OOOซ3a<93
ASBESTOS
PLANT NAME: PHEONIX, A/
4244560734145 OOOOO3
H30 19 4 . ซ5Ofe 1 3 O . 2 1 fe 1 S3 . 4fe2ซ97
HHOO3 7 . "5O6 1 3 . O . ป 1 6 1 1 H^H^ /'
11:? 14 so 1 a fofo 13 o . 7ซ->o 14 '::;4;.ป<:) /
2-32
-------
Columns 1-10: Daytime Decay rate (/minute)
Columns 11- 20: Nighttime Decay rate (/minute)
To convert half-lives to decay rates, you may use the following formula:
Decay Rate = 0.693/Ti/2
where 1\/2 *s the half-life in minutes.
Running the Program
Entering data into the program file stores the data for future use.
The contents of the program file must be entered into the data file in
order to run the program.
Adding the program file to the data file consists of three simple
steps: 1) open the file, 2) delete any previously stored data, and 3) copy
the program file into the data file. These steps can be easily performed
using any text editor. The Maryland Editor would use the following commands:
(?EOM (Qualifier)*Gauss-In. XMIT [Hit XMIT a second time if not in
edit mode.]
D * XMIT [This step deletes all previously
stored data.]
Add (Filename).(Element) XMIT
This places the data from the source parameter program file into the
Gauss-In data file. If decay rates are to be included, this data must also
be entered into a data file. To do this, using the Maryland editor, type:
ซEDM (Qualifier)*0ecay. XMIT
0 * XMIT
Add (Filename).(Element-DK) XMIT
Once the data is added to the file, the file should be exited and a
start card entered. The start card for the HEM without chemical decay
2-33
-------
should be entered as below:
@Start SASD*Start.Xposure/Point-50,/(Site ID),,,(Qualifier)
The start card for the HEM with chemical decay should be entered as follows:
$Start SASO*Start.Xposure/Decay-50,/(Site 10),,, (Qualifier)
The site 10 is the code which indicates where the results will be printed.
If the site 10 is omitted the results will be printed at Research Triangle Park.
A site 10 of FD05CR will cause the results to be printed on the 6th floor of
the Mutual Building. Most regional offices have a printer dedicated to the
UNIVAC that will have a Site 10. If there is not a UNIVAC printer available
to you, please see the information below. The Qualifier is the same as the
Qualifier in Qualifier*Gauss-In and Qualifier*0ecay. Once XMIT is hit, the
computer will print out a line of information. This information states the
run 10, the category and whether the project was accepted or rejected. If
it is accepted, the program is queued for execution and it is a matter of
time before the results will be printed.
The run 10 is the value printed after *TM*. If you would like to know
if the program has finished, you may use the run 10 in one of two commands.
The first is:
30CONS RC (run id)
This /nil tell you how many pages have been finished or if the program
has "finned." The second:
0SASD*WAIT.WAIT (run id)
will give you the same information but will continue to update the information
every 60 seconds or when the XMIT key is pressed. Typing any other command
cancels the 0WAIT.WAIT command.
Users who are using a remote terminal and who do not wish the results
of the SHED run to go to the National Computer Center (NCC) and do not have
2-34
-------
access to another site ID should use a different run card. This is typed as
as follows for the 50 Km run:
@ START SASD*START.XPOSURE/USER-50,,,(Filename)
The 50 may be replaced with 20 or 80 for 20 Km or 80 Km analyses.
Once executed, the file will not print out but will be saved until you
t '
type in:
(?@SEND, U
This down loads the files to your PC. Before typing this, however,
check on the file to see if it has been completed and is in the queue for
being printed. To do this type:
@CONS SX (run id)
Additional Miscellaneous Information
If the program is accepted but does not complete running, the most
common error is in the entering of the data. To check the data in the file,
reopen the file with the @EDM Filename.Element command and type:
NSITE X Y RM95PR
2-35
-------
The symbols "X" and "Y" here reoresent the the beginning line number and
ending line number. The RM95PR indicates where the data will be printed.
This specific code is for the Mutual Building 6th floor printer. Other
codes should be printed if another location is desired.
When the printout is available make sure all the data was entered
i '
exactly as the cards indicate. The most common error is inconsistency
between the number of point sources indicated in the third card and the
number of emission point source data listed. This will prevent the program
from running.
Another common problem occurs when large amounts of data are being
run. If the run takes longer than 10 minutes to run, the system will "time
out". This can be resolved by adding a comma and the number of minutes
needed to run the program to the end of the start statement. For example,
if 30 minutes were needed, the start card would appear as below:
flStart SASO*Start.Xposure/Point-50,/(site id),,,(Qualifier),30
Printouts of programs which exceed 200 pages are not allowed to be
printed on the Mutual Building printer. A simple addition to the start
card will cause only the summary pages to be printed at the Mutual Building
or other Site ID while the bulk of the material is laser printed at Research
Triangle Park. The simple addition is "-L" and is inserted after xposure
as below:
fcStart SASO*Start.Xposure-L/Point-50,/(site id),,,(Qualifier),30
This manual cannot cover all possible errors and you will probably
find newer and more exciting ways to make mistakes. Therefore, please use
References 2 and 3 to help find your errors, correct them and naybe learn a
few short cuts.
2-36
-------
2-6. Using Output from other Dispersion Models
The exposure portion of SHED model can be run using concentration
inputs from other dispersion models. To do this, the concentration file
must be in a compatible format. The Model Application Section of the
Monitoring and Data Analysis Division in the OAOPS ((919) 541-5690 or FTS
i '
629-5690) has succeeded in causing the Industrial Source Complex Long-Term
Dispersion Model (ISCLT) to yield compatible output. Once the ISCLT .output
is stored, you need only the filename and element (if there is one) to
access the concentrations.
Entering Data
Similar to running SHED without concentration input data you must set
up a file. The following information describes what data must be entered
and the proper format.
The first card is entered once for each run and contains the following
information:
Columns 2-3
Column 4
Column 5
Columns 6-10
Columns 11-20
= Number of radial rings you wish to analyze, right
justified (generally 10).
= Indicator as to whether maps are to be supplied
as part of the output, (maps - table of estimated
BG/ED and population at centroid by 16 wind
directions and 10 distances), T = Yes, F = Mo.
= Indicator as to whether the exposure analysis
should be performed out to each ring distance
separately, T = Yes, F = No.
= Number of sources to be analyzed.
= Conversion factor. (This number will be multiplied
times the concentration points to yield a converted
2-37
-------
concentration. Since the emission rate is propor-
tional to the concentration points, this factor may
be used to analyze various possible emission rates
with only one ISCLT run. Enter 1.0 if you wish the
concentration points to remain the same).
i *
Columns 21-30 = Unit Risk Number for lifetime risk; right justified.
The second, third, and fourth cards are entered only once for each run
and depend on the number entered above as the number of radial rings. If the
number is ten or less, only card 2 needs to be completed. If the number is
twenty or less, cards 2 and 3 must be filled. If the number is thirty or
less, cards 2, 3 and 4 must be used. The program is prepared to handle only
up to 30 radial distances. The format for each of the cards is identical.
Eight digits are allowed for each distance, ten distances are allowed per
card. For example, the first three distances would be entered as below on
card 1:
Columns 1-8 = radial distance closest to the plant (Km)
Columns 9-16 = radial distance second closest to the plant (Km)
Columns 17-24 = radial distance third closes to the plant (Km)
The next group of cards is entered for each plant or each chemical
analyzed and contain the following information:
Card 1, Columns 1-80 = Title of the concentration chart that
will be output. Generally, we enter,
"Concentration in Micrograms per Cubic
Meter."
Card 2, Columns 1-80 = The name of the chemical being modeled.
Card 3, Columns 1-80 = Name of the facility.
2-38
-------
Card 4, Columns 2-7 = Latitude of the facility in degrees,
minutes, seconds (two digits each).
Columns 9-15 = Longitude of the facility in degrees
(three digits), minutes (two digits)
and seconds (two digits).
Now the concentration information must be added to the file. If you
are analyzing only one plant and have only one concentration group, you may
add the entire file with the following command:
ADD concentration filename.element
If you have concentration results for several plants, you may add blocks
of data with the following command:
NUMADD concentration filename.element x y
where x is the starting line number and y is the ending line number of the
section you want to copy.
The process of entering plant data and copying the concentration file
for that chemical must be repeated until all plants have been entered.
Running the Program
Once the program file is complete, it must be entered into the data
file in order to run the program. This process is identical to running
SHED without concentration inputs except that the data file is called
GAUSS-OUT, rather than GAUSS-IN.. Using the Maryland editor, you would
type the following commands:
(3EDM (Qualifier)*GAUSS-OUT. XMIT
D * XMIT
ADD Filename.Element XMIT
Once the data has been entered into the data file, you may type the
following start card to execute the program:
2-39
-------
0START SASD*START.XPOSURE/XQT,/(Site id),,,(Qual1fler)
Now you may follow the Instructions in Section 2-5 to check on the
status of the run and obtain the printout.
2-7. Output from SHED
SHED produces two sets of output. The first set included the input data
t '
and the concentration grid table for each plant and the cumtnlulative risk summary
and the overall plant summary. This set also contains maps of population
centroids if this option was selected. The second set contains only the
cummulative risk summary and the individual plant summary.
This summary of the input data for one plant is shown in Figure 2-8.
Some of the values are rounded off but can be used to proof the input data.
The concentration grid, as shown in Figure 2-9, presents the modeled
concentration at each grid point. For example, the figure shows that the
concentration 1.00 kilometers south of the plant is predicted to be
8.8588 x 10-6 g/m3. The column labeled wind direction is actual direction
from the plant, not wind direction.
The optional maps show the population distribution about the source as a
polar grid displayed rectangularly. The four plots differ in the orientation of
their grids relative to the input concentration grid. Again, direction refers
to actual direction from the plant, not wind direction.
The first plot, seen in Figure 2-10, shows both the number of 8G/EO
centroids and the number of people in each cell of the input concentration
grid. The labels of the wind directions refer to the line directly above
them and the radius label refers to the line directly to the right.
The second plot, seen in Figure 2-11, gives the same type of plot as the
first except that the spaces shown are patches rather than grid cells.
2-40
-------
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2-44
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Patches are defined by the midpoint between cell radii and the midpoint between
wind directions. These patches form an area surrounding a receptor site
rather than each corner being a receptor site as in the case of the grid cell.
The last two plots, not shown here, are versions of the first plot, with
each input grid subdivided into quadrants. For each quadrant, the number of
3G/EO centroids (third plot) or the population (fourth plot) is shown.
The cummulative summary is shown in Figure 2-12. This table starts at
the highest concentration to which an individual is exposed. It then reports
how many people are predicted to be exposed to that concentration and the
resulting exoosure. The exposure is the product of the population and con-
centration. The next level is a certain increment lower concentration (about
1/2 of the previous concentration) with the number of people exposed to
that concentration or higher. The exposure in this instance is the cummulative
exposure from the level 2 concentration and those higher. The following levels
are similarly calculated until the concentration level reaches the miniumum
predicted.
The overall plant summary is shown in Figure 2-13. Three such summaries
are usually produced. The first is ordered according to the order of the data
file. The second is ordered highest to lowest by the maximum lifetime risk
number. The third is ordered highest to lowest by the annual incidence.
The first half of the overall plant summary deals with the risk to the
maximum concentration. The first column reports the maximum concentration to
which a person is predicted to be exposed. The second column reports the
number of people predicted to bp exposed to that concentration. The third
column reports the exposure (people x concentration) due to that concentration.
The fourth column reports the predicted lifetime incidence (exposure x unit
2-45
-------
Figure 2-12. Cummulative Summary
SUMMARY FOR IRON AND STEEL
MAXIMUM RADIUS ป 50.0 KM
LEVEL CONCENTRATION POPULATION
1
2
3
4
5
6
7
8
9
10
11
12
13
15
16
EXPOSURE
1.64E-03
l.OOE-03
5.00E-04
2.50E-04
l.OOE-04
5.00E-05
2.50E-05
l.OOE-05
5.00E-06
2.50E-06
l.OOE-06
5.00E-07
2.SOE-07
1.006-07
s.ooE-oa
4.61E-03
7
32
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7,230
66,700
240,000
733.000
2,310,000
9.000,000
22,500,000
23.000,000
31,500,000
33,500,000
33,600,000
33,600,000
33,600,000
1.19E-02
4.24E-02
3.17E-01
2.72Eป00
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7.00E*01
1.04E<>02
1.57E*02
1.67E+02
1.70E+02
1.706*02
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1.70Et02
2-46
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risk) due to the maximum concentration. The fifth column is one of the values
EPA uses to report risk. This is the maximum individual lifetime risk and
is calculated by multiplying the maximum concentration by the unit risk number.
The next part of the summary deals with the minimum and overall concentra-
tions and exposures. The first column of this half (the sixth column overall)
reports the minimum predicted concentration within 50Km of the plant. The
next column reports the total number of people exposed to any concentration of
the chemical within 50Km of the plant. The next column reports the cummulative
exposure. This is calculated by summing the exposure from each modeled receptor
site. The next column reports annual incidence and is calculated by multiplying
the cutnmulative exposure by the unit risk number which yields lifetime risk and
dividing by seventy (the estimated life span) to yield an average annual incidence,
This number is also frequently used to describe risk. The next column,
labeled repeat interval, is simply the inverse of the annual incidence column.
This is used to describe how many years elapse before one death is predicted
to occur. The last column reports the source name.
2-48
-------
Chaoter 3
3-1. Introduction to SHEAR
The Systems Applications Human Expsoure and Risk (SHEAR) model is
based on code and concepts developed in SHED. In contrast to SHED, which
was developed for a national estimation of risk, SHEAR was developed for
regional analysis. SHEAR is also more complicated to run as it has more
options and input files than does SHED.
There are four basic instances where SHEAR should be used: 1) If
there are two major point sources very close (within 5 km) to each other
and the additive concentration needs to be determined, 2) multiple pollutants
from one source need to be analyzed, 3) there are a large number of sources
within an area which cannot feasibly be located individually, or 4) when the
sources are so numerous and widespread that they act as an area source
rather than several point sources. In the first instance, SHEAR holds the
population constant within the study area and sums the risk. So, if a
person were exposed to a concentration X from source A and a concentration
Y from source B, SHEAR would report a single person exposed to a concentration
(X+Y). In contrast, SHED would report 2 people, one exposed to concentration
X and the other to concentration Y. Both models yield the same exposure
results but SHED double counts some of the people. Unfortunately, the same
mechanise which allows SHEAR to prevent double counting often causes the
model to underpredict the maximum lifetime risk. Even though SHEAR sums
the risk, it only sums these risks at population centroids. This eliminates
the area closer to the plant where people actually may be residing and
where the concentrations are much higher. For this reason, SHED, which
spreads the population out, almost always predicts a higher maximum lifetime
risk than SHEAR. Hence, SHEAR is generally not used to determine maximum
lifetime risk.
3-1
-------
In the second instance, SHEAR merely allows many chemicals to be run
at once. The same results could be obtained manually with SHED by adding
results of each run. SHEAR automates this procedure and, again, holds the
population constant.
The last two instances in which SHEAR would be used provide a means of
i '
analyses not available through SHED. SHEAR allows modeling of sources too
numerous to model individually through its prototype and area source .models.
Therefore, such sources as service stations, dry cleaners, etc. are more
appropriately modeled with SHEAR rather than SHEO.
In addition, SHEAR allows areas to be specified within the study
region. For instance, you can define each neighborhood in a county in
order to model residential emissions for that county, rather including
downtown areas, farmland and lakes. These capabilities make SHEAR a very
useful model for sources which cannot be modeled with SHEO.
3-2. Input Data
SHEAR requires several pieces of information in order to run properly.
Although SHEAR requires somewhat different input data than SHED, the
information still falls into the four major categories:
> Location Data
> Emissions Data
> Vent Parameter Data
> Atmospheric Reactivities
In addition, SHEAR requires input of the STAR station code number to
identify which meteorological data should be used. The following section
describes the input information needed for SHEAR and possible sources of
this information. Much of this additional information can be derived from
the same sources as those indicated in Section 2-2. In those instances,
3-2
-------
the appropriate earlier section will be referenced. Placement of the data .
Into the various files for use by the SHEAR program is discussed in Section
3-5.
As in SHED, SHEAR requires input of the unit risk estimate to link the
exposure to health risk. These estimates for cancer risk are generally
generated by the Carcinogen Assessment Group in a Health Assessment Document
for the chemical. A unit risk estimate is the estimated risk to an Individual
of contracting cancer if the individual Is exposed to one ug/rn^ of the
chemical for their entire lifetime. Hence it is expressed in units of
(ug/m3)-l. if the unit risk is not included, the concentrations and exposure
results are calculated with no calculations of health risk. Insertion of zero
for the unit risk will prevent the program from running properly. So, insert
one or leave blank if the unit risk is unknown.
Location Data
The location data for the major point source portion of SHEAR can be
determined by the means discussed in Section 2-2. It is important with
SHEAR, as with SHED, to locate the plants accurately, as the additive
concentrations will not be representative of the actual situation.
The location of area and prototype sources is different from major
point sources. These sources are not located specifically, but a box is
defined around them. First, you must determine the general area you wish
to study. (The area should be about the size of a county or a few counties.)
Then you must determine the specific coordinates of the southwest corner of
the box and the length and width of the box. This information can be
determined from:
> United States Geological Survey maps (7 1/2 and 15 minute series).
> U.S. atlas which has county breakdowns in state maps.
3-3
-------
The southwest corner must be in UTM coordinates. To translate geodetic
coordinates to UTM use the program described in Appendix B.
Often you will wish to model only a specific county(s) or part of a
county(s) within the box. The program has the areas of all the counties in
the U.S. defined. You still must box in the county and define the grid
cells but if you enter the Federal Information Processing System (FIPS)
( '
code of the county(s), only the area both inside the county and inside the
box will be modeled. The FIPS codes for the counties can be obtained from
the most recent copy of Worldwide Geographic Location Codes produced by the
U.S. General Service Administration, Office of Finance or from the National
Bureau of Standards FIPS Publication 55.
Emissions Data
Again, for major point sources, the emissions data can be obtained as
discussed in Section 2-2.
The emissions data for prototype sources can also be obtained by using
methods in Section 2-2. The emission rate used, however, should be an
average or prototypical emission rate because all sources will be modeled
to emit at the same rate.
The area emission rate may be obtained from a number of published
sources which include:
> Statistical Abstracts of the United States.
> Chemical Engineering Progress and other journals.
> Government publications of emissions and/or material consumption.
From these, the emission rate may determine as emissions/area or
emissions/person. Consumption rates can yield emission rates if an emission
factor is applied as earlier discussed.
Vent Parameter Data
Vent parameter data are necessary for the major point and prototype
dispersion modeling. These data can be obtained in the manner discussed in
3-4
-------
section 2-2. The parameters include the number of vents, vent height, vent dia-
meter, gas discharge temperature, gas velocity, fugitive discharge area and build-
ing cross-sectional area. The area source analysis does not require these data.
Atmospheric Reactivities
At^resent, chemical reactivity input is not available with the SHEAR
model. Although the card is structured to accept the data input, a separate
runstream initiating the program to use the data has not been implemented.
The need has not yet risen to develop this portion of the program because
very few chemicals are reactive enough to demonstrate changes within the
50 km radius.
Meteorological Data
Unlike SHED, SHEAR requires input of the desired STAR station code
number. The station selected should normally be the station closest to the
region currently being analyzed. A more remote station can be selected
if it is judged that its climate is more representative of conditions in
the analysis region. This might occur because of the relative oroximity of
the region and each weather station to coastlines or major topographical
features. Selection of a station other than the closest should be made only
upon expert advice. (See Section 1-2 for additional information.)
To obtain STAR station code numbers for the area of interest, a program
available on UNIVAC may be used. This program is called STAR-PICK and is
described in detail in Appendix A.
3-3. Dispersion Modeling
This section describes the algorithms used to process the input data
into the resulting exposures to populations. Each of the three types of
sources, major point, prototype and area, must be discussed individually as
each uses its own method to reach the end result.
3-5
-------
Major Point Source
The major point source for SHEAR is analyzed almost exactly the same
as for SHED (see Section 2-3). Therefore, the complete discussion will not
be repeated here. Two differences exist between the SHEAR point source and
the SHED point source. First, the two-level scheme adopted by SHED for
i '
pairing concentrations to populations is not used in SHEAR. SHEAR uses the
method of interpolating the concentration receptors to the BG/EDs from the
source out to the maximum radius. This is the same method SHED uses outside
the 3.5 km radius. Secondly, SHEAR is capable of storing all the con-
centrations and their locations. In the event that another plant emits the
pollutant within the same area, the new concentrations at each location
(BG/ED centroid) will be added to the stored concentrations at that same
location. SHEAR handles exposure to several chemicals from the same plant
in a similar manner. SHED does not have this capability.
Prototype Sources
Prototype sources are treated exactly as specific point sources except
for an algorithm for selecting sites for the required samples of each
prototype. PROTO code is the POINT code with the addition of the siting
algorithm and the provision of a single source characterization (the
prototype) to be used for every source that is sited.
The siting algorithm provides for a random selection of L centroids
where L is the number of locations to be selected. If it is desired that
some sites serve multiple samplesas, for example, a fraction of gasoline
service stations are sited in pairs, triplets, etc.then the number of
locations is determined by L = S + 2(0) + 3(T) + 4(Q):
3-6
-------
where
L = number of locations,
S = number of singles (single source),
D = number of doubles (two sources),
T = number of triplets (group of three sources),
i '
Q = number of quadruplets (group of four sources)
The actual sites are placed at randomly perturbed locations with.in
each selected district. That is, each site location is at the population
centroid map coordinates + (-) a random fraction of the district mean
radius to the east (west) + (-) a random fraction to the north (south).
This procedure approximately distributes sources by population density.
However, there is a rural/urban bias to ^G/ED population because some rural
BG/EOs can be very small; urban 3G/EOs almost never are. This bias would
tend to over-represent rural districts since the small rural BG/EOs would
have an equal probability of being selected; a counter-bias is provided
whereby BG/EOs of less than 1,000 population are randomly rejected and
replaced with another selection.
Area Source Analysis
The area source is used for those sources which cannot be specified in
detail. Such emissions must be inferred by relating them to oopulation,
motor vehicles, etc. For these sources, it is necessary to use a simple
dispersion algorithm to estimate concentration patterns. The Gifford urban
area dispersion algorithm (Hanna and Gifford, 1973) has proved to be a
simple but physically realistic model capable of estimating atmospheric
3-7
-------
pollutant concentrations caused by area source emissions in cities. The
basic Hanna-Gifford Equation is qiven as:
X = COo/U ,
where X is the air pollutant concentration, QQ is the effective emissions
rate per unit area, and U is the wind speed. The parameter C, qenerally
i '
referred to as the Gifford coefficient, is a weak function of the city
size; it mav be taken to be approximately constant. Theoretically, the
parameter C is qiven by:
C = (?) 1/J? . xl-b/[a(l - bH-1 ,
where X is the distance from a receptor point to the upwind edge of the
area source. The constants a and b are defined bv the vertical atmospheric
diffusion length, 0*2 = axb. Values of a and b for different atmospheric
dispersion conditions have been discussed by Pasqu-HI (1970, 1Q71). The
parameter C can be estimated for various combinations of the stability
factors a and b and by assuming that x enuals *alf the city size (Hanna,
1978). For example, 213 would be an aporonrlate value of C for a city with
a land area of 400 km2 under Pasquill Class D stability (while a = 0.15 and
b * 0.75). Specific values of the parameter C h?ve been emo*recallv
estimated bv Hanna and Gifford (1973) for a large number of 'J.S. cities
based on a larqe quantity of air quality data, averaoe annua1 emissions,
and meteoroloqical conditions. The mean value of C has been found to equal
225, with a standard deviation rounhlv half that magnitude. This value of
the parameter C has been recommended for use in evaluatinq an area source
by the EPA (1977a, b) if removal and decay orocesses "ปav hฎ neolected.
Estimates of the parameter C were calculated bv usino Equation 11 and bv
3-3
-------
assuming Pasquill Class D stability as the average long-term meteorological
condition.
The application of the Gifford approach within SHEAR has been modified
to provide variation of atmospheric concentration across a modeling region
in proportion to the local emission rate per unit area. This approach
provides a higher degree of resolution of concentration patterns than does
the single urban box approach, but does not address the details of pollutant
advection and dispersion that are treated by grid dispersion models.
In the present approach, box model (Gifford model) dispersion results
are simply scaled at each 8G/ED by the ratio of the density of emissions
per surface area at the 8G/ED to the regional mean emission density.
Options in the AREA code provide for varying or non-varying (from
district to district) emission rates. Emissions that vary with BG/EO are
scaled by the population density of the BG/ED. This is to address pollutant
emitting activities that uniform fractions of the population are expected
to be engaged in at any given time. Examples of such activities are motor
vehicle usage and operation of home furnaces.
Either uniform or nonuniform emission rates may be restricted to
specified portion of the modeling region. This feature is provided so that
the user may address such source types as crop spraying, tillage dust, area
burning, or other activities for which specified areas may be identified.
Equation 11 shows that the concentration is inversely proportional to
the wind speed. In SHEAR, each wind speed in the STAR set is used. The
STAR matrix is summed over wind direction and stability class to give the
frequency of occurrence of each speed. The concentration is computed as
the sum of the frequency-weighted concentrations for each wind speed.
3-9
-------
3-4. Assumptions
Similar to SHED, SHEAR makes certain assumptions in order to run with
limited data. This section describes the necessary assumptions to provide
the user with an understanding of the limitations of SHEAR and the need to
consider .such limitations in the use of the output data. The assumptions
for SHEAR include both those listed here and those covered in Section 2-4.
The SHEAR model uses census data to the BG/ED level. Although this is
the smallest defined population unit, it still places approximately 800
people at one point. This is not a realistic depiction of their residence.
Some of the people may actually be located closer to the plant and receive
greater exposure than modeled or vice versa. Unlike SHED, this is especially
true closer into the plant. Where SHED spreads the population out to all
the concentration points within the 3.5 km range, SHEAR simply uses the
interpolation method (which SHED uses from 3.5 - 50 km radius) for all
distances from the source so that all exposure occurs only at the population
centroid. This can result in concentration receptors close to the plant
being ignored because no people are assigned to them, even though people
counted in a nearby population centroid may actually be living in such
areas. This would result in an under estimation of the maximum concentration
to which people are exposed. Thus, even though the major point source portion
of SHEAR can add concentrations from several plants and risks of different
chemicals, the modeled maximum risk may not be as high as that modeled by
SHED. One advantage of the SHEAR methodology for using the interpolation
of concentration to people rather than people to concentration, is that
this method never locates people over large bodies of water, provided
population centroids are not so located (a circumstance the Census Bureau
strives to avoid).
3-10
-------
The prototype algorithm of SHEAR with the random location of sources
obviously cannot be assumed to correctly represent the actual source locations.
The results of the prototype model depend strongly on the population density
of the county being modeled.
The area source model requires more fundamental assumptions concerning
population and concentrations than do the other two types of sources. Unless
the area is well known and defined, portions of the study area such as parks
or lakes which contain no sources may be included into the area over which
the emissions are spread. Since area is contained in the denominator of
the Hanna Gifford Equation, the resulting concentration may be somewhat
lower than the actual. In addition, unless rural areas are deleted from
models of urban sources, people in the rural area who may not be exposed to
the pollutant will be included with those exposed. This model should be
used only to deternine a rough estimate of what public exposure might be,
unless the study is restricted to urban areas.
3-5. Using the SHEAR Model
The SHEAR model is more complex to run than the SHEO model. It is
designed to handle the various modeling techniques (area, prototype and
point), as well as, multiple chemicals. This flexibility requires the use
of several files and each file has its own format. Some of the data entered
in each file may seem redundant but must be entered in order for the
program to identify the appropriate files and to execute properly.
The number of files and neans of accessing the appropriate files
requires a brief explanation of how files are identified before you can
effectively use SHEAR. In order for a file to be identified, the qualifier
and the filename must be provided. If you type only the filename, the
3-11
-------
project ID is assumed as the qualifier. If you type *filename, the program
searches for the last @QUAL statement. That statement becomes the qualifier.
If no @QUAL exists, the project ID again becomes the default. If these
methods cannot define the appropriate file, you must type qualifier*filename
to identify the file.
* * *
NOTE: For all the instructions below, all information within
commands which are specific to your file or run will be
typed in small letters and contained in parentheses. For
example, (a<3CONS RC (run id) means type (a@CONS RC 08PT if
08PT is the run id of the run you needed to check. Do_
not type the parentheses.
* * *
SHEAR groups its files into two categories; area specific and chemical
specific. This allows several chemicals to be analyzed for the same study
area, using the same study area file. Both groups of files must be cataloged
before entering the data.
To name the area specific files, type:
0QUAL (Study Area)
The study area name may be any alpha numeric name with 1-12 characters.
This name is now the qualifier for all the area specific files. To catalog
the files type:
@ADD SASD*HEP-RUN.SHEAR-CAT/NON-QUALED
Several lines of symbols will be printed when you push XMIT. When the
computer responds with "READY" the area specific files are cataloged. You
may enter data now or catalog the second group of files.
To name the chemical specific files, type:
(3QUAL (Chemical Name)
3-12
-------
The chemical name may be any alpha numeric name with 1-12 characters.
This chemical name is now the qualifier for all the chemical specific
files. To catalog these files type:
0ADD SASD*HEP-RUN.SHEAR-CAT/OUALED
Again, the computer will print several lines of symbols until it responds
with "READY." At this point the chemical specific files are cataloged and
t *
you are ready to enter data.
Entering the Data
You are now ready to enter data into each data file. To do this, some
sort of text editor must be called. Several text editors are avilable but
for this example, we will use the Maryland text editor. Specific editing
commands for the Maryland editor are available in Hagerty and Sibbald's
"Text Editor User's Guide." A few commands are also provided in Appendix C
of this manual.
The first file to be entered is an area specific file which identifies
to the program the name of the chemical-specific files. This is the only
area-specific file which must be changed when running an additional chemical
with the same study area.
To open the file type:
3EOM {Study-Area)*QUAL.
Enter the following information:
0QUAL (Chemical Name)
In order to have the output printout alligned correctly, the format
should follow figure 3-1.
To open the first data file type:
9EDM (Studyarea)*SHR-XTRACT.
The data you enter into this file defines the area of the country which
will be modeled. Each line of data, referred to as a card, has a specific
3-13
-------
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function and format. If data Is not entered in the correct columns and
rows, the data will be misinterpreted by the program. Therefore, you should
enter the data exactly as described below (see also Figure 3-2):
Card 1, Columns 1-80 = An identifying name of the region, to be selected by
' ' user. This name is used in subsequent outnut headings
generated by any module using this data. The name may
be up to 80 alpha characters.
Card 2, Columns 1-10 = The UTM easting of the SW corner of a rectangle
sufficiently large to include the desired modeling
region. UTM coordinates are expressed in meters on all
USG maps. The 7 1/2- and 15-minute series .naps are
likely to be most appropriate sources of this data.
Because UTM coordinates are numerically large,
trailing zeros may be suppressed on some map displays.
Care should be taken to acquire and input coordinates
in kilometers. Up to 10 digits are allowed.
= The UTM northing of the SW corner referred to above.
- The UT"1 zone number. Since UTM coordinates are plane
approximations to a spherical surface, they are
defined for zones, each of which is limited in size
to limit the approximation error. UGS maps note zones
used. Coordinates are entered as up to 5-digit
integers.
= The size of cell to be used in Cartesian grid resolution
of 3G/ED areas. Small cells lead to fine resolution on
the plotter, but, since actual 3G/EO perimeters are
3-15
Columns 10-20
Columns 21-25
Columns 26-34
-------
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not known, finer resolution does not necessarily
produce more accurate definition of 3G/ED areas.
Hence, larger grid cells produce the same risk results
as small grid cells but the smaller cells produce
better plotted output. Larger cells also require
less computer time to run. The number of grid cells
used may be limited by available space or computing
time on the computer used. This XTRACT code limits
the grid to 10,000 cells. This limitation may be
changed at the user's discretion by recompiling the
programs. The cells will be square, so this datum
serves as both as X and a Y cell dimension.
Columns 35-40 = The number of grid cells desired in the X (E-W)
direction.
Columns 41-45 = The number of grid cells desired in the Y (N-S)
direction.
Card 3, Columns 1-4 = The year for which population is desired (used for
extrapolation from 1980).
Columns 5-9 = The number of counties for which the populations is
desired, (optional)
Card 4, Columns 15 = The FIPS codes of the counties to be selected. The
number of codes listed must be the same number of
counties stated in Card 3. (optional) If this option
is exercised, the analysis will be restricted to the
county(s) specified. The study area then consists
of the portions of the specified counties that are
within the box defined above.
3-17
-------
Card 5 = The region within the defined analysis area to
be excluded from the analysis (optional). The
region Is defined in the card by the minimum
and maximum rows (y coordinates) of any cluster
of cells to be deleted followed by the minimum
and maximum columns (x coordinates) in each
affected row, in sequence. Coordinates are .
expressed in units of cell number (five digits).
Cell number (1, 1) 1s the lower left corner of
the defined rectangle. (See Figure 3-3.)
This is all the data needed for the XTRACT file. The next data file
requires information concerning the weather (STAR) data. To open the file
type:
@EOM (chenical)*SHR-STAR.
The data should then be entered in the following format (see also
Figure 3-4):
Card 1, Columns 1-80 = The name of the chemical addressed in the present run.
This is to be used in subsequent headings.
Card 2, Columns 1-10 = The hazard factor (unit risk) for the chemical, if
available. This is required if hazard or risk or other
multi-species computations are desired. The factor has
units of cases (of health effect) per person.ug/m3.year.
Hazard factors are based on extensive analysis of
clinical and/or epidemic toxicology.
Card 3, Column 1 = \ flag, zero or one, to indicate if rural (1) or urban
(0) dispersion conditions prevail. This flag should be
3-18
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Columns 11-15
Columns 21-27,
Columns 31-36 and
Columns 41-56
set by a person familiar with EPA dispersion modeling
practices.
The station number of the United States Weather Service
reporting station from which STAR dispersion data is
desired for the present run. The station selected
will normally be the station closest to the region
currrently being analyzed. A more remote station
might be selected if it is judged that its climate
is more representative of conditions in the analysis
region. This might occur because of the relative
proximity of the region and each weather station to
coast lines or major topographic features. Selection
of a station other than the closest should be only
upon expert advice. (See Section 1-2)
Specification of portions of the selected STAR data matrix
to be deleted. The STAR matrix consists of a three-
dimensional array. The array variables are wind speed,
direction, and atmospheric stability. The set of
standard values of one or more of these variables
may be diminished if it is assuned that correlations
between source operation and occurrence of meteorological
conditions are such that the emissions and the variable
values are mutually exclusive. This data should only
be entered upon expert advice. These data entries
are in flag style (zeros and ones). Each parameter
is addressed by a string of flags, one for each
3-21
-------
standard value, In sequence. There are six wind speeds,
so there is a string of six flags for this parameter;
there are seven stabilities and 16 directions with
corresponding flag strings. If these columns are left
blank, all of the STAR data is used.
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Card 4, Columns 1-40 = Anbient temperature (in ฐK) and lapse rate (in ฐK/m).
Since the computation is an annual average computation,
only representative values can be used. Depending on the
application, mean or extreme values might be used. If
these cards are left blank, default values are used.
It is important, however, that a blank card actually
be inserted here. One way to do this is to type:
I Y (WIT)
C / Y / / (XMIT)
This will insert a blank card.
This completes the STAR data. The next set of commands demonstrates
what to enter for point, prototype and area sources. For major point
source model, enter the following (see also Figure 3-5):
0EDM (chemical)*SHR-POINT.
The data to be entered for this file is very similar to that entered for
SHED with a few exceptions. In fact, a SHED file can be added and edited to
create this file. The three cards should be entered for each plant and
each chemical. The data is entered in the following format:
Card 1, Columns 1-80 = The facility identification in alpha numeric characters.
Card 2, Columns 1-6 = Latitude of the facility in degrees, minutes and
seconds.
3-22
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Columns 2-13
Columns 14-17
Columns 18-21
Columns 7-13 = Longitude of the facility in degrees, minutes and
seconds.
(This is all that is entered in Card 2 for major point sources)
Card 3, Column 1 = Indicator as the emission type.
P = process vent; S * storage vent
F = fugitive emissions; H = stack
= Emission rate in Kg/year including decimal point.
= Stack or vent height in meters with decimal point.
= Building (of vent or stack) cross sectional area
(M^) perpendicular to the mean wind flow, including
demical point.
= Indicator as to vent type.
0 = vertical stack, 1 = nonvertical stack or vent.
= Inside stack or vent diameter in meters, including
decimal point.
= Gas exit velocity from vent or stack in m/sec
including decimal point.
- Gas exit temperature in degrees K including decimal
point.
In order to use the prototype portion of the SHEAR model you must open
the following file:
9EOM (chemical)*SHR-PROTO.
The data entered for the prototype source is identical to the data
entered for the major point source described above except for Card 2. This
card should be filled out exactly as follows (see also Figure 3-5):
Card 2, Columns 1-39 = Blank
3-24
Column 22
Columns 23-26
Columns 27-31
Columns 32-35
-------
Columns 40-44 = The number of prototype sources to be located
within the specified area.
Columns 45-49 = The number of sources which will not be located
in the same cell as another prototype (protosingle).
Columns 50-54 = The number of times that sources which will be
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colocated with only one other prototype.
Columns 55-59 = The number of times three prototype sources
will be colocated.
Columns 60-64 = The number of times four prototype sources will
be colocated.
(The sum of columns 45-49 plus 2X columns 50-54 plus 3X columns 55-59
plus 4X columns 60-64 must equal the number entered in columns 40-44.)
In order to use the area source portion of the SHEAR program type in the
following:
@EDM (chemical )*SHR-AREA.
The data should be entered into this file as indicated below (see also
Figure 3-6):
Card 1, Columns 1-30 = The area source identification name.
Card 2, Columns 1-10 = The emission rate per year per unit population
or per square kilometer. The units are Kg/yr.
Columns 11-20 = The number of people which you use as the unit
population above. If this number is zero, the
model assumes the emission rate to be Kg/yr/Km2.
Card 3, Columns 1-5 = Indicator as to whether the whole area is to be
used or whether additional areas are to be
added or subtracted. If the number of areas
is positive, then the areas are included; if
3-25
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negative, the areas are excluded and if the
number of areas is zero, the whole area is used.
= These cards define the area to be included or
excluded from the defined analysis region
(optional). The area is defined by the minimum
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and maximum UTM x coordinates (10 digits each
in kilometers) and- the minimum and maximum y
coordinates (10 digits each in kilometers).
This could be used to look at only crop areas
in a county (inclusion) or deleting a city park
from the analysis area (exclusion).
The last data file, called the Summarization Data File, must be filled
out for any SHEAR run. This file enters the unit risk number for the final
calculation. To open this file type:
(3EDM (studyarea)*SHR-REPORT.
Enter the data as follows (see also Figure 3-7):
Card 1, Columns 1-80 = Enter the chemical name as previously entered.
Card 2, Columns 1-10 = Unit risk number for lifetime risk.
Columns 11-42 = Filename, (chemical name*CONC-FILE.)
Cards 1 and 2 should be filled out for each chemical to be analyzed. This
allows separate reports to be printed for each chemical when running multiple
chemicals.
Figures 3-1 through 3-7 gives a summary of the data to be entered for
each file described above. It is strongly recommended that these summary
sheets be used when entering data into the data files.
3-27
-------
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Running the Program
Once the files have been filled as described above, the program is
ready to run. Unlike SHED, you have entered data into data files not
program files. Therefore, the files are ready to use by the model and do
not need to be copied.
Also unlike SHED, SHEAR has several options for being run. The
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following set of commands demonstrate a good way to run the prototype and
area sources. To begin, type:
QSTART START.SHR-PROTO-A,/(Site id),,.(Filename)
Once the program has finished running for prototype sources, you must
empty the XTRACT file of all concentrations. This is accomplished by entering:
0Copy (Filename)*86ED-FlLE., (Filename)*CONC-FIi_E.
This allows the program to use the data derived from EXTRACT without
rerunning that portion of the program. It also blanks out the prototype
data to prevent its addition to any subsequent runs.
To run area sources, type:
0START START.SHR-AREA,/(Site id),,,(Filename)
If you want to run area first, just substitute the word "area" for
"proto" and vice versa. The same applies to point source.
Two points are important to remember:
1. The "-A" as typed in the first start command is only used in the
start command for the first run of a chemical. (The "A" initiates the
XTRACT portion of the program which is not necessary to run again.)
2. Before making the next run, you must always empty the CONC. file
using the @copy command described above.
This method of running the program keeps the analyses separate. If
you wish to know the cumulative risk from thee point prototype and area
sources, simply omit the step in which you empty the cone. file.
3-29
-------
Users who would like the results of the SHEAR run to go to their PC or
user ID rather than be printed at the Mutual Building or other dedicated
UNIVAC printer should replace the letters SHR in the start card with USR.
Do not replace SHR with USR in the filenames. The file will then not print
out until requested. Please see instructions in section 2-5 to obtain
results(at your PC. To receive a laser printout at the Research Triangle
Park replace SHR with LAZ.
Plotting SHEAR Data
Each time SHEAR is run by the commands listed earlier, a plot of the
study area is sent to the CALCOMP plotter. These plots include: 1) the
8G/ED locations in the region analyzed, 2) the population density, 3) trie
locations of the sources, and 4) the concentrations around each source.
These plots are large and use various colors to depict the variable plotted.
The TEKTROMICS plotter could also be used for the SHEAR output. This
produces 8 1/2 x 11 plots that are not color. To send the SHEAR output to
the TEKTRONICS plotter rather the calcomp plotter, type /TEK after the
point, proto or area portion of the start command. To run a stripped down
version (no legends) of the output, type/TEK-B in the same place. These
commands are shown in Appendix 0 to demonstrate all the variations (e.g.,
different radial distances).
The specifications for the plots described above are initiated by the
run stream and can only be changed by a programmer who is familiar with the
Executive Control Language (ECU. The format for the information is shown
in the top portion of Figure 3-8. Additional legends, however, can be
added to the plot by the general user. This format is shown in the bottom
portion of Figure 3-8 and is described below:
Columns 1-13 = location of legend in UTM coordinates (e.g., source
locations that you need to label.
3-30
-------
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Columns 14-17 = symbol number (see Appendix E).
Column 18 = color of symbol. 1 = black, 2 = red, 3 = blue,
4 = green.
Column 19-21 = Height of symbol in inches.
Column 22 = Color of the text.
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Columns 23-25 = Height of letters of text in inches.
Columns 26-28 = Angle at which the text should be printed in.
degrees.
Columns 29-80 = The text of the label (will be printed in
Simplex Roman type).
Miscellaneous
As mentioned previously, SHEAR is much more complicated to run
than SHED. You must complete a larger number of files and select the
appropriate start card for the analysis. The available SHEAR start cards
are listed in Appendix D.
Some of the start cards cause the SHEAR program to generate a
concentration ranking from the center of the box. These start cards
are noted in Appendix D. If these cards are used, it is also possible
for the user to choose a location other than the center of the box.
See Figure 3-9 for the appropriate format.
Figure 3-10 is provided for the programmer who has a good knowledge
of ECL. The radial distances for SHEAR can be altered by changing the
runstream. Figure 3-10 provides the appropriate format. The current
defaults for 50 Km run are ten radii at .20, .50, 1.00, 2.00, 5.00,
10.00, 20.00, 30.00, 40.00 and 50.00 Km. The decay rate is assumed to
be zero.
3-32
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3-6. Using Output from other Dispersion Models
Similar to SHED, SHEAR can be executed using concentration inputs
from other models for the point source portion of the model. It is cur-
rently capable of using ISCLT results. The ISCLT output must be created
as tape fi.le output on disk using options when the ISCLT model is run.
You need then know only the filename(s) to access the concentrations.
Entering Data
To execute SHEAR using output concentrations, you must enter data
into all the files as usual with one additional file. To open this file,
type:
(3EDM (chemical )*SHR-ISCLT.
Enter the data as follows (see also Figure 3-11):
Card 1, Columns 1-6 = Latitude of the plant in degrees, minutes,
and seconds (two digits each).
Columns 7-13 = Longitude of the plant in degrees (three
digits), minutes (two digits), and seconds
(two digits).
Columns 14-23 = Conversion factor. (This number will be
multiplied by the concentration points to
yield a converted concentration. Since the
emission rate is proportional to the con-
centration points, this factor may be used
to analyze various possible emission rates
with only one ISCLT run. Enter 1.0 if you
wish the concentration points to remain the
same.)
3-35
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Columns 24-25 * filename in which the ISCLT concentration
values are listed.
Columns 56-80 = Point sources (individual stacks) at the
plant to be included. Each digit represents
, . each stack. If the stack is to be included,
type 1; if excluded, type 0. Leaving this
part blank includes all the stacks.
This card should be completed for each plant and chemical analyzed.
Running the Program
There are several options for running the program depending upon your
needs. If you have not yet executed a SHEAR run for these sources, the
XTRACT program must be run. Hence the start card would be as follows:
9 START START*SHR-ISCLT-A,/(Site ID),, .(filename)
If XTRACT has been run previously for these sources, simply empty the cone.
file as described in section 3-5 and type the start card as shown above
deleting the "-A".
3-7. Output from SHEAR
The major output from SHEAR is very similar to SHED. It includes a
listing of the input data and concentration grid for each point source.
The output also includes the cummulative exposure summary similar to that
discussed under SHED. The overall summary constitutes the major difference
between SHEAR and SHED output. SHEAR output presents a chart similar to
the cummulative exposure summary in lieu of the overall summary. This
chart presents levels of hazard (concentration plus unit risk divided by
seventy), the number of people exposed to that hazard or greater and the
annual incidence (people x hazard).
3-37
-------
In addition to these output, SHEAR also reports the location of each
prototype source and each BG/ED used in the analysis. The area and prototype
data output are cummulative for the area analyzed rather than presented for
each individual source.
3-38
-------
References
1. Anderson, G.E. and G.VI. Lundberg, (May 1983) "User's Manual for SHEAR."
(Prepared for the Environmental Protection Agency, Durham, Morth
Carolina.) Publication Number SYSAPP-83/124, Systems Applications,
Incorporated.
2. EPA (1977), "User's Manual for Single Source (CRSTER) Model," U.S.
Environmental Protection Agency, U.S. Department of Commerce, MTIS
PB-271360.
3. Hagerty, P.E. and K.E. Sibbald, (1975) "Text Editor User's Guide"
Computer Science Center, University of Maryland, 1975.
4. Hanna, S.R. (1978), "Diurnal Variation of the Stability Factor in the
Simple ATDL Urban Dispersion Model," J. Air Pollut. Control Assoc.
Vol. 28, No. 2, pp. 147-150.
5. Manna, S.R. and F.A. Gifford (1973), "Modeling Urban Air Poillution,"
Atmos. Environ., Vol 7, po. 131-136.
6. Martin, O.O., and J.A. Tikvart (1968), "A General Atmospheric Diffusion
Model for Estimating the Effects on Air Quality of One or More
Sources, "APCA Paper, presented at the 61st Annual APCA Meeting,
June 1968, St. Paul, Minnesota.
7. Pasquill, F. (1961), "The Estimation of the Dispersion of Uindborne Material,"
Met. Mag., Vol 90, pp 33-49.
8. Systems Applications, Incorporated (March 1983) "Hunan Exposure to
Atmospheric Concentrations of Selected Chemicals". (Prepared for
the Environmental Protection Agency, Research Triangle Park,
Morth Carolina.) Volume I, Publication Number EPA-2/250-1, and
Volume II, Publication Number EPA-1/250-2.
R-l
-------
9. Turner, D.B. (1964), "A Diffusion Model for an Urban Area, Atmospheric
Dispersion Estimates," 6th Printing Rev., Government Printing
Office, U.S. Environmental Protection Agency, Office of Air
Programs, Publ. No. Ap-26, Washington, D.C.
R-2
-------
Appendix A
STAR-PICK
To access STAR-PICK you must have access to the UNIVAC corrputer system
(as described in Section 1-3) and be logged on (as described in Section 2-
4). Once logged on type the following:
@ADD,PL HEP-RUN.STAR-PICK
and hit XMIT. The program will then respond with several strange lines of
information. At the end of the information the computer types:
Enter the location's latitude (DEC, MIN, SEC) and longitude
(DEG, MIN, SEC) and the number of sites to list (default of 20)
Format (312, 14, 212, 14) or @ EOF if finished.
You should now type the following in exactly the format shown below:
DDMMSS DODMMSSNNNN
where: 0 = degrees (latitude in first group of number, longitude in
the second
M = minutes
S = seconds
N - Digits of the number of star stations you wish to be
displayed (default is 20)
When you hit XMIT, the computer will respond with the STAR station code number,
the city in which it is located, its distance from the source longitude and
latitude, and other information. The listing will be in order of closest
distance from the given longitude and latitude.
After you have obtained all the STAR station code numbers you need, type:
0EOF
and hit XMIT. This will exit you from the program.
A-l
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Appendix 3
Conversion of UTM Coordinates to Latitude/Longitude Coordinates
To use the program available on the UNI VAC system you must have access
to the UNIVAC system (as described in Section 1-3) and be logged on (as
described in Section 2-4). To access the program type the following:
@XQT EOS*RUN.UTM-CALC
and hit XMIT. You then must enter the UTM coordinates in the following
format:
UEEE.E0NNNN.N0ZZ
where: U = signals program that these are UTM coordinates
E = digits of the UTM easting
N = digits of the UTM northing
Z - zone of the UTM coordinates
3e careful to place exactly the indicated number of digits and to place the
zeros or spaces in. Once you hit XMIT, the computer will respond with the
latitude and longitude with both decimal units and degrees, minutes, seconds
units. You are interested in the degrees, minutes, seconds reading for
SHED.
You may also translate geoditic coordinates to UTM by using the
following format:
LDDMMSS000DMMSS
where: L = signals program that these are geodetic coordinates
0 = degrees (latitude in the first number; longitude in the second)
M = minutes
S = seconds
Be careful to enter all the digits indicated and the zero (or space).
Once you hit XMIT, the computer will respond with the same format ?'
the conversion of UTM to latitude and longitude.
B-l
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It is also possible to translate longitude and latitude represented by
a decimal figure into UTM coordinates or units of degrees, minutes and
seconds. To do this, use the following format:
DXX.XXXX0YYY.YYYY
where: 0 - signals program that these are decimal coordinates
t '
X = latitude digits
Y = longitude digits
Be careful to enter the digits and zero (or blank) as shown with the
decimal points in the indicated positions. The computer will respond with
the same format as with the previous conversions.
B-2
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Appendix C
Helpful Hints With the Maryland Editor
The Maryland Editor operates In two modes, the Input mode and the edit
mode. In the Input mode, every typed character Is entered into the data
file, lii the edit mode, the user directs the Editor to change or scan the
text in various ways. Data can also be input in the edit mode by typing I,
a space, and the information to be inserted.
The Editor toggles between edit and input modes by pressing XMIT after
an SOE (>). We suggest remaining in the edit mode at all times in order to
make use of the editing commands.
The most used commands are listed below in brief summary form. Please
refer to reference 2 to obtain a complete explanation of the Editor, a more
extensive list of commands and a more complete definition. The numbers 9 and 0
used below are examples, any number may be used.
Maryland Editor Commands:
To move around in a file (Remember that moving the cursor may move you around
on the screen but it does not move you around in the
file.)
0 - deletes the line you are on
0 9 - deletes the line you are on and the next eight lines
0 9 - prints the next 9 lines on the screen
P 9 - prints the line you are on & the next 3 lines
N - prints the next line on the screen
T - takes you to the top of the file (this also stores any changes
that have been made in a backup
data file)
C-l
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LA - takes you to the last line of a file
9 - takes you to line number 9
-9 - moves you up 9 lines
+9 - moves you down 9 lines
To Chan'ge a file
C /old/new/ - changes the old (type whatever you want changed) to the
new (type what you want it changed to) the first time it
appears in the line
C /old/new/ G - changes the old to the new everytime it occurs in the line
C /old/new/ 9 - changes the old to the new the first time it occurs
in the line for the line you are on and the next 8 lines
R (a space) new - replace the line you are on with new
R,9(a space) new - replace part of line starting in column 9 with new
To Copy a Part of a file
Ditto 09 - copies lines 0 to 9 below the line you are on
BE - begins to copy (move to first line you want copied
before typing)
CO - ends part to copy (move to the line below the last
line you want copied before typing)
AOO - copies the data defined by BE and CO below the
line you are on
CO Filename - used in place of CO and ADO to copy data to a separate
file
For Help
HELPS[Procedure Name] - displays information on a particular procedure;
use 0EOF to exit
SC - prints column scale
C-2
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Appendix D
Summary of SHEAR Run Cards
This Appendix lists parts of the SHEAR run card which can be inserted
for slight variations of the SHEAR run. The general format for all the
cards wll 1 be:
(3START SASO*START. [part from below],/site ID ,,, filename
The following rules apply to the variations and may help in selecting
the correct card:
1. If TEK is included as part of the card, the output will be
plotted on the tektronics plotter. Otherwise the output goes
to the calcomp plotter. The "-8" omits the legends on the plots.
2. If the point orproto run cards have no numbers, the analysis
will be performed out to 20 Km. A number with the card indicates
the distance to which the analysis will be performed, (e.g., 50 Km)
3. The "-A" commands the XTRACT portion of SHR to be executed.
4. The "All" commands all (point, proto and area) to be run.
5. The "-P" commands the concentration values to be added to those
values already in the CONC. FILE (i.e., XTRACT must have been
run previously). This is similar to running without "-A" except
that -P also commands the output to be plotted.
0-1
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The following inserts include as output the concentration levels
surrounding the center of the city or other designated location:
SHR-ALL SHR-POINT/50-KM
SHR-ALL/TEK SHR-POINT-A/50-KM
SHR-ALL/TEK-B SHR-POINT-A/TEK-50-KM
' SHR-AREA-A SHR-POINT-A/TEK-B-50-KM
SHR-AREA-A/TEK SHR-POINT-P/50-KM
SHR-AREA-A/TEK-B SHR-POINT-P/TEK-50-KM
SHR-ISCLT SHR-POINT-P/TEK-B-50-KM
SHR-ISCLT-A SHR-POINT/80-KM
SHR-ISCLT-A/TEK SHR-POINT-A/80-KM
SHR-ISCLT-A/TEK-8 SHR-POINT-A/TEK-80-KM
SHR-ISCLT-P SHR-POINT-A/TEK-B-80-KM
SHR-ISCLT-P/TEK SHR-POINT-P/80-KM
SHR-ISCLT-P/TEK-B SHR-POINT-P/TEK-80-KM
SHR-POINT SHR-POINT-P/TEK-B-80-KM
SHR-POINT-A SHR-POINT/100-KM
SHR-POINT-A/TEK SHR-POINT-A/100-KM
SHR-POINT-A/TEK-B SHR-POINT-A/TEK-100-KM
SHR-POINT-P SHR-POINT-A/TEK-B-100-KM
SHR-POINT-P/TEK
SHR-POINT-P/TEK-8
SHR-PROTO
SHR-PROTO-A
SHR-PROTO-A/TEK
SHR-PROTO-A/TEK-B
The following inserts do not include the concentration ranking as output:
SHR-AREA
SHR-AREA-P
SHR-AREA-P/TEK
SHR-AREA-P/TEK-B
SHR-PROTO-P
SHR-PROTO-P/TEK
SHR-PROTO-P/TEK-B
To send the results of the SHEAR run to your specific location to be
printed out from your PC substitute USR for SHR in any of the above start
cards. The actual printout of the material requires that you type !?@SEND,
U after the program has finished running (see section 2-5). To print out
on the laser printer substitute LAZ for SHR.
n-2
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Appendix E
BG/ED Block Group/Enumeration District
COM C1imatolog1ca1 Dispersion Model
ECU Executive Control Language
EI'O Emission Inventory Questionnaires
FIPS Federal Information Processing System
HAD Health Assessment Document
HEM Human Exposure Model
ISCLT Industrial Source Complex Long-Term
MARF2 Master Area Reference File 2
NCC National Climatic Center, National Computer Center
NEDS National Emissions data System
NTIS National Technical Information Service
SAI Systems Aoplications Incorporated
SHEAR Systems Applications Human Exposure and Risk
SHED Systems Applications Human Exposure and Dosage
STAR Stability Array
U.S.G.S. United States Geological Survey
UTM Universal Transverse Mercator
E-l
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INSTRUCTIONS
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EPA Form 2220-1 (Rev. 4-77) (Reverse)
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing/
1. REPORT NO, 2.
450/5-86-001
4. TITLE AND SUBTITLE
User's Manual for the Human Exposure Model (HEM)
7. AUTHOR(S)
Pollutant Assessment Branch
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Pollutant' Assessment Branch
MD-12
Research Triangle Park, NC 27711
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Protection Agency
401 M Street, S.W.
Washington, D.C. 20460
3. RECIPIENT'S ACCESSION NO.
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Date of Approval - June 1986
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11. CONTRACT/GRANT NO.
13. TYPE OF REPORT AND PERIOD COVERED
Interim
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
This document describes the Human Exposure Model, furnishes contact personnel
to establish access to the UNIVAC System, and provides step-by-step instructions for
operating both the SHED and SHEAR portions of the model. The manual also lists
caveats which should be considered when using the HEM and criteria to distinguish
situations which are appropriately modeled by each portion of HEM. The intended
audience ranges from someone with limited knowledge of modeling to someone well-
acquainted with the UNIVAC.
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a. DESCRIPTORS
Exposure Modeling
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Unlimited
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Unl imi toH
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22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
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