EPA/600/8-85/002
February 1985
RAPID ASSESSMENT OF EXPOSURE TO PARTICULATE EMISSIONS
FROM SURFACE CONTAMINATION SITES
by
Chatten Cowherd, Jr.
Gregory E. Muleski
Phillip J. Englehart
Dale A. Gillette
Midwest Research Institute
Kansas City, Missouri 64110
Contract No. 68-03-3116
Project Officer
Mr. Anthony S. Donigian, Jr.
Anderson-Nichols and Company, Inc.
2666 East Bayshore Road
Palo Alto, California 94303
Technical Project Monitor
Mr. John Schaum
Office of Health and Environmental Assessment
U.S. Environmental Protection Agency
Washington, D.C. 20460
OFFICE OF HEALTH AND ENVIRONMENTAL ASSESSMENT
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, DC 20460
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DISCLAIMER
This report has been reviewed in accordance with U.S. Environmental
Protection Agency policy, and approved for publication. Mention of trade
names or commercial products does not constitute endorsement or recommenda-
tion for use.
n
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FOREWORD
The Exposure Assessment Group (EAG) of EPA's Office of Research and
Development has three main functions: (1) to conduct exposure assessments-
(2) to review assessments and related documents; and (3) to develop guide-
lines for Agency exposure assessments. The activities under each of these
functions are supported by and respond to the needs of the various EPA pro-
gram offices. In relation to the third function, EAG sponsors projects
aimed at developing or refining techniques used in exposure assessments.
This study is one of these projects and was done for the Office of Emergency
and Remedial Response.
The Comprehensive Environmental Response, Compensation, and Liability
Act of 1980 established a national fund for the purpose of cleaning up
spills and abandoned sites containing hazardous substances. When these
sites are discovered EPA must decide quickly if an urgent threat exists
requiring immediate action. This project is intended to aid the Agency in
making these decisions by providing a method for rapidly evaluating the
human health and environmental threat caused by particulate emissions from
land contamination sites.
Spills, waste disposal, and various waste industrial operations can
result in the contamination of land surfaces with toxic chemicals. Soil
particles from these areas can be entrained into the air, transported off-
site via the wind, and result in human exposure by direct inhalation.
Indirect exposure could result if particulates are deposited in agricultural
fields, pastures, or waterways and enter the human food chain. This exposure
route is enhanced by the facts that many of the environmentally troublesome
compounds are tightly bound to particles and that many surface contaminated
sites have conditions favoring wind erosion, such as sparse vegetation cover
and high levels of activity which disturb the surface.
James W. Falco, Director
Exposure Assessment Group
111
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ABSTRACT
Emergency response actions at chemical spills and abandoned hazardous
waste sites often require rapid assessment of (a) the potential for atmo-
spheric contamination by the chemical or waste compound and (b) the inhala-
tion exposure of people living in the vicinity of a surface contamination
site. This manual provides a methodology for rapid assessment of inhalation
exposure to respirable particulate emissions from surface contamination
sites. Respirable particulate matter is defined as airborne particles equal
to or smaller than 10 urn aerodynamic diameter. The methodology consists of
a site survey procedure, particulate emission factor equations for wind
and mechanical entrainment processes, procedures for mapping atmospheric
contaminant concentration distributions by scaling the output of pre-solved
computer models of regional atmospheric dispersion, and an equation for cal-
culation of inhalation exposure. In addition to the components of the
methodology, this manual discusses critical contaminant and site charac-
teristics, describes assumptions and limitations of the procedures, and
presents example applications.
The quantitative procedures for estimating atmospheric contaminant con-
centrations are based on a number of simplifying assumptions related to the
contaminated surface and the atmospheric environment, to conform to the data,
time, and resource limitations expected during an emergency response. Con-
sequently, the assessment methodology provides order-of-magnitude estimates
of atmospheric contaminant concentrations as a function of averaging time
and downwind location. The user should carefully review all the assumptions
and limitations, and make specific judgments as to their validity for the
specific site, contaminant(s), and emergency situation being analyzed.
Familiarity and prior training in the use of this manual is highly recom-
mended for efficient use during an emergency response situation.
IV
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CONTENTS
Appendices
Foreword j-jj
Abstract iv
Figures V1-
Tables v-ji
Acknowledgements vjjj
1. Introduction 1
1.1 Scope and limitations of this manual 1
1.2 Required user background, training, and
preparation 2
1.3 Format of the manual 4
1.4 Caveat 4
2. Overview of Rapid Assessment Methodology 5
2.1 Application scenarios 5
2.2 Methodology flowchart 6
2.3 Critical contaminant and site characteristics ... 11
3. Site Survey and Data Gathering 17
3.1 Assessment of extent of surface contamination ... 17
3.2 Characterization of wind erosion potential 21
3.3 Characterization of mechanical resuspension by
vehicle traffic 26
4. Calculations and Gathering of Results 29
4.1 Calculation of average/worst-case emission rates. . 29
4.2 Dispersion modeling 41
4.3 Estimation of exposure 58
4.4 Assumptions, limitations, and parameter
sensitivity 63
5. Example Applications 69
5.1 Example one 69
5.2 Example two 76
6. References 85
A. Photographs of nonerodible element distributions A-l
B. Function needed for unlimited erosion model B-l
C. Atmospheric dispersion models and meteorological
input data C-l
D. Annual unsealed concentration values D-l
E. Emission factors for other forms of mechanical
disturbance E-l
F. Glossary p_l
G. Annual and worst-case overlays G-l
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FIGURES
Number paq(
—2_
2~I Diagram of assessment procedure 7
3-1 Site survey worksheet 18
3-2 Site survey decision flowchart 20
3-3 Field procedure for determination of threshold friction
velocity 23
3-4 Relationship of threshold friction velocity to size
distribution mode 24
3-5 Increase in threshold friction velocity with L 25
3-6 Roughness heights for various surfaces . . . .c 27
4-1 Ratio of wind speed at 7 m to friction velocity as a
function of roughness height 31
4-2 Map of P-E index for state climatic divisions 35
4-3 Graph of function F(X) needed to estimate unlimited
erosion 35
4-4 Map of precipitation frequency 39
4-5 Climatic region 42
4-6 Portion of receptor network showing coarse and fine
grids 44
4-7 Annual dispersion model worksheet 45
4-8 Unsealed ambient concentrations - fine grid 48
4-9 Unsealed ambient concentrations - coarse grid 49
4-10 Calculator program for isopleth construction 51
4-lla Worst-case isopleths for a 10 m x 10 m source 54
4-llb Worst-case isopleths for a 100 m x 100 m source 55
4-12 Unsealed worst-case concentration versus downwind
distance 57
4-13 Inspired fraction versus particle size 60
5-1 Sketch of the hypothetical site (example one) 70
5-2 Completed worksheet for hypothetical site (example one). . 73
5-3 Annual ambient concentration field for the hypothetical
site (example one) 74
5-4 Annual concentration isopleths for the hypothetical site
(example one) 75
5-5 Worst-case isopleths for the hypothetical site (example
one) 77
5-6 Sketch of the hypothetical site (example two) 78
5-7 Sketch of contaminated area (example two) 79
5-8 Conservative annual concentration isopleths for hypo-
thetical site (example two) 81
5-9 Worst-case concentration isopleths for hypothetical site
(example two) 83
VI
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TABLES
Number pag)
2-1 Example Insoluble Hazardous Chemicals for the Recommended
Cleanup Procedure Is Physical Removal 11
4-1 Fastest Mile [u ] and Mean Wind Speed [u] for Selected
United States Stations 32
4-2 Default Values for Independent Variables of Equation 4-6 . 38
4-3 Distribution of Inspired Particles 61
4-4 Census Bureau Regional Offices - Information Services. . . 63
4-5 Sensitivity Analysis Guidelines 67
5-1 Values to Compute Average Daily Lifetime Exposure 72
VI 1
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ACKNOWLEDGEMENTS
A number of organizations and individuals contributed to the pre-
paration of this document. Financial support was provided by the EPA Office
of Emergency and Remedial Response through a prime contract with Anderson-
Nichols and Company, Inc. Mr. Anthony S. Donigian, Jr., was the Project
Officer for Anderson-Nichols and Mr. John Schaum (Exposure Assessment Group)
was the EPA Technical Project Monitor. These individuals provided valuable
technical guidance to Midwest Research Institute.
Midwest Research Institute was assisted in the area of wind ero-
sion emission assessment by Dr. Dale A. Gillette of the NOAA Environmental
Research Laboratories. In addition, technical review comments were provided
by the following individuals: Mr. Rodger K. Woodruff, Dr. G. A. Sehmel,
and Dr. T. W. Horst of Battelle Pacific Northwest Laboratories; Dr. H. E.
Cramer of H. E. Cramer Company, Inc.; Mr. David Lincoln of CH2M Hill; and
Ms. Geraldine K. Cox of the Chemical Manufacturers Association.
Among the authors, Dr. Chatten Cowherd was the program manager for
Midwest Research Institute. Dr. Gregory Mulesjd developed the dispersion
modeling approach and the output format. Mr. Phillip Englehart provided ex-
pertise in meteorology and climatology related to the estimation of param-
eters for emissions and dispersion models. Dr. Cowherd and Dr. Gillette
collaborated on developing the emission models and the field survey
procedure.
VI 1 1
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SECTION 1
INTRODUCTION
The purpose of this manual is to provide a rapid assessment methodology
for estimating potential atmospheric contamination and resulting inhalation
exposure of people living in areas surrounding an abandoned hazardous waste
or toxic chemical spill site. Only respirable particulate emissions, defined
as particles equal to or smaller than 10 [jm aerodynamic diameter (denoted
by the symbol PM10) are considered in this assessment methodology. PM10 is
the anticipated size fraction for the impending revision to the primary
(health-related) national ambient air quality standard (Federal Register
1984). a
Specifically, this manual is designed for use by field personnel to
quickly estimate how breathing-height concentrations of contaminated respir-
able particulate matter might change with distance and direction from an
emergency response site, under annual average and worst-case 24-hr condi-
tions. The procedures include evaluation of critical contaminant and site
characteristics as input to an assessment methodology for analyzing the
entrainment and atmospheric dispersion of chemicals or contaminated surface
material. ^ A modeling technique has been developed for determining the
spatial^ distribution of atmospheric contaminant concentration resulting
from wind and/or mechanical entrainment processes, taking into account
regional differences in meteorology. Guidelines for evaluating critical
contaminant and site characteristics are provided to allow estimation of
needed input parameters.
1.1 SCOPE AND LIMITATIONS OF THIS MANUAL
The phrase EMERGENCY RESPONSE is emphasized throughout this manual be-
cause it has been the overriding criterion (and constraint) for selection,
evaluation, and development of pollutant transport assessment methods and
parameter evaluation techniques included herein. Emergency response situa-
tions require assessments of potential atmospheric contamination to be com-
pleted in less than 24 hr. Consequently, extensive field sampling, labora-
tory analyses, data search and collection, and sophisticated computer
analyses are generally impractical during this limited time frame. Although
these extensive sampling and analysis activities may be initiated during
the emergency response period, the results cannot be expected to be avail-
able for use in an emergency assessment. The assessment procedures in this
manual are designed to allow emergency response personnel to make a first-
cut, order-of-magnitude estimate of the potential extent of atmospheric
contamination and exposure resulting from a waste site or chemical spill,
within the 24-hr emergency response time frame.
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The primary goal of this manual is to provide the basis for determin-
ing the need for emergency actions, such as emergency sampling, containment/
stabilization or removal, in order to minimize human exposure to atmospheric
contamination by respirable particulate matter in the vicinity of an emer-
gency response site. Two specific emergency response situations are envi-
sioned where the assessment procedures in this manual would be applied:
1. Discovery of an abandoned hazardous waste site where an assess-
ment of the potential extent of the atmospheric contamination is
needed within the emergency response time frame.
2. Spill (or leakage) of a toxic waste or chemical where the poten-
tial for atmospheric contamination and/or the extent of contami-
nation must be assessed within the emergency response time frame.
Time and resource limitations expected during an emergency response
have required a number of simplifying assumptions in the assessment proce-
dures; additional simplifications may be needed by the user due to limited
data and information available at a particular emergency response site.
The most fundamental assumptions incorporated into the assessment procedures
in this manual are as follows:
1. Uniform contamination of a symmetrical land area is assumed, with
the concentration in respirable particulate emissions matching
the bulk contaminant concentration in the surface material.
2. Emission rates associated with wind and mechanical entrainment
processes are modeled as continuous and steady.
A variety of other assumptions and limitations in the procedures are further
discussed in Section 4.4. The user should carefully review all the assump-
tions and limitations, and make specific judgments as to their validity for
the specific site, contaminant(s), and emergency situation being analyzed.
Perhaps the most critical aspect of an emergency response situation
will be the ability of the user to adequately characterize, within the 24-hr
time frame, the surface media (e.g., erodibility, suspendible particle con-
tent, level and extent of surface contamination) from which the contaminants
are emitted. Consequently, access to and/or availability of data, expertise,
and familiarity with local, site-specific surface conditions is critical to
the successful application of the assessment procedures in this manual. If
the emergency response situation consists of a long-term surface contamina-
tion problem with no apparent change in intensity, it may be reasonable to
extend the response time frame beyond 24 hr.
1.2 REQUIRED USER BACKGROUND, TRAINING, AND PREPARATION
Effective use of this manual requires a general understanding of a mix
of disciplines, such as climatology, soil science, chemistry, on the part
of the intended user, and sufficient familiarity or training with the tech-
niques, procedures, and auxiliary sources of information described herein.
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This manual is not intended to be a primer on pollutant release and trans-
port through the atmosphere; a variety of excellent introductory textbooks
and reports in these areas are available to the potential user to provide
the needed background.
Ideally, advanced academic training in physical science supplemented
with pertinent work experience and job training, (e.g., short course atten-
dance) provides a profile of the recommended background for a user. Alter-
natively, an engineering or science undergraduate degree with appropriate
training is acceptable as long as a basic understanding in the following
areas is included:
1. The mechanisms of wind and mechanical entrainment of surface par-
ticulate matter.
2. Meteorological concepts, processes, and terminology related to
atmospheric transport.
3. Soil science concepts related to surface soil processes.
4. Chemical processes, parameters, and terminology.
5. Mathematical capabilities and skills in the use of scientific hand
calculators.
6. Map reading techniques.
In many emergency response situations, the user will have access to ex-
perts in the above disciplines to provide guidance in parameter evaluation.
Thus, it is important that the user comprehend the fundamental concepts of
each discipline in order to take full advantage of available expertise.
User training and preparation is needed to develop familiarity with
the assessment procedures described in this manual. Training and/or famil-
iarity with the specific procedures described herein is absolutely essential
to effectively use this manual. Without prior study, users cannot expect
to use this manual for assessing potential atmospheric contamination within
a 24-hr period. Every effort has been made to simplify the procedures and
parameter evaluation guidelines; however prior study is needed to become
familiar^with the assumptions/limitations, the step-by-step calculations,
the application of the graphs, the parameter evaluation guidelines, and the
auxiliary sources of information.
Since site characterization may require the greatest effort during an
emergency assessment, preparation of a regional or local data base on meteo-
rology, soils properties, and local experts (i.e., contacts and phone num-
bers) could considerably shorten the time needed to obtain data and improve
the resulting parameter estimates. A similar, regional data base for the
characteristics of wastes and chemicals produced in, or transported through,
the region would be extremely valuable. Recommendations for the contents
and format of such a regional data base have been developed for EPA (Battelle
PNL, 1982).
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1.3 FORMAT OF THE MANUAL
The format of this manual is similar to that used in the companion
manual on the rapid assessment of potential groundwater contamination.
(Donigian et al., 1983). In this section as well as Section 2, much of the
wording was taken directly from the companion manual whenever the subject
matter was common to both manuals.
Section 2 describes the types of hazardous waste and spill situations
for which the assessment procedures are designed, and provides a methodol-
ogy flowchart to guide an application. An overview of critical compound
and site characteristics is provided along with a discussion of recommended
sources of information. Section 3 provides technical guidelines for con-
ducting a contamination site survey.
Section 4 provides a detailed description of the assessment methodology,
making use of information gathered from the site. Guidelines are presented
for estimating the other input parameters for the assessment. Emphasis is
placed on obtaining local site and contaminant specific data in order to
obtain realistic parameter estimates. Section 4 also discusses the assump-
tions and limitations of the assessment procedures; these should be carefully
reviewed and understood by the user.
Section 5 presents example applications for the assessment. Section 6
includes cited references. Appendix A contains photographs of ground sur-
faces of varying erodibility. Appendix B describes the evaluation of the
integral needed for calculation of wind erosion emission rates. Appendix C
presents a general discussion of atmospheric dispersion models and their
applicability to the assessment; Appendix C also describes the process by
which meteorological input to the assessment procedures was developed.
Appendix D provides the tabulated dispersion modeling output needed for
implementation of the assessment procedure. Appendix E provides particulate
emission factors for several mechanical entrainment processes other than
vehicle traffic. Appendix F is a glossary of terms. Finally, Appendix G
contains graphics needed to create the map overlays for use in the assessment
process.
1.4 CAVEAT
Although all efforts have been made to insure the accuracy and reli-
ability of the methods and data included in this manual, the ultimate re-
sponsibility for accuracy of the final predictions must rest with the user.
Since parameter estimates can range within wide limits, especially under
the resource and time constraints of an emergency response, the user should
assess the effect of methodology assumptions and parameter variability on
predicted concentrations for the specific site. The methodology predictions
must be evaluated with common sense, engineering judgment, and fundamental
principles of soil science, meteorology, and chemistry. Accordingly, neither
the authors nor Midwest Research Institute (MRI) assume liability from use
of the methods and/or data described in this manual.
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SECTION 2
OVERVIEW OF RAPID ASSESSMENT METHODOLOGY
An emergency response to releases of hazardous substances is generally
comprised of three steps—characterization, assessment, mitigation—defined
as follows (Battelle PNL, 1982):
Characterization - The acquisition, compilation, and processing
of data to describe the scene so that a valid assessment of al-
ternative actions can be made.
Assessment - An analysis of the severity of an incident; the
evaluation of possible response actions for effectiveness and
environmental impact.
Mitigation - The implementation of the best response action and
followup activities.
This manual addresses the first and second steps relative to potential for
atmospheric contamination and resulting exposure.
The assessment procedures for potential atmospheric contamination in
this manual draw upon data and information developed in the characteriza-
tion phase in order to provide a tool for performing parts of the assessment
phase when atmospheric contamination is suspect. The EPA Field Guide for
Scientific Support Activities Associated with Superfund Emergency Response
(Battelle PNL, 1982) provides an excellent framework within which to view
these procedures as part of the arsenal of the emergency response team for
assessments of hazardous substance releases. This field guide identifies
the calculation of transport rates of hazardous materials as an important
element in the assessment phase. When entrainment and atmospheric transport
of hazardous substances is important at an emergency response site, these
calculations can be made with the procedures described herein based on the
methodology assumptions and data expected to be available within the emer-
gency response time frame.
2.1 APPLICATION SCENARIOS
Surface contamination by hazardous materials may result from surface
spills; seepage from waste injection operations, waste storage/burial sites;
and upward migration from leaks in underground containers (i.e., waste or
storage) or pipelines. The rapid assessment procedures are designed for
application in two typical scenarios, or cases, based on the temporal nature
of the release:
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A typical hazardous waste site or chemical/waste storage facil-
ity where the depth of surface contamination provides a relatively
continuous and constant potential for emissions over an extended
period of time (e.g., years).
A typical spill incident where the contaminant is highly exposed
in a relatively thin surface layer such that emissions can be ex-
pected to decay significantly over a relatively short period of
time (e.g., weeks or months).
The assumption of a constant release either on a continuous or inter-
mittent basis is necessary for the analytical solutions which have been
developed for application within the emergency response time frame. Con-
sequently, although actual releases may be time decaying, the user will need
to approximate the actual release as a constant over a given exposure period.
However, the constant can be adjusted to reflect the decrease in release
rate as the surface contamination is depleted.
Superimposed on the temporal nature of the release is the averaging
time of concern for the assessment of resulting atmospheric contamination.
The averaging time may represent either long-term (monthly, annual) condi-
tions or short-term (24-hr) "worst-case" conditions. Thus, the time period
of concern and the temporal nature of the release jointly determine the
appropriate type of analysis (i.e., annual average versus worst-case) and
parameter estimates for the driving force behind contaminant transport.
2.2 METHODOLOGY FLOWCHART
The overall flowchart for the rapid assessment methdology is shown in
Figure 2-1. Prior to initiating application of these procedures, the On-
Scene Coordinator (OSC) at the emergency response site must determine that
(a) the potential for atmospheric contamination exists, and (b) an assess-
ment of the potential or current extent of contamination must be made within
the 24-hr emergency response time frame. These decisions will be based on
the results of the characterization phase of the emergency response effort
and will depend on current conditions (e.g., extent of contamination of sur-
face material, weather forecasts), contaminant characteristics (e.g., toxic-
ity, solubility, sorption, volatility), and site characteristics (e.g., soil
characteristics, distance to populated areas). If no emergency assessment
is deemed necessary, the procedures in this manual should not be used, except
as preliminary guidance for subsequent detailed sampling, analysis, and
investigations. If an emergency assessment is deemed necessary, the steps
in Figure 2-1 should be followed.
The rapid assessment methodology is directed to estimation of respirable
particulate inhalation exposure of people living in the vicinity of a surface
contamination site. The assessment methodology consists of three sequential
estimating procedures as described in the following subsections.
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Step 1 - Estimation of Emissions
The technical approach for estimating respirable (PM10) emissions from
surface contamination sites is consistent with the technique used in air
pollution assessments. It is based on the following equation:
RIO = « EIO A (2-1)
where R10 = emission rate of contaminant as PM10 (mass/time)
a = fraction of contaminant in PM10 emissions (mass/mass)
E10 = PM10 emission factor (mass/source extent)
A = source extent (source-dependent units)
The emission factor is simply the ratio of uncontrolled emissions per
unit of source extent. For wind erosion, the source extent is the area of
erodible surface. In the case of emissions generated by mechanical dis-
turbance, source extent is also the area (or volume) of the material from
which the emissions emanate. Normally, the "uncontrolled" emission factor
incorporates the effects of natural mitigation (e.g., rainfall). If anthro-
pogenic control measures (e.g., treating the surface with a chemical binder
which forms an artificial crust) are applied to the source, the uncontrolled
emission factor must be reduced to reflect the resulting fractional control.
The first step in the estimation of atmospheric particulate emissions
from a surface contamination site is to decide whether potential emissions
are limited to those generated by wind erosion. If traffic over the site
occurs, it is likely that the traffic emissions (or emissions from other
forms of mechanical disturbance) substantially exceed emissions from wind
erosion. This is because, for most parts of the country, vehicle traffic
is an intensive entrainment mechanism in comparison with wind erosion.
For estimation of emissions from traffic on unpaved surfaces, a pre-
dictive emission factor equation is recommended in Section 4. This equation,
developed from regression analysis of field test data, explains much of
the observed variance in road dust emission factor values on the basis of
variances in specific road surface and traffic parameters. Thus it provides
more reliable estimates of source emissions on a site specific basis than
does a single-valued average emission factor. The appropriate measure of
source extent for this emission factor is obtained by converting traffic
counts and road segment lengths into the total vehicle-distance traveled;
in effect this represents the cumulative road surface area from which the
emissions are released.
For estimating emissions from wind erosion, either of two emission
factor equations are recommended in Section 4 depending on the credibility
of the surface material. In both cases, the appropriate measure of source
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extent is the contaminated area of the site. The contaminated surface must
be placed in one of two erodibility classes described below. The division
between these classes is best defined in terms of the threshold wind speed
for the onset of wind erosion.
Nonhomogeneous surfaces impregnated with nonerodible elements (stones,
clumps of vegetation, etc.) are characterized by the finite availability
("limited reservoir") of credible material. Such surfaces have high
threshold wind speeds for wind erosion, and particulate emission rates tend
to decay rapidly during an erosion event. An emission factor equation de-
veloped from wind tunnel data on coarse textured aggregate materials is
suitable for this application. It relates the rapidly occurring fine
particle loss from the surface to wind speed maxima during periods between
mechanical disturbance of the surface.
Bare surfaces of finely divided material such as sandy agricultural
soil are characterized by a large number ("unlimited reservoir") of erodible
particles. Such surfaces have low threshold wind speeds for wind erosion,
and particulate emission rates are relatively time independent at a given
wind speed. An emission factor equation based on fine particle emission
measurements performed during agricultural wind erosion events is suitable
for this application. For either class of erodible surface, the source
extent is simply the area contaminated.
As noted in Eq. (2-1), estimation of contaminant emissions requires
knowledge of the contaminant levels in the erodible surface material. It
is presumed that the surface contamination data which triggered the emer-
gency response will be available. In the case of spills, the estimated
level of contamination can be based on the amount of material spilled and
the volume of receiving material penetrated by the spill.
Contaminants in particulate form may be present either as discrete solid
particles or adsorbed onto soil or other surface aggregate materials. This
depends on the physical and chemical interaction between the contaminant
species and the surface aggregate. For adsorbed contaminants, there is
usually an enrichment of contamination in the finer particle sizes because
of larger surface-to-volume ratio. However, in the absence of data on the
contamination level of PM10 particles in the surface material, it will be
assumed that the level of contamination (denoted throughout by the symbol
a) in the respirable particulate emissions matches that measured in the bulk
surface material.
Step 2 - Estimation of Ambient Concentrations
The primary purpose of this assessment is to provide the user with
first-order estimates of atmospheric concentrations and exposures caused by
respirable particulate emissions from a surface contamination site. Using
the emissions estimates developed in Step 1, the assessment procedure employs
atmospheric dispersion models to estimate pollutant transport and dilution
under annual average and worst-case 24 hour meteorological conditions. An
introduction to air quality dispersion models and the rationale for selection
of specific models for this assessment are provided as Appendix C.
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Numerous "off-the-shelf" computer models for atmospheric dispersion
have been developed in the past. The most common air quality models are
contained in the EPA's User's Network for Applied Modeling of Air Pollution
(UNAMAP). The applicability of such models within the emergency response
time frame, however, is severely constrained by the amount of time required
to collect and prepare input data in a suitable format and by the constraint
of having immediate access to an implemented model.
It is also possible to develop hand calculation algorithms for use in
the assessment process (Versar, 1983; Dynamac, 1983; EPA, 1981). However,
this approach requires either restrictive assumptions about the site's
meteorology or excessive time to extract information from wind data (which
may not be available for the site). Other complications in these hand
calculation schemes would involve using a point to represent a source with
a definite non-zero areal extent and assuming that the directional distribu-
tion of the high-speed winds is identical to that observed over all wind
speeds. Both of these complications would result in distortion of the con-
centration field.
Thus, although computerized models are capable of modeling area sources
with emission rates that are functions of wind speed, their direct use is
limited by time constraints and accessibility. Hand calculation algorithms
are readily implemented but either require restrictive simplification or
become unwieldly in terms of application.
The approach adopted in this manual attempts to combine the best
features of both options. The manual user scales tabulated output from two
relatively sophisticated UNAMAP computer models as a basis for assessing the
impact of the site in question. This approach allows the analyst to obtain
concentration estimates of a quality comparable to that for computer models
while performing calculations that are algebraically simpler than those re-
quired for the hand calculation algorithms.
Step 3 - Estimation of Exposure
Human exposure resulting from the air transport of particulate emis-
sions from surface contamination sites is the final aspect of the emergency
response assessment procedure. The primary interest of this manual is direct
exposure due to inhalation of the airborne contaminant. Although not ad-
dressed in this manual, the assessment of acute risk focuses on the worst-
case 24-hr exposure, while chronic risk is associated with annual average
exposure levels.
When the dispersion modeling is completed, the user will have maps show-
ing the spatial variation of atmospheric contaminant concentrations at
breathing height. These maps are overlaid onto a map of the site and sur-
rounding area, and the number of people residing within areas bounded by
certain respirable particulate concentration isopleths is then estimated.
Thus, the analyst is presented with information about the number of people
exposed to specified levels of respirable concentrations of the contaminant.
10
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Indirect exposure resulting from spreading of the surface contamination
is also possible. Spreading of the surface contamination can be attributed
to settling of airborne emissions from the original site. Such surface
spreading can constitute an exposure risk, especially to field workers or
children at play. In addition, particulate settling may result in contam-
ination entering the food chain. The treatment of indirect exposure, how-
ever, is beyond the scope of this manual.
2.3 CRITICAL CONTAMINANT AND SITE CHARACTERISTICS
The EPA has compiled a list of 271 hazardous chemicals that are abun-
dant and dangerous enough to be singled out for special attention (Federal
Register, 1981). This list provides a good starting point for considering
the properties such as solubility, physical state, viscosity, size distri-
bution, chemical reactivity, etc., which allows one to divide the chemicals
into groups for which similar fates in the soil would be expected. For ex-
ample, a study by Wentsel et al. (1981) on land restoration recommends phys-
ical removal for 98 of the 271 hazardous chemicals. Of these 98 chemicals,
18 are insoluble (Table 2-1) and may offer a long-term air pollution hazard
because they will not be removed from the soil surface by rainfall. Thus,
transport by wind to populations vulnerable to the chemical contaminant
exposure may be possible for long periods following the contamination.
TABLE 2-1. EXAMPLE INSOLUBLE HAZARDOUS CHEMICALS FOR THE RECOMMENDED
CLEANUP PROCEDURE IS PHYSICAL REMOVAL
Common name
Synonyms
Aldrin
Arsenic trioxide
Arsenic trisulfide
Calcium arsenate
Chlordane
Dichlone
Dieldrin
Diuron
Endosultan
Endrin
Kelthane
Lead arsenate
Lead sulfate
Lead sulfide
Lindane
Polychlorinated biphenyls
Tetraethyl lead
Toxaphene
Octalene, HHDN
Arsenious acid, arsenious oxides, white
arsenic
Arsenious sulfide, yellow arsenic sulfide
Tricalcium orthoarsenate
Toxichlor, chlorodan
Phygon, dichoronaphtoquinone
Alvit
DCMU, DMU
Thiodan
Mendrin, Compound 269
Di(p-chlorophenyl)-
trichloromethycarbonol, DTMC, dicofol
Galena
Gamma-BHC, Gamma-benzene hexachloride
PCB, Arochor, polychlorinated diphenyls
Lead tetraethyl, TEL
Camphechlor
11
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The extent of contaminant transport following releases to the land
surface and subsequent entrainment to the atmosphere depends upon a variety
of critical contaminant and site characteristics. This section briefly de-
scribes the important contaminant and site characteristics. It provides
the user with an understanding of the types of information needed to per-
form a valid assessment. Guidelines for translating these characteristics
into required specific parameter values required by the assessment procedures
are provided in Section 4.
2.3.1 Critical Contaminant Characteristics
To assess the potential for atmospheric contamination in an emergency
response situation, several properties of the compound or waste must first
be determined, especially in the case of chemical spills. Much of this in-
formation may be difficult to accurately quantify within a 24-hr time frame,
but it is likely that an applicable range of values will be estimated. Some
properties are used directly in the assessment or to estimate parameters,
while others are needed to interpret the results. Those characteristics
deemed crucial to an informed assessment are discussed below:
1. Contaminant identity - The identities of the contaminants must be
known to determine those physical/chemical properties necessary for assess-
ing pollutant fate and migration. The physical state of the contaminant
(liquid or solid) should be assessed as part of the identification process.
Within the emergency response time frame, it may be possible to identify
only general classes of chemicals rather than specific compounds. In such
instances, parameter estimation will be especially difficult.
2. Extent of the contamination - The extent of the surface contamina-
tion must be defined to determine the source term used in estimating trans-
port into the atmosphere. This assessment should provide an estimate of
the mass fraction of the contaminant in the surface material. Ideally, the
level of contamination in the PM10 fraction of the surface material is
needed. In addition, the total ground area contaminated by the spill or
the disposal operation should be ascertained. In the case of a spill it is
necessary to account for contaminant losses by volatilization into the air,
runoff, and containment or removal measures on the land surface in estimating
the extent of residual contamination. Information on the volatility and
reactivity of the waste may be required in making this assessment.
3. Volatility - The volatility of an organic liquid affects its loss
to the atmosphere as a vapor. This is especially important in the case of
spills where a high degree of atmosphere exposure is typical. As with most
other critical contaminant properties, volatility is strongly temperature
dependent.
4. Solubility - The solubility of a compound affects its mobility in
the soil. The spreading of the contaminant from a surface spill is usually
controlled by its tendency to dissolve in the water moving through the soil.
12
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A material's solubility may also affect the ease with which it can adsorb
on soil particles, with less soluble wastes being more easily adsorbed.
The existence of solvents other than water should also be determined since
it can affect the compound's miscibility with soil water.
5. Adsorption - Adsorption can be a significant means of retarding
contaminant movement through the soil. It is a property dependent upon both
the nature of the compound and the soil. Adsorption capabilities for organic,
nonionic compounds are often described in terms of adsorption (or partition)
coefficients for a particular compound/soil combination. These coefficients
are often estimated from the organic carbon (or organic matter) content of
the soil and the organic carbon partition coefficient (which in turn can be
estimated from compound characteristics such as the octanol/water partition
coefficient). Adsorption of ionic compounds is also a function of ion ex-
change capacities and clay type and content. This is especially important
for soils or media with low organic matter.
6. Degradation - Degradation by both chemical and biological mecha-
nisms is important because it can reduce levels of contaminants in the sur-
face material. Common degradation mechanisms in the environment are hydro-
lysis, photolysis, biodegradation, chemical oxidation, and radioactive decay.
Hydrolysis and chemical oxidation are important primarily for contaminants
in soils. Photolysis can occur only on the surface of the soil. Biodegrada-
tion is most important in the top few feet of soil where bacterial concen-
trations are high. Radioactive decay occurs in all environments under all
conditions.
6- Toxicity - To assess the hazard of any predicted or observed atmo-
spheric contamination, the toxicity of the pollutants must be determined.
Since nearly all chemicals are toxic at very high concentrations, the con-
cern in this assessment is for materials that are moderately to severely
toxic or are carcinogenic, mutagenic, or teratogenic to humans and other
organisms.
7. Density, viscosity and surface tension - These compound parameters
are important in evaluating the penetration characteristics of the contami-
nant into the soil and the potential for particle reentrainment into the
atmosphere.
2.3.2 Critical Site Characteristics
To assess potential atmospheric contamination at a hazardous waste or
spill site, a number of site characteristics are important in addition to
the contaminant characteristics discussed above. The discussions below are
intended to provide an overview of the information needed to characterize
an emergency response site in appropriate detail to estimate contaminant
release to and transport in the air environment; specific guidelines on
parameter estimation are presented in Sections 3 and 4.
Emissions from open dust sources associated with contaminated land areas
exhibit a high degree of variability from one site to another, and emissions
at any one site tend to fluctuate widely. The site characteristics which
13
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cause these variations may be grouped into two categories: measures of
energy expended by wind or machinery interacting with the contaminated
surface (for example, the wind speed or the speed of a vehicle traveling
over the surface); and properties of the contaminated surface material (for
example, the content of suspendable fines in the surface material and its
moisture content or, for a crusted surface, the strength of the crust).
1. Surface material texture - The dry particle size distribution of
the exposed soil or surface material determines its susceptibiliy to wind
erosion and mechanical entrainment. Wind forces move soil by three trans-
port modes: saltation, surface creep, and suspension. Saltation describes
particles, ranging in diameter from about 75 to 500 urn that jump or bounce
within a layer close to the air-surface interface. Particles transported
by surface creep range in diameter from about 500 to 1,000 urn. These sur-
face creep particles move very close to the ground propelled by wind stress
and the impact of smaller particles transported in saltation. Particles
smaller than about 75 urn in diameter move by suspension and tend to follow
air motions. The upper size limit of silt particles (75 urn in diameter) is
roughly the smallest particle size for which size analysis by dry sieving
is practical, and this particle size is also a reasonable upper limit for
particulat.es which can become suspended. The threshold wind speed for the
onset of saltation, which drives the wind erosion process, is also depen-
dent on soil texture, with 100 to 150 urn particles having the lowest thresh-
old speed.
2. Surface material moisture - Dust emissions are known to be strongly
dependent on the moisture level of the emitting material. Water acts as a
dust suppressant by forming cohesive moisture films among the discrete grains
of surface material. In turn, the moisture level depends on the moisture
added by natural precipitation and on the moisture removed by evaporation
and moisture movement beneath the surface. The evaporation rate depends on
the degree of air movement over the surface soil texture, clay minerology
and crust presence. The moisture holding capacity of the air is also impor-
tant, and it correlates strongly with the surface temperature. Vehicle
traffic intensifies the drying process primarily by increasing air movement
over the surface.
3. Nonerodible elements - Nonerodible elements such as clumps of grass
or stones (larger than about 1 cm in diameter) on the surface, consume part
of the shear stress of the wind which otherwise would be transferred to
erodible soil. Surfaces impregnated with a large density of nonerodible
elements behave as having a "limited reservoir" of erodible particles, even
if the material protected by nonerodible elements is of itself highly erod-
ible. Wind-generated emissions from such surfaces decay sharply with time,
as the particle reservoir is depleted. Surfaces covered by unbroken grass
are virtually nonerodible.
4. Crust formation - Following the wetting of a soil or other surface
material, fine particles will move to form a surface crust. The surface
crust acts to hold in soil moisture and resist erosion. The degree of pro-
tection that is afforded by a soil crust to the underlying soil may be mea-
sured by the modulus of rupture and thickness of the crust. This modulus
14
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of rupture is roughly a measure of hardness of the crust. A soil which lacks
a surface crust (for example a disturbed soil or a very sandy soil) is much
more susceptible to wind erosion.
5. Frequency of mechanical disturbance - Emissions generated by wind
erosion are also dependent on the frequency of disturbance of the erodible
surface. A disturbance is defined as an action which results in the expo-
sure of fresh surface material. This would occur whenever aggregate mate-
rial is either added to or removed from the old surface. A disturbance of
an exposed area may also result from the turning of surface material to a
depth exceeding the size of the largest pieces of material present. Each
time that a surface is disturbed, its erosion potential is increased by de-
stroying the mitigative effects of crusts, vegetation and friable non-
erodible elements and by exposing new surface fines. Although vehicular
traffic alters the surface by pulverizing surface material, this effect
probably does not restore the full erosion potential, except for surfaces
that crust before substanital wind erosion occurs. In that case, breaking
of the crust over the area of the tire/surface contact once again exposes
the erodible material beneath.
6. Wind speed - Agricultural scientists have established that total
soil loss by continuous wind erosion is dependent on the cube of wind speed.
More recent work has shown that the loss of particles in suspension mode
follows the same dependence. Soils protected by non-erodible elements or
crusts exhibit a weaker dependence of suspended particulate emissions on
wind speed. In fact, mean atmospheric wind speeds in many areas of the
country are not sufficient to initiate wind erosion from "limited reservoir"
surfaces. However, wind gusts may quickly deplete a substantial portion of
the erosion potential of surfaces having a "limited reservoir" of erodible
particles. In addition, because erosion potential (mass of particles con-
stituting the "limited reservior") increases rapidly with increasing wind
speed, estimated emissions should be related to the gusts of highest
magnitude.
The routinely measured meteorological variable which best reflects the
magnitude of wind gusts is the fastest mile. The quantity represents the
wind speed corresponding to the whole mile of wind movement which has passed
by the 1-mile contact anemometer in the least amount of time. Daily measure-
ments of the fastest mile are presented in the monthly Local Climatological
Data (LCD) summaries. The duration of the fastest mile, typically about
1-2 min (for fastest miles of 30-60 mph, respectively), matches well with
the half-life (i.e., the time required to remove one-half the erodible par-
ticles on the surface) of the erosion process. It should be noted, however,
that peak wind speeds can significantly exceed the daily fastest mile.
15
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-------
SECTION 3
SITE SURVEY AND DATA GATHERING
3.1 ASSESSMENT OF EXTENT OF SURFACE CONTAMINATION
As stated in Section 2.1, it is presumed that surface contamination
data will be available for the spill site or the abandoned waste disposal
site being assessed. Ideally, the surface contaminant levels will have been
determined for that fraction of the surface material which has the potential
to become airborne, i.e., the silt fraction (defined in this manual as
particles passing a 200 mesh screen on dry sieving). In any case, unless
data can be obtained on the fine particle enrichment of contamination for
classes of compounds which are readily adsorbed onto soil particles, the
analyst should assume that the level of contamination in the particulate
emissions matches that measured in the bulk surface material.
As an alternative to contamination measurements for chemical spills,
it may be possible to estimate the level of contamination based on the amount
of material spilled and the volume of receiving material penetrated by the
spill. Although the size of the surface affected by the spill may be easily
determined, the depth of penetration depends on several factors such as
viscosity and surface tension of the chemical and the porosity of the receiv-
ing surface. For volatile chemicals, that portion of the spill which evapo-
rates must also be accounted for.
Unless the level of contamination in the surface material is uniform
over the full extent of the contaminated area, it is desirable to know the
spatial distribution of surface contamination. Also, it is implied that
there are well defined boundaries to the contaminated area. Generally, ex-
cept for spills, such will not be the case because of the spreading of con-
tamination over a period of time by successive entrainment/deposition pro-
cesses.
If no data are available on the distribution of contamination and its
boundaries, the emergency response team must estimate the size of the con-
taminated area based on historical data on the typical size ranges of con-
taminated areas of various types. Also, surface features (cover, topography,
surface texture, etc.) can be used to delineate site boundaries. A worksheet
has been prepared for use in conducting a site survey and is shown in
Figure 3-1. An expanded version of the site survey decision flowchart is
given in Figure 3-2.
17
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c/
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Figure 3-1. (concluded)
19
-------
NO
WIND
EROSION
SBLEC.T
UNLIMITED
MODEL
SELECT
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MOPEL
^
-------
The second step in the estimation of emissions from an abandoned waste
dump or spill site is the determination of the potential for entrainment of
contaminated soil by wind or by mechanical disturbance. This determination
will be based on a visual site inspection coupled with optional hand siev-
ing of surface material.
3.2 CHARACTERIZATION OF WIND EROSION POTENTIAL
With regard to estimating particulate emissions from wind erosion of
contaminated surface material, site inspection can be used to determine the
potential for continuous wind erosion. The two basic requirements for wind
erosion are that the surface be dry and exposed to the wind. For example,
if the contaminated site lies in a swampy area or is covered by unbroken
grass, the potential for wind erosion is virtually nil. The same would be
true if a substance spilled or otherwise applied to the surface solidifies
and acts as impervious binder. If, on the other hand, the vegetative cover
is not continuous over the contaminated surface, then the plants are con-
sidered to be nonerodible elements which absorb a fraction of the wind
stress that otherwise acts to suspend the intervening contaminated soil.
For estimating emissions from wind erosion, either of two emission fac-
tor equations are recommended (Section 4) depending on the credibility of
the surface material. Based on the site survey, the contaminated surface
must be placed in one of two erodibility classes described below. The
division between these classes is best defined in terms of the threshold
wind speed for the onset of wind erosion.
Nonhomogeneous surfaces impregnated with nonerodible elements (stones,
clumps of vegetation, etc.) are characterized by the finite availability
("limited reservoir") of erodible material. Such surfaces have high thresh-
old wind speeds for wind erosion, and particulate emission rates tend to
decay rapidly during an erosion event. On the other hand, bare surfaces of
finely divided material such as sandy agricultural soil are characterized
by an "unlimited reservoir" of erodible particles. Such surfaces have low
threshold wind speeds for wind erosion, and particulate emission rates are
relatively time independent at a given wind speed.
For surface areas not covered by continuous vegetation the classifica-
tion of surface material as either having a "limited reservoir" or an
"unlimited reservoir" of erodible surface particles is determined by estimat-
ing the threshold friction velocity. Based on the authors' analysis of wind
erosion research, the dividing line for the two erodibility classes is a
threshold friction velocity of about 75 cm/sec. This somewhat arbitrary
division is based on the observation that highly erodible surfaces, usually
corresponding to sandy surface soils that are fairly deep, have threshold
friction velocities below 75 cm/sec. Surfaces with friction velocities
larger than 75 cm/sec tend to be composed of aggregates too large to be
eroded mixed in with a small amount of erodible material or of crusts that
are resistent to erosion (Gillette et al., 1982).
The cutoff friction velocity of 75 cm/sec corresponds to an ambient
wind speed of about 10 m/sec (22 mph), measured at a height of about 7 m.
21
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In turn, a specific value of threshold friction velocity for the erodible
surface is needed for either wind erosion emission factor equation (model).
Crusted surfaces are regarded as having a "limited reservoir" of erodi-
ble particles. Crust thickness and strength should be examined during the
site inspection, by testing with a pocket knife. If the crust is more than
0.6 cm thick and not easily crumbled between the fingers (modulus of rupture
> 1 bar), then the soil may be considered nonerodible. If the crust thick-
ness is less than 0.6 cm or is easily crumbled, then the surface should be
treated as having a limited reservoir of erodible particles. If a crust is
found beneath a loose deposit, the amount of this loose deposit, which con-
stitutes the limited erosion reservoir, should be carefully estimated.
For uncrusted surfaces, the threshold friction velocity is best esti-
mated from the dry aggregate structure of the soil. A simple hand sieving
test of surface soil is highly desirable to determine the mode of the sur-
face aggregate size distribution by inspection of relative sieve catch
amounts, following the procedure specified in Figure 3-3. The threshold
friction velocity for erosion can be determined from the mode of the
aggregate size distribution, following a relationship derived by Gillette
(1980) as shown in Figure 3-4.
A more approximate basis for determining threshold friction velocity
would be based on hand sieving with just one sieve, but otherwise follows
the procedure specified in Figure 3-3. Based on the relationship developed
by Bisal and Ferguson (1970), if more than 60% of the soil passes a 1-mm
sieve, the "unlimited reservoir" model will apply; if not, the "limited
reservoir" model will apply. This relationship has been verified by Gillette
(1980) on desert soils.
If the soil contains nonerodible elements which are too large to in-
clude in the sieving (i.e., greater than about 1 cm in diameter), the effect
of these elements must be taken into account by increasing the threshold
friction velocity. Marshall (1971) has employed wind tunnel studies to
quantify the increase in the threshold velocity for differing kinds of non-
erodible elements. His results are depicted in terms of a graph of the rate
of corrected to uncorrected friction velocity versus L (Figure 3-5), where
L is the ratio of the silhouette area of the roughnesS elements to the total
area of the bare loose soil. The silhouette area of a nonerodible element
is the projected frontal area normal to the wind direction.
A value for l_c is obtained by marking off a 1 m x 1 m surface area and
determining the fraction of area, as viewed from directly overhead, that
is occupied by non-erodible elements. Then the overhead area should be
corrected to the equivalent frontal area; for example, if a spherical non-
erodible element is half imbedded in the surface, the frontal area is one-
half of the overhead area. Although it is difficult to estimate L for
values below 0.05, the correction to friction velocity becomes less Sensi-
tive to the estimated value of L .
22
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FIELD PROCEDURE FOR DETERMINATION OF THRESHOLD FRICTION VELOCITY*
1. Prepare a nest of sieves with the following openings: 4 mm, 2 mm,
1 mm, 0.5 mm, 0.25 mm. Place a collector pan below the bottom sieve
(0.25 mm opening).
2. Collect a sample representing the surface layer of loose particles
(approximately 1 cm in depth for an uncrusted surface), removing
any rocks larger than about 1 cm in average physical diameter. The
area to be sampled should not be less than 30 cm x 30 cm.
3. Pour the sample into the top sieve (4 mm opening), and place a lid
on the top.
4. Rotate the covered sieve/pan unit by hand using broad sweeping arm
motions in the horizontal plane. Complete 20 rotations at a speed
just necessary to achieve some relative horizontal motion between
the sieve and the particles.
5. Inspect the relative quantities of catch within each sieve and de-
termine where the mode in the aggregate size distribution lies, i.e.,
between the opening size of the sieve with the largest catch and the
opening size of the next largest sieve.
* Adapted from a laboratory procedure published by W. S. Chepil (1952).
Figure 3-3.
23
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The difficulty in estimating L also increases for small non-erodible
elements. However, because small nbn-erodible elements are more likely to
be evenly distributed over the surface, it is usually acceptable to examine
a smal er surface area, e.g., 30 cm x 30 cm. The photographs of various non-
erodible element distributions presented in Appendix A can be used as an aid
in estimating L for surfaces with small non-erodible elements. These photo-
graphs illustrate the physical appearance corresponding to various values of L
i
The least acceptable technique for classifying the erodibility of the
surface material is by visual surface examination and matching with the photo-
graphs given in Appendix A. Once again, loose sandy soils fall into the high
erodibility ('unlimited reservoir"). These soils do not promote crust forma-
tion, and show only a brief effect of moisture addition by rainfall On the
other hand, compacted soils with a tendency for crust formation fall into the
low ( limited reservoir") erodibility group. Clay content in soil, which
tends to promote crust formation, is evident from crack formation upon drying.
The roughness height, z which is related to the size and spacing of
surface roughness elements, Ss needed to convert the friction velocity to
the equivalent wind speed at the typical weather station sensor height of
7 m^ above the surface. Figure 3-6 depicts the roughness height scale for
various conditions of ground cover (Cowherd and Guenther, 1976). The con-
version to the 7 m value is discussed in Section 4 (Figure 4-2).
In addition to these surface properties, it is also important that the
field personnel note the location and orientation of significant topographic
features that are likely to influence the dispersion of contaminated material
from the site. Significant topographic features will include not only the
terrain of the surrounding area but also the large-scale roughness elements
such as trees and buildings that might enhance or obstruct the wind flow
for the site in question. A consideration of these features is important
in the proper interpretation of the modeling results presented in Section 4 2
In order to ensure the best possible characterization of the local-scale wind'
flow it is recommended that the response team contact both the nearest Na-
tional Weather Service office and an American Meteorological Society (AMS)
Certified Consulting Meteorologist1.
3.3 CHARACTERIZATION OF MECHANICAL RESUSPENSION BY VEHICLE TRAFFIC
The most typical type of intensive mechanical disturbance occurs with
vehicle travel over the contaminated surface material. The occurrence of
traffic over the site can be determined by inspection of the site for ex-
istence of roads. Other less common forms of mechanical disturbance are
associated with any operation which moves or turns over surface material
(i.e scraping grading tilling, etc.). All of these operations not only
nntPnt? S,Ufe^ particulate matter into the air, but greatly increase the
potential for subsequent wind erosion by destroying protective surface crusts
and removing vegetative cover. Because these types of disturbance are rare
nh dl.sci;ssion ls limited t° Chicle traffic as the typically sig-
mechanical resuspension process.
A list °f Certified Consulting Meteorologists is available from the
""*>"• M^ ^husetts
26
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High Rise Buildings
(30+ Floors)
Suburban
Medium Buildings-
(Institutional )
E
u
o
N
o
LU
X
CO
CO
LU
z
o
o
Suburban
Residential Dwellings
Wheat Field
Plowed Field
Zo (cm)
1000
—40.0-
—20.0—
10.0
Natural Snow
-800-
-600-
-400-
-200-
100
-80.0-
-60.0-
-8.0-
-6.0-
-4.0-
2.0—
1.0
-0.8-
-0.6-
-0.4-
-0.2-
0.1
Urban Area
Woodland Forest
Grassland
Figure 3-6. Roughness Heights for Various Surfaces (Cowherd and
Guenther, 1976)
27
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The emission factor equation for vehicle travel on unpaved surfaces,
as presented in Section 4, requires estimates of site-specific traffic and
surface parameters. Average vehicle speed and number of wheels can be esti-
mated from direct observation of traffic, site inspection of road condition,
and interviews with people living or working near the site. Vehicle weight
can be estimated from vehicle type and number of wheels, using a chart
presented in Section 4. Default values for road surface silt content are
also provided.
28
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SECTION 4
CALCULATIONS AND GATHERING OF RESULTS
The assessment procedure developed in this manual follows a source-
oriented approach. It requires the user first to estimate particulate
emission rates for the contamination site, and then to link these estimates
to the results of a general Gaussian dispersion algorithm in order to esti-
mate ambient concentrations of contaminant in the form of respirable parti-
culate matter. The following sections describe the emission factor models
used to estimate contaminant emissions generated by wind erosion and
mechanical entrainment, and the procedure for "translating" these results
into ambient concentrations and associated exposures.
4.1 CALCULATION OF AVERAGE/WORST-CASE EMISSION RATES
This section describes the emission factor models used to estimate
particulate emissions generated by mechanical entrainment and by wind ero-
sion of contaminated surface material. Also this section describes the
sources of data and the procedures used to estimate the parameters required
for input to the emission models.
In the case of wind erosion emissions, there are no "ready-made" models
fully capable of meeting the requirements of rapid assessment. As such,
the information presented in Sections 4.1.1 and 4.1.2 provides best estimates
for wind generated emissions, based on current knowledge of the suspension
of surface material by wind action.
4.1.1 Wind Erosion from Surfaces with Limited Erosion Potential
For estimating respirable particulate emissions from surfaces charac-
terized by a "limited reservoir" of erodible material, a predictive emission
factor equation developed by Cowherd (1983) from field measurements using a
portable wind tunnel at surface mines is recommended. In relating the
annual average rate of respirable particulate emissions to surface and
climatic factors, the equation takes the following form:
f P(u+
•10 - O-8^ ~
where: E10 = PM10 emission factor, i.e., annual average PMi0 emission rate
per unit area of contaminated surface (mg/nr-hr)
f = frequency of disturbance per month
29
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u - observed (or probable) fastest mile of wind for the period
between disturbances (m/s)
P(u ) = erosion potential, i.e., quantity of erodible particles
present on the surface prior to the onset of wind erosion
(g/m2)
V = fraction of contaminated surface area covered by continuous
vegetative cover (equals 0 for bare soil)
PE = Thornthwaite's Precipitation Evaporation Index used as a
measure of average soil moisture content
Although Equation 4-1 is based primarily on field tests of nonsoil sur-
faces (e.g. , coal with a top size of 3 cm and a silt content exceeding 4%)
subsoil and other crustal materials showed similar behavior. The erosion'
potential (in g/m2) depends on the fastest mile (in m/s) as follows:
P(u+) = 6.7 (u+ - ut), u+ £ ut (4-2)
0 , u+
where u. is the erosion threshold wind speed (in m/s), measured at a typical
weather station sensor height of 7 m.
The threshold friction velocity determined from the site survey is con-
verted to the equivalent wind speed at a height of 7 m using Figure 4-1.
This figure assumes a logarithmic velocity profile near the earth's surface:
u(z) _ 1 -, / / > C4-^
— - o In (z/zo) ^ *>
where: u = wind speed at height z (m/s)
z = height above surface (cm)
u^ = friction velocity (m/sec)
ZQ = roughness height (cm)
Mean annual fastest mile (u+) values are presented in Table 4-1. The
value for the weather station closest to the surface contamination site
should be used.
Emissions generated by wind erosion of "limited reservoir" surfaces
are also dependent on the frequency of disturbance (f) of the erodible sur-
face, because each time that a surface is disturbed, its erosion potential
is restored. A disturbance is defined as an action which results in the
30
-------
o
o
'a;
>
c
o
•£
o
CD
O
+-> CO
CO
E OJ
en
-M 13
tts o
•r- O
O
O
CfL
UOJ4DIJJ 04 LU/ 40
jo oj
31
-------
TABLE 4-1.
FASTEST MILE3 [u+] AND MEAN WIND SPEEDb [u]
FOR SELECTED UNITED STATES STATIONS
Station
Birmingham
Montgomery
Tucson
Yuma
Fort Smith
Little Rock
Fresno
Red Bluff
Sacramento
San Diego
Denver
Grand Junction
Pueblo
Hartford
Washington
Jacksonville
Tampa
Atlanta
Macon
Savannah
Boise
Pocatello
Chicago
Mo line
Peoria
Springfield
Evansville
Fort Wayne
Indianapolis
Burlington
Des Moines
Sioux City
Concordia
Dodge City
Topeka
Wichita
Louisville
Shreveport
Portland
Baltimore
Boston
State
AL
AL
AZ
AZ
AR
AR
CA
CA
CA
CA
CO
CO
CO
CT
DC
FL
FL
GA
GA
GA
ID
ID
IL
IL
IL
IL
IN
IN
IN
IA
IA
IA
KS
KS
KS
KS
KY
LA
ME
MD
MA
[u+]
(m/s)
20.8
20.2
23.0
21.8
20.8
20.9
15.4
23.3
20.6
15.4
22.0
23.6
28.1
20.2
21.6
21.7
22.2
21.2
20.1
21.3
21.4
23.8
21.0
24.5
23.2
24.2
20.9
23.7
24.8
25.0
25.8
25.9
25.7
27.1
24.4
26.0
22.0
19.9
21.7
25.0
25.2
[u]
(m/s)
3.3
3.0
3.7
3.5
3.4
3.6
2.8
3.9
3.7
3.0
4.1
3.6
3.9
4.0
3.4
3.8
3.9
4.1
3.5
3.6
4.0
4.6
4.6
4.4
4.6
5.1
3.7
4.6
4.3
4.6
5.0
4.9
5.4
6.3
4.6
5.6
3.8
3.9
3.9
4.2
5.6
Station
Detroit
Grand Rapids
Lansing
Sault St. Marie
Duluth
Minneapol is
Jackson
Columbia
Kansas City
St. Louis
Springfield
Billings
Great Falls
Havre
Helena
Missoula
North Platte
Omaha
Valentine
Ely
Las Vegas
Reno
Winnemucca
Concord
Albuquerque
Roswell
Albany
Binghampton
Buffalo
New York
Rochester
Syracuse
Cape Hatteros
Charlotte
Greensboro
Wilmington
Bismarck
Fargo
Cleveland
Columbus
Dayton
State
MI
MI
MI
MI
MN
MN
MS
MO
MO
MO
MO
MT
MT
MT
MT
MT
NE
NE
NE
NV
NV
NV
NV
NH
NM
NM
NY
NY
NY
NY
NY
NY
NC
NC
NC
NC
ND
ND
OH
OH
OH
[u+]
(m/s)
21.8
21.6
23.7
21.6
22.8
22.0
20.5
22.4
22.6
21.2
22.4
26.6
26.4
25.9
24.7
21.6
27.7
24.6
27.1
23.6
24.4
25 2
C_ <*J • C_
22.4
19.2
25.6
26.0
21.4
22.0
24. 1
22.5
23.9
22.5
25.9
20.0
18.9
22.3
26.1
26.6
23.6
22.1
24.0
[u]
(m/s)
4 6
i • W
4.5
4.6
4.3
5 1
*J • -L
4.7
3 4
*J • t
4.4
4.6
4.2
5.0
5.1
5 9
+j • «/
4 5
i • \J
3 5
*_/ * w
2.7
4.6
4.8
4 8
T • \J
4.7
4.0
2 g
c_ • J
3.5
3.0
4.0
4 1
T • i
4.0
4.6
5 5
*J • *J
5 5
\j • \j
4 3
i • +J
4.4
5.1
3.4
3.4
4.0
4. 7
5.7
4 8
i • \J
3.9
4.6
32
-------
TABLE 4-1 (concluded)
Station
Toledo
Oklahoma City
Tulsa
Portland
Harrisburg
Philadelphia
Pittsburgh
Scranton
Huron
Rapid City
Chattanooga
Knoxvil le
Memphis
Nashville
Abilene
Amarillo
Austin
Brownsville
Corpus Christi
a Data taken
[u+]
State (m/s)
OH
OK
OK
OR
PA
PA
PA
PA
SD
SD
TN
TN
TN
TN
TX
TX
TX
TX
TX
from
United States.
22
24
21
23
20
22
21
19
27
27
21
21
20
20
24
27
20
19
24
Extreme
Simiu,
.7
.1
.4
.5
.4
.1
.6
.9
.4
.3
.4
.8
.3
.9
.4
.3
.2
.5
.4
Wind
E.,
[u]
(m/s)
4.
5.
4.
3.
3.
4.
4.
3.
5.
5.
2.
3.
4.
3.
5.
6.
4.
5.
5.
2
7
7
5
4
3
2
8
3
0
8
3
1
6
4
1
2
3
4
Speeds
Fil
Station
Dallas
El Paso
Port Arthur
San Antonio
Salt Lake City
Burlington
Lynchburg
Norfolk
Richmond
Quillayute
Seattle
Spokane
Green Bay
Madison
Milwaukee
Cheyenne
Lander
Sheridan
Elkins
at 129 Stations
liben, J. J. , and M.
State
TX
TX
TX
TX
UT
VT
VA
VA
VA
WA
WA
WA
WI
WI
WI
WY
WY
WY
WV
in the
[u+]
(m/s)
21.
24.
23.
21.
22.
20.
18.
21.
18.
16.
18.
21.
25.
24.
24.
27.
27.
27.
22.
9
8
7
0
6
4
3
8
9
3
7
4
3
9
0
0
4
5
8
[u]
(m/s)
4.
4.
4.
4.
3.
3.
3.
4.
3.
3.
4.
3.
4.
4.
5.
5.
3.
3.
2.
9
2
5
2
9
9
5
7
4
0
1
9
6
4
3
9
1
6
8
Contiguous
J. Changery.
NBS Building Science Series 118. U.S. Department of Commerce,
National Bureau of Standards, 1979.
Data taken from Local Climatological Data - Annual Summaries for 1977.
U.S. Department of Commerce, National Oceanic and Atmospheric Ad-
ministration/Environmental Data Service/National Climatic Data
Center.
33
-------
exposure of fresh surface material. This would occur whenever aggregate
material is either added to or removed from the old surface. A disturbance
of an exposed area may also result from the turning of surface material to
a depth exceeding the size of the largest pieces of material present.
Although vehicular traffic alters the surface by pulverizing surface
material, several vehicle passes may be required to restore the full ero-
sion potential, except for surfaces that crust before substantial wind ero-
sion occurs. In that case, breaking of the crust over the area of the tire/
surface contact once again exposes the erodible material beneath.
Thornthwaites1 P-E (PE) Index is a useful indicator of average surface
soil moisture conditions. In the present context, the P-E Index is applied
as a correction parameter for wind generated emissions in the limited reser-
voir case. Figure 4-2 provides a basis for selecting an appropriate P-E
value.
The worst-case emission rate is calculated by assuming that a disturb-
ance occurs just prior to the annual fastest mile event, both within the
24-h period of interest. For this calculation, use Equation (4-1) with
f =30 mo-1.
4.1.2 Wind Erosion from Surfaces with Unlimited Erosion Potential
For estimating respirable particulate emissions from wind erosion of
surfaces with an "unlimited reservoir" of erodible particles, a predictive
emission factor equation developed from Gillette's (1981) field measurements
of highly erodible soils is recommended. In relating the annual average
rate of respirable particulate emissions (per unit area) to field and clima-
tic factors, the equation takes the following form:
E10 = 0.036 (1-V) [1HJ\ F(x) (4-4)
wnere: Eio ~ PM10 emission factor, i.e., annual average PM10 emission
rate per unit area of contaminated surface (g/m2-hr)
V = fraction of contaminated surface vegetative cover
(equals 0 for bare soil)
[u] = mean annual wind speed (m/s), taken from Table 4-1
x = 0.886 ut/[u] = dimensionless ratio
F(x) = function plotted in Figure 4-3
ut = threshold value of wind speed at 7 m (m/s)
This follows from the empirical relationship that the vertical flux of
particles smaller than 10 pm diameter is proportional to the cube of wind
speed. Because highly erodible soils do not readily retain moisture no
moisture-related parameter is included in the equation.
34
-------
CO
c
o
•I—
CO
>
•r—
O
O
O)
+->
03
+J
OO
X
-------
CT
UJ
O)
-o
(D
a
o
o
c
13
u_
1.5
0.5
o
F(x) Tends to 1.91
as x tends to zero.
0
x = 0.886 ut/[u]
0.5
See Appendix B for
larger values of x.
1.5
Figure 4-3. Graph of Function F(X) Needed to
Estimate Unlimited Erosion
36
-------
In this assessment process, the mean annual wind speed ([u]) for the
weather station nearest the site (Table 4-1) should be used. The threshold
wind speed at 7 m (u.) is found by converting the threshold friction velocity
(determined from the site survey) using Figure 4-2. Equation 4-3 is based
upon an expected value using an estimated annual wind speed probability dis-
tribution as the weighting function. The function F(x) is proportional to
this expected value. Details of the integration are presented in Appendix B.
The worst-case emission factor is calculated using a simplified form
of Equation (4-3):
E10 - 0.036 (1-V) [U6_hr]3 (4-5)
where: Cuc_h ] = expected maximum 6-hr mean wind speed during the year.
From a physical viewpoint, it is apparent that the maximum 6-hr mean wind
speed must be somewhat lower than the corresponding annual fastest mile.
In order to roughly account for the influence of increasing averaging
time, the following expression should be applied to the [u ] values in
Table 4-1:
[u6_hr] - [u+] - 2 m/s (4-6)
This relationship has been proposed by the World Meteorological Organiza-
tion (1961) for correction of 1-min to corresponding 1-hr extremes.
4.1.3 Vehicle Traffic
For estimation of PM10 emissions from vehicle traffic over unpaved sur-
faces, the following equation should be used:
= 0.85 i . (4-7)
where: E10 = PM10 emission factor, i.e., the quantity of PM10 emissions
from an unpaved road per vehicle- kilometer of travel (kg/VKT)
s = silt content of road surface material (%)
S = mean vehicle speed (km/hr)
W = mean vehicle weight (Mg)
w = mean number of wheels
p = number of days with at least 0.254 mm (0.01 in.) of precipi-
tation per year
Default values for the various parameters in the equation are given in
Table 4-2. These should only be applied when site-specific information from
local sources is unavailable.
37
-------
TABLE 4-2. DEFAULT VALUES FOR INDEPENDENT VARIABLES OF EQUATION 4-6'
Site
Rural/Residential
Industrial
s(%) S(km/hr) W(Mg)
15 (5-68) 48 (40-64) 2
8 (2-29) 24 (8-32) 3
15
26
w
4
4
6
10
Numbers in parentheses are ranges of measured values.
Values for p (wet days per year) are obtained from Figure 4-4 or from
a local source. Worst-case 24-hr emissions would occur on a dry day (p = 0)
with the highest volume of traffic expressed as vehicle-kilometers traveled.
If the vehicle mix varies, periods with a greater portion of larger vehicles
produce greater emissions.
4.1.4 Determination of Emission Rates
Contaminant emission rates (R10) are determined from the above emission
factors (E10) using Equation 2-1:
RIO := <* E10 A (2-1)
where R10 = emission rate of contaminant as PM10
a = mass fraction of contaminant in PM10 emissions
A = source extent (for a specified averaging time in the case
of mechanical resuspension)
For wind erosion, the source extent is simply the contaminated area.
For example, if an area of 2,000 m2 is contaminated, the annual emission
factor is 0.17 mg/m2-hr and a = 16 ppm, the annual contaminant emission rate
is:
R10 = (16 • 10"6) (0.17 mg/m2-hr) (2,000 m2) = 5.4 ug/hr (4-9)
In the case of mechanical resuspension in the form of travel on unpaved sur-
faces, the source extent is found as the product of the contaminated travel
length times the daily traffic count. Note that the daily traffic count
for a worst-case would be greater than that for annual conditions. An
example is provided in Section 5.2.
38
-------
g
z
z
o
LU
OC
o_
o
LU
O
OH
O
u
Z
o
o
X
H-
£
t-O
o
c£
LU
CO
Z>
Z
39
-------
Once the contaminant emission rates associated with wind and traffic
entrainment have been calculated, the next step is to estimate the duration
of exposure to the airborne contaminant. This is done by comparing the an-
nual average contaminant mass emission rate to the total mass of contaminant
available for entrainment. In the case of a deep horizon of surface contam-
ination, long-term wind erosion will be limited to the depth of surface mate-
rial that is unprotected by large non-erodible elements; on the other hand
mechanical entrainment by vehicle traffic can wear the surface indefinitely.
As a first approximation of the duration of exposure, the total initial
mass of contaminant in the form of PM10 particles on the surface should be
divided by the initial value of the annual average contaminant emission
rate (R10). If the resulting value exceeds 70 years (the time basis for
lifetime exposure assessment), no correction for decay in emission rate is
required. Otherwise, the annual average contaminant emission rate must be
adjusted downward, to account for the significant depletion in the contam-
inant mass. This situation would be expected, for example, in the case of
a spill of a powder which neither penetrates nor adheres to the soil.
If the duration of exposure obtained above does not exceed 70 years,
it is recommended that the expected decay in emission be derived from first
order kinetics, based on the principle that the contaminant emission rate
at any point in time is proportional to the amount of contaminant remaining
in the exposed surface material. The decay constant is given by:
k = RIO/MIO (4-10)
where k = decay constant (I/time)
R10 = initial value of combined annual average emission rate
(mass/time)
M10 = initial mass of the contaminant in the form of PM10 particles
on the surface (mass)
Based on this model, the times required to entrain 90% or more of the ini-
tial mass of contaminant, and the average emission rates during these time
periods are as follows:
Fraction of
initial mass
remaining
10%
1%
0.1%
Time
required
2.3/k
4.6/k
6.9/k
Ratio of average
to initial
emission rate
0.39
0.21
0.14
It is recommended that exposure assessment be carried out to the point in
time at which 10% of the initial contaminant mass remains. Thus, the cal-
culated initial annual average emission rate should be multiplied by 0.39.
40
-------
4.2 DISPERSION MODELING
In order to obtain estimates of ambient concentrations attributable to
participate emissions from surface contamination sites, an atmospheric dis-
persion model is required. The modeling procedure described below is based
on using previously obtained computer dispersion model output in a way that
allows the user to quickly scale these results for the particular site being
assessed. The development of this modeling approach and the rationale for
selection of the core dispersion models are described in Appendix C. The
following sections discuss the procedure to be followed in transforming the
annual and worst-case emission rates determined in the previous section, to
corresponding spatial distributions of annual and worst-case respirable
particulate concentrations in the vicinity of the contamination land area.
4.2.1 Annual Average Concentration Estimates
Annual Concentration Model
A series of Industrial Source Complex - Long Term (ISCLT) model outputs
have been tabulated using averaged meteorological data for each of the seven
climatic regions shown in Figure 4-5. ISCLT is a refined model in the EPA's
UNAMAP family of models and incorporates features particularly well-suited
for wind erosion applications. A description of this model is found in Ap-
pendix C and more detail may be found in the user's guide (Bowers et al. ,
1979). Rationale for the regional delineation shown in Figure 4-5 is also
provided in Appendix C.
Four separate model outputs (annual concentration estimates) are tabu-
lated in Appendix D for each climatic region for unit emission rates.
Emissions from both wind erosion and mechanical resuspension were modeled
for each of two area source sizes: a 10 m x 10 m square and a 100 m x 100 m
square. The choice of source sizes was based on examination of a data base
of contamination sites with "actual soil contamination" (John Schaum, EPA,
personal communication, 1984). During the development of the methodology
sources larger (175 m2, 250 m2) and smaller (55 m2) than 100 m2 were also
considered; however, the resultant concentration estimates from the 10 and
100 m2 sources were found to be reasonable approximations to the concentra-
tions for the other source sizes. More specifically, for a constant emission
rate, the maximum difference in concentration estimates was < 20% at 1 km
from the source center, regardless of source size; differences decreased
rapidly beyond this point.
Although ISCLT requires that all individual area sources be squares,
it is unlikely that any contamination site will match the shape or the dimen-
sions of either area source. Because tabulated results from ISCLT are used,
the analyst is not able to use the exact source configuration in the model-
ing process. This is not believed restrictive because in most emergency
response situations, the spatial extent of the contamination (or, in other
words the size of the emitting source) will probably be difficult to estimate
The possible exception to this may be for spill incidents in which the sur-
face contaminant boundary may be well defined. It is necessary to decide
which of the two area sources better represents the site to be modeled.
41
-------
O)
OJ
OH
O
03
in
I
S-
3
en
42
-------
Although no hard and fast rules are possible, a few general guidelines are
provided below:
1. If most of the emissions emanate from a small, confined area, the
10 m x 10 m will probably better represent the site.
2. If the nearest population center lies in the direction of the pre-
vailing wind, the 10 m x 10 m will generally provide the larger
exposure estimates. Otherwise, the 100 m x 100 m will tend to
provide the higher (more conservative) estimates of exposure.
(See the discussion at the end of Section 4.2.1.)
3. If the surface contamination extends over an area of 1/2 acre or
more, the 100 m x 100 m source is more appropriate.
There are 192 receptor points at which concentration estimates may be
obtained. These points are arranged in a polar coordinate system at dis-
stances from 200 to 7000 m away from the center of the contaminated site.
The maximum distance of 7 km corresponds to the 4-mile radius used in the
Hazard Ranking System (MRS) as an indicator of the "population which may be
harmed should hazardous substances be released to the air" (Federal Register,
1982).
The receptors are grouped into "fine" and "coarse" grids as shown in
Figure 4-6.
Fine Grid Coarse Grid
32 receptors at 4 distances 160 receptors at 10 distances
(200, 300, 400, 500 m) along (750-7,000 m) along 16 directions
8 directions (N, NE,...NW radials). (N, NNE,...NNW radials).
The complete receptor network should be plotted on an overlay of scale
1:24,000. A partial receptor network of the correct scale, from which the
overlay can readily be prepared on translucent paper, is provided on page G-2
of Appendix G.
The scale of the overlay will be the same as that used in United States
Geological Survey (USGS) 7.5 min topographic map series. Thus, once the
spatial variation of concentrations has been determined and plotted, the
overlay may be placed on the USGS maps to determine populated areas exposed
to specific concentration levels. No more than six USGS maps will be re-
quired for any one site. It is suggested that response teams either main-
tain a set of maps of the areas for which they are responsible, or identify
a source from which the necessary maps are available in an emergency.
Scaling and Plotting of Results
In order to estimate annual average ambient respirable concentrations
attributable to a surface contamination site, it is necessary to first com-
plete the worksheet shown in Figure 4-7. Each data item is summarized below:
43
-------
Figure 4-6.
Portion of Receptor Network Showing
Coarse and Fine Grids
44
-------
DISPERSION MODELING WORKSHEET
Climatic Date
Region By
Checked
Source Size 10 m x 10 m
or
100 m x 100 m
ANNUAL ESTIMATES
I Annual Wind Erosion Scaling Factor, Qj
A. Annual Wind Erosion Rate, RIO = 9/s
B. Select approproate value of PR from below
Climatic Region 1234567
PD 0.152 0.262 0.396 0.288 0.182 0.134 0.296
K
RIO
C. Annual Scaling Factor, QT = = g/s
P
PR
II Annual Mechanical Resuspension Scaling Factor, QJJ
QTT = Annual Mechanical Emission Rate, RIO = 9/s
Figure 4-7. Annual Dispersion Model Worksheet
45
-------
Climatic Region - Determine according to Figure 4-5
Source Size - Estimate according to the guidelines pre-
sented in the preceeding subsection
Annual Wind
Erosion Rate - Estimate as product of emission factor
(based on the guidelines presented
in Section 4.1) and annual source extent
PR " Take value from the table on the worksheet
(Figure 4-7) for the appropriate climate
region. Pr represents the fraction of time
in the model runs that wind erosion occurs.
Q! ~ Wind erosion scaling factor.
QH " Mechanical scaling factor which equals an-
nual mechanical emission rate.
After determining Q for wind erosion and QTT for mechanical resuspen-
sion the analyst may proceed to scale the mode! output (i.e., concentra-
tions). The scaling process is represented as follows:
X = QT^T + Qnfn (4-11)
where x = respirable concentration (mass/volume)
Qj = wind erosion scaling factor (mass/time), from Figure 4-7
QJJ = mechanical resuspension scaling factor (mass/time),
from Figure 4-7
fj = unsealed concentration (time/volume) due a unit erosion rate
from Appendix D
fjj = unsealed concentration (time/volume) due to a unit mechanical
emission rate from Appendix D
The concentration units depend on the units used for the scaling factors
It is critical that Q and Qn be expressed in identical units. The most
suitable units involve SI masY units and seconds": The following is a table
ot corresponding scaling factor and concentration units.
QT and QTT Respirable Concentration
Units Units
g/s
mg/s
pg/s
ng/s
pg/s
46
-------
As can be seen from the two sets of units above and Equation 4-11, the units
for fy and fJT are us/m3. Once again, it is imperative that both scaling
factors be expressed in the same units.
The values of f, and fJT are tabulated for the two source sizes for
each climatic region in Tablei D-l through D-14 in Appendix D. For purposes
of illustration, the tables for the 10 m x 10 m source in Region 3 are repro-
duced as Figures 4-8 and 4-9. The steps involved in plotting the concentra-
tion are as follows:
1. Beginning with the fine grid and the north direction (N) multiply
the entry under 200 m for wind erosion by Qj and add that to the
product of the corresponding entry for mechanical resuspension
and QTT. Write the result next to the point 200 m to the north
of the source on the receptor grid overlay prepared by the analyst.
2. Continue with the 300, 400, and 500 m entries in the north direc-
tion.
3. Repeat the process with the NE direction and continue until all
of the fine grid has been completed.
4. Repeat the process for the coarse grid. Again starting with the
N direction, multiply corresponding entries by the appropriate
scaling factor, starting with 750 m and ending at 7000 m.
5. Repeat the process in Step 4 with the NNE, NE, etc., radials until
the coarse grid is completed.
A few remarks on the above are in order:
a. If no mechanically generated emissions are present at the site
then the analyst, of course, needs to consider only the concen-
tration field due to wind erosion.
b. A programmable calculator (or at least one with multiple memories)
is recommended to reduce the number of keystrokes (and, hence,
the chance of error).
c. If certain radials are in the direction of areas in which inhala-
tion exposure is of no concern (e.g., bodies of water, uninhabited
areas, etc.), the concentrations at those points need not be calcu-
lated.
d. If an estimated concentration falls below a lower limit of interest
in terms of inhalation exposure, the process may be shortened by
moving immediately to the innermost distance along the next radial.
Construction of Isopleths
Once the annual concentration estimates have been plotted on the 1:24,000
receptor overlay, the next step in conducting the assessment is to draw
47
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REGION 3
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE (M)
N
NE
E
SE
S
SW
W
NW
SCALING
200
8.573
2,326
2,953
5.052
5,105
1.699
1 .300
2.898
FACTOR =
300
4. 169
1.078
1 ,415
2,399
2,436
0,802
0.621
1.351
400
2.508
0.629
0.844
1.422
1 .450
0.474
0.370
0.793
500
1.685
0,415
0.564
0,947
0.968
0.315
0.247
0.524
(UNITS)
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SW
W
NW
GL * SCALING
55
17
24
22
28
18
21
29
200
.299
.769
.456
.641
,413
.987
.242
.882
28
8
12
11
14
9
10
14
RANGE
300
.003
.631
.326
,174
.143
.392
.641
,680
(M)
400
17.
5 »
7,
6.
8,
5.
6,
8.
106
135
511
727
563
655
452
796
11
3
5
4
5
3
4
5
500
.595
.419
.083
.519
.771
.799
.749
.888
FACTOR = _
(UNITS)
Figure 4-8. Unsealed Ambient Concentrations (ps/m3) - Fine Grid
48
-------
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isopleths of concentration. These isopleths indicate the spatial variation
of concentration and are used to develop estimates of population exposure
The procedure described below uses the entire concentration field obtained
by scaling the tabulated results in order to construct isopleths.
Use of a programmable calculator is especially recommended for this
procedure. Figure 4-10 presents a program for a Texas Instruments TI-55-
programs for other calculators are similar.
The equation which is solved by this program is
xt - x
d_ o u
(4-12)
Xi - XQ
where d - relative distance from receptor 0 to receptor 1 where
concentration equals \.
Lc
Xt = target concentration (i.e., concentration to which the isopleth
corresponds)
Xo - (lower) concentration value at receptor 0
Xi - (higher) concentration value at receptor 1
and Xo ^ Xt ^ Xi-
The linear interpolation given above produces a value of d between 0 and
1. If the result is not in this range, the analyst will know that an error
has occurred.
Use of this program is as follows:
1. Determine the "target" concentration value for the isopleth (e.g.,
100 ug/m3, 25 ng/m3) and store this value in memory 3.
2. Starting at north, locate the two adjacent receptors along that
direction whose concentration values bound the target value.
3. Enter the smaller concentration and start the program.
4. When the display stops (the display should be the negative of the
smaller concentration), enter the larger value and restart the
program.
5. Once the display stops flashing, the value of 0 ^ d ^ 1 is shown.
Plot this point on north radial. The value of d represents the
relative distance from receptor 0 to receptor 1. Thus a value of
0.62 implies that the isopleth intersects the radial approximately
two-thirds of the way from receptor 0 to receptor 1.
50
-------
Fiaure 4-10. Calculator Program for Isopleth Construction
51
-------
6. Continue with the next radial until all have been completed.
7. Connect the points with straight lines to form the isopleth.
8. Choose a new target value and repeat the process.
A number of remarks about the procedure follow:
a. Selection of the target values should be made in conjunction with
an examination of nearby centers of population. Clearly, if there
are no people residing within the first, say, 2 km of the site,
then there is no need to construct isopleths in the uninhabited
area in order to assess direct inhalation exposure.
b. It is not necessary to use a scale to pinpoint the location of
the isopleth; the calculator program is designed to allow the user
to roughly "eyeball" the location, by using the nearest third,
quarter, and so on.
c. Because only one source is modeled, the isopleths for different
target values should be of approximately the same geometric shape.
(See isopleths in Example One in Section 5.)
The preceding is a description of how isopleths of estimated annual
pollutant concentration can be developed using the model output results.
There are a number of situations in which the analyst may want to modify
the plotted concentration field. One possible situation might involve the
need to incorporate more site-specific, and thus presumably more realistic,
meteorological information concerning the local-scale wind flows. This is
particularly true with respect to wind direction, since it is known to be
highly variable in both time and space.
One possible modification would involve "rotation" of the initial con-
centration field so that the axis or radial of maximum concentration is
oriented parallel to the prevailing wind direction. Although rotation could
be applied separately to both wind erosion and mechanical resuspension emis-
sions, the complexity involved in combining the results is not considered
worthwhile in the rapid assessment procedure. Such a rotation should be ap-
plied only in cases in which erosion is the dominant resuspension mechanism
and only if the results of the site survey, including consultation with an
expert meteorologist, suggest that this procedure is warranted.
A second modification applicable to both the wind erosion and mechani-
cally generated concentration estimates, involves the construction of con-
centric circles (or isopleths). This may be accomplished by first scaling
the concentrations at 750 m from the site (for each direction), and then
determining the radial with the largest concentration estimates. The
remaining estimates are then calculated for each downwind distance on this
radial, and concentric isopleths may be then be drawn. The advantages of
this method are (a) it is inherently very conservative and (b) it can be
accomplished very quickly thus leaving additional time for the analyst to
refine the critical emission rate and source extent estimates. An example
of this procedure is provided in Section 5.2.
52
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4.2.2 Worst-Case Concentration Estimates
A series of VALLEY model runs have been prepared for use in the manual
in order to assess worst-case, short-term conditions. VALLEY is a screen-
ing model contained in the EPA's UNAMAP series, and is typically employed
in evaluating worst-case scenarios. The model is designed to produce con-
servatively high estimates of 24-hr average concentrations (Burt, 1977).
Although there is a short-term version of ISC, the VALLEY model was selected
for use because it requires considerably fewer site-specific assumptions
for the meteorological input. A description of VALLEY is provided in Ap-
pendix C; greater detail may be found in the user's manual (Burt, 1977).
Worst-case estimates of concentration depend on both emission rates
and meteorological conditions. It is particularly important to distinguish
between mechanically generated emissions and those attributable to wind ero-
sion in this type of analysis. Most emissions from open dust sources are
essentially independent of wind speed; maximum concentrations due to these
sources are associated with very stable atmospheric conditions and light
winds. Wind erosion, of course, is highly dependent on wind speed; however,
higher winds act to enhance dispersion and thus reduce the air quality impact.
It is important that the analyst realize that the worst case for mechanical
resuspension and that for wind erosion cannot occur simultaneously. Thus,
two separate worst-case meteorological conditions must be considered:
Wind Atmospheric
Speed Stability
Scenario Source of Emissions (m/s) Class
1 Mechanical resuspension 2.5 F
2 Mechanical resuspension and 4.3 E
wind erosion
Each scenario above was considered using the two different source sizes em-
ployed earlier. If no mechanically generated emissions are present at the
site, then only scenario 2 is considered using a zero value for the mechani-
cal resuspension rate.
Once the worst-case emission rates are available, it is a relatively
easy matter to determine which scenario produces higher ambient concentra-
tions. If the worst-case mechanical emission rate is at least one-half the
value for wind erosion, then scenario 1 will generally result in larger
estimates for worst-case concentration values.
The output of four VALLEY runs have been plotted in Figures 4-lla and b.
These figures have been reduced from the originals which are provided as
masters for map overlays, on pages G-3 and G-4 of Appendix G at the end of
this manual. These masters have a scale of 1:24,000, so that the overlays
(of the same scale) may be placed directly upon USGS 7.5 min maps. Prior
to interpretation, however, the values of the concentration isopleths must
be scaled for use at the specific site.
53
-------
f \
I \
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55
-------
Scaling of worst-case concentration estimates is considerably simpler
than that for annual estimates. The following describes the scaling process:
Scenario Scaling Factor
1 Worst-case mechanical emission rate
2 Sum of worst-case mechanical and erosion emission
rates
The earlier remarks concerning corresponding scaling factor and concentration
units and the importance of expressing the emission rates in identical units
are equally applicable here.
Thus, for a 10 m x 10 m source, if the worst-case emission rates are
17 Ib/day = 0.089 g/s (mechanical) and 12 Ib/day = 0.063 g/s (wind erosion),
the farthest isopleths in Figure 4-10 would correspond to 0.044 ug/m3 and
0.038 ug/m3 for scenarios 1 and 2, respectively. If an isopleth for a par-
ticular concentration value is required, Figure 4-12 provides a means of
quickly constructing an additional isopleth. For the example given above,
suppose the 0.5 ug/m3 isopleth is required. In scenario 1, the unsealed'
concentration corresponding to 0.5 ug/m3 for scaling factor of 0.089 g/s is
0.5 ug/m3 _ r c / , (4-13)
0.0089 g/s ~ 5'6 ^s/m3 C j
Entering Figure 4-12 at the ordinate 5.6, it is seen that, for scenario 1,
the required isopleth extends 1.8 km downwind from the source. For
scenario 2, the required unsealed concentration is
0.5 ug/m3 - q q / 3 (4-14)
(0.089 + 0.063) g/s ~ 6 MS/m
Thus, in the second scenario, the isopleth extends 1.3 km downwind. Knowing
the extent of these isopleths, the user could then draw curves going through
the point and having the same general shape as those drawn in the figures.
(See also the example problems in Section 5.0.)
Figure 4-12 may also be used to construct very conservative estimates
of worst-case concentrations. Conceivably, this could be done if the con-
taminated site is located in the middle of a populated area and thus any
wind direction would transport the contamination toward a portion of the
receptor population. In this case, downwind distances corresponding to spe-
cific (scaled) concentrations are obtained from the figure and concentric
56
-------
500
i
3.
c
o
c
-------
circles are drawn. Although such an isopleth is extremely conservative, it
does provide a rapid means of determining a maximum population potentially
exposed as a worst case and may prove useful in a screening application.
4.3 ESTIMATION OF EXPOSURE
By this point, the analyst will have maps showing annual and worst case
concentrations for the particular site being assessed. The final step in
the emergency response assessment consists of estimating levels of con-
tamination to which surrounding residents may be exposed. Direct human ex-
posure due to respirable particulate from the surface contamination site is
the primary interest in this manual.
However, users should be aware that particulate emissions can also cause
human exposure in a variety of other ways:
Deposition on soil resulting in human exposure via dermal
absorption or ingestion,
Deposition on crops or pasture lands and introduction into
the human food chain, and
Deposition on waterways, uptake through aquatic organisms,
and eventual human consumption.
In order to facilitate health effects risk calculations, exposure is
generally calculated as a daily dose rate averaged over an individual's life-
time and bodyweight:
[Contaminant 1 [Respiration] [Exposure] [Absorption]
Average Daily = [Concentration] L Rate J [.Duration] L Fraction J
Lifetime Exposure (Body Weight) (Lifetime)
(4-15)
Recommendations for how to estimate each factor in the above equation
are given below:
1. Contaminant Concentration - This is the contaminant concentration
in the air as calculated in Section 4.2 Since the exposure could
be occurring over long time periods (i.e. up to 70 yr) the user
must consider whether degradation of the contaminant at the source
could occur. The chemical and biological degradation properties
of the contaminant should be reviewed. If significant degradation
is likely to occur, exposure calculations become much more compli-
cated. In that case, source contaminant levels, resulting air
concentrations and exposure levels must be calculated at frequent
intervals and summed over the exposure period. This procedure
would be very cumbersome via the approach presented in this manual
and is really only practical via computer programs. Assuming first
order kinetics, an approximation of the degradation effects can be
achieved by multiplying the concentration by: (1-e )/(kt),
58
-------
where k = degradation rate constant (days)-1 and t = time period
over which exposure occurs (days). The k value is compound-
specific and this approach should be applied after consultation
with experts.
2. Respiration Rate - In situations where a person is exposed 24 hr/
day, a respiration rate of 23 m3/day should be used. This value
is based on Snyder et al. (1975) who report that an average adult
male spends 8 hr/day resting at a respiration rate of 7.5 1/min
and 12 hr/day engaged in light activity at a respiration rate of
20 1/min. If the exposure occurs during only a portion of the
day, the respiration rate should be reduced accordingly.
3. Exposure Duration - This is the time that exposure occurs. In a
worst case analysis assume that the exposure occurs 24 hr/day for
an entire life-time (70 year) for a total of 25,550 days. However,
this value should be adjusted to reflect site conditions such as
the behavior patterns of the exposed population. For example,
the travel habits of the exposed people and time spent indoors
versus outdoors could affect the exposure duration.
4. Absorption Fraction - This is the fraction of the contaminant
entering in the lungs which is absorbed into the body. The frac-
tion of particles which are inspired (i.e. enter the respiratory
system) depends on numerous factors such as breathing rate, parti-
cle size distribution, wind speed, and whether breathing is done
through the nose or mouth. The International Standards Organiza-
tion (1981) has estimated the inspired fraction as a function of
particle size under average conditions (Figure 4-13). The proce-
dures in this manual provide concentration estimates of the PM10
particles which are generally considered most important in estimat-
ing health effects. Virtually all of these particles will be
inspired.
However, the fate of PM10 particles after entering the lungs is
less certain. Generally, the heavier particles deposit in the
upper regions of the respiratory tract, the lighter particles in
the lower regions, and the very lightest are exhaled. Most of the
deposited particles in the upper regions and some in the lower
region are cleared by ciliary action and swallowed. Lacking
specific particle size distribution information, the fate of in-
spired particles should be assumed to follow the recommendations
of the International Commission on Radiological Protection (1968)
as given in Table 4-3.
After determining the fraction of particles swallowed, the overall
absorption fraction can be further refined on the basis of GI
tract absorption. This is a chemical specific phenomenom and must
be based on available literature.
In summary, the overall absorption fraction is calculated as
follows:
59
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60
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Absorption _ Inspired [Traction Remaining + / Fraction\ / GI Tract \|
Fraction Fraction |_ in Lungs \Swal 1 owed/ \Absorption/I (4-16)
Fraction
The inspired fraction should be assumed equal to 100% for PM10
particles; the fractions remaining in lungs and swallowed are
determined from Table 4-3; and the GI tract absorption fraction
is determined from the available literature on the specific con-
taminant.
5. Body Weight - This is generally considered equal to 70 kg which
represents an average adult male (Snyder et al., 1975). If data
are available on the exposed population which suggests that a dif-
ferent bodyweight may be more representative, this value should be
adjusted accordingly.
6. Lifetime - This is generally assumed equal to 70 years which repre-
sents an average U.S. male.
TABLE 4-3. DISTRIBUTION OF INSPIRED PARTICLES
Readily soluble Other
compounds compounds
Exhaled 25 25
Deposited in upper respiratory
passages and subsequently
swallowed 50 50
Deposited in the lungs (lower
respiratory passages) 25a 25b
This is taken up into the body.
Of this, half is eliminated from the lungs and swallowed in the first
24 hr, making a total of 62.5% swallowed. The remaining 12.5% is re-
tained in the lungs with a half-life of 120 days, it being assumed
that this portion is taken up into the body fluids.
Source: International Commission on Radiological Protection, 1968.
61
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Exposures can be calculated on the basis of the annual concentration
estimates from Section 4.2, using the model just presented. A different
model would be necessary to calculate acute exposure from the worst-case
concentration field. The exposure estimates can be used to estimate risk on
the basis of the toxicological properties of the contaminants. However, the
details on how to calculate risks are beyond the scope of this manual.
After exposure estimates are completed, they can be plotted and isopleths
constructed as done for the concentration estimates.
The isopleths for annual exposure obtained in the preceding section are
now used to assess direct exposure to people living in the vicinity of the
contamination site. Because the isopleths are drawn on a 1:24,000 map scale,
they may be overlaid directly onto USGS maps. Because the USGS topographic
maps indicate populated areas, it is an easy matter to identify populated
areas exposed to certain concentration levels. It is more difficult, how-
ever, to determine the number of residents contained within these isopleths;
the techniques used to estimate population by receptor area will largely
depend on the location of the site.
For example, if the contamination site is located in a sparsely popu-
lated area, then the USGS maps will show individual buildings. Consultation
with knowledgeable officials (such as the sheriff, county agent, county clerk,
local utility personnel, etc.) should result in reliable estimates of popula-
tion. Should it not prove feasible to consult with other personnel because
of time constraints or inaccessibility, a default value of 3.8 persons per
dwelling may be used in conjunction with the USGS maps (or, possibly, aerial
photgraphs). A standard road atlas or a state highway map with populations
listed may also prove valuable.
On the other hand, if the site is located near a densely populated area,
then other means of estimating population are available. In this instance,
authorities of the type discussed above may again be consulted. In addition,
a greater amount of Bureau of the Census data may be available to the user.
The smallest statistical units reported by the Bureau are block groups,
enumeration districts, and census tracts. Complete-count statistics are
available for areas as small as a city block. Additional sources of infor-
mation include the Federal Emergency Management Agency (FEMA), municipal
libraries, assessor offices, and election boards. A readily available
technique for estimates in this type of area would be to assume a uniform
density for the town or city in question, and then multiply the population
(taken from a road atlas) by the fraction of the town contained in the
isopleth.
It is recommended that response personnel contact the appropriate
regional offices of the Bureau of the Census (Table 4-4) well in advance of
an emergency in order to identify the types of data generally available and
to establish a means of rapidly obtaining information (especially during
evenings and weekends).
It is clear that no fixed set of rules may be followed to obtain popu-
lation estimates. For example, a contaminated site might be located at the
edge of a town. In this case, it may be necessary to employ different
62
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techniques for the urban and rural areas. By using a road atlas as well as
the 3.8 persons per residence assumption, it is possible to obtain rapid
estimates of population within isopleths without outside consultation. It
is strongly recommended, however, that outside help be sought if possible
and at a very early stage of the assessment procedure. Because population
estimates for smaller areas surrounding the contamination site may be de-
veloped independently of the emission/concentration estimation process, it
is quite possible to have a well-defined population field at the time when
direct exposure is assessed.
TABLE 4-4. CENSUS BUREAU REGIONAL OFFICES -
INFORMATION SERVICES
Atlanta, GA 404/881-2274
Boston, MA 617/223-0026
Charlotte, NC 704/371-6144
Chicago, IL 312/353-0980
Dallas, TX 214/767-0625
Denver, CO 303/234-5825
Detroit, MI 313/226-4675
Kansas City, KS 913/236-3731
Los Angeles, CA 213/209-6612
New York, NY 212/264-4730
Philadelphia, PA 215/597-8313
Seattle, WA 206/442-7080
4.4 ASSUMPTIONS, LIMITATIONS, AND PARAMETER SENSITIVITY
4-4.1 Assumptions and Limitations of the Assessment Procedure
The assumptions inherent in the Gaussian dispersion model as applied
here are as follows:
a. There is no diffusion in the direction of the wind.
b. There is no variation in meteorology between the source and receptor
c. Ground level concentrations are estimated assuming that there is
no deposition or reaction at the ground surface.
The above are basic assumptions of the Gaussian algorithm. Assumptions
specific to the particular problem at hand are:
a. Only particulate less than 10 urn are considered.
b. All sources are modeled as either 10 m or 100 m side squares.
These source sizes were chosen after discussion with EPA on NPL
sites and consideration of sources of different sizes.
63
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c. The meteorology at the site may be adequately represented using
average climatological data from the climatic regions.
d. The emissions are uniformly distributed over the area source.
The assumptions specific to the problem are not considered to be too
restrictive in light of the emergency response. The intent in this phase
of the manual was to provide a means of quickly obtaining estimates of
ambient concentrations with accuracy similar to that associated with UNAMAP
models.
The accuracy of estimates obtained by Gaussian dispersion models is
often expressed as a factor of two (i.e., +100%, - 50%) for flat terrain.
There are several factors (dispersion in complex terrain, for example) how-
ever, that may significantly affect the accuracy of the model estimates.
No attempt has been made in this manual to include these complexities because
of their very site-specific nature. The modeling approach adopted here is,
in many ways, quite similar to that which might be used by a regulatory
agency in screening potential air quality impacts.
Assumptions related to the direct exposure analysis are:
a. The indoor contaminant concentration is identical to the ambient
concentration.
b. Only residents are considered in determining the exposed popula-
tion.
Neither of the above assumptions are deemed restrictive in light of
the emergency. It should be noted that HRS counts transients such as workers
in factories, offices, restaurants, motels, and students in addition to
residents. The manual does not consider these potentially exposed persons
because their inclusion would require either canvassing or consultation with
knowledgeable officials. Because of the time involved in this process,
these transients are excluded in conducting the 24-hr assessment. Should
additional time or personnel be available during the emergency response,
inclusion of transients may be accomplished using the above methods.
The most restrictive assumptions in the assessment process are related
to the emission rates:
a. The level of contamination in potentially airborne particle size
range is identical to that in the bulk material.
b. Vehicular traffic is the only mechanical resuspension process
considered.
c. The Rayleigh distribution provides an acceptable fit to the annual
wind speed distribution at a given site.
64
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There is evidence to suspect that smaller particles may contain higher
levels of contamination than larger ones. This is obviously the case if
the contaminant adheres to the surface of an individual particle; because
of their greater surface to mass ratio, these smaller particles have greater
contamination level (on a mass basis) than does the bulk material as a whole
it is strongly recommended that a contamination level be determined for silt
sample of the surface because the silt represents the portion of the surface
material that may become airborne.
Vehicular traffic on unpaved surfaces easily represents the largest
open dust source in most industrial settings. Because materials handling
operations are generally accomplished by a good deal of vehicular traffic
it is mostly likely that any other source of mechanical resuspension would
be considerably less than that due to traffic.
4.4.2 Sensitivity of the Solution
The concentration estimates obtained in Sections 4.2 are the product
of numerous prior calculations. Because the estimated concentration field
is essentially the final result of the assessment, it is important to realize
how the pieces fit together" and what effect a change in one of the param-
eters has on the final results.
The single most important piece of information in the procedure is a
the level of contamination. This parameter influences all subsequent cal-'
culations. The effect of a on all the calculations is linear; that is
if a is estimated 50% too low, then the resulting emission/erosion rates
and the concentrations will all be 50% low, assuming that all other parame-
ters are correct. This is the only parameter which is capable by itself of
affecting the entire assessment process in such a manner. As noted in the
section above, it is strongly suggested that the contamination level be
determined for a silt sample if at all possible.
The concentration field is also highly dependent on the emission factors
and source extent calculations, because the results are employed in the scal-
ing process. The collection of relevant, site-specific data with which to
estimate the necessary parameters may easily present the greatest limitation
in the procedure. It is strongly recommended that prior to the scaling of
the dispersion model results, users perform a sensitivity analysis in order
to assess the impact of parameter variation.
It is important to note that, once the site is located in a climatic
region and erosion/emission rates are calculated, the resulting concentration
field is then predetermined. This is due to the fact that previously ob-
tained computer model output is used to generate the field. Of course this
procedure will not allow the user to vary the meteorological input and this
will make it difficult to assess the uncertainties associated with the aver-
age meteorological input for given emergency response situations. Although
this is something of a limitation, the intent in preparing the manual was to
UK^M. the USer with a means of 9uickly obtaining dispersion estimates of
UNAMAP quality. During the manual preparation period, alternative approaches
were evaluated. The approach adopted here represents a condensed form of a
typical screening process employed by a regulatory agency.
65
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The use of regional climatologies in the modeling process serves to
emphasize the large-scale meteorology in describing the near surface wind
field for the site. The common practice of employing a STAR deck recorded
tens of miles away may emphasize small-scale differences at the recording
station. Thus, in the absence of climatological data recorded at the con-
tamination site, it is believed that the regional climatologies employed
better represent the meteorology, especially in the case of wind erosion
(which is potentially present at all sites), because wind speeds of this
magnitude are typically associated with passage of large-scale frontal
systems.
To summarize, numerous assumptions have been made in developing the
assessment procedure. In many cases, the "presolved" nature of the procedure
does not allow the analyst the flexibility of modifying these basic assump-
tions. Table 4-5, however, provides a quantitative evaluation of parameter
variability on emission rates as well as a qualitative evaluation of the
expected sensitivity of the overall results to input parameters that the
analyst may choose to vary in the course of conducting an emergency response
assessment. The table is intended primarily as guidance for the response
team in deciding how to best allocate data collection resources so as to
obtain the most reliable concentration estimates within the 24 hr time frame.
66
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TABLE 4-5. SENSITIVITY ANALYSIS GUIDELINES
Influence on Emission Ratesc
Un- Overall
a Inherent , Limited limited Effect gn
Parameter Variability Mechanical Erosion Erosion Results3
Contamination
Level
Contamination
Area (or,,
Travel Length
Contaminated)
Traffic
Volume
Threshold Wind
Speed
Vegetative Cover
Sparse (< 20%)
Dense (> 80%)
Frequency of
Disturbance
M
M
10%
10%
10%
10%
10%
N/A
N/A
-10%
10%
10%
N/A
-20%'
C-M
C-M
N/A -2.5% to 0%f -2.5% to 0%f L
N/A <-40%g <-40%g C
N/A 10% N/A M
51 It
Vehicle Speed
Vehicle Weight
Wheels
M-L
L
M-L
L
10% N/A
8% N/A
3% N/A
12% N/A
N/A
N/A
N/A
N/A
M
M-L
L
M
Average climatological variables given in tables or figures not con-
sidered.
H = Highly variable; M - moderately variable; L = little variability
Values given represent percent change when parameter is increased 10%
C = critical, M = moderate; L = low
Change highly dependent on original estimate of u,. Example value is
based on u = 10 m/s, [u] - 5 m/s. t
Decrease of less than 2.5%
Decrease of more than 40%.
67
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-------
SECTION 5
EXAMPLE APPLICATIONS
5.1 EXAMPLE ONE
This example illustrates the use of the emergency response assessment
manual. The hypothetical site is located in Climatic Region 3 and the near-
est NWS station in Table 4-1 is North Platte, Nebraska.
The site survey indicated that the contamination extended approximately
6 in. below the surface and that the soil itself consisted of finely divided
material. Furthermore, the contaminated surface was essentially unvegetated
with no nonerodible elements and no evidence of crusting. Thus, the surface
was characterized as one of unlimited wind erosion potential. Because no
evidence of traffic (e.g., tire tracks, ruts, etc.) was found during the
survey, the resuspension mechanisms were considered to be limited to wind
erosion only. Finally, a contamination level (a) of 6.4 ppm in the bulk
surface material had triggered the emergency response assessment.
A sketch of the site was also made during the survey, and is shown in
Figure 5-1. The site is located in a sparsely settled area in a large valley
oriented from SW to NE. Information obtained from the county sheriff and
the county agent indicates that the only residents within a 7 km (4 mi)
radius are the Loner family, whose farm is approximately 2 km NW of the site
and residents of a mobile home park roughly 3 km to the NE.
The on-site coordinator (OSC) has decided that an emergency response
assessment for both worst-case and annual conditions must be carried out
within 24 hr. Using the guidelines presented in Section 4, the following
are determined.
1. Because the source covers more than 1/2 acre, the 100 m x 100 m
source representation is selected. The area of the source is
150 m x 300 m = 45,000 m2.
2. Based on the particle size mode of 500 urn obtained from a hand
sieving test of the surface material, Figure 3-4 is used to esti-
mate a wind erosion threshold friction velocity of 50 cm/s.
3. Using a ZQ value of 2 cm (value in Figure 3-5 for grassland which
characterizes most of the surrounding area), the equivalent 7 m
threshold wind speed is found (using Figure 4-1) to be
15 (50 cm/s) =7.5 m/s
69
-------
I
$
<4j -
-^
1 £
^
S.
^
^>
^
^
^
v^ .
O)
E
O
QJ
Q.
E
o»
oo
o
CU
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OJ
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-------
4. Because the threshold friction velocity is less than 75 cm/s, the
"unlimited reservoir" emission model for wind erosion (Section
4.1.2) is used. From the data for North Platte in Table 4-1, the
mean annual wind speed is 4.6 m/s. Thus,
x = 0.886 (7.5 m/s)/(4.6 m/s) = 1.4
and from Figure 4-3,
F(1.4) = 1.0
Thus, Equation 4-4 gives an annual average PM10 emission factor of
E1Q = 0.036 (4.6/7.5)3 F(x) = 0.0083 g/hr/m2
5. The annual average PM10 emission rate is found by multiplying the
area by the emission factor
(45,000 m2) (0.0083 g/hr/m2) = 370 g/hr = 0.10 g/s
The annual emission rate of the contaminant in the form of PM10 is
6.4 (10"6) (0.10) = 0.67 ug/s
using a = 6.4 ppm.
6. For worst-case 24-hr conditions, Equation 4-6 gives
[ufi_h 1 = [u+] - 2 m/s
= 27.7 -2
= 25.7 m/s
using the data for North Platte in Table 4-1. Thus, by Equation 4-5
the PM10 emission factor is '
EIQ = 0.036 (25.7)3 = 610 g/nr/m2
The corresponding contaminant emission rate is
6.4 (10"6) (610 g/hr/m2) (45,000) = 180 g/hr - 49 mg/s
As an additional step in the procedure, the analyst must consider
whether or not "rotation" of the annual concentration field is appropriate
Rotation of the field implies that one should orient the axis of maximum
concentration parallel to the direction of prevailing winds for the site in
question. This should be done if it appears that channeling of the wind
flow by topographic features (including buildings) would be likely This
should be considered after consulting people living in the area and an ex-
pert meteorologist familiar with local wind conditions. Because the valley
in this example problem is relatively shallow, no rotation was deemed
necessary.
71
-------
Annual Estimates
The annual dispersion modeling worksheet is next completed as shown in
Figure 5-2. Because only wind erosion is present at the site, only the upper
portion of Figure 5-2 is used in estimating the concentration field. Also,
because all population within the 7 km radius is within 3 km and north of
the site, only the receptors in this area are considered. The results of
the scaling are shown in Figure 5-3. Note that the concentrations are in
units of pg/m3.
Isopleths drawn using the data of Figure 5-3 are shown superimposed on
the sketch of the site in Figure 5-4. From this figure, it may be seen that
the seven members of the Loner family are exposed to annual ambient concen-
tration of ~ 0.125 pg/m3.
Using the method outlined in Section 4.3, the average daily lifetime
exposure (ADLE) may be calculated using the pertinent parameters given in
Table 5-1.
TABLE 5-1. VALUES TO COMPUTE AVERAGE DAILY LIFETIME
EXPOSURE (ADLE)
Parameter
Value
Respiration rate
Exposure duration
Inspired fraction
Fraction remaining in lungs
Fraction swallowed
GI tract absorption fraction
Body weight
Life time
23 m3/day
70 yr
100% (10 urn or less)
12.5%
62.5%
100%
70 kg
70 yr
All the above are based on the parameter estimation guidelines presented in
Section 4.3, with the exception of GI tract absorption which has been set
equal to its most conservative value. Using the above, Equation 4-15
estimates ADLE at the Loner farm as 0.031 pg/kg-day, corresponding to the
airborne contaminant concentration of 0.125 pg/m3.
Worst Case Estimates
Using the worst-case emission factor of 49 mg/s and the curve for Sce-
nario 2 in Figure 4-12,it is seen that at 3 km, the estimated contaminant
concentration is
(49 mg/s) (0.8 ps/m3) = 39 ng/m3
72
-------
DISPERSION MODELING WORKSHEET
Climatic _ Date
Region __%^5___ By
Checked
Source Size 10 rn x 10 m
or
100 m x 100 m _
ANNUAL ESTIMATES
I Annual Wind Erosion Scaling Factor, QT
A. Annual Wind Erosion Rate, R10 = _ ^* (* r X^C 9/s
B. Select approproate value of PD from below
K
Climatic Region 1234567
PR 0.152 0.262 0.396 0.288 0.182 0.134 0.296
RIO /
C. Annual Scaling Factor, QT = - = _ /•
II Annual Mechanical Resuspension Scaling Factor, QTT
QJJ = Annual Mechanical Emission Rate, R10 = _ /UrJ* 9/s
Figure 5-2. Completed Worksheet for Hypothetical
Site (Example One)
73
-------
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75
-------
The isopleths from Figure 4-11 are shown superimposed on the sketch in
Figure 5-5. The worst-case isopleths are aimed at the mobile home park be-
cause more people reside at this location in comparison to the Loner farm
house which is approximately the same distance from the source. Additional
isopleths may be drawn using the technique discussed in the text.
5.2 EXAMPLE TWO
The hypothetical site in this example is located in Climatic Region 4
and the nearest NWS station in Table 4-1 is Grand Rapids, Michigan. The
contamination level is 100,000 ppm.
The source is located approximately halfway between Extown (population
1,500) and the Point, a peninsula extending into Lake Extown. The lake
itself is fairly large, and all populated areas within 7 km lie in the sec-
tor south to southwest from the source, as shown in Figure 5-6.
Details of the contamination are sketchy, but roughly 1/5 acre appears
to have been contaminated (Figure 5-7). However, approximately 80% of the
area is covered by continuous vegetation, with the only unvegetated portion
of contaminated area consisting of a 100-ft length of an unpaved road 15 ft
wide. This road is fairly well traveled (approximately 2,000 round trips
per month).
A hand sieving procedure showed that the mode of distribution was ap-
proximately 6 mm. The threshold friction velocity is thus approximately
150 cm/s (from Figure 3-4) or 22 m/s at 7 m (Figure 4-1), assuming a rough-
ness height of 2 cjn (value for grassland in Figure 3-6). Because this value
is greater than u for Grand Rapids, only road emissions were considered in
the modeling process.
Discussion with the sheriff confirmed the 2,000 round trip figure and
also yielded the following traffic parameters:
Average vehicle speed = 20 mph = 32 kph
Average vehicle weight = 3 tons = 2.7 mg
Average no. wheels = 4
Using Equation 4-7 with a silt value of 10% and p=140 (taken from Figure 4-4)
yields an annual average PM10 emission factor of
0_305JgL
VKT
76
-------
-M
O
Q.
CU
o
O
oo
§•
77
LO
I
un
0)
s-
-------
LAKE
LAKE
1 km
0
1 mil
1 km
1 mil
Figure 5-6. Sketch of the Hypothetical Site (Example Two)
78
-------
To
OF
CONTAM /AM T/OM
GRASSLAND ^*v
To
Figure 5-7. Sketch of Contaminated Area (Example Two)
79
-------
The annual source extent is
2 000 round tri'Ps . 2 vehicles . 100 ft . 1 mile 12 month
month round trip vehicle * 5280 ft * year
on 910_veh-mile/year = 1,460 veh-km/yr. Thus for a = 0.1 the annual average
contaminant emission rate is
0.1 • 0.305 . i>460 = 44.5 kg/yr = IA mg/s
The resulting annual average concentration estimates are in units of
H12 . Hi _ ng
3 3
m m
For worst-case emissions, the OSC has determined to consider a dry day
(p - 0) with a total vehicle count of 500 round trips. Thus, the worst-case
PM10 emission factor (from Equation 4-7) is
-2 = 0.494 kg/VKT
24J 7
The corresponding worst-case contaminant emission rate (from Equation 2-1) is
" (0.494 M_) (ieh) (m^- (»* = 15.0 kg/day = 0.017 g/s
Thus, the worst-case scaling factor is 0.017 g/s (as seen from the table on
page 56) and resulting concentration estimates are in units of jjg/m3.
A conservative annual average concentration field (as discussed at the
end of Section 4.2.1) was obtained by scaling the radial for Region 4 with
the largest unsealed concentration estimates (i.e., north, from the tables
on pages D-15 and D-16) and then constructing concentric isopleths. Because
the actual emitting area is fairly small, the 10m x 10m source was used.
The result is shown as Figure 5-8.
Using the same assumptions for the ADLE calculation as in the preceding
example, the following values result:
Annual Fraction of town
average concentration within isopleth ADLE
(ng/m3) (%) (ng/kg-day)
4.5 1 L!
3-5 7 0.86
2-5 17 0.62
!-75 32 0.43
!-25 43 0.31
Thus, approximately 100 persons (7% of the population) have an ADLE value of
0.86 ng/kg-day, for example. This estimate assumes that population fs uni-
formly distributed over the town's area.
80
-------
NORTH
1 km
0
1 km
1 mil
0
1 mile
Figure 5-8. Conservative Annual Concentration Isopleths for
Hypothetical Site (Example Two)
81
-------
The worst-case 24-hr concentrations are plotted in Figure 5-9.
Figure 4-12 was used to construct these isopleths. Note that a value of
0.03 pg/m3 was conservatively assumed for portions of the town outside the
lowest isopleth shown in Figure 5-9.
82
-------
LAKE*
COKTC CMTI? AT tOfO
1 km
1 km
1 mil
0
1 mile
Figure 5-9. Worst-Case Concentration Isopleths for
Hypothetical Site (Example Two)
83
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SECTION 6
REFERENCES
Abramowitz, M. and I. A.
Dover Publications.
Stegun. 1972.
New York.
Handbook of Mathematical Functions.
AMS. 1981. Air Quality Modeling and the Clean Air Act: Recommendations to
EPA on Dispersion Modeling for Regulatory Applications. American
Meteorological Society, Boston, MA. NTIS, PB83-106237.
AMS. 1978. Accuracy of Dispersion Models: A Position
Committee on Atmospheric Turbulence and Diffusion.
American Meteorological Society, 59(8):1025-26.
Paper of the AMS
Bulletin of the
Battene PNL. 1982. EPA Field Guide for Scientific Support Activities Asso-
ciated with Superfund Emergency Response. U.S. EPA Office of Emergency
and Remedial Response, Washington, D.C. and Environmental Research
Laboratory, Corvallis, OR. EPA-600/8-82-025.
Bisal, F. and W. Ferguson. 1970. Effect of Nonerodible Aggregates and
Wheat Stubble on Initiation of Soil Drifting. Canadian Journal of
Soil Science, 50:31-34.
Bowers, J. F., J. R. Bjorklund and C. S. Cheney. 1979. Industrial Source
Complex (ISC) Dispersion Model User's Guide. U.S. EPA, Research
Triangle Park, NC. EPA-450/4-79-030.
Burt, E. W. 1977. Valley Model User's Guide. U.S. EPA, Research Triangle
Park, NC. EPA-450/2-77-018.
Chepil, W. S. 1952. Improved Rotary Sieve for Measuring State and Stabil-
ity of Dry Soil Structure. Soil Science Society of America Proceedings,
16:113-117.
Commerce Department.
D.C.
1968. Climatic Atlas of the United States, Washington,
Cortis, R. B.
Velocity
A. B. Sigl, and J. Klein. 1978. Probability Models of Wind
Magnitude and Persistence. Solar Energy, 20(5):483-493.
Coty, U.A., A. Court, and J. W. Reed. 1975. United States Wind Speed and
Wind Power Duration Tables, By Months (Cumulative Distributions). U.S.
Energy Research and Development Administration, Washington, D.C.
SAN/1075-2, Scientific Report No. 1.
85
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Cowherd, C. 1983. A New Approach for Estimating Wind-Generated Emissions
from Storage Piles. Proceedings of the APCA Specialty Conference on
Fugitive Dust Issues in the Coal Use Cycle, April 1983. Pittsburgh, PA.
Cowherd, C. and C. Guenther. 1976. Development of a Methodology and Emis-
sion Inventory for Fugitive Dust for the Regional Air Pollution Study.
Prepared for U.S. EPA, Office of Air and Waste Management, Office of
Air Quality Planning and Standards, Research Triangle Park, NC.
EPA-450/3-76-003.
Donigian, A. S. , T. Y. R. Lo, and E. W. Shanahan. 1983. Rapid Assessment
of Potential Ground-Water Contamination Under Emergency Response Condi-
tions. U.S. EPA, Office of Health and Environmental Assessment,
Washington, D.C.
EPA. 1983. Compilation of Air Pollution Emission Factors (Supplement
No. 14), AP-42. Office of Air Quality Planning and Standards, Research
Triangle Park, NC.
EPA. 1981. Evaluation Guidelines for Toxic Air Emissions from Land Dis-
posal Facilities. U.S. EPA, Office of Solid Waste, Washington, D.C.
EPA. 1980. Guidelines and Methodology for the Preparation of Health Effect
Assessment Chapters of the Ambient Water Quality Criteria Documents.
U.S. EPA, Environmental Criteria and Assessment Office, Cincinnati, OH.
Dynamac, Inc. 1983. Methods of Assessing Exposure to Windblown Particulates
U.S. EPA. Washington, D.C. EPA-600/4-83-007.
Federal Register. 1984. Proposed Revisions to the National Ambient Air
Quality Standards for Particulate Matter. March 20, 1984 (40 CFR 50).
Federal Register. 1982. National Oil and Hazardous Substances Contingency
Plan. July 16, 1982. (47 FR 31219).
Federal Register. 1981. RCRA List of Hazardous Wastes. (40 CFR 261 31
261.32, 261.33). ' '
Gillette, D. A., J. Adams, D. Muhs, and R. Kihl. 1982. Threshold friction
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9003-9015.
Gillette, D. A. 1981. Production of dust that may be carried great dis-
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Gillette, D. A., et al. 1980. Threshold Velocities for Input of Soil Parti-
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86
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Harman, H. H. 1967. Modern Factor Analysis. 3rd Edition (Rev.), University
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Hennessey, J. P. 1977. Some Aspects of Wind Power Statistics. Journal of
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Holzworth, G. C. 1972. Mixing Heights, Wind Speeds, and Potential for
Urban Air Pollution Throughout the Contiguous United States. U.S. EPA,
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International Standards Organization (ISO). 1981. Recommendations on Size
Definitions for Particle Sampling. Report of Ad Hoc Working Group to
Technical Committee 146 - Air Quality, ISO. American Industrial
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Marshall, J. 1971. Drag Measurements in Roughness Arrays of Varying Density
and Distribution. Agricultural Meteorology, 8:269-292.
McCormick, R. A., and G. C. Holzworth. 1976. Air Pollution Climatology in
Air Pollution (3rd ed.), Vol. I, Air Pollutants, Their Transformation
and Transport, A. C. Stein (ed), Academic Press, New York.
Snyder, W. S., M. J. Cook, E. S. Nasset, L. R. Karhausen, G. Parry Howells,
and I. H. Tipton. 1975. Report of the Task Group on Reference Manual.
International Commission of Radiological Protection No. 23. Pergamon
Press, New York.
Turner, D. G. 1970. Workbook of Atmospheric Dispersion Estimates. AP-26.
U.S. EPA, Office of Air Programs, Research Triangle Park, NC.
Turner, D. B. 1961. Relationships Between 24-Hour Mean Air Quality Measure-
ments and Meteorological Factors in Nashville, Tennessee. Journal of
the Air Pollution Control Association, 11(10):483-488.
Versar, Inc. 1983. Superfund Feasibility Study Manual: Source Release,
Environmental Fate, Exposed Population, and Integrated Exposure Analy-
ses. Preliminary Draft. U.S. EPA, Exposure Evaluation Division,
Office of Toxic Substances, Washington, D.C.
Wentsel, R. S. , et al. 1981. Restoring Hazardous Spill - Damaged Areas.
U.S. EPA, Office of Research and Development, Cincinnati, OH. EPA-600/
2-81-208.
WMO. 1961.. Applications of Climatological Analysis. Technical Paper
44, Supplement No. 5. Geneva, Switzerland.
87
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APPENDIX A
PHOTOGRAPHS OF NONERODIBLE ELEMENT DISTRIBUTIONS
A-l
-------
This Appendix presents a series of photographs of nonerodible element
distributions along with the associated multipliers for correcting the thresh-
old friction velocity (u* ) determined only for the erodible material The
non-erodible elements are generally larger than about 1 cm in equivalent
physical diameter. The appearance of the contaminated surface in question
should be compared to the photographs for the purpose of determining the
appropriate correction factor.
The correction factors for the subsequent figures are as follows:
Figure A-l No correction. |_ < 10~3
c
Figure A-2 (u*t} corrected = 2 L ~ 0.01
(u*t) uncorrected c
Figure A-3 (u*t} corrected = 5 L ~ 0 1
(u*t) uncorrected c
The remaining photographs illustrate the appearance of dusted surfaces
and a surface protected by dried vegetation. Figure A-4 shows a dusted sur-
face covered with an appreciable amount of both erodible and nonerodible
particles. Figure A-5 shows a dusted surface with a negligible reservoir
of loose erodible material; the quarter coin in the photograph indicates
approximate scale. Figure A-6 shows a surface that is well protected by
dried vegetation, rendering the surface nonerodible; the white square in
the photograph is of 1 mx 1 m inside dimensions.
A-2
-------
- ;-~^ vy,.* * -. >-r"- ^>z?"\3£*;$*£^ •;•*^v/% . * *^,#>. — ^ ",
V. ^^-5 r.-^ , *-r ^;;^V^ sr>' f^^If^*-- -'" - - - i :• ' ; /";\ ^ * •' ; '. * .
!*~ **t \ir *'"'^*o>^-'*- * -^'»*** * '**«-.''*vAic^"1* ^". **« V ~%^* ^* *; r ***», *- jvf-f^**\ <^- « "^ Vr <• > •• "-,/W ,v *<* * v * ,^ ^ ,-
Centimeters
0
1
1
0
2
1 '
1
}
4 6
1 ' 1
1
2
Inches
A-3
8
1
I
3
10
1 1
I
4
-------
Figure A-2
-------
Figure A-3
-------
-------
A-7
-------
-------
APPENDIX B
FUNCTION NEEDED FOR UNLIMITED EROSION MODEL
B-l
-------
The integral
t) = / freq
ut
£i1n ™rreSresnentesmaSnSe°nS ^ SUrfaC6S with unll'mited erosion
([u], ut) = ([u])3 F(x)
where
^-=0.886
2 [u] [U]
F(x) = function plotted in Figure 4-4.
*?tpbm™ hrelationshl'P Assumes that the wind speed distribution for
site may be represented by a Rayleigh distribution
freq (u) = 5 JL exp (_/t jj*
2 [u]2 4 [u]2
^ Thi "•Uf"8 v""- °f
lim F(x) = = 1.91
x -» o
Furthermore, for values of x greater than 2, F(x) may be approximated by
F(x) = 0.18 (8x3 + 12x) exp (- x2)
B-2
-------
APPENDIX C
ATMOSPHERIC DISPERSION MODELS
AND METEOROLOGICAL INPUT DATA
C-l
-------
C.I ATMOSPHERIC DISPERSION MODELS
Air quality models may be divided into two broad categories: (a) sta-
tistical models, and (b) simulation models. Statistical models differ from
simulation models in that they require actual atmospheric monitoring data
and do not attempt to explicitly describe the physical processes involved
in pollutant dispersion. Instead, relationships between measured pollutant
concentrations and various meteorlogical and source parameters are deter-
mined empirically through statistical techniques.
Simulation models, commonly referred to as "dispersion" models, attempt
to simulate the physical processes of the transport and dilution of airborne
pollutants. The principal requirements are source emission rates and mete-
orlogical input consisting of wind speed, direction, and atmospheric stabil-
ity. The model then predicts time-averaged concentrations at specific loca-
tions for these emission rates, based on mathematical relationships using
empirical data corresponding to the particular meteorlogical condition. It
is important to realize that this type of model does not attempt to describe
instantaneous conditions but rather time-averaged conditions. Because they
are developed in terms of fundamental physical principles of general appli-
cability, simulation models have the important property of being transferable
from one location to another and thus, are much more applicable in the
present analysis.
The fundamental dispersion equation for a ground level point emission
source with no plume rise is
where
X = concentration (mass/volume)
Q = emission rate (mass/time)
CTy»CTz = horizontal and vertical dispersion coefficients,
respectively (length)
u = wind speed (length/time)
x = downwind coordinate (length)
y,z = horizontal and vertical coordinates, respectively (length)
The dispersion coefficients are empirical functions of x and stability class
Furthermore, for area sources of the type considered in this manual, a
"virtual point" source may be used in the modeling process. This type of
source has a non-zero initial (i.e., at x=0) horizontal dispersion coeffi-
cient. A virtual distance x is found by determining the distance downwind
from^point source at whichya equals the initial value for the appropriate
stability class. Subsequent horizontal dispersion coefficients are deter-
mined as a function of x + x (Turner, 1970).
The basic assumptions underlying this model are: (a) the plume spread
follows a Gaussian distribution (which accounts for the term "Gaussian dis-
persion model"); (b) the emission rate is uniformly distributed over the
C-2
-------
source and is continuous; (c) meteorlogical conditions remain constant be-
tween the source at the coordinate origin and the receptor point (x,y,z);
and (d) no deposition or reaction occurs at the ground surface.
Because of the large number of source-receptor combinations in a typi-
cal application, many computerized dispersion models have been developed
over the years. The most important air quality models are those approved
by the EPA and included in its User's Network for Applied Modeling of Air
Pollution (UNAMAP) series. Both models selected for inclusion in this man-
ual are members of the UNAMAP family. All are based on the assumptions de-
scribed above. The differences between models are mostly due to variations
in the treatment of: (a) plume rise, (b) pollutant half-life, (c) diffusion
limitations due to mixing heights, (d) source configurations, and (e) dis-
persion coefficients to characterize plume growth.
C.2 MODEL ACCURACY/LIMITATIONS
Three major factors influence the accuracy of air quality simulation
models (AMS, 1981; AMS, 1978). These are: (a) the capability of the algo-
rithms to reproduce the important physical and chemical processes; (b) the
quality of the emission data; and (c) the quality or appropriateness of the
meteorlogical data. The overall accuracy of the Gaussian dispersion model
will be dependent upon the specific application.
The Gaussian model will perform best under the conditions used to form
the basis for the current models. These conditions include:
Source: Low-level, continuous, nonbuoyant emission, in simple terrain.
Meteorology: Near neutral stability, steady and relatively homogeneous
wind field.
Estimate: Local, short-term, concentrations of inert pollutants.
Under these relatively simple conditions, "factor of two" agreement
between predicted and observed concentrations is probably realistic. This
estimate of accuracy assumes that the controlling meteorlogical parameters
are measured on-site, an assumption that in many practical applications is
not valid. At present, routine dispersion modeling applications often rely
on ground-level observations taken hourly at NWS airport sites. These obser-
vations are intended primarily for aviation needs.
With a complete range of meteorlogical measurements and correspondingly
accurate emission data, true concentrations for the simple dispersion case
can probably be estimated to within ± 40% (AMS, 1978). Addition of compli-
cating features will substantially increase the uncertainties. Such fea-
tures include:
1. Aerodynamic wake flows of all kinds.
2. Buoyant fluid flows and accidental releases of heavy toxic gases.
C-3
-------
3. Flows over surfaces markedly different from those represented in
the basic experiments, e.g., forests, cities, water, rough ter-
rain.
4. Dispersion in extremely stable and unstable conditions.
5. Dispersion at great downwind distances (> 10 to 20 km).
No estimates of accuracy are available for cases where the basic point
source model is extended (with modifications) to the prediction of dispersion
from large area sources, or for long-term average dispersion. However, it
is generally accepted that more confidence can be placed in long-term pre-
dicted concentrations than in short-term predictions of worst-case impacts
(EPA, 1980).
C.3 DESCRIPTION OF MODELS USED IN MANUAL
Several hand calculation algorithms based on Gaussian dispersion equa-
tions have been proposed for use in assessing the impact of surface contami-
nation sites (Versar 1983; Dynamac 1983; EPA, 1981). These algorithms were
examined in terms of their applicability in an emergency response assessment.
Although these calculation schemes are fairly easy to implement, they may
not be suitable for application in areas close to the source where the
largest concentrations will occur. Furthermore, these models underestimate
the concentrations at receptor points because the contribution of wind di-
rections other than those directly along the line between the source and
the receptor are not addressed. Because the complexities introduced to ac-
count for these other contributions effectively destroy the attractiveness
of a hand dispersion algorithm, an alternate approach has been adopted in
this manual.
C.3.1 ISC
The Industrial Source Complex (ISC) model is the most versatile of the
EPA models for analyzing concentrations because of its numerous features
that aid the user. If used unwisely, it can prove to be very expensive in
terms of computer time.
Sources may be grouped together, thus alowing calculation of average
concentrations or deposition from combined sources. The ISC model con-
siders point, area, and volume sources. Emission rates may be varied. Re-
ceptors may be specified with either Cartesian or polar coordinates. The
effects of stack-tip downwash, building wakes, and gravitational settling
are also optional. ISC also has one rural and two urban modes. The pol-
lutant may be depleted by an exponential time-dependent decay mechanism,
with the user specifying a decay coefficient. Particulate matter with ap-
preciable gravitational settling can be simulated. The user divides par-
ticulate emissions into at most 20 categories according to particle size.
The settling velocity, mass fraction and surface reflection coefficient must
be specified for each category. Emission rates may be varied by season,
stability class, and wind speed category.
C-4
-------
The user selects either a Cartesian or polar coordinate system for re-
ceptors. For a single source or a group of sources in close proximity, the
polar system is easiest to use. For widely separated sources, the Cartesian
system is usually more convenient.
C.3.2 VALLEY
This model is used to estimate 24-hr and annual concentrations at 112
receptors located at seven distances from the source on sixteen radial lines.
The user also specifies worst case short-term meteorology. Short-term
calculated concentrations from area or point sources are calculated using
Briggs1 plume rise and Pasquill-Gifford vertical dispersion coefficients.
In the horizontal direction, the plume is assumed to be 22.5° wide. The
model assumes that a given meteorology will persist for 6 hr out of 24.
The short-term calculated values are divided by 4 to produce a 24-hr
estimate. The output consists of a print-plots of calculated concentrations.
C.4 METEOROLOGICAL INPUT FOR LONG-TERM ESTIMATES
For many routine modeling applications in which the desired product is
seasonal or annual concentration estimates, the meteorology/climatology of
a site is represented by a STAR (stability array) tabulation. Derived from
historical data (usually 1-5 years), these STAR listings are multivariate
frequency distributions of surface wind speed versus direction as a function
of stability class. The latter serves as an indicator of the degree of
atmospheric turbulence and is normally inferred from surface observations
(Turner, 1961). A typical STAR tabulation contains 576 elements (6 stability
classes • 6 wind speeds • 16 wind directions) with each element representing
the percentage of time that the wind is from a particular direction and in
a given wind speed class and stability class.
It must be stressed that these STAR tabulations are developed from ob-
servations taken at first-order or Class A National Weather Service (NWS)
stations. Hourly wind speeds and direction are not based on continuous or
integrated measurements but rather represent an approximately 15-20 sec
average centered on the time of observation. In principle, these observa-
tions represent open, relatively uniform terrain conditions. Although ob-
servations of this type are routinely employed for dispersion modeling pur-
poses, it is generally understood that the spatial and temporal variability
of most climate elements and particularly the near surface wind field, makes
it highly desirable to obtain continuous measurements in close proximity to
the site in question. The use of NWS observations rather than actual on-site
meteorology may be expected to introduce additional uncertainties in the
concentration estimates computed by a Gaussian dispersion model.
The assessment procedure was developed based on the view that compila-
tion of appropriate meteorological/climatological data for use in a disper-
sion algorithm would be a primary constraint imposed by the 24 hour emer-
gency response. It was further assumed that the emergency response team
would not have access to either:
C-5
-------
1. On-site meteorological measurements from which to construct a suit-
able STAR tabulation
2. A preprocessed STAR tabulation from a nearby (less than 10-20 km)
location that presumably would be representative of conditions at
the site in question.
Based on these considerations, the decision was made to develop regional STAR
tabulations as the necessary meteorological input to the annual dispersion
algorithm. By using the regional STAR tabulation it becomes possible to
obtain annual concentration estimates from a relatively sophisticated dis-
persion model, and at the same time present these results in a convenient
form in the assessment manual.
Climatic regions, as shown in Figure 4-4, were delineated in part based
on the results of a factor analysis of climatological data from 59 first-
order National Weather Service stations. Factor analysis is one of a group
of "pattern recognition" techniques that has been widely used to help define
relationships among large sets of interrelated observations (Harman, 1967).
Details concerning the climatological parameters in the analysis are sum-
marized below.
Regional STAR tabulations were developed by averaging individual sta-
tion STAR tabulations for between three and six stations in each region.
The station selection process was based on the criteria of:
1. STAR tabulation availability in pre-processed form from the
National Climatic Data Center.
2. Format compatibility with the annual model.
3. Record length of 5 years (in most cases 1967-71 or 1968-72).
4. No change in anemometer height (h) with h = 6 m ± 1 m.
A major assumption involved in this procedure is that the uncertainties
created by using regional data are of the same order as those associated
with using data from a single station that is not on or very near (say,
< 10 km) the site in question. This is a plausible assumption given the
great variations in the near-surface boundary layer that occur over short
distance. Use of average or regional data may have certain advantages over
the use of a single station located say 50 km or more away from the site in
question. The latter is a common practice in many routine dispersion model-
ing applications. The averaging process may, for example, help smooth
local-scale influences present in a given station record while at the same
time tend to emphasize the large-scale wind and stability features that are
most closely tied to the general circulation. This is particularly impor-
tant for wind erosion emissions, because events of sufficient force to
entrain particulate will typically occur in conjunction with the periodic
passage of large-scale frontal systems across the continent.
C-6
-------
Factor analysis was used to examine the interrelationships between 3
basic sets of climatological parameters for 59 NWS stations selected so as
to provide relatively uniform coverage over the continuous United States.
The parameters considered in the analysis include the following:
1. WIND SPEED/DIRECTION
a Percentage of hourly observations in each of the "standard"
wind speed classes: 0-3 mph; 4-7 mph; 8-12 mph; 13-18 mph;
19-24 mph; 25-31 mph; > 31 mph.
b. Percentage of hourly observations for the most frequently
occurring wind direction^ defined in terms of a 45° sector.
c. Mean seasonal wind speeds.
2. PRECIPITATION: Seasonal "normals" of number of days with pre-
cipitation > 2.54 mm (0.10 in.).
3. MIXING HEIGHTS: Seasonal mean morning and afternoon mixing heights
These parameters were chosen for their ready availability and because
they represent physical processes which are known to be important in the
resuspension and dispersion of particulate from ground-level sources.
Group 1 a,b data were taken from the United States Weather Bureau pub-
lication, Climatography of the United States No. 82 of the Decennial Census
of United States Climate, Summary of Hourly Observations. These summaries
cover the periods 1951-60 or 1956-60. In large part, these data are biased
by the relocation of wind instruments that occurred between 1955 and 1959 at
most civilian airports. Group Ic data were taken from the publication
Local Climatological Data, Annual Summaries 1977, prepared by the National
Climatic Center. These data are for variable record lengths and presumably
suffer from the same bias noted above. In addition, it should be recognized
that this type of noncontiguous wind speed observation tends to overestimate
prevailing wind speed, though the extent of the bias is presently unknown
(Coty, et al., 1975).
Group 2 data are for the "normal" period 1951-80. These data were
developed in part by MRI under existing National Science Foundation Grant
ATM-8219370. Group 3 data were taken from Holzworth (1972).
The results of the factor analysis procedures were far from conclusive;
part of the reason for this may be the nonhomogeneous quality of much of
the initial input data. Nevertheless, the procedure did indicate a fair
degree of spatial coherence in the climate elements, particularly the wind
speed data which is of primary importance to the present problem. The ac-
tual delineation of the regional boundaries shown in Figure 4-4, was based
both on the factor analysis results and a consideration of a variety of
other sources of climatological information (Coty et al. 1975; McCormick
and Holzworth, 1976).
C-7
-------
-------
APPENDIX D
ANNUAL UNSCALED CONCENTRATION VALUES
D-l
-------
The following pages contain the unsealed concentration values for each
of the seven regions. There are eight tables per region; these are organ-
ized as follows:
Source Size Process Grid Type
1 10 x 10 m Wind erosion Fine
2 10 x 10 m Mechanical resuspension Fine
3 10 x 10 m Wind erosion Coarse
4 10 x 10 m Mechanical resuspension Coarse
5 100 x 100 m Wind erosion Fine
6 100 x 100 m Mechanical resuspension Fine
7 100 x 100 m Wind erosion Coarse
8 100 x 100 m Mechanical resuspension Coarse
The units for the unsealed concentration are jjs/m3.
The results for specific climatic regions are found as follows:
Region Pages
1 D-3 through D-6
2 D-7 through D-10
3 D-ll through D-14
4 D-15 through D-18
5 D-19 through D-22
6 D-23 through D-26
7 D-27 through D-30
D-2
-------
REGION 1
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE
2
2
1
y
2
A
9
0
5
6
2
3
8
RANGF
300
,720
.470
.803
, 132
,793
.835
.002
.641
(M)
2
1
1
1
1
1
1
4
7.
1 ,
2 ,
5 ,
6.
7,
4,
7 ,
00
406
718
510
189
327
706
031
420
5
18,
7,
8,
10,
11,
5 ,
9,
11 .
00
604
861
380
214
034
161
494
772
SCALING FACTOR =
(UNITS)
D-3
-------
o o oooooooooooooo
CO CK ro vr
in CM o rv
r-4 TH TH o
o o co in T ro
in co -c co ro -r
TH O O O TH TH
o o o o
oooooooo
co ro a-- ro [Ti r-j r-j r-4 •»
'-i TH O O O O O O O O O O O O O <">
O O OOOOOOOOOOOOOO
-•----.»....,.,,
o o o •-•> o o o o o o o o o o o o
Pv «T O ro O- C
CM o ro cs ro CM
L~! C^ TH -O PV
•<) co o co o
o o o o o o o o o o o o o
T rv cM T -o ro r-J i"? s:> rn TH TH TH TH CM LI
r-j " TH o o o o o o o o o o o o o
o o o o o o o o o o o o o o o o
o o o o o o o o o o o o o o o o
TH r--. (-.j ro ro o- r-4 rv o~-
ro TH rv r-j co co ro TH ^o o ^ r--j .-,
o rj o in co in cs TH r*-. co T
"T M M r*5 TH TH TH ro r-n » ro
in o
o o o o o o o o o o o o o
fv L~J CD r--. in o ro rv CM «r ro ^o -« o- -r
TV, to TH rj TH TH CM rj TH o o o o o CM
ooooooooooooooo
>oooooooooooo
z:
•i o
o- rr> in
co r-j TJ
rv CN rx
M -o ro o rv o- CM -r o ct- - co o in TH - in o- -O CM r-j TH »r
r-j -o TH ro in ro r-4 in n CM o o TH TH r-4 in
r j TH TH o o o o o o o o o o o o o
OOOOOOOOOOOOOOOO
co in CM co in co «r ro in rv ro o-- co co o rj
r-i •t rv LT CD ^ ro rv. co ro TH o TH TH ro cb
ro CM TH O O O O O O O O O O O O O
OOOOOOOOOOOOOOOO
CD in TH co co o TH in ro o o o o o o o
CO -I
U il
CM ro o- «r TH TH ps o TH CM o- ^o ro o
in CM o- o- -«r ro iii co c> c^ co T-: in TH
TH c>-- rv rv. o o CK -o ro c>- T o -JD o
~Z. UJ ~Z. CO UJ CO CO 3
-- -i- uj uj ui en co en en en
3 13
,-z -3. -~r
3 2: ^:
D-4
CO 3 CO -Z. -3. "C
en en co 3 3 3 :r "::
-------
REGION 1
WIND EROSION
DIR
N
NE
E
SE
S
SW
U
NU
O- = RHAI Tl
200
3.089
2.438
1.057
0.796
0,886
0.347
0.235
0.900
200
N
NE
E
SE
S
SU
W
NU
53
34
34
41
35
25
34
45
.650
.919
.437
.016
.622
.223
.050
.667
300
29,
15.
17.
21 ,
19,
11 .
17.
22 .
567
603
335
040
029
075
610
198
20
10
11
14
12
7
11
14
400
.250
.415
.551
,057
,908
.360
.899
.964
14
7
8
10
9
5
8
10
500
.730
.420
,206
,012
.312
.220
.553
,742
GL= SCALING FACTOR
(UNITS)
D-5
-------
o o o ooo ooooooooo o
*T SD in L~.; TH «r TH CO >o rx CO >C
IH rx «r ro m co rx co ro «r -o LI
THTHT-'THTHOOOtHT-liHTH
O O O O O O O O O O O O
•T f 'T ;?•• T r-< ro T-I o r-- o CM CM «o
CM rx ro CN TH rx co
rO TH rH O TH CM -r-lTHTHTHOiHTHTH
O O O O O
o o o o o o o c o
O O O O O O O O O O C) O
CM ro
•T CM
j CM -0 i-l CM O CO IX SO C.-)
T CM in «r CM T a v co
J CM CM CM TH TH ,-) CM CM CM
o o o o o o o o o o o o o o o o
o o o o o o o o o o o o
it" CM CM o- r-j !>•
o- f; in co r^ o
a"3 ro c j -r-i rj T
o ro 1^5 o CK o r^
r-j un o ix o 1-1 o -o in -o o- o 1-1 ^
o o o o c;.,
O O O O O O O O O C) O
-------
REGION 2
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE (M)
N
NE
E
SE
S
su
w
NW
r SHALI
200
5,043
3,910
4,476
1,621
3,617
1 ,738
0.566
0.920
NO FACTOR =
300
2.448
1,852
2.176
0,759
1 ,767
0,824
0.262
0.428
400
1,471
1 .096
1.309
0,446
1.066
0.488
0.153
0.250
500
0,988
0.729
0.879
0.296
0.718
0,325
0.101
0.165
(UNITS)
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SU
w
NW
SCALING
2
78.
47.
48.
31 .
54.
27.
23.
00
479
143
445
709
949
648
455
27,295
FACTOR =
40
23
24
15
28
13
11
13
RANGE
300
,228
,419
,583
,894
,226
.817
.854
.684
(M)
400
24,
14,
14.
9.
17,
8.
7,
8,
693
103
993
608
332
340
201
267
500
16
9
10
6
11
5
4
5
.780
.471
. 144
,465
,774
,601
,852
.556
(UNITS)
D-7
-------
CM ON co ix T-> d-> ro o in fo TH TH r-4 ^o
O TH-rHTHOTHOOOTHOOOOOOO
o oooooooooooooooo
o -
'•O OOOOOOOOOOOOOOOO
oooooooooooooooo
r-4THTHTHTHOOOTHOOOOOOO
oooooooooooooooo
oooooooooooooooo
r>i TH r-4 >c «r
O 0>- CO T-I 0" M
O M C-J T-J »H CM
o .....
liT OOOOOOOOOOOOOOOO
r-4 «»• o r-4 TH co T-I K) TH
o »-• CD CK r-4 r-j o ~o ro r-4 LT i-i
o CM r-j n »H r-4 »H o o CM —i o o o o o »-i
o oooooooooooooooo
o ................
•f OOOOOOOOOOOOOOOO
T OOOOOOOOOOOOOOOO
oooooooooooooooo
................
OOOOOOOOOOOOOOOO
OOOOOOOOOOOOOOOO
u
CD
2
oooooooooooooooo
Ci£ o *o TH co co o- in »o in TH in in 1*0 «r f*3 in ^o
o
r-4 TH-rHOOOOOO-rHOOOOOOO
LT oo •T n o ix r-4 co rv r-4 rv r-4 ................
TH OOOOOOOOOOOOOOOO
UT 03 UT TH CK C-4 'T ^O CO fO CK CO CO O Tj
rsTHTHiiTsor^>OTHCKrob")r-4'o r*x ^^ rx o* rx i \Q s/^ Q fw r-.j .
in r-4Oinr-4CNTHT-iTHrxcKixcor*)coo«
-------
REGION 2
WIND EROSION
FINE GRID
SOURCE SIZE 100M X 100M
KIR
RANGE
N
NE
E
SE
S
SW
U
NW
SCALING
47
41
33
28
33
22
17
25
200
.633
.777
.968
. 458
.180
.969
.764
.015
300
26.
19,
17,
12,
18.
10.
8,
10.
821
765
821
764
345
517
633
726
400
18,
13,
12,
8.
12,
7,
5 ,
7,
379
180
079
546
590
050
825
186
13
9
8
6
9
5
4
5
500
.373
,377
,708
.100
,172
.041
.184
,132
FACTOR -
(UNITS)
D-9
-------
r-4 o CN co TH tn ro -q- CN in «r M TH ,H r-4 in
O THTHOOrHOOOOOOOOOOO
o oooooooooooooooo
o ••.••.-...».......
r^ oooooooooooooooo
in T r-4 r-4 r-4 o o o «r in m in -o -q-
o o o* S3 CD -^3 o- r-4
r-4 TH o o o o o TH
oooooooooo oooooo
o rx m o >o K
rx CM H 2 !
CD i— i
UJ 3 i
o:
0 »"5"^S"^MK^*"2^S
*-< OOOOOOOOOOOOOOOO
in oo S3 rx u") s3 r-4 in CN co ix in m *»• m r 4
O r 4 r 4 r 4 r 4 r 4 »H O TH ,H TH o O O O O *H
*H OOOOOOOOOOOOOOOO
II
TH ix CM m rn rx r4 m ^
o r4 o in «r rx r4 UT CN CN r-j in o in *r co r4 i—
n T ^- rn m m rj TH TH r-4 r-4 TH TH o o o r-4 u
OOOOOOOOOOOOOOOO U_
CD
2:
— 1
iV ' • *^
CO
1-
1—1
2
^3
2 II
0 ii
^H ||
CO il
2 II
U II
Ci_ M
CO 1!
Z3 II
CO !!
UJ II
ii: II
II
—1 il
CJ M
J'
^ '•
X II
CJ II
UJ M
„_,
co rx rx m CN iiT iii r-j rx rx TH ^r CN o co TH ^
UT r-4 rx o CN o T rn UT r-4 -TrHCOcNCOTHrx ^
•H m r-4 r-4 TH r-4 TH TH TH r-4 TH TH o o o TH TH v_
o UT T TH o T rx CN UT TH r-4 in CN o fx rx in
O S3 CN O CO CN TH CN r-4 f4 TH S3 r-4
-------
REGION 3
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE (M>
N
NE
E
SE
S
SW
U
NW
• SCALING
8
2
2
5
5
1
1
9
200
,573
,326
.953
,052
,105
,699
,300
,898
4
1
1
•p
2
0
0
1
300
. 169
.078
.415
,399
,436
.802
,621
,351
2
0
0
1
1
0
0
0
400
,508
.629
.844
.422
.450
.474
,370
,793
5
1 .
0,
0.
0,
0.
0.
0.
0,
00
685
415
564
947
968
315
247
524
FACTOR = _ _ _ __ _
(UNITS)
MECHANICAL. RESUSPENSION
DIR
N
NE
E
SE
S
SW
U
NW
(?_ = SCALING
55
17
24
22
28
18
21
29
200
.299
.769
.456
,641
,413
,987
,242
.882
28
8
12
11
14
9
10
14
RANGE
300
,003
,631
,326
, 174
.143
,392
,641
.680
(M)
400
17
5
7
6
B
5
6
B
. 106
, 135
, 5
,7
,5
.6
.4
11
27
63
55
52
.796
11
3
5
4
5
3
4
5
500
,595
,419
,083
,519
.771
,799
.349
.888
FACTOR = _„. _.
(UNITS)
D-ll
-------
o o- in ^- rv rx TH LT TH tn -T ro M CM -o m
CMOOOOO-I-HTHTHOOOOOOTH
oooooooooooooooo
oooooooooooooooo
CKrxvCi!nrx>CCK
cMoooooooooooooo
oooooooooooooooo
n TH o o TH *H T-( CM CM o o o o o TH CM
oooooooooooooooo
oooooooooooooooo
SD CM CM in in CK *r o- CD «r TH rx oo CD
TH rx oo T-tixcs'-ir-Jo.aDrxo^oor-j
oooooooooooooooo
UT r -i T-H >-i TH »-i CM M r-j »-i o o o o •<-! n
oooooooooooooooo
oooooooooooooooo
oooooooooooooooo
rv M ^« T-I r-j CN ••r iii THhOrOOrxCKO-CK
OT CDCMTHOOTTHbTOO^OfOO
M n oo o r-j O bT rx o O TH ^" 00 P-J O TH
r*jxJrx>yTH CD"O*C/^^OOOCDvOIXT~l °
oo T TH TH r-4 r-4 «r >o 'r r-4 TH TH TH TH tM \r> u
oooooooooooooooo u_
CD
z
1— 1
_J
LULULULU3333U
ZLUZ cnujcn coscn zsz co
CO
1—
I-H
z
-
z
0
t-H
CO
z
LU
u_
CO
CO
UJ
*
bT ro o o rx
TH CM TH O O
o m oo rx CK
o *r lit CK o
o ....
CM 00 T *O
o os tn ro o
L~) -O -O -O CO
a: LU LU
HH Z LU Z
mTHTHT-,«r0rxrxb-3«rx.o
«t"OTHinrxo*ob*3coorxrx
oixcKO-rHO-rxmcDOOTHO
THOOTHTHOOOOO-rHTH
TH CM CM CM O O TH lit CO rx TH >0
bi o ro bT rx n TH o r-4 TH rx oo
^.H.-H^^.H^O^TH^CM
CKinco*-io-rxocorxr*D«orN
^TH^g^SS^ctgK
UJ UJ 3 3 3 3
COLUCO CO3O5 ZSZ
II
.
O
1—
CJ
U-
CD
Z
t— 1
— 1
-------
REGION 3
WIND EROSION
DIR
N
NE
£
SE
S
SU
U
NW
0,.=- SCALING
FINE GRID
200
4,789
2,505
2,204
3,712
3.527
1.532
1 .067
2.729
FACTOR =
RANGE
300
2.747
0.988
1.046
1.896
1.856
0.656
0.469
1,192
SOURCE SI
(M)
400
1 .859
0.644
0.698
1.256
1.235
0.432
0.312
0.780
(UNITS)
500
1.341
0,450
0,498
0,890
0.878
0.306
0,222
0.547
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SU
W
NU
On - SCALING
200
34.215
18.713
16.715
18.246
20.173
15.937
16.112
26.349
FACTOR =
RANGE
300
19.415
7.771
8.732
8.841
10,662
7,596
7,952
12,608
(M)
400
13.221
5.129
5.927
5.912
7.175
5.074
5.360
8.372
500
9,573
3,618
4,280
4.220
5.145
3,618
3,847
5.937
(UNITS)
D-13
-------
oooooooooooooooo
................
OOOOOOOOOOOOOOOO
o in o- in ix in in -iT-i
oooooooooooooooo
in ix o. ix r-4 ro o -<
oooooooooooooooo
CD ^ o rv rx o ui o- >o tn \r> »n r-j »H ui > n &. o- M o rx CK r-4 r-j
iv co ix o^ UT oo r-4 >o oo r-4 CK tx TH o o o
in r-4 r-i TH r-j TH r-4 r-4 r-4 r-4 TH TH r-4 r-4 n -o in in *o o^ ^? f*3 *T ^
in r*} TH o o TH TH TH r-4 TH TH ^5 ^5 o o TH r-4
r-4 ................
TH OOOOOOOOOOOOOOOO
{MXinmoT-.oooroinTH,HeDvo*o
o r-4 li") IX r-4 00 IX O TH O -O CJ
^ ^
UT n TH TH r-4 TH r-4 r-4 r-4 r-4 TH TH CM r-4 ro -q- u_
CO
^«i
-i
-------
REGION 4
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE (M)
N
NE
E
SE
S
3W
W
NW
QT a SCALING
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SW
W
NW
200
6,096
2,857
4.190
4.833
3,182
0,992
1,353
2. 167
FACTOR
200
61 .345
30.722
31 .350
31 ,455
39,107
15.768
31.106
53.652
300
2.974
1.351
2.012
2.327
1,536
0.466
0.647
1.019
400
1 . 793
0.799
1.202
1.391
0.921
0.274
0.385
0.600
(UNITS)
RANGE (M)
300
31.293
15.298
15,713
15,723
20.041
7.780
15,506
27.369
ar SCALING FACTOR =
400
19.167
9,218
9,525
9,516
12.301
4.670
9,371
16.721
(UNITS)
500
1.206
0.531
0.804
0.931
0.617
0,182
0,257
0.398
500
13.009
6.190
6.420
6.412
8.360
3.129
6,304
11 .335
D-15
-------
in ix SD in o ON TH ix ix r*j CM r-j ro ro in ix
O THOOOTHOi-iOOOOOOOOO
o oooooooooooooooo
o
ix oooooooooooooooo
TH co roros3cos3cooooTHO'rm *H co
O OOONCOOOCOS3COIXTHinH »-i o o o o o TH »H
oooooooooooooooo
.................
OOOOOOOOOOOOOOOO
Kl l> M M T-J CK TH C-J UT C-
-------
REGION 4
WIND EROSION
FINE GRID
SOURCE SIZE 100M X 100M
DIR
RANGE (M)
200
N
NE
E
SE
S
SW
U
NW
SCALING
3.
2,
2.
3.
2,
0.
1.
1.
425
564
937
265
167
983
007
986
1
1
1
1
1
0
0
0
300
,914
,090
.463
.670
.077
.396
,486
.859
1
0
0
1
0
0
0
0
400
.300
.720
.978
.119
.723
.260
.324
*565
500
0.
0.
0.
0.
0.
0,
0.
0.
940
509
699
801
519
183
231
398
FACTOR = _
(UNITS)
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SW
W
NW
CL- SCALING
200
39.834
27.546
23.777
24.467
24.573
15,717
24,926
39.259
FACTOR =
RANGE
300
21.285
12.712
12.025
11 .915
13,404
6.491
12,302
20.254
(M)
400
14.546
8.486
8.093
8,017
9, 180
4.321
8.251
13,731
500
10.560
6.043
5.801
5.750
6.677
3.070
5.896
9.905
(UNITS)
D-17
-------
in CD o SD o o TH rs is. ro CM CM to ro in co
O THOOOTHTHTHOOOOOOOOO
o oooooooooooooooo
o • •
is. OOOOOOOOOOOOOOOO
•rH f*7 U"5 U"3 CO *~* PS. T-H CO *f C^J rO *O &•• FO L"^
o co o co co co is. co CD TH m «r ON rs ON m in rs co r-4 o
o ro r 4 TH TH r-4 r-4 r 4 ^ TH o o o o o TH r-4
o ................
TH OOOOOOOOOOOOOOOO
r-4 rs o TH -q- UT oo oo r-4 ro ro o ON 'J- r-4 •*
LO UT ro r-4 r-4 ro is3is.uTONTHONroroTH
THSS-q-sssjooroTHnssooTHooooNro
rs o TH o o rs o r-4 SD r-4 uT oo o UT r-4 o
IT T ro ro ro r-4 ro ro ro r-4 TH TH ro ^ u") t"3
-------
REGION 5
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE (M)
200
N
NE
E
SE
S
SW
W
NW
SCALING
3.
0,
0,
1.
3.
1.
1 ,
4,
613
568
358
026
410
426
632
285
300
1 .
0,
0.
0.
1 .
0,
0.
2.
743
265
168
483
670
671 "
764
061
1
0
0
0
1
0
0
1
400
,044
, 155
,099
.285
,009
.396
.449
.231
0
0
0
0
0
0
0
0
500
.699
.103
.065
,189
.680
,263
,297
,824
FACTOR = __ __ .__ _ _
(UNITS)
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SW
U
NU
O_ « q n A I
200
83.080
38,341
39,708
35,700
78.805
52.575
75.198
62,602
TNR FACTOR =
RANGE
300
43,203
19.597
20.436
18.184
41 . 136
26.532
38.594
31 .760
(M)
400
26.660
11.938
12.508
11.059
25.427
16.068
23.645
19.325
500
18.175
8.070
8.475
7,468
17.349
10.820
16.041
13.062
(UNITS)
D-19
-------
oo r 4 -H TH TH TH r-4 «r co o oo w ^- o CM ^r r 4 TH
o -o rg c-4 r-4 04 r-4 04 r-4 UT ro ro >o r-4 in r-4 r4 ro »H oo o T-I o o o o TH ro >o r-4 r4 r-4 r-4 ^r rx rx
oooooooooooooooo
oooooooooooooooo
r-4 T-lOOOOOOO»-«O
T-I oo rx 03 r-4 n o ro
o •T ro ro -T >o r%i TH
r-4 co T o CN ro rx.
o o r-4 T-t TH o •«-<. r-4 •
o THOOOOOO
in ........ ..... ...
TH OOOOOOOOOOOOOOOO
co CK CK ro r-4 rx rx rx rx UT TH TH rx o» r-4 ro
o roroTHTHTHTHM>oro^oinininoo~oin
liT THOOOOOOOiHOOOOOTHTH
r-4
TH OOOOOOOOOOOOOOOO
o rx oo o- co in ro rx rx
-------
REGION 5
WIND EROSION
FINE GRID
SOURCE SIZE 100M X 100M
DIR
RANGE (M)
N
NE
E
SE
S
SU
W
NU
: SCALING
200
2.333
0.669
0.341
0.951
1.850
1 .294
1.496
2.789
FACTOR =
300
1.217
0.231
0.142
0.402
1.049
0.558
0.655
1 .474
400
0 . 8 1 7
0.151
0,093
0.265
0,715
0.368
0,430
0.987
500
0.586
0, 106
0.066
0,187
0.519
0.259
0.302
0.706
(UNITS)
MECHANICAL RESUSPENSION
DIR
N
NE
E
SE
S
SU
U
NU
CL = SCALING
2
53.
34,
29.
32.
48.
47.
52.
00
034
356
840
765
508
042
465
51.788
FACTOR =
RANGE
300
29,
15.
15.
14.
26.
21 ,
27,
24.
110
646
417
777
991
859
824
779
(M)
400
20.
10.
10.
9.
18.
14,
18,
16.
003
536
447
930
604
638
923
700
14
7
7
7
13
10
13
11
500
,580
,553
.524
.105
.593
.447
.677
.984
(UNITS)
D-21
-------
oo r-4 TH TH TH TH r-4 *r CD o o^ ix -c
O '-lOOOOOOOTHOOOOOTHrH
o oooooooooooooooo
o ................
in oooooooooooooooo
ra w CM M r j
oooooooooooooooo
r-j o o o o o o «H r-j »H o o o »H r-j r-4
oooooooooooooooo
................
oooooooooooooooo
•H T-I m o rv IIT UT ~o r-j ix M TH «r LT oo Is-.
o T-«orxincoi'Oii-)CKcoiiT^orviMKMo cs oo •«»• o •* \n UT oo in in r-4 «r o oo •« (n ui OK \r>
o ........^T^(^r]!l'?*"?rj ^
r-4 THOOOOOOOTHTHTHTHTHTHTHTH
o
o
bT
O
r-4
o
o
o
2 II O
O II lit
I-H ii rx
CO II
O II
a: ;i
U II
ii
1=4 II
2 II
••H ii ce
3 l| KH
^— .
oroTHi-iTHTHCNbTOKbT^'^'^-rxrjTH
THOOOOOOOOOOOOOTHTH
oooooooooooooooo
bT r-4 r-4 UT O bT bT 1*3 OK TH r-4
fO u J r-4 TH TH r-4 ^* Px r-4 rx b") b^ ^O OK ^o >O
rHOOOOOOOTHOOOOO-rHTH
OOOOOOOOOOOOOOOO
r-4 rv r-4 TH o o- oo TH rv r-4 o o- r-4 m o n
OK rx rn r-4 r-4 r-4 bT TH ix TH oo Is* OK THOooooTHr-4THTHTHTHr>iMn u
oooooooooooooooo u.
CO
2
1
o r^ oo oo oo o
r-4 M r-4 CM r^ ro rj r 4
r-4 r-4 r-4 r-4 r-4
U4UUILU33
2U42 cnuitn cnscn
D-22
-------
REGION A
WIND EROSION
FINE GRID
SOURCE SIZE 10M X 10M
DIR
RANGE
N
NE
E
SE
S
SW
U
NU
r crai
200
4.566
1.790
2.206
1.578
1.822
0.837
0.140
0.242
TNfi FACTOR -
300
2.280
0.844
1 .057
0.749
0.886
0.411
0.064
0.113
400
1.393
0.498
0.630
0.444
0.533
0,248
0.037
0,066
500
0,945
0.331
0.421
0.296
0.358
0.167
0.024
0,044
(UNITS)
MECHANICAL RESUSF'ENSION
DIR
N
NE
E
SE
S
SW
W
200
82.
49.
36,
34,
77.
49.
71 ,
780
019
967
918
675
906
731
NW 47.035
Q «= SCALING FACTOR =
RANGE
300
42
24
18
17
40
25
36
23
.568
,609
.389
.459
,009
,036
.985
.710
-------
THOOOOOOOOOOOOOOO
oooooooooooooooo
oooooooooooooooo
O 0* »O CM &• O 00 CD 00 IO M \Tl o oooooooooooooooo
•o rr> CM r j v> o TH »H o ix in rx o n o o*
o r-i -o r> «r CM o CM CM o co rx \n CD M -o CM
o MTHTHTHTHTHTHTHroTHTHTHCMCMTHiH
o ................
o oooooooooooooooo
o -c -o o o in >o -o rx CM jraMTH»Hooooo
cc:o oooooooooooooooo
o ................
CM OOOOOOOOOOOOOOOO
Ul
CD
2
CO >O 00 C-J
o THOOOOOOOOOOOOOOO
UT
TH OOOOOOOOOOOOOOOO
CN »-l i-< TH
u-i fJCN^^MMOO
£t
CD
Ul
cn
o in in o o n
on in ••r TH TH r-4 r-4 TH
cn i o o o o o o
0 i
CC 1
Ul i
1
Ci i
Z 1
o
«r
CO
o
o
*H
*
o
i-i ii ii: ui ui ui
3 ii >-« zuiz cnui
1=1 z z z ui ui ui cn
r-4
o
0
o^
o
o
T-4
bT
O
Ul
cn
cn
r-4 r-4 T
rx r-4 ro
O 0 O
o o o
M n co
TH O O
000
ro r^ rH
K bT CO
o o o
3
cn 3
tn cn cn
o-
o
o
0
«r
o
0
^
r-4
o
3
tn
3
»r rx
0 0
o o
0 O
rx o
0 0
o o
TH ^Q
TH TH
0 0
3
Z
3 3
CO 0-
O TH
0 0
0 0
r-4 cs
TH r-4
o o
0 0
TH r-j
r-4 bT
o o
0 0
3
3 Z
Z Z
cn
h-
i-l
Z
ID
Z II
O II
cn ii
Z II
Ul II
••»- II
ii cn u
=i u
(£. cn u
O Ul II
h- CC II
U II
u. X3fOTH.-immrK
o M
-------
REGION 6
WIND EROSION
FINE GRID
SOURCE SIZE LOOM X 100M
DIR
N
NE
E
SE
S
SW
W
NW
SCALI
200
2,009
1.678
1,518
1.272
1.123
0 . 550
0.187
0,538
NG FACTOR =
RANGE
300
1.203
0,693
0,784
0,593
0.588
0.254
0.063
0.099
(M)
400
0,841
0.457
0.523
0.392
0.398
0.174
0.041
0.065
500
0,623
0,323
0,373
0,278
0.287
0.126
0.028
0,046
(UNITS)
MECHANICAL RESUSPENSION
RANGE (M)
L" i r\
N
NE
E
SE
S
SU
U
NW
m ar AI
200
49,149
39.803
29,941
30,864
47,488
43.659
49.128
43.623
TMR FACTOR
300
26.992
19.050
14.762
13,801
26.301
20.018
26,626
19,697
400
18.606
12,802
9,872
9.248
18.060
13.424
18.133
13.189
500
13.603
9.171
7.037
6.608
13.163
9,596
13,119
9,410
(UNITS)
D-25
-------
r-4 -T ^- in in m •<>• i co n T-I
OOOOOOOOOOOOOOOO
oooooooooooooooo
oooooooooooooooo
ix « r-j ix •q- o ro UT ••r
in f«J to r-j CM CM CM CM in
oooooooooooooooo
oooooooooooooooo
oooooooooooooooo
CO CM
IX r-4 >O O O UT
t*) OOOOOOOOOOOOOOOO
UJ
CD
o ^ o
OOOOOOOOOOOOOOOO
II
ct:
r^ODTOTrvM^orjrjoor^^^Mos o
^-O-OOOsT'^'liTliTOO«OMi-i»-ir-4'-' h-
r*)r-4r-ir-4T-i»-i,-H»-iT-toooooo-'-i u
CO I
O i
oooooooooooooooo
-------
REGION 7
WIND EROSION
FINE GRID
SOURCE SIZE ion x IOM
DIR
RANGE (M)
N
NE
E
SE
S
SW
U
NW
Qs « SCALING
MECHANICAL RESUSF'ENSION
3
3
4
5
4
2
1
0
200
,680
.391
, 622
.454
.151
.686
,358
.668
FACTOR
300
1 .805
1.626
2. 192
2.610
2.000
1.285
0.640
0.305
400
1 .091
0.970
1.301
1.555
1.198
0.766
0.377
0,177
(UNITS)
500
0.735
0.648
0.866
1.039
0,802
0.511
0.250
0.116
DIR
N
NE
E
SE
S
SW
U
NU
CL. = SCALING
2
43.
41.
39.
29.
40.
34.
26.
00
224
792
522
911
962
257
682
16.752
FACTOR =
22
21
19
14
20
17
13
8
RANGE
300
.172
, 160
.843
.844
,833
.154
.384
,328
(M)
13
12
12
8
12
10
8
5
400
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. 117
,017
500
9.
8.
8,
6,
8.
7.
5.
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279
725
124
014
645
005
473
369
(UNITS)
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D-28
-------
REGION 7
WIND EROSION
COARSE GRID
SOURCE SIZE tOOM X 100M
DIR
N
NE
E
SE
S
3W
U
NW
SCALING
200
2.050
2,559
3.502
3.837
2.893
1,975
1 .104
0.881
FACTOR =
RANGE
300
1 . 106
1.196
1 .735
1 .956
1.422
0.963
0.526
0.302
(M)
400
0.755
0,798
1.149
1.303
0.954
0,642
0.346
0.195
500
0.549
0,570
0,314
0.929
0.683
0,457
0.244
0.135
MECHANICAL RESUSPENSION
(UNITS)
DIR
N
NE
E
SE
S
SW
W
NW
GL ts SCALING
200
26,882
31,453
30.207
25.238
27.523
26,393
20.291
16.270
FACTOR =
300
14.401
15,781
15.515
11 .923
14.442
13.241
10.328
6.811
400
9.906
10,679
10,436
7,976
9,843
8.903
6,947
4.547
500
7.231
7.695
7.477
5,692
7. 131
6.382
4,978
3.239
(UNITS)
D-29
-------
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APPENDIX E
EMISSION FACTORS FOR OTHER FORMS OF MECHANICAL DISTURBANCE
E-l
-------
As stated in the body of this report, vehicle traffic is the most
likely mechanical entrainment mechanism for surface material contaminated
by a recent spill or by prior waste dump activities that have been linked
to the recently discovered surface contamination. However, other mechanical
entrainment mechanisms may be significant in association with remedial
action taken to eliminate the atmospheric exposure of contaminated surface
materials. Such activities normally require the removal, transport and dis-
posal of the contaminated material.
In estimating emissions from the removal and transfer of contaminated
soil, it is necessary to subdivide the site activities into unit operational
steps. Recently EPA (1983) issued revised particulate emission factors for
agricultural tilling and for aggregate handling and storage piles. These
emission factors take the form of predictive equations, and as such they
must be applied within the ranges of source parameters tested in order to
retain the specified quality ratings. The emission factor for agricultural
tilling may be used to estimate emissions from pushing or scraping material
from the surface with an implement traveling at a speed of about 8 to 10 km/hr.
The loading of material into trucks or the dumping of trucks is best described
by the "batch drop" equation contained in the section on aggregate handling
and storage piles.
The remainder of this Appendix consists of the appropriate sections of
EPA's Compilation of Air Pollutant Emission Factors, as described above.
E-2
-------
11.2.2 AGRICULTURAL TILLING
11.2.2.1 General
The two universal objectives of agricultural tilling are the creation
of the desired soil structure to be used as the crop seedbed and the eradi-
cation of weeds. Plowing, the most common method of tillage, consists of
some form of cutting loose, granulating and inverting the soil, and turning
under the organic litter. Implements that loosen the soil and cut off the
weeds but leave the surface trash in place have recently become more popu-
lar for tilling in dryland farming areas.
During a tilling operation, dust particles from the loosening and pul-
verization of the soil are injected into the atmosphere as the soil is
dropped to the surface. Dust emissions are greatest during periods of dry
soil and during final seedbed preparation.
11.2.2.2 Emissions and Correction Parameters
The quantity of dust from agricultural tilling is proportional to the
area of land tilled. Also, emissions depend on surface soil texture and
surface soil moisture content, conditions of a particular field being
tilled.
Dust emissions from agricultural tilling have been found to vary di-
rectly with the silt content (defined as particles < 75 micrometers in di-
ameter) of the surface soil depth (0 to 10 cm [0 to 4 in.]). The soil silt
content is determined by measuring the proportion of dry soil that passes a
200 mesh screen, using ASTM-C-136 method. Note that this definition of
silt differs from that customarily used by soil scientists, for whom silt
is particles from 2 to 50 micrometers in diameter.
Field measurements2 indicate that dust emissions from agricultural
tilling are not significantly related to surface soil moisture, although
limited earlier data had suggested such a dependence.1 This is now be-
lieved to reflect the fact that most tilling is performed under dry soil
conditions, as were the majority of the field tests.1"2
Available test data indicate no substantial dependence of emissions on
the type of tillage implement, if operating at a typical speed (for exam-
ple, 8 to 10 km/hr [5 to 6 mph]).1-2
11.2.2.3 Predictive Emission Factor Equation
The quantity of dust emissions from agricultural tilling, per acre of
land tilled, may be estimated with a rating of A or B (see below) using the
following empirical expression2:
E = k(604)(s)°'6 (kg/hectare) (1)
E = k(538)(s)°-6 (Ib/acre)
5/83 Miscellaneous Sources 11.2.2-1
E-3
-------
where: E = emission factor
k = particle size multipler (dimensionless)
s = silt content of surface soil (%)
The particle size multiplier (k) in the equation varies with aerodynamic
particle size range as follows:
Aerodynamic Particle Size Multiplier for Equation 1
Total
particulate
1.0
< 30 pm
0.33
< 15 pro
0.25
< 10 pm
0.21
< 5 pm
0.15
< 2.5 pro
0.10
Equation 1 is rated A if used to estimate total particulate emissions,
and B if used for a specific particle size range. The equation retains its
assigned quality rating if applied within the range of surface soil silt
content (1.7 to 88 percent) that was tested in developing the equation.
Also, to retain the quality rating of Equation 1 applied to a specific ag-
ricultural field, it is necessary to obtain a reliable silt value(s) for
that field. The sampling and analysis procedures for determining agricul-
tural silt content are given in Reference 2. In the event that a site spe-
cific value for silt content cannot be obtained, the mean value of 18 per-
cent may be used, but the quality rating of the equation is reduced by one
level.
11.2.2.4 Control Methods3
In general, control methods are not applied to reduce emissions from
agricultural tilling. Irrigation of fields before plowing will reduce
emissions, but in many cases, this practice would make the soil unworkable
and would adversely affect the plowed soil's characteristics. Control
methods for agricultural activities are aimed primarily at reduction of
emissions from wind erosion through such practices as continuous cropping,
stubble mulching, strip cropping, applying limited irrigation to fallow
fields, building windbreaks, and using chemical stabilizers. No data are
available to indicate the effects of these or other control methods on
agricultural tilling, but as a practical matter, it may be assumed that
emission reductions are not significant.
References for Section 11.2.2
1. C. Cowherd, Jr., et al., Development of Emission Factors for Fugitive
Dust Sources, EPA-450/3-74-037, U. S. Environmental Protection Agency,
Research Triangle Park, NC, June 1974.
2. T. A. Cuscino, Jr., et al. , The Role of Agricultural Practices in
Fugitive Dust Emissions, California Air Resources Board, Sacramento,
CA, June 1981.
3. G. A Jutze, et al., Investigation of Fugitive Dust - Sources Emissions
And Control, EPA-450/3-74-036a, U. S. Environmental Protection Agency,
Research Triangle Park, NC, June 1974.
11.2.2-2 EMISSION FACTORS 5/83
E-4
-------
11.2.3 AGGREGATE HANDLING AND STORAGE PILES
11.2.3.1 General
Inherent in operations that use minerals in aggregate form is the
maintenance of outdoor storage piles. Storage piles are usually left un-
covered, partially because of the need for frequent material transfer into
or out of storage.
Dust emissions occur at several points in the storage cycle, during
material loading onto the pile, during disturbances by strong wind cur-
rents, and during loadout from the pile. The movement of trucks and load-
ing equipment in the storage pile area is also a substantial source of
dust.
11.2.3.2 Emissions and Correction Parameters
The quantity of dust emissions from aggregate storage operations var-
ies with the volume of aggregate passing through the storage cycle. Also,
emissions depend on three correction parameters that characterize the con-
dition of a particular storage pile: age of the pile, moisture content and
proportion of aggregate fines.
When freshly processed aggregate is loaded onto a storage pile, its
potential for dust emissions is at a maximum. Fines are easily disaggre-
gated and released to the atmosphere upon exposure to air currents from ag-
gregate transfer itself or high winds. As the aggregate weathers, how-
ever, potential for dust emissions is greatly reduced. Moisture causes ag-
gregation and cementation of fines to the surfaces of larger particles.
Any significant rainfall soaks the interior of the pile, and the drying
process is very slow.
Field investigations have shown that emissions from aggregate storage
operations vary in direct proportion to the percentage of silt (particles
< 75 urn in diameter) in the aggregate material.1 3 The silt content is de-
termined by measuring the proportion of dry aggregate material that passes
through a 200 mesh screen, using ASTM-C-136 method. Table 11.2.3-1 summa-
rizes measured silt and moisture values for industrial aggregate materials.
11.2.3.3 Predictive Emission Factor Equations
Total dust emissions from aggregate storage piles are contributions of
several distinct source activities within the storage cycle:
1. Loading of aggregate onto storage piles (batch or continuous drop
operations).
2. Equipment traffic in storage area.
3. Wind erosion of pile surfaces and ground areas around piles.
4. Loadout of aggregate for shipment or for return to the process
stream (batch or continuous drop operations).
Miscellaneous Sources 11.2.3-1
E-5
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EMISSION FACTORS
E-6
5/83
-------
Adding aggregate material to a storage pile or removing it usually in-
volves dropping the material onto a receiving surface. Truck dumping on
the pile or loading out from the pile to a truck with a front end loader
are examples of batch drop operations. Adding material to the pile by a
conveyor stacker is an example of a continuous drop operation.
The quantity of particulate emissions generated by a batch drop opera-
tion, per ton of material transferred, may be estimated, with a rating of
C, using the following empirical expression2:
E = k(0.00090)
E = k(0.0018)
(5) (2.2) (1.5)
0.33
(kg/Mg)
(1)
(I) ® (f)
0
(Ib/ton)
where:
E = emission factor
k = particle size multipler (dimensionless)
s = material silt content (%)
U = mean wind speed, m/s (mph)
H = drop height, m (ft)
M = material moisture content (%)
Y = dumping device capacity, m3 (yd3)
The particle size multipler (k) for Equation 1 varies with aerodynamic par-
ticle size, shown in Table 11.2.3-2.
TABLE 11.2.3-2.
AERODYNAMIC PARTICLE SIZE
MULTIPLIER (k) FOR
EQUATIONS 1 AND 2
Equation < 30 < 15 < 10 < 5 < 2.5
pro pm pm fJm |jm
Batch drop 0.73 0.48 0.36 0.23 0.13
Continuous
drop 0.77 0.49 0.37 0.21 0.11
The quantity of particulate emissions generated by a continuous drop
operation, per ton of material transferred, may be estimated, with a rating
of C, using the following empirical expression3:
5/83
Miscellaneous Sources
E-7
11.2.3-3
-------
E = k(0.00090)
E = k(0.0018)
(5) (2.2)
(I)
(f ) (g) (if
(kg/Mg)
(2)
(Ib/ton)
where: E = emission factor
k = particle size multiplier (dimensionless)
s = material silt content (%)
U = mean wind speed, m/s (mph)
H = drop height, m (ft)
M = material moisture content (%)
The particle size multiplier (k) for Equation 2 varies with aerodynamic
particle size, as shown in Table 11.2.3-2.
Equations 1 and 2 retain the assigned quality rating if applied within
the ranges of source conditions that were tested in developing the equa-
tions, as given in Table 11.2.3-3. Also, to retain the quality ratings of
Equations 1 or 2 applied to a specific facility, it is necessary that reli-
able correction parameters be determined for the specific sources of inter-
6St; r flCld and laboratory procedures for aggregate sampling are given
in Reference 3. In the event that site specific values for correction pa-
rameters cannot be obtained, the appropriate mean values from Table
11.2.3-1 may be used, but in that case, the quality ratings of the equa-
tions are reduced by one level.
TABLE 11.2.3-3. RANGES OF SOURCE CONDITIONS FOR
EQUATIONS 1 AND 2a
Silt Moisture
Equation content content
(%) (%)
Dumping capacity
m3 yd3
Drop height
m ft
Batch drop 1.3 - 7.3 0.25 - 0.70 2.10 - 7.6 2.75 - 10 NA NA
NA NA 1.5 - 12 4.8 - 39
Continuous
drop 1.4 - 19 0.64 - 4.8
NA = not applicable.
For emissions from equipment traffic (trucks, front end loaders doz-
ers, etc.) traveling between or on piles, it is recommended that the equa-
tions for vehicle traffic on unpaved surfaces be used (see Section 11 2 1)
For vehicle travel between storage piles, the silt value(s) for the areas'
11.2.3-4
EMISSION FACTORS
E-8
5/83
-------
among the piles (which may differ from the silt values for the stored mate-
rials) should be used.
For emissions from wind erosion of active storage piles, the following
total suspended particulate (TSP) emission factor equation is recommended:
E = 1.9
(if) (kg/day/hectare) (3)
E = !'7 iTs > (if) ("-/day/acre)
where: E = total suspended particulate emission factor
s = silt content of aggregate (%)
p = number of days with ^ 0.25 mm (0.01 in.) of precipitation
per year
f = percentage of time that the unobstructed wind speed ex-
ceeds 5.4 m/s (12 mph) at the mean pile height
The coefficient in Equation 3 is taken from Reference 1, based on sam-
pling of emissions from a sand and gravel storage pile area during periods
when transfer and maintenance equipment was not operating. The factor from
Test Report 1, expressed in mass per unit area per day, is more reliable
than the factor expressed in mass per unit mass of material placed in stor-
age, for reasons stated in that report. Note that the coefficient has been
halved to adjust for the estimate taat the wind speed through the emission
layer at the test site was one half of the value measured above the top of
the piles. The other terms in this equation were added to correct for
silt, precipitation and frequency of high winds, as discussed in Refer-
ence 2. Equation 3 is rated C for application in the sand and gravel in-
dustry and D for other industries.
Worst case emissions from storage pile areas occur under dry windy
conditions. Worst case emissions from materials handling (batch and con-
tinuous drop) operations may be calculated by substituting into Equations 1
and 2 appropriate values for aggregate material moisture content and for
anticipated wind speeds during the worst case averaging period, usually
24 hours. The treatment of dry conditions for vehicle traffic (Section
11.2.1) and for wind erosion (Equation 3), centering around parameter p,
follows the methodology described in Section 11.2.1. Also, a separate set
of nonclimatic correction parameters and source extent values corresponding
to higher than normal storage pile activity may be justified for the worst
case averaging period.
11.2.3.4 Control Methods
Watering and chemical wetting agents are the principal means for con-
trol of aggregate storage pile emissions. Enclosure or covering of in-
active piles to reduce wind erosion can also reduce emissions. Watering is
useful mainly to reduce emissions from vehicle traffic in the storage pile
area. Watering of the storage piles themselves typically has only a very
temporary slight effect on total emissions. A much more effective tech-
nique is to apply chemical wetting agents for better wetting of fines and
5/83 Miscellaneous Sources 11.2.3-5
E-9
-------
longer retention of the moisture film. Continuous chemical treatment of
material loaded onto piles, coupled with watering or treatment of roadways,
can reduce total particulate emissions from aggregate storage operations by
up to 90 percent.8
References for Section 11.2.3
1. C. Cowherd, Jr., et al., Development of Emission Factors for Fugitive
Dust Sources, EPA-450/3-74-037, U. S. Environmental Protection Agency,
Research Triangle Park, NC, June 1974.
2. R. Bonn, et al. , Fugitive Emissions from Integrated Iron and Steel
Plants, EPA-600/2-78-050, U. S. Environmental Protection Agency,
Research Triangle Park, NC, March 1978.
3. C. Cowherd, Jr., et al. , Iron and Steel Plant Open Dust Source Fugi-
tive Emission Evaluation, EPA-600/2-79-103, U. S. Environmental Pro-
tection Agency, Research Triangle Park, NC, May 1979.
4. R. Bohn, Evaluation of Open Dust Sources in the Vicinity of Buffalo,
New York, U. S. Environmental Protection Agency, New York, NY, March
1979.
5. C. Cowherd, Jr., and T. Cuscino, Jr., Fugitive Emissions Evaluation,
Equitable Environmental Health, Inc., Elmhurst, IL, February 1977.
6. T. Cuscino, et al. , Taconite Mining Fugitive Emissions Study,
Minnesota Pollution Control Agency, Roseville, MN, June 1979.
7. K. Axetell and C. Cowherd, Jr., Improved Emission Factors for Fugitive
Dust from Western Surface Coal Mining Sources, 2 Volumes, EPA Contract
No. 68-03-2924, PEDCo Environmental, Inc., Kansas City, MO, July 1981.
8. G. A. Jutze, et al., Investigation of Fugitive Dust Sources Emissions
and Control, EPA-450/3-74-036a, U. S. Environmental Protection Agency,
Research Triangle Park, NC, June 1974.
11.2.3-6 EMISSION FACTORS 5/83
E-10
-------
APPENDIX F
GLOSSARY
F-l
-------
Climatic Region - One of the seven areas shown.in Figure 4-5 of the text
for which regional meteorologies have been developed.
Contamination Level - The ratio of the mass of the contaminant in a sample
to the total sample mass.
Dry Day - Day without measurable (0.01 in. or more) precipitation.
Emission Factor - The quantity (mass) of airborne particulate generated per
unit of source extent.
Erosion Potential - Total quantity of erodible particles, in any size range,
present on the surface (per unit area) prior to the onset of erosion.
Factor Analysis - A multivariate statistical technique useful in examining
relationships between sets of intercorrelated observations.
Fastest Mile of Wind - Routinely measured variable which represents the wind
speed corresponding to the whole mile of wind movement which passes by
the 1 mile contact anemometer in the least amount of time.
Friction Velocity - A reference wind velocity defined by the relation u* =
VT/P where T is the Reynold's stress, p the density, and u* the friction
velocity. It is usually applied to motion near the ground where the
shearing stress if often assumed to be independent of height and approx-
imately proportional to the square of the mean velocity. The friction
velocity is, therefore, exactly that velocity for which this square law
would be valid.
Gaussian Dispersion - A mathematical technique used to estimate ambient air
pollution concentration, assuming a bivariate normal distribution with
empirically determined coefficients.
Mechanical Resuspension - The generation of airborne particulate by the
movement of machinery, such as vehicular traffic on an unpaved surface
or the dumping of an aggregate material.
Moisture Content - The mass portion of an aggregate sample consisting of
unbound moisture as determined from weight loss in oven drying with
correction for the estimated difference from total unbound moisture.
Nonerodible elements - Elements on the soil surface which remain firmly in
place during a wind episode and inhibit soil loss by consuming part
of the shear stress of the wind. Examples are clumps of grass or
stones larger than about 1 cm in diameter.
Particle Diameter, Aerodynamic - The diameter of a hypothetical sphere of
unit density (1 g/cm3) having the same terminal settling velocity as
the particle in question, regardless of its geometric size, shape, and
true density.
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Particulate, Respirable - Airborne particulate matter with aerodynamic
diameter of 10 micrometers or less; often referred to as PM10.
Precipitation-Evaporation Index - A climatic factor equal to 10 times the
sum of 12 consecutive monthly ratios of precipitation in inches over
evaporation in inches, which is used as a measure of the annual aver-
age moisture of exposed material on a flat surface of compacted aggre-
gate.
Rayleigh Distribution - A chi-squared distribution with 2 degrees of free-
dom.
Reservoir, Limited - In wind erosion, a surface with a large amount of non-
erodible elements (e.g., stones, vegetation) characterized by a high
threshold velocity and an emission that decays with time.
Reservoir, Unlimited - In wind erosion, a bare surface of finely divided
material (such as agricultural soil) characterized by a low threshold
velocity and a particulate emission rate that is essentially time-
independent.
Roughness Height - A measure of the roughness of a surface over which a fluid
is flowing, defined as follows: z = E/30 where z is the roughness
height and E is the average height 8f surface irregularities.
Silhouette Area - The 2-dimensional frontal view of a nonerodible element
as seen by the wind velocity vector.
Silt Content - The mass portion of an aggregate sample smaller than 75 microm-
eters in physical diameter as determined by dry sieving.
Source Extent - For open dust sources, extent is defined as area or volume
from which emissions emanate. In estimating wind erosion for example,
the source extent is the area (m2) of erodible surface.
STAR (STability ARray) - Multivariate frequency distribution of wind speed,
direction, and atmospheric stability.
Surface Erodibility - Potential for wind erosion losses from an unsheltered
area, based on the percentage of erodible particles (smaller than
0.85 mm in diameter) in the surface material.
Threshold (Friction) Velocity - The wind velocity necessary to initiate soil
erosion. This wind speed depends upon such factors as the presence or
absence of surface crust, soil moisture content, size distribution of
the exposed material, and the presence of nonerodible elements.
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APPENDIX G
ANNUAL AND WORST-CASE OVERLAYS
This appendix contains graphics for use in creating map overlays on
translucent paper, as discussed on pages 43 and 53 of the report. The
overlays must retain the 1:24,000 scale (4.2 cm = 1 km) so that they can
be placed directly on United States Geological Survey (USGS) 7.5 min topo-
graphic maps.
G-l
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