United States
Environmental Protection
Agency
Solid Waste and
Emergency Response
(5305W)
EPA530-R-99-004
May 1999
www.epa.gov/osw
&EPA Industrial Waste Air
Model Technical
Background Document
Printed on paper that contains at least 30 percent postconsumer fiber
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Industrial Waste Air Model
Technical Background Document
Office of Solid Waste
U.S. Environmental Protection Agency
Washington, DC 20460
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Table of Contents
Section
Page
1.0 Introduction 1-1
1.1 Guide for Industrial Waste Management and IWAIR 1-1
1.2 Model Design 1-2
1.2.1 Emission Model .1-2
1.2.2 Dispersion Model ,. 1-2
1.2.3 RiskModel 1-4
1.3 About This Document 1-5
2.0 Model Selection and Overview of CHEMDAT8 2-1
2.1 Model Selection and Overview of CHEMDAT8 2-1
2.2 Emission Model Input Parameters 2-2
2.2.1 Chemical-Specific Input Parameters 2-4
2.2.2 Input Parameters for LAUs and Landfills, and Wastepiles 2-5
2.2.3 Input Parameters for Surface Impoundments 2-8
2.3 Mathematical Development of Emisisons 2-9
2.3.1 Landfills 2-9
2.3.2 Land Application Units 2-10
2.3.3 Wastepiles - 2-13
2.3.4 Aerated or Quiescent Surface Impoundments 2-15
3.0 Development of Dispersion Factors Using ISCST3 3-1
3.1 Development of Dispersion Factor Database 3-2
3.1.1 Industrial D Survey of WMU Sites and Locations (Step 1) 3-3
3.1.2 WMU Strata Classification Based on Survey (Step 2) 3-3
3.1.3 Receptor Data Used for Dispersion Modeling (Step 3) 3-4
3.1.4 Meteorological Data Used for 29 Meterological Stations (Step 4) ... 3-5
3.1.5 Industrial Source Complex Short-term Version 3 Model (Step 5) ... 3-8
3.1.6 Dispersion Factors Available in Program (Step 6) 3-9
3.2 Interpolation of Dispersion Factor 3-10
4.0 Exposure Factors 4-1
4.1 Exposure Duration 4-1
4.2 Inhalation Rate 4-2
4.3 Body Weight 4-3
4.4 Exposure Frequency 4-4
5.0 Development of Inhalation Health Benchmarks 5-1
5.1 Alternate Chronic Inhalation Health Benchmarks Identified 5-1
5.2 Chronic Inhalation Health Benchmarks Derived for IWAIR 5-6
111
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Table of Contents (continued)
Section
Page
6.0 Calculation of Risk/Hazard Quotient or Waste Concentration 6-1
6.1 Forward Calculation of Risk or Hazard Quotient 6-1
6.2 Backward Calculation of Waste Concentration 6-2
6.2.1 Constraints on Backcalculated Waste Concentrations to Reflect
Physical Limitations 6-3
6.2.2 General Newton-Raphson Method 6-3
6.2.3 Application of Newton-Raphson Method to Account for
Aqueous vs. Oily Phase 6-5
7.0 References 7-1
Appendix A - Chemical-Specific Data Used in Emission Modeling A-l
Appendix B - Summary Data for 29 Meteorological Stations B-l
Appendix C - Derivation of Chronic Inhalation Noncancer and Cancer Health
Benchmark Values C-l
Appendix D - Sensitivity Analysis of ISC Air Model D-1
IV
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List of Figures
Figure
3-1
3-2
3-3
Page
Development of ISCST3 dispersion factors 3-2
Meteorological station regions 3-7
Maximum UAC by meteorological location (landfills, LAUs, and surface
impoundments) 3-13
3-4 Maximum UAC by meteorological location (2-m wastepiles) 3-14
3-5 Maximum UAC by meteorological location (5-m wastepiles) 3-15
3-6 Air concentration vs. size of area source 3-16
5-1 Approach used to select chronic inhalation health benchmark values 5-2
6-1 Graphical interpretation of the Newton-Raphson Method 6-4
List of Tables
Table
Page
1-1
Constituents Included in IWAIR 1-3
2-1 Input Parameters for Landfills 2-3
2-2 Input Parameters for Land Application Units (LAUs) 2-4
2-3 Input Parameters for Wastepiles 2-5
2-4 Input Parameters for Aerated and Nonaerated Surface Impoundments (Sis) 2-6
3-1 Final WMU Area Strata Used for ISCST3 Model Runs for Wastepiles 3-3
3-2 Final WMU Area Strata Used for ISGST3 Model Runs for Landfills, Land
Application Units, and Surface Impoundments 3-4
3-3 Meteorological Stations Used in the Air Characteristic Study 3-6
3-4 Maximum Annual Average Unitized Air Concentrations (ug/m3 / ug/s-m2) for
Landfills, Land Application Units, and Surface Impoundments 3-11
3-5 Maximum Annual Average Unitized Air Concentrations (ng/m3 / ng/s-m2) for
Wastepiles 3-12
3-6 Areas Modeled for Landfills, Land Application Units, and Surface Impoundments .. 3-17
3-7 Areas and Source Heights Modeled for Wastepiles 3-17
4-1 Summary of Exposure Factors Used in IWAIR 4-2
4-2 Recommended Inhalation Rates for Residents 4-3
4-3 Recommended Inhalation Rates for Workers 4-3
4-4 Body Weights for Adults, Males and Females Combined, by Age 4-4
4-5 Body Weights for Male and Female Children Combined, Ages 6 Months to 18 Years 4-4
5-1 Chronic Inhalation Health Benchmarks Used in PWAIR 5-3
5-2 Alternate Chronic Inhalation Health Benchmarks 5-6
5-3 Chronic Inhalation Health Benchmarks Derived for IWAIR 5-8
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IWAIR Technical Background Document
Section 1.0
1.0 Introduction
This document provides technical background information on the the Industrial Waste
Air (IWAIR) model. This document is a companion document to the IWAIR User's Guide,
which provides detailed information on how to install and use the model.
1.1 Guide for Industrial Waste Management and IWAIR
The U.S. Environmental Protection Agency (EPA) and representatives from 12 state
environmental agencies have developed a. voluntary Guide for Industrial Waste Management
(hereafter, the Guide) to recommend a baseline of protective design and operating practices to
manage industrial nonhazardous waste throughout the country. The guidance is designed for
facility managers, regulatory agency staff, and the public and reflects four underlying principles:
Adopt a multimedia approach to protect human health and the environment.
Tailor management practices to risk in this enormously diverse universe of waste,
using the innovative user-friendly modeling tools provided in the Guide.^
Reaffirm state and tribal leadership in ensuring protective industrial waste
management and use the Guide to complement their programs.
Foster partnerships among facility managers, the public, and regulatory agencies.
The Guide.recommends best management practices and key factors to take into account
to protect groundwater, surface water and ambient air quality in siting, operation, design,
monitoring, corrective action, and closure and post closure care. In particular, the guidance
recommends risk-based approaches to choose liner systems and waste application rates for
groundwater protection and to evaluate the need for air controls. The CD ROM version of the
Guide includes user-friendly air and groundwater models to conduct these risk evaluations.
The chapter of the Guide entitled "Protecting Air Quality" highlights several key
recommendations:
Adopt controls to minimize particulate emissions.
Determine whether waste management units at a facility are addressed by Clean
Air Act requirements and comply with those requirements.
1-1
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IWAIR Technical Background Document
Section 1.0
If waste management units are not specifically addressed by Clean Air Act
requirements, use IWAIR to assess risks associated with volatile air emissions
from units.
Implement pollution prevention, treatment, or controls to reduce volatile air
emission risks.
EPA developed the IWAIR model and this Technical Background Document to
accompany the Guide for use in evaluating inhalation risks. Workers and residents in the vicinity
of a waste management unit (WMU) may be exposed to volatile chemicals from the WMU in the
air they breathe. Exposure to some of these chemicals at sufficient concentrations may cause a
variety of cancer and noncancer health effects (such as developmental effects in the fetus or
neurological effects in an adult). With a limited amount of site-specific information, IWAIR can
estimate whether specific wastes and management practices may pose an unacceptable risk to
human health.
1.2 Model Design
IWAIR is an interactive computer program with three main components: an emissions
model; a dispersion model to estimate fate and transport of constituents through the atmosphere
and determine ambient air concentrations at specified receptor locations; and a risk model to
calculate either the risk to exposed individuals or waste constituent concentrations that can be
managed in the unit while being protective of human health. The program requires only a
limited amount of site-specific information, including facility location, WMU characteristics,
waste characteristics, and receptor information. A brief description of each component follows.
The IWAIR Technical Background Document.
1.2.1 Emission Model
The emission model uses waste characterization, WMU, and facility information to
estimate emissions for 95 constituents identified in Table 1-1. The emission model selected for
incorporation into IWAIR is EPA's CHEMDAT8 model. This model has undergone extensive
review by both EPA and industry representatives and is publicly available from EPA's Web page
(http://www.epa.gov/ttn/chief/software.html).
To facilitate emission modeling with CHEMDAT8, IWAIR prompts the user to provide
the required waste- and unit-specific data. Once these data are entered, the model calculates and
displays chemical-specific emission rates. If users decide not to develop or use the CHEMDAT8
rates, they can enter their own site-specific emission rates (g/m2-s).
1.2.2 Dispersion Model
IWAIR's second modeling component estimates dispersion of volatilized contaminants
and determines air concentrations at specified receptor locations using default dispersion factors
developed with EPA's Industrial Source Complex, Short-Term Model, version 3 (ISCST3).
1-2
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IWAIR Technical Background Document
Section 1.0
Table 1-1. Constituents Included in IWAIR
75070 Acetaldehyde
67641 Acetone
75058 Acetonitrile
107028 Acrolein
79061 Acrylamide
79107 Acrylic acid
107131 Acrylonitrile
107051 Allyl chloride
62533 Aniline
71432 Benzene
92875 Benzidine
50328 Benzo(a)pyrene
75274 Bromodichloromethane
106990 Butadiene, 1,3-
75150 . Carbon disulfide
56235 Carbon tetrachloride
108907 Chlorobenzene
124481 Chlorodibromomethane
67663 Chloroform
95578 Chlorophenol, 2-
126998 , Chloroprene
10061015 cis-1,3-Dichloropropylene
1319773 Cresols (total)
98828 Cumene
108930 Cyclohexanol
96128 Dibromo-3-chloropropane, 1,2-
75718 Dichlorodifluoromethane
107062 Dichloroethane, 1,2-
75354 Dichloroethylene, 1,1-
78875 Dichloropropane, 1,2 -
57976 Dimethylbenz[a]anthracene, 7,12-
95658 Dimethylphenol, 3,4-
121142 Dinitrotoluene, 2,4-
123911 Dioxane, 1,4-
122667 Diphenylhydrazine, 1,2-
106898 Epichlorohydrin
106887 Epoxybutane, 1,2-
111159 Ethoxyethanol acetate, 2-
110805 Ethoxyethanol, 2-
100414 Ethylbenzene
106934 Ethylene dibromide
107211 Ethylene glycol
75218 Ethylene oxide
50000 Formaldehyde
98011 Furfural
87683 Hexachloro-1,3-butadiene
118741 Hexaehlorobenzene
77474 Hexachlorocyclopentadiene
67721 Hexachloroethane
78591 Isophorone
7439976 Mercury
67561 Methanol
110496 Methoxyethanol acetate, 2-
109864 Methoxyethanol, 2-
74839 Methyl bromide
74873 Methyl chloride
78933 Methyl ethyl ketone
108101 Methyl isobutyl ketone
80626 Methyl methacrylate
1634044 Methyl tert-butyl ether
56495 Methylcholanthrene, 3-
75092 Methylene chloride
68122 N,N-Dimethyl formamide
91203 Naphthalene
110543 n-Hexane
98953 Nitrobenzene
79469 Nitropropane, 2-
55185 N-Nitrosodiethylamine
924163 N-Nitrosodi-n-butylamine
930552 N-Nitrosopyrrolidine
95501 o-Dichlorobenzene
95534 o-ToIuidine
106467 p-Dichlorobenzene
108952 Phenol
85449 Phthalic anhydride
75569 Propylene oxide
110861 Pyridine
100425 Styrene
1746016 TCDD, 2,3,7,8-
630206 Tetrachloroethane, 1,1,1,2-
79345 Tetrachloroethane, 1,1,2,2-
127184 Tetrachloroethylene
108883 Toluene
10061026 trans-1,3-Dichloropropylene
75252 Tribromomethane
76131 Trichloro-1,2,2-trifluoroethane, 1,1,2-
120821 Trichlorobenzene, 1,2,4-
71556 Trichloroethane, 1,1,1-
79005 Trichloroethane, 1,1,2-
79016 Trichloroethylene
75694 Trichlorofluoromethane
121448 Triethylamine
108054 Vinyl acetate
75014 Vinyl chloride
1330207 Xylenes
1-3
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IWAIR Technical Background Document
Section 1.0
ISCST3 was run to calculate dispersion for a standardized unit emission rate (1 ug/m2 - s) to
obtain a unitized air concentration (UAC), also called a dispersion factor, which is measured in
micrograms/cubic meter per microgram/square meter-second. The total air concentration
estimates are then developed by multiplying the constituent-specific emission rates derived from
CHEMDAT8 (or from another source) with a site-specific dispersion factor. Running ISCST3
to develop a new dispersion factor for each location/WMU is very time consuming, and requires
extensive meteorological data and technical expertise. Therefore, IWAIR incorporates default
dispersion factors developed by ISCST3 for many separate scenarios designed to cover a broad
range of unit characteristics, including:
29 meteorological stations chosen to represent the nine general climate regions of
the continental United States
4 unit types
14 surface area sizes for landfills, land application units, and surface
impoundments and 7 surface area sizes and 2 heights for wastepiles
6 receptor distances from the unit (25, 50, 75, 150, 500, 1,000 meters)
16 directions in relation to the edge of the unit.
The default dispersion factors were derived by modeling each of these scenarios, then
choosing as the default the maximum dispersion factor for each waste management unit/surface
area/meteorological station/receptor distance combination.
Based on the size and location of a unit, as specified by a user, IWAIR selects an
appropriate dispersion factor from the default dispersion factors in the model. If the user
specifies a unit surface area that falls between two of the sizes already modeled, a linear
interpolation method will estimate dispersion in relation to the two closest unit sizes.
Alternatively, a user may enter a site-specific dispersion factor developed by conducting
independent modeling with ISCST3 or with a different model and proceed to the next step, the
risk calculation.
1.2.3 Risk Model
The third component combines the constituent's air concentration with receptor exposure
factors and toxicity benchmarks to calculate either the risk from concentrations managed in the
unit or the waste concentration (Cw) in the unit that must not be exceeded to protect human
health. In calculating either estimate, the model applies default values for exposure factors,
including inhalation rate, body weight, exposure duration, and exposure frequency. These
default values are based on data presented in EPA's Exposure Factors Handbook (U.S. EPA,
1997a) and represent average exposure conditions. IWAIR maintains standard health
benchmarks (cancer slope factors for carcinogens and reference concentrations for
noncarcinogens) for 95 constituents. These health benchmarks are from the Integrated Risk
Information System (IRIS) and the Health Effects Assessment Summary Tables (HEAST) (U.S.
EPA, 1997b, 1998a). The IWAIR uses these data to perform either a forward calculation to
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JWA7R Technical Background Document
Section 1.0
obtain risk estimates or a backward calculation to obtain protective waste concentration
estimates.
1.3 About This Document
The remainder of this background document is organized as follows:
Section 2, Source Emission Estimates Using CHEMDAT8, describes the
CHEMDAT8 model used to calculate emissions
Section 3, Development of Dispersion Factors Using ISCST3, describes how
dispersion factors were developed using ISCST3 and how these are used in the
model
Section 4, Exposure Factors, describes the exposure factors used in the model
Section 5, Development of Inhalation Health Benchmarks, describes the health
benchmarks used in the model, and how these were developed if health
benchmarks were not available from standard sources
Section 6, Calculation of Risk/Hazard Quotient or Waste Concentration,
describes the forward risk calculation, and the iterative method used by the model
for performing backward calculations
Section 1, References.
1-5
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IWAIR Technical Background Document
Section 2.0
2.0 Source Emission Estimates Using
CHEMDAT8
This section describes the CHEMDAT8 emission model used to develop the emission
estimates for each WMU. Section 2.1 describes why CHEMDAT8 was chosen and provides an
overview of CHEMDAT8. Section 2.2 describes the input parameters. Section 2.3 describes the
important modeling assumptions and equations used to convert IWAIR inputs to those needed
for CHEMDAT8 and to calculate actual emission rates from the fraction emitted estimated by
CHEMDAT8.
2.1 Model Selection and Overview of CHEMDAT8
EPA's CHEMDAT8 model was selected as the model to estimate volatile emissions rates
from the waste management units in IWAIR. CHEMDAT8 meets the goals that were considered
during the model selection process. These goals were to:
Provide emission estimates that are as accurate as possible without
underestimating the contaminant emissions
Provide a relatively consistent modeling approach (in terms of model complexity
and conservatism) for each of the different emission sources under consideration
Undergo extensive peer review and be widely accepted by both EPA and industry
Be publicly available for use in more site-specific evaluations.
The CHEMDAT8 model was originally developed in projects funded by EPA's Office of
Research and Development (ORD) and Office of Air Quality Planning and Standards (OAQPS)
to support National Emission Standards for Hazardous Air Pollutants (NESHAPs) from sources
such as tanks, surface impoundments, landfills, wastepiles, and land application units for a
variety of industry categories including chemical manufacturers, pulp and paper manufacturing,
and petroleum refining. It also has been used to support the emissions standards for hazardous
waste treatment, storage, and disposal facilities (U.S. EPA, 1991) regulated under Subpart CC
rules of the Resource Conservation and Recovery Act (RCRA), as amended in 1984. The
CHEMDAT8 model is publicly available and has undergone extensive review by both EPA and
industry representatives.
The CHEMDAT8 model considers most of the competing removal pathways that might
limit air emissions, including adsorption and hydrolysis for surface impoundments and
2-1
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IWAIR Technical Background Document
Section 2.0
biodegradation for all units. While the land-based units do not consider adsorption per se,
volatilization is limited by the relative air porosity of the soil or waste matrix. Hydrolysis is not
considered in the land-based units, even for soil moisture or percolating rainwater. Adsorption is
the tendency of a chemical or liquid media to attach or bind to the surface of particles in the
waste and therefore not volatilize into the air. Biodegradation is the tendency of a chemical to be
broken down or decomposed into less-complex chemicals by organisms in the waste or soil.
Similarly, hydrolysis is the tendency of a chemical to be broken down or decomposed into less
complex chemicals by reaction with water. Chemicals that decompose due to either
biodegradation or hydrolysis have lower potential for emission to the air as gases because the
mass of chemical is reduced by these processes. Biodegradation and hydrolysis may generate
daughter products; however, for the chemicals covered by IWAIR, the daughter products were
found to be less toxic than the parents. CHEMDAT8 models only the parent. Loss of
contaminant by leaching or runoff is not included in the CHEMDAT8 model. Both leaching and
runoff are a function of a chemical's tendency to become soluble in water and follow the flow of
water (e.g., due to rainfall) down through the soil to groundwater (leaching) or downhill to
surface water (runoff). These two mechanisms would also result in less chemical being available
for emission to the air as gases or particles. As such, CHEMDAT8 is considered to provide
reasonable to slightly high (environmentally conservative) estimates of air emissions from the
various emission sources.
EPA's CHEMDAT8 model is provided as a modular component of IWAIR. For
complete documentation on the CHEMDAT8 model, refer to documents available on
EPA's web page. The CHEMDAT8 spreadsheet model and model documentation may be
downloaded at no charge from EPA's web page (http://www.epa.gov/ttn/chief/software.html).
This document provides information about CHEMDATS that is pertinent to the IWAIR program;
however, it does not document the CHEMD ATS equations. CHEMD ATS is a Lotus 1-2-3
spreadsheet that includes analytical models for estimating volatile organic compound emissions
from treatment, storage, and disposal facility processes under user-specified input parameters.
The original CHEMD ATS spreadsheet was converted to Visual Basic code for use in IWAIR. In
addition, the chemical-specific data in the original code were evaluated for accuracy. Some of
these values have been changed to reflect newer or better information. A list of the physical-
chemical properties is provided in Appendix A of this document. Extensive testing was
performed to ensure that the coded version produces results identical to the spreadsheet version.
CHEMD ATS calculates the fraction of a waste constituent that is released to air and, for
surface impoundments, the amount adsorbed and the amount remaining in the effluent. The
fraction emitted is converted to annual emissions in the appropriate units required for the IWAIR
program calculations.
2.2 Emission Model Input Parameters
Emission modeling using CHEMD ATS is conducted using unit-specific data entered by
the user. Most of the inputs are used directly by CHEMD ATS; a few are used to calculate inputs
for CHEMD ATS. The IWAIR program provides default input data for some parameters. For
example, the temperature and windspeed for a WMU site are automatically used as a default for a
site once the site is assigned to one of the 29 meteorological stations in the IWAIR program.
Users may choose to override the default data and enter their own estimates for these parameters.
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IWAIR Technical Background Document
Section 2.0
Thus, modeling emissions using CHEMDAT8 can be performed with a very limited amount of
site-specific information using the default data that are provided. The unit-specific input
parameters required to run IWAIR and the default values for those, parameters are listed in
Tables 2-1 through 2-4.
This section discusses the various parameters that significantly impact the estimated
emission rates. Inputs that influence these rates include input parameters specific to the physical
and chemical properties of the constituent being modeled, the physical and chemical
characteristics of the waste material being managed, input parameters specific to the process and
operating conditions of the WMU being modeled, and meteorological parameters.
A general discussion of the physical and chemical properties of the constituents is
provided in the Section 2.2.1. Critical input parameters for the remaining sets of inputs are
discussed for land-based WMUs in Section 2.2.2 and for surface impoundments in Section 2.2.3.
The input parameters used in IWAIR differ in some respects from those needed by CHEMDAT8.
When the CHEMDAT8 inputs are not readily available but can be calculated from more readily
available data, IWAIR uses the more readily available input parameters. The equations used to
convert these to the CHEMDAT8 inputs are documented in Section 2.3.
Table 2-1. Input Parameters for Landfills
%
«& -s4-
;v 4*
^Input Parameter ^ *
:*£*
; Default
Value
-R*ng/
^"' -* , Basis'*',
Unit Design and Operating Parameters
Operating Life of Landfill
Total Area of Landfill - All Cells
Average Depth of Landfill Cell
Total Number of Cells in Landfill
Average Annual Quantity of Waste
Disposed
years
m2
m
unitless
Mg/yr
None
None
None
None
None
0-100
0-1 07
0-20
0-10,000
0-1. 2x1 07
Required input
Required input
Required input
Required input
Required input
Waste Characterization Information
Dry Bulk Density of Waste in Landfill
Average Molecular Weight of Oily Waste
Total Porosity of Waste
Air-filled Porosity of Waste
g/cm3
g/gmol
volume
fraction
volume
fraction
1.4
147
0.50
0.25
0.8-3
18-400
0-1
0-total
porosity
ERG and Abt (1992). Uses a default of 1 .4
g/cm3 for waste sludge
U.S. EPA (1989). Uses sludge density of 1.01
g/cm3
RTI (1988). Default input for CHEMDAT8
landfill
U.S. EPA (1991). Input used for all active
landfills
RTI (1988). Default input for CHEMDAT8
landfill
ERG and Abt (1992). Uses default of 0.40
Schroeder et al. (1994). Halogenated
Aliphatics used 0.46
U.S. EPA (1991). Input used for all active
landfills
RTI (1988). Default input for CHEMDAT8
landfill
Schroeder et al. (1994). Halogenated
Aliphatics used ranqe = 0.16 to 0.31
"Parameters with ranges shown as "0-x" must be greater than zero
2-3
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IWAIR Technical Background Document
Section 2.0
Table 2-2. Input Parameters for Land Application Units (LAUs)
Input Parameter
Units
Default
Value
Range9
/jf f * \ y
Basis
Unit Design and Operating Parameters
Operating Life of LAU
Tilling Depth of LAU
Surface Area of LAU
Average Annual Quantity of Waste
Applied
Number of Applications per Year
years
m
m2
Mg/yr
yr1
None
None
None
None
None
0-100
0-1
0-1 07
0-5.2x1 07
0-12
Required input
Required input
Required input
Required input
Required input
Waste Characterization Information
Dry Bulk Density of Waste/Soil Mixture
Average Molecular Weight of Oily Waste
Total Porosity of Waste/Soil Mixture
Air-filled Porosity of Waste/Soil
g/cm3
g/gmol
volume
fraction
volume
fraction
1.3
282
0.61
0.5
0.8-3
18-400
0-1
0-total
porosity
Loehr et al. (1993). Reports density = 1.39
g/cm3 for surface soil
U.S. EPA (1992). Uses a default value of
1 .4 g/cm3 for sewage sludge/soil in LAU
Li and Voudrias (1994). Wet soil column
density = 1 .03 g/cm3
RTI (1988). Default input for CHEMDAT8
LAU
U.S. EPA (1991). Default input used for all
model LAU.
RTI (1988). Default input for CHEMDAT8
LAU
U.S. EPA (1992). Uses default of 0.4
Loehr et al. (1993). Reports porosity = 0.49
for surface soil
Li and Voudrias (1994). Wet soil column
porosity = 0.558
U.S. EPA (1991). Default input used for all
model LAU
RTI (1988). Default input for CHEMDAT8
LAU
parameters witn ranges shown as u-x must be greater tan zero.
2.2.1 Chemical-Specific Input Parameters
Chemical-specific input parameters are those parameters that relate to the physical or chemical
properties of each individual chemical. The values of these parameters are different for each of
the 95 chemicals covered by IWAIR. Key chemical-specific input parameters that have a
significant impact on modeled emissions include: air-liquid equilibrium partitioning coefficients
(vapor pressure or Henry's law constant), liquid-solid equilibrium partitioning coefficient (log
octanol-water partition coefficient for organics), biodegradation rate constants, and liquid and air
diffusivities. The hazardous waste identification rule (HWIR) chemical properties database
(RTI, 1995) was used as the primary data source for the physical and chemical properties for the
constituents being modeled. This chemical properties database provided the following chemical-
specific input parameters: molecular weight, vapor pressure, Henry's law constant, solubility,
liquid and air diffusivities, log octanol-water partition coefficient, and the soil biodegradation
rate constants. The CHEMDAT8 chemical properties database (U.S. EPA, 1994a) was used as a
secondary data source for the physical and chemical properties for the constituents being
modeled. This chemical properties database provided the following chemical-specific input
parameters: density, boiling point, Antoine's coefficients (for adjusting vapor pressure to
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IWAIR Technical Background Document
Section 2.0
Table 2-3. Input Parameters for Wastepiles
Unit Design and Operating Parameters
Height of Wastepile
Surface Area of Wastepile
Average Annual Quantity of Waste Added
to waste pile
Dry Bulk Density of Waste
m
m2
Mg/yr
g/cm3
None
None
None
1.4
0-10
0-1. 5x1 07
0-1 06
0.8-3
Required input
Required input
Required input
ERG and Abt (1992). Uses default of 1 .4
g/cm3 for waste sludge
U.S. EPA (1991). Uses default of 1 .8 g/cm3
for wastepile
RTI (1988). Uses "liquid in fixed waste"
density of 1 .16 g/cm3
U.S. EPA (1989). Uses sludge density of
1.01 g/cm3
Waste Characterization Information
Average Molecular Weight of Waste
Total Porosity of Waste
Air-filled Porosity of Waste
g/gmol
volume
fraction
volume
fraction
147
0.5
0.25
18-400
0-1
0-total
porosity
RTI (1988). Default input for CHEMDAtS
U.S. EPA (1991). Input used for all model
wastepiles
RTI (1988). Default input for CHEMDATS
wastepile
U.S. EPA (1991). Input used for all model
wastepiles
RTI (1 988). Default input for CHEMDATS
wastepile
"Parameters with ranges shown as "0-x" must be greater than zero.
temperature), and biodegradation rate constants for surface impoundments. The biodegradation
rate constants in the downloaded CHEMDATS database file were compared with the values
reported in the summary report that provided the basis for the CHEMDATS surface
impoundment biodegradation rate values (Coburn et al., 1988). Surface impoundment
biodegradation rate constants for compounds with no data were assigned biodegradation rates
equal to the most similar compound in the biodegradation rate database. The specific chemical
properties input database used for the emission modeling is provided in Appendix A.
2.2.2 Input Parameters for LAUs, Landfills, and Wastepiles
The input parameters for land-based units are presented in Tables 2-1 through 2-3.
Unit Design and Operating Parameters. The annual waste quantity is a critical site-specific
input parameter. This parameter, along with assumptions regarding the frequency of
contaminant addition and the dimensions of the unit, combine to influence a number of model
input parameters. Because these are so critical, and because the values of these parameters for a
specific unit to be modeled should be readily available to the user, no default values are provided
for these parameters.
2-5
-------
IWAIR Technical Background Document
Section 2.0
Table 2-4. Input Parameters for Aerated and Nonaerated Surface Impoundments (Sis)
Input Parameter
Units
' Default
Value *
Range'
' ""' X'-#Y x '
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IWAIR Technical Background Document
Section 2.0
Waste Characterization. One of the
most important inputs for emission estimates
is whether the waste is aqueous or oily. This
input tells the CHEMDAT8 model which
equilibrium partitioning model to use
between the liquid and gas phases. For oily
(organic) wastes, the model uses Raoult's law
and the liquid-to-air partition coefficient
becomes proportional to the contaminant's
partial vapor pressure. For aqueous Wastes,
the model uses Henry's law and the liquid-to-
air partition coefficient becomes proportional
to the contaminant's Henry's law coefficient.
A useful rule of thumb for determining if a
waste is aqueous or oily is to determine if the
waste contains more than 10 percent organics.
If it does, emissions are more accurately modeled as oily. Therefore, for forward calculations, if
the total concentration of all chemicals entered exceeds 100,000 ppm (or 10 percent), IWAIR
automatically considers the waste oily. However, the user can designate wastes as oily even if
the chemicals being modeled do not exceed 10 percent of the waste stream. For backward
calculations, IWAIR calculates both an aqueous and an oily emission rate. Section 6 describes
how the model determines which of these emission rates to use.
CHEMDAT8 is fairly sensitive to the total porosity and air porosity values that are used.
Total porosity includes air porosity and the space occupied by oil and water within soil. Total
porosity is related to bulk density of the waste (which is also an input) as follows:
Organic Chemicals
The IWAIR model covers only organic
chemicals, with the exception of mercury.
Organic chemicals are those pertaining to or
derived from living organisms. All organic
chemicals contain carbon and most also contain
hydrogen, although there are some substituted
carbon compounds that do not contain hydrogen
but are generally considered to be organics
(e.g., carbon tetrachloride). However,
elemental carbon and certain other carbon-
containing compounds (e.g., carbon dioxide) are
considered inorganic compounds.
r, = 1 -
BD
(2-1)
where
BD
Ps
total porosity (unitless)
bulk density (g/cm3)
particle density (g/cm3)
A typical value for ps is 2.65 g/cm3. Default values are provided for waste bulk density,
total porosity, and air-filled porosity, but the user is strongly encouraged to enter site-specific
data if available.
Meteorological Conditions. Two meteorological parameters are used as inputs to
CHEMDAT8: annual average windspeed and temperature. The CHEMDAT8 model is
insensitive to windspeeds for long-term emission estimates from land-based units. Temperature
affects the air diffusivity, which affects the volatilization rate. Consequently, temperature is the
only meteorological data input that potentially impacts the emissions results for the CHEMDAT8
model for the land-based WMU. By default, IWAIR uses the annual average temperature and
2-7
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1WAIR Technical Background Document
Section 2.0
windspeed for the meteorological station identified as most representative for the site location.
However, the user may override these with site-specific data.
2.2.3 Input Parameters for Surface Impoundments
The input parameters for surface impoundments are presented in Table 2-1.
Unit Design Data. The annual waste quantity (flow rate), the dimensions of the surface
impoundment, and whether or not the impoundment is aerated are critical input parameters for
impoundments. Because these are so critical, and because the values of these parameters for a
specific unit to be modeled should be readily available to the user, no default values are provided
for these parameters.
Aeration. Factors that impact the relative surface area of turbulence and the intensity of
that turbulence are important in determining the rate of volatilization of the'chemicals in aerated
surface impoundments. The aerated surface impoundment model has several input parameters
that impact the degree and intensity of the turbulence created by the aeration (or mixing). The
aerated surface impoundment model is most sensitive to the fraction aerated. The total power,
power per aerator (number of aerators), and impeller diameter have some impact on the emission
results. The other parameters have only a slight impact on the estimated emissions. Default
values are provided for these inputs, but the user is strongly encouraged to enter site-specific
values if available.
Meteorological Conditions. Meteorological inputs are also important for the surface
impoundment emission model. Emissions estimates for nonaerated impoundments are impacted
by both temperature and windspeed. Emissions for aerated impoundments are predominantly
driven by the turbulent area and associated mass transfer coefficients; therefore, the emissions
from aerated impoundments are not strongly impacted by the windspeed; they are impacted by
temperature. Note that, dependent on the residence time of the waste in the impoundment, the
temperature of the waste is not expected to vary significantly with changing atmospheric
temperatures. Therefore, annual average temperatures are used to estimate the average waste
temperature in the impoundment. By default, IWAIR uses the annual average temperature and
windspeed for the meteorological station identified as most representative for the site location.
However, the user may override these with site-specific data.
Waste Characterization Inputs. Factors that influence the rate of biodegradation are
important in determining emissions from surface impoundments. Unlike the biodegradation rate
model that was used for the land-based units, the biodegradation rate model used in
CHEMDAT8 for surface impoundments is dependent on the amount of active biomass in the
WMU. Therefore, the active biomass concentration is a critical parameter for impoundments. A
default value is provided, but the user is encouraged to enter a site-specific value if available.
The total suspended solids in, total organics in, and total biorate impact the rate of biomass
production and subsequently the amount of contaminant that is absorbed onto the solids. These
inputs, however, have little or no impact on the estimated emission rates for most of the
contaminants modeled in this analysis. Default values are provided, but the user is strongly
encouraged to enter site-specific values if available.
2-8
-------
IWAIR Technical Background Document
Section 2.O
2.3 Mathematical Development of Emissions
This section describes how the inputs described in Section 2.2 are used to calculate the
inputs needed for CHEMDAT8 and how the output of CHEMDAT8 (the fraction emitted) is
converted to a mass emission rate for use in IWAIR. This section does not document the
CHEMDAT8 model equations used to calculate fraction emitted from the CHEMDAT8 inputs.
For documentation on CHEMDAT8, refer to the model documentation, which may be
downloaded from EPA's web site (http://www/epa.gov/ttn/chief/software.html) at no charge.
2.3.1 Landfills
The basic assumptions used for modeling landfills are as follows:
The landfill operates for tlife years filling N cells of equal size sequentially.
The active cell is modeled as being instantaneously filled at time t=0, and remains
open for t]ife/N years.
Emissions are only calculated for one cell for t,ife/N years (it is assumed that the
cell is capped after tlife/N years and that the emissions from the capped landfill
cells are negligible); the time of calculation is calculated as follows:
tlife x 365.25 x 24 x 3,600
calc
N
(2-2)
where
tcalc = time of calculation (s)
tlife = lifetime of unit (yr)
N = total number of cells (unitless)
365.25 = units conversion (d/yr)
24 = units conversion (h/d)
3,600 = units conversion (s/h).
The modeled waste is homogeneous with an initial concentration of 1 mg/kg for
backward calculations or is user-specified for forward calculations; the landfill
may also contain other wastes with different properties.
Loading is calculated from the annual waste quantity and the size of the landfill as
follows:
L =
^annual
Atotal X Dtotal
(2-3)
2-9
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IWAIR Technical Background Document
Section 2.0
where
L
^cannual
total
loading rate (Mg/m3 = g/cm3)
annual waste quantity (Mg/yr)
lifetime of unit (yr)
total area of unit (m2)
total depth of unit (m).
Note that if the unit is a monofill receiving only the waste modeled, the loading should equal the
bulk density entered by the user. If the unit receives other wastes in addition to the waste
modeled, the loading should be less than the bulk density of the waste. The loading cannot
exceed the bulk density of the waste; if this occurs, the user will get an error message asking for
the inputs to be changed.
Landfill cell areas and depth are used for the model run: Areacell = Area^ / N;
Depthcell = Depthtotal.
Biodegradation is not modeled.
CHEMDAT8 is used to calculate the emission fraction for each of the selected
contaminants. The average emission rate for the landfill can be calculated as follows:
E =
annual
X
X L X femitted
Acell x BD x 365.25 x 24 x 3,600
(2-4)
where
E
L
f
* emitted
BD
365.25
24
3,600
emission rate (g/m2 - s)
annual waste quantity (Mg/yr)
concentration of chemical in waste (mg/kg = g/Mg)
loading rate (Mg/m3 = g/cm3)
emission fraction (unitless)
area of cell (m2)
bulk density of waste in landfill (g/cm3)
units conversion (d/yr)
units conversion (h/d)
units conversion (s/h).
2.3.2 Land Application Units
The assumptions used for modeling land application units are as follows:
The land treatment unit operates for tlife years.
Waste application occurs Nappl per year.
2-10
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IWAJR Technical Background Document
Section 2.0
Emissions are calculated for one application using a time of calculation as
follows:
365.25 x 24 x 3,600
Lcalc
N.
(2-5)
appl
where
*Nappl
365.25
24
3,600
time of calculation (s)
number of applications per year (yr"1)
units conversion (d/yr)
units conversion (h/d)
units conversion (s/h).
The waste is homogeneous with an initial concentration of 1 mg/kg for backward
calculations or is user-specified for forward calculations.
Loading is calculated from the annual waste quantity and the size of the LAU as
follows:
'annual
xlOO
NapPi X A x dtm
(2-6)
where
L
Nappl
A
100
loading rate (Mg/m3 = g/cm3)
annual quantity of waste (Mg/yr)
number of waste applicatons per year (yr"1)
area of unit (m2)
tilling depth (cm)
units conversion (cm/m).
Biodegradation is modeled.
The CHEMDAT8 model calculates the fraction emitted and biodegraded for each
chemical to the time of one application. However, for the land treatment unit, additional waste is
added to and mixed with the oil/waste matrix after the modeled time step. It is assumed that the
volume of the land treatment unit remains constant. Therefore, as more waste is applied, it is
assumed that an equal volume of waste/soil mixture becomes buried or otherwise removed from
the active tilling :depth. For the first application, the mass of constituent in the LAU is:
= M
Qx C
annual waste
start>1
N
(2-7)
appl
2-11
-------
/ WAIR Technical Background Document
Section 2.0
where
M0 =
Mstart|1 =
N
appl
mass of chemical in unit at time 0 (g)
mass of chemical in unit at start of time step 1 (g)
annual quantity of waste (Mg/yr)
concentration of chemical in waste (mg/kg = g/Mg)
number of waste applications per year (yr"1).
The mass of constituent in the LAU at the end of the first time of calculation (just prior to
more waste being added) is
M
end,l
X
- fb.o)
(2-8)
where
Mcndil =
M =
Ario
^emitted
mass of chemical in unit at end of time step 1 (g)
mass of chemical in unit at time 0 (g)
fraction emitted (unitless).
fraction biodegraded (unitless).
The generalized equation for the starting mass of contaminant (just after any waste
application number, n) is
MStart,n = Mo + Mend.n-i X
_ appl
dun
(2-9)
where
Ms,
tart.n
M,
da
dtill
cnd,n-l
ippl
mass of chemical in unit at start of time step n (g)
mass of chemical in unit at time 0 (g)
mass of chemical in unit at end of time step n-1 (g)
depth of waste applied (cm) - see Equation 2-10.
tilling depth (cm).
Depth of waste applied is calculated as
'annual
x 100
appl
Nappl X BD X A
(2-10)
where
Nappl
BD
A
100
depth of waste applied (cm)
annual quantity of waste (Mg/yr)
number of applications per year f (yr"1)
bulk density of waste (g/cm3 = Mg/m3)
area of unit (m2)
units conversion (cm/m).
2-12
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IWAIR Technical Background Document
Section 2.0
Note that ddll must exceed dapp, and should probably be at least three to four times dappl. The user
will be warned if this condition is not met.
The generalized equation for the ending mass of constituent in the LAU for any waste
application number, n, (just prior to the n+1 waste application) is
M
^start.n X
~
emitted
~ fbio)
(2-11)
where
M
end,n
f
emitted
mass of chemical in unit at end of time step n (g)
mass of chemical in unit at start of time step n (g)
fraction emitted (unitless)
fraction biodegraded (unitless).
The generalized equation for the mass of constituent emitted during any application
period (time of calculation) is
emitted,n start.n X emitted
(2-12)
where
M,
M
emitted.n
start,n
'emitted
mass of chemical emitted in time step n (g)
mass of chemical in unit at start of time step n (g)
fraction emitted (unitless).
For each time period, the emission rate is calculated as follows:
M
'emitted.n
x A
(2-13)
where
En
M,
emitted.n
t,
calc
A
emission rate in time step n (g/m2-s)
mass of chemical emitted in time step n (g)
time of calculation (s) - see Equation 2-5
area of unit (m2).
The starting, ending, and emitted mass of constituent is calculated for the life of the unit
plus 30 years. For noncarcinogens, the maximum En is used in calculating hazard quotient. For
carcinogens, IWAIR determines the highest 30-year average of the En values.
2.3.3 Wastepiles
The modeling assumptions used for modeling wastepiles are as follows:
2-13
-------
IWAIR Technical Background Document
Section 2.0
The wastepile is modeled as a batch process with the waste remaining in the
wastepile for the average residence time (Res.Time). This encompasses two
scenarios:
1. The wastepile is instantaneously filled at time t=0 and remains dormant
(no other waste added) for Res.Time, at which time the entire wastepile is
emptied and completely filled with fresh waste.
2. An annual quantity of waste is added to the wastepile consistently (in
small quantities) throughout the year and a corresponding quantity of old
waste is removed from the wastepile (so that the wastepile becomes a
steady-state plug flow system).
The waste added is homogeneous with an initial concentration of 1 mg/kg for
backward calculations or is user-specified for forward calculations.
Biodegradation is modeled.
Loading is the bulk density of the waste material.
Time of calculation = average Res.Time of waste in the wastepile as follows:
A x D x BD x 365.25 x 24 x 3,600
calc
where
'calc
A
D
BD
365.25
24
3,600
'annual
time of calculation (s)
area of unit (m2)
depth of unit (m)
bulk density of waste (g/cm3 = Mg/m3)
annual waste quantity (Mg/yr)
units conversion (d/yr)
units conversion (h/d)
units conversion (s/h).
(2-14)
The average emission rate for the wastepile can be calculated as follows:
E =
) x C x f
'-annual waste emitted
A x 365.25 x 24 x 3,600
(2-15)
ceii
where
^cannual
^waste
'emitted
emission rate (g/m2 - s)
annual waste quantity (Mg/yr)
concentration of chemical in waste (mg/kg = g/Mg)
emission fraction (unitless)
2-14
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IWAIR Technical Background Document
Section 2.0
AceU = area of cell (m2)
365.25 = units conversion (d/yr)
24 = units conversion (h/d)
3,600 = units conversion (s/h).
2.3.4 Aerated or Quiescent Surface Impoundments
The basic modeling assumptions used for modeling surface impoundments include:
The WMU operates at steady state
The WMU is well mixed
Waste has an influent concentration of 1 mg/L (= 1 g/m3) for backward
calculations or is user-specified for forward calculations
Biodegradation rate is first order with respect to biomass concentrations
Biodegradation rate follows Monod kinetics with, respect to contaminant
concentrations
Hydrolysis rate is first order with respect to contaminant concentrations.
The surface area, depth, and flow rate are all directly specified by the model units. The
CHEMDAT8 model is used to calculate the emission fractions for the model units, and the
emission rate, in grams per square meter per second, is calculated from the fraction emitted, the
flow rate, waste concentration, and the surface area as follows:
E =
'flow
p
^-
f
Emitted
(2-16)
where
"emitted
A
emission rate (g/m2 - s)
flow rate (mVs)
influent concentration (g/m3)
fraction emitted (unitless)
area of unit (m2).
2-15
-------
-------
IWAIR Technical Background Document
Section 3.0
3.0 Development of Dispersion Factors Using
ISCST3
In assessing the potential risk from an emissions source, one of the properties that must
be evaluated is the ability of the atmosphere in the local area to disperse the chemicals emitted.
When a chemical is emitted, as the resulting plume moves away from the source, it will begin to
spread both horizontally and. vertically at a rate that is dependant on local atmospheric
conditions. The more the plume spreads (i.e., disperses), the lower the concentration of the
emitted chemicals will be in the ambient air. Dispersion models are designed to integrate
meteorologic information into a series of mathematical equations to determine where the material
travels after release and how fast the material is ultimately removed from the atmosphere.
IWAIR uses dispersion factors to relate an emission rate to an air concentration at some
specified location. A dispersion factor is essentially a measure of the amount of dispersion that
occurs from a unit of emission. Dispersion modeling is complex and requires an extensive data
set; therefore the IWAIR model has incorporated the use of a database of dispersion factors.
For IWAIR, the dispersion was calculated for a standardized unit emission rate (1 ug/m2 - s) to
obtain the air concentration (referred to as either a unitized air concentration (UAC) or a
dispersion factor) at a specific point away from the emission source. The unit of measure of the
dispersion factor is in micrograms/cubic meter per microgram/square meter-second. The most
important inputs to dispersion modeling are the emission rate, meteorological data, the area of
the waste management unit (WMU), the height of the WMU relative to the surrounding terrain,
and the location of the receptor relative to the WMU. The default dispersion factors in IWAIR
were developed for many separate scenarios designed to cover a broad range of unit
characteristics, including:
29 meteorological stations, chosen to represent the nine general climate regions of
the continental U.S.
4 unit types
14 surface area sizes for landfills, land application units and surface
impoundments, and 7 surface area sizes and 2 heights for waste piles
6 receptor distances from the unit (25, 50, 75, 150, 500, 1000 meters)
16 directions
The default dispersion factors were derived by modeling many scenarios with various
combinations of parameters, then choosing as the default the maximum dispersion factor for each
waste management unit/surface area/meteorological station/receptor distance combination.
-------
IWAIR Technical Background Document
Section 3.0
Based on the size and location of a unit, as specified by a user, IWAIR selects an
appropriate dispersion factor from the default dispersion factors in the model. If the user specifies
a unit surface area that falls between two of the sizes already modeled, a linear interpolation
method will estimate dispersion in relation to the two closest unit sizes.
The Industrial Source Complex - Short Term v.3 (ISCST3) (U.S. EPA, 1995) dispersion
model was selected for development of the dispersion factors in IWAIR. ISCST3 was chosen
because it can provide reasonably accurate dispersion estimates for area sources that are both
ground-level and elevated. Section 3.1 describes the development of the dispersion factor
database used in IWAIR. Section 3.2 describes the interpolation routine.
3.1 Development of Dispersion Factor Database
Figure 3-1 summarizes the process by which the dispersion factor database was
developed. Each step is described in the following subsections.
STEPl
STEP 2
Industrial D Survey of WMU
Sites & Location
Screening Survey of industrial
Subtitle D Establishments
(Shroederetal., 1987)
WMU Strata Classification
based on Area
.'.! ' -.?-;-,; v;;-".<,V;#
STEPS
STEP 4
Meteorological Data for 29
Met Stations
Receptor Data: Distances from
Edge of WMU for Different Strata
- Receptor Distances used to
. generate Dispersion Factors:
3 0,25,50,75,150,500,1000
meters
STEPS
Industrial Source Complex
Short Term model (ISCST3)
STEPS
1
Dispersion Factors for WMU sizes
Dispersion Factors are
I calculated for each of the 29 Met
I Stations and for each Receptor
Distance
Figure 3-1. Development of ISCST3 dispersion factors.
3-2
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IWAIR Technical Background Document
Section 3.0
3.1.1 Industrial D Survey of WMU Sites and Locations (Step 1)
The primary source of data used in the analysis for determining the appropriate range of
WMU sizes to model is the Industrial D Screening Survey responses (Schroeder et al., 1987).
These survey data provide information on the distribution of areas for nonhazardous WMUs
across the continental United States.
3.1.2 WMU Strata Classification Based on Survey (Step 2)
Area of a WMU is one of the most sensitive parameters in dispersion modeling. To
construct a database that contained benchmark dispersion coefficients, an appropriate set of
"model" units to run had to be determined.
To develop representative cutpoints, a statistical method called the Dalenius-Hodges
procedure was used as a starting point. This method attempts to break the distribution of a
known variable (in this case, area) that is assumed to be highly correlated with the model output
(in this case, dispersion factor) into a fixed number of strata in an optimal way. An area near the
midpoint for each strata is then used to represent that stratum. Used on a highly skewed
distribution, this process results in strata that tend to emphasize the tail. In this case, the
distribution of WMU areas is highly skewed to the rightthere is a long tail with a few very
large areas. As a result, the initial results of this method yielded strata that over characterized a
few very large units and inadequately characterized the smaller units that make up the bulk of the
distribution. Therefore, the strata were modified to better capture these smaller areas.
Landfills, land application units, and surface impoundments are all ground-level sources,
and are therefore modeled the same way using ISCST3. However, wastepiles are elevated
sources and so must be modeled separately in ISCST3. Therefore, two sets of areas were
developed, one for landfills, LAUs, and surface impoundments and one for wastepiles. Tables 3-
1 and 3-2 show the final area strata used for IWAIR. For each stratum, the median area was
modeled.
Table 3-1. Final WMU Area Strata Used for ISCST3 Model Runs for Wastepiles
Average Area (m2)
^/y^trata/' '*
1
2
3
4
5
6
7
j, * Low ,,/./^,'
5
94
324
1,010
5,200
45,200
251 ,000
,
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IWAIR Technical Background Document
Section 3.0
Table 3-2. Final WMU Area Strata Used for ISCST3 Model Runs
for Landfills, Land Application Units, and Surface Impoundments
*> -::;-"
! Strata
1
2
3
4
5
6
7
8
9
10
11
12
13
14
/
Low
14
310
809
2,307
7,588
27,115
60,300
120,763
210,444
303,525
554,439
753,754
1,007,703
2,521,281
Average Area ,{mz)
Median ,
81
567
1,551
4,047
12,546
40,500
78,957
161,880
243,000
376,776
607,000
906,528
1 ,408,356
8,090,000
' ; ,' 'A
> "-High' -1
293
789
2,293
7,487
26,980
59,653
119,000
210,000
295,000
546,345
728,460
999,609
2,430,000
13,500,000
3.1.3 Receptor Data Used for Dispersion Modeling (Step 3)
The receptor pathway in the ISCST3 model allows the user to specify receptors with
Cartesian receptor grid and/or polar receptor grid. In general, Cartesian receptors are used for
near-source receptors and polar grid receptors for more distant receptors. Because it takes a
substantial amount of time for the ISCST3 model to execute with a large number of receptor
points, it was necessary to reduce the number of receptors without missing representative
outputs. Therefore, a sensitivity analysis was conducted on area sources to determine the
receptor locations and spacings. See Appendix D for details.
The results of the sensitivity analysis of area sources show that the maximum impacts are
generally higher for a dense receptor grid (i.e., 64 or 32 receptors on each square) than for a
scattered receptor grid (i.e., 16 receptors on each square). For this application, however, the
differences of the maximum receptor impacts are not significant between a dense and a scattered
receptor grid. Therefore, 16 evenly spaced receptor points on each square were used in the
modeling. The sensitivity analysis also shows that the maximum downwind concentrations
decrease sharply from the edge of the area source to about 1,000 meters from the source.
Therefore, receptor points were placed at 25, 50, 75, 150, 500, and 1,000 meters so that a user
could examine the areas that are most likely to have a risk.
Since the flat terrain option is used in the modeling, receptor elevations were not
considered.
3-4
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IWAIR Technical Background Document
Section 3.0
3.1.4 Meteorological Data Used for 29 Meterological Stations (Step 4)
Meteorological data at over 200 meteorological stations in the United States are available
on the SCRAM Bulletin Board (http://www.epa.gov/scram001) and from a number of other
sources. A set of 29 meteorological stations selected in an assessment for EPA's Superfund
program Soil Screening Levels (SSLs) (EQM and Pechan, 1993) as being representative of the
nine general climate regions of the continental United States was used in this analysis. Summary
data and windroses for the 29 meteorological stations are provided in Appendix B.
In EPA's SSL study, it was determined that 29 meteorological stations would be a
sufficient sample to represent the population of 200 meteorological stations and predict mean
dispersion values with a high (95 percent) degree of confidence. The 29 meteorological stations
were distributed among nine climate regions based on meteorological representativeness and
variability across each region.
These climate regions were:
North Pacific Coastal
South Pacific Coastal
Southwest
Northwest Mountains
Central Plains
Southeast
Midwest
Northern Atlantic
South Florida.
Large-scale regional average conditions were used to select the actual stations (EQM and
Pechan, 1993).
The 29 meteorological stations are listed in Table 3-3. To assign facilities to a
meteorological station, IWAIR uses a set of polygons around each station. These polygons were
constructed using a geographic information system (GIS) to construct Thiessen polygons around
each station that enclose the areas closest to each station. The boundaries of these areas were
then adjusted to ensure that each boundary encloses an area that is most similar in meteorological
conditions to those measured at the meteorological station. To assist in this process, a GIS
coverage of Bailey's ecoregion divisions and provinces (Bailey et al., 1994) was used to conflate
the boundaries to correspond to physiographic features likely to influence climate or boundaries
corresponding to changes in temperature or precipitation. General wind regimes were also
considered in the conflation process.
Key factors considered in the conflation process include: defining coastal regimes as
narrow polygons, which generally stretched about 25 to 50 miles inland, to capture regions
dominated by coastal climate effects; maintaining tropical/subtropical and arid/semiarid divisions
in the southwestern United States; and using the ecoregion boundaries in Washington, Oregon,
and California to separate the more humid marine/redwood or Mediterranean mountain regimes
from the deserts to the east. In general, Thiessen polygons were used to define the
meteorological station areas for the remainder of the country.
ZIP codes were overlaid on the polygons and a database matching zip codes to
meteorological stations was generated for use in IWAIR. In addition, latitudinal/longitudinal
coordinates of the polygons are used in IWAIR to select a meteorological station based on a
3-5
-------
IWAIR Technical Background Document
Section 3.0
Table 3-3. Meteorological Stations Used in the Air Characteristic Study
City
Albuquerque
Atlanta
Bismarck
Boise
Casper
Charleston
Chicago
Cleveland
Denver
Fresno
Harrisburg
Hartford
Houston
Huntington
Las Vegas
Lincoln
Little Rock
Los Angeles
Miami
Minneapolis
Philadelphia
Phoenix
Portland
Raleigh-Durham
Salem
Salt Lake City
San Francisco
Seattle
Wlnnemucca
Met Station
State
NM
GA
ND
ID
WY
SC
IL
OH
CO
CA
PA
CT
TX
WV
NV
NE
AR
CA
FL
MN
PA
AZ
ME
NC
OR
UT
CA
WA
NV
#
23050
13874
24011
24131
24089
13880
94846
14820
23062
93193
14751
14740
12960
03860
23169
14939
13963
23174
12839
14922
13739
23183
14764
13722
24232
24127
23234
24233
24128
Latitude ;,;' -*
Degree
35
33
46
43
42
32
41
41
39
36
40
41
29
38
36
40
34
33
25
44
39
33
43
35
44
40
37
47
40
Minute
3
39
46
34
55
54
59
25
46
46
13
56
58
22
5
51
44
56
49
53
53
26
39
52
55
47
37
27
54
.« s , Longitude
Degree
106
84
100
116
106
80
87
81
104
119
76
72
95
82
115
96
92
118
80
93
75
112
70
78
123
111
122
122
117
Minute
37
25
45
13
28
2
54
52
52
43
51
41
21
33
10
45
14
24
17
13
15
1
19
47
0
57
23
18
48
Source: EQM and Pechan (1993).
facility's latitudinal/longitudinal coordinates. Figure 3-2 shows the final meteorological station
boundaries used for the study along with the locations of the Industrial D facility sites.
The modeling analysis was conducted
using 5 years of representative meteorological
data from each of the 29 meteorological
stations. Five-year wind roses representing the
frequency of wind directions and windspeeds
for the 29 meteorological stations were
analyzed. These show that the 29
meteorological stations represent a variety of
wind patterns.
Shape of Wind Rose for
29 Meteorological Stations
Shape of Wind Rose No. of Stations
Narrowly distributed
Moderately distributed
Evenly distributed
Bimodally distributed
10
4
6
9
3-6
-------
% V
^ I .
r-41**^ >
*
5 , ,7 1 < \>
Figure 3-2. Meteorological station regions.
I
8
*
3
if
a.
§
-------
IWAIR Technical Background Document
Section 3.0
Meteorological Data for
the ISCST3 Model
without Depletion
Wind Direction (or Row Vector)
Windspeed
Ambient Temperature
Stability Class
Mixing Height
Wind direction and windspeed are typically the
most important meteorological inputs for dispersion
modeling analysis. Wind direction determines the
direction of the greatest impacts. Windspeed is
inversely proportional to ground-level air
concentrations, so that the lower the windspeed, the
higher the air concentration.
Mixing height determines the heights to which
pollutants can be diffused vertically. Stability class is
also an important factor in determining the rate of lateral
and vertical diffusion. The more unstable the air, the greater the diffusion.
3.1.5 Industrial Source Complex Short-term Version 3 Model (Step 5)
This section discusses the critical
parameters of the selected model, ISCST3,
the results of sensitivity analyses
, performed to investigate several of the
model parameters, and the receptor
locations. Results of the sensitivity
analyses are presented in Appendix D.
3.1.5.1 General Assumptions.
This section discusses depletion, rural vs.
urban, and terrain assumptions.
Depletion. Air concentrations can
be calculated in ISCST3 with or without
wet and dry depletion. Modeled
concentrations without depletions are
higher than those with depletions. A
sensitivity analysis was conducted that
showed that the differences in the
maximum concentrations with depletion
and without depletion are small at close-to-
source receptors, increasing only slightly as
the distance from the source increases. The ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
sensitivity analysis also shows that the run
time for calculating concentrations using the ISCST3 model with depletion options is 15 to 30
times longer than the run time without depletions for the 5th and 95th percentile of the sizes of
LAUs. (The difference is greater for larger sources; see sensitivity analysis in Appendix D for
details.) Therefore, concentrations were calculated without depletions in this analysis so that a
greater number of meteorological locations could be modeled and included in IWAIR.
Rural vs. Urban. ISCST3 may be run in rural or urban mode, depending on land use
within a 3-km radius from the source. These modes differ with respect to wind profile exponent
Assumptions Made for Dispersion Modeling
Dry and wet depletion options were not activated in
the dispersion modeling.
The rural option was used in the dispersion modeling
since the types of WMUs being assessed are
typically in nonurban areas.
Flat terrain was assumed.
An area source was modeled for all WMUs.
To minimize error due to site orientation, a square
area source with sides parallel to X- and Y- axes was
modeled.
Receptor points were placed on 0, 25, 50, 75, 150,
500, and 1,000 m receptor squares starting from the
edge of the source with 16 receptor points on each
square.
Modeling was conducted using a unit emission rate
of 1 y
3-8
-------
IWAIR Technical Background Document
Section 3.0
and potential temperature gradients. Unless the site is located in a heavily metropolitan area, the
rural option is generally more appropriate. Because the types of WMUs being assessed are
typically in nonurban areas, the rural option was used in this analysis.
Terrain. Flat terrain for both the source and the surrounding area was assumed in the
modeling analysis for two reasons: (1) ISCST3 models all area sources as flat, and (2) complex
terrain simulations in the surrounding area result in air concentrations that are highly dependent
on site-specific topography. A specific WMU's location in relation to a hill or valley produces
results that would not be applicable to other locations. Complex terrain applications are
extremely site-specific; therefore, model calculations from one particular complex terrain
location cannot be applied to another. Conversely, simulations from flat terrain produce values
that are more universally applicable.
3.1.5.2 Source Release Parameters. This section describes the source parameters and
assumptions used in the dispersion modeling, including source type and elevation, source shape
and orientation, and source areas.
Source Type and Elevation. All WMU types modeled in this analysis were modeled as
area sources. Landfills, land application units, and surface impoundments were modeled as
ground-level sources, and wastepiles were modeled as elevated sources.
Source Shape and Orientation. The ISCST3 models an area source as a rectangle or
combination of rectangles. The user may also specify an angle of rotation relative to a north-
south orientation. A sensitivity analysis was conducted to compare the air concentrations from a
square area source, a rectangular area source oriented east to west, and a rectangular area source
oriented north to south to determine what role source shape and orientation play in determining
dispersion coefficients of air pollutants. The results show that the differences in unitized air
concentration between the square area source and the two rectangular area sources are less than
the differences between the two rectangular sources. In addition, a square area source has the
least amount of impact on orientation. Because information on source shapes or orientations is
not available, a square source was chosen to minimize the errors caused by source shapes and
orientations. (See sensitivity analysis in Appendix D for details.)
3.1.6 Dispersion Factors Available in Program (Step 6)
Unitized air concentrations were calculated by running ISCST3 with a unit emission rate
(i.e., 1 /^g/m2-s). The selected areas for each type of WMU were modeled with 29 representative
meteorological locations in the continental United States to estimate UACs. The 5-year average
UACs at all receptor points were calculated.
The maximum annual average UACs are presented in Tables 3-4 and 3-5 for the different
types of WMUs. Typically, the location of maximum impacts with respect to the source are
determined by the prevailing wind direction. For ground-level area sources (i.e., landfills, land
application units, and surface impoundments), maximum annual average UACs are always
located on the first receptor square (i.e., 25-m receptors). For elevated area sources, the
3-9
-------
IWAIR Technical Background Document
Section 3.0
maximum annual average UACs are usually located on the first receptor square and occasionally
located on the second or third receptor square. The results in Tables 3-4 and 3-5 show that the
annual average UACs increase with the increasing area size of the sources.
Figures 3-3 through 3-5 show that maximum UACs vary with meteorological location.
For landfills and LAUs, the maximum UACs at some meteorological locations can be twice as
much as those at other locations. For wastepiles, the maximum UACs at some meteorological
locations are more than twice those at other meteorological locations.
3.2 Interpolation of Dispersion Factor
Because the ISCST3 model is sensitive to the size of the area source, the relationship
between air concentrations and size of the area source was analyzed. As illustrated in Figure 3-6,
the results show that, for relatively small area sources, air concentrations increase significantly as
the size of the area source increases. For large area sources, this increase in air concentrations is
not as significant.
As described in Section 3.2.2, area strata were identified from WMU data in the
Industrial D Survey. The median area size for each stratum was used in the dispersion modeling
analysis. Tables 3-6 and 3-7 present the source areas and heights used in the modeling analysis.
This provided a set of UACs for use in the analysis. For any specific WMU, IWAIR
estimates a dispersion factor using an interpolation routine that uses the UACs associated with
modeled areas immediately above and below the actual area of the unit as follows:
x (UACj-UACj) + UAq
(3-D
where
UAC
A
A
UAC. =
UAC =
unitized air concentration for specific WMU ([ug/m3]/[ug/m2-s])
area of specific WMU (m2)
area modeled in dispersion modeling immediate below area of specific WMU
(m2)
area modeled in dispersion modeling immediate above area of specific WMU
(m2)
unitized air concentration developed for area i ([ug/m3]/[ug/m2-s])
unitized air concentration developed for area j ([ug/m3]/[ug/m2-s]).
and UACj are set to the values for the
If a WMU area is less than the smallest area modeled,
smallest area modeled, and A; and UAQ are set to zero. If a WMU area is greater than the
largest area modeled, the A;, UAQ, AJ5 and UACj are set to correspond to the two largest areas
3-10
-------
Table 3-4. Maximum Annual Average Unitized Air Concentrations (^g/m3
Landfills, Land Application Units, and Surface Impoundments
for
* - ; ^ , \
/ s V. , * *\
« V
% MetStatiorT
Albuquerque, NM
Atlanta, GA
Bismarck, ND
Boise, ID
Casper, WY
Charleston, SC
Chicago, IL
Cleveland, OH
Denver, CO
Fresno, CA
Harrisburg, PA
Hartford, CT
Houston, TX
Huntington, WV
Las Vegas, NV
Lincoln, NE
Little Rock, AR
Los Angeles, CA
Miami, FL
Minneapolis, MN
Philadelphia, PA
Phoenix, AZ
Portland, ME
Raleigh-Durham, NC
Salem, OR
Salt Lake City, UT
San Francisco, CA
Seattle, WA
Winnemucca NV
\v N
Station
No. '
23050
13874
24011
24131
24089
13880
94846
14820
23062
93193
14751
14740
12960
3860
23169
14939
13963
24174
12839
14922
13739
23183
14764
13722
24232
24127
23234
24233
24128
\ \, % / ^ x c- x ' >-' - '^\^ Area(m4)' - '' , ^ *' ' ;- * %' *>
81 '4
3.521
3.919
3.598
4.806
3.532
3.760
3.678
4.163
5.364
5.783
4.291
4.478
4.137
5.548
4.353
3.007
4.500
4.492
3.752
3.334
4.359
5.640
5.028
4.407
4.580
4.735
4.500
4.276
4.123
SGT\
5.791
6.369
5.871
7.739
5.718
6.134
6.011
6.639
8.645
9.460
6.892
7.454
6.811
9.154
7.072
4.867
7.402
7.480
6.150
5.453
7.076
9.043
8.269
7.196
7.348
7.576
7.257
6.799
6.720
1,551
7.103
7.789
7.182
9.458
6.980
7.503
7.356
8.064
10.541
11.587
8.380
9.176
8.352
11.240
8.645
5.936
9.079
9.269
7.550
6.676
8.643
11.002
10.146
8.805
8.939
9.218
8.842
8.231
8.222
, 4,047 '
8.450
9.236
8.528
11.251
8.265
8.907
8.726
9.519
12.488
13.794
9.900
10.934
9.925
13.378
10.254
7.027
10.795
11.100
8.984
7.924
10.243
13.016
12.070
10.453
10.567
10.909
10.465
9.691
9.763
,12,545s
10.175
11.119
10.273
13.543
9.923
10.733
10.505
11.415
15.039
16.611
11.877
13.216
11.961
16.161
12.349
8.445
13.023
13.457
10.845
9.541
12.317
15.650
14.574
12.599
12.687
13.095
12.585
11.592
11.772
40,500
12.112
13.224
12.231
16.138
11.790
12.778
12.493
13.527
17.898
19.800
14.073
15.775
14.239
19.282
14.700
10.027
15.528
16.112
12.944
11.354
14.644
18.591
17.389
14.999
15.053
15.546
14.946
13.686
14.028
78,957
13.316
14.526
13.443
17.770
12.931
14.045
13.712
14.833
19.690
21.792
15.434
17.344
15.632
21.207
16.159
11.000
17.065
17.745
14.240
12.464
16.076
20.439
19.127
16.483
18.120
18.754
17.977
16.390
16.889
161,880s;
14.535
15.927
14.816
19.508
14.184
15.392
14.980
16.268
21.634
24.024
16.882
18.848
17.227
23.265
17.697
12.036
18.732
19.332
15.718
13.676
17.596
22.494
20.946
18.079
18.120
18.754
17.977
16.390
16.889
243,000
15.487
16.902
15.650
20.710
15.020
16.350
15.944
17.227
22.945
25.383
17.900
20.221
18.189
24.728
18.816
12.781
19.883
20.709
16.612
14.502
18.689
23.763
22.310
19.192
19.185
19.865
19.084
17.324
17.980
,376,776
16.406
17.896
16.579
21.978
15.892
17.320
16.871
18.232
24.336
26.916
18.937
21.412
19.244
26.197
19.941
13.525
21.053
21.944
17.608
15.347
19.784
25.185
23.642
20.327
20.308
21.050
20.213
18.310
19.055
607,000
17.299
18.937
17.620
23.311
16.833
18.316
17.797
19.308
25.798
28.634
20.006
22.470
20.448
27.720
21.081
14.291
22.296
23.083
18.731
16.253
20.908
26.729
24.983
21.510
21.513
22.318
21.376
19.359
20.130
906,529
18.206
19.950
18.566
24.550
17.724
19.302
18.741
20.341
27.217
30.144
21.060
23.684
21.531
29.218
22.222
15.051
23.486
24.311
19.750
17.121
22.021
28.164
26.344
22.665
22.661
23.521
22.524
20.365
21.224
1,408,356j.
19.287
21.142
19.667
26.052
18.751
20.451
19.843
21.564
28.886
31.955
22.298
25.101
22.784
30.966
23.557
15.939
24.888
25.753
20.932
18.127
23.317
29.850
27.933
24.018
24.005
24.956
23.882
' 21.547
22.505
*^~
8,090JOOO
25.002
27.323
25.220
33.867
24.085
26.415
25.626
27.959
37.541
41.022
28.745
32.702
28.985
39.932
30.668
20.577
32.110
33.445
26.829
23.300
30.083
30.083
36.239
30.956
31.007
32.412
30.988
27.722
29.215
-------
to
Table 3-5. Maximum Annual Average Unitized Air Concentrations fag/m31 ^g/s-m2) for Wastepiles
i Met Station
Albuquerque, NM
Atlanta, GA
Bismarck, ND
Boise, ID
Casper, WY
Charleston, SC
Chicago, IL
Cleveland, OH
Denver, CO
Fresno, CA
Harrisburg, PA
Hartford, CT
Houston, TX
Huntington, WV
Las Vegas, NV
Lincoln, NE
Little Rock, AR
Los Angeles, CA
Miami, FL
Minneapolis, MN
Philadelphia, PA
Phoenix, AZ
Portland, ME
Raleigh-Durham, NC
Salem, OR
Salt Lake City, UT
San Francisco, CA
Seattle, WA
Winnemucca, NV
Station
No.
23050
13874
24011
24131
24089
13880
94846
14820
23062
93193
14751
14740
12960
3860
23169
14939
13963
24174
12839
14922
13739
23183
14764
13722
24232
24127
23234
24233
24128
Area (m*) (2-m Height Wastepiles)
20
0.037
0.043
0.035
0.056
0.040
0.038
0.038
0.049
0.054
0.077
0.047
0.049
0.042
0.057
0.045
0.032
0.045
0.055
0.041
0.033
0.045
0.062
0.046
0.043
0.048
0.052
0.046
0.053
0.040
162
0.171
0.195
0.155
0.235
0.181
0.168
0.170
0.214
0.237
0.344
0.214
0.212
0.191
0.248
0.194
0.142
0.201
0.255
0.181
0.147
0.198
0.274
0.196
0.191
0.209
0.232
0.207
0.240
0.172
486
0.378
0.431
0.343
0.520
0.405
0.372
0.380
0.479
0.518
0.744
0.477
0.474
0.424
0.548
0.432
0.317
0.442
0.564
0.404
0.326
0.439
0.597
0.433
0.424
0.466
0.514
0.464
0.540
0.380
2,100
0.993
1.141
0.932
1.389
1.084
1.003
1.030
1.251
1.401
1.858
1.269
1.283
1.129
1.450
1.185
0.867
1.181
1.466
1.080
0.896
1.200
1.555
1.209
1.152
1.287
1.386
1.252
1.440
1.040
10,100
2.359
2.644
2.273
3.183
2.461
2.393
2.431
2.897
3.393
4.018
2.978
2.999
2.696
3.416
2.852
2.046
2.830
3.232
2.521
2.168
2.876
3.628
3.056
2.802
3.060
3.218
2.975
3.187
2.555
101,000
5.704
6.284
5.685
7.621
5.714
5.944
5.897
6.712
8.397
9.168
6.960
7.096
6.640
8.647
6.949
4.850
7.049
7.230
6.016
5.320
6.962
8.793
7.866
6.956
7.288
7.569
7.163
7.022
6.432
1,300,000
- 11.011
12.066
11.093
14.732
10.846
11.581
11.340
12.611
16.369
17.785
13.027
14.060
12.839
17.196
13.504
9.212
13.894
14.069
11.650
10.290
13.365
16.962
15.636
13.566
13.859
14.453
13.747
12.804
12.676
Area Strata (m2) (5-m Height Wastepiles) \
20
0.014
0.016
0.013
0.021
0.015
0.014
0.014
0.018
0.020
0.028
0.018
0.018
0.016
0.021
0.017
0.012
0.017
0.020
0.015
0.013
0.017
0.023
0.018
0.016
0.018
0.020
0.018
0.020
0.015
162
0.053
0.060
0.049
0.072
0.056
0.053
0.053
0.064
0.075
0.101
0.066
0.067
0.059
0.077
0.062
0.045
0.063
0.076
0.056
0.047
0.063
0.085
0.065
0.061
0.067
0.072
0.065
0.073
0.056
486
0.107
0.120
0.097
0.143
0.110
0.105
0.106
0.128
0.148
0.205
0.131
0.132
0.119
0.153
0.122
0.088
0.126
0.153
0.112
0.093
0.124
0.170
0.126
0.120
0.130
0.142
0.127
0.145
0.109
2,100
0.288
0.325
0.258
0.384
0.301
0.280
0.285
0.353
0.391
0.562
0.357
0.354
0.320
0.410
0.323
0.237
0.335
0.465
0.303
0.246
0.330
0.455
0.327
0.320
0.347
0.383
0.345
0.399
10,100
0.824
0.940
0.759
1.132
0.894
0.820
0.845
1.038
1.137
1.556
1.049
1.050
0.933
1.191
0.961
0.708
0.967
1.263
0.889
0.729
0.978
1.281
0.972
0.936
1.045
1.131
1.029
1.193
101,000
2.956
3.312
2.867
3.996
3.080
3.008
3.049
3.634
4.262
5.002
3.731
3.762
3.392
4.284
3.588
2.566
3.553
4.022
3.163
2.726
3.610
4.533
3.857
3.523
3.844
4.041
3.743
3.974
1,300,000 !
7.671
8.467
7.693
10.383
7.678
8.027
7.929
9.059
11.383
12.248
9.318
9.585
8.910
11.707
9.440
6.520
9.533
9.655
8.083
7.166
9.369
11.828
10.701
9.394
9.833
10.268
9.704
9.363
-------
IWAIR Technical Background Document
Section 3.0
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IWAIR Technical Background Document
Section 3.0
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IWAIR Technical Background Document
Section 3.0
Winnemucca, NV
San Francisco, CA
Salem, OR
Portland, ME
Philadelphia, PA
.Miami, FL
Little Rock, AR
Las Vegas, NV
Houston, TX
Harrisburg, PA
Denver, CO
Chicago, IL
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Bismarck, ND
Albuquerque, NM
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-------
IWAIR Technical Background Document
Section 3.0
0
Air Concentrations vs. Surface Area
(Landfills)
Little Rock
Los Angeles
T T
0 . 400,000 800,000 1,200,000 1,600,000
Surface Area (m)
Air Concentrations vs. Surface Area
(2m High Waste Piles)
Little Rock
Los Angeles
0 20,000 40,000 60,000 80,000 100,000
Surface Area (m2)
Note: Largest areas modeled for each WMU type have been omitted from the chart to improve clarity.
Figure 3-6. Air concentration vs. size of area source.
3-16
-------
FWAIR Technical Background Document
Section 3.0
Table 3-6. Areas Modeled for Landfills,
Land Application Units, and Surface Impoundments
i^Vi/* " §
-------
-------
IWAIR Technical Background Document
Section 4.0
4.0 Exposure Factors
This section describes the development of the
exposure factors used in IWAIR. All data in this section
are from the Exposure Factors Handbook (U.S. EPA,
1997a; hereafter, the EFH). These exposure factors are
used only for carcinogenic chemicals (see box at right). For
noncarcinogens, the hazard quotient is a ratio of air
concentration to the health benchmark (a Reference
Concentration) and no exposure factors are used.
All exposure factors were developed for the
following subpopulations:
Adult residents (ages 19 and older)
Children ages <1 year
Children ages 1-5 years
Children ages 6-11 years
Children ages 12-18 years
Workers.
The age ranges for children were used for
consistency with the data on inhalation rate in the draft
EFH. Most exposure factors were selected to represent
typical or central tendency values, not high-end values.
Table 4-1 summarizes the exposure factors used in
IWAIR. Sections 4.1 through 4.4 describe how the values
for exposure duration, inhalation rate, body weight, and
exosure frequency, respectively, were determined.
4.1 Exposure Duration
An overall exposure duration of 30 years was
selected as a high end value for residents. This was then
allocated to the various age ranges modeled, based on the
number of years in each age bracket. Table 4-1 shows the
values used.
Carcinogens Modeled
Acetaldehyde
Acrylamide
Acrylonitrile
Benzene
Benzidine
Benzo(a)pyrene
Bromodichloromethane
Bromoform
Butadiene, 1,3-
Carbon tetrachloride
Chlorodibromomethane
Chloroform
Dibromo-3-chloropropane, 1,2-
Dichloroethane, 1,2-
Dichloroethylene, 1,1-
Dichloropropene, cis-1,3-
Dichloropropene, trans-1,3-
Dimethylbenz(
-------
IWAIR Technical Background Document
Section 4.0
Table 4-1. Summary of Exposure Factors Used in IWAIR
pi
Receptor
Child <1
Child 1-5
Child 6-11
Child 12-18
Adult Resident
Worker
Exposure
Duration
(yr)
1
5
6
7
11
7.2
Inhalation Rate
(mVd) ':,
4.5
7.55
11.75
14.0
13.3
10.4
Body Weight
'//(kg) ,
9.1
15.4
30.8
57.2
69.1
71.8
Exposure .
Frequency
(d/yr)
350
350
350
350
350
250
For workers, the typical default exposure values used in the past were an 8-h shift,
240 d/wk, for 40 years. The EFH presents data on occupational mobility that are in stark contrast
to the assumed value of 40 years at a single place of employment. As presented in the EFH, the
median occupational tenure of the working population (109.1 million people) ages 16 years of
age and older in January 1987 was 6.6 years. This value includes full- and part-time workers.
The worker modeled in IWAIR is assumed to be a full-time worker. Therefore, a value of 7.2
years, from EFH Table 15-160 and reflecting full-time male and female workers of all ages, was
used.
4.2 Inhalation Rate
To assess chronic exposures, an average daily inhalation rate is needed. Such a rate is
based on inhalation values for a variety of activities being averaged together.
Table 4-2 summarizes the inhalation rates for long-term exposure recommended in the
EFH. The values for adult females (11.3 mVd) and adult males (15.2 mVd) were averaged and
used in IWAIR. For children, the values for males and females were first averaged for each age
group if they were not presented as combined male and female. These combined male/female
rates for each age group were averaged to get the age groups used in IWAIR. For example, the
combined values for ages 1 through 2 and 3 through 5 were averaged to obtain a value for ages 1
through 5.
Table 4-3 summarizes the values for inhalation rate for workers presented in the EFH.
The recommended hourly average of 1.3 mVh was used in IWAIR. To convert this to a daily
value, an 8-h workday was assumed, yielding a daily inhalation rate for workers of 10.4 mVd.
4-2
-------
IWAIR Technical Background Document
Section 4.0
Table 4-2. Recommended Inhalation Rates for Residents
BS^^^JS5
Age (yr)
<1
1-2
3-5
6-8
9-11
12-14
15-18
Adults (19-65+)
-i^ j
Males
NA
NA
NA
NA
14
15
17
15.2
Females
NA
NA
NA
NA
13
12
,12
11.3
Males and Females
4.5
6.8
8.3
10
NA
NA
NA
NA
NA = Not available.
Source: U.S. EPA, 1997a, Table 5-23.
Table 4-3. Recommended Inhalation Rates for Workers
* -^-~^^.?^S v,/* " f ,<*
^Activity Type >* , ''x ' " -^vV ?--
Slow activities
Moderate activities
Heavy activities
Hourly average
Mean
-' (m3/hX ;. -
1.1
1.5
2.3
1.3
, ^'^ Upper Percentile < ^ ,
ix x ^ (m3/h) ^ ' ^ -
NA
NA
NA
3.5
NA = Not available.
Source: U.S. EPA, 1997a, Table 5-23.
4.3 Body Weight
Body weights were needed that were consistent with the inhalation rates used. Therefore,
body weights for children ages <1, 1-5, 6-11, and 12-18 years, adult residents aged 19-29 years,
and workers of all ages were needed.
The EFH presents summary data on body weight for adults in Table 7-2. The data for
males and females combined are summarized here in Table 4-4. Because an adult resident aged
19-29 was desired, the weighted average of the values for ages 18-24 and 25-34 was used,
weighting each by the number of years in that age range (6 in 18-24 and 5 in 25-34).
4-3
-------
IWAIR Technical Background Document
Section 4.0
Table 4-4. Body Weights for Adults, Males and Females
Combined, by Age
Age(yr)
18-24
25-34
35-44
45-54
55-65
65-74
All (18-74)
Bkxly Weight (kg)'' ' V
67.2
71.5
74.0
74.5
73.4
70.7
71.8
Source: U.S. EPA (1997a), Table 7-2.
For children, the EFH contains mean body weights for 1-year age intervals (e.g., 1 year, 2
years). These values, summarized in Table 4-5 were averaged across the age ranges used in
IWAIR.
Table 4-5. Body Weights for Male and Female Children
Combined, Ages 6 Months to 18 Years
Age (years)
6-1 1 months
1
2
3
4
5
6
7
8
9
Mean (kg)
9.1
11.3
13.3
15.3
17.4
19.7
22.6
24.9
28.1
31.5
Age (years),.
10
11
12
13
14
15
16
17
18
>5->v,l '- '*'
v/ -, -Mean, (kg),;-
36.3
41.1
45.3
50.4
56.0
58.1
62.6
63.2
65.1
Source: U.S. EPA (1997a), Table 7-3.
4.4 Exposure Frequency
Exposure frequency is the number of days per year that a receptor is exposed. A value of
350 d/yr was used for residents, and a value of 240 d/yr was used for workers. These are based,
respectively, on 7 d/wk and 5 d/wk for 50 wk/yr and account for the receptor being elsewhere on
vacation for 2 wk/yr.
4-4
-------
IWAIR Technical Background Document
Section 5.0
5.0 Development of Inhalation Health
Benchmarks
Chronic inhalation health benchmarks used in IWAIR include inhalation reference
concentrations (RfCs) for noncarcinogens and inhalation cancer slope factors (CSFs) for
carcinogens. Unit risk factors (URFs) and CSFs are used in the model for carcinogenic
constituents, regardless of the availability of an RfC. Inhalation health benchmarks were
identified in the IRIS and AST (U.S. EPA, 1997b, 1998a). IRIS and HEAST are maintained by
EPA, and values from IRIS and HEAST were used in the model whenever available. Provisional
EPA benchmarks and Agency for Toxic Substances and Disease Registry (ATSDR) minimal risk
levels (MRLs) were used to fill in data gaps (see Section 5.1). Additional chronic inhalation
health benchmarks were derived for use in this analysis for constituents lacking EPA or ATSDR
values (see Section 5.2).
Figure 5-1 describes the approach used to develop the chronic inhalation health
benchmarks used in this analysis. The benchmarks are summarized in Table 5-1.
5.1 Alternate Chronic Inhalation Health Benchmarks Identified
If IRIS or HEAST chronic inhalation health benchmarks were not available, benchmarks
from alternative sources were sought. Provisional EPA benchmarks, ATSDR inhalation MRLs,
and California EPA noncancer chronic reference exposure levels (CalEPA, 1997a) were included
whenever available. Alternate RfCs were identified for
Acetone
Cyclohexanol
Isophorone
2-Methoxyethanol acetate
Phenol
Pyridine
Tetrachloroethylene
1,1,1 -Trichloroethane
Xylenes.
5-1
-------
IWAIR Technical Background Document
Section 5.0
Used IRIS value
if not available
Used HEAST value
if not available
Obtained value from other
sources (e.g., ATSDR,
EPA, CalEPA)
if not available
Derived value for
Noncarcinogen
1. Conducted literature search
and calculated RfC using
standard RfC methodology
or
2. If no appropriate inhalation
toxicity studies available,
developed RfC by using
alternative methodology,
including route-to-route
extrapolation
Carcinogen
Calculated inhalation URF
using route-to-route
extrapolation from oral CSF
Figure 5-1. Approach used to select chronic
inhalation health benchmark values.
5-2
-------
TWA/7? Technical Background Document
Section 5.O
Table 5-1. Chronic Inhalation Health Benchmarks Used in IWAIR
1
75-07-0
67-64-1
75-05-8
107-02-8
79-06-1
79-10-7
107-13-1
107-05-1
62-53-3
71-43-2
92-87-5
50-32-8
75-27-4
75-25-2
106-99-0
75-15-0
56-23-5
126-99-8
108-90-7
124-48-1
67-66-3
95-57-8
1319-77-3
98-82-8
108-93-0
96-12-8
95-50-1
106-46-7
75-71-8
107-06-2
75-35-4
78-87-5
10061-01-5
10061-02-6
57-97-6
68-12-2
95-65-8
121-14-2
123-91-1
^"V^^--- %&/:"''/&£/<' -'X^^V^.' -.,
&"'.' *$ -/|r ?.£-;*- *>*$*', ''%&
<& ''£^^iS^fy^^l^
^x^^a^l|pf\|;
cetaldehyde
cetone
cetonitrile
crolein
crylamide
crylic acid
crylonitrile
llyl chloride
Aniline
Benzene
Benzidine
Benzo(a)pyrene
Bromodichloromethane
Bromoform (Tribromomethane)
Butadiene, 1 ,3-
Carbon disulfide
Carbon tetrachloride
Chloro-1 ,3-butadiene, 2-
Chloroprene)
Chlorobenzene
Chlorodibromomethane
Chloroform
Chlorophenol, 2-
Cresols (total)
Cumene
Cyclohexanol
Dibromo-3-chloropropane, '1 ,2-
Dichlorobenzene, 1 ,2-
Dichlorobenzene, 1 ,4-
Dichlorodifluoromethane
Dichloroethane, 1 ,2-
Dichloroethylene, 1,1-
Dichloropropane, 1 ,2-
Dichloropropene, cis-1 ,3-
Dichloropropene, trans-1 ,3-
Dimethylbenz(a)anthracene,
7,12-
Dimethylformamide, N,N-
Dimethylphenol, 3,4-
Dinitrotoluene, 2,4-
Dioxane, 1 ,4-
^^f^^^niiaWint^ehis^'; :^^'
ll^'^ii
fc(mg/m3)
9.0E-03
3.1E+01
5.0E-02
2.0E-05
NA
1.0E-03
2.0E-03
1.0E-03
1.0E-03
NA
NA
NA
NA
NA
NA
7.0E-01
NA
7.0E-03
2.0E-02
NA
NA
1.4E-03
4.0E-04
4.0E-01
2.0E-05
2.0E-04
2.0E-01
8.0E-01
2.0E-01
NA
NA
4.0E-03
2.0E-02
2.0E-02
NA
3.0E-02
NA
NA
8.0E-01
?::':"' :. ., -J* iig>? '-4-
< /;<; , ; .^."if.^^f.'i-, '
/Rfiri,Tar;get"dir|an ;,^
espiratory
eurological
ver
espiratory
Respiratory
espiratory
eurological
pleen
Reproductive
Respiratory
Kidney and liver
Repro/developmental
Hematological
Kidney and adrenal
NA
Reproductive
Body weight
Reproductive
Liver
Respiratory
Respiratory
Respiratory
Liver
NA
No liver, kidney, or
hemato effects
< ?&~^
*
I
A
H
I
I
I
I
I
I
H
H
D
D
I
S
I
H
I
H
I
I
1
1
D
£$$' ^arcintigens^'^' .^-.
&~<: >> 'i%s&? ,'.
nhal;|jRF:
twi^^
2.2E-06
NA
NA
NA
1.3E-03
NA
6.8E-05
NA
NA
8.3E-06
6.7E-02
1.7E-03
1.8E-05
1.1E-06
2.8E-04
NA
1.5E-05
NA
NA
2.4E-05
2.3E-05
NA
NA
NA
NA
6.9E-07
NA
NA
NA
2.6E-05
5.0E-05
NA
3.7E-05
3.7E-05
2.4E-02
NA
NA
1.9E-04
NA
frriHai^SiFff
'$&*$?£
7.7E-03
NA
NA
NA
4.6E+00
NA
2.4E-01
NA
NA
2.9E-02
2.3E+02
6.0E+00
6.2E-02
3.9E-03
9.8E-01
NA
5.3E-02
NA
NA
8.4E-02
8.1E-02
NA
NA
NA
NA
2.4E-03
NA
NA
NA
9.1E-02
1.8E-01
NA
1.3E-01
1.3E-01
8.4E+01
NA
NA
6.8E-01
NA
''^
R#
I
I
I
I
I
D
I
I
I
D
I
H
I
I
H
H
D
D
(continued)
5-3
-------
IWAIR Technical Background Document
Section 5.0
Table 5-1. (continued)
p*> 1
*.'. CAS#
122-66-7
106-89-8
106-88-7
111-15-9
110-80-5
100-41-4
106-93-4
107-21-1
75-21-8
50-00-0
98-01-1
87-68-3
118-74-1
77-47-4
67-72-1
110-54-3
78-59-1
7439-97-6
67-56-1
110-49-6
109-86-4
74-83-9
74-87-3
78-93-3
108-10-1
80-62-6
1634-04-4
56-49-5
75-09-2
91-20-3
98-95-3
79-46-9
55-18-5
924-16-3
930-55-2
108-95-2
85-44-9
75-56-9
Name
Diphenylhydrazine, 1 ,2-
Epichlorohydrin
Epoxybutane, 1,2-
Ethoxyethanol acetate, 2-
Ethoxyethanol, 2-
Ethylbenzene
Ethylene dibromide
Ethylene glycol
Ethylene oxide
Formaldehyde
Furfural
texachloro-1 ,3-butadiene
Hexaohlorobenzene
Hexachlorocyclopentadiene
Hexachloroethane
Hexane, n-
Isophorone
Mercury
ulethanol
Methoxyethanol acetate, 2-
Methoxyethanol, 2-
Methyl bromide (bromomethane)
Methyl chloride (chloromethane)
Methyl ethyl ketone
Methyl isobutyl ketone
Methyl methacrylate
Methyl terf-butyl ether
vlethylcholanthrene, 3-
Methylene chloride
aphthalene
Nitrobenzene
itropropane, 2-
itrosodiethylamine
itrosodi-n-butylamine
T-Nitrosopyrrolidine
henol
hthalic anhydride
ropylene oxide
" Noncarcinogens /~"f
RfC (mg/m3
NA
1.0E-03
2.0E-02
7.0E-02
2.0E-01
1.0E+00
2.0E-04
6.0E-01
NA
NA
5.0E-02
NA
NA
7.0E-05
NA
2.0E-01
1.2E-02
3.0E-04
1.3E+01
2.6E+01
2.0E-02
5.0E-03
NA
1.0E+00
8.0E-02
7.0E-01
3.0E+00
NA
3.0E+00
3.0E-03
2.0E-03
2.0E-02
NA
NA
NA
6.0E-03
1.2E-01
3.0E-02
^
RfC Target Organ
Respiratory
Respiratory
NA
Reproductive
Developmental
Reproductive
Respiratory
Respiratory
Respiratory
Respiratory and
neurological
NA
Neurological
Developmental
NA
Reproductive
Respiratory
Developmental
Kidney and liver
Respiratory
Kidney and liver
iver
Respiratory
-------
IWAIR Technical Background Document
Section 5.0
Table 5-1. (continued)
ns^$r; v
r< &$$
* » atK'/O "> \.
4&s* :
110-86-1
100-42-5
1746-01-6
630-20-6
127-18-4
79-34-5
108-88-3
95-53-4
76-13-1
120-82-1
71-55-6
79-00-5
79-01-6
75-69-4
121-44-8
108-05-4
75-01-4
1330-20-7
, /*-,,;. /r<;
;VlT'V ', ^V" .-x/
%. ' Name _ f/'
Pyridine
Styrene
TCDD, 2,3,7,8-
Tetrachloroethane, 1,1,1,2-
Tetrachloroethylene
Tetrachloroethane, 1,1,2,2- ,
Toluene
Toluidine, o-
Trichloro-1,2,2-trifluoroethane,
1,1,2-
Trichlorobenzene, 1 ,2,4-
Trichlorpethane, 1,1,1-
Trichloroethane, 1,1,2-
Trichloroethylene
Trichlorofluoromethane
Triethylamine
Vinyl acetate
Vinyl chloride
Xylenes (total)
f^ojtearcinogens
RfC,(migAn')
7.0E-03
1.0E+00
NA
NA
' 3.0E-01
NA
4.0E-01
NA
3.0E+01
2.0E-01
1.0E+00
NA
NA
7.0E-01
7.0E-03
2.0E-01
NA
3.0E-01
RfC Tafg'et Organ "-;
-iver
Neurological
Neurological
Respiratory and
neurological
Body weight
Liver
Neurological
Kidney and respiratory
No respiratory effects
Respiratory
Neurological
lief1
O
1
A
1
H
, H
SF
H
1
1
A
^ " ^Carclhogensj" ;
tliiHalURF
(Hg/m3)-1''
NA
NA
NA
7.4E-06
NA
5.8E-05
NA
6.9E-05
NA
NA
NA
1.6E-05
1.7E-06
NA
NA
NA
8.4E-05
NA
, Irihal CSR *
(mg/Kg/dfi' ,
NA
NA
1.6E+05
2.6E-02
NA
2.0E-01
NA
2.4E-01
NA
NA
NA
5.6E-02
6.0E-03
NA
NA
NA
3.0E-01
NA
if-
Ftef*:
H
I
I
D
I
SF
H
CAS = Chemical Abstract Service.
CSF = Cancer slope factor.
NA = Not available.
RfC = Reference concentration.
URF = Unit risk factor.
a Sources:
I = IRIS (U.S. EPA, 1998a)
H = HEAST(U.S.EPA,1997b)
A = Agency for Toxic Substances Disease Registry (ATSDR) minimal risk levels (MRLs)
SF = Superfund Risk Issue Paper (U.S. EPA, 1996b; U.S. EPA, n.d.)
FR = 61 FR 42317-354 (U.S. EPA, 1996a)
D = Developed for this study.
O = Other source (see Sections 5.1 and 5.2).
S = Solvents listing, 63FR 64371-402 (U.S. EPA, 1998b)
For acetone, naphthalene, tetrachloroethylene, and total xylenes, ATSDR's chronic
inhalation MRLs were used. Naphthalene is currently undergoing review by EPA's IRIS pilot
program (future publication date not known) and a new RfC may be available soon. Provisional
RfCs were identified for cyclohexanol, isophorone, and phenol in a Federal Register notice
(61 FR 42317) concerning solvents listings (U.S. EPA, 1996b). An inhalation acceptable daily
intake (ADI) was identified for pyridine (U.S. EPA, 1986). An RfC for 1,1,1-trichloroethane
5-5
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IWAIR Technical Background Document
Section 5,0
was identified in a Superfund risk issue paper (U.S. EPA, 1996c). Table 5-2 summarizes the
alternate RfCs identified as well as the target organs, sources, and critical studies.
Table 5-2. Alternate Chronic Inhalation Health Benchmarks
CAS#
67-64-1
108-93-0
111-15-9
78-59-1
110-49-6
108-95-2
110-86-1
127-18-4
71-55-6
1330-20-7
Chemical Name
Acetone
(2-propanone)
Cyclohexanol
2-Ethoxyethanol
Acute
Isophorone
2-Methoxyethanol
acetate
Phenol
Pyridine
Tetrachloroethylene
1 ,1 ,1 -Trichloroethane
Xylenes (total)
Inhalation Benchmark
and Benchmark Value
RfC = 13 ppm (31 mg/m3)
Provisional RfC = 0.00002
mg/m3
Provisional RfC = 0.07
mg/m3
Provisional RfC= 0.012
mg/m3
Provisional RfC = 26 mg/m3
Provisional RfC =
0.006 mg/m3
Inhalation ADI= 0.002
mg/kg/d; converts to 0.007
mg/m3
RfC = 0.04 ppm (0.3
mg/m3)
RfC= 1.0 mg/m3
RfC = 0.1 ppm (0.3 mg/m3)
's * *""
Target Organ
Neurological
NA
NA
NA
NA
NA
Liver
Neurological
Neurological
Neurological
- s - , v
^ , Source
ATSDR chronic inhalation MRL based
on Stewart et al. (1975) Acetone:
Development of a Biological Standard
for the Industrial Worker by Breath
Analysis, Cincinnati, OH: NIOSH.
NTIS PB82-172917
63 FR 64371 (U.S. EPA, 1998b)
63 FR 64371 (U.S. EPA, 1998b)
63 FR 64371 (U.S. EPA, 1998b)
63 FR 64371 (U.S. EPA, 1998b)
63 FR 64371 (U.S. EPA, 1998b)
Cited in Health and Environmental
Effects Profile (HEEP) for Pyridine
(EPA/600/X-86-168)
ATSDR chronic inhalation MRL based
on Ferroni et al. (1 992)
Neurobehavioral and neuroendocrine
effects of occupational exposure to
perchloroethylene. Neurotoxicology
12:243-247
Superfund risk issue paper (U.S. EPA
1996b)
ATSDR chronic inhalation MRL based
on Uchida et al. (1993) Symptoms
and signs in workers exposed
predominantly to xylenes. IntArch
Occup Environ Health 64:597-605.
5.2 Chronic Inhalation Health Benchmarks Derived for IWAIR
Chronic inhalation health benchmarks for constituents lacking IRIS, HE AST, alternative
EPA, or ATSDR values were developed for IWAIR. RfCs were developed for
2-Chlorophenol
Cresols
1,4-Dioxane
Ethylene glycol
Methanol.
5-6
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IWAIR Technical Background Document
Section 5.0
For cresols, 1,4-dioxane, ethylene glycol, and methanol, appropriate inhalation studies
were identified and RfCs were developed using EPA's standard RfC methodology as detailed in
Methods for Derivation of Inhalation Reference Concentrations and Application of Inhalation
Dosimetry(U.S. EPA, 1994b). For 2-chlorophenol, an RfC was developed using route-to-route
extrapolation of the oral RfD for 2-chlorophenol (U.S. EPA, 1998a).
Inhalation cancer slope factors were developed for
Bromodichloromethane
Chlorodibromomethane
7,12-Dimethylbenz[a]anthracene
2,4-Dinitrotoluene
3-Methylcholanthrene
o-Toluidine.
For bromodichloromethane, Chlorodibromomethane, 2,4-dinitrotoluene, and o-toluidine,
the oral CSFs (U.S. EPA, 1997b, 1998a) were used to develop inhalation CSFs for the
compounds. For 7,12-dimethylbenz[a]anthracene and 3-methylcholanthrene, inhalation URFs
developed by California's EPA (CalEPA,1997b) were used as the cancer benchmarks.
Table 5-3 summarizes the RfCs, inhalation unit risk factors, and inhalation cancer slope
factors that were derived; the method of development and critical studies used; and the target
organs identified. Details on the derivation of these inhalation benchmark values are provided in
Appendix C.
5-7
-------
00
Table 5-3. Chronic Inhalation Health Benchmarks Derived for IWAIR
1 CAS#
75-27-4
124-48-1
95-57-8
1319-77-3
57-97-6
95-65-8
121-14-2
123-91-1
107-21-1
67-56-1
56-49-5
95-53-4
Chemical Name
Bromodichloromethane
(dichlorobromomethane)
Chlorodibromomethane
(dibromochloromethane)
2-Chlorophenol (o-)
Cresols, total
7,12-
Dimethylbenz[a]anthracene
3,4-Dimethylphenol
2,4-Dinitrotoluene
1,4-Dioxane
(1,4-diethyleneoxide)
Ethylene glycol
Methanol
3-Methylcholanthrene
o-Toluidine
Inhalation Benchmark
and Benchmark Value
Inhal CSF = 6.2E-02 per mg/kg/d
Inhal URF = 1.8E-05 per ug/m3
Inhal CSF = 8.4E-02 per mg/kg/d
Inhal URF = 2.4E-05 per ng/m3
RfC = 0.0014 mg/m3
RfC = 0.0004 mg/m3
Inhal CSF = 8.4E+01 per mg/kg/d
Inhal URF = 2.4E-02 per ng/m3
NA - RfC derivation is inappropriate
Inhal CSF = 6.8E-01 per mg/kg/d
Inhal URF=1.9E-04 per |ag/m3
RfC = 0.8 mg/m3
RfC= 0.6 mg/m3
RfC =13 mg/m3
Inhal CSF = 7.4E+00 per mg/kg/d
Inhal URF = 2.1E-03 per |ag/m3
Inhal CSF = 2.4E-01 per mg/kg/d
Inhal URF = 6.9E-05 per ug/m3
HfC Target
Organ
Repro/
developmental
Hematological
Liver, kidney,
hematological
Respiratory
Developmental
1
Method of Derivation |
Inhal CSF and URF based on IRIS oral CSF
(renal)
Inhal CSF and URF based on IRIS oral CSF
(hepatocellular adenoma/carcinoma)
Route-to-route extrapolation of IRIS RfD
(0.005 mg/kg/d for reproductive effects)
Standard RfC derivation based on: Uzhdavini
etal. (1972)
Inhal CSF and URF derived by CalEPA
(1997b) based on TD50 approach
Inhal CSF and URF based on IRIS oral CSF
(liver, mammary gland)
Standard RfC derivation based on Torkelson
etal. (1974)
Derived using standard RfC methodology
Standard RfC derivation based on Rogers et al.
(1993)
Inhal CSF and URF derived by CalEPA
(1997b) based on TD50 approach
Inhal CSF and URF based on HEAST oral CSF
(skin fibroma)
8
*
3
I
§
-------
IWAIR Technical Background Document
Section 6.O
6.0 Calculation of Risk/Hazard Quotient or
Waste Concentration
This section describes how IWAIR calculates risk or waste concentration using the
emission rate, dispersion factor, exposure factors, and health benchmarks described in previous
chapters.
6.1 Forward Calculation of Risk or Hazard Quotient
To calculate risk, the air concentration must first be calculated from the WMU emission
rate and the dispersion factor, as follows:
Cair,j = (Ej X 106 Ug/g) X DF
(6-1)
where
'air.j
E
DF
air concentration of chemical j (ug/m3)
volatile emission rate of chemical j ([g/m2-s])
dispersion factor ([ug/m3]|/[ug/m2-s]).
The risk or hazard quotient is calculated based on the calculated air concentration and the
exposure factors.
Risk for carcinogens is calculated as follows:
., x 1CT3 :
where
Risk,
CSFj
ED£
EF
AT
Risk -
S
x CSFj x EF
AT x 365 d/yr
(6-2)
individual risk for chemical j (unitless)
air concentration for chemical j ([ug/m3])
cancer slope factor for chemical j (per mg/kg-d)
index on age group (e.g., <1 yr, 1-5 yr, 6-11 yr, 12-19 yr, adult)
inhalation rate for age group i (m3/d)
exposure duration for age group i (yr)
exposure frequency (d/yr)
body weight for age group i (kg)
averaging time (yr) = 70.
6-1
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IWAIR Technical Background Document
Section 6.0
Averaging time is a fixed input to this equation because it must be consistent with the averaging
time used to develop the cancer slope factor. For workers, only exposure factors for adult
workers are used.
IWAIR also calculates the cumulative risk for all carcinogens modeled. This is a simple
sum of the chemical-specific risks already calculated, as follows:
N
CumRisk =
(6-3)
where
CumRisk
j
N
Risk,
cumulative individual risk for all carcinogens modeled (unitless)
index on chemical
number of carcinogens modeled
individual risk for chemical j (unitless).
The hazard quotient for noncarcinogens was calculated as follows:
HO - Cair.j x
(6-4)
where
= hazard quotient for chemical j (unitless)
= air concentration for chemical j ([jug/m3])
= reference concentration for chemical j (mg/m3).
No cumulative hazard quotient is calculated for noncarcinogens. Such summing of
hazard quotients is appropriate only when the chemicals involved have the same target organ.
6.2 Backward Calculation of Waste Concentration
The backward calculation of protective waste concentration from a target risk or hazard
quotient is somewhat more complex than a forward calculation of risk, because care must be
taken to ensure that a physically impossible result is not achieved. To ensure that result, an
iterative forward calculation methodology adapted from the Newton-Raphson method was used
in IWAIR. The following subsections describe the constraints on backcalculated waste
concentrations to reflect physical limitations, the calculation of air concentration for the
backcalculation, the Newton-Raphson method, and the application of that method in IWAIR.
6-2
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FWAIR Technical Background Document
Section 6.0
6.2.1 Constraints on Backcalculated Waste Concentrations to Reflect Physical
Limitations
Wastes are typically assumed to be aqueous phase (i.e., dilute wastes that partition
primarily to water within the soil). However, aqueous phase wastes can only occur in land-based
units up to the soil saturation limit. At concentrations above the soil saturation limit, wastes can
only occur in oily phase. The soil saturation limit is calculated as follows:
c - --
sat
(6-5)
where
Csat =
s
Pb =
ew
H'
e,,
soil saturation limit (mg/kg)
solubility limit (mg/L)
bulk density of soil / waste matrix (kg/L)
soil-water partition coefficient (L/kg)
water-filled soil porosity (unitless)
dimensionless Henry's law constant (unitless = H/RT)
air-filled soil porosity (unitless).
Wastes can also occur in the oily phase at concentrations below the soil saturation limit,
but, for most chemicals, the aqueous phase produces greater emissions than the organic phase for
the same concentration and, therefore, greater risk. A few chemicals (most notably
formaldehyde) have greater emissions (and therefore greater risk) from the oily phase than the
aqueous phase.
For surface impoundments, the concentration limit for the aqueous phase is the solubility
of the chemical in water.
Regardless of whether the chemical is in the aqueous or oily phase, the concentration can
not exceed 1,000,000 mg/kg or mg/L (ppm) by definition.
6.2.2 General Newton-Raphson Method
The Newton-Raphson method is a commonly used formula for locating the root of an
equation; i.e., the value of x at which f(x) is zero (Chapra and Canale, 1985). The method is
based on the geometrical argument that the intersection of a tangent to a function at an initial
guess, Xj with the x axis is a better approximation of the root than Xj. As illustrated in Figure 6-1,
the method can be adapted to a nonzero target value of f(x), a.
6-3
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IWAIR Technical Background Document
Section 6.0
Figure 6-1. Graphical interpretation of the Newton-Raphson Method.
Mathematically, the slope of this tangent, f (x;) is given as follows:
(6-6)
where
f(Xi)
K
= the slope of f (x) at x;
= the value of f(x) at x;
= the target value for f(x)
= the initial guess for x
= the next value of x.
6-4
-------
IWAIR Technical Background Document
Section 6.0
This can be rearranged as follows to solve for xi+1:
(6-7)
Equation 6-7 gives an improved value of x for the next iteration; however, to use it,
must first be estimated. This was done using finite difference methods:
f(Xj + e)-f(Xj)
(6-8)
where
f (x.) = the slope of f(x) at Xj
f(Xj + e) = the value of f(x) at x; + e
X; = the initial guess for x
e = a small value relative to Xj.
For IWAIR, e was. set to 0. lx;.
This method can be applied iteratively until f(x) is within a predefined tolerance of the
target, oc. In this case, the stopping criteria was set to f(x) = a ± 1%.
6.2.3 Application of Newton-Raphson Method to Account for Aqueous vs. Oily Phase
The variable x in the general Newton-Raphson method is waste concentation, and the
function f(x) is the calculation of either risk or hazard quotient presented in Equations 6-2 and
6-4. However, the air concentration used in those equations differs slightly from Equation 6-1
because the emission rate is normalized to a unit concentration in the WMU rather than an actual
emission rate associated with a specific concentration. For the backcalculation, air concentration
is calculated as follows:
Cair = (C
wxEunit x 106 |ag/g) x DF
(6-9)
where
DF =
air concentration (ug/m3)
waste concentration (mg/kg or mg/L)
normalized volatile emission rate of constituent ([g/m2-s]/[mg/kg] or
[g/m2-s]/[mg/L])
dispersion factor ([ng/m3]/[ug/m2-s]).
Due to the difference in emission rates in the aqueous and oily phases, f(x) is actually a
discontinuous function, with a break at the soil saturation limit or the solubility. To account for
this, IWAIR first checks the maximum possible concentration in each phase (the soil saturation
6-5
-------
IWAIR Technical Background Document
Section 6.0
limit or solubility for the aqueous phase and 1 million ppm for the oily phase) to see if the target
risk or hazard quotient is achievable in that phase. If it is, the Newton-Raphson method is
applied to that phase. If it is not, the waste concentration for that phase is set to the maximum,
and the risk or hazard quotient associated with that concentration is saved as the maximum risk
or hazard quotient achievable in that phase. Finally, IWAIR compares the results for the two
phases and outputs the smallest concentration that achieves the target risk or hazard quotient. If
the target risk or hazard quotient cannot be achieved in one or both phases, IWAIR outputs the
concentration that maximizes risk or hazard quotient.
6-6
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IWAIR Technical Background Document
Section 7.0
7.0 References
Agency for Toxic Substances and Disease Registry (ATSDR). Minimal Risk Levels (MRLs) for
Hazardous Substances. http://atsdrl.atsdr.cdc.gov:8080/mrls.html
Bailey, Robert G., Peter E. Avers, Thomas King, W. Henry McNab, eds. 1994. Ecoregions and
subregions of the United States (map). Washington DC; U.S. Geological Survey. Scale
1:7,500,000; colored. Accompanied by a supplementary table of map unit descriptions compiled
and edited by McNab, W. Henry, and Bailey, Robert G. Prepared for the U.S. Department of
Agriculture, Forest Service, http://www.epa.gov/docs/grdwebpg/bailey/
CalEPA (California Environmental Protection Agency). 1997a. Technical Support Document
for the Determination ofNoncancer Chronic Reference Exposure Levels. Draft for Public
Review. Office of Environmental Health Hazard Assessment, Air Toxicology and Epidemiology
Section, Berkeley, CA.
CalEPA (California Environmental Protection Agency). 1997b. Air Toxics Hot Spots Program
Risk Assessment Guidelines: Technical Support Document for Determining Cancer Potency
Factors. Draft for Public Comment. Office of Environmental Health Hazard Assessment,
Berkeley, CA.
Chapra, Steven C., and Raymond P. Canale. 1985. Numerical Methods for Engineers with
Personal Computer Applications. McGraw-Hill Book Company. New York.
Coburn, J., C. Allen, D. Green, and K. Leese. 1988. Site Visits of'Aerated and Nonaerated
Impoundments. Summary Report. U.S. EPA, Contract No. 68-03-3253, Work Assignment 3-8.
Research Triangle Institute, Research Triangle Park, NC.
ERG (Eastern Research Group) and Abt Associates. 1992. Technical Support Document for the
Surface Disposal of Sewage Sludge. Prepared for U.S. Environmental Protection Agency, Office
of Water, Washington, DC. November 1992.
EQM (Environmental Quality Management, Inc.) and E.H. Pechan & Associates. 1993.
Evaluation of Dispersion Equations in Risk Assessment Guidance for Superfund (RAGS):
Volume I - Human Health Evaluation Manual. Prepared for U.S. Environmental Protection
Agency, Office of Emergency and Remedial Response, Toxics Integration Branch, Washington,
DC.
Ferroni, C., L. Selis, A. Mutti, et al. 1992. Neurobehavioral and neuroendocrine effects of
ocupational exposure to perchloroethylene. Neurotoxicology 12:243-247.
7-1
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IWAIR Technical Background Document
Section 7.0
Li, C., and E. Voudrias. 1994. Migration and sorption of jet fuel cycloalkane and aromatic
vapors in unsaturated soil. Environmental Progress 13(4):290-297.
Loehr, R., D. Erickson, and L. Kelmar. 1993. Characteristics of residues at hazardous waste
land treatment units. Water Research 27(7):1127-1138.
RTI (Research Triangle Institute). 1988. Site Visits of Aerated and Nonaerated Impoundments -
Summary Report. Prepared for U.S. Environmental Protection Agency under Contract No. 68-
03-3253, Work Assignment No. 3-8, Hazardous Waste Engineering Research Laboratory,
Cincinnati, OH. April.
RTI (Research Triangle Institute). 1995. Technical Support Document for Hazardous Waste
Identification Rule (HWIR): Risk Assessment for Human and Ecological Receptors. Prepared for
U.S. Environmental Protection Agency, Office of Solid Waste, Washington, DC.
Rogers et al. 1993. The developmental toxicity of inhaled methanol in the CD-I mouse, with
quantitative dose-response modeling for estimation of benchmark doses. Teratology 47(3): 175-
188.
Shroeder, K., R. Clickner, and E. Miller. 1987. Screening Survey of Industrial Subtitle D
Establishments. Draft Final Report. Westat, Inc., Rockville, MD. Prepared for U.S.
Environmental Protection Agency, Office of Solid Waste. EPA Contract 68-01-7359. December.
Schroeder, P. R., T.S. Dozier, P.A. Zappi, B.M; McEnroe, J.W. Sjostrom, and R.L. Peyton.
1994. "The Hydrologic Evaluation of Landfill Performance (HELP) Model: Engineering
Documentation for Version 3," EPA/600/9-94/xxx, U.S. Environmental Protection Agency Risk
Reduction Engineering Laboratory, Cincinnati, OH.
Stewart, R.D., C.L. Hake, A. Wu, et al. 1975. Acetone: Development of a Biological Standard
for the industrial worker by Breath Analysis. NTIS PB82-172917. NIOSH, Cincinnati, OH.
Torkelson et al. 1974. 1,4-Dioxane. II. Results of a 2-year inhalation study in rats. Toxicol
Appl Pharmacol 30:287-298.
Uchida, Y., H. Nakatsuka, H. Ukai, et al. 1993. Symptoms and signs in workers exposed
predominantly to xylenes. Int Arch Occup Environ Health 64:597-605.
U.S. (Environmental Protection Agency). 1986. Health and Environmental Effects Profile for
Pyridine. Environmental Criteria and Assessment Office, Office of Research and Development,
Cincinnati, OH. EPA/600/X-86-168.
U.S. EPA (Environmental Protection Agency). 1989. Development of Risk Assessment
Methodology for Municipal Sludge Landfilling. EPA 600 6-90-008. Office of Research and
Development, Washington, DC. August.
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IWAIR Technical Background Document
Section 7.0
U.S. EPA (Environmental Protection Agency). 1991. Hazardous Waste TSDF - Background
Information for Proposed Air Emissions Standards. Appendix C. EPA-450/3-89-023a. Office
of Air Quality Planning and Standards, Research Triangle Park, North Carolina. Pp. C-19
through C-30.
U.S. EPA (Environmental Protection Agency). 1992. Technical Support Document for the Land
Application of Sewage Sludge - Volume H. EPA 822/R-93-001b. Office of Water, Washington,
DC. November.
U.S. EPA (Environmental Protection Agency). 1994a. Air Emissions Models for Waste and
Wastewater. EPA-453/R-94-080A. Appendix C. Office of Air Quality Planning and Standards,
Research Triangle Park, NC.
U.S. EPA (Environmental Protection Agency). 1994b. Methods for Derivation of Inhalation
Reference Concentrations and Application of Inhalation Dosimetry. EPA/600/8-90-066F.
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Office of Research and Development, Research Triangle Park, NC.
U.S. EPA (Environmental Protection Agency). 1995. User's Guide for the Industrial Source
Complex (ISC3) Dispersion Models. EPA-454/B-95-003a. Office of Air Quality Planning and
Standards, Research Triangle Park, NC.
U.S. EPA (Environmental Protection Agency). 1996a. Hazardous Waste Management System:
Identification and Listing of Hazardous Waste; Solvents; CERCLA Hazardous Substance
Designation and Reportable Quantities; Proposed Rule. 61 FR 42317-354. August 14.
U.S. EPA (Environmental Protection Agency). 1996b. Risk Assessment Issue Paper for:
Derivation of a Chronic RfCfor 1,1,1-Trichloroethane (CASRN 71-55-6). 96-007d/8-09-96.
National Center for Environmental Assessment. Superfund Technical Support Center,
Cincinnati, OH.
U.S. EPA (Environmental Protection Agency). 1997b. Health Effects Assessment Summary
Tables (HEAST). EPA-540-R-97-036. FY 1997 Update. Office of Solid Waste and Emergency
Response, Washington, DC.
U.S. Environmental Protection Agency. 1997a. Exposure Factors Handbook. Draft. Office of
Research and Development, National Center for Environmental Assessment.
U.S. EPA (Environmental Protection Agency). 1998a Integrated Risk Information System
(IRIS) - online. Duluth, MN. http://www.epa.gov/iris/
U.S. EPA (Environmental Protection Agency). 1998b. Hazardous Waste Management System:
Identification and Listing of Hazardous Waste; Solvents; Final Rule. 63 FR 64371-402,
November 19.
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IWAIR Technical Background Document
Section 7.0
U.S. EPA (Environmental Protection Agency), (no date available). Risk Assessment Issue
Paper for: Carcinogenicity Information for Trichloroethylene (TCE)(CASRN 79-01-6).
National Center for Environmental Assessment, Superfund Technical Support Center,
Cincinnati, OH.
Uzhdavini, E.R., Astafyeva K, Mamayeva AA, Bakhtizina GZ. 1972. [Inhalation toxicity of o-
cresol]. Trudy Ufimskogo Nauchno-Isseldovatel'skogo Institute Gigiyeny Profzabolevaniya,
7:115-9. (Russian)
7-4
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Appendix A
Chemical-Specific Data Used in
Emission Modeling
-------
-------
IWAIR Technical Background Document
Appendix A
A. Chemical-Specific Data Used in
Emission Modeling
Key chemical-specific input parameters include: air-liquid equilibrium partitioning
coefficient (vapor pressure or Henry's law constant), liquid-solid equilibrium partitioning
coefficient (log octanol-water partition coefficient for organics), biodegradation rate constants,
and liquid and air diffusivities. The HWIR chemical properties database (RTI, 1995) was used
as the primary data source for the physical and chemical properties for the constituents being
modeled! This chemical properties database provided the following chemical-specific input
parameters: molecular weight, vapor pressure, Henry's law constant, solubility, liquid and air
diffusivities, log octanol-water partition coefficient, and the soil biodegradation rate constants.
The CHEMDAT8 chemical properties database (U.S. EPA, 1994) was used as a secondary data
source for the physical and chemical properties not included in the HWIR data base. The
CHEMDAT8 chemical properties database primarily provided the following chemical-specific
input parameters: density, boiling point, Antoine's coefficients (for adjusting vapor pressure to
temperature), and biodegradation rate constants for surface impoundments. Hydrolysis rates
were taken from Kollig et al. (1993). The biodegradation rate constants in the downloaded
CHEMDAT8 data base file were compared with the values reported in the summary report that
provided the basis for the CHEMDAT8 surface impoundment biodegradation rate values
(Coburn et al., 1988). Tank biodegradation rates constants for compounds with no data were
assigned biodegradation rates equal to the most similar compound in the biodegradation rate data
base. The chemical specific input parameters used for the emission model estimates are
presented in Table A-1.
References
Coburn, J., C. Allen, D. Green, and K. Leese. 1988. Site Visits of Aerated and Nonaerated
Impoundments. Summary Report. U.S. EPA, Contract No. 68-03-3253, Work
Assignment 3-8. Research Triangle Institute, Research Triangle Park, NC.
Kollig, H.P., J.J. Ellington, S.W. Karickhoff, B.E. Kitchens, J.M. Long, E.J. Weber, and N.L.
Wolfe. 1993. Environmental Fate Constants for Organic Chemicals Under
Consideration for EPA's Hazardous Waste Identification Projects. U.S. Environmental
Protection Agency, Office of Research and Development, Athens, GA.
RTI (Research Triangle Institute). 1995. Technical Support Document for the Hazardous Waste
Identification Rule: Risk Assessment for Human Health and Ecological Receptors
Volumes I & II. Research Triangle Park, NC.
U.S. Environmental Protection Agency. 1994. Air Emissions Models for Waste and
Wastewater. EPA-453/R-94-080A. Appendix C. Office of Air Quality Planning and
Standards, Research Triangle Park, NC.
A-l
-------
Table A-1. Chemical Specific Input Parameters
i
i
| CASf COMPOUND NAME
50000 Formaldehyde
50328 Benzo(a)pyrene
55185 N-Nitrosodiethylamine
56235 Carbon tetrachloride
56495 3-Methylcholanthrene
57976 7, 1 2-Dimethylbenz[a]anthracene
62533 Aniline
67561 Methanol
67641 Acetone
67663 Chloroform
67721 Hexachloroethane
68122 N,N-Dimethyl formamide
71432 Benzene
71556 1,1,1-Trichloroethane
74839 Methyl bromide
74873 Methyl chloride
75014 Vinyl chloride
75058 Acetonitrile
75070 Acetaldehyde
75092 Methylene chloride
75150 Carbon disuifide
75218 Ethylene oxide
75252 Tribromomethane
75274 Bromodichloromethane
75354 1,1-Dichloroethylene
75569 Propylene oxide
75694 Trichlorofluoromethane
75718 Dichlorodifluoromethane
76131 1,1,2-Trichloro-1,2,2-
trifluoroethane
77474 Hexachlorocyclopentadiene
78591 Isophorone
78875 1,2-Dichloropropane
Mol. Wt.
(g/mol)
30.03
252.32
102.14
153.82
268.36
256.35
93.13
32.04
58.08
119.38
236.74
73.09
78.11
133.4
94.94
50.49
62.5
41.05
44.05
84.93
76.14
44.06
252.73
163.83
96.94
58.08
137.37
120.91
187.38
272.77
138.21
112.99
Density
(g/cc)
0.97
1.11
1.59
1.02
1.02
1.02
0.79
0.79
1.49
2.09
0.9445
0.87
1.33
1.41
0.95
0.91
0.78
0.788
1.34
1.26
0.87
2.89
1.97
1.213
0.83
1.49
1.41
1.41
1.7
0.92
1.156
VAP. H Law
Press. Const.
{fltrri"
(mmHg) m3/mol)
5240 3.4E-07
5.5E-09 1.1E-06
0.86 3.6E-06
115 0.0304
7.7E-09 9.4E-07
5.6E-09 3.1E-08
0.49 1.9E-06
126 4.6E-06
230 3.9E-05
197 0.00367
0.21 0.00389
4 1.9E-07
95 0.00558
124 0.0172
1620 0.00624
4300 0.00882
2980 0.027
91.1 3.5E-05
902 7.9E-05
433 0.00219
359 0.03022
1094 0.00012
5.51 0.00054
50 0.0016
600 0.0261
532.1 8.5E-05
803 0.097
4850 0.343
332 0.4815
0.0596 0.027
0.438 6.6E-06
52 0.0028
Diffusivity Dlffustvtty
in.Water in Air
(cm2/sec) (cm2/sec)
1.98E-05 1.78E-01
9.00E-06 4.30E-02
8.00E-06 8.00E-02
8.80E-06 7.80E-02
5.36E-06 2.09E-02
4.98E-06 4.61 E-02
8.30E-06 7.00E-02
1.64E-05 1.50E-01
1.14E-05 1.24E-01
1.00E-05 1.04E-01
6.80E-06 2.49E-03
1.92E-05 9.39E-02
9.80E-06 8.80E-02
8.80E-06 7.80E-02
1.21E-05 7.28E-02
6.50E-06 1.26E-01
1.23E-05 1.06E-01
1.66E-05 1.28E-01
1.41E-05 1.24E-01
1.17E-05 1.01E-01
1.00E-05 1.04E-01
1.45E-05 1.04E-01
1.03E-05 1.49E-02
1.06E-05 2.98E-02
1.04E-05 9.00E-02
1.00E-05 1.04E-01
9.70E-06 8.70E-02
8.00E-06 8.00E-02
8.20E-06 7.80E-02
6.16E-06 5.61 E-02
6.76E-06 6.23E-02
8.73E-06 7.82E-02
Antoines' Vapor
Pressure Coefficients
ABC
7.195 971 244
9.246 3724 273
273
6.934 1242 230
8.164 3364 273
6.955 2163 171
6.950 1467 177
7.897 1474 229
7.117 1211 230
6.493 929 196
7.228 1348 133
6.928 1401 196
6.905 1211 221
6.827 1147 219
7.566 1301 273
7.093 949 249
6.991 969 251
7.119 1314 230
8.005 1600 292
6.968 1074 223
6.942 1169 242
7.128 1055 238
7.988 2159 273
7.966 1847 273
6.972 1099 237
7.067 1133 236
6.884 1043 237
7.590 1329 273
8.784 1894 273
8.415 2835 273
7.963 2481 273
6.980 1380 223
log
Oct
Water
Part.
Coeff.
-0.05
6.11
0.48
2.73
6.42
6.62
0.98
-0.71
-0.24
1.92
4
-1.01
2.13
2.48
1.19
0.91
1.5
-0.34
1.25
1.25
2
-0.3
2.35
2.1
2.13
0.03
2.53
2.16
3.16
5.39
1.7
1.97
Km ax
mnVO/ci-
'"y *-*/y
hr.
5
0.001
4.4
1.5
0.001
0.001
7.1
18
1.3
28
0.001
9.7
19
3.5
10.76
10.76
10.76
9.7
82.42
18
15.3
4.2
10.76
10.76
10.76
17.56
1.076
1.076
0.001
0.001
15.3
17
K1
L/g-hr.
0.25
0.31
0.45
1.50
0.31
0.31
21.00
0.20
1.15
0.79
0.03
0.13
1.40
0.74
0.35
0.72
0.14
0.10
0.20
0.38
0.89
0.91
1.01
0.70
0.90
0.17
0.12
0.07
0.03
0.03
0.60
1.40
Soil
Hydro!. Bfodeg.
Rate Rate
sec-1 sec-1
0 6.08E-10
0 4.61 E-08
1.56E-08
0 3.13E-08
0 1.22E-07
0 2.43E-09
0 6.95E-10
0 6.08E-10
0 6.08E-10
0 2.43E-09
0 1.56E-08
0 1.00E-20
0 1.39E-09
2E-08 2.37E-08
0 2.43E-09
0 2.43E-09
0 1.56E-08
0 2.43E-09
0 1.00E-20
0 2.43E-09
0 1.00E-20
0 1.00E-20
0 1.56E-08
0 1.00E-20
0 1.56E-08
0 1.00E-20
0 3.13E-08
0 1.56E-08
0 1.00E-20
0 2.43E-09
0 2.43E-09
0 1.12E-07
Solubility i
mg/L !
5.50E+05
2.50E-02
9.30E+04
7.93E+02
3.23E-03
2.50E-02
3.61 E+04
1. OOE+06
1. OOE+06
7.92E+03
5.00E+01
1. OOE+06
1 .75E+03
1.33E+03
1.52E+04
5.33E+03
2.76E+03
1 .OOE+06
1 .OOE+06
1.30E+04
1.19E+03
3.83E+05
3.10E+03
6.74E+03
2.25E+03
4.76E+05
1.10E+03
2.80E+02
1.70E+02
1.80E+00
1.20E+04
) snPxns
(continued)
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-------
IWAIR Technical Background Document
Appendix A
*(
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13
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A-3
-------
Table A-1. Chemical Specific Input Parameters
I
j CAS# COMPOUND NAME
108054 Vinyl acetate
1 081 01 Methyl isbbutyl ketone
108883 Toluene
108907 Chlorobenzene
108930 Cyolohexanol
108952 Phenol
109864 2-Methoxyethanol
110496 2-Methoxyethanol acetate
110543 n-Hexane
110805 2-Ethoxyethanol
110861 Pyridine
1 1 1 159 2-Ethoxyethanol acetate
1 1 8741 Hexachlorobenzene
120821 1,2,4-Trichlorobenzene
1 21 1 42 2,4-Dinitrotoluene
121448 Triethylamine
122667 1 ,2-Diphenylhydrazine
123911 1,4-Dioxane
124481 Chlorodibromomethane
126998 Chloroprene
127184 Tetrachloroethylene
630206 1,1,1 ,2-Tetrachloroethane
924163 N-Nitrosodi-n-butylamine
930552 N-Nitrosopyrrolidine
1319773 Cresols (total)
1330207 Xylenes
1634044 Methyl tert-butyl ether
1746016 2,3,7,8-TCDD
7439976 Mercury
1 0061 01 5 cis-1 ,3-Dichloropropylene
1 0061 026 trans-1 ,3-Dichloropropylene
Mol. Wt.
(g/mol)
86.09
100.16
92.14
112.56
100.2
94.11
76.09
130.15
86.18
90.12
79.1
143.01
284.78
181.45
182.14
101.19
184.24
88.11
208.28
88.54
165.83
167.85
158.24
100.12
108.1
106.17
88
322
200.59
110.97
110.97
VAP.
Density Press.
(g/cc) (mmHg)
0.93 90.2
0.8 19.9
0.87 28.4
1.11 12
0.95 1.22
1.07 0.276
2.55697
9.28503
0.66 151
0.9 5.31
0.98 20.8
11.6912
2.04 1.8E-05
1.41 0.431
1.31 0.00015
0.7326 57.07
1.19 0.00043
1.03 38.1
2.451 4.9
0.958 213.658
1.624 18.6
1.59 12.03
0.03
0.092
1.03 0.3
0.86 8.04178
0.97 185.949
.1.41 7.4E-10
0.00196
1.2 32.8
1.2 23.3
HLaw
Const
(atm-
m3/mol)
0.00051
0.00014
0.00664
0.0037
4.5E-06
4E-07
2.6E-07
1.6E-06
0.0143
3.5E-07
8.9E-06
2.2E-06
0.00132
0.00142
9.3E-08
0.00014
1.5E-06
4.8E-06
0.00078
0.0143
0.0184
0.00242
0.00032
1.2E-08
1.6E-06
0.00604
0.00056
1.6E-05
0.0092
0.00176
0.00125
Diffusivity
in Water
(cm2feec)
9.20E-06
7.80E-06
8.60E-06
8.70E-06
8.31 E-06
9.10E-06
8.00E-06
8.00E-06
7.77E-06
9.57E-06
7.60E-06
8.00E-06
5.91 E-06
8.23E-06
7.06E-06
7.88E-06
7.36E-06
1.02E-05
1.05E-05
1.00E-05
8.20E-06
7.90E-06
8.00E-06
1.04E-05
9.30E-06
9.34E-06
1.05E-05
8.00E-06
6.30E-06
1.10E-05
1.10E-05
Diffusivity
in Air
(cm2/sec)
8.50E-02
7.50E-02
8.70E-02
7.30E-02
2.14E-01
8.20E-02
8.00E-02
8.00E-02
2.00E-01
9.47E-02
9.10E-02
8.00E-02
5.42E-02
3.00E-02
2.03E-01
8.81 E-02
3.17E-02
2.29E-01
1.96E-02
1.04E-01
7.20E-02
7.10E-02
8.00E-02
7.36E-02
6.94E-02
7.14E-02
1.02E-01
4.70E-02
3.07E-02
5.85E-02
5.85E-02
log
Antoines' Vapor Oct
Pressure Coefficients Water
A B
7.210 1296
6.672 1168
6.954 1345
6.978 1431
6.255 913
7.133 1517
6.876 1171
7.874 1844
7.041 1374
9.554 3249
7.706 2243
7.981 3074
6.959 1272
13.836 5403
7.351 1518
8.220 2100
6.161 783
6.976 1387
6.894 1355
8.850 "2795
7.940 2090
6.852 1104
6.977 2377
6.807 1328
6.807 1328
Part.
C Coeff.
227 0.73
192 1.19
219 2.75
218 2.86
109 1.577
175 1.48
273 -0.77
273 0
224 4
234 -0.1
215 0.67
273 0
203 5.89
253 4.01
280 2.01
223 1.45
273 2.94
238 -0.39
273 2.17
180 2.08
218 2.67
192 2.63
273 2.41
273 -0.19
273 0
273 3.17
223 1.901
159 6.64
273 4.978
230 2
230 2
Km ax
mgVO/g-
hr.
17.56
0.74
6.7
0.39
17.56
97
19.8
19.8
15.3
19.8
35.03
19.8
0.001
1.076
9.7
9.7
19
17.56
10.76
10.76
6.2
6.2
0.0001
0.0001
23
40.8
17.56
0.001
10.76
10.76
K1
L/g-hr.
0.30
0.45
2.40
10.00
0.54
13.00
1.00
1.00
1.47
1.00
0.24
1.00
0.03
0.44
0.78
1.06
1.91
0.39
0.04
0.22
0.68
0.68
1.00
1.00
17.00
1.80
0.71
0.03
0.76
0.76
Soil
Hydro!. Biodeg. I
Rate Rate Solubility \
sec-1 sec-1 mg/L
0 1.00E-20 2.00E+04
0 6.08E-10 1.90E+04
0 1.91E-09 5.26E+02
0 1.30E-08 4.72E+02
0 1.00E-20 3.60E+04
0 8.69E-10 8.28E+04
1.00E-20 1.00E+06
1.00E-20 1.00E+06
0 1.00E-20 1.24E+01
0 2.43E-09 1.00E+06
0 6.08E-10 1.00E+06
1.00E-20 1.00E+06
0 1.82E-07 6.20E+00
0 1.56E-08 3.00E+02
0 1.56E-08 2.70E+02
0 1.00E-20 5.50E+04
0 1.00E-20 6.80E+01
0 1.56E-08 1.00E+06
0 1.56E-08 2.60E+03
0 1.56E-08 1T4E+03
0 3.13E-08 2.00E+02
0 5.81 E-09 1.10E+03
1.00E-20 1.27E+03
1.56E-08 1.00E+06
0 1.00E-20 2.20E+04
0 2.43E-09 1.86E+02
0 1.00E-20 3.88E+04
0 1.00E-20 1.90E-05
1.00E-20 5.62E-02
0 9.81 E-10 2.72E+03
0 9.81 E-10 2.72E+03
S
S3
1
5
1
3
it
r»<
i3
K
«f
3
»
-------
Appendix B
Summary Data for 29 Meteorological Stations
-------
-------
IWAIR Technical Background Document
Appendix B
Table B-l.
, Meteorological Data for 29
^^^^^^^^^^^^^'^^:4-r*^*
^allft^^r^i/*!i^^§^^felJBrectioii''"'~ v?>'cn"'VT^'"''**:'Q/yr '.''*- ,
Albuquerque
Atlanta
Bismark
Boise
Casper
Charleston
Chicago
Cleveland
Denver
Fresno
Harrisburg
Hartford
Houston
Huntington
Las Vegas
Lincoln
Little Rock
Los Angeles
Miami
Minneapolis
Philadelphia
Phoenix
Portland
Raleigh-Durham
Salem
Salt Lake City
San Francisco
Seattle
Winnemucca
N
NW
SSE
ESE
SW
NE
SW
SW
s
WNW
W
S
SE
SW
SW
S
SW
wsw
E
SE
SW
E
S
SSW
S
SE
WNW
S ,
S
21
126
39
30
30
132
90
94
39
27
99
112
119
105
10
75
129
29
145
69
105
19
110
107
102
40
49
98
21
58
116
96
91
95
113
125
157
89
89
125
126
101
142
27
91
104
33
128
113
117
37
129
110
146
92
63
157
67
Meteorological Locations Used
"' ; i< /&%T^S^£;<,'r'- - J-ssZ'&iC '^y%fy's/''-^-s&$
'eimpeEatin-e^tWin.dJspeeaU,-;
^^c^^'^H^^^.
14
17
6
11
8
18
9
10
11
17
12
10
21
13
19
11
17
17
24
7
13
22
8
16
11
11
14
11
9
4.1
4.6
6.2
4.6
7.2
4.1
4.6
5.1
4.1
3.6
4.6
4.1
4.1
3.6
5.1
5.1
3.6
4.1
4.6
5.7
4.6
3.1
4.6
4.1
4.6
4.6
6.2
5.1
4.1
i&'tf't v^?x*?'"-";f':.i'<.^' vf '; fit: ^
f J^qu^cy^f , ;j
T,'^5^;«%|?.TJ
,,-* v->v>/\«.'*-y-'',^#?
^*- JK/S^)^-.'^;
22
21
33.2
21
47.3
19.1
31.7
33.6
20.9
7.4
16.6
21.9
16.3
8.2
25.9
31.1
14.4
14.7
25.5
35.2
25.6
6.8
23
14.5
15.2
20.1
37.4
22.1
17.2
B-l
-------
-------
Appendix C
Derivation of Chronic Inhalation
Noncancer and Cancer Health
Benchmark Values
-------
-------
TWAIR Technical Background Document
Appendix C
C.I Derivation of Inhalation Reference Concentrations
This section contains derivations of Reference Concentrations for:
2-Chlorophenol
Cresols
3,4-Dimethylphenol
1,4-Dioxane
Ethylene glycol
Methanol
C-l
-------
IWAIR Technical Background Document
Appendix C
RfC:
Basis for RfC:
Critical Study:
Critical Dose:
Critical Effect:
Species:
Route of Exposure:
Duration:
Uncertainty Factor:
Modifying Factor:
2-Chlorophenol
CAS #95-57-8
0.0014mg/m3
Route-to-route extrapolation from the RfD
Exon, J.H., and L.D. Roller. 1982. Effects of transplacental exposure to
chlorinated phenols. Environ Health Perspect 46:137-140 (as cited in
U.S. EPA, 1998).
5 mg/kg/d
[X ] NOAEL [ ] LOAEL
Increase in conception rate and number of stillbirths and decrease in
size of litters
Rat
Drinking water
10 weeks
1000:
10 for extrapolation from animals to humans
10 for protection of sensitive human subpopulations
10 for use of a subchronic study
1
Calculations:
RfC = RfD x 1/70 kg x 20 m3/d = 0.005 mg/kg/d x 1/70 kg x 20 m3/d = 0.0014 mg/m3
where:
70 kg = default adult human body weight
20 m3/d = default human daily rate of inhalation
Calculations assume 100% absorption.
Summary of Study:
The RfD is based on a NOAEL of 5 mg/kg/d with a LOAEL of 50 mg/kg/d for reproductive
effects in a subchronic drinking water study in rats (Exon and Roller, 1982, as cited in U.S. EPA,
1998). In this study, groups of 12 to 20 weanling female Sprague-Dawley rats were exposed to 0,
5, 50, or 500 ppm of 2-chlorophenol in the drinking water and bred after 10 weeks of
2-chlorophenol treatment. Treatment was continued during breeding, gestation, and weaning.
The weanling rats were evaluated for percent conception, litter size, birth weight, weaning
weight, number of stillbirths, and hematology (hematocrit, hemoglobin levels, red and white cell
counts, and mean corpuscular volume). The evaluations revealed an increase in the conception
rate and in the number of stillborns as well as a decrease in the size of the litters in the rats
exposed to 500 ppm, which can be converted to a dosage of 50 mg/kg/d-the LOAEL. No effects
C-2
-------
IWAIR Technical Background Document
Appendix C
were observed at 50 ppm, which can be converted to a dosage of 5 mg/kg/d. Dividing the
NOAEL of 5 mg/kg/d by an uncertainty factor of 1,000 (10 factors each for animal to human
extrapolation, interspecies variability, and the use of subchronic data), yields the RfD of 0.005
mg/kg/d (EPA, 1998).
Rationale for Route-to-Route Extrapolation:
A first pass in the liver or respiratory tract is not expected to contribute to the toxicity of
2-chlorophenol because it has been demonstrated that the toxic action of the lower chlorinated
phenols is due to the undissociated molecule. In studies with rats, it was observed that the
toxicity of chlorophenols administered via subcutaneous and intraperitoneal routes is similar to
that which is observed in orally administered chlorophenols (Deichmann and Keplinger, 1981).
Since the dermal irritation index for 2-chlorophenol is low, no significant portal of entry effect is
expected from inhalation exposure to 2-chlorophenol (HSDB, 1998).
Consequently, route-specific difference in toxicity is not expected for 2-chlorophenol. Therefore,
in accordance with EPA guidelines (U.S. EPA, 1994), the oral toxicity data for 2-chlorophenol
are adequate for use in the calculation of an inhalation RfC for the substance.
Strengths and Uncertainties:
The strength of the RfC is that it is based on an RfD on IRIS that has undergone rigorous EPA
peer review.
The major uncertainty of the RfC is the lack of inhalation toxicity studies in humans or animals
and the use of default values in the route-to-route extrapolation.
References:
Deichmann, W.B., andM.L. Keplinger. 1981. Aromatic Hydrocarbons. In: G.D. Clayton and
F.E. Clayton (eds). Patty's Industrial Hygiene and Toxicology. 3rd revised edition. Volume 2A:
Toxicology. New York: John Wiley and Sons, pp. 3325-3415.
Exon, J.H., and L.D. Koller. 1982. Effects of transplacental exposure to chlorinated phenols.
Environ Health Perspect 46:137-140 (as cited in U.S. EPA, 1998).
Hazardous Substances Databank (HSDB): 2-Chlorophenol. 1998. Online database. National
Library of Medicine, Bethesda, MD.
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NC:
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Office of Research and Development, U.S. EPA. EPA/600/8-90-066F.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
2-Chlorophenol. Environmental Criteria and Assessment Office, Office of Health and
Environmental Assessment, Cincinnati, OH.
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IWAIR Technical Background Document
Appendix C
Cresols
CAS #1319-77-3
RfC:
Critical Study:
Critical Dose:
Critical Effect:
Species:
Route of Exposure:
Duration:
Uncertainty Factor:
Modifying Factor:
Calculations:
RfC =
0.0004 mg/m3
Uzhdavini, E.R., K. Astaf yeva, A.A. Mamayeva, and G.Z. Bakhtizina.
1972. [Inhalation toxicity of o-cresol]. Trudy Ufimskogo Nauchno-
IsseldovateFskogo Institute Gigiyeny Profzabolevaniya, 7:115-9.
(Russian) [as cited in CalEPA, 1997, and U.S. EPA 1985, 1986]
9 mg/m3
[ ] NOAEL [X] LOAEL
Alterations in bone marrow cellularity
Rat
Inhalation
4 months
3000:
10 for use of a LOAEL
10 for extrapolation from animals to humans
10 for protection of sensitive human subpopulations
3 for extrapolation from subchronic to chronic exposure
1
-T- UP = 1.3 mg/m3 + 3000 = 0.0004 mg/m3
Summary of Study:
Male and female rats were exposed to 0 or 9.0 mg/m3 o-cresol via inhalation, first for 2 months
(6 h/d, 5 d/wk) and then for 2 more months (4 h/d, 5 d/wk) (Uzhdavini et al., 1972, as cited in
CalEPA, 1997). The following endpoints were examined: elemental conditioned defensive
reflex, white blood cell levels, bone marrow elements, and liver function (as indicated indirectly
by hexobarbital narcosis). Both exposed and control animals showed some loss of the defensive
reflex, with the effect occurring in all exposed animals before the end of the second month and in
control animals at later times. White blood cell counts were elevated in male animals, peaking at
the end of the exposure period and returning to normal 1 month after cessation of exposure.
Exposed animals also showed a statistically significant change in the leukoid-to-erythroid ratio in
the bone marrow. Liver toxicity was suggested by an extension of hexobarbital narcosis duration
in treated animals. A LOAEL of 9 mg/m3 for hematological effects was identified.
The LOAEL of 9 mg/m3 was adjusted for continuous exposure (1.3 mg/m3). A LOAE!^^ was
calculated as per EPA's inhalation dosimetry methodology (1994), using equation 4-48a
(category 3 - extrarespiratory effects). An uncertainty factor of 3000 was applied: 10 for use of a
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1WAIR Technical Background Document
Appendix C
LOAEL, 10 for extrapolation from humans to animals, 10 for human variability, and 3 for
extrapolation from subchronic to chronic exposure.
Conversion Factors:
= 9 mg/m3 x (5/24 h) x (5/7 d) = 1.3 mg/m3
= LOAELADJ x RGDR
= LOAELADJ x (Hb/g)A/(Hb/g)H
= 1.3 mg/m3 x 1 = 1.3 mg/m3
where
LOAELADJ is the adjusted LOAEL, RGDR is the regional gas dose ratio (animalrhuman), and
(Hb/g)A/(Hb/g)H is the ratio of blood:gas partition coefficient; (Hb/g)A/(Hb/g)H defaults to 1
where Hb/g values are not known.
Additional Information:
In humans, inhalation exposure is reported to cause respiratory effects, including the
development of pneumonia, pulmonary edema, and hemorrhage (Clayton and Clayton, 1981).
Irritation of the nose and throat, nasal constriction, and dryness was reported in 8 of 10
individuals briefly exposed to 6 mg/m3 (Uzhdavini et al., 1972, as cited in CalEPA 1997).
Signs of respiratory irritation (as indicated by increased paratid gland secretions) were observed
in cats exposed to 5 to 9 mg/m3 o-cresol for 30 minutes (Uzhdavini et al., 1972, as cited in
CalEPA 1997). Exposure of mice to 50 mg/m3 o-cresol for 2 h/d for 1 month did not affect
mortality; however, heart muscle degeneration and degeneration of nerve cells and glial elements
were reported (Uzhdavini et al., 1972, as cited in CalEPA, 1997, U.S. EPA, 1985).
Strengths and Uncertainties:
Major areas of uncertainty are the lack of human data, the scarcity of animal inhalation data, and
the lack of a NOAEL for this study. Also, the data presented were incomplete, the number of
animals used is not known, exposure and control conditions were not described, statistical
analyses were not provided, and the purity of the compound tested could not be ascertained.
References:
California Environmental Protection Agency (CalEPA). 1997. Technical support document for
the determination of noncancer chronic reference exposure levels, Draft for Public Review.
Office of Environmental Health Hazard Assessment, Air Toxicology and Epidemiology Section,
Berkeley, CA.
Clayton, G.D., and F.E. Clayton (eds). 1981. Patty's Industrial Hygiene and Toxicology. 3rd
revised edition. Volume 2A: Toxicology. New York: John Wiley and Sons, pp. 2597-2601.
U.S. Environmental Protection Agency. 1985. Health and environmental effects profile for
cresols. Cincinnati, OH: Environmental Criteria and Assessment Office, Office of Research and
Development, U.S. EPA. EPA/600/X-85-358.
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IWAIR Technical Background Document
Appendix C
U.S. Environmental Protection Agency. 1986. Health effects assessment for cresols. Cincinnati
OH: Environmental Criteria and Assessment Office, Office of Health and Environmental
Assessment, Office of Research and Development, U.S. EPA. EPA/540/1-86-050.
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NO
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment
Office of Research and Development, U.S. EPA. EPA/600/8-90-066F.
Uzhdavini, E.R., K. Astaf'yeva, A.A. Mamayeva, and G.Z. Bakhtizina. 1972. [Inhalation
toxicity of o-cresol]. Trudy Ufimskogo Nauchno-Isseldovatel'skogo Institute Gigiyeny
Profzabolevaniya, 7:115-9. [as cited in CalEPA, 1997, and U.S. EPA 1985, 1986]
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IWAIR Technical Background Document
Appendix C
3,4-Dimethylphenol
CAS #95-65-8
RfC: Data are inadequate to support the derivation of an RfC at this time.
Supporting Data:
An RfD of 0.001 mg/kg/d is listed in IRIS (U.S. EPA, 1998), based on a subchronic feeding
study in rats. Changes in blood pressure and body weight and histopathological changes in liver,
kidney and spleen were reported (Veldre and Janes, 1979). Route-to-route extrapolation of an
RfC from the RfD is not recommended because of the potential for respiratory tract effects
following inhalation exposure and first-pass effects following ingestion exposure.
Although dimethylphenols have been detected in tobacco smoke, automobile exhausts, and
exhausts from stationary sources, they have not been detected in ambient air (U.S. EPA, 1986).
3,4-Dimethylphenol is not likely to occur at detectable concentrations in ambient air because it is
a'solid at ambient temperatures and has a low vapor pressure. Consequently, inhalation
exposures are unlikely to be important for the general population. Skin absorption and ingestion,
which can be evaluated by the RfD, are likely to be the predominant exposure pathways.
Very little toxicity or metabolism data specific to 3,4-dimethylphenol are available.
Dimethylphenols and related compounds (phenol and methylphenols [cresols]) are rapidly
absorbed following ingestion, inhalation, or skin contact and are corrosive to skin, eyes, mucous
membranes, and the respiratory tract. Therefore, portal-of-entry effects are likely to be important
and cannot be addressed from route-to-route extrapolation. First-pass effects also may be
important. These compounds are metabolized predominantly to glucuronide and sulfate
conjugates and excreted in the urine (U.S. EPA, 1986). Skowronski et al. (1994) suggested that a
lack of first-pass metabolism in the liver may contribute to the toxicity of phenol following skin
absorption; therefore, differences in metabolism following ingestion and inhalation exposures
also could affect toxicity.
References:
Skowronski, G.A., A.M. Kadry, R.M. Turkall, et al. 1994. Soil decreases the dermal penetration
of phenol in male pig in vitro. J Toxicol Environ Health 41:467-479.
U.S. Environmental Protection Agency. 1986. Health and environmental effects profile for
dimethylphenols. Environmental Criteria and Assessment Office, Cincinnati, OH.
EPA/600/X-86/256.
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NC:
Environmental Criteria and Assessment Office, Office of Health and Environmental Assesment,
Office of Research and Development, U.S. EPA. EPA /600//8-90-066F.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS). 3,4-
Dimethylphenol. Environmental Criteria and Assessment Office, Office of Health and
Environmental Assessment, Cincinnati, OH.
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IWAIR Technical Background Document
Appendix C
Veldre, LA., and H.J. Janes. 1979. Toxicological studies of shale oils, some of their components
and commercial products. Environ Health Perspect 30:141-146 (as cited in U.S. EPA, 1998).
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TWAIR Technical Background Document
Appendix C
1,4-Dioxane
CAS # 123-91-1
RfC:
Critical Study:
Critical Dose:
Critical Effect:
Species:
Route of Exposure:
Duration:
Uncertainty Factor:
Modifying Factor:
Calculations:
RfC =
0.8 mg/m3
Torkelson, T.R., B.K.J. Leong, RJ. Kociba, et al. 1974. 1,4-Dioxane.
n. Results of a 2-year inhalation study in rats. Toxicol Appl
Pharmacol 30:287-298.
400 mg/m3
[X] NOAEL [ ] LOAEL
No effect on liver, kidney, or hematological endpoints
Rat
Inhalation
2 years
100:
10 for extrapolation from animals to humans
10 for protection of sensitive human subpopulations
1
+ UF = 83.3 mg/m3 -r 100 = 0.8 mg/m3 (0.2 ppm)
Summary of Study:
Groups of Wistar rats were exposed to 0 or 1 1 1 ppm (0 or 400 mg/m3) 1 ,4-dioxane 7 h/d, 5 d/wk
for 2 years (Torkelson et al., 1974). Animals were observed for signs of toxicity, including
behavioral changes, eye and nasal irritation, respiratory distress, and skin condition. Body
weight was measured weekly. Hematological measurements were made at 16 and 23 months and
included serum glutamic-pyruvic transaminase (SGPT) activity, blood urea nitrogen (BUN),
alkaline phosphatase (AP) activity, and total protein determinations. At sacrifice, gross necropsy
of all animals was performed, and organs were examined for tumors. Histological examination
of tissues was conducted.
No significant differences in survival, body weight, general appearance, or behavior were
reported. Packed cell volume (PCV), red blood cells, and hemoglobin were slightly, but
significantly (p<0.05), increased and white blood cells were significantly decreased in exposed
males; however, the study authors note that these differences were within normal physiological
levels and not considered of toxic importance. Slightly decreased BUN and AP values observed
in exposed males were not considered to be biologically significant by the investigators based on
the fact that an increase, not a decrease, in these parameters would indicate kidney or liver
damage. Increased total protein in exposed, males was also reported but not considered to be
biologically significant. No significant differences in liver, kidney, or spleen weights, or gross or
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IWAIR Technical Background Document Appendix C
microscopic alterations were observed. Tumor incidence (including hepatic and nasal) was not
significantly different in any of the organs examined.
The NOAEL of 400 mg/m3 was adjusted for continuous exposure (83.3 mg/m3). A NOAELHEC
was calculated as per EPA's inhalation dosimetry methodology (1994), using equation 4-48a
(category 3 - extrarespiratory effects). An uncertainty factor of 100 was applied: 10 for
extrapolationifrom humans to animals and 10 for human variability.
Conversion Factors:
0.4 mg/L x 1,000 L/m3 = 400 mg/m3
NOAELADJ = 400 mg/m3 x (7/24 hr>x (5/7 d) = 83.3 mg/m3
: = NOAELADJ * RGDR
: = NOAELADJ x (Hb/g)A/(Hb/g)H
: = 83.3 mg/m3 x 1 = 83.3 mg/m3
where
NOAELADJ is the adjusted NOAEL, RGDR is the regional gas dose ratio (animahhuman),
and (Hb/gVOH^H is the ratio of blood:gas partition coefficient; (Hb/g)A/(Hb/g)H defaults to 1
where Hb/g values are not known.
Additional Information:
The major metabolite of 1,4-dioxane in rats is beta-hydroxyethoxyacetic acid (HEAA), which is
excreted in the urine (Braun and Young, 1977). Results from a study by Young et al. (1978)
show that the fate of 1,4-dioxane in rats is markedly dose-dependent due to a limited capacity to
metabolize dioxane to HEAA. Exposure to 1,4-dioxane by ingestion results in saturation of
metabolism above a single dose of 100 mg/kg, or as low as 10 mg/kg when administered in
multiple doses. When rats were exposed to 50 ppm for 6 hours, nearly all the inhaled
1,4-dioxane was also metabolized to HEAA (99%); the plasma half-life was 1.1 hours (Young et
al., 1978). The correlation of the dose-dependent fate of 1,4-dioxane with the results of
lexicological studies in rats supports the conclusion that there is an apparent threshold for the
toxic effects of dioxane that coincides with saturation of the metabolic pathway for its
detoxification (Young et al., 1978). 1,4-Dioxane and HEAA were also found in the urine of
dioxane plant workers exposed to an average concentration of 1.6 ppm (TWA) for 7.5 hours
(Young etal., 1976, 1977).
In a study by Kociba et al. (1974), Sherman rats were exposed to 0, 0.01, 0.1, or 1.0%
1,4-dioxane in drinking water for up to 2 years. No hematologic changes were reported.
Histopathologic examination revealed hepatocellular and renal tubular degenerative changes,
accompanied by regenerative activity, in rats exposed to the two highest dose levels, but not at
the low dose (Kociba et al., 1974). The lack of hematological effects observed in the ingestion
study suggests that the toxicity of 1,4-dioxane may be route-specific. Studies suggest that the
inhalation of 1,4-dioxane may lead to adverse effects, but good dose-response data are not
available. The toxicity of 1,4-dioxane may be a function of the saturation of the mechanism of
metabolism (Young et al., 1978).
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IWAIR Technical Background Document
Appendix C
Strengths and Uncertainties:
The strengths of the RfC are" that it is based on a lifetime study, with a large number of toxic
endpoints examined and a large sample size (n=192-288). The weaknesses of the inhalation
benchmark value include the use of a free-standing NOAEL, that only one exposure level was
used in the Torkelson et al. (1974) study, the limited human data, the limited inhalation data in
animals, and the lack of developmental and. reproductive studies.
References:
Braun, W.H., and J.D. Young. 1977. Identification of beta-hydoxyethoxyacetic acid the major
urinary metabolite of 1,4-dioxane in the rat. Toxicol Appl Pharmacol 39:33-38.
California Environmental Protection Agency (CalEPA). 1997. Technical support document for
the determination of noncancer chronic reference exposure levels, Draft for Public Review.
Office of Environmental Health Hazard Assessment, Air Toxicology and Epidemiology Section,
' Berkeley, CA.
Kociba, R.J., S.B. McCollister, C. Park, et al. 1974. 1,4-Dioxane. I. Results of a 2-year
ingestion study in rats. Toxicol Appl Pharmacol 30:275-286.
Torkelson, T.R., B.K.J. Leong, RJ. Kociba, et al. 1974. 1,4-Dioxane. H Results of a 2-year
inhalation study in rats. Toxicol Appl Pharmacol 30:287-298.
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NC:
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Office of Research and Development, U.S. EPA. EPA/600/8-90-066F.
Young, J.D., W.H. Braun, and P.J. Gehring. 1978. Dose-dependent fate of 1,4-dioxane in rats.
J Toxicol Environ Health 4:709-726.
Young, J.D., W.H. Braun, P.J. Gehring, et al. 1976. 1,4-Dioxane and beta-hydroxyethoxyacetic
acid excretion in urine of humans exposed to dioxane vapors. Toxicol Appl Pharmacol 38:643-
646.
Young, J.D., W.H. Braun, L.W. Rampy, et al. 1977. Pharmacokinetics of 1,4-dioxane in
humans. J Toxicol Environ Health 3:507-520.
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IWAIR Technical Background Document
Appendix C
Ethylene glycol
CAS # 107-21-1
RfC:
Critical Study:
Critical Dose:
Critical Effect:
Species:
Route of Exposure:
Duration:
Uncertainty Factor:
Modifying Factor:
0.6 mg/m3
Wills, J.H., F. Coulston, E.S. Harris, et al. 1974. Inhalation of
aerosolized ethylene glycol by man. Clin Toxicol 7:463-476.
67 mg/m3
[X ] NOAEL [ ] LOAEL
Throat and upper respiratory tract irritation
Humans
Inhalation
30 days
100:
10 for protection of sensitive human subpopulations
10 for use of a subchronic study
1
Calculations:
RfC = NOAELADJ-=- UF = 55.8 mg/m3 -MOO = 0.6 mg/m3
Summary of Study:
Twenty volunteer male prisoners were exposed to ethylene glycol in mean daily concentrations
between 3 and 67 mg/m3 for 30 days, 20 h/d, without effect (Wills et al., 1974). Irritation was -
noted after 15 minutes at an exposure concentration of 188 mg/m3 and was judged intolerable at
244 mg/m3. No effects were observed in clinical serum enzyme levels for liver and kidney
toxicity, hematotoxicity, or psychological responses. The irritation resolved soon after exposure
with no effects noted after a 6-week followup period.
A NOAEL of 67 mg/m3 was selected and adjusted for continuous exposure (55.8 mg/m3). An
uncertainty factor of 100 was applied: 10 for use of a subchronic study (30 day-duration) and 10
for protection of sensitive human subpopulations.
Conversion Factors:
NOAELADj = 67 mg/m3 x 20/24 h = 55.8 mg/m3
Additional Information:.
Animal studies are inconclusive regarding the respiratory effects of ethylene glycol. Suber et al.
(1989, as cited in ATSDR, 1997) report thickened respiratory epithelium with enlarged goblet
cells in rats that inhaled ethylene glycol over 90 days. Another study in rhesus monkeys and rats
showed no respiratory effects from continuous exposure to propylene glycol for 13 to 18 months
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IWAIR Technical Background Document
Appendix C
(Robertson et al., 1947, as cited in ATSDR, 1997). Developmental effects have been seen in
animal studies. Tyl et al. (1995a, 1995b, as cited in CalEPA, 1997) reported reduced ossification
in humerus, zygmotatic arch, and the metatarsals in fetuses of rats and mice exposed to ethylene
glycol on days 6 through 15 of gestation.
Strengths and Uncertainties:
The major strength of the RfC is that it was based on human data with controlled inhalation
exposures and the observation of a NOAEL. The major uncertainty to the RfC is the lack of
chronic inhalation studies in humans and confirming studies in animals.
References:
Agency for Toxic Substances and Disease Registry. 1997. Toxicological profile for ethylene
glycol and propylene glycol. Atlanta, GA: U.S. Department of Health and Human Services,
Public Health Service.
California Environmental Protection Agency (CalEPA). 1997. Technical support document for
the determination of noncancer chronic exposure levels, Draft for Public Review. Office of
Environmental Health Hazard Assessment, Air Toxicology and Epidemiology Section, Berkeley,
CA.
Robertson, O.H., C.G. Loosli, and T.T. Puck. 1947. Test for chronic toxicity of propylene
glycol and triethylene glycol on monkeys and rats by vapor inhalation and oral administration. J
Pharmacol Exper Therap 91:52-76 (as cited in ATSDR 1997).
Suber, R.L., R.D. Deskin, I. Nikiforov, et al. 1989. Subchronic nose-only inhalation study of
propylene glycol in Sprague-Dawley rats. Food Chem Toxicol 27(9): 573-584 (as cited in
ATSDR, 1997).
Tyl, R.W., B. Ballantyne, L.C. Fisher, et al. 1995a. Evaluation of the developmental toxicity of
ethylene glycol aerosol in CD-I mice by nose-only exposure. FundamAppl Toxicol 27:49-62 (as
cited in CalEPA, 1997).
Tyl, R.W., B. Ballantyne, L.C. Fisher, et al. 1995b. Evaluation of the developmental toxicity of
ethylene glycol aerosol in CD rat and CD-I mouse by whole-body exposure. Fundam Appl
Toxicol 24:57-75 (as cited in CalEPA, 1997).
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NC:
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Office of Research and Development, U.S. EPA. EPA/600/8-90-066F.
Wills, J.H., F. Coulston, E.S. Harris, et al. 1974. Inhalation of aerosolized ethylene glycol by
man. Clin Toxicol 7:463-476.
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IWAIR Technical Background Document
Appendix C
Methanol
CAS # 67-S6-1
RfC:
Critical Study:
Critical Dose:
Critical Effects:
Species:
Route of Exposure:
Duration:
13 mg/m3
Rogers, J.M., M.L. Mole, N. Chernoff, et al. 1993. The developmental
toxicity of inhaled methanol in the CD-I mouse, with quantitative
dose-response modeling for estimation of benchmark doses.
Teratology 47(3):175-188.
l,310mg/m3
[X] NOAEL [ ] LOAEL
Developmental malformations (increased cervical ribs, exencephaly,
and cleft palate)
Mouse
Inhalation
Gd 6-15
Uncertainty Factor: 100:
Modifying Factor:
10 for extrapolation from animals to humans
10 for protection of sensitive human subpopulations
1
Calculations:
RfC =
-r UF = 1310 mg/m3 4- 100 = 13 mg/m3 (10 ppm)
Summary of Study:
Groups of pregnant CD-I mice were exposed to 1,000, 2,000, 5,000, 7,500, 10,000, or 15,000
ppm methanol (1,310, 2,620, 6,552, 9,828, 13,104, or 19,656 mg/m3) for 7 h/d on days 6 through
15 of gestation (Rogers etal., 1993). Three groups of controls were used. Sham-exposed
controls were exposed to filtered air. Additional control groups remained in their cages and
received food and water ad libitum or were food-deprived for 7 h/d (to match the food
deprivation experienced by the exposed mice). Dams were observed twice daily and weighed on
alternate days during the exposure period. Blood methanol concentrations were determined in
three mice per exposure level on gestation days 6, 10, and 15. On day 17, the remaining mice
were weighed and sacrificed and the gravid uteri removed. Implantation sites, live and dead
fetuses, and resorptions were counted, and fetuses were examinee! externally and weighed as a
-litter. Half of each litter were examined for skeletal morphology and the other half of each litter
were examined for internal soft tissue anomalies.
One dam died in each of the three highest exposure groups, but no dose-response relationship
was evident for maternal death. The sham-exposed and food-deprived controls, as well as all
methanol-exposed dams, gained less weight than did unexposed dams fed ad libitum, but
methanol did not exacerbate this effect. Significant increases in the incidence of exencephaly
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TWAIR Technical Background Document
Appendix C
and cleft palate were observed at 6,552 mg/m3 and above, increased embryo/fetal death at 9,828
mg/m3 and above (including an increasing incidence of full-litter resorptions), and reduced fetal
weight at 13,104 mg/m3 and above. A dose-related increase in cervical ribs (small ossification
sites lateral to the seventh cervical vertebra) was significant at 2,620 mg/m3 and above.
Therefore, a NOAEL of 1,310 mg/m3 for developmental toxicity in mice was identified in this
study.
Because this is a developmental study, the NOAEL of 1,310 mg/m3 was not adjusted for
continuous exposure. A NOAELHEC was calculated as per EPA's inhalation dosimetry
methodology (1994), using equation 4-48a (category 3 - extrarespiratory effects). An uncertainty
factor of 100 was applied: 10 for extrapolation from humans to animals and 10 for human
variability.
Conversion Factors:
Dose levels are:
(1,000 ppm x 32.04)/ 24.45 = 1,310 mg/m3; 2,000 ppm = 2,620 mg/m3; 5,000 ppm = 6,552
mg/m3; 7,500 ppm = 9,828 mg/m3; 10,000 ppm = 13,104 mg/m3; 15,000 ppm = 19,656 mg/m3
= NOAEL x RGDR
= NOAEL x (Hb/g)A/(Hb/g)H
=1310 mg/m3 x 1 = 1310 mg/m3
where
RGDR is the regional gas dose ratio (animal:human) and (Hb/g)A/(Hb/g)H is the ratio of
blood: gas partition coefficient; (Hb/g)A/(Hb/g)H defaults to 1 where Hb/g values are not known.
Additional Information:
Developmental effects ^ere also reported in a study by Nelson et al. (1985). Pregnant
Sprague-Dawley rats were exposed to methanol at concentrations of 0, 5,000, 10,000, and 20,000
ppm (0, 6,552, 13,104, and 26,208 mg/m3) 7 h/d on days 1 through 19 of gestation (high dose rats
were exposed on Gd 7-15 only). Dams were sacrificed on Day 20. Half of the fetuses were
examined for visceral defects, and the other half were examined for skeletal defects. No effect
on the numbers of corpora lutea or implantations or the percentage of dead or resorbed fetuses
was observed. At the two highest concentrations, a dose-related decrease in fetal weights was
reported. The highest concentration of methanol produced slight maternal toxicity and a high
incidence of congenital malformations (p<0.001), predominantly extra or rudimentary cervical
ribs and urinary or cardiovascular defects. Similar malformations were seen in the 10,000 ppm
group, but the incidence was not significantly different from controls. No adverse effects were
noted in the 6552 mg/m3 group (Nelson et al., 1985).
Strengths and Uncertainties:
The major strengths of the Rogers et al. (1993) study are the identification of a NOAEL and the
demonstration of a dose-response relationship. The study was well performed, large numbers of
animals were used (n=20-44 per group), and effects at six exposure concentrations were
examined. The results are also supported by an additional developmental study (Nelson et al.,
1985).
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Appendix C
The major uncertainties of the RfC are the lack of human data for chronic inhalation exposure
and the lack of comprehensive, long-term muliple dose studies.
References:
California Environmental Protection Agency (CalEPA). 1997. Technical support document for
the determination of noncancer chronic reference exposure levels, Draft for Public Review.
Office of Environmental Health Hazard Assessment, Air Toxicology and Epidemiology Section,
Berkeley, CA.
Nelson, B.K., W.S. Brightwell, D.R. MacKenzie, et al. 1985. Teratological assessment of
methanol and ethanol at high inhalation levels in rats. FundamAppl Toxicol 5:727-736.
Rogers, J.M., M.L. Mole, N. Chernoff, et al. 1993. The developmental toxicity of inhaled
methanol in the CD-I mouse., with quantitative dose-response modeling for estimation of
benchmark doses. Teratology 47(3):175-188.
U.S. Environmental Protection Agency. 1994. Methods for derivation of inhalation reference
concentrations and application of inhalation dosimetry. Research Triangle Park, NC:
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Office of Research and Development, U.S. EPA. EPA/600/8-90-066F.
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TWAIR Technical Background Document
Appendix C
C.2 Derivation of Inhalation Unit Risk Factors and Cancer Slope Factors
This section contains the derivations of inhalation unit risk factors and cancer slope
factors for:
Bromodichloromethane
Chlorodibromomethane
7,12-Dimethylbenz[a]anthracene
2,4-Dinitrotoluene
3-Methylcholanthrene
o-Toluidine (2-Methylaniline)
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IWAIR Technical Background Document
Appendix C
Inhalation Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
Route of Exposure:
Duration:
Bromodichloromethane
CAS #75-27-4
1.8E-05 (ug/m3)-1
6.2E-02 (mg/kg/d)-1
Tubular cell adenoma and tubular cell adenocarcinoma
Mice
Gavage, corn oil
2 years
Basis for Toxicity Values:
EPA has not developed an inhalation reference concentration (RfC) for bromodichloromethane.
An oral reference dose (RfD) value of 0.02 mg/kg/d, based on a chronic gavage study in mice for
renal cytomegaly is available on IRIS for bromodichloromethane (U.S. EPA, 1998).
Based on inadequate human data and sufficient evidence of carcinogenicity in animals, EPA
considers bromodichloromethane a probable human carcinogen (Class B2) by the oral route and
has calculated an oral cancer slope factor (CSF) of 0.062 (mg/kg/d)'1 for the substance. In a
National Toxicology Program (NTP) study, 2-year gavage administration of bromodichloro-
methane to both sexes of F344/N rats and B6C3F1 resulted in compound-related statistically
significant increases in tumors of the kidney in male mice, the liver in female mice, and the
kidney and large intestine in male and female rats (NTP, 1987, as cited in U.S. EPA, 1998).
In male mice, the incidences of tubular cell adenomas and the combined incidence of tubular cell
adenomas and adenocarcinomas of the kidneys were significantly increased in the high-dose
animals. In female mice, there were significant increases of hepatocellular adenomas and
hepatocellular carcinomas. The combined incidence of hepatocellular adenomas or carcinomas
in vehicle control, low-dose, and high-dose groups were 3/50, 18/48, and 29/50, respectively.
In male and female rats, the incidences of tubular cell adenomas, adenocarcinomas, and the
combined incidence of adenomas and adenocarcinomas of the kidneys were statistically
significantly increased only in the high-dose groups. The combined incidence of tubular cell
adenomas or adenocarcinomas in vehicle control, low-dose, and high-dose groups were 0/50,
1/49, and 13/50 for males and 0/50, 1/50, and 15/50 for females, respectively.
Tumors of the large intestines, namely adenocarcinomas and adenomatous polyps, were
significantly increased in male rats in a dose-dependent manner. These large intestinal tumors,
however, were observed only in high-dose female rats (adenocarcinomas 0/46, 0/50, 6/47;
adenomatous polyps 0/46, 0/50, 7/47 in the vehicle control, low-dose and high-dose groups,
respectively). The combined incidence of large intestine adenocarcinomas and/or adenomatous
polyps in vehicle control, low-dose, and high-dose groups were 0/50, 13/49, and 45/50 for males
and 0/46, 0/50, and 12/47 for females. The combined tumor incidences in the large intestine and
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1WAIR Technical Background Document
Appendix C
kidney in male and female rats at control, low dose, and high dose were 0/50,13/49,46/50 and
0/46, 1/50, 24/48, respectively. Under the conditions of this bioassay, the NTP concluded there
was clear evidence of carcinogenicity of bromodichloromethane in male and female F344/N rats
and B6C3F1 mice (U.S. EPA, 1998).
The mechanism for the carcinogenicity of bromodichloromethane appears to be genotoxic
carcinogenesis, independent of liver activation and, hence, route-independent. In one
genotoxicity assay, bromodichloromethane was mutagenic in Salmonella typhimurium strain
TA100 in the absence of liver homogenate in a vapor phase test performed in a desiccator.
Positive results for mutagenicity were reported for bromodichloromethane in other
S. typhimurium assays in which the TA100 and TA1537 strains were used without rat liver
homogenate activation. Bromodichloromethane also induced weak mutagenic effects in
Saccharomyces cerevisiae strains D7 and XV185-14C in the absence of liver homogenate (U.S.
EPA, 1998; HSDB, 1998).
Thus, inhalation exposure to bromodichloromethane is likely to lead to carcinogenic
consequences not dissimilar from that from oral exposure. Therefore, in accordance with current
EPA guidelines, it is considered appropriate to calculate an inhalation unit risk factor for
bromodichloromethane from the oral CSF listed for that substance in IRIS (U.S. EPA, 1994,
1996).
Calculations:
URF = CSF x 1 mg/1,000 //g x 1/70 kg x 20 nrVday =
0.062 (mg/kg/d)'1 x 1 mg/1,000 ^g x 1/70 kg x 20 mVd = l.SE-OS^g/m3)-1
where
70 kg = default adult human body weight
20 m3 = default adult human daily rate of inhalation
Calculations assume 100% absorption.
Additional Information:
Inhalation CSFs are often derived from oral data. Of the 51 chemicals currently listed in IRIS
(U.S. EPA, 1998) and HEAST (U.S. EPA, 1997) that have both an oral and inhalation CSF,
about 60%'of the inhalation CSFs were derived from oral studies and are identical or essentially
identical to the oral CSF (see Table C-l, Figure C-l). In at least one case (benzene), the oral
CSF was based on inhalation data resulting in identical values for both routes of exposure. In
most cases (>75%) where an inhalation CSF was derived from an inhalation study, the inhalation
CSF was lower than the corresponding oral CSF. Therefore, use of an oral CSF as an interim
inhalation CSF appears reasonable and is unlikely to result in underestimating risk.
References:
Hazardous Substances Databank (HSDB): Bromodichloromethane. 1998. Online database.
National Library of Medicine, Bethesda, MD.
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IWAIR Technical Background Document
Appendix C
National Toxicology Program (NTP). 1987. NTP Technical Report on the Toxicology and
Carcinogenesis Studies of Bromodichloromethane (CAS no. 75-27-4) in F344/N Rats and
B6C3F1 Mice (gavage studies). NTP Tech. Report Series No.321. U.S. Dept. Health and Human
Services, Public Health Service, National Institute of Health (as cited in U.S. EPA, 1998).
U.S. Environmental Protection Agency. 1994. Provisional Guidance for the Qualitative Risk
Assessment of Polycyclic Aromatic Hydrocarbons. Prepared by the Environmental Criteria and
Assessment Office, Office of Health and Environmental Assessment, Cincinnati, OH, for the
Office of Research and Development, Cincinnati, OH. EPA/600/R-93.
U.S. Environmental Protection Agency. 1996. Proposed Guidelines for Carcinogen Risk
Assessment. Office of Research and Development. Washington, DC. EPA/600/P-92/003C.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables
(HEAST), FY 1997 Update. Office of Emergency and Remedial Response, Washington DC
EPA-540-R-97-036.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Bromodichloromethane. Environmental Criteria and Assessment Office, Office of Health and
Environmental Assessment, Cincinnati, OH.
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IWAIR Technical Background Document
Appendix C
Chlorodibromomethane
CAS #124-48-1
Inhalation Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
Route of Exposure:
Duration:
2.4E-05
8.4E-02 (mg/kg/d)'1
Hepatocellular adenoma or carcinoma
Mice
Gavage
2 years
Basis for Toxicity Values:
EPA has not developed an inhalation reference concentration (RfC) for chlorodibromomethane.
An oral reference dose (RfD) value of 0.02 mg/kg/d, based on a subchronic gavage study in rats
for hepatic lesions is available on IRIS for chlorodibromomethane (U.S. EPA, 1998)
Based on inadequate human data and limited evidence of carcinogenicity in animals, EPA
considers chlorodibromomethane a possible human carcinogen (Class C) by the oral route and
has calculated an oral cancer slope factor (CSF) of 0.084 (mg/kg/d)-1 for the substance. In the
study, 2-year gavage administration of chlorodibromomethane to both sexes of B6C3F1 mice
caused increased incidence of adenomas and carcinomas in female mice and a significantly
increased incidence of hepatocellular carcinomas in high-dose male mice (NTP, 1985, as cited in
U.S. EPA, 1998). Drinking water administration of chlorodibromomethane to both sexes of
CBAxC57Bl/6 mice also resulted in significantly increased incidence of tumors (U.S. EPA, 1998).
The mechanism for the carcinogenicity of chlorodibromomethane appears to be genotoxic
carcinogenesis, independent of liver activation and, hence, route-independent. In one
genotoxicity assay, chlorodibromomethane produced reverse mutations in Salmonella
typhimurium strain TA100 in a vapor-phase test performed in a desiccator. Positive results for
gene conversion in Saccharomyces cerevisiae strain D4 without, but not with, hepatic
homogenates, and negative results for mutation in strain XV185-14C both with and without
hepatic homogenates have been reported for chlorodibromomethane. In others tests,
chlorodibromomethane produced sister chromatid exchange in cultured human lymphocytes and
in bone marrow cells of mice treated orally (U.S. EPA, 1998; HSDB, 1998).
Thus inhalation exposure to chlorodibromomethane is likely to lead to carcinogenic
consequences not dissimilar from that from oral exposure. Therefore, in accordance with current
EPA guidelines, it is considered appropriate to calculate an inhalation unit risk factor for
chlorodibromomethane from the oral CSF listed for that substance in IRIS (U.S. EPA, 1994,
1996).
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Appendix C
Calculations:
URF = CSF x 1 mg/1,000 ^g x 1/70 kg x 20 m3/d =
0.084 (mg/kg/d)-1 x 1 mg/1,000 ^g x 1/70 kg x 20 m3/d = 2.4E-05(Mg/m3)-1
where
70 kg = default adult human body weight
20 m3 = default adult human daily rate of inhalation
Calculations assume 100% absorption.
Additional Information:
Inhalation CSFs are often derived from oral data. Of the 51 chemicals currently listed in IRIS
(EPA, 1998) and HEAST (U.S. EPA, 1997) that have both an oral and inhalation CSF, about
60% of the inhalation CSFs were derived from oral studies and are identical or essentially
identical to the oral CSF (see Table C-l, Figure C-l). In at least one case (benzene), the oral
CSF was based on inhalation data resulting in identical values for both routes of exposure. In
most cases (>75%) where an inhalation CSF was derived from an inhalation study, the inhalation
CSF was lower than the corresponding oral CSF. Therefore, use of an oral CSF as an interim
inhalation CSF appears reasonable and is unlikely to result in underestimating risk.
References:
Hazardous Substances Databank (HSDB): Chlorodibromomethane. 1998. Online database.
National Library of Medicine, Bethesda, MD.
National Toxicology Program (NTP). 1985. Toxicology and Carcinogenesis Studies of
Chlorodibromomethane in F344/N Rats and B6C3F1 Mice (gavage studies) NTP TR282 fas
cited in U.S. EPA, 1998).
U.S. Environmental Protection Agency. 1994. Provisional Guidance for the Qualitative Risk
Assessment of Polycyclic Aromatic Hydrocarbons. Prepared by the Environmental Criteria and
Assessment Office, Office of Health and Environmental Assessment, Cincinnati, OH, for the
Office of Research and Development, Cincinnati, OH.
U.S. Environmental Protection Agency. 1996. Proposed Guidelines for Carcinogen Risk
Assessment. Office of Research and Development. Washington, DC. EPA/600/P-92/003C.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables
(HEAST), FY 1997 Update. Office of Emergency and Remedial Response, Washington DC
EPA-540-R-97-036. '
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Chlorodibromomethane. Environmental Criteria and Assessment Office, Office of Health and
Environmental Assessment, Cincinnati, OH.
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IWAfR Technical Background Document
Appendix C
7jl2-Dimethylbenz[«]anthracene
CAS #57-97-6
Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
2.4E-02
8.4E+01 (mg/kg/d)-1
Malignant angioendothelioma of the mesenteric intestine
Mouse (albino)
Route of Exposure: Diet
Duration: 60 weeks
Basis for Toxicity Values:
There are no human data available that may be used to address the carcinogemcity of
7 12-dimethylbenz[a]anthracene (DMBA). However, DMBA belongs to a class of chemicals
known as polycyclic. aromatic hydrocarbons (PAHs), which are components of coal tar and
incomplete combustion. Many of the PAHs have been demonstrated to be carcinogenic to rats
and mice following oral exposure, skin painting, intrapulmonary injection, inhalation,
subcutaneous injection, and intraperitoneal injection; however, most of these studies are not
considered suitable for quantitative risk assessment. Nevertheless, the data do indicate that the
carcinogenic potencies vary and that DMBA is considered one of the most potent PAHs (Pitot
and Dragan, 1996).
DMBA is not listed in EPA's IRIS (U.S. EPA, 1998) or HEAST (U.S. EPA, 1997) databases and
was not included in EPA's (1993) Provisional Guidance for Quantitative Risk Assessment of
PAHs However the California Environmental Protection Agency (CalEPA) has developed a
unit risk factor (URF) and cancer slope factor (CSF) for DMBA in support of the Air Toxics Hot
Spots Program (CalEPA, 1994a, 1994b, 1997). The CalEPA URF and inhalation CSF are listed
above and are recommended as interim values.
The CalEPA developed an "expedited" approach for deriving cancer potency values in order to
implement Proposition 65 (Hoover et al., 1995). The expedited approach was used for DMBA.
Under the expedited approach, instead of conducting a comprehensive literature review, cancer
dose response data are taken from the Carcinogenic Potency Database (CPDB) (Gold and Zeiger,
1997). The linearized multistage model is automatically used to derive cancer potency estimates
for low-dose exposures, and pharmacokinetic adjustments are not made.
Only one study was listed in the CPDB (Chouroulinkov et al., 1967). Female albino mice were
fed DMBA for 60 weeks at a dose rate of 0.39 mg/kg/d. No tumors were reported in 40 control
mice. Malignant angioendotheliomas of the intestine were reported in 49 of 75 test animals.
Twenty test animals also had nonmalignant forestomach papillomas.
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IWAIR Technical Background Document
Appendix C
Additional Information:
The CPDB summarizes the results of 5,152 cancer tests on 1,298 chemicals. Carcinogenic
potency estimates are presented as TD50 values. TD50 is defined as that dose-rate in mg/kg body
wt/d which, if administered chronically for the standard lifespan of the species, will halve the
probability of remaining tumorless throughout that period (Gold and Zeiger 1997) TheTD is
analogous to the dose that is lethal to 50 percent of test animals (LD50). A low TD5o indicates'0
high potency, just as a low LD50 indicates high acute toxicity.
Some studies have reported high correlations between various measures of cancer potency and
i neo^imUm tolerated dose or maximum dose tested in the carcinogenicity studies (Gaylor
1989; Krewski et al., 1993). The correlation of TD50 values as reported in the CPDB and '
inhalation CSFs derived from IRIS or HEAST was evaluated as a possible means to estimate the
S£ f Omr M^5°; ?rty-flve chem*cals were identified that had both a TD50 and an inhalation
CSF (see Table C-2, Figure C-2). The correlation coefficient for the regression is 0 95 The
TD50 reported for DMBA is 0.084 mg/kg/d (Gold and Zeiger, 1997). Based on a linear
regression of log TD50 as the independent variable and log (1/CSF) as the dependent variable, an
inhalation CSF of 55 (mg/kg/d)-' and a URF of 1.6E-02 (ug/m3)-' are predicted. These values are
in close agreement with the CalEPA values of. 84 (mg/kg/d)'1 and 2.4E-02(//g/m3)-1, respectively.
References:
California Environmental Protection Agency (CalEPA). 1994a. Benzo[a]pyrene as a Toxic Air
Contaminant. Executive Summary. California Air Resources Board, Office of Environmental
Health Hazard Assessment, Berkeley, CA.
California Environmental Protection Agency (CalEPA). 1994b. Benzo[a]pyrene as a Toxic Air
Contaminant. Part B Health Effects of Benzo(a)Pyrene. California Air Resources Board Office
or Environmental Health Hazard Assessment, Berkeley, CA.
California Environmental Protection Agency (CalEPA). 1997. Air Toxics Hot Spots Program
Risk Assessment Guidelines: Technical Support Document for Determining Cancer Potency
Factors. Draft for Public Comment. Office of Environmental Health Hazard Assessment.
Chouroulinkov, L, A. Gentil, and M. Guerin. 1967. Etude de 1'activite carcinogene du 9 10-
dim6thyl-benzanthracene et du 3,4-benzopyrene administres par voie digestive. Bull Cancer
54:67-78 (as cited in Gold and Zeiger, 1997).
Gaylor, D.W. 1989. Preliminary estimates of the virtually safe dose for tumors obtained from
the maximum tolerated dose. Regulatory Toxicology and Pharmacology 9:1-18,
Gold L.S., and E. Zeiger (eds). 1997. Handbook of Carcinogenic Potency and Genotoxicity
Databases. Boca Raton, FL: CRC Press, 754 pp.
Hoover, S.M., L. Zeise, W.S. Pease, et al. 1995. Improving the regulation of carcinogens by
expediting cancer potency estimation. Risk Analysis 15(2):267-280.
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Appendix C
Krewski, D., D.W. Gaylor, A.P. Soms, and M. Szyszkowicz. 1993. An overview of the report:
Correlation between carcinogenic potency and the maximum tolerated dose: Implications for risk
assessment. Risk Analysis 13(4):383-398.
Pitot, H.C., ffl, and Y.P. Dragan. 1996. Chemical Carcinogenesis. In: Casarett & Doull's
Toxicology the Basic Science of Poisons. 5th edition. C.D. Klaassen (ed). New York: McGraw-
Hill, pp. 202-203.
U.S. Environmental Protection Agency. 1993. Provisional Guidance for Quantitative Risk
Assessment of Polycyclic Aromatic Hydrocarbons. Environmental Criteria and Assessment
Office, Office of Healttfand Environmental Assessment, Cincinnati, OH. EPA/600/R-93/089.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables
(HEAST), FY 1997 Update. Office of Emergency and Remedial Response, Washington, DC.
EPA-540-R-97-036.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Cincinnati, OH.
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IWAIR Technical Background Document
Appendix C
Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
Route of exposure:
Duration:
2,4-Dinitrotoluene
CAS #121-14-2
1.9E-04(|ag/m3)-1
6.8E-01 (mg/kg/d)-1
Hepatocellular carcinoma, liver neoplastic nodules, benign and
malignant mammary gland tumors.
Female Sprague-Dawley rats
Diet
2 years
Basis for Toxicity Values:
There are no human data available that may be used to address the carcinogenicity of
2,4-dinitrotoluene. 2,4-Dinitrotoluene is not listed in EPA's IRIS (U.S. EPA, 1998) or HEAST
(U.S. EPA, 1997) databases. However, an oral CSF of 0.68 (mg/kg/d)'1 is available in IRIS for a
mixture of 2,4-and 2,6-dinitrotoluene. The mixture was 98% 2,4-dinitrotoluene and 2%
2,6-dinitrotoluene. The oral CSF for the mixture is proposed as an interim value for the
inhalation CSF for 2,4-dinitrotoluene.
Inhalation CSFs are often derived from oral data. Of the 51 chemicals currently listed in IRIS
and HEAST that have both an oral and inhalation CSF, about 60% of the inhalation CSFs were
derived from oral studies and are identical or essentially identical to the oral CSF (see Table E-l,
Figure C-l). In at least one case (benzene), the oral CSF was based on inhalation data resulting
in identical values for both routes of exposure. In most cases (>75%) where an inhalation CSF
was derived from an inhalation study, the inhalation CSF was lower than the corresponding oral
CSF. Therefore, use of an oral CSF as an interim inhalation CSF appears reasonable and is
unlikely to result in underestimating risk.
Dose-Response Data:
The oral CSF listed in HEAST was based on a study by Ellis et al. (1979). Sprague-Dawley rats
were fed dietary concentrations of 0, 15, 100, and 700 ppm and Swiss mice were fed 0, 100, 700,
and 5,000 ppm for 2 years. Mortality was high in all treatment groups. A statistically significant
increase in liver tumors was observed in both male and female rats and a statistically significant
increase in benign mammary gland tumors was observed in female rats. In addition, an increased
incidence of kidney tumors was observed in the mid-dose male mice. Data used to derive the
CSF were based on liver and mammary tumors in female rats and are presented below as
reported in IRIS.
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IWAIR Technical Background Document
Appendix C
pssvv^Ffv> s^%sr?3^^.
|.d^mster, e^.::E>p,sje _; .,
0
0
11/23
15
0.129
12/35
100
0.927
17/27
700
7.557
34/35
Calculations:
URF = CSF x 1 mg/1,000 ug x 1/70 kg x 20 m3/d =
0.68 (mg/kg/d)-1 x 1 mg/1,000 ug x 1/70 kg x 20 m3/d = 1.9E-04(ug/m3)-1
where
70 kg = default adult human body weight
20 m3 = default adult human daily rate of inhalation
Calculations assume 100% absorption.
Additional Information:
The California Environmental Protection Agency (CalEPA) adopted a URF of 8.9E-05 (ug/m )"
and an inhalation CSF of 3.1E-01 (mg/kg/d)-1 for practical grade 2,4-dinitrotoluene based on a
potency factor derived by EPA (U.S. EPA, 1987) (CalEPA, 1997). These values were based on a
feeding study using Sprague-Dawley rats (Lee et al., 1978). Liver and mammary tumors in
female rats were used to develop the CSF and results were very similar to the Ellis et al. (1979)
study discussed above.
The Carcinogenic Potency Database (CPDB) summarizes the results of 5,152 cancer tests on
1,298 chemicals (Gold and Zeiger, 1997). Carcinogenic potency estimates are presented as TD50
values. TD50 values are defined as that dose-rate in mg/kg body wt/day which, if administered
chronically for the standard lifespan of the species, will halve the probability of remaining
tumorless throughout that period (Gold and Zeiger, 1997). The TD50 is analogous to the dose
that is lethal to 50% of test animals (LD50). A low TD50 indicates high potency, just as a low
LD50 indicates high acute toxicity.
Some studies have reported high correlations between various measures of cancer potency and
the maximum tolerated dose or maximum dose tested in the carcinogenicity studies (Gaylor,
1989; Krewski et al., 1993). The correlation of TD50s as reported in the CPDB and inhalation
CSFs derived from IRIS or HEAST was evaluated as a possible means to estimate the CSF from
the TD50. Forty-five chemicals were identified that had both a TD50 and an inhalation CSF (see
Table C-2, Figure C-2). The correlation coefficient for the regression is 0.95. The reported TD50
is 9.35 mg/kg/d (Gold and Zeiger, 1997). Based on a linear regression of log TDSO as the
independent variable and log (1/CSF) as the dependent variable, an inhalation CSF of 0.53
(mg/kg/d)-1 and a URF of 1.5E-04 (ug/m3)-1 are predicted. These values are in close agreement
with the oral CSF listed in IRIS for a mixture of ~2T,4- and 2,6-dinitrotoluene and the CalEPA
values.
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IWAIR Technical Background Document
Appendix C
References:
California Environmental Protection Agency (CalEPA). 1997. Air Toxics Hot Spots Program
Risk Assessment Guidelines: Technical Support Document for Determining Cancer Potency
Factors. Draft for Public Comment. Office of Environmental Health Hazard Assessment.
Ellis, H.V., HE, J.H. Hagensen, J.R. Hodgson, et al. 1979. Mammalian toxicity of munitions
compounds. Phase ffl: Effects of life-time exposure. Part I: 2,4-dinitrotoluene. Final report No.
7. U.S. Army Medical Bioengineering Research and Development Laboratory. Midwest
Research Institute. Report Order No. AD-A077692.
Gaylor, D.W. 1989. Preliminary estimates of the virtually safe dose for tumors obtained from the
maximum tolerated dose. Regulatory Toxicology and Pharmacology 9:1-18.
Gold, L.S., and E. Zeiger (eds). 1997. Handbook of Carcinogenic Potency and Genotoxicity
Databases. Boca Raton, FL: CRC Press, 754 pp.
Krewski, D., D.W. Gaylor, A.P. Soms, and M. Szyszkowicz. 1993. An overview of the report:
Correlation between carcinogenic potency and the maximum tolerated dose: Implications for risk
assessment. Risk Analysis 13(4):383-398.
Lee, C.C., H.V. Ellis, J.J. Kowalski, et al. 1978. Mammalian toxicity of munition compounds.
Phase II. Effects of multiple doses and Phase m. Effects of lifetime exposure. Part n.
2,4-Dinitrotoluene. U.S. Army Medical Bioengineering Research and Development Laboratory.
Midwest Research Institute, Kansas City, MO. NTIS ADA 061715.
U.S. Environmental Protection Agency. 1987. Health Effects Assessment for 2,4- and 2,6-
Dinitrotoluene. Office of Health and Environmental Assessment, Cincinnati, OH. EPA/600/8-
88/032.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables
(HEAST), FY 1997 Update. Office of Emergency and Remedial Response, Washington, DC.
EPA-540-R-97-036.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Cincinnati, OH.
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Appendix C
Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
Route of Exposure:
Duration:
3-Methylcholanthrene
CAS # 56-49-5
2.1E-03 (ug/m3)-1
7.4E+00 (mg/kg/day)-1
Mammary gland adenocarcinomas
Wistar rats
Gavage
26 to 52 weeks
Basis for Toxicity Values:
There are no human data available that may be used to address the carcinogenicity of
3-methylcholanthrene (3-MC). However, 3-MC belongs to a class of chemicals known as
polycyclic aromatic hydrocarbons (PAHs), which are components of coal tar and incomplete
combustion. Many of the PAHs have been demonstrated to be carcinogenic to rats and mice
following oral exposure, skin painting, intrapulmonary injection, inhalation, subcutaneous
injection, and intraperitoneal injection; however, most of these studies are not considered suitable
for quantitative risk assessment. Nevertheless, the data do indicate that the carcinogenic
potencies vary and that 3-MC is considered one of the most potent PAHs (Pitot and Dragan,
1996).
3-MC is not listed in EPA's IRIS (U.S. EPA, 1998) or HEAST (U.S. EPA, 1997) databases and
was not included in EPA's (1993) Provisional Guidance for Quantitative Risk Assessment of
PAHs. However, the California Environmental Protection Agency (CalEPA) has developed a
unit risk factor (URF) and cancer slope factor (CSF) for 3-MC in support of the Air Toxics Hot
Spots Program (CalEPA, 1994a, 1994b, 1997). The CalEPA URF and inhalation CSF are listed
above and recommended as interim values.
The CalEPA developed an "expedited" approach for deriving cancer potency values in order to
implement Proposition 65 (Hoover et al., 1995). The expedited approach was used for 3-MC.
Under the expedited approach, instead of conducting a comprehensive literature review, cancer
dose response data are taken from the Carcinogenic Potency Database (CPDB) (Gold and Zeiger,
1997). The linearized multistage model is automatically used to derive cancer potency estimates
for low-dose exposures, and pharmacokinetic adjustments are not made.
Fifteen studies (4 diet and 11 gavage) were listed in the CPDB (Gold and Zeiger, 1997). All of
the studies included a control group and one treatment group. No tumors were reported in any of
the dietary studies; however, a significant increase in tumors was reported in all of the gavage
studies. Doses for the gavage studies ranged from 2.46 mg/kg/d to 12.2 mg/kg/d.
Adenocarcinomas of the mammary gland were reported in nine studies and two studies identified
unspecified mammary tissue tumors. Tumor incidence ranged from 67% to 100%.
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Appendix C
Additional Information:
The CPDB summarizes the results of 5,152 cancer tests on 1,298 chemicals. Carcinogenic
potency estimates are presented as TD50s. TD50s are defined as that dose-rate in mg/kg body
wt/day which, if administered chronically for the standard lifespan of the species, will halve the
probability of remaining tumorless throughout that period (Gold and Zeiger, 1997). The TD50 is
analogous to the dose that is lethal to 50% of test animals (LD50). A low TD50 indicates high
potency, just as a low LD50 indicates high acute toxicity.
Some studies have reported high correlations between various measures of cancer potency and
the maximum tolerated dose or maximum dose tested in the carcinogenicity studies (Gaylor,
1989; Krewski et al., 1993). The correlation of TD50s as reported in the CPDB and inhalation
CSFs derived from IRIS or HEAST was evaluated as a possible means to estimate the CSF from
the TDS0. Forty-five chemicals were identified that had both a TD50 and an inhalation CSF (see
Table C-2, Figure C-2). The correlation coefficient for the regression is 0.95. The TDSO reported
for 3-MC is 0.491 mg/kg/d (Gold and Zeiger, 1997). Based on a linear regression of log TD50 as
the independent variable and log (1/CSF) as the dependent variable, an inhalation CSF of 9.6
(mg/kg/d)-1 and a URF of 2.7E-03 (ug/m3)'1 are predicted. These values are in close agreement
with the CalEPA values of 7.4 (mg/kg/d)-1 and 2.1E-03 Cag/m3)'1, respectively.
References:
California Environmental Protection Agency (CalEPA). 1994a. Benzo[a]pyrene as a Toxic Air
Contaminant. Executive Summary. California Air Resources Board, Office of Environmental
Health Hazard Assessment, Berkeley, CA.
California Environmental Protection Agency (CalEPA). 1994b. Benzo[a]pyrene as a Toxic Air
Contaminant. Part B Health Effects of Benzo(a)pyrene. California Air Resources Board, Office
of Environmental Health Hazard Assessment, Berkeley, CA.
California Environmental Protection Agency (CalEPA). 1997. Air Toxics Hot Spots Program
Risk Assessment Guidelines: Technical Support Document for Determining Cancer Potency
Factors. Draft for Public Comment. Environmental Criteria and Assessment Office, Office of
Environmental Health Hazard Assessment.
Gaylor, D.W. 1989. Preliminary estimates of the virtually safe dose for tumors obtained from the
maximum tolerated dose. Regulatory Toxicology and Pharmacology 9:1-18.
Gold, L.S., and E. Zeiger (eds). 1997. Handbook of Carcinogenic Potency and Genotoxicity
Databases. Boca Raton, FL: CRC Press, 754pp.
Hoover, S.M., L. Zeise, W.S. Pease, et al. 1995. Improving the regulation of carcinogens by
expediting cancer potency estimation. Risk Analysis 15(2):267-280.
Krewski, D., D.W. Gaylor, A.P. Soms, and M. Szyszkowicz. 1993. An overview of the report:
Correlation between carcinogenic potency and the maximum tolerated dose: Implications for risk
assessment. Risk Analysis 13(4):383-398.
C-30
-------
IWAIR Technical Background Document
Appendix C
Pitot, H.C., m, and Y.P. Dragan. 1996. Chemical Carcinogenesis. In: Casarett & Doull's
Toxicology the Basic Science of Poisons. 5th edition. CD. Klaassen (ed). New York:
McGraw-Hill, pp. 202-203.
U.S. Environmental Protection Agency. 1993. Provisional Guidance for Quantitative Risk
Assessment/of;Polycyclic Aromatic Hydrocarbons. Environmental Criteria and Assessment
Office, Office 6?Health and Environmental Assessment, Cincinnati, OH. EPA/600/R-93/089.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables, FY
1997 Update. Office of Emergency and Remedial Response, Washington, DC. EPA-540-R-97-
036.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Cincinnati, OH.
C-31
-------
IWAIR Technical Background Document
Appendix C
Unit Risk Factor:
Slope Factor:
Critical Effects:
Species:
Route of Exposure:
Duration:
o-ToIuidine (2-MethylaniIine)
CAS # 95-53-4
6.9E-05 (ing/m3)-1
2.4E-01 (mg/kg/d)'1
Skin fibromas - also increased incidence of other tumor types
including sarcomas, mesotheliomas, carcinomas, hemangiosarcomas,
and hepatocellular carcinomas of various tissues.
F-344 rats and B6C3F1 mice
Diet
2 years
Basis for Toxicity Values:
There is limited evidence that o-toluidine is carcinogenic in humans; however, data are
inadequate for a quantitative risk assessment (U.S. EPA, 1987). o-Toluidine is not listed in
EPA's IRIS (U.S. EPA, 1998) but an oral CSF is included in HEAST (U.S. EPA, 1997). The
oral CSF of 2.4E-01 mg/kg/d is proposed as an interim value for the inhalation CSF.
Inhalation CSFs are often derived from oral data. Of the 51 chemicals currently listed in IRIS
and HEAST that have both an oral and inhalation CSF, about 60% of the inhalation CSFs were
derived from oral studies and are identical or essentially identical to the oral CSF (see Table E-l,
Figure C-l). In at least one case (benzene), the oral CSF was based on inhalation data resulting
in identical values for both routes of exposure. In most cases (>75%) where an inhalation CSF
was derived from an inhalation study, the inhalation CSF was lower than the corresponding oral
CSF. Therefore, use of an oral CSF as an interim inhalation CSF appears reasonable and is
unlikely to result in underestimating risk.
Dose-Response Data:
The oral CSF listed in HEAST was based on a study by Hecht et al. (1982). Groups of 30 male
F344 rats were fed dietary concentrations of 0 or 4,000 ppm o-toluidine hydrochloride for 73
weeks followed by 20 weeks of observation. An increased incidence of skin fibromas, mammary
fibroadenomas, spleen fibromas, and peritoneal sarcomas was reported. Skin fibromas gave the
greatest response and were used to derive the CSF. The data are summarized below as reported
in U.S. EPA (1987).
Experimental Dose
:;" :'';o-TQluidipe»HCl' ,.',.'...'-
]i!'l'l|iir' ',,| ' , i, ,,, "II1,1"!,;1!; "M'iij'ib; i1"1,,!/! , " i,1 '' '. ' ';-,-'
i ,?:;?:; :»: tissfav*)
0
62
Transformed Dose
o-Toluidine
(mg/kg/d)
0
80
Incidence ,
1/27
25/30
C-32
-------
TWAIR Technical Background Document
Appendix C
Calculations:
URF = CSF x 1 mg/1,000 //g x 1/70 kg x 20 m3/d =
0.24 (mg/kg/d)'1 x 1 mg/1,000 jtg x 1/70 kg x 20 mVd = 6.9E-05(//g/m3)
3\-l
where
70 kg = default adult human body weight
20 m3 = default adult human daily rate of inhalation
Calculations assume 100% absorption.
Additional Information:
The National Cancer Institute (NCI) also has conducted a cancer bioassay of o-toluidine
hydrochloride (NCI, 1979). F344 rats were fed djets containing 0, 3,000, and 6,000 ppm and
B6C3FJ mice were fed diets containing 0, 1,000, and 3,000 ppm for 2 years. Multiple site
sarcomas, subcutaneous fibromas, and multiple site mesotheliomas were observed in male rats.
Female rats had multiple site sarcomas, mammary fibroadenomas, splenic sarcomas, and urinary
bladder carcinomas. Multiple site hemangiosarcomas were seen in male mice and hepatocellular
carcinomas and adenomas were seen in female mice. U.S. EPA (1987) reported that the Hecht et
al. (1982) study was selected over the NCI (1979) study because the former resulted in a higher"
cancer potency estimate.
References:
Hecht, S.S., K. El-Bayoumy, A. Rivenson, and E. Fiala. 1982. Comparative earcinogenicity of
o-toluidine hydrochloride and o-nitrosotoluene in F-344 Rats. Cancer Letters 16:103-108.
National Cancer Institute (NCI). 1979. Bioassay of o-Toluidine Hydrochloride for Possible
Carcinogenicity. TR-153. Bethesda, MD.
U.S. Environmental Protection Agency. 1987. Health and Environmental Effects Profile for
2-Methylaniline and 2-Methylaniline Hydrochloride. Office of Health and Envrionmental
Assessment, Cincinnati, OH. EPA/600/X-877092.
U.S. Environmental Protection Agency. 1997. Health Effects Assessment Summary Tables
(HEAST), FY 1997 Update. Off ice of Emergency and Remedial Response, Washington, DC.
EPA-540-R-97-036.
U.S. Environmental Protection Agency. 1998. Integrated Risk Information System (IRIS).
Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Cincinnati, OH.
C-33
-------
IWAIR Technical Background Document
Appendix C
Table C-1. Correlation of Oral and Inhalation Cancer Slope Factors
Reported in IRIS and HEAST
CAS#
79-06-1
107-13-1
309-00-2
140-57-8
7440-38-2
103-33-3
71-43-2
92-87-5
7440-41-7
111-44-4
542-88-1
108-60-1
75-25-2
56-23-5
57-74-9
510-15-6
67-66-3
74-87-3
50-29-3
96-12-8
106-93-4
107-06-2
75-35-4
542-75-6
60-57-1
122-66-7
106-89-8
75-21-8
319-84-6
319-85-7
608-73-1
76-44-8
1024-57-3
118-74-1
87-68-3
67-72-1
Chemical
Acrylamide
Acrylonitrile
Aldrin
Aramite
Arsenic
Azobenzene
Benzene
Benzidine
Beryllium
Bis(2-chloroethyl)ether
Bis(chloromethyl)ether
Bis(2-chloro-1-
methylethyl)ether
Bromoform
Carbon tetrachloride
Chlordane
Chlorobenzilate
Chloroform
Chloromethane
DDT
1 ,2-Dibromo-3-
chloropropane
1 ,2-Dibromoethane
1 ,2-Dichloroethane
1,1-Dichloroethylene
,3-Dichloropropene
Dieldrin
,2-Diphenylhydrazine
Epichlorohydrin
Ethylene oxide
HCH alpha
HCH beta
HCH tech.
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Hexachlorobutadiene
Hexachloroethane
Oral
CSF
4.5
0.54
17
0.025
1.5
0.11
0.029
230
4.3
1.1
220
0.07
0.0079
0.13
1.3
0.27
0.0061
0.013
0.34
1.4
85
0.091
0.6
0.18
16
0.8
0.0099
1.02
6.3
1.8
1.8
4.5
9.1
1.6
0.078
0.014
Inh
CSF
4.5
0.24
17
0.025
15
0.11
0.029
235
8.4
1.16
217
0.035
0.0039
0.053
1.3
0.27
0.08
0.0063
0.34
0.0024
0.77
0.091
0.175
0.13
16
0.77
0.0042
0.35
6.3
1.8
1.8
4.5
9.1
1.6
0.077
0.014
log Oral
CSF
0.6532
-0.2676
1 .2304
-1 .6021
0.1761
-0.9586
-1.5376
2.3617
0.6335
0.0414
2.3424
-1.1549
-2.1024
-0.8861
0.1139
-0.5686
-2.2147
-1.8861
-0.4685
0.1461
1 .9294
-1.0410
-0.2218
-0.7447
1.2041
-0.0969
-2.0044
0.0086
0.7993
0.2553
0.2553
0.6532
0.9590
0.2041
-1.1079
-1 .8539
log Inh.
CSF
0.6532
-0.6198
1.2304
-1.6021
1.1761
-0.9586
-1.5376
2.3711
0.9243
0.0645
2.3365
-1.4559
-2.4145
-1.2757
0.1139
-0.5686
-1.0969
-2.2007
-0.4685
-2.6162
-0.1135
-1.0410
-0.7570
-0.8861
1.2041
-0.1135
-2.3768
-0.4559
0.7993
0.2553
0.2553
0.6532
0.9590
0.2041
-1.1135
-1 .8539
(continued)
C-34
-------
IWAIR Technical Background Document
Appendix C
Table C-l. (continued)
302-01-2
75-09-2
101-14-4
924-16-3
55-18-5
62-75-9
930-55-2
1336-36-3
75-56-9
630-20-6
79-34-5
8001-35-2
79-00-5
88-06-2
75-01-4
'&-Wtffis$$?^i<
,:> --, Chemicah .:---
Hydrazine
Methylene chloride
4,4'-Methylenebis(2-
chloroaniline)
/V-Nitrosodi-n-butylamine
A/-Nitrosodiethylamine
/V-Nitrosodimethylamine
A/-Nitrosopyrrolidine
PCBs
Propylene oxide
1,1,1 ,2,-Tetrachloroethane
1 ,1 ,2,2,-Tetrachloroethane
Toxaphene
1 ,1 ,2-Trichloroethane
2,4,6,-Trichlorophenol
Vinyl chloride
s ^<'6f ail*#
-;»»- /.fX-Wrt'
Ji^GSF' .
3
0.0075
0.13
5.4
150
51
2.1
2
0.24
0.026
0.2
1.1
0.057
0.011
1.9
^?~- . liiHisss^''
;5 ' . -^^Sg^w-
>,;aESI^:4:
17.1
0.0016
0.13
5.6
151
49 .
2.13
0.4
0.013
0.026
0.2
1.1
0.056
0.011
0.3
ViSipDraTf^.
0.4771
-2.1249
-0.8861
0.7324
2.1761
1.7076
0.3222
0.3010
-0.6198
-1 .5850
-0.6990 ''
0.0414
-1.2441
-1 .9586
0.2788
f:*$&W^^
1.2330
-2.7959
-0.8861
0.7482
2.1790
1.6902
0.3284
-0.3979
-1.8861
-1 .5850
-0.6990
0.0414
-1.2518
-1 .9586
-0.5229
C-35
-------
IWAIR Technical Background Document
Appendix C
Figure C-1. Correlation of Oral and Inhalation Cancer Slope Factors.
C-36
-------
IWAIR Technical Background Document
Appendix C
Table C-2. Correlation of TD50s Reported in the Cancer Potency Database and Inhalation
Cancer Slope Factors Reported in IRIS and HEAST.
Carbon tetrachloride_
Bis_(2-chloroethyl)ether
Chlorobenzilate
1.1-Dchloroethvlene
1 .3-Dichloropropene
Hexach oroethane
N-Nitrosodi-n-butylamine
1.1.1,2.-Tetrachloroethane
1 ,1 ,2,2,-Tetrachloroethane
1.1.2-Trichloroethane
Acetaldehyde
Bis(ChloromethyJ)ether
1,2-Diphenylhydrazine
4,4>Methylenebis(2-choroaniline)
a Gold and Zeiger, 1997
b Geometric mean of the "
c IRIS, 1998 or HEAST, 1
d Test species reported a
e Selected to correspond
n Number of chemicals w
r2 Correlation coefficient.
CAS#
56-23-5
50-29-3
309-00-2
111-44-4
106-99-0
57-74-9
510-15-6
67-66-3
75-35-4
542-75-6
60-57-1
319-84-6
319-85-7
608-73-1
76-44-8
67-72-1
75-09-2
924-16-3
630-20-6
79-34-5
8001-35-2
79-06-1
107-13-1
140-57-8
103-33-3
542-88-1
593-60-2
106-93-4
1 22-66-7
75-21-8
118-74-1
. 87-68-3
302-01-2
101-14-4
62-75-9
75-56-9
1746-01-6
75-01-4
rDEO reported f(
997.
5 the basis for t
with the CSF te
th a TD50 and
TD50a
Rat
2.29
84.7
261 '
262
~94~
11.2
55.4
724
0.691~
153
6.15_
16.9
96.7
24.1
648
1.52
8.04
~2T73~
65.8
0.309
19.3
0.124
0.799
74.4
2E-05
405
19.1
jr mice
he CSF
st speci
inhalatic
TD50a
i/louse
150
12.3
11.7
13.9
2 99
93.9
90.3
34.6
49.6
0.912
6.62
27.8
14.8
1.21
338
1.09
182
38.3
5.57
158
0.182
7.45
26
63.7
65.1
2.93
0.189
912
2E-04
1070
20.9
and rats
derivatu
es.
nCSF.
TD60
Geo
Meanb
18.53
32.28
(only use
m ("b" is
nh CSF°
0.053
0.34
17
1.16
0.98
1.3
0.27
0.175
0.13
as
1.8
1.8
4.5
0.014
0.0016
5.6
O2
1.1
0.0077
4.5
0.025
0.11
217
0.11
0.004
0.77
0.091
0.77
0.35
1.6
0.077
17.1
0.13
151
49
2.13
0.013
150000
0.01 1
0.3
d when th
both rats a
SSF test
speciesd
b
b
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
m
3 CSF was
nd mice, '
1/CSF
18.87
2.94
0.059
0.86
1.020
0.77
3.70
12.50
5.71
0.159
71.429
0.179
38.4615
0.909
129.870
40
9.091
1.299
1 .298701
; derived frc
m" is mice,
ogTD50e
(X)
1.539
1.267
itope
m both sp«
and "r" is n
log 1/CSF
(Y)
jcies).
ats).
No data available.
Not calculated because the CSF was based on a single species.
C-37
-------
IWAIR Technical Background Document
Appendix C
" v;":.
|-6
en
3
>^"-l: "" ' ' .
i
., , ,
* > > ' ' >-#*/<
1 ' '' f ' ~s 3,000
, '' / " im
i ' ; '.'-£&
100 -5.000 -4000 -3000 -2000 ' -1000 0*(
/ *
5 4. ' * -a ooo-
^ , ^
'4- ^ -5006
i in I ' ill 1 ii i iii y » / * i s" ^ *
log TDSO
^ If-
f ~* \ * .>-
^ ^ X " ^ J
^ ^ fSjFfy ^ i '<. ^ jgf -S& i V i ^ ""^^^^^
. ? ^> "-s- *h * ^^^t^^^^ ^
. * ^₯> '
>'<"i * ' +t *' 'v ~
: ' * , **fc.* , ' ~ >
}f*-v*p,£f s^h« ^' T "*
-* * T ? ^
»^y^^^^».ynuf.^^ia»^^^w^wfHmtM^H.5MJ^^( ^ Vfvrfrt^,,..,.jnmiin
2p 4tOQ# ^ 2^)00 $600 * 4<
r * x ^
* > t
-^ * ^j^ ~ / ^ '*?< *&$ s?/* f
s ; ^
/'^, " ; ,/ ' >.'» ^i
-v^ .^^^^^^^.^ . j .^.4'° ,^ i o^ & ,* f "^ ^^>f
wj\
00
*!
Figure C-2. Correlation of TD50 and inhalation cancer slope factors.
C-38
-------
Appendix D
Sensitivity Analysis of ISC Air Model
-------
-------
TWAIR Technical Background Document
Appendix D
D. Sensitivity Analysis of ISC Air Dispersion Model
This appendix describes sensitivity analysis on depletion options, source shape and
orientation and receptor location and spacing.
D.I Options With and Without Depletions
A sensitivity analysis was conducted using the ISCST3 model to determine whether dry
and wet depletion options should be used in the risk analysis for five types of waste management
units. A discussion of the analysis follows.
The depletion options (dry depletion and wet depletion) may be used with concentrations
and depositions in the ISCST3 model runs. The model concentrations/depositions without
depletion are higher than those with depletion. Because it takes much longer to run the ISCST3
model with depletions than without depletions, a sensitivity analysis was performed to
investigate the differences of model outputs with and without selecting depletion options.
In this investigation, the 5th and the 95th percentile of sizes of LAUs were used to
determine the relationship between concentrations with depletions and sizes of units.
For dry depletion, two meteorological stations (Little Rock, Arkansas, and Winnemucca,
Nevada) were selected for the sensitivity analysis. The average particle sizes used in the
sensitivity analysis are 20 |-im and 5 ^m with corresponding mass fraction of 50 percent each.
The roughness length at application site was assumed as 0.4 meters.
For wet depletion, two meteorological stations were selected for the sensitivity analysis:
Atlanta, Georgia, with 49.8 inches precipitation per year (4th highest annual precipitation rate
among the 29 meteorological stations to be modeled), and Winnemucca, Nevada, with 8.1 inches
precipitation per year (3rd lowest annual precipitation rate). The reason for selecting a wet site
and a dry site was to examine (1) whether wet depletion has a more significant impact for a wet
site than a dry site; and (2) the differences of ambient concentrations that a very wet site can
make with and without selecting wet depletion.
Five-year average concentrations with and without dry depletion were calculated using
meteorological data from Little Rock and Winnemucca for the 5th and the 95th percentile of
sizes of LAUs. The results show that the differences of the maximum concentrations with and
without dry depletion are very small at close-to-source receptors. As the distance from the
source increases, the differences between the dry depletion option and without dry depletion
increase only slightly. The differences of concentrations are about 10 percent of the
concentrations for the 95th percentile and are less than 2 percent of the concentrations for the 5th
percentile at 50 meters from the edge of the LAU. The larger the area source, the larger the
differences of the maximum concentrations. The results are shown in Figures D-la through
D-ld.
D-l
-------
IWAIR Technical Background Document
Appendix D
Five-year average concentrations with and without wet depletion also were calculated
using meteorological data from Atlanta and Winnemucca for the 5th and 95th percentile of sizes
of LAUs. The results show that the differences of the maximum concentrations with and without
wet depletion are small for both Atlanta and Winnemucca sites. However, the differences in the
maximum concentrations between the wet depletion option and without wet depletion are about 5
to 10 times greater for the Atlanta site than the Winnemucca site. Tables D-la and D-lb show
that for the 95th percentile unit size, at 50 meters from the edge of the unit, the differences in the
maximum concentrations are only 0.03% and 0.37% for Winnemucca and Atlanta, respectively.
This means that model concentrations with and without wet depletion are about the same.
D-2
-------
IWAIR Technical Background Document
Appendix D
§ ,
*z> <
+
1
Cu ^
o 5
5 »
1 3
fl oT
"°
SJD
S
D-3
-------
o
£_.
/-N
Cjj
^ o i , , , ,
& I A P 4 R ft 1
s '
1 -2 -
^^
fi ^
o
C J A
~4
o
J -5 -
"X^
^7^777^7^7^^
Distance (km)
Figure D-lb. Air Concentrations of Particles
(LAU, 5th Percentile, Winnemucca, NV)
I
is
8
B-
«s
i
g.
s
S
3
-------
2.0 -r
? 1.5-
1 1-°-
1 °-5~
^ 0.0-
e i
O
-\ .0 -
o
J -1.5-
\
\
XV^
9 '^^2^- fr^^ P. 1
Distance (km)
0
, , , j .
....... w/ Hrv Hpnlption
Figure D-lc. Air Concentrations of Particles
(LAU, 95th Percentile, Little Rock, AR)
^
>3
5"
S
1
1
0)
s
1
ft-
t
§
b
-------
o\
w/o dry depletion
w/ dry depletion
»
§.
8
5
n
3
a
cume
Distance (km)
Figure D-ld. Air Concentrations of Particles
(LAU, 95th Percentile, Winnemucca, NV)
3
5'
-------
I
8
Table D-la. Differences of Air Concentrations for Vapors Between Wet Depletion Option and Without Wet Depletion
(Atlanta. GA
, Site)
5th Percentile
w/o wet depletion
Distance Concentrations
(ml fug/m3 / E/nL=sl_
19.3 (1)
47.3 (I)
75.2 (1)
100
103.2 (1)
187.0 (1)
200
300
400
500
600
800
1000
1500
2000
3000
4000
5000
10000
7.40752
0.93175
0.38178
0.25129
0.21003
0.06886
0.07091
0.03390
0.02026
0.01359
0.00981
0.00590
0.00400
0.00205
0.00128
0.00068
0.00044
0.00031
0.00011
w/ wet depletion
Concentrations
fug/m3 / e/m -s)
7.40716
0.93159
0.38168
0.25121
0.20996
0.06882
0.07086
0.03387
0.02024
0.01357
0.00979
0.00589
0.00399
0.00205
0.00128
0.00067
0.00043
0.00031
0.00011
Difference
fuB/m3 / s/m2-s)
0.00036
0.00016
0.00010
0.00008
0.00007
0.00004
0.00005
0.00003
0.00002
0.00002
0.00002
0.00001
. 0.00001
0.00000
0.00000
0.00001
0.00001
0.00000
0.00000
Difference in
Percentage
0.005%
0.017%
0.026%
0.032%
0.033%
0.058%
0.071%
0.088%
0.099%
0.147%
0.204%
0.169%
0.250%
0.000%
0.000%
1.471%
2.273%
0.000%
0.000%
95th Percentile
w/o wet depletion
Distance Concentrations
(m) fus/m / 2/m -s)
651.9 (I)
676.9 0)
701.9 0)
726.9 0)
801.9 (1)
1000
1100
1200
1300
1400
1500
1600
1800
2000
3000
4000
5000
10000
0.00614
0.00574
0.00539
0.00507
0.00427
0.00400
0.00342
0.00296
0.00260
0.00230
0.00205
0.00185
0.00152
0.00128
0.00068
0.00044
0.00031
0.00011
w/ wet depletion
Concentrations
-------
c?
00
1
Table D-lb. Differences of Air Concentrations for Vapors Between Wet Depletion Option and Without Wet Depletion
5th Percentile
w/o wet depletion
Distance Concentrations
fin) fne/rn3 / g/m2-s1
17.3 H)
42.3 (1)
67.3 (1)
92.3 0)
100
167.3 (1)
200
300
400
500
600
800
1000
1500
2000
3000
4000
5000
10000
7.79132
1.08468
0.48369
0.27965
0.24315
0.09949
0.07296
0.03600
0.02181
0.01475
0.01070
0.00649
0.00443
0.00229
0.00144
0.00077
0.00050
0.00036
0.00013
w/ wet depletion
Concentrations
(us/in3 / e/m2-s)
7.79125
1.08464
0.48367
0.27963
0.24313
0.09948
0.07295
0.03599
0.02180
0.01474
0.01070
0.00648
0.00443
0.00229
0.00144
0.00077
0.00050
0.00036
0.00013
Difference
dig/m / g/m -si
0.00007
0.00004
0.00002
0.00002
0.00002
0.00001
0.00001
0.00001
0.00001
0.00001
0.00000
0.00001
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
Difference in
0.001%
0.004%
0.004%
0.007%
0.008%
0.010%
0.014%
0.028%
0.046%
0.068%
0.000%
0.154%
0.000%
0.000%
0.000%
0.000%
0.000%
0.000%
0.000%
95th Percentile
w/o wet depletion
Distance Concentrations
(m) (ue/m3 1 sr/m2-s1
651.9 (1)
676.9 (1)
701.9 (1)
726.9 (1)
801.9 0)
1000
1100
1200
1300
1400
1500
1600
1800
2000
3000
4000
5000
10000
23.14326
13.86979
11.62889
10.25373
7.84900
5.85241
4.69239
3.98357
3.43255
2.99083
2.63019
2.33211
1.93762
1.65686
0.91889
0.61160
0.45013
0.17843
w/ wet depletion
Concentrations
fug/m 1 elm'.s\
23.13885
13.86551
11.62486
10.24985
7.84548
5.84988
4.68991
3.98130
3.43045
2.98887
2.62837
2.33042
1.93554
1.65487
0.91727
0.61020
0.44890
0.17767
Difference
dig/m /g/m -si
0.00441
0.00428
0.00403
0.00388
0.00352
0.00253
0.00248
0.00227
0.00210
0.00196
0.00182
0.00169
0.00208
0.00199
0.00162
0.00140
0.00123
0.00076
Difference in
0.02%
0.03%
0.03%
0.04%
0.04%
0.04%
0.05%
0.06%
0.06%
0.07%
0.07%
0.07%
0.11%
0.12%
0.18%
0.23%
0.27%
0.43%
8
3
a
3
^
(i)
These refer to the distances from the center of emission source to the maximum concentration points along 0,25,50,75, and 150 meter receptor squares, respectively.
-------
IWAIR Technical Background Document
Appendix D
D.2 Source Shape and Orientation
A sensitivity analysis was conducted using the ISCST3 air model to determine what role
source shape and orientation play in determining dispersion coefficients of air pollutants. A
discussion of this analysis follows.
Three different sources were chosen for this analysis. The sources were a square (source
No. 1), a rectangle oriented east to west (source No. 2), and a rectangle oriented north to south
(source No. 3) All three sources had an area of 400 m2 in order to ensure that equal emission
rates were compared. The rectangles were selected to be exactly two times longer and half as
wide as the square (see Figure D-2).
Two meteorological stations at Little Rock, Arkansas, and Los Angeles, California, were
selected for this modeling analysis in order to compare two different meteorological regimes.
Little Rock was selected because of its evenly distributed wind directions and Los Angeles was
selected because it has a predominantly southwest wind direction (see Figure D-3). Five years of
meteorological data were used for this analysis.
Each area source was modeled with similar receptor grids to ensure consistency. Sixteen
receptors were placed on the edge of each of the area sources and another 16 were placed 25
meters out from the edge. Each of these two receptor groups were modeled as a Cartesian
receptor grid. Two receptor rings were also placed at 50 and 100 meters out from the center of
the source. This polar receptor grid consisted of 16 receptors with a 22.5 degree interval between
receptors. See Figures D-4a through D-4c for receptor locations.
The ISCST3 model was run using the meteorological data from Little Rock, Arkansas,
and Los Angeles, California, and the results are shown in Tables D-2a and D-2b. The results
indicated that the standard deviation of the differences in air concentrations is greatest between
source No. 2 and source No. 3. This difference is due to the orientation of the source. This
occurs for both the Cartesian receptor grid and the polar receptor grid at both meteorological
locations. This shows that the model is sensitive to the orientation of the rectangular area source.
Standard deviations are significantly smaller when source No. 1 is compared to source
Nos. 2 or 3. This shows that the differences in Unitized Air Concentration (UAC) between the
square source and the two rectangular sources are less than the differences between the two
rectangular sources. A square area source also contributes the least amount of impact of
orientation. Since no information on source shape or orientation is available, a square source
will minimize the errors caused by different source shapes and orientations.
D-9
-------
IWAIR Technical Background Document
Appendix D
0 -20 -10 0 10 20 30
30 I .-
20-
10-
0-
-10-
-20-
-30-
*?
Srcl
Src3
Src2
JU-f II !
-30 -20 -10 0 10 20 3
-3U
-20
-10
-o
--10
-20
--30
(meters)
Figure D-2. Source Shapes and Orientations
D-10
-------
IWAIR Technical Background Document
Appendix D
Los Angeles, California
NNW
NNE
NW
NE
WNW
W
ENE
ESE
SE
2-°-3-5 5.5-8.5
Little Rock, Arkansas
NNW
NW
NE
WNW
W
WSW
ENE
ESE
SW
SE
Figure D-3. Wind Roses
D-ll
-------
IWAIR Technical Background Document
Appendix D
- °°
100
-50
50
100
-100
50-
0-
-50-
+ + 4-
o i
Srcl
-50
-0
-50
-100
-100
~T~
-50
50
100
(meters)
Figure D-4a. Receptor Locations (Source No. 1)
D-12
-------
IWAIR Technical Background Document
Appendix D
inn -50 0 50 10
-]r i .,11 i i i iii i
100-
50-
0-
-50-
-100-
-1
-
+
+ + +
+ + + H- +
:: Src2 ::
+
+
0
-100
-50
-0
-50
--100
00 -50 0 50 100
(meters)
Figure D-4b. Receptor Locations (Source No. 2)
D-13
-------
TWAIR Technical Background Document
-1
100-
50-
0-
-50-
100-
°° , ? , , ° , , 50 ,
+
+
Src3 .
+ +
+
+
-100 -50 0 50 lft
-100
-50
-0
-50
-100
0
(meters)
Figure D-4c. Receptor Locations (Source No. 3)
D-14
-------
Table
Comparisons of Unitized Air Concentrations (ug/m3 / ug/s-m2) for Different Source Shapes and Orientations
(Littte Rock. Arkansas)
'olar R
\(m\
19
38
35
71
46
92
50
100
46
92
35
71
19
38
.0
0
-19
-38
-35
-71
-46
-92
-50
No. 1 (20m x 20m)
\(m)
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
-100 0
-46
-92
-35
-71
-19
-38
0
0.
19
38
. 35
71
46
92
50
100
Mr -K(m)
0.190
0.050
0.249
0.067
0.321
0.095
0.124
0.030
0.085
0.023
0.106
0.030
0.117
0.033
0.122
0.035
0.134
0.038
0.161
0.043
0.159
0.044
0.103
0.027
0.126
0.035
0.152
0.041
0.173
0.047
0.224
0.068
19
38
35
71
46
92
50
100
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
2 (40m
Vfart
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
19
38
35
71
46
92
50
100
xlOint 1 Source No.
IUr. Xftnl
0.199
0.051
0.243
0.067
0.361
0.098
0.128
0.030
0.096
0.024
0.109
0.030
0.113
0.032
0.117
0.033
0.128
0.036
0.158
0.043
0.185
0.046
0.114
0.027
0.145
0.036
0.160
0.042
0.179
0.047
0.191
0.061
19
38
35
71
46
92
50
100
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
46
-92
-35
-71
-19
-38
0
0
3flOmx40m)
Yfml
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
19
38
35
71
46
92
50
100
TJAC
0.211
0.051
0.278
0.069
0.256
0.088
0.147
0.033
0.084
0.023
0.103
0.029
0.128
0.034
0.143
0.037
0.150
0.038
0.170
0.045
0.140
0.043
0.107
0.027
o.iis :
0.034
0.153
0.041
0.187
0.048
0,276
0.074
Standard Deviation:
Differences in UACs
Sources No. 1 and No. 2
niff. Tn tTAr % of niff.
0.010 5%
0.001 1%
-0.007 -3%
-0.001 -1%
0.041 13%
0.003 3%
0.004 3%
0.000 -1%
0.011 12%.
0.001 2%
0.003 3%
0.000 0%
-0,005 -4%
-0.001 -4%
-0.005 -4%
-0.002 -5%
-0.006 -4%
-0.002 -4%
-0.003 -2%
0.000 1%
0.026 16%
0.002 4%
0.011 11%
0.000 2%
0.019 15%
0.001 4%
0.008 5%
0.001 3%
0.007 4%
0.000 0%
-0.032 -14%
-0.008 -11%
0.012 7%
Differences in UACs
Sources No. 1 and No. 3
Differences in UACs
Sources No. 2 and No. 3
rtiff.TnTIAC %nfniff. niff.TntTAC J%_ofDiff.
0.021 11%
0.001 2%
0.028 11%
0.001 2%
-0.065 -20%
-0.007 -7%
0.023 19%
0.003 9%
-0.001 -1%
-0.001 -2%
-0.003 -3%
0.000 -1%
0.011 9%
0.001 2%
0.021 17%
0.002 5%
0.016 12%
0.001 2%
0.009 6%
0.001 3%
-0.019 -12%
-0.002 -4%
0.004 4%
0.000 . ' 1%
-0.008 -6%
-0.001 -4%
0.001 0%
0.001 2%
0.014 8%
0.001 3%
0.052 23%
0.006 9%
0.018 9%
0.012 6%
0.000 1%
0.035 14%
0.002 3%
-0.105 -29%
-0.010 -10%
0.020 15%
0.003 11%
-0.011 -12%
-0.001 -5%
-0.006 -6%
-0.001 -2%
0.016 14%
0.002 7%
0.026 22%
0.004 11%
0.022 17%
0.002 6%
0.012 8%
0.001 3%
-0.045 -24%
-0.004 -8%
-0.007 -6%
0.000 0%
-0.027 -18%
-0.003 -7%
-0.007 -5%
-0.001 -2%
0.008 4%
0.001 3%
0.085 44%
0.014 22%
0.028 14%
8s
S"
3
I
ta
,2?"
OQ
3
a
8
d
Ul
(continued)
-------
D
>«*
ox
Table D-2a (Cont.). Comparisons of Unitized Air Concentrations (uE/m3 / ug/s-m2) for Different Source Shapes and Orientations
SmrceNo. If20mx20m>
Source No
Carlcslon Recentor Grid
XftrO
-10
-5
0
5
10
10
10
10
10
5
0
-5
-10
-10
-10
-10
-35
-17.5
0
17.5
35
35
35
35
35
17.5
0
-17.5
-35
-35
-35
-35
V fml
-10
-10
-10
-10
-10
-5
0
5
10
10
10
10
10
5
0
-5
-35
-35
-35
-35
-35
-17.5
0
17.5
35
35
35
35
35
17.5
0
-17.5
HAT Yfmi
3.014
4.266
4.354
3.961
2.175
5.211
5.968
6.012
4.946
6.804
6.846
6.157
3.245
4.923
5.169
4.809
0.164
0.219
0.243
0.186
0.108
0.141
0.277
0.503
0.254
0.315
0.417
0.272
0.155
0.211
0.213
0.265
-20
-10
0
10
20
20
20
20
20
10
0
-10
-20
-20
-20
-20
-45
-22.5
0
22.5
45
45
45
45
45
22.5
0
-22.5
-45
-45
-45
-45
2 (40m
Vim)
-5
-5
-5
-5
-5
-2.5
0
2.5
5
5
5
5
5
2.5
0
-2.5
-30
-30
-30
-30
-30
-15
0
15
30
30
30
30
30
15
0
-15
x 10m) ISource No.
TIAr X fnO
2.675
4.219
4.307
4.069
1.899
3.875
4.704
4.918
4.468
6.758
6.830
6.353
2.793
3.801
4.032
3.727
0.158
0.247
0.284
0.192
0.088
0.105
0.164
0.396
0.263
0.373
0.445
0.286
0.131
0.155
0.145
0.193
-5
-2.5
0
2.5
5
5
5
5
5
2.5
0
-2.5
-5
-5
-5
-5
-30
-15
0
15
30
30
30
30
30
15
0
-15
-30
-30
-30
-30
HLittte Rock.
,3 (10m x4QmT
-20
-20
-20
-20
-20
-10
0
10
20
20
20
20
20
10
0
-10
-45
-45
-45
-45
-45
-22.5
0
22.5
45
45
45
45
45
22.5
0
-22 5
2.673
3.451
3.526
3.152
2.011
5.567
5.913
5.834
4.344
5.550
5.604
4.954
3.052
5.166
5.287
4.991
0.132
0.167
0.179
0.147
0.100
0.160
0.401
0.466
0.200
0.234
0.341
0.214
0.146
0.232
0.298
0.264
Standard Deviation:
Ain.au:>.!:>)
Differences in UACs
Sources No. 1
ruff. TnlTAT
-0.339
-0.047
-0.047
0.109
-0.276
-1.337
-1.264
-1.094
-0.477
-0.047
-0.016
0.196
-0.451
-1.121
-1.137
-1.081
-0.006
0.027
0.041
0.006
-0.020
-0.036
-0.113
-0.107
0.009
0.058
0.028
0.014
-0.024
-0.056
-0.068
-0.073
0.463
and No. 2
Differences in UACs
Sources No.
% nfnirr. nifrinriAr
-11%
-1%
-1%
3%
-13%
-26%
-21%
-18%
-10%
-1%
0%
3%
-14%
-23%
-22%
-22%
-4% -
12%
17%
3%
-19%
-25%
-41%
-21%
3%
18%
7%
5%
-15%
-27%
-32%
-27%
15%
-0.341
-0.815
-0.827
-0.809
-0.164
0.355
-0.055
-0.178
-0.602
-1.254
-1.242
-1.203
-0.193
0.244
0.118
0.182
-0.032
-0.052
-0.063
-0.039
-0.008
0.019
0.124
-0.037
-0.054
-0.081
-0.076
-0.057
-0.009
0.022
0.084
-0 002
0.435
I and No. 3
Differences in
Sources No. 2 a
UACs
nd Nn. 3
-11%
-19%
-19%
-20%
-8%
7%
-1%
-3%
-12%
-18%
-18%
-20%
-6%
5%
2%
4%
-19%
-24%
-26%
-21%
-7%
14%
45%
-7%
-21%
-26%
-18%
-21%
-6%
10%
40%
-1%
17%
-0.002
-0.769
-0.781
-0.918
0.112
1.692
1.209
0.916
-0.125
-1.208
-1.226
-1.399
0.259
1.365
1.255
1.264
-0.026
-0.079
-0.104
-0.045
0.012
0.055
0.236
0.070
-0.063
-0.139
-0.104
-0.071
0.015
0.078
0.153
0.071
0.747
0%
-18%
-18%
-23%
6%
44%
26%
19%
-3%
-18%
-18%
-22%
9%
36%
31%
34%
-16%
-32%
-37%
-23%
14%
52%
144%
18%
-24%
-37%
-23%
-25%
11%
50%
106%
37%
41%
I
s-
>
-------
Table D-2b. Comparisons of Unitized Air Concentrations (ug/m3 / ug/s-m2) for Different Source Shapes and
(Los Angeles
Orientations
H20m
X(m\
19
38
35
71
46
92
50
100
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92'
-35
-71
-19
-38
0
0
YCml
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
19
38
35
71
46
92
50
100
x20m)
Source No.
TT A.C; -vcmi
0.059
0.016
0.188
0.046
0.582
0.172
0.278
0.068
0.061
0.015
0.062
0.016
0.080
0.023
0.086
0.023
0.099
0.028
0.122
0.033
0.218
0.060
0.320
0.093
0.264
0.074
0.137
0.037
0.063
0.017
0.067
0.020
19
38
35
71
46
92
50
100
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
2 (40m x 10m)
Vfm)
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
. 19
38
35
71
46
92
50
100
Source No. 3 (10m x 40m)
TiAr xrmi
0.065
0.016
0.168
0.045
0.607
0.174
0.293
0.067
0.062
0.015
0.068
0.017
0.076
0.022
0.084
0.024
0.092
0.027
0.119
0.032
0.223
0.061
0.378
0.098
0.273
0.075
0.123
0.035
0.066
0.017
0.058
0.018
19
38
35
71
46
92
50
100
46
92
35.
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
400
-46
-92
-35
-71
-19
-38
0
0
vrnrt
46
92
35
71
19
38
0
0
-19
-38
-35
-71
-46
-92
-50
-100
-46
-92
-35
-71
-19
-38
0
0
19
38
35
71
46
92
50
100
TTAC
0.069
0.016
0.284
0.052
0.461
0.161
0.293
0.074
0.087
0.016
0.062
0.017
0.087
0.024
0.096
0.024
0.108
0.028
0.143
0.034
0.226
0.061
0.278
0.087
0.260
0.073
0.164
0.039
0.073
0.018
0.080
0.021
Standard Deviation:
Differences in UACs
Sources No. 1 and No. 2
Differences in UACs
Sources No. 1
Fliff. Tn TTAP % of TKff Hiff. Tn TTAC
0.006 9%
0.000 -1%
-0.020 -11%
-0.001 -3%
0.025 4%
0.003 2%
0.014 5%
-0.001 -2%
0.002 3%
0.000 0%
0.006 10%
0.001 4%
-0.004 -4%
-0.001 -5%
-0.003 -3%
0.000 1%
-0.006 -7%
-0.001 -2%
-0.003 -2%
0.000 -1%
0.005 2%
0.001 1%
0.057 18%
0.005 6%
0.009 3%
0.001 1%
-0.014 -10%
-0.002 -5%
0.003 4%
0.000 -2%
-0.008 -12%
-0.002 -9%
0.013 6%
0.010
q.ooo
0.096
0.006
-0.121
-0.011
0.015
0.005
0.026
0.002
0.000
0.001
0.007
0.001
0.009
0.001
0.009
0.000
0.021
0.001
0.008
0.001
-0.042
-0.006
-0.005
-0.001
0.027
0.002
0.010
0.001
0.014
0.001
0.030
and No. 3
Differences in UACs
Sources No.
^nfniff. niff.TnlJAC
17%
3%
51%
13%
-21%
-6%
5%
8%
43%
10%
0%
3%
9%
3%
11%
3%
9%
1%
18%
4%
4%
1%
-13%
-6%
-2%
-2%
20%
4%
15%
3%
21%
6%
14%
0.005
0.001
0.116
0.007
-0.146
-0.014
0.001
0.007
0.025
0.002
-0.006
0.000
0.011
0.002
0.012
0.000
0.016
0.001
0.024
0.002
0.003
0.000
-0.099
-0.011
-0.013
-0.002
0.041
0.003
0.007
0.001
0.022
0.003
0.040
2 and No. 3
% of Diff.
7%
4%
69%
16%
-24%
-8%
0%
10%
40%
11%
-9%
-1%
14%
8%
15%
2%
17%
3%
20%
5%
2%
0%
-26%
-11%
-5%
-2%
33%
9%
11%
5%
37%
15%
18%
8
«-«
to
a
*
3
I
(continued)
f
s-
-------
D
V-«i
CO
Table D-2b (Cont.). Comparisons of Unitized Air Concentrations (ug/m3 / ug/s-m2) for Different Source Shapes and Orientations
, California)
Source No. I (20m x 20m)
Source No. 2 (40m x 10m)
Source No. 3 (10m
x40m)
Cartesion Receotor Grid
X Airt
-10
-5
0
5
10
10
10
10
10
5
0
-5
-10
-10
-10
-10
-35
-17.5
0
17.5
35
35
35
35
35
17.5
0
-17.5
-35
-35
-35
-35
Yfnrt
-10
-10
-10
-10
-10
-5
0
5
10
10
10
10
10
5
0
-5
-35
-35
-35
-35
-35
-17.5
0
17.5
35
35
35
35
35
17.5
0
-17.5
TTAP Y dirt
3.225
4.025
3.952
3.431
1.683
5.931
6.636
6.640
5.600
6.893
6.860
6.031
3.393
5.649
5.944
5.663
0.124
0.158
0.172
0.123
0.064
0.095
0.592
0.829
0.192
0.109
0.125
0.113
0.139
0.387
0.603
0.318
-20
-10
0
10
20
20
20
20
20
10
0
-10
-20
-20
-20
-20
45
-22.5
0
22.5
45
45
45
45
45
22.5
0
-22.5
-45
-45
-45
-45
V dirt
-5
-5
-5
-5
-5
-2.5
0
2.5
5
5
5
5
5
2.5
0
-2.5
-30
-30
-30
-30
-30
-15
0
15
30
30
30
30
30
15
0
-15
TTAP ~X fnrt
3.241
4.333
4.297
3.871
1.592
4.787
5.882
6.294
5.866
8.126
8.285
7.442
3.497
5.102
5.373
5.028
0.139
0.183
0.199
0.124
0.053
0.076
0.377
0.739
0.304
0.195
0.144
0.160
0.166
0.335
0.472
0.275
-5
-2.5
0
25
5
5
5
5
5
2.5
0
-2.5
-5
-5
-5
-5
-30
-15
0
15
30
30
30
30
30
15
0
-15
-30
-30
-30
-30
Yfnrt
-20
-20
-20
-20
-20
-10
0
10
20
20
20
20
20
10
0
-10
-45
-45
-45
-45
-45
-22.5
0
22.5
45
45 '
45
45
45
22.5
0
-225
TTAP
2.674
3.119
3.050
2.564
1.511
5.570
5.644
5.524
4.325
4.939
4.913
4.156
2.702
5.015
5.167
5.104
0.095
0.123
0.121
0.100
0.063
0.119
0.696
0.683
0.101
0.072
0.100
0.077
0.089
0.370
0.603
0316
Standard Deviation:
Differences in UACs
Sources No.
niff.TnlTAC
0.016
0.308
0.345
0.440
-0.091
-1.143
-0.754
-0.346
0.266
1.232
1.424
1.411
0.103
-0.547
-0.572
-0.635
0.014
0.025
0.028
0.001
-0.011
-0.019
-0.215
-0.090.:
0.112
0.086
0.019
0.047
0.026
-0.053
-0.131
-0.043
0.542
1 and No. 2
Differences in UACs
Sources No. 1
% nf niff. niff. Tn TIAC
1%
8%
9%
13%
-5%
-19%
-11%
-5%
5%
18%
21%
23%
3%
-10%
-10%
-11%
11%
16%
16%
0%
-17%
-20%
-36%
-11%
58%
78%
15%
42%
19%
-14%
-22%
-13%
24%
-0.551
-0.906
-0.902
-0.867
-0.172
-0.360
-0.992
-1.116
-1.275
-1.955
-1.947
-1.875
-0.691
-0.634
-0.777
-0.559
-0.029
-0.035
-0.050
-0.024
-0.001
0.024
0.104
-0.146
-0.091
-0.037
-0.025
-0.035
-0.050
-0.017
0.000
-0.002
0.614
and No. 3
Differences in UACs
Sources No.
% of niff niff Tn TIAr
-17%
-23%
-23%
-25%
-10%
-6%
-15%
-17%
-23%
-28%
-28%
-31%
-20%
-11%
-13%
-10%
-23%
-22%
-29%
-19%
-2%
25%
18%
-18% .
-47%
-34%
-20%
-31%
-36% s"
4%"
0%
-1%
15%
-0.567
-1.214
-1.247
-1.307
-0.081
0.783
-0.238
-0.770
-1.541
-3.187
-3.371
-3.286
-0.794
'-0.088
-0.205
0.076
-0.043
-0.060
-0.078
-0.024
0.010
0.043
0.319
-0:055
-0.203
-0.122
-0.044
-0.082
-0.077
0.036
0.131
0.041
1.026
2 and No. 3
% nf niff
-17%
-28%
-29%
-34%
-5%
16%
-4%
-12%
-26%
-39%
-41%
44%
-23%
-2%
4%
2%
-31%
-33%
-39%
-20%
19%
57%
85%
-7%
-67%
-63%
-31%
-52%
46%
11%
28%
15%
33%
8'
f
s
s
13
*3
Cfc
a
«
b
-------
IWAIR Technical Background Document
Appendix D
D.3 Receptor Locations and Spacings
A sensitivity analysis was conducted using the ISCST3 model to determine what receptor
locations and spacings should be used in the risk analysis for five types of waste management
units (WMUs). A discussion of the analysis follows.
Because it takes a substantial amount of time for the ISCST3 model to execute, it was
necessary to choose a limited number of receptors to be used in the dispersion modeling
analysis,. The larger the number of receptor points, the longer the run time. However, modeling
fewer receptors may result in the omission of the maximum point for assessing exposure impacts.
Therefore, a sensitivity analysis was conducted to determine the number of receptors needed for
the model run and to locate ideal receptor placements.
A wind rose was plotted for each of the 29 meteorological stations to be used in the risk
analysis for a 5-year time period in order to choose two meteorological stations for this
sensitivity analysis. Little Rock, Arkansas, and Los Angeles, California, meteorological stations
were selected for the sensitivity analysis. The wind roses show that Little Rock has very evenly
distributed wind directions, and Los Angeles has a predominant southwest to west wind
(Figure D-3). Little Rock and Los Angeles were chosen to determine if a higher density of
receptors should be placed downwind of a site near Los Angeles, as compared to a site near Little
Rock. Similarly, the 5th, 50th, and 95th percentile of sizes of LAUs were used in the sensitivity
analysis to determine whether sizes of units can affect receptor locations and spacings. The areas
of the 5th, 50th, and 95th percentile of sizes of LAUs are 1,200 m2, 100,000 m2, and 1,700,000
m2, respectively.
The dispersion modeling was conducted using two sets of receptor grids. The first set of
receptor points (Cartesian receptor grid) was placed around the modeled source with distances of
0,25, 50,75, and 150 meters from the edge of the unit. Square-shaped ground-level area sources
were used in the modeling. Therefore, these receptors are located on five squares surrounding
the source. The second set of receptor points (polar receptor grid) was placed outside of the first
set of receptors to 10 kilometers from the center of the source. Since the ISCST3 model's area
source algorithm does not consider elevated terrain, receptor elevations were not input in the
modeling.
In this sensitivity analysis, both downwind and lateral receptor spacings were
investigated for three unit sizes using 5 years of meteorological data from Little Rock and Los
Angeles. For the first set of receptor points (i.e., Cartesian receptor grid), five downwind
distances of 0, 25, 50,75, and 150 meters from the edge of the source were used. For lateral
receptor spacing, choices of 64, 32, and 16 equally spaced receptor points for each square were
used in the modeling to determine the number of receptors needed to catch the maximum
impacts. (See Figures D-5a through D-5c for Cartesian receptor locations and spacings [50th
percentile]). For the second set of receptor points (i.e., polar receptor grid), about 20 downwind
distances (i.e., receptor rings) were used. Receptor lateral intervals of 22.5° and 10° were used
to determine whether 22.5° spacing can catch the maximum impacts. With a 22.5° interval,
there are 16 receptors on each ring. There are 36 receptors on each ring for the 10° interval. See
Figures D-6a and D-6b for polar receptor locations (5th percentile).
D-19
-------
IWAIR Technical Background Document
Appendix D
The results (Figures D-7a through D-7f) show that the maximum downwind
concentrations decrease sharply from the edge of the area source to 150 meters from the source.
The maximum concentrations decrease more sharply for a smaller area source than for a larger
one. This means that more close-to-source receptors are generally needed for a small area source
than for a large one.
The results also show that the maximum impacts are generally higher for a dense receptor
grid (i.e., 64 or 32 receptors on each square) than for a scattered receptor grid (i.e., 16 receptors
on each square). However, the differences of the maximum receptor impacts are not significant
between a dense and a scattered receptor grid (Figures D-7a through D-7f). It should be noted
that the above conclusions apply to both Little Rock and Los Angeles. This means that the
distribution of wind directions does not play an important role in determining receptor lateral
spacings.
Figures D-8a through D-8f compare the maximum concentrations at each ring for 22.5°
and 10° intervals. The results show that the differences of the maximum concentrations are
greater for close-to-source receptors than for further out receptors, and the differences are greater
for larger area sources than for smaller area sources. The differences of the maximum
concentrations for 22.5° and 10° intervals are generally small, and the concentrations tend to be
the same at 10 kilometers. The conclusions were drawn from both Little Rock and Los Angeles
meteorological data.
D-20
-------
IWAIR Technical Background Document
Appendix D
-40
400-
300-
200-
100-
0-
-100-
900
-iVJU
-300-
-400
-A
0 -300 -200
*
+
+ +
+ + + '
+
+ + +
+
+ +
+ +
+ ,
+ +
,^ + + .
+ + '+ +
+ + +
+ + +
"*"
+ +
-t- +
+ + +
+
+
+
+ + +
+
+ + + H
+
*
1 1
00 -300 -200
-100 0 100
1 II
, i - i i i I t 1 11 1 1 1 1
f 1 1 " i 1 1 1 ' I 1 " I r ' ' '
Land Application Unit
, , . ._ !..-,_ 1 II 1 1 t 1 ( 1
1 1 1 1 1 i1 t 1 1 I 1 ' ' ' '
1 1 1
-100 0 100
200 300 40
I I
+
+
+ -f +
.).
+
+ + +
+ +
4.
. + +
+ +
+ + +
+ + + +
+ + +
+ + +
+
+ +
+ +
+
+
i-
+
+
+
+
200 300 4
0
-400
-300
-200
-100
~°
-100
-200
300
400
00
(meters)
Figure D-5a. Cartesian Receptor Grid (64 receptors each square)
D-21
-------
IWAIR Technical Background Document
Appendix D
-400
400
-300
I
-200
-100
I
100
I
200
L_
300
I
400
400
-300
-200,
-100
-0
-100
-200
300
300-
200-
100-
0-
-100-
-200-
-300-
-400-
+ + + + +
Land Ajfjfhcnuaa C/DIL
+ + + +
-400
-300 -200
-100
100
--40 0
200
300
400
(meters)
Figure D-5b. Cartesian Receptor Grid (32 receptors each square)
D-22
-------
IWAIR Technical Background Document
Appendix D
.400 -300 -200 -100 0 100 200 300 4(
400-
300-
200-
100-
o-
-100-
-200-
-300-
-400-
-4
+
+ + + + -i-
* +
+ : ....
-
+
Land Apph EOUDD Unit
'
+ -i- + +
-f
H- + + + +
' +
0
-400
-300
-200
-100
-0
-100
-200
-300
400
)0 -300 -200 -100 0 100 200 300 400
(meters)
Figure D-5c. Cartesian Receptor Grid (16 receptors each square)
D-23
-------
IWAIR Technical Background Document
Appendix D
-1000 -800
1000-1 L
-600 -400
-200
L_
200
L_
400
600
I
800 1000
-1000
-800
-600
^100
-200
800-
600-
400-
200-
0-
-200-
-400-
-600-
-800-
[ |
+ +
+ +
1000-
1
I
+ -o
-200
-400
--600
-800
-1000
-1000 -800 -600 -400 -200 0
1
1
200 400
600
T~
800
1000
(meters)
Figure D-6a. Polar Receptor Grid (22.5 degree)
D-24
-------
TWA/7? Technical Background Document
Appendix D
-1000
1000-
-800
I
-600 -400 -200 0 200 400 600
I I I I I 1_ I
800
1000
-1000
800-
600-
400-
200-
o-
-200-
-400-
-600-
-800-
f +
+ +
+ )-
+ + +
+ +
+ + + +
+ +
+*+*+++
+ +
+. + +
-800
-600
-400
-200
-0
. + + + +
+ + + + + + + + +
+ +
- + + + +
+ + + H- +
+
-1000
+ +
+ +
+ +
+ +
+ +
T
-1000 -800 -600 -400
-200 0 200
(meters)
T
"T
-200
-400
600
-800
-1000
400 600 800 1000
Figure D-6b. Polar Receptor Grid (10 degree)
D-25
-------
/~\
/ s
CO
s
o "530
S 3
3£
I
OD
^^^
10
o .
./
8 -
o
7 .
£
u
C .
«j
4 -
^
«>
2 -
i -
0 -
u \
(
I
\
\
\
\
\
\
V
i \ \ \
> 50 100 150 2C
Distance from the edge of the unit (m)
Figure D-7a. Maximum Concentrations
(5th Percentile, LAU, Los Angeles, CA)
64 receptors
32 receptors
16 receptors
10
I
I
5*
3
§
3
^!
b
-------
IWAIR Technical Background Document
Appendix D
t/J
0
"p
0)
O
-------
g
CO
30
25
Cfi
20
10
0
0
64 receptors
32 receptors
16 receptors
50 100 150
Distance from the edge of the unit (m)
200
s
-
3
s
§
Rgure D-7c. Maximum Concentrations
(95th Percentile, LAU, Los Angeles, CA)
-------
>
53
0
0
64 receptors
32 receptors
16 receptors
50 100 150
Distance from the edge of the unit (m)
200
§.
8
,8-
CK)
3
s
sx
o
o
Figure D-7d. Maximum Concentrations
(5th Percentile, LAU, Little Rock, AR)
t
§
to
-------
o
c
0
0
64 receptors
32 receptors
16 receptors
50 100 150
Distance from the edge of the unit (m)
200
8
I
jf
figure D-7e. Maximum Concentrations
(50th Percentile, LAU, Little Rock, AR)
-------
3
V
5
0
0
64 receptors
32 receptors
16 receptors
50 100 150
Distance from the edge of the unit (m)
200
s
X.
*>
3
Figure D-7f. Maximum Concentrations
(95th Percentile, LAU, Little Rock, AR)
a
t
«1
-------
o
N:
06 -,
05 -
XN
^ 04 -
s
1 3 03 -
Q ^^ >/ V^
S 02 -
«^< V/.C_.
00 -
v_
22.5° Interval
10° Interval
u0
3
I
3
*i
-------
TWAIR Technical Background Document
Appendix D
*H !?
(O J>
-!-> i-H
r £
c4 o
WD
s
O §
CM g
LOOLOOUOOIOOLOO
'^^l-COCOCVjCNiT-T-OO
a <
o O
tr2 «N
03 <«
t. ^^
1/3
cs
£
-<
X
°? u
«a
h
E S
D-33
-------
'
10
8
6
0
0
2000 4000 6000 8000
Distance from the edge of the unit (m)
10000
22.5° Interval
10° Interval
8.
b
Figure D-8c. Maximum Concentrations
(95th Percentile, LAU, Los Angeles, CA)
I
*
b
-------
0.3
0.3
^ «
§0.2
wo
<
0.1
0.0
22.5° Interval
10° Interval
0 2000 4000 6000 8000 10000
Distance from the edge of the unit (m)
Rgure D-8d. Maximum Concentrations
(5th Percentile, LAU, Little Rock, AR)
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to
a
f
o
s
f
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I
35
30 -
? 25 -
ei 20 -
3*1 15-
W fT) '"J
E
an 1 0 -
3
^ 05 -
0.0-
(
V
N^^_
22.5° Interval
10° Interval
) 2000 4000 6000 8000 10000
Distance from the edge of the unit (m)
Rgure D-8e. Maximum Concentrations
(50th Percentile, LAU, Little Rock, AR)
I
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IWAIR Technical Background Document
Appendix D
13
§
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(N
!-i
a
hi
o
O
O
d
3
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